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Article ; Online: Towards the Genetic Architecture of Complex Gene Expression Traits: Challenges and Prospects for eQTL Mapping in Humans.

Lee, Chaeyoung

2022 Volume 13, Issue 2

Abstract: The discovery of expression quantitative trait loci (eQTLs) and their target genes (eGenes) has not only compensated for the limitations of genome-wide association studies for complex phenotypes but has also provided a basis for predicting gene ... ...

Abstract	The discovery of expression quantitative trait loci (eQTLs) and their target genes (eGenes) has not only compensated for the limitations of genome-wide association studies for complex phenotypes but has also provided a basis for predicting gene expression. Efforts have been made to develop analytical methods in statistical genetics, a key discipline in eQTL analysis. In particular, mixed model- and deep learning-based analytical methods have been extremely beneficial in mapping eQTLs and predicting gene expression. Nevertheless, we still face many challenges associated with eQTL discovery. Here, we discuss two key aspects of these challenges: 1, the complexity of eTraits with various factors such as polygenicity and epistasis and 2, the voluminous work required for various types of eQTL profiles. The properties and prospects of statistical methods, including the mixed model method, Bayesian inference, the deep learning method, and the integration method, are presented as future directions for eQTL discovery. This review will help expedite the design and use of efficient methods for eQTL discovery and eTrait prediction.
MeSH term(s)	Bayes Theorem ; Gene Expression ; Genome-Wide Association Study/methods ; Humans ; Multifactorial Inheritance/genetics ; Quantitative Trait Loci/genetics
Language	English
Publishing date	2022-01-26
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes13020235
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Generating PET scan patterns in Alzheimer's by a mathematical model.

Lee, Chaeyoung / Friedman, Avner

PloS one

2024 Volume 19, Issue 4, Page(s) e0299637

Abstract: Alzheimer disease (AD) is the most common form of dementia. The cause of the disease is unknown, and it has no cure. Symptoms include cognitive decline, memory loss, and impairment of daily functioning. The pathological hallmarks of the disease are ... ...

Abstract	Alzheimer disease (AD) is the most common form of dementia. The cause of the disease is unknown, and it has no cure. Symptoms include cognitive decline, memory loss, and impairment of daily functioning. The pathological hallmarks of the disease are aggregation of plaques of amyloid-β (Aβ) and neurofibrillary tangles of tau proteins (τ), which can be detected in PET scans of the brain. The disease can remain asymptomatic for decades, while the densities of Aβ and τ continue to grow. Inflammation is considered an early event that drives the disease. In this paper, we develop a mathematical model that can produce simulated patterns of (Aβ,τ) seen in PET scans of AD patients. The model is based on the assumption that early inflammations, R and [Formula: see text], drive the growth of Aβ and τ, respectively. Recently approved drugs can slow the progression of AD in patients, provided treatment begins early, before significant damage to the brain has occurred. In line with current longitudinal studies, we used the model to demonstrate how to assess the efficacy of such drugs when given years before the disease becomes symptomatic.
MeSH term(s)	Humans ; Alzheimer Disease/pathology ; tau Proteins/metabolism ; Amyloid beta-Peptides/metabolism ; Positron-Emission Tomography ; Models, Theoretical
Chemical Substances	tau Proteins ; Amyloid beta-Peptides
Language	English
Publishing date	2024-04-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0299637
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Article: Towards the Genetic Architecture of Complex Gene Expression Traits: Challenges and Prospects for eQTL Mapping in Humans

Lee, Chaeyoung

Genes. 2022 Jan. 26, v. 13, no. 2

2022

Abstract	The discovery of expression quantitative trait loci (eQTLs) and their target genes (eGenes) has not only compensated for the limitations of genome-wide association studies for complex phenotypes but has also provided a basis for predicting gene expression. Efforts have been made to develop analytical methods in statistical genetics, a key discipline in eQTL analysis. In particular, mixed model– and deep learning–based analytical methods have been extremely beneficial in mapping eQTLs and predicting gene expression. Nevertheless, we still face many challenges associated with eQTL discovery. Here, we discuss two key aspects of these challenges: 1, the complexity of eTraits with various factors such as polygenicity and epistasis and 2, the voluminous work required for various types of eQTL profiles. The properties and prospects of statistical methods, including the mixed model method, Bayesian inference, the deep learning method, and the integration method, are presented as future directions for eQTL discovery. This review will help expedite the design and use of efficient methods for eQTL discovery and eTrait prediction.
Keywords	Bayesian theory ; epistasis ; gene expression ; prediction ; quantitative traits ; statistical models
Language	English
Dates of publication	2022-0126
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2527218-4
ISSN	2073-4425
ISSN	2073-4425
DOI	10.3390/genes13020235
Database	NAL-Catalogue (AGRICOLA)

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Article: Heterogeneous genetic architecture by gender for precision medicine of cardiovascular disease.

Lee, Chaeyoung

Journal of geriatric cardiology : JGC

2018 Volume 15, Issue 5, Page(s) 325–327

Language	English
Publishing date	2018-07-23
Publishing country	China
Document type	Journal Article
ZDB-ID	2421391-3
ISSN	1671-5411
ISSN	1671-5411
DOI	10.11909/j.issn.1671-5411.2018.05.001
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Article ; Online: Identification and Interpretation of eQTL and eGenes for Hodgkin Lymphoma Susceptibility.

An, Yeeun / Lee, Chaeyoung

Genes

2023 Volume 14, Issue 6

Abstract: Genome-wide association studies (GWAS) have revealed approximately 100 genomic signals associated with Hodgkin lymphoma (HL); however, their target genes and underlying mechanisms causing HL susceptibility remain unclear. In this study, transcriptome- ... ...

Abstract	Genome-wide association studies (GWAS) have revealed approximately 100 genomic signals associated with Hodgkin lymphoma (HL); however, their target genes and underlying mechanisms causing HL susceptibility remain unclear. In this study, transcriptome-wide analysis of expression quantitative trait loci (eQTL) was conducted to identify target genes associated with HL GWAS signals. A mixed model, which explains polygenic regulatory effects by the genomic covariance among individuals, was implemented to discover expression genes (eGenes) using genotype data from 462 European/African individuals. Overall, 80 eGenes were identified to be associated with 20 HL GWAS signals. Enrichment analysis identified apoptosis, immune responses, and cytoskeletal processes as functions of these eGenes. The eGene of rs27524 encodes ERAP1 that can cleave peptides attached to human leukocyte antigen in immune responses; its minor allele may help Reed-Sternberg cells to escape the immune response. The eGene of rs7745098 encodes ALDH8A1 that can oxidize the precursor of acetyl-CoA for the production of ATP; its minor allele may increase oxidization activity to evade apoptosis of pre-apoptotic germinal center B cells. Thus, these minor alleles may be genetic risk factors for HL susceptibility. Experimental studies on genetic risk factors are needed to elucidate the underlying mechanisms of HL susceptibility and improve the accuracy of precision oncology.
MeSH term(s)	Humans ; Hodgkin Disease/genetics ; Quantitative Trait Loci ; Genome-Wide Association Study ; Precision Medicine ; Gene Expression ; Aminopeptidases/genetics ; Minor Histocompatibility Antigens
Chemical Substances	ERAP1 protein, human (EC 3.4.11.-) ; Aminopeptidases (EC 3.4.11.-) ; Minor Histocompatibility Antigens
Language	English
Publishing date	2023-05-24
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes14061142
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Article: Bayesian Inference for Mixed Model-Based Genome-Wide Analysis of Expression Quantitative Trait Loci by Gibbs Sampling.

Lee, Chaeyoung

Frontiers in genetics

2019 Volume 10, Page(s) 199

Abstract: The importance of expression quantitative trait locus (eQTL) has been emphasized in understanding the genetic basis of cellular activities and complex phenotypes. Mixed models can be employed to effectively identify eQTLs by explaining polygenic effects. ...

