ABSTRACT
BACKGROUND: Coronary atherosclerotic burden and adverse coronary heart disease events are related phenotypes with likely shared genetic cause. METHODS: We analyzed 6021 patients with available coronary angiography, genotyping, and exome sequencing data. We tested for associations of polygenic risk scores for coronary heart disease (PRSCHD) with multiple measures of coronary artery disease (CAD) severity. We assessed the interplay between PRSCHD and pathogenic/likely pathogenic variants in 3 familial hypercholesterolemia genes. We performed mediation analyses to explore whether CAD severity mediated the association of PRSCHD with prevalent coronary heart disease and incident myocardial infarction. RESULTS: A 1-SD increase in PRSCHD was associated with multiple measures of CAD severity, including the log Gensini score (ß, 0.31 [95% CI, 0.28-0.33]). Carrying a pathogenic/likely pathogenic familial hypercholesterolemia variant was associated with a higher log Gensini score after adjustment for PRSCHD (ß, 0.21 [95% CI, 0.03-0.38]). PRSCHD was associated with incident myocardial infarction over a mean follow-up of 9.2 years (hazard ratio, 1.20 [95% CI, 1.13-1.27]; P=5×10-10), and the Gensini score mediated 90% of this association. CONCLUSIONS: PRSCHD was associated with multiple measures of CAD severity. The association of PRSCHD with incident myocardial infarction was almost fully mediated by CAD severity, indicating a considerable genetic overlap between the 2 phenotypes.
ABSTRACT
BACKGROUND AND OBJECTIVE: Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. METHODS: We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. RESULTS: We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet. CONCLUSION: Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.
Subject(s)
Heart Failure , Metabolomics , Heart Failure/metabolism , Humans , Metabolomics/methods , Male , Female , Prospective Studies , Middle Aged , Metabolome , Aged , Metabolic Networks and PathwaysABSTRACT
In this report, we provide a follow-up analysis of a previously published genome-wide association study of host genetic variants associated with inter-individual variations in cellular immune responses to mumps vaccine. Here we report the results of a polygenic score (PGS) analysis showing how common variants can predict mumps vaccine response. We found higher PGS for IFNγ, IL-2, and TNFα were predictive of higher post-vaccine IFNγ (p-value = 2e-6), IL-2 (p = 2e-7), and TNFα (p = 0.004) levels, respectively. Control of immune responses after vaccination is complex and polygenic in nature. Our results suggest that the PGS-based approach enables better capture of the combined genetic effects that contribute to mumps vaccine-induced immunity, potentially offering a more comprehensive understanding than traditional single-variant GWAS. This approach will likely have broad utility in studying genetic control of immune responses to other vaccines and to infectious diseases.
ABSTRACT
BACKGROUND: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRSCHD) for 5 genetic ancestry groups. METHODS: We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSPT) and ancestry-based continuous shrinkage priors (PRSCSx) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRSCHD in 176,988 individuals across 9 diverse cohorts. RESULTS: Multi-ancestry PRSPT and PRSCSx outperformed ancestry-specific PRSPT and PRSCSx across a range of tuning values. Two best-performing multi-ancestry PRSCHD (ie, PRSPTmult and PRSCSxmult) and 1 ancestry-specific (PRSCSxEUR) were taken forward for validation. PRSPTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41-3.14], 1.65 [1.59-1.72]), followed by East Asian ancestry (1.56 [1.50-1.61]), Hispanic/Latino ancestry (1.38 [1.24-1.54]), and African ancestry (1.16 [1.11-1.21]). PRSCSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38-3.00]) and European ancestry (1.65 [1.59-1.71]), lower in East Asian ancestry (1.59 [1.54-1.64]), Hispanic/Latino ancestry (1.51 [1.35-1.69]), and the lowest in African ancestry (1.20 [1.15-1.26]). CONCLUSIONS: The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRSCHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRSCHD.
