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PubMed2026

Methods for modeling gene-environment interplay using polygenic risk scores.

Polygenic risk scores (PRS) are increasingly recognized as pivotal tools for quantifying disease risk through the aggregation of multiple genetic variants. As sample sizes in genome-wide association studies (GWAS) continue to expand and PRS become more powerful, they are set to play a key role in translational research and personalized medicine. Understanding the interplay of PRS with environmental factors is critical for interpreting and applying PRS in diverse contexts. This interplay manifests in two forms: PRS-by-environment interaction (PRS × E) and gene-environment correlation (rGE). However, despite the growing application and importance of PRS, there are limited guidelines for performing PRS × E interaction analyses while controlling for rGE, which can lead to inconsistencies across studies and misinterpretation of results. Here we provide a review of different methods for performing PRSxE interaction in various epidemiological study designs, propose recommendations for best-practice, and discuss future challenges.

Gene-Environment Interaction↗

PubMed2025

XPRS: a tool for interpretable and explainable polygenic risk score.

SUMMARY: The polygenic risk score (PRS) is an important method for assessing genetic susceptibility to diseases; however, its clinical utility is limited by a lack of interpretability tools. To address this problem, we introduce eXplainable PRS (XPRS), an interpretation and visualization tool that decomposes PRSs into genes/regions and single nucleotide polymorphism (SNP) contribution scores via Shapley additive explanations (SHAPs), which provide insights into specific genes and SNPs that significantly contribute to the PRS of an individual. This software features a multilevel visualization approach, including Manhattan plots, LocusZoom-like plots, and tables at the population and individual levels, to highlight important genes and SNPs. By implementing with a user-friendly web interface, XPRS allows for straightforward data input and interpretation. By bridging the gap between complex genetic data and actionable clinical insights, XPRS can improve communication between clinicians and patients. AVAILABILITY AND IMPLEMENTATION: The XPRS software is publicly available on GitHub at https://github.com/nayeonkim93/XPRS and can see the demo through our cloud-based web service at https://xprs.leelabsg.org/.

Software↗

PubMed2025

Development and evaluation of patient-centred polygenic risk score reports for glaucoma screening.

BACKGROUND: Polygenic risk scores (PRS), which provide an individual probabilistic estimate of genetic susceptibility to develop a disease, have shown effective risk stratification for glaucoma onset. However, there is limited best practice evidence for reporting PRS and patient-friendly reports for communicating PRS effectively are lacking. Here we developed patient-centred PRS reports for glaucoma screening based on the literature, and evaluated them with participants using a qualitative research approach. METHODS: We first reviewed existing PRS reports and literature on probabilistic risk communication. This informed the development of a draft glaucoma screening PRS report for a hypothetical high risk individual from the general population. We designed three versions of the report to illustrate risk using a pictograph, a pie chart and a bell curve. We then conducted semi-structured interviews to assess preference of visual risk communication aids, understanding of risk, content, format and structure of the reports. Participants were invited from an existing study, which aims to evaluate the clinical validity of glaucoma PRS among individuals > 50 years from the general population. Numeracy and literacy levels were assessed. RESULTS: We interviewed 12 individuals. The cohort was highly educated (42% university education), all were European and 50% were female. Numeracy (mean 2.1 ± 0.9, range 0 to 3), graph literacy (mean 2.8 ± 0.8, range 0 to 4) and genetic literacy (mean 24.2 ± 6.2, range - 20 to + 46) showed a range of levels. We analysed the reports under three main themes: visual preferences, understanding risk and reports formatting. The visual component was deemed important to understanding risk, with the pictograph being the preferred visual risk representation, followed by the pie chart and the bell curve. Participants expressed preference for absolute risk in understanding risk, along with the written content explaining the results. The importance of follow-up recommendations and time to glaucoma onset were deemed important. Participants expressed varied opinions in the level of information and the colours used, which informed revisions of the report. CONCLUSIONS: Our study revealed preferences for reporting PRS information in the context of glaucoma screening, to support the development of clinical PRS reporting. Further research is needed to assess PRS communication in other groups representative of target populations and with other target audiences (e.g. referring clinicians), and its potential psychosocial impact in the wider community.

Humans↗

PubMed2026

Addition of CAD polygenic risk score to coronary artery calcium score enhances prediction of MACE.

