Increased Cardiovascular and Cerebrovascular Events in Patients With Lean vs Non-lean MASLD: A Multicenter Analysis

Abstract

INTRODUCTION:

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a significant contributor to morbidity and mortality, linked to adverse cardiovascular outcomes. While extensive research highlights the cardiovascular burden in non-lean MASLD, lean MASLD remains comparatively understudied. To address this gap, our study evaluates cardiovascular outcomes in lean MASLD compared with non-lean MASLD.

METHODS:

This is a retrospective cohort study of patients with MASLD identified in the multi-institutional database, TriNetX. Lean MASLD was defined as a body mass index <25 kg/m². Leveraging 1:1 propensity score matching, we balanced baseline characteristics, including age, sex, comorbidities, laboratory values, and medication use. Cox proportional hazards models were used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for cardiovascular events, cerebrovascular outcomes, new-onset heart failure, and all-cause mortality over 1-, 3-, 5-, and 7-year follow-up.

RESULTS:

After matching, there were 67,519 patients in both groups. At 7-year follow-up, lean patients with MASLD demonstrated significantly higher rates of new onset heart failure compared with non-lean patients with MASLD (HR: 1.23, 95% CI: 1.16–1.31, P < 0.0001), composite cardiovascular events (HR: 1.21, 95% CI: 1.13–1.30, P < 0.0001), cerebrovascular events (HR: 1.33, 95% CI: 1.24–1.43, P < 0.0001), and all-cause mortality (HR: 1.48, 95% CI: 1.38–1.59, P < 0.0001). These increased risks were noted at 1-, 3-, and 5-year follow-up.

DISCUSSION:

Patients with lean MASLD are at significantly higher risks of cardiovascular events and all-cause mortality compared with non-lean patients with MASLD. Further research is needed to clarify the underlying pathophysiology and develop tailored interventions to improve outcomes for this growing population.

INTRODUCTION

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease, affects approximately 1.7 billion individuals worldwide as of 2020. This number is projected to increase, potentially affecting one-third of the global population by 2030 (1) and up to 50% by 2040 (2). MASLD is linked to several metabolic conditions such as obesity, type 2 diabetes mellitus, insulin resistance, hypertriglyceridemia, and hypertension. These factors also contribute to the development of cardiovascular disease (CVD). Consequently, CVD is recognized as the leading cause of death in patients with MASLD (3–7).

While obesity is considered one of the key risk factors for developing MASLD, it is not exclusively limited to obese individuals (7,8). Lean MASLD, which is defined as MASLD in individuals with a body mass index (BMI) of less than 25, contributes to 15% of all patients with MASLD (9). Importantly, lean MASLD has been associated with a higher risk of cardiovascular mortality compared with non-lean MASLD (10).

Despite the growing recognition of the cardiovascular burden of MASLD, there is a paucity of literature examining the cardiovascular implications differences between lean and non-lean MASLD. Using a large multinetwork US database, we aim to evaluate cardiovascular events and mortality in lean MASLD compared with non-lean MASLD, thereby enhancing our understanding and guiding future therapeutic approaches.

METHODS

This cohort study used data from the TriNetX database, which collects deidentified, patient-level data from electronic health records. Information in the TriNetX database comes from health care organizations, typically academic centers, that collect data from their main and satellite hospitals and outpatient clinics. Available data include demographics, diagnoses (based on International Classification of Diseases, Tenth Revision, Clinical Modification codes), procedures (classified by International Classification of Diseases, Tenth Revision Procedure Coding System or Current Procedural Terminology), medications (Veterans Affairs Drug Classification System and RxNorm codes), laboratory tests (organized using Logical Observation Identifiers Names and Codes), and health care utilization records. We used the US Collaborative Network in TriNetX, which includes data from more than 110 million patients from 67 health care organizations in the United States (11,12).

