Biogeographical Ancestry Analyses Using the ForenSeqTM DNA Signature Prep Kit and Multiple Prediction Tools

The inference of biogeographical ancestry (BGA) can assist in police investigations of serious crime cases and help to identify missing people and victims of mass disasters. In this study, we evaluated the typing performance of 56 ancestry-informative SNPs in 177 samples using the ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system. Furthermore, we compared the prediction accuracy of the tools Universal Analysis Software v1.2 (UAS), the FROG-kb, and GenoGeographer when inferring the ancestry of 503 Europeans, 22 non-Europeans, and 5 individuals with co-ancestry. The kit was highly sensitive with complete aiSNP profiles in samples with as low as 250pg input DNA. However, in line with others, we observed low read depth and occasional drop-out in some SNPs. Therefore, we suggest not using less than the recommended 1ng of input DNA. FROG-kb and GenoGeographer accurately predicted both Europeans (99.6% and 91.8% correct, respectively) and non-Europeans (95.4% and 90.9% correct, respectively). The UAS was highly accurate when predicting Europeans (96.0% correct) but performed poorer when predicting non-Europeans (40.9% correct). None of the tools were able to correctly predict individuals with co-ancestry. Our study demonstrates that the use of multiple prediction tools will increase the prediction accuracy of BGA inference in forensic casework.

Pharmacogenomic implications of the differential distribution of CYP3A5 metabolic phenotypes among Latin American populations

This study shows that the distribution of CYP3A5 alleles (*1, *3, *6 and *7) and genotype-predicted CYP3A5 phenotypes vary significantly across Latin American cohorts (Brazilians and the One Thousand Genomes Admixed American superpopulation), as well as among subcohorts comprising individuals with the highest proportions of Native, European or sub-Saharan African ancestry. Differences in biogeographical ancestry across the study groups are the likely explanation for these results. The differential distribution of CYP3A5 phenotypes has major pharmacogenomic implications, affecting the proportion of individuals carrying high risk CYP3A5 phenotypes for the immunosuppressant tacrolimus and the number of patients that would need to be genotyped to prevent acute rejection in kidney transplant recipients under tacrolimus treatment.

Pharmacogenomic implications of the differential distribution of CYP2C9 metabolic phenotypes among Latin American populations

The CYP2C9 gene encodes the major drug metabolism enzyme CYP2C9. This gene is highly polymorphic, and no-function (CYP2C9*3) plus decreased function (CYP2C9*2, *5, *8 and *11) star alleles (haplotypes) are commonly used to predict CYP2C9 metabolic phenotypes. This study explores the pharmacogenomic implications of the differential distribution of genotype-predicted CYP2C9 phenotypes across Latin American populations. Data from 1,404 individuals from the South American countries Brazil, Colombia and Peru, from Puerto Rico in the Caribbean and from persons with Mexican ancestry living in North America were analysed. The results showed that the distribution of CYP2C9 alleles and diplotypes, and diplotype-predicted CYP2C9 phenotypes vary significantly across the distinct country cohorts, as well as among self-identified White, Brown and Black Brazilians. Differences in average proportions of biogeographical ancestry across the study groups, especially Native American and African ancestry, are the likely explanation for these results. The differential distribution of genotype-predicted CYP2C9 phenotypes has potentially clinically-relevant pharmacogenomic implications, through its influence on the proportion of individuals at high risk for adverse response to medications that are CYP2C9 substrates, the proportion on individuals with CPIC therapeutic recommendations for dosing and choice of nonsteroidal antinflammatory drugs (NSAIDs) and the number of individuals that need to be genotyped in order to prevent adverse effects of NSAIDs. Collectively, these findings are likely to impact the perceived benefits, cost-effectiveness and clinical adoption of pharmacogenomic screening for drugs that are predominantly metabolized by CYP2C9.

Pharmacogenetic differentiation across Latin America

Aim: To explore the pharmacogenetic differentiation across Latin American populations, using the fixation index statistics (F_ST). Materials & methods: F_ST analyses were applied to 1519 pharmacogenetic markers in the 1000 Genomes Admixed American superpopulation (1KG_AMR) and an admixed Brazilian sample. Results: Allele-specific F_ST values for the overall cohort point to little overall pharmacogenetic differentiation (average F_ST = 0.017); however, moderate differentiation (F_ST = 0.05-0.15) was observed for 83 markers, while large differentiation (F_ST = 0.15-0.25) was restricted to three markers. Pairwise F_ST analysis identified three markers with very large differentiation (F_ST >0.25). Conclusion: The present study verifies and extends previous reports of little overall pharmacogenetic divergence across Latin America, although a number of markers display substantial differentiation.

