Exploring Clinical Risk Factors for Breast Cancer among American Indian Women

Objective: Very little is known about the breast cancer risk profile among American Indian women. Previous research shows that the proportion of American Indian/Alaska Native women with baseline characteristics (commonly known breast cancer risk factors) differs from other ethnicities. This retrospective case control study was designed to the explore the association of these factors among American Indian women with and without breast cancer. Methods: Cases and controls were retrospectively selected from the medical records of American Indian women who obtained their health care from Quentin N. Burdick Memorial Health Care Facility (IHS) in Belcourt, ND. For each woman with breast cancer (n=141), two controls were selected when possible (n=278). Risk factors examined included woman’s age, age at first live birth, age of menarche, the number of previous benign breast biopsies, the total number of first-degree relatives with breast cancer, body mass index and parity. Odds ratios and 95% confidence intervals were calculated using logistic regression. Results: Many of the associations found among American Indian women who obtained their health care from Quentin N. Burdick Memorial Health Care Facility (IHS) in Belcourt, ND, between risk factors commonly identified in other populations and breast cancer were weakly positive. Nulliparity was the only risk factor to consistently show a positive significant association (OR = 2.87, 95% CI 1.16-.7.12). Conclusion: Disparities in breast cancer incidence, mortality and screening among Northern Plains American Indian emphasize the need to better understand the risk factors associated with breast cancer in this population. Based on the results of this study, the value of current risk prediction models in American Indian communities is uncertain and clinicians should be cautious in using these models to inform American Indian patients of their risk for breast cancer

Fine mapping and identification of serum urate loci in American Indians: The Strong Heart Family Study

While studies have reported genetic loci affecting serum urate (SU) concentrations, few studies have been conducted in minority populations. Our objective for this study was to identify genetic loci regulating SU in a multigenerational family-based cohort of American Indians, the Strong Heart Family Study (SHFS). We genotyped 162,718 single nucleotide polymorphisms (SNPs) in 2000 SHFS participants using an Illumina MetaboChip array. A genome-wide association analysis of SU was conducted using measured genotype analysis approach accounting for kinships in SOLAR, and meta-analysis in METAL. Our results showed strong association of SU with rs4481233, rs9998811, rs7696092 and rs13145758 (minor allele frequency (MAF) = 25–44%; P \u3c 3 × 10−14) of solute carrier family 2, member 9 (SLC2A9) and rs41481455, rs2231142 and rs1481012 (MAF = 29%; p \u3c 3 × 10−9) of ATP-binding cassette protein, subfamily G, member 2 (ABCG2). Carriers of G alleles of rs9998811, rs4148155 and rs1481012 and A alleles of rs4481233, rs7696092 and rs13145758 and rs2231142 had lower SU concentrations as compared to non-carriers. Genetic analysis of SU conditional on significant SLC2A9 and ABCG2 SNPs revealed new loci, nucleobindin 1 (NUCB1) and neuronal PAS domain protein 4 (NPAS4) (p \u3c6× 10−6). To identify American Indian-specific SNPs, we conducted targeted sequencing of key regions of SLC2A9. A total of 233 SNPs were identified of which 89 were strongly associated with SU (p \u3c 7.1 × 10−10) and 117 were American Indian specific. Analysis of key SNPs in cohorts of Mexican-mestizos, European, Indian and East Asian ancestries showed replication of common SNPs, including our lead SNPs. Our results demonstrate the association of SU with uric acid transporters in a minority population of American Indians and potential novel associations of SU with neuronal-related genes which warrant further investigation

IBC CARe Microarray Allelic Population Prevalences in an American Indian Population

