| Title: | Genomic ascertainment of systemic autoinflammatory diseases: a retrospective cohort study in two population-based biobanks |
| Journal: | The Lancet Rheumatology |
| Published: | 13 Oct 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42869051/ |
| DOI: | https://doi.org/10.1016/s2665-9913(26)00217-1 |
Publication 21532
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Abstract
BACKGROUND: Systemic autoinflammatory diseases are rare diseases caused by innate immune dysregulation and are often linked to single-gene variants. Diagnosis remains challenging due to incomplete penetrance and variable expressivity. This study aimed to quantify the prevalence, penetrance, and clinical spectrum of systemic autoinflammatory diseases associated with pathogenic or likely pathogenic variants in 28 genes.</p>
METHODS: This retrospective cohort study applied a genome-first approach to whole exome sequencing linked to electronic health records from Geisinger MyCode Community Health Initiative (USA) and the UK Biobank (UK). From a curated list of 27 dominantly inherited and one acquired disease gene, individuals with autosomal dominant pathogenic or likely pathogenic variants or somatic pathogenic or likely pathogenic variants of UBA1 were classified as cases. Variants were classified according to American College of Medical Genetics and Genomics guidelines and assigned to tier 1 or tier 2. Controls were participants without any pathogenic or likely pathogenic variant in the 28 genes. Penetrance (≥1 systemic autoinflammatory disease-associated ICD-10 code group) and clinical spectrum were assessed in tier 1 cases by comparing inflammatory ICD-10 codes and immunosuppressant use between cases and controls, with expressivity defined as the number of enriched ICD-10 code groups. Odds ratios (ORs) were calculated using Fisher's exact test with Bonferroni-Holm correction, and cohorts were analysed separately. There was no lived experience involvement in the study design or conduct.</p>
FINDINGS: The final dataset consisted of 640 092 participants (170 503 from Geisinger MyCode and 469 589 from the UK Biobank). 280 958 (43·9%) were male and 359 134 (56·1%) were female. We identified 159 individuals carrying rare pathogenic or likely pathogenic variants in 17 genes, corresponding to a prevalence of 0·04% (63 of 170 503) in Geisinger MyCode and 0·02% (96 of 469 589) in the UK Biobank with a combined estimated prevalence of one in 4026 individuals (0·02%). Only one participant had a documented diagnosis of an autoinflammatory disorder. Geisinger MyCode cases had a disease penetrance of 79% (50 of 63) compared with a disease penetrance of 32% (31 of 96) in the UK Biobank. Overall, disease penetrance was 51%, with 81 of 159 cases exhibiting inflammatory features across multiple organ systems, especially pulmonary and cutaneous manifestations, as well as diagnoses of vasculitis (Geisinger MyCode OR 5·06 [1·01-15·54]) and rheumatic autoimmune disorders (Geisinger MyCode OR 2·29 [0·88-5·04]; UK Biobank OR 12·28 [4·12-30·68]. We also observed increased use of immunosuppressive medications in cases compared to controls (Geisinger MyCode OR 3·98 [95% CI 1·40-9·23]) consistent with clinically relevant disease.</p>
INTERPRETATION: These findings suggest that monogenic autoinflammatory diseases are more common than currently recognised. Despite carrying disease-associated variants, almost no affected individuals had a documented systemic autoinflammatory disease diagnoses, pointing to a substantial gap in disease recognition and a missed opportunity to identify individuals with systemic inflammation who could benefit from genetic evaluation to guide therapy.</p>
FUNDING: Division of Cancer Epidemiology and Genetics, National Cancer Institute, the National Institutes of Health.</p>
11 Authors
- Defne Ercelen
- Meghan Anderson
- Jung Kim
- Jeremy S Haley
- Adam Cook
- Wesley Hill
- James Dove
- Ivona Aksentijevich
- David J Carey
- Douglas R Stewart
- David B Beck
1 Application
| Application ID | Title |
|---|---|
| 105564 | Identification of genetic causes of human disease |
Enabling scientific discoveries that improve human health