Evidence map›Paper›PMID 37115397›Full record

ArticleCurrent medical science2023

Correlation between Toll-like Receptor Gene Polymorphisms and Idiopathic Nephrotic Syndrome in Chinese Children.

Hui-Hui Gao, Wei Li, Xin-Yi Shou, Jian-Hua Mao

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Article in Current medical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
1 · What the graph read from it

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3 · Its place in the literature

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0 citing papers in PubMed, 1 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Hui-Hui Gao *Department of Pediatric and Adolescent, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310052, China.
Wei Li *Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310052, China.
Xin-Yi ShouDepartment of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310052, China.
Jian-Hua MaoDepartment of Nephrology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310052, China. maojh88@zju.edu.cn.
Children's Hospital of Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIdiopathic nephrotic syndrome (INS) is the most common glomerular disease in children. Toll-like receptors (TLRs) have been reported to be associated with response to steroid treatment in children with INS. Nevertheless, the correlation between TLR genes and the progression of INS has not yet been clarified. The present study aimed to investigate the association of single-nucleotide polymorphisms (SNPs) in TLR2, TLR4, and TLR9 with susceptibility to INS as well as the clinical phenotyping of steroid responsiveness in Chinese children with INS.

methodsA total of 183 pediatric inpatients with INS were included and given standard steroid therapy. Based on their clinical response to steroids, the patients were classified into three groups: steroid-sensitive nephrotic syndrome (SSNS), steroid-dependent nephrotic syndrome (SDNS), and steroid-resistant nephrotic syndrome (SRNS). A total of 100 healthy children were employed as controls. The blood genome DNA was extracted from each participant. Six SNPs (rs11536889, rs1927914, rs7869402, rs11536891, rs352140, and rs3804099) in TLR2, TLR4, and TLR9 were selected and detected by multiplex polymerase chain reaction with next-generation sequencing to assess TLR gene polymorphisms.

resultsAmong the 183 patients with INS, 89 (48.6%) had SSNS, 73 (39.9%) had SDNS, and 21 (11.5%) had SRNS. No significant difference was found in the genotype distribution between healthy children and patients with INS. However, the genotype and allele frequencies of TLR4 rs7869402 were significantly different between SRNS and SSNS. Compared with patients with the C allele and CC genotype, patients with the T allele and CT genotype had an increased risk of SRNS.

conclusionTLR4 rs7869402 affected the steroid response in Chinese children with INS. It might be a predictor for the early detection of SRNS in this population.

Indexed as

Nephrotic SyndromeToll-Like Receptor 4ChildEast Asian PeopleHumansPolymorphism, Single NucleotideSteroidsToll-Like Receptor 2Toll-Like Receptor 9SteroidsTLR4 protein, humanToll-Like Receptor 2Toll-Like Receptor 4Toll-Like Receptor 9childrenidiopathic nephrotic syndromepolymorphismssteroid resistanceToll-like receptor genes

Identifiers

PMID37115397
OpenAlexW4367315572

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.