Human genetic admixture

Using Portuguese BRCA pathogenic variation as a model to study the impact of human admixture on human health

BACKGROUND

Admixture occurs between different ethnic human populations. The global colonization in recent centuries by Europeans led to the most significant admixture in human history. While admixture may enhance genetic diversity for better fitness, it may also impact on human health by transmitting genetic variants for disease susceptibility in the admixture population. The admixture by Portuguese global exploration initiated in the 15th century has reached over 20 million of Portuguese-heritage population worldwide. It provides a valuable model to study the impact of admixture on human health. BRCA1 and BRCA2 (BRCA) are two of the important tumor suppressor genes. The pathogenic variation (PV) in BRCA is well determined to cause high risk of hereditary breast and ovarian cancer. Tracing the distribution of Portuguese BRCA PV in Portuguese-heritage population will help to understand the impact of admixture on cancer susceptibility in modern humans. In this study, we analyzed the distribution of the Portuguese-originated BRCA variation in Brazilian population, which has high degree Portuguese-heritage.

METHODS

By comprehensive data mining, standardization and annotation, we generated a Portuguese-derived BRCA variation dataset and a Brazilian-derived BRCA variation dataset. We compared the two BRCA variation datasets to identify the BRCA variants shared between the two populations.

RESULTS

The Portuguese-derived BRCA variation dataset consists of 220 BRCA variants including 78 PVs from 11,482 Portuguese cancer patients, 93 (42.2%) in BRCA1 and 127 (57.7%) in BRCA2. Of the 556 Portuguese BRCA PV carriers carrying the 78 PVs, 331 (59.5%) carried the three Portuguese-BRCA founder PVs of BRCA1 c.2037delinsCC, BRCA1 c.3331_3334del and BRCA2 c.156_157insAlu. The Brazilian-derived BRCA variation dataset consists of 255 BRCA PVs from 7,711 cancer patients, 136 (53.3%) in BRCA1 and 119 (46.6%) in BRCA2. We developed an open database named dbBRCA-Portuguese ( https://genemutation.fhs.um.edu.mo/dbbrca-portuguese/ ) and an open database named dbBRCA-Brazilian ( https://genemutation.fhs.um.edu.mo/dbbrca-brazilian ) to host the BRCA variation data from Portuguese and Brazilian populations. We compared the BRCA PV datasets between Portuguese and Brazilian populations, and identified 29 Portuguese-specific BRCA PVs shared between Portuguese and Brazilian populations, 14 in BRCA1 including the Portuguese founder BRCA1 c.3331_3334del and BRCA1 c.2037delinsCC, and 15 in BRCA2 including the Portuguese founder BRCA2 c.156_157insAlu. Searching the 78 Portuguese BRCA PVs in over 5,000 ancient human genomes identified evolution origin for only 8 PVs in Europeans dated between 37,470 and 3,818 years before present, confirming the Portuguese-specificity of Portuguese BRCA PVs; comparing the 78 Portuguese BRCA PVs Portuguese, 255 Brazilian BRCA PVs, and 134 African BRCA PVs showed little overlapping, ruling out the possibility that the BRCA PVs shared between Portuguese and Brazilian may also be contributed by African.

CONCLUSION

Our study provides evidence that the admixture in recent human history contributed to cancer susceptibility in modern humans.

Genomic ancestry and cancer among Latin Americans

Latin American populations, characterized by intricate admixture patterns resulting from the intermingling of ancestries from European, Native American (NA) Asian, and African ancestries which result in a vast and complex genetic landscape, harboring unique combinations of novel variants. This genetic diversity not only poses challenges in traditional population genetics methods but also opens avenues for a deeper understanding of its implications in health. In cancer, the interplay between genetic ancestry, lifestyle factors, and healthcare disparities adds a layer of complexity to the varying incidence and mortality rates observed across different Latin American subpopulations. This complex interdependence has been unveiled through numerous studies, whether conducted on Latin American patients residing on the continent or abroad, revealing discernible differences in germline composition that influence divergent disease phenotypes such as higher incidence of Luminal B and Her2 breast tumors, EGFR and KRAS mutated lung adenocarcinomas in addition to an enrichment in BRCA1/2 pathogenic variants and a higher than expected prevalence of variants in colorectal cancer associated genes such as APC and MLH1. In prostate cancer novel risk variants have also been solely identified in Latin American populations. Due to the complexity of genetic divergence, inputs from each individual ancestry seem to carry independent contributions that interplay in the development of these complex disease phenotypes. By understanding these unique population characteristics, genomic ancestries hold a promising avenue for tailoring prognostic assessments and optimizing responses to oncological interventions.

