A genomewide single-nucleotide-polymorphism panel for Mexican American admixture mapping

Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations

The knowledge of ancestral origin is monumental in conservation of endangered animals since it can aid in preservation of population level genetic integrity and prevent inbreeding among related individuals. Despite maintenance of studbook, the biogeographical affiliation of most captive gorillas is largely unknown, which has constrained management of captive gorillas aiming at maximizing genetic diversity at the population level. In recent years, ancestry informative markers (AIMs) has been successfully employed for the inference of genomic ancestry in a wide range of studies in evolutionary genetics, biomedical research, genetic stock identification, and introgression analysis and forensic analyses. In this study, we sought to derive the AIMs yielding the most cohesive and faithful understanding of biogeographical affiliation of query gorillas. To this end, we compared three commonly used AIMs-determining methods namely, Infocalc, F ST , and Smart Principal Component Analysis (SmartPCA) with ADMIXTURE, using gorilla genome data available through Great Ape Genome Project database. Our findings suggest that the SNPs that were detected by at least three of the four AIMs-determining approaches (N = 1,531), is likely most suitable for delineation of gorilla AIMs. It recapitulated the finer structure within western lowland gorilla genomes with high degree of precision. We further have validated the robustness of our results using a randomized negative control containing the same number of SNPs. To the best of our knowledge, this is the first report of an AIMs panel for gorillas that may aid in developing cost-effective resources for large-scale demographic analyses, and greatly help in conservation of this charismatic mega-fauna.

MultiWaver 2.0: modeling discrete and continuous gene flow to reconstruct complex population admixtures

Our goal in developing the MultiWaver software series was to be able to infer population admixture history under various complex scenarios. The earlier version of MultiWaver considered only discrete admixture models. Here, we report a newly developed version, MultiWaver 2.0, that implements a more flexible framework and is capable of inferring multiple-wave admixture histories under both discrete and continuous admixture models. MultiWaver 2.0 can automatically select an optimal admixture model based on the length distribution of ancestral tracks of chromosomes, and the program can estimate the corresponding parameters under the selected model. Specifically, for discrete admixture models, we used a likelihood ratio test (LRT) to determine the optimal discrete model and an expectation-maximization algorithm to estimate the parameters. In addition, according to the principles of the Bayesian Information Criterion (BIC), we compared the optimal discrete model with several continuous admixture models. In MultiWaver 2.0, we also applied a bootstrapping technique to provide levels of support for the chosen model and the confidence interval (CI) of the estimations of admixture time. Simulation studies validated the reliability and effectiveness of our method. Finally, the program performed well when applied to real datasets of typical admixed populations, such as African Americans, Uyghurs, and Hazaras.

Ancient Ancestry Informative Markers for Identifying Fine-Scale Ancient Population Structure in Eurasians

The rapid accumulation of ancient human genomes from various areas and time periods potentially enables the expansion of studies of biodiversity, biogeography, forensics, population history, and epidemiology into past populations. However, most ancient DNA (aDNA) data were generated through microarrays designed for modern-day populations, which are known to misrepresent the population structure. Past studies addressed these problems by using ancestry informative markers (AIMs). It is, thereby, unclear whether AIMs derived from contemporary human genomes can capture ancient population structures, and whether AIM-finding methods are applicable to aDNA, provided that the high missingness rates in ancient-and oftentimes haploid-DNA can also distort the population structure. Here, we define ancient AIMs (aAIMs) and develop a framework to evaluate established and novel AIM-finding methods in identifying the most informative markers. We show that aAIMs identified by a novel principal component analysis (PCA)-based method outperform all of the competing methods in classifying ancient individuals into populations and identifying admixed individuals. In some cases, predictions made using the aAIMs were more accurate than those made with a complete marker set. We discuss the features of the ancient Eurasian population structure and strategies to identify aAIMs. This work informs the design of single nucleotide polymorphism (SNP) microarrays and the interpretation of aDNA results, which enables a population-wide testing of primordialist theories.

Human ancestry indentification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

BACKGROUND

While continental level ancestry is relatively simple using genomic information, distinguishing between individuals from closely associated sub-populations (e.g., from the same continent) is still a difficult challenge.

METHODS

We study the problem of predicting human biogeographical ancestry from genomic data under resource constraints. In particular, we focus on the case where the analysis is constrained to using single nucleotide polymorphisms (SNPs) from just one chromosome. We propose methods to construct such ancestry informative SNP panels using correlation-based and outlier-based methods.

RESULTS

We accessed the performance of the proposed SNP panels derived from just one chromosome, using data from the 1000 Genome Project, Phase 3. For continental-level ancestry classification, we achieved an overall classification rate of 96.75% using 206 single nucleotide polymorphisms (SNPs). For sub-population level ancestry prediction, we achieved an average pairwise binary classification rates as follows: subpopulations in Europe: 76.6% (58 SNPs); Africa: 87.02% (87 SNPs); East Asia: 73.30% (68 SNPs); South Asia: 81.14% (75 SNPs); America: 85.85% (68 SNPs).

CONCLUSION

Our results demonstrate that one single chromosome (in particular, Chromosome 1), if carefully analyzed, could hold enough information for accurate prediction of human biogeographical ancestry. This has significant implications in terms of the computational resources required for analysis of ancestry, and in the applications of such analyses, such as in studies of genetic diseases, forensics, and soft biometrics.

An Ancestry Informative Marker Set Which Recapitulates the Known Fine Structure of Populations in South Asia

The inference of genomic ancestry using ancestry informative markers (AIMs) can be useful for a range of studies in evolutionary genetics, biomedical research, and forensic analyses. However, the determination of AIMs for highly admixed populations with complex ancestries has remained a formidable challenge. Given the immense genetic heterogeneity and unique population structure of the Indian subcontinent, here we sought to derive AIMs that would yield a cohesive and faithful understanding of South Asian genetic origins. To discern the most optimal strategy for extracting AIMs for South Asians we compared three commonly used AIMs-determining methods namely, Infocalc, FST, and Smart Principal Component Analysis with ADMIXTURE, using previously published whole genome data from the Indian subcontinent. Our findings suggest that the Infocalc approach is likely most suitable for delineation of South Asian AIMs. In particular, Infocalc-2,000 (N = 2,000) appeared as the most informative South Asian AIMs panel that recapitulated the finer structure within South Asian genomes with high degree of sensitivity and precision, whereas a negative control with an equivalent number of randomly selected markers when used to interrogate the South Asian populations, failed to do so. We discuss the utility of all approaches under evaluation for AIMs derivation and interpreting South Asian genomic ancestries. Notably, this is the first report of an AIMs panel for South Asian ancestry inference. Overall these findings may aid in developing cost-effective resources for large-scale demographic analyses and foster expansion of our knowledge of human origins and disease, in the South Asian context.

Polygenic risk, family cohesion, and adolescent aggression in Mexican American and European American families: Developmental pathways to alcohol use

Poor family cohesion and elevated adolescent aggression are associated with greater alcohol use in adolescence and early adulthood. In addition, evocative gene-environment correlations (rGEs) can underlie the interplay between offspring characteristics and negative family functioning, contributing to substance use. Gene-environment interplay has rarely been examined in racial/ethnic minority populations. The current study examined adolescents' polygenic risk scores for aggression in evocative rGEs underlying aggression and family cohesion during adolescence, their contributions to alcohol use in early adulthood (n = 479), and differences between Mexican American and European American subsamples. Results suggest an evocative rGE between polygenic risk scores, aggression, and low family cohesion, with aggression contributing to low family cohesion over time. Greater family cohesion was associated with lower levels of alcohol use in early adulthood and this association was stronger for Mexican American adolescents compared to European American adolescents. Results are discussed with respect to integration of culture and racial/ethnic minority samples into genetic research and implications for alcohol use.

Identity-by-Descent Mapping Identifies Major Locus for Serum Triglycerides in Amerindians Largely Explained by an APOC3 Founder Mutation

BACKGROUND

Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment the inherent genetic information that can be used for localization.

METHODS AND RESULTS

Through identity-by-descent mapping, using ≈400 000 single-nucleotide polymorphisms (SNPs), of serum lipid profiles, we identified a major linkage signal for triglycerides in 1007 Pima Indians (LOD=9.23; P=3.5×10^-11 on chromosome 11q). In subsequent fine-mapping and replication association studies in ≈7500 Amerindians, we determined that this signal reflects effects of a loss-of-function Ala43Thr substitution in APOC3 (rs147210663) and 3 established functional SNPs in APOA5. The association with rs147210663 was particularly strong; each copy of the Thr allele conferred 42% lower triglycerides (β=-0.92±0.059 SD unit; P=9.6×10^-55 in 4668 Pimas and 2793 Southwest Amerindians combined). The Thr allele is extremely rare in most global populations but has a frequency of 2.5% in Pimas. We further demonstrated that 3 APOA5 SNPs with established functional impact could explain the association with the most well-replicated SNP (rs964184) for triglycerides identified by genome-wide association studies. Collectively, these 4 SNPs account for 6.9% of variation in triglycerides in Pimas (and 4.1% in Southwest Amerindians), and their inclusion in the original linkage model reduced the linkage signal to virtually null.

