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At least 19 recordsLinked to original sources

The Longue Durée of genetic ancestry: multiple genetic marker systems and Celtic origins on the Atlantic facade of Europe.

Celtic languages are now spoken only on the Atlantic facade of Europe, mainly in Britain and Ireland, but were spoken more widely in western and central Europe until the collapse of the Roman Empire in the first millennium a.d. It has been common to couple archaeological evidence for the expansion of Iron Age elites in central Europe with the dispersal of these languages and of Celtic ethnicity and to posit a central European "homeland" for the Celtic peoples. More recently, however, archaeologists have questioned this "migrationist" view of Celtic ethnogenesis. The proposition of a central European ancestry should be testable by examining the distribution of genetic markers; however, although Y-chromosome patterns in Atlantic Europe show little evidence of central European influence, there has hitherto been insufficient data to confirm this by use of mitochondrial DNA (mtDNA). Here, we present both new mtDNA data from Ireland and a novel analysis of a greatly enlarged European mtDNA database. We show that mtDNA lineages, when analyzed in sufficiently large numbers, display patterns significantly similar to a large fraction of both Y-chromosome and autosomal variation. These multiple genetic marker systems indicate a shared ancestry throughout the Atlantic zone, from northern Iberia to western Scandinavia, that dates back to the end of the last Ice Age.

Base Sequence↗

Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.

The broader application of polygenic risk score (PRS) is hindered by the limited transferability of PRS developed in Europeans to non-European populations. While many statistical methods have been developed to improve the performance of PRS in non-European populations, most of them focused on discrete genetic ancestry clusters and did not consider admixed individuals. Admixed individuals pose a unique challenge for PRS calculation due to the complexity of local ancestry and cross-ancestry effect sizes. Here, we present a statistical method called SDPR_admix for calculating PRS in admixed individuals. SDPR_admix characterizes the joint distribution of the effect sizes of a genetic variant with two ancestries to be both zero, ancestry enriched, or shared with correlation. SDPR_admix outperformed other methods in simulations and improved the prediction of real traits in European-African admixed individuals in UK Biobank when trained on the Population Architecture using Genomics and Epidemiology (PAGE) dataset (N = 13,000). Deployment of SDPR_admix on All of Us (N = 52,000) further increased the prediction accuracy by approximately 5-fold on average compared with training on PAGE. This enhancement was achieved with manageable computational time and cost, demonstrating the feasibility of training PRS models on large-scale All of Us data. We provided several examples demonstrating that both ancestral-enriched and shared effects, as included in the SDPR_admix prediction model, are helpful for improving polygenic prediction in admixed populations. We also applied SDPR_admix to construct PRS for admixed Americans with mixture of European and Amerindigenous ancestries and showed that SDPR_admix overall outperformed other methods.

Humans↗

The Landscape of Genomic and Socioeconomic Variables in Patients with Colorectal Cancer Based on Genetic Ancestry.

BACKGROUND: Despite differences in tumor alterations across genetic ancestries, investigations of the colorectal cancer molecular landscape have used self-reported ethnicity instead of genetic ancestry. METHODS: We used tumor and matched normal whole-exome sequencing data from 16,388 patients with stage I to IV colorectal cancer to investigate colorectal cancer's germline and somatic molecular landscape and the potential influence of socioeconomic factors (Distressed Communities Index, DCI) across diverse genetic ancestries. Genetic ancestry determined via supervised local ancestry inference included African (AFR, N = 1,697), Native American (AMR, N = 1,291), East Asian (EAS, N = 2,247), European (EUR, N = 9,726), Levantine Middle Eastern (LME, N = 1,192), and South Asian (SAS, N = 184). RESULTS: Microsatellite instability (MSI) was the most common form of hypermutation (80.8%), higher in the EUR genetic ancestry than in the AFR, AMR, and EAS genetic ancestry. Among germline findings, positive results were most common in high-penetrance genes associated with Lynch syndrome. Enrichment patterns included MLH1 (SAS) and PMS2 (AFR). There were significant differences in the frequency of driver mutations in APC, BRAF, KRAS, TP53, and PIK3CA between the EUR and other ancestry groups in both MSI and microsatellite stable tumors. Mutational signatures suggested enrichment of reactive oxygen species and POLE in AFR, colibactin in EAS, and aflatoxin and NTHL1 in SAS. DCI scores differed by ancestry (higher distress in AFR/AMR than in EUR), but driver mutation frequencies did not vary across DCI quintiles. CONCLUSIONS: Genetic ancestry shapes hereditary risk, tumor biology, and environmental exposures. IMPACT: These findings suggest that incorporating ancestry into screening, trials, and precision oncology may improve equity, though outcome-linked prospective studies and implementation research are warranted.

