Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses.
- Authors
- Als, Thomas D; Kurki, Mitja I; Grove, Jakob; Voloudakis, Georgios; Therrien, Karen; Tasanko, Elisa; Nielsen, Trine Tollerup; Naamanka, Joonas; Veerapen, Kumar; Levey, Daniel F; Bendl, Jaroslav; Bybjerg-Grauholm, Jonas; Zeng, Biao; Demontis, Ditte; Rosengren, Anders; Athanasiadis, Georgios; Bækved-Hansen, Marie; Qvist, Per; Bragi Walters, G; Thorgeirsson, Thorgeir; StefÑnsson, Hreinn; Musliner, Katherine L; Rajagopal, Veera M; Farajzadeh, Leila; Thirstrup, Janne; VilhjÑlmsson, Bjarni J; McGrath, John J; Mattheisen, Manuel; Meier, Sandra; Agerbo, Esben; StefÑnsson, KÑri; Nordentoft, Merete; Werge, Thomas; Hougaard, David M; Mortensen, Preben B; Stein, Murray B; Gelernter, Joel; Hovatta, Iiris; Roussos, Panos; Daly, Mark J; Mors, Ole; Palotie, Aarno; Børglum, Anders D
- Year
- 2023
- Journal
- Nature medicine
- PMID
- 37464041
- DOI
- 10.1038/s41591-023-02352-1
- PMCID
- PMC10839245
Depression is a common psychiatric disorder and a leading cause of disability worldwide. Here we conducted a genome-wide association study meta-analysis of six datasets, including >1.3 million individuals (371,184 with depression) and identified 243 risk loci. Overall, 64 loci were new, including genes encoding glutamate and GABA receptors, which are targets for antidepressant drugs. Intersection with functional genomics data prioritized likely causal genes and revealed new enrichment of prenatal GABAergic neurons, astrocytes and oligodendrocyte lineages. We found depression to be highly polygenic, with ~11,700 variants explaining 90% of the single-nucleotide polymorphism heritability, estimating that >95% of risk variants for other psychiatric disorders (anxiety, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder) were influencing depression risk when both concordant and discordant variants were considered, and nearly all depression risk variants influenced educational attainment. Additionally, depression genetic risk was associated with impaired complex cognition domains. We dissected the genetic and clinical heterogeneity, revealing distinct polygenic architectures across subgroups of depression and demonstrating significantly increased absolute risks for recurrence and psychiatric comorbidity among cases of depression with the highest polygenic burden, with considerable sex differences. The risks were up to 5- and 32-fold higher than cases with the lowest polygenic burden and the background population, respectively. These results deepen the understanding of the biology underlying depression, its disease progression and inform precision medicine approaches to treatment.
The x-axes show genomic position, and the y-axes shows statistical significance as βlog10(P). (A) Manhattan plot of the primary meta-analysis (371184 cases and 978703 controls) using an inverse variance-weighted fixed-effects model, the y-axis shows statistical significance as βlog10(P) of z statistics (two-sided nominal P-values). The red horizontal line represents the threshold for genome-wide significant association (P=5Γ10β8), QQ-plot in Supplementary figure S5. Data on chromosome X were only available for iPSYCH and FinnGen, see Supplementary Figure S2). (B) Manhattan plot of the primary meta-analysis from A, the y-axis shows βlog10(P) of z statistics (two-sided nominal P-values), with highlighted joint p-values from GCTA-COJO plotted on top. The red horizontal line represents the threshold for genome-wide significant association (P=5Γ10β8). (C) Gene-based analysis: y-axis shows βlog10(P) of F statistics (two-sided nominal P-values) implemented in MAGMA. A red line indicates Bonferroni corrected genome-wide significance; P<2.8Γ10β6 (testing 17,840 protein coding genes). A total 411 significant genes of which 268 were in 93 of the 243 genomic risk loci (Supplementary Table S6). The most significant gene, overlapping with a top gene in the TWAS D, within each of the 93 genomic loci are highlighted. (D) TWAS: The y-axis shows significance as βlog10(P) of association z statistics (Wald test; two-sided P-values). Genes are represented by both gene and isoform expression. A red line indicates Bonferroni corrected genome-wide significance; P<1.44Γ10β6 (34,646 tests for all reliably imputed genes and isoforms). The top transcript is labelled and the corresponding βlog10(P) is highlighted for each independent linkage disequilibrium block.
MvPRS analyses of depression cases with/without substance use disorder (SUD). Depression-subphenotype is shown on the x-axis (NDEPwoSUD=25620, NDEPwSUD=3538 and Nctrls=38142). The slope (Ξ²) of the linear regression (95% CI) for each depression subphenotype is shown on the y-axis. Significant difference between Ξ² for depression without/with an additional diagnosis is indicated with horizontal line with nominal two-sided P-value above, i.e. the Wald test of equal group effect (see Supplementary Table 12J). Overall two-sided P-value=6.4e-97. Cases with bipolar disorder were excluded. The polygenic risk scores analyzed are (A) PRS for depression (DEP-PRS), (B) PRS for anxiety (ANX-PRS), (C) PRS for bipolar disorder (BP-PRS), (D) PRS for schizophrenia (SZ-PRS), (E) PRS for ADHD (ADHD-PRS), (F) PRS for autism (ASD-PRS), (G) PRS for neuroticism (Neuroticism-PRS), (H) PRS for substance use (SU-PRS), and (I) PRS for substance use disorder (SUD-PRS). See Supplementary Table S12K, S12L, Supplementary Figure S14-1 and S14-2 for sex-stratified analyses.
Left subpanels: Absolute risk (95%-CI) of developing anxiety since first depression episode for three groups of PRS deciles (1st, 2nd-to-9th and 10th) among 25124 depression cases with/without (NDEPwANX=3010, NDEPwoANX=221 14) anxiety. The absolute risk (95%-CI) of anxiety in light blue for the iPSYCH2015 subcohort (random population sample) excluding all depression cases, aligned to match the endpoint for the depression-cohort. Right subpanels: HRRs (95%) for 1st and 10th decile using 2nd-to-9th decile as reference (see Supplementary Table S13A) in colors matching the absolute risks curves. For deciles of (A) Depression DEP-PRS, (B) Anxiety ANX-PRS, (C) Bipolar disorder BP-PRS, (D) Schizophrenia SZ-PRS, (E) ADHD-PRS, (F) Autism ASD-PRS, (G) Neuroticism-PRS, (H) Substance Use SU-PRS, (I) Substance Use Disorder SUD-PRS and (J) sum of PRSs. The SUM-PRS was calculated by adding PRSs for multiple phenotypes weighted by log(OR) with the aim of optimizing prediction (see methods for details). See Supplementary Figure S15-1 β S15-2 and Supplementary Table S13B - S13C for sex-stratified analyses.
