ABSTRACT
The heritability explained by local ancestry markers in an admixed population (hγ2) provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of hγ2 can be susceptible to biases due to population structure in ancestral populations. Here, we present heritability estimation from admixture mapping summary statistics (HAMSTA), an approach that uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA hγ2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of â¼5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe hËγ2 in the 20 phenotypes range from 0.0025 to 0.033 (mean hËγ2 = 0.012 ± 9.2 × 10-4), which translates to hË2 ranging from 0.062 to 0.85 (mean hË2 = 0.30 ± 0.023). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 ± 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies.
Subject(s)
Black or African American , Genetics, Population , Humans , Chromosome Mapping , Phenotype , Polymorphism, Single Nucleotide/geneticsABSTRACT
Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.
ABSTRACT
Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.
ABSTRACT
Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.
Subject(s)
Clonal Hematopoiesis , Prostatic Neoplasms , Male , Humans , Hematopoiesis/genetics , Risk Factors , Hematopoietic Stem Cells , Prostatic Neoplasms/genetics , MutationABSTRACT
Transcriptome-wide association studies (TWASs) are a powerful approach to identify genes whose expression is associated with complex disease risk. However, non-causal genes can exhibit association signals due to confounding by linkage disequilibrium (LD) patterns and eQTL pleiotropy at genomic risk regions, which necessitates fine-mapping of TWAS signals. Here, we present MA-FOCUS, a multi-ancestry framework for the improved identification of genes underlying traits of interest. We demonstrate that by leveraging differences in ancestry-specific patterns of LD and eQTL signals, MA-FOCUS consistently outperforms single-ancestry fine-mapping approaches with equivalent total sample sizes across multiple metrics. We perform TWASs for 15 blood traits using genome-wide summary statistics (average nEA = 511 k, nAA = 13 k) and lymphoblastoid cell line eQTL data from cohorts of primarily European and African continental ancestries. We recapitulate evidence demonstrating shared genetic architectures for eQTL and blood traits between the two ancestry groups and observe that gene-level effects correlate 20% more strongly across ancestries than SNP-level effects. Lastly, we perform fine-mapping using MA-FOCUS and find evidence that genes at TWAS risk regions are more likely to be shared across ancestries than they are to be ancestry specific. Using multiple lines of evidence to validate our findings, we find that gene sets produced by MA-FOCUS are more enriched in hematopoietic categories than alternative approaches (p = 2.36 × 10-15). Our work demonstrates that including and appropriately accounting for genetic diversity can drive more profound insights into the genetic architecture of complex traits.
Subject(s)
Genome-Wide Association Study , Transcriptome , Humans , Linkage Disequilibrium , Multifactorial Inheritance/genetics , Polymorphism, Single Nucleotide/genetics , Transcriptome/geneticsABSTRACT
Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.
Subject(s)
Breast Neoplasms , Genome-Wide Association Study , Breast Neoplasms/genetics , Female , Genetic Predisposition to Disease , Humans , Multifactorial Inheritance/genetics , Receptors, Estrogen/genetics , Risk FactorsABSTRACT
BACKGROUND: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk. METHODS: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated. RESULTS: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10-8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10-14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10-3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk. CONCLUSIONS: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.
Subject(s)
Colorectal Neoplasms , Genetic Predisposition to Disease , Humans , Female , Colorectal Neoplasms/genetics , Colorectal Neoplasms/epidemiology , Middle Aged , Case-Control Studies , Risk Factors , Aged , Hormone Replacement Therapy/adverse effects , Risk Assessment , Menopause , Postmenopause , Estrogen Replacement Therapy/adverse effectsABSTRACT
PURPOSE: Risk factors for pancreatic cancer include racial/ethnic disparities and smoking. However, risk trajectories by smoking history and race/ethnicity are unknown. We examined the association of smoking with pancreatic cancer by race/ethnicity to generate age-specific incidence estimates by smoking history. METHODS: We modeled pancreatic cancer incidence by race/ethnicity, age, pack-years, and years-quit using an excess relative risk model for 182,011 Multiethnic Cohort participants. We tested heterogeneity of smoking variables and pancreatic cancer by race/ethnicity and predicted incidence by smoking history. RESULTS: We identified 1,831 incident pancreatic cancer cases over an average 19.3 years of follow-up. Associations of pack-years (p interaction by race/ethnicity = 0.41) and years-quit (p interaction = 0.83) with pancreatic cancer did not differ by race/ethnicity. Fifty pack-years smoked was associated with 91% increased risk (95% CI 54%, 127%) relative to never smokers in the combined sample. Every year quit corresponded to 9% decreased excess risk (95% CI 2%, 15%) from pack-years smoked. Differences in baseline pancreatic cancer risk across racial/ethnic groups (p < 0.001) translated to large differences in risk for smokers at older ages across racial/ethnic groups (65-122 cases per 100,000 at age 70). CONCLUSION: Smoking pack-years were positively associated with elevated pancreatic cancer risk. Predicted risk trajectories showed a high impact of smoking cessation at < 65 years. Although we did not identify significant heterogeneity in the association of pack-years or years quit with pancreatic cancer risk, current smoker risk varied greatly by race/ethnicity in later life due to large differences in baseline risk.
