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Genetic Association Studies and GWAS
October 16, 2015
Topics
• Study Design
• Potential Threats to validity:
- sample recruitment
- genotyping error
-errors in data analysis
- replication
- population structure
West Nile Virus Transmission Cycle
West Nile Outbreaks
• Israel - 1951-1954, 1957• France - 1962• South Africa - 1974• Romania – 1996• Italy 1998• Russia - 1999
1999 West Nile Virus Activity NYC1999 West Nile Virus Activity NYC
MosquitoesMosquitoes
BirdsBirds
HumansHumans
Clinical Syndromes
• 80% asymptomatic
• 20% “West Nile Fever”
• 1 in 20 of symptomatic patients develop neuroinvasive disease
- Meningitis
- Encephalitis
- Acute Flaccid Paralysis
• Apart from increased age, risk factors ill defined
Hypothesis
• WNV neuroinvasive disease is a consequence of genetic factors that result in increased WNV replication and subsequent pathology
Q. Why detect Genes associated with Disease ?
• Diagnosis
• Prognosis
• Therapeutics
• Basic Mechanisms of disease
Objectives
• To assess the association between immune response genotype sets and susceptibility to neuroinvasive disease
• To characterize the relationship between gene polymorphisms, protein function, and WNV infection
Q. What sort of evidence do you look for to see if the question is
worthwhile?
Is there evidence for a ‘familial’ effect?• Migration Studies
• Do immigrants have disease risk similar to their native population or to the new population?
• Migration Studies• Familial Aggregation studies
Disease Healthy
FH+ a b
FH- c d
Subjects are relatives Disease Healthy
Relative of a case a b
Relative of a control c d
OR = ad/bc > 1 ?
• Sibling relative risk: s
P(disease|sibling is affected)
P(disease)
• Familial aggregation if s > 1
Is there evidence for a ‘genetic’ effect?
• Familial correlations in phenotype?
• Heritability can be thought of as the similarity between related individuals that is due to shared genes.
• If trait is heritable, individuals who share genes should have higher correlation between trait values than individuals who do not share genes– Parent & offspring trait values should be correlated– Identical twins should be more correlated than siblings– Sibling values should be more correlated than cousins
Heritability – Familial CorrelationsP
heno
type
sim
ilarit
y (c
ovar
ianc
e)
Distant Relatives
2nd cousins
Cousins Sibs/DZ twins
MZ twins
Heritable Trait
Non-Heritable Trait
Ve
ry s
imila
rN
o s
imi la
ri ty
Calculating Heritability Of A Disease
• So if disease is genetically determined,MZ > DZ
concordance MZ twins > concordance DZ twins
MZ twins share 100% of the genome
DZ twins share 50% of the genome, on average
• Twin studies• One way to study heritability
note:
• Any variation in phenotype between MZ twins must be due to environmental variation
• Variation in phenotype among DZ twins due to environmental variation AND genetic variation (they don’t necessarily have the same genes)
Genetic Epidemiology Questions
Is there familial clustering? (Ycould be shared genes or
shared environments)
Is there evidence for a genetic effect?
(covariance structure may indicate gene vs environment)
Is there evidence for a particular genetic model?
(dominant, recessive, polygenic)
Where is the disease gene?
• Linkage • Association
How does this gene contribute to disease in the general population?
