Association of Circulating Serum miR-34a and miR-122 with Dyslipidemia among Patients with Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) covers a spectrum of diseases from simple steatosis to non-alcoholic steatohepatitis, with approximately 20% risk of progressing to fibrosis and cirrhosis. The aim of this study was to compare the relative expression levels of circulating miR-21, miR-34a, miR-122, miR-125b and miR-375 between healthy controls and NAFLD patients, and to assess the feasibility of microRNAs as potential biomarkers for NAFLD. A cross-sectional study was conducted to evaluate circulating serum miRNAs as potential diagnostic markers for NAFLD. Twenty-eight clinically diagnosed and histologically-confirmed NAFLD patients, as well as 36 healthy controls were enrolled in this study. The relative expression of serum microRNAs were calculated using the comparative cycle threshold with spiked-in C. elegans miR-39 as exogenous internal control. Serum levels of miR-34a and miR-122 were significantly higher in NAFLD patients than in healthy controls (P = <0.0001). Positive correlations were observed between serum miR-34a with very low density lipoprotein cholesterol (VLDL-C) and triglyceride levels. However, the expression levels of miR-34a and miR-122 did not correlate with the histological features of NAFLD. Interestingly, receiver operating characteristic (ROC) curve analysis revealed that miR-34a and miR-122 are potential markers for discriminating NAFLD patients from healthy controls with an area under the curve (AUC) values of 0.781 and 0.858, respectively. Serum levels of miR-34a and miR-122 were found to be significantly higher among NAFLD patients, and were positively correlated with VLDL-C and triglyceride levels. Thus, circulating miR-34a and miR-122 can be used as potential biomarkers for discriminating NAFLD patients from healthy controls. Larger cohorts are required to validate the utility of miR-34a and miR-122 in monitoring liver injury.     

Influence of Non-Alcoholic Fatty Liver Disease on Autonomic Changes Evaluated by the Time Domain,Frequency Domain,and Symbolic Dynamics of Heart Rate Variability

Background

Non-alcoholic fatty liver disease (NAFLD) is associated with cardiovascular atherosclerosis independent of classical risk factors. This study investigated the influence of NAFLD on autonomic changes, which is currently unknown.

Methods

Subjects without an overt history of cardiovascular disease were enrolled during health checkups. The subjects diagnosed for NAFLD using ultrasonography underwent 5-min heart rate variability (HRV) measurements that was analyzed using the following indices: (1) the time domain with the standard deviation of N-N (SDNN) intervals and root mean square of successive differences between adjacent N-N intervals (rMSSD); (2) the frequency domain with low frequency (LF) and high frequency (HF) components; and (3) symbolic dynamics analysis. Routine blood biochemistry data and serum leptin levels were analyzed. Homeostasis model assessment of insulin resistance (HOMA-IR) was measured.

Results

Of the 497 subjects (mean age, 46.2 years), 176 (35.4%) had NAFLD. The HRV indices (Ln SDNN, Ln rMSSD, Ln LF, and Ln HF) were significantly decreased in the NAFLD group (3.51 vs 3.62 ms, 3.06 vs 3.22 ms, 5.26 vs 5.49 ms², 4.49 vs 5.21 ms², respectively, all P<0.05). Ln SDNN was significantly lower in the NAFLD group after adjustment for age, sex, hypertension, dyslipidemia, metabolic syndrome, body mass index, smoking, estimated glomerular filtration rate, HOMA-IR, and leptin (P<0.05). In the symbolic dynamic analysis, 0 V percentage was significantly higher in the NAFLD group (33.8% vs 28.7%, P = 0.001) and significantly correlated with linear HRV indices (Ln SDNN, Ln rMSSD, and Ln HF).

Conclusions

NAFLD is associated with decreased Ln SDNN and increased 0 V percentage. The former association was independent of conventional cardiovascular risk factors and serum biomarkers (insulin resistance and leptin). Further risk stratification of autonomic dysfunction with falls or cardiovascular diseases by these HRV parameters is required in patients with NAFLD.     

