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Record W4385431716 · doi:10.1016/j.heliyon.2023.e18395

Diffusion tensor imaging techniques show that parkin gene S/N167 polymorphism is responsible for extensive brain white matter damage in patients with Parkinson's disease

2023· article· en· W4385431716 on OpenAlexaboutno aff
Jinqiu Yu, Jinying Shi, Lina Chen, Ying-Qing Wang, Guoen Cai, Xiaochun Chen, Weiming Hong, Qinyong Ye

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsWhite matterSubstantia nigraParkinson's diseaseDiffusion MRIStriatumMontreal Cognitive AssessmentPsychologyInternal medicineMedicineNeuroscienceMagnetic resonance imagingCognitionDiseaseDopamineCognitive impairmentRadiology

Abstract

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Objective To explore the influence of disease and genetic factors on the white matter microstructure in patients with PD. The white matter microstructural changes in the substantia nigra-striatum system were detected by diffusion tensor imaging (DTI) using the region of interest (ROI) and diffusion tensor tracer (DTT) methods. Methods Patients with primary Parkinson's disease (PD) without a family history of PD were selected and divided into PD-G/G and PD-G/A groups according to their parkin S/N167 polymorphism. Control groups matched for age, sex, and gene type (G/G and G/A) were also included. Three-dimensional brain volume imaging (3D-BRAVO) and DTI were performed. The microstructural changes in the substantia nigra-striatum system were evaluated by the ROI and DTT methods. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hoehn-Yahr (H–Y) staging, and the third part of the Unified Parkinson's Disease Rating (UPDRS-III) scales evaluated the cognitive and motor function impairment in patients with PD. Independent samples t -test compared normally-distributed data, and the Wilcoxon rank sum test compared measurement or categorical non-normally distributed data. Multiple regression analysis was used to analyze the correlation between various DTI indicators and the MMSE, MoCA, UPDRS-III, and H–Y scores in the PD-G/G and PD-G/A groups. P < 0.05 was considered statistically significant. Results The white matter microstructural changes in the nigrostriatal pathway differed significantly between the PD or PD-G/A and the control group ( P < 0.05) The ROI method showed that the left globus pallidus radial diffusivity (RD) value was negatively correlated with the MMSE score (r = −0.404, P = 0.040), and the left substantia nigra (LSN) fractional anisotropy (FA) value was positively correlated with the MoCA score (r = 0.405, P = 0.040) and negatively with the H–Y stage (r = −0.479, P = 0.013). The DTT method showed that the MMSE score was positively correlated with the right substantia nigra (RSN) FA value (r = 0.592, P = 0.001) and negatively with its RD value (r = −0.439, P = 0.025). The H–Y grade was negatively correlated with the number of fibers in the RSN (r = −0.406, P = 0.040). The UPDRS-Ⅲ score was positively correlated with the mean diffusivity (r = 0.420, P = 0.033) and RD (r = 0.396, P = 0.045) values of the LSN, and the AD value of the RSN (r = 0.439, P = 0.025). Conclusion The DTI technique detected extensive white matter fiber damage in patients with PD, primarily in those with the G/A genotype, that led to motor and cognitivesymptoms.

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)0.000
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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