TwinsMX: Exploring the Genetic and Environmental Influences on Health Traits in the Mexican Population

TwinsMX registry is a national research initiative in Mexico that aims to understand the complex interplay between genetics and environment in shaping physical and mental health traits among the country's population. With a multidisciplinary approach, TwinsMX aims to advance our knowledge of the genetic and environmental mechanisms underlying ethnic variations in complex traits and diseases, including behavioral, psychometric, anthropometric, metabolic, cardiovascular and mental disorders. With information gathered from over 2800 twins, this article updates the prevalence of several complex traits; and describes the advances and novel ideas we have implemented such as magnetic resonance imaging. The future expansion of the TwinsMX registry will enhance our comprehension of the intricate interplay between genetics and environment in shaping health and disease in the Mexican population. Overall, this report describes the progress in the building of a solid database that will allow the study of complex traits in the Mexican population, valuable not only for our consortium, but also for the worldwide scientific community, by providing new insights of understudied genetically admixed populations.

Genetic evidence for a single founding population of the Lakshadweep Islands

Lakshadweep is an archipelago of 36 islands located in the Southeastern Arabian Sea. In the absence of a detailed archaeological record, the human settlement timing of this island is vague. Previous genetic studies on haploid DNA makers suggested sex-biased ancestry linked to North and South Indian populations. Maternal ancestry suggested a closer link with the Southern Indian, while paternal ancestry advocated the Northern Indian genetic affinity. Since the haploid markers are more sensitive to genetic drift, which is evident for the Island populations, we have used the biparental high-resolution single-nucleotide polymorphic markers to reconstruct the population history of Lakshadweep Islands.  Using the fine-scaled analyses, we specifically focused on (A) the ancestry components of Lakshadweep Islands populations; (B) their relation with East, West Eurasia and South Asia; (C) the number of founding lineages and (D) the putative migration from Northern India as the paternal ancestry was closer to the North Indian populations. Our analysis of ancestry components confirmed relatively higher North Indian ancestry among the Lakshadweep population. These populations are closely related to the South Asian populations. We identified mainly a single founding population for these Islands, geographically divided into two sub-clusters. By examining the population's genetic composition and analysing the gene flow from different source populations, this study contributes to our understanding of Lakshadweep Island's evolutionary history and population dynamics. These findings shed light on the complex interactions between ethnic groups and their genetic contributions in making the Lakshadweep population.

Association between the Number of Days/Week of Different Levels of Physical Activity and Chronic Pain in People of Different Races: A Mendelian Randomization Study

OBJECTIVE

Regular physical activity is beneficial for health, but the effect of the number of days/week of physical activity on chronic pain (CP) remains unclear, so we used a two-sample Mendelian randomization (MR) analysis to explore the relationship between the number of days/weeks of different levels of physical activity and chronic pain in people of different races.

METHODS

We obtained summary data from genome-wide association studies (GWASs) on the number of days/week of physical activity and multisite chronic pain in European, South Asian, East Asian, Middle Eastern, and African American populations. The single-nucleotide polymorphisms (SNPs) of the exposed data were visualized with a Manhattan plot via the R program. MR analysis was performed by the MR-Base platform.

RESULTS

The results indicated that a higher number of days/week with ≥10 min of walking protects against CP in African American and Afro-Caribbean populations (inverse-variance weighting, IVW p < 0.05) but has little effect on people of different races (IVW p > 0.05). A higher number of days/week with ≥10 min of moderate physical activity increased the risk of CP in European and South Asia (IVW p < 0.05) but had little effect on people of different races (IVW p > 0.05). The number of days/week of ≥10 min of vigorous physical activity increased the risk of CP in Europeans (IVW p < 0.05) and protected against CP in African Americans and Afro-Caribbeans (IVW p < 0.05).

CONCLUSIONS

A higher number of days/week of moderate and vigorous physical activity increased the risk of CP in Europeans; however, a higher number of days/week of walking and vigorous physical activity may protect against CP in African American and Afro-Caribbean individuals.