Study population

All adult patients (older than 18 years) diagnosed with MASLD in the TriNetX database between January 1, 2005, and December 31, 2023, were included. Follow-up for these patients concluded on November 30, 2024. Patients were excluded if they met any of the following criteria: chronic liver disease other than MASLD (including alcohol-associated, viral, drug-induced, autoimmune, and genetic liver diseases, as well as liver cirrhosis); a history of excessive alcohol use, alcohol abuse, or alcohol use disorder; a history of alcohol-related disorders; HIV infection; solid organ transplantation; or a history of dialysis treatment. In addition, patients with a history of heart failure (HF), ischemic heart disease, unstable angina, myocardial infarction, aortic aneurysm or dissection, stroke (ischemic or hemorrhagic), cerebral infarction, transient ischemic attack, carotid intervention or surgery, coronary stenting, percutaneous coronary intervention, or coronary artery bypass grafting prior to MASLD diagnosis were also excluded, as shown in Supplementary Table 1 (http://links.lww.com/CTG/B463).

Study cohorts

Patients meeting the inclusion criteria were categorized into 2 groups: lean (study group) and non-lean (control group). Lean MASLD was defined as a BMI of <25 kg/m², while non-lean MASLD was classified as a BMI of ≥25 kg/m². The index event for both the study and control groups was defined as the first instance a patient met the eligibility criteria for inclusion (based on an MASLD diagnosis and BMI at time of diagnosis) within the predefined study.

We also conducted subgroup analyses according to age and ethnicity because ethnicity has been shown to influence metabolic and histologic features in MASLD (13). To account for ethnic differences in body composition, we applied a BMI cutoff of <25 kg/m² for lean MASLD in non-Asian individuals and <23 kg/m² for Asian individuals, consistent with prior studies (14).

Matching process

Each patient in the lean group was matched to a patient in the non-lean group using 1:1 propensity score matching (PSM) to minimize confounding. The propensity score model was adjusted for predefined potential confounders, including age, sex, self-reported race and ethnicity, nicotine dependence, BMI, diabetes, hypertension, hyperlipidemia, chronic respiratory disease, blood pressure, use of oral diabetes medications, insulin, angiotensin-converting enzyme inhibitors, β-blockers, antiarrhythmics, antilipemic agents, angiotensin receptor blockers, other antihypertensive medications, cholesterol levels, low-density lipoprotein levels, and serum triglyceride levels as shown in Table 1 (14,15).

Table 1.

Baseline characteristics of patients with lean and non-lean metabolic dysfunction-associated steatotic liver disease after propensity score matching

