A Systems Biology Roadmap to Decode mTOR Control System in Cancer

Cornerstone Cellular Pathways for Metabolic Disorders and Diabetes Mellitus: Non-Coding RNAs, Wnt Signaling, and AMPK

Metabolic disorders and diabetes (DM) impact more than five hundred million individuals throughout the world and are insidious in onset, chronic in nature, and yield significant disability and death. Current therapies that address nutritional status, weight management, and pharmacological options may delay disability but cannot alter disease course or functional organ loss, such as dementia and degeneration of systemic bodily functions. Underlying these challenges are the onset of aging disorders associated with increased lifespan, telomere dysfunction, and oxidative stress generation that lead to multi-system dysfunction. These significant hurdles point to the urgent need to address underlying disease mechanisms with innovative applications. New treatment strategies involve non-coding RNA pathways with microRNAs (miRNAs) and circular ribonucleic acids (circRNAs), Wnt signaling, and Wnt1 inducible signaling pathway protein 1 (WISP1) that are dependent upon programmed cell death pathways, cellular metabolic pathways with AMP-activated protein kinase (AMPK) and nicotinamide, and growth factor applications. Non-coding RNAs, Wnt signaling, and AMPK are cornerstone mechanisms for overseeing complex metabolic pathways that offer innovative treatment avenues for metabolic disease and DM but will necessitate continued appreciation of the ability of each of these cellular mechanisms to independently and in unison influence clinical outcome.

The impact of aging and oxidative stress in metabolic and nervous system disorders: programmed cell death and molecular signal transduction crosstalk

Life expectancy is increasing throughout the world and coincides with a rise in non-communicable diseases (NCDs), especially for metabolic disease that includes diabetes mellitus (DM) and neurodegenerative disorders. The debilitating effects of metabolic disorders influence the entire body and significantly affect the nervous system impacting greater than one billion people with disability in the peripheral nervous system as well as with cognitive loss, now the seventh leading cause of death worldwide. Metabolic disorders, such as DM, and neurologic disease remain a significant challenge for the treatment and care of individuals since present therapies may limit symptoms but do not halt overall disease progression. These clinical challenges to address the interplay between metabolic and neurodegenerative disorders warrant innovative strategies that can focus upon the underlying mechanisms of aging-related disorders, oxidative stress, cell senescence, and cell death. Programmed cell death pathways that involve autophagy, apoptosis, ferroptosis, and pyroptosis can play a critical role in metabolic and neurodegenerative disorders and oversee processes that include insulin resistance, β-cell function, mitochondrial integrity, reactive oxygen species release, and inflammatory cell activation. The silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae) (SIRT1), AMP activated protein kinase (AMPK), and Wnt1 inducible signaling pathway protein 1 (WISP1) are novel targets that can oversee programmed cell death pathways tied to β-nicotinamide adenine dinucleotide (NAD+), nicotinamide, apolipoprotein E (APOE), severe acute respiratory syndrome (SARS-CoV-2) exposure with coronavirus disease 2019 (COVID-19), and trophic factors, such as erythropoietin (EPO). The pathways of programmed cell death, SIRT1, AMPK, and WISP1 offer exciting prospects for maintaining metabolic homeostasis and nervous system function that can be compromised during aging-related disorders and lead to cognitive impairment, but these pathways have dual roles in determining the ultimate fate of cells and organ systems that warrant thoughtful insight into complex autofeedback mechanisms.

A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

BACKGROUND

Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis.

METHODS

Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes.

RESULTS

Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages.

CONCLUSIONS

These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation.

Cognitive Impairment in Multiple Sclerosis

Almost three million individuals suffer from multiple sclerosis (MS) throughout the world, a demyelinating disease in the nervous system with increased prevalence over the last five decades, and is now being recognized as one significant etiology of cognitive loss and dementia. Presently, disease modifying therapies can limit the rate of relapse and potentially reduce brain volume loss in patients with MS, but unfortunately cannot prevent disease progression or the onset of cognitive disability. Innovative strategies are therefore required to address areas of inflammation, immune cell activation, and cell survival that involve novel pathways of programmed cell death, mammalian forkhead transcription factors (FoxOs), the mechanistic target of rapamycin (mTOR), AMP activated protein kinase (AMPK), the silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae) (SIRT1), and associated pathways with the apolipoprotein E (APOE-ε4) gene and severe acute respiratory syndrome coronavirus (SARS-CoV-2). These pathways are intertwined at multiple levels and can involve metabolic oversight with cellular metabolism dependent upon nicotinamide adenine dinucleotide (NAD+). Insight into the mechanisms of these pathways can provide new avenues of discovery for the therapeutic treatment of dementia and loss in cognition that occurs during MS.

Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients' characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O₂ Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

From classical mendelian randomization to causal networks for systematic integration of multi-omics

The number of studies with information at multiple biological levels of granularity, such as genomics, proteomics, and metabolomics, is increasing each year, and a biomedical questaion is how to systematically integrate these data to discover new biological mechanisms that have the potential to elucidate the processes of health and disease. Causal frameworks, such as Mendelian randomization (MR), provide a foundation to begin integrating data for new biological discoveries. Despite the growing number of MR applications in a wide variety of biomedical studies, there are few approaches for the systematic analysis of omic data. The large number and diverse types of molecular components involved in complex diseases interact through complex networks, and classical MR approaches targeting individual components do not consider the underlying relationships. In contrast, causal network models established in the principles of MR offer significant improvements to the classical MR framework for understanding omic data. Integration of these mostly distinct branches of statistics is a recent development, and we here review the current progress. To set the stage for causal network models, we review some recent progress in the classical MR framework. We then explain how to transition from the classical MR framework to causal networks. We discuss the identification of causal networks and evaluate the underlying assumptions. We also introduce some tests for sensitivity analysis and stability assessment of causal networks. We then review practical details to perform real data analysis and identify causal networks and highlight some of the utility of causal networks. The utilities with validated novel findings reveal the full potential of causal networks as a systems approach that will become necessary to integrate large-scale omic data.

Cognitive Impairment and Dementia: Gaining Insight through Circadian Clock Gene Pathways

Neurodegenerative disorders affect fifteen percent of the world's population and pose a significant financial burden to all nations. Cognitive impairment is the seventh leading cause of death throughout the globe. Given the enormous challenges to treat cognitive disorders, such as Alzheimer's disease, and the inability to markedly limit disease progression, circadian clock gene pathways offer an exciting strategy to address cognitive loss. Alterations in circadian clock genes can result in age-related motor deficits, affect treatment regimens with neurodegenerative disorders, and lead to the onset and progression of dementia. Interestingly, circadian pathways hold an intricate relationship with autophagy, the mechanistic target of rapamycin (mTOR), the silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae) (SIRT1), mammalian forkhead transcription factors (FoxOs), and the trophic factor erythropoietin. Autophagy induction is necessary to maintain circadian rhythm homeostasis and limit cortical neurodegenerative disease, but requires a fine balance in biological activity to foster proper circadian clock gene regulation that is intimately dependent upon mTOR, SIRT1, FoxOs, and growth factor expression. Circadian rhythm mechanisms offer innovative prospects for the development of new avenues to comprehend the underlying mechanisms of cognitive loss and forge ahead with new therapeutics for dementia that can offer effective clinical treatments.

Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O 2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

Potential Repositioning of Anti-cancer EGFR Inhibitors in Alzheimer's Disease: Current Perspectives and Challenging Prospects

Clinical trials of new drugs for Alzheimer's disease (AD) have ended with disappointing results, with tremendous resources and time. Repositioning of existing anti-cancer epidermal growth factor receptors (EGFR) inhibitors in various preclinical AD models has gained growing attention in recent years because hyperactivation of EGFR has been implicated in many neurodegenerative disorders, including AD. Many recent studies have established that EGFR inhibition suppresses reactive astrocytes, enhances autophagy, ameliorates Aβ toxicity, neuroinflammation, and regenerates axonal degradation. However, there is no incontrovertible neuroprotective proof using EGFR inhibitors due to many under-explored signaling transductions, poor blood-brain barrier (BBB) permeability of the most tested drugs, and disappointing outcomes of most clinical trials. This has caused debate about the possible involvement of EGFR inhibitors in future clinical trials. In this perspective article, we recap recent studies to merge data on the neuroprotective effects of EGFR inhibition. By consequent analysis of previous data, we notably find the under-investigated neuroprotective pathways that highlight the importance of additional research of EGFR inhibitors in attempts to be repurposed as burgeoning therapeutic strategies for AD. Finally, we will discuss future prospective challenges in the repositioning of EGFR inhibitors in AD.

Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson's disease

Speech diagnosis of Parkinson’s disease (PD) as a non-invasive and simple diagnosis method is particularly worth exploring. However, the number of samples of speech-based PD is relatively small, and there exist discrepancies in the distribution between subjects. In order to solve the two problems, a novel unsupervised two-step sparse transfer learning is proposed in this paper to tackle with PD speech diagnosis. In the first step, convolution sparse coding with the coordinate selection of samples and features is designed to learn speech structure from the source domain to replenish sample information of the target domain. In the second step, joint local structure distribution alignment is designed to maintain the neighbor relationship between the respective samples of the training set and test set, and reduce the distribution difference between the two domains at the same time. Two representative public PD speech datasets and one real-world PD speech dataset were exploited to verify the proposed method on PD speech diagnosis. Experimental results demonstrate that each step of the proposed method has a positive effect on the PD speech classification results, and it also delivers superior performance over the existing relative methods.

Nicotinamide as a Foundation for Treating Neurodegenerative Disease and Metabolic Disorders

Neurodegenerative disorders impact more than one billion individuals worldwide and are intimately tied to metabolic disease that can affect another nine hundred individuals throughout the globe. Nicotinamide is a critical agent that may offer fruitful prospects for neurodegenerative diseases and metabolic disorders, such as diabetes mellitus. Nicotinamide protects against multiple toxic environments that include reactive oxygen species exposure, anoxia, excitotoxicity, ethanolinduced neuronal injury, amyloid (Aß) toxicity, age-related vascular disease, mitochondrial dysfunction, insulin resistance, excess lactate production, and loss of glucose homeostasis with pancreatic β-cell dysfunction. However, nicotinamide offers cellular protection in a specific concentration range, with dosing outside of this range leading to detrimental effects. The underlying biological pathways of nicotinamide that involve the silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae) (SIRT1), the mechanistic target of rapamycin (mTOR), AMP activated protein kinase (AMPK), and mammalian forkhead transcription factors (FoxOs) may offer insight for the clinical translation of nicotinamide into a safe and efficacious therapy through the modulation of oxidative stress, apoptosis, and autophagy. Nicotinamide is a highly promising target for the development of innovative strategies for neurodegenerative disorders and metabolic disease, but the benefits of this foundation depend greatly on gaining a further understanding of nicotinamide's complex biology.

Dihydroartemisinin inhibits activation of the AIM2 inflammasome pathway and NF-κB/HIF-1α/VEGF pathway by inducing autophagy in A431 human cutaneous squamous cell carcinoma cells

The therapeutic effect of dihydroartemisinin (DHA) against cutaneous squamous cell carcinoma (cSCC) has been previously demonstrated; however, the underlying mechanism remains unclear. This study sought to verify the therapeutic effect of DHA against cSCC and explore its underlying mechanism in A431 cSCC cells. This study reported that DHA inhibited A431 cells proliferation in a time- and concentration-dependent manner and promoted A431 cells apoptosis. Moreover, DHA inhibited the invasion and migration of A431 cells. Mechanistically, DHA promoted autophagy and inhibited activation of the absent in melanoma 2 (AIM2) inflammasome pathway and NF-κB/HIF-1α/VEGF pathway. Treatment of A431 cells with the mTOR inhibitor, and autophagy promoter, rapamycin also inhibited these two pathways. In conclusion, DHA inhibited activation of the AIM2 inflammasome pathway and NF-κB/HIF-1α/VEGF pathway by promoting autophagy in A431 cells, thus accounting for its therapeutic effect. Induction of autophagy by DHA may be mediated by inhibiting the mTOR pathway and promoting reactive oxygen species production.

Targeting the core of neurodegeneration: FoxO, mTOR, and SIRT1

The global increase in lifespan noted not only in developed nations, but also in large developing countries parallels an observed increase in a significant number of non-communicable diseases, most notable neurodegenerative disorders. Neurodegenerative disorders present a number of challenges for treatment options that do not resolve disease progression. Furthermore, it is believed by the year 2030, the services required to treat cognitive disorders in the United States alone will exceed $2 trillion annually. Mammalian forkhead transcription factors, silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae), the mechanistic target of rapamycin, and the pathways of autophagy and apoptosis offer exciting avenues to address these challenges by focusing upon core cellular mechanisms that may significantly impact nervous system disease. These pathways are intimately linked such as through cell signaling pathways involving protein kinase B and can foster, sometimes in conjunction with trophic factors, enhanced neuronal survival, reduction in toxic intracellular accumulations, and mitochondrial stability. Feedback mechanisms among these pathways also exist that can oversee reparative processes in the nervous system. However, mammalian forkhead transcription factors, silent mating type information regulation 2 homolog 1, mechanistic target of rapamycin, and autophagy can lead to cellular demise under some scenarios that may be dependent upon the precise cellular environment, warranting future studies to effectively translate these core pathways into successful clinical treatment strategies for neurodegenerative disorders.

Dysregulation of metabolic flexibility: The impact of mTOR on autophagy in neurodegenerative disease

Non-communicable diseases (NCDs) that involve neurodegenerative disorders and metabolic disease impact over 400 million individuals globally. Interestingly, metabolic disorders, such as diabetes mellitus, are significant risk factors for the development of neurodegenerative diseases. Given that current therapies for these NCDs address symptomatic care, new avenues of discovery are required to offer treatments that affect disease progression. Innovative strategies that fill this void involve the mechanistic target of rapamycin (mTOR) and its associated pathways of mTOR complex 1 (mTORC1), mTOR complex 2 (mTORC2), AMP activated protein kinase (AMPK), trophic factors that include erythropoietin (EPO), and the programmed cell death pathways of autophagy and apoptosis. These pathways are intriguing in their potential to provide effective care for metabolic and neurodegenerative disorders. Yet, future work is necessary to fully comprehend the entire breadth of the mTOR pathways that can effectively and safely translate treatments to clinical medicine without the development of unexpected clinical disabilities.

New Insights for nicotinamide: Metabolic disease, autophagy, and mTOR

Metabolic disorders, such as diabetes mellitus (DM), are increasingly becoming significant risk factors for the health of the global population and consume substantial portions of the gross domestic product of all nations. Although conventional therapies that include early diagnosis, nutritional modification of diet, and pharmacological treatments may limit disease progression, tight serum glucose control cannot prevent the onset of future disease complications. With these concerns, novel strategies for the treatment of metabolic disorders that involve the vitamin nicotinamide, the mechanistic target of rapamycin (mTOR), mTOR Complex 1 (mTORC1), mTOR Complex 2 (mTORC2), AMP activated protein kinase (AMPK), and the cellular pathways of autophagy and apoptosis offer exceptional promise to provide new avenues of treatment. Oversight of these pathways can promote cellular energy homeostasis, maintain mitochondrial function, improve glucose utilization, and preserve pancreatic beta-cell function. Yet, the interplay among mTOR, AMPK, and autophagy pathways can be complex and affect desired clinical outcomes, necessitating further investigations to provide efficacious treatment strategies for metabolic dysfunction and DM.

Fate decisions mediated by crosstalk of autophagy and apoptosis in mammalian cells

Autophagy is an important cell activity which is the process of formation of autophagosomes, docking with lysosomes and degradation. The intrinsic pathway of apoptosis involves mitochondrial outer membrane permeabilization (MOMP) and cytochrome c release followed by caspase activation. Many molecules, e.g., Ca²⁺ and mTOR, and different stresses such as endoplasmic reticulum (ER) stress and nutritional stress take part in these two processes. However, the mechanism of how they work together so as to determine cell fate decisions remains to be clarified. Here, we present a computational model for cell fate decisions based on intertwined dynamics with autophagy and apoptosis involving Ca²⁺, mTOR, and both ER stress and nutritional stress. In agreement with experimental observations, the model predicts that both Ca²⁺ and the stresses play critical roles in regulating the choice between autophagy and apoptosis in a combinatorial way. The model presented here might be a good candidate for providing the qualitative mechanism of cell fate decisions mediated by Ca²⁺, mTOR, and two kinds of stress.

Computational modeling of the effects of autophagy on amyloid-β peptide levels

BACKGROUND

Autophagy is an evolutionarily conserved intracellular process that is used for delivering proteins and organelles to the lysosome for degradation. For decades, autophagy has been speculated to regulate amyloid-β peptide (Aβ) accumulation, which is involved in Alzheimer's disease (AD); however, specific autophagic effects on the Aβ kinetics only have begun to be explored.

RESULTS

We develop a mathematical model for autophagy with respect to Aβ kinetics and perform simulations to understand the quantitative relationship between Aβ levels and autophagy activity. In the case of an abnormal increase in the Aβ generation, the degradation, secretion, and clearance rates of Aβ are significantly changed, leading to increased levels of Aβ. When the autophagic Aβ degradation is defective in addition to the increased Aβ generation, the Aβ-regulation failure is accompanied by elevated concentrations of autophagosome and autolysosome, which may further clog neurons.

CONCLUSIONS

The model predicts that modulations of different steps of the autophagy pathway (i.e., Aβ sequestration, autophagosome maturation, and intralysosomal hydrolysis) have significant step-specific and combined effects on the Aβ levels and thus suggests therapeutic and preventive implications of autophagy in AD.

AICAR and nicotinamide treatment synergistically augment the proliferation and attenuate senescence-associated changes in mesenchymal stromal cells

Background

Mesenchymal stromal cell (MSC) stemness capacity diminishes over prolonged in vitro culture, which negatively affects their application in regenerative medicine. To slow down the senescence of MSCs, here, we have evaluated the in vitro effects of 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR), an AMPK activator, and nicotinamide (NAM), an activator of sirtuin1 (SIRT1).

Methods

Human adipose-derived MSCs were cultured to passage (P) 5. Subsequently, the cells were grown in either normal medium alone (control group), the medium supplemented with AICAR (1 mM) and NAM (5 mM), or in the presence of both for 5 weeks to P10. Cell proliferation, differentiation capacity, level of apoptosis and autophagy, morphological changes, total cellular reactive oxygen species (ROS), and activity of mTORC1 and AMPK were compared among different treatment groups.

Results

MSCs treated with AICAR, NAM, or both displayed an increase in proliferation and osteogenic differentiation, which was augmented in the group receiving both. Treatment with AICAR or NAM led to decreased expression of β-galactosidase, reduced accumulation of dysfunctional lysosomes, and characteristic morphologic features of young MSCs. Furthermore, while NAM administration could significantly reduce the total cellular ROS in aged MSCs, AICAR treatment did not. Moreover, AICAR-treated cells possess a high proliferation capacity; however, they also show the highest level of cellular apoptosis. The observed effects of AICAR and NAM were in light of the attenuated mTORC1 activity and increased AMPK activity and autophagy.

Conclusions

Selective inhibition of mTORC1 by AICAR and NAM boosts autophagy, retains MSCs’ self-renewal and multi-lineage differentiation capacity, and postpones senescence-associated changes after prolonged in vitro culture. Additionally, co-administration of AICAR and NAM shows an additive or probably a synergistic effect on cellular senescence.

The Mechanistic Target of Rapamycin (mTOR): Novel Considerations as an Antiviral Treatment

Multiple viral pathogens can pose a significant health risk to individuals. As a recent example, the β-coronavirus family virion, SARS-CoV-2, has quickly evolved as a pandemic leading to coronavirus disease 2019 (COVID-19) and has been declared by the World Health Organization as a Public Health Emergency of International Concern. To date, no definitive treatment or vaccine application exists for COVID-19. Although new investigations seek to repurpose existing antiviral treatments for COVID-19, innovative treatment strategies not normally considered to have antiviral capabilities may be critical to address this global concern. One such avenue that may prove to be exceedingly fruitful and offer exciting potential as new antiviral therapy involves the mechanistic target of rapamycin (mTOR) and its associated pathways of mTOR Complex 1 (mTORC1), mTOR Complex 2 (mTORC2), and AMP activated protein kinase (AMPK). Recent work has shown that mTOR pathways in conjunction with AMPK may offer valuable targets to control cell injury, oxidative stress, mitochondrial dysfunction, and the onset of hyperinflammation, a significant disability associated with COVID-19. Furthermore, pathways that can activate mTOR may be necessary for anti-hepatitis C activity, reduction of influenza A virus replication, and vital for type-1 interferon responses with influenza vaccination. Yet, important considerations for the development of safe and effective antiviral therapy with mTOR pathways exist. Under some conditions, mTOR can act as a double edge sword and participate in virion replication and virion release from cells. Future work with mTOR as a potential antiviral target is highly warranted and with a greater understanding of this novel pathway, new treatments against several viral pathogens may successfully emerge.

Nicotinamide: Oversight of Metabolic Dysfunction Through SIRT1, mTOR, and Clock Genes

Metabolic disorders that include diabetes mellitus present significant challenges for maintaining the welfare of the global population. Metabolic diseases impact all systems of the body and despite current therapies that offer some protection through tight serum glucose control, ultimately such treatments cannot block the progression of disability and death realized with metabolic disorders. As a result, novel therapeutic avenues are critical for further development to address these concerns. An innovative strategy involves the vitamin nicotinamide and the pathways associated with the silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae) (SIRT1), the mechanistic target of rapamycin (mTOR), mTOR Complex 1 (mTORC1), mTOR Complex 2 (mTORC2), AMP activated protein kinase (AMPK), and clock genes. Nicotinamide maintains an intimate relationship with these pathways to oversee metabolic disease and improve glucose utilization, limit mitochondrial dysfunction, block oxidative stress, potentially function as antiviral therapy, and foster cellular survival through mechanisms involving autophagy. However, the pathways of nicotinamide, SIRT1, mTOR, AMPK, and clock genes are complex and involve feedback pathways as well as trophic factors such as erythropoietin that require a careful balance to ensure metabolic homeostasis. Future work is warranted to gain additional insight into these vital pathways that can oversee both normal metabolic physiology and metabolic disease.