• Genomics & Informatics
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• v.8 no.3
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• pp.142-149
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• 2010

In recent years, genome-wide association (GWA) studies have successfully led to many discoveries of genetic variants affecting common complex traits, including height, blood pressure, and diabetes. Although GWA studies have made much progress in finding single nucleotide polymorphisms (SNPs) associated with many complex traits, such SNPs have been shown to explain only a very small proportion of the underlying genetic variance of complex traits. This is partly due to that fact that most current GWA studies have relied on single-marker approaches that identify single genetic factors individually and have limitations in considering the joint effects of multiple genetic factors on complex traits. Joint identification of multiple genetic factors would be more powerful and provide a better prediction of complex traits, since it utilizes combined information across variants. Recently, a new statistical method for joint identification of genetic variants for common complex traits via the elastic-net regularization method was proposed. In this study, we applied this joint identification approach to a large-scale GWA dataset (i.e., 8842 samples and 327,872 SNPs) in order to identify genetic variants of obesity for the Korean population. In addition, in order to test for the biological significance of the jointly identified SNPs, gene ontology and pathway enrichment analyses were further conducted.

• Clinical and Experimental Reproductive Medicine
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• v.51 no.2
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• pp.91-101
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• 2024

Infertility is a complex disease characterized by extreme genetic heterogeneity, compounded by various environmental factors. While there are exceptions, individual genetic and genomic variations related to infertility are typically rare, often family-specific, and may serve as susceptibility factors rather than direct causes of the disease. Consequently, identifying the cause of infertility and developing prevention and treatment strategies based on these factors remain challenging tasks, even in the modern genomic era. In this review, we first examine the genetic and genomic variations associated with infertility, and subsequently summarize the concepts and methods of preimplantation genetic testing in light of advances in genome analysis technology.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.21 no.3
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• pp.133-140
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• 2010

Tic disorders, including Tourette syndrome, are known as neurobiologic disorders and as such, much emphasis has been placed on isolating genetic determinants. Although previous reports involving studies of discordance among monozygotic twins have shown the importance of genetic predisposition, they have also supported a role for environmental factors in the development of tic disorders. Therefore, it is important to consider that both genetic and environmental factors contribute to their clinical expression. The goal of this article was to review recent reports regarding the role of environmental factors in development and progression of tics. Specific environmental factors associated either with a more severe course of illness or improved outcomes were discussed. Given that accumulating evidence had suggested the usefulness of behavior therapies in the suppression of tic disorders, particular emphasis was placed on the impact of several contextual factors.

• Genomics & Informatics
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• v.10 no.4
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• pp.239-243
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• 2012

Gestational diabetes mellitus (GDM) is a complex metabolic disorder of pregnancy that is suspected to have a strong genetic predisposition. It is associated with poor perinatal outcome, and both GDM women and their offspring are at increased risk of future development of type 2 diabetes mellitus (T2DM). During the past several years, there has been progress in finding the genetic risk factors of GDM in relation to T2DM. Some of the genetic variants that were proven to be significantly associated with T2DM are also genetic risk factors of GDM. Recently, a genome-wide association study of GDM was performed and reported that genetic variants in CDKAL1 and MTNR1B were associated with GDM at a genome-wide significance level. Current investigations using next-generation sequencing will improve our insight into the pathophysiology of GDM. It would be important to know whether genetic information revealed from these studies could improve our prediction of GDM and the future development of T2DM. We hope further research on the genetics of GDM would ultimately lead us to personalized genomic medicine and improved patient care.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6005-6010
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• 2012

Background: Nasopharyngeal carcinoma (NPC) is endemic in Southern Chinese and Southeast Asian populations. Geographical and ethnic clustering of the cancer is due to genetic, environmental, and lifestyle risk factors. This case-control study aimed to identify or confirm both genetic and non-genetic risk factors for NPC in one of the endemic countries, Malaysia. Materials and Methods: A panel of 768 single-nucleotide polymorphisms (SNPs) previously associated with various cancers and known non-genetic risk factors for NPC were selected and analyzed for their associations with NPC in a case-control study. Results: Statistical analysis identified 40 SNPs associated with NPC risk in our population, including 5 documented previously by genome-wide association studies (GWAS) and other case-control studies; the associations of the remaining 35 SNPs with NPC were novel. In addition, consistent with previous studies, exposure to occupational hazards, overconsumption of salt-cured foods, red meat, as well as low intake of fruits and vegetables were also associated with NPC risk. Conclusions: In short, this study confirmed and/or identified genetic, environmental and dietary risk factors associated with NPC susceptibility in a Southeast Asian population.

