scholarly journals Hypothetical molecular interconnection between type 2 diabetes and dyslexia

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tuğba Bülbül ◽  
Maryam Baharlooie ◽  
Zahra Safaeinejad ◽  
Ali Osmay Gure ◽  
Kamran Ghaedi
Keyword(s):  
Type 2 Diabetes ◽  
Learning Disabilities ◽  
Literature Review ◽  
Interaction Analysis ◽  
Large Population ◽  
Protein Protein Interaction ◽  
Gene Associations ◽  
Common Learning ◽  
Type Two Diabetes

Abstract Background Dyslexia is one of the most common learning disabilities, especially among children. Type 2 diabetes is a metabolic disorder that affects a large population globally, with metabolic disorders. There have been several genes that are identified as causes of Dyslexia, and in recent studies, it has been found out that some of those genes are also involved in several metabolic pathways. For several years, it has been known that type 2 diabetes causes several neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease. Furthermore, in several studies, it was suggested that type 2 diabetes also has some associations with learning disabilities. This raises the question of whether “Is there a connection between type 2 diabetes and dyslexia?”. In this study, this question is elaborated by linking their developmental processes via bioinformatics analysis about these two diseases individually and collectively. Result The literature review for dyslexia and type two diabetes was completed. As the result of this literature review, the genes that are associated to type 2 diabetes and dyslexia were identified. The biological pathways of dyslexia, and dyslexia associated genes, type 2 diabetes, and type 2 diabetes associated genes were identified. The association of these genes, regarding to their association with pathways were analysed, and using STRING database the gene associations were analysed and identified. Conclusion The findings of this research included the interaction analysis via gene association, co-expression and protein–protein interaction. These findings clarified the interconnection between dyslexia and type 2 diabetes in molecular level and it will be the beginning of an answer regarding to the relationship between T2D and dyslexia. Finally, by improving the understanding this paper aims to open the way for the possible future approach to examine this hypothesis.

scholarly journals A Network-Based Bioinformatics Approach to Identify Molecular Biomarkers for Type 2 Diabetes that Are Linked to the Progression of Neurological Diseases

2020 ◽  
Vol 17 (3) ◽  
pp. 1035 ◽  
Author(s):  
Md Habibur Rahman ◽  
Silong Peng ◽  
Xiyuan Hu ◽  
Chen Chen ◽  
Md Rezanur Rahman ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Interaction Analysis ◽  
Neurological Diseases ◽  
Molecular Pathways ◽  
Literature Searching ◽  
Multilayer Network ◽  
Protein Protein Interaction ◽  
Unaffected Control ◽  
Go Terms

Neurological diseases (NDs) are progressive disorders, the progression of which can be significantly affected by a range of common diseases that present as comorbidities. Clinical studies, including epidemiological and neuropathological analyses, indicate that patients with type 2 diabetes (T2D) have worse progression of NDs, suggesting pathogenic links between NDs and T2D. However, finding causal or predisposing factors that link T2D and NDs remains challenging. To address these problems, we developed a high-throughput network-based quantitative pipeline using agnostic approaches to identify genes expressed abnormally in both T2D and NDs, to identify some of the shared molecular pathways that may underpin T2D and ND interaction. We employed gene expression transcriptomic datasets from control and disease-affected individuals and identified differentially expressed genes (DEGs) in tissues of patients with T2D and ND when compared to unaffected control individuals. One hundred and ninety seven DEGs (99 up-regulated and 98 down-regulated in affected individuals) that were common to both the T2D and the ND datasets were identified. Functional annotation of these identified DEGs revealed the involvement of significant cell signaling associated molecular pathways. The overlapping DEGs (i.e., seen in both T2D and ND datasets) were then used to extract the most significant GO terms. We performed validation of these results with gold benchmark databases and literature searching, which identified which genes and pathways had been previously linked to NDs or T2D and which are novel. Hub proteins in the pathways were identified (including DNM2, DNM1, MYH14, PACSIN2, TFRC, PDE4D, ENTPD1, PLK4, CDC20B, and CDC14A) using protein-protein interaction analysis which have not previously been described as playing a role in these diseases. To reveal the transcriptional and post-transcriptional regulators of the DEGs we used transcription factor (TF) interactions analysis and DEG-microRNAs (miRNAs) interaction analysis, respectively. We thus identified the following TFs as important in driving expression of our T2D/ND common genes: FOXC1, GATA2, FOXL1, YY1, E2F1, NFIC, NFYA, USF2, HINFP, MEF2A, SRF, NFKB1, USF2, HINFP, MEF2A, SRF, NFKB1, PDE4D, CREB1, SP1, HOXA5, SREBF1, TFAP2A, STAT3, POU2F2, TP53, PPARG, and JUN. MicroRNAs that affect expression of these genes include mir-335-5p, mir-16-5p, mir-93-5p, mir-17-5p, mir-124-3p. Thus, our transcriptomic data analysis identifies novel potential links between NDs and T2D pathologies that may underlie comorbidity interactions, links that may include potential targets for therapeutic intervention. In sum, our neighborhood-based benchmarking and multilayer network topology methods identified novel putative biomarkers that indicate how type 2 diabetes (T2D) and these neurological diseases interact and pathways that, in the future, may be targeted for treatment.

Systematic Literature Review and Network Meta-analysis (NMA) of SGLT2i as Monotherapy for Type 2 Diabetes Mellitus (T2DM)

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1159-P
Author(s):  
GLENN M. DAVIES ◽  
ANN MARIE MCNEILL ◽  
ELIZA KRUGER ◽  
STACEY L. KOWAL ◽  
FLAVIA EJZYKOWICZ ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Meta Analysis

Physical activity and adipokine levels in individuals with type 2 diabetes: A literature review and practical applications

2021 ◽  
Author(s):  
Hassane Zouhal ◽  
Navabeh Zare-kookandeh ◽  
Marjan Mosalman Haghighi ◽  
Ali Daraei ◽  
Maysa de Sousa ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Literature Review ◽  
Practical Applications

Hepatic fibrosis of any origin in a large population of type 2 diabetes patients

2021 ◽  
Author(s):  
Carlo b. Giorda ◽  
Roberta Picariello ◽  
Barbara Tartaglino ◽  
Elisa Nada ◽  
Cristina Linzalata ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Hepatic Fibrosis ◽  
Large Population ◽  
Diabetes Patients

scholarly journals Type 2 diabetes and tuberculosis in a dynamic bi-national border population

2006 ◽  
Vol 135 (3) ◽  
pp. 483-491 ◽  
Author(s):  
B. I. RESTREPO ◽  
S. P. FISHER-HOCH ◽  
J. G. CRESPO ◽  
E. WHITNEY ◽  
A. PEREZ ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Large Population ◽  
The United States ◽  
South Texas ◽  
Control Programmes ◽  
Mexico Border ◽  
Northeastern Mexico ◽  
The Impact ◽  
Border Population

The epidemic of type 2 diabetes in the United States prompted us to explore the association between diabetes and tuberculosis (TB) on the South Texas–Mexico border, in a large population of mostly non-hospitalized TB patients. We examined 6 years of retrospective data from all TB patients (n=5049) in South Texas and northeastern Mexico and found diabetes self-reported by 27·8% of Texan and 17·8% of Mexican TB patients, significantly exceeding national self-reported diabetes rates for both countries. Diabetes comorbidity substantially exceeded that of HIV/AIDS. Patients with TB and diabetes were older, more likely to have haemoptysis, pulmonary cavitations, be smear positive at diagnosis, and remain positive at the end of the first (Texas) or second (Mexico) month of treatment. The impact of type 2 diabetes on TB is underappreciated, and in the light of its epidemic status in many countries, it should be actively considered by TB control programmes, particularly in older patients.

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