Aging and gene expression in the primate brain

Brain aging and rejuvenation at single-cell resolution

Brain aging leads to a decline in cognitive function and a concomitant increase in the susceptibility to neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. A key question is how changes within individual cells of the brain give rise to age-related dysfunction. Developments in single-cell "omics" technologies, such as single-cell transcriptomics, have facilitated high-dimensional profiling of individual cells. These technologies have led to new and comprehensive characterizations of brain aging at single-cell resolution. Here, we review insights gleaned from single-cell omics studies of brain aging, starting with a cell-type-centric overview of age-associated changes and followed by a discussion of cell-cell interactions during aging. We highlight how single-cell omics studies provide an unbiased view of different rejuvenation interventions and comment on the promise of combinatorial rejuvenation approaches for the brain. Finally, we propose new directions, including models of brain aging and neural stem cells as a focal point for rejuvenation.

Incomplete filling in the basal region of maize endosperm: timing of development of starch synthesis and cell vitality

Starch synthesis in maize endosperm adheres to the basipetal sequence from the apex downwards. However, the mechanism underlying nonuniformity among regions of the endosperm in starch accumulation and its significance is poorly understood. Here, we examined the spatiotemporal transcriptomes and starch accumulation dynamics in apical (AE), middle (ME), and basal (BE) regions of endosperm throughout the filling stage. Results demonstrated that the BE had lower levels of gene transcripts and enzymes facilitating starch synthesis, corresponding to incomplete starch storage at maturity, compared with AE and ME. Contrarily, the BE showed abundant gene expression for genetic processing and slow progress in physiological development (quantified by an index calculated from the expression values of development progress marker genes), revealing a sustained cell vitality of the BE. Further analysis demonstrated a significant parabolic correlation between starch synthesis and physiological development. An in-depth examination showed that the BE had more active signaling pathways of IAA and ABA than the AE throughout the filling stage, while ethylene showed the opposite pattern. Besides, SNF1-related protein kinase1 (SnRK1) activity, a regulator for starch synthesis modulated by trehalose-6-phosphate (T6P) signaling, was kept at a lower level in the BE than the AE and ME, corresponding to the distinct gene expression in the T6P pathway in starch synthesis regulation. Collectively, the findings support an improved understanding of the timing of starch synthesis and cell vitality in regions of the endosperm during development, and potential regulation from hormone signaling and T6P/SnRK1 signaling.

Spatially resolved transcriptome of the aging mouse brain

Brain aging is associated with cognitive decline, memory loss and many neurodegenerative disorders. The mammalian brain has distinct structural regions that perform specific functions. However, our understanding in gene expression and cell types within the context of the spatial organization of the mammalian aging brain is limited. Here we generated spatial transcriptomic maps of young and old mouse brains. We identified 27 distinguished brain spatial domains, including layer-specific subregions that are difficult to dissect individually. We comprehensively characterized spatial-specific changes in gene expression in the aging brain, particularly for isocortex, the hippocampal formation, brainstem and fiber tracts, and validated some gene expression differences by qPCR and immunohistochemistry. We identified aging-related genes and pathways that vary in a coordinated manner across spatial regions and parsed the spatial features of aging-related signals, providing important clues to understand genes with specific functions in different brain regions during aging. Combined with single-cell transcriptomics data, we characterized the spatial distribution of brain cell types. The proportion of immature neurons decreased in the DG region with aging, indicating that the formation of new neurons is blocked. Finally, we detected changes in information interactions between regions and found specific pathways were deregulated with aging, including classic signaling WNT and layer-specific signaling COLLAGEN. In summary, we established a spatial molecular atlas of the aging mouse brain (http://sysbio.gzzoc.com/Mouse-Brain-Aging/), which provides important resources and novel insights into the molecular mechanism of brain aging.

Functional transcriptional signatures for tumor-type-agnostic phenotype prediction

Cancer transcriptional patterns exhibit both shared and unique features across diverse cancer types, but whether these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that cancer transcriptional diversity mirrors patterns in normal tissues optimized for distinct functional tasks. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2- breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.

Gene expression changes in cerebellum induced by dietary restriction

Background

Dietary restriction (DR) is a well-established universal anti-aging intervention, and is neuroprotective in multiple models of nervous system disease, including models with cerebellar pathology. The beneficial effects of DR are associated with a rearrangement of gene expression that modulate metabolic and cytoprotective pathways. However, the effect of DR on the cerebellar transcriptome remained to be fully defined.

Results

Here we analyzed the effect of a classical 30% DR protocol on the transcriptome of cerebellar cortex of young-adult male mice using RNAseq. We found that about 5% of expressed genes were differentially expressed in DR cerebellum, the far majority of whom showing subtle expression changes. A large proportion of down-regulated genes are implicated in signaling pathways, in particular pathways associated with neuronal signaling. DR up regulated pathways in large part were associated with cytoprotection and DNA repair. Analysis of the expression of cell-specific gene sets, indicated a strong enrichment of DR down genes in Purkinje cells, while genes specifically associated with granule cells did not show such a preferential down-regulation.

Conclusion

Our data show that DR may have a clear effect on the cerebellar transcriptome inducing a mild shift from physiology towards maintenance and repair, and having cell-type specific effects.

Locomotion and brain gene expression exhibit sex-specific non-monotonic dose-response to HFPO-DA during Drosophila melanogaster lifespan

BACKGROUND

Legacy per- and polyfluoroalkyl substances (PFAS), known for their environmental persistence and bio-accumulative properties, have been phased out in the U.S. due to public health concerns. A newer polymerization aid used in the manufacture of some fluoropolymers, hexafluoropropylene oxide-dimer acid (HFPO-DA), has lower reported bioaccumulation and toxicity, but is a potential neurotoxicant implicated in dopaminergic neurodegeneration.

OBJECTIVE

We investigated HFPO-DA's bio-accumulative potential and sex-specific effects on lifespan, locomotion, and brain gene expression in fruit flies.

METHODS

We quantified bioaccumulation of HFPO-DA in fruit flies exposed to 8.7×10⁴µg/L of HFPO-DA in the fly media for 14 days via UHPLC-MS. Long-term effect on lifespan was determined by exposing both sexes to 8.7×10² - 8.7×10⁵µg/L of HFPO-DA in media. Locomotion was measured following 3, 7, and 14 days of exposures at 8.7×10¹ - 8.7×10⁵µg/L of HFPO-DA in media, and high-throughput 3'-end RNA-sequencing was used to quantify gene expression in fly brains across the same time points.

RESULTS

Bioaccumulation of HFPO-DA in fruit flies was not detected. HFPO-DA-induced effects on lifespan, locomotion, and brain gene expression, and lowest adverse effect level (LOAEL) showed sexually dimorphic patterns. Locomotion scores significantly decreased in at least one dose at all time points for females and only at 3-day exposure for males, while brain gene expression exhibited non-monotonic dose-response. Differentially expressed genes correlated to locomotion scores revealed sex-specific numbers of positively and negatively correlated genes per functional category.

CONCLUSION

Although HFPO-DA effects on locomotion and survival were significant at doses higher than the US EPA reference dose, the brain transcriptomic profiling reveals sex-specific changes and neurological molecular targets; gene enrichments highlight disproportionately affected categories, including immune response: female-specific co-upregulation suggests potential neuroinflammation. Consistent sex-specific exposure effects necessitate blocking for sex in experimental design during HFPO-DA risk assessment.

