On combining triads and unrelated subjects data in candidate gene studies: an application to data on testicular cancer.

Combining data collected from different sources is a cost-effective and time-efficient approach for enhancing the statistical efficiency in estimating weak-to-modest genetic effects or gene-gene or gene-environment interactions. However, combining data across studies becomes complicated when data are collected under different study designs, such as family-based and unrelated individual-based (e.g., population-based case-control design). In this paper, we describe a general method that permits the joint estimation of effects on disease risk of genes, environmental factors, and gene-gene/gene-environment interactions under a hybrid design that includes cases, parents of cases, and unrelated individuals. We provide both asymptotic theory and statistical inference. Extensive simulation experiments demonstrate that the proposed estimation and inferential methods perform well in realistic settings. We illustrate the method by an application to a study of testicular cancer

Distribution of Transmissible Amyloid Proteins in the Liver with Apolipoprotein A-II Amyloidosis

Article信州医学雑誌 64(4): 183-194(2016)journal articl

Tissue-specific patterns of gene expression in the epithelium and stroma of normal colon in healthy individuals in an aspirin intervention trial

AbstractRegular aspirin use reduces colon adenoma and carcinoma incidence. UDP-glucuronosyltransferases (UGT) are involved in aspirin metabolism and clearance, and variant alleles in UGT1A6 have been shown to alter salicylic acid metabolism and risk of colon neoplasia. In a randomized, cross-over, placebo-controlled trial of 44 healthy men and women, homozygous for UGT1A6*1 or UGT1A6*2, we explored differences between global epithelial and stromal expression, using Affymetrix U133+2.0 microarrays and tested effects of 60-day aspirin supplementation (325mg/d) on epithelial and stromal gene expression and colon prostaglandin E2 (PGE2) levels. We conducted a comprehensive study of differential gene expression between normal human colonic epithelium and stroma from healthy individuals. Although no statistically significant differences in gene expression were observed in response to aspirin or UGT1A6 genotype, we have identified the genes uniquely and reproducibly expressed in each tissue type and have analyzed the biologic processes they represent. Here we describe in detail how the data, deposited in the Gene Expression Omnibus (GEO) – accession number GSE71571 – was generated including the basic analysis as contained in the manuscript published in BMC Medical Genetics with the PMID 25927723 (Thomas et al., 2015 [9])

All-Weather and Superpixel Water Extraction Methods Based on Multisource Remote Sensing Data Fusion

The high spatial and temporal resolution of water body data offers valuable guidance for disaster monitoring and assessment. These data can be employed to quickly identify water bodies, especially small water bodies, and to accurately locate affected areas, which is significant for protecting people’s lives and property. However, the application of optical remote sensing is often limited by clouds and fog during actual floods. In this paper, water extraction methods of the multisource data fusion model (MDFM) and superpixel water extraction model (SWEM) are proposed, in which the MDFM fuses optical and synthetic aperture radar (SAR) images, and all-weather water extraction is achieved by using spectral information of optical images, texture information and the good penetration performance of SAR images. The SWEM further improves the accuracy of the water boundary with superpixel decomposition for extracted water boundaries using the fully constrained least squares (FCLS) method. The results show that the correlation coefficient (r) and area accuracy (Parea) of the MDFM and SWEM are improved by 2.22% and 9.20% (without clouds), respectively, and 3.61% and 18.99% (with clouds), respectively, compared with the MDFM, and 41.54% and 85.09% (without clouds), respectively, and 32.31% and 84.31% (with clouds), respectively, compared with the global surface water product of the European Commission Joint Research Centre’s Global Surface Water Explorer (JRC-GSWE). The MDFM and SWEM can extract water bodies with all weather and superpixel and improve the temporal and spatial resolution of water extraction, which has obvious advantages

The Mural Form of Eosinophilic Esophagitis Is Accompanied by Superficial Esophageal Squamous Cell Carcinoma

Eosinophilic esophagitis (EE) is an increasingly recognized primary clinicopathologic disorder of the esophagus which lacks a specific etiology. Most reports on EE have been limited to the esophagus mucosa. We present a 56-year-old man with the mural form of EE and superficial squamous cell carcinoma in the esophagus. The eosinophils diffusely invaded the full-thickness of the esophagus, mainly infiltrating the muscularis, including the skeletal and smooth muscles. The lesions in the mucosa, submucosa, and adventitia were slight. Although the superficial squamous cell carcinoma was excited by an endoscopic biopsy, there were some changes in the architecture and size of the squamous epithelial cells. The changed cells also expressed the p53 protein. It appears that the eosinophils stimulated cell proliferation, followed by genetic mutations and cancer development. The patient survived with resection of the esophagus and inhaled corticosteroids

On Combining Triads and Unrelated Subjects Data in Candidate Gene Studies: An Application to Data on Testicular Cancer

Combining data collected from different sources is a cost-effective and time-efficient approach for enhancing the statistical efficiency in estimating weak-to-modest genetic effects or gene-gene or gene-environment interactions. However, combining data across studies becomes complicated when data are collected under different study designs, such as family-based and unrelated individual-based (e.g., population-based case-control design). In this paper, we describe a general method that permits the joint estimation of effects on disease risk of genes, environmental factors, and gene-gene/gene-environment interactions under a hybrid design that includes cases, parents of cases, and unrelated individuals. We provide both asymptotic theory and statistical inference. Extensive simulation experiments demonstrate that the proposed estimation and inferential methods perform well in realistic settings. We illustrate the method by an application to a study of testicular cancer