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Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Diabetes Mellitus, Type 2↗

Genomic analyses implicate hormonal and metabolic dysregulation in polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) and its underlying features remain poorly understood. In this genetic study (n = 544,513), we expand the number of genetic loci from 16 to 29, and additionally identify 31 associated plasma proteins. Many risk-increasing loci were associated with later age at menopause, underscoring the reproductive longevity related to an increased oocyte number and/or availability across the lifespan. Hormonal regulation in the etiology of this condition, through metabolic and reproductive features, was emphasized. The proteomic analysis highlighted metabolic biology known to be related to PCOS. A polygenic risk score (PRS) was associated with adverse cardiometabolic outcomes, with differing relevance of testosterone and body mass index in women and men. Finally, while oligo-anovulation and anovulatory infertility are features of PCOS, we observed no impact of PCOS susceptibility on childlessness. We suggest that PCOS susceptibility confers balanced pleiotropic influences on fertility in women, and life-long adverse metabolic consequences in both sexes.

Humans↗

Recommendations for return of secondary genomic findings in observational cohort studies.

The return of secondary genomic findings (ROSF) to participants in observational cohort studies has evolved from a topic of debate to an accepted standard. This Perspective synthesizes the proceedings of a 2024 National Heart, Lung and Blood Institute-sponsored workshop and the broader literature to provide updated guidance for ROSF. Building on the 2010 National Heart, Lung and Blood Institute Working Group recommendations and the 2014 Clinical Sequencing Exploratory Research/Electronic Medical Records and Genomics 'floor and ceiling' framework, we address four areas: an integrated ethical framework for observational cohort settings; the emerging challenge of returning novel result types beyond monogenic variants, including polygenic risk scores, somatic mosaicism and pharmacogenomic findings; health equity and community engagement as structural prerequisites for ethical ROSF; and scalability challenges, including technology-assisted disclosure. Drawing on implementation experience from large-scale sequencing programs, we offer recommendations that balance researcher obligations with participant autonomy and equitable access to the benefits of genomic research.

Journal Article↗

Selphi, a tool for improving genotype imputation accuracy.

Genotype imputation is a powerful tool for inferring missing genotype data in large-scale genetic studies. Over the last two decades, multiple imputation algorithms have been developed, steadily improving in speed and overall accuracy. However, accurate imputation of rare and infrequent variants remains a challenge, largely because existing methods rely on local haplotype matching within genomic windows and do not fully exploit the extended patterns of haplotype sharing that span entire chromosomes. Here we present Selphi, a new genotype imputation algorithm that combines the Positional Burrows-Wheeler Transform (PBWT) with a multi-stage haplotype selection heuristic operating across entire chromosomes. When compared to state-of-the-art methods Beagle 5.4, IMPUTE5, and Minimac4, Selphi showed higher accuracy on the 1000 Genomes Project and TOPMed datasets, across all super-populations and allele frequencies. Similarly, Selphi achieved higher accuracy than Beagle 5.4 on the UK Biobank dataset, which translated into improved concordance with hc-WGS GWAS summary statistics at known trait-associated loci and more accurate polygenic risk scores (PRS). Selphi outputs standard VCF files with genotype dosages (DS), haplotype-specific allele probabilities (AP1, AP2), and a per-variant dosage R-squared quality score (DR2), enabling direct integration with downstream analytical pipelines including standard post-imputation quality filtering.

Genome-Wide Association Study↗

Genomic meta-analyses of binge-eating behavior and anorexia nervosa yield insights into the unique and shared biology of eating disorder phenotypes.

Eating disorders-including anorexia nervosa (AN), bulimia nervosa and binge-eating disorder-are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. Here we conducted a genomic meta-analysis of case-control studies of binge-eating behavior (BE; 39,279 cases, 1,227,436 controls), alongside analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six BE-associated loci, including loci associated with a higher body mass index and impulse-control behaviors. AN genome-wide association studies yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry studies. BE and AN exhibited similar positive genetic correlations with psychiatric disorders but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with body mass index. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries.

Behavioural genetics↗

Secure bioinformatics: privacy-preserving federated analytics using homomorphic encryption.

