The MHC is recognized for its importance in human health and disease. However, many disease-associated variants throughout the region remain of unknown significance, residing predominantly within non-coding regions of the MHC. The characterization of non-coding RNA transcripts throughout the MHC is thus central to understanding the genetic contribution of these variants. Therefore, we characterize novel miRNA transcripts throughout the MHC by performing deep RNA sequencing of two B lymphoblastoid cell lines with completely characterized MHC haplotypes. Our analysis identifies 89 novel miRNA transcripts, 48 of which undergo Dicer-dependent biogenesis and are loaded onto the Argonaute silencing complex. Several of the identified mature miRNA and pre-miRNA transcripts are unique to specific MHC haplotypes and overlap common SNPs. Furthermore, 43 of the 89 identified novel miRNA transcripts lie within linkage disequilibrium blocks that contain a disease-associated SNP. These disease associated SNPs are associated with 65 unique disease phenotypes, suggesting that these transcripts may play a role in the etiology of numerous diseases associated with the MHC. Additional in silico analysis reveals the potential for thousands of putative pre-miRNA encoding loci within the MHC that may be expressed by different cell types and at different developmental stages.
New and improved techniques have been continuously introduced into CT and MR imaging modalities for the diagnosis and therapy planning of acute stroke. Nevertheless, non-contrast CT (NCCT) is almost always used by every institution as the front line diagnostic imaging modality due to its high affordability and availability. Consequently, the potential reward of extracting as much clinical information as possible from NCCT images can be very great. Intravenous tissue plasminogen activator (tPA) has become the gold standard for treating acute ischemic stroke because it is the only acute stroke intervention approved by the FDA. ASPECTS scoring based on NCCT images has been shown to be a reliable scoring method that helps physicians to make sound decisions regarding tPA administration. In order to further reduce inter-observer variation, we have developed the first end-to-end automatic ASPECTS scoring system using a novel method of contralateral comparison. Due to the self-adaptive nature of the method, our system is robust and has good generalizability. ROC analysis based on evaluation of 103 subjects who presented to the stroke center of Chang Gung Memorial Hospital with symptoms of acute stroke has shown that our system's dichromatic classification of patients into thrombolysis indicated or thrombolysis contraindicated groups has achieved a high accuracy rate with AUC equal to 90.2 %. The average processing time for a single case is 170 s. In conclusion, our system has the potential of enhancing quality of care and providing clinical support in the setting of a busy stroke or emergency center.
Background. HLA molecular mismatch (MM) is a risk factor for de novo donor-specific antibody (dnDSA) development in solid organ transplantation. HLA expression differences have also been associated with adverse outcomes in hematopoietic cell transplantation. We sought to study both MM and expression in assessing dnDSA risk. Methods. One hundred three HLA-DP-mismatched solid organ transplantation pairs were retrospectively analyzed. MM was computed using amino acids (aa), eplets, and, supplementarily, Grantham/Epstein scores. DPB1 alleles were classified as rs9277534-A (low-expression) or rs9277534-G (high-expression) linked. To determine the associations between risk factors and dnDSA, logistic regression, linkage disequilibrium (LD), and population-based analyses were performed. Results. A high-risk AA:GX (recipient:donor) expression combination (X = A or G) demonstrated strong association with HLA-DP dnDSA (P = 0.001). MM was also associated with HLA-DP dnDSA when evaluated by itself (eplet P = 0.007, aa P = 0.003, Grantham P = 0.005, Epstein P = 0.004). When attempting to determine the relative individual effects of the risk factors in multivariable analysis, only AA:GX expression status retained a strong association (relative risk = 18.6, P = 0.007 with eplet; relative risk = 15.8, P = 0.02 with aa), while MM was no longer significant (eplet P = 0.56, aa P = 0.51). Importantly, these risk factors are correlated, due to LD between the expression-tagging single-nucleotide polymorphism and polymorphisms along HLA-DPB1. Conclusions. The MM and expression risk factors each appear to be strong predictors of HLA-DP dnDSA and to possess clinical utility; however, these two risk factors are closely correlated. These metrics may represent distinct ways of characterizing a common overlapping dnDSA risk profile, but they are not independent. Further, we demonstrate the importance and detailed implications of LD effects in dnDSA risk assessment and possibly transplantation overall.
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