Alzheimer's disease plasma biomarkers in a global cohort: experience from the DAWN study

Abstract Background The DAWN study aims to investigate Alzheimer's disease (AD) genetics and underlying biological markers in a global population including African Americans (AA: 4,000) and Hispanic/Latinos (HI: 4,000) ascertained in the US and indigenous Africans (AF: 5,000) through collaboration with the African Dementia Consortium (AfDC) from 10 African counties. These 13,000 participants include AD cases and individuals with mild (MCI) or no cognitive impairment (NCI). To understand the underlying blood‐based AD biomarkers profile of this unique cohort, we are analyzing the plasma levels of pTau181, neurofilament light chain (NFL), and Glial fibrillary acidic protein (GFAP). Method We measured pTau181 and NFL, and GFAP with Simoa chemistry using the pTau181 AdvantageV2 and NEUROLOGY 4‐PLEX A assays, respectively, on the Quanterix HD‐X instrument. Our preliminary cohort consisted of 174 AF (86 AD; 88 NCI) from Nigeria and Ghana study sites, 254 AA (24 AD; 102 MCI; 85 NCI), and 166 HI (44 AD; 61 MCI; 62 NCI). Linear mixed‐effect regression models adjusted for age, sex, population substructure and relatedness followed by Bonferroni correction were applied to identify biomarker differences. Result There were no significant differences between the ancestral groups within the diagnostic categories for any of the biomarkers measured. Plasma pTau181 concentrations were increased in AD relative to NCI in all three populations ( p = 5.1x10 ‐4 , 9.6x10 ‐5 , 5.1x10‐4 in AA, AF, and HI respectively) and AD relative to MCI ( p = 0.012, 0.0014 in AA and HI respectively), though no differences were noted between MCI and NCI. Interestingly, GFAP and NFL were highly significantly increased in AF AD vs NCI ( p = 4.5x10 ‐9 , 7.9x10 ‐7 for GFAP and NFL respectively) and in HI ( p = 7.9x10 ‐8 , 1.6x10 ‐6 for GFAP and NFL respectively), but no differences noted in AA. Conclusion These results suggest AD biomarkers are generalizable across global populations, with baseline values being consistent. However, there are notable differences, particularly in NFL and GFAP levels, which may reflect underlying differences in environmental or genetic influences on AD. Ultimately, increasing sample sizes and combining genomic, biomarker, and social and environmental data will increase understanding of genetic risk of AD.