Evidence map›Paper›PMID 39996021›Full record

ArticleFrontiers in human neuroscience2025

A network medicine approach to investigating ME/CFS pathogenesis in severely ill patients: a pilot study.

Li-Yuan Hung, Chan-Shuo Wu, Chia-Jung Chang, Peng Li, Kimberly Hicks, Joshua J Dibble, Braxton Morrison, Chimere L Smith, Ronald W Davis, Wenzhong Xiao

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Li-Yuan Hung *Computational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Chan-Shuo Wu *Computational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Chia-Jung ChangME/CFS Collaborative Research Center, Stanford University School of Medicine, Palo Alto, CA, United States.
Peng LiComputational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Kimberly HicksOpen Medicine Foundation, Agoura Hills, CA, United States.
Joshua J DibbleComputational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Braxton MorrisonComputational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Chimere L SmithPatient Led Research Collaborative, Washington, DC, United States.
Ronald W DavisME/CFS Collaborative Research Center, Stanford University School of Medicine, Palo Alto, CA, United States.
Wenzhong XiaoComputational Research Center for Complex Chronic Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This pilot study harnessed the power of network medicine to unravel the complex pathogenesis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). By utilizing a network analysis on whole genome sequencing (WGS) data from the Severely Ill Patient Study (SIPS), we identified ME/CFS-associated proteins and delineated the corresponding network-level module, termed the SIPS disease module, together with its relevant pathways. This module demonstrated significant overlap with genes implicated in fatigue, cognitive disorders, and neurodegenerative diseases. Our pathway analysis revealed potential associations between ME/CFS and conditions such as COVID-19, Epstein-Barr virus (EBV) infection, neurodegenerative diseases, and pathways involved in cortisol synthesis and secretion, supporting the hypothesis that ME/CFS is a neuroimmune disorder. Additionally, our findings underscore a potential link between ME/CFS and estrogen signaling pathways, which may elucidate the higher prevalence of ME/CFS in females. These findings provide insights into the pathogenesis of ME/CFS from a network medicine perspective and highlight potential therapeutic targets. Further research is needed to validate these findings and explore their implications for improving diagnosis and treatment.

Indexed as

chronic fatigue syndromecognitive disorderslong COVIDME/CFSnetwork medicineneurodegenerative diseasesneuroimmunologyPPI network analysis

Identifiers

PMID39996021
PMCPMC11847890

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.