A latent modeling approach to genotype–phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype

Abstract

This study illustrates the application of a latent modeling approach to genotype–phenotype relationships and gene×environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the mono-amine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N=192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA× physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA.

Association between monoamine oxidase gene polymorphisms and smoking behavior: A meta-analysis

“…Here, we used the dominant, recessive and codominant models to analyze the data. The OR of active group vs. inactive group was calculated in MOA-A VNTR, based on alleles with 3.5 or four repeats with greater efficiency than other alleles (Lewis et al, 2007;McGrath et al, 2012). The recessive model was applied in MAO-B for the consistent results in published articles.…”

Separating Family-Level and Direct Exposure Effects of Smoking During Pregnancy on Offspring Externalizing Symptoms: Bridging the Behavior Genetic and Behavior Teratologic Divide

“…Mechanistic studies with high quality exposure measurement have demonstrated links to disruptive behavior, deficits in executive function, and alterations in orbital frontal brain regions that subserve reward processing (Ernst, Moolchan, & Robinson, 2001; Lotfipour, et al, 2009; Wakschlag, et al, 2002). Gene×environment interactions have also been demonstrated, including the interaction of prenatal tobacco exposure with a functional polymorphism in the monoamine oxidase A gene ( MAOA ) that increases susceptibility to environmental adversity (Kim-Cohen et al 2006; Wakschlag et al 2009; McGrath et al 2012). Adoption studies, which are designed to disentangle heritability from postnatal influences (Leve et al, 2013), have further demonstrated independent effects of MDSP on child externalizing problems in exposed children reared by genetically unrelated adoptive parents (Marceau et al 2013).…”

“…The few existing studies that have specifically compared smokers who quit early in pregnancy (pregnancy quitters) with smokers who continued smoking during pregnancy (persistent pregnancy smokers) have shown significant differences in history of antisocial behavior between these groups (Wakschlag, Pickett, Middlekamp et al, 2003; Kodl & Wakschlag, 2004; Pickett, Wilkinson, & Wakschlag, 2009; McGrath et al, 2012). Importantly, while never smokers may differ from ever smokers, pregnancy quitters are also significantly different from persistent pregnancy smokers (Massey, Bublitz, Magee, et al, 2015, Massey, Estabrook, O’Brien et al, 2015).…”

Do dopamine gene variants and prenatal smoking interactively predict youth externalizing behavior?

“…We also take a spectrum approach to externalizing behavior, which enhances linkage to mechanisms, has ecological validity, and yields a highly heritable component of behavior (Farmer et al, 2009; Krueger et al, 2002; 2007). We have found that this approach captures phenotypic patterns well (McGrath et al, 2012). While our sample is fairly small relative to many G × E studies, this limitation is partially offset by the high quality measurement of exposure (prospective, repeated measure and includes biologic measures) and of externalizing behavior (multi-faceted, repeated-measures) and rigorous control for gene-environment correlation (r ge ).…”