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ME/CFS Related Disorders Multi-Omics Study
Using Family and Population Approaches

Study AIM

Beginning in 2016, the aim of this study was to extend the Severely ill Patient Study (SIPS) and conduct a comprehensive “Big Data” analysis on ME/CFS patients and their families. 

LEAD INVESTIGATORS
  • Fereshteh K. Jahaniani, PhD
  • Michael P. Snyder, PhD
  • Ronald W. Davis, PhD
Updates and Potential
  • Published a paper on the characteristics of immune cells in ME/CFS (read here).
  • Continuing to collect longitudinal samples from patients, their unaffected family members and healthy volunteers.
  • Functional studies such as immunostaining, western blot, and RTCPR/PCR, in progress.
  • DNA and RNA extraction for whole genome, transcriptome, and DNA methylation studies in progress.
  • Two manuscripts under preparation on ME/CFS autoantibody profiling and ME/CFS plasma proteomics and cytokine landscape, which are aimed to be published in 2023.
STUDY HYPOTHESIS AND DESCRIPTION

In 2016, Fereshteh Jahanbani collaborated with Ron Davis and Mike Snyder to launch a study with the aim of deepening our understanding of how genetic and epigenetic variations impact our health, including our susceptibility to complex diseases such as ME/CFS and related comorbidities and multimorbidities.

The study was designed with the rationale that using unaffected family members as a control group would enable researchers to identify genetic and environmental risk factors that are associated with disease development, while longitudinal multi omics profiling could help to identify biomarkers and therapeutic strategies.

OBJECTIVES

Stick figure illustration of a family.

Use blood from each patient to compare patients to healthy relatives and examine:

  • Genome
  • Gene expression
  • Metabolomics
  • Proteomics
  • Cytokines
  • Microbiome
  • Autoantibodies

By comparing patients to healthy blood relatives, we are more likely to understand what genes cause or contribute to the development of ME/CFS. This data will also be integrated with the SIPS data.

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OMF is a non-profit 501(c)(3) organization
(EIN# 26-4712664). All donations are tax-deductible to the extent allowed by law.

2024 YEAR END REPORT

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