Modeling Depression in Mice to Identify Genetic Mechanisms of Mood Disorder

1. Modeling Depression in Mice to Identify Genetic Mechanisms of Mood Disorder Cristina Santos1, Brooke Miller2, Matthew Pletcher2, Andrew Su4, Lisa Tarantino5, and Tim Wiltshire1 1University of North Carolina at Chapel Hill, Division of Pharmacotherapy and Experimental Therapeutics 2Department of Molecular Pharmaceutics The Scripps Institute Jupiter, Florida 3Genomics Institute of Novartis Research Foundation La Jolla, California 4University of North Carolina at Chapel Hill, Department of Psychiatry Background Evidence from twin studies support the role of genetics in depression. Inbred mouse strains are good models to study the genetic basis of disease since mice within the same strain are genetically similar. By comparing inter-strain phenotypic differences and correlating each trait with known genotypes, we can identify genomic regions associated with depression known as quantitative trait loci (QTL). We hypothesize that regions associated with variable neurobiochemical levels and behavior contain candidate genes involved in depression. Methods Depressive Behavior: Mice were suspended in air by its tail and percent time spent immobile within 5 minutes was measured as an index of depressive behavior (n=10/strain). Neurobiochemical Levels:Analytes proposed to have a significant role in depression were simultaneously measured in brain and serum using a reverse-array ELISA. Chip was spotted at a range 0-2mg/mL of brain lysates. QTL Identification: Genotype information obtained for over 600,000 SNPs at a density of one SNP every 4.3 kB (Ding et al 2009) was used in an efficient mixed model association (Kang et al 2008) and haplotype association mapping algorithms (Pletcheret al 2004) to identify putative QTLs. Only QTLs that had 1/1000 likelihood to be false positive (-logP>3) were considered significant. i Results 1. Neurobiochemical Levels 3.Genes Associated with Neurobiochemical Levels and Depressive Behavior Fig3a Fig3c Likelihood of Association (-logP) Fig3d Fig3b Cdh2: candidate gene within QTL on Chr18 Igsf4a: candidate gene within QTL on Chr9 Fig3a-d: Genome-wide association plots display QTLs or genomic regions associated with depressive behavior (Fig3a and Fig3c) and neurobiochemical levels (Fig3b and Fig3d). Fig3a-b: Region on chr18 (Chr18: 15.6-18.5) was significantly correlated with depressive behavior (-logP>5) as well as levels of glutathione reductase (-logP>5, Fig3b ), PAQR8, MCH, NR3C1, and APOD (data not shown). Genes within candidate QTL on chr 18 include Cdh2 and 4921533I20Rik . Fig3c-d:Region on chr9 (Chr9: 46.3-47.6) was significantly correlated with depressive behavior (-logP>6) and levels of glutamate decarboxylase67 (-logP>5, Fig3d). Igsf4a (also known as Cadm1)and 2900052N01Rik are the two genes found within putative depressive QTL on chr9. Table1lists 31 neurobiochemical markers that were measured by ELISA.Figure1shows differential levels of GAD67, APOD, and PAQR8 between strains which suggests role of genetics in modulating neurobiochemical levels. 2.Variable Depressive Behavior Discussions 4.Cdh2 and Igsf4a are Involved in Cell Adhesion • Modeling depression in • mice can identify • mechanisms underlying • disease and treatment • Genes associated with • behavior and biochemical • levels are likely to have a • critical role in depression. Fig4a Fig4b Fig4a:Cdh2 and Igsf4a are cell adhesion molecules in the neural system. Pathway was derived from KEGG database Fig4b:Interaction of Cadm1 (also known as Igsf4a)with other molecules like IL22 and progesterone can mediate behavior. Cadm1 pathway was derived from Ingenuity Figure2shows greater inter-strain differences in depressive behavior, therefore response in this assay is likely to be modulated by genes. Immobility is an index of depressive behavior since it models “hopelessness” and is reduced by anti-depressants (data not shown).