Background: The prevalence of variant alleles among single nucleotide polymorphisms (SNPs) is not well known for many minority populations. These population allele frequencies (PAFs) are necessary to guide genetic epidemiology studies and to understand the population specific contribution of these variants to disease risk. Large differences in PAF among certain functional groups of genes could also indicate possible selection pressure or founder effects of interest. The 50K SNP, custom genotyping microarray (CARe) was developed, focusing on about 2,000 candidate genes and pathways with demonstrated pathophysiologic influence on cardiovascular disease (CVD). Methods: The CARe microarray was used to genotype 216 unaffected controls in a study of pre-eclampsia among a Northern Plains, American Indian tribe. The allelic prevalences of 34,240 SNPs suitable for analysis, were determined and compared with corresponding HapMap prevalences for the Caucasian population. Further analysis was conducted to compare the frequency of statistically different prevalences among functionally related SNPs, as determined by the DAVID Bioinformatics Resource. Results: Of the SNPs with PAFs in both datasets, 9.8%,37.2% and 47.1% showed allele frequencies among the American Indian population greater than, less than and either greater or less than (respectively) the HapMap Caucasian population. The 2,547 genes were divided into 53 functional groups using the highest stringency criteria. While none of these groups reached the Bonferroni corrected p value of 0.00094, there were 7 of these 53 groups with significantly more or less differing PAFs, each with a probability of less than 0.05 and an overall probability of 0.0046. Conclusion: In comparison to the HapMap Caucasian population, there are substantial differences in the prevalence among an American Indian community of SNPs related to CVD. Certain functional groups of genes and related SNPs show possible evidence of selection pressure or founder effects

Markers of Inflammation, Metabolic Risk Factors, and Incident Heart Failure in American Indians: The Strong Heart Study

Inflammation may play a role in increased risk of heart failure (HF) that is associated with obesity, metabolic syndrome (MS), and diabetes. This study investigated associations between inflammatory markers, MS, and incident HF in a population with high prevalence of diabetes, obesity, and MS. The cohort consisted of 3098 American Indians, without prevalent cardiovascular disease who had C-reactive protein (CRP) and fibrinogen measured at the SHS Phase II exam. Independent associations between inflammatory markers, MS, and HF were analyzed by Cox hazard models. During mean follow-up of 11 years, 218 participants developed HF. After the adjustment for cardiovascular risk factors, fibrinogen, (HR 1.36, 95% C.I.:1.15–1.59) but not CRP, (HR 1.25, 95% C.I.:0.97–1.32) remained significant HF predictor. In individuals without diabetes, concomitant presence of MS and elevated CRP or fibrinogen increased HF risk (for MS and CRP: HR 2.02, 95% C.I.: 0.95–4.31; for CRP and fibrinogen: HR 1.75, 95% C.I.:0.83–3.72). In a population with high prevalence of obesity, MS, and diabetes, elevated CRP and fibrinogen predict increased HF risk. These associations are attenuated by the adjustments for conventional risk factors suggesting that inflammation acts in concert with metabolic and clinical risk factors in increasing HF risk

Two Variants of the C-Reactive Protein Gene Are Associated with Risk of Pre-Eclampsia in an American Indian Population

Background: The etiology of pre-eclampsia (PE) is unknown; but it is accepted that normal pregnancy represents a distinctive challenge to the maternal immune system. C-reactive protein is a prominent component of the innate immune system; and we previously reported an association between PE and the CRP polymorphism, rs1205. Our aim was to explore the effects of additional CRP variants. The IBC (Cardiochip) genotyping microarray focuses on candidate genes and pathways related to the pathophysiology of cardiovascular disease. Methods: This study recruited 140 cases of PE and 270 matched controls, of which 95 cases met criteria as severe PE, from an American Indian community. IBC array genotypes from 10 suitable CRP SNPs were analyzed. A replication sample of 178 cases and 427 controls of European ancestry was also genotyped. Results: A nominally significant difference (p value <0.05) was seen in the distribution of discordant matched pairs for rs3093068; and Bonferroni corrected differences (P<0.005) were seen for rs876538, rs2794521, and rs3091244. Univariate conditional logistic regression odds ratios (OR) were nominally significant for rs3093068 and rs876538 models only. Multivariate logistic models with adjustment for mother's age, nulliparity and BMI attenuated the effect (OR 1.58, P = 0.066, 95% CI 0.97–2.58) for rs876538 and (OR 2.59, P = 0.050, 95% CI 1.00–6.68) for rs3093068. An additive risk score of the above two risk genotypes shows a multivariate adjusted OR of 2.04 (P = 0.013, 95% CI 1.16–3.56). The replication sample also demonstrated significant association between PE and the rs876538 allele (OR = 1.55, P = 0.01, 95% CI 2.16–1.10). We also show putative functionality for the rs876538 and rs3093068 CRP variants. Conclusion: The CRP variants, rs876538 and rs3093068, previously associated with other cardiovascular disease phenotypes, show suggestive association with PE in this American Indian population, further supporting a possible role for CRP in PE

