scholarly journals Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortality

2019 ◽  
Author(s):  
Mbemba Jabbi ◽  
Dhivya Arasappan ◽  
Simon B. Eickhoff ◽  
Stephen M. Strakowski ◽  
Charles B. Nemeroff ◽  
...  
Keyword(s):  
Gene Expression ◽  
Factor Analysis ◽  
Mood Disorders ◽  
Rna Sequencing ◽  
Meta Analysis ◽  
Psychiatric Morbidity ◽  
Higher Order ◽  
Suicide Mortality ◽  
High Morbidity ◽  
Order Factor

ABSTRACTSuicidal behaviors are strongly linked with mood disorders, but the specific neurobiological and functional gene-expression correlates for this linkage remain elusive. We performed neuroimaging-guided RNA-sequencing in two studies to test the hypothesis that imaging-localized gray matter volume (GMV) loss in mood disorders, harbors gene-expression changes associated with disease morbidity and related suicide mortality in an independent postmortem cohort. To do so, first, we conducted study 1 using an anatomical likelihood estimation (ALE) MRI meta-analysis including a total of 47 voxel-based morphometry (VBM) publications (i.e. 26 control>major depressive disorder (MDD) studies, and 21 control>bipolar disorder (BD) studies) in 2387 (living) participants. Study 1 meta-analysis identified a selective anterior insula cortex (AIC) GMV loss in mood disorders. We then used this results to guide study 2 postmortem tissue dissection and RNA-Sequencing of 100 independent donor brain samples with a life-time history of MDD (N=30), BD (N=37) and control (N=33). In study 2, exploratory factor-analysis identified a higher-order factor representing number of Axis-1 diagnoses (e.g. substance use disorders/psychosis/anxiety, etc.), referred to here as morbidity and suicide-completion referred to as mortality. Comparisons of case-vs-control, and factor-analysis defined higher-order-factor contrast variables revealed that the imaging-identified AIC GMV loss sub-region harbors differential gene-expression changes in high morbidity-&-mortality versus low morbidity-&-mortality cohorts in immune, inflammasome, and neurodevelopmental pathways. Weighted gene co-expression network analysis further identified co-activated gene modules for psychiatric morbidity and mortality outcomes. These results provide evidence that AIC anatomical signature for mood disorders are possible correlates for gene-expression abnormalities in mood morbidity and suicide mortality.

scholarly journals A multi-group higher-order factor analysis for studying the gender-effect in Teacher Job Satisfaction

METRON ◽  
2021 ◽  
Author(s):  
Carlo Cavicchia ◽  
Pasquale Sarnacchiaro
Keyword(s):  
Job Satisfaction ◽  
Factor Analysis ◽  
Secondary School Teachers ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Higher Order ◽  
Teacher Job Satisfaction ◽  
Public Secondary School ◽  
Order Factor ◽  
Maximum Likelihood Estimation Method

AbstractTeachers’ performances also depend on whether and how they are satisfied with their job. Therefore, Teacher Job Satisfaction must be considered as the driver of teachers’ accomplishments. To plan future policies and improve the overall teaching process, it is crucial to understand which factors mostly contribute to Teacher Job Satisfaction. A Common Assessment Framework and Education questionnaire was administered to 163 Italian public secondary school teachers to collect data, and a second-order factor analysis was used to detect which factors impact on Teacher Job Satisfaction, and to what extent. This model-based approach guarantees to detect factors which respect important properties: unidimensionality and reliability. All the coefficients are estimated according to the maximum likelihood estimation method in order to make inference on the parameters and on the validity of the model. Moreover, a new multi-group test for higher-order factor analysis was proposed and implemented. Finally, we analyzed in detail whether the factors impacting Teacher Job Satisfaction are characterized by gender.

scholarly journals Identification of Inflammatory Genes, Pathways, and Immune Cells in Necrotizing Enterocolitis of Preterm Infant by Bioinformatics Approaches

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lili Zhang ◽  
Lizhen Sun ◽  
Mingli Wu ◽  
Jie Huang
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
Rna Sequencing ◽  
Necrotizing Enterocolitis ◽  
Immune Cells ◽  
Gastrointestinal Disease ◽  
Gene Set Enrichment Analysis ◽  
High Morbidity ◽  
Expression Levels ◽  
Gene Expression Levels

Background. Necrotizing enterocolitis (NEC) is one of the most serious gastrointestinal disease-causing high morbidity and mortality in premature infants. However, the underlying mechanism of the pathogenesis of NEC is still not fully understood. Methods. RNA sequencing of intestinal specimens from 9 NEC and 5 controls was employed to quantify the gene expression levels. RNA sequencing was employed to quantify the gene expression levels. DESeq2 tool was used to identify the differentially expressed genes. The biological function, pathways, transcription factors, and immune cells dysregulated in NEC were characterized by gene set enrichment analysis. Results. In the present study, we analyzed RNA sequencing data of NECs and controls and revealed that immune-related pathways were highly activated, while some cellular responses to external stimuli-related pathways were inactivated in NEC. Moreover, B cells, macrophages M1, and plasma cells were identified as the major cell types involved in NEC. Furthermore, we also found that inflammation-related transcription factor genes, such as STAT1, STAT2, and IRF2, were significantly activated in NEC, further suggesting that these TFs might play critical roles in NEC pathogenesis. In addition, NEC samples exhibited heterogeneity to some extent. Interestingly, two subgroups in the NEC samples were identified by hierarchical clustering analysis. Notably, B cells, T cells, Th1, and Tregs involved in adaptive immune were predicted to highly infiltrate into subgroup I, while subgroup II was significantly infiltrated by neutrophils. The heterogeneity of immune cells in NEC indicated that both innate and adaptive immunes might induce NEC-related inflammatory response. Conclusions. In summary, we systematically analyzed inflammation-related genes, signaling pathways, and immune cells to characterize the NEC pathogenesis and samples, which greatly improved our understanding of the roles of inflammatory responses in NEC.

Higher-order factor analysis of an instrument with dichotomous data

2005 ◽  
Vol 28 (5) ◽  
pp. 431-440 ◽  
Author(s):  
Kathleen A. Baldwin ◽  
Margaret S. Grinslade ◽  
Lynn C. Baer ◽  
Parris Watts ◽  
Mary K. Dinger ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Higher Order ◽  
Dichotomous Data ◽  
Order Factor

Helping Orientations: Four Dimensions

1989 ◽  
Vol 69 (3_suppl) ◽  
pp. 1371-1378 ◽  
Author(s):  
Joseph F. Michlitsch ◽  
Stanley Frankel
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Helping Behavior ◽  
Higher Order ◽  
Convenience Sample ◽  
Four Dimensions ◽  
Underlying Factor ◽  
Target Sample ◽  
Order Factor ◽  
And Coping

The underlying factor structure of four helping and coping orientations was investigated. The four orientations are the foundations of four models of helping and coping. Each model consists of a person's orientations toward helping behavior and the set of likely factors and behaviors related to the orientations. The orientations are believed to influence how a person interacts with others in a helping situation and how that person attempts to help himself (cope). Factor analysis in two studies supports the prediction of four helping orientations across a convenience and a target sample. Secondary, higher-order factor analysis further provides support based on the convenience sample, but not the target sample.

Personality Assessment Inventory: A Confirmatory Factor Analysis

1994 ◽  
Vol 79 (3_suppl) ◽  
pp. 1441-1442 ◽  
Author(s):  
Gregory J. Boyle ◽  
James Ward ◽  
Tania J. Lennon
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Personality Assessment ◽  
Personality Assessment Inventory ◽  
Higher Order ◽  
Self Report ◽  
Proposed Model ◽  
Confirmatory Factor ◽  
Order Factor ◽  
Report Measure

The Personality Assessment Inventory is a recently constructed multidimensional self-report measure of personality traits. Morey reported the results of a scale factoring, claiming that the instrument measures four separate higher-order dimensions; however, in an independent Australian study of the psychometric properties of the inventory, Boyle and Lennon found five higher-order dimensions, using factor analytic procedures intended to maximize simple structure. The present paper reports the results of a confirmatory factor analysis for the proposed model based on the Australian data. The results indicate that the model does not provide a satisfactory fit, raising questions about the higher-order factor structure.

Validity of Higher-Order Ability Constructs in Structure-of-Intellect Tests All Involving Semantic Content and Operations of Cognition or Evaluation: A Confirmatory Maximum Likelihood Factor Analysis

1985 ◽  
Vol 45 (2) ◽  
pp. 353-359 ◽  
Author(s):  
David E. Mace ◽  
William B. Michael ◽  
Dennis Hocevar
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Semantic Content ◽  
Higher Order ◽  
Second Order ◽  
Third Order ◽  
Maximum Likelihood Factor Analysis ◽  
Practical Standpoint ◽  
Order Factor ◽  
Structure Of Intellect

Through use of confirmatory maximum likelihood factor analysis in conjunction with the LISREL V computer program devised by Jöreskog and Sörbom, an evaluation was made of the validity of higher-order ability constructs in structure-of-intellect tests all containing semantic content and operations of cognition or evaluation. The hypothesized first-, second-, and third-order factors were all reproducible with every one of the estimated factor loadings being significant beyond the .01 level. Although the first- and second-order factors were shown to be reproducible and statistically separable, the high intercorrelations among the six first-order product factors and the two second-order operations factors would suggest from a practical standpoint that the single third-order factor of semantic content would constitute a plausible alternative for accounting for much of the covariance among the test variables.

scholarly journals Transcription factor motifs associated with anterior insula gene-expression underlying mood disorder phenotypes

2019 ◽  
Author(s):  
Dhivya Arasappan ◽  
Simon B. Eickhoff ◽  
Charles B Nemeroff ◽  
Hans A. Hofmann ◽  
Mbemba Jabbi
Keyword(s):  
Gene Expression ◽  
Mood Disorder ◽  
Mood Disorders ◽  
Rna Sequencing ◽  
Gray Matter Volume ◽  
Anterior Insula ◽  
Psychiatric Disease ◽  
Homeostatic Control ◽  
Imaging Results ◽  
Axis I

ABSTRACTBackgroundMood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined.MethodsBecause the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from postmortem mood disorder samples and compared with unaffected control samples for RNA-sequencing identification of differentially expressed genes (DEGs) in a) bipolar disorder (BD; n=37) versus (vs.) controls (n=33), and b) major depressive disorder (MDD n=30) vs controls, and c) low vs. high Axis-I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs.ResultsWe found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low Axis-I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ and brain development.DiscussionRobust imaging-guided transcriptomics (i.e., using meta-analytic imaging results to guide independent post-mortem dissection for RNA-sequencing) was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. TF motifs were identified for immune, cellular, embryonic and neurodevelopmental processes.ConclusionOur findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provides novel information about the hierarchical relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders.

Higher-Order Factor Analysis and Functional Regionalization: A Case Study in South Wales, 1971

1980 ◽  
Vol 12 (6) ◽  
pp. 685-701 ◽  
Author(s):  
W K D Davies
Keyword(s):  
Factor Analysis ◽  
Higher Order ◽  
Factorial Approach ◽  
South Wales ◽  
Functional Regionalization ◽  
Order Factor ◽  
Journey To Work ◽  
The Stability

A method for functional regionalization based on higher-order factor analysis is proposed. The utility of the method when using alternative factorial procedures is described by reference to a study of journey-to-work flows in South Wales in 1971, in which the stability of the results under alternative factorial procedures is explored. The advantages of the higher-order factorial approach compared with previously suggested methodologies are documented.

Helping Orientations: Four Dimensions,

1989 ◽  
Vol 69 (3-2) ◽  
pp. 1371-1378
Author(s):  
Joseph F. Michlitsch ◽  
Stanley Frankel
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Helping Behavior ◽  
Higher Order ◽  
Convenience Sample ◽  
Four Dimensions ◽  
Underlying Factor ◽  
Target Sample ◽  
Order Factor ◽  
And Coping

The underlying factor structure of four helping and coping orientations was investigated. The four orientations are the foundations of four models of helping and coping. Each model consists of a person's orientations toward helping behavior and the set of likely factors and behaviors related to the orientations. The orientations are believed to influence how a person interacts with others in a helping situation and how that person attempts to help himself (cope). Factor analysis in two studies supports the prediction of four helping orientations across a convenience and a target sample. Secondary, higher-order factor analysis further provides support based on the convenience sample, but not the target sample.

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