INTRODUCTION · Web viewIt also known that APOE plays direct roles in CNS cholesterol transport and...

Ministero dell'Istruzione,dell'Università e della

Ricerca

Università degliStudi di Palermo

Dottorato di Ricerca in

Medicina Sperimentale e Molecolare

XXIII ciclo

Metabolic Syndrome as putative independent associated/risk factor for Alzheimer’Disease and Mild Cognitive Impairment

Tesi di Dottorato della:

Dott.ssa Caterina Claudia Ventimiglia

Dipartimento di Biomedicina Sperimentale e Neuroscienze Cliniche

Tutor: Chiar.mo Prof. Cecilia Camarda

Settore scientifico-disciplinare MED/26

Coordinatore:

Chiar.mo Prof. Giovanni Zummo

INTRODUCTION

1

Metabolic syndrome (MetS) is a cluster of vascular risk factors

[1] that is well established to increase the risk of diabetes,

cardiovascular disease, and stroke [2, 3]. MetS also appears to

increase the risk of age-associated cognitive decline, overall dementia,

and vascular dementia (VaD) in particular [4], but the role of MetS in

Alzheimer’s disease (AD) remains inconclusive from the contrasting

findings reported so far [5–11].

Amnestic Mild Cognitive Impairment (aMCI) is presumably a

pathological-based prodromal stage of AD with an annual rate of

conversion to dementia of 5 to 10% in community-based populations

[12] and 10 to 15% among those in specialty clinics [13]. Only a few

studies have investigated the relationship between MetS and MCI [14–

16] and they provided very limited findings to form firm conclusions on

the role of MetS in aMCI and AD.

2

The Multiple Outcomes of Raloxifene Evaluation (MORE)

study showed an association between MetS and an increased risk of

developing cognitive impairment (defined as a composite outcome

comprising clinically adjudicated dementia or MCI or cognitive

impairment not clinically adjudicated) during a 4-year period in older

women [15]. The study showed that the number of MetS components

increased the risk of developing cognitive impairment with

hyperglycemia as the only MetS component associated with a higher

risk of cognitive impairment. Unfortunately, this study lacked the power

to analyze the effect of MetS on the risk of developing MCI or AD

alone. Subsequently, a cross-sectional, population-based study with

1,969 participants from Olmsted Country, MN, USA, found no

significant association of MetS with MCI overall or aMCI, and only the

combination of MetS and high levels of inflammation was significantly

associated with non-amnestic MCI (naMCI) [14].

3

More recently, the Italian Longitudinal Study of Ageing (ILSA)

reported no significant differences in overall risk of developing incident

MCI in non-cognitively impaired individuals with MetS compared with

those without MetS over 3.5-year follow-up [16].

APOE- 4 genotype has been found to be associated with an

increased risk of AD [17] and conversion from MCI to AD [18]. The

association of APOE-Σ4 with AD is reduced in older cases [19],

however, none of the abovementioned research has examined the

modifying effects of APOE-Σ4 and age on the association between

MetS and aMCI.

In the present dissertation, the association between MetS and

aMCI in a population sample of older adults from the CogItA study was

studied. I investigated whether MetS and its individual components,

were associated with aMCI. I also investigated the possible effects of

APOE-Σ4 genotype status and age in influencing the association

between MetS and aMCI and MetS and AD .

4

I hypothesized that among individuals carrying the APOE-Σ4

allele there would be an association between MetS and aMCI and AD.

5

MATERIAL AND METHODS

Population

Data from the Cognitive Impairment through Aging (CogItA)

study were used. The CogItA study is a large hospital-based

observational study including a cross-sectional and longitudinal

prospective begun in January 2000 and still ongoing. The main aim of

the project is to collect data from adult-to-elderly subjects aged 45

years or over with normal cognition, cognitive impairment and

cognitive disorders and to evaluate the determinants of individual

differences in cognitive ageing and/or the putative risk factors for the

conversion from normal cognition to cognitive impairment and/or

dementia at follow-up.

CogIta’s subjects were recruited from a large sample of

outpatients who enrolled voluntarily for health screening at the Centre

for Aging Brain and Dementia, the Movement Disorders Centre, the

Headache Centre and the Adult General Neurology Centre of the

6

Department of Experimental Biomedicine and Clinical Neurosciences

(BioNeC), Faculty of Medicine, University of Palermo. The study was

approved by the Medical Ethical Committee of the Faculty of Medicine

affiliated Hospital (AOUP “P.Giaccone”).

In the CogIta study, inclusion criteria were the presence of an

informant and age 45 years. Exclusion criteria were presence of

systemic diseases (cardiac, hepatic or renal failure, cancer or blood

diseases); history of significant head injury, severe sensory

impairment, mental retardation, severe psychiatric disorders, epilepsy

and metabolic, immunological, demyelinating and neoplastic brain’s

diseases. After a complete description of the study, and signing the

written informed consent subjects performed neurological,

neuropsychological and laboratory examinations. All subjects were

evaluated with the same examination procedures. Using a structured,

comprehensive and teasing questionnaire administered to the patient

by trained medical personnel, all possible medical information and

7

patient’s previous hospital records were collected in order to reach a

confident evaluation of subject’s health status. Collected data included

demographic characteristics, education (expressed as years of

schooling), occupational status, marital status, lifestyle habits (alcohol

and coffee consumption, smoking habits), family history of migraine,

epilepsy, psychiatric disturbances, stroke, dementia, diabetes mellitus,

hypertension and hyperlipidemias, osteoporosis, personal medical

history including thyroid diseases, head injuries, bladder disturbances,

gait and balance problems, falls in the last year, hip fractures, visual

and hearing impairment, vascular risk factors and vascular diseases,

actual and previous pharmacological treatments registered in a

structured way, evaluation of co-morbidity, body mass index (BMI),

metabolic syndrome. All these information were defined according to

the currently most widely accepted criteria, selected after a systematic

literature search.

