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Breaking tolerance to the natural human liver autoantigen cytochrome P450 2D6 by virus infection
(2008)
Autoimmune liver diseases, such as autoimmune hepatitis (AIH) and primary biliary cirrhosis, often have severe consequences for the patient. Because of a lack of appropriate animal models, not much is known about their potential viral etiology. Infection by liver-tropic viruses is one possibility for the breakdown of self-tolerance. Therefore, we infected mice with adenovirus Ad5 expressing human cytochrome P450 2D6 (Ad-2D6). Ad-2D6–infected mice developed persistent autoimmune liver disease, apparent by cellular infiltration, hepatic fibrosis, “fused” liver lobules, and necrosis. Similar to type 2 AIH patients, Ad-2D6–infected mice generated type 1 liver kidney microsomal–like antibodies recognizing the immunodominant epitope WDPAQPPRD of cytochrome P450 2D6 (CYP2D6). Interestingly, Ad-2D6–infected wild-type FVB/N mice displayed exacerbated liver damage when compared with transgenic mice expressing the identical human CYP2D6 protein in the liver, indicating the presence of a stronger immunological tolerance in CYP2D6 mice. We demonstrate for the first time that infection with a virus expressing a natural human autoantigen breaks tolerance, resulting in a chronic form of severe, autoimmune liver damage. Our novel model system should be instrumental for studying mechanisms involved in the initiation, propagation, and precipitation of virus-induced autoimmune liver diseases.
The emerging disciplines of lipidomics and metabolomics show great potential for the discovery of diagnostic biomarkers, but appropriate pre-analytical sample-handling procedures are critical because several analytes are prone to ex vivo distortions during sample collection. To test how the intermediate storage temperature and storage period of plasma samples from K3EDTA whole-blood collection tubes affect analyte concentrations, we assessed samples from non-fasting healthy volunteers (n = 9) for a broad spectrum of metabolites, including lipids and lipid mediators, using a well-established LC-MS-based platform. We used a fold change-based approach as a relative measure of analyte stability to evaluate 489 analytes, employing a combination of targeted LC-MS/MS and LC-HRMS screening. The concentrations of many analytes were found to be reliable, often justifying less strict sample handling; however, certain analytes were unstable, supporting the need for meticulous processing. We make four data-driven recommendations for sample-handling protocols with varying degrees of stringency, based on the maximum number of analytes and the feasibility of routine clinical implementation. These protocols also enable the simple evaluation of biomarker candidates based on their analyte-specific vulnerability to ex vivo distortions. In summary, pre-analytical sample handling has a major effect on the suitability of certain metabolites as biomarkers, including several lipids and lipid mediators. Our sample-handling recommendations will increase the reliability and quality of samples when such metabolites are necessary for routine clinical diagnosis.