DOI: https://doi.org/10.21203/rs.3.rs-2017919/v1
Background and aims
Non-alcoholic fatty liver disease (NAFLD) is associated with a greater risk of developing cardiovascular disease and have adverse impacts on the cardiac structure and function. Little is known about the effect of non-obese NAFLD upon cardiac function and structure. We aimed to compare the echocardiographic parameters reflecting the structures and functions of left ventricle (LV) between non-obese NAFLD group and control group, and explore the correlation of non-obese NAFLD with early LV diastolic dysfunction.
Methods and results
In this cross-sectional study, 316 non-obese inpatients were enrolled, including 72 participants with NAFLD (non-obese NAFLD group) and 244 participants without NAFLD (control group). LV structural and functional indices of two groups were comparatively analyzed. Early LV diastolic dysfunction was defined as the ratio of the peak velocity of the early filling (E) wave to the atrial contraction (A) wave <1. Compared with control group, the non-obese NAFLD group had the lower E/A〔(0.80±0.22) vs (0.88±0.35), X2=2.528, p =0.012〕and the smaller LV end-diastolic diameter〔(4.51±0.42)cm vs (4.64±0.43)cm, X2=2.182, p=0.030〕. Multivariate Logistic regression analysis showed that non-obese NAFLD was independently associated with an increased risk of early LV diastolic dysfunction〔OR=4.050，95%CI (1.452，11.296)，p=0.008〕.
Conclusions
Non-obese NAFLD was associated with an increased risk of early LV diastolic dysfunction, independent of well-identified cardiovascular risk factors.
In recent years, nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease globally. The disease is associated with many metabolic risk factors such as obesity, diabetes mellitus (DM), insulin resistance, dyslipidemia[1]. In the general population, the prevalence of NAFLD is estimated to be 25% in the world[2] and it is about 30% in China[3]. Previous studies have shown that NAFLD is closely related to obesity which will increase the prevalence of NAFLD[4], while it may also affect normal-weight individuals, a condition termed as non-obese NAFLD[5], which includes individuals with a BMI < 30kg/m2 in the Caucasian population and a BMI < 25 kg/m2 in the Asian population[6, 7]. The global incidence of NAFLD in the non-obese population was about 25 per 1000 person-years and around 40% of the global NAFLD population were classified as non-obese[5, 8]. In Asia, about 30% of NAFLD population were non-obese[9]. The prevalence of NAFLD is about 7–19%[10, 11] and 8–20% among people with BMI < 25kg/m2 in Asia and China respectively[12, 13], which is increasing with years[14].
Non-obese NAFLD is similar to obese NAFLD in pathophysiological mechanisms, such as hepatic lipid accumulation[15], insulin resistance[13], metabolic dysfunction of visceral fat[16], genetic susceptibility[17]. Many studies have shown that NAFLD has an adverse impact on the cardiac structure and function[18–20], which may associate with myocardial glucose uptake, myocardial fat infiltration, inflammation, oxidative stress[21, 22]. Studies have shown that an incrementally increased risk for LV diastolic dysfunction according to fibrosis grade was prominent in the non-obese population[23]. However, less studies are about the effect of non-obese NAFLD on left ventricular (LV) structure and function, so the purpose of this study is to assess the correlation of non-obese NAFLD with early LV diastolic dysfunction by comparing LV structural and functional indices between non-obese NAFLD group and control group.
The subjects of this cross-sectional study were inpatients from the Department of Geriatrics, Peking University People's Hospital from January 2018 to December 2020. The inclusion criteria were: (1) age ≥ 40 years old; (2)BMI<25kg/m2; (3) the imaging examination of liver (abdominal ultrasound or CT) and echocardiography were performed during hospitalization; (4) complete demographic, laboratory and imaging information. The exclusion criteria refer to the Guidelines of Prevention and Treatment for Nonalcoholic Fatty Liver Disease (2018 Updated Edition)[24] as follows: (1) excessive alcohol intake (> 30g/d in men and > 20g/d in women); (2) detected positive serum markers of hepatitis B and C; (3) secondary causes of fatty liver including viral hepatitis, drug-induced liver disease, autoimmune liver disease, hepatolenticular degeneration, total parenteral nutrition, inflammatory bowel disease, celiac disease, Cushing's syndrome, β-lipoprotein deficiency, lipid atrophy diabetes mellitus, Mauriac syndrome; (4) end-stage liver diseases including hepatic fibrosis, liver cirrhosis, liver cancer and liver failure; (5) basic heart diseases including coronary heart disease, congenital heart disease, valvular heart disease, pulmonary heart disease, hypertrophic cardiomyopathy, cardiac surgery, aortic dissection, heart failure; (6) chronic renal failure or malignancies; (7) pregnancy. Patients who met the inclusion criteria were divided into non-obese NAFLD group and control group according to the results of imaging examination of liver. The imaging diagnostic criteria of NAFLD refer to the Guidelines for Management of Nonalcoholic Fatty Liver Disease (2010 Revision)[25].
