Abstract
INTRODUCTION
There is an unmet need for tools to quantify dementia risk during its multi-decade preclinical/prodromal phase, given that current biomarkers predict risk over shorter follow-up periods and are specific to Alzheimer’s disease.
METHODS
Using high-throughput proteomic assays and machine learning techniques in the Atherosclerosis Risk in Communities study (n = 11,277), we developed the Dementia SomaSignal Test (dSST).
RESULTS
In addition to outperforming existing plasma biomarkers, the dSST predicted mid-life dementia risk over a 20-year follow-up across two independent cohorts with different ethnic backgrounds (areas under the curve [AUCs]: dSST 0.68–0.70, dSST+age 0.75–0.81). In a separate cohort, the dSST was associated with longitudinal declines across multiple cognitive domains, accelerated brain atrophy, and elevated measures of neuropathology (as evidenced by positron emission tomography and plasma biomarkers).
DISCUSSION
The dSST is a cost-effective, scalable, and minimally invasive protein-based prognostic aid that can quantify risk up to two decades before dementia onset.
Highlights
The Dementia SomaSignal Test (dSST) predicts 20-year dementia risk across two independent cohorts.
dSST outperforms existing plasma biomarkers in predicting multi-decade dementia risk.
dSST predicts cognitive decline and accelerated brain atrophy in a third cohort.
dSST is a prognostic aid that can predict dementia risk over two decades.
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This post is Copyright: Michael R. Duggan,
Clare Paterson,
Yifei Lu,
Hannah Biegel,
Heather E. Dark,
Jenifer Cordon,
Murat Bilgel,
Naoto Kaneko,
Masaki Shibayama,
Shintaro Kato,
Makio Furuichi,
Iwao Waga,
Keita Hiraga,
Masahisa Katsuno,
Yukiko Nishita,
Rei Otsuka,
Christos Davatzikos,
Guray Erus,
Kelsey Loupy,
Melissa Simpson,
Alexandria Lewis,
Abhay Moghekar,
Priya Palta,
Rebecca F. Gottesman,
Susan M. Resnick,
Josef Coresh,
Stephen A. Williams,
Keenan A. Walker | February 12, 2025