Genetic Determinants of the Acute Effects And Withdrawal Symptoms of Caffeine

by

Erica Day-Tasevski

A thesis submitted in conformity with the requirements for the degree of Master of Science (M.Sc.)

Graduate Department of Nutritional Sciences

University of Toronto

© Copyright by Erica Day-Tasevski 2010

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Genetic Determinants of the Acute Effects and Withdrawal Symptoms of Caffeine

Erica Day-Tasevski

Master of Science

Graduate Department of Nutritional Sciences

University of Toronto

2010

ABSTRACT

The mechanisms underlying caffeine’s acute effects and withdrawal symptoms are not

entirely understood. The purpose was to determine whether these effects or symptoms

co-exist in clusters, and whether they are associated with polymorphisms in β1- and β2-

adrenoceptors. Subjects (n=1271) were from the Toronto Nutrigenomics and Health

Study. The acute effects and withdrawal symptoms clustered into 4 and 6 factors,

respectively. Subjects with the ADRβ2 Gly16Arg Gly/Arg genotype were more likely than

Gly allele homozygotes to report “fatigue” withdrawal symptoms. Among >200 mg/d

caffeine consumers, ADRβ2 Gly allele carriers had a greater risk, compared to Arg allele

homozygotes, of reporting ‘flu-like somatic’ withdrawal symptoms. Among subjects with

the CYP1A2 -163 A>C A/A genotype and 100-200 mg/d caffeine consumers, ADRβ1

Arg389Gly Gly allele carriers had a greater risk, compared to Arg allele homozygotes, of

reporting “dysphoric mood” withdrawal symptoms. The findings suggest that β1- and β2-

adrenoceptors play a role in caffeine withdrawal.

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ACKNOWLEDGEMENTS

I offer much gratitude to Dr. Janet Chappell, who wisely denied me exemption from

FNR 301. This course was pivotal to the discovery of my love of research. I express

sincere appreciation to Ms. Lindsay Stewart for introducing me to my supervisor, Dr.

Ahmed El-Sohemy, and the Toronto Nutrigenomics & Health Study and for her valuable

contributions to the Study. I offer many thanks to Dr. Enza Gucciardi for her ongoing

support and encouragement leading up to and during my Masters.

My deepest gratitude goes to my wonderful husband, Naume Tasevski, for his constant

support. Without him, the Masters would not have been possible. I express a special

thanks to my parents, Patricia and Laurence Day, for empowering me and for their

unending faith in me. I am thankful to my beloved pet Nermal for lending me peace

and perspective throughout my Masters with his sweet, gentle, loving ways.

I thank all members of the El-Sohemy, Bazinet and Archer labs for their friendship and

support. Special thanks to the senior El-Sohemy lab students, Leah Cahill and Karen Eny,

who routinely went above and beyond since day one with their kind, generous

mentorship – it helped me tremendously and meant so much. I am grateful to Dr.

Richard Bazinet and Dr. Steven Narod of my Advisory Committee for their valuable

guidance.

I offer my sincerest gratitude to my supervisor, Dr. Ahmed El-Sohemy, for giving me this

opportunity, for the countless hours he spent mentoring me, and for his encouragement

and devotion to my success. I learned a tremendous amount from him and will be

eternally grateful.

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TABLE OF CONTENTS

CHAPTER ONE .............................................................................................................................1  1.1 INTRODUCTION .......................................................................................................................1  1.2 CAFFEINE ...............................................................................................................................2  

1.2.1 Physical and Chemical Properties of Caffeine.......................................................2  1.2.2 Caffeine Consumption – Sources and Trends.........................................................3  1.2.3 Pharmacokinetics of Caffeine ..................................................................................6  

1.2.3.1 Absorption........................................................................................................................... 6  1.2.3.2 Distribution........................................................................................................................... 7  1.2.3.3 Metabolism ......................................................................................................................... 7  1.2.3.4 Excretion.............................................................................................................................. 9  

1.2.4 Pharmacodynamics and Mechanisms of Action of Caffeine..............................9  1.2.4.1 Pharmacodynamics .......................................................................................................... 9  1.2.4.2 Mechanisms of Action..................................................................................................... 12  

1.2.5 Adrenergic System ...................................................................................................13  1.2.5.1 Epinephrine and Norepinephrine .................................................................................. 13  1.2.5.2 β1- and β2- Adrenergic Receptors................................................................................... 16  1.2.5.3 Genetic Variability in ADRβ1 and ADRβ2 ...................................................................... 19  

1.2.5.3.1 β1-Adrenergic Receptor Gene (ADRβ1)............................................................... 19  1.2.5.3.2 ADRβ1 Arg389Gly Polymorphism............................................................................ 20  1.2.5.3.3 β2-Adrenergic Receptor Gene (ADRβ2) ............................................................... 21  1.2.5.3.4 ADRβ2 Gly16Arg Polymorphism.............................................................................. 21  

1.2.6 Caffeine Withdrawal, Dependence and Tolerance............................................22  1.2.6.1 Withdrawal........................................................................................................................ 22  1.2.6.2 Dependence.................................................................................................................... 25  1.2.6.3 Tolerance .......................................................................................................................... 26  

1.3 HYPOTHESES AND THESIS ORGANIZATION.................................................................................28  CHAPTER TWO ...........................................................................................................................29  

2.1 ABSTRACT ............................................................................................................................29  2.2 INTRODUCTION .....................................................................................................................30  2.3 METHODS.............................................................................................................................31  

2.3.1 Subjects and Data Collection.................................................................................31  2.3.2 Caffeine and Energy Intake....................................................................................32  2.3.3 Caffeine Habits Questionnaire................................................................................33  2.3.4 Statistical Analysis .....................................................................................................34  

2.4 RESULTS ................................................................................................................................35  2.5 DISCUSSION..........................................................................................................................43  

CHAPTER THREE .........................................................................................................................48  3.1 ABSTRACT ............................................................................................................................48  3.2 INTRODUCTION .....................................................................................................................49  3.3 METHODS.............................................................................................................................51  

3.3.1 Subjects and Data Collection.................................................................................51  3.3.2 Caffeine and Energy Intake....................................................................................51  3.3.3 Caffeine Habits Questionnaire................................................................................51  3.3.4 Genotyping ...............................................................................................................51  3.3.5 Statistical Analysis .....................................................................................................51  

3.4 RESULTS ................................................................................................................................53  

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3.5 DISCUSSION..........................................................................................................................63  CHAPTER FOUR..........................................................................................................................68  

4.1 SYNOPSIS..............................................................................................................................68  4.2 LIMITATIONS..........................................................................................................................70  4.3 FUTURE RESEARCH.................................................................................................................72  

REFERENCES...............................................................................................................................74  

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LIST OF TABLES TABLE 1-1 PHYSICAL AND CHEMICAL PROPERTIES OF CAFFEINE ............................................................3  TABLE 1-2. CAFFEINE CONTENT OF BEVERAGES, FOODS AND MEDICATIONS ..........................................6  TABLE 1-3. EFFECTS OF β1- AND β2-ADRENERGIC RECEPTOR STIMULATION............................................18  TABLE 2-1. SUBJECT CHARACTERISTICS .............................................................................................37  TABLE 2-2. SELF-REPORTED ACUTE EFFECTS WITHIN 12H OF CONSUMING A CAFFEINE-CONTAINING

BEVERAGE..............................................................................................................................38  TABLE 2-3. PRINCIPAL COMPONENTS FACTOR ANALYSIS LOADINGS OF THE ACUTE EFFECTS OF CAFFEINE

AND CRONBACH’S α.............................................................................................................38  TABLE 2-4. SELF-REPORTED WITHDRAWAL SYMPTOMS WITHIN 48H OF ABSTAINING FROM CAFFEINE-

CONTAINING BEVERAGES........................................................................................................41  TABLE 2-5. PRINCIPAL COMPONENTS FACTOR ANALYSIS LOADINGS OF CAFFEINE WITHDRAWAL

SYMPTOMS AND CRONBACH’S α. ............................................................................................42  TABLE 3-1. SUBJECT CHARACTERISTICS BY β1-ADRENOCEPTOR ARG389GLY GENOTYPE. ......................56  TABLE 3-2. SUBJECT CHARACTERISTICS BY β2-ADRENOCEPTOR GLY16ARG GENOTYPE. ........................57  TABLE 3-3. FREQUENCY OF THE CLUSTERS OF ACUTE EFFECTS OF CAFFEINE AMONG β1-ADRENOCEPTOR

ARG389GLY GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS ...........................58  TABLE 3-4. FREQUENCY OF THE CLUSTERS OF ACUTE EFFECTS OF CAFFEINE AMONG β2-ADRENOCEPTOR

GLY16ARG GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS .............................59  TABLE 3-5. FREQUENCY OF THE CLUSTERS OF CAFFEINE WITHDRAWAL SYMPTOMS AMONG β1-

ADRENOCEPTOR ARG389GLY GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS..60  TABLE 3-6. FREQUENCY OF THE CLUSTERS OF CAFFEINE WITHDRAWAL SYMPTOMS AMONG β2-

ADRENOCEPTOR GLY16ARG GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS....61  TABLE 3-7. FREQUENCY OF CAFFEINE WITHDRAWAL SYMPTOMS CLUSTER 2 ‘DYSPHORIC MOOD’ AMONG

β1-ADRENOCEPTOR ARG389GLY GENOTYPES STRATIFIED BY CYP1A2 -163A>C GENOTYPES AND

THE OR (95% CI) OF REPORTING THE CLUSTER....................................................................61  TABLE 3-8. FREQUENCY OF CAFFEINE WITHDRAWAL SYMPTOMS CLUSTER 2 ‘DYSPHORIC MOOD’ AMONG

β1-ADRENOCEPTOR ARG389GLY GENOTYPES STRATIFIED BY HABITUAL CAFFEINE INTAKE AND THE

OR (95% CI) OF REPORTING THE CLUSTERS ..............................................................................62  TABLE 3-9. FREQUENCY OF CAFFEINE WITHDRAWAL SYMPTOM CLUSTER 3 ‘FLU-LIKE SOMATIC’ AMONG

β2-ADRENOCEPTOR GLY16ARG GENOTYPES STRATIFIED BY HABITUAL CAFFEINE INTAKE AND THE OR

(95% CI) OF REPORTING THE CLUSTERS ....................................................................................62  

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LIST OF FIGURES FIGURE 2-1 FREQUENCY OF FACTORS OF SELF-REPORTED ACUTE EFFECTS WITHIN 12H OF CONSUMING A

CAFFEINE-CONTAINING EVERAGE…………………………………………………………………..39 FIGURE 2-2 FREQUENCY OF FACTORS OF SELF-REPORTED WITHDRAWAL SYMPTOMS WITHIN 48H OF

ABSTAINING FROM CAFFEINE-CONTAINING EVERAGES.……………………………………………42

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LIST OF APPENDICES

APPENDIX I: CAFFEINE-CONTAINING BEVERAGE & FOOD FFQ ITEMS………………………………90 APPENDIX II: CAFFEINE HABITS QUESTIONNAIRE……….…………………………………………….93

1

CHAPTER ONE

INTRODUCTION AND LITERATURE REVIEW

1.1 INTRODUCTION

Caffeine is the most commonly used psychoactive drug in the world [1]. Its common

usage is related in part to its hedonic acute effects [2] and the desire to avoid its

aversive withdrawal symptoms, which occur upon caffeine abstinence following regular

use [3]. Caffeine’s numerous physiological, behavioural and subjective acute effects

and withdrawal symptoms have been well characterized. However, our understanding

of the physiological mechanisms that give rise to these acute effects and withdrawal

symptoms is not as well established. For instance, there is a paucity of knowledge as to

which neuro/endocrine systems, directly or indirectly stimulated by caffeine, underlie

each acute effect or withdrawal symptom and the extent to which these systems

mediate the effects or symptoms. It is also not known whether the acute effects occur

independently of one another or whether certain ones co-exist, possibly through

common underlying mechanisms.

The type and severity of acute effects and withdrawal symptoms of caffeine vary from

person to person [4, 5]. This variability has been partly explained by various lifestyle,

environmental, health-related and physiological factors. Twin studies [6-8] and genetic

association studies [9] suggest that genetics is among the physiological factors that

influence caffeine’s acute effects and withdrawal symptoms. However, there is

currently little knowledge as to what the specific genetic factors are. Some of these

genetic factors may lie in the adrenergic system, given that this system mediates some

of the physiological effects of caffeine.

2

The purpose of this thesis is to determine whether the acute effects or withdrawal

symptoms of caffeine co-exist in clusters, and whether functional genetic

polymorphisms in the β1- and β2-adrenergic receptors are associated with any of these

effects or symptoms. Positive associations would suggest that the examined

polymorphisms account for part of the inter-individual variability in the incidence of the

acute effects or withdrawal symptoms of caffeine and that β1- and β2-adrenergic

receptor activity play a role in producing the effects or symptoms that are associated

with the polymorphisms.

1.2 CAFFEINE

1.2.1 PHYSICAL AND CHEMICAL PROPERTIES OF CAFFEINE

The systematic name for caffeine is 1,3,7-trimethylxanthine and its chemical formula is

C8H10N4O2 [10]. Pure caffeine is obtained by a number of methods including coffee and

black or green tea decaffeination, methylation of other methylxanthines (theophylline

and theobromine), and synthesis from dimethyl urea and malonic acid [11]. At room

temperature caffeine consists of an odourless, slightly bitter, white powder or long,

flexible crystals [11]. Physical and chemical properties of caffeine are described in Table

1-1.

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TABLE 1-1 PHYSICAL AND CHEMICAL PROPERTIES OF CAFFEINE

Property Value Molecular weight 194.2 g/mol 1 Melting point 236 oC 1 Sublimation point 178oC 1 Specific gravity 1.2 1 Volatility 0.5% 1 Solubility (in water) 2.2% 1 Vapour pressure (at 178 oC) 760 mmHg 1 Vapour density 6.7 1 pH (1% solution) 6.9 1 Base dissociation constant 10.4 2 Median lethal dose 192 mg/kg (200 µM) 3

1 [10], 2 [12] 3 [13-15].

1.2.2 CAFFEINE CONSUMPTION – SOURCES AND TRENDS

Caffeine is a mild central nervous system stimulant, which occurs naturally in the leaves,

seeds and/or fruits of at least 63 plant species worldwide [16], including Coffea

arabica/robusta (coffee), Camellia sinensis (tea), Theobroma cacao (cocoa), Paullinia

cupana (guarana), and Cola acuminata/nitida (kola) [17]. It is a natural pesticide to

some insects [18] and a deterrent to herbivores in general given its bitter taste [19].

Some archaeologists speculate that early man consumed caffeine from plants during

the Lower Paleolithic era, 700,000 years ago [11].

Today, caffeine is consumed daily by over 80% of the world’s population regardless of

age, sex, geography or culture [20, 21]. Its use exceeds that of alcohol and nicotine,

and it has thus been called the world’s most commonly used psychoactive drug [1].

Caffeine intake from all sources has been estimated to be 70 – 75 mg/person/day

worldwide [1], slightly less than an average 8 oz cup of coffee, which contains

approximately 100 mg [11].

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Caffeine’s common use is related to its widespread availability, social acceptance,

reinforcing beneficial effects such as elevated mood and alertness [2, 22], and the

desire to avoid withdrawal symptoms [3]. It should be noted that the reinforcement of

caffeine consumption is dose dependent – low to moderate doses (even under

1mg/kg) are reinforcing, while doses above 10 to 15 mg/kg are usually aversive and

associated with dysphoric or even toxic effects [14]. It is believed that most individuals

who habitually consume caffeine adjust their intake to achieve plasma caffeine levels

that maximize caffeine’s positive effects and minimize its negative ones [4].

Caffeine occurs naturally in plant sources from which coffee, tea, chocolate or cocoa

containing products and energy drinks are made, while caffeine is added after

extraction from coffee or tea to certain soft drinks such as colas and some energy drinks

[11]. Caffeine is also added to some commercial water, chewing gum, mints, candy,

potato chips, and oatmeal [19]. It is an ingredient in a number of medications, including

some pain relief tablets in which it serves as an analgesic adjuvant [11], non-drowsy

cold remedies, over-the-counter stimulant tablets [16], and diet aids given caffeine’s

appetite suppressant effect and stimulation of energy expenditure [23, 24].

Caffeine content varies widely between the various types of caffeinated products, with

coffee and energy drinks containing the most caffeine on average and chocolate or

cocoa confectionery items containing the least (see Table 1-2) [16]. Although tea

leaves have more naturally occurring caffeine than coffee beans, the brewing process

tends to dilute tea more than coffee, resulting in one quarter to one third less caffeine

per cup [25]. Caffeine content can vary widely within certain product types – especially

coffee and tea, as shown in Table 1-2. The caffeine content of coffee and tea depends

on a range of factors, including plant variety, growing conditions, treatment,

5

processing, storage and preparation method [26]. It also varies by brand and purchase

location [27-30]

Major sources of dietary caffeine vary between populations, such as

culture/geographical region and age group [14]. Coffee is the main dietary source of

caffeine in North America and many European countries, whereas tea is the primary

source in the United Kingdom and in many Asian countries [26, 31]. Adults obtain

caffeine mainly from coffee or tea, while youths consume caffeine primarily from

carbonated beverages and in recent years, energy drinks and coffee-type drinks [19].

