Minority-centric meta-analyses of blood lipid levels identify novel loci in the Population Architecture using Genomics and Epidemiology (PAGE) study.

Lipid levels are important markers for the development of cardio-metabolic diseases. Although hundreds of associated loci have been identified through genetic association studies, the contribution of genetic factors to variation in lipids is not fully understood, particularly in U.S. minority groups. We performed genome-wide association analyses for four lipid traits in over 45,000 ancestrally diverse participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study, followed by a meta-analysis with several European ancestry studies. We identified nine novel lipid loci, five of which showed evidence of replication in independent studies. Furthermore, we discovered one novel gene in a PrediXcan analysis, minority-specific independent signals at eight previously reported loci, and potential functional variants at two known loci through fine-mapping. Systematic examination of known lipid loci revealed smaller effect estimates in African American and Hispanic ancestry populations than those in Europeans, and better performance of polygenic risk scores based on minority-specific effect estimates. Our findings provide new insight into the genetic architecture of lipid traits and highlight the importance of conducting genetic studies in diverse populations in the era of precision medicine.

Effects of Colorectal Cancer Risk Factors on the Association Between Aspirin and Colorectal Cancer.

BACKGROUND/AIM: We investigated the effect of aspirin on colorectal cancer (CRC) risk among subgroups of women with and without risk factors for CRC. PATIENTS AND METHODS: Using data from the Women's Health Initiative, we estimated hazard ratios for CRC in association with aspirin use, with stratifications by cardiovascular disease (CVD) risk status, family history of CRC, and history of colorectal polypectomy. RESULTS: Aspirin was associated with a lower risk of CRC among women with low/normal or high CVD-risk status; no family history of CRC; or a history of colonoscopy with polypectomy. Aspirin was not associated with CRC among women with a family history of CRC or a history of colonoscopy without polypectomy. CONCLUSION: Aspirin was associated with a lower risk of CRC in women at all levels of CVD-risk, in those with a history of colonoscopy with polypectomy, and in those without a family history of CRC.

Genetic analyses of diverse populations improves discovery for complex traits.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Genetic Predisposition Impacts Clinical Changes in a Lifestyle Coaching Program.

Both genetic and lifestyle factors contribute to an individual's disease risk, suggesting a multi-omic approach is essential for personalized prevention. Studies have examined the effectiveness of lifestyle coaching on clinical outcomes, however, little is known about the impact of genetic predisposition on the response to lifestyle coaching. Here we report on the results of a real-world observational study in 2531 participants enrolled in a commercial "Scientific Wellness" program, which combines multi-omic data with personalized, telephonic lifestyle coaching. Specifically, we examined: 1) the impact of this program on 55 clinical markers and 2) the effect of genetic predisposition on these clinical changes. We identified sustained improvements in clinical markers related to cardiometabolic risk, inflammation, nutrition, and anthropometrics. Notably, improvements in HbA1c were akin to those observed in landmark trials. Furthermore, genetic markers were associated with longitudinal changes in clinical markers. For example, individuals with genetic predisposition for higher LDL-C had a lesser decrease in LDL-C on average than those with genetic predisposition for average LDL-C. Overall, these results suggest that a program combining multi-omic data with lifestyle coaching produces clinically meaningful improvements, and that genetic predisposition impacts clinical responses to lifestyle change.

A Multi-omic Association Study of Trimethylamine N-Oxide.

Trimethylamine N-oxide (TMAO) is a circulating metabolite that has been implicated in the development of atherosclerosis and cardiovascular disease (CVD). In this paper, we identify blood markers, metabolites, proteins, gut microbiota patterns, and diets that are significantly associated with levels of plasma TMAO. We find that kidney markers are strongly associated with TMAO and identify CVD-related proteins that are positively correlated with TMAO. We show that metabolites derived by the gut microbiota are strongly correlated with TMAO and that the magnitude of this correlation varies with kidney function. Moreover, we identify diet-associated patterns in the microbiome that are correlated with TMAO. These findings suggest that both the process of TMAO accumulation and the mechanism by which TMAO promotes atherosclerosis are a complex interplay between diet and the microbiome on one hand and other system-level factors such as circulating proteins, metabolites, and kidney function.

Influence of Smoking, Body Mass Index, and Other Factors on the Preventive Effect of Nonsteroidal Anti-Inflammatory Drugs on Colorectal Cancer Risk.