MOTIVATION: Large-scale bioinformatics analyses increasingly require collaboration across multiple cohorts and institutions, yet existing workflows often rely on data co-localization, which is slow, difficult to scale, and raises privacy concerns. We present a privacy-preserving federated analytics framework that enables secure statistical analysis across distributed datasets without transferring raw data, by performing all computations on encrypted data via cryptographic methods. RESULTS: We evaluate the framework by validating polygenic risk scores and conducting meta-analyses on two real-world cohorts. The proposed solution achieves over 99.9% accuracy relative to plaintext analyses, while maintaining scalable runtime performance with increasing data size and number of participating sites. These results demonstrate the feasibility of secure federated analytics for practical bioinformatics applications involving sensitive data.

Computational Biology↗

Genetic determinants of childhood blood pressure and heart rate in relation to adult health outcomes: the consortium of childhood blood pressure.

BACKGROUND AND AIMS: To elucidate the genetic architecture of blood pressure (BP) and heart rate (HR) during early life and assess their potential relevance to adult health outcomes. METHODS: The largest genome-wide association study (GWAS) meta-analyses to date of childhood systolic BP, diastolic BP, pulse pressure, and mean arterial pressure (n = 28 425) and HR (n = 22 565) were conducted in children of European ancestry aged 4-17 years. Follow-up analyses included comparisons with adult GWAS results, polygenic risk score (PRS) analyses in independent cohorts of diverse ancestries, and a phenome-wide association study in the UK Biobank. RESULTS: Eight genome-wide significant loci were identified for childhood BP (KIAA2013, CACNB2, PLCE1, PAX2, COL4A2, RP11-236L14.1, CFDP1, TPX2) and three loci for childhood HR (CCDC141, ACHE, MYH6); all novel in children but previously reported in adults. Childhood PRSs explained up to 1.6% of BP variance and 5.2% of HR variance among children of European ancestry. Genetic correlations between childhood and adulthood BP traits were moderate (rg = 0.4-0.7), suggesting age-specific genetic effects on BP. In the UK Biobank, higher childhood BP PRS levels were significantly associated with a broad range of adult health outcomes, particularly cardiometabolic outcomes such as hypertension, angina, myocardial infarction, and cardiovascular disease-related mortality. CONCLUSIONS: These findings advance the understanding of the genetic architecture of childhood BP and HR and provide compelling genetic evidence linking childhood BP to a broad spectrum of adult health outcomes-particularly cardiometabolic conditions-which may inform targeted prevention strategies from a young age.

Humans↗

Polygenic risk of coronary artery disease for long-term survivors of breast cancer.

BACKGROUND: Cardiovascular disease is a leading cause of death for long-term breast cancer survivors. We evaluated whether a polygenic risk score for coronary artery disease (CAD-PRS) was associated with the risk of incident CAD for survivors of unilateral or contralateral breast cancer. METHODS: The study included 1307 women with breast cancer first diagnosed at younger than 55 years of age who participated in the Women's Environmental Cancer and Radiation Epidemiology Follow-up Study. The CAD-PRS was based on a PRS developed and validated in a separate population. We modeled the association between incident CAD and the CAD-PRS, adjusting for age, CAD risk factors, first (and second) breast cancer treatment, study recruitment phase, and genetic population stratification. We also explored whether the risk of CAD depended on interactions between the CAD-PRS and cardiotoxic cancer treatment. RESULTS: There were 66 incident CAD diagnoses reported at a median of 16 years after breast cancer diagnosis. Participants with CAD-PRS at or above the median had a 2.48-times increased risk of CAD (95% confidence interval [CI] = 1.44 to 4.29) relative to participants with CAD-PRS below the median. Anthracycline-based chemotherapy was associated with increased CAD risk (hazard ratio [HR] = 2.04, 95% CI = 1.04 to 3.98), and the association was not modified by the CAD-PRS. The association between incident CAD and left-sided radiation therapy (RT) was increased for those with CAD-PRS at or above the median (HR = 2.90, 95% CI = 1.26 to 6.68) but not for those with CAD-PRS below the median (HR = 0.96, 95% CI = 0.32 to 2.88). There was evidence of super-additive interaction between the CAD-PRS and left-sided RT (relative excess risk due to interaction = 2.06, 95% CI = 0.05 to 4.06). CONCLUSION: A genome-wide CAD-PRS was associated with nonfatal CAD risk for long-term breast cancer survivors, providing potential utility for personalized cardiovascular care, particularly after RT.

Humans↗

Integrating genetic predictors into subsequent breast cancer risk prediction in survivors of childhood cancer.

