A genome-wide linkage analysis of alcoholism on microsatellite and single-nucleotide polymorphism data, using alcohol dependence phenotypes and electroencephalogram measures

The Collaborative Study on the Genetics of Alcoholism (COGA) is a large-scale family study designed to identify genes that affect the risk for alcoholism and alcohol-related phenotypes. We performed genome-wide linkage analyses on the COGA data made available to participants in the Genetic Analysis Workshop 14 (GAW 14). The dataset comprised 1,350 participants from 143 families. The samples were analyzed on three technologies: microsatellites spaced at 10 cM, Affymetrix GeneChip(® )Human Mapping 10 K Array (HMA10K) and Illumina SNP-based Linkage III Panel. We used ALDX1 and ALDX2, the COGA definitions of alcohol dependence, as well as electrophysiological measures TTTH1 and ECB21 to detect alcoholism susceptibility loci. Many chromosomal regions were found to be significant for each of the phenotypes at a p-value of 0.05. The most significant region for ALDX1 is on chromosome 7, with a maximum LOD score of 2.25 for Affymetrix SNPs, 1.97 for Illumina SNPs, and 1.72 for microsatellites. The same regions on chromosome 7 (96–106 cM) and 10 (149–176 cM) were found to be significant for both ALDX1 and ALDX2. A region on chromosome 7 (112–153 cM) and a region on chromosome 6 (169–185 cM) were identified as the most significant regions for TTTH1 and ECB21, respectively. We also performed linkage analysis on denser maps of markers by combining the SNPs datasets from Affymetrix and Illumina. Adding the microsatellite data to the combined SNP dataset improved the results only marginally. The results indicated that SNPs outperform microsatellites with the densest marker sets performing the best

DNA Copy Number Analysis in Gastrointestinal Stromal Tumors Using Gene Expression Microarrays

We report a method, Expression-Microarray Copy Number Analysis (ECNA) for the detection of copy number changes using Affymetrix Human Genome U133 Plus 2.0 arrays, starting with as little as 5 ng input genomic DNA. An analytical approach was developed using DNA isolated from cell lines containing various X-chromosome numbers, and validated with DNA from cell lines with defined deletions and amplifications in other chromosomal locations. We applied this method to examine the copy number changes in DNA from 5 frozen gastrointestinal stromal tumors (GIST). We detected known copy number aberrations consistent with previously published results using conventional or BAC-array CGH, as well as novel changes in GIST tumors. These changes were concordant with results from Affymetrix 100K human SNP mapping arrays. Gene expression data for these GIST samples had previously been generated on U133A arrays, allowing us to explore correlations between chromosomal copy number and RNA expression levels. One of the novel aberrations identified in the GIST samples, a previously unreported gain on 1q21.1 containing the PEX11B gene, was confirmed in this study by FISH and was also shown to have significant differences in expression pattern when compared to a control sample. In summary, we have demonstrated the use of gene expression microarrays for the detection of genomic copy number aberrations in tumor samples. This method may be used to study copy number changes in other species for which RNA expression arrays are available, e.g. other mammals, plants, etc., and for which SNPs have not yet been mapped

Description of the data from the Collaborative Study on the Genetics of Alcoholism (COGA) and single-nucleotide polymorphism genotyping for Genetic Analysis Workshop 14

The data provided to the Genetic Analysis Workshop 14 (GAW 14) was the result of a collaboration among several different groups, catalyzed by Elizabeth Pugh from The Center for Inherited Disease Research (CIDR) and the organizers of GAW 14, Jean MacCluer and Laura Almasy. The DNA, phenotypic characterization, and microsatellite genomic survey were provided by the Collaborative Study on the Genetics of Alcoholism (COGA), a nine-site national collaboration funded by the National Institute of Alcohol and Alcoholism (NIAAA) and the National Institute of Drug Abuse (NIDA) with the overarching goal of identifying and characterizing genes that affect the susceptibility to develop alcohol dependence and related phenotypes. CIDR, Affymetrix, and Illumina provided single-nucleotide polymorphism genotyping of a large subset of the COGA subjects. This article briefly describes the dataset that was provided

Overexpression of Intrarenal Renin-Angiotensin System in Human Acute Tubular Necrosis

Background/Aims: Acute tubular necrosis (ATN), a leading cause of acute kidney injury (AKI), is associated with decreased survival and increased progression of chronic kidney disease. A barrier to improving the clinical outcomes is the incomplete understanding of the pathogenesis of AKI. Our objective is to test the hypothesis that intrarenal renin-angiotensin system (RAS) is overexpressed in patients with ATN and could be an indicator of ATN severity. Methods: A transversal study was conducted in patients with biopsy-proven ATN. Intrarenal expression of angiotensinogen and angiotensin II, and urinary angiotensinogen were measured. Results: Patients with ATN demonstrated upregulation of intrarenal RAS, evidenced by upregulation of intrarenal angiotensinogen and angiotensin II. Patients with ATN also have elevated urinary angiotensinogen level that correlated with the overexpressed intrarenal RAS. Moreover, this increase in intrarenal RAS expression and urinary angiotensinogen was associated with the extent of acute tubular injury and urinary albumin excretion, respectively. Conclusions: We demonstrate that the intrarenal RAS is upregulated in patients with ATN and is associated with the severity of ATN. Urinary angiotensinogen reflects intrarenal RAS status, and is of value to assess the severity of ATN

Altered resting-state functional connectivity patterns of anterior cingulate cortex in adolescents with attention deficit hyperactivity disorder

Dorsal anterior cingulate cortex (dACC) has been found to function abnormally in attention deficit hyperactivity disorder (ADHD) patients in several former functional MRI (fMRI) studies. Resting-state low-frequency fluctuations (LFFs) of blood oxygen level-dependent (BOLD) fMRI signals have been proved to be quite informative. This study used resting-state LFFs to investigate the resting-state functional connectivity pattern differences of dACC in adolescents with and without ADHD. As compared to the controls, the ADHD patients exhibited more significant resting-state functional connectivities with the dACC in bilateral dACC, bilateral thalamus, bilateral cerebellum, bilateral insula and bilateral brainstem (pons). No brain region in the controls was found to exhibit more significant resting-state functional connectivity with the dACC. We suggest these abnormally more significant functional connectivities in the ADHD patients may indicate the abnormality of autonomic control functions in them

High-Resolution Identification of Chromosomal Abnormalities Using Oligonucleotide Arrays Containing 116,204 SNPs

Mutation of the human genome ranges from single base-pair changes to whole-chromosome aneuploidy. Karyotyping, fluorescence in situ hybridization, and comparative genome hybridization are currently used to detect chromosome abnormalities of clinical significance. These methods, although powerful, suffer from limitations in speed, ease of use, and resolution, and they do not detect copy-neutral chromosomal aberrations—for example, uniparental disomy (UPD). We have developed a high-throughput approach for assessment of DNA copy-number changes, through use of high-density synthetic oligonucleotide arrays containing 116,204 single-nucleotide polymorphisms, spaced at an average distance of 23.6 kb across the genome. Using this approach, we analyzed samples that failed conventional karyotypic analysis, and we detected amplifications and deletions across a wide range of sizes (1.3–145.9 Mb), identified chromosomes containing anonymous chromatin, and used genotype data to determine the molecular origin of two cases of UPD. Furthermore, our data provided independent confirmation for a case that had been misinterpreted by karyotype analysis. The high resolution of our approach provides more-precise breakpoint mapping, which allows subtle phenotypic heterogeneity to be distinguished at a molecular level. The accurate genotype information provided on these arrays enables the identification of copy-neutral loss-of-heterozygosity events, and the minimal requirement of DNA (250 ng per array) allows rapid analysis of samples without the need for cell culture. This technology overcomes many limitations currently encountered in routine clinical diagnostic laboratories tasked with accurate and rapid diagnosis of chromosomal abnormalities