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PubMed2025

Polygenic Risk Scores for Preeclampsia Prediction Beyond Gold-Standard Clinical Models in Multiethnic Populations.

BACKGROUND: Preeclampsia is a major cause of maternal and fetal mortality and morbidity. Early risk stratification enables timely preventative therapy in high-risk women. Polygenic risk scores (PGS) improve prediction in complex diseases, but their added value for preeclampsia remains unclear, particularly in comparison to gold-standard first-trimester prediction models and across non-European ancestries. METHODS: We evaluated the performance of both a preeclampsia and systolic blood pressure PGS in 2 prospective pregnancy cohorts with detailed phenotyping: the Fetal Medicine Foundation study (n=5207; 2127 cases) and the Pregnancy Outcome Prediction study (n=3659; 228 cases). Risk models included (1) clinical factors; (2) clinical factors plus PGS; (3) advanced model including first-trimester mean arterial pressure, PAPP-A (pregnancy-associated plasma protein-A), and uterine artery pulsatility index; and (4) advanced model plus PGS. Discriminative performance, measured by the area under the receiver operating characteristic curve, was assessed overall and by ancestry. RESULTS: The preeclampsia PGS was independently associated with preeclampsia (odds ratio per SD, 1.24 [95% CI, 1.17-1.31]; P<0.001). It modestly improved prediction over clinical models (area under the receiver operating characteristic curve 0.746 versus 0.750; P=0.017) but not over the advanced model (area under the receiver operating characteristic curve 0.817 versus 0.818; P=0.326). The systolic blood pressure PGS showed stronger performance, improving prediction over both models in women of European ancestry. No improvement was observed with either score in women of African ancestry. CONCLUSIONS: PGSs for preeclampsia and SBP provide modest added predictive value beyond clinical risk factors in European ancestry women. Limited utility in African ancestry women reflects underrepresentation in the genome-wide association studies used to develop current scores. As cohort sizes grow and models are refined, PGSs may become important tools for equitable risk stratification in maternal health.

Adult↗
PubMed2026

Variance Polygenic Scores (vPGS) as a Tool for Studying Gene-Environment Interactions Associated With Refractive Error.

PURPOSE: Conventional polygenic scores predict an individual's phenotype based on their genetics. By contrast, variance polygenic scores (vPGS) quantify genetic predisposition to phenotypic variance. We tested the hypothesis that a vPGS for refractive error can identify individuals with increased susceptibility to environmental risk factors for myopia. METHODS: Six vPGS construction strategies were evaluated in UK Biobank participants: three variance heterogeneity genome-wide association study (vGWAS) methods and two reweighting schemes. vPGS performance was assessed using two metrics: (i) "Diff"-difference in phenotypic variance in vPGS decile ten versus one; (ii) Spearman correlation of phenotypic variance versus vPGS decile. The optimal vPGS was used to test for vPGS &#xd7; time spent reading or vPGS &#xd7; time spent outdoors interactions in children aged 15 years (ALSPAC cohort; n = 3471). RESULTS: Of the vGWAS methods, conditional quantile regression outperformed SCAMPI and Levene's Test. Of the re-weighting schemes, LDpred2 outperformed pruning and thresholding. In an independent sample of UK Biobank participants (n = 19,470), the top-performing vPGS successfully stratified individuals into groups with increasing variance in refractive error, even after adjusting for a conventional PGS (Diff: 2.55, 95% confidence interval [CI], 1.64-3.47; Spearman correlation = 0.87; 95% CI, 0.43-0.93). However, in ALSPAC participants, there was minimal support for vPGS interactions with time reading (P = 0.80) or time outdoors (P = 0.89). CONCLUSIONS: A novel vPGS successfully stratified individuals into groups with relatively high or low genetic susceptibility to refractive error variance. However, the vPGS could not identify individuals at enhanced risk from lifestyle risk factors for myopia.

Humans↗
PubMed2026

Agnostic polygenic prediction of weight loss after bariatric surgery.

