• 응용통계연구
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• 제29권6호
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• pp.1117-1128
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• 2016

고차원 유전체 자료를 사용하는 유전체 연관 분석에서는 벌점 우도함수 기반의 회귀계수 규제화 방법이 질병 및 표현형질에 영향을 주는 유전자를 발견하는데 많이 이용된다. 특히, 네트워크 기반의 규제화 방법은 유전체 연관성 연구에서의 유전체 경로나 신호 전달 경로와 같은 생물학적 네트워크 정보를 사용할 수 있으므로, Lasso나 Elastic-net과 같은 다른 규제화 방법들과 비교했을 경우 네트워크 기반의 규제화 방법이 보다 더 정확하게 관련 유전자들을 찾아낼 수 있다는 장점을 가지고 있다. 그러나 네트워크 기반의 규제화 방법은 그룹 구조를 갖고 있는 고차원 유전체 자료에는 적용시킬 수 없다는 문제점을 가지고 있다. 실제 SNP 데이터와 DNA 메틸화 데이터처럼 대다수의 고차원 유전체 자료는 그룹 구조를 가지고 있으므로 본 논문에서는 이러한 그룹 구조를 가지고 있는 고차원 유전체 자료를 분석하고자 네트워크 기반의 규제화 방법에 주성분 분석(principal component analysis; PCA)과 부분 최소 자승법(partial least square; PLS)과 같은 차원 축소 방법을 결합시키는 새로운 분석 방법을 제안하고자 한다. 새롭게 제안한 분석 방법은 몇 가지의 모의실험을 통해 변수 선택의 우수성을 입증하였으며, 또한 152명의 정상인들과 123명의 난소암 환자들로 구성된 고차원 DNA 메틸화 자료 분석에도 사용하였다. DNA 메틸화 자료는 대략 20,000여개의 CpG sites가 12,770개의 유전자에 포함되어 있는 그룹 구조를 가지고 있으며 Illumina Innium uman Methylation27 BeadChip으로부터 생성되었다. 분석 결과 우리는 실제로 암에 연관된 몇 가지의 유전자를 발견할 수 있었다.

• 한국수산과학회지
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• 제56권4호
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• pp.411-418
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• 2023

Genome wide association studies (GWAS) identify genetic loci associated with quantitative traits in genomic selection. Although several studies have compared performance of various algorithms, no study compares them in olive flounder Paralichthys olivaceus. This study compared the GWAS results of four mixed linear model (MLM) algorithms and one Fixed and random model Circulating Probability Unification (FarmCPU) algorithm in olive flounder. Considering gender and genetic association matrices as fixed and random effects, the MLM had stable performance without inflation for λ_GC (genomic inflation factor) of -log₁₀P. The FarmCPU algorithm had some appropriate λ_GC of -log₁₀P, and an upward tail was identified in quantile-quantile plots. Therefore, the models were suitable for detecting genetic variants associated with olive flounder growth traits. Moreover, significant genotypes appeared several times at chromosome 22, around which quantitative trait loci are expected to exist. Finally, in both models, some of the most genetic variants were found in genes related to growth traits, confirming their reliability. These results will be helpful when applied to the genomic selection of olive flounder growth traits in the future.

• Genomics & Informatics
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• 제12권4호
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• pp.216-224
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• 2014

Gastritis is a common but a serious disease with a potential risk of developing carcinoma. Helicobacter pylori infection is reported as the most common cause of gastritis, but other genetic and genomic factors exist, especially single-nucleotide polymorphisms (SNPs). Association studies between SNPs and gastritis disease are important, but results on epistatic interactions from multiple SNPs are rarely found in previous genome-wide association (GWA) studies. In this study, we performed computational GWA case-control studies for gastritis in Korea Associated Resource (KARE) data. By transforming the resulting SNP epistasis network into a gene-gene epistasis network, we also identified potential gene-gene interaction factors that affect the susceptibility to gastritis.

• Asian Pacific Journal of Cancer Prevention
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• 제15권12호
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• pp.4977-4982
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• 2014

Background: Cytochrome P450 2E1 (CYP2E1) might be involved in the development of bladder cancer. However, previous studies of any association between CYP2E1 RsaI/PstI polymorphism and bladder cancer risk have yielded conflicting results. In this study, we performed a more precise estimation of the relationship by a meta-analysis based on the currently available evidence from the literature. Method: To assess the effect of CYP2E1 RsaI/PstI polymorphism on bladder cancer susceptibility, a meta-analysis of 6 available studies with 1,510 cases and 1,560 controls were performed through Feb 2014. Summary odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were used to estimate the strength of association for CYP2E1 RsaI/PstI polymorphism under different genetic models. Results: When available studies were pooled into the meta-analysis, we found that the C1C2 and C2C2 genotypes of CYP2E1 RsaI/PstI polymorphism significantly decreased bladder cancer risk under different genetic models (heterozygote: OR=0.766, 95%CI=0.613-0.957, $P_{OR}$=0.019; homozygote: OR=0.51, 95%CI=0.303-0.858, $P_{OR}$=0.011; dominant: OR=0.733, 95%CI=0.593-0.905, $P_{OR}$=0.004; recessive: OR=0.565, 95%CI=0.337-0.947, $P_{OR}$=0.030). Subgroup analysis indicated that C2C2 genotype was significantly associated with decreased bladder cancer risk under the homozygote genetic model in Caucasians. There was no evidence of heterogeneity or publication bias. Conclusions: The current meta-analysis suggested that the CYP2E1 RsaI/PstI polymorphism might be associated with bladder cancer susceptibility, especially in Caucasians. Further studies are needed to validate the above conclusion.

