Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19

Background The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data. Methods GAW19 data were donated by the T2D-GENES Consortium and the San Antonio Family Heart Study and included whole genome and exome sequences for odd-numbered autosomes, measures of gene expression, systolic and diastolic blood pressures, and related covariates in two Mexican American samples. These two samples were a collection of 20 large families with whole genome sequence and transcriptomic data and a set of 1943 unrelated individuals with exome sequence. For each sample, simulated phenotypes were constructed based on the real sequence data. ‘Functional’ genes and variants for the simulations were chosen based on observed correlations between gene expression and blood pressure. The simulations focused primarily on additive genetic models but also included a genotype-by-medication interaction. A total of 245 genes were designated as ‘functional’ in the simulations with a few genes of large effect and most genes explaining \u3c 1 % of the trait variation. An additional phenotype, Q1, was simulated to be correlated among related individuals, based on theoretical or empirical kinship matrices, but was not associated with any sequence variants. Two hundred replicates of the phenotypes were simulated. The GAW19 data are an expansion of the data used at GAW18, which included the family-based whole genome sequence, blood pressure, and simulated phenotypes, but not the gene expression data or the set of 1943 unrelated individuals with exome sequence

An epigenome-wide association study identifies multiple DNA methylation markers of exposure to endocrine disruptors

Background: Exposure to environmental endocrine disrupting chemicals (EDCs) may play an important role in the epidemic of metabolic diseases. Epigenetic alterations may functionally link EDCs with gene expression and metabolic traits. Objectives: We aimed to evaluate metabolic-related effects of the exposure to endocrine disruptors including five parabens, three bisphenols, and 13 metabolites of nine phthalates as measured in 24-hour urine on epigenome-wide DNA methylation. Methods: A blood-based epigenome-wide association study was performed in 622 participants from the Lifelines DEEP cohort using Illumina Infinium HumanMethylation450 methylation data and EDC excretions in 24-hour urine. Out of the 21 EDCs, 13 compounds were detected in >75% of the samples and, together with bisphenol F, were included in these analyses. Furthermore, we explored the putative function of identified methylation markers and their correlations with metabolic traits. Results: We found 20 differentially methylated cytosine-phosphate-guanines (CpGs) associated with 10 EDCs at suggestive p-value < 1 × 10−6, of which four, associated with MEHP and MEHHP, were genome-wide significant (Bonferroni-corrected p-value < 1.19 × 10−7). Nine out of 20 CpGs were significantly associated with at least one of the tested metabolic traits, such as fasting glucose, glycated hemoglobin, blood lipids, and/or blood pressure. 18 out of 20 EDC-associated CpGs were annotated to genes functionally related to metabolic syndrome, hypertension, obesity, type 2 diabetes, insulin resistance and glycemic traits. Conclusions: The identified DNA methylation markers for exposure to the most common EDCs provide suggestive mechanism underlying the contributions of EDCs to metabolic health. Follow-up studies are needed to unravel the causality of EDC-induced methylation changes in metabolic alterations

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in &gt;100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P &lt; 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD

Incidence, mortality and survival patterns of prostate cancer among residents in Singapore from 1968 to 2002

<p>Abstract</p> <p>Background</p> <p>From 1968 to 2002, Singapore experienced an almost four-fold increase in prostate cancer incidence. This paper examines the incidence, mortality and survival patterns for prostate cancer among all residents in Singapore from 1968 to 2002.</p> <p>Methods</p> <p>This is a retrospective population-based cohort study including all prostate cancer cases aged over 20 (n = 3613) reported to the Singapore Cancer Registry from 1968 to 2002. Age-standardized incidence, mortality rates and 5-year Relative Survival Ratios (RSRs) were obtained for each 5-year period. Follow-up was ascertained by matching with the National Death Register until 2002. A weighted linear regression was performed on the log-transformed age-standardized incidence and mortality rates over period.</p> <p>Results</p> <p>The percentage increase in the age-standardized incidence rate per year was 5.0%, 5.6%, 4.0% and 1.9% for all residents, Chinese, Malays and Indians respectively. The percentage increase in age-standardized mortality rate per year was 5.7%, 6.0%, 6.6% and 2.5% for all residents, Chinese, Malays and Indians respectively. When all Singapore residents were considered, the RSRs for prostate cancer were fairly constant across the study period with slight improvement from 1995 onwards among the Chinese.</p> <p>Conclusion</p> <p>Ethnic differences in prostate cancer incidence, mortality and survival patterns were observed. There has been a substantial improvement in RSRs since the 1990s for the Chinese.</p

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Haploinsufficiency of CYP8B1 associates with increased insulin sensitivity in humans

10.1172/JCI152961The Journal of clinical investigation13221e152961

An atlas of genetic scores to predict multi-omic traits

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics. Here we examine a large cohort (the INTERVAL study; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores

Metadherin Contributes to the Pathogenesis of Diffuse Large B-cell Lymphoma

BACKGROUND: Metadherin (MTDH) has been demonstrated as a potentially crucial mediator of various types of human malignancies. However, the expression and role of MTDH in diffuse large-B-cell lymphoma (DLBCL) have not been reported yet. This study aimed to illuminate the role of MTDH in the pathogenesis of DLBCL. METHODOLOGY/PRINCIPAL FINDINGS: A remarkable elevation of MTDH on mRNA level was detected in DLBCL tissues by quantitative polymerase chain reaction (PCR). Using Western-blot analysis we found that the expression of MTDH protein was significantly upregulated in DLBCL cell lines and DLBCL tissues compared with peripheral blood mononuclear cells (PBMCs) from healthy samples and tissues from patients of reactive hyperplasia of lymph node. The results showed high expression of MTDH in 23 of 30 (76.67%) DLBCL tissues by using immunohistochemical analysis and the over expression of MTDH was strongly correlated to the clinical staging of patients with DLBCL (P<0.05). Furthermore, the finding suggested that the increase of MTDH in DLBCL cells could distinctly enhance cell proliferation and inhibit cell apoptosis; meanwhile, inhibition of MTDH expression by specific siRNA clearly enhanced LY8 cell apoptosis. Upregulation of MTDH elevated the protein level of total β-catenin and translocation of β-catenin to the nucleus directly or indirectly. Knockdown of MTDH decreased the level of total, cytoplasmic β-catenin and reduced nuclear accumulation of β-catenin protein. This indicated that the function of MTDH on the development of DLBCL was mediated through regulation of Wnt/β-catenin signaling pathway. CONCLUSIONS/SIGNIFICANCE: Our results suggest that MTDH contributes to the pathogenesis of DLBCL mediated by activation of Wnt/β-catenin pathway. This novel study may contribute to further investigation on the useful biomarkers and potential therapeutic target in the DLBCL patients

Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure

OBJECTIVE: We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP).METHODS: We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses.RESULTS: We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction &lt; 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P = 4e-273) and cis-DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSION: We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.</p