Colloquium paper: genome-wide patterns of population structure and admixture among Hispanic/Latino populations. Proc Natl Acad Sci U S A. 2010;107 Suppl 2:8954-8961. [PMID: 20445096 DOI: 10.1073/pnas.0914618107]

Old vs. new local ancestry inference in HCHS/SOL: a comparative study

Hispanic/Latino populations are admixed, with genetic contributions from multiple ancestral populations. To uncover genetic associations in these populations, researchers often turn to admixture mapping, which relies on inferred counts of "local" ancestry, i.e. the source ancestral population at a locus. Local ancestries are inferred using external reference panels that represent ancestral populations, making the choice of inference method and reference panel critical. This study used a dataset of Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) to evaluate how updates in local ancestry inference (LAI) affect results, specifically, the 'old' LAI performed using a popular inference method RFMix alongside 'new' inferences performed using Fast Local Ancestry Estimation (FLARE) with an updated reference panel. We compared their performance in terms of global and local ancestry correlations, as well as admixture mapping-based associations. Overall, the old and new inferences produced highly similar global and local ancestry estimates, with FLARE-based results closely matching those from RFMix in admixture mapping analyses. However, in some genomic regions, the old and new local ancestries showed relatively lower correlations (Pearson R < 0.9). Most of these regions (86.42%) were mapped to either ENCODE blacklist regions or gene clusters, compared to 7.67% of randomly-matched regions with high correlations (Pearson R > 0.97). These findings show that old and new inferences largely agree and suggest that regions of lower agreement are mostly due to genomic sequence contexts that lead to less stable inference, rather than due to the LAI software or genotyping technology used.

Polygenic Risk Score Analysis of 37 SNPs Associated with Melanoma Risk in Colombian Population

Melanoma incidence is increasing, with distinct genetic and clinical patterns observed in the Latin American population. This study aimed to evaluate melanoma risk in a Colombian cohort through polygenic risk analysis using 37 variants across nine genes previously associated with melanoma. We performed polygenic risk score (PRS) analysis on 85 melanoma patients and 165 controls. Genotyping was performed for 37 melanoma-associated SNPs, and on the basis of previous GWAS reports, individual PRSs were calculated for each participant. The participants were then stratified into quartiles to examine risk gradients. In addition, phenotypic features such as eye and hair color were evaluated, and genetic models and haplotype analyses were performed, adjusting for sex and family history of cancer. PRS quartile stratification revealed a clear risk gradient. Notably, 31.8% of the melanoma cases were clustered in the highest-risk quartile (Q4), with a maximum PRS of 1.04. Variants in TYR, TYRP1, CDKN2A, and HERC2 significantly contributed to risk, and light brown eye and hair colors were strongly associated with increased melanoma risk. Moreover, a protective haplotype in the OCA2-HERC2 region was identified among males. The integration of the PRS with clinical and phenotypic factors has potential for improving melanoma risk stratification in the Colombian population, warranting further investigation in larger, diverse cohorts.

Genetic ancestry influences gene-environment interactions with sociocultural factors: Results from the Hispanic Community Health Study/Study of Latinos

Often, studies will aggregate all participants identified as Hispanic/Latino, despite genetic and environmental substructures, preventing the meaningful interrogation of the roles of genetics and environment in human health. Using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we examined how self-identified background group and genetic ancestry influence gene-environment interactions between body mass index (BMI) and a polygenic score for BMI (PGSBMI). Participants (n = 7,075) identified with six background groups: Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American. Generalized linear models incorporating complex survey weighting were used to model BMI through joint and stratified (background group, estimated Amerindigenous [AME] ancestry) analyses including PGSBMI and other health-related variables. Interaction effects were modeled between PGSBMI and diet and age at immigration. Comparing pooled to background group-stratified analyses, we observe heterogeneous distributions of environmental and sociocultural variables, as well as differing associations with AME ancestry. Within the multivariate model, PGSBMI performance decreased with increasing AME ancestry. After stratification, PGS-age-at-immigration interactions remained statistically significant in some strata: Mexican background individuals born in the US (50 states/DC) (β = 1.33, p < 0.01), Dominican background individuals 6-12 years old (β = 4.38, p < 0.001), and Cuban background individuals 0-5 years old (β = 2.20, p = 0.015) relative to those ≥ 21 years old at migration. It is vital to understand populations of interest to model them appropriately and prevent possible confounding or misinterpretation. While this work focuses specifically on Hispanic/Latino groups, these lessons are relevant to other groups as we diversify work to better understand gene-environment interactions.

Old vs. New Local Ancestry Inference in HCHS/SOL: A Comparative Study

Hispanic/Latino populations are admixed, with genetic contributions from multiple ancestral populations. Studies of genetic association in these admixed populations often use methods such as admixture mapping, which relies on inferred counts of "local" ancestry, i.e., of the source ancestral population at a locus. Local ancestries are inferred using external reference panels that represent ancestral populations, making the choice of inference method and reference panel critical. This study used a dataset of Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) to evaluate the "old" local ancestry inference performed using the state-of-the-art inference method, RFMix, alongside "new" inferences performed using Fast Local Ancestry Estimation (FLARE), which also used an updated reference panel. We compared their performance in terms of global and local ancestry correlations, as well as admixture mapping-based associations. Overall, the old RFMix and new FLARE inferences were highly similar for both global and local ancestries, with FLARE-inferred datasets yielding admixture mapping results consistent with those computed from RFMix. However, in some genomic regions the old and new local ancestries have relatively lower correlations (Pearson R < 0.9). Most of these genomic regions (86.42%) were mapped to either ENCODE blacklist regions, or to gene clusters, compared to 7.67% of randomly-matched regions with high correlations (Pearson R > 0.97) between old and new local ancestries.

Evaluation of Multiple Breast Cancer Polygenic Risk Score Panels in Women of Latin American Heritage

BACKGROUND

A substantial portion of the genetic predisposition for breast cancer is explained by multiple common genetic variants of relatively small effect. A subset of these variants, which have been identified mostly in individuals of European (EUR) and Asian ancestries, have been combined to construct a polygenic risk score (PRS) to predict breast cancer risk, but the prediction accuracy of existing PRSs in Hispanic/Latinx individuals (H/L) remain relatively low. We assessed the performance of several existing PRS panels with and without addition of H/L-specific variants among self-reported H/L women.

METHODS

PRS performance was evaluated using multivariable logistic regression and the area under the ROC curve.

RESULTS

Both EUR and Asian PRSs performed worse in H/L samples compared with original reports. The best EUR PRS performed better than the best Asian PRS in pooled H/L samples. EUR PRSs had decreased performance with increasing Indigenous American (IA) ancestry, while Asian PRSs had increased performance with increasing IA ancestry. The addition of two H/L SNPs increased performance for all PRSs, most notably in the samples with high IA ancestry, and did not impact the performance of PRSs in individuals with lower IA ancestry.

CONCLUSIONS

A single PRS that incorporates risk variants relevant to the multiple ancestral components of individuals from Latin America, instead of a set of ancestry-specific panels, could be used in clinical practice.