	Patients, no. (%)		P value	Standard mean difference
	Lean	Non-lean
Number of patients	67,519	67,519
Female	37,368 (55.3)	37,732 (55.9)	0.046	0.011
Male	28,125 (41.7)	27,849 (41.2)	0.127	0.008
Age at index, mean (SD)	49.4 (18.6)	48.0 (17.4)	0.010	0.014
Ethnicity
Hispanic	9,946 (14.7)	10,334 (15.3)	0.003	0.016
Not Hispanic	43,029 (63.7)	43,338 (64.2)	0.080	0.010
Others	14,544 (21.5)	13,847 (20.5)	<0.001	0.025
Race
White	41,997 (62.2)	41,930 (62.1)	0.707	0.002
Black or African American	6,288 (9.3)	6,356 (9.4)	0.525	0.003
Asian	5,996 (8.9)	5,617 (8.3)	<0.001	0.020
Others	4,431 (6.6)	4,667 (6.9)	0.010	0.014
Comorbidities
Type 2 diabetes	13,403 (19.9)	12,239 (18.1)	<0.001	0.044
Hypertension	23,641 (35.0)	22,232 (32.9)	<0.001	0.044
Dyslipidemia	17,076 (25.3)	16,192 (24.0)	<0.001	0.030
Obstructive sleep apnea	4,807 (7.1)	4,568 (6.8)	0.011	0.014
Atrial fibrillation and flutter	3,011 (4.5)	2,758 (4.1)	0.001	0.019
Chronic lower respiratory diseases	13,222 (19.6)	13,624 (20.2)	0.006	0.015
Nicotine dependence	10,537 (15.6)	10,859 (16.1)	0.016	0.013
Blood pressure, mean (SD), mm Hg
Systolic	124.8 (18.9)	127.1 (18.4)	<0.001	0.124
Diastolic	74.6 (12.3)	76.3 (12.2)	<0.001	0.142
Laboratory tests, mean (SD)
HbA1c, %	6.3 (2.0)	6.3 (1.9)	0.254	0.011
Alanine aminotransferase, U/L	44.9 (71.7)	47.2 (66.9)	<0.001	0.034
Aspartate aminotransferase, U/L	38.8 (71.9)	37.6 (77.9)	0.026	0.015
Total bilirubin, mg/dL	0.6 (0.6)	0.6 (0.5)	<0.001	0.066
Albumin, g/dL	4.1 (0.6)	4.1 (0.6)	0.011	0.017
Protein, g/dL	7.2 (0.8)	7.2 (0.8)	<0.001	0.066
Hemoglobin, g/dL	13.4 (2.0)	13.6 (2.0)	<0.001	0.092
Platelets, ×103/µL	260.9 (84.2)	263.0 (78.8)	<0.001	0.026
Creatine, mg/dL	0.8 (0.9)	0.8 (1.2)	0.173	0.009
Blood urea nitrogen, mg/dL	14.2 (7.4)	14.0 (6.6)	<0.001	0.026
Cholesterol, mg/dL	179.2 (56.2)	182.5 (52.8)	<0.001	0.060
Triglyceride, mg/dL	159.5 (171.5)	169.6 (198.5)	<0.001	0.055
High-density lipoprotein, mg/dL	47.7 (20.1)	45.4 (17.7)	<0.001	0.120
Low-density lipoprotein, mg/dL	101.4 (41.6)	105.1 (40.0)	<0.001	0.092
Prothrombin time (PT)	13.2 (3.9)	13.1 (3.9)	0.005	0.029
International normalized ratio	1.1 (0.4)	1.1 (0.3)	0.004	0.029
Medications
Cardiovascular
Antiarrhythmics	26,298 (38.9)	26,956 (39.9)	<0.001	0.020
β-Blockers	15,882 (23.5)	15,411 (22.8)	0.002	0.017
Antilipemic agents	17,667 (26.2)	16,790 (24.9)	<0.001	0.030
Angiotensin-converting enzyme inhibitors	9,467 (14.0)	8,985 (13.3)	<0.001	0.021
Angiotensin-II inhibitor	6,634 (9.8)	6,288 (9.3)	0.001	0.017
Calcium channel blockers	9,899 (14.7)	9,623 (14.3)	0.033	0.012
Diuretics	11,867 (17.6)	11,426 (16.9)	0.001	0.017
Other antihypertensives	8,672 (12.8)	8,575 (12.7)	0.429	0.004
Antidiabetic
Oral hypoglycemic agents	9,488 (14.1)	8,855 (13.1)	<0.001	0.027
Insulin	9,133 (13.5)	8,698 (12.9)	<0.001	0.019
Supplements
Vitamin D	11,342 (16.8)	11,523 (17.1)	0.189	0.007
Vitamin E	1,206 (1.8)	1,219 (1.8)	0.790	0.001

Study outcomes

The primary objective of this study was to determine the incidence or new onset of major adverse cardiovascular events, which were categorized into HF, composite cardiovascular events, and composite cerebrovascular events. Composite cardiovascular events were defined as the first occurrence of unstable angina, myocardial infarction, or revascularization procedures, including percutaneous coronary intervention or coronary artery bypass grafting. Composite cerebrovascular events were defined as the first occurrence of stroke (ischemic or hemorrhagic), cerebral infarction, transient ischemic attack, carotid intervention, or related surgical procedures. The secondary objective was to evaluate the incidence of all-cause mortality. Details of the codes used for these definitions are provided in Supplementary Table 2 (http://links.lww.com/CTG/B463).