Combined Serum Biomarkers in Non-Invasive Diagnosis of Non-Alcoholic Steatohepatitis

Background

Non-alcoholic steatoheaptitis (NASH), the critical stage of non-alcoholic fatty liver disease (NAFLD), is of chronic progression and can develop cirrhosis even hepatocellular carcinoma (HCC). However, non-invasive biomarkers for NASH diagnosis remain poorly applied in clinical practice. Our study aims at testing the accuracy of the combination of cytokeratin-18 M30 fragment (CK-18-M30), fibroblast growth factor 21 (FGF-21), interleukin 1 receptor antagonist (IL-1Ra), pigment epithelium-derived factor (PEDF) and osteoprotegerin (OPG) in diagnosing NAFLD and NASH.

Methods

179 patients with biopsy-proven NAFLD were enrolled as training group, 91 age- and gender-matched healthy subjects were recruited at the same time as controls. 63 other NAFLD patients were separately collected as validation group. 45 alcoholic fatty liver disease (AFLD) patients, 50 hepatitis B virus (HBV) patients, 52 hepatitis C virus (HCV) patients were also included. Serum biomarker levels were measured by enzyme-linked immunosorbent assay.

Results

Serum levels of CK-18-M30, FGF-21, IL-1Ra and PEDF increased, while OPG decreased in a stepwise fashion in controls, non-NASH NAFLD patients and NASH patients (P < 0.01). The area under receiver-operating characteristics curve to diagnose NASH was 0.86 for CK-18-M30, 0.89 for FGF-21, 0.89 for IL-1Ra, 0.89 for PEDF and 0.89 for OPG. CK-18-M30 had 70% negative predictive value (NPV) and 79% positive predictive value (PPV) to diagnose NASH. A 5-step approach measuring CK-18-M30 followed by FGF21, IL-1Ra, PEDF and OPG gradually improved the NPV to 76% and PPV to 85%, which reached 80% and 76% respectively in the validation cohort.

Conclusion

Compared to single biomarker, stepwise combination of CK-18-M30, FGF-21, IL-1Ra, PEDF and OPG can further improve the accuracy in diagnosing NASH.     

Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease

Background

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide. However, its molecular pathogenesis is incompletely characterized and clinical biomarkers remain scarce. The aims of these experiments were to identify and characterize liver protein alterations in an animal model of early, diet-related, liver injury and to assess novel candidate biomarkers in NAFLD patients.

Methods

Liver membrane and cytosolic protein fractions from high fat fed apolipoprotein E knockout (ApoE^?/?) animals were analyzed by quantitative proteomics, utilizing isobaric tags for relative and absolute quantitation (iTRAQ) combined with nano-liquid chromatography and tandem mass spectrometry (nLC-MS/MS). Differential protein expression was confirmed independently by immunoblotting and immunohistochemistry in both murine tissue and biopsies from paediatric NAFLD patients. Candidate biomarkers were analyzed by enzyme-linked immunosorbent assay in serum from adult NAFLD patients.

Results

Through proteomic profiling, we identified decreased expression of hepatic glyoxalase 1 (GLO1) in a murine model. GLO1 protein expression was also found altered in tissue biopsies from paediatric NAFLD patients. In vitro experiments demonstrated that, in response to lipid loading in hepatocytes, GLO1 is first hyperacetylated then ubiquitinated and degraded, leading to an increase in reactive methylglyoxal. In a cohort of 59 biopsy-confirmed adult NAFLD patients, increased serum levels of the primary methylglyoxal-derived advanced glycation endproduct, hydroimidazolone (MG-H1) were significantly correlated with body mass index (r?=?0.520, p <?0.0001).

Conclusion

Collectively these results demonstrate the dysregulation of GLO1 in NAFLD and implicate the acetylation-ubquitination degradation pathway as the functional mechanism. Further investigation of the role of GLO1 in the molecular pathogenesis of NAFLD is warranted.

