Novel peptide‐driven global proteomics platform to identify unique peptide profiles linked to Alzheimer's disease. (20th December 2022)

• Record Type: Journal Article
• Authors: Saxena, Satya; Devanarayan, Viswanath; Ye, Yuanqing; Reyderman, Larisa; Koyama, Akihiko; Sachdev, Pallavi
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 6
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.066599
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: There is a growing need for new biomarker signature(s) to further improve the predictive values of currently used markers for Alzheimer's disease (AD) staging, monitoring, and prognostic prediction of disease progression. Most AD biomarker discovery studies have not focused on peptide level alterations despite unquestionable importance of abnormal proteolysis in AD. Here we present a peptide‐focused unbiased global proteomics platform to identify unique peptide profiles associated with amyloid pathology in cognitively impaired subjects. Method: We used the mass spectrometry (MS) data from a recently published multi‐cohort study (PRIDE archive PXD016278) using cerebrospinal fluid (CSF) from cognitively impaired AD (classified based on t‐tau > 400 ng/l, Aβ1–42 <550 ng/l and Aβ1–42/Aβ1–40 ratio <0.065) and non‐AD control participants. Data from the Sweden cohort was used for "discovery" and Magdeburg and Kiel cohort for "validation". RAW MS files were analyzed using a novel platform integrating a de novo ‐based workflow with comprehensive project‐specific hybrid spectral libraries to enable the identification of non‐tryptic and microbial peptides missed in traditional proteomics workflows. Raw intensities were quantile normalized and log transformed to reduce technical variation and ensure distribution symmetry. Differentially expressed peptides were identified via analysis of covariance after adjusting for age and gender, at 20% false discovery rate. Result: 1199 peptides identified as significant for amyloid positivity in discovery cohort were confirmed in an independent validation cohort. Most of the confirmed peptides demonstrate strong separation of amyloid (+) and amyloid (‐) subjects; 270 out of 1199 peptides had area under receiver operating characteristic curve (ROC‐AUC) over 90%, and 975 peptides had ROC‐AUC over 80%. Interestingly, 64.4% of CSF proteins identified as significant for amyloid positivity were altered only at the peptide‐level, including recently reported markers of AD progression such as VGF and PTPRN, underscoring the importance of tracking peptide‐based alterations in biomarker discovery. Conclusion: Our unbiased peptide‐focused global proteomics platform has yielded a unique profile of over 1000 novel peptide signatures linked to amyloid pathology. Further evaluation is ongoing to study the pathways and interactions associated with these unique peptide profiles, and their potential utility for disease staging, monitoring, and progression.