Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Abstract

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

Fig. 1. Results of GWA meta-analysis of seven cohorts for major depression

(a) Relation between adding cohorts and number of genome-wide significant genomic regions (before the rigorous vetting used to define the final 44 regions). Beginning with the largest cohort (#1 on the x-axis), added the next largest cohort (#2) until all cohorts were included (#7). The number next to each point shows the total effective sample size equivalent to sample size where the numbers of cases and controls are equal. (b) Association test quantile-quantile plot showing a marked departure from a null model of no associations (y-axis truncated 10⁻¹²). (c) Manhattan plot with x-axis showing genomic position (chr1-chr22 plus chrX), and the y-axis showing statistical significance as –log₁₀(P) t-statistic; threshold for significance accounting for multiple testing shown by horizontal line. Association test from meta-analysis of 135,458 major depression cases and 344,901 controls. The red line shows the genome-wide significance threshold (P=5×10⁻⁸).

Fig. 2. Genetic risk score (GRS) prediction analyses into PGC29 MDD target samples

(a) Variance explained (liability scale) based on different discovery samples for three target samples: PGC29 (16,823 cases, 25,632 controls), iPSYCH (a nationally representative sample of 18,629 cases and 17,841 controls,) and a clinical cohort from Münster not included in the GWA analysis (845 MDD inpatient cases, 834 controls). PGC29-LOO: Target sample is one of the PGC29 samples, with discovery sample the remaining 28 PGC29 samples, hence, leave-one-out. (b) Odds ratios of major depression per GRS decile relative to the first decile for iPSYCH and PGC29 target samples. (c) Odds ratios of major depression in GRS standard deviation (SD): 3,950 early onset vs 3,950 late onset cases earlier age at onset; 4,958 severe vs 3,976 moderate cases defined by count of endorsed MDD symptom criteria; 5,574 cases recurrent MDD vs 12,968 single episode cases; severity defined as chronic/unremitting MDD 610 “Stage IV” cases vs 499 “Stage II” or 332 first-episode MDD used the NESDA sample from PGC29. Error bars represent 95% confidence intervals. Logistic regression association test p-values in the target sample for GRS generated from SNPs with p-value < 0.05 in the discovery sample.

Fig. 3. Comparisons of the major depression GWA meta-analysis

(a) Enrichment in bulk tissue mRNA-seq from GTEx; t-statistic, sample sizes in GTEx range from N=75–564. Threshold for significance accounting for multiple testing shown by vertical line. (b) Major depression results and enrichment in three major brain cell types; t-statistic; threshold for significance accounting for multiple testing shown by horizontal line. Sample sizes vary as these data are aggregated from many different sources. (c) Partitioned LDSC to evaluate enrichment of the major depression GWA findings in over 50 functional genomic annotations (Supplementary Table 8); enrichment statistic; threshold for significance accounting for multiple testing given by horizontal dashed line. Sample sizes vary as these data are aggregated from many different sources.

Fig. 4

Generative topographic mapping of the 19 significant pathway results. The average position of each pathway on the map is represented by a point. The map is colored by the –log₁₀(P) obtained using MAGMA. The X and Y coordinates result from a kernel generative topographic mapping algorithm (GTM) that reduces high dimensional gene sets to a two-dimensional scatterplot by accounting for gene overlap between gene sets. Each point represents a gene set. Nearby points are more similar in gene overlap than more distant points. The color surrounding each point (gene set) indicates significance per the scale on the right. The significant pathways (Supplementary Table 11) fall into nine main clusters as described in the text.