Estimating African American admixture proportions by use of population-specific alleles

Epidemiology of fractures in adults of African ancestry with diabetes mellitus: A systematic review and meta-analysis

Diabetes mellitus (DM) is associated with increased fracture risk in White adults. However, the impact of DM on fractures in Black adults is unknown. This systematic review and meta-analysis investigated the association between DM and fractures in adults of African ancestry. MEDLINE, Scopus, CINAHL and Embase databases were searched from their inception up to November 2023 for all studies in the English language investigating the epidemiology of fractures (prevalence, incidence, or risk) in Black men and women (age ≥ 18 years) with type 1 or type 2 DM. Effect sizes for prevalence of previous fractures (%) and incident fracture risk (hazard ratio [HR]) were calculated using a random-effects model on Stata (version 18.0). There were 13 eligible studies, of which 12 were conducted in Black adults from the United States, while one was conducted in adults of West African ancestry from Trinidad and Tobago. We found no fracture data in Black adults with DM living in Africa. Five studies were included in a meta-analysis of incident fracture risk, reporting data from 2926 Black and 6531 White adults with DM. There was increased risk of fractures in Black adults with DM compared to non-DM (HR = 1.65; 95 % confidence interval [CI]: 1.14, 2.39). The risk of fractures was also higher in White adults with DM compared to non-DM (HR = 1.31; 95 % CI: 1.06, 1.61) among these studies. Five studies were included in a meta-analysis of fracture prevalence, of which three also reported fracture prevalence in White adults. There were 175 previous fractures among 993 Black adults with DM and 384 previous fractures among 1467 White adults with DM, with a pooled prevalence of 17.5 % (95 % CI: 15.4, 19.6) and 25.8 % (95 % CI: 4.8, 46.8), respectively. Our results indicate a high burden of fractures in Black adults with DM.

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.

Simplified detection of genetic background admixture using artificial intelligence

Admixture refers to the mixing of genetic ancestry from different populations. Admixture is important for genomic medicine because it can affect how an individual responds to certain medications, how they metabolize drugs, and susceptibility to certain diseases. For example, some genetic variants associated with drug metabolism and response may be more common in certain populations, and individuals with admixed ancestry may have a different frequency of these variants than individuals from the ancestral populations. Understanding the patterns of admixture in a population can also help researchers identify new genetic variants associated with diseases or traits and develop more personalized and targeted treatments. In this study, we compared and classified the known and self-reported genetic backgrounds from 1000 Genomes Project and admixed samples from GTEx projects using supervised, unsupervised and statistical classification methodologies. We developed a novel tool called Admix-AI that uses a one-dimensional convolutional neural network to understand and classify admixed genetic backgrounds using 213 DNA-marker based genetic background labels. Admix-AI can be used to discover admixed proportions in samples and ultimately aid personalized genomic medicine by identifying specific biomarker systems. We compared Admix-AI to the existing admixture categorization software and found our tool to be computationally faster with 2× speedup and streamlined usage. Admix-AI is available as open-source code under GPL version 3.0 license at https://github.com/rpauly/Admix-AI.

Characterizing epigenetic aging in an adult sickle cell disease cohort

ABSTRACT

Sickle cell disease (SCD) affects ∼100 000 predominantly African American individuals in the United States, causing significant cellular damage, increased disease complications, and premature death. However, the contribution of epigenetic factors to SCD pathophysiology remains relatively unexplored. DNA methylation (DNAm), a primary epigenetic mechanism for regulating gene expression in response to the environment, is an important driver of normal cellular aging. Several DNAm epigenetic clocks have been developed to serve as a proxy for cellular aging. We calculated the epigenetic ages of 89 adults with SCD (mean age, 30.64 years; 60.64% female) using 5 published epigenetic clocks: Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE. We hypothesized that in chronic disease, such as SCD, individuals would demonstrate epigenetic age acceleration, but the results differed depending on the clock used. Recently developed clocks more consistently demonstrated acceleration (GrimAge, DunedinPACE). Additional demographic and clinical phenotypes were analyzed to explore their association with epigenetic age estimates. Chronological age was significantly correlated with epigenetic age in all clocks (Horvath, r = 0.88; Hannum, r = 0.89; PhenoAge, r = 0.85; GrimAge, r = 0.88; DunedinPACE, r = 0.34). The SCD genotype was associated with 2 clocks (PhenoAge, P = .02; DunedinPACE, P < .001). Genetic ancestry, biological sex, β-globin haplotypes, BCL11A rs11886868, and SCD severity were not associated. These findings, among the first to interrogate epigenetic aging in adults with SCD, demonstrate epigenetic age acceleration with recently developed epigenetic clocks but not older-generation clocks. Further development of epigenetic clocks may improve their predictive ability and utility for chronic diseases such as SCD.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Treatment Intensity, Prescribing Patterns, and Blood Pressure Control in Rural Black Patients with Uncontrolled Hypertension

BACKGROUND/OBJECTIVE

Because racial disparities in hypertension treatment persist, the objective of the present study was to examine patient vs. practice characteristics that influence antihypertensive selection and treatment intensity for non-Hispanic Black (hereafter "Black") patients with uncontrolled hypertension in the rural southeastern USA.

METHODS

We enrolled 25 Black patients from each of 69 rural practices in Alabama and North Carolina with uncontrolled hypertension (systolic blood pressure (BP) ≥ 140 mm Hg) in a 4-arm cluster randomized trial of BP control interventions. Patients' antihypertensive medications were abstracted from medical records and reconciled at the baseline visit. Treatment intensity was computed using the defined daily dose (DDD) method of the World Health Organization. Correlates of greater antihypertensive medication intensity were assessed by linear regression modeling, and antihypertensive medication classes were compared by baseline systolic BP (SBP) level.

RESULTS

A total of 1431 patients were enrolled and had complete baseline data. Antihypertensive treatment intensity averaged 3.7 ± 2.6 equivalent medications at usual dosages and was significantly related to higher baseline systolic BP, older age, male sex, insurance availability, higher BMI, and concurrent diabetes, but not to practice type or medication barriers in regression models. Renin-angiotensin system inhibitors were the most commonly used medications, followed by diuretics and calcium channel blockers.

CONCLUSION/RELEVANCE

Antihypertensive treatment intensity for Black patients in the rural southeastern USA with a history of uncontrolled hypertension averaged the equivalent of almost four medications at usual dosages and was significantly associated with baseline SBP levels and other patient characteristics, but not clinic type.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02866669.

Ancestry component as a major predictor of lithium response in the treatment of bipolar disorder

BACKGROUND

Bipolar Disorder (BD) represents the seventh major cause of disability life-years-adjusted. Lithium remains as a first-line treatment, but clinical improvement occurs only in 30 % of treated patients. Studies suggest that genetics plays a major role in shaping the individual response of BD patients to lithium.

METHODS

We used machine-learning techniques (Advance Recursive Partitioned Analysis, ARPA) to build a personalized prediction framework of BD lithium response using biological, clinical, and demographical data. Using the Alda scale, we classified 172 BD I-II patients as responders or non-responders to lithium treatment. ARPA methods were used to build individual prediction frameworks and to define variable importance. Two predictive models were evaluated: 1) demographic and clinical data, and 2) demographic, clinical and ancestry data. Model performance was assessed using Receiver Operating Characteristic (ROC) curves.

