Project description:Note: Data Use Restrictions: <ul> <li>The data must only be used for genetic research projects solely in the area of health-related social-network research.</li> </ul> This study compiles detailed information on family and social ties linked to participants in the offspring cohort of the Framingham Heart Study. The investigators took computerized information from self-report data used by the FHS for over 30 years to facilitate health exam scheduling. These tracking sheets asked participants to identify people close to them, which were assumed by the investigators to indicate a social tie. Individuals are listed as "egos" (if the ties are from their perspective) and/or "alters" (if they are linked as a friend or family members to one of the other participants). All egos were FHS offspring participants while alters could be FHS participants in any cohort or non-participants. This information was combined with internal FHS pedigree data on family ties to list family member alters (as well as the nature of their relationship). The resultant dataset therefore includes each ego-alter tie, the nature of their relationship and the start and end dates for their ties for each of seven waves for the offspring study. Due to privacy concerns, all exam dates for individuals are listed relative to the initial FHS exam date. The study investigators chose a random, confidential date, to which all initial exam dates are linked (by number of months from random date to initial exam date). With this information, researchers can have access to the temporal relationships among participants' exam dates while remaining unaware of the actual exam dates for individual participants. During each clinic exam cycle, the participants undergo a detailed examination including physical examination, medical history, laboratory testing, and electrocardiogram. Over the years, other tests (that may not be performed at every exam cycle) have included pulmonary function, lifestyle, physical function, cognitive function questionnaires, and various noninvasive cardiovascular tests including echocardiograms. This study involves phenotypic data from these exams including (when available) basic body measurements (height, weight, blood pressure), laboratory values (blood sugar levels, LDL levels), information on smoking and alcohol use, and tests of depression and cognitive functioning. Important links to apply for individual-level data <ol> <li><a href="http://dbgap.ncbi.nlm.nih.gov/aa/wga.cgi?view_pdf&stacc=phs000153.v3.p3" target="_blank">Data Use Certification Requirements (DUC)</a></li> <li><a href="GetPdf.cgi?id=phd001183.1" target="_blank">Instructions to Request Authorized Access</a></li> <li><a href="http://view.ncbi.nlm.nih.gov/dbgap-controlled" target="_blank">Apply here for controlled access to individual level data</a></li> <li><a href="GetPdf.cgi?id=phd000317" target="_blank">Participant Protection Policy FAQ</a></li> </ol> In 1948, researchers recruited men and women from the town of Framingham, Massachusetts, beginning the first round of extensive physical examinations and lifestyle interviews that would later be analyzed for common patterns related to CVD development. Initially, the Framingham Heart Study enrolled 5,209 men and women from the Framingham area who were between the ages of 28 and 62 years. Beginning in 1971, the Framingham Heart Study enrolled 5,124 men and women, who were either offspring of the original cohort or spouses of those offspring. In 2002, 4,095 third generation participants (men and women) were enrolled.

Project description:Prostate cancer incidence and related mortality are disproportionately higher in African American (AA) men than European American (EA) men, but the molecular mechanisms contributing to racial disparities are not fully elucidated. To identify molecular factors that can contribute to disease biology in prostate cancer from AA and EA men, we utilized a multi-omics approach to measure and integrate DNA methylation with gene expression changes. We compared and contrasted results from adjacent non-tumor and tumor tissues from AA and EA men. We found that hypermethylated regions are enriched for PRC2 and H3K27me3 pathways and EZH2/SUZ12 cofactors in a race-independent manner. On the other hand, hypomethylated regions in prostate tumors from AA men were enriched for olfactory/ribosomal pathways as well as distinct cofactors such as CTCF and KMT2A. DNA methylation at transcription start sites and 5’-UTR at GATA3, an androgen receptor (AR) coregulator, is associated with decreased gene expression in prostate tumors of AA men. Our analysis also showed an inverse correlation between DNA methylation and RNA expression of AR transcriptional targets, such as TRIM63, in prostate tumors of AA men. Our observations suggest a dysregulation of the AR signaling pathway in prostate cancer from AA men. To determine whether targeting AR results in race-specific gene expression changes, we utilized a prostate-cancer-specific Boolean network. Our simulation revealed that prolonged AR inhibition results in significant dysregulation in TGF-β, IDH1, and cell cycle pathways in prostate cancer of AA men. We expanded our observation of gene expression changes in the Boolean network and investigated RNA-sequencing data to better understand overall transcriptional alterations occurring in prostate tumors from AA and EA men. We found that gene expression changes related to microtubules, a subset of immune-related, and TMPRSS2-fusion pathways were dysregulated in prostate tumors of AA men and corresponded with progression-free survival of AA men. Altogether, the current study dissects complex signaling networks that are clinically actionable in prostate cancer from AA and EA men.

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Men at High Genetic Risk for Prostate Cancer

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