Habitual caffeine consumption quantity varies between populations [14]. For example,

Scandinavian nations consume some of the highest levels of caffeine (greater than 400

mg/person/day) [32], whereas African countries like Algeria and Nigeria consume some

of the lowest levels (4 mg/person/day) [14]. The U.S. and Canada consume

approximately the median quantity (211 – 238 mg/person/day) [32]. Habitual caffeine

consumption also varies by age group, with adults consuming 2.4 mg/kg, and children

consuming 1.1 mg/kg [33].

Usual caffeine intake level is variable at the individual level as well as at the population

level [1, 31, 34]. Lifestyle, personality, health conditions and caffeine tolerance level are

some factors that are associated with and therefore might partly explain certain inter-

individual differences in habitual caffeine consumption [35-37]. Genetics also appears

to account for a portion of this variability. Twin studies [8, 38] have found that

monozygotic twins consume more similar amounts of caffeine compared to dizygotic

twins. Caffeine consumption was found to be associated specifically with the 1976C>T

polymorphism of the adenosine A2A receptor gene (ADORA2A) [39].

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TABLE 1-2. CAFFEINE CONTENT OF BEVERAGES, FOODS AND MEDICATIONS

Caffeine content (mg) Product Volume or weight Range Average

Roasted and ground coffee Percolated 150 ml 64-124 83 Drip 150 ml -- 112 Decaffeinated 150 ml 2-5 3

Instant coffee 150 ml 40-108 59 Tea

Bagged 150 ml 8-91 27 Leaf 150 ml 30-48 41 Instant 150 ml 24-31 28

Cocoa 150 ml 2-7 4 Chocolate milk 240 ml 2-7 4 Milk chocolate 28 g 1-15 6 Sweet chocolate 28 g 3-35 20 Chocolate bar 28 g -- 20 Chocolate candy 28 g 1.5-6 -- Baking chocolate 28 g 18-118 60 Soft drinks

Coca Cola / Diet Coke 355 ml 45 -- Dr. Pepper 355 ml 40 -- Mountain Dew 355 ml 54 --

Energy drinks Red Bull 245 ml 80 -- Rockstar 473 ml 160 -- Full throttle 473 ml 144 --

Medications Excedrin Extra Strength 1 tablet 65 -- Midol Maximum Strength 1 tablet 60 -- NoDoz Maximum Strength 1 tablet 200 --

Adapted from [31, 40-42].

1.2.3 PHARMACOKINETICS OF CAFFEINE

1.2.3.1 ABSORPTION

Caffeine is almost completely (99%) absorbed directly from the stomach into the blood

stream following oral ingestion [14, 43]. Caffeine absorption occurs within 5 minutes of

ingestion [44] and reaches peak plasma concentration between 15 min and 120 min

[26]. Absorption rate varies in part due to the chemical properties of the caffeine

source [45]. For instance, absorption is somewhat delayed when caffeine is consumed

from soft drinks [11].

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Caffeine doses of 5 to 8 mg/kg yield peak plasma concentrations of 8 to 10 mg/l [45,

46]. Therefore, one cup of coffee, which provides a dose of 0.4 to 2.5 mg/kg, gives an

estimated peak concentration of 0.25 to 2 mg/l or approximately 1 to 10 µM [14, 47].

Plasma levels of caffeine increase over time in persons who consume coffee

throughout the day, leveling off in the afternoon or early evening [47].

1.2.3.2 DISTRIBUTION

Upon absorption, caffeine distributes throughout total body water [48]. Due to

caffeine’s hydrophobicity, it is able to pass through all biological membranes [26].

Caffeine concentrations are therefore virtually the same in blood, saliva, breast milk

and semen [11]. Saliva caffeine levels are in fact used as a valid and noninvasive

measure of serum caffeine concentrations [49-51]. The blood-to-plasma ratio of

caffeine is near unity [52], which suggests only modest plasma protein binding and free

entry of caffeine into blood cells [14].

Caffeine passes through the blood-brain barrier via diffusion and a saturable transport

system [52]. Its quick penetration into the brain [53] accounts for the fairly rapid onset of

psychological effects following consumption [20]. Caffeine also penetrates the

placental barrier [54, 55] and as a result, premature infants born to mothers who

consume large amounts of caffeine are found to have unusually elevated systemic

levels of the drug [56].

1.2.3.3 METABOLISM

More than 95% of caffeine metabolism occurs in the liver via catalysis by the

cytochrome P450 1A2 (CYP1A2) enzyme [57, 58]. A small portion of caffeine metabolism

occurs via CYP2E1, the ethanol-inducible CYP [57]. CYP1A2 converts approximately 80%

8

of caffeine to paraxanthine, 11% to theobromine and 4% to theophylline via N3, N1 and

N7 demethylations, respectively [59]. These three metabolites undergo N-

monodimethylation reactions, which yield monomethylxanthines (1-methylxanthine, 3-

methylxanthine and 7-methylxanthine, respectively), as well as hydroxylation reactions,

which yield uric acids (1,3,7-trimethyluric acid, 1,3-dimethyluric acid; 1,7-dimethyluric

acid; 3,7-dimethyluric acid; 1-methyluric acid; 3-methyluric acid and 7-methyluric acid,

respectively) [60]. Paraxanthine is metabolized also via an unknown intermediate to

uracil derivatives (5-acetylamino-6-formylamino-3-methyluracil; 5-acetylamino-6-

formylamino-3-methyluracil) [61]. These metabolic reactions occur mainly in liver

microsomes [14].

Caffeine elimination half-life ranges from 2 to 12 hours and averages 4 to 6 hours [20].

10 to 14 hour overnight caffeine abstinence generally allows for substantial caffeine

elimination [58]. However, in some individuals, large amounts of caffeine remain even

after 24 hours of abstinence [62, 63]. This variability in caffeine elimination rate can be

partly explained by caffeine dose [14, 64] since elimination is saturable at doses greater

than 10 mg/kg [65].

CYP1A2 inducibility is affected by multiple factors, including CYP1A2 -163 A>C

genotype [66], age [67], sex [68, 69], pregnancy [70], oral contraceptive use [71-73],

smoking status (de Leon, 2003), long-term alcohol use [74], and liver disease [75]. A

polymorphism in the CYP1A2 gene involving an A to C nucleotide substitution at

position -163 (rs762551) causes carriers of the CYP1A2 -163C allele to metabolize

caffeine more slowly than homozygotes for the -163A allele [66]. It has been estimated

that approximately 70% of the variability in CYP1A2 activity is due to genotype, while

other factors, such as those listed above, determine the remaining portion [76]. For

9

instance, females metabolize caffeine 20 to 30% faster than males [77]. However,

women who use oral contraceptives have approximately double the caffeine half-life

of women who do not use them [78]. Smoking, on the other hand, decreases half-life by

30 to 50% [79-81]. Long-term alcohol consumption and chronic liver disease, however,

slow caffeine elimination rate [20, 21]. Pregnancy also prolongs caffeine half-life, which

increases gradually from 4 hours during the first trimester to up to 15 hours during the

third trimester [82-84]. Half-life extends to 80 ± 23 hours in neonates [85] and can exceed

100 hours if they are premature [86], due to immaturity of some methylation and

acetylation pathways [87, 88], in addition to decreased CYP1A2 activity [67]. At 6

months of age, caffeine half-life gradually approaches that of an adult [77].

1.2.3.4 EXCRETION

Approximately a dozen caffeine metabolites are recovered in the urine [89], the major

ones being 3-methyluracil, 1-methylxanthine, 1,7-dimethyluric acid and 1,7-

dimethylxanthine [90]. Only 1 to 2% of ingested caffeine is excreted unchanged in the

urine [91, 92]. However, infants 8 to 9 months of age, who have a reduced ability to

metabolize caffeine, eliminate about 85% of caffeine through renal excretion [93-95].

1.2.4 PHARMACODYNAMICS AND MECHANISMS OF ACTION OF CAFFEINE

1.2.4.1 PHARMACODYNAMICS

Caffeine acts on a number of physiological systems through which it causes a range of

subjective, behavioural and physiological acute effects. These effects are highly

variable due to a variety of factors. One of these factors is the biphasic response to

caffeine. Low to moderate caffeine doses produce a subset of generally positive acute

effects, while elevated doses often produce negative effects [96]. Habituation to

caffeine also influences sensitivity; nonhabitual or light caffeine consumers are

10

vulnerable to certain adverse effects that habitual or heavy consumers may not

experience [97].

Caffeine produces many of its subjective and behavioural effects through central

nervous system stimulation. These effects are generally dose-dependent. Low to

moderate doses (32 to 200 mg) tend to produce desirable effects, including enhanced

alertness [98], cognitive performance [99], auditory vigilance [100] and reaction time

for some tasks [100, 101]. Somewhat higher (200 to 300 mg) yet still moderate doses are

associated with a heightened sense of well-being, concentration, arousal and energy

[102, 103]. Large caffeine doses (>400 mg), on the other hand, can lead to dysphoric

feelings of anxiety and nervousness, as well as insomnia, jitteriness, tremors and seizures

[20, 102]. However, insomnia tends to occur mainly in light caffeine users [20], and

certain vulnerable populations such as those diagnosed with anxiety or panic disorders

are vulnerable to episodes of anxiety and panic even after low caffeine doses [104-

107].

Caffeine has the potential to induce cardiovascular responses. However, these

responses depend largely on other conditions occurring at the time of administration,

as well as dose and history of caffeine use [40, 108]. In nonhabitual caffeine consumers,

one dose can lead to a slight decrease in heart rate and an increase in blood pressure

[109]. These effects are minimal in those who habitually consume moderate amounts of

caffeine [110]. Toxic quantities of caffeine can cause hypotension and severe

tachycardia [111].

Caffeine consumption influences a number of other physiological systems, including

respiratory, muscular, gastrointestinal, and renal systems. It causes an increase in

11

respiratory rate and minute volume (tidal volume x respiratory rate) by sensitizing the

medullary centre to CO2 [20, 40]. It relaxes bronchial smooth muscle and thereby

increases vital lung capacity, yet stimulates skeletal muscle and thus enhances

capacity for work [108]. Caffeine promotes gastric secretion of acid and pepsin [112,

113], and has been suspect to cause gastroesophageal reflux by decreasing lower

esophageal sphincter (LES) pressure [114]. However, LES reduction has not been well

established – one study found that LES was significantly increased by both regular and

decaffeinated coffee, but showed minimal changes in response to caffeine itself [115].

Caffeine stimulates diuresis by inhibiting sodium, chloride and water reabsorption into

the renal tubule [20, 40]. It also appears to have adjunctive and sometimes intrinsic

analgesic properties [116].

Factors in addition to caffeine dose, habituation and mental health contribute to

variability in the above-mentioned acute effects of caffeine. Physiological factors such

as rate of gastric emptying and absorption [117], as well as large differences in the

metabolic half-life of caffeine [118] are linked to this variability. Another factor is body

weight, which influences physiological caffeine concentration and therefore can affect

the intensity and/or type of acute effects experienced [11]. Reactions to caffeine have

been found to depend on personality type, particularly introversion versus extroversion

[119-121] and can also be affected by an individual’s expectations [122].

Some of the variability in the acute effects has a genetic basis. Genetic involvement is

suggested by studies that found that monozygotic twins react more uniformly to the

effects of caffeine compared to dizygotic twins [6, 7]. The 1976T>C adenosine A2A

receptor gene polymorphism in particular has been linked to anxiety following caffeine

consumption, with individuals homozygous for the 1976T allele reporting greater

12

increases in anxiety after caffeine consumption compared to the other genotypic

groups [9].

1.2.4.2 MECHANISMS OF ACTION

Researchers have postulated three main mechanisms of action of caffeine at the

cellular level. One is the release of intracellular calcium from skeletal and cardiac

muscle and neuronal tissue [40]. According to this mechanism, caffeine binds to a site

on a cyclic ADP ribose-sensitive calcium channel, leading to a release of calcium from

storage sites in the sarcoplasmic and endoplasmic reticulum [123]. The second

mechanism is inhibition of cyclic nucleotide phosphodiesterases. Phosphodiesterase

inhibition increases the concentration of cAMP, which is important in adrenergic post-

synaptic signal transduction [124]. However, the caffeine concentrations required for

these two mechanisms are too high to be attained by normal caffeine consumption

from dietary sources, and could lead to convulsions and even death in vivo [123].

Therefore, it is unlikely that these mechanisms significantly contribute to the in vivo

pharmacology of moderate caffeine doses [123]. The third mechanism is adenosine

receptor antagonism. Caffeine non-selectively antagonizes adenosine A1 and A2

receptors, which are located in the brain, adipose tissue and cardiovascular,

respiratory, renal and gastrointestinal systems [20]. Adenosine acts presynaptically to

inhibit neuronal release of acetylcholine, norepinephrine, dopamine, gamma amino

butyric acid (GABA) and serotonin. It thereby reduces spontaneous neuronal firing in

many brain regions and produces sedation [20].

Adenosine receptor antagonism is the only one of the three above-mentioned

mechanisms that is significantly affected by typical doses of dietary caffeine [14], and is

therefore considered to be the most important primary mechanism of action of

13

caffeine [15]. Some consider caffeine’s secondary mechanisms of action to be its

indirect neuronal release of norepinephrine, dopamine and serotonin [20] by way of

adenosine receptor blockage, as these neurotransmitters influence a large number of

different physiological functions [14]. However, further research is required to determine

the specific roles that these neurotransmitters play in the acute effects of caffeine [11].

In animal models, caffeine stimulates the peripheral release of epinephrine and

norepinephrine from adrenal medulla chromafin cells [125]. This release occurs by way

of calcium secretion from intracellular pools, stimulated by millimolar concentrations of

caffeine (40 mM), which would require doses that are toxic to humans [126]. Therefore,

adrenal medullary epinephrine and norepinephrine release would likely not mediate

acute effects stimulated by moderate doses of caffeine.

Some of caffeine’s primary metabolites have pronounced pharmacological activity.

Given that their xanthine structures are similar to that of caffeine, they may potentiate

some of caffeine’s effects [20]. For instance paraxanthine, which is at least as potent as

caffeine as an inhibitor of adenosine receptors [14], readily mimics some of caffeine’s

effects in humans [127]. Theophylline is approximately three to five times more potent

than caffeine in inhibiting adenosine A1 and A2 receptors [14].

1.2.5 ADRENERGIC SYSTEM

1.2.5.1 EPINEPHRINE AND NOREPINEPHRINE

Epinephrine and norepinephrine are the adrenergic receptor agonists. They are

biologically active amines and members of the catecholamine family. The term

“catechol” refers to their ring structure, which contains two hydroxyl groups [128, 129].

14

Epinephrine and norepinephrine prepare the individual for emergency “fight or flight”

situations through their dual roles as hormones and neurotransmitters [128].

Epinephrine and norepinephrine function as hormones when secreted from the adrenal

gland into the circulation. Once released, they interact with α- and β-adrenergic

receptors on the plasma membrane of target tissue cells to produce their physiological

effects [128]. Epinephrine and norepinephrine are released from the adrenal medulla in

response to an acetylcholine-stimulated influx of calcium [128], brought about by fright,

exercise, cold and low blood glucose levels [129]. Epinephrine rises selectively in

situations in which the individual does not know what to expect, whereas familiar

emotional stresses tend to selectively increase norepinephrine secretion [130]. In

general, most of the catecholamine output from the adrenal medulla is epinephrine

[130].

Whereas epinephrine functions mainly as a hormone, norepinephrine acts primarily as a

neurotransmitter [131] in both the brain and autonomic nervous system. As such,

norepinephrine regulates signal transmission across the juncture between the nerve

terminal of a proximal nerve axon and the cell body of a distal neuron [129]. In the

brain, the locus ceruleus is the main noradrenergic nucleus. Axons radiate from this

nucleus out to all layers of the cerebral cortex, to the cerebellum, and to other

structures [132]. In the autonomic nervous system, norepinephrine is released from

postganglionic sympathetic nerve fibres in direct relation to postjunctional adrenergic

receptors on effector cells [131].

Only about 10% of neurally released norepinephrine escapes into the circulation. As a

result, some consider norepinephrine’s circulatory transport unnecessary to explain its

15

biological actions. However, plasma norepinephrine concentration remains a valid

index of sympathetic neuronal activity [131]; under basal conditions, the adrenal

medullae have been estimated to produce only 2 to 8 percent of circulating

norepinephrine [131]. As a neurotransmitter, epinephrine does not act as widely as does

norepinephrine. Levels of epinephrine in the central nervous system are only about 10%

of those of norepinephrine. Epinephrine-containing neurons are located in the

brainstem [132].