BACKGROUND: Coronary heart disease (CHD) is prevalent in the United States, highlighting the need for accurate risk prediction to inform primary prevention strategies. While multivariate risk models like the Framingham Risk Score and ACC/AHA Pooled Cohort Equations are commonly utilized, novel risk markers, such as the coronary artery calcium score (CACS) and polygenic risk score (PRS), are increasingly gaining recognition. OBJECTIVES: This study aimed to compare the diagnostic utility of CACS and CAD PRS, both individually and in combination, for predicting major adverse cardiovascular events (MACE). METHODS: We conducted a retrospective analysis of a cohort comprising 1,380 predominantly Caucasian participants from the Sanford Health System. CAD PRS was constructed using genetic variants, while CACS was assessed via cardiac computed tomography (CT). Statistical analyses evaluated the relationship between each modality and MACE. RESULTS: Both CAD PRS and CACS were significantly associated with future MACE. Following the adjustment for covariates, the area under the curve (AUC) for both the CACS and PRS models was comparable, indicating similar predictive capabilities for MACE. However, the combination of CAD PRS with CACS significantly enhanced predictive accuracy, outperforming either modality alone. CONCLUSIONS: This study underscores the value of integrating CACS and CAD PRS in predicting MACE. The synergistic effect of CAD PRS combined with CACS markedly improves predictive power. Further research and prospective studies are necessary to validate these findings and assess their clinical implications. Investigating the interactions between PRS and CACS will be crucial for refining cardiovascular risk prediction and optimizing prevention strategies.

cardiac genetics↗

PubMed2026

Polygenic risk score for early identification of coronary artery disease in a real-world clinical setting within the Latvian patient population.

STUDY OBJECTIVE: Polygenic risk scores (PRS) are increasingly recognized for their potential to improve coronary artery disease (CAD) prediction beyond traditional clinical models. This study evaluated the utility of genome-wide association study (GWAS) - derived PRS and pathway-specific PRS (PS-PRS) in the Latvian population, aiming to assess their association with CAD and compare their predictive performance with conventional risk factors. DESIGN PARTICIPANTS AND MAIN OUTCOME MEASURES: The study included 90 early-onset CAD patients and 43 controls with no evidence of atherosclerotic lesions on coronary angiography, with next-generation sequencing performed. PRS was calculated using 192 single nucleotide variants identified from the CARDIoGRAMplusC4D GWAS meta-analysis. The predictive accuracy of PRS, PS-PRS, clinical risk factors, and their combinations was analyzed via ROC curves. RESULTS: The average age was 48.7 years in CAD patients and 49.8 in controls. CAD patients showed significantly higher PRS (mean 0.31) compared to controls (mean - 0.65; p < 0.0001). PRS alone had moderate discriminatory power (AUC = 0.773), slightly lower than LDL cholesterol (AUC = 0.775) and total cholesterol (AUC = 0.821). Combining clinical risk factors improved prediction (AUC = 0.872), with the highest accuracy when PRS was integrated with all clinical factors (AUC = 0.933). The PRS distributions were significantly elevated in early-onset CAD patients across the angiogenesis/tissue repair pathway (p = 0.00038), inflammation pathway (p = 0.043), vascular remodelling pathway (p = 0.0116), and pathway of genes with unknown function in atherosclerosis (p = 0.0035), but overall PRS demonstrated superior discrimination compared to pathway-specific PRS. CONCLUSIONS: Incorporating PRS enhances early-onset CAD risk prediction. Pathway specific PRS had lower discriminative ability than the overall PRS.

Atherosclerosis↗

PubMed2026

Polygenic risk score and its role in cancer susceptibility.

BACKGROUND: Polygenic risk score (PRS) has the ability to stratify inherited susceptibility to cancer and, as a complement to monogenic testing, can identify individuals at increased genetic risk even when no pathogenic variant is detected in high- or moderate-penetrance genes. It reflects the combined additive effects of a large number of low-penetrance variants across the genome, and represents a continuum of genetic susceptibility with an approximately normal distribution. Clinically relevant differences are typically observed in individuals in the highest and lowest percentiles of the PRS distribution, while relative risk gradients depend on the cancer type, the specific PRS model, and the reference population used. PRS is not a single test but rather a family of statistical models that differ in their design, predictive performance, and transferability across populations, underscoring the need for external validation and population-specific calibration of absolute risk. Broader implementation is thus still held back by differences between individual PRS models, limited transferability, and the lack of harmonized guidance on indication, reporting, and clinical decision-making. Consequently, clinical use in the European Union remains largely confined to pilot studies and local projects. Within these initiatives, PRS is most commonly applied in two main ways - either as a triage tool for intensified diagnostics or screening in higher-risk groups, or as a component of multifactorial absolute-risk models (e. g. BOADICEA/CanRisk) that integrate PRS with other risk factors such as pathogenic variants in moderate-penetrance genes (e. g. ATM or CHEK2), family history, or lifestyle factors. By refining absolute-risk estimates, PRS may shift individuals across clinical decision thresholds for more intensive surveillance and preventive strategies. AIM: This review summarizes the principles of PRS, the main sources of variability between models, and its potential applications in risk stratification and personalized cancer screening. It also addresses limitations in transferability, the need for calibration, and the currently limited evidence for improvements in hard clinical outcomes.