A large interindividual variability in weight loss outcomes following bariatric surgery is reported. To ensure optimal management of patients, it is crucial to accurately identify candidates most likely to benefit the most from the intervention. Since genetic variants largely contribute to surgery response, polygenic scores (PGS) derived from genome-wide association studies (GWAS) could constitute valuable tools for clinical decision making. We developed and evaluated PGS to predict the weight loss response in 540 patients with a body mass index (BMI) of 35 kg/m2 or higher who underwent biliopancreatic diversion with duodenal switch. Summary statistics derived from BMI-derived GWAS, together with summary statistics from previously published GWAS of BMI and adiposity features, were used to construct, evaluate, and benchmark weight loss PGS. The full-adjusted BMI PGS model built in the entire cohort explained 39.6% of the mean-over-time excessive body weight loss (%EBWL), while the BMI-PGS built in the training dataset explained 38.9%. All benchmarked PGS based on BMI showed a significant relationship with mean-over-time %EBWL. These findings highlight the potential of BMI PGS in predicting weight loss after bariatric surgery and support their use as promising tools to improve the effectiveness of future antiobesity treatments.

Humans↗
PubMed2026

Multi-trait polygenic scores for COPD and COPD exacerbations implicate druggable proteins.

BACKGROUNDWe constructed multi-trait polygenic risk scores (PRSs) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validated their performance in diverse cohorts, and identified PRS-related proteins for potential therapeutic targeting.METHODSPRSmix+, a multi-trait PRS framework, is used to train a composite PRS (PRSmulti) in COPDGene non-Hispanic White participants (n = 6,647). Associations of PRSmulti with COPD status (GOLD 2-4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American (n = 2,466), ECLIPSE (n = 1,858), Mass General Brigham Biobank (n = 15,152), and All of Us (n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRSmulti and were validated with proteomic data in COPDGene (n = 5,173) and UK Biobank (n = 5,012).RESULTSPRSmix+ selected 7 traits for PRSmulti. In multivariable models, PRSmulti was associated with COPD status (meta-analysis random effects [RE] OR 1.58 [95% CI: 1.28-1.94]) and exacerbation frequency (meta-analysis RE &#x3b2; 0.21 [95% CI: 0.11-0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRSmulti outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRSs that were also validated with measured protein levels in COPDGene and UK Biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations.CONCLUSIONSMulti-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management.TRIAL REGISTRATIONCOPDGene: ClinicalTrials.gov NCT00608764; ECLIPSE: ClinicalTrials.gov NCT00292552.

Humans↗
PubMed2000

Differing relationships of methylene tetrahydrofolate reductase genotypes with cardiovascular risk in familial and polygenic hypercholesterolaemia.

BACKGROUND: Plasma homocysteine and the methylene tetrahydrofolate reductase C677T polymorphism have been suggested as being risk factors for cardiovascular disease. OBJECTIVE: To determine whether plasma homocysteine and the methylene tetrahydrofolate reductase C677T polymorphism are risk factors for coronary heart disease in patients with heterozygous familial hypercholesterolaemia as compared with those with polygenic hyperlipidaemia. METHODS: Plasma homocysteine and the methylene tetrahydrofolate reductase polymorphism were assessed with other risk factors in 112 patients with familial hypercholesterolaemia and 72 patients with polygenic hyperlipidaemia, of whom 29 (25.8%) and 30 (41%) respectively had established cardiovascular disease and in 100 healthy normal subjects. RESULTS: Plasma homocysteine was not significantly elevated in patients with and without coronary heart disease with familial hypercholesterolaemia or polygenic hyperlipidaemia compared with controls. The allele frequencies for C677T were significantly different in patients with coronary heart disease and with polygenic hyperlipidaemia (0.35 versus 0.29) (P = 0.02) as opposed to those with coronary heart disease and familial hypercholesterolaemia (0.25 versus 0.30) (P = 0.63). Methylene tetrahydrofolate reductase genotype but not homocysteine had a weak association with coronary heart disease in logistic regression analysis in patients with polygenic hyperlipidaemia (P = 0.05) but neither methylene tetrahydrofolate reductase genotype or plasma homocysteine was a risk factor in patients with familial hypercholesterolaemia. CONCLUSION: Whilst methylene tetrahydrofolate reductase genotype may be a weak risk factor for coronary heart disease in polygenic hyperlipidaemia as opposed to familial hypercholesterolaemia, homocysteine does not seem to be an important risk factor for coronary heart disease in patients in southern UK.

Adult↗
PubMed2003

Coinheritance of Factor V (FV) Leiden enhances thrombin formation and is associated with a mild bleeding phenotype in patients homozygous for the FVII 9726+5G>A (FVII Lazio) mutation.