Evaluation of the Precision of Ancestry Inferences in South American Admixed Populations

Ancestry informative markers (AIMs) are used in forensic genetics to infer biogeographical ancestry (BGA) of individuals and may also have a prominent role in future police and identification investigations. In the last few years, many studies have been published reporting new AIM sets. These sets include markers (usually around 100 or less) selected with different purposes and different population resolutions. Regardless of the ability of these sets to separate populations from different continents or regions, the uncertainty associated with the estimates provided by these panels and their capacity to accurately report the different ancestral contributions in individuals of admixed populations has rarely been investigated. This issue is addressed in this study by evaluating different AIM sets. Ancestry inference was carried out in admixed South American populations, both at population and individual levels. The results of ancestry inferences using AIM sets with different numbers of markers among admixed reference populations were compared. To evaluate the performance of the different ancestry panels at the individual level, expected and observed estimates among families and their offspring were compared, considering that (1) the apportionment of ancestry in the offspring should be closer to the average ancestry of the parents, and (2) full siblings should present similar ancestry values. The results obtained illustrate the importance of having a good balance/compromise between not only the number of markers and their ability to differentiate ancestral populations, but also a balanced differentiation among reference groups, to obtain more precise values of genetic ancestry. This work also highlights the importance of estimating errors associated with the use of a limited number of markers. We demonstrate that although these errors have a moderate effect at the population level, they may have an important impact at the individual level. Considering that many AIM-sets are being described for inferences at the individual level and not at the population level, e.g., in association studies or the determination of a suspect's BGA, the results of this work point to the need of a more careful evaluation of the uncertainty associated with the ancestry estimates in admixed populations, when small AIM-sets are used.

Ancestry patterns inferred from massive RNA-seq data

There is a growing body of evidence suggesting that patterns of gene expression vary within and between human populations. However, the impact of this variation in human diseases has been poorly explored, in part owing to the lack of a standardized protocol to estimate biogeographical ancestry from gene expression studies. Here we examine several studies that provide new solid evidence indicating that the ancestral background of individuals impacts gene expression patterns. Next, we test a procedure to infer genetic ancestry from RNA-seq data in 25 data sets where information on ethnicity was reported. Genome data of reference continental populations retrieved from The 1000 Genomes Project were used for comparisons. Remarkably, only eight out of 25 data sets passed FastQC default filters. We demonstrate that, for these eight population sets, the ancestral background of donors could be inferred very efficiently, even in data sets including samples with complex patterns of admixture (e.g., American-admixed populations). For most of the gene expression data sets of suboptimal quality, ancestral inference yielded odd patterns. The present study thus brings a cautionary note for gene expression studies highlighting the importance to control for the potential confounding effect of ancestral genetic background.

African biogeographical ancestry, atopic and non-atopic asthma and atopy: A study in Latin American children

BACKGROUND

Genetic variants underlying African ancestry have been suggested be implicated in the ethnic-racial inequalities reported for asthma and allergies.

OBJECTIVES

To investigate the association between individual African ancestry and asthma symptoms, atopic and non-atopic asthma, and atopy in children.

METHODS

A cross-sectional study encompassing 1190 individuals was conducted. African biogeographic ancestry was estimated using 370 539 genome-wide SNPs. Serum levels of specific IgE were measured, and skin prick test (SPT) performed for the most common local aeroallergens. Information on asthma symptoms was obtained by applying the International Study of Allergy and Asthma in Childhood questionnaire. The associations between the proportion of individual African ancestry and the outcomes investigated were analyzed through multivariate models adjusted for socio-environmental variables, infections markers, and psychosocial factors.

RESULTS

Each 20% increase in the proportion of African ancestry was negatively associated with SPT reactivity (OR: 0.79, 95%CI: 0.66-0.96) and positively associated with asthma symptoms in non-atopic individuals (OR: 1.40, 95%CI: 1.03-1.89). We estimated that socioeconomic status and number of infections mediated 28.4% of the effect of African ancestry on SPT reactivity, while 20.2% of the effect on non-atopic asthma was explained by socioeconomic status and behavioral problems in children.

CONCLUSIONS

The negative association observed between African ancestry and atopy is most probably explained by unobserved environmental or social factors that covariate with ancestry. For non-atopic asthma, in turn, putative genetic variants of risk underlying African ancestry may play some role.

Influence of pharmacogenetic polymorphisms and demographic variables on metformin pharmacokinetics in an admixed Brazilian cohort

AIMS

To identify pharmacogenetic and demographic variables that influence the systemic exposure to metformin in an admixed Brazilian cohort.