Subject(s)
Pancreatic Neoplasms , Smoking Cessation , Humans , Aged , Cohort Studies , Smoking/adverse effects , Smoking/epidemiology , Risk Factors , Pancreatic Neoplasms/epidemiology , Pancreatic Neoplasms/etiologyABSTRACT
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) may impair bone development in adolescence, which impacts life-long bone health. No previous studies have examined prospective associations of individual PFAS and their mixture with bone mineral density (BMD) changes in Hispanic young persons, a population at high risk of osteoporosis in adulthood. OBJECTIVES: To examine associations of individual PFAS and PFAS mixtures with longitudinal changes in BMD in an adolescent Hispanic cohort and examine generalizability of findings in a mixed-ethnicity young adult cohort (58.4% Hispanic). METHODS: Overweight/obese adolescents from the Study of Latino Adolescents at Risk of Type 2 Diabetes (SOLAR; n = 304; mean follow-up = 1.4 years) and young adults from the Southern California Children's Health Study (CHS; n = 137; mean follow-up = 4.1 years) were included in this study. Plasma PFAS were measured at baseline and dual x-ray absorptiometry scans were performed at baseline and follow-up to measure BMD. We estimated longitudinal associations between BMD and five PFAS via separate covariate-adjusted linear mixed effects models, and between BMD and the PFAS mixture via quantile g-computation. RESULTS: In SOLAR adolescents, baseline plasma perfluorooctanesulfonic acid (PFOS) was associated with longitudinal changes in BMD. Each doubling of PFOS was associated with an average -0.003 g/cm2 difference in change in trunk BMD per year over follow-up (95% CI: -0.005, -0.0002). Associations with PFOS persisted in CHS young adults, where each doubling of plasma PFOS was associated with an average -0.032 g/cm2 difference in total BMD at baseline (95% CI -0.062, -0.003), though longitudinal associations were non-significant. We did not find associations of other PFAS with BMD; associations of the PFAS mixture with BMD outcomes were primarily negative though non-significant. DISCUSSION: PFOS exposure was associated with lower BMD in adolescence and young adulthood, important periods for bone development, which may have implications on future bone health and risk of osteoporosis in adulthood.
Subject(s)
Alkanesulfonic Acids , Diabetes Mellitus, Type 2 , Environmental Pollutants , Fluorocarbons , Osteoporosis , Child , Humans , Adolescent , Young Adult , Adult , Bone Density , Cohort Studies , Environmental Pollutants/toxicity , Fluorocarbons/toxicityABSTRACT
BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.
