Candidate Gene Polymorphisms and Their Association with TCD Velocities in Children with Sickle Cell Disease.
Bibliographic record
Abstract
Abstract Ischemic stroke occurs in 11% of patients with sickle cell disease (SCD) by age 20. The STOP and STOP-II trials showed that the risk of ischemic stroke increases with Transcranial Doppler (TCD) velocities in major intracranial arteries in children with SCD 2–16 years of age, and that the risk in children with abnormal velocities (>200 cm/sec) can be significantly reduced by prophylactic transfusions. Risk factors for development of high TCD phenotype are not clearly established. In an ancillary study to STOP/STOP-II, we analyzed 28 polymorphisms in 20 candidate genes for association with elevated TCD velocity. DNA was extracted from 130 patients randomized in the STOP trial, all of whom had abnormal TCD velocities, and from 355 patients who were screened for STOP II at 8 participating centers. None of the subjects from either trial had histories of overt stroke when they were screened. Samples from STOP subjects were anonymized according to an IRB-approved plan; informed consent/assent was obtained from subjects screened for the STOP-II trial. Hb phenotype was ascertained by HPLC. High throughput genotyping was performed using the MassARRAY™ System (Sequenom Inc., San Diego, CA) at Mass U. TCD status was classified as normal (<170 cm/sec) or not normal (>170 cm/sec) using the average of all TCDs on each patient, excluding any TCDs obtained after starting transfusion (median: 2 TCD exams, range 1–16). Genotyping results for each SNP were also reduced to a binary classification (mutation present or absent) by combining heterozygous subjects with those homozygous for the mutation. Conditional logistic regression was employed to model the probability of having at least 1copy of the mutant allele as a function of TCD status stratified on age class. Under this approach, the odds ratio (OR) relating TCD status to genotype is assumed to be the same at all ages but the prevalence of abnormal or conditional TCD is allowed to vary with age. Seven SNPs were excluded from analyses: all subjects studied (479) were homozygous for the common allele for 5 SNPs, and only 2 subjects were heterozygous for the minor allele for 2 SNPs. The prevalence of abnormal TCD varied with age; the highest prevalence was found in 8–9 year old subjects. Only one SNP, VCAM G1238C, had a significant OR of 0.6 (p=0.03) suggesting this SNP is protective from high TCD. The same polymorphism was found to be protective from stroke with an OR of 0.3 in a different cohort of patients by Taylor et al (Blood, 100:4303–9, 2002). Several published studies have reported on association of stroke with candidate gene polymorphisms with differing results. This is the first large scale study of the association of abnormal TCD (stroke risk) with genetic polymorphisms. To our knowledge, it is also the first confirmatory genetic association study in SCD and cerebrovascular disease in a different population of subjects. Functional analyses of this polymorphism and association of stroke and candidate gene polymorphisms in this cohort are planned.
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".