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The role of single nucleotide polymorphisms of IL-1A -889C>T (rs1800587), TNF-A -238G>A (rs361525), and VDR TaqI (rs731236) on susceptibility to herniated nucleus pulposus: a systematic review and meta-analysis

2021· review· en· W3194288051 on OpenAlexaboutno aff
Azharuddin Azharuddin, Muhammad Ilmawan, Jonny Karunia Fajar, Marhami Fahriani, Sukamto S. Mamada, Helnida Anggun Maliga, Firzan Nainu, Kuldeep Dhama, Harapan Harapan, Rahadyan Magetsari

Bibliographic record

VenueF1000Research · 2021
Typereview
Languageen
FieldMedicine
TopicPregnancy-related medical research
Canadian institutionsnot available
Fundersnot available
KeywordsBiology

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background</ns4:bold> : The pathogenesis of herniated nucleus pulposus (HNP) is complex and may involve the wide variety of gene polymorphism. However, the reports from the existing studies are inconclusive. The objective of this study was to determine the role of single nucleotide polymorphisms (SNPs) in interleukin 1 alpha ( <ns4:italic>IL-1A</ns4:italic> ), tumor necrosis factor-alpha ( <ns4:italic>TNF-A</ns4:italic> ), and vitamin D receptor ( <ns4:italic>VDR</ns4:italic> ) genes on the susceptibility to herniated nucleus pulposus (HNP). </ns4:p> <ns4:p> <ns4:bold>Methods</ns4:bold> : Four databases (PubMed, Embase, Cochrane, and Web of Science) were searched as of April 1 <ns4:sup>st</ns4:sup> , 2021. Authors, publication year, targeted genes, genotype and allele frequency in each case and control groups were collected. Newcastle-Ottawa scale was used to evaluate the publication quality. The pooled estimates of association of <ns4:italic>IL-1A</ns4:italic> -889C&gt;T (rs1800587), <ns4:italic>TNF-A</ns4:italic> -238G&gt;A (rs361525), and <ns4:italic>VDR TaqI</ns4:italic> (rs731236) and susceptibility to HNP were assessed using Z test. </ns4:p> <ns4:p> <ns4:bold>Results</ns4:bold> : We screened 3,067 unique studies for eligibility and three, two and nine case-control studies on <ns4:italic>IL-1A</ns4:italic> -889C&gt;T, <ns4:italic>TNF-A</ns4:italic> -238G&gt;A, and <ns4:italic>VDR TaqI</ns4:italic> were included, respectively, in our meta-analysis. The studies consisting 369 HNP cases and 433 controls for <ns4:italic>IL-1A</ns4:italic> -889C&gt;T, 252 cases and 259 controls for <ns4:italic>TNF-A</ns4:italic> -238G&gt;A and 1130 cases and 2096 controls for <ns4:italic>VDR TaqI.</ns4:italic> Our pooled estimates indicated that there was no significant association of those SNPs with the susceptibility to HNP in any genotype, dominant model, recessive model, or allele comparations. </ns4:p> <ns4:p> <ns4:bold>Conclusion</ns4:bold> : Although individual studies suggested the important role of gene expression dysregulation associated with SNPs in <ns4:italic>IL-1A</ns4:italic> , <ns4:italic>TNF-A</ns4:italic> , and <ns4:italic>VDR</ns4:italic> , our data indicated that <ns4:italic>IL-1A</ns4:italic> -889C&gt;T, <ns4:italic>TNF-A</ns4:italic> -238G&gt;A, and <ns4:italic>VDR TaqI</ns4:italic> had weak association with HNP susceptibility in both genotypes and allele distributions. However, since heterogeneity was identified among studies included in this meta-analysis, further meta-analysis with a larger population and subgroup analysis on specific population are warranted to support this finding. </ns4:p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0140.003
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.393
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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