Complete blood count, blood biochemistry, blood glucose metabolism and other indicators of patients were collected retrospectively. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ-glutamyl transpeptidase (γ-GT), serum albumin (Alb), serum creatinine (Cr), serum uric acid (UA), fasting blood glucose (FBG), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were detected by automatic biochemical analyzer AU5832. Hemoglobin (Hb) and platelet count (PLT) were measured by blood cell analyzer DxH800, HbA1c was measured by glycosylated hemoglobin analyzer Primus9210, and estimated glomerular filtration rate (eGFR) was obtained by CKD-EPI method[26]. Height and body weight were measured using a digital scale. The body mass index (BMI) was calculated as weight (kg)/height (m2). The body surface area (BSA, male) was calculated as 0.0057× height (cm) + 0.0121× weight (kg) + 0.0082, and BSA (female) was calculated as 0.0073× height (cm) + 0.0127× weight (kg)-0.2106[27]. Obesity is defined as BMI ≥ 25kg/m2 and non-obesity is defined as BMI < 25kg/m2 [7]. We collected current comorbidities, including hypertension, DM and obstructive sleep apnea-hypopnea syndrome (OSAHS), and medication history, including antihypertensive, lipid-lowering and hypoglycemic drugs. Smoking history and family history of heart diseases were also collected. Smokers were defined as individuals who had a continuous or cumulative smoking time ≥ 1 year.
The results of echocardiography were collected retrospectively. Echocardiography was performed by Acusonsc-2000 Full Digital Color Doppler Ultrasonic Instrument, which was completed and reviewed by two sonographers (at least one of them is associate chief physician or chief physician). In this study, the results of echocardiography were used to evaluate the cardiac structure and function, and the echocardiographic parameters included interventricular septal thickness at diastole (IVSd), left ventricular posterior wall thickness at diastole (LVPWd), left ventricular mass (LVM), left ventricular mass index (LVMI), ejection fraction (EF), left ventricular end-systolic diameter (LVESD), left ventricular end-diastolic diameter (LVEDD), the peak velocity of the early filling (E) wave, the peak velocity of the atrial contraction (A) wave and E/A. In this study, E/A<1 indicates the early LV diastolic dysfunction.
Statistical analyses were conducted using SPSS 26.0 software package of IBM. The measurement data conforming to the normal distribution was expressed as the mean ± standard deviation (‾x ± s), and the independent sample t-test or variance analysis was used to compare the continuous variables between two groups. The categorical variables were analyzed by x2 test. Univariate logistic regression was used to find out confounding factors, and two-class logistic regression (backward: LR) was used to analyze the relationship between non-obese NAFLD and early LV diastolic dysfunction. p value of < 0.05 was considered statistically significant.
A total of 316 subjects met the inclusion criteria for the study and were finally included in this analysis, which including 118 males and 198 females, with an average age of (69 ± 12) years, (72 ± 13) years for males and (67 ± 12) years for females respectively. According to the imaging results, 72 subjects (22.8%) were diagnosed as non-obese NAFLD and 244 subjects (77.2%) belonged to control group. The general data of the subjects with and without non-obese NAFLD is provided in Table 1. BMI and BSA were significantly higher in subjects with non-obese NAFLD compared with control group (p < 0.01), but there was no significant statistical difference in sex composition and age between the two groups.
| Non-obese NAFLD group(n = 72) | Control group (n = 244) | t/x2 | P-value | ||
|---|---|---|---|---|---|
| Males〔n(%)〕 | 22(30.6) | 96(39.3) | 1.835 | 0.176 | |
| Age(years) | 67.57 ± 11.59 | 69.62 ± 12.88 | 1.287 | 0.200 | |
| BMI(kg/m2) | 22.82 ± 1.74 | 21.85 ± 2.26 | -3.896 | <0.001 | |
| BSA(m2) | 1.74 ± 0.13 | 1.69 ± 0.13 | -2.630 | 0.009 | |
Table 2 describes the biochemical and glucose metabolic characteristics of the study cohort according to the presence of non-obese NAFLD. Subjects with non-obese NAFLD had higher ALT, γ-GT, TG, Alb, UA, Hb, FBG and HbA1c, and lower HDL-C, than subjects in the control group (p < 0.05). There was no significant difference in other indexes.
| Non-obese NAFLD group(n = 72) | Control group (n = 244) | t/x2 | P-value | |
|---|---|---|---|---|
| ALT(U/L) | 20.69 ± 9.63 | 16.29 ± 9.90 | -3.331 | 0.001 |
| AST(U/L) | 20.19 ± 4.86 | 20.06 ± 6.96 | -0.155 | 0.877 |
| γ-GT(U/L) | 28.31 ± 22.77 | 23.01 ± 18.14 | -2.042 | 0.042 |
| TC(mmol/L) | 4.79 ± 1.17 | 4.51 ± 1.00 | -1.864 | 0.065 |
| TG(mmol/L) | 1.88 ± 1.23 | 1.19 ± 0.58 | -4.668 | <0.001 |
| HDL-C(mmol/L) | 1.17 ± 0.29 | 1.30 ± 0.34 | 2.990 | 0.003 |
| LDL-C(mmol/L) | 2.95 ± 0.85 | 2.73 ± 0.98 | -1.680 | 0.094 |
| Alb(g/L) | 40.74 ± 3.83 | 38.82 ± 4.28 | -3.412 | 0.001 |
| UA(umol/L) | 354.85 ± 81.05 | 304.18 ± 77.59 | -3.897 | <0.001 |
| Cr(umol/L) | 66.31 ± 17.39 | 71.58 ± 22.51 | 1.834 | 0.068 |
| eGFR(ml/min*1.73m2) | 86.76 ± 15.71 | 83.50 ± 17.21 | -1.439 | 0.151 |
| Hb(g/L) | 135.54 ± 12.51 | 127.23 ± 15.31 | -4.211 | <0.001 |
| PLT(×109/L) | 214.13 ± 44.86 | 203.52 ± 67.82 | -1.551 | 0.123 |
| FBG(mmol/L) | 6.02 ± 1.85 | 5.15 ± 1.13 | -3.757 | <0.001 |
| HbA1c(%) | 6.73 ± 1.38 | 6.01 ± 0.93 | -4.043 | <0.001 |
The subjects' complications and medications are compared in Table 3. Subjects with non-obese NAFLD had higher prevalence rates of DM and longer course of DM than subjects in the control group (p < 0.05). The proportion of patients taking hypoglycemic drugs in the non-obese NAFLD group was significantly higher than that in the control group (P < 0.01).
| Non-obese NAFLD group(n = 72) | Control group (n = 244) | t/x2 | P-value | ||
|---|---|---|---|---|---|
| Hypertension〔n(%)〕 | 35(50.0) | 102(42.1) | 1.359 | 0.244 | |
| Course of hypertension(years) | 6.85 ± 10.82 | 6.48 ± 11.17 | -0.248 | 0.804 | |
| DM〔n(%)〕 | 30(42.9) | 52(21.6) | 12.653 | <0.001 | |
| Course of DM(years) | 4.96 ± 7.66 | 2.52 ± 5.89 | -2.461 | 0.016 | |
| OSAHS〔n(%)〕 | 0(0) | 2(0.9) | 0.000 | 1.000 | |
| Smoking history〔n(%)〕 | 8(11.1) | 32(13.1) | 0.202 | 0.653 | |
| Family history of heart disease〔n(%)〕 | 7(9.7) | 8(3.3) | 3.779 | 0.052 | |
| History of taking lipid-lowering drugs〔n(%)〕 | 23(31.9) | 67(27.5) | 0.549 | 0.459 | |
| History of taking antihypertensive drugs〔n(%)〕 | 32(44.4) | 95(38.9) | 0.702 | 0.402 | |
| History of taking hypoglycemic drugs〔n(%)〕 | 30(41.7) | 51(20.9) | 12.575 | <0.001 | |
LV structure and function of two groups were assessed by subjects' echocardiographic parameters, which are compared in Table 4. Subjects with non-obese NAFLD had more unfavorable echocardiographic parameters, including a lower E/A and a lower LVEDD, than the control group (p < 0.05), suggesting worse LV diastolic function. There was no significant difference in other indexes.
