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Record W3138569498 · doi:10.1002/mds.28517

Genotype–Phenotype Relations for the Atypical Parkinsonism Genes: MDSGene Systematic Review

2021· review· en· W3138569498 on OpenAlexafffund
Christina Wittke, Sonja Petkovic, Valerija Dobričić, Susen Schaake, Gesine Respondek, Anne Weißbach, Harutyun Madoev, Joanne Trinh, Eva‐Juliane Vollstedt, Neele Kuhnke, Katja Lohmann, Marija Dulovic Mahlow, Connie Marras, Inke R. König, María Stamelou, Vincenzo Bonifati, Christina M. Lill, Meike Kasten, Hans‐Jürgen Huppertz, Günter U. Höglinger, Christine Klein

Bibliographic record

VenueMovement Disorders · 2021
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchDeutsche KrebshilfeNational Institute on AgingDeutsche ForschungsgemeinschaftNOMIS StiftungBundesministerium für Bildung und ForschungAlzheimer NederlandZonMwInternational Parkinson and Movement Disorder SocietyMichael J. Fox Foundation for Parkinson's Research
KeywordsParkinsonismProgressive supranuclear palsyCorticobasal degenerationLevodopaMedicineAge of onsetMovement disordersPediatricsPsychologyAtrophyPathologyParkinson's diseaseDisease

Abstract

fetched live from OpenAlex

ABSTRACT This Movement Disorder Society Genetic mutation database Systematic Review focuses on monogenic atypical parkinsonism with mutations in the ATP13A2, DCTN1, DNAJC6, FBXO7, SYNJ1, and VPS13C genes. We screened 673 citations and extracted genotypic and phenotypic data for 140 patients (73 families) from 77 publications. In an exploratory fashion, we applied an automated classification procedure via an ensemble of bootstrap‐aggregated (“bagged”) decision trees to distinguish these 6 forms of monogenic atypical parkinsonism and found a high accuracy of 86.5% (95%CI, 86.3%–86.7%) based on the following 10 clinical variables: age at onset, spasticity and pyramidal signs, hypoventilation, decreased body weight, minimyoclonus, vertical gaze palsy, autonomic symptoms, other nonmotor symptoms, levodopa response quantification, and cognitive decline. Comparing monogenic atypical with monogenic typical parkinsonism using 2063 data sets from Movement Disorder Society Genetic mutation database on patients with SNCA, LRRK2, VPS35, Parkin, PINK1, and DJ‐1 mutations, the age at onset was earlier in monogenic atypical parkinsonism (24 vs 40 years; P = 1.2647 × 10−12) and levodopa response less favorable than in patients with monogenic typical presentations (49% vs 93%). In addition, we compared monogenic to nonmonogenic atypical parkinsonism using data from 362 patients with progressive supranuclear gaze palsy, corticobasal degeneration, multiple system atrophy, or frontotemporal lobar degeneration. Although these conditions share many clinical features with the monogenic atypical forms, they can typically be distinguished based on their later median age at onset (64 years; IQR, 57–70 years). In conclusion, age at onset, presence of specific signs, and degree of levodopa response inform differential diagnostic considerations and genetic testing indications in atypical forms of parkinsonism. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.

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)0.005
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0130.014
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.328
Teacher spread0.289 · 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 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

Citations55
Published2021
Admission routes2
Has abstractyes

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