The epistemic harms of direct-to-consumer genetic tests

In this paper, I provide an epistemic evaluation of the harms that result from the widespread marketing of direct-to-consumer (DTC) genetic tests. While genetic tests are a valuable accessory diagnostic tool when ordered by a medical practitioner, there are different implications when they are sold directly to consumers. I aim to show that there are both epistemic and non-epistemic harms associated with the widespread commoditization of DTC genetic tests. I argue that the epistemic harms produced by DTC genetic tests have been disregarded in discussions on the topic. Drawing on the notion of contributory epistemic injustices, I highlight two pertinent epistemic harms: (1) a failure to uptake an individual's articulations about their identity and (2) the presiding reductionist framework dismisses useful hermeneutical resources. I then propose ways to mitigate these harms.

R. EP, Moreira MV, Stahlke EVR, Possuelo LG, Rossetti MLR, Rabahi MF, Silva LFM, Leme PA, Woods WJ, Nobre ML, de Oliveira MLWDR, Narahashi K, Cavalcanti M, Suffys PN, Boukouvala S, Gallo MEN, Santos AR. Human N-acetyltransferase 2 (NAT2) gene variability in Brazilian populations from different geographical areas

Introduction: Several polymorphisms altering the NAT2 activity have already been identified. The geographical distribution of NAT2 variants has been extensively studied and has been demonstrated to vary significantly among different ethnic population. Here, we describe the genetic variability of human N-acetyltransferase 2 (NAT2) gene and the predominant genotype-deduced acetylation profiles of Brazilians. Methods: A total of 964 individuals, from five geographical different regions, were genotyped for NAT2 by sequencing the entire coding exon. Results: Twenty-three previously described NAT2 single nucleotide polymorphisms (SNPs) were identified, including the seven most common ones globally (c.191G>A, c.282C>T, c.341T>C, c.481C>T, c.590G>A, c.803A>G and c.857G>A). The main allelic groups were NAT2*5 (36%) and NAT2*6 (18.2%), followed to the reference allele NAT2*4 (20.4%). Combined into genotypes, the most prevalent allelic groups were NAT2*5/*5 (14.6%), NAT2*5/*6 (11.9%) and NAT2*6/*6 (6.2%). The genotype deduced NAT2 slow acetylation phenotype was predominant but showed significant variability between geographical regions. The prevalence of slow acetylation phenotype was higher in the Northeast, North and Midwest (51.3%, 45.5% and 41.5%, respectively) of the country. In the Southeast, the intermediate acetylation phenotype was the most prevalent (40.3%) and, in the South, the prevalence of rapid acetylation phenotype was significantly higher (36.7%), when compared to other Brazilian states (p < 0.0001). Comparison of the predicted acetylation profile among regions showed homogeneity among the North and Northeast but was significantly different when compared to the Southeast (p = 0.0396). The Southern region was significantly different from all other regions (p < 0.0001). Discussion: This study contributes not only to current knowledge of the NAT2 population genetic diversity in different geographical regions of Brazil, but also to the reconstruction of a more accurate phenotypic picture of NAT2 acetylator profiles in those regions.

Getting it right: Teaching undergraduate biology to undermine racial essentialism

How we teach human genetics matters for social equity. The biology curriculum appears to be a crucial locus of intervention for either reinforcing or undermining students' racial essentialist views. The Mendelian genetic models dominating textbooks, particularly in combination with racially inflected language sometimes used when teaching about monogenic disorders, can increase middle and high school students' racial essentialism and opposition to policies to increase equity. These findings are of particular concern given the increasing spread of racist misinformation online and the misappropriation of human genomics research by white supremacists, who take advantage of low levels of genetics literacy in the general public. Encouragingly, however, teaching updated information about the geographical distribution of human genetic variation and the complex, multifactorial basis of most human traits, reduces students' endorsement of racial essentialism. The genetics curriculum is therefore a key tool in combating misinformation and scientific racism. Here, we describe a framework and example teaching materials for teaching students key concepts in genetics, human evolutionary history, and human phenotypic variation at the undergraduate level. This framework can be flexibly applied in biology and anthropology classes and adjusted based on time availability. Our goal is to provide undergraduate-level instructors with varying levels of expertise with a set of evidence-informed tools for teaching human genetics to combat scientific racism, including an evolving set of instructional resources, as well as learning goals and pedagogical approaches. Resources can be found at https://noto.li/YIlhZ5. Additionally, we hope to generate conversation about integrating modern genetics into the undergraduate curriculum, in light of recent findings about the risks and opportunities associated with teaching genetics.

