Browsing by Subject "HLA antigen"

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Open Access
Evaluation of X chromosome inactivation with respect to HLA genetic susceptibility in rheumatoid arthritis and systemic sclerosis
(Public Library of Science, 2016) Kanaan, S. B.; Onat, O. E.; Balandraud, N.; Martin, G. V.; Nelson, J. L.; Azzouz, D. F.; Auger, I.; Arnoux, F.; Martin, M.; Roudier, J.; Ozcelik, T.; Lambert, N. C.
Background: Autoimmune diseases, including rheumatoid arthritis (RA) and systemic sclerosis (SSc) are characterized by a strong genetic susceptibility from the Human Leucocyte Antigen (HLA) locus. Additionally, disorders of epigenetic processes, in particular non-random X chromosome inactivation (XCI), have been reported in many female-predominant autoimmune diseases. Here we test the hypothesis that women with RA or SSc who are strongly genetically predisposed are less susceptible to XCI bias. Methods: Using methylation sensitive genotyping of the androgen receptor (AR) gene, XCI profiles were performed in peripheral blood mononuclear cells from 161 women with RA, 96 women with SSc and 100 healthy women. HLA-DRB1 and DQB1 were genotyped. Presence of specific autoantibodies was documented for patients. XCI skewing was defined as having a ratio ≥ 80:20 of cells inactivating the same X chromosome. Results: 110 women with RA, 68 women with SSc, and 69 controls were informative for the AR polymorphism. Among them 40.9% of RA patients and 36.8% of SSc patients had skewed XCI compared to 17.4% of healthy women (P = 0.002 and 0.018, respectively). Presence of RA-susceptibility alleles coding for the "shared epitope" correlated with higher skewing among RA patients (P = 0.002) and such correlation was not observed in other women, healthy or with SSc. Presence of SSc-susceptibility alleles did not correlate with XCI patterns among SSc patients. Conclusion: Data demonstrate XCI skewing in both RA and SSc compared to healthy women. Unexpectedly, skewed XCI occurs more often in women with RA carrying the shared epitope, which usually reflects severe disease. This reinforces the view that loss of mosaicism in peripheral blood may be a consequence of chronic autoimmunity. © 2016 Kanaan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Privacy-preserving genomic testing in the clinic: a model using HIV treatment
(Nature Publishing Group, 2016) Mclaren, P. J.; Raisaro, J. L.; Aouri, M.; Rotger, M.; Ayday, E.; Bartha, I.; Delgado, M. B.; Vallet, Y.; Günthard, H. F.; Cavassini, M.; Furrer, H.; Doco-Lecompte, T.; Marzolini, C.; Schmid, P.; Di Benedetto, C.; Decosterd, L. A.; Fellay, J.; Hubaux, Jean-Pierre; Telenti A.
Purpose:The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics.Methods:We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers.Results:A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%.Conclusions:The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.