Prevalence, Patterns, and Genetic Association Analysis of Modic Vertebral Endplate Changes

Rishi Mugesh Kanna,Rajasekaran Shanmuganathan,Veera Ranjani Rajagopalan,Senthil Natesan,Raveendran Muthuraja,Kenneth Man Chee Cheung,Danny Chan,Patrick Yu Ping Kao,Anita Yee,Ajoy Prasad Shetty 대한척추외과학회 2017 Asian Spine Journal Vol.11 No.4

Study Design: A prospective genetic association study. Purpose: The etiology of Modic changes (MCs) is unclear. Recently, the role of genetic factors in the etiology of MCs has been evaluated. However, studies with a larger patient subset are lacking, and candidate genes involved in other disc degeneration phenotypes have not been evaluated. We studied the prevalence of MCs and genetic association of 41 candidate genes in a large Indian cohort. Overview of Literature: MCs are vertebral endplate signal changes predominantly observed in the lumbar spine. A significant association between MCs and lumbar disc degeneration and nonspecific low back pain has been described, with the etiopathogenesis implicating various mechanical, infective, and biochemical factors. Methods: We studied 809 patients using 1.5-T magnetic resonance imaging to determine the prevalence, patterns, distribution, and type of lumbar MCs. Genetic association analysis of 71 single nucleotide polymorphisms (SNPs) of 41 candidate genes was performed based on the presence or absence of MCs. SNPs were genotyped using the Sequenome platform, and an association test was performed using PLINK software. Results: The mean age of the study population (n=809) was 36.7±10.8 years. Based on the presence of MCs, the cohort was divided into 702 controls and 107 cases (prevalence, 13%). MCs were more commonly present in the lower (149/251, 59.4%) than in the upper (102/251, 40.6%) endplates. L4–5 endplates were the most commonly affected levels (30.7%). Type 2 MCs were the most commonly observed pattern (n=206, 82%). The rs2228570 SNP of VDR (p =0.02) and rs17099008 SNP of MMP20 (p =0.03) were significantly associated with MCs. Conclusions: Genetic polymorphisms of SNPs of VDR and MMP20 were significantly associated with MCs. Understanding the etiopathogenetic mechanisms of MCs is important for planning preventive and therapeutic strategies.

Sample Size and Statistical Power Calculation in Genetic Association Studies

Hong, Eun-Pyo,Park, Ji-Wan Korea Genome Organization 2012 Genomics & informatics Vol.10 No.2

A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5% minor allele frequency, complete linkage disequilibrium (LD), 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.

Sample Size and Statistical Power Calculation in Genetic Association Studies

홍은표,박지완 한국유전체학회 2012 Genomics & informatics Vol.10 No.2

A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5%minor allele frequency, complete linkage disequilibrium (LD), 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.

Multiple Group Testing Procedures for Analysis of High-Dimensional Genomic Data

Ko, Hyoseok,Kim, Kipoong,Sun, Hokeun Korea Genome Organization 2016 Genomics & informatics Vol.14 No.4

In genetic association studies with high-dimensional genomic data, multiple group testing procedures are often required in order to identify disease/trait-related genes or genetic regions, where multiple genetic sites or variants are located within the same gene or genetic region. However, statistical testing procedures based on an individual test suffer from multiple testing issues such as the control of family-wise error rate and dependent tests. Moreover, detecting only a few of genes associated with a phenotype outcome among tens of thousands of genes is of main interest in genetic association studies. In this reason regularization procedures, where a phenotype outcome regresses on all genomic markers and then regression coefficients are estimated based on a penalized likelihood, have been considered as a good alternative approach to analysis of high-dimensional genomic data. But, selection performance of regularization procedures has been rarely compared with that of statistical group testing procedures. In this article, we performed extensive simulation studies where commonly used group testing procedures such as principal component analysis, Hotelling's $T^2$ test, and permutation test are compared with group lasso (least absolute selection and shrinkage operator) in terms of true positive selection. Also, we applied all methods considered in simulation studies to identify genes associated with ovarian cancer from over 20,000 genetic sites generated from Illumina Infinium HumanMethylation27K Beadchip. We found a big discrepancy of selected genes between multiple group testing procedures and group lasso.

