Current Perspectives: Obesity and Neurodegeneration - Links and Risks

Paul J Kueck; Jill K Morris; John A Stanford

doi:10.2147/DNND.S388579

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Review

Current Perspectives: Obesity and Neurodegeneration - Links and Risks

Authors Kueck PJ , Morris JK , Stanford JA

Received 1 August 2023

Accepted for publication 21 December 2023

Published 3 January 2024 Volume 2023:13 Pages 111—129

DOI https://doi.org/10.2147/DNND.S388579

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Thomas Müller

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Paul J Kueck,^1,² Jill K Morris,^{1– 3} John A Stanford^3,⁴

¹Department of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA; ²Department of Cell Biology and Physiology, University of Kansas Medical Center, Kansas City, KS, 66160, USA; ³University of Kansas Alzheimer’s Disease Research Center, University of Kansas Medical Center, Kansas City, KS, 66160, USA; ⁴Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS, 66160, USA

Correspondence: John A Stanford, Email [email protected]

Abstract: Obesity is increasing in prevalence across all age groups. Long-term obesity can lead to the development of metabolic and cardiovascular diseases through its effects on adipose, skeletal muscle, and liver tissue. Pathological mechanisms associated with obesity include immune response and inflammation as well as oxidative stress and consequent endothelial and mitochondrial dysfunction. Recent evidence links obesity to diminished brain health and neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). Both AD and PD are associated with insulin resistance, an underlying syndrome of obesity. Despite these links, causative mechanism(s) resulting in neurodegenerative disease remain unclear. This review discusses relationships between obesity, AD, and PD, including clinical and preclinical findings. The review then briefly explores nonpharmacological directions for intervention.

Keywords: obesity, metabolism, Alzheimer’s, Parkinson’s, neurodegeneration

Introduction

Obesity is a disease of excessive fat accumulation and is defined by a body mass index (BMI) greater than or equal to 30kg/m². While obesity develops gradually and is traditionally seen in the older sedentary population, the disease is becoming more common in younger individuals.¹ The development of obesity is driven mostly by caloric excess from a “Western”-style diet.² Despite increasing evidence for the negative health effects of obesity,³ the World Health Organization reported 13% of the world population to be obese in 2016 and since 1975 the prevalence of obesity has nearly tripled.⁴ This has important implications for other chronic diseases that have been linked to metabolic dysregulation, including neurodegenerative diseases.

Research has identified both modifiable and nonmodifiable risk factors for obesity. Early twin studies report a heritability of 40–80% for BMI.⁵ More recently, Genome-Wide Association Studies have identified 115 genetic loci, accounting for 2–3% of the variation in BMI. This suggests that approximately 20% of the variation in BMI may be due to genetic factors.⁶ Socioeconomic factors such as education, income, and occupation may also contribute to obesity at both an individual and environmental level.^7–9 The literature is clear that weight reduction can be achieved by modifying lifestyle behaviors. Although weight loss can result from exercise alone,^10–12 exercise in combination with dietary programs lead to greater weight loss.^13–17 Sleep is also associated with obesity. Low sleep duration is associated with a greater incidence of obesity.^18–20 However, this relationship appears to be a “U shaped” function as obesity risk increases with long sleep duration.^21,22

Obesity can negatively affect many systems throughout the body, most notably the cardiovascular system. Individuals with obesity have elevated blood pressure independent of adrenergic activity.²³ The observed hypertension in obese patients is due to an increase in stroke volume, which can lead to left ventricular hypertrophy.^24,25 Another adverse effect of obesity is disrupted hemodynamics. Individuals with obesity have elevated cholesterol and low-density lipoprotein levels,^26,27 which can impair vascular tone.²⁸ Cholesterol accumulation alone can also drive atherosclerotic plaque formation which can further damage endothelial cells from increased shear stress.^29,30 Concurrently, obesity has a negative impact on other organs such as the liver. Obesity is strongly linked to nonalcoholic fatty liver disease (NAFLD), with disease severity related to impaired glycemic status.^31,32 Direct relationships between the prevalence of type 2 diabetes (T2D) and BMI have been reported.³³ The overnutrition associated with obesity leads to chronically elevated insulin and inflammation, which can result in insulin resistance that precedes hyperglycemia.^34,35

Obesity and related metabolic changes have been linked to impaired brain health and development of neurodegenerative disease. There is evidence that insulin resistance can develop not only in the periphery but also in the central nervous system (CNS).^36,37 Mechanisms linking metabolic dysfunction and neurodegeneration include insulin resistance and associated factors such as inflammation, immune response, oxidative stress, and mitochondrial dysfunction. The review summarizes obesity-related metabolic changes across tissue types that are linked to neurodegeneration as well as potential interventions.

Metabolic Changes Associated with Obesity

Total energy expenditure is defined as the daily amount of energy an individual expends and is a combination of basal metabolic rate, thermogenic effect of food, and physical activity.³⁸ Basal metabolic rate accounts for the majority of total energy expenditure, and variability amongst individuals depends primarily on their lean and fat mass composition. All cells require mitochondrial ATP production to sustain cellular function. Impaired nutrient delivery, uptake, and biogenesis can impair mitochondrial function. In healthy individuals, elevated glucose levels stimulate the release of insulin from the beta cells of the pancreas. Many cells utilize insulin-dependent glucose transports, such as Glucose Transporter Type 4 (GLUT4), to transport glucose from the blood into the cell. Elevated fatty acid levels in individuals with obesity can impair glucose metabolism and insulin production and result in beta cell loss.³⁹ Over time, skeletal muscle, adipose tissue, and liver become less responsive to elevated insulin, leading to detrimental effects in additional organs including the brain.⁴⁰ These tissue specific effects will be discussed in the following section.

Adipose Tissue

The most prominent manifestation of obesity is accumulation of adipose tissue. There are two primary types of adipose tissue with important differences in their distribution patterns, their function, and their metabolic properties. White adipose tissue is located throughout the body, where it stores lipids and regulates circulating fatty acid levels.⁴¹ White adipose is distributed in two anatomically distinct regions: subcutaneous adipose lies beneath the skin and visceral adipose (ie abdominal fat) surrounds internal organs. While only accounting for ~10% of total fat mass, visceral fat is more strongly associated with cardiovascular risk than subcutaneous fat.^42–44 Brown adipose tissue is distinctly different due to its role in maintaining body temperature, which can profoundly affect energy expenditure.⁴⁵ Brown adipose tissue distribution is more limited and is most active during the early years of life.⁴⁶ Brown adipose activity is lower in males whose BMI is greater than 25 compared to males with lower BMI.⁴⁷ The thermogenic properties of brown adipose tissue results in greater energy consumption and may prevent obesity by lowering plasma glucose and lipids, thus improving glucose homeostasis.⁴⁸

In addition, the increased adipose tissue seen in obese individuals may stimulate the release of fatty acids into the plasma.⁴⁹ Elevated fatty acids can accumulate in skeletal muscle which may cause insulin resistance in skeletal muscle and liver.⁵⁰ Hyperglycemia stimulates the glycolytic pathway and the Krebs cycle, leading to a heightened influx of electron carriers into the mitochondria. This, in turn, results in the production of free radicals in the form of superoxide.⁵¹ Furthermore, elevated fatty acids can generate superoxide, thus increasing oxidative stress.⁵²

Skeletal Muscle

Skeletal muscle accounts for about 40% of total body weight and is a metabolically active tissue that plays a significant role in energy homeostasis.^53,54 Skeletal muscle consists of distinct fiber types, classified generally as Type I (slow-twitch) fibers, and Type II (fast-twitch) fibers. Although these two fiber types can be further divided into subtypes, this review will focus broadly on Type I and Type II muscle fibers. Type I fibers have a greater oxidative potential than Type II fibers⁵⁵ due to their greater mitochondrial density.⁵⁶ The composition of skeletal muscle varies across muscle groups, with Type I fibers predominating in anti-gravity muscles and Type II fibers predominating in muscles involved in fast movements. Physical exercise can promote skeletal muscle hypertrophy, while physical inactivity and various diseases such as cancer and diabetes can cause muscle atrophy.⁵⁷ Although the greater body weight associated with obesity may lead to muscle hypertrophy, strength per body mass is lower in obesity.⁵⁸ Defining muscle quality as grip strength divided by lean mass, Raghupathy et al reported that individuals with obesity, particularly women, may have greater muscle mass but their muscle quality is lower.⁵⁹ Grip strength is a noninvasive biomarker that may indicate an individual’s health status.⁶⁰ Grip strength is inversely correlated with blood glucose levels.^61,62

Sarcopenia, which is the loss of muscle mass and strength, is associated with aging and is a risk factor for cognitive decline.⁶³ Sarcopenia can begin as early as age twenty-five⁶⁴ and progresses thereafter.⁶⁵ The association between sarcopenia and obesity is complex but it does increase the risk of disability, morbidity, and mortality.⁶⁶ Interestingly, obesity in the elderly is considered a risk factor for sarcopenia when defined by body fat percentage, but protective when defined by BMI.⁶⁷ Due to the decreased muscle and bone mass in the elderly compared to young, these different outcome measures should be assessed.⁶⁸ Skeletal muscle plays a major role in metabolism, so sarcopenia can profoundly impact these processes, leading to pathologies such as oxidative stress, inflammation, and insulin resistance.⁶⁹

Skeletal muscle energy production is fiber type specific. Type I fibers use oxidative metabolism and Type II fibers rely primarily on glycolytic metabolism.⁷⁰ Type I fibers have a greater expression of proteins that transport, phosphorylate, and oxidize glucose compared to Type II fibers, suggesting that glucose uptake and metabolism is greater in Type I fibers.⁷¹ Skeletal muscle from individuals with obesity is characterized by insulin signaling deficits that lead to impaired glucose metabolism.^72–74 While the exact mechanism remains unclear, chronic overnutrition likely stresses insulin signaling, resulting in decreased glucose uptake in skeletal muscle. Greater blood glucose resulting from decreased uptake in muscle results in increased liver glucose and impaired liver insulin resistance.⁴⁰ Obesity is associated with a reduced percentage of Type I fibers and an increased percentage of Type II fibers.⁷⁵ Given that glucose trafficking and utilization is greater in Type I fibers, this selective decrease may further exacerbate insulin signaling deficits. In addition, obesity is accompanied by greater lipid deposits in skeletal muscle, greater lipid oxidation, and lower glycemic oxidation.^76–78 These alterations require greater metabolic flexibility. The failure to adequately meet these energy demands can trigger autophagy⁷⁹ and potentially contribute to the development of neurodegenerative disease.⁸⁰

Liver

The liver plays a central role in metabolism by synthesizing, storing, and releasing lipids and glucose.⁸¹ In the healthy insulin sensitive state, insulin decreases gluconeogenesis (glucose production) in the liver.⁸² The most common liver disease is NAFLD,⁸³ which is associated with obesity.⁸⁴ The hyperinsulinemia and hyperglycemia that accompany insulin resistance result in an imbalance favoring fat storage in the liver, which can progress to NAFLD.⁸⁵ NAFLD begins as low-grade localized inflammation, but obesity and insulin resistance can exacerbate this inflammation and cause it to spread systemically, affecting multiple organ systems including the brain.⁸⁶ While the CNS is generally protected from systemic circulation, cytokines and chemokines can cross the blood brain barrier and have been implicated in cognitive impairment.⁸⁷

Early studies by Stanhope et al linked the consumption of fructose-sweetened beverages to the development of NAFLD.⁸⁸ Over the past 30 years, total sugar consumption (ie sucrose and high-fructose corn syrup) has increased by about 15%.⁸⁹ Although commonly compared to glucose, fructose differs in that it decreases liver ATP levels and increases liver de novo lipogenesis.⁹⁰ Uric acid is a byproduct of fructose metabolism and accumulates in visceral fat in individuals with obesity.⁹¹ While common in the “Western Diet”, fructose can also be elevated indirectly. The Polyol pathway, better known as the aldose reductase pathway, is a two-step pathway that converts glucose to fructose with sorbitol as an intermediate. Uric acid can activate aldose reductase, further promoting the development of NAFLD.⁹² Furthermore, correlations between beta-amyloid load and inflammation in individuals with mild cognitive impairment have been observed.⁹³ Microglia can release pro-inflammatory cytokines upon activation and contribute to neuroinflammation.⁹⁴ Aldose reductase has been linked to inflammation and using BV-2 cells, Song et al reported aldose reductase inhibitors reduce the beta-amyloid stimulated production of TNF-α in microglia.⁹⁵ In addition, a prospective study reported individuals with the highest consumption of fructose were at a greater risk of dementia compared to those who reported no fructose intake.⁹⁶ Further research into the role fructose and aldose reductase have in metabolism and neurodegenerative diseases is warranted.