Demographic modeling of admixed Latin American populations from whole genomes

Demographic models of Latin American populations often fail to fully capture their complex evolutionary history, which has been shaped by both recent admixture and deeper-in-time demographic events. To address this gap, we used high-coverage whole-genome data from Indigenous American ancestries in present-day Mexico and existing genomes from across Latin America to infer multiple demographic models that capture the impact of different timescales on genetic diversity. Our approach, which combines analyses of allele frequencies and ancestry tract length distributions, represents a significant improvement over current models in predicting patterns of genetic variation in admixed Latin American populations. We jointly modeled the contribution of European, African, East Asian, and Indigenous American ancestries into present-day Latin American populations. We infer that the ancestors of Indigenous Americans and East Asians diverged ∼30 thousand years ago, and we characterize genetic contributions of recent migrations from East and Southeast Asia to Peru and Mexico. Our inferred demographic histories are consistent across different genomic regions and annotations, suggesting that our inferences are robust to the potential effects of linked selection. In conjunction with published distributions of fitness effects for new nonsynonymous mutations in humans, we show in large-scale simulations that our models recover important features of both neutral and deleterious variation. By providing a more realistic framework for understanding the evolutionary history of Latin American populations, our models can help address the historical under-representation of admixed groups in genomics research and can be a valuable resource for future studies of populations with complex admixture and demographic histories.

Strategies for the Genomic Analysis of Admixed Populations

Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.

On the number of genealogical ancestors tracing to the source groups of an admixed population

Members of genetically admixed populations possess ancestry from multiple source groups, and studies of human genetic admixture frequently estimate ancestry components corresponding to fractions of individual genomes that trace to specific ancestral populations. However, the same numerical ancestry fraction can represent a wide array of admixture scenarios within an individual's genealogy. Using a mechanistic model of admixture, we consider admixture genealogically: how many ancestors from the source populations does the admixture represent? We consider African-Americans, for whom continent-level estimates produce a 75-85% value for African ancestry on average and 15-25% for European ancestry. Genetic studies together with key features of African-American demographic history suggest ranges for parameters of a simple three-epoch model. Considering parameter sets compatible with estimates of current ancestry levels, we infer that if all genealogical lines of a random African-American born during 1960-1965 are traced back until they reach members of source populations, the mean over parameter sets of the expected number of genealogical lines terminating with African individuals is 314 (interquartile range 240-376), and the mean of the expected number terminating in Europeans is 51 (interquartile range 32-69). Across discrete generations, the peak number of African genealogical ancestors occurs in birth cohorts from the early 1700s, and the probability exceeds 50% that at least one European ancestor was born more recently than 1835. Our genealogical perspective can contribute to further understanding the admixture processes that underlie admixed populations. For African-Americans, the results provide insight both on how many of the ancestors of a typical African-American might have been forcibly displaced in the Transatlantic Slave Trade and on how many separate European admixture events might exist in a typical African-American genealogy.

Impact of cross-ancestry genetic architecture on GWASs in admixed populations

Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.

The Impact of Modern Admixture on Archaic Human Ancestry in Human Populations

Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, which have shaped genetic ancestry in modern humans. For example, populations in the Americas are often mosaics of different ancestries due to recent admixture events as part of European colonization. Admixed individuals also often have introgressed DNA from Neanderthals and Denisovans that may have come from multiple ancestral populations, which may affect how archaic ancestry is distributed across an admixed genome. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individual's archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight increase of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.

Association and Interaction of Genetics and Area-Level Socioeconomic Factors on the Prevalence of Type 2 Diabetes and Obesity

OBJECTIVE

Quantify the impact of genetic and socioeconomic factors on risk of type 2 diabetes (T2D) and obesity.

RESEARCH DESIGN AND METHODS

Among participants in the Mass General Brigham Biobank (MGBB) and UK Biobank (UKB), we used logistic regression models to calculate cross-sectional odds of T2D and obesity using 1) polygenic risk scores for T2D and BMI and 2) area-level socioeconomic risk (educational attainment) measures. The primary analysis included 26,737 participants of European genetic ancestry in MGBB with replication in UKB (N = 223,843), as well as in participants of non-European ancestry (MGBB N = 3,468; UKB N = 7,459).

