Clinical proteomics最新文献

{"title":"Human tear film protein sampling using soft contact lenses.","authors":"Robert K Roden, Nathan Zuniga, Joshua C Wright, David H Parkinson, Fangfang Jiang, Leena M Patil, Rebecca S Burlett, Alyssa A Nitz, Joshua J Rogers, Jarett T Pittman, Kenneth L Virgin, P Christine Ackroyd, Samuel H Payne, John C Price, Kenneth A Christensen","doi":"10.1186/s12014-024-09475-8","DOIUrl":"10.1186/s12014-024-09475-8","url":null,"abstract":"<p><strong>Background: </strong>Human tear protein biomarkers are useful for detecting ocular and systemic diseases. Unfortunately, existing tear film sampling methods (Schirmer strip; SS and microcapillary tube; MCT) have significant drawbacks, such as pain, risk of injury, sampling difficulty, and proteomic disparities between methods. Here, we present an alternative tear protein sampling method using soft contact lenses (SCLs).</p><p><strong>Results: </strong>We optimized the SCL protein sampling in vitro and performed in vivo studies in 6 subjects. Using Etafilcon A SCLs and 4M guanidine-HCl for protein removal, we sampled an average of 60 ± 31 µg of protein per eye. We also performed objective and subjective assessments of all sampling methods. Signs of irritation post-sampling were observed with SS but not with MCT and SCLs. Proteomic analysis by mass spectrometry (MS) revealed that all sampling methods resulted in the detection of abundant tear proteins. However, smaller subsets of unique and shared proteins were identified, particularly for SS and MCT. Additionally, there was no significant intrasubject variation between MCT and SCL sampling.</p><p><strong>Conclusions: </strong>These experiments demonstrate that SCLs are an accessible tear-sampling method with the potential to surpass current methods in sampling basal tears.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"23"},"PeriodicalIF":3.8,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140118971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neat plasma proteomics: getting the best out of the worst.","authors":"Ines Metatla, Kevin Roger, Cerina Chhuon, Sara Ceccacci, Manuel Chapelle, Pierre-Olivier Schmit, Vadim Demichev, Ida Chiara Guerrera","doi":"10.1186/s12014-024-09477-6","DOIUrl":"10.1186/s12014-024-09477-6","url":null,"abstract":"<p><p>Plasma proteomics holds immense potential for clinical research and biomarker discovery, serving as a non-invasive \"liquid biopsy\" for tissue sampling. Mass spectrometry (MS)-based proteomics, thanks to improvement in speed and robustness, emerges as an ideal technology for exploring the plasma proteome for its unbiased and highly specific protein identification and quantification. Despite its potential, plasma proteomics is still a challenge due to the vast dynamic range of protein abundance, hindering the detection of less abundant proteins. Different approaches can help overcome this challenge. Conventional depletion methods face limitations in cost, throughput, accuracy, and off-target depletion. Nanoparticle-based enrichment shows promise in compressing dynamic range, but cost remains a constraint. Enrichment strategies for extracellular vesicles (EVs) can enhance plasma proteome coverage dramatically, but current methods are still too laborious for large series. Neat plasma remains popular for its cost-effectiveness, time efficiency, and low volume requirement. We used a test set of 33 plasma samples for all evaluations. Samples were digested using S-Trap and analyzed on Evosep One and nanoElute coupled to a timsTOF Pro using different elution gradients and ion mobility ranges. Data were mainly analyzed using library-free searches using DIA-NN. This study explores ways to improve proteome coverage in neat plasma both in MS data acquisition and MS data analysis. We demonstrate the value of sampling smaller hydrophilic peptides, increasing chromatographic separation, and using library-free searches. Additionally, we introduce the EV boost approach, that leverages on the extracellular vesicle fraction to enhance protein identification in neat plasma samples. Globally, our optimized analysis workflow allows the quantification of over 1000 proteins in neat plasma with a 24SPD throughput. We believe that these considerations can be of help independently of the LC-MS platform used.