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High dimensional endophenotype ranking in the search for major depression risk genes.

ABSTRACT: Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here, we describe the endophenotype ranking value, a new objective index of the genetic utility of endophenotypes for any heritable illness.Applying endophenotype ranking value analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individuals (n = 1122) from large randomly selected extended pedigrees.Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume, and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (logarithm of odds = 3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk.The wider use of quantitative endophenotypes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression.

SUBMITTER: Glahn DC

PROVIDER: S-EPMC3230692 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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High dimensional endophenotype ranking in the search for major depression risk genes.

Glahn David C DC Curran Joanne E JE Winkler Anderson M AM Carless Melanie A MA Kent Jack W JW Charlesworth Jac C JC Johnson Matthew P MP Göring Harald H H HH Cole Shelley A SA Dyer Thomas D TD Moses Eric K EK Olvera Rene L RL Kochunov Peter P Duggirala Ravi R Fox Peter T PT Almasy Laura L Blangero John J

Biological psychiatry 20111007 1

<h4>Background</h4>Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently ...[more]

PMID: 21982424

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Project description:BACKGROUND: Biologists may need to know the set of genes that are semantically related to a given set of genes. For instance, a biologist may need to know the set of genes related to another set of genes known to be involved in a specific disease. Some works use the concept of gene clustering in order to identify semantically related genes. Others propose tools that return the set of genes that are semantically related to a given set of genes. Most of these gene similarity measures determine the semantic similarities among the genes based solely on the proximity to each other of the GO terms annotating the genes, while overlook the structural dependencies among these GO terms, which may lead to low recall and precision of results. RESULTS: We propose in this paper a search engine called GRank, which overcomes the limitations of the current gene similarity measures outlined above as follows. It employs the concept of existence dependency to determine the structural dependencies among the GO terms annotating a given set of gene. After determining the set of genes that are semantically related to input genes, GRank would use microarray experiment to rank these genes based on their degree of relativity to the input genes. We evaluated GRank experimentally and compared it with a comparable gene prediction tool called DynGO, which retrieves the genes and gene products that are relatives of input genes. Results showed marked improvement. CONCLUSIONS: The experimental results demonstrated that GRank overcomes the limitations of current gene similarity measures. We attribute this performance to GRank's use of existence dependency concept for determining the semantic relationships among gene annotations. The recall and precision values for two benchmarking datasets showed that GRank outperforms DynGO tool, which does not employ the concept of existence dependency. The demo of GRank using 11000 KEGG yeast genes and a Gene Expression Omnibus (GEO) microarray file named "GSM34635.pad" is available at: http://ecesrvr.kustar.ac.ae:8080/ (click on the link labelled Gene Ontology 2).

Project description:BackgroundMajor depressive disorder has been associated with specific attentional biases in processing emotional facial expressions: heightened attention for negative and decreased attention for positive faces. However, using visual search paradigms, previous reaction-time-based research failed, in general, to find evidence for increased spatial attention toward negative facial expressions and reduced spatial attention toward positive facial expressions in depressed individuals. Eye-tracking analyses allow for a more detailed examination of visual search processes over time during the perception of multiple stimuli and can provide more specific insights into the attentional processing of multiple emotional stimuli.MethodsGaze behavior of 38 clinically depressed individuals and 38 gender matched healthy controls was compared in a face-in-the-crowd task. Pictures of happy, angry, and neutral facial expressions were utilized as target and distractor stimuli. Four distinct measures of eye gaze served as dependent variables: (a) latency to the target face, (b) number of distractor faces fixated prior to fixating the target, (c) mean fixation time per distractor face before fixating the target and (d) mean fixation time on the target.ResultsDepressed and healthy individuals did not differ in their manual response times. Our eye-tracking data revealed no differences between study groups in attention guidance to emotional target faces as well as in the duration of attention allocation to emotional distractor and target faces. However, depressed individuals fixated fewer distractor faces before fixating the target than controls, regardless of valence of expressions.ConclusionsDepressed individuals seem to process angry and happy expressions in crowds of faces mainly in the same way as healthy individuals. Our data indicate no biased attention guidance to emotional targets and no biased processing of angry and happy distractors and targets in depression during visual search. Under conditions of clear task demand depressed individuals seem to be able to allocate and guide their attention in crowds of angry and happy faces as efficiently as healthy individuals.

Dataset Information

High dimensional endophenotype ranking in the search for major depression risk genes.

Publications

High dimensional endophenotype ranking in the search for major depression risk genes.

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