RESULTS

The area-level socioeconomic measure most strongly associated with both T2D and obesity was percent without a college degree, and associations with disease prevalence were independent of genetic risk (P < 0.001 for each). Moving from lowest to highest quintiles of combined genetic and socioeconomic burden more than tripled T2D (3.1% to 22.2%) and obesity (20.9% to 69.0%) prevalence. Favorable socioeconomic risk was associated with lower disease prevalence, even in those with highest genetic risk (T2D 13.0% vs. 22.2%, obesity 53.6% vs. 69.0% in lowest vs. highest socioeconomic risk quintiles). Additive effects of genetic and socioeconomic factors accounted for 13.2% and 16.7% of T2D and obesity prevalence, respectively, explained by these models. Findings were replicated in independent European and non-European ancestral populations.

CONCLUSIONS

Genetic and socioeconomic factors significantly interact to increase risk of T2D and obesity. Favorable area-level socioeconomic status was associated with an almost 50% lower T2D prevalence in those with high genetic risk.

Impact of cross-ancestry genetic architecture on GWAS in admixed populations

Genome-wide association studies (GWAS) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWAS in admixed populations, such as the need to correctly adjust for population stratification to balance type I error with statistical power. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes we find that modeling HetLanc in its absence reduces statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs HetLanc is not large enough for GWAS to benefit from modeling heterogeneity.

The impact of modern admixture on archaic human ancestry in human populations

Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, as well as introgression between humans and archaic humans, Neanderthals and Denisovans. One example are genomes from populations in the Americas, as these are often mosaics of different ancestries due to recent admixture events as part of European colonization. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individual’s archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight enrichment of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.

Challenges in selecting admixture models and marker sets to infer genetic ancestry in a Brazilian admixed population

The inference of genetic ancestry plays an increasingly prominent role in clinical, population, and forensic genetics studies. Several genotyping strategies and analytical methodologies have been developed over the last few decades to assign individuals to specific biogeographic regions. However, despite these efforts, ancestry inference in populations with a recent history of admixture, such as those in Brazil, remains a challenge. In admixed populations, proportion and components of genetic ancestry vary on different levels: (i) between populations; (ii) between individuals of the same population, and (iii) throughout the individual's genome. The present study evaluated 1171 admixed Brazilian samples to compare the genetic ancestry inferred by tri-/tetra-hybrid admixture models and evaluated different marker sets from those with small numbers of ancestry informative markers panels (AIMs), to high-density SNPs (HDSNP) and whole-genome-sequence (WGS) data. Analyses revealed greater variation in the correlation coefficient of ancestry components within and between admixed populations, especially for minority ancestral components. We also observed positive correlation between the number of markers in the AIMs panel and HDSNP/WGS. Furthermore, the greater the number of markers, the more accurate the tri-/tetra-hybrid admixture models.

Sex-biased admixture and assortative mating shape genetic variation and influence demographic inference in admixed Cabo Verdeans

Genetic data can provide insights into population history, but first, we must understand the patterns that complex histories leave in genomes. Here, we consider the admixed human population of Cabo Verde to understand the patterns of genetic variation left by social and demographic processes. First settled in the late 1400s, Cabo Verdeans are admixed descendants of Portuguese colonizers and enslaved West African people. We consider Cabo Verde’s well-studied historical record alongside genome-wide SNP data from 563 individuals from 4 regions within the archipelago. We use genetic ancestry to test for patterns of nonrandom mating and sex-specific gene flow, and we examine the consequences of these processes for common demographic inference methods and genetic patterns. Notably, multiple population genetic tools that assume random mating underestimate the timing of admixture, but incorporating nonrandom mating produces estimates more consistent with historical records. We consider how admixture interrupts common summaries of genomic variation such as runs of homozygosity. While summaries of runs of homozygosity may be difficult to interpret in admixed populations, differentiating runs of homozygosity by length class shows that runs of homozygosity reflect historical differences between the islands in their contributions from the source populations and postadmixture population dynamics. Finally, we find higher African ancestry on the X chromosome than on the autosomes, consistent with an excess of European males and African females contributing to the gene pool. Considering these genomic insights into population history in the context of Cabo Verde’s historical record, we can identify how assumptions in genetic models impact inference of population history more broadly.