• Journal of Korean Biological Nursing Science
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• v.25 no.1
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• pp.73-85
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• 2023

Purpose: This study focused on identifying the interaction effects of genetic and lifestyle-environmental factors on the development of type 2 diabetes mellitus (T2D). Methods: Study subjects were selected from the Korean Genome and Epidemiology Study (KoGES) from 2001 to 2014. Data on genetic variations, anthropometric measurements, biochemical data, and seven lifestyle factors (diet, physical activity, alcohol drinking, smoking, sleep, depression, and stress) were obtained from 4,836 Koreans aged between 40 and 59 years, including those with T2D at baseline (n = 1,209), newly developed T2D (n= 1,298) and verified controls (n = 3,538). The genetic risk score (GRS) was calculated by using 11 single-nucleotide polymorphisms (SNPs) related to T2D development and the second quartile was used as the reference category. A Cox proportional hazards regression model was used to evaluate the associations of GRS and lifestyle factors with T2D risk, controlling for covariates. Results: Multivariate regression analysis revealed that GRS was the strongest risk factor for T2D, and body mass index (BMI), smoking, drinking, and spicy food preference also increased the risk. Lifestyle/environmental factors that showed significant interactions with GRS were BMI, current smoking, current drinking, fatty food preference, and spicy food preference. Conclusions: Interactions between genetic factors and lifestyle/environmental factors were associated with an increased risk of T2D. The results will be useful to provide a new perspective on genetic profiling for the earlier detection of T2D risk and clues for personalized interventions, which might be more effective prevention strategies or therapies in individuals with a genetic predisposition to T2D.

• Journal of Preventive Medicine and Public Health
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• v.45 no.1
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• pp.29-36
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• 2012

Objectives: The purpose of this study was to identify any influence of socioeconomic status on smoking and smoking cessation in a situation where genetic factors are controlled. Methods: The sample for this study was 2502 members of the twins and families cohort who participated in the Korean Healthy Twins Study from 2005 to 2009. Groups of brothers or sisters, including twins and fraternal twins, were compared in terms of smoking and smoking cessation behaviors according to differences in socioeconomic status and gender. Results: In a situation with complete control of genetic factors, results showed that the daily smoking amount, cumulative smoking amount, and dependence on nicotine decreased with higher-status occupations, and the rate of smoking and amount of cumulative smoking decreased with higher levels of education. Regarding smoking cessation behavior, a higher level of education was associated with a lower smoking cessation rate, and no significant gender differences were found. Conclusions: Environmental factors had a stronger influence on smoking behavior than did genetic factors. Genetic factors had greater influence on smoking cessation than did environmental factors; however, this requires verification in further studies.

• BMB Reports
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• v.52 no.4
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• pp.250-258
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• 2019

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by selective and progressive loss of dopaminergic neurons. Genetic and environmental risk factors are associated with this disease. The genetic factors are composed of approximately 20 genes, such as SNCA, parkin, PTEN-induced kinase1 (pink1), leucine-rich repeat kinase 2 (LRRK2), ATP13A2, MAPT, VPS35, and DJ-1, whereas the environmental factors consist of oxidative stress-induced toxins such as 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP), rotenone, and paraquat. The analyses of their functions and mechanisms have provided important insights into the disease process, which has demonstrated that these factors cause oxidative damage and mitochondrial dysfunction. The most invaluable studies have been performed using disease model organisms, such as mice, fruit flies, and worms. Among them, Drosophila melanogaster has emerged as an excellent model organism to study both environmental and genetic factors and provide insights to the pathways relevant for PD pathogenesis, facilitating development of therapeutic strategies. In this review, we have focused on the fly model organism to summarize recent progress, including pathogenesis, neuroprotective compounds, and newer approaches.

• BioChip Journal
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• v.12 no.4
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• pp.304-308
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• 2018

Atopic disease is caused by a complex combination of environmental factors and genetic factors, and studies on influence of exposure to various environmental factors on atopic diseases are continuously reported. However, the exact cause of atopic dermatitis is not yet known. Our study was conducted to analyse the association of SNPs with the development of atopic disease in a small cohort. Samples were collected from the Mothers' and Children's Environmental Health (MOCEH) study and 192 cord blood DNA samples were used to identify incidence of atopy due to influence of exposure to environmental factors. Genetic elements were analysed using a precision medicine research (PMR) array designed with various SNPs for personalized medicine. Case-control analysis of atopy disease revealed 253 significant variants (p<0.0001) and SNPs on five genes (CARD11, ZNF365, KIF3A, DMRTA1, and SFMBT1) were variants identified in previous atopic studies. These results are important to confirm the genetic mutation that may lead to the onset of foetal atopy due to maternal exposure to harmful environmental factors. Our results also suggest that a small-scale genome-wide association analysis is beneficial to confirm specific variants as direct factors in the development of atopy.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.