Genetic Polymorphism Predisposing to Differentiated Thyroid Cancer: A Review of Major Findings of the Genome-Wide Association Studies

Vladimir Saenko,Tatiana I. Rogounovitch 대한내분비학회 2018 Endocrinology and metabolism Vol.33 No.2

Thyroid cancer has one of the highest hereditary component among human malignancies as seen in medical epidemiology investigations, suggesting the potential meaningfulness of genetic studies. Here we review researches into genetic variations that influence the chance of developing non-familial differentiated thyroid cancer (DTC), focusing on the major findings of the genome-wide association studies (GWASs) of common single-nucleotide polymorphisms (SNPs). To date, eight GWAS have been performed, and the association of a number of SNPs have been reproduced in dozens of replication investigations across different ethnicities, including Korea and Japan. Despite the cumulative effect of the strongest SNPs demonstrates gradual increase in the risk for cancer and their association signals are statistically quite significant, the overall prediction ability for DTC appears to be very limited. Thus, genotyping of common SNPs only would be insufficient for evidence-based counseling in clinical setting at present. Further studies to include less significant and rare SNPs, non-SNP genetic information, gene-gene interactions, ethnicity, non-genetic and environmental factors, and development of more advanced computational algorithms are warranted to approach to personalized disease risk prediction and prognostication.

Genetic Variations in TXNRD1 as Potential Predictors of Drug-Induced Liver Injury

권재우,Eun-Soon Shin,Jong-Eun Lee,김상헌,김상훈,지영구,김윤근,박해심,민경업,Heung-Woo Park 대한천식알레르기학회 2012 Allergy, Asthma & Immunology Research Vol.4 No.3

Purpose: Drug-induced liver injury (DILI) is the most common adverse drug reaction; however, it is not easily predicted. We hypothesize that DILI has a common genetic basis. Based on the findings of previous animal studies on toxic hepatitis, we selected the thioredoxin reductase 1 gene (TXNRD1) as a candidate marker of DILI for this genetic association study. Methods: Records from 118 patients with DILI were extracted from the database of the Adverse Drug Reaction Research Group in South Korea. Causative drugs included antituberculosis drugs (n=68, 57.6%), antibiotics (n=22, 18.6%), antiepileptic drugs (n=7, 5.9%), non-steroidal anti-inflammatory drugs (n=5, 4.2%), and others (n=16, 13.7%). Seven single nucleotide polymorphisms (SNPs) in TXNRD1 (rs10735393, rs4964287, rs4595619, rs10861201, rs11111997, rs4246270, and rs4246271) were scored in 118 DILI patients and in 120 drug-matched controls without liver injury. Results: No differences were found between the frequencies of any of the 7 SNPs in the cases and controls; however, a significant association was found between a TTA haplotype composed of rs10735393, rs4964287, and rs4595619 and DILI using an allele model (odds ratio, 1.79; 95% confidence interval, 1.18-2.73; P=0.008; Bonferroni corrected P=0.024). Conclusions:These results suggest that genetic variations in TXNRD1 favor the development of DILI, although a larger confirmative study is needed.

Multiple susceptibility loci at chromosome 11q23.3 are associated with plasma triglyceride in East Asians

Gombojav, Bayasgalan,Lee, Soo Ji,Kho, Minjung,Song, Yun-Mi,Lee, Kayoung,Sung, Joohon American Society for Biochemistry and Molecular Bi 2016 Journal of lipid research Vol.57 No.2

<P>Genetic studies of plasma TG levels have identified associations with multiple candidate loci on chromosome11q23.3, which harbors a number of genes, including BUD13, ZNF259, and APOA5-A4-C3-A1. This study aimed to examine whether these multiple candidate genes on the 11q23.3 regions exert independent effects on TG levels or whether their effects are confounded by linkage disequilibrium (LD). We performed a genome-wide association study and consequent fine-mapping analyses on TG levels in two Korean population-based cohorts: the Korea Association Resource study (n = 8,223) and the Healthy Twin study (n = 1,735). A total of 301 loci reached genome-wide significance level in pooled analysis, including 10 SNPs with weak LD (r(2) < 0.06) clustered on 11q23.3: ApoA5 (rs651821, rs2075291); ZNF259 (rs964184, rs603446); BUD13 (rs11216126); Apoa4 (rs7396851); SIK3 (rs12292858); PCSK7 (rs199890178); PAFAH1B2 (rs12420127), and SIDT2 (rs2269399). When the inter-dependence between alleles was examined using conditional models, five loci on BUD13, ZNF259, and ApoA 5 showed possible independent associations. A haplotype analysis using five SNPs revealed both hyper-and hypotriglyceridemic haplotypes, which are relatively common in Koreans (haplotype frequency 0.08-0.22). Our findings suggest the presence of multiple functional loci on 11q23.3, which might exert their effects on plasma TG level independently or through complex interactions between functional loci.</P>

