For years, fibromyalgia’s underlying causes have remained elusive, with no clear biomarkers or highly effective treatments. But a groundbreaking preprint study posted on medRxiv in September 2025 changes that narrative. Analyzing genetic data from over 2.5 million individuals across 11 cohorts, researchers have identified the first robust genetic risk factors for fibromyalgia, firmly establishing it as a disorder rooted in the central nervous system (CNS).

A Massive Genetic Dive

Led by an international team including experts from institutions such as deCODE Genetics and collaborators from the University of Michigan, the Broad Institute, and others, this genome-wide association study (GWAS) meta-analysis pooled data from diverse populations. It included 54,629 fibromyalgia cases and 2,509,126 controls, marking a 100-fold increase over previous fibromyalgia GWAS efforts.

Cases were defined using ICD-10 code M79.7 from inpatient and primary care records; no exclusions for comorbidities were applied to avoid biasing toward "super-healthy" controls. The analysis spanned multiple ancestries but was dominated by European samples (89.7% of cases). Secondary analyses included sex-stratified and leave-one-cohort-out versions to enable unbiased risk prediction.

Findings: 26 Risk Loci and a Neural Focus

The primary analysis identified 26 independent genome-wide significant risk loci (p < 5 × 10⁻⁸), with effect sizes ranging from 4% to 9% increased odds per risk allele. The strongest hit? A variant in the HTT gene, infamous for causing Huntington's disease via CAG repeats, but this fibromyalgia-linked deletion is outside that region and doesn't associate with Huntington's after conditioning. Gene prioritization highlighted neural players:

• GPR52: Regulates HTT levels; a brain-specific receptor targeted for Huntington's therapy.
• CAMKV: Crucial for synaptic plasticity and dendritic spine maintenance.
• CELF4: Reduces pain sensitivity by regulating nociceptor excitability; a candidate for chronic pain gene therapy.
• DCC: Guides axon development and myelin organization.
• DRD2/NCAM1: Involved in dopamine signaling, sleep, and neural adhesion/immune function.
• MDGA2: Suppresses synapse formation; linked to autism.

Other genes, such as KYNU (the kynurenine pathway for pain) and NPY (neuropeptide modulating nociception), further underscore pain-processing roles. Heritability was enriched exclusively in brain tissues (i.e., cortex, caudate) and neural cell types, such as dentate gyrus neurons and interneurons, with no signal in immune or peripheral cells, challenging autoimmune theories.

Shared Genetics with Comorbidities

Fibromyalgia's lead variants are highly pleiotropic, associating with traits like educational attainment, BMI, type 2 diabetes, pain intensity, and insomnia in the GWAS Catalog. A phenome-wide scan across 330 diseases linked them to back pain (dorsalgia), metabolic issues, and immune conditions like asthma and hypothyroidism.

Genetic correlations with 855 FinnGen endpoints revealed strong overlaps (rg > 0.7) with widespread pain syndromes, post-traumatic stress disorder (PTSD), irritable bowel syndrome (IBS), and more, highlighting a transdiagnostic CNS vulnerability. Subtype analyses showed stronger ties to "atypical" forms like T2-low asthma and seronegative rheumatoid arthritis, distancing fibromyalgia from classic autoimmunity.

Despite a 2-3x higher prevalence in women, male-female genetic correlations were nearly identical (rg = 1.03), suggesting that environmental or hormonal factors drive the sex bias.

A Path to Better Understanding and Treatments

This study provides the first solid genetic evidence framing fibromyalgia as a CNS disorder, not just a "peripheral" pain issue. It opens doors for:

• Targeted Therapies: Genes like GPR52 and CELF4 are already drug targets—repurposing could accelerate relief.
• Risk Prediction: Polygenic risk scores (PRSs) modestly stratify risk (AUC ~0.59 in Europeans), with top-quintile individuals facing 1.5x odds.
• Personalized Medicine: Insights into neural mechanisms could refine diagnostics and reduce misclassification with comorbidities.

While limitations include reliance on ICD codes and European bias, the sheer scale of the dataset advances the field tremendously.

This research not only validates the experiences of those living with fibromyalgia but also paves the way for hope that genetic clues could finally lead to breakthroughs in managing this debilitating condition.

For full details, check out the preprint: The genetic architecture of fibromyalgia across 2.5 million individuals.

References:

Kerrebijn, I., Bjornsdottir, G., Arbabi, K., Urpa, L., Haapaniemi, H., Thorleifsson, G., Stefansdottir, L., Frangakis, S., Valliere, J., Kunorozva, L., Abner, E., Ji, C., Aagaard, B., Bliddal, H., Brunak, S., Bruun, M. T., Didriksen, M., Erikstrup, C., Geirsson, A. J., ... Wainberg, M. (2025). The genetic architecture of fibromyalgia across 2.5 million individuals [Preprint]. medRxiv. https://doi.org/10.1101/2025.09.18.25335914