8

An overnight fasting venous blood sample was taken to each

subject for laboratory blood tests including glucose, lipids levels,

triglyceride, homocysteine, and APOE genotyping. Diabetes mellitus

was defined as glucose ≥ 110 (7.0mmol/L), haemoglobin A1c of ≥

6,5% or use of oral antidiabetic drugs or insulin. Hyperlipidemia was

defined as a total cholesterol ≥ 240 mg/dL (> 5.0 mmol/L) or low-

density lipoprotein cholesterol (≥ 160 mg/dL) or high-density

lipoprotein cholesterol < 40 mmol/L in men and < 50 mmol/L in

women and/or the use of cholesterol lowering drugs.

Hypertriglyceridemia was defined as a plasma triglyceride ≥ 150

mg/dL. Hyperhomocysteinemia was defined as a plasma

homocysteine ≥ 13 micromol/L. [20]. Height was measured withouth

shoes and weight and waist circumference were measured withouth

heavy clothing, and the body mass index (BMI) was calculated

(Kg/m2). Blood pressure (mmHg) was measured twice with a

sphygmomanometer and the average of the two measures was

9

calculated. Hypertension was defined as a mean systolic blood

pressure ≥ 140 mmHg or a mean diastolic pressure ≥ 95 mmHg or use

of antihypertensive drugs. Smoking, coffee intake was categorized as

never or current. Lastly, all subjects were evaluated with a dedicated

neurological examination including a careful evaluation of the primitive

reflexes.

Functional, Neuropsychological and neuropsychiatric assessment

The CogItA protocol included a large assessment containing

several tests evaluating disability, cognition, behaviour and

comorbidity.

The functional status was assessed with the Basic Activities

of Daily Living (BADL) [21] and the Instrumental Activities of Daily

Living (IADL) [22] scales.

10

The neuropsychological assessment included the Mini Mental

State Examination (MMSE), as test of general cognition [23], and

specific tests to assess the following five cognitive domains: (1) verbal

memory [Story Recall Test] and the immediate and delayed recall of

Rey’s Auditory Verbal Learning Test; (2) executive functioning (Raven

Coloured Matrices, Letter Fluency and the Frontal Assessment

Battery; (3) language (Token Test for verbal comprehension and the

naming subtest of the Aachener Aphasie test; (4) selective and

divided attention (Visual Search Test,Trail Making Test part A and B ;

(5) and visuospatial and constructional abilities (Copy Drawing Test

and the position discrimination subtest of the Visual Object and Space

Perception test and construttive apraxia. Details on administration

procedures and Italian normative data for score adjustment based on

age and education as well as normality cut-off scores (>95% of the

lower tolerance limit of the normal population distribution) were

available [24-30]. The neuropsychiatric assessment included the

11

Neuropsychiatric Inventory [31] which evaluate the presence and

severity of 12 non-cognitive symptoms in the month previous the last

examination, as well as tests for the evaluation of depression ( Cornell

Depression Scale) [32] and Hospital Anxiety and Depression Scale,

depression subscore) [34]. Anxiety symptoms were evaluated through

the Hamilton Anxiety Rating Scale [33] and Hospital Anxiety and

Depression Scale, anxiety subscore) [34].

Assessment of comorbidity

Somatic comorbidity was quantified by the Cumulative Illness

Rating Scale (CIRS) [35], which evaluates a score to the total burden

of illness of 13 body systems (cardiac, hypertension, vascular,

respiratory disease, eye-nose-throat dysfunction, upper and lower

gastro-intestinal disease, hepatic, renal or genitor-urinary disease,

musculoskeletal disease, neurological disease and

endocrine/metabolic disease), ranging from no disease (score = 1) to

12

life-threatening disease (score = 5). The CIRS illness severity index

was also calculated, as summary score based on the average of all

CIRS items.

Furthermore, the following vascular risk factors and diseases

were evaluated:

(a) Vascular risk factors:

- Current smoking: included all subject with current smoking (any

amount at least in the last five years);

- Hypertension, diabetes mellitus, hypercholesterolaemia with low-

and high-density lipoprotein cholesterol, hypertrigliceridaemia,

hyperhomocysteinemia as previously defined,

- Obesity (body mass index ≥30)

- Carotid atherosclerosis (degree of stenosis ≥50% of the internal

carotid arteries assessed by colour Doppler ultrasound);

- Intima-media tickness ( assessed as a value ≥ 1,1 mm)

13

(b) Vascular diseases:

- Coronary ischaemic heart disease (as evidenced by medical history

of myocardial infarction, angina, coronary artery bypass graft or

angioplasty and/or detected by EKG),

- Atrial fibrillation (evidenced by medical history and/or detected by

EKG, and/or treatment with dipiridamole or warfarin)

- Cardiac Valvulopaties and Rythm disturbances (evidenced by

medical history and documented by cardiological records)

- TIA/Stroke (evidenced by medical history and/or detected by

significant lesion on CT or MRI brain or confirmed by neurological

examination)

In the present study, subjects with previous stroke documented

by clinical history or CT/MRI scan positive for stroke were excluded.

