African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping

Associations of ethnicity, skin tone, and genome-wide sequencing with bone mineral density in adolescents

BACKGROUND

Dual-energy x-ray absorptiometry reference data designate Black and non-Black categories, as higher BMD has been documented among Black youth. We examined associations of race, skin tone, and genetic factors with bone mineral density (BMD).

METHODS

557 adolescents were followed longitudinally. Exposures included race, skin tone, and principal components (PC) from genome-wide arrays. Total body BMD Z-score (BMD-Z) was the primary outcome using linear regression.

RESULTS

359 adolescents identified as non-Hispanic White (NHW) and 75, non-Hispanic Black (NHB). BMD-Z was higher in NHB vs. NHW (β: 0.92 units, 95% CI: 0.64, 1.19) or those with darker skin (0.79, 95% CI: 0.49, 1.08 for brown vs. medium). The first genetic PC (PC1) correlated with identification as NHB. PC1 was associated with higher BMD-Z (0.09, 95% CI: 0.06, 0.12), even after including race (0.07, 95% CI: 0.00, 0.14) or skin tone (0.10, 95% CI: 0.05, 0.15); both race (0.26, 95% CI: -0.49, 1.01 for NHB vs. NHW) and skin tone (-0.08, 95% CI: -0.59, 0.44 for brown vs. medium) no longer predicted BMD-Z after adjustment for PC1.

CONCLUSION

Genetic similarity was robustly associated with BMD, prompting a reevaluation of adolescent BMD reference data to exclude the consideration of race.

IMPACT

Current bone density reference databases include a binary assignment of patients into "Black" and "non-Black" categories, as a higher BMD has been documented among those identifying as Black compared with individuals of other racial and ethnic backgrounds. This study found genetic similarity to be more strongly associated with bone density by dual-energy x-ray absorptiometry than race or skin tone. These data emphasize a need to reevaluate how bone density measurements are interpreted, including exploring reference data that exclude the consideration of race.

MHConstructor: a high-throughput, haplotype-informed solution to the MHC assembly challenge

The extremely high levels of genetic polymorphism within the human major histocompatibility complex (MHC) limit the usefulness of reference-based alignment methods for sequence assembly. We incorporate a short-read, de novo assembly algorithm into a workflow for novel application to the MHC. MHConstructor is a containerized pipeline designed for high-throughput, haplotype-informed, reproducible assembly of both whole genome sequencing and target capture short-read data in large, population cohorts. To-date, no other self-contained tool exists for the generation of de novo MHC assemblies from short-read data. MHConstructor facilitates wide-spread access to high-quality, alignment-free MHC sequence analysis.

Heterogeneity-aware integrative regression for ancestry-specific association studies

Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral groups. These studies require ancestry-specific models for protein expression as a function of SNP genotypes. In order to improve protein expression prediction in ancestral populations historically underrepresented in genomic studies, we propose a new penalized maximum likelihood estimator for fitting ancestry-specific joint protein quantitative trait loci models. Our estimator borrows information across ancestral groups, while simultaneously allowing for heterogeneous error variances and regression coefficients. We propose an alternative parameterization of our model that makes the objective function convex and the penalty scale invariant. To improve computational efficiency, we propose an approximate version of our method and study its theoretical properties. Our method provides a substantial improvement in protein expression prediction accuracy in individuals of African ancestry, and in a downstream PWAS analysis, leads to the discovery of multiple associations between protein expression and blood lipid traits in the African ancestry population.

Genetic etiology of autism spectrum disorder in the African population: a scoping review

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) characterized by significant impairments in social, communicative, and behavioral abilities. However, only a limited number of studies address the genetic basis of ASD in the African population. This study aims to document the genes associated with ASD in Africa and the techniques used to identify them. Additionally, genes identified elsewhere but not yet in Africa are also noted.

Methods

Online databases such as Wiley Online Library, PubMed, and Africa Journal Online were used. The review was conducted using the keyword related to genetic and genomic ASD study in the African population.

Result

In this scoping review, 40 genetic studies on ASD in Africa were reviewed. The Egyptian and South African populations were the most studied, with 25 and 5 studies, respectively. Countries with fewer studies included Tunisia (4), East African countries (3), Libya (1), Nigeria (1), and Morocco (1). Some 61 genes responsible for ASD were identified in the African population: 26 were identified using a polymerase chain reaction (PCR)-based method, 22 were identified using sequencing technologies, and 12 genes and one de novo chromosomal aberration were identified through other techniques. No African study identified any ASD gene with genome-wide association studies (GWAS). Notably, at least 20 ASD risk genes reported in non-African countries were yet to be confirmed in Africa's population.

Conclusion

There are insufficient genetic studies on ASD in the African population, with sample size being a major limitation in most genetic association studies, leading to inconclusive results. Thus, there is a need to conduct more studies with large sample sizes to identify other genes associated with ASD in Africa's population using high-throughput sequencing technology.

High Resolution Class I HLA -A, -B, and -C Diversity in Eastern and Southern African Populations

Africa remains significantly underrepresented in high-resolution Human Leukocyte Antigen (HLA) data, despite being one of the most genetically diverse regions in the world. This critical gap in genetic information poses a substantial barrier to HLA-based research on the continent. In this study, Class I HLA data from Eastern and Southern African populations were analysed to assess genetic diversity across the region. We examined allele and haplotype frequency distributions, deviations from Hardy-Weinberg Equilibrium (HWE), linkage disequilibrium (LD), and conducted neutrality tests of homozygosity across various populations. Additionally, the African HLA data were compared to those of Caucasian and African American populations using the Jaccard index and multidimensional scaling (MDS) methods. The study revealed that South African populations exhibited 50.4% more genetic diversity within the Class I HLA region compared to other African populations. Zambia showed an estimated 36.5% genetic diversity, with Kenya, Rwanda and Uganda showing 35.7%, 34.2%, and 31.1%, respectively. Furthermore, an analysis of in-country diversity among different tribes indicated an average Class I HLA diversity of 25.7% in Kenya, 17% in Rwanda, 2.8% in South Africa, 13.6% in Uganda, and 6.5% in Zambia. The study also highlighted the genetic distinctness of Caucasian and African American populations compared to African populations. Notably, the differential frequencies of disease-promoting and disease-preventing HLA alleles across these populations emphasize the urgent need to generate high-quality HLA data for all regions of Africa and its major ethnic groups. Such efforts will be crucial in enhancing healthcare outcomes across the continent.

Collecting and reporting adverse events in low-income settings-perspectives from vaccine trials in the Gambia

BACKGROUND

Despite Africa's significant infectious disease burden, it is underrepresented in global vaccine clinical trials. While this trend is slowly reversing, it is important to recognize and mitigate the challenges that arise when conducting vaccine clinical trials in this environment. These challenges stem from a variety of factors peculiar to the population and may negatively impact adverse event collection and reporting if not properly addressed.

METHODS

As a team of clinical researchers working within the MRCG (Medical Research Council Unit The Gambia), we have conducted 12 phase 1 to 3 vaccine trials over the past 10 years. In this article, we discuss the challenges we face and the strategies we have developed to improve the collection and reporting of adverse events in low-income settings.

