Associations Between Apolipoprotein A1, High-Density Lipoprotein Cholesterol, and Urinary Cytokine Levels in Elderly Males and Females

Quantitative proteomics based on TMT revealed the response of PK15 cells infected PEDV wild strain

Porcine epidemic diarrhea (PED), caused by porcine epidemic diarrhea virus (PEDV), is an acute and highly contagious enteric disease with a high mortality rate in suckling piglets. Identification of proteins associated with PEDV infection may provide insights into the pathogenesis of this viral disease. In this study, we employed tandem mass tag (TMT) quantitative protein analysis to investigate proteomic changes in PK15 cells following PEDV infection, and differential protein expression profiles were obtained at 0 h, 24 h, and 48 h post-infection. Overall, a total of 6330 proteins were identified. Applying criteria for fold change >1.5 < 0.67 and p-values <0.05 resulted in the identification of 59 up-regulated proteins and 103 down-regulated proteins that exhibited significant alterations in the H24 group compared to the H0 group. The H48 group demonstrated significant upregulation of 110 proteins and downregulation of 144 proteins compared to the H0 group; additionally, there were also 10 upregulated and 30 downregulated proteins in the H48 group when compared to the H24 group. These differentially expressed proteins (DEPs) were involved in immune response regulation, signal transduction, lipid transport and metabolism processes as well as cell apoptosis pathways. Based on these DEPs, we propose that PEDV may disrupt signal transduction pathways along with lipid transport and metabolism processes leading to maximal viral replication, it may also trigger inflammatory cascades accordingly. These findings could provide valuable information for elucidating specific pathogenesis related to PEDV infection while contributing towards developing new antiviral strategies.

Association of apolipoproteins and lipoprotein(a) with metabolic syndrome: a systematic review and meta-analysis

BACKGROUND & AIMS

Apolipoproteins and lipoprotein(a) are associated with various cardiometabolic diseases, including insulin resistance, diabetes mellitus, hypertension, dyslipidemia, among others. This systematic review and meta-analysis was conducted to evaluate the association of these markers with metabolic syndrome (MetS).

METHODS

We ran a systematic search through PubMed, Scopus, Embase, Ovid/Medline, and Web of Science on March 15, 2023. No language or date restrictions were applied. The only synthesised effect measure reported was the odds ratio (OR) with its corresponding 95% confidence interval (95% CI). We utilised the random-effects model for the quantitative synthesis.

RESULTS

We analysed 50 studies (n = 150 519) with different definitions for MetS. Increased ApoB values were associated with MetS (OR = 2.8; 95% CI: 2.44-3.22; p < 0.01, I² = 99%). Decreased ApoA1 values were associated with MetS (OR = 0.42; 95% CI: 0.38-0.47; p < 0.01, I² = 99%). Increased values of the ApoB/ApoA1 ratio were associated with MetS (OR = 4.97; 95% CI: 3.83-6.44; p < 0.01, I² = 97%). Decreased values of Lp(a) were associated with MetS (OR = 0.89; 95% CI: 0.82-0.96; p < 0.01; I² = 92%).

CONCLUSIONS

Increased values of ApoB and ApoB/ApoA1 ratio are associated with MetS, while decreased values of ApoA1 and Lp(a) are associated with MetS. These findings suggest that these lipid markers may serve as potential indicators for identifying subjects at risk of developing MetS. However, further research is required to elucidate the underlying mechanisms of these associations.

A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we used the Immuno-oncology panel and the Target 96 Oncology III panel to simultaneously detect the levels of 92 cancer-related proteins in serum, using a proximity extension assay. By applying this methodology, we identified 20 proteins, associated with the outcome at binary logistic regression, with a p-value below 0.01 for the first panel and 24 proteins with a p-value below 0.02 for the second one. The final multivariate logistic regression model, combining proteins from the two panels, generated a model with a sensitivity of 97.67% and a specificity of 83.72%. These results support the use of the proposed algorithm after a validation phase.

Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis

Understanding the dynamics of the human proteome is crucial for developing biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. The Proximity Extension Assay (PEA) is a technology that translates protein information into actionable knowledge by linking protein-specific antibodies to DNA-encoded tags. In this report we demonstrate how we have combined the unique PEA technology with an innovative and automated sample preparation and high-throughput sequencing readout enabling parallel measurement of nearly 1500 proteins in 96 samples generating close to 150,000 data points per run. This advancement will have a major impact on the discovery of new biomarkers for disease prediction and prognosis and contribute to the development of the rapidly evolving fields of wellness monitoring and precision medicine.

Apolipoprotein-AI and AIBP synergetic anti-inflammation as vascular diseases therapy: the new perspective

Vascular diseases (VDs) including pulmonary arterial hypertension (PAH), atherosclerosis (AS) and coronary arterial diseases (CADs) contribute to the higher morbidity and mortality worldwide. Apolipoprotein A-I (Apo A-I) binding protein (AIBP) and Apo-AI negatively correlate with VDs. However, the mechanism by which AIBP and apo-AI regulate VDs still remains unexplained. Here, we provide an overview of the role of AIBP and apo-AI regulation of vascular diseases molecular mechanisms such as vascular energy homeostasis imbalance, oxidative and endoplasmic reticulum stress and inflammation in VDs. In addition, the role of AIBP and apo-AI in endothelial cells (ECs), vascular smooth muscle (VSMCs) and immune cells activation in the pathogenesis of VDs are explained. The in-depth understanding of AIBP and apo-AI function in the vascular system may lead to the discovery of VDs therapy.

Arsenic Exposure and Cancer-Related Proteins in Urine of Indigenous Bolivian Women

Indigenous people living in the Bolivian Andes are exposed through their drinking water to inorganic arsenic, a potent carcinogen. However, the health consequences of arsenic exposure in this region are unknown. The aim of this study was to evaluate associations between arsenic exposure and changes in cancer-related proteins in indigenous women (n = 176) from communities around the Andean Lake Poopó, Bolivia. Arsenic exposure was assessed in whole blood (B-As) and urine (as the sum of arsenic metabolites, U-As) by inductively coupled plasma-mass spectrometry (ICP-MS). Cancer-related proteins (N = 92) were measured in urine using the proximity extension assay. The median B-As concentration was 2.1 (range 0.60-9.1) ng/g, and U-As concentration was 67 (12-399) μg/L. Using linear regression models adjusted for age, urinary osmolality, and urinary leukocytes, we identified associations between B-As and four putative cancer-related proteins: FASLG, SEZ6L, LYPD3, and TFPI2. Increasing B-As concentrations were associated with lower protein expression of SEZ6L, LYPD3, and TFPI2, and with higher expression of FASLG in urine (no association was statistically significant after correcting for multiple comparisons). The associations were similar across groups with different arsenic metabolism efficiency, a susceptibility factor for arsenic toxicity. In conclusion, arsenic exposure in this region was associated with changes in the expression of some cancer-related proteins in urine. Future research is warranted to understand if these proteins could serve as valid biomarkers for arsenic-related toxicity.