     

Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression

Our understanding of the mechanisms by which nonalcoholic fatty liver disease (NAFLD) progresses from simple steatosis to steatohepatitis (NASH) is still very limited. Despite the growing number of studies linking the disease with altered serum metabolite levels, an obstacle to the development of metabolome-based NAFLD predictors has been the lack of large cohort data from biopsy-proven patients matched for key metabolic features such as obesity. We studied 467 biopsied individuals with normal liver histology (n=90) or diagnosed with NAFLD (steatosis, n=246; NASH, n=131), randomly divided into estimation (80% of all patients) and validation (20% of all patients) groups. Qualitative determinations of 540 serum metabolite variables were performed using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). The metabolic profile was dependent on patient body-mass index (BMI), suggesting that the NAFLD pathogenesis mechanism may be quite different depending on an individual's level of obesity. A BMI-stratified multivariate model based on the NAFLD serum metabolic profile was used to separate patients with and without NASH. The area under the receiver operating characteristic curve was 0.87 in the estimation and 0.85 in the validation group. The cutoff (0.54) corresponding to maximum average diagnostic accuracy (0.82) predicted NASH with a sensitivity of 0.71 and a specificity of 0.92 (negative/positive predictive values=0.82/0.84). The present data, indicating that a BMI-dependent serum metabolic profile may be able to reliably distinguish NASH from steatosis patients, have significant implications for the development of NASH biomarkers and potential novel targets for therapeutic intervention.     

Computational and Empirical Studies Predict Mycobacterium tuberculosis-Specific T Cells as a Biomarker for Infection Outcome

Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2- year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identified T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. We emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.     

达格列净对2型糖尿病合并非酒精性脂肪性肝病患者血清FGF-21水平的影响

摘要 目的：分析血清成纤维细胞生长因子-21（FGF-21）与2型糖尿病（T2DM）合并非酒精性脂肪性肝病（NAFLD）患者常见指标及NAFLD纤维化评分（NFS）的相关性,进一步探讨达格列净对T2DM合并NAFLD患者血清FGF-21水平的影响。方法：选取2022年1月至2022年6月徐州医科大学附属徐州市立医院收治的80例T2DM合并NAFLD患者为研究对象（T2DM合并NAFLD组）,选择同期80例T2DM不合并NAFLD患者为T2DM组。收集腰围（WC）、身高、体重数据,计算体重指数（BMI）。测定空腹血糖（FPG）、糖化血红蛋白（HbA1c）、空腹胰岛素（FINS）、甘油三酯（TG）、总胆固醇（TC）、高密度脂蛋白胆固醇（HDL-c）,低密度脂蛋白胆固醇（LDL-c）、肌酐（Cr）、丙氨酸氨基转移酶（ALT）、天冬氨酸氨基转移酶（AST ）、白蛋白（Alb）、血小板计数（PLT）等指标,计算胰岛素抵抗指数（HOMA-IR）、NFS。采用酶联免疫吸附（ELISA）法测定FGF-21水平。比较T2DM组和T2DM合并NAFLD组各项指标的差异,探讨血清FGF-21水平与T2DM合并NAFLD患者其他指标的相关性,Logistic回归分析T2DM合并NAFLD的影响因素,受试者工作特征曲线（ROC）分析各影响因素对T2DM合并NAFLD的诊断价值。将80例T2DM合并NAFLD患者按随机数字表法随机分为二甲双胍组和达格列净组各40例,治疗前后观测各项指标变化,并密切监测不良反应。结果：T2DM合并NAFLD组患者WC、BMI、FINS、HbA1c、TG、AST、ALT、HOMA-IR、NFS及FGF-21均高于 T2DM组（P＜0.05）。相关性分析显示,FGF-21水平与T2DM合并NAFLD组患者WC、BMI、HbA1c、TG、HOMA-IR、NFS均存在正相关（P<0.05）。Logistic回归分析显示,BMI、HbA1c、FGF-21、HOMA-IR为影响T2DM患者合并NAFLD的危险因素。ROC曲线分析显示,BMI、HbA1c、FGF-21、HOMA-IR对T2DM合并NAFLD均具有一定预测价值,其中以FGF-21的预测效能最佳。治疗后,达格列净组TG、AST、ALT、NFS、FGF-21水平较二甲双胍组降低更为明显（P＜0.05）。结论：血清FGF-21水平为T2DM合并NAFLD的危险因素,参与了T2DM合并NAFLD发病及进展,且对T2DM合并NAFLD有较好的预测效能。相较于二甲双胍,达格列净可明显降低T2DM合并NAFLD患者血清FGF-21水平并改善NFS,具有一定程度的肝脏保护作用。     