OUTCOME

Healthcare-seeking behaviors in the Gambia are influenced by spiritual and cultural beliefs as well as barriers to accessing orthodox healthcare; participants in trials may resort to non-orthodox care, reducing the accuracy of reported adverse events. To address this, trial eligibility criteria prohibit self-treatment and herbal product use during trials. Instead, round-the-clock care is provided to trial participants, facilitating safety follow-up. Constraints in the healthcare system in the Gambia such as limitations in diagnostic tools limit the specificity of diagnosis when reporting adverse events. To overcome these challenges, the Medical Research Council Unit maintains a Clinical Services Department, offering medical care and diagnostic services to study participants. Sociocultural factors, including low literacy rates and social influences, impact adverse event collection. Solicited adverse events are collected during home visits on paper-based or electronic report forms. Community engagement meetings are held before each study starts to inform community stakeholders about the study and answer any questions they may have. These meetings ensure that influential members of the community understand the purpose of the study and the risks and benefits of participating in the trial. This understanding makes them more likely to support participation within their communities.

CONCLUSION

Conducting ethical vaccine clinical trials in resource-limited settings requires strategies to accurately collect and report adverse events. Our experiences from the Gambia offer insights into adverse event collection in these settings.

Prevalence and Reclassification of Genetic Variants in South African Populations with Breast Cancer

Concurrent testing of numerous genes for hereditary breast cancer (BC) is available but can result in management difficulties. We evaluated use of an expanded BC gene panel in women of diverse South African ancestries and assessed use of African genomic data to reclassify variants of uncertain significance (VUS). A total of 331 women of White, Black African, or Mixed Ancestry with BC had a 9-gene panel test, with an additional 75 genes tested in those without a pathogenic/likely pathogenic (P/LP) variant. The proportion of VUS reclassified using ClinGen gene-specific allele frequency (AF) thresholds or an AF > 0.001 in nonguidelines genes in African genomic data was determined. The 9-gene panel identified 58 P/LP variants, but only two of the P/LP variants detected using the 75-gene panel were in confirmed BC genes, resulting in a total of 60 (18.1%) in all participants. P/LP variant prevalence was similar across ancestry groups, but VUS prevalence was higher in Black African and Mixed Ancestry than in White participants. In total, 611 VUS were detected, representing 324 distinct variants. 10.8% (9/83) of VUS met ClinGen AF thresholds in genomic data while 10.8% (26/240) in nonguideline genes had an AF > 0.001. Overall, 27.0% of VUS occurrences could potentially be reclassified using African genomic data. Thus, expanding the gene panel yielded few clinically actionable variants but many VUS, particularly in participants of Black African and Mixed Ancestry. However, use of African genomic data has the potential to reclassify a significant proportion of VUS.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Insights into pharmacogenetics, drug-gene interactions, and drug-drug-gene interactions

This review explores genetic contributors to drug interactions, known as drug-gene and drug-drug-gene interactions (DGI and DDGI, respectively). This article is part of a mini-review issue led by the International Society for the Study of Xenobiotics (ISSX) New Investigators Group. Pharmacogenetics (PGx) is the study of the impact of genetic variation on pharmacokinetics (PK), pharmacodynamics (PD), and adverse drug reactions. Genetic variation in pharmacogenes, including drug metabolizing enzymes and drug transporters, is common and can increase the risk of adverse drug events or contribute to reduced efficacy. In this review, we summarize clinically actionable genetic variants, and touch on methodologies such as genotyping patient DNA to identify genetic variation in targeted genes, and deep mutational scanning as a high-throughput in vitro approach to study the impact of genetic variation on protein function and/or expression in vitro. We highlight the utility of physiologically based pharmacokinetic (PBPK) models to integrate genetic and chemical inhibitor and inducer data for more accurate human PK simulations. Additionally, we analyze the limitations of historical ethnic descriptors in pharmacogenomics research. Altogether, the work herein underscores the importance of identifying and understanding complex DGI and DDGIs with the intention to provide better treatment outcomes for patients. We also highlight current barriers to wide-scale implementation of PGx-guided dosing as standard or care in clinical settings.

Addressing the research gap: access to care hinders genetic discovery in systemic lupus erythematosus patients throughout the African diaspora

Systemic lupus erythematosus (SLE) is a complex autoimmune condition that disproportionately impacts non-White ethnic and racial groups, particularly individuals in the African diaspora who experience heightened incidence, prevalence, and adverse outcomes. Genetic and epigenetic factors play significant roles in SLE risk, however these factors neither explain the whole of SLE risk nor the stark racial disparities we observe. Moreover, our understanding of genetic risk factors within African ancestry populations is limited due to social and environmental influences on research participation, disease presentation, and healthcare access. Globally, the African diaspora faces barriers in accessing essential SLE diagnostic tools, therapeutics, healthcare practitioners, and high-quality clinical and translational research studies. Here, we provide insights into the current state of genetic studies within African ancestry populations and highlight the unique challenges encountered in SLE care and research across countries of varying income levels. We also identify opportunities to address these disparities and promote scientific equity for individuals affected by SLE within the global African diaspora.

Mapping Epigenetic Gene Variant Dynamics: Comparative Analysis of Frequency, Functional Impact and Trait Associations in African and European Populations

Epigenetic modifications influence gene expression levels, impact organismal traits, and play a role in the development of diseases. Therefore, variants in genes involved in epigenetic processes are likely to be important in disease susceptibility, and the frequency of variants may vary between populations with African and European ancestries. Here, we analyse an integrated dataset to define the frequencies, associated traits, and functional impact of epigenetic gene variants among individuals of African and European ancestry represented in the UK Biobank. We find that the frequencies of 88.4% of epigenetic gene variants significantly differ between these groups. Furthermore, we find that the variants are associated with many traits and diseases, and some of these associations may be population-specific owing to allele frequency differences. Additionally, we observe that variants associated with traits are significantly enriched for quantitative trait loci that affect DNA methylation, chromatin accessibility, and gene expression. We find that methylation quantitative trait loci account for 71.2% of the variants influencing gene expression. Moreover, variants linked to biomarker traits exhibit high correlation. We therefore conclude that epigenetic gene variants associated with traits tend to differ in their allele frequencies among African and European populations and are enriched for QTLs.

Genetic variation present in the CYP3A4 gene in Ni-Vanuatu and Kenyan populations in malaria endemicity

Cytochrome P450 3A4 (CYP3A4) enzyme is involved in the metabolism of about 30 % of clinically used drugs, including the antimalarials artemether and lumefantrine. CYP3A4 polymorphisms yield enzymatic variants that contribute to inter-individual variation in drug metabolism. Here, we examined CYP3A4 polymorphisms in populations from malaria-endemic islands in Lake Victoria, Kenya, and Vanuatu, to expand on the limited data sets. We used archived dried blood spots collected from 142 Kenyan and 263 ni-Vanuatu adults during cross-sectional malaria surveys in 2013 and 2005-13, respectively, to detect CYP3A4 variation by polymerase chain reaction (PCR) and sequencing. In Kenya, we identified 14 CYP3A4 single nucleotide polymorphisms (SNPs), including the 4713G (CYP3A4∗1B; allele frequency 83.9 %) and 19382A (CYP3A4∗15; 0.7 %) variants that were previously linked to altered metabolism of antimalarials. In Vanuatu, we detected 15 SNPs, including the 4713A (CYP3A4∗1A; 88.6 %) and 25183C (CYP3A4∗18; 0.6 %) variants. Additionally, we detected a rare and novel SNP C4614T (0.8 %) in the 5' untranslated region. A higher proportion of CYP3A4 genetic variance was found among ni-Vanuatu populations (16 %) than among Lake Victoria Kenyan populations (8 %). Our work augments the scarce data sets and contributes to improved precision medicine approaches, particularly to anti-malarial chemotherapy, in East African and Pacific Islander populations.

