ReviewF1000Research2022
Polygenic Risk Score in African populations: progress and challenges.
Review in F1000Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 13 citations in OpenAlex.
- Genomic Landscape of Systemic Lupus Erythematosus and Lupus Nephritis Globally and the Gaps in Africa.International journal of molecular sciences · 2026Review
- Individual differences in effects of stressful life events on childhood ADHD: genetic, neural, and familial contributions.Journal of child psychology and psychiatry, and allied disciplines · 2026Article
- Behavioural and genetic correlates of malnutrition.The British journal of nutrition · 2026Article
- Polygenic risk and air pollution trends in relation to type 2 diabetes: evidence from the Taiwan Biobank.Diabetology & metabolic syndrome · 2026Article
- Polygenic risk and trajectories of depressive symptoms in diverse adolescents: Gene-environment interplay with family conflict and parental acceptance.Development and psychopathology · 2025Article
- Stakeholder experiences and perspectives of genetic and genomic screening procedures in the Gulf Cooperation Council (GCC) region: a qualitative exploration.Journal of community genetics · 2025Article
- Ancestry gaps in cardiovascular GWAS: a multi-database review of African representation in genomic studies.Frontiers in genetics · 2025Review
- A review of methods and software for polygenic risk score analysis.PeerJ. Computer science · 2025Article
- Genetic association and transferability for urinary albumin-creatinine ratio as a marker of kidney disease in four Sub-Saharan African populations and non-continental individuals of African ancestry.Frontiers in genetics · 2024Article
- PRS-ing Forward to Identify Genetic Risk in Idiopathic Pulmonary Fibrosis.American journal of respiratory and critical care medicine · 2023Article
- Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations.Communications biology · 2022Article
- Polygenic Risk Score in African populations: progress and challenges.F1000Research · 2022Review
- Performing post-genome-wide association study analysis: overview, challenges and recommendations.F1000Research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 3 countries.
Funding
Abstract
Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.