An integrated analysis of molecular aberrations in NCI-60 cell lines

<p>Abstract</p> <p>Background</p> <p>Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.</p> <p>Results</p> <p>We propose an integrated modeling framework to identify the statistical and putative causal relations of various molecular aberrations and gene expressions in cancer. To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. Layer 1 models associate gene expressions with the molecular aberrations on the same loci. Layer 2 models associate expressions with the aberrations on different loci but have known mechanistic links. Layer 3 models associate expressions with nonlocal aberrations which have unknown mechanistic links. We applied the layered models to the integrated datasets of NCI-60 cancer cell lines and validated the results with large-scale statistical analysis. Furthermore, we discovered/reaffirmed the following prominent links: (1)Protein expressions are generally consistent with mRNA expressions. (2)Several gene expressions are modulated by composite local aberrations. For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3)Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4)Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.</p> <p>Conclusions</p> <p>The analysis results on NCI-60 data justify the utility of the layered models for the incoming flow of cancer genomic data. Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.</p

Extending Epigenesis: From Phenotypic Plasticity to the Bio-Cultural Feedback

The paper aims at proposing an extended notion of epigenesis acknowledging an actual causal import to the phenotypic dimension for the evolutionary diversification of life forms. Section 1 offers introductory remarks on the issue of epigenesis contrasting it with ancient and modern preformationist views. In Section 2 we propose to intend epigenesis as a process of phenotypic formation and diversification a) dependent on environmental influences, b) independent of changes in the genomic nucleotide sequence, and c) occurring during the whole life span. Then, Section 3 focuses on phenotypic plasticity and offers an overview of basic properties (like robustness, modularity and degeneracy) that allows biological systems to be evolvable – i.e. to have the potentiality of producing phenotypic variation. Successively (Section 4), the emphasis is put on environmentally-induced modification in the regulation of gene expression giving rise to phenotypic variation and diversification. After some brief considerations on the debated issue of epigenetic inheritance (Section 5), the issue of culture (kept in the background of the preceding sections) is considered. The key point is that, in the case of humans and of the evolutionary history of the genus Homo at least, the environment is also, importantly, the cultural environment. Thus, Section 6 argues that a bio-cultural feedback should be acknowledged in the “epigenic” processes leading to phenotypic diversification and innovation in Homo evolution. Finally, Section 7 introduces the notion of “cultural neural reuse”, which refers to phenotypic/neural modifications induced by specific features of the cultural environment that are effective in human cultural evolution without involving genetic changes. Therefore, cultural neural reuse may be regarded as a key instance of the bio-cultural feedback and ultimately of the extended notion of epigenesis proposed in this work

ADHD and Disruptive behavior scores – associations with MAO-A and 5-HTT genes and with platelet MAO-B activity in adolescents

<p>Abstract</p> <p>Background</p> <p>Pharmacological and genetic studies suggest the importance of the dopaminergic, serotonergic, and noradrenergic systems in the pathogenesis of Attention Deficit Hyperactivity Disorder (ADHD) and Disruptive Behavior Disorder (DBD). We have, in a population-based sample, studied associations between dimensions of the ADHD/DBD phenotype and Monoamine Oxidase B (MAO-B) activity in platelets and polymorphisms in two serotonergic genes: the Monoamine Oxidase A Variable Number of Tandem Repeats (MAO-A VNTR) and the 5-Hydroxytryptamine Transporter gene-Linked Polymorphic Region (5-HTT LPR).</p> <p>Methods</p> <p>A population-based sample of twins, with an average age of 16 years, was assessed for ADHD/DBD with a clinical interview; Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL). Blood was drawn from 247 subjects and analyzed for platelet MAO-B activity and polymorphisms in the MAO-A and 5-HTT genes.</p> <p>Results</p> <p>We found an association in girls between low platelet MAO-B activity and symptoms of Oppositional Defiant Disorder (ODD). In girls, there was also an association between the heterozygote long/short 5-HTT LPR genotype and symptoms of conduct disorder. Furthermore the heterozygote 5-HTT LPR genotype in boys was found to be associated with symptoms of Conduct Disorder (CD). In boys, hemizygosity for the short MAO-A VNTR allele was associated with disruptive behavior.</p> <p>Conclusion</p> <p>Our study suggests that the serotonin system, in addition to the dopamine system, should be further investigated when studying genetic influences on the development of Disruptive Behavior Disorders.</p

Shared heritability of attention-deficit/hyperactivity disorder and autism spectrum disorder

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders. Evidence indicates both disorders co-occur with a high frequency, in 20–50% of children with ADHD meeting criteria for ASD and in 30-80% of ASD children meeting criteria for ADHD. This review will provide an overview on all available studies [family based, twin, candidate gene, linkage, and genome wide association (GWA) studies] shedding light on the role of shared genetic underpinnings of ADHD and ASD. It is concluded that family and twin studies do provide support for the hypothesis that ADHD and ASD originate from partly similar familial/genetic factors. Only a few candidate gene studies, linkage studies and GWA studies have specifically addressed this co-occurrence, pinpointing to some promising pleiotropic genes, loci and single nucleotide polymorphisms (SNPs), but the research field is in urgent need for better designed and powered studies to tackle this complex issue. We propose that future studies examining shared familial etiological factors for ADHD and ASD use a family-based design in which the same phenotypic (ADHD and ASD), candidate endophenotypic, and environmental measurements are obtained from all family members. Multivariate multi-level models are probably best suited for the statistical analysis

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871