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"22"},"PeriodicalIF":3.8,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10935919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140109554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomics of prostate cancer serum and plasma using low and high throughput approaches","authors":"Ghaith M. Hamza, Rekha Raghunathan, Stephanie Ashenden, Bairu Zhang, Eric Miele, Andrew F. Jarnuczak","doi":"10.1186/s12014-024-09461-0","DOIUrl":"https://doi.org/10.1186/s12014-024-09461-0","url":null,"abstract":"Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"23 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140106666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources","authors":"Sara R. Savage, Bing Zhang","doi":"10.1186/s12014-024-09473-w","DOIUrl":"https://doi.org/10.1186/s12014-024-09473-w","url":null,"abstract":"&lt;p&gt;Correction to: Clinical Proteomics (2023) 17:27&lt;/p&gt;&lt;p&gt;https://doi.org/10.1186/s12014-020-09290-x&lt;/p&gt;&lt;p&gt;In the main text, under the section heading “Knowledge bases of kinases and phosphatases“, 6th paragraph, the 3rd sentence that reads as “DEPOD used data from HuPho as a starting point and therefore contains much of the same information [19]” should have read as “DEPOD also includes pathways, substrates, and links to orthologs in addition to interacting partners and upstream kinases [19]”. The original article has been corrected.&lt;/p&gt;&lt;ul data-track-component=\"outbound reference\"&gt;&lt;li&gt;&lt;p&gt;Savage, S.R., Zhang, B. Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources. Clin Proteom. 2020;17:27. https://doi.org/10.1186/s12014-020-09290-x.&lt;/p&gt;&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;Download references&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-download-medium\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/p&gt;&lt;h3&gt;Authors and Affiliations&lt;/h3&gt;&lt;ol&gt;&lt;li&gt;&lt;p&gt;Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA&lt;/p&gt;&lt;p&gt;Sara R. Savage&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;p&gt;Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA&lt;/p&gt;&lt;p&gt;Sara R. Savage &amp; Bing Zhang&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;p&gt;Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA&lt;/p&gt;&lt;p&gt;Bing Zhang&lt;/p&gt;&lt;/li&gt;&lt;/ol&gt;&lt;span&gt;Authors&lt;/span&gt;&lt;ol&gt;&lt;li&gt;&lt;span&gt;Sara R. Savage&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;Bing Zhang&lt;/span&gt;View author publications&lt;p&gt;You can also search for this author in &lt;span&gt;PubMed&lt;span&gt; &lt;/span&gt;Google Scholar&lt;/span&gt;&lt;/p&gt;&lt;/li&gt;&lt;/ol&gt;&lt;h3&gt;Corresponding author&lt;/h3&gt;&lt;p&gt;Correspondence to Bing Zhang.&lt;/p&gt;&lt;h3&gt;Publisher’s Note&lt;/h3&gt;&lt;p&gt;Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.&lt;/p&gt;&lt;p&gt;The online version of the original article can be found at https://doi.org/10.1186/s12014-020-09290-x&lt;/p&gt;&lt;p&gt;&lt;b&gt;Open Access&lt;/b&gt; 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/. The Creative Commons Public Domain Dedication waiver","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Closing the gaps in patient management of dyslipidemia: stepping into cardiovascular precision diagnostics with apolipoprotein profiling.","authors":"Esther Reijnders, Arnoud van der Laarse, L Renee Ruhaak, Christa M Cobbaert","doi":"10.1186/s12014-024-09465-w","DOIUrl":"10.1186/s12014-024-09465-w","url":null,"abstract":"<p><p>In persons with dyslipidemia, a high residual risk of cardiovascular disease remains despite lipid lowering therapy. Current cardiovascular risk prediction mainly focuses on low-density lipoprotein cholesterol (LDL-c) levels, neglecting other contributing risk factors. Moreover, the efficacy of LDL-c lowering by statins resulting in reduced cardiovascular risk is only partially effective. Secondly, from a metrological viewpoint LDL-c falls short as a reliable measurand. Both direct and calculated LDL-c tests produce inaccurate test results at the low end under aggressive lipid lowering therapy. As LDL-c tests underperform