Left subpanels: Absolute risk (95%-CI) of transitioning into bipolar disorder since first depression episode for three groups of PRS deciles (1st, 2nd-to-9th and 10th) among 30300 depression cases with/without (NDEPwBP=1142, NDEPwoBP=29158) anxiety. The absolute risk (95%-CI) of anxiety in light blue for the iPSYCH2015 subcohort (random population sample) excluding all depression cases, aligned to match the endpoint for the depression-cohort. Right subpanels: HRRs (95%) for 1st and 10th decile using 2nd-to-9th decile as reference (see Supplementary Table S14A) in colors matching the absolute risks curves. For deciles of (A) Depression DEP-PRS, (B) Anxiety ANX-PRS, (C) Bipolar disorder BP-PRS, (D) Schizophrenia SZ-PRS, (E) ADHD-PRS, (F) Autism ASD-PRS, (G) Neuroticism-PRS, (H) Substance Use SU-PRS, (I) Substance Use Disorder SUD-PRS and (J) sum of PRSs. The SUM-PRS was calculated by adding PRSs for multiple phenotypes weighted by log(OR) with the aim of optimizing prediction (see methods for details). See Supplementary Figure S16-1 β S16-2 Supplementary Tables S14B β S14C for sex-stratified analyses.
Left subpanels: Absolute risk (95%-CI) of developing schizophrenia since first depression episode for three groups of PRS deciles (1st, 2nd-to-9th and 10th) among 28714 depression cases with/without (NDEPwSZ=1606, NDEPwoSZ=27108) anxiety. The absolute risk (95%-CI) of anxiety in light blue for the iPSYCH2015 subcohort (random population sample) excluding all depression cases, aligned to match the endpoint for the depression-cohort. Right subpanels: HRRs (95%) for 1st and 10th decile using 2nd-to- 9th decile as reference (see Supplementary Table S15A) in colors matching the absolute risks curves. For deciles of (A) Depression DEP-PRS, (B) Anxiety ANX-PRS, (C) Bipolar disorder BP-PRS, (D) Schizophrenia SZ-PRS, (E) ADHD-PRS, (F) Autism ASD-PRS, (G) Neuroticism-PRS, (H) Substance Use SU-PRS, (I) Substance Use Disorder SUD-PRS and (J) sum of PRSs. The SUM-PRS was calculated by adding PRSs for multiple phenotypes weighted by log(OR) with the aim of optimizing prediction (see methods for details). See Supplementary Figure S17-1 β S17-2 and Supplementary Tables S15B β S15C for sex-stratified analyses.
Left subpanels: Absolute risk (95%-CI) of developing SUD since first depression episode for three groups of PRS deciles (1st, 2nd-to-9th and 10th) among 27249 depression cases with/without (NDEPwSUD=1629, NDEPwoSUD=25620) anxiety. The absolute risk (95%-CI) of anxiety in light blue for the iPSYCH2015 subcohort (random population sample) excluding all depression cases, aligned to match the endpoint for the depression-cohort. Right subpanels: HRRs (95%) for 1st and 10th decile using 2nd-to-9th decile as reference (see Supplementary Table S16A) in colors matching the absolute risks curves. For deciles of (A) Depression DEP-PRS, (B) Anxiety ANX-PRS, (C) Bipolar disorder BP-PRS, (D) Schizophrenia SZ-PRS, (E) ADHD-PRS, (F) Autism ASD-PRS, (G) Neuroticism-PRS, (H) Substance Use SU-PRS, (I) Substance Use Disorder SUD-PRS and (J) sum of PRSs. The SUM-PRS was calculated by adding PRSs for multiple phenotypes weighted by log(OR) with the aim of optimizing prediction (see methods for details). See Supplementary Figure S18-1 β S18-2 and Supplementary Tables S16B β S16C for sex-stratified analyses.
Venn diagrams showing MiXeR results of the estimated number of variants shared between depression (N=1349887) and psychiatric disorders (anxiety (N= 361365), bipolar disorder (N= 405771), schizophrenia (N=153808), ADHD (N=225534), autism (N=46350, SUD (N=46568), neuroticism (N=380506)) and genetically correlated phenotypes (smoking initiation (N=632803), educational attainment (N=3037499)) and other phenotypes (height (N=1597374), Alzheimerβs (N=788989), epilepsy (N=44889)) not expected to show high genetic correlation with depression. Circles represent loci unique to depression and unique to the phenotype of interest and corresponding overlapping shared loci. The number of shared variants +/β SE are shown in thousands. The size of the circles reflects the polygenicity of each phenotype, with larger circles corresponding to greater polygenicity. Point estimates of genetic correlation (rg) and 95% CI between depression and each phenotype is shown at the bottom with an accompanying scale (β1 to +1) (see also Supplementary Table S6A and Figure S9-1).
(A) Significant cell types across datasets in MAGMA analysis implemented in FUMA. The y-axis shows βlog10 of one-sided nominal P-values based on z statistics for cell- types significant across datasets (x-axis), i.e. after experiment wide Bonferroni correction. The primary depression GWAS (Ncases=371184 and Nctrls=978703) was used as input for this analysis. (B) Enrichment of depression risk variants with cell-specific open chromatin regions. Dots represents the LD score coefficients and horizontal bars reflect standard error (x-axis) for various cell-types (y-axis). A positive LD score coefficient signifies enrichment in heritability. Dot size reflects two-sided P-value of LD score z statistics, and color code indicate test-wide significance (BH-corrected P-value<0.05). The primary depression GWAS (Ncases = 371184 and Nctrls = 978703) was used as input for this analysis.
Association of DEP-PRS (broadly and narrowly defined) with measures of cognitive abilities in the PNC cohort (N=4,973). Regression coefficients (Ξ²) and 95% confidence interval) from linear regression testing for the association of DEP-PRS with the 15 neurocognitive measures listed on the y-axis. Significance is based on two-sided FDR adjusted P-values from linear regression t statistics. Colors indicate FDR-adjusted (to account for 30 total tests) P-value intervals (See supplementary table S12 for details) and ** corresponds to FDR-adjusted P-value (q-value) <0.01, * corresponds to 0.01<=q-value<0.05. The primary DEP-PRS was significantly associated with Abstraction and mental flexibility (q-value=0.03). The narrow DEP-PRS was significantly associated with Verbal reasoning (q-value=0.009), Attention (q-value=0.011) and Abstraction and mental flexibility (q-value=0.012). The neurocognitive phenotypes included performance on the Computerized Neurocognitive Battery (CNB: age differentiation, emotion identification, facial memory, sensorimotor processing, finger tapping speed, emotion differentiation, spatial reasoning, verbal memory, nonverbal reasoning, working memory, verbal reasoning, spatial memory, attention, abstraction and mental flexibility)68, as well as results from the Wide Range Achievement Test (WRAT-4)69.
Absolute risk (95% CI) over time since first depression episode and HRR (95% CI) of (A,B) a second episode of depression stratified by three groups of DEP-PRS and DEP-SUM-PRS deciles (N=29158); (C,D) developing anxiety stratified by ANX-PRS and ANX-SUM-PRS (N=25124); (E,F) transitioning into bipolar disorder stratified by BP-PRS and BP- SUM-PRS (N=30300); (G,H) developing schizophrenia stratified by SZ-PRS and SZ-SUM-PRS (N=28714); (I,J) developing substance-use-disorder stratified by SU-PRS and SUD- SUM-PRS (N=18856). SUM-PRSs were calculated by adding PRSs for multiple phenotypes weighted by log(OR) aiming to optimize prediction. HRR (95% CI) for 1st, 2nd-to-9th and 10th decile are shown as large dots in different colors, using the middle (80% prediction interval) of the PRS as reference. Absolute risk (95% CI) of anxiety (C,D), bipolar disorder (E,F), schizophrenia (G,H) and SUD (I,J) is shown for the iPSYCH2015 random population (sub-cohort) in less bright colors.
Highlighted Regional Miami plots of GWAS and TWAS results, corresponding to the genomic region of (A) GABRA1, (B) CYP7B1, (C) DCC, (D) CTTNBP2, (E) FURIN and (F) GIGYF2 genes/transcripts (1Mbp window from start site). Top panels: GWAS results (black dots): The x-axis shows genomic position, and the y-axis shows significance as βlog10(P) of z statistics (two-sided nominal P-values); blue line corresponds to P=1Γ10β5, orange line to P=5Γ10β8 (genome-wide significance). Bottom panels: TWAS results: The x-axis shows genomic position. The y-axis shows significance as βlog10(P) of z statistics (two-sided nominal P-values) for genes represented by both gene expression and isoform expression. Green triangles facing upwards or downwards for a positive or negative association z-score (Wald test; two-sided P-values) respectively (up- or down-regulation); transcripts with Bonferroni-adjusted (for all reliably imputed transcripts) P-value<0.1 are labelled; orange line corresponds to Bonferroni-adjusted P=0.05. Each Bonferroni-significant transcript is connected with lines to the SNPs contributing to its transcriptomic imputation model; lines are grey when the SNPs have a P>1Γ10β5, blue when P<1Γ10β5 but orange when P<5Γ10β8. The SNPs that are above the blue line and contribute to the transcriptomic imputation models of significant transcripts are labelled. See Supplementary Figure S19-1 to S19-88 and Table S19.
MvPRS analyses of depression cases with/without anxiety (ANX). Depression-subphenotype is shown on the x-axis (NDEPwoANX=22114, NDEPwoANX=7044 and Nctrls=38142). The slope (Ξ²) of the linear regression (95% CI) for each depression subphenotype is shown on the y-axis. Significant difference between Ξ² for depression without/with an additional diagnosis is indicated with horizontal line with nominal two-sided P-value above, i.e. the Wald test of equal group effect (see Supplementary Table 12A). Overall two-sided P-value=1.2e-21. Cases with bipolar disorder were excluded. The polygenic risk scores analyzed are (A) PRS for depression (DEP-PRS), (B) PRS for anxiety (ANX-PRS), (C) PRS for bipolar disorder (BP-PRS), (D) PRS for schizophrenia (SZ-PRS), (E) PRS for ADHD (ADHD-PRS), (F) PRS for autism (ASD-PRS), (G) PRS for neuroticism (Neuroticism-PRS), (H) PRS for substance use (SU-PRS), and (I) PRS for substance use disorder (SUD-PRS). See Supplementary Table S12B, S12C, Supplementary Figure S14-1 and S14-2 for sex-stratified analyses.
MvPRS analyses of depression cases with/without bipolar disorder (BP). Depression-subphenotype is shown on the x-axis (NDEPwoBP=29158, DEPwBP, N=1460 and Nctrls=38200). The slope (Ξ²) of the linear regression (95% CI) for each depression subphenotype is shown on the y-axis. Significant difference between Ξ² for depression without/with an additional diagnosis is indicated with horizontal line with nominal two-sided P-value above, i.e. the Wald test of equal group effect (See Supplementary Table 12D). Overall two-sided P-value=1.5e-15. The polygenic risk scores analyzed are (A) PRS for depression (DEP-PRS), (B) PRS for anxiety (ANX-PRS), (C) PRS for bipolar disorder (BP-PRS), (D) PRS for schizophrenia (SZ-PRS), (E) PRS for ADHD (ADHD-PRS), (F) PRS for autism (ASD-PRS), (G) PRS for neuroticism (Neuroticism-PRS), (H) PRS for substance use (SU-PRS), and (I) PRS for substance use disorder (SUD-PRS). See Supplementary Table S12E, S12F, Supplementary Figure S14β1 and S14-2 for sex-stratified analyses.
MvPRS analyses of depression cases with/without schizophrenia (SZ). Depression-subphenotype is shown on the x-axis (NDEPwoSZ=25253, NDEPwSZ=3905 and Nctrls=38142). The slope (Ξ²) of the linear regression (95% CI) for each depression subphenotype is shown on the y-axis. Significant difference between Ξ² for depression without/with an additional diagnosis is indicated with horizontal line with nominal two-sided P-value above, i.e. the Wald test of equal group effect (see Supplementary Table 12G). Overall two-sided P-value=1.7e-15. Cases with bipolar disorder were excluded. The polygenic risk scores analyzed are (A) PRS for depression (DEP-PRS), (B) PRS for anxiety (ANX-PRS), (C) PRS for bipolar disorder (BP-PRS), (D) PRS for schizophrenia (SZ-PRS), (E) PRS for ADHD (ADHD-PRS), (F) PRS for autism (ASD-PRS), (G) PRS for neuroticism (Neuroticism-PRS), (H) PRS for substance use (SU-PRS), and (I) PRS for substance use disorder (SUD-PRS). See Supplementary Table S12H, S12I, Supplementary Figure S14-1 and S14-2 for sex-stratified analyses.
| Name | Type |
|---|---|
| 1000 Genomes Project | cohort |
| 10th depression-PRS decile local | cohort |
| 23andMe | cohort |
| 23andMe, Inc. | cohort |
| abstraction | phenotype |
| additional traits local | phenotype |
| ADHD | phenotype |
| ADHD-PRS local | phenotype |
| affective disorders | phenotype |
| Affymetrix | drug |
| Age differentiation | phenotype |
| age of initiation as a regular smoker local | phenotype |
| Age of initiation as a regular smoker local | phenotype |
| Aggregate polygenic risk score local | drug |
| alcohol | phenotype |
| alcohol dependence | phenotype |
| Alzheimer local | phenotype |
| Alzheimerβs disease | phenotype |
| AMPA receptor | drug |
| AMPA receptor potentiators local | drug |
| AMPA receptors | drug |
| Ancestry-outlier depression GWAS local | cohort |
| ancestry outliers local | cohort |
| ancestry outlier sample local | cohort |
| Ancestry outlier sample local | cohort |
| anorexia nervosa | phenotype |
| antidepressants | drug |
| anxiety | phenotype |
| ANX-PRS local | drug |
| ANX-PRS local | phenotype |
| Array.Batch local | cohort |
| ArrayPlate.ID local | cohort |
| ASD | phenotype |
| ASD-PRS local | phenotype |
| astrocytes | phenotype |
| attention | phenotype |
| attention deficit hyperactivity disorder | phenotype |
| Attenuated cognitive performance local | phenotype |
| autism | phenotype |
| autism spectrum disorder | phenotype |
| autism spectrum disorders | phenotype |
| background population local | cohort |
| Background population without depression diagnosis local | cohort |
| baseline cohort local | cohort |
| behavioral traits | phenotype |
| bipolar disorder | phenotype |
| Birdseed 1.6102 local | drug |
| Both sexes in lowest aggregate PRS decile local | cohort |
| BP-PRS local | drug |
| BP-PRS local | phenotype |
| BP-PRS local | variant |
| BPTF local | gene |
| brain | anatomy |
| broad depression | phenotype |
| Broadly defined depression local | phenotype |
| cannabis use | phenotype |
| cannabis use disorder | phenotype |
| cases | cohort |
| cigarettes | phenotype |
| CKS2 local | gene |
| clinical/phenotypic variables local | phenotype |
| CNB measure of nonverbal reasoning local | phenotype |
| cognition | phenotype |
| cognitive phenotypes | phenotype |
| Common risk variants for psychiatric phenotypes local | variant |
| Community cohort of youths local | cohort |
| Community youth cohort local | cohort |
| comorbidity | phenotype |
| complex cognitive processing local | phenotype |
| Computerized Neurocognitive Battery local | phenotype |
| control group | cohort |
| controls | cohort |
| Core anxiety local | phenotype |
| Credible variant local | variant |
| Danish Neonatal Screening Biobank local | cohort |
| Danish population local | cohort |
| Danish Psychiatric Central Research Register local | cohort |
| decode genetics | cohort |
| deficits in functional connectivity local | phenotype |
| DEP-PRS local | drug |
| DEP-PRS local | phenotype |
| DEP-PRS local | variant |
| depression | phenotype |
| depression-anxiety comorbidity local | phenotype |
| Depression case group local | cohort |
| Depression-only case group local | cohort |
| depression phenotype local | phenotype |
| Depression phenotype local | phenotype |
| Depression polygenic burden local | phenotype |
| depression polygenic score local | phenotype |
| Depression-PRS local | drug |
| Depression risk genes local | gene |
| Depression risk variant local | variant |
| Depression transitioning to bipolar disorder local | phenotype |
| Depression with anxiety local | cohort |
| Depression with bipolar disorder local | cohort |
| Depression with co-diagnosis of schizophrenia local | phenotype |
| Depression with schizophrenia local | cohort |
| Depression with substance use disorder local | cohort |
| DEP-SUM-PRS local | drug |
| DLFPC | anatomy |
| dlPFC | anatomy |
| dopaminergic neurons | anatomy |
| dorsolateral prefrontal cortex | anatomy |
| drinks per week | phenotype |
| Eagle v2.3.5 local | drug |
| early-onset depression local | phenotype |
| educational attainment | phenotype |
| Emotion differentiation local | phenotype |
| emotion identification | phenotype |
| epilepsy | phenotype |
| episodic memory | phenotype |
| eQTL signatures local | drug |
| European ancestry | cohort |
| European LD reference panel local | drug |
| European population | cohort |
| executive-control local | phenotype |
| executive function | phenotype |
| external GWAS summary statistics local | cohort |
| facial memory local | phenotype |
| family history positive | phenotype |
| fast-acting antidepressants local | drug |
| finger tapping speed local | phenotype |
| FinnGen | cohort |
| FinnGen22 local | cohort |
| FinnGen22 release 6 local | cohort |
| FinnGen23 local | cohort |
| FinnGen release 2 local | cohort |
| First depression-PRS decile local | cohort |
| First-onset depression local | phenotype |
| FUMA | drug |
| FURIN | gene |
| GABA | phenotype |
| GABAA receptor | drug |
| Gabra1 | gene |
| GenCall 1.6.2.2101 local | drug |
| general Danish population local | cohort |
| generalized anxiety disorder | phenotype |
| general population | cohort |
| Genes/transcripts local | gene |
| genetic correlation | phenotype |
| genetic depression risk local | phenotype |
| genetic loci | cohort |
| genetic variants | cohort |
| GenTrain V3 local | drug |
| Global Screening Array v2 | drug |
| GPR27 local | gene |
| GRIA1 | gene |
| GTEx | cohort |
| GTEx brain regions | anatomy |
| GWAS | cohort |
| GWAS signatures local | drug |
| Haplotype Reference Consortium (HRC) local | drug |
| height | phenotype |
| HIST1 local | gene |
| Hospital cohort with first diagnosis of depression local | cohort |
| Howard2019 local | cohort |
| Howard et al. 2019 local | cohort |
| HRC r1.1 2016 local | drug |
| human tissues local | anatomy |
| ICD-10 F32 local | phenotype |
| ICD-10 F33 local | phenotype |
| Illumina | drug |
| index variant | variant |
| influencing variant local | variant |
| intellectual disability | phenotype |
| iPSYCH | cohort |
| iPSYCH2012 local | cohort |
| iPSYCH201226 local | cohort |
| iPSYCH2012 sample local | cohort |
| iPSYCH2015 local | cohort |
| iPSYCH2015 cohort local | cohort |
| iPSYCH2015i local | cohort |
| iPSYCH2015i sample local | cohort |
| iPSYCH2015 sample local | cohort |
| iPSYCH26 local | cohort |
| iPSYCH cohort | cohort |
| iPSYCH depression-cohort local | cohort |
| iPSYCH sample | cohort |
| iPSYCH subcohort local | cohort |
| IQ | phenotype |
| language | phenotype |
| late-onset depression local | phenotype |
| LAVA local | drug |
| LD Hub | cohort |
| LD-pruned SNPs local | variant |
| Levey2020 local | cohort |
| LINGO1 local | gene |
| lowest decile case group local | cohort |
| MAGMA | drug |
| Major depressive disorder, recurrent, in remission local | phenotype |
| major psychiatric disorders | phenotype |
| Males in top aggregate PRS decile local | cohort |
| marker genotype local | phenotype |
| memory | phenotype |
| mental flexibility local | phenotype |
| Mental flexibility local | phenotype |
| Michigan Imputation Server | drug |
| Middle depression-PRS deciles local | cohort |
| Million Veteran Program | cohort |
| minimac3 | drug |
| Miserableness local | phenotype |
| Mixed population | cohort |
| MiXeR | drug |
| Mood (affective) disorders local | phenotype |
| mood swings | phenotype |
| MSigDB local | cohort |
| MVP | cohort |
| MVP112 local | cohort |
| MVP24,112 local | cohort |
| mvPRS approach local | drug |
| narrow depression phenotype local | phenotype |
| Narrowly defined depression local | phenotype |
| NEGR1 | gene |
| neurodevelopmental disorder | phenotype |
| neurons | phenotype |
| neuroticism | phenotype |
| Neuroticism PRS local | phenotype |
| Neuroticism-PRS local | drug |
| Neuroticism-PRS local | phenotype |
| Nonverbal reasoning local | phenotype |
| oligodendrocyte lineages local | phenotype |
| Oligodendrocyte lineages local | anatomy |
| panic disorder | phenotype |
| pathophysiology local | phenotype |
| PEIT-AB local | phenotype |
| PEIT-C local | phenotype |
| PEIT-D local | phenotype |
| PEIT-E local | phenotype |
| Persistent mood disorders local | phenotype |
| PGC | cohort |
| phenotype Pi local | phenotype |
| Philadelphia Neurodevelopmental Cohort | cohort |
| phobic anxiety | phenotype |
| Plink v2.0 local | drug |
| PMAT-18B local | phenotype |
| PMAT-24A local | phenotype |
| PNC | gene |
| PNC cohort local | cohort |
| Polygenic load local | phenotype |
| polygenic risk score | cohort |
| prefrontal cortex | anatomy |
| Prenatal GABAergic neurons local | anatomy |
| PreProc. Plate local | cohort |
| Primary depression meta-analysis local | cohort |
| primary depression phenotype local | phenotype |
| protein-coding gene | gene |
| PRS-CS | drug |
| PsychArray V1.0 local | drug |
| PsychChip arrays local | drug |
| PsychENCODE | cohort |
| psychiatric disorders | phenotype |
| Psychiatric Genomics Consortium | cohort |
| psychosis | phenotype |
| recurrence | phenotype |
| recurrent episodes of depression local | phenotype |
| recurrent major depressive disorder | phenotype |
| relatedness and ancestry pruned dataset local | cohort |
| Ricopili104 pipeline local | drug |
| ricopili pipeline | drug |
| Ricopili-pipeline local | drug |
| risk loci | cohort |
| Rosmap | cohort |
| SAIGE | drug |
| schizophrenia | phenotype |
| Second episode of depression local | phenotype |
| Seen doctor (GP) for nerves_ anxiety_ tension or depression local | phenotype |
| Sensorimotor processing local | phenotype |
| sensorimotor speed local | phenotype |
| severe synaptic loss local | phenotype |
| sex | phenotype |
| shared causal variants local | variant |
| Single-disorder polygenic risk score local | drug |
| single-episode depression local | phenotype |
| Single episode depression local | phenotype |
| Single-episode depression local | phenotype |
| smoking cessation | phenotype |
| smoking ever local | phenotype |
| Smoking ever local | phenotype |
| smoking initiation | phenotype |
| SNP | cohort |
| social cognition | phenotype |
| somatic disorders local | phenotype |
| SORCS3 | gene |
| spatial memory | phenotype |
| spatial reasoning local | phenotype |
| Statens Serum Institute local | cohort |
| sub-phenotype of interest local | phenotype |
| substance use | phenotype |
| SUD | phenotype |
| SUD comorbidities local | phenotype |
| SUD-PRS local | phenotype |
| SUD-SUM-PRS local | phenotype |
| SU-PRS local | phenotype |
| SZ-PRS local | drug |
| SZ-PRS local | phenotype |
| SZ-SUM-PRS local | phenotype |
| TCTA local | gene |
| Thermo Fisher Scientific | drug |
| tobacco use | phenotype |
| top decile case groups local | cohort |
| Twin cohort | cohort |
| UKB | cohort |
| UK Biobank | cohort |
| UKB traits local | cohort |
| Unspecified mood disorder local | phenotype |
| verbal memory | phenotype |
| verbal reasoning | phenotype |
| wave 2 | cohort |
| Wide Range Achievement Test local | phenotype |
| working memory | phenotype |
| Wray2018 local | cohort |
| Wray et al. 2018 local | cohort |
| zCall 1103 local | drug |
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder. | 2025 | 40360802 |
External
