Chronic nicotine differentially affects murine transcriptome profiling in isolated cortical interneurons and pyramidal neurons.

BACKGROUND: Nicotine is known to differentially regulate cortical interneuron and pyramidal neuron activities in the neocortex, while the underlying molecular mechanisms have not been well studied. In this study, RNA-sequencing was performed in acutely isolated cortical somatostatin (Sst)- positive interneurons and pyramidal neurons (Thy1) from mice treated with systemic nicotine for 14 days. We assessed the differentially expressed genes (DEGs) by nicotine in Sst- or Thy1- neurons, respectively, and then compared DEGs between Sst- and Thy1- neurons in the absence and presence of nicotine. RESULTS: In Sst-neurons, the DEGs by nicotine were associated with glycerophospholipid and nicotinate and nicotinamide metabolism; while in Thy1-neurons those related to immune response and purine and pyrimidine metabolisms were affected. Under basal condition, the DEGs between Sst- and Thy1- neurons were frequently associated with signal transduction, phosphorylation and potassium channel regulation. However, some new DEGs between Sst- and Thy1- neurons were found after nicotine, the majority of which belong to mitochondrial respiratory chain complex. CONCLUSIONS: Nicotine differentially affected subset of genes in Sst- and Thy1- neurons, which might contribute to the distinct effect of nicotine on interneuron and pyramidal neuron activities. Meanwhile, the altered transcripts associated with mitochondrial activity were found between interneurons and pyramidal neurons after chronic nicotine.

Estimation of Variance Components in the Mixed-Effects Models: A Comparison Between Analysis of Variance and Spectral Decomposition.

The mixed-effects models with two variance components are often used to analyze longitudinal data. For these models, we compare two approaches to estimating the variance components, the analysis of variance approach and the spectral decomposition approach. We establish a necessary and sufficient condition for the two approaches to yield identical estimates, and some sufficient conditions for the superiority of one approach over the other, under the mean squared error criterion. Applications of the methods to circular models and longitudinal data are discussed. Furthermore, simulation results indicate that better estimates of variance components do not necessarily imply higher power of the tests or shorter confidence intervals.