RESULTS

The predictive model including ancestry yield the best performance (sensibility = 84.6 %, specificity = 93.8 % and AUC = 89.2 %) compared to the model without ancestry (sensibility = 50 %, Specificity = 94.5 %, and AUC = 72.2 %). This ancestry component best predicted lithium individual response. Clinical variables such as disease duration, the number of depressive episodes, the total number of affective episodes, and the number of manic episodes were also important predictors.

CONCLUSION

Ancestry component is a major predictor and significantly improves the definition of individual Lithium response in BD patients. We provide classification trees with potential bench application in the clinical setting. While this prediction framework might be applied in specific populations, the used methodology might be of general use in precision and translational medicine.

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

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

African genetic ancestry is associated with lower frequency of PNPLA3 G allele in non-alcoholic fatty liver in an admixed population

INTRODUCTION AND OBJECTIVES

PNPLA3 (rs738409) and TM6SF2 (rs58542926) variants, interindividual and ethnic differences may be risk factors for non-alcoholic fatty liver disease (NAFLD). The PNPLA3 G allele is associated with worse NAFLD evolution in Hispanics and Caucasians. TM6SF2 is associated with hypertriglyceridemia, NAFLD, and cardiovascular disease. We aimed to evaluate the association between genetic ancestry by Ancestry Informative Markers (AIM), PNPLA3 and TM6SF2 polymorphisms in patients with biopsy-proven NAFLD in an admixed population.

METHODS

We included adults with biopsy-proven NAFLD and excluded patients with the presence of other chronic liver disease, alcohol intake &gt;100g/week, HIV, drug-induced fatty liver disease, or liver transplantation. We classified NAFLD using the Non-Alcoholic Steatohepatitis Clinical Research Network (NASH-CRN) histological scoring system. The PNPLA3 (rs738409 c.444C&gt;G) and TM6SF2 (rs58542926 c.449C&gt;T) genotyping were performed by RT-PCR. Genetic ancestry was determined using 46 insertion-deletion AIM; α&lt;0.05 was considered significant.

RESULTS

A total of 248 patients with NAFLD were enrolled [34 with simple steatosis (NAFL); 214 with NASH]. Overall, we detected a greater European ancestry contribution (0.645), followed by African (0.173), Amerindian (0.095), and East Asian (0.087) ancestry contribution, without differences between NAFL and NASH patients. However, we found a higher African genetic ancestry contribution among patients with NAFL who had the PNPLA3 C/C genotype than those with the G allele (0.216 ± 0.205 versus 0.105 ± 0.101, respectively; p=0.047). Ancestry contributions did not differ among TM6SF2 genotypes.

CONCLUSION

Among NAFL patients, greater African genetic ancestry was associated to a lower frequency of the PNPLA3 G allele, demonstrating a possible NASH ancestry-related protective factor.

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.

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.

Exploring the Effects of Mitonuclear Interactions on Mitochondrial DNA Gene Expression in Humans

Most mitochondrial protein complexes include both nuclear and mitochondrial gene products, which coevolved to work together. This coevolution can be disrupted due to disparity in genetic ancestry between the nuclear and mitochondrial genomes in recently admixed populations. Such mitonuclear DNA discordance might result in phenotypic effects. Several nuclear-encoded proteins regulate expression of mitochondrial DNA (mtDNA) genes. We hypothesized that mitonuclear DNA discordance affects expression of genes encoded by mtDNA. To test this, we utilized the data from the GTEx project, which contains expression levels for ∼100 African Americans and >600 European Americans. The varying proportion of African and European ancestry in recently admixed African Americans provides a range of mitonuclear discordance values, which can be correlated with mtDNA gene expression levels (adjusted for age and ischemic time). In contrast, European Americans did not undergo recent admixture. We demonstrated that, for most mtDNA protein-coding genes, expression levels in energetically-demanding tissues were lower in African Americans than in European Americans. Furthermore, gene expression levels were lower in individuals with higher mitonuclear discordance, independent of population. Moreover, we found a negative correlation between mtDNA gene expression and mitonuclear discordance. In African Americans, the average value of African ancestry was higher for nuclear-encoded mitochondrial than non-mitochondrial genes, facilitating a match in ancestry with the mtDNA and more optimal interactions. These results represent an example of a phenotypic effect of mitonuclear discordance on human admixed populations, and have potential biomedical applications.

Estimates of West African Ancestry in African Americans Using Alleles of Iron-Related Genes HJV, SLC40A1, and TFR2

Background: Few studies have estimated African ancestry of African Americans (AA). In sub-Saharan West African (WA) Blacks, some nonancestral alleles of iron-related genes HJV, SLC40A1, and TFR2 are common, whereas in European Americans (EA) the same alleles are rare. These alleles have not been used to estimate WA Black ancestry in AA. Methods: We estimated WA Black ancestry in AA (M) using published HJV c.929C>G (rs7540883), SLC40A1 c.744G>T (rs11568350), and TFR2 c.713C>T (rs34242818) allele frequencies in WA Blacks, AA, and EA. We computed standard error (SE) and one-sided 95% confidence intervals (CI) for each M. Results: The combined representation of WA Blacks from The Gambia and Nigeria was 79-89%. Aggregate HJV, SLC40A1, and TFR2 allele frequencies in WA Blacks were 0.1025 [95% CI: 0.0835-0.1253] (n = 405), 0.0517 [0.0469-0.0569] (n = 3839), and 0.1432 [0.1202-0.1697] (n = 405), respectively. Aggregate HJV, SLC40A1, and TFR2 allele frequencies in AA were 0.0718 [0.0648-0.0797] (n = 2352), 0.0557 [0.0506-0.0613] (n = 3590), and 0.1224 [0.1132-0.1322] (n = 2352), respectively. Aggregate HJV, SLC40A1, and TFR2 allele frequencies in 4449 EA were 0.0002 [0-0.0009], 0.0003 [0.0001-0.0010], and 0.0004 [0.0001-0.0012], respectively. M (SE [one-sided 95% CI]) for HJV, SLC40A1, and TFR2 alleles was 0.7006 (0.0818 [0.5402-1.0000]), 1.0000 (0.0752 [0.9306-1.0000]), and 0.8546 (0.0810 [0.6959-1.0000]), respectively. Mean of these M is 0.8777 (87.8%). Conclusions: The mean proportional WA Black ancestry in AA of 87.8% using HJV c.929C>G, SLC40A1 c.744G>T, and TFR2 c.713C>T allele frequencies is consistent with that of previous studies that used other autosomal markers and methods.

