Adaptive, behavioral, and cognitive outcomes in individuals with fragile X syndrome with varying autism severity
Bibliographic record
Abstract
Abstract This study aimed to determine the association between severity of autism spectrum disorder (ASD) and cognitive, behavioral, and molecular measures in individuals with fragile X syndrome (FXS). Study inclusion criteria included individuals with FXS and (1) age 6–40 years, (2) full‐scale IQ < 84, and (3) language ≥3‐word phrases. ASD symptom severity was determined by Autism Diagnostic Observation Schedule‐2 (ADOS‐2). Other measures identified non‐verbal IQ, adaptive skills, and aberrant behaviors. Molecular measures included blood FMR1 and CYFIP1 mRNA levels, FMRP and MMP9 levels. Analysis of variance (ANOVA) and Spearman's correlations were used to compare ASD severity groups. Data from 54 individuals was included with no/mild ( N = 7), moderate ( N = 18), and severe ( N = 29) ASD. Individuals with high ASD severity had lower adaptive behavior scores (47.48 ± 17.49) than the no/mild group (69.00 ± 20.45, p = 0.0366); they also had more challenging behaviors, lethargy, and stereotypic behaviors. CYFIP1 mRNA expression levels positively correlated with the ADOS‐2 comparison score( r 2 = 0.33, p = 0.0349), with no significant correlations with other molecular markers. In conclusion, autism symptom severity is associated with more adverse cognitive and adaptive skills and specific behaviors in FXS, whereas CYFIP1 mRNA expression levels may be a potential biomarker for severity of ASD in FXS.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".