In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.

The rapid increase in genetic dataset volume has demanded extensive adoption of biological knowledge to reduce the computational complexity, and the biological pathway is one well-known source of such knowledge. In this regard, we have introduced a novel statistical method that enables the pathway-based association study of large-scale genetic dataset—namely, PHARAOH. However, researcher-level application of the PHARAOH method has been limited by a lack of generally used file formats and the absence of various quality control options that are essential to practical analysis. In order to overcome these limitations, we introduce our integration of the PHARAOH method into our recently developed all-in-one workbench. The proposed new PHARAOH program not only supports various de facto standard genetic data formats but also provides many quality control measures and filters based on those measures. We expect that our updated PHARAOH provides advanced accessibility of the pathway-level analysis of large-scale genetic datasets to researchers.
Dataset ; Genetic Association Studies ; Methods ; Quality Control

Gene-gene interaction (GGI) analysis is known to play an important role in explaining missing heritability. Many previous studies have already proposed software to analyze GGI, but most methods focus on a binary phenotype in a case-control design. In this study, we developed “Hierarchical structural CoMponent analysis of Gene-Gene Interactions” (HisCoM-GGI) software for GGI analysis with a continuous phenotype. The HisCoM-GGI method considers hierarchical structural relationships between genes and single nucleotide polymorphisms (SNPs), enabling both gene-level and SNP-level interaction analysis in a single model. Furthermore, this software accepts various types of genomic data and supports data management and multithreading to improve the efficiency of genome-wide association study data analysis. We expect that HisCoM-GGI software will provide advanced accessibility to researchers in genetic interaction studies and a more effective way to understand biological mechanisms of complex diseases.
Case-Control Studies ; Genome-Wide Association Study ; Methods ; Phenotype ; Polymorphism, Single Nucleotide ; Statistics as Topic

In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Body Mass Index ; Genome-Wide Association Study ; Hypertension ; Multifactor Dimensionality Reduction ; Obesity ; Resin Cements

The term “multiple primary (MP) cancers” refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation.

The term “multiple primary (MP) cancers” refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation.

The term “multiple primary (MP) cancers” refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation.

The term “multiple primary (MP) cancers” refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation.

Computed tomographic arthrography (CTA) of four cadaveric canine stifles was performed before and after partial cranial cruciate ligament rupture in order to verify the usefulness of CTA examination for the diagnosis of partial cranial cruciate ligament rupture. To obtain the sequential true transverse image of a cranial cruciate ligament, the computed tomography gantry was angled such that the scanning plane was parallel to the fibula. True transverse images of cranial cruciate ligaments were identified on every sequential image, beginning just proximal to the origin of the cranial cruciate ligament distal to the tibial attachment, after the administration of iodinated contrast medium. A significant decrease in the area of the cranial cruciate ligament was identified on CTA imaging after partial surgical rupture of the cranial cruciate ligament. This finding implies that CTA can be used for assessing partial cranial cruciate ligament ruptures in dogs.
Animals ; Anterior Cruciate Ligament/*injuries/*radiography ; Arthrography/methods/veterinary ; Contrast Media/*pharmacology ; Dog Diseases/*radiography ; Dogs ; Hindlimb ; Predictive Value of Tests ; Stifle/radiography ; Tomography, X-Ray Computed/methods/*veterinary