Convolutional Embedded Networks for Population Scale Clustering and Bio-Ancestry Inferencing

The study of genetic variants (GVs) can help find correlating population groups and to identify cohorts that are predisposed to common diseases and explain differences in disease susceptibility and how patients react to drugs. Machine learning techniques are increasingly being applied to identify interacting GVs to understand their complex phenotypic traits. Since the performance of a learning algorithm not only depends on the size and nature of the data but also on the quality of underlying representation, deep neural networks (DNNs) can learn non-linear mappings that allow transforming GVs data into more clustering and classification friendly representations than manual feature selection. In this paper, we propose convolutional embedded networks (CEN) in which we combine two DNN architectures called convolutional embedded clustering (CEC) and convolutional autoencoder (CAE) classifier for clustering individuals and predicting geographic ethnicity based on GVs, respectively. We employed CAE-based representation learning to 95 million GVs from the '1000 genomes' (covering 2,504 individuals from 26 ethnic origins) and 'Simons genome diversity' (covering 279 individuals from 130 ethnic origins) projects. Quantitative and qualitative analyses with a focus on accuracy and scalability show that our approach outperforms state-of-the-art approaches such as VariantSpark and ADMIXTURE. In particular, CEC can cluster targeted population groups in 22 hours with an adjusted rand index (ARI) of 0.915, the normalized mutual information (NMI) of 0.92, and the clustering accuracy (ACC) of 89 percent. Contrarily, the CAE classifier can predict the geographic ethnicity of unknown samples with an F1 and Mathews correlation coefficient (MCC) score of 0.9004 and 0.8245, respectively. Further, to provide interpretations of the predictions, we identify significant biomarkers using gradient boosted trees (GBT) and SHapley Additive exPlanations (SHAP). Overall, our approach is transparent and faster than the baseline methods, and scalable for 5 to 100 percent of the full human genome.

African Ancestry vs. Creatine Kinase to Predict Hypertension Control: Time for a Change?

BACKGROUND

African ancestry patients are considered separately in hypertension guidelines because of more severe hypertension that is presumably harder to control. However, despite the perceived benefit in reducing health disparities, racial profiling in medicine is increasingly criticized for its potential of bias and stereotyping. Therefore, we studied whether creatine kinase (CK), an ATP-regenerating enzyme that enhances vascular contractility and sodium retention, could serve as a more proximate causal parameter of therapy failure than race/ancestry.

METHODS

In a random multiethnic population sample, we compared the performance of African ancestry vs. resting plasma CK as predictors of treated uncontrolled hypertension. Difference in area under the receiver operating curve (AUC) was the primary outcome.

RESULTS

We analyzed 1,405 persons of African, Asian, and European ancestry (40.2% men, mean age 45.5 years, SE 0.2). Hypertension prevalence was 39% in African vs. 29% in non-African ancestry participants vs. 41% and 27% by high and low CK tertiles. Control rates of treated patients were similar by ancestry (African ancestry patients 40%, non-African ancestry 41%; P = 0.84), but 27% vs. 53% in patients with high vs. low CK (22% vs. 67% in African and 32% vs. 52% in non-African participants). AUC was 0.51 [0.41-0.60] for African ancestry vs. 0.64 [0.55-0.73] for log CK (P = 0.02).

CONCLUSIONS

In contrast to African ancestry, CK might identify hypertensive patients at risk for therapy failure across different ancestry groups. Larger, prospective studies should establish whether resting plasma CK is clinically useful as an impartial method to help predict antihypertensive therapy failure.

Evolutionary perspectives on African North American genetic diversity: Origins and prospects for future investigations

African-descended peoples of the Americas represent an amalgamation of West, Central, and Southeast African regional and ethnic groups with modest gene flow from specific non-African populations. Despite 16+ generations of residence in the Americas, there is a deficit of evolutionary knowledge about these populations. Focusing on Legacy African American, the African North American descendants of survivors of the transatlantic trade in enslaved Africans, we report on emic evolutionary perspectives of their self-identity gleaned from our interviews of 600 individuals collected over 2 years. Gullah-Geechee peoples of Carolina Coastal regions are a model case study due to their historical antiquity, substantial African retentions, relative geospatial isolation, and proposed progenitor status to other Legacy African American microethnic groups. We identify salient research questions for future studies that will begin to bridge the evolutionary gaps in our knowledge of these diverse peoples and the historical evidence for specific evolutionary processes.

Genetic landscape of Gullah African Americans

OBJECTIVES

Gullah African Americans are descendants of formerly enslaved Africans living in the Sea Islands along the coast of the southeastern U.S., from North Carolina to Florida. Their relatively high numbers and geographic isolation were conducive to the development and preservation of a unique culture that retains deep African features. Although historical evidence supports a West-Central African ancestry for the Gullah, linguistic and cultural evidence of a connection to Sierra Leone has led to the suggestion of this country/region as their ancestral home. This study sought to elucidate the genetic structure and ancestry of the Gullah.

MATERIALS AND METHODS

We leveraged whole-genome genotype data from Gullah, African Americans from Jackson, Mississippi, African populations from Sierra Leone, and population reference panels from Africa and Europe to infer population structure, ancestry proportions, and global estimates of admixture.

RESULTS

Relative to non-Gullah African Americans from the Southeast US, the Gullah exhibited higher mean African ancestry, lower European admixture, a similarly small Native American contribution, and increased male-biased European admixture. A slightly tighter bottleneck in the Gullah 13 generations ago suggests a largely shared demographic history with non-Gullah African Americans. Despite a slightly higher relatedness to populations from Sierra Leone, our data demonstrate that the Gullah are genetically related to many West African populations.

DISCUSSION

This study confirms that subtle differences in African American population structure exist at finer regional levels. Such observations can help to inform medical genetics research in African Americans, and guide the interpretation of genetic data used by African Americans seeking to explore ancestral identities.

Skin deep: The decoupling of genetic admixture levels from phenotypes that differed between source populations

OBJECTIVES

In genetic admixture processes, source groups for an admixed population possess distinct patterns of genotype and phenotype at the onset of admixture. Particularly in the context of recent and ongoing admixture, such differences are sometimes taken to serve as markers of ancestry for individuals-that is, phenotypes initially associated with the ancestral background in one source population are assumed to continue to reflect ancestry in that population. Such phenotypes might possess ongoing significance in social categorizations of individuals, owing in part to perceived continuing correlations with ancestry. However, genotypes or phenotypes initially associated with ancestry in one specific source population have been seen to decouple from overall admixture levels, so that they no longer serve as proxies for genetic ancestry. Here, we aim to develop an understanding of the joint dynamics of admixture levels and phenotype distributions in an admixed population.

METHODS

We devise a mechanistic model, consisting of an admixture model, a quantitative trait model, and a mating model. We analyze the behavior of the mechanistic model in relation to the model parameters.

RESULTS

We find that it is possible for the decoupling of genetic ancestry and phenotype to proceed quickly, and that it occurs faster if the phenotype is driven by fewer loci. Positive assortative mating attenuates the process of dissociation relative to a scenario in which mating is random with respect to genetic admixture and with respect to phenotype.

CONCLUSIONS

The mechanistic framework suggests that in an admixed population, a trait that initially differed between source populations might serve as a reliable proxy for ancestry for only a short time, especially if the trait is determined by few loci. It follows that a social categorization based on such a trait is increasingly uninformative about genetic ancestry and about other traits that differed between source populations at the onset of admixture.

The Role of Genetic Ancestry as a Risk Factor for Primary Open-angle Glaucoma in African Americans

Purpose

POAG is the leading cause of irreversible blindness in African Americans. In this study, we quantitatively assess the association of autosomal ancestry with POAG risk in a large cohort of self-identified African Americans.

