Research capacity. Enabling the genomic revolution in Africa

APOL1 Bi- and Monoallelic Variants and Chronic Kidney Disease in West Africans

BACKGROUND

Apolipoprotein L1 gene (APOL1) variants are risk factors for chronic kidney disease (CKD) among Black Americans. Data are sparse on the genetic epidemiology of CKD and the clinical association of APOL1 variants with CKD in West Africans, a major group in the Black population.

METHODS

We conducted a case-control study involving participants from Ghana and Nigeria who had CKD stages 2 through 5, biopsy-proven glomerular disease, or no kidney disease. We analyzed the association of CKD with APOL1 variants among participants with high-risk genotypes (two APOL1 risk alleles) and those with low-risk genotypes (fewer than two APOL1 risk alleles) by fitting logistic-regression models that controlled for covariates, including clinical site, age, and sex.

RESULTS

Among 8355 participants (4712 with CKD stages 2 through 5, 866 with glomerular diseases, and 2777 with no kidney disease), the prevalence of monoallelic APOL1 variants was 43.0% and that of biallelic APOL1 variants was 29.7%. Participants with two APOL1 risk alleles had higher odds of having CKD than those with one risk allele or no risk alleles (adjusted odds ratio, 1.25; 95% confidence interval [CI], 1.11 to 1.40), as well as higher odds of focal segmental glomerulosclerosis (adjusted odds ratio, 1.84; 95% CI, 1.30 to 2.61). Participants with one APOL1 risk allele had higher odds of having CKD than those with no risk alleles (adjusted odds ratio, 1.18; 95% CI, 1.04 to 1.33), as well as higher odds of focal segmental glomerulosclerosis (adjusted odds ratio, 1.61; 95% CI, 1.04 to 2.48). The inclusion of covariates did not modify the association of monoallelic and biallelic APOL1 variants with CKD or focal segmental glomerulosclerosis.

CONCLUSIONS

In this study, monoallelic APOL1 variants were associated with 18% higher odds of CKD and 61% higher odds of focal segmental glomerulosclerosis; biallelic APOL1 variants were associated with 25% higher odds of CKD and 84% higher odds of focal segmental glomerulosclerosis. (Funded by the National Human Genome Research Institute and others.).

Universal newborn screening using genome sequencing: early experience from the GUARDIAN study

For more than 20 years there has been speculation about a future in which newborns are routinely screened at birth for genetic disorders using genome sequencing, but prospective large-scale studies assessing this vision have only recently begun. Genome sequencing may provide a means of expanding the scope of conditions included in newborn screening programs and improving the positive predictive value of traditional newborn screening. However, the use of genome sequencing for newborn screening has also raised concerns including acceptability, equity, and scalability. By reviewing the initial results of the GUARDIAN study and contrasting them with other pilot studies investigating the use of genome sequencing for large-scale newborn screening, we highlight how the lessons learned from these studies are shaping the future for the implementation of truly universal and equitable newborn genomic screening.

A call to action to scale up research and clinical genomic data sharing

Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit.

Genome Tunisia Project: paving the way for precision medicine in North Africa

BACKGROUND

Key discoveries and innovations in the field of human genetics have led to the foundation of molecular and personalized medicine. Here, we present the Genome Tunisia Project, a two-phased initiative (2022-2035) which aims to deliver the reference sequence of the Tunisian Genome and to support the implementation of personalized medicine in Tunisia, a North African country that represents a central hub of population admixture and human migration between African, European, and Asian populations. The main goal of this initiative is to develop a healthcare system capable of incorporating omics data for use in routine medical practice, enabling medical doctors to better prevent, diagnose, and treat patients.

METHODS

A multidisciplinary partnership involving Tunisian experts from different institutions has come to discern all requirements that would be of high priority to fulfill the project's goals. One of the most urgent priorities is to determine the reference sequence of the Tunisian Genome. In addition, extensive situation analysis and revision of the education programs, community awareness, appropriate infrastructure including sequencing platforms and biobanking, as well as ethical and regulatory frameworks, have been undertaken towards building sufficient capacity to integrate personalized medicine into the Tunisian healthcare system.

RESULTS

In the framework of this project, an ecosystem with all engaged stakeholders has been implemented including healthcare providers, clinicians, researchers, pharmacists, bioinformaticians, industry, policymakers, and advocacy groups. This initiative will also help to reinforce research and innovation capacities in the field of genomics and to strengthen discoverability in the health sector.

CONCLUSIONS

Genome Tunisia is the first initiative in North Africa that seeks to demonstrate the major impact that can be achieved by Human Genome Projects in low- and middle-income countries to strengthen research and to improve disease management and treatment outcomes, thereby reducing the social and economic burden on healthcare systems. Sharing this experience within the African scientific community is a chance to turn a major challenge into an opportunity for dissemination and outreach. Additional efforts are now being made to advance personalized medicine in patient care by educating consumers and providers, accelerating research and innovation, and supporting necessary changes in policy and regulation.

Advancing microbiome research through standardized data and metadata collection: introducing the Microbiome Research Data Toolkit

Microbiome research has made significant gains with the evolution of sequencing technologies. Ensuring comparability between studies and enhancing the findability, accessibility, interoperability and reproducibility of microbiome data are crucial for maximizing the value of this growing body of research. Addressing the challenges of standardized metadata reporting, collection and curation, the Microbiome Working Group of the Human Hereditary and Health in Africa (H3Africa) consortium aimed to develop a comprehensive solution. In this paper, we present the Microbiome Research Data Toolkit, a versatile tool designed to standardize microbiome research metadata, facilitate MIxS-MIMS and PhenX reporting, standardize prospective collection of participant biological and lifestyle data, and retrospectively harmonize such data. This toolkit enables past, present and future microbiome research endeavors to collaborate effectively, fostering novel collaborations and accelerating knowledge discovery in the field. Database URL: https://doi.org/10.25375/uct.24218999.v2.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

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.

