Genome Wide Association Studies in Psychiatry

GWAS
IN
PSYCHIATRY
Presenter- Dr. Guru S
Chair person- Dr. Sanjeev Jain
1
SEMINAR PRESENTATION
SNP chip
Department of Psychiatry
NIMHANS, Bangalore 12 Dec 2013

Outline of Topic
 Overview on GWAS.
 History of G W A Studies.
 GWAS and Psychiatry.
 Network Analysis.
 Implication of GWAS.
 Conclusion.
 Future direction.
2 Department of Psychiatry
NIMHANS, Bangalore

Overview on GWAS
 Normal human Cells –
 23 chromosomes.
 ≥ 3.2 Billion Base Pairs.
 Identity: 99.9 %
 Variable: 0.1 %
 Less than 2 percent of
the genome-20000
Genes.
 DNA→ RNA→ protein
NIMHANS, Bangalore3

Overview on GWAS
 Gene - Unit of heredity.
- Segment of DNA encoding a protein.
 Allele : One of two or more versions of a genetic
sequence at a particular location in the genome.
 Heritability- Proportion of phenotypic variance
(disease, trait) attributable to genetic variance.
Psychiatric GWAS Consortium
Coordinating Committee
4
NIMHANS, Bangalore

Single Nucleotide Polymorphisms (S N P)
NIMHANS, Bangalore
•SNP – It a Specific position
(among 3.2 billion in the genome)
where chromosomes carry
different nucleic acids.
•11 to 15 million SNPs with
frequency ≥ 1%.
•The HapMap Project catalogues
approximately 4 million.
5

SNP Continued…
Common SNPs :
 ≥ 5 % frequency.
 10 million in the genome.
 2.8 million on the current HapMap Project.
 These SNPs are targeted by GWAS.
Rare variants (rare SNPs) :
 <1% frequency
 Rarer SNPs in protein-coding regions tend to be
more harmful. Psychiatric GWAS Consortium
NIMHANS, Bangalore

Copy number variation (CNV)
NIMHANS, Bangalore
C N V : Chromosomal
segment where DNA has
been deleted or duplicated.
Other structural variants
include inversions and
translocations.
7

Complex diseases
 Most Psychiatric diseases are do not follow
simple Mendelian inheritance patterns.
 Etiological complexity
may be due to many factors.
- Incomplete penetrance.
- Locus heterogeneity.
- Polygenic inheritance.
- Environmental factors. Psychiatric GWAS Consortium
8
NIMHANS, Bangalore
Complex diseases : Many Causes = many causal pathways !

How to explore the pathogenesis of
the complex disease?
The Human
Genome
Project (HGP)
Hap Map
Project
GWAS
-Launched in 2002.
- First phase (2005):
~1 million SNPs for 270
individuals from four populations
- Second phase (2007):
~3.1 million SNPs for 270
individuals from four populations
- Third phase (ongoing):
> 1 million SNPs for 1115
individuals across 11 populations
9
NIMHANS, Bangalore

What is Genome-Wide Association Study
(GWAS)?
 It is an approach to identify common genetic
variations associated with a disease / Traits.
 It is based on common disease and common
variant (CDCV) hypothesis.
 It will detect common genetic variants, including
Single-Nucleotide Polymorphism (SNP) and
Copy Number Variation (CNV).
10
NIMHANS, Bangalore

GWAS
 Non-candidate-gene-driven study.
 Used to determine the genetic basis of diseases.
 GWAS is a well-known approach to identify the
susceptibility genes or loci for a complex disease /
polygenic disease.
11
NIMHANS, Bangalore

GWAS Method
Department Presentation
NIMHANS, Bangalore12

Phenotype - Well-defined, adequately heritable disorder
(e.g., schizophrenia) or traits.
Sample type -
1) Case/control type –
2) Family based -
Sample size - Actual frequency and
Genetic effect of risk variants.
SNPs - 300,000 to 1,000,000 common SNPs.
Match case/ Control for ancestry ; apply statistical
correction for population differences.
13
NIMHANS, Bangalore