Subject(s)
Coronary Disease , Genome-Wide Association Study , Multifactorial Inheritance , Humans , Coronary Disease/genetics , Male , Female , Genetic Predisposition to Disease , Polymorphism, Single Nucleotide , Risk Factors , Middle Aged , Genetic Risk ScoreABSTRACT
Background: The joint effects of polygenic risk and social determinants of health (SDOH) on coronary heart disease (CHD) in the United States are unknown. Methods: In 67,256 All of Us (AoU) participants with available SDOH data, we ascertained self-reported race/ethnicity and calculated a polygenic risk score for CHD (PRS CHD ). We used 90 SDOH survey questions to develop an SDOH score for CHD (SDOH CHD ). We assessed the distribution of SDOH CHD across self-reported races and US states. We tested the joint association of SDOH CHD and PRS CHD with CHD in regression models that included clinical risk factors. Results: SDOH CHD was highest in self-reported black and Hispanic people. Self-reporting as black was associated with higher odds of CHD but not after adjustment for SDOH CHD . Median SDOH CHD values varied by US state and were associated with heart disease mortality. A 1-SD increase in SDOH CHD was associated with CHD (OR=1.36; 95% CI, 1.29 to 1.46) and incident CHD (HR=1.73; 95% CI, 1.27 to 2.35) in models that included PRS CHD and clinical risk factors. Among people in the top 20% of PRS CHD , CHD prevalence was 4.8% and 7.8% in the bottom and top 20% of SDOH CHD , respectively. Conclusions: Increased odds of CHD in self-reported black people are likely due to higher SDOH burden. SDOH and PRS were independently associated with CHD in the US. Our findings emphasize the need to consider both PRS and SDOH for equitable disease risk assessment.
ABSTRACT
Polygenic scores (PGS) for coronary heart disease (CHD) are constructed using GWAS summary statistics for CHD. However, pleiotropy is pervasive in biology and disease-associated variants often share etiologic pathways with multiple traits. Therefore, incorporating GWAS summary statistics of additional traits could improve the performance of PGS for CHD. Using lasso regression models, we developed two multi-PGS for CHD: 1) multiPGSCHD, utilizing GWAS summary statistics for CHD, its risk factors, and other ASCVD as training data and the UK Biobank for tuning, and 2) extendedPGSCHD, using existing PGS for a broader range of traits in the PGS Catalog as training data and the Atherosclerosis Risk in Communities Study (ARIC) cohort for tuning. We evaluated the performance of multiPGSCHD and extendedPGSCHD in the Mayo Clinic Biobank, an independent cohort of 43,578 adults of European ancestry which included 4,479 CHD cases and 39,099 controls. In the Mayo Clinic Biobank, a 1 SD increase in multiPGSCHD and extendedPGSCHD was associated with a 1.66-fold (95% CI: 1.60-1.71) and 1.70-fold (95% CI: 1.64-1.76) increased odds of CHD, respectively, in models that included age, sex, and 10 PCs, whereas an already published PGS for CHD (CHD_PRSCS) increased the odds by 1.50 (95% CI: 1.45-1.56). In the highest deciles of extendedPGSCHD, multiPGSCHD, and CHD_PRSCS, 18.4%, 17.5%, and 16.3% of patients had CHD, respectively.
Subject(s)
Coronary Disease , Adult , Humans , Coronary Disease/genetics , Risk Factors , PhenotypeABSTRACT
Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.
Subject(s)
Genetic Predisposition to Disease , Humans , Risk Factors , Multifactorial Inheritance , Precision Medicine , Genome-Wide Association StudyABSTRACT
Refinement of breast cancer risk estimates with a polygenic-risk score (PRS) may improve uptake of risk-reducing endocrine therapy (ET). A previous clinical trial assessed the influence of adding a PRS to traditional risk estimates on ET use. We stratified participants according to PRS-refined breast cancer risk and evaluated ET use and ET-related quality of life (QOL) at 1-year (previously reported) and 2-year follow-ups. Of 151 participants, 58 (38.4%) initiated ET, and 22 (14.6%) discontinued ET by 2 years; 42 (27.8%) and 36 (23.8%) participants were using ET at 1- and 2-year follow-ups, respectively. At the 2-year follow-up, 39% of participants with a lifetime breast cancer risk of 40.1% to 100.0%, 18% with a 20.1% to 40.0% risk, and 16% with a 0.0% to 20.0% risk were taking ET (overall P = 0.01). Moreover, 40% of participants whose breast cancer risk increased by 10% or greater with addition of the PRS to a traditional breast cancer-risk model were taking ET versus 0% whose risk decreased by 10% or greater (P = 0.004). QOL was similar for participants taking or not taking ET at 1- and 2-year follow-ups, although most who discontinued ET did so because of adverse effects. However, these QOL results may have been skewed by the long interval between QOL surveys and lack of baseline QOL data. PRS-informed breast cancer prevention counseling has a lasting, but waning, effect over time. Additional follow-up studies are needed to address the effect of PRS on ET adherence, ET-related QOL, supplemental breast cancer screening, and other risk-reducing behaviors. PREVENTION RELEVANCE: Risk-reducing medications for breast cancer are considerably underused. Informing women at risk with precise and individualized risk assessment tools may substantially affect the incidence of breast cancer. In our study, a risk assessment tool (IBIS-polygenic-risk score) yielded promising results, with 39% of women at highest risk starting preventive medication.