Statistical analysis

All statistical analyses were conducted in real time using the TriNetX platform, which facilitated data processing and evaluation. Continuous variables were expressed as mean with SD, while categorical variables were presented as frequency and percentage. To address potential confounding, PSM was used to balance covariates between the lean and non-lean groups, with balance assessed using standardized mean differences (SMD), and an a priori threshold of 0.10. SMD was selected over P values for its robustness to sample size, ensuring a more accurate measure of group differences (17). Cox proportional hazards models were applied to estimate hazard ratios (HRs) for outcomes, while Kaplan-Meier survival analysis was used to calculate survival probabilities up to 7 years after the index event. Survival curves were compared using the log-rank test, and statistical significance was defined as a 2-sided α < 0.05. Data analysis was completed in November 2024.

Sensitivity analysis

Cardiovascular risks linked to MASLD may not become apparent immediately after diagnosis because short-term outcomes can be affected by various preexisting high-risk factors. Consequently, following the approach of Krishnan et al, we performed a sensitivity analysis by assessing risk after excluding patients who experienced outcomes within the initial 1 or 2 years postindex event, as shown in Supplementary Table 3 (http://links.lww.com/CTG/B463) (15,16).

RESULTS

A total of 381,989 patients with MASLD were identified. Among these patients, 67,541 were in the lean MASLD cohort, and 314,448 were in the non-lean MASLD cohort. After PSM, a total of 67,519 patients were included in each group (lean: mean [SD] age, 49.4 [18.6] years; 37,368 [55.3%] female; non-lean: mean [SD] age, 48.0 [17.4] years; 37,732 [55.9%] female). The groups were well-matched after PSM (SMD, <0.1) with only minor residual imbalances remaining after PSM (SMD, <0.25).

Patient characteristics

Table 1 describes the patient demographics, baseline comorbidities, laboratory parameters, and medications in both groups; most variables were similar in both groups (SMD, <0.1). However, there were some residual differences: patients who were non-lean, compared with those who were lean, had a higher baseline systolic blood pressure (mean [SD], 127.1 [18.4] vs 124.8 [18.9]; SMD, 0.124), diastolic blood pressure (mean [SD], 76.3 [12.2] vs 74.6 [12.3]; SMD, 0.142), and high-density lipoprotein levels (45.4 [17.7] mg/dL vs 47.7 [20.1] mg/dL; SMD 0.120). The remaining laboratory values, as well as medication use, were similar between both groups.

Outcomes

Patients were followed for 1, 3, 5, and 7 years to compare outcomes between the lean and non-lean groups. At the 1-year follow-up, lean patients exhibited a significantly higher rate of new-onset HF, with 2,629 cases in the lean group compared with 2,159 in the non-lean group (HR: 1.28, 95% CI: 1.18–1.38, P < 0.0001). Similarly, the incidence of composite cardiovascular events was greater in the lean group, with 1,361 events vs 1,120 in the non-lean group (HR: 1.27, 95% CI: 1.14–1.40, P < 0.0001). A comparable trend was observed for composite cerebrovascular events, with 1,403 events in the lean group and 1,063 in the non-lean group (HR: 1.42, 95% CI: 1.27–1.58, P < 0.0001). These risks were observed through the 3- and 5-year follow-up time points (Table 2) (Figure 1).

Table 2.

Measuring Outcomes Associated with Patients with Lean vs Non-lean Metabolic dysfunction-associated steatotic liver disease

Outcome	Number of events		Hazard ratio (95% CI)	P value
	Lean	Non-lean
New-onset heart failure, follow-up (yr)
1	2,629	2,159	1.254 (1.184, 1.327)	<0.0001
3	3,335	2,813	1.235 (1.175, 1.299)	<0.0001
5	3,599	3,104	1.219 (1.161, 1.278)	<0.0001
7	3,951	3,411	1.225 (1.17, 1.282)	<0.0001
Composite cardiovascular events, follow-up (yr)
1	1,361	1,120	1.249 (1.154, 1.351)	<0.0001
3	1,936	1,702	1.189 (1.114, 1.269)	<0.0001
5	2,164	1,941	1.179 (1.109, 1.253)	<0.0001
7	2,381	2,158	1.174 (1.107, 1.244)	<0.0001
Composite cerebrovascular events, follow-up (yr)
1	1,403	1,063	1.361 (1.257, 1.474)	<0.0001
3	2,043	1,653	1.297 (1.215, 1.384)	<0.0001
5	2,297	1,906	1.28 (1.204, 1.36)	<0.0001
7	2,521	2,035	1.326 (1.25, 1.405)	<0.0001
All-cause mortality, follow-up (yr)
1	1,233	800	1.588 (1.453, 1.736)	<0.0001
3	1,846	1,239	1.559 (1.451, 1.676)	<0.0001
5	2,109	1,449	1.543 (1.443, 1.649)	<0.0001
7	2,483	1,728	1.538 (1.446, 1.635)	<0.0001

Figure 1.

Incidence of cardiovascular disease in lean vs non-lean patients with metabolic dysfunction-associated steatotic liver disease.

At the 7-year follow-up, the cumulative incidence of adverse outcomes continued to be higher in the lean group. For HF, there were 3,951 cases in the lean group compared with 3,411 in the non-lean group (HR: 1.23, 95% CI: 1.16–1.31, P < 0.0001). Similarly, 2,381 composite cardiovascular events occurred in the lean group vs 2,158 in the non-lean group (HR: 1.21, 95% CI: 1.13–1.30, P < 0.0001). Composite cerebrovascular events were also more frequent among lean patients, with 2,521 events compared with 2,035 in the non-lean group (HR: 1.33, 95% CI: 1.24–1.43, P < 0.0001).

All-cause mortality

Mortality was significantly higher in the lean group compared with the non-lean group at the 7-year follow-up, with 2,483 deaths in the lean group vs 1,728 in the non-lean group, corresponding to an HR of 1.48 (95% CI: 1.38–1.59, P < 0.0001). Similarly, risks of all-cause mortality were significantly elevated in the lean group at earlier time points, including 1-year (1,233 vs 800 deaths; HR: 1.59, 95% CI: 1.45–1.74, P < 0.0001), 3-year (1,846 vs 1,239 deaths; HR: 1.56, 95% CI: 1.45–1.68, P < 0.0001), and 5-year follow-ups (2,109 vs 1,449 deaths; HR: 1.54, 95% CI: 1.44–1.65, P < 0.0001), as detailed in Table 2.

Subgroup analyses by sex and ethnicity

Figure 2 and Supplementary Table 4 (http://links.lww.com/CTG/B463) summarize the risk of adverse cardiovascular and mortality outcomes among patients with lean MASLD across different demographic subgroups. Among male patients with MASLD, those with lean MASLD had higher risks of new-onset HF (HR 1.29, 95% confidence interval (CI) 1.21–1.38, P < 0.0001), composite cardiovascular events (HR 1.23, 95% CI 1.14–1.32, P < 0.0001), composite cerebrovascular events (HR 1.43, 95% CI 1.31–1.55, P < 0.0001), and all-cause mortality (HR 1.62, 95% CI 1.49–1.76, P < 0.0001). Similar associations were observed among female patients with MASLD, with elevated risks of HF (HR 1.16, 95% CI 1.10–1.23, P < 0.0001), cardiovascular events (HR 1.13, 95% CI 1.05–1.22, P = 0.0009), cerebrovascular events (HR 1.31, 95% CI 1.22–1.40, P < 0.0001), and all-cause mortality (HR 1.62, 95% CI 1.50–1.74, P < 0.0001).

Figure 2.

Subgroup analyses of cardiovascular and mortality outcomes by sex and ethnicity.

