# What is Endometriosis? Deep Phenotyping to Advance Diagnosis and Treatment

> **NIH NIH R01** · MICHIGAN STATE UNIVERSITY · 2021 · $944,397

## Abstract

Project Summary: Women with endometriosis may experience debilitating pelvic pain and infertility, reduced
quality of life and incur significant health care costs. Endometriosis requires a surgical diagnosis, which results
in an average delay of seven years to obtain a diagnosis. Once a woman is diagnosed, there is scant data on
optimal treatment options and short- and long-term prognosis. Endometriosis is a heterogeneous disease not
only in disease presentation but also in symptom presentation. Understanding and quantifying this
heterogeneity is a crucial step to discover non-invasive diagnostic tools and to advance personalized, precision
treatment options - a scientific gap addressed herein. Our proposal addresses identifying endometriosis-
specific inflammatory, hormonal and miRNA (transcriptomic) plasma markers and inflammatory and
transcriptomic profiles of the ectopic endometrium (endometrial lesions). We will quantify the heterogeneity in
these plasma and tissue markers across: (1) symptom presentation at endometriosis diagnosis including pain
sensitization, (2) surgically visualized endometriosis subtypes, and (3) participant characteristics including
reproductive and gynecologic history and co-morbidities. Through the collaboration of global leading
endometriosis research centers (MSU, Harvard, Oxford, Eunice Kennedy Shriver NICHD), and multidisciplinary
molecular and physiology partners, we will address the hypotheses that 1) the combination of inflammatory,
hormonal, and transcriptional plasma markers can be used to differentiate women with and without
endometriosis; and 2) differences in the hormonal, inflammatory and transcriptional plasma and ectopic
endometrial markers can be further refined by assessing the heterogeneity in disease and symptom
presentation and participant characteristics. We further hypothesize that this heterogeneity will inform
treatment response and prognosis. Our combined data and samples were collected by standard operating
procedures, established by our World Endometriosis Research Foundation Endometriosis Phenome and
Biobanking Harmonization Project (WERF-EPHect). Together they total nearly 2000 women with and without
endometriosis and with well-annotated phenotypic data and blood samples. Among women with endometriosis,
we have more than 300 existing well-annotated ectopic endometrial samples.
Relevance: The discovery of informative subtypes of endometriosis and classifications of disease that lead to
precise non-invasive diagnostic tools for endometriosis and the application of personalized endometriosis
treatment options have remained elusive. This has resulted in significant delays in diagnosis and potentially
financial and personal costs for women with endometriosis. Leveraging our multidisciplinary team with expertise
in biomarkers, endometriosis heterogeneity, and epidemiology, provides an unprecedented opportunity to
advance the discovery of a non-invasive diagnostic and to advance personalized, pr...

## Key facts

- **NIH application ID:** 10155536
- **Project number:** 5R01HD094842-04
- **Recipient organization:** MICHIGAN STATE UNIVERSITY
- **Principal Investigator:** Asgerally T. Fazleabas
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $944,397
- **Award type:** 5
- **Project period:** 2018-08-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10155536

## Citation

> US National Institutes of Health, RePORTER application 10155536, What is Endometriosis? Deep Phenotyping to Advance Diagnosis and Treatment (5R01HD094842-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10155536. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*