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Artificial Intelligence In Precision Cardiovascular Medicine
By Yashendra Sethi Yashendra Sethi Scilit Preprints.org Google Scholar 1, 2, †, Neil Patel Neil Patel Scilit Preprints.org Google Scholar 1, 3, †, Nirja Kaka Nirja Kaka Scilit Preprints.org Google Scholar 1, 3, *, † , Oroshay Kaiwan Oroshay Kaiwan Scilit Preprints.org Google Scholar 1, 4, Jill Kar Jill Kar Scilit Preprints.org Google Scholar 1, 5, Arsalan Moinuddin Arsalan Moinuddin Scilit Preprints.org Google Scholar 6, * , Ashish Goel Ashish Goel Scilit Preprints.org Google Scholar 2, Hitesh Chopra Hitesh Chopra Scilit Preprints.org Google Scholar 7 and Simona Cavalu Simona Cavalu Scilit Preprints.org Google Scholar 8, *
Cardiac diseases form the lion’s share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced “omics”. These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the “omics”, involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach.
Over the past three decades, cardiovascular diseases (CVDs) have preponderated global disease burden––93% prevalence, 54% mortality, and 60% in disability-adjusted life years (DALY) [1, 2, 3]. This is further exacerbated by disparities in the inter- and intra-continental disease burden, costing USD 216 billion and USD 147 billion annually for healthcare and productivity loss, respectively [4, 5, 6].
Study To Advance Precision Medicine For Cardiovascular Disease
The rectitude of medicine has always emphasized treating the patient rather than the disease. Today’s medicine is honing itself to be more precise and patient-centric. Precision medicine is an innovative clinical approach that uses individual genomic, environmental, and lifestyle information to guide medical management. It has already revolutionized oncology [7]; CVDs form their current epicenter owing to their heterogeneity and multi-causality, which leads to altered responses to treatment for each patient. The long-old treatment principles are succored by technological evolution in the “omics”—genomics, transcriptomics, epigenomics, metabolomics, proteomics, and microbiomics— which, together, help frame the position for future medicine [8]. “Omics” is aided by advanced “big data” analysis, which has helped in the development of in-depth clinical, biological, and molecular phenotyping, promoting better-integrated healthcare with early diagnosis, enhanced risk stratification, and disease management with the least possible side effects [9].
Most CVDs stem from a complex interplay of modifiable and non-modifiable factors which aggravate the set “omic” predisposition. In contemporary cardiology, most diagnostic criteria and therapeutic approaches rely on population-based studies, with less focus on approaches tailored to individualize patient treatment [10]. As such, a comprehensive analysis of phenotypes and the “omics” can help cluster patient groups sheathing disparities, simultaneously reinforcing patient-centric clinical care. Further, it will enhance patient quality of life (QOL) and help reduce complications via novel biomarkers, improved AI-assisted diagnostics, targeted therapeutics, and appropriate long-term risk assessment [11].
With technological advancements in data science and machine learning, the applicability of precision medicine in CVDs seems within reach, especially with the significant evolving literature in the pipeline over the past decade. As such, we aim to: 1. pool evolving clinically relevant information on precision medicine in cardiology, and 2. provide a comprehensive synthesis of the relevant literature to date. Thus, this will help with the evidence-based precise management of cardiac diseases and identification of possible challenges.
Penn Medicine Nabs $6m Nih Grant To Study Cardiac Cell Development
The advent of precision medicine has the potential to revolutionize the future of cardiovascular disease (CVD) healthcare via its application through “omics” in cardiology (Figure 1). It empowers a physician to treat cardiac diseases on an individual basis—based on the patient’s unique profile. Recent times have seen a growing body of literature underlining the application of precision medicine in cardiology. Table 1 presents a compilation underlining the clinical significance of all “reviews” published over the past decade regarding the same, while Table 2, Table 3 and Table 4 present an omic-stratified and disease-specific compilation of the literature for myocardial infarction, hypertension, and heart failure, respectively. As such, precision medicine in cardiology promises to improve health and revolutionize the management previously manifested in oncology. The evolution of precision medicine in cardiology has been remarkable (Figure 2). Its applicability can have the best impact if enacted on the diseases with the highest impact (associated with the highest DALY), these include—myocardial infarction, hypertension, and heart failure.
Myocardial infarction (MI) is the leading cause of death globally—16% of total deaths. Its pathogenesis is peculiar in terms of its heterogeneous causality and largely varied genetic predisposition. MI is a critical medical emergency, true to its scientific adage “Time is equal to Myocardium”. An opportune diagnosis with sensitive markers, optimal intervention, and the prevention of complications and recurrence is extremely consequential. Precision medicine may find its applications in all these areas (Table 2) and may guide research and drug development to add to the pharmacotherapeutic armamentarium for this disease [29, 30].
The activation of NrF2 by bFGF lowers oxidative stress. This can significantly lessen the apoptosis of cardiomyocytes and the size of the infarcts brought on by MI, thereby lessening the damage to the heart.
Applying Precision Medicine To Healthy Living For The Prevention And Treatment Of Cardiovascular Disease.
Deep phenotyping data, blood biobank, cardiac stress-MRI test, and identified candidate biomarkers (such as miRNAs, troponin, CRP, etc.) will be used to derive a biomarker specifically for ischemia.
A patient-specific treatment plan for MINOCA requires determining the cause. Some diagnostic tools for this purpose include the electrocardiogram (ECG), cardiac enzymes, echocardiography, coronary angiography, left ventricular angiography, coronary vasomotion, and intravascular imaging techniques.
The biomechanical aspects of LV function, such as contractility, stiffness, strain, and stress, which are related to LV pump performance and, consequently, prognosis, can be learned through computational modeling.
Contemporary And Future Approaches To Precision Medicine In Inherited Cardiomyopathies: Jacc Focus Seminar 3/5
When deciding whether to continue DAPT therapy (in patients 1 year after acute MI), prognostic factors such as demographics, behavior, cardiovascular history, non-cardiovascular history, biomarkers, and medications should be taken into account.
MiRNAs can be used to diagnose acute MI, stratify MI risk, and other medical conditions. After an MI, circulating miRNA levels have some prognostic value, and BNP’s diagnostic value is enhanced.
AT2R has a protective role in the heart after MI, leading to improved cardiovascular health. The protective function includes improvement of LV contractility, protection from early LV dilatation, and an antifibrotic effect under certain conditions.
Moving Towards Individualized Care For Cardiovascular Disease
Epoxyeicosatrienoic acids (EETs) possess cardioprotective effects as they elicit anti-inflammatory, vasodilatory, fibrinolytic, and anti-apoptotic effects. They can be used as a treatment for acute MI.
Better diagnostic capability is provided by imaging methods such as myocardial perfusion single-photon emission computed tomography or cardiac magnetic resonance. Infarct size, left ventricular ejection fraction, a history of diabetes, CAD, and other factors are independent predictors of silent MI.
A genotype (CYP2C19 LOF mutation)-selected P2Y12 inhibitor instead of traditional clopidogrel shows no difference in ischemic events, thereby suggesting the incorporation of precision medicine earlier in the course of PCI.
Cardiovascular Disease 'anticipation Medicine.' There Are Two...
After PCI, genotype (CYP2C19)-guided P2Y12 inhibitor selection was superior to standard treatment in terms of thrombotic events and had less bleeding events.
Six genes (CNR2, DPP4, GLP1R, SLC5A1, HTR2C, MCHR1) encode the therapeutic targets in development of type 2 diabetes or
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