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Hong, S.-C.

Publications and source records attributed to Hong, S.-C..

3 recordsLinked to original sources

Narcolepsy risk loci are enriched in immune cells and suggest autoimmune modulation of the T cell receptor repertoire

Type 1 narcolepsy (T1N) is a neurological condition, in which the death of hypocretin-producing neurons in the lateral hypothalamus leads to excessive daytime sleepiness and symptoms of abnormal Rapid Eye Movement (REM) sleep. Known triggers for narcolepsy are influenza-A infection and associated immunization during the 2009 H1N1 influenza pandemic. Here, we genotyped all remaining consented narcolepsy cases worldwide and assembled this with the existing genotyped individuals. We used this multi-ethnic sample in genome wide association study (GWAS) to dissect disease mechanisms and interactions with environmental triggers (5,339 cases and 20,518 controls). Overall, we found significant associations with HLA (2 GWA significant subloci) and 11 other loci. Six of these other loci have been previously reported (TRA, TRB, CTSH, IFNAR1, ZNF365 and P2RY11) and five are new (PRF1, CD207, SIRPG, IL27 and ZFAND2A). Strikingly, in vaccination-related cases GWA significant effects were found in HLA, TRA, and in a novel variant near SIRPB1. Furthermore, IFNAR1 associated polymorphisms regulated dendritic cell response to influenza-A infection in vitro (p-value =1.92*10-25). A partitioned heritability analysis indicated specific enrichment of functional elements active in cytotoxic and helper T cells. Furthermore, functional analysis showed the genetic variants in TRA and TRB loci act as remarkable strong chain usage QTLs for TRAJ*24 (p-value = 0.0017), TRAJ*28 (p-value = 1.36*10-10) and TRBV*4-2 (p-value = 3.71*10-117). This was further validated in TCR sequencing of 60 narcolepsy cases and 60 DQB1*06:02 positive controls, where chain usage effects were further accentuated. Together these findings show that the autoimmune component in narcolepsy is defined by antigen presentation, mediated through specific T cell receptor chains, and modulated by influenza-A as a critical trigger.

genetics

Climate Change Influences the Japanese Cedar (Cryptomeria japonica) Pollen Count and Sensitization Rate in South Korea

BackgroundJapanese cedar pollen (JCP) is the major outdoor allergen for spring pollinosis and seasonal allergic rhinitis (SAR) caused by JCP is the most common disease in Jeju Island, South Korea and in Japan. Prior to our research, JCP counts were strongly temperature dependent and were significantly associated with the JCP sensitization rate and JC pollinosis. This event may still be ongoing due to the effects of global climate change, such as increasing temperature.\n\nMethods and FindingFor these reasons, we are studying the correlation among increasing temperatures, the JCP counts in the atmosphere and the JCP sensitization rate.\n\nConclusionsIn this study, our data show that increasing temperatures in January and April might lead to earlier and longer JCP seasons and that earlier and longer JCP seasons lead to an increase in the JCP sensitization rate, which influences the prevalence of JC pollinosis.

epidemiology

Decoding Single Molecule Time Traces with Dynamic Disorder

Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed. Here we report a new algorithm - Variational Bayes-double chain Markov model (VB-DCMM) - to analyze single molecule time trajectories that display dynamic disorder. The proposed analysis employing VB-DCMM allows us to detect the presence of dynamic disorder, if any, in each trajectory, identify the number of internal states, and estimate transition rates between the internal states as well as the rates of conformational transition within each internal state. Applying VB-DCMM algorithm to single molecule FRET data of H-DNA in 100 mM-Na+ solution, followed by data clustering, we show that at least 6 kinetic paths linking 4 distinct internal states are required to correctly interpret the duplex-triplex transitions of H-DNA.\n\nAuthor SummaryWe have developed a new algorithm to better decode single molecule data with dynamic disorder. Our new algorithm, which represents a substantial improvement over other methodologies, can detect the presence of dynamic disorder in each trajectory and quantify the kinetic characteristics of underlying energy landscape. As a model system, we applied our algorithm to the single molecule FRET time traces of H-DNA. While duplex-triplex transitions of H-DNA are conventionally interpreted in terms of two-state kinetics, slowly varying dynamic patterns corresponding to hidden internal states can also be identified from the individual time traces. Our algorithm reveals that at least 4 distinct internal states are required to correctly interpret the data.

biophysics