Subject(s)
Colorectal Neoplasms , Diabetes Mellitus , Humans , Gene-Environment Interaction , Genetic Predisposition to Disease , Risk Factors , Diabetes Mellitus/genetics , Colorectal Neoplasms/genetics , Polymorphism, Single Nucleotide , Genome-Wide Association Study/methods , Microfilament Proteins/geneticsABSTRACT
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), and polybrominated diphenyl ethers (PBDEs) are intentionally produced persistent organic pollutants (POPs) that are resistant to environmental degradation. Previous in-vitro and in-vivo studies have shown that POPs can induce oxidative stress, which is linked to neurodegenerative diseases, cardiovascular diseases, and cancer. However, findings in epidemiological studies are inconsistent and an evidence synthesis study is lacking to summarize the existing literature and explore research gaps. OBJECTIVE: We evaluated the effects of PFAS, PCBs, OCPs, and PBDEs, on oxidative stress biomarkers in epidemiological studies. METHODS: A literature search was conducted in PubMed, Embase, and Cochrane CENTRAL to identify all published studies related to POPs and oxidative stress up to December 7th, 2022. We included human observational studies reporting at least one exposure to POPs and an oxidative stress biomarker of interest. Random-effects meta-analyses on standardized regression coefficients and effect direction plots with one-tailed sign tests were used for quantitative synthesis. RESULTS: We identified 33 studies on OCPs, 35 on PCBs, 49 on PFAS, and 12 on PBDEs. Meta-analyses revealed significant positive associations of α-HCH with protein carbonyls (0.035 [0.017, 0.054]) and of 4'4-DDE with malondialdehyde (0.121 [0.056, 0.187]), as well as a significant negative association between 2'4-DDE and total antioxidant capacity (TAC) (-0.042 [-0.079, -0.004]), all ß [95%CI]. Sign tests showed a significant positive association between PCBs and malondialdehyde (pone-tailed = 0.03). Additionally, we found significant negative associations of OCPs with acetylcholine esterase (pone-tailed = 0.02) and paraoxonase-1 (pone-tailed = 0.03). However, there were inconsistent associations of OCPs with superoxide dismutase, glutathione peroxidase, and catalase. CONCLUSIONS: Higher levels of OCPs were associated with increased levels of oxidative stress through increased pro-oxidant biomarkers involving protein oxidation, DNA damage, and lipid peroxidation, as well as decreased TAC. These findings have the potential to reveal the underlying mechanisms of POPs toxicity.
Subject(s)
Environmental Pollutants , Fluorocarbons , Hydrocarbons, Chlorinated , Pesticides , Polychlorinated Biphenyls , Humans , Antioxidants , Biomarkers , Environmental Pollutants/toxicity , Fluorocarbons/toxicity , Halogenated Diphenyl Ethers/toxicity , Hydrocarbons, Chlorinated/toxicity , Malondialdehyde , Oxidative Stress , Pesticides/toxicity , Polychlorinated Biphenyls/toxicityABSTRACT
BACKGROUND AND AIM: Ambient air pollution (AAP) exposure has been associated with altered blood lipids and liver fat in young adults. MicroRNAs regulate gene expression and may mediate these relationships. This work investigated associations between AAP exposure, serum microRNA networks, lipid profiles, and non-alcoholic fatty liver disease (NAFLD) risk in young adults. METHODS: Participants were 170 young adults (17-22 years) from the Meta-AIR cohort of the Children's Health Study (CHS). Residential AAP exposure (PM2.5, PM10, NO2, 8-hour maximum O3, redox-weighted oxidative capacity [Oxwt]) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Fasting serum lipids were assayed. Liver fat was imaged by MRI and NAFLD was defined by ≥ 5.5% hepatic fat fraction. Serum microRNAs were measured via NanoString and microRNA networks were constructed by weighted gene correlation network analysis. The first principal component of each network represented its expression profile. Multivariable mixed effects regression models adjusted for sociodemographic, behavioral, and clinical covariates; baseline CHS town code was a random effect. Effects estimates are scaled to one standard deviation of exposure. Mediation analysis explored microRNA profiles as potential mediators of exposure-outcome associations. DIANA-mirPATH identified overrepresented gene pathways targeted by miRNA networks. RESULTS: Prior-month Oxwt was associated with NAFLD (OR=3.45; p = 0.003) and inversely associated with microRNA Network A (ß = -0.016; p = 0.026). Prior-year NO2 was associated with non-HDL-cholesterol (ß = 7.13; p = 0.01) and inversely associated with miRNA Network A (ß = -0.019; p = 0.022). Network A expression was inversely associated with NAFLD (OR=0.35; p = 0.010) and non-HDL-C (ß = -6.94 mg/dL; p = 0.035). Network A members miR-199a/b-3p and miR-130a, which both target fatty acid synthase, mediated 21% of the association between prior-month Oxwt exposure with NAFLD (p = 0.048) and 23.3% of the association between prior-year NO2 exposure and non-HDL-cholesterol (p = 0.026), respectively. CONCLUSIONS: Exposure to AAP may contribute to adverse lipid profiles and NAFLD risk among young adults via altered expression of microRNA profiles.
Subject(s)
Air Pollutants , Environmental Pollutants , MicroRNAs , Non-alcoholic Fatty Liver Disease , Child , Humans , Young Adult , MicroRNAs/genetics , Air Pollutants/toxicity , Non-alcoholic Fatty Liver Disease/genetics , Lipid Metabolism/genetics , Nitrogen DioxideABSTRACT
BACKGROUND AND AIMS: Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes. METHODS: Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted. RESULTS: We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis. CONCLUSIONS: Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.