Abstract	The importance of expression quantitative trait locus (eQTL) has been emphasized in understanding the genetic basis of cellular activities and complex phenotypes. Mixed models can be employed to effectively identify eQTLs by explaining polygenic effects. In these mixed models, the polygenic effects are considered as random variables, and their variability is explained by the polygenic variance component. The polygenic and residual variance components are first estimated, and then eQTL effects are estimated depending on the variance component estimates within the frequentist mixed model framework. The Bayesian approach to the mixed model-based genome-wide eQTL analysis can also be applied to estimate the parameters that exhibit various benefits. Bayesian inferences on unknown parameters are based on their marginal posterior distributions, and the marginalization of the joint posterior distribution is a challenging task. This problem can be solved by employing a numerical algorithm of integrals called Gibbs sampling as a Markov chain Monte Carlo. This article reviews the mixed model-based Bayesian eQTL analysis by Gibbs sampling. Theoretical and practical issues of Bayesian inference are discussed using a concise description of Bayesian modeling and the corresponding Gibbs sampling. The strengths of Bayesian inference are also discussed. Posterior probability distribution in the Bayesian inference reflects uncertainty in unknown parameters. This factor is useful in the context of eQTL analysis where a sample size is too small to apply the frequentist approach. Bayesian inference based on the posterior that reflects prior knowledge, will be increasingly preferred with the accumulation of eQTL data. Extensive use of the mixed model-based Bayesian eQTL analysis will accelerate understanding of eQTLs exhibiting various regulatory functions.
Language	English
Publishing date	2019-03-22
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2019.00199
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Article ; Online: Identification and Interpretation of eQTL and eGenes for Hodgkin Lymphoma Susceptibility

An, Yeeun / Lee, Chaeyoung

Genes (Basel). 2023 May 24, v. 14, no. 6

2023

Abstract	Genome-wide association studies (GWAS) have revealed approximately 100 genomic signals associated with Hodgkin lymphoma (HL); however, their target genes and underlying mechanisms causing HL susceptibility remain unclear. In this study, transcriptome-wide analysis of expression quantitative trait loci (eQTL) was conducted to identify target genes associated with HL GWAS signals. A mixed model, which explains polygenic regulatory effects by the genomic covariance among individuals, was implemented to discover expression genes (eGenes) using genotype data from 462 European/African individuals. Overall, 80 eGenes were identified to be associated with 20 HL GWAS signals. Enrichment analysis identified apoptosis, immune responses, and cytoskeletal processes as functions of these eGenes. The eGene of rs27524 encodes ERAP1 that can cleave peptides attached to human leukocyte antigen in immune responses; its minor allele may help Reed–Sternberg cells to escape the immune response. The eGene of rs7745098 encodes ALDH8A1 that can oxidize the precursor of acetyl-CoA for the production of ATP; its minor allele may increase oxidization activity to evade apoptosis of pre-apoptotic germinal center B cells. Thus, these minor alleles may be genetic risk factors for HL susceptibility. Experimental studies on genetic risk factors are needed to elucidate the underlying mechanisms of HL susceptibility and improve the accuracy of precision oncology.
Keywords	HLA antigens ; Hodgkin disease ; acetyl coenzyme A ; alleles ; apoptosis ; covariance ; cytoskeleton ; genomics ; genotype ; immune response ; lymph nodes ; peptides ; quantitative traits ; risk ; statistical models
Language	English
Dates of publication	2023-0524
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ZDB-ID	2527218-4
ISSN	2073-4425
ISSN	2073-4425
DOI	10.3390/genes14061142
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Article: Genome-Wide Expression Quantitative Trait Loci Analysis Using Mixed Models.

Lee, Chaeyoung

Frontiers in genetics

2018 Volume 9, Page(s) 341

Abstract: Expression quantitative trait loci (eQTLs) are important for understanding the genetic basis of cellular activities and complex phenotypes. Genome-wide eQTL analyses can be effectively conducted by employing a mixed model. The mixed model includes random ...

Abstract	Expression quantitative trait loci (eQTLs) are important for understanding the genetic basis of cellular activities and complex phenotypes. Genome-wide eQTL analyses can be effectively conducted by employing a mixed model. The mixed model includes random polygenic effects with variability, which can be estimated by the covariance structure of pairwise genomic similarity among individuals based on genotype information for nucleotide sequence variants. This increases the accuracy of identifying eQTLs by avoiding population stratification. Its extensive use will accelerate our understanding of the genetics of gene expression and complex phenotypes. An overview of genome-wide eQTL analyses using mixed model methodology is provided, including discussions of both theoretical and practical issues. The advantages of employing mixed models are also discussed in this review.
Language	English
Publishing date	2018-08-21
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2018.00341
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Article ; Online: Mixed model-based eQTL analysis reveals lncRNAs associated with regulation of genes involved in sex determination and spermatogenesis: The key to understanding human gender imbalance.

An, Yeeun / Lee, Chaeyoung

Computational biology and chemistry

2022 Volume 99, Page(s) 107713

Abstract: Background: An imbalance in the prenatal sex ratio in humans may be due to several factors affecting sperm physiology, including genetic features. In this study, we conducted a transcriptome-wide analysis of expression quantitative trait loci (eQTLs) to ...