The Value Proposition of Coordinated Population Cohorts Across Africa

Building longitudinal population cohorts in Africa for coordinated research and surveillance can influence the setting of national health priorities, lead to the introduction of appropriate interventions, and provide evidence for targeted treatment, leading to better health across the continent. However, compared to cohorts from the global north, longitudinal continental African population cohorts remain scarce, are relatively small in size, and lack data complexity. As infections and noncommunicable diseases disproportionately affect Africa's approximately 1.4 billion inhabitants, African cohorts present a unique opportunity for research and surveillance. High genetic diversity in African populations and multiomic research studies, together with detailed phenotyping and clinical profiling, will be a treasure trove for discovery. The outcomes, including novel drug targets, biological pathways for disease, and gene-environment interactions, will boost precision medicine approaches, not only in Africa but across the globe.

Nutrition, Other Environmental Influences, and Genetics in the Determination of Human Stature

Linear growth during three distinct stages of life determines attained stature in adulthood: namely, in utero, early postnatal life, and puberty and the adolescent period. Individual host factors, genetics, and the environment, including nutrition, influence attained human stature. Each period of physical growth has its specific biological and environmental considerations. Recent epidemiologic investigations reveal a strong influence of prenatal factors on linear size at birth that in turn influence the postnatal growth trajectory. Although average population height changes have been documented in high-income regions, stature as a complex human trait is not well understood or easily modified. This review summarizes the biology of linear growth and its major drivers, including nutrition from a life-course perspective, the genetics of programmed growth patterns or height, and gene-environment interactions that determine human stature in toto over the life span. Implications for public health interventions and knowledge gaps are discussed.

Assessing the lack of diversity in genetics research across neurodegenerative diseases: A systematic review of the GWAS Catalog and literature

The under-representation of non-European cohorts in neurodegenerative disease genome-wide association studies (GWAS) hampers precision medicine efforts. Despite the inherent genetic and phenotypic diversity in these diseases, GWAS research consistently exhibits a disproportionate emphasis on participants of European ancestry. This study reviews GWAS up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. We conducted a systematic review of GWAS results and publications up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. Rigorous article inclusion and quality assessment methods were employed. Of 123 neurodegenerative disease (NDD) GWAS reviewed, 82% predominantly featured European ancestry participants. A single European study identified over 90 risk loci, compared to a total of 50 novel loci in identified in all non-European or multi-ancestry studies. Notably, only six of the loci have been replicated. The significant under-representation of non-European ancestries in NDD GWAS hinders comprehensive genetic understanding. Prioritizing genomic diversity in future research is crucial for advancing NDD therapies and understanding. HIGHLIGHTS: Eighty-two percent of neurodegenerative genome-wide association studies (GWAS) focus on Europeans. Only 6 of 50 novel neurodegenerative disease (NDD) genetic loci have been replicated. Lack of diversity significantly hampers understanding of NDDs. Increasing diversity in NDD genetic research is urgently required. New initiatives are aiming to enhance diversity in NDD research.

Structural polymorphism and diversity of human segmental duplications

Segmental duplications (SDs) contribute significantly to human disease, evolution, and diversity yet have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies where the majority of SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms, we identify 173.2 Mbp of duplicated sequence (47.4 Mbp not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy number when compared to non-African samples. A comparison to a resource of 563 million full-length Iso-Seq reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.

Characterizing genetic profiles for high triglyceride levels in U.S. patients of African ancestry

Hypertriglyceridemia (HTG) is a common cardiovascular risk factor characterized by elevated triglyceride (TG) levels. Researchers have assessed the genetic factors that influence HTG in studies focused predominantly on individuals of European ancestry. However, relatively little is known about the contribution of genetic variation of HTG in people of African ancestry (AA), potentially constraining research and treatment opportunities. Our objective was to characterize genetic profiles among individuals of AA with mild-to-moderate HTG and severe HTG versus those with normal TGs by leveraging whole-genome sequencing data and longitudinal electronic health records available in the All of Us program. We compared the enrichment of functional variants within five canonical TG metabolism genes, an AA-specific polygenic risk score for TGs, and frequencies of 145 known potentially causal TG variants between HTG patients and normal TG among a cohort of AA patients (N = 15,373). Those with mild-to-moderate HTG (N = 342) and severe HTG (N ≤ 20) were more likely to carry APOA5 p.S19W (odds ratio = 1.94, 95% confidence interval = [1.48-2.54], P = 1.63 × 10-6 and OR = 3.65, 95% confidence interval: [1.22-10.93], P = 0.02, respectively) than those with normal TG. They were also more likely to have an elevated (top 10%) polygenic risk score, elevated carriage of potentially causal variant alleles, and carry any genetic risk factor. Alternative definitions of HTG yielded comparable results. In conclusion, individuals of AA with HTG were enriched for genetic risk factors compared to individuals with normal TGs.

MHConstructor: A high-throughput, haplotype-informed solution to the MHC assembly challenge

The extremely high levels of genetic polymorphism within the human major histocompatibility complex (MHC) limit the usefulness of reference-based alignment methods for sequence assembly. We incorporate a short read de novo assembly algorithm into a workflow for novel application to the MHC. MHConstructor is a containerized pipeline designed for high-throughput, haplotype-informed, reproducible assembly of both whole genome sequencing and target-capture short read data in large, population cohorts. To-date, no other self-contained tool exists for the generation of de novo MHC assemblies from short read data. MHConstructor facilitates wide-spread access to high quality, alignment-free MHC sequence analysis.

Characterizing genetic profiles for high triglyceride levels in U.S. patients of African ancestry

Hypertriglyceridemia (HTG) is a common cardiovascular risk factor characterized by elevated circulating triglyceride (TG) levels. Researchers have assessed the genetic factors that influence HTG in studies focused predominantly on individuals of European ancestry (EA). However, relatively little is known about the contribution of genetic variation to HTG in people of AA, potentially constraining research and treatment opportunities; the lipid profile for African ancestry (AA) populations differs from that of EA populations-which may be partially attributable to genetics. Our objective was to characterize genetic profiles among individuals of AA with mild-to-moderate HTG and severe HTG versus those with normal TGs by leveraging whole genome sequencing (WGS) data and longitudinal electronic health records (EHRs) available in the All of Us (AoU) program. We compared the enrichment of functional variants within five canonical TG metabolism genes, an AA-specific polygenic risk score for TGs, and frequencies of 145 known potentially causal TG variants between patients with HTG and normal TG among a cohort of AA patients (N=15,373). Those with mild-to-moderate HTG (N=342) and severe HTG (N≤20) were more likely to carry APOA5 p.S19W (OR=1.94, 95% CI [1.48-2.54], p=1.63×10 -6 and OR=3.65, 95% CI [1.22-10.93], p=0.02, respectively) than those with normal TG. They were also more likely to have an elevated (top 10%) PRS, elevated carriage of potentially causal variant alleles, and carry any genetic risk factor. Alternative definitions of HTG yielded comparable results. In conclusion, individuals of AA with HTG were enriched for genetic risk factors compared to individuals with normal TGs.

Characterizing substructure via mixture modeling in large-scale genetic summary statistics

Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.

