Association between NAFLD and risk of prevalent chronic kidney disease: why there is a difference between east and west?

BACKGROUNDS: There is a discrepancy between west and east on the relationship between non-alcoholic fatty liver disease (NAFLD) and chronic kidney disease (CKD). This study aimed to find out the possible reason for this and to clarify the association between NAFLD and CKD by analyzing two population-based datasets from the US and China. METHODS: Two health examination datasets from China and the US were used. CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73m2 or and/or abnormal albuminuria and/or overt proteinuria. Binary logistic regression was used to examine the association between NAFLD and CKD. RESULTS: A total of 60,965 participants were analyzed, including 11,844 from the US and 51,229 from China. The prevalence of NAFLD was 27.12% in the Chinese population and 36.08% in the US population (p < 0.001). The proportions of CKD and late stage CKD (stages 3-5) were higher in the US population than the Chinese one. NAFLD was independently associated with an increased risk of CKD in Chinese population, whereas in the US population, the NAFLD was not an independent risk factor of CKD. In subgroup analyses which excluded late stages CKD (stages 3-5), the risks of mild renal function decline became consistent: NAFLD was associated with early stages of CKD but not the late stages of CKD in both populations. CONCLUSION: NAFLD increased the risk of early stages of CKD in both Chinese and the US population. The conflicting results reported by previous studies might result from the different proportion of late stages of CKD.

MetS Risk Score: A Clear Scoring Model to Predict a 3-Year Risk for Metabolic Syndrome.

Although several risk factors for metabolic syndrome (MetS) have been reported, there are few clinical scores that predict its incidence. Therefore, we created and validated a risk score for prediction of 3-year risk for MetS. Three-year follow-up data of 4395 initially MetS-free subjects, enrolled for an annual physical examination from Wenzhou Medical Center were analyzed. Subjects at enrollment were randomly divided into the training and the validation cohort. Univariate and multivariate logistic regression models were employed for model development. The selected variables were assigned an integer or half-integer risk score proportional to the estimated coefficient from the logistic model. Risk scores were tested in a validation cohort. The predictive performance of the model was tested by computing the area under the receiver operating characteristic curve (AUROC). Four independent predictors were chosen to construct the MetS risk score, including BMI (HR=1.906, 95% CI: 1.040-1.155), FPG (HR=1.507, 95% CI: 1.305-1.741), DBP (HR=1.061, 95% CI: 1.002-1.031), HDL-C (HR=0.539, 95% CI: 0.303-0.959). The model was created as -1.5 to 4 points, which demonstrated a considerable discrimination both in the training cohort (AUROC=0.674) and validation cohort (AUROC=0.690). Comparison of the observed with the estimated incidence of MetS revealed satisfactory precision. We developed and validated the MetS risk score with 4 risk factors to predict 3-year risk of MetS, useful for assessing the individual risk for MetS in medical practice.

NAFL screening score: A basic score identifying ultrasound-diagnosed non-alcoholic fatty liver.

BACKGROUND: Several non-invasive diagnostic scores for non-alcoholic fatty liver (NAFL) have been developed, but the clinical application is limited because of their complexity. AIM: To develop and validate an easy-to-calculate scoring system to identify ultrasound-diagnosed NAFL. METHODS: 48,489 patients from 2 centers were included in this study. Multivariable logistic regression models were employed for model development. Ultrasonography was applied to diagnose NAFL. The selected variables were assigned an integer score proportional to the estimated coefficient from the logistic regression analysis, namely NAFL Screening Score (NSS). The ability of the NSS to identify NAFL was assessed by analyzing the area under the receiver operating characteristic curve (AUROC) and was tested in an independent validation cohort. Additionally, the performance of NSS was compared with existing models. RESULTS: NSS was developed as a basic score comprising of age, body mass index (BMI), triglyceride (TG), ALT/AST, fasting plasma glucose (FPG) and uric acid (UA) in both sexes. NSS showed a relatively good discriminative power (AUROC=0.825 for males, 0.861 for females in the validation cohort) in comparison with other models. The optimal cut-off point was 32 for males and 29 for females. CONCLUSION: We developed and validated NSS, an easy-to-use score sheet identify ultrasound-diagnosed NAFL. NSS may be clinically useful for initial diagnosing NAFL.

Serum alkaline phosphatase, a risk factor for non-alcoholic fatty liver, but only for women in their 30s and 40s: evidence from a large cohort study.

