Dataset Information

Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.

ABSTRACT: The genomic best linear unbiased prediction (GBLUP) model has proven to be useful for prediction of complex traits as well as estimation of population genetic parameters. Improved inference and prediction accuracy of GBLUP may be achieved by identifying genomic regions enriched for causal genetic variants. We aimed at searching for patterns in GBLUP-derived single-marker statistics, by including them in genetic marker set tests, that could reveal associations between a set of genetic markers (genomic feature) and a complex trait. GBLUP-derived set tests proved to be powerful for detecting genomic features, here defined by gene ontology (GO) terms, enriched for causal variants affecting a quantitative trait in a population with low degree of relatedness. Different set test approaches were compared using simulated data illustrating the impact of trait- and genomic feature-specific factors on detection power. We extended the most powerful single trait set test, covariance association test (CVAT), to a multiple trait setting. The multiple trait CVAT (MT-CVAT) identified functionally relevant GO categories associated with the quantitative trait, chill coma recovery time, in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel.

SUBMITTER: Sorensen IF

PROVIDER: S-EPMC5445101 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.

Sørensen Izel Fourie IF Edwards Stefan M SM Rohde Palle Duun PD Sørensen Peter P

Scientific reports 20170525 1

The genomic best linear unbiased prediction (GBLUP) model has proven to be useful for prediction of complex traits as well as estimation of population genetic parameters. Improved inference and prediction accuracy of GBLUP may be achieved by identifying genomic regions enriched for causal genetic variants. We aimed at searching for patterns in GBLUP-derived single-marker statistics, by including them in genetic marker set tests, that could reveal associations between a set of genetic markers (ge ...[more]

PMID: 28546557

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Project description:BackgroundIt is not currently possible to predict which patients will develop chronic disorders of consciousness (DoC) after severe traumatic brain injury (TBI). Although the ascending arousal network (AAN) supports human consciousness, it is unknown which AAN pathways must be preserved for patients to recover consciousness.MethodsSixteen patients with acute traumatic coma and 16 matched healthy controls were scanned with high angular resolution diffusion imaging (HARDI). All patients recovered consciousness (Recovery Cohort). Nine were scanned longitudinally: first in the ICU (Acute), then at ≥5 months post-injury (Follow-up). Six separate patients with post-traumatic DoC were scanned ≥5 months post-injury (Chronic DoC Cohort). For each AAN pathway, we computed the median relative change in Acute-to-Follow-up Connectivity Probability (CP) in the Recovery Cohort. We then used Wilcoxon tests with Bonferroni correction to compare CP in each AAN pathway in the Recovery Cohort at Follow-up versus the Chronic DoC Cohort. In an exploratory analysis, we used principal component analysis (PCA) to determine whether linear combinations of AAN CP values could separate the Chronic DoC Cohort from the Recovery Cohort and the healthy controls.ResultsIn the Recovery Cohort, the largest relative AAN CP changes were in the brainstem-to-thalamus (median [IQR] = 0.7 [0.09, 0.9]) and forebrain-to-occipital lobe (-0.8 [-0.9, -0.8]) pathways. The AAN connections that differed in the cross-sectional analysis between the Recovery Cohort at Follow-up and the Chronic DoC Cohort included brainstem-to-hypothalamus (W = 53, PBonf = 0.02), brainstem-to-temporal lobe (W = 52, PBonf = 0.04), and thalamus-to-temporal lobe (W = 54, PBonf = 0.009). Plotting the first two principal components of AAN connectivity resulted in a linear separation of Chronic DoC patients from other study groups.ConclusionsWe provide evidence for a longitudinal increase in brainstem-thalamic connectivity during recovery of consciousness after traumatic coma. Cross-sectional analyses revealed that brainstem-hypothalamus, brainstem-temporal lobe, and thalamus-temporal lobe connectivity differed between patients who recovered consciousness and those with a chronic DoC. These observations provide the basis for further investigation into AAN connectivity as a biomarker for recovery of consciousness after traumatic coma.

Dataset Information

Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.

Publications

Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.

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