The New Creatinine-Based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021 Equation: Potential Impact on Screening for Chronic Kidney Disease in an Asymptomatic Black African Population

BACKGROUND

In 2021, a new Chronic Kidney Disease Epidemiology (CKD-EPI) Collaboration equation was introduced that excluded race correction. We set out to compare estimated glomerular filtration rate (eGFR) determined using the creatinine-based CKD-EPI 2009 and 2021 equations and the reclassification of chronic kidney disease (CKD) eGFR staging to explore the potential ramifications of adopting the 2021 equation on reported eGFR and CKD staging.

METHODS

We analyzed secondary data previously utilized to determine reference intervals among Black African individuals residing in urban towns in Kenya. Serum creatinine was measured using a standardized modified Jaffé kinetic method on a Beckman AU5800 analyzer. Glomerular filtration rate (GFR) was estimated using both the 2009 and 2021 CKD-EPI creatinine equations. Classification of CKD based on eGFR was performed using the Kidney Disease: Improving Global Outcomes (KDIGO) practice guidelines.

RESULTS

Using 533 study samples, the median eGFR was highest when determined using the race-corrected CKD-EPI 2009 equation. The CKD-EPI 2021 equation yielded a median eGFR that was similar to the non-race-corrected CKD-EPI 2009 equation. The race-corrected CKD-EPI 2009 equation classified 93.6% of participants into CKD stage G1 compared with 85.6% by the CKD-EPI 2021 equation. The CKD-EPI 2021 equation classified 14.3% of participants into CKD stage G2 compared to 6.4% by the race-corrected CKD-EPI 2009 equation.

CONCLUSIONS

The CKD-EPI 2021 equation gave a comparable eGFR to the non-race-corrected CKD-EPI 2009 equation and its implementation in laboratories reporting eGFR in Kenya will help in identifying patients with an appropriate decrease in renal function.

The risk of breast cancer and gynecologic malignancies after ovarian stimulation: Meta-analysis of cohort study

The effects of ovarian stimulation on breast and gynecological tumor incidence remain controversial. Therefore, the aim of this meta-analysis was to study the risk of cancer in ovarian stimulation. Of the 22713 studies initially identified, 28 were eligible for inclusion. The results revealed that the impact of ovarian cancer (RR = 1.33, [1.05; 1.69]) and cervical cancer (RR = 0.67, [0.46; 0.97]) is significant among the overall effects. In subgroup analysis, in the nulliparous population (RR = 0.81 [0.68; 0.96]) was the protective factor for the breast cancer. In the Caucasians subgroup (RR = 1.45, [1.12; 1.88]), the ovarian cancer incidence was statistically significant. In the Asian subgroup (RR = 1.51, [1.00; 2.28]), the endometrial cancer incidence was statistically significant. In the subgroup of Asians (RR = 0.55 [0.44; 0.68]) and the multiparous population (RR = 0.31, [0.21; 0.46]), them can be the statistically protective factor for the cervical cancer.

Investigation of the interaction between genetic risk score (GRS) and fatty acid quality indices on metabolic syndrome among overweight and obese women

BACKGROUND AND AIM

Metabolic syndrome is one of the major public-health challenges, affecting one-quarter of the world population. Fatty acid quality indices are novel determinants of this disease and their interactions with genetic factors may have an impact on metabolic syndrome risk. Therefore, we aimed to investigate the interaction between genetic risk score (GRS) and fatty acid quality indices with metabolic syndrome (MetS) among overweight and obese women.

METHODS

In the present cross-sectional study, 279 overweight and obese women (18-48 years old) were included. Several anthropometric measurements such as weight, height, body mass index (BMI), waist circumference (WC), and body fat percent (BF%) were measured. Also, systolic and diastolic blood pressure (SBP and DBP) were measured. Biochemical determination was performed for fasting blood glucose (FBS), triglyceride (TG), and high-density lipoprotein (HDL). MetS was determined according to National Cholesterol Education Program (NCEP ATP III) criteria. Dietary intake was evaluated by a validated and reliable 147-item semi-quantitative food frequency questionnaire. Cholesterol-saturated fat index (CSI) and the ratio of omega-6/omega-3 (ω-6/ω-3) essential fatty acids were considered as fat quality indices. The salting-out method was used to extract the total DNA. The unweighted GRS was calculated using the risk alleles of the three single nucleotide polymorphisms. The total average GRS value was 2 and the sum of the risk alleles of the 3 polymorphisms was 6.

RESULT

The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was a positive interaction between T2 of GRS and T2 of N6/N3 ratio on WC (β = 7.95, 95%CI = 0.83,15.08, P = 0.029), T3 of GRS and T2 of N6/N3 ratio on DBP (β = 5.93, 95%CI= -0.76,12.63, P = 0.083), and FBS (β = 6.47, 95%CI = 0.59,13.53, P = 0.073), T3 of GRS and T3 of N6/N3 ratio on TG (β = 54.42, 95%CI = 1.76,107.08, P = 0.043), and T3 of GRS and T3 of CSI on BF% (β = 3.55, 95%CI= -0.35,7.45, P = 0.075). Also T2 of GRS in the interaction with T3 of CSI leads to an decrease - 8.35 mg/dl in HDL level after adjustment in (β= -8.35, 95%CI= -17.34,0.62, P = 0.068).

CONCLUSION

It seems the interaction of GRS and fatty acid quality indices is positively associated with several components of metabolic syndrome such as WC, TG and BF%. Our findings are of importance to public health, considering the high consumption of foods that are high on fatty acids. Conflicting evidence of many previous studies regarding the effect of fat intake and obesity and cardiovascular diseases could be because of the gene-diet interactions and genetic heterogeneity across various ethnic groups. Hence, the synergism effect of genetic and dietay intakes should be considered in future studies.

Demographic bias in misdiagnosis by computational pathology models

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas. For example, when using common modeling approaches, we observed performance gaps (in area under the receiver operating characteristic curve) between white and Black patients of 3.0% for breast cancer subtyping, 10.9% for lung cancer subtyping and 16.0% for IDH1 mutation prediction in gliomas. We found that richer feature representations obtained from self-supervised vision foundation models reduce performance variations between groups. These representations provide improvements upon weaker models even when those weaker models are combined with state-of-the-art bias mitigation strategies and modeling choices. Nevertheless, self-supervised vision foundation models do not fully eliminate these discrepancies, highlighting the continuing need for bias mitigation efforts in computational pathology. Finally, we demonstrate that our results extend to other demographic factors beyond patient race. Given these findings, we encourage regulatory and policy agencies to integrate demographic-stratified evaluation into their assessment guidelines.

Polymorphisms in Immune Genes and Their Association with Tuberculosis Susceptibility: An Analysis of the African Population

Tuberculosis remains a global health concern, with substantial mortality rates worldwide. Genetic factors play a significant role in influencing susceptibility to tuberculosis. This review examines the current progress in studying polymorphisms within immune genes associated with tuberculosis susceptibility, focusing on African populations. The roles of various proteins, including Toll-like receptors, Dendritic Cell-Specific Intercellular Adhesion Molecule-3 Grabbing Non-Integrin, vitamin D nuclear receptor, soluble C-type lectins such as surfactant proteins A and D, C-type Lectin Domain Family 4 Member E, and mannose-binding lectin, phagocyte cytokines such as Interleukin-1, Interleukin-6, Interleukin-10, Interleukin-12, and Interleukin-18, and chemokines such as Interleukin-8, monocyte chemoattractant protein 1, Regulated upon activation, normal T-cell expressed and secreted are explored in the context of tuberculosis susceptibility. We also address the potential impact of genetic variants on protein functions, as well as how these findings align with the genetic polymorphisms not associated with tuberculosis. Functional studies in model systems provide insights into the intricate host-pathogen interactions and susceptibility mechanisms. Despite progress, gaps in knowledge remain, highlighting the need for further investigations. This review emphasizes the association of Single Nucleotide Polymorphisms with diverse aspects of tuberculosis pathogenesis, including disease detection and Mycobacterium tuberculosis infection.

Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings

Noncommunicable diseases (NCDs) are influenced by the interplay between genetics and environmental exposures, particularly diet. However, many healthcare professionals, including nutritionists and dietitians, have limited genetic background and, therefore, they may lack understanding of gene-environment interactions (GxEs) studies. Even researchers deeply involved in nutrition studies, but with a focus elsewhere, can struggle to interpret, evaluate, and conduct GxE studies. There is an urgent need to study African populations that bear a heavy burden of NCDs, demonstrate unique genetic variability, and have cultural practices resulting in distinctive environmental exposures compared with Europeans or Americans, who are studied more. Although diverse and rapidly changing environments, as well as the high genetic variability of Africans and difference in linkage disequilibrium (ie, certain gene variants are inherited together more often than expected by chance), provide unparalleled potential to investigate the omics fields, only a small percentage of studies come from Africa. Furthermore, research evidence lags behind the practices of companies offering genetic testing for personalized medicine and nutrition. We need to generate more evidence on GxEs that also considers continental African populations to be able to prevent unethical practices and enable tailored treatments. This review aims to introduce nutrition professionals to genetics terms and valid methods to investigate GxEs and their challenges, and proposes ways to improve quality and reproducibility. The review also provides insight into the potential contributions of nutrigenetics and nutrigenomics to the healthcare sphere, addresses direct-to-consumer genetic testing, and concludes by offering insights into the field's future, including advanced technologies like artificial intelligence and machine learning.

Asthma morbidity measures across Black ethnic subgroups

BACKGROUND

Black adults are disproportionately affected by asthma and are often considered a homogeneous group in research studies despite cultural and ancestral differences.

OBJECTIVE

We sought to determine if asthma morbidity differs across adults in Black ethnic subgroups.

METHODS

Adults with moderate-severe asthma were recruited across the continental United States and Puerto Rico for the PREPARE (PeRson EmPowered Asthma RElief) trial. Using self-identifications, we categorized multiethnic Black (ME/B) participants (n = 226) as Black Latinx participants (n = 146) or Caribbean, continental African, or other Black participants (n = 80). African American (AA/B) participants (n = 518) were categorized as Black participants who identified their ethnicity as being American. Baseline characteristics and retrospective asthma morbidity measures (self-reported exacerbations requiring systemic corticosteroids [SCs], emergency department/urgent care [ED/UC] visits, hospitalizations) were compared across subgroups using multivariable regression.

RESULTS

Compared with AA/B participants, ME/B participants were more likely to be younger, residing in the US Northeast, and Spanish speaking and to have lower body mass index, health literacy, and <1 comorbidity, but higher blood eosinophil counts. In a multivariable analysis, ME/B participants were significantly more likely to have ED/UC visits (incidence rate ratio [IRR] = 1.34, 95% CI = 1.04-1.72) and SC use (IRR = 1.27, 95% CI = 1.00-1.62) for asthma than AA/B participants. Of the ME/B subgroups, Puerto Rican Black Latinx participants (n = 120) were significantly more likely to have ED/UC visits (IRR = 1.64, 95% CI = 1.22-2.21) and SC use for asthma (IRR = 1.43, 95% CI = 1.06-1.92) than AA/B participants. There were no significant differences in hospitalizations for asthma among subgroups.

CONCLUSIONS

ME/B adults, specifically Puerto Rican Black Latinx adults, have higher risk of ED/UC visits and SC use for asthma than other Black subgroups.

Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture

The heritability of susceptibility to tuberculosis (TB) disease has been well recognized. Over 100 genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicate. We established the International Tuberculosis Host Genetics Consortium to perform a multi-ancestry meta-analysis of GWAS, including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h2 = 26.3%, 95% CI 23.7-29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p<5 × 10-8) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value=5.2 × 10-9) but failed to replicate variants previously associated with TB susceptibility. These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressure.

Assessing the lack of diversity in genetics research across neurodegenerative diseases: a systematic review of the GWAS Catalog and literature

Importance

The under-representation of participants with non-European ancestry in genome-wide association studies (GWAS) is a critical issue that has significant implications, including hindering the progress of precision medicine initiatives. This issue is particularly significant in the context of neurodegenerative diseases (NDDs), where current therapeutic approaches have shown limited success. Addressing this under-representation is crucial to harnessing the full potential of genomic medicine in underserved communities and improving outcomes for NDD patients.

Objective

Our primary objective was to assess the representation of non-European ancestry participants in genetic discovery efforts related to NDDs. We aimed to quantify the extent of inclusion of diverse ancestry groups in NDD studies and determine the number of associated loci identified in more inclusive studies. Specifically, we sought to highlight the disparities in research efforts and outcomes between studies predominantly involving European ancestry participants and those deliberately targeting non-European or multi-ancestry populations across NDDs.

Evidence Review

We conducted a systematic review utilizing existing GWAS results and publications to assess the inclusion of diverse ancestry groups in neurodegeneration and neurogenetics studies. Our search encompassed studies published up to the end of 2022, with a focus on identifying research that deliberately included non-European or multi-ancestry cohorts. We employed rigorous methods for the inclusion of identified articles and quality assessment.

Findings

Our review identified a total of 123 NDD GWAS. Strikingly, 82% of these studies predominantly featured participants of European ancestry. Endeavors specifically targeting non-European or multi-ancestry populations across NDDs identified only 52 risk loci. This contrasts with predominantly European studies, which reported over 90 risk loci for a single disease. Encouragingly, over 65% of these discoveries occurred in 2020 or later, indicating a recent increase in studies deliberately including non-European cohorts.

Conclusions and relevance

Our findings underscore the pressing need for increased diversity in neurodegenerative research. The significant under-representation of non-European ancestry participants in NDD GWAS limits our understanding of the genetic underpinnings of these diseases. To advance the field of neurodegenerative research and develop more effective therapies, it is imperative that future investigations prioritize and harness the genomic diversity present within and across global populations.

Feasibility of preemptive pharmacogenetic testing and improvement of medication treatment satisfaction among medically underserved patients

Previous findings suggest that medically underserved patients are prescribed medications with pharmacogenetic (PGx) guidelines at a high frequency. Thus, underserved patients may especially benefit from PGx testing, but little evidence exists regarding the effect of testing in this population. This pilot study aimed to generate key feasibility data and explore clinical outcomes of PGx implementation in underserved populations. Black and Latino patients were recruited from an outpatient clinic and underwent PGx testing. Feasibility measures included enrollment metrics and actionable genotype frequencies. The primary clinical outcome was patient medication treatment satisfaction 6 months after testing. Implementation outcomes included the number of healthcare provider encounters and medication changes within the 6-month follow-up. Effectiveness outcomes included medication adherence, patient-perceived test value, and time spent discussing medications with providers. Ninety-nine patients completed the study. Proton-pump inhibitors were the most frequent PGx drug class prescribed at baseline (61%) followed by nonsteroidal anti-inflammatory drugs (36%). Patients with an actionable genotype constituted 96% of the population, whereas 28% had an actionable genotype related to their PGx drug. Patient treatment satisfaction significantly increased over the 6 months after PGx testing. In addition, medication adherence and the number of provider encounters significantly increased over the study period. In a pilot study, preemptive PGx testing was feasible in primary care clinics, improved patient treatment satisfaction and adherence, and increased the number of provider encounters in medically underserved patients. Future clinical trials are warranted to assess the long-term effects of PGx testing in a larger diverse patient population.