Humans↗

PubMed2022

Patient and provider perspectives on polygenic risk scores: implications for clinical reporting and utilization.

BACKGROUND: Polygenic risk scores (PRS), which offer information about genomic risk for common diseases, have been proposed for clinical implementation. The ways in which PRS information may influence a patient's health trajectory depend on how both the patient and their primary care provider (PCP) interpret and act on PRS information. We aimed to probe patient and PCP responses to PRS clinical reporting choices METHODS: Qualitative semi-structured interviews of both patients (N=25) and PCPs (N=21) exploring responses to mock PRS clinical reports of two different designs: binary and continuous representations of PRS. RESULTS: Many patients did not understand the numbers representing risk, with high numeracy patients being the exception. However, all the patients still understood a key takeaway that they should ask their PCP about actions to lower their disease risk. PCPs described a diverse range of heuristics they would use to interpret and act on PRS information. Three separate use cases for PRS emerged: to aid in gray-area clinical decision-making, to encourage patients to do what PCPs think patients should be doing anyway (such as exercising regularly), and to identify previously unrecognized high-risk patients. PCPs indicated that receiving "below average risk" information could be both beneficial and potentially harmful, depending on the use case. For "increased risk" patients, PCPs were favorable towards integrating PRS information into their practice, though some would only act in the presence of evidence-based guidelines. PCPs describe the report as more than a way to convey information, viewing it as something to structure the whole interaction with the patient. Both patients and PCPs preferred the continuous over the binary representation of PRS (23/25 and 17/21, respectively). We offer recommendations for the developers of PRS to consider for PRS clinical report design in the light of these patient and PCP viewpoints. CONCLUSIONS: PCPs saw PRS information as a natural extension of their current practice. The most pressing gap for PRS implementation is evidence for clinical utility. Careful clinical report design can help ensure that benefits are realized and harms are minimized.

Clinical Decision-Making↗

PubMed2026

Genome-wide association, polygenic risk scores, and machine learning for chronic post-surgical pain risk stratification: A UK biobank study.

Chronic post-surgical pain is a prevalent and debilitating complication following surgery, representing a clinical challenge. Despite the established heritability of pain phenotypes, large-scale genetic studies remain limited. This study aimed to identify genetic variants associated with chronic post-surgical pain, develop polygenic risk scores, and integrate these with clinical features for risk prediction. UK Biobank data from 47,836 participants (2490 cases and 45,346 controls) were split into training (80%; n = 38,268) and validation (20%; n = 9568) sets prior to analysis. A genome-wide association study was conducted on the training set only, across 19 million variants, and polygenic risk scores were constructed and integrated with clinical features in a logistic regression framework. Two close, rare, imputed signals crossed the genome-wide significance threshold but lacked local linkage-disequilibrium support, while 220 variants crossed the suggestive threshold. In the held-out validation set, cases had higher mean polygenic risk scores than controls (0.138 vs. -0.021; Cohen's d = 0.16, p < 0.001). A logistic regression model integrating clinical features and polygenic risk scores achieved an area under the curve of 0.639 (95% CI: 0.583-0.693), higher than models using either feature set alone. The polygenic risk score for chronic post-surgical pain was among the most important predictors. Risk stratification revealed the top quartile had 3.84-fold higher odds of chronic post-surgical pain than the bottom quartile (95% CI: 2.00-7.37). These findings suggest a possible modest genetic contribution to chronic post-surgical pain. Polygenic risk scores may complement clinical factors in surgical risk stratification. PERSPECTIVE: Chronic post-surgical pain may have a modest genetic contribution. This UK Biobank study identified over 220 variants at suggestive significance and constructed a polygenic risk score that was significantly elevated in cases. A combined clinical-genomic model achieved a 3.84-fold difference in odds across predicted-risk quartiles.

