Dementia is a progressive and debilitating neurological disease that affects millions of people worldwide. Identifying the minimally invasive biomarkers associated with dementia that could provide insights into the disease pathogenesis, improve early diagnosis, and facilitate the development of effective treatments is pressing. Proteomic studies have emerged as a promising approach for identifying the protein biomarkers associated with dementia. This pilot study aimed to investigate the plasma proteome profile and identify a panel of various protein biomarkers for dementia. We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. There was also the dysregulation of 153 plasma proteins in individuals with dementia compared with those with MCI, and machine learning algorithms identified 8 biomarkers that classified dementia from MCI with an AUC of 0.87 ± 0.07. Moreover, multiple proteins selected in both diagnostic panels such as NEFL, IL17D, WNT9A, and PGF were negatively correlated with cognitive performance, with a correlation coefficient (r²) ≤ −0.47. Gene Ontology (GO) and pathway analysis of dementia-associated proteins implicated immune response, vascular injury, and extracellular matrix organization pathways in dementia pathogenesis. In conclusion, the combination of high-throughput proteomics and machine learning enabled us to identify a blood-based protein signature capable of potentially differentiating dementia from MCI and cognitively normal controls. Further research is required to validate these biomarkers and investigate the potential underlying mechanisms for the development of dementia.

Obesity promotes premature aging and dysfunction of white adipose tissue (WAT) through the accumulation of cellular senescence. The senescent cells burden in WAT has been linked to inflammation, insulin-resistance (IR), and type 2 diabetes (T2D). There is limited knowledge about molecular mechanisms that sustain inflammation in obese states. Here, we describe a robust and physiologically relevant in vitro system to trigger senescence in mouse 3T3-L1 preadipocytes. By employing transcriptomics analyses, we discovered up-regulation of key pro-inflammatory molecules and activation of interferon/signal transducer and activator of transcription (STAT)1/3 signaling in senescent preadipocytes, and expression of downstream targets was induced in epididymal WAT of obese mice, and obese human adipose tissue. To test the relevance of STAT1/3 signaling to preadipocyte senescence, we used Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated protein 9 (CRISPR/Cas9) technology to delete STAT1/3 and discovered that STAT1 promoted growth arrest and cooperated with cyclic Guanosine Monophosphate-Adenosine Monophosphate (GMP-AMP) synthase-stimulator of interferon genes (cGAS-STING) to drive the expression of interferon β (IFNβ), C-X-C motif chemokine ligand 10 (CXCL10), and interferon signaling-related genes. In contrast, we discovered that STAT3 was a negative regulator of STAT1/cGAS-STING signaling—it suppressed senescence and inflammation. These data provide insights into how STAT1/STAT3 signaling coordinates senescence and inflammation through functional interactions with the cGAS/STING pathway.

There is an urgent need to find reliable and accessible blood-based biomarkers for early diagnosis of Parkinson's disease (PD) correlating with clinical symptoms and displaying predictive potential to improve future clinical trials. This led us to a conduct large-scale proteomics approach using an advanced high-throughput proteomics technology to create a proteomic profile for PD. Over 1300 proteins were measured in serum samples from a de novo Parkinson's (DeNoPa) cohort made up of 85 deep clinically phenotyped drug-naïve de novo PD patients and 93 matched healthy controls (HC) with longitudinal clinical follow-up available of up to 8 years. The analysis identified 73 differentially expressed proteins (DEPs) of which 14 proteins were confirmed as stable potential diagnostic markers using machine learning tools. Among the DEPs identified, eight proteins-ALCAM, contactin 1, CD36, DUS3, NEGR1, Notch1, TrkB, and BTK- significantly correlated with longitudinal clinical scores including motor and non-motor symptom scores, cognitive function and depression scales, indicating potential predictive values for progression in PD among various phenotypes. Known functions of these proteins and their possible relation to the pathophysiology or symptomatology of PD were discussed and presented with a particular emphasis on the potential biological mechanisms involved, such as cell adhesion, axonal guidance and neuroinflammation, and T-cell activation. In conclusion, with the use of advance multiplex proteomic technology, a blood-based protein signature profile was identified from serum samples of a well-characterized PD cohort capable of potentially differentiating PD from HC and predicting clinical disease progression of related motor and non-motor PD symptoms. We thereby highlight the need to validate and further investigate these markers in future prospective cohorts and assess their possible PD-related mechanisms.

The COVID-19 pandemic has affected all individuals across the globe in some way. Despite large numbers of reported seroprevalence studies, there remains a limited understanding of how the magnitude and epitope utilization of the humoral immune response to SARS-CoV-2 viral anti-gens varies within populations following natural infection. Here, we designed a quantitative, multi-epitope protein microarray comprising various nucleocapsid protein structural motifs, including two structural domains and three intrinsically disordered regions. Quantitative data from the microarray provided complete differentiation between cases and pre-pandemic controls (100% sensitivity and specificity) in a case-control cohort (n = 100). We then assessed the influence of disease severity, age, and ethnicity on the strength and breadth of the humoral response in a multi-ethnic cohort (n = 138). As expected, patients with severe disease showed significantly higher antibody titers and interestingly also had significantly broader epitope coverage. A significant increase in antibody titer and epitope coverage was observed with increasing age, in both mild and severe disease, which is promising for vaccine efficacy in older individuals. Additionally, we observed significant differences in the breadth and strength of the humoral immune response in relation to ethnicity, which may reflect differences in genetic and lifestyle factors. Furthermore, our data enabled localization of the immuno-dominant epitope to the C-terminal structural domain of the viral nucleocapsid protein in two independent cohorts. Overall, we have designed, validated, and tested an advanced serological assay that enables accurate quantitation of the humoral response post natural infection and that has revealed unexpected differences in the magnitude and epitope utilization within a population.

The majority of α-synuclein (α-syn) within Lewy bodies (LBs) has been reported to be phosphorylated at serine 129 (pS129-α-syn), suggesting a central role for phosphorylation in the pathogenesis of Parkinson's disease (PD) and related synucleinopathies. Various studies have investigated the effect of α-syn phosphorylation but have failed to reach a consensus as to whether this modification accelerates or inhibits α-syn aggregation. Nevertheless, pS129-α-syn is a reliable marker of α-syn aggregates and is widely evaluated in biomarkers and post-mortem studies. While several antibodies specific for pS129-α-syn exist, their reactivity with non-specific antigens appears to be a common challenge. To gain valuable insights into the role of α-syn phosphorylation in disease pathogenesis, antibodies that are highly specific to pS129-α-syn are necessary. In this study, we describe the generation of three mouse monoclonal antibodies (mAbs; 5B9, 6H5 and 9G1) using hybridoma technology. These were thoroughly characterized and validated in combination with our previously generated mAb (PS129), and the commercial ab51253 (Abcam). We demonstrated that our mAbs are highly specific for pS129-α-syn and do not cross react with wild-type α-syn. Results from staining of post-mortem human brain tissue showed that our mAbs detect pS129-α-syn pathology in patients with synucleinopathies. This study highlights three new antibodies as excellent and highly specific research tools to explore the role of pS129-α-syn inclusions in synucleinopathies.

The aggregation of α-synuclein (α-syn) into neurotoxic oligomers and fibrils is an important pathogenic feature of synucleinopatheis, including Parkinson’s disease (PD). A further characteristic of PD is the oxidative stress that results in the formation of aldehydes by lipid peroxidation. It has been reported that the brains of deceased patients with PD contain high levels of protein oligomers that are cross-linked to these aldehydes. Increasing evidence also suggests that prefibrillar oligomeric species are more toxic than the mature amyloid fibrils. However, due to the heterogenous and metastable nature, characterization of the α-syn oligomeric species has been challenging. Here, we generated and characterized distinct α-syn oligomers in vitro in the presence of DA and lipid peroxidation products 4-hydroxy-2-nonenal (HNE) and 4-oxo-2-nonenal (ONE). HNE and ONE oligomer were stable towards the treatment with SDS, urea, and temperature. The secondary structure analysis revealed that only HNE and ONE oligomers contain β-sheet content. In the seeding assay, both DA and ONE oligomers significantly accelerated the aggregation. Furthermore, all oligomeric preparations were found to seed the aggregation of α-syn monomers in vitro and found to be cytotoxic when added to SH-SY5Y cells. Finally, both HNE and ONE α-syn oligomers can be used as a calibrator in an α-syn oligomers-specific ELISA.