Association Analysis between Genes’ Variants for Regulating Mitochondrial Dynamics and Fasting Blood Glucose Level

Dongju Jung,Hyun-Seok Jin 대한의생명과학회 2016 Biomedical Science Letters Vol.22 No.3

Maintenance of fasting blood glucose levels is important for glucose homeostasis. Disruption of feedback mechanisms are a major reason for elevations of glucose level in blood, which is a risk factor for type 2 diabetes mellitus that is mainly caused by malfunction of pancreatic beta-cell and insulin. The fasting blood glucose level has been known to be influenced by genetic and environmental factors. Mitochondria have many functions for cell survival and death: glucose metabolism, fatty acid oxidation, ATP generation, reactive oxygen species (ROS) metabolism, calcium handling, and apoptosis regulation. In addition to these functions, mitochondria change their morphology dynamically in response to multiple signals resulting in fusion and fission. In this study, we aimed to examine association between fasting blood glucose levels and variants of the genes that are reported to have functions in mitochondrial dynamics, fusion and fission, using a cohort study. A total 416 SNPs from 36 mitochondrial dynamics genes were selected to analyze the quantitative association with fasting glucose level. Among the 416 SNPs, 4 SNPs of PRKACB, 13 SNPs of PPP3CA, 6 SNPs of PARK2, and 3 SNPs of GDAP1 were significantly associated. In this study, we were able to confirm an association of mitochondrial dynamics genes with glucose levels. To our knowledge our study is the first to identify specific SNPs related to fasting blood glucose level.

복합성 질환에서 질병관련 유전자 연구 방법

이영호 ( Young Ho Lee ),지종대 ( Jong Dae Ji ),송관규 ( Gwan Gyu Song ) 대한류마티스학회 2006 대한류마티스학회지 Vol.13 No.4

Most common diseases are complex genetic traits. Identifying the genes that underlie the variation in the diseases has been challenging. Two major approaches have been used to map genetic variants that influence disease risk: linkage analysis and association study. Linkage analysis tests for the co-segregation of a marker and disease phenotype within a pedigree, whereas association study tests for differences in marker allele frequencies between patients and a control population. Linkage analysis is applied without any prior knowledge of the biological basis of the disease. In association study, genes with a known function with the potential to influence the disease phenotype are investigated for a direct role in disease. No single method is sufficient. A multi-strategy approach to the mapping of complex diseases is required. We review the different types of genetic studies to find genes for complex genetic traits.

Associations of Ubiquitin-Specific Protease Genes with Resilience and Social Anxiety in Healthy Youths

서준호,박천일,김세주,강지인 대한불안의학회 2019 대한불안의학회지 Vol.15 No.2

Objective : Dynamic proteolysis, through the ubiquitin-proteasome system, is an important molecular mechanism for the constant regulation of synaptic plasticity and stress responses in humans. In this study, we examined whether genetic variants in the ubiquitin-specific peptidase (USP) genes were associated with psychological traits of resilience and susceptibility to neuropsychiatric disorders for each gender. Methods : A total of 344 Korean healthy youths (190 males, 154 females) were included in the study. A genotyping of rs2241646 of USP2 and rs346006 of USP46 was performed. The Connor–Davidson Resilience Scale and Brief Fear of Negative Evaluation Scale were administered for measuring trait resilience and social anxiety, respectively. The genetic associations of the USP variants were tested using multiple analyses of covariance with psychological traits as dependent variables after controlling for age in each gender. Results : For USP2 rs2241646, women with the TT genotype showed significantly higher resilience and lower social anxiety, as compared to those carrying the C allele. There were no associations between USP46 rs346005 and the psychological traits in both genders. Conclusions : The present study showed a possible genetic association between the USP2 rs2241646 and stress resilience and trait anxiety in women. The findings suggest that ubiquitin-proteasome system may be related to the resilience and susceptibility to stress-related neuropsychiatric disorders such as anxiety disorders, possibly through the regulation of dynamic proteolysis responses to stress. (Anxiety and Mood 2019;15(2):122-126)