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Race and ethnicity are population descriptors that clinicians and researchers often use to classify humans. The utility of these groupings in research and clinical contexts warrants scrutiny, since these groupings fail to adequately capture genetic diversity and instead, are proxies for the complex interplay of genetic, social, and structural determinants of health. Here, the authors review the concepts of race, ethnicity, and genetics. They also describe laboratory medicine examples where race and ethnicity are used that warrant scrutiny and revision, and areas where greater emphasis on including racialized minorities is necessary to improve health disparities., Competing Interests: Disclosure The author has nothing to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Quantitative studies of cultural evolution and gene-culture coevolution (henceforth "CE" and "GCC") emerged in the 1970s, in the aftermath of the "race and intelligence quotient (IQ)" and "human sociobiology" debates, as a counter to extreme hereditarian positions. These studies incorporated cultural transmission and its interaction with genetics in contributing to patterns of human variation. Neither CE nor GCC results were consistent with racist claims of ubiquitous genetic differences between socially defined races. We summarize how genetic data refute the notion of racial substructure for human populations and address naive interpretations of race across the biological sciences, including those related to ancestry, health, and intelligence, that help to perpetuate racist ideas. A GCC perspective can refute reductionist and determinist claims while providing a more inclusive multidisciplinary framework in which to interpret human variation., Competing Interests: Competing interests statement:The authors declare no competing interest.

Purpose: To describe the association between geographic location of residence and use of aneuploidy screening or prenatal genetic counseling and how it is modified by maternal race and ethnicity., Methods: Retrospective cohort of individuals at a tertiary care center between 2017-2019. County of residence was classified as rural or metropolitan based in US Office of Management and Budget 2019 definitions. Maternal race and ethnicity were self-identified. Our composite outcome was defined as use of aneuploidy screening or genetic counseling visit. The composite outcome was compared by geographic location and ethnicity. Logistic regression was used to model the relationship between geographic location and the composite outcome., Results: A total of 8774 pregnancies were included. Of these, 4770 (54%) had genetic screening, and 3781 (43%) had at least 1 genetic counseling visit. Rural patients were significantly less likely to have the composite outcome compared with metropolitan peers (37.1% vs 47.2%, P < .001). In addition, we identified differences in the composite outcome between White rural patients and LatinX rural patients (37.7% vs 35.6%, P < .001) and between Asian rural patients and LatinX and Black rural patients (41.0% vs 35.6%, P < .001; 41.0% vs 36.8%, P < .001). Logistic regression demonstrated that rural patients were significantly less likely to have the composite outcome compared with metropolitan peers, after adjusting for LatinX ethnicity and gestational age at first prenatal visit (OR 0.72, [0.55, 0.95], P = .002)., Conclusion: Rural, minority patients were significantly less likely to receive reproductive genetic services compared with metropolitan peers extending our knowledge of disparities in maternity care., Competing Interests: Conflict of Interest Asha N. Talati receives research support from the National Institutes of Health, Billion to One, and The Greenwall Foundation. Divya P. Mallampati receives salary support from the Department of Health and Human Services. Neeta L. Vora receives research support from National Institutes of Health and received supplies in kind from Illumina unrelated to this research., (Copyright © 2024. Published by Elsevier Inc.)

We leveraged information from more than 1.2 million participants, including 97,383 cases, to investigate the genetics of anxiety disorders across five continental groups. Through ancestry-specific and cross-ancestry genome-wide association studies, we identified 51 anxiety-associated loci, 39 of which were novel. In addition, polygenic risk scores derived from individuals of European descent were associated with anxiety in African, admixed American and East Asian groups. The heritability of anxiety was enriched for genes expressed in the limbic system, cerebral cortex, cerebellum, metencephalon, entorhinal cortex and brain stem. Transcriptome-wide and proteome-wide analyses highlighted 115 genes associated with anxiety through brain-specific and cross-tissue regulation. Anxiety also showed global and local genetic correlations with depression, schizophrenia and bipolar disorder and widespread pleiotropy with several physical health domains. Overall, this study expands our knowledge regarding the genetic risk and pathogenesis of anxiety disorders, highlighting the importance of investigating diverse populations and integrating multi-omics information., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Racial biases, which harm marginalized and excluded communities, may be combatted by clarifying misconceptions about race during biology lessons. We developed a human genetics laboratory activity that challenges the misconception that race is biological (biological essentialism). We assessed the relationship between this activity and student outcomes using a survey of students' attitudes about biological essentialism and color-evasive ideology and a concept inventory about phylogeny and human diversity. Students in the human genetics laboratory activity showed a significant decrease in their acceptance of biological essentialism compared with a control group, but did not show changes in color-evasive ideology. Students in both groups exhibited increased knowledge in both areas of the concept inventory, but the gains were larger in the human genetics laboratory. In the second iteration of this activity, we found that only white students' decreases in biological essentialist beliefs were significant and the activity failed to decrease color-evasive ideologies for all students. Concept inventory gains were similar and significant for both white and non-white students in this iteration. Our findings underscore the effectiveness of addressing misconceptions about the biological origins of race and encourage more research on ways to effectively change damaging student attitudes about race in undergraduate genetics education., Competing Interests: Conflicts of interests: The authors declare no conflicts of interest.

