Using Affinity-Based Proteomics to Identify Diagnostic and Plasma Biomarkers for Endometriosis

Abstract

Endometriosis, which is characterized by pain and infertility, is the most frequent reproductive health diagnosis among female veterans along with menstrual disorders. Notoriously difficult to diagnose, the time between symptom onset and endometriosis diagnosis averages seven years, resulting in prolonged pain symptoms leading to decreased activity and poor mental health, greatly impacting women physically, psychologically, and economically over the life-course. Identifying diagnostic and prognostic biomarkers would enable earlier intervention and prevent progression to severe pain and infertility. However, identification of endometriosis biomarkers has been limited by the heterogeneity of the disease, inappropriate control groups, and lack of prospectively collected samples. Furthermore, progression of endometriosis is not well understood. Discovery of non-invasive diagnostic and prognostic biomarkers for endometriosis has the potential to revolutionize current medical practice, leading to earlier diagnosis and interventions as well as better clinical care that could significantly impact improvement in clinical outcomes of endometriosis. We hypothesize that endometriosis development and progression will lead to altered circulating protein profiles related to systemic inflammation and immunity years before emergence of symptoms and the clinical diagnosis of endometriosis that will be detectable through the novel proteomics technology, SOMA scan, enabling early diagnosis of endometriosis. In addition, alteration of inflammation and immune proteins in systemic environments will be greater among women who do not experience pain remediation after surgical treatment.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2020
Accession Number
AD1114551

Entities

People

  • Kathryn L. Terry

Organizations

  • Brigham and Women's Hospital

Tags

DTIC Thesaurus Topics

  • Adolescents
  • Age Groups
  • Biomedical Research
  • Blood Proteins
  • Body Weight
  • Chemistry
  • Computational Biology
  • Covid-19
  • Data Analysis
  • Department Of Defense
  • Detection
  • Drug Therapy
  • Health Services
  • Information Science
  • Ligation
  • Mental Health
  • Pain
  • Personalized Medicine
  • Proteomics
  • Quality Control
  • Sars
  • Standards
  • Surgery
  • Systems Biology
  • Therapy
  • Women'S Health

Fields of Study

  • Medicine

Readers

  • Mental Health of Military Veterans with Posttraumatic Stress Disorder (PTSD): Risk Factors, Prevalence, Symptoms, and Treatment.
  • Neuroscience
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • Biotechnology