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      Effect of APOB polymorphism rs562338 (G/A) on serum proteome of coronary artery disease patients: a “proteogenomic” approach

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          Abstract

          In the current study, APOB ( rs1052031) genotype-guided proteomic analysis was performed in a cohort of Pakistani population. A total of 700 study subjects, including Coronary Artery Disease (CAD) patients (n = 480) and healthy individuals (n = 220) as a control group were included in the study. Genotyping was carried out by using tetra primer-amplification refractory mutation system-based polymerase chain reaction (T-ARMS-PCR) whereas mass spectrometry (Orbitrap MS) was used for label free quantification of serum samples. Genotypic frequency of GG genotype was found to be 90.1%, while 6.4% was for GA genotype and 3.5% was for AA genotypes in CAD patients. In the control group, 87.2% healthy subjects were found to have GG genotype, 11.8% had GA genotype, and 0.9% were with AA genotypes. Significant ( p = 0.007) difference was observed between genotypic frequencies in the patients and the control group. The rare allele AA was found to be strongly associated with the CAD [OR: 4 (1.9–16.7)], as compared to the control group in recessive genetic model ( p = 0.04). Using label free proteomics, altered expression of 60 significant proteins was observed. Enrichment analysis of these protein showed higher number of up-regulated pathways, including phosphatidylcholine-sterol O-acyltransferase activator activity, cholesterol transfer activity, and sterol transfer activity in AA genotype of rs562338 (G>A) as compared to the wild type GG genotype. This study provides a deeper insight into CAD pathobiology with reference to proteogenomics, and proving this approach as a good platform for identifying the novel proteins and signaling pathways in relation to cardiovascular diseases.

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          2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk

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            Andromeda: a peptide search engine integrated into the MaxQuant environment.

            A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.
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              Multi-omics approaches to disease

              High-throughput technologies have revolutionized medical research. The advent of genotyping arrays enabled large-scale genome-wide association studies and methods for examining global transcript levels, which gave rise to the field of “integrative genetics”. Other omics technologies, such as proteomics and metabolomics, are now often incorporated into the everyday methodology of biological researchers. In this review, we provide an overview of such omics technologies and focus on methods for their integration across multiple omics layers. As compared to studies of a single omics type, multi-omics offers the opportunity to understand the flow of information that underlies disease.
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                Author and article information

                Contributors
                munzihyder@yahoo.com
                awan.fr@gmail.com
                imran.riaz@uos.edu.pk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                23 November 2021
                23 November 2021
                2021
                : 11
                : 22766
                Affiliations
                [1 ]GRID grid.266518.e, ISNI 0000 0001 0219 3705, Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences ICCBS), , University of Karachi, ; Karachi, 75270 Pakistan
                [2 ]GRID grid.412782.a, ISNI 0000 0004 0609 4693, Department of Biotechnology, , University of Sargodha, ; Sargodha, Pakistan
                [3 ]GRID grid.419397.1, ISNI 0000 0004 0447 0237, Diabetes and Cardio-Metabolic Disorders Lab, Health Biotechnology Division, , National Institute for Biotechnology and Genetic Engineering (NIBGE), ; Jhang Road, P.O. Box. 577, Faisalabad, Pakistan
                [4 ]GRID grid.415422.4, ISNI 0000 0004 0607 131X, Allied Hospital, , Faisalabad Medical University, ; Faisalabad, Pakistan
                [5 ]Faisalabad Institute of Cardiology (FIC), Faisalabad, Pakistan
                [6 ]GRID grid.10825.3e, ISNI 0000 0001 0728 0170, Department of Biochemistry and Molecular Biology, , University of Southern Denmark, ; Odense, Denmark
                Article
                2211
                10.1038/s41598-021-02211-4
                8610978
                34815491
                4d9f4a7d-50f9-407e-8b3d-0c60bdd61aba
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 March 2021
                : 9 November 2021
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                © The Author(s) 2021

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                biotechnology,molecular biology
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                biotechnology, molecular biology

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