Aged↗

Genetic ancestry and risk factors for breast cancer among Latinas in the San Francisco Bay Area.

BACKGROUND: Genetic association studies using case-control designs are susceptible to false-positive and false-negative results if there are differences in genetic ancestry between cases and controls. We measured genetic ancestry among Latinas in a population-based case-control study of breast cancer and tested the association between ancestry and known breast cancer risk factors. We reasoned that if genetic ancestry is associated with known breast cancer risk factors, then the results of genetic association studies would be confounded. METHODS: We used 44 ancestry informative markers to estimate individuals' genetic ancestry in 563 Latina participants. To test whether ancestry is a predictor of hormone therapy use, parity, and body mass index (BMI), we used multivariate logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) associated with a 25% increase in Indigenous American ancestry, adjusting for age, education, and the participant's and grandparents' place of birth. RESULTS: Hormone therapy use was significantly less common among women with higher Indigenous American ancestry (OR, 0.78; 95% CI, 0.63-0.96). Higher Indigenous American ancestry was also significantly associated with overweight (BMI, 25-29.9 versus <25) and obesity (BMI, > or =30 versus <25), but only among foreign-born Latina women (OR, 3.44; 95% CI, 1.97-5.99 and OR, 1.95; 95% CI, 1.24-3.06, respectively). CONCLUSION: Some breast cancer risk factors are associated with genetic ancestry among Latinas in the San Francisco Bay Area. Therefore, case-control genetic association studies for breast cancer should directly measure genetic ancestry to avoid potential confounding.

Adult↗

Proportioning whole-genome single-nucleotide-polymorphism diversity for the identification of geographic population structure and genetic ancestry.

The identification of geographic population structure and genetic ancestry on the basis of a minimal set of genetic markers is desirable for a wide range of applications in medical and forensic sciences. However, the absence of sharp discontinuities in the neutral genetic diversity among human populations implies that, in practice, a large number of neutral markers will be required to identify the genetic ancestry of one individual. We showed that it is possible to reduce the amount of markers required for detecting continental population structure to only 10 single-nucleotide polymorphisms (SNPs), by applying a newly developed ascertainment algorithm to Affymetrix GeneChip Mapping 10K SNP array data that we obtained from samples of globally dispersed human individuals (the Y Chromosome Consortium panel). Furthermore, this set of SNPs was able to recover the genetic ancestry of individuals from all four continents represented in the original data set when applied to an independent, much larger, worldwide population data set (Centre d'Etude du Polymorphisme Humain-Human Genome Diversity Project Cell Line Panel). Finally, we provide evidence that the unusual patterns of genetic variation we observed at the respective genomic regions surrounding the five most informative SNPs is in agreement with local positive selection being the explanation for the striking SNP allele-frequency differences we found between continental groups of human populations.

Algorithms↗

Genetic Ancestry and Colorectal Cancer in the All of Us Dataset.

