Early Onset Dementia: Experience from Thailand
Bibliographic record
Abstract
BACKGROUND: Early-onset dementia (EOD) is a uncommon form of dementia that afflicts people before age 65. Only a few studies analyzing the genetics of EOD have been performed in Thai population. EOD remains a challenge due to the diverse genetic and clinical heterogeneity of these diseases. The aim of this study was to investigate the genetic spectrum of Thai EOD and those with familial history of dementia. METHOD: 150 subjects with EOD AND 18 individuals with familial dementia were recruited. Targeted next generation (NGS) analyses were performed to screen 38 genes associated with dementia. RESULT: Subject characteristics were demonstrated in table 1. Fifteen had pathogenic variants. Among pathogenic (47%) and likely pathogenic (53%) variants, 5 (33.33%) were in PSEN1 (c.417G>T, p.Met139Ile), (c.344A>G, p.Tyr115Cys), (c.817G>A, p.Glu273Lys), (c.817G>A, p.Glu273Lys), (c.485T>C, p.Ile162Thr)); 2 (13.33%) in CSF1R (c.704T>G, p.Val235Gly), (c.2522A>G, p.Tyr841Cys); 1(6.67%) each in ABCA7 (c.5571-1G>C, p.?), SNCB (c.372G>A, p.Gln124=), SORL1 (c.2212G>A, p.Gly738Arg), APP (c.2149G>A, p.Val717Ile), VAPB (c.301G>T, p.Asp101Tyr), GRN (c.276C>A, p.Cys92Ter), SOD1 (c.143T>C, p.Val48Ala), and NOTCH3 (c.1630C>T, p.Arg544Cys). Among these, the PSEN1 variant c.817G>A (p.Glu273Lys) had not previously been reported. 61 had variants of uncertain significance (VUS). Graphs 1-3 showed results of NGS for dementia in the whole cohort, in those with pathogenic variants, and in those with VUS. CONCLUSION: Our study demonstrated the genetic spectrum of EOD and familial dementia in Thai patients. The utilization of next-generation sequencing could help deciphering the genetic causes of Alzheimer's disease. The genetic testing of known causal genes in EOD patients can help make a precise diagnosis. We acknowledged Thailand Science Research and Innovation for supporting this study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".