Whole-exome Sequencing of Nigerian Prostate Tumors from the Prostate Cancer Transatlantic Consortium (CaPTC) Reveals DNA Repair Genes Associated with African Ancestry

In this study, we used whole-exome sequencing of a cohort of 45 advanced-stage, treatment-naïve Nigerian (NG) primary prostate cancer tumors and 11 unmatched nontumor tissues to compare genomic mutations with African American (AA) and European American (EA) The Cancer Genome Atlas (TCGA) prostate cancer. NG samples were collected from six sites in central and southwest Nigeria. After whole-exome sequencing, samples were processed using GATK best practices. BRCA1 (100%), BARD1 (45%), BRCA2 (27%), and PMS2(18%) had germline alterations in at least two NG nontumor samples. Across 111 germline variants, the AA cohort reflected a pattern [BRCA1 (68%), BARD1 (34%), BRCA2 (28%), and PMS2 (16%)] similar to NG samples. Of the most frequently mutated genes, BRCA1 showed a statistically (P ≤ 0.05) higher germline mutation frequency in men of African ancestry (MAA) and increasing variant frequency with increased African ancestry. Disaggregating gene-level mutation frequencies by variants revealed both ancestry-linked and NG-specific germline variant patterns. Driven by rs799917 (T>C), BRCA1 showed an increasing mutation frequency as African ancestry increased. BRCA2_rs11571831 was present only in MAA, and BRCA2_rs766173 was elevated in NG men. A total of 133 somatic variants were present in 26 prostate cancer-associated genes within the NG tumor cohort. BRCA2 (27%), APC (20%), ATM (20%), BRCA1 (13%), DNAJC6 (13%), EGFR (13%), MAD1L1 (13%), MLH1 (11%), and PMS2 (11%) showed mutation frequencies >10%. Compared with TCGA cohorts, NG tumors showed statistically significant elevated frequencies of BRCA2, APC, and BRCA1. The NG cohort variant pattern shared similarities (cosign similarities ≥0.734) with Catalogue of Somatic Mutations in Cancer signatures 5 and 6, and mutated genes showed significant (q < 0.001) gene ontology (GO) and functional enrichment in mismatch repair and non-homologous repair deficiency pathways. Here, we showed that mutations in DNA damage response genes were higher in NG prostate cancer samples and that a portion of those mutations correlate with African ancestry. Moreover, we identified variants of unknown significance that may contribute to population-specific routes of tumorigenesis and treatment. These results present the most comprehensive characterization of the NG prostate cancer exome to date and highlight the need to increase diversity of study populations.

Significance

MAA have higher rates of prostate cancer incidence and mortality, however, are severely underrepresented in genomic studies. This is the first study utilizing whole-exome sequencing in NG men to identify West African ancestry-linked variant patterns that impact DNA damage repair pathways.

Estimation of the covariance structure from SNP allele frequencies

We propose two new statistics, V ̂ $\hat{V}$ and S ̂ $\hat{S}$ , to disentangle the population history of related populations from SNP frequency data. If the populations are related by a tree, we show by theoretical means as well as by simulation that the new statistics are able to identify the root of a tree correctly, in contrast to standard statistics, such as the observed matrix of F 2-statistics (distances between pairs of populations). The statistic V ̂ $\hat{V}$ is obtained by averaging over all SNPs (similar to standard statistics). Its expectation is the true covariance matrix of the observed population SNP frequencies, offset by a matrix with identical entries. In contrast, the statistic S ̂ $\hat{S}$ is put in a Bayesian context and is obtained by averaging over pairs of SNPs, such that each SNP is only used once. It thus makes use of the joint distribution of pairs of SNPs. In addition, we provide a number of novel mathematical results about old and new statistics, and their mutual relationship.

Precision Medicine Needs to Think Outside the Box

Precision medicine offers a precious opportunity to change clinical practice and disrupt medicine’s reliance on crude racial, ethnic, or ancestral categories by focusing on an individual’s unique genetic, environmental, and lifestyle characteristics. However, precision medicine and the genomic studies that are its cornerstone have thus far failed to account for human diversity. This failure is made clearer when looking at individuals who encapsulate a mosaic of different genetic ancestries and do not fit neatly into existing population labels. This piece argues that precision medicine continues to rely on the same forms of crude categorization it seeks to unsettle. Until the scientific community creates inclusive solutions for individuals who fall outside or between our existing population labels, precision medicine will continue to fall short in its aims.

