Gene-environment interplay across development as related to hazardous alcohol use in early midlife
Notice bibliographique
Résumé
Approximately 1 in 20 adults globally exhibit hazardous alcohol use (MacKillop et al., 2022), defined as alcohol consumption that increases the risk of adverse health events (MacKillop et al., 2022). Estimated economic costs of hazardous alcohol use in the United States are upwards of a quarter of a trillion dollars yearly (Manthey et al., 2021), notwithstanding the numerous associated social costs (MacKillop et al., 2022). Hazardous alcohol use remains common in early midlife (ages 30–40), a distinct developmental period relatively unexplored in psychological literature (Mehta et al., 2020); 25% of early midlife individuals report heavy episodic drinking (i.e., 5+ drinks in a session) (Schulenberg et al., 2015) and 16% of early midlife individuals meet criteria for past year alcohol use disorder (Braudt ; Grant et al., 2015). Furthermore, the prevalence of early midlife hazardous alcohol use differs between males and females, with males more likely to report alcohol problems than females (Lumpe et al., 2025). Epidemiological evidence suggests that both new onset and persistent courses of hazardous alcohol use are prevalent in early midlife (Vergés et al., 2012), providing evidence for the dynamic nature of hazardous alcohol use across the life course (Jester et al., 2016). Individuals in early midlife currently comprise the bulk of the labor force in the United States and tend to take on additional roles outside work such as parenthood and caring for older family members (Mehta et al., 2020). In previous generations, key demographic shifts such as marriage, parenthood, financial independence, and advanced education occurred more frequently in young adulthood (i.e., the 20’s), corresponding to the heightened attention this developmental period received in the literature (Mehta et al., 2020). Recently, however, individuals experience these demographic transitions at a later age (i.e., early midlife) and functioning in this developmental period can influence the remainder of an adult’s life (Mehta et al., 2020). Early midlife hazardous alcohol use has previously been associated with poorer health and well-being (Lumpe et al., 2025). Therefore, given the heightened responsibility and pressures of this age group, it is important to identify individuals at risk of hazardous alcohol use in this developmental period. It is well established that an individual’s genetic make-up and environmental exposures both contribute to physical and psychological outcomes (Dick, 2011), including hazardous alcohol use (Dick and Kendler, 2012). According to twin models, approximately 50% of variation in hazardous alcohol use across development is attributed to genetic influences (Verhulst et al., 2015). Findings from gene-environment (GE) interplay analyses suggest environments that affect access to alcohol (e.g., early substance use initiation, parental monitoring, and religiosity) moderate genetic influences on hazardous alcohol use (Dick and Kendler, 2012). Furthermore, there is evidence that environments may differentially moderate genetic influences across sex (Salvatore et al., 2017). A limitation of extant GE interplay literature is a historic focus on cross-sectional moderation without accounting for the legacy of early life exposures as moderators of genetic predispositions (Barr et al., 2016; Button et al., 2008; Dash et al., 2023). Developmental theory and evidence, however, suggest that behavioral and environmental risk factors from across the lifespan contribute to hazardous alcohol use in adult developmental periods (i.e., early midlife) (Bountress et al., 2017; Elam et al., 2018). An illustrative example is Bronfenbrenner’s Bioecological Model of human development, which provides a theoretical framework that recognizes the interplay between individual characteristics (e.g., genetic factors) and environmental contexts (e.g., socioeconomic status) across time (Bronfenbrenner, 1994). This model assumes that all environments (varying in proximity to an individual), and how an individual interacts with that environment, contributes to the development of an individual. Given this logic, early life exposures will continue to influence later life outcomes. Historically, analyses examining the interplay between genetic factors and environmental exposures to predict hazardous alcohol use only accounted for a single (or a handful of) environment(s) (Barr et al., 2016; Cooke et al., 2015; Davis and Slutske, 2018; Young-Wolff et al., 2011). Environmental exposures across development, however, are correlated therefore making it difficult to disentangle which environment (or combination of environments) is driving significant results (D'Errico et al., 2023). Recent advances in elucidating GE interplay have leveraged phenotypically rich datasets to characterize how a comprehensive measure of environmental exposures interacts with genetic predispositions to predict psychopathology (Choi et al., 2022; Kranzler et al., 2024). These analyses demonstrate that including a broad set of environmental exposures increases the percentage of variance in psychopathology accounted for when compared to GE designs with single environmental exposures (Choi et al., 2022). As yet, limited studies have included a comprehensive set of environmental variables in GE interplay analyses to predict hazardous alcohol use (Barr et al., 2022). Moreover, prior studies have not examined how the accumulation of environmental exposures across development interface with genetic predispositions to predict hazardous alcohol use in early midlife, specifically. In the proposed project, we will integrate developmental theory with advanced statistical genetic approaches to provide a comprehensive understanding of how genetic, behavioral, and environmental risk for hazardous alcohol use interface across development. Using longitudinal prospective data on early midlife participants from FinnTwin12 (N = 2,038), the National Longitudinal Study of Adolescent to Adult Health (AddHealth; N =12,238), and the Collaborative Study on the Genetics of Alcoholism (COGA; N = 1,158) samples, we will examine gene-environment interplay between genetic predispositions (latent and measured) and longitudinal behavioral and environmental risk factors to predict hazardous alcohol use in early midlife. The proposed samples are diverse in their recruitment strategies and offer a unique opportunity to generalize across populations and individuals with varying levels of risk for alcohol use disorders. Given evidence that the prevalence and heritability of early midlife hazardous alcohol use significantly differs across males and females, we will also test for sex differences in all phenotypic associations and gene-environment effects. Our aims are as follows: Aim 1. Examine associations between adolescent and young adult behavioral and environmental risk indices and early midlife hazardous alcohol use. Given previously established phenotypic associations between early life experiences and adult hazardous alcohol use, we will test the working hypothesis (H1) that behavioral and environmental risk indices across development (i.e., adolescence and young adulthood) will be associated with increased hazardous alcohol use in early midlife. Aim 2. Examine gene-environment interplay between adolescent and young adult behavioral and environmental risk factors and genetic predispositions to hazardous alcohol use in early midlife. a. Examine whether genetic predispositions for hazardous alcohol use are associated with adolescent and young adult behavioral and environmental risk indices (i.e., gene-environment correlation). Evidence suggests that an individual's behavior and environments are shaped by genetic predispositions through gene-environment correlation processes. Therefore, we will test the working hypothesis that (H2a1) in latent (i.e., twin) models, genetic influences will account for differences in behavioral and environmental risk indices across development, and (H2a2) in a polygenic framework, polygenic predispositions to externalizing behaviors and problem alcohol use in early midlife will be associated with higher behavioral and environmental risk indices in adolescence and young adulthood. b. Examine whether adolescent and young adult behavioral and environmental risk indices moderate genetic predispositions for hazardous alcohol use (i.e., gene-environment interaction). Informed by developmental theory and diathesis-stress mechanisms of gene-environment interactions, we will test the working hypothesis that (H2b1) etiological (i.e., genetic and environmental) influences on early midlife hazardous alcohol use will be moderated by behavioral and environmental risk factors across development and (H2b2) the positive association between behavioral and environmental risk indices across development and early midlife hazardous alcohol use will be stronger among those with higher polygenic risk for externalizing behaviors and problem alcohol use compared to those with lower polygenic risk.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,009 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,069 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».