Subject(s)
Biomarkers, Tumor/genetics , Colorectal Neoplasms/genetics , Genetic Predisposition to Disease , Models, Genetic , Alleles , Carcinogenesis/genetics , Case-Control Studies , Cohort Studies , Colorectal Neoplasms/epidemiology , Gene Knockdown Techniques , Genome-Wide Association Study , Humans , Polymorphism, Single Nucleotide , Promoter Regions, Genetic/genetics , RNA-Seq , Risk Factors , Xenograft Model Antitumor AssaysABSTRACT
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most prevalent cause of liver disease in children. Mercury (Hg), a ubiquitous toxic metal, has been proposed as an environmental factor contributing to toxicant-associated fatty liver disease. APPROACH AND RESULTS: We investigated the effect of prenatal exposure to Hg on childhood liver injury by combining epidemiological results from a multicenter mother-child cohort with complementary in vitro experiments on monocyte cells that are known to play a key role in liver immune homeostasis and NAFLD. We used data from 872 mothers and their children (median age, 8.1 years; interquartile range [IQR], 6.5-8.7) from the European Human Early-Life Exposome cohort. We measured Hg concentration in maternal blood during pregnancy (median, 2.0 µg/L; IQR, 1.1-3.6). We also assessed serum levels of alanine aminotransferase (ALT), a common screening tool for pediatric NAFLD, and plasma concentrations of inflammation-related cytokines in children. We found that prenatal Hg exposure was associated with a phenotype in children that was characterized by elevated ALT (≥22.1 U/L for females and ≥25.8 U/L for males) and increased concentrations of circulating IL-1ß, IL-6, IL-8, and TNF-α. Consistently, inflammatory monocytes exposed in vitro to a physiologically relevant dose of Hg demonstrated significant up-regulation of genes encoding these four cytokines and increased concentrations of IL-8 and TNF-α in the supernatants. CONCLUSIONS: These findings suggest that developmental exposure to Hg can contribute to inflammation and increased NAFLD risk in early life.
Subject(s)
Mercury/blood , Non-alcoholic Fatty Liver Disease/epidemiology , Prenatal Exposure Delayed Effects/epidemiology , Adult , Alanine Transaminase , Child , Cohort Studies , Cytokines , Disease Susceptibility , Exposome , Female , Humans , Inflammation , Interleukin-1beta/genetics , Interleukin-1beta/metabolism , Interleukin-6/genetics , Interleukin-6/metabolism , Interleukin-8/genetics , Interleukin-8/metabolism , Male , Maternal Exposure , Non-alcoholic Fatty Liver Disease/genetics , Non-alcoholic Fatty Liver Disease/metabolism , Pregnancy , Prenatal Exposure Delayed Effects/genetics , Prenatal Exposure Delayed Effects/metabolism , Tumor Necrosis Factor-alpha/genetics , Tumor Necrosis Factor-alpha/metabolismABSTRACT
BACKGROUND: Exposure to lipophilic persistent organic pollutants (POPs) is ubiquitous. POPs are metabolic disrupting chemicals and are potentially diabetogenic. METHODS: Using a multi-cohort study including overweight adolescents from the Study of Latino Adolescents at Risk (SOLAR, N = 301, 2001-2012) and young adults from the Southern California Children's Health Study (CHS, N = 135, 2014-2018), we examined associations of POPs and risk factors for type 2 diabetes. SOLAR participants underwent annual visits for a median of 2.2 years and CHS participants performed a single visit, during which a 2-h oral glucose tolerance test was performed. Linear mixed models were used to examine associations between plasma concentrations of POPs [4,4'-dichlorodiphenyldichloroethylene (4,4'-DDE), hexachlorobenzene (HCB), PCBs-153, 138, 118, 180 and PBDEs-154, 153, 100, 85, 47] and changes in glucose homeostasis across age and pubertal stage. RESULTS: In SOLAR, exposure to HCB, PCB-118, and PBDE-153 was associated with dysregulated glucose metabolism. For example, each two-fold increase in HCB was associated with approximately 2 mg/dL higher glucose concentrations at 30 min (p = 0.001), 45 min (p = 0.0006), and 60 min (p = 0.03) post glucose challenge. Compared to individuals with low levels of PCB-118, individuals with high levels exhibited a 4.7 mg/dL (p = 0.02) higher glucose concentration at 15 min and a 3.6 mg/dL (p = 0.01) higher glucose concentration at 30 min. The effects observed with exposure to organochlorine compounds were independent of pubertal stages. PBDE-153 was associated with the development of dysregulated glucose metabolism beginning in late puberty. At Tanner stage 4, exposure to PBDE-153 was associated with a 12.7 mg/dL higher 60-min glucose concentration (p = 0.009) and a 16.1 mg*dl-1*hr-1 higher glucose AUC (p = 0.01). These associations persisted at Tanner 5. In CHS, PBDE-153 and total PBDE were associated with similar increases in glucose concentrations. CONCLUSION: Our results suggest that childhood exposure to lipophilic POPs is associated with dysregulated glucose metabolism.