The response of a given neuron or tissue to epinephrine and norepinephrine is essentially

a function of the types of adrenergic receptors that reside in that neuron or tissue [131].

Norepinephrine release from hippocampal neurons produces widespread cortical

activation and excitation through β-adrenoceptor activation. This effect may explain

much of the hyperattentiveness and lack of fatigue that accompanies use of agents

like caffeine, which increase noradrenergic activity in the brain [132]. Norepinephrine

released in outer cortical areas produces an inhibitory effect through α-adrenoceptor

agonism [132].

Via peripheral β1-adrenergic receptors, norepinephrine and epinephrine increase the

force and rate of cardiac contraction. They also increase myocardial excitability and

thereby can cause arrhythmias. Norepinephrine produces vasoconstriction in most if

not all organs through α1-adrenoceptors, and in turn increases systolic and diastolic

blood pressure [130]. Epinephrine also causes vasoconstriction in many tissues including

the skin, kidney and mucosae and in turn increases systolic blood pressure [131].

Epinephrine leads to vasodilation in skeletal muscle and the liver via β2-receptors [130].

Epinephrine and norepinephrine increase alertness, but epinephrine tends to arouse

more anxiety and fear. Both catecholamines cause glycogenolysis and

16

gluconeogenesis through β- and α-adrenergic receptors and lipolysis through β1- and

β3-adrenergic receptors. They increase insulin and glucagon secretion via β-adrenergic

mechanisms and inhibit the secretion of these hormones via α-adrenergic mechanisms

[130]. Norepinephrine and epinephrine also increase metabolic rate through hepatic-

dependent and -independent pathways [130]. Other effects of epinephrine and

norepinephrine include bronchodilation via β2-adrenoceptors, decreased

gastrointestinal motility through β1-adrenoceptors, uterine contraction and relaxation

via α- and β2-adrenoceptors, respectively, and stimulation and inhibition of mast cell

mediators by α- and β-adrenoceptors, respectively [131].

1.2.5.2 β1- AND β2- ADRENERGIC RECEPTORS

The β1- and β2-adrenergic receptors are the first two of the three β-adrenergic receptor

subtypes. They belong to the superfamily of G-protein coupled receptors [133] and are

located in the plasma membrane of neurons and neuronal and non-neuronal target

cells throughout the central nervous system and periphery [134]. These two receptors

differ pharmacologically according to their interaction with the endogenous agonists,

epinephrine and norepinephrine, and with selective antagonists. While the β1-

adrenoceptor binds epinephrine and norepinephrine with roughly equal affinities, the

β2-adrenoceptor binds epinephrine with about a 30-fold greater affinity than it does

norepinephrine [135].

The β1-adrenergic receptor is on chromosome 10 (q24-26) and is composed of 477

amino acids [135], whereas the β2-adrenergic receptor is located on chromosome 5

(q31-33) [136] and consists of 413 amino acids [135]. However, the amino acid

sequences of the β1- and β2-adrenergic receptors are very similar [135, 137]. The

17

receptors are each composed of a single polypeptide chain [138] and share a

rhodopsin-like plasma membrane arrangement with seven alpha-helical [139],

hydrophobic [135], transmembrane spanning [133] regions of 20 to 28 amino acid

residues each. These regions are connected by 3 intracellular and 3 extracellular loops

[139]. The first and second extracellular loops are connected by a disulfide bridge,

which plays a key role the receptors’ agonist-promoted conformational change [133].

The receptors also include a glycosylated extracellular N-terminal domain and an

intracellular C-terminal tail [133, 138].

The transmembrane spanning regions of the receptors create a pocket in which the

receptor agonists and competitive antagonists bind [133]. The interaction sites of the

binding domain include the Asp113 in the third transmembrane region, the Ser165 in the

fourth region and the Ser204 and Ser207 in the fifth region [140-142]. Upon agonist

binding, the receptors undergo a conformational change. This conformational change

leads the heterotrimeric stimulatory guanine nucleotide-binding protein (Gs) to activate

adenylyl cyclase and thereby increase the production of the second messenger cyclic

AMP (cAMP) [133, 134]. cAMP in turn activates protein kinase A, which phosphorylates

and thereby regulates the activity of various proteins in the cytoplasm and nucleus,

including enzymes, ion channels, chromosomal proteins and transcription factors [143].

The β1- and β2-adrenoceptors often co-exist in the same tissue or organ and sometimes

even in the same cell [144, 145]. However, peripheral β1-adrenoceptors occur mainly in

the heart [132], large intestine [131], and adipose tissue [146], whereas peripheral β2-

adrenoceptors occur predominantly in the liver and skeletal, tracheal and uterine

muscles [128, 131]. Within the central nervous system, the β1-adrenoceptor is at its

highest concentration in the pineal gland, cerebral cortex and striatum, and the β2-

18

adrenergic receptor is present at low concentration in several brain areas [135],

including the olfactory bulb, cerebral cortex, hippocampus, thalamus, hypothalamus,

pineal gland and spinal cord [147]. Physiological functions of the β1- and β2-adrenergic

receptors are summarized in Table 1-3.

TABLE 1-3. EFFECTS OF β1- AND β2-ADRENERGIC RECEPTOR STIMULATION

Organ, tissue or biochemical

mediator Receptor Effect

Adipose tissue β1 Lipolysis Heart β1 Heart rate ↑, atrioventricular conduction ↑,

contractile force ↑ Adenylyl cyclase β1 + β2 Hyperglycemia, free fatty acid ↑ Intestine β1 + β2 Relaxation Bronchi β2 > β1 Relaxation Blood vessels in skeletal muscle and liver

β2 Dilatation

Uterus β2 Relaxation Skeletal muscle β2 Tremor Skeletal muscle, liver β2 Glycogenolysis Liver β2 Gluconeogenesis Pancreas β2 Insulin secretion Pancreas β2 Glucagon secretion Mast cell mediators β2 Inhibition Eye β2 Intraocular pressure ↓ Adapted from [150-153].

Receptor desensitization is an autoregulatory phenomenon that accompanies β-

adrenoceptor activation [148]. It prevents overstimulation of the receptors in the midst

of persistent agonist exposure [148]. There are three mechanisms by which receptor

desensitization occurs. These are: (1) uncoupling of receptors from Gs, (2) internalization

(sequestration) of uncoupled receptors, and (3) receptor downregulation [148, 149].

Uncoupling is a short-term mechanism by which the receptor becomes phosphorylated

by kinases such as protein kinase A. This phosphorylation results in the binding of β-

arrestin and partial uncoupling of the agonist-bound receptor from Gs, which in turn

19

inhibits signal transduction. Uncoupling can be reversed within minutes [148]. More

prolonged agonist exposure leads to internalization of a percentage of receptors [148],

whereby the receptors are unavailable to couple with Gs [149]. Internalization takes

hours to reverse [148]. Prolonged agonist exposure over hours to days results in receptor

downregulation, whereby the total receptor complement decreases in some systems

[133].

1.2.5.3 GENETIC VARIABILITY IN ADRβ1 AND ADRβ2

1.2.5.3.1 β1-ADRENERGIC RECEPTOR GENE (ADRβ1)

The β1-adrenoceptor is encoded by a nonintronic gene, 1,714 base pairs long on

chromosome 10q24-26 [154, 155]. Twenty-three polymorphisms in ADRβ1 have been

reported, some of which are very rare and most of which have not been formally

verified. Thirteen of the identified ADRβ1 polymorphisms are nonsynonymous and result

in amino acid substitutions in the β1-adrenoceptor protein [156-158]. Of these thirteen,

the Ser49Gly and Ala59Ser polymorphisms occur in the extracellular amino terminus and

may thus affect agonist affinity. The Arg318Ser, Lys324Arg, Ala343Thr, Glu352Asp,

Arg399Cys, Arg400Leu, His402Arg, Thr404Ala, Pro418Ala, Asp460Glu and Arg389Gly

polymorphisms are located in the intracellular carboxy terminus and may therefore

affect Gs protein coupling, as has been hypothesized for Arg389Gly [156, 159].

Arg389Gly and Ser49Gly are the most common and well-studied polymorphisms in

ADRβ1. They are in linkage disequilibrium [160] and have distinct functional significance

[161, 162].

20

1.2.5.3.2 ADRβ1 ARG389GLY POLYMORPHISM

The ADRβ1 Arg389Gly polymorphism involves a C to G substitution at nucleotide position

1165 of the ADRβ1 gene. This polymorphism occurs at amino acid position 389 of the

ADRβ1 receptor, in its putative Gs protein-binding domain near the receptor’s

intracellular tail [162]. The minor allele (Gly) frequency is 27% in Caucasians, 26% in

Chinese, 33% in Hispanics and 42% in African Americans [163].

Likely related to the polymorphism’s location in the β1-adrenoceptor’s putative Gs

protein-binding region, an in vitro study of a hamster fibroblast cell line (CHW-1102)

transfected to express both versions of the receptor revealed that the Gly allele has a

lower capacity to form the agonist-receptor-Gs-complex compared to the Arg allele.

(Agonist promoted Gs protein-receptor coupling is the first intracellular step in β-

adrenoceptor signal transduction.) Accordingly, the Gly389 allele was associated with

lower agonist-stimulated adenylyl cyclase activity (i.e. conversion of ATP to cyclic AMP

(cAMP) and inorganic phosphate (Pi))) compared to the Arg389 allele [162]. (Adenylyl

cyclase activity is a component of β-adrenoceptor signal transduction that occurs

downstream of Gs protein-receptor coupling.) Moreover, in transgenic mice expressing

human ADRβ1 Gly389 and Arg389 alleles, the Gly389 allele showed increased

downregulation compared to the Arg389 allele [164]. The Arg allele has been

associated with hypertension [165] and Alzheimer’s disease [166], however, evidence

for its association with obesity related parameters such as BMI is equivocal [167, 168].

21

1.2.5.3.3 β2-ADRENERGIC RECEPTOR GENE (ADRβ2) The β2-adrenoceptor is encoded by a nonintronic gene, 1,239 base pairs long on

chromosome 5q31-33 [169, 170]. Twelve polymorphisms have been reported for the

ADRβ2 gene [158]. Five of these are nonsynonymous, including Gly16Arg, Gln27Glu,

Thr164Ile, Val34Met and Ser220Cys [158]. A nonsynonymous polymorphism results in a

codon that codes for a different amino acid, which potentially alters the functionality of

the resulting protein [171]. The first four nonsynonymous polymorphisms have functional

effects as evidenced by in vitro and in vivo studies reviewed by Ligget [142]. The

Ser220Cys polymorphism has been found exclusively in African Americans and to date,

there have been no functional studies on this polymorphism. The Gly16Arg and

Gln27Glu are in partial linkage disequilibrium [172]. If they were in complete linkage

disequilibrium then the polymorphisms’ alleles would be close enough on the same

chromosome that they would never be separated by recombination and therefore

would always be inherited together. In partial linkage disequilibrium, the two alleles are

close enough to usually be inherited together, but far enough away from each other

that they are occasionally separated by recombination and thus occasionally not

inherited together. Therefore, in most but not all individuals, a particular Gly16Arg allele

is a marker of a particular Gln27Glu allele, and vice versa.

1.2.5.3.4 ADRβ2 GLY16ARG POLYMORPHISM

The ADRβ2 Gly16Arg polymorphism involves a G to A substitution at nucleotide position

46 of the ADRβ2 gene. The polymorphism occurs at amino acid position 16 of the ADRβ2

receptor near the extracellular N-terminus [173]. The minor allele (Arg) frequency is

about 40% in Caucasians, 60% in Asians, and 50% in African Americans [174].

22

In spite of its extracellular locus, the Gly16Arg polymorphism does not affect agonist

affinity [175]. However, it does influence receptor downregulation. The Gly16 receptor

downregulates following agonist exposure to a much greater extent than Arg16

receptors in transfected CHW and HASM cell lines as well as in primary cultured human

airway smooth muscle cells [176]. The Arg16 allele has been associated with type 2

diabetes [177], and myasthenia gravis [178], whereas the Gly16 allele has been

associated with nocturnal asthma [158]. ADRβ2 association studies of hypertensive

populations have yielded mixed results. Hypertension has been associated with both

the Gly16 allele [179, 180] as well as the Arg16 allele [165]. These inconsistencies may be

due to other genetic or environmental differences between the populations studied.

1.2.6 CAFFEINE WITHDRAWAL, DEPENDENCE AND TOLERANCE

1.2.6.1 WITHDRAWAL

The caffeine withdrawal syndrome is characterized by symptoms that begin between 1

to 43 hours after reducing usual caffeine intake [181] or ceasing to consume caffeine

following regular use [103, 182-184]. Symptoms reach peak intensity between 20 to 51

hours following abstinence [185] and can last for 2 to 9 days [103, 186-189] or even

several months [190, 191]. Symptoms can occur following cessation of habitual caffeine

doses as low as 100 mg per day (approximately equivalent to a 8 oz cup of coffee)

[31], and possibly much less [99, 100, 181], after only 3 days of exposure [181]. Symptoms

can be prevented or rapidly reversed following ingestion of just 25 mg of caffeine [181].

Caffeine withdrawal symptoms have been described for over 170 years [185]. In 2004,

Juliano and Griffiths validated 13 of 49 possible withdrawal symptoms reported in 66

studies dating back to 1883 [185]. The 13 validated symptoms included headache,

tiredness/fatigue, decreased energy/activeness, decreased alertness/attentiveness,

23

drowsiness/sleepiness, decreased contentedness/well-being, depressed mood,

difficulty concentrating, irritability, muzzy/foggy/not clearheaded, flu-like symptoms,

nausea/vomiting, and muscle pain/stiffness [185]. Anxiety was not one of the validated

symptoms, but the American Psychiatric Association’s Diagnostic and Statistical Manual

of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) proposes it as a potential

symptom of the caffeine withdrawal syndrome [192].

Using a principal components factor analysis, Ozsungur et al found that these 13

validated caffeine withdrawal symptoms plus anxiety factor into and, therefore, might

co-exist in 3 distinct clusters [193]. These clusters were termed fatigue and headache,

dysphoric mood, and flu-like somatic [193]. The authors proposed that the clusters might

represent the adenosinergic, dopaminergic, serotonergic, or adrenergic pathways,

since these pathways mediate many of the physiological effects of caffeine [14, 193].

Further research is required to clarify the specific roles that these pathways play in the

production of caffeine withdrawal symptoms.

Currently, the main hypothesis is that the adenosinergic system underlies caffeine

withdrawal. It is believed that habitual consumption of caffeine, which competitively

antagonizes adenosine receptors [194], upregulates adenosine receptors in the brain

[190, 195-197], shifts cerebral adenosine A1 receptors to a high affinity state [198], and

increases functional sensitivity to adenosine [190, 198, 199]. Adenosine depresses firing

of neurons and release of neurotransmitters that may mediate some of caffeine’s acute

effects [200]. Therefore, the hypersensitivity to adenosine during caffeine abstinence is

thought to mediate caffeine withdrawal symptoms [199, 201].

24

Some studies also suggest that adrenergic and noradrenergic systems influence

caffeine withdrawal symptoms. For instance, operant behavioral experiments in rats

demonstrating symmetrical cross-tolerance between caffeine and methylphenidate (a

psychostimulant) suggest noradrenergic mediation of effects [202-204]. Also, repeated

caffeine exposure decreases β-adrenoceptor number [198, 205], whereas caffeine

withdrawal decreases β-adrenoceptor sensitivity [206] and increased excretion of the

norepinephrine metabolite, MHPG, in one subject [204, 207].

Caffeine withdrawal has the potential to cause clinically significant distress and

functional impairment [185]. Caffeine withdrawal is thus an official diagnosis in the

World Health Organization’s International Classification of Disorders (ICD-10) [208, 209]

and a proposed research diagnosis in DSM-IV-TR [192]. Evidence suggests that the

aversiveness of caffeine withdrawal symptoms contributes to the reinforcing properties

of caffeine [3, 5, 184, 186, 210, 211].

Caffeine withdrawal symptoms vary widely within and between individuals in both

severity and type [181, 185]. Much evidence suggests that caffeine dose is a source of

this variability [181, 184, 193, 212-218]. However, a relationship between habitual

caffeine dose and severity or incidence of withdrawal symptoms is not demonstrated

by all studies and might vary according to the type of withdrawal symptom [5, 188, 219,

220]. Inter-individual variability in severity and/or type of caffeine withdrawal symptoms

may also have a genetic basis. Kendler and Prescott found that female monozygotic

twins experience caffeine withdrawal much more similarly than do female dizygotic

twins [8]. However, it is not yet clear what the specific genetic factors that affect

caffeine withdrawal risk might be. Perhaps some of these potential genetic factors are

25

part of the adenosinergic, dopaminergic, serotonergic, and/or adrenergic systems

since, as mentioned, these systems regulate many of caffeine’s physiological effects

[14].

