764 research outputs found

    Hierarchical maximum likelihood clustering approach

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    Objective: In this work, we focused on developing a clustering approach for biological data. In many biological analyses, such as multi-omics data analysis and genome-wide association studies (GWAS) analysis, it is crucial to find groups of data belonging to subtypes of diseases or tumors. Methods: Conventionally, the k-means clustering algorithm is overwhelmingly applied in many areas including biological sciences. There are, however, several alternative clustering algorithms that can be applied, including support vector clustering. In this paper, taking into consideration the nature of biological data, we propose a maximum likelihood clustering scheme based on a hierarchical framework. Results: This method can perform clustering even when the data belonging to different groups overlap. It can also perform clustering when the number of samples is lower than the data dimensionality. Conclusion: The proposed scheme is free from selecting initial settings to begin the search process. In addition, it does not require the computation of the first and second derivative of likelihood functions, as is required by many other maximum likelihood based methods. Significance: This algorithm uses distribution and centroid information to cluster a sample and was applied to biological data. A Matlab implementation of this method can be downloaded from the web-link http://www.riken.jp/en/research/labs/ims/med_sci_math/

    Differential quantification of CYP2D6 gene copy number by four different quantitative real-time PCR assays

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    Copy number variations (CNVs) in the CYP2D6 gene contribute to interindividual variation in drug metabolism. As the most common duplicated allele in Asian populations is the nonfunctional CYP2D6*36 allele, the goal of this study was to identify CNV assays that can differentiate between multiple copies of the CYP2D6*36 allele and multiple copies of other CYP2D6 alleles. We determined CYP2D6 gene copy numbers in 32 individuals with known CYP2D6 CNVs from the Coriell Japanese-Chinese panel using four quantitative real-time PCR assays. These assays target different regions of the CYP2D6 gene: 5'-flanking region, intron 2, intron 6, and exon 9 (Ex9). The specific target site of the Ex9 assay was verified by sequencing the PCR amplicon. Three of the CYP2D6 CNV assays (5'-flanking region, intron 2, and intron 6) estimated CYP2D6 copy numbers that were concordant for all 32 individuals. However, the Ex9 assay was concordant in only 10 of 32 samples. The 10 concordant samples did not contain any CYP2D6*36 alleles and the 22 discordant samples contained at least one CYP2D6*36 allele. In addition, the Ex9 assay accurately quantified all of the non-CYP2D6*36 alleles in all samples. Ex9 amplicon sequencing indicated that it targets a region of CYP2D6 exon 9 that undergoes partial gene-conversion in the CYP2D6*36 allele. In conclusion, CYP2D6 Ex9 CNV assay can be used to determine the copy number of non-CYP2D6*36 alleles. Selective amplification of non-CYP2D6*36 sequence by the Ex9 assay should be useful in determining the number of functional copies of CYP2D6 in Asian populations

    Comprehensive Analysis of Risk Factors for Periodontitis Focusing on the Saliva Microbiome and Polymorphism

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    Few studies have exhaustively assessed relationships among polymorphisms, the microbiome, and periodontitis. The objective of the present study was to assess associations simultaneously among polymorphisms, the microbiome, and periodontitis. We used propensity score matching with a 1:1 ratio to select subjects, and then 22 individuals (mean age +/- standard deviation, 60.7 +/- 9.9 years) were analyzed. After saliva collection, V3-4 regions of the 16S rRNA gene were sequenced to investigate microbiome composition, alpha diversity (Shannon index, Simpson index, Chao1, and abundance-based coverage estimator) and beta diversity using principal coordinate analysis (PCoA) based on weighted and unweighted UniFrac distances. A total of 51 single-nucleotide polymorphisms (SNPs) related to periodontitis were identified. The frequencies of SNPs were collected from Genome-Wide Association Study data. The PCoA of unweighted UniFrac distance showed a significant difference between periodontitis and control groups (p 0.05). Two families (Lactobacillaceae and Desulfobulbaceae) and one species (Porphyromonas gingivalis) were observed only in the periodontitis group. No SNPs showed significant expression. These results suggest that periodontitis was related to the presence of P. gingivalis and the families Lactobacillaceae and Desulfobulbaceae but not SNPs

    Genome-wide association studies identify polygenic effects for completed suicide in the Japanese population

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    Suicide is a significant public health problem worldwide, and several Asian countries including Japan have relatively high suicide rates on a world scale. Twin, family, and adoption studies have suggested high heritability for suicide, but genetics lags behind due to difficulty in obtaining samples from individuals who died by suicide, especially in non-European populations. In this study, we carried out genome-wide association studies combining two independent datasets totaling 746 suicides and 14,049 non-suicide controls in the Japanese population. Although we identified no genome-wide significant single-nucleotide polymorphisms (SNPs), we demonstrated significant SNP-based heritability (35–48%; P < 0.001) for completed suicide by genomic restricted maximum-likelihood analysis and a shared genetic risk between two datasets (P best = 2.7 × 10−13) by polygenic risk score analysis. This study is the first genome-wide association study for suicidal behavior in an East Asian population, and our results provided the evidence of polygenic architecture underlying completed suicide

    Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls

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    Pathogenic variants in highly penetrant genes are useful for the diagnosis, therapy, and surveillance for hereditary breast cancer. Large-scale studies are needed to inform future testing and variant classification processes in Japanese. We performed a case-control association study for variants in coding regions of 11 hereditary breast cancer genes in 7051 unselected breast cancer patients and 11,241 female controls of Japanese ancestry. Here, we identify 244 germline pathogenic variants. Pathogenic variants are found in 5.7% of patients, ranging from 15% in women diagnosed <40 years to 3.2% in patients ≥80 years, with BRCA1/2, explaining two-thirds of pathogenic variants identified at all ages. BRCA1/2, PALB2, and TP53 are significant causative genes. Patients with pathogenic variants in BRCA1/2 or PTEN have significantly younger age at diagnosis. In conclusion, BRCA1/2, PALB2, and TP53 are the major hereditary breast cancer genes, irrespective of age at diagnosis, in Japanese women
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