Dysregulation of Metabolic Flexibility: The Impact of mTOR on Autophagy in Neurodegenerative Disease

Abstract

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.

Non-communicable Diseases and Neurodegenerative Disease

With the increasing prevalence of non-communicable diseases (NCDs), it is now estimated that almost seventy percent of the annual deaths that occur each year are the result of NCDs (World Health Organization, 2011, 2017). As a result, over 40 million people die from NCDs each year. Of these individuals, 15 million are between 30 and 69 years old, illustrating that even younger individuals can be impacted by NCDs. For NCDs, greater than 10 percent of the population under 60 years of age is affected in high-income countries (World Health Organization, 2011). In contrast, NCDs affect a much larger proportion of the population in in low and middle-income countries with at least one-third of the population under the age of 60 suffering from NCDs. Interestingly, the rise in NCDs parallels an observed increase in life expectancy of the world’s population (Maiese, 2018d). The age of the global population continues to increase with life expectancy approaching 80 years of age (Maiese, 2014a). In addition, the number of individuals over the age of 65 has doubled during the previous 50 years (Hayutin, 2007). Life expectancy also has been marked by a 1 percent decrease in the age-adjusted death rate from the years 2000 through 2011 (Minino, 2013). It is expected that the number of elderly individuals in large developing countries such as India and China also will increase from five to ten percent over the next several decades (Maiese, 2015f, 2015g). There are a number of reasons that may account for the increased lifespan, but improvements in effective treatments for multiple disorders (Diamanti-Kandarakis et al., 2017; Fann, Ng, Poh, & Arumugam, 2017; Lushchak et al., 2017; Maiese, 2017d; Stefanatos & Sanz, 2018) and broader access to preventive care are believed to have contributed to the increased life span of the world’s population. .

Neurodegenerative disorders form a significant component for NCDs and include more than 600 disease entities that can progressively lead to nervous system dysfunction (Z. Z. Chong, Y. C. Shang, S. Wang, & K. Maiese, 2012; Maiese, 2014b). Both acute and chronic neurodegenerative disorders lead to disability and death for a significant number of individuals worldwide that can approach greater than 30 million individuals worldwide (Borjini et al., 2019; Handa et al., 2019; Maiese, 2019b, 2020).

As a result of improvements in global healthcare and the progressive increase in life span, neurodegenerative disorders are expected to increase in prevalence among the world’s population. For example, the incidence of sporadic cases of Alzheimer’s disease (AD) is expected to significantly increase throughout the globe (Maiese, 2019b; Su et al., 2019). Dementia is now considered to be the 7^th leading cause of death. According to the World Health Organization (World Health Organization, 2017), dementia affects all countries throughout the world at a significant financial burden. Cognitive disorders that include AD affect more than 5 million individuals in the United States (US) alone (Filley et al., 2007; Maiese, 2014c). At minimum, 60 percent of dementia cases result from AD (Chong, Li, & Maiese, 2005; Maiese, 2014c, 2015g; Maiese, Chong, Shang, & Wang, 2013a). At least 5 percent of the world’s elderly population suffer from dementia and this represents 50 million individuals. With new cases increasing at a rapid rate, it is estimated by the year 2030, 82 million people are expected to have dementia. If once considers the year 2050, 152 million individuals will suffer from dementia.

Consideration for the financial and service burdens for neurodegenerative disorders are equally staggering. Prior estimates for the cost of neurodegenerative disorders exceeded $700 billion United States dollars (USD) in the United States (US) alone and included dementias, stroke, back pain, epilepsy, trauma to the nervous system, and Parkinson’s disease. Currently, dementia care is considered the most significant cost factor with more than $800 billion USD spent to care for individuals with dementia on an annual basis. These costs approximate 2 percent of the global gross domestic product. By the year 2030, medical and social services could reach in the US to 2 trillion USD annually with the ability to easily overwhelm the system. These projections fail to include the significant financial costs that involve social and adult living care as well as informal and companion care for individual families. In addition, the World Health Organization estimates the need for close to 60 million new health and social care workers (World Health Organization, 2011, 2012, 2017). Other challenges for the care of individuals with neurodegenerative disorders also exist such as when to address the need for these healthcare workers in a timely and implementation of healthcare workers that will occur in efficient manner, since the onset and progression of dementia in individuals is not always well recognized. An additional consideration is that dementia is considered to be under diagnosed throughout the world (Maiese, 2019b, 2019c). Once diagnosis is correctly performed, it can be in the late or end stages of the disease, leaving little time or options for treatment and possibly leading to fragmented care.

Metabolic Disease and Neurodegenerative Disease

Diabetes mellitus (DM) is a significant metabolic disorder of the NCDs that has widespread implications for new treatment options for the global population (Esterline, Vaag, Oscarsson, & Vora, 2018; Klimontov et al., 2019; Maiese, 2016d, 2020). At present, an estimated 460 million individuals currently have DM (Haldar et al., 2015; Jia, Aroor, Martinez-Lemus, & Sowers, 2014; Maiese, 2015a; Maiese, 2015g; Ye & Fu, 2018). At least another 374 million individuals are believed to have metabolic disease and are at risk for developing DM but presently are undiagnosed (Harris & Eastman, 2000; International Diabetes Federation, 2019; Maiese, 2015e; Maiese, Chong, & Shang, 2007). The number of individuals with DM is expected to rise to 700 million individuals by 2045 according to the International Diabetes Federation (International Diabetes Federation, 2019). Obesity and impaired glucose tolerance are closely linked as factors that lead to the development of DM (Barchetta, Cimini, Ciccarelli, Baroni, & Cavallo, 2019; Maiese, 2015a; A. R. Wang et al., 2018). Impaired glucose tolerance and obesity increases the risk of developing DM in young individuals (Maiese, Chong, Shang, & Hou, 2011). Obesity and excess body fat can affect stem cell proliferation, aging, inflammation, oxidative stress injury, and mitochondrial function (Cernea, Tang, Guan, & Yang, 2016; Curjuric et al., 2016; Hill, Solt, & Foster, 2018; Z. Liu, Gan, Zhang, Ren, & Sun, 2018; Maiese, 2016e; Mehta, Rayalam, & Wang, 2018; A. R. Wang et al., 2018).

