CoAIMs: a cost-effective panel of ancestry informative markers for determining continental origins

XGBoost as a reliable machine learning tool for predicting ancestry using autosomal STR profiles - Proof of method

The aim of this study was to test the validity of a predictive model of ancestry affiliation based on Short Tandem Repeat (STR) profiles. Frequencies of 29 genetic markers from the Promega website for four distinct population groups (African Americans, Asians, Caucasians, Hispanic Americans) were used to generate 360,000 profiles (90000 profiles per group), which were later used to train and test a range of machine learning algorithms with the goal of establishing the most optimal model for accurate ancestry prediction. The chosen models (Decision Trees, Support Vector Machines, XGBoost, among others) were deployed in Python, and their performance was compared. The XGBoost model outperformed others, displaying significant predictive power with an accuracy rating of 94.24 % for all four classes, and an accuracy rating of 99.06 % on a differentiation task involving Asian, African American, and Caucasian subsamples and an accuracy rating of 98.57 % when differentiating between the African-American, Asian, and the mixed group combining Caucasians and Hispanics. Evaluating the impact of training set size revealed that model accuracy peaked at 94 % with 90,000 profiles per category, but decreased to 83 % as the number of profiles per category was reduced to 500, particularly affecting precision when distinguishing between Caucasian and Hispanic subgroups. The study further investigated the impact of marker quantity on model accuracy, finding that the use of 21 markers, commonly available in commercial amplification kits, resulted in an accuracy of 96.3 % for African Americans, Asians, and Caucasians, and 88.28 % for all four groups combined. These findings underscore the potential of STR-based models in forensic analysis and hint at the broader applicability of machine learning in genetic ancestry determination, with implications for enhancing the precision and reliability of forensic investigations, particularly in heterogeneous environments where ancestral background can be a crucial piece of information.

Genetic ancestry plays a central role in population pharmacogenomics

Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD (http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/).

Hsin-Chou Yang et al. examine population structure in several genomic databases and identify that pharmacogenetic loci are enriched for markers of genetic ancestry. Their results suggest that genetic ancestry must be carefully considered in population pharmacogenetics studies.

Development of a small panel of SNPs to infer ancestry in Chileans that distinguishes Aymara and Mapuche components

Background

Current South American populations trace their origins mainly to three continental ancestries, i.e. European, Amerindian and African. Individual variation in relative proportions of each of these ancestries may be confounded with socio-economic factors due to population stratification. Therefore, ancestry is a potential confounder variable that should be considered in epidemiologic studies and in public health plans. However, there are few studies that have assessed the ancestry of the current admixed Chilean population. This is partly due to the high cost of genome-scale technologies commonly used to estimate ancestry. In this study we have designed a small panel of SNPs to accurately assess ancestry in the largest sampling to date of the Chilean mestizo population (n = 3349) from eight cities. Our panel is also able to distinguish between the two main Amerindian components of Chileans: Aymara from the north and Mapuche from the south.

Results

A panel of 150 ancestry-informative markers (AIMs) of SNP type was selected to maximize ancestry informativeness and genome coverage. Of these, 147 were successfully genotyped by KASPar assays in 2843 samples, with an average missing rate of 0.012, and a 0.95 concordance with microarray data. The ancestries estimated with the panel of AIMs had relative high correlations (0.88 for European, 0.91 for Amerindian, 0.70 for Aymara, and 0.68 for Mapuche components) with those obtained with AXIOM LAT1 array. The country’s average ancestry was 0.53 ± 0.14 European, 0.04 ± 0.04 African, and 0.42 ± 0.14 Amerindian, disaggregated into 0.18 ± 0.15 Aymara and 0.25 ± 0.13 Mapuche. However, Mapuche ancestry was highest in the south (40.03%) and Aymara in the north (35.61%) as expected from the historical location of these ethnic groups. We make our results available through an online app and demonstrate how it can be used to adjust for ancestry when testing association between incidence of a disease and nongenetic risk factors.

