{"title":"(Prote)omics for Superior Management of Kidney and Cardiovascular Disease-A Thought-Provoking Impulse From Nephrology.","authors":"Joachim Beige, Michael Masanneck","doi":"10.1002/pmic.202400143","DOIUrl":null,"url":null,"abstract":"<p><p>Chronic kidney disease (CKD) and cardiovascular disease (CVD) are complex conditions often managed by nephrologists. This viewpoint paper advocates for a multi-omics approach, integrating clinical symptom patterns, non-invasive biomarkers, imaging and invasive diagnostics to enhance diagnosis and treatment. Early detection of molecular changes, particularly in collagen turnover, is crucial for preventing disease progression. For instance, urinary proteomics can detect early molecular changes in diabetic kidney disease (DKD), heart failure (HF) and coronary artery disease (CAD), enabling proactive interventions and reducing the need for invasive procedures like renal biopsies. For example, urinary proteomic patterns can differentiate between glomerular and extraglomerular pathologies, aiding in the diagnosis of specific kidney diseases. Additionally, urinary peptides can predict CKD progression and HF development, offering a non-invasive alternative to traditional biomarkers like eGFR and NT-proBNP. The integration of multi-omics data with artificial intelligence (AI) holds promise for personalised treatment strategies, optimizing patient outcomes. This approach can also reduce healthcare costs by minimizing unnecessary invasive procedures and hospitalizations. In conclusion, the adoption of multi-omics and non-invasive biomarkers in nephrology and cardiology can revolutionize disease management, enabling early detection, personalised treatment and improved patient outcomes.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e202400143"},"PeriodicalIF":3.4000,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proteomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/pmic.202400143","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Chronic kidney disease (CKD) and cardiovascular disease (CVD) are complex conditions often managed by nephrologists. This viewpoint paper advocates for a multi-omics approach, integrating clinical symptom patterns, non-invasive biomarkers, imaging and invasive diagnostics to enhance diagnosis and treatment. Early detection of molecular changes, particularly in collagen turnover, is crucial for preventing disease progression. For instance, urinary proteomics can detect early molecular changes in diabetic kidney disease (DKD), heart failure (HF) and coronary artery disease (CAD), enabling proactive interventions and reducing the need for invasive procedures like renal biopsies. For example, urinary proteomic patterns can differentiate between glomerular and extraglomerular pathologies, aiding in the diagnosis of specific kidney diseases. Additionally, urinary peptides can predict CKD progression and HF development, offering a non-invasive alternative to traditional biomarkers like eGFR and NT-proBNP. The integration of multi-omics data with artificial intelligence (AI) holds promise for personalised treatment strategies, optimizing patient outcomes. This approach can also reduce healthcare costs by minimizing unnecessary invasive procedures and hospitalizations. In conclusion, the adoption of multi-omics and non-invasive biomarkers in nephrology and cardiology can revolutionize disease management, enabling early detection, personalised treatment and improved patient outcomes.
期刊介绍:
PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.