Elevated Plus Maze Test

Suppose m phenotypes are measured as indicators of one trait, e.g., individual symptoms within a disorder, items within a test, or multiple measures of one trait using different instruments (e.g., open-field test, a light-dark box, and an elevated plus maze to measure anxiety in mice). Rather than combining these m phenotypes into one general phenotype, we test the association between all m phenotypes and all n genotyped genetic variants (GVs) using a statistically appropriate method (e.g., linear or logistic regression). Let p(1)…p(m) be the ascending p-values of the m phenotypes for a given GV. TATES combines within each GV the m phenotype-specific p-values to obtain one overall trait-based p-value P_T as follows: where m_e denotes the effective number of independent p-values of all m phenotypes for a given GV, and m_ej the effective number of p-values among the top j p-values, where j runs from 1 to m, and p_j denotes the j^th p-value in the list of ordered p-values. P_T is thus the smallest weighted p-value, associated with the null hypothesis that none of the phenotypes is associated with the GV, and the alternative hypothesis that at least one of the phenotypes is associated with the GV.
Following Li et al [15] (link), we obtain an estimate of the effective number of p-values m_ej through a correction based on eigenvalue decomposition of the m×m correlation matrix ρ between the p-values associated with the m phenotypes. The effective number of p-values m_ej for the top j p-values is calculated as: where j is the number of top j p-values, λ_i denotes the i^th eigenvalue, and I( λ_i−1) is an indicator function taking on value 0 if λ_i≤1 and 1 if λ_i>1. That is, the effective number of p-values m_ej is calculated as the observed number of p-values j minus the sum of the difference between the eigenvalues λ_i and 1 for those eigenvalues λ_i>1. If the j phenotypes are all uncorrelated, then all j eigenvalues equal 1, and m_ej = j−0 = j. In contrast, if the j phenotypes are perfectly correlated, then the first eigenvalue equals j, and the other eigenvalues equal 0, rendering m_ej = j−(j−1) = 1 (i.e., j perfectly correlated phenotypes represent only 1 unique unit of information). In practice, phenotypes show intercorrelations of variable magnitude (but not 0 or 1), so the effective number of p-values m_ej will usually be smaller than j, but greater than 1. Note that m_e is equal to m_ej for the case that j = m, i.e., when the selection of top phenotypes covers all phenotypes.

The elevated plus maze test (EPMT) was used to assess anxiety-like behaviors. The apparatus used in this experiment included two closed arms (50 × 10 cm, with 40 cm walls), two open arms (50 × 10 cm, without walls), and a center platform (10 × 10 cm). Each mouse was gently placed on the central platform facing the closed arms and was allowed to freely explore the arena for 6 min. The time spent in the open arms and track movements of mice were recorded by a video camera system (SMART 3.0; Panlab S. L., Barcelona, Spain). The criterion for entering an open arm was defined as 50% of the body being positioned within the arm.

After drug treatment, the mice were sequentially subjected to a series of behavioral tests, including an open-field experiment, including an open field test (OFT), elevated plus maze test (EPMT), Y-maze test (YMT), sucrose preference test (SPT), tail suspension test (TST), and Forced swimming test (FST). All the behavioral tests were carried out during the light phase (9:00–21:00) on days 30–35. And the interval between behavioral tests was 24 h.