Conclusions

We have conducted the most extensive sampling, across many different cities, of current Chilean population. Ancestry varied significantly by latitude and human development. The panel of AIMs is available to the community for estimating ancestry at low cost in Chileans and other populations with similar ancestry.

The three-hybrid genetic composition of an Ecuadorian population using AIMs-InDels compared with autosomes, mitochondrial DNA and Y chromosome data

The history of Ecuador was marked by the arrival of Europeans with Africans, resulting in the mixture of Native Americans with Africans and Europeans. The present study contributes to the knowledge of the Ecuadorian mestizo population by offering information about ancestry and ethnic heterogeneity. Forty-six AIM-InDels (Ancestry Informative Insertion/Deletion Markers) were used to obtain information on 240 Ecuadorian individuals from three regions (Amazonia, the Highlands, and the Coast). As a result, the population involved a significant contribution from Native Americans (values up to 51%), followed by Europeans (values up to 33%) and Africans (values up to 13%). Furthermore, we compared the data obtained with nine previously reported scientific articles on autosomal, mitochondrial DNA and Y chromosomes. The admixture results correspond to Ecuador's historical background and vary slightly between regions.

Inferring biogeographic ancestry with compound markers of slow and fast evolving polymorphisms

Bio-geographic ancestry is an area of considerable interest in the medical genetics, anthropology and forensics. Although genome-wide panels are ideal as they provide dense genotyping data, small sets of ancestry informative marker provide a cost-effective way to investigate genetic ancestry and population structure. Here, we investigate the performance of a reduced marker set that combine different types of autosomal markers through haplotype analysis. In particular, recently described DIP-STR markers should offer the advantage of comprising both, low mutation rate Indels (DIPs), to study human history over longer time scale; and high mutation rate STRs, to trace relatively recent demographic events. In this study, we assessed the ability of an initial set of 23 DIP-STRs to distinguish major population groups using the HGDP-CEPH reference samples. The results obtained applying the STRUCTURE algorithm show that the discrimination capacity of the DIP-STRs is comparable to currently used small-scale ancestry informative markers by approaching seven major demographic groups. Yet, the DIP-STRs show an improved success rate in assigning individuals to populations of Europe and Middle East. These data show a remarkable ability of a preliminary set of 23 DIP-STR markers to infer major biogeographic origins. A novel set of DIP-STRs preselected to contain ancestry information should lead to further improvements.

The interaction between the dopamine receptor D4 (DRD4) variable number tandem repeat polymorphism and perceived peer drinking norms in adolescent alcohol use and misuse

Peer drinking norms are arguably one of the strongest correlates of adolescent drinking. Prospective studies indicate that adolescents tend to select peers based on drinking (peer selection) and their peers' drinking is associated with changes in adolescent drinking over time (peer socialization). The present study investigated whether the peer selection and socialization processes in adolescent drinking differed as a function of the dopamine receptor D4 (DRD4) variable number tandem repeat genotype in two independent prospective data sets. The first sample was 174 high school students drawn from a two-wave 6-month prospective study. The second sample was 237 college students drawn from a three-wave annual prospective study. Multigroup cross-lagged panel analyses of the high school student sample indicated stronger socialization via peer drinking norms among carriers, whereas analyses of the college student sample indicated stronger drinking-based peer selection in the junior year among carriers, compared to noncarriers. Although replication and meta-analytic synthesis are needed, these findings suggest that in part genetically determined peer selection (carriers of the DRD4 seven-repeat allele tend to associate with peers who have more favorable attitudes toward drinking and greater alcohol use) and peer socialization (carriers' subsequent drinking behaviors are more strongly associated with their peer drinking norms) may differ across adolescent developmental stages.

Inference of Ancestry in Forensic Analysis I: Autosomal Ancestry-Informative Marker Sets

An expanding choice of ancestry-informative marker single nucleotide polymorphisms (AIM-SNPs) is becoming available for the forensic user in the form of sensitive SNaPshot-based tests or in alternative single-base extension genotyping systems (e.g., Sequenom iPLEX) that can be adapted for analysis with SNaPshot. In addition, alternative ancestry-informative variation: Indels and STRs can be analyzed using direct PCR-to-CE techniques that offer the possibility to detect mixed profiles. We review the current forensically viable AIM panels, their optimized PCR multiplexes, and the population differentiation power they offer. We also describe how improved population divergence balance can be achieved with the enlarged multiplex scales of next-generation sequencing approaches to enable analysis of admixed individuals without biased estimation of co-ancestry proportions.

