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PubMed2026

Genetic Risk Factors for Kidney Function in Individuals with Type 1 Diabetes.

KEY POINTS: Previous research has identified polygenic risk scores that are associated with low eGFR and albuminuria in the general population. We observed that these eGFR and albuminuria polygenic risk scores were associated with eGFR and albuminuria, respectively, in type 1 diabetes. Associations were independent of glycemic control and suggest shared genetic kidney risk factors between type 1 diabetes and the general population. BACKGROUND: Genetic risk factors underlying kidney disease in type 1 diabetes (T1D) remain poorly understood. We examined whether previously established polygenic risk scores (PRS) for eGFR and albuminuria are associated with these measures in adults with T1D in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications study. METHODS: We applied eGFR and albuminuria PRS derived in general population cohorts to 1304 DCCT/Epidemiology of Diabetes Interventions and Complications participants with genome-wide genotyping. We tested PRS associations with eGFR and urine albumin excretion rate (AER) as well as incident eGFR <60 ml/min per 1.73 m 2 , AER ≥30 mg/24 h, and AER ≥300 mg/24 h. For consistency, PRS values were linearly transformed so higher scores corresponded to higher eGFR and AER. We also examined associations of kidney outcomes with rs55703767 in COL4A3 , which has previously been associated with CKD in T1D. RESULTS: At DCCT baseline, participants had a mean age of 27 years; 53% were male. 49% of participants were randomized to intensive versus conventional glucose-lowering therapy. Participants were followed for median of (first-third quartiles) 35 (33-37) years. The eGFR PRS was significantly associated with continuous eGFR (per one SD higher PRS 2.72 ml/min per 1.73 m 2 higher [95% confidence interval (CI), 2.05 to 3.40]) and incident eGFR <60 ml/min per 1.73 m 2 (hazard ratio [HR]=0.82 [95% CI, 0.73 to 0.92]), but not consistently with albuminuria. There was no association with quantitative AER (2.42 mg/24 h [95% CI, -1.86 to 6.89]) or sustained AER ≥30 mg/24 h (HR=1.03; [95% CI, 0.94 to 1.14]). The albuminuria PRS was significantly associated with incident AER ≥30 mg/24 h (HR=1.12 [95% CI, 1.02 to 1.22]) but not continuous eGFR (0.49 ml/min per 1.73 m 2 higher [95% CI, -0.23 to 1.21]) or incident eGFR <60 ml/min per 1.73 m 2 (HR=0.96 [95% CI, 0.85 to 1.08]). Associations were similar in analyses stratified by DCCT treatment group assignment. rs55703767 was associated with lower incident macroalbuminuria in the overall cohort (HR=0.77 per minor allele [95% CI, 0.59 to 0.99]), and upon stratification by DCCT treatment group assignment, only within the conventional and not intensive glucose-lowering therapy group. CONCLUSIONS: PRS associated with eGFR and albuminuria in the general population were associated with corresponding measures in adults with T1D. The results suggest shared genetic risk factors for kidney disease between T1D and the general population but different genetic risk factors for albuminuria and eGFR in T1D. CLINICAL TRIALS REGISTRATION NUMBERS: NCT00360893 , NCT00360815 .

Adult↗

PubMed2026

Non-genetic Risk Factors for Allopurinol-Induced Severe Cutaneous Adverse Reaction (SCAR): A Systematic Review.

