Neurological consequences of obesity

Review

Neurological consequences of obesity Phillipe D O’Brien, Lucy M Hinder, Brian C Callaghan, Eva L Feldman

The high prevalence of obesity is associated with an enormous medical, social, and economic burden. The metabolic dysfunction, dyslipidaemia, and inflammation caused by obesity contribute to the development of a wide variety of disorders and effects on the nervous system. In the CNS, mild cognitive impairment can be attributed to obesityinduced alterations in hippocampal structure and function in some patients. Likewise, compromised hypothalamic function and subsequent defects in maintaining whole-body energy balance might be early events that contribute to weight gain and obesity development. In the peripheral nervous system, obesity-driven alterations in the autonomic nervous system prompt imbalances in sympathetic–parasympathetic activity, while alterations in the sensory–somatic nervous system underlie peripheral polyneuropathy, a common complication of diabetes. Pharmacotherapy and bariatric surgery are promising interventions for people with obesity that can improve neurological function. However, lifestyle interventions via dietary changes and exercise are the preferred approach to combat obesity and reduce its associated health risks.

Introduction About 2·1 billion individuals are overweight or obese.1 Genetic background predisposes certain individuals and ethnicities to develop obesity;2 however, weight gain is largely driven by factors that arose in high-income countries in the late 20th century.3 This obesogenic environment is attributable to several factors, including the overconsumption of processed, affordable, heavily marketed, highly palatable, and energy-dense foods combined with an increased sedentary lifestyle. Although there are indications that the exponential increase in obesity incidence has plateaued in high-income countries, numerous regions worldwide that have adopted the lifestyle of a high-income society continue to show an increase in obesity incidence, which then gets reflected in a worldwide increase.1 Projections estimate that more than 18% of adults will be obese by 2025.4 Defined as an increase of fat mass that adversely affects health, obesity is a risk factor for cardiovascular disease and certain cancers (panel 1). Central obesity, which is accompanied by a low-grade metabolic inflammation in visceral adipose tissue, is also recognised as both a component and a driver of the metabolic syndrome.8 The metabolic syndrome is characterised by the presence of multiple comorbidities, including dyslipidaemia, decreased insulin sensitivity, hyperinsulinaemia, hyper­ glycaemia, and hypertension; thus, obesity is an underlying promoter of systemic metabolic dysfunction. Multiple tissues, including those of the liver, pancreas, kidney, and the vasculature, exhibit dysfunction as a consequence of obesity. Accumulating evidence also links obesity with several neurological disorders. Although the CNS and the peripheral nervous system (PNS) are quite distinct in form and function, both are susceptible to obesity-driven dysfunction, suggesting that common mechanisms might be enabled by visceral adiposity. Obesity drives components of the metabolic syndrome that are strongly linked to neurological deficits (eg, strong associations exist between insulin resistance and cognitive decline). As a result, multiple mechanisms might be interacting to culminate in neurological dysfunction, but www.thelancet.com/neurology Vol 16 June 2017

Lancet Neurol 2017; 16: 465–77 Department of Neurology, University of Michigan, Ann Arbor, MI, USA (P D O’Brien PhD, L M Hinder PhD, B C Callaghan MD, E L Feldman MD) Correspondence to: Dr Eva L Feldman, Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA [email protected]

ascertaining direct causality of visceral adiposity on neurological complications is challenging. Mechanistic insights provided by animal models of obesity suggest that excess dietary fat compromises the hypothalamic control of energy homoeostasis. This mechanism might contribute to adipose tissue dys­ function, leading to elevated concen­trations of free fatty acids and systemic dyslipidaemia. Chronic caloric excess affects multiple organs, including the liver, and leads to an increase in circulating triglycerides. This dyslipidaemia can result in free fatty acids-induced lipotoxicity, and changes in intracellular signalling or lipid use that can result in neurological dysfunction. Although these mechanisms are likely to affect the CNS and PNS in a Panel 1: Obesity screening In clinical research, accurate methods for obesity quantification include dual energy x-ray absorptiometry (DEXA), MRI, and CT. However, because it is not feasible to do these methods routinely in clinical practice or for large population studies, body-mass index (BMI) and, to a lesser degree, waist to hip ratio (WHR) are used to assess the degree of obesity, as they are inexpensive, easy to do, and adequate surrogate markers. For white men, a BMI of 25–29 kg/m² is defined as overweight, a BMI of more than 30 kg/m² is defined as obese, and a BMI of more than 40 kg/m² is defined as morbidly obese (because adipose distribution varies depending on age, sex, and ethnicity, different criteria are used for children, women, and ethnic groups). Although routinely used to screen for obesity, BMI does not reveal differences in fat distribution, and therefore can give an inaccurate assessment of disease risk. For example, a subgroup of individuals who are obese according to the BMI criteria (BMI >30 kg/m²) can be relatively metabolically healthy with low fasting insulin, glucose, and triglycerides, and protected from diseases related to metabolic dysfunction.5 This protection can possibly be attributed to increased adiposity in lower fat depots than in abdominal regions; these depots (eg, gluteal, femoral, subcutaneous, and intramuscular) show distinct physiological features from abdominal depots and are comprised of adipocytes that have greater capacity to deal with an increased metabolic load.6 Moreover, individuals with or without obesity but with excess fat in the intra-abdominal region (visceral fat consisting of omental and mesenteric depots) are more susceptible to obesity-related diseases than those without abdominal fat.7 For these reasons, clinical assessment of abdominal waist circumference, a surrogate marker of abdominal adipose fat mass, is a better marker for disease risk than assessment of BMI.