Nonsteroidal anti-inflammatory drugs' (NSAID) use has consistently been associated with lower risk of colorectal cancer; however, studies showed inconsistent results on which cohort of individuals may benefit most. We performed multivariable logistic regression analysis to systematically test for the interaction between regular use of NSAIDs and other lifestyle and dietary factors on colorectal cancer risk among 11,894 cases and 15,999 controls. Fixed-effects meta-analyses were used for stratified analyses across studies for each risk factor and to summarize the estimates from interactions. Regular use of any NSAID, aspirin, or nonaspirin NSAIDs was significantly associated with a lower risk of colorectal cancer within almost all subgroups. However, smoking status and BMI were found to modify the NSAID-colorectal cancer association. Aspirin use was associated with a 29% lower colorectal cancer risk among never-smokers [odds ratios (OR) = 0.71; 95% confidence intervals (CI): 0.64-0.79], compared with 19% and 17% lower colorectal cancer risk among smokers of pack-years below median (OR, 0.81; 95% CI, 0.71-0.92) and above median (OR, 0.83; 95% CI, 0.74-0.94), respectively (P interaction = 0.048). The association between any NSAID use and colorectal cancer risk was also attenuated with increasing BMI (P interaction = 0.075). Collectively, these results suggest that obese individuals and heavy smokers are unlikely to benefit as much as other groups from the prophylactic effect of aspirin against colorectal cancer.Significance: Obesity and heavy smoking attenuate the benefit of aspirin use for colorectal cancer prevention. Cancer Res; 78(16); 4790-9. ©2018 AACR.

Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors.

BACKGROUND & AIMS: Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening. METHODS: We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry. RESULTS: In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62-0.64) for men and 0.62 (95% confidence interval, 0.61-0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk. CONCLUSIONS: We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.

Fine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations.

BACKGROUND: The electrocardiographically measured QT interval (QT) is heritable and its prolongation is an established risk factor for several cardiovascular diseases. Yet, most QT genetic studies have been performed in European ancestral populations, possibly reducing their global relevance. OBJECTIVE: To leverage diversity and improve biological insight, we fine mapped 16 of the 35 previously identified QT loci (46%) in populations of African American (n = 12,410) and Hispanic/Latino (n = 14,837) ancestry. METHODS: Racial/ethnic-specific multiple linear regression analyses adjusted for heart rate and clinical covariates were examined separately and in combination after inverse-variance weighted trans-ethnic meta-analysis. RESULTS: The 16 fine-mapped QT loci included on the Illumina Metabochip represented 21 independent signals, of which 16 (76%) were significantly (P-value≤9.1×10-5) associated with QT. Through sequential conditional analysis we also identified three trans-ethnic novel SNPs at ATP1B1, SCN5A-SCN10A, and KCNQ1 and three Hispanic/Latino-specific novel SNPs at NOS1AP and SCN5A-SCN10A (two novel SNPs) with evidence of associations with QT independent of previous identified GWAS lead SNPs. Linkage disequilibrium patterns helped to narrow the region likely to contain the functional variants at several loci, including NOS1AP, USP50-TRPM7, and PRKCA, although intervals surrounding SLC35F1-PLN and CNOT1 remained broad in size (>100 kb). Finally, bioinformatics-based functional characterization suggested a regulatory function in cardiac tissues for the majority of independent signals that generalized and the novel SNPs. CONCLUSION: Our findings suggest that a majority of identified SNPs implicate gene regulatory dysfunction in QT prolongation, that the same loci influence variation in QT across global populations, and that additional, novel, population-specific QT signals exist.

Strategies for Enriching Variant Coverage in Candidate Disease Loci on a Multiethnic Genotyping Array.

Investigating genetic architecture of complex traits in ancestrally diverse populations is imperative to understand the etiology of disease. However, the current paucity of genetic research in people of African and Latin American ancestry, Hispanic and indigenous peoples in the United States is likely to exacerbate existing health disparities for many common diseases. The Population Architecture using Genomics and Epidemiology, Phase II (PAGE II), Study was initiated in 2013 by the National Human Genome Research Institute to expand our understanding of complex trait loci in ethnically diverse and well characterized study populations. To meet this goal, the Multi-Ethnic Genotyping Array (MEGA) was designed to substantially improve fine-mapping and functional discovery by increasing variant coverage across multiple ethnicities at known loci for metabolic, cardiovascular, renal, inflammatory, anthropometric, and a variety of lifestyle traits. Studying the frequency distribution of clinically relevant mutations, putative risk alleles, and known functional variants across multiple populations will provide important insight into the genetic architecture of complex diseases and facilitate the discovery of novel, sometimes population-specific, disease associations. DNA samples from 51,650 self-identified African ancestry (17,328), Hispanic/Latino (22,379), Asian/Pacific Islander (8,640), and American Indian (653) and an additional 2,650 participants of either South Asian or European ancestry, and other reference panels have been genotyped on MEGA by PAGE II. MEGA was designed as a new resource for studying ancestrally diverse populations. Here, we describe the methodology for selecting trait-specific content for use in multi-ethnic populations and how enriching MEGA for this content may contribute to deeper biological understanding of the genetic etiology of complex disease.