Subject(s)
Breast Neoplasms , Female , Humans , Breast Neoplasms/epidemiology , Breast Neoplasms/genetics , Breast Neoplasms/prevention & control , Quality of Life , Follow-Up Studies , Risk Assessment , Genetic Risk Score , Risk Factors , Genetic Predisposition to DiseaseABSTRACT
BACKGROUND: We have previously described genetic polymorphisms in candidate genes that are associated with inter-individual variations in antibody responses to mumps vaccination. To expand upon our previous work, we performed a genome-wide association study (GWAS) to discover host genetic variants associated with mumps vaccine-induced cellular immune responses. METHODS: We performed a GWAS of mumps-specific immune response outcomes (11 secreted cytokines/chemokines) in a cohort of 1,406 subjects. RESULTS: Among the 11 cytokine/chemokines we studied, four (IFN-γ, IL-2, IL-1ß, and TNFα) demonstrated GWAS signals reaching genome-wide significance (p < 5 × 10-8). A genomic region (encoding Sialic acid-binding immunoglobulin-type lectins/SIGLEC) located on chromosome 19q13 (p < 5 × 10-8) was associated with both IL-1ß and TNFα responses. The SIGLEC5/SIGLEC14 region contained 11 statistically significant single nucleotide polymorphisms (SNPs), including the intronic SIGLEC5 rs872629 (p = 1.3E-11) and rs1106476 (p = 1.32E-11) whose alternate alleles were significantly associated with decreased levels of mumps-specific IL-1ß (rs872629, p = 1.77E-09; rs1106476, p = 1.78E-09) and TNFα (rs872629, p = 1.3E-11; rs1106476, p = 1.32E-11) production. CONCLUSIONS: Our results suggest that SNPs in the SIGLEC5/SIGLEC14 genes play a role in cellular and inflammatory immune responses to mumps vaccination. These findings motivate further research into the functional roles of SIGLEC genes in the regulation of mumps vaccine-induced immunity.
Subject(s)
Measles , Mumps , Rubella , Humans , Mumps Vaccine/genetics , Tumor Necrosis Factor-alpha , Mumps/prevention & control , Genome-Wide Association Study , Immunity, Cellular , Cytokines , Chemokines , Sialic Acid Binding Immunoglobulin-like Lectins/genetics , Measles-Mumps-Rubella Vaccine , Antibodies, Viral , Rubella/prevention & controlABSTRACT
Background: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (PRSCHD) for 5 genetic ancestry groups. Methods: We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSP+T) and continuous shrinkage priors (PRSCSx) applied on summary statistics from the largest multi-ancestry genome-wide meta-analysis for CHD to date, including 1.1 million participants from 5 continental populations. Following training and optimization of PRSCHD in the Million Veteran Program, we evaluated predictive performance of the best performing PRSCHD in 176,988 individuals across 9 cohorts of diverse genetic ancestry. Results: Multi-ancestry PRSP+T outperformed ancestry specific PRSP+T across a range of tuning values. In training stage, for all ancestry groups, PRSCSx performed better than PRSP+T and multi-ancestry PRS outperformed ancestry-specific PRS. In independent validation cohorts, the selected multi-ancestry PRSP+T demonstrated the strongest association with CHD in individuals of South Asian (SAS) and European (EUR) ancestry (OR per 1SD[95% CI]; 2.75[2.41-3.14], 1.65[1.59-1.72]), followed by East Asian (EAS) (1.56[1.50-1.61]), Hispanic/Latino (HIS) (1.38[1.24-1.54]), and weakest in African (AFR) ancestry (1.16[1.11-1.21]). The selected multi-ancestry PRSCSx showed stronger associacion with CHD in comparison within each ancestry group where the association was strongest in SAS (2.67[2.38-3.00]) and EUR (1.65[1.59-1.71]), progressively decreasing in EAS (1.59[1.54-1.64]), HIS (1.51[1.35-1.69]), and lowest in AFR (1.20[1.15-1.26]). Conclusions: Utilizing diverse summary statistics from a large multi-ancestry genome-wide meta-analysis led to improved performance of PRSCHD in most ancestry groups compared to single-ancestry methods. Improvement of predictive performance was limited, specifically in AFR and HIS, despite use of one of the largest and most diverse set of training and validation cohorts to date. This highlights the need for larger GWAS datasets of AFR and HIS individuals to enhance performance of PRSCHD.