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|---|---|---|---|---|
| A genome-wide investigation of depression among individuals with and without irritability. | St-Pierre J et al. | β | 2026 | β |
| Association of Polygenic Risk Scores for Depression, Anxiety, and Neuroticism with Lower Urinary Tract Symptoms Among Women. | Rajan Z et al. | β | 2026 | β |
| Associations of polygenic risk scores for major depression and depression severity: an investigation of 105 623 individuals with 16 years follow-up. | Haram M et al. | β | 2026 | β |
| B cell pathways implicate shared genetic architecture between schizophrenia and immune-mediated diseases. | Yuan R et al. | β | 2026 | β |
| Divergent Patterns of Genetic Overlap Between Severe Mental Disorders and Metabolic Markers. | van der Meer D et al. | β | 2026 | β |
| Functional polygenic risk score of glucocorticoid-dependent regulatory element activity and its relation to clinical and stress-related phenotypes. | Linsen F et al. | β | 2026 | β |
| Genetic and epigenetic analysis of plasma glial fibrillary acidic protein (GFAP) levels in PTSD. | Miller MW et al. | β | 2026 | β |
| Genetic exploration of the relationship between liability to psychiatric disorders and acne vulgaris. | Mitchell BL et al. | β | 2026 | β |
| Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling. | Strom NI et al. | β | 2026 | β |
| Genome-wide methylation patterns associated with chronic stress. | O'Toole N et al. | β | 2026 | β |
| Heterogeneity in the longitudinal course of depressive symptomatology in adults with a history of recurrent major depressive disorder. | Weavers B et al. | β | 2026 | β |
| Inclusion bias affects common variant discovery and replication in a health-system linked biobank. | Pimplaskar A et al. | β | 2026 | β |
| Leveraging the genetics of psychiatric disorders to prioritize potential drug targets and compounds. | Parker N et al. | β | 2026 | β |
| Leveraging transdiagnostic genetic liability to psychiatric disorders to dissect clinical outcomes of anorexia nervosa. | Lu ZA et al. | β | 2026 | β |
| Multi-organ network of cardiometabolic disease-depression multimorbidity revealed by phenotypic and genetic analyses of MR images. | Wang J et al. | β | 2026 | β |
| Novel insights into genetic associations and drug targets of mitochondria-associated proteins with major depressive disorder. | Sun W et al. | β | 2026 | β |
| Sex-specific interaction effects of Syntaxin 1A coexpression network and childhood trauma on adult depressive symptoms. | Arcego DM et al. | β | 2026 | β |
| Shared genetic architecture of psychiatric disorders and ocular diseases: Evidence from genome-wide analyses. | Zhang ZY et al. | β | 2026 | β |
| Standardized chronic restraint stress protocols reveal dynamic evolution of behavioral adaptations in male mice: implications for translational neuroscience. | Lv Z et al. | β | 2026 | β |
| Substance Use Disorders as Genetic Bridges Across Psychiatric Disorders in Diverse Ancestries. | Ohi K | β | 2026 | β |
| Three shades of gloom: investigating the genetic background of current depressive symptoms associated with different severity of current stress exposure in a general population. | Erdelyi-Hamza B et al. | β | 2026 | β |
| Transdiagnostic and Disorder-Level Genome-Wide Association Studies Enhance Precision of Substance Use and Psychiatric Genetic Risk Profiles in African and European Ancestries. | Khan Y et al. | β | 2026 | β |
| Uncovering plasma protein biomarkers linked to depression: A differential abundance analysis and Mendelian randomization using large-scale data. | Abebe E et al. | β | 2026 | β |
| Unique and shared internalizing and externalizing genetic factors associated with suicidal thoughts and behaviors: Findings from the adolescent brain cognitive development study. | Thomas NS et al. | β | 2026 | β |
| Unravelling depression heterogeneity: Exploring the role of external risk factors in symptom network dynamics. | Yang T et al. | β | 2026 | β |
| Activity and Heterogeneity of Astrocytes in Neurological Diseases: Molecular Mechanisms and Therapeutic Targets. | Mao S et al. | β | 2025 | β |
| Advancing Antidepressive Agents: Drug Discovery and Polymer-Based Drug Delivery Systems for Improved Treatment Outcome. | Zhang Y et al. | β | 2025 | β |
| An encompassing Mendelian randomization study of the causes and consequences of major depressive disorder. | Pasman JA et al. | β | 2025 | β |
| A Novel Integrative Framework for Depression: Combining Network Pharmacology, Artificial Intelligence, and Multi-Omics with a Focus on the Microbiota-Gut-Brain Axis. | Zhang L et al. | β | 2025 | β |
| Association of branched-chain amino acids with major depressive disorder: A bidirectional Mendelian randomization study. | Ma Z et al. | β | 2025 | β |
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| Blunted cortisol as a biomarker of depression based on the attenuation hypothesis: A Mendelian randomization analysis using depression as exposure. | Chan II | β | 2025 | β |
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| Cardiovascular diseases and depression: A meta-analysis and Mendelian randomization analysis. | Zeng J et al. | β | 2025 | β |
| Causal Associations Between Smoking, Brain Structural Alterations and Psychiatric Disorders: Evidence From a Mediation Analysis. | Chen Y et al. | β | 2025 | β |
| Challenges and Opportunities in Characterizing the Genetics of Stuttering: From Sample Acquisition to Functional Interpretation of the Genome. | Pruett DG et al. | β | 2025 | β |
| Circulating Blood-Based Proteins in Psychopathology and Cognition: A Mendelian Randomization Study. | Bhattacharyya U et al. | β | 2025 | β |
| Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression. | Li Y et al. | β | 2025 | β |
| Depression genetics through the lens of age at onset. | Cai N | β | 2025 | β |
| Developing an individual depression risk score based on traditional risk factors and routine biochemical markers. | Ma S et al. | β | 2025 | β |
| Directional Selection and Evolution of Polygenic Traits in Eastern Eurasia: Insights from Ancient DNA. | Piffer D | β | 2025 | β |