CONCLUSIONS

APOC3/APOA5 constitutes a major locus for serum triglycerides in Amerindians, especially the Pimas, and these results provide an empirical example for the concept that population-based linkage analysis is a useful strategy to identify complex trait variants.

Inference of multiple-wave admixtures by length distribution of ancestral tracks

The ancestral tracks in admixed genomes are valuable for population history inference. While a few methods have been developed to infer admixture history based on ancestral tracks, these methods suffer the same flaw: only population admixture history under some specific models can be inferred. In addition, the inference of history might be biased or even unreliable if the specific model deviates from the real situation. To address this problem, we firstly proposed a general discrete admixture model to describe the admixture history with multiple ancestral populations and multiple-wave admixtures. We next deduced the length distribution of ancestral tracks under the general discrete admixture model. We further developed a new method, MultiWaver, to explore multiple-wave admixture histories. Our method could automatically determine an optimal admixture model based on the length distribution of ancestral tracks, and estimate the corresponding parameters under this optimal model. Specifically, we used a likelihood ratio test (LRT) to determine the number of admixture waves, and implemented an expectation-maximization (EM) algorithm to estimate parameters. We used simulation studies to validate the reliability and effectiveness of our method. Finally, good performance was observed when our method was applied to real data sets of African Americans and Mexicans, and new insights were gained into the admixture history of Uyghurs and Hazaras.

Analysis of type 2 diabetes and obesity genetic variants in Mexican Pima Indians: Marked allelic differentiation among Amerindians at HLA

Prevalence of diabetes and obesity in Mexican Pima Indians is low, while prevalence in US Pima Indians is high. Although lifestyle likely accounts for much of the difference, the role of genetic factors is not well explored. To examine this, we genotyped 359 single nucleotide polymorphisms, including established type 2 diabetes and obesity variants from genome-wide association studies (GWAS) and 96 random markers, in 342 Mexican Pimas. A multimarker risk score of obesity variants was associated with body mass index (BMI; β = 0.81 kg/m² per SD, P = 0.0066). The mean value of the score was lower in Mexican Pimas than in US Pimas (P = 4.3 × 10^-11 ), and differences in allele frequencies at established loci could account for approximately 7% of the population difference in BMI; however, the difference in risk scores was consistent with evolutionary neutrality given genetic distance. To identify loci potentially under recent natural selection, allele frequencies at 283 variants were compared between US and Mexican Pimas, accounting for genetic distance. The largest differences were seen at HLA markers (e.g., rs9271720, difference = 0.75, P = 8.7 × 10^-9 ); genetic distances at HLA were greater than at random markers (P = 1.6 × 10^-46 ). Analyses of GWAS data in 937 US Pimas also showed sharing of alleles identical by descent at HLA that exceeds its genomic expectation (P = 7.0 × 10^-10 ). These results suggest that, in addition to the widely recognized balancing selection at HLA, recent directional selection may also occur, resulting in marked allelic differentiation between closely related populations.

The 22Rv1 prostate cancer cell line carries mixed genetic ancestry: Implications for prostate cancer health disparities research using pre-clinical models

BACKGROUND

Understanding how biological factors contribute to prostate cancer (PCa) health disparities requires mechanistic functional analysis of specific genes or pathways in pre-clinical cellular and animal models of this malignancy. The 22Rv1 human prostatic carcinoma cell line was originally derived from the parental CWR22R cell line. Although 22Rv1 has been well characterized and used in numerous mechanistic studies, no racial identifier has ever been disclosed for this cell line. In accordance with the need for racial diversity in cancer biospecimens and recent guidelines by the NIH on authentication of key biological resources, we sought to determine the ancestry of 22RV1 and authenticate previously reported racial identifications for four other PCa cell lines.

METHODS

We used 29 established Ancestry Informative Marker (AIM) single nucleotide polymorphisms (SNPs) to conduct DNA ancestry analysis and assign ancestral proportions to a panel of five PCa cell lines that included 22Rv1, PC3, DU145, MDA-PCa-2b, and RC-77T/E.

RESULTS

We found that 22Rv1 carries mixed genetic ancestry. The main ancestry proportions for this cell line were 0.41 West African (AFR) and 0.42 European (EUR). In addition, we verified the previously reported racial identifications for PC3 (0.73 EUR), DU145 (0.63 EUR), MDA-PCa-2b (0.73 AFR), and RC-77T/E (0.74 AFR) cell lines.

CONCLUSIONS

Considering the mortality disparities associated with PCa, which disproportionately affect African American men, there remains a burden on the scientific community to diversify the availability of biospecimens, including cell lines, for mechanistic studies on potential biological mediators of these disparities. This study is beneficial by identifying another PCa cell line that carries substantial AFR ancestry. This finding may also open the door to new perspectives on previously published studies using this cell line.

Affiliation with substance-using peers: Examining gene-environment correlations among parent monitoring, polygenic risk, and children's impulsivity

Parental monitoring can buffer the effect of deviant peers on adolescents' substance use by reducing affiliation with substance-using peers. However, children's genetic predispositions may evoke poorer monitoring, contributing to negative child outcomes. We examined evocative genotype-environment correlations underlying children's genetic predisposition for behavioral undercontrol and parental monitoring in early adolescence via children's impulsivity in middle childhood, and the influence of parental monitoring on affiliation with substance-using peers a year and a half later (n = 359). Genetic predisposition for behavioral undercontrol was captured using a polygenic risk score, and a portion of passive rGE was controlled by including parents' polygenic risk scores. Children's polygenic risk predicted poorer parental monitoring via greater children's impulsivity, indicating evocative rGE, controlling for a portion of passive rGE. Poorer parental monitoring predicted greater children's affiliation with substance-using peers a year and a half later. Results are discussed with respect to gene-environment correlations within developmental cascades.

MS in self-identified Hispanic/Latino individuals living in the US

Self-identified Hispanic/Latino individuals living with multiple sclerosis (MS) in the continental United States (US) are a diverse group that represents different cultural and ancestral backgrounds. A marked variability in the way MS affects various subgroups of Hispanics in the US has been observed. We reviewed and synthesized available data about MS in Hispanics in the US. There are likely a host of multifactorial elements contributing to these observations that could be explained by genetic, environmental, and social underpinnings. Barriers to adequate MS care in Hispanics are likely to include delivery of culturally competent care and social and economic disadvantages. Considerable efforts, including the formation of a national consortium known as the Alliance for Research in Hispanic Multiple Sclerosis (ARHMS), are underway to help further explore these various factors.

Assessing variation across 8 established East Asian loci for type 2 diabetes mellitus in American Indians: Suggestive evidence for new sex-specific diabetes signals in GLIS3 and ZFAND3

BACKGROUND

Eight new loci for type 2 diabetes mellitus (T2DM) were identified in an East Asian genome-wide association study meta-analysis. We assess tag SNPs across these loci for associations with T2DM in American Indians.

METHODS

A total of 435 SNPs that tag (R²  ≥ .85) common variation across the 8 loci were analyzed for association with T2DM (n = 7710), early onset T2DM (n = 1060), body mass index (n = 6839), insulin sensitivity (n = 555), and insulin secretion (n = 298).

RESULTS

Tag SNPs within FITM2-R3HDML-HNF4A, GLIS3, KCNK16, and ZFAND3 associated with T2DM after accounting for locus-wide multiple testing. The T2DM association in FITM2-R3HDML-HNF4A (rs3212183; P = .0002; OR = 1.19 [1.09-1.30]) was independent from the East Asian lead SNP (rs6017317), which did not associate with T2DM in American Indians. The top signals in GLIS3 (rs7875253; P = .0004; OR = 1.23 [1.10-1.38]) and KCNK16 (rs1544050; P = .002; OR = 1.16 [1.06-1.27]) were attenuated after adjustment for the East Asian lead SNPs (rs7041847 in GLIS3; rs1535500 in KCNK16), both of which also associated with T2DM in American Indians (P = .02; OR = 1.11 [1.01-1.21]; P = .007; OR = 1.19 [1.05-1.36] respectively). The top SNP in ZFAND3 (rs9470794; P = .002; OR = 1.43 [1.14-1.80]) was the identical East Asian lead SNP. Additional SNPs in GLIS3 (rs180867004) and ZFAND3 (rs4714120 and rs9470701) had significant genotype × sex interactions (P ≤ .008). The GLIS3 SNP (rs180867004) associated with T2DM only in men (P = .00006, OR = 1.94 [1.40-2.68]). The ZFAND3 SNPs (rs4714120 and rs9470701) associated with T2DM only in women (P = .0002, OR = 1.35 [1.16-1.59]; P = .0003, OR = 1.37 [1.16-1.63] respectively).

