Association of retinoic acid receptor genes with meningomyelocele.

BACKGROUND: Neural tube defects (NTDs) occur in as many as 0.5-2 per 1000 live births in the United States. One of the most common and severe neural tube defects is meningomyelocele (MM) resulting from failed closure of the caudal end of the neural tube. MM has been induced by retinoic acid teratogenicity in rodent models. We hypothesized that genetic variants influencing retinoic acid (RA) induction via retinoic acid receptors (RARs) may be associated with risk for MM. METHODS: We analyzed 47 single nucleotide polymorphisms (SNPs) that span across the three retinoic acid receptor genes using the SNPlex genotyping platform. Our cohort consisted of 610 MM families. RESULTS: One variant in the RARA gene (rs12051734), three variants in the RARB gene (rs6799734, rs12630816, rs17016462), and a single variant in the RARG gene (rs3741434) were found to be statistically significant at p \u3c 0.05. CONCLUSION: RAR genes were associated with risk for MM. For all associated SNPs, the rare allele conferred a protective effect for MM susceptibility

Association of folate receptor (FOLR1, FOLR2, FOLR3) and reduced folate carrier (SLC19A1) genes with meningomyelocele.

BACKGROUND: Meningomyelocele (MM) results from lack of closure of the neural tube during embryologic development. Periconceptional folic acid supplementation is a modifier of MM risk in humans, leading toan interest in the folate transport genes as potential candidates for association to MM. METHODS: This study used the SNPlex Genotyping (ABI, Foster City, CA) platform to genotype 20 single polymorphic variants across the folate receptor genes (FOLR1, FOLR2, FOLR3) and the folate carrier gene (SLC19A1) to assess their association to MM. The study population included 329 trio and 281 duo families. Only cases with MM were included. Genetic association was assessed using the transmission disequilibrium test in PLINK. RESULTS: A variant in the FOLR2 gene (rs13908), three linked variants in the FOLR3 gene (rs7925545, rs7926875, rs7926987), and two variants in the SLC19A1 gene (rs1888530 and rs3788200) were statistically significant for association to MM in our population. CONCLUSION: This study involved the analyses of selected single nucleotide polymorphisms across the folate receptor genes and the folate carrier gene in a large population sample. It provided evidence that the rare alleles of specific single nucleotide polymorphisms within these genes appear to be statistically significant for association to MM in the patient population that was tested

GEM: Scalable and flexible gene-environment interaction analysis in millions of samples

MOTIVATION: Gene-environment interaction (GEI) studies are a general framework that can be used to identify genetic variants that modify the effects of environmental, physiological, lifestyle or treatment effects on complex traits. Moreover, accounting for GEIs can enhance our understanding of the genetic architecture of complex diseases and traits. However, commonly used statistical software programs for GEI studies are either not applicable to testing certain types of GEI hypotheses or have not been optimized for use in large samples. RESULTS: Here, we develop a new software program, GEM (Gene-Environment interaction analysis in Millions of samples), which supports the inclusion of multiple GEI terms, adjustment for GEI covariates and robust inference, while allowing multi-threading to reduce computation time. GEM can conduct GEI tests as well as joint tests of genetic main and interaction effects for both continuous and binary phenotypes. Through simulations, we demonstrate that GEM scales to millions of samples while addressing limitations of existing software programs. We additionally conduct a gene-sex interaction analysis on waist-hip ratio in 352 768 unrelated individuals from the UK Biobank, identifying 24 novel loci in the joint test that have not previously been reported in combined or sex-specific analyses. Our results demonstrate that GEM can facilitate the next generation of large-scale GEI studies and help advance our understanding of the genetic architecture of complex diseases and traits. AVAILABILITY AND IMPLEMENTATION: GEM is freely available as an open source project at https://github.com/large-scale-gxe-methods/GEM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

The impact of multiple single day blood pressure readings on cardiovascular risk estimation: The Atherosclerosis Risk in Communities study

To determine the magnitude of change in estimated cardiovascular disease risk when multiple same day blood pressure measurements are used in estimating coronary heart disease (CHD), heart failure (HF) and stroke risks

Comprehensive linkage and linkage heterogeneity analysis of 4344 sibling pairs affected with hypertension from the Family Blood Pressure Program

