Gene-expression differences in peripheral blood between lithium responders and non-responders in the Lithium Treatment-Moderate dose Use Study (LiTMUS)

Beech, Robert D.; Leffert, Janine J.; Ai, Lin; Sylvia, Louisa G.; Umlauf, Sheila; Mane, Shrikant; Zhao, Hongyu; Bowden, Charles L.; Calabrese, Joseph R.; Friedman, Edward S.; Ketter, Terence A.; Iosifescu, Dan V.; Reilly-Harrington, Noreen A.; Ostacher, Michael J.; Thase, Michael E.; Nierenberg, Andrew A.

doi:10.1038/tpj.2013.16

Cited by 42 publications

(31 citation statements)

References 59 publications

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“…Few such studies to date have been undertaken using patient samples but rather cultured cells that have undergone immortalisation 30–32 . Results so far have implicated, for example, apoptotic pathways 30,31 , neutral amino acid transport 30 , protein ubiquitination, and protein synthesis 32 .…”

Section: Introductionmentioning

confidence: 99%

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

et al. 2018

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Lithium is the first-line treatment for bipolar affective disorder (BPAD) but two-thirds of patients respond only partially or not at all. The reasons for this high variability in lithium response are not well understood. Transcriptome-wide profiling, which tests the interface between genes and the environment, represents a viable means of exploring the molecular mechanisms underlying lithium response variability. Thus, in the present study we performed co-expression network analyses of whole-blood-derived RNA-seq data from n = 50 lithium-treated BPAD patients. Lithium response was assessed using the well-validated ALDA scale, which we used to define both a continuous and a dichotomous measure. We identified a nominally significant correlation between a co-expression module comprising 46 genes and lithium response represented as a continuous (i.e., scale ranging 0–10) phenotype (cor = −0.299, p = 0.035). Forty-three of these 46 genes had reduced mRNA expression levels in better lithium responders relative to poorer responders, and the central regulators of this module were all mitochondrially-encoded (MT-ND1, MT-ATP6, MT-CYB). Accordingly, enrichment analyses indicated that genes involved in mitochondrial functioning were heavily over-represented in this module, specifically highlighting the electron transport chain (ETC) and oxidative phosphorylation (OXPHOS) as affected processes. Disrupted ETC and OXPHOS activity have previously been implicated in the pathophysiology of BPAD. Our data adds to previous evidence suggesting that a normalisation of these processes could be central to lithium’s mode of action, and could underlie a favourable therapeutic response.

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Section: Introductionmentioning

confidence: 99%

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

et al. 2018

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“…Beech et al [16] conducted studies of gene expression changes in peripheral lymphocytes in bipolar subjects on lithium treatment for 1 month as well as bipolar subjects prospectively treated with lithium for 6 months [17]. After 6 months of treatment, responders had a greater upregulation of antiapoptotic genes (BCL2) while proapoptotic genes were downregulated.…”

Section: Introductionmentioning

confidence: 99%

Effects of Lithium Monotherapy for Bipolar Disorder on Gene Expression in Peripheral Lymphocytes

et al. 2016

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Background: This study investigated the effect of lithium monotherapy on peripheral lymphocyte gene expression in bipolar disorder (BD). Method: Twenty-two medication-free bipolar subjects (11 hypomanic, 11 depressed) were started on lithium monotherapy. Closely matched healthy subjects (n = 15) were included as controls but did not receive treatment. Blood RNA samples were collected at baseline and after 2 and 8 weeks of treatment. RNA expression was measured using the Affymetrix GeneChip® Human Gene 1.0 ST Array followed by Ingenuity pathways analysis. The results for the contrast of weeks 2 and 8 were not significantly different and were combined. Results: In BD subjects, 56 genes showed significant (false discovery rate <0.1) expression changes from baseline; the effect sizes and directions for all of these were similar at weeks 2 and 8. Among these were immune-related genes (IL5RA, MOK, IFI6, and RFX2), purinergic receptors (P2RY14, P2RY2, and ADORA3) and signal transduction-related genes (CAMK1 and PIK3R6). Pathway and upstream regulator analysis also revealed that lithium altered several immune- and signal transduction-related functions. Differentially expressed genes did not correlate with week 8 clinical response, but other genes involved in protein synthesis and degradation did. Conclusion: Peripheral gene expression may serve as a biomarker of lithium effect.

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“…The fifth, GSE98793, compares the whole blood of major mood disorder patients with controls (Leday et al, ). The sixth, GDS5393, compares the peripheral blood of bipolar I patients before and after lithium treatment (Beech et al, ). Data were acquired already normalized and were not modified further.…”

Section: Methodsmentioning

confidence: 99%

Improving the classification of neuropsychiatric conditions using gene ontology terms as features

Quinn

Lee

Venkatesh

et al. 2019

American J of Med Genetics Pt B

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Although neuropsychiatric disorders have an established genetic background, their molecular foundations remain elusive. This has prompted many investigators to search for explanatory biomarkers that can predict clinical outcomes. One approach uses machine learning to classify patients based on blood mRNA expression. However, these endeavors typically fail to achieve the high level of performance, stability, and generalizability required for clinical translation. Moreover, these classifiers can lack interpretability because not all genes have relevance to researchers. For this study, we hypothesized that annotation-based classifiers can improve classification performance, stability, generalizability, and interpretability. To this end, we evaluated the models of four classification algorithms on six neuropsychiatric data sets using four annotation databases. Our results suggest that the Gene Ontology Biological Process database can transform gene expression into an annotation-based feature space that is accurate and stable. We also show how annotation features can improve the interpretability of classifiers: as annotations are used to assign biological importance to genes, the biological importance of annotation-based features are the features themselves. In evaluating the annotation features, we find that top ranked annotations tend contain top ranked genes, suggesting that the most predictive annotations are a superset of the most predictive genes. Based on this, and the fact that annotations are used routinely to assign biological importance to genetic data, we recommend transforming gene-level expression into annotation-level expression prior to the classification of neuropsychiatric conditions.

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Gene-expression differences in peripheral blood between lithium responders and non-responders in the Lithium Treatment-Moderate dose Use Study (LiTMUS)

Cited by 42 publications

References 59 publications

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

Effects of Lithium Monotherapy for Bipolar Disorder on Gene Expression in Peripheral Lymphocytes

Improving the classification of neuropsychiatric conditions using gene ontology terms as features

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