CONCLUSIONS

Replication of lead T2DM SNPs in GLIS3, KCNK16, and ZFAND3 was observed in American Indians. Sex-specific T2DM signals in GLIS3 and ZFAND3, which are distinct from the East Asian GWAS signals, were also identified.

Differential methylation of genes in individuals exposed to maternal diabetes in utero

AIMS/HYPOTHESIS

Individuals exposed to maternal diabetes in utero are more likely to develop metabolic and cardiovascular diseases later in life. This may be partially attributable to epigenetic regulation of gene expression. We performed an epigenome-wide association study to examine whether differential DNA methylation, a major source of epigenetic regulation, can be observed in offspring of mothers with type 2 diabetes during the pregnancy (OMD) compared with offspring of mothers with no diabetes during the pregnancy (OMND).

METHODS

DNA methylation was measured in peripheral blood using the Illumina HumanMethylation450K BeadChip. A total of 423,311 CpG sites were analysed in 388 Pima Indian individuals, mean age at examination was 13.0 years, 187 of whom were OMD and 201 were OMND. Differences in methylation between OMD and OMND were assessed.

RESULTS

Forty-eight differentially methylated CpG sites (with an empirical false discovery rate ≤0.05), mapping to 29 genes and ten intergenic regions, were identified. The gene with the strongest evidence was LHX3, in which six CpG sites were hypermethylated in OMD compared with OMND (p ≤ 1.1 × 10^-5). Similarly, a CpG near PRDM16 was hypermethylated in OMD (1.1% higher, p = 5.6 × 10^-7), where hypermethylation also predicted future diabetes risk (HR 2.12 per SD methylation increase, p = 9.7 × 10^-5). Hypermethylation near AK3 and hypomethylation at PCDHGA4 and STC1 were associated with exposure to diabetes in utero (AK3: 2.5% higher, p = 7.8 × 10^-6; PCDHGA4: 2.8% lower, p = 3.0 × 10^-5; STC1: 2.9% lower, p = 1.6 × 10^-5) and decreased insulin secretory function among offspring with normal glucose tolerance (AK3: 0.088 SD lower per SD of methylation increase, p = 0.02; PCDHGA4: 0.08 lower SD per SD of methylation decrease, p = 0.03; STC1: 0.072 SD lower per SD of methylation decrease, p = 0.05). Seventeen CpG sites were also associated with BMI (p ≤ 0.05). Pathway analysis of the genes with at least one differentially methylated CpG (p < 0.005) showed enrichment for three relevant biological pathways.

CONCLUSIONS/INTERPRETATION

Intrauterine exposure to diabetes can affect methylation at multiple genomic sites. Methylation status at some of these sites can impair insulin secretion, increase body weight and increase risk of type 2 diabetes.

Admixture in Latin America

Latin Americans arguably represent the largest recently admixed populations in the world. This reflects a history of massive settlement by immigrants (mostly Europeans and Africans) and their variable admixture with Natives, starting in 1492. This process resulted in the population of Latin America showing an extensive genetic and phenotypic diversity. Here we review how genetic analyses are being applied to examine the demographic history of this population, including patterns of mating, population structure and ancestry. The admixture history of Latin America, and the resulting extensive diversity of the region, represents a natural experiment offering an advantageous setting for genetic association studies. We review how recent analyses in Latin Americans are contributing to elucidating the genetic architecture of human complex traits.

Predicting substance use in emerging adulthood: A genetically informed study of developmental transactions between impulsivity and family conflict

Deviance proneness models propose a multilevel interplay in which transactions among genetic, individual, and family risk factors place children at increased risk for substance use. We examined bidirectional transactions between impulsivity and family conflict from middle childhood to adolescence and their contributions to substance use in adolescence and emerging adulthood (n = 380). Moreover, we examined children's, mothers', and fathers' polygenic risk scores for behavioral undercontrol, and mothers' and fathers' interparental conflict and substance disorder diagnoses as predictors of these transactions. The results support a developmental cascade model in which children's polygenic risk scores predicted greater impulsivity in middle childhood. Impulsivity in middle childhood predicted greater family conflict in late childhood, which in turn predicted greater impulsivity in late adolescence. Adolescent impulsivity subsequently predicted greater substance use in emerging adulthood. Results are discussed with respect to evocative genotype-environment correlations within developmental cascades and applications to prevention efforts.

The impact of genetic variants on BMI increase during childhood versus adulthood

BACKGROUND

Genetic variants that predispose individuals to obesity may have differing influences during childhood versus adulthood, and additive effects of such variants are likely to occur. Our ongoing studies to identify genetic determinants of obesity in American Indians have identified 67 single-nucleotide polymorphisms (SNPs) that reproducibly associate with maximum lifetime non-diabetic body mass index (BMI). This study aimed to identify when, during the lifetime, these variants have their greatest impact on BMI increase.

SUBJECTS/METHODS

A total of 5906 Native Americans of predominantly Pima Indian heritage with repeated measures of BMI between the ages of 5 and 45 years were included in this study. The association between each SNP with the rates of BMI increase during childhood (5-19 years) and adulthood (20-45 years) were assessed separately. The significant SNPs were used to calculate a cumulative allelic risk score (ARS) for childhood and adulthood, respectively, to assess the additive effect of these variants within each period of life.

RESULTS

The majority of these SNPs (36 of 67) were associated with rate of BMI increase during childhood (P-value range: 0.00004-0.05), whereas only nine SNPs were associated with rate of BMI change during adulthood (P-value range: 0.002-0.02). These 36 SNPs associated with childhood BMI gain likely had a cumulative effect as a higher childhood-ARS associated with rate of BMI change (β=0.032 kg m(-2) per year per risk allele, 95% confidence interval: 0.027-0.036, P<0.0001), such that at age 19 years, individuals with the highest number of risk alleles had a BMI of 10.2 kg m(-2) greater than subjects with the lowest number of risk alleles.

CONCLUSIONS

Overall, our data indicates that genetic polymorphisms associated with lifetime BMI may influence the rate of BMI increase during different periods in the life course. The majority of these polymorphisms have a larger impact on BMI during childhood, providing further evidence that prevention of obesity will need to begin early in life.

Assessment of established HDL-C loci for association with HDL-C levels and type 2 diabetes in Pima Indians

AIMS/HYPOTHESIS

Epidemiological studies in Pima Indians identified elevated levels of HDL-cholesterol (HDL-C) as a protective factor against type 2 diabetes risk in women. We assessed whether HDL-C-associated single-nucleotide polymorphisms (SNPs) also associate with type 2 diabetes in female Pima Indians.

METHODS

Twenty-one SNPs in established HDL-C loci were initially analysed in 2,675 full-heritage Pima Indians. SNPs shown to associate with HDL-C (12 SNPs) were assessed for association with type 2 diabetes in 7,710 Pima Indians (55.6% female sex). The CETP locus provided the strongest evidence for association with HDL-C and was further interrogated by analysing tag SNPs.

RESULTS

Twelve of the 21 SNPs analysed had a significant association with HDL-C in Pima Indians; five SNPs representing four loci (CETP, DOCK6, PPP1R3B and ABCA1) reached genome-wide significance. Three SNPs, at CETP, KLF14 and HNF4A, associated with type 2 diabetes only in female participants with the HDL-C-lowering allele increasing diabetes risk (p values: 3.2 × 10(-4) to 7.7 × 10(-5)); the association remained significant even after adjustment for HDL-C. Additional analysis across CETP identified rs6499863 as having the strongest association with type 2 diabetes in female participants (p = 5.0 × 10(-6)) and this association remained independent of the HDL-C association.

CONCLUSIONS/INTERPRETATION

SNPs at the CETP, HNF4A and KLF14 locus are associated with HDL-C levels and type 2 diabetes (in female participants). However, since HNF4A and KLF14 are established loci for type 2 diabetes, it is unlikely that HDL-C solely mediates these associations.