Methods

Subjects recruited to the Primary Open-Angle African American Glaucoma Genetics (POAAGG) study were classified as glaucoma cases or controls by fellowship-trained glaucoma specialists. POAAGG subjects were genotyped using the MEGA Ex array (discovery cohort, n = 3830; replication cohort, n = 2135). Population structure was interrogated using principal component analysis in the context of the 1000 Genomes Project superpopulations.

Results

The majority of POAAGG samples lie on an axis between African and European superpopulations, with great variation in admixture. Cases had a significantly lower mean value of the ancestral component q0 than controls for both cohorts (P = 6.14-4; P = 3-6), consistent with higher degree of African ancestry. Among POAG cases, higher African ancestry was also associated with thinner central corneal thickness (P = 2-4). Admixture mapping showed that local genetic ancestry was not a significant risk factor for POAG. A polygenic risk score, comprised of 23 glaucoma-associated single nucleotide polymorphisms from the NHGRI-EBI genome-wide association study catalog, was significant in both cohorts (P < 0.001), suggesting that both known POAG single nucleotide polymorphisms and an omnigenic ancestry effect influence POAG risk.

Conclusions

In sum, the POAAGG study population is very admixed, with a higher degree of African ancestry associated with an increased POAG risk. Further analyses should consider social and environmental factors as possible confounding factors for disease predisposition.

Association of variants in IL1B, TLR9, TREM1, IL10RA, and CD3G and Native American ancestry on malaria susceptibility in Colombian populations

Host genetics is an influencing factor in the manifestation of infectious diseases. In this study, the association of mild malaria with 28 variants in 16 genes previously reported in other populations and/or close to ancestry-informative markers (AIMs) selected was evaluated in an admixed 736 Colombian population sample. Additionally, the effect of genetic ancestry on phenotype expression was explored. For this purpose, the ancestral genetic composition of Turbo and El Bagre was determined. A higher Native American ancestry trend was found in the population with lower malaria susceptibility [odds ratio (OR) = 0.416, 95% confidence interval (95% CI) = 0.234-0.740, P = 0.003]. Three AIMs presented significant associations with the disease phenotype (MID1752, MID921, and MID1586). The first two were associated with greater malaria susceptibility (D/D, OR = 2.23, 95% CI = 1.06-4.69, P = 0.032 and I/D-I/I, OR = 2.14, 95% CI = 1.18-3.87, P = 0.011, respectively), and the latter has a protective effect on the appearance of malaria (I/I, OR = 0.18, 95% CI = 0.08-0.40, P < 0.0001). After adjustment by age, sex, municipality, and genetic ancestry, genotype association analysis showed evidence of association with malaria susceptibility for variants in or near IL1B, TLR9, TREM1, IL10RA, and CD3G genes: rs1143629-IL1B (G/A-A/A, OR = 0.41, 95% CI = 0.21-0.78, P = 0.0051), rs352139-TLR9 (T/T, OR = 0.28, 95% CI = 0.11-0.72, P = 0.0053), rs352140-TLR9 (C/C, OR = 0.41, 95% CI = 0.20-0.87, P = 0.019), rs2234237-TREM1 (T/A-A/A, OR = 0.43, 95% CI = 0.23-0.79, P = 0.0056), rs4252246-IL10RA (C/A-A/A, OR = 2.11, 95% CI = 1.18-3.75, P = 0.01), and rs1561966-CD3G (A/A, OR = 0.20, 95% CI = 0.06-0.69, P = 0.0058). The results showed the participation of genes involved in immunological processes and suggested an effect of ancestral genetic composition over the traits analyzed. Compared to the paisa population (Antioquia), Turbo and El Bagre showed a strong decrease in European ancestry and an increase in African and Native American ancestries. Also, a novel association of two single nucleotide polymorphisms with malaria susceptibility was identified in this study.

Genetic admixture in Brazil

We review studies from our laboratories using different molecular tools to characterize the Amerindian, European and African ancestry of Brazilians. Initially we used uniparental DNA markers to investigate the contribution of distinct Y chromosome and mitochondrial DNA lineages to present-day populations. High levels of genetic admixture and strong directional mating between European males and Amerindian and African females were unraveled. We next analyzed different types of biparental autosomal polymorphisms. Especially useful was a set of 40 insertion-deletion polymorphisms (indels) that when studied worldwide proved exquisitely sensitive in discriminating between Amerindians, Europeans and Sub-Saharan Africans. When applied to the study of Brazilians these markers confirmed extensive genomic admixture. We then studied ancestry differences in different regions by statistically controlling them to eliminate color considerations. The European ancestry was predominant in all regions studied, with proportions ranging from 60.6% in the Northeast to 77.7% in the South. We propose that the immigration of 6 million Europeans to Brazil in the 19th and 20th centuries is in large part responsible for dissipating previous ancestry dissimilarities that reflected region-specific population histories. Brazilians should be assessed individually, as 210 million human beings, and not as members of specific regions or color groups.

Association of Genetic West African Ancestry, Blood Pressure Response to Therapy, and Cardiovascular Risk Among Self-Reported Black Individuals in the Systolic Blood Pressure Reduction Intervention Trial (SPRINT)

IMPORTANCE

Self-identified Black race is associated with higher hypertension prevalence and worse blood pressure (BP) control compared with other race/ethnic groups. The contribution of genetic West African ancestry to these racial disparities appears not to have been completely determined.

OBJECTIVE

To determine the association between the proportion of West African ancestry with the response to antihypertensive medication, BP control, kidney function, and risk of adverse cardiovascular (CV) events among self-identified Black individuals in the Systolic Blood Pressure Intervention Trial (SPRINT).

DESIGN, SETTING, AND PARTICIPANTS

This post hoc analysis of the SPRINT trial incorporated data from a multicenter study of self-identified Black participants with available West African ancestry proportion, estimated using 106 biallelic autosomal ancestry informative genetic markers. Recruitment started on October 20, 2010, and ended on August 20, 2015. Data were analyzed from May 2020 to September 2020.

MAIN OUTCOMES AND MEASURES

Trajectories of BP and kidney function parameters on follow-up of the trial were assessed across tertiles of the proportion of West African ancestry using linear mixed-effect modeling after adjustment for potential confounders. Multivariable adjusted Cox models evaluated the association of West African ancestry with the risk of composite CV events (nonfatal myocardial infarction, CV death, and heart failure event).

RESULTS

Among 2466 participants in the current analysis (1122 women [45.5%]; median West African ancestry, 81% [interquartile range, 73%-87%]), there were 120 composite CV events (4.9%) over a mean (SD) of 3.2 (0.9) years of follow-up. At baseline, mean (SD) high-density lipoprotein cholesterol levels were higher (tertile 3: 56.5 [15.0] mg/dL vs tertile 1: 54.2 [14.9] mg/dL; P = .006), smoking prevalence (never smoking: tertile 3: 367 [47.9%] vs tertile 1: 372 [42.2%]; P = .009) and mean (SD) Framingham Risk scores (tertile 3: 16.7 [9.7] vs tertile 1: 18.1 [10.2]; P = .01) were lower, and baseline BP was not different across increasing tertiles of West African ancestry. On follow-up, there was no evidence of differences in longitudinal trajectories of BP, kidney function parameters, or left ventricular mass (Cornell voltage by electrocardiogram) across tertiles of West African ancestry in either intensive or standard treatment arms. In adjusted Cox models, higher West African ancestry was associated with a lower risk of a composite CV event after adjustment for potential confounders (adjusted hazard ratio per 5% higher West African ancestry, 0.92 [95% CI, 0.85-0.99]).