Individual Trajectories of Depressive Symptoms Within Racially-Ethnically Diverse Youth: Associations with Polygenic Risk for Depression and Substance Use Intent and Perceived Harm

There are distinct individual trajectories of depressive symptoms across adolescence which are most often differentiated into low, moderate/stable, and high/increasing groups. Research has found genetic predisposition for depression associated with trajectories characterized by greater depressive symptoms. However, the majority of this research has been conducted in White youth. Moreover, a separate literature indicates that trajectories with elevated depressive symptoms can result in substance use. It is critical to identify depressive symptom trajectories, genetic predictors, and substance use outcomes in diverse samples in early adolescence to understand distinct processes and convey equitable benefits from research. Using data from the Adolescent Cognitive Brain Development Study (ABCD), we examined parent-reported depressive symptom trajectories within Black/African American (AA, n = 1783), White/European American (EA, n = 6179), and Hispanic/Latinx (LX, n = 2410) youth across four annual assessments in early adolescence (age 9-10 to 12-13). We examined racially/ethnically aligned polygenic scores (Dep-PGS) as predictors of trajectories as well as substance use intent and perceived substance use harm as outcomes at age 12-13. Differential trajectories were found in AA, EA, and LX youth but low and high trajectories were represented within each group. In EA youth, greater Dep-PGS were broadly associated with membership in trajectories with greater depressive symptoms. Genetic effects were not significant in AA and LX youth. In AA youth, membership in the low trajectory was associated with greater substance use intent. In EA youth, membership in trajectories with higher depressive symptoms was associated with greater substance use intent and less perceived harm. There were no associations between trajectories and substance use intent and perceived harm in LX youth. These findings indicate that there are distinct depressive symptom trajectories in AA, EA, and LX youth, accompanied by unique associations with genetic predisposition for depressive symptoms and substance use outcomes.

Early-onset diabetes in Africa: A mini-review of the current genetic profile

Early-onset diabetes is poorly diagnosed partly due to its heterogeneity and variable presentations. Although several genes have been associated with the disease, these genes are not well studied in Africa. We sought to identify the major neonatal, early childhood, juvenile, or early-onset diabetes genes in Africa; and evaluate the available molecular methods used for investigating these gene variants. A literature search was conducted on PubMed, Scopus, Africa-Wide Information, and Web of Science databases. The retrieved records were screened and analyzed to identify genetic variants associated with early-onset diabetes. Although 319 records were retrieved, 32 were considered for the current review. Most of these records (22/32) were from North Africa. The disease condition was genetically heterogenous with most cases possessing unique gene variants. We identified 22 genes associated with early-onset diabetes, 9 of which had variants (n = 19) classified as pathogenic or likely pathogenic (PLP). Among the PLP variants, IER3IP1: p.(Leu78Pro) was the variant with the highest number of cases. There was limited data from West Africa, hence the contribution of genetic variability to early-onset diabetes in Africa could not be comprehensively evaluated. It is worth mentioning that most studies were focused on natural products as antidiabetics and only a few studies reported on the genetics of the disease. ABCC8 and KCNJ11 were implicated as major contributors to early-onset diabetes gene networks. Gene ontology analysis of the network associated ion channels, impaired glucose tolerance, and decreased insulin secretions to the disease. Our review highlights 9 genes from which PLP variants have been identified and can be considered for the development of an African diagnostic panel. There is a gap in early-onset diabetes genetic research from sub-Saharan Africa which is much needed to develop a comprehensive, efficient, and cost-effective genetic panel that will be useful in clinical practice on the continent and among the African diasporas.

Population diversity and equity in the genomic era: going global to return to the local

Advances in precision medicine depend on the quantity and quality of available genomic information. Various articles alert about the current disparities between the world's regions regarding the amount of genomic information available and the negative impact this will have on global health. The objective of this paper is to review these articles to describe what aspects they emphasize and highlight some issues that remain to be analyzed from the perspective of a "peripheral" country. Most of these articles come from central countries, where the need for more diversity in genomics is already detected. Several authors analyze lack of human diversity with focus on national, while others analyze the problem from a global perspective. Depending on the country of origin of the research, the claim for greater diversity has different meanings. Broadly, high-income countries advocate for better coverage looking within the boundaries of their own countries. In other regions of the world, where this field of research has not yet been massively developed, the same need for greater inclusiveness of origins in population genomics studies is not detected. An under-analyzed aspect is the unequal starting point between regions regarding the economic resources available for the development of this field of medicine, and for science and health in general. Although this macroeconomic and social aspect is usually absent in scientific analyses, without it solved, it will be impossible to guarantee that all world populations are equally represented in the panels or genomic databases that serve as input for precision medicine development.

Cancer genetic mutation prevalence in sub-Saharan Africa: A review of existing data

BACKGROUND

Cancer represents a leading cause of death worldwide. Germline mutations in several genes increase the risk of developing several cancers, including cancers of the breast, ovary, pancreas, colorectum, and melanoma. An understanding of the population prevalence of pathogenic germline variants can be helpful in the design of public health interventions, such as genetic testing, which has downstream implications for cancer screening, prevention, and treatment. While population-based studies of pathogenic germline variants exist, most such studies have been conducted in White populations. Limited data exist regarding the prevalence of germline mutations within sub-Saharan African populations.

MATERIALS AND METHODS

We identified countries defined as sub-Saharan Africa by the World Bank and conducted a scoping literature review using PubMed. For each country, we identified and summarized studies that focused on the prevalence of germline genetic mutations with sample sizes >10 and in a population directly from sub-Saharan Africa, either with or without diseases associated with the relevant genetic mutations. Studies that evaluated the prevalence of somatic or likely benign variants were excluded.

RESULTS

Within the 48 countries in sub-Saharan Africa, we identified 34 studies which meet the inclusion criteria. Twenty studies were conducted in South Africa, Nigeria, or Burkina Faso; four countries had more than two published papers. We found that 33 of 48 countries in sub-Saharan Africa lacked any genetic studies. Notably, there has been an increase in relevant studies starting in 2020. Importantly, of the 34 studies identified, 29 included data on BRCA1 or BRCA2. Data on the prevalence of mutations contributing to familial cancer syndromes other than BRCA1 and BRCA2 was limited.

CONCLUSIONS

While some progress has been made towards understanding the prevalence of germline mutations in cancer susceptibility genes, the characterization of genetic mutations among sub-Saharan African populations remains strikingly incomplete. Given the genetic diversity in the region, there remains a great need for large-scale, population-based studies to understand the prevalence of germline pathogenic variants and adequately capture all the subpopulations in this part of the world.