1.2.6.2 DEPENDENCE

Physical dependence on caffeine is evidenced by the occurrence of the caffeine

withdrawal syndrome upon abstinence following chronic caffeine use [221]. Physical

caffeine dependence is distinct from the clinical caffeine dependence syndrome,

although they are sometimes mistakenly equated [222]. Clinical dependence is not

required for physical dependence [223]. And, while physical dependence is one

potential criterion for a diagnosis of clinical dependence, the former is neither a

necessary nor a sufficient condition of the latter [222].

A clinical dependence syndrome diagnosis requires fulfillment of at least three of the six

ICD-10 [208, 224] or seven DSM-IV criteria [225-227]. The seven DSM-IV dependence

criteria are: (i) tolerance; (ii) substance-specific withdrawal syndrome; (iii) substance is

often taken in larger amounts or over a longer period than intended; (iv) persistent

desire or unsuccessful efforts to cut down or control use; (v) a great deal of time spent

in activities necessary to obtain, use or recover from the effects of the substance; (vi)

important social, occupational or recreational activities given up or reduced because

of substance abuse; and (vii) use continued despite knowledge of a persistent or

recurrent physical or psychological problem that is likely to have been caused or

exacerbated by the substance [226]. The six ICD-10 criteria are similar to those of the

DSM-IV, but combine DSM-IV criteria (v) and (vi) into a single criterion [224, 227]. In ICD-

10, clinical caffeine dependence could be diagnosed under ‘Mental and behavioral

disorders due to use of other stimulants [i.e. besides cocaine], including caffeine’ [228].

26

However, caffeine dependence is not yet included in the DSM-IV due to a lack of

clinical evidence of caffeine dependence [228].

There are currently two studies that provide clinical evidence of a caffeine

dependence syndrome. In 16.2% of adult subjects who thought they were

psychologically or physically dependent on caffeine, evidence of clinical caffeine

dependence was found using DSM-IV dependence criteria tailored for caffeine [222].

Caffeine dependence was diagnosed based on fulfillment of at least three of a subset

of four of the original DSM-IV dependence criteria (i, ii, iv, vi), given that not all seven

criteria are necessarily appropriate for a socially accepted, licit substance such as

caffeine [222]. Another study found that 27% of subjects had mild caffeine

dependence (three to four criteria), 14% had moderate dependence (five to six

criteria) and 3% had severe dependence (seven to nine criteria), based on the nine

substance dependence criteria of the Diagnostic and Statistical Manual of Mental

Disorders, Third Edition, Revised (DSM III-R) [228].

1.2.6.3 TOLERANCE

Tolerance to caffeine’s acute physiological, behavioural and subjective effects occurs

with chronic caffeine use [201, 203, 221]. Tolerance refers to an acquired change in

responsiveness to a drug upon regular use [227], leading to a need for markedly greater

amounts of the drug to achieve its desired effects [19, 229]. Greater use of caffeine due

to tolerance may lead to physical or psychological dependence [228].

Tolerance develops to some but not all effects of caffeine [230, 231]. Typically within a

few days, tolerance occurs to some physiological effects, including heart rate [230],

diuresis [232], plasma epinephrine and norepinephrine levels and renin activity [230].

27

Tolerance also develops to subjective effects such as tension-anxiety, jitteriness,

nervousness and activity/stimulation/energy [233]. Tolerance to the aversive subjective

effects can cause individuals to consume even higher doses of caffeine [227].

For certain effects, tolerance appears to be incomplete, with chronic caffeine users

showing an attenuated response to caffeine compared to non-users, but still

manifesting a significant response compared to baseline. Partial tolerance develops to

caffeine’s disruptive effect on sleep. Sleep efficiency remains below 90% of baseline

even after 7 days of caffeine exposure [234]. Peripheral blood pressure elevation can

also exhibit incomplete tolerance to caffeine [235-237].

There are inter-individual differences in tolerance to the effects of caffeine, particularly

to blood pressure elevation. For instance, Farag et al. found that subjects could be

separated into low and high tolerance groups based on degree of hemodynamic

response to caffeine [238]. Lovallo et al found that among habitual caffeine consumers

on a randomized caffeine-dosing schedule, 50% had no hemodynamic response to a

caffeine challenge dose, whereas the remaining 50% showed no decline in blood

pressure response during the highest caffeine dosing days compared to the lowest

[239]. In addition, a twin study, which assessed tolerance using a questionnaire, found

that only 15% of subjects affirmed tolerance to effects of caffeine [8].

The precise mechanism(s) underlying the development of tolerance to the effects of

caffeine is unclear [227]. Adaptive changes to adenosine receptors do not appear to

cause tolerance [240, 241]. Rather, tolerance may be due to adaptive changes at the

level of gene transcription [14] or compensatory changes in the dopaminergic system

secondary to chronic adenosine receptor antagonism [242].

28

1.3 HYPOTHESES AND THESIS ORGANIZATION

The hypotheses of this dissertation are that i) 14 well-recognized subjective, behavioural

and physiological acute effects of caffeine and the 14 well-established caffeine

withdrawal symptoms co-exist in groups, and ii) functional genetic variations in

receptors (ADRβ1 and ADRβ2) that mediate many physiological effects of caffeine

affect sensitivity to, and in turn incidence of some of these groups. The objectives are to

ascertain whether these acute effects and withdrawal symptoms cluster into distinct

groups and whether ADRβ1 (Arg389Gly) or ADRβ2 (Gly16Arg) genotypes modify the

likelihood of reporting any of the groups of acute effects or withdrawal symptoms. The

chapter-specific objectives are as follows:

OBJECTIVE 1 (Chapter Two): To determine whether 14 well-recognized subjective,

behavioural and physiological acute effects of caffeine and 14 well-described

caffeine withdrawal symptoms factor into distinct clusters.

OBJECTIVE 2 (Chapter Three): To determine whether two functional adrenergic system

polymorphisms, ADRβ1 (Arg389Gly) and ADRβ2 (Gly16Arg), are associated with the

clusters of acute effects and withdrawal symptoms of caffeine.

29

CHAPTER TWO

2.1 ABSTRACT

There are 14 well-described acute effects of caffeine and 14 well-established caffeine

withdrawal symptoms. The objective was to determine if any of these acute effects or

withdrawal symptoms co-exist in clusters potentially through shared physiological

mechanisms, or if each occurs independently of the others. Subjects were 20-29 year-

old women (n=883) and men (n=388) from the Toronto Nutrigenomics and Health Study.

Subjects completed a caffeine habits questionnaire asking them the degree to which

they experience the 14 acute effects within 12 hours of consuming 1 caffeinated

beverage, and the 14 withdrawal symptoms within 48 hours of ceasing to consume any

caffeinated beverages. Principal components factor analysis was performed to

determine if any acute effects or withdrawal symptoms factor into distinct clusters.

Results revealed that the acute effects co-exist in 6 groups (‘anxiousness’, ‘arousal’,

‘headache and dizziness’, ‘insomnia/impaired sleep’, ‘laxative effect’, ‘upset

stomach’) and the withdrawal symptoms clustered into 4 groups (‘fatigue’, ‘dysphoric

mood’, ‘flu-like somatic’, ‘headache’). These findings suggest that common

mechanisms may exist among some of the acute effects or withdrawal symptoms of

caffeine.

30

2.2 INTRODUCTION

Caffeine is rapidly and completely absorbed from the gastrointestinal tract and

reaches peak plasma concentration within 30-40 minutes [185, 243-245] The

concentration of caffeine in the blood has a half-life of 2.5- to 10-hours, which is

influenced by factors that affect the activity of cytochrome P450 1A2 (CYP1A2), the

primary enzyme involved in caffeine metabolism [246].

Caffeine can elicit a number of dose-dependent, reinforcing and adverse

physiological, behavioural and subjective effects [185, 204, 247-249]. Fourteen such

effects are well-characterized, including headache [3, 250], increased

energy/activeness [100, 251, 252], increased alterness/attentiveness [99, 100, 253],

elevated mood [100, 254, 255], increased heart rate [192, 230, 256, 257],

anxiety/nervousness [257-259], panic attacks [105, 260], restlessness [192, 251], agitation

[192, 261], tremors/jitters/shakiness [256, 262, 263], dizziness [264, 265], insomnia/impaired

sleep [213, 266, 267], upset stomach [3, 192, 204] and laxative effect [268]. It is unclear

whether these acute effects occur independently of each other, or if they co-exist in

clusters through potentially similar mechanisms.

The caffeine withdrawal syndrome is characterized by symptoms that begin between 1

to 43 hours after reducing usual caffeine intake [181] or ceasing to consume caffeine

following regular use [103, 182-185]. Symptoms reach peak intensity between 20 to 51

hours following abstinence [185] and last for 2 to 9 days [103, 187-189, 269] or even

several months [190, 191]. There are 14 well-described caffeine withdrawal symptoms,

including headache, tiredness/ fatigue, decreased energy/activeness,

drowsiness/sleepiness, decreased contentedness/well-being, anxiety, depressed mood,

31

difficulty concentrating, irritability, muzzy/foggy/not clearheaded, flu-like symptoms,

nausea/vomiting and muscle pain/stiffness [204]. These symptoms can impair daily

functioning and cause clinically significant distress [185]. Caffeine withdrawal is thus an

official diagnosis in the World Health Organization’s International Classification of

Disorders (ICD-10) [270, 271] and a proposed research diagnosis in the American

Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders, Fourth

Edition, Text Revision (DSM-IV-TR) [272]. A matter warranting further research is whether

these withdrawal symptoms arise separately from one another, or if they co-exist in

clusters, possibly via common physiological mechanisms.

The objective of this chapter is to determine whether the 14 well-described acute

effects of caffeine and 14 well-characterized caffeine withdrawal symptoms co-exist in

groups.

2.3 METHODS

2.3.1 SUBJECTS AND DATA COLLECTION

Subjects (n=1276) are from the cross-sectional Toronto Nutrigenomics and Health Study.

They are 20 to 29 year-old women (n=885) and men (n=391) of Caucasian (n=602), East

Asian (n=442), South Asian (n=136), or mixed and other ethnocultural backgrounds

(n=96), recruited from the University of Toronto campus. Subjects did not participate in

the study if they were non-English speaking, pregnant, breastfeeding, or unable to

provide a blood sample, and were excluded if they had missing data (n=5). After

exclusions, 1271 subjects (883 women and 388 men) remained. Subjects were recruited

between September 2004 and June 2009 through University of Toronto campus

postings, email bulletins, University newspaper advertisements and classroom

announcements.

32

Anthropometric measurements, including height and weight were taken. Subjects

completed a general health and lifestyle questionnaire reporting their sex, age,

ethnocultural group, smoking status, oral contraceptive use and physical activity level,

which was measured in metabolic equivalent task (MET) units. 1 MET is equivalent to 1

kcal/kg bw/hr energy, which is the average energy expenditure of an adult while sitting

at rest [273]. The questionnaire assessed physical activity level by asking subjects to

report the number of hours they spent engaging in various levels of activity including

sleeping (0.9 METs), sitting or reclining (1.0 METs), light activity (2.4 METs), moderate

activity (3.6 METs) and vigorous activity (7.5 METs) on a typical week day and weekend

day during the last month [274].

Subjects signed a consent form and the research protocol was approved by the

University of Toronto Research Ethics Board.

2.3.2 CAFFEINE AND ENERGY INTAKE

Caffeine consumption and energy intake over the past month were derived from the

estimated intake of various foods and beverages, assessed using a 196-item, semi-

quantitative, Toronto-modified Willet food frequency questionnaire (FFQ). FFQ items

prompted subjects to choose the option from a list that best captured their intake

quantity and frequency of given foods and beverages, which were in turn converted to

average daily intake quantities. The FFQ assessed all major dietary sources of caffeine in

North America except “energy drinks” such as Red Bull (Appendix I). However,

subjects were able to record energy drinks in response to the question “Are there any

other caffeinated beverages not mentioned above that you usually drink at least once

per week?”. The FFQ provided questions with pre-set options on the method by which

subjects’ homemade coffee was usually prepared and where they usually purchased

33

coffee, to account for the different caffeine content of coffee across preparation

methods and places purchased. Completed FFQs were analyzed by Harvard University.

2.3.3 CAFFEINE HABITS QUESTIONNAIRE

The caffeine habits questionnaire (Appendix II) assessed subjects’ regular consumption,

acute effects and withdrawal symptoms of caffeine (see Appendix II). Subjects were

asked, “Do you currently, or have you ever, consumed caffeine-containing beverages

(e.g. coffee, tea, cola) regularly?”. They were informed that “regularly” referred to daily

or several times per week and responded “Yes, I currently consume them regularly”,

“Yes, I used to consume them regularly but do not anymore”, or “No, I have never

consumed them”. Next, subjects were asked, “If yes, please indicate next to each of

the following withdrawal symptoms the degree to which you experience(d) them up to

48 hours after ceasing to consume caffeine-containing beverages”. Finally, subjects

were asked “Do you experience any of the following effects up to 12 hours after

consuming one caffeine-containing beverage (e.g. coffee, tea, cola)?” Subjects

responded either “don’t know”, “none”, “mild”, “moderate” or “severe” to each of the

14 acute effects and 14 withdrawal symptoms of caffeine. Subjects who responded

either “Yes, I used to consume them regularly but do not anymore” (n=132) or “No, I

have never regularly consumed them” (n=330) to the question, “Do you currently, or

have you ever, consumed caffeine-containing beverages regularly?” were excluded

from withdrawal symptom analysis since those who gave the latter response were

instructed to skip the withdrawal symptom question, and those who gave the former

may have inaccurately recalled past withdrawal symptoms if recollection required

long-term memory.

34

2.3.4 STATISTICAL ANALYSIS

All statistical analyses were performed using the Statistical Analysis Software program

(SAS V9.1; SAS Institute, Cary, NC, USA). Subject characteristics were assessed using

median ± standard deviation for normally distributed continuous variables (age, energy

intake, physical activity level), median and interquartile range for non-normally

distributed continuous variables (weight, BMI, caffeine intake), and frequency and

percentage for categorical variables (sex, ethnocultural group, CYP1A2 genotype, oral

contraceptive use, smoking status). Percentage of total dietary caffeine intake from

various sources was assessed.

Frequency of degrees of intensity of acute effects within 12 hours of consuming a

caffeinated beverage and withdrawal symptoms up to 48 hours after abstinence from

caffeinated beverages were assessed. Subject responses to degree of acute effects

and withdrawal symptoms were then dichotomized as “no” (none) and “yes” (mild,

moderate, and severe) given the low response rates in the moderate and severe

categories, perhaps related to subjects’ somewhat low average level of habitual

caffeine consumption in this population (120.2 mg/day) [193].

Principal components factor analysis was performed to detect patterns of association

among acute effects and withdrawal symptoms [275]. The number of acute effect and

withdrawal symptom factors were ascertained using the scree test and the Kaiser

criterion for eigenvalues. According to the scree test, eigenvalues (representing the

amount of variance each factor accounts for) are plotted in a scree plot; only those

factors whose eigenvalues lie above the “elbow” of the curve joining the plotted

eigenvalues are retained. According to the Kaiser criterion for eigenvalues, only factors

35

with eigenvalues greater than 1 are retained as only these eigenvalues explain

variance better than any single effect or symptom [276]. Varimax orthogonal rotation

maximized each factor’s squared loading variance, thereby simplifying factor structure.

Orthogonal rotation involves rotating the reference axes so that they are at 90 degrees

to each other [277]. Orthogonal rotation improves the interpretation of factor loadings,

rendering them equivalent to correlations between observed variables and

components [278]. Effects or symptoms with loadings above 0.50 were deemed

elements of a factor. Cronbach’s alpha coefficients were calculated to determine the

factors’ internal consistency, representing the extent of correlation between elements

of a factor [279]. Frequency of each factor of acute effects and withdrawal symptoms

was assessed.

2.4 RESULTS Subject characteristics are displayed in Table 2-1. Of the total amount of caffeine

consumed by subjects, 56.8% came from coffee, 31.0% came from tea, 7.9% came

from cola beverages 1.3% came from chocolate or cocoa containing confectionery

items and 3.0% came from all other caffeine containing foods and beverages.

Table 2-2 reveals frequency of degrees of intensity of the acute effects of caffeine. The

majority of subjects reported an intensity of ‘none’ for each acute effect except for

increased energy/activeness, increased alertness, elevated mood and increased heart

rate. For most acute effects a relatively small percentage of subjects responded in the

‘moderate’ or ‘severe’ categories.

