Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity
Abstract Background Attention deficit hyperactivity disorder (ADHD) is commonly associated with developmental dyslexia (DD), which are both prevalent and complicated pediatric neurodevelopmental disorders that have a significant influence on children’s learning and development. Clinically, the comor...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-09-01
|
| Series: | BMC Medical Genomics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12920-023-01502-1 |
| _version_ | 1797555791830450176 |
|---|---|
| author | HE Hongyao JI Chun Gao Xiaoyan Liu Fangfang Zhang Jing Zhong Lin Zuo Pengxiang Li Zengchun |
| author_facet | HE Hongyao JI Chun Gao Xiaoyan Liu Fangfang Zhang Jing Zhong Lin Zuo Pengxiang Li Zengchun |
| author_sort | HE Hongyao |
| collection | DOAJ |
| description | Abstract Background Attention deficit hyperactivity disorder (ADHD) is commonly associated with developmental dyslexia (DD), which are both prevalent and complicated pediatric neurodevelopmental disorders that have a significant influence on children’s learning and development. Clinically, the comorbidity incidence of DD and ADHD is between 25 and 48%. Children with DD and ADHD may have more severe cognitive deficiencies, a poorer level of schooling, and a higher risk of social and emotional management disorders. Furthermore, patients with this comorbidity are frequently treated for a single condition in clinical settings, and the therapeutic outcome is poor. The development of effective treatment approaches against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and treatment. In this study, we developed bioinformatical methodology for the analysis of the comorbidity of these two diseases. As such, the search for candidate genes related to the comorbid conditions of ADHD and DD can help in elucidating the molecular mechanisms underlying the comorbid condition, and can also be useful for genotyping and identifying new drug targets. Results Using the ANDSystem tool, the reconstruction and analysis of gene networks associated with ADHD and dyslexia was carried out. The gene network of ADHD included 599 genes/proteins and 148,978 interactions, while that of dyslexia included 167 genes/proteins and 27,083 interactions. When the ANDSystem and GeneCards data were combined, a total of 213 genes/proteins for ADHD and dyslexia were found. An approach for ranking genes implicated in the comorbid condition of the two diseases was proposed. The approach is based on ten criteria for ranking genes by their importance, including relevance scores of association between disease and genes, standard methods of gene prioritization, as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analyzed genes. Among the top 20 genes with the highest priority DRD2, DRD4, CNTNAP2 and GRIN2B are mentioned in the literature as directly linked with the comorbidity of ADHD and dyslexia. According to the proposed approach, the genes OPRM1, CHRNA4 and SNCA had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the most relevant genes are involved in biological processes related to signal transduction, positive regulation of transcription from RNA polymerase II promoters, chemical synaptic transmission, response to drugs, ion transmembrane transport, nervous system development, cell adhesion, and neuron migration. Conclusions The application of methods of reconstruction and analysis of gene networks is a powerful tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance for the comorbid condition of ADHD and dyslexia was employed to predict genes that play key roles in the development of the comorbid condition. The results can be utilized to plan experiments for the identification of novel candidate genes and search for novel pharmacological targets. |
| first_indexed | 2024-03-10T16:53:42Z |
| format | Article |
| id | doaj.art-293d79212a9e4564b119a1daf36152bd |
| institution | Directory Open Access Journal |
| issn | 1755-8794 |
| language | English |
| last_indexed | 2024-03-10T16:53:42Z |
| publishDate | 2023-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Genomics |
| spelling | doaj.art-293d79212a9e4564b119a1daf36152bd2023-11-20T11:13:33ZengBMCBMC Medical Genomics1755-87942023-09-0116111710.1186/s12920-023-01502-1Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidityHE Hongyao0JI Chun1Gao Xiaoyan2Liu Fangfang3Zhang Jing4Zhong Lin5Zuo Pengxiang6Li Zengchun7Medical College of Shihezi UniversityMedical College of Shihezi UniversityMedical College of Shihezi UniversityMedical College of Shihezi UniversityMedical College of Shihezi UniversityMedical College of Shihezi UniversityMedical College of Shihezi UniversityMedical College of Shihezi UniversityAbstract Background Attention deficit hyperactivity disorder (ADHD) is commonly associated with developmental dyslexia (DD), which are both prevalent and complicated pediatric neurodevelopmental disorders that have a significant influence on children’s learning and development. Clinically, the comorbidity incidence of DD and ADHD is between 25 and 48%. Children with DD and ADHD may have more severe cognitive deficiencies, a poorer level of schooling, and a higher risk of social and emotional management disorders. Furthermore, patients with this comorbidity are frequently treated for a single condition in clinical settings, and the therapeutic outcome is poor. The development of effective treatment approaches against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and treatment. In this study, we developed bioinformatical methodology for the analysis of the comorbidity of these two diseases. As such, the search for candidate genes related to the comorbid conditions of ADHD and DD can help in elucidating the molecular mechanisms underlying the comorbid condition, and can also be useful for genotyping and identifying new drug targets. Results Using the ANDSystem tool, the reconstruction and analysis of gene networks associated with ADHD and dyslexia was carried out. The gene network of ADHD included 599 genes/proteins and 148,978 interactions, while that of dyslexia included 167 genes/proteins and 27,083 interactions. When the ANDSystem and GeneCards data were combined, a total of 213 genes/proteins for ADHD and dyslexia were found. An approach for ranking genes implicated in the comorbid condition of the two diseases was proposed. The approach is based on ten criteria for ranking genes by their importance, including relevance scores of association between disease and genes, standard methods of gene prioritization, as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analyzed genes. Among the top 20 genes with the highest priority DRD2, DRD4, CNTNAP2 and GRIN2B are mentioned in the literature as directly linked with the comorbidity of ADHD and dyslexia. According to the proposed approach, the genes OPRM1, CHRNA4 and SNCA had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the most relevant genes are involved in biological processes related to signal transduction, positive regulation of transcription from RNA polymerase II promoters, chemical synaptic transmission, response to drugs, ion transmembrane transport, nervous system development, cell adhesion, and neuron migration. Conclusions The application of methods of reconstruction and analysis of gene networks is a powerful tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance for the comorbid condition of ADHD and dyslexia was employed to predict genes that play key roles in the development of the comorbid condition. The results can be utilized to plan experiments for the identification of novel candidate genes and search for novel pharmacological targets.https://doi.org/10.1186/s12920-023-01502-1ComorbidityADHDDyslexiaANDSystemGene prioritizationBiological processes |
| spellingShingle | HE Hongyao JI Chun Gao Xiaoyan Liu Fangfang Zhang Jing Zhong Lin Zuo Pengxiang Li Zengchun Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity BMC Medical Genomics Comorbidity ADHD Dyslexia ANDSystem Gene prioritization Biological processes |
| title | Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity |
| title_full | Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity |
| title_fullStr | Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity |
| title_full_unstemmed | Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity |
| title_short | Associative gene networks reveal novel candidates important for ADHD and dyslexia comorbidity |
| title_sort | associative gene networks reveal novel candidates important for adhd and dyslexia comorbidity |
| topic | Comorbidity ADHD Dyslexia ANDSystem Gene prioritization Biological processes |
| url | https://doi.org/10.1186/s12920-023-01502-1 |
| work_keys_str_mv | AT hehongyao associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT jichun associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT gaoxiaoyan associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT liufangfang associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT zhangjing associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT zhonglin associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT zuopengxiang associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity AT lizengchun associativegenenetworksrevealnovelcandidatesimportantforadhdanddyslexiacomorbidity |