We investigated the role of thrombophilic mutations as possible modifiers of the clinical phenotype in severe factor VII (FVII) deficiency. Among 7 patients homozygous for a cross-reacting material-negative (CRM-) FVII defect (9726+5G>A, FVII Lazio), the only asymptomatic individual carried FV Leiden. Differential modulation of FVII levels by intragenic polymorphisms was excluded by a FVII to factor X (FX) gene haplotype analysis. The coagulation efficiency in the FV Leiden carrier and a noncarrier was evaluated by measuring FXa, FVa, and thrombin generation after extrinsic activation of plasma in the absence and presence of activated protein C (APC). In both patients coagulation factor activation was much slower and resulted in significantly lower amounts of FXa and thrombin than in a normal control. However, more FXa and thrombin were formed in the plasma of the patient carrying FV Leiden than in the noncarrier, especially in the presence of APC. These results were confirmed in FV-FVII doubly deficient plasma reconstituted with purified normal FV or FV Leiden. The difference in thrombin generation between plasmas reconstituted with normal FV or FV Leiden gradually decreased at increasing FVII concentration. We conclude that coinheritance of FV Leiden increases thrombin formation and can improve the clinical phenotype in patients with severe FVII deficiency.

Adult↗
PubMedDate not supplied

Detection of quantitative trait loci for growth and fatness in pigs.

A quantitative trait locus (QTL) analysis of growth and fatness data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six boars and 23 F1 sows, the progeny of six LW boars and six MS sows, produced 530 F2 males and 573 F2 females. Nine growth traits, i.e. body weight at birth and at 3, 10, 13, 17 and 22 weeks of age, average daily gain from birth to 3 weeks, from 3 to 10 weeks and from 10 to 22 weeks of age, as well as backfat thickness at 13, 17 and 22 weeks of age and at 40 and 60 kg live weight were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half-/full-sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed highly significant gene effects for growth on chromosomes 1, 4 and 7 and for backfat thickness on chromosomes 1, 4, 5, 7 and X, and significant gene effects on chromosome 6 for growth and backfat thickness. Suggestive QTLs were also revealed by both methods on chromosomes 2 and 3 for growth and 2 for backfat thickness. Significant gene effects were detected for growth on chromosomes 11, 13, 14, 16 and 18 and for backfat thickness on chromosome 8, 10, 13 and 14. LW alleles were associated with high growth rate and low backfat thickness, except for those of chromosome 7 and to a lesser extent early-growth alleles on chromosomes 1 and 2 and backfat thickness alleles on chromosome 6.

Adipose Tissue↗
PubMedDate not supplied

Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs.

A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG), feed conversion ratio (FCR), carcass lean content and meat quality index were combined to analyse data from 1449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to describe its residual variance. The same fixed (batch) and random (additive genetic, pen and individual permanent environmental) effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550000 rounds each, from which 50000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult.

Analysis of Variance↗
PubMedDate not supplied

Optimal selection on two quantitative trait loci with linkage.

A mathematical approach to optimize selection on multiple quantitative trait loci (QTL) and an estimate of residual polygenic effects was applied to selection on two linked or unlinked additive QTL. Strategies to maximize total or cumulative discounted response over ten generations were compared to standard QTL selection on the sum of breeding values for the QTL and an estimated breeding value for polygenes, and to phenotypic selection. Optimal selection resulted in greater response to selection than standard QTL or phenotypic selection. Tight linkage between the QTL (recombination rate 0.05) resulted in a slightly lower response for standard QTL and phenotypic selection but in a greater response for optimal selection. Optimal selection capitalized on linkage by emphasizing selection on favorable haplotypes. When the objective was to maximize total response after ten generations and QTL were unlinked, optimal selection increased QTL frequencies to fixation in a near linear manner. When starting frequencies were equal for the two QTL, equal emphasis was given to each QTL, regardless of the difference in effects of the QTL and regardless of the linkage, but the emphasis given to each of the two QTL was not additive. These results demonstrate the ability of optimal selection to capitalize on information on the complex genetic basis of quantitative traits that is forthcoming.

Animals↗
PubMedDate not supplied

A further look at quantitative trait loci affecting growth and fatness in a cross between Meishan and Large White pig populations.

A detailed quantitative trait locus (QTL) analysis of growth and fatness data from a three generation experimental cross between Large White (LW) and Meishan (MS) pig breeds was carried out to search for sex x QTL interactions, imprinting effects and multiple linked QTLs. A total of 530 F(2) males and 573 F(2) females issued from 6 F(1) boars and 23 F(1) sows were typed for a total of 137 markers covering the entire porcine genome. Nine growth traits and three backfat thickness measurements were analysed. All analyses were performed using line cross regression procedures. A QTL with sex-specific expression was revealed in the proximal region of chromosome 8, although some confusion between herd and sex effects could not be discarded. This previously undetected QTL affected male growth during the fattening period, with a favourable additive effect of the LW allele. The analyses also revealed the presence of two linked QTLs segregating on chromosome 1, affecting growth traits during the post-weaning period. The first QTL, previously detected using a single QTL model, was located at the end of the q arm of chromosome 1 and had a favourable MS allele. The second QTL had a favourable LW allele and was located in the proximal extremity of the q arm of chromosome 1. Suggestive genomic imprinting was found in the distal region of chromosome 9 affecting growth during the fattening period.