In regards to the financial considerations for the treatment and care of individuals with DM, almost 80 percent of adults with DM are living in low- and middle-income countries (International Diabetes Federation, 2019). More than $20,000 USD are required to care for each individual with DM per year. The care for patients with DM equals approximately $760 billion USD (International Diabetes Federation, 2019) and consumes more than 17 percent of the Gross Domestic Product in the US as reported by the Centers for Medicare and Medicaid Services (CMS) (Centers for Medicare and Medicaid Services, 2019). With the loss of function and disability that results from DM, an estimated $69 billion USD are consumed from reduced productivity linked to DM.

DM affects all systems of the body including the vascular system and the peripheral and central nervous systems. DM can lead to retinal disease (Maiese, 2015b; Mishra, Duraisamy, & Kowluru, 2018; Ponnalagu, Subramani, Jayadev, Shetty, & Das, 2017), endothelial dysfunction (Arildsen, Andersen, Waagepetersen, Nissen, & Sheykhzade, 2019; S. Ding et al., 2018; Maiese, 2015g, 2018d; Pal, Sonowal, Shukla, Srivastava, & Ramana, 2019), cardiovascular disease (Alexandru, Popov, & Georgescu, 2012; Barchetta et al., 2019; Chiu et al., 2017; S. Ding et al., 2018; Esterline et al., 2018; Maiese, 2016b; Maiese et al., 2007; Maiese, Chong, Shang, & Hou, 2008; Maiese, Li, Chong, & Shang, 2008; Perez-Hernandez et al., 2016; Thackeray et al., 2011), immune function disorders (Kell & Pretorius, 2018; X. Lin & Zhang, 2018; Maiese, 2015c; Maiese, Chong, Shang, & Wang, 2011; Woodhams & Al-Salami, 2017; Y. Zhao et al., 2015), inflammation (Maiese, 2015b; Mishra et al., 2018; Ponnalagu et al., 2017), and injury to the neurovascular unit (Maiese, 2015b; Mishra et al., 2018; Ponnalagu et al., 2017). In the peripheral nervous system, at least 70 percent of individuals with DM can develop some degree of diabetic peripheral neuropathy. DM can lead to both autonomic neuropathy (Albiero et al., 2014) and peripheral nerve disease (Gomes & Negrato, 2014; Gomez-Brouchet et al., 2015). Assessments of the progress of peripheral neuropathies can be challenging, since the disorder is chronic in nature, may be sub-clinical, and prior deficits may go undetected if improved control over glucose homeostasis is initiated. In the central nervous system, DM leads to insulin resistance and dementia that occurs in patients with AD (Caberlotto et al., 2019; Maiese, 2020; Su et al., 2019). DM can affect multiple cellular pathways that lead to the progression of cognitive loss (Maiese, 2015g; Maiese, Chong, Shang, & Hou, 2009; Tang, Ng, Ho, Gyda, & Chan, 2014; Xiang, Mittwede, & Clemmer, 2015; Y. J. Xu, Tappia, Neki, & Dhalla, 2014; Yao, Fujimura, Murayama, Okumura, & Seko, 2017). DM also has been linked to mental illness (Hadamitzky et al., 2018; Ignacio et al., 2016), cerebral vascular injury (Di Rosa & Malaguarnera, 2016; Maiese, 2015e, 2015g; Maiese, Chong, Hou, & Shang, 2008; Tulsulkar, Nada, Slotterbeck, McInerney, & Shah, 2015; F. H. Xiao et al., 2015), impairment of microglial activity (Caberlotto et al., 2019; Maiese, 2020; Su et al., 2019), and can impact stem cell proliferation (Maiese, 2015g; Maiese et al., 2009; Tang et al., 2014; Xiang et al., 2015; Y. J. Xu et al., 2014; Yao et al., 2017).

Innovative Approaches to Target Metabolic Disease and Neurodegenerative Disease

Metabolic disorders, such as DM, pose a significant challenge for the treatment of neurodegenerative disorders. Early diagnosis of DM and quickly focusing on therapeutic targets can offer some degree of protection. Rapid treatment may inhibit the progression of DM (Guo et al., 2019; Klimova & Kristian, 2019; Maiese, 2015a; Maiese, 2018d; Maiese, Chong, Shang, & Wang, 2013b; Othman et al., 2018; Yelumalai, Giribabu, Karim, Omar, & Salleh, 2019). However, tight serum glucose control does not always resolve the complications from DM (Coca, Ismail-Beigi, Haq, Krumholz, & Parikh, 2012; Maiese, Chong, Shang, & Hou, 2011). Use of diet control treatments may be effective to prevent hyperglycemic events, but these strategies have potential risks that can decrease organ mass through processes that involve autophagy (J. H. Lee et al., 2014). In addition to DM, there are other risk factors for neurodegenerative disorders and cognitive loss that include hypertension, low education in early life, and tobacco use (Maiese, 2019b, 2019c). Vascular disease as a result of DM also may lead to dementia (F. Chen et al., 2018; Maiese, 2018a, 2018d; Ong, Wu, Farooqui, & Farooqui, 2018). Current therapies for cognitive loss and AD that may be attributed to metabolic dysregulation are considered to be focused primarily on symptomatic care (Caberlotto et al., 2019; Maiese, 2019c; Su et al., 2019; Sun, Martin, Vanderpoel, & Sumbria, 2019; Ullah, Khan, Shah, Saeed, & Kim, 2019; H. Yu & Blair, 2019). Treatments that are directed to treat AD alone involve the use of cholinesterase inhibitors that may alleviate symptoms, but not disease progression (Ruhal & Dhingra, 2018). Strategies for dementia as a result of vascular disease focus on vascular and metabolic disorders, such as DM (Maiese, 2018b). Novel avenues of discovery are required to address metabolic dysfunction in tandem with neurodegenerative disease, such as cognitive loss. One innovative strategy that offers exciting prospects to fruitfully target both metabolic disease and neurodegenerative disorders 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).

