The need to diversify genomic studies: Insights from Andean highlanders and Amazonians.

More globally diverse perspectives are needed in genomic studies and precision medicine practices on non-Europeans. Here, we illustrate this by discussing the distribution of clinically actionable genetic variants involved in drug response in Andean highlanders and Amazonians, considering their environment, history, genetic structure, and historical biases in the perception of biological diversity of Native Americans.

Survival disparities in non-Hispanic Black and White cervical cancer patients vary by histology and are largely explained by modifiable factors.

PURPOSE: We investigated racial disparities in survival by histology in cervical cancer and examined the factors contributing to these disparities. METHODS: Non-Hispanic Black and non-Hispanic White (hereafter known as Black and White) patients with stage I-IV cervical carcinoma diagnosed between 2004 and 2017 in the National Cancer Database were studied. Survival differences were compared using Cox modeling to estimate hazard ratio (HR) or adjusted HR (AHR) and 95% confidence interval (CI). The contribution of demographic, socioeconomic and clinical factors to the Black vs White differences in survival was estimated after applying propensity score weighting in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC). RESULTS: This study included 10,111 Black and 43,252 White patients with cervical cancer. Black patients had worse survival than White cervical cancer patients (HR = 1.40, 95% CI = 1.35-1.45). Survival disparities between Black and White patients varied significantly by histology (HR = 1.20, 95% CI = 1.15-1.24 for SCC; HR = 2.32, 95% CI = 2.12-2.54 for AC, interaction p < 0.0001). After balancing the selected demographic, socioeconomic and clinical factors, survival in Black vs. White patients was no longer different in those with SCC (AHR = 1.01, 95% CI 0.97-1.06) or AC (AHR = 1.09, 95% CI = 0.96-1.24). In SCC, the largest contributors to survival disparities were neighborhood income and insurance. In AC, age was the most significant contributor followed by neighborhood income, insurance, and stage. Diagnosis of AC (but not SCC) at ≥65 years old was more common in Black vs. White patients (26% vs. 13%, respectively). CONCLUSIONS: Histology matters in survival disparities and diagnosis at ≥65 years old between Black and White cervical cancer patients. These disparities were largely explained by modifiable factors.

Racial, ethnic and country of origin disparities in aggressive endometrial cancer histologic subtypes.

OBJECTIVE: This study investigated the risk of an aggressive endometrial cancer (EC) diagnosis by race, ethnicity, and country of origin to further elucidate histologic disparities in non-Hispanic Black (NHB), Hispanic, Asian/Pacific Islander (API), American Indian/Alaskan Native (AIAN) vs. non-Hispanic White (NHW) patients, particularly in Hispanic or API subgroups. METHODS: Patient diagnosed between 2004 and 2020 with low grade (LG)-endometrioid endometrial cancer (ECC) or an aggressive EC including grade 3 EEC, serous carcinoma, clear cell carcinoma, mixed epithelial carcinoma, or carcinosarcoma in the National Cancer Database were studied. The odds ratio (OR) and 95% confidence interval (CI) for diagnosis of an aggressive EC histology was estimated using logistic modeling. RESULTS: There were 343,868 NHW, 48,897 NHB, 30,013 Hispanic, 15,015 API and 1646 AIAN patients. The OR (95% CI) for an aggressive EC diagnosis was 3.07 (3.01-3.13) for NHB, 1.08 (1.06-1.11) for Hispanic, 1.17 (1.13-1.21) for API and 1.07 (0.96-1.19) for AIAN, relative to NHW patients. Subset analyses by country of origin illustrated the diversity in the OR for an aggressive EC diagnosis among Hispanic (1.18 for Mexican to 1.87 for Dominican), Asian (1.14 Asian Indian-Pakistani to 1.48 Korean) and Pacific Islander (1.00 for Hawaiian to 1.33 for Samoan) descendants. Hispanic, API and AIAN patients were diagnosed 5-years younger that NHW patients, and the risk for an aggressive EC histology were all significantly higher than NHW patients after correcting for age. Insurance status was another independent risk factor for aggressive histology. CONCLUSIONS: Risk of an aggressive EC diagnosis varied by race, ethnicity, and country of origin. NHB patients had the highest risk, followed by Dominican, South/Central American, Cuban, Korean, Thai, Vietnamese, and Filipino descendants.

Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in High-Recombining Plasmodium falciparum Genomes.