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.

An assessment of the genomic structural variation landscape in Sub-Saharan African populations

Structural variants are responsible for a large part of genomic variation between individuals and play a role in both common and rare diseases. Databases cataloguing structural variants notably do not represent the full spectrum of global diversity, particularly missing information from most African populations. To address this representation gap, we analysed 1,091 high-coverage African genomes, 545 of which are public data sets, and 546 which have been analysed for structural variants for the first time. Variants were called using five different tools and datasets merged and jointly called using SURVIVOR. We identified 67,795 structural variants throughout the genome, with 10,421 genes having at least one variant. Using a conservative overlap in merged data, 6,414 of the structural variants (9.5%) are novel compared to the Database of Genomic Variants. This study contributes to knowledge of the landscape of structural variant diversity in Africa and presents a reliable dataset for potential applications in population genetics and health-related research.

Parental Perspectives Regarding the Return of Genomic Research Results in Neurodevelopmental Disorders in South Africa: Anticipated Impact and Preferences

Few policies and little research exist regarding the disclosure of genomic results to research participants in Africa. As understanding participant preferences would be pivotal to the success of the feedback process, this study set out to address this issue by engaging with enrolled participants from an ongoing genomics research project on neurodevelopmental disorders with the aim to assess the anticipated impact of receiving pertinent results and explore the preferences for feedback in a South-African context. Twelve semi-structured interviews were conducted with 17 parents of children participating in the research study. Transcribed interview data and observational notes were analysed using thematic analysis and framework matrices. Participants linked their own meaning to the impact of receiving a pertinent result and perceived the information as useful for reasons other than only clinical utility. These included closure, improved management of their child's condition and information regarding recurrence risks. In terms of preferences for feedback, an in-person result delivery session, conducted by a member of the study team or medical professional familiar with their child was preferred. In addition, participants felt a sense of ownership over their blood or their contribution to the research study, finding meaning even in non-pertinent (secondary findings) or negative results. These findings provide insight into the type of discussions that may be valuable in enabling the development of best practices and guidelines for the return of individual genetic research results, in a culturally appropriate manner, within South-African communities.

Validity of European-centric cardiometabolic polygenic scores in multi-ancestry populations

Polygenic scores (PGSs) provide an individual level estimate of genetic risk for any given disease. Since most PGSs have been derived from genome wide association studies (GWASs) conducted in populations of White European ancestry, their validity in other ancestry groups remains unconfirmed. This is especially relevant for cardiometabolic diseases which are known to disproportionately affect people of non-European ancestry. Thus, we aimed to evaluate the performance of PGSs for glycaemic traits (glycated haemoglobin, and type 1 and type 2 diabetes mellitus), cardiometabolic risk factors (body mass index, hypertension, high- and low-density lipoproteins, and total cholesterol and triglycerides) and cardiovascular diseases (including stroke and coronary artery disease) in people of White European, South Asian, and African Caribbean ethnicity in the UK Biobank. Whilst PGSs incorporated some GWAS data from multi-ethnic populations, the vast majority originated from White Europeans. For most outcomes, PGSs derived mostly from European populations had an overall better performance in White Europeans compared to South Asians and African Caribbeans. Thus, multi-ancestry GWAS data are needed to derive ancestry stratified PGSs to tackle health inequalities.

A regionally based precision medicine implementation initiative in North Africa:The PerMediNA consortium

Precision Medicine is being increasingly used in the developed world to improve health care. While several Precision Medicine (PM) initiatives have been launched worldwide, their implementations have proven to be more challenging particularly in low- and middle-income countries. To address this issue, the "Personalized Medicine in North Africa" initiative (PerMediNA) was launched in three North African countries namely Tunisia, Algeria and Morocco. PerMediNA is coordinated by Institut Pasteur de Tunis together with the French Ministry for Europe and Foreign Affairs, with the support of Institut Pasteur in France. The project is carried out along with Institut Pasteur d'Algérie and Institut Pasteur du Maroc in collaboration with national and international leading institutions in the field of PM including Institut Gustave Roussy in Paris. PerMediNA aims to assess the readiness level of PM implementation in North Africa, to strengthen PM infrastructure, to provide workforce training, to generate genomic data on North African populations, to implement cost effective, affordable and sustainable genetic testing for cancer patients and to inform policy makers on how to translate research knowledge into health products and services. Gender equity and involvement of young scientists in this implementation process are other key goals of the PerMediNA project. In this paper, we are describing PerMediNA as the first PM implementation initiative in North Africa. Such initiatives contribute significantly in shortening existing health disparities and inequities between developed and developing countries and accelerate access to innovative treatments for global health.

Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry

Ancestral differences in genomic variation affect the regulation of gene expression; however, most gene expression studies have been limited to European ancestry samples or adjusted to identify ancestry-independent associations. Here, we instead examined the impact of genetic ancestry on gene expression and DNA methylation in the postmortem brain tissue of admixed Black American neurotypical individuals to identify ancestry-dependent and ancestry-independent contributions. Ancestry-associated differentially expressed genes (DEGs), transcripts and gene networks, while notably not implicating neurons, are enriched for genes related to the immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson disease and 30% of heritability for Alzheimer's disease. Ancestry-associated DEGs also show general enrichment for the heritability of diverse immune-related traits but depletion for psychiatric-related traits. We also compared Black and non-Hispanic white Americans, confirming most ancestry-associated DEGs. Our results delineate the extent to which genetic ancestry affects differences in gene expression in the human brain and the implications for brain illness risk.

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.

Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus

Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.

Bridging the gap between omics research and dental practice

AIM

The burgeoning field of omics research has witnessed exponential growth in both medicine and dentistry. However, despite more than a decade of advancements, clinical dentistry, particularly in Low- and Middle-Income Countries (LMICs), has seen limited progress in integrating omics-based approaches into routine practice. This review aims to provide a comprehensive overview of the integration of omics approaches in dentistry, focusing on the challenges and opportunities for translating research findings into clinical practice.

METHODS

we conducted a literature review using key databases to provide a brief overview of the history of genomics in dentistry. Additionally, we summarised recent breakthroughs in omics relevant to oral health practitioners, emphasising the inadequate translation of omics research into clinical practice.

RESULTS

Despite significant growth in omics research in both medicine and dentistry, its translation into routine clinical practice in dentistry remains limited. We summarise recent breakthroughs in omics and highlight the gap between research advancements and clinical implementation.

DISCUSSION AND CONCLUSION

The integration of omics approaches holds promise for enhancing diagnostics, personalised treatment strategies, and preventive measures in dental practice, ushering in a new era of precision oral healthcare. However, several challenges, including infrastructure limitations, cost-effectiveness, and education gaps, hinder the widespread adoption of omics-based approaches in clinical dentistry. A strong commitment to transforming dentistry is required to embrace this transition. This shift has the potential to revolutionise oral healthcare by advancing precision diagnostics and treatment strategies tailored to individual patient needs.

Characterization of CYP2B6 and CYP2A6 Pharmacogenetic Variation in Sub-Saharan African Populations

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

BACKGROUND

African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans.

METHODS

Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation.

RESULTS

We observed genome-wide significant (P-value < 5.0E-8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E-6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E-6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E-6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping.

CONCLUSIONS

Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke's risk prediction and development of new targeted interventions to prevent or treat stroke.

Cross-population applications of genomics to understand the risk of multifactorial traits involving inflammation and immunity

The interplay between genetic and environmental factors plays a significant role in interindividual variation in immune and inflammatory responses. The availability of high-throughput low-cost genotyping and next-generation sequencing has revolutionized our ability to identify human genetic variation and understand how this varies within and between populations, and the relationship with disease. In this review, we explore the potential of genomics for patient benefit, specifically in the diagnosis, prognosis and treatment of inflammatory and immune-related diseases. We summarize the knowledge arising from genetic and functional genomic approaches, and the opportunity for personalized medicine. The review covers applications in infectious diseases, rare immunodeficiencies and autoimmune diseases, illustrating advances in diagnosis and understanding risk including use of polygenic risk scores. We further explore the application for patient stratification and drug target prioritization. The review highlights a key challenge to the field arising from the lack of sufficient representation of genetically diverse populations in genomic studies. This currently limits the clinical utility of genetic-based diagnostic and risk-based applications in non-Caucasian populations. We highlight current genome projects, initiatives and biobanks from diverse populations and how this is being used to improve healthcare globally by improving our understanding of genetic susceptibility to diseases and regional pathogens such as malaria and tuberculosis. Future directions and opportunities for personalized medicine and wider application of genomics in health care are described, for the benefit of individual patients and populations worldwide.

TargetGene: a comprehensive database of cell-type-specific target genes for genetic variants

Annotating genetic variants to their target genes is of great importance in unraveling the causal variants and genetic mechanisms that underlie complex diseases. However, disease-associated genetic variants are often located in non-coding regions and manifest context-specific effects, making it challenging to accurately identify the target genes and regulatory mechanisms. Here, we present TargetGene (https://ngdc.cncb.ac.cn/targetgene/), a comprehensive database reporting target genes for human genetic variants from various aspects. Specifically, we collected a comprehensive catalog of multi-omics data at the single-cell and bulk levels and from various human tissues, cell types and developmental stages. To facilitate the identification of Single Nucleotide Polymorphism (SNP)-to-gene connections, we have implemented multiple analytical tools based on chromatin co-accessibility, 3D interaction, enhancer activities and quantitative trait loci, among others. We applied the pipeline to evaluate variants from nearly 1300 Genome-wide association studies (GWAS) and assembled a comprehensive atlas of multiscale regulation of genetic variants. TargetGene is equipped with user-friendly web interfaces that enable intuitive searching, navigation and browsing through the results. Overall, TargetGene provides a unique resource to empower researchers to study the regulatory mechanisms of genetic variants in complex human traits.

An Assessment of the Knowledge and Perceptions of Precision Medicine (PM) in the Rwandan Healthcare Setting

INTRODUCTION

Precision medicine (PM) or personalized medicine is an innovative approach that aims to tailor disease prevention and treatment to consider the differences in people's genes, environments, and lifestyles. Although many efforts have been made to accelerate the universal adoption of PM, several challenges need to be addressed in order to advance PM in Africa. Therefore, our study aimed to establish baseline data on the knowledge and perceptions of the implementation of PM in the Rwandan healthcare setting.