The Mechanistic Target of Rapamycin

The mechanistic target of rapamycin (mTOR), a 289-kDa serine/threonine protein kinase, is encoded by a single gene FRAP1 (Z. Z. Chong et al., 2012; Esterline et al., 2018; Jesko, Stepien, Lukiw, & Strosznajder, 2019; Maiese, 2016b) (Figure 1). mTOR also is termed the mammalian target of rapamycin and the FK506-binding protein 12-rapamycin complex-associated protein 1 (Maiese, 2018b, 2018c). The target of rapamycin (TOR) was initially discovered in Saccharomyces cerevisiae with the genes TOR1 and TOR2 (Maiese, Chong, et al., 2013a). Through the use of rapamycin-resistant TOR mutants, TOR1 and TOR2 were found to encode the Tor1 and Tor2 isoforms in yeast (Heitman, Movva, & Hall, 1991). The agent rapamycin is a macrolide antibiotic in Streptomyces hygroscopicus that blocks TOR and mTOR activity (Maiese, 2015e).

Figure 1: Novel Therapeutic Avenues with mTOR.

The mechanistic target of rapamycin (mTOR) and its associated pathways of mTOR Complex 1 (mTORC1), mTOR Complex 2 (mTORC2), AMP activated protein kinase (AMPK), and the trophic factor erythropoietin offer novel therapeutic avenues to treat neurodegenerative disorders through metabolic pathways. mTOR and its pathways broadly impact metabolic disease and the nervous system through the oversight of programmed cell death pathways of autophagy and apoptosis. Given that current therapies for metabolic disease and neurodegenerative disorders address only symptomatic care, mTOR and its associated pathways provide strong prospects to treat both the onset and progression of metabolic disease in association with neurodegenerative disorders. Yet, it is clear that comprehensive understanding is required to appreciate the large breadth of mTOR pathways to safely translate treatments to clinical medicine without the onset of unexpected clinical disabilities.

mTOR plays a significant role as the principal component of the protein complexes mTOR Complex 1 (mTORC1) and mTOR Complex 2 (mTORC2) (Hwang & Kim, 2011; Maiese, 2016c; Martinez de Morentin et al., 2014). Rapamycin can prevent mTORC1 activity by binding to immunophilin FK-506-binding protein 12 (FKBP12) that attaches to the FKBP12 -rapamycin-binding domain (FRB) at the carboxy (C) -terminal of mTOR to interfere with the FRB domain of mTORC1 (Maiese, 2014c). The mechanism of how rapamycin blocks mTORC1 activity with the interaction of the domain of FRB is unclear. One consideration may involve allosteric changes on the catalytic domain as well as the inhibition of phosphorylation of protein kinase B (Akt) and p70 ribosomal S6 kinase (p70S6K) (Xue et al., 2009). mTORC1 appears to be more sensitive to inhibition by rapamycin than mTORC2, but chronic administration of rapamycin can inhibit mTORC2 activity as a result of the disruption of the assembly of mTORC2.

mTORC1 and mTORC2 are divided into subcomponents. mTORC1 is composed of Raptor, the proline rich Akt substrate 40 kDa (PRAS40), Deptor (DEP domain-containing mTOR interacting protein), and mammalian lethal with Sec13 protein 8, termed mLST8 (mLST8) (Maiese, Chong, et al., 2013a). mTORC1 can bind to its constituents through the protein Ras homologue enriched in brain (Rheb) that phosphorylates the Raptor residue serine⁸⁶³ and other residues that include serine⁸⁵⁹, serine⁸⁵⁵, serine⁸⁷⁷, serine⁶⁹⁶, and threonine⁷⁰⁶ (Foster et al., 2010). The inability to phosphorylate serine⁸⁶³ limits mTORC1 activity, as shown using a site-direct mutation of serine⁸⁶³ (L. Wang, Lawrence, Sturgill, & Harris, 2009). mTOR can control Raptor activity which can be blocked by rapamycin (L. Wang et al., 2009). Deptor, an inhibitor as well, blocks mTORC1 activity by binding to the FAT domain (FKBP12 -rapamycin-associated protein (FRAP), ataxia-telangiectasia (ATM), and the transactivation/transformation domain-associated protein) of mTOR. If the activity of Deptor is decreased, Akt, mTORC1, and mTORC2 activities are increased (Peterson et al., 2009). PRAS40 is known to block mTORC1 activity by preventing the association of p70 ribosomal S6 kinase (p70S6K) and the eukaryotic initiation factor 4E (eIF4E)-binding protein 1 (4EBP1) with Raptor (Maiese, 2014b; Malla, Ashby, et al., 2015). mTORC1 is active once PRAS40 is phosphorylated by Akt. This releases PRAS40 from Raptor to sequester PRAS40 in the cell cytoplasm with the docking protein 14–3-3 (Zhao Zhong Chong, Yan Chen Shang, Shaohui Wang, & Kenneth Maiese, 2012; Fonseca, Smith, Lee, MacKintosh, & Proud, 2007; Shang, Chong, Wang, & Maiese, 2012b; H. Wang et al., 2012; Xiong et al., 2014). mLST8, in contrast to Deptor and PRAS40, promotes mTOR kinase activity. This involves the binding of p70S6K and 4EBP1 to Raptor (D. H. Kim et al., 2003). Interestingly, mLST8 also controls insulin signaling through the transcription factor FoxO3 (Guertin et al., 2006; Maiese, 2015c), is necessary for Akt and protein kinase C-α (PKCα) phosphorylation, and is required for Rictor to associate with mTOR (Guertin et al., 2006).

mTORC1 is associated with metabolic cellular pathways (Esterline et al., 2018; Maiese, 2016d). mTORC1 can stimulate lipogenesis and fat storage (Chakrabarti, English, Shi, Smas, & Kandror, 2010), may increase pancreatic ß-cell mass (Hamada et al., 2009), and can improve glucose homeostasis (Malla, Wang, Chan, Tiwari, & Faridi, 2015). However, in the presence of other cellular pathways and systems such as with silent mating type information regulation 2 homolog 1 (Saccharomyces cerevisiae) (SIRT1), mTORC1 activity may require down-regulation to preserve glucose homeostasis (Y. Li et al., 2011).

mTORC2 has similarities as well as differences to mTORC1. mTORC2 is composed of Rictor, mLST8, Deptor, the mammalian stress-activated protein kinase interacting protein (mSIN1), and the protein observed with Rictor-1 (Protor-1) (Z. Z. Chong et al., 2012; Maiese, 2014b). mTORC2 controls cytoskeleton remodeling through PKCα and cell migration through the Rac guanine nucleotide exchange factors P-Rex1 and P-Rex2 and through Rho signaling (Jacinto et al., 2004). mTORC2 activates protein kinases that includes glucocorticoid induced protein kinase 1 (SGK1), a member of the protein kinase A/protein kinase G/protein kinase C (AGC) family of protein kinases. Protor-1, a Rictor-binding subunit of mTORC2, activates SGK1 (Garcia-Martinez & Alessi, 2008; Pearce, Sommer, Sakamoto, Wullschleger, & Alessi, 2011). The kinase domain of mTOR phosphorylates mSIN1 and prevents lysosomal degradation of this protein. Rictor and mSIN1 also can phosphorylate Akt at serine⁴⁷³ and foster threonine³⁰⁸ phosphorylation by phosphoinositide-dependent kinase 1 (PDK1) to enhance cell survival.

mTORC2 may be necessary to maintain glucose homeostasis (Maiese, 2016d), since loss of this pathway can promote severe hyperglycemia (Treins et al., 2012). Impairment in mTORC2 signaling also leads to oxidative damage and insulin resistance (R. H. Wang et al., 2011). In addition, mTORC2 signaling plays a significant role for the maintenance of pancreatic β-cell proliferation and mass (Gu, Lindner, Kumar, Yuan, & Magnuson, 2011).

AMP activated protein kinase (AMPK): A Negative Modulator of mTOR

The AMP activated protein kinase (AMPK) is closely tied to the mTOR pathway and metabolic disease (Chiu et al., 2017; Du et al., 2015; Jiang et al., 2014; Maiese, 2020) (Figure 1). AMPK can prevent mTORC1 activity through the hamartin (tuberous sclerosis 1)/tuberin (tuberous sclerosis 2) (TSC1/TSC2) complex that inhibits mTORC1 (Maiese, 2017c; Peixoto, de Oliveira, da Rocha Araujo, & Nunes, 2017). Control of the TSC1/TSC2 complex also is overseen though phosphoinositide 3-kinase (PI 3-K), Akt, and its phosphorylation of TSC2. Extracellular signal-regulated kinases (ERKs), protein p90 ribosomal S6 kinase 1 (RSK1), and glycogen synthase kinase −3β (GSK-3β) also can modulate the activity of the TSC1/TSC2 complex. TSC2 functions as a GTPase-activating protein (GAP) that converts G protein Rheb (Rheb-GTP) into the inactive GDP-bound form (Rheb-GDP). Once Rheb-GTP is active, Rheb-GTP associates with Raptor to oversee the binding of 4EBP1 to mTORC1 and increase mTORC1 activity (Sato, Nakashima, Guo, & Tamanoi, 2009). AMPK phosphorylates TSC2 to increase GAP activity to change Rheb-GTP into the inactive Rheb-GDP and to block mTORC1 activity (Inoki, Zhu, & Guan, 2003).

mTOR Pathways and the Intimate Link Between Autophagy and Apoptosis

mTOR and its downstream pathways of AMPK oversee pathways of both autophagy and apoptosis (Cheng et al., 2018; J. Dong, Li, Bai, & Wu, 2019; Dorvash, Farahmandnia, & Tavassoly, 2020; Maiese, 2015d, 2015e, 2016g; Zimmerman, Biggers, & Li, 2018) (Figure 1). This relationship with autophagy and apoptosis even extends to novel signaling systems that involve hydrogen sulfide (Maiese, 2019d; Wu et al., 2018; Q. Xiao, Ying, Xiang, & Zhang, 2018). Programmed cell death includes the pathways of autophagy and apoptosis (Klionsky et al., 2016; Maiese, 2017a; Maiese, Chong, Shang, & Wang, 2012b). Autophagy recycles components of the cytoplasm in cells for tissue remodeling (Preau et al., 2019; Y. Wang & Le, 2019; N. Zhang & Zhao, 2019) and eliminates non-functional organelles (C. Chen et al., 2017; Di Rosa, Distefano, Gagliano, Rusciano, & Malaguarnera, 2016; Klionsky et al., 2016; Maiese, 2015e; Maiese et al., 2012b). Macroautophagy recycles organelles and sequesters cytoplasmic proteins and organelles into autophagosomes. Autophagosomes then combine with lysosomes for degradation and recycling (Maiese, 2014b; White, Datta, & Giordano, 2017). Microautophagy involves lysosomal membranes invagination for the sequestration and digestion of cytoplasmic components (Maiese, 2015f). Chaperone-mediated autophagy (Maiese, 2015c) uses cytosolic chaperones to transport cytoplasmic components across lysosomal membranes (Moors et al., 2017).

Approximately 33 autophagic related genes (Atg) that have been identified in yeast with TOR that can affect multiple disorders including DM (Maiese, 2015e; Weckman et al., 2014). Atg1, Atg13 (also known as Apg13), and Atg17 are associated with Akt and TOR pathways (Klionsky et al., 2016). Either the Atg1 complex in yeast or the UNC-51 like kinase 1 (ULK1) complex in mammals is requires for the induction of autophagy (Kamada et al., 2000; Maiese et al., 2012b). The mammalian homologues of Atg1 are UNC-51 like kinase 1 (ULK1) and ULK2 (Z. Z. Chong et al., 2012). Mammalian Atg13 binds to ULK1, ULK2, and FIP200 (focal adhesion kinase family interacting protein of 200 kDa) to activate ULKs, promote the phosphorylation of FIP200 by ULKs, and lead to autophagy induction (Jung et al., 2009). mTOR activity blocks the onset of autophagy by phosphorylating Atg13 and ULKs to prevent formation of the ULK-Atg13-FIP200 complex (Jung et al., 2009).

Autophagy can be important for clinical aging pathways (Maiese, 2016a, 2017d; Y. Wang & Le, 2019). Studies with Drosophila show that neural aggregate accumulation observed with aging is linked to a reduction in the autophagy pathway. These neural aggregates lead to behavior impairments that can be resolved with the maintenance of autophagy pathways in neurons (Ratliff et al., 2015).

Autophagy is involved in a number of metabolic and neurodegenerative disorders, such as dementia (Crino, 2016; Hsieh, Liu, Lee, Yu, & Wang, 2019; M. Hu et al., 2017; Maiese, 2016a; Maiese, 2017b; Su et al., 2019), AD (Caberlotto et al., 2019; Cheng et al., 2018; Han, Jia, Zhong, & Shang, 2017; Hsieh et al., 2019; L. Li, 2017; Maiese, 2015g, 2017d; Saleem & Biswas, 2017; Su et al., 2019; Z. H. Zhang et al., 2017), Parkinson’s disease (Z. Z. Chong et al., 2012; Jang et al., 2015; Maiese, 2015b; Maiese, Chong, Wang, & Shang, 2013; Moors et al., 2017; Niranjan, Mishra, & Thakur, 2018; Savitt & Jankovic, 2019; Wen et al., 2018), Huntington’s disease (J. H. Lee et al., 2015; Maiese, 2015b, 2018b; Vidal et al., 2012), and DM (Caberlotto et al., 2019; Esterline et al., 2018; Hsieh et al., 2019; Maiese, 2015a; Maiese, 2015a, 2015b; Su et al., 2019; Tong et al., 2018).

In many cases, activation of autophagy with the concurrent inhibition of mTOR can result in neuroprotection in the nervous system (Maiese, 2016c). Autophagy may be particularly important for memory processing in individuals. Tau and Aß neurotoxicity may be reduced with autophagy (Cheng et al., 2018; Morris, Berk, Maes, & Puri, 2019; Z. H. Zhang et al., 2017). Activation of autophagy may be able to reduce Aß levels in the brain as one possible component to limit neurodegenerative decline (Cheng et al., 2018; Maiese, 2017b; Saleem & Biswas, 2017; Su et al., 2019). In regards to pathways associated with mTOR, learning and memory may be preserved with low calorie diets that promote autophagy and limit mTOR activity (W. Dong et al., 2016). Similar results of neuronal protection have also been noted with improved memory, greater insulin signaling, and autophagy activation that can decrease mTOR activity and increase Aß clearance (Han et al., 2017). Other studies find improvements in memory with increased autophagic flux, mTOR inhibition, and resultant tau clearance (Z. H. Zhang et al., 2017).

However, oversight of autophagy is vitally important in a number of scenarios that require mTOR activation for the nervous system. For example, interneuron progenitor growth in the brain relies upon mTOR activity with the inhibition of autophagy (Ka, Smith, & Kim, 2017). In addition, autophagy activation can impair endothelial progenitor cells, lead to mitochondrial oxidative stress, and block new blood vessel formation during elevated glucose exposure (K. A. Kim et al., 2014). During ischemic stroke in rodents, blockade of autophagy may also limit infarct size and rescue cerebral neurons (Yin et al., 2013). Trophic factors that can provide both neuronal and vascular protection in the nervous system, such as erythropoietin (EPO) (Chong, Kang, & Maiese, 2002; Maiese, 2016f; Maiese, Li, & Chong, 2005), can offer protection against neurotoxic by limiting the induction of autophagy and promoting the activation of mTOR (Jang et al., 2015; Maiese, 2017e) (Figure 1). EPO can regulate a number of components of the mTOR pathway, such as PRAS40 and Akt, to promote neuroprotection (Zhao Zhong Chong et al., 2012; H. J. Lee, Koh, Song, Seol, & Park, 2016; Maiese, Chong, Shang, & Wang, 2012a; G. B. Wang, Ni, Zhou, & Zhang, 2014).

In contrast to autophagy, apoptosis has two distinct phases. The early phase involves the loss of plasma membrane phosphatidylserine (PS) asymmetry (Hou, Chong, Shang, & Maiese, 2010; Maiese & Vincent, 2000; Schutters & Reutelingsperger, 2010; Shang, Chong, Hou, & Maiese, 2010; Taveira et al., 2018; Wei et al., 2013; Williams & Dexter, 2014) and a subsequent later phase that leads to genomic DNA degradation (Hou, Wang, Shang, Chong, & Maiese, 2011; S. Kim et al., 2015; S. L. Liu et al., 2017; Lu, Shen, Yang, & Gu, 2016; Maiese, 2012; Taveira et al., 2018). Apoptosis is the result of a cascade activation of nucleases and proteases that involve caspases (Chong et al., 2005; Dai et al., 2017; C. Ding et al., 2017; Gao et al., 2017; Maiese, 2016a; A. Park & Koh, 2019). These processes can influence both the early phase of apoptosis with the loss of plasma membrane PS asymmetry and a later phase that leads to genomic DNA degradation. Loss of membrane PS asymmetry activates inflammatory cells to target, engulf, and remove injured cells (Bailey, Fossum, Fimbel, Montgomery, & Hyde, 2010; Hou et al., 2010; Shang, Chong, Hou, & Maiese, 2009; Wei et al., 2013). Yet, if the engulfment of inflammatory cells can be prevented and not be removed from the nervous system, then functional cells expressing membrane PS residues can be rescued (S. Kim et al., 2015; Maiese, 2015b; Xin et al., 2015; T. Yu et al., 2015). On the flip side, once the destruction of cellular DNA occurs, it is usually not considered to be completely reversible (Maiese, 2015b).

mTOR activation usually can act to prevent apoptotic cell death in the nervous system (Z. Z. Chong et al., 2012; Maiese, 2018c; Wen et al., 2018; Q. Zhou et al., 2016). During periods of mTOR activity, microglia can be protected from oxidative stress (Shang, Chong, Wang, & Maiese, 2011), retinal ganglion cell regeneration occurs (Teotia, Van Hook, Fischer, & Ahmad, 2019), and diabetic peripheral neuropathy can be reduced (J. Dong et al., 2019). This reduction by mTOR of oxidative stress induction has been suggested to be protective in neurodegenerative disorders such as Parkinson’s disease (PD) (C. Zhang et al., 2017). In addition with mTOR activation, Aß toxicity can be prevented (Bellozi et al., 2016; Morris et al., 2019; Shang, Chong, Wang, & Maiese, 2012a; Shang et al., 2012b; Shang, Chong, Wang, & Maiese, 2013; Y. Wang et al., 2015), vascular cell death minimized (Maiese, 2014c; J. A. Park & Lee, 2017), oxidative stress with mitochondrial injury can be blocked (Dai et al., 2019), neuroplasticity can be enhanced (Farmer et al., 2019), neuronal differentiation can be promoted (Huang et al., 2019), neonatal central nervous system hypoxic injury can be averted (Xi, Wang, Long, & Ma, 2018), and reduced stroke volume with decreased apoptotic cell death dependent upon circadian rhythm activity can occur (Beker et al., 2018).

However, it should be noted that apoptosis has an inverse relationship with autophagy (Y. Dong et al., 2019; Maiese, 2017e). Activation of autophagy blocks the activity of mTOR (Dorvash et al., 2020; Maiese, 2019a, 2020). Under some circumstances, cellular protection can occur that ultimately leads to mTOR inhibition. For example, autophagy activation with the blockade of mTOR can prevent injury to dopamine dependent cells (A. Park & Koh, 2019), decrease reactive oxygen species release (Javdan et al., 2018), control neuroprotection with glutamine dependent mechanisms (Y. Zhao et al., 2019), and prevent mitochondrial dysfunction (Dai et al., 2017). In addition, recent work demonstrates that limitations in mTOR activity may reduce markers of senescence and aging in human skin (Chung et al., 2019) and limit aging with extension of cell longevity through AMPK in endothelial cells (H. Zhang et al., 2019). These studies highlight the intimate link between autophagy and apoptosis that center upon mTOR that must be considered for the development of new treatment strategies in the nervous system. The oversight of autophagy and apoptosis require careful modulation since inhibition of mTOR pathways with autophagy activation also can control tumor cell growth (Mu et al., 2019; L. Zhou et al., 2019). Other studies also point to the balance required during embryogenesis for autophagy and apoptosis that can affect body axis formation (G. Xu et al., 2019).

Targeting Metabolic Dysfunction with mTOR Pathways

mTOR has a significant role in cellular metabolic function (Chong & Maiese, 2012; Esterline et al., 2018) (Figure 1). In patients with metabolic syndrome, mTOR activation has been found to be diminished and possibly responsible for insulin resistance and the increased risk of vascular thrombosis (Pasini et al., 2010). Activation of mTOR pathways with p70S6K and 4EBP1 can improve insulin secretion in pancreatic β-cells and increase resistance to β-cell streptozotocin toxicity and obesity in mice (Hamada et al., 2009). Loss of p70S6K activity leads to hypo-insulinemia and glucose intolerance with decreased pancreatic β-cell size (Pende et al., 2000). Activation of mTOR also can protect pancreatic β- cells against cholesterol-induced apoptosis (J. Zhou, Wu, Zheng, Jin, & Li, 2015), lead to enhanced neuronal cell survival in cell models of DM (Y. W. Liu et al., 2015), and lessen glucolipotoxicity (Miao et al., 2013). mTOR activity also appears to be able to modulate insulin signaling in experimental models of AD and maintain astrocyte viability (Crespo et al., 2017), allow for the differentiation of adipocytes (Jung et al., 2015), prevent endothelial cell dysfunction during hyperglycemia (Pal et al., 2019), and preserve glucose homeostasis (Malla, Wang, et al., 2015). In regards to nutrition, mTOR may offer protection as a component of the Mediterranean diet. This diet has been tied to a reduction in Aβ toxicity in astrocytes through enhanced Akt activity by consumption of polyphenol of olives and olive oil that ultimately could prevent the onset or progression of AD (Crespo et al., 2017).

Modulation of the activity of mTOR appears to be a critical point in targeting this pathway. During mTOR inhibition with rapamycin, reduced β-cell function, insulin resistance, and decreased insulin secretion can lead to the progression of DM (Fraenkel et al., 2008). Decreased activity of mTOR has been shown to increase mortality in a mouse model of DM (Sataranatarajan et al., 2016). Without mTOR activity, translocation of glucose transporters to the plasma membrane in skeletal muscle are also affected (Deblon et al., 2012). Interestingly, inhibition of mTOR during DM can sometimes offer protection such as during cerebral ischemia (P. Liu et al., 2016) and be necessary for maintaining a balance between pancreatic β-cell proliferation and cell size (Gu et al., 2011). This suggests that there may be biological feedback pathways with mTOR, such as through AMPK inhibition, to prevent excessive mTOR activity. For example, if mTOR activity is allowed to go unchecked with the down-regulation of AMPK activity during experimental studies, mTOR and p70S6K can lead to glucose intolerance by inhibiting the insulin receptor substrate 1 (IRS-1) (Kang, Chemaly, Hajjar, & Lebeche, 2011).

In addition to potential feedback pathways with mTOR, loss of mTOR activity during metabolic disease may be beneficial through the activation of pathways associated with autophagy. Current studies point to the dysregulation of autophagy as a central pathway that can potentially lead to the progression of cognitive loss with AD and the induction of DM (Caberlotto et al., 2019). At least 33 autophagy-related genes (Atg) that have been identified in yeast and 40 autophagy-related genes involved in the formation of autophagosomes (N. Zhang & Zhao, 2019) that can affect multiple disorders including DM (Maiese, 2015c, 2016d; Weckman et al., 2014). Atg1, Atg13 (also known as Apg13), and Atg17 are associated with the PI 3-K, Akt, and TOR pathways (Klionsky et al., 2016). Earlier studies have shown that autophagy haploinsufficiency with deletion of Atg7 gene in mouse models of obesity promotes increased insulin resistance with elevated lipids and inflammation (Lim et al., 2014). Loss of autophagic proteins Atg7, Atg5, and LC3 can be responsible for diabetic nephropathy (Ma et al., 2016). Autophagy can remove misfolded proteins and eliminate non-functioning mitochondria to maintain β-cell function and prevent the onset of DM (Z. Liu, Stanojevic, Brindamour, & Habener, 2012). Exercise in mice has been shown to promote the induction of autophagy and regulate glucose homeostasis (He et al., 2012). Autophagy can improve insulin sensitivity during high fat diets in mice (Y. Liu et al., 2014) and may be protective to microglia during acute glucose fluctuations (Hsieh et al., 2019).

As a pathway of mTOR, AMPK is vital in regulating cellular metabolism and the pathways of programmed cell death. AMPK has been shown to reduce insulin resistance, since the loss of AMPK results in reduced tolerance to the development of insulin resistance (Y. Liu et al., 2014). AMPK also is involved in the protection of endothelial progenitor cells during periods of hyperglycemia (Chiu et al., 2017). During periods of dietary restriction that may increase lifespan (Balan et al., 2008), AMPK can be one factor to shift to beneficial oxidative metabolism (Moroz et al., 2014). As a result, AMPK can reduce ischemic brain damage in diabetic animal models (P. Liu et al., 2016). In regards to cognition, AMPK activation can improve memory retention in models of AD and DM (Du et al., 2015), may assist with the elimination of ß-amyloid (Aß) in the brain (Zhao, Wang, Wang, & Chen, 2015), facilitate tau clearance (Z. H. Zhang et al., 2017), modulate chronic inflammation in neurodegenerative disorders (Maiese, 2016g, 2017d; Peixoto et al., 2017), and limit Aß neurotoxicity (C. L. Lin et al., 2015).

AMPK functions through both apoptosis and autophagy. During periods of hyperglycemia, AMPK activity may be necessary to increase basal autophagy activity (Klionsky et al., 2016; Maiese, 2015b) and maintain endothelial cell survival (Pal et al., 2019; Weikel, Cacicedo, Ruderman, & Ido, 2016). AMPK also can regulate apoptosis and autophagy during coronary artery disease (Y. Dong et al., 2019), endothelial dysfunction during hyperglycemia (Pal et al., 2019), and oxidative stress cell injury (Shokri Afra et al., 2019; D. Zhao et al., 2019). Anti-senescence activity also can be fostered through mTOR inhibition, AMPK activation, and the acceleration of autophagic flux (H. Zhang et al., 2019).

Present agents used to treat DM such as biguanides and metformin rely upon mTOR and autophagy pathways to restore cellular function. Metformin inhibits mTOR activity, promotes autophagy, and may function at times in an AMPK-independent manner (Kalender et al., 2010). Other reports note that through metformin, AMPK is activated, restores the induction of autophagy, and protects against diabetic cardiac cell apoptosis (He, Zhu, Li, Zou, & Xie, 2013). Metformin also has been shown to limit lipid peroxidation in the brain and spinal cord and decrease caspase activity during toxic insults (Oda, 2017). Such results may be associated with the ability of autophagic pathways to limit oxidative stress under some circumstances (Maiese, 2015a; Zimmerman et al., 2018).

However, it should be recognized that autophagy pathways require a fine balance in activity. In some experimental models of AD, autophagy can be one factor that leads to neuronal cell death (Saleem & Biswas, 2017). Increased activity of autophagy can lead to significant loss of cardiac and liver tissue in diabetic rats during attempts to achieve glycemic control through diet modification (J. H. Lee et al., 2014). During periods of elevated glucose, advanced glycation end products (AGEs), agents that can result in complications during DM, have been shown to lead to the induction of autophagy and vascular smooth muscle proliferation that can result in atherosclerosis (P. Hu, Lai, Lu, Gao, & He, 2012) as well as cardiomyopathy (Y. Lee, Hong, Lee, & Chang, 2012). During elevated glucose exposure, autophagy also can impair endothelial progenitor cells, lead to mitochondrial oxidative stress (Martino et al., 2012), and block angiogenesis (K. A. Kim et al., 2014). Furthermore, chronic inflammatory conditions such as lichen planus have been linked to mTOR inhibition and autophagy activation (L. Wang et al., 2019).

Future Perspectives

More than 40 million people die from NCDs each year (Table 1). Even more concerning to note is that a significant proportion of the 15 million affected by NCDs are between 30 and 69 years old, impacting a significant portion of the growing global population. In addition, NCDs affect a much larger proportion of the population in low and middle-income countries with at least one-third of the population under the age of 60 suffering from NCDs. The rise in NCDs parallels the increase in life expectancy of the world’s population and includes a large component of disease entities that can progressively lead to neurodegenerative disorders. Of these neurodegenerative diseases, dementia is now considered to be the 7^th leading cause of death. It is estimated by the year 2030, 82 million people are expected to have dementia and by the year 2050, 152 million individuals will suffer from dementia.

Table 1: Highlights.

• The rise in non-communicable diseases (NCDs) parallels an increase in life expectancy of the world’s population leading to a heightened prevalence of metabolic disorders and neurodegenerative diseases, such as cognitive loss.

• Metabolic disorders, such as diabetes mellitus, are significant risk factors for the development of neurodegenerative disease.

• Given that current therapies for these NCDs address only symptomatic care, the mechanistic target of rapamycin (mTOR) and its associated pathways of mTOR Complex 1 (mTORC1), mTOR Complex 2 (mTORC2), AMP activated protein kinase (AMPK), and the trophic factor erythropoietin offer innovative strategies to treat neurodegenerative disorders through metabolic pathways.

• mTOR and its pathways broadly impact metabolic disease and the nervous system through the oversight of programmed cell death pathways of autophagy and apoptosis.

• mTOR and its associated pathways offer strong prospects to treat both the onset and progression of metabolic disease that can affect neurodegenerative disorders, but comprehensive understanding is required of the breadth of mTOR pathways to safely translate treatments to clinical medicine without the development of unexpected clinical disabilities.

Intimately tied to neurodegenerative disorders are metabolic disorders, such as DM. DM affects all systems of the body including the neurovascular systems. The number of individuals with DM is expected to rise to 700 million by the year 2045. New work highlights metabolic disorders and DM as significant risk factors that can affect the development of treatment strategies for neurodegenerative disorders. Innovative avenues of investigation are necessary to address metabolic dysfunction in tandem with neurodegenerative disease, especially those disorders that involve cognitive loss and AD.

Currently, treatments for DM and cognitive disease are limited. Tight serum glucose control does not always lead to the resolution of complications from DM (Coca et al., 2012; Maiese, Chong, Shang, & Hou, 2011). In addition, use of diet and body mass control may control hyperglycemic events, but these strategies also can potentially decrease organ mass through processes that involve autophagy (J. H. Lee et al., 2014). In regards to cognitive disease, most available treatments that are directed to treat AD alone involve the use of cholinesterase inhibitors (Ruhal & Dhingra, 2018). Dementia as a result of vascular disease may be treated with therapies that focus on vascular and metabolic disorders, such as DM (Maiese, 2018b). Yet, these treatments for the most part focus upon symptoms and do not alter disease progression. Given these severe limitations for treating neurodegenerative disorders during metabolic dysfunction, it is vital to address novel pathways that can identify the cellular links between metabolic dysfunction and neurodegenerative disorders.

The pathways of mTOR that include mTORC1, mTORC2, AMPK, and trophic factors that include EPO provide exciting opportunities to identify new treatment strategies that can address neurodegenerative disorders that are dependent upon metabolic dysfunction. For example, mTORC1 can stimulate lipogenesis and fat storage (Chakrabarti et al., 2010), may increase pancreatic ß-cell mass (Hamada et al., 2009), and may improve glucose homeostasis (Malla, Wang, et al., 2015). Impairment in mTORC2 signaling results in oxidative damage and insulin resistance (R. H. Wang et al., 2011) and mTORC2 signaling plays an important role for the maintenance of pancreatic β-cell proliferation and mass (Gu et al., 2011). Trophic factors, such as EPO, also can provide cellular protection against neurotoxic insults by promoting the activation of mTOR (Jang et al., 2015; Maiese, 2017e). EPO can regulate a number of components of the mTOR pathway, such as PRAS40 and Akt, to promote neuroprotection (Zhao Zhong Chong et al., 2012; H. J. Lee et al., 2016; Maiese et al., 2012a; G. B. Wang et al., 2014). As a result, EPO may be relevant for clinical disorders such as PD. EPO modulation of mTOR and autophagic pathways may lead to protection of the dopaminergic system (Jang et al., 2015).

These pathways oversee cellular survival and function through the programmed cell death pathways of autophagy and apoptosis. Modulating autophagy and apoptosis, mTOR broadly impacts metabolic disease and the nervous system such as offering protection for pancreatic β- cells (J. Zhou et al., 2015), controlling insulin signaling during AD (Crespo et al., 2017), and preventing endothelial cell dysfunction during hyperglycemia (Pal et al., 2019). Equally important is the function of AMPK as evidenced by its ability to reduce ischemic brain damage in diabetic animal models (P. Liu et al., 2016).

Yet, a number of challenges exist for the development of new treatments for neurodegenerative disorders linked to metabolic disease. Pathways such as mTOR, mTORC1, mTORC2, AMPK, and autophagy require a fine level of control to not only prevent the onset and progression of neurodegenerative disorders, but also to limit the development of undesired or unexpected clinical disabilities. For example, AMPK activation can improve memory retention in models of AD and DM (Du et al., 2015), prevent lipid accumulation and obesity (Maiese, 2015e), and promote neuroprotection (Jiang et al., 2014). Yet, under different cellular environments, inhibition of AMPK activity is required to offer protection of pancreatic islet cells in mice (Guan et al., 2014), limit Aβ toxicity (Shang et al., 2013), and prevent inflammation in the nervous system (Russo et al., 2014). In addition, internal cellular feedback pathways need to be further identified to gain sufficient insight for the careful biological control of mTOR and autophagy in order to successfully translate these pathways to clinical medicine. Unchecked mTOR activity in combination with the down-regulation of AMPK activity can lead to glucose intolerance and progression of neurodegenerative disorders. Current studies have provided an enormous wealth of information for elucidating previously unrecognized contributions of metabolic disease to disorders such as AD. However, given the complexity of the underlying pathways with mTOR and programmed cell death, further comprehensive work is required to properly capture the potential of these pathways to effectively treat metabolic dysfunction and neurodegenerative disease for the growing population that is increasingly affected by these disorders throughout the world.

Abbreviations:

AD

Alzheimer’s disease

AMPK

AMP activated protein kinase

Atg

Autophagic related genes

Deptor

DEP domain-containing mTOR interacting protein

DM

Diabetes mellitus

EPO

Erythropoietin

4EBP1

Eukaryotic initiation factor 4E (eIF4E)-binding protein 1

ERKs

Extracellular signal-regulated kinases

TSC1/TSC2

Hamartin (tuberous sclerosis 1)/tuberin (tuberous sclerosis 2)

IRS-1

Insulin receptor substrate 1

mLST8

Mammalian lethal with Sec13 protein 8, termed mLST8

mTOR

Mechanistic target of rapamycin

mTORC1

mTOR Complex 1

mTORC2

mTOR Complex 2

NCDs

Non-communicable diseases

p70S6K

p70 ribosomal S6 kinase

PD

Parkinson’s disease

PS

Phosphatidylserine

PDK1

Phosphoinositide-dependent kinase 1

PRAS40

Proline rich Akt substrate 40 kDa

Akt

Protein kinase B

ULK1

UNC-51 like kinase 1

US

United States

USD

United States dollars