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Elmore AR, Adhikari N, Hartley AE, Aparicio HJ, Posner DC, Hemani G, Tilling K, Gaunt TR, Wilson PW, Casas JP, Gaziano JM, Davey Smith G, Paternoster L, Cho K, Peloso GM. Protein Identification for Stroke Progression via Mendelian Randomization in Million Veteran Program and UK Biobank. Stroke 2024; 55:2045-2054. [PMID: 39038097 PMCID: PMC11259242 DOI: 10.1161/strokeaha.124.047103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 06/07/2024] [Indexed: 07/24/2024]
Abstract
BACKGROUND Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. METHODS We performed genome-wide association studies for subsequent major adverse cardiovascular events (MACE; ncases=51 929; ncontrols=39 980) and subsequent arterial ischemic stroke (AIS; ncases=45 120; ncontrols=46 789) after the first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (protein quantitative trait loci) to determine the effect of 1463 plasma protein abundances on subsequent MACE using Mendelian randomization. RESULTS Two variants were significantly associated with subsequent cardiovascular events: rs76472767 near gene RNF220 (odds ratio, 0.75 [95% CI, 0.64-0.85]; P=3.69×10-8) with subsequent AIS and rs13294166 near gene LINC01492 (odds ratio, 1.52 [95% CI, 1.37-1.67]; P=3.77×10-8) with subsequent MACE. Using Mendelian randomization, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 ([C-C motif chemokine 27], effect odds ratio, 0.77 [95% CI, 0.66-0.88]; adjusted P=0.05) and TNFRSF14 ([tumor necrosis factor receptor superfamily member 14], effect odds ratio, 1.42 [95% CI, 1.24-1.60]; adjusted P=0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. CONCLUSIONS We found evidence that 2 proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.
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Affiliation(s)
- Andrew R. Elmore
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Nimish Adhikari
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Department of Biostatistics, Boston University School of Public Health, MA (N.A., G.M.P.)
| | - April E. Hartley
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Hugo Javier Aparicio
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, MA (H.J.A.)
- Boston Medical Center, MA (H.J.A.)
| | - Daniel C. Posner
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
| | - Gibran Hemani
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Kate Tilling
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Tom R. Gaunt
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | | | - Juan P. Casas
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (J.P.C., J.M.G., K.C.)
| | - John Michael Gaziano
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (J.P.C., J.M.G., K.C.)
| | - George Davey Smith
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Lavinia Paternoster
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, United Kingdom (A.R.E., A.E.H., G.H., K.T., T.R.G., G.D.S., L.P.)
| | - Kelly Cho
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (J.P.C., J.M.G., K.C.)
| | - Gina M. Peloso
- Veteran’s Affairs Healthcare System, Boston, MA (N.A., D.C.P., J.P.C., J.M.G., K.C., G.M.P.)
- Department of Biostatistics, Boston University School of Public Health, MA (N.A., G.M.P.)
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Gao X, Luo W, Qu L, Yang M, Chen S, Lei L, Yan S, Liang H, Zhang X, Xiao M, Liao Y, Lee APW, Zhou Z, Chen J, Zhang Q, Wang Y, Xiu J. Genetic association of lipid-lowering drugs with aortic aneurysms: a Mendelian randomization study. Eur J Prev Cardiol 2024; 31:1132-1140. [PMID: 38302118 DOI: 10.1093/eurjpc/zwae044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/28/2024] [Accepted: 01/30/2024] [Indexed: 02/03/2024]
Abstract
AIMS The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA remains controversial. The study aimed to investigate the genetic association between lipid-lowering drugs and AA. METHODS AND RESULTS Our research used publicly available data on genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) studies. Genetic instruments, specifically eQTLs related to drug-target genes and SNPs (single nucleotide polymorphisms) located near or within the drug-target loci associated with low-density lipoprotein cholesterol (LDL-C), have been served as proxies for lipid-lowering medications. Drug-Target Mendelian Randomization (MR) study is used to determine the causal association between lipid-lowering drugs and different types of AA. The MR analysis revealed that higher expression of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase) was associated with increased risk of AA (OR = 1.58, 95% CI = 1.20-2.09, P = 1.20 × 10-03) and larger lumen size (aortic maximum area: OR = 1.28, 95% CI = 1.13-1.46, P = 1.48 × 10-04; aortic minimum area: OR = 1.26, 95% CI = 1.21-1.42, P = 1.78 × 10-04). PCSK9 (proprotein convertase subtilisin/kexin type 9) and CETP (cholesteryl ester transfer protein) show a suggestive relationship with AA (PCSK9: OR = 1.34, 95% CI = 1.10-1.63, P = 3.07 × 10-03; CETP: OR = 1.38, 95% CI = 1.06-1.80, P = 1.47 × 10-02). No evidence to support genetically mediated NPC1L1 (Niemann-Pick C1-Like 1) and LDLR (low-density lipoprotein cholesterol receptor) are associated with AA. CONCLUSION This study provides causal evidence for the genetic association between lipid-lowering drugs and AA. Higher gene expression of HMGCR, PCSK9, and CETP increases AA risk. Furthermore, HMGCR inhibitors may link with smaller aortic lumen size.
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Affiliation(s)
- Xiong Gao
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Wei Luo
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Liyuan Qu
- Department of Endocrinology, Boluo County People's Hospital, No. 1 Kangbo West Road, Luoyang Street, Boluo County, Huizhou City, Guangdong Province, China
| | - Miaomiao Yang
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Siyu Chen
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Li Lei
- Department of Cardiology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), 1017 Dongmen North Road, Luohu District, Shenzhen City, Guangdong Province, China
| | - Shaohua Yan
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Hongbin Liang
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Xinlu Zhang
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Min Xiao
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Yulin Liao
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Alex Pui-Wai Lee
- Division of Cardiology, Department of Medicine and Therapeutics, Prince of Wales Hospital and Laboratory of Cardiac Imaging and 3D Printing, Li Ka Shing Institute of Health Science, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong Special Administrative Region, China
| | - Zhongjiang Zhou
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Jiejian Chen
- Department of Medical Oncology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, No. 1 Panfu Road, Yuexiu District, Guangzhou City, Guangdong Province, China
| | - Qiuxia Zhang
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Yuegang Wang
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
| | - Jiancheng Xiu
- Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province 510515, China
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Lee PC, Jung IH, Thussu S, Patel V, Wagoner R, Burks KH, Amrute J, Elenbaas JS, Kang CJ, Young EP, Scherer PE, Stitziel NO. Instrumental variable and colocalization analyses identify endotrophin and HTRA1 as potential therapeutic targets for coronary artery disease. iScience 2024; 27:110104. [PMID: 38989470 PMCID: PMC11233907 DOI: 10.1016/j.isci.2024.110104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/26/2024] [Accepted: 05/22/2024] [Indexed: 07/12/2024] Open
Abstract
Coronary artery disease (CAD) remains a leading cause of disease burden globally, and there is a persistent need for new therapeutic targets. Instrumental variable (IV) and genetic colocalization analyses can help identify novel therapeutic targets for human disease by nominating causal genes in genome-wide association study (GWAS) loci. We conducted cis-IV analyses for 20,125 genes and 1,746 plasma proteins with CAD using molecular trait quantitative trait loci variant (QTLs) data from three different studies. 19 proteins and 119 genes were significantly associated with CAD risk by IV analyses and demonstrated evidence of genetic colocalization. Notably, our analyses validated well-established targets such as PCSK9 and ANGPTL4 while also identifying HTRA1 and endotrophin (a cleavage product of COL6A3) as proteins whose levels are causally associated with CAD risk. Further experimental studies are needed to confirm the causal role of the genes and proteins identified through our multiomic cis-IV analyses on human disease.
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Affiliation(s)
- Paul C. Lee
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, 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
| | - Shreeya Thussu
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Ved Patel
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Ryan Wagoner
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Kendall H. Burks
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Junedh Amrute
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Jared S. Elenbaas
- Center for Cardiovascular Research, Division of Cardiology, Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Chul Joo Kang
- McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO 63108, USA
| | - Erica P. Young
- 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
| | - Philipp E. Scherer
- Touchstone Diabetes Center, University of Texas Southwestern Medical Center, Dallas, TX, 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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Bayat A, Grimes H, de Boer E, Herlin MK, Dahl RS, Lund ICB, Bayat M, Bolund ACS, Gjerulfsen CE, Gregersen PA, Zilmer M, Juhl S, Cebula K, Rahikkala E, Maystadt I, Peron A, Vignoli A, Alfano RM, Stanzial F, Benedicenti F, Currò A, Luk HM, Jouret G, Zurita E, Heuft L, Schnabel F, Busche A, Veenstra-Knol HE, Tkemaladze T, Vrielynck P, Lederer D, Platzer K, Ockeloen CW, Goel H, Low KJ. Natural history of adults with KBG syndrome: A physician-reported experience. Genet Med 2024; 26:101170. [PMID: 38818797 DOI: 10.1016/j.gim.2024.101170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/22/2024] [Accepted: 05/22/2024] [Indexed: 06/01/2024] Open
Abstract
PURPOSE KBG syndrome (KBGS) is a rare neurodevelopmental syndrome caused by haploinsufficiency of ANKRD11. The childhood phenotype is extensively reported but limited for adults. Thus, we aimed to delineate the clinical features of KBGS. METHODS We collected physician-reported data of adults with molecularly confirmed KBGS through an international collaboration. Moreover, we undertook a systematic literature review to determine the scope of previously reported data. RESULTS The international collaboration identified 36 adults from 31 unrelated families with KBGS. Symptoms included mild/borderline intellectual disability (n = 22); gross and/or fine motor difficulties (n = 15); psychiatric and behavioral comorbidities including aggression, anxiety, reduced attention span, and autistic features (n = 26); nonverbal (n = 3), seizures with various seizure types and treatment responses (n = 10); ophthalmological comorbidities (n = 20). Cognitive regression during adulthood was reported once. Infrequent features included dilatation of the ascending aorta (n = 2) and autoimmune conditions (n = 4). Education, work, and residence varied, and the diversity of professional and personal roles highlighted the range of abilities seen. The literature review identified 154 adults reported across the literature, and we have summarized the features across both data sets. CONCLUSION Our study sheds light on the long-term neurodevelopmental outcomes, seizures, behavioral and psychiatric features, and education, work, and living arrangements for adults with KBGS.
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Affiliation(s)
- Allan Bayat
- Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Department of Epilepsy Genetics and Personalized Medicine, Danish Epilepsy Center, Dianalund, Denmark; Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
| | - Hannah Grimes
- Department of Clinical Genetics, University Hospital Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom
| | - Elke de Boer
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands; Department of Clinical Genetics, Erasmus Medical Centre - Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Morten Krogh Herlin
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark
| | - Rebekka Staal Dahl
- Department of Epilepsy Genetics and Personalized Medicine, Danish Epilepsy Center, Dianalund, Denmark
| | - Ida Charlotte Bay Lund
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Michael Bayat
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark; Center for Rare Diseases, Department of Pediatric and Adolescent Medicine, Aarhus University Hospital, Aarhus, Denmark
| | | | | | - Pernille Axél Gregersen
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Center for Rare Diseases, Department of Pediatric and Adolescent Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Monica Zilmer
- Department of Child Neurology, Danish Epilepsy Center, Dianalund, Denmark
| | - Stefan Juhl
- Department of Neurology, Danish Epilepsy Center, Dianalund, Denmark
| | - Katarzyna Cebula
- Department of Neurology, Danish Epilepsy Center, Dianalund, Denmark
| | - Elisa Rahikkala
- Dept of Clinical Genetics, Research Unit of Clinical Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Isabelle Maystadt
- Center for Human Genetics, Institute for Pathology and Genetics, Gosselies, Belgium; URPhyM, Faculty of Medicine, University of Namur, Namur, Belgium
| | - Angela Peron
- Medical Genetics, ASST Santi Paolo e Carlo, San Paolo Hospital, Milan, Italy; Division of Medical Genetics, Meyer Children's Hospital IRCCS, Florence, Italy; Department of Experimental and Clinical Biomedical Sciences "Mario Serio," Università degli Studi di Firenze, Florence, Italy
| | - Aglaia Vignoli
- Child Neuropsychiatry Unit, Grande Ospedale Metropolitano Niguarda, University of Milan, Milan, Italy
| | - Rosa Maria Alfano
- Medical Genetics, ASST Santi Paolo e Carlo, San Paolo Hospital, Milan, Italy
| | - Franco Stanzial
- Genetic Counseling Service, Department of Pediatrics, Regional Hospital of Bolzano, Bolzano, Italy
| | - Francesco Benedicenti
- Genetic Counseling Service, Department of Pediatrics, Regional Hospital of Bolzano, Bolzano, Italy
| | - Aurora Currò
- Genetic Counseling Service, Department of Pediatrics, Regional Hospital of Bolzano, Bolzano, Italy
| | - Ho-Ming Luk
- Clinical Genetics Service Unit, Hong Kong Children's Hospital, HKSAR, Hong Kong
| | - Guillaume Jouret
- National Center of Genetics, Laboratoire National de Santé, Dudelange, Luxembourg
| | - Ella Zurita
- Hunter Genetics, New South Wales Health, Waratah, NSW, Australia
| | - Lara Heuft
- Institute for Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Franziska Schnabel
- Institute for Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Andreas Busche
- Department of Medical Genetics, University Hospital Münster, Germany
| | | | - Tinatin Tkemaladze
- Department of Molecular and Medical Genetics, Tbilisi State Medical University, Tbilisi, Georgia; Givi Zhvania Pediatric Academic Clinic, Tbilisi State Medical University, Tbilisi, Georgia
| | - Pascal Vrielynck
- Reference Center for Refractory Epilepsy, Catholic University of Louvain, William Lennox Neurological Hospital, Ottignies, Belgium
| | - Damien Lederer
- Institute for Pathology and Genetics, 6040, Gosselies, Belgium
| | - Konrad Platzer
- Institute for Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | | | - Himanshu Goel
- Hunter Genetics, New South Wales Health, Waratah, NSW, Australia
| | - Karen Jaqueline Low
- Department of Clinical Genetics, University Hospital Bristol and Weston NHS Foundation Trust, Bristol, United Kingdom; Centre for Academic Child Health, Bristol Medical School, University of Bristol, United Kingdom
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Beeche C, Dib MJ, Zhao B, Azzo JD, Maynard H, Duda J, Gee J, Salman O, Witschey WR, Chirinos JA. Three-dimensional aortic geometry: clinical correlates, prognostic value and genetic architecture. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.09.593413. [PMID: 38798566 PMCID: PMC11118285 DOI: 10.1101/2024.05.09.593413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Aortic structure and function impact cardiovascular health through multiple mechanisms. Aortic structural degeneration increases left ventricular afterload, pulse pressure and promotes target organ damage. Despite the impact of aortic structure on cardiovascular health, aortic 3D-geometry has yet to be comprehensively assessed. Using a convolutional neural network (U-Net) combined with morphological operations, we quantified aortic 3D-geometric phenotypes (AGPs) from 53,612 participants in the UK Biobank and 8,066 participants in the Penn Medicine Biobank. AGPs reflective of structural aortic degeneration, characterized by arch unfolding, descending aortic lengthening and luminal dilation exhibited cross-sectional associations with hypertension and cardiac diseases, and were predictive for new-onset hypertension, heart failure, cardiomyopathy, and atrial fibrillation. We identified 237 novel genetic loci associated with 3D-AGPs. Fibrillin-2 gene polymorphisms were identified as key determinants of aortic arch-3D structure. Mendelian randomization identified putative causal effects of aortic geometry on the risk of chronic kidney disease and stroke.
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Rypdal KB, Apte SS, Lunde IG. Emerging roles for the ADAMTS-like family of matricellular proteins in cardiovascular disease through regulation of the extracellular microenvironment. Mol Biol Rep 2024; 51:280. [PMID: 38324186 PMCID: PMC10850197 DOI: 10.1007/s11033-024-09255-5] [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: 12/05/2023] [Accepted: 01/12/2024] [Indexed: 02/08/2024]
Abstract
Dysregulation of the extracellular matrix (ECM) occurs widely across cardiovascular pathologies. Recent work has revealed important roles for the «a disintegrin-like and metalloprotease domain with thrombospondin-type 1 motifs like" (ADAMTSL) family of secreted glycoproteins in cardiovascular tissues during development and disease. Key insights in this regard have come from naturally occurring gene mutations in humans and animals that result in severe diseases with cardiovascular manifestations or aortopathies. Expression of ADAMTSL genes is greatly increased in the myocardium during heart failure. Genetically modified mice recapitulate phenotypes of patients with ADAMTSL mutations and demonstrate important functions in the ECM. The novel functions thus disclosed are intriguing because, while these proteins are neither structural, nor proteases like the related ADAMTS proteases, they appear to act as regulatory, i.e., matricellular proteins. Evidence from genetic variants, genetically engineered mouse mutants, and in vitro investigations have revealed regulatory functions of ADAMTSLs related to fibrillin microfibrils and growth factor signaling. Interestingly, the ability to regulate transforming growth factor (TGF)β signaling may be a shared characteristic of some ADAMTSLs. TGFβ signaling is important in cardiovascular development, health and disease and a central driver of ECM remodeling and cardiac fibrosis. New strategies to target dysregulated TGFβ signaling are warranted in aortopathies and cardiac fibrosis. With their emerging roles in cardiovascular tissues, the ADAMTSL proteins may provide causative genes, diagnostic biomarkers and novel treatment targets in cardiovascular disease. Here, we discuss the relevance of ADAMTSLs to cardiovascular medicine.
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Affiliation(s)
- Karoline Bjarnesdatter Rypdal
- KG Jebsen Center for Cardiac Biomarkers, Institute for Clinical Medicine, University of Oslo, Oslo, Norway.
- Oslo Center for Clinical Heart Research, Department of Cardiology Ullevaal, Oslo University Hospital, Oslo, Norway.
| | - Suneel S Apte
- Department of Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, OH, USA
| | - Ida G Lunde
- KG Jebsen Center for Cardiac Biomarkers, Institute for Clinical Medicine, University of Oslo, Oslo, Norway
- Oslo Center for Clinical Heart Research, Department of Cardiology Ullevaal, Oslo University Hospital, Oslo, Norway
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7
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Liu D, Billington CJ, Raja N, Wong ZC, Levin MD, Resch W, Alba C, Hupalo DN, Biamino E, Bedeschi MF, Digilio MC, Squeo GM, Villa R, Parrish PCR, Knutsen RH, Osgood S, Freeman JA, Dalgard CL, Merla G, Pober BR, Mervis CB, Roberts AE, Morris CA, Osborne LR, Kozel BA. Matrisome and Immune Pathways Contribute to Extreme Vascular Outcomes in Williams-Beuren Syndrome. J Am Heart Assoc 2024; 13:e031377. [PMID: 38293922 PMCID: PMC11056152 DOI: 10.1161/jaha.123.031377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 11/28/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND Supravalvar aortic stenosis (SVAS) is a characteristic feature of Williams-Beuren syndrome (WBS). Its severity varies: ~20% of people with Williams-Beuren syndrome have SVAS requiring surgical intervention, whereas ~35% have no appreciable SVAS. The remaining individuals have SVAS of intermediate severity. Little is known about genetic modifiers that contribute to this variability. METHODS AND RESULTS We performed genome sequencing on 473 individuals with Williams-Beuren syndrome and developed strategies for modifier discovery in this rare disease population. Approaches include extreme phenotyping and nonsynonymous variant prioritization, followed by gene set enrichment and pathway-level association tests. We next used GTEx v8 and proteomic data sets to verify expression of candidate modifiers in relevant tissues. Finally, we evaluated overlap between the genes/pathways identified here and those ascertained through larger aortic disease/trait genome-wide association studies. We show that SVAS severity in Williams-Beuren syndrome is associated with increased frequency of common and rarer variants in matrisome and immune pathways. Two implicated matrisome genes (ACAN and LTBP4) were uniquely expressed in the aorta. Many genes in the identified pathways were previously reported in genome-wide association studies for aneurysm, bicuspid aortic valve, or aortic size. CONCLUSIONS Smaller sample sizes in rare disease studies necessitate new approaches to detect modifiers. Our strategies identified variation in matrisome and immune pathways that are associated with SVAS severity. These findings suggest that, like other aortopathies, SVAS may be influenced by the balance of synthesis and degradation of matrisome proteins. Leveraging multiomic data and results from larger aorta-focused genome-wide association studies may accelerate modifier discovery for rare aortopathies like SVAS.
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Affiliation(s)
- Delong Liu
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Charles J. Billington
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
- Department of PediatricsUniversity of MinnesotaMinneapolisMN
| | - Neelam Raja
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Zoe C. Wong
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Mark D. Levin
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Wulfgang Resch
- The High Performance Computing FacilityCenter for Information Technology, National Institutes of HealthBethesdaMD
| | - Camille Alba
- Henry M Jackson Foundation for the Advancement of Military MedicineBethesdaMD
| | - Daniel N. Hupalo
- Henry M Jackson Foundation for the Advancement of Military MedicineBethesdaMD
| | | | | | | | - Gabriella Maria Squeo
- Laboratory of Regulatory and Functional GenomicsFondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (Foggia)Italy
| | - Roberta Villa
- Fondazione IRCCS Ca Granda Ospedale Maggiore Policlinico Medical Genetic UnitMilanItaly
| | - Pheobe C. R. Parrish
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
- Department of Genome SciencesUniversity of WashingtonSeattleWA
| | - Russell H. Knutsen
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Sharon Osgood
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Joy A. Freeman
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
| | - Clifton L. Dalgard
- Department of Anatomy, Physiology and Genetics, School of Medicinethe Uniformed Services University of the Health SciencesBethesdaMD
| | - Giuseppe Merla
- Laboratory of Regulatory and Functional GenomicsFondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (Foggia)Italy
- Department of Molecular Medicine and Medical BiotechnologyUniversity of Naples Federico IINaplesItaly
| | - Barbara R. Pober
- Section of Genetics, Department of PediatricsMassachusetts General HospitalBostonMA
| | - Carolyn B. Mervis
- Department of Psychological and Brain SciencesUniversity of LouisvilleLouisvilleKY
| | - Amy E. Roberts
- Department of Cardiology and Division of Genetics and Genomics, Department of PediatricsBoston Children’s HospitalBostonMA
| | - Colleen A. Morris
- Department of PediatricsKirk Kerkorian School of Medicine at UNLVLas VegasNV
| | - Lucy R. Osborne
- Departments of Medicine and Molecular GeneticsUniversity of TorontoCanada
| | - Beth A. Kozel
- National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMD
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8
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Elmore A, Adhikari N, Hartley AE, Javier Aparicio H, Posner DC, Hemani G, Tilling K, Gaunt TR, Wilson P, Casas JP, Michael Gaziano J, Smith GD, Paternoster L, Cho K, Peloso GM. Protein identification for stroke progression via Mendelian Randomization in Million Veteran Program and UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.31.24302111. [PMID: 38352469 PMCID: PMC10863017 DOI: 10.1101/2024.01.31.24302111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Background Individuals who have experienced a stroke, or transient ischemic attack, face a heightened risk of future cardiovascular events. Identification of genetic and molecular risk factors for subsequent cardiovascular outcomes may identify effective therapeutic targets to improve prognosis after an incident stroke. Methods We performed genome-wide association studies (GWAS) for subsequent major adverse cardiovascular events (MACE) (Ncases=51,929, Ncntrl=39,980) and subsequent arterial ischemic stroke (AIS) Ncases=45,120, Ncntrl=46,789) after first incident stroke within the Million Veteran Program and UK Biobank. We then used genetic variants associated with proteins (pQTLs) to determine the effect of 1,463 plasma protein abundances on subsequent MACE using Mendelian randomization (MR). Results Two variants were significantly associated with subsequent cardiovascular events: rs76472767 (OR=0.75, 95% CI = 0.64-0.85, p= 3.69×10-08) with subsequent AIS and rs13294166 (OR=1.52, 95% CI = 1.37-1.67, p=3.77×10-08) with subsequent MACE. Using MR, we identified 2 proteins with an effect on subsequent MACE after a stroke: CCL27 (effect OR= 0.77, 95% CI = 0.66-0.88, adj. p=0.05), and TNFRSF14 (effect OR=1.42, 95% CI = 1.24-1.60, adj. p=0.006). These proteins are not associated with incident AIS and are implicated to have a role in inflammation. Conclusions We found evidence that two proteins with little effect on incident stroke appear to influence subsequent MACE after incident AIS. These associations suggest that inflammation is a contributing factor to subsequent MACE outcomes after incident AIS and highlights potential novel targets.
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Affiliation(s)
- Andrew Elmore
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Nimish Adhikari
- Veteran’s Affairs Healthcare System, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - April E Hartley
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Hugo Javier Aparicio
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA
- Boston Medical Center, Boston, MA
| | | | - Gibran Hemani
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Kate Tilling
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Tom R Gaunt
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | | | - JP Casas
- Veteran’s Affairs Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School
| | - John Michael Gaziano
- Veteran’s Affairs Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School
| | - George Davey Smith
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Lavinia Paternoster
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol
| | - Kelly Cho
- Veteran’s Affairs Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School
| | - Gina M Peloso
- Veteran’s Affairs Healthcare System, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
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9
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Gomes B, Singh A, O'Sullivan JW, Schnurr TM, Goddard PC, Loong S, Amar D, Hughes JW, Kostur M, Haddad F, Salerno M, Foo R, Montgomery SB, Parikh VN, Meder B, Ashley EA. Genetic architecture of cardiac dynamic flow volumes. Nat Genet 2024; 56:245-257. [PMID: 38082205 DOI: 10.1038/s41588-023-01587-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 10/23/2023] [Indexed: 02/04/2024]
Abstract
Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.
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Affiliation(s)
- Bruna Gomes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Aditya Singh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Jack W O'Sullivan
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Theresia M Schnurr
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Pagé C Goddard
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Shaun Loong
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - David Amar
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - J Weston Hughes
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Mykhailo Kostur
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Francois Haddad
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Michael Salerno
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Roger Foo
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Stephen B Montgomery
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Victoria N Parikh
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Benjamin Meder
- Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
- Informatics for Life, Heidelberg, Germany
| | - Euan A Ashley
- Departments of Medicine, Genetics, Computer Science and Biomedical Data Science, Stanford University, Stanford, CA, USA.
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10
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Raghavan A, Pirruccello JP, Ellinor PT, Lindsay ME. Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease. Arterioscler Thromb Vasc Biol 2024; 44:334-351. [PMID: 38095107 PMCID: PMC10843699 DOI: 10.1161/atvbaha.123.318771] [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: 06/26/2023] [Accepted: 11/21/2023] [Indexed: 01/04/2024]
Abstract
Aortic disease, including dissection, aneurysm, and rupture, carries significant morbidity and mortality and is a notable cause of sudden cardiac death. Much of our knowledge regarding the genetic basis of aortic disease has relied on the study of individuals with Mendelian aortopathies and, until recently, the genetic determinants of population-level variance in aortic phenotypes remained unclear. However, the application of machine learning methodologies to large imaging datasets has enabled researchers to rapidly define aortic traits and mine dozens of novel genetic associations for phenotypes such as aortic diameter and distensibility. In this review, we highlight the emerging potential of genomics for identifying causal genes and candidate drug targets for aortic disease. We describe how deep learning technologies have accelerated the pace of genetic discovery in this field. We then provide a blueprint for translating genetic associations to biological insights, reviewing techniques for locus and cell type prioritization, high-throughput functional screening, and disease modeling using cellular and animal models of aortic disease.
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Affiliation(s)
- Avanthi Raghavan
- Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - James P. Pirruccello
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - Patrick T. Ellinor
- Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Mark E. Lindsay
- Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiovascular Disease Initiative, Broad Institute, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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11
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Li Z, Xiong J, Guo Y, Tang H, Guo B, Wang B, Gao D, Dong Z, Tu Y. Effects of diabetes mellitus and glycemic traits on cardiovascular morpho-functional phenotypes. Cardiovasc Diabetol 2023; 22:336. [PMID: 38066511 PMCID: PMC10709859 DOI: 10.1186/s12933-023-02079-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND The effects of diabetes on the cardiac and aortic structure and function remain unclear. Detecting and intervening these variations early is crucial for the prevention and management of complications. Cardiovascular magnetic resonance imaging-derived traits are established endophenotypes and serve as precise, early-detection, noninvasive clinical risk biomarkers. We conducted a Mendelian randomization (MR) study to examine the association between two types of diabetes, four glycemic traits, and preclinical endophenotypes of cardiac and aortic structure and function. METHODS Independent genetic variants significantly associated with type 1 diabetes, type 2 diabetes, fasting insulin (FIns), fasting glucose (FGlu), 2 h-glucose post-challenge (2hGlu), and glycated hemoglobin (HbA1c) were selected as instrumental variables. The 96 cardiovascular magnetic resonance imaging traits came from six independent genome-wide association studies. These traits serve as preclinical endophenotypes and offer an early indication of the structure and function of the four cardiac chambers and two aortic sections. The primary analysis was performed using MR with the inverse-variance weighted method. Confirmation was achieved through Steiger filtering and testing to determine the causal direction. Sensitivity analyses were conducted using the weighted median, MR-Egger, and MR-PRESSO methods. Additionally, multivariable MR was used to adjust for potential effects associated with body mass index. RESULTS Genetic susceptibility to type 1 diabetes was associated with increased ascending aortic distensibility. Conversely, type 2 diabetes showed a correlation with a reduced diameter and areas of the ascending aorta, as well as decreased distensibility of the descending aorta. Genetically predicted higher levels of FGlu and HbA1c were correlated with a decrease in diameter and areas of the ascending aorta. Furthermore, higher 2hGlu levels predominantly showed association with a reduced diameter of both the ascending and descending aorta. Higher FIns levels corresponded to increased regional myocardial-wall thicknesses at end-diastole, global myocardial-wall thickness at end-diastole, and regional peak circumferential strain of the left ventricle. CONCLUSIONS This study provides evidence that diabetes and glycemic traits have a causal relationship with cardiac and aortic structural and functional remodeling, highlighting the importance of intensive glucose-lowering for primary prevention of cardiovascular diseases.
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Affiliation(s)
- Zhaoyue Li
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Jie Xiong
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Yutong Guo
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Hao Tang
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Bingchen Guo
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Bo Wang
- Harbin Medical University, Harbin, China
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Dianyu Gao
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Zengxiang Dong
- Harbin Medical University, Harbin, China.
- The Key Laboratory of Cardiovascular Disease Acousto-Optic Electromagnetic Diagnosis and Treatment in Heilongjiang Province, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
- NHC Key Laboratory of Cell Transplantation, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Yingfeng Tu
- Harbin Medical University, Harbin, China.
- Department of Cardiology, the First Affiliated Hospital, Harbin Medical University, Harbin, China.
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12
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Grilo LF, Zimmerman KD, Puppala S, Chan J, Huber HF, Li G, Jadhav AYL, Wang B, Li C, Clarke GD, Register TC, Oliveira PJ, Nathanielsz PW, Olivier M, Pereira SP, Cox LA. Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation Via Hexosamine Biosynthetic Pathway. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.17.567640. [PMID: 38014295 PMCID: PMC10680868 DOI: 10.1101/2023.11.17.567640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Age is a prominent risk factor for cardiometabolic disease, and often leads to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction resulting from physiological aging per se remain elusive. Understanding these mechanisms requires biological models with optimal translation to humans. Previous research demonstrated that baboons undergo age-related reduction in ejection fraction and increased heart sphericity, mirroring changes observed in humans. The goal of this study was to identify early cardiac molecular alterations that precede functional adaptations, shedding light on the regulation of age-associated changes. We performed unbiased transcriptomics of left ventricle (LV) samples from female baboons aged 7.5-22.1 years (human equivalent ~30-88 years). Weighted-gene correlation network and pathway enrichment analyses were performed to identify potential age-associated mechanisms in LV, with histological validation. Myocardial modules of transcripts negatively associated with age were primarily enriched for cardiac metabolism, including oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggest upregulation of glucose uptake, pentose phosphate pathway, and hexosamine biosynthetic pathway (HBP), indicating a metabolic shift towards glucose-dependent anabolic pathways. Upregulation of HBP commonly results in increased glycosaminoglycan precursor synthesis. Transcripts involved in glycosaminoglycan synthesis, modification, and intermediate metabolism were also upregulated in older animals, while glycosaminoglycan degradation transcripts were downregulated with age. These alterations would promote glycosaminoglycan accumulation, which was verified histologically. Upregulation of extracellular matrix (ECM)-induced signaling pathways temporally coincided with glycosaminoglycan accumulation. We found a subsequent upregulation of cardiac hypertrophy-related pathways and an increase in cardiomyocyte width. Overall, our findings revealed a transcriptional shift in metabolism from catabolic to anabolic pathways that leads to ECM glycosaminoglycan accumulation through HBP prior to upregulation of transcripts of cardiac hypertrophy-related pathways. This study illuminates cellular mechanisms that precede development of cardiac hypertrophy, providing novel potential targets to remediate age-related cardiac diseases.
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Affiliation(s)
- Luís F. Grilo
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
- University of Coimbra, Institute for Interdisciplinary Research, PDBEB - Doctoral Programme in Experimental Biology and Biomedicine
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kip D. Zimmerman
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Sobha Puppala
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jeannie Chan
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Hillary F. Huber
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ge Li
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Avinash Y. L. Jadhav
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Benlian Wang
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, Wyoming, USA
| | - Geoffrey D. Clarke
- Department of Radiology, University of Texas Health Science Center, San Antonio, Texas
| | - Thomas C. Register
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Paulo J. Oliveira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
| | - Peter W. Nathanielsz
- Texas Pregnancy & Life-Course Health Research Center, Department of Animal Science, University of Wyoming, Laramie, Wyoming, USA
| | - Michael Olivier
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Susana P. Pereira
- CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal
- CIBB, Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Portugal
- Laboratory of Metabolism and Exercise (LaMetEx), Research Centre in Physical Activity, Health and Leisure (CIAFEL), Laboratory for Integrative and Translational Research in Population Health (ITR), Faculty of Sports, University of Porto, Porto, Portugal
| | - Laura A. Cox
- Center for Precision Medicine, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Section on Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
- Section on Comparative Medicine, Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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13
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Lareyre F, Chaudhuri A, Nasr B, Raffort J. Machine Learning and Omics Analysis in Aortic Aneurysm. Angiology 2023:33197231206427. [PMID: 37817423 DOI: 10.1177/00033197231206427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/12/2023]
Abstract
Aortic aneurysm is a life-threatening condition and mechanisms underlying its formation and progression are still incompletely understood. Omics approach has brought new insights to identify a broad spectrum of biomarkers and better understand cellular and molecular pathways involved. Omics generate a large amount of data and several studies have highlighted that artificial intelligence (AI) and techniques such as machine learning (ML)/deep learning (DL) can be of use in analyzing such complex datasets. However, only a few studies have so far reported the use of ML/DL for omics analysis in aortic aneurysms. The aim of this study is to summarize recent advances on the use of ML/DL for omics analysis to decipher aortic aneurysm pathophysiology and develop patient-tailored risk prediction models. In the light of current knowledge, we discuss current limits and highlight future directions in the field.
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Affiliation(s)
- Fabien Lareyre
- Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, Nice, France
- Inserm U1065, C3M, Université Côte d'Azur, Nice, France
| | - Arindam Chaudhuri
- Bedfordshire-Milton Keynes Vascular Centre, Bedfordshire Hospitals NHS Foundation Trust, Bedford, UK
| | - Bahaa Nasr
- Department of Vascular and Endovascular Surgery, Brest University Hospital, Brest, France
- INSERM UMR 1101, LaTIM, Brest, France
| | - Juliette Raffort
- Inserm U1065, C3M, Université Côte d'Azur, Nice, France
- Clinical Chemistry Laboratory, University Hospital of Nice, Nice, France
- 3IA Institute, Université Côte d'Azur, Nice, France
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14
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Yang M, Zhou X, Pearce SW, Yang Z, Chen Q, Niu K, Liu C, Luo J, Li D, Shao Y, Zhang C, Chen D, Wu Q, Cutillas PR, Zhao L, Xiao Q, Zhang L. Causal Role for Neutrophil Elastase in Thoracic Aortic Dissection in Mice. Arterioscler Thromb Vasc Biol 2023; 43:1900-1920. [PMID: 37589142 PMCID: PMC10521802 DOI: 10.1161/atvbaha.123.319281] [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: 03/10/2023] [Accepted: 08/01/2023] [Indexed: 08/18/2023]
Abstract
BACKGROUND Thoracic aortic dissection (TAD) is a life-threatening aortic disease without effective medical treatment. Increasing evidence has suggested a role for NE (neutrophil elastase) in vascular diseases. In this study, we aimed at investigating a causal role for NE in TAD and exploring the molecular mechanisms involved. METHODS β-aminopropionitrile monofumarate was administrated in mice to induce TAD. NE deficiency mice, pharmacological inhibitor GW311616A, and adeno-associated virus-2-mediated in vivo gene transfer were applied to explore a causal role for NE and associated target gene in TAD formation. Multiple functional assays and biochemical analyses were conducted to unravel the underlying cellular and molecular mechanisms of NE in TAD. RESULTS NE aortic gene expression and plasma activity was significantly increased during β-aminopropionitrile monofumarate-induced TAD and in patients with acute TAD. NE deficiency prevents β-aminopropionitrile monofumarate-induced TAD onset/development, and GW311616A administration ameliorated TAD formation/progression. Decreased levels of neutrophil extracellular traps, inflammatory cells, and MMP (matrix metalloproteinase)-2/9 were observed in NE-deficient mice. TBL1x (F-box-like/WD repeat-containing protein TBL1x) has been identified as a novel substrate and functional downstream target of NE in TAD. Loss-of-function studies revealed that NE mediated inflammatory cell transendothelial migration by modulating TBL1x-LTA4H (leukotriene A4 hydrolase) signaling and that NE regulated smooth muscle cell phenotype modulation under TAD pathological condition by regulating TBL1x-MECP2 (methyl CpG-binding protein 2) signal axis. Further mechanistic studies showed that TBL1x inhibition decreased the binding of TBL1x and HDAC3 (histone deacetylase 3) to MECP2 and LTA4H gene promoters, respectively. Finally, adeno-associated virus-2-mediated Tbl1x gene knockdown in aortic smooth muscle cells confirmed a regulatory role for TBL1x in NE-mediated TAD formation. CONCLUSIONS We unravel a critical role of NE and its target TBL1x in regulating inflammatory cell migration and smooth muscle cell phenotype modulation in the context of TAD. Our findings suggest that the NE-TBL1x signal axis represents a valuable therapeutic for treating high-risk TAD patients.
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Affiliation(s)
- Mei Yang
- Department of Cardiology, Institute for Developmental and Regenerative Cardiovascular Medicine, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, China (M.Y., Q.C., D.L., L. Zhang)
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
| | - Xinmiao Zhou
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
- Department of Respiratory and Critical Care Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China (X.Z.)
| | - Stuart W.A. Pearce
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
| | - Zhisheng Yang
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
| | - Qishan Chen
- Department of Cardiology, Institute for Developmental and Regenerative Cardiovascular Medicine, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, China (M.Y., Q.C., D.L., L. Zhang)
| | - Kaiyuan Niu
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
| | - Chenxin Liu
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
| | - Jun Luo
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, China (J.L., Y.S., C.Z., D.C., Q.W.)
| | - Dan Li
- Department of Cardiology, Institute for Developmental and Regenerative Cardiovascular Medicine, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, China (M.Y., Q.C., D.L., L. Zhang)
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, China (D.L., L. Zhao)
| | - Yue Shao
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, China (J.L., Y.S., C.Z., D.C., Q.W.)
| | - Cheng Zhang
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, China (J.L., Y.S., C.Z., D.C., Q.W.)
| | - Dan Chen
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, China (J.L., Y.S., C.Z., D.C., Q.W.)
| | - Qingchen Wu
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, China (J.L., Y.S., C.Z., D.C., Q.W.)
| | - Pedro R. Cutillas
- Faculty of Medicine and Dentistry, Centre for Haemato-Oncology, Barts Cancer Institute (P.R.C.), Queen Mary University of London, United Kingdom
| | - Lin Zhao
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, China (D.L., L. Zhao)
| | - Qingzhong Xiao
- Faculty of Medicine and Dentistry, William Harvey Research Institute (M.Y., X.Z., S.W.A.P., Z.Y., K.N., C.L., Q.X.), Queen Mary University of London, United Kingdom
- Key Laboratory of Cardiovascular Diseases, School of Basic Medical Sciences, Guangzhou Institute of Cardiovascular Disease, The Second Affiliated Hospital, Guangzhou Medical University, China (Q.X.)
| | - Li Zhang
- Department of Cardiology, Institute for Developmental and Regenerative Cardiovascular Medicine, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, China (M.Y., Q.C., D.L., L. Zhang)
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15
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Lum RTW, Wang X, Zhang M, Zhang X, Ho JYK, Chow SCY, Fujikawa T, Wong RHL. Emerging role of radiogenomics in genetically triggered thoracic aortic aneurysm and dissection: a narrative review. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:356. [PMID: 37675315 PMCID: PMC10477616 DOI: 10.21037/atm-22-6149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 03/17/2023] [Indexed: 09/08/2023]
Abstract
Background and Objective Thoracic aortic aneurysm and dissection (TAAD) and its complications are life-threatening conditions. Hypertension and atherosclerosis had all along been recognized as the predominant risk factors for the development of TAAD. However, it was increasingly reported that genetic factors, such as single nucleotide polymorphisms (SNPs), are playing an important role in the disease development. The development of next-generation sequencing (NGS) and the rapid growth in radiomics provide a promising new platform to evaluate genetically triggered thoracic aortic aneurysm and dissection (GTAAD) from a new angle. This review is to present an overview of currently available knowledge regarding the use of radiomics and radiogenomics in GTAAD. Methods We performed literature searches in PubMed, EMBASE and Cochrane database from 2012 to 2022 regarding the use of radiomics and radiogenomics in GTAAD. Key Content and Findings There were only 13 studies on radiomics and 4 studies on radiogenomics integration retrieved from the search and it signifies there is still a significant knowledge gap in this field of translational medicine. An overview of the current knowledge of GTAAD, the workflow and role of radiomics, the radiogenomics integration for GTAAD including its potential role in the development of polygenic scores, as well as the implications, challenges, and limitations of radiogenomics research were discussed. Conclusions In the contemporary era, radiogenomics has been emerging as a state-of-the art approach to establish statistical correlation with radiomics features with genomic information in diagnosis, risk modeling and prediction and treatment decision in TAAD.
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Affiliation(s)
- Ray Tak Wai Lum
- Division of Cardiothoracic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Xin Wang
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China
| | - Miaoru Zhang
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China
| | - Xianrui Zhang
- Department of Biomedical Science, The City University of Hong Kong, Hong Kong, China
| | - Jacky Yan Kit Ho
- Division of Cardiothoracic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Simon Chi Ying Chow
- Division of Cardiothoracic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Takuya Fujikawa
- Division of Cardiothoracic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Randolph Hung Leung Wong
- Division of Cardiothoracic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
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16
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Shah M, de A Inácio MH, Lu C, Schiratti PR, Zheng SL, Clement A, de Marvao A, Bai W, King AP, Ware JS, Wilkins MR, Mielke J, Elci E, Kryukov I, McGurk KA, Bender C, Freitag DF, O'Regan DP. Environmental and genetic predictors of human cardiovascular ageing. Nat Commun 2023; 14:4941. [PMID: 37604819 PMCID: PMC10442405 DOI: 10.1038/s41467-023-40566-6] [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] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 08/02/2023] [Indexed: 08/23/2023] Open
Abstract
Cardiovascular ageing is a process that begins early in life and leads to a progressive change in structure and decline in function due to accumulated damage across diverse cell types, tissues and organs contributing to multi-morbidity. Damaging biophysical, metabolic and immunological factors exceed endogenous repair mechanisms resulting in a pro-fibrotic state, cellular senescence and end-organ damage, however the genetic architecture of cardiovascular ageing is not known. Here we use machine learning approaches to quantify cardiovascular age from image-derived traits of vascular function, cardiac motion and myocardial fibrosis, as well as conduction traits from electrocardiograms, in 39,559 participants of UK Biobank. Cardiovascular ageing is found to be significantly associated with common or rare variants in genes regulating sarcomere homeostasis, myocardial immunomodulation, and tissue responses to biophysical stress. Ageing is accelerated by cardiometabolic risk factors and we also identify prescribed medications that are potential modifiers of ageing. Through large-scale modelling of ageing across multiple traits our results reveal insights into the mechanisms driving premature cardiovascular ageing and reveal potential molecular targets to attenuate age-related processes.
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Affiliation(s)
- Mit Shah
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
| | - Marco H de A Inácio
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
| | - Chang Lu
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
| | | | - Sean L Zheng
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Adam Clement
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
| | - Antonio de Marvao
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
| | - Wenjia Bai
- Department of Computing, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Andrew P King
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - James S Ware
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Martin R Wilkins
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Johanna Mielke
- Bayer AG, Research & Development, Pharmaceuticals, Wuppertal, Germany
| | - Eren Elci
- Bayer AG, Research & Development, Pharmaceuticals, Wuppertal, Germany
| | - Ivan Kryukov
- Bayer AG, Research & Development, Pharmaceuticals, Wuppertal, Germany
| | - Kathryn A McGurk
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Christian Bender
- Bayer AG, Research & Development, Pharmaceuticals, Wuppertal, Germany
| | - Daniel F Freitag
- Bayer AG, Research & Development, Pharmaceuticals, Wuppertal, Germany
| | - Declan P O'Regan
- MRC London Institute of Medical Sciences, Imperial College London, London, UK.
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17
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Hu Y, Cai Z, He B. Smooth Muscle Heterogeneity and Plasticity in Health and Aortic Aneurysmal Disease. Int J Mol Sci 2023; 24:11701. [PMID: 37511460 PMCID: PMC10380637 DOI: 10.3390/ijms241411701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 07/16/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Vascular smooth muscle cells (VSMCs) are the predominant cell type in the medial layer of the aorta, which plays a critical role in the maintenance of aortic wall integrity. VSMCs have been suggested to have contractile and synthetic phenotypes and undergo phenotypic switching to contribute to the deteriorating aortic wall structure. Recently, the unprecedented heterogeneity and diversity of VSMCs and their complex relationship to aortic aneurysms (AAs) have been revealed by high-resolution research methods, such as lineage tracing and single-cell RNA sequencing. The aortic wall consists of VSMCs from different embryonic origins that respond unevenly to genetic defects that directly or indirectly regulate VSMC contractile phenotype. This difference predisposes to hereditary AAs in the aortic root and ascending aorta. Several VSMC phenotypes with different functions, for example, secreting VSMCs, proliferative VSMCs, mesenchymal stem cell-like VSMCs, immune-related VSMCs, proinflammatory VSMCs, senescent VSMCs, and stressed VSMCs are identified in non-hereditary AAs. The transformation of VSMCs into different phenotypes is an adaptive response to deleterious stimuli but can also trigger pathological remodeling that exacerbates the pathogenesis and development of AAs. This review is intended to contribute to the understanding of VSMC diversity in health and aneurysmal diseases. Papers that give an update on VSMC phenotype diversity in health and aneurysmal disease are summarized and recent insights on the role of VSMCs in AAs are discussed.
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Affiliation(s)
- Yunwen Hu
- Department of Cardiology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhaohua Cai
- Department of Cardiology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Ben He
- Department of Cardiology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
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18
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Luperchio TR, Kozel BA. Extending the spectrum in aortopathy: stenosis to aneurysm. Curr Opin Genet Dev 2022; 76:101962. [DOI: 10.1016/j.gde.2022.101962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 06/21/2022] [Accepted: 06/25/2022] [Indexed: 11/03/2022]
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19
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Abstract
The complexity and volume of data associated with population-based cohorts means that generating health-related outcomes can be challenging. Using one such cohort, the UK Biobank-a major open access resource-we present a protocol to efficiently integrate the main dataset and record-level data files, to harmonize and process the data using an R package named "ukbpheno". We describe how to use the package to generate binary phenotypes in a standardized and machine-actionable manner. For complete details on the use and execution of this protocol, please refer to Yeung et al. (2022).
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20
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Procknow SS, Kozel BA. Emerging mechanisms of elastin transcriptional regulation. Am J Physiol Cell Physiol 2022; 323:C666-C677. [PMID: 35816641 PMCID: PMC9448287 DOI: 10.1152/ajpcell.00228.2022] [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: 06/01/2022] [Revised: 07/06/2022] [Accepted: 07/06/2022] [Indexed: 11/22/2022]
Abstract
Elastin provides recoil to tissues that stretch such as the lung, blood vessels, and skin. It is deposited in a brief window starting in the prenatal period and extending to adolescence in vertebrates, and then slowly turns over. Elastin insufficiency is seen in conditions such as Williams-Beuren syndrome and elastin-related supravalvar aortic stenosis, which are associated with a range of vascular and connective tissue manifestations. Regulation of the elastin (ELN) gene occurs at multiple levels including promoter activation/inhibition, mRNA stability, interaction with microRNAs, and alternative splicing. However, these mechanisms are incompletely understood. Better understanding of the processes controlling ELN gene expression may improve medicine's ability to intervene in these rare conditions, as well as to replace age-associated losses by re-initiating elastin production. This review describes what is known about the ELN gene promoter structure, transcriptional regulation by cytokines and transcription factors, and posttranscriptional regulation via mRNA stability and micro-RNA and highlights new approaches that may influence regenerative medicine.
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Affiliation(s)
- Sara S Procknow
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri
| | - Beth A Kozel
- Translational Vascular Medicine Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland
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21
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Genome-wide associations of aortic distensibility suggest causality for aortic aneurysms and brain white matter hyperintensities. Nat Commun 2022; 13:4505. [PMID: 35922433 PMCID: PMC9349177 DOI: 10.1038/s41467-022-32219-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 07/20/2022] [Indexed: 12/13/2022] Open
Abstract
Aortic dimensions and distensibility are key risk factors for aortic aneurysms and dissections, as well as for other cardiovascular and cerebrovascular diseases. We present genome-wide associations of ascending and descending aortic distensibility and area derived from cardiac magnetic resonance imaging (MRI) data of up to 32,590 Caucasian individuals in UK Biobank. We identify 102 loci (including 27 novel associations) tagging genes related to cardiovascular development, extracellular matrix production, smooth muscle cell contraction and heritable aortic diseases. Functional analyses highlight four signalling pathways associated with aortic distensibility (TGF-β, IGF, VEGF and PDGF). We identify distinct sex-specific associations with aortic traits. We develop co-expression networks associated with aortic traits and apply phenome-wide Mendelian randomization (MR-PheWAS), generating evidence for a causal role for aortic distensibility in development of aortic aneurysms. Multivariable MR suggests a causal relationship between aortic distensibility and cerebral white matter hyperintensities, mechanistically linking aortic traits and brain small vessel disease.
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22
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Battineni G, Hossain MA, Chintalapudi N, Amenta F. A Survey on the Role of Artificial Intelligence in Biobanking Studies: A Systematic Review. Diagnostics (Basel) 2022; 12:1179. [PMID: 35626333 PMCID: PMC9140088 DOI: 10.3390/diagnostics12051179] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/02/2022] [Accepted: 05/06/2022] [Indexed: 02/04/2023] Open
Abstract
Introduction: In biobanks, participants' biological samples are stored for future research. The application of artificial intelligence (AI) involves the analysis of data and the prediction of any pathological outcomes. In AI, models are used to diagnose diseases as well as classify and predict disease risks. Our research analyzed AI's role in the development of biobanks in the healthcare industry, systematically. Methods: The literature search was conducted using three digital reference databases, namely PubMed, CINAHL, and WoS. Guidelines for preferred reporting elements for systematic reviews and meta-analyses (PRISMA)-2020 in conducting the systematic review were followed. The search terms included "biobanks", "AI", "machine learning", and "deep learning", as well as combinations such as "biobanks with AI", "deep learning in the biobanking field", and "recent advances in biobanking". Only English-language papers were included in the study, and to assess the quality of selected works, the Newcastle-Ottawa scale (NOS) was used. The good quality range (NOS ≥ 7) is only considered for further review. Results: A literature analysis of the above entries resulted in 239 studies. Based on their relevance to the study's goal, research characteristics, and NOS criteria, we included 18 articles for reviewing. In the last decade, biobanks and artificial intelligence have had a relatively large impact on the medical system. Interestingly, UK biobanks account for the highest percentage of high-quality works, followed by Qatar, South Korea, Singapore, Japan, and Denmark. Conclusions: Translational bioinformatics probably represent a future leader in precision medicine. AI and machine learning applications to biobanking research may contribute to the development of biobanks for the utility of health services and citizens.
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Affiliation(s)
- Gopi Battineni
- Clinical Research Centre, School of Medicinal and Health Products Sciences, University of Camerino, 62032 Camerino, Italy; (M.A.H.); (N.C.); (F.A.)
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