BACKGROUND: Several risk factors are able to predict non-alcoholic fatty liver (NAFL) development, but the predictive value of serum alkaline phosphatase (ALP) remains uncertain. Our aim is to investigate the association between serum ALP levels and NAFL. METHODS: 21,331 NAFL-free subjects were included. Sex-specific ALP quartiles (Q1 to Q4) were defined. With Q1 used as reference, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated across each quartile. RESULTS: After adjusting for confounding variables, values in Q2, Q3 and Q4 had HRs (95%CIs) of 1.16 (0.94-1.43), 1.38 (1.13-1.69), 1.51 (1.24-1.83) in females and 0.99 (0.90-1.09), 1.04 (0.95-1.14), 0.96 (0.87-1.05) in males, respectively. A subgroup analysis of age factors in females, from Q2 to Q4, adjusted HRs (95%CIs) were 1.31 (0.81-1.99), 1.86 (1.23-2.81), 2.44 (1.60-3.71) in their 30 s, 1.13 (0.83-1.54), 1.17 (0.85-1.62), 1.65 (1.22-2.25) in their 40 s, and 0.95 (0.51-1.78), 0.91 (0.52-1.62), 0.89 (0.53-1.52) in their 50 s. CONCLUSIONS: Higher serum ALP levels are considered a significant predictor for NAFL development in females aged 30 to 50.

The NAFL Risk Score: A simple scoring model to predict 4-y risk for non-alcoholic fatty liver.

BACKGROUND: Although several risk factors for non-alcoholic fatty liver (NAFL) have been reported, there are few clinical scores that predict its incidence in the long term. We developed and validate a scoring model for individual prediction of 4-y risk for NAFL. METHODS: Four-year follow-up data of 8226 initially NAFL-free subjects enrolled for an annual physical examination from Wenzhou Medical Center were analyzed. These subjects are randomly split into the training and the validation cohort. Univariate and multivariable logistic regression models were employed for model development. The selected variables were assigned an integer or half-integer risk score proportional to the estimated coefficient from the logistic model. Risk scores were tested in a validation cohort. We also compared the predictive performance of with that of the NAFLD Index by computing the area under the receiver operating characteristic curve (AUROC). RESULTS: The NAFL Risk Score was developed as 0 to 18 points comprising of BMI, TG×GGT, ALT/AST, LDL-C/HDL-C and UA in both sexes. Comparison of the observed with the estimated incidence of NAFL at both cohorts showed satisfactory precision. In addition, the NAFL Risk Score showed relatively good discriminative power (AUROC=0.739 for males, 0.823 for females) compared with the NAFLD Index (AUROC=0.661 for males, 0.729 for females) in these Chinese subjects. CONCLUSIONS: We developed and validated the NAFL Risk Score, a new scoring model to predict 4-y risk for NAFL. The NAFL Risk Score may be clinically simple and useful for assessing individual risk for NAFL.

Association of low-density lipoprotein cholesterol within the normal range and NAFLD in the non-obese Chinese population: a cross-sectional and longitudinal study.

OBJECTIVES: The relationship between normal low-density lipoprotein cholesterol (LDL-c) levels and non-alcoholic fatty liver disease (NAFLD) in non-obese individuals remains unclear. We aimed to investigate the precise prevalence and incidence of NAFLD within the normal LDL-c range in non-obese individuals. DESIGN: Cross-sectional and longitudinal study. SETTING: Wenzhou Medical Center of Wenzhou People's Hospital from 2010 to 2014. PARTICIPANTS: 183 903 non-obese individuals were enrolled from a cross-sectional population, and a total of 16 173 initially NAFLD-free non-obese individuals were included who completed a 5-year follow-up examination in the longitudinal population. RESULTS: In our study, NAFLD was defined by ultrasonographic detection of steatosis in the absence of other liver disease. The cross-sectional study showed that at baseline, the prevalence of NAFLD was 13.9% in non-obese individuals with normal LDL-c levels. The prospective study demonstrated that NAFLD-free participants developed NAFLD during the 5-year follow-up period, with a cumulative incidence of 14.4%. In addition, the ORs for NAFLD in the cross-sectional population were 1.11 (95% CI 1.04 to 1.18), 1.37 (95% CI 1.27 to 1.47) and 1.56 (95% CI 1.43 to 1.69), respectively, after adjusting for known confounding variables. The HRs for NAFLD in the longitudinal population were 1.15 (95% CI 0.98 to 1.36), 1.32 (95% CI 1.10 to 1.58) and 1.82 (95% CI 1.47 to 2.52), compared with Q1. Individuals with higher LDL-c level within the normal range had an increased cumulative incidence rate of NAFLD in non-obese individuals. CONCLUSIONS: NAFLD is prevalent in the non-obese Chinese population. Furthermore, this is the first study to demonstrate that increased normal LDL-c levels are independently associated with an elevated risk of NAFLD in non-obese individuals.

