Evidence map›Paper›PMID 41576141›Full record

ArticlePLoS genetics2026

Shared latent genetic liability across fibromyalgia and psychiatric traits: Novel insights from genomic structural equation modeling.

Liling Lin, Yankai Li, Fengtao Ji, Jianwei Lin, Mengyi Zhu, Diefei Liang, Minghui Cao, Ganglan Fu, Yanni Fu

Abstract read
In one paragraph

Article in PLoS genetics, 2026. 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

9 authors.

Liling LinDepartment of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0001-5487-1758
Yankai LiZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0009-0005-0151-2774
Fengtao JiDepartment of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Jianwei LinBig Data Laboratory, Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, Guangdong, China.
Mengyi ZhuDepartment of Urology Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Diefei LiangDepartment of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Minghui CaoDepartment of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Ganglan FuDepartment of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Yanni FuDepartment of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFibromyalgia, insomnia, depression, and anxiety share common clinical comorbidities, but their underlying genetic architecture and mechanism remain unclear.

methodsWe conducted phenotype-specific Genome-wide association study (GWAS) meta-analyses for fibromyalgia, insomnia, depression, and anxiety, respectively. Genomic structural equation modeling was employed to identify a shared genetic factor (mvFibroPsych). Lead SNPs and associated genes were annotated using Functional Mapping and Annotation (FUMA), followed by gene-set and tissue enrichment analyses. The Latent Causal Variable (LCV) method was utilized to identify modifiable risk factors and phenotypes influenced by mvFibroPsych. Additionally, brain-wide and proteome-wide Mendelian randomization (MR) analyses were applied to explore brain regions and biomarkers associated with mvFibroPsych. Multi-layer molecular quantitative trait locus (QTL) analyses were conducted for mechanistic insights into mvFibroPsych.

resultsStrong genetic correlations were observed among the four phenotypes (rg = 0.55-0.84), with excellent model fit for the common factor [comparative fit index (CFI) = 0.999, standardized root mean square residual (SRMR) = 0.015]. The mvFibroPsych GWAS identified 49 lead SNPs across 43 loci, including 32 novel loci. Gene prioritization revealed 342 protein-coding genes, and pathway analysis indicated enrichment in synaptic function pathway. LCV identified 133 phenotypes causally linked to mvFibroPsych. Brain-wide MR found fractional anisotropy in the splenium of the corpus callosum to be inversely associated with mvFibroPsych. Proteome-wide MR identified five proteins significantly associated with mvFibroPsych, while multi-layer brain QTL analysis prioritized CD40 as a potential target.

conclusionsThis study provides strong evidence for a shared genetic factor underlying fibromyalgia, insomnia, depression, and anxiety, linked to synaptic function, brain structure integrity, and neuroinflammatory pathways.

Indexed as

DepressionFibromyalgiaGenetic Predisposition to DiseaseAnxietyBrainGenome-Wide Association StudyGenomicsHumansMendelian Randomization AnalysisPhenotypePolymorphism, Single NucleotideQuantitative Trait LociSleep Initiation and Maintenance Disorders

Identifiers

PMID41576141
PMCPMC12867332

What Socratic 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 Socratic graph.