Showing papers by "Vamsi K. Mootha published in 2005"

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals

Abstract: Comprehensive identification of all functional elements encoded in the human genome is a fundamental need in biomedical research. Here, we present a comparative analysis of the human, mouse, rat and dog genomes to create a systematic catalogue of common regulatory motifs in promoters and 3' untranslated regions (3' UTRs). The promoter analysis yields 174 candidate motifs, including most previously known transcription-factor binding sites and 105 new motifs. The 3'-UTR analysis yields 106 motifs likely to be involved in post-transcriptional regulation. Nearly one-half are associated with microRNAs (miRNAs), leading to the discovery of many new miRNA genes and their likely target genes. Our results suggest that previous estimates of the number of human miRNA genes were low, and that miRNAs regulate at least 20% of human genes. The overall results provide a systematic view of gene regulation in the human, which will be refined as additional mammalian genomes become available.

Relationship Between Testosterone Levels, Insulin Sensitivity, and Mitochondrial Function in Men

Abstract: OBJECTIVE — The goal of this study was to examine the relationship between serum testosterone levels and insulin sensitivity and mitochondrial function in men. RESEARCH DESIGN AND METHODS —A total of 60 men (mean age 60.5 ± 1.2 years) had a detailed hormonal and metabolic evaluation. Insulin sensitivity was measured using a hyperinsulinemic-euglycemic clamp. Mitochondrial function was assessed by measuring maximal aerobic capacity ( V o 2max ) and expression of oxidative phosphorylation genes in skeletal muscle. RESULTS —A total of 45% of subjects had normal glucose tolerance, 20% had impaired glucose tolerance, and 35% had type 2 diabetes. Testosterone levels were positively correlated with insulin sensitivity ( r = 0.4, P n = 10) had a BMI >25 kg/m 2 and a threefold higher prevalence of the metabolic syndrome than their eugonadal counterparts ( n = 50); this relationship held true after adjusting for age and sex hormone–binding globulin but not BMI. Testosterone levels also correlated with V o 2max ( r = 0.43, P r = 0.57, P CONCLUSIONS —These data indicate that low serum testosterone levels are associated with an adverse metabolic profile and suggest a novel unifying mechanism for the previously independent observations that low testosterone levels and impaired mitochondrial function promote insulin resistance in men.

Coenzyme Q deficiency and cerebellar ataxia associated with an aprataxin mutation.

Abstract: Primary muscle coenzyme Q10 (CoQ10) deficiency is an apparently autosomal recessive condition with heterogeneous clinical presentations. Patients with these disorders improve with CoQ10 supplementation. In a family with ataxia and CoQ10 deficiency, analysis of genome-wide microsatellite markers suggested linkage of the disease to chromosome 9p13 and led to identification of an aprataxin gene (APTX) mutation that causes ataxia oculomotor apraxia (AOA1 [MIM606350]). The authors' observations indicate that CoQ10 deficiency may contribute to the pathogenesis of AOA1.

Disease gene discovery through integrative genomics

Abstract: Ke yW ords human genetics, positional cloning, functional genomics, machine learning ■ Abstract The availability of complete genome sequences and the wealth of large- scale biological data sets now provide an unprecedented opportunity to elucidate the genetic basis of rare and common human diseases. Here we review some of the emerg- ing genomics technologies and data resources that can be used to infer gene function to prioritize candidate genes. We then describe some computational strategies for integrat- ing these large-scale data sets to provide more faithful descriptions of gene function, and how such approaches have recently been applied to discover genes underlying Mendelian disorders. Finally, we discuss future prospects and challenges for using integrative genomics to systematically discover not only single genes but also entire gene networks that underlie and modify human disease.