Table 2-3 shows factor loadings and Cronbach’s alpha coefficients for the acute

effects. Effects with factor loadings >0.5 were included in a factor and thereby 11 of the

36

14 acute effects clustered into 3 factors. We called the first factor “anxiousness” as it

included agitation, anxiety/nervousness, restlessness, panic attacks and

tremor/jitters/shakiness. The second factor, which we termed “arousal”, included

increased alertness/attentiveness, increased energy/activeness, elevated mood and

increased heart rate. We referred to the third factor as “headache and dizziness” as it

included only the headache and dizziness effects. Because 3 of the acute effects –

insomnia/impaired sleep, laxative effect and upset stomach – did not load onto any of

the factors, we considered these to be 3 additional distinct factors, for a total of 6

acute effect factors. As shown in Figure 2-1, the frequency of reported acute effect

factors occurred in the following descending order: ‘arousal’ (79.2%), ‘anxiousness’

(44.0%), ‘insomnia/impaired sleep’ (37.0%), ‘laxative effect’ (30.8%), ‘upset stomach’

(23.2%) and ‘headache and dizziness’ (15.2%).

37

TABLE 2-1. SUBJECT CHARACTERISTICS

Characteristic Subjects

388 (30.5)

Sex, n (%) Men Women 883 (69.5)

Age, mean years ± SD 22.6 ± 2.4

598 (47.0) 442 (34.8) 135 (10.6)

Ethnocultural group, n (%) Caucasian East Asian South Asian Other 96 (7.6)

Weight, median kg (IQR) 61.6 (16.5) BMI, median kg/m2 (IQR) 22.2 (4.1) Energy intake, mean kcal/d ± SD 2054.2 ± 890.8 Physical activity level, mean MET hrs/week ± SD 183.5 ± 74.2 Oral contraceptive use, n (% of women) 265 (30.0)

1069 (84.1)

114 (9.0)

Smoking status, n (%) Never Past Current 88 (6.9)

78.2 (132.8)

Caffeine intake Median mg/d (IQR) Median mg/kg bw /d (IQR) 1.2 (2.3)

Subject characteristics are described using mean ± SD for normally distributed continuous variables, median (IQR) for non-normally distributed continuous variables and n (%) for categorical variables. Abbreviations: SD = standard deviation; IQR = interquartile range; BMI = body mass index; METs= metabolic equivalent tasks.

38

TABLE 2-2. SELF-REPORTED ACUTE EFFECTS WITHIN 12H OF CONSUMING A CAFFEINE-CONTAINING BEVERAGE.

Acute Effect None Mild Moderate Severe “Don’t Know”

n (%)

Headache 982 (85.4) 97 (8.4) 20 (1.7) 4 (0.4) 47 (4.1)

Increased energy/activeness 359 (31.2) 465 (40.4) 250 (21.7) 28 (2.4) 48 (4.2)

Increased alertness 323 (28.1) 463 (40.3) 279 (24.3) 30 (2.6) 55 (4.8)

Elevated mood 558 (48.5) 325 (28.3) 172 (15.0) 16 (1.4) 79 (6.9)

Increased heart rate 524 (45.6) 296 (25.7) 117 (10.2) 24 (2.1) 189 (16.4)

Anxiety/ Nervousness 822 (71.5) 178 (15.5) 68 (5.9) 12 (1.0) 70 (6.1)

Panic attacks 1040 (90.4) 42 (3.6) 16 (1.4) 1 (0.1) 51 (4.4)

Restlessness 743 (64.6) 254 (22.1) 80 (7.0) 17 (1.5) 56 (4.9)

Agitation 901 (78.4) 144 (12.50 39 (3.4) 8 (0.7) 58 (5.0)

Tremors/ Jitters/ Shakiness 884 (76.9) 141 (12.3) 67 (5.8) 17 (1.5) 40 (3.5)

Dizziness 1021 (89.0) 63 (5.5) 14 (1.2) 6 (0.5) 45 (3.9)

Insomnia/ Impaired sleep 692 (60.2) 401 (35.40 0 (0) 0 (0) 50 (4.4)

Upset stomach 846 (73.6) 181 (15.8) 60 (5.2) 14 (1.2) 48 (4.2)

Laxative effect 747 (65.0) 333 (29.0) 0 (0) 0 (0) 69 (6.0)

TABLE 2-3. PRINCIPAL COMPONENTS FACTOR ANALYSIS LOADINGS OF THE ACUTE EFFECTS OF CAFFEINE AND

CRONBACH’S α.

Acute Effect Factor 1 Factor 2 Factor 3

Agitation 0.78 0.12 0.08

Anxiety/ Nervousness 0.74 0.21 0.13

Restlessness 0.73 0.25 0.05

Panic attacks 0.60 -0.03 0.16

Tremor/ Jitters/ Shakiness 0.56 0.16 0.32

Increased alertness/attentiveness

0.02 0.85 0.07

Increased energy/activeness 0.07 0.84 0.06

Elevated mood 0.16 0.70 0.05

Increased heart rate 0.47 0.53 0.12

Dizziness 0.08 0.02 0.73

Headache 0.11 0.10 0.72

Insomnia/ Impaired sleep 0.37 0.41 0.24

Laxative effect 0.24 0.34 0.15

Upset stomach 0.26 0.16 0.49

Cronbach’s α coefficient 0.77 0.78 0.42

39

FIGURE 2-1. FREQUENCY OF FACTORS OF SELF-REPORTED ACUTE EFFECTS WITHIN 12H OF CONSUMING A CAFFEINE-CONTAINING BEVERAGE.

40

Frequency of caffeine withdrawal symptom severities is displayed in Table 2-4. For each

withdrawal symptom except tiredness/fatigue, decreased energy/activeness,

decreased alertness/attentiveness and decreased drowsiness/sleepiness, the majority

of subjects reported a severity of ‘none’. A fairly small proportion of subjects responded

in the ‘moderate’ or ‘severe’ categories for most withdrawal symptoms.

Table 2-5 shows factor loadings and Cronbach’s α coefficients for the withdrawal

symptoms, which reveal that 13 of the 14 withdrawal symptoms clustered into 3 factors.

One symptom, difficulty concentrating, loaded onto 2 of these factors. We called the

first factor “fatigue” as it included decreased energy/activeness, decreased

alertness/attentiveness, tiredness/fatigue, drowsiness/sleepiness and difficulty

concentrating. The second factor, which we termed “dysphoric mood”, included

difficulty concentrating, foggy/not clearheaded, depressed mood,

anxiety/nervousness, irritability and decreased contentedness/well-being. We named

the third factor “flu-like somatic” as it included nausea/vomiting/upset stomach, flu-like

symptoms and muscle pain/stiffness. Only headache did not load onto any of the

factors, and was considered a fourth withdrawal symptom factor on its own. As shown

in Figure 2-2, frequency of reported withdrawal symptom factors occurred in

descending order as follows: “fatigue” (70.0%), “dysphoric mood” (53.8%), “headache”

(33.8%) and “flu-like somatic” (13.0%).

41

TABLE 2-4. SELF-REPORTED WITHDRAWAL SYMPTOMS WITHIN 48H OF ABSTAINING FROM CAFFEINE-CONTAINING

BEVERAGES

Withdrawal Symptom None Mild Moderate Severe “Don’t Know”

n (%)

Headache 510 (62.0) 145 (17.7) 86 (10.5) 29 (3.5) 50 (6.1)

Tiredness/Fatigue 315 (38.4) 266 (32.4) 160 (19.5) 42 (5.1) 38 (4.6)

Decreased energy/activeness

355 (43.2) 265 (32.3) 126 (15.4) 29 (3.5) 46 (5.6)

Decreased alertness/attentiveness

374 (45.7) 242 (29.6) 122 (14.9) 30 (3.7) 51 (6.2)

Drowsiness/ Sleepiness 365 (44.6) 253 (30.9) 132 (16.1) 28 (3.4) 41 (5.0)

Decreased contentedness/well-being

544 (66.3) 138 (16.8) 68 (8.3) 12 (1.5) 59 (7.2)

Depressed mood 602 (73.5) 107 (13.1) 43 (5.2) 5 (0.6) 62 (7.6)

Difficulty concentrating 475 (57.9) 188 (22.9) 80 (9.8) 14 (1.7) 63 (7.7)

Irritability 535 (65.2) 148 (18.1) 70 (8.5) 14 (1.7) 53 (6.5)

Foggy/Not clearheaded 526 (64.1) 153 (18.6) 69 (8.4) 19 (2.3) 54 (6.6)

“Flu-like” symptoms 722 (87.9) 37 (4.5) 13 (1.6) 1 (0.1) 48 (5.8)

Nausea/ Vomiting/ Upset Stomach

738 (89.9) 32 (4.0) 11 (1.3) 4 (0.5) 36 (4.4)

Muscle pain/ Stiffness 730 (89.0) 30 (3.7) 9 (1.10 1 (0.1) 50 (6.1)

Anxiety/ Nervousness 663 (80.8) 77 (9.4) 30 (3.6) 4 (0.5) 47 (5.7)

42

TABLE 2-5. PRINCIPAL COMPONENTS FACTOR ANALYSIS LOADINGS OF CAFFEINE WITHDRAWAL SYMPTOMS AND

CRONBACH’S α.

FIGURE 2-2. FREQUENCY OF FACTORS OF SELF-REPORTED WITHDRAWAL SYMPTOMS WITHIN 48H OF ABSTAINING FROM

CAFFEINE-CONTAINING BEVERAGES.

Withdrawal Symptom Factor 1 Factor 2 Factor 3

Decreased energy/activeness 0.82 0.25 0.08

Decreased alertness/attentiveness

0.85 0.24 0.03

Tiredness/fatigue 0.84 0.19 0.09

Drowsiness/sleepiness 0.79 0.19 0.06

Difficulty concentrating 0.51 0.56 0.17

Foggy/not clearheaded 0.46 0.57 0.07

Depressed mood 0.17 0.80 0.14

Anxiety/nervousness > 0.01 0.54 0.48

Irritability 0.29 0.68 0.18

Decreased contentedness/well-being

0.33 0.73 0.02

Nausea/vomiting/upset stomach 0.08 -0.04 0.80

Flu-like symptoms 0.11 0.24 0.60

Muscle pain/stiffness 0.04 0.12 0.78

Headache 0.42 0.38 0.07

Cronbach’s α coefficient 0.89 0.84 0.58

43

2.5 DISCUSSION

The present study sought to determine whether 14 well-described acute effects of

caffeine or 14 well-characterized caffeine withdrawal symptoms co-exist in clusters. Our

findings show that 11 of the 14 acute effects tend to co-exist in 3 groups, which we

termed “anxiousness”, “arousal” and “headache and dizziness”, and that the

remaining 3 effects (insomnia/impaired sleep, laxative effect and upset stomach) each

tend to occur independently, for a total of 6 acute effect factors. It is conceivable that

the acute effects within a given factor arise through the same physiological mechanism

and that each factor represents a distinct mechanism.

The arousal factor occurred the most frequently whereas headache and dizziness

occurred the least. Arousal-type acute effects of caffeine have been reported in at

least 35 studies [100, 204, 233, 251, 252, 280-282] and are probably the most ubiquitous

type of acute effect of caffeine, which is consistent with our findings. Given this

probability and the fact that arousal-type acute effects are generally favourable, it is

not surprising that caffeine is so widely and frequently consumed throughout the world

[25]. In keeping with our observation that ‘headache and dizziness’ is the least

frequently reported acute effects factor, headache and dizziness are not commonly

recorded acute effects in caffeine research [3, 250]. Although there is a limited body of

evidence supporting a laxative effect of caffeine [283], a fairly substantial proportion of

subjects (30.8%) reported a laxative effect in the present study. It is possible that almost

one third of our subjects experienced this effect due to other properties of caffeinated

beverages. Indeed, there is evidence that both caffeinated and decaffeinated coffee

44

produce laxation and that laxation may not be caused by caffeine or caffeine alone

[284-286].

To our knowledge, there are no systematic reviews or validations of reported acute

effects of caffeine as there are for caffeine withdrawal symptoms, such as those by

Griffiths and Woodson (1988), and Juliano and Griffiths (2004). Such a review or

validation would help to further advance discourse and research on the acute effects

of caffeine.

We also found that 13 of the 14 caffeine withdrawal symptoms tend to group into 3

clusters, which we termed “fatigue”, “dysphoric mood” and “flu-like somatic”, and the

remaining symptom, headache, tends to occur on its own and therefore may be

considered a fourth withdrawal symptom factor. It is possible that the same

physiological mechanism underlies symptoms of a common factor and that separate

mechanisms underlie each factor.

A study by Ozsungur et al also empirically derived caffeine withdrawal symptom factors

from the same 14 withdrawal symptoms [193]. The principal components factor analysis

findings from the present study differ from the latter study in 2 main ways. First, whereas

the current investigation found that headache occurs independently of other

withdrawal symptom factors, Ozsungur et al observed that headache co-exists with

fatigue symptoms [193]. A number of other studies endorse our finding that caffeine

withdrawal induced fatigue can occur in the absence of headache [191, 204, 287-291].

Second, Ozsungur et al identified foggy/not clearheaded as an element of both the

‘fatigue’ and ‘dysphoric mood’ factors, whereas we found foggy/not clearheaded to

be an element of only the ‘dysphoric mood’ factor. In both the present study and that

45

of Ozsungur et al, the ‘fatigue’ factor loadings and ‘dysphoric mood’ factor loadings

for headache and foggy/not clearheaded were close to the minimum 0.5 cutoff

criterion for inclusion in a factor. These factor loadings differed between the present

study and that of Ozsungur et al by only 0.14 – 0.19. These small differential results can

be attributed to sample size, as Ozsungur et al used a lesser number of subjects (n=495),

all of who were included in the present study [193].

Interestingly, Juliano and Griffiths conceptually derived caffeine withdrawal symptom

clusters almost identical to those that we empirically derived [185]. They proposed that

part B of the DSM-IV-TR research criteria be amended so that a caffeine withdrawal

diagnosis would require at least 3 of 5 symptom clusters including: (1) headache, (2)

fatigue or drowsiness, (3) dysphoric mood, depressed mood, or irritability, (4) difficulty

concentrating, and (5) flu-like somatic symptoms, nausea, vomiting, or muscle

pain/stiffness. There are 2 differences between these clusters and those we identified.

First, Juliano and Griffiths intentionally disregarded anxiety as a withdrawal symptom,

whereas it formed part of our ‘dysphoric mood’ cluster. Second, while Juliano and

Griffiths posited difficulty concentrating as an independent symptom, our analyses

showed that it co-presents with both ‘fatigue’ and ‘dysphoric mood’ symptoms,

loading more heavily onto the latter cluster than onto the former.

It is biologically plausible that difficulty concentrating would be related to the

‘dysphoric mood’ and ‘fatigue’ factors given that both factors represent neurologic-

type symptoms [193]. Difficulty concentrating is apt to be associated with both of these

factors also given that it is more subjective and thus prone to greater variability in

interpretation than other symptoms within the ‘fatigue’ and ‘dysphoric mood’ factors

[193].

46

We observed ‘fatigue’ to be the most commonly reported withdrawal symptom factor,

similar to Ozsungur et al, who found fatigue symptoms to be the most commonly

reported withdrawal symptoms [193]. In contrast, a review conducted by Griffiths and

Woodson revealed that headache was the most frequently reported symptom among

19 studies that investigated caffeine withdrawal signs and symptoms [204]. In our study,

headache was only the third most commonly reported factor. The discrepancy in the

relative frequencies of reporting caffeine withdrawal headache between the current

study and those reviewed by Griffiths and Woodson may be related to differences in

caffeine intake level. Subjects who reported caffeine withdrawal headache in the

studies reviewed by Griffiths and Woodson tended to consume relatively large amounts

of caffeine (e.g. 560 – 1100 mg/day) either out of habit or as dictated by experimental

protocol, whereas mean caffeine intake in the present study was only 120.2 mg/day

among all subjects and 170.1 mg/day among subjects who reported consuming

caffeine containing beverages regularly. Indeed, two of the studies described by

Griffiths and Woodson found that subjects who reported caffeine withdrawal

headache had a higher mean caffeine intake than those who did not report

headache [184, 292]. Together, these findings suggest that caffeine withdrawal

headache may be dose-dependent, as are a number of other caffeine withdrawal

symptoms. According to our findings, the ‘flu-like somatic’ factor was the least

commonly reported withdrawal symptom factor. ‘Flu-like somatic’ caffeine withdrawal

symptoms such as nausea, vomiting and muscle pain are also reported infrequently

within other studies [204, 293].

In summary, we found that 14 well-described acute effects of caffeine co-exist in 6

groups (‘anxiousness’, ‘arousal’, ‘headache and dizziness’, ‘insomnia/impaired sleep’,

47

‘laxative effect’, ‘upset stomach’) and 14 well-characterized caffeine withdrawal

symptoms co-exist in 4 groups (‘fatigue’, ‘dysphoric mood’, ‘flu-like somatic’,

‘headache’). These findings suggest that 6 mechanisms may underlie the acute effects

of caffeine and 4 mechanisms may give rise to caffeine withdrawal symptoms. These

groups of effects and symptoms may occur through pathways that mediate caffeine

action, including the adrenergic, adenosinergic, dopaminergic and serotonergic

systems. Further research is required to determine the specific mechanism(s) that may

underlie each group.

