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Dr GURSHARAN KALSI LEARNING AIMS  Overview of genetics of complex disorders, particularly addictive disorder  Main pharmacotherapies.

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Presentation on theme: "Dr GURSHARAN KALSI LEARNING AIMS  Overview of genetics of complex disorders, particularly addictive disorder  Main pharmacotherapies."— Presentation transcript:


2 LEARNING AIMS  Overview of genetics of complex disorders, particularly addictive disorder  Main pharmacotherapies available for treatment, using alcohol dependence as example  Genetic variants and their effect on treatment and recovery  Relative efficacy of pharmacotherapies and tailored treatment for addictions

3 Pharmacogenomics and addiction  The genetic variation underlying an individual’s response to drugs  Genetics may affect all aspects of drug experience, i.e. initiation, motivation, craving, inability to withdraw and clinical treatment

4 Nature or nurture  Large twin and family studies were set up in the 50s  Family studies show that children of addicts are 8 times more likely to develop addiction  In twin studies, the idea is that identical twins share same genes and family environment whereas non-identical or fraternal twins only share family environment  In a study looking at 861 pairs of identical twins and 653 fraternal twins showed that genetic factors contributed 50-60% of the risk of being alcoholic; other large twin samples showed a similar figures

5 The effect of genetic and environmental effects across age in 1796 male-male twin pairs A= caffeine B= cigarettes smoked C= alcoholic drinks D= cannabis Kendler et al, 2008

6 Epidemiology  Family, twin and adoption studies support existence of genetic influences on risk for alcohol dependence (AD) and other drug dependence  Heritability estimates show 40-60% of liability is due to genetic factors  Lifetime risk for AD is approx 10-15% for men and 3-5% for women  Age of onset is probably mid-20s to approx 40 yrs of age  The earlier the onset, the greater is the severity and the higher the probability of a pre-existing independent psychiatric condition

7 Basics of Genetics

8 The genome  The genome is the hereditary material in an organism  Comprises of the coding and non-coding sequences  Human genome ○ Nuclear genome ○ Mitochondrial genome  Size of the human genome is ~ 3 – 3.2Gb and ~20,000 – 25,000 genes

9 Chromosomes  22 pairs of chromosomes plus sex chromosomes  Banding pattern – differences in GC contents Slide courtesy of Dr Katherine Tansey

10 The gene The basic unit of genome is the gene

11 Gene is the functional unit  Molecular unit of heredity  Double-helical structure  Expression involves transcribing into RNA  Regulatory sequences control the process  Genes can have more than one promoter  microRNAs at 3’ UTR now seen to be important as epigenetic factors

12 Structure of the gene

13 Genetic polymorphisms  Single Nucleotide Polymorphisms (SNPs) A single base-pair has been altered Silent / missense / nonsense  Sequence Repeats (Insertions/deletions) A small segment of DNA (i.e. 2-,3-,4-..1000 base-pairs) is repeated Variable tandem repeats / micro- / mini-satellites  Positional Variants Changes > 1000bp  inversions / translocations

14 Types of DNA markers  RFLP (Restriction Fragment Length Polymorphism)  VNTR (Variable Number Tandem Repeat)  SSR (Simple Sequence Repeat)  SNP (Single Nucleotide Polymorphism)  STR (Short Tandem Repeat) Single base change at one site along a sequence cagTcga or cagCcga The possible genotypes for this SNP are TT, TC or CC

15 Genes and the addiction cycle Initiation (impulsivity) Tolerance Inability to withdraw Craving / relapse Compulsive use Response to treatment

16 Genes and drug metabolism

17 Genetic basis of alcohol metabolism  Alcohol metabolism is catalysed by alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH)  Metabolism is primarily in the liver

18 Edenberg et al, 2007

19 Alcohol dehydrogenase, ADH  Association with variants of ADH and ALDH shown to be the strongest and most widely replicated  Individuals with certain variants suffer reduced risk of alcohol dependence  Presence or absence of variants influence consumption e.g. ADH1B*2 and ADH1B*3 possess high enzyme activity and rapidly metabolize alcohol to acetaldehyde; accumulated acetaldehyde produces “flushing”  ADH1B*2 found in higher frequency in East Asians; it acts as a protective variant  In Jewish populations, variant has moderate frequency and prevents binge drinking