Brain Metabolism

The brain is the most metabolically active organ of the body, consuming 20% of available glucose and oxygen at rest.^97,98 Neural activation causes rapid changes to local brain blood flow.⁹⁹ To maintain adequate global brain blood perfusion and removal of waste products, baroreceptors and chemoreceptors continuously monitor and adapt to changes in blood pressure and chemicals such as CO2.^100,101

Although similar in some ways, the brain has unique mechanisms to maintain metabolic needs compared to the periphery. The blood-brain barrier is a specialized layer of endothelial cells supported by astrocytes and pericytes that limits the permeability of blood-borne substances into the CNS.¹⁰² Unlike other tissues, neurons and astrocytes primarily use insulin-independent transporters to transport glucose across this barrier. Another difference between central and peripheral metabolism is their preferred energy substrates. While peripheral tissues can leverage fatty acids as alternative fuel substrates, the CNS is more limited. When less glucose is available, such as times of starvation or exercise, the brain becomes more reliant on ketones¹⁰³ or lactate.¹⁰⁴ Finally, the brain uses a unique and localized glucose transport system. GLUT1 is primarily localized to endothelial cells and the perivascular endfeet of astrocytes.¹⁰⁵ Both GLUT3 and GLUT4 are located on neurons, with localization of GLUT4 corresponding to insulin receptor expression.^106–109 GLUT5 is primarily located on microglia.¹¹⁰ Additional research into the intersection between peripheral and central glucose metabolism and its role in aging and neurodegeneration is ongoing and warranted. In addition to the mechanisms reviewed in this section, obesity is associated with reduced cerebral perfusion^111–113 and individuals with obesity exhibit cortical thinning even in the absence of cognitive impairment.¹¹⁴

Potential Mechanisms for Links Between Obesity and Brain Health

Our focus of the review so far has covered defining obesity, risk factors associated with obesity, and the effects of obesity in various tissues. We will now shift our attention to how these changes interact with mechanisms that link insulin resistance to the two most common neurodegenerative diseases, AD and PD.

Insulin Resistance

Insulin resistance is defined as the impaired response of the body to insulin. Insulin secreted from the pancreas circulates throughout the body and binds to cell surface receptors, initiating a signaling cascade. Insulin resistance can occur when any step along the signaling pathway is disrupted. Mechanisms that cause insulin resistance are not clearly understood and beyond the scope of this review. As mentioned earlier, elevated fatty acids can suppress insulin stimulated glucose uptake in skeletal muscle and liver. I insulin-dependent GLUT is predominately expressed in these tissues. However, insulin resistance is also observed in cells that primarily express insulin-independent GLUT such as the endothelial cells in that comprise the blood-brain barrier.

Plasma glucose is commonly elevated in obesity and is associated with reduced cerebral glucose uptake.¹¹⁵ In cognitively impaired individuals, increased glucose levels in serum were associated with attenuated regional cerebral glucose metabolism.¹¹⁶ In addition, our group reported that individuals whose fasting glucose levels increased over one year also had greater brain atrophy and increased cerebral amyloid accumulation compared to individuals whose fasting plasma glucose levels decreased over the same amount of time.¹¹⁷

During an immune response, blood flow and leukocytes are increased to eliminate a pathogen. Toll-like receptors (TLR) expressed on the surface of innate immune cells recognize pathogen associated molecular patterns. When a pathogen associated molecular pattern binds to a TLR, cytokines, such as IL-6 and TNF-α are released to recruit immune cells. These inflammatory cytokines are chronically elevated in obesity,¹¹⁸ and chronic inflammation is believed to contribute to insulin resistance.¹¹⁹

Although IL-6 is well known for its role in immune and inflammatory responses, it has recently gained more recognition for its acute effect on metabolism.¹²⁰ Increased release of IL-6 from adipose tissue occurs 60 minutes post-exercise in healthy adults.¹²¹ When healthy adults were infused with IL-6, lipolysis increased without changes in catecholamines, glucagon, or insulin, and the infusion did not cause hypertriglyceridemia.¹²² In a randomized controlled trial that included exercise and the IL-6 receptor antagonist tocilizumab, reduced visceral fat mass was observed in the exercise alone group but not in the group that exercised and received tocilizumab.¹²³ Cumulatively, these studies show the important acute role IL-6 has in prevention of adiposity. The chronically increased levels of IL-6 seen in individuals with obesity may reflect a shift in whole body preference to fatty acid metabolism, resulting in glucose sparing. Glucose is stored in the form of glycogen and is primarily found in skeletal muscle but is also found abundantly in the liver. Thus, changes in metabolic signaling may cause insulin resistance and NAFLD, two diseases commonly present in obesity.

TNF-α is a proinflammatory cytokine that can activate nuclear factor-kappa B (NF-kB) and may lead to insulin resistance.¹²⁴ NF-kB is negatively correlated with lipoprotein lipase activity, which can lead to an accumulation of triglycerides.¹²⁵ Peroxisome proliferator activated receptors (PPARs) are a set of nuclear receptors that can exert anti-inflammatory effects. Remels and others showed that PPAR activation, specifically the subtype PPARγ, can suppress cytokine induced NF-kB activity in skeletal muscle.¹²⁶ Anti-TNF-α-drugs (eg infliximab, etanercept) are currently used to treat inflammatory diseases such as Crohn’s Disease, rheumatoid arthritis and plaque psoriasis. Initial results from the use of these drugs to treat insulin resistance in obesity have been mixed. Following 32 weeks of infliximab treatment, insulin sensitivity did not improve in obese men.¹²⁷ Likewise, four weeks of etanercept treatment did not affect insulin sensitivity in obese individuals.¹²⁸ However, when administered to participants with obesity for six months, etanercept improved fasting glucose levels compared to placebo.¹²⁹

Microbiota Shift

The discovery of Helicobacter pylori as a cause of stomach ulcers ushered a new focus on the role of endogenous microbes in disease.¹³⁰ This new perspective led to efforts to identify all microbes that colonize the human body. Bacteroidetes constitute the most abundant bacteria in the human gut. While their relationship with humans is viewed as symbiotic, microbiota can also produce harmful products such as neurotoxins and immunotoxins. Nondigestible carbohydrates ingested by humans can be used by microbiota via fermentation, resulting in beneficial byproducts such as vitamins (vitamin K, vitamin B components) and short chain fatty acids (ie acetate, butyrate and propionate).^131,132 Short chain fatty acids can be used as an energy source but also play a major role in regulating immune cells such as macrophages.¹³³ Although one recent study reported that obese adults have more Firmicutes and fewer Bacteroidetes than normal-weight and lean adults,¹³⁴ another study reported no such difference.¹³⁵ To the best our knowledge no studies have explored the relative time course of microbiota shift and development of obesity.

Metformin is commonly prescribed to individuals with T2D because it lowers hepatic glucose production and decreases intestinal glucose absorption. Recent research suggests that some of the effects of Metformin may result from its ability to alter the gut microbiota of patients with T2D.¹³⁶ Transplantation of human gut microbiota from obese individuals to germ free mice was reported to induce vascular dysfunction and impair glucose tolerance compared to germ free mice transplanted with gut microbiota from a lean individual.¹³⁷ This study aligns with the microbiota shift hypothesis and the relative differences in Firmicutes and Bacteroidetes in individuals with obesity compared to lean individuals. Vrieze et al completed a hyperinsulinemic-euglycemic clamp before and after six weeks of fecal microbiota transplantation from a lean donor and found that insulin sensitivity was improved by the procedure in metabolically impaired individuals.¹³⁸ While the same group observed similar findings in a different study, the effects were no longer present at 18 weeks.¹³⁹

The production of short chain fatty acids may improve glucose metabolism via glucagon-like peptide 1 (GLP-1).¹⁴⁰ GLP-1 can increase insulin levels and can to increase glucose disposal through an insulin-independent mechanism.¹⁴¹ This may explain why early life obesity is a risk factor for neurodegeneration while late life obesity can be protective. Long-term effects of early life obesity on the pancreas results in beta cell failure, decreased insulin secretion, and metabolic dysfunction. Pancreatic function is likely intact in individuals who increase adiposity later in life. When these insulin-sensitive individuals experience dysbiosis, the production of short chain fatty acids leads to synthesis of GLP-1 and their body is still sensitive to insulin-dependent pathways.

The short chain fatty acids act on two G-protein coupled receptors, FFAR2 and FFAR3, that bind GLP-1 and peptide YY (PYY), respectively.¹⁴² Our group has reported that individuals diagnosed with AD have a greater early response to GLP-1 and PYY during a mixed-meal test. Further analysis revealed that PYY was associated with decreased brain volume in the cognitively healthy group but not in the AD group. The elevated metabolic response may be elicited to compensate for reduced receptor density in the brain.¹⁴³

Oxidative Stress

Oxidative stress is elevated in obesity.⁴² Oxidative stress is a condition where the production of reactive oxygen species (ROS) outweighs the body’s ability to detoxify these products.¹⁴⁴ While ROS play a physiological role in metabolic signaling,¹⁴⁵ they can also cause damage to lipids, proteins and DNA.¹⁴⁶ One major source of ROS production is through oxidative metabolism in mitochondria. During oxidative phosphorylation electrons interact with oxygen and produce ROS such as superoxide, mostly at complex I and III.¹⁴⁷ The overproduction of ROS has been shown to cause cellular damage which can lead to mitochondrial dysfunction.¹⁴⁸ While the etiology remains unclear, PD and AD are both associated with mitochondrial dysfunction, which may result from oxidative stress.^149,150

Endothelial cell vascular tone is regulated by the release of nitric oxide (NO).¹⁵¹ NO can also act as an antioxidant by reacting with superoxide to form peroxynitrite.¹⁵² ROS can uncouple endothelial nitric oxide synthase, thus lowering NO bioavailability which may further contribute to ROS production.¹⁵³ In addition, cytokines associated with insulin resistance (ie IL-6 and TNF-α) can compromise NO bioavailability and cause endothelial dysfunction.¹⁵⁴ Reduced NO disrupts endothelial-dependent vasodilation, leading to cardiovascular diseases such as atherosclerosis.¹⁵⁵ Venturelli et al reported lower NO bioavailability and peripheral circulation in the aging population with further reductions seen in AD.¹⁵⁶

ROS can damage oligodendrocytes and lead to myelin loss in the CNS.¹⁵⁷ The degradation of gray matter volume, specifically in the hippocampus in AD and substantia nigra in PD, is a hallmark feature. However, white matter abnormalities are also associated with AD and PD and may even precede changes seen in gray matter.^158,159 Recent studies have used magnetic resonance imaging to quantify myelin water fraction to provide a surrogate measure of myelin content. Obesity¹⁶⁰ and common comorbidities such as hypertension¹⁶¹ and metabolic syndrome¹⁶² have been associated with lower myelin content in the brain. Together, these findings suggest that obesity-related ROS production can disrupt endothelial cell function and decrease white matter integrity. Further research is needed to determine interactions between endothelial and mitochondrial dysfunction and their effects on neurodegenerative diseases.

Emerging Links Between Obesity and Neurodegenerative Diseases

Introduction to Risk Factors for AD and PD

We have discussed the links between obesity and neurodegeneration so far. In both AD and PD, overlapping risk factors such as age,¹⁶³ T2D,^164,165 and depression^166,167 have been observed. Insulin resistance can play a role, both directly and indirectly, as highlighted throughout the review. However, the complexity of these diseases extends beyond insulin resistance. Understanding these links and risk factors should pave the way for optimal preventative and therapeutic treatments. Although they share some risk factors, neurodegenerative diseases such as AD and PD also have specific risk factors. A major risk factor for AD is the apolipoprotein Epsilon-4 allele (APOE4).¹⁶⁸ Apolipoprotein E (apoE) is a protein that mediates lipid transport and is known for regulating CNS lipid metabolism,¹⁶⁹ and APOE4 carriers have been shown to express lower levels of apoE.¹⁷⁰ In APOE4 carriers, APOE promotes Aβ production and reduces clearance.¹⁷¹ In addition, the APOE4 allele is associated with lower cerebral myelin content in otherwise healthy older individuals.¹⁷² APOE2 carriers, who have a lower risk for AD, exhibited significantly greater cerebral myelin. For PD, family history, dyspepsia, and exposure to toxins (ie pesticides, oils and metals) have been shown to be a risk factors.¹⁷³ Interestingly, α-synuclein has been linked to demyelination in multisystem atrophy, a rare form of parkinsonism.¹⁷⁴ The Lewy bodies that are found in PD substantia nigra express α-synuclein¹⁷⁵ and mutations in α-synuclein were the first form of familial PD discovered.¹⁷⁶ Because the α-synuclein histopathology differs between multisystem atrophy and PD¹⁷⁷ disease mechanisms likely also differ for this protein. It is possible that multiple influences from genetic and lifestyle factors to myelin content may link risk for AD, PD, and potentially other neurodegenerative diseases. Further research is needed to determine these temporal and functional relationships.

Obesity and Alzheimer’s Disease

As relationships between obesity and brain health have become apparent, preclinical studies support a link between obesity and AD.^178–180 With few exceptions, these studies report that diet-induced obesity worsens cognitive performance and increases AD-like peripheral biomarkers and histological makers in the brain. Early studies hypothesized a primary role for altered cholesterol metabolism in AD. These studies reported greater cortical and hippocampal Aβ accumulation in rabbits and transgenic mice (PSAPP model of AD) fed high cholesterol or high fat/high cholesterol diets.^181,182 These findings were extended to memory deficits and markers of diminished cortical and hippocampal cholinergic function in non-transgenic rodents fed a high cholesterol or high fat/high cholesterol diet.^183,184 Using Tg2576 mice, Ho et al found that the spatial memory deficits and Aβ pathology present in this model of AD are exacerbated following the onset of high-fat diet-induced insulin resistance.¹⁸⁵ The lack of elevated cholesterol in the insulin-resistant mice led the group to conclude that impaired insulin signaling is a key mechanism linking diet-induced obesity and AD. Similar effects following streptozotocin (STZ)-induced insulin depletion in the APP/PS1 transgenic mouse model of AD support this conclusion.¹⁸⁶

Recently, the Hascup lab focused on the effects of a high fat diet on extracellular glutamate dynamics and phenotypic markers in the AβPP/PS1 mouse model of AD.¹⁸⁷ Using enzyme-coated multisite electrode arrays, the group reported that a high fat diet exacerbated cognitive impairment and further elevated basal extracellular levels and stimulus-evoked glutamate release in the hippocampus of AβPP/PS1 mice. The insulin-resistant, high fat-fed AβPP/PS1 exhibited greater vesicular glutamate 1 transporter and glial fibrillary acidic protein density in the hippocampal regions where glutamate dynamics were affected.