Chronic post-surgical pain↗

PubMed2025

Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation.

Diabetes mellitus encompasses several disorders, each with differing clinical presentation, prognoses and pathophysiology. Distinct polygenic architectures underlie type 1 diabetes mellitus and type 2 diabetes mellitus, and govern numerous pathophysiological pathways that converge on dysglycaemia. Over the previous decade, polygenic risk scores (PRS) derived from large genome-wide association studies have become broadly recognized for their potential in precision medicine. PRS, and now partitioned polygenic scores generated by clustering of risk variants, can quantify individual genetic predisposition to diabetes mellitus and reveal molecular heterogeneity responsible for variation in clinical presentation and prognoses. In this Review, we examine and contrast progress in the development of type 1 diabetes mellitus PRS and type 2 diabetes mellitus PRS, and discuss paths to further methodological advances. We examine how studies in the past 10 years have harnessed PRS and novel partitioned polygenic scores to reveal insights into diabetes mellitus aetiology and characterize changes in cellular and tissue-specific disease-modifying molecular pathways. Additionally, we discuss advances and opportunities in areas of clinical translation, including improved classification of diabetes mellitus type, screening of those at risk and personalized interventions informed by PRS. Finally, we emphasize the urgent need to overcome ancestry-related challenges and highlight current progress and gaps in ensuring the equitable translation of PRS for diabetes mellitus precision medicine.

Humans↗

PubMed2026

bioETH-PRS: confidential polygenic risk scoring with smart contracts on an FHE-enabled blockchain.

Polygenic risk scores (PRSs) aggregate genetic effect estimates to predict disease susceptibility, yet calculating one through an external service can require exposing raw genotype data. Homomorphic encryption hides those data during the calculation but, in prior work, still places a designated evaluator in a position of trust. We present bioETH-PRS, a protocol that replaces the evaluator with publicly auditable smart contracts on a blockchain supporting Fully Homomorphic Ethereum Virtual Machine (fhEVM). Using integer-exact encrypted arithmetic, bioETH-PRS computes the PRS dot product entirely in the encrypted domain, so genotype dosages and, at the model provider's discretion, the GWAS weights stay hidden from the parties performing the computation. A fixed-point encoding represents signed weights as nonnegative integers within a bound that rules out overflow, recovering the score to the precision of the published weights. A four-contract architecture separates data custody, model publication, computation, and output release, and supports both a classic path that stores encrypted inputs and an appreciably cheaper streaming path that discards them. A release oracle can return a randomized risk category instead of the raw score, limiting what a repeated querier learns. Prototype evaluation on real GWAS fixtures, including a run on a public testnet, shows cost growing linearly with variant count and suggests the approach may be practical where transaction fees are low. Trust is redistributed rather than removed: the system still depends on the contracts, the blockchain, and the fhEVM services. We evaluate additive models of moderate size, not genome-wide or clinical use.

Blockchain↗

PubMed2025

Predicting Weight Loss After Vertical Sleeve Gastrectomy Using a Whole-genome Sequencing-derived Polygenic Risk Score in the All of Us Cohort.

OBJECTIVE: To create a genome-wide polygenic risk score (PRS) to improve prediction of a 12-month percentage weight loss (WL) after vertical sleeve gastrectomy (VSG). BACKGROUND: Variability in post-VSG WL is not well explained by clinical factors. The All of Us program provides access to a 414,830 short-read whole-genome sequencing resource, enabling unbiased discovery of genetic predictors after VSG. METHODS: VSG counts, demographic, anthropomorphic and vital sign information were obtained from the linked electronic health record. The discovery cohort (DC) included participants from version 7 carried into version 8 while the validation cohort (VC) included those newly added to v8. We defined good responders and nonresponders as having WL±1SD from the mean. Following quality filtering, we applied a 2-stage penalized-regression, followed by elastic-net logistic regression, to identify 1583 stable variants and derive β-weights. We then tested this PRS on the DC into a prediction model. RESULTS: We identified 395 participants in the DC and 336 participants in the VC, respectively. Of these, VSG, 44 were classified as good responders (≥37% WL) and 55 as nonresponders (≤19% WL). In the VC, 55 were classified as good responders and 48 as nonresponders. Adding the PRS to models to clinical predictors increased the area under the curve following logistic regression by 0.03; P <4.3 × 10 -14 , random forest by 0.03; P <9.1 × 10 -7 , decision tree by 0.05; P = 1.2 × 10 -3 , and gradient boosting by 0.08; P <8.3 × 10 -10 . CONCLUSIONS: Use of short-read whole-genome sequencing from All of Us (AoU) can be effectively used to generate PRS to enhance predictive WL accuracy. This work has implications for outcomes of both bariatric surgery and other surgical procedures.