20 Aldehyde dehydrogenase, ALDH  ALDH2 is primarily responsible for metabolism of acetaldehyde to acetate  ALDH2 deficiency common in parts of Asia  ALDH2*1 encodes the active subunit; ALDH2*2 encodes an essentially inactive subunit  Individuals with one or two copies of ALDH2*2 are deficient in oxidation of acetaldehyde and suffer from adverse reactions to alcohol, including severe facial flushing, nausea, headache and tachycardia  Disulfiram, acts in similar way; it interferes with ALDH and leads to increased acetaldehyde levels, causing same symptoms

21 Macgregor et al, 2009


23 Disulfram for alcohol dependence  Treatment is based on aversive therapy and has been in use for over 60 years  Stimulates the toxic affects of acetaldehyde accumulation  Disulfram works through inhibiting alcohol dehydrogenase  Induces flushing, sweating, headaches, nausea and vomiting  Also used to treat cocaine dependence  In some individuals, it produces psychosis

24 Genes and nicotine metabolism  Nicotine is broken down by a number of liver enzymes, cytochrome A6 (CYP2A6) and cytochrome B6 (CYP2B6)  CYPA6 variants have been associated with higher adult smoking cessation rates  Individuals with CYPA6*2 variant showed reduced function of the enzyme and reduced smoking Chenoweth et al, 2013 Ray et al, 2009

25 Neurochemical basis of addiction

26 Neural pathways in addiction  Dopamine  Glutamate  Opioid  GABA  Serotonin  Cannabinoid  CRH/HPA Spanagel R, 2008.

27 Dopamine (DA)  DRD2: 20 year controversial history focus on Taq1A RFLP; located in ANKK1 A1 allele produces lower DRD2 receptor density in striatum A1 allele associated with alcohol dependence, heroin use, smoking and cocaine dependence  DRD4 VNTR shown to be associated with craving for addictive substances  DAT1 cocaine dependence and risk for cocaine-induced paranoia; smoking behaviours  COMT: variation may impact DA levels in PFC, thus affecting social cognition, affect and reward processes high activity 1947G allele associated with risk for methamphetamine abuse

28 10 DA family genes in US/Irish study  5 receptors D1-like: DRD1, DRD5 D2-like: DRD2-DRD4  2 transporters Vesicular Monoamine Transporter 2 (VMAT2) Dopamine Active Transporter 1 (DAT1)  3 enzymes Tyrosine Hydroxylase (TH) Dopa Decarboxylase (DDC) Catechol-O-methyl transferase (COMT) Kreek et al., 2002

29 Irish Affected Sib Pair Study of Alcohol Dependence (IASPSAD)  Ethnically and genetically homogeneous sample collected in Ireland  Severely affected individuals; clinical sample  575 independent cases and 530 controls  Evaluated by structured SSAGA interview  Diagnosed using DSM-IV


31 Results  Six SNPs (single nucleotide polymorphisms) in 5 genes were associated with alcohol dependence or related trait  2 SNPs were associated with disinhibitory symptom count  1 SNP was associated with general disinhibitory factor score

32 IONOTROPIC METABOTROPIC Glutamate receptors

33 Glutamate receptor genes  Crucial role in withdrawal symptoms  Gp 1 mGluRs couple to diverse intracellular signaling transduction pathways  Homer family of proteins regulate cellular localization and function of group 1 mGluR receptors Homer knockout mice avoid drinking in large quantities Do not increase dopamine and extracellular glutamate  mGluR1 increases NMDA receptor trafficking

34 Glutamate study in IASPSAD  Genes GRM1, GRIN1A, GRIN2B, GRIK1 tested on addiction array  Association analysis for alcohol dependence  Haplotype analysis  gene x gene interaction

35 Haplotype association with alcohol dependence in IASPSAD

36 G X G INTERACTION in IASPSAD GENESNPGENESNPP-VALUE GRM1rs9403765GRIN2Brs128294550.000583 GRM1rs2268666GRIN2Ars10715040.0003489 GRIN2Brs2193511GRIN2Ars172089050.0001232 GRIN2Brs10845848GRIK1rs65169260.0007265

37 Opioid system  Critical to euphoric and compulsive behavior of opiates  May be just as, or perhaps more, critical than dopamine pathway in modulating reward  Regulated through a family of receptors: µ, δ, κ and non- opioid FQ receptor  Belong to the larger G-protein coupled receptor family  Interact with DA and GABA systems to reinforce hedonic effects of heroin

38 µ (mu) opioid receptor: variants  Primary site of action for opioid peptides  Large scale sequencing identified 43 variants

39 Results of genetic studies

40 The functional polymorphism A118G  The most prevalent polymorphism (A to G)  Produces amino acid change at a putative N- glycosylation site : Asparagine (Asn) to Aspartic acid (Asp)  Peptide binding studies show A118G variant do not alter binding affinity to opioid peptides  The variant does bind β-endorphin more tightly than the common allele  Used as an active side for many pharmaceutical treatments for drug dependence

41 Kalsi et al, 2009

42 Summary of candidate gene studies  100s of genes encoding for receptors, neurotransmitters and transporters in several different systems have been tested  Results have been generally inconclusive  Sample sizes have been small  Most studies test diagnostic criteria rather than narrower, more specific phenotype  Results from drug metabolism genes have been robust

43 Neurotransmitters and clinical treatments

44 Naltrexone  Agonists/antagonists for opioid, GABA, serotonin and DA systems used as pharmaceutical compounds  Naltrexone is an antagonist for the µ-opioid receptor  It is a commonly used treatment for alcohol dependence  The variant A118G affects treatment response; alcohol dependent individuals with G allele showed lower relapse rate, reduced drinking and increased abstinence


46 Sturgess et al, 2011 Pharmacogenetic studies in alcohol dependence

47 Methadone  Was synthesized for analgesia and targets the opioid system; is an agonist for the µ-opioid receptor, just like heroin, but has a longer half-life  Prevents craving, withdrawal and is designed to block the receptor  The polymorphism A118G influences response  Highly variable individual response, influenced by cytochrome P genes  Response may also be affected by DRD2 polymorphisms; common allele of 957C>T (CC genotype) higher in non-responders

48 Sturgess et al, 2011

49 Acamprosate  Mostly used to treat alcohol-dependence  Acts as antagonist for NMDA receptors and agonist for GABA receptors  Helps to ameliorate withdrawal symptoms and affects processes related to reward  Works best when complemented by CBT

50 Summary 1. Current treatments have limited efficacy 2. Highly variable individual response 3. Need to have better understanding of mechanisms and hence treatments


52 Mechanisms....


54 Rodd et al, 2007 Wang et al, 2011

55 And finally...  Genetics has revealed heterogeneity of drug dependence and recovery  There is limited efficacy of most treatments (yes, again probably due to genetics)  A systems approach will help to resolve mechanisms  But there is more...epigenetics could play a role  And the environment...

56 Useful references 1. Sturgess JE, George TP et al (2011) Pharmacogenetics of alcohol, nicotine and drug addiction treatments. Addiction Biol; 16, 357-376 2. Khokhar JY, Ferguson CS et al (2010) Pharmacogenetics of drug dependence: role of gene variations in susceptibility and treatment. Ann Rev Pharmacol Toxicol; 50, 39-61 3. Agrawal A, Verweij KJH et al (2012) The genetics of addiction – a translational perspective. Transl Psychiatry, July 17 4. Arias AJ and Sewell RA (2012) Pharmacogenetically driven treatments for alcoholism: are we there yet? CNS Drugs; 26(6), 461-476 5. Wang J, Yuan W and Li MD (2011) Genes and pathways co-associated with the exposure to multiple drugs of abuse, including alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine and/or nicotine: a review of proteomics analyses. Mol Neurobiol; 44, 269-286 6. Kalsi G, Prescott CA et al (2009) Unravelling the molecular mechanisms of alcohol dependence. Trends in Genet; 25(1), 49-55

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