BACKGROUND: Allopurinol-induced severe cutaneous adverse reactions (SCARs) are rare but potentially life threatening, particularly in Asian populations. While the genetic marker HLA-B*58:01 is a well-established risk factor, non-genetic factors may also contribute. This systematic review synthesizes evidence on associations between non-genetic risk factors and allopurinol-induced SCAR. METHODS: We searched MEDLINE, Scopus, Cochrane Library and Web of Science from inception to 29 June 2026 for observational studies examining non-genetic risk factors for SCAR, defined as Stevens-Johnson Syndrome, Toxic Epidermal Necrolysis, Acute Generalised Exanthematous Pustulosis, or Hypersensitivity Syndrome/Drug Reaction with Eosinophilia and Systemic Symptoms. Adults aged ≥ 18 years were included. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model; heterogeneity was assessed with I2. Mean differences were calculated for continuous variables. NIH Study Quality Assessment Tool was used for quality assessment of the studies. RESULTS: Twenty-six studies were included. Female sex (20 studies; 3340 SCAR cases, 562,647 controls) was associated with an increased risk of allopurinol-induced SCAR (OR 2.06; 95% confidence interval (CI) 1.25-3.38). Chronic kidney disease (16 studies; 1625 SCAR cases, 553,804 controls) was also significantly associated with SCAR (OR 3.78; 95% CI 1.99-7.17). Five studies (177 SCAR cases, 1368 controls) reported higher allopurinol doses among SCAR cases than tolerant controls (mean difference 19.61 mg; 95% CI 2.97-36.24). No significant associations were observed for age or concomitant diuretic use in the primary meta-analyses. Substantial heterogeneity was observed across studies. Sensitivity analyses demonstrated consistent findings for most factors, although concomitant diuretic use became significantly associated with SCAR after exclusion of non-Asian and zero-event studies. CONCLUSION: CKD, female sex, and higher allopurinol dose were identified as significant non-genetic risk factors for allopurinol-induced SCAR. These findings support consideration of non-genetic factors alongside pharmacogenomic screening in future risk-stratification strategies. However, substantial heterogeneity and potential publication bias limit the certainty of the available evidence. Well-designed studies evaluating non-genetic predictors as primary outcomes are needed to develop robust integrated risk prediction models for clinical decision making.

Journal Article↗

PubMed2026

Genetic risk factors of late-onset Alzheimer's disease: Insights into pathophysiology and emerging therapeutic directions.

Late-onset Alzheimer's disease is a devastating and complex neurodegenerative disorder with a multifactorial etiology. Over the past decade, advances in genetic research have identified novel risk genes, shedding light on the underlying pathogenic mechanisms of late-onset Alzheimer's disease. This review provides a comprehensive overview of several of these crucial genetic factors and their potential mechanisms in the pathogenesis of Alzheimer's disease. Genome-wide association studies, whole-genome sequencing, and multi-omics studies have played a crucial role in identifying key risk genes, particularly those involved in amyloid-β metabolism and clearance, such as CLU and APOE, which influence amyloid-β aggregation. Tau pathology, characterized by neurofibrillary tangles, is another hallmark of Alzheimer's disease, with genes such as BIN1 implicated in tau-mediated neurodegeneration. Additionally, immune regulatory genes, including CR1, MS4A6A, CD33, and TREM2, play crucial roles in microglial activation and neuroinflammation, thereby contributing to disease progression. Synaptic dysfunction is also a critical factor in Alzheimer's disease pathology, with genes such as IQCK, EPHA1, and CD2AP linked to synaptic function and plasticity, highlighting their potential impact on cognitive decline. Understanding these genetic risk factors provides valuable insights into the complex genetic landscape of Alzheimer's disease and its highly heterogeneous pathological mechanisms, including amyloid-β metabolism, tau pathology, immune response and neuroinflammation, and synaptic dysfunction. Future research should focus on elucidating the functional roles of these individual genes and their potential as therapeutic targets for altering the course of Alzheimer's disease.

Alzheimer’s disease↗

PubMed2025

Reproducibility of genetic risk factors identified for long COVID using combinatorial analysis across US and UK patient cohorts with diverse ancestries.

BACKGROUND: Long COVID is a major public health burden causing a diverse array of debilitating symptoms in tens of millions of patients globally. In spite of this overwhelming disease prevalence, staggering cost, severe impact on patients' lives and intense global research efforts, study of the disease has proved challenging due to its complexity. Genome-wide association studies (GWAS) have identified only four loci potentially associated with the disease, although these results did not statistically replicate between studies. A previous combinatorial analysis study identified a total of 73 genes that were highly associated with two long COVID cohorts in the predominantly (> 91%) white European ancestry Sano GOLD population, and we sought to reproduce these findings in the independent and ancestrally more diverse All of Us (AoU) population. METHODS: We assessed the reproducibility of the 5343 long COVID disease signatures from the original study in the AoU population. Because the very small population sizes provide very limited power to replicate findings, we initially tested whether we observed a statistically significant enrichment of the Sano GOLD disease signatures that are also positively correlated with long COVID in the AoU cohort after controlling for population substructure. RESULTS: For the Sano GOLD disease signatures that have a case frequency greater than 5% in AoU, we consistently observed a significant enrichment (77-83%, p < 0.01) of signatures that are also positively associated with long COVID in the AoU cohort. These encompassed 92% of the genes identified in the original study. At least five of the disease signatures found in Sano GOLD were also shown to be individually significantly associated with increased long COVID prevalence in the AoU population. Rates of signature reproducibility are strongest among self-identified white patients, but we also observe significant enrichment of reproducing disease associations in self-identified black/African-American and Hispanic/Latino cohorts. Signatures associated with 11 out of the 13 drug repurposing candidates identified in the original Sano GOLD study were reproduced in this study. CONCLUSION: These results demonstrate the reproducibility of long COVID disease signal found by combinatorial analysis, broadly validating the results of the original analysis. They provide compelling evidence for a much broader array of genetic associations with long COVID than previously identified through traditional GWAS studies. This strongly supports the hypothesis that genetic factors play a critical role in determining an individual's susceptibility to long COVID following recovery from acute SARS-CoV-2 infection. It also lends weight to the drug repurposing candidates identified in the original analysis. Together these results may help to stimulate much needed new precision medicine approaches to more effectively diagnose and treat the disease. This is also the first reproduction of long COVID genetic associations across multiple populations with substantially different ancestry distributions. Given the high reproducibility rate across diverse populations, these findings may have broader clinical application and promote better health equity. We hope that this will provide confidence to explore some of these mechanisms and drug targets and help advance research into novel ways to diagnose the disease and accelerate the discovery and selection of better therapeutic options, both in the form of newly discovered drugs and/or the immediate prioritization of coordinated investigations into the efficacy of repurposed drug candidates.

Humans↗

PubMed2025

Genetic risk factors in rheumatoid arthritis: A Mendelian randomization study of chronic kidney disease in European populations.

Rheumatoid arthritis (RA) is a heritable autoimmune disease linked to chronic kidney disease (CKD) in observational studies. However, whether this association is causal and driven by shared genetic risk remains unclear, warranting genetic investigation. To investigate possible causal relationships between RA and different CKD subtypes, we used Mendelian randomization (MR) analyses with data from genome-wide association studies. The inverse variance weighted (IVW) methodology was the main method, and sensitivity analyses were added to improve the validity of the causal estimations. Our analysis predicted that RA significantly increases the risk of IgA nephropathy (IVW odds ratio [OR] = 1.041, 95% confidence interval [CI] = 1.018-1.065, P = 4.286e-04), diabetic nephropathy (IVW OR = 1.078, 95% CI = 1.009-1.152, P = .027), nephrotic syndrome (IVW OR = 1.164, 95% CI = 1.078-1.257, P = 1.012e-04), and chronic renal failure (IVW OR = 1.046, 95% CI = 1.018-1.075, P = 1.000e-03). MR analyses confirmed RA's positive causal effect on these CKD subtypes (all P < .05). While heterogeneity was observed for IgA nephropathy and chronic renal failure, sensitivity analyses (MR-Egger intercept, all P > .05) revealed no evidence of horizontal pleiotropy, supporting the robustness of our findings. Our findings suggest that in European-ancestry populations, a genetic predisposition to RA is causally associated with a higher risk of specific types of CKD. While these results require validation in diverse ethnic groups, they highlight the potential importance of renal monitoring for genetically susceptible RA patients, which may help mitigate the public health burden of CKD.

Humans↗

PubMed2025

Genetic risk factors modulate the association between physical activity and colorectal cancer.