| Non-obese NAFLD group(n = 72) | Control group (n = 244) | t/x2 | P-value | ||
|---|---|---|---|---|---|
| IVSd(cm) | 0.91 ± 0.15 | 0.88 ± 0.13 | -1.628 | 0.107 | |
| LVPWd(cm) | 0.84 ± 0.12 | 0.87 ± 0.24 | 0.296 | 0.397 | |
| LVM(g) | 130.14 ± 28.95 | 132.94 ± 34.91 | 0.684 | 0.495 | |
| LVMI(g/m2) | 74.82 ± 15.26 | 78.44 ± 19.68 | 1.644 | 0.102 | |
| EF(%) | 68.49 ± 5.21 | 69.64 ± 5.55 | 1.563 | 0.119 | |
| LVESD(cm) | 2.78 ± 0.31 | 2.81 ± 0.33 | 0.716 | 0.474 | |
| LVEDD(cm) | 4.51 ± 0.42 | 4.64 ± 0.43 | 2.182 | 0.030 | |
| E(cm/s) | 68.34 ± 15.94 | 72.26 ± 18.05 | 1.664 | 0.097 | |
| A(cm/s) | 88.16 ± 16.87 | 86.05 ± 20.66 | -0.789 | 0.431 | |
| E/A | 0.80 ± 0.22 | 0.88 ± 0.35 | 2.528 | 0.012 | |
The early LV diastolic function in subjects with non-obese NAFLD was worse than subjects in control group, so we analyzed the independent association between non-obese NAFLD and the presence of early LV diastolic dysfunction using logistic regression analysis.
According to whether E/A<1, 228 subjects (72.2%) were divided into early LV diastolic dysfunction group and 88 subjects (27.8%) belonged to normal group. With the early LV diastolic dysfunction as dependent variable, univariate logistic regression analysis showed that NAFLD, gender, age, BMI, hypertension, course of hypertension, course of DM, history of lipid-lowering and antihypertensive drugs, HbA1c, UA, Cr and eGFR were associated with early LV diastolic dysfunction (p < 0.05). In the univariate model, subjects with non-obese NAFLD had a 2-fold increased risk for early LV diastolic dysfunction (OR = 2.262, 95%CI 1.150–4.449, p = 0.018, Table 5).
