Genetic Consequences of the Transatlantic Slave Trade in the Americas

Local Ancestry Inference Based on Population-Specific Single-Nucleotide Polymorphisms-A Study of Admixed Populations in the 1000 Genomes Project

Human populations have interacted throughout history, and a considerable portion of modern human populations show evidence of admixture. Local ancestry inference (LAI) is focused on detecting the genetic ancestry of chromosomal segments in admixed individuals and has wide applications. In this work, we proposed a new LAI method based on population-specific single-nucleotide polymorphisms (SNPs) and applied it in the analysis of admixed populations in the 1000 Genomes Project (1KGP). Based on population-specific SNPs in a sliding window, we computed local ancestry information vectors, which are moment estimators of local ancestral proportions, for two haplotypes of an admixed individual and inferred the local ancestral origins. Then we used African (AFR), East Asian (EAS), European (EUR) and South Asian (SAS) populations from the 1KGP and indigenous American (AMR) populations from the Human Genome Diversity Project (HGDP) as reference populations and conducted the proposed LAI analysis on African American populations and American populations in the 1KGP. The results were compared with those obtained by RFMix, G-Nomix and FLARE. We demonstrated that the existence of alleles in a chromosomal region that are specific to a particular reference population and the absence of alleles specific to the other reference populations provide reasonable evidence for determining the ancestral origin of the region. Contemporary AFR, AMR and EUR populations approximate ancestral populations of the admixed populations well, and the results from RFMix, G-Nomix and FLARE largely agree with those from the Ancestral Spectrum Analyzer (ASA), in which the proposed method was implemented. When admixtures are ancient and contemporary reference populations do not satisfactorily approximate ancestral populations, the performances of RFMix, G-Nomix and FLARE deteriorate with increased error rates and fragmented chromosomal segments. In contrast, our method provides fair results.

mtDNA "nomenclutter" and its consequences on the interpretation of genetic data

Population-based studies of human mitochondrial genetic diversity often require the classification of mitochondrial DNA (mtDNA) haplotypes into more than 5400 described haplogroups, and further grouping those into hierarchically higher haplogroups. Such secondary haplogroup groupings (e.g., "macro-haplogroups") vary across studies, as they depend on the sample quality, technical factors of haplogroup calling, the aims of the study, and the researchers' understanding of the mtDNA haplogroup nomenclature. Retention of historical nomenclature coupled with a growing number of newly described mtDNA lineages results in increasingly complex and inconsistent nomenclature that does not reflect phylogeny well. This "clutter" leaves room for grouping errors and inconsistencies across scientific publications, especially when the haplogroup names are used as a proxy for secondary groupings, and represents a source for scientific misinterpretation. Here we explore the effects of phylogenetically insensitive secondary mtDNA haplogroup groupings, and the lack of standardized secondary haplogroup groupings on downstream analyses and interpretation of genetic data. We demonstrate that frequency-based analyses produce inconsistent results when different secondary mtDNA groupings are applied, and thus allow for vastly different interpretations of the same genetic data. The lack of guidelines and recommendations on how to choose appropriate secondary haplogroup groupings presents an issue for the interpretation of results, as well as their comparison and reproducibility across studies. To reduce biases originating from arbitrarily defined secondary nomenclature-based groupings, we suggest that future updates of mtDNA phylogenies aimed for the use in mtDNA haplogroup nomenclature should also provide well-defined and standardized sets of phylogenetically meaningful algorithm-based secondary haplogroup groupings such as "macro-haplogroups", "meso-haplogroups", and "micro-haplogroups". Ideally, each of the secondary haplogroup grouping levels should be informative about different human population history events. Those phylogenetically informative levels of haplogroup groupings can be easily defined using TreeCluster, and then implemented into haplogroup callers such as HaploGrep3. This would foster reproducibility across studies, provide a grouping standard for population-based studies, and reduce errors associated with haplogroup nomenclatures in future studies.

CORRECTING MODEL MISSPECIFICATION IN RELATIONSHIP ESTIMATES

The datasets of large genotyping biobanks and direct-to-consumer genetic testing companies contain many related individuals. Until now, it has been widely accepted that the most distant relationships that can be detected are around fifteen degrees (approximately 8 th cousins) and that practical relationship estimates have a ceiling around ten degrees (approximately 5 th cousins). However, we show that these assumptions are incorrect and that they are due to a misapplication of relationship estimators. In particular, relationship estimators are applied almost exclusively to putative relatives who have been identified because they share detectable tracts of DNA identically by descent (IBD). However, no existing relationship estimator conditions on the event that two individuals share at least one detectable segment of IBD anywhere in the genome. As a result, the relationship estimates obtained using existing estimators are dramatically biased for distant relationships, inferring all sufficiently distant relationships to be around ten degrees regardless of the depth of the true relationship. Moreover, existing relationship estimators are derived under a model that assumes that each pair of related individuals shares a single common ancestor (or mating pair of ancestors). This model breaks down for relationships beyond 10 generations in the past because individuals share many thousands of cryptic common ancestors due to pedigree collapse. We first derive a corrected likelihood that conditions on the event that at least one segment is observed between a pair of putative relatives and we demonstrate that the corrected likelihood largely eliminates the bias in estimates of pairwise relationships and provides a more accurate characterization of the uncertainty in these estimates. We then reformulate the relationship inference problem to account for the fact that individuals share many common ancestors, not just one. We demonstrate that the most distant relationship that can be inferred may be forty degrees or more, rather than ten, extending the time-to-common ancestor from approximately 200 years in the past to approximately 600 years in the past or more. This dramatic increase in the range of relationship estimators makes it possible to infer relationships whose common ancestors lived before historical events such as European settlement of the Americas and the Transatlantic Slave Trade, and possibly much earlier.