Humans↗

PubMed2025

Psychiatric Polygenic Risk Scores and Week-by-Week Symptomatic Status in Youth with Bipolar Disorder: An Exploratory Study.

Introduction: Prior studies have demonstrated that, in both adults and youth, bipolar disorder (BD) is a polygenic illness. However, no studies have examined polygenic risk scores (PRSs) in relation to the longitudinal course of mood symptoms in youth with BD. Methods: This study included 246 youth of European ancestry with BD (7-20 years old at intake) from the Course and Outcome of Bipolar Youth study and Centre for Youth Bipolar Disorder. Mood symptom severity was assessed at intake and, for 168 participants, prospectively for a median of 8.7 years. PRSs for BD, schizophrenia (SCZ), major depressive disorder (MDD), and attention-deficit/hyperactivity disorder (ADHD) were constructed using genome-wide summary statistics from independent adult cohorts. Results: Higher BD-PRS was significantly associated with lower most severe lifetime depression score at intake (β = -0.14, p = 0.03). Higher SCZ-PRS and MDD-PRS were associated with significantly less time spent in euthymia (SCZ-PRS: β = -0.21, p = 0.02; MDD-PRS: β = -0.22, p = 0.01) and more time with any subsyndromal mood symptoms (i.e., any mania, mixed, or depression symptoms; SCZ-PRS: β = 0.15, p = 0.04; MDD-PRS: β = 0.17, p = 0.01) during follow-up. PRSs for BD and ADHD were not significantly associated with any longitudinal mood variable. Conclusions: This exploratory analysis was the first to examine psychiatric PRSs in relation to the prospective course of mood symptoms among youth with BD. Results from the current study can serve to guide future youth BD studies with larger sample sizes on this topic.

Humans↗

PubMed2025

Coronary Artery Disease-Based Polygenic Risk Score in Early-Onset Acute Myocardial Infarction Subtypes.

BACKGROUND: The coronary artery disease-based polygenic risk score (PRS-CAD) estimates risk of acute myocardial infarction (AMI), but its performance across AMI subtypes in younger individuals, especially women, remains uncertain. OBJECTIVES: The authors assessed PRS-CAD's performance in AMI subtypes. METHODS: We included 2,079 AMI patients aged 18 to 55 years with a 2:1 female-to-male ratio from the VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young Acute Myocardial Infarction Patients) study and 3,761 controls from the MESA (Multi-Ethnic Study of Atherosclerosis) study. AMI subtypes were classified using the VIRGO taxonomy. We evaluated PRS-CAD's association with AMI subtypes using multinomial logistic regression and with 1-year outcomes in AMI subtypes using Cox regression. RESULTS: PRS-CAD was significantly associated with MI due to coronary artery disease (N = 1,876; OR: 1.82 per 1-SD increase; 95% CI: 1.67-1.97; P < 0.001) but not with MI with nonobstructive coronary artery disease (N = 188; OR: 1.13 per 1-SD increase; 95% CI: 0.96-1.34; P = 0.14). PRS-CAD's performance did not differ by sex. A 1-SD increase in PRS-CAD was associated with higher risk of 1-year hospitalization or death in patients with MI with nonobstructive coronary artery disease (HR: 1.50; 95% CI: 1.08-2.10; P = 0.02) but not in patients with MI due to coronary artery disease (HR: 0.98; 95% CI: 0.91-1.07; P = 0.67). CONCLUSIONS: PRS-CAD's association with AMI varied by subtype but not by sex in young adults, warranting caution in application.

acute myocardial infarction↗

PubMed2026

A multi-ancestry polygenic risk score for body mass index predicts longitudinal weight change.