Subject(s)
Diabetes Mellitus, Type 2 , Environmental Pollutants , Hydrocarbons, Chlorinated , Polychlorinated Biphenyls , Adolescent , Child , Cohort Studies , Dichlorodiphenyl Dichloroethylene , Glucose , Hexachlorobenzene , Homeostasis , Humans , Hydrocarbons, Chlorinated/toxicity , Persistent Organic Pollutants , Young AdultABSTRACT
BACKGROUND: The majority of research to understand the risk factors of nonsyndromic orofacial clefts (NSOFCs) has been conducted in high-income populations. Although patients with NSOFCs in low- and middle-income countries (LMICs) are at the highest risk of not receiving care, global health infrastructure allows innovative partnerships to explore the etiologic mechanisms of cleft and targets for prevention unique to these populations. METHODS: The International Family Study (IFS) is an ongoing case-control study with supplemental parental trio data designed to examine genetic, environmental, lifestyle, and sociodemographic risk factors for NSOFCs in 8 LMICs (through August 2020). Interview and biological samples are collected for each family. The interview includes demographics, family history of cleft, diet and water sources, maternal pregnancy history, and other lifestyle and environmental factors. RESULTS: Seven of 8 countries are currently summarized (2012-2017) for a total of 2955 case and 2774 control families with 11 946 unique biological samples from Vietnam, Philippines, Honduras, Madagascar, Morocco, Democratic Republic of the Congo, and Nicaragua. The phenotype distribution was 1641 (55.5%) cases with cleft lip and palate, 782 (26.5%) with cleft lip (CL), and 432 (14.6%) with cleft palate (CP). DISCUSSION: The International Family Study is the largest case set of NSOFCs with an associated biobank in LMICs currently assembled. The biobank, family, and case-control study now include samples from 8 LMICs where local health care infrastructure cannot address the surgical burden of cleft or investigate causal mechanisms. The International Family Study can be a source of information and may collaborate with local public health institutions regarding education and interventions to potentially prevent NSOFCs.
Subject(s)
Cleft Lip , Cleft Palate , Brain/abnormalities , Case-Control Studies , Cleft Lip/epidemiology , Cleft Lip/genetics , Cleft Palate/epidemiology , Cleft Palate/genetics , Female , Humans , PregnancyABSTRACT
OBJECTIVE: An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. DESIGN: To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. RESULTS: We identified 13 loci that reached genome-wide significance (p<5×10-8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. CONCLUSION: Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.
Subject(s)
Colon , Colonic Neoplasms/genetics , Genetic Heterogeneity , Rectal Neoplasms/genetics , Adult , Age Distribution , Age of Onset , Aged , Aged, 80 and over , Alleles , Case-Control Studies , Cecum , Colon, Ascending , Colon, Descending , Colon, Sigmoid , Colon, Transverse , Colonic Neoplasms/diagnosis , Female , Genome-Wide Association Study , Genotype , Humans , Male , Middle Aged , Polymorphism, Single Nucleotide , Rectal Neoplasms/diagnosis , Risk Factors , White People/genetics , Young AdultABSTRACT
Previous research has demonstrated the usefulness of hierarchical modeling for incorporating a flexible array of prior information in genetic association studies. When this prior information consists of estimates from association analyses of single-nucleotide polymorphisms (SNP)-intermediate or SNP-gene expression, a hierarchical model is equivalent to a 2-stage instrumental or transcriptome-wide association study (TWAS) analysis, respectively. We propose to extend our previous approach for the joint analysis of marginal summary statistics to incorporate prior information via a hierarchical model (hJAM). In this framework, the use of appropriate estimates as prior information yields an analysis similar to Mendelian randomization (MR) and TWAS approaches. hJAM is applicable to multiple correlated SNPs and intermediates to yield conditional estimates for the intermediates on the outcome, thus providing advantages over alternative approaches. We investigated the performance of hJAM in comparison with existing MR and TWAS approaches and demonstrated that hJAM yields an unbiased estimate, maintains correct type-I error, and has increased power across extensive simulations. We applied hJAM to 2 examples: estimating the causal effects of body mass index (GIANT Consortium) and type 2 diabetes (DIAGRAM data set, GERA Cohort, and UK Biobank) on myocardial infarction (UK Biobank) and estimating the causal effects of the expressions of the genes for nuclear casein kinase and cyclin dependent kinase substrate 1 and peptidase M20 domain containing 1 on the risk of prostate cancer (PRACTICAL and GTEx).