Imputation accuracy across global human populations

Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of references from non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative improved the imputation of admixed African-ancestry and Hispanic/Latino samples, but imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we imputed the genotypes of over 43,000 individuals across 123 populations around the world and identified numerous populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for variants with minor allele frequencies between 1% and 5% in Saudi Arabians (n = 1,061), Vietnamese (n = 1,264), Thai (n = 2,435), and Papua New Guineans (n = 776) were 0.79, 0.78, 0.76, and 0.62, respectively, compared to 0.90-0.93 for comparable European populations matched in sample size and SNP array content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European-ancestry reference increased, as predicted. Using sequencing data as ground truth, we also showed that Rsq may over-estimate imputation accuracy for non-European populations more than European populations, suggesting further disparity in accuracy between populations. Using 1,496 sequenced individuals from Taiwan Biobank as a second reference panel to TOPMed, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, but this design did not improve accuracy across frequency spectra. Taken together, our analyses suggest that we must ultimately strive to increase diversity and size to promote equity within genetics research.

A Public Health Emergency: Breast Cancer Among Black Communities in the United States

While Black people have a similar incidence of breast cancer compared to White people, they have a 40% increased death rate. Black people are more likely to be diagnosed with aggressive subtypes such as triple-negative breast cancer. However, despite biological factors, systemic racism and social determinants of health create delays in care and barriers to treatment. While genetic testing holds incredible promise for Black people, uptake remains low and results may be challenging to interpret. There is a need for more robust, multidisciplinary, and antiracist interventions to reverse breast cancer-related racial disparities.

Trends of Prostate Cancer Morbidity in Low-Incidence Countries from 1990-2019

BACKGROUND

Our study was designed to elucidate the morbidity trends of prostate cancer in low-incidence countries.

METHODS

Data on prostate cancer were extracted from the 2019 Global Burden of Disease study. A cluster analysis of growth rates stratified by age was conducted, and correlation analyses were performed between age-standardized incidence rates (ASIR), estimated annual percent change (EAPC), and socio-demographic index (SDI).

RESULTS

Among 35 low-incidence countries for prostate cancer, predominantly located in Asia and North Africa, the SDI ranged from low to high-middle levels. Higher SDI regions exhibited considerably higher ASIR. With the exception of Kyrgyzstan, Kiribati, and Samoa that experienced a decrease in ASIR, the remaining 32 countries displayed an upward morbidity trend since 1990, with all their EAPCs exceeding the global average. In addition, men ages 90 years and above consistently exhibited the highest ASIR for prostate cancer. The most notable growth rate of ASIR was observed in individuals ages 20 to 44 years.

CONCLUSIONS

Overall, low-incidence countries generally witnessed an increase in prostate cancer morbidity, albeit at levels lower than those seen in Western countries. Individuals ages 90 years and above consistently maintained the highest ASIR since 1990. Notably, more substantial increase of ASIR in younger age was also observed in low-incidence countries.

IMPACT

This study offers a comprehensive overview of prostate cancer morbidity in low-incidence countries worldwide from 1990 to 2019. Future research should delve into the associations between incidence, clinical stages, PSA screening, environmental factors, lifestyle, and genetic risk in these low-incidence countries.

Systems that promote mental health in the teeth of oppression

Emotional distress can disproportionately disable individuals from minoritized groups, such as Black Americans, due to multiple intersecting factors. Addressing these challenges requires a comprehensive, culturally sensitive approach to mental health care that promotes inclusivity, accessibility, and representation within the field, to foster empowerment and resilience among minoritized communities. Given the weight of negative factors that can lead to psychological distress and mental illness, the wellness of Black Americans and how they support their mental health is important to acknowledge. In this Series paper, we propose that Black Americans have developed systems for managing many of these threats to their survival and wellbeing.

Huntington disease-like 2: insight into neurodegeneration from an African disease

Huntington disease (HD)-like 2 (HDL2) is a rare genetic disease caused by an expanded trinucleotide repeat in the JPH3 gene (encoding junctophilin 3) that shows remarkable clinical similarity to HD. To date, HDL2 has been reported only in patients with definite or probable African ancestry. A single haplotype background is shared by patients with HDL2 from different populations, supporting a common African origin for the expansion mutation. Nevertheless, outside South Africa, reports of patients with HDL2 in Africa are scarce, probably owing to limited clinical services across the continent. Systematic comparisons of HDL2 and HD have revealed closely overlapping motor, cognitive and psychiatric features and similar patterns of cerebral and striatal atrophy. The pathogenesis of HDL2 remains unclear but it is proposed to occur through several mechanisms, including loss of protein function and RNA and/or protein toxicity. This Review summarizes our current knowledge of this African-specific HD phenocopy and highlights key areas of overlap between HDL2 and HD. Given the aforementioned similarities in clinical phenotype and pathology, an improved understanding of HDL2 could provide novel insights into HD and other neurodegenerative and/or trinucleotide repeat expansion disorders.

Whole genomes from Angola and Mozambique inform about the origins and dispersals of major African migrations

As the continent of origin for our species, Africa harbours the highest levels of diversity anywhere on Earth. However, many regions of Africa remain under-sampled genetically. Here we present 350 whole genomes from Angola and Mozambique belonging to ten Bantu ethnolinguistic groups, enabling the construction of a reference variation catalogue including 2.9 million novel SNPs. We investigate the emergence of Bantu speaker population structure, admixture involving migrations across sub-Saharan Africa and model the demographic histories of Angolan and Mozambican Bantu speakers. Our results bring together concordant views from genomics, archaeology, and linguistics to paint an updated view of the complexity of the Bantu Expansion. Moreover, we generate reference panels that better represents the diversity of African populations involved in the trans-Atlantic slave trade, improving imputation accuracy in African Americans and Brazilians. We anticipate that our collection of genomes will form the foundation for future African genomic healthcare initiatives.

The role of admixture in the rare variant contribution to inflammatory bowel disease

BACKGROUND

Identification of rare variants involved in complex, polygenic diseases like Crohn's disease (CD) has accelerated with the introduction of whole exome/genome sequencing association studies. Rare variants can be used in both diagnostic and therapeutic assessments; however, since they are likely to be restricted to specific ancestry groups, their contributions to risk assessment need to be evaluated outside the discovery population. Prior studies implied that the three known rare variants in NOD2 are absent in West African and Asian populations and only contribute in African Americans via admixture.

