OBJECTIVE: The aim of this study was to clone and express Hev b 3 and to obtain the immunologic active and soluble recombinant allergen for diagnosis of SB-associated latex allergy.
METHODS: A complementary DNA (cDNA) coding for Hev b 3 was amplified from RNA of fresh latex collected from Malaysian rubber trees (Hevea brasiliensis). PCR primers were designed according to sequences of internal peptide fragments of natural (n) Hev b 3. The 5'-end sequence was obtained by specific amplification of cDNA ends. The recombinant (r) Hev b 3 was produced in Escherichia coli as a 6xHis tagged protein. Immunoblotting and inhibition assays were performed to characterize the recombinant allergen.
RESULTS: An Hev b 3 cDNA clone of 922 bp encoding a protein of 204 amino acid residues corresponding to a molecular weight of 22.3 kd was obtained. In immunoblots 29/35, latex-allergic patients with SB revealed IgE binding to rHev b 3, as did 4 of 15 of the latex-sensitized group. The presence of all IgE epitopes on rHev b 3 was shown by its ability to abolish all IgE binding to nHev b 3. Hev b 3 is related to Hev b 1 by a sequence identity of 47%. Cross-reactivity between these 2 latex allergens was illustrated by the large extent of inhibition of IgE binding to nHev b 1 by rHev b 3.
CONCLUSION: rHev b 3 constitutes a suitable in vitro reagent for the diagnosis of latex allergy in patients with SB. The determination of the full sequence of Hev b 3 and the production of the recombinant allergen will allow the epitope mapping and improve diagnostic reagents for latex allergy.
METHODS: A review of the literature identified studies containing histology verified CAP data (M probe, vibration controlled transient elastography with FibroScan®) for grading of steatosis (S0-S3). Receiver operating characteristic analysis after correcting for center effects was used as well as mixed models to test the impact of covariates on CAP. The primary outcome was establishing CAP cut-offs for distinguishing steatosis grades.
RESULTS: Data from 19/21 eligible papers were provided, comprising 3830/3968 (97%) of patients. Considering data overlap and exclusion criteria, 2735 patients were included in the final analysis (37% hepatitis B, 36% hepatitis C, 20% NAFLD/NASH, 7% other). Steatosis distribution was 51%/27%/16%/6% for S0/S1/S2/S3. CAP values in dB/m (95% CI) were influenced by several covariates with an estimated shift of 10 (4.5-17) for NAFLD/NASH patients, 10 (3.5-16) for diabetics and 4.4 (3.8-5.0) per BMI unit. Areas under the curves were 0.823 (0.809-0.837) and 0.865 (0.850-0.880) respectively. Optimal cut-offs were 248 (237-261) and 268 (257-284) for those above S0 and S1 respectively.
CONCLUSIONS: CAP provides a standardized non-invasive measure of hepatic steatosis. Prevalence, etiology, diabetes, and BMI deserve consideration when interpreting CAP. Longitudinal data are needed to demonstrate how CAP relates to clinical outcomes.
LAY SUMMARY: There is an increase in fatty liver for patients with chronic liver disease, linked to the epidemic of the obesity. Invasive liver biopsies are considered the best means of diagnosing fatty liver. The ultrasound based controlled attenuation parameter (CAP) can be used instead, but factors such as the underlying disease, BMI and diabetes must be taken into account. Registration: Prospero CRD42015027238.
AIM: To determine how to use CAP in interpreting liver stiffness measurements.
METHODS: This is a secondary analysis of data from an individual patient data meta-analysis on CAP. The main exclusion criteria for the current analysis were unknown aetiology, unreliable elastography measurement and data already used for the same research question. Aetiology-specific liver stiffness measurement cut-offs were determined and used to estimate positive and negative predictive values (PPV/NPV) with logistic regression as functions of CAP.
RESULTS: Two thousand and fifty eight patients fulfilled the inclusion criteria (37% women, 18% NAFLD/NASH, 42% HBV, 40% HCV, 51% significant fibrosis ≥ F2). Youden optimised cut-offs were only sufficient for ruling out cirrhosis (NPV of 98%). With sensitivity and specificity-optimised cut-offs, NPV for ruling out significant fibrosis was moderate (70%) and could be improved slightly through consideration of CAP. PPV for significant fibrosis and cirrhosis were 68% and 55% respectively, despite specificity-optimised cut-offs for cirrhosis.
CONCLUSIONS: Liver stiffness measurement values below aetiology-specific cut-offs are very useful for ruling out cirrhosis, and to a lesser extent for ruling out significant fibrosis. In the case of the latter, Controlled Attenuation Parameter can improve interpretation slightly. Even if cut-offs are very high, liver stiffness measurements are not very reliable for ruling in fibrosis or cirrhosis.