48

CHAPTER THREE

3.1 ABSTRACT

14 acute effects and 14 withdrawal symptoms of caffeine co-exist in 6 and 4 clusters,

respectively, which may represent mechanisms of caffeine action and withdrawal.

Some of these mechanisms may reside in the adrenergic system. The objective was to

determine whether polymorphisms of β1 or β2 adrenergic receptors (ADRβ1 or ADRβ2)

are associated with clusters of acute effects and withdrawal symptoms. Subjects were

20-29 year-old women (n=883) and men (n=388) from the Toronto Nutrigenomics and

Health Study. Multivariate logistic regression was used to assess the association between

ADRβ1 Arg389Gly or ADRβ2 Gly16Arg and the acute effects or withdrawal symptoms

clusters. The ORs (95% CIs) representing the association between the polymorphisms

and the acute effects clusters were nonsignificant. The OR (95% CI) of subjects with the

ADRβ2 Gly/Arg genotype reporting “fatigue” withdrawal symptoms, compared to those

with the Gly/Gly genotype, was 1.72 (1.20 – 2.48). Among CYP1A2 -163A>C A allele

homozygotes, the adjusted OR (95% CI) of ADRβ1 Gly389 allele carriers reporting

“dysphoric mood” symptoms, compared to Arg389 allele homozygotes, was 1.63 (1.05 –

2.51). Among subjects consuming 100 – 200 mg/d caffeine, the adjusted OR (95% CI) of

Gly389 allele carriers reporting “dysphoric mood” symptoms, compared to Arg389 allele

homozygotes, was 2.00 (1.15 - 3.48). Among subjects consuming >200 mg of caffeine

per day, the adjusted OR (95% CI) of ADRβ2 Arg16 allele carriers reporting “flu-like

somatic” symptoms, compared to Gly16 homozygotes, was 8.94 (1.81 – 44.14). Our

findings suggest that β1- and β2-adrenoceptors may play a role in caffeine withdrawal.

49

3.2 INTRODUCTION

In Chapter 2, we observed that in our sample of 20-29 year old women and men, 11 of

14 well-described acute effects of caffeine tended to co-exist in 3 clusters, which we

termed ‘anxiousness’, ‘arousal’ and ‘headache and dizziness’, and that the remaining 3

effects, insomnia/impaired sleep, laxative effect and upset stomach, tended to occur

on their own, for a total of 6 groups of acute effects. We also observed that 13 of 14

well-established caffeine withdrawal symptoms tended to co-exist in 3 groups which we

termed ‘fatigue’, ‘dysphoric mood’ and ‘flu-like somatic, and that the remaining

symptom, headache, tended to occur on its own for a total of 4 groups of withdrawal

symptoms. It is possible that caffeine elicits acute effects within a given cluster through

a common physiological mechanism, and that there are 6 such mechanisms, each

underlying one cluster. Likewise, it is possible that caffeine abstinence elicits withdrawal

symptoms within a given cluster through a common physiological mechanism, and that

there are 4 such mechanisms. These proposed acute effects and withdrawal symptoms

mechanisms could be elements of the adrenergic system given that it mediates some

of the physiological effects of caffeine.

The adrenergic system regulates neuronal, endocrine, cardiovascular and metabolic

functions [294]. It consists of the G-protein coupled α1 (α1a, α1b, α1d), α2 (α2a, α2b, α2c), β1,

β2 and β3 adrenergic receptors and agents of adrenergic receptor signal transduction,

namely G proteins, adenylyl cyclase and cAMP [295]. The adrenergic system mediates

some of caffeine’s physiological effects by indirectly stimulating the release of

adrenergic receptor agonists such as epinephrine [296-298] and norepinephrine [299],

thereby increasing adrenergic receptor activity and its physiological effects.

50

A genomics approach to evaluating the adrenergic system’s role in giving rise to the

clusters of acute effects and withdrawal symptoms of caffeine is to ascertain whether

functional polymorphisms in this pathway affect the likelihood of experiencing such

effects and symptoms. The first polymorphism we examined was Arg389Gly of the β1-

adrenergic receptor (ADRβ1) gene, in which guanine replaces cytosine at position

1165. Consistent with this polymorphism’s location in a putative G-protein binding

domain, the Arg389 allele is associated with greater agonist-promoted signal

transduction, as evidenced by increased receptor-Gs binding and subsequent adenylyl

cyclase activity, compared to the Gly389 allele [162]. Moreover, in transgenic mice

expressing human ADRβ1 Gly389 and Arg389 alleles, the Gly389 allele showed

increased downregulation compared to the Arg389 allele [164]. Therefore, it is possible

that compared to the Arg389 allele, Gly389 decreases sensitivity to and in turn reduces

incidence of any acute effects of caffeine that β1-adrenoceptor activity might

mediate. The second polymorphism we investigated was Gly16Arg of the β2-adrenergic

receptor (ADRβ2) gene, in which adenine replaces guanine at nucleotide position 46.

The Gly16 allele is downregulated to a greater extent upon prolonged agonist exposure

compared to the Arg16 allele [300]. Thus, relative to the Arg16 allele, Gly16 may reduce

sensitivity to and in turn incidence of any acute effects β2-adrenoceptor activity might

regulate. Related to their functional significance, it is possible that these polymorphisms

also alter sensitivity to, and in turn incidence of, any caffeine withdrawal symptoms

clusters that β1- or β2-adrenoceptors may regulate.

The objective was to determine whether ADRβ1 Arg389Gly or ADRβ2 Gly16Arg

genotype affect the risk of reporting any clusters of acute effects or withdrawal

symptoms of caffeine.

51

3.3 METHODS

3.3.1 SUBJECTS AND DATA COLLECTION

Refer to Chapter 2, section 2.3.1.

3.3.2 CAFFEINE AND ENERGY INTAKE

Refer to Chapter 2, section 2.3.2.

3.3.3 CAFFEINE HABITS QUESTIONNAIRE

Refer to Chapter 2, section 2.3.3.

3.3.4 GENOTYPING

DNA was isolated from whole blood using the GenomicPrepTM Blood DNA Isolation kit

(Amersham Pharmacia Biotech Inc., Piscataway, NJ). Genotyping for the Arg389Gly

polymorphism of ADRβ1 (rs1801253), Gly16Arg of ADRβ2 (rs1042713) and the -163A>C

SNP of CYP1A2 (rs762551) was performed by real-time PCR using TaqMan® allelic

discrimination assays (ABI no. C_8898494_10; C_2084764_20; and C___8881221_40,

respectively) from Applied Biosystems (Foster City, CA, USA). PCR conditions were 10

min at 95°C, followed by 40 cycles at 95°C for 15 s and 60°C for 1 min. The ABI

Sequence Detection System was used for allelic discrimination.

3.3.5 STATISTICAL ANALYSIS

All statistical analyses were performed using Statistical Analysis Software (SAS V9.1; SAS

Institute, Cary, NC, USA). Hardy-Weinberg Equilibrium (HWE) was assessed using χ2 tests

with 1 degree of freedom. P-values were 2-sided and significant at less than 0.05. HWE is

essentially an ideal state that provides a baseline against which to identify genetic

change in a population. Testing for HWE is often used in genetic association studies as a

52

method to detect errors or peculiarities in the data set since deviation may also be due

to sampling errors, genotyping errors, failure to detect rare alleles and inclusion of non-

existent alleles [301].

Subject characteristics were assessed among ADRβ1 and ADRβ2 genotypes using

median ± standard deviation for normally distributed continuous variables (age,

physical activity level and energy intake), median and interquartile range for non-

normally distributed continuous variables (BMI, caffeine intake and alcohol intake), and

frequency and percentage for categorical variables (sex, ethnocultural group, clinical

anxiety, clinical depression, CYP1A2 -163 A>C genotype, oral contraceptive use and

smoking status). Differences in subject characteristics between genotypes were

determined via one-way analysis of variance using the GLM procedure for normally

distributed continuous variables, NPAR1WAY WILCOXON procedure for non-normally

distributed continuous variables, and LOGISTIC procedure for categorical variables.

Unconditional multivariate logistic regression with adjustment for covariates yielded

odds ratios (OR) and 95% confidence intervals (CI) representing the likelihood of

experiencing each acute effects and withdrawal symptoms cluster among the ADRβ1

and ADRβ2 genotypes. Covariates considered for adjustment in the regression models

included sex, age, ethnocultural group, physical activity level, BMI, alcohol intake,

energy intake, caffeine intake, clinical anxiety, clinical depression, CYP1A2 -163 A>C

genotype, smoking status and oral contraceptive use. All considered covariates were

included in the final models as they all modified logistic regression beta estimates by at

least 10%. Non-normally distributed variables were log-transformed (BMI, alcohol intake)

for inclusion in the models, or square root-transformed (caffeine intake) if log-

transformation did not render the variable’s skewness and kurtosis to fall between the

53

limits of -1.00 and 1.00. Covariate interactions with genotype on the withdrawal

symptoms clusters were evidenced by significant ADRβ1*covariate or ADRβ2*covariate

logistic regression interaction terms. Analyses were stratified only by covariates that

interacted with ADRβ1 or ADRβ2 genotype. Dominant genetic models were used when

stratified analyses were conducted so that carriers of the Gly allele were combined for

ADRβ1, and carriers of the Arg allele were combined for ADRβ2.

3.4 RESULTS

Genotype frequencies for the ADRβ1 Arg389Gly polymorphism were 53% for Arg/Arg,

39% for Arg/Gly and 8% for Gly/Gly. Frequencies for the ADRβ2 Gly16Arg genotype

were 32% for Gly/Gly, 49% for Gly/Arg, and 19% for Arg/Arg. For the CYP1A2 -163A>C

polymorphism, frequencies were 45% for A/A, 45% for A/C and 10% for C/C. The minor

ADRβ1 Gly, ADRβ2 Arg and CYP1A2 C allele frequencies were 28%, 43% and 32%,

respectively. ADRβ1, ADRβ2 and CYP1A2 genotype frequencies did not deviate from

Hardy–Weinberg equilibrium (p = 0.60; p = 0.88; p = 0.51, respectively).

Subject characteristics did not differ significantly between ADRβ1 genotypes, as shown

in Table 3-1. However as shown in Table 3-2, the various ethnocultural groups as well as

CYP1A2 genotypes had significantly different ADRβ2 genotype frequencies (p < 0.0001;

p = 0.002, respectively). The ADRβ2 polymorphism was associated with differences in

physical activity level measured as MET hours per week (p = 0.04). ADRβ2 Gly/Arg had

significantly higher weekly physical activity levels than Arg/Arg.

Tables 3-3 and 3-4 show the unadjusted and adjusted ORs (95% CIs) for reporting the

acute effects clusters by ADRβ1 and ADRβ2 genotypes. The OR (95% CI) for reporting

54

upset stomach among ADRβ1 Gly/Gly compared to Arg/Arg was 0.49 (0.26 – 0.96)

when unadjusted, and (0.52 (0.26 - 1.01) after adjusting for the covariates. ADRβ1

genotype did not influence the likelihood of reporting the remaining acute effect

clusters. ADRβ2 did not affect the odds of reporting any of the acute effects clusters.

The unadjusted and multivariate-adjusted ORs (95% CIs) for reporting the withdrawal

symptoms clusters among ADRβ1 and ADRβ2 genotypes are shown in Table 3-5 and 3-6.

ADRβ1 genotype did not affect the crude or multivariate-adjusted odds of reporting

any withdrawal symptoms cluster. Compared to ADRβ2 Gly/Gly, the adjusted OR (95%

CI) of reporting the ‘fatigue’ cluster among Gly/Arg was 1.71 (1.2 – 2.48). ADRβ2

genotype was not associated with any other withdrawal symptoms clusters.

As shown in Table 3-7, there was a gene-gene interaction between CYP1A2 genotype,

grouped as “rapid” (A/A) and “slow” (A/C + C/C) caffeine metabolizers [66], and

ADRβ1 genotype on the ‘dysphoric mood’ cluster (p = 0.003). Among those with the

CYP1A2 A/C + C/C allele, the adjusted OR (95% CI) for reporting the ‘dysphoric mood’

cluster among ADRβ1Arg/Gly + Gly/Gly compared to Arg/Arg was 1.63 (1.05 – 2.51).

However, among those with the CYP1A2 A/A genotype, ADRβ1 genotype was not

associated with different odds of reporting the ‘dysphoric mood’ cluster (0.72 (0.48 –

1.08)).

We observed a diet-gene interaction between habitual caffeine consumption and the

ADRβ1 polymorphism on the ‘dysphoric mood’ cluster (p = 0.003), as seen in Table 3-8.

Among those consuming <100 mg/day caffeine, the OR (95% CI) for reporting the

‘dysphoric mood’ cluster among ADRβ1 Arg/Gly + Gly/Gly compared to Arg/Arg was

0.65 (0.43 – 1.00) when unadjusted, and 0.66 (0.42 – 1.04) after adjusting for covariates.

55

However, among those consuming 100 – 200 mg/day caffeine, the adjusted OR (95%

CI) for reporting the ‘dysphoric mood’ cluster among ADRβ1 Arg/Gly + Gly/Gly

compared to Arg/Arg was 2.00 (1.15 – 3.48).

Habitual caffeine consumption also interacted with the ADRβ2 polymorphism on the

‘flu-like somatic’ cluster (p = 0.009) as shown in Table 3-9. The adjusted ORs (95% CIs) for

reporting the ‘flu-like somatic’ cluster among ADRβ2 Arg/Arg + Arg/Gly compared to

Gly/Gly within the >200 mg/day caffeine intake category was 8.94 (1.81 – 44.14).

56

TABLE 3-1. SUBJECT CHARACTERISTICS BY β1-ADRENOCEPTOR ARG389GLY GENOTYPE.

C Characteristic Arg/Arg

(n=670)

Arg/Gly

(n=499)

Gly/Gly

(n=102) p

210 (54.1)

148 (38.1)

30 (7.7)

Sex, n (%)

Men

Women 460 (52.0) 351 (39.8) 73 (8.3)

0.78 §

Age, mean years ± SD 22.7 ± 2.4 22.4 ± 2.3 22.8 ± 2.6 0.17 †

324 (54.2)

223 (37.3)

51 (8.5)

232 (52.5) 181 (41.0) 29 (6.6)

69 (51.1) 54 (40.0) 12 (8.9)

Ethnocultural group, n (%)

Caucasian

East Asian

South Asian

Other 44 (45.8) 41 (42.7) 11 (11.5)

0.57 §

BMI, median kg/m2 (IQR) 22.2 (3.9) 22.1 (4.1) 22.7 (3.9) 0.30 ‡

Mean MET hrs/week ± SD 183.3 ± 73.0 185.7 ± 75.5 174.4 ± 76.1 0.37 †

Energy intake, mean kcal/d ± SD 2109.4 ± 922.2 2001.4 ± 871.3 1951.5 ± 748.4 0.06 †

Fibre intake, median g/d (IQR) 21.9 (15.5) 20.5 (15.4) 19.8 (16.0) 0.1 ‡

Alcohol intake, median g/d (IQR) 2.3 (7.6) 2.0 (7.2) 2.1 (7.6) 0.4 ‡

82.3 (142.8)

77.7 (120.8)

62.1 (107.4)

0.20 ‡

Caffeine intake

Median mg/d (IQR)

Median mg/kg bw /d (IQR) 1.2 (2.4) 1.1 (2.1) 1.0 (2.0) 0.15 ‡

Clinical anxiety, n (%) 42 (6.3) 29 (5.8) 3 (2.9) 0.4 §

Clinical depression, n (%) 68 (10.2) 55 (11.0) 13 (12.6) 0.6 §

302 (52.6)

225 (39.2)

47 (8.2)

CYP1A2 genotype, n (%)

A/A

A/C + C/C 368 (52.6) 274 (39.3) 56 (8.0) 0.99 §

558 (52.1)

421 (39.4)

91 (8.5)

67 (58.8) 41 (36.0) 6 (5.3)

Smoking status, n (%)

Never

Past

Current 45 (51.1) 37 (42.1) 6 (6.8)

0.57 §

p-Values for differences between genotypes were tested using †one-way ANOVA, § the χ2 test and ‡ the Kruskal Wallis test. Abbreviations: SD = standard deviation; IQR = interquartile range; BMI = body mass index; METs= metabolic equivalent tasks.

57

TABLE 3-2. SUBJECT CHARACTERISTICS BY β2-ADRENOCEPTOR GLY16ARG GENOTYPE.