PURPOSE: Female survivors of childhood cancer are at high risk for developing breast cancer. The contributions of most general population primary breast cancer genetic predictors to this risk have not been explored. METHODS: Analyses included females who survived &#x2265;5 years after their childhood cancer diagnosis with available array (N&#x2009;=&#x2009;2096, subsequent breast cancer [SBC]=218) or whole-genome sequencing (WGS; N&#x2009;=&#x2009;3292, SBC=101) data from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort. We computed 99 externally-validated primary breast cancer polygenic risk scores (PRS). Using deep-coverage WGS, ClinVar-annotated pathogenic/likely pathogenic (P/LP) variants in breast cancer susceptibility genes were identified. Cox proportional hazards models assessed associations with SBC risk, adjusting for treatments and genetic ancestry. RESULTS: Among 5388 female survivors (genetic ancestry, European: N&#x2009;=&#x2009;4,752; African: N&#x2009;=&#x2009;444; East Asian: N&#x2009;=&#x2009;192), 319 developed SBC. Most (90.9%) PRSs were nominally associated with SBC risk (P&#x2009;<&#x2009;0.05), but effect sizes varied substantially. PRSs with superior discriminatory ability had greater genome-wide coverage (e.g., 6.4 million-variant PRS, HR per SD&#x2009;=&#x2009;1.71, 95% CI&#x2009;=&#x2009;1.43 to 2.05; P&#x2009;=&#x2009;4.2x10-9) and 7.7-fold higher odds (P&#x2009;=&#x2009;7.0x10-4) of including variants in multiple DNA damage repair pathways compared with PRSs with weaker risk associations. Among survivors with WGS, 1.6% carried P/LP variants in clinical testing panel genes, which was associated with a 7.4-fold greater risk (95% CI&#x2009;=&#x2009;3.16 to 17.19). Including genetic factors improved SBC risk prediction by age 40 (P&#x2009;<&#x2009;0.001) compared to treatment exposures alone. CONCLUSIONS: Externally-validated primary breast cancer genetic susceptibility predictors are relevant for SBC risk prediction and should be prioritized for risk stratification in survivors.

Journal Article↗

Genetic risk stratification of common diseases in breast cancer survivors: a population-based cohort study.

IMPORTANCE: Patients diagnosed with breast cancer (BCa) are at increased risk of multiple common diseases; however, the spectrum of these diseases and the contribution of inherited genetic susceptibility remain incompletely characterized. METHODS: We evaluated 15 common diseases and tested their associations with BCa exposure and disease-specific polygenic risk scores (PRS) in the UK Biobank (UKB; N&#x2009;=&#x2009;254,736). Analyses were performed using cause-specific Cox proportional hazards models within a full-cohort framework, with time-updated BCa status, delayed entry at study recruitment, and age as the underlying time scale. RESULTS: After recruitment, incident BCa was diagnosed in 11,386 women (4.47%), including 2,742 (24.08%) with metastatic BCa. Patients with BCa had an increased risk of nine diseases spanning cardiovascular, metabolic, and neuropsychiatric domains (P<0.003, Bonferroni-corrected). Elevated risks were generally observed among patients with both early staged and advanced BCa. Inherited susceptibility further stratified disease risk, with the highest risks observed among patients with BCa with elevated disease-specific PRS. For example, compared with women without BCa, the hazard ratio (HR; 95% CI) for osteoporosis was 2.33 (2.15-2.52) among women with any BCa, 2.38 (2.18-2.59) among those with non-metastatic BCa, and 2.12 (1.78-2.54) among those with metastatic BCa; the HR was 4.48 (3.99-5.02) among patients with BCa in the highest quartile of osteoporosis-specific PRS (all P<0.001). In contrast, BCa was not significantly associated with risk of coronary artery disease. CONCLUSION: BCa and inherited genetic susceptibility jointly contribute to increased risk of multiple common diseases, supporting the integration of genetic risk stratification into survivorship care.

Complications↗

Genetic Susceptibility to the Environment Moderates the Impact of Childhood Experiences on Psychotic, Depressive, and Anxiety Dimensions.

