Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase

Analysis and visualization of Arabidopsis thaliana GWAS using web 2.0 technologies

With large-scale genomic data becoming the norm in biological studies, the storing, integrating, viewing and searching of such data have become a major challenge. In this article, we describe the development of an Arabidopsis thaliana database that hosts the geographic information and genetic polymorphism data for over 6000 accessions and genome-wide association study (GWAS) results for 107 phenotypes representing the largest collection of Arabidopsis polymorphism data and GWAS results to date. Taking advantage of a series of the latest web 2.0 technologies, such as Ajax (Asynchronous JavaScript and XML), GWT (Google-Web-Toolkit), MVC (Model-View-Controller) web framework and Object Relationship Mapper, we have created a web-based application (web app) for the database, that offers an integrated and dynamic view of geographic information, genetic polymorphism and GWAS results. Essential search functionalities are incorporated into the web app to aid reverse genetics research. The database and its web app have proven to be a valuable resource to the Arabidopsis community. The whole framework serves as an example of how biological data, especially GWAS, can be presented and accessed through the web. In the end, we illustrate the potential to gain new insights through the web app by two examples, showcasing how it can be used to facilitate forward and reverse genetics research. Database URL: http://arabidopsis.usc.edu

Polygenic risk score, parental socioeconomic status, family history of psychiatric disorders, and the risk for schizophrenia: a Danish population-based study and meta-analysis

IMPORTANCE Schizophrenia has a complex etiology influenced both by genetic and nongenetic factors but disentangling these factors is difficult. OBJECTIVE To estimate (1) how strongly the risk for schizophrenia relates to the mutual effect of the polygenic risk score, parental socioeconomic status, and family history of psychiatric disorders; (2) the fraction of cases that could be prevented if no one was exposed to these factors; (3) whether family background interacts with an individual's genetic liability so that specific subgroups are particularly risk prone; and (4) to what extent a proband's genetic makeup mediates the risk associated with familial background. DESIGN, SETTINGS, AND PARTICIPANTS We conducted a nested case-control study based onDanish population-based registers. The study consisted of 866 patients diagnosed as having schizophrenia between January 1, 1994, and December 31, 2006, and 871 matched control individuals. Genome-wide data and family psychiatric and socioeconomic background information were obtained from neonatal biobanks and national registers. Results from a separate meta-analysis (34 600 cases and 45 968 control individuals) were applied to calculate polygenic risk scores. EXPOSURES Polygenic risk scores, parental socioeconomic status, and family psychiatric history. MAIN OUTCOMES AND MEASURES Odds ratios (ORs), attributable risks, liability R2 values, and proportions mediated. RESULTS Schizophrenia was associated with the polygenic risk score (OR, 8.01; 95%CI, 4.53-14.16 for highest vs lowest decile), socioeconomic status (OR, 8.10; 95%CI, 3.24-20.3 for 6 vs no exposures), and a history of schizophrenia/psychoses (OR, 4.18; 95%CI, 2.57-6.79). The R2 values were 3.4%(95%CI, 2.1-4.6) for the polygenic risk score, 3.1%(95%CI, 1.9-4.3) for parental socioeconomic status, and 3.4%(95%CI, 2.1-4.6) for family history. Socioeconomic status and psychiatric history accounted for 45.8% (95%CI, 36.1-55.5) and 25.8% (95%CI, 21.2-30.5) of cases, respectively. There was an interaction between the polygenic risk score and family history (P = .03). A total of 17.4%(95%CI, 9.1-26.6) of the effect associated with family history of schizophrenia/psychoses was mediated through the polygenic risk score. CONCLUSIONS AND RELEVANCE Schizophrenia was associated with the polygenic risk score, family psychiatric history, and socioeconomic status. Our study demonstrated that family history of schizophrenia/psychoses is partly mediated through the individual's genetic liability

Social inequalities in changes in health-related behaviour among Slovak adolescents aged between 15 and 19: A longitudinal study

<p>Abstract</p> <p>Background</p> <p>Lower socioeconomic position is generally associated with higher rates of smoking and alcohol consumption and lower levels of physical activity. Health-related behaviour is usually established during late childhood and adolescence. The aim of this study is to explore changes in health-related behaviour in a cohort of adolescents aged between 15 and 19, overall and by socioeconomic position.</p> <p>Methods</p> <p>The sample consisted of 844 first-year students (42.8% males, baseline in 1998 – mean age 14.9, follow-up in 2002 – mean age 18.8) from 31 secondary schools located in Kosice, Slovakia. This study focuses on changes in adolescents' smoking, alcohol use, experience with marijuana and lack of physical exercise with regard to their socioeconomic position. Four indicators of socioeconomic position were used – adolescents' current education level and employment status, and the highest education level and highest occupational status of their parents. We first made cross tabulations of HRB with these four indicators, using McNemar's test to assess differences. Next, we used logistic regression to assess adjusted associations, using likelihood ratio tests to assess statistical significance.</p> <p>Results</p> <p>Statistically significant increases were found in all health-related behaviours. Among males, the most obvious socioeconomic gradient was found in smoking, both at age 15 and at 19. Variations in socioeconomic differences in health-related behaviour were more apparent among females. Although at age 15, almost no socioeconomic differences in health-related behaviour were found, at age 19 differences were found for almost all socioeconomic indicators. Among males, only traditional socioeconomic gradients were found (the lower the socioeconomic position, the higher the prevalence of potentially harmful health-related behaviour), while among females reverse socioeconomic gradients were also found.</p> <p>Conclusion</p> <p>We confirmed an increase in unhealthy health-related behaviour during adolescence. This increase was related to socioeconomic position, and was more apparent in females.</p

Quantifying Missing Heritability at Known GWAS Loci

Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain 1.29 X more heritability than GWAS-associated SNPs on average (P = 3.3 X 10[superscript -5]). For some diseases, this increase was individually significant:2.07 X for Multiple Sclerosis (MS) (P = 6.5 X 10 [superscript -9]) and for Crohn's Disease (CD) (P = 1.3 X 10[superscript -3]); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained 7.15 X more MS heritability than known MS SNPs (P 20,000 Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with 2.37 X more heritability from all SNPs at GWAS loci (P = 2.3 X 10[superscript -6]) and more heritability from all autoimmune disease loci (P < 1 X 10[superscript -16]) compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.National Institutes of Health (U.S.) (Grant R03HG006731)National Institutes of Health (U.S.) (Fellowship F32GM106584

Monitoring activities of teenagers to comprehend their habits: study protocol for a mixed-methods cohort study

Abstract: Background: Efforts to increase physical activity in youth need to consider which activities are most likely to be sustained over time in order to promote lifelong participation in physical activity. The Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study is a prospective cohort study that uses quantitative and qualitative methods to develop new knowledge on the sustainability of specific physical activities. Methods/design: Eight hundred and forty-three grade 5 and 6 students recruited from 17 elementary schools in New Brunswick, Canada, are followed-up three times per year. At each survey cycle, participants complete self-report questionnaires in their classroom under the supervision of trained data collectors. A sub-sample of 24 physically active students is interviewed annually using a semi-structured interview protocol. Parents (or guardians) complete telephone administered questionnaires every two years, and a health and wellness school audit is completed for each school. Discussion: MATCH will provide a description of the patterns of participation in specific physical activities in youth, and enable identification of the determinants of maintenance, decline, and uptake of participation in each activity. These data will inform the development of interventions that take into account which activities are the most likely to be maintained and why activities are maintained or dropped

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth

This is the final version. Available on open access from Nature Research via the DOI in this record. Data availability: Individual cohorts contributing to the meta-analysis should be contacted directly as each cohort has different data access policies. GWAS summary statistics from this study are available via the EGG website (https://egg-consortium.org/placental-weight-2023.html, https://www.ebi.ac.uk/gwas/), as well as the GWAS catalog (https://www.ebi.ac.uk/gwas/, accession numbers GCST90275189, GCST90275190, GCST90275191, GCST90275192, GCST90275193, GCST90275194, GCST90275195, GCST90275196, GCST90275197, GCST90275198, GCST90275199). Access to personal-level information from Gen3G (including methylation array data) is subject to controlled access according to participants’ consent concerning sharing of personal data. Request for conditions of access and for data access should be addressed to Center Hospitalier Universitaire de Sherbrooke institutional ethics committee: [email protected] availability: Analysis code is available from https://github.com/EarlyGrowthGenetics/placental_weight_codeA well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth.Wellcome Trus