<i>CNKSR1</i> gene defect can cause syndromic autosomal recessive intellectual disability

Kazeminasab, Somayeh; Taskiran, Ibrahim Ihsan; Fattahi, Zohreh; Bazazzadegan, Niloofar; Hosseini, Masoumeh; Rahimi, Maryam; Oladnabi, Morteza; Haddadi, Mohammad; Çelik, Arzu; Ropers, Hans‐Hilger; Najmabadi, Hossein; Kahrizi, Kimia

doi:10.1002/ajmg.b.32648

Cited by 5 publications

(4 citation statements)

References 45 publications

(53 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cg13690126 is located in CNKSR1 , a protein-coding gene with low tissue expression specificity. Defects in CNKSR1 have been linked to syndromic autosomal recessive intellectual disability (ID) [ 59 , 60 ]. Najmabadi et al [ 61 ] speculate its function as a scaffold protein mediating communication between Ras and Rho GTPase signaling pathways which have in turn been shown to play a role in neurodevelopmental disorders [ 61 , 62 ].…”

Section: Discussionmentioning

confidence: 99%

DNA methylation as a potential mediator of the association between indoor air pollution and neurodevelopmental delay in a South African birth cohort

et al. 2023

View full text Add to dashboard Cite

Background Exposure to indoor air pollution during pregnancy has been linked to neurodevelopmental delay in toddlers. Epigenetic modification, particularly DNA methylation (DNAm), may explain this link. In this study, we employed three high-dimensional mediation analysis methods (HIMA, DACT, and gHMA) followed by causal mediation analysis to identify differentially methylated CpG sites and genes that mediate the association between indoor air pollution and neurodevelopmental delay. Analyses were performed using data from 142 mother to child pairs from a South African birth cohort, the Drakenstein Child Health Study. DNAm from cord blood was measured using the Infinium MethylationEPIC and HumanMethylation450 arrays. Neurodevelopment was assessed at age 2 years using the Bayley Scores of Infant and Toddler Development, 3rd edition across four domains (cognitive development, general adaptive behavior, language, and motor function). Particulate matter with an aerodynamic diameter of 10 μm or less (PM10) was measured inside participants’ homes during the second trimester of pregnancy. Results A total of 29 CpG sites and 4 genes (GOPC, RP11-74K11.1, DYRK1A, RNMT) were identified as significant mediators of the association between PM10 and cognitive neurodevelopment. The estimated proportion mediated (95%-confidence interval) ranged from 0.29 [0.01, 0.86] for cg00694520 to 0.54 [0.11, 1.56] for cg05023582. Conclusions Our findings suggest that DNAm may mediate the association between prenatal PM10 exposure and cognitive neurodevelopment. DYRK1A and several genes that our CpG sites mapped to, including CNKSR1, IPO13, IFNGR1, LONP2, and CDH1, are associated with biological pathways implicated in cognitive neurodevelopment and three of our identified CpG sites (cg23560546 [DAPL1], cg22572779 [C6orf218], cg15000966 [NT5C]) have been previously associated with fetal brain development. These findings are novel and add to the limited literature investigating the relationship between indoor air pollution, DNAm, and neurodevelopment, particularly in low- and middle-income country settings and non-white populations.

show abstract

Section: Discussionmentioning

confidence: 99%

DNA methylation as a potential mediator of the association between indoor air pollution and neurodevelopmental delay in a South African birth cohort

et al. 2023

View full text Add to dashboard Cite

show abstract

“…ASD represents a broad clinical condition including deficits in social communication and interactions, repetitive behaviors, and restrictive interests ( Totsika et al, 2011 ). As well as epilepsy ASD frequently coexists with ID: it is estimated that 40%–70% of ASD individuals suffers also from ID ( Bertrand et al, 2001 ; Chakrabarti and Fombonne, 2001 ; Charman et al, 2011 ; Almuhtaseb et al, 2014 ; Jensen and Girirajan, 2017 ; Kazeminasab et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

The Usefulness of a Targeted Next Generation Sequencing Gene Panel in Providing Molecular Diagnosis to Patients With a Broad Spectrum of Neurodevelopmental Disorders

et al. 2022

View full text Add to dashboard Cite

Background: Neurodevelopmental disorders comprise a clinically and genetically heterogeneous group of conditions that affect 2%–5% of children and represents a public health challenge due to complexity of the etiology. Only few patients with unexplained syndromic and non-syndromic NDDs receive a diagnosis through first-tier genetic tests as array-CGH and the search for FMR1 CGG expansion. The aim of this study was to evaluate the clinical performance of a targeted next-generation sequencing (NGS) gene panel as a second-tier test in a group of undiagnosed patients with NDDs.Method: A 221-gene next-generation sequencing custom panel was designed and used to analyze a cohort of 338 patients with a broad spectrum of NDDs (202 males and 136 females) including Intellectual Disability (ID), Autism Spectrum Disorders (ASD), Epilepsy, language and motor disorders.Results: A molecular diagnosis was established in 71 patients (21%) and a de novo origin was present in 38 (64.4%) of the available trios. The diagnostic yield was significantly higher in females than in males (29.4% vs. 15.3%; p = 0.0019) in particular in ASD (36.8% vs. 7.6%; p = 0.0026) and Epilepsy (38.9% vs. 14.4% p = 0.001). The most involved genes were SLC2A1, SCN1A, ANKRD11, ATP1A2, CACNA1A, FOXP1, and GNAS altered in more than two patients and accounting for the 19.7% of the diagnosis.Conclusion: Our findings showed that this NGS panel represents a powerful and affordable clinical tool, significantly increasing the diagnostic yield in patients with different form of NDDs in a cost- and time-effective manner without the need of large investments in data storage and bioinformatic analysis.

show abstract

“…According to the UniProt database, CNKSR1 , EPHA2 , CLSPN , OLFML3 , and TARBP1 encode Connector enhancer of kinase suppressor of ras 1, Ephrin type-A receptor 2, Claspin, olfactomedin-like protein, and probable methyltransferase TARBP1, respectively [ 53 ]. Studies have suggested the role of CNKSR1 in brain development [ 54 ], EPHA2 in axon guidance [ 55 ], and CLSPN in cell homeostasis [ 56 ]. OLFML3 has been recognized as a microglia-specific gene whose loss of expression disrupts microglia-associated biological functions [ 57 ].…”

Section: Discussionmentioning

confidence: 99%

AITeQ: a machine learning framework for Alzheimer’s prediction using a distinctive five-gene signature

Ahammad,

Lamisa,

Bhattacharjee

et al. 2024

Briefings in Bioinformatics

View full text Add to dashboard Cite

Neurodegenerative diseases, such as Alzheimer’s disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer’s Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer’s from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew’s correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.

show abstract

CNKSR1 gene defect can cause syndromic autosomal recessive intellectual disability

Cited by 5 publications

References 45 publications

DNA methylation as a potential mediator of the association between indoor air pollution and neurodevelopmental delay in a South African birth cohort

DNA methylation as a potential mediator of the association between indoor air pollution and neurodevelopmental delay in a South African birth cohort

The Usefulness of a Targeted Next Generation Sequencing Gene Panel in Providing Molecular Diagnosis to Patients With a Broad Spectrum of Neurodevelopmental Disorders

AITeQ: a machine learning framework for Alzheimer’s prediction using a distinctive five-gene signature

Contact Info

Product

Resources

About