{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T20:29:00Z","timestamp":1786739340027,"version":"build-2736575974"},"reference-count":55,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"6","license":[{"start":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:00:00Z","timestamp":1760227200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>Abstract:<\/jats:title>\n                  <jats:p>This review article is based upon the findings of the role of different biomarkers in the progression of the diseases. These findings were from past studies and meta-analysis of the biomarker in cardiovascular and chronic kidney diseases (CKDs). It mainly focuses on the organ crosstalk of diseases because of different biomarkers such as proteomics, genomics, metabolomics, and bioinformatics. In this reviewing process, we analyzed some biomarkers responsible for various cardiovascular and CKDs, out of which we found few biomarkers which are responsible for indication and diagnosis of disease relating to both the systems. It was found that the MiR-21, a type of genomic biomarker C-reactive protein, N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, and estimated glomerular filtration rate, types of proteomics biomarkers has shown role in the prediction of diseases. As well as we also reviewed research work from the past to analyze the relation between the disease and its clinical outcomes using machine learning, which can be used to create few models to predict the clinical outcomes. Out of all the algorithms used, they showing most promising results was XGBoost method. In the past, there were studies supporting the statement \u2013 algorithms created by the scientists gives variables relating to the disease. These variables can be used to predict the disease based on the levels of biomarkers present in the sample of the patients.<\/jats:p>","DOI":"10.4103\/ijp.ijp_66_24","type":"journal-article","created":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T10:00:07Z","timestamp":1762941607000},"page":"371-379","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":2,"title":["A comprehensive review on cardiovascular and chronic kidney disease interplay, exploring biomarkers and algorithmic approaches in unraveling organ crosstalk"],"prefix":"10.4103","volume":"57","author":[{"given":"Prashant","family":"Kumar","sequence":"first","affiliation":[{"name":"Department of Pharmacy, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yogendra","family":"Pal","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiv Dev","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shashi Bhooshan","family":"Tiwari","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2025,10,12]]},"reference":[{"key":"R1-20251112","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.dsx.2008.04.005","article-title":"Burden of non-communicable disease:Global overview","volume":"4","author":"Habib","year":"2010","journal-title":"Diabetes Metab Syndr Clin Res Rev"},{"key":"R2-20251112","doi-asserted-by":"crossref","first-page":"e1489","DOI":"10.1016\/S2214-109X(20)30358-2","article-title":"Burden of non-communicable diseases from infectious causes in 2017:A modelling study","volume":"8","author":"Coates","year":"2020","journal-title":"Lancet Glob Health"},{"key":"R3-20251112","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1079\/PHN2001298","article-title":"Cardiovascular diseases in the developing countries:Dimensions, determinants, dynamics and directions for public health action","volume":"5","author":"Reddy","year":"2002","journal-title":"Public Health Nutr"},{"key":"R4-20251112","article-title":"Cardiovascular disease","author":"Lopez","year":"2025","journal-title":"StatPearls"},{"key":"R5-20251112","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1001\/jama.2018.10897","article-title":"Screening for cervical cancer:US preventive services task force recommendation statement","volume":"320","author":"Curry","year":"2018","journal-title":"JAMA"},{"key":"R6-20251112","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1038\/ncpneph0673","article-title":"Cardiorenal versus renocardiac syndrome:Is there a difference?","volume":"3","author":"Schrier","year":"2007","journal-title":"Nat Clin Pract Nephrol"},{"key":"R7-20251112","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1159\/000329233","article-title":"Cardiorenal syndrome:A complex series of combined heart\/kidney disorders","volume":"174","author":"Goh","year":"2011","journal-title":"Controversies In Acute Kidney Injury"},{"key":"R8-20251112","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.amjmed.2019.05.047","article-title":"Relation of kidney function decline and NT-proBNP with risk of mortality and readmission in acute decompensated heart failure","volume":"133","author":"McCallum","year":"2020","journal-title":"Am J Med"},{"key":"R9-20251112","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1159\/000349968","article-title":"Pathophysiology of cardiorenal syndrome type 2 in stable chronic heart failure:Workgroup statements from the eleventh consensus conference of the Acute Dialysis Quality Initiative (ADQI)","volume":"182","author":"Cruz","year":"2013","journal-title":"ADQI Consensus on AKI Biomarkers and Cardiorenal Syndromes"},{"key":"R10-20251112","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1161\/CIRCULATIONAHA.106.683110","article-title":"Benchmarks for the assessment of novel cardiovascular biomarkers","volume":"115","author":"Morrow","year":"2007","journal-title":"Circulation"},{"key":"R11-20251112","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1136\/bmj.39063.689375.55","article-title":"Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance:Systematic review and meta-analysis","volume":"334","author":"Gillies","year":"2007","journal-title":"BMJ"},{"key":"R12-20251112","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1038\/clpt.2011.93","article-title":"Biomarkers for the prediction of type 2 diabetes and cardiovascular disease","volume":"90","author":"Herder","year":"2011","journal-title":"Clin Pharmacol Ther"},{"key":"R13-20251112","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1038\/nature09534","article-title":"Amap of human genome variation from population-scale sequencing","volume":"467","author":"Abecasis","year":"2010","journal-title":"Nature"},{"key":"R14-20251112","doi-asserted-by":"crossref","first-page":"e011468","DOI":"10.1161\/JAHA.118.011468","article-title":"Change in the NT-proBNP\/Mature BNP molar ratio precedes worsening renal function in patients with acute heart failure:A novel predictor candidate for cardiorenal syndrome","volume":"8","author":"Takahama","year":"2019","journal-title":"J Am Heart Assoc"},{"key":"R15-20251112","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1074\/mcp.R200007-MCP200","article-title":"The human plasma proteome:History, character, and diagnostic prospects","volume":"1","author":"Anderson","year":"2002","journal-title":"Mol Cell Proteomics"},{"key":"R16-20251112","doi-asserted-by":"crossref","first-page":"e13953","DOI":"10.1371\/journal.pone.0013953","article-title":"Metabolic footprint of diabetes:A multiplatform metabolomics study in an epidemiological setting","volume":"5","author":"Suhre","year":"2010","journal-title":"PLoS One"},{"key":"R17-20251112","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.1001\/jama.1995.03520400049043","article-title":"Evaluation of a rapid bedside assay for detection of serum cardiac troponin T","volume":"273","author":"Antman","year":"1995","journal-title":"JAMA"},{"key":"R18-20251112","first-page":"40","article-title":"Plasma proteomics to identify biomarkers\u2013application to cardiovascular diseases","volume":"7","author":"Beck","year":"2015","journal-title":"Transl Proteom"},{"key":"R19-20251112","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1159\/000349969","article-title":"Pathogenesis of cardiorenal syndrome type 1 in acute decompensated heart failure:Workgroup statements from the eleventh consensus conference of the Acute Dialysis Quality Initiative (ADQI)","volume":"182","author":"Haase","year":"2013","journal-title":"Contrib Nephrol"},{"key":"R20-20251112","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1146\/annurev-genom-082410-101446","article-title":"Personalized medicine:Progress and promise","volume":"12","author":"Chan","year":"2011","journal-title":"Annu Rev Genomics Hum Genet"},{"key":"R21-20251112","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1159\/000349971","article-title":"Cardiorenal syndrome type 3:Pathophysiologic and epidemiologic considerations","volume":"182","author":"Bagshaw","year":"2013","journal-title":"Contrib Nephrol"},{"key":"R22-20251112","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1159\/000349968","article-title":"Pathophysiology of cardiorenal syndrome type 2 in stable chronic heart failure:Workgroup statements from the eleventh consensus conference of the Acute Dialysis Quality Initiative (ADQI)","volume":"182","author":"Cruz","year":"2013","journal-title":"Contrib Nephrol"},{"key":"R23-20251112","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1159\/000349972","article-title":"Cardiorenal syndrome type 4:Insights on clinical presentation and pathophysiology from the eleventh consensus conference of the Acute Dialysis Quality Initiative (ADQI)","volume":"182","author":"Tumlin","year":"2013","journal-title":"ADQI Consensus on AKI Biomarkers and Cardiorenal Syndromes"},{"key":"R24-20251112","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1159\/000337714","article-title":"A single-centre study of acute cardiorenal syndrome:Incidence, risk factors and consequences","volume":"2","author":"Eren","year":"2012","journal-title":"Cardiorenal Med"},{"key":"R25-20251112","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.amjcard.2006.08.042","article-title":"Chronic kidney disease associated mortality in diastolic versus systolic heart failure:A propensity matched study","volume":"99","author":"Ahmed","year":"2007","journal-title":"Am J Cardiol"},{"key":"R26-20251112","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1093\/eurheartj\/ehi020","article-title":"The severe cardiorenal syndrome:'Guyton revisited'","volume":"26","author":"Bongartz","year":"2005","journal-title":"Eur Heart J"},{"key":"R27-20251112","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1161\/01.CIR.74.4.766","article-title":"Preservation of glomerular filtration rate in human heart failure by activation of the renin-angiotensin system","volume":"74","author":"Packer","year":"1986","journal-title":"Circulation"},{"key":"R28-20251112","doi-asserted-by":"crossref","first-page":"831","DOI":"10.3109\/00365510903307947","article-title":"Biological variation of cystatin C and creatinine","volume":"69","author":"Reinhard","year":"2009","journal-title":"Scand J Clin Lab Invest"},{"key":"R29-20251112","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1159\/000362650","article-title":"The hemodynamic and nonhemodynamic crosstalk in cardiorenal syndrome type 1","volume":"4","author":"Virz\u00ec","year":"2014","journal-title":"Cardiorenal Med"},{"key":"R30-20251112","doi-asserted-by":"crossref","first-page":"628","DOI":"10.1161\/CIRCHEARTFAILURE.111.962290","article-title":"Admission, discharge, or change in B-type natriuretic peptide and long-term outcomes:Data from organized program to initiate lifesaving treatment in hospitalized patients with heart failure (OPTIMIZE-HF) linked to medicare claims","volume":"4","author":"Kociol","year":"2011","journal-title":"Circ Heart Fail"},{"key":"R31-20251112","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1159\/000349966","article-title":"Pathophysiology of the cardiorenal syndromes:Executive summary from the eleventh consensus conference of the Acute Dialysis Quality Initiative (ADQI)","volume":"182","author":"McCullough","year":"2013","journal-title":"ADQI Consensus on AKI Biomarkers and Cardiorenal Syndromes"},{"key":"R32-20251112","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1111\/bjh.15955","article-title":"Cardiorenal AL amyloidosis:Risk stratification and outcomes based upon cardiac and renal biomarkers","volume":"186","author":"Rezk","year":"2019","journal-title":"Br J Haematol"},{"key":"R33-20251112","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1159\/000353593","article-title":"The role of fibroblast growth factor-23 in cardiorenal syndrome","volume":"123","author":"Kovesdy","year":"2013","journal-title":"Nephron Clin Pract"},{"key":"R34-20251112","first-page":"17","article-title":"New markers of cardio-renal links in chronic kidney disease","volume":"85","author":"Milovanova","year":"2013","journal-title":"Ter Arkh"},{"key":"R35-20251112","doi-asserted-by":"crossref","first-page":"e20","DOI":"10.3346\/jkms.2020.35.e20","article-title":"Hepcidin as a biomarker of cardiorenal syndrome","volume":"35","author":"Kim","year":"2020","journal-title":"J Korean Med Sci"},{"key":"R36-20251112","first-page":"229","article-title":"The urine podocin\/creatinine ratio as a novel biomarker of cardiorenal syndrome in dogs due to degenerative mitral valve disease","volume":"70","author":"Szczepankiewicz","year":"2019","journal-title":"J Physiol Pharmacol"},{"key":"R37-20251112","doi-asserted-by":"crossref","first-page":"e015452","DOI":"10.1161\/JAHA.119.015452","article-title":"Cardio-Renal biomarker soluble urokinase-type plasminogen activator receptor is associated with cardiovascular death and myocardial infarction in patients with coronary artery disease independent of troponin, C-reactive protein, and renal function","volume":"9","author":"Nikorowitsch","year":"2020","journal-title":"J Am Heart Assoc"},{"key":"R38-20251112","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1007\/s11255-021-02904-9","article-title":"Monocyte to HDL ratio:A novel marker of resistant hypertension in CKD patients","volume":"54","author":"Gembillo","year":"2022","journal-title":"Int Urol Nephrol"},{"key":"R39-20251112","doi-asserted-by":"crossref","first-page":"e6825","DOI":"10.1097\/MD.0000000000006825","article-title":"miRNAs as biomarkers for diagnosis of heart failure:A systematic review and meta-analysis","volume":"96","author":"Yan","year":"2017","journal-title":"Medicine (Baltimore)"},{"key":"R40-20251112","doi-asserted-by":"crossref","first-page":"374","DOI":"10.4161\/oxim.3.6.14787","article-title":"Mammalian target of rapamycin:Hitting the bull's-eye for neurological disorders","volume":"3","author":"Chong","year":"2010","journal-title":"Oxid Med Cell Longev"},{"key":"R41-20251112","doi-asserted-by":"crossref","first-page":"506","DOI":"10.5483\/BMBRep.2011.44.8.506","article-title":"The functions of mTOR in ischemic diseases","volume":"44","author":"Hwang","year":"2011","journal-title":"BMB Rep"},{"key":"R42-20251112","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1161\/CIRCRESAHA.116.303549","article-title":"Long noncoding RNAs and microRNAs in cardiovascular pathophysiology","volume":"116","author":"Thum","year":"2015","journal-title":"Circ Res"},{"key":"R43-20251112","doi-asserted-by":"crossref","first-page":"1484","DOI":"10.1161\/CIRCULATIONAHA.116.023686","article-title":"Long noncoding RNAs in cardiovascular pathology, diagnosis, and therapy","volume":"134","author":"B\u00e4r","year":"2016","journal-title":"Circulation"},{"key":"R44-20251112","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.freeradbiomed.2013.06.044","article-title":"Regulation of cardiac and renal ischemia-reperfusion injury by microRNAs","volume":"64","author":"Lorenzen","year":"2013","journal-title":"Free Radic Biol Med"},{"key":"R45-20251112","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1016\/j.kint.2018.06.033","article-title":"Noncoding RNAs in acute kidney injury","volume":"94","author":"Brandenburger","year":"2018","journal-title":"Kidney Int"},{"key":"R46-20251112","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.kint.2017.02.012","article-title":"Antagonism of profibrotic microRNA-21 improvesoutcome of murine chronic renal allograft dysfunction","volume":"92","author":"Schauerte","year":"2017","journal-title":"Kidney Int"},{"key":"R47-20251112","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s11010-015-2580-2","article-title":"MicroRNA21 promotes interstitial fibrosis via targeting DDAH1:A potential role in renal fibrosis","volume":"411","author":"Liu","year":"2016","journal-title":"Mol Cell Biochem"},{"key":"R48-20251112","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1038\/s41467-020-14349-2","article-title":"Preclinical development of a miR-132 inhibitor for heart failure treatment","volume":"11","author":"Foinquinos","year":"2020","journal-title":"Nat Commun"},{"key":"R49-20251112","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1038\/nsb0303-155","article-title":"An ACE structure","volume":"10","author":"Hooper","year":"2003","journal-title":"Nat Struct Biol"},{"key":"R50-20251112","doi-asserted-by":"crossref","first-page":"E1","DOI":"10.1161\/01.RES.87.5.e1","article-title":"Anovel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1-9","volume":"87","author":"Donoghue","year":"2000","journal-title":"Circ Res"},{"key":"R51-20251112","doi-asserted-by":"crossref","first-page":"2201","DOI":"10.1016\/j.arth.2019.05.055","article-title":"Artificial intelligence and machine learning in lower extremity arthroplasty:A review","volume":"34","author":"Haeberle","year":"2019","journal-title":"J Arthroplasty"},{"key":"R52-20251112","doi-asserted-by":"crossref","first-page":"114","DOI":"10.3390\/jpm12010114","article-title":"Predicting venous thrombosis in osteoarthritis using a machine learning algorithm:A population-based cohort study","volume":"12","author":"Lu","year":"2022","journal-title":"J Pers Med"},{"key":"R53-20251112","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1176\/appi.ajp.2016.16101169","article-title":"Machine learning and electronic health records:A paradigm shift","volume":"174","author":"Adkins","year":"2017","journal-title":"Am J Psychiatry"},{"key":"R54-20251112","doi-asserted-by":"crossref","first-page":"616","DOI":"10.3390\/jpm12040616","article-title":"Predicting the need for therapeutic intervention and mortality in acute pancreatitis:A two-center international study using machine learning","volume":"12","author":"Shi","year":"2022","journal-title":"J Pers Med"},{"key":"R55-20251112","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/S0014-5793(02)03640-2","article-title":"Quantitative mRNA expression profiling of ACE 2, a novel homologue of angiotensin converting enzyme","volume":"532","author":"Harmer","year":"2002","journal-title":"FEBS Lett"}],"container-title":["Indian Journal of Pharmacology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ovid.com\/10.4103\/ijp.ijp_66_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T19:28:10Z","timestamp":1786735690000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ovid.com\/10.4103\/ijp.ijp_66_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,12]]},"references-count":55,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.4103\/ijp.ijp_66_24","relation":{},"ISSN":["0253-7613","1998-3751"],"issn-type":[{"value":"0253-7613","type":"print"},{"value":"1998-3751","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,12]]},"assertion":[{"value":"2024-01-24","name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-15","name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}}]}}