Variant Discovery and Fine Mapping of Genetic Loci Associated with Blood Pressure Traits in Hispanics and African Americans.

Despite the substantial burden of hypertension in US minority populations, few genetic studies of blood pressure have been conducted in Hispanics and African Americans, and it is unclear whether many of the established loci identified in European-descent populations contribute to blood pressure variation in non-European descent populations. Using the Metabochip array, we sought to characterize the genetic architecture of previously identified blood pressure loci, and identify novel cardiometabolic variants related to systolic and diastolic blood pressure in a multi-ethnic US population including Hispanics (n = 19,706) and African Americans (n = 18,744). Several known blood pressure loci replicated in African Americans and Hispanics. Fourteen variants in three loci (KCNK3, FGF5, ATXN2-SH2B3) were significantly associated with blood pressure in Hispanics. The most significant diastolic blood pressure variant identified in our analysis, rs2586886/KCNK3 (P = 5.2 x 10-9), also replicated in independent Hispanic and European-descent samples. African American and trans-ethnic meta-analysis data identified novel variants in the FGF5, ULK4 and HOXA-EVX1 loci, which have not been previously associated with blood pressure traits. Our identification and independent replication of variants in KCNK3, a gene implicated in primary hyperaldosteronism, as well as a variant in HOTTIP (HOXA-EVX1) suggest that further work to clarify the roles of these genes may be warranted. Overall, our findings suggest that loci identified in European descent populations also contribute to blood pressure variation in diverse populations including Hispanics and African Americans-populations that are understudied for hypertension genetic risk factors.

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci.

Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.

Genetic architecture of colorectal cancer.

Colorectal cancer (CRC) is a complex disease that develops as a consequence of both genetic and environmental risk factors. A small proportion (3-5%) of cases arise from hereditary syndromes predisposing to early onset CRC as a result of mutations in over a dozen well defined genes. In contrast, CRC is predominantly a late onset 'sporadic' disease, developing in individuals with no obvious hereditary syndrome. In recent years, genome wide association studies have discovered that over 40 genetic regions are associated with weak effects on sporadic CRC, and it has been estimated that increasingly large genome wide scans will identify many additional novel genetic regions. Subsequent experimental validations have identified the causally related variant(s) in a limited number of these genetic regions. Further biological insight could be obtained through ethnically diverse study populations, larger genetic sequencing studies and development of higher throughput functional experiments. Along with inherited variation, integration of the tumour genome may shed light on the carcinogenic processes in CRC. In addition to summarising the genetic architecture of CRC, this review discusses genetic factors that modify environmental predictors of CRC, as well as examples of how genetic insight has improved clinical surveillance, prevention and treatment strategies. In summary, substantial progress has been made in uncovering the genetic architecture of CRC, and continued research efforts are expected to identify additional genetic risk factors that further our biological understanding of this disease. Subsequently these new insights will lead to improved treatment and prevention of colorectal cancer.

Genetic variation predicts serum lycopene concentrations in a multiethnic population of postmenopausal women.

