Estimating disease prevalence in large datasets using genetic risk scores
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ABSTRACT:
SUBMITTER: Evans B
PROVIDER: S-EPMC8575951 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Rare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesize that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS). We propose a method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance. The RVGRS identifies 1.5% of the population with substantial risk of early CAD and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and a common variant genetic risk score.
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Project description:The genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.
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Project description:This study is the first genetically-informed investigation of avoidant/restrictive food intake disorder (ARFID), an eating disorder that profoundly impacts quality of life for those affected. ARFID is highly comorbid with autism, and we provide the first estimate of its prevalence in a large and phenotypically diverse autism cohort (a subsample of the SPARK study, N = 5,157 probands). This estimate, 21% (at a balanced accuracy 80%), is at the upper end of previous estimates from studies based on clinical samples, suggesting under-diagnosis and potentially lack of awareness among caretakers and clinicians. Although some studies suggest a decrease of disordered eating symptoms by age 6, our estimates indicate that up to 17% (at a balanced accuracy 87%) of parents of autistic children are also at heightened risk for ARFID, suggesting a lifelong risk for disordered eating. We were also able to provide the first estimates of narrow-sense heritability (h2) for ARFID risk, at 0.45. Genome-wide association revealed a single hit near ZSWIM6, a gene previously implicated in neurodevelopmental conditions. While, the current sample was not well-powered for GWAS, effect size and heritability estimates allowed us to project the sample sizes necessary to more robustly discover ARFID-linked loci via common variants. Further genetic analysis using polygenic risk scores (PRS) affirmed genetic links to autism as well as neuroticism and metabolic syndrome.
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Project description:Brief alcohol counseling interventions can reduce alcohol consumption and related morbidity among non-dependent risky drinkers, but more intensive alcohol treatment is recommended for persons with alcohol dependence. This study evaluated whether scores on common alcohol screening tests could identify patients likely to have current alcohol dependence so that more appropriate follow-up assessment and/or intervention could be offered. This cross-sectional study used secondary data from 392 male and 927 female adult family medicine outpatients (1993-1994). Likelihood ratios were used to empirically identify and evaluate ranges of scores of the AUDIT, the AUDIT-C, two single-item questions about frequency of binge drinking, and the CAGE questionnaire for detecting DSM-IV past-year alcohol dependence. Based on the prevalence of past-year alcohol dependence in this sample (men: 12.2%; women: 5.8%), zones of the AUDIT and AUDIT-C identified wide variability in the post-screening risk of alcohol dependence in men and women, even among those who screened positive for alcohol misuse. Among men, AUDIT zones 5-10, 11-14 and 15-40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 18 to 87%, and AUDIT-C zones 5-6, 7-9 and 10-12 were associated with probabilities ranging from 22 to 75%. Among women, AUDIT zones 3-4, 5-8, 9-12 and 13-40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 6 to 94%, and AUDIT-C zones 3, 4-6, 7-9 and 10-12 were associated with probabilities ranging from 9 to 88%. AUDIT or AUDIT-C scores could be used to estimate the probability of past-year alcohol dependence among patients who screen positive for alcohol misuse and inform clinical decision-making.
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Project description:Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearman's ??=?0.32, p?<?10-16); and (3) the disease onset age and heritability are negatively correlated (??=?-0.46, p?<?10-16).
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Project description:Genome-wide variation data with millions of genetic markers have become commonplace. However, the potential for interpretation and application of these data for clinical assessment of outcomes of interest, and prediction of disease risk, is currently not fully realized. Many common complex diseases now have numerous, well-established risk loci and likely harbor many genetic determinants with effects too small to be detected at genome-wide levels of statistical significance. A simple and intuitive approach for converting genetic data to a predictive measure of disease susceptibility is to aggregate the effects of these loci into a single measure, the genetic risk score. Here, we describe some common methods and software packages for calculating genetic risk scores and polygenic risk scores, with focus on studies of common complex diseases. We review the basic information needed, as well as important considerations for constructing genetic risk scores, including specific requirements for phenotypic and genetic data, and limitations in their application. © 2019 by John Wiley & Sons, Inc.
| S-EPMC6941594 | biostudies-literature
Project description:Background and aimsInflammatory bowel disease [IBD] phenotypes are very heterogeneous between patients, and current clinical and molecular classifications do not accurately predict the course that IBD will take over time. Genetic determinants of disease phenotypes remain largely unknown but could aid drug development and allow for personalised management. We used genetic risk scores [GRS] to disentangle the genetic contributions to IBD phenotypes.MethodsClinical characteristics and imputed genome-wide genetic array data of patients with IBD were obtained from two independent cohorts [cohort A, n = 1097; cohort B, n = 2156]. Genetic risk scoring [GRS] was used to assess genetic aetiology shared across traits and IBD phenotypes. Significant GRS-phenotype (false-discovery rate [FDR] corrected p <0.05) associations identified in cohort A were put forward for replication in cohort B.ResultsCrohn's disease [CD] GRS were associated with fibrostenotic CD [R2 = 7.4%, FDR = 0.02] and ileocaecal resection [R2 = 4.1%, FDR = 1.6E-03], and this remained significant after correcting for previously identified clinical and genetic risk factors. Ulcerative colitis [UC] GRS [R2 = 7.1%, FDR = 0.02] and primary sclerosing cholangitis [PSC] GRS [R2 = 3.6%, FDR = 0.03] were associated with colonic CD, and these two associations were largely driven by genetic variation in MHC. We also observed pleiotropy between PSC genetic risk and smoking behaviour [R2 = 1.7%, FDR = 0.04].ConclusionsPatients with a higher genetic burden of CD are more likely to develop fibrostenotic disease and undergo ileocaecal resection, whereas colonic CD shares genetic aetiology with PSC and UC that is largely driven by variation in MHC. These results further our understanding of specific IBD phenotypes.
