Historically, most psychiatric genetics research studies were undertaken in European-ancestry individuals. In the last decade, with the support of organizations such as the National Institutes of ...Mental Health (NIMH) and the Stanley Center for Psychiatric Research at the Broad Institute, ongoing large-scale psychiatric genetics studies have been conducted globally, focused on non-European ancestry populations. One such initiative is the Neuropsychiatric Genetics of African Populations (NeuroGAP). The NeuroGAP, the largest psychiatric genomics study conducted in Africa, aims to expand our understanding of the genetic and environmental causes of various neuropsychiatric disorders through large-scale sample collection and analyses. Studies such as the NeuroGAP provide critical information for gene discovery and allow the identification of true disease-causal gene variants. Equally important to advancing science is creating training and skill transfer opportunities for researchers in a way that allows for more equitable partnerships. In this presentation, I will provide my perspective as an early career investigator and alumnus of the Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER) program. The Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER) is a multi-year neuropsychiatric genetics training and career development program for African researchers. Some of the lessons I learned include the importance of forging mutually beneficial relationships between inter- and inter-continental collaborations; keeping expertise on the continent by minimizing brain drain; encouraging mentorship rather than supervision; having more funding mechanisms targeted to researchers in low research areas; meaningfully investing in research infrastructure and conducting research in a culturally informed way. Although not an exhaustive list of suggestions, these and others are essential to building capacity such that there's justice and equity in genetics research.
Asthma is a complex disease that varies widely in prevalence across populations. The extent to which genetic variation contributes to these disparities is unclear, as the genetics underlying asthma ...have been investigated primarily in populations of European descent. As part of the Global Biobank Meta-analysis Initiative, we conducted a large-scale genome-wide association study of asthma (153,763 cases and 1,647,022 controls) via meta-analysis across 22 biobanks spanning multiple ancestries. We discovered 179 asthma-associated loci, 49 of which were not previously reported. Despite the wide range in asthma prevalence among biobanks, we found largely consistent genetic effects across biobanks and ancestries. The meta-analysis also improved polygenic risk prediction in non-European populations compared with previous studies. Additionally, we found considerable genetic overlap between age-of-onset subtypes and between asthma and comorbid diseases. Our work underscores the multi-factorial nature of asthma development and offers insight into its shared genetic architecture.
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•22 biobank meta-analysis of >150k individuals with asthma discovers 49 novel loci•Genetic effects are consistent across ancestries and biobanks with varying prevalence•Greater ancestral diversity improves genetic discovery and risk prediction•Strong genetic correlations are observed between asthma subtypes and comorbidities
Tsuo et al. investigated genetic signatures underlying asthma using data from 22 biobanks worldwide. They demonstrate that the increased diversity and sample size of this resource can accelerate gene discovery, improve risk prediction, and advance our understanding of asthma’s shared genetic basis across populations and with related diseases.
African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of ...genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRSs) in simulations across Africa and in empirical data from South Africa, Uganda, and the United Kingdom to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South African individuals, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the United Kingdom versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.
Majara et al. show that polygenic scores generalize variably across diverse populations due to genetic differences between target and discovery cohorts. Multi-ancestry discovery GWAS typically improve prediction accuracy in underrepresented populations more than an increase in the European sample size, but not necessarily when sample sizes are imbalanced.
Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among ...study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.
With increasing representation of global populations in genetic studies, there is an opportunity for advanced methods development and a need for consensus “best practices” for analyzing datasets. We provide background on the scientific and ethical importance of including underrepresented groups in genetics research and offer guidance for genome-wide analysis of ancestrally diverse study cohorts.
The Psychiatric Genomics Consortium (PGC) has established an Africa Working Group with the objectives of pursuing funding, developing new policies and ethical frameworks, coordinating recruitment ...activities and training, facilitating integration of African PGC analysts, and undertaking large-scale analyses of African datasets, while promoting an inclusive clinical translation. In pursuing these objectives, the working group has conducted preliminary reviews and cohort inventories, gathering valuable insights and information to inform and shape future research efforts in Africa.
We conducted (a scoping review of published psychiatric genetics research in Africa,) member surveys of the areas of interest of working group members, and an inventory of existing cohorts with a focus on mental health conditions.
Our findings encompass the outcomes of the scoping review, member survey, and research database including a working inventory of ongoing research projects under each disorder of interest as well as genomic, population-level and longitudinal cohorts without a mental health focus (which are potential sources data).
While there is paucity of published literature on psychiatric genetics in Africa, there is a modest increase in the number of genomic studies on the continent. By building upon the achievements of projects such as H3Africa/H3ABionet and NeuroGAP, and fostering collaborations across health and population data infrastructure, we aspire to contribute to the sustainable and equitable expansion of psychiatric genetics research in Africa.
African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and ...comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa.
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Africa has immense genetic, linguistic, and cultural diversity. Here, we examine how languages relate to genetics across individuals from Ethiopia, Kenya, Uganda, and South Africa. We find self-reported language tags genetic variation, and we observe shifts in language transmission through three generations. African genetic variation is informative for broader variant interpretation.
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