The Basics of Metabolic Dysfunction–Associated Steatotic Liver Disease for Cardiologists

Pathophysiology, Diagnosis, and Treatment

Muhammad Shahzeb Khan, MD, MSC; Syed Sarmad Javaid, MBBS; Amreen Dinani, MD; Kara Wegermann, MD; Ambarish Pandey, MD; Ankeet S. Bhatt, MD, MBA, SCM; Mark Muthiah, MBBS; Harriette G.C. Van Spall, MD, MPH; Faiez Zannad, MD, PHD; Javed Butler, MD, MPH, MBA; Michael L. Volk, MD; Marat Fudim, MD, MHS

Disclosures

J Am Coll Cardiol. 2025;86(20):1861–1884

Abstract and Introduction

Abstract

Metabolic dysfunction–associated steatotic liver disease (MASLD) is now recognized as a multisystem disease closely linked to cardiovascular disease, which is the leading cause of death in this population. MASLD and cardiovascular disease share overlapping pathophysiological mechanisms including insulin resistance, chronic inflammation, oxidative stress, and endothelial dysfunction that not only drive the progression of each disease but may also potentiate one another. Recent initiatives, such as the cardiovascular-kidney-metabolic health framework and the cardiovascular-renalhepatic- metabolic model, underscore the importance of integrated, multidisciplinary care for managing multisystemic conditions like MASLD. In this context, cardiologists who frequently encounter MASLD-related comorbidities such as diabetes and obesity are well positioned to lead efforts in early detection, risk stratification, and management. This review offers cardiologists a comprehensive overview of MASLD, including the epidemiology, diagnostic approaches, and therapeutic options of MASLD while highlighting cardiologists’ pivotal role in its multidisciplinary management.

Introduction

Metabolic dysfunction–associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease (NAFLD), is one of the fastest-growing causes of chronic liver disease in the United States. Globally, MASLD affects about one-third of the population, with a higher prevalence among male (40%) compared with female (26%) individuals.^[1] In the United States, MASLD has now become the leading indication for liver trans- plantation, reflecting its growing clinical and public health burden. Although traditionally regarded as a liver-specific condition, growing evidence suggests that MASLD is a multisystem disease, linked to a range of extrahepatic conditions such as cardiovascular disease (CVD).^[2] In fact, CVD is the leading cause of mortality in individuals with MASLD.^[3] A meta-analysis involving 34,043 patients demonstrated a significantly increased risk of both fatal and nonfatal cardiovascular (CV) events among those with MASLD.^[4] Given this substantial burden, the relationship between MASLD and CVD has gained increasing attention within the field of cardiology.

Reflecting this evolving perspective, recent initiatives have emphasized the need for an integrated, multidisciplinary approach to the management of MASLD and related cardiometabolic disorders.^[5] In 2023, the American Heart Association (AHA) introduced the cardiovascular-kidney-metabolic health (CKMH) initiative, which calls for closer collaboration among cardiology, nephrology, and endocrinology to address overlapping pathophysiological processes.^[6] Building on this model, the cardiovascular- renal-hepatic-metabolic (CRHM) framework was developed to further recognize the impact of MASLD and its progression to metabolic dysfunction–associated steatoheatitis (MASH) on cardiometabolic outcomes.^[7] In parallel, there is growing recognition that the liver is not peripheral to CV health, prompting calls for the inclusion of individuals with MASLD in cardio-renal-metabolic clinical trials.^[8]

MASLD and CVD share key risk factors and converge on common pathological pathways, such as insulin resistance, chronic inflammation, oxidative stress, and endothelial dysfunction.^[9] Each condition may exacerbate the other’s progression. As a result, MASLD falls well within the scope of contemporary cardiology practice. Cardiologists routinely manage patients with metabolic comorbidities such as diabetes, obesity, and dyslipidemia, all of which are closely tied to MASLD. In addition, cardiologists frequently encounter clinical manifestations of hepatic dysfunction, including heart failure with preserved ejection fraction, atherosclerosis, and arrhythmias. These intersections highlight the need for cardiologists to develop a solid understanding of MASLD to effectively contribute to integrated care within multidisciplinary teams.

In this context, this article presents a comprehensive review of MASLD geared toward the practicing cardiologist. We discuss the disease’s definition, epidemiology, risk factors, diagnostic tools, and therapeutic options, while also summarizing current evidence linking MASLD to a range of CV conditions. In addition, we highlight the key role of cardiologists in multidisciplinary care, with a focus on early detection, risk assessment, and timely intervention to improve outcomes in MASLD.

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TABLE 1 Summary of Studies Investigating the Association Between MASLD/MASH and CVD
Author, Year	Study Design	Study Settings	Patient Population	Sample Size (n)	MASLD Diagnosis	Objectives	Covariates Adjusted	Outcomes	Effect Size (RR, OR, HR, MD, 95% CI)
Atherosclerotic disease
Atherosclerotic disease Sung et al, 2023⁷³	Cross-sectional and longitudinal cohort Study	South Korea	Participants who underwent health examinations for the assessment of fatty liver and CAC	162,180 (Cross-sectional study) 34,233 (Longitudinal cohort study)	US or CT	To examine associations between MASLD and the risk of having or developing CAC	Age, sex, education level, smoking history, exercise, LDL, prior history of CAD, and use of lipid-lowering medications	Association between MASLD and presence of CAC (cross-sectional analysis) Association between MASLD and incident CAC (longitudinal analysis)	aOR: 1.34 (1.29 to 1.39) P < 0.05 aHR: 1.68 (1.43 to 1.99) P < 0.05
Ma et al, 2022⁷⁴	Prospective cohort study	United Kingdom	Adults aged 40–69 years, free of baseline CVD and chronic liver disease	215,245	FLI	To investigate the link between MASLD and adverse CVD outcomes	Age, sex, ethnicity, smoking status, TC, diabetes, and HTN	Association between MASLD and AMI mortality Association between MASLD and stroke mortality	aHR: 1.58 (1.19 to 2.11) P < 0.01 aHR: 1.18 (0.85 to 1.64) P = 0.32
Shang et al, 2022⁷⁵	Retrospective cohort study	Sweden	Adults ≥18 years with MASLD and cardiometabolic risk factors	106,336	ICD-9/10 codes	To assess the association between MASLD and CV outcomes compared with the general population	Matched for age, sex, municipality, and HTN; adjusted for T2DM, dyslipidemia, obesity, and COPD	Association between MASLD and fatal CVD events Association between MASLD and nonfatal CVD events	aHR: 1.20 (0.98 to 1.42) P > 0.05 aHR: 3.71 (3.29 to 4.17) P < 0.05
Mantovani et al, 2021⁷⁶	Meta-analysis	Asia, Europe, the United States, and Egypt	Adults (≥18 years) with and without MASLD, excluding those with significant alcohol consumption or other causes of liver disease	5,802,226	Imaging, ICD-9/10 codes, or liver biopsy	To assess the long-term risk of fatal and nonfatal CVD events associated with MASLD	Age, sex, smoking status, adiposity measures, SBP, or HTN status, lipid profile, and glycemic status (preexisting diabetes, FBG, or HbA1c levels)	Association between MASLD and risk of fatal or nonfatal CVD events	aHR: 1.31 (1.31 to 1.61) P < 0.05
Chang et al, 2020⁷⁷	Prospective cohort study	South Korea	Individuals with and without MASLD, excluding those with other causes of liver disease	218,030	US	To assess the risk of CVD hospitalization in patients with MASLD	Age, sex, BMI, smoking, physical activity, educational level, total calorie intake, family history of CVD, diabetes, HTN, LDL, medications, plasma high-sensitivity CRP, HOMA-IR	Association between MASLD and CVD hospitalization for ischemic heart disease or ischemic stroke	aHR: 1.05 (0.89 to 1.23) P > 0.05
Alexander et al, 2019⁷⁸	Retrospective cohort study	Italy, Spain, and the Netherlands	Adults with MASLD/MASH from 4 European primary care databases	120,795	ICD/Read/ICPC codes	To assess the risk of incident AMI and stroke in people with MASLD, compared with matched controls	Age, sex, smoking, T2DM, SBP, TC, statin use, and HTN	Risk of incident AMI in patients with MASLD aHR: 1.01 (0.91 to 1.12) P = 0.12	Risk of incident stroke in patients with MASLD aHR: 1.04 (0.99 to 1.09) P = 0.92
Allen et al, 2019⁷⁹	Retrospective cohort study	United States	Adults diagnosed with MASLD	19,078	ICD-9 codes	To examine whether female sex remains a protective factor against CVD in MASLD	Age, sex, county	To assess the association between MASLD and CV events in women	aHR: 0.90 (0.74 to 1.08) P = 0.25
Hwang et al, 2018⁸⁰	Prospective cohort study	South Korea	Adults aged 20–94 years undergoing health screening, with cardiometabolic risk factor assessment	318,224	US	To assess the link between MASLD and CVD mortality in men and women	Age, sex, BMI, smoking status, alcohol consumption, physical activity, diabetes, HTN, hypercholesterolemia	Association between MASLD and CVD mortality in men Association between MASLD and CVD mortality in women	aHR: 1.09 (0.82 to 1.44) P = 0.56 aHR: 1.63 (1.00 to 2.66) P = 0.05
Zou et al, 2017⁸¹	Cross-sectional study	China	Patients aged ≥40 years with T2DM	2,646	US	To explore the association between MASLD and PAD in patients with T2DM	Age, gender, education, smoking status, use of insulin or oral antidiabetic medication, BMI, FPG, SBP, TG, and TC	Association between MASLD and PAD	aOR: 1.49 (1.12 to 2.00) P = 0.009
Sinn et al, 2016⁸²	Retrospective cohort study	South Korea	Males with abdominal and carotid US performed at least 1 year apart	8,020	US	This study assessed the longitudinal association between MASLD and the onset of SCA	Age, smoking, alcohol consumption, BMI, weight change, SBP, use of antihypertensive and lipid-lowering medications, FPG, use of hypoglycemic medications, LDL, HDL, TG level	Risk of SCA in MASLD Risk of SCA in patients with high FIB-4 score	aHR: 0.91 (0.80 to 1.03) P = 0.12 aHR: 1.43 (1.19 to 1.70) P < 0.001
Lazo et al, 2011⁸³	Prospective cohort study	United States	Adults aged 20–74 years with cardiometabolic risk factors	11,371	US	To evaluate the link between MASLD/MASH and CVD mortality.	Age, sex, BMI, ethnicity, education, smoking status, alcohol consumption, physical activity, HTN, dyslipidemia, T2DM	Association between MASLD and CVD mortality Association between MASH and CVD mortality	aHR: 0.86 (0.67 to 1.12) P > 0.05 aHR: 0.59 (0.29 to 1.20) P > 0.05
Cardiac arrhythmias
Simon et al, 2023⁸⁴	Retrospective cohort study	Sweden	Adults ≥18 years in with liver biopsy–confirmed MASLD	63,062	Liver biopsy	To examine the incidence of cardiac arrhythmias according to the presence and histological severity of MASLD	Age, sex, calendar year, county, diabetes, obesity, HTN, dyslipidemia, CKD, a family history of early CVD, education, hospitalizations, and alcohol use	Association between MASLD and incident cardiac arrhythmias	aHR: 1.30 (1.22 to 1.38) P < 0.05
Cai et al, 2020⁸⁵	Meta-analysis	Korea, Germany, the United States, and Italy	Adult patients (≥18 years) diagnosed with MASLD and having cardiometabolic risk factors	614,673	FLI, CT, and ICD-10 code	To examine the association of MASLD with the risks of AF	Age, gender, smoking, BMI or obesity, HTN, BP or antihypertensive treatment, FPG, HbA1c or T2DM, and serum cholesterol or hypercholesterolemia	Association between MASLD and AF risk	aRR: 1.19 (1.04 to 1.31) P = 0.001
Mantovani et al, 2019⁸⁶	Meta-analysis	Europe, Asia, the United States	Adult patients (≥18 years) diagnosed with MASLD and having cardiometabolic risk factors	364,919	FLI, CT, US, and ICD-9 code	To examine the association between MASLD and the risk of prevalent AF	Age, sex, BMI, HTN, T2DM, dyslipidemia, and smoking	Association between MASLD and prevalent AF	aOR: 2.07 (1.38 to 3.10) P < 0.05
Hung et al, 2015⁸⁷	Cross-sectional study	Taiwan	Adults ≥20 years attending routine health checkups	31,116	US	To investigate the association between MASLD and QT prolongation among the general population with or without diabetes	Age, sex, diabetes, HTN, cholesterol, HDL, TGs, AST, BMI, LV hypertrophy, a history of CAD, hypokalemia, eGFR, CRP, and smoking	Association between severe MASLD and QTC prolongation (≥440 ms) in men, bazett's criteria Association between severe MASLD and QTC prolongation (=440 ms) in women, Bazett's criteria	aOR: 1.87 (1.51 to 2.31) P < 0.001 aOR: 2.28 (1.89 to 2.74) P < 0.001
Cardiomyopathy
Yong et al, 2022⁸⁸	Meta-analysis	Asia, Europe, the United States, and Brazil	Patients with MASLD and cardiometabolic risk factors are undergoing evaluation of echocardiographic parameters	33,891	Liver biopsy, US, MRI, and CT	To examine the systolic, diastolic, and structural echocardiographic characteristics in patients with MASLD	NR	LVEF MASLD vs non-MASLD (%) LVM MASLD vs non-MASLD (g)	MD: -0.693 (-1.11 to -0.27) P = 0.001 MD: 34.5 (26.24 to 42.73) P < 0.001
VanWagner et al, 2020⁸⁹	Longitudinal cohort study	United States	Patients who underwent ECG and CT during the 25-year follow-up examination	2,713	CT	To determine the association between MASLD and subclinical abnormalities in cardiac structure and function	Unadjusted	LVM in MASLD vs non-MASLD patients (g) LVMI, in MASLD vs non-MASLD patients (g/m indexed to height 2.7) LVEF MASLD vs non-MASLD (%)	196.5 vs 164.1 P < 0.0001 45.1 vs 39.3 P < 0.0001 62.0 vs 61.6 P = 0.42
Jung et al, 2017⁹⁰	Cross-sectional study	South Korea	Adults aged 18-84 years undergoing routine health checkups	20,821	US	To assess whether MASLD is associated with the risk for LV diastolic dysfunction and remodeling	Sex, age, physical activity, current smoking, alcohol consumption, HTN, diabetes, CRP, HOMA-IR, HDL, TC, creatinine, and BMI	Association between MASLD and abnormal LV relaxation Association between MASLD and LV remodeling	aOR: 1.95 (1.61 to 2.35) P < 0.05 aOR: 1.95 (1.61 to 2.35) P < 0.05
Valvular heart disease
Hao et al, 2024⁹¹	Observational study	United States	Participants aged between 45 and 84 years with no prior history of CVD	4,226	Liver enzymes, CT, MRI, and liver biopsy	To investigate the association between MASLD and incident aortic valve calcification	Age, race, sex, BMI, alcohol drinking status, physical activity, SBP, smoking status, CRP, FPG, HTN, LDL, use of lipid-lowering medication, and hypoglycemic medication	Association between MASLD and incident aortic valve calcification	aHR: 1.58 (1.03 to 2.43) P = 0.038
Mantovani et al, 2015⁹²	Cross-sectional study	Italy	T2DM outpatients without a history of HF, valvular heart conditions, or liver diseases	247	US	To determine the association between MASLD and valvular calcification in diabetic patients	Age, sex, WC, smoking history, HbA1c, LDL, eGFR, DBP, use of hypoglycemic, lipid-lowering, and antihypertensive drugs	Association between MASLD and valvular calcification (AVS and/or MAC) Association between MASLD and MAC Association between MASLD and AVS	aOR: 2.70 (1.23 to 7.38) P < 0.01 aOR: 3.01 (1.12 to 7.99) P = 0.026 aOR: 2.65 (1.07 to 6.31) P = 0.035
Bonapace et al, 2014⁹³	Cross-sectional study	Italy	T2DM patients free from ischemic heart disease, valvular heart conditions, liver disorders, or excessive alcohol use	180	US	To investigate the association between MASLD and AVS in patients with T2DM	Age, sex, BMI, smoking status, daily alcohol consumption, HTN, dyslipidemia, duration of diabetes, diabetes treatment, HbA1c, and eGFR	Association between MASLD and AVS	aOR: 3.04 (1.30 to 7.30) P = 0.01
Hypertension
Li et al, 2022⁹⁴	Meta-analysis	Asia, Europe, and the United States	Participants aged ≥18 years with cardiometabolic risk factors	86,342	US, CT, and surrogate scores (FLI, hepatic steatosis index, and comprehensive MASLD score)	To examine the association between MASLD and HTN	Age and sex	Association between MASLD and the incidence of HTN	aHR: 1.55 (1.29 to 1.87) P < 0.01
Bonnet et al, 2017⁹⁵	Prospective cohort study	France	Adults aged 30–65 years without baseline HTN	2,565	FLI	To evaluate whether the FLI predicts incident HTN in normotensive individuals	Age, sex, smoking, FPG, alcohol intake, and HOMA-IR	Association between FLI and incident HTN	aOR: 1.44 (1.20 to 1.74) P = 0.0001
Ryoo et al, 2014⁹⁶	Prospective cohort study	South Korea	Participants free of CVD and liver disease, undergoing routine health checkups	22,090	US	To investigate the association between MASLD and the development of HTN	Age, BMI, TG, serum creatinine, liver enzymes, recent smoking status, regular exercise, and T2DM	Association between severe to moderate MASLD and incident HTN	aHR: 1.14 (1.00 to 1.30) P ≥ 0.05
Lau et al, 2010⁹⁷	Prospective longitudinal cohort study	Germany	Patients aged 20–79 years with cardiometabolic risk factors	3,191	US	To examine the relationship between FLD and BP, including HTN	Age, sex, WC, BMI, T2DM, mean daily alcohol consumption, and the use of antihypertensive medication	Association between HTN and US+ with increased ALT at follow-up
Heart failure
Roderburg et al, 2023⁹⁸	Retrospective cohort study	Germany	Participants =18 years with cardiometabolic risk factors	173,966	ICD-10 codes	To examine the association between MASLD and incident HF, adjusting for established HF risk factors	CKD Antihypertensive and statin therapy	Association between MASLD and incident HF	aHR: 1.29 (1.24 to 1.34) P < 0.001 aHR: 1.41 (1.36 to 1.47) P < 0.001
Simon et al, 2022⁹⁹	Retrospective cohort Study	Sweden	Adults aged ≥18 with no underlying cause of liver disease and free from CVD	56,939	Liver biopsy	To investigate the relationship between the severity of biopsy-confirmed MASLD and the incidence of major adverse CV events (CHF)	Age, sex, year, county of residence, education, diabetes, obesity, HTN, dyslipidemia, CKD, family history of CVD, and alcohol use disorder	Association between MASLD and CHF Association between MASH without fibrosis and CHF	aHR: 1.75 (1.63 to 1.87) P < 0.05 aHR: 1.60 (1.31 to 1.96) P < 0.05
Fudim et al, 2021¹⁰⁰	Retrospective cohort study	United States	Medicare beneficiaries with no known history of HF	870,535	ICD-9 codes	To evaluate the relationship between MASLD and the risk of developing HF, including HFpEF and HFrEF	Age, sex, race, region, HTN, diabetes, obesity, AMI, AF, CKD, and VD	Risk of overall HF in MASLD Risk of HFpEF in MASLD	aHR: 1.23 (1.18 to 1.29) P < 0.001 aHR: 1.24 (1.14 to 1.34) P < 0.001
Roh et al, 2020¹⁰¹	Retrospective cohort Study	South Korea	Adults aged ≥20 with no history of HF and comorbid conditions	308,578	FLI	To assess the relationship between FLI and the risk of new-onset HF	Age, sex, smoking, alcohol consumption, physical activity, SBP, DBP, and cholesterol	Association between FLI (12.6-31.0) and new-onset HF Association between FLI (>31.0) and new-onset HF	aHR: 1.31 (1.147 to 1.504) P < 0.001 aHR: 1.71 (1.489 to 1.964) P < 0.001

AF = atrial fibrillation; aHR = adjusted hazard ratio; ALT = alanine aminotransferase; AMI = acute myocardial infarction; aOR = adjusted odds ratio; aRR = adjusted relative risk; AST = aspartate aminotransferase; AVS = aortic valve sclerosis; BMI = body mass index; BP = blood pressure; CAC = coronary artery calcification; CAD = coronary artery disease; CHF = congestive heart failure; CI = confidence interval; CKD = chronic kidney disease; COPD = chronic obstructive pulmonary disease; CRP = C-reactive protein; CT = computed tomography; CV = cardiovascular; CVD = cardiovascular disease; DBP = diastolic blood pressure; ECG = electrocardiogram; eGFR = estimated glomerular filtration rate; FBG = fasting blood glucose; FIB-4 = Fibrosis-4 index; FLD = fatty liver disease; FLI = fatty liver index; FPG = fasting plasma glucose; HbA1c = hemoglobin A1c; HDL = high-density lipoprotein; HF = heart failure; HFpEF = heart failure with preserved ejection fraction; HFrEF = heart failure with reduced ejection fraction; HOMA-IR = homeostasis model assessment of insulin resistance; HTN = hypertension; ICD = International Classification of Diseases; ICPC = International Classification of Primary Care; LDL = low-density lipoprotein; LV = left ventricle; LVEF = left ventricular ejection fraction; LVM = left ventricular mass; LVMI = left ventricular mass index; MAC = mitral annular calcification; MASLD = metabolic dysfunction–associated steatotic liver disease; MASH = metabolic dysfunction–associated steatohepatitis; MD = mean difference; MRI = magnetic resonance imaging; PAD = peripheral arterial disease; QTc = corrected QT interval; SBP = systolic blood pressure; SCA = subclinical atherosclerosis; T2DM = type 2 diabetes mellitus; TC = total cholesterol; TG = triglyceride; US = ultrasound; US+ = ultrasound positive; VD = valvular disease; WC = waist circumference.

Authors and Disclosures

Muhammad Shahzeb Khan, MD, MSC_a,b,c; Syed Sarmad Javaid, MBBS^d; Amreen Dinani, MD^e,f; Kara Wegermann, MD^g; Ambarish Pandey, MD^h; Ankeet S. Bhatt, MD, MBA, SCM^i,j; Mark Muthiah, MBBS^k,l,m; Harriette G.C. Van Spall, MD, MPHⁿ; Faiez Zannad, MD, PHD^o; Javed Butler, MD, MPH, MBA^a; Michael L. Volk, MD^p; Marat Fudim, MD, MHS^q

From the ^aBaylor Scott and White Research Institute, Dallas, Texas, USA; ^b Department of Medicine, Baylor School of Medicine, Temple, Texas, USA; ^c Division of Cardiology, Heart Hospital Plano, Plano, Texas, USA; ^dDepartment of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA; ^eDivision of Gastroenterology, Duke University, Durham, North Carolina, USA; ^fDivision of Liver Diseases, Icahn School of Medicine at Mount Sinai, New York, New York, USA; ^gDepartment of Medicine, Division of Gastroenterology and Hepatology, Duke University, Durham, North Carolina, USA; ^hDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA; ⁱDivision of Research, Kaiser Permanente San Francisco Medical Center, San Francisco, California, USA; ^jDivision of Cardiovascular Medicine, Stanford University School of Medicine, Palo Alto, California, USA; ^kDivision of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore; ^l Yong Loo Lin School of Medicine, National University of Singapore, Singapore; ^mNational University Centre for Organ Transplantation, National University Health System, Singapore; ⁿDepartment of Medicine and Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; ^oCentre d’Investigations Cliniques Plurithématique 1433, Université de Lorraine, Nancy, France; ^pDepartment of Internal Medicine, Baylor Scott and White Central Texas, Temple, Texas, USA; and the ^q Division of Cardiology, Duke University Medical Center, Durham, North Carolina, USA.

FUNDING SUPPORT AND AUTHOR DISCLOSURES No funding was received for this study. Dr Khan has received fees from Bayer, Boehringer Ingelheim, and Novartis. Dr Van Spall serves on a trial executive committee for Novo Nordisk. Dr. Dinani is a consultant for Guidepoint and Kinetix. Dr Pandey has received grant funding (to the institution) from Applied Therapeutics, Gilead Sciences, Ultromics, Myovista, and Roche; has served as a consultant for and/or received honoraria outside of the present study as an advisor/consultant for Tricog Health Inc, Lilly USA, Rivus, Cytokinetics, Roche Diagnostics, Sarfez Therapeutics, Edwards Life-sciences, Merck, Bayer, Novo Nordisk, Alleviant, and Axon Therapies; has received nonfinancial support from Pfizer and Merck; is a consultant for Palomarin Inc with stocks compensation; and has received research support from the National Institute on Aging GEMSSTAR Grant (1R03AG067960-01), the National Institute on Minority Health and Disparities (R01MD017529), and the National Heart, Lung, and Blood Institute (NHLBI) (R21HL169708). Dr Bhatt has received research grant support to his institution from NIH/ NHLBI, NIH/National Institute on Aging, the American College of Cardiology Foundation, and the Centers for Disease Control and Prevention; and has received consulting fees from Novo Nordisk, Merck, and Sanofi. Dr Butler has served as a consultant for Abbott, American Regent, Amgen, Applied Therapeutic, AskBio, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, Cardiac Dimension, Cardiocell, Cardior, Cardiorem, CSL Bearing, CVRx, Cytokinetics, Daxor, Edwards, Element Science, Faraday, Foundry, G3P, Innolife, Impulse Dynamics, Imbria, Inventiva, Ionis, Lexicon, Lilly, LivaNova, Janssen, Medtronics, Merck, Occlutech, Owkin, Novartis, Novo Nordisk, Pfizer, Pharmacosmos, Pharmain, Prolaio, Regeneron, Renibus, Roche, Salamandra, Sanofi, SC Pharma, Secretome, Sequana, SQ Innovation, Tenex, Tricog, Ultromics, Vifor, and Zoll. Dr Zannad has received personal fees from 89Bio, Abbott, Acceleron, Applied Therapeutics, Bayer, Betagenon, Boehringer, BMS, CVRx, Cambrian, Cardior, Cereno Pharmaceutical, Cellprothera, CEVA, Inventiva, KBP, Merck, Novo Nordisk, Owkin, Otsuka, Roche Diagnostics, Northsea, and USa2; has stock options at G3Pharmaceutical and equities at Cereno, Cardiorenal, and Eshmoun Clinical Research; and is the founder of Cardiovascular Clinical Trialists. Dr Fudim is supported by American Heart Association Grant 17MCPRP33460225 and NIH T32 Grant 5T32HL007101; and is a consultant for Coridea and Galvani. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

ADDRESS FOR CORRESPONDENCE: Dr Muhammad Shahzeb Khan, The Heart Hospital Plano, 1100 Allied Drive, Plano, Texas 75024, USA. E-mail: Shahzeb. Khan@Bswhealth.org. OR Dr Marat Fudim, Division of Cardiology, Duke University Medical Center, 2301 Erwin Road, Durham, North Carolina 27710, USA. E-mail: marat.fudim@duke.edu.

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The Basics of Metabolic Dysfunction–Associated Steatotic Liver Disease for Cardiologists

Pathophysiology, Diagnosis, and Treatment

Abstract and Introduction

Abstract

Introduction

Tables

References

Authors and Disclosures

Authors and Disclosures

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