On the contrary, subjects showing silent strokes on CT/MRI done

during the investigation were not excluded.

14

For each subject, all data collected were recorded on a

computer by means of a dedicated data entry programme, and the

data acquired were processed for quality control and statistical

analysis.

APOE genotyping from blood samples was done using the

DNA PCR amplification and single nucleotide extension technique.

Patients with either one or both 4 alleles were considered as 4 carriers

15

Neuroimaging

Carotid arteries duplex ultrasonography was

performed in all subjects to measure the intima-media

thickness (IMT) in the left and right common carotid arteries

by the mean value of six measurements [36]. IMT is a marker

for the extent of subclinical atherosclerosis. Stenosis of

internal carotid arteries was graded according to NASCET

trials [37] as low-degree stenosis (0% to 40%), moderate

stenosis (50% to 60%), and hemodinamically relevant

stenosis (≥ 70%).

All subjects underwent brain scans either CT or MRI.

Due to the prevalent epidemiological-clinical design of our

projects, and to the fact than in our country the number of

MRI scanners is limited whereas the less expensive CT

scanners are numerous and are the most used brain imaging

tool worldwide, we did not advise a common scanning

protocol and we allowed the use of different machineries.

The MRI equipment used operated from 0.5 to 1.5 T.

Axial T1- and T2-weighted images, axial fluid-attenuated

16

inversion recovery and proton density images were used.

Slice thickness was 5mm mm.

Findings on CT/MRI images were evaluated on the

computer screen by one experienced radiologist and two

trained neurologists who were blinded to subject’s clinical

data examined.

Brain atrophy

With the assumption that ventricular enlargement

basically reflects brain tissue loss either at cortical level as

well as at white matter axonal tracts, global brain atrophy

was determined within the axially acquired images on CT and

MRI using a multiplicity of linear distances measures using a

transparent metric ruler: a) the bifrontal span of the lateral

ventricle, b) the width of the lateral ventricles at the head of

the caudate nucleus, c) the minimum width of the bodies of

the lateral ventricles at the waist. For these three ventricular

measurements (a,b,c, above), ratios were determined by

dividing the values obtained by the maximum width of the

skull at the same level as the bifrontal span, caudate nuclei

17

an lateral ventricles measurement, resulting the following

ratios : bifrontal ratio, bicaudate ratio, lateral ventricular ratio.

Brain atrophy was evaluated semi-quantitatively using

the bicaudate ratio. Within the axially acquired images those

on which the two caudate nuclei produced the greatest

indentation on the lateral ventricles was selected, the

distance between the two caudate apices ie the ventricular

dimension, was measured in millimeters and divided by the

maximum width of the skull at the same level as the caudate

measurement. With this simple measurements, the highest

is the ventricular enlargement the highest is the distance

between the two caudate nuclei resulting in a higher

bicaudate ratio. Therefore, a larger value of bicaudate ratio

indicates a greater degree of atrophy.

Vascular lesions

Vascular lesions were classified according to size

(lacuna, defined as area of tissue destruction 3-10 mm in

diameter with their centre isointense to CFS on MRI and

18

hypodense on CT, or infarction), number (single or multiple)

and size of the vessels involved (large vessels, small vessels

or combined). Large-vessel cortical-subcortical infarcts were

considered as well-defined areas with an abnormal TC/MRI

signal in a specific vascular distribution territory with no mass

effect. Small-vessel lacunar infarcts were considered areas

with an abnormal TC/MRI signal sized ≥ 10 mm in diameter

(small subcortical infarcts) located in the subcortical white

matter, thalamus, nucleo-capsular region or basal ganglia.

The number of lacunes and small-vessel lacunar infarcts was

categorized into none =0, one=1 (1 lacuna/lacunar infarct),

few =2 (2 to 3 lacunes/lacunar infarcts), and many= 3 (4

lacunes/lacunar infarcts or more). For each hemisphere, the

brain areas used for rating the location of lacunes and lacunar

infarcts were the same rated for white matter lesion (WML)

by Wahlund et al [38] : frontal, parieto-occipital, temporal,

infratentorial (brainstem/cerebellum) and basal ganglia

(striatum,/globus pallidus, thalamus, internal/external

capsule). The region-specific scores of both hemispheres were

summed in order to use both the total categorized number

19

of lacunes (range 0 to 30) and the partial degree for brain

regions (range 0 to 24) and basal ganglia (range 0 to 6). The

same modalities of categorization and scoring were used for

small lacunar infarcts. For the following analyses, the

presence of ≥1 focal lesion in at least one brain region, it

was scored as “presence of lacuna/lacunar infarct”.

White Matter Lesion [WML].

WML involving the periventricular and deep sub-

cortical white matter were defined as areas of ill-defined

hypodensity on CT scans (leukoaraiosis) and areas with high

signal intensities on proton-density and T2-weighted MRI

scans. The presence, location, and severity of WML on MRI

were rated visually according to the Walhund scale [38]

applicable to both CT and MRI and to the a 4-point visual

scale of Fazekas et al. [39] applicable to MRI only. Using the

Fazekas scales [39], WML were assessed as periventricular

hyperintensities (WML-PV) or deep, subcortical, wither

matter hyperintensities (WML-SB). WML-PV were graded as

follow: Grade 0= no changes, Grade 1 = “caps” or pencil-thin

lining, Grade 2 = smooth “halo”, Grade 3 = irregular

20

periventricular WML extending into the deep with matter.

