Recent Advances in Biomarkers of Addiction: A Narrative Review
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Background & Aims: There is a growing need to identify and treat individuals with addictive disorders with the goal of improving outcomes for some of the most prevalent and stigmatized illnesses. Recently, international scientific advances have trended towards developing dimensional approaches in our understanding of addiction and addictive disorders. This has been driven largely by the search for biomarkers of addiction—an important example of the thrust to translate advances in neurobiology into clinical psychiatric practice. The present review summarizes recent advances in the pursuit of biomarkers of addiction. Design: Narrative review. Findings: The search for candidate biomarkers of addiction has explored several interdisciplinary modalities. Novel structural and functional neuroimaging techniques show promise as biomarkers of several addictive syndromes. The fields of proteomics and genomics are advancing our ability to identify genes and aberrant proteins involved in the physiology of addiction. Conclusions: Several promising brain, plasma, genetic, and epigenetic indices have been recently identified as putative biomarkers of addiction. For many, there are documented clinical applications in substance use disorders and behavioral addictions. Further research aiming to refine biological and psychological markers into sophisticated risk assessment tools for addictive disorders is on the horizon. Contexte et objectifs: Il existe un besoin croissant d’identifier et de traiter les personnes souffrant de troubles addictifs dans le but d’améliorer les résultats de certaines des maladies les plus répandues et les plus stigmatisées. Récemment, les avancées scientifiques internationales ont eu tendance à développer des approches dimensionnelles dans notre compréhension de la toxicomanie et des troubles addictifs. Cela a été largement motivé par la recherche de bio-marqueurs de la toxicomanie - un exemple important de la volonté de traduire les progrès de la neurobiologie en pratique clinique psychiatrique. La présente revue résume les avancées récentes dans la recherche de bio-marqueurs de la toxicomanie. Conception: revue narrative: Résultats: La recherche de candidats comme bio-marqueurs de la toxicomanie a exploré plusieurs modalités interdisciplinaires. De nouvelles techniques de neuro imagerie structurale et fonctionnelle sont prometteuses en tant que bio-marqueurs de plusieurs syndromes addictifs. Les domaines de la protéomique et de la génomique font progresser notre capacité à identifier les gènes et les protéines aberrantes impliqués dans la physiologie de la toxicomanie. Conclusions: Plusieurs indices prometteurs du cerveau, du plasma, génétiques et épigénétiques ont récemment été identifiés comme des bio-marqueurs putatifs de la dépendance. Pour beaucoup, il existe des applications cliniques documentées dans les troubles liés à la consommation de substances et les dépendances comportementales. D’autres recherches visant à affiner les marqueurs biologiques et psychologiques en outils sophistiqués d’évaluation des risques de troubles addictifs sont à l’horizon.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it