Association of protein function-altering variants with cardiometabolic traits:the strong heart study

Clinical and biomarker phenotypic associations for carriers of protein function-altering variants may help to elucidate gene function and health effects in populations. We genotyped 1127 Strong Heart Family Study participants for protein function-altering single nucleotide variants (SNV) and indels selected from a low coverage whole exome sequencing of American Indians. We tested the association of each SNV/indel with 35 cardiometabolic traits. Among 1206 variants (average minor allele count = 20, range of 1 to 1064), similar to 43% were not present in publicly available repositories. We identified seven SNV-trait significant associations including a missense SNV at ABCA10 (rs779392624, p= 8 x 10(-9)) associated with fasting triglycerides, which gene product is involved in macrophage lipid homeostasis. Among non-diabetic individuals, missense SNVs at four genes were associated with fasting insulin adjusted for BMI (PHIL, chr6:79,650,711, p= 2.1 x 10(-6); TRPM3, rs760461668, p= 5 x10(-8); SPTY2D1, rs756851199, p= 1.6 x 10(-8); and TSPO, rs566547284, p= 2.4 x 10(-6)). PHIL encoded protein is involved in pancreatic beta-cell proliferation and survival, and TRPM3 protein mediates calcium signaling in pancreatic beta-cells in response to glucose. A genetic risk score combining increasing insulin risk alleles of these four genes was associated with 53% (95% confidence interval 1.09, 2.15) increased odds of incident diabetes and 83% (95% confidence interval 1.35, 2.48) increased odds of impaired fasting glucose at follow-up. Our study uncovered novel gene-trait associations through the study of protein-coding variants and demonstrates the advantages of association screenings targeting diverse and high-risk populations to study variants absent in publicly available repositories

Diabetes-specific genetic effects on obesity traits in American Indian populations: the Strong Heart Family Study

<p>Abstract</p> <p>Background</p> <p>Body fat mass distribution and deposition are determined by multiple environmental and genetic factors. Obesity is associated with insulin resistance, hyperinsulinemia, and type 2 diabetes. We previously identified evidence for genotype-by-diabetes interaction on obesity traits in Strong Heart Family Study (SHFS) participants. To localize these genetic effects, we conducted genome-wide linkage scans of obesity traits in individuals with and without type 2 diabetes, and in the combined sample while modeling interaction with diabetes using maximum likelihood methods (SOLAR 2.1.4).</p> <p>Methods</p> <p>SHFS recruited American Indians from Arizona, North and South Dakota, and Oklahoma. Anthropometric measures and diabetes status were obtained during a clinic visit. Marker allele frequencies were derived using maximum likelihood methods estimated from all individuals and multipoint identity by descent sharing was estimated using Loki. We used variance component linkage analysis to localize quantitative trait loci (QTLs) influencing obesity traits. We tested for evidence of additive and QTL-specific genotype-by-diabetes interactions using the regions identified in the diabetes-stratified analyses.</p> <p>Results</p> <p>Among 245 diabetic and 704 non-diabetic American Indian individuals, we detected significant additive gene-by-diabetes interaction for weight and BMI (<it>P </it>< 0.02). In analysis accounting for QTL-specific interaction (<it>P </it>< 0.001), we detected a QTL for weight on chromosome 1 at 242 cM (LOD = 3.7). This chromosome region harbors the adiponectin receptor 1 gene, which has been previously associated with obesity.</p> <p>Conclusion</p> <p>These results suggest distinct genetic effects on body mass in individuals with diabetes compared to those without diabetes, and a possible role for one or more genes on chromosome 1 in the pathogenesis of obesity.</p

Dietary determinants of cadmium exposure in the Strong Heart Family Study

Urinary cadmium (Cd) concentrations in the Strong Heart Family Study (SHFS) participants are higher than in the general US population. This difference is unlikely to be related to tobacco smoking. We evaluated the association of consumption of processed meats and other dietary products with urinary Cd concentrations in the SHFS, a family-based study conducted in American Indian communities. We included 1725 participants with urine Cd concentrations (standardized to urine creatinine) and food frequency questionnaire data grouped in 24 categories, including processed meat. Median (IQR) urinary Cd concentrations were 0.42 (0.20–0.85) μg/g creatinine. The age, sex, smoking, education, center, body mass index, and total kcal adjusted geometric mean ratio (GMR) (95%CI) of urinary cadmium concentrations per IQR increase in each dietary category was 1.16 (1.04–1.29) for processed meat, 1.10 (1.00–1.21) for fries and chips, 0.87 (0.80–0.95) for dairy products, and 0.89 (0.82–0.97) for fruit juices. The results remained similar after further adjustment for the dietary categories associated with urinary Cd in the previous model except for fries and chips, which was no longer statistically significant. These findings revealed the potential importance of processed meat products as a dietary source of cadmium