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| Elucidation and application of the neuroimmune axis between depression and autoimmune diseases: A genome wide and cohort study. | Sun F et al. | β | 2025 | β |
| Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses. | Pathak GA et al. | β | 2025 | β |
| Epigenetic insights into neuropsychiatric and cognitive symptoms in Parkinson's disease: A DNA co-methylation network analysis. | Harvey J et al. | β | 2025 | β |
| Evaluation of the two-way associations between mental disorders and menstrual irregularities: A Mendelian randomization study from both directions. | Dong F et al. | β | 2025 | β |
| Evidence of bidirectional relationship between type 2 diabetes and depression; a Mendelian randomization study. | Bala R et al. | β | 2025 | β |
| Exploring depression treatment response by using polygenic risk scoring across diverse populations. | Lapinska S et al. | β | 2025 | β |
| Exploring the Potential of Precision Medicine in Neuropsychiatry: A Commentary on New Insights for Tailored Treatments Based on Genetic, Environmental, and Lifestyle Factors. | Milic J et al. | β | 2025 | β |
| Familial and genetic relationships of major depressive disorders and adiposity markers in the community. | Berney A et al. | β | 2025 | β |
| From Clinic to Mechanisms: Multi-Omics Provide New Insights into Cerebrospinal Fluid Metabolites and the Spectrum of Psychiatric Disorders. | Wen J et al. | β | 2025 | β |
| Genetic analyses point to alterations in immune-related pathways underpinning the association between psychiatric disorders and COVID-19. | Monistrol-Mula A et al. | β | 2025 | β |
| Genetic Architecture and Risk of Childhood Maltreatment Across 5 Psychiatric Diagnoses. | Nielsen TT et al. | β | 2025 | β |
| Genetic association and drug target exploration of inflammation-related proteins with risk of major depressive disorder. | Sun W et al. | β | 2025 | β |
| Genetic Confounding of the Association Between Age at First Hormonal Contraception and Depression. | Mundy J et al. | β | 2025 | β |
| Genetic insights into the role of mitochondria-related genes in mental disorders: An integrative multi-omics analysis. | Lu Y et al. | β | 2025 | β |
| Genetic liability to depression and cerebral small vessel disease: A mendelian randomization study. | Wang M et al. | β | 2025 | β |
| Genetic relationship between epilepsy and mental disorders: A comprehensive GWAS analysis. | Abudusalamu R et al. | β | 2025 | β |
| Genetic risk scores of psychiatric phenotypes are associated with depression risk in a prospective Dutch population-based cohort. | Hofman A et al. | β | 2025 | β |
| Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder. | Strom NI et al. | β | 2025 | β |
| Genome-wide analysis identifies novel shared loci between depression and white matter microstructure. | Zhao Q et al. | β | 2025 | β |
| Genome-wide association analyses identify distinct genetic architectures for early-onset and late-onset depression. | Shorter JR et al. | β | 2025 | β |
| Genome-wide association meta-analysis and rare copy number variant analysis of treatment-resistant depression. | Xiong Y et al. | β | 2025 | β |
| Genome-wide by trait interaction analyses with neuroticism reveal chronic pain-associated depression as a distinct genetic subtype. | Krause S et al. | β | 2025 | β |
| Genomics of schizophrenia, bipolar disorder and major depressive disorder. | Owen MJ et al. | β | 2025 | β |
| Heritability and polygenic load for comorbid anxiety and depression. | Tabrizi F et al. | β | 2025 | β |
| Hippocampal Zkscan4 confers resilience to chronic stress-induced depression-like behaviors. | Gao K et al. | β | 2025 | β |
| Human mood disorder risk gene Synaptotagmin-14 contributes to mania-like behaviors in mice. | Zhang Y et al. | β | 2025 | β |
| Identification of 1q25.2 as a novel shared locus between schizophrenia and major depressive disorder in east Asians by integrative analyses. | Guo X et al. | β | 2025 | β |
| Identification of <i>TMEM106B</i> as a Shared Potential Drug Target for Depression and Stroke Through Comprehensive Genetic Analyses. | Zhang W et al. | β | 2025 | β |
| Identifying genetic differences between bipolar disorder and major depression through multiple genome-wide association analyses. | Panagiotaropoulou G et al. | β | 2025 | β |
| Immunological drivers and potential novel drug targets for major psychiatric, neurodevelopmental, and neurodegenerative conditions. | Dardani C et al. | β | 2025 | β |
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| Integrating genetics and transcriptomics to characterize shared mechanisms in digestive diseases and psychiatric disorders. | Ding H et al. | β | 2025 | β |
| Integrating HiTOP and RDoC frameworks Part I: Genetic architecture of externalizing and internalizing psychopathology. | Davis CN et al. | β | 2025 | β |
| Integrating HiTOP and RDoC frameworks part II: shared and distinct biological mechanisms of externalizing and internalizing psychopathology. | Davis CN et al. | β | 2025 | β |
| Integrative neuroimmunology reveals leukocyte-expressing PAX6 as a critical predictor of major depressive disorder. | Dias HD et al. | β | 2025 | β |
| Interplay of psychological factors and bronchial asthma: a comprehensive review. | Verma AK et al. | β | 2025 | β |
| Investigating Irritability as a Potentially Causal Risk Pathway to Depression Using Two Genetically Informed Designs. | Shakeshaft A et al. | β | 2025 | β |
| Investigating the causal role of circulating metabolites in major depressive disorder. | Fu L et al. | β | 2025 | β |
| Large-scale transcriptomic analyses of major depressive disorder reveal convergent dysregulation of synaptic pathways in excitatory neurons. | Goes FS et al. | β | 2025 | β |
| Leveraging haplotype information in heritability estimation and polygenic prediction. | Meisner J et al. | β | 2025 | β |
| Linking Genome-Wide Association Studies to Pharmacological Treatments for Psychiatric Disorders. | Arnatkeviciute A et al. | β | 2025 | β |
| Long-term physical health conditions and youth anxiety and depression: Is there a causal link? | Shakeshaft A et al. | β | 2025 | β |
