Genome-wide by environment interaction studies (GWEIS) of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Soler, A.; Macdonald-Dunlop, Erin; Adams, Mark; Clarke, Toni‐Kim; MacIntyre, Donald J.; Milburn, Keith; Navrady, Lauren; Scotland, Generation; Hayward, Caroline; McIntosh, Andrew M.; Thomson, Pippa A.

doi:10.1101/479691

Cited by 4 publications

(5 citation statements)

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“…Compared to the analyses of the full sample (joint male and female), the meta-analysed interaction variance was smaller when explored within the female sample and increased when explored within the male sample. Similar results were observed when using only unrelated individuals (supplementary tables [19][20].…”

Section: Resultssupporting

confidence: 84%

“…17,18 Minimal evidence of interaction effects has been yielded from studies exploring SNP-by-trauma effects. 16,[19][20][21][22] Moreover, research utilising polygenic scores (PGSs); genetic measures that can be calculated for each individual by identifying, weighting, and summing genotyped risk variants found to be associated with depression 23,24 , have yielded inconsistent findings. Whilst some studies have highlighted sex differences and found significant interaction effects associated with MDD outcomes 18,[25][26][27] , some replication attempts reported null findings 28, 29 and follow up meta-analyses have suggested that reported findings were likely to be false positives.…”

Section: Introductionmentioning

confidence: 99%

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Genome-by-Trauma Exposure Interaction Effects in Depression

Chuong

Adams

Kwong

et al. 2022

Preprint

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Background Self-reported trauma exposure has consistently been found to be a risk factor for Major Depressive Disorder (MDD) and several studies have reported interactions with genetic liability. To date, most studies have examined interaction effects with trauma exposure using genome-wide variants (single nucleotide polymorphisms SNPs) or polygenic scores, both typically capturing less than 3% of phenotypic risk variance. We sought to re-examine genome-by-trauma interaction effects using genetic measures utilising all available genotyped data and thus, maximising accounted variance. Methods Measures of self-reported depression, neuroticism and trauma exposure for 148 129 participants with whole genome SNP data are available from the UK Biobank study. Here, we used a mixed-model statistical approach utilising genetic, trauma exposure and genome-by-trauma exposure interaction similarity matrices to explore sources of variation in depression and neuroticism. Findings Our approach estimated the heritability of MDD to be approximately 0.160 [SE 0.016]. Subtypes of self-reported trauma exposure (catastrophic, adult, childhood and full trauma) accounted for a significant proportion of the variance of each trait, ranging from 0.056 [SE 0.013] to 0.176 [SE 0.025]. The proportion of MDD risk variance accounted for by significant genome-by-trauma interaction ranged from 0.074 [SE 0.006] to 0.201 [SE 0.009]. Results from sex-specific analyses found genome-by-trauma interaction variance estimates approximately 5-fold greater for MDD in males than in females. Interpretation This is the first study to utilise an approach combining all genome-wide SNP data when exploring genome-by-trauma interaction effects in MDD and present evidence that interaction effects are influential in depression manifestation. This effect accounts for greater trait variance within males which points to potential differences in depression aetiology between the sexes. The methodology utilised in this study can be extrapolated to other environmental factors to identify modifiable risk environments and at-risk groups to target with interventions.

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Section: Resultssupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Genome-by-Trauma Exposure Interaction Effects in Depression

Chuong

Adams

Kwong

et al. 2022

Preprint

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“…This SNP, from among hundreds now known in the DRD2 region, was assayable as a restriction fragmentlength polymorphism (RFLP) in 1990, when the association of DRD2 and other genes with alcoholism was first examined. 1 Newer technologies enabling large-scale genotyping of hundreds of SNPs in the DRD2 region, and hundreds of thousands of SNPs genome-wide, have been applied in genome-wide association studies (GWAS) of many phenotypes, including AUD 2,3 and related phenotypes, 4 such as brain dopamine D2 binding potential. [5][6][7] The disproportionate focus on rs1800497 has been amplified by positive meta-analyses, such that approximately 20 studies on the association between rs1800497 and AUD have been published per decade since 1990.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Association of D2 Dopamine Receptor Gene and Reported Allele Frequencies With Alcohol Use Disorders

et al. 2019

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IMPORTANCE The association between the D2 dopamine receptor gene (DRD2) Taq1A locus (rs1800497) and alcohol use disorder (AUD) is enduring but the subject of long-standing controversy; meta-analysis of studies across 3 decades shows an association between rs1800497 and AUD, but genome-wide analyses have detected no role for rs1800497 in any phenotype. No evidence has emerged that rs1800497, which is located in ANKK1, perturbs the expression or function of DRD2. OBJECTIVE To resolve contradictions in previous studies by identifying hidden confounders and assaying for functional effects of rs1800497 and other loci in the DRD2 region. DATA SOURCES PubMed (882 studies), Embase (1056 studies), and Web of Science (501 studies) databases were searched through August 2018. Three clinical populations-Finnish, Native American, and African American participants-were genotyped for 208 to 277 informative singlenucleotide polymorphisms (SNPs) across the DRD2 region to test the associations of SNPs in this region with AUD. STUDY SELECTION Eligible studies had diagnosis of AUD made by accepted criteria, reliable genotyping methods, sufficient genotype data to calculate odds ratios and 95% CIs, and availability of control allele frequencies or genotype frequencies. DATA EXTRACTION AND SYNTHESIS After meta-analysis of 62 studies, metaregression was performed to detect between-study heterogeneity and to explore the effects of moderators, including deviations of cases and controls from allele frequencies in large population databases (ExAC and 1000 Genomes). Linkage to AUD and the effect on gene expression of rs1800497 were evaluated in the context of other SNPs in the DRD2 region. Data analysis was performed from August 2018 to March 2019. This study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. MAIN OUTCOMES AND MEASURES The effects of rs1800497 and other SNPs in the DRD2 region on gene expression were measured in human postmortem brain samples via differential allelic expression and evaluated in other tissues via publicly available expression quantitative locus data. RESULTS A total of 62 studies of DRD2 and AUD with 16 294 participants were meta-analyzed. The rs1800497 SNP was associated with AUD (odds ratio, 1.23; 95% CI, 1.14-1.31; P < .001). However, the association was attributable to spuriously low allele frequencies in controls in positive studies, which also accounted for some between-study heterogeneity (I 2 = 43%; 95% CI, 23%-58%; Q 61 = 107.20).

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“…For height, these genes have been reported to be associated with height in humans (33)(34)(35)(36)(37)(38)(39). For MDD, these genes have been reported to be associated with major depressive disorder and other psychiatry phenotypes (17,18,(40)(41)(42)(43). In one of such regions for MDD, five SNPs within the region are individually significantly associated with MDD at the nominal level (p-value < 0.05).…”

Section: Discussionmentioning

confidence: 99%

SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): joint mapping of common and rare variation affecting complex traits

Oppong

Navarro

Haley

et al. 2021

Preprint

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We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value <1x10^(-5) ) for MDD. These significant regions have genes mapped to within 400kb of them. The genes mapped for height have been reported to be associated with height in humans, whiles those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.

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Genome-wide by environment interaction studies (GWEIS) of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Cited by 4 publications

References 95 publications

Genome-by-Trauma Exposure Interaction Effects in Depression

Genome-by-Trauma Exposure Interaction Effects in Depression

Assessment of the Association of D2 Dopamine Receptor Gene and Reported Allele Frequencies With Alcohol Use Disorders

SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): joint mapping of common and rare variation affecting complex traits

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