From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer’s disease

Topic/Product:
Alzheimer's, CNS Disease Panel 120
Disease Area:
Alzheimer's Disease
Sample Type:
Plasma

Abstract

Alzheimer’s disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations.
Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954–0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14–3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10−6), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54–57%) but increased to 73–80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Authors & Affiliations

aDepartment of Biomedical Engineering, Sakarya University of Applied Sciences, 54050 Serdivan, Sakarya, Turkey
bDepartment of Mechatronics Engineering, Sakarya University of Applied Sciences, 54050 Serdivan, Sakarya, Turkey

Steve Williams, MD, PhD

CSO

Dr. Willams serves as the company’s Chief Scientific Officer. He was previously Chief Medical Officer at Standard Biotools and at SomaLogic where he pioneered the discipline for discovery and validation of predictive, diagnostic and prognostic models using machine-learning applied to large-plex proteomics. 20 such tests were used for drug characterization, safety and efficacy when incorporated in clinical drug trials at Pharma/Biotech and 17 different multivariate tests were validated and translated into regulated healthcare uses. Prior to SomaLogic, Dr. Williams was at Pfizer in the UK and the USA as a clinical triallist in Translational Medicine, and subsequently as VP, Global Clinical Technology. He sat on the National Advisory Council for the National Institute of Biomedical Imaging and Bioengineering, the Executive Committee for the FNIH Biomarkers Consortium, and worked with FDA and PhRMA on developing evidentiary standards for biomarker qualification. Dr. William’s medical training was in London, at Charing Cross and Westminster Medical School, followed by a PhD in medicine/physiology at the same institution and training in Radiology at the University of Newcastle Upon Tyne. Steve is co-inventor on 26 proteomics patents and author/coauthor on multiple foundational proteomics manuscripts.

Justin McAnear

CFO

Mr. McAnear serves as the company’s Chief Financial Officer. He brings over 25 years of operational and financial leadership experience across various sectors and was instrumental in taking 10x Genomics public in 2019, serving as its CFO for over five years. Mr. McAnear served for over 3 years as Tesla’s VP of Worldwide Finance and Operations, supporting landmark initiatives such as the Model X and Model 3 launches and Solar City acquisition.  He also held various roles at Apple and J&J earlier in his career and served as a naval officer and aviator for over 9 years.