Human genetic admixture through the lens of population genomics

Over the past 50 years, geneticists have made great strides in understanding how our species' evolutionary history gave rise to current patterns of human genetic diversity classically summarized by Lewontin in his 1972 paper, ‘The Apportionment of Human Diversity’. One evolutionary process that requires special attention in both population genetics and statistical genetics is admixture: gene flow between two or more previously separated source populations to form a new admixed population. The admixture process introduces ancestry-based structure into patterns of genetic variation within and between populations, which in turn influences the inference of demographic histories, identification of genetic targets of selection and prediction of complex traits. In this review, we outline some challenges for admixture population genetics, including limitations of applying methods designed for populations without recent admixture to the study of admixed populations. We highlight recent studies and methodological advances that aim to overcome such challenges, leveraging genomic signatures of admixture that occurred in the past tens of generations to gain insights into human history, natural selection and complex trait architecture.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Variants in the VDR Gene May Influence 25(OH)D Levels in Type 1 Diabetes Mellitus in a Brazilian Population

Vitamin D has been considered a strong contributing factor to type 1 diabetes mellitus (T1DM). Many studies have investigated polymorphisms in the VDR gene in association with T1DM in different populations, but there are still conflicting findings. This study aimed to evaluate the association of four variants in the VDR gene (rs7975232, rs1544410, rs731236, and rs2228570) with T1DM risk and vitamin D levels within a population from North Region, Brazil, as well as the influence of genomic ancestry on T1DM. A total of 65 T1DM patients and 83 non-T1DM patients were enrolled in this study. VDR gene polymorphisms were assessed using Sanger sequencing analysis. Genomic ancestry was analyzed using a set of 61 ancestry-informative markers. T1DM patients showed higher European genomic contribution and lower Native American genomic contribution when compared to non-T1DM patients. T1DM patients with AA genotype in rs1544410 or CC genotype in rs731236 had significantly lower 25(OH)D levels compared to the other two genotypes (p = 0.013 and p = 0.02, respectively), while T1DM with TT genotype in rs2228570 had higher 25(OH)D levels compared to CC + TC in the same polymorphism (p = 0.011). Our findings suggest that the association between 25(OH)D and T1DM may be modified by VDR variants, possibly influencing the development of this autoimmune disease.

Multispecies coalescent and its applications to infer species phylogenies and cross-species gene flow

Multispecies coalescent (MSC) is the extension of the single-population coalescent model to multiple species. It integrates the phylogenetic process of species divergences and the population genetic process of coalescent, and provides a powerful framework for a number of inference problems using genomic sequence data from multiple species, including estimation of species divergence times and population sizes, estimation of species trees accommodating discordant gene trees, inference of cross-species gene flow and species delimitation. In this review, we introduce the major features of the MSC model, discuss full-likelihood and heuristic methods of species tree estimation and summarize recent methodological advances in inference of cross-species gene flow. We discuss the statistical and computational challenges in the field and research directions where breakthroughs may be likely in the next few years.

Differences in Neuronal Numbers, Morphology, and Developmental Apoptosis in Mice Nigra Provide Experimental Evidence of Ontogenic Origin of Vulnerability to Parkinson's Disease

Parkinson disease (PD) prevalence varies by ethnicity. In an earlier study, we replicated the reduced vulnerability to PD in an admixed population, using 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-susceptible C57BL/6 J, MPTP-resistant CD-1 and their F1 crossbreds. In the present study, we investigated if the differences have a developmental origin. Substantia nigra was evaluated at postnatal days 2 (P2), P6, P10, P14, P18, and P22. C57BL/6 J mice had smaller nigra and fewer dopaminergic neurons than the CD-1 and crossbreds at P2, which persisted through development. A significant increase in numbers and nigral volume was observed across strains until P14. A drastic decline thereafter was specific to C57BL/6 J. CD-1 and crossbreds retained their numbers from P14 to stabilize with supernumerary neurons at adulthood. The neuronal size increased gradually to attain adult morphology at P10 in the resistant strains, vis-à-vis at P22 in C57BL/6 J. Accordingly, in comparison to C57BL/6 J, the nigra of CD-1 and reciprocal crossbreds possessed cytomorphological features of resilience, since birth. The considerably lesser dopaminergic neuronal loss in the CD-1 and crossbreds was seen at P2 and P14 and thereafter was complemented by attenuated developmental cell death. The differences in programmed cell death were confirmed by reduced TUNEL labelling, AIF, and caspase-3 expression. GDNF expression aligned with the cell death pattern at P2 and P14 in both nigra and striatum. Earlier maturity of nigra and its neurons appears to be better features that reflect as MPTP resistance at adulthood. Thus, variable MPTP vulnerability in mice and also differential susceptibility to PD in humans may arise early during nigral development.