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Record W4296312693 · doi:10.1155/2022/3481102

<i>MAO-B</i> Polymorphism Associated with Progression in a Chinese Parkinson’s Disease Cohort but Not in the PPMI Cohort

2022· article· en· W4296312693 on OpenAlexaboutno aff
Shishuang Cui, Lingyu Wu, Gen Li, Juanjuan Du, Pei Huang, Jin Liu, Yun Ling, Kang Ren, Zhonglue Chen, Shengdi Chen

Bibliographic record

VenueParkinson s Disease · 2022
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersShanghai Municipal Education CommissionNational Natural Science Foundation of China
KeywordsMedicineCohortParkinson's diseaseDiseaseCohort studyPolymorphism (computer science)Internal medicineGeneticsGenotypeGeneBiology

Abstract

fetched live from OpenAlex

Introduction . Genetic factors play an important role in Parkinson’s disease (PD) risk. However, the genetic contribution to progression in Chinese PD patients has rarely been studied. This study investigated genetic associations with progression based on 30 PD risk loci common in a longitudinal cohort of Chinese PD patients and the Parkinson’s Progression Markers Initiative (PPMI) cohort. Methods . PD patients from the true world (TW) Chinese PD longitudinal cohort and the PPMI cohort with demographic information and assessment scales were assessed. A panel containing 30 PD risk single nucleotide polymorphisms was tested. Progression rates of each scale were derived from random‐effect slope values of mixed‐effects regression models. Progression rates of multiple assessments were combined by using principal component analysis (PCA) to derive scores for composite, motor, and nonmotor progression. The association of genetic polymorphism and separate scales or PCA progression was analysed via linear regression. Results . In the Chinese PD cohort, MAOB rs1799836 was associated with progression based on the Montreal Cognitive Assessment, the top 3 principal components (PCs) of nonmotor PCA and PC1 of the composite PCA. In the PPMI cohort, both MDS‐Unified Parkinson’s Disease Rating Scale II and motor PC1 progression were associated with RIT2 rs12456492. The PARK16 haplotype was associated with Geriatric Depression Scale and the State‐Trait Anxiety Inventory for Adults progression, and the SNCA haplotype was associated with the Hoehn‐Yahr staging progression and motor PC1 progression. Ethnicity‐stratified analysis showed that the association between MAOB rs1799836 and PD progression may be specific to Asian or Chinese patients. Conclusion . MAOB rs1799836 was associated with the progression of nonmotor symptoms, especially cognitive impairment, and the composite progression of motor and nonmotor symptoms within our Chinese PD cohort. The RIT2 rs12456492 and SNCA haplotypes were associated with motor function decline, and the PARK16 haplotype was associated with progression in mood in the PPMI cohort.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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 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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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