Animal models for studies of alcohol effects on the trajectory of age-related cognitive decline

There is growing interest in understanding how ethanol use interacts with advancing age to influence the brain and cognition. Animal models are employed to investigate the cellular and molecular mechanisms of brain aging and age-related neurodegenerative diseases that underlie cognitive decline. However, all too often research on problems and diseases of the elderly are conducted in healthy young animals, providing little clinical relevance. The validity of animal models is discussed, and confounds due to age-related differences in anxiety, sensory-motor function, and procedural learning are highlighted in order to enhance the successful translation of preclinical results into clinical settings. The mechanism of action of ethanol on brain aging will depend on the dose, acute or chronic treatment, or withdrawal from treatment and the age examined. Due to the fact that humans experience alcohol use throughout life, important questions concern the effects of the dose and duration of ethanol treatment on the trajectory of cognitive function. Central to this research will be questions of the specificity of alcohol effects on cognitive functions and related brain regions that decline with age, as well as the interaction of alcohol with mechanisms or biomarkers of brain aging. Alternatively, moderate alcohol use may provide a source of reserve and resilience against brain aging. Longitudinal studies have the advantage of being sensitive to detecting the effects of treatment on the emergence of cognitive impairment in middle age and can minimize effects of stress/anxiety associated with the novelty of alcohol exposure and behavioral testing, which disproportionately influence aged animals. Finally, the effect of alcohol on senescent neurophysiology and biomarkers of brain aging are discussed. In particular, the interaction of age and effects of alcohol on inflammation, oxidative stress, N-methyl-d-aspartate receptor function, and the balance of excitatory and inhibitory synaptic transmission are highlighted.

Neurobiological Mechanisms of Cognitive Decline Correlated with Brain Aging

Cognitive decline has emerged as one of the greatest health threats of old age. Meanwhile, aging is the primary risk factor for Alzheimer's disease (AD) and other prevalent neurodegenerative disorders. Developing therapeutic interventions for such conditions demands a greater understanding of the processes underlying normal and pathological brain aging. Despite playing an important role in the pathogenesis and incidence of disease, brain aging has not been well understood at a molecular level. Recent advances in the biology of aging in model organisms, together with molecular- and systems-level studies of the brain, are beginning to shed light on these mechanisms and their potential roles in cognitive decline. This chapter seeks to integrate the knowledge about the neurological mechanisms of age-related cognitive changes that underlie aging.

Neutrophil dynamics and inflammaging in acute ischemic stroke: A transcriptomic review

Stroke is among the leading causes of death and disability worldwide. Restoring blood flow through recanalization is currently the only acute treatment for cerebral ischemia. Unfortunately, many patients that achieve a complete recanalization fail to regain functional independence. Recent studies indicate that activation of peripheral immune cells, particularly neutrophils, may contribute to microcirculatory failure and futile recanalization. Stroke primarily affects the elderly population, and mortality after endovascular therapies is associated with advanced age. Previous analyses of differential gene expression across injury status and age identify ischemic stroke as a complex age-related disease. It also suggests robust interactions between stroke injury, aging, and inflammation on a cellular and molecular level. Understanding such interactions is crucial in developing effective protective treatments. The global stroke burden will continue to increase with a rapidly aging human population. Unfortunately, the mechanisms of age-dependent vulnerability are poorly defined. In this review, we will discuss how neutrophil-specific gene expression patterns may contribute to poor treatment responses in stroke patients. We will also discuss age-related transcriptional changes that may contribute to poor clinical outcomes and greater susceptibility to cerebrovascular diseases.

Normal Aging Induces Changes in the Brain and Neurodegeneration Progress: Review of the Structural, Biochemical, Metabolic, Cellular, and Molecular Changes

Aging is accompanied by many changes in brain and contributes to progressive cognitive decline. In contrast to pathological changes in brain, normal aging brain changes have relatively mild but important changes in structural, biochemical and molecular level. Representatively, aging associated brain changes include atrophy of tissues, alteration in neurotransmitters and damage accumulation in cellular environment. These effects have causative link with age associated changes which ultimately results in cognitive decline. Although several evidences were found in normal aging changes of brain, it is not clearly integrated. Figuring out aging related changes in brain is important as aging is the process that everyone goes through, and comprehensive understanding may help to progress further studies. This review clarifies normal aging brain changes in an asymptotic and comprehensive manner, from a gross level to a microscopic and molecular level, and discusses potential approaches to seek the changes with cognitive decline.

Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin

BACKGROUND

Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

RESULTS

We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

CONCLUSION

The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.

Plasmalogens Eliminate Aging-Associated Synaptic Defects and Microglia-Mediated Neuroinflammation in Mice

Neurodegeneration is a pathological condition in which nervous system or neuron losses its structure, function, or both leading to progressive neural degeneration. Growing evidence strongly suggests that reduction of plasmalogens (Pls), one of the key brain lipids, might be associated with multiple neurodegenerative diseases, including Alzheimer’s disease (AD). Plasmalogens are abundant members of ether-phospholipids. Approximately 1 in 5 phospholipids are plasmalogens in human tissue where they are particularly enriched in brain, heart and immune cells. In this study, we employed a scheme of 2-months Pls intragastric administration to aged female C57BL/6J mice, starting at the age of 16 months old. Noticeably, the aged Pls-fed mice exhibited a better cognitive performance, thicker and glossier body hair in appearance than that of aged control mice. The transmission electron microscopic (TEM) data showed that 2-months Pls supplementations surprisingly alleviate age-associated hippocampal synaptic loss and also promote synaptogenesis and synaptic vesicles formation in aged murine brain. Further RNA-sequencing, immunoblotting and immunofluorescence analyses confirmed that plasmalogens remarkably enhanced both the synaptic plasticity and neurogenesis in aged murine hippocampus. In addition, we have demonstrated that Pls treatment inhibited the age-related microglia activation and attenuated the neuroinflammation in the murine brain. These findings suggest for the first time that Pls administration might be a potential intervention strategy for halting neurodegeneration and promoting neuroregeneration.

Statistical testing in transcriptomic-neuroimaging studies: A how-to and evaluation of methods assessing spatial and gene specificity

Multiscale integration of gene transcriptomic and neuroimaging data is becoming a widely used approach for exploring the molecular underpinnings of large‐scale brain organization in health and disease. Proper statistical evaluation of determined associations between imaging‐based phenotypic and transcriptomic data is key in these explorations, in particular to establish whether observed associations exceed “chance level” of random, nonspecific effects. Recent approaches have shown the importance of statistical models that can correct for spatial autocorrelation effects in the data to avoid inflation of reported statistics. Here, we discuss the need for examination of a second category of statistical models in transcriptomic‐neuroimaging analyses, namely those that can provide “gene specificity.” By means of a couple of simple examples of commonly performed transcriptomic‐neuroimaging analyses, we illustrate some of the potentials and challenges of transcriptomic‐imaging analyses, showing that providing gene specificity on observed transcriptomic‐neuroimaging effects is of high importance to avoid reports of nonspecific effects. Through means of simulations we show that the rate of reported nonspecific effects (i.e., effects that cannot be specifically linked to a specific gene or gene‐set) can run as high as 60%, with only less than 5% of transcriptomic‐neuroimaging associations observed through ordinary linear regression analyses showing both spatial and gene specificity. We provide a discussion, a tutorial, and an easy‐to‐use toolbox for the different options of null models in transcriptomic‐neuroimaging analyses.

