Research

Overarching goals:

- Develop new understandings of mechanisms underlying major depression, life-long maturation or aging of the brain, and their
respective interactions,

- Use this knowledge to develop strategies for new therapeutic approaches.

Research Themes and Representative Publications:


Characterization of the primary molecular pathology of depression in human postmortem subjects

Our research goals focus on translational studies aimed at identifying the cellular and molecular basis of major depression. Current effort encompasses genomic, proteomic and genetic/epigenetic studies in postmortem brains of depressed and control subjects. We have provided direct evidence for a BDNF/GABA-related pathology in MDD with gender- and brain region-specific features. These studies provide a mechanistic link between two major hypotheses of depression, namely the reduced neurotrophic support and altered GABA hypothesis. Combined with imaging evidence from other research groups, we have proposed a model linking cellular, biochemical, and neural network findings for a role of cortical GABA neurons in the increased self-focus/rumination symptom dimension in depression.

a. Sibille E, Wang Y, Joeyen-Waldorf J, Gaiteri C, Surget A, et al. A molecular signature of depression in the amygdala. Am J Psychiatry. 2009 Sep;166(9):1011-24. PMID: 19605536. PMCID: PMC2882057. NIHMSID: 206316.

b. Tripp A, Oh H, Guilloux JP, Martinowich K, Lewis DA, et al. Brain-derived neurotrophic factor signaling and subgenual anterior cingulate cortex dysfunction in major depressive disorder. Am J Psychiatry. 2012 Nov;169(11):1194-202.
PMID: 23128924. PMCID: PMC3638149.

c. Guilloux JP, Douillard-Guilloux G, Kota R, Wang X, Gardier AM, et al. Molecular evidence for BDNF- and GABA-related dysfunctions in the amygdala of female subjects with major depression. Mol Psychiatry. 2012 Nov;17(11):1130-42.
PMID: 21912391. PMCID: PMC3237836.

d. Northoff G, Sibille E. Why are cortical GABA neurons relevant to internal focus in depression? A cross-level model linking cellular, biochemical and neural network findings. Mol Psychiatry. 2014 Sep;19(9):966-77.
PMID: 25048001. PMCID: PMC4169738.

Within cortical-like structures, GABA neurons can be subdivided according to their expression of neuropeptides and targeted pyramidal cell (PYR) compartment: Parvalbumin- (PV) and cholecystokinin- (CCK) positive GABA neurons target the cell body and initial segment, while SST, neuropeptide Y (NPY) and cortistatin (CORT)-expressing GABA neurons specifically target PYR dendrites. We have identified a decrease in somatostatin (SST) expression in dorsolateral prefrontal cortex, ACC and amygdala in MDD subjects. We also showed that all three markers of dendritic targeting interneurons (SST, NPY and CORT) are downregulated in the ACC of MDD subjects. Other subtypes were mostly not affected in dorsolateral prefrontal cortex and ACC. Together this suggests a selective downregulation in dendritic inhibition of PYR function in MDD.


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Translation of human molecular pathology to mouse models for investigating causal links and testing new therapeutic approaches

Our laboratory investigates causal links between candidate molecular and cellular pathologies (i.e. informed by our human studies - see above) and mood regulation, as a way to functionally characterize the primary pathology of depression. For instance, using genetic, environmental and pharmacological manipulations we recently showed a causal effect of altered function of SST-positive GABA neurons on rodent anxiety-/depressive-like behaviors. Using cell-specific molecular analyses, we have proposed specific molecular pathways (i.e, ER stress) as mediating the selective vulnerabilities of the SST-positive GABA neuronal population in depression and other brain disorders. We then identify novel targets within those particular biological modules and test their therapeutic potential using relevant (and new) pharmacological compounds.

a. Surget A, Wang Y, Leman S, Ibarguen-Vargas Y, Edgar N, et al. Corticolimbic transcriptome changes are state-dependent and region-specific in a rodent model of depression and of antidepressant reversal. Neuropsychopharmacology. 2009 May;34(6):1363-80.
PMID: 18536703. PMCID: PMC2669699.

b. Joeyen-Waldorf J, Nikolova YS, Edgar N, Walsh C, Kota R, et al. Adenylate cyclase 7 is implicated in the biology of depression and modulation of affective neural circuitry. Biol Psychiatry. 2012 Apr 1;71(7):627-32.
PMID: 22264442. PMCID: PMC3307939.

c. Soumier A, Sibille E. Opposing effects of acute versus chronic blockade of frontal cortex somatostatin-positive inhibitory neurons on behavioral emotionality in mice. Neuropsychopharmacology. 2014 Aug;39(9):2252-62.
PMID: 24690741. PMCID: PMC4104344.

d. Lin LC, Sibille E. Somatostatin, neuronal vulnerability and behavioral emotionality. Mol Psychiatry. 2015 Mar;20(3):377-87.
PMID: 25600109. PMCID: PMC4355106.

Loss of somatostatin (Sst) leads to high anxious/depressive-like behavior in the novelty suppressed feeding (NSF) test and overall elevated behavioral emotionality. Before (not shown) and after exposure to unpredictable mild chronic stress (UCMS) (Top panel), Sst-KO mice display increased latency in the NSF test and elevated overall emotionality Z-score (an integrated result from four related tests. UCMS induced a typical progressive fur coat degradation, which did not differ between groups (left). From d. Lin & Sibille (Mol Psychiatry. 2015).


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Age by Disease molecular interactions

As the largest source of biological variability in brain transcriptomes is due to aging, we have characterized the nature, extent and specificities of the gene expression correlates of aging in the human postmortem brain. Recent findings from our group demonstrate that these age-related changes include neuropsychiatric and neurodegenerative disease pathways and may in fact promote disease. Together this provides a compelling rationale for the simultaneous investigation of aging and disease pathways. These experimental findings have been conceptualized in a novel age-by-disease interaction hypothesis (PMID: 23576889), which we are now testing at the genetic levels, using a combined human postmortem brain and epidemiological cohort research approach.

a. Erraji-Benchekroun L, Underwood MD, Arango V, Galfalvy H, Pavlidis P, et al. Molecular aging in human prefrontal cortex is selective and continuous throughout adult life. Biol Psychiatry. 2005 Mar 1;57(5):549-58.
PMID: 15737671.

b. Sibille E, Su J, Leman S, Le Guisquet AM, Ibarguen-Vargas Y, et al. Lack of serotonin1B receptor expression leads to age-related motor dysfunction, early onset of brain molecular aging and reduced longevity. Mol Psychiatry. 2007 Nov;12(11):1042-56, 975.
PMID: 17420766. PMCID: PMC2515886.

c. Douillard-Guilloux G, Guilloux JP, Lewis DA, Sibille E. Anticipated brain molecular aging in major depression. Am J Geriatr Psychiatry. 2013 May;21(5):450-60.
PMID: 23570888. PMCID: PMC3615087.

d. McKinney BC, Sibille E. The age-by-disease interaction hypothesis of late-life depression. Am J Geriatr Psychiatry. 2013 May;21(5):418-32.
PMID: 23570886. PMCID: PMC3549303.

e. Sibille E. Molecular Aging of the Brain, Neuroplasticity, and Vulnerability to Depression and other Brain-related Disorders. Dialogues Clin Neurosci. 2013 Mar;15(1):53-65.
PMID: 23576889. PMCID: PMC3622469.

A proposed age-by-disease molecular interaction model. The graph depicts the age-dependent change in expression that is frequently observed for genes that are otherwise implicated in brain-related disorders (a decrease is shown here). Progression below a threshold (horizontal red line) marks the onset of disease symptoms. Changes in the trajectory of agerelated changes in expression of disease-related genes (Y-axis) determine the age (X-axis), or even if, an individual develops disease symptoms (vertical red arrows). Per this model, modulators (black arrows), genetic or environmental, place subjects on an "at risk" or protected trajectory for developing symptoms or brain-related disorders LLD (late-life depression).



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Biomarker development

Biological markers (i.e. biomarkers) are necessary to translate mechanistic studies in rodents to human settings, and for monitoring risk and progression of disease in live subjects. Examples of studies performed in my group include testing the potential of gene expression to predict non-remission in depression prior to antidepressant treatment initiation, of proteomic, structural and imaging data to predict cognitive impairment in late-life depression, and of integrated genetic scores to predict higher risk for having depression in later life.

Peripheral blod gene expression biomarker detection in depression and treatment response. Biomarker prediction performance assessment flowchart with corrected model selection bias. To search for the optimal number of features (2-30 genes) in the prediction model, we applied nested cross-validation (CV) utilizing two nested CV loops. The dataset is initially divided into one sample as the test set and the remaining as the training set. Then leave-one-out cross validation (LOOCV) is applied on the training set using all classifiers (top 2-30 genes). The classifier with the smallest error rate is selected and used to build the model on the training set. Finally, the model is evaluated on the left-out test sample and the procedure is repeated until all samples are left-out once. In this manner, the left-out test sample is independent from the model selection stage, including the selection of the model with the minimum error rate. This procedure guarantees an unbiased error estimate. (From Guilloux et al, 2014)

a. Diniz BS, Reynolds CF 3rd, Begley A, Dew MA, Anderson SJ, et al. Brain-derived neurotrophic factor levels in late-life depression and comorbid mild cognitive impairment: a longitudinal study. J Psychiatr Res. 2014 Feb;49:96-101. PMID: 24290367. PMCID: PMC3921964.

b. Guilloux JP, Bassi S, Ding Y, Walsh C, Turecki G, et al. Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression. Neuropsychopharmacology. 2015 Feb;40(3):701-10. PMID: 25176167. PMCID: PMC4289958.



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Methods development

In support of the research effort described above, we have been consistently involved in methods development. Examples include novel methods in biostatistics, bioinformatics, gene network and graph theory analyses and integrated behavioral scoring.

Multi-scale mapping of gene expression traits and coexpression networks. Disease-related gene expression traits can be aggregated at various scales in the context of coexpression networks. A) Coexpression links stem from multiple sources, but aggregate into an approximately scale-free network. B) Global coexpression networks may be decomposed into groups of coexpressed gene through many different clustering methods. These clusters are overlapping and may be generated by multiple regulatory systems. C) Because coexpressed gene sets tend to have similar functions, they may be useful bins in which to assess the most disease-impacted systems. D) Final selection of disease or potential therapeutic targets can integrate information from all scales to identify genes at the center of complex regulatory changes. E) Changes in any of the regulatory systems that create coexpression may be reflected in differentially coexpressed links, genes or modules that are enriched in coexpressed links. Finding the source of differential coexpression requires additional data drawn from scientific literature or ideally assessed experimentally in the same model system (represented by color-coded arrows for disease-specific coexpression links). (From Gaiteri et al 2014)

a. Guilloux JP, Seney M, Edgar N, Sibille E. Integrated behavioral z-scoring increases the sensitivity and reliability of behavioral phenotyping in mice: relevance to emotionality and sex. J Neurosci Methods. 2011 Apr 15;197(1):21-31. PMID: 21277897. PMCID: PMC3086134.

b. Kang DD, Sibille E, Kaminski N, Tseng GC. MetaQC: objective quality control and inclusion/exclusion criteria for genomic meta-analysis. Nucleic Acids Res. 2012 Jan;40(2):e15. PMID: 22116060. PMCID: PMC3258120.

c. Chang LC, Jamain S, Lin CW, Rujescu D, Tseng GC, et al. A conserved BDNF, glutamate- and GABA-enriched gene module related to human depression identified by coexpression meta-analysis and DNA variant genome-wide association studies. PLoS One. 2014;9(3):e90980.
PMID: 24608543. PMCID: PMC3946570.

d. Gaiteri C, Ding Y, French B, Tseng GC, Sibille E. Beyond modules and hubs: the potential of gene coexpression networks for investigating molecular mechanisms of complex brain disorders. Genes Brain Behav. 2014 Jan;13(1):13-24. PMID: 24320616. PMCID: PMC3896950.



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