A rapid molecular approach for chromosomal phasing

Determining the chromosomal phase of pairs of sequence variants - the arrangement of specific alleles as haplotypes - is a routine challenge in molecular genetics. Here we describe Drop-Phase, a molecular method for quickly ascertaining the phase of pairs of DNA sequence variants (separated by 1-200 kb) without cloning or manual single-molecule dilution. In each Drop-Phase reaction, genomic DNA segments are isolated in tens of thousands of nanoliter-sized droplets together with allele-specific fluorescence probes, in a single reaction well. Physically linked alleles partition into the same droplets, revealing their chromosomal phase in the co-distribution of fluorophores across droplets. We demonstrated the accuracy of this method by phasing members of trios (revealing 100% concordance with inheritance information), and demonstrate a common clinical application by phasing CFTR alleles at genomic distances of 11-116 kb in the genomes of cystic fibrosis patients. Drop-Phase is rapid (requiring less than 4 hours), scalable (to hundreds of samples), and effective at long genomic distances (200 kb).

Atopic dermatitis increases the effect of exposure to peanut antigen in dust on peanut sensitization and likely peanut allergy

BACKGROUND

History and severity of atopic dermatitis (AD) are risk factors for peanut allergy. Recent evidence suggests that children can become sensitized to food allergens through an impaired skin barrier. Household peanut consumption, which correlates strongly with peanut protein levels in household dust, is a risk factor for peanut allergy.

OBJECTIVE

We sought to assess whether environmental peanut exposure (EPE) is a risk for peanut sensitization and allergy and whether markers of an impaired skin barrier modify this risk.

METHODS

Peanut protein in household dust (in micrograms per gram) was assessed in highly atopic children (age, 3-15 months) recruited to the Consortium of Food Allergy Research Observational Study. History and severity of AD, peanut sensitization, and likely allergy (peanut-specific IgE, ≥5 kUA/mL) were assessed at recruitment into the Consortium of Food Allergy Research study.

RESULTS

There was an exposure-response relationship between peanut protein levels in household dust and peanut skin prick test (SPT) sensitization and likely allergy. In the final multivariate model an increase in 4 log2 EPE units increased the odds of peanut SPT sensitization (1.71-fold; 95% CI, 1.13- to 2.59-fold; P = .01) and likely peanut allergy (PA; 2.10-fold; 95% CI, 1.20- to 3.67-fold; P < .01). The effect of EPE on peanut SPT sensitization was augmented in children with a history of AD (OR, 1.97; 95% CI, 1.26-3.09; P < .01) and augmented even further in children with a history of severe AD (OR, 2.41; 95% CI, 1.30-4.47; P < .01); the effect of EPE on PA was also augmented in children with a history of AD (OR, 2.34; 95% CI, 1.31-4.18; P < .01).

CONCLUSION

Exposure to peanut antigen in dust through an impaired skin barrier in atopically inflamed skin is a plausible route for peanut SPT sensitization and PA.

Applying genome-wide gene-based expression quantitative trait locus mapping to study population ancestry and pharmacogenetics

BACKGROUND

Gene-based analysis has become popular in genomic research because of its appealing biological and statistical properties compared with those of a single-locus analysis. However, only a few, if any, studies have discussed a mapping of expression quantitative trait loci (eQTL) in a gene-based framework. Neither study has discussed ancestry-informative eQTL nor investigated their roles in pharmacogenetics by integrating single nucleotide polymorphism (SNP)-based eQTL (s-eQTL) and gene-based eQTL (g-eQTL).