Biological trace samples consisting of very few cells pose a challenge to conventional forensic genetic DNA analysis. RNA may be an alternative to DNA when handling low template samples. Whereas each cell only contains two copies of an autosomal DNA segment, the transcriptome retains much of the genomic variation replicated in abundant RNA fragments. In this study, we describe the development of a prototype RNA-based SNP selection set for forensic human identification from low template samples (50 pg gDNA). Whole blood from a subset of the Danish population (41 individuals) and blood stains subjected to degradation at room temperature for up to two weeks were analysed by whole transcriptome shotgun sequencing. Concordance was determined by DNA genotyping with the Infinium Omni5-4 SNP chip. In the 100 protein-coding genes with the most reads, 5214 bi-allelic SNPs with gnomAD minor allele frequencies > 0.1 in the African/African American, East Asian, and (non-Finnish) European populations were identified. Of these, 24 SNPs in 21 genes passed screening in whole blood and degraded blood stains, with a resulting mean match probability of 4.5 ∙ 10 -9 . Additionally, ancestry informative SNPs and SNPs in genes useful for body fluid identification were identified in the transcriptome. Consequently, shotgun sequencing of RNA from low template samples may be used for a vast host of forensic genetics purposes, including simultaneous human and body fluid identification, leading to direct donor identification in the identified body fluid., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The All of Us Research Program ("All of Us") is an initiative led by the National Institutes of Health whose goal is to advance research on personalized medicine and health equity through the collection of genetic, environmental, demographic, and health data from volunteer participants who reside in the USA. The program's emphasis on recruiting a diverse participant cohort makes "All of Us" an effective platform for investigating health disparities. In this work, we analyzed participant electronic health record (EHR) data to identify the diseases and disease categories in the "All of Us" cohort for which racial and ethnic prevalence disparities can be observed. In conjunction with these analyses, we developed the US Health Disparities Browser as an interactive web application that enables users to visualize differences in race- and ethnic-group-specific prevalence estimates for 1755 different diseases: https://usdisparities.biosci.gatech.edu/. The web application features a catalog of all diseases represented in the browser, which can be sorted by overall prevalence as well as the variance in prevalence across racial and ethnic groups. The analyses outlined here provide details on the nature and extent of racial and ethnic health disparities in the "All of Us" participant cohort, and the accompanying browser can serve as a resource through which researchers can explore these disparities Database URL: https://usdisparities.biosci.gatech.edu., (Published by Oxford University Press 2024. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Genetic counseling outcomes are influenced by the processes and strategies used by counselors, yet little is known about how these strategies directly impact patients and populations. In particular, tailoring genetic counseling consultations to best meet the needs of cultural, racial, and ethnically diverse populations has been explored. This review aims to identify genetic counseling strategies tailored for a diversity of racial and ethnic populations with the goal to find ways to improve genetic counseling outcomes. Medline, Cochrane CENTRAL, Embase, PsychInfo, and CINAHL databases were searched for original research articles published in English that employed genetic counseling processes and strategies to improve genetic counseling outcomes, specifically for participants from ethnically or racially diverse populations. A review of 5300 titles and abstracts resulted in the identification of 36 articles that met the inclusion criteria. Three themes emerged: (1) community involvement in culturally tailoring genetic counseling, (2) creation and use of culturally tailored resources, and (3) modifications to the genetic counseling process. The effectiveness of genetic counseling strategies could not be evaluated due to lack of consistent outcome measures in the articles. The involvement of diverse ethnic and racial populations in developing inclusive genetic counseling tools and practices will help the profession provide better patient care in the future. More research connecting genetic counseling processes and outcomes will help to assess how well these modified approaches meet the needs of diverse populations., (© 2023 The Authors. Journal of Genetic Counseling published by Wiley Periodicals LLC on behalf of National Society of Genetic Counselors.)

Genetic variation that influences gene expression and splicing is a key source of phenotypic diversity 1-5 . Although invaluable, studies investigating these links in humans have been strongly biased towards participants of European ancestries, which constrains generalizability and hinders evolutionary research. Here to address these limitations, we developed MAGE, an open-access RNA sequencing dataset of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project 6 , spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, which mirrored the variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-expression quantitative trait loci (eQTLs) and cis-splicing QTLs (sQTLs), respectively). We identified more than 15,000 putatively causal eQTLs and more than 16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1,310 eQTLs and 1,657 sQTLs that are largely private to underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations. Moreover, the apparent 'population-specific' effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands our understanding of human gene expression diversity and provides an inclusive resource for studying the evolution and function of human genomes., (© 2024. The Author(s).)

