Subjecting Elite Athletes to Inspiratory Breathing Load Reveals Behavioral and Neural Signatures of Optimal Performers in Extreme Environments

Background: It is unclear whether and how elite athletes process physiological or psychological challenges differently than healthy comparison subjects. In general, individuals optimize exercise level as it relates to differences between expected and experienced exertion, which can be conceptualized as a body prediction error. The process of computing a body prediction error involves the insular cortex, which is important for interoception, i.e. the sense of the physiological condition of the body. Thus, optimal performance may be related to efficient minimization of the body prediction error. We examined the hypothesis that elite athletes, compared to control subjects, show attenuated insular cortex activation during an aversive interoceptive challenge. Methodology/Principal Findings: Elite adventure racers (n = 10) and healthy volunteers (n = 11) performed a continuous performance task with varying degrees of a non-hypercapnic breathing load while undergoing functional magnetic resonance imaging. The results indicate that (1) non-hypercapnic inspiratory breathing load is an aversive experience associated with a profound activation of a distributed set of brain areas including bilateral insula, dorsolateral prefrontal cortex and anterior cingulated; (2) adventure racers relative to comparison subjects show greater accuracy on the continuous performance task during the aversive interoceptive condition; and (3) adventure racers show an attenuated right insula cortex response during and following the aversive interoceptive condition of non-hypercapnic inspirator

Temporal Growth Variation in High-Elevation Forests: Case Study of Polylepis Forests in Central Andes

Polylepis species form the dominant high-altitude forests in the tropicalAndes, one of the most vulnerable regions to future climate change scenarios. Thestudy of the growth of these forests provides useful information about their ontogenyand the environmental conditions where they develop. The identification ofgrowth patterns is relevant for understanding the dynamics of the forests in responseto climatic variables. In this chapter, we present a brief review of dendroecologicalstudies on Polylepis species. We also developed for the first time in the centralAndes of Peru three new Polylepis ring-width chronologies together with a diametergrowth modeling for the following species: Polylepis rodolfo-vasquezii, Polylepisrugulosa, and Polylepis tarapacana. Dendrochronological techniques together with a biologically based model help us to obtain information on forestry traits ofPolylepis species. P. rodolfo-vasquezii to growth response to summer temperature ofthe current growth period determined radial growth, whereas spring and summerprecipitation from the previous growth period determined the radial growth in P.rugulosa and P. tarapacana, respectively. The radial growth models indicated differencesin the growth of the three Polylepis species with P. rodolfo-vasquezii reachingthe highest rate (0.11 cm/yr), while P. tarapacana showed the lowest (0.08 cm/yr). Due to the low growth rates of these Polylepis species, long periods (>100 years)are required to establish and provide ecosystem services. As these forests face thechallenge of climate change and anthropogenic pressure, there is a clear need toobtain precise information in order to formulate guidelines for the conservation ofthese forests, and the application of dendroecology is indispensable in this context.Fil: Requena Rojas, Edilson Jimmy. Universidad Continental; PerúFil: Crispín DelaCruz, Doris B.. Universidad Continental; PerúFil: Ticse-Otarola, Ginette. Universidad Continental; PerúFil: Rusbelth Quispe Melgar, Harold. Universidad Continental; PerúFil: Inga Guillen, Janet G.. Universidad Continental; PerúFil: Camel Paucar, Vladimir. Universidad Nacional Agraria La Molina; PerúFil: Guerra, Anthony. Universidad Nacional del Centro del Perú; PerúFil: Ames Martinez, Fressia Nathalie. Universidad Continental; PerúFil: Morales, Mariano Santos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentin

Longitudinal GWAS Identifies Novel Genetic Variants and Complex Traits Associated with Resilience to Alzheimer’s Disease

Background We completed a large genetic analysis of resilience to cognitive decline in Alzheimer’s Disease (AD) and discovered novel variants, genes, and complex traits associated with better‐than or worse‐than‐expected cognitive performance given an individual’s age, sex, and APOE genotype. Method Leveraging 15,933 non‐Hispanic white participants across four longitudinal cohort studies of aging and AD (Figure 1), our group determined the effects of genetic variants on resilience metrics using mixed‐effects regressions. Models adjusted for age, sex, APOE ε4 allele count, presence of the APOE ε2 allele and all covariate interactions with interval (years from baseline). The outcomes of interest were residual cognitive resilience, quantified from residuals in three cognitive domains (memory, executive function, and language), and combined resilience, summarized as the covariance of educational attainment with residual cognitive resilience. Post‐GWAS analyses included gene tests using MAGMA and estimates of genetic correlation with 65 complex traits using GNOVA. Result We observed genome‐wide significant associations at multiple established AD loci, including BIN1 and CR1 (Figure 2). We observed a novel association with combined resilience on chromosome 13 (top SNP: rs11838654, MAF = 0.06, P = 4.7×10−8; Figure 3) and a novel signal on chromosome 1 approaching significance (top SNP: rs2817183, MAF = 0.41, P = 5.1×10−8). Interestingly, rs11838654 is an eQTL for four genes in hippocampus (WBP4, COG6, MRPS31, and NHLRC3I; Braineac database). We also observed an association with residual cognitive resilience on chromosome 5 that approached genome‐wide significance (top SNP: rs4482935, MAF = 0.25, P = 5.5×10−8; Figure 2). Gene‐level tests identified associations of CD2AP (P.fdr = 0.027) and ZNF146 (P.fdr = 0.049) with residual cognitive resilience and combined resilience, respectively. Additionally, we identified negative genetic correlations of combined resilience with ischemic stroke and coronary artery disease (all P.fdr<2.5×10−2; Figure 4). Conclusion Compared to models of resilience that regress out the effects of AD neuropathology on cognition, the present models benefit from larger sample size at the cost of molecular precision. Although the genetic architecture of resilience from these less precise models more closely resembles that of clinical AD, we uncovered novel genetic drivers of resilience through this approach. Such findings will require future replication but suggest a trajectory‐based definition of resilience holds substantial promise for discovery