IMPACT

The results highlight the importance of population-specific discovery and suggest a straightforward approach to integrate ancestry-specific variants into PRSs for clinical application.

The impact of Indigenous American-like ancestry on risk of acute lymphoblastic leukemia in Hispanic/Latino children

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, with Hispanic/Latino children having a higher incidence of ALL than other racial/ethnic groups. Genetic variants, particularly ones found enriched in Indigenous American (IA)-like ancestry and inherited by Hispanics/Latinos, may contribute to this disparity. In this study, we characterized the impact of IA-like ancestry on overall ALL risk and the frequency and effect size of known risk alleles in a large cohort of self-reported Hispanic/Latino individuals. We also performed genome-wide admixture mapping analysis to identify potentially novel ALL risk loci. We found that global IA ancestry was positively associated with ALL risk, but the association was not significant after adjusting for socio-economic indicators. In a series of local ancestry analyses, we uncovered that at known ALL risk loci, increasing copies of the IA-like haplotype were positively and significantly associated with ALL case-control status. Further, the IA-like haplotype had ~1.33 times the odds of harboring the risk allele compared to non-IA-like haplotypes. We found no evidence of interaction between genotype and ancestry (local or global) in relation to ALL risk. Admixture mapping identified association signals on chromosomes 2 (2q21.2), 7 (7p12.2), 10 (10q21.2), and 15 (15q22.31); however, only the variants at 7p12.2 and 10q21.2 replicated in additional cohorts. Taken together, our results suggest that increased risk of ALL in Hispanic/Latino children may be conferred by higher frequency of risk alleles within IA-like ancestry, which can be leveraged as targets of new precision health strategies and therapeutics.

Dense SNP-based analyses complement forensic anthropology biogeographical ancestry assessments

Identification of unidentified human remains (UHRs) is crucial yet challenging, especially with traditional forensic techniques. Forensic anthropological examinations can yield ancestry estimations; however, the utility of these estimates is limited by the data points that can be collected from partial remains, complexities of admixture, and variation of phenotypic expression due to environmental effects. While it is generally known that anthropological estimates can be imprecise, the performance of these methods has not been studied at scale. Genome-wide SNP testing is an orthogonal approach for estimating ancestry and offers a unique opportunity to measure the magnitude of anthropological ancestry misattribution. Genomic ancestry inference leverages principal component analysis (PCA) and model-based clustering approaches. This study compares anthropologically determined ancestry with those estimated using genome-wide SNP markers. A dataset of 611 UHR samples with publicly available ancestry assessments from National Missing and Unidentified Persons System (NamUs) was analyzed. The genetic ancestry approach, validated against reference population samples, offers robust ancestry calculations for major population groups. Inconsistency between anthropological and genomic ancestry assignments were observed, particularly for admixed populations. Although forensic anthropological examinations remain valuable, their limitations emphasize the need for refinement and enhancement through the augmentation of SNP-based analyses. Further validation studies are crucial to define the uncertainty associated with both anthropological and genome-based ancestry estimates to resolve cases and aid law enforcement investigations. Additionally, current policy and practices for reporting ancestry for UHRs should be revisited to reduce potential misinformation.

Coancestry superposed on admixed populations yields measures of relatedness at individual-level resolution

The admixture model is widely applied to estimate and interpret population structure among individuals. Here we consider a "standard admixture" model that assumes the admixed populations are unrelated and also a generalized model, where the admixed populations themselves are related via coancestry (or covariance) of allele frequencies. The generalized model yields a potentially more realistic and substantially more flexible model that we call "super admixture". This super admixture model provides a one-to-one mapping in terms of probability moments with the population-level kinship model, the latter of which is a general model of genome-wide relatedness and structure based on identity-by-descent. We introduce a method to estimate the super admixture model that is based on method of moments, does not rely on likelihoods, is computationally efficient, and scales to massive sample sizes. We apply the method to several human data sets and show that the admixed populations are indeed substantially related, implying the proposed method captures a new and important component of evolutionary history and structure in the admixture model. We show that the fitted super admixture model estimates relatedness between all pairs of individuals at a resolution similar to the kinship model. The super admixture model therefore provides a tractable, forward generating probabilistic model of complex structure and relatedness that should be useful in a variety of scenarios.

Diagnostic Accuracy of a Blood-Based Biomarker Panel for Colorectal Cancer Detection: A Pilot Study

Background: Colorectal cancer (CRC) is a leading cause of death worldwide. Despite its preventability through screening, compliance still needs to improve due to the invasiveness of current tools. There is a growing demand for validated molecular biomarker panels for minimally invasive blood-based CRC screening. This study assessed the diagnostic accuracy of four promising blood-based CRC biomarkers, individually and in combination. Methods: This case-control study involved plasma samples from 124 CRC cases and 124 age- and sex-matched controls. Biomarkers tested included methylated DNA encoding the Septin-9 gene (mSEPT9) using Epi proColon® 2.0 CE, insulin-like growth factor binding protein 2 (IGFBP2), dickkopf-3 (DKK3), and pyruvate kinase M2 (PKM2) by ELISA. Diagnostic accuracy was measured using the receiver operating characteristic (ROC), area under the curve (AUC), as well as sensitivity and specificity. Results: Diagnostic accuracy for mSEPT9, IGFBP2, DKK3, and PKM2 was 62.9% (95% CI: 56.8-62.9%), 69.7% (95% CI: 63.1-69.7%), 61.6% (95% CI: 54.6-61.6%), and 50.8% (95% CI: 43.4-50.8%), respectively. The combined biomarkers yielded an AUC of 74.4% (95% CI: 68.1-80.6%), outperforming all biomarkers except IGFBP2. Conclusions: These biomarkers show potential for developing a minimally invasive CRC detection tool as an alternative to existing approaches, potentially increasing adherence, early detection, and survivorship.

A Narrative Review of the Digital Equity Gap of Apps for Cigarette Smoking Cessation for Persons Living in the Hispanosphere

Purpose of Review

The Hispanosphere is a vast region of the world that has received little attention in the digital health literature. No study to date has examined the availability and quality of publicly available mobile applications (apps) for cigarette smoking cessation in this region. Three coders utilized the American Psychiatry Association (APA)'s Brief App Evaluation Model Screener (Brief-AEM Screener) to evaluate the quality of the label and public-facing screens of smoking cessation apps in Spanish. Availability of apps in the Hispanosphere was compared to availability of apps in the Anglosphere.

Recent Findings

We identified and reviewed 19 apps in Spanish in Google Play. The median score using the Brief-AEM Screener was 63 out of 100 suggesting generally acceptable app quality and features according to the quality standards for digital health tools proposed by the APA. However, we found (1) notable inaccurate and misleading labelling claims, (2) poor grammar or incomplete translations, and (3) a lack of cultural and linguistic adaptation to countries in the Hispanosphere. Our comparison of smoking cessation apps between the Hispanosphere and the Anglosphere suggested that there is a large digital equity gap between these two regions, with a four to sevenfold gap in app availability.

