Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a needĀ for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity. We find that obesity results in profound perturbation of the metabolome; nearly a third of the assayed metabolites associated with changes in BMI. A metabolome signature identifies the healthy obese and lean individuals with abnormal metabolomes-these groups differ in health outcomes and underlying genetic risk. Specifically, an abnormal metabolome associated with a 2- to 5-fold increase in cardiovascular events when comparing individuals who were matched for BMI but had opposing metabolome signatures. Because metabolome profiling identifies clinically meaningful heterogeneity in obesity, this approach could help select patients for clinical trials.
Pubmed ID: 30318341
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Curated database of known (published) gene lesions responsible for human inherited disease.
View all literature mentionsA web-based hosting service for software development projects that use the Git revision control system offering powerful collaboration, code review, and code management. It offers both paid plans for private repositories, and free accounts for open source projects. Large or small, every repository comes with the same powerful tools. These tools are open to the community for public projects and secure for private projects. Features include: * Integrated issue tracking * Collaborative code review * Easily manage teams within organizations * Text entry with understated power * A growing list of programming languages and data formats * On the desktop and in your pocket - Android app and mobile web views let you keep track of your projects on the go.
View all literature mentionsCloud-based data repository for storing, publishing and accessing scientific data. Mendeley Data creates a permanent location and issues Force 11 compliant citations for uploaded data.
View all literature mentionsCurated database of known (published) gene lesions responsible for human inherited disease.
View all literature mentionsSoftware environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.
View all literature mentionsArchive of aggregated information about sequence variation and its relationship to human health. Provides reports of relationships among human variations and phenotypes along with supporting evidence. Submissions from clinical testing labs, research labs, locus-specific databases, expert panels and professional societies are welcome. Collects reports of variants found in patient samples, assertions made regarding their clinical significance, information about submitter, and other supporting data. Alleles described in submissions are mapped to reference sequences, and reported according to HGVS standard.
View all literature mentionsDatabase that aggregates exome and genome sequencing data from large-scale sequencing projects. The gnomAD data set contains individuals sequenced using multiple exome capture methods and sequencing chemistries. Raw data from the projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects.
View all literature mentionsFaST-LMM (Factored Spectrally Transformed Linear Mixed Models) is a set of tools for efficiently performing genome-wide association studies (GWAS), prediction, and heritability estimation on large data sets.
View all literature mentions