A mathematical model of aging-related and cortisol induced hippocampal dysfunction

Flibanserin conquers murine depressive pseudodementia by amending HPA axis, maladaptive inflammation and AKT/GSK/STAT/BDNF trajectory: Center-staging of the serotonergic/adrenergic circuitry

Depressive pseudodementia (DPD) is a debilitating cognitive dysfunction that accompanies major and/or frequent depressive attacks. DPD has gained significant research attention owing to its negative effects on the patients' quality of life and productivity. This study tested the procognitive potential of Flibanserin (FBN), the serotonin (5HT) receptor modulator, against propranolol (PRP), as β/5HT1A receptors blocker. Serving this purpose, female Wistar Albino rats were subjected to chronic unpredictable stress (CUS) and subsequently treated with FBN only (3 mg/kg/day, p.o), PRP only (10 mg/kg/day, p.o), or PRP followed by FBN, using the same doses. FBN ameliorated the behavioral/cognitive alterations and calmed the hypothalamic-pituitary-adrenal (HPA) axis storm by reducing the levels of stress-related hormones, viz, corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH), corticosterone (CORT) parallel to epinephrine (EPI) hyperstimulation. The maladaptive inflammatory response, comprising of interleukin (IL)-1β/6, and tumor necrosis factor (TNF)-α, was consequently blunted. This was contemporaneous to the partial restoration of the protein kinase-B (AKT)/glycogen synthase kinase (GSK)3β/signal transducer and activator of transcription (STAT)-3 survival trajectory and the reinstatement of the levels of brain derived neurotrophic factor (BDNF). Microscopically, FBN repaired the hippocampal architecture and lessened CD68/GFAP immunoreactivity. Pre-administration of PRP partially abolished FBN effect along the estimated parameters, except for 5HT2A receptor expression and epinephrine level, to prove 5HT1A receptor as a fulcrum initiator of the investigated pathway, while its sole administration worsened the underlying condition. Ultimately, these findings highlight the immense procognitive potential of FBN, offering a new paradigm for halting DPD advancement via synchronizing adrenergic/serotonergic circuitry.

Vascular dementia: From pathobiology to emerging perspectives

Vascular dementia (VaD) is the second most common type of dementia. VaD is synonymous with ageing, and its symptoms place a significant burden on the health and wellbeing of older people. Despite the identification of a substantial number of risk factors for VaD, the pathological mechanisms underpinning this disease remain to be fully elucidated. Consequently, a biogerontological imperative exists to highlight the modifiable lifestyle factors which can mitigate against the risk of developing VaD. This review will critically examine some of the factors which have been revealed to modulate VaD risk. The survey commences by providing an overview of the putative mechanisms which are associated with the pathobiology of VaD. Next, the factors which influence the risk of developing VaD are examined. Finally, emerging treatment avenues including epigenetics, the gut microbiome, and pro-longevity pharmaceuticals are discussed. By drawing this key evidence together, it is our hope that it can be used to inform future experimental investigations in this field.

The amyloid cascade hypothesis: an updated critical review

Results from recent clinical trials of antibodies that target amyloid-β (Aβ) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aβ may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aβ playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

Infertility and cortisol: a systematic review

Introduction

Stress and infertility form a complex relationship. In line with this, various stress-related biological markers have been investigated in infertility.

Methods

This systematic review was performed using PRISMA guidelines (i) to report whether cortisol is highly present in infertile patients compared to fertile control; (ii) to report whether there is any significant difference in the cortisol level in infertile subjects that conceive and those that didn't at the end of assisted reproduction treatments. Original articles involving human (male and female) as subjects were extracted from four electronic databases, including the list of references from the published papers. Sixteen original full-length articles involving male (4), female (11), and both genders (1) were included.

Results

Findings from studies that compared the cortisol level between infertile and fertile subjects indicate that (i) Male: three studies reported elevated cortisol level in infertile patients and one found no significant difference; (ii) Female: four studies reported increased cortisol level in infertile subjects and three studies found no significant difference. Findings from studies that measured the cortisol level from infertile patients that conceived and those that didn't indicate that (i) Male: one study reported no significant difference; (ii) Female: one study reported elevated cortisol in infertile patients that conceived, whereas two studies reported increased cortisol in infertile patients that was unable to conceive. Five studies found no significant difference between the groups.