When stratified by ethnicity, patients with lean MASLD who were White had higher risks of HF (HR 1.25, 95% CI 1.18–1.32, P < 0.0001), cardiovascular events (HR 1.36, 95% CI 1.27–1.46, P < 0.0001), cerebrovascular events (HR 1.18, 95% CI 1.11–1.26, P < 0.0001), and mortality (HR 1.57, 95% CI 1.47–1.69, P < 0.0001). Patients with lean MASLD who were Black also demonstrated increased risks of HF (HR 1.21, 95% CI 1.07–1.36, P = 0.0018), cardiovascular events (HR 1.21, 95% CI 1.03–1.43, P = 0.0232), cerebrovascular events (HR 1.36, 95% CI 1.17–1.59, P < 0.0001), and mortality (HR 1.49, 95% CI 1.25–1.78, P < 0.0001). Patients with lean MASLD who were Hispanic exhibited the strongest associations, with higher risks of HF (HR 1.40, 95% CI 1.21–1.62, P < 0.0001), cardiovascular events (HR 1.32, 95% CI 1.12–1.56, P = 0.0010), cerebrovascular events (HR 1.35, 95% CI 1.15–1.59, P = 0.0003), and mortality (HR 1.86, 95% CI 1.46–2.36, P < 0.0001). By contrast, among Asian patients with MASLD, lean status was associated with higher all-cause mortality (HR 1.44, 95% CI 1.01–2.05, P = 0.0434), while other cardiovascular and cerebrovascular outcomes were not significantly different from those with non-lean MASLD.

Sensitivity analysis

The sensitivity analysis showed that patients with lean MASLD continued to have significantly higher risks of new-onset HF, composite cardiovascular events, and composite cerebrovascular events across all follow-up periods. Similarly, the increased risk of all-cause mortality in the lean group compared with the non-lean group remained consistent. Full results of the sensitivity analysis are available in Supplemental Table 1 (http://links.lww.com/CTG/B463).

DISCUSSION

Our study investigated cardiovascular outcomes in lean vs non-lean individuals with MASLD across a large cohort of 137,242 participants followed over 7 years. Statistical adjustments were performed with priori-identified potential confounders to ensure baseline balance of the critical variables. At the 1-year follow-up, patients with lean MASLD exhibited markedly increased risks of new-onset HF, composite cardiovascular, and cerebrovascular events compared with non-lean MASLD which persisted throughout the 3-, 5-, and 7-year follow-up time points. Elevated cardiovascular and mortality risks also persisted when analyses were stratified by sex and was observed across racial and ethnic groups, with lean White, Black, and Hispanic patients demonstrating higher cardiovascular event rates compared with their non-lean counterparts at 7 years. However, among Asian patients, while all-cause mortality remained significantly elevated, cardiovascular outcomes did not differ between the lean and non-lean groups.

Our findings showed that while the association between lean MASLD and cardiovascular outcomes persisted across other racial and ethnic groups, it was not observed among Asian patients. A prior study from Japan similarly reported no difference in cardiovascular outcomes between lean and non-lean individuals with MASLD (18). Thus, our study suggests that the relationship between adiposity and cardiovascular risk may vary by race and ethnicity and may reflect population-specific genetic and metabolic characteristics. For instance, independent studies found that the PNPLA3 I148M mutation was associated with increased vascular damage in high-risk Hispanic individuals with MASLD but showed no or even protective effect on CVD in Asians (19). Further studies are warranted to elucidate these differences and clarify the underlying genetic and metabolic determinants of cardiovascular risk among patients with MASLD.

MASLD is one of the leading causes of chronic liver disease worldwide and has been associated with a higher risk of all-cause mortality, CVD, and cardiovascular mortality (20,21). While MASLD and obesity have a well-established relationship, a clinically important subgroup might be overlooked in lean individuals. Njei et al found that lean Veterans had a significantly higher risk of cardiovascular events and all-cause mortality compared with their non-lean counterparts, a trend that was also observed in a study of patients with type 2 diabetes across 16 centers, where lean individuals exhibited a greater risk of hypertension and CVD (22,23). Meanwhile, a systematic review reported that although lean MASLD was associated with higher cardiovascular mortality, the incidence of cardiovascular events was lower in this group (10). Another systematic review also demonstrated that while lean MASLD carried a higher all-cause mortality risk compared with non-lean MASLD, major adverse cardiovascular events were less frequent (24). Notably, Huo et al recently reported that lean MASLD carried higher risks of liver related outcomes and cardiovascular mortality but lower CVD incidence in 3 population-based cohorts (25). The contrasting findings in CVD risk likely reflect differences in cohort definition, population characteristics, cardiovascular outcome classification, and follow-up duration, as well as variability in mortality patterns that can influence how frequently cardiovascular events are captured across studies.

