Defining Endometriosis Physiologic Subphenotypes and Subsequent Cancer and Comorbidities Risk Through Discovery of Novel Genetic Variants

Abstract

The main objectives of this study are: 1) To identify novel genetic variants associated with specific endometriosis sub-phenotypes defined by symptom and macro-surgically visualized presentation. These novel sub-phenotype-specific variants will suggest distinct physiologic pathways that underlie the poorly understood endometriosis heterogeneity, potentially catalyzing discovery of precision medicine treatment and prevention targets. 2) To determine the common and unique genetic variants that are associated with the higher risk of subsequent development of cancers, autoimmune and cardiovascular diseases among women with endometriosis. To address these objectives, we will capitalize upon our ongoing International Endometriosis Genome Consortium (IEGC) investigations and deploy our existing genetic analysis pipeline on a wider scale. The IEGC is a consortium of well-established case: control and cohort studies all of which have completed genome-wide genotyping of their participants. Within the IEGC, nine studies have harmonized clinical data compliant with the Endometriosis Phenome and Biobanking Harmonization Project (WERF-EPHect) tools to facilitate deeply phenotyped definitions of potentially informative endometriosis sub-phenotypes. Also, in the exploratory analyses, we will delve more deeply into one consortium cohort, the Women's Health Study: from Adolescence to Adulthood (A2A), which in addition to the genotyped and deeply-phenotyped EPHect compliant data, has measured an array of blood chemokine and cytokine markers. Operationalizing these time- and cost-efficient unique resources available in-hand.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2022
Accession Number
AD1190897

Entities

People

  • Stacey Missmer

Organizations

  • Michigan State University

Tags

DTIC Thesaurus Topics

  • Autoimmune Diseases
  • Blood
  • Brain Injuries
  • Cardiovascular Diseases
  • Chemistry
  • Covid-19
  • Cytokines
  • Data Analysis
  • Disease Attributes
  • Diseases
  • Fatty Acids
  • Health Services
  • Medical Personnel
  • Microbiomes
  • Pain
  • Personalized Medicine
  • Proteins
  • Therapy

Fields of Study

  • Biology
  • Medicine

Readers

  • Molecular and genetic basis of cancer.
  • Systems Analysis and Design
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • Biotechnology