BACKGROUND: Physical activity (PA) is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene-PA interaction analysis. METHODS: Using logistic regression and two-step and joint tests, we analyzed interactions between common genetic variants across the genome and PA in relation to CRC risk. Self-reported PA levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk) and as study- and sex-specific quartiles of activity. RESULTS: PA had an overall protective effect on CRC (OR [active vs. inactive] = 0.85; 95%CI = 0.81-0.90). The two-step GxE method identified an interaction between rs4779584, an intergenic variant near the GREM1 and SCG5 genes, and PA for CRC risk (p-interaction = 2.6×10- 8). Stratification by genotype at this locus showed a significant reduction in CRC risk by 20% in active vs. inactive participants with the CC genotype (OR = 0.80; 95%CI = 0.75-0.85), but no significant PA-CRC association among CT or TT carriers. When PA was modeled as quartiles, the 1-d.f. GxE test identified that rs56906466, an intergenic variant near the KCNG1 gene, modified the association between PA and CRC (p-interaction = 3.5×10- 8). Stratification at this locus showed that increase in PA (highest vs. lowest quartile) was associated with a lower CRC risk solely among TT carriers (OR = 0.77; 95%CI = 0.72-0.82). CONCLUSIONS: In summary, we identified two genetic variants that modified the association between PA and CRC risk. One of them, related to GREM1 and SCG5, suggests that the bone morphogenetic protein (BMP)-related, inflammatory, and/or insulin signaling pathways may be associated with the protective influence of PA on colorectal carcinogenesis.

GWAS↗

PubMed2025

Identification and Validation of Novel Combinatorial Genetic Risk Factors for Endometriosis across Multiple UK and US Patient Cohorts.

BACKGROUND: Endometriosis affects about 10% of women usually of reproductive age. It often has severe negative impacts on patients' quality of life, but the average time to a definitive diagnosis remains 7-9 years, and there are few effective therapeutic options. Relatively little is known about the genetic drivers of the disease even though its heritability is fairly high. A recent large genome wide association study (GWAS) meta-analysis identified 42 genomic loci associated with risk of endometriosis, but together these explain only 5% of disease variance. METHODS: We used the PrecisionLife® combinatorial analytics platform to identify multi-SNP disease signatures significantly associated with endometriosis in a white European UK Biobank (UKB) cohort. We assessed the reproducibility of these multi-SNP disease signatures as well as 35 of the 42 meta-GWAS SNPs in a multi-ancestry American endometriosis cohort from All of Us (AoU) after controlling for population structure. RESULTS: We identified 1,709 disease signatures, comprising 2,957 unique SNPs in combinations of 2-5 SNPs, that were associated with increased prevalence of endometriosis in UKB. Pathways enriched in the disease signatures included cell adhesion, proliferation and migration, cytoskeleton remodeling, angiogenesis as well as biological processes involved in fibrosis and neuropathic pain.We observed a significant enrichment of these signatures (58-88%, p<0.04) that are also positively associated with endometriosis in the AoU cohort, including one 2-SNP signature that is individually significant. Reproducibility rates were greatest for higher frequency signatures, ranging from 80-88% for signatures with greater than 9% frequency (p<0.01) in AoU. Encouragingly, the disease signatures also show high reproducibility rates in non-white European AoU sub-cohorts (66-76%, p<0.04 for signatures with greater than 4% frequency).A total of 195 unique SNPs mapping to 98 genes were identified in the high frequency reproducing signatures (>9%). Of these, 7 genes were previously identified in the endometriosis meta-GWAS study and 16 genes have a previous association with endometriosis. 75 novel genes were identified in this study.We characterized 9 novel genes that occur at the highest frequency in reproducing signatures and that do not contain any SNPs linked to known GWAS genes, providing new evidence for links between endometriosis and autophagy and macrophage biology. Reproducibility rates, ranging between 73% to 85%. are especially strong for the signatures that contain these 9 genes independently of any SNPs mapping to the meta-GWAS genes. CONCLUSION: Although using much smaller, less well-characterized datasets than the previous whole genome meta-GWAS study, combinatorial analysis has provided important new insights into the genetics and biology of endometriosis including reproducible biologically relevant genes that are overlooked by GWAS approaches.The 75 novel gene associations provide new insights and routes for study of the disease and potential new therapies. Several of the novel genes identified are credible targets for drug discovery, repurposing and/or repositioning. Using the disease signatures identified as genetic biomarkers in trials of candidates drugs targeting specific mechanisms will enable precision medicine-based approaches. We hope this will encourage new targeted therapy discovery efforts.