IMPORTANCE: Genetic ancestry may complement biological, behavioral, and clinical factors in understanding colorectal cancer (CRC) disparities; yet, ancestry-informed analyses in CRC remain limited. OBJECTIVE: To characterize associations of genetic ancestry with CRC burden, age at diagnosis, and age-specific risk, and to develop a multiethnic CRC risk-prediction model. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used All of Us data from July 1986 to October 2023, with follow-up through last visit or death (median [IQR], 133.1 [57.1-186.5] months); analyses were conducted from February to June 2026. All of Us is a US research cohort with linked electronic health record (EHR) and short-read whole-genome sequencing (srWGS) data. All of Us Research Program participants with srWGS and linked EHR data were included, except those with hereditary polyposis or Lynch syndrome. EXPOSURES: Genetically inferred ancestry categories and principal components. MAIN OUTCOMES AND MEASURES: Any CRC was the primary outcome. Associations were evaluated using Fisher exact tests, cumulative incidence functions with Gray tests, cause-specific and Fine-Gray subdistribution hazard models, and pooled multivariable logistic regression. Prediction models used penalized least absolute shrinkage and selection operator and extreme gradient boosting (XGBoost). RESULTS: Among 316&#x202f;624 participants (median [IQR] age, 56.3 [40.2-68.2] years; 172&#x202f;327 [54.4%] of European ancestry; 191&#x202f;705 female [61.2%]; 121&#x202f;585 male [38.8%]), 2914 (0.9%) developed CRC. European ancestry was associated with higher odds of CRC vs all other ancestries combined (odds ratio, 1.50; 95% CI, 1.39-1.62). The median age at CRC diagnosis was older in European (63.4 [53.9-71.2] years) than in American admixed-Latino, African, East Asian, and Other ancestry groups. In cause-specific hazard models on the attained-age scale, American admixed-Latino (hazard ratio, 1.30; 95% CI, 1.14-1.47) and East Asian (hazard ratio, 1.43; 95% CI, 1.06-1.94) ancestry had higher age-specific CRC hazard than European ancestry, with consistent findings on the subdistribution scale accounting for competing death. The multiethnic XGBoost model performed best (receiver operating characteristic area under the curve, 0.898; 95% CI, 0.882-0.912; precision-recall area under the curve, 0.338; 95% CI, 0.296-0.379) and was well calibrated. CONCLUSIONS AND RELEVANCE: In this cohort study, genetic ancestry was associated with meaningful differences in CRC burden and age-specific risk. These findings suggest that a multiethnic XGBoost model may complement CRC screening as a risk-enrichment tool.

Aged↗

Optimizing genetic ancestry adjustment in DNA methylation studies: a comparative analysis of approaches.

BACKGROUND: Genetic ancestry is an important factor to account for in DNA methylation studies because genetic variation influences DNA methylation patterns. One approach uses principal components (PCs) calculated from CpG sites that overlap with common SNPs to adjust for ancestry when genotyping data is not available. However, this method does not remove technical and biological variations, such as sex and age, prior to calculating the PCs. The first PC is therefore often associated with factors other than ancestry. METHODS: We developed and adapted the adapted EpiAnceR+&#x2009;approach, which includes (1) residualizing the CpG data overlapping with common SNPs for control probe PCs, sex, age, and cell type proportions to remove the effects of technical and biological factors, and (2) integrating the residualized data with genotype calls from the SNP probes (commonly referred to as rs probes) present on the arrays, before calculating PCs and evaluated the clustering ability and relationship to genetic ancestry. RESULTS: The PCs generated by EpiAnceR+&#x2009;led to improved clustering for repeated samples from the same individual and stronger associations with genetic ancestry groups predicted from genotype information compared to the original approach. EpiAnceR+&#x2009;also outperformed the use of DNA methylation PCs or surrogate variables for ancestry adjustment. CONCLUSIONS: We show that the EpiAnceR+&#x2009;approach improves the adjustment for genetic ancestry in DNA methylation studies. EpiAnceR+&#x2009;can be integrated into existing R pipelines for commercial methylation arrays, such as 450&#xa0;K, EPIC v1, and EPIC v2. The code is available on GitHub ( https://github.com/KiraHoeffler/EpiAnceR ).

DNA Methylation↗

Assessment of Genetic Correlations Between Tobacco or Alcohol Use and Neurodegenerative Diseases Using East Asian Genetic Ancestry Genome-Wide Association Study Results.

