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Ahmad A, Lim LL, Morieri ML, Tam CHT, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza RJ, Tobias DK, Gomez MF, Ma RCW, Mathioudakis N. Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis. COMMUNICATIONS MEDICINE 2024; 4:11. [PMID: 38253823 PMCID: PMC10803333 DOI: 10.1038/s43856-023-00429-z] [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: 05/12/2023] [Accepted: 12/14/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). METHODS We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. RESULTS Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. CONCLUSIONS Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
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Affiliation(s)
- Abrar Ahmad
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Asia Diabetes Foundation, Hong Kong SAR, China
| | - Mario Luca Morieri
- Metabolic Disease Unit, University Hospital of Padova, Padova, Italy
- Department of Medicine, University of Padova, Padova, Italy
| | - Claudia Ha-Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Feifei Cheng
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | | | - Hugo Fitipaldi
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | | | - Sudipa Sarkar
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Robert Wilhelm Koivula
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Sok Cin Tye
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands
- Sections on Genetics and Epidemiology, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yingchai Zhang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Michele Provenzano
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Diana Sherifali
- Heather M. Arthur Population Health Research Institute, McMaster University, Ontario, Canada
| | - Russell J de Souza
- Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences Corporation, Hamilton, Ontario, Canada
| | | | - Maria F Gomez
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
- Faculty of Health, Aarhus University, Aarhus, Denmark.
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Nestoras Mathioudakis
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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Ahmad A, Lim LL, Morieri ML, Tam CHT, Cheng F, Chikowore T, Dudenhöffer-Pfeifer M, Fitipaldi H, Huang C, Kanbour S, Sarkar S, Koivula RW, Motala AA, Tye SC, Yu G, Zhang Y, Provenzano M, Sherifali D, de Souza R, Tobias DK, Gomez MF, Ma RCW, Mathioudakis NN. Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.26.23289177. [PMID: 37162891 PMCID: PMC10168509 DOI: 10.1101/2023.04.26.23289177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.
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Brito MDF, Torre C, Silva-Lima B. Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative. Front Med (Lausanne) 2021; 8:688438. [PMID: 34295913 PMCID: PMC8290522 DOI: 10.3389/fmed.2021.688438] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/02/2021] [Indexed: 12/16/2022] Open
Abstract
Diabetes Mellitus is one of the World Health Organization's priority diseases under research by the first and second programmes of Innovative Medicines Initiative, with the acronyms IMI1 and IMI2, respectively. Up to October of 2019, 13 projects were funded by IMI for Diabetes & Metabolic disorders, namely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. In order to prompt a better integration of achievements between the different projects, we perform a literature review and used three data sources, namely the official project's websites, the contact with the project's coordinators and co-coordinator, and the CORDIS database. From the 662 citations identified, 185 were included. The data collected were integrated into the objectives proposed for the four IMI2 program research axes: (1) target and biomarker identification, (2) innovative clinical trials paradigms, (3) innovative medicines, and (4) patient-tailored adherence programmes. The IMI funded projects identified new biomarkers, medical and research tools, determinants of inter-individual variability, relevant pathways, clinical trial designs, clinical endpoints, therapeutic targets and concepts, pharmacologic agents, large-scale production strategies, and patient-centered predictive models for diabetes and its complications. Taking into account the scientific data produced, we provided a joint vision with strategies for integrating personalized medicine into healthcare practice. The major limitations of this article were the large gap of data in the libraries on the official project websites and even the Cordis database was not complete and up to date.
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Affiliation(s)
| | - Carla Torre
- Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal.,Laboratory of Systems Integration Pharmacology, Clinical & Regulatory Science-Research Institute for Medicines (iMED.ULisboa), Lisbon, Portugal
| | - Beatriz Silva-Lima
- Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal.,Laboratory of Systems Integration Pharmacology, Clinical & Regulatory Science-Research Institute for Medicines (iMED.ULisboa), Lisbon, Portugal
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Haye A, Ansari MA, Rahman SO, Shamsi Y, Ahmed D, Sharma M. Role of AMP-activated protein kinase on cardio-metabolic abnormalities in the development of diabetic cardiomyopathy: A molecular landscape. Eur J Pharmacol 2020; 888:173376. [PMID: 32810493 DOI: 10.1016/j.ejphar.2020.173376] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 07/10/2020] [Accepted: 07/13/2020] [Indexed: 12/13/2022]
Abstract
Cardiovascular complications associated with diabetes mellitus remains a leading cause of morbidity and mortality across the world. Diabetic cardiomyopathy is a descriptive pathology that in absence of co-morbidities such as hypertension, dyslipidemia initially characterized by cardiac stiffness, myocardial fibrosis, ventricular hypertrophy, and remodeling. These abnormalities further contribute to diastolic dysfunctions followed by systolic dysfunctions and eventually results in clinical heart failure (HF). The clinical outcomes associated with HF are considerably worse in patients with diabetes. The complexity of the pathogenesis and clinical features of diabetic cardiomyopathy raises serious questions in developing a therapeutic strategy to manage cardio-metabolic abnormalities. Despite extensive research in the past decade the compelling approaches to manage and treat diabetic cardiomyopathy are limited. AMP-Activated Protein Kinase (AMPK), a serine-threonine kinase, often referred to as cellular "metabolic master switch". During the development and progression of diabetic cardiomyopathy, a plethora of evidence demonstrate the beneficial role of AMPK on cardio-metabolic abnormalities including altered substrate utilization, impaired cardiac insulin metabolic signaling, mitochondrial dysfunction and oxidative stress, myocardial inflammation, increased accumulation of advanced glycation end-products, impaired cardiac calcium handling, maladaptive activation of the renin-angiotensin-aldosterone system, endoplasmic reticulum stress, myocardial fibrosis, ventricular hypertrophy, cardiac apoptosis, and impaired autophagy. Therefore, in this review, we have summarized the findings from pre-clinical and clinical studies and provided a collective overview of the pathophysiological mechanism and the regulatory role of AMPK on cardio-metabolic abnormalities during the development of diabetic cardiomyopathy.
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Affiliation(s)
- Abdul Haye
- Pharmaceutical Medicine, Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Mohd Asif Ansari
- Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Syed Obaidur Rahman
- Pharmaceutical Medicine, Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Yasmeen Shamsi
- Department of Moalejat, School of Unani Medical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Danish Ahmed
- Department of Pharmaceutical Sciences, Faculty of Health Sciences, Sam Higginbottom University of Agriculture Technology and Sciences, Allahabad, Uttar Pradesh, India
| | - Manju Sharma
- Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India.
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