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multifactorial fashion, recent advances have improved our insight into the neurological complications that can occur with obesity. In this Review, we outline the pathophysio­ logical development of obesity and dyslipidaemia, describe diseases of the CNS and PNS that can arise as a consequence, present evidence for lipotoxicity and metabolic inflammation as the principal mechanisms underlying these neurological consequences of obesity, and discuss potential treatment approaches.

The pathophysiology of obesity The adipose tissue performs functions that include the storage and release of energy, thermal insulation, and protection of internal organs from trauma. Additionally, the adipose tissue possesses endocrine activity that is mediated by adipokines, a diverse set of signalling molecules that includes hormones, cytokines, acute phase reactants, and growth factors. These molecules are essential in regulating metabolically active tissues and organs involved in maintaining energy homoeostasis, such as the adipose tissue itself and the liver, the pancreas, and the brain. The adipose tissue is composed of adipocytes and a stromovascular compartment containing pre-adipocytes, fibroblasts, endothelial cells, resident immune cells, blood vessels, and nerve terminals. The adipocytes are highly efficient fat-storing cells that stockpile energy in the form of triglyceride-rich lipid droplets. Regulation of adipocyte energy uptake and storage is primarily maintained by insulin, which mediates the uptake of fatty acids and lipogenesis but inhibits lipolysis. During periods of negative energy balance, when non-adipose tissues require energy, the stimulation of adipose tissue by sympathetic nerves promotes the lipolysis of the stored triglycerides to fatty acids within adipocytes. Fatty acids are then released into the circulation to serve as fuel for non-adipose tissues.9 However, during protracted periods of positive energy balance (ie, caloric excess), adipocytes undergo hypertrophy (adipocyte enlargement) or hyperplasia (adipose progenitor cells proliferate and differentiate into new adipocytes), or both, resulting in adipose tissue expansion to accommodate the storage of surplus calories. Substantial increases in adipose mass, particularly in the visceral depots, contribute to adipose tissue dysfunction and promote metabolic disease via a lowgrade metabolic inflammation that underlies systemic metabolic dysfunction.8 Consequences of adipose tissue inflammation include an altered adipokine secretion profile, impaired insulin signalling, compromised triglyceride storage, and increased basal lipolysis. These alterations culminate in increased circulating adipokines and free fatty acids, and are essential to cause peripheral-tissue and nervous-tissue dysfunction (figure 1). Metabolic inflammation occurs primarily in hyper­ trophied adipose tissue as a consequence of sustained caloric excess that initiates stress signalling 466

pathways, and leads to activated resident macrophages. Local adipose tissue inflammation is characterised by increased expression of pro-inflammatory adipokines, including C-reactive protein, interleukin 1, interleukin 6, interleukin 1β, tumour necrosis factor α (TNFα), and leptin. Furthermore, chemotactic adipokines such as monocyte chemoattractant protein 1 can further amplify local inflammation by promoting the infiltration and accumulation of circulating leucocytes to the adipose tissue. Activation of resident macrophages can trigger the recruitment of circulating monocytes and macro­ phages, T cells, natural killer T cells, B lymphocytes, and mast cells.10 Moreover, chronic adipose tissue inflammation can lead to so-called spillover of proinflammatory mediators into the circulation; hence, individuals who are obese typically have high concentrations of circulating pro-inflammatory adipo­ kines that correlate with adipose mass. Metabolic inflammation also promotes insulin resistance in the adipose tissue, a state of decreased responsiveness to insulin that is mediated by TNFα signalling.11 Because the uptake and storage of circulating free fatty acids in adipocytes is insulin-dependent, compromised insulin signalling within adipose tissue impairs clearance of circulating free fatty acids,12 thus contributing to increased levels of circulating fatty acids (such as palmitic, oleic, and linoleic acids) in obese people.

Obesity and dyslipidaemia In addition to the increase in adipose-derived free fatty acids, liver-derived and diet-derived VLDL triglycerides substantially contribute to dyslipidaemia in obese people.12 Free fatty acids-induced liver dysfunction leads to an increase in production of liver-derived VLDL triglycerides, while caloric excess increases circulating VLDL triglycerides from chylomicrons (lipoprotein particles). These triglycerides are hydrolysed to their constituent long chain fatty acids by lipoprotein lipases present in vascular endothelium, neurons, and glia, therefore adding to the free fatty acid load on all organs, as well as the CNS and PNS. These bioactive lipids can also be deposited along blood vessels, compromising blood flow and tissue perfusion via atherogenesis; can accumulate ectopically in tissue, compromising structure and cellular signalling; and can dysregulate local metabolism, compromising energy production. Obesity-induced dyslipidaemia can therefore result in dysfunction in numerous types of tissues, including that of the CNS and PNS.