both clinically and metrologically, there is an urging need for molecularly defined biomarkers. Over the years, apolipoproteins have emerged as promising biomarkers in the context of cardiovascular disease as they are the functional workhorses in lipid metabolism. Among these, apolipoprotein B (ApoB), present on all atherogenic lipoprotein particles, has demonstrated to clinically outperform LDL-c. Other apolipoproteins, such as Apo(a) - the characteristic apolipoprotein of the emerging risk factor lipoprotein(a) -, and ApoC-III - an inhibitor of triglyceride-rich lipoprotein clearance -, have attracted attention as well. To support personalized medicine, we need to move to molecularly defined risk markers, like the apolipoproteins. Molecularly defined diagnosis and molecularly targeted therapy require molecularly measured biomarkers. This review provides a summary of the scientific validity and (patho)physiological role of nine serum apolipoproteins, Apo(a), ApoB, ApoC-I, ApoC-II, ApoC-III, ApoE and its phenotypes, ApoA-I, ApoA-II, and ApoA-IV, in lipid metabolism, their association with cardiovascular disease, and their potential as cardiovascular risk markers when measured in a multiplex apolipoprotein panel.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"19"},"PeriodicalIF":3.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10908091/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140012359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic analysis of plasma proteins from patients with cardiac rupture after acute myocardial infarction using TMT-based quantitative proteomics approach.","authors":"Jingyuan Hou, Qiaoting Deng, Xiaohong Qiu, Sudong Liu, Youqian Li, Changjing Huang, Xianfang Wang, Qunji Zhang, Xunwei Deng, Zhixiong Zhong, Wei Zhong","doi":"10.1186/s12014-024-09474-9","DOIUrl":"10.1186/s12014-024-09474-9","url":null,"abstract":"<p><strong>Background: </strong>Cardiac rupture (CR) is a rare but catastrophic mechanical complication of acute myocardial infarction (AMI) that seriously threatens human health. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of CR has yet to be elucidated.</p><p><strong>Methods: </strong>In the present study, a quantitative approach with tandem mass tag (TMT) labeling and liquid chromatography-tandem mass spectrometry was used to characterize the differential protein expression profiles of patients with CR. Plasma samples were collected from patients with CR (n = 37), patients with AMI (n = 47), and healthy controls (n = 47). Candidate proteins were selected for validation by multiple reaction monitoring (MRM) and enzyme-linked immunosorbent assay (ELISA).</p><p><strong>Results: </strong>In total, 1208 proteins were quantified and 958 differentially expressed proteins (DEPs) were identified. The difference in the expression levels of the DEPs was more noticeable between the CR and Con groups than between the AMI and Con groups. Bioinformatics analysis showed most of the DEPs to be involved in numerous crucial biological processes and signaling pathways, such as RNA transport, ribosome, proteasome, and protein processing in the endoplasmic reticulum, as well as necroptosis and leukocyte transendothelial migration, which might play essential roles in the complex pathological processes associated with CR. MRM analysis confirmed the accuracy of the proteomic analysis results. Four proteins i.e., C-reactive protein (CRP), heat shock protein beta-1 (HSPB1), vinculin (VINC) and growth/differentiation factor 15 (GDF15), were further validated via ELISA. By receiver operating characteristic (ROC) analysis, combinations of these four proteins distinguished CR patients from AMI patients with a high area under the curve (AUC) value (0.895, 95% CI, 0.802-0.988, p < 0.001).</p><p><strong>Conclusions: </strong>Our study highlights the value of comprehensive proteomic characterization for identifying plasma proteome changes in patients with CR. This pilot study could serve as a valid foundation and initiation point for elucidation of the mechanisms of CR, which might aid in identifying effective diagnostic biomarkers in the future.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"18"},"PeriodicalIF":3.