Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Sensory ecology and perceptual allocation: new prospects for neural networks

Sensory ecology provides a conceptual framework for considering how animals ought to design sensory systems to capture meaningful information from their environments. The framework has been particularly successful at describing how one should allocate sensory receptors to maximize performance on a given task. Neural networks, in contrast, have made unique contributions to understanding how ‘hidden preferences’ can emerge as a by-product of sensory design. The two frameworks comprise complementary techniques for understanding the design and the evolution of sensation. This article reviews empirical literature from multiple modalities and levels of sensory processing, considering vision, audition and touch from the viewpoints of sensory ecology and neuroethology. In the process, it presents modifications of extant neural network algorithms that would allow a more effective integration of these diverse approaches. Together, the reviewed literature suggests important advances that can be made by explicitly formulating neural network models in terms of sensory ecology, by incorporating neural costs into models of perceptual evolution and by exploring how such demands interact with historical forces