Oxytocin and its association with reward-based personality traits: A multilocus genetic profile (MLGP) approach. (1st February 2019)

• Record Type: Journal Article
• Authors: Davis, Caroline; Zai, Clement C.; Adams, Nicole; Bonder, Revi; Kennedy, James L.
• Is Part Of: Personality and individual differences. Volume 138(2019)
• Page Start: 231
• Page End: 236
• Publication Date: 2019-02-01
• Subjects: Oxytocin -- OXTR -- CD38 -- Reward -- Personality; Personality -- Periodicals; Individuality -- Periodicals; Individuality -- Periodicals; Personality Development -- Periodicals; Personnalité -- Périodiques; Individualité -- Périodiques; 155.205
• DOI: 10.1016/j.paid.2018.09.002
• Languages: English
• ISSNs: 0191-8869

Abstract

Abstract: Oxytocin is an evolutionarily ancient neuropeptide that aids in the regulation of many survival behaviors including affiliation, creativity, and reproduction. The oxytocin system also converges with mesolimbic dopamine pathways and thereby plays a role in reward motivation and hedonic capacity. The present study investigated genetic markers of two oxytocin genes in relation to reward-based personality traits. Since individual polymorphic loci typically contribute only a small proportion of phenotypic variance, we used a MLGP quantitative approach whereby genetic variants are aggregated into composites that reflect a polygenic liability. Eleven single nucleotide polymorphisms (SNPs) on the oxytocin receptor gene ( OXTR ), and two SNPs on the cluster-of-differentiation 38 gene ( CD38 ) were selected for genotyping. Community-recruited healthy adults (N = 426) participated in the study. Results identified 4 OXTR and 2 CD38 SNPs with a significant genotypic association to the reward-based traits. The MLGP accounted for greater phenotypic variance than any of the SNPs individually. Findings confirm links between the oxytocin system and reward responsiveness —an important relationship in the preservation of evolutionarily significant survival behaviors. Future research would benefit from targeting additional SNPs that influence oxytocin levels in the brain, in order to enhance the predictive utility of the current MLGP.