Ancestry variation and footprints of natural selection along the genome in Latin American populations

Latin American populations stem from the admixture of Europeans, Africans and Native Americans, which started over 400 years ago and had lasted for several centuries. Extreme deviation over the genome-wide average in ancestry estimations at certain genomic locations could reflect recent natural selection. We evaluated the distribution of ancestry estimations using 678 genome-wide microsatellite markers in 249 individuals from 13 admixed populations across Latin America. We found significant deviations in ancestry estimations including three locations with more than 3.5 times standard deviations from the genome-wide average: an excess of European ancestry at 1p36 and 14q32, and an excess of African ancestry at 6p22. Using simulations, we could show that at least the deviation at 6p22 was unlikely to result from genetic drift alone. By applying different linguistic groups as well as the most likely ancestral Native American populations as the ancestry, we showed that the choice of Native American ancestry could affect the local ancestry estimation. However, the signal at 6p22 consistently appeared in most of the analyses using various ancestral groups. This study provided important insights for recent natural selection in the context of the unique history of the New World and implications for disease mapping.

Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans

Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10(-28)) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits.

Analysis of SLC16A11 Variants in 12,811 American Indians: Genotype-Obesity Interaction for Type 2 Diabetes and an Association With RNASEK Expression

Genetic variants in SLC16A11 were recently reported to be associated with type 2 diabetes in Mexican and other Latin American populations. The diabetes risk haplotype had a frequency of 50% in Native Americans from Mexico but was rare in Europeans and Africans. In the current study, we analyzed SLC16A11 in 12,811 North American Indians and found that the diabetes risk haplotype, tagged by the rs75493593 A allele, was nominally associated with type 2 diabetes (P = 0.001, odds ratio 1.11). However, there was a strong interaction with BMI (P = 5.1 × 10(-7)) such that the diabetes association was stronger in leaner individuals. rs75493593 was also strongly associated with BMI in individuals with type 2 diabetes (P = 3.4 × 10(-15)) but not in individuals without diabetes (P = 0.77). Longitudinal analyses suggest that this is due, in part, to an association of the A allele with greater weight loss following diabetes onset (P = 0.02). Analyses of global gene expression data from adipose tissue, skeletal muscle, and whole blood provide evidence that rs75493593 is associated with expression of the nearby RNASEK gene, suggesting that RNASEK expression may mediate the effect of genotype on diabetes.

Parent and peer influences on emerging adult substance use disorder: A genetically informed study

The present study utilizes longitudinal data from a high-risk community sample to examine the unique effects of genetic risk, parental knowledge about the daily activities of adolescents, and peer substance use on emerging adult substance use disorders (SUDs). These effects are examined over and above a polygenic risk score. In addition, this polygenic risk score is used to examine gene-environment correlation and interaction. The results show that during older adolescence, higher adolescent genetic risk for SUDs predicts less parental knowledge, but this relation is nonsignificant in younger adolescence. Parental knowledge (using mother report) mediates the effects of parental alcohol use disorder (AUD) and adolescent genetic risk on risk for SUD, and peer substance use mediates the effect of parent AUD on offspring SUD. Finally, there are significant gene-environment interactions such that, for those at the highest levels of genetic risk, less parental knowledge and more peer substance use confers greater risk for SUDs. However, for those at medium and low genetic risk, these effects are attenuated. These findings suggest that the evocative effects of adolescent genetic risk on parenting increase with age across adolescence. They also suggest that some of the most important environmental risk factors for SUDs exert effects that vary across level of genetic propensity.

ABCC8 R1420H Loss-of-Function Variant in a Southwest American Indian Community: Association With Increased Birth Weight and Doubled Risk of Type 2 Diabetes

Missense variants in KCNJ11 and ABCC8, which encode the KIR6.2 and SUR1 subunits of the β-cell KATP channel, have previously been implicated in type 2 diabetes, neonatal diabetes, and hyperinsulinemic hypoglycemia of infancy (HHI). To determine whether variation in these genes affects risk for type 2 diabetes or increased birth weight as a consequence of fetal hyperinsulinemia in Pima Indians, missense and common noncoding variants were analyzed in individuals living in the Gila River Indian Community. A R1420H variant in SUR1 (ABCC8) was identified in 3.3% of the population (N = 7,710). R1420H carriers had higher mean birth weights and a twofold increased risk for type 2 diabetes with a 7-year earlier onset age despite being leaner than noncarriers. One individual homozygous for R1420H was identified; retrospective review of his medical records was consistent with HHI and a diagnosis of diabetes at age 3.5 years. In vitro studies showed that the R1420H substitution decreases KATP channel activity. Identification of this loss-of-function variant in ABCC8 with a carrier frequency of 3.3% affects clinical care as homozygous inheritance and potential HHI will occur in 1/3,600 births in this American Indian population.

Assessing FOXO1A as a potential susceptibility locus for type 2 diabetes and obesity in American Indians

OBJECTIVE

A prior genome-wide association study (GWAS) in Pima Indians identified variation within FOXO1A that modestly associated with early-onset (onset age < 25 years) type 2 diabetes (T2D). FOXO1A encodes the forkhead transcription factor involved in pancreatic β-cell growth and hypothalamic energy balance; therefore, FOXO1A was analyzed as a candidate gene for T2D and obesity in a population-based sample of 7,710 American Indians.

METHODS

Tag SNPs in/near FOXO1A (minor allele frequency ≥ 0.05) were analyzed for association with T2D at early onset (n = 1,060) and all ages (n = 7,710) and with insulin secretion (n = 298). SNPs were also analyzed for association with maximum body mass index (BMI) in adulthood (n = 5,918), maximum BMI z-score in childhood (n = 5,350), and % body fat (n = 555).

RESULTS

An intronic SNP rs2297627 associated with early-onset T2D [OR = 1.34 (1.13-1.58), P = 8.7 × 10(-4)] and T2D onset at any age [OR = 1.19 (1.09-1.30), P = 1 × 10(-4) ]. The T2D risk allele also associated with lower acute insulin secretion (β = 0.88, as a multiplier, P = 0.02). Another intronic SNP (rs1334241, D' = 0.99, r(2) = 0.49 with rs2297627) associated with maximum adulthood BMI (β = 1.02, as a multiplier, P = 3 × 10(-5)), maximum childhood BMI z-score (β = 0.08, P = 3 × 10(-4)), and % body fat (β = 0.83%, P = 0.04).

CONCLUSIONS

Common variation in FOXO1A may modestly affect risk for T2D and obesity in American Indians.

Role of Established Type 2 Diabetes-Susceptibility Genetic Variants in a High Prevalence American Indian Population

Several single nucleotide polymorphisms (SNPs) associated with type 2 diabetes mellitus (T2DM) have been identified, but there is little information on their role in populations at high risk for T2DM. We genotyped SNPs at 63 T2DM loci in 3,421 individuals from a high-risk American Indian population. Nominally significant (P < 0.05) associations were observed at nine SNPs in a direction consistent with the established association. A genetic risk score derived from all loci was strongly associated with T2DM (odds ratio 1.05 per risk allele, P = 6.2 × 10(-6)) and, in 292 nondiabetic individuals, with lower insulin secretion (by 4% per copy, P = 4.1 × 10(-6)). Genetic distances between American Indians and HapMap populations at T2DM markers did not differ significantly from genomic expectations. Analysis of U.S. national survey data suggested that 66% of the difference in T2DM prevalence between African Americans and European Americans, but none of the difference between American Indians and European Americans, was attributable to allele frequency differences at these loci. These analyses suggest that, in general, established T2DM loci influence T2DM in American Indians and that risk is mediated in part through an effect on insulin secretion. However, differences in allele frequencies do not account for the high population prevalence of T2DM.

Genetic structure characterization of Chileans reflects historical immigration patterns

Identifying the ancestral components of genomes of admixed individuals helps uncovering the genetic basis of diseases and understanding the demographic history of populations. We estimate local ancestry on 313 Chileans and assess the contribution from three continental populations. The distribution of ancestry block-length suggests an average admixing time around 10 generations ago. Sex-chromosome analyses confirm imbalanced contribution of European men and Native-American women. Previously known genes under selection contain SNPs showing large difference in allele frequencies. Furthermore, we show that assessing ancestry is harder at SNPs with higher recombination rates and easier at SNPs with large difference in allele frequencies at the ancestral populations. Two observations, that African ancestry proportions systematically decrease from North to South, and that European ancestry proportions are highest in central regions, show that the genetic structure of Chileans is under the influence of a diffusion process leading to an ancestry gradient related to geography.