The KRAS mutation is the most common oncogenic driver in patients with non-small cell lung cancer (NSCLC). However, a detailed understanding of how self-reported race and/or ethnicity (SIRE), genetically inferred ancestry (GIA), and their interaction affect KRAS mutation is largely unknown. Here, we investigated the associations between SIRE, quantitative GIA, and KRAS mutation and its allele-specific subtypes in a multi-ethnic cohort of 3,918 patients from the Boston Lung Cancer Survival cohort and the Chinese OrigiMed cohort with an independent validation cohort of 1,450 patients with NSCLC. This comprehensive analysis included detailed covariates such as age at diagnosis, sex, clinical stage, cancer histology, and smoking status. We report that SIRE is significantly associated with KRAS mutations, modified by sex, with SIRE-Asian patients showing lower rates of KRAS mutation, transversion substitution, and the allele-specific subtype KRAS G12C compared to SIRE-White patients after adjusting for potential confounders. Moreover, GIA was found to correlate with KRAS mutations, where patients with a higher proportion of European ancestry had an increased risk of KRAS mutations, especially more transition substitutions and KRAS G12D . Notably, among SIRE-White patients, an increase in European ancestry was linked to a higher likelihood of KRAS mutations, whereas an increase in admixed American ancestry was associated with a reduced likelihood, suggesting that quantitative GIA offers additional information beyond SIRE. The association of SIRE, GIA, and their interplay with KRAS driver mutations in NSCLC highlights the importance of incorporating both into population-based cancer research, aiming to refine clinical decision-making processes and mitigate health disparities., Competing Interests: Declaration of interests B.E.J. reports he is a paid consultant to Novartis, Checkpoint Therapeutics, Astra Zeneca, Daichi Sankyo, GSK, Hummingbird Diagnostics, Genentech, Bluedot Bio, G1 Therapeutics, Jazz Pharmaceuticals, Merus, Abdera, Redona, and Simcere Pharmaceutical; an unpaid member of the steering committee for Pfizer; and has received research support from Cannon Medical Imaging. B.R. reports honoraria from Targeted Oncology and advisory board participation from Regeneron, AstraZeneca, and AMGEN. J.L. reports honoraria from Targeted Oncology, Physicians’ Education Resource, VJ Oncology, Cancer GRACE, and Community Cancer Education, Inc.; advisory board participation from AstraZeneca; research support to her institution from Erasca, Genentech, Kronos Bio, Novartis, and Revolution Medicines; and personal fees from Erasca, Blueprint Medicines, and Daiichi Sankyo. A patent filed by MSK related to multimodal features to predict response to immunotherapy (PCT/US2023/115872) is pending. M.M.A. serves as a consultant to Merck, Bristol-Myers Squibb, Genentech, AstraZeneca, Nektar, Maverick, Blueprint Medicine, Syndax, Abbvie, Gritstone, ArcherDX, Mirati, NextCure, and EMD Serono and has received research funding from Bristol-Myers Squibb, Lilly, Genentech, AstraZeneca, and the Elva J. and Clayton L. McLaughlin Fund for Lung Cancer Research., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Epidemiological studies frequently classify groups based on phenotypes like self-reported skin color/race, which inaccurately represent genetic ancestry and may lead to misclassification, particularly among individuals of multiracial backgrounds. This study aimed to characterize both global and local genome-wide genetic ancestries and to assess their relationship with self-reported skin color/race in an admixed population of Sao Paulo city. We analyzed 226,346 single-nucleotide polymorphisms from 841 individuals participating in the population-based ISA-Nutrition study. Our findings confirmed the admixed nature of the population, demonstrating substantial European, significant Sub-Saharan African, and minor Native American ancestries, irrespective of skin color. A correlation was observed between global genetic ancestry and self-reported color-race, which was more evident in the extreme proportions of African and European ancestries. Individuals with higher African ancestry tended to identify as Black, those with higher European ancestry tended to identify as White, and individuals with higher Native American ancestry were more likely to self-identify as Mixed, a group with diverse ancestral compositions. However, at the individual level, this correlation was notably weak, and no deviations were observed for specific regions throughout the individual's genome. Our findings emphasize the significance of accurately defining and thoroughly analyzing race and ancestry, especially within admixed populations.

The use of genetic markers, specifically Short Tandem Repeats (STRs), has been a valuable tool for identifying persons of interest. However, the ability to analyze additional markers including Single Nucleotide Polymorphisms (SNPs) and Insertion/Deletion (INDELs) polymorphisms allows laboratories to explore other investigative leads. INDELs were chosen in this study because large panels can be differentiated by size, allowing them to be genotyped by capillary electrophoresis. Moreover, these markers do not produce stutter and are smaller in size than STRs, facilitating the recovery of genetic information from degraded samples. The INDEL Ancestry Informative Markers (AIMs) in this study were selected from the 1000 Genomes Project based on a fixation index (F ST ) greater than 0.50, high allele frequency divergence, and genetic distance. A total of 25 INDEL-AIMs were optimized and validated according to SWGDAM guidelines in a five-dye multiplex. To validate the panel, genotyping was performed on 155 unrelated individuals from four ancestral groups (Caucasian, African, Hispanic, and East Asian). Bayesian clustering and principal component analysis (PCA) were performed revealing clear separation among three groups, with some observed overlap within the Hispanic group. Additionally, the PCA results were compared against a training set of 793 samples from the 1000 Genomes Project, demonstrating consistent results. Validation studies showed the assay to be reproducible, tolerant to common inhibitors, robust with challenging casework type samples, and sensitive down to 125 pg. In conclusion, our results demonstrated the robustness and effectiveness of a 25 loci INDEL system for ancestry inference of four ancestries commonly found in the United States., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: Ethnic diversity in cancer research is crucial as race/ethnicity influences cancer incidence, survival, drug response, molecular pathways, and epigenetic phenomena. In 2018, we began a project to examine racial/ethnic diversity in cancer research, with a commitment to review these disparities every 4 years. This report is our second assessment, detailing the present state of racial/ethnic diversity in cancer genomics and clinical trials., Methods: To study racial/ethnic inclusion in cancer genomics, we extracted ethnic records from all data sets available at cBioPortal (n = 125,128 patients) and cancer-related genome-wide association studies (n = 28,011,282 patients) between 2018 and 2022. Concerning clinical trials, we selected studies related to breast cancer (n = 125,518 patients, 181 studies), lung cancer (n = 34,329 patients, 119 studies), and colorectal cancer (n = 40,808 patients, 105 studies)., Results: In cancer genomics (N = 28,136,410), 3% of individuals lack racial/ethnic registries; tumor samples were collected predominantly from White patients (89.14%), followed by Asian (7%), African American (0.55%), and Hispanic (0.21%) patients and other populations (0.1%). In clinical trials (N = 200,655), data on race/ethnicity are missing for 60.14% of the participants; for individuals whose race/ethnicity was recorded, most were characterized as White (28.33%), followed by Asian (7.64%), African (1.79), other ethnicities (1.37), and Hispanic (0.73). Racial/ethnic representation significantly deviates from global ethnic proportions ( P ≤ .001) across all data sets, with White patients outnumbering other ethnic groups by a factor of approximately 4-6., Conclusion: Our second update on racial/ethnic representation in cancer research highlights the persistent overrepresentation of White populations in cancer genomics and a notable absence of racial/ethnic information across clinical trials. To ensure more equitable and effective precision oncology, future efforts should address the reasons behind the insufficient representation of ethnically diverse populations in cancer research.

