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. 2022 Apr;27(4):2206-2215.
doi: 10.1038/s41380-022-01469-y. Epub 2022 Feb 18.

Using phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder

Frank R Wendt  1   2 , Gita A Pathak  3   4 , Joseph D Deak  3   4 , Flavio De Angelis  3   4 , Dora Koller  3   4 , Brenda Cabrera-Mendoza  3   4 , Dannielle S Lebovitch  5   6   7   8 , Daniel F Levey  3   4 , Murray B Stein  9   10   11 , Henry R Kranzler  12   13 , Karestan C Koenen  14   15   16 , Joel Gelernter  3   4   17   18 , Laura M Huckins  5   6   7   8   19   20 , Renato Polimanti  21   22
Affiliations

Using phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder

Frank R Wendt et al. Mol Psychiatry. 2022 Apr.

Abstract

UK Biobank (UKB) is a key contributor in mental health genome-wide association studies (GWAS) but only ~31% of participants completed the Mental Health Questionnaire ("MHQ responders"). We predicted generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and major depression symptoms using elastic net regression in the ~69% of UKB participants lacking MHQ data ("MHQ non-responders"; NTraining = 50%; NTest = 50%), maximizing the informative sample for these traits. MHQ responders were more likely to be female, from higher socioeconomic positions, and less anxious than non-responders. Genetic correlation of GAD and PTSD between MHQ responders and non-responders ranged from 0.636 to 1.08; both were predicted by polygenic scores generated from independent cohorts. In meta-analyses of GAD (N = 489,579) and PTSD (N = 497,803), we discovered many novel genomic risk loci (13 for GAD and 40 for PTSD). Transcriptomic analyses converged on altered regulation of prenatal dorsolateral prefrontal cortex in these disorders. Our results provide one roadmap by which sample size and statistical power may be improved for gene discovery of incompletely ascertained traits in the UKB and other biobanks with limited mental health assessment.

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Conflict of interest statement

Competing Interests

Dr. Kranzler is a member of an advisory board for Dicerna Pharmaceuticals, a consultant to Sophrosyne Pharmaceuticals, a member of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which for the past three years was supported by AbbVie, Alkermes, Amygdala Neurosciences, Arbor, DIicerna, Ethypharm, Indivior, Lilly, Lundbeck, Otsuka, and Pfizer, and is paid for his editorial work on the journal Alcoholism: Clinical and Experimental Research. Drs. Kranzler and Gelernter are named as inventors on PCT patent application #15/878,640 entitled: “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. Dr. Stein is paid for his editorial work on the journals Biological Psychiatry and Depression and Anxiety, and the health professional reference Up-To-Date; he has also in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech, and has stock options in Oxeia Biopharmaceuticals and Epivario. Drs. Polimanti and Gelernter are paid for their editorial work on the journal Complex Psychiatry. The other authors have no competing interests to report.

Figures

Fig. 1 ∣
Fig. 1 ∣. Study design for understanding the genetic architectures of internalizing co-phenomes.
Features (i.e., comorbid phenotypes) were correlated with GAD-7, PCL-6, and PHQ-9. Outcomes were predicted using elastic net regression in two ways: (i) each quantitative outcome was predicted as the dependent variable in elastic net regression and (ii) elastic net regression weights were used to calculate a co-phenome risk score.
Fig. 2 ∣
Fig. 2 ∣. Verifying the concordant genetic architectures of true and predicted internalizing outcomes.
a, SNP-heritability (h2) of each internalizing outcome and the current largest unrelated sampling of a corresponding phenotype (GAD-2, PCL-17, and broad depression) after multi-trait conditioning with neuroticism. Each data point is the trait h2 point estimate and error bars represent the 95% confidence interval (CI) associated with each estimate. b, Genetic correlation (rg) within and between internalizing outcomes derived from the Mental Health Questionnaire (MHQ responders) and those predicted in the MHQ non-responders of the UKB before (bottom left triangle) and after (top right triangle) multi-trait conditioning with neuroticism. Pale text indicates a phenotype from the MHQ non-responders and dark text indicates a phenotype from the MHQ responders. Each rg heatmap contains a positive control with positive rg (largest Million Veteran Program (MVP) corresponding phenotype) and positive control with negative rg (subjective well-being) phenotype. All rgs survive multiple testing correction (FDR<0.05).
Fig. 3 ∣
Fig. 3 ∣. SNP annotation of GAD and PTSD GWAS.
The bottom row shows Manhattan plots for each trait. Two horizontal dashed lines in each plot show the genome-wide significance threshold per phenotype (P<5x10−8) and study-wide (Padj<1.25x10−8). Above each Manhattan plot are Combined Annotation Dependent Depletion (CADD) scores and RegulomeDB scores for each genome-wide significant locus.
Fig. 4 ∣
Fig. 4 ∣. Out-sample polygenic prediction of relevant phenotypes.
Maximum observed association (R2) between polygenic risk scores (PRS) for GAD and PTSD outcomes in this study and out-sample GAD and PTSD phenotypes from large consortia (ANGST, FinnGen, and PGC using summary-level PRS in PRSice v1.25, Panel A) and individual-level cohorts informative for mental health outcomes (Philadelphia Neurodevelopmental Cohort (PNC) and Yale-Penn using PRSice v2, Panel B).
Fig. 5 ∣
Fig. 5 ∣. Prenatal transcriptomic signatures of GAD and PTSD outcomes.
a, Enrichment of transcriptomic profiles from prenatal tissue based on BrainSpan 11 developmental stages. Each bar represents the results from one-sided tests for enrichment of a given transcriptomic profile. Effect size estimates (β) are color coded. Dashed horizontal lines indicate the significance threshold after multiple testing correction (FDR<0.05) across all tests. b, Manhattan plots of Hi-C coupled gene-based association studies of GAD and PTSD in fetal paracentral tissue. Each data point represents a single gene positionally aligned across each autosome. The height of each point along the y-axis indicates the significance of association between gene and phenotype with each colored data point indicating a significantly associated gene after analysis-wide multiple testing correction (P<9.43x10−7). A subset of genes are labeled and all genes are provided in Supplementary Table 16.
See this image and copyright information in PMC

References

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