Adipose Tissue↗
PubMed2006

The efficiency of mapping of quantitative trait loci using cofactor analysis in half-sib design.

This simulation study was designed to study the power and type I error rate in QTL mapping using cofactor analysis in half-sib designs. A number of scenarios were simulated with different power to identify QTL by varying family size, heritability, QTL effect and map density, and three threshold levels for cofactor were considered. Generally cofactor analysis did not increase the power of QTL mapping in a half-sib design, but increased the type I error rate. The exception was with small family size where the number of correctly identified QTL increased by 13% when heritability was high and 21% when heritability was low. However, in the same scenarios the number of false positives increased by 49% and 45% respectively. With a liberal threshold level of 10% for cofactor combined with a low heritability, the number of correctly identified QTL increased by 14% but there was a 41% increase in the number of false positives. Also, the power of QTL mapping did not increase with cofactor analysis in scenarios with unequal QTL effect, sparse marker density and large QTL effect (25% of the genetic variance), but the type I error rate tended to increase. A priori, cofactor analysis was expected to have higher power than individual chromosome analysis especially in experiments with lower power to detect QTL. Our study shows that cofactor analysis increased the number of false positives in all scenarios with low heritability and the increase was up to 50% in low power experiments and with lower thresholds for cofactors.

Chromosome Mapping↗
PubMed2003

Multiple genome-wide analyses of smoking behavior in the Framingham Heart Study.

BACKGROUND: Cigarette smoking behavior may have a genetic basis. We assessed evidence for quantitative trait loci (QTLs) affecting the maximum number of cigarettes smoked per day, a trait meant to quantify this behavior, using data collected over 40 years as part of the Framingham Heart Study's original and offspring cohorts. RESULTS: Heritability was estimated to be approximately 21% using variance components (VC) methods (SOLAR), while oligogenic linkage and segregation analysis based on Bayesian Markov chain Monte Carlo (MCMC) methods (LOKI) estimated a mean of two large QTLs contributing approximately 28% and 20%, respectively, to the trait's variance. Genome-wide parametric (FASTLINK) and VC linkage analyses (SOLAR) revealed several LOD scores greater than 1.0, with peak LOD scores using both methods on chromosomes 2, 17, and 20; multi-point MCMC methods followed up on these chromosomes. The most robust linkage results were for a QTL between 65 and 84 cM on chromosome 20 with signals from multiple sex- and age-adjusted analyses including two-point LOD scores of 1.30 (parametric) and 1.07 (heritability = 0.17, VC) at 70.51 cM, a multi-point LOD score of 1.50 (heritability = 0.20, VC) at 84 cM, and an intensity ratio of 12.0 (MCMC) at 65 cM. CONCLUSION: Familial aggregation of the maximum number of cigarettes smoked per day was consistent with a genetic component to this behavior, and oligogenic segregation analyses using MCMC suggested two important QTLs. Linkage signals on chromosome 20 between 65 and 84 cM were seen using multiple analytical methods. No linkage result, however, met genome-wide statistical significance criteria, and the true relationship between these regions and smoking behavior remains unclear.

Adolescent↗
PubMed2003

Empirically derived phenotypic subgroups - qualitative and quantitative trait analyses.

BACKGROUND: The Framingham Heart Study has contributed a great deal to advances in medicine. Most of the phenotypes investigated have been univariate traits (quantitative or qualitative). The aims of this study are to derive multivariate traits by identifying homogeneous groups of people and assigning both qualitative and quantitative trait scores; to assess the heritability of the derived traits; and to conduct both qualitative and quantitative linkage analysis on one of the heritable traits. METHODS: Multiple correspondence analysis, a nonparametric analogue of principal components analysis, was used for data reduction. Two-stage clustering, using both k-means and agglomerative hierarchical clustering, was used to cluster individuals based upon axes (factor) scores obtained from the data reduction. Probability of cluster membership was calculated using binary logistic regression. Heritability was calculated using SOLAR, which was also used for the quantitative trait analysis. GENEHUNTER-PLUS was used for the qualitative trait analysis. RESULTS: We found four phenotypically distinct groups. Membership in the smallest group was heritable (38%, p < 1 x 10(-6)) and had characteristics consistent with atherogenic dyslipidemia. We found both qualitative and quantitative LOD scores above 3 on chromosomes 11 and 14 (11q13, 14q23, 14q31). There were two Kong & Cox LOD scores above 1.0 on chromosome 6 (6p21) and chromosome 11 (11q23). CONCLUSION: This approach may be useful for the identification of genetic heterogeneity in complex phenotypes by clarifying the phenotype definition prior to linkage analysis. Some of our findings are in regions linked to elements of atherogenic dyslipidemia and related diagnoses, some may be novel, or may be false positives.