BACKGROUND AND HYPOTHESIS: Gene-by-environment (GxE) studies in psychosis have exclusively focused on negative exposures. However, evidence supports the resilience-enhancing effect of positive factors on psychosis outcome. The Differential Susceptibility (DS) model proposes that common genetic variants may confer not only disproportionate responsiveness to negative environments, but also greater sensitivity to positive, resilience-enhancing conditions. This study is the first to apply the DS model to the expression of subclinical psychosis, employing polygenic risk scores of environmental sensitivity (PRS-ES). PRS-ES were hypothesized to moderate, in a DS manner, associations between childhood adversity and psychosis, affective, and anxiety dimensions in young adults. An exploratory goal examined whether PRS for psychotic-like experiences (PRS-PLE) also showed DS patterns. STUDY DESIGN: PRS, schizotypy, PLE, depression, anxiety, and childhood adversity ratings were obtained for 197 nonclinical young adults. LEGIT software for testing competitive-confirmatory GxE models was employed. STUDY RESULTS: Results largely supported DS: Individuals high on PRS-ES showed increased subclinical psychosis, depression, and anxiety if they had experienced elevated childhood adversity, and lower symptoms if exposed to low levels of adversity as compared with those with low PRS-ES. Similarly, PRS-PLE moderated the effect of adversity on PLE, positive schizotypy, and depression following the DS model, but only PRS-ES moderation on PLE survived statistical correction. CONCLUSIONS: Our results suggest that genetic DS to the environment is relevant to psychosis, depression, and anxiety. Current debates on reconceptualization of genetic "risk" and resilience may benefit from this insight that support optimistic views on preventative efforts for early detection and intervention.

Humans↗

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES: Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS: We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS: We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS: Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Female↗

From genotype to phenotype: understanding the genetic basis of autism.

PURPOSE OF REVIEW: This paper covers some of the key findings on the topic of genetic influences in autism over the last 12-18&#x200a;months, which consist of significant conceptual shifts and new insights from recent technological advances. RECENT FINDINGS: Autism is a highly heritable condition, with significant heterogeneity of the genes that influence the development of this condition. The heterogeneity of autism, and multiple pathways contributing to the development of an autistic phenotype, create challenges in our understanding, diagnosis, and management of this condition.Recent studies of common genetic variation and polygenic risk scores have focussed on resolving phenotypic heterogeneity and identifying meaningful autism subtypes. Rare-variant discovery has expanded across ancestries, the X chromosome, noncoding loci, structural variants, and tandem repeats, aided by long-read and pangenome-informed sequencing. Single-cell multiomics, spatial perturbation methods and human organoid models have connected genetic variation to cell-type-specific and developmental phenotypes, while also revealing substantial mutation-specific effects and methodological sensitivity. Genetic testing increasingly provides aetiological diagnoses and informs medical surveillance. Recent developments also illustrate the therapeutic potential of gene-first approaches for selected monogenic neurodevelopmental disorders. SUMMARY: Recent developments have expanded our understanding of the way the genetic basis of autism manifests phenotypically.

autism↗

Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results across studies. Here, we performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) and genetic data to understand which decision points may affect performance. Clinical data in the form of structured diagnostic codes, medications, procedural codes, and demographics were extracted from two large independent health systems and polygenic risk scores (PRS) were generated across all patients with genetic data in the corresponding biobanks. Crohn's disease was used as the model phenotype based on its substantial genetic component, established EHR-based definition, and sufficient prevalence for model training and testing. We investigated the impact of PRS integration method, as well as choices regarding training sample, model complexity, and performance metrics. Overall, our results show that including PRS resulted in higher performance by some metrics but the gain in performance was only robust when combined with demographic data alone. Improvements were inconsistent or negligible after including additional clinical information. The impact of genetic information on performance also varied by PRS integration method, with a small improvement in some cases from combining PRS with the output of a clinical model (late-fusion) compared to its inclusion an additional feature (early-fusion). The effects of other modeling decisions varied between institutions though performance increased with more compute-intensive models such as random forest. This work highlights the importance of considering methodological decision points in interpreting the impact on prediction performance when including PRS information in clinical models.

Preprint↗

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

BACKGROUND: Comorbid anxiety disorders (ANX) and major depression (MD) have worse clinical outcomes than either disorder alone. Analysis of genomic data based on comorbidity status may reveal more precise biological pathways and causal relationships with potential clinical implications. We investigated the genetic relationship between ANX and MD with and without mutual comorbidity. METHODS: We leveraged data from UK Biobank to perform disorder-specific genome-wide association studies (GWAS) of ANX-only (n=189,422) and MD-only (n=194,339) and generate polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa, n = 130,992) served to test the associations of PRS with diagnoses. MD and ANX GWAS, including comorbidities (MD-comorbid and ANX-comorbid), were used for comparison. Genetic correlations were compared by comorbidity status, and Mendelian randomization was employed to assess causal relationships. RESULTS: The MD-only PRS showed a stronger association with MD-only compared to ANX-only cases (Z=3.74; Padjusted=0.002); however, MD-comorbid PRS did not show a significant difference (Z=2.71; Padjusted=0.08). The genetic correlation between ANX-only and MD-only was 0.53, lower than between ANX-comorbid and MD-comorbid (0.90). ANX-only showed a causal relationship with MD-only (Padjusted=0.015), but not vice versa, and contrasted the bidirectional causal relationship (Padjusted=2.9e-12, and Padjusted=9.3e-06) when comorbidity was included. Gene sets of MD-comorbid, ANX-comorbid, and MD-only, but not of ANX-only, were enriched for immune regulation pathways such as interleukin production. CONCLUSIONS: ANX and MD show more distinct genetics when comorbid cases are excluded, and ANX may be causal for MD. Disorder-specific genetic studies help uncover more relevant biological mechanisms and guide tailored clinical interventions.