WML-SB were graded as follow: Grade 0 = no changes, Grade

1 = mild WML punctuate foci single or “grouped” WM lesions

below 10 and 20 mm respectively); grade 2= moderate WML

(single lesion between 10 and 20 mm; areas of “grouped”

lesions more than 20 mm in diameter; no “connecting

bridges” between individual lesions, grade 3= severe WML

(single lesion or confluent areas of WML 20 mm in diameter;

selective deep WML separate from periventricular regions).

The presence of caps on anterior and posterior horns of the

lateral ventricles and of pencil-thin lining of periventricular

WML corresponding to Fazekas’s WML-PV grade 1 was

defined as absence of WML. Fazekas’s WML-PV grade 2 and

Fazekas’s WML-SC grade 1 were defined as presence of

mild WML, whereas Fazekas’s WML-PV grade 3 and

Fazekas’s WML-SC grade 2 and 3 were defined as presence

of severe WML. Using the Whalund scale [38], WML were

defined as images of ≥ 5 mm hyperintense on T2,PD, or

FLAIR images and hypointense on CT and were rated

visually as follow: 0= no lesions (including symmetrical, well-

21

defined caps or bands); 1= focal lesions; 2= beginning

confluence of lesions; 3= diffuse involvement of the entire

region ,with or without involvement of U fibers. For each

hemisphere, the brain areas used for rating were: frontal,

parieto-occipital, temporal, infratentorial

(brainstem/cerebellum) and basal ganglia (striatum, globus

pallidus, thalamus, internal/external capsule, and insula). The

region-specific scores of both hemispheres were summed in

order to use both the total degree of WML (range 0 to 30)

and the partial degree of WML for brain regions (range 0 to

24) and basal ganglia (range 0 to 6). For the following

analyses when a score of ≥1 focal lesion in at least one

brain region was observed, it was scored as “presence of

WML”.

22

Diagnostic criteria for AD

NINDS-ADRDA Diagnostic criteria for Alzheimer's Disease

(AD) [40] were used to diagnostic AD subjects. Core diagnostic criteria

for AD subjects was the presence of an early and significant episodic

memory impairment that includes the following features:

- gradual and progressive change in memory function reported by

patients or informants over more than 6 months;

23

- objective evidence of significantly impaired episodic memory on

testing: this generally consists of recall deficit that does not improve

significantly or does not normalise with cueing or recognition testing

and after effective encoding of information has been previously

controlled;

- the episodic memory impairment can be isolated or associated with

other cognitive changes at the onset of AD or as AD advances

We did not have the opportunity of evaluate supportive

features for AD as the presence of medial temporal lobe atrophy and

of abnormal cerebrospinal fluid biomarkers (low amyloid β1–42

concentrations, increased total tau concentrations, or increased

phospho-tau concentrations, or combinations of the three)

Diagnostic criteria for amnestic mild cognitive impairment [aMCI]

aMCI was defined according to criteria recommended by the

MCI Working Group of the European Consortium on AD [41], which is

24

cognitive decline relative to previous abilities during the past year

reported by patient or informant; impairment in memory domain;

essentially normal functional activities; and absence of dementia.

The operational criteria included: 1) Subjective cognitive

complaints from a single question asking whether subject had more

problems with memory than most, or a single ‘yes or-no’ informant

report of memory decline, “Do you think your family member’s memory

or other mental abilities have declined?”; 2) Memory impairment was

defined as a score that was 1.5 SD below age education adjusted

norms of the Rey Auditory Verbal Learning Test (RAVLT) and delayed

recall or the Short story and delayed recall; 3) functional independence

was defined with respect to performing ten basic activities of daily

living (BADL) [31]: bowels, bladder, grooming, toilet use, feeding,

transferring, mobility, dressing, stairs, and bathing; 4) The absence of

dementia was defined by the presence of (i) Mini-Mental State

Examination (MMSE) [23] score more than 24, or (ii) Clinical Dementia

25

Rating (CDR) scale [42] global score of 0,5 and Sum of Boxes score

less than 3 [43].

Cognitively healthy controls

Cognitively healthy controls were identified from participants

with no subjective memory complaints, whose cognitive test

performance on delayed memory recall from the RAVLT and BVMT-R,

attention and executive function (RCPM, Phonemic Fluency, Attentive

Matrices), visual-spatial ability (Constructive Apraxia), and language

(Aachener denomination, Token Test) were above−1.5 SD of age-

education adjusted norms, were functionally independent on BADL,

and did not have dementia.

Metabolic syndrome

26

MetS was defined using the International Diabetes Federation

criteria [1]. Based on this definition, patients must have central obesity

(waist circumference ≥90 for male and ≥80 for female) plus at least

two of the following components: raised triglyceride level (≥150 mg/dL

(1.7 mmol/L) or specific treatment for this lipid abnormality); reduced

high density lipoprotein (HDL) cholesterol (<40 mg/dL (1.03 mmol/L) in

males, and <50 mg/dL (1.29 mmol/L) in females or specific treatment

for this lipid abnormality); raised blood pressure (BP) (systolic BP≥130

or diastolic BP≥85mm Hg, or treatment of previously diagnosed

hypertension), and raised fasting plasma glucose (FPG) (≥100 mg/dL

(5.6 mmol/L), or previously diagnosed type 2 diabetes).

Self-report of a physician diagnosis of diabetes, hypertension,

or treatment for these conditions was ascertained by interview.

Participants were asked to show all their current medications to the

research nurses during interviews, details of drugs use for diabetes,

hypertension,

27

Statistical analysis

Means among groups were analysed by one-way analisys of

variance (ANOVA), while contingency tables were evaluated by the -

test.