| β | SE | Wald | OR | 95%CI | P-value | ||
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| Male | 0.626 | 0.275 | 5.203 | 1.871 | 1.092 | 3.204 | 0.023 |
| Age | 0.091 | 0.013 | 48.668 | 1.095 | 1.067 | 1.123 | <0.001 |
| BMI | 0.155 | 0.056 | 7.697 | 1.168 | 1.047 | 1.303 | 0.006 |
| BSA | -0.134 | 0.994 | 0.018 | 0.874 | 0.125 | 6.134 | 0.892 |
| Hypertension | 1.025 | 0.278 | 13.644 | 2.788 | 1.618 | 4.804 | <0.001 |
| Course of hypertension | 0.048 | 0.016 | 8.341 | 1.049 | 1.015 | 1.083 | 0.004 |
| DM | 0.576 | 0.314 | 3.372 | 1.779 | 0.962 | 3.290 | 0.066 |
| Course of DM | 0.063 | 0.026 | 5.718 | 1.065 | 1.011 | 1.122 | 0.017 |
| OSAHS | -1.019 | 1.421 | 0.514 | 0.361 | 0.022 | 5.845 | 0.361 |
| NAFLD | 0.816 | 0.345 | 5.593 | 2.262 | 1.150 | 4.449 | 0.018 |
| History of taking lipid-lowering drugs | 0.972 | 0.324 | 9.023 | 2.643 | 1.403 | 4.983 | 0.003 |
| History of taking antihypertensive drugs | 1.101 | 0.287 | 14.721 | 3.007 | 1.713 | 5.276 | <0.001 |
| History of taking hypoglycemic drugs | 0.585 | 0.313 | 3.492 | 1.794 | 0.972 | 3.313 | 0.062 |
| Smoking history | -0.255 | 0.364 | 0.491 | 0.775 | 0.380 | 1.581 | 0.483 |
| Family history of heart disease | 0.063 | 0.598 | 0.011 | 1.065 | 0.330 | 3.436 | 0.917 |
| HR | 0.026 | 0.017 | 2.360 | 1.026 | 0.993 | 1.060 | 0.124 |
| FBG | 0.102 | 0.101 | 1.035 | 1.108 | 0.910 | 1.349 | 0.309 |
| HbA1c | 0.362 | 0.161 | 5.078 | 1.437 | 1.048 | 1.969 | 0.024 |
| BNP | 0.001 | 0.002 | 0.356 | 1.001 | 0.997 | 1.006 | 0.551 |
| ALT | -0.003 | 0.012 | 0.062 | 0.996 | 0.973 | 1.021 | 0.457 |
| AST | 0.006 | 0.020 | 0.093 | 0.999 | 0.968 | 1.046 | 0.940 |
| γ-GT | -0.007 | 0.006 | 1.129 | 0.998 | 0.982 | 1.006 | 0.309 |
| TC | -0.186 | 0.122 | 2.295 | 0.831 | 0.653 | 1.056 | 0.130 |
| TG | 0.172 | 0.179 | 0.916 | 1.187 | 0.835 | 1.687 | 0.338 |
| HDL-C | -0.846 | 0.375 | 5.099 | 1.018 | 0.206 | 0.894 | 0.672 |
| LDL-C | -0.052 | 0.129 | 0.159 | 0.950 | 0.737 | 1.224 | 0.690 |
| Alb | -0.027 | 0.031 | 0.768 | 0.973 | 0.916 | 1.034 | 0.381 |
| UA | 0.005 | 0.002 | 5.326 | 1.005 | 1.001 | 1.009 | 0.021 |
| Cr | 0.014 | 0.007 | 3.902 | 1.014 | 1.000 | 1.029 | 0.048 |
| eGFR | -0.044 | 0.010 | 20.838 | 0.957 | 0.939 | 0.975 | <0.001 |
| Hb | 0.002 | 0.008 | 0.038 | 1.002 | 0.986 | 1.018 | 0.845 |
| PLT | 0.000 | 0.002 | 0.061 | 1.000 | 0.996 | 1.003 | 0.805 |
Further stepwise multivariate logistic regression analysis, including the above-mentioned significant variables, showed that non-obese NAFLD was associated with an increase in early LV diastolic dysfunction (OR = 4.050, 95%CI 1.452–11.296, p = 0.008, Table 6).
| B | SE | Wald | OR | 95%CI | P-value | ||
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| NAFLD | 1.399 | 0.523 | 7.142 | 4.050 | 1.452 | 11.296 | 0.008 |
| Age | 0.099 | 0.017 | 32.532 | 1.104 | 1.067 | 1.143 | <0.001 |
| BMI | 0.258 | 0.093 | 7.793 | 1.295 | 1.080 | 1.552 | 0.005 |
| constant | -11.739 | 2.676 | 19.241 | 0.000 | - | - | <0.001 |
In this study, non-obese NAFLD was associated with an increased risk of early LV diastolic dysfunction, independent of well-identified cardiovascular risk factors.
Previously, several studies have suggested that NAFLD was an independent risk factor affecting cardiac structure and function, but there are few studies on the correlation between non-obese NAFLD and LV function or structure in Chinese population. Therefore, this paper studied the changes of LV structure and function in hospitalized non-obese NAFLD patients, and discussed the correlation between non-obese NAFLD and early LV diastolic dysfunction, aiming to provide scientific evidence for clinicians to pay attention to the cardiac structure and function of non-obese NAFLD patients.