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most prevalent late-onset neurodegenerative diseases worldwide. Both are influenced in part by genetic factors and are currently incurable. Tobacco and alcohol, the two most common substances used among the general adult population, are potential AD/PD risk factors and are also heritable. Although important progress has been made, most existing research on the genetics of AD and PD has been carried out in individuals of European genetic ancestry. Investigations in a broad range of groups are crucial to understand disease mechanisms. Given the current availability of ancestry-specific tobacco and alcohol use as well as AD and PD genome-wide association study summary statistics, we performed global and local genetic correlation analyses using East Asian datasets. Genes within the correlated genetic regions were subsequently used to identify potentially enriched biological pathways between substance use and neurodegenerative diseases. We identified a global genetic correlation between smoking cessation and PD, which we confirmed in complementary European genetic ancestry data. Gene set enrichment analyses highlighted potentially shared genetic mechanisms between breast cancer and AD, which warrants further exploration. This work aims to promote further analyses across genetic ancestry groups.

Female↗

Comparison of three methods to estimate genetic ancestry and control for stratification in genetic association studies among admixed populations.

Population stratification may confound the results of genetic association studies among unrelated individuals from admixed populations. Several methods have been proposed to estimate the ancestral information in admixed populations and used to adjust the population stratification in genetic association tests. We evaluate the performances of three different methods: maximum likelihood estimation, ADMIXMAP and Structure through various simulated data sets and real data from Latino subjects participating in a genetic study of asthma. All three methods provide similar information on the accuracy of ancestral estimates and control type I error rate at an approximately similar rate. The most important factor in determining accuracy of the ancestry estimate and in minimizing type I error rate is the number of markers used to estimate ancestry. We demonstrate that approximately 100 ancestry informative markers (AIMs) are required to obtain estimates of ancestry that correlate with correlation coefficients more than 0.9 with the true individual ancestral proportions. In addition, after accounting for the ancestry information in association tests, the excess of type I error rate is controlled at the 5% level when 100 markers are used to estimate ancestry. However, since the effect of admixture on the type I error rate worsens with sample size, the accuracy of ancestry estimates also needs to increase to make the appropriate correction. Using data from the Latino subjects, we also apply these methods to an association study between body mass index and 44 AIMs. These simulations are meant to provide some practical guidelines for investigators conducting association studies in admixed populations.

Asthma↗

AncestryGeni: a novel genetic ancestry classification pipeline for small and noisy sequence data.

MOTIVATION: Efforts to address health disparities are often limited by the lack of robust computational tools for inferring genetic ancestry by calculating an individual's genetic similarity to continental groups. We have already shown that a preferred alternative to self-described race is using ancestry-informative markers (AIMs) that can be classified into ancestral components and used to estimate their similarity to those of known populations to identify continental groups. However, real-world genomic data can present challenges, including limited availability of germline DNA, a small number of AIMs for each sample, and the use of different variant calling software, limiting the application of existing solutions. RESULTS: Here, we describe a novel supervised machine-learning tool AncestryGeni, which infers genetic ancestry for samples with even a hundred markers and is applicable to any genomic data, including whole exome sequencing (WES) and RNA sequencing (RNA-Seq) data. Applying AncestryGeni to a real-world genomic dataset obtained from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, we show that it is more accurate than the commonly used FastNGSadmix when using nonstandard genomic material. We also demonstrate that when using AncestryGeni, the tumor-derived sequence obtained from WES and RNA-Seq can be a robust data source to accurately estimate an individual's genetic similarity to a continental group. AVAILABILITY AND IMPLEMENTATION: AncestryGeni pipeline is available at https://github.com/eelhaik/AncestryGeni/tree/main.

Humans↗

DiscoDivas: Leveraging genetic ancestry continuum information to interpolate PRS for admixed populations.

The relatively low representation of admixed populations in both discovery and fine-tuning individual-level datasets limits polygenic risk score (PRS) development and equitable clinical translation for admixed populations. Under the assumption that the most informative PRS model for a genetically homogeneous sample varies linearly in an ancestry continuum space, we introduce a Genetic Distance-assisted PRS Combination Pipeline for Diverse Genetic Ancestries (DiscoDivas) to interpolate a harmonized PRS for diverse, especially admixed, genetic ancestries, leveraging multiple PRS models fine-tuned within existing samples, which are mostly of single ancestry, and genetic distance. DiscoDivas treats genetic ancestry as a continuous variable and does not require shifting between different models when calculating PRS for different ancestries. We generated PRS with DiscoDivas and the current conventional method, i.e. fine-tuning multiple GWAS PRS using the matched or similar genetic ancestry samples. DiscoDivas generated a harmonized PRS of the accuracy comparable to or higher than the conventional approach, with the greatest advantage exhibited in admixed individuals.

PRS harmonization↗

The impact of sex, age, and genetic ancestry on DNA methylation across tissues.

Understanding the consequences of individual DNA methylation variation is crucial for advancing our knowledge of human biology and disease, yet the collective impact of individual traits on DNA methylation and their downstream effects on gene expression across human tissues remains poorly understood. Here, we quantify the contributions of sex, age, genetic ancestry, and BMI on autosomal DNA methylation variation across nine human tissues and 424 individuals from the Genotype-Tissue Expression project. We show that genetic ancestry and age have a greater impact on DNA methylation compared with sex, with aging effects being more widespread but less pronounced. On average, <10% of the gene expression variation in sex, age, and ancestry is mediated by DNA methylation differences, with ancestry showing the largest proportion of mediation. We further show that ancestry-associated DNA methylation differences accumulate at CpG sites with extreme methylation states and are largely under genetic control. The female autosomal genome exhibits consistent hypermethylation across tissues at Polycomb-repressed regions. Ultimately, we show that age-related Polycomb target hypermethylation is observed across multiple tissues but not in the gonads. Our multi-individual, multitissue approach defines the key drivers of human DNA methylation variation in healthy conditions, establishing a baseline for the interpretation of DNA methylation changes in disease contexts.

Humans↗

Reduced FOXP3 expression and its association with genetic ancestry in neuromyelitis Optica spectrum disorder: a Colombian cohort.

BACKGROUND: Autoimmune disorders are characterized by impaired immune tolerance, largely mediated by CD4&#x207a; regulatory T cells (Tregs), whose function depends on the transcription factor FOXP3. OBJECTIVES: To compare FOXP3 expression levels between patients with neuromyelitis optica spectrum disorder (NMOSD) and healthy controls from Bogot&#xe1;, Colombia, and to explore their association with genetic ancestry. METHODS: FOXP3 expression was quantified from peripheral blood mononuclear cells using RNA-based analysis. Genomic ancestry proportions were estimated using ancestry-informative markers. RESULTS: FOXP3 mRNA expression was significantly reduced in NMOSD patients compared with controls (&#x223c;2.4-fold decrease in median expression; p&#x202f;=&#x202f;0.027). Lower FOXP3 mRNA expression was associated with optic neuritis (p&#x202f;=&#x202f;0.0059), but not with historical or current AQP4-IgG seropositivity. In a sensitivity analysis restricted to patients with documented historical AQP4-IgG seropositivity, the direction of reduced FOXP3 mRNA expression was preserved but did not reach statistical significance. In pre-specified exploratory ancestry-related analyses, African (p&#x202f;=&#x202f;0.035) and Amerindian ancestry (p&#x202f;=&#x202f;0.012) were associated with FOXP3 mRNA expression levels. CONCLUSIONS: Reduced FOXP3 mRNA expression in Peripheral Blood Mononuclear Cells (PBMCs) suggests an altered immune regulatory profile in NMOSD, potentially involving mechanisms beyond antibody-mediated immunity. The association between genetic ancestry and FOXP3 mRNA expression suggests that population-specific genetic background may influence immune regulatory pathways. These findings should be interpreted as exploratory and require validation in larger, clinically homogeneous cohorts.

Adolescent↗

Chemical evidence for common genetic ancestry of complement components C3 and C5.

Sequence studies reveal a marked similarity between the partial primary structures of human C3a and C5a anaphylatoxins. Eight of the first 25 residues are identical when threonine at position 1 in C5a is aligned with glutamine at position 3 in C3a and one gap is inserted in the C3a sequence. A unique cysteinyl-cysteine sequence is conserved in the 2 molecules, which further suggests a genetic relatedness. Computer-generated alignment scores from comparison of the NH2-terminal portions of human C3a and C5a exceeded by 4 standard deviations the score from random permutations of these same sequences. This sequence similarity between the two anaphylatoxins suggests that the respective precursors, C3 and C5, had a common genetic ancestry. The proposed genetic relationship between C3 and C5 may express itself functionally through a similar molecular behavior in complement-dependent cytolysis.

Amino Acid Sequence↗

Is there are relationship between polymorphisms TSHR gene frequencies and genetic ancestry markers in patients with Primary Congenital Hypothyroidism?

The literature shows a correlation between ethnicity and pathogenic variants of the thyroid stimulating hormone receptor (TSHR) gene. Some of these polymorphisms may be risk factors for the development of primary congenital hypothyroidism (PCH). In this study, we investigated the relationship between the frequency of TSHR gene polymorphisms and the genetic influence of African, Amerindian, and European ancestry-informative markers in patients from an Amazonian population in Brazil who were diagnosed with PCH. The study was conducted on samples from 106 patients who were diagnosed with PCH. Genomic DNA was isolated from peripheral blood samples, and 10 exons from the TSHR gene were automatically sequenced. Ancestry-informative marker identification was performed using a panel of 48 markers, and the results were compared with parental Amerindian, Western European, and Sub-Saharan African populations using Structure v2.3.4 software. Four nucleotide alterations were identified among 49 patients. The distribution of tested ancestry markers among the 106 patients indicated a significant difference in the percentages of Amerindian (25.90 %), European (41.80 %), and African (32.20 %) ancestry. Logistic regression analysis revealed no significant association between the rs2075179 and rs1991517 polymorphisms and genetic ancestry. This study revealed no evidence of a relationship between polymorphic TSHR gene variants and genetic ancestry markers in patients with PCH.

Journal Article↗

Implications of correlations between skin color and genetic ancestry for biomedical research.

Skin pigmentation is a central element of most discussions on 'race' and genetics. Research on the genetic basis of population variation in this phenotype, which is important in mediating both social experiences and environmental exposures, is sparse. We studied the relationship between pigmentation and ancestry in five populations of mixed ancestry with a wide range of pigmentation and ancestral proportions (African Americans from Washington, DC; African Caribbeans living in England; Puerto Ricans from New York; Mexicans from Guerrero; and Hispanics from San Luis Valley). The strength of the relationship between skin color and ancestry was quite variable, with the correlations ranging in intensity from moderately strong (Puerto Rico, rho = 0.633) to weak (Mexico, rho = 0.212). These results demonstrate the utility of ancestry-informative genetic markers and admixture methods and emphasize the need to be cautious when using pigmentation as a proxy of ancestry or when extrapolating the results from one admixed population to another.

Biomedical Research↗

The paradoxical extinction: Exploring signatures of assortative mating as a possible mechanism that maintains canonical Red Wolf genetic ancestry in the American Gulf Coast canids.

Admixed genomes, particularly those with an evolutionary history of genetic exchange with an endangered or extinct species, are valued for innovative and unconventional conservation actions. Here, we show the substantial conservation value that the admixed canids of the Gulf Coast have as they retain high amounts of contemporary Red Wolf ancestry and unique genetic variation of past Red Wolf lineages (e.g. ghost ancestry). We analyzed 54,439 loci genotyped across the genome of 413 North American canids and investigated the role that assortative mating with respect to ancestry proportions played in the retention of endangered genetic variation. We report high correlations of inter-chromosomal ancestry proportions that varied with geographic location along Texas and Louisiana Gulf Coast populations, with the stronger signatures reported in the latter. We found that models of assortative mating promoted greater ancestry variance compared with random mating leading to increased efficiency of selection for Red Wolf and ghost alleles. Despite the Red Wolf being extinct in the wild, original, and ghost genomic variation persists in Gulf Coast admixed canids. We suggest two conservation strategies that value and preserve this unique and endangered genomic variation through designed breeding programs. Ultimately the incorporation of this ghost genetic variation would be valuable to boost the genetic viability of the ex situ Red Wolf breeding program, create in situ redundancy, and avoid extinction for this endemic American wolf species.

Animals↗