‘Multi-omics of iCPET Plasma Samples
This project aims to understand the origin of postural orthostatic tachycardia syndrome (POTS).
Copyright © 2025 Open Medicine Foundation. All Rights Reserved.
From Data to Disease Mechanism and Treatments
Each OMF funded study is selected, with oversight from our Scientific Advisory Board, for its ability to provide meaningful data that will fuel the search for treatment and diagnosis. This data is essential to develop diagnostic technologies, understand the molecular basis of the diseases, and uncover effective diagnostic tools and treatments. Under the direction of Wenzhong Xiao, PhD, the Computational Research Center for Complex Diseases analyzes and integrates the data from OMF funded studies, an essential step in developing diagnostics and treatments.
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Dr. Xiao is a world expert in computational genomics and the Director of the Immuno-Metabolic Computational Center at Massachusetts General Hospital (MGH), Harvard Medical School. He also leads a Computational Genomics Group at Stanford Genome Technology Center (SGTC). His research is at the interface of computation, genomics and medicine. In collaboration with Open Medicine Foundation, his lab analyzes studies on ME / CFS and compares ME / CFS with other diseases.
This project aims to understand the origin of postural orthostatic tachycardia syndrome (POTS).
The aim is to investigate potential differences in adrenergic and muscarinic receptor autoantibody levels in plasma and cerebrospinal fluid samples between ME/CFS patients and healthy controls.
This study provides an excellent opportunity to understand the mechanism of long-lasting viral-induced cognitive complications, commonly referred to as “brain fog.”
We will explore the hypothesis that deranged flow of the cerebrospinal fluid (CSF) due to craniocervical obstructions and/or instability may cause deranged intracranial pressure (ICP), neuroinflammation and cardinal symptoms of ME/CFS.
We intend to examine multiple sleep studies that have been conducted in the past two years and performed at the MGH Neurology Sleep Medicine Laboratory in well characterized patients with ME/CFS.
Decode the molecular mechanisms underlying ME/CFS and contributing to specific symptoms with a particular emphasis of post-exertional malaise (PEM). This includes deep phenotyping of ME patients and global proteomic/metabolomics plasma profiling of ME..
The aim is to investigate potential differences in adrenergic and muscarinic receptor autoantibody levels in plasma and cerebrospinal fluid samples between ME/CFS patients and healthy controls.
Studying microRNAs could help to bridge the conceptual gap between genetic predisposition and environmental factors causing ME/CFS or exacerbating specific symptoms.
This study explores the biological changes that occur in the muscles during post-exertional malaise (PEM), both in historical cases of ME/CFS and cases of Long COVID that meet the criteria for ME/CFS.
The purpose of the OMF Data Center is to house raw data and processed results, which is shared with our research network through the web-based data portal.
This Harvard study evaluates the different explanations of heart preload failure in ME/CFS patients to determine which is active in many, if not all, ME/CFS patients. The Computation Center is now seeking to better understand the causes of ME/CFS (PLF, the high flow type) as well as to identify potential drug targets for future therapies.
The goal of this project is to use data integration and network analyses to discover disease mechanisms and potential treatments.
The Life Improvement Trial (LIFT) aims to investigate two drugs, separately and in combination, Pyridostigmine (commonly known as Mestinon) and Low-Dose Naltrexone (LDN), for efficacy and to research the difference between responders and non-responders.
The purpose of this study is to facilitate early detection of ME/CFS in people with Long COVID and better understand disease progression.
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