METHODS

The extreme discordant phenotype was used to select 106 data sets from nine metformin bioequivalence trials, comprising 256 healthy adults. Eleven single-nucleotide polymorphisms in SLC22A1, SLC22A2, SLC47A1 SLC47A2 and in transcription factor SP1 were genotyped and a validated panel of ancestry informative markers was used to estimate the individual proportions of biogeographical ancestry. Two-step (univariate followed by multivariate) regression modelling was developed to identify covariates associated with systemic exposure to metformin, accessed by the area under the plasma concentration-time curve, between 0 and 48 h (AUC_0-48h ), after single oral doses of metformin (500 or 1000 mg).

RESULTS

The individual proportions of African, Amerindian and European ancestry varied widely, as anticipated from the structure of the Brazilian population The dose-adjusted, log-transformed AUC_0-48h 's (ng h ml^-1  mg^-1 ) differed largely in the two groups at the opposite ends of the distribution histogram, namely 0.82, 0.79-0.85 and 1.08, 1.06-1.11 (mean, 95% confidence interval; P = 6.10^-26 , t test). Multivariate modelling revealed that metformin AUC_0-48h increased with age, food and carriage of rs12208357 in SLC22A1 but was inversely associated with body surface area and individual proportions of African ancestry.

CONCLUSIONS

A pharmacogenetic marker in OCT1 (SLC22A1 rs12208357), combined with demographic covariates (age, body surface area and individual proportion of African ancestry) and a food effect explained 29.7% of the variability in metformin AUC_0-48h .

Pharmacogenomic Diversity among Brazilians: Influence of Ancestry, Self-Reported Color, and Geographical Origin

BY VIRTUE OF BEING THE PRODUCT OF THE GENETIC ADMIXTURE OF THREE ANCESTRAL ROOTS: Europeans, Africans, and Amerindians, the present-day Brazilian population displays very high levels of genomic diversity, which have important pharmacogenetic/-genomic (PGx) implications. Recognition of this fact has prompted the creation of the Brazilian Pharmacogenomics Network (Refargen), a nationwide consortium of research groups, with the mission to provide leadership in PGx research and education in Brazil, with a population heath impact. Here, we present original data and review published results from a Refargen comprehensive study of the distribution of PGx polymorphisms in a representative cohort of the Brazilian people, comprising 1,034 healthy, unrelated adults, self-identified as white, brown, or black, according to the Color categories adopted by the Brazilian Census. Multinomial log-linear regression analysis was applied to infer the statistical association between allele, genotype, and haplotype distributions among Brazilians (response variables) and self-reported Color, geographical region, and biogeographical ancestry (explanatory variables), whereas Wright's F(ST) statistics was used to assess the extent of PGx divergence among different strata of the Brazilian population. Major PGx implications of these findings are: first, extrapolation of data from relatively well-defined ethnic groups is clearly not applicable to the majority of Brazilians; second, the frequency distribution of polymorphisms in several pharmacogenes of clinical relevance (e.g., ABCB1, CYP3A5, CYP2C9, VKORC) varies continuously among Brazilians and is not captured by race/Color self-identification; third, the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of PGx studies in order to avoid spurious conclusions based on improper matching of study cohorts.

Pharmacogenetics in the brazilian population

Brazil is the fifth largest country in the world and its present population, in excess of 190;million, is highly heterogeneous, as a result of centuries of admixture between Amerindians, Europeans, and Sub-Saharan Africans. The estimated individual proportions of biogeographical ancestry vary widely and continuously among Brazilians: most individuals, irrespective of self-identification as White, Brown or Black - the major categories of the Brazilian Census "race/color" system - have significant degrees of European and African ancestry, while a sizeable number display also Amerindian ancestry. These features have important pharmacogenetic (PGx) implications: first, extrapolation of PGx data from relatively well-defined ethnic groups is clearly not applicable to the majority of Brazilians; second, the frequency distribution of polymorphisms in pharmacogenes (e.g., CYP3A5, CYP2C9, GSTM1, ABCB1, GSTM3, VKORC, etc) varies continuously among Brazilians and is not captured by race/color self-identification; third, the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of PGx studies in order to avoid spurious conclusions based on improper matching of study cohorts. The peculiarities of PGx in Brazilians are illustrated with data for different therapeutic groups, such as anticoagulants, HIV protease inhibitors and non-steroidal antinflammatory drugs, and the challenges and advantages created by population admixture for the study and implementation of PGx are discussed. PGx data for Amerindian groups and Brazilian-born, first-generation Japanese are presented to illustrate the rich diversity of the Brazilian population. Finally, I introduce the reader to the Brazilian Pharmacogenetic Network or Refargen, a nation-wide consortium of research groups, with the mission to provide leadership in PGx research and education in Brazil, with a population health impact.