| Low Stability and Specificity of Polygenic Risk Scores for Major Psychiatric Disorders Limit Their Clinical Utility. | Mollon J et al. | β | 2025 | β |
| Measures of General Intelligence and Risk for Alcohol Use Disorder. | Capusan AJ et al. | β | 2025 | β |
| Mechanistic intersections between migraine and major depressive disorder. | Johnson M et al. | β | 2025 | β |
| MMDD: A Multimodal Multitask Dynamic Disentanglement Framework for Robust Major Depressive Disorder Diagnosis Across Neuroimaging Sites. | Chen Q et al. | β | 2025 | β |
| Multiancestry brain pQTL fine-mapping and integration with genome-wide association studies of 21 neurologic and psychiatric conditions. | Wingo AP et al. | β | 2025 | β |
| Multidimensional EEG features integration with feature selection strategy for precision diagnosis of depressive disorders. | Luo X et al. | β | 2025 | β |
| Multitrait Genetic Analysis Identifies Novel Pleiotropic Loci for Depression and Schizophrenia in East Asians. | Song Y et al. | β | 2025 | β |
| New perspectives on galectin in major depressive disorder treatment. | Peixoto LC et al. | β | 2025 | β |
| Not just old wine in new bottles: Polygenic liability for ADHD is associated with electrophysiological affective-motivational processing beyond anxiety, depression, and ODD. | Γgrez K et al. | β | 2025 | β |
| Novel Gene-Informed Regional Brain Targets for Clinical Screening for Major Depression. | Odierna GL et al. | β | 2025 | β |
| Optimism moderates the relationship between inflammatory polygenic risk and major depressive disorder in U.S. Military veterans. | Fischer IC et al. | β | 2025 | β |
| Overexpression of OTX2 in human neural cells links depression risk genes. | Feng Y et al. | β | 2025 | β |
| Polygenic and developmental profiles of autism differ by age at diagnosis. | Zhang X et al. | β | 2025 | β |
| Polygenic and pharmacogenomic contributions to medication dosing: a real-world longitudinal biobank study. | Kasela S et al. | β | 2025 | β |
| Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants. | Kanjira SC et al. | β | 2025 | β |
| Polygenic scores and symptom severity change after internet-delivered cognitive behaviour therapy for depression and anxiety. | BΓ€ckman J et al. | β | 2025 | β |
| Polygenic scores for depression are associated with indices of neighborhood adversity. | Feurer C et al. | β | 2025 | β |
| Predicting adolescent suicide risk using integrated data from adolescents, parents and siblings: An analysis of multiple machine learning models. | Niu W et al. | β | 2025 | β |
| Prevalences and differences of depressive symptomology among first-episode of depression and recurrent depression: An analysis of data from NSSD. | Huang J et al. | β | 2025 | β |
| Psychiatric genetics in the diverse landscape of Latin American populations. | Bruxel EM et al. | β | 2025 | β |
| Sex-Specific Association Between Polymorphisms in Estrogen Receptor Alpha Gene (ESR1) and Depression: A Genome-Wide Association Study of All of Us and UK Biobank Data. | Hu Y et al. | β | 2025 | β |
| Sexual Trauma, Polygenic Scores, and Mental Health Diagnoses and Outcomes. | Lake AM et al. | β | 2025 | β |
| Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus. | Guo X et al. | β | 2025 | β |
| Shared neuroimaging and molecular profiles in type 2 diabetes mellitus and major depressive disorder: an integrative analysis of genetic, transcriptomic, and neuroimaging data. | Xu J et al. | β | 2025 | β |
| Single-cell transcriptomics reveals Sox6 positive interneurons enriched in the prefrontal cortex of female mice vulnerable to chronic social stress. | Ma G et al. | β | 2025 | β |
| Single-nucleus chromatin accessibility profiling identifies cell types and functional variants contributing to major depression. | Chawla A et al. | β | 2025 | β |
| Specification of claustro-amygdalar and palaeocortical neurons and circuits. | Kaur N et al. | β | 2025 | β |
| SynaptopathyDB integrates synaptic proteomes, genetic and phenotypic data to advance research on nervous system disorders. | Sorokina O et al. | β | 2025 | β |
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| The Causal Relationships Between Inflammatory Proteins, Brain Structure, and Psychiatric Disorders: A Two-Step Mendelian Randomization Analysis. | Zhao L et al. | β | 2025 | β |
| The Genetic Architecture of the Human Corpus Callosum and its Subregions. | Bhatt RR et al. | β | 2025 | β |
| The genetic overlap between major depressive disorder, white blood cell counts and interleukin 6. | WistrΓΆm ED et al. | β | 2025 | β |
| The genetics of severe depression. | Franklin CE et al. | β | 2025 | β |
| The inflammatory and genetic mechanisms underlying the cumulative effect of co-occurring pain conditions on depression. | Jiang R et al. | β | 2025 | β |
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| Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies. | Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. Electronic address: andrew.mcintosh@ed.ac.uk et al. | β | 2025 | β |
| Transcriptomic pathology of neocortical microcircuit cell types across psychiatric disorders. | Arbabi K et al. | β | 2025 | β |
| Triangulated evidence provides no support for bidirectional causal pathways between diet/physical activity and depression/anxiety. | van Hooijdonk KJM et al. | β | 2025 | β |
| Unveiling causal relationship between white matter tracts and psychiatric disorders. | Yu Y et al. | β | 2025 | β |
| Unveiling the enigma of anxiety disorders and depression: from pathogenesis to treatment. | Pan HQ et al. | β | 2025 | β |
| Whole exome sequencing identified six novel genes for depressive symptoms. | Li ZY et al. | β | 2025 | β |
| Whole Genome Sequencing of Pedigrees With High Density of Substance Use and Psychiatric Disorders: A Meeting Report. | Hill SY et al. | β | 2025 | β |
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| Investigating the Shared Genetic Architecture Between Psychiatric Disorders and Executive Function. | Zhang S et al. | β | 2024 | β |
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