# Peripheral blood mononuclear cell epigenetic associations in and biomarkers for knee osteoarthritis development and progression.

> **NIH NIH R01** · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · 2020 · $21,455

## Abstract

Project Summary / Abstract
The objective of the proposed research is to better understand how peripheral blood epigenetic patterns
are associated with knee osteoarthritis (OA). A great deal of work has already been demonstrated widespread
epigenetic changes within articular tissues in both knee and hip OA. Others have described serum and urine
protein biomarkers as predictors of future knee OA progression. Our first Aim is to evaluate peripheral blood
cell DNA epigenetic patterns in baseline blood samples from patients who will go on to have rapid radiographc
and/or pain progression in the subsequent 24 months. We will then use these data to develop develop and
evaluate the performance of epigenetic algorithmic models to discriminate these groups. Patient samples will
parallel the National Institutes of Health OA Biomarkers Consortium (OABC-FNIH) study. DNA methylation
will be evaluated using a next-generation bisulfite sequencing approach (methylSeq), and algorithms developed
using cutting-edge machine learning techniques. We will then translate our findings into a more high-
throughput, inexpensive, and clinically relevant form by developing and validating a targeted capture
sequencing system to interrogate these specific epigenetic locations. Our second Aim is to evaluate the
peripheral blood DNA methylation patterns that precede the development of OA, using samples from 48-, 24-,
12-, and 0-months before incident OA. We will again develop algorithms to predict future OA development
using similar techniques as Aim 1 and translate this to a targeted capture sequencing system. This unique
longitudinal approach which will allow us not only to determine whether and when epigenetic patterns develop
preceding OA development, but also track longitudinal epigenetic changes as OA develops. The proposed
work is important, as there are no FDA approved biomarkers for OA diagnosis or prognosis. Our work is
quite innovative both in its combination of "big data" epigenetic analysis and cutting-edge machine learning
techniques applied to a specific clinical problem, as well as in its examination of PBMC epigenetics in OA,
which has not yet been described. Moreover, we tackle the problem of translation of big-data research by
aiming specifically to develop high-throughput methods to translate our findings into a clinically-relevant and
accessible form. Success in our proposal will produce both algorithmic models with direct clinical impact to
predict future OA development and progression, as well as broaden our understanding of epigenetic changes in
peripheral blood cells from OA patients.

## Key facts

- **NIH application ID:** 9861881
- **Project number:** 1R01AR076440-01
- **Recipient organization:** UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR
- **Principal Investigator:** Matlock Jeffries
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $21,455
- **Award type:** 1
- **Project period:** 2020-06-16 → 2020-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9861881

## Citation

> US National Institutes of Health, RePORTER application 9861881, Peripheral blood mononuclear cell epigenetic associations in and biomarkers for knee osteoarthritis development and progression. (1R01AR076440-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9861881. Licensed CC0.

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