Where the genome meets the connectome: Understanding how genes shape human brain connectivity

The integration of modern neuroimaging methods with genetically informative designs and data can shed light on the molecular mechanisms underlying the structural and functional organization of the human connectome. Here, we review studies that have investigated the genetic basis of human brain network structure and function through three complementary frameworks: (1) the quantification of phenotypic heritability through classical twin designs; (2) the identification of specific DNA variants linked to phenotypic variation through association and related studies; and (3) the analysis of correlations between spatial variations in imaging phenotypes and gene expression profiles through the integration of neuroimaging and transcriptional atlas data. We consider the basic foundations, strengths, limitations, and discoveries associated with each approach. We present converging evidence to indicate that anatomical connectivity is under stronger genetic influence than functional connectivity and that genetic influences are not uniformly distributed throughout the brain, with phenotypic variation in certain regions and connections being under stronger genetic control than others. We also consider how the combination of imaging and genetics can be used to understand the ways in which genes may drive brain dysfunction in different clinical disorders.

Imaging Transcriptomics of Brain Disorders

Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes.

Brain organoids: A promising model to assess oxidative stress-induced central nervous system damage

Oxidative stress (OS) is one of the most significant propagators of systemic damage with implications for widespread pathologies such as vascular disease, accelerated aging, degenerative disease, inflammation, and traumatic injury. OS can be induced by numerous factors such as environmental conditions, lifestyle choices, disease states, and genetic susceptibility. It is tied to the accumulation of free radicals, mitochondrial dysfunction, and insufficient antioxidant protection, which leads to cell aging and tissue degeneration over time. Unregulated systemic increase in reactive species, which contain harmful free radicals, can lead to diverse tissue-specific OS responses and disease. Studies of OS in the brain, for example, have demonstrated how this state contributes to neurodegeneration and altered neural plasticity. As the worldwide life expectancy has increased over the last few decades, the prevalence of OS-related diseases resulting from age-associated progressive tissue degeneration. Unfortunately, vital translational research studies designed to identify and target disease biomarkers in human patients have been impeded by many factors (e.g., limited access to human brain tissue for research purposes and poor translation of experimental models). In recent years, stem cell-derived three-dimensional tissue cultures known as "brain organoids" have taken the spotlight as a novel model for studying central nervous system (CNS) diseases. In this review, we discuss the potential of brain organoids to model the responses of human neural cells to OS, noting current and prospective limitations. Overall, brain organoids show promise as an innovative translational model to study CNS susceptibility to OS and elucidate the pathophysiology of the aging brain.

Increased Brain Age Gap Estimate (BrainAGE) in Young Adults After Premature Birth

Recent evidence suggests increased metabolic and physiologic aging rates in premature-born adults. While the lasting consequences of premature birth on human brain development are known, its impact on brain aging remains unclear. We addressed the question of whether premature birth impacts brain age gap estimates (BrainAGE) using an accurate and robust machine-learning framework based on structural MRI in a large cohort of young premature-born adults (n = 101) and full-term (FT) controls (n = 111). Study participants are part of a geographically defined population study of premature-born individuals, which have been followed longitudinally from birth until young adulthood. We investigated the association between BrainAGE scores and perinatal variables as well as with outcomes of physical (total intracranial volume, TIV) and cognitive development (full-scale IQ, FS-IQ). We found increased BrainAGE in premature-born adults [median (interquartile range) = 1.4 (-1.3-4.7 years)] compared to full-term controls (p = 0.002, Cohen's d = 0.443), which was associated with low Gestational age (GA), low birth weight (BW), and increased neonatal treatment intensity but not with TIV or FS-IQ. In conclusion, results demonstrate elevated BrainAGE in premature-born adults, suggesting an increased risk for accelerated brain aging in human prematurity.

Improved Human Age Prediction by Using Gene Expression Profiles From Multiple Tissues

Studying transcriptome chronological change from tissues across the whole body can provide valuable information for understanding aging and longevity. Although there has been research on the effect of single-tissue transcriptomes on human aging or aging in mice across multiple tissues, the study of human body-wide multi-tissue transcriptomes on aging is not yet available. In this study, we propose a quantitative model to predict human age by using gene expression data from 46 tissues generated by the Genotype-Tissue Expression (GTEx) project. Specifically, the biological age of a person is first predicted via the gene expression profile of a single tissue. Then, we combine the gene expression profiles from two tissues and compare the predictive accuracy between single and two tissues. The best performance as measured by the root-mean-square error is 3.92 years for single tissue (pituitary), which deceased to 3.6 years when we combined two tissues (pituitary and muscle) together. Different tissues have different potential in predicting chronological age. The prediction accuracy is improved by combining multiple tissues, supporting that aging is a systemic process involving multiple tissues across the human body.

Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data

MOTIVATION

Predictive models are a powerful tool for solving complex problems in computational biology. They are typically designed to predict or classify data coming from the same unknown distribution as the training data. In many real-world settings, however, uncontrolled biological or technical factors can lead to a distribution mismatch between datasets acquired at different times, causing model performance to deteriorate on new data. A common additional obstacle in computational biology is scarce data with many more features than samples. To address these problems, we propose a method for unsupervised domain adaptation that is based on a weighted elastic net. The key idea of our approach is to compare dependencies between inputs in training and test data and to increase the cost of differently behaving features in the elastic net regularization term. In doing so, we encourage the model to assign a higher importance to features that are robust and behave similarly across domains.

RESULTS

We evaluate our method both on simulated data with varying degrees of distribution mismatch and on real data, considering the problem of age prediction based on DNA methylation data across multiple tissues. Compared with a non-adaptive standard model, our approach substantially reduces errors on samples with a mismatched distribution. On real data, we achieve far lower errors on cerebellum samples, a tissue which is not part of the training data and poorly predicted by standard models. Our results demonstrate that unsupervised domain adaptation is possible for applications in computational biology, even with many more features than samples.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/PfeiferLabTue/wenda.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Resistance, vulnerability and resilience: A review of the cognitive cerebellum in aging and neurodegenerative diseases

In the context of neurodegeneration and aging, the cerebellum is an enigma. Genetic markers of cellular aging in cerebellum accumulate more slowly than in the rest of the brain, and it generates unknown factors that may slow or even reverse neurodegenerative pathology in animal models of Alzheimer's Disease (AD). Cerebellum shows increased activity in early AD and Parkinson's disease (PD), suggesting a compensatory function that may mitigate early symptoms of neurodegenerative pathophysiology. Perhaps most notably, different parts of the brain accumulate neuropathological markers of AD in a recognized progression and generally, cerebellum is the last brain region to do so. Taken together, these data suggest that cerebellum may be resistant to certain neurodegenerative mechanisms. On the other hand, in some contexts of accelerated neurodegeneration, such as that seen in chronic traumatic encephalopathy (CTE) following repeated traumatic brain injury (TBI), the cerebellum appears to be one of the most susceptible brain regions to injury and one of the first to exhibit signs of pathology. Cerebellar pathology in neurodegenerative disorders is strongly associated with cognitive dysfunction. In neurodegenerative or neurological disorders associated with cerebellar pathology, such as spinocerebellar ataxia, cerebellar cortical atrophy, and essential tremor, rates of cognitive dysfunction, dementia and neuropsychiatric symptoms increase. When the cerebellum shows AD pathology, such as in familial AD, it is associated with earlier onset and greater severity of disease. These data suggest that when neurodegenerative processes are active in the cerebellum, it may contribute to pathological behavioral outcomes. The cerebellum is well known for comparing internal representations of information with observed outcomes and providing real-time feedback to cortical regions, a critical function that is disturbed in neuropsychiatric disorders such as intellectual disability, schizophrenia, dementia, and autism, and required for cognitive domains such as working memory. While cerebellum has reciprocal connections with non-motor brain regions and likely plays a role in complex, goal-directed behaviors, it has proven difficult to establish what it does mechanistically to modulate these behaviors. Due to this lack of understanding, it's not surprising to see the cerebellum reflexively dismissed or even ignored in basic and translational neuropsychiatric literature. The overarching goals of this review are to answer the following questions from primary literature: When the cerebellum is affected by pathology, is it associated with decreased cognitive function? When it is intact, does it play a compensatory or protective role in maintaining cognitive function? Are there theoretical frameworks for understanding the role of cerebellum in cognition, and perhaps, illnesses characterized by cognitive dysfunction? Understanding the role of the cognitive cerebellum in neurodegenerative diseases has the potential to offer insight into origins of cognitive deficits in other neuropsychiatric disorders, which are often underappreciated, poorly understood, and not often treated.

