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Neurodegenerative diseases in Sub-Saharan Africa: diagnostic invisibility, biological heterogeneity and a precision-neuroscience agenda.

Created on 17 Oct 2026

Authors

Maulilio John Kipanyula

Published in

Neuroscience. Oct 16, 2026. Epub Oct 16, 2026.

Abstract

Neurodegenerative diseases (NDs) are increasingly recognised in Sub-Saharan Africa (SSA), but the principal scientific challenge is no longer simply to document a presumed hidden burden. It is to determine how much of the observed heterogeneity reflects underlying neurobiology and how much arises from age structure, case ascertainment, culturally sensitive phenotyping and unequal access to neurological diagnosis. This critical narrative review synthesises evidence from 2000 to July 2026 across epidemiology, disease mechanisms, genomics, biomarkers, environmental exposures, therapeutics and health systems, using Tanzania as an illustrative case rather than a regional proxy. Community studies demonstrate substantial diagnostic invisibility, while recent African-ancestry research shows that inclusion of genetically diverse populations can reveal mechanisms that are poorly captured in ancestry-restricted datasets. The glucosylceramidase beta 1 (GBA1) rs3115534-G Parkinson's disease signal provides a proof of principle, linking an African-ancestry-enriched association to altered ribonucleic acid (RNA) splicing and glucocerebrosidase biology. Emerging plasma biomarkers and ancestry-aware genomics create a route from syndromic diagnosis towards biological characterisation, but thresholds and models require population-specific validation. This review proposes that the next phase of African neurodegeneration research should integrate culturally valid phenotype, biomarkers, imaging, genomics, measured exposures and longitudinal outcomes from inception. Such platforms could distinguish measurement artefact from biological variation, improve regional diagnosis and test the global generalisability of prevailing models of neurodegeneration.

PMID:
42887722
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.

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