Abstract
Background The identification of reliable blood biomarkers for neurodegenerative Diseases (NDs) has been of pivotal importance in translational/clinical research. However, conventional omics struggle with the complexity of blood samples, which makes it difficult to achieve the desired goal. To address this, 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.
Methods 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). Univariate analysis was applied to the proteins quantified by each approach to identify the subset of proteins altered among the different groups (AD, PD and CT). Subsequently, linear discriminant analysis was performed using each subset of differently altered proteins, either individually or in combination, to construct the predictive models for the diseases under study and to identify a panel of potential biomarkers that could aid in the diagnosis of AD and PD.
Results Although both approaches quantified a similar set of proteins, it was observed that each approach capture a distinct subset of differentially altered proteins, suggesting that HMW fractionation is capable of identifying additional types of alterations beyond conventional protein level changes. The discriminant model created by combining altered proteins from both datasets demonstrated an impressive efficacy in distinguishing 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.
Conclusions 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 Statement
The authors have declared no competing interest.
Footnotes
E-mail addresses: Miguel Rosado - mmva.rosado{at}gmail.com; Ines Baldeiras - ibaldeiras{at}cnc.uc.pt; Andreia Gomes - andmaggomes{at}gmail.com; Diana Pires - diana.santos.pires{at}gmail.com; Cátia Santa - catiajmsanta{at}gmail.com; Joana Pinto - joana.amaralpinto{at}gmail.com; Cristina Januário - cristinajanuario{at}gmail.com; Isabel Santana - isabeljsantana{at}gmail.com; Ana Verdelho - averdelho{at}medicina.ulisboa.pt; Alexandre de Mendonça - mendonca{at}medicina.ulisboa.pt; Miguel Castelo-Branco - mcbranco{at}fmed.uc.pt.
Re-organization of the whole manuscript, including sectioning of supplementary results/files into additional files. New supplementary results added. Substantial alterations to the text of the manuscript, particularly in the Abstract, Results, and Discussion sections. Minor corrections to some figures.
List of abbreviations
- 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.