ABSTRACT
Clinical trials have been the bedrock of research to evaluate the safety and efficacy of new medical, surgical, or other interventions. Traditional "explanatory" clinical trials have aimed to explain a biological cause (new treatment) and effect (patient outcome) while controlling for many factors that might impact the evaluation, such as restricted eligibility criteria, frequent follow-up visits, and multiple clinical and laboratory measures. Despite the benefits of a well-controlled clinical trial, compromises have been made that can limit who might benefit from a new intervention, can increase complexity of the conduct of a trial, or that lead to excessively long durations of trials. An alternative approach to evaluate the effectiveness of an intervention is based on "pragmatic" clinical trials, which consider how an intervention affects a patient's condition in the real world, accounting for how to optimize an intervention within the operations of busy and diverse clinical practices. Although we describe explanatory and pragmatic trial designs as separate approaches, there is a continuum of approaches that intersect. Some key points are the need to maintain scientific rigor, increase efficiency of clinical trials operations, ensure that trial results can be generalized to a broad spectrum of patients, and balance the needs of real-world clinical care. Pragmatic trials can leverage technology and telecommunication strategies of decentralized trials to further reach underrepresented and underserved patients to close the health disparity gaps.
Subject(s)
Research Design , Humans , Time Factors , Clinical Trials as TopicABSTRACT
Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.
Subject(s)
Genetic Predisposition to Disease , Prostatic Neoplasms , Humans , Male , Black People/genetics , Genome-Wide Association Study , Multifactorial Inheritance/genetics , Prostatic Neoplasms/genetics , Risk Factors , White People/geneticsABSTRACT
Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.
ABSTRACT
Background: We have previously described genetic polymorphisms in candidate genes that are associated with inter-individual variations in antibody responses to mumps vaccination. To expand upon our previous work, we performed a genome-wide association study (GWAS) to discover host genetic variants associated with mumps vaccine-induced cellular immune responses. Methods: We performed a GWAS of mumps-specific immune response outcomes (11 secreted cytokines/chemokines) in a cohort of 1,406 subjects. Results: Among the 11 cytokine/chemokines we studied, four (IFN-γ, IL-2, IL-1ß, and TNFα) demonstrated GWAS signals reaching genome-wide significance (p<5 x 10 -8 ). A genomic region (encoding Sialic acid-binding immunoglobulin-type lectins/SIGLEC) located on chromosome 19q13 (p<5×10 -8 ) was associated with both IL-1ß and TNFα responses. The SIGLEC5/SIGLEC14 region contained 11 statistically significant single nucleotide polymorphisms (SNPs), including the intronic SIGLEC5 rs872629 (p=1.3E-11) and rs1106476 (p=1.32E-11) whose alternate alleles were significantly associated with decreased levels of mumps-specific IL-1ß (rs872629, p=1.77E-09; rs1106476, p=1.78E-09) and TNFα (rs872629, p=1.3E-11; rs1106476, p=1.32E-11) production. Conclusions: Our results suggest that SNPs in the SIGLEC5/SIGLEC14 genes play a role in cellular and inflammatory immune responses to mumps vaccination. These findings motivate further research into the functional roles of SIGLEC genes in the regulation of mumps vaccine-induced immunity.
ABSTRACT
PURPOSE OF REVIEW: There is considerable interest in using polygenic risk scores (PRSs) for assessing risk of atherosclerotic cardiovascular disease (ASCVD). A barrier to the clinical use of PRSs is heterogeneity in how PRS studies are reported. In this review, we summarize approaches to establish a uniform reporting framework for PRSs for coronary heart disease (CHD), the most common form of ASCVD. RECENT FINDINGS: Reporting standards for PRSs need to be contextualized for disease specific applications. In addition to metrics of predictive performance, reporting standards for PRSs for CHD should include how cases/control were ascertained, degree of adjustment for conventional CHD risk factors, portability to diverse genetic ancestry groups and admixed individuals, and quality control measures for clinical deployment. Such a framework will enable PRSs to be optimized and benchmarked for clinical use.
