Chaco Canyon Dig Unearths Ethical Concerns

The field of paleogenomics (the study of ancient genomes) is rapidly advancing with more robust methods of isolating ancient DNA and increasing access to next-generation DNA sequencing technology. As these studies progress, many important ethical issues have emerged that should be considered when ancient Native American remains, whom we refer to as ancestors, are used in research. We highlight a recent article by Kennett et al. (2017), “Archaeogenomic evidence reveals prehistoric matrilineal dynasty,” that brings several ethical issues to light that should be addressed in paleogenomics research (Kennett et al. 2017). The study helps elucidate the matrilineal relationships in ancient Chacoan society through ancient DNA analysis. However, we, as Indigenous researchers and allies, raise ethical concerns with the study’s scientific conclusions that can be problematic for Native American communities: (1) the lack of tribal consultation, (2) the use of culturally-insensitive descriptions, and (3) the potential impact on marginalized groups. Further, we explore the limitations of the Native American Graves Protection and Repatriation Act (NAGPRA), which addresses repatriation but not research, as clear ethical guidelines have not been established for research involving Native American ancestors, especially those deemed “culturally unaffiliated”. As multiple studies of culturally unaffiliated remains have been initiated recently, it is imperative that researchers consider the ethical ramifications of paleogenomics research. Past research indiscretions have created a history of mistrust and exploitation in many Native American communities. To promote ethical engagement of Native American communities in research, we therefore suggest careful attention to the ethical considerations, strong tribal consultation requirements, and greater collaborations amongst museums, federal agencies, researchers, scientific journals, and granting agencies

Indigenous Peoples and research: self-determination in research governance

Indigenous Peoples are reimagining their relationship with research and researchers through greater self-determination and involvement in research governance. The emerging discourse around Indigenous Data Sovereignty has provoked discussions about decolonizing data practices and highlighted the importance of Indigenous Data Governance to support Indigenous decision-making and control of data. Given that much data are generated from research, Indigenous research governance and Indigenous Data Governance overlap. In this paper, we broaden the concept of Indigenous Data Sovereignty by using the CARE Principles for Indigenous Data Governance to discuss how research legislation and policy adopted by Indigenous Peoples in the US set expectations around recognizing sovereign relationships, acknowledging rights and interests in data, and enabling Indigenous Peoples' participation in research governance

Recent shifts in the genomic ancestry of Mexican Americans may alter the genetic architecture of biomedical traits

People in the Americas represent a diverse continuum of populations with varying degrees of admixture among African, European, and Amerindigenous ancestries. In the United States, populations with non-European ancestry remain understudied, and thus little is known about the genetic architecture of phenotypic variation in these populations. Using genotype data from the Hispanic Community Health Study/Study of Latinos, we find that Amerindigenous ancestry increased by an average of ~20% spanning 1940s-1990s in Mexican Americans. These patterns result from complex interactions between several population and cultural factors which shaped patterns of genetic variation and influenced the genetic architecture of complex traits in Mexican Americans. We show for height how polygenic risk scores based on summary statistics from a European-based genome-wide association study perform poorly in Mexican Americans. Our findings reveal temporal changes in population structure within Hispanics/Latinos that may influence biomedical traits, demonstrating a need to improve our understanding of admixed populations

Different Risk for Hypertension, Diabetes, Dyslipidemia, and Hyperuricemia According to Level of Body Mass Index in Japanese and American Subjects

Obesity is a risk factor for hypertension, diabetes mellitus (DM), dyslipidemia, and hyperuricemia. Here, we evaluated whether the same body mass index (BMI) for the U.S. population conferred similar metabolic risk in Japan. This was a cross-sectional analysis involving 90,047 Japanese adults (18–85 years) from St. Luke’s International Hospital, Tokyo, Japan and 14,734 adults from National Health and Nutrition Examination Survey (NHANES) collected in the U.S. We compared the prevalence of hypertension, DM, dyslipidemia, and hyperuricemia according to BMI in Japan and the U.S. The prevalence of hypertension, DM, and dyslipidemia were significantly higher in the U.S. than Japan, whereas the prevalence of hyperuricemia did not differ between countries. Higher BMI was an independent risk factor for hypertension, DM, dyslipidemia, and hyperuricemia both in Japan and in the U.S. after adjusting for age, sex, smoking and drinking habits, chronic kidney disease, and other cardiovascular risk factors. The BMI cut-off above which the prevalence of these cardio-metabolic risk factors increased was significantly higher in the U.S. than in Japan (27 vs. 23 kg/m2 for hypertension, 29 vs. 23 kg/m2 for DM, 26 vs. 22 kg/m2 for dyslipidemia, and 27 vs. 23 kg/m2 for hyperuricemia). Higher BMI is associated with an increased prevalence of hypertension, DM, dyslipidemia, and hyperuricemia both in Japan and U.S. The BMI cut-off above which the prevalence of cardio-metabolic risk factors increases is significantly lower in Japan than the U.S., suggesting that the same definition of overweight/obesity may not be similarly applicable in both countries

Locus-Specific Differential DNA Methylation and Urinary Arsenic: An Epigenome-Wide Association Study in Blood among Adults with Low-to-Moderate Arsenic Exposure.

BackgroundChronic exposure to arsenic (As), a human toxicant and carcinogen, remains a global public health problem. Health risks persist after As exposure has ended, suggesting epigenetic dysregulation as a mechanistic link between exposure and health outcomes.ObjectivesWe investigated the association between total urinary As and locus-specific DNA methylation in the Strong Heart Study, a cohort of American Indian adults with low-to-moderate As exposure [total urinary As, mean (±SD) μg/g creatinine: 11.7 (10.6)].MethodsDNA methylation was measured in 2,325 participants using the Illumina MethylationEPIC array. We implemented linear models to test differentially methylated positions (DMPs) and the DMRcate method to identify regions (DMRs) and conducted gene ontology enrichment analysis. Models were adjusted for estimated cell type proportions, age, sex, body mass index, smoking, education, estimated glomerular filtration rate, and study center. Arsenic was measured in urine as the sum of inorganic and methylated species.ResultsIn adjusted models, methylation at 20 CpGs was associated with urinary As after false discovery rate (FDR) correction (FDR< 0.05). After Bonferroni correction, 5 CpGs remained associated with total urinary As (pBonferroni<0.05), located in SLC7A11, ANKS3, LINGO3, CSNK1D, ADAMTSL4. We identified one DMR on chromosome 11 (chr11:2,322,050-2,323,247), annotated to C11orf2; TSPAN32 genes.DiscussionThis is one of the first epigenome-wide association studies to investigate As exposure and locus-specific DNA methylation using the Illumina MethylationEPIC array and the largest epigenome-wide study of As exposure. The top DMP was located in SLC7A11A, a gene involved in cystine/glutamate transport and the biosynthesis of glutathione, an antioxidant that may protect against As-induced oxidative stress. Additional DMPs were located in genes associated with tumor development and glucose metabolism. Further research is needed, including research in more diverse populations, to investigate whether As-related DNA methylation signatures are associated with gene expression or may serve as biomarkers of disease development. https://doi.org/10.1289/EHP6263

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/EHP25