Interaction between serum BDNF and aerobic fitness predicts recognition memory in healthy young adults

Abstract

Convergent evidence from human and non-human animal studies suggests aerobic exercise and increased aerobic capacity may be beneficial for brain health and cognition. It is thought growth factors may mediate this putative relationship, particularly by augmenting plasticity mechanisms in the hippocampus, a brain region critical for learning and memory. Among these factors, glucocorticoids, brain derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), and vascular endothelial growth factor (VEGF), hormones that have considerable and diverse physiological importance, are thought to effect normal and exercise-induced hippocampal plasticity. Despite these predictions, relatively few published human studies have tested hypotheses that relate exercise and fitness to the hippocampus, and none have considered the potential links to all of these hormonal components. Here we present cross-sectional data from a study of recognition memory; serum BDNF, cortisol, IGF-1, and VEGF levels; and aerobic capacity in healthy young adults. We measured circulating levels of these hormones together with performance on a recognition memory task, and a standard graded treadmill test of aerobic fitness. Regression analyses demonstrated BDNF and aerobic fitness predict recognition memory in an interactive manner. In addition, IGF-1 was positively associated with aerobic fitness, but not with recognition memory. Our results may suggest an exercise adaptation-related change in the BDNF dose-response curve that relates to hippocampal memory.

Keywords: ACSM; American College of Sports Medicine; BDNF; BMI; Cardiovascular fitness; DMS; ELISA; Hippocampus; IGF-1; MTL; OLS; RER; RERmax; Recognition memory; SMT; VEGF; body mass index; brain-derived neurotrophic factor; delayed matching-to-sample; enzyme-linked immunosorbent assay; insulin-like growth factor-1; max; maximum observed respiratory exchange ratio; medial temporal lobes; ordinary least squares; peak; peak rate of oxygen consumption in mL per kg of body weight per min, measured during test; rate of maximal oxygen consumption in mL per kg of body weight per min; respiratory exchange ratio; subsequent memory test; vascular endothelial growth factor.

Figure 1

Recognition memory task. Adapted from Schon et al. [20], participants were first shown a series of 144 pseudo-randomized, trial unique but content similar outdoor scenes in the context of a delayed match to sample (DMS) working memory paradigm. Approximately 15 minutes later, participants were administered a surprise subsequent memory test (SMT) where they were shown all 144 DMS images, plus 144 lure images, and asked to rate their recognition confidence. Participants were blind to the ratio of old to new images.

Figure 2

Summary of raw VO₂ peak data and fitness percentile transformation. Boxplots and raw data points from our sample are overlaid on histograms of simulated population distributions of VO₂ max and fitness percentile based on [29]. The goal of transforming VO₂ peak to fitness percentile was to compare individuals on an age and gender independent scale. Boxplots indicate quartiles and medians for VO₂ peak data for (top) female and (middle) male participants, and fitness percentile data for both genders (bottom). Individual data points are jittered slightly in the y dimension to appear more visually distinct.

Figure 3

Summary of BDNF and IGF-1 findings. Top: maximum likelihood beta regression models of subsequent memory accuracy by resting serum brain-derived neurotrophic factor (BDNF) and insulin-like growth factor-1 (IGF-1). Corrected accuracy is defined as the proportion of subsequent memory test (SMT) stimuli correctly identified as old less the proportion of SMT lure stimuli incorrectly identified as old. The top-left panel shows a significant negative association between BDNF and SMT accuracy. Bottom: ordinary least squares (OLS) regression models of BDNF and IGF-1 by cardiovascular fitness percentile. Outcome variables were modeled on the log scale. The bottom-right panel shows strong evidence of a positive association between IGF-1 and fitness. Aggregated gray lines represent 95% confidence interval estimates for each regression.

Figure 4

Interaction between BDNF and fitness on subsequent memory accuracy. SMT corrected accuracy was modeled, using beta regression, as a function of resting serum BDNF, cardiovascular fitness percentile, and their interaction, adjusting for confounding covariates sex, an indicator of aerobic threshold (RER ≥ 1.15), and assay round. The top panel conveys the shape of a strong, positive interaction between continuous variables BDNF and fitness percentile. For example, at low fitness, increasing serum BDNF clearly predicts lower SMT accuracy. As fitness increases, BDNF begins to positively predict subsequent memory accuracy, with an estimated inflection point around the 75^th aerobic fitness percentile. Bottom panels show effects of covariates on the regression at mean BDNF and 50^th fitness percentile.