CONCLUSIONS AND RELEVANCE

Among self-reported Black individuals enrolled in SPRINT, the trajectories of BP, kidney function, and left ventricular mass over time were not different across tertiles of the proportion of West African ancestry. A higher proportion of West African ancestry was associated with a modestly lower risk for CV events. These findings suggest that extrinsic and structural societal factors, more than genetic ancestry, may be the major drivers of the well-established racial disparity in cardiovascular health associated with hypertension.

Genetic ancestry, skin color and social attainment: The four cities study

Introduction

The Black population in the US is heterogeneous but is often treated as monolithic in research, with skin pigmentation being the primary indicator of racial classification. Objective: This paper examines the differences among Blacks by comparing genetic ancestry, skin color and social attainment of 259 residents across four US cities—Norman, Oklahoma; Cincinnati, Ohio; Harlem, New York; and Washington, District of Columbia.

Methods

Participants were recruited between 2004 and 2006 at community-based forums. Cross-sectional data were analyzed using chi-square tests, correlation analyses and logistic regression.

Results

There were variations in ancestry, melanin index and social attainment across some cities. Overall, men with darker skin color, and women with lighter skin color were significantly more likely to be married. Darker skin individuals with significantly more West African ancestry reported attainment of graduate degrees, and professional occupations than lighter skin individuals.

Conclusions

Our findings suggest differences in skin pigmentation by geography and support regional variations in ancestry of US Blacks. Biomedical research should consider genetic ancestry and local historical/social context rather than relying solely on skin pigmentation as a proxy for race.

Estimates of European American Ancestry in African Americans Using HFE p.C282Y

Background: HFE p.C282Y (chromosome 6p22.2; exon 4, c.845G>A; rs1800562), a hemochromatosis-associated polymorphism in European Americans, is absent in sub-Saharan West African blacks. Methods: We estimated European American ancestry in African Americans (M) using published p.C282Y allele frequencies of sub-Saharan West African blacks; and ≥50 unselected African Americans and ≥50 unselected European Americans in the same city/region. Results: p.C282Y allele frequency in 870 West African blacks (The Gambia, Ghana, Nigeria, Senegal, Sierra Leone) was 0.0000 (confidence interval [95% CI 0.0000-0.0027]). p.C282Y allele frequencies in European Americans were 0.0600 (12,592 participants; five single-site studies) and 0.0673 (54,882 participants; two multisite studies). p.C282Y allele frequencies in African Americans were 0.0102 (3084 participants; five single-site studies) and 0.0122 (30,762 participants; two multisite studies). M for all data was 0.1803 (standard error 0.0049; [95% CI 0.1706-0.1900]). City/region estimates of M differed 1.8-fold: 0.1321, Rochester, NY; 0.1456, Birmingham, AL; 0.1569, Upper Savannah Region, SC; 0.1612, Portland, OR; 0.1746, San Diego, CA; 0.1780, Hartford, CT; 0.1957, District of Columbia; 0.2377, Oakland, CA; and 0.2429, Irvine, CA. Conclusions: Estimates of M using p.C282Y are consistent with those using other autosomal markers, differ across nine cities/regions, and reflect paternal and maternal contributions of European American ancestry in African Americans.

Insights into the genetic characteristics and population structures of Chinese two Tibetan groups using 35 insertion/deletion polymorphic loci

Studying the genetic structure of each ethnic group is helpful to clarify the genetic background and trace back to the ethnic origin. Tibetan people have lived in the Qinghai-Tibet Plateau (mean elevation over 4500 m) for generations, and have well adapted to the high-altitude environment. Due to the relatively closed geographical environment, Tibetans have preserved their representative physical characteristics and genetic information, thereby become an important research group in human genetics. In this study, genetic characteristics and population structures of two Tibetan groups (Qinghai Tibetans and Tibet Tibetans) were revealed by 35 insertion/deletion polymorphism (DIP) loci, aiming to provide valuable genetic information for population genetic differentiation analyses and forensic identifications. The combined discrimination power, cumulative exclusion probability and combined match probability of the 35 DIP loci in Qinghai Tibetan and Tibet Tibetan groups were 0.9999999999999945, 0.9988, 5.56623 × 10^-15; and 0.9999999999999904, 0.9990, 9.69071 × 10^-15, respectively, indicating that the panel possessed a strong capability for Tibetan personal identifications. Population differentiations and genetic relationship analyses among the two studied Tibetan groups and other 27 comparison populations were carried out using the Nei's D_A genetic distances, population pairwise genetic distances F-statistics (F_ST), analysis of molecular variance (AMOVA), phylogenetic tree reconstruction, principal component analysis and STRUCTURE methods. Results demonstrated that the most intimate genetic relationships existed in these two Tibetan groups; and genetic similarities between two Tibetan groups and the populations from East Asia were much stronger than that between the Tibetan groups and other geographical populations. Furthermore, forensic ancestral informativeness assessments suggested that several loci could be regarded as ancestry informative markers inferring individual biogeographic origins as well as contributing to forensic anthropology and population genetic researches.

Population Histories of the United States Revealed through Fine-Scale Migration and Haplotype Analysis

The population of the United States is shaped by centuries of migration, isolation, growth, and admixture between ancestors of global origins. Here, we assemble a comprehensive view of recent population history by studying the ancestry and population structure of more than 32,000 individuals in the US using genetic, ancestral birth origin, and geographic data from the National Geographic Genographic Project. We identify migration routes and barriers that reflect historical demographic events. We also uncover the spatial patterns of relatedness in subpopulations through the combination of haplotype clustering, ancestral birth origin analysis, and local ancestry inference. Examples of these patterns include substantial substructure and heterogeneity in Hispanics/Latinos, isolation-by-distance in African Americans, elevated levels of relatedness and homozygosity in Asian immigrants, and fine-scale structure in European descents. Taken together, our results provide detailed insights into the genetic structure and demographic history of the diverse US population.

A Likelihood-Free Estimator of Population Structure Bridging Admixture Models and Principal Components Analysis

We introduce a simple and computationally efficient method for fitting the admixture model of genetic population structure, called ALStructure The strategy of ALStructure is to first estimate the low-dimensional linear subspace of the population admixture components, and then search for a model within this subspace that is consistent with the admixture model's natural probabilistic constraints. Central to this strategy is the observation that all models belonging to this constrained space of solutions are risk-minimizing and have equal likelihood, rendering any additional optimization unnecessary. The low-dimensional linear subspace is estimated through a recently introduced principal components analysis method that is appropriate for genotype data, thereby providing a solution that has both principal components and probabilistic admixture interpretations. Our approach differs fundamentally from other existing methods for estimating admixture, which aim to fit the admixture model directly by searching for parameters that maximize the likelihood function or the posterior probability. We observe that ALStructure typically outperforms existing methods both in accuracy and computational speed under a wide array of simulated and real human genotype datasets. Throughout this work, we emphasize that the admixture model is a special case of a much broader class of models for which algorithms similar to ALStructure may be successfully employed.

Gut microbiota composition explains more variance in the host cardiometabolic risk than genetic ancestry

Cardiometabolic affections greatly contribute to the global burden of disease. The susceptibility to obesity, cardiovascular disease, and type-2 diabetes, conditions that add to the cardiometabolic syndrome (CMS), was associated with the ancestral genetic composition and gut microbiota. Studies explicitly testing associations between genetic ancestry and gut microbes are growing. We here examined whether the host genetic ancestry was associated with gut microbiota composition, and distinguished the effects of genetic ancestry and non-genetic factors on human cardiometabolic health. We performed a cross-sectional study with 441 community-dwelling Colombian mestizos from five cities spanning the Andes, Pacific, and Caribbean coasts. We characterized the host genetic ancestry by genotyping 40 ancestry informative markers; characterized gut microbiota through 16S rRNA gene sequencing; assessed diet intake, physical activity, cigarette, and medicament consumption; and measured cardiometabolic outcomes that allowed calculating a CMS risk scale. On average, each individual of our cohort was 67 ± 6% European, 21 ± 5% Native American and 12 ± 5% African. Multivariable-adjusted generalized linear models showed that individuals with higher Native American and African ancestries had increased fasting insulin, body mass index and CMS risk, as assessed by the CMS risk scale. Furthermore, we identified 21 OTUs associated to the host genetic ancestry and 20 to cardiometabolic health. While we highlight novel associations between genetic ancestry and gut microbiota, we found that the effect of intestinal microbes was more likely to explain the variance in CMS risk scale than the contributions of European, Native American and African genetic backgrounds.

A Social Determinant of Health May Modify Genetic Associations for Blood Pressure: Evidence From a SNP by Education Interaction in an African American Population

African Americans experience the highest burden of hypertension in the United States compared with other groups. Genetic contributions to this complex condition are now emerging in this as well as other populations through large-scale genome-wide association studies (GWAS) and meta-analyses. Despite these recent discovery efforts, relatively few large-scale studies of blood pressure have considered the joint influence of genetics and social determinants of health despite extensive evidence supporting their impact on hypertension. To identify these expected interactions, we accessed a subset of the Vanderbilt University Medical Center (VUMC) biorepository linked to de-identified electronic health records (EHRs) of adult African Americans genotyped using the Illumina Metabochip (n = 2,577). To examine potential interactions between education, a recognized social determinant of health, and genetic variants contributing to blood pressure, we used linear regression models to investigate two-way interactions for systolic and diastolic blood pressure (DBP). We identified a two-way interaction between rs6687976 and education affecting DBP (p = 0.052). Individuals homozygous for the minor allele and having less than a high school education had higher DBP compared with (1) individuals homozygous for the minor allele and high school education or greater and (2) individuals not homozygous for the minor allele and less than a high school education. To our knowledge, this is the first EHR -based study to suggest a gene-environment interaction for blood pressure in African Americans, supporting the hypothesis that genetic contributions to hypertension may be modulated by social factors.

Genetic associations of the vitamin D and antiviral pathways with natural resistance to HIV-1 infection are influenced by interpopulation variability

Vitamin D (VitD) may modulate anti-HIV-1 responses modifying the risk to acquire the HIV-1-infection. We performed a nested case-control exploratory study involving 413 individuals; HIV-1-exposed seropositives (cases) and seronegatives (HESN) (controls) from three cohorts: sexually-exposed from Colombia and Italy and parenterally-exposed from Spain. The association and interactions of 139 variants in 9 VitD pathway genes, and in 14 antiviral genes with resistance/susceptibility (R/S) to HIV-1 infection was evaluated. Associations between variants and mRNA levels were also analyzed in the Colombian samples. Variants and haplotypes in genes of VitD and antiviral pathways were associated with R/S, but specific associations were not reproduced in all cohorts. Allelic heterogeneity could explain such inconsistency since the associations found in all cohorts were consistently in the same genes: VDR and RXRA of the VitD pathway genes and in TLR2 and RNASE4. Remarkably, the multi-locus genotypes (interacting variants) observed in genes of VitD and antiviral pathways were present in most HESNs of all cohorts. Finally, HESNs carrying resistance-associated variants had higher levels of VitD in plasma, of VDR mRNA in blood cells, and of ELAFIN and defensins mRNA in the oral mucosa. In conclusion, despite allelic heterogeneity, most likely due to differences in the genetic history of the populations, the associations were locus dependent suggesting that genes of the VitD pathway might act in concert with antiviral genes modulating the resistance phenotype of the HESNs. Although these associations were significant after permutation test, only haplotype results remained statistically significant after Bonferroni test, requiring further replications in larger cohorts and functional analyzes to validate these conclusions.

Identifying Rare Variant Associations in Admixed Populations

An admixed population and its ancestral populations bear different burdens of a complex disease. The ancestral populations may have different haplotypes of deleterious alleles and thus ancestry-gene interaction can influence disease risk in the admixed population. Among admixed individuals, deleterious haplotypes and their ancestries are dependent and can provide non-redundant association information. Herein we propose a local ancestry boosted sum test (LABST) for identifying chromosomal blocks that harbor rare variants but have no ancestry switches. For such a stable ancestral block, our LABST exploits ancestry-gene interaction and the number of rare alleles therein. Under the null of no genetic association, the test statistic asymptotically follows a chi-square distribution with one degree of freedom (1-df). Our LABST properly controlled type I error rates under extensive simulations, suggesting that the asymptotic approximation was accurate for the null distribution of the test statistic. In terms of power for identifying rare variant associations, our LABST uniformly outperformed several famed methods under four important modes of disease genetics over a large range of relative risks. In conclusion, exploiting ancestry-gene interaction can boost statistical power for rare variant association mapping in admixed populations.

Evaluation of variants in IL6R, TLR3, and DC-SIGN genes associated with dengue in sampled Colombian population

INTRODUCTION

Host genetics is recognized as an influential factor for the development of dengue disease.

OBJECTIVE

This study evaluated the association of dengue with the polymorphisms rs8192284 for gene IL6R, rs3775290 for TLR3, and rs7248637 for DC-SIGN.

MATERIALS AND METHODS

Of the 292 surveyed subjects, 191 were confirmed for dengue fever and the remaining 101 were included as controls. The genotypes were resolved using polymerase chain reaction and restriction fragment length polymorphism (PCRRFLP). In an attempt to determine the risk (Odds Ratio) of suffering dengue fever, data were analyzed using chi-square for alleles and logistic regression for both genotypes and allelic combinations. Confidence intervals were set to 95% for all tests regardless of the adjustment by either self-identification or ancestry.