Abstract	Background: An imbalance in the prenatal sex ratio in humans may be due to several factors affecting sperm physiology, including genetic features. In this study, we conducted a transcriptome-wide analysis of expression quantitative trait loci (eQTLs) to identify target genes associated with previously described QTLs associated with gender imbalance. Methods: A mixed model explaining polygenic effects by genomic covariance among individuals was used to identify the eQTLs using gene expression and genotype data from 462 European/African individuals. Results: Eight eGenes were associated with four QTLs (P < 4.00 × 10 Conclusions: The above eGenes contribute directly or indirectly to gene regulation for sex determination and spermatogenesis, thereby serving as important functional clues for gender-biased selection.
MeSH term(s)	Co-Repressor Proteins/genetics ; DNA-Binding Proteins ; Genome-Wide Association Study ; Humans ; Male ; Polymorphism, Single Nucleotide ; Proteins/genetics ; Quantitative Trait Loci/genetics ; RNA, Long Noncoding/genetics ; Repressor Proteins ; Semen ; Spermatogenesis/genetics ; Transcription Factors/genetics
Chemical Substances	Co-Repressor Proteins ; DNA-Binding Proteins ; FATE1 protein, human ; PELP1 protein, human ; Proteins ; RNA, Long Noncoding ; Repressor Proteins ; SPATA3 protein, human ; TEX14 protein, human ; Transcription Factors ; ZNF433 protein, human
Language	English
Publishing date	2022-06-09
Publishing country	England
Document type	Journal Article
ISSN	1476-928X
ISSN (online)	1476-928X
DOI	10.1016/j.compbiolchem.2022.107713
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Article ; Online: Antagonistic regulatory effects of a single cis-acting expression quantitative trait locus between transcription and translation of the MRPL43 gene.

Han, Jooyeon / Lee, Chaeyoung

BMC genomic data

2022 Volume 23, Issue 1, Page(s) 42

Abstract: Background: Heterogeneity of expression quantitative trait locus (eQTL) effects have been shown across gene expression processes. Knowledge on how to produce the heterogeneity is quite limited. This study aims to examine fluctuations in differential ... ...

Abstract	Background: Heterogeneity of expression quantitative trait locus (eQTL) effects have been shown across gene expression processes. Knowledge on how to produce the heterogeneity is quite limited. This study aims to examine fluctuations in differential gene expression by alleles of sequence variants across expression processes. Results: Genome-wide eQTL analyses with transcriptome-wide gene expression data revealed 20 cis-acting eQTLs associated simultaneously with mRNA expression, ribosome occupancy, and protein abundance. A 97 kb-long eQTL signal for mitochondrial ribosomal protein L43 (MRPL43) covered the gene, showing a heterogeneous effect size on gene products across expression stages. One allele of the eQTL was associated with increased mRNA expression and ribosome occupancy but decreased protein abundance. We examined the heterogeneity and found that the eQTL can be attributed to the independent functions of three nucleotide variants, with a strong linkage. NC_000010.11:g.100987606G > T, upstream of MRPL43, may regulate the binding affinity of transcription factors. NC_000010.11:g.100986746C > G, 3 bp from an MRPL43 splice donor site, may alter the splice site. NC_000010.11:g.100978794A > G, in the isoform with a long 3'-UTR, may strengthen the binding affinity of the microRNA. Individuals with the TGG haplotype at these three variants had higher levels of mRNA expression and ribosome occupancy than individuals with the GCA haplotype but lower protein levels, producing the flipped effect throughout the expression process. Conclusions: These findings suggest that multiple functional variants in a linkage exert their regulatory functions at different points in the gene expression process, producing a complexity of single eQTLs.
MeSH term(s)	Alleles ; Genome-Wide Association Study ; Humans ; Mitochondrial Proteins/genetics ; Polymorphism, Single Nucleotide/genetics ; Quantitative Trait Loci/genetics ; RNA, Messenger/genetics ; Ribosomal Proteins/genetics
Chemical Substances	MRPL43 protein, human ; Mitochondrial Proteins ; RNA, Messenger ; Ribosomal Proteins
Language	English
Publishing date	2022-06-04
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2730-6844
ISSN (online)	2730-6844
DOI	10.1186/s12863-022-01057-7
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