METHODS

Whole genome sequencing (WGS) data from 3418 African American individuals, 1774 inflammatory bowel disease (IBD) cases, and 1644 controls were used to assess odds ratios and allele frequencies (AF), as well as haplotype-specific ancestral origins of European-derived CD variants discovered in a large exome-wide association study. Local and global ancestry was performed to assess the contribution of admixture to IBD contrasting European and African American cohorts.

RESULTS

Twenty-five rare variants associated with CD in European discovery cohorts are typically five-fold lower frequency in African Americans. Correspondingly, where comparisons could be made, the rare variants were found to have a predicted four-fold reduced burden for IBD in African Americans, when compared to European individuals. Almost all of the rare CD European variants were found on European haplotypes in the African American cohort, implying that they contribute to disease risk in African Americans primarily due to recent admixture. In addition, proportion of European ancestry correlates the number of rare CD European variants each African American individual carry, as well as their polygenic risk of disease. Similar findings were observed for 23 mutations affecting 10 other common complex diseases for which the rare variants were discovered in European cohorts.

CONCLUSIONS

European-derived Crohn's disease rare variants are even more rare in African Americans and contribute to disease risk mainly due to admixture, which needs to be accounted for when performing cross-ancestry genetic assessments.

Reconsidering the use of race adjustments in maternal serum screening

The use of race in maternal serum screening is problematic because race is a social construct rather than a distinct biological classifier. Nevertheless, laboratories offering this testing are encouraged to use race-specific cutoff values for maternal serum screening biomarkers to determine the risk of fetal abnormalities. Large cohort studies examining racial differences in maternal serum screening biomarker concentrations have yielded conflicting results, which we postulate may be explained by genetic and socioeconomic differences between racial cohorts in different studies. We recommend that the use of race in maternal serum screening should be abandoned. Further research is needed to identify socioeconomic and environmental factors that contribute to differences in maternal serum screening biomarker concentrations observed between races. A better understanding of these factors may facilitate accurate race-agnostic risk estimates for aneuploidy and neural tube defects.

Neighborhood Deprivation and DNA Methylation and Expression of Cancer Genes in Breast Tumors

Importance

The biological processes that underlie the association of neighborhood environment with chronic diseases, such as cancer, remain poorly understood.

Objective

To determine whether differences in breast tissue DNA methylation are associated with neighborhood deprivation among Black and White women with breast cancer.

Design, Setting, and Participants

This cross-sectional study collected breast tissue from women undergoing surgery for breast cancer between January 1, 1993, and December 31, 2003. Participants were recruited through the University of Maryland Medical Center, with additional collection sites at Baltimore-area hospitals. Data analysis was performed from March 1 through December 1, 2022.

Exposure

Year 2000 census tract-level socioeconomic deprivation measured via neighborhood deprivation index (NDI) as a standardized score, with Black and White race being ascertained through self-report.

Main Outcome and Measures

The primary outcome was tissue DNA methylation using genome-wide measurements. The secondary outcome was tissue gene expression.

Results

Participants included 185 women with breast cancer (110 Black [59.5%], 75 White [40.5%]). Mean (SD) age at surgery was 56.0 (14.1) years. Neighborhood deprivation was higher for Black women than for White women (Mean [SD] NDI, 2.96 [3.03] for Black women and -0.54 [1.91] for White women; difference, -3.50; 95% CI, -4.22 to -2.79; P < .001). In unstratified analysis, 8 hypomethylated CpG sites were identified as associated with the NDI, including sites in 2 tumor suppressor genes, LRIG1 and WWOX. Moreover, expression of the 2 genes inversely correlated with neighborhood deprivation. In the race-stratified analysis, the negative correlation between the LRIG1 gene body CpG site cg26131019 and the NDI remained significant in Black women. A neighborhood deprivation-associated decrease in gene expression was also observed for LRIG1 and WWOX in tumors from Black women.

Conclusions and Relevance

In this study, high neighborhood deprivation was associated with differences in tissue DNA methylation and gene expression among Black women. These findings suggest that continued investment in public health interventions and policy changes at the neighborhood level may help to remedy biological alterations that could make minoritized populations more susceptible to chronic diseases.

Imputation Accuracy Across Global Human Populations

Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of populations with non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative contains a substantial number of admixed African-ancestry and Hispanic/Latino samples to impute these populations with nearly the same accuracy as European-ancestry cohorts. However, imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we curated genome-wide array data from 23 publications published between 2008 to 2021. In total, we imputed over 43k individuals across 123 populations around the world. We identified a number of populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for 1-5% alleles in Saudi Arabians (N=1061), Vietnamese (N=1264), Thai (N=2435), and Papua New Guineans (N=776) were 0.79, 0.78, 0.76, and 0.62, respectively. In contrast, the mean Rsq ranged from 0.90 to 0.93 for comparable European populations matched in sample size and SNP content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European reference increased, as predicted. Further analysis using sequencing data as ground truth suggested that imputation software may over-estimate imputation accuracy for non-European populations than European populations, suggesting further disparity between populations. Using 1496 whole genome sequenced individuals from Taiwan Biobank as a reference, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, which can combine results from TOPMed with smaller population-specific reference panels. We found that meta-imputation in this design did not improve Rsq genome-wide. Taken together, our analysis suggests that with the current size of alternative reference panels, meta-imputation alone cannot improve imputation efficacy for underrepresented cohorts and we must ultimately strive to increase diversity and size to promote equity within genetics research.

Heterogeneous genetic architectures and evolutionary genomics of prostate cancer in Sub-Saharan Africa

Men of African descent have the highest prostate cancer (CaP) incidence and mortality rates, yet the genetic basis of CaP in African men has been understudied. We used genomic data from 3,963 CaP cases and 3,509 controls recruited in Ghana, Nigeria, Senegal, South Africa, and Uganda, to infer ancestry-specific genetic architectures and fine-mapped disease associations. Fifteen independent associations at 8q24.21, 6q22.1, and 11q13.3 reached genome-wide significance, including four novel associations. Intriguingly, multiple lead SNPs are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of CaP differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African CaP associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.

Ethical considerations when co-analyzing ancient DNA and data from private genetic databases

Ancient DNA studies have begun to explore the possibility of identifying identical DNA segments shared between historical and living people. This research requires access to large genetic datasets to maximize the likelihood of identifying previously unknown, close genetic connections. Direct-to-consumer genetic testing companies, such as 23andMe, Inc., manage by far the largest and most diverse genetic databases that can be used for this purpose. It is therefore important to think carefully about guidelines for carrying out collaborations between researchers and such companies. Such collaborations require consideration of ethical issues, including policies for sharing ancient DNA datasets, and ensuring reproducibility of research findings when access to privately controlled genetic datasets is limited. At the same time, they introduce unique possibilities for returning results to the research participants whose data are analyzed, including those who are identified as close genetic relatives of historical individuals, thereby enabling ancient DNA research to contribute to the restoration of information about ancestral connections that were lost over time, which can be particularly meaningful for families and groups where such history has not been well documented. We explore these issues by describing our experience designing and carrying out a study searching for genetic connections between 18th- and 19th-century enslaved and free African Americans who labored at Catoctin Furnace, Maryland, and 23andMe research participants. We share our experience in the hope of helping future researchers navigate similar ethical considerations, recognizing that our perspective is part of a larger conversation about best ethical practices.

The genetic legacy of African Americans from Catoctin Furnace

Few African Americans have been able to trace family lineages back to ancestors who died before the 1870 United States Census, the first in which all Black people were listed by name. We analyzed 27 individuals from Maryland's Catoctin Furnace African American Cemetery (1774-1850), identifying 41,799 genetic relatives among consenting research participants in 23andMe, Inc.'s genetic database. One of the highest concentrations of close relatives is in Maryland, suggesting that descendants of the Catoctin individuals remain in the area. We find that many of the Catoctin individuals derived African ancestry from the Wolof or Kongo groups and European ancestry from Great Britain and Ireland. This study demonstrates the power of joint analysis of historical DNA and large datasets generated through direct-to-consumer ancestry testing.

Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for all

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease [1-8]. Therapeutics and outcomes remain hidden because we lack insights that we could gain from analyzing ancestry-unbiased genomic data. To address this significant gap, we present PhyloFrame, the first-ever machine learning method for equitable genomic precision medicine. PhyloFrame corrects for ancestral bias by integrating big data tissue-specific functional interaction networks, global population variation data, and disease-relevant transcriptomic data. Application of PhyloFrame to breast, thyroid, and uterine cancers shows marked improvements in predictive power across all ancestries, less model overfitting, and a higher likelihood of identifying known cancer-related genes. The ability to provide accurate predictions for underrepresented groups, in particular, is substantially increased. These results demonstrate how AI can mitigate ancestral bias in training data and contribute to equitable representation in medical research.

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.

AACC/NKF Guidance Document on Improving Equity in Chronic Kidney Disease Care

BACKGROUND

Kidney disease (KD) is an important health equity issue with Black, Hispanic, and socioeconomically disadvantaged individuals experiencing a disproportionate disease burden. Prior to 2021, the commonly used estimated glomerular filtration rate (eGFR) equations incorporated coefficients for Black race that conferred higher GFR estimates for Black individuals compared to non-Black individuals of the same sex, age, and blood creatinine concentration. With a recognition that race does not delineate distinct biological categories, a joint task force of the National Kidney Foundation and the American Society of Nephrology recommended the adoption of the CKD-EPI 2021 race-agnostic equations.

CONTENT

This document provides guidance on implementation of the CKD-EPI 2021 equations. It describes recommendations for KD biomarker testing, and opportunities for collaboration between clinical laboratories and providers to improve KD detection in high-risk populations. Further, the document provides guidance on the use of cystatin C, and eGFR reporting and interpretation in gender-diverse populations.

SUMMARY

Implementation of the CKD-EPI 2021 eGFR equations represents progress toward health equity in the management of KD. Ongoing efforts by multidisciplinary teams, including clinical laboratorians, should focus on improved disease detection in clinically and socially high-risk populations. Routine use of cystatin C is recommended to improve the accuracy of eGFR, particularly in patients whose blood creatinine concentrations are confounded by processes other than glomerular filtration. When managing gender-diverse individuals, eGFR should be calculated and reported with both male and female coefficients. Gender-diverse individuals can benefit from a more holistic management approach, particularly at important clinical decision points.

Native American genetic ancestry and pigmentation allele contributions to skin color in a Caribbean population

Our interest in the genetic basis of skin color variation between populations led us to seek a Native American population with genetically African admixture but low frequency of European light skin alleles. Analysis of 458 genomes from individuals residing in the Kalinago Territory of the Commonwealth of Dominica showed approximately 55% Native American, 32% African, and 12% European genetic ancestry, the highest Native American genetic ancestry among Caribbean populations to date. Skin pigmentation ranged from 20 to 80 melanin units, averaging 46. Three albino individuals were determined to be homozygous for a causative multi-nucleotide polymorphism OCA2NW273KV contained within a haplotype of African origin; its allele frequency was 0.03 and single allele effect size was -8 melanin units. Derived allele frequencies of SLC24A5A111T and SLC45A2L374F were 0.14 and 0.06, with single allele effect sizes of -6 and -4, respectively. Native American genetic ancestry by itself reduced pigmentation by more than 20 melanin units (range 24-29). The responsible hypopigmenting genetic variants remain to be identified, since none of the published polymorphisms predicted in prior literature to affect skin color in Native Americans caused detectable hypopigmentation in the Kalinago.

