Browsing by Author "Kim, Kyung Tae"

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    Mg2+ Effect on Argonaute and RNA Duplex by Molecular Dynamics and Bioinformatics Implications
    (PLOS (Public Library of Science), 2014-10-17) Nam, Seungyoon; Ryu, Hyojung; Son, Won-joon; Kim, Yon Hui; Kim, Kyung Tae; Balch, Curt; Nephew, Kenneth P.; Lee, Jinhyuk; Medical Sciences Program at Indiana University Bloomington
    RNA interference (RNAi), mediated by small non-coding RNAs (e.g., miRNAs, siRNAs), influences diverse cellular functions. Highly complementary miRNA-target RNA (or siRNA-target RNA) duplexes are recognized by an Argonaute family protein (Ago2), and recent observations indicate that the concentration of Mg2+ ions influences miRNA targeting of specific mRNAs, thereby modulating miRNA-mRNA networks. In the present report, we studied the thermodynamic effects of differential [Mg2+] on slicing (RNA silencing cycle) through molecular dynamics simulation analysis, and its subsequent statistical analysis. Those analyses revealed different structural conformations of the RNA duplex in Ago2, depending on Mg2+ concentration. We also demonstrate that cation effects on Ago2 structural flexibility are critical to its catalytic/functional activity, with low [Mg2+] favoring greater Ago2 flexibility (e.g., greater entropy) and less miRNA/mRNA duplex stability, thus favoring slicing. The latter finding was supported by a negative correlation between expression of an Mg2+ influx channel, TRPM7, and one miRNA’s (miR-378) ability to downregulate its mRNA target, TMEM245. These results imply that thermodynamics could be applied to siRNA-based therapeutic strategies, using highly complementary binding targets, because Ago2 is also involved in RNAi slicing by exogenous siRNAs. However, the efficacy of a siRNA-based approach will differ, to some extent, based on the Mg2+ concentration even within the same disease type; therefore, different siRNA-based approaches might be considered for patient-to-patient needs.
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    Subtypes of Longitudinal Progression Trajectories Among Cognitively Impaired Older Adults with A+N+ Biomarkers: Trajectory Clustering Analysis
    (Wiley, 2025-01-09) Park, Sangyong; Byun, Min Soo; Yi, Dahyun; Ahn, Hyejin; Chumin, Evgeny J.; Jung, Gijung; Kim, Kyung Tae; Choi, Hyeji; Kim, Yoon Hee; Kim, Yu Kyeong; Lee, Yun-Sang; Kang, Koung Mi; Sohn, Chul-Ho; Lee, Jun-Young; Risacher, Shannon L.; Sporns, Olaf; Saykin, Andrew J.; Nho, Kwangsik; Lee, Dong Young; Radiology and Imaging Sciences, School of Medicine
    Background: We investigated heterogeneities in clinical progression trajectories among cognitively impaired (CI) older adults who were positive for both beta‐amyloid (Aβ) and neurodegeneration biomarkers of Alzheimer’s disease (AD) using trajectory clustering analysis. We then compared clinical and neuroimaging variables across clusters with different clinical trajectories. Method: CI older adults, consisting of individuals with mild cognitive impairment (MCI) or mild AD dementia were recruited from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (KBASE). All participants underwent comprehensive clinical assessment, and multi‐modal neuroimaging including 11C‐PiB PET, 18F‐FDG PET, and MRI with resting‐state functional MRI (fMRI). Among them, participants who were both amyloid positive (A+) and neurodegeneration positive (N+), including those with hypometabolism and cortical thinning in AD‐vulnerable regions, as well as hippocampal atrophy, were included. A subset of participants underwent 18F‐AV1451 PET to measure brain tau deposition. Group‐based trajectory modeling (GBTM) using the Clinical Dementia Rating (CDR)‐Sum of boxes (SOB) measured at baseline and longitudinal follow‐up up to four years, was used to identify clusters among A+N+ CI participants. Result: A total of 86 A+N+ CI individuals were included for the final analysis. A GBTM, based on longitudinal CDR‐SOB, identified two clusters with different trajectories: Cluster A (N = 54 [62.8%]) with slow progression and Cluster B (N = 32 [37.2%]) with rapid progression (Figure 1). No significant differences among age, sex, educational years, clinical diagnosis, global CDR, and APOE e4 carrier status were observed between the two clusters at baseline. These two clusters did not differ regarding global tau deposition and Braak Stages in a subset of participants (N = 34). However, at baseline, network segregation measure for the whole cortex and sensory‐motor network, and functional connectivity (FC) within the sensory‐motor network, differed between the two clusters after adjusting for age, sex, and education. Conclusion: Our study identified two clusters with heterogeneous clinical progression trajectories even among CI older adults who exhibited both Aβ and neurodegeneration biomarkers. Further studies are necessary to elucidate the relationship between resting‐state FC measures and AD subtypes with different clinical trajectories.