Unmasking Hidden Systemic Effects of Neurodegenerative Diseases: A Two-Pronged Approach to Biomarker Discovery

Identification of reliable blood biomarkers for neurodegenerative diseases (NDs) is crucial for translational and clinical research. However, conventional omics struggle with blood samples complexity, hindering desired outcomes. In this work the potential of High Molecular Weight (HMW) fractionation under non-denaturing conditions as a complementary approach to the conventional proteomics for identifying serum biomarkers in NDs was explored. A cohort of 58 serum samples of Alzheimer’s disease (AD), Parkinson’s disease (PD) patients and control (CT) individuals was used to compare the two proteomics strategies: i) direct analysis of whole serum and ii) non-denaturing fractionation using 300 kDa cut-off filters (HMW serum).Although both approaches quantified a similar set of proteins, each approach captured a distinct subset of differentially altered proteins, suggesting that HMW fractionation identified additional types of alterations beyond conventional protein level changes. A discriminant model combining altered proteins from both datasets effectively distinguished between the three groups (AUC = 0.999 and median sensitivity and specificity of 97.4% and 91.7%, respectively). Importantly, this performance surpassed that of any model created using each method individually.Altogether, this work demonstrated that HMW fractionation can be a valuable complementary method to direct serum analysis and could enhance biomarker discovery. The 10 proteins included in the model (5 from each strategy), comprise clear evidence for the contribution of apolipoproteins for the diagnosis of NDs, revealing potential changes within lipid metabolism and the organization of macromolecules and their complexes, thereby uncovering effects that remain hidden from a conventional serum proteome analysis.### Competing Interest StatementThe authors have declared no competing interest.* AD : Alzheimer’s Disease; APOA1-HDL : High-Density Lipoproteins containing Apolipoprotein A1; AUC : Area Under the Curve; Aβ : Amyloid-β; BBB : Blood-Brain Barrier; BioGRID : Biological General Repository for Interaction Datasets; CE : Collision Energy; CES : Collision Energy Spread; CHUC : Centro Hospitalar e Universitário de Coimbra; CI : Confidence Interval; CNS : Central Nervous System; CT : Healthy Controls; DDA : Data-dependent Acquisition; DMSO : Dimethyl Sulfoxide; FA : Formic Acid; FDR : False Discovery Rate; GO : Gene Ontology; HDL : High-Density Lipoproteins; HMW : High Molecular Weight; IS : Internal Standard; LDA : Linear Discriminant Analysis; MCI : Mild Cognitive Impairment; MS : Mass Spectrometry; MW : Molecular Weight; MWCO : Molecular Weight Cut-Off; NDs : Neurodegenerative Diseases; PD : Parkinson’s Disease; ROC : Receiver Operating Curve; SE : Standard Error; STRING : Search Tool for Retrieval of Interacting Genes/Proteins; XIC : Extracted Ion Chromatogram.