Roles and mechanisms of ankyrin-G in neuropsychiatric disorders

Objective: Complex machine learning classification algorithms using transcriptome data from post-mortem cerebellar tissue of bipolar patients and unaffected controls, have been recently included in pipelines for patient control classification and identification of characteristic biomarkers. Transcriptomic profile differences between patients and controls, can provide useful information about the role of the cerebellum in the pathogenesis of bipolar disorder and mood deregulation and in normal mood regulation and physiology. User-friendly, fully automated machine learning algorithms, using data extracted from established repositories, could achieve extremely high classification scores and disease- related predictive biomarker identification, in very short time frames and scaled down to small datasets, thus facilitating research on mood disorders. Method: An application of a fully automated machine learning platform, based on the most suitable algorithm selection and relevant set of hyper- parameter values, for classification between patients and controls and the production of models for biosignature selection, is presented. Transcriptome data used for the analysis were downloaded from the BioDataome preprocessed datasets database. The Dataome dataset, derived from the parent Gene Expression Omnibus GSE35974 (2013) and GSE35978 datasets, which have been originally produced from the cerebellar and parietal lobe tissue of deceased bipolar patients and unaffected controls, (from the Stanley Medical Research Institute Neuropathology Consortium and Array collections), using Affymetrix Human Gene 1.0 ST Array. Patient and control groups were closely matched for age and sex . Results: Bipolar patients have been identified from controls based on the cerebellar transcriptomic profile with AUC 0.929 and Average Precision 0.955. Patients and Controls have been classified in two separated groups with no close to the boundary cases. Using 6 of the characteristic features discovered during the selection process, 99,6% classification accuracy was achieved. The three biomarkers contributing most to the predictive power of the model (92,7%), are also deregulated in temporal lobe epilepsy. Conclusion: The cerebellar transcriptome of bipolar patients has a discrete profile and can be used for further exploration of the role of this area in health and disease. 93% AUC and 96% Precision were achieved during classification between unaffected controls and patients with Bipolar Disorder.

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“…[29], [70]. ANK3 and could be connected to the neurobiology of bipolar disorder [70], [92], [93], [94], [95].…”

Section: Kegg Analysis Results and Neuropsychiatric Diseasementioning

confidence: 99%

“…The hsa05206 pathway is of particular interest, as it includes also miR-34a gene; Both ANK3 (Ankyrin-3) and CACNB3 (voltage-dependent L-type calcium channel subunit beta-3) genes, are directly targeted by miR-34a [29], [70]. ANK3 and could be connected to the neurobiology of bipolar disorder [70], [92], [93], [94], [95].…”

Section: Discussionmentioning

confidence: 99%

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

Thomaidis

Michos

Papadimitriou³

et al. 2022

Preprint

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“…Gain-of-function and loss-of-function experiments were employed by inducing signaling upon treatment of hippocampal neurons with exogenous TGF-β2 and by using neuronal cultures and tissue from Tgf-β2 constitutive knockout mice, respectively. Ank3 gene codes for several Ankyrin-G isoforms, most of which are poorly characterized (reviewed by Yoon et al, 2022). Hence, we focused on the isoforms with well-established roles in neurons, known as Ankyrin-G 190/ 270/ 480 kDa (Smith et al, 2014; Jenkins et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…Ank3 gene, encoding Ankyrin-G, has been implicated in a spectrum of neuropsychiatric disorders such as bipolar disorder and autism (Ferreira et al, 2008; Schulze et al, 2009; Bi et al, 2012). Human Ank3 gene codes for different isoforms of Ankyrin-G with distinct spatial and temporal expression patterns and functions in the brain (reviewed by Yoon et al, 2022). Three of these isoforms are collectively known as Ankyrin-G 190 kDa because they migrate at ∼190 kDa when analysed by SDS-PAGE.…”

Section: Introductionmentioning

confidence: 99%

TGF-β2 regulates neuronal Ankyrin-G and promotes its interaction with KCC2

Rigkou,

Pethe,

Roussa

2023

Preprint

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The neuronal K+/Cl-cotransporter 2 (KCC2) is the major Cl-extruder in CNS neurons and responsible for fast hyperpolarizing postsynaptic inhibition in mature neurons. Impaired KCC2 function has been associated with several brain pathologies. KCC2 forms immunocomplexes with several proteins that may regulate KCC2 membrane trafficking, stability and function, thus, tuning important cellular processes, including chloride homeostasis and dendritic spine development. In the brain, the scaffold protein Ankyrin-G, encoded by theAnk3gene, is expressed in several isoforms with distinct spatial and temporal expression patterns, is regulated by TGF-β signalling and is proposed as a KCC2 interaction partner. Moreover,Ank3gene has been implicated in several neuropsychiatric disorders.Here, we investigated a putative impact of transforming growth factor beta 2 (TGF-β2) on KCC2/Ankyrin-G interaction using quantitative RT-PCR, immunoblotting, immunoprecipitation and immunofluorescence in mouse immature and differentiated hippocampal neurons and in forebrain and brainstem tissue fromTgf-β2deficient mice. The results show TGF-β2-dependent downregulation ofAnk3transcripts, as well as KCC2/Ankyrin-G interaction in mouse brainstem tissue at embryonic day (E) 17.5.In vitro, loss ofTgf-β2resulted in significantly reduced axonal and somatic Ankyrin-G in immature neurons and significantly reduced somatic Ankyrin-G abundance in differentiated mouse hippocampal neurons. Membrane abundance of Ankyrin-G was downregulated inTgf-β2mutants as well, a phenotype rescued by application of exogenous TGF-β2. Moreover, the results suggest the presence of a Golgi-associated Ankyrin-G isoform in neurons and significantly impaired membrane KCC2 abundance following knock down ofAnk3. Thus, the present study provides new insights into Ankyrin-G regulation by TGF-β2 in neurons and first evidence of a TGF-β2-regulated interaction of KCC2 with Ankyrin-G. Moreover, these results strengthen the notion for TGF-β2 as pivotal regulator of KCC2 abundance and function.

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“…Multiple neurological disorders of children are caused by postzygotic mutations of genes that occur during the late stages of development that impair their capacity to signal effectively. These include gene families that code for the voltage‐gated sodium, 3 potassium 4 and calcium 5 ion channels, the Na‐K ATPase ion pump, 6 and the cytoskeletal proteins ankyrin 7 and spectrin 8–10 that maintain the localization of ion channels at the axonal membranes. The consequences of these mutations span a wide variety of neurological problems, including epilepsy, ataxia, dementia, and other cognitive defects.…”

Section: Neurological Diseases Are Caused By Mutations That Impair El...mentioning

confidence: 99%

Impaired electrical activity of the brain explains the onset of dementia in aging people

Marchesi

2023

The FASEB Journal

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Roles and mechanisms of ankyrin-G in neuropsychiatric disorders

Cited by 13 publications

References 126 publications

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

TGF-β2 regulates neuronal Ankyrin-G and promotes its interaction with KCC2

Impaired electrical activity of the brain explains the onset of dementia in aging people

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