Soluble programmed death-1 (sPD-1) and programmed death ligand 1 (sPD-L1) as potential biomarkers for the diagnosis and prognosis of glioma patients

BackgroundThis study aimed at investigating the feasibility of testing for soluble programmed death-1 (sPD-1) and soluble programmed death ligand 1 (sPD-L1) in serum samples of glioma patients and to evaluate the diagnostic and prognostic value of these two soluble molecules.MethodsSerum samples collected from 70 glioma patients before surgery were designated as the pre-operative (Pre) group, samples obtained from 90 post-surgery glioblastoma patients were designated as the Post group, and samples from 20 healthy volunteers were used as controls. Peripheral blood sPD-1 and sPD-L1 levels were detected by using ELISA kits and compared among the groups. The associations of these soluble molecule levels with clinicopathological variables and tumour progression were investigated.ResultsAmong the three groups, the Pre group had the highest sPD-1 levels, whereas the median sPD-L1 level was significantly lower in the Post group than in the other two groups. The area under the curve (AUC) of sPD-1 (0.762) for diagnosis was similar to that of sPD-L1 (0.718). Higher serum levels of sPD-1 and sPD-L1 were present in samples of patients with more advanced brain tumours. Kaplan-Meier analysis showed that higher serum levels of sPD-1 (>11.14 pg/mL) and sPD-L1 (>63.03 pg/mL) might predict shorter progression-free survival times of glioma patients.ConclusionsThis study showed that sPD-1 and sPD-L1 might be promising predictive biomarkers for the diagnosis and prognosis of glioma patients.     

Cytokeratin 18, Alanine Aminotransferase,Platelets and Triglycerides Predict the Presence of Nonalcoholic Steatohepatitis

Background

Nonalcoholic fatty liver disease (NAFLD) is one of the critical public health problems in China. The full spectrum of the disease ranges from simple steatosis and nonalcoholic steatohepatitis (NASH) to cirrhosis and hepatocellular carcinoma(HCC). The infiltration of inflammatory cells characterizes NASH. This characteristic contributes to the progression of hepatitis, fibrosis, cirrhosis, and HCC. Therefore, distinguishing NASH from NAFLD is crucial.

Objective and Methods

Ninety-five patients with NAFLD, 44 with NASH, and 51 with non-NASH were included in the study to develop a new scoring system for differentiating NASH from NAFLD. Data on clinical and biological characteristics, as well as blood information, were obtained. Cytokeratin-18 (CK-18) fragments levels were measured using an enzyme-linked immunosorbant assay.

Results

Several indexes show significant differences between the two groups, which include body mass index (BMI), waist-on-hip ratio (WHR), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), γ-glutamyl transpeptidase (γ-GT), platelets, uric acid (UA), hs-C-reactive protein (hs-CRP), triglycerides (TG), albumin (ALB), and CK-18 fragments (all P < 0.05). The CK-18 fragment levels showed a significant positive correlation with steatosis severity, ballooning, lobular inflammation, and fibrosis stage (all P < 0.05). Therefore, a new model that combines ALT, platelets, CK-18 fragments, and TG was established by logistic regression among NAFLD patients. The AUROC curve in predicting NASH was 0.920 (95% CI: 0.866 - 0.974, cutoff value = 0.361, sensitivity = 89%, specificity = 86%, positive predictive value = 89%, negative predictive value = 89%).

Conclusion

The novel scoring system may be considered as a useful model in predicting the presence of NASH in NAFLD patients.     

Systemic levels of the soluble co-inhibitory immune checkpoints,CTLA-4, LAG-3, PD-1/PD-L1 and TIM-3 are markedly increased in basal cell carcinoma