Discussion

In the present review we only included the cortisol value that was measured prior to stimulation or IVF treatment or during natural or spontaneous cycles, despite this, there are still variations in the sampling period, assessment techniques and patients' characteristics. Hence, at present, we are still unable to conclude that cortisol is significantly elevated in infertile patients. We warrant future studies to standardize the time of biological sample collection and other limitations that were addressed in the review to negate the unwanted influencing factors.

A Neurobiological Framework for the Therapeutic Potential of Music and Sound Interventions for Post-Traumatic Stress Symptoms in Critical Illness Survivors

Overview: Post traumatic stress disorder (PTSD) has emerged as a severely debilitating psychiatric disorder associated with critical illness. Little progress has been made in the treatment of post-intensive care unit (ICU) PTSD. Aim: To synthesize neurobiological evidence on the pathophysiology of PTSD and the brain areas involved, and to highlight the potential of music to treat post-ICU PTSD. Methods: Critical narrative review to elucidate an evidence-based neurobiological framework to inform the study of music interventions for PTSD post-ICU. Literature searches were performed in PubMed and CINAHL. The Scale for the Assessment of Narrative Review Articles (SANRA) guided reporting. Results: A dysfunctional HPA axis feedback loop, an increased amygdalic response, hippocampal atrophy, and a hypoactive prefrontal cortex contribute to PTSD symptoms. Playing or listening to music can stimulate neurogenesis and neuroplasticity, enhance brain recovery, and normalize stress response. Additionally, evidence supports effectiveness of music to improve coping and emotional regulation, decrease dissociation symptoms, reduce depression and anxiety levels, and overall reduce severity of PTSD symptoms. Conclusions: Despite the lack of music interventions for ICU survivors, music has the potential to help people suffering from PTSD by decreasing amygdala activity, improving hippocampal and prefrontal brain function, and balancing the HPA-axis.

Modeling cholesterol metabolism and atherosclerosis

Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality among Western populations. Many risk factors have been identified for ASCVD; however, elevated low-density lipoprotein cholesterol (LDL-C) remains the gold standard. Cholesterol metabolism at the cellular and whole-body level is maintained by an array of interacting components. These regulatory mechanisms have complex behavior. Likewise, the mechanisms which underpin atherogenesis are nontrivial and multifaceted. To help overcome the challenge of investigating these processes mathematical modeling, which is a core constituent of the systems biology paradigm has played a pivotal role in deciphering their dynamics. In so doing models have revealed new insights about the key drivers of ASCVD. The aim of this review is fourfold; to provide an overview of cholesterol metabolism and atherosclerosis, to briefly introduce mathematical approaches used in this field, to critically discuss models of cholesterol metabolism and atherosclerosis, and to highlight areas where mathematical modeling could help to investigate in the future. This article is categorized under: Cardiovascular Diseases > Computational Models.

Aging, Social Distancing, and COVID-19 Risk: Who is more Vulnerable and Why?

Perceived social support represents an important predictor of healthy aging. The global COVID-19 pandemic has dramatically changed the face of social relationships and revealed elderly to be particularly vulnerable to the effects of social isolation. Social distancing may represent a double-edged sword for older adults, protecting them against COVID-19 infection while also sacrificing personal interaction and attention at a critical time. Here, we consider the moderating role of social relationships as a potential influence on stress resilience, allostatic load, and vulnerability to infection and adverse health outcomes in the elderly population. Understanding the mechanisms how social support enhances resilience to stress and promotes mental and physical health into old age will enable new preventive strategies. Targeted social interventions may provide effective relief from the impact of COVID-19-related isolation and loneliness. In this regard, a pandemic may also offer a window of opportunity for raising awareness and mobilizing resources for new strategies that help build resilience in our aging population and future generations.

Omics in a Digital World: The Role of Bioinformatics in Providing New Insights Into Human Aging

Background

Aging is a complex phenotype influenced by a combination of genetic and environmental factors. Although many studies addressed its cellular and physiological age-related changes, the molecular causes of aging remain undetermined. Considering the biological complexity and heterogeneity of the aging process, it is now clear that full understanding of mechanisms underlying aging can only be achieved through the integration of different data types and sources, and with new computational methods capable to achieve such integration.

Recent Advances

In this review, we show that an omics vision of the age-dependent changes occurring as the individual ages can provide researchers with new opportunities to understand the mechanisms of aging. Combining results from single-cell analysis with systems biology tools would allow building interaction networks and investigate how these networks are perturbed during aging and disease. The development of high-throughput technologies such as next-generation sequencing, proteomics, metabolomics, able to investigate different biological markers and to monitor them simultaneously during the aging process with high accuracy and specificity, represents a unique opportunity offered to biogerontologists today.