Objective: The influence of socioeconomic factors on racial disparities among patients with sporadic meningiomas is well established, yet other potential causative factors warrant further exploration. The authors of this study aimed to determine whether there is significant variation in the genomic profile of meningiomas among patients of different races and ethnicities and its correlation with clinical outcomes., Methods: The demographic, genomic, and clinical data of patients aged 18 years and older who had undergone surgery for sporadic meningioma between September 2008 and November 2021 were analyzed. Statistical analyses were performed to detect differences across all racial/ethnic groups, as were direct comparisons between Black and non-Black groups plus Hispanic and non-Hispanic groups., Results: This study included 460 patients with intracranial meningioma. Hispanic patients were significantly younger at surgery (53.9 vs 60.2 years, p = 0.0006) and more likely to show symptoms. Black patients had a higher incidence of anterior skull base tumors (OR 3.2, 95% CI 1.7-6.3, p = 0.0008) and somatic hedgehog mutations (OR 5.3, 95% CI 1.6-16.6, p = 0.003). Hispanics were less likely to exhibit the aggressive genomic characteristic of chromosome 1p deletion (OR 0.28, 95% CI 0.07-1.2, p = 0.06) and displayed higher rates of TRAF7 somatic driver mutations (OR 2.96 95% CI 1.1-7.8, p = 0.036). Black patients had higher rates of recurrence (OR 2.6, 95% CI 1.3-5.2, p = 0.009) and shorter progression-free survival (PFS; HR 2.9, 95% CI 1.6-5.4, p = 0.002) despite extents of resection (EORs) similar to those of non-Black patients (p = 0.745). No significant differences in overall survival were observed among groups., Conclusions: Despite similar EORs, Black patients had worse clinical outcomes following meningioma resection, characterized by a higher prevalence of somatic hedgehog mutations, increased recurrence rates, and shorter PFS. Meanwhile, Hispanic patients had less aggressive meningiomas, a predisposition for TRAF7 mutations, and no difference in PFS. These findings could inform the care and treatment strategies for meningiomas, and they establish the foundation for future studies focusing on the genomic origins of these observed differences.

Differences in cancer genomes between racial groups may impact tumor biology and health disparities. However, the discovery of race-associated mutations is constrained by the limited representation and sample size of different racial groups in prior genomic studies. We evaluated the influence of race on the frequency of gene mutations using the Genomics, Evidence, Neoplasia, Information, Exchange database, a large genomic dataset aggregated from clinical sequencing. Matched cohort analyses were used to identify histology-specific race-associated mutations including increased TERT promoter mutations in Black and Asian patients with gliomas and bladder cancers, and a decreased frequency of mutations in DNA repair pathway genes and subunits of the SWI/SNF chromatin complex in Asian and Black patients across multiple cancer types. The distribution of actionable mutations in oncogenes was also race-specific, demonstrating how targeted therapies may have a disparate impact on racial groups. Down-sampling analyses indicate that larger sample sizes are likely to discover more race-associated mutations. These results provide a resource to understand differences in cancer genomes between racial groups which may inform the design of clinical studies and patient recruitment strategies in biomarker trials., (© The Author(s) 2024. Published by Oxford University Press.)

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics 1-4 . The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health 5,6 . Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all., (© 2024. The Author(s).)

Background: Genetic testing can help determine the risk of many cancers and guide cancer prevention and treatment plans. Despite increasing concern about disparities in precision cancer medicine, public knowledge and cancer genetic testing by race and ethnicity have not been well investigated., Methods: We analyzed data from the 2020 Health Information National Trends Survey in 2022. Self-reported cancer genetic testing (e.g., Lynch syndrome, BRCA1/2) knowledge and utilization were compared by race and ethnicity. Perceived importance of genetic information for cancer care (prevention, detection, and treatment) was also examined in relation to the uptake of cancer genetic testing. Multivariable logistic regression models were employed to examine factors associated with knowledge and genetic testing to calculate predicted probability of undergoing genetic testing by race and ethnicity., Results: Of 3551 study participants, 37.8% reported having heard of genetic testing for cancer risk and 3.9% stated that they underwent cancer genetic testing. Being non-Hispanic Black (OR=0.47, 95% CI=0.30-0.75) or Hispanic (OR=0.56, CI=0.35-0.90) was associated with lower odds of genetic testing knowledge. Although Hispanic or non-Hispanic Black respondents were more likely to perceive higher importance of genetic information versus non-Hispanic Whites, they had a lower predicted probability of cancer genetic testing., Conclusion: Non-Hispanic Black and Hispanic adults had lower knowledge and were less likely to undergo cancer genetic testing than non-Hispanic Whites. Further research is needed on sources of genetic testing information for racial and ethnic minorities and the barriers to accessing genetic testing to inform the development of effective cancer risk genetic testing promotion., (© 2023. W. Montague Cobb-NMA Health Institute.)

