Investigating the complex genetic architecture of ankle-brachial index, a measure of peripheral arterial disease, in non-Hispanic whites

<p>Abstract</p> <p>Background</p> <p>Atherosclerotic peripheral arterial disease (PAD) affects 8–10 million people in the United States and is associated with a marked impairment in quality of life and an increased risk of cardiovascular events. Noninvasive assessment of PAD is performed by measuring the ankle-brachial index (ABI). Complex traits, such as ABI, are influenced by a large array of genetic and environmental factors and their interactions. We attempted to characterize the genetic architecture of ABI by examining the main and interactive effects of individual single nucleotide polymorphisms (SNPs) and conventional risk factors.</p> <p>Methods</p> <p>We applied linear regression analysis to investigate the association of 435 SNPs in 112 positional and biological candidate genes with ABI and related physiological and biochemical traits in 1046 non-Hispanic white, hypertensive participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. The main effects of each SNP, as well as SNP-covariate and SNP-SNP interactions, were assessed to investigate how they contribute to the inter-individual variation in ABI. Multivariable linear regression models were then used to assess the joint contributions of the top SNP associations and interactions to ABI after adjustment for covariates. We reduced the chance of false positives by 1) correcting for multiple testing using the false discovery rate, 2) internal replication, and 3) four-fold cross-validation.</p> <p>Results</p> <p>When the results from these three procedures were combined, only two SNP main effects in <it>NOS3</it>, three SNP-covariate interactions (<it>ADRB2 </it>Gly 16 – lipoprotein(a) and <it>SLC4A5 </it>– diabetes interactions), and 25 SNP-SNP interactions (involving SNPs from 29 different genes) were significant, replicated, and cross-validated. Combining the top SNPs, risk factors, and their interactions into a model explained nearly 18% of variation in ABI in the sample. SNPs in six genes (<it>ADD2, ATP6V1B1, PRKAR2B, SLC17A2, SLC22A3, and TGFB3</it>) were also influencing triglycerides, C-reactive protein, homocysteine, and lipoprotein(a) levels.</p> <p>Conclusion</p> <p>We found that candidate gene SNP main effects, SNP-covariate and SNP-SNP interactions contribute to the inter-individual variation in ABI, a marker of PAD. Our findings underscore the importance of conducting systematic investigations that consider context-dependent frameworks for developing a deeper understanding of the multidimensional genetic and environmental factors that contribute to complex diseases.</p

The eMERGE Network: A consortium of biorepositories linked to electronic medical records data for conducting genomic studies

<p>Abstract</p> <p>Introduction</p> <p>The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record (EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors.</p> <p>Organization</p> <p>The five sites are supported by an Administrative Coordinating Center. Setting of network goals is initiated by working groups: (1) Genomics, (2) Informatics, and (3) Consent & Community Consultation, which also includes active participation by investigators outside the eMERGE funded sites, and (4) Return of Results Oversight Committee. The Steering Committee, comprised of site PIs and representatives and NHGRI staff, meet three times per year, once per year with the External Scientific Panel.</p> <p>Current progress</p> <p>The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in ≈2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped. Funded by ARRA supplements, secondary phenotypes have been added at all sites to leverage the genotyping data, and hypothyroidism is being analyzed as a cross-network phenotype. Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site.</p> <p>Future activities</p> <p>Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care.</p> <p>Summary</p> <p>By combining advanced clinical informatics, genome science, and community consultation, eMERGE represents a first step in the development of data-driven approaches to incorporate genomic information into routine healthcare delivery.</p

Patterns of population differentiation of candidate genes for cardiovascular disease

<p>Abstract</p> <p>Background</p> <p>The basis for ethnic differences in cardiovascular disease (CVD) susceptibility is not fully understood. We investigated patterns of population differentiation (<it>F</it>_<it>ST</it>) of a set of genes in etiologic pathways of CVD among 3 ethnic groups: Yoruba in Nigeria (YRI), Utah residents with European ancestry (CEU), and Han Chinese (CHB) + Japanese (JPT). We identified 37 pathways implicated in CVD based on the PANTHER classification and 416 genes in these pathways were further studied; these genes belonged to 6 biological processes (apoptosis, blood circulation and gas exchange, blood clotting, homeostasis, immune response, and lipoprotein metabolism). Genotype data were obtained from the HapMap database.</p> <p>Results</p> <p>We calculated <it>F</it>_{<it>ST </it>}for 15,559 common SNPs (minor allele frequency ≥ 0.10 in at least one population) in genes that co-segregated among the populations, as well as an average-weighted <it>F</it>_{<it>ST </it>}for each gene. SNPs were classified as putatively functional (non-synonymous and untranslated regions) or non-functional (intronic and synonymous sites). Mean <it>F</it>_{<it>ST </it>}values for common putatively functional variants were significantly higher than <it>F</it>_{<it>ST </it>}values for nonfunctional variants. A significant variation in <it>F</it>_{<it>ST </it>}was also seen based on biological processes; the processes of 'apoptosis' and 'lipoprotein metabolism' showed an excess of genes with high <it>F</it>_<it>ST</it>. Thus, putative functional SNPs in genes in etiologic pathways for CVD show greater population differentiation than non-functional SNPs and a significant variance of <it>F</it>_{<it>ST </it>}values was noted among pairwise population comparisons for different biological processes.</p> <p>Conclusion</p> <p>These results suggest a possible basis for varying susceptibility to CVD among ethnic groups.</p

A Clinical Decision Support Tool for Familial Hypercholesterolemia Based on Physician Input

Objective: To develop clinical decision support (CDS) for familial hypercholesterolemia (FH), based on physician input obtained by a mixed methods approach. Introduction: Awareness, detection, and control of FH—a relatively common genetic disorder—is low. Clinical decision support could address knowledge gaps and provide point-of-care guidance for the management of FH. Methods: A 16-question survey that assessed familiarity with FH and sought input on potential content of the CDS tool was emailed to 1161 clinicians including 208 cardiologists. In addition, 4 physician focus groups were held to gather input on the structure and form of the CDS tool. This study took place between September 12, 2016, and January 16, 2017. Results: The response rate to the survey was 18.1%. Clinicians were overwhelmingly (97.6%) in favor of a CDS tool that assists in managing patients with FH at the point of care and this was confirmed in the focus group discussions. Key themes emerged during the focus groups including providers' knowledge and understanding of FH, facilitators and barriers to implementing a CDS tool, and suggestions for its design and content. Conclusion: Clinicians were supportive of development of a CDS tool to assist with the evaluation and treatment of FH and provided feedback related to the design and implementation of such a tool

Establishment of Specialized Clinical Cardiovascular Genetics Programs: Recognizing the Need and Meeting Standards: A Scientific Statement From the American Heart Association.

Cardiovascular genetics is a rapidly evolving subspecialty within cardiovascular medicine, and its growth is attributed to advances in genome sequencing and genetic testing and the expanding understanding of the genetic basis of multiple cardiac conditions, including arrhythmias (channelopathies), heart failure (cardiomyopathies), lipid disorders, cardiac complications of neuromuscular conditions, and vascular disease, including aortopathies. There have also been great advances in clinical diagnostic methods, as well as in therapies to ameliorate symptoms, slow progression of disease, and mitigate the risk of adverse outcomes. Emerging challenges include interpretation of genetic test results and the evaluation, counseling, and management of genetically at-risk family members who have inherited pathogenic variants but do not yet manifest disease. With these advances and challenges, there is a need for specialized programs combining both cardiovascular medicine and genetics expertise. The integration of clinical cardiovascular findings, including those obtained from physical examination, imaging, and functional assessment, with genetic information allows for improved diagnosis, prognostication, and cascade family testing to identify and to manage risk, and in some cases to provide genotype-specific therapy. This emerging subspecialty may ultimately require a new cardiovascular subspecialist, the genetic cardiologist, equipped with these combined skills, to permit interpretation of genetic variation within the context of phenotype and to extend the utility of genetic testing. This scientific statement outlines current best practices for delivering cardiovascular genetic evaluation and care in both the pediatric and the adult settings, with a focus on team member expertise and conditions that most benefit from genetic evaluation