Critical Issues

Although the capacity to produce big data drastically increased over the years, integration, interpretation and sharing of high-throughput data remain major challenges. In this paper we present a survey of the emerging omics approaches in aging research and provide a large collection of datasets and databases as a useful resource for the scientific community to identify causes of aging. We discuss their peculiarities, emphasizing the need for the development of methods focused on the integration of different data types.

Future Directions

We critically review the contribution of bioinformatics into the omics of aging research, and we propose a few recommendations to boost collaborations and produce new insights. We believe that significant advancements can be achieved by following major developments in bioinformatics, investing in diversity, data sharing and community-driven portable bioinformatics methods. We also argue in favor of more engagement and participation, and we highlight the benefits of new collaborations along these lines. This review aims at being a useful resource for many researchers in the field, and a call for new partnerships in aging research.

Modeling Neurotransmission: Computational Tools to Investigate Neurological Disorders

The investigation of synaptic functions remains one of the most fascinating challenges in the field of neuroscience and a large number of experimental methods have been tuned to dissect the mechanisms taking part in the neurotransmission process. Furthermore, the understanding of the insights of neurological disorders originating from alterations in neurotransmission often requires the development of (i) animal models of pathologies, (ii) invasive tools and (iii) targeted pharmacological approaches. In the last decades, additional tools to explore neurological diseases have been provided to the scientific community. A wide range of computational models in fact have been developed to explore the alterations of the mechanisms involved in neurotransmission following the emergence of neurological pathologies. Here, we review some of the advancements in the development of computational methods employed to investigate neuronal circuits with a particular focus on the application to the most diffuse neurological disorders.

Role of testosterone: cortisol ratio in age- and sex-specific cortico-hippocampal development and cognitive performance

Testosterone (T) and cortisol (C) are steroid hormones that have been argued to play opposing roles in shaping physical and behavioral development in humans. While there is evidence linking T and C to different memory processes during adulthood, it remains unclear how the relative levels of T and C (TC ratio) may influence brain and behavioral development, whether they are influenced by sex of the child, and whether or not they occur as a result of stable changes in brain structure (organizational changes), as opposed to transient changes in brain function (activational changes). As such, we tested for associations among TC ratio, cortico-hippocampal structure, and standardized tests of executive, verbal, and visuo-spatial function in a longitudinal sample of typically developing 4-22-year-old children and adolescents. We found greater TC ratios to be associated with greater coordinated growth (i.e. covariance) between the hippocampus and cortical thickness in several areas primarily devoted to visual function. In addition, there was an age-related association between TC ratio and parieto-hippocampal covariance, as well as a sex-specific association between TC ratio and prefrontal-hippocampal covariance. Differences in brain structure related to TC ratio were in turn associated with lower verbal/executive function, as well as greater attention in tests of visuo-spatial abilities. These results support the notion that TC ratio may shift the balance between top-down (cortex to hippocampus) and bottom-up (hippocampus to cortex) processes, impairing more complex, cortical-based tasks and optimizing visuospatial tasks relying primarily on the hippocampus.

The sustaining effects of e-waste-related metal exposure on hypothalamus-pituitary-adrenal axis reactivity and oxidative stress

Taizhou is one of the three largest electronic waste (e-waste) recycling locations in China. At present, to prevent the environmental problems stem from e-waste dismantling, the local government shut down all the industries in 2015. However, little is known to the sustaining effects of e-waste exposure on human health after the e-waste recycling factories were closed. In this study, we collected blood samples in the residents living near e-waste dismantling factories (exposed group) and a chosen reference area (reference group) for comparison in Taizhou in December 2017.17 metals were quantitatively determined in all blood samples. Among them, the concentrations of altogether 9 metals, including chromium (Cr), arsenic (As), cobalt (Co), nickel (Ni), silver (Ag), stannum (Sn), mercury (Hg), lanthanum (La) and cerium (Ce) were significant higher in the individuals in exposed group than in reference group. Hypothalamus-pituitary-adrenal axis (HPA axis) is critical endocrine system in regulating many physical functions. We found that the concentrations of hormones in HPA axis, including corticotropin releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol, were higher in exposed group than in reference group. Moreover, we also observed significantly higher concentrations of biomarkers of oxidative stress (OS), including malondialdehyde (MDA) and 8-isoprostane (8-I), in exposed group compared with reference group even though the e-waste industries have been shut down for over 2 years. Meanwhile, the hormones in the HPA axis and the biomarkers of OS showed sinificantly positive correlation. The results of Pearson correlation and multiple linear regression showed that blood Cr and Ni positively correlated with the 3 hormones and 2 biomarkers of OS. Considering the relationship between Ni and Cr, HPA axis, OS, we speculated that high concentrations of Cr and Ni exposure could induce oxidative damage in e-waste exposure persons, and the regulations of HPA axis could play the important role during the process.

Cholesterol Homeostasis: An In Silico Investigation into How Aging Disrupts Its Key Hepatic Regulatory Mechanisms

The dysregulation of intracellular cholesterol homeostasis is associated with several age-related diseases, most notably cardiovascular disease (CVD). Research in this area has benefitted from using computational modelling to study the inherent complexity associated with the regulation of this system. In addition to facilitating hypothesis exploration, the utility of modelling lies in its ability to represent an array of rate limiting enzymatic reactions, together with multiple feedback loops, which collectively define the dynamics of cholesterol homeostasis. However, to date no model has specifically investigated the effects aging has on this system. This work addresses this shortcoming by explicitly focusing on the impact of aging on hepatic intracellular cholesterol homeostasis. The model was used to investigate the experimental findings that reactive oxygen species induce the total activation of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase (HMGCR). Moreover, the model explored the impact of an age-related decrease in hepatic acetyl-CoA acetyltransferase 2 (ACAT2). The model suggested that an increase in the activity of HMGCR does not have as significant an impact on cholesterol homeostasis as a decrease in hepatic ACAT2 activity. According to the model, a decrease in the activity of hepatic ACAT2 raises free cholesterol (FC) and decreases low-density lipoprotein cholesterol (LDL-C) levels. Increased acetyl CoA synthesis resulted in a reduction in the number of hepatic low-density lipoprotein receptors, and increased LDL-C, FC, and cholesterol esters. The rise in LDL-C was restricted by elevated hepatic FC accumulation. Taken together these findings have important implications for healthspan. This is because emerging clinical data suggest hepatic FC accumulation is relevant to the pathogenesis of non-alcoholic fatty liver disease (NAFLD), which is associated with an increased risk of CVD. These pathophysiological changes could, in part, help to explain the phenomenon of increased mortality associated with low levels of LDL-C which have been observed in certain studies involving the oldest old (≥85 years).

A Mathematical Modeling Approach to the Cort-Fitness Hypothesis

The Cort-Fitness Hypothesis has generated much interest from investigators integrating field endocrinology with evolutionary biology, ecology, and conservation. The hypothesis was developed to test the assumption that if glucocorticoid levels increase with environmental challenges and fitness decreases with environmental challenges, then there should be a negative relationship between baseline glucocorticoid levels and fitness. Indeed, studies across diverse taxa have found that the relationship between baseline glucocorticoid levels and fitness are not consistent: some studies show a positive relationship, others negative, and some show no correlation. Hence, a deeper understanding of the mechanisms underlying the relationship between baseline glucocorticoid levels, environmental challenges, and fitness is needed. We propose a mathematical model representing the links between baseline glucocorticoid levels, environmental challenges, and fitness. Our model describes how variation in the predictability and intensity of environmental challenges, reproductive strategies, and fitness metrics can all contribute to the variability observed in empirical tests of the Cort-Fitness Hypothesis. We provide qualitative results showing that much of the inconsistency in previous studies can be explained and we discuss how the model can be used to inform future Cort-Fitness studies.

Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease (Review)

Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule‑associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity.

Behaviour-Based Husbandry-A Holistic Approach to the Management of Abnormal Repetitive Behaviors

The field of zoo animal welfare science has developed significantly over recent years. However despite this progress in terms of scientific research, globally, zoo animals still face many welfare challenges. Recently, animal welfare frameworks such as the five domains or five needs have been developed and suggested to improve the welfare of zoo animals, but without practical guidance, such tools may remain abstract from the daily experience of zoo animals. Similarly specific practical strategies such as those for enrichment development exist, but their lack of holistic integration with other aspects of animal husbandry and behavioral medicine means that overall, good zoo animal welfare may still be lacking. This paper outlines some of the barriers to implementing improved zoo animal welfare in practice, and proposes a new strategy for the development of behavioral husbandry routines focused on the management and mitigation of abnormal repetitive behaviors. Focusing on enhancing zoo animal welfare by integrating aspects of ecology, ethology and clinical animal behavior into a practical and comprehensive approach to behavior-based husbandry.

The Interplay Between Cholesterol Metabolism and Intrinsic Ageing

The last few decades have witnessed remarkable progress in our understanding of ageing. From an evolutionary standpoint it is generally accepted that ageing is a non-adaptive process which is underscored by a decrease in the force of natural selection with time. From a mechanistic perspective ageing is characterized by a wide variety of cellular mechanisms, including processes such as cellular senescence, telomere attrition, oxidative damage, molecular chaperone activity, and the regulation of biochemical pathways by sirtuins. These biological findings have been accompanied by an unrelenting rise in both life expectancy and the number of older people globally. However, despite age being recognized demographically as a risk factor for healthspan, the processes associated with ageing are routinely overlooked in disease mechanisms. Thus, a central goal of biogerontology is to understand how diseases such as cardiovascular disease (CVD) are shaped by ageing. This challenge cannot be ignored because CVD is the main cause of morbidity in older people. A worthwhile way to examine how ageing intersects with CVD is to consider the effects ageing has on cholesterol metabolism, because dysregualted cholesterol metabolism is the key factor which underpins the pathology of CVD. The aim of this chapter is to outline a hypothesis which accounts for how ageing intersects with intracellular cholesterol metabolism. Moreover, we discuss the implications of this relationship for the onset of disease in the 'oldest old' (individuals ≥85 years of age). We conclude the chapter by discussing the important role mathematical modelling has to play in improving our understanding of cholesterol metabolism and ageing.

Systems Biology in Aging Research

Systems biology is an approach to collect high-dimensional data and analyze in an integrated manner. As aging is a complicated physiological functional decline in biological system, the methods in systems biology could be utilized in aging studies. Here we reviewed recent advances in systems biology in aging research and divide them into two major parts. One is the data resource, which includes omics data from DNA, RNA, proteins, epigenetic changes, metabolisms, and recently single-cell-level variations. The other is the data analysis methods consisting of network and modeling approaches. With all the data and the tools to analyze them, we could further promote our understanding of the systematic aging.

The Impact of Mathematical Modeling in Understanding the Mechanisms Underlying Neurodegeneration: Evolving Dimensions and Future Directions

Neurodegenerative diseases are a heterogeneous group of disorders that are characterized by the progressive dysfunction and loss of neurons. Here, we distil and discuss the current state of modeling in the area of neurodegeneration, and objectively compare the gaps between existing clinical knowledge and the mechanistic understanding of the major pathological processes implicated in neurodegenerative disorders. We also discuss new directions in the field of neurodegeneration that hold potential for furthering therapeutic interventions and strategies.

Investigating cholesterol metabolism and ageing using a systems biology approach

CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

Obesity and the dysregulation of fatty acid metabolism: implications for healthy aging

The population of the world is aging. In 2010, an estimated 524 million people were aged 65 years or older representing eight percent of the global population. By 2050, this number is expected to nearly triple to approximately 1.5 billion, 16 percent of the world's population. Although people are living longer, the quality of their lives are often compromised due to ill-health. Areas covered: Of the conditions which compromise health as we age, obesity is at the forefront. Over half of the global older population were overweight or obese in 2010, significantly increasing the risk of a range of metabolic diseases. Although, it is well recognised excessive calorie intake is a fundamental driver of adipose tissue dysfunction, the relationship between obesity; intrinsic aging; and fat metabolism is less understood. In this review we discuss the intersection between obesity, aging and the factors which contribute to the dysregulation of whole-body fat metabolism. Expert commentary: Being obese disrupts an array of physiological systems and there is significant crosstalk among these. Moreover it is imperative to acknowledge the contribution intrinsic aging makes to the dysregulation of these systems and the onset of disease.

Cholesterol metabolism: A review of how ageing disrupts the biological mechanisms responsible for its regulation

Cholesterol plays a vital role in the human body as a precursor of steroid hormones and bile acids, in addition to providing structure to cell membranes. Whole body cholesterol metabolism is maintained by a highly coordinated balancing act between cholesterol ingestion, synthesis, absorption, and excretion. The aim of this review is to discuss how ageing interacts with these processes. Firstly, we will present an overview of cholesterol metabolism. Following this, we discuss how the biological mechanisms which underpin cholesterol metabolism are effected by ageing. Included in this discussion are lipoprotein dynamics, cholesterol absorption/synthesis and the enterohepatic circulation/synthesis of bile acids. Moreover, we discuss the role of oxidative stress in the pathological progression of atherosclerosis and also discuss how cholesterol biosynthesis is effected by both the mammalian target of rapamycin and sirtuin pathways. Next, we examine how diet and alterations to the gut microbiome can be used to mitigate the impact ageing has on cholesterol metabolism. We conclude by discussing how mathematical models of cholesterol metabolism can be used to identify therapeutic interventions.

Aging and computational systems biology

Aging research is undergoing a paradigm shift, which has led to new and innovative methods of exploring this complex phenomenon. The systems biology approach endeavors to understand biological systems in a holistic manner, by taking account of intrinsic interactions, while also attempting to account for the impact of external inputs, such as diet. A key technique employed in systems biology is computational modeling, which involves mathematically describing and simulating the dynamics of biological systems. Although a large number of computational models have been developed in recent years, these models have focused on various discrete components of the aging process, and to date no model has succeeded in completely representing the full scope of aging. Combining existing models or developing new models may help to address this need and in so doing could help achieve an improved understanding of the intrinsic mechanisms which underpin aging.

Integration of 'omics' data in aging research: from biomarkers to systems biology

Age is the strongest risk factor for many diseases including neurodegenerative disorders, coronary heart disease, type 2 diabetes and cancer. Due to increasing life expectancy and low birth rates, the incidence of age-related diseases is increasing in industrialized countries. Therefore, understanding the relationship between diseases and aging and facilitating healthy aging are major goals in medical research. In the last decades, the dimension of biological data has drastically increased with high-throughput technologies now measuring thousands of (epi) genetic, expression and metabolic variables. The most common and so far successful approach to the analysis of these data is the so-called reductionist approach. It consists of separately testing each variable for association with the phenotype of interest such as age or age-related disease. However, a large portion of the observed phenotypic variance remains unexplained and a comprehensive understanding of most complex phenotypes is lacking. Systems biology aims to integrate data from different experiments to gain an understanding of the system as a whole rather than focusing on individual factors. It thus allows deeper insights into the mechanisms of complex traits, which are caused by the joint influence of several, interacting changes in the biological system. In this review, we look at the current progress of applying omics technologies to identify biomarkers of aging. We then survey existing systems biology approaches that allow for an integration of different types of data and highlight the need for further developments in this area to improve epidemiologic investigations.

Modeling the hypothalamus-pituitary-adrenal axis: A review and extension

Multiple models of the hypothalamus-pituitary-adrenal (HPA) axis have been developed to characterize the oscillations seen in the hormone concentrations and to examine HPA axis dysfunction. We reviewed the existing models, then replicated and compared five of them by finding their correspondence to a dataset consisting of ACTH and cortisol concentrations of 17 healthy individuals. We found that existing models use different feedback mechanisms, vary in the level of details and complexities, and offer inconsistent conclusions. None of the models fit the validation dataset well. Therefore, we re-calibrated the best performing model using partial calibration and extended the model by adding individual fixed effects and an exogenous circadian function. Our estimated parameters reduced the mean absolute percent error significantly and offer a validated reference model that can be used in diverse applications. Our analysis suggests that the circadian and ultradian cycles are not created endogenously by the HPA axis feedbacks, which is consistent with the recent literature on the circadian clock and HPA axis.

Mathematical modelling of metabolic regulation in aging

The underlying cellular mechanisms that characterize aging are complex and multifaceted. However, it is emerging that aging could be regulated by two distinct metabolic hubs. These hubs are the pathway defined by the mammalian target of rapamycin (mTOR) and that defined by the NAD+-dependent deacetylase enzyme, SIRT1. Recent experimental evidence suggests that there is crosstalk between these two important pathways; however, the mechanisms underpinning their interaction(s) remains poorly understood. In this review, we propose using computational modelling in tandem with experimentation to delineate the mechanism(s). We briefly discuss the main modelling frameworks that could be used to disentangle this relationship and present a reduced reaction pathway that could be modelled. We conclude by outlining the limitations of computational modelling and by discussing opportunities for future progress in this area.

Poor head growth as a presenting sign of a cortisol-secreting adrenal adenoma in a 2-year-old boy

Typical signs of glucocorticoid excess in children are weight gain and poor linear growth. We describe a 2-year-old boy with a cortisol-secreting adenoma who presented with a dramatic decline in head growth. This case underscores concern of adverse effects of excess glucocorticoid on brain growth in very young children.

Systems Biology and Synthetic Biology: A New Epoch for Toxicology Research

Systems biology and synthetic biology are emerging disciplines which are becoming increasingly utilised in several areas of bioscience. Toxicology is beginning to benefit from systems biology and we suggest in the future that is will also benefit from synthetic biology. Thus, a new era is on the horizon. This review illustrates how a suite of innovative techniques and tools can be applied to understanding complex health and toxicology issues. We review limitations confronted by the traditional computational approaches to toxicology and epidemiology research, using polycyclic aromatic hydrocarbons (PAHs) and their effects on adverse birth outcomes as an illustrative example. We introduce how systems toxicology (and their subdisciplines, genomic, proteomic, and metabolomic toxicology) will help to overcome such limitations. In particular, we discuss the advantages and disadvantages of mathematical frameworks that computationally represent biological systems. Finally, we discuss the nascent discipline of synthetic biology and highlight relevant toxicological centred applications of this technique, including improvements in personalised medicine. We conclude this review by presenting a number of opportunities and challenges that could shape the future of these rapidly evolving disciplines.

Isolation Housing Exacerbates Alzheimer's Disease-Like Pathophysiology in Aged APP/PS1 Mice

BACKGROUND

Alzheimer's disease is a neurodegenerative disease characterized by gradual declines in social, cognitive, and emotional functions, leading to a loss of expected social behavior. Social isolation has been shown to have adverse effects on individual development and growth as well as health and aging. Previous experiments have shown that social isolation causes an early onset of Alzheimer's disease-like phenotypes in young APP695/PS1-dE9 transgenic mice. However, the interactions between social isolation and Alzheimer's disease still remain unknown.

METHODS

Seventeen-month-old male APP695/PS1-dE9 transgenic mice were either singly housed or continued group housing for 3 months. Then, Alzheimer's disease-like pathophysiological changes were evaluated by using behavioral, biochemical, and pathological analyses.

RESULTS

Isolation housing further promoted cognitive dysfunction and Aβ plaque accumulation in the hippocampus of aged APP695/PS1-dE9 transgenic mice, associated with increased γ-secretase and decreased neprilysin expression. Furthermore, exacerbated hippocampal atrophy, synapse and myelin associated protein loss, and glial neuroinflammatory reactions were observed in the hippocampus of isolated aged APP695/PS1-dE9 transgenic mice.

CONCLUSIONS

The results demonstrate that social isolation exacerbates Alzheimer's disease-like pathophysiology in aged APP695/PS1-dE9 transgenic mice, highlighting the potential role of group life for delaying or counteracting the Alzheimer's disease process.

Computationally Modeling Lipid Metabolism and Aging: A Mini-review

One of the greatest challenges in biology is to improve the understanding of the mechanisms which underpin aging and how these affect health. The need to better understand aging is amplified by demographic changes, which have caused a gradual increase in the global population of older people. Aging western populations have resulted in a rise in the prevalence of age-related pathologies. Of these diseases, cardiovascular disease is the most common underlying condition in older people. The dysregulation of lipid metabolism due to aging impinges significantly on cardiovascular health. However, the multifaceted nature of lipid metabolism and the complexities of its interaction with aging make it challenging to understand by conventional means. To address this challenge computational modeling, a key component of the systems biology paradigm is being used to study the dynamics of lipid metabolism. This mini-review briefly outlines the key regulators of lipid metabolism, their dysregulation, and how computational modeling is being used to gain an increased insight into this system.

Post-traumatic stress disorder: revisiting adrenergics, glucocorticoids, immune system effects and homeostasis

This review focuses on post-traumatic stress disorder (PTSD). Several sequelae of PTSD are partially attributed to glucocorticoid-induced neuronal loss in the hippocampus and amygdala. Glucocorticoids and adrenergic agents cause both immediate and late sequelae and are considered from the perspective of their actions on the expression of cytokines as well as some of their physiological and psychological effects. A shift in immune system balance from Th1 to Th2 dominance is thought to result from the actions of both molecular groups. The secretion of glucocorticoids and adrenergic agents is commonly induced by trauma or stress, and synergy between these two parallel but separate pathways can produce long- and short-term sequelae in individuals with PTSD. Potential therapies are suggested, and older therapies that involve the early effects of adrenergics or glucocorticoids are reviewed for their control of acute symptoms. These therapies may also be useful for acute flashback therapy. Timely and more precise glucocorticoid and adrenergic control is recommended for maintaining these molecular groups within acceptable homeostatic limits and thus managing immune and brain sequelae. Psychotherapy should supplement the above therapeutic measures; however, psychotherapy is not the focus of this paper. Instead, this review focuses on the probable molecular basis of PTSD. Integrating historical findings regarding glucocorticoids and adrenergic agents into current research and clinical applications returns the focus to potentially life-changing treatments. Autologous adoptive immune therapy may also offer utility. This paper reports clinical and translational research that connects and challenges separate fields of study, current and classical, in an attempt to better understand and ameliorate the effects of PTSD.

Lipid metabolism and hormonal interactions: impact on cardiovascular disease and healthy aging

Populations in developed nations are aging gradually; it is predicted that by 2050 almost a quarter of the world's population will be over 60 years old, more than twice the figure at the turn of the 20th century. Although we are living longer, this does not mean the extra years will be spent in good health. Cardiovascular diseases are the primary cause of ill health and their prevalence increases with age. Traditionally, lipid biomarkers have been utilized to stratify disease risk and predict the onset of cardiovascular events. However, recent evidence suggests that hormonal interplay with lipid metabolism could have a significant role to play in modulating cardiovascular disease risk. This review will explore recent findings which have investigated the role hormones have on the dynamics of lipid metabolism. The aim is to offer an insight into potential avenues for therapeutic intervention.

The impact of stress and glucocorticoids on memory

Responses to stress are mediated by a complex network of the nervous and endocrine systems. Glucocorticoids, which are among the most important “players” in stress resilience, may have important implications in the cognitive functions, particularly in the modulation of memory. Declarative memory, the memory for facts, events and word meaning is the most studied type of memory on which glucocorticoids exert an influence, both positively through consolidation and negatively through impairment. These effects depend on the receptor type, dose, time of exposure, memory component and the salience of stimuli, retrieval being generally affected and storage being facilitated, especially for emotionally relevant events. Glucocorticoids also induce hippocampal atrophy, which is a hallmark seen in various diseases accompanied by a chronic high level of cortisol, such as the Cushing syndrome, major depression, post-traumatic stress disorder. Also, chronic stress might be a risk factor for the development of Alzheimer’s disease, especially when a genetic background and other environmental influences are present.

Blood-based protein biomarkers for diagnosis of Alzheimer disease

OBJECTIVE

To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD).

DESIGN

Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data.

SETTING

General community-based, prospective, longitudinal study of aging.

PARTICIPANTS

A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort.

RESULTS

A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve.

CONCLUSIONS

This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.

Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer's disease: a stochastic modelling approach

Background

Alzheimer’s disease (AD) is the most frequently diagnosed neurodegenerative disorder affecting humans, with advanced age being the most prominent risk factor for developing AD. Despite intense research efforts aimed at elucidating the precise molecular underpinnings of AD, a definitive answer is still lacking. In recent years, consensus has grown that dimerisation of the polypeptide amyloid-beta (Aß), particularly Aß₄₂, plays a crucial role in the neuropathology that characterise AD-affected post-mortem brains, including the large-scale accumulation of fibrils, also referred to as senile plaques. This has led to the realistic hope that targeting Aß₄₂ immunotherapeutically could drastically reduce plaque burden in the ageing brain, thus delaying AD onset or symptom progression. Stochastic modelling is a useful tool for increasing understanding of the processes underlying complex systems-affecting disorders such as AD, providing a rapid and inexpensive strategy for testing putative new therapies. In light of the tool’s utility, we developed computer simulation models to examine Aß₄₂ turnover and its aggregation in detail and to test the effect of immunization against Aß dimers.

Results

Our model demonstrates for the first time that even a slight decrease in the clearance rate of Aß₄₂ monomers is sufficient to increase the chance of dimers forming, which could act as instigators of protofibril and fibril formation, resulting in increased plaque levels. As the process is slow and levels of Aβ are normally low, stochastic effects are important. Our model predicts that reducing the rate of dimerisation leads to a significant reduction in plaque levels and delays onset of plaque formation. The model was used to test the effect of an antibody mediated immunological response. Our results showed that plaque levels were reduced compared to conditions where antibodies are not present.

Conclusion

Our model supports the current thinking that levels of dimers are important in initiating the aggregation process. Although substantial knowledge exists regarding the process, no therapeutic intervention is on offer that reliably decreases disease burden in AD patients. Computer modelling could serve as one of a number of tools to examine both the validity of reliable biomarkers and aid the discovery of successful intervention strategies.

Computational biology for ageing

High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions.