scholarly journals Aggregation of Omic Data and Secretome Prediction Enable the Discovery of Candidate Plasma Biomarkers for Beef Tenderness

2020 ◽  
Vol 21 (2) ◽  
pp. 664 ◽  
Author(s):  
Sabrina Boudon ◽  
Joelle Henry-Berger ◽  
Isabelle Cassar-Malek
Keyword(s):  
Plasma Proteins ◽  
Biological Information ◽  
Plasma Proteome ◽  
Complex Phenotype ◽  
Beef Tenderness ◽  
Plasma Biomarkers ◽  
Bovine Plasma ◽  
Computational Reconstruction ◽  
Beef Sector ◽  
Omic Data

Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome.

scholarly journals Dietary zinc depletion and repletion affects plasma proteins: an analysis of the plasma proteome

BioMetals ◽  
2012 ◽  
Vol 26 (1) ◽  
pp. 133-140 ◽  
Author(s):  
Arthur Grider ◽  
Kathie Wickwire ◽  
Emily Ho ◽  
Carolyn S. Chung ◽  
Janet King
Keyword(s):  
Plasma Proteins ◽  
Plasma Proteome ◽  
Dietary Zinc ◽  
Zinc Depletion

scholarly journals Plasma Biomarkers: Potent Screeners of Alzheimer’s Disease

2019 ◽  
Vol 34 (5) ◽  
pp. 290-301 ◽  
Author(s):  
Muhammad Naveed ◽  
Shamsa Mubeen ◽  
Abeer Khan ◽  
Sehrish Ibrahim ◽  
Bisma Meer
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Plasma Proteins ◽  
Great Accuracy ◽  
Vital Role ◽  
Brain Cell ◽  
Plasma Biomarkers ◽  
Factors Associated ◽  
Specificity And Sensitivity ◽  
Complex Chronic Disease

Alzheimer’s disease (AD), a neurological disorder, is as a complex chronic disease of brain cell death that usher to cognitive decline and loss of memory. Its prevalence differs according to risk factors associated with it and necropsy performs vital role in its definite diagnosis. The stages of AD vary from preclinical to severe that proceeds to death of patient with no availability of treatment. Biomarker may be a biochemical change that can be recognized by different emerging technologies such as proteomics and metabolomics. Plasma biomarkers, 5-protein classifiers, are readily being used for the diagnosis of AD and can also predict its progression with a great accuracy, specificity, and sensitivity. In this review, upregulation or downregulation of few plasma proteins in patients with AD has also been discussed, when juxtaposed with control, and thus serves as potent biomarker in the diagnosis of AD.

scholarly journals An atlas of genetic correlations between psychiatric disorders and human blood plasma proteome

2020 ◽  
Vol 63 (1) ◽  
Author(s):  
Shiqiang Cheng ◽  
Fanglin Guan ◽  
Mei Ma ◽  
Lu Zhang ◽  
Bolun Cheng ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Plasma Proteins ◽  
Genome Wide Association Study ◽  
Genetic Relationships ◽  
Genetic Correlations ◽  
Tumor Necrosis Factor Receptor ◽  
Autism Spectrum ◽  
Human Blood Plasma ◽  
Plasma Proteome ◽  
Genome Wide

Abstract Background. Psychiatric disorders are a group of complex psychological syndromes with high prevalence. Recent studies observed associations between altered plasma proteins and psychiatric disorders. This study aims to systematically explore the potential genetic relationships between five major psychiatric disorders and more than 3,000 plasma proteins. Methods. The genome-wide association study (GWAS) datasets of attention deficiency/hyperactive disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) were driven from the Psychiatric GWAS Consortium. The GWAS datasets of 3,283 human plasma proteins were derived from recently published study, including 3,301 study subjects. Linkage disequilibrium score (LDSC) regression analysis were conducted to evaluate the genetic correlations between psychiatric disorders and each of the 3,283 plasma proteins. Results. LDSC observed several genetic correlations between plasma proteins and psychiatric disorders, such as ADHD and lysosomal Pro-X carboxypeptidase (p value = 0.015), ASD and extracellular superoxide dismutase (Cu-Zn; p value = 0.023), BD and alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 6 (p value = 0.007), MDD and trefoil factor 1 (p value = 0.011), and SCZ and insulin-like growth factor-binding protein 6 (p value = 0.011). Additionally, we detected four common plasma proteins showing correlation evidence with both BD and SCZ, such as tumor necrosis factor receptor superfamily member 1B (p value = 0.012 for BD, p value = 0.011 for SCZ). Conclusions. This study provided an atlas of genetic correlations between psychiatric disorders and plasma proteome, providing novel clues for pathogenetic and biomarkers, therapeutic studies of psychiatric disorders.

Improvement of gluten-free bread properties by the incorporation of bovine plasma proteins and different saccharides into the matrix

2015 ◽  
Vol 170 ◽  
pp. 257-264 ◽  
Author(s):  
Laura T. Rodriguez Furlán ◽  
Antonio Pérez Padilla ◽  
Mercedes E. Campderrós
Keyword(s):  
Plasma Proteins ◽  
Gluten Free ◽  
Bovine Plasma ◽  
The Matrix ◽  
Bread Properties

Inulin like lyoprotectant of bovine plasma proteins concentrated by ultrafiltration

2010 ◽  
Vol 43 (3) ◽  
pp. 788-796 ◽  
Author(s):  
Laura T. Rodríguez Furlán ◽  
Antonio Pérez Padilla ◽  
Mercedes E. Campderrós
Keyword(s):  
Plasma Proteins ◽  
Bovine Plasma

scholarly journals Multi-platforms approach for plasma proteomics: complementarity of Olink PEA technology to mass spectrometry-based protein profiling

2020 ◽  
Author(s):  
Agnese Petrera ◽  
Christine von Toerne ◽  
Jennifer Behler ◽  
Cornelia Huth ◽  
Barbara Thorand ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Plasma Proteins ◽  
Biomarker Discovery ◽  
Dynamic Range ◽  
High Sensitivity ◽  
Living Organism ◽  
Protein Profiling ◽  
German Population ◽  
Plasma Proteome ◽  
Broad Dynamic Range

AbstractThe plasma proteome is the ultimate target for biomarker discovery. It stores an endless amount of information on the pathophysiological status of a living organism, which is however still difficult to comprehensively access. The high structural complexity of the plasma proteome can be addressed by either a system-wide and unbiased tool such as mass spectrometry (LC-MS/MS) or a highly sensitive targeted immunoassay such as the Proximity Extension Assays (PEA). In order to address relevant differences and important shared characteristics, we tested the performance of LC-MS/MS in data-dependent and -independent acquisition modes and PEA Olink to measure circulating plasma proteins in 173 human plasma samples from a Southern German population-based cohort. We demonstrated the measurement of more than 300 proteins with both LC-MS/MS approaches applied, mainly including high abundance plasma proteins. By the use of the PEA technology, we measured 728 plasma proteins, covering a broad dynamic range with high sensitivity down to pg/ml concentrations. In a next step, we quantified 35 overlapping proteins with all three analytical platforms, verifying the reproducibility of data distributions, measurement correlation and gender-based differential expression. Our work highlights the limitations and the advantages of both, targeted and untargeted approaches, and prove their complementary strengths. We demonstrated a significant gain in proteome coverage depth and subsequent biological insight by platforms combination – a promising approach for future biomarker and mechanistic studies.

scholarly journals Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

Biomedicines ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 162
Author(s):  
Nicolai Bjødstrup Palstrøm ◽  
Rune Matthiesen ◽  
Lars Melholt Rasmussen ◽  
Hans Christian Beck
Keyword(s):  
Cardiovascular Diseases ◽  
Human Plasma ◽  
Myocardial Infarct ◽  
Physiological State ◽  
Plasma Proteome ◽  
Cardiovascular Research ◽  
Acute Myocardial Infarct ◽  
Plasma Biomarkers ◽  
Vein Thrombosis ◽  
Human Plasma Proteome

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

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