Shared Genetic Control of Brain Activity During Sleep and Insulin Secretion: A Laboratory-Based Family Study

Abstract

Over the past 20 years, a large body of experimental and epidemiologic evidence has linked sleep duration and quality to glucose homeostasis, although the mechanistic pathways remain unclear. The aim of the current study was to determine whether genetic variation influencing both sleep and glucose regulation could underlie their functional relationship. We hypothesized that the genetic regulation of electroencephalographic (EEG) activity during non-rapid eye movement sleep, a highly heritable trait with fingerprint reproducibility, is correlated with the genetic control of metabolic traits including insulin sensitivity and β-cell function. We tested our hypotheses through univariate and bivariate heritability analyses in a three-generation pedigree with in-depth phenotyping of both sleep EEG and metabolic traits in 48 family members. Our analyses accounted for age, sex, adiposity, and the use of psychoactive medications. In univariate analyses, we found significant heritability for measures of fasting insulin sensitivity and β-cell function, for time spent in slow-wave sleep, and for EEG spectral power in the delta, theta, and sigma ranges. Bivariate heritability analyses provided the first evidence for a shared genetic control of brain activity during deep sleep and fasting insulin secretion rate.

Figure 1

Pedigree. The shaded symbols represent the family members who completed the study. Squares represent men, circles represent women. The index subject is indicated with an arrow. The crossed-out symbols indicate deceased family members.

Figure 2

For glucose, insulin, C-peptide, and ISR, the upper panel illustrates the mean (± SEM) concentrations measured at each time point of the OGTT. Gray vertical bars in the lower panels show heritability for each time point. Fixed covariates included age and sex. BMI was included in the model if it significantly (P < 0.1) impacted the results based on a LRT comparing the models with and without BMI. Error bars are shown for all heritability estimates greater than zero. BL, baseline. *P < 0.05; **P < 0.01.

Figure 3

Heritability estimated for sleep variables (upper panel) and spectral analysis results (bottom panel). Sleep stages (N1, N2, SWS, and REM) are expressed as percentage of total sleep time. NREM total, delta, theta, alpha, and sigma power were computed in the first 6 h of sleep. Fixed covariates included age and sex. Additional covariates including BMI and psychotropic medications were included in the model if they significantly (P < 0.1) impacted the results based on a LRT comparing the models with and without these covariates. Error bars are shown for all estimates greater than zero.

Figure 4

A heat map illustrating the genetic correlations calculated with SOLAR using the pedigree relationships. Blue indicates negative correlations and red indicates positive correlations. Although the point estimates are large for several trait pairs due to the small sample size, the SE are also sizeable and the only correlation reaching significance is delta power/ISR (rhoG = 1, SE = 0.46, P = 0.0062), indicated with an asterisk.

Figure 5

Four possible causal models underlying the observed relationship between glucose metabolism and NREM sleep quality. The panels illustrate the following models in which genetic effects govern NREM sleep quality that in turn influences glucose metabolism (A), genetic effects govern glucose metabolism which in turn influences NREM sleep quality (B), NREM sleep quality and glucose metabolism are coregulated through shared genetic effects (C), and NREM sleep quality and glucose metabolism are coregulated through shared genetic effects and influence each other (D). Our genetic correlation results rule out the models shown in panels A and B. Taken together with experimental findings, our data suggests the most likely model underlying the relationship between NREM sleep and glucose metabolism is shown in panel D.