(variant frequency, risk magnitude, attributable risk, environmental interactions)
Epidemic of Polio in North America
• In North America, although sporadic epidemic disease occurred in the first half of the 20th century, by the 1950s epidemics of polio were widespread in North America
• Prior to introduction of
vaccination, it has been estimated that 600,000 cases of paralytic poliomyelitis occurred annually
Nathanson N. Amer J Epidemiol 2010;172: 1213-1229
Host Factors
• < 1% of individuals infected with poliovirus developed paralytic polio in pre-vaccine era
• In families with a clinical case of poliomyelitis, ratio of inapparent to apparent infection between 3:1 and 7:1 versus 100:1 in the general population
Other Evidence for Genetic Predisposition
Herndon and Jennings. AJHG 1951:3:17-46
Genetic Epidemiology Process - Methods
Familial clustering? – Familial Aggregation studies
Where is the disease gene? - Disease gene identification
Evidence for genetic effects? – Heritability studies
Mode of inheritance model? – Segregation Analyses
Based on phenotype data
(don’t need DNA)
• Genome wide
• Particular chromosomal regions
• Candidate genes
Linkage analysis (families)• Model-based• Model-free
Association studies (families or population samples)
• LD• Direct
• Genome wide
• Particular chromosomal regions
• Candidate genes
Linkage analysis (families)• Model-based• Model-free
Association studies (families or population samples)
• LD• Direct
• Genome wide
• Particular chromosomal regions
• Candidate genes
Linkage analysis (families)• Model-based• Model-free
Association studies (families or population samples)
• LD• Direct
• Genome wide
• Particular chromosomal regions
• Candidate genes
Linkage analysis (families)• Model-based• Model-free
Association studies (families or population samples)
• LD• Direct
Cases Controls
40% T, 60% C 15% T, 85% C
C/C C/T
C/C C/T C/C
C/C
C/TC/C C/C
C/T C/CC/TC/TC/C
Multiple Genes with Small Contributions and Environmental Contexts
Variant(s) Common in the Population
Polymorphic Markers > 1,000,000Single Nucleotide Polymorphisms (SNPs)
Single Gene with Major Effect
Variant Rare in the Population
~600 Short Tandem Repeat Markers
Human Genetic Analysis
FamiliesLinkage Studies
Populations Association Studies
Simple Inheritance (Segregate) Complex Inheritance (Aggregate)
Q. What is the first step in designing the study?
Define the phenotype!
•Relationship between genotype and disease-related phenotype is key concern in genetic epidemiology!
•This can be very direct: •Blood type A corresponds exactly to genotypes AA and AO
•Or very complicated: •Serum APOE levels may be a function of APOE genotypes as well of other genes and environments
• The ‘phenotype’ is an observable trait in people
• Phenotype must be measurable• External ex:
Hair color (qualitative): , ,Height (quantitative): .....4ft.....5ft.....6ft.....
• Biological measurement ex:Protein isoform (qual): APOE2, APOE3,
APOE4Protein amount (quant): ...2copies……
3.....100... Blood antigen: A, B, AB, O
Step 1: Define Phenotype – What is the trait?
Mendelian Genetics…..
A,a
AA aA Aa aa
A,a A,a
AA aA Aa aa
A,a
Dominant inheritance Recessive inheritance
+ Phenotype corresponds to:
2 genotypes: 1 genotype: A,A a,a A,a
- Phenotype corresponds to:
1 genotype: 2 genotypes: a,a A,a
A,A
+ +
++ + +-
- -
---
T t T t
T t T T t t T t
t t
T T T t t t
t t
T t T t
t t
T t t t t t T t
Family Pedigree following gene ‘T’:
T t T t
T t T t t t T T
t t
T T T t t t
t t
T t T t
t t
T t T t T t T t
Family Pedigree following gene ‘T’:
T t T t
T t T T t t T tt t
t t T t T t
T T T t t t
t t
T t t t t t T t
Dominant Trait/Disease:Ex: Early-onset Alzheimer’s disease
Recessive Trait/Disease:
T t T t
T t T T t t T tt t
t t T t
T T T t t t
t t
T t t t t t T t
Ex: Cystic Fibrosis T t, Gg
T t, Gg
T t, GG
T T,Gg
t t, Gg
T t, g g