METHOD

A descriptive qualitative study was conducted in five hospitals offering diagnostics and oncology services to cancer patients in Rwanda. To understand the existing policies regarding PM implementation in the country, two additional institutions were surveyed: the Ministry of Health (MOH), which creates and sets policies for the overall vision of the health sector, and the Rwanda Biomedical Center (RBC), which coordinates the implementation of health sector policies in the country. The researchers conducted 32 key informant interviews and assessed the functionality of available PM equipment in the 5 selected health facilities. The data were thematically categorized and analyzed.

RESULTS

The study revealed that PM is perceived as a complex and expensive program by most health managers and health providers. The most cited challenges to implementing PM included the following: the lack of policies and guidelines; the lack of supportive infrastructures and limited suppliers of required equipment and laboratory consumables; financial constraints; cultural, behavioral, and religious beliefs; and limited trained, motivated, and specialized healthcare providers. Regarding access to health services for cancer treatment, patients with health insurance pay 10% of their medical costs, which is still too expensive for Rwandans.

CONCLUSION

The study participants highlighted the importance of PM to enhance healthcare delivery if the identified barriers are addressed. For instance, Rwandan health sector leadership might consider the creation of specialized oncology centers in all or some referral hospitals with all the necessary genomic equipment and trained staff to serve the needs of the country and implement a PM program.

Webinar report: stakeholder perspectives on informed consent for the use of genomic data by commercial entities

In July 2020, the H3Africa Ethics and Community Engagement (E&CE) Working Group organised a webinar with ethics committee members and biomedical researchers from various African institutions throughout the Continent to discuss the issue of whether and how biological samples for scientific research may be accessed by commercial entities when broad consents obtained for the samples are silent. 128 people including Research Ethics Committee members (10), H3Africa researchers (46) including members of the E&CE working group, biomedical researchers not associated with H3Africa (27), representatives from the National Institutes of Health (16) and 10 other participants attended the webinar and shared their views. Several major themes emerged during the webinar, with the topics of broad versus explicit informed consent, defining commercial use, legacy samples and benefit sharing prevailing in the discussion. This report describes the consensus concerns and recommendations raised during the meeting and will be informative for future research on ethical considerations for genomic research in the African research context.

Increased bacterial taxonomic and functional diversity is associated with impaired rotavirus vaccine immunogenicity in infants from India and Malawi

The immunogenicity and effectiveness of oral rotavirus vaccines (ORVs) against severe rotavirus-associated gastroenteritis are impaired in low- and middle-income countries (LMICs) where the burden of disease is highest. Determining risk factors for impaired ORV response may help identify strategies to enhance vaccine effectiveness. In this study, we use metagenomic sequencing to provide a high-resolution taxonomic analysis of stool samples collected at 6 weeks of age (coinciding with the first ORV dose) during a prospective study of ORV immunogenicity in India and Malawi. We then analyse the functional capacity of the developing microbiome in these cohorts. Microbiome composition differed significantly between countries, although functional capacity was more similar than taxonomic composition. Our results confirm previously reported findings that the developing microbiome is more diverse in taxonomic composition in ORV non-seroconverters compared with seroconverters, and we additionally demonstrate a similar pattern in functional capacity. Although taxonomic or functional feature abundances are poor predictors of ORV response, we show that skews in the direction of associations within these microbiome data can be used to identify consistent markers of ORV response across LMIC infant cohorts. We also highlight the systemic under-representation of reference genes from LMICs that limit functional annotation in our study (7% and 13% annotation at pathway and enzyme commission level, respectively). Overall, higher microbiome diversity in early life may act as marker for impaired ORV response in India and Malawi, whilst a holistic perspective of functional capacity may be hidden in the "dark matter" of the microbiome.

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.

Building blocks for better biorepositories in Africa

BACKGROUND

Biorepositories archive and distribute well-characterized biospecimens for research to support the development of medical diagnostics and therapeutics. Knowledge of biobanking and associated practices is incomplete in low- and middle-income countries where disease burden is disproportionately high. In 2011, the African Society of Human Genetics (AfSHG), the National Institutes of Health (NIH), and the Wellcome Trust founded the Human Heredity and Health in Africa (H3Africa) consortium to promote genomic research in Africa and established a network of three biorepositories regionally located in East, West, and Southern Africa to support biomedical research. This manuscript describes the processes established by H3Africa biorepositories to prepare research sites to collect high-quality biospecimens for deposit at H3Africa biorepositories.

METHODS

The biorepositories harmonized practices between the biorepositories and the research sites. The biorepositories developed guidelines to establish best practices and define biospecimen requirements; standard operating procedures (SOPs) for common processes such as biospecimen collection, processing, storage, transportation, and documentation as references; requirements for minimal associated datasets and formats; and a template material transfer agreements (MTA) to govern biospecimen exchange. The biorepositories also trained and mentored collection sites in relevant biobanking processes and procedures and verified biospecimen deposit processes. Throughout these procedures, the biorepositories followed ethical and legal requirements.

RESULTS

The 20 research projects deposited 107,982 biospecimens (76% DNA, 81,067), in accordance with the ethical and legal requirements and established best practices. The biorepositories developed and customized resources and human capacity building to support the projects. [The biorepositories developed 34 guidelines, SOPs, and documents; trained 176 clinicians and scientists in over 30 topics; sensitized ethical bodies; established MTAs and reviewed consent forms for all projects; attained import permits; and evaluated pilot exercises and provided feedback.

CONCLUSIONS

Biobanking in low- and middle-income countries by local skilled staff is critical to advance biobanking and genomic research and requires human capacity and resources for global partnerships. Biorepositories can help build human capacity and resources to support biobanking by partnering with researchers. Partnerships can be structured and customized to incorporate document development, ethics, training, mentorship, and pilots to prepare sites to collect, process, store, and transport biospecimens of high quality for future research.

The African Society of Human Genetics successfully launches global data science workshops

To accelerate the impact of African genomics on human health, data science skills and awareness of Africa's rich genetic diversity must be strengthened globally. We describe the first African genomics data science workshop, implemented by the African Society of Human Genetics (AfSHG) and international partners, providing a framework for future workshops.

Variants of IL6, IL10, FCN2, RNASE3, IL12B and IL17B loci are associated with Schistosoma mansoni worm burden in the Albert Nile region of Uganda

BACKGROUND

Individuals genetically susceptible to high schistosomiasis worm burden may contribute disproportionately to transmission and could be prioritized for control. Identifying genes involved may guide development of therapy.

METHODOLOGY/PRINCIPAL FINDINGS

A cohort of 606 children aged 10-15 years were recruited in the Albert Nile region of Uganda and assessed for Schistosoma mansoni worm burden using the Up-Converting Particle Lateral Flow (UCP-LF) test detecting circulating anodic antigen (CAA), point-of-care Circulating Cathodic Antigen (POC-CCA) and Kato-Katz tests. Whole genome genotyping was conducted on 326 children comprising the top and bottom 25% of worm burden. Linear models were fitted to identify variants associated with worm burden in preselected candidate genes. Expression quantitative trait locus (eQTL) analysis was conducted for candidate genes with UCP-LF worm burden included as a covariate. Single Nucleotide Polymorphism loci associated with UCP-LF CAA included IL6 rs2066992 (OR = 0.43, p = 0.0006) and rs7793163 (OR = 2.0, p = 0.0007); IL21 SNP kgp513476 (OR 1.79, p = 0.0025) and IL17B SNP kgp708159 (OR = 0.35, p = 0.0028). A haplotype in the IL10 locus was associated with lower worm burden (OR = 0.53, p = 0.015) and overlapped SNPs rs1800896, rs1800871 and rs1800872. Significant haplotypes (p<0.05, overlapping significant SNP) associated with worm burden were observed in IL6 and the Th17 pathway IL12B and IL17B genes. There were significant eQTL in the IL6, IL5, IL21, IL25 and IFNG regions.

CONCLUSIONS

Variants associated with S. mansoni worm burden were in IL6, FCN2, RNASE3, IL10, IL12B and IL17B gene loci. However only eQTL associations remained significant after Bonferroni correction. In summary, immune balance, pathogen recognition and Th17 pathways may play a role in modulating Schistosoma worm burden. Individuals carrying risk variants may be targeted first in allocation of control efforts to reduce the burden of schistosomiasis in the community.

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.

Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations

Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized that methods that leverage shared regulatory effects across different conditions, in this case, across different populations, may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWASs) using different methods (elastic net, joint-tissue imputation [JTI], matrix expression quantitative trait loci [Matrix eQTL], multivariate adaptive shrinkage in R [MASHR], and transcriptome-integrated genetic association resource [TIGAR]) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios. Additionally, to evaluate model applicability in TWASs, we integrated publicly available multiethnic genome-wide association study (GWAS) summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study and Pan-ancestry genetic analysis of the UK Biobank (PanUKBB) with our developed transcriptome prediction models. In regard to transcriptome prediction accuracy, MASHR models performed better or the same as other methods in both population-matched and cross-population transcriptome predictions. Furthermore, in multiethnic TWASs, MASHR models yielded more discoveries that replicate in both PAGE and PanUKBB across all methods analyzed, including loci previously mapped in GWASs and loci previously not found in GWASs. Overall, our study demonstrates the importance of using methods that benefit from different populations' effect size estimates in order to improve TWASs for multiethnic or underrepresented populations.

Genetic and environmental contributions to ancestry differences in gene expression in the human brain

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson's disease, and 30% of heritability for Alzhemier's disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness.

Genome-wide association study of esophageal squamous cell cancer identifies shared and distinct risk variants in African and Chinese populations

Esophageal squamous cell carcinoma (ESCC) has a high disease burden in sub-Saharan Africa and has a very poor prognosis. Genome-wide association studies (GWASs) of ESCC in predominantly East Asian populations indicate a substantial genetic contribution to its etiology, but no genome-wide studies have been done in populations of African ancestry. Here, we report a GWAS in 1,686 African individuals with ESCC and 3,217 population-matched control individuals to investigate its genetic etiology. We identified a genome-wide-significant risk locus on chromosome 9 upstream of FAM120A (rs12379660, p = 4.58 × 10-8, odds ratio = 1.28, 95% confidence interval = 1.22-1.34), as well as a potential African-specific risk locus on chromosome 2 (rs142741123, p = 5.49 × 10-8) within MYO1B. FAM120A is a component of oxidative stress-induced survival signals, and the associated variants at the FAM120A locus co-localized with highly significant cis-eQTLs in FAM120AOS in both esophageal mucosa and esophageal muscularis tissue. A trans-ethnic meta-analysis was then performed with the African ESCC study and a Chinese ESCC study in a combined total of 3,699 ESCC-affected individuals and 5,918 control individuals, which identified three genome-wide-significant loci on chromosome 9 at FAM120A (rs12379660, pmeta = 9.36 × 10-10), chromosome 10 at PLCE1 (rs7099485, pmeta = 1.48 × 10-8), and chromosome 22 at CHEK2 (rs1033667, pmeta = 1.47 × 10-9). This indicates the existence of both shared and distinct genetic risk loci for ESCC in African and Asian populations. Our GWAS of ESCC conducted in a population of African ancestry indicates a substantial genetic contribution to ESCC risk in Africa.