Parabolic relationship between sex-specific serum high sensitive C reactive protein and non-alcoholic fatty liver disease in Chinese adults: a large population-based study.

OBJECTIVES: To evaluate the association between sex-specific serum high sensitive C reactive protein (hsCRP) levels and NAFLD in a large population-based study. RESULTS: From Q1 to Q4, the incidence ratios were 21.1 (95% CI 17.5 24.7), 18.6 (95% CI 16.5 20.8), 24.8 (95% CI 22.4 27.2) and 31.1 (95% CI 28.5 33.6) in males and 6.2 (95% CI 4.4 8.0), 6.0 (95% CI 5.1 7.1), 11.4 (95% CI 9.2 13.7) and 19.5 (95% CI 16.1 22.9) in females. Compared with a 1.7-fold increase (Q4 vs Q2) in males, actuarial incidence increased 3.3-fold (Q4 vs Q2) in females. After adjusting for known confounding variables in this study, in the longitudinal population, compared with the reference group, those in Q1, Q3, and Q4 had HRs of 1.63 (95% CI 1.29-2.05), 1.11 (95% CI 0.93-1.31), 1.14 (95% CI 0.97-1.35) in male and 1.77 (95% CI 1.25-2.49), 1.22 (95% CI 0.93-1.59), 1.36 (95% CI 1.03-1.80) in female for NAFLD, respectively. METHODS: 8618 subjects from Wenzhou Medical Center of Wenzhou People's Hospital were included. Sex specific hsCRP quartiles (Q1 to Q4) were defined: 0-0.1, 0.2-0.4, 0.5-0.8 and 0.9-25.9 for male; 0-0.1, 0.2-0.6, 0.7-1.2 and1.3-28.4 for female. Applying Q2 as reference, Hazard ratios (HRs) and 95% confidence intervals (CIs) for NAFLD were calculated across each quartile of hsCRP. CONCLUSIONS: We report that a sex-specific hsCRP level is independently associated with NAFLD. The association between hsCRP and NAFLD was significantly stronger in females than in males.

Increased levels of low-density lipoprotein cholesterol within the normal range as a risk factor for nonalcoholic fatty liver disease.

OBJECTIVES: Dyslipidemia exists within the setting of NAFLD and the relationship of a normal level of low-density lipoprotein cholesterol (LDL-c) with NAFLD is largely unknown. This large population-based study aimed to investigate the association between LDL-c levels within the normal range and the incidence of NAFLD. METHODS: A total of 60527 subjects from 2 medical centers who had undergone liver ultrasonography were initially enrolled into this study. NAFLD was defined by ultrasonographic detection of steatosis in the absence of other liver disease. Subjects were divided into 4 groups (Q1 to Q4) by normal LDL-c quartiles : Q1: ≤ 2.00, Q2: 2.10-2.35, Q3: 2.36-2.68 and Q4: 2.69-3.12 mmol/L. The odds ratios (OR), hazard ratio (HR) and 95% confidence intervals (CIs) for NAFLD were calculated across each quartile of LDL-c, using the Q1 as reference. RESULTS: The prevalence rates of NAFLD in a cross-sectional population from Q1 to Q4 were 19.34%, 25.86%, 35.65% and 42.08%, respectively. The OR for NAFLD in the cross-sectional population were 1.31 (95% CI 1.14-1.54), 1.73 (95% CI 1.46-2.04), and 1.82 (95% CI 1.49-2.23), respectively, after adjusting for known confounding variables. The HR for NAFLD in the longitudinal population were 1.23 (95% CI 1.12-1.35), 1.57 (95% CI 1.44-1.72) and 2.02 (95% CI 1.86-2.21), compared with Q1. Subjects with higher LDL-c level within the normal range had an increased cumulative incidence rate of NAFLD. CONCLUSIONS: Increased levels of LDL-c within the normal range may play a significant role in the prevalence and incidence of NAFLD, independent of other confounding factors.