The association between cognitive status, MetS and putative risk

factors/diseases was investigated with binary multiple logistic

regression analyses, controlling for age, sex and education (model 1).

A subsequent model included other significant variables which resulted

significant from the model 1, and age, sex and education was added

(model 2). All tests were two-tailed; statistical significance was set at p

≥0.05. Results are presented as odds ratios (ORs) with 95%

confidence intervals (95% CIs). All analyses were performed using the

SPSS statistical package version 12.0 (SPSS Inc., Chicago, Ill., USA).

28

RESULTS

Fig. 1 shows the flow diagram of the CogItA study at 30 July

2012. Among the 6948 selected participants, we excluded subjects

without imaging (n. 657), young (n.1372), partecipants with previous

stroke (n. 69), meaningful neurological examination (n. 56),

Parkinson’s disease (n. 441) and vascular parkinsonism (n. 60), VaD

29

(n. 146), and naMCI (n. 551). Therefore, the present study involved

3665 participants (n. 1748 controls, n. 1180 aMCI and n. 737 AD).

Demographics, comorbidity scores, vascular risk factors and

vascular imaging scores of our sample are reported in Tab 1.

The mean age of the controls participants was 61.9 (±10.7), the

mean (±SD) education score was 8.6 (±4.5) and the mean (±SD) mild

subcortical atrophy was 0.12 (±0.02).

About 64.7% (n = 1131) were female, 32.3% (n = 565) were

current smokers, 36.8% (n = 644) had hypercholesterolemia, 3.1% (n

= 54) had hyperuricemia, 58.3% (n = 256) had hyperhomocysteinemia,

39.6% (n = 692) had depression, 41.7% (n = 729) had anxiety, 3.7% (n

= 65) had atrial fibrillation, 8.2% (n = 144) had ischemic cardiopathy,

15.5% (n = 56) had cardiac valvulopaties, 28.5% (n = 434) had intima-

media tickness, 1.4% (n = 22) had carotid stenosis, 15.1% (n = 102)

had APOE-4, 5.9% (n = 104) had TIA, 11.5% (n = 201) had WML,

0.8% (n = 14) had stroke, and 16.2% (n = 284) had lacunae, 34.3 % (n

30

= 481) had MetS, 23.1 % (n = 319) had Hypertension, 20.6 % (n =

294) had diabetes, 22.1 % (n = 315) had hypertrygliceridemia, 64.4%

(n = 1112) had obesity and 29.0% (n = 375) raised high-density

lipoprotein.

The mean age of the aMCI participants was 69.8 (±9.5), the

mean (±SD) education score was 6.9 (±4.6)and the mean (±SD) mild







30.9% (n = 68) had cardiac valvulopaties, 51.9% (n = 595) had intima


had APOE-4, 7.8% (n = 92) had TIA, 27.0% (n = 319) had WML, 8.1%

(n = 96) had stroke, and 31.9% (n = 376) had lacunae, 38.3 % (n =

31

403) had MetS, 24.2% (n = 218) had hypertension, 25.2 % (n = 270)

had diabetes, 23.3% (n = 248) had hypertrygliceridemia, 59.2% (n =

682) had obesity and 30.1% (n = 304) raised high-density lipoprotein.

The mean age of the AD participants was 76.5 (±7.5), the

mean (±SD) education score was 4.7 (±3.5)and the mean (±SD) mild







21.2% (n = 25) had cardiac valvulopaties, 70.2% (n = 482) had intima


had APOE-4, 4.2% (n = 31) had TIA, 34.9% (n = 257) had WML, 1.6%

(n = 12) had stroke, and 24.8% (n = 183) had lacunae, 29.4% (n =

168) had hypertension, 25.5 % (n = 166) had diabetes, 25.9% (n =

32

169) had hypertrygliceridemia, 69.8% (n = 469) had obesity, and

38.1% (n = 235) raised high-density lipoprotein.

Cognitively healthy controls participants compared with aMCI

and AD were significantly younger, had higher education level and

lower percentage of comorbidity and lower levels of hyperuricemia

and hyperhomocystenemia. Furthermore, depression, atrial fibrillation,

ischemic cardiopathy, intima-media tickness, carotid stenosis, WML,

lacunae, higher mild subcortical atrophy level, MetS, diabetes, raised

high-density lipoprotein were more frequently present in aMCI and AD.

Healthy controls had lower percentage of smoking, and anxiety

than aMCI, and higher percentage than AD patients. Healthy controls

had higher percentage of obesity than aMCI and had lower percentage

than AD patients. Arterial hypertension and APOE-Σ4 were less

present in healthy controls than in AD subjects. Cardiac valvulopaties,

TIAs and stroke were less present in healthy controls than in aMCI

subjects.

33

Table 2 shows the multivariate associations of those vascular

risk factors, imaging scores and MetS components that at the

univariate analysis resulted positively associated in Controls versus

aMCI and in Controls versus AD.

In the adjusted model for sex, age and education (model 1), in

wich cognitively healthy controls were compared with aMCI, smoking

(OR = 1.3; 95% CI 1.1–1.6), hyperuricemia (OR = 1.8; 95% CI 1.1–

2.4), depression (OR = 2.5; 95% CI 2.1–3.0), anxiety (OR = 1.6; 95%

CI 1.3–1.9), cardiac valvulopathies (OR = 1.7; 95% CI 1.1–2.7), intima-

media tickness (OR = 1.6; 95% CI 1.3–1.9), carotid stenosis (OR =

2.0; 95% CI 1.2–3.4), WML (OR = 1.9; 95% CI 1.5–2.3), stroke (OR =

13.2; 95% CI 7.3–24.1), lacunae (OR = 1.6; 95% CI 1.4–2.0), mild

subcortical atrophy (OR = 1.9; 95% CI 5.8–6.4) and obesity (OR = 0.7;

95% CI 0.6–0.8) were significantly associated with increased odds of

aMCI. Adjustment for demographic and clinical covariates including

vascular risk factor and neuroimaging measurements (model 2)

34

reduced the estimate of the odd ratio for aMCI leaving statistically

significant depression (OR = 2.3; 95% CI 1.3–4.2), stroke (OR = 4.2;

95% CI 1.3–13.7), mild subcortical atrophy (OR = 2.5; 95% CI 2.4–2.6)

and obesity (OR = 0.5; 95% CI 0.3–0.8) only.

In the adjusted model for sex, age and education (model 1), in

wich cognitively healthy controls were compared with AD subjects,

depression (OR = 2.3; 95% CI 1.3–4.2), intima-media tickness (OR =

1.9; 95% CI 1.5–2.5), APOE-Σ4 (OR = 3.0; 95% CI 2.0–4.3), WML

(OR = 1.9; 95% CI 1.4–2.4), mild subcortical atrophy (OR = 1.1; 95%

CI 2.8–4.7) and obesity (OR = 0.7; 95% CI 0.5–0.8) were significantly

associated with increased odds of AD. Adjustment for demographic

and clinical covariates including vascular risk factor and neuroimaging

measurements modestly reduced the estimate of the odd ratio leaving

statistically significant depression (OR = 1.7; 95% CI 1.2–2.4), APOE-

4 (OR = 2.4; 95% CI 1.6–3.8) and mild subcortical atrophy (OR = 7.2;

95% CI 6.2–8.4) only.

35

Tab. 3 shows the association between MetS and aMCI

subjects stratified for age, APOE-Σ4 variously combinated. It appears

from the table that MetS was significantly associated with increased

odds in subjects aged ≤ 65 years.

Table 4 shows the association between MetS and AD subjects

stratified for age, APOE-Σ4 variously combinated.

It appears from the table that MetS was significantly

associated with increased odds in all subjects. Furthemore, MetS

was significantly associated with AD independently of the type of

APOE. When APOE-Σ4 carriers and age were associated, MetS was

significantly associated with increased odds in AD subjects aged ≥ 65

years. By the end, when non APOE-Σ4 carriers and age were

associated, MetS appeared not associated with AD.

36

DISCUSSION

We found that MetS is not associated with aMCI. Only one

component of MetS, central obesity, showed increased odds of

association with aMCI. The association of MetS with aMCI appeared

not to be influenced by APOE-Σ4 status. However, when subjects

37

were stratified for age, MetS was modestly associated with younger

age in aMCI subjects.

On the contrary, we found that MetS is associated with AD

independently of the age and of the APOE-Σ4 status since non APOE-

Σ4 carriers showed an increased odd [2.0 (1.1-3.6)] respects to APOE-

Σ4 carriers [1.4 (1.1- 1.9)]. However, when subjects were stratified for

age and APOE-Σ4 status, MetS was associated with a reasonable

odd [ 2.3 ( 1.1-4,9] in subjects APOE-Σ4 carriers aged ≥65 years.

This study failed to demonstrate directly a positive association

between MetS and aMCI, a precursor state of AD. This stands in

agreement with several recent studies that have failed to demonstrate

a positive relationship directly between MetS and MCI [14, 16].

In contrast, among studies of old-old cohorts, MetS have been

found be associated with either no increased odds of association with

MCI overall as in the relatively older Omsted county study of

individuals aged 70 to 89 [14], or decelerated decline in cognition from

38

follow up as in the Leiden 85 + study [44], or significantly better

cognitive function among elderly aged 75 + in Tuscania (Italy) [45].

We found that the principal component of MetS, central obesity,

was not associated with aMCI and AD. This finding is not consistent

with published findings that obesity in mid-life is a risk factor for late-

life dementia [46–48] Interestingly too, this finding is in agreement with

other published findings showing hat in old-old study populations, high

bodymass index was not found to be associated with AD [49, 50].

Together, the different ages at which MetS and its components were

measured in these studies, and the reverse causality underlying the

paradoxical relationship between MetS and dementia onset in very old

age [51, 52] are likely explanations for the variable findings across

studies.

We found in this study that the association between MetS and

aMCI was present, albeit not particularly strong, only among

39

individuals aged < 65 years. No association was found between MetS

and aMCI wathever was the APOE allele.

MetS was associated with 1.8 times increased odds for AD

aged <65 years and 1,3 times among subjects aged >65 years. MetS

was also associated with 1,4 times odds for APOE-Σ4 carriers AD and

2,0 times in AD non APOE-Σ4 carriers. However, when APOE status

and age were variously combined, MetS was associated with 2,3

times increased odds only for AD aged >65 years but not for AD aged

<65 years and AD non APOE-Σ4 carriers.

It is well known that APOE modulates susceptibility to both

atherosclerosis and AD through its pleiotropic and context-dependent

effects on plasma lipoprotein metabolism, coagulation, oxidative

processes, macrophage, glial cell and neuronal cell homeostasis,

central nervous system (CNS) physiology, inflammation, and cell

proliferation [53]. It also known that APOE plays direct roles in CNS

cholesterol transport and lipid homeostasis, amyloid-β (Aβ) clearance,

40

synaptic plasticity, and neuronal repair [54]. Carriers of the APOE-Σ4

allele are at increased risk of AD [55, 56] as well as an earlier age at

onset of AD [19].

Our results are in agreement with other reports of relevant

risks among APOE-Σ4 carriers of AD associated for components of

MetS, namely hypertension [57], diabetes [57–60], hypercholesterol

[60], and with atherosclerosis [59].

However, this study confirms that beside the APOE status,

age is another important risk factor for AD since MetS is not

associated with AD when APOE-Σ4 status and age <65 years are

taken into consideration.

The mechanisms underlying the association between MetS and

AD are still not fully understood. Several hypotheses have been

proposed to explain their relationship. First, macrovacular and

microvascular injury caused by diabetes could contribute to the

findings [61]. The presence of heart disease and stroke contributed in

41

part to the observed association in this study, but it is also likely that

subclinical vascular diseases such as lacunae and white matter

hyperintensities could possibly be an underlying factor. Some

researchers also reported that white matter lesions [WML], a

surrogate marker of small vessel disease, could partially mediate the

association [62].

The multiple-adjusted logistic regression analysis for the

association between vascular and metabolic risk factors for aMCI and

AD with MetS shows that stroke and subcortical atrophy increase the

risk of aMCI of 4,2 and 2,5 respectively, whereas for AD only cerebral

atrophy is strongly associated since the odd is equal to 7,2.

In conclusion, our data permit to affirm that MetS components

are cofactors of vascular cerebral damage with a consequent fiber

tracts lesions and cerebral atrophy. Both lesions, APOE-Σ4 status and

age >65 years greatly contribute to the AD onset.

42

Possible limitations to this study should be discussed. First, the

associations of MetS and its individual components with aMCI and AD

were estimated from cross-sectional analyses, hence precluding firm

causal inference. In general, bias from selective non participation by

subjects who are impaired by their exposure to the risk factor may

cause underestimation of effects. However, this did not appear to have

mitigated the observed relationship between MetS and cognitive

impairment. Furthermore, cases of non-amnestic MCI were not

included in the study because the number of cases was too small to

give meaningful results. This precludes us from a wider examination of

the associations between MetS and different MCI subtypes together.

This should be further investigated in future studies.

ACKNOWLEDGMENTS

43

Thanks are due for encouragment and support to Prof.

Rosolino Camarda former Director of the UOC di Neurologia e

Patologie Cognitive of the Policlinico P.Giaccone, Palermo.

I am deeply indebted also to Dr. Giusi D. Ventimigila, PhD, for

the assistance in the preparation of this thesis.

Appendix

Figure 1: flow diagram of the study population

Sample

44

N. 6948 No Imaging N. 657 ≤ 44 anni N. 1372 Stroke N. 69

Normali

Meaningful N. 56

Parkinson Desease

N. 441

Vascular

Park N. 60

VaD N. 146

naMCI ≥45 anni N. 551

Controls aMCI+ AD+ N. 1748 N. 1180 N. 737

aMCI N. 469 aMCImd N. 711

Table 1. Demographics, comorbidity scores, vascular risk factors and vascular imaging scores of controls, aMCI and AD

Controls

(n=1748)

aMCI

(n=1180)

AD

(n=738)

45

Female, n (%) 1131 (64.7) 636 (53.9)*** 503 (68.2)***

Age, years 61.9 (10.7) 69.8 (9.5)*** 76.5 (7.5)***

Education, years 8.6 (4.5) 6.9 (4.6) *** 4.7 (3.5)***

CIRS score 19.8 (3.1) 21.7 (3.6)*** 21.4 (3.1)

Smoking 565 (32,3) 439 (37,2)** 172 (23,3)***

Hypercolesterolemia 644 (36,8) 464 (39,3) 248 (33,6)

Hyperuricemia 54 (3,1) 88 (7,5)*** 45 (6,1)***

Hyperhomocystenemia 256 (58,3) 490 (68,5)*** 322 (76,1)***

Current depression 692 (39,6) 676 (57,3)*** 333 (53,5)***

Current anxiety 729 (41,7) 537 (45,5)* 243 (33) ***

Atrial Fibrillation 65 (3,7) 71 (6)** 66 (9)***

Ischemic Cardiopathy 144 (8,2) 156 (13,3)*** 113 (15,5)***

Cardiac Valvulopaties 56 (15,5) 68 (30,9)*** 25 (21,2)

Intima-media tickness 434 (28,5) 595 (51,9)*** 482 (70,2)***

Carotid stenosis 22 (1,4) 49 (4,3)*** 30 (4,4)***

ApoE4 allele 102 (15,1) 162 (18,2) 152 (28,6)***

TIA 104 (5,9) 92 (7,8)* 31 (4,2)

Neuro_Imaging

Whalund Total score 201 (11,5) 319 (27)*** 257 (34,9)***

Stroke Total score 14 (0,8) 96 (8,1)*** 12 (1,6)

Lacunae total score 284 (16,2) 376 (31,9)*** 183 (24,8)***

Mild subcortical atrophy (m±sd)

0,12 (0,02) 0,15 (0,02) *** 0,17 (0,02) ***

46

MetS

MetS 481 (34,3) 403 (38,3)* 308 (47.8)***

Raised blood pressure 319 (23,1) 218 (24,2) 168 (29.4)**

Raised fasting plasma glucose 294 (20,6) 270 (25.2)** 166 (25,5)*

Raised triglycerides 315 (22,1) 248 (23,3) 169 (25.9)

Obesity 1112 (64,4) 682 (59.2)** 469 (69,8)*

Raised high-density lipoprotein 375 (29,0) 304 (30,1) 235 (38,1)***

Abbreviations: aMCI+= amnestic mild cognitive impairment, AD= Alzheimer's disease; CIRS=

Comorbidity Inventory Rating Scale

Significant differences at pair comparison (one-way analysis of variance with

Scheffe’s post-hoc test) are starred (compared to PC-cn group) as follows: * p=

<0.05; **p= <0.01; ***p= <0.001.