Although co-inhibitory immune checkpoint proteins are primarily involved in promoting cell-cell interactions that suppress adaptive immunity, especially tumor immunity, the soluble cell-free variants of these molecules are also detectable in the circulation of cancer patients where they retain immunosuppressive activity. Nevertheless, little is known about the systemic levels of these soluble co-inhibitory immune checkpoints in patients with various subtypes of basal cell carcinoma (BCC), which is the most invasive and treatment-resistant type of this most commonly-occurring malignancy. In the current study, we have measured the systemic concentrations of five prominent co-inhibitory immune checkpoints, namely CTLA-4, LAG-3, PD-1/PD-L1 and TIM-3, as well as those of C-reactive protein (CRP) and vitamin D (VD), in a cohort of patients (n = 40) with BCC, relative to those of a group of control participants, using the combination of multiplex bead array, laser nephelometry and ELISA technologies, respectively. The median systemic concentrations of CRP and VD were comparable between the two groups; however, those of all five immune checkpoints were significantly elevated (P = 0.0184 - P = < 0.00001), with those of CTLA-4 and PD-1 being highly correlated (r = 0.87; P < 0.00001). This seemingly novel finding not only identifies the existence of significant systemic immunosuppression in BCC, but also underscores the therapeutic promise of immune checkpoint targeted therapy, as well as the potential of these proteins to serve as prognostic/predictive biomarkers in BCC.     

Accuracy of prediction scores and novel biomarkers for predicting nonalcoholic fatty liver disease in obese children

Background:

Accurate prediction scores for liver steatosis are demanded to enable clinicians to noninvasively screen for nonalcoholic fatty liver disease (NAFLD). Several prediction scores have been developed, however external validation is lacking.

Objective:

The aim was to determine the diagnostic accuracy of four existing prediction scores in severely obese children, to develop a new prediction score using novel biomarkers and to compare these results to the performance of ultrasonography.

Design and Results:

Liver steatosis was measured using proton magnetic resonance spectroscopy in 119 severely obese children (mean age 14.3 ± 2.1 years, BMI z‐score 3.35 ± 0.35). Prevalence of steatosis was 47%. The four existing predictions scores (“NAFLD liver fat score,” “fatty liver index,” “hepatic steatosis index,” and the pediatric prediction score) had only moderate diagnostic accuracy in this cohort (positive predictive value (PPV): 70, 61, 61, 69% and negative predictive value (NPV) 77, 69, 68, 75%, respectively). A new prediction score was built using anthropometry, routine biochemistry and novel biomarkers (leptin, adiponectin, TNF‐alpha, IL‐6, CK‐18, FGF‐21, and adiponutrin polymorphisms). The final model included ALT, HOMA, sex, and leptin. This equation (PPV 79% and NPV 80%) did not perform substantially better than the four other equations and did not outperform ultrasonography for excluding NAFLD (NPV 82%).

Conclusion:

The conclusion is in severely obese children and adolescents existing prediction scores and the tested novel biomarkers have insufficient diagnostic accuracy for diagnosing or excluding NAFLD.     

Soluble Co-Signaling Molecules Predict Long-Term Graft Outcome in Kidney-Transplanted Patients

Co-signaling molecules are responsible for full T-cell activation after solid organ transplantation. Their increased expression can lead to the release of a soluble form that can modulate the immune response post-transplantation. We analyzed the presence of co-signaling molecules (sCD30, sCD40, sCD137, sCTLA-4, sCD80, sCD28, sCD40L, sPD-1, and sPD-L1) in serum from kidney-transplanted patients (n = 59) obtained at different times (before transplantation, and 15 days, 3 months and 1 year post-transplantation) and their contribution to graft outcome was evaluated using principal component analysis. Before transplantation, high levels of soluble co-signaling molecules (mainly sCD30, sCD137 and sCD40) were detected in all patients. These molecules were modulated soon after receiving an allograft but never attained similar levels to those of healthy controls. A signature based on the determination of six soluble co-stimulatory (sCD30, sCD40, sCD137 and sCD40L) and co-inhibitory (sPD-1 and sPD-L1) molecules at 3 months post-transplantation allowed a group of patients to be identified (27.12%) with a worse long-term graft outcome. Patients with high levels of soluble molecules showed a progressive and gradual deterioration of kidney function (increased creatinine and proteinuria levels and decreased estimated glomerular filtration rate) over time and a higher risk of graft loss at 6 years post-transplantation than patients with low levels of these molecules (62.55% versus 5.14%, p<0.001). Thus, our data show an aberrant expression of soluble co-signaling molecules in kidney-transplanted patients whose quantification at 3 months post-transplantation might be a useful biomarker of immune status and help to predict long-term graft evolution.     