As mentioned previously, elevated cytokines can activate NF-KB. Studies have shown that inhibition of NF-KB can improve insulin resistance, suggesting its importance in the development of inflammation-induced insulin resistance.^188,189 In the CNS, reactive microglia are associated with neuroinflammation and tauopathy and may be a result of activated NF-KB. Microglial NF-KB signaling has been shown to drive tauopathy in PS19 mice.¹⁹⁰ Sandhu et al recently reported that friedelin, a molecule with antioxidant and anti-inflammatory properties, reversed scopolamine-induced memory dysfunction. In addition to its anticholinergic properties, scopolamine is known to activate neuroinflammatory markers such as NF-KB. Friedelin reduced NF-KB in this study.¹⁹¹

There is growing evidence that midlife obesity is a risk factor for AD and dementia, but that this relationship does not hold in late life.^192–194 It is unclear the degree to which this is modulated by survival bias, as excess body weight and obesity have been linked to premature mortality.¹⁹⁵ In addition, other factors such as changes in substrate metabolism throughout the body, and tissue-specific changes, such as loss of lean mass may contribute. Finally, there is evidence that BMI instability is related to neuropathological markers of AD and related dementias, suggesting that cycles of weight loss and regain may also be a contributing factor.¹⁹⁶ In midlife, it has also been observed that individuals with elevated amyloid in addition to hypertension or obesity experienced faster cognitive decline compared to individuals with elevated amyloid or cardiovascular risk factors alone.¹⁹⁷

A meta-analysis of whole brain studies showed that individuals with obesity have abnormalities in gray matter volume.¹⁹⁸ White matter is also reduced in individuals with elevated BMI.^199,200 These alterations in brain structure can predispose an individual to neurodegenerative diseases such as PD and AD, and potentially contribute to peripheral neurodegeneration as seen in multiple sclerosis (MS) and diabetic neuropathy.

Women are at a greater risk of developing AD compared to men, regardless of their APOE allele.²⁰¹ Gustafson et al, conducted a study to measure anthropometrics, neuropsychiatric assessment, and brain atrophy with computerized tomography (CT) and repeated measurements after 24 years. This study found that obesity may contribute to temporal atrophy in women.²⁰² It is important to understand the association between early adulthood obesity and menopausal symptoms to possibly identify why women are at a greater risk of developing AD. The onset of menopause tends to occur at a later age in obese women.²⁰³ Studies have reported that perimenopausal and postmenopausal women experience greater changes in brain volume. One study reported that perimenopausal women have greater reductions in grey matter volume.²⁰⁴ Similarly, perimenopausal and postmenopausal women have greater reductions in hippocampal volume compared to premenopausal women.²⁰⁵ However, Franz et al have reported similar results in men after following them for 40 years.²⁰⁶ While this relationship has been shown for decades, the mechanism remains unclear.

More recently, metabolic, and cerebrovascular dysfunction have been shown to be potential mediators that link obesity to cognitive decline.²⁰⁷ An additional molecule of interest in obesity is leptin. Leptin is a hormone that is released from adipose tissue that regulates energy balance by inhibiting hunger. Leptin has been reported to be strongly correlated to BMI.^208,209 Both changes in leptin levels and alterations in leptin signaling may be relevant to the link between obesity and brain health. Leptin can cross the blood-brain barrier.²¹⁰ In addition to its pro-satiety effect, leptin also has a role in hippocampal neurogenesis.²¹¹ Narita et al reported a positive relationship between plasma leptin levels and gray matter volume in the right hippocampus in elderly individuals free from metabolic syndrome and dementia.²¹² Genetic mutations in leptin receptors and defects in the pathway that synthesize leptin can occur in obesity resulting in “leptin resistance”.²¹³ While the mechanism is unclear, the impaired signaling of leptin may lead to structural changes in the hippocampus. Witte et al reported individuals with mild cognitive impairment have lower serum leptin levels compared to healthy controls. While no association between leptin and memory performance was observed, higher leptin levels did correlate with larger right hippocampus volume.²¹⁴

Obesity and Parkinson’s Disease

The motor symptoms of PD result from degeneration of dopamine neurons that project from the midbrain substantia nigra to the caudate nucleus and putamen (collectively, striatum) in the forebrain. Clinical diagnosis usually occurs with the onset of motor symptoms, which emerge only after substantial nigrostriatal dopamine loss. In fact, the preclinical phase of PD (which is often accompanied by autonomic and affective dysfunction) can last more than 20 years.²¹⁵ Although many contributing factors have been linked to PD, we will focus on obesity-related factors in the following section.

Evidence supporting a relationship between peripheral glucose dysregulation and nigrostriatal dopamine function initially came from studies using streptozotocin (STZ) to destroy pancreas insulin-producing beta cells in a rat model of Type 1 diabetes.²¹⁶ These studies report lower midbrain and striatal tissue dopamine content²¹⁷ and lower measures of dopamine turnover in the striatum in STZ-treated rats.²¹⁸ The dopamine turnover measure correlated with blood glucose levels in the latter study. Unlike Type 1 diabetes, obesity is accompanied by both hyperglycemia and hyperinsulinemia prior to the onset of insulin resistance and eventual T2D. Dopamine signaling is affected not only by DA content and release, but also by postsynaptic DA receptors, where the intercellular signal is propagated, and presynaptic DA transporters, where DA is taken up for recycling and to terminate the signal. Evidence from in vitro and in vivo studies report that insulin can affect both postsynaptic DA receptor and presynaptic DA transporter expression and function.^219,220

Preclinical studies using the MPTP and 6-hydroxydopamine (6-OHDA) neurotoxin models of PD report enhanced neurotoxicity in rodent models of diet-induced obesity. In 2005, Choi et al reported that mice fed a high-fat diet for 8 weeks exhibited greater striatal DA depletion and lower TH levels in the substantia nigra following a low dose of MPTP in mice.²²¹ We extended this study in 2010 to the 6-OHDA rat model and reported greater striatal DA depletion in high fat-fed than chow-fed animals.²²² The high fat-fed rats in our 6-OHDA study exhibited hyperglycemia and hyperinsulinemia, and DA depletion in the striatum and the substantia nigra correlated significantly with HOMA-IR values and epididymal fat mass. Preclinical studies conducted by others using these toxin models have replicated and extended these findings.^223,224

Preclinical studies also reveal that obesogenic diets facilitate disease processes in mice harboring PD-related α-synuclein mutations. In a study using A53T mice, a high calorie diet exacerbated autonomic dysfunction that occurs in early disease stage in these animals.²²⁵ This effect, which was manifested as an elevated resting heart rate, was ameliorated by intermittent energy restriction. These findings were extended to motor decline and mortality in the A30P α-synuclein mouse model of PD. When fed a high-fat diet, these mice became insulin-resistant and exhibited earlier motor decline and death than their standard chow-fed counterparts.²²⁶ Histology revealed greater α-synuclein aggregation in the brainstem of the obese mice.

To explore obesity-related mechanisms that might occur during a preclinical period in PD, we tested the effects of a high fat diet on DA release dynamics in non-lesioned, young adult rats. We reported that after a 12-week high-fat diet, insulin-resistant young adult rats exhibited significantly blunted DA release in the striatum compared to insulin-sensitive rats fed normal chow.²²⁷ The amplitude of DA released was significantly negatively correlated with the HOMA-IR measurement of insulin resistance. Extracellular DA clearance was also prolonged in this group. Despite being 7-months-old, their DA release and clearance dynamics resembled those measured previously in senescent 24-month-old rats.²²⁸ Iron content was greater in the high fat group and proteins related to iron metabolism differed significantly between the two diet groups. Iron content in the substantia nigra iron increases with aging and with PD, where it is involved in generating highly reactive free radical species and promotes DA auto-oxidation.²²⁹

We followed this study with one to determine whether adopting a “healthier” diet reverses neural vulnerability following a high-fat diet.²³⁰ After feeding two groups of rats a high-fat diet for 3 months, we switched one of the groups to normal chow while the other group continued with the high-fat diet. We included a control group that was fed normal chow throughout the study. Although systemic insulin resistance and protein markers of mitochondrial and proteasomal dysfunction in the striatum were lower in the group that was switched to normal chow, nigrostriatal DA depletion was similar between the two high-fat diet groups.

PD is the second most common neurodegenerative disorder with an incidence rate of every 17 per 100,000 individuals per year.²³¹ Similar to AD, increasing age is positively correlated to PD incidence. However, unique to PD is the high prevalence and incidence of PD in areas where herbicides and pesticides are commonly used.²³² The association between pesticide use and PD has been confirmed in population-based control studies.²³³ Pesticides are believed to promote oxidative stress which can lead to mitochondrial dysfunction, thus paralleling the findings previously mentioned in preclinical studies.

Emerging Directions for Interventions

There are no cures for AD and PD and current treatments are limited to symptom management. Drugs like donepezil and levodopa can respectively enhance acetylcholine and dopamine function, but both lose efficacy with disease progression. Likewise, deep brain stimulation in PD can improve symptoms but does not alter disease course. Newly developed monoclonal antibodies, such as lecanemab do exist and may show a potential option for treatment of AD, they come with a steep annual cost that will place barriers on who can receive treatment. Therefore, the focus of this review will be on nonpharmacological interventions.

Dietary Intervention

Given the link between metabolic dysfunction in obesity and neurodegeneration, dietary interventions are a logical approach. In a mouse model of pre-diabetes, alternate day fasting attenuated ROS production and reduced peripheral nerve damage.²³⁴ Clinical studies in aging volunteers report salutary effects of long-term dietary interventions on brain health.^235,236 In older adults free from metabolic disorder and memory impairments, participants assigned to a 30% reduced calorie diet for 3 months exhibited improved memory scores compared to the control diet group.²³⁷ Similarly, calorically restricted postmenopausal with obesity exhibited improved memory function as well as increased gray matter volume in the inferior frontal gyrus and hippocampus as well as enhanced functional connectivity in the hippocampus compared to a control group.²³⁸

A ketogenic diet essentially eliminates carbohydrates (<20g/day) while increasing caloric intake from fat and protein. With general fasting or a ketogenic diet, ketones such as beta-hydroxybutyrate are produced by the liver and are used as an alternative fuel source.²³⁹ In a single-phase, assessor-blinded, two-period randomized crossover trial, participants diagnosed with AD (n=26) were randomized into a ketogenic diet (29% protein, 6% carbohydrates and 58% fat) or a low fat diet (19% protein, 62% carbohydrates and 11% fat) for 12 weeks. After a 10-week washout period, participants completed the alternate diet for an additional 12 weeks. Although cognitive function was not affected by diet, activities of daily living and quality of life were significantly improved by the ketogenic diet. The ketogenic diet also resulted in greater weight loss and resulted in mostly favorable effects on cardiovascular risk factors.²⁴⁰ In a double-blinded placebo-controlled study, participants diagnosed with AD (n=20) ingested a ketogenic formula after an overnight fast. Initial cognitive performance was not affected by the ketogenic supplement despite elevated circulating ketones²⁴¹ Repeated testing in participants in the ketogenic group revealed improved performance in immediate and delayed memory tasks at week 8 compared to baseline. In a recent randomized controlled trial (n=47), participants diagnosed with PD underwent ketogenic or low fat diet intervention for 8 weeks.²⁴² Although motor and nonmotor symptoms were improved in both diet groups, the ketogenic urinary problems, pain, fatigue, daytime sleepiness, and cognitive impairment were lower in the ketogenic group.

Exercise

Exercise can improve cardiovascular health and metabolic function and can increase neuroplasticity.^243–245 It has become evident that things that benefit the heart also benefit the brain. Guidelines from the American Academy of Sports Medicine recommend at least 150 minutes of moderate-intensity aerobic activity or 75 minutes of vigorous-intensity aerobic activity, and at least two days of resistance exercise each week.²⁴⁶ Goodpaster et al reported lower muscle glycogen oxidation during exercise in individuals with obesity compared to their lean counterparts.²⁴⁷ This suggests that exercise protocols should be customized based on individual metabolic profiles rather than general guidelines. In a pilot study, we tested the effects of 150 minutes aerobic exercise in individuals who were at least 55 years old, sedentary, and diagnosed with probable AD or MCI. After 26 weeks the exercise group showed improved memory performance and reduced hippocampal atrophy compared to the stretching and toning control group.²⁴⁸ Individuals with neurodegenerative disease are likely to be physically inactive due to changes in coordination, fatigue, and mood. In these populations, exercise is accompanied by risk of injury. A meta-analysis of exercise interventions in patients with chronic brain disorders, (such as PD, MS and AD) addressed the safety of exercising these populations. The meta-analysis found that that 83.3% of the studies reported no effect of physical injuries on completion of the exercise intervention.²⁴⁹ Exercise decreased symptoms of depressive symptoms and had a positive effect on cognition.²⁴⁹ It should be noted that the intensity of exercise was classified as “high” in only 18 of the 122 studies included in the meta-analysis. A randomized control trial tested the feasibility of exercising individuals with PD at various intensities, with target heart rates at 60–65% of maximum heart rate in the moderate intensity group and 80–85% maximum in the high intensity group. Participants in both exercise groups were able to meet their exercise intensity 4 times a week for 6 months.²⁵⁰

A recent study reported that exercise influences gut microbiota in obesity. In a group of insulin resistant individuals with an average BMI of 29.3, two weeks of aerobic exercise training reduced levels TNF-α and decreased the Firmicute/Bacteroidetes ratio by increasing the level of Bacteroidetes. While exercise had no effect on intestinal glucose uptake, HbA1c and body fat percentage were decreased in both exercise groups.²⁵¹ While this study demonstrates that exercise-mediated improvement in glucose uptake and body fat are accompanied by alterations in gut microbiota, follow up studies with these participants are necessary to link these effects to neurological outcomes.

Brain-derived neurotrophic factor (BDNF) plays an important role in neurogenesis, synaptic plasticity, and memory function.²⁵² A recent study reported that 12 weeks of probiotic supplements increased circulating BDNF levels, improved mental flexibility, and decreased stress in older adults.²⁵³ BDNF is increased by exercise and may contribute to learning and memory due to its expression in the hippocampus.²⁵⁴ In C57BL/6 mice, exercise reversed memory impairments and attenuated chronic stress-induced BDNF expression. These effects were diminished when the mice were injected with the AMPK inhibitor compound C. This suggests that exercise may protect against stress induced memory impairments by upregulating hippocampal AMPK-mediated BDNF induction.²⁵⁵ In a recent study of physically inactive but cognitively healthy middle-aged adults at risk for AD (eg family history, APOE4), participants were randomly assigned to an exercise group or usual activity group. Although the chronic (26 weeks) exercise protocol did not affect BDNF, the myokine Cathepsin B was elevated with exercise and correlated with cognitive function. BDNF did correlate with metabolites however, suggesting a role for role for metabolic factors in BDNF regulation.²⁵⁶ Further analysis of metabolomics did show close correlation to BDNF.

Sleep

As mentioned earlier, sleep is a modifiable risk factor for obesity. Lack of sleep can reduce endogenous antioxidant production, leading to activation of cytokines.²⁵⁷ Obesity is associated with a greater risk for sleep disorders such as insomnia, sleep apnea, and restless leg syndrome.²⁵⁸ Sleep deprivation has been shown to increase AB production overnight in humans.²⁵⁹ Although the immediate negative effects of sleep deprivation on cognitive function are well known, the consequences of long-term sleep deprivation remain unknown.^260–262 In the 3xTgAD mouse model of AD, sleep restriction for 6 weeks worsened memory loss and resulted in greater Aβ and pTau accumulation in the cortex compared to controls.²⁶³ Recent research has shown that improving sleep duration and quality results in decreased appetite and greater loss of fat mass in overweight participants.²⁶⁴ These results occurred by extending sleep duration by ~1.2 hours.

Conclusions

Taken together, these studies suggest that through various mechanisms, obesity and its sequelae can impair CNS cellular function and lower the threshold for neuropathology or degeneration that accompany symptoms of neurodegenerative diseases such as AD and PD. Obesity is a complex disease influenced by numerous factors. These include energy expenditure, mitochondrial dysfunction, insulin resistance, adipose tissue accumulation, skeletal muscle alterations, liver involvement, gut microbiota dysregulation, inflammation, and oxidative stress. These factors contribute to metabolic dysfunction and increase the risk of developing chronic diseases, including neurodegenerative conditions such as AD and PD.

We are just beginning to understand the significant connection between metabolic dysfunction and neurodegeneration. Targeted dietary interventions, along with exercise, offer promising avenues for managing obesity-related cognitive, motor, and affective symptoms in neurodegenerative diseases. Future research into these mechanisms will afford opportunities to not only optimize population-based guidelines, but to also implement personalized strategies to combat the negative impact of obesity on brain health.

Funding

Supported by R01 AG062548 and R01 AG081304.

Disclosure

The authors report no conflicts of interest in this work.

References

1. Garnett SP, Baur LA, Jones AM, Hardy LL. Trends in the prevalence of morbid and severe obesity in Australian children aged 7-15 years, 1985–2012. PLoS One. 2016;11:e0154879. doi:10.1371/journal.pone.0154879

2. Beam A, Clinger E, Hao L. Effect of diet and dietary components on the composition of the Gut microbiota. Nutrients. 2021;13:2795.

3. Armstrong DB, Dublin LI, Wheatley GM, Marks HH. Obesity and its relation to health and disease. J Am Med Assoc. 1951;147:1007–1014. doi:10.1001/jama.1951.03670280009003

4. WHO. Facts about overweight and obesity [online]. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight#:~:text=Of%20these%20over%20650%20million,overweight%20or%20obese%20in%202020. Accessed December 23, 2023.

5. Maes HH, Neale MC, Eaves LJ. Genetic and environmental factors in relative body weight and human adiposity. Behav Genet. 1997;27:325–351. doi:10.1023/A:1025635913927

6. Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206. doi:10.1038/nature14177

7. Anekwe CV, Jarrell AR, Townsend MJ, Gaudier GI, Hiserodt JM, Stanford FC. Socioeconomics of Obesity. Curr Obes Rep. 2020;9:272–279. doi:10.1007/s13679-020-00398-7

8. Hruby A, Hu FB. The epidemiology of obesity: a big picture. Pharmacoeconomics. 2015;33:673–689. doi:10.1007/s40273-014-0243-x

9. Kwarteng JL, Schulz AJ, Mentz GB, Israel BA, Perkins DW. Independent effects of neighborhood poverty and psychosocial stress on obesity over time. J Urban Health. 2017;94:791–802. doi:10.1007/s11524-017-0193-7

10. Donnelly JE, Honas JJ, Smith BK, et al. Aerobic exercise alone results in clinically significant weight loss for men and women: midwest exercise trial 2. Obesity (Silver Spring). 2013;21:E219–228. doi:10.1002/oby.20145

11. Ross R, Dagnone D, Jones PJ, et al. Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. A randomized, controlled trial. Ann Intern Med. 2000;133:92–103. doi:10.7326/0003-4819-133-2-200007180-00008

12. Swift DL, Johannsen NM, Lavie CJ, Earnest CP, Blair SN, Church TS. Effects of clinically significant weight loss with exercise training on insulin resistance and cardiometabolic adaptations. Obesity (Silver Spring). 2016;24:812–819. doi:10.1002/oby.21404

13. Donnelly JE, Blair SN, Jakicic JM, et al. American College of Sports Medicine Position Stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc. 2009;41:459–471. doi:10.1249/MSS.0b013e3181949333

14. Flechtner-Mors M, Ditschuneit HH, Johnson TD, Suchard MA, Adler G. Metabolic and weight loss effects of long-term dietary intervention in obese patients: four-year results. Obes Res. 2000;8:399–402. doi:10.1038/oby.2000.48

15. Foster-Schubert KE, Alfano CM, Duggan CR, et al. Effect of diet and exercise, alone or combined, on weight and body composition in overweight-to-obese postmenopausal women. Obesity (Silver Spring). 2012;20:1628–1638. doi:10.1038/oby.2011.76

16. Johns DJ, Hartmann-Boyce J, Jebb SA, Aveyard P; Behavioural Weight Management Review G. Diet or exercise interventions vs combined behavioral weight management programs: a systematic review and meta-analysis of direct comparisons. J Acad Nutr Diet. 2014;114:1557–1568. doi:10.1016/j.jand.2014.07.005

17. Messier SP, Mihalko SL, Legault C, et al. Effects of intensive diet and exercise on knee joint loads, inflammation, and clinical outcomes among overweight and obese adults with knee osteoarthritis: the IDEA randomized clinical trial. JAMA. 2013;310:1263–1273. doi:10.1001/jama.2013.277669

18. Capers PL, Fobian AD, Kaiser KA, Borah R, Allison DB. A systematic review and meta-analysis of randomized controlled trials of the impact of sleep duration on adiposity and components of energy balance. Obes Rev. 2015;16:771–782. doi:10.1111/obr.12296

19. Sperry SD, Scully ID, Gramzow RH, Jorgensen RS. Sleep duration and waist circumference in adults: a meta-analysis. Sleep. 2015;38:1269–1276. doi:10.5665/sleep.4906

20. Wu Y, Zhai L, Zhang D. Sleep duration and obesity among adults: a meta-analysis of prospective studies. Sleep Med. 2014;15:1456–1462. doi:10.1016/j.sleep.2014.07.018

21. Ahern T, O’Malley E, Dunlevy C, et al. Sleep duration and physical function in people with severe obesity: a prospective cross-sectional study. Ir J Med Sci. 2020;189:517–523. doi:10.1007/s11845-019-02110-8

22. Jike M, Itani O, Watanabe N, Buysse DJ, Kaneita Y. Long sleep duration and health outcomes: a systematic review, meta-analysis and meta-regression. Sleep Med Rev. 2018;39:25–36. doi:10.1016/j.smrv.2017.06.011

23. Messerli FH, Ventura HO, Reisin E, et al. Borderline hypertension and obesity: two prehypertensive states with elevated cardiac output. Circulation. 1982;66:55–60. doi:10.1161/01.CIR.66.1.55

24. Alpert MA. Obesity cardiomyopathy: pathophysiology and evolution of the clinical syndrome. Am J Med Sci. 2001;321:225–236. doi:10.1097/00000441-200104000-00003

25. Lavie CJ, Milani RV. Obesity and cardiovascular disease: the Hippocrates paradox? J Am Coll Cardiol. 2003;42:677–679. doi:10.1016/S0735-1097(03)00784-8

26. Park YM, Sui X, Liu J, et al. The effect of cardiorespiratory fitness on age-related lipids and lipoproteins. J Am Coll Cardiol. 2015;65:2091–2100. doi:10.1016/j.jacc.2015.03.517

27. Parto P, Lavie CJ, Arena R, Bond S, Popovic D, Ventura HO. Body habitus in heart failure: understanding the mechanisms and clinical significance of the obesity paradox. Future Cardiol. 2016;12:639–653. doi:10.2217/fca-2016-0029

28. Dart AM, Chin-Dusting JP. Lipids and the endothelium. Cardiovasc Res. 1999;43:308–322. doi:10.1016/S0008-6363(99)00150-9

29. Chiu JJ, Usami S, Chien S. Vascular endothelial responses to altered shear stress: pathologic implications for atherosclerosis. Ann Med. 2009;41:19–28. doi:10.1080/07853890802186921

30. Glass CK, Witztum JL. Atherosclerosis. the road ahead. Cell. 2001;104:503–516. doi:10.1016/S0092-8674(01)00238-0

31. Silverman JF, O’Brien KF, Long S, et al. Liver pathology in morbidly obese patients with and without diabetes. Am J Gastroenterol. 1990;85:1349–1355.

32. Williams CD, Stengel J, Asike MI, et al. Prevalence of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among a largely middle-aged population utilizing ultrasound and liver biopsy: a prospective study. Gastroenterology. 2011;140:124–131. doi:10.1053/j.gastro.2010.09.038

33. Zhu Y, Sidell MA, Arterburn D, et al. Racial/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U.S. Diabetes Care. 2019;42:2211–2219. doi:10.2337/dc19-0532

34. Rachdaoui N. Insulin: the friend and the Foe in the development of type 2 diabetes mellitus. Int J Mol Sci. 2020;21. doi:10.3390/ijms22010021

35. Verdile G, Keane KN, Cruzat VF, et al. Inflammation and oxidative stress: the molecular connectivity between insulin resistance, obesity, and Alzheimer’s disease. Mediators Inflamm. 2015;2015:105828. doi:10.1155/2015/105828

36. Morris JK, Burns JM. Insulin: an emerging treatment for Alzheimer’s disease dementia? Curr Neurol Neurosci Rep. 2012;12:520–527. doi:10.1007/s11910-012-0297-0

37. Kellar D, Craft S. Brain insulin resistance in Alzheimer’s disease and related disorders: mechanisms and therapeutic approaches. Lancet Neurol. 2020;19:758–766. doi:10.1016/S1474-4422(20)30231-3

38. Heydenreich J, Kayser B, Schutz Y, Melzer K. Total energy expenditure, energy intake, and body composition in endurance athletes across the training season: a systematic review. Sports Med Open. 2017;3:8. doi:10.1186/s40798-017-0076-1

39. Cerf ME. Beta cell dysfunction and insulin resistance. Front Endocrinol (Lausanne). 2013;4:37. doi:10.3389/fendo.2013.00037

40. Petersen MC, Shulman GI. Mechanisms of Insulin Action and Insulin Resistance. Physiol Rev. 2018;98:2133–2223. doi:10.1152/physrev.00063.2017

41. Goossens GH. The role of adipose tissue dysfunction in the pathogenesis of obesity-related insulin resistance. Physiol Behav. 2008;94:206–218. doi:10.1016/j.physbeh.2007.10.010

42. Fox CS, Massaro JM, Hoffmann U, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation. 2007;116:39–48. doi:10.1161/CIRCULATIONAHA.106.675355

43. Taksali SE, Caprio S, Dziura J, et al. High visceral and low abdominal subcutaneous fat stores in the obese adolescent: a determinant of an adverse metabolic phenotype. Diabetes. 2008;57:367–371. doi:10.2337/db07-0932

44. Liu J, Fox CS, Hickson DA, et al. Impact of abdominal visceral and subcutaneous adipose tissue on cardiometabolic risk factors: the Jackson Heart Study. J Clin Endocrinol Metab. 2010;95:5419–5426. doi:10.1210/jc.2010-1378

45. Rosenwald M, Wolfrum C. The origin and definition of brite versus white and classical brown adipocytes. Adipocyte. 2014;3:4–9. doi:10.4161/adip.26232

46. Heaton JM. The distribution of brown adipose tissue in the human. J Anat. 1972;112:35–39.

47. van Marken Lichtenbelt WD, Vanhommerig JW, Smulders NM, et al. Cold-activated brown adipose tissue in healthy men. N Engl J Med. 2009;360:1500–1508. doi:10.1056/NEJMoa0808718

48. Cheng L, Wang J, Dai H, et al. Brown and beige adipose tissue: a novel therapeutic strategy for obesity and type 2 diabetes mellitus. Adipocyte. 2021;10:48–65. doi:10.1080/21623945.2020.1870060

49. Jensen MD, Haymond MW, Rizza RA, Cryer PE, Miles JM. Influence of body fat distribution on free fatty acid metabolism in obesity. J Clin Invest. 1989;83:1168–1173. doi:10.1172/JCI113997

50. Boden G. Effects of free fatty acids (FFA) on glucose metabolism: significance for insulin resistance and type 2 diabetes. Exp Clin Endocrinol Diabetes. 2003;111:121–124. doi:10.1055/s-2003-39781

51. Manna P, Jain SK. Obesity, oxidative stress, adipose tissue dysfunction, and the associated health risks: causes and therapeutic strategies. Metab Syndr Relat Disord. 2015;13:423–444. doi:10.1089/met.2015.0095

52. Bakker SJ, IJzerman RG, Teerlink T, Westerhoff HV, Gans RO, Heine RJ. Cytosolic triglycerides and oxidative stress in central obesity: the missing link between excessive atherosclerosis, endothelial dysfunction, and beta-cell failure? Atherosclerosis. 2000;148:17–21. doi:10.1016/S0021-9150(99)00329-9

53. Frontera WR, Ochala J. Skeletal muscle: a brief review of structure and function. Calcif Tissue Int. 2015;96:183–195. doi:10.1007/s00223-014-9915-y

54. Slentz CA, Houmard JA, Kraus WE. Exercise, abdominal obesity, skeletal muscle, and metabolic risk: evidence for a dose response. Obesity (Silver Spring). 2009;17 Suppl 3:S27–33.

55. Essen B, Jansson E, Henriksson J, Taylor AW, Saltin B. Metabolic characteristics of fibre types in human skeletal muscle. Acta Physiol Scand. 1975;95:153–165. doi:10.1111/j.1748-1716.1975.tb10038.x

56. Sanchez B, Li J, Bragos R, Rutkove SB. Differentiation of the intracellular structure of slow- versus fast-twitch muscle fibers through evaluation of the dielectric properties of tissue. Phys Med Biol. 2014;59:2369–2380. doi:10.1088/0031-9155/59/10/2369

57. Sartori R, Romanello V, Sandri M. Mechanisms of muscle atrophy and hypertrophy: implications in health and disease. Nat Commun. 2021;12:330. doi:10.1038/s41467-020-20123-1

58. Tomlinson DJ, Erskine RM, Morse CI, Winwood K, Onambele-Pearson G. The impact of obesity on skeletal muscle strength and structure through adolescence to old age. Biogerontology. 2016;17:467–483. doi:10.1007/s10522-015-9626-4

59. Raghupathy R, McLean RR, Kiel DP, Hannan MT, Sahni S. Higher abdominal adiposity is associated with higher lean muscle mass but lower muscle quality in middle-aged and older men and women: the Framingham Heart Study. Aging Clin Exp Res. 2023;35(7):1477–1485. doi:10.1007/s40520-023-02427-6

60. Bohannon RW. Grip strength: an indispensable biomarker for older adults. Clin Interv Aging. 2019;14:1681–1691. doi:10.2147/CIA.S194543

61. Chang CY, Chu NF, Lin MH, et al. Association between grip strength, obesity, and cardiometabolic risk factors among the community-dwelling elderly population in Taiwan. Int J Environ Res Public Health. 2022;19:11359. doi:10.3390/ijerph191811359

62. Lee MR, Jung SM, Bang H, Kim HS, Kim YB. Association between muscle strength and type 2 diabetes mellitus in adults in Korea: data from the Korea national health and nutrition examination survey (KNHANES) VI. Medicine (Baltimore). 2018;97:e10984. doi:10.1097/MD.0000000000010984

63. Arosio B, Calvani R, Ferri E, et al. Sarcopenia and cognitive decline in older adults: targeting the muscle-brain axis. Nutrients. 2023;15:1853.

64. Lexell J, Taylor CC, Sjostrom M. What is the cause of the ageing atrophy? Total number, size and proportion of different fiber types studied in whole vastus lateralis muscle from 15- to 83-year-old men. J Neurol Sci. 1988;84:275–294. doi:10.1016/0022-510X(88)90132-3

65. Melton LJ 3rd, Khosla S, Crowson CS, O’Connor MK, O’Fallon WM, Riggs BL. Epidemiology of sarcopenia. J Am Geriatr Soc. 2000;48:625–630. doi:10.1111/j.1532-5415.2000.tb04719.x

66. Ji T, Li Y, Ma L. Sarcopenic obesity: an emerging public health problem. Aging Dis. 2022;13:379–388. doi:10.14336/AD.2021.1006

67. Liu C, Cheng KY, Tong X, et al. The role of obesity in sarcopenia and the optimal body composition to prevent against sarcopenia and obesity. Front Endocrinol (Lausanne). 2023;14:1077255. doi:10.3389/fendo.2023.1077255

68. Baumgartner RN. Body composition in healthy aging. Ann N Y Acad Sci. 2000;904:437–448. doi:10.1111/j.1749-6632.2000.tb06498.x

69. Nishikawa H, Asai A, Fukunishi S, Nishiguchi S, Higuchi K. Metabolic syndrome and Sarcopenia. Nutrients. 2021;13:3519. doi:10.3390/nu13103519

70. Talbot J, Maves L. Skeletal muscle fiber type: using insights from muscle developmental biology to dissect targets for susceptibility and resistance to muscle disease. Wiley Interdiscip Rev Dev Biol. 2016;5:518–534. doi:10.1002/wdev.230

71. Albers PH, Pedersen AJ, Birk JB, et al. Human muscle fiber type-specific insulin signaling: impact of obesity and type 2 diabetes. Diabetes. 2015;64:485–497. doi:10.2337/db14-0590

72. Dohm GL, Tapscott EB, Pories WJ, et al. An in vitro human muscle preparation suitable for metabolic studies. Decreased insulin stimulation of glucose transport in muscle from morbidly obese and diabetic subjects. J Clin Invest. 1988;82:486–494. doi:10.1172/JCI113622

73. Elton CW, Tapscott EB, Pories WJ, Dohm GL. Effect of moderate obesity on glucose transport in human muscle. Horm Metab Res. 1994;26:181–183. doi:10.1055/s-2007-1000807

74. Friedman JE, Caro JF, Pories WJ, Azevedo JL Jr, Dohm GL. Glucose metabolism in incubated human muscle: effect of obesity and non-insulin-dependent diabetes mellitus. Metabolism. 1994;43:1047–1054. doi:10.1016/0026-0495(94)90188-0

75. Tanner CJ, Barakat HA, Dohm GL, et al. Muscle fiber type is associated with obesity and weight loss. Am J Physiol Endocrinol Metab. 2002;282:E1191–1196. doi:10.1152/ajpendo.00416.2001

76. Akhmedov D, Berdeaux R. The effects of obesity on skeletal muscle regeneration. Front Physiol. 2013;4:371. doi:10.3389/fphys.2013.00371

77. Weyer C, Snitker S, Rising R, Bogardus C, Ravussin E. Determinants of energy expenditure and fuel utilization in man: effects of body composition, age, sex, ethnicity and glucose tolerance in 916 subjects. Int J Obes Relat Metab Disord. 1999;23:715–722. doi:10.1038/sj.ijo.0800910

78. Felber JP, Ferrannini E, Golay A, et al. Role of lipid oxidation in pathogenesis of insulin resistance of obesity and type II diabetes. Diabetes. 1987;36:1341–1350. doi:10.2337/diab.36.11.1341

79. Singh R, Cuervo AM. Autophagy in the cellular energetic balance. Cell Metab. 2011;13:495–504. doi:10.1016/j.cmet.2011.04.004

80. Yin F, Sancheti H, Patil I, Cadenas E. Energy metabolism and inflammation in brain aging and Alzheimer’s disease. Free Radic Biol Med. 2016;100:108–122. doi:10.1016/j.freeradbiomed.2016.04.200

81. Mirza MS. Obesity, visceral fat, and NAFLD: querying the role of adipokines in the progression of nonalcoholic fatty liver disease. ISRN Gastroenterol. 2011;2011:592404. doi:10.5402/2011/592404

82. Brown MS, Goldstein JL. Selective versus total insulin resistance: a pathogenic paradox. Cell Metab. 2008;7:95–96. doi:10.1016/j.cmet.2007.12.009

83. Mavrogiannaki AN, Migdalis IN. Nonalcoholic fatty liver disease, diabetes mellitus and cardiovascular disease: newer data. Int J Endocrinol. 2013;2013:450639. doi:10.1155/2013/450639

84. Monsour HP, Frenette CT, Wyne K. Fatty liver: a link to cardiovascular disease--its natural history, pathogenesis, and treatment. Methodist Debakey Cardiovasc J. 2012;8:21–25. doi:10.14797/mdcj-8-3-21

85. Asaoka Y, Terai S, Sakaida I, Nishina H. The expanding role of fish models in understanding non-alcoholic fatty liver disease. Dis Model Mech. 2013;6:905–914. doi:10.1242/dmm.011981

86. Luo Y, Lin H. Inflammation initiates a vicious cycle between obesity and nonalcoholic fatty liver disease. Immun Inflamm Dis. 2021;9:59–73. doi:10.1002/iid3.391

87. Miller AA, Spencer SJ. Obesity and neuroinflammation: a pathway to cognitive impairment. Brain Behav Immun. 2014;42:10–21. doi:10.1016/j.bbi.2014.04.001

88. Stanhope KL, Schwarz JM, Keim NL, et al. Consuming fructose-sweetened, not glucose-sweetened, beverages increases visceral adiposity and lipids and decreases insulin sensitivity in overweight/obese humans. J Clin Invest. 2009;119:1322–1334. doi:10.1172/JCI37385

89. Tappy L, Le KA. Metabolic effects of fructose and the worldwide increase in obesity. Physiol Rev. 2010;90:23–46. doi:10.1152/physrev.00019.2009

90. Softic S, Stanhope KL, Boucher J, et al. Fructose and hepatic insulin resistance. Crit Rev Clin Lab Sci. 2020;57:308–322. doi:10.1080/10408363.2019.1711360

91. Matsuura F, Yamashita S, Nakamura T, et al. Effect of visceral fat accumulation on uric acid metabolism in male obese subjects: visceral fat obesity is linked more closely to overproduction of uric acid than subcutaneous fat obesity. Metabolism. 1998;47:929–933. doi:10.1016/S0026-0495(98)90346-8

92. Sanchez-Lozada LG, Andres-Hernando A, Garcia-Arroyo FE, et al. Uric acid activates aldose reductase and the polyol pathway for endogenous fructose and fat production causing development of fatty liver in rats. J Biol Chem. 2019;294:4272–4281. doi:10.1074/jbc.RA118.006158

93. Parbo P, Ismail R, Hansen KV, et al. Brain inflammation accompanies amyloid in the majority of mild cognitive impairment cases due to Alzheimer’s disease. Brain. 2017;140:2002–2011. doi:10.1093/brain/awx120

94. Laurent C, Buee L, Blum D. Tau and neuroinflammation: what impact for Alzheimer’s disease and tauopathies? Biomed J. 2018;41:21–33. doi:10.1016/j.bj.2018.01.003

95. Song XM, Yu Q, Dong X, et al. Aldose reductase inhibitors attenuate beta-amyloid-induced TNF-alpha production in microlgia via ROS-PKC-mediated NF-kappaB and MAPK pathways. Int Immunopharmacol. 2017;50:30–37. doi:10.1016/j.intimp.2017.06.005

96. Yan J, Zheng K, Zhang X, Jiang Y. Fructose Consumption is associated with a higher risk of dementia and Alzheimer’s disease: a prospective cohort study. J Prev Alzheimers Dis. 2023;10:186–192. doi:10.14283/jpad.2023.7

97. Mergenthaler P, Lindauer U, Dienel GA, Meisel A. Sugar for the brain: the role of glucose in physiological and pathological brain function. Trends Neurosci. 2013;36:587–597. doi:10.1016/j.tins.2013.07.001

98. Rink C, Khanna S. Significance of brain tissue oxygenation and the arachidonic acid cascade in stroke. Antioxid Redox Signal. 2011;14:1889–1903. doi:10.1089/ars.2010.3474

99. Hillman EM. Coupling mechanism and significance of the BOLD signal: a status report. Annu Rev Neurosci. 2014;37:161–181. doi:10.1146/annurev-neuro-071013-014111

100. Cipolla MJ. The cerebral circulation. San Rafael (CA); 2009.

101. Claassen J, Thijssen DHJ, Panerai RB, Faraci FM. Regulation of cerebral blood flow in humans: physiology and clinical implications of autoregulation. Physiol Rev. 2021;101:1487–1559. doi:10.1152/physrev.00022.2020

102. Mizee MR, de Vries HE. Blood-brain barrier regulation: environmental cues controlling the onset of barrier properties. Tissue Barriers. 2013;1:e26882. doi:10.4161/tisb.26882

103. Nehlig A. Brain uptake and metabolism of ketone bodies in animal models. Prostaglandins Leukot Essent Fatty Acids. 2004;70:265–275. doi:10.1016/j.plefa.2003.07.006

104. Xue X, Liu B, Hu J, Bian X, Lou S. The potential mechanisms of lactate in mediating exercise-enhanced cognitive function: a dual role as an energy supply substrate and a signaling molecule. Nutr Metab (Lond). 2022;19:52. doi:10.1186/s12986-022-00687-z

105. Kacem K, Lacombe P, Seylaz J, Bonvento G. Structural organization of the perivascular astrocyte endfeet and their relationship with the endothelial glucose transporter: a confocal microscopy study. Glia. 1998;23:1–10. doi:10.1002/(SICI)1098-1136(199805)23:1<1::AID-GLIA1>3.0.CO;2-B

106. Watanabe T, Matsushima S, Okazaki M, et al. Localization and ontogeny of GLUT3 expression in the rat retina. Brain Res Dev Brain Res. 1996;94:60–66. doi:10.1016/0165-3806(96)00044-2

107. Leloup C, Arluison M, Kassis N, et al. Discrete brain areas express the insulin-responsive glucose transporter GLUT4. Brain Res Mol Brain Res. 1996;38:45–53. doi:10.1016/0169-328X(95)00306-D

108. Kobayashi M, Nikami H, Morimatsu M, Saito M. Expression and localization of insulin-regulatable glucose transporter (GLUT4) in rat brain. Neurosci Lett. 1996;213:103–106. doi:10.1016/0304-3940(96)12845-7

109. Maher F. Immunolocalization of GLUT1 and GLUT3 glucose transporters in primary cultured neurons and glia. J Neurosci Res. 1995;42:459–469. doi:10.1002/jnr.490420404

110. Vannucci SJ, Maher F, Simpson IA. Glucose transporter proteins in brain: delivery of glucose to neurons and glia. Glia. 1997;21:2–21. doi:10.1002/(SICI)1098-1136(199709)21:1<2::AID-GLIA2>3.0.CO;2-C

111. Alosco ML, Spitznagel MB, Raz N, et al. Obesity interacts with cerebral hypoperfusion to exacerbate cognitive impairment in older adults with heart failure. Cerebrovasc Dis Extra. 2012;2:88–98. doi:10.1159/000343222

112. Selim M, Jones R, Novak P, Zhao P, Novak V. The effects of body mass index on cerebral blood flow velocity. Clin Auton Res. 2008;18:331–338. doi:10.1007/s10286-008-0490-z

113. Willeumier KC, Taylor DV, Amen DG. Elevated BMI is associated with decreased blood flow in the prefrontal cortex using SPECT imaging in healthy adults. Obesity (Silver Spring). 2011;19:1095–1097. doi:10.1038/oby.2011.16

114. Pegueroles J, Pane A, Vilaplana E, et al. Obesity impacts brain metabolism and structure independently of amyloid and tau pathology in healthy elderly. Alzheimers Dement (Amst). 2020;12:e12052.

115. Ishibashi K, Onishi A, Fujiwara Y, Ishiwata K, Ishii K. Relationship between Alzheimer disease-like pattern of 18F-FDG and fasting plasma glucose levels in cognitively normal volunteers. J Nucl Med. 2015;56:229–233. doi:10.2967/jnumed.114.150045

116. Burns CM, Chen K, Kaszniak AW, et al. Higher serum glucose levels are associated with cerebral hypometabolism in Alzheimer regions. Neurology. 2013;80:1557–1564. doi:10.1212/WNL.0b013e31828f17de

117. Honea RA, John CS, Green ZD, et al. Relationship of fasting glucose and longitudinal Alzheimer’s disease imaging markers. Alzheimers Dement (N Y). 2022;8:e12239. doi:10.1002/trc2.12239

118. Park HS, Park JY, Yu R. Relationship of obesity and visceral adiposity with serum concentrations of CRP, TNF-alpha and IL-6. Diabet Res Clin Pract. 2005;69:29–35. doi:10.1016/j.diabres.2004.11.007

119. Matulewicz N, Karczewska-Kupczewska M. Insulin resistance and chronic inflammation. Postepy Hig Med Dosw (Online). 2016;70:1245–1258.

120. Mauer J, Denson JL, Bruning JC. Versatile functions for IL-6 in metabolism and cancer. Trends Immunol. 2015;36:92–101. doi:10.1016/j.it.2014.12.008

121. Lyngso D, Simonsen L, Bulow J. Interleukin-6 production in human subcutaneous abdominal adipose tissue: the effect of exercise. J Physiol. 2002;543:373–378. doi:10.1113/jphysiol.2002.019380

122. van Hall G, Steensberg A, Sacchetti M, et al. Interleukin-6 stimulates lipolysis and fat oxidation in humans. J Clin Endocrinol Metab. 2003;88:3005–3010. doi:10.1210/jc.2002-021687

123. Wedell-Neergaard AS, Lang Lehrskov L, Christensen RH, et al. Exercise-induced changes in visceral adipose tissue mass are regulated by IL-6 signaling: a randomized controlled trial. Cell Metab. 2019;29:844–855 e843. doi:10.1016/j.cmet.2018.12.007

124. Cai D, Yuan M, Frantz DF, et al. Local and systemic insulin resistance resulting from hepatic activation of IKK-beta and NF-kappaB. Nat Med. 2005;11:183–190. doi:10.1038/nm1166

125. Kern PA, Saghizadeh M, Ong JM, Bosch RJ, Deem R, Simsolo RB. The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest. 1995;95:2111–2119. doi:10.1172/JCI117899

126. Remels AH, Langen RC, Gosker HR, et al. PPARgamma inhibits NF-kappaB-dependent transcriptional activation in skeletal muscle. Am J Physiol Endocrinol Metab. 2009;297:E174–183. doi:10.1152/ajpendo.90632.2008

127. Wascher TC, Lindeman JH, Sourij H, Kooistra T, Pacini G, Roden M. Chronic TNF-alpha neutralization does not improve insulin resistance or endothelial function in ”healthy” men with metabolic syndrome. Mol Med. 2011;17:189–193. doi:10.2119/molmed.2010.00221

128. Bernstein LE, Berry J, Kim S, Canavan B, Grinspoon SK. Effects of etanercept in patients with the metabolic syndrome. Arch Intern Med. 2006;166:902–908. doi:10.1001/archinte.166.8.902

129. Stanley TL, Zanni MV, Johnsen S, et al. TNF-alpha antagonism with etanercept decreases glucose and increases the proportion of high molecular weight adiponectin in obese subjects with features of the metabolic syndrome. J Clin Endocrinol Metab. 2011;96:E146–150. doi:10.1210/jc.2010-1170

130. Watts G. Nobel prize is awarded to doctors who discovered H pylori. BMJ. 2005;331:795. doi:10.1136/bmj.331.7520.795

131. Lloyd-Price J, Abu-Ali G, Huttenhower C. The healthy human microbiome. Genome Med. 2016;8:51. doi:10.1186/s13073-016-0307-y

132. Al-Lahham SH, Peppelenbosch MP, Roelofsen H, Vonk RJ, Venema K. Biological effects of propionic acid in humans; metabolism, potential applications and underlying mechanisms. Biochim Biophys Acta. 2010;1801:1175–1183. doi:10.1016/j.bbalip.2010.07.007

133. Yao Y, Cai X, Fei W, Ye Y, Zhao M, Zheng C. The role of short-chain fatty acids in immunity, inflammation and metabolism. Crit Rev Food Sci Nutr. 2022;62:1–12. doi:10.1080/10408398.2020.1854675

134. Koliada A, Syzenko G, Moseiko V, et al. Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian population. BMC Microbiol. 2017;17:120. doi:10.1186/s12866-017-1027-1

135. Duncan SH, Lobley GE, Holtrop G, et al. Human colonic microbiota associated with diet, obesity and weight loss. Int J Obes Lond. 2008;32:1720–1724. doi:10.1038/ijo.2008.155

136. Zhang Q, Hu N. Effects of metformin on the gut microbiota in obesity and type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2020;13:5003–5014. doi:10.2147/DMSO.S286430

137. Trikha SRJ, Lee DM, Ecton KE, et al. Transplantation of an obesity-associated human gut microbiota to mice induces vascular dysfunction and glucose intolerance. Gut Microbes. 2021;13:1940791. doi:10.1080/19490976.2021.1940791

138. Vrieze A, Van Nood E, Holleman F, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. 2012;143:913–916 e917. doi:10.1053/j.gastro.2012.06.031

139. Kootte RS, Levin E, Salojarvi J, et al. Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell Metab. 2017;26:611–619 e616. doi:10.1016/j.cmet.2017.09.008

140. Nogal A, Valdes AM, Menni C. The role of short-chain fatty acids in the interplay between gut microbiota and diet in cardio-metabolic health. Gut Microbes. 2021;13:1–24. doi:10.1080/19490976.2021.1897212

141. D’Alessio DA, Kahn SE, Leusner CR, Ensinck JW. Glucagon-like peptide 1 enhances glucose tolerance both by stimulation of insulin release and by increasing insulin-independent glucose disposal. J Clin Invest. 1994;93:2263–2266. doi:10.1172/JCI117225

142. Puddu A, Sanguineti R, Montecucco F, Viviani GL. Evidence for the gut microbiota short-chain fatty acids as key pathophysiological molecules improving diabetes. Mediators Inflamm. 2014;2014:162021. doi:10.1155/2014/162021

143. Morris JK, John CS, Green ZD, et al. Characterization of the meal-stimulated incretin response and relationship with structural brain outcomes in aging and Alzheimer’s Disease. Front Neurosci. 2020;14:608862. doi:10.3389/fnins.2020.608862

144. Pizzino G, Irrera N, Cucinotta M, et al. Oxidative stress: harms and benefits for human health. Oxid Med Cell Longev. 2017;2017:8416763. doi:10.1155/2017/8416763

145. Hancock JT, Desikan R, Neill SJ. Role of reactive oxygen species in cell signalling pathways. Biochem Soc Trans. 2001;29:345–350. doi:10.1042/bst0290345

146. Schieber M, Chandel NS. ROS function in redox signaling and oxidative stress. Curr Biol. 2014;24:R453–462. doi:10.1016/j.cub.2014.03.034

147. Tirichen H, Yaigoub H, Xu W, Wu C, Li R, Li Y. Mitochondrial reactive oxygen species and their contribution in chronic kidney disease progression through oxidative stress. Front Physiol. 2021;12:627837. doi:10.3389/fphys.2021.627837

148. Guo C, Sun L, Chen X, Zhang D. Oxidative stress, mitochondrial damage and neurodegenerative diseases. Neural Regen Res. 2013;8:2003–2014. doi:10.3969/j.issn.1673-5374.2013.21.009

149. Wang X, Wang W, Li L, Perry G, Lee HG, Zhu X. Oxidative stress and mitochondrial dysfunction in Alzheimer’s disease. Biochim Biophys Acta. 2014;1842:1240–1247. doi:10.1016/j.bbadis.2013.10.015

150. Subramaniam SR, Chesselet MF. Mitochondrial dysfunction and oxidative stress in Parkinson’s disease. Prog Neurobiol. 2013;106–107:17–32. doi:10.1016/j.pneurobio.2013.04.004

151. Heiss C, Rodriguez-Mateos A, Kelm M. Central role of eNOS in the maintenance of endothelial homeostasis. Antioxid Redox Signal. 2015;22:1230–1242. doi:10.1089/ars.2014.6158

152. Arora D, Jain P, Singh N, Kaur H, Bhatla SC. Mechanisms of nitric oxide crosstalk with reactive oxygen species scavenging enzymes during abiotic stress tolerance in plants. Free Radic Res. 2016;50:291–303. doi:10.3109/10715762.2015.1118473

153. Haruna Y, Morita Y, Komai N, et al. Endothelial dysfunction in rat adjuvant-induced arthritis: vascular superoxide production by NAD(P)H oxidase and uncoupled endothelial nitric oxide synthase. Arthritis Rheum. 2006;54:1847–1855. doi:10.1002/art.21891

154. Zhang C. The role of inflammatory cytokines in endothelial dysfunction. Basic Res Cardiol. 2008;103:398–406. doi:10.1007/s00395-008-0733-0

155. Anderson TJ. Assessment and treatment of endothelial dysfunction in humans. J Am Coll Cardiol. 1999;34:631–638. doi:10.1016/S0735-1097(99)00259-4

156. Venturelli M, Pedrinolla A, Boscolo Galazzo I, et al. Impact of nitric oxide bioavailability on the progressive cerebral and peripheral circulatory impairments during aging and Alzheimer’s disease. Front Physiol. 2018;9:169. doi:10.3389/fphys.2018.00169

157. Smith KJ, Kapoor R, Felts PA. Demyelination: the role of reactive oxygen and nitrogen species. Brain Pathol. 1999;9:69–92. doi:10.1111/j.1750-3639.1999.tb00212.x

158. Yang K, Wu Z, Long J, et al. White matter changes in Parkinson’s disease. NPJ Parkinsons Dis. 2023;9:150. doi:10.1038/s41531-023-00592-z

159. Kloppenborg RP, Nederkoorn PJ, Geerlings MI, van den Berg E. Presence and progression of white matter hyperintensities and cognition: a meta-analysis. Neurology. 2014;82:2127–2138. doi:10.1212/WNL.0000000000000505

160. Bouhrara M, Khattar N, Elango P, Resnick SM, Ferrucci L, Spencer RG. Evidence of association between obesity and lower cerebral myelin content in cognitively unimpaired adults. Int J Obes Lond. 2021;45:850–859. doi:10.1038/s41366-021-00749-x

161. Laporte JP, Faulkner ME, Gong Z, et al. Hypertensive adults exhibit lower myelin content: a multicomponent relaxometry and diffusion magnetic resonance imaging study. Hypertension. 2023;80:1728–1738. doi:10.1161/HYPERTENSIONAHA.123.21012

162. Burzynska AZ, Anderson C, Arciniegas DB, et al. Metabolic syndrome and adiposity: risk factors for decreased myelin in cognitively healthy adults. Cereb Circ Cogn Behav. 2023;5:100180. doi:10.1016/j.cccb.2023.100180

163. Hindle JV. Ageing, neurodegeneration and Parkinson’s disease. Age Ageing. 2010;39:156–161. doi:10.1093/ageing/afp223

164. Pagano G, Polychronis S, Wilson H, et al. Diabetes mellitus and Parkinson disease. Neurology. 2018;90:e1654–e1662. doi:10.1212/WNL.0000000000005475

165. Arvanitakis Z, Wilson RS, Bienias JL, Evans DA, Bennett DA. Diabetes mellitus and risk of Alzheimer disease and decline in cognitive function. Arch Neurol. 2004;61:661–666. doi:10.1001/archneur.61.5.661

166. Ismail Z, Malick A, Smith EE, Schweizer T, Fischer C. Depression versus dementia: is this construct still relevant? Neurodegener Dis Manag. 2014;4:119–126. doi:10.2217/nmt.14.5

167. Djamshidian A, Friedman JH. Anxiety and depression in Parkinson’s disease. Curr Treat Options Neurol. 2014;16:285. doi:10.1007/s11940-014-0285-6

168. Corder EH, Saunders AM, Strittmatter WJ, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science. 1993;261:921–923. doi:10.1126/science.8346443

169. Linton MF, Gish R, Hubl ST, et al. Phenotypes of apolipoprotein B and apolipoprotein E after liver transplantation. J Clin Invest. 1991;88:270–281. doi:10.1172/JCI115288

170. Martinez-Morillo E, Hansson O, Atagi Y, et al. Total apolipoprotein E levels and specific isoform composition in cerebrospinal fluid and plasma from Alzheimer’s disease patients and controls. Acta Neuropathol. 2014;127:633–643. doi:10.1007/s00401-014-1266-2

171. Serrano-Pozo A, Das S, Hyman BT. APOE and Alzheimer’s disease: advances in genetics, pathophysiology, and therapeutic approaches. Lancet Neurol. 2021;20:68–80. doi:10.1006/exnr.1994.1044

172. Triebswetter C, Kiely M, Khattar N, et al. Differential associations between apolipoprotein E alleles and cerebral myelin content in normative aging. Neuroimage. 2022;251:118988. doi:10.1016/j.neuroimage.2022.118988

173. Belvisi D, Pellicciari R, Fabbrini A, et al. Risk factors of Parkinson disease: simultaneous assessment, interactions, and etiologic subtypes. Neurology. 2020;95:e2500–e2508. doi:10.1212/WNL.0000000000010813

174. Ettle B, Kerman BE, Valera E, et al. alpha-Synuclein-induced myelination deficit defines a novel interventional target for multiple system atrophy. Acta Neuropathol. 2016;132:59–75. doi:10.1007/s00401-016-1572-y

175. Spillantini MG, Schmidt ML, Lee VM, Trojanowski JQ, Jakes R, Goedert M. Alpha-synuclein in Lewy bodies. Nature. 1997;388:839–840. doi:10.1038/42166

176. Polymeropoulos MH, Lavedan C, Leroy E, et al. Mutation in the alpha-synuclein gene identified in families with Parkinson’s disease. Science. 1997;276:2045–2047. doi:10.1126/science.276.5321.2045

177. Peng C, Gathagan RJ, Covell DJ, et al. Cellular milieu imparts distinct pathological alpha-synuclein strains in alpha-synucleinopathies. Nature. 2018;557:558–563. doi:10.1038/s41586-018-0104-4

178. de Bem AF, Krolow R, Farias HR, et al. Animal models of metabolic disorders in the study of neurodegenerative diseases: an overview. Front Neurosci. 2020;14:604150. doi:10.3389/fnins.2020.604150

179. Wieckowska-Gacek A, Mietelska-Porowska A, Wydrych M, Wojda U. Western diet as a trigger of Alzheimer’s disease: from metabolic syndrome and systemic inflammation to neuroinflammation and neurodegeneration. Ageing Res Rev. 2021;70:101397. doi:10.1016/j.arr.2021.101397

180. Amelianchik A, Sweetland-Martin L, Norris EH. The effect of dietary fat consumption on Alzheimer’s disease pathogenesis in mouse models. Transl Psychiatry. 2022;12:293. doi:10.1038/s41398-022-02067-w

181. Sparks DL, Scheff SW, Hunsaker JC 3rd, Liu H, Landers T, Gross DR. Induction of Alzheimer-like beta-amyloid immunoreactivity in the brains of rabbits with dietary cholesterol. Exp Neurol. 1994;126:88–94.

182. Refolo LM, Malester B, LaFrancois J, et al. Hypercholesterolemia accelerates the Alzheimer’s amyloid pathology in a transgenic mouse model. Neurobiol Dis. 2000;7:321–331. doi:10.1006/nbdi.2000.0304

183. Ullrich C, Pirchl M, Humpel C. Hypercholesterolemia in rats impairs the cholinergic system and leads to memory deficits. Mol Cell Neurosci. 2010;45:408–417. doi:10.1016/j.mcn.2010.08.001

184. Moreira EL, de Oliveira J, Engel DF, et al. Hypercholesterolemia induces short-term spatial memory impairments in mice: up-regulation of acetylcholinesterase activity as an early and causal event? J Neural Transm (Vienna). 2014;121:415–426. doi:10.1007/s00702-013-1107-9

185. Ho L, Qin W, Pompl PN, et al. Diet-induced insulin resistance promotes amyloidosis in a transgenic mouse model of Alzheimer’s disease. FASEB J. 2004;18:902–904. doi:10.1096/fj.03-0978fje

186. Wang X, Zheng W, Xie JW, et al. Insulin deficiency exacerbates cerebral amyloidosis and behavioral deficits in an Alzheimer transgenic mouse model. Mol Neurodegener. 2010;5:46. doi:10.1186/1750-1326-5-46

187. Hascup ER, Broderick SO, Russell MK, et al. Diet-induced insulin resistance elevates hippocampal glutamate as well as VGLUT1 and GFAP expression in AbetaPP/PS1 mice. J Neurochem. 2019;148:219–237. doi:10.1111/jnc.14634

188. Yekollu SK, Thomas R, O’Sullivan B. Targeting curcusomes to inflammatory dendritic cells inhibits NF-kappaB and improves insulin resistance in obese mice. Diabetes. 2011;60:2928–2938. doi:10.2337/db11-0275

189. Hasegawa Y, Saito T, Ogihara T, et al. Blockade of the nuclear factor-kappaB pathway in the endothelium prevents insulin resistance and prolongs life spans. Circulation. 2012;125:1122–1133. doi:10.1161/CIRCULATIONAHA.111.054346

190. Wang C, Fan L, Khawaja RR, et al. Microglial NF-kappaB drives tau spreading and toxicity in a mouse model of tauopathy. Nat Commun. 2022;13:1969. doi:10.1038/s41467-022-29552-6

191. Sandhu M, Irfan HM, Shah SA, et al. Friedelin attenuates neuronal dysfunction and memory impairment by inhibition of the activated JNK/NF-kappaB signalling pathway in scopolamine-induced mice model of neurodegeneration. Molecules. 2022;27. doi:10.3390/molecules28010027

192. Dye L, Boyle NB, Champ C, Lawton C. The relationship between obesity and cognitive health and decline. Proc Nutr Soc. 2017;76:443–454. doi:10.1017/S0029665117002014

193. Pugazhenthi S, Qin L, Reddy PH. Common neurodegenerative pathways in obesity, diabetes, and Alzheimer’s disease. Biochim Biophys Acta Mol Basis Dis. 2017;1863:1037–1045. doi:10.1016/j.bbadis.2016.04.017

194. Garcia-Ptacek S, Faxen-Irving G, Cermakova P, Eriksdotter M, Religa D. Body mass index in dementia. Eur J Clin Nutr. 2014;68:1204–1209. doi:10.1038/ejcn.2014.199

195. Lung T, Jan S, Tan EJ, Killedar A, Hayes A. Impact of overweight, obesity and severe obesity on life expectancy of Australian adults. Int J Obes Lond. 2019;43:782–789. doi:10.1038/s41366-018-0210-2

196. Buchman AS, Capuano AW, VanderHorst V, et al. Brain beta-amyloid links the association of change in body mass index with cognitive decline in community-dwelling older adults. J Gerontol a Biol Sci Med Sci. 2023;78:277–285. doi:10.1093/gerona/glab320

197. Clark LR, Koscik RL, Allison SL, et al. Hypertension and obesity moderate the relationship between beta-amyloid and cognitive decline in midlife. Alzheimers Dement. 2019;15:418–428. doi:10.1016/j.jalz.2018.09.008

198. Herrmann MJ, Tesar AK, Beier J, Berg M, Warrings B. Grey matter alterations in obesity: a meta-analysis of whole-brain studies. Obes Rev. 2019;20:464–471. doi:10.1111/obr.12799

199. Papageorgiou I, Astrakas LG, Xydis V, et al. Abnormalities of brain neural circuits related to obesity: a diffusion tensor imaging study. Magn Reson Imaging. 2017;37:116–121. doi:10.1016/j.mri.2016.11.018

200. Repple J, Opel N, Meinert S, et al. Elevated body-mass index is associated with reduced white matter integrity in two large independent cohorts. Psychoneuroendocrinology. 2018;91:179–185. doi:10.1016/j.psyneuen.2018.03.007

201. Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA. 1997;278:1349–1356. doi:10.1001/jama.1997.03550160069041

202. Gustafson D, Lissner L, Bengtsson C, Bjorkelund C, Skoog I. A 24-year follow-up of body mass index and cerebral atrophy. Neurology. 2004;63:1876–1881. doi:10.1212/01.WNL.0000141850.47773.5F

203. Zhu D, Chung HF, Pandeya N, et al. Body mass index and age at natural menopause: an international pooled analysis of 11 prospective studies. Eur J Epidemiol. 2018;33:699–710. doi:10.1007/s10654-018-0367-y

204. Lu W, Guo W, Hou K, et al. Grey matter differences associated with age and sex hormone levels between premenopausal and perimenopausal women: a voxel-based morphometry study. J Neuroendocrinol. 2018;30:e12655. doi:10.1111/jne.12655

205. Mosconi L, Rahman A, Diaz I, et al. Increased Alzheimer’s risk during the menopause transition: a 3-year longitudinal brain imaging study. PLoS One. 2018;13:e0207885. doi:10.1371/journal.pone.0207885

206. Franz CE, Xian H, Lew D, et al. Body mass trajectories and cortical thickness in middle-aged men: a 42-year longitudinal study starting in young adulthood. Neurobiol Aging. 2019;79:11–21. doi:10.1016/j.neurobiolaging.2019.03.003

207. Morys F, Dadar M, Dagher A. Association between midlife obesity and its metabolic consequences, cerebrovascular disease, and cognitive decline. J Clin Endocrinol Metab. 2021;106:e4260–e4274. doi:10.1210/clinem/dgab135

208. Maffei M, Halaas J, Ravussin E, et al. Leptin levels in human and rodent: measurement of plasma leptin and ob RNA in obese and weight-reduced subjects. Nat Med. 1995;1:1155–1161. doi:10.1038/nm1195-1155

209. Alexander C, Cochran CJ, Gallicchio L, Miller SR, Flaws JA, Zacur H. Serum leptin levels, hormone levels, and hot flashes in midlife women. Fertil Steril. 2010;94:1037–1043. doi:10.1016/j.fertnstert.2009.04.001

210. Banks WA, Kastin AJ, Huang W, Jaspan JB, Maness LM. Leptin enters the brain by a saturable system independent of insulin. Peptides. 1996;17:305–311. doi:10.1016/0196-9781(96)00025-3

211. Garza JC, Guo M, Zhang W, Lu XY. Leptin increases adult hippocampal neurogenesis in vivo and in vitro. J Biol Chem. 2008;283:18238–18247. doi:10.1074/jbc.M800053200

212. Narita K, Kosaka H, Okazawa H, Murata T, Wada Y. Relationship between plasma leptin level and brain structure in elderly: a voxel-based morphometric study. Biol Psychiatry. 2009;65:992–994. doi:10.1016/j.biopsych.2008.10.006

213. Obradovic M, Sudar-Milovanovic E, Soskic S, et al. Leptin and obesity: role and clinical implication. Front Endocrinol (Lausanne). 2021;12:585887. doi:10.3389/fendo.2021.585887

214. Witte AV, Kobe T, Graunke A, et al. Impact of leptin on memory function and hippocampal structure in mild cognitive impairment. Hum Brain Mapp. 2016;37:4539–4549. doi:10.1002/hbm.23327

215. Savica R, Rocca WA, Ahlskog JE. When does Parkinson disease start? Arch Neurol. 2010;67:798–801. doi:10.1001/archneurol.2010.135

216. Szkudelski T. The mechanism of alloxan and streptozotocin action in B cells of the rat pancreas. Physiol Res. 2001;50:537–546.

217. Gallego M, Setien R, Izquierdo MJ, Casis O, Casis E. Diabetes-induced biochemical changes in central and peripheral catecholaminergic systems. Physiol Res. 2003;52:735–741. doi:10.33549/physiolres.930334

218. Shimomura Y, Shimizu H, Takahashi M, et al. Changes in ambulatory activity and dopamine turnover in streptozotocin-induced diabetic rats. Endocrinology. 1988;123:2621–2625. doi:10.1210/endo-123-6-2621

219. Jones KT, Woods C, Zhen J, Antonio T, Carr KD, Reith ME. Effects of diet and insulin on dopamine transporter activity and expression in rat caudate-putamen, nucleus accumbens, and midbrain. J Neurochem. 2017;140:728–740. doi:10.1111/jnc.13930

220. Anitha M, Abraham PM, Paulose CS. Striatal dopamine receptors modulate the expression of insulin receptor, IGF-1 and GLUT-3 in diabetic rats: effect of pyridoxine treatment. Eur J Pharmacol. 2012;696:54–61. doi:10.1016/j.ejphar.2012.09.006

221. Choi JY, Jang EH, Park CS, Kang JH. Enhanced susceptibility to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine neurotoxicity in high-fat diet-induced obesity. Free Radic Biol Med. 2005;38:806–816. doi:10.1016/j.freeradbiomed.2004.12.008

222. Morris JK, Bomhoff GL, Stanford JA, Geiger PC. Neurodegeneration in an animal model of Parkinson’s disease is exacerbated by a high-fat diet. Am J Physiol Regul Integr Comp Physiol. 2010;299:R1082–1090. doi:10.1152/ajpregu.00449.2010

223. Sharma S, Taliyan R. High fat diet feeding induced insulin resistance exacerbates 6-OHDA mediated neurotoxicity and behavioral abnormalities in rats. Behav Brain Res. 2018;351:17–23. doi:10.1016/j.bbr.2018.05.025

224. Bousquet M, St-Amour I, Vandal M, Julien P, Cicchetti F, Calon F. High-fat diet exacerbates MPTP-induced dopaminergic degeneration in mice. Neurobiol Dis. 2012;45:529–538. doi:10.1016/j.nbd.2011.09.009

225. Griffioen KJ, Rothman SM, Ladenheim B, et al. Dietary energy intake modifies brainstem autonomic dysfunction caused by mutant alpha-synuclein. Neurobiol Aging. 2013;34:928–935. doi:10.1016/j.neurobiolaging.2012.07.008

226. Rotermund C, Truckenmuller FM, Schell H, Kahle PJ. Diet-induced obesity accelerates the onset of terminal phenotypes in alpha-synuclein transgenic mice. J Neurochem. 2014;131:848–858. doi:10.1111/jnc.12813

227. Morris JK, Bomhoff GL, Gorres BK, et al. Insulin resistance impairs nigrostriatal dopamine function. Exp Neurol. 2011;231:171–180. doi:10.1016/j.expneurol.2011.06.005

228. Hebert MA, Gerhardt GA. Normal and drug-induced locomotor behavior in aging: comparison to evoked DA release and tissue content in Fischer 344 rats. Brain Res. 1998;797:42–54. doi:10.1016/S0006-8993(98)00370-9

229. Bharath S, Hsu M, Kaur D, Rajagopalan S, Andersen JK. Glutathione, iron and Parkinson’s disease. Biochem Pharmacol. 2002;64:1037–1048. doi:10.1016/S0006-2952(02)01174-7

230. Ma D, Shuler JM, Raider KD, et al. Effects of discontinuing a high-fat diet on mitochondrial proteins and 6-hydroxydopamine-induced dopamine depletion in rats. Brain Res. 2015;1613:49–58. doi:10.1016/j.brainres.2015.03.053

231. Hirsch L, Jette N, Frolkis A, Steeves T, Pringsheim T. The incidence of Parkinson’s disease: a systematic review and meta-analysis. Neuroepidemiology. 2016;46:292–300. doi:10.1159/000445751

232. Wright Willis A, Evanoff BA, Lian M, Criswell SR, Racette BA. Geographic and ethnic variation in Parkinson disease: a population-based study of US Medicare beneficiaries. Neuroepidemiology. 2010;34:143–151. doi:10.1159/000275491

233. Narayan S, Liew Z, Bronstein JM, Ritz B. Occupational pesticide use and Parkinson’s disease in the Parkinson Environment Gene (PEG) study. Environ Int. 2017;107:266–273. doi:10.1016/j.envint.2017.04.010

234. Dannawi M, Riachi ME, Haddad AF, et al. Influence of intermittent fasting on prediabetes-induced neuropathy: insights on a novel mechanistic pathway. Metabol Open. 2022;14:100175. doi:10.1016/j.metop.2022.100175

235. Schonknecht YB, Crommen S, Stoffel-Wagner B, et al. Acute effects of three different meal patterns on postprandial metabolism in older individuals with a risk phenotype for cardiometabolic diseases: a randomized controlled crossover trial. Mol Nutr Food Res. 2020;64:e1901035. doi:10.1002/mnfr.201901035

236. Schonknecht YB, Crommen S, Stoffel-Wagner B, et al. APOE varepsilon4 is associated with postprandial inflammation in older adults with metabolic syndrome traits. Nutrients. 2021;13:3924.

237. Witte AV, Fobker M, Gellner R, Knecht S, Floel A. Caloric restriction improves memory in elderly humans. Proc Natl Acad Sci U S A. 2009;106:1255–1260. doi:10.1073/pnas.0808587106

238. Prehn K, Jumpertz von schwartzenberg R, Mai K, et al. Caloric restriction in older adults-differential effects of weight loss and reduced weight on brain structure and function. Cereb Cortex. 2017;27:1765–1778. doi:10.1093/cercor/bhw008

239. Owen OE, Felig P, Morgan AP, Wahren J, Cahill GF Jr. Liver and kidney metabolism during prolonged starvation. J Clin Invest. 1969;48:574–583. doi:10.1172/JCI106016

240. Phillips MCL, Deprez LM, Mortimer GMN, et al. Randomized crossover trial of a modified ketogenic diet in Alzheimer’s disease. Alzheimers Res Ther. 2021;13:51. doi:10.1186/s13195-021-00783-x

241. Ota M, Matsuo J, Ishida I, et al. Effects of a medium-chain triglyceride-based ketogenic formula on cognitive function in patients with mild-to-moderate Alzheimer’s disease. Neurosci Lett. 2019;690:232–236. doi:10.1016/j.neulet.2018.10.048

242. Phillips MCL, Murtagh DKJ, Gilbertson LJ, Asztely FJS, Lynch CDP. Low-fat versus ketogenic diet in Parkinson’s disease: a pilot randomized controlled trial. Mov Disord. 2018;33:1306–1314. doi:10.1002/mds.27390

243. Myers J, Kokkinos P, Nyelin E. Physical activity, cardiorespiratory fitness, and the metabolic syndrome. Nutrients. 2019;11:1652.

244. Lavie CJ, Ozemek C, Carbone S, Katzmarzyk PT, Blair SN. Sedentary behavior, exercise, and cardiovascular health. Circ Res. 2019;124:799–815. doi:10.1161/CIRCRESAHA.118.312669

245. Hotting K, Roder B. Beneficial effects of physical exercise on neuroplasticity and cognition. Neurosci Biobehav Rev. 2013;37:2243–2257. doi:10.1016/j.neubiorev.2013.04.005

246. Chodzko-Zajko WJ, Proctor DN; American College of Sports M. American College of Sports Medicine position stand. Exercise and physical activity for older adults. Med Sci Sports Exerc. 2009;41:1510–1530. doi:10.1249/MSS.0b013e3181a0c95c

247. Goodpaster BH, Wolfe RR, Kelley DE. Effects of obesity on substrate utilization during exercise. Obes Res. 2002;10:575–584. doi:10.1038/oby.2002.78

248. Morris JK, Vidoni ED, Johnson DK, et al. Aerobic exercise for Alzheimer’s disease: a randomized controlled pilot trial. PLoS One. 2017;12:e0170547. doi:10.1371/journal.pone.0170547

249. Dauwan M, Begemann MJH, Slot MIE, Lee EHM, Scheltens P, Sommer IEC. Physical exercise improves quality of life, depressive symptoms, and cognition across chronic brain disorders: a transdiagnostic systematic review and meta-analysis of randomized controlled trials. J Neurol. 2021;268:1222–1246. doi:10.1007/s00415-019-09493-9

250. Schenkman M, Moore CG, Kohrt WM, et al. Effect of high-intensity treadmill exercise on motor symptoms in patients with de novo Parkinson disease: a Phase 2 randomized clinical trial. JAMA Neurol. 2018;75:219–226. doi:10.1001/jamaneurol.2017.3517

251. Motiani KK, Collado MC, Eskelinen JJ, et al. Exercise training modulates gut microbiota profile and improves endotoxemia. Med Sci Sports Exerc. 2020;52:94–104. doi:10.1249/MSS.0000000000002112

252. Numakawa T, Odaka H. The Role of neurotrophin signaling in age-related cognitive decline and cognitive diseases. Int J Mol Sci. 2022;23:7726. doi:10.3390/ijms23147726

253. Kim CS, Cha L, Sim M, et al. Probiotic supplementation improves cognitive function and mood with changes in gut microbiota in community-dwelling older adults: a randomized, double-blind, placebo-controlled, multicenter trial. J Gerontol a Biol Sci Med Sci. 2021;76:32–40. doi:10.1093/gerona/glaa090

254. Berchtold NC, Chinn G, Chou M, Kesslak JP, Cotman CW. Exercise primes a molecular memory for brain-derived neurotrophic factor protein induction in the rat hippocampus. Neuroscience. 2005;133:853–861. doi:10.1016/j.neuroscience.2005.03.026

255. Kim DM, Leem YH. Chronic stress-induced memory deficits are reversed by regular exercise via AMPK-mediated BDNF induction. Neuroscience. 2016;324:271–285. doi:10.1016/j.neuroscience.2016.03.019

256. Gaitan JM, Moon HY, Stremlau M, et al. Effects of aerobic exercise training on systemic biomarkers and cognition in late middle-aged adults at risk for Alzheimer’s disease. Front Endocrinol (Lausanne). 2021;12:660181. doi:10.3389/fendo.2021.660181

257. Atrooz F, Salim S. Sleep deprivation, oxidative stress and inflammation. Adv Protein Chem Struct Biol. 2020;119:309–336.

258. Hargens TA, Kaleth AS, Edwards ES, Butner KL. Association between sleep disorders, obesity, and exercise: a review. Nat Sci Sleep. 2013;5:27–35. doi:10.2147/NSS.S34838

259. Lucey BP, Hicks TJ, McLeland JS, et al. Effect of sleep on overnight cerebrospinal fluid amyloid beta kinetics. Ann Neurol. 2018;83:197–204. doi:10.1002/ana.25117

260. Curcio G, Ferrara M, De Gennaro L. Sleep loss, learning capacity and academic performance. Sleep Med Rev. 2006;10:323–337. doi:10.1016/j.smrv.2005.11.001

261. Gillen-O’Neel C, Huynh VW, Fuligni AJ. To study or to sleep? The academic costs of extra studying at the expense of sleep. Child Dev. 2013;84:133–142. doi:10.1111/j.1467-8624.2012.01834.x

262. Krause AJ, Simon EB, Mander BA, et al. The sleep-deprived human brain. Nat Rev Neurosci. 2017;18:404–418. doi:10.1038/nrn.2017.55

263. Rothman SM, Herdener N, Frankola KA, Mughal MR, Mattson MP. Chronic mild sleep restriction accentuates contextual memory impairments, and accumulations of cortical Abeta and pTau in a mouse model of Alzheimer’s disease. Brain Res. 2013;1529:200–208. doi:10.1016/j.brainres.2013.07.010

264. Reutrakul S, Van Cauter E. Sleep influences on obesity, insulin resistance, and risk of type 2 diabetes. Metabolism. 2018;84:56–66. doi:10.1016/j.metabol.2018.02.010

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