t t, Gg
t t, GG
T t, Gg
T t, Gg
T T, GG
T t, Gg
t t, gg
t t, Gg
T t, Gg
t t, Gg
t t, gg
T t, gg
Quantitative Trait/Disease:
T t, Gg
T t, Gg
T t, GG
T T, Gg
t t, Gg
T t, g g
t t, Gg
t t, GG
T t, Gg
T t, Gg
T T, GG
T t, Gg
t t, gg
t t, Gg
T t, Gg
t t, Gg
t t, gg
T t, gg
Complex Trait/Disease:
Diagnostic Criteria
West Nile Meningitis
A. Clinical signs of meningeal inflammation
B. 1 or more of the following: T > 38 C or < 35 C, CSF cells, WBC > 10,000, compatible CT or MRI results
West Nile EncephalitisA. Encephalopathy ≥ 24 hrsB. 2 or more of the following: T > 38 C or < 35 C, CSF pleocytosis, WBC >
10,000, compatible neuroimaging, focal neurologic deficit, meningismus, EEG, seizures
Acute Flaccid ParalysisA. Acute onset of limb weakness with progression ≥ 48 hrsB. 2 or more of the following: asymmetric weakness, areflexia/hyporeflexia,
absence of pain, paresthesia, or numbness in affected limb, ≥ 5 leuk in CSF and ≥ 48 protein,WBC > 10,000, compatible neuroimaging, or EMG
Resistance to WNV in Mice
• First demonstrated in 1920’s• Resistant phenotype is
determined by a major locus - WNV/FLv on chromosome 5
• Susceptibility completely correlated to point mutation resulting in truncation of the 2’-5’ OAS L1 isoform
• Homologous region in human chromosome 12q
Mashimo, PNAS 2002; 99:11311-11316
Clinical Syndromes
• 80% asymptomatic
• 20% “West Nile Fever”
• 1 in 20 of symptomatic patients develop neuroinvasive disease
- Meningitis
- Encephalitis
- Acute Flaccid Paralysis
• Apart from increased age, risk factors ill defined
Q. How do you find genes responsible for human disease?
Difficult:• Many risk models (genotype-phenotype correlations do not follow
simple patterns – ‘complex disease’)• Many possible genes (~30,000 human genes)
page
‘chromosomal region’
This is a sentence in a paragraph…
‘gene’
This it a sentence in a paragraph…
‘mutation’
• Difficult challenge to find a disease gene: like finding a misspelled word in a set of encyclopedias!
‘which chromosome?’
Vol 7
A1
Z247
A Z
page
‘chromosome’
‘region’
This is a sentence in a paragraph…
‘gene’
This it a sentence in a paragraph…
‘mutation’
• Too many words to ‘read’ the entire set of volumes (genome) for every individual
• Need ‘markers’ to represent sections
• Need study designs and statistical methods to find regions (sets of markers) correlated with disease
• Then, ultimately look for specific disease-associated DNA variation
Definitions…
Genome –
• The entire sequence of DNA (across all chromosomes) of a particular species.
Gene –
• A segment of DNA composed of a transcribed region and a regulatory sequence that makes transcription possible.
Genetic locus –
• Loose term with several interpretations. Often: the specific location of a gene on a chromosome. However, some use the term to refer to a location of a putative gene. One definition: a region, or location, on the genome harboring a particular sequence of interest (gene or several genes).
Genetic site –
• Loose term with several interpretations. One definition: a particular
nucleotide position on the genome.
Definitions…
genome locus gene site
One possible visualization:
ATCTGA
ACCTGA
ATCTGA
ACCAGA
ACCAGA
ACCAGA
Mom’s Dad’s Mom’s Dad’sMom’s Dad’s
Haplotype -• Haploid – one copy of each chromosome• Set of alleles on a particular chromosome transmitted from parent to child (pink for
haplotype from Mom, blue from Dad).Diplotype – • Diploid – two homologous copies of each chromosome• Set of two haplotypes carried by an individual (one from each parent), where phase is
known.
Definitions…
Phase – • Knowledge of the orientation of alleles on a particular transmitted
chromosome
Illustration of Phase
(T, C)
(C, C)
(T, A)
(G, G)
T C
C C
T A
G G
Diploid person with 4 genotypes:
• Phase (orientation of alleles on particular chromosomes) is unknown based solely on these genotypes.
