Evidence map›Paper›PMID 41444612›Full record

ArticleJournal of translational medicine2025

Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation.

Camille L Birch, Brandon M Wilk, Manavalan Gajapathy, Shaurita D Hutchins, Gurpreet Kaur, Donna M Brown, Tarun K K Mamidi, Kathleen S Hodgin, Alp Turgut, Jarred W Younger and 1 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

11 authors.

Camille L BirchCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Brandon M WilkCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Manavalan GajapathyCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Shaurita D HutchinsCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Gurpreet KaurCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Donna M BrownCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Tarun K K MamidiCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA.
Kathleen S HodginDepartment of Psychology, University of Alabama-Birmingham, 1300 University Blvd Suite 233, Birmingham, AL, 35294, USA.
Alp TurgutDepartment of Psychology, University of Alabama-Birmingham, 1300 University Blvd Suite 233, Birmingham, AL, 35294, USA.
Jarred W YoungerDepartment of Psychology, University of Alabama-Birmingham, 1300 University Blvd Suite 233, Birmingham, AL, 35294, USA.
Elizabeth A WortheyCenter for Computational Genomics and Data Science, Department of Genetics, 701 20th St S, Birmingham, AL, 35233, USA. lworthey@uab.edu.ORCID 0000-0003-4083-7764

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling and heterogeneous disorder lacking validated biomarkers or targeted therapies. Clinical variability and elusive pathophysiology hinder progress toward effective diagnostics and treatment. Core symptoms include persistent fatigue, post-exertional malaise, unrefreshing sleep, cognitive dysfunction, and pain. We tested whether an individualized, “n-of-1” genomic and transcriptomic framework combined with comprehensive, participant-informed phenotyping could reveal molecular signatures unique to each patient.

methodsClinical-grade whole-genome sequencing was conducted in 31 affected individuals from 25 families, with RNA-seq performed on a subset (16 affected, 7 unaffected) using blood samples. Machine-learning assisted variant triage, transcript-aware damage prediction, and expert review identified pathogenic or likely pathogenic variants in 8 of 25 probands (32%) and 12 of 31 affected individuals (39%).

resultsFindings revealed marked genetic heterogeneity, including large-effect rare and more common variants. Implicated pathways included ATP generation, oxidative phosphorylation, fatty acid oxidation; regulation of glycolysis, amino acid and lipid turnover; ion and solute homeostasis; synaptic signaling, excitability, oxygen transport, and muscle integrity, resilience, and post-exertional recovery; previously implicated processes. Plausible modifiers influencing disease onset, severity, and relapsing–remitting patterns and possibly explaining intrafamilial variability and inconsistent findings across studies, were also identified. Despite gene-level diversity, downstream effects converged on impaired energy production, reduced stress resilience, and vulnerability to post-exertional metabolic failure; disruptions consistent with core ME/CFS symptoms of exertional intolerance, cognitive fog, and fatigue.

conclusionsOur findings support the hypothesis that at least a subset of ME/CFS cases represent distinct molecular disorders that converge on shared physiological pathways. Validation in larger, more diverse cohorts will be essential to test this hypothesis and establish generalizability, but increase size alone is unlikely to resolve causation in a disorder defined by rarity, heterogeneity, and molecular complexity. We suggest that progress will require experimental designs that integrate individual-level genomic data with deep, participant-informed deep phenotyping, capturing the combined effects of rare and common variants and environmental modifiers on disease expression and progression. We believe that an individualized precision medicine framework will uncover molecular drivers and modifiers of ME/CFS previously obscured by heterogeneity, enabling biologically informed stratification, improved trial design, biomarker discovery, and targeted interventions in this historically neglected condition.

Indexed as

Fatigue Syndrome, ChronicGenetic Predisposition to DiseaseGenetic VariationPrecision MedicineAdultFemaleGenetic HeterogeneityHumansMalePhenotypeConvergenceGenome sequencingMolecular diagnosticsMyalgic Encephalomyelitis/Chronic fatigue syndromePhenotype modelingPrecision medicineTranscriptomics

Identifiers

PMID41444612
PMCPMC12888368

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.