Association of Cardiometabolic Genes with Arsenic Metabolism Biomarkers in American Indian Communities: The Strong Heart Family Study (SHFS)

BACKGROUND: Metabolism of inorganic arsenic (iAs) is subject to inter-individual variability, which is explained partly by genetic determinants. OBJECTIVES: We investigated the association of genetic variants with arsenic species and principal components of arsenic species in the Strong Heart Family Study (SHFS). METHODS: We examined variants previously associated with cardiometabolic traits (~ 200,000 from Illumina Cardio MetaboChip) or arsenic metabolism and toxicity (670) among 2,428 American Indian participants in the SHFS. Urine arsenic species were measured by high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS), and percent arsenic species [iAs, monomethylarsonate (MMA), and dimethylarsinate (DMA), divided by their sum × 100] were logit transformed. We created two orthogonal principal components that summarized iAs, MMA, and DMA and were also phenotypes for genetic analyses. Linear regression was performed for each phenotype, dependent on allele dosage of the variant. Models accounted for familial relatedness and were adjusted for age, sex, total arsenic levels, and population stratification. Single nucleotide polymorphism (SNP) associations were stratified by study site and were meta-analyzed. Bonferroni correction was used to account for multiple testing. RESULTS: Variants at 10q24 were statistically significant for all percent arsenic species and principal components of arsenic species. The index SNP for iAs%, MMA%, and DMA% (rs12768205) and for the principal components (rs3740394, rs3740393) were located near AS3MT, whose gene product catalyzes methylation of iAs to MMA and DMA. Among the candidate arsenic variant associations, functional SNPs in AS3MT and 10q24 were most significant (p < 9.33 × 10-5). CONCLUSIONS: This hypothesis-driven association study supports the role of common variants in arsenic metabolism, particularly AS3MT and 10q24. Citation: Balakrishnan P, Vaidya D, Franceschini N, Voruganti VS, Gribble MO, Haack K, Laston S, Umans JG, Francesconi KA, Goessler W, North KE, Lee E, Yracheta J, Best LG, MacCluer JW, Kent J Jr., Cole SA, Navas-Acien A. 2017. Association of cardiometabolic genes with arsenic metabolism biomarkers in American Indian communities: the Strong Heart Family Study (SHFS). Environ Health Perspect 125:15-22; http://dx.doi.org/10.1289/EHP251

Metabolic Profiles of Obesity in American Indians: The Strong Heart Family Study

The authors would like to thank the Strong Heart Study participants, Indian Health Service facilities, and participating tribal communities for their extraordinary cooperation and involvement, which has contributed to the success of the Strong Heart Study. The views expressed in this article are those of the authors and do not necessarily reflect those of the Indian Health Service.Obesity is a typical metabolic disorder resulting from the imbalance between energy intake and expenditure. American Indians suffer disproportionately high rates of obesity and diabetes. The goal of this study is to identify metabolic profiles of obesity in 431 normoglycemic American Indians participating in the Strong Heart Family Study. Using an untargeted liquid chromatography–mass spectrometry, we detected 1,364 distinct m/z features matched to known compounds in the current metabolomics databases. We conducted multivariate analysis to identify metabolic profiles for obesity, adjusting for standard obesity indicators. After adjusting for covariates and multiple testing, five metabolites were associated with body mass index and seven were associated with waist circumference. Of them, three were associated with both. Majority of the obesity-related metabolites belongs to lipids, e.g., fatty amides, sphingolipids, prenol lipids, and steroid derivatives. Other identified metabolites are amino acids or peptides. Of the nine identified metabolites, five metabolites (oleoylethanolamide, mannosyl-diinositol-phosphorylceramide, pristanic acid, glutamate, and kynurenine) have been previously implicated in obesity or its related pathways. Future studies are warranted to replicate these findings in larger populations or other ethnic groups.Yeshttp://www.plosone.org/static/editorial#pee