{"id":6,"date":"2024-08-19T15:03:19","date_gmt":"2024-08-19T19:03:19","guid":{"rendered":"https:\/\/sites.bu.edu\/dhanm-lab\/news\/"},"modified":"2024-08-22T14:51:32","modified_gmt":"2024-08-22T18:51:32","slug":"research","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/dhanm-lab\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<p>We are using digital health monitoring tools and network modeling to understand the determinants of cardiometabolic disease.<\/p>\n<p>Many of our research projects also involve multi-omic datasets in large cohort studies, including the <a href=\"https:\/\/www.framinghamheartstudy.org\/\" target=\"_blank\" rel=\"noopener noreferrer\">Framingham Heart Study<\/a> (a multi-generational family study, which has been continuously collecting data from 1948-today). The unique data resources we are using will help us to uncover the biological mechanisms linking lifestyle behaviors with cardiometabolic disease.<\/p>\n<h4 style=\"color: #CC0000;\">Digital health tools currently in use:<\/h4>\n<ul>\n<li>Continuous glucose monitoring (Dexcom and Abbott Libre products)<\/li>\n<li>Physical activity monitoring (accelerometers including Fitbit, Apple Watch, Actical, smartphone apps)<\/li>\n<li>Digital diet assessment (ASA24, Keenoa smartphone app, RedCap digital FFQ)<\/li>\n<\/ul>\n<h4 style=\"color: #CC0000;\">Multi-omic data sources we use:<\/h4>\n<ul>\n<li>Genetic and Epigenetic data<\/li>\n<li>Metabolomics and Proteomics<\/li>\n<li>Gut Microbiome<\/li>\n<\/ul>\n<h4 style=\"color: #CC0000;\">Examples of our current projects in the Framingham Heart Study:<\/h4>\n<ul>\n<li>Diabetes transmission across social networks and through families<\/li>\n<li>Gut microbial traits associated with prediabetes and diabetes<\/li>\n<li>Associations of diet composition and quality with continuous glucose monitor-derived measures of glycemic variability<\/li>\n<li>Plant-based diets, gut microbiome, and metabolomic determinants of cardiometabolic disease <\/li>\n<li>Meal and sleep timing relate to continuous glucose monitor-derived glycemic traits<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>We are using digital health monitoring tools and network modeling to understand the determinants of cardiometabolic disease. Many of our research projects also involve multi-omic datasets in large cohort studies, including the Framingham Heart Study (a multi-generational family study, which has been continuously collecting data from 1948-today). The unique data resources we are using will [&hellip;]<\/p>\n","protected":false},"author":23966,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/pages\/6"}],"collection":[{"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/users\/23966"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/comments?post=6"}],"version-history":[{"count":2,"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/pages\/6\/revisions"}],"predecessor-version":[{"id":19,"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/pages\/6\/revisions\/19"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/dhanm-lab\/wp-json\/wp\/v2\/media?parent=6"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}