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Record W3082288894 · doi:10.3389/fgene.2020.00952

The Association Analysis of GPNMB rs156429 With Clinical Manifestations in Chinese Population With Parkinson's Disease

2020· article· en· W3082288894 on OpenAlexaboutno aff
Jin Liu, Gen Li, Yixi He, Guiying He, Pingchen Zhang, Xin Shen, Weishan Zhang, Shengdi Chen, Shishuang Cui, Yuyan Tan

Bibliographic record

VenueFrontiers in Genetics · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersScience and Technology Commission of Shanghai MunicipalityShanghai Municipal Education CommissionNational Natural Science Foundation of China
KeywordsDiseaseParkinson's diseaseChinese populationMedicineAssociation (psychology)PopulationGenetic associationGeneticsBiologyInternal medicineSingle-nucleotide polymorphismPsychologyEnvironmental healthGenotypeGene

Abstract

fetched live from OpenAlex

Background: The mechanisms of Parkinson’s disease (PD) include complicated genetic factors. The roles of newly found risk genes need to be further verified among different ethnicities. In a two-stage meta-analysis, single nucleotide polymorphism (SNP) of rs156429 in glycoprotein nonmetastatic melanoma protein B (GPNMB) was reported to be associated with PD. So far clinical studies have focused on association between rs156429 and PD onset, however there is little evidence linking rs156429 with PD symptoms. Objective: This study aimed to investigate the possible association of GPNMB rs156429 with PD manifestations among southeastern Chinese people. Methods: Demographic variables, disease-related factors, and motor and non-motor assessments of 511 PD patients were collected. Polymerase chain reaction (PCR) and SNaPshot technique were used to detect GPNMB rs156429. The associations of rs156429 with PD rating scales and clinical manifestations were analyzed by Kruskal-Wallis test and logistic regression model separately. Results: Kruskal-Wallis test and logistic regression model failed to reveal an association between GPNMB rs156429 and scores from Montreal Cognitive Assessment (MoCA) (p = 0.037; p = 1.000 after correction), and pain symptoms of 511 PD patients (p = 0.008, OR = 0.59, 95% CI = 0.40-0.87, overdominant model after adjustment; p = 0.168 after correction, overdominant model after adjustment). However, further analysis based on genders showed that GPNMB rs156429 might have a trend for being associated with cognitive dysfunction (Mini-Mental State Examination (MMSE), p = 0.064 after correction; MoCA, p = 0.064 after correction) and pain symptoms (p = 0.063 after correction, overdominant model after adjustment) in female PD patients but not male patients. Conclusions: This study revealed that GPNMB rs156429 might have a trend for being associated with cognitive dysfunction and pain symptoms of female PD patients in the southeastern Chinese population. Further studies from a larger sample size are needed to confirm these findings.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.285
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2020
Admission routes1
Has abstractyes

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