Effects of obesity on the CNS Accumulating evidence indicates that obesity adversely affects the CNS and, in particular, cognitive function. For example, meta-analyses have shown a strong association between obesity and neurological disorders, such as Alzheimer’s disease and other dementias.13,14 Epidemiological evidence indicates that obesity doubles the risk of Alzheimer’s disease when compared with that www.thelancet.com/neurology Vol 16 June 2017

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CNS Risk of mild cognitive impairment and Alzheimer’s disease Adipose tissue Caloric excess

Decreased FFA uptake Circulation ↑ FFA flux

Adipocyte hypertrophy, altered adipokine secretion, and inflammation

Increased lipolysis

Autonomic nerves

Sympathetic tone

Peripheral nerves

Risk of polyneuropathy

Ectopic fat deposition

FFAs VLDL triglycerides Liver

Muscle

Pancreas

Insulin resistance and tissue dysfunction Risk of metabolic syndrome

Figure 1: Neurological consequences of obesity Increased caloric intake and decreased energy expenditure result in a net energy overload, leading to adipose tissue expansion (hyperplasia and hypertrophy). Sustained caloric excess in visceral adipose tissue activates resident macrophages, contributing to adipose tissue dysfunction and metabolic inflammation. When circulating free fatty acids increase, they become lipotoxic to peripheral tissues and contribute to the development of metabolic dyshomoeostasis. Their high flux into the liver increases VLDL triglyceride production, further promoting dyslipidaemia, while fat deposition in the muscle promotes insulin resistance and fat deposition in the pancreas promotes β-cell dysfunction. Collectively, these impairments lead to metabolic syndrome. The CNS and PNS are also detrimentally affected by obesity and obesity-induced metabolic dysfunction, which we hypothesise is driven by the lipotoxic effects of dyslipidaemia and increased circulating free fatty acids. In the CNS, dysfunction can lead to mild cognitive impairment and eventually Alzheimer’s disease, whereas in the autonomic nerve system the end result is autonomic neuropathy and, in the PNS, peripheral neuropathy. FFAs=free fatty acids.

of individuals of healthy bodyweight,13 and that a higher body-mass index (BMI) in midlife predicts greater risk of dementia in later life.15 Furthermore, data from a postmortem study showed that elderly patients with morbid obesity displayed higher concentrations of hippocampal markers associated with Alzheimer’s disease (amyloid β and tau) than those who were not obese.16 Mild cognitive impairment occurs well before frank dementia, and several prospective studies17–21 have shown that obesity confers increased risk of mild cognitive impairment, independent of age (table 1). Although there is some controversy (one study reported that lower weight in the elderly predicts mild cognitive impairment,22 and another reported no increase of mild cognitive impairment risk with high BMI23), several studies indicate that a high BMI can be associated with attention deficits, poor executive function, impaired decision making, and decreased verbal learning and memory. Individuals with severe obesity can have mild cognitive impairment,24 and children and adolescents who are obese, and those with metabolic syndrome,25 can display lower cognitive function than those who are not www.thelancet.com/neurology Vol 16 June 2017

obese or do not have metabolic syndrome.26 Reports also suggest that men who are obese are more susceptible than women to mild cognitive impairment,17 with obese men also displaying greater brain atrophy than obese women27 which might be due to an oestrogen-dependent protection from components of the metabolic syndrome.28 In mild cognitive impairment and Alzheimer’s disease, symptoms might be a consequence of structural changes in the brain and decreased cerebral integrity, particularly in the hippocampus—a structure essential for learning and memory that is susceptible to ageingrelated atrophy.29 Patients with Alzheimer’s disease show brain atrophy in the medial temporal lobe, which contains the hippocampus, while patients with mild cognitive impairment show a similar pattern of hippocampal loss, but to a lesser extent than those with Alzheimer’s disease.30 In patients with obesity or metabolic syndrome, there is also evidence for a decrease in hippocampal volume.31 Using CT, a crosssectional analysis showed that women with temporal lobe atrophy had higher BMI than women without atrophy,29 while longitudinal analysis of the same cohort 467

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Participants

Age

Location Study of study design

Elias et al (2005)17

551 men and 872 women

55–88 years USA

Prospective cohort

18 years* Individuals were divided into groups of healthy bodyweight, overweight, or obese

Obesity was associated with adverse Eight subtests: logical cognitive effects in men but not memory-immediate recall, visual reproductions, paired associates learning, women digit span forward, digit span backward, word fluency (Controlled Oral Word Associations), similarities, and logical memory-delayed recall

Cournot et al (2006)18

1660 men and 1576 women

32–62 years at baseline

France

Prospective cohort

··

Word-list learning and recall; digit-symbol Cross-sectional analysis: participants with higher BMI had lower cognitive substitution test, attention test; scores; prospective analysis: a higher delayed-free recall test BMI predicted a higher cognitive decline

Sabia 3788 men and et al (2009)19 1343 women

35–55 years at baseline

UK

Prospective cohort

Cohort consisted of 36 years only white individuals

Mini-Mental State Examination and tests of memory and executive function

Hassing 140 men and et al (2010)20 277 women

50–60 years Sweden at baseline

Prospective cohort

Swedish twin registry

Testing of long-term memory, short-term Overweight in midlife was associated with lower overall cognitive function memory, speed of memory recall, and in old age verbal and spatial ability

Dahl 280 men and et al (2013)21 377 women

25–50 years at baseline

Prospective cohort

Swedish adoption and 21·4 years twin study of ageing

Sweden

Additional information

Followup

5 years

30 years

Cognitive tests

Observations

Verbal, spatial and fluid, memory, and perceptual speed were tested

Cumulative effect of obesity on cognition

Overweight or obesity in early midlife predicted lower cognitive function and cognitive decline in late life

*This study involved an 18-year continuous assessment of diabetes and obesity up to the timepoint when neuropsychological testing was done. Two analyses were done. In the first analysis, the surveillance period preceded the neuropsychological testing by 4–8 years; whereas in the second analysis, the surveillance period was redefined allowing for an examination of the effects of risk factors up to, and including, the time of cognitive testing. The authors report that the findings of the study were the same for both surveillance groups.