The Self-Fulfilling Process of Clinical Race Correction: The Case of Eighth Joint National Committee Recommendations

There is growing attention to how unfounded beliefs about biological differences between racial groups affect biomedical research and health care, in part, through race adjustment in clinical tools. We develop a case study of the Eighth Joint National Committee (JNC 8)'s 2014 Evidence-Based Guideline for the Management of High Blood Pressure in Adults, which recommends a distinct initial hypertension treatment for Black versus nonblack patients. We analyze the historical context, study design, and racialized findings of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) that informed development of the guideline. We argue that ALLHAT's racialized outcomes emanated from a poor and artificial study design and analysis weakened by implicit assumptions about race as biological. We show that the acceptance and utilization of ALLHAT for race correction arises from its historical context within the "inclusion-and-difference paradigm" and its indication of the inefficacy of angiotensin-converting-enzyme inhibitors for Black patients, which follows from the enduring, yet, refuted slavery hypertension hypothesis. We demonstrate that the JNC 8 guideline displays the self-fulfilling process of racial reasoning: presuppositions about racial differences inform the design and interpretation of research, which then conceptually reinforce ideas about racial differences leading to differential medical treatment. We advocate for the abolition of race adjustment and the integration of structural competency, biocritical inquiry, and race-conscious medicine into biomedical research and clinical medicine to disrupt the use of race as a proxy for ancestry, environment, and social treatment and to address the genuine determinants of racialized disparities in hypertension.

A phenome-wide scan reveals convergence of common and rare variant associations

BACKGROUND

Common and rare variants contribute to the etiology of complex traits. However, the extent to which the phenotypic effects of common and rare variants involve shared molecular mediators remains poorly understood. The question is essential to the basic and translational goals of the science of genomics, with critical basic-science, methodological, and clinical consequences.

METHODS

Leveraging the latest release of whole-exome sequencing (WES, for rare variants) and genome-wide association study (GWAS, for common variants) data from the UK Biobank, we developed a metric, the COmmon variant and RAre variant Convergence (CORAC) signature, to quantify the convergence for a broad range of complex traits. We characterized the relationship between CORAC and effective sample size across phenome-wide association studies.

RESULTS

We found that the signature is positively correlated with effective sample size (Spearman ρ = 0.594, P < 2.2e - 16), indicating increased functional convergence of trait-associated genetic variation, across the allele frequency spectrum, with increased power. Sensitivity analyses, including accounting for heteroskedasticity and varying the number of detected association signals, further strengthened the validity of the finding. In addition, consistent with empirical data, extensive simulations showed that negative selection, in line with enhancing polygenicity, has a dampening effect on the convergence signature. Methodologically, leveraging the convergence leads to enhanced association analysis.

CONCLUSIONS

The presented framework for the convergence signature has important implications for fine-mapping strategies and drug discovery efforts. In addition, our study provides a blueprint for the expectation from future large-scale whole-genome sequencing (WGS)/WES and sheds methodological light on post-GWAS studies.

Research participants' perspectives regarding the feedback of secondary findings-A cohort from the DDD-Africa study, South Africa

Genomic researchers face an ethical dilemma regarding feedback of individual results generated from genomic studies. In the African setting, genomic research is still not widely implemented and, coupled with this, the limited African-specific guidelines on how to feedback on individual research findings. A qualitative study was performed to assess participants' expectations and preferences regarding the feedback of secondary findings from genomic research. Participants were parents of children with a developmental disorder, enrolled in the Deciphering Developmental Disorders in Africa (DDD-Africa) research project, and were purposefully selected. Three deliberative focus group discussions were conducted with 14 participants. Each deliberative focus group consisted of two separate audio-recorded interviews and presented different case scenarios for different types of secondary findings that could be theoretically detected during genomic research. We aimed to explore participants' preferences for the extent, nature, timing, and methods for receiving individual study results, specifically pertaining to secondary findings. Thematic content analysis was done, with a deductive approach to coding. Four themes emerged which included participants' perception of readiness to receive secondary findings, queries raised around who has access to research findings and feedback of findings consent, responsibilities of the researcher, and reasons for not wanting/wanting secondary findings. Overall, participants expressed that they want to receive feedback on secondary findings irrespective of disease severity and treatment availability. Lifestyle changes, early prevention or treatment, impact on future generations, and preparedness were strong motivations for wanting feedback on results. Participants felt that when the research involved minors, it was the parents' right to receive results on behalf of their children. This study provides new insights into participants' preferences around feedback on genomic research results and could serve as an important basis for creating guidelines and recommendations for feedback on genomic results in the African context.

Assessing a Polygenic Risk Score for Lung Cancer Susceptibility in Non-Hispanic White and Black Populations

BACKGROUND

Polygenic risk scores (PRS) have become an increasingly popular approach to evaluate cancer susceptibility, but have not adequately represented Black populations in model development.

METHODS

We used a previously published lung cancer PRS on the basis of 80 SNPs associated with lung cancer risk in the OncoArray cohort and validated in UK Biobank. The PRS was evaluated for association with lung cancer risk adjusting for age, sex, total pack-years, family history of lung cancer, history of chronic obstructive pulmonary disease, and the top five principal components for genetic ancestry.

RESULTS

Among the 80 PRS SNPs included in the score, 14 were significantly associated with lung cancer risk (P < 0.05) in INHALE White participants, while there were no significant SNPs among INHALE Black participants. After adjusting for covariates, the PRS was significantly associated with risk in Whites (continuous score P = 0.007), but not in Blacks (continuous score P = 0.88). The PRS remained a statistically significant predictor of lung cancer risk in Whites ineligible for lung cancer screening under current U.S. Preventive Services Task Force guidelines (P = 0.02).

CONCLUSIONS

Using a previously validated PRS, we did find some predictive ability for lung cancer in INHALE White participants beyond traditional risk factors. However, this effect was not observed in Black participants, indicating the need to develop and validate ancestry-specific lung cancer risk models.

IMPACT

While a previously published lung cancer PRS was able to stratify White participants into different levels of risk, the model was not predictive in Blacks. Our findings highlight the need to develop and validate ancestry-specific lung cancer risk models.

Polygenic risk scores for disease risk prediction in Africa: current challenges and future directions

Early identification of genetic risk factors for complex diseases can enable timely interventions and prevent serious outcomes, including mortality. While the genetics underlying many Mendelian diseases have been elucidated, it is harder to predict risk for complex diseases arising from the combined effects of many genetic variants with smaller individual effects on disease aetiology. Polygenic risk scores (PRS), which combine multiple contributing variants to predict disease risk, have the potential to influence the implementation for precision medicine. However, the majority of existing PRS were developed from European data with limited transferability to African populations. Notably, African populations have diverse genetic backgrounds, and a genomic architecture with smaller haplotype blocks compared to European genomes. Subsequently, growing evidence shows that using large-scale African ancestry cohorts as discovery for PRS development may generate more generalizable findings. Here, we (1) discuss the factors contributing to the poor transferability of PRS in African populations, (2) showcase the novel Africa genomic datasets for PRS development, (3) explore the potential clinical utility of PRS in African populations, and (4) provide insight into the future of PRS in Africa.