Two possibilities:
Diplotype 1:Haplotypes: TCTG | CCAG
C T
C C
T A
G G
T C
C C
T A
G G
or =
Diplotype 2:Haplotypes: CCTG | TCAG
• Linkage Analysis– Follows meiotic events through families for co-segregation of disease and
particular genetic variants – Large Families– Sibling Pairs (or other family pairs)
– Works VERY well for ‘Mendelian’ diseases
• Association Studies– Detect association between genetic variants and disease across families:
exploits linkage disequilibrium– Case-Control designs– Cohort designs – Parents – affected child trios (TDT)
– May be more appropriate for complex diseases
Broad Genetic Epidemiology Study Design Categories:
Q. What approaches exist for association studies ?
• All 4 loci are ‘linked’ to the (unobserved) disease allele WITHIN each of the 3 families
A,aB,bC,cd,D
A,aB,bC,cd,D
a,Ab,bc,CD,D
A,aB,bC,cd,D
A,AB,bC,Cd,D
A,ab,bC,cD,D
Linkage
A,Ab,bC,cD,d
A,ab,Bc,Cd,D
A,ab,BC,CD,D
A,Ab,bC,cD,D
a,AB,bC,cD,D
A,aB,bC,cD,D
A,ab,bc,cD,D
A,aB,bC,cD,D
A,AB,bC,cD,D
a,ab,bc,cD,D
A,aB,bc, cD,D
A,AB,bC,cD,D
A,ab, bc, cD,D
• All 4 loci are ‘linked’ to the (unobserved) disease allele WITHIN each of the 3 families
• Only alleles ‘B’ and ‘C’ are associated with the disease allele ACROSS families (LD)
A,aB,bC,cD,D
A,Ab,bC,cD,d
A,ab,Bc,Cd,D
A,ab,BC,CD,D
A,Ab,bC,cD,D
A,aB,bC,cd,D
A,aB,bC,cd,D
a,Ab,bc,CD,D
A,aB,bC,cd,D
A,AB,bC,Cd,D
A,ab,bc,cD,D
a,AB,bC,cD,D
A,ab,bC,cD,D
A,aB,bC,cD,D
A,AB,bC,cD,D
a,ab,bc,cD,D
Linkage .vs. Linkage Disequilibrium (LD)
Genetic Association Studies
1. Candidate locus testing (direct method)– Testing whether a particular locus allele is a disease
predisposing allele– Not really ‘LD mapping’, more like direct association test
normally seen with ‘exposure status’ in traditional epidemiology– Very applicable to studies of disease gene variant’s effect on
population levels of disease (risk and attributable risk assessment)
2. ‘LD Mapping’ (indirect method)– Exploitation of relationship between linkage disequilibrium (LD)
and genetic distance– Testing for LD between marker(s) and (putative) disease allele
Genetic association studies – two different concepts
Genetic Association Studies – Two Different Concepts
SNP has direct effect on protein and phenotype
Known polymorphism
Fallin, L3a, 6/21/2005 slide # 46
1. Direct method
– Testing whether a particular allele is a disease - predisposing (causative) allele
– ‘exposure status’ directly measured
Genetic Association Studies – Two Different Concepts
..GACTAAGGCCC CCGTTCAAGGAA..
C/T
APOE gene on c19
Eg: A particular APOE allele (e4) changes protein isoform
• Genotype that particular site for association study
Genetic Association Studies – Two Different Concepts
SNP with direct effect on protein and risk
SNP is a marker (proxy)in LD with allele that has a direct effect
Known polymorphism
Unmeasured!
2. ‘LD Mapping’ (indirect method)
– ‘exposure status’ not directly measured
– Rely on MARKERS correlated with true exposure status
• This correlation is due to linkage disequilibrium
Genetic Association Studies – Two Different Concepts
..GACTAAGGCCC CCGTTCAAG…GA CCTG..
C/T A/G
APOE gene on c19
Eg: Genotype a nearby genetic marker among study participants
Rely on correlation (LD) between these alleles to detect association!
Marker-based Studies
• We often do not measure the genetic variant of interest
• Instead, we genotype markers at known locations in the genome
• Look for markers the may indicate close proximity to a disease-related DNA variant
Candidate gene analysis• Instead of genome-wide approach, many pursue particular
genes as ‘candidates’– plausible biological role in the phenotype– location in regions where prior evidence for linkage or
association has been observed (positional candidate)
Taken from: Makridakis and Reichardt, Molecular Epidemiology of Hormone-Metabolic Loci in Prostate cancer. Epidemiologic Reviews, 23: 24-29.
Candidate Genes
• CD209 (DC-SIGN)• VDR• Fc γ receptor II• TNF-, IL-10• HLA-A, HLA-B • TAP1, TAP2, and
CTLA-4
Case Control Comparison Groups
Genome Wide Association Studies
• Large number of individuals with disease and a relevant comparison group
• DNA isolation and genotyping
• Statistical tests for associations between the SNPs passing quality thresholds and the disease/trait
• Replication of identified associations in an independent population sample or examination of functional implications
experimentally.
Lessons Learned from initial G WA Studies
• This actually works• Size and luck matter!• Replication matters• Collaboration matters• Controls matter, but can be shared sometimes• Non-coding SNPs matter • Current hypotheses regarding candidate genes and
pathways may not matter so much• Several genes influence more than one disease
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls: Comparison of P values for 2
different controls
Q. What is the basis for LD?
Crossing over and recombination fraction
• Crossing over between 2 genes is directly proportional to the distance between them. • Those sites closest together will have the least number of cross-overs
between themEx above:1 recombination between A & B
1 recombination between B & C 2 recombinations between A & C (further
apart)• The frequency of recombination between sites is measure of ‘genetic distance’,
often expressed as the recombination fraction
.
Diploid parent
Chromosome duplication in meiosis
Cross-overs occur
Gamete production
4 haploid gametes: One is passed on to child
Loci
A
B
C
LD Mapping Caveats: Other Reasons for Observed Allelic Associations in Populations
• Population stratification / subdivision
• Recent admixture
• Genetic drift
• Selection
• Assortative mating
• Type 1 error
Q. What are key assumptions made in genetic epidemiology
studies?
Random Mating• Under random mating, all individuals of the opposite sex are equally likely to
mate, regardless of their genotype
• The combination of two individual genotypes that produce offspring is referred to as a mating type
• If random mating, the probability of each mating type is the product of the two genotype probabilities (frequencies) in the population:
Mom
Genotypes AA Aa aa
AA P(AA) x P(AA) P(AA) x P(Aa) P(AA x P(aa)
Dad Aa P(Aa) x P(AA) P(Aa) x P(Aa) P(Aa) x P(aa)
aa P(aa) x P(AA) P(aa) x P(Aa) P(aa) x P(aa)
Random Mating…• P(MT) = P(mom genotype) * P(dad genotype)• There are 6 distinct mating types
Mom
Genotypes AA Aa aa
AA pAA2 pAA* pAa pAA * paa
Dad Aa pAA* pAa pAa2 pAa * paa
aa pAA * paa pAa * paa paa2
There are 6 distinct mating types
(assuming parent gender doesn’t matter)
Mating Type Probability of MT
AA x AA pAA2
AA x Aa 2pAA* pAa
AA x aa 2pAA * paa
Aa x Aa pAa2
Aa x aa 2pAa * paa
aa x aa paa2
Mating type
MT
Freq
Offspring conditional genotype probability, P(g’|MT)
P(MT) AA Aa aa
AA x AA 0.5 x 0.5 1 0 0
AA x aa 2(0.5 x 0.5) 0 1 0
aa x aa 0.5 x 0.5 0 0 1
A Population-based Theoretical Example…• With random mating we should have the following:
• After one generation of random mating, • P(AA) = MT P(AA|MT)P(MT) = 1(.5*.5)+ 0 + 0 = .25• P(Aa) = MT P(Aa|MT)P(MT) = 0 + 1(2*.5*.5) + 0 = .5• P(aa) = MT P(aa|MT)P(MT) = 0 + 0 + 1(.5*.5) = .25
• Genotype frequencies will be: p2 =P(AA), 2pq = P(Aa), q2= P(aa)
WNV study: Potential Gene Categories
• Primary Response Modifiers (e.g. ISGs)• Cytokines, Chemokines, Chemokine receptors,
MHC• Signal Transduction Proteins (e.g. JAK Kinases)• Transcription factors (e.g. IFN regulatory factors)• Antiviral Effector Proteins (e.g. OAS)
WNV Study Methods: genotyping
• Whole genome screening of non-synonymous variants performed using the Illumina HumanNS-12 Infinium array;
• 13,371 single nucleotide polymorphisms (SNPs) in ~6000 genes;
• Mostly non-synonymous coding, also includes synonymous, UTR, tag-SNPs (MHC).
Case-Control Study
• Cases from states/provinces with highest rates of WNV infection
• Meet CDC criteria for WNV infection and have evidence of neuroinvasive diease
• Controls are those who meet criteria for infection with WNV but who did not develop neuroinvasive disease
Pearson, T. A. et al. JAMA 2008;299:1335-1344.
Study Designs Used in Genome-wide Association Studies
Implementation
• State and provincial public health agencies contact all WNV infected individuals in 2002-2008
• 4 Clinical Centers – Pennsylvania, Texas, Nebraska, Ontario
• Whole blood is collected from participants and sent to McGill Genome Center
Analysis• Two stage design, retest the best candidates
in a second cohort
• 600 cases for each stage to detect alleles with MAF > 0.05 for a two fold risk increase
• Unconditional LR to compute odds ratios and 95% CI adjusted for site
Samples: Genotyped and Phenotyped
Stage 1 Stage 2
Cases: 488 (445) 143 +
Controls: 858 (813) 142 +
SNP discovery is dependent on your sample population size
GTTACGCCAATACAGGTTACGCCAATACAGGGATCCAGGAGATTACCATCCAGGAGATTACCGTTACGCCAATACAGGTTACGCCAATACAGCCATCCAGGAGATTACCATCCAGGAGATTACC{{2 chromosomes2 chromosomes
0.0 0.2 0.3 0.4 0.50.10.0
0.5
1.0
Minor Allele Frequency (MAF)
Fra
ctio
n o
f S
NP
s D
isco
vere
d
2
888
Replication A Must
Replication
Replication
Replication
Hirschhorn & Daly Nat. Genet. Rev. 6: 95, 2005
NCI-NHGRI Working Group on Replication Nature 447: 655, 2007
Copyright restrictions may apply.
Pearson, T. A. et al. JAMA 2008;299:1335-1344.
Examples of Multistage Designs in Genome-wide Association Studies
Results
• Phenotypic data on 1371
patients
• 488 NI disease
• 858 controls
• 25 equivocal
Samples: age distribution
casescontrols
Samples: gender distribution
Genotyping: quality control
Out of 13,371 SNPs:• 133 failed;• 174 have call rate below 95% and were considered
failed;• Average call rate is 99.8% for remaining 13,064
SNPs.
Out of 1,677 unique samples genotyped• two failed (call rate < 88%);• all others have call rate > 98% (average 99.7%).
Minor allele frequency spectrum
includes 1009 monomorphic SNPs
Copyright restrictions may apply.
Pearson, T. A. et al. JAMA 2008;299:1335-1344.
Hypothetical Quantile-Quantile Plots in Genome-wide Association Studies
Population Structure
Pairs who share less alleles(due to different ancestries/
differences in allelic frequencies)
Pairs who share more alleles(due to relatedness/identity bydescent)
Population structure
Population structure
Population structure
Population structure
Cryptic relatedness
Cryptic relatedness
Hardy-Weinberg equilibrium
• For each SNP: test to evaluate if there
is an excess of heterozygous or
homozygous;
• After excluding markers that failed
HWE at p<0.0005 (48 SNPs)
Statistical Tests for HWP
• Q: Is an observed departure from HWP statistically significant?
– Ho: DHW = 0 HA: DHW 0
• Methods:– Chi-square goodness of fit (GOF)
• Ho: Do the data fit a model where genotype frequencies equal expected values under HWP?
– Likelihood ratio test (LRT)• Ho: Does a model assuming HWE fit the observed data better than
a model that does not assume HWE?– I.e. compare likelihood of data, fixing genotype frequencies to
HWP (Lo) versus likelihood of the data without fixing genotype frequencies to match HWP (L1)
• Population allele frequencies can change from generation to generation due to:
• Migration / admixture• Chance, in small populations - genetic drift• Mutation• Selection - depends on fertility of parents and viability
of offspring• Survival bias and gender proportions - Allele
frequencies can also change with age within a generation, and could be sex dependent.