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10908035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140012360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic analysis of breast cancer based on immune subtypes.","authors":"Yeonjin Jeon, GunHee Lee, Hwangkyo Jeong, Gyungyub Gong, JiSun Kim, Kyunggon Kim, Jae Ho Jeong, Hee Jin Lee","doi":"10.1186/s12014-024-09463-y","DOIUrl":"10.1186/s12014-024-09463-y","url":null,"abstract":"<p><strong>Background: </strong>Immunotherapy is applied to breast cancer to resolve the limitations of survival gain in existing treatment modalities. With immunotherapy, a tumor can be classified into immune-inflamed, excluded and desert based on the distribution of immune cells. We assessed the clinicopathological features, each subtype's prognostic value and differentially expressed proteins between immune subtypes.</p><p><strong>Methods: </strong>Immune subtyping and proteomic analysis were performed on 56 breast cancer cases with neoadjuvant chemotherapy. The immune subtyping was based on the level of tumor-infiltrating lymphocytes (TILs) and Klintrup criteria. If the level of TILs was ≥ 10%, it was classified as immune-inflamed type without consideration of the Klintrup criteria. In cases of 1-9% TIL, Klintrup criteria 1-3 were classified as the immune-excluded subtype and Klintrup criteria not available (NA) was classified as NA. Cases of 1% TILs and Klintrup 0 were classified as the immune-desert subtype. Mass spectrometry was used to identify differentially expressed proteins in formalin-fixed paraffin-embedded biopsy tissues.</p><p><strong>Results: </strong>Of the 56 cases, 31 (55%) were immune-inflamed, 21 (38%) were immune-excluded, 2 (4%) were immune-desert and 2 (4%) were NA. Welch's t-test revealed two differentially expressed proteins between immune-inflamed and immune-excluded/desert subtypes. Coronin-1A was upregulated in immune-inflamed tumors (adjusted p = 0.008) and α-1-antitrypsin was upregulated in immune-excluded/desert tumors (adjusted p = 0.008). Titin was upregulated in pathologic complete response (pCR) than non-pCR among immune-inflamed tumors (adjusted p = 0.036).</p><p><strong>Conclusions: </strong>Coronin-1A and α-1-antitrypsin were upregulated in immune-inflamed and immune-excluded/desert subtypes, respectively. Titin's elevated expression in pCR within the immune-inflamed subtype may indicate a favorable prognosis. Further studies involving large representative cohorts are necessary to validate these findings.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"17"},"PeriodicalIF":3.8,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139995807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Highly sensitive therapeutic drug monitoring of infliximab in serum by targeted mass spectrometry in comparison to ELISA data.","authors":"Andreas Hentschel, Gina Piontek, Rob Dahlmann, Peter Findeisen, Roman Sakson, Phil Carbow, Thomas Renné, Yvonne Reinders, Albert Sickmann","doi":"10.1186/s12014-024-09464-x","DOIUrl":"10.1186/s12014-024-09464-x","url":null,"abstract":"<p><strong>Background: </strong>Presently, antibody concentration measurements for patients undergoing treatment are predominantly determined by ELISA, which still comes with known disadvantages. Therefore, our aim was to establish a targeted mass-spectrometric assay enabling the reproducible absolute quantification of peptides from the hypervariable and interaction regions of infliximab.</p><p><strong>Methods: </strong>Peptides of infliximab were measured post-trypsin digestion and subsequent separation on a Vanquish Horizon UHPLC coupled to a TSQ Altis Triple-Quad mass spectrometer. Normalization and absolute quantification were conducted using stable isotope-synthesized peptides. Calibration curves covering a range of 0.25-50 µg/ml were employed for quantitation.</p><p><strong>Results: </strong>We demonstrated the substantial influence of peptide selection, choice of hydrolase for digestion, and digestion time on absolute peptide yield (28-44% for peptide 1 and 64-97% for peptide 2). Furthermore, we showed that the generated calibration curves for absolute quantification were highly reproducible and robust (LLOQ1 0.72 µg/ml and LLOQ2 1.00 µg/ml) over several months. In comparison to ELISA values, the absolute values obtained by mass spectrometry often yielded lower results for both targeted peptides.</p><p><strong>Conclusions: </strong>In this study, a semi-automated workflow was employed and tested with 8 patients and corresponding replicates (n = 3-4). We demonstrated the robust implementation of calibration curves for the absolute quantification of infliximab in patient samples, with coefficients of variation ranging from 0.5 to 9%. Taken together, we have developed a platform enabling the rapid (2 days of sample preparation and 30 min of measurement time per sample) and robust quantification of Infliximab antibody concentration in patients. The use of mass spectrometry also facilitates the straightforward expansion of the method to include additional antibody peptides.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"16"},"PeriodicalIF":3.8,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905900/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139995806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic insights into the pathophysiology of hypertension-associated albuminuria: Pilot study in a South African cohort.","authors":"Melanie A Govender, Stoyan H Stoychev, Jean-Tristan Brandenburg, Michèle Ramsay, June Fabian, Ireshyn S Govender","doi":"10.1186/s12014-024-09458-9","DOIUrl":"10.1186/s12014-024-09458-9","url":null,"abstract":"<p><strong>Background: </strong>Hypertension is an important public health priority with a high prevalence in Africa. It is also an independent risk factor for kidney outcomes. We aimed to identify potential proteins and pathways involved in hypertension-associated albuminuria by assessing urinary proteomic profiles in black South African participants with combined hypertension and albuminuria compared to those who have neither condition.</p><p><strong>Methods: </strong>The study included 24 South African cases with both hypertension and albuminuria and 49 control participants who had neither condition. Protein was extracted from urine samples and analysed using ultra-high-performance liquid chromatography coupled with mass spectrometry. Data were generated using data-independent acquisition (DIA) and processed using Spectronaut™ 15. Statistical and functional data annotation were performed on Perseus and Cytoscape to identify and annotate differentially abundant proteins. Machine learning was applied to the dataset using the OmicLearn platform.</p><p><strong>Results: </strong>Overall, a mean of 1,225 and 915 proteins were quantified in the control and case groups, respectively. Three hundred and thirty-two differentially abundant proteins were constructed into a network. Pathways associated with these differentially abundant proteins included the immune system (q-value [false discovery rate] = 1.4 × 10^- 45), innate immune system (q = 1.1 × 10^- 32), extracellular matrix (ECM) organisation (q = 0.03) and activation of matrix metalloproteinases (q = 0.04). Proteins with high disease scores (76-100% confidence) for both hypertension and chronic kidney disease included angiotensinogen (AGT), albumin (ALB), apolipoprotein L1 (APOL1), and uromodulin (UMOD). A machine learning approach was able to identify a set of 20 proteins, differentiating between cases and controls.</p><p><strong>Conclusions: </strong>The urinary proteomic data combined with the machine learning approach was able to classify disease status and identify proteins and pathways associated with hypertension-associated albuminuria.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"15"},"PeriodicalIF":3.8,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10893729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139943978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent progress in mass spectrometry-based urinary proteomics.","authors":"Neha Joshi, Kishore Garapati, Vivek Ghose, Richard K Kandasamy, Akhilesh Pandey","doi":"10.1186/s12014-024-09462-z","DOIUrl":"10.1186/s12014-024-09462-z","url":null,"abstract":"<p><p>Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":"21 1","pages":"14"},"PeriodicalIF":2.8,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10885485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139930345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}