• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.114-121
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• 2007

Power and sample size estimation is one of the crucially important steps in planning a genetic association study to achieve the ultimate goal, identifying candidate genes for disease susceptibility, by designing the study in such a way as to maximize the success possibility and minimize the cost. Here we review the optimal two-stage genotyping designs for genomewide association studies recently investigated by Wang et al(2006). We review two mathematical frameworks most commonly used to compute power in genetic association studies prior to the main study: Monte-Carlo and non-central chi-square estimates. Statistical powers are computed by these two approaches for case-control genotypic tests under one-stage direct association study design. Then we discuss how the linkage-disequilibrium strength affects power and sample size, and how to use empirically-derived distributions of important parameters for power calculations. We provide useful information on publicly available softwares developed to compute power and sample size for various study designs.

• Korean Journal of Biological Psychiatry
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• v.18 no.4
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• pp.176-180
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• 2011

Depressive disorders have strong genetic components. However, conventional linkage and association studies have not yielded definitive results. These might be due to the absence of objective diagnostic tests, the complex nature of human behavior or the incomplete penetrance of psychiatric traits. Imaging genetics explores the influences of genetic variation on the brain function or structure. This technique could provide a more sensitive assessment than traditional behavioral measures in psychiatric studies. Imaging genetics is a relatively new field of psychiatric researches, and may improve our understanding on neurobiology of psychiatric disorders. In this review, current understanding in neurobiology of depressive disorders, especially imaging genetic studies on serotonin transporter will be discussed.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9347-9353
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• 2014

Background: Excision repair crossing-complementing group 2 (ERCC2), also called xeroderma pigmentosum complementary group D (XPD), plays a crucial role in the nucleotide excision repair (NER) pathway. Previous epidemiological studies have reported associations between ERCC2 polymorphisms and non-Hodgkin lymphoma (NHL) risk, but the results have remained controversial. Materials and Methods: We conducted this meta-analysis based on eligible case-control studies to investigate the role of two ERCC2 polymorphisms (Lys751Gln and Asp312Asn) in determining susceptibility to NHL. Ten case-control studies from several electronic databases were included in our study up to August 14, 2014. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using fixed- or random-effects models to estimate the association strength. Results: The combined results based on all studies did not show any association between Lys751Gln/Asp312Asn polymorphisms and NHL risk for all genetic models. Stratified analyses by histological subtype and ethnicity did not indicate any significant association between Lys751Gln polymorphism and NHL risk. However, a significant reduced risk of NHL was found among population-based studies (Lys/Gln versus Lys/Lys: OR=0.87, 95% CI=0.77-0.99, P=0.037) but not hospital-based studies. As for Asp312Asn polymorphism, there was no evidence for the association between this polymorphism and the risk of NHL in all subgroup analyses. Conclusions: This meta-analysis suggests that there may be no association between Lys751Gln/Asp312Asn polymorphism and the risk of NHL and its two subtypes, whereas ERCC2 Lys751Gln heterozygote genotype may provide protective effects against the risk of NHL in population-based studies. Therefore, large-scale and well-designed studies are needed to clarify the effects of haplotypes, gene-gene, and gene-environment interactions on these polymorphisms and the risk of NHL and its different histological subtypes in an ethnicity specific population.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• Genomics & Informatics
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• v.5 no.4
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• pp.152-160
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• 2007

Most common diseases are caused by multiple genetic and environmental factors. Among the genetic factors, single nucleotide polymorphisms (SNPs) are common DNA sequence variations in individuals and can serve as important genetic markers. Recently, investigations of gene-based and whole genome-based SNPs have been applied to association studies for marker discovery. However, SNPs are so population-specific that the association needs to be verified. Fifty-five genes and 384 SNPs were selected based on association with disease. Genotypes of 337 SNPs in candidate genes were determined using Illumina Sentrix Array Matrix (SAM) chips by an allele-specific extension method in 364 unrelated Korean individuals. Allelic frequencies of SNPs were compared with those of other populations obtained from the International HapMap database. Minor allele frequencies, linkage disequilibrium blocks, tagSNPs, and haplotypes of functional candidate SNPs in 55 genetic disease-associated genes were provided. Our data may provide useful information for the selection of genetic markers for gene-based genetic disease-association studies of the Korean population.

• Preventive Nutrition and Food Science
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• v.20 no.1
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• pp.1-7
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• 2015

Obesity has become one of the major public health problems all over the world. Recent novel eras of research are opening for the effective management of obesity though gene and nutrient intake interactions because the causes of obesity are complex and multifactorial. Through GWASs (genome-wide association studies) and genetic variations (SNPs, single nucleotide polymorphisms), as the genetic factors are likely to determine individuals' obesity predisposition. The understanding of genetic approaches in nutritional sciences is referred as "nutrigenomics". Nutrigenomics explores the interaction between genetic factors and dietary nutrient intake on various disease phenotypes such as obesity. Therefore, this novel approach might suggest a solution for the effective prevention and treatment of obesity through individual genetic profiles and help improve health conditions.

• Clinical and Experimental Pediatrics
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• v.53 no.3
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• pp.273-285
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• 2010

Completion of the human genome project has allowed a deeper understanding of molecular pathophysiology and has provided invaluable genomic information for the diagnosis of genetic disorders. Advent of new technologies has lead to an explosion in genetic testing. However, this overwhelming stream of genetic information often misleads physicians and patients into a misguided faith in the power of genetic testing. Moreover, genetic testing raises a number of ethical, legal, and social issues. Diagnostic genetic tests can be divided into three primary but overlapping categories: cytogenetic studies (including routine karyotyping, high-resolution karyotyping, and fluorescent in situ hybridization studies), biochemical tests, and DNA-based diagnostic tests. DNA-based testing has grown rapidly over the past decade and includes preandpostnatal testing for the diagnosis of genetic diseases, testing for carriers of genetic diseases, genetic testing for susceptibility to common non-genetic diseases, and screening for common genetic diseases in a particular population. Theoretically, once a gene's structure, function, and association with a disease are well established, the clinical application of genetic testing should be feasible. However, for routine applications in a clinical setting, such tests must satisfy a number of criteria. These criteria include an acceptable degree of clinical and analytical validity, support of a quality assurance program, possibility of modifying the course of the diagnosed disease with treatment, inclusion of pre-and postnatal genetic counseling, and determination of whether the proposed test satisfies cost-benefit criteria and should replace or complement traditional tests. In the near future, the application of genetic testing to common diseases is expected to expand and will likely be extended to include individual pharmacogenetic assessments.

• Genomics & Informatics
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• v.9 no.2
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• pp.45-51
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• 2011

How personality forms and whether personality genes exist are long-studied questions. Various concepts and theories have been presented for centuries. Personality is a complex trait and is developed through the interaction of genes and the environment. Twin and family studies have found that there are critical genetic and environmental components in the inheritance of personality traits, and modern advances in genetics are making it possible to identify specific variants for personality traits. Although genes that were found in studies on personality have not provided replicable association between genetic and personality variability, more and more genetic variants associated with personality traits are being discovered. Here, we present the current state of the art on genetic research in the personality field and finally list several of the recently published research highlights. First, we briefly describe the commonly used self-reported measures that define personality traits. Then, we summarize the characteristics of the candidate genes for personality traits and investigate gene variants that have been suggested to be associated with personality traits.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4689-4695
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• 2014

Background: A great number of studies have shown that cytochrome P450 1A1 (CYP1A1) genetic polymorphisms, CYP1A1 Msp I and CYP1A1 Ile/Val, might be risk factors for digestive tract cancers, including esophageal cancer (EC), gastric cancer (GC), hepatic carcinoma (HC), as well as colorectal cancer (CC), but the results are controversial. In this study, a meta-analysis of this literature aimed to clarify associations of CYP1A1 genetic polymorphisms with digestive tract cancers susceptibility in Chinese populations. Materials and Methods: Eligible case-control studies published until December 2013 were retrieved by systematic literature searches from PubMed, Embase, CBM, CNKI and other Chinese databases by two investigators independently. The associated literature was acquired through deliberate search and selection based on established inclusion criteria. Fixed-effects or random-effects models were used to estimate odds ratios (ORs and 95%CIs). The meta-analysis was conducted using Review Manager 5.2 and Stata 12.0 softwares with stability evaluated by both stratified and sensitivity analyses. Moreover, sensitivity analysis and publication bias diagnostics confirmed the reliability and stability. Results: Eighteen case-control studies with 1,747 cases and 2,923 controls were selected for CYP1A1 MspI polymorphisms, and twenty case-control studies with 3, 790 cases and 4, 907 controls for the CYP1A1 Ile/Val polymorphisms. Correlation associations between CYP1A1 Ile/Val polymorphisms and digestive tract cancers susceptibility were observed in four genetic models in the meta-analysis (GG vs AA:OR= 2.03, 95%CI =1.52- 2.72; AG vs AA: OR=1.26, 95%CI =1.07-1.48; [GG+AG vs AA] :OR =1.42, 95%CI=1.20-1.68, [GG vs AA+AG]:OR=1.80, 95%CI =1.40-2.31). There was no association between CYP1A1 Msp I polymorphisms and digestive tract cancers risk. Subgroup analysis for tumor type showed a significant association of CYP1A1 Ile/Val genetic polymorphisms with EC in China. However, available data collected by the study failed to reveal remarkable associations of GC or HC with CYP1A1 Ile/Val genetic polymorphisms and EC, GC or CC with CYP1A1 MspI genetic polymorphisms. Conclusions: Our results indicated that CYP1A1 Ile/Val genetic polymorphisms, but not CYP1A1 Msp I polymorphisms, are associated with an increased digestive tract cancers risk in Chinese populations. Additional well-designed studies, with larger sample size, focusing on different ethnicities and cancer types are now warranted to validate this finding.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.3
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• pp.309-319
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• 2017

Objective: Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods: This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results: We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion: This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.