Chileans are genetically admixed. Here, the authors find that the average admixing time is around 10 generations ago and show the contribution of European men and Native-American women to the Chilean population.

A cis-eQTL in PFKFB2 is associated with diabetic nephropathy, adiposity and insulin secretion in American Indians

A prior genome-wide association study (GWAS) in Pima Indians identified a variant within PFKFB2 (rs17258746) associated with body mass index (BMI). PFKFB2 encodes 6-phosphofructo-2-kinase/fructose 2,6-bisphosphatase isoform 2, which plays a role in glucose metabolism. To follow-up on the GWAS, tag SNPs across PFKFB2 were genotyped in American Indians (AI) who had longitudinal data on BMI (n = 6839), type 2 diabetes (T2D; n = 7710), diabetic nephropathy (DN; n = 2452), % body fat (n = 555) and insulin secretion (n = 298). Two SNPs were further genotyped in urban AI to assess replication for DN (n = 864). PFKFB2 expression was measured in 201 adipose biopsies using real-time RT-PCR and 61 kidney biopsies using the Affymetrix U133 array. Two SNPs (rs17258746 and rs11120137), which capture the same signal, were associated with maximum BMI in adulthood (β = 1.02 per risk allele, P = 7.3 × 10(-4)), maximum BMI z-score in childhood (β = 0.079, P = 0.03) and % body fat in adulthood (β = 3.4%, P = 3 × 10(-7)). The adiposity-increasing allele correlated with lower PFKFB2 adipose expression (β = 0.81, P = 9.4 × 10(-4)). Lower expression of PFKFB2 further correlated with higher % body fat (r = -0.16, P = 0.02) and BMI (r = -0.17, P = 0.02). This allele was also associated with increased risk for DN in both cohorts of AI [odds ratio = 1.64 (1.32-2.02), P = 5.8 × 10(-6)], and similarly correlated with lower PFKFB2 expression in kidney glomeruli (β = 0.87, P = 0.03). The same allele was also associated with lower insulin secretion assessed by acute insulin response (β = 0.78, P = 0.03) and 30-min plasma insulin concentrations (β = 0.78, P = 1.1 × 10(-4)). Variation in PFKFB2 appears to reduce PFKFB2 expression in adipose and kidney tissues, and thereby increase risk for adiposity and DN.

Status of cardiovascular disease and stroke in Hispanics/Latinos in the United States: a science advisory from the American Heart Association

BACKGROUND AND PURPOSE

This American Heart Association (AHA) scientific statement provides a comprehensive overview of current evidence on the burden cardiovascular disease (CVD) among Hispanics in the United States. Hispanics are the largest minority ethnic group in the United States, and their health is vital to the public health of the nation and to achieving the AHA's 2020 goals. This statement describes the CVD epidemiology and related personal beliefs and the social and health issues of US Hispanics, and it identifies potential prevention and treatment opportunities. The intended audience for this statement includes healthcare professionals, researchers, and policy makers.

METHODS

Writing group members were nominated by the AHA's Manuscript Oversight Committee and represent a broad range of expertise in relation to Hispanic individuals and CVD. The writers used a general framework outlined by the committee chair to produce a comprehensive literature review that summarizes existing evidence, indicate gaps in current knowledge, and formulate recommendations. Only English-language studies were reviewed, with PubMed/MEDLINE as our primary resource, as well as the Cochrane Library Reviews, Centers for Disease Control and Prevention, and the US Census data as secondary resources. Inductive methods and descriptive studies that focused on CVD outcomes incidence, prevalence, treatment response, and risks were included. Because of the wide scope of these topics, members of the writing committee were responsible for drafting individual sections selected by the chair of the writing committee, and the group chair assembled the complete statement. The conclusions of this statement are the views of the authors and do not necessarily represent the official view of the AHA. All members of the writing group had the opportunity to comment on the initial drafts and approved the final version of this document. The manuscript underwent extensive AHA internal peer review before consideration and approval by the AHA Science Advisory and Coordinating Committee.

RESULTS

This statement documents the status of knowledge regarding CVD among Hispanics and the sociocultural issues that impact all subgroups of Hispanics with regard to cardiovascular health. In this review, whenever possible, we identify the specific Hispanic subgroups examined to avoid generalizations. We identify specific areas for which current evidence was less robust, as well as inconsistencies and evidence gaps that inform the need for further rigorous and interdisciplinary approaches to increase our understanding of the US Hispanic population and its potential impact on the public health and cardiovascular health of the total US population. We provide recommendations specific to the 9 domains outlined by the chair to support the development of these culturally tailored and targeted approaches.

CONCLUSIONS

Healthcare professionals and researchers need to consider the impact of culture and ethnicity on health behavior and ultimately health outcomes. There is a need to tailor and develop culturally relevant strategies to engage Hispanics in cardiovascular health promotion and cultivate a larger workforce of healthcare providers, researchers, and allies with the focused goal of improving cardiovascular health and reducing CVD among the US Hispanic population.

Common genetic variation in and near the melanocortin 4 receptor gene (MC4R) is associated with body mass index in American Indian adults and children

Six rare functional coding mutations were previously identified in melanocortin 4 receptor (MC4R) in 6,760 American Indians. Individuals heterozygous for one of these mutations become obese while young. We now investigate whether common non-coding variation near MC4R also contributes to obesity. Fifty-six tag single-nucleotide polymorphisms (SNPs) were genotyped in 3,229 full-heritage Pima Indians, and nine of these SNPs which showed evidence for association were genotyped in additional 3,852 mixed-heritage American Indians. Associations of SNPs with maximum body mass index (BMI) in adulthood (n = 5,918), BMI z score in childhood (n = 5,350), percent body fat (n = 864), energy expenditure (n = 358) and ad libitum food intake (n = 178) were assessed. Conditional analyses demonstrated that SNPs, rs74861148 and rs483125, were independently associated with BMI in adulthood (β = 0.68 kg/m² per risk allele, p = 5 × 10⁻⁵; β = 0.58 kg/m², p = 0.002, respectively) and BMI z score in childhood (β = 0.05, p = 0.02; β = 0.07, p = 0.01, respectively). One haplotype (frequency = 0.35) of the G allele at rs74861148 and the A allele at rs483125 provided the strongest evidence for association with adult BMI (β = 0.89 kg/m², p = 5.5 × 10⁻⁷), and was also associated with childhood BMI z score (β = 0.08, p = 0.001). In addition, a promoter SNP rs11872992 was nominally associated with adult BMI (β = 0.61 kg/m², p = 0.05) and childhood BMI z score (β = 0.11, p = 0.01), where the risk allele also modestly decreased transcription in vitro by 12 % (p = 0.005). This risk allele was further associated with increased percent body fat (β = 2.2 %, p = 0.002), increased food intake (β = 676 kcal/day, p = 0.007) and decreased energy expenditure (β = −53.4 kcal/day, p = 0.054). Common and rare variation in MC4R contributes to obesity in American Indians.

Enhanced methods for local ancestry assignment in sequenced admixed individuals

Inferring the ancestry at each locus in the genome of recently admixed individuals (e.g., Latino Americans) plays a major role in medical and population genetic inferences, ranging from finding disease-risk loci, to inferring recombination rates, to mapping missing contigs in the human genome. Although many methods for local ancestry inference have been proposed, most are designed for use with genotyping arrays and fail to make use of the full spectrum of data available from sequencing. In addition, current haplotype-based approaches are very computationally demanding, requiring large computational time for moderately large sample sizes. Here we present new methods for local ancestry inference that leverage continent-specific variants (CSVs) to attain increased performance over existing approaches in sequenced admixed genomes. A key feature of our approach is that it incorporates the admixed genomes themselves jointly with public datasets, such as 1000 Genomes, to improve the accuracy of CSV calling. We use simulations to show that our approach attains accuracy similar to widely used computationally intensive haplotype-based approaches with large decreases in runtime. Most importantly, we show that our method recovers comparable local ancestries, as the 1000 Genomes consensus local ancestry calls in the real admixed individuals from the 1000 Genomes Project. We extend our approach to account for low-coverage sequencing and show that accurate local ancestry inference can be attained at low sequencing coverage. Finally, we generalize CSVs to sub-continental population-specific variants (sCSVs) and show that in some cases it is possible to determine the sub-continental ancestry for short chromosomal segments on the basis of sCSVs.

Advances in sequencing technologies are dramatically changing the volume and type of data collected in genetic studies. Although most genetic studies so far have focused on individuals of European ancestry, recent studies are increasingly being performed in individuals of admixed ancestry (i.e., with recent ancestors from multiple continents, e.g., Latino Americans). A key component in such studies is the accurate inference of continental ancestry at each segment in the genome of these individuals. In this work we present accurate and robust methods that use continent-specific variants (i.e., genetic variants observed only in individuals of a given continent), now readily accessible through sequencing technology, to perform extremely fast and accurate inference of the ancestral origin of each genomic segment in recently admixed individuals.

