Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.

Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.

The pathogenesis of Alzheimer's disease is complex. The amyloid hypothesis has directed research efforts for many years, but it has recently been questioned after failed drug trials. Here, we review the evidence for and against and suggest that it might be premature to abandon the amyloid hypothesis.

Objective This study used data from the South African Stress and Health Study (SASH) to examine both structural and attitudinal barriers to treatment initiation among South Africans with mental disorders and to investigate predictors of treatment dropout. Methods Face-to-face interviews were conducted with 4,315 adult South Africans living in households or hostel quarters. The interview included a core diagnostic assessment of past-12-month mental disorders and assessments of disorder severity, service use, and barriers to treatment. Multivariate logistic regression models were used to determine predictors of not seeking treatment in relation to disorder severity and sociodemographic characteristics, as well as factors that were predictive of premature treatment discontinuation by participants who had received mental health treatment in the previous 12 months. Predictors of dropout were identified by cross-tabulation and discrete-time survival analysis. Results Of the 4,315 adults, 729 (16.9% weighted) met criteria for a mental disorder in the past 12 months. Across all levels of severity, the most frequently cited reason for not seeking professional treatment was a low perceived need for treatment. Among those who recognized the need but did not access treatment during the past 12 months (7.2%), attitudinal barriers to treatment seeking were reported more commonly than structural barriers (100% and 34%, respectively). Of the 182 respondents who received treatment (25% weighted), 20% discontinued prematurely. Various factors, such as substance use disorders and absence of health insurance, increased the odds of treatment dropout. Conclusions Low rates of treatment seeking and high treatment dropout rates for common mental disorders among South Africans are a major concern. Public health efforts to improve treatment of mental disorders should consider the multiple influences on treatment initiation and discontinuation.

Background: Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD. Objective: This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration. Methods: We searched the literature from July 2008-July 2018 following PRISMA guidelines. Results: 57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes. Conclusion: PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.