Summary

There is a relative shortage of quality and quantity of digital health apps for smoking cessation in the Hispanosphere. To ensure the cultural appropriateness of those digital interventions, it is essential that developers of digital health tools establish community partners in the region prior to developing apps for smoking cessation.

Adjusting for principal components can induce collider bias in genome-wide association studies

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Influence of Genetic Ancestry on Gene-Environment Interactions of Polygenic Risk and Sociocultural Factors: Results from the Hispanic Community Health Study/Study of Latinos

Background

Many present analyses of Hispanic/Latino populations in epidemiologic research aggregate all members of this ethnic group, despite immense diversity in genetic backgrounds, environment, and culture between and across Hispanic/Latino background groups. Using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we examined the role of self-identified background group and genetic ancestry proportions in gene-environment interactions influencing the relationship between body mass index (BMI) and a polygenic score for BMI (PGSBMI).

Methods

Weighted univariate and multivariable generalized linear models were executed to compare the effects of environmental variables identified a priori by McArdle et al. 2021. Both Amerindigenous (AME) ancestry proportion and background group identity were statistically modeled as confounders both through stratified and joint analyses to understand their influence on the relationship between BMI and PGSBMI, while incorporating gene-environment interactions of PGS x diet and PGS x age-at-immigration.

Results

After complex survey weighting, 7,075 participants remained in the analytic sample, representing individuals of six background groups: Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American. The distributions of key environmental and sociocultural variables were heterogeneous between Hispanic/Latino background groups. Associations of these variables with AME ancestry were similarly heterogeneous upon stratification, indicating confounding by background group. In a predictive model for BMI incorporating health, immigration, and environmental variables, PGSBMI performance decreased with increasing AME ancestry proportion. In this model, most statistically significant GxE interactions lost significance after ancestry and background stratification, except for PGS x age-at-immigration interactions in some strata: Mexican background individuals born in the US compared to those >=21 years old at migration (β=1.33, p<0.01), Dominican background individuals 6-12 years old at migration compared to those >=21 years old at migration (β=4.38, p<0.001), and Cuban background individuals 0-5 years old at migration compared to those >=21 years old at migration (β=2.20, p=0.015), where US-born includes individuals born in the US 50 states/DC.

Conclusions

Controlling for self-identified background group identity and genetic ancestry did not eliminate statistically significant differences in interactions between AME ancestry and environmental variables in certain strata of AME ancestry among some Hispanic/Latino background groups in HCHS/SOL.

Systematic comparison of phenome-wide admixture mapping and genome-wide association in a diverse biobank

Biobank-scale association studies that include Hispanic/Latino(a) (HL) and African American (AA) populations remain underrepresented, limiting the discovery of disease associated genetic factors in these groups. We present here a systematic comparison of phenome-wide admixture mapping (AM) and genome-wide association (GWAS) using data from the diverse Bio Me biobank in New York City. Our analysis highlights 77 genome-wide significant AM signals, 48 of which were not detected by GWAS, emphasizing the complementary nature of these two approaches. AM-tagged variants show significantly higher minor allele frequency and population differentiation (Fst) while GWAS demonstrated higher odds ratios, underscoring the distinct genetic architecture identified by each method. This study offers a comprehensive phenome-wide AM resource, demonstrating its utility in uncovering novel genetic associations in underrepresented populations, particularly for variants missed by traditional GWAS approaches.

Novel risk loci for COVID-19 hospitalization among admixed American populations

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

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.

Exploring the relationship between admixture and genetic susceptibility to attention deficit hyperactivity disorder in two Latin American cohorts

Contemporary research on the genomics of Attention Deficit Hyperactivity Disorder (ADHD) often underrepresents admixed populations of diverse genomic ancestries, such as Latin Americans. This study explores the relationship between admixture and genetic associations for ADHD in Colombian and Mexican cohorts. Some 546 participants in two groups, ADHD and Control, were genotyped with Infinium PsychArray®. Global ancestry levels were estimated using overall admixture proportions and principal component analysis, while local ancestry was determined using a method to estimate ancestral components along the genome. Genome-wide association analysis (GWAS) was conducted to identify significant associations. Differences between Colombia and Mexico were evaluated using appropriate statistical tests. 354 Single-nucleotide polymorphisms (SNPs) and Single-nucleotide variants (SNVs) related to some genes and intergenic regions exhibited suggestive significance (p-value < 5*10e-5) in the GWAS. None of the variants revealed genome-wide significance (p-value < 5*10e-8). The study identified a significant relationship between risk SNPs and the European component of admixture, notably observed in the LOC105379109 gene. Despite differences in risk association loci, such as FOXP2, our findings suggest a possible homogeneity in genetic variation's impact on ADHD between Colombian and Mexican populations. Current reference datasets for ADHD predominantly consist of samples with high European ancestry, underscoring the need for further research to enhance the representation of reference populations and improve the identification of ADHD risk traits in Latin Americans.

ClOneHORT: Approaches for Improved Fidelity in Generative Models of Synthetic Genomes

Motivation

Deep generative models have the potential to overcome difficulties in sharing individual-level genomic data by producing synthetic genomes that preserve the genomic associations specific to a cohort while not violating the privacy of any individual cohort member. However, there is significant room for improvement in the fidelity and usability of existing synthetic genome approaches.

Results

We demonstrate that when combined with plentiful data and with population-specific selection criteria, deep generative models can produce synthetic genomes and cohorts that closely model the original populations. Our methods improve fidelity in the site-frequency spectra and linkage disequilibrium decay and yield synthetic genomes that can be substituted in downstream local ancestry inference analysis, recreating results with .91 to .94 accuracy.

Availability

The model described in this paper is freely available at github.com/rlaboulaye/clonehort .

Ancient genomes reveal insights into ritual life at Chichén Itzá

The ancient city of Chichén Itzá in Yucatán, Mexico, was one of the largest and most influential Maya settlements during the Late and Terminal Classic periods (AD 600-1000) and it remains one of the most intensively studied archaeological sites in Mesoamerica1-4. However, many questions about the social and cultural use of its ceremonial spaces, as well as its population's genetic ties to other Mesoamerican groups, remain unanswered2. Here we present genome-wide data obtained from 64 subadult individuals dating to around AD 500-900 that were found in a subterranean mass burial near the Sacred Cenote (sinkhole) in the ceremonial centre of Chichén Itzá. Genetic analyses showed that all analysed individuals were male and several individuals were closely related, including two pairs of monozygotic twins. Twins feature prominently in Mayan and broader Mesoamerican mythology, where they embody qualities of duality among deities and heroes5, but until now they had not been identified in ancient Mayan mortuary contexts. Genetic comparison to present-day people in the region shows genetic continuity with the ancient inhabitants of Chichén Itzá, except at certain genetic loci related to human immunity, including the human leukocyte antigen complex, suggesting signals of adaptation due to infectious diseases introduced to the region during the colonial period.