Table 1: Clinical studies showing an association between obesity and cognitive impairment

revealed that BMI was a predictor for temporal lobe atrophy.29 MRI analysis has also shown an inverse relationship between BMI and brain volume32 and neuronal viability,33 and BMI correlates with gliosis in the hypothalamus that is coincident with obesity.34 Likewise, voxel-based morphometry has revealed a relationship between BMI and grey matter ratio (ie, the percentage of grey matter volume in the intracranial volume), with grey matter volume in the medial temporal lobes, anterior lobe of the cerebellum, occipital lobe, frontal lobe, precuneus, and midbrain showing negative correlations with BMI.27,35 Use of tensor-based morphometry to examine grey and white matter volumes in a bivariate analysis of elderly patients with normal cognitive function linked increased BMI, hyper­ insulinaemia, and type 2 diabetes to atrophy in frontal, temporal, and subcortical brain regions.36 In the same study, ANCOVA analyses showed atrophy in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus of patients who were obese compared with those of healthy BMI when controlling for age, sex, race, and type 2 diabetes.36 Individuals with a high BMI displayed brain atrophy in the frontal lobe, hippocampus, and thalamus when compared with individuals who were not obese.36 Children and adolescents with high BMI have also been reported to have decreased volume of frontal and limbic cerebral grey matter regions,37 and decreased hippocampal volume compared with children with healthy BMIs.25 The hippocampus and prefrontal cortex, which are particularly vulnerable to obesityrelated changes,38 are essential for learning and memory, and reduction in hippocampal volume correlate with 468

declines in memory performance.39 In fact, increased hippocampal atrophy in patients with mild cognitive impairment can predict the development of Alzheimer’s disease.40

Mechanisms underlying cognitive impairment Consistent with clinical data, numerous experimental studies using animal models of high fat diet-induced obesity have revealed modifications in hippocampal structure and function, and these animals also have learning and memory deficits, and impaired executive function.41–47 These animal models provide insights into the mechanisms underlying obesity-induced cerebral changes. For example, long-term potentiation in the hippocampus, considered to be a major mechanism in learning and memory, is impaired in high fat diet-fed mouse models.48,49 A high fat diet also leads to a reduction in markers of neurogenesis, synaptic plasticity, and neuronal growth, such as BDNF.50,51 Many studies that involve the use of these animal models provide strong evidence that hypothalamic inflammation is an early step in a vicious feed-forward cycle of CNS dysfunction leading to cognitive decline.34 The hypothalamus is pivotal in maintaining energy homoeostasis by regulating food intake and energy expenditure.52 To rapidly monitor and regulate metabolic homoeostasis, the hypothalamus senses circulating nutrients and hormones via the median eminence, which has a unique capillary system and, importantly, integrates these signals of satiety and nutritional status through neuroendocrine and autonomic signalling.53 Notably, the median eminence is not protected by the www.thelancet.com/neurology Vol 16 June 2017

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blood–brain barrier, which possibly contributes to its vulnerability to circulating factors such as free fatty acids and inflammatory adipokines. Early markers of inflammation, including TNFα and microglial activation, are present in the arcuate nucleus of the hypothalamus in these animal models of obesity.54 Hypothalamic inflammation is an early acute response to elevated concentrations of free fatty acids: after one day of high fat diet feeding, inflammatory markers, including TNFα, are present in the mediobasal hypothalamus,34 and inflammation occurs in the hypothalamus earlier than in adipose tissue or peripheral blood.55 Glial cell activation is an early essential step in high fat dietinduced hypothalamic inflammation, with microglial and astrocyte reactivity.34 In particular, microglia have been proposed as the sensors of diet-induced hypothalamic inflammation because they express tolllike receptor 4 (TLR4), which recognises long-chain fatty acids (LCFAs).56 In animal models of obesity, activation of TLR4 signalling by high fat diet feeding promotes cytokine production (TNFα, interleukin 1β, and interleukin 6),57 activation of endo­ plasmic reticulum stress pathways,58 and subsequent activation of the c-Jun N-terminal kinase (Jnk)54 and inhibitor of κB kinase β/nuclear factor-κB (IKKβ/NF-κB)56,58,59 pathways, resulting in the propagation of pro-inflammatory signalling and promotion of gliosis in the hypothalamus.34 Inflammation can cause further downstream dyslipi­ daemia by compromising the neural circuitry governing satiety control (figure 2A).57 In animals that are obese, leptin-induced satiety is blunted,60 although leptin concentrations in blood positively correlate with adipose tissue mass, and increased hypothalamic inflammatory signalling leads to leptin resistance. This inflammatory signalling can impair appetite control mediated by hypothalamic proopio­ melanocortin neurons, which function to reduce appetite and increase energy expenditure. Moreover, high fat diet feeding leads to apoptosis in hypothalmic nuclei, resulting in decreased inhibition of feeding.61 Dysregulation of satiety signalling promotes hyperphagia, and increases susceptibility to obesity,60 while loss of proopio­ melanocortin neurons contributes to weight gain.62 In addition to inflammation, altered metabolism of free fatty acids might contribute to changes in CNS function. Cerebral uptake of free fatty acids is higher in individuals who are obese than in those with a healthy weight,63 and evidence from animal studies suggests that free fatty acids are not completely catabolised in the hypothalamus but instead accumulate as long chain acylCoA esters and other bioactive lipids.59 Diacylglycerols and ceramides are present in the hypothalamus of high fat diet-fed mice64 and Zucker fa/fa rats, a model of obesity and type 2 diabetes as a consequence of a leptin receptor mutation.65 It has been shown that palmitate induces ceramide production in primary hypothalamic neurons in vitro.66 These bioactive lipid molecules www.thelancet.com/neurology Vol 16 June 2017