A proton nuclear magnetic resonance metabonomics approach for biomarker discovery in nonalcoholic fatty liver disease

This study was undertaken to discover novel biomarkers for the noninvasive early diagnosis of nonalcoholic fatty liver disease (NAFLD). A methionine and choline deficient (MCD) diet was used to represent different stages of NAFLD in male C57BL/6 mice. (1)H NMR spectroscopy and principal components analysis (PCA) were used to investigate the time-related biochemical changes in mice sera induced by the MCD diet. Many serum metabolites' concentrations changed between control and MCD-fed mice. Hierarchical cluster analysis (HCA) and artificial neural networks (ANNs) were used to select the least number of metabolites to be used for the noninvasive diagnosis of various stages of NAFLD; four potential biomarkers, serum glucose, lactate, glutamate/glutamine, and taurine were selected. To verify the diagnostic accuracy of these selected metabolites, their serum concentrations were measured in healthy controls (n = 28), NAFLD patients with steatosis (n = 15), steatosis patients with necro-inflammatory disease (n = 11), and NASH patients (n = 6). On the basis of results from MCD-fed mice model, clinical tests, and previous reports, we propose using the levels of the four metabolites for diagnosing NAFLD at various stages. Furthermore, the probability of developing NAFLD at a particular stage was assessed by multinomial logistic regression (MLR) based on the clinical results of the four serum metabolites.     

Glycemic Variability Is an Independent Predictive Factor for Development of Hepatic Fibrosis in Nonalcoholic Fatty Liver Disease

Patients with nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) often have metabolic disorders including insulin resistance and type 2 diabetes mellitus (T2DM). We clarified the predictive factors in glucose metabolism for progression of hepatic fibrosis in patients with NAFLD by the 75-g oral glucose tolerance test (75gOGTT) and a continuous glucose monitoring system (CGMS). One hundred sixty-nine patients (68 female and 101 male patients) with biopsy-proven NAFLD with performance with 75gOGTT were enrolled and divided into four groups according to the stage of hepatic fibrosis (F0–3). The proportion of patients with T2DM significantly gradually increased, HbA1c and the homeostasis model assessment of insulin resistance were significantly elevated, and 1,5-anhydroglucitol (1,5-AG) was remarkably decreased with the progression of fibrosis. In the 75gOGTT, both plasma glucose and insulin secretion were remarkably increased with the progression of fibrosis. The only factor significantly associated with advanced fibrosis was 1,5-AG (P = 0.008) as determined by multivariate logistic regression analysis. We next evaluated the changes in blood glucose during 24 hours by monitoring with the CGMS to confirm the relationship between glycemic variability and progression of fibrosis. Variability of median glucose, standard deviation of median glucose (P = 0.0022), maximum blood glucose (P = 0.0019), and ΔMin–max blood glucose (P = 0.0029) were remarkably higher in severe fibrosis than in mild fibrosis.

Conclusion

Hyperinsulinemia and hyperglycemia, especially glycemic variability, are important predictive factors in glucose impairment for the progression of hepatic fibrosis in NAFLD.     

Combined Biomarker Analysis for Risk of Acute Kidney Injury in Patients with ST-Segment Elevation Myocardial Infarction

Background

Acute kidney injury (AKI) complicating ST-segment elevation myocardial infarction (STEMI) increases subsequent morbidity and mortality. We combined the biomarkers of heart failure (HF; B-type natriuretic peptide [BNP] and soluble ST2 [sST2]) and renal injury (NGAL [neutrophil gelatinase-associated lipocalin] and cystatin C) in predicting the development of AKI in patients with STEMI undergoing primary percutaneous coronary intervention (PCI).

Methods and Results

From March 2010 to September 2013, 189 STEMI patients were sequentially enrolled and serum samples were collected at presentation for BNP, sST2, NGAL and cystatin C analysis. 37 patients (19.6%) developed AKI of varying severity within 48 hours of presentation. Univariate analysis showed age, Killip class ≥2, hypertension, white blood cell counts, hemoglobin, estimated glomerular filtration rate, blood urea nitrogen, creatinine, and all the four biomarkers were predictive of AKI. Serum levels of the biomarkers were correlated with risk of AKI and the Acute Kidney Injury Network (AKIN) stage and all significantly discriminated AKI (area under the receiver operating characteristic [ROC] curve: BNP: 0.86, sST2: 0.74, NGAL: 0.75, cystatin C: 0.73; all P < 0.05). Elevation of ≥2 of the biomarkers higher than the cutoff values derived from the ROC analysis improved AKI risk stratification, regardless of the creatine level (creatinine < 1.24 mg/dL: odds ratio [OR] 11.25, 95% confidence interval [CI] 1.63-77.92, P = 0.014; creatinine ≥ 1.24: OR 15.0, 95% CI 1.23-183.6, P = 0.034).