RESULTS

For Afro-Colombians, the allele rs8192284 C offered protection against dengue [OR=0.425,(0.204-0.887), p=0.020]. The alleles rs7248637 A and rs3775290 A posed, respectively, an increased risk of dengue for Afro-Colombians [OR=2.389, (1.170-4.879), p=0.015] and Mestizos [OR=2.329, (1.283-4.226), p=0.005]. The reproducibility for rs8192284 C/C [OR=2.45, (1.05-5.76), p=0.013] remained after adjustment by Amerindian ancestry [OR=2.52, (1.04-6.09), p=0.013]. The reproducibility for rs3775290 A/A [OR=2.48, (1.09-5.65), p=0.033] remained after adjustment by European [OR=2.34, (1.02-5.35), p=0.048], Amerindian [OR=2.49, (1.09-5.66), p=0.035], and African ancestry [OR=2.37, (1.04-5.41), p=0.046]. Finally, the association of dengue fever with the allelic combination CAG [OR=2.07, (1.06-4.05), p=0.033] remained after adjustment by Amerindian ancestry [OR=2.16, (1.09-4.28), p=0.028].

CONCLUSIONS

Polymorphisms rs8192284 for IL6R, rs3775290 for TLR3, and rs7248637 for DC-SIGN were associated with the susceptibility to suffer dengue fever in the sampled Colombian population.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

Genomic Predictors of Asthma Phenotypes and Treatment Response

Asthma is a complex respiratory disease considered as the most common chronic condition in children. A large genetic contribution to asthma susceptibility is predicted by the clustering of asthma and allergy symptoms among relatives and the large disease heritability estimated from twin studies, ranging from 55 to 90%. Genetic basis of asthma has been extensively investigated in the past 40 years using linkage analysis and candidate-gene association studies. However, the development of dense arrays for polymorphism genotyping has enabled the transition toward genome-wide association studies (GWAS), which have led the discovery of several unanticipated asthma genes in the last 11 years. Despite this, currently known risk variants identified using many thousand samples from distinct ethnicities only explain a small proportion of asthma heritability. This review examines the main findings of the last 2 years in genomic studies of asthma using GWAS and admixture mapping studies, as well as the direction of studies fostering integrative perspectives involving omics data. Additionally, we discuss the need for assessing the whole spectrum of genetic variation in association studies of asthma susceptibility, severity, and treatment response in order to further improve our knowledge of asthma genes and predictive biomarkers. Leveraging the individual's genetic information will allow a better understanding of asthma pathogenesis and will facilitate the transition toward a more precise diagnosis and treatment.

Estimating Asian Contribution to the Brazilian Population: A New Application of a Validated Set of 61 Ancestry Informative Markers

Estimates of different ancestral proportions in admixed populations are very important in population genetics studies, especially for the detection of population substructure effects in studies of case-control associations. Brazil is one of the most heterogeneous countries in the world, both from a socio-cultural and a genetic point of view. In this work, we investigated a previously developed set of 61 ancestry informative markers (AIM), aiming to estimate the proportions of four different ancestral groups (African, European, Native American and Asian) in Brazilian populations. To the best of our knowledge, this is the first study to use a set of AIM to investigate the genetic contribution of all four main parental populations to the Brazilian population, including Asian contribution. All selected markers were genotyped through multiplex PCR and capillary electrophoresis. The set was able to successfully differentiate the four ancestral populations (represented by 939 individuals) and identify their genetic contributions to the Brazilian population. In addition, it was used to estimate individual interethnic admixture of 1050 individuals from the Southeast region of Brazil and it showed that these individuals present a higher European ancestry contribution, followed by African, Asian and Native American ancestry contributions. Therefore, the 61 AIM set has proved to be a valuable tool to estimate individual and global ancestry proportions in populations mainly formed by these four groups. Our findings highlight the importance of using sets of AIM to evaluate population substructure in studies carried in admixed populations, in order to avoid misinterpretation of results.

An Analytic Approach Using Candidate Gene Selection and Logic Forest to Identify Gene by Environment Interactions (G × E) for Systemic Lupus Erythematosus in African Americans

Development and progression of many human diseases, such as systemic lupus erythematosus (SLE), are hypothesized to result from interactions between genetic and environmental factors. Current approaches to identify and evaluate interactions are limited, most often focusing on main effects and two-way interactions. While higher order interactions associated with disease are documented, they are difficult to detect since expanding the search space to all possible interactions of p predictors means evaluating 2^p − 1 terms. For example, data with 150 candidate predictors requires considering over 10⁴⁵ main effects and interactions. In this study, we present an analytical approach involving selection of candidate single nucleotide polymorphisms (SNPs) and environmental and/or clinical factors and use of Logic Forest to identify predictors of disease, including higher order interactions, followed by confirmation of the association between those predictors and interactions identified with disease outcome using logistic regression. We applied this approach to a study investigating whether smoking and/or secondhand smoke exposure interacts with candidate SNPs resulting in elevated risk of SLE. The approach identified both genetic and environmental risk factors, with evidence suggesting potential interactions between exposure to secondhand smoke as a child and genetic variation in the ITGAM gene associated with increased risk of SLE.

Local genetic ancestry in CDKN2B-AS1 is associated with primary open-angle glaucoma in an African American cohort extracted from de-identified electronic health records

BACKGROUND

Glaucoma is a leading cause of blindness in developed countries. Primary open-angle glaucoma (POAG), the most prevalent clinical subtype of glaucoma in the United States, affects African Americans at a higher rate compared with European Americans. Risk factors identified for POAG include increased age and family history, which coupled with heritability estimates, suggest this complex condition is associated with genetic and environmental factors. To date, several genome-wide studies have identified loci significantly associated with POAG risk, but most of these studies were performed in populations of European-descent.

METHODS

To identify population-specific and trans-population genetic associations for POAG, we genotyped 11,521 African Americans using the Illumina Metabochip as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessing BioVU, the Vanderbilt University Medical Center's biorepository linked to de-identified electronic health records. Among this study population, we identified 138 cases of POAG and 1376 controls and performed Metabochip-wide tests of association. We also estimated local genetic ancestry at CDKN2B-AS1, a POAG-associated locus established in European-descent populations.

RESULTS

Overall, we did not identify significant single SNP-POAG associations after adjusting for multiple testing. We did, however, detect a significant association between POAG risk and local African genetic ancestry at CDKN2B-AS1, where on average cases were of 90% African descent compared with controls at 58% (p = 2 × 10- 6).

CONCLUSIONS

These data suggest that CDKN2B-AS1 is an important locus for POAG risk among African Americans, warranting further investigation to identify the variants underlying this association.

Ideal cardiovascular health among Ghanaian populations in three European countries and rural and urban Ghana: the RODAM study

Cardiovascular health (CVH) is a construct defined by the American Heart Association (AHA) as part of its 2020 Impact Goal definition. CVH has, until now, not been evaluated in Sub-Saharan African populations. The aim of this study was to investigate differences in the prevalence of ideal CVH and its constituent metrics among Ghanaians living in rural and urban Ghana and Ghanaian migrants living in three European countries. The AHA definition of CVH is based on 7 metrics: smoking, body mass index, diet, physical activity, blood pressure, total cholesterol, and fasting plasma glucose. These were evaluated among 3510 Ghanaian adults (aged 25-70 years) residing in rural and urban Ghana and three European cities (Amsterdam, London and Berlin) in the multi-centre RODAM study. Differences between groups were assessed using logistic regression with adjustments for gender, age, and education. Only 0.3% of all participants met all 7 metrics of the AHA's definition of ideal CVH. Compared to rural Ghana (25.7%), the proportions and adjusted odds ratio (OR) of individuals who had 6-7 CVH metrics in the ideal category were substantially lower in urban Ghana, (7.5%; OR 0.204, 95% CI 0.15-0.29), Amsterdam (4.4%; 0.13, 0.08-0.19), Berlin (2.7%; 0.06, 0.03-0.11), and London (1.7%; 0.04, 0.02-0.09), respectively. The proportion of ideal CVH for the various metrics ranged from 96% for all sites in the smoking metric to below 6% in the diet metric. The proportion of ideal CVH is extremely low in Ghanaians, especially among those living in urban Ghana and Ghanaian migrants in Europe.

Application and validation of Diagnose Sexuelle Probabiliste V2 tool in a miscegenated population

The hip bone (os coxae) is the skeletal element that presents the greatest level of sexual dimorphism. Therefore, methods involving the analysis of the os coxae provide the most accurate sex estimation, and DSP2 (Diagnose Sexuelle Probabiliste v.2) is one of the most accurate tools used in this identification. The goal of this study is to apply and validate DSP2 in the identification of 103 os coxae (53 male and 50 female) belonging to a Brazilian-identified skeletal collection. Differences between sexes were statistically significant for all measurements, except for the acetabulo-symphyseal and spino-auricular lengths. From the 103 os coxae analyzed, there was a 9.43% error in male individuals and a 14% error in females. The results revealed that DSP2 can be applied to Brazilian-mixed populations with a good index of accuracy, although at a lower accuracy than other population samples. This study also clearly demonstrates that metric variation of the os coxae is extremely useful in sex estimation and reinforces the notion that pelvic sexual dimorphism is not population-specific.

Inference on admixture fractions in a mechanistic model of recurrent admixture

Signatures of recent historical admixture are ubiquitous in human populations. We present a mechanistic model of admixture with two source populations, encompassing recurrent admixture periods and study the distribution of admixture fractions for finite but arbitrary genome size. We provide simulation-based methods to estimate the introgression parameters and discuss the implications of reaching stationarity on estimability of parameters when there are recurrent admixture events with different rates.

Genetic Ancestry and Susceptibility to Late-Onset Alzheimer Disease (LOAD) in the Admixed Colombian Population

INTRODUCTION

Differences in the prevalence of dementia among populations and in the effect of apolipoprotein E (APOE) on the emergence of Alzheimer disease (AD), which is the main type of dementia, have been reported.

METHODS

This study estimated the ancestry of a group of individuals with late-onset Alzheimer disease (LOAD) (N=280) and established whether there were any differences when compared with a control group (N=357) in a sample of the Colombian population.

RESULTS

When the analyses were adjusted for known risk factors such as age, sex, presence of APOE[Latin Small Letter Open E]4, socioeconomic status, educational attainment, and place of birth, African ancestry was associated with an increased LOAD risk (odds ratio: 1.55; 95% confidence interval, 1.09-2.03; P=0.029), whereas Native American ancestry was associated with lower risk (odds ratio: 0.75; 95% confidence interval, 0.61-0.98; P=0.046), for every 10% increase in ancestry. In addition, there were significant differences in the proportion of Native American ancestry between carriers and noncarriers of the APOE[Latin Small Letter Open E]4 allele (Mann-Whitney U test, P=0.047), with noncarriers having higher mean Native American ancestry when compared with carriers.

CONCLUSIONS

Our results are consistent with the presence of variants of African origin in the genome of the Colombian population and different from APOE[Latin Small Letter Open E]4 that represents a risk factor for the development of LOAD, whereas variants of Native American origin may be conferring protection. However, unknown environmental factors or epigenetic differences among continental groups could also explain the observed associations.

A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations

Genetic association studies in admixed populations allow us to gain deeper understanding of the genetic architecture of human diseases and traits. However, population stratification, complicated linkage disequilibrium (LD) patterns, and the complex interplay of allelic and ancestry effects on phenotypic traits pose challenges in such analyses. These issues may lead to detecting spurious associations and/or result in reduced statistical power. Fortunately, if handled appropriately, these same challenges provide unique opportunities for gene mapping. To address these challenges and to take these opportunities, we propose a robust and powerful two-step testing procedure Local Ancestry Adjusted Allelic (LAAA) association. In the first step, LAAA robustly captures associations due to allelic effect, ancestry effect, and interaction effect, allowing detection of effect heterogeneity across ancestral populations. In the second step, LAAA identifies the source of association, namely allelic, ancestry, or the combination. By jointly modeling allele, local ancestry, and ancestry-specific allelic effects, LAAA is highly powerful in capturing the presence of interaction between ancestry and allele effect. We evaluated the validity and statistical power of LAAA through simulations over a broad spectrum of scenarios. We further illustrated its usefulness by application to the Candidate Gene Association Resource (CARe) African American participants for association with hemoglobin levels. We were able to replicate independent groups' previously identified loci that would have been missed in CARe without joint testing. Moreover, the loci, for which LAAA detected potential effect heterogeneity, were replicated among African Americans from the Women's Health Initiative study. LAAA is freely available at https://yunliweb.its.unc.edu/LAAA.

Tests of fit of historically-informed models of African American Admixture

OBJECTIVES

African American populations in the U.S. formed primarily by mating between Africans and Europeans over the last 500 years. To date, studies of admixture have focused on either a one-time admixture event or continuous input into the African American population from Europeans only. Our goal is to gain a better understanding of the admixture process by examining models that take into account (a) assortative mating by ancestry in the African American population, (b) continuous input from both Europeans and Africans, and (c) historically informed variation in the rate of African migration over time.

MATERIALS AND METHODS

We used a model-based clustering method to generate distributions of African ancestry in three samples comprised of 147 African Americans from two published sources. We used a log-likelihood method to examine the fit of four models to these distributions and used a log-likelihood ratio test to compare the relative fit of each model.

RESULTS

The mean ancestry estimates for our datasets of 77% African/23% European to 83% African/17% European ancestry are consistent with previous studies. We find admixture models that incorporate continuous gene flow from Europeans fit significantly better than one-time event models, and that a model involving continuous gene flow from Africans and Europeans fits better than one with continuous gene flow from Europeans only for two samples. Importantly, models that involve continuous input from Africans necessitate a higher level of gene flow from Europeans than previously reported.

DISCUSSION

We demonstrate that models that take into account information about the rate of African migration over the past 500 years fit observed patterns of African ancestry better than alternative models. Our approach will enrich our understanding of the admixture process in extant and past populations.

PRECISION MEDICINE: FROM DIPLOTYPES TO DISPARITIES TOWARDS IMPROVED HEALTH AND THERAPIES

Precision medicine research efforts both in basic science discovery and clinical implementation are well underway and promise to provide individualized preventions and treatments, improving overall health care delivery. To achieve these goals, advances in data capture and analysis are needed spanning different types of 'omic and clinical data. The efforts to enhance precise treatments for all may accentuate healthcare disparities unless specific challenges are identified and addressed. This session of the 2018 Pacific Symposium on Biocomputing presents the latest developments in this transdisciplinary research space of genomics, medicine, and population health.