Liver fibrosis indices are related to diabetic peripheral neuropathy in individuals with type 2 diabetes

The association between nonalcoholic fatty liver (NAFL) or liver fibrosis and diabetic peripheral neuropathy (DPN) has not been well studied. We aimed to investigate the association of NAFL or liver fibrosis indices and DPN in individuals with type 2 diabetes. In this observational study, we included 264 individuals with type 2 diabetes, and calculated non-alcoholic fatty liver disease (NAFLD) liver fat score, NAFLD fibrosis score, and Fibrosis-4 (FIB-4) index to evaluate the status of NAFLD or liver fibrosis. DPN was diagnosed when the Michigan Neuropathy Screening Instrument—Physical Examination score was ≥ 2.5. The NAFLD fibrosis score and FIB-4 index were significantly higher in individuals with DPN than in those without DPN. Logistic analyses showed that the NAFLD fibrosis score and FIB-4 index were associated with DPN after adjustment for covariates (adjusted odds ratio 1.474 and 1.961, respectively). In the subgroup analysis, this association was only significant in the group with a high NAFLD liver fat score (> − 0.640). Serum levels of fetuin-A, a hepatokine, were decreased in individuals with abnormal vibration perception or 10-g monofilament tests compared with their counterparts. The present study suggests that liver fibrosis might be associated with DPN in individuals with type 2 diabetes.

Differences among Three Skeletal Muscle Mass Indices in Predicting Non-Alcoholic Fatty Liver Disease: Korean Nationwide Population-Based Study

Recent studies have investigated the relationship between sarcopenia and non-alcoholic fatty liver disease (NAFLD); however, there is no unified definition of sarcopenia. Thus, we aimed to investigate the differences among three skeletal muscle mass indices (SMI) in predicting NAFLD. This study included 8133 adults from the 2008–2010 Korea National Health and Nutrition Survey. SMI was calculated as appendicular skeletal muscle mass divided by height-square (hSMI), weight (wSMI), or body mass index (bSMI). The presence of NAFLD was defined by using the NAFLD-liver fat score. On the receiver operating characteristic curve analysis, the predictive power of wSMI for NAFLD was significantly higher than those of hSMI and bSMI in men (wSMI vs. hSMI, p = 0.003; wSMI vs. bSMI, p < 0.001). In women, the predictive power of hSMI was only significantly higher than that of bSMI (p = 0.023), and other predictive powers were not significantly different. In addition, hSMI was correlated with insulin resistance and NAFLD-liver fat score in the opposite direction to wSMI and bSMI in both men and women. Among the three definitions of SMI, wSMI showed the highest diagnostic performance for predicting NAFLD in men, suggesting the importance of defining sarcopenia for its association with specific diseases.

SHBG as a Marker of NAFLD and Metabolic Impairments in Women Referred for Oligomenorrhea and/or Hirsutism and in Women With Sexual Dysfunction

PCOS is one of the most common endocrine disorders and NAFLD is one of its most dangerous metabolic consequences. The diagnosis of NAFLD is not a practical task and the condition is at risk of being overlooked. The use of simpler but still reliable surrogate markers is necessary to identify women with a high likelihood of NAFLD. The aim of this study was to evaluate the clinical correlates of NAFLD Liver Fat Score (NAFLD-LFS) in women with oligomenorrhea and/or hirsutism. Furthermore, the study aimed to evaluate whether, among the hormonal parameters evaluated in such women, possible hallmarks of NAFLD may be identified. To this purpose, 66 women who attended our Outpatient Clinic for oligomenorrhea and/or hyperandrogenism were included in the study. In order to validate the results obtained in the first cohort, a second independent sample of 233 women evaluated for female sexual dysfunction (FSD) was analyzed. In cohort 1, NAFLD-LFS positively correlated with metabolic and inflammatory parameters. Among the hormone parameters, NAFLD-LFS showed no significant relationships with androgens but a significant negative correlation with SHBG (p&lt;0.0001) that therefore appeared as a candidate hallmark for pathologic NAFLD-LFS. The ROC analysis showed a significant accuracy (81.1%, C.I.69.1-93.0, p &lt;0.0001) for SHBG in identifying women with a pathological NAFLD-LFS. In particular, a SHBG 33.4 nmol/l was recognized as the best threshold, with a sensitivity of 73.3% and a specificity of 70.7%. In order to validate this SHBG as a marker of metabolic impairment possible related with the presence of NAFLD, we tested this threshold in cohort 2. FSD women with SHBG &lt;33.4 nmol/l had worse metabolic parameters than women with SHBG ≥33.4 nmol/l and a significantly higher NAFLD-LFS even after adjusting for confounders (B=4.18 [2.05; 6.31], p=0.001). In conclusion, this study provides a new evidence in the diagnostic process of NAFLD, showing that the measurement of SHBG, which is routinely assessed in the workup of women referred for possible PCOS, could identify women at higher metabolic risk, thus detecting those who may deserve further targeted diagnostic assessment.

Comparative Assessment and External Validation of Hepatic Steatosis Formulae in a Community-Based Setting

Several hepatic steatosis formulae have been validated in various cohorts using ultrasonography. However, none of these studies has been validated in a community-based setting using the gold standard method. Thus, the aim of this study was to externally validate hepatic steatosis formulae in community-based settings using magnetic resonance imaging (MRI). A total of 1301 community-based health checkup subjects who underwent liver fat quantification with MRI were enrolled in this study. Diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUROC). Non-alcoholic fatty liver disease (NAFLD) liver fat score showed the highest diagnostic performance with an AUROC of 0.72, followed by Framingham steatosis index (0.70), hepatic steatosis index (HSI, 0.69), ZJU index (0.69), and fatty liver index (FLI, 0.68). There were considerable gray zones in three fatty liver prediction models using two cutoffs (FLI, 28.9%; HSI, 48.9%; and ZJU index, 53.6%). The diagnostic performance of NAFLD liver fat score for detecting steatosis was comparable to that of ultrasonography. The diagnostic agreement was 72.7% between NAFLD liver fat score and 70.9% between ultrasound and MRI. In conclusion, the NAFLD liver fat score showed the best diagnostic performance for detecting hepatic steatosis. Its diagnostic performance was comparable to that of ultrasonography in a community-based setting.