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

The genomic footprint of social stratification in admixing American populations

Cultural and socioeconomic differences stratify human societies and shape their genetic structure beyond the sole effect of geography. Despite mating being limited by sociocultural stratification, most demographic models in population genetics often assume random mating. Taking advantage of the correlation between sociocultural stratification and the proportion of genetic ancestry in admixed populations, we sought to infer the former process in the Americas. To this aim, we define a mating model where the individual proportions of the genome inherited from Native American, European, and sub-Saharan African ancestral populations constrain the mating probabilities through ancestry-related assortative mating and sex bias parameters. We simulate a wide range of admixture scenarios under this model. Then, we train a deep neural network and retrieve good performance in predicting mating parameters from genomic data. Our results show how population stratification, shaped by socially constructed racial and gender hierarchies, has constrained the admixture processes in the Americas since the European colonization and the subsequent Atlantic slave trade.

Population-Specific Distribution of TPMT Deficiency Variants and Ancestry Proportions in Ecuadorian Ethnic Groups: Towards Personalized Medicine

Purpose

Thiopurine S-methyltransferase (TPMT) is an enzyme that metabolizes purine analogs, agents used in the treatment of acute lymphoblastic leukemia. Improper drug metabolism leads to toxicity in chemotherapy patients and reduces treatment effectiveness. TPMT variants associated with reduced enzymatic activity vary across populations. Therefore, studying these variants in heterogeneous populations, such as Ecuadorians, can help identify molecular causes of deficiency for this enzyme.

Methods

We sequenced the entire TPMT coding region in 550 Ecuadorian individuals from Afro-Ecuadorian, Indigenous, Mestizo, and Montubio ethnicities. Moreover, we conducted an ancestry analysis using 46 informative ancestry markers.

Results

We identified 8 single nucleotide variants in the coding region of TPMT. The most prevalent alleles were TPMT*3A, TPMT*3B, and TPMT*3C, with frequencies of 0.055, 0.012, and 0.015, respectively. Additionally, we found rare alleles TPMT*4 and TPMT*8 with frequencies of 0.005 and 0.003. Correlating the ancestry proportions with TPMT-deficient genotypes, we observed that the Native American ancestry proportion influenced the distribution of the TPMT*1/TPMT*3A genotype (OR = 5.977, p = 0.002), while the contribution of African ancestral populations was associated with the TPMT*1/TPMT*3C genotype (OR = 9.769, p = 0.003). The rates of TPMT-deficient genotypes observed in Mestizo (f = 0.121) and Indigenous (f = 0.273) groups provide evidence for the influence of Native American ancestry and the prevalence of the TPMT*3A allele. In contrast, although Afro-Ecuadorian groups demonstrate similar deficiency rates (f = 0.160), the genetic factors involved are associated with contributions from African ancestral populations, specifically the prevalent TPMT*3C allele.

Conclusion

The distribution of TPMT-deficient variants offers valuable insights into the populations under study, underscoring the necessity for genetic screening strategies to prevent thiopurine toxicity events among Latin American minority groups.

Native American ancestry and breast cancer risk in Colombian and Mexican women: ruling out potential confounding through ancestry-informative markers

BACKGROUND

Latin American and Hispanic women are less likely to develop breast cancer (BC) than women of European descent. Observational studies have found an inverse relationship between the individual proportion of Native American ancestry and BC risk. Here, we use ancestry-informative markers to rule out potential confounding of this relationship, estimating the confounder-free effect of Native American ancestry on BC risk.

METHODS AND STUDY POPULATION

We used the informativeness for assignment measure to select robust instrumental variables for the individual proportion of Native American ancestry. We then conducted separate Mendelian randomization (MR) analyses based on 1401 Colombian women, most of them from the central Andean regions of Cundinamarca and Huila, and 1366 Mexican women from Mexico City, Monterrey and Veracruz, supplemented by sensitivity and stratified analyses.

RESULTS

The proportion of Colombian Native American ancestry showed a putatively causal protective effect on BC risk (inverse variance-weighted odds ratio [OR] = 0.974 per 1% increase in ancestry proportion, 95% confidence interval [CI] 0.970-0.978, p = 3.1 × 10-40). The corresponding OR for Mexican Native American ancestry was 0.988 (95% CI 0.987-0.990, p = 1.4 × 10-44). Stratified analyses revealed a stronger association between Native American ancestry and familial BC (Colombian women: OR = 0.958, 95% CI 0.952-0.964; Mexican women: OR = 0.973, 95% CI 0.969-0.978), and stronger protective effects on oestrogen receptor (ER)-positive BC than on ER-negative and triple-negative BC.

CONCLUSIONS

The present results point to an unconfounded protective effect of Native American ancestry on BC risk in both Colombian and Mexican women which appears to be stronger for familial and ER-positive BC. These findings provide a rationale for personalised prevention programmes that take genetic ancestry into account, as well as for future admixture mapping studies.

Polygenic prediction of bipolar disorder in a Latin American sample

To date, bipolar disorder (BD) genetic studies and polygenic risk scores (PRSs) for BD are based primarily on populations of European descent (EUR) and lack representation from other ancestries including Latin American (LAT). Here, we describe a new LAT cohort from the Mayo Clinic Bipolar Biobank (MCBB), a multisite collaboration with recruitment sites in the United States (EUR; 1,443 cases and 777 controls) and Mexico and Chile (LAT; 211 cases and 161 controls) and use the sample to explore the performance of a BD-PRS in a LAT population. Using results from the largest genome-wide association study of BD in EUR individuals, PRSice2 and LDpred2 were used to compute BD-PRSs in the LAT and EUR samples from the MCBB. PRSs explained up to 1.4% (PRSice) and 4% (LDpred2) of the phenotypic variance on the liability scale in the LAT sample compared to 3.8% (PRSice2) and 3.4% (LDpred2) in the EUR samples. Future larger studies should further explore the differential performance of different PRS approaches across ancestries. International multisite studies, such as this one, have the potential to address diversity-related limitations of prior genomic studies and ultimately contribute to the reduction of health disparities.

Incidence and Mortality Rates for Childhood Acute Lymphoblastic Leukemia in Puerto Rican Hispanics, 2012-2016

BACKGROUND

Acute lymphoblastic leukemia (ALL) accounts for 80% of all leukemias diagnosed in children. Although ALL age patterns are consistent across racial/ethnic groups, their incidence and mortality rates are highly variable. We assessed the age-standardized ALL incidence and mortality rates of Puerto Rican Hispanic (PRH) children and compared them with those of US mainland Hispanics (USH), non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), and Non-Hispanic Asian or Pacific Islanders (NHAPI).

METHODS

Differences between racial/ethnic groups were assessed by estimating the standardized rate ratio (SRR) for 2010 to 2014. Secondary data analyses of the Puerto Rico Central Cancer Registry and the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) databases were performed for the 2001 to 2016 period.

RESULTS

PRH children had 31% lower incidence rates than USH, but 86% higher incidence rates than NHB. In addition, the incidence trends of ALL increased significantly from 2001 to 2016 among PRH and USH, with 5% and 0.9% per year, respectively. Moreover, PRH have a lower 5-year overall survival (81.7%) when compared with other racial/ethnic groups.