C Characteristic Gly/Gly

(n=402)

Gly/Arg

(n=628)

Arg/Arg

(n=240) p

119 (30.7)

197 (50.8)

72 (18.6)

Sex, n (%)

Men

Women 285 (32.2) 431 (48.8) 168 (19.0)

0.81 §

Age, mean years ± SD 22.5 ± 2.4 22.7 ± 2.5 22.4 ± 2.2 0.08 †

236 (39.3) a

287 (48.2) a

75 (12.5) a

94 (21.3) b 226 (51.1) b 122 (27.6) b

44 (32.6) c 66 (48.9) c 25 (18.5) c

Ethnocultural group, n (%)

Caucasian

East Asian

South Asian

Other 30 (31.2) c 48 (50.0) c 18 (18.8) c

<0.0001 §

BMI, median kg/m2 (IQR) 22.3 (4.0) 22.2 (4.2) 21.9 (3.6) 0.27 ‡

Mean MET hrs/week ± SD 183.6 ± 74.6 187.4 ± 74.0 173.4 ± 73.4 0.04 †

Energy intake, mean kcal/d ± SD 2034.6 ± 767.7 2093.8 ± 929.0 1989.5 ± 973.2 0.26 †

Fibre intake, median g/d (IQR) 22.0 (15.1) 21.4 (16.5) 20.4 (15.6) 0.3 ‡

Alcohol intake, median g/d (IQR) 2.6 (7.8) 2.1 (7.3) 1.8 (7.0) 0.2 ‡

73.8 (134.5)

82.7 (129.5)

62.9 (135.2) 0.34 ‡

Caffeine intake

Median mg/d (IQR)

Median mg/kg bw /d (IQR) 1.1 (2.3) 1.3 (2.3) 1.1 (2.0) 0.35 ‡

Clinical anxiety, n (%) 27 (6.7) 35 (5.6) 12 (5.0) 0.6 §

Clinical depression, n (%) 48 (11.9) 66 (10.5) 22 (9.2) 0.5 §

170 (29.6) a

313 (54.5)

91 (15.9) a

CYP1A2 genotype, n (%)

A/A

A/C + C/C 234 (33.4) b 315 (45.2) 149 (21.4) b 0.002 §

338 (31.5)

528 (49.4)

204 (19.1)

37 (32.5) 58 (50.9) 19 (16.7)

Smoking status, n (%)

Never

Past

Current 29 (33.0) 42 (47.7) 17 (19.3)

0.97 §

p-Values for differences between genotypes were tested using †one-way ANOVA, § the χ2 test and ‡ the Kruskal Wallis test. a,b,c Ethnocultural groups or CYP1A2 genotypes not sharing the same letter are significantly different genotypes (p<0.05). Abbreviations: SD = standard deviation; IQR = interquartile range; BMI = body mass index; METs= metabolic equivalent tasks.

58

TABLE 3-3. FREQUENCY OF THE CLUSTERS OF ACUTE EFFECTS OF CAFFEINE AMONG β1-ADRENOCEPTOR ARG389GLY

GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS

a Unadjusted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, physical activity level, BMI, smoking status, alcohol intake, energy intake, caffeine intake, fibre intake, anxiety, depression, oral contraceptive use, CYP1A2 genotype.

No Yes Cluster / ADRβ1 Genotype

n (%) OR (95% CI) a OR (95% CI) b

Cluster 1 “Anxiousness”

Arg/Arg 214 (34) 145 (29) 1.00 1.00

Arg/Gly 300 (48) 250 (51) 1.23 (0.94 – 1.61) 1.20 (0.91 - 1.59)

Gly/Gly 117 (19) 100 (20) 1.26 (0.90 – 1.77) 1.20 (0.84 - 1.71)

Cluster 2 “Arousal”

Arg/Arg 80 (34) 276 (31) 1.00 1.00

Arg/Gly 111 (47) 438 (49) 1.14 (0.83 – 1.58) 1.18 (0.84 - 1.64)

Gly/Gly 43 (18) 176 (20) 1.19 (0.78 – 1.8) 1.23 (0.80 - 1.89)

Cluster 3 “Headache/Dizziness”

Arg/Arg 306 (32) 55 (32) 1.00 1.00

Arg/Gly 460 (48) 87 (51) 1.05 (0.73 – 1.52) 1.02 (0.70 - 1.50)

Gly/Gly 189 (20) 30 (17) 0.88 (0.55 – 1.43) 0.87 (0.53 - 1.44)

Cluster 4 “Insomnia”

Arg/Arg 218 (32) 126 (31) 1.00 1.00

Arg/Gly 342 (49) 201 (49) 1.02 (0.77 – 1.35) 0.99 (0.74 - 1.32)

Gly/Gly 131 (19) 80 (20) 1.06 (0.74 – 1.51) 1.04 (0.72 - 1.51)

Cluster 5 “Laxative effect ”

Arg/Arg 242 (32) 103 (31) 1.00 1.00

Arg/Gly 358 (48) 169 (51) 1.11 (0.83 – 1.49) 1.30 (0.95 - 1.78)

Gly/Gly 146 (20) 61 (18) 0.98 (0.67 – 1.43) 1.38 (0.92 - 2.07)

Cluster “Upset stomach”

Arg/Arg 135 (53) 443 (52) 1.00 1.00

Arg/Gly 109 (43) 329 (39) 1.09 (0.81 – 1.45) 1.10 (0.82 – 1.48)

Gly/Gly 11 (4) 73 (9) 0.49 (0.26 – 0.96) 0.52 (0.26 - 1.01)

59

TABLE 3-4. FREQUENCY OF THE CLUSTERS OF ACUTE EFFECTS OF CAFFEINE AMONG β2-ADRENOCEPTOR GLY16ARG

GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS

No Yes Cluster / ADRβ2 Genotype

n (%) OR (95% CI) a OR (95% CI) b

Cluster 1 “Anxiousness”

Gly/Gly 339 (54) 251 (51) 1.00 1.00

Gly/Arg 241 (38) 206 (42) 1.15 (0.90 – 1.48) 1.15 (0.89 - 1.48)

Arg/Arg 51 (8) 38 (8) 1.01 (0.64 – 1.58) 1.13 (0.71 - 1.79)

Cluster 2 “Arousal”

Gly/Gly 121 (52) 469 (53) 1.00 1.00

Gly/Arg 88 (38) 357 (40) 1.05 (0.77 – 1.42) 1.04 (0.76 - 1.42)

Arg/Arg 25 (11) 64 (7) 0.66 (0.40 – 1.09) 0.70 (0.42 - 1.17)

Cluster 3 “Headache/Dizziness”

Gly/Gly 87 (51) 505 (53) 1.00 1.00

Gly/Arg 73 (42) 371 (39) 1.14 (0.81 – 1.60 1.14 (0.81 - 1.61)

Arg/Arg 12 (7) 78 (8) 0.89 (0.47 – 1.71) 0.89 (0.46 - 1.73)

Cluster 4 “Insomnia”

Gly/Gly 360 (52) 214 (53) 1.00 1.00

Gly/Arg 274 (40) 163 (40) 1.00 (0.77 – 1.29) 1.01 (0.78 - 1.32)

Arg/Arg 57 (8) 30 (7) 0.89 (0.55 – 1.42) 0.97 (0.60 - 1.58)

Cluster 5 “Laxative effect ”

Gly/Gly 396 (53) 175 (53) 1.00 1.00

Gly/Arg 290 (39) 134 (40) 1.05 (0.80 – 1.37) 1.12 (0.84 - 1.48)

Arg/Arg 60 (8) 24 (7) 0.91 (0.55 – 1.5) 0.93 (0.54 - 1.59)

Cluster 6 “Upset stomach”

Gly/Gly 84 (33) 267 (32) 1.00 1.00

Gly/Arg 127 (50) 410 (49) 0.99 (0.72 – 1.35) 1.00 (0.72 - 1.38)

Arg/Arg 44 (17) 168 (20) 0.83 (0.55 – 1.26) 0.89 (0.58 - 1.38) a Unadjusted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, physical activity level, BMI, smoking status, alcohol intake, energy intake, caffeine intake, fibre intake, anxiety, depression, oral contraceptive use, CYP1A2 genotype.

60

TABLE 3-5. FREQUENCY OF THE CLUSTERS OF CAFFEINE WITHDRAWAL SYMPTOMS AMONG β1-ADRENOCEPTOR

ARG389GLY GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS

a Unadjusted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, physical activity level, BMI, smoking status, alcohol intake, energy intake, caffeine intake, fibre intake, anxiety, depression, oral contraceptive use, CYP1A2 genotype.

No Yes Cluster / ADRβ1 Genotype

n (%) OR (95% CI) a OR (95% CI) b

Cluster 1 “Fatigue”

Arg/Arg 132 (55) 298 (54) 1.00 1.00

ArgGly 89 (37) 217 (39) 1.08 (0.78 – 1.49) 1.11 (0.79 - 1.56)

Gl/Gly 18 (8) 42 (8) 1.03 (0.57 – 1.86) 1.34 (0.71 - 2.53)

Cluster 2 “Dysphoric mood”

Arg/Arg 201 (54) 229 (53) 1.00 1.00

Arg/Gly 138 (37) 170 (40) 1.08 (0.81 – 1.45) 1.11 (0.82 - 1.50)

Gly/Gly 30 (8) 30 (7) 0.88 (0.51 – 1.51) 1.05 (0.59 - 1.85)

Cluster 3 “Flu-like somatic”

Arg/Arg 365 (53) 60 (58) 1.00 1.00

Ar/Gly 267 (39) 39 (38) 0.89 (0.58 – 1.37) 0.87 (0.56 - 1.37)

Gly/Gly 55 (8) 4 (4) 0.44 (0.16 – 1.27) 0.46 (0.16 - 1.33)

Cluster 4 “Headache”

Arg/Arg 267 (52) 147 (57) 1.00 1.00

Arg/Gly 204 (40) 92 (35) 0.82 (0.6 – 1.13) 0.82 (0.58 - 1.16)

Gly/Gly 38 (7) 21 (8) 1.0 (0.57 – 1.77) 1.14 (0.61 - 2.14)

61

TABLE 3-6. FREQUENCY OF THE CLUSTERS OF CAFFEINE WITHDRAWAL SYMPTOMS AMONG β2-ADRENOCEPTOR

GLY16ARG GENOTYPES AND THE OR (95% CI) OF REPORTING THE CLUSTERS

No Yes Cluster / ADRβ2 Genotype

n (%) OR (95% CI) a OR (95% CI) b

Cluster 1 “Fatigue”

Gly/Gly 93 (39) 168 (30) 1.00 1.00

Gly/Arg 99 (41) 288 (52) 1.61 (1.15 – 2.27) 1.72 (1.2 - 2.48)

Arg/Arg 47 (20) 101 (18) 1.19 (0.78 – 1.83) 1.38 (0.87 - 2.19)

Cluster 2 “Dysphoric mood”

Gly/Gly 124 (34) 138 (32) 1.00 1.00

Gly/Arg 173 (47) 215 (50) 1.12 (0.82 – 1.53) 1.12 (0.81 - 1.56)

Arg/Arg 72 (20) 76 (18) 0.95 (0.63 – 1.42) 0.99 (0.65 - 1.53)

Cluster 3 “Flu-like somatic”

Gly/Gly 229 (33) 29 (28) 1.00 1.00

Gly/Arg 330 (48) 54 (52) 1.29 (0.8 – 2.09) 1.33 (0.81 - 2.21)

Arg/Arg 128 (19) 20 (19) 1.23 (0.67 – 2.27) 1.23 (0.64 - 2.35)

Cluster 4 “Headeache”

Gly/Gly 165 (32) 90 (35) 1.00 1.00

Gly/Arg 246 (48) 126 (48) 0.94 (0.67 – 1.31) 1.03 (0.72 - 1.49)

Arg/Arg 98 (19) 44 (17) 0.82 (0.53 – 1.28) 1.12 (0.68 - 1.83) a Unadjusted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, physical activity level, BMI, smoking status, alcohol intake, energy intake, caffeine intake, fibre intake, anxiety, depression, oral contraceptive use, CYP1A2 genotype.

TABLE 3-7. FREQUENCY OF CAFFEINE WITHDRAWAL SYMPTOMS CLUSTER 2 ‘DYSPHORIC MOOD’ AMONG β1-ADRENOCEPTOR ARG389GLY GENOTYPES STRATIFIED BY CYP1A2 -163A>C GENOTYPES AND THE

OR (95% CI) OF REPORTING THE CLUSTER

a Unadjsuted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, BMI, physical activity level, smoking status, alcohol intake, caffeine intake, energy intake, oral contraceptive use, clinical anxiety, clinical depression.

No Yes CYP1A2 / ADRβ1 Genotype n (%)

OR (95% CI) a OR (95% CI) b Interaction

p

A/A

Arg/Arg 102 (59) 91 (46) 1.00 1.00

Arg/Gly + Gly/Gly 71 (41) 105 (54) 1.66 (1.1 - 2.51) 1.63 (1.05 - 2.51)

A/C + C/C

Arg/Arg 99 (51) 138 (59) 1.00 1.00

Arg/Gly + Gly/Gly 97 (49) 95 (41) 0.70 (0.48 - 1.03) 0.72 (0.48 - 1.08)

0.003

62

TABLE 3-8. FREQUENCY OF CAFFEINE WITHDRAWAL SYMPTOMS CLUSTER 2 ‘DYSPHORIC MOOD’ AMONG β1-ADRENOCEPTOR ARG389GLY GENOTYPES STRATIFIED BY HABITUAL CAFFEINE INTAKE AND THE OR (95% CI) OF

REPORTING THE CLUSTERS

No Yes Caffeine intake / ADRβ1 Genotype n (%)

OR (95% CI) b OR (95% CI) a Interaction

p

<100 mg/d

Arg/Arg 91 (47) 89 (580 1.00 1.00

Arg/Gly + Gly/Gly 102 (53) 65 (42) 0.65 (0.43 – 1.00) 0.66 (0.42 - 1.04)

100-200 mg/d

Arg/Arg 68 (63) 61 (47) 1.00 1.00

Arg/Gly + Gly/Gly 40 (37) 68 (53) 1.90 (1.13 - 3.19) 2.00 (1.15 - 3.48)

>200 mg/d

Ar/Arg 42 (62) 79 (54) 1.00 1.00

Arg/Gly + Gly/Gly 26 (38) 67 (46) 1.37 (0.76 - 2.47) 1.48 (0.78 - 2.79)

0.003

a Unadjusted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, BMI, physical activity level, smoking status, alcohol intake, energy intake, oral contraceptive use, clinical anxiety, clinical depression, CYP1A2 genotype.

TABLE 3-9. FREQUENCY OF CAFFEINE WITHDRAWAL SYMPTOM CLUSTER 3 ‘FLU-LIKE SOMATIC’ AMONG β2-ADRENOCEPTOR GLY16ARG GENOTYPES STRATIFIED BY HABITUAL CAFFEINE INTAKE AND THE OR (95% CI)

OF REPORTING THE CLUSTERS

a Unadjusted logistic regression b Logistic regression model adjusted for sex, age, ethnocultural group, BMI, physical activity level, smoking status, alcohol intake, energy intake, oral contraceptive use, clinical anxiety, clinical depression, CYP1A2 genotype.

No Yes Caffeine intake / ADRβ2 Genotype n (%)

OR (95% CI) b OR (95% CI) a Interaction

p

<100 mg/d

Gy/Gly 94 (32) 16 (36) 1.00 1.00

Gly/Arg + Arg/Arg 204 (68) 29 (64) 0.84 (0.43 – 1.61) 0.90 (0.44 – 1.84)

100-200 mg/d

Gly/Gly 66 (32) 11 (35) 1.00 1.00

Gly/Arg + Arg/Arg 138 (68) 20 (64) 0.87 (0.39 – 1.92) 0.77 (0.32 – 1.86)

>200 mg/d

Gly/Gly 69 (37) 2 (7) 1.00 1.00

Gly/Arg + Arg/Arg 116 (63) 25 (92) 7.43 (1.71 –

32.36) 8.94 (1.81 –

44.14)

0.009

63

3.5 DISCUSSION

In Chapter 2, we found that within a sample of 20-29 year-old women and men, the 14

well-described acute effects of caffeine co-exist in 6 clusters and the 14 well-

established caffeine withdrawal symptoms co-exist in 4 clusters. We hypothesized that

caffeine gives rise to acute effects within a given cluster through a common

physiological mechanism, and that there are 6 such mechanisms, each representing

one cluster. Likewise, we hypothesized that abrupt cessation of caffeine elicits

withdrawal symptoms within a particular cluster through a common physiological

mechanism, and that there are 4 such mechanisms. Some of these postulated

mechanisms may be components of the adrenergic system since it is one of the

pathways that mediate the physiological effects of caffeine. As a preliminary attempt

to explore whether β1- or β2-adrenergic receptor activity in particular elicit any of the

clusters of acute effects or withdrawal symptoms, we determined whether functional

polymorphisms (ADRβ1 Arg389Gly or ADRβ2 Gly16Arg) in these receptors alter the risk of

reporting the clusters.