The heritability of susceptibility to tuberculosis (TB) disease has been well recognized. Over 100 genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicate. We established the International Tuberculosis Host Genetics Consortium to perform a multi-ancestry meta-analysis of GWAS, including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h 2 = 26.3%, 95% CI 23.7-29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p<5 × 10 -8 ) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value=5.2 × 10 -9 ) but failed to replicate variants previously associated with TB susceptibility. These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressure., Competing Interests: HS, VN, TY, JG, TP, PD, MM, EH, AM, AH No competing interests declared, (© 2024, Schurz et al.)

Racial disparities between Black/African Americans (AA) and White patients in colorectal cancer are an ever-growing area of concern. Black/AA show the highest incidence and have the highest mortality among major U.S. racial groups. There is no definite cause other than possible sociodemographic, socioeconomic, education, nutrition, delivery of healthcare, screening, and cultural factors. A primary limitation in this field is the lack of and small sample size of Black/AA studies. Thus, this study aimed to investigate whether differences in gene expression contribute to this ongoing unanswered racial disparity issue. In this study, we examined transcriptomic data of Black/AA and White patient cohorts using a bioinformatic and systems biology approach. We performed a Kaplan-Meier overall survival analysis between both patient cohorts across critical colorectal cancer signal transduction networks (STN), to determine the differences in significant genes across each cohort. Other bioinformatic analyses performed included PROGENy (pathway responsive genes for activity inference), RNA sequencing differential expression using DESeq2, multivariable-adjusted regression, and other associated Kaplan-Meier analyses. These analyses identified novel prognostic genes independent from each cohort, 176 differentially expressed genes, and specific patient cohort STN survival associations. Despite the overarching limitation, the results revealed several novel differences in gene expression between the colorectal cancer Black/AA and White patient cohorts, which allows one to dive deeper into and understand the behavior on a systems level of what could be driving this racial difference across colorectal cancer. Concretely, this information can guide precision medicine approaches tailored specifically for colorectal cancer racial disparities., Significance: The purpose of this work is to investigate the racial disparities in colorectal cancer between Black/AA and White patient cohorts using a systems biology and bioinformatic approach. Our study investigates the underlying biology of each patient cohort. Concretely, the findings of this study include disparity-associated genes and pathways, which provide a tangible starting point to guide precision medicine approaches tailored specifically for colorectal cancer racial disparities., (© 2024 The Authors; Published by the American Association for Cancer Research.)

Background: We previously showed the 21-gene breast recurrence score (RS) has lower prognostic accuracy for non-Hispanic Black (NHB) compared with non-Hispanic White (NHW) women with estrogen receptor (ER)-positive/HER2-negative breast cancer. The purpose of this study was to determine the clinical validity of the RS for predicting chemotherapy benefit as recommended in the current NCCN Guidelines for Breast Cancer among women from diverse racial/ethnic groups., Methods: Using the SEER Oncotype database, we estimated propensity score-weighted hazard ratios (HRs) and 95% confidence intervals for breast cancer death with chemotherapy for women with ER-positive/HER2-negative, AJCC stages I-II, axillary node-negative, invasive breast cancer according to race/ethnicity., Results: We included 6,033 (8.2%) Asian/Pacific Islander (API), 5,697 (7.8%) NHB, 6,688 (9.1%) Hispanic, and 54,945 (74.9%) NHW women. Breast cancer death was reduced with chemotherapy for NHB (HR, 0.48, 95% CI, 0.28-0.81), Hispanic (HR, 0.48; 95% CI, 0.25-0.94), and NHW (HR, 0.80; 95% CI, 0.65-0.99) women with an RS of 26 to 100. There was a nonsignificant reduction for API women (HR, 0.59; 95% CI, 0.28-1.24). For women with an RS of 11 to 25, there was no reduction in death for any racial/ethnic group. Among women aged ≤50 years, the reduction in breast cancer death with chemotherapy differed according to race (NHB: HR, 0.37 [95% CI, 0.20-0.67]; NHW: HR, 0.56 [95% CI, 0.44-0.74]; Pinteraction for chemotherapy * race <.0499). An exploratory subgroup analysis found that young NHB women may benefit from chemotherapy at a lower RS cutoff than other women., Conclusions: The RS was clinically validated as a predictive biomarker for NHB, Hispanic, and NHW women with ER-positive, axillary node-negative breast cancer, but it may underestimate the benefit of chemotherapy for young NHB women. If this finding is confirmed, the RS cutoff for recommending adjuvant chemotherapy for young NHB women with ER-positive, axillary node-negative breast cancer may need to be lower than for other women.

The incompleteness of race and ethnicity information in real-world data (RWD) hampers its utility in promoting healthcare equity. This study introduces two methods-one heuristic and the other machine learning-based-to impute race and ethnicity from genetic ancestry using tumor profiling data. Analyzing de-identified data from over 100,000 cancer patients sequenced with the Tempus xT panel, we demonstrate that both methods outperform existing geolocation and surname-based methods, with the machine learning approach achieving high recall (range: 0.859-0.993) and precision (range: 0.932-0.981) across four mutually exclusive race and ethnicity categories. This work presents a novel pathway to enhance RWD utility in studying racial disparities in healthcare.

There is a desire in research to move away from the concept of race as a clinical factor because it is a societal construct used as an imprecise proxy for geographic ancestry. In this study, we leverage the biobank from Vanderbilt University Medical Center, BioVU, to investigate relationships between genetic ancestry proportion and the clinical phenome. For all samples in BioVU, we calculated six ancestry proportions based on 1000 Genomes references: eastern African (EAFR), western African (WAFR), northern European (NEUR), southern European (SEUR), eastern Asian (EAS), and southern Asian (SAS). From PheWAS, we found phecode categories significantly enriched neoplasms for EAFR, WAFR, and SEUR, and pregnancy complication in SEUR, NEUR, SAS, and EAS (p < 0.003). We then selected phenotypes hypertension (HTN) and atrial fibrillation (AFib) to further investigate the relationships between these phenotypes and EAFR, WAFR, SEUR, and NEUR using logistic regression modeling and non-linear restricted cubic spline modeling (RCS). For EAS and SAS, we chose renal failure (RF) for further modeling. The relationships between HTN and AFib and the ancestries EAFR, WAFR, and SEUR were best fit by the linear model (beta p < 1x10-4 for all) while the relationships with NEUR were best fit with RCS (HTN ANOVA p = 0.001, AFib ANOVA p < 1x10-4). For RF, the relationship with SAS was best fit with a linear model (beta p < 1x10-4) while RCS model was a better fit for EAS (ANOVA p < 1x10-4). In this study, we identify relationships between genetic ancestry and phenotypes that are best fit with non-linear modeling techniques. The assumption of linearity for regression modeling is integral for proper fitting of a model and there is no knowing a priori to modeling if the relationship is truly linear.

The mapping and sequencing of the human genome at the turn of the new millennium marks a pivotal reassessment of genomic science in its potential to replace traditional "one-size-fits-all" medicine with a personalised approach. The use of racial proxies in the development of pharmacogenomic products risks conflating genetics with race under the guise of alleviating health disparities. This article argues that the current genomic approaches to realising personalised medicine do not deliver on the promise for optimised health for all and may result in irreversible harm, including psychological, social and medical harm, to racial minority groups. In light of recent epigenetic findings, the article provides a reconceptualisation of the genome and race, which is necessary to understand enduring racial disparities and the cumulative effects of racial discrimination. It then addresses the need for regulatory oversight of the approval of race-based pharmacogenomic products., Competing Interests: No conflict declared.

Importance: Variants of uncertain significance (VUSs) are rampant in clinical genetic testing, frustrating clinicians, patients, and laboratories because the uncertainty hinders diagnoses and clinical management. A comprehensive assessment of VUSs across many disease genes is needed to guide efforts to reduce uncertainty., Objective: To describe the sources, gene distribution, and population-level attributes of VUSs and to evaluate the impact of the different types of evidence used to reclassify them., Design, Setting, and Participants: This cohort study used germline DNA variant data from individuals referred by clinicians for diagnostic genetic testing for hereditary disorders. Participants included individuals for whom gene panel testing was conducted between September 9, 2014, and September 7, 2022. Data were analyzed from September 1, 2022, to April 1, 2023., Main Outcomes and Measures: The outcomes of interest were VUS rates (stratified by age; clinician-reported race, ethnicity, and ancestry groups; types of gene panels; and variant attributes), percentage of VUSs reclassified as benign or likely benign vs pathogenic or likely pathogenic, and enrichment of evidence types used for reclassifying VUSs., Results: The study cohort included 1 689 845 individuals ranging in age from 0 to 89 years at time of testing (median age, 50 years), with 1 203 210 (71.2%) female individuals. There were 39 150 Ashkenazi Jewish individuals (2.3%), 64 730 Asian individuals (3.8%), 126 739 Black individuals (7.5%), 5539 French Canadian individuals (0.3%), 169 714 Hispanic individuals (10.0%), 5058 Native American individuals (0.3%), 2696 Pacific Islander individuals (0.2%), 4842 Sephardic Jewish individuals (0.3%), and 974 383 White individuals (57.7%). Among all individuals tested, 692 227 (41.0%) had at least 1 VUS and 535 385 (31.7%) had only VUS results. The number of VUSs per individual increased as more genes were tested, and most VUSs were missense changes (86.6%). More VUSs were observed per sequenced gene in individuals who were not from a European White population, in middle-aged and older adults, and in individuals who underwent testing for disorders with incomplete penetrance. Of 37 699 unique VUSs that were reclassified, 30 239 (80.2%) were ultimately categorized as benign or likely benign. A mean (SD) of 30.7 (20.0) months elapsed for VUSs to be reclassified to benign or likely benign, and a mean (SD) of 22.4 (18.9) months elapsed for VUSs to be reclassified to pathogenic or likely pathogenic. Clinical evidence contributed most to reclassification., Conclusions and Relevance: This cohort study of approximately 1.6 million individuals highlighted the need for better methods for interpreting missense variants, increased availability of clinical and experimental evidence for variant classification, and more diverse representation of race, ethnicity, and ancestry groups in genomic databases. Data from this study could provide a sound basis for understanding the sources and resolution of VUSs and navigating appropriate next steps in patient care.

Biogeographical origin inferences of different populations can provide valuable clues in the forensic investigation by narrowing down the detection scope. However, much research mainly focuses on forensic ancestral origin analyses of major continental populations, which may provide limited information in forensic practice. To improve the ancestral resolution of East Asian populations, we systematically selected ancestry informative single-nucleotide polymorphisms (AISNPs) for differentiating Han, Dai, Japanese, and Kinh populations. In addition, we evaluated the performance of the selected AISNPs to differentiate these populations via multiple methods. Totally 116 AISNPs were selected from the genome-wide data to infer the population origins of these four populations. Results of principle component analysis and population genetic structure of these populations indicated that the selected 116 AISNPs could achieve ancestral resolution of most individuals. Furthermore, the machine learning model built by 116 AISNPs unveiled that most individuals from these four populations could be assigned to correct population origins. To sum up, the selected 116 SNPs could be available for ancestral origin predictions of Han, Dai, Japanese, and Kinh populations, which could provide valuable information for forensic research and genome-wide association study in East Asian populations to some extent., (© 2023 Wiley-VCH GmbH.)

In addition to the validated ancestry-informative single nucleotide polymorphisms (AI-SNPs) in classic panels, there are many new potential AI-SNPs yet to be explored. Moreover, the search for AI-SNPs with highly discriminative power for ancestry inference in inter- and intra-continental populations has become a realistic need. In this study, 126 novel AI-SNPs were selected to distinguish the African, European, Central/South Asian and East Asian populations, and a random forest model was introduced to assess the performance of the AI-SNP set. This panel was further used in the genetic analysis of the Manchu group in Inner Mongolia, China, based on 79 reference populations from seven continental regions. Results showed that the 126 AI-SNPs were able to achieve the ancestry informative inference for African, East Asian, European, and Central/South Asian populations. Population genetic analyses indicated that the Manchu group in Inner Mongolia was genetically typical of East Asian populations and was more closely related to the northern Han Chinese and Japanese than to other Altaic-speaking populations. Overall, this study provided a selection of new promising loci of ancestry inference for major intercontinental populations and intracontinental subgroups, as well as genetic insights and valuable data for dissecting the genetic structure of the Inner Mongolian Manchu group., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Less than a decade after the discovery of the ABO antigens as a Mendelian inherited trait, blood group antigen frequencies were first used to define racial groups. This approach, known as seroanthropology, was the basis for collecting large amounts of blood group frequency data in different populations and was also sometimes used for racist purposes. Ultimately, population geneticists used these data to disprove race as a biological construct. Through understanding the history of seroanthropology, and recognizing the harms of its lingering presence, healthcare providers can better practice race-conscious, as opposed to race-based, transfusion medicine., Competing Interests: Declaration of Competing Interest The authors report no conflicts of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Introduction: Introduction: the GA haplotype of polymorphisms rs1554483 and rs4864548 has been associated with components of the metabolic syndrome such as high blood pressure and triglyceride levels; its carriers have a risk of obesity, 1.5 times higher than the rest of the population. Methodology: SNP rs1554483 and rs4864548 were obtained from 2504 individuals from the "1000genomes phase 3" database. Data were grouped into five macro populations (Africa, East Asia, South Asia, Europe and Latin America) covering a total of 26 populations. Differences in haplotype frequency between macro populations and populations were analyzed, for which Fisher's F statistic was used. Results: the macro population of Africa presented the lowest frequency (17.9 %) and that of East Asia the highest (57.4 %). Within the populations there is a relative homogeneity in the frequencies, except in the case of those that make up the macro population of Latin America where the Peruvian population of Lima and the Puerto Rican population present much higher frequencies than the rest. Conclusions: the GA haplotype presents heterogeneity between macro populations, which suggests highly differentiated micro evolutionary processes between continents. We propose to study the association of the GA haplotype with other polymorphisms such as rs3749474, rs11932595 and rs6859524 that have also been associated with risk of obesity and factors associated with metabolic syndrome.

Background: The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953])., Results: Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010 < Cohen's d < 0.259, p < 7.80 × 10 -4 ). Conversely, HARE-assigned East Asians showed an increase in European ancestry proportion over time. In GWAS of height using HARE assignments, genomic inflation due to population stratification was prevalent across all birth cohorts (linkage disequilibrium score regression intercept = 1.08 ± 0.042). The 1kGP + HGDP-based ancestry assignment significantly reduced the population stratification (mean intercept reduction = 0.045 ± 0.007, p < 0.05) confounding in the GWAS statistics., Conclusions: This study provides a characterization of ancestry diversity of the MVP cohort over time and compares two strategies to infer genetically defined ancestry groups by assessing differences in controlling population stratification in genome-wide association studies., (© 2023. The Author(s).)

Polygenic scores (PGSs) have limited portability across different groupings of individuals (for example, by genetic ancestries and/or social determinants of health), preventing their equitable use 1-3 . PGS portability has typically been assessed using a single aggregate population-level statistic (for example, R 2 ) 4 , ignoring inter-individual variation within the population. Here, using a large and diverse Los Angeles biobank 5 (ATLAS, n = 36,778) along with the UK Biobank 6 (UKBB, n = 487,409), we show that PGS accuracy decreases individual-to-individual along the continuum of genetic ancestries 7 in all considered populations, even within traditionally labelled 'homogeneous' genetic ancestries. The decreasing trend is well captured by a continuous measure of genetic distance (GD) from the PGS training data: Pearson correlation of -0.95 between GD and PGS accuracy averaged across 84 traits. When applying PGS models trained on individuals labelled as white British in the UKBB to individuals with European ancestries in ATLAS, individuals in the furthest GD decile have 14% lower accuracy relative to the closest decile; notably, the closest GD decile of individuals with Hispanic Latino American ancestries show similar PGS performance to the furthest GD decile of individuals with European ancestries. GD is significantly correlated with PGS estimates themselves for 82 of 84 traits, further emphasizing the importance of incorporating the continuum of genetic ancestries in PGS interpretation. Our results highlight the need to move away from discrete genetic ancestry clusters towards the continuum of genetic ancestries when considering PGSs., (© 2023. The Author(s).)

Dental size variation in modern humans has been assessed from regional to worldwide scales, especially under microevolutionary and forensic contexts. Despite this, populations of mixed continental ancestry such as contemporary Latin Americans remain unexplored. In the present study we investigated a large Latin American sample from Colombia (N = 804) and obtained buccolingual and mesiodistal diameters and three indices for maxillary and mandibular teeth (except third molars). We evaluated the correlation between 28 dental measurements (and three indices) with age, sex and genomic ancestry (estimated using genome-wide SNP data). In addition, we explored correlation patterns between dental measurements and the biological affinities, based on these measurements, between two Latin American samples (Colombians and Mexicans) and three putative parental populations: Central and South Native Americans, western Europeans and western Africans through PCA and DFA. Our results indicate that Latin Americans have high dental size diversity, overlapping the variation exhibited by the parental populations. Several dental dimensions and indices have significant correlations with sex and age. Western Europeans presented closer biological affinities with Colombians, and the European genomic ancestry exhibited the highest correlations with tooth size. Correlations between tooth measurements reveal distinct dental modules, as well as a higher integration of postcanine dentition. The effects on dental size of age, sex and genomic ancestry is of relevance for forensic, biohistorical and microevolutionary studies in Latin Americans., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Biogeographical ancestry (BGA) inference from ancestry-informative markers (AIMs) has strong potential to support forensic investigations. Over the past two decades, several forensic panels composed of AIMs have been developed to predict ancestry at a continental scale. These panels typically comprise fewer than 200 AIMs and have been designed and tested with a limited set of populations. How well these panels recover patterns of genetic diversity relative to larger sets of markers, and how accurately they infer ancestry of individuals and populations not included in their design remains poorly understood. The lack of comparative studies addressing these aspects makes the selection of appropriate panels for forensic laboratories difficult. In this study, the model-based genetic clustering tool STRUCTURE was used to compare three popular forensic BGA panels: MAPlex, Precision ID Ancestry Panel (PIDAP), and VISAGE Basic Tool (VISAGE BT) relative to a genome-wide reference set of 10k SNPs. The genotypes for all these markers were obtained for a comprehensive set of 3957 individuals from 228 worldwide human populations. Our results indicate that at the broad continental scale (K=6) typically examined in forensic studies, all forensic panels produced similar genetic structure patterns compared to the reference set (G'≈90%) and had high classification performance across all regions (average AUC-PR > 97%). However, at K= 7 and K= 8, the forensic panels displayed some region-specific clustering deviations from the reference set, particularly in Europe and the region of East and South-East Asia, which may be attributed to differences in the design of the respective panels. Overall, the panel with the most consistent performance in all regions was VISAGE BT with an average weighted AUC̅ W score of 96.26% across the three scales of geographical resolution investigated., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Individuals of admixed ancestries (for example, African Americans) inherit a mosaic of ancestry segments (local ancestry) originating from multiple continental ancestral populations. This offers the unique opportunity of investigating the similarity of genetic effects on traits across ancestries within the same population. Here we introduce an approach to estimate correlation of causal genetic effects (r admix ) across local ancestries and analyze 38 complex traits in African-European admixed individuals (N = 53,001) to observe very high correlations (meta-analysis r admix  = 0.95, 95% credible interval 0.93-0.97), much higher than correlation of causal effects across continental ancestries. We replicate our results using regression-based methods from marginal genome-wide association study summary statistics. We also report realistic scenarios where regression-based methods yield inflated heterogeneity-by-ancestry due to ancestry-specific tagging of causal effects, and/or polygenicity. Our results motivate genetic analyses that assume minimal heterogeneity in causal effects by ancestry, with implications for the inclusion of ancestry-diverse individuals in studies., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

The prevalence and severity of SLE have been found to vary across populations of different ancestries. This review explores whether these differences can be explained by the genetic aetiology of the condition. Large genetic studies suggest that populations of different ancestry share the same risk loci but individual risk alleles are more common in some, leading to a higher prevalence and severity and an earlier onset of the condition. Despite many of the loci being shared across populations, some have been found to be ancestry specific and these are hypothesized to have undergone differential selective pressure in recent human history. Additionally, the effectiveness of some of the drugs used in SLE has been found to vary across ancestries, which might affect progression of the disease, but it is unclear whether these differences are pharmacogenetic. We concluded that to understand the full role of genetics in the risk, presentation and response to treatment of SLE, larger studies including individuals from a wider representation of ancestries will be required., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

The biogeographical ancestry (BGA) of a trace or a person/skeleton refers to the component of ethnicity, constituted of biological and cultural elements, that is biologically determined. Nowadays, many individuals are interested in exploring their genealogy, and the capability to distinguish biogeographic information about population groups and subgroups via DNA analysis plays an essential role in several fields such as in forensics. In fact, for investigative and intelligence purposes, it is beneficial to inference the biogeographical origins of perpetrators of crimes or victims of unsolved cold cases when no reference profile from perpetrators or database hits for comparative purposes are available. Current approaches for biogeographical ancestry estimation using SNPs data are usually based on PCA and Structure software. The present study provides an alternative method that involves multivariate data analysis and machine learning strategies to evaluate BGA discriminating power of unknown samples using different commercial panels. Starting from 1000 Genomes project, Simons Genome Diversity Project and Human Genome Diversity Project datasets involving African, American, Asian, European and Oceania individuals, and moving towards further and more geographically restricted populations, powerful multivariate techniques such as Partial Least Squares-Discriminant Analysis (PLS-DA) and machine learning techniques such as XGBoost were employed, and their discriminating power was compared. PLS-DA method provided more robust classifications than XGBoost method, showing that the adopted approach might be an interesting tool for forensic experts to infer BGA information from the DNA profile of unknown individuals, but also highlighting that the commercial forensic panels could be inadequate to discriminate populations at intra-continental level., (© 2022. The Author(s).)

Of the multifactorial determinants that lead to cancer health disparities among race groups, quantified genetic ancestry has begun to expand our knowledge beyond self-reported race. However, it is essential to study these biological determinants in the context of social determinants to truly improve clinical tools and achieve equitable survival outcomes., (Copyright © 2021. Published by Elsevier Inc.)