Examination of Mitochondrial Genetic Variation in Reported Autism Spectrum Disorder
Bibliographic record
Abstract
The knowledge surrounding the neurobiology of Autism Spectrum Disorder (ASD) remains limited. Mitochondrial dysfunction appears to be involved in the etiology of ASD, given evidence indicating disrupted oxidative phosphorylation and increased oxidative stress in ASD. Therefore, variation within mitochondrial genes may contribute to ASD. The objective of this study is to examine whether mitochondrial genetic variation is associated with ASD risk. N = 172 reported autism cases and 9854 controls ages 9-10 from the Adolescent Brain Cognitive Development (ABCD) study were selected for analysis. Tractor software was used to conduct an ancestry-aware logistic regression for reported autism diagnosis and nuclear-encoded mitochondrial SNPs. Next, a meta-analysis using the ABCD European sub-sample, and the Psychiatric Genetics Consortium ASD sample was conducted using METAL. Finally, mtDNA haplogroups were analyzed for association with reported ASD diagnosis using the Chi-squared test. No nuclear-encoded mitochondrial SNPs or mtDNA haplogroups were significantly associated with reported ASD diagnosis.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".