• Abnormal gene segregation (segregation distortion, meiotic drive - all maternal and paternal gametic contributions are not equally probable)
Reasons for Departure from HWP
Why is the H-W model useful to Genetic Epidemiology?
• Can use HWP assumption to calculate genotype frequencies from observed phenotypes
• Can use HWP to obtain haplotype frequencies from observed genotypes – useful for assessing inter-locus equilibrium, later lectures…
• Can measure departures from HWP as an indication of population genetic features in a sample:– Inbreeding– Migration / admixture
• Can judge potential genotyping errors
Important to test for HWE!
Testing for association
After applying all QC filters:• 445 neuroinvasive cases,
813 controls;• 10,591 SNPs with MAF > 1% in controls
entered the analysis;• Logistic model, adjusting for collection center;• X chromosome: risk of males = risk of
homozygous females; gender as additional covariate.
Methods: samples
• Data on 1371 patients, collected in centers in USA and Canada;
• All have been infected with the WNv;
• 488 developed neuroinvasive disease (meningitis, encephalitis, acute flaccid paralysis);
• 858 did not (controls);• 25 equivocal.
Methods: genotyping
•Whole genome screening of non-synonymous variants performed using the Illumina HumanNS-12 Infinium array;
• 13,371 single nucleotide polymorphisms (SNPs);
• Mostly non-synonymous coding, also includes synonymous, UTR, tag-SNPs (MHC).
Preliminary results: Manhattan Plot
Testing for associationrs2066786p = 1.67 x 10-6
RFC1 (4p14-p13)
Frq
Cases
Frq
Ctrls
Alberta .76 .55
Colorado .67 .50
Nebraska .63 .55
Ontario/Manitoba .65 .44
Saskatchewan .57 .54
Texas .59 .43
OR: 1.64 (1.34; 2.01)
RFC1• REPLICATION FACTOR C, 140-KD SUBUNIT -- 25 exons;• Has been shown to be essential for coordinated synthesis of both DNA strands
during simian virus 40 DNA replication in vitro;
• rs2066786: coding synonymous (Pro847Pro) p = 1.67 x 10-6;• No other SNPs in RFC1 on the genotyping array.
RFC1• REPLICATION FACTOR C, 140-KD SUBUNIT -- 25 exons;• Has been shown to be essential for coordinated synthesis of both DNA strands
during simian virus 40 DNA replication in vitro;
• rs2066786: coding synonymous (Pro847Pro) p = 1.67 x 10-6;• No other SNPs in RFC1 on the genotyping array.
• SNPs in or near RFC1 (rs2066786, or in LD with it) are potentially regulatory
(p<2.78 x 10-9)
Testing for associationrs2298771p = 1.73 x 10-4
SCN1A(2q24)
Frq
Cases
Frq
Ctrls
Alberta .50 .39
Colorado .40 .34
Nebraska .37 .27
Ontario/Manitoba .28 .31
Saskatchewan .52 .30
Texas .31 .34
OR: 1.50 (1.21; 1.86)
SCN1A• SODIUM CHANNEL, NEURONAL TYPE I, ALPHA SUBUNIT -- 26 exons;• Shown to be associated with generalized epilepsy with febrile seizures, myoclonic
epilepsy, familial hemiplegic migraine;
• rs2298771: coding non-synonymous (Ala1056Thr) p = 1.73 x 10-4;• No other SNPs in SCN1A on the genotyping array.
Testing for associationrs25651p = 5.5 x 10-4
ANPEP(15q26.1)
Frq
Cases
Frq
Ctrls
Alberta .76 .69
Colorado .64 .65
Nebraska .72 .63
Ontario/Manitoba .73 .63
Saskatchewan .74 .67
Texas .67 .57
OR: 1.47 (1.18; 1.83)
ANPEP• ALANYL AMINOPEPTIDASE -- 20 exons;• Serves as receptor for HCoV-229E (human coronavirus 229E); mediates human
cytomegalovirus (HCMV) infection;
• rs25651: coding non-synonymous (Ser752Asn) p = 5.5 x 10-4;• rs8192297: coding non-synonymous (Ile603Met) p = 0.39.
Validation and replication panel
Genotyping
• Panel of 33 SNPs was designed (Sequenom MassARRAY iPLEX Gold):
• Top 12 SNPs from primary analysis for validation, replication;
• TagSNPs in RFC1.
Results in primary samples
• SNP reproducibility rate between Illumina/Sequenom: > 99.62%;
• Tag-SNPs results in RFC1:
Replication samples
• Data on 617 patients;• All have been infected with the
WNv;• 277 developed neuroinvasive
disease (meningitis, encephalitis, acute flaccid paralysis);
• 340 did not (controls).
SNP Gene Allele Freq OR Sample size required
rs2066786 RFC1 0.53 1.64 285 cases/285 controls
rs2298771 SCN1A 0.30 1.50 450 cases/450 controls
rs25651 ANPEP 0.65 1.47 530 cases/530 controls
80% power; p<0.001
Lack of replicationPrimary Replication Joint
SNP Chr Pos Allele1 Allele2 Pvalue Pvalue Pvalue
LOC56964-rs3738573 1 84636844 2 3 0.003108 0.53 0.007122SCN1A-rs2298771 2 166601034 2 4 0.000299 0.66 0.0014552'-PDE-rs2241988 3 57517213 4 2 0.001476 0.42 0.000713RFC1-rs4974996 4 38903943 2 1 0.000006 0.60 0.000103RFC1-rs11096990 4 38963344 4 2 0.001328 0.65 0.004485RFC1-rs3733282 4 38965339 3 1 0.053486 0.66 0.219224RFC1-rs17288828 4 38966786 1 3 0.583279 0.87 0.484087RFC1-rs2306597 4 38973595 1 3 0.009005 0.21 0.142987RFC1-rs2066786 4 38978424 4 2 0.000001 0.56 0.000030RFC1-rs2066789 4 38984582 3 1 0.028359 0.50 0.051783RFC1-rs13147094 4 38987277 1 3 0.036064 0.95 0.106146RFC1-rs4975003 4 38989865 2 3 0.000011 0.44 0.000114RFC1-rs3796517 4 39013348 3 1 0.003467 0.82 0.012938RFC1-rs6835022 4 39030221 4 1 0.187690 0.61 0.257738RFC1-rs6851075 4 39044049 2 4 0.003936 0.94 0.020592RFC1-rs12644680 4 39047276 2 4 0.922901 0.31 0.659812RFC1-rs13123782 4 39053800 1 2 0.000806 0.57 0.005485na-rs9380006 6 27764478 2 1 0.003029 0.13 0.064231TEX15-rs323347 8 30825766 3 1 0.000238 0.13 0.045269CWF19L1-rs2270962 10 102006034 4 2 0.003019 0.81 0.029862na-rs10778292 12 102784417 2 4 0.001459 0.83 0.011818F7-rs6046 13 112821160 1 3 0.002125 0.83 0.019520TLN2-rs3816988 15 60898792 2 4 0.004330 0.69 0.012611LOC56964-rs7163367 15 88061149 1 4 0.000446 0.45 0.008170ANPEP-rs25651 15 88136792 4 2 0.000438 0.88 0.003159ANPEP-rs17240268 15 88148818 1 3 0.127363 0.59 0.268328ANPEP-rs25653 15 88150562 2 4 0.074759 0.89 0.187736GOT2-rs11076256 16 57309967 4 2 0.003654 0.98 0.027808GRIN3B-rs2240154 19 954172 4 2 0.001397 0.86 0.007999XKR3-rs5748648 22 15660822 1 3 0.001685 0.89 0.005334
Age distribution
Primary Replication
Gender distribution
Primary Replication
Neuroinvasive disease type
Primary Replication
Ancestry: U.S. census 2000
Forest plots
Primary
Replication
Forest plots
Primary
Replication
Forest plots
Primary
Replication
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