Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses

Hess, Jonathan; Tylee, Daniel S.; Barve, Rahul; Jong, Simone de; Ophoff, Roel A.; Kumarasinghe, Nishantha; Tooney, Paul A.; Schall, Ulrich; Gardiner, Erin; Beveridge, Natalie J.; Scott, Rodney J.; Yasawardene, S.G.; Perera, Antionette; Mendis, Jayan; Carr, Vaughan J.; Kelly, Brian; Cairns, Murray J.; Tsuang, Ming T.; Glatt, Stephen J.

doi:10.1016/j.schres.2019.07.036

Cited by 21 publications

(16 citation statements)

References 79 publications

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“…Gene expression in the brain is not a practical biomarker, but expression in the peripheral blood tends to mirror expression in the brain 251 . Indeed, blood transcriptomic profiles of schizophrenia and bipolar disorder were found to be similar and include altered expression of immune system genes 252,253 . Relations between gene expression and symptom dimensions are understudied, but preliminary evidence suggests that altered expression of immune genes is specific to psychoticism, whereas expression of mitochondrial genes is associated with detachment 253 .…”

Section: Validity Evidencementioning

confidence: 99%

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

et al. 2020

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The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co‐occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis‐related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

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Section: Validity Evidencementioning

confidence: 99%

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

et al. 2020

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“…65,[72][73][74] DNA methylation in promoters is typically associated with the repression of gene expression and may underlie at least some of the transcriptomic changes reported for BD in multiple tissues. [75][76][77][78][79] Moreover, several preclinical and clinical studies have shown that early-life traumatic experiences can induce stable methylation alterations that persist into adulthood, suggesting epigenetic-based alterations as mediators of the clinical effects of early adversity. [80][81][82] Interestingly, one of the mechanisms by which methylomes have been shown to interfere with BD phenotype is the modulation of biological aging processes.…”

Section: Genetics and Epigenetics Of Bipolar Disordermentioning

confidence: 99%

Neurobiology of bipolar disorders: a review of genetic components, signaling pathways, biochemical changes, and neuroimaging findings

Scaini

Valvassori

Diaz

et al. 2020

Braz. J. Psychiatry

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Bipolar disorder (BD) is a chronic mental illness characterized by changes in mood that alternate between mania and hypomania or between depression and mixed states, often associated with functional impairment. Although effective pharmacological and non-pharmacological treatments are available, several patients with BD remain symptomatic. The advance in the understanding of the neurobiology underlying BD could help in the identification of new therapeutic targets as well as biomarkers for early detection, prognosis, and response to treatment in BD. In this review, we discuss genetic, epigenetic, molecular, physiological and neuroimaging findings associated with the neurobiology of BD. Despite the advances in the pathophysiological knowledge of BD, the diagnosis and management of the disease are still essentially clinical. Given the complexity of the brain and the close relationship between environmental exposure and brain function, initiatives that incorporate genetic, epigenetic, molecular, physiological, clinical, environmental data, and brain imaging are necessary to produce information that can be translated into prevention and better outcomes for patients with BD.

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“…Descriptions for each dataset are provided in Supplementary Table 1 . Pre-processing and normalization steps used to prepare blood-based transcriptome profiles for the SCZ, BD, and ASD datasets are described in our previously published studies 10,45,46 . Details of our normalization procedure are available in the supplement ( Supplementary Methods ).…”

Section: Methodsmentioning

confidence: 99%

“…Descriptions for each dataset are provided in Supplementary Table 1. Pre-processing and normalization steps used to prepare individual-level blood-based transcriptome profiles for the SZ, BD, and ASD dataset are described in our previously published studies (Hess et al, 2016(Hess et al, , 2019Tylee et al, 2017).…”

Section: Concordance Of Disease-related Transcriptomic Signaturesmentioning

confidence: 99%

BrainGENIE: The Brain Gene Expression and Network Imputation Engine

Hess

Chen

Quinn

et al. 2020

Preprint

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Ex vivo molecular analysis of the human brain is virtually impossible given major risks and ethical concerns. Transcriptome imputation offers a promising and non-invasive alternative for developing models (albeit imperfect) of brain gene expression in lieu of biopsying brain tissue. Popular tools such as FUSION (Gusev et al., 2016) and PrediXcan (Gamazon et al., 2015) use genotypes at common cis-expression quantitative trait loci (eQTLs) to predict tissue-specific gene expression levels. However, those tools cannot reliably predict expression levels for a majority of genes in the brain. This raises the question of whether an alternative modeling approach should be evaluated to capture greater variance in more genes in the brain that are not yet imputable with existing cis-eQTL imputation tools. To address this problem, we developed a novel transcriptome-imputation method called the Brain Gene Expression and Network Imputation Engine (BrainGENIE) that imputes brain-region-specific gene expression levels from peripheral blood gene expression. BrainGENIE predicted brain-region-specific expression levels for 1,733 - 11,569 genes (cross-validation R2≥0.01, false-discovery rate-adjusted p<0.05), few of which are imputable by PrediXcan. Disease-related transcriptome signals detected by BrainGENIE showed stronger agreement with known transcriptome signatures from postmortem brain when compared with findings from analyses of peripheral blood or S-PrediXcan. BrainGENIE complements and outperforms existing transcriptome-imputation tools, provides biologically meaningful predictions, and opens avenues for studying brain transcriptomes longitudinally. BrainGENIE was developed using R (v.3.6.3, tested in 4.0.2) and is freely available at: https://github.com/hessJ/BrainGENIE.

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Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses

Cited by 21 publications

References 79 publications

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

Neurobiology of bipolar disorders: a review of genetic components, signaling pathways, biochemical changes, and neuroimaging findings

BrainGENIE: The Brain Gene Expression and Network Imputation Engine

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