Whole Exome Sequencing reveals clinically important pathogenic mutations in DNA repair genes across lung cancer patients

Lung cancer remains a substantial health challenge, with distinct genetic factors influencing disease susceptibility and progression. This study aimed to decipher the landscape of DNA repair gene mutations in Pakistani lung cancer patients using Whole Exome Sequencing (WES) and to investigate their potential functional implications through downstream analyses. WES analysis of genomic DNA from 15 lung cancer patients identified clinically important pathogenic mutations in 6 DNA repair genes, including, BReast CAncer gene 1 (BRCA1), BReast CAncer gene 2 (BRCA2), Excision Repair Cross Complementing rodent repair deficiency, complementation group 6 (ERCC6), Checkpoint Kinase 1 (CHEK1), mutY DNA glycosylase (MUTYH), and RAD51D (RAD51 Paralog D). Kaplan-Meier (KM) analysis showed that pathogenic mutations in BRCA1, BRCA2, ERCC6, CHEK1, MUTYH, and RAD51D genes were the prognostic biomarkers of worse OS in lung cancer patients. To explore the functional impact of these mutations, we performed Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Immunohistochemistry (IHC) analyses. Our results revealed a down-regulation in the expression of the mutated genes, indicating a potential link between the identified mutations and reduced gene activity. This down-regulation could contribute to compromised DNA repair efficiency, thereby fostering genomic instability in lung cancer cells. Furthermore, targeted bisulfite sequencing analysis was employed to assess the DNA methylation status of the mutated genes. Strikingly, hypermethylation in the promoters of BRCA1, BRCA2, ERCC6, CHEK1, MUTYH, and RAD51D was observed across lung cancer samples harboring pathogenic mutations, suggesting the involvement of epigenetic mechanism underlying the altered gene expression. In conclusion, this study provides insights into the genetic landscape of DNA repair gene mutations in Pakistani lung cancer patients. The observed pathogenic mutations in BRCA1, BRCA2, ERCC6, CHEK1, MUTYH, and RAD51D, coupled with their down-regulation and hypermethylation, suggest a potential convergence of genetic and epigenetic factors driving genomic instability in lung cancer cells. These findings contribute to our understanding of lung cancer susceptibility and highlight potential avenues for targeted therapeutic interventions in Pakistani lung cancer patients.

Paving the way while playing catch up: mitochondrial genetics in African ancestry primary open-angle glaucoma

Glaucoma, the leading cause of irreversible blindness worldwide, disproportionately affects individuals of African descent. Specifically, previous research has indicated that primary open-angle glaucoma (POAG), the most common form of disease, is more prevalent, severe, early-onset, and rapidly-progressive in populations of African ancestry. Recent studies have identified genetic variations that may contribute to the greater burden of disease in this population. In particular, mitochondrial genetics has emerged as a profoundly influential factor in multiple neurodegenerative diseases, including POAG. Several hypotheses explaining the underlying mechanisms of mitochondrial genetic contribution to disease progression have been proposed, including nuclear-mitochondrial gene mismatch. Exploring the fundamentals of mitochondrial genetics and disease pathways within the understudied African ancestry population can lead to groundbreaking advancements in the research and clinical understanding of POAG. This article discusses the currently known involvements of mitochondrial genetic factors in POAG, recent directions of study, and potential future prospects in mitochondrial genetic studies in individuals of African descent.

Feasibility and impact of haplogroup matching for mitochondrial replacement treatment

Mitochondrial replacement technology (MRT) aims to reduce the risk of serious disease in children born to women who carry pathogenic mitochondrial DNA (mtDNA) variants. By transplanting nuclear genomes from eggs of an affected woman to enucleated eggs from an unaffected donor, MRT creates new combinations of nuclear and mtDNA. Based on sets of shared sequence variants, mtDNA is classified into ~30 haplogroups. Haplogroup matching between egg donors and women undergoing MRT has been proposed as a means of reducing mtDNA sequence divergence between them. Here we investigate the potential effect of mtDNA haplogroup matching on clinical delivery of MRT and on mtDNA sequence divergence between donor/recipient pairs. Our findings indicate that haplogroup matching would limit the availability of egg donors such that women belonging to rare haplogroups may have to wait > 4 years for treatment. Moreover, we find that intra-haplogroup sequence variation is frequently within the range observed between randomly matched mtDNA pairs. We conclude that haplogroup matching would restrict the availability of MRT, without necessarily reducing mtDNA sequence divergence between donor/recipient pairs.

Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer's Diseases Sequencing Project Subjects

Structural variations (SVs) are important contributors to the genetics of human diseases. However, their role in Alzheimer's disease (AD) remains largely unstudied due to challenges in accurately detecting SVs. We analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (N = 16,905) and identified 400,234 (168,223 high-quality) SVs. Laboratory validation yielded a sensitivity of 82% (85% for high-quality). We found a significant burden of deletions and duplications in AD cases, particularly for singletons and homozygous events. On AD genes, we observed the ultra-rare SVs associated with the disease, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1. Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, exemplified by a 5k deletion in complete LD with rs143080277 in NCK2. We also identified 16 SVs associated with AD and 13 SVs linked to AD-related pathological/cognitive endophenotypes. This study highlights the pivotal role of SVs in shaping our understanding of AD genetics.

Alcohol use polygenic risk score, social support, and alcohol use among European American and African American adults

Alcohol use is influenced by genetic and environmental factors. We examined the interactive effects between genome-wide polygenic risk scores for alcohol use (alc-PRS) and social support in relation to alcohol use among European American (EA) and African American (AA) adults across sex and developmental stages (emerging adulthood, young adulthood, and middle adulthood). Data were drawn from 4,011 EA and 1,274 AA adults from the Collaborative Study on the Genetics of Alcoholism who were between ages 18-65 and had ever used alcohol. Participants completed the Semi-Structured Assessment for the Genetics of Alcoholism and provided saliva or blood samples for genotyping. Results indicated that social support from friends, but not family, moderated the association between alc-PRS and alcohol use among EAs and AAs (only in middle adulthood for AAs); alc-PRS was associated with higher levels of alcohol use when friend support was low, but not when friend support was high. Associations were similar across sex but differed across developmental stages. Findings support the important role of social support from friends in buffering genetic risk for alcohol use among EA and AA adults and highlight the need to consider developmental changes in the role of social support in relation to alcohol use.

A pilot study examining the relationship between chronic heroin use and telomere length among individuals of African ancestry

BACKGROUND

Prior research has suggested a possible link between heroin use and shortened telomere length (TL), a marker of cellular aging and genomic stability. We sought to replicate these findings by examining the relationship between TL and heroin use among individuals of African ancestry.

METHODS

This cross-sectional study examined TL among 57 participants [17.5 % female; mean age 48.0 (±6.80) years] of African ancestry with Opioid Use Disorder (OUD) and a mean heroin use duration of 18.2 (±10.7) years. Quantitative polymerase chain reaction (qPCR) was used to calculate TL as the ratio between telomere repeat copy number (T) and a single-copy gene, copy number (S). The primary dependent variable was TL (T/S Ratio) measured in kilobase pairs. Covariates included heroin use years and personality traits. Using a hybrid approach, multiple linear regression and Bayesian linear regression examined the association of chronological age, heroin use years and personality traits with TL.

RESULTS

The multiple linear regression model fit the data well, R2 = 0.265, F(7,49) = 2.53, p < .026. Chronological age (β = -0.36, p = .017), neuroticism (β = 0.46, p = .044), and conscientiousness (β = 0.52, p = .040) were significant predictors of TL. Bayesian linear regression provided moderate support for the alternate hypothesis that chronological age and TL are associated, BF10 = 5.77, R2 = 0.120. The posterior summary of the coefficient was M = 0.719 (SD = 0.278, 95 % credible interval [-1.28, -0.163]).

CONCLUSIONS

Contrary to prior studies, these findings suggest that heroin use duration may not be significantly associated with TL among individuals of African ancestry, highlighting the need for more rigorous research to elucidate the complexity of this relationship.