Whole exome sequencing identifies variation in CYB5A and RNF10 associated with adiposity and type 2 diabetes

OBJECTIVE

Few coding variants in genes associated with type 2 diabetes (T2D) have been identified, and the underlying physiologic mechanisms whereby susceptibility genes influence T2D risk are often unknown. The objective of this study was to identify coding variation that increases risk for T2D via an effect on a pre-diabetic trait.

METHODS

Whole exome sequencing was done in 177 Pima Indians. Selected variants (N = 345) were genotyped in 555 subjects characterized for body fatness, glucose disposal rates during a clamp, acute insulin response to glucose, and 2-h plasma glucose concentrations during an OGTT, and were also genotyped in up to 5,880 subjects with longitudinal measures of BMI. Variants associated with quantitative traits were assessed for association with T2D in 7,667 subjects.

RESULTS

rs7238987 in CYB5A associated with body fatness (P = 7.0 × 10(-6) ). This SNP and a novel SNP in RNF10 also associated with maximum recorded BMI (P = 6.2 × 10(-7) and P = 7.2 × 10(-4) ) and maximum childhood BMI z-score (P = 5.9 × 10(-4) and P = 8.5 × 10(-7) ). The BMI increasing alleles increased the risk for T2D (P = 0.01; OR = 1.13 [1.03-1.24] and 9.5 × 10(-3) ; OR = 1.49 [1.10-2.02]).

CONCLUSIONS

CYB5A, which has a role in stearyl-CoA-desaturase activity, and RNF10, with an unknown role in weight regulating pathways, associated with adiposity and nominally increased the risk for T2D in American Indians.

Interethnic admixture and the evolution of Latin American populations

A general introduction to the origins and history of Latin American populations is followed by a systematic review of the data from molecular autosomal assessments of the ethnic/continental (European, African, Amerindian) ancestries for 24 Latin American countries or territories. The data surveyed are of varying quality but provide a general picture of the present constitution of these populations. A brief discussion about the applications of these results (admixture mapping) is also provided. Latin American populations can be viewed as natural experiments for the investigation of unique anthropological and epidemiological issues.

A genome-wide association study in American Indians implicates DNER as a susceptibility locus for type 2 diabetes

Most genetic variants associated with type 2 diabetes mellitus (T2DM) have been identified through genome-wide association studies (GWASs) in Europeans. The current study reports a GWAS for young-onset T2DM in American Indians. Participants were selected from a longitudinal study conducted in Pima Indians and included 278 cases with diabetes with onset before 25 years of age, 295 nondiabetic controls ≥45 years of age, and 267 siblings of cases or controls. Individuals were genotyped on a ∼1M single nucleotide polymorphism (SNP) array, resulting in 453,654 SNPs with minor allele frequency >0.05. SNPs were analyzed for association in cases and controls, and a family-based association test was conducted. Tag SNPs (n = 311) were selected for 499 SNPs associated with diabetes (P < 0.0005 in case-control analyses or P < 0.0003 in family-based analyses), and these SNPs were genotyped in up to 6,834 additional Pima Indians to assess replication. Rs1861612 in DNER was associated with T2DM (odds ratio = 1.29 per copy of the T allele; P = 6.6 × 10(-8), which represents genome-wide significance accounting for the number of effectively independent SNPs analyzed). Transfection studies in murine pancreatic β-cells suggested that DNER regulates expression of notch signaling pathway genes. These studies implicate DNER as a susceptibility gene for T2DM in American Indians.

Distribution of ancestral chromosomal segments in admixed genomes and its implications for inferring population history and admixture mapping

The ancestral chromosomal segments in admixed genomes are of significant importance for both population history inference and admixture mapping, because they essentially provide the basic information for tracking genetic events. However, the distributions of the lengths of ancestral chromosomal segments (LACS) under some admixture models remain poorly understood. Here we introduced a theoretical framework on the distribution of LACS in two representative admixture models, that is, hybrid isolation (HI) model and gradual admixture (GA) model. Although the distribution of LACS in the GA model differs from that in the HI model, we demonstrated that the mean LACS in the HI model is approximately half of that in the GA model if both admixture proportion and admixture time in the two models are identical. We showed that the theoretical framework greatly facilitated the inference and understanding of population admixture history by analyzing African-American and Mexican empirical data. In addition, we found the peak of association signatures in the HI model was much narrower and sharper than that in the GA model, indicating that the identification of putative causal allele in the HI model is more efficient than that in the GA model. Thus admixture mapping with case-only data would be a reasonable and economical choice in the HI model due to the weak background noise. However, according to our previous studies, many populations are likely to be gradually admixed and have pretty high background linkage disequilibrium. Therefore, we suggest using a case-control approach rather than a case-only approach to conduct admixture mapping to retain the statistics power in recently admixed populations.

Susceptibility gene search for nephropathy and related traits in Mexican-Americans

The rising global epidemic of diabetic nephropathy (DN) will likely lead to increase in the prevalence of cardiovascular morbidity and mortality posing a serious burden for public health care. Despite greater understanding of the etiology of diabetes and the development of novel treatment strategies to control blood glucose levels, the prevalence and incidence rate of DN is increasing especially in minority populations including Mexican-Americans. Mexican-Americans with type 2 diabetes (T2DM) are three times more likely to develop microalbuminuria, and four times more likely to develop clinical proteinuria compared to non-Hispanic whites. Furthermore, Mexican-Americans have a sixfold increased risk of developing renal failure secondary to T2DM compared to Caucasians. Prevention and better treatment of DN should be a high priority for both health-care organizations and society at large. Pathogenesis of DN is multi-factorial. Familial clustering of DN-related traits in MAs show that DN and related traits are heritable and that genes play a susceptibility role. While, there has been some progress in identifying genes which when mutated influence an individual's risk, major gene(s) responsible for DN are yet to be identified. Knowledge of the genetic causes of DN is essential for elucidation of its mechanisms, and for adequate classification, prognosis, and treatment. Self-identification and collaboration among researchers with suitable genomic and clinical data for meta-analyses in Mexican-Americans is critical for progress in replicating/identifying DN risk genes in this population. This paper reviews the approaches and recent efforts made to identify genetic variants contributing to risk for DN and related phenotypes in the Mexican-American population.

The Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study protocol

BACKGROUND AND PURPOSE

Epidemiological studies of intracerebral hemorrhage (ICH) have consistently demonstrated variation in incidence, location, age at presentation, and outcomes among non-Hispanic white, black, and Hispanic populations. We report here the design and methods for this large, prospective, multi-center case-control study of ICH.

METHODS

The Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study is a multi-center, prospective case-control study of ICH. Cases are identified by hot-pursuit and enrolled using standard phenotype and risk factor information and include neuroimaging and blood sample collection. Controls are centrally identified by random digit dialing to match cases by age (±5 years), race, ethnicity, sex, and metropolitan region.

RESULTS

As of March 22, 2013, 1655 cases of ICH had been recruited into the study, which is 101.5% of the target for that date, and 851 controls had been recruited, which is 67.2% of the target for that date (1267 controls) for a total of 2506 subjects, which is 86.5% of the target for that date (2897 subjects). Of the 1655 cases enrolled, 1640 cases had the case interview entered into the database, of which 628 (38%) were non-Hispanic black, 458 (28%) were non-Hispanic white, and 554 (34%) were Hispanic. Of the 1197 cases with imaging submitted, 876 (73.2%) had a 24 hour follow-up CT available. In addition to CT imaging, 607 cases have had MRI evaluation.

CONCLUSIONS

The ERICH study is a large, case-control study of ICH with particular emphasis on recruitment of minority populations for the identification of genetic and epidemiological risk factors for ICH and outcomes after ICH.

