Biology subjects

Yoon, J. H.

Publications and source records attributed to Yoon, J. H..

4 recordsLinked to original sources

bioRxiv2025

Peripheral Complement C4 Protein in Schizophrenia: Association with Gene Copy Number and Immune Cell Subtypes

The lack of disease-modifying treatments for schizophrenia necessitates the exploration of novel aspects of its pathophysiology, including innate immune mechanisms in the periphery. C4 protein activation, associated with the complement cascade of innate immunity, associates with symptoms and predicts outcomes. However, C4 protein activation does not coincide with expected changes to other proteins in the complement cascade, suggesting another source of C4 protein activation. Using a combination of fresh whole blood from ten anonymous donors and a large set of publicly available microarray data, we show, for the first time, that C4 protein is found and expressed primarily in neutrophils and monocytes. Then, we compared the correlation between C4 protein in neutrophils, classical monocytes, plasma and the number of C4A gene copies. We determined the number of C4A genes using digital droplet PCR, C4 protein in neutrophils (15 patients/21 controls) and plasma (30 patients/38 controls) using western blotting, and classical monocytes (30 patients/38 controls) using flow cytometry. We found a moderate positive correlation between the number of C4A gene copies and the amount of C4 protein only in neutrophils and only in the schizophrenia group (Spearmans rho, r = 0.64, p = 0.01, Cohens d [~]1.67). Our results indicate a convergence of innate immunity mechanisms associated with schizophrenia. This novel mechanism of innate immunity in schizophrenia deserves further study to determine whether it could be a useful drug target.

immunology↗

bioRxiv2025

WRN and WRNIP1 ATPases impose high fidelity on translesion synthesis by Y-family DNA polymerases

Y-family DNA polymerases (Pols) are intrinsically highly error-prone; yet they conduct predominantly error-free translesion synthesis (TLS) in normal human cells. In response to DNA damage, Y-family Pols assemble and function together with WRN, WRNIP1, and Rev1 in TLS. Among these proteins, WRN possesses a 3[->]5 exonuclease activity and an ATPase/3[->]5 DNA helicase activity, and WRNIP1 has a DNA-dependent ATPase activity. In a previous study, we identified a role of WRN 3[->]5 exonuclease activity in the high in vivo fidelity of TLS by Y-family Pols. Here we provide evidence for a crucial role of WRN and WRNIP1 ATPase activities in raising the fidelity of TLS by these Pols. Defects in WRN and WRNIP1 ATPase activities cause a diversity of nucleotide (nt) misincorporations opposite DNA lesions by Y-family Pols, implicating an unprecedented role of these activities in restraining nt misincorporations, which they could accomplish by tightening the active site of the TLS Pol. Altogether, the combined actions of WRN and WRNIP1 ATPases in preventing nt misincorporations and of WRN exonuclease in removing misinserted nts confer such an enormous rise in the fidelity of Y-family Pols that they perform error-free TLS - essential for genome stability and cellular homeostasis.

genetics↗

bioRxiv2023

Learning gene networks under SNP perturbation using SNP and allele-specific expression data

Allele-specific expression quantification from RNA-seq reads provides opportunities to study the control of gene regulatory networks by cis-acting and trans-acting genetic variants. Many existing methods performed a single-gene and single-SNP association analysis to identify expression quantitative trait loci (eQTLs), and placed the eQTLs against known gene networks for functional interpretation. Instead, we view eQTL data as a capture of the effects of perturbation of gene regulatory system by a large number of genetic variants and reconstruct a gene network perturbed by eQTLs. We introduce a statistical framework called CiTruss for simultaneously learning a gene network and cis-acting and trans-acting eQTLs that perturb this network, given population allele-specific expression and SNP data. CiTruss uses a multi-level conditional Gaussian graphical model to model trans-acting eQTLs perturbing the expression of both alleles in gene network at the top level and cis-acting eQTLs perturbing the expression of each allele at the bottom level. We derive a transformation of this model that allows efficient learning for large-scale human data. Our analysis of the GTEx and LGxSM advanced intercross line mouse data for multiple tissue types with CiTruss provides new insights into genetics of gene regulation. CiTruss revealed that gene networks consist of local subnetworks over proximally located genes and global subnetworks over genes scattered across genome, and that several aspects of gene regulation by eQTLs such as the impact of genetic diversity, pleiotropy, tissue-specific gene regulation, and local and long-range linkage disequilibrium among eQTLs can be explained through these local and global subnetworks.

genetics↗

bioRxiv2018

Quantifying the effects of head movement on magnetic resonance spectroscopy estimates of gamma-aminobutyric acid

There has been keen interest in measuring in vivo GABA. However, GABA signal is low and typically measured using techniques vulnerable to the confounding effects of in-scanner head movement. This issue is particularly problematic for clinical studies since it may lead to Type I or II error in testing for group differences. While solutions to mitigate the effects of movement have been proposed, fundamental and largely unexamined issues are the nature and scale of this effect. We developed a method to quantify and characterize head movement during GABA spectroscopy and found that two parameters of movement, displacement and instantaneous movement, were inversely correlated with and accounted for 12.1% and 20.2% variance of GABA estimates respectively. We conclude that head movement can significantly affect GABA measurements and the application of methods to account for movement may improve of GABA measurement accuracy and the detection of true group differences in clinical studies.

neuroscience↗