Journal Article↗

Linkage between HLA-B8 and HLA-DQ2.5 Contributes to Ancestry-Dependent Genetic Risk for Celiac Disease.

BACKGROUND: Most genetic studies on celiac disease (CeD) have focused on individuals of European descent. Limited data are available for the Hispanic and black populations. METHODS: We analyzed whole-genome sequencing data, electronic health records (EHR), and laboratory results from the All of Us Research Program. We identified 3,481 individuals with CeD through EHR, self-reporting, or both. Of these, 2,899 carried one of the four well-established risk haplotypes, including 262 of admixed American (89% Hispanic) and 108 of African (70% black) ancestry. Five sex-, age-, and ancestry-matched controls per case were selected for the assessment of genetic and clinical risk factors. RESULTS: An enrichment in the DQB1*02:01 allele was observed in CeD patients across all ancestries, with the strongest association in Europeans (32.3% vs. 11.6%), followed by Americans (18.5% vs. 8.1%) and Africans (15.7% vs. 8.1%). Among individuals carrying the DQ2.5 (DQA1*05:01-DQB1*02:01 haplotype), HLA-B8 was present in 72.3% of Europeans, 42.3% of Admixed Americans, and lower in Africans. This linkage disequilibrium was higher in CeD patients than in controls across all three ancestries. A polygenic risk score distinguished seropositive CeD from controls with 86% accuracy. Incorporating clinical risk factors, including family history, hypothyroidism, diarrhea, vitamin D deficiency, and anemia, increased predictive accuracy to 92%. The model identified 93% of CeD patients with tTG-IgA levels greater than 10 IU/mL. CONCLUSION: Linkage between HLA-B8 and DQ2.5 differs significantly among individuals of European, admixed American, and African ancestry, contributing to ancestry-dependent genetic risk for CeD.

Celiac disease↗

Genome-wide association studies of binge eating behaviour and anorexia nervosa yield insights into the unique and shared biology of eating disorder phenotypes.

Eating disorders -including anorexia nervosa (AN), bulimia nervosa, and binge eating disorder-are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. We conducted the first genomic meta-analysis of binge eating behaviour (BE; 39,279 cases, 1,227,436 controls), alongside new analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six loci associated with BE, including loci associated with higher body mass index (BMI) and impulse-control behaviours. AN GWAS yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry cohorts. BE and AN exhibited similar positive genetic correlations with psychiatric disorders, but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with BMI. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries.

Journal Article↗

Genetic liability to meniscus degeneration and its comorbidity patterns: a phenome-wide association study in the UK Biobank.

Meniscus degeneration is a common knee pathology causing pain, disability, and osteoarthritis. While mechanical factors are established, the contribution of inherited genetic liability to its systemic disease patterns remains unclear. We applied a polygenic risk score (PRS) for meniscus degeneration, derived from FinnGen genome-wide association study (GWAS) results to 323,999 UK Biobank participants and conducted a phenome-wide association study (PRS-PheWAS) across 962 clinical phenotypes. The PRS-PheWAS revealed significant associations beyond musculoskeletal traits, extending to metabolic, cardiovascular, psychiatric, and gastrointestinal domains, indicating broad shared genetic architecture. To support these findings, linkage disequilibrium score regression confirmed strong genetic correlations with osteoarthritis and related arthropathies, and genotype-tissue expression (GTEx) analysis highlighted tissue-specific expression of lead genes (e.g., GDF5, SOX5, BMP6) in connective and metabolic tissues. The results demonstrate that genetic liability to meniscus degeneration extends beyond the knee, sharing pathways with systemic conditions. This systemic genetic architecture underscores the need for integrative management approaches that combine orthopedic care with metabolic and lifestyle interventions.

Journal Article↗