Our study showed that compared with the control group, non-obese NAFLD patients had higher BMI, BSA, levels of liver enzymes, blood lipids, proportion of DM, and worse glucose metabolism, which were consistent with previous reports. Although BMI of non-obese NAFLD patients is within the normal range, the visceral fat index is still high[13, 28]. Obesity is related to higher all-cause mortality[29], so both obese and non-obese NAFLD patients can benefit from losing weight[30]. For non-obese NAFLD patients, losing weight by 5–10% through lifestyle intervention can also benefit significantly[31].
In this study, LV structure and function are mainly evaluated by echocardiographic parameters, among which E/A is an important index to evaluate early LV diastolic function. E/A > 1 generally indicates the normal early LV diastolic function[32], while in dysfunction, the E value decreases due to the decrease of the maximum mitral blood flow velocity in the early LV diastole, which leads to E/A < 1[33]. Therefore, we used E/A<1 to determine early LV diastolic dysfunction. We compared the LV structure and function indexes between non-obese NAFLD group and control group, and the results showed that non-obese NAFLD patients had smaller LVEDD and worse early LV diastolic function. In non-obese people, subjects with non-obese NAFLD had a 4-fold increased risk for early LV diastolic dysfunction. The above results were consistent with many previous research on NAFLD[23, 34–36].
Non-obese NAFLD is similar to obese NAFLD in pathophysiology. A previous study based on liver biopsy showed that compared with obese NAFLD patients, non-obese NAFLD patients had lighter degree of hepatocytic steatosis, lobular inflammation and advanced liver fibrosis, and lower prevalence of NASH (54.1% vs 71.2%, p < 0.001)[37], and it also believed that liver fibrosis in non-obese NAFLD patients was obviously related to metabolic disorders. Another meta-analysis including 493 non-obese NAFLD patients and 2209 obese NAFLD patients compared the liver histological features between the two groups, which also showed that pathological changes of non-obese NAFLD were mild[38]. Insulin resistance is universal in NAFLD patients[12, 39, 40]. Non-obese NAFLD patients generally had higher prevalence of DM and glucose intolerance than healthy subjects, while there was no statistical difference between non-obese and obese NAFLD patients[41]. The changes of intestinal microbiota are also associated with the progress of NAFLD and liver fibrosis[42, 43]. A previous report about gut microbiota composition showed that Eubacterium abundance was significantly decreased in non-obese NAFLD patients compared with that in obese NAFLD patients and healthy subjects, then the results demonstrated a negative correlation between Eubacterium and hepatic fibrosis and that the decrease in the abundance of Eubacterium producing butyric acid may play an important role in the development of non-obese NAFLD[44]. It was found that a variety of gene sites are related to the risk, disease severity, hepatic steatosis and advanced fibrosis of NAFLD, including PNPLA3, TM6SF2, GCKR, MBOAT7, APOC3, HSD17B13, etc[45–50]. Among them, PNPLA3 is one of the earliest genes related to NAFLD in genome-wide association studies. the PNPLA3 rs738409 GG genotype was found in 13–19% of the general population in Asian, which is higher than that in other regions[12]. PNPLA3 not only plays a role in increasing the susceptibility to NAFLD, but also is related to abdominal visceral fat accumulation[51], and this gene has been proved to be one of the risk factors for NAFLD in non-obese people[52]. TM6SF2 has a protective effect on cardiovascular system, but it participates in hepatic steatosis and increases the susceptibility to NASH and hepatic fibrosis[53]. Compared with obese NAFLD patients, TM6SF2 E167K mutation is more common in non-obese NAFLD patients[54]. At present, it is considered that NAFLD is not only related to systemic insulin resistance, but also related to endothelial dysfunction, oxidative stress, plaque formation, vascular tone change, systemic inflammatory response, metabolic disorders of blood lipid and so on[55–57]. Previous studies have shown that compared with healthy people, non-obese NAFLD patients also have a higher risk of coronary heart disease[58], and there is no statistical difference between non-obese NAFLD patients and obese NAFLD patients in the risk of cardiovascular diseases and malignant tumors, and they all have a higher risk of all-cause mortality. The main causes of death of non-obese NAFLD patients are malignant tumors and cardiovascular diseases[59].