Research participants' perception of ethical issues in stroke genomics and neurobiobanking research in Africa

Background

There is a growing interest in stroke genomics and neurobiobanking research in Africa. These raise several ethical issues, such as consent, re-use, data sharing, storage, and incidental result of biological samples. Despite the availability of ethical guidelines developed for research in Africa, there is paucity of information on how the research participants' perspectives could guide the research community on ethical issues in stroke genomics and neurobiobanking research. To explore African research participants' perspectives on these issues, a study was conducted at existing Stroke Investigation Research and Education Network (SIREN) sites in Nigeria and Ghana.

Method

Using an exploratory design, twenty-eight Focus Group Discussions (FGDs) sessions were conducted with stroke survivors (n=7), caregivers(n=7), stroke - free controls(n=7), and Community Advisory Board members(n=7). Data were collected using an interview guide. Interviews were conducted in English and indigenous languages of the community, audio recorded, and transcribed verbatim. Data were analyzed using NVivo (March, 2020) Software.

Result

Results revealed that stroke genomics and neurobiobanking research in Africa require researchers' direct attention to ethical issues. Concerns were raised about understanding, disclosure and absence of coercion as components of true autonomous decision making in research participation. Participants argued that the risk and benefits attached to participation should be disclosed at the time of recruitment. Fears around data sharing were voiced as adherence to the principle of privacy and confidentiality were of paramount importance to participants. The preference was to receive the results of incidental findings with no stigma attached from society.

Conclusion

Research participants' perspectives are a vital aspect of community engagement in stroke genomics and neurobiobanking research. Findings from this study suggest that research participants are interested in these fields of research in Africa if their concerns about ethical issues are appropriately addressed within the research framework.

The promise of data science for health research in Africa

Data science health research promises tremendous benefits for African populations, but its implementation is fraught with substantial ethical governance risks that could thwart the delivery of these anticipated benefits. We discuss emerging efforts to build ethical governance frameworks for data science health research in Africa and the opportunities to advance these through investments by African governments and institutions, international funding organizations and collaborations for research and capacity development.

Genetic variation in environmental enteropathy and stunting in Zambian children: A pilot genome wide association study using the H3Africa chip

PURPOSE

Stunting is known to be heavily influenced by environmental factors, so the genetic contribution has received little attention. Here we report an exploration of genetic influences in stunted Zambian children with environmental enteropathy.

METHOD

Children with stunting (LAZ < -2) were enrolled and given nutritional therapy. Those that were non-responsive to therapy were designated as cases, and children with good growth (LAZ > -1) from the same community as controls. Blood and stool samples were taken to measure biomarkers of intestinal inflammation, epithelial damage, and microbial translocation. Single nucleotide polymorphism array genotyping was carried out on saliva samples using the H3Africa consortium array.

RESULTS

Genome wide associations were analysed in 117 cases and 41 controls. While no significant associations with stunting were observed at P<5x10-8, likely due to the small sample size, interesting associations were observed at lower thresholds. SNPs associated with stunting were in genomic regions known to modulate neuronal differentiation and fatty acid biosynthesis. SNPs associated with increased microbial translocation were associated with non-integrin membrane ECM interactions, tight junctions, hemostasis, and G-alpha signalling events. SNPs associated with increased inflammation were associated with, ECM interactions, purine metabolism, axon guidance, and cell motility. SNPs negatively associated with inflammation overlapped genes involved in semaphoring interactions. We explored the existing coeliac disease risk HLA genotypes and found present: DQ2.5 (7.5%), DQ8 (3.5%) and DQ2.2 (3.8%); however, no children were positive for coeliac antibodies. We detected HLA-DRB:1301 and HLA-C:1802 with high odds ratios and P<0.05 in stunted children compared to controls.

CONCLUSION

Genetic variations associated with stunting and the enteropathy underlying it, include variants associated with multiple pathways relating to gene expression, glycosylation, nerve signalling, and sensing of the nutritional and microbiological milieu.

The future of lymphoma diagnosis, prognosis, and treatment monitoring in countries with limited access to pathology services

The world is moving towards precision medicine for cancer. This movement goes hand in hand with the development of newer advanced technologies for early, precise diagnosis of cancer and personalized treatment plans with fewer adverse effects for the patient. Liquid biopsy is one such advancement. At the same time, it has the advantage of minimal invasion and avoids serial invasive biopsies. In countries with limited access to pathology services, such as sub-Saharan Africa, liquid biopsy may provide an opportunity for early detection and prognostication of lymphoma. We discuss the current diagnostic modalities for lymphoma, highlighting the existing challenges with tissue biopsy, and how feasible it is for countries with limited pathology resources to leverage advancements made in the clinical application of liquid biopsy to improve lymphoma care.

