Histological activity despite normal ALT and IgG serum levels in patients with autoimmune hepatitis and cirrhosis.

BACKGROUND & AIMS: In autoimmune hepatitis (AIH), normal levels of transaminases and IgG define biochemical remission and are considered the best surrogate markers for histological remission. This study assessed whether this also applies to patients with AIH cirrhosis. METHODS: In this European multicentric study, we included 125 biopsies from 113 patients with AIH and histologically proven cirrhosis; 105 biopsies from 104 patients with AIH without cirrhosis served as controls. Biochemical parameters were available within 4 weeks of biopsy. AIH activity was graded according to the modified Hepatitis Activity Index (mHAI), with mHAI ≥4/18 considered to indicate risk of disease progression. RESULTS: In total, 47 out of 125 liver biopsies were obtained from patients with AIH cirrhosis and normal ALT levels at time of biopsy. Only 26% (12/47) of those livers showed histological remission (mHAI <4/18), whereas 36% (17/47) showed moderate to high histological activity (mHAI ≥6/18). In patients with noncirrhotic AIH, 88% (46/52 biopsies) of cases with normal ALT levels had histological remission and only 4% (2/52) had an mHAI ≥6/18 (p <0.001). The addition of IgG to define complete biochemical remission only slightly improved the association with histological remission in the limited number of patients with AIH cirrhosis available for analysis [29% (5/17) of biopsies with mHAI <4/18]. ALT correlated closely with mHAI in AIH without cirrhosis but poorly in AIH with cirrhosis. CONCLUSIONS: In contrast to patients with noncirrhotic AIH, in patients with AIH cirrhosis, who are at risk of disease progression, normal ALT levels and potentially also complete biochemical remission are poor surrogate markers of histological remission. Thus, new biomarkers are needed to monitor disease activity and progression in patients with AIH cirrhosis. LAY SUMMARY: Autoimmune hepatitis (AIH) is an inflammatory disease of the liver that usually responds to immunosuppressive therapy. Serum transaminases and IgG levels within the normal ranges define complete biochemical remission and are considered as surrogate markers for histological disease activity. Here, we show that those biochemical markers are not sufficient to indicate low disease activity in patients with AIH and already established cirrhosis. Consequently, until better biomarkers for disease activity are found, only liver biopsy can reliably indicate disease activity in the presence of cirrhosis. Additional investigations, such as measurements of liver stiffness, should be undertaken to monitor non-invasively for disease progression in patients with AIH and established cirrhosis.

AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics.

SUMMARY: Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines. AVAILABILITY AND IMPLEMENTATION: The AlpsNMR R package and tutorial is freely available to download from http://github.com/sipss/AlpsNMR under the MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The differential plasma proteome of obese and overweight individuals undergoing a nutritional weight loss and maintenance intervention.

PURPOSE: The nutritional intervention program "DiOGenes" focuses on how obesity can be prevented and treated from a dietary perspective. We generated differential plasma proteome profiles in the DiOGenes cohort to identify proteins associated with weight loss and maintenance and explore their relation to body mass index, fat mass, insulin resistance, and sensitivity. EXPERIMENTAL DESIGN: Relative protein quantification was obtained at baseline and after combined weight loss/maintenance phases using isobaric tagging and MS/MS. A Welch t-test determined proteins differentially present after intervention. Protein relationships with clinical variables were explored using univariate linear models, considering collection center, gender and age as confounding factors. RESULTS: Four hundred and seventy three subjects were measured at baseline and end of the intervention; 39 proteins were longitudinally differential. Proteins with largest changes were sex hormone-binding globulin, adiponectin, C-reactive protein, calprotectin, serum amyloid A, and proteoglycan 4 (PRG4), whose association with obesity and weight loss is known. We identified new putative biomarkers for weight loss/maintenance. Correlation between PRG4 and proline-rich acidic protein 1 variation and Matsuda insulin sensitivity increment was showed. CONCLUSION AND CLINICAL RELEVANCE: MS-based proteomic analysis of a large cohort of non-diabetic overweight and obese individuals concomitantly identified known and novel proteins associated with weight loss and maintenance.

Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.