RESULTS

In this g-eQTL mapping study, the transcript expression levels of genes (transcript-level genes; T-genes) were correlated with the SNPs of genes (sequence-level genes; S-genes) by using a method of gene-based partial least squares (PLS). Ancestry-informative transcripts were identified using a rank-score-based multivariate association test, and ancestry-informative eQTL were identified using Fisher's exact test. Furthermore, key ancestry-predictive eQTL were selected in a flexible discriminant analysis. We analyzed SNPs and gene expression of 210 independent people of African-, Asian- and European-descent. We identified numerous cis- and trans-acting g-eQTL and s-eQTL for each population by using PLS. We observed ancestry information enriched in eQTL. Furthermore, we identified 2 ancestry-informative eQTL associated with adverse drug reactions and/or drug response. Rs1045642, located on MDR1, is an ancestry-informative eQTL (P = 2.13E-13, using Fisher's exact test) associated with adverse drug reactions to amitriptyline and nortriptyline and drug responses to morphine. Rs20455, located in KIF6, is an ancestry-informative eQTL (P = 2.76E-23, using Fisher's exact test) associated with the response to statin drugs (e.g., pravastatin and atorvastatin). The ancestry-informative eQTL of drug biotransformation genes were also observed; cross-population cis-acting expression regulators included SPG7, TAP2, SLC7A7, and CYP4F2. Finally, we also identified key ancestry-predictive eQTL and established classification models with promising training and testing accuracies in separating samples from close populations.

CONCLUSIONS

In summary, we developed a gene-based PLS procedure and a SAS macro for identifying g-eQTL and s-eQTL. We established data archives of eQTL for global populations. The program and data archives are accessible at http://www.stat.sinica.edu.tw/hsinchou/genetics/eQTL/HapMapII.htm. Finally, the results from our investigations regarding the interrelationship between eQTL, ancestry information, and pharmacodynamics provide rich resources for future eQTL studies and practical applications in population genetics and medical genetics.

An overview of STRUCTURE: applications, parameter settings, and supporting software

Objectives: We present an up-to-date review of STRUCTURE software: one of the most widely used population analysis tools that allows researchers to assess patterns of genetic structure in a set of samples. STRUCTURE can identify subsets of the whole sample by detecting allele frequency differences within the data and can assign individuals to those sub-populations based on analysis of likelihoods. The review covers STRUCTURE's most commonly used ancestry and frequency models, plus an overview of the main applications of the software in human genetics including case-control association studies (CCAS), population genetics, and forensic analysis. The review is accompanied by supplementary material providing a step-by-step guide to running STRUCTURE.

Methods: With reference to a worked example, we explore the effects of changing the principal analysis parameters on STRUCTURE results when analyzing a uniform set of human genetic data. Use of the supporting software: CLUMPP and distruct is detailed and we provide an overview and worked example of STRAT software, applicable to CCAS.

Conclusion: The guide offers a simplified view of how STRUCTURE, CLUMPP, distruct, and STRAT can be applied to provide researchers with an informed choice of parameter settings and supporting software when analyzing their own genetic data.

Integrative analysis of single nucleotide polymorphisms and gene expression efficiently distinguishes samples from closely related ethnic populations

Background

Ancestry informative markers (AIMs) are a type of genetic marker that is informative for tracing the ancestral ethnicity of individuals. Application of AIMs has gained substantial attention in population genetics, forensic sciences, and medical genetics. Single nucleotide polymorphisms (SNPs), the materials of AIMs, are useful for classifying individuals from distinct continental origins but cannot discriminate individuals with subtle genetic differences from closely related ancestral lineages. Proof-of-principle studies have shown that gene expression (GE) also is a heritable human variation that exhibits differential intensity distributions among ethnic groups. GE supplies ethnic information supplemental to SNPs; this motivated us to integrate SNP and GE markers to construct AIM panels with a reduced number of required markers and provide high accuracy in ancestry inference. Few studies in the literature have considered GE in this aspect, and none have integrated SNP and GE markers to aid classification of samples from closely related ethnic populations.

