Extracellular RNAs in Relation to Cardiometabolic Risk
Condition: Subclinical Atherosclerotic Cardiovascular Disease; Blood Pressure; Obesity
MeSH terms: Cardiovascular Diseases; Atherosclerosis
Study type: Observational

Summary: 
      Background:

      Extracellular RNAs (exRNAs) send genetic data from cell to cell. This is how they affect the
      way cells communicate with each other. There are many types of exRNA, and they each serve
      different roles. But they have also been linked to some diseases. Researchers want to measure
      exRNAs to see how they relate to certain traits over time. They will use blood samples that
      were taken as part of the Framingham Heart Study (FHS).

      Objectives:

      To identify cross-sectional associations of exRNAs with age, sex, and cardiometabolic risk
      factors.

      Eligibility:

      People ages 30-70 who had blood taken as part of the FHS Third Generation cohort.

      Design:

      Researchers will study samples that have already been collected in the FHS. There will be no
      active participant contact for this project, only use of data that are collected as part of
      planned follow up from other studies.

      As part of the FHS, participants gave blood samples. They gave permission for the blood to be
      used for research.

      The exRNAs from the blood samples will be studied to see how they relate to certain traits.
      These include age, sex, and body mass index.

      The exRNAs will also be studied for their usefulness as biomarkers of risk for subclinical
      atherosclerotic cardiovascular disease.

      No study participants will be contacted for this study....
    

Detailed description: 
      Extracellular RNAs (exRNAs) impact a wide range of biological processes and function to
      transfer genetic information between cells. In doing so, exRNAs affect cell-to-cell
      communications. Recent studies indicate that exRNAs are associated with a variety of
      diseases. Emerging data from elderly participants in the Framingham Heart Study (FHS)
      demonstrate that circulating levels of exRNA are correlated with several key traits including
      age, sex, and body mass index. Much more work is needed to determine the extent to which
      exRNAs are associated with a variety of clinically relevant traits across the age spectrum.
      We seek to measure a 665 exRNAs spanning a variety of classes in plasma from 4095 young to
      middle-aged adult participants in the Third Generation cohort of the FHS and to relate them
      to age, sex, and cardiometabolic risk factors (BMI, lipids, blood pressure, and fasting
      glucose) in cross-sectional analyses and to determine the relations of these exRNAs measured
      at baseline to serial changes in cardiometabolic risk factors during seven years of follow
      up. We also seek to relate exRNAs to subclinical atherosclerotic cardiovascular disease
      (ASCVD; assessed via multidetector CT measures of coronary artery calcium), and its
      progression during seven years of follow up. This grant application will establish an
      association of exRNAs with clinically relevant traits and diseases and will establish their
      utility as biomarkers of risk for cardiometabolic disease and subclinical ASCVD. To this end,
      we propose three aims: 1) To identify associations of exRNAs with age, sex, and
      cardiometabolic risk factors and subclinical ASCVD at a baseline examination, 2) To identify
      associations of exRNAs with longitudinal changes in cardiometabolic risk factors and
      subclinical ASCVD during seven years of follow up, and 3) To explore the genetic regulation
      of exRNAs via analysis of whole genome sequence data. We demonstrate that we have adequate
      power to detect associations of exRNAs with cardiometabolic risk factors and subclinical
      atherosclerosis at baseline and with their longitudinal change during follow up.
    

Observational model: Cohort
Time perspective: Cross-Sectional
Sampling method: Non-Probability Sample
Study population: 
        We seek to measure a 665 exRNAs spanning a variety of classes in plasma from 4095 young to
        middle-aged adult participants in the Third Generation cohort of the FHS
      
Keywords: Extracellular RNA; MicroRNA; Natural History