• Asian-Australasian Journal of Animal Sciences
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• 제22권12호
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• pp.1718-1734
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• 2009

The aim of this review is to address some characteristics that influence meat quality. Genetic groups, nutrition, finishing systems and gender are the major factors that change carcass characteristics, chemical composition and fatty acid profile. Genetic groups that have zebu genes in their composition show higher hot carcass dressing than genetic groups without zebu genes. Genetic groups that have European breeds in their composition have higher marbling scores. On the other hand, genetic groups that have zebu breeds show low marbling scores. Bulls finished in feedlots present higher final weight than steers, cull cows and heifers. Fat thickness is one of the principal parameters that are affected by different gender. Cull cows (4.72 mm) and heifers (4.00 mm) present higher values than bulls (1.75 mm) and steers (2.81 mm). The major effects observed by different systems of termination are fat thickness and marbling. Crude protein presents variation due to nutrition. Nutrition influences variation of fatty acid profile. Genetic groups also influence fatty acid profile. Genetic groups that have zebu genes in their composition show high percentage of PUFA. The major class of fatty acids that is changed with nutrition is PUFA. The better ratios of PUFA/SFA and n-6/n-3 are found in Longissimus muscle of animals finished in pasture systems.

• Asian Pacific Journal of Cancer Prevention
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• 제15권15호
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• pp.6131-6136
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• 2014

Objective: Epidemiology studies have reported conflicting results between glutathione S-transferase Mu-1 (GSTM1), glutathione S-transferase theta-1 (GSTT1) and glutathione S-transferase pi-1 (GSTP1) and ovarian cancer (OC) susceptibility. In this study, an updated meta-analysis was applied to determine whether the deletion of GSTM1, GSTT1 and GSTP1 has an influence on OC susceptibility. Methods: A published literature search was performed through PubMed, Embase, Cochrane Library, and Science Citation Index Expanded database for articles published in English. Pooled odds ratios (ORs) and 95% confidence intervals (95%CIs) were calculated using random or fixed effects models. Heterogeneity between studies was assessed using the Cochrane Q test and $I^2$ statistics. Sub-group analysis was conducted to explore the sources of heterogeneity. Sensitivity analysis was employed to evaluate the respective influence of each study on the overall estimate. Results: In total, 10 published studies were included in the final analysis. The combined analysis revealed that there was no significant association between GSTM1 null genotype and OC risk (OR=1.01, 95%CI: 0.91-1.12). Additionally, there was no significant association between GSTT1 genetic polymorphisms and OC risk (OR=0.98, 95% CI: 0.85-1.13). Similalry, no significant associations were found concerning the GSTP1 rs1695 locus and OC risk. Meanwhile, subgroup analysis did not show a significant increase in eligible studies with low heterogeneity. However, sensitivity analysis, publication bias and cumulative analysis demonstrated the reliability and stability of the current meta-analysis. Conclusions: These findings suggest that GSTs genetic polymorphisms may not contribute to OC susceptibility. Large epidemiological studies with the combination of GSTM1 null, GSTT1 null and GSTP1 Ile105Val polymorphisms and more specific histological subtypes of OC are needed to prove our findings.

• 응용통계연구
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• 제21권6호
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• pp.933-945
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• 2008

발병연령과 이에 관련되었다고 의심되는 좌위와의 연관성이 실제로 존재하는 경우에 유전자형 정보에 따라 발병연령(age of onset) 분포의 추세가 뚜렷하게 나타난다. 그러나 연관성 검정에서 주로 채택하고 있는 발병연령의 상한연령(cutoff age)을 제한하는 표본추출은 유전자형에 따른 여러 군의 미완결 자료의 분포가 다름을 초래하게 되며, 이러한 미완결 분포 차이는 발병연령의 추세 검정에 있어 효율성을 낮추는 원인이 된다. 일반적으로 두 군의 경우에 그 대책으로써 윌콕슨(Wilcoxon) 통계량보다는 미완결 자료의 분포가 다름에 영향을 덜 받는다고 알려진 로그순위(log-rank) 통계량을 사용한다. 본 논문에서는 로그순위 통계량 적용을 유전자형에 따른 여러 군의 경우로 확장하여 Jones와 Browley (1989)에 언급된 일반화 로그순위 추세 검정통계량(generalized log-rank statistic for trend)을 제안하며, 연관성 연구에서 이 검정통계량과 여러 다른 추세 검정통계량의 효율성을 모의실험으로 알아본다.