Core issues, case studies, and the need for expanded Legacy African American genomics

Introduction: Genomic studies of Legacy African Americans have a tangled and convoluted history in western science. In this review paper, core issues affecting African American genomic studies are addressed and two case studies, the New York African Burial Ground and the Gullah Geechee peoples, are presented to highlight the current status of genomic research among Africa Americans. Methods: To investigate our target population's core issues, a metadatabase derived from 22 publicly accessible databases were reviewed, evaluated, and synthesized to identify the core bioethical issues prevalent during the centuries of the African American presence in North America. The sequence of metadatabase development included 5 steps: identification of information, record screening and retention of topic relevant information, identification of eligibility via synthesis for concept identifications, and inclusion of studies used for conceptual summaries and studies used for genetic and genomic summaries. To these data we added our emic perspectives and specific insights from our case studies. Results: Overall, there is a paucity of existing research on underrepresent African American genomic diversity. In every category of genomic testing (i.e., diagnostic, clinical predictive, pharmacogenomic, direct-to-consumer, and tumor testing), African Americans are disproportionately underrepresented compared to European Americans. The first of our case studies is from the New York African Burial Ground Project where genomic studies of grave soil derived aDNA yields insights into the causes of death of 17^th and 18^th Century African Americans. In the second of our case studies, research among the Gullah Geechee people of the Carolina Lowcountry reveals a connection between genomic studies and health disparities. Discussion: African Americans have historically borne the brunt of the earliest biomedical studies used to generate and refine primitive concepts in genetics. As exploited victims these investigations, African American men, women, and children were subjected to an ethics-free western science. Now that bioethical safeguards have been added, underrepresented and marginalized people who were once the convenient targets of western science, are now excluded from its health-related benefits. Recommendations to enhance the inclusion of African Americans in global genomic databases and clinical trials should include the following: emphasis on the connection of inclusion to advances in precision medicine, emphasis on the relevance of inclusion to fundamental questions in human evolutionary biology, emphasis on the historical relevance of inclusion for Legacy African Americans, emphasis on the ability of inclusion to foster expanded scientific expertise in the target population, ethical engagement with their descendants, and increase the number of science researchers from these communities.

Historical genomes elucidate European settlement and the African diaspora in Delaware

The 17th-century colonization of North America brought thousands of Europeans to Indigenous lands in the Delaware region, which comprises the eastern boundary of the Chesapeake Bay in what is now the Mid-Atlantic region of the United States.1 The demographic features of these initial colonial migrations are not uniformly characterized, with Europeans and European-Americans migrating to the Delaware area from other countries and neighboring colonies as single persons or in family units of free persons, indentured servants, or tenant farmers.2 European colonizers also instituted a system of racialized slavery through which they forcibly transported thousands of Africans to the Chesapeake region. Historical information about African-descended individuals in the Delaware region is limited, with a population estimate of less than 500 persons by 1700 CE.3,4 To shed light on the population histories of this period, we analyzed low-coverage genomes of 11 individuals from the Avery's Rest archaeological site (circa 1675-1725 CE), located in Delaware. Previous osteological and mitochondrial DNA (mtDNA) sequence analyses showed a southern group of eight individuals of European maternal descent, buried 15-20 feet from a northern group of three individuals of African maternal descent.5 Autosomal results further illuminate genomic similarities to Northwestern European reference populations or West and West-Central African reference populations, respectively. We also identify three generations of maternal kin of European ancestry and a paternal parent-offspring relationship between an adult and child of African ancestry. These findings expand our understanding of the origins and familial relationships in late 17th and early 18th century North America.

Addressing the feasibility of people of African descent finding living African relatives using direct-to-consumer genetic testing

People of African descent use direct-to-consumer genomics services such as 23andMe and AncestryDNA for various family histories and health reasons, including identifying and interacting with the previously unknown living African genetic relatives. In this commentary, I argue that it is reasonable to consider that cousin pairs consisting of an African person and a descendant of an African person enslaved in the Americans during the Transatlantic Slave Trade (i.e., a person of African descent) have genealogical ancestors recent enough to be detected using autosomal DNA testing where the pair has shared ancestors in the range of 20-6 generations ago from the present.

Selection and adaptive introgression guided the complex evolutionary history of the European common bean

Domesticated crops have been disseminated by humans over vast geographic areas. Common bean (Phaseolus vulgaris L.) was introduced in Europe after 1492. Here, by combining whole-genome profiling, metabolic fingerprinting and phenotypic characterisation, we show that the first common bean cultigens successfully introduced into Europe were of Andean origin, after Francisco Pizarro's expedition to northern Peru in 1529. We reveal that hybridisation, selection and recombination have shaped the genomic diversity of the European common bean in parallel with political constraints. There is clear evidence of adaptive introgression into the Mesoamerican-derived European genotypes, with 44 Andean introgressed genomic segments shared by more than 90% of European accessions and distributed across all chromosomes except PvChr11. Genomic scans for signatures of selection highlight the role of genes relevant to flowering and environmental adaptation, suggesting that introgression has been crucial for the dissemination of this tropical crop to the temperate regions of Europe.

Estimating human mobility in Holocene Western Eurasia with large-scale ancient genomic data

The recent increase in openly available ancient human DNA samples allows for large-scale meta-analysis applications. Trans-generational past human mobility is one of the key aspects that ancient genomics can contribute to since changes in genetic ancestry-unlike cultural changes seen in the archaeological record-necessarily reflect movements of people. Here, we present an algorithm for spatiotemporal mapping of genetic profiles, which allow for direct estimates of past human mobility from large ancient genomic datasets. The key idea of the method is to derive a spatial probability surface of genetic similarity for each individual in its respective past. This is achieved by first creating an interpolated ancestry field through space and time based on multivariate statistics and Gaussian process regression and then using this field to map the ancient individuals into space according to their genetic profile. We apply this algorithm to a dataset of 3138 aDNA samples with genome-wide data from Western Eurasia in the last 10,000 y. Finally, we condense this sample-wise record with a simple summary statistic into a diachronic measure of mobility for subregions in Western, Central, and Southern Europe. For regions and periods with sufficient data coverage, our similarity surfaces and mobility estimates show general concordance with previous results and provide a meta-perspective of genetic changes and human mobility.

