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Record W3083214683 · doi:10.1111/acer.14450

Influence of Comorbid Psychiatric Disorders on the Risk of Development of Alcohol Dependence by Genetic Variations of <i>ALDH2</i> and <i>ADH1B</i>

2020· article· en· W3083214683 on OpenAlexaff
Mitsuru Itoh, Tomoko Yonemoto, Fumihiko Ueno, Chie Iwahara, Yosuke Yumoto, Hideki Nakayama, Hitoshi Maesato, Mitsuru Kimura, Sachio Matsushita

Bibliographic record

VenueAlcoholism Clinical and Experimental Research · 2020
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsADH1BALDH2PsychiatryAlcohol use disorderMedicineAntisocial personality disorderClinical psychologyAlcohol dependenceAttention deficit hyperactivity disorderPsychologyAlcoholGenotypePoison controlEnvironmental healthInjury preventionGeneticsBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Inactive aldehyde dehydrogenase-2 (ALDH2) is a well-known deterrent to the development of alcohol use disorder (AUD), and however, some individuals with inactive ALDH2 do go on to develop AUD. These alcoholics are likely to have strong risk factors for the development of this disorder. Using a model of alcoholics with inactive ALDH2 (the AIA model), we investigated the unique characteristics of alcoholics with inactive ALDH2 in an attempt to identify the risk factors for AUD. In this study, we focused on comorbid psychiatric and personality disorders as potential risk factors for AUD. METHODS: The subjects were 103 male alcoholics with inactive ALDH2 (AIAs), 87 age- and ADH1B genotype-matched alcoholics with active ALDH2 (AAAs) and 200 age-matched healthy men. The alcoholics were divided into 4 subgroups according to their ALDH2 and ADH1B genotypes (inactive ALDH2 vs. active ALDH2, usual ADH1B vs. superactive ADH1B). To assess the participants' comorbid psychiatric disorders, we conducted semi-structured interviews using the Japanese translation of SSAGA version 2. We compared the prevalence of comorbid psychiatric and personality disorders among groups with different combinations of the ALDH2 and ADH1B genotypes. RESULTS: The prevalence of attention-deficit/hyperactivity disorder (ADHD) was significantly higher in the AIAs with usual ADH1B than in the other 3 subgroups of alcoholics. In contrast, the prevalence rates of agoraphobia and panic disorder were significantly lower in the AIAs with superactive ADH1B than in the other 3 subgroups of alcoholics. CONCLUSIONS: This study suggested that (i) ADHD is a risk factor for AUD, consistent with previous reports; (ii) agoraphobia and panic disorder may have deterrent effects against the development of AUD in individuals with inactive ALDH2, probably attributable to the similarity between the symptoms of agoraphobia and panic disorder and the adverse reactions to consumption of alcohol in subjects with inactive ALDH2.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.023
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.179
GPT teacher head0.476
Teacher spread0.296 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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