Rett Syndrome, a Neurodevelopmental Disorder, Whole-Transcriptome, and Mitochondrial Genome Multiomics Analyses Identify Novel Variations and Disease Pathways

Aldosary, Mazhor; Al-Bakheet, Albandary; Aldhalaan, Hesham; Almass, Rawan; Alsagob, Maysoon; Al-Younes, Banan; AlQuait, Laila; Mustafa, Osama M.; Bulbul, Mustafa G.; Rahbeeni, Zuhair; Alfadhel, Majid; Chedrawi, Aziza; Al‐Hassnan, Zuhair N.; Al‐Dosari, Mohammed S.; Alzaidan, Hamad; Al–Muhaizea, Mohammad A.; AlSayed, Moeenaldeen; Salih, Mustafa A.; AlShammari, Mai; Faiyaz-Ul-Haque, Muhammad; Chishti, Mohammad Azhar; Al‐Harazi, Olfat; Al‐Odaib, Ali; Kaya, Namik; Çolak, Dilek

doi:10.1089/omi.2019.0192

Cited by 25 publications

(18 citation statements)

References 91 publications

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“…The more severe syndromic ASDs can be associated with additional functional and/or morphological alterations. This is observed in fragile X syndrome (57)(58)(59)(60), Rett syndrome (61,62), Angelman syndrome (63-65), Phelan-McDermid syndrome (66,67), and the 22q11 CNV (45). More severe mitochondrial defects, such as our nDNA heart-muscle-brain adenine nucleotide translocator isoform 1 gene null mutant mouse, presents with cardiomyopathy (68,69) and has impaired interneuron migration (42), and thus approximates a syndromic autism.…”

Section: Discussionmentioning

confidence: 99%

An mtDNA mutant mouse demonstrates that mitochondrial deficiency can result in autism endophenotypes

Yardeni

Cristancho

McCoy

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Autism spectrum disorders (ASDs) are characterized by a deficit in social communication, pathologic repetitive behaviors, restricted interests, and electroencephalogram (EEG) aberrations. While exhaustive analysis of nuclear DNA (nDNA) variation has revealed hundreds of copy number variants (CNVs) and loss-of-function (LOF) mutations, no unifying hypothesis as to the pathophysiology of ASD has yet emerged. Based on biochemical and physiological analyses, it has been hypothesized that ASD may be the result of a systemic mitochondrial deficiency with brain-specific manifestations. This proposal has been supported by recent mitochondrial DNA (mtDNA) analyses identifying both germline and somatic mtDNA variants in ASD. If mitochondrial defects do predispose to ASD, then mice with certain mtDNA mutations should present with autism endophenotypes. To test this prediction, we examined a mouse strain harboring an mtDNA ND6 gene missense mutation (P25L). This mouse manifests impaired social interactions, increased repetitive behaviors and anxiety, EEG alterations, and a decreased seizure threshold, in the absence of reduced hippocampal interneuron numbers. EEG aberrations were most pronounced in the cortex followed by the hippocampus. Aberrations in mitochondrial respiratory function and reactive oxygen species (ROS) levels were also most pronounced in the cortex followed by the hippocampus, but absent in the olfactory bulb. These data demonstrate that mild systemic mitochondrial defects can result in ASD without apparent neuroanatomical defects and that systemic mitochondrial mutations can cause tissue-specific brain defects accompanied by regional neurophysiological alterations.

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Section: Discussionmentioning

confidence: 99%

An mtDNA mutant mouse demonstrates that mitochondrial deficiency can result in autism endophenotypes

Yardeni

Cristancho

McCoy

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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“…Recent multi-omics analyses on patient blood samples identified alterations in mitochondrial DNA [ 18 ], and further mutations in genomic DNA that are relevant for mitochondrial and redox-regulatory functions. In the liver and skeletal muscles of male Mecp2-deficient mice, indications of disturbed utilization of mitochondrial substrate were obtained, pointing to potential disturbances in the TCA cycle [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Metabolomic Fingerprint of Mecp2-Deficient Mouse Cortex: Evidence for a Pronounced Multi-Facetted Metabolic Component in Rett Syndrome

Golubiani

Lagani

Solomonia

et al. 2021

Cells

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Using unsupervised metabolomics, we defined the complex metabolic conditions in the cortex of a mouse model of Rett syndrome (RTT). RTT, which represents a cause of mental and cognitive disabilities in females, results in profound cognitive impairment with autistic features, motor disabilities, seizures, gastrointestinal problems, and cardiorespiratory irregularities. Typical RTT originates from mutations in the X-chromosomal methyl-CpG-binding-protein-2 (Mecp2) gene, which encodes a transcriptional modulator. It then causes a deregulation of several target genes and metabolic alterations in the nervous system and peripheral organs. We identified 101 significantly deregulated metabolites in the Mecp2-deficient cortex of adult male mice; 68 were increased and 33 were decreased compared to wildtypes. Pathway analysis identified 31 mostly upregulated metabolic pathways, in particular carbohydrate and amino acid metabolism, key metabolic mitochondrial/extramitochondrial pathways, and lipid metabolism. In contrast, neurotransmitter-signaling is dampened. This metabolic fingerprint of the Mecp2-deficient cortex of severely symptomatic mice provides further mechanistic insights into the complex RTT pathogenesis. The deregulated pathways that were identified—in particular the markedly affected amino acid and carbohydrate metabolism—confirm a complex and multifaceted metabolic component in RTT, which in turn signifies putative therapeutic targets. Furthermore, the deregulated key metabolites provide a choice of potential biomarkers for a more detailed rating of disease severity and disease progression.

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“…Artificial intelligence (AI) and Machine learning (ML) approaches have been widely used to investigate the disease diagnosis and predict the outcome ( Maciukiewicz et al, 2018 ; Lai et al, 2019 ; Eicher et al, 2020 ; Jamal et al, 2020 ; Sanchez and Mackenzie, 2020 ; Sinkala et al, 2020 ; Stafford et al, 2020 ; Toraih et al, 2020 ). The integration of multiple high-throughput omics datasets, such as messenger RNA (mRNA) expression profiles, proteomics, copy number alterations (CNAs), methylation and others, may increase the robustness and reliability in identifying disease associated biomarkers ( Colak et al, 2010 ; Colak et al, 2013 ; List et al, 2014 ; Al-Harazi et al, 2016 ; Colak et al, 2016 ; Aldosary et al, 2020 ; Eicher et al, 2020 ). A protein−protein interaction (PPI) network can be defined as a directed or undirected network that consists of vertices as proteins or genes and edges as the interactions among them ( Wiredja and Bebek, 2017 ; Sanchez and Mackenzie, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

A Network-Based Methodology to Identify Subnetwork Markers for Diagnosis and Prognosis of Colorectal Cancer

et al. 2021

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The development of reliable methods for identification of robust biomarkers for complex diseases is critical for disease diagnosis and prognosis efforts. Integrating multi-omics data with protein-protein interaction (PPI) networks to investigate diseases may help better understand disease characteristics at the molecular level. In this study, we developed and tested a novel network-based method to detect subnetwork markers for patients with colorectal cancer (CRC). We performed an integrated omics analysis using whole-genome gene expression profiling and copy number alterations (CNAs) datasets followed by building a gene interaction network for the significantly altered genes. We then clustered the constructed gene network into subnetworks and assigned a score for each significant subnetwork. We developed a support vector machine (SVM) classifier using these scores as feature values and tested the methodology in independent CRC transcriptomic datasets. The network analysis resulted in 15 subnetwork markers that revealed several hub genes that may play a significant role in colorectal cancer, including PTP4A3, FGFR2, PTX3, AURKA, FEN1, INHBA, and YES1. The 15-subnetwork classifier displayed over 98 percent accuracy in detecting patients with CRC. In comparison to individual gene biomarkers, subnetwork markers based on integrated multi-omics and network analyses may lead to better disease classification, diagnosis, and prognosis.

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Rett Syndrome, a Neurodevelopmental Disorder, Whole-Transcriptome, and Mitochondrial Genome Multiomics Analyses Identify Novel Variations and Disease Pathways

Cited by 25 publications

References 91 publications

An mtDNA mutant mouse demonstrates that mitochondrial deficiency can result in autism endophenotypes

An mtDNA mutant mouse demonstrates that mitochondrial deficiency can result in autism endophenotypes

Metabolomic Fingerprint of Mecp2-Deficient Mouse Cortex: Evidence for a Pronounced Multi-Facetted Metabolic Component in Rett Syndrome

A Network-Based Methodology to Identify Subnetwork Markers for Diagnosis and Prognosis of Colorectal Cancer

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