Subject(s)
Data Interpretation, Statistical , Gene Expression Profiling/methods , Mendelian Randomization Analysis/methods , Models, Genetic , Amidohydrolases/analysis , Bias , Body Mass Index , Diabetes Mellitus, Type 2/genetics , Female , Genome-Wide Association Study , Humans , Male , Myocardial Infarction/genetics , Nuclear Proteins/analysis , Phosphoproteins/analysis , Polymorphism, Single Nucleotide , Prostatic Neoplasms/geneticsABSTRACT
BACKGROUND & AIMS: Early-onset colorectal cancer (CRC, in persons younger than 50 years old) is increasing in incidence; yet, in the absence of a family history of CRC, this population lacks harmonized recommendations for prevention. We aimed to determine whether a polygenic risk score (PRS) developed from 95 CRC-associated common genetic risk variants was associated with risk for early-onset CRC. METHODS: We studied risk for CRC associated with a weighted PRS in 12,197 participants younger than 50 years old vs 95,865 participants 50 years or older. PRS was calculated based on single nucleotide polymorphisms associated with CRC in a large-scale genome-wide association study as of January 2019. Participants were pooled from 3 large consortia that provided clinical and genotyping data: the Colon Cancer Family Registry, the Colorectal Transdisciplinary Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium and were all of genetically defined European descent. Findings were replicated in an independent cohort of 72,573 participants. RESULTS: Overall associations with CRC per standard deviation of PRS were significant for early-onset cancer, and were stronger compared with late-onset cancer (P for interaction = .01); when we compared the highest PRS quartile with the lowest, risk increased 3.7-fold for early-onset CRC (95% CI 3.28-4.24) vs 2.9-fold for late-onset CRC (95% CI 2.80-3.04). This association was strongest for participants without a first-degree family history of CRC (P for interaction = 5.61 × 10-5). When we compared the highest with the lowest quartiles in this group, risk increased 4.3-fold for early-onset CRC (95% CI 3.61-5.01) vs 2.9-fold for late-onset CRC (95% CI 2.70-3.00). Sensitivity analyses were consistent with these findings. CONCLUSIONS: In an analysis of associations with CRC per standard deviation of PRS, we found the cumulative burden of CRC-associated common genetic variants to associate with early-onset cancer, and to be more strongly associated with early-onset than late-onset cancer, particularly in the absence of CRC family history. Analyses of PRS, along with environmental and lifestyle risk factors, might identify younger individuals who would benefit from preventive measures.
Subject(s)
Colorectal Neoplasms/genetics , Genetic Predisposition to Disease , Age of Onset , Case-Control Studies , Cohort Studies , DNA Mutational Analysis , Datasets as Topic , Female , Genome-Wide Association Study , Genotyping Techniques , Humans , Life Style , Male , Medical History Taking , Middle Aged , Mutation Rate , Polymorphism, Single Nucleotide , Risk Factors , Whole Genome SequencingABSTRACT
MOTIVATION: Epidemiologic, clinical and translational studies are increasingly generating multiplatform omics data. Methods that can integrate across multiple high-dimensional data types while accounting for differential patterns are critical for uncovering novel associations and underlying relevant subgroups. RESULTS: We propose an integrative model to estimate latent unknown clusters (LUCID) aiming to both distinguish unique genomic, exposure and informative biomarkers/omic effects while jointly estimating subgroups relevant to the outcome of interest. Simulation studies indicate that we can obtain consistent estimates reflective of the true simulated values, accurately estimate subgroups and recapitulate subgroup-specific effects. We also demonstrate the use of the integrated model for future prediction of risk subgroups and phenotypes. We apply this approach to two real data applications to highlight the integration of genomic, exposure and metabolomic data. AVAILABILITY AND IMPLEMENTATION: The LUCID method is implemented through the LUCIDus R package available on CRAN (https://CRAN.R-project.org/package=LUCIDus). SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.