Slide 1

The imaging genetics study in heroin addiction Jie Shi National Institute on Drug Dependence, Peking University

Slide 2

Harm of drug addiction Induce fraud, violent crime, prostitution, etc Cause a direct economic loss of more than 200 billion a year Impair individual health and cause higher death rate Cause spread of infectious diseases such as HIV, HCV, etc China Narcotics Control Report in 2014 Registered drug addicts (10 4 ) 2

Slide 3

Harm of heroin addiction Heroin addiction has been associated with multiple impaired behavioral functions, such as global cognition, impulsive decision- making and impulsivity Drug Alcohol Depend, 2008 J Psychopharmacol, 2010 Repeated exposure to heroin could result in persistent molecular and morphological changes in the brain J Neuropsychiatry Clin Neurosci., 2007 Science, 2012 3

Slide 4

Genetic factors in drug addiction Heroin addiction was influenced by genetic factors to a greater degree than other drug addiction. Arch Gen Psychiatry., 1998 Applying genetic approaches would contribute great to addiction therapy methods Pharmacol Ther., 2005 Oncogene., 2002 4 Opiate addiction Genetic factors Drug addiction Nat Genetic., 2005

Slide 5

Genetic factors Cognition Decision-making Relapse Genetics affect drug addiction Brain 5

Slide 6

Imaging Genetics Curr Opin Genet Dev. 2011 Imaging genetics is a form of genetic association analysis It provide a unique tool to explore the functional impact of brain relevant genetic polymorphisms, which may thus fill the gap between the gene and the diagnostic category 6

Slide 7

Imaging Genetics Curr Opin Genet Dev. 2011 7

Slide 8

Limited to the single candidate gene association in small sample The study of genetic effects on addiction-related phenotype is still in its infancy The mechanism underlying the association is unclear 8 Gene Cell Behavior Brain Current limitations of genetics studies in addiction 8

Slide 9

Imaging genetics study in heroin addiction Genetic effects on endophenotypes Recruiting subjects and collecting genetic sample Brain network Brain morphometry Behavior tests Animals or multi-modal analysis and molecular biology experiments Screening candidate genetic risk factors Verified in large sample Endophenotype Genetic association analysis Genetic regulatory mechanism 9

Slide 10

Research contents Behavioral and imaging abnormality of heroin addicts 1 The genetic risk factors of heroin addiction 2 Association analysis between ZNF804A variants and heroin addiction Association analysis between MAOA variants and heroin addiction 10

Slide 11

Research contents Behavioral and imaging abnormality of heroin addicts 1 The genetic risk factors of heroin addiction 2 Association analysis between ZNF804A variants and heroin addiction Association analysis between MAOA variants and heroin addiction 11

Slide 12

Methods Imaging analysis Brain structure Brain connection Brain network Behavioral analysis Cognition -Montreal cognitive assessment Impulsivity-Iowa gambling task (IGT) Barratt Impulsiveness Scale (BIS-11) 12

Slide 13

Behavioral abnormalities of heroin addicts Heroin addicts showed significantly worse cognition and impulsivity Montreal cognitive assessment (MoCA) Barratt Impulsiveness Scale (BIS -11) Iowa gambling task (IGT) 13

Slide 14

Gray matter abnormality of heroin addicts 14 The gray matter of heroin addicts showed widely atrophy, mainly in frontal and temporal lobe.

Slide 15

White matter abnormality of heroin addicts 15 The FA value of white matter in heroin addicts was widely increased, mainly in corpus callosum and inferior longitudinal fasciculus.

Slide 16

Disrupted network connectivity in heroin abusers 16 The subnetwork was significantly increased in heroin abusers, which can be categorized into 3 systems: default-mode system, attention system and vision system.

Slide 17

Relationships between network metrics and clinical variables and performance 17 Within-frontal connection strength was positively associated with daily dosage of heroin use (A), within-temporal connection strength was negatively associated with non-planning scores on BIS-11 (B).

Slide 18

Brain functional system network Impulsive/reflective dual-system network Cognitive control system network Reward system network 18

Slide 19

IGT -9 -4 1 6 controlheroin a)Impulsive system: Amygdala, Striatum b)Reflective system: VMPFC, DLPFC, ACC, Insular, Hip Bechara et al., Nat. Neurosci. 2005 Hsu et al., Science, 2005 Impulsive/reflective dual-system network 19

Slide 20

The Impulsive/reflective network in heroin addicts Normal vs addiction, p 100 20 The impulsive control network was significantly abnormal in heroin addicts. The most significant area is insula.

Slide 21

Research contents Behavioral and imaging abnormality of heroin addicts 1 The genetic risk factors of heroin addiction 2 Association analysis between ZNF804A variants and heroin addiction Association analysis between MAOA variants and heroin addiction 21

Slide 22

Candidate SNPs 1.Validated genetic risk factors for addiction: COMT, BDNF, HTR2A, MAOA, CNR1 2. Molecules critical for psychiatric disorders : Orexin receptor, GSK-3, TrkB 3. MicroRNA related to psychosis: Mir-146a, Mir-137 4. Genetic risk factor in other psychiatric disorders: ZNF804A, CACNA1C 22

Slide 23

ZNF804A rs1344706 is the first genetic variant to achieve genome wide significance for psychosis that the A allele is associated with increased risk for schizophrenia. Nat Genet, 2008 Rs1344706 was significantly associated with expression of ZNF804A mRNA, and the disease risk A allele was associated with higher expression. Mol Psychiatry, 2011 ZNF804A knockdown on the expression of genes involved in cell adhesion, suggesting a role for it in processes such as neural migration, neurite outgrowth and synapse formation. Hum Mol Genet, 2012 ZNF804A may affect the transcription of PRSS16 and COMT (up) and PDE4B and DRD2 (down), DRD2 plays an important role in addiction. Biol Psychiatry, 2012 23 ZNF804A variants

Slide 24

Large genetic sample Heroin addicts 1036 (726 male, 309 female) Han South of China native Age 30-60 Education: 9 -12 year Controls 2887 (1313 male, 1574 female) 24

Slide 25

The candidate SNPs in ZNF804A SNPs in coding exons and critical synonymous SNPs in the intron SNP_IDGENEMAF rs1344706ZNF804A 0.453 rs7597593ZNF804A 0.402 rs12476147ZNF804A 0.221 rs4667001ZNF804A 0.189 rs1366842ZNF804A 0.179 rs12477430ZNF804A 0.163 25 The candidate SNPs were in high linkage disequilibrium D value r2 value

Slide 26

The ZNF804A variants were significant associated with heroin addiction 26

Slide 27

The variants in ZNF804A associated gene were significant correlated with heroin addiction Proteins interacting with ZNF804A (BioGRID) The critical SNPs associated with heroin addiction Results SNP_IDGENEMAF rs10946904PRSS16 0.289 rs2144719PDE4B 0.151 rs879471STMN3 0.163 rs10804166C2ORF80 0.122 rs1079597DRD2 0.5 rs4680COMT 0.256 rs179943ATXN1 0.465 rs11730582SPP1 0.326 rs6265BDNF 0.4762 rs6313HTR2A 0.4359 rs1137070MAOA 0.4011 rs279871GABRA2 0.417 rs1799971OPRM1 0.36 SNP_IDGENEP value rs10946904PRSS16p