Two types of Association studies
Case – Control
Adv :
More powerful
Dis adv:
Population stratification.
Limited by case /control
definition.
Family Based
Adv :
Population stratification
not a problem.
Dis adv:
Less powerful.
Hard to collect parents
for some phenotypes.
NIMHANS, Bangalore

ADHD
and
GWAS
15
NIMHANS, Bangalore

GWAS (SNP) and ADHD
Study Year Type Sample Size Promising Candidate Genes
Lesch et al 2008 Case-control 343/250 CDH13, ASTN2, CTNNA2 and KALRN
Neale et al 2010 Case-control 896/2,455 PRKG1, FLNC, TCERG1L, PPM1H,
NXPH1, PPM1H, CDH13, HK1, and
HKDC1
Hinney et al 2011 Case-control 495/1,300 GRM5
Stergiakouli et al 2012 Case-control 727/5,081 CHRNA7
Neale et al 2008 Family 909 trios XKR4, and FAM190A
Lasky-Su et al 2008 Family 930 trios SLC9A9
Mick et al 2010 Family 735 trios SLC9A9
Neale et al 2010 Combined 2,064 trios
and 896/2,455
CHMP7, TNFRSF10D, TNFRSF10A,
and LOXL2
(Kathryn Ashmore et al. 2013)
16
NIMHANS, Bangalore

GWAS (CNV) and ADHD
Study Type Sample Results
Michael
O’Donovan et al,
Anita Thapar et al,
2012
Case /
Control
727 / 5,081 Large, rare CNVs were significantly
more common in case subjects than
comparison subjects
Nigel M et al, 2012 Case /
Control
460/ 1,102 Large, rare CNVs - duplications
at 15q13.3
(Kathryn Ashmore et al 2013)
NIMHANS, Bangalore

GWAS
and
Autism spectrum disorder
18
NIMHANS, Bangalore

GWAS and Autism spectrum disorder
19
NIMHANS, Bangalore

GWAS and Autism
 In Autism –
Three studies have reported large , high
Penetrance deletion on chromosome on
16p11.2.
 Common SNP have yet to reported in autism
GWAS.
20
NIMHANS, Bangalore

Anxiety disorders
and
GWAS
21
NIMHANS, Bangalore

Genome-Wide Association Study on Anxiety-
Related Behaviours in Childhood
G W A S Design Population
/ Sample
S N P
Maciej Trzaskowski et
al ,2013
Twins Early Development
Study (TEDS)
United Kingdom / 2810 700,000
Results
No SNP associations met the demanding criterion of genome-wide
significance.
22
NIMHANS, Bangalore

Alzheimer’s Disease
and
GWAS
23
NIMHANS, Bangalore

GWAS and Alzheimer's disease
Lars bertram et al ,2009
24
NIMHANS, Bangalore

Results
In Alzheimer's disease , GWAS results
consistent with APO E locus SNP
and
Less consistent for other SNP locus
like BCR, ACAN, GAB2.
GWAS and Alzheimer's disease
(Lars bertram et al ,2009)
25
NIMHANS, Bangalore

ApoE4 allele
AD with co-morbid DM - (0.35)
AD without DM - (0.25),
Non AD with DM - (0.13),
Non AD without co-morbid DM - (0.12),
Conclusion. There is a significant association
between AD with co-morbid DM and ApoE4
genotype.
(Lakshmi Narayanan Kota et al,2012)
26
NIMHANS, Bangalore

ApoE4 allele
 The ApoE4 allele was significantly more
prevalent in dementia compared to other allele.
 ApoE4 carrier status did not differ between the
other dementia.
 Cognitive and functional deficits were not
correlated to the presence ApoE4 polymorphism
in the dementia group.
(Srikala Bharath et al, 2011)
27
NIMHANS, Bangalore

Alzheimer’s Disease and C N V
Results
ATXN1, HLA-DPB1, RELN, DOPEY2, GSTT1, CHRFAM7A, ERBB4, NRXN1) and
identified a new gene (IMMP2L)
(Swaminathan et al, 2012)
28
NIMHANS, Bangalore

Bipolar Disorder
and
GWAS
29
NIMHANS, Bangalore

Genome wide Association Studies (SNP) and
Bipolar disease
G W A S Design Sample Population Results
Wellcome
Trust
Consortium.
Case / Control 1,868/
2,938
(United Kingdom) NO Significant
finding…
Sklar et al. Case / Control
Consortium
1,461/
2,008
United States,
United Kingdom,
STEP-BD
NO Significant
finding…
Ferreira et al. Case / Control
Consortium
4,387/
6,209
Well come Trust
Case Control
Consortium
ANK3 gene (odds
ratio=1.45);
frequency of the
associated allele in
comparison
subjects=0.053)
30
NIMHANS, Bangalore

 In bipolar disorder, three individual studies by
each, failed to detect significant association,
 The three data sets combined produced a
p value of 9.1 , 10 –9 for ankyrin-G (ANK3),
 The product of which links membrane proteins,
such as voltage dependent sodium channels, to
the axonal cytoskeleton.
31
NIMHANS, Bangalore

Schizophrenia
And
GWAS
32
NIMHANS, Bangalore

GWAS (SNP) and Schizophrenia
G W A S Design Sample Population Results
Lencz et al. Case / Control
Consortium
178/144 United States No significant
finding
Sullivan et al. Case / Control
Consortium
738/733 United States No significant
finding
O’Donovan et
al
Case / Control
Consortium
479/
2,937
(United Kingdom) +
(1,865 Wellcome
Trust)
No significant
finding
Case Control
Consortium
Case Control
Consortium
6,829 /
9,897
(United Kingdom,
Europe, United States,
Australia, Japan,
Israel)
Results -
ZNF804A gene
(odds
ratio=1.12;)
33
NIMHANS, Bangalore

Schizophrenia and related neuro
cognitive measures were detected with
two SNPs from the NRG1 promoter
region( neuroglin -1) in a north Indian
cohort study.
(Prachi Kukshal et al 2013)
34
NIMHANS, Bangalore

GWAS (CNV) and Schizophrenia
 Deletions in chromosomes 1q21.1, 15q13.3, and
22q11.21,
 Duplications in 16p11.2, and
 Exon-disrupting deletions in NRXN1.
(Levinson et al, 2011)
35
NIMHANS, Bangalore

Two large studies done in 2008 by stefansson et al
and stone J L et al.
Two rare deletions that are significantly associated
with schizophrenia on chromosomes
1q21.1 (0.2% of case subjects) and
15q13.3 (0.3% of case subjects).
A large (3Mb) deletion at chromosome 22q11.21 has
long been known as a significant risk factor for
schizophrenia.
36
NIMHANS, Bangalore
(Karayiorgou et al., 1995)

Approximately 25% of 22q11.2 deletion carriers
manifest symptoms of psychosis.
Recent genome-wide studies have found strong
evidence of association for other loci including
Deletions at chr1q21.1
Deletions at chr3q29
Duplications of chr16p11.2
Deletions at chr15q13.3
Exonic deletions at chr2p16.3 (NRXN1) and
Duplications at chr7q36.3 (VIPR2). (Malhotra et al , 2013)
37
NIMHANS, Bangalore

Depression
and
GWAS
38
NIMHANS, Bangalore

GWAS meta-analysis and Depression
( Hetteme et al, 2010 )
39
NIMHANS, Bangalore

Depression and CNV(GWAS)
Case control studies
 The results of case-control studies have been
inconsistent.
 However, very few of the CNVs that contribute to risk
for schizophrenia are also associated with bipolar
disorder.
 The possible exceptions.
Micro duplications of 16p11.2
Microdeletions of 3q29
(McCarthy et al., 2009 , Clayton-Smith et al.,
2010; Malhotra et al., 2011)
40
NIMHANS, Bangalore

Family-based studies in DEPRESSION
(GWAS – CNV)
- Frequencies of de novo CNVs were significantly higher
(4.3%) in bipolar disorder as compared with healthy
individuals (0.09%).
- Early age of onset (< 18 yrs) associated with higher
frequency of de novo CNVs mutation - (5.6%)
- Early-onset bipolar disorder was consistent with a inherited
or de novo CNVs higher rate than late onset bipolar disorder.
(Malhotra et al., 2011; Priebe et al., 2011)
- Late-onset bipolar disorder was consistent with a
multifactorial aetiology.
41
NIMHANS, Bangalore
(Grigoroiu-Serbanescu et al. 2001)

SUICIDE
and
GWAS
42
NIMHANS, Bangalore

GWAS and Completed Suicide
Meta-analysis and forest plot of the Val66Met
polymorphism and suicide.
43
NIMHANS, Bangalore

44
NIMHANS, Bangalore

Completed Suicide and GWAS
 A single nucleotide polymorphism (SNP) (Val66Met,
rs6265 SNP) was reported to be associated with
suicidal behaviour in depressive disorder.
( W. Ratta - apha et al, 2013.)
 ( Val66met, rs6265 SNP ) will code for Brain-
Derived Neurotrophic Factor (BDNF) plays a crucial
role in brain plasticity and neuronal development
(Duman et al , 2002).
45
NIMHANS, Bangalore

Addiction
and
GWAS
46
NIMHANS, Bangalore

GWAS and Alcohol Dependence syndrome
G W A S Design Sample Population SNP Results
Biernacka
et al
Case /
Control
(both sex are
included)
808 /
1248
Minnesota
(USA)
43 SNPs ADH1C
gene show
assoiation
with ADS
47
NIMHANS, Bangalore

GWAS and Alcohol Dependence syndrome
48
NIMHANS, Bangalore

ADDICTION and SNP
Cindy L ehlers et al
49
NIMHANS, Bangalore

GWAS and Addiction
Cindy L ehlers et al
50
NIMHANS, Bangalore

Pharmacogenomics
and
GWAS
51
NIMHANS, Bangalore

G W A S Design Sample Population SNP Results
GENDEP
project
Compara
tive
On treatment
Escitalopram /
Nortryptaline
394/312 -------
-----
Treatment response to
Escitalopram was
predicted by IL-11
GWAS and Pharmaco genomics

GWAS and Pharmaco- genomics
Pharmaco - genetics treatment in Epilepsy53

GWAS Discoveries over Time
54
NIMHANS, Bangalore

Progress in Genotype Technology
1 10 102 103 104 105 106
Nb of
SNPs
Costpergenotype(Cents,USD)
10
1
102
ABI
TaqMan
ABI
SNPlex Illumina
Golden Gate
Illumina
Infinium/Sentrix
Affymetrix
100K/500K
Perlegen
Affymetrix
MegAllele
2001 2005
Affymetrix
10K
Courtesy S. Chanock, NCI
© Francis Collins, 2008
Department Presentation
NIMHANS, Bangalore
55

Complex network
And
Pathway analysis
NIMHANS, Bangalore

Coherence and SNPs, CNVs
No coherence
No meaningful
connections are
observed between the
genes.
Schematic gene network analysis of risk genes found by replicated GWAS
KS Kendler et al, 201357
NIMHANS, Bangalore

Network of meaningful
connections are
observed between small
numbers of genes.
Minimal coherence
NIMHANS, Bangalore

Moderate Coherence
Meaningful connections
are observed between
two large groups of
genes.
But
These networks are not
inter-connected.
NIMHANS, Bangalore

High Coherence
Meaningful connections
are observed between
nearly all the genes,
Which largely combined
into a single large
network.
NIMHANS, Bangalore

Systems Genetics Strategies
61
NIMHANS, Bangalore
Systems genetics studies
have provided the first
global view of the
molecular architecture of
complex traits and are
useful for the identification
of genes, pathways and
networks that underlie
common human diseases.
( Mete Civelek et al. 2013)

The relationship between such modules and clinical traits can
then be examined by correlating either the average gene
expression levels or principal components in a module with the
trait
Systems Genetics Strategies
( Mete Civelek et al. 2013)

INSIGHTS INTO THE ETIOLOGY OF PSYCHIATRIC
DISORDERS FROM GWAS FINDINGS
Biochemical – simple and direct
networks of genes.
Ex- Neuron dysfunction can be
caused by-
Dysfunctional receptors,
Down regulated second messenger
systems
Deficient transport mechanisms.
2. Cellular - Synaptic functioning the
pathways from genes will be more
complex in nature..
63 KS Kendler et al, 2013
NIMHANS, Bangalore

INSIGHTS INTO THE ETIOLOGY OF PSYCHIATRIC
DISORDERS FROM GWAS FINDINGS
3) Neuronal network- Pathways
from genes to disorder will be
further complicated with more
intervening steps and multiple
interaction.
4) Brain circuit - Very difficult to
‘see’ coherent gene networks
because of the numerous
intervening steps and
interactions that occur
between gene function and
casual effects.
64
NIMHANS, Bangalore

Cross disorder analysis
Between schizophrenia and BPAD
65
Michael J.Owen et al, 2007
NIMHANS, Bangalore

Rare CNVs and Phenotypic expressions
Anne S et al, 2010
66
NIMHANS, Bangalore

Variable Expressivity of CNV Genotype
 Genes Don’t Code for Behaviours.
 Micro duplications of 1q21.1 include autism or
schizophrenia.
 Micro duplications of 16p11.2 are associated with
autism, schizophrenia or bipolar disorder.
 16p11.2 CNV region in zebra fish, human and
mouse influences brain size. (Nicholas Katsanis et al)
( Malhotra et al., 2011,)
67
NIMHANS, Bangalore

Venn diagram of primary candidate genes associated with
four disorders: blue (ASD), green (SZ), yellow (ADHD) and
red (XLID)
AS Cristino et al,2013
68
NIMHANS, Bangalore

Graphical representation of the 13 most populated protein
modules of the AXAS–PPI network.
69
NIMHANS, Bangalore

 The AXAS–PPI network indicates that there are up
to 4000 genes that may contribute to
neurodevelopmental and neuropsychiatric disorders.
 Genes associated with ASD, XLID, ADHD and SZ
are mainly distributed in 13 modules.
 Proteins are predominantly involved in the
regulation of transcription, synaptic transmission,
cell–cell communication, intracellular signalling
pathways, cell cycle, metabolic processes and
nervous system development.
70
NIMHANS, Bangalore

Emerging Genetic Evidence on Complex Brain
Disorders
A) Multiple subunits of voltage-
gated calcium channels are
among the genome’s strongest
associations to schizophrenia
and bipolar disorder.
B) Genes encoding the
postsynaptic components of
excitatory synapses are
implicated by both rare and
common variants in
schizophrenia.
Steven A. McCarroll et al, 2013
71
NIMHANS, Bangalore

Current Association
Study Challenges
NIMHANS, Bangalore

Current Association Study Challenge
DEFINING CASES AND CONTROL
-Biological mechanisms underlying psychiatric illness.
-Need of high number of cases.
-We are not able define proper control.
- High rates of false positive findings.
GOLD Standard for association studies.
- Replications of Results in different centre with different ethnic
group.
- High level associations traits and SNPs.
73
NIMHANS, Bangalore

Conclusion and summary
 Results have been remarkably consistent with
expectations .
 Common SNP associations have been discovered
for many common mental disorders.
 GWAS will be a powerful venue for such
investigations, particularly by enabling the integrated
analysis of SNPs and CNVs.
74
NIMHANS, Bangalore

Future direction
 GWAS methods should be applied systematically to
major psychiatric disorders in large samples.
 We are entering a new era now with more mature
molecular and statistical methods.
 Systems genetics approaches, Network and pathway
analyses, phenome-wide association studies
(PheWASs) are proceeding in psychiatry and may
reveal coherent biological processes contributing to
illnesses but the evidence is limited to date.
75
NIMHANS, Bangalore

Future direction
 It will be very useful for disease diagnosis,
prediction, risk evaluation, prevention, and
treatment.
 The ultimate goals are to develop new drug for
treatment and finally make personalized medicine
come true.
76
NIMHANS, Bangalore

Future Direction
GENE
PUBLIC
HEALTH
• Therapeutic target
• Prevention strategy
• Risk stratification
TRAIT
77
© Helen Hobbs 2009
NIMHANS, Bangalore

Thank You

Genome Wide Association Studies in Psychiatry

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