Subject(s)
Atherosclerosis , Cardiovascular Diseases , Coronary Disease , Humans , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/genetics , Risk Factors , Atherosclerosis/genetics , Genome-Wide Association Study , Genetic Predisposition to DiseaseABSTRACT
Leveraging linkage disequilibrium (LD) patterns as representative of population substructure enables the discovery of additive association signals in genome-wide association studies (GWASs). Standard GWASs are well-powered to interrogate additive models; however, new approaches are required for invesigating other modes of inheritance such as dominance and epistasis. Epistasis, or non-additive interaction between genes, exists across the genome but often goes undetected because of a lack of statistical power. Furthermore, the adoption of LD pruning as customary in standard GWASs excludes detection of sites that are in LD but might underlie the genetic architecture of complex traits. We hypothesize that uncovering long-range interactions between loci with strong LD due to epistatic selection can elucidate genetic mechanisms underlying common diseases. To investigate this hypothesis, we tested for associations between 23 common diseases and 5,625,845 epistatic SNP-SNP pairs (determined by Ohta's D statistics) in long-range LD (>0.25 cM). Across five disease phenotypes, we identified one significant and four near-significant associations that replicated in two large genotype-phenotype datasets (UK Biobank and eMERGE). The genes that were most likely involved in the replicated associations were (1) members of highly conserved gene families with complex roles in multiple pathways, (2) essential genes, and/or (3) genes that were associated in the literature with complex traits that display variable expressivity. These results support the highly pleiotropic and conserved nature of variants in long-range LD under epistatic selection. Our work supports the hypothesis that epistatic interactions regulate diverse clinical mechanisms and might especially be driving factors in conditions with a wide range of phenotypic outcomes.
Subject(s)
Epistasis, Genetic , Genome-Wide Association Study , Linkage Disequilibrium/genetics , Genotype , Biological Specimen Banks , United Kingdom , Polymorphism, Single Nucleotide/geneticsABSTRACT
The number of studies with information at multiple biological levels of granularity, such as genomics, proteomics, and metabolomics, is increasing each year, and a biomedical questaion is how to systematically integrate these data to discover new biological mechanisms that have the potential to elucidate the processes of health and disease. Causal frameworks, such as Mendelian randomization (MR), provide a foundation to begin integrating data for new biological discoveries. Despite the growing number of MR applications in a wide variety of biomedical studies, there are few approaches for the systematic analysis of omic data. The large number and diverse types of molecular components involved in complex diseases interact through complex networks, and classical MR approaches targeting individual components do not consider the underlying relationships. In contrast, causal network models established in the principles of MR offer significant improvements to the classical MR framework for understanding omic data. Integration of these mostly distinct branches of statistics is a recent development, and we here review the current progress. To set the stage for causal network models, we review some recent progress in the classical MR framework. We then explain how to transition from the classical MR framework to causal networks. We discuss the identification of causal networks and evaluate the underlying assumptions. We also introduce some tests for sensitivity analysis and stability assessment of causal networks. We then review practical details to perform real data analysis and identify causal networks and highlight some of the utility of causal networks. The utilities with validated novel findings reveal the full potential of causal networks as a systems approach that will become necessary to integrate large-scale omic data.
ABSTRACT
PURPOSE OF REVIEW: A polygenic risk score (PRS) is a measure of genetic liability to a disease and is typically normally distributed in a population. Individuals in the upper tail of this distribution often have relative risk equivalent to that of monogenic form of the disease. The majority of currently available PRSs for coronary heart disease (CHD) have been generated from cohorts of European ancestry (EUR) and vary in their applicability to other ancestry groups. In this report, we review the performance of PRSs for CHD across different ancestries and efforts to reduce variability in performance including novel population and statistical genetics approaches. RECENT FINDINGS: PRSs for CHD perform robustly in EUR populations but lag in performance in non-EUR groups, particularly individuals of African ancestry. Several large consortia have been established to enable genomic studies in diverse ancestry groups and develop methods to improve PRS performance in multi-ancestry contexts as well as admixed individuals. These include fine-mapping to ascertain causal variants, trans ancestry meta-analyses, and ancestry deconvolution in admixed individuals. PRSs are being used in the clinical setting but enthusiasm has been tempered by the variable performance in non-EUR ancestry groups. Increasing diversity in genomic association studies and continued innovation in methodological approaches are needed to improve PRS performance in non-EUR individuals for equitable implementation of genomic medicine.
Subject(s)
Coronary Disease , Genome-Wide Association Study , Coronary Disease/genetics , Genetic Predisposition to Disease , Humans , Risk FactorsABSTRACT
PURPOSE: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS). EXPERIMENTAL DESIGN: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes. RESULTS: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE. CONCLUSIONS: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways.