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Liu M, Zhang Y, Ye Z, He P, Zhou C, Yang S, Zhang Y, Gan X, Qin X. Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores. Heart 2024; 110:1270-1276. [PMID: 39237126 DOI: 10.1136/heartjnl-2024-324274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 08/21/2024] [Indexed: 09/07/2024] Open
Abstract
BACKGROUND Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank. METHODS We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score. RESULTS Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively). CONCLUSIONS A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.
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Affiliation(s)
- Mengyi Liu
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Yuanyuan Zhang
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Ziliang Ye
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Panpan He
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Chun Zhou
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Sisi Yang
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Yanjun Zhang
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Xiaoqin Gan
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Xianhui Qin
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
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Kuo C, Chen Z, Liu P, Pilling LC, Atkins JL, Fortinsky RH, Kuchel GA, Diniz BS. Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults. Aging Cell 2024; 23:e14195. [PMID: 38747160 PMCID: PMC11320350 DOI: 10.1111/acel.14195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/28/2024] Open
Abstract
Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2923 plasma proteins assessed using the Olink Explore 3072 assay®. 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death of 70.1 years. The Spearman correlation between PAC proteomic age and chronological age was 0.77. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC proteomic age deviation were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that biological age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.
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Affiliation(s)
- Chia‐Ling Kuo
- Department of Public Health SciencesUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
- The Cato T. Laurencin Institute for Regenerative EngineeringUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
| | - Zhiduo Chen
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
| | - Peiran Liu
- The Cato T. Laurencin Institute for Regenerative EngineeringUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
| | - Luke C. Pilling
- Epidemiology and Public Health Group, Department of Clinical and Biomedical SciencesUniversity of ExeterExeterUK
| | - Janice L. Atkins
- Epidemiology and Public Health Group, Department of Clinical and Biomedical SciencesUniversity of ExeterExeterUK
| | - Richard H. Fortinsky
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
| | - George A. Kuchel
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
| | - Breno S. Diniz
- Department of Public Health SciencesUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
- UConn Center on AgingUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
- Department of PsychiatryUniversity of Connecticut Health CenterFarmingtonConnecticutUSA
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3
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Machado FJDM, Marta-Enguita J, Gómez SU, Rodriguez JA, Páramo-Fernández JA, Herrera M, Zandio B, Aymerich N, Muñoz R, Bermejo R, Marta-Moreno J, López B, González A, Roncal C, Orbe J. Transcriptomic Analysis of Extracellular Vesicles in the Search for Novel Plasma and Thrombus Biomarkers of Ischemic Stroke Etiologies. Int J Mol Sci 2024; 25:4379. [PMID: 38673963 PMCID: PMC11050408 DOI: 10.3390/ijms25084379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 04/10/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Accurate etiologic diagnosis provides an appropriate secondary prevention and better prognosis in ischemic stroke (IS) patients; still, 45% of IS are cryptogenic, urging us to enhance diagnostic precision. We have studied the transcriptomic content of plasma extracellular vesicles (EVs) (n = 21) to identify potential biomarkers of IS etiologies. The proteins encoded by the selected genes were measured in the sera of IS patients (n = 114) and in hypertensive patients with (n = 78) and without atrial fibrillation (AF) (n = 20). IGFBP-2, the most promising candidate, was studied using immunohistochemistry in the IS thrombi (n = 23) and atrium of AF patients (n = 13). In vitro, the IGFBP-2 blockade was analyzed using thromboelastometry and endothelial cell cultures. We identified 745 differentially expressed genes among EVs of cardioembolic, atherothrombotic, and ESUS groups. From these, IGFBP-2 (cutoff > 247.6 ng/mL) emerged as a potential circulating biomarker of embolic IS [OR = 8.70 (1.84-41.13) p = 0.003], which was increased in patients with AF vs. controls (p < 0.001) and was augmented in cardioembolic vs. atherothrombotic thrombi (p < 0.01). Ex vivo, the blockage of IGFBP-2 reduced clot firmness (p < 0.01) and lysis time (p < 0.001) and in vitro, diminished endothelial permeability (p < 0.05) and transmigration (p = 0.06). IGFBP-2 could be a biomarker of embolic IS and a new therapeutic target involved in clot formation and endothelial dysfunction.
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Affiliation(s)
- Florencio J. D. M. Machado
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
| | - Juan Marta-Enguita
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
| | - Susan U. Gómez
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
| | - Jose A. Rodriguez
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - José Antonio Páramo-Fernández
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Hematology Department, Clinica Universidad de Navarra, 31008 Pamplona, Spain
| | - María Herrera
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
- Neurology Department, Hospital Universitario de Navarra, 31008 Pamplona, Spain
| | - Beatriz Zandio
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
- Neurology Department, Hospital Universitario de Navarra, 31008 Pamplona, Spain
| | - Nuria Aymerich
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
- Neurology Department, Hospital Universitario de Navarra, 31008 Pamplona, Spain
| | - Roberto Muñoz
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
- Neurology Department, Hospital Universitario de Navarra, 31008 Pamplona, Spain
| | - Rebeca Bermejo
- Neurointervencionist Radiology, Hospital Universitario de Navarra, 31008 Pamplona, Spain;
| | - Javier Marta-Moreno
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
- Neurology Department, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria de Aragón (IIS-Aragon), 50009 Zaragoza, Spain
| | - Begoña López
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Cardiovascular Diseases Program, Cima Universidad de Navarra, 31008 Pamplona, Spain
| | - Arantxa González
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Cardiovascular Diseases Program, Cima Universidad de Navarra, 31008 Pamplona, Spain
- Department of Pathology, Anatomy and Physiology, Universidad de Navarra, 31008 Pamplona, Spain
| | - Carmen Roncal
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Josune Orbe
- Laboratory of Atherothrombosis, Cima Universidad de Navarra, 31008 Pamplona, Spain; (F.J.D.M.M.); (J.M.-E.); (S.U.G.); (J.A.R.); (J.A.P.-F.); (C.R.)
- Instituto de Investigación Sanitaria de Navarra IdiSNA, 31008 Pamplona, Spain; (M.H.); (B.L.)
- Red de Investigación Cooperativa Orientada a Resultados en Salud (RICORS)-Ictus, Instituto Salud Carlos III, 28029 Madrid, Spain; (B.Z.); (N.A.); (R.M.); (J.M.-M.)
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 182] [Impact Index Per Article: 182.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Jonmundsson T, Steindorsdottir AE, Austin TR, Frick EA, Axelsson GT, Launer L, Psaty BM, Loureiro J, Orth AP, Aspelund T, Emilsson V, Floyd JS, Jennings L, Gudnason V, Gudmundsdottir V. A proteomic analysis of atrial fibrillation in a prospective longitudinal cohort (AGES-Reykjavik study). Europace 2023; 25:euad320. [PMID: 37967346 PMCID: PMC10685397 DOI: 10.1093/europace/euad320] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/01/2023] [Accepted: 10/06/2023] [Indexed: 11/17/2023] Open
Abstract
AIMS Atrial fibrillation (AF) is associated with high risk of comorbidities and mortality. Our aim was to examine causal and predictive relationships between 4137 serum proteins and incident AF in the prospective population-based Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) study. METHODS AND RESULTS The study included 4765 participants, of whom 1172 developed AF. Cox proportional hazards regression models were fitted for 4137 baseline protein measurements adjusting for known risk factors. Protein associations were tested for replication in the Cardiovascular Health Study (CHS). Causal relationships were examined in a bidirectional, two-sample Mendelian randomization analysis. The time-dependent area under the receiver operating characteristic curve (AUC)-statistic was examined as protein levels and an AF-polygenic risk score (PRS) were added to clinical risk models. The proteomic signature of incident AF consisted of 76 proteins, of which 63 (83%) were novel and 29 (38%) were replicated in CHS. The signature included both N-terminal prohormone of brain natriuretic peptide (NT-proBNP)-dependent (e.g. CHST15, ATP1B1, and SVEP1) and independent components (e.g. ASPN, AKR1B, and LAMA1/LAMB1/LAMC1). Nine causal candidates were identified (TAGLN, WARS, CHST15, CHMP3, COL15A1, DUSP13, MANBA, QSOX2, and SRL). The reverse causal analysis suggested that most AF-associated proteins were affected by the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide improved the prediction of incident AF events close to baseline with further improvements gained by the AF-PRS at all time points. CONCLUSION The AF proteomic signature includes biologically relevant proteins, some of which may be causal. It mainly reflects an NT-proBNP-dependent consequence of the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide is a promising marker for incident AF in the short term, but risk assessment incorporating a PRS may improve long-term risk assessment.
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Affiliation(s)
- Thorarinn Jonmundsson
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | | | - Thomas R Austin
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Elisabet A Frick
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Gisli T Axelsson
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | | | | | - Thor Aspelund
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Valur Emilsson
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | | | - Vilmundur Gudnason
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Holtasmari 1, Kopavogur 201, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
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Elenbaas JS, Jung IH, Coler-Reilly A, Lee PC, Alisio A, Stitziel NO. The emerging Janus face of SVEP1 in development and disease. Trends Mol Med 2023; 29:939-950. [PMID: 37673700 PMCID: PMC10592172 DOI: 10.1016/j.molmed.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/03/2023] [Accepted: 08/07/2023] [Indexed: 09/08/2023]
Abstract
Sushi, von Willebrand factor type A, EGF, and pentraxin domain containing 1 (SVEP1) is a large extracellular matrix protein that is also detected in circulation. Recent plasma proteomic and genomic studies have revealed a large number of associations between SVEP1 and human traits, particularly chronic disease. These include associations with cardiac death and disease, diabetes, platelet traits, glaucoma, dementia, and aging; many of these are causal. Animal models demonstrate that SVEP1 is critical in vascular development and disease, but its molecular and cellular mechanisms remain poorly defined. Future studies should aim to characterize these mechanisms and determine the diagnostic, prognostic, and therapeutic value of measuring or intervening on this enigmatic protein.
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Affiliation(s)
- Jared S Elenbaas
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA; Medical Scientist Training Program, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - In-Hyuk Jung
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Ariella Coler-Reilly
- Medical Scientist Training Program, Washington University School of Medicine, Saint Louis, MO 63110, USA; Division of Bone and Mineral Diseases, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Paul C Lee
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA; Medical Scientist Training Program, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Arturo Alisio
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Nathan O Stitziel
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA; McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO 63108, USA; Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110, USA.
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Mathews L, Hu X, Ding N, Ishigami J, Al Rifai M, Hoogeveen RC, Coresh J, Ballantyne CM, Selvin E, Matsushita K. Growth Differentiation Factor 15 and Risk of Bleeding Events: The Atherosclerosis Risk in Communities Study. J Am Heart Assoc 2023; 12:e023847. [PMID: 36927042 PMCID: PMC10111534 DOI: 10.1161/jaha.121.023847] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 01/05/2023] [Indexed: 03/18/2023]
Abstract
Background GDF15 (growth differentiation factor 15) is a potent predictor of bleeding in people with cardiovascular disease. However, whether GDF15 is associated with bleeding in individuals without a history of cardiovascular disease is unknown. Methods and Results The study population was from the ARIC (Atherosclerosis Risk in Communities) study. We studied the association of GDF15 with hospitalized bleeding events among 9205 participants (1993-1995) without prior bleeding and cardiovascular disease (mean age 60 years, 57% women, 21% Black). Plasma levels of GDF15 were measured in relative fluorescence units using DNA-based aptamer technology. Bleeding was ascertained using discharge codes. We examined hazard ratios (HRs) of incident bleeding using Cox models and risk prediction with the addition of GDF15 to clinical predictors of bleeding. There were 1328 hospitalizations with bleeding during a median follow-up of 22.5 years. The majority (76.5%) were because of gastrointestinal bleeding. The absolute incidence rate of bleeding per 1000 person-years was 11.64 in the highest quartile of GDF15 versus 5.22 in the lowest quartile. The highest versus lowest quartile of GDF15 demonstrated an adjusted HR of 2.00 (95% CI, 1.69-2.35) for total bleeding. The findings were consistent when we examined bleeding as the primary discharge diagnosis. The addition of GDF15 to clinical predictors of bleeding improved the C-statistic by 0.006 (0.002-0.011) from 0.684 to 0.690, P=0.008. Conclusions Higher levels of GDF15 were associated with bleeding events and improved the risk prediction beyond clinical predictors in individuals without cardiovascular disease.
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Affiliation(s)
- Lena Mathews
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
- Division of CardiologyCiccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of MedicineBaltimoreMD
| | - Xiao Hu
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
| | - Ning Ding
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
| | - Junichi Ishigami
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
| | - Mahmoud Al Rifai
- Division of CardiologyCiccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of MedicineBaltimoreMD
- Houston Methodist DeBakey Heart & Vascular CenterHoustonTX
| | - Ron C. Hoogeveen
- Department of Medicine, Section of Cardiovascular Research HoustonBaylor College of MedicineHoustonTX
| | - Josef Coresh
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
| | - Christie M. Ballantyne
- Department of Medicine, Section of Cardiovascular Research HoustonBaylor College of MedicineHoustonTX
| | - Elizabeth Selvin
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
| | - Kunihiro Matsushita
- Department of Epidemiology, Welch Center Department of Epidemiology, Prevention and Clinical ResearchJohns Hopkins Bloomberg School of Public HealthBaltimoreMD
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1460] [Impact Index Per Article: 1460.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Palà E, Escudero-Martínez I, Penalba A, Bustamante A, Lamana-Vallverdú M, Mancha F, Ocete RF, Piñero P, Galvao-Carmona A, Gómez-Herranz M, Pérez-Sánchez S, Moniche F, González A, Montaner J. Association of blood-based biomarkers with radiologic markers and cognitive decline in atrial fibrillation patients. J Stroke Cerebrovasc Dis 2022; 31:106833. [DOI: 10.1016/j.jstrokecerebrovasdis.2022.106833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 09/28/2022] [Accepted: 10/11/2022] [Indexed: 11/21/2022] Open
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10
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Jiang W, Jones JC, Shankavaram U, Sproull M, Camphausen K, Krauze AV. Analytical Considerations of Large-Scale Aptamer-Based Datasets for Translational Applications. Cancers (Basel) 2022; 14:2227. [PMID: 35565358 PMCID: PMC9105298 DOI: 10.3390/cancers14092227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/15/2022] [Accepted: 04/18/2022] [Indexed: 11/17/2022] Open
Abstract
The development and advancement of aptamer technology has opened a new realm of possibilities for unlocking the biocomplexity available within proteomics. With ultra-high-throughput and multiplexing, alongside remarkable specificity and sensitivity, aptamers could represent a powerful tool in disease-specific research, such as supporting the discovery and validation of clinically relevant biomarkers. One of the fundamental challenges underlying past and current proteomic technology has been the difficulty of translating proteomic datasets into standards of practice. Aptamers provide the capacity to generate single panels that span over 7000 different proteins from a singular sample. However, as a recent technology, they also present unique challenges, as the field of translational aptamer-based proteomics still lacks a standardizing methodology for analyzing these large datasets and the novel considerations that must be made in response to the differentiation amongst current proteomic platforms and aptamers. We address these analytical considerations with respect to surveying initial data, deploying proper statistical methodologies to identify differential protein expressions, and applying datasets to discover multimarker and pathway-level findings. Additionally, we present aptamer datasets within the multi-omics landscape by exploring the intersectionality of aptamer-based proteomics amongst genomics, transcriptomics, and metabolomics, alongside pre-existing proteomic platforms. Understanding the broader applications of aptamer datasets will substantially enhance current efforts to generate translatable findings for the clinic.
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Affiliation(s)
- Will Jiang
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA; (W.J.); (U.S.); (M.S.); (K.C.)
| | - Jennifer C. Jones
- Translational Nanobiology Section, Laboratory of Pathology, NIH/NCI/CCR, Bethesda, MD 20892, USA;
| | - Uma Shankavaram
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA; (W.J.); (U.S.); (M.S.); (K.C.)
| | - Mary Sproull
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA; (W.J.); (U.S.); (M.S.); (K.C.)
| | - Kevin Camphausen
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA; (W.J.); (U.S.); (M.S.); (K.C.)
| | - Andra V. Krauze
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA; (W.J.); (U.S.); (M.S.); (K.C.)
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