Table n. 2 Odds Ratio (OR) and 95% Confidence Intervals (CIs) from simple-adjusted (Model 1) and multiple-adjusted (Model 2) logistic regression analysis for the association between vascular and metabolic risk factors and aMCI or AD with metabolic syndrome

47

Controls vs aMCI Controls vs AD

Variables Model 1 Model 2 Model 1 Model 2

OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)

Smoking1.3 (1.1-1.6) 1.2 (0.7- 2.1) 1.1 (0.8-1.4)

Hyperuricemia1.8 (1.1-2.4) 1.7 (0.6- 4.7) 0.9 (0.6-1.5)

Hyperhomocystenemia1.2 (0.9-1.5) 1.3 (0.9-1.9)

Current depression2.5 (2.1-3.0) 2.3 (1.3-4.2) 1.7 (1.4-2.2) 1.7 (1.2-2.4)

Current anxiety1.6 (1.3-1.9) 0.8 (1.3- 4.2) 0.8 (0.6-1.0)

Atrial Fibrillation0.9 (0.7-1.4) 1.1 (0.7-1.7)

Ischemic Cardiopathy1.1 (0.8-1.4) 1.2 (0.9-1.7)

Cardiac Valvulopaties1.7 (1.1-2.7) 1.7 (0.9- 2.8)

Intima-media tickness1.6 (1.3-1.9) 1.2 (0.7-2.0) 1.9 (1.5-2.5) 1.3 (0.9-2.0)

Carotid stenosis2.0 (1.2-3.4) 1.6 (0.6-4.6) 1.5 (0.8-2.9)

ApoE4 allele3.0 (2.0-4.3) 2.4 (1.6-3.8)

TIA1.0 (0.7-1.4)

Neuro Imaging

Whalund Total score1.9 (1.5-2.3) 1.0 (0.6-1.8) 1.9 (1.4-2.4) 1.5 (0.9-2.2)

Stroke Total score13.2 (7.3-24.1) 4.2 (1.3-13.7)

Lacunae total score1.6 (1.4-2.0) 1.5 (0.9- 2.4) 0.8 (0.6-1.0)

Mild subcortical atrophy (m±sd) 1.9 (5.8-6.4) 2.5 (2.4-2.6) 1.1 (2.8-4.7) 7.2 (6.2-8.4)

MetS

MetS1.0 (0.8-1.2) 1.2 (0.9-1.5)

Raised blood pressure1.3 (0.9-1.7)

48

Raised fasting plasma glucose1.1 (0.9-1.4) 1.1 (0.9-1.5)

Obesity0.7 (0.6-0.8) 0.5 (0.3-0.8) 0.7 (0.5-0.8) 0.6 (0.4-1.0)

Raised high-density lipoprotein 1.2 (0.9-1.5)

Abbreviations: aMCI+= amnestic mild cognitive impairment, AD= Alzheimer's disease;Model 1: data are adjusted for age, sex and education; Model 2: data are adjusted for demographics and the other vascular/metabolic variables which significantly differs when comparing controls vs MCI and controls vs AD from chi-square analysis (Table 6)

Tab. 3 Association between MetS and aMCI after stratification for age, APOΣ4 status and various combination of age and APOE status

49

Subgroups n OR (95%CI) p

Age < 65 1357 1.3 (1.1-1.8) 0.041

Age>=65 1571 0.9 (0.7-1.1) 0.504

APOE4 carrier 264 1.2 (0.7-2.2) 0.506

Non APOE4 carrier 1300 1.1 (0.8-1.3) 0.572

APOE4 carrier and Age < 65

86 0.8 (0.3-2.4) 0.712

APOE4 carrier and Age>=65

178 1.4 (0.7-3.0) 0.370

Non APOE4 carrier and Age < 65

470 1.2 (0.8-1.8) 0.398

Non APOE4 carrier and Age>=65

830 0.9 (0.7-1.2) 0.438

Tab. 4 Association between MetS and AD after stratification for age, APOΣ4 status and various combination of age and APOE status

50

Subgroups n OR (95%CI) p

Age < 65 1099 1.8 (1.0-3.1) 0.041

Age>=65 1386 1.3 (1.1-1.7) 0.012

APOE4 carrier 254 1.4 (1.1-1.9) 0.015

Non APOE4 carrier 954 2.0 (1.1-3.6) 0.022

APOE4 carrier and Age < 65

69 0.8 (0.2-3.1) 0.768

APOE4 carrier and Age>=65

185 2.3 (1.1-4.9) 0.027

Non APOE4 carrier and Age < 65

317 1.9 (0.8-4.2) 0.130

Non APOE4 carrier and Age>=65

637 1.1 (0.8-1.5) 0.530

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INTRODUCTION · Web viewIt also known that APOE plays direct roles in CNS cholesterol transport and...

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