Endometriosis↗

PubMed2024

Cardiovascular Risk Factors and Genetic Risk in Transthyretin V142I Carriers.

BACKGROUND: Nearly 3% to 4% of Black individuals in the United States carry the transthyretin V142I variant, which increases their risk of heart failure. However, the role of cardiovascular (CV) risk factors (RFs) in influencing the risk of clinical outcomes among V142I variant carriers is unknown. OBJECTIVES: This study aimed to assess the impact of CV RFs on the risk of heart failure in V142I carriers. METHODS: This study included self-identified Black individuals without prevalent heart failure from 6 TOPMed (Trans-Omics for Precision Medicine) cohorts, the REGARDS (Reasons for Geographic And Racial Differences in Stroke) study, and the All of Us Research Program. The cohort was stratified based on the V142I genotype and the number of CV RFs (hypertension, diabetes, obesity, and hypercholesterolemia). Adjusted Cox models were used to assess the association of heart failure with the V142I genotype and CV RF profile, taking noncarriers with a favorable CV RF profile as reference. RESULTS: The cross-sectional analysis, including 1,625 V142I carriers among 48,365 Black individuals, found that the prevalence of CV RFs did not vary by V142I carrier status. In the longitudinal analysis, there were 587 (3.2%) V142I carriers among 18,407 Black individuals (median age: 60 years [Q1-Q3: 52-68 years], 63.0% female). Among carriers, the heart failure risk was attenuated with a favorable (0 or 1 RF) CV RF profile (adjusted HR: 2.26; 95% CI: 1.58-3.23) compared with an unfavorable (3 or 4 RFs) CV RF profile (adjusted HR: 4.14; 95% CI: 2.79-6.14). CONCLUSIONS: A favorable CV RF profile lowers but does not abrogate V142I variant-associated heart failure risk. This study highlights the importance of having a favorable CV RF profile among V142I carriers for risk reduction of heart failure.

Aged↗

PubMed2024

Limbic-predominant age-related TDP-43 encephalopathy (LATE-NC): Co-pathologies and genetic risk factors provide clues about pathogenesis.

Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is detectable at autopsy in more than one-third of people beyond age 85 years and is robustly associated with dementia independent of other pathologies. Although LATE-NC has a large impact on public health, there remain uncertainties about the underlying biologic mechanisms. Here, we review the literature from human studies that may shed light on pathogenetic mechanisms. It is increasingly clear that certain combinations of pathologic changes tend to coexist in aging brains. Although "pure" LATE-NC is not rare, LATE-NC often coexists in the same brains with Alzheimer disease neuropathologic change, brain arteriolosclerosis, hippocampal sclerosis of aging, and/or age-related tau astrogliopathy (ARTAG). The patterns of pathologic comorbidities provide circumstantial evidence of mechanistic interactions ("synergies") between the pathologies, and also suggest common upstream influences. As to primary mediators of vulnerability to neuropathologic changes, genetics may play key roles. Genes associated with LATE-NC include TMEM106B, GRN, APOE, SORL1, ABCC9, and others. Although the anatomic distribution of TDP-43 pathology defines the condition, important cofactors for LATE-NC may include Tau pathology, endolysosomal pathways, and blood-brain barrier dysfunction. A review of the human phenomenology offers insights into disease-driving mechanisms, and may provide clues for diagnostic and therapeutic targets.

Humans↗

PubMed2026

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions↗

PubMed2024

Rhinovirus infection of airway epithelial cells uncovers the non-ciliated subset as a likely driver of genetic risk to childhood-onset asthma.