BACKGROUND: Identifying individuals at risk for future weight gain is challenging, partly because associations with traditional clinical risk factors may be biased by confounding and reverse causation. Polygenic risk scores (PRS) provide a stable, lifelong measure of genetic predisposition to obesity. However, existing PRS have not been evaluated for their association with longitudinal weight change in adulthood and often lack generalizability across diverse genetic ancestry groups. METHODS: We conducted ancestry-specific genome-wide association study meta-analyses of body mass index (BMI) in populations of European, African or African American, Admixed American, East Asian, and South Asian ancestries and developed ancestry-specific PRS. A multi-ancestry polygenic risk score (MAPRS) was trained using ancestry-specific PRS in a model selection dataset (N = 39,685) from the All of Us Research Program (AoU). We evaluated the MAPRS in an independent AoU model evaluation dataset (N = 158,743) for BMI prediction and in a separate AoU test dataset (N = 78,219) with repeated measurements over 1.5-2.5 years for weight change prediction. The outcomes included change in BMI and ≥ 10% or ≥ 5% total body weight (TBW) gain. We further examined the relationship between MAPRS and 12 clinical risk factors commonly comorbid with obesity in relation to weight change. RESULTS: The MAPRS captured 7.05% of the variance in measured BMI in the AoU model evaluation dataset and demonstrated improved generalizability across all non-European genetic ancestry groups. In the AoU test dataset, conditioned on baseline BMI at the second-to-last measurement, a one SD increase in MAPRS was associated with a 0.16 kg/m2 increase in future BMI (standard error = 0.012 kg/m2; p-value = 2.2 × 10-39), 1.27-fold increased odds of experiencing ≥ 10% TBW gain (95% CI: 1.24-1.31; p-value = 1.4 × 10-55), and 1.15-fold increased odds of experiencing ≥ 5% TBW gain (95% CI: 1.13-1.18; p-value = 2.8 × 10-39). These associations were observed across all genetic ancestry groups and remained highly consistent after adjustment for any clinical risk factor. In contrast, most clinical risk factors demonstrated inconsistent or weaker associations with weight change outcomes. CONCLUSIONS: We developed an MAPRS for BMI that represents a robust and generalizable risk factor for longitudinal weight gain in adulthood, providing a foundation for genetically informed risk stratification and earlier, more targeted obesity prevention strategies.

Humans↗

PubMed2024

Cost-effectiveness of population-wide genomic screening for Lynch Syndrome and polygenic risk scores to inform colorectal cancer screening.

PURPOSE: Genomic screening to identify individuals with Lynch Syndrome (LS) and those with a high polygenic risk score (PRS) promises to personalize colorectal cancer (CRC) screening. Understanding its clinical and economic impact is needed to inform screening guidelines and reimbursement policies. METHODS: We developed a Markov model to simulate individuals over a lifetime. We compared LS+PRS genomic screening with standard of care (SOC) for a cohort of US adults at age 30. The Markov model included health states of no CRC, CRC stages (A-D), and death. We estimated incidence, mortality, and discounted economic outcomes of the population under different interventions. RESULTS: Screening 1000 individuals for LS+PRS resulted in 1.36 fewer CRC cases and 0.65 fewer deaths compared with SOC. The incremental cost-effectiveness ratio was $124,415 per quality-adjusted life year; screening had a 69% probability of being cost-effective using a willingness-to-pay threshold of $150,000/quality-adjusted life year . Setting the PRS threshold at the 90th percentile of the LS+PRS screening program to define individuals at high risk was most likely to be cost-effective compared with 95th, 85th, and 80th percentiles. CONCLUSION: Population-level LS+PRS screening is marginally cost-effective, and a threshold of 90th percentile is more likely to be cost-effective than other thresholds.

Humans↗

PubMed2026

Polygenic risk scores and lifestyle factors predicting new onset of type 2 diabetes in the Japanese general population.