While MASLD has been associated with an increased risk of HF (26), the specific relationship between lean MASLD and HF is less clear. Our study contributes to this gap by providing new data on the association between lean MASLD and the onset of HF. In addition, our findings align with the concept of the obesity paradox, as supported by a meta-analysis showing that patients with acute myocardial infarction and a BMI of less than 25 have a lower risk of all-cause mortality than those with a BMI greater than 25 (27).

The elevated incidence of CVDs and the associated mortality risk in patients with lean MASLD observed in this study can arise from several potential mechanisms. First, prior studies have shown that patients with lean MASLD often exhibit disproportionate visceral adiposity and insulin resistance relative to BMI-matched controls, contributing to increased inflammation and atherogenic dyslipidemia that elevate cardiovascular risk (28,29). Although these pathophysiologic factors were not directly assessed in our dataset, our analysis accounted for metabolic comorbidities, HbA1c, and laboratory surrogates of disease activity to minimize residual confounding and partially capture differences in fibrosis severity and metabolic status. Furthermore, patients with lean MASLD exhibit a higher prevalence of subclinical atherosclerosis, as evidenced by increased carotid intima-media thickness and the presence of carotid plaques, indicators of early CVD (28). In addition, insulin resistance and hyperinsulinemia contribute to endothelial dysfunction and promote atherosclerosis, further elevating cardiovascular risk. Patients with lean MASLD are more likely to carry specific polymorphisms, such as the rs738409 C>G variant in the PNPLA3 gene, which is associated with a severe form of liver disease and, consequently, a higher risk of cardiovascular complications (30). Moreover, given that hepatocellular carcinoma is one of the leading causes of death in MASLD (31), a recent study has shown that lean MASLD is associated with a higher rate of hepatocellular carcinoma development compared with non-lean MASLD (9), which could also explain our findings of elevated mortality.

Overall, the atypical presentation of lean MASLD may lead to delayed diagnoses, highlighting the need for early recognition and tailored cardiovascular risk management. The American Diabetes Association's 2024 guidelines emphasize the necessity of comprehensive cardiometabolic risk management in patients with MASLD, given its strong association with CVD (32). This approach includes regular screening for cardiovascular risk factors and implementing targeted interventions to reduce these risks. Therefore, early recognition of lean MASLD and tailored cardiovascular risk management are crucial because of the significant risk of liver-related and cardiovascular events in this population. Conventional methods often focus on overweight or obese individuals, which may result in underdiagnosis of lean MASLD. Future research should focus on investigating the molecular mechanisms driving the metabolic abnormalities in lean MASLD, which might help to identify potential screening strategies and therapeutic targets.

Our study presents several strengths. The data derived from the TriNetX-based database were extensive and diverse, enabling thorough analyses of lean MASLD across various populations. Furthermore, our findings provide novel insights into the paradoxical cardiovascular risk patterns associated with lean MASLD, enriching the existing literature over 3 different time intervals, with follow-up extending up to 7 years. However, we acknowledge certain limitations in our study. The TriNetX-based data may be prone to errors related to coding or data entry, including misclassification and incomplete documentation. To mitigate these issues, we implemented standardized measures to identify outcomes and reduce the likelihood of documentation errors. While we adjusted our analyses accordingly, some residual confounding might still be present. In addition, our dataset lacked imaging modalities, such as conventional imaging techniques or elastography, and biopsy results which could have confirmed the diagnosis of MASLD. We also did not assess severe and progressive forms of MASLD, such as metabolic dysfunction-associated steatohepatitis, nor did we have access to detailed histologic or imaging-based assessments of steatosis severity or fibrosis stage. As a result, we were unable to explore how disease severity or fibrosis progression may influence prognosis or outcomes. Furthermore, as no approved therapies for metabolic dysfunction-associated steatohepatitis/MASLD existed during the study period, we could not assess medication effects but included key drug classes in our matching to minimize confounding. Finally, because data on alcohol consumption and alcohol use is often underreported, some cases of lean MASLD may actually fall under the category of alcohol-associated liver disease/met-ALD.

In conclusion, our study provides evidence that patients with lean MASLD face significantly higher risks of cardiovascular and cerebrovascular events, as well as all-cause mortality, compared with their non-lean counterparts. These findings emphasize the need for heightened awareness and tailored cardiovascular risk management in this unique MASLD subgroup, which is often overlooked because of its atypical presentation. Given the growing burden of MASLD worldwide, future research should focus on elucidating the underlying mechanisms driving this increased risk in lean individuals and exploring targeted screening and treatment strategies.

CONFLICTS OF INTEREST

Guarantor of the article: Yahya Alhalalmeh, MD.

Specific author contributions: O.A.T.: Study Design, Data collection, Statistical analysis, Data interpretation, Manuscript preparation, Literature search, Manuscript review. Y.A.: Study Design, Data collection, Statistical analysis, Data interpretation, Manuscript preparation, Literature search, Manuscript review. M.A.: Study Design, Manuscript preparation, Literature search, Manuscript review. A.N.: Study Design, Manuscript preparation, Literature search, Manuscript review. S.A.: Study Design, Manuscript preparation, Literature search, Manuscript review. S.S.: Manuscript preparation, Literature search, Manuscript review. P.D.: Manuscript preparation, Literature search, Manuscript review. D.D.S.: Manuscript preparation, Literature search, Manuscript review. B.N.: Study Design, Manuscript preparation, Literature search, Manuscript review. N.D.: Study Design, Manuscript preparation, Literature search, Manuscript review.

Financial support: None to report.

Potential competing interests: The authors have no conflicts of interests to declare.

Ethics approval and consent to participate: Given that we used deidentified patient data from the TriNetX database, no IRB approval or individual consent was required. TriNetX complies with HIPAA and other relevant privacy regulations to ensure data anonymity and security.

Consent for publication: Given that we used deidentified patient data from the TriNetX database, individual consent for publication is not required.

Data availability statement: The data supporting this study's findings were obtained from the TriNetX database, which provides access to real-world deidentified clinical data from multiple healthcare organizations. The dataset used for this analysis can be accessed through TriNetX with appropriate institutional access and agreements. For more information about TriNetX and its data access policies, please visit https://www.trinetx.com. Access is subject to TriNetX's terms and conditions, ensuring ethical use for research purposes.

Study Highlights.

WHAT IS KNOWN

• ✓ Patients with Metabolic dysfunction-associated steatotic liver disease are at increased risk of cardiovascular disease, especially those who are overweight or obese.

WHAT IS NEW HERE

• ✓ Lean patients with Metabolic dysfunction-associated steatotic liver disease have significantly higher risks of heart failure, cardiovascular and cerebrovascular events, and all-cause mortality compared with non-lean patients.

Supplementary Material

ct9-17-e00974-s001.docx ^{(22.2KB, docx)}

ABBREVIATIONS:

BMI

body mass index

CABG

coronary artery bypass grafting

CI

confidence interval

CVD

cardiovascular disease

HCO

health care organization

HbA1c

hemoglobin A1c

HF

heart failure

HIV

human immunodeficiency virus

HR

hazard ratio

ICD-10-CM

International Classification of Diseases

Tenth Revision

Clinical Modification

ICD-10-PCS

International Classification of Diseases

Tenth Revision

Procedure Coding System

LOINC

Logical Observation Identifiers Names and Codes

MACE

major adverse cardiovascular events

MASH

metabolic dysfunction-associated steatohepatitis

MASLD

metabolic dysfunction-associated steatotic liver disease

NAFLD

non-alcoholic fatty liver disease

PCI

percutaneous coronary intervention

PNPLA3

patatin-like phospholipase domain-containing 3

PSM

propensity score matching

RxNorm

National Library of Medicine standardized drug nomenclature

SD

standard deviation

SMD

standardized mean difference