• 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.

• Biotechnology and Bioprocess Engineering:BBE
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• v.6 no.4
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• pp.231-236
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• 2001

How much do we know about the biology of aging from cell culture studies Most normal somatic cells have a finite potential to divide due to a process termed cellular or replicative senescence. A growing body evidence suggests that senescence evolved to protect higher eu-karyotes, particularly mammals, from developing cancer, We now know that telomere shortening due to the biochemistry of DNA replication, induces replicative senescence in human cells. How-ever in rodent cells, replicative senescence occurs despite very long telomeres. Recent findings suggest that replicative senescence is just the tip of the iceberg of a more general process termed cellular senescence. It appears that cellular senescence is a response to potentially oncogenic in-sults, including oxidative damage. In young orgainsms, growth arrest by cell senescence sup-presses tumor development, but later in life, due to the accumulation of senescent cells which se-cret factors that can disrupt tissues during aging, cellular senescence promotes tumorigenesis. Therefore, antagonistic pleiotropy may explain, if not in whole the apparently paradoxical effects of cellular senescence, though this still remains an open question.

• Molecules and Cells
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• v.19 no.3
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• pp.303-309
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• 2005

The end of eukaryotic genomic DNA is capped by a specialized structure called as "telomere" which consists of the repetitive array of nucleotide sequence, TTAGGG, in humans and mice, and a variety of binding proteins. Telomerase is a ribonucleoprotein (RNP) complex responsible for the elongation of telomeres to maintain the genomic integrity, and is composed of telomerase reverse transcriptase (TERT), telomerase RNA component (TERC), and their associated factors regulating the catalytic activity of telomerase. Although it is now apparent that telomerase protects cells from apoptosis via the maintenance of genomic integrity by stabilizing telomeres, our understanding for the physiological role of telomerase is yet far from completion, and emerging evidence suggests that telomerase has additional extratelomeric roles in mediating cell survival and anti-apoptotic functions against various cytotoxic stresses. Here we summarize and discuss how telomerase and telomeres are involved in mediating cellular protection against apoptosis.

• Animal cells and systems
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• v.2 no.2
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• pp.153-164
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• 1998

Cytokines regulate proliferation, differentiation and functions of haemotopoietic cells. Each cytokine possesses a variety of activities on various target cells (pleiotropy) and various cytokines have similar and overlapping activities on the same target cells (redundancy). The nature of these cytokine activities predicts unique feature of cytokine receptors, namely, cytokine has multiple receptors, different cytokines share a common receptor, and different cytokine receptors are linked to common signaling pathways. cDNA cloning of genes for cytokine receptors revealed distinct sets of receptor family with different structural features. The cytokine receptor superfamily consists of a largest family, and contains more than twenty cytokine receptor subunits. This receptor has common structural features in both extracellular and intracellular regions without tyrosine kinase domain. Another striking feature of the receptor is to share common subunit of multiple cytokines, which partly explains the redundancy of activities of some cytokines. Recent studies revealed detailed signaling events of the cytokine receptor, the primary activation of JAK and subsequent phosphorylation of tyrosine residues of receptor, and various cellular proteins. Many SH2 containing adapter proteins play an important role in cytokine signals, and this system has similarities with tyrosine kinase receptor signal transduction. STAT may mainly account for cytokine specific functions as suggested by knockout mice studies. It is of importance to note that cytokine activates multiple signaling pathways and the balance and combination of related signaling events may determine the specificity of functions of cytokines.

• Childhood Kidney Diseases
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• v.28 no.1
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• pp.8-15
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• 2024

With the rapid evolution of diagnostic tools, particularly next-generation sequencing, the identification of genetic diseases, predominantly those with pediatric-onset, has significantly advanced. However, this progress presents challenges that span from selecting appropriate tests to the final interpretation of results. This review examines various genetic testing methodologies, each with specific indications and characteristics, emphasizing the importance of selecting the appropriate genetic test in clinical practice, taking into account factors like detection range, cost, turnaround time, and specificity of the clinical diagnosis. Interpretation of variants has become more challenging, often requiring further validation and significant resource allocation. Laboratories primarily classify variants based on the American College of Medical Genetics and Genomics and the Association for Clinical Genomic Science guidelines, however, this process has limitations. This review underscores the critical role of clinicians in matching patient phenotypes with reported genes/variants and considering additional factors such as variable expressivity, disease pleiotropy, and incomplete penetrance. These considerations should be aligned with specific gene-disease characteristics and segregation results based on an extended pedigree. In conclusion, this review aims to enhance understanding of the complexities of clinical genetic testing, advocating for a multidisciplinary approach to ensure accurate diagnosis and effective management of rare genetic diseases.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.1 no.1
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• pp.42-45
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• 1963

In a plant breeding program, an efficient selection of desired characters in a population is important. Generally, many agronomic characters in a given population are determined by polygenes and quantitatively inherited. In practice, the genetic relationship between two observed characters which are undoubtedly subjected to the environmental influence is difficult to identify. In recent years, many workers have attempted to understant the genetic relationship between characters in terms of genotypic correlation, and the knowledge thus gained should furnish many important and useful information for the planning of breeding, selection, and interpretation of the result. The genotypic correlation is the result of pleiotropy, linkage of genes(2, 3, 5, 6, 8) and natural or artificial selection(4). The purposes of this study were to estimate genotyric and phenotypic correlations between all possible pairs of nine characters. and to seek certain characters which may be useful as indicators of certain important agronomic characters. Weber and Moorthy(10), Johnson et al. (5) and Sheth(7) found that in general, the genotypic correlations were higher than the phenotypic correlations. Weiss et al. (11) obtained significant positive correlations between maturity and oil content, maturity and low protein content, and high protein content and low oil content. Weber and Moorthy(10) reported the positive genotypic correlations between flowering and maturity, yield and maturity, yield and plant height, yield and seed weight, and negative genotypic correlations between maturity and oil content, and oil content and seed weight. Johnson et al. (5) studied the genotypic and phenotypic correlations among 24 characters and concluded that selection based entirely on a long fruiting period, lateness, heavy seed, low protein, high oil and resistance to lodging would be effective in increasing yield. Sheth(7) found the following positive associations among characters; height and maturity, yield and lodging, low protein content and high oil content, and yield and low protein content. Hanson et al.(1) also reported high negative correlation between seed yield and protein content.

• Nutrition Research and Practice
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• v.17 no.4
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• pp.789-802
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• 2023

BACKGROUND/OBJECTIVES: Habitual coffee consumption was inversely associated with type 2 diabetes (T2D) and hyperglycemia in observational studies, but the causality of the association remains uncertain. This study tested a causal association of genetically predicted coffee consumption with T2D using the Mendelian randomization (MR) method. SUBJECTS/METHODS: We used five single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with habitual coffee consumption in a previous genome-wide association study among Koreans. We analyzed the associations between IVs and T2D, fasting blood glucose (FBG), 2h-postprandial glucose (2h-PG), and glycated haemoglobin (HbA1C) levels. The MR results were further evaluated by standard sensitivity tests for possible pleiotropism. RESULTS: MR analysis revealed that increased genetically predicted coffee consumption was associated with a reduced prevalence of T2D; ORs per one-unit increment of log-transformed cup per day of coffee consumption ranged from 0.75 (0.62-0.90) for the weighted mode-based method to 0.79 (0.62-0.99) for Wald ratio estimator. We also used the inverse-variance-weighted method, weighted median-based method, MR-Egger method, and MR-PRESSO method. Similarly, genetically predicted coffee consumption was inversely associated with FBG and 2h-PG levels but not with HbA1c. Sensitivity measures gave similar results without evidence of pleiotropy. CONCLUSIONS: A genetic predisposition to habitual coffee consumption was inversely associated with T2D prevalence and lower levels of FBG and 2h-PG profiles. Our study warrants further exploration.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.123-127
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• 2014

A recent study summarized several published genome-wide association studies (GWASs) of cancer and reported two pleiotropic loci at 6p21.1 and 7p15.3 contributing to multiple cancers including lung cancer, noncardia gastric cancer (NCGC), and esophageal squamous-cell carcinoma (ESCC) in Han Chinese. However, it is not known whether such genetic variants have similar effects on the risk of gynecologic cancers, such as ovarian cancer. Hence, we explored associations between genetic variants in 6p21.1 and 7p15.3 and ovarian cancer risk in Han Chinese women. We performed an independent case-control study by genotyping the two loci (rs2494938 A > G at 6p21.1 and rs2285947 A > G at 7p15.3) in a total of 377 ovarian cancer cases and 1,034 cancer-free controls using TaqMan allelic discrimination assay. We found that rs2285947 at 7p15.3 was significantly associated with risk of ovarian cancer with per allele odds ratio (OR) of 1.33 [95% confidence interval (CI): 1.08-1.64, P=0.008]. However, no significant association was observed between rs2494938 and ovarian cancer risk. Our results showed that rs2285947 at 7p15.3 may also contribute to the development of ovarian cancer in Han Chinese women, further suggesting pleiotropy of 7p15.3 in multiple cancers.