Asthma is a complex disease caused by genetic and environmental factors. Studies show that wheezing during rhinovirus infection correlates with childhood asthma development. Over 150 non-coding risk variants for asthma have been identified, many affecting gene regulation in T cells, but the effects of most risk variants remain unknown. We hypothesized that airway epithelial cells could also mediate genetic susceptibility to asthma given they are the first line of defense against respiratory viruses and allergens. We integrated genetic data with transcriptomics of airway epithelial cells subject to different stimuli. We demonstrate that rhinovirus infection significantly upregulates childhood-onset asthma-associated genes, particularly in non-ciliated cells. This enrichment is also observed with influenza infection but not with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or cytokine activation. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.

Humans↗

PubMed2026

Genome-wide association study of asthma with high treatment burden and/or worse outcomes defined using electronic healthcare data in UK Biobank.

BACKGROUND: In ∼10% of asthma patients, symptoms remain uncontrolled despite maximal treatment, representing an unmet clinical need. The causal variants, genes and pathways underlying genetic risk factors have not been fully elucidated, and it is unclear whether there are unique genetic risk factors for this asthma subtype. METHODS: We used electronic healthcare records linked to UK Biobank to identify asthma patients with high treatment burden and/or worse outcomes. We performed a genome-wide association study (GWAS) with this case population and healthy controls. We sought replication for associated (p≤5×10-6) signals in four independent studies (12 152 cases and 32 316 controls). Replicated signals were fine-mapped and linked to genes and pathways. RESULTS: In total, 7681 participants met our case definition and showed enrichment for adult-onset asthma, female gender and higher body mass index compared to asthma individuals not meeting case criteria. GWAS with 7681 cases and 38 405 controls revealed 21 reproducible association signals that had previously been associated with asthma, but had a larger effect size in our study. Variant-to-gene mapping highlighted 85 candidate genes, five of which were considered high confidence (BACH2, D2HGDH, IL1RL1, RPS26, SMAD3). CONCLUSION: We present the first use of electronic healthcare records in UK Biobank to identify a subtype of asthma enriched for patients with high treatment burden and/or worse outcomes. Our findings support the role of known asthma genes, highlighting genetic risk variants with stronger effect in these groups of patients. The prioritised genes provide potential therapeutic opportunities for this difficult-to-treat patient population.

Journal Article↗

PubMed2025

Patient stratification by genetic risk in Alzheimer's disease is only effective in the presence of phenotypic heterogeneity.

Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (α = 5×10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE ε4 status predicts amyloid-β and tau positive versus negative patients (odds ratio for an additional APOE ε4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results.

Alzheimer Disease↗

PubMed2026

Implementing a Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease in a Diverse Cohort.

PURPOSE: We describe a prospective cohort study (NCT05277116) conducted in phase IV of the electronic MEdical Records and GEnomics (eMERGE) Network to implement a multi-ancestry polygenic risk score for coronary heart disease (PRSCHD: PGS004696) and assess outcomes after return of results (RoR). METHODS: PRSCHD was considered alongside family history (FamHxCHD), monogenic risk from familial hypercholesterolemia (FH), and clinical risk factors, to return CHD risk as part of a Genome Informed Risk Assessment (GIRA) report. Participants with high PRSCHD (top 5th percentile) or FH received their results from study personnel, while participants with FamHxCHD were informed by mail/email. Results were placed in the electronic health record and communicated to the primary care provider. The primary outcome of initiation/intensification of lipid lowering therapy within 12 months after RoR is compared between participants with PRSCHD ≥95th percentile and those with PRSCHD 90th-94th percentile, using a regression discontinuity design. Secondary outcomes include ordering of screening tests, a new CHD diagnosis, and lifestyle changes. RESULTS: By April 2025, 20,421 adults were enrolled: mean age 50±15 years (range 18-75 years), 68% female, 50% belonging to health disparity groups, and 40% non-White by self-report. Prevalence of CHD, FamHxCHD, high PRSCHD and FH was 4.0%, 10.2%, 4.3% and 0.7%, respectively; 14.3% had at least one of the three CHD genetic risk factors and CHD risk estimates were highest in those who self-reported as Black. CONCLUSION: The prevalence of increased genetic risk for CHD was high and at least one of the three genetic risk factors for CHD was present in 14.2% of the cohort. Analyses are underway to assess outcomes after PRSCHD implementation in the context of FamHxCHD, FH, and clinical risk, across the age spectrum in a diverse cohort.

PRS↗

PubMed2026

Joint effects of childhood adversity and genetic risk for psychosis on psychopathology in the UK Biobank.

BACKGROUND: The individual effects of genetic factors and adverse childhood experiences (ACEs) on risk of psychosis, including schizophrenia (SCZ) and bipolar disorder (BIP), have been widely acknowledged, but their interaction effects on individual psychopathological symptoms remain unclear. METHODS: Based on data from 163,704 individuals in the UK Biobank, we investigated the joint effects of polygenic risk scores (PRSs) of SCZ and BIP and ACEs on psychopathology. ACEs status and 55 psychopathological symptoms from seven domains were measured retrospectively using an online mental health questionnaire in 2016. Recent genome-wide association studies for SCZ and BIP were combined with genotype data to generate PRSs. Logistic regression analyses were then conducted to explore univariate and joint main effects of PRSs and ACEs on psychopathological symptoms, as well as their additive and multiplicative interaction effects. RESULTS: The interaction mechanisms for PRSs and ACEs varied across symptom domains: additive interactions were observed on the depression (RERIBIP-ACEs = 0.20-0.25), anxiety (RERISCZ-ACEs = 0.20; RERIBIP-ACEs = 0.22-0.26), help-seeking (RERISCZ-ACEs = 0.24; RERIBIP-ACEs = 0.23), and cognition domains (RERISCZ-ACEs = -0.23 to -0.17), whereas multiplicative interactions were only detected on the psychotic (betaSCZ-ACEs = -0.543; betaBIP-ACEs = -0.181), mania (betaBIP-ACEs = -0.195), self-harm or suicide (betaSCZ-ACEs = -0.118), and cognitive domains (betaSCZ-ACEs = -0.204 to -0.157). CONCLUSIONS: The interplay mechanisms for genetic liability to SCZ and BIP and ACEs vary across symptom domains. This study reveals heterogeneity in gene-ACEs interaction mechanisms underlying psychosis and may provide personalized guidance for psychological care after ACEs.

Humans↗

PubMed1978

[Genetically determined risk factors for malignant tumors in man].

Explore the source record for details and available documents.

Cell Transformation, Neoplastic↗

PubMed2026

Maternal age as a driver of genome instability: mechanisms linking aneuploidy, mutagenesis and mitochondrial dysfunction.

Advanced maternal age is a well-established risk factor for adverse reproductive outcomes due to increased rates of aneuploidy. However, emerging evidence indicates that the genetic consequences of maternal aging extend well beyond chromosome mis-segregation. Aging oocytes acquire a broad spectrum of genetic abnormalities, including maternally derived nuclear de novo mutations (DNMs) and mitochondrial DNA mutations, together with epigenetic dysregulation of DNA methylation and post-translational modification levels. These changes reflect the unique biology of the female germline in which oocytes remain arrested in meiotic prophase I for decades. Age-related deterioration of key processes, such as erosion of cohesion complexes, altered meiotic recombination, and weakened spindle assembly checkpoint surveillance collectively destabilize meiotic chromosome architecture, directly driving chromosome mis-segregation. At the same time, accumulation of endogenous DNA damage and declining DNA damage and repair processes increase the chances of transmitting lesions that can be converted into sequence-level mutations during the earliest embryonic divisions, when genome maintenance relies exclusively on maternal factors. High-resolution sequencing studies further demonstrate that maternal aging is associated with increased DNMs burden in both nuclear and mitochondrial DNA. Together, these findings support a model in which maternal aging is a driver of genome-wide instability that links aneuploidy and mutagenesis through shared defects in meiotic surveillance, declining DNA repair efficiency, and mitochondrial function. This framework positions delayed childbearing as a multifaceted genetic risk factor that extend beyond aneuploidy to include mutations and other genomic alterations that can impact intergenerational genetic risk.

Aneuploidy↗

PubMed2026

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans↗