Finite mixture regression model analysis on antipsychotics induced weight gain: investigation of the role of the serotonergic genes

Eur Neuropsychopharmacol. 2013 Mar;23(3):224-8. doi: 10.1016/j.euroneuro.2012.05.008. Epub 2012 Jul 26.

Abstract

Antipsychotics-induced weight gain is a complex phenomenon with a relevant underlying genetic basis. Polymorphisms of serotonin receptors and related proteins were genotyped in 139 schizophrenia patients and incorporated as covariates in a mixture regression model of weight gain in combination with clinical covariates. The HTR1D rs6300 polymorphism was showing a slight significance conferring risk for obesity (heavy weight gain group) under additive model. After correcting for multiple testing all the genetic predictors were non-significant, however the clinical predictors were associated with the risk of heavy weight gain. These findings suggest a role of ethnicity and olanzapine in increasing the risk for obesity in the heavy weight gain group and haloperidol protecting against heavy weight gain. The mixture regression model appears to be a useful strategy to highlight different weight gain subgroups that are affected differently by clinical and genetic predictors.

MeSH terms

  • Adult
  • Antipsychotic Agents / adverse effects*
  • Black or African American / genetics
  • Female
  • Genotype
  • Humans
  • Male
  • Middle Aged
  • Obesity / chemically induced*
  • Obesity / ethnology
  • Obesity / genetics
  • Polymorphism, Single Nucleotide
  • Receptors, Serotonin / genetics*
  • Regression Analysis
  • Risk
  • Schizophrenia / drug therapy*
  • Serotonin Plasma Membrane Transport Proteins / genetics
  • Tryptophan Hydroxylase / genetics
  • Weight Gain / ethnology
  • Weight Gain / genetics*
  • White People / genetics

Substances

  • Antipsychotic Agents
  • Receptors, Serotonin
  • SLC6A4 protein, human
  • Serotonin Plasma Membrane Transport Proteins
  • TPH1 protein, human
  • Tryptophan Hydroxylase