Despite the fact that NAFLD is usually associated with obesity, it has also been noted that the prevalence of NAFLD is increasing in non-obese individuals. Non-obese NAFLD is similar to the obese NAFLD in pathophysiological mechanism and influence on other related diseases. Compared with the healthy individuals, the non-obese NAFLD patients have a higher risk of liver cirrhosis, hypertension, DM, coronary heart disease and other diseases, as well as the risk of all-cause death, which needs to be confirmed by more studies in the future. The results of this study indicated that non-obese NAFLD was an independent risk factor for early LV diastolic dysfunction, which was consistent with the current research results. This research is meaningful for clinicians and patients because the results can remind clinicians to pay more attention to cardiac structure and function of non-obese NAFLD patients, and early intervention on non-obese NAFLD to delay its progress may be helpful to prevent or improve myocardial dysfunction.
However, this study has several limitations. First, the cross-sectional design of this study is difficult to explore the causal relationship between NAFLD and early LV diastolic dysfunction. Second, imaging examination were used to diagnose NAFLD and we were unable to obtain liver histological samples, the gold standard for the diagnosis of NAFLD. Third, we used E/A<1 to determine early LV diastolic dysfunction, while subjects with E/A ≥ 1 may have middle and late LV diastolic dysfunction. However, the above situation is extremely impossible because all the subjects enrolled in this study excluded heart disease patients and all of them had normal LV size and ejection fraction, and there was no evidence of heart failure. More accurate methods are needed to evaluate the LV structure and function in the future. Fourth, this study's cohort is a selected population, so may not be representative of the general population. In addition, this study only included subjects of East Asian ethnicity, so the conclusions may not be generalizable to other ethnic groups. Further studies are needed to validate our results.
In conclusion, non-obese NAFLD is associated with increased risk of early LV diastolic dysfunction. Therefore, intervention of non-obese NAFLD may be beneficial to improve early LV diastolic dysfunction.
NAFLD, non-alcoholic fatty liver disease; LV, left ventricle; DM, diabetes mellitus; ALT, alanine aminotransferase; AST, aspartate aminotransferase; γ-GT, γ-glutamyl transpeptidase; Alb, serum albumin; Cr, serum creatinine; UA, serum uric acid; FBG, fasting blood glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; Hb, hemoglobin; PLT, platelet count; eGFR, estimated glomerular filtration rate; BMI, body mass index; BSA, body surface area; OSAHS, obstructive sleep apnea-hypopnea syndrome; IVSd, interventricular septal thickness at diastole; LVPWd, left ventricular posterior wall thickness at diastole; LVM, left ventricular mass; LVMI, left ventricular mass index; EF, ejection fraction; LVESD, left ventricular end-systolic diameter; LVEDD, left ventricular end-diastolic diameter; E, the peak velocity of the early filling wave; A, the peak velocity of the atrial contraction wave
Ethics approval and consent to participate
All methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by ethics review committee of Peking University People’s Hospital. Informed consent was obtained from all subjects.
Consent for publication
Not applicable.
Availability of data and materials
The datasets used and analyzed during the current study are not publicly available due not all of the researchers wish to share the data with public at present, but available from the corresponding author on reasonable request.
Competing interests
The authors declare no conflicts of interest.
Funding
This study is funded by Peking University Health Science Center health International Institute of Comprehensive Health and the National Project of Multidisciplinary Diagnosis and Treatment of Major Diseases.
Authors contributions
(I) Conception and design: Fangyuan Cong, Jingtong Wang;
(II) Administrative support: Qian Xue, Jingtong Wang;
(III) Provision of study materials or patients: Fangyuan Cong, Luying Zhu, Lihua Deng, Qian Xue;
(IV) Collection and assembly of data: Fangyuan Cong, Qian Xue;
(V) Data analysis and interpretation: Fangyuan Cong, Luying Zhu, Jingtong Wang;
(VI) Manuscript writing: All authors;
(VII) Final approval of manuscript: All authors.
Acknowledgements
We thank all the staff members participating in this study from Geriatric Department of Peking University People’s Hospital.