A Journey from Blood Cells to Genes and Back

I was attracted to hematology because by combining clinical findings with the use of a microscope and simple laboratory tests, one could often make a diagnosis. I was attracted to genetics when I learned about inherited blood disorders, at a time when we had only hints that somatic mutations were also important. It seemed clear that if we understood not only what genetic changes caused what diseases but also the mechanisms through which those genetic changes contribute to cause disease, we could improve management. Thus, I investigated many aspects of the glucose-6-phosphate dehydrogenase system, including cloning of the gene, and in the study of paroxysmal nocturnal hemoglobinuria (PNH), I found that it is a clonal disorder; subsequently, we were able to explain how a nonmalignant clone can expand, and I was involved in the first trial of PNH treatment by complement inhibition. I was fortunate to do clinical and research hematology in five countries; in all of them, I learned from mentors, from colleagues, and from patients.

Strategies for the Genomic Analysis of Admixed Populations

Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.

Admixture mapping of peripheral artery disease in a Dominican population reveals a putative risk locus on 2q35

Peripheral artery disease (PAD) is a form of atherosclerotic cardiovascular disease, affecting ∼8 million Americans, and is known to have racial and ethnic disparities. PAD has been reported to have a significantly higher prevalence in African Americans (AAs) compared to non-Hispanic European Americans (EAs). Hispanic/Latinos (HLs) have been reported to have lower or similar rates of PAD compared to EAs, despite having a paradoxically high burden of PAD risk factors; however, recent work suggests prevalence may differ between sub-groups. Here, we examined a large cohort of diverse adults in the BioMe biobank in New York City. We observed the prevalence of PAD at 1.7% in EAs vs. 8.5% and 9.4% in AAs and HLs, respectively, and among HL sub-groups, the prevalence was found at 11.4% and 11.5% in Puerto Rican and Dominican populations, respectively. Follow-up analysis that adjusted for common risk factors demonstrated that Dominicans had the highest increased risk for PAD relative to EAs [OR = 3.15 (95% CI 2.33-4.25), p < 6.44 × 10-14]. To investigate whether genetic factors may explain this increased risk, we performed admixture mapping by testing the association between local ancestry and PAD in Dominican BioMe participants (N = 1,813) separately from European, African, and Native American (NAT) continental ancestry tracts. The top association with PAD was an NAT ancestry tract at chromosome 2q35 [OR = 1.96 (SE = 0.16), p < 2.75 × 10-05) with 22.6% vs. 12.9% PAD prevalence in heterozygous NAT tract carriers versus non-carriers, respectively. Fine-mapping at this locus implicated tag SNP rs78529201 located within a long intergenic non-coding RNA (lincRNA) LINC00607, a gene expression regulator of key genes related to thrombosis and extracellular remodeling of endothelial cells, suggesting a putative link of the 2q35 locus to PAD etiology. Efforts to reproduce the signal in other Hispanic cohorts were unsuccessful. In summary, we showed how leveraging health system data helped understand nuances of PAD risk across HL sub-groups and admixture mapping approaches elucidated a putative risk locus in a Dominican population.

From target discovery to clinical drug development with human genetics

The substantial investments in human genetics and genomics made over the past three decades were anticipated to result in many innovative therapies. Here we investigate the extent to which these expectations have been met, excluding cancer treatments. In our search, we identified 40 germline genetic observations that led directly to new targets and subsequently to novel approved therapies for 36 rare and 4 common conditions. The median time between genetic target discovery and drug approval was 25 years. Most of the genetically driven therapies for rare diseases compensate for disease-causing loss-of-function mutations. The therapies approved for common conditions are all inhibitors designed to pharmacologically mimic the natural, disease-protective effects of rare loss-of-function variants. Large biobank-based genetic studies have the power to identify and validate a large number of new drug targets. Genetics can also assist in the clinical development phase of drugs-for example, by selecting individuals who are most likely to respond to investigational therapies. This approach to drug development requires investments into large, diverse cohorts of deeply phenotyped individuals with appropriate consent for genetically assisted trials. A robust framework that facilitates responsible, sustainable benefit sharing will be required to capture the full potential of human genetics and genomics and bring effective and safe innovative therapies to patients quickly.

Bridging the diversity gap: Analytical and study design considerations for improving the accuracy of trans-ancestry genetic prediction

Genetic prediction of common complex disease risk is an essential component of precision medicine. Currently, genome-wide association studies (GWASs) are mostly composed of European-ancestry samples and resulting polygenic scores (PGSs) have been shown to poorly transfer to other ancestries partly due to heterogeneity of allelic effects between populations. Fixed-effects (FETA) and random-effects (RETA) trans-ancestry meta-analyses do not model such ancestry-related heterogeneity, while ancestry-specific (AS) scores may suffer from low power due to low sample sizes. In contrast, trans-ancestry meta-regression (TAMR) builds ancestry-aware PGS that account for more complex trans-ancestry architectures. Here, we examine the predictive performance of these four PGSs under multiple genetic architectures and ancestry configurations. We show that the predictive performance of FETA and RETA is strongly affected by cross-ancestry genetic heterogeneity, while AS PGS performance decreases in under-represented target populations. TAMR PGS is also impacted by heterogeneity but maintains good prediction performance in most situations, especially in ancestry-diverse scenarios. In simulations of human complex traits, TAMR scores currently explain 25% more phenotypic variance than AS in triglyceride levels and 33% more phenotypic variance than FETA in type 2 diabetes in most non-European populations. Importantly, a high proportion of non-European-ancestry individuals is needed to reach prediction levels that are comparable in those populations to the one observed in European-ancestry studies. Our results highlight the need to rebalance the ancestral composition of GWAS to enable accurate prediction in non-European-ancestry groups, and demonstrate the relevance of meta-regression approaches for compensating some of the current population biases in GWAS.