PURPOSE: This study investigated the association of polygenic risk scores (PRS) and lifestyle factors with type 2 diabetes mellitus development in Japanese populations and evaluated whether PRS can improve diabetes risk prediction beyond traditional risk factors. METHODS: We conducted a cross-sectional and a longitudinal study using the Shika resident cohort (n = 895) and the Toshiba worker cohort (n = 7019), respectively. Participants were categorized into low, intermediate, and high genetic risk groups using PRS constructed with genome-wide association study data from East Asian populations. We defined diabetes based on hemoglobin A1c, fasting blood glucose, self-reported diagnosis, or medication use. The associations of PRS and lifestyle factors with diabetes development were analyzed using multivariate logistic regression and Cox proportional hazards models. RESULTS: Higher PRS were associated with increased diabetes risk in both cohorts (resident cohort: odds ratio 4.51, 95% CI 2.53-8.04; worker cohort: hazard ratio 1.50, 95% CI 1.23-1.83 for high vs low PRS), which remained consistent across age, body mass index, and comorbidities. Regular exercise, absence of hypertension, and absence of dyslipidemia were associated with lower diabetes risk, particularly in the high PRS group. The addition of PRS to conventional prediction models improved the discrimination of diabetes risk. MAIN CONCLUSION: PRS are associated with diabetes risk in Japanese general populations, independent of traditional risk factors. Nonetheless, healthy lifestyle habits may reduce diabetes risk even among genetically susceptible individuals, which support the utility of PRS for personalized diabetes risk assessment and prevention strategies.

Adult↗

PubMed2025

Polygenic risk scores in the clinic: Health-system leaders and primary care providers weigh in.

PURPOSE: The fourth phase of the Electronic Medical Records and Genome Network is testing the return of 10 polygenic risk scores (PRS) across multiple clinics. Understanding the perspectives of health-system leaders and frontline clinicians can inform plans for implementation of PRS. METHODS: A total of 15 health-system leaders and 20 primary care providers took part in semistructured interviews. A descriptive thematic analysis was performed. RESULTS: Interviewees generally perceived PRS to have limited clinical utility, although they saw value in the potential to identify and act upon risks that are not otherwise detectable. Perceived potential drawbacks included negative psycho-emotional effects on patients, unnecessary follow-up, distracting from population health priorities, opportunity costs, and medicolegal liability. Implementation considerations included increased encounter time and the need for clinical practice guidelines, provider training, care coordination, and point-of-care resources. CONCLUSION: Participants generally expressed favorable views of precision medicine and also identified potential challenges to introducing PRS in clinical care. Implementation will require careful assessment of clinical utility vs usual care; ensuring that the benefit to be realized merits the time and resources required to interpret, return, and act on results and developing guidelines and other decision-making supports for providers and patients.

Humans↗

PubMed2026

Comparison of Performance of Publicly Available Polygenic Risk Scores to Predict Clinically Actionable Coronary Artery Calcium Scores: The BioHEART-CT Cohort.

AIM: Coronary artery disease (CAD) remains the leading cause of morbidity and mortality globally. Polygenic Risk Scores (PRS) have been trained against major adverse cardiovascular outcomes (MACE) in large cohorts. Few studies have examined the effectiveness of these CAD MACE PRS tools in detecting individuals with subclinical coronary calcification. An association would provide an opportunity for clinical translation and targeting of CT imaging to new patients at risk for subclinical disease. METHODS: An analysis of 53 publicly available CAD PRS tools was completed in participants of the BioHEART-CT Discovery 1000 cohort presenting for clinically referred CT coronary angiography (CCTA). Associations between PRS and two binary CACS outcomes reflecting clinically significant coronary calcification were assessed: a) Absolute CACS (CACS ≥100 Agatston units [AU]; and b) Percentile CACS (CACS ≥75th age-/sex-adjusted percentile). Models were adjusted for genetic principal components, modifiable cardiovascular risk factors, and age/sex (in Absolute CACS). A subgroup analysis was performed using Framingham Risk Score (FRS) at baseline. RESULTS: Among 803 BioHEART-CT Discovery 1000 participants, 487 (60.6%) had any detectable coronary calcium. Most PRS tools demonstrated significant association with CACS outcomes, particularly evident when PRS was modelled as a continuous predictor. For Percentile CACS, 94.3% of PRS tools were significantly associated after full adjustment (median OR per PRS SD 1.41 (IQR 1.23-1.60). Quintile-based analysis revealed that individuals in the Top Quintile PRS had up to 7.99-fold increased odds of Percentile CACS ≥75th compared to those in the Bottom Quintile. Analysis by FRS group revealed positive performance, especially in individuals of Low FRS wherein incorporating a PRS increased pre-test probability from 14% to 26%. CONCLUSION: Whilst most CAD PRS tools have been developed against clinical events, we show their ability to predict clinically relevant coronary calcification. Utility appears strongest in individuals traditionally considered lower risk, presenting an opportunity for clinical translation for improved diagnosis in the primary prevention setting, with the potential to triage individuals into a CACS screening pathway.

coronary artery disease↗