Oxidative Stress, Frailty and Cardiovascular Diseases: Current Evidence

The aim of this chapter is to review the results of recent studies analyzing the role of oxidative stress and systemic inflammation as potential contributors to frailty and CVD, and to explain a possible pathogenic relationship between the latter two conditions. Available evidence suggests that frail patients have elevated levels of oxidative stress biomarkers and proinflammatory cytokines, as well as with reduced concentrations of endogenous antioxidants. This implies that oxidative stress and systemic inflammation might play a role in the pathogenesis of frailty, but an underlying mechanism of this relationship is still mostly hypothetical. Oxidative stress and systemic inflammation are also involved in the pathogenesis of CVD. Cardiovascular conditions are established risk factor for frailty and in turn, presence of frailty constitutes an unfavorable prognostic factor in cardiac patients. Finally, some cardiovascular risk factors, such as lack of physical activity, smoking, obesity and inappropriate diet, are also involved in the etiology of oxidative stress, chronic inflammation and frailty. This complex interplay between intrinsic and extrinsic elements should be considered during holistic management of older persons with frailty and/or cardiovascular conditions.

547 transcriptomes from 44 brain areas reveal features of the aging brain in non-human primates

BACKGROUND

Brain aging is a complex process that depends on the precise regulation of multiple brain regions; however, the underlying molecular mechanisms behind this process remain to be clarified in non-human primates.

RESULTS

Here, we explore non-human primate brain aging using 547 transcriptomes originating from 44 brain areas in rhesus macaques (Macaca mulatta). We show that expression connectivity between pairs of cerebral cortex areas as well as expression symmetry between the left and right hemispheres both decrease after aging. Although the aging mechanisms across different brain areas are largely convergent, changes in gene expression and alternative splicing vary at diverse genes, reinforcing the complex multifactorial basis of aging. Through gene co-expression network analysis, we identify nine modules that exhibit gain of connectivity in the aged brain and uncovered a hub gene, PGLS, underlying brain aging. We further confirm the functional significance of PGLS in mice at the gene transcription, molecular, and behavioral levels.

CONCLUSIONS

Taken together, our study provides comprehensive transcriptomes on multiple brain regions in non-human primates and provides novel insights into the molecular mechanism of healthy brain aging.

Computed Tomography Assessment of Brain Atrophy in Centenarians

The aim of our study was to compare the degree of brain atrophy in centenarians and in seniors 70–99 years old. The study group consisted of 23 patients aged 100–106 years. The control group consisted of 90 patients, 30 in each age subgroup 90–99, 80–89, 70–79. In all the patients, the brain atrophy linear parameters were measured on computed tomography scans, in relation to both “subcortical atrophy”, evaluated as progressive widening of the ventricular system, and “cortical atrophy”, defined as widening of subarachnoid space. Secondary indices based on the parameters were calculated. Correlations between the above parameters/indices and age were tested. Significantly different values between the centenarians and the control group were found in the brain atrophy parameters: A, B, C, E, FI, ICR, ICL, SW, CFW, F/A ‘frontal horn index’, A/G ‘Evans index’, D/A ‘ventricular index’, H/E ‘cella media Schiersmann index’, A+B ‘Huckman number’. Correlations between parameter/index and age were found for: A, B, C, FI, ICR, ICL, SW, F/A ‘frontal horn index’, A/G ‘Evans index’, D/A ‘ventricular index’, H/E ‘cella media Schiersmann index’, A+B ‘Huckman number’. Brain atrophy associated with aging is a continuously advancing process, affecting centenarians even more than people before the “magic” threshold of 100 years.

Writers and Readers of DNA Methylation/Hydroxymethylation in Physiological Aging and Its Impact on Cognitive Function

The chromatin landscape has acquired deep attention from several fields ranging from cell biology to neurological and psychiatric diseases. The role that DNA modifications have on gene expression regulation has become apparent in several physiological processes, and numerous efforts have been performed to establish a relationship between DNA modifications and physiological conditions, such as cognitive performance and aging. DNA modifications are incorporated by specific sets of enzymes-the writers-and the modified DNA-interacting partners-the readers-are ultimately responsible for maintaining a functional epigenetic landscape. Therefore, understanding how these epigenetic mediators-writers and readers-are modulated in physiological aging will contribute to unraveling how aging-associated neuronal disturbances arise and contribute to the cognitive decline associated with this period of life. In this review, we focused on DNA modifications, writers and readers, highlighting that despite some methodological disparities, the evidence suggests a critical role for epigenetic mediators in the aging-associated neuronal dysfunction.

Regional mitochondrial DNA and cell-type changes in post-mortem brains of non-diabetic Alzheimer's disease are not present in diabetic Alzheimer's disease

Diabetes increases the risk of Alzheimer's disease (AD), and mitochondrial dysfunction is implicated in both diseases, however the impact of both diabetes and AD on brain mitochondria is not known. We measured mitochondrial DNA (mtDNA), an indicator of mitochondrial function, in frontal, parietal, and cerebellar regions of post-mortem human brains (n = 74) from non-cognitively impaired controls (NCI), mild-cognitively impaired (MCI) and AD cases. In a subset of parietal cortices, we measured mRNAs corresponding to cell types and mitochondrial function and semi-automated stereological assessment was performed on immune-staining of parietal cortex sections. mtDNA showed significant regional variation, highest in parietal cortex, and lowest in cerebellum. Irrespective of cognitive status, all brain regions had significantly higher mtDNA in diabetic cases. In the absence of diabetes, AD parietal cortices had decreased mtDNA, reduced MAP2 (neuronal) and increased GFAP (astrocyte) mRNA, relative to NCI. However, in the presence of diabetes, we did not observe these AD-related changes, suggesting that the pathology observed in diabetic AD may be different to that seen in non-diabetic AD. The lack of clear functional changes in mitochondrial parameters in diabetic AD suggest different cellular mechanisms contributing to cognitive impairment in diabetes which remain to be fully understood.

Dentate Gyrus Peroxiredoxin 6 Levels Discriminate Aged Unimpaired From Impaired Rats in a Spatial Memory Task

Similar to humans, the normal aged rat population is not homogeneous in terms of cognitive function. Two distinct subpopulations of aged Sprague-Dawley rats can be identified on the basis of spatial memory performance in the hole-board paradigm. It was the aim of the study to reveal protein changes relevant to aging and spatial memory performance. Aged impaired (AI) and unimpaired (AU) male rats, 22-24 months old were selected from a large cohort of 160 animals; young animals served as control. Enriched synaptosomal fractions from dentate gyrus from behaviorally characterized old animals were used for isobaric tags labeling based quantitative proteomic analysis. As differences in peroxiredoxin 6 (PRDX6) levels were a pronounced finding, PRDX6 levels were also quantified by immunoblotting. AI showed impaired spatial memory abilities while AU performed comparably to young animals. Our study demonstrates substantial quantitative alteration of proteins involved in energy metabolism, inflammation and synaptic plasticity during aging. Moreover, we identified protein changes specifically coupled to memory performance of aged rats. PRDX6 levels clearly differentiated AI from AU and levels in AU were comparable to those of young animals. In addition, it was observed that stochasticity in protein levels increased with age and discriminate between AI and AU groups. Moreover, there was a significantly higher variability of protein levels in AI. PRDX6 is a member of the PRDX family and well-defined as a cystein-1 PRDX that reduces and detoxifies hydroxyperoxides. It is well-known and documented that the aging brain shows increased active oxygen species but so far no study proposed a potential target with antioxidant activity that would discriminate between impaired and unimpaired memory performers. Current data, representing so far the largest proteomics data set in aging dentate gyrus (DG), provide the first evidence for a probable role of PRDX6 in memory performance.

Uncovering the Transcriptional Correlates of Hub Connectivity in Neural Networks

Connections in nervous systems are disproportionately concentrated on a small subset of neural elements that act as network hubs. Hubs have been found across different species and scales ranging from C. elegans to mouse, rat, cat, macaque, and human, suggesting a role for genetic influences. The recent availability of brain-wide gene expression atlases provides new opportunities for mapping the transcriptional correlates of large-scale network-level phenotypes. Here we review studies that use these atlases to investigate gene expression patterns associated with hub connectivity in neural networks and present evidence that some of these patterns are conserved across species and scales.

Quercetin Affects the Growth and Development of the Grasshopper Oedaleus asiaticus (Orthoptera: Acrididae)

Flavonoids are secondary metabolites that help plants resist insect attack, but pest insects have evolved enzymes that reduce the toxicity of these secondary metabolites. We studied the response of the grasshopper Oedaleus asiaticus Bey-Bienko fed different concentrations of quercetin, a representative flavonoid. Oedaleus asiaticus growth (survival rate and growth rate) was significantly reduced at high quercetin concentrations. Reactive oxygen species (ROS) increased significantly in response to the diet stress associated with high quercetin concentrations. Gene expression and protein phosphorylation level of the IGF→FOXO cascade related to the stress response in the O. asiaticus insulin-like signaling pathway (ILP) were also reduced. Multiple protective enzyme activities were regulated by FOXO. Mixed-function oxidase (MFO), superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), were all significantly increased with exposure to high quercetin concentrations. Quercetin negatively regulated the ILP pathway, and was detrimental to O. asiaticus growth and survival, as more energy was required for detoxification. This study showed how flavonoids impact on O. asiaticus biochemical pathways, physiology, and development. Flavonoids offer a new option for the development of biological pesticides for application to grasshopper biological control.

Role of PTP/PTK trans activated insulin-like signalling pathway in regulation of grasshopper (Oedaleus asiaticus) development

Protein tyrosine phosphatase (PTPs) and protein tyrosine kinase (PTKs) genes are responsible for the regulation of insect insulin-like pathway (ILP), cells growth, metabolism initiation, gene transcription and observing immune response. Signal transduction in insect cell is also associated with PTPs and PTKs. The grasshopper (Oedaleus asiaticus) 'Bey-Bienko' were treated with dsRNA of protein tyrosine non-receptor type 4 (PTPN4) and protein tyrosine kinase 5 (PTK5) along with control (water). Applying dsPTK5 treatments in 5th instar of Oedaleus asiaticus, significant reduction was recorded in body dry mass, growth rate and overall performance except survival rate. Whereas with PTPN4, no such significant impact on all of these growth parameters was recorded. Expression of genes in ILP 5th instar of Oedaleus asiaticus by the application of dsPTPN4 and dsPTK5 revealed that PTK, INSR (insulin receptor), IRS (insulin receptor substrate), PI3K (phosphoinositide 3-kinase), PDK (3-phosphoinositide-dependent protein kinase), Akt (protein kinase B) and FOXO (forkhead transcription factor) significantly expressed with downregulation except PTPN4, which remained non-significant. On the other hand, the phosphorylation level of ILP four proteins in O. asiaticus with the treatment of dsPTPN4 and dsPTK5 significantly affected P-IRS and P-FOXO, while P-INSR and P-AKT remained stable at the probability level of 5%. This indicated that the stress response in the O. asiaticus insulin-like signalling pathway (ILP) reduced. Regarding association of protective enzymatic activities, ROS (relative oxygen species), CAT (catalase) and PO (phenol oxidase) increased significantly with exposure to dsPTK5 as compared to dsPTPN4 and control, while exposure of 5th instar of O. asiaticus to dsPTPN4 treatment slightly raised CAT and PO activities with but significant contribution. No such significant effect on MFO and POD was seen using dsPTPN4 and dsPTK5. This showed that in the ILP of O. asiaticus, PTK5 was detrimental to growth, body mass and overall performance, which ultimately benefited insect detoxification with high-energy cost.

Comprehensive transcriptional profiling of porcine brain aging

The brain as an important organ can be affected largely by aging, and the comprehensive transcriptional underpinnings of brain aging remain poorly understood. Here, we performed a high throughput RNA sequencing to evaluate the expression profiles of messenger RNA (mRNA), long non-coding RNAs (lncRNAs), micro RNAs (miRNAs), and circular RNAs (circRNAs) in porcine brain. We have identified 714 mRNAs, 38lncRNAs, 41miRNAs, and 148circRNAs were age-related genes in the porcine cerebral cortex. The lncRNAs, miRNAs and circRNAs have effect on the age of porcine brain due to the much changes of expression level as noncoding RNAs. The up-regulated genes were significantly enriched for stress response, reproductive regulatory process, immune response and metabolic process, and the down-regulated genes were related to neurologic function, stress response and signaling pathway. The synaptic transmission pathway may be the key role in aging of porcine brain that it was co-enriched for in both differentially expressed mRNAs and lncRNAs. Moreover, some lncRNAs and their target genes were also differentially expressed during brain aging. We further assessed the multi-group cooperative control relationships and constructed circRNA-miRNA co-expression networks during brain aging. We also selected 2 mRNAs, 2 lncRNAs, 2 miRNAs, and 1 circRNAs to perform the q-PCR, and the expression patterns were highly consistent between the two methods confirming the high reproducibility and reliability of the gene expression profiling in our study. In conclusion, our findings will contribute to understand the transcriptional underpinnings of brain aging and provide a foundation for future studies on the molecular mechanisms underlying brain aging.

A practical guide to linking brain-wide gene expression and neuroimaging data

The recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field.

The effect of age, sex and strains on the performance and outcome in animal models of stroke

Stroke is one of the leading causes of death worldwide, and the majority of cerebral stroke is caused by occlusion of cerebral circulation, which eventually leads to brain infarction. Although stroke occurs mainly in the aged population, most animal models for experimental stroke in vivo almost universally rely on young-adult rodents for the evaluation of neuropathological, neurological, or behavioral outcomes after stroke due to their greater availability, lower cost, and fewer health problems. However, it is well established that aged animals differ from young animals in terms of physiology, neurochemistry, and behavior. Stroke-induced changes are more pronounced with advancing age. Therefore, the overlooked role of age in animal models of stroke could have an impact on data quality and hinder the translation of rodent models to humans. In addition to aging, other factors also influence functional performance after ischemic stroke. In this article, we summarize the differences between young and aged animals, the impact of age, sex and animal strains on performance and outcome in animal models of stroke and emphasize age as a key factor in preclinical stroke studies.

Observations of extensive gene expression differences in the cerebellum and potential relevance to Alzheimer's disease

Objectives

In order to determine how gene expression is altered in disease it is of fundamental importance that the global distribution of gene expression levels across the disease-free brain are understood and how differences between tissue types might inform tissue choice for investigation of altered expression in disease state. The aim of this pilot project was to use RNA-sequencing to investigate gene expression differences between five general areas of post-mortem human brain (frontal, temporal, occipital, parietal and cerebellum), and in particular changes in gene expression in the cerebellum compared to cortex regions for genes relevant to Alzheimer’s disease, as the cerebellum is largely preserved from disease pathology and could be an area of interest for neuroprotective pathways.

Results

General gene expression profiles were found to be similar between cortical regions of the brain, however the cerebellum presented a distinct expression profile. Focused exploration of gene expression for genes associated with Alzheimer’s disease suggest that those involved in the immunity pathway show little expression in the brain. Furthermore some Alzheimer’s disease associated genes display significantly different expression in the cerebellum compared with other brain regions, which might indicate potential neuroprotective measures.

Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes

It is widely assumed that cells must be physically isolated to study their molecular profiles. However, intact tissue samples naturally exhibit variation in cellular composition, which drives covariation of cell-class-specific molecular features. By analyzing transcriptional covariation in 7,221 intact CNS samples from 840 neurotypical individuals, representing billions of cells, we reveal the core transcriptional identities of major CNS cell classes in humans. By modeling intact CNS transcriptomes as a function of variation in cellular composition, we identify cell-class-specific transcriptional differences in Alzheimer's disease, among brain regions, and between species. Among these, we show that PMP2 is expressed by human but not mouse astrocytes and significantly increases mouse astrocyte size upon ectopic expression in vivo, causing them to more closely resemble their human counterparts. Our work is available as an online resource ( http://oldhamlab.ctec.ucsf.edu/ ) and provides a generalizable strategy for determining the core molecular features of cellular identity in intact biological systems.

Human Age Prediction Based on DNA Methylation Using a Gradient Boosting Regressor

All tissues of organisms will become old as time goes on. In recent years, epigenetic investigations have found that there is a close correlation between DNA methylation and aging. With the development of DNA methylation research, a quantitative statistical relationship between DNA methylation and different ages was established based on the change rule of methylation with age, it is then possible to predict the age of individuals. All the data in this work were retrieved from the Illumina HumanMethylation BeadChip platform (27K or 450K). We analyzed 16 sets of healthy samples and 9 sets of diseased samples. The healthy samples included a total of 1899 publicly available blood samples (0–103 years old) and the diseased samples included 2395 blood samples. Six age-related CpG sites were selected through calculating Pearson correlation coefficients between age and DNA methylation values. We built a gradient boosting regressor model for these age-related CpG sites. 70% of the data was randomly selected as training data and the other 30% as independent data in each dataset for 25 runs in total. In the training dataset, the healthy samples showed that the correlation between predicted age and DNA methylation was 0.97, and the mean absolute deviation (MAD) was 2.72 years. In the independent dataset, the MAD was 4.06 years. The proposed model was further tested using the diseased samples. The MAD was 5.44 years for the training dataset and 7.08 years for the independent dataset. Furthermore, our model worked well when it was applied to saliva samples. These results illustrated that the age prediction based on six DNA methylation markers is very effective using the gradient boosting regressor.

Age-related gene expression in luminal epithelial cells is driven by a microenvironment made from myoepithelial cells

Luminal epithelial cells in the breast gradually alter gene and protein expression with age, appearing to lose lineage-specificity by acquiring myoepithelial-like characteristics. We hypothesize that the luminal lineage is particularly sensitive to microenvironment changes, and age-related microenvironment changes cause altered luminal cell phenotypes. To evaluate the effects of different microenvironments on the fidelity of epigenetically regulated luminal and myoepithelial gene expression, we generated a set of lineage-specific probes for genes that are controlled through DNA methylation. Culturing primary luminal cells under conditions that favor myoepithelial propogation led to their reprogramming at the level of gene methylation, and to a more myoepithelial-like expression profile. Primary luminal cells' lineage-specific gene expression could be maintained when they were cultured as bilayers with primary myoepithelial cells. Isogenic stromal fibroblast co-cultures were unable to maintain the luminal phenotype. Mixed-age luminal-myoepithelial bilayers revealed that luminal cells adopt transcription and methylation patterns consistent with the chronological age of the myoepithelial cells. We provide evidence that the luminal epithelial phenotype is exquisitely sensitive to microenvironment conditions, and that states of aging are cell non-autonomously communicated through microenvironment cues over at least one cell diameter.

Transcriptomics of aged Drosophila motor neurons reveals a matrix metalloproteinase that impairs motor function

The neuromuscular junction (NMJ) is responsible for transforming nervous system signals into motor behavior and locomotion. In the fruit fly Drosophila melanogaster, an age-dependent decline in motor function occurs, analogous to the decline experienced in mice, humans, and other mammals. The molecular and cellular underpinnings of this decline are still poorly understood. By specifically profiling the transcriptome of Drosophila motor neurons across age using custom microarrays, we found that the expression of the matrix metalloproteinase 1 (dMMP1) gene reproducibly increased in motor neurons in an age-dependent manner. Modulation of physiological aging also altered the rate of dMMP1 expression, validating dMMP1 expression as a bona fide aging biomarker for motor neurons. Temporally controlled overexpression of dMMP1 specifically in motor neurons was sufficient to induce deficits in climbing behavior and cause a decrease in neurotransmitter release at neuromuscular synapses. These deficits were reversible if the dMMP1 expression was shut off again immediately after the onset of motor dysfunction. Additionally, repression of dMMP1 enzymatic activity via overexpression of a tissue inhibitor of metalloproteinases delayed the onset of age-dependent motor dysfunction. MMPs are required for proper tissue architecture during development. Our results support the idea that matrix metalloproteinase 1 is acting as a downstream effector of antagonistic pleiotropy in motor neurons and is necessary for proper development, but deleterious when reactivated at an advanced age.

Increased Degradation Rates in the Components of the Mitochondrial Oxidative Phosphorylation Chain in the Cerebellum of Old Mice

Brain structures differ in the magnitude of age-related neuron loss with the cerebellum being more affected. An underlying cause could be an age-related decline in mitochondrial bioenergetics. Successful aging of mitochondria reflects a balanced turnover of proteins involved in mitochondrial biogenesis and mitophagy. Thus, an imbalance in mitochondrial turnover can contribute to the diminution of cellular function seen during aging. Mitochondrial biogenesis and mitophagy are mediated by a set of proteins including MFN1, MFN2, OPA1, DRP1, FIS1 as well as DMN1l and DNM1, all of which are required for mitochondrial fission. Using N15 labeling, we report that the turnover rates for DMN1l and FIS1 go in opposite directions in the cerebellum of 22-month-old C57BL6j mice as compared to 3-month-old mice. Previous studies have reported decreased turnover rates for the mitochondrial respiratory complexes of aged rodents. In contrast, we found increased turnover rates for mitochondrial proteins of the oxidative phosphorylation chain in the aged mice as compared to young mice. Furthermore, the turnover rate of the components that are most affected by aging –complex III components (ubiquinol cytochrome C oxidoreductase) and complex IV components (cytochrome C oxidase)– was significantly increased in the senescent cerebellum. However, the turnover rates of proteins involved in mitophagy (i.e., the proteasomal and lysosomal degradation of damaged mitochondria) were not significantly altered with age. Overall, our results suggest that an age-related imbalance in the turnover rates of proteins involved in mitochondrial biogenesis and mitophagy (DMN1l, FIS1) in conjunction with an age-related imbalance in the turnover rates of proteins of the complexes III and IV of the electron transfer chain, might impair cerebellar mitochondrial bioenergetics in old mice.

Identification of human age-associated gene co-expressions in functional modules using liquid association

Aging is a major risk factor for age-related diseases such as certain cancers. In this study, we developed Age Associated Gene Co-expression Identifier (AAGCI), a liquid association based method to infer age-associated gene co-expressions at thousands of biological processes and pathways across 9 human tissues. Several hundred to thousands of gene pairs were inferred to be age co-expressed across different tissues, the genes involved in which are significantly enriched in functions like immunity, ATP binding, DNA damage, and many cancer pathways. The age co-expressed genes are significantly overlapped with aging genes curated in the GenAge database across all 9 tissues, suggesting a tissue-wide correlation between age-associated genes and co-expressions. Interestingly, age-associated gene co-expressions are significantly different from gene co-expressions identified through correlation analysis, indicating that aging might only contribute to a small portion of gene co-expressions. Moreover, the key driver analysis identified biologically meaningful genes in important function modules. For example, IGF1, ERBB2, TP53 and STAT5A were inferred to be key genes driving age co-expressed genes in the network module associated with function “T cell proliferation”. Finally, we prioritized a few anti-aging drugs such as metformin based on an enrichment analysis between age co-expressed genes and drug signatures from a recent study. The predicted drugs were partially validated by literature mining and can be readily used to generate hypothesis for further experimental validations.

Hippocampal Transcriptomic Profiles: Subfield Vulnerability to Age and Cognitive Impairment

The current study employed next-generation RNA sequencing to examine gene expression differences related to brain aging, cognitive decline, and hippocampal subfields. Young and aged rats were trained on a spatial episodic memory task. Hippocampal regions CA1, CA3, and the dentate gyrus were isolated. Poly-A mRNA was examined using two different sequencing platforms, Illumina, and Ion Proton. The Illumina platform was used to generate seed lists of genes that were statistically differentially expressed across regions, ages, or in association with cognitive function. The gene lists were then retested using the data from the Ion Proton platform. The results indicate hippocampal subfield differences in gene expression and point to regional differences in vulnerability to aging. Aging was associated with increased expression of immune response-related genes, particularly in the dentate gyrus. For the memory task, impaired performance of aged animals was linked to the regulation of Ca²⁺ and synaptic function in region CA1. Finally, we provide a transcriptomic characterization of the three subfields regardless of age or cognitive status, highlighting and confirming a correspondence between cytoarchitectural boundaries and molecular profiling.

Aging as an Epigenetic Phenomenon

INTRODUCTION

Hypermethylation of genes associated with promoter CpG islands, and hypomethylation of CpG poor genes, repeat sequences, transposable elements and intergenic genome sections occur during aging in mammals. Methylation levels of certain CpG sites display strict correlation to age and could be used as "epigenetic clock" to predict biological age. Multi-substrate deacetylases SIRT1 and SIRT6 affect aging via locus-specific modulations of chromatin structure and activity of multiple regulatory proteins involved in aging. Random errors in DNA methylation and other epigenetic marks during aging increase the transcriptional noise, and thus lead to enhanced phenotypic variation between cells of the same tissue. Such variation could cause progressive organ dysfunction observed in aged individuals. Multiple experimental data show that induction of NF-κB regulated gene sets occurs in various tissues of aged mammals. Upregulation of multiple miRNAs occurs at mid age leading to downregulation of enzymes and regulatory proteins involved in basic cellular functions, such as DNA repair, oxidative phosphorylation, intermediate metabolism, and others.

CONCLUSION

Strong evidence shows that all epigenetic systems contribute to the lifespan control in various organisms. Similar to other cell systems, epigenome is prone to gradual degradation due to the genome damage, stressful agents, and other aging factors. But unlike mutations and other kinds of the genome damage, age-related epigenetic changes could be fully or partially reversed to a "young" state.

Microarray analysis of aging-associated immune system alterations in the rostral ventrolateral medulla of F344 rats

The rostral ventrolateral medulla (RVLM) is an area of the brain stem that contains diverse neural substrates that are involved in systems critical for physiological function. There is evidence that aging affects some neural substrates within the RVLM, although age-related changes in RVLM molecular mechanisms are not well established. The goal of the present study was to characterize the transcriptomic profile of the aging RVLM and to test the hypothesis that aging is associated with altered gene expression in the RVLM, with an emphasis on immune system associated gene transcripts. RVLM tissue punches from young, middle-aged, and aged F344 rats were analyzed with Agilent's whole rat genome microarray. The RVLM gene expression profile varied with age, and an association between chronological age and specific RVLM gene expression patterns was observed [P < 0.05, false discovery rate (FDR) < 0.3]. Functional analysis of RVLM microarray data via gene ontology profiling and pathway analysis identified upregulation of genes associated with immune- and stress-related responses and downregulation of genes associated with lipid biosynthesis and neurotransmission in aged compared with middle-aged and young rats. Differentially expressed genes associated with the complement system and microglial cells were further validated by quantitative PCR with separate RVLM samples (P < 0.05, FDR < 0.1). The present results have identified age-related changes in the transcriptomic profile of the RVLM, modifications that may provide the molecular backdrop for understanding age-dependent changes in physiological regulation.

Identification of a T cell gene expression clock obtained by exploiting a MZ twin design

Many studies investigated age-related changes in gene expression of different tissues, with scarce agreement due to the high number of affecting factors. Similarly, no consensus has been reached on which genes change expression as a function of age and not because of environment. In this study we analysed gene expression of T lymphocytes from 27 healthy monozygotic twin couples, with ages ranging over whole adult lifespan (22 to 98 years). This unique experimental design allowed us to identify genes involved in normative aging, which expression changes independently from environmental factors. We obtained a transcriptomic signature with 125 genes, from which chronological age can be estimated. This signature has been tested in two datasets of same cell type hybridized over two different platforms, showing a significantly better performance compared to random signatures. Moreover, the same signature was applied on a dataset from a different cell type (human muscle). A lower performance was obtained, indicating the possibility that the signature is T cell-specific. As a whole our results suggest that this approach can be useful to identify age-modulated genes.

Cell-based therapeutic strategies for replacement and preservation in retinal degenerative diseases

Cell-based therapeutics offer diverse options for treating retinal degenerative diseases, such as age-related macular degeneration (AMD) and retinitis pigmentosa (RP). AMD is characterized by both genetic and environmental risks factors, whereas RP is mainly a monogenic disorder. Though treatments exist for some patients with neovascular AMD, a majority of retinal degenerative patients have no effective therapeutics, thus indicating a need for universal therapies to target diverse patient populations. Two main cell-based mechanistic approaches are being tested in clinical trials. Replacement therapies utilize cell-derived retinal pigment epithelial (RPE) cells to supplant lost or defective host RPE cells. These cells are similar in morphology and function to native RPE cells and can potentially supplant the responsibilities of RPE in vivo. Preservation therapies utilize supportive cells to aid in visual function and photoreceptor preservation partially by neurotrophic mechanisms. The goal of preservation strategies is to halt or slow the progression of disease and maintain remaining visual function. A number of clinical trials are testing the safety of replacement and preservation cell therapies in patients; however, measures of efficacy will need to be further evaluated. In addition, a number of prevailing concerns with regards to the immune-related response, longevity, and functionality of the grafted cells will need to be addressed in future trials. This review will summarize the current status of cell-based preclinical and clinical studies with a focus on replacement and preservation strategies and the obstacles that remain regarding these types of treatments.

Nuclear but not mitochondrial-encoded oxidative phosphorylation genes are altered in aging, mild cognitive impairment, and Alzheimer's disease

INTRODUCTION

We have comprehensively described the expression profiles of mitochondrial DNA and nuclear DNA genes that encode subunits of the respiratory oxidative phosphorylation (OXPHOS) complexes (I-V) in the hippocampus from young controls, age matched, mild cognitively impaired (MCI), and Alzheimer's disease (AD) subjects.

METHODS

Hippocampal tissues from 44 non-AD controls (NC), 10 amnestic MCI, and 18 AD cases were analyzed on Affymetrix Hg-U133 plus 2.0 arrays.

RESULTS

The microarray data revealed significant down regulation in OXPHOS genes in AD, particularly those encoded in the nucleus. In contrast, there was up regulation of the same gene(s) in MCI subjects compared to AD and ND cases. No significant differences were observed in mtDNA genes identified in the array between AD, ND, and MCI subjects except one mt-ND6.

DISCUSSION

Our findings suggest that restoration of the expression of nuclear-encoded OXPHOS genes in aging could be a viable strategy for blunting AD progression.

Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts

Aging is a major risk factor in many forms of late-onset neurodegenerative disorders. The ability to recapitulate age-related characteristics of human neurons in culture will offer unprecedented opportunities to study the biological processes underlying neuronal aging. Here, we show that using a recently demonstrated microRNA-based cellular reprogramming approach, human fibroblasts from postnatal to near centenarian donors can be efficiently converted into neurons that maintain multiple age-associated signatures. Application of an epigenetic biomarker of aging (referred to as epigenetic clock) to DNA methylation data revealed that the epigenetic ages of fibroblasts were highly correlated with corresponding age estimates of reprogrammed neurons. Transcriptome and microRNA profiles reveal genes differentially expressed between young and old neurons. Further analyses of oxidative stress, DNA damage and telomere length exhibit the retention of age-associated cellular properties in converted neurons from corresponding fibroblasts. Our results collectively demonstrate the maintenance of age after neuronal conversion.

Aging Shapes the Population-Mean and -Dispersion of Gene Expression in Human Brains

Human aging is associated with cognitive decline and an increased risk of neurodegenerative disease. Our objective for this study was to evaluate potential relationships between age and variation in gene expression across different regions of the brain. We analyzed the Genotype-Tissue Expression (GTEx) data from 54 to 101 tissue samples across 13 brain regions in post-mortem donors of European descent aged between 20 and 70 years at death. After accounting for the effects of covariates and hidden confounding factors, we identified 1446 protein-coding genes whose expression in one or more brain regions is correlated with chronological age at a false discovery rate of 5%. These genes are involved in various biological processes including apoptosis, mRNA splicing, amino acid biosynthesis, and neurotransmitter transport. The distribution of these genes among brain regions is uneven, suggesting variable regional responses to aging. We also found that the aging response of many genes, e.g., TP37 and C1QA, depends on individuals' genotypic backgrounds. Finally, using dispersion-specific analysis, we identified genes such as IL7R, MS4A4E, and TERF1/TERF2 whose expressions are differentially dispersed by aging, i.e., variances differ between age groups. Our results demonstrate that age-related gene expression is brain region-specific, genotype-dependent, and associated with both mean and dispersion changes. Our findings provide a foundation for more sophisticated gene expression modeling in the studies of age-related neurodegenerative diseases.

Sixteen kiwi (Apteryx spp) transcriptomes provide a wealth of genetic markers and insight into sex chromosome evolution in birds

Background

Kiwi represent the most basal extant avian lineage (paleognaths) and exhibit biological attributes that are unusual or extreme among living birds, such as large egg size, strong olfaction, nocturnality, flightlessness and long lifespan. Despite intense interest in their evolution and their threatened status, genomic resources for kiwi were virtually non-existent until the recent publication of a single genome. Here we present the most comprehensive kiwi transcriptomes to date, obtained via Illumina sequencing of whole blood and de novo assembly of mRNA sequences of eight individuals from each of the two rarest kiwi species, little spotted kiwi (LSK; Apteryx owenii) and rowi (A. rowi).

Results

Sequences obtained were orthologous with a wide diversity of functional genes despite the sequencing of a single tissue type. Individual and composite assemblies contain more than 7900 unique protein coding transcripts in each of LSK and rowi that show strong homology with chicken (Gallus gallus), including those associated with growth, development, disease resistance, reproduction and behavior. The assemblies also contain 66,909 SNPs that distinguish between LSK and rowi, 12,384 SNPs among LSK (associated with 3088 genes), and 29,313 SNPs among rowi (associated with 4953 genes). We found 3084 transcripts differentially expressed between LSK and rowi and 150 transcripts differentially expressed between the sexes. Of the latter, 83 could be mapped to chicken chromosomes with 95% syntenic with chromosome Z.

Conclusions

Our study has simultaneously sequenced multiple species, sexes, and individual kiwi at thousands of genes, and thus represents a significant leap forward in genomic resources available for kiwi. The expression pattern we observed among chromosome Z related genes in kiwi is similar to that observed in ostriches and emu, suggesting a common and ancestral pattern of sex chromosome homomorphy, recombination, and gene dosage among living paleognaths. The transcriptome assemblies described here will provide a rich resource for polymorphic marker development and studies of adaptation of these highly unusual and endangered birds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2714-2) contains supplementary material, which is available to authorized users.

Transcription Profile of Aging and Cognition-Related Genes in the Medial Prefrontal Cortex

Cognitive function depends on transcription; however, there is little information linking altered gene expression to impaired prefrontal cortex function during aging. Young and aged F344 rats were characterized on attentional set shift and spatial memory tasks. Transcriptional differences associated with age and cognition were examined using RNA sequencing to construct transcriptomic profiles for the medial prefrontal cortex (mPFC), white matter, and region CA1 of the hippocampus. The results indicate regional differences in vulnerability to aging. Age-related gene expression in the mPFC was similar to, though less robust than, changes in the dorsolateral PFC of aging humans suggesting that aging processes may be similar. Importantly, the pattern of transcription associated with aging did not predict cognitive decline. Rather, increased mPFC expression of genes involved in regulation of transcription, including transcription factors that regulate the strength of excitatory and inhibitory inputs, and neural activity-related immediate-early genes was observed in aged animals that exhibit delayed set shift behavior. The specificity of impairment on a mPFC-dependent task, associated with a particular mPFC transcriptional profile indicates that impaired executive function involves altered transcriptional regulation and neural activity/plasticity processes that are distinct from that described for impaired hippocampal function.