Mitochondrial Dysfunction in Age‐Related Metabolic Disorders

Aging is a natural biological process in living organisms characterized by receding bioenergetics. Mitochondria are crucial for cellular bioenergetics and thus an important contributor to age‐related energetics deterioration. In addition, mitochondria play a major role in calcium signaling, redox homeostasis, and thermogenesis making this organelle a major cellular component that dictates the fate of a cell. To maintain its quantity and quality, mitochondria undergo multiple processes such as fission, fusion, and mitophagy to eliminate or replace damaged mitochondria. While this bioenergetics machinery is properly protected, the functional decline associated with age and age‐related metabolic diseases is mostly a result of failure in such protective mechanisms. In addition, metabolic by‐products like reactive oxygen species also aid in this destructive pathway. Mitochondrial dysfunction has always been thought to be associated with diseases. Moreover, studies in recent years have pointed out that aging contributes to the decay of mitochondrial health by promoting imbalances in key mitochondrial‐regulated pathways. Hence, it is crucial to understand the nexus of mitochondrial dysfunction in age‐related diseases. This review focuses on various aspects of basic mitochondrial biology and its status in aging and age‐related metabolic diseases.     

Accumulation of “Old Proteins” and the Critical Need for MS‐based Protein Turnover Measurements in Aging and Longevity

Aging and age‐related diseases are accompanied by proteome remodeling and progressive declines in cellular machinery required to maintain protein homeostasis (proteostasis), such as autophagy, ubiquitin‐mediated degradation, and protein synthesis. While many studies have focused on capturing changes in proteostasis, the identification of proteins that evade these cellular processes has recently emerged as an approach to studying the aging proteome. With advances in proteomic technology, it is possible to monitor protein half‐lives and protein turnover at the level of individual proteins in vivo. For large‐scale studies, these technologies typically include the use of stable isotope labeling coupled with MS and comprehensive assessment of protein turnover rates. Protein turnover studies have revealed groups of highly relevant long‐lived proteins (LLPs), such as the nuclear pore complexes, extracellular matrix proteins, and protein aggregates. Here, the role of LLPs during aging and age‐related diseases and the methods used to identify and quantify their changes are reviewed. The methods available to conduct studies of protein turnover, used in combination with traditional proteomic methods, will enable the field to perform studies in a systems biology context, as changes in proteostasis may not be revealed in studies that solely measure differential protein abundances.     

Genetic evidence for common pathways in human age‐related diseases

Aging is the single largest risk factor for chronic disease. Studies in model organisms have identified conserved pathways that modulate aging rate and the onset and progression of multiple age‐related diseases, suggesting that common pathways of aging may influence age‐related diseases in humans as well. To determine whether there is genetic evidence supporting the notion of common pathways underlying age‐related diseases, we analyzed the genes and pathways found to be associated with five major categories of age‐related disease using a total of 410 genomewide association studies (GWAS). While only a small number of genes are shared among all five disease categories, those found in at least three of the five major age‐related disease categories are highly enriched for apoliprotein metabolism genes. We found that a more substantial number of gene ontology (GO) terms are shared among the 5 age‐related disease categories and shared GO terms include canonical aging pathways identified in model organisms, such as nutrient‐sensing signaling, translation, proteostasis, stress responses, and genome maintenance. Taking advantage of the vast amount of genetic data from the GWAS, our findings provide the first direct evidence that conserved pathways of aging simultaneously influence multiple age‐related diseases in humans as has been demonstrated in model organisms.     

Molecular and physiological manifestations and measurement of aging in humans

Biological aging is associated with a reduction in the reparative and regenerative potential in tissues and organs. This reduction manifests as a decreased physiological reserve in response to stress (termed homeostenosis) and a time‐dependent failure of complex molecular mechanisms that cumulatively create disorder. Aging inevitably occurs with time in all organisms and emerges on a molecular, cellular, organ, and organismal level with genetic, epigenetic, and environmental modulators. Individuals with the same chronological age exhibit differential trajectories of age‐related decline, and it follows that we should assess biological age distinctly from chronological age. In this review, we outline mechanisms of aging with attention to well‐described molecular and cellular hallmarks and discuss physiological changes of aging at the organ‐system level. We suggest methods to measure aging with attention to both molecular biology (e.g., telomere length and epigenetic marks) and physiological function (e.g., lung function and echocardiographic measurements). Finally, we propose a framework to integrate these molecular and physiological data into a composite score that measures biological aging in humans. Understanding the molecular and physiological phenomena that drive the complex and multifactorial processes underlying the variable pace of biological aging in humans will inform how researchers assess and investigate health and disease over the life course. This composite biological age score could be of use to researchers seeking to characterize normal, accelerated, and exceptionally successful aging as well as to assess the effect of interventions aimed at modulating human aging.     

比较图元向量和点的聚类系数对差异网络的研究

差异分析对于揭示生命体的生长、发育和衰老过程及疾病发生具有重大的意义,基于网络的差异分析方法已经成为系统生物学的一个研究热点。网络节点往往通过与局部结构作用实现某种功能,其与局部结构的关系变化,很可能影响其功能。本文利用仿真实验的方法比较了图元向量和点的聚类系数两种局部结构测度的性能,并且利用他们分别设计算法挖掘差异网络中模块化变化的基因簇。应用AGEMAP数据库中小鼠12个组织基因表达数据进行实验,大部分聚类簇都高度显著富集与衰老相关的GO项。     

Integrating cellular senescence with the concept of damage accumulation in aging: Relevance for clearance of senescent cells

Understanding the aging process and ways to manipulate it is of major importance for biology and medicine. Among the many aging theories advanced over the years, the concept most consistent with experimental evidence posits the buildup of numerous forms of molecular damage as a foundation of the aging process. Here, we discuss that this concept integrates well with recent findings on cellular senescence, offering a novel view on the role of senescence in aging and age‐related disease. Cellular senescence has a well‐established role in cellular aging, but its impact on the rate of organismal aging is less defined. One of the most prominent features of cellular senescence is its association with macromolecular damage. The relationship between cell senescence and damage concerns both damage as a molecular signal of senescence induction and accelerated accumulation of damage in senescent cells. We describe the origin, regulatory mechanisms, and relevance of various damage forms in senescent cells. This view on senescent cells as carriers and inducers of damage puts new light on senescence, considering it as a significant contributor to the rise in organismal damage. Applying these ideas, we critically examine current evidence for a role of cellular senescence in aging and age‐related diseases. We also discuss the differential impact of longevity interventions on senescence burden and other types of age‐related damage. Finally, we propose a model on the role of aging‐related damage accumulation and the rate of aging observed upon senescent cell clearance.     

Predicting Disease-Related Proteins Based on Clique Backbone in Protein-Protein Interaction Network

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.     

Resveratrol and rapamycin: are they anti‐aging drugs?

Studies of the basic biology of aging have advanced to the point where anti‐aging interventions, identified from experiments in model organisms, are beginning to be tested in people. Resveratrol and rapamycin, two compounds that target conserved longevity pathways and may mimic some aspects of dietary restriction, represent the first such interventions. Both compounds have been reported to slow aging in yeast and invertebrate species, and rapamycin has also recently been found to increase life span in rodents. In addition, both compounds also show impressive effects in rodent models of age‐associated diseases. Clinical trials are underway to assess whether resveratrol is useful as an anti‐cancer treatment, and rapamycin is already approved for use in human patients. Compounds such as these, identified from longevity studies in model organisms, hold great promise as therapies to target multiple age‐related diseases by modulating the molecular causes of aging.     

Telomere length behaves as biomarker of somatic redundancy rather than biological age

Biomarkers of aging are essential to predict mortality and aging‐related diseases. Paradoxically, age itself imposes a limitation on the use of known biomarkers of aging because their associations with mortality generally diminish with age. How this pattern arises is, however, not understood. With meta‐analysis we show that human leucocyte telomere length (TL) predicts mortality, and that this mortality association diminishes with age, as found for other biomarkers of aging. Subsequently, we demonstrate with simulation models that this observation cannot be reconciled with the popular hypothesis that TL is proportional to biological age. Using the reliability theory of aging, we instead propose that TL is a biomarker of somatic redundancy, the body's capacity to absorb damage, which fits the observed pattern well. We discuss to what extent diminishing redundancy with age may also explain the observed diminishing mortality modulation with age of other biomarkers of aging. Considering diminishing somatic redundancy as the causal agent of aging may critically advance our understanding of the aging process, and improve predictions of life expectancy and vulnerability to aging‐related diseases.     

Reducing signs of aging and increasing lifespan by drug synergy

Disease incidence rises rapidly with age and increases both human suffering and economic hardship while shortening life. Advances in understanding the signaling pathways and cellular processes that influence aging support the possibility of reducing the incidence of age‐related diseases and increasing lifespan by pharmacological intervention. Here, we demonstrate a novel pharmacological strategy that both reduces signs of aging in the budding yeast Saccharomyces cerevisiae and generates a synergistic increase in lifespan. By combining a low dose of rapamycin, to reduce activity of the target of rapamycin complex 1 (TORC1) protein kinase, and myriocin, to reduce sphingolipid synthesis, we show enhancement of autophagy, genomic stability, mitochondrial function, and AMP kinase pathway activity. These processes are controlled by evolutionarily conserved signal transduction pathways that are vital for maintaining a healthy state and promoting a long life. Thus, our data show that it ought to be possible to find pharmacological approaches to generate a synergistic reduction in the incidence of human age‐related diseases to improve health quality in the elderly and enhance lifespan.     

Is the secret for a successful aging to keep track of cancer pathways?

A successful aging could be gained by life satisfaction, social functioning, or psychological resources and, definitely, by increasing resistance to diverse age‐related pathologies. Nowadays, cancer can be considered an age‐related disease since the incidence of most cancers increases with age, rising more rapidly beginning in midlife. Although adults with extended longevity are less likely to develop cancer, it is now emerging that aging and cancer share common molecular links, and thus targeting these mechanisms may be suitable to treat multiple disorders, for the prolonging of healthy aging. At present, one of the cornerstones of antiaging is hormone‐replacement therapy to treat diseases associated with a state of age‐related sex‐hormone deficiency in women and men; however, many studies question the relationship of hormone replacement to cancer recurrence. Here, we discuss signaling and metabolic molecular crossroad linking aging and cancer. This is useful to argue about the current knowledge of prolongevity and druggable targets and to motivate specific intervention strategies that could modify practices of the aging population, activating multiple longevity pathways but keeping track of cancer pathways, thereby potentially preserving health status.     

Toward computational systems biology

The development and successful application of high-throughput technologies are transforming biological research. The large quantities of data being generated by these technologies have led to the emergence of systems biology, which emphasizes large-scale, parallel characterization of biological systems and integration of fragmentary information into a coherent whole. Complementing the reductionist approach that has dominated biology for the last century, mathematical modeling is becoming a powerful tool to achieve an integrated understanding of complex biological systems and to guide experimental efforts of engineering biological systems for practical applications. Here I give an overview of current mainstream approaches in modeling biological systems, highlight specific applications of modeling in various settings, and point out future research opportunities and challenges.     

Epigenetics and migraine; complex mitochondrial interactions contributing to disease susceptibility

Migraine is a common neurological disorder classified by the World Health Organisation (WHO) as one of the top twenty most debilitating diseases in the developed world. Current therapies are only effective for a proportion of sufferers and new therapeutic targets are desperately needed to alleviate this burden. Recently the role of epigenetics in the development of many complex diseases including migraine has become an emerging topic. By understanding the importance of acetylation, methylation and other epigenetic modifications, it then follows that this modification process is a potential target to manipulate epigenetic status with the goal of treating disease. Bisulphite sequencing and methylated DNA immunoprecipitation have been used to demonstrate the presence of methylated cytosines in the human D-loop of mitochondrial DNA (mtDNA), proving that the mitochondrial genome is methylated. For the first time, it has been shown that there is a difference in mtDNA epigenetic status between healthy controls and those with disease, especially for neurodegenerative and age related conditions. Given co-morbidities with migraine and the suggestive link between mitochondrial dysfunction and the lowered threshold for triggering a migraine attack, mitochondrial methylation may be a new avenue to pursue. Creative thinking and new approaches are needed to solve complex problems and a systems biology approach, where multiple layers of information are integrated is becoming more important in complex disease modelling.     

Potentials of single‐cell biology in identification and validation of disease biomarkers

Single‐cell biology is considered a new approach to identify and validate disease‐specific biomarkers. However, the concern raised by clinicians is how to apply single‐cell measurements for clinical practice, translate the message of single‐cell systems biology into clinical phenotype or explain alterations of single‐cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single‐cell gene sequencing in the identification and development of disease‐specific biomarkers, the definition and significance of single‐cell biology and single‐cell systems biology in the understanding of single‐cell full picture, the development and establishment of whole‐cell models in the validation of targeted biological function and the figure and meaning of single‐molecule imaging in single cell to trace intra‐single‐cell molecule expression, signal, interaction and location. We headline the important role of single‐cell biology in the discovery and development of disease‐specific biomarkers with a special emphasis on understanding single‐cell biological functions, e.g. mechanical phenotypes, single‐cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi‐dimensional, multi‐layer, multi‐crossing and stereoscopic single‐cell biology definitely benefits the discovery and development of disease‐specific biomarkers.     

Transcriptome analysis reveals the difference between “healthy” and “common” aging and their connection with age‐related diseases

A key goal of aging research was to understand mechanisms underlying healthy aging and develop methods to promote the human healthspan. One approach is to identify gene regulations unique to healthy aging compared with aging in the general population (i.e., “common” aging). Here, we leveraged Genotype‐Tissue Expression (GTEx) project data to investigate “healthy” and “common” aging gene expression regulations at a tissue level in humans and their interconnection with diseases. Using GTEx donors' disease annotations, we defined a “healthy” aging cohort for each tissue. We then compared the age‐associated genes derived from this cohort with age‐associated genes from the “common” aging cohort which included all GTEx donors; we also compared the “healthy” and “common” aging gene expressions with various disease‐associated gene expressions to elucidate the relationships among “healthy,” “common” aging and disease. Our analyses showed that 1. GTEx “healthy” and “common” aging shared a large number of gene regulations; 2. Despite the substantial commonality, “healthy” and “common” aging genes also showed distinct function enrichment, and “common” aging genes had a higher enrichment for disease genes; 3. Disease‐associated gene regulations were overall different from aging gene regulations. However, for genes regulated by both, their regulation directions were largely consistent, implying some aging processes could increase the susceptibility to disease development; and 4. Possible protective mechanisms were associated with some “healthy” aging gene regulations. In summary, our work highlights several unique features of GTEx “healthy” aging program. This new knowledge could potentially be used to develop interventions to promote the human healthspan.     

Liver diseases and aging: friends or foes?

The liver is the only internal human organ capable of natural regeneration of lost tissue, as little as 25% of a liver can regenerate into a whole liver. The process of aging predisposes to hepatic functional and structural impairment and metabolic risk. Therefore, understanding how aging could affect the molecular pathology of liver diseases is particularly important, and few studies to date have tackled this complex process. The most common liver disease, affecting one‐third of the overall population, is nonalcoholic fatty liver disease (NAFLD), characterized by an intrahepatic accumulation of lipids. NAFLD can evolve into nonalcoholic steatohepatitis (NASH) in the presence of oxidative stress and inflammation. NASH is a serious risk factor for disabling and deadly liver diseases such as cirrhosis and hepatocellular carcinoma (HCC). Old age seems to favor NAFLD, NASH, and ultimately HCC, in agreement with the inflamm‐aging theory, according to which aging accrues inflammation. However, the incidence of HCC drops significantly in the very elderly (individuals aged more than 70) and the relationship between the progression of NAFLD/NASH/HCC and very old age is obscure. In this review, we discuss the literature and we argue that there might be an age window in which the liver becomes resistant to the development of injury; this needs to be studied to understand fully the interaction between age and liver diseases from a therapeutic perspective.