Adult Children↗
PubMed2003

Longitudinal variance-components analysis of the Framingham Heart Study data.

The Framingham Heart Study offspring cohort, a complex data set with irregularly spaced longitudinal phenotype data, was made available as part of Genetic Analysis Workshop 13. To allow an analysis of all of the data simultaneously, a mixed-model- based random-regression (RR) approach was used. The RR accounted for the variation in genetic effects (including marker-specific quantitative trait locus (QTL) effects) across time by fitting polynomials of age. The use of a mixed model allowed both fixed (such as sex) and random (such as familial environment) effects to be accounted for appropriately. Using this method we performed a QTL analysis of all of the available adult phenotype data (26,106 phenotypic records). In addition to RR, conventional univariate variance component techniques were applied. The traits of interest were BMI, HDLC, total cholesterol, and height. The longitudinal method allowed the characterization of the change in QTL effects with aging. A QTL affecting BMI was shown to act mainly at early ages.

Adult↗
PubMed2003

Longitudinal variance components models for systolic blood pressure, fitted using Gibbs sampling.

This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects on the baseline blood pressure and on the rate of change (slope) of blood pressure with time. Generalized linear mixed models were fitted using Gibbs sampling in WinBUGS, and the additive polygenic random effects estimated using these models were then used as continuous phenotypes in a variance components linkage analysis. The first-stage analysis provided evidence for general genetic effects on both the baseline and slope of blood pressure, and the linkage analysis found evidence of several genes, again for both baseline and slope.

Adult Children↗
PubMed2003

Consistency of linkage results across exams and methods in the Framingham Heart Study.

BACKGROUND: The repeated measures in the Framingham Heart Study in the Genetic Analysis Workshop 13 data set allow us to test for consistency of linkage results within a study across time. We compared regression-based linkage to variance components linkage across time for six quantitative traits in the real data. RESULTS: The variance components approach found 11 significant linkages, the regression-based approach found 4. There was only one region that overlapped. Consistency between exams generally decreased as the time interval between exams increased. The regression-based approach showed higher consistency in linkage results across exams. CONCLUSION: The low consistency between exams and between methods may help explain the lack of replication between studies in this field.

Adult Children↗
PubMed2003

Age-stratified QTL genome scan analyses for anthropometric measures.

With the availability of longitudinal data, age-specific (stratified) or age-adjusted genetic analyses have the potential to localize different putative trait influencing loci. If age does not influence the locus-specific penetrance function within the range examined, age-stratified analyses will tend to yield comparable results for an individual trait. However, age-stratified results should vary across age strata when the locus-specific penetrance function is age dependent. In this paper, age-stratified and age-adjusted quantitative trait loci (QTL) linkage analyses were contrasted for height, weight, body mass index (BMI), and systolic blood pressure on a subset of the Framingham Heart Study. The strata comprised individuals with data present in each of three age groups: 31-49, 50-60, 61-79. Genome-wide QTL analyses were performed using SOLAR. Over all ages, a linkage signal for height was detected on chromosome 14q11.2 near marker GATA74E02A (LOD for ages 31-49 = 2.38, LOD for ages 50-60 = 1.84, LOD for ages 61-79 = 2.45). Evidence of linkage to BMI in the 31-49 age group was found on chromosome 3q22 (GATA3C02, LOD = 2.89, p = 0.0003) at the same location as the signal for weight (LOD = 3.10, p = 0.0002). Linkage was also supported on chromosome 1p22.1 for BMI (LOD = 2.21, p = 0.0014) and weight (LOD = 2.47, p = 0.0007) in the 31-49 age group. Our age-stratified results suggest that QTL that are expressed over long periods of time and affecting multiple, correlated traits may be identified using genome scan and variance-component methodology to help detect early and/or late gene expression.

Adult↗