Challenges of accurately estimating sex-biased admixture from X chromosomal and autosomal ancestry proportions

Sex-biased admixture can be inferred from ancestry-specific proportions of X chromosome and autosomes. In a paper published in the American Journal of Human Genetics, Micheletti et al.1 used this approach to quantify male and female contributions following the transatlantic slave trade. Using a large dataset from 23andMe, they concluded that African and European contributions to gene pools in the Americas were much more sex biased than previously thought. We show that the reported extreme sex-specific contributions can be attributed to unassigned genetic ancestry as well as the limitations of simple models of sex-biased admixture. Unassigned ancestry proportions in the study by Micheletti et al. ranged from ∼1% to 21%, depending on the type of chromosome and geographic region. A sensitivity analysis illustrates how this unassigned ancestry can create false patterns of sex bias and that mathematical models are highly sensitive to slight sampling errors when inferring mean ancestry proportions, making confidence intervals necessary. Thus, unassigned ancestry and the sensitivity of the models effectively prohibit the interpretation of estimated sex biases for many geographic regions in Micheletti et al. Furthermore, Micheletti et al. assumed models of a single admixture event. Using simulations, we find that violations of demographic assumptions, such as subsequent gene flow and/or sex-specific assortative mating, may have confounded the analyses of Micheletti et al., but unassigned ancestry was likely the more important confounding factor. Our findings underscore the importance of using complete ancestry information, sufficiently large sample sizes, and appropriate models when inferring sex-biased patterns of demography. This Matters Arising paper is in response to Micheletti et al.,1 published in American Journal of Human Genetics. See also the response by Micheletti et al.,2 published in this issue.

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.

A review of ancestrality and admixture in Latin America and the caribbean focusing on native American and African descendant populations

Genomics can reveal essential features about the demographic evolution of a population that may not be apparent from historical elements. In recent years, there has been a significant increase in the number of studies applying genomic epidemiological approaches to understand the genetic structure and diversity of human populations in the context of demographic history and for implementing precision medicine. These efforts have traditionally been applied predominantly to populations of European origin. More recently, initiatives in the United States and Africa are including more diverse populations, establishing new horizons for research in human populations with African and/or Native ancestries. Still, even in the most recent projects, the under-representation of genomic data from Latin America and the Caribbean (LAC) is remarkable. In addition, because the region presents the most recent global miscegenation, genomics data from LAC may add relevant information to understand population admixture better. Admixture in LAC started during the colonial period, in the 15th century, with intense miscegenation between European settlers, mainly from Portugal and Spain, with local indigenous and sub-Saharan Africans brought through the slave trade. Since, there are descendants of formerly enslaved and Native American populations in the LAC territory; they are considered vulnerable populations because of their history and current living conditions. In this context, studying LAC Native American and African descendant populations is important for several reasons. First, studying human populations from different origins makes it possible to understand the diversity of the human genome better. Second, it also has an immediate application to these populations, such as empowering communities with the knowledge of their ancestral origins. Furthermore, because knowledge of the population genomic structure is an essential requirement for implementing genomic medicine and precision health practices, population genomics studies may ensure that these communities have access to genomic information for risk assessment, prevention, and the delivery of optimized treatment; thus, helping to reduce inequalities in the Western Hemisphere. Hoping to set the stage for future studies, we review different aspects related to genetic and genomic research in vulnerable populations from LAC countries.

Obesity Pillars Roundtable: Body mass index and body composition in Black and Female individuals. Race-relevant or racist? Sex-relevant or sexist?

Background

Body mass index (BMI or weight in kilograms/height in meters2) is the most common metric to diagnose overweight and obesity. However, a body composition analysis more thoroughly assesses adiposity, percent body fat, lean body mass (i.e., including skeletal muscle), and sometimes bone mineral density. BMI is not an accurate assessment of body fat in individuals with increased or decreased muscle mass; the diagnostic utility of BMI in individuals is also influenced by race and sex.

Methods

Previous Obesity Pillars Roundtables addressed the diagnostic limitations of BMI, the importance of android and visceral fat (especially among those with South and East Asian ancestry), and considerations of obesity among individuals who identify as Hispanic, diverse in sexual-orientation, Black, Native American, and having ancestry from the Mediterranean and Middle East regions. This roundtable examines considerations of BMI in Black and female individuals.

Results

The panelists agreed that body composition assessment was a more accurate measure of adiposity and muscle mass than BMI. When it came to matters of race and sex, one panelist felt: "race is a social construct and not a defining biology." Another felt that: "BMI should be a screening tool to prompt further evaluation of adiposity that utilizes better diagnostic tools for body composition." Regarding bias and misperceptions of resistance training in female individuals, another panelist stated: "I have spent my entire medical career taking care of women and have never seen a woman unintentionally gain 'too much' muscle mass and bulk up from moderate strength training."

Conclusions

Conveying the importance of race and sex regarding body composition has proven challenging, with the discussion sometimes devolving into misunderstandings or misinformation that may be perceived as racist or sexist. Body composition analysis is the ultimate diagnostic equalizer in addressing the inaccuracies and biases inherent in the exclusive use of BMI.

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations.

Luck, lottery, or legacy? The problem of confounding. A reply to Harden

A reply to Harden's response to Coop and Przeworski (2022).

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.

Phylogeography of Sub-Saharan Mitochondrial Lineages Outside Africa Highlights the Roles of the Holocene Climate Changes and the Atlantic Slave Trade

Despite the importance of ancient DNA for understanding human prehistoric dispersals, poor survival means that data remain sparse for many areas in the tropics, including in Africa. In such instances, analysis of contemporary genomes remains invaluable. One promising approach is founder analysis, which identifies and dates migration events in non-recombining systems. However, it has yet to be fully exploited as its application remains controversial. Here, we test the approach by evaluating the age of sub-Saharan mitogenome lineages sampled outside Africa. The analysis confirms that such lineages in the Americas date to recent centuries—the time of the Atlantic slave trade—thereby validating the approach. By contrast, in North Africa, Southwestern Asia and Europe, roughly half of the dispersal signal dates to the early Holocene, during the “greening” of the Sahara. We elaborate these results by showing that the main source regions for the two main dispersal episodes are distinct. For the recent dispersal, the major source was West Africa, but with two exceptions: South America, where the fraction from Southern Africa was greater, and Southwest Asia, where Eastern Africa was the primary source. These observations show the potential of founder analysis as both a supplement and complement to ancient DNA studies.

Simultaneous inference of parental admixture proportions and admixture times from unphased local ancestry calls

Population genetic analyses of local ancestry tracts routinely assume that the ancestral admixture process is identical for both parents of an individual, an assumption that may be invalid when considering recent admixture. Here, we present Parental Admixture Proportion Inference (PAPI), a Bayesian tool for inferring the admixture proportions and admixture times for each parent of a single admixed individual. PAPI analyzes unphased local ancestry tracts and has two components: a binomial model that leverages genome-wide ancestry fractions to infer parental admixture proportions and a hidden Markov model (HMM) that infers admixture times from tract lengths. Crucially, the HMM accounts for unobserved within-ancestry recombination by approximating the pedigree crossover dynamics, enabling inference of parental admixture times. In simulations, we find that PAPI's admixture proportion estimates deviate from the truth by 0.047 on average, outperforming ANCESTOR and PedMix by 46.0% and 57.6%, respectively. Moreover, PAPI's admixture time estimates were strongly correlated with the truth (R=0.76) but have an average downward bias of 1.01 generations that is partly attributable to inaccuracies in local ancestry inference. As an illustration of its utility, we ran PAPI on African American genotypes from the PAGE study (N = 5,786) and found strong evidence of assortative mating by ancestry proportion: couples' ancestry proportions are highly correlated (R = 0.87) and are closer to each other than expected under random mating (p < 10-6). We anticipate that PAPI will be useful in studying the population dynamics of admixture and will also be of interest to individuals seeking to learn about their personal genealogies.

Racial and Ethnic Differences in the Association Between Classical Cardiovascular Risk Factors and Common Carotid Intima-Media Thickness: An Individual Participant Data Meta-Analysis

Background The major risk factors for atherosclerotic cardiovascular disease differ by race or ethnicity but have largely been defined using populations of European ancestry. Despite the rising prevalence of cardiovascular disease in Africa there are few related data from African populations. Therefore, we compared the association of established cardiovascular risk factors with carotid-intima media thickness (CIMT), a subclinical marker of atherosclerosis, between African, African American, Asian, European, and Hispanic populations. Methods and Results Cross-sectional analyses of 34 025 men and women drawn from 15 cohorts in Africa, Asia, Europe, and North America were undertaken. Classical cardiovascular risk factors were assessed and CIMT measured using B-mode ultrasound. Ethnic differences in the association of established cardiovascular risk factors with CIMT were determined using a 2-stage individual participant data meta-analysis with beta coefficients expressed as a percentage using the White population as the reference group. CIMT adjusted for risk factors was the greatest among African American populations followed by Asian, European, and Hispanic populations with African populations having the lowest mean CIMT. In all racial or ethnic groups, men had higher CIMT levels compared with women. Age, sex, body mass index, and systolic blood pressure had a significant positive association with CIMT in all races and ethnicities at varying magnitudes. When compared with European populations, the association of age, sex, and systolic blood pressure with CIMT was weaker in all races and ethnicities. Smoking (beta coefficient, 0.39; 95% CI, 0.09-0.70), body mass index (beta coefficient, 0.05; 95% CI, 0.01-0.08) and glucose (beta coefficient, 0.13; 95% CI, 0.06-0.19) had the strongest positive association with CIMT in the Asian population when compared with all other racial and ethnic groups. High-density lipoprotein-cholesterol had significant protective effects in African American (beta coefficient, -0.31; 95% CI, -0.42 to -0.21) and African (beta coefficient, -0.26; 95% CI, -0.31 to -0.19) populations only. Conclusions The strength of association between established cardiovascular risk factors and CIMT differed across the racial or ethnic groups and may be due to lifestyle risk factors and genetics. These differences have implications for race- ethnicity-specific primary prevention strategies and also give insights into the differential contribution of risk factors to the pathogenesis of cardiovascular disease. The greatest burden of subclinical atherosclerosis in African American individuals warrants further investigations.

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'.

pmTR database: population matched (pm) germline allelic variants of T-cell receptor (TR) loci

The IMGT database profiles the TR germline alleles for all four TR loci (TRA, TRB, TRG and TRD), however, it does not comprise of the information regarding population specificity and allelic frequencies of these germline alleles. The specificity of allelic variants to different human populations can, however, be a rich source of information when studying the genetic basis of population-specific immune responses in disease and in vaccination. Therefore, we meticulously identified true germline alleles enriched with complete TR allele sequences and their frequencies across 26 different human populations, profiled by "1000 Genomes data". We identified 205 TRAV, 249 TRBV, 16 TRGV and 5 TRDV germline alleles supported by at least four haplotypes. The diversity of germline allelic variants in the TR loci is the highest in Africans, while the majority of the Non-African alleles are specific to the Asian populations, suggesting a diverse profile of TR germline alleles in different human populations. Interestingly, the alleles in the IMGT database are frequent and common across all five super-populations. We believe that this new set of germline TR sequences represents a valuable new resource which we have made available through the new population-matched TR (pmTR) database, accessible via https://pmtrig.lumc.nl/ .

Lottery, luck, or legacy. A review of "The Genetic Lottery: Why DNA matters for social equality"

A book review of "The genetic lottery: why DNA matters for social equality." (Princeton University Press, 2021) by Kathryn Paige Harden.

The evolving story of apolipoprotein L1 nephropathy: the end of the beginning

Genetic coding variants in APOL1, which encodes apolipoprotein L1 (APOL1), were identified in 2010 and are relatively common among individuals of sub-Saharan African ancestry. Approximately 13% of African Americans carry two APOL1 risk alleles. These variants, termed G1 and G2, are a frequent cause of kidney disease — termed APOL1 nephropathy — that typically manifests as focal segmental glomerulosclerosis and the clinical syndrome of hypertension and arterionephrosclerosis. Cell culture studies suggest that APOL1 variants cause cell dysfunction through several processes, including alterations in cation channel activity, inflammasome activation, increased endoplasmic reticulum stress, activation of protein kinase R, mitochondrial dysfunction and disruption of APOL1 ubiquitinylation. Risk of APOL1 nephropathy is mostly confined to individuals with two APOL1 risk variants. However, only a minority of individuals with two APOL1 risk alleles develop kidney disease, suggesting the need for a ‘second hit’. The best recognized factor responsible for this ‘second hit’ is a chronic viral infection, particularly HIV-1, resulting in interferon-mediated activation of the APOL1 promoter, although most individuals with APOL1 nephropathy do not have an obvious cofactor. Current therapies for APOL1 nephropathies are not adequate to halt progression of chronic kidney disease, and new targeted molecular therapies are in clinical trials.

This Review summarizes current understanding of the role of APOL1 variants in kidney disease. The authors discuss the genetics, protein structure and biological functions of APOL1 variants and provide an overview of promising therapeutic strategies.

In contrast to other APOL family members, which are primarily intracellular, APOL1 contains a unique secretory signal peptide, resulting in its secretion into plasma.

APOL1 renal risk alleles provide protection from African human trypanosomiasis but are a risk factor for progressive kidney disease in those carrying two risk alleles.

APOL1 risk allele frequency is ~35% in the African American population in the United States, with ~13% of individuals having two risk alleles; the highest allele frequencies are found in West African populations and their descendants.

Cell and mouse models implicate endolysosomal and mitochondrial dysfunction, altered ion channel activity, altered autophagy, and activation of protein kinase R in the pathogenesis of APOL1-associated kidney disease; however, the relevance of these injury pathways to human disease has not been resolved.

APOL1 kidney disease tends to be progressive, and current standard therapies are generally ineffective; targeted therapeutic strategies hold the most promise.

Health inequities and the inappropriate use of race in nephrology

Chronic kidney disease is an important clinical condition beset with racial and ethnic disparities that are associated with social inequities. Many medical schools and health centres across the USA have raised concerns about the use of race - a socio-political construct that mediates the effect of structural racism - as a fixed, measurable biological variable in the assessment of kidney disease. We discuss the role of race and racism in medicine and outline many of the concerns that have been raised by the medical and social justice communities regarding the use of race in estimated glomerular filtration rate equations, including its relationship with structural racism and racial inequities. Although race can be used to identify populations who experience racism and subsequent differential treatment, ignoring the biological and social heterogeneity within any racial group and inferring innate individual-level attributes is methodologically flawed. Therefore, although more accurate measures for estimating kidney function are under investigation, we support the use of biomarkers for determining estimated glomerular filtration rate without adjustments for race. Clinicians have a duty to recognize and elucidate the nuances of racism and its effects on health and disease. Otherwise, we risk perpetuating historical racist concepts in medicine that exacerbate health inequities and impact marginalized patient populations.

Imputation Performance in Latin American Populations: Improving Rare Variants Representation With the Inclusion of Native American Genomes

Current Genome-Wide Association Studies (GWAS) rely on genotype imputation to increase statistical power, improve fine-mapping of association signals, and facilitate meta-analyses. Due to the complex demographic history of Latin America and the lack of balanced representation of Native American genomes in current imputation panels, the discovery of locally relevant disease variants is likely to be missed, limiting the scope and impact of biomedical research in these populations. Therefore, the necessity of better diversity representation in genomic databases is a scientific imperative. Here, we expand the 1,000 Genomes reference panel (1KGP) with 134 Native American genomes (1KGP + NAT) to assess imputation performance in Latin American individuals of mixed ancestry. Our panel increased the number of SNPs above the GWAS quality threshold, thus improving statistical power for association studies in the region. It also increased imputation accuracy, particularly in low-frequency variants segregating in Native American ancestry tracts. The improvement is subtle but consistent across countries and proportional to the number of genomes added from local source populations. To project the potential improvement with a higher number of reference genomes, we performed simulations and found that at least 3,000 Native American genomes are needed to equal the imputation performance of variants in European ancestry tracts. This reflects the concerning imbalance of diversity in current references and highlights the contribution of our work to reducing it while complementing efforts to improve global equity in genomic research.

Is History the Same as Evolution? No. Is it Independent of Evolution? Certainly Not

History is full of violence and oppression within and between groups, and although group conflicts enhance within-group cooperation (mediated by oxytocin, which promotes parochial altruism) the hierarchy within groups ensures that spoils accrue very unevenly. Darwin suggested, and we now know, that sexual selection is as powerful as selection by mortality, and the main purpose of survival is reproduction. Male reproductive skew is greater than that among females in all societies, but the difference became much greater after the hunting-gathering era, and the rise of so-called "civilization" was everywhere a process of predatory expansion, producing kingdoms and empires where top males achieved astounding heights of reproductive success. This was shown by historical and ethnographic data now strongly confirmed by genomic science. Psychological research confirms that group identity, out-group stigmatization, leadership characterized by charisma, the will to power, narcissism, sociopathy, and cruelty, and followership characterized by hypnotic obedience, loss of individuality, and cruelty are integral parts of human nature. We can thank at least ten or twelve millennia of microevolutionary processes such as those described above, all more prominent in males than females. Followers in wars have faced a difficult risk-benefit analysis, but if they survived and won they too could increase their reproductive success through the rape and other sexual exploitation that have accompanied almost all wars. For modern leaders, social monogamy and contraception have separated autocracy from reproductive success, but only partly, and current worldwide autocratic trends still depend on the evolved will to power, obedience, and cruelty.

A Genetic Map of the Modern Urban Society of Amsterdam

Genetic differences between individuals underlie susceptibility to many diseases. Genome-wide association studies (GWAS) have discovered many susceptibility genes but were often limited to cohorts of predominantly European ancestry. Genetic diversity between individuals due to different ancestries and evolutionary histories shows that this approach has limitations. In order to gain a better understanding of the associated genetic variation, we need a more global genomics approach including a greater diversity. Here, we introduce the Healthy Life in an Urban Setting (HELIUS) cohort. The HELIUS cohort consists of participants living in Amsterdam, with a level of diversity that reflects the Dutch colonial and recent migration past. The current study includes 10,283 participants with genetic data available from seven groups of inhabitants, namely, Dutch, African Surinamese, South-Asian Surinamese, Turkish, Moroccan, Ghanaian, and Javanese Surinamese. First, we describe the genetic variation and admixture within the HELIUS cohort. Second, we show the challenges during imputation when having a genetically diverse cohort. Third, we conduct a body mass index (BMI) and height GWAS where we investigate the effects of a joint analysis of the entire cohort and a meta-analysis approach for the different subgroups. Finally, we construct polygenic scores for BMI and height and compare their predictive power across the different ethnic groups. Overall, we give a comprehensive overview of a genetically diverse cohort from Amsterdam. Our study emphasizes the importance of a less biased and more realistic representation of urban populations for mapping genetic associations with complex traits and disease risk for all.