BACKGROUND: The consumption and blood concentrations of lycopene are both positively and inversely associated with the risk of several chronic diseases. The inconsistences in lycopene disease association studies may stem from a lack of knowledge about the genetic variation in the synthesis, metabolism, and deposition of transport and binding proteins, which potentially influence serum lycopene concentrations. OBJECTIVE: We examined the association between variation across the genome and serum concentrations of lycopene in a multiethnic population. METHODS: Participants included African (n = 914), Hispanic (n = 464), and European (n = 1203) American postmenopausal women from the Women's Health Initiative. We analyzed ∼7 million single nucleotide polymorphisms (SNPs). Linear regression models were used to assess associations between each SNP and serum concentrations (log transformed, continuous) of lycopene; we adjusted for age, body mass index, and population substructure. Models were run separately by ethnicity, and results were combined in a transethnic fixed-effects meta-analysis. RESULTS: In the meta-analysis, the scavenger receptor class B, member 1 (SCARB1) gene, which encodes for a cholesterol membrane transporter, was significantly associated with lycopene concentrations (rs1672879; P < 2.68 × 10(-9)). Each additional G allele resulted in a 12% decrease in lycopene concentrations for African Americans, 20% decrease for Hispanic Americans, and 9% decrease for European Americans. In addition, 2 regions were significantly associated with serum lycopene concentrations in African Americans: the slit homolog 3 gene (SLIT3), which serves as a molecular guidance cue in cellular migration, and the dehydrogenase/reductase (SDR family) member 2 (DHRS2) gene, which codes for an oxidoreductase that mitigates the breakdown of steroids. CONCLUSIONS: We found 3 novel loci associated with serum lycopene concentrations, 2 of which were specific to African Americans. Future functional studies looking at these specific genes may provide insight into the metabolism and underlying function of lycopene in humans, which may further elucidate lycopene's influence on disease risk and health. This trial was registered at clinicaltrials.gov as NCT00000611.

Clustering and determinants of cardiometabolic risk factors among Filipino young adults.

BACKGROUND: With modernization, cardiometabolic disease risk has increased in low and middle-income countries. To better understand cardiometabolic disease etiology, we evaluated the patterning risk factors in a susceptible young adult population. METHODS AND RESULTS: Participants included 1,621 individuals from the 2005 Cebu Longitudinal Health and Nutrition Survey. Using cluster analysis, we grouped individuals by the following biomarkers: triglycerides, HDL and LDL cholesterol, C-reactive protein, blood pressure, homeostasis model assessment of insulin resistance, and fasting glucose. Using multinomial logistic regression models we assessed how diet, adiposity, and environment predicted cardiometabolic clusters. We identified 5 distinct sexspecific clusters: 1) Healthy/High HDL cholesterol (with the addition of high LDL cholesterol in women); 2) Healthy/Low blood pressure; 3) High blood pressure; 4) Insulin resistant/High triglycerides; and 5) High Creactive protein. Low HDL cholesterol was the most prevalent risk factor (63%). In men and women, a higher intake of saturated fat increased the likelihood of being in the healthy clusters. In men, poorer environmental hygiene increased the likelihood of being in the High C-reactive protein cluster, compared to the healthy clusters (OR 0.74 [95% CI 0.60-0.90] and 0.83 [0.70-0.99]). Adiposity most strongly associated with membership to the Insulin resistant/high triglyceride cluster. CONCLUSIONS: Despite the population's youth and leanness, cluster analysis found patterns of cardiometabolic risk. While adiposity measures predicted clustering, diet and environment also independently predicted clustering, emphasizing the importance of screening lean and overweight individuals for cardiometabolic risk. Finding predictors of risk in early adulthood could help inform prevention efforts for future disease.

Cluster analysis reveals important determinants of cardiometabolic risk patterns in Filipino women.

With modernization, the Philippines has experienced increasing rates of obesity and related cardiometabolic diseases. Studying how risk factors cluster in individuals may offer insight into cardiometabolic disease etiology. We used cluster analysis to group women who share the following cardiometabolic biomarkers: fasting triglycerides, HDL-C and LDL-C, C-reactive protein, systolic and diastolic blood pressure, homeostasis model assessment of insulin resistance, and fasting glucose. Participants included 1,768 women (36-69 years) in the Cebu Longitudinal Health and Nutrition Survey. We identified five distinct clusters characterized by: 1) low levels of all risk factors (except HDL-C and LDL-C) or "healthy"; 2) low HDL-C in the absence of other risk factors; 3) elevated blood pressure; 4) insulin resistance; and 5) high C-reactive protein. We identified predictors of cluster membership using multinomial logistic regression. Clusters differed by age, menopausal status, socioeconomic status, saturated fat intake, and combinations of overweight (BMI >23) and high waist circumference (>80 cm). In comparison to the healthy cluster, overweight women without high waist circumference were more likely to be in the high CRP cluster (OR=2.26, 95% CI=1.24-4.11), while women with high waist circumference and not overweight were more likely to be in the elevated blood pressure (OR=2.56, 95% CI=1.20-5.46) or insulin resistant clusters (OR=4.05, 95% CI=1.39-11.8). In addition, a diet lower in saturated fat uniquely increased the likelihood of membership to the low HDL-C cluster. Cluster analysis identified biologically meaningful groups, predicted by modifiable risk factors; this may have implications for the prevention of cardiometabolic diseases.