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is increasingly being used in Plasmodium population genomics to estimate genetic relatedness, effective population size (N e ), population structure, and signals of positive selection. Despite its potential, a thorough evaluation of IBD segment detection tools for species with high recombination rates, such as P. falciparum, remains absent. Here, we perform comprehensive benchmarking of IBD callers - probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD) - using population genetic simulations tailored for high recombination, and IBD quality metrics at both the IBD segment level and the IBD-based downstream inference level. Our results demonstrate that low marker density per genetic unit, related to high recombination relative to mutation, significantly compromises the accuracy of detected IBD segments. In genomes with high recombination rates resembling P. falciparum, most IBD callers exhibit high false negative rates for shorter IBD segments, which can be partially mitigated through optimization of IBD caller parameters, especially those related to marker density. Notably, IBD detected with optimized parameters allows for more accurate capture of selection signals and population structure; IBD-based N e inference is very sensitive to IBD detection errors, with IBD called from hmmIBD uniquely providing less biased estimates of N e in this context. Validation with empirical data from the MalariaGEN Pf 7 database, representing different transmission settings, corroborates these findings. We conclude that context-specific evaluation and parameter optimization are essential for accurate IBD detection in high-recombining species and recommend hmmIBD for quality-sensitive analysis, such as estimation of N e in these species. Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.

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 .

Variation in spatial population structure in the Anopheles gambiae species complex.

Anopheles gambiae, Anopheles coluzzii , and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of these closely related species, including the extent to which populations are connected by gene flow, is essential for understanding how vector control implemented in one location might indirectly affect vector populations in other locations. Here, we assessed the population structure of each species based on whole-genome sequences from the third phase of the Anopheles gambiae 1000 Genomes Project. The data set included single nucleotide polymorphisms from whole genomes of 2,242 individual mosquitoes sampled from 119 locations across 19 African countries. We found that A. gambiae sampled from several countries in West and Central Africa showed low genetic differentiation from each other according to principal components analysis (PCA) and ADMIXTURE modeling. Using Estimated Effective Migration Surfaces (EEMS), we showed that this low genetic differentiation indicates high effective migration rates for A. gambiae across this region. Outside of this region, we found six groups of sampling locations from Central, East, and Southern Africa for which A. gambiae showed higher genetic differentiation, and lower effective migration rates, between each other and the West/Central Africa group. These results indicate that the barriers to and corridors for migration between populations of A. gambiae differ across the geographical range of this malaria vector species. Using the same methods, we found higher genetic differentiation and lower migration rates between populations of A. coluzzii in West and Central Africa than for A. gambiae in the same region. On the other hand, we found lower genetic differentiation and higher migration rates between populations of A. arabiensis in Tanzania, compared to A. gambiae in the same region. These differences between A. gambiae, A. coluzzii , and A. arabiensis indicate that migration barriers and corridors may vary between species, even for very closely related species. Overall, our results demonstrate that migration rates vary both between and within species of Anopheles mosquitoes, presumably based on species-specific responses to the ecological or environmental conditions that may impede or facilitate migration, and the geographical patterns of these conditions across the landscape. Together with previous findings, this study provides robust evidence that migration rates between populations of malaria vectors depend on the ecological context, which should be considered when planning surveillance of vector populations, monitoring for insecticide resistance, and evaluating interventions.

Comparing the effect of imputation reference panel composition in four distinct Latin American cohorts.

Genome-wide association studies have been useful in identifying genetic risk factors for various phenotypes. These studies rely on imputation and many existing panels are largely composed of individuals of European ancestry, resulting in lower levels of imputation quality in underrepresented populations. We aim to analyze how the composition of imputation reference panels affects imputation quality in four target Latin American cohorts. We compared imputation quality for chromosomes 7 and X when altering the imputation reference panel by: 1) increasing the number of Latin American individuals; 2) excluding either Latin American, African, or European individuals, or 3) increasing the Indigenous American (IA) admixture proportions of included Latin Americans. We found that increasing the number of Latin Americans in the reference panel improved imputation quality in the four populations; however, there were differences between chromosomes 7 and X in some cohorts. Excluding Latin Americans from analysis resulted in worse imputation quality in every cohort, while differential effects were seen when excluding Europeans and Africans between and within cohorts and between chromosomes 7 and X. Finally, increasing IA-like admixture proportions in the reference panel increased imputation quality at different levels in different populations. The difference in results between populations and chromosomes suggests that existing and future reference panels containing Latin American individuals are likely to perform differently in different Latin American populations.

Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum.

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.