The genetics of autism spectrum disorder in an East African familial cohort

Autism spectrum disorder (ASD) is a group of complex neurodevelopmental conditions affecting communication and social interaction in 2.3% of children. Studies that demonstrated its complex genetic architecture have been mainly performed in populations of European ancestry. We investigate the genetics of ASD in an East African cohort (129 individuals) from a population with higher prevalence (5%). Whole-genome sequencing identified 2.13 million private variants in the cohort and potentially pathogenic variants in known ASD genes (including CACNA1C, CHD7, FMR1, and TCF7L2). Admixture analysis demonstrated that the cohort comprises two ancestral populations, African and Eurasian. Admixture mapping discovered 10 regions that confer ASD risk on the African haplotypes, containing several known ASD genes. The increased ASD prevalence in this population suggests decreased heterogeneity in the underlying genetic etiology, enabling risk allele identification. Our approach emphasizes the power of African genetic variation and admixture analysis to inform the architecture of complex disorders.

Optimal strategies for learning multi-ancestry polygenic scores vary across traits

Polygenic scores (PGSs) are individual-level measures that aggregate the genome-wide genetic predisposition to a given trait. As PGS have predominantly been developed using European-ancestry samples, trait prediction using such European ancestry-derived PGS is less accurate in non-European ancestry individuals. Although there has been recent progress in combining multiple PGS trained on distinct populations, the problem of how to maximize performance given a multiple-ancestry cohort is largely unexplored. Here, we investigate the effect of sample size and ancestry composition on PGS performance for fifteen traits in UK Biobank. For some traits, PGS estimated using a relatively small African-ancestry training set outperformed, on an African-ancestry test set, PGS estimated using a much larger European-ancestry only training set. We observe similar, but not identical, results when considering other minority-ancestry groups within UK Biobank. Our results emphasise the importance of targeted data collection from underrepresented groups in order to address existing disparities in PGS performance.

Hiding in plain sight: genetics of childhood steroid-resistant nephrotic syndrome in Sub-Saharan Africa

Steroid-resistant nephrotic syndrome (SRNS) is the most severe form of childhood nephrotic syndrome with an increased risk of progression to chronic kidney disease stage 5. Research endeavors to date have identified more than 80 genes that are associated with SRNS. Most of these genes regulate the structure and function of the podocyte, the visceral epithelial cells of the glomerulus. Although individuals of African ancestry have the highest prevalence of SRNS, especially those from Sub-Saharan Africa (SSA), with rates as high as 30-40% of all cases of nephrotic syndrome, studies focusing on the characterization and understanding of the genetic basis of SRNS in the region are negligible compared with Europe and North America. Therefore, it remains unclear if some of the variants in SRNS genes that are deemed pathogenic for SRNS are truly disease causing, and if the leading causes of monogenic nephrotic syndrome in other populations are the same for children in SSA with SRNS. Other implications of this lack of genetic data for SRNS in the region include the exclusion of children from the region from clinical trials aimed at identifying potential novel therapeutic agents for this severe form of nephrotic syndrome. This review underlines a need for concerted efforts to advance the genetic basis of SRNS in children in SSA. Such endeavors will complement global efforts at understanding the genetic basis of nephrotic syndrome.

Rare penetrant mutations confer severe risk of common diseases

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ~10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared with common-variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.

Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations

Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized methods that leverage shared regulatory effects across different conditions, in this case, across different populations may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWAS) using different methods (Elastic Net, Joint-Tissue Imputation (JTI), Matrix eQTL, Multivariate Adaptive Shrinkage in R (MASHR), and Transcriptome-Integrated Genetic Association Resource (TIGAR)) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios. Additionally, to evaluate model applicability in TWAS, we integrated publicly available multi-ethnic genome-wide association study (GWAS) summary statistics from the Population Architecture using Genomics and Epidemiology Study (PAGE) and Pan-UK Biobank with our developed transcriptome prediction models. In regard to transcriptome prediction accuracy, MASHR models performed better or the same as other methods in both population-matched and cross-population transcriptome predictions. Furthermore, in multi-ethnic TWAS, MASHR models yielded more discoveries that replicate in both PAGE and PanUKBB across all methods analyzed, including loci previously mapped in GWAS and new loci previously not found in GWAS. Overall, our study demonstrates the importance of using methods that benefit from different populations' effect size estimates in order to improve TWAS for multi-ethnic or underrepresented populations.

Reconstruction of the personal information from human genome reads in gut metagenome sequencing data

Human DNA present in faecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is presently unclear how much personal information can be reconstructed from such reads, and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable efficient use of human genetic information in stool samples, such as for research and forensics. Here we used genomic approaches to reconstruct personal information from the faecal metagenomes of 343 Japanese individuals with associated human genotype data. Genetic sex could be accurately predicted based on the sequencing depth of sex chromosomes for 97.3% of the samples. Individuals could be re-identified from the matched genotype data based on human reads recovered from the faecal metagenomic data with 93.3% sensitivity using a likelihood score-based method. This method also enabled us to predict the ancestries of 98.3% of the samples. Finally, we performed ultra-deep shotgun metagenomic sequencing of five faecal samples as well as whole-genome sequencing of blood samples. Using genotype-calling approaches, we demonstrated that the genotypes of both common and rare variants could be reconstructed from faecal samples. This included clinically relevant variants. Our approach can be used to quantify personal information contained within gut metagenome data.