Genetics and epigenetics of ADHD and comorbid conditions

Genetics and epigenetics of attention-
deficit/hyperactivity disorder and comorbid
conditions
Anu Shivalikanjli
April 06, 2020
Profs. Bru Cormand and Stephen Faraone

HORIZON
2020
This project has received funding from the European Union’s Horizon 2020 research and innovation
programme under the Marie Sklodowska-Curie grant agreement No 643051.
“Mastering skills in the training network for attention deficit
hyperactivity and autism spectrum disorders”

Beneficiaries
Partners
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant
agreement No 643051.

WP 2
WP 3
WP 4
PREVALENCE AND DEFINITION
GENETICS AND EPIGENETICS
MODEL SYSTEMS
PREDICTION AND TREATMENT
WP 1
T
R
A
I
N
I
N
G
WP 5
I
M
P
A
C
T
WP 6

WP 2 GENETICS AND EPIGENETICS
Common and rare
genetic variation
in ADHD and ASD
Epigenetics:
methylation,
miRNAs Parent-of-origin
effects in
epigenetics
Interplay
genome-
microbiome

Completed stay in UB
Setting up the data, high-
computing cluster accounts
and pipelines
Joined the lab
Bioinformatic analysis
Late 2015
JULY 2017- mid 2018
2016
2018 2019
PUblications
2020
Thesis
2021
India

10
1
Background
Clinical Presentation of ADHD
Three core
symptoms of
ADHD

12 years
3
Background
Epidemiology
3.4% adults
Persistence

Neurobiology of ADHD
13
Background
Mid- Sagittal view
4
Executive
functioning
Attention
Reward
Outside left hemisphere view

Anatomical brain changes in ADHD
14
Background
5

Genetic models
15
Mendelian Model Complex Model
Variants
Disease type
Genes
Size of cohort
Whole exome/whole genome GWAS
Technology
Family Populations
6
Background

Genetic approaches
16
Background
7

General heritability
17
Heritability
due to GWS
SNPs <5%
Global
heritability
estimates of
SNPs ~20%
SNP-based heritability
>70% heritability in ADHD
Background
8

Family
burden
Comorbidities
ADHD
Core
symptoms
Clinical condition
Clinical condition Clinical condition
Comorbid disorders
e.g. Intellectual disability
Anxiety disorders
Tic disorders
ODD, CD
Comorbid disorders
Anxiety disorders
Tic disorders
Bipolar disorder
Depression
ODD, CD
Comorbid disorders
Anxiety disorders
Tic disorders
Bipolar disorder
Depression
Substance use disorder
Personality disorder
ADHD
Core
symptoms
ADHD
Core
symptoms
Adolescence
Childhood Adulthood
Background
9

Cocaine dependence
19
5.2% of adults have tried cocaine
Heritability
20% will develop addiction
Background
10

Cocaine dependence
Background
Reward Deficit
& Stress Surfeit
Executive
function deficits
Incentive
Salience
Background
11

ADHD and Cocaine dependence
No ADHD
No cocaine
dependence
ADHD ADHD + cocaine
dependence
Cognitive impulsivity
Response inhibition
Self-medication
Impulsivity
Risk-taking
ADHD
Cocaine dependence
Conduct disorder
Oppositional defiant
Drug/alcohol
exposure in
womb
[Endo-] phenotypes
(cognitive functioning, impulsivity,
dysregulations in neurotransmission)
Genetic factors
Background
12

Implicated Genes and Biomarkers
22
Probably not
useful
biomarkers
Useful biomarkers
ADHD Addiction
Background
13

Epigenetics
Stable changes in
gene expression
Gene function and
brain structure
15
Background

DNA Methylation
25
16
Background

▹ Identification of
genetic variation that
influences brain
methylation in ADHD
▹ Hypothesis-free +
hypothesis driven
▹ Identification of
common variation in
microRNA genes
that contribute to
ADHD
▹ Hypothesis-free +
hypothesis driven
▹ Genome-wide
association meta-
analysis of cocaine-
dependence: Shared
genetics with comorbid
conditions
▹ Hypothesis-free
28
1 3
2
19
Objectives

 Identification of
genetic variation
that influences brain
methylation in
ADHD
common variation
in microRNA
genes that
contribute to
ADHD
 Genome-wide
association meta-
analysis of
cocaine-
dependence:
Shared genetics
with comorbid
conditions
30
1 3
2
20
Results

Selection of allele-specific methylation (ASM)
SNPs
31
Results – Chapter 1: Identification of genetic variation that influences brain methylation in ADHD
21

32
Association results obtained
for ASM-variants in ADHD
3,896 tagSNPs
22

23
Functional follow-up of associated ASM-
variants/CpG
SNPs as
eQTLs for
genes
Location of CpGs
in promoter
regions
23

34
Functional follow-up of associated ASM-variants and
CpGs
Location of CpGs in
promoter regions
24
24

CpGs
Location of CpGs in
promoter regions
ARTN C2orf82 NEUROD6 PIDD1 RPLP2 GAL
25

36
CpGs
SNPs as eQTLs of
the same genes
36
26

37
CpGs
SNPs as eQTLs of
the same genes
37
27

cg22930187
and
cg06207804
38
Artemin
• Ligand of GDNF family
• survival of sensory and sympathetic peripheral neurons
• Neuron excitability
38
28

39
cg1304759
6
Same direction
C2orf82
• Proteoglycan transmembrane protein
• Highly expressed in brain tissues
39
29

40
cg2022591
5
P53-Induced
Death
Domain
Protein 1
• Cell life regulator gene
40
30

41
Correlation with
methylation levels
60 ASM SNPs
cg22930187
cg06207804
cg13047596 cg11554507 cg20225915 cg04464446
3 SNPs 45 SNPs 3 SNP 7 SNPs 2 SNPs
ARTN C2orf82 NEUROD6 PIDD1 GAL
RPLP2
Within promoter
regions of genes
eQTLs ARTN C2orf82 NEUROD6 PIDD1 GAL
RPLP2
Correlation with
brain volumes
↑ NAc ↑ CN ↓NAc ↓ CN
↓T
41
31

PGC ADHD GWAS meta-analysis is enriched in ASM-SNPs
Better OR for SNPs with low (better) p-values.
Significance
Threshold
N SNPs N ASM SNPs p-value OR
5.00E-08 303 6 1.70-03 4.92
5.00E-07 945 8 4.30E-02 2.08
5.00E-06 2,122 15 3.15E-02 1.74
5.00E-05 6,970 35 1.31E-01 1.23
5.00E-04 25,288 139 4.58E-04 1.35
5.00E-03 115,681 527 6.94E-03 1.12
5.00E-02 651,772 2790 5.54-03 1.05
32

43
Lookup
43
33
IF: 5.2

genetic variation
methylation in
ADHD
common variation
in microRNA
genes that
contribute to
ADHD
 Genome-wide
association meta-
analysis of
cocaine-
dependence:
Shared genetics
with comorbid
conditions
44
Results
1 3
2
34

1355
Intragenic
Clustered
Singleton
miRNAs
are <10Kb
apart
1761
autosomal
miRNA
genes
406  135
879
Exonic
Clustered
Clustered
Singleton
Intronic Host
gene
Selection of
miRNA
regions
45
Results - Chapter 2: Role of common variation in micro-RNA genes in ADHD
35

Exonic
Clustered
Clustered
Singleton
1355
Intragenic
Clustered
Singleton
1761
autosomal
miRNA
genes
406  135
879
10kb
10kb 5kb
5kb
10kb
Host
gene
Intronic
10kb
Selection of regulatory
elements for miRNA
genes
miRNAs
are
<10Kb
apart
36

47
Association results
obtained for miRNA
common variants in
ADHD
~22K tagSNPs
19 tagSNPs
Overcoming 5% FDR
~17K tagSNPs
Retrieved p-values from summary statistics
12 Associated miRNAs
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
Chr 1 Chr 3 Chr 7 Chr 9 Chr 16
miR-4655 miR-6506
miR-4271 miR-5193
5’ 3’
phg
5’
5’
5’ 5’ 5’ 5’ 5’ 5’
phg
3’ 5’
Variant
location
5’: Upstream of miRNA gene
3’ Downstream of miRNA gene
phg: Promoter region of host gene
5’
miR-6872
5’
5’
5’
3’
1761 miRNAs 12 SNPs per region
47
37

48
Follow-up of significantly associated miRNAs
Brain
expression
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Validated
target genes
Network
analysis
• BrainSpan Atlas
• miRMine
• miRIAD
• Spatio-temporal miRNA
profiles in developing
human brain (Ziats and
Rennert)
• Ingenuity Pathway Analysis
o TarBase
o TargetScan Human
o miRecords
48
38

49
Brain
expression
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Validated
target genes
Network
analysis
• BrainSpan Atlas
• miRMine
• miRIAD
Rennert)
o TarBase
o TargetScan Human
o miRecords
49
38

50
Brain
expression
Cerebellum
Cerebellar
cortex
Cerebellar
cortex
Primary
somato-
sensory
cortex
Primary
somato-
sensory
cortex
Ventral
parietal
cortex
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Primary
somato-
sensory
cortex
Primary
visual
cortex
Cerebellum
Whole brain Whole brain
Cerebellum
Whole brain
Cerebellum
Whole brain
Cerebellum
Whole brain
Cerebellum
Whole brain Whole brain
Data
unavailable
Differentially
expressed
between PFC
and
cerebellum –
late childhood
development
50
39

51
Brain
expression
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Validated
target genes
Network
analysis
• BrainSpan Atlas
• miRMine
• miRIAD
Rennert)
o TarBase
o TargetScan Human
o miRecords
51
39

52
18
9 1
Follow-up of significantly associated miRNAs 12 Associated miRNAs
miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Validated
target
genes
40

53
18
9 1
Follow-up of significantly associated miRNAs 12 Associated miRNAs
miR-7-1
miR-3666 miR-1273h
Chr 7 Chr 9 Chr 16
Validated
target
genes
41
41

54
Functions of validated target genes
 Lithium-responsive BIP
 Brain thalamus volumes
EGFR
SNCA
 Cognitive empathy
 Depressive episodes in BIP
EIF4E
 Parkinson disease
MKNK1  SCZ
SLC17A7
(VGLUT1)
 Brain-specific manner
 Mediates uptake of gluatamate into
synaptic vesicles
 Cognitive decline, SCZ, MDD and
bipolar disorder
TAC1
 Brain region volumes
 Intracranial volume
 Subcortical volumes
MEOX2
 Encodes neuropeptides
– neurotransmitters and
induces behavioural
response
 Risk-taking
 Feeling nervous traits
Moderate
expression in
caudate, NAc,
and putamen
miR-7-1
miR-3666
54
42

55
Brain
expression
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Validated
target genes
Network
analysis
• BrainSpan Atlas
• miRMine
• miRIAD
Rennert)
o TarBase
o TargetScan Human
o miRecords
o Using all miRNAs as
input – focal miRNAs
43

56
miR-
5193
IL9
miR-7-1-
3p
miR-
3135a
miR-7a-5p
miR-610
miR-6734-3p
miR-6735-3p
miR-1273h-
3p
miR-
4271
UTS2
R
GPR6
5
GPR174
ADGRA
3
ADGRE2
RGR
ADRB
2
GPR26
XCR1
ADRA2A
HTR1D
YWHAG
Adrenorecept
or
Beta arrestin
PTGER1
GPR7
8
OR10H
2
GPR161
ADGRF
4
CCKA
R
HTR4
GPR25
Network analysis
ADGRG7
C3AR1
ADGRG4
44

57
CCKA
R
 SCZ
YWHAG
 Moderate language laterization
 Superior frontal grey matter
volumes
 SCZ risk allele
ADGRE2  MDD
GPR26
 Encodes a protein distantly related to Serotonin
 Expressed exclusively in brain tissue
45

58
Brain
expression
miR-6734 miR-6735 miR-6079 miR-7-1
miR-3135a miR-3666 miR-1273h
miR-4655 miR-6506
miR-4271 miR-5193 miR-6872
Data
unavailable
Validated
target
genes
Orthologs
Network
analysis
46

59
Overlap of associated miRNA regions and GWS-ADHD loci
Demontis et
al., 2019
47

60
Overlap of associated miRNA regions and GWS-ADHD loci
Demontis et
al., 2019
48

61
Lookup
49

genetic variation
methylation in
ADHD
common variation
in microRNA
genes that
contribute to
ADHD
 Genome-wide
association meta-
analysis of
cocaine-
dependence:
Shared genetics
with comorbid
conditions
62
Results
1 3
2
50

63
Results – Chapter 3: GWA meta-analysis of cocaine dependence
Sample sets and pipeline
N cases = 2,085
N controls=
4,293
EUR
Sample 2 Sample 3 Sample 4
468
N controls
609 504 504
N cases
1284 410 1190 1409
Illumina HumanOmni1-Quad_v1-0_B
Illumina ILMN_Human-1 Illumina HumanOmni1-Quad_v1-0_B
Illumina Human660Q-Quad_v1_A
QC PCA Imputation
SNP-based analysis
Sample 1
RICOPILI - Rapid Imputation and COmputational PIpeLIne
Gene-based analysis
METAL
MAGMA
9,290,362 markers
GWAS
51

64
Results from the GWAS meta-
analysis
QQ plot
SNP-based
analysis 23 lead SNPs = 22 genomic risk loci =
112 genes
Suggestive
Association
s
SNP to
Gene
447 - brain eQTLs - 12 genes
BTN3A2, HIST1H2AK, ZSCAN31, PRSS16,
ZNF184
Chromosom
e 6
Schizophrenia-associated
2 lead SNPs
GWAS P = 3.1e-06 and 3.4e-06
458 nominally associated SNPs
77 genes
52

65
Circo-plot of
chromosome
6 genomic
risk locus
0.8
0.6
0.
4
r2 for the
SNPs in
the GRL
<=0.2
Top SNPs in the risk locus
Chromosome ring
Chromatin interactions
eQTLs
Manhattan plot
SNPs P < 0.05
Risk locus
53

66
Gene-based
analysis
SNP-based
analysis
10% FDR
threshold
54

67
Gene-based
analysis
 Enriched in immune system and
histone-related genes
 Five SNPs nominally associated with
cocaine dependence (P < 1e-04) and
been associated with SCZ and BIP: the
risk allele is the same in all studies.
 rs17693963 - reported in five studies -
brain eQTL for: PRSS16, ZSCAN9,
ZNF184 and ZSCAN31
 Top differentially expressed genes
HIST1H2BD, HIST1H2BC, HIST1H2BH,
HIST1H2BG and HIST1H4K
- lymphoblastoid cell lines in SCZ
10% FDR threshold
55

*nominal result
2.17
23.63
68
Polygenic architecture of cocaine dependence
Partitioned heritability analysis by functional annotations on LD Score Regression (LDSC)
55

Cocaine dependence and
shared genetic factors with
comorbid conditions
(including ADHD)
56

Cocaine dependence and shared genetic factors with comorbid
conditions
Error bars: 95% confidence limits
Significance threshold: P < 7.1e-03
Genetic correlation based on LD Score (LDSC) regression
analysis
 Cocaine dependence shares genetic risk factors with several comorbid traits
-> Horizontal (biological) pleiotropy
57

Cocaine dependence and shared genetic factors with comorbid
conditions
Best fit results from Polygenic Risk Score (PRS) analysis for each tested
phenotype
Values: p-value for significance for the most predictive models
Significance threshold: P < 5.7e-04
58

72
Lookup
 The largest GWAS meta-analysis on cocaine dependence in European ancestry individuals
 Identified susceptibility regions on chromosome 6 – HIST1H2BD
IF 4.3
59

▹ Common genetic risk variants for ADHD
identified in a previous genome-wide
association study (GWAS) that included
20,000 cases and 35,000 controls are
enriched in SNPs that correlate with levels
of DNA methylation.
▹ Eight Allele-Specific Methylation tagSNPs
are significantly associated with ADHD and
correlate with differential methylation at
six CpG sites in cis in different brain
areas.
▹ These six CpG sites are located at
possible promoter regions of six genes
expressed in brain: ARTN, C2orf82,
NEUROD6 , PIDD1, RPLP2 and GAL.
▹ For three of these six genes, SNPs
associated with ADHD and correlating
with methylation levels are eQTLs in
brain. Consistently, methylation and
gene expression show opposite
directions: ARTN and PIDD1 (reduced
methylation, increased expression),
C2orf82 (increased methylation,
reduced expression).
▹ ADHD risk alleles are associated with
increased brain expression of ARTN
and PIDD1 and with decreased brain
expression of C2orf82.
▹ SNPs in C2orf82 correlate with
changes in brain volumes.
▹ Our study highlights the ARTN,
C2orf82 and PIDD1 genes as potential
contributors to ADHD susceptibility.
74
Conclusions – Chapter 1
60

▹ We have performed a case-control
association study to investigate the
contribution to ADHD of common genetic
variation in 1,761 autosomal miRNAs
using pre-existing GWAS data from
20,000 cases and 35,000 controls.
▹ We have identified 19 significant
associations of SNPs with ADHD that
highlight 12 miRNA genes, all located
within protein-coding genes.
▹ The associated variants are located in
the putative regulatory regions of the
miRNA genes or in the promoter region of
the host protein-coding gene.
▹ The highlighted miRNAs are
expressed in different brain tissues,
specifically in cerebellum
▹ Three of the highlighted miRNAs -
miR-3666, miR-7-1 and miR-1273h -
have validated target mRNAs.
▹ Pathway analysis of ADHD-
associated miRNAs revealed two
biological pathways. One of the
pathways involves miRNA-mediated
regulation of serotonin receptor genes
and it is likely to be involved in
neurological functions and diseases.
75
60

▹ We have performed the largest
cocaine dependence GWAS meta-
analysis in individuals of European
ancestry, including 2,100 cases and
4,300 controls.
▹ Although the SNP-based analysis
revealed no genome-wide significant
associations with cocaine
dependence, probably due to limited
sample size, the gene-based analysis
identified the HIST1H2BD gene,
previously associated with
schizophrenia.
▹ The estimated SNP-based heritability
of cocaine dependence is
approximately 30%.
▹ A significant genetic correlation has
been observed between cocaine
dependence and ADHD,
schizophrenia, major depressive
disorder and risk-taking behaviour,
suggesting a shared genetic basis
across pathologies and traits.
▹ Polygenic risk score (PRS) analysis
shows that all the comorbid features
analysed (ADHD, schizophrenia,
major depressive disorder,
aggressiveness, antisocial personality
or risk-taking behaviour) can predict
cocaine dependence
76
60

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