Use of multiple strategies to understand the complex genetic architecture of ADHD
Bibliographic record
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly prevalent, clinically heterogeneous neurodevelopmental disorder with a complex etiology implicating both genetic and environmental factors. Although it is well accepted that multiple genes are involved in the pathophysiology of ADHD, no genetic risk variants have been identified beyond doubt. In addition, environmental factors, including, maternal smoking and maternal exposure to stress during pregnancy have been consistently associated with this disorder.This thesis will describe multiple genetic strategies that may help reduce the "clinical heterogeneity" and "etiological complexity" of ADHD phenotype facilitating the identification of genetic variants, which may help, in dissecting pathways to the disorder.1. By using the "endophenotypes" approach and selecting COMT gene, which is firmly implicated in the modulation of brain catecholamines, we found a tentative association between Catechol-O-Methyltransferase alleles/haplotypes and the modulation of Executive Functions in ADHD children.2. We used "gene/environment interplay" i.e. stratifying ADHD children based on exposure to maternal smoking during pregnancy and maternal stress during pregnancy and investigated the implication of latrophilin3 gene LPHN3, a candidate gene consistently shown to be involved in ADHD (based on linkage studies, and candidate association studies) in increasing the risk for ADHD. This approach allowed the uncovering of differential associations between single nucleotide polymorphisms (SNPs) within the LPHN3 and a number of endophenotypes in patients according to their exposure to maternal stress during pregnancy.3. "Comorbidity" with obesity was employed as a tool to index a more homogenous subgroup of ADHD children and facilitate the identification of genetic variants implicate in ADHD. Using this scheme, we comprehensively (behaviorally and clinically) characterized children with ADHD in relation to their BMI/weight categories. We showed that, self-regulation deficits, usually hypothesized to mediate obesity in children with ADHD, are not more present in children with ADHD and obesity compared to the non-obese ADHD children. Furthermore, in a group of children not exposed to maternal smoking during pregnancy, we observed a novel association between ADHD pertinent phenotypes and a Fat Mass and Obesity (FTO) gene polymorphism that has been strongly associated to obesity by genome-wide association studies (GWAS). In summary, this research work demonstrates the usefulness of multiple strategies to reduce the clinical heterogeneity and etiological complexity of ADHD which may facilitate identification of genetic risk variants and the interaction of these with environmental factors. This in turn may help in elucidating the pathophysiology of ADHD.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| 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".