The pathogenic effect of SNPs on structure and function of human TLR4 using a computational approach

Prakasam, Priya; Salam, Abdul Ajees Abdul; Ahamed, Syed Ibrahim Basheer

doi:10.1080/07391102.2023.2166998

Cited by 2 publications

(1 citation statement)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Intronic sequences might be conserved, as they contain expression-regulating elements that impose functional constraints on their evolution 67,68 . SNPs located in these regions could be pathogenic even if they are conserved 69 . Variation analysis revealed that all three studied polymorphisms, specifically SLC11A1 rs3731864 G/A and rs3731865 G/C, reside in unconserved regions across multiple mammalian species.…”

Section: Discussionmentioning

confidence: 99%

Association of SLC11A1 polymorphisms with anthropometric and biochemical parameters describing Type 2 Diabetes Mellitus

Kavian

Sargazi

Majidpour

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Diabetes, a leading cause of death globally, has different types, with Type 2 Diabetes Mellitus (T2DM) being the most prevalent one. It has been established that variations in the SLC11A1 gene impact risk of developing infectious, inflammatory, and endocrine disorders. This study is aimed to investigate the association between the SLC11A1 gene polymorphisms (rs3731864 G/A, rs3731865 C/G, and rs17235416 + TGTG/− TGTG) and anthropometric and biochemical parameters describing T2DM. Eight hundred participants (400 in each case and control group) were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) and amplification-refractory mutation system-PCR (ARMS-PCR) methods. Lipid profile, fasting blood sugar (FBS), hemoglobin A1c level, and anthropometric indices were also recorded for each subject. Findings revealed that SLC11A1–rs3731864 G/A, –rs17235416 (+ TGTG/− TGTG) were associated with T2DM susceptibility, providing protection against the disease. In contrast, SLC11A1–rs3731865 G/C conferred an increased risk of T2DM. We also noticed a significant association between SLC11A1–rs3731864 G/A and triglyceride levels in patients with T2DM. In silico evaluations demonstrated that the SLC11A2 and ATP7A proteins also interact directly with the SLC11A1 protein in Homo sapiens. In addition, allelic substitutions for both intronic variants disrupt or create binding sites for splicing factors and serve a functional effect. Overall, our findings highlighted the role of SLC11A1 gene variations might have positive (rs3731865 G/C) or negative (rs3731864 G/A and rs17235416 + TGTG/− TGTG) associations with a predisposition to T2DM.

show abstract

Section: Discussionmentioning

confidence: 99%

Association of SLC11A1 polymorphisms with anthropometric and biochemical parameters describing Type 2 Diabetes Mellitus

Kavian

Sargazi

Majidpour

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

An Integrated Framework for Analysis and Prediction of Impact of Single Nucleotide Polymorphism Associated with Human Diseases

Muhammad,

Shoaib,

Pervez

2024

Evol Bioinform Online

View full text Add to dashboard Cite

Single nucleotide polymorphisms are most common type of genetic variation in human genome. Analyzing genetic variants can help us better understand the genetic basis of diseases and develop predictive models which are useful to identify individuals who are at increased risk for certain diseases. Several SNP analysis tools have already been developed. For running these tools, the user needs to collect data from various databases. Secondly, often researchers have to use multiple variant analysis tools for cross validating their results and increase confidence in their findings. Extracting data from multiple databases and running multiple tools at a time, increases complexity and time required for analysis. There are some web-based tools that integrate multiple genetic variant databases and provide variant annotations for a few tools. These approaches have some limitations such as retrieving annotation information, filtering common pathogenic variants. The proposed web-based tool, namely IPSNP: An Integrated Platform for Predicting Impact of SNPs is written in Django which is a python-based framework. It uses RESTful API of MyVariant.info to extract annotation information of variants associated with a given gene, rsID, HGVS format variants specified in a VCF file for 29 tools. The results are in the form of a CSV file of predictions (1) derived from the consensus decision, (2) a file having annotations for the variants associated with the given gene, (3) a file showing variants declared as pathogenic commonly by the selected tools, and (4) a CSV file containing chromosome coordinates based on GRCh37 and GRCh38 genome assemblies, rsIDs and proteomic data, so that users may use tools of their choice and avoiding manual parameter collection for each tool. IPSNP is a valuable resource for researchers and clinicians and it can help to save time and effort in discovering the novel disease-associated variants and the development of personalized treatments.

show abstract

The pathogenic effect of SNPs on structure and function of human TLR4 using a computational approach

Cited by 2 publications

References 69 publications

Association of SLC11A1 polymorphisms with anthropometric and biochemical parameters describing Type 2 Diabetes Mellitus

Association of SLC11A1 polymorphisms with anthropometric and biochemical parameters describing Type 2 Diabetes Mellitus

An Integrated Framework for Analysis and Prediction of Impact of Single Nucleotide Polymorphism Associated with Human Diseases

Contact Info

Product

Resources

About