Results

We integrated a forward variable selection procedure into flexible discriminant analysis to identify key SNP and/or GE markers with the highest cross-validation prediction accuracy. By analyzing genome-wide SNP and/or GE markers in 210 independent samples from four ethnic groups in the HapMap II Project, we found that average testing accuracies for a majority of classification analyses were quite high, except for SNP-only analyses that were performed to discern study samples containing individuals from two close Asian populations. The average testing accuracies ranged from 0.53 to 0.79 for SNP-only analyses and increased to around 0.90 when GE markers were integrated together with SNP markers for the classification of samples from closely related Asian populations. Compared to GE-only analyses, integrative analyses of SNP and GE markers showed comparable testing accuracies and a reduced number of selected markers in AIM panels.

Conclusions

Integrative analysis of SNP and GE markers provides high-accuracy and/or cost-effective classification results for assigning samples from closely related or distantly related ancestral lineages to their original ancestral populations. User-friendly BIASLESS (Biomarkers Identification and Samples Subdivision) software was developed as an efficient tool for selecting key SNP and/or GE markers and then building models for sample subdivision. BIASLESS was programmed in R and R-GUI and is available online at http://www.stat.sinica.edu.tw/hsinchou/genetics/prediction/BIASLESS.htm.

Education, genetic ancestry, and blood pressure in African Americans and Whites

OBJECTIVES

We assessed the relative roles of education and genetic ancestry in predicting blood pressure (BP) within African Americans and explored the association between education and BP across racial groups.

METHODS

We used t tests and linear regressions to examine the associations of genetic ancestry, estimated from a genomewide set of autosomal markers, and education with BP variation among African Americans in the Family Blood Pressure Program. We also performed linear regressions in self-identified African Americans and Whites to explore the association of education with BP across racial groups.

RESULTS

Education, but not genetic ancestry, significantly predicted BP variation in the African American subsample (b=-0.51 mm Hg per year additional education; P=.001). Although education was inversely associated with BP in the total population, within-group analyses showed that education remained a significant predictor of BP only among the African Americans. We found a significant interaction (b=3.20; P=.006) between education and self-identified race in predicting BP.

CONCLUSIONS

Racial disparities in BP may be better explained by differences in education than by genetic ancestry. Future studies of ancestry and disease should include measures of the social environment.

Ancestry informative marker set for han chinese population

The population of Han Chinese is ∼1.226 billion people. Genetic heterogeneity between northern Han Chinese (N-Han) and southern Han Chinese (S-Han) has been demonstrated by recent genome-wide studies. As an initial step toward health disparities and personalized medicine in Chinese population, this study developed a set of ancestry informative markers (AIM) for Han Chinese population.

Straightforward inference of ancestry and admixture proportions through ancestry-informative insertion deletion multiplexing

Ancestry-informative markers (AIMs) show high allele frequency divergence between different ancestral or geographically distant populations. These genetic markers are especially useful in inferring the likely ancestral origin of an individual or estimating the apportionment of ancestry components in admixed individuals or populations. The study of AIMs is of great interest in clinical genetics research, particularly to detect and correct for population substructure effects in case-control association studies, but also in population and forensic genetics studies. This work presents a set of 46 ancestry-informative insertion deletion polymorphisms selected to efficiently measure population admixture proportions of four different origins (African, European, East Asian and Native American). All markers are analyzed in short fragments (under 230 basepairs) through a single PCR followed by capillary electrophoresis (CE) allowing a very simple one tube PCR-to-CE approach. HGDP-CEPH diversity panel samples from the four groups, together with Oceanians, were genotyped to evaluate the efficiency of the assay in clustering populations from different continental origins and to establish reference databases. In addition, other populations from diverse geographic origins were tested using the HGDP-CEPH samples as reference data. The results revealed that the AIM-INDEL set developed is highly efficient at inferring the ancestry of individuals and provides good estimates of ancestry proportions at the population level. In conclusion, we have optimized the multiplexed genotyping of 46 AIM-INDELs in a simple and informative assay, enabling a more straightforward alternative to the commonly available AIM-SNP typing methods dependent on complex, multi-step protocols or implementation of large-scale genotyping technologies.