• 생명과학회지
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• 제26권7호
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• pp.855-867
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• 2016

말은 인류에 의해 상대적으로 일찍 가축화된 종 중 하나로써, 경주능력, 강건성 및 항병성 등과 같은 능력을 위해 인공적으로 선택되었다. 그 결과, 현재 경주마로 많이 쓰이고 있는 서러브레드의 게놈은 운동 능력에 특화된 유전자형을 많이 갖고 있다. 최근 NGS 기술의 도래와 함께 전장게놈을 대상으로 경주마의 우수한 유전형질을 찾는 연구가 유전체학의 관점에서 진행되고 있다. 그 결과 말의 게놈에 대해서도 GWAS (Genome-wide Association study)가 적용되고 있고, 우수 경주능력을 나타내는 유전자 마커가 발굴되고 있다. 아울러, 특정 샘플의 전장 전사체를 NGS 기법으로 분석할 수 있는 RNA-Seq 기법 역시 활용되고 있는데, 이를 통하여 각 개체별, 운동 전후, 한 개체의 조직별 특정 유전자의 발현 양상과 함께 전사체의 서열 등을 확인할 수 있다. DNA 서열의 변화 없이 유전자 발현을 조절하는 강력한 인자로써 DNA methylation이 주목받고 있다. 말의 게놈에 있어서도 운동 특이적 또는 개체 특이적 DNA methylation 패턴을 보여 주었고, 이는 우수 개체 선정을 위한 마커 개발에 좋은 단서를 제공해 줄 것이다. 유전자 발현을 억제하는 miRNA와, 포유동물의 유전체 내 절반 정도를 차지하고 있는 이동성 유전인자는 기능유전체 연구에 있어서 중요한 인자들이다. 이들은 인간의 게놈에서 많이 연구가 되어 왔으나, 말에서의 연구는 현재 미미한 실정이다. 하지만, 현재까지 말에서 되어 있는 위의 두 인자에 대한 연구 현황을 알아보고, 차후 우수 마 선별 연구에 적용될 가능성을 제시하였다. 기능유전체 및 후성유전체 분석 기법이 발전함에 따라 말에서도 본 연구에서 소개된 여러 가지 분석 기법이 적용되고, 우수한 경주마를 선정하는 데 많은 도움을 줄 것으로 기대하고 있다. 이에 현재까지의 우수한 경주마를 선택하기 위한 많은 연구들 및, 말 연구에 대한 앞으로의 발전 가능성에 대해 고찰하고 토의하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권15호
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• pp.6211-6217
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• 2014

Previous genome-wide association studies (GWAS) have implicated several single nucleotide polymorphisms (SNPs) in the AT-rich interactive domain 5B (ARID5B) gene with childhood acute lymphoblastic leukemia (ALL). However, replicated studies reported some inconsistent results in different populations. Using meta-analysis, we here aimed to clarify the nature of the genetic risks contributed by the two polymorphisms (rs10994982, rs7089424) for developing childhood ALL. Through searches of PubMed, EMBASE, and manually searching relevant references, a total of 14 articles with 16 independent studies were included. Odds ratios (ORs) with 95% confidence intervals (95%CI) were calculated to assess the associations. Both SNPs rs10994982 and rs7089424 showed significant associations with childhood ALL risk in all genetic models after Bonferroni correction. Furthermore, subtype analyses of B-lineage ALL provided strong evidence that SNP rs10994982 is highly associated with the risk of developing B-hyperdiploid ALL. These results indicate that SNPs rs10994982 and rs7089424 are indeed significantly associated with increased risk of childhood ALL.

• Tuberculosis and Respiratory Diseases
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• 제76권3호
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• pp.105-113
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• 2014

From January 2012 up until March 2013, many articles with huge clinical importance in asthma were published based on large numbered clinical trials or meta-analysis. The main subjects of these studies were the new therapeutic plan based on the asthma phenotype or efficacy along with the safety issues regarding the current treatment guidelines. For efficacy and safety issues, inhaled corticosteroid tapering strategy or continued long-acting beta agonists use was the major concern. As new therapeutic trials, monoclonal antibodies or macrolide antibiotics based on inflammatory phenotypes have been under investigation, with promising preliminary results. There were other issues on the disease susceptibility or genetic background of asthma, particularly for the "severe asthma" phenotype. In the era of genome and pharmacogenetics, there have been extensive studies to identify susceptible candidate genes based on the results of genome wide association studies (GWAS). However, for severe asthma, which is where most of the mortality or medical costs develop, it is very unclear. Moreover, there have been some efforts to find important genetic information in order to predict the possible disease progression, but with few significant results up until now. In conclusion, there are new on-going aspects in the phenotypic classification of asthma and therapeutic strategy according to the phenotypic variations. With more pharmacogenomic information and clear identification of the "severe asthma" group even before disease progression from GWAS data, more adequate and individualized therapeutic strategy could be realized in the future.