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Record W2090941748 · doi:10.1002/ajhb.20565

Prevalence of dopamine and 5HT2C receptor polymorphisms in Amerindians and in an urban population from Argentina

2006· article· en· W2090941748 on OpenAlexaff
Verónica L. Martínez‐Marignac, N. O. Bianchi

Bibliographic record

VenueAmerican Journal of Human Biology · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGenotypeAlleleDemographyAllele frequencyConfoundingPopulationGenotype frequencyGeneticsBiologyMedicineGeneInternal medicine

Abstract

fetched live from OpenAlex

We report on the frequency of DRD2A1, DRD3A1, DRD4/2R-10R, and 5HT2CA1 variants in the population of the city of La Plata (Argentina) and in Amerindians from Argentina, Paraguay, and Chile. In the Amerindian sample, the prevalence of DRD2A1 and DRD4/4R variants were, respectively, significantly lower and significantly higher than frequencies reported in other Native Americans. Comparison of average allele and genotype frequencies between La Plata and Amerindians showed significant differences for 5HT2CA1 and DRD4. As La Plata is a population with predominant European and Amerindian components, we used mtDNA and Y-specific markers to subdivide the La Plata sample into two strata: Amerindian La Plata and non-Amerindian La Plata. Significant variations between the two strata were detected for DRD2A1, DRD3A1, and DRD4/4R allele frequencies, and for the homozygous DRD4/4R/4R genotype. Several controversial reports suggest a possible association between a variant of DRD and/or 5HT2C receptor genes and the clinical expression of several psychiatric disorders. We suggest that ethnic variations in the prevalence of the allelic forms of these genes may be a confounding factor to be taken into consideration in studies of association between dopaminergic and serotonergic receptor genotypes and neuropsychiatric and mood disorders.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.285
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

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