Conclusions

In this study of STEMI patients undergoing primary PCI, the biomarkers of heart failure (BNP and sST2) and renal injury (NGAL and cystatin C) at presentation were predictive of AKI. High serum levels of the biomarkers were associated with an elevated risk and more advanced stage of AKI. Regardless of the creatinine level, elevation of ≥2 of the biomarkers higher than the cutoff values indicated a further rise in AKI risk. Combined biomarker approach may assist in risk stratification of AKI in patients with STEMI.     

IGFBP3 Methylation Is a Novel Diagnostic and Predictive Biomarker in Colorectal Cancer

Background and Aim

Aberrant hypermethylation of cancer-related genes has emerged as a promising strategy for the development of diagnostic, prognostic and predictive biomarkers in human cancer, including colorectal cancer (CRC). The aim of this study was to perform a systematic and comprehensive analysis of a panel of CRC-specific genes as potential diagnostic, prognostic and predictive biomarkers in a large, population-based CRC cohort.

Patients and Methods

Methylation status of the SEPT9, TWIST1, IGFBP3, GAS7, ALX4 and miR137 genes was studied by quantitative bisulfite pyrosequencing in a population-based cohort of 425 CRC patients.

Results

Methylation levels of all genes analyzed were significantly higher in tumor tissues compared to normal mucosa (p<0.0001); however, cancer-associated hypermethylation was most frequently observed for miR137 (86.7%) and IGFBP3 (83%) in CRC patients. Methylation analysis using the combination of these two genes demonstrated greatest accuracy for the identification of colonic tumors (sensitivity 95.5%; specificity 90.5%). Low levels of IGFBP3 promoter methylation emerged as an independent risk factor for predicting poor disease free survival in stage II and III CRC patients (HR = 0.49, 95% CI: 0.28–0.85, p = 0.01). Our results also suggest that stage II & III CRC patients with high levels of IGFBP3 methylation do not benefit from adjuvant 5FU-based chemotherapy.

Conclusion

By analyzing a large, population-based CRC cohort, we demonstrate the potential clinical significance of miR137 and IGFBP3 hypermethylation as promising diagnostic biomarkers in CRC. Our data also revealed that IGFBP3 hypermethylation may serve as an independent prognostic and predictive biomarker in stage II and III CRC patients.     

Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools

The identification of a causal mutation is essential for molecular diagnosis and clinical management of many genetic disorders. However, even if next-generation exome sequencing has greatly improved the detection of nucleotide changes, the biological interpretation of most exonic variants remains challenging. Moreover, particular attention is typically given to protein-coding changes often neglecting the potential impact of exonic variants on RNA splicing. Here, we used the exon 10 of MLH1, a gene implicated in hereditary cancer, as a model system to assess the prevalence of RNA splicing mutations among all single-nucleotide variants identified in a given exon. We performed comprehensive minigene assays and analyzed patient’s RNA when available. Our study revealed a staggering number of splicing mutations in MLH1 exon 10 (77% of the 22 analyzed variants), including mutations directly affecting splice sites and, particularly, mutations altering potential splicing regulatory elements (ESRs). We then used this thoroughly characterized dataset, together with experimental data derived from previous studies on BRCA1, BRCA2, CFTR and NF1, to evaluate the predictive power of 3 in silico approaches recently described as promising tools for pinpointing ESR-mutations. Our results indicate that ΔtESRseq and ΔHZ_EI-based approaches not only discriminate which variants affect splicing, but also predict the direction and severity of the induced splicing defects. In contrast, the ΔΨ-based approach did not show a compelling predictive power. Our data indicates that exonic splicing mutations are more prevalent than currently appreciated and that they can now be predicted by using bioinformatics methods. These findings have implications for all genetically-caused diseases.