Work

Multi-tissue proteomics identifies molecular signatures for sporadic and genetically defined Alzheimer disease cases

Year: 2021

Type: preprint

Abstract: Alzheimer disease (AD) is a heterogeneous disease with many genes are associated with AD risk. Most proteomic studies, while instrumental in identifying AD pathways and genes, focus on single tissues and sporadic AD cases. Multi-tissue proteomic signatures for sporadic and genetically defined AD (e.g., pathogenic variant carriers in APP and PSEN1/2 and risk variant carriers in TREM2) will illuminate the biology of this heterogeneous disease.1,2 Here, we present one of the largest multi-tissue proteomic profiles, accessible through our web portal, based on 1,305 proteins in brain (n=360), cerebrospinal fluid (CSF; n=717), and plasma (n=490) from the Knight Alzheimer Disease Research Center (Knight ADRC) and Dominantly Inherited Alzheimer Network (DIAN) cohorts.3-5 We identified proteomic signatures in brain, CSF, and plasma for sporadic AD status and replicated these findings in multiple, independent datasets. The area under the curve (AUC) for CSF proteins was 0.89 in discovery and 0.90 in the replication dataset, which was significantly higher than the AUC for CSF p-tau181/Aβ42 (AUC = 0.81; P = 2.4×10-6). We also identified a specific proteomic signature for TREM2 variant carriers that differentiated TREM2 variant carriers from sporadic AD cases and controls with high sensitivity and specificity (AUC = 0.81 - 1). In addition, the proteins that showed differential levels in sporadic AD were also altered in autosomal dominant AD, but with greater effect size (1.4 times, P = 3.8×10-5), and proteins associated with autosomal dominant AD, in brain tissue also replicated on CSF (p=1.36×10-9). Enrichment analyses highlighted several pathways including AD (calcineurin, APOE, GRN), Parkinson disease (α-synuclein, LRRK2), and innate immune response (SHC1, MAPK3, SPP1) for the sporadic AD or TREM2 variant carriers. Our findings show the power of multi-tissue proteomics’ contribution to the understanding of AD biology and to the creation of tissue-specific prediction models for individuals with specific genetic profiles, ultimately supporting its utility in creating individualized disease risk evaluation and treatment.

Source: Research Square

DOI: 10.21203/rs.3.rs-923492/v1