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Project description:BackgroundFor most disease-related traits the magnitude of the contribution of genetic factors in adolescents remains unclear.MethodsTwenty continuous traits related to anthropometry, cardiovascular and renal function, metabolism, and inflammation were selected from the ongoing prospective Tracking Adolescents' Individual Lives Survey cohort in the Netherlands with measurements of up to 5 waves from age 11 to 22 years (n=1354, 47.6% males) and all traits available at the third wave (mean age [SD]=16.22 [0.66]). For each trait, unweighted and weighted genetic risk scores (GRSs) were generated based on significantly associated single nucleotide polymorphisms identified from literature. The variance explained by the GRSs in adolescents were estimated by linear regression after adjustment for covariates.ResultsExcept for ALT (alanine transaminase), all GRSs were significantly associated with their traits. The trait variance explained by the GRSs was highest for lipoprotein[a] (39.59%) and varied between 0.09% (ALT) and 18.49% (LDL [low-density lipoprotein]) for the other traits. For most traits, the variances explained in adolescents were comparable with or slightly smaller than those in adults. Significant increases of trait levels (except ALT) and increased risks for overweight/obesity (odds ratio, 6.41 [95% CI, 2.95-15.56]) and hypertension (odds ratio, 2.86 [95% CI, 1.39-6.17]) were found in individuals in the top GRS decile compared with those at the bottom decile.ConclusionsVariances explained by adult-based GRSs for disease-related traits in adolescents, although still relatively modest, were comparable with or slightly smaller than in adults offering promise for improved risk prediction at early ages.
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Project description:We introduce a method of estimating disease prevalence from case-control family study data. Case-control family studies are performed to investigate the familial aggregation of disease; families are sampled via either a case or a control proband, and the resulting data contain information on disease status and covariates for the probands and their relatives. Here, we introduce estimators for overall prevalence and for covariate-stratum-specific (e.g., sex-specific) prevalence. These estimators combine the proportion of affected relatives of control probands with the proportion of affected relatives of case probands and are designed to yield approximately unbiased estimates of their population counterparts under certain commonly made assumptions. We also introduce corresponding confidence intervals designed to have good coverage properties even for small prevalences. Next, we describe simulation experiments where our estimators and intervals were applied to case-control family data sampled from fictional populations with various levels of familial aggregation. At all aggregation levels, the resulting estimates varied closely and symmetrically around their population counterparts, and the resulting intervals had good coverage properties, even for small sample sizes. Finally, we discuss the assumptions required for our estimators to be approximately unbiased, highlighting situations where an alternative estimator based only on relatives of control probands may perform better.
| S-EPMC2933418 | biostudies-literature
Project description:BackgroundSurveys measuring effectiveness of public awareness campaigns in reducing cardiovascular disease (CVD) incidence have yielded equivocal findings. The aim of this study was to describe cardiovascular risk factors (CVRFs) changes over the years in an untreated population-based study.MethodsBetween 2007 and 2012, we conducted a screening campaign for CVRFs in men aged 40 to 65 yrs and women aged 50 to 70 yrs in the western suburbs of Paris. Data were complete for 20,324 participants of which 14,709 were untreated.ResultsThe prevalence trend over six years was statistically significant for hypertension in men from 25.9% in 2007 to 21.1% in 2012 (p=0.002) and from 23% in 2007 to 12.7% in 2012 in women (p<0.0001). The prevalence trend of tobacco smoking decreased from 38.6% to 27.7% in men (p=0.0001) and from 22.6% to 16.8% in women (p=0.113). The Framingham 10-year risk for CVD decreased from 13.3 ± 8.2 % in 2007 to 11.7 ± 9.0 % in 2012 in men and from 8.0 ± 4.1 % to 5.9 ± 3.4 % in women. The 10-year risk of fatal CVD based on the European Systematic COronary Risk Evaluation (SCORE) decreased in men and in women (p <0.0001).ConclusionsOver a 6-year period, several CVRFs have decreased in our screening campaign, leading to decrease in the 10-year risk for CVD and the 10-year risk of fatal CVD. Cardiologists should recognize the importance of community prevention programs and communication policies, particularly tobacco control and healthier diets to decrease the CVRFs in the general population.
| S-EPMC4408033 | biostudies-literature