The results showed that neither of the 2 functional polymorphisms we examined

affected the odds of reporting any cluster of the acute effects of caffeine. However,

the results suggest that the polymorphisms may have some impact on risk of reporting

certain withdrawal symptoms. For instance, heterozygotes for the ADRβ2 Gly16Arg

polymorphism had a somewhat increased risk (1.72-fold) of reporting the ‘fatigue’

cluster of withdrawal symptoms within 48 hours of ceasing to consume any caffeinated

beverages, compared to subjects homozygous for the ancestral Gly16 allele. An

increased risk was not observed among subjects homozygous for the Arg16 allele,

64

perhaps because of the smaller sample size in the Arg/Arg group. It is biologically

plausible that β2-adrenoceptors play a role in mental fatigue withdrawal symptoms

given that these receptors regulate glycogenolysis [302] and in turn a portion of

available glucose, which is required for cerebral activity [303]. β2-adrenoceptor

mediation of muscular fatigue is plausible given the β2-adrenoceptor’s regulation of

glycogenolysis and insulin secretion [304] and thereby intramuscular transport of

glucose, which is used to fuel muscle activity [302].

We also observed a gene-gene interaction between the ADRβ1 Gly16Arg and CYP1A2

-163A>C polymorphisms on the ‘dysphoric mood’ withdrawal symptoms cluster. Among

subjects homozygous for the CYP1A2 A allele (i.e. ‘rapid’ caffeine metabolizers) [66],

ADRβ1 Gly389 allele carriers had a slightly increased risk (1.63-fold) of reporting the

‘dysphoric mood’ cluster compared to Arg389 homozygotes. It is plausible that

adrenergic receptors play a role in mediating dysphoric symptoms given that altered

neurotransmission of norepinephrine, a primary adrenoceptor agonist, is thought to

contribute to the etiology of depression [305]. Vulnerability to this cluster of symptoms

may have been observed only among the ‘rapid’ caffeine metabolizers since

physiological levels of caffeine taper off more quickly in these individuals, possibly

affording them less opportunity to adapt to caffeine loss compared to ‘slow’ caffeine

metabolizers.

We identified a diet-gene interaction between the ADRβ1 polymorphism and caffeine

intake level on risk of reporting the ‘dysphoric mood’ cluster. Among subjects who

habitually consume 100 – 200 mg/d caffeine – equivalent to approximately 1-2 cups of

coffee per day –ADRβ1 Gly389 allele carriers showed twice the risk of reporting the

‘dysphoric mood’ cluster compared to Arg389 homozygotes. Previous research has

65

found that the incidence of some withdrawal symptoms such as headache [193, 213,

217, 218], fatigue [193, 214] and dysphoric mood [193, 214] increase with increasing

habitual caffeine intake levels. The trend toward increased caffeine withdrawal

symptom risk with increasing habitual caffeine intake levels was only partially

demonstrated here since the point estimate for the ‘dysphoric mood’ cluster did not rise

further with the highest caffeine intake level.

ADRβ2 genotype also interacted with caffeine intake to influence risk of reporting the

‘flu-like somatic’ withdrawal symptom cluster. Among subjects who usually consume

>200 mg/d caffeine, ADRβ2 Arg16 allele carriers showed up to an almost 9-fold

increased risk of reporting the ‘flu-like somatic’ cluster compared to Gly16

homozygotes. Some studies did not detect an association between increased

incidence or severity of flu-like somatic symptoms and increasing daily caffeine intake

[185, 193]. However if genetics plays a role in the risk of caffeine withdrawal flu-like

somatic symptoms, perhaps the association between flu-like somatic symptom risk and

habitual caffeine intake level was masked in those studies by subjects’ genetic

variability.

It is possible that an increased risk of ‘dysphoric mood’ and ‘flu-like somatic’ symptoms

exists among ADRβ1 Gly389 allele carriers and ADRβ2 Arg16 allele carriers, respectively,

independent of CYP1A2 genotype and habitual caffeine intake level and that such

potentially increased risks were not detected in the present study due to small sample

size. It is possible that the CYP1A2 C allele or moderate to high habitual caffeine intake

merely heighten these already increased risks. The mechanisms by which ADRβ1 Gly389

and ADRβ2 Arg16 receptors increase risk for the ‘fatigue’, ‘dysphoric mood’ and ‘flu-like

somatic’ caffeine withdrawal symptom clusters are not yet clear. Caffeine withdrawal

66

has previously been reported to decrease β-adrenergic receptor sensitivity, when

measured by the ratio of cyclic adenosine monophosphate (cAMP) production after in

vitro incubation with isoproterenol (a synthetic catecholamine that stimulates β1- and

β2-adrenoceptors) to cAMP production after in vitro incubation with a blank [206].

Therefore, future in vitro studies examining whether the ADRβ1 Gly389 and ADRβ2 Arg16

receptors demonstrate a greater reduction in sensitivity during caffeine withdrawal

following exposure compared to ADRβ1 Arg389 and ADRβ2 Gly16 receptors may help

to explain the differential risk of reporting certain withdrawal symptoms clusters across

ADRβ1 Arg389Gly and ADRβ2 Gly16Arg genotypes.

Lack of association between the clusters of acute effects of caffeine and ADRβ2

Gly16Arg or ADRβ1 Arg389Gly does not necessarily negate the possibility that β1- and β2-

adrenoceptor activity underlie some of these acute effects. Future studies could

continue to investigate the possible involvement of β1- and β2-adrenoceptor activity in

producing acute effects of caffeine by examining the impact of other functional SNPs

in the genes that encode these receptors. Future research should also explore whether

the intensity or incidence of clusters of acute effects and withdrawal symptoms are

associated with functional genetic variations in other components of the adrenergic

system and with elements of the adenosinergic, dopaminergic and serotonergic

systems. Such studies would have the potential to improve our understanding of the

pharmacodynamics of caffeine and the mechanisms that underlie the symptoms of

caffeine withdrawal.

In summary, we observed that ADRβ2 Gly16Arg genotype modifies the risk of caffeine

withdrawal fatigue symptoms and interacts with habitual caffeine intake level to alter

67

the risk of caffeine withdrawal flu-like somatic symptoms. We also found that ADRβ1

Arg389Gly genotype interacts with CYP1A2 -163 A>C genotype as well as caffeine

intake level to influence the risk of caffeine withdrawal dysphoric symptoms. The

findings suggest that β1-and β2-adrenoceptors play a role in some aspects of caffeine

withdrawal, which has historically been attributed mainly to adenosine receptors [221],

and that the β1- and β2-adrenoceptor polymorphisms examined herein may explain

part of the inter-individual variability in risk of fatigue, dysphoric and flu-like somatic

caffeine withdrawal symptoms.

68

CHAPTER FOUR

SYNOPSIS, LIMITATIONS AND FUTURE RESEARCH

4.1 SYNOPSIS

The hypotheses of this dissertation were that i) 14 well-recognized subjective,

behavioural and physiological acute effects of caffeine and the 14 well-established

caffeine withdrawal symptoms co-exist in groups, and ii) functional genetic variations in

receptors (ADRβ1 and ADRβ2) that mediate many physiological effects of caffeine

affect sensitivity to, and in turn incidence of some of these groups. The objectives were

to ascertain whether these acute effects and withdrawal symptoms cluster into distinct

groups and whether ADRβ1 (Arg389Gly) or ADRβ2 (Gly16Arg) genotypes modify the

likelihood of reporting any of the groups of acute effects or withdrawal symptoms. The

chapter-specific objectives and summary of findings are as follows:

OBJECTIVE 1 (Chapter Two): To determine whether 14 well-recognized subjective,

behavioural and physiological acute effects of caffeine and 14 well-described

caffeine withdrawal symptoms factor into distinct clusters.

Results: 11 of the 14 acute effects tended to co-exist in 3 groups, that were termed

“anxiousness”, “arousal” and “headache and dizziness”, and the remaining 3 acute

effects (insomnia/ impaired sleep, laxative effect and upset stomach) tended to

occur independently for a total of 6 acute effect clusters. 13 of the 14 caffeine

withdrawal symptoms were likely to co-exist in 3 clusters, termed “fatigue”,

“dysphoric mood” and “flu-like somatic”, and the remaining symptom, headache

tended to occur on its own for a total of 4 withdrawal symptom clusters.

69

OBJECTIVE 2 (Chapter Three): To determine whether two functional adrenergic system

polymorphisms, ADRβ1 (Arg389Gly) and ADRβ2 (Gly16Arg), are associated with the

clusters of acute effects and withdrawal symptoms of caffeine identified in Chapter

Two.

Results: Neither the ADRβ1 Arg389Gly nor ADRβ2 Gly16Arg polymorphism affected the

odds of reporting any clusters of acute effects of caffeine. ADRβ1 Arg/Gly was

associated with increased risk of the “fatigue” caffeine withdrawal symptoms cluster

compared to Gly/Gly. Among CYP1A2 -163C allele carriers and among 100-200

mg/d caffeine consumers, ADRβ1 Gly389 allele carriers had an elevated risk of the

“dysphoric mood” cluster of withdrawal symptoms compared to Arg389 allele

homozygotes. Among >200 mg/d caffeine consumers, ADRβ2 Arg16 allele carriers

had a heightened risk of the “flu-like somatic” cluster of withdrawal symptoms

compared to Gly16 allele homozygotes.

The findings suggest that 6 mechanisms may underlie the acute effects of caffeine and

4 main mechanisms may underlie the caffeine withdrawal symptoms. Such overarching

mechanisms, if they indeed exist, may reside in pathways including the adrenergic,

adenosinergic, dopaminergic and serotonergic systems, which mediate some of the

physiological effects of caffeine. Lack of association between the clusters of acute

effects and ADRβ1 Arg389Gly or ADRβ2 Gly16Arg does not necessarily negate the

possibility that β1- and β2-adrenoceptor activity underlie some of these categories.

However, the results do suggest that β1- and β2-adrenoceptors play a mechanistic role

in some aspects of caffeine withdrawal, and that the polymorphisms examined herein

70

may explain part of the inter-individual variability in risk for fatigue, dysphoric and flu-like

somatic caffeine withdrawal symptoms.

4.2 LIMITATIONS

The caffeine habits questionnaire assessing the type and degree of acute effects

experienced within 12 hours of consuming one caffeinated beverage was limited partly

in that the “one caffeinated beverage” that subjects referred to in answering this

question would have varied across subjects in size, type and/or preparation method

and, therefore, in caffeine quantity, which itself can influence degree and incidence of

acute effects. It is possible that the lack of standardization of caffeine quantity in

subjects' caffeinated beverage reference added noise to the acute effects data, thus

potentially masking associations between acute effect categories and genotype.

The questionnaire item assessing the type and severity of caffeine withdrawal symptoms

up to 48 hours of ceasing to consume caffeinated beverages also had drawbacks. For

example, during abstinence from caffeinated beverages some subjects may have

consumed caffeine from other sources. A mere 25 mg of caffeine, present in less than 2

oz of milk chocolate or in a tablet of certain over-the-counter pain medications can be

sufficient to prevent caffeine withdrawal symptoms [181, 306] and could, therefore,

have caused misclassification (underestimation) in susceptibility to some symptoms.

However, it is unlikely that such misclassification errors would have confounded

associations between caffeine withdrawal symptom categories and genotype since

the errors would likely have been nondifferential across genotypes.

A potential limitation to the questionnaire items on both the acute effects and

withdrawal symptoms was that subjects may have confused symptoms of other

71

conditions they were experiencing such as illness or premenstrual syndrome with acute

effects or withdrawal symptoms of caffeine. Such confusion may have resulted in

misclassification (especially overestimation) of susceptibility to certain acute effects or

withdrawal symptoms. These questionnaire items were also both limited in that they

relied on memory, which can be unreliable. However, it is unlikely that misclassification

errors arising from the aforementioned symptom confusion or inaccurate recollection

confounded regression results since again, the errors were likely nondifferential across

genotypes. Given the limitations discussed above, the most rigorous assessment of

acute effects and withdrawal symptoms of caffeine would involve controlled caffeine

dosing conditions and occur contemporaneously with the acute effects and

withdrawal symptoms.

A further potential limitation of the study was the small size of the genotypic groups

among those who do and do not experience a given category of acute effects or

withdrawal symptoms, especially when stratified by CYP1A2 genotype or caffeine

intake category. Such small subgroup sizes would have resulted in limited statistical

power to detect actual associations, and thereby would have increased risk for Type II

errors as well as Type I errors. Additionally, the multiple comparisons performed between

the genotypes and clusters of acute effects or withdrawal symptoms increased the risk

of Type I errors.

Finally, the clusters of acute effects and withdrawal symptoms may not have

represented common underlying physiological mechanisms of caffeine action and

withdrawal as we conjectured they did. Moreover, it is possible that the acute effects

and withdrawal symptoms would have factored into somewhat different groups if a

larger sample size with greater variability was used. Although our sample of 20-29 year

72

olds was not representative of the adult population in age, it might have reduced

misclassification regarding susceptibility to acute effects and withdrawal symptoms

since individuals in this age range compared to older adults are likely to have fewer

health conditions that could influence or be confused with the acute effects and

withdrawal symptoms of caffeine.

4.3 FUTURE RESEARCH

Future research can build upon the current project’s limitations and investigate related

unexplored areas. For instance, although the acute effects of caffeine have been well

documented from numerous blinded clinical studies, a systematic review or meta-

analysis should be performed to validate the many reported acute effects since, to our

knowledge, no such systematic review or meta-analysis yet exists. Future studies that

assess acute effects and withdrawal symptoms of caffeine would ideally involve a test

and re-test, using a randomized control design and controlled caffeine dosing

conditions with contemporaneous assessment of acute effects and withdrawal

symptoms. This approach would allow standardized exposure conditions and avoid

misclassification of outcomes due to recall error. Research that investigates associations

between categories of acute effects or withdrawal symptoms of caffeine and

genotype should additionally involve larger sample sizes to strengthen statistical power

among genotypic groups who do and do not experience particular categories of

acute effects or withdrawal symptoms of caffeine, to decrease risk for Type II as well as

Type I errors. Such research should also correct for multiple comparisons using the

Bonferoni correction to reduce the risk of Type I errors.

73

Studies could continue to research the possible involvement of β1- and β2-adrenoceptor

activity in giving rise to categories of acute effects and withdrawal symptoms of

caffeine by examining whether other functional SNPs, such as ADRβ1 Ser49Gly, in the

genes that encode these receptors affect likelihood of experiencing such categories.

Future research should also explore whether the intensity or incidence of categories of

acute effects or withdrawal symptoms of caffeine are associated with functional

genetic variations in other components of the adrenergic system and with components

of the adenosinergic, dopaminergic and serotonergic systems. Such studies would have

the potential to improve our understanding of the pharmacodynamics of caffeine and

the mechanisms of caffeine withdrawal.

Caffeine withdrawal has been reported to decrease β-adrenergic receptor sensitivity

[206]. Therefore, studies should examine whether the ADRβ1 Gly389 and ADRβ2 Arg16

receptors demonstrate a greater reduction in sensitivity during caffeine withdrawal

compared to ADRβ1 Arg389 and ADRβ2 Gly16 receptors to potentially help elucidate

the cause of the differential risk we observed of certain withdrawal symptom categories

across ADRβ1 Arg389Gly and ADRβ2 Gly16Arg genotypes.

74

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Appendix I CAFFEINE-CONTAINING BEVERAGE & FOOD FFQ ITEMS

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Appendix II CAFFEINE HABITS QUESTIONNAIRE

Do you currently, or have you ever, consumed caffeine-containing beverages (e.g., coffee, tea, cola) regularly?

No, I have never regularly consumed them (GO TO Q17) Yes, I currently consume them regularly Yes, I used to consume them regularly but do not anymore

If yes, please indicate next to each of the following withdrawal symptoms the degree to which you experience(d) them up to 48 hours after ceasing to consume caffeine-containing beverages.

SYMPTOM Don’t know

None Mild Moderate Severe

Headache Tiredness/fatigue Decreased energy/activeness Decreased alertness/attentiveness Drowsiness/sleepiness Decreased contentedness/well-being Depressed mood Difficulty concentrating Irritability Foggy/not clearheaded “Flu-like” symptoms Nausea/vomiting/upset stomach Muscle pain/stiffness Anxiety/nervousness

Do you experience any of the following effects up to 12 hours after consuming one caffeine-containing beverage (e.g., coffee, tea, cola)? EFFECT Don’t

know None Mild Moderate Severe

Headache Increased energy/ activeness Increased alertness/attentiveness Elevated mood Increased heart rate Anxiety/nervousness Panic attacks Restlessness Agitation Tremors/ Jitters/ Shakiness

Dizziness

Insomnia/ Impaired sleep

Upset stomach

Laxative effect