A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

Background: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors. / Methods: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared. / Results: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively. / Conclusions: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders

Empowerment and women in adventure tourism : a negotiated journey

Women’s participation in adventure tourism is growing, yet few studies have explored this group of tourists. This conceptual paper seeks to extend our understanding of female adventure tourists by examining the empowering journey women can take through constraint negotiation to enjoy the benefits of adventure tourism. Using content analysis to review the literature on women’s adventure experiences in tourism and recreation settings reveals prominent themes that have been consolidated to propose constraint, negotiation and benefit categories. A conceptual model is presented that illustrates the opportunities for women’s empowerment within these categories and examines the interrelationships and interdependency between them. The model shows that constraints, negotiations and benefits can be experienced simultaneously, at different points in a woman’s adventure tourism journey and used as a vehicle for empowerment. Women will also re-evaluate these categories before, during and after their adventure tourism experience. Therefore, the categories are not fixed and evolve each time a woman participates in adventure tourism throughout her life. Suggestions are made for further study in this under-researched area

Meta-analyses of genome-wide association studies for postpartum depression

Objective: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD. Method: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)–based heritability (), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system. Results: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD. Conclusions: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone)

Supplementary Material for: Comprehensive sex-stratified genetic analysis of 28 blood biomarkers and depression reveals a significant association between depression and low levels of total protein in females

Introduction Major depression (MD) is more common amongst women than men, and MD episodes have been associated with fluctuations in reproductive hormones amongst women. To investigate biological underpinnings of heterogeneity in MD, the associations between depression, stratified by sex and including perinatal depression (PND), and blood biomarkers, using UK Biobank (UKB) data, were evaluated, and extended to include the association of depression with biomarker polygenic scores (PGS), generated as proxy for each biomarker. Method Using female (N=39,761) and male (N=38,821) UKB participants, lifetime major depression (MD) and PND, were tested for association with 28 blood biomarkers. A GWAS was conducted for each biomarker and genetic correlations with depression subgroups were estimated. Using independent data from the Australian Genetics of Depression Study, PGS were constructed for each biomarker, and tested for association with depression status (n [female cases/controls]=9,006/6,442; n [male cases/controls]=3,106/6,222). Regions of significant local genetic correlation between depression subgroups and biomarkers highlighted by the PGS analysis were identified. Results Depression in females was significantly associated with levels of twelve biomarkers, including total protein (OR=0.90, CI=[0.86,0.94], P=3.9x10-6) and vitamin D (OR=0.94, CI=[0.90, 0.97], P=2.6x10-4), and PND with five biomarker levels, also including total protein (OR=0.88, CI=[0.81, 0.96], P=4.7x10-3). Depression in males was significantly associated with levels of eleven biomarkers. In the independent Australian Genetics of Depression Study, PGS analysis found significant associations for female depression and PND with total protein (female depression: OR=0.93, CI=[0.88, 0.98], P=3.6x10-3; PND: OR=0.91, CI=[0.86, 0.96], P=1.1x10-3), as well as with vitamin D (female depression: OR=0.93, CI=[0.89, 0.97], P=2.0x10-3; PND: OR=0.92, CI=[0.87, 0.97], P=1.4x10-3). The male depression sample did not report any significant results, and the point estimate of total protein (OR=0.98, CI=[0.92-1.04], P=4.7x10-1) did not indicate any association. Local genetic correlation analysis highlighted significant genetic correlation between PND and total protein, located in 5q13.3 (rG=0.68, CI=[0.33, 1.0], P=3.6x10-4). Discussion and Conclusion Multiple lines of evidence from genetic analysis highlight an association between total serum protein levels and depression in females. Further research involving prospective measurement of total protein and depressive symptoms is warranted