Improving genetic prediction by leveraging genetic correlations among human diseases and traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait

Spiritual care may impact mental health and medication adherence in HIV+ populations

Valerie U Oji,1–3 Leslie C Hung,3 Reza Abbasgholizadeh,1,4 Flora Terrell Hamilton,5 E James Essien,6 Evaristus Nwulia7 1Lifefountain Center Ministries Inc, Houston, TX, USA; 2Feik School of Pharmacy, University of the Incarnate Word, San Antonio, TX, USA; 3University of Texas, College of Pharmacy, Austin, TX, USA; 4University of Houston, Houston, TX, USA; 5Administration, Family & Medical Counseling Service, Inc. (FMCS), Washington, DC, USA; 6University of Houston Institute for Community Health, Houston, TX, USA; 7Psychiatry, Howard University Translational Neuroscience Laboratory, Washington, DC, USA Objective: To explore a potential role for spirituality in medication-related needs assessment for integrated care in chronically ill populations. Method: A systematic literature review was conducted to explore the impact of faith beliefs on health and/or medication adherence in individuals with depression and/or HIV+/AIDS. Retrospective electronic medical record review of adult HIV+ patients of an urban primary care clinic with integrated mental health services was conducted, with Substance Abuse and Mental Illness Symptoms Screener (SAMISS), major depressive disorder (MDD) incidence over the preceding year, and history of contact with a spiritual advisor. A convenience sample was interviewed to qualitatively assess potential medication therapy management needs and medication-related problems. Another sample was examined utilizing the Daily Spiritual Experience Scale. Results: The literature reports positive influence on health behaviors, coping and outcomes; and poor medication adherence and treatment decisions due to patient passivity or resistance. Spiritual advisor contact (not limited to a specific religion) was significantly associated with MDD absence (1.7% vs. 15.3%, P<0.005) and inversely related to SAMISS, depression, and poor health behaviors. Patient interviews reflected significance of faith in terms of insight and acceptance of illness, the role or need for medications, coping, and medication adherence. An illustrative model was designed based on the literature and data collection. Conclusion: Spiritual assessment may help identify positive or negative influence on health. Spiritual interventions could be beneficial in promoting adherence and positive health outcomes. Further research is recommended. Keywords: HIV+/AIDS, mental illness, depression, spirituality and health, African Americans&nbsp

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of > 9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P= 5.87×10-9; odds ratio (OR)=1.12) and markers within ERBB2 (rs2517959, P= 4.53×10-9; OR=1.13). No significant X-chromosome associations were detected and Xlinked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS

Identification of Pathways for Bipolar Disorder: a Meta-analysis

Importance: Genome-wide investigations provide systematic information regarding the neurobiology of psychiatric disorders. Objective: To identify biological pathways that contribute to risk for bipolar disorder (BP) using genes with consistent evidence for association in multiple genome-wide association studies (GWAS). Data Sources: Four independent data sets with individual genome-wide data available in July 2011 along with all data sets contributed to the Psychiatric Genomics Consortium Bipolar Group by May 2012. A prior meta-analysis was used as a source for brain gene expression data. Study Selection: The 4 published GWAS were included in the initial sample. All independent BP data sets providing genome-wide data in the Psychiatric Genomics Consortium were included as a replication sample. Data Extraction and Synthesis: We identified 966 genes that contained 2 or more variants associated with BP at P < .05 in 3 of 4 GWAS data sets (n = 12 127 [5253 cases, 6874 controls]). Simulations using 10 000 replicates of these data sets corrected for gene size and allowed the calculation of an empirical P value for each gene; empirically significant genes were entered into a pathway analysis. Each of these pathways was then tested in the replication sample (n = 8396 [3507 cases, 4889 controls]) using gene set enrichment analysis for single-nucleotide polymorphisms. The 226 genes were also compared with results from a meta-analysis of gene expression in the dorsolateral prefrontal cortex. Main Outcomes and Measures: Empirically significant genes and biological pathways. Results: Among 966 genes, 226 were empirically significant (P < .05). Seventeen pathways were overrepresented in analyses of the initial data set. Six of the 17 pathways were associated with BP in both the initial and replication samples: corticotropin-releasing hormone signaling, cardiac β-adrenergic signaling, phospholipase C signaling, glutamate receptor signaling, endothelin 1 signaling, and cardiac hypertrophy signaling. Among the 226 genes, 9 differed in expression in the dorsolateral prefrontal cortex in patients with BP: CACNA1C, DTNA, FOXP1, GNG2, ITPR2, LSAMP, NPAS3, NCOA2, and NTRK3. Conclusions and Relevance: Pathways involved in the genetic predisposition to BP include hormonal regulation, calcium channels, second messenger systems, and glutamate signaling. Gene expression studies implicate neuronal development pathways as well. These results tend to reinforce specific hypotheses regarding BP neurobiology and may provide clues for new approaches to treatment and prevention