Linkage analyses of complex, multifactorial traits and diseases, such as essential hypertension, have been difficult to interpret and reconcile. Many published studies provide evidence suggesting that different genes and genomic regions influence hypertension, but knowing which of these studies reflect true positive results is challenging. The reasons for this include the diversity of analytical methods used across these studies, the different samples and sample sizes in each study, and the complicated biological underpinnings of hypertension. We have undertaken a comprehensive linkage analysis of 371 autosomal microsatellite markers genotyped on 4,334 sibling pairs affected with hypertension from five ethnic groups sampled from 13 different field centers associated with the Family Blood Pressure Program (FBPP). We used a single analytical technique known to be robust to interpretive problems associated with a lack of completely informative markers to assess evidence for linkage to hypertension both within and across the ethnic groups and field centers. We find evidence for linkage to a number of genomic regions, with the most compelling evidence from analyses that combine data across field center and ethnic groups (e.g., chromosomes 2 and 9). We also pursued linkage analyses that accommodate locus heterogeneity, which is known to plague the identification of disease susceptibility loci in linkage studies of complex diseases. We find evidence for linkage heterogeneity on chromosomes 2 and 17. Ultimately our results suggest that evidence for linkage heterogeneity can only be detected with large sample sizes, such as the FBPP, which is consistent with theoretical sample size calculations. Genet. Epidemiol . 2007. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56011/1/20202_ftp.pd

GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk

Male pattern baldness (MPB) or androgenetic alopecia is one of the most common conditions affecting men, reaching a prevalence of similar to 50% by the age of 50; however, the known genes explain little of the heritability. Here, we present the results of a genome-wide association study including more than 70,000 men, identifying 71 independently replicated loci, of which 30 are novel. These loci explain 38% of the risk, suggesting that MPB is less genetically complex than other complex traits. We show that many of these loci contain genes that are relevant to the pathology and highlight pathways and functions underlying baldness. Finally, despite only showing genome-wide genetic correlation with height, pathway-specific genetic correlations are significant for traits including lifespan and cancer. Our study not only greatly increases the number of MPB loci, illuminating the genetic architecture, but also provides a new approach to disentangling the shared biological pathways underlying complex diseases

Coronary heart disease and ischemic stroke polygenic risk scores and atherosclerotic cardiovascular disease in a diverse, population-based cohort study

The predictive ability of coronary heart disease (CHD) and ischemic stroke (IS) polygenic risk scores (PRS) have been evaluated individually, but whether they predict the combined outcome of atherosclerotic cardiovascular disease (ASCVD) remains insufficiently researched. It is also unclear whether associations of the CHD and IS PRS with ASCVD are independent of subclinical atherosclerosis measures. 7,286 White and 2,016 Black participants from the population-based Atherosclerosis Risk in Communities study who were free of cardiovascular disease and type 2 diabetes at baseline were included. We computed previously validated CHD and IS PRS consisting of 1,745,179 and 3,225,583 genetic variants, respectively. Cox proportional hazards models were used to test the association between each PRS and ASCVD, adjusting for traditional risk factors, ankle-brachial index, carotid intima media thickness, and carotid plaque. The hazard ratios (HR) for the CHD and IS PRS were significant with HR of 1.50 (95% CI: 1.36–1.66) and 1.31 (95% CI: 1.18–1.45) respectively for the risk of incident ASCVD per standard deviation increase in CHD and IS PRS among White participants after adjusting for traditional risk factors. The HR for the CHD PRS was not significant with an HR of 0.95 (95% CI: 0.79–1.13) for the risk of incident ASCVD in Black participants. The HR for the IS PRS was significant with an HR of 1.26 (95%CI: 1.05–1.51) for the risk of incident ASCVD in Black participants. The association of the CHD and IS PRS with ASCVD was not attenuated in White participants after adjustment for ankle-brachial index, carotid intima media thickness, and carotid plaque. The CHD and IS PRS do not cross-predict well, and predict better the outcome for which they were created than the composite ASCVD outcome. Thus, the use of the composite outcome of ASCVD may not be ideal for genetic risk prediction

Identification of Novel and Rare Variants Associated with Handgrip Strength Using Whole Genome Sequence Data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings