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PubMed2004

Polygenic variation maintained by balancing selection: pleiotropy, sex-dependent allelic effects and G x E interactions.

We investigate three alternative selection-based scenarios proposed to maintain polygenic variation: pleiotropic balancing selection, G x E interactions (with spatial or temporal variation in allelic effects), and sex-dependent allelic effects. Each analysis assumes an additive polygenic trait with n diallelic loci under stabilizing selection. We allow loci to have different effects and consider equilibria at which the population mean departs from the stabilizing-selection optimum. Under weak selection, each model produces essentially identical, approximate allele-frequency dynamics. Variation is maintained under pleiotropic balancing selection only at loci for which the strength of balancing selection exceeds the effective strength of stabilizing selection. In addition, for all models, polymorphism requires that the population mean be close enough to the optimum that directional selection does not overwhelm balancing selection. This balance allows many simultaneously stable equilibria, and we explore their properties numerically. Both spatial and temporal G x E can maintain variation at loci for which the coefficient of variation (across environments) of the effect of a substitution exceeds a critical value greater than one. The critical value depends on the correlation between substitution effects at different loci. For large positive correlations (e.g., rho(ij)2>3/4), even extreme fluctuations in allelic effects cannot maintain variation. Surprisingly, this constraint on correlations implies that sex-dependent allelic effects cannot maintain polygenic variation. We present numerical results that support our analytical approximations and discuss our results in connection to relevant data and alternative variance-maintaining mechanisms.

Data Interpretation, Statistical↗

PubMed1975

Studies on the nature and function of polygenic loci in Drosophila. III. Veinlet modifiers having region-specific effects upon the vein pattern.

Polygenic modifiers affecting the expression of the mutant veinlet were studied to determine whether each acts specifically upon one vein or wing region or whether they affect the venation pattern in some general way. Selection experiments showed that the L4 vein can be modified independently of the L2 and L3 veins. Similarly, the L2 vein can be shortened while the L3 is selected to be longer, although there is some interdependence between the L2 and L3 veins. Assays of heterozygous whole chromosome effects show that different chromosomes are involved in the responses of separate veins, and one polygenic locus causing a decrease in L4 vein length has been isolated. Substitutions of whole chromosomes from selection lines into unselected backgrounds of non-homologous mutants demonstrate that the selected modifiers have the same qualitative effects upon other mutants having similar phenotypes. These results support the hypothesis that the polygenic modifiers affecting veinlet expression function independently of the veinlet locus, presumably by influencing common steps in the developmental processes leading to the formation of individual veins.

Alleles↗

PubMed1997

Evidence by allelic association-dependent methods for a type 1 diabetes polygene (IDDM6) on chromosome 18q21.

Type 1 diabetes is a common polygenic disease. Fine mapping of polygenes by affected sibpair linkage analysis is not practical and allelic association or linkage disequilibrium mapping will have to be employed to attempt to detect founder chromosomes. Given prior evidence of linkage of the Jk-D18S64 region of chromosome 18q12-q21 to type 1 diabetes, we evaluated the 12 informative microsatellite markers in the region for linkage with disease by the transmission disequilibrium test (TDT) in a UK data set of type 1 diabetic families (n = 195). Increased transmission of allele 4 of marker D18S487 to affected children was detected (P = 0.02). Support for this was extended in a total of 1067 families from four different countries by isolating, and evaluating by the TDT, two novel microsatellites within 70 kb of D18S487. Evidence for linkage and association was P = 5 x 10(-5) and 3 x 10(-4), respectively. There was no evidence for increased transmission of associated alleles to nonaffected siblings. Analysis of an additional 390 families by the TDT did not extend the evidence further, and reduced support in the total 1457 families to P = 0.001 for linkage and P = 0.003 for association. However, evidence for linkage by affected sibpair allele sharing was strong (P = 3.2 x 10(-5)) in the second data set. Heterogeneity in TDT results between data sets was, in part, accounted for by the presence of more than one common disease-associated haplotype (allelic heterogeneity) which confounds the analysis of individual alleles by the TDT. Guidelines for strategies for the mapping of polygenes are suggested with the emphasis on collections of large numbers of families from multiple populations that should be as genetically homogeneous as possible.

Adolescent↗

PubMed1996

A polygenic model of inherited predisposition to cancer.

Polygenic inheritance of predisposition to cancer is demonstrated in experimental animals for different tumor types. Genetic susceptibility to hepatocarcinogenesis, lung tumorigenesis, skin and intestine carcinogenesis, and plasmacytomagenesis is determined by inheritance of multiple cancer predisposition and resistance alleles, whose chromosomal locations have been found by genetic linkage analysis. In some of these experimental models, genetic heterogeneity has also been reported. In humans, increased risk of lung cancer associated with multiple genes coding for drug metabolizing enzymes, increased risk of cancer in relatives of cancer patients, and genetic heterogeneity are compatible with polygenic inheritance of cancer predisposition. Polygenic inheritance based on the combination of multiple alleles that give predisposition and resistance to cancer would predict a very high risk of cancer in carrier individuals and a marginal increase in the relative risk of cancer in the progeny of the cancer patients. Therefore, predisposition to cancer may be genetically determined even in the absence of familial clustering of cases.

Animals↗

PubMed2026

Two Genomes, one Outcome: Stratifying Donor and Recipient Polygenic Risk Score to Improve Kidney Allograft Longevity.

Kidney transplantation outcomes arise from complex interactions among donor organ quality, recipient susceptibility, and immunologic compatibility, yet conventional clinical risk models explain only a modest fraction of outcome variability. Polygenic risk scores (PRS) offer a promising framework to enhance transplant risk assessment by integrating genome-wide genetic information from both donor and recipient into biologically informed models. This narrative review examines the mechanistic basis for PRS application in kidney transplantation and variant clustering approaches that link polygenic signals to specific biological pathways underlying alloimmunity, fibrosis, and metabolic dysfunction. We compare current PRS construction methodologies, highlighting their respective strengths and limitations in transplant cohorts. Transplant PRS are distinguished from single-genome disease models by their capacity to capture dual-genome interactions, simultaneously quantifying inherited donor organ liability and recipient genetic susceptibility within an integrated framework. This dual-genome architecture requires novel risk stratification paradigms in which combined donor-recipient polygenic profiles inform pretransplant decision-making in ways that neither genome alone can achieve. However, current PRS contribute only incremental variance beyond established clinical predictors, and critical limitations persist, including European ancestry bias, small cohort sizes, incomplete replication, and undefined clinical actionability thresholds. We critically evaluate these implementation barriers and outline future directions for integrating dual-genome PRS with clinical, molecular, and environmental data. The longer-term goal is to advance precision kidney transplantation through applications such as donor selection, immunosuppression tailoring, and individualized posttransplant surveillance. Realizing this potential will require validation in adequately powered, ancestry diverse, prospective transplant cohorts.

Journal Article↗

PubMed2025

Multi-Polygenic prediction of Frailty and its Trajectories highlights Chronic Pain, Rheumatoid Arthritis, and Educational Attainment pathways.

Frailty is a complex ageing-related trait with a growing evidence base for genetic influence. While a single polygenic score (PGS) for frailty has shown predictive value, few studies have examined the joint effect of multiple genetic risks. This study used a multi-polygenic score (MPS) approach to evaluate the combined and relative contributions of 26 PGSs to frailty, measured via the Frailty Index (FI), in two UK cohorts aged 65 and older: the English Longitudinal Study of Ageing (ELSA) and the Lothian Birth Cohort 1936 (LBC1936). Using elastic net regression with repeated cross-validation, we identified chronic pain and depressive symptoms PGSs as the strongest risk predictors of cross-sectional frailty status, while educational attainment, parental longevity, and rheumatoid arthritis PGSs were protective. Compared to single PGS models, MPS models provided improved prediction of frailty levels, explaining up to 4.7% of variance in frailty status - an improvement over the best single PGS (2.5%). To assess whether PGSs also predicted longitudinal frailty progression, we applied generalized additive mixed models (GAMMs) to model age-related trajectories. In ELSA, five PGSs (chronic pain, depressive symptoms, rheumatoid arthritis, educational attainment, and parental death) significantly interacted with age, influencing the rate of frailty change. In LBC1936, consistent though weaker effects were observed for chronic pain and education PGSs. These findings show that polygenic liability shapes both frailty levels and trajectories in later life. Our results support the use of multi-trait genomic models to improve risk prediction and understanding of frailty's complex aetiology.

Journal Article↗

PubMed1997

Evidence from Polygene Mapping for a Causal Relationship between Potato Tuber Dormancy and Abscisic Acid Content.

In previous studies polygene mapping of a backcross population derived from haploid potato (Solanum tuberosum) and a diploid wild species (Solanum berthaultii) showed at least eight quantitative trait loci (QTLs) associated with tuber dormancy. The same population was mapped for abscisic acid (ABA) content in tubers so that any QTLs identified could be compared with those detected previously. At least three distinct loci on three chromosomes (2, 4, and 7) were associated with variation in ABA content. One of the QTLs was detected only as a main (single locus) effect, and two QTLs were found through two-locus interaction analysis (epistasis). Interaction between QTLs at markers TG234 (chromosome 2) and TG155 (chromosome 4) explained 20% of total phenotypic variance for this trait. The interaction closely resembled one previously detected for dormancy, suggesting an association between high ABA content and long tuber dormancy. Although relationships between ABA level and dormancy could be demonstrated through polygene mapping, there was no indication of a relationship between these traits when they were subjected to a conventional correlation test. This illustrates the usefulness of polygene mapping as a tool to identify possible associations between hormone levels and plant development.

Journal Article↗

PubMed2001

Molecular analysis of apo(a) fragmentation in polygenic hypercholesterolemia: characterization of a new plasma fragment pattern.

Hypercholesterolemia is frequently associated with elevated Lp(a) levels, an independent risk factor for coronary, cerebrovascular, and peripheral vascular disease. A portion of apolipoprotein(a) [apo(a)] circulates as a series of fragments derived from the N-terminal region of apo(a). The relationship of elevated lipoprotein(a) [Lp(a)] levels to those of circulating apo(a) fragments in polygenic hypercholesterolemia is indeterminate. Therefore, plasma Lp(a) and plasma and urinary apo(a) fragment levels were measured by ELISA in 82 patients with polygenic type IIa hypercholesterolemia (low density lipoprotein cholesterol >/=4.13 mmol/L and triglycerides <2.24 mmol/L) and in 90 normolipidemic subjects. Lp(a) levels were significantly elevated in patients compared with control subjects (0.35+/-0.4 and 0.24+/-0.31 mg/mL, respectively; median 0.13 and 0.11 mg/mL, respectively; P=0.039), although apo(a) isoform distribution did not differ. Patients displayed significantly higher plasma and urinary apo(a) fragment levels than did control subjects (respective values were as follows: 4.97+/-5.51 and 2.15+/-2.57 [median 2.85 and 1.17] microg/mL in plasma, P<0.0001; 75+/-86 and 40+/-57 [median 38 and 17] ng/mg urinary creatinine in urine, P<0.0001). The ratio of plasma apo(a) fragments to Lp(a) levels was also significantly higher in patients than in control subjects (1.93+/-1.5% and 1.75+/-2.36%, respectively; P<0.0001). We conclude that increased plasma Lp(a) levels in polygenic hypercholesterolemia are associated with elevated circulating levels of apo(a) fragments but that this increase is not due to decreased renal clearance of apo(a) fragments. Furthermore, we identified a new pattern of apo(a) fragmentation characterized by the predominance of a fragment band whose size was related to that of the parent apo(a) isoform and that was superimposed on the series of fragments described previously by Mooser et al (J Clin Invest. 1996; 98:2414-2424). This new pattern was associated with small apo(a) isoforms and did not discriminate between hypercholesterolemic and normal subjects. However, this new apo(a) fragment pattern may constitute a novel marker for cardiovascular risk.

Adolescent↗

PubMed2026

Improving the reliability of polygenic risk score-based prediction for cardiovascular and renal complications across ancestries in type 2 diabetes using Mondrian Cross-Conformal Prediction.

Polygenic risk scores (PRS) developed in European populations often show reduced predictive performance in non-European populations, limiting their clinical utility. This lack of transferability across ancestries remains a major challenge in genomic medicine and raises concerns about health equity. We aimed to evaluate whether uncertainty-aware prediction, implemented through Mondrian Cross-Conformal Prediction, improves the performance and reliability of polygenic risk score-based predictions across ancestries for nephropathy, stroke, and myocardial infarction in individuals with type 2 diabetes in a multi-ethnic cohort. We leveraged Mondrian Cross-Conformal Prediction (MCCP), an uncertainty quantification framework, combined with logistic regression applied to a multi-polygenic risk score (multiPRS) to predict the risk of nephropathy, stroke, and myocardial infarction in individuals with type 2 diabetes. Two training frameworks were evaluated: one using 4,098 individuals with type 2 diabetes of European ancestry from the ADVANCE trial for training and 17,574 White British, 1,145 South Asian, and 749 African UK Biobank participants for testing; and another using the 17,574 White British UK Biobank participants for training and the South Asian and African participants for testing. Logistic regression provided robust baseline performance across populations. On top of this baseline, MCCP did not improve performance but added capabilities absent from probability-based stratification: for each individual, it issued a prediction together with an explicit confidence and credibility level; it allowed a tolerated error level to be set in advance and delivered prediction sets respecting it in the majority of settings; and it flagged individuals for whom no reliable prediction could be made. Applying MCCP to PRS-based prediction thus enables uncertainty-aware risk stratification and improves the reliability of risk prediction across ancestries, providing a more equitable framework for clinical use.

Female↗

PubMed2006

Use of routinely collected amniotic fluid for whole-genome expression analysis of polygenic disorders.

BACKGROUND: Neural tube defects related to polygenic disorders are the second most common birth defects in the world, but no molecular biologic tests are available to analyze the genes involved in the pathomechanism of these disorders. We explored the use of routinely collected amniotic fluid to characterize the differential gene expression profiles of polygenic disorders. METHODS: We used oligonucleotide microarrays to analyze amniotic fluid samples obtained from pregnant women carrying fetuses with neural tube defects diagnosed during ultrasound examination. The control samples were obtained from pregnant women who underwent routine genetic amniocentesis because of advanced maternal age (>35 years). We also investigated specific folate-related genes because maternal periconceptional folic acid supplementation has been found to have a protective effect with respect to neural tube defects. RESULTS: Fetal mRNA from amniocytes was successfully isolated, amplified, labeled, and hybridized to whole-genome transcript arrays. We detected differential gene expression profiles between cases and controls. Highlighted genes such as SLA, LST1, and BENE might be important in the development of neural tube defects. None of the specific folate-related genes were in the top 100 associated transcripts. CONCLUSIONS: This pilot study demonstrated that a routinely collected amount of amniotic fluid (as small as 6 mL) can provide sufficient RNA to successfully hybridize to expression arrays. Analysis of the differences in fetal gene expressions might help us decipher the complex genetic background of polygenic disorders.

Amniotic Fluid↗

PubMed2000

[Identification of mixed major genes and polygenes inheritance model of quantitative traits by using DH or RIL population].

The accuracy of the mixed inheritance analysis of quantitative traits with larger experimental error could be improved while using DH or RIL population. The segregation analysis method of identifying mixed major genes and polygenes inheritance model, including linkage inheritance model, of quantitative traits by using DH or RIL population was developed in this paper. The method may be applied to identify the mixed major gene and polygenes inheritance model of quantitative traits, estimate genetic effects and variances of major genes and polygenes, and the recombination value while there is linkage between two major genes. Finally, an example was used to illuminate the above procedure.

Genetic Linkage↗

PubMed2002

[Major-polygene effect analysis of super quality fiber properties in upland cotton (G. hirsutum L.)].

The modern textile industry depends on the improvement of fiber quality, especially strength to meet the needs of higher spinning speed. Inheritance of super quality fiber properties in Upland cotton was conducted in the present paper. P1, P2, F1, B1, B2 and F2 of eight crosses from five parents with different fiber strength, i.e. 7235 x TM1, TM1 x 7235, HS42 x TM1, PD69 x TM1, MD51 x TM1, 7235 x HS42, 7235 x PD69 and HS42 x PD69, and F2:3 for 7235 x TM1, were used in the study. The materials were planted in Nanjing or Hainan in 1998 and 1999, the individual plant fiber samples were tested with HVI system in Cotton Research Institute of CAAS at Anyang. The segregation analysis methods for major genes plus polygene mixed inheritance model developed by Gai were used to identify the genetic system of fiber qualities. The results from joint analyses of multiple segregating generations as well as single segregating generations, especially for F2:3, showed one major gene plus polygene mixed inheritance model in all fiber quality characters. The heritability values of major gene in F2 of 7235 x TM1 with great parent difference were estimated as 19.6% for fiber strength, 32.0% for micronaire and 13.9% for fiber length, but little in B1 and B2 for fiber qualities. The fiber length showed high and positive dominant effect, but negative value or zero of major or polygene dominant effects for other fiber qualities. Therefore, Mid-parent value or tendency to lower parent in F1 for most of fiber qualities lead to low selection efficiency, which suggests that molecular assisted selection should be considered at first in the improvement of fiber qualities.

Cotton Fiber↗

PubMed2003

[Stabilizing selection and computer models of the joint evolution of patterns of polygenes, transposable elements, and origin identity labels].

A computer model of the populations dynamics of the patterns of polygenes, transposable elements (TEs), and origin identity labels (OILs) in the course of stabilizing selection for an additive quantitative trait (with the target value being 0.4 of the maximum) was analyzed. It was demonstrated that the final plateaus of the trait value and the frequencies of the active values of polygenes are reached rapidly, namely, within five to seven generations (the effective selection period). The inbreeding coefficient during this period also grows rapidly and then gradually increases eventually reaching approximately 0.7. The inbreeding coefficient reaches plateau (at approximately 1.0) only in generations 300-350, which suggests the effect of gene drift. Dendrograms of the patterns of polygenes, TEs, and OILs were constructed for all generations. By generation 100 of selection, the final patterns of TEs and OILs were not formed completely. Fixations and losses, especially those of the OIL pattern, were delayed. In general, however, the population heterogeneity with respect to the patterns studied does not stabilize. This heterogeneity decreases the case of stabilizing selection, although more slowly than in the cases of positive and negative selections.

Animals↗

PubMed1981

Adipose cellularity, serum glucose, insulin and cholesterol in polygenic obese mice fed high-fat or high-carbohydrate diets.

Polygenic obese (M16) and nonobese (ICR) mice were fed ad libitum either a high-fat (FAT) or high-carbohydrate (CHO) diet from 6 to 10 weeks of age. After this four-week period, M16 exceeded (P less than 0.01) ICR mice and FAT-fed exceeded (P less than 0.01) CHO-fed mice in body energy percent, body fat percent, and weight and proportional weight of epididymal and subcutaneous fat pads. Fat cell size and number in both fat depots were greater (P less than 0.01) in the M16 than in the ICR line. Mice fed FAT had larger (P less than 0.01) fat cells in both depots compared with CHO-fed mice, but fat cell nuber was not altered significantly. M16 mice were hyperglycemic, hyperinsulinemic and hypercholesterolemic, Dietary treatment did not affect glucose or insulin levels, but cholesterol was greater (P less than 0.01) on FAT than on CHO diet. Lipoprotein lipase and fatty acid synthetase activities were greater in M16 than in ICR mice, while fatty acid synthetase activity was greater in mice fed CHO than in those fed FAT. Genotype by diet interactions were not important for the traits studied. Polygenic obese mice, developed by selection for increased growth rate, share many of the characteristics of the single gene obesity syndromes in rodents. The development of obesity in polygenic obese mice may be due, in part, to an acceleration of the normal developmental process of growth, in addition to hyperphagia and increased energetic efficiency.

Adipose Tissue↗

PubMed2026

Additive value of polygenic risk and family history for coronary heart disease risk stratification in two diverse US cohorts.

Whether polygenic risk, monogenic familial hypercholesterolemia (FH), and family history (FamHx) are additively informative for coronary heart disease (CHD) risk prediction across self-identified race/ethnicity (SIRE) groups has not been established. In two diverse cohorts-Electronic Medical Records and Genomics (eMERGE) phase IV (eIV; n = 19,348) and All of Us (AoU; n = 239,645)-we quantified the associations of a polygenic risk score (PRSCHD), pathogenic/likely pathogenic variants in genes associated with FH, and FamHx with CHD and evaluated their incremental value when added to the pooled cohort equations (PCEs). CHD was defined as myocardial infarction, unstable angina, or coronary revascularization. We modeled associations with multivariable logistic regression (prevalent CHD in eIV) and Cox proportional hazards (incident CHD in AoU) and characterized predictive performance with the c-statistic and reclassification and decision-curve net benefits across actionable 10-year risk thresholds. The effects of PRSCHD and FamHx were independent and additive in both cohorts and consistent across White, Black, and Latino SIRE groups. In eIV, adding PRSCHD and FamHx to the PCE increased the c-statistic for prevalent CHD from 0.719 to 0.753 (p-diff = 9.1 × 10-3) and reclassified 18.8% of participants at the 7.5% 10-year threshold, yielding approximately 4 additional true-positive CHD identifications per 1,000 screened. Net benefit gains were observed between the 7.5% and 10% thresholds across all three SIRE groups. In conclusion, PRSCHD and FamHx were independently and additively associated with CHD across major SIRE groups in two diverse cohorts in the United States (US), motivating the addition of these factors to clinical risk algorithms.

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↗

PubMed2026

Development and pilot testing of a prostate cancer polygenic risk report.

BACKGROUND: Polygenic risk scores (PRS) are increasingly being incorporated into clinical care, yet optimal strategies for communicating PRS results to patients and clinicians remain undefined. Effective report design is critical to ensure comprehension and appropriate use, particularly for complex conditions such as prostate cancer where screening decisions are nuanced. We developed and pilot tested patient-facing materials to communicate integrated polygenic and monogenic risk for prostate cancer in the context of a randomized clinical trial. METHODS: We designed a summary report and accompanying Frequently Asked Questions (FAQ) page to communicate prostate cancer genetic risk within the Prostate Cancer, Genetic Risk, and Equitable Screening Study (ProGRESS). Materials were developed through an iterative, multidisciplinary process informed by existing literature on genomic risk communication. We conducted semi-structured interviews with a national sample of eight men eligible for prostate cancer screening to evaluate comprehension, interpretation of visual elements, perceived usefulness, and preferences for improvement. Interviews were transcribed and analyzed using reflexive thematic analysis. RESULTS: Participants generally found the summary report and FAQ page understandable and visually engaging. Graphical displays of absolute risk, particularly pictograph arrays, facilitated comprehension and helped contextualize risk. Visual cues such as color and bold formatting effectively directed attention to key information, with red coloring perceived as particularly salient for high-risk results. In contrast, more complex visualizations, including bell curves and incidence curves, were frequently misunderstood or not interpreted as intended. Participants expressed a desire for clearer guidance regarding next steps and additional accessible information, suggesting supplementary resources such as hyperlinks or QR codes. Concerns about readability included small font size and high text density. CONCLUSIONS: In this qualitative pilot study, patient-facing materials for communicating prostate cancer PRS were generally well received, with specific design features such as simple visualizations and clear formatting enhancing understanding. Findings highlight the importance of intuitive risk displays and actionable guidance in PRS reporting. These results provide practical insights to inform the design of genomic risk reports as PRS-based prostate cancer screening approaches move toward clinical implementation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05926102; date of registry: July 3, 2023.

Aged↗

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↗