Clinical and genetic analysis of Costa Rican patients with Parkinson’s disease
Bibliographic record
Abstract
Abstract Background Parkinson’s disease (PD) involves environmental risk and protective factors as well as genetic variance. Most of the research in genomics has been done in subjects of European ancestry leading to sampling bias and leaving Latin American populations underrepresented. Objective We sought to phenotype and genotype Costa Rican PD cases and controls. Methods We enrolled 118 PD patients with 97 unrelated controls. Collected information included demographics, exposure to risk and protective factors, motor and cognitive assessments. We sequenced coding and untranslated regions in familial PD and atypical parkinsonism-associated genes including GBA, SNCA, VPS35, LRRK2, GCH1, PRKN, PINK1, DJ-1, VPS13C, ATP13A2 . Results Mean age of PD probands was 62.12 ± 13.51 years, 57.6% were male. Prevalence of risk and protective factors reached 30%. Physical activity significantly correlated with better motor performance despite years of disease. Increased years of education were significantly associated with better cognitive function, whereas hallucinations, falls, mood disorders and coffee consumption correlated with worse cognitive performance. We did not identify an association between tested genes and PD or any damaging homozygous or compound heterozygous variants. Rare variants in LRRK2 were nominally associated with PD, six were located between amino acids p.1620-1623 in the C-terminal-of-ROC (COR) domain of LRRK2. Nonsynonymous GBA variants (p.T369M, p.N370S, p.L444P) were identified in three healthy individuals. One PD patient carried a pathogenic GCH1 variant, p.K224R. Conclusion This is the first study that reports on sociodemographic, risk factors, clinical presentation and genetics of Costa Rican patients with PD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".