Frontiers in Aging Neuroscience is a leading journal in its field, publishing rigorously peer-reviewed research that advances our understanding of the mechanisms of Central Nervous System aging and age-related neural diseases. Specialty Chief Editor Thomas Wisniewski at the New York University School of Medicine is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
Shouneng Peng, Lu Zeng, Jean‐Vianney Haure‐Mirande, Minghui Wang, Derek M. Huffman, Vahram Haroutunian, Michelle E. Ehrlich, Bin Zhang, Zhidong Tu
Aging is a major risk factor for late-onset Alzheimer’s disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic datasets from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45–70 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic datasets from another cohort of older individuals (>70 years), we found that samples from cognitively normal older individuals clustered with the “healthy aging” subgroup while AD samples mainly clustered with the “AD similar” subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the “normal brain aging” to identify the very early molecular events that may lead to LOAD development.
Aging is characterized generally by progressive and overall physiological decline of functions and is observed in all animals. A long line of evidence has established the laboratory mouse as the prime model of human aging. However, relatively little is known about the detailed behavioral and functional changes that occur across their lifespan, and how this maps onto the phenotype of human aging. To better understand age-related changes across the life-span, we characterized functional aging in male C57BL/6J mice of five different ages (3, 6, 12, 18, and 22 months of age) using a multi-domain behavioral test battery. Spatial memory and physical activities, including locomotor activity, gait velocity, and grip strength progressively declined with increasing age, although at different rates; anxiety-like behaviors increased with aging. Estimated age-related patterns showed that these functional alterations across ages are non-linear, and the patterns are unique for each behavioral trait. Physical function progressively declines, starting as early as 6 months of age in mice, while cognitive function begins to decline later, with considerable impairment present at 22 months of age. Importantly, functional aging of male C57BL/6J mouse starts at younger relative ages compared to when it starts in humans. Our study suggests that human-equivalent ages of mouse might be better determined on the basis of its functional capabilities.
Interoceptive accuracy refers to the ability to consciously perceive the physical condition of the inner body, including one’s heartbeat. In younger adults, interoceptive accuracy is correlated with insular and orbitofrontal cortical connectivity within the salience network (SN). As interoceptive accuracy and insular cortex volume are known to decrease with aging, we aimed to evaluate the correlation between SN connectivity and interoceptive accuracy in older adults. 27 older adults (mean age, 77.29 years, SD = 6.24; 19 female) underwent resting-state functional magnetic resonance imaging, followed by a heartbeat counting task and neuropsychological test. We evaluated the correlation between interoceptive accuracy and SN connectivity with age, sex, cognitive function, and total gray matter volume as covariates. Region of interest-to-region of interest analyses showed that interoceptive accuracy was positively correlated with the functional connectivity (FC) of the left rostral prefrontal cortex with the right insular, right orbitofrontal, and anterior cingulate cortices [F(6,16) = 4.52, false discovery rate (FDR)-correctedp< 0.05]. Moreover, interoceptive accuracy was negatively correlated to the FC of the left anterior insular cortex with right intra-calcarine and visual medial cortices (F(6,16) = 2.04, FDR-correctedp< 0.10). These findings suggest that coordination between systems, with a positive correlation between left rostral prefrontal cortex and the SN and a negative correlation between left insular cortex and vision-related exteroceptive brain regions, is important for maintaining interoceptive accuracy in older adults.
Michelle S. Goodman, Sanjeev Kumar, Reza Zomorrodi, Zaid Ghazala, Amay Cheam, Mera S. Barr, Zafiris J. Daskalakis, Daniel M. Blumberger, Corinne E. Fischer, Alastair J. Flint, Linda Mah, Nathan Herrmann, Christopher R. Bowie, Benoit H. Mulsant, Tarek K. Rajji