Functional promoter variants in sphingosine 1-phosphate receptor 3 associate with susceptibility to sepsis-associated acute respiratory distress syndrome

The genetic mechanisms underlying the susceptibility to acute respiratory distress syndrome (ARDS) are poorly understood. We previously demonstrated that sphingosine 1-phosphate (S1P) and the S1P receptor S1PR3 are intimately involved in lung inflammatory responses and vascular barrier regulation. Furthermore, plasma S1PR3 protein levels were shown to serve as a biomarker of severity in critically ill ARDS patients. This study explores the contribution of single nucleotide polymorphisms (SNPs) of the S1PR3 gene to sepsis-associated ARDS. S1PR3 SNPs were identified by sequencing the entire gene and tagging SNPs selected for case-control association analysis in African- and ED samples from Chicago, with independent replication in a European case-control study of Spanish individuals. Electrophoretic mobility shift assays, luciferase activity assays, and protein immunoassays were utilized to assess the functionality of associated SNPs. A total of 80 variants, including 29 novel SNPs, were identified. Because of limited sample size, conclusive findings could not be drawn in African-descent ARDS subjects; however, significant associations were found for two promoter SNPs (rs7022797 -1899T/G; rs11137480 -1785G/C), across two ED samples supporting the association of alleles -1899G and -1785C with decreased risk for sepsis-associated ARDS. In addition, these alleles significantly reduced transcription factor binding to the S1PR3 promoter; reduced S1PR3 promoter activity, a response particularly striking after TNF-α challenge; and were associated with lower plasma S1PR3 protein levels in ARDS patients. These highly functional studies support S1PR3 as a novel ARDS candidate gene and a potential target for individualized therapy.

Strong parent-of-origin effects in the association of KCNQ1 variants with type 2 diabetes in American Indians

Parent-of-origin effects were observed in an Icelandic population for several genetic variants associated with type 2 diabetes, including those in KLF14 (rs4731702), MOB2 (rs2334499), and KCNQ1 (rs2237892, rs231362). We analyzed parent-of-origin effects for these variants, along with two others in KCNQ1 identified in previous genome-wide association studies (rs2237895, rs2299620), in 7,351 Pima Indians from 4,549 nuclear families; 34% of participants had diabetes. In a subset of 287 normoglycemic individuals, acute insulin secretion was measured by an intravenous glucose tolerance test. Statistically significant (P < 0.05) parent-of-origin effects were seen for association with type 2 diabetes for all variants. The strongest effect was seen at rs2299620 in KCNQ1; the C allele was associated with increased diabetes when maternally derived (odds ratio [OR], 1.92; P = 4.1 × 10(-12)), but not when paternally derived (OR, 0.93; P = 0.47; P = 9.9 × 10(-6) for difference in maternal and paternal effects). A maternally derived C allele also was associated with a 28% decrease in insulin secretion (P = 0.002). This study confirms parent-of-origin effects in the association with type 2 diabetes for variants in KLF14, MOB2, and KCNQ1. In Pima Indians, the effect of maternally derived KCNQ1 variants appears to be mediated through decreased insulin secretion and is particularly strong, accounting for 4% of the variance in liability to diabetes.

MAP2K3 is associated with body mass index in American Indians and Caucasians and may mediate hypothalamic inflammation

To identify genes that affect body mass index (BMI) in American Indians who are predominately of Pima Indian heritage, we previously completed a genome-wide association study in 1120 American Indians. That study also included follow-up genotyping for 9 SNPs in 2133 additional subjects. A comprehensive follow-up study has subsequently been completed where 292 SNPs were genotyped in 3562 subjects, of which 128 SNPs were assessed for replication in 3238 additional subjects. In the combined subjects (n = 6800), BMI associations for two SNPs, rs12882548 and rs11652094, approached genome-wide significance (P = 6.7 × 10⁻⁷ and 8.1 × 10⁻⁷, respectively). Rs12882548 is located in a gene desert on chromosome 14 and rs11652094 maps near MAP2K3. Several SNPs in the MAP2K3 region including rs11652094 were also associated with BMI in Caucasians from the GIANT consortium (P = 10⁻²–10⁻⁵), and the combined P-values across both American Indians and Caucasian were P = 10⁻⁴–10⁻⁹. Follow-up sequencing across MAP2K3 identified several paralogous sequence variants indicating that the region may have been duplicated. MAP2K3 expression levels in adipose tissue biopsies were positively correlated with BMI, although it is unclear if this correlation is a cause or effect. In vitro studies with cloned MAP2K3 promoters suggest that MAP2K3 expression may be up-regulated during adipogenesis. Microarray analyses of mouse hypothalamus cells expressing constitutively active MAP2K3 identified several up-regulated genes involved in immune/inflammatory pathways and a gene, Hap1, thought to play a role in appetite regulation. We conclude that MAP2K3 is a reproducible obesity locus that may affect body weight via complex mechanisms involving appetite regulation and hypothalamic inflammation.

Identification of genetic variation that determines human trehalase activity and its association with type 2 diabetes

A prior linkage scan in Pima Indians identified a putative locus for type two diabetes (T2D) and body mass index (BMI) on chromosome 11q23-25. Association mapping across this region identified single nucleotide polymorphisms (SNPs) in the trehalase gene (TREH) that were associated with T2D. To assess the putative connection between trehalase activity and T2D, we performed a linkage study for trehalase activity in 570 Pima Indians who had measures of trehalase activity. Strong evidence of linkage of plasma trehalase activity (LOD = 7.0) was observed in the TREH locus. Four tag SNPs in TREH were genotyped in these subjects and plasma trehalase activity was highly associated with three SNPs: rs2276064, rs117619140 and rs558907 (p = 2.2 × 10⁻¹¹–1.4 × 10⁻²³), and the fourth SNP, rs10790256, was associated conditionally on these three (p = 2.9 × 10⁻⁷). Together, the four tag SNPs explained 51 % of the variance in plasma trehalase activity and 79 % of the variance attributed to the linked locus. These four tag SNPs were further genotyped in 828 subjects used for association mapping of T2D, and rs558907 was associated with T2D (odds ratio (OR) 1.94, p = 0.002). To assess replication of the T2D association, all four tag SNPs were additionally genotyped in two non-overlapping samples of Native Americans. Rs558907 was reproducibly associated with T2D in 2,942 full-heritage Pima Indians (OR 1.27 p = 0.03) and 3,897 “mixed” heritage Native Americans (OR 1.21, p = 0.03), and the strongest evidence for association came from combining all samples (OR 1.27 p = 1.6 × 10⁻⁴, n = 7,667). However, among 320 longitudinally studied subjects, measures of trehalase activity from a non-diabetic exam did not predict those who would eventually develop diabetes versus those who would remain non-diabetic (hazard ratio 0.94 per SD of trehalase activity, p = 0.29). We conclude that variants in TREH control trehalase activity, and although one of these variants is also reproducibly associated with T2D, it is likely that the effect of the SNP on risk of T2D occurs by a mechanism different than affecting trehalase activity. Alternatively, TREH variants may be tagging a nearby T2D locus.

ETHNOPRED: a novel machine learning method for accurate continental and sub-continental ancestry identification and population stratification correction

BACKGROUND

Population stratification is a systematic difference in allele frequencies between subpopulations. This can lead to spurious association findings in the case-control genome wide association studies (GWASs) used to identify single nucleotide polymorphisms (SNPs) associated with disease-linked phenotypes. Methods such as self-declared ancestry, ancestry informative markers, genomic control, structured association, and principal component analysis are used to assess and correct population stratification but each has limitations. We provide an alternative technique to address population stratification.

RESULTS

We propose a novel machine learning method, ETHNOPRED, which uses the genotype and ethnicity data from the HapMap project to learn ensembles of disjoint decision trees, capable of accurately predicting an individual's continental and sub-continental ancestry. To predict an individual's continental ancestry, ETHNOPRED produced an ensemble of 3 decision trees involving a total of 10 SNPs, with 10-fold cross validation accuracy of 100% using HapMap II dataset. We extended this model to involve 29 disjoint decision trees over 149 SNPs, and showed that this ensemble has an accuracy of ≥ 99.9%, even if some of those 149 SNP values were missing. On an independent dataset, predominantly of Caucasian origin, our continental classifier showed 96.8% accuracy and improved genomic control's λ from 1.22 to 1.11. We next used the HapMap III dataset to learn classifiers to distinguish European subpopulations (North-Western vs. Southern), East Asian subpopulations (Chinese vs. Japanese), African subpopulations (Eastern vs. Western), North American subpopulations (European vs. Chinese vs. African vs. Mexican vs. Indian), and Kenyan subpopulations (Luhya vs. Maasai). In these cases, ETHNOPRED produced ensembles of 3, 39, 21, 11, and 25 disjoint decision trees, respectively involving 31, 502, 526, 242 and 271 SNPs, with 10-fold cross validation accuracy of 86.5% ± 2.4%, 95.6% ± 3.9%, 95.6% ± 2.1%, 98.3% ± 2.0%, and 95.9% ± 1.5%. However, ETHNOPRED was unable to produce a classifier that can accurately distinguish Chinese in Beijing vs. Chinese in Denver.

CONCLUSIONS

ETHNOPRED is a novel technique for producing classifiers that can identify an individual's continental and sub-continental heritage, based on a small number of SNPs. We show that its learned classifiers are simple, cost-efficient, accurate, transparent, flexible, fast, applicable to large scale GWASs, and robust to missing values.

Genotype-based ancestral background consistently predicts efficacy and side effects across treatments in CATIE and STAR*D

Only a subset of patients will typically respond to any given prescribed drug. The time it takes clinicians to declare a treatment ineffective leaves the patient in an impaired state and at unnecessary risk for adverse drug effects. Thus, diagnostic tests robustly predicting the most effective and safe medication for each patient prior to starting pharmacotherapy would have tremendous clinical value. In this article, we evaluated the use of genetic markers to estimate ancestry as a predictive component of such diagnostic tests. We first estimated each patient’s unique mosaic of ancestral backgrounds using genome-wide SNP data collected in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) (n = 765) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) (n = 1892). Next, we performed multiple regression analyses to estimate the predictive power of these ancestral dimensions. For 136/89 treatment-outcome combinations tested in CATIE/STAR*D, results indicated 1.67/1.84 times higher median test statistics than expected under the null hypothesis assuming no predictive power (p<0.01, both samples). Thus, ancestry showed robust and pervasive correlations with drug efficacy and side effects in both CATIE and STAR*D. Comparison of the marginal predictive power of MDS ancestral dimensions and self-reported race indicated significant improvements to model fit with the inclusion of MDS dimensions, but mixed evidence for self-reported race. Knowledge of each patient’s unique mosaic of ancestral backgrounds provides a potent immediate starting point for developing algorithms identifying the most effective and safe medication for a wide variety of drug-treatment response combinations. As relatively few new psychiatric drugs are currently under development, such personalized medicine offers a promising approach toward optimizing pharmacotherapy for psychiatric conditions.

Softwares and methods for estimating genetic ancestry in human populations

The estimation of genetic ancestry in human populations has important applications in medical genetic studies. Genetic ancestry is used to control for population stratification in genetic association studies, and is used to understand the genetic basis for ethnic differences in disease susceptibility. In this review, we present an overview of genetic ancestry estimation in human disease studies, followed by a review of popular softwares and methods used for this estimation.

Evidence for a role of LPGAT1 in influencing BMI and percent body fat in Native Americans

OBJECTIVE

A genome-wide association study (GWAS) was recently completed in 1120 Pima Indians to identify loci that influence BMI. Among the top 100 signals were three variants that mapped within the lysophosphatidylglycerol acyltransferase 1 (LPGAT1) gene. LPGAT1 belongs to a large family of acyltransferases, which are involved in a variety of biological processes including pathways that regulate energy homeostasis and body weight. Therefore LPGAT1 was analyzed as a candidate gene for obesity in Pima Indians.

DESIGN AND METHODS

Variants (n = 26) located within and adjacent to LPGAT1 including a novel 27bp deletion in the 5'-untranslated region identified by sequencing were genotyped in a population-based sample of 3,391 full-heritage Pima Indians living in the Gila River Indian Community. Replication of selected variants was assessed in a second sample of 3,327 mixed-heritage Native Americans from the same community.

RESULTS

Variants with nominal associations with BMI in each of the two independent samples (tagged by rs112662024 and rs12058008) had associations of P = 1-4 × 10(-5) in the combined sample (n = 6718). A haplotype that includes the novel 27bp deletion, which does not occur in Caucasians, showed the strongest association with BMI in the full-heritage Pima Indians. In vitro functional studies provided suggestive evidence that this 27bp deletion may affect transcriptional or posttranscriptional regulation. Analysis of LPGAT1 cDNA from human preadipocytes identified an additional exon whose sequence could potentially serve as a mitochondrial targeting peptide.

CONCLUSIONS

LPGAT1 is a novel gene that influences BMI in Native Americans.

Variants in the LEPR gene are nominally associated with higher BMI and lower 24-h energy expenditure in Pima Indians

Genome-wide association studies (GWASs) have been used to search for susceptibility genes for type 2 diabetes and obesity in the Pima Indians, a population with a high prevalence of both diseases. In these studies, a variant (rs2025804) in the LEPR gene was nominally associated with BMI in 1,082 subjects (P = 0.03 adjusted for age, sex, birth year, and family membership). Therefore the LEPR and leptin overlapping transcript (LEPROT) genes were selected for further sequencing and genotyping in larger population-based samples for association analyses with obesity-related phenotypes. Selected variants (n = 80) spanning these genes were genotyped in a sample of full-heritage Pima Indians (n = 2,842) and several common variants including rs2025804 were nominally associated with BMI (P = 0.05-0.003 adjusted for age, sex, birth year, and family membership). Four common tag variants associated with BMI in the full-heritage Pima Indian sample were genotyped in a second sample of mixed-heritage Native Americans (n = 2,969) and three of the variants showed nominal replication (P = 0.03-0.006 adjusted as above and additionally for Indian heritage). Combining both samples provided the strongest evidence for association (adjusted P = 0.0003-0.0001). A subset of these individuals (n = 403) had been metabolically characterized for predictors of obesity and the BMI risk alleles for the variants tagged by rs2025804 were also associated with lower 24-h energy expenditure (24hEE) as assessed in a human respiratory chamber (P = 0.0007 adjusted for age, sex, fat mass, fat-free mass, activity, and family membership). We conclude that common noncoding variation in the LEPR gene is associated with higher BMI and lower energy expenditure in Native Americans.

Exploring population admixture dynamics via empirical and simulated genome-wide distribution of ancestral chromosomal segments

The processes of genetic admixture determine the haplotype structure and linkage disequilibrium patterns of the admixed population, which is important for medical and evolutionary studies. However, most previous studies do not consider the inherent complexity of admixture processes. Here we proposed two approaches to explore population admixture dynamics, and we demonstrated, by analyzing genome-wide empirical and simulated data, that the approach based on the distribution of chromosomal segments of distinct ancestry (CSDAs) was more powerful than that based on the distribution of individual ancestry proportions. Analysis of 1,890 African Americans showed that a continuous gene flow model, in which the African American population continuously received gene flow from European populations over about 14 generations, best explained the admixture dynamics of African Americans among several putative models. Interestingly, we observed that some African Americans had much more European ancestry than the simulated samples, indicating substructures of local ancestries in African Americans that could have been caused by individuals from some particular lineages having repeatedly admixed with people of European ancestry. In contrast, the admixture dynamics of Mexicans could be explained by a gradual admixture model in which the Mexican population continuously received gene flow from both European and Amerindian populations over about 24 generations. Our results also indicated that recent gene flows from Sub-Saharan Africans have contributed to the gene pool of Middle Eastern populations such as Mozabite, Bedouin, and Palestinian. In summary, this study not only provides approaches to explore population admixture dynamics, but also advances our understanding on population history of African Americans, Mexicans, and Middle Eastern populations.

An exploratory case-only analysis of gene-hazardous air pollutant interactions and the risk of childhood medulloblastoma

BACKGROUND

There is evidence that exposure to chlorinated solvents may be associated with childhood medulloblastoma and primitive neuroectodermal tumor (M/PNET) risk. Animal models suggest genes related to detoxification and DNA repair are important in the carcinogenicity of these pollutants; however, there have been no human studies assessing the modifying effects of these genotypes on the association between chlorinated solvents and childhood M/PNET risk.

PROCEDURE

We conducted a case-only study to evaluate census tract-level exposure to chlorinated solvents and the risk of childhood M/PNET in the context of detoxification and DNA repair genotypes. Cases (n = 98) were obtained from Texas Children's Hospital and MD Anderson Cancer Center. Key genotypes (n = 22) were selected from the Illumina Human 1M Quad SNP Chip. Exposure to chlorinated solvents (methylene chloride, perchloroethylene, trichloroethylene, and vinyl chloride) was estimated from the US EPA's 1999 Assessment System for Population Exposure Nationwide (ASPEN). Logistic regression was used to estimate the case-only odds ratios and 95% confidence intervals (CIs).

RESULTS

There were 11 significant gene-environment interactions associated with childhood M/PNET risk. However, after correcting for multiple comparisons, only the interaction between high trichloroethylene levels and OGG1 rs293795 significantly increased the risk of childhood M/PNET risk (OR = 9.24, 95% CI: 2.24, 38.24, Q = 0.04).

CONCLUSIONS

This study provides an initial assessment of the interaction between ambient levels of chlorinated solvents and potentially relevant genotypes on childhood M/PNET risk. Our results are exploratory and must be validated in animal models, as well as additional human studies.