Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, Meddens SF, Linnér RK, Rietveld CA, Derringer J, Gratten J, Lee JJ, Liu JZ, de Vlaming R, Ahluwalia TS, Buchwald J, Cavadino A, Frazier-Wood AC, Furlotte NA, Garfield V, Geisel MH, Gonzalez JR, Haitjema S, Karlsson R, van der Laan SW, Ladwig KH, Lahti J, van der Lee SJ, Lind PA, Liu T, Matteson L, Mihailov E, Miller MB, Minica CC, Nolte IM, Mook-Kanamori D, van der Most PJ, Oldmeadow C, Qian Y, Raitakari O, Rawal R, Realo A, Rueedi R, Schmidt B, Smith AV, Stergiakouli E, Tanaka T, Taylor K, Thorleifsson G, Wedenoja J, Wellmann J, Westra HJ, Willems SM, Zhao W; LifeLines Cohort Study; Amin N, Bakshi A, Bergmann S, Bjornsdottir G, Boyle PA, Cherney S, Cox SR, Davies G, Davis OS, Ding J, Direk N, Eibich P, Emeny RT, Fatemifar G, Faul JD, Ferrucci L, Forstner AJ, Gieger C, Gupta R, Harris TB, Harris JM, Holliday EG, Hottenga JJ, De Jager PL, Kaakinen MA, Kajantie E, Karhunen V, Kolcic I, Kumari M, Launer LJ, Franke L, Li-Gao R, Liewald DC, Koini M, Loukola A, Marques-Vidal P, Montgomery GW, Mosing MA, Paternoster L, Pattie A, Petrovic KE, Pulkki-Råback L, Quaye L, Räikkönen K, Rudan I, Scott RJ, Smith JA, Sutin AR, Tr…See abstract for full author list ➔Okbay A, et al.Nat Genet. 2016 Nov 29;48(12):1591. doi: 10.1038/ng1216-1587b.Nat Genet. 2016.PMID: 27898078Free PMC article.No abstract available.
Abstract
Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.
Competing Financial Interests: The authors declare no competing financial interests.
Figures
Fig. 1. Manhattan plots of GWAS results.
Fig. 1. Manhattan plots of GWAS results.
(a) Subjective well-being ( N = 298,420), (b) …
Fig. 1. Manhattan plots of GWAS results.
(a) Subjective well-being (N = 298,420), (b) Depressive symptoms (N = 180,866), (c) Neuroticism (N = 170,911). The x-axis is chromosomal position, and the y-axis is the significance on a −log10 scale. The upper dashed line marks the threshold for genome-wide significance (p = 5×10−8); the lower line marks the threshold for nominal significance (p = 10−5). Each approximately independent genome-wide significant association (“lead SNP”) is marked by ×. Each lead SNP is the lowest p-value SNP within the locus, as defined by our clumping algorithm (Supplementary Note).
Fig. 2. Genetic correlations with bars representing…
Fig. 2. Genetic correlations with bars representing 95% confidence intervals.
The correlations are estimated using…
Fig. 2. Genetic correlations with bars representing 95% confidence intervals.
The correlations are estimated using bivariate LD Score (LDSC) regression. (a) Genetic correlations between subjective well-being, depressive symptoms, and neuroticism (“our three phenotypes”), as well as between our three phenotypes and height. (b) Genetic correlations between our three phenotypes and selected neuropsychiatric phenotypes. (c) Genetic correlations between our three phenotypes and selected physical health phenotypes. In (b) and (c), we report the negative of the estimated correlation with depressive symptoms and neuroticism (but not subjective well-being).
Fig. 3. Quasi-replication and lookup of lead…
Fig. 3. Quasi-replication and lookup of lead SNPs.
In quasi-replication analyses, we examined whether ( …
Fig. 3. Quasi-replication and lookup of lead SNPs.
In quasi-replication analyses, we examined whether (a) lead SNPs identified in the subjective well-being meta-analyses are associated with depressive symptoms or neuroticism, (b) lead SNPs identified in the analyses of depressive symptoms are associated with subjective well-being, and (c) lead SNPs identified in the analyses of neuroticism are associated with subjective well-being. The quasi-replication sample is always restricted to non-overlapping cohorts. In a separate lookup exercise, we examined whether lead SNPs for depressive symptoms and neuroticism are associated with depression in an independent sample of 23andMe customers (N = 368,890). The results from this lookup are depicted as green crosses in (b) and (c). Bars represent 95% CIs (not adjusted for multiple testing). For interpretational ease, we choose the reference allele so that positive coefficients imply that the estimated effect is in the predicted direction. Listed below each lead SNP is the nearest gene.
Fig. 4. Results from selected biological analyses.
Fig. 4. Results from selected biological analyses.
( a ) Estimates of the expected increase…
Fig. 4. Results from selected biological analyses.
(a) Estimates of the expected increase in the phenotypic variance accounted for by a SNP due to the SNP’s being in a given category (τc), divided by the LD Score heritability of the phenotype (h2). Each estimate of τc comes from a separate stratified LD Score regression, controlling for the 52 functional annotation categories in the “baseline model.” The bars represent 95% CIs (not adjusted for multiple testing). To benchmark the estimates, we compare them to those obtained from a recent study of height. (b) Inversion polymorphism on chromosome 8 and the 7 genes for which the inversion is a significant cis-eQTL at FDR < 0.05. The upper half of the figure shows the Manhattan plot for neuroticism for the inversion and surrounding regions. The bottom half shows the squared correlation between the SNPs and the principal component that captures the inversion. The inlay plots the relationship, for each SNP in the inversion region, between the SNP’s significance and its squared correlation with the principal component that captures the inversion.
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