A Mediobasal hypothalamus Second-order neuronal populations

Inflammation

Median eminance

Arcuate nucleus containing proopiomelanocortin and Agouti-related peptide

Diet-derived saturated fatty acids

B Dorsal root

Obesity

Dorsal root ganglia Epineurium

C-fibre nerve ending Epidermis

Perineurium Unmyelinated axons

Dermis

Thinly myelinated axon Myelinated axon Blood vessels Fascicle Endoneurium

Mitochondria Ca2+ overload ↑Acylcarnitine Depolarisation ↑Reactive oxygen species Altered mitochondrial trafficking

Endoplasmic p reticulum Endoplasmic reticulum stress 2+ Altered Ca homoeostasis Altered endoplasmic reticulum—mitochondria tethering

Figure 2: Neurological complications associated with obesity and dyslipidaemia (A) Diet-modified hypothalamic function in the CNS. The hypothalamus is responsible for controlling global energy balance by monitoring metabolic homoeostasis. Diet-derived saturated fatty acids can enter the CNS via the median eminence and accumulate in the mediobasal hypothalamus. In response to saturated fatty acids, resident hypothalamic microglia become activated, resulting in inflammation, gliosis, and neuronal stress. Pro-inflammatory signalling in the arcuate nucleus (ARC) is associated with the development of impaired leptin signalling in the proopiomelanocortin (POMC) and Agouti-related peptide (AgRP) neurons that in turn can affect second-order neurons that govern energy balance. Hypothalamic inflammation alters satiety control, thus increasing the risk of developing obesity. (B) Overview of obesity-mediated PNS injury. As a consequence of obesity, increased concentrations of free fatty acids lead to decreased neurotrophic support and increased neurodegeneration in peripheral nerves. Long-chain fatty acids and inflammatory mediators directly injure the dorsal root ganglia neurons, C-fibre cutaneous nerve endings, and the blood–nerve barrier. As the blood–nerve barrier gets compromised, axons and their associated Schwann cells become vulnerable to injury, leading to neurogenic inflammation, mitochondrial dysfunction, and endoplasmic reticulum stress. Together, these changes alter nerve structure and function, and contribute to the development of polyneuropathy. PNS=peripheral nervous system. FFAs=free fatty acids.

activate IKKβ and promote hypothalamic insulin resistance.59,64,65 Moreover, stimulating fatty acid catabolism in hypothalamic neurons in vitro reduces neuronal inflammation by decreasing production of bioactive lipids,66 a finding that supports a potential role for lipotoxicity in hypothalamic dysfunction. Although hypothalamic injury can occur in response to increased dietary fat very early (1–3 days) before the development of obesity,34 inflammation, metabolic 469

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dysfunction, and a paucity of satiety, in combination with alterations in free fatty acids, triglycerides, and insulin resistance, can contribute in a multifactorial manner to establish a feed-forward cycle of injury that eventually affects other brain regions, most importantly the hippocampus. Hippocampal injury occurs in high fat dietfed animals in response to increased blood–brain barrier permeability,67 as a consequence of reactive glial cytokine production and circulating pro-inflammatory adipokines.68 Free fatty acids and triglycerides have also been shown to directly alter hippocampal function,51 and insulin resistance has been linked to neurocognitive dysfunction69 and shown to decrease hippocampal function in animal models and in human beings.70 Unchecked entry—ie, increased permeability of the blood–brain barrier—of proinflammatory proteins into the hippocampus can initiate or amplify neuroinflammation and promote neuro­ degeneration.71,72 Increased permeability of the blood–brain barrier and markers of hippocampal inflam­ mation, including microglial activation, are detected by 20 weeks of age in high fat diet-fed animals.73 Over time, increased permeability allows free or unrestricted entry of cytokines and chemokines, immune cells,74 free fatty acids, and triglycerides51 that further potentiate hippocampal injury, and subsequent atrophy. These findings provide a mechanistic link between blood–brain barrier breakdown and impaired cognition in obesity.

Effects of obesity in the PNS The PNS is divided into the autonomic nervous system, with the sympathetic and parasympathetic divisions, and the somatic nervous system, composed of the sensory and motor peripheral nerves. The autonomic and sensory ganglia, along with unmyelinated fibres and synaptic terminals of the PNS are not protected by the blood–brain barrier, and are therefore susceptible to the pathophysiological consequences of obesity. The autonomic nervous system plays a crucial role in regulating energy balance through its control of anabolic and catabolic processes and its close relationship with the hypothalamus. The autonomic nervous system is particularly sensitive to obesity-induced perturbations, and dysfunction in this system is often present in young individuals who are overweight.75 Obesity is associated with an imbalance between the sympathetic and para­ sympathetic divisions of the autonomic nervous system. Increased sympathetic outflow to neuro-adipose junctions stimulates lipolysis via stimulatory G-protein coupled β adrenoceptors. This increased sympathetic outflow triggers a downstream signalling pathway that ends with the activation of adipose triglyceride lipase, resulting in triglyceride hydrolysis. Thus, sympathetic hyper­activation can promote a feed-forward mechanism leading to an increased pool of circulating LCFAs.76 Increased sympathetic outflow to the cardiovascular system also results in increases in heart rate, blood pressure, and microvasculature tone. Sustained sympathetic outflow is 470

speculated to decrease perfusion, and in turn these physiological changes promote further neurological dysfunction in both the CNS and PNS.

Obesity and polyneuropathy Polyneuropathy is clinically defined as the distal-toproximal loss of sensory perception, affecting initially the feet but over time also the hands. Frequently referred to as a stocking-glove loss of sensation, polyneuropathy occurs when there is a distal-to-proximal loss of sensory axons, with motor axons only involved in very severe or end-stage disease. The most common causes of polyneuropathy in high-income countries are prediabetes and type 2 diabetes. However, a systematic review of clinical trials in patients with type 2 diabetes in whom polyneuropathy was measured, including several large multicentre trials, suggested that glucose-lowering therapies have little effect on the prevention of polyneuropathy in patients with type 2 diabetes.77 These unanticipated results suggest that other metabolic syndrome components, which are present in more than 75% of patients with type 2 diabetes, play a role in the pathogenesis of polyneuropathy. In support of this hypothesis, we have reported78 that the likelihood of polyneuropathy increased as did the number of metabolic syndrome components in the Health, Aging, and Body Composition (Health ABC) study (N=2382), independently of glycaemic control. These findings78 confirm those of several reports indicating that obesity alone is an independent risk factor for polyneuropathy,79 including multiple clinical studies linking obesity with polyneuropathy (table 2).78–83 Lipid profiles are often atypical early in the disease course of patients with type 2 diabetes and correlate with the early onset of polyneuropathy,84 and triglycerides are associated with polyneuropathy progression in patients with diabetes.85 Moreover, elevated triglycerides are sub­ stantially higher in patients with idiopathic poly­ neuropathy than in those without idiopathic poly­neuro­pathy.86 Prediabetes, which is highly prevalent in individuals who are obese, is also associated with polyneuropathy.80,87–89 Taken together, these data suggest a role for obesity, prediabetes, and dyslipidaemia in the pathophysiology of polyneuropathy.

Mechanisms underlying PNS injury Sensory nerves consist of neurons within the dorsal root ganglia, their axons, and supporting Schwann cells, with each nerve covered by a connective tissue layer known as the epineurium. A second connective tissue layer known as the perineurium surrounds groups of nerves to form nerve fibres, and bundles of nerve fibres are encapsulated along with blood vessels by the final layer of connective tissue, the endoneurium, to form sensory, motor, or mixed sensorimotor nerves. Similar to the blood–brain barrier, the PNS has a blood–nerve barrier consisting of endoneurial microvessels and the perineurium. www.thelancet.com/neurology Vol 16 June 2017

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Participants Location of (N) study

Aim

Health ABC; Callaghan et al (2016)78

2382

Pittsburgh and Memphis, USA

Waist circumference associated with Determine the association of metabolic Questionnaire plus at least one of three syndrome components with polyneuropathy confirmatory tests (heavy monofilament, peroneal polyneuropathy conduction velocity, or vibration threshold)

EURODIAB; Tesfaye et al (2005)79

1172

Europe

Identify risk factors for polyneuropathy in patients with type 1 diabetes

Clinical evaluation, quantitative sensory testing, and autonomic-function testing

Higher BMI, total cholesterol, and VLDL cholesterol significantly associated with polyneuropathy

MONICA/KORA Study; Ziegler et al (2008)80

393

Augsburg, Germany

Identify risk factors for polyneuropathy in patients with impaired glucose tolerance

Michigan neuropathy screening instrument to establish polyneuropathy

Waist circumference associated with polyneuropathy

2035

Shanghai, China

Identify risk factors for polyneuropathy in patients with impaired glucose tolerance

Foot examination or neuropathy symptom and disability scores

Waist circumference associated with polyneuropathy in patients who were not diabetic

SH-DREAMS Study; Lu et al (2013)81

Methodology

Observations

PROMISE Study; Lee et al (2015)82

467

Toronto and Ontario, Canada

Establish the association of metabolic syndrome components with polyneuropathy risk

Vibration perception thresholds to measure nerve Increased waist circumference confers increased neuropathy risk dysfunction; Michigan neuropathy screening instrument to establish polyneuropathy

Utah Study; Smith et al (2008)83

219

Utah, USA

Identify whether features of metabolic syndrome other than hyperglycaemia increase polyneuropathy risk

Clinical diagnosis and nerve conduction studies, and skin biopsy for measurement of epidermal nerve fibre density to confirm when necessary

Lipid abnormalities observed in patients with polyneuropathy

PROMISE=Prospective Metabolism and Islet Cell Evaluation. MONICA/KORA=Monitoring Trends and Determinants on Cardiovascular Diseases/Cooperative Research in the Region of Augsburg. SH-DREAMS=ShangHai Diabetic neuRopathy Epidemiology and Molecular Genetics Study. EURODIAB=European Diabetes Prospective Complications Study. Health ABC=Health, Aging, and Body Composition Study. BMI=body-mass index.

Table 2: Clinical studies suggesting an association between obesity and polyneuropathy

However, sensory neurons, specifically dorsal root ganglion neurons, and peripheral sensory receptors lie outside of the blood–nerve barrier, allowing them to be exposed to systemic metabolic insults that make them susceptible to injury. The blood–nerve barrier protects the peripheral nerves in the same fashion as the blood– brain barrier protects the CNS, except for two important exceptions: dorsal root ganglia and all sensory nerve endings in the skin do not have the blood–nerve barrier. These two unprotected components of the PNS along with the endoneurial microvessels and the perineurium of the blood–nerve barrier are susceptible to initial obesity-mediated inflammatory injury with cor­ responding loss of function (figure 2B). To reveal the mechanisms underlying obesity-mediated PNS injury, several studies have used high fat diet-fed mice that develop obesity, dyslipidaemia, prediabetes, and polyneuropathy, but not type 2 diabetes.90 LCFAs and inflammatory mediators, which are found in these animals,91 can injure and penetrate the blood–nerve barrier and activate neurogenic inflammation in the PNS.92 In response, neurons of the dorsal root ganglia release vasoactive and chemoattractant signals to increase vasculature permeability and attract innate and adaptive immune cells to sites of damage. Although this response is initially protective, chronic dysfunction secondary to obesity-mediated inflammation can lead to changes in nerve structure, and subsequent pain.92 Moreover, these animal show increased accumulation of macrophages in peripheral nerves, increased expression of TNFα and interleukin 1β mRNA, and polyneuropathy,91 all without developing type 2 diabetes.90 Studies using animal models of obesity and type 2 diabetes with microvascular complications also support a www.thelancet.com/neurology Vol 16 June 2017

role for lipotoxicity in polyneuropathy. Gene expression analyses of peripheral nerves of ob/ob and db/db mice, mouse models of obesity and diabetes with impaired leptin signalling, have identified dysregulation of inflammation as early as 5 weeks of age.93 In db/db mice, treatment with pioglitazone improved small fibre function and cutaneous innervation;94 and in Zucker fa/fa rats, treatment with acipimox normalised sensory nerve conduction velocities and alleviated thermal and mechanical hypoalgesia, independently of prediabetes.95 Pioglitazone is known to lower triglycerides, and acipimox is known to reduce free fatty acids; however, these drugs also exert effects on other metabolic and endocrine measures, which might contribute to their effectiveness for polyneuropathy. Together, these data suggest a role for obesity and lipidinduced inflammation in polyneuropathy. As in the CNS, evidence suggests that obesity-mediated increases in free fatty acids and LCFAs alter healthy lipid metabolism in the PNS. Excess LCFAs promote increased mitochondrial β-oxidation in Schwann cells96,97 that is coincident with polyneuropathy.98,99 Products of LCFA metabolism, such as long-chain acylcarnitines, accumulate in peripheral nerves of mice97 and these bioactive lipids are associated with Schwann cell dysfunction,96 axonal degeneration,97 and polyneuropathy. Accumulation of LCFAs or long chain acylcarnitines in non-obesity-mediated diseases affecting mitochondrial β-oxidation also results in polyneuropathy, strengthening the association between aberrant lipid metabolism and PNS dysfunction.100 Injury to the PNS by LCFAs also occurs when excess LCFAs in Schwann cells induce endoplasmic reticulum dysfunction that includes a decrease in Ca²+ content of the endoplasmic reticulum, followed by endoplasmic 471

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Panel 2: Neurological consequences of obesity Central nervous system Structural effects • Brain atrophy and reduced grey matter volume in frontal and temporal lobes, and enlarged orbitofrontal white matter • Decreased volume of the hippocampus and hypothalamus, measured by structural MRI Physiological effects • Cerebral ischaemia and hypoperfusion • Altered brain metabolism and nerve function Clinical effects • Altered feeding behaviour and satiety control • Mild cognitive impairment (attention, learning, and memory deficits, and impairments in decision making), cognitive decline, and increased risk of Alzheimer’s disease and other dementias • Mood disorders, including anxiety and depression Peripheral nervous system Structural effects • Organ damage due to chronic activation of the sympathetic nervous system • Loss of peripheral sensory neurons and small intraepidermal nerve fibres Physiological effects • Blunted but chronic activation of sympathetic nervous tone resulting in increased efferent muscle activity, cardiac output, adrenaline release from adrenal medulla, adipose tissue lipolysis, and liver gluconeogenesis, and decreased release of pancreatic insulin • Gastroparesis and intestinal dysmotility • Decreased motor and sensory nerve function Clinical effects • Symptoms of sensory polyneuropathy, including early onset pain, paraesthesias, allodynia, and hyperalgesia, that over time can lead to numbness and loss of sensory perception • Symptoms and signs occur in a stocking-glove distribution

reticulum stress, mitochondrial depolarisation, and generation of toxic reactive oxygen species.101 As anticipated, these LCFA-mediated markers of endo­ plasmic reticulum dysfunction are present in the PNS of fa/fa rats and high fat diet-fed mice with polyneuropathy, supporting their role in disease pathogenesis.102 In parallel, LCFA-induced endoplasmic reticulum dysfunction also negatively affects mito­ chondrial ATP production in nerves, which is required for normal nerve physiology. It is well established that tightly regulated Ca²+ release of the endoplasmic reticulum is crucial for proper mito­chondrial Ca²+ uptake and ATP production. This delicate balance is disrupted in the nerves of high fat diet-fed mice with polyneuropathy, in which disruption of endoplasmic reticulum–mitochondrial tethering results in mitochondrial Ca²+ overload and impaired ATP production.103 Together, these results suggest that disruption of Ca²+ transport between the endoplasmic reticulum and the mito­chondria in the PNS contributes to obesity-mediated polyneuropathy, and supports the idea 472