CONCLUSIONS

PRH children were found to have disparities in ALL incidence and mortality rates compared with other racial/ethnic groups in the US. Additional research is warranted to identify the genetic and environmental risk factors that may be associated with the disparities observed.

IMPACT

This is the first study reporting the incidence and mortality rates of childhood ALL for PRH and making comparisons with other racial/ethnic groups in the US. See related commentary by Mejía-Aranguré and Núñez-Enríquez, p. 999.

Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program

Importance

Primary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation.

Objective

To determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population.

Design, Setting, and Participants

This was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023.

Exposures

PRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status.

Main Outcomes and Measures

Incident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events.

Results

A total of 79 151 participants (mean [SD] age, 57.8 [13.7] years; 68 503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18 505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53 861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk >3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, -0.07% to 3.30%).

Conclusions and Relevance

Study results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.

Sequence-based allelic variations and frequencies for 22 autosomal STR loci in the Lebanese population

This is the first study that characterizes the sequence-based allelic variations of 22 autosomal Short Tandem Repeat (aSTR) loci in a population dataset collected from Lebanon. Genomic DNA extracts from 195 unrelated Lebanese individuals were amplified with PowerSeq 46GY System Prototype. Targeted amplicons were subjected to DNA library preparation and sequenced on the Verogen MiSeq FGx Sequencing System. Raw FASTQ data files were processed by STRait Razor v3. Sequence strings were annotated according to the considerations of the DNA Commission of the International Society for Forensic Genetics (ISFG) and tabulated herein with their respective allelic frequencies and GeneBank accession and version numbers. The sequenced Lebanese dataset resulted in 429 distinct allelic sequences as compared to the 236 alleles identified by length only. The increase in the number of alleles was observed at 18 out of 22 aSTR loci and was attributed to the sequence variations residing in both the STR repeat motifs and flanking regions. The study uncovered 25 novel aSTR allelic sequences across 12 loci for which GenBank records did not previously exist in the STRSeq BioProject, PRJNA380127. For a concordance check, the length-based allelic calls derived from the full sequences were compared to those genotyped using capillary electrophoresis (CE) methods. Population genetic parameters relevant to the evaluation of forensic DNA evidence were assessed for the sequence-based data and compared to the parameters generated from the length-based information. Using the sequence-based data, Analysis of MOlecular VAriance (AMOVA), genetic distances, and population genetic structure were evaluated for 1231 individuals sampled from the Lebanese and four U.S. populations (African American, Asian, Caucasian, and Hispanic). The results were tabulated and visualized in a population tree, multidimensional scaling scatter plots, and bar plots. This newly established sequence-based database for the Lebanese population can be beneficial for extending NGS applicability to casework or paternity testing and assessing the strength of evidence for NGS-STR profiles. The described novel sequence variants at certain loci can further help in the effort to characterize the sequence diversity of STR markers from different populations around the world.

Pressure-Induced Fibroid Ischemia: First-In-Human Experience with a Novel Device for Laparoscopic Treatment of Symptomatic Uterine Fibroids

The purpose of this study was to assess the feasibility of use of a novel uterine fibroid treatment device hypothesized to cause fibroid infarction by increasing intra-tumoral pressure. Between August 2019 and January 2020, 21 uterine fibroids were treated in 16 symptomatic pre-menopausal black women. Pelvic magnetic resonance imaging was performed before the procedure, a day after the procedure and at 1, 3, 6, and 12 months. The subjects were also followed for clinical outcomes and quality of life up to 12 months at a single investigational site. At 3 months, the mean reduction in the fibroid volume was 36.3% (P = .002). Incremental reduction in volume peaked at the end of the follow-up, at the 12-month mark (60.4%; P = .008). There were no procedures in which the users failed to perform laparoscopic pressure suturing of fibroids with the pressure-induced fibroid ischemia device. Improvement in the quality of life was evident in the Health-Related Quality of Life total, Energy/Mood, Control, and Sexual Function domains of the Uterine Fibroid Symptom and Quality of Life questionnaire at 3 months post-procedure. Unanticipated risks were not identified. Serious adverse events were not identified. The initial clinical assessment of the pressure-induced fibroid ischemia device supports feasibility of the approach and does not reveal serious safety concerns. Trial is currently being registered retrospectively (This was a feasibility study and therefore registration was not mandatory).

The Legacy of Infectious Disease Exposure on the Genomic Diversity of Indigenous Southern Mexicans

To characterize host risk factors for infectious disease in Mesoamerican populations, we interrogated 857,481 SNPs assayed using the Affymetrix 6.0 genotyping array for signatures of natural selection in immune response genes. We applied three statistical tests to identify signatures of natural selection: locus-specific branch length (LSBL), the cross-population extended haplotype homozygosity (XP-EHH), and the integrated haplotype score (iHS). Each of the haplotype tests (XP-EHH and iHS) were paired with LSBL and significance was determined at the 1% level. For the paired analyses, we identified 95 statistically significant windows for XP-EHH/LSBL and 63 statistically significant windows for iHS/LSBL. Among our top immune response loci, we found evidence of recent directional selection associated with the major histocompatibility complex (MHC) and the peroxisome proliferator-activated receptor gamma (PPAR-γ) signaling pathway. These findings illustrate that Mesoamerican populations' immunity has been shaped by exposure to infectious disease. As targets of selection, these variants are likely to encode phenotypes that manifest themselves physiologically and therefore may contribute to population-level variation in immune response. Our results shed light on past selective events influencing the host response to modern diseases, both pathogenic infection as well as autoimmune disorders.

The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients

Biobanks of linked clinical patient histories and biological samples are an efficient strategy to generate large cohorts for modern genetics research. Biobank recruitment varies by factors such as geographic catchment and sampling strategy, which affect biobank demographics and research utility. Here, we describe the Michigan Genomics Initiative (MGI), a single-health-system biobank currently consisting of >91,000 participants recruited primarily during surgical encounters at Michigan Medicine. The surgical enrollment results in a biobank enriched for many diseases and ideally suited for a disease genetics cohort. Compared with the much larger population-based UK Biobank, MGI has higher prevalence for nearly all diagnosis-code-based phenotypes and larger absolute case counts for many phenotypes. Genome-wide association study (GWAS) results replicate known findings, thereby validating the genetic and clinical data. Our results illustrate that opportunistic biobank sampling within single health systems provides a unique and complementary resource for exploring the genetics of complex diseases.

Whole exome sequencing and replication for breast cancer among Hispanic/Latino women identifies FANCM as a susceptibility gene for estrogen-receptor-negative breast cancer

Introduction

Breast cancer (BC) is one of the most common cancers globally. Genetic testing can facilitate screening and risk-reducing recommendations, and inform use of targeted treatments. However, genes included in testing panels are from studies of European-ancestry participants. We sequenced Hispanic/Latina (H/L) women to identify BC susceptibility genes.

Methods

We conducted a pooled BC case-control analysis in H/L women from the San Francisco Bay area, Los Angeles County, and Mexico (4,178 cases and 4,344 controls). Whole exome sequencing was conducted on 1,043 cases and 1,188 controls and a targeted 857-gene panel on the remaining samples. Using ancestry-adjusted SKAT-O analyses, we tested the association of loss of function (LoF) variants with overall, estrogen receptor (ER)-positive, and ER-negative BC risk. We calculated odds ratios (OR) for BC using ancestry-adjusted logistic regression models. We also tested the association of single variants with BC risk.

Results

We saw a strong association of LoF variants in FANCM with ER-negative BC (p=4.1×10-7, OR [CI]: 6.7 [2.9-15.6]) and a nominal association with overall BC risk. Among known susceptibility genes, BRCA1 (p=2.3×10-10, OR [CI]: 24.9 [6.1-102.5]), BRCA2 (p=8.4×10-10, OR [CI]: 7.0 [3.5-14.0]), and PALB2 (p=1.8×10-8, OR [CI]: 6.5 [3.2-13.1]) were strongly associated with BC. There were nominally significant associations with CHEK2, RAD51D, and TP53.

Conclusion

In H/L women, LoF variants in FANCM were strongly associated with ER-negative breast cancer risk. It previously was proposed as a possible susceptibility gene for ER-negative BC, but is not routinely tested in clinical practice. Our results demonstrate that FANCM should be added to BC gene panels.

Pharmacogenomics and health disparities, are we helping?

Pharmacogenomics has been at the forefront of precision medicine during the last few decades. Precision medicine carries the potential of improving health outcomes at both the individual as well as population levels. To harness the benefits of its initiatives, careful dissection of existing health disparities as they relate to precision medicine is of paramount importance. Attempting to address the existing disparities at the early stages of design and implementation of these efforts is the only guarantee of a successful just outcome. In this review, we glance at a few determinants of existing health disparities as they intersect with pharmacogenomics research and implementation. In our opinion, highlighting these disparities is imperative for the purpose of researching meaningful solutions. Failing to identify, and hence address, these disparities in the context of the current and future precision medicine initiatives would leave an already strained health system, even more inundated with inequality.

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.

Diversity is key for cross-ancestry transferability of glaucoma genetic risk scores in Hispanic Veterans in the Million Veteran Program

A major goal of precision medicine is to stratify patients based on their genetic risk for a disease to inform future screening and intervention strategies. For conditions like primary open-angle glaucoma (POAG), the genetic risk architecture is complicated with multiple variants contributing small effects on risk. Following the tepid success of genome-wide association studies for high-effect disease risk variant discovery, genetic risk scores (GRS), which collate effects from multiple genetic variants into a single measure, have shown promise for disease risk stratification. We assessed the application of GRS for POAG risk stratification in Hispanic-descent (HIS) and European-descent (EUR) Veterans in the Million Veteran Program. Unweighted and cross-ancestry meta-weighted GRS were calculated based on 127 genomic variants identified in the most recent report of cross-ancestry POAG meta-analyses. We found that both GRS types were associated with POAG case-control status and performed similarly in HIS and EUR Veterans. This trend was also seen in our subset analysis of HIS Veterans with less than 50% EUR global genetic ancestry. Our findings highlight the importance of evaluating GRS based on known POAG risk variants in different ancestry groups and emphasize the need for more multi-ancestry POAG genetic studies.

Genomic Consequences of and Demographic Response to Pervasive Hybridization Over Time in Climate-Sensitive Pikas

Rare and geographically restricted species may be vulnerable to genetic effects from inbreeding depression in small populations or from genetic swamping through hybridization with common species, but a third possibility is that selective gene flow can restore fitness (genetic rescue). Climate-sensitive pikas (Ochotona spp.) of the Qinghai-Tibetan Plateau (QHTP) and its vicinity have been reduced to residual populations through the movement of climatic zones during the Pleistocene and recent anthropogenic disturbance, whereas the plateau pika (O. curzoniae) remains common. Population-level whole-genome sequencing (n = 142) of six closely related species in the subgenus Ochotona revealed several phases of ancient introgression, lineage replacement, and bidirectional introgression. The strength of gene flow was the greatest from the dominant O. curzoniae to ecologically distinct species in areas peripheral to the QHTP. Genetic analyses were consistent with environmental reconstructions of past population movements. Recurrent periods of introgression throughout the Pleistocene revealed an increase in genetic variation at first but subsequent loss of genetic variation in later phases. Enhanced dispersion of introgressed genomic regions apparently contributed to demographic recovery in three peripheral species that underwent range shifts following climate oscillations on the QHTP, although it failed to drive recovery of northeastern O. dauurica and geographically isolated O. sikimaria. Our findings highlight differences in timescale and environmental background to determine the consequence of hybridization and the unique role of the QHTP in conserving key evolutionary processes of sky island species.

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.

MultiWaverX: modeling latent sex-biased admixture history

Sex-biased gene flow has been common in the demographic history of modern humans. However, the lack of sophisticated methods for delineating the detailed sex-biased admixture process prevents insights into complex admixture history and thus our understanding of the evolutionary mechanisms of genetic diversity. Here, we present a novel algorithm, MultiWaverX, for modeling complex admixture history with sex-biased gene flow. Systematic simulations showed that MultiWaverX is a powerful tool for modeling complex admixture history and inferring sex-biased gene flow. Application of MultiWaverX to empirical data of 17 typical admixed populations in America, Central Asia, and the Middle East revealed sex-biased admixture histories that were largely consistent with the historical records. Notably, fine-scale admixture process reconstruction enabled us to recognize latent sex-biased gene flow in certain populations that would likely be overlooked by much of the routine analysis with commonly used methods. An outstanding example in the real world is the Kazakh population that experienced complex admixture with sex-biased gene flow but in which the overall signature has been canceled due to biased gene flow from an opposite direction.

Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations

BACKGROUND

Concurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations.

METHODS

Using multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals.

RESULTS

Of the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation.

CONCLUSIONS

Results from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.

Addressing the disparities in dementia risk, early detection and care in Latino populations: Highlights from the second Latinos & Alzheimer's Symposium

The Alzheimer's Association hosted the second Latinos & Alzheimer's Symposium in May 2021. Due to the COVID-19 pandemic, the meeting was held online over 2 days, with virtual presentations, discussions, mentoring sessions, and posters. The Latino population in the United States is projected to have the steepest increase in Alzheimer's disease (AD) in the next 40 years, compared to other ethnic groups. Latinos have increased risk for AD and other dementias, limited access to quality care, and are severely underrepresented in AD and dementia research and clinical trials. The symposium highlighted developments in AD research with Latino populations, including advances in AD biomarkers, and novel cognitive assessments for Spanish-speaking populations, as well as the need to effectively recruit and retain Latinos in clinical research, and how best to deliver health-care services and to aid caregivers of Latinos living with AD.

Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing

Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r2 > 0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF > 5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.

Influence of county-level geographic/ancestral origin on glioma incidence and outcomes in US Hispanics

BACKGROUND

Glioma incidence is 25% lower in Hispanics than White non-Hispanics. The US Hispanic population is diverse, and registry-based analyses may mask incidence differences associated with geographic/ancestral origins.

METHODS

County-level glioma incidence data in Hispanics were retrieved from the Central Brain Tumor Registry of the United States. American Community Survey data were used to determine the county-level proportion of the Hispanic population of Mexican/Central American and Caribbean origins. Age-adjusted incidence rate ratios and incidence rate ratios (IRRs) quantified the glioma incidence differences across groups. State-level estimates of admixture in Hispanics were obtained from published 23andMe data.

RESULTS

Compared to predominantly Caribbean-origin counties, predominantly Mexican/Central American-origin counties had lower age-adjusted risks of glioma (IRR = 0.83; P < 0.0001), glioblastoma (IRR = 0.86; P < 0.0001), diffuse/anaplastic astrocytoma (IRR = 0.78; P < 0.0001), oligodendroglioma (IRR = 0.82; P < 0.0001), ependymoma (IRR = 0.88; P = 0.012), and pilocytic astrocytoma (IRR = 0.76; P < 0.0001). Associations were consistent in children and adults and using more granular geographic regions. Despite having lower glioma incidence, Hispanic glioblastoma patients from predominantly Mexican/Central American-origin counties had poorer survival than Hispanics living in predominantly Caribbean-origin counties. Incidence and survival differences could be partially explained by state-level estimates of European admixture in Hispanics with European admixture associated with higher incidence and improved survival.

CONCLUSIONS

Glioma incidence and outcomes differ in association with the geographic origins of Hispanic communities, with counties of predominantly Mexican/Central American origin at significantly reduced risk and those of Caribbean origin at comparatively greater risk. Although typically classified as a single ethnic group, appreciating the cultural, socioeconomic, and genetic diversity of Hispanics can advance cancer disparities research.

Deep structure, long-distance migration and admixture in the colour polymorphic land snail Cepaea nemoralis

Although snails of the genus Cepaea have historically been important in studying colour polymorphism, an ongoing issue is that there is a lack of knowledge of the underlying genetics of the polymorphism, as well as an absence of genomic data to put findings in context. We, therefore, used phylogenomic methods to begin to investigate the post‐glacial history of Cepaea nemoralis, with a long‐term aim to understand the roles that selection and drift have in determining both European‐wide and local patterns of colour polymorphism. By combining prior and new mitochondrial DNA data from over 1500 individuals with ddRAD genomic data from representative individuals across Europe, we show that patterns of differentiation are primarily due to multiple deeply diverged populations of snails. Minimally, there is a widespread Central European population and additional diverged groups in Northern Spain, the Pyrenees, as well as likely Italy and South Eastern Europe. The genomic analysis showed that the present‐day snails in Ireland and possibly some other locations are likely descendants of admixture between snails from the Pyrenees and the Central European group, an observation that is consistent with prior inferences from mitochondrial DNA alone. The interpretation is that C. nemoralis may have arrived in Ireland via long‐distance migration from the Pyrenean region, subsequently admixing with arrivals from elsewhere. This work, therefore, provides a baseline expectation for future studies on the genetics of the colour polymorphism, as well as providing a comparator for similar species.

Demographic history differences between Hispanics and Brazilians imprint haplotype features

Admixture is known to greatly impact the genetic landscape of a population and, while genetic variation underlying human phenotypes has been shown to differ among populations, studies on admixed subjects are still scarce. Latin American populations are the result of complex demographic history, such as 2 or 3-way admixing events, bottlenecks and/or expansions, and adaptive events unique to the American continent. To explore the impact of these events on the genetic structure of Latino populations, we evaluated the following haplotype features: linkage disequilibrium, shared identity by descent segments, runs of homozygosity, and extended haplotype homozygosity (integrated haplotype score) in Latinos represented in the 1000 Genome Project along with array data from 171 Brazilians sampled in the South and Southeast regions of Brazil. We found that linkage disequilibrium decay relates to the amount of American and African ancestry. The extent of identity by descent sharing positively correlates with historical effective population sizes, which we found to be steady or growing, except for Puerto Ricans and Colombians. Long runs of homozygosity, a particular instance of autozygosity, was only enriched in Peruvians and Native Americans. We used simulations to account for random sampling and linkage disequilibrium to filter positive selection indexes and found 244 unique markers under selection, 26 of which are common to 2 or more populations. Some markers exhibiting positive selection signals had estimated time to the most recent common ancestor consistent with human adaptation to the American continent. In conclusion, Latino populations present highly divergent haplotype characteristics that impact genetic architecture and underlie complex phenotypes.

Germline Pathogenic Variant Prevalence Among Latin American and US Hispanic Individuals Undergoing Testing for Hereditary Breast and Ovarian Cancer: A Cross-Sectional Study

PURPOSE

To report on pathogenic germline variants detected among individuals undergoing genetic testing for hereditary breast and/or ovarian cancer (HBOC) from Latin America and compare them with self-reported Hispanic individuals from the United States.

METHODS

In this cross-sectional study, unrelated individuals with a personal/family history suggestive of HBOC who received clinician-ordered germline multigene sequencing were grouped according to the location of the ordering physician: group A, Mexico, Central America, and the Caribbean; group B, South America; and group C, United States with individuals who self-reported Hispanic ethnicity. Relatives who underwent cascade testing were analyzed separately.

RESULTS

Among 24,075 unrelated probands across all regions, most were female (94.9%) and reported a personal history suggestive of HBOC (range, 65.0%-80.6%); the mean age at testing was 49.1 ± 13.1 years. The average number of genes analyzed per patient was highest in group A (A 63 ± 28, B 56 ± 29, and C 40 ± 28). Between 9.1% and 18.7% of patients had pathogenic germline variants in HBOC genes (highest yield in group A), with the majority associated with high HBOC risk. Compared with US Hispanics individuals the overall yield was significantly higher in both Latin American regions (A v C P = 1.64×10-9, B v C P < 2.2×10-16). Rates of variants of uncertain significance were similar across all three regions (33.7%-42.6%). Cascade testing uptake was low in all regions (A 6.6%, B 4.5%, and C 1.9%).

CONCLUSION

This study highlights the importance of multigene panel testing in Latin American individuals with newly diagnosed or history of HBOC, who can benefit from medical management changes including targeted therapies, eligibility to clinical trials, risk-reducing surgeries, surveillance and prevention of secondary malignancy, and genetic counseling and subsequent cascade testing of at-risk relatives.

Recommendations to encourage participation of individuals from diverse backgrounds in psychiatric genetic studies

We present innovative research practices in psychiatric genetic studies to ensure representation of individuals from diverse ancestry, sex assigned at birth, gender identity, age, body shape and size, and socioeconomic backgrounds. Due to histories of inappropriate and harmful practices against marginalized groups in both psychiatry and genetics, people of certain identities may be hesitant to participate in research studies. Yet their participation is essential to ensure diverse representation, as it is incorrect to assume that the same genetic and environmental factors influence the risk for various psychiatric disorders across all demographic groups. We present approaches developed as part of the Eating Disorders Genetics Initiative (EDGI), a study that required tailored approaches to recruit diverse populations across many countries. Considerations include research priorities and design, recruitment and study branding, transparency, and community investment and ownership. Ensuring representation in participants is costly and funders need to provide adequate support to achieve diversity in recruitment in prime awards, not just as supplemental afterthoughts. The need for diverse samples in genetic studies is critical to minimize the risk of perpetuating health disparities in psychiatry and other health research. Although the EDGI strategies were designed specifically to attract and enroll individuals with eating disorders, our approach is broadly applicable across psychiatry and other fields.

Genetic diversity and population structure of Caryopteris mongholica revealed by reduced representation sequencing

BACKGROUND

Caryopteris mongholica Bunge is a rare broad-leaved shrub distributed in the desert and arid regions of Mongol and North China. Due to land reclamation, natural habitat deterioration and anthropogenic activities in recent years, the wild resources have sharply reduced. To effectively protect and rationally use it, we investigated the genetic diversity and population structure from 18 populations across the range of C. mongholica in China by reduced representation sequencing technology.

RESULTS

We found the overall average values of observed heterozygosity (Ho), expected heterozygosity (He), and average nucleotide diversity (π) were 0.43, 0.35 and 0.135, respectively. Furthermore, the NM17 population exhibited higher genetic diversity than other populations. The phylogenetic tree, principal component analysis (PCA) and structure analysis showed the sampled individuals clustered into two main groups. The NM03 population, with individuals clustered in both groups, may be a transitional population located between the two groups. In addition, most genetic variation existed within populations (90.97%) compared to that among the populations (9.03%). Interestingly, geographic and environmental distances were almost equally important to the observed genetic differences. Redundancy analysis (RDA) identified optical radiation (OR), minimum temperature (MIT) and mean annual precipitation (MAP) related variables as the most important environment factors influencing genetic variation, and the importance of MIT was also confirmed in the latent factor mixed models (LFMM).

CONCLUSIONS

The results of this study facilitate research on the genetic diversity of C. mongholica. These genetic features provided vital information for conserving and sustainably developing the C. mongholica genetic resources.

Clinical Benefits of Olaparib in Mexican Ovarian Cancer Patients With Founder Mutation BRCA1-Del ex9-12

Background: Ovarian cancer (OC) is gynecologic cancer with the highest mortality rate. It is estimated that 13–17% of ovarian cancers are due to heritable mutations in BRCA1 and BRCA2. The BRCA1 (BRCA1-Del ex9-12) Mexican founder mutation is responsible for 28–35% of the cases with ovarian cancer. The aim was to describe the PFS of OC patients treated with olaparib, emphasizing patients carrying the Mexican founder mutation (BRCA1-Del ex9-12).

Methods: In this observational study, of 107 patients with BRCAm, 35 patients were treated with olaparib from November 2016 to May 2021 at the Ovarian Cancer Program (COE) of Mexico; patient information was extracted from electronic medical records.

Results: Of 311 patients, 107 (34.4%) were with BRCAm; 71.9% (77/107) were with BRCA1, of which 27.3% (21/77) were with BRCA1-Del ex9-12, and 28.1% (30/107) were with BRCA2 mutations. Only 35 patients received olaparib treatment, and the median follow-up was 12.87 months. The PFS of BRCA1-Del ex9-12 was NR (non-reach); however, 73% of the patients received the treatment at 36 vs. 11.59 months (95% CI; 10.43–12.75) in patients with other BRCAm (p = 0.008). Almost 50% of patients required dose reduction due to toxicity; the most frequent adverse events were hematological in 76.5% and gastrointestinal in 4%.

Conclusion: Mexican OC BRCA1-Del ex9-12 patients treated with olaparib had a significant increase in PFS regardless of the line of treatment compared to other mutations in BRCA.

An ancient founder mutation located between ROBO1 and ROBO2 is responsible for increased microtia risk in Amerindigenous populations

Microtia is a congenital malformation that encompasses mild hypoplasia to complete loss of the external ear, or pinna. Although the contribution of genetic variation and environmental factors to microtia remains elusive, Amerindigenous populations have the highest reported incidence. Here, using both transmission disequilibrium tests and association studies in microtia trios (parents and affected child) and microtia cohorts enrolled in Latin America, we map an ∼10-kb microtia locus (odds ratio = 4.7; P = 6.78e-18) to the intergenic region between Roundabout 1 (ROBO1) and Roundabout 2 (ROBO2) (chr3: 78546526 to 78555137). While alleles at the microtia locus significantly increase the risk of microtia, their penetrance is low (<1%). We demonstrate that the microtia locus contains a polymorphic complex repeat element that is expanded in affected individuals. The locus is located near a chromatin loop region that regulates ROBO1 and ROBO2 expression in induced pluripotent stem cell–derived neural crest cells. Furthermore, we use single nuclear RNA sequencing to demonstrate ROBO1 and ROBO2 expression in both fibroblasts and chondrocytes of the mature human pinna. Because the microtia allele is enriched in Amerindigenous populations and is shared by some East Asian subjects with craniofacial malformations, we propose that both populations share a mutation that arose in a common ancestor prior to the ancient migration of Eurasian populations into the Americas and that the high incidence of microtia among Amerindigenous populations reflects the population bottleneck that occurred during the migration out of Eurasia.

Anthropological genetic insights on Caribbean population history

As the last American region settled by humans, yet the first to experience European colonization, the Caribbean islands have a complex history characterized by continuous migration, admixture, and demographic change. In the last 20 years, genetics research has transformed our understanding of Caribbean population history and revisited major debates in Caribbean anthropology, such as those surrounding the first peopling of the Antilles and the relationship between ancient Indigenous communities and present-day islanders. Genetics studies have also contributed novel perspectives for understanding pivotal events in Caribbean post-contact history such as European colonization, the Atlantic Slave Trade, and the Asian Indenture system. Here, I discuss the last 20 years of Caribbean genetics research and emphasize the importance of integrating genetics with interdisciplinary historic, archaeological, and anthropological approaches. Such interdisciplinary research is essential for investigating the dynamic history of the Caribbean and characterizing its impact on the biocultural diversity of present-day Caribbean peoples.

Incorporating local ancestry improves identification of ancestry-associated methylation signatures and meQTLs in African Americans

Here we report three epigenome-wide association studies (EWAS) of DNA methylation on self-reported race, global genetic ancestry, and local genetic ancestry in admixed Americans from three sets of samples, including internal and external replications (Ntotal = 1224). Our EWAS on local ancestry (LA) identified the largest number of ancestry-associated DNA methylation sites and also featured the highest replication rate. Furthermore, by incorporating ancestry origins of genetic variations, we identified 36 methylation quantitative trait loci (meQTL) clumps for LA-associated CpGs that cannot be captured by a model that assumes identical genetic effects across ancestry origins. Lead SNPs at 152 meQTL clumps had significantly different genetic effects in the context of an African or European ancestry background. Local ancestry information enables superior capture of ancestry-associated methylation signatures and identification of ancestry-specific genetic effects on DNA methylation. These findings highlight the importance of incorporating local ancestry for EWAS in admixed samples from multi-ancestry cohorts.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.