that LCFA-induced endoplasmic reticulum stress in Schwann cells acts in a feed-forward manner to disrupt ATP mitochondrial energy production and to promote further nerve injury. Finally, mitochondrial trafficking from neuronal cell bodies along the length of the axons is required to deliver ATP for normal nerve function and, in human beings, this axonal length can be greater than 1 m. Because mitochondrial trafficking is an ATP-dependent process,104 compromised ATP generation during obesity can disrupt mitochondrial trafficking in a feed-forward loop, resulting in even greater peripheral nerve damage.

Neurological benefits of targeting obesity Because obesity and dyslipidaemia can provoke highly morbid neurological consequences (panel 2), the optimal therapy is to target obesity itself. Lifestyle interventions, consisting of dietary modifications combined with exercise, provide an accessible and inexpensive strategy that is effective in combating obesity and restoring neurological function (table 3). The physiological benefits of lifestyle interventions, which are greatest when dietary and exercise regimens are used in concert, improve the metabolic profile and strongly correlate with improved cognitive and nerve functions. General physiological benefits include improved cellular metabolism, restoration of glucose and insulin homoeostasis, decreased metabolic inflammation, and improved lipid profiles. For example, in a prospective controlled clinical trial, 80 elderly patients (aged ≥60 years) with mild cognitive impairment and an average BMI of 35·5 were randomly assigned to either medical care alone or medical care with nutritional counselling to promote weight loss through caloric restriction. After 12 months, two patients had dropped out from the caloric restriction cohort and the remaining 38 patients had improved verbal memory, verbal fluency, executive function, and global cognition.105 Moreover, in a double-blind, randomised controlled trial of 2654 individuals (aged 60–77 years) who were screened, 1260 were randomly assigned to an intervention group (n=631), consisting of dietary intervention coupled with increased exercise and cognitive training over a 2-year period, or control group (n=629). The primary outcome was change in cognition as measured through a comprehensive neuropsychological test battery (NTB) Z score. The estimated mean change in NTB total Z score at 2 years was 0·20 (SD 0·51) in the intervention group and 0·16 (0·51) in the control group. Between-group difference in the change of NTB total score per year was 0·022 (95% CI 0·002–0·042; p=0·030).106 In a randomised trial of 22 patients (aged 60–80 years) with mild cognitive impairment, evaluation of the effect of two 6-month interventions (target intervention of combined omega-3 fatty acid supplementation, aerobic exercise, and cognitive stimulation [n=13] vs control intervention of omega-3 fatty acid supplementation and non-aerobic exercise [n=9]) on cognitive function and grey matter volume showed that the target intervention positively benefited brain structure www.thelancet.com/neurology Vol 16 June 2017

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Partici­ Mean age of participants pants (N)

Method

Study duration

Metabolic selection criteria

Metabolic observations

Neurological observations

BMI ≥30

Decreased BMI (1·7 [range –0·1 to 3·5]); improved HOMA; and decreased CRP

Improved memory, cognition, and executive function

Baseline BMI 28·3 (no exclusions)

Decreased BMI (0·49 [range 0·44–0·54])

Improved processing speed and executive function

Cognitive impairment, dementia risk, and cerebral volume or integrity Horie et al (2016)105

80

Ngandu et al (2015)106

1260

Kobe et al (2015)107

Witte et al (2009)108

≥60 years

Caloric restriction

69·3 (64·7–74·0) years

Diet, exercise, and 24 months cognitive training

22

60–80 years

Omega-3 supplementation, exercise, and cognitive stimulation

6 months

NA

No significant metabolic improvements Preserved and increased grey matter volume in intervention group compared with those in control group, but no improvements in cognitive function in intervention group

50

60·5 (52·9–68·1) years

Caloric restriction

3 months

Healthy bodyweight to overweight (mean BMI 28 [range 24·3–31·7])

Decreased BMI (0·8), CRP (0·22 pg/mL), and insulin (3·5 µIU/mL)

Improved memory performance (increase in verbal memory score)

124

52·3 (42·7–61·9) years

Caloric restriction, dietary changes, and exercise

4 months

BMI 25–40 (mean BMI 32·8 [range 29–36·6])

Decreased BMI (3·3), improved cardiovascular fitness, and reduced blood pressure

Improved executive function– memory–learning and psychomotor speed

Siervo et al (2012)110

21

56·9 (47·2–66·6) years

Intentional weight loss

About 4 months

BMI 30–50 (mean BMI 36·7)

Decreased BMI (3·5) and fat mass (7·5kg) Improvements in hand-grip strength and cognitive function (Mini-Mental State Examination, short portable mental status questionnaire, and trailmaking test)

Napoli et al (2014)111

28

70 (66–74) years

Caloric restriction and exercise

12 months

BMI 37·2 (range 31·8–42·6)

Decreased bodyweight (8·6 kg [range 4·8–12·4]), visceral fat (787 cm³ [–109 to 1683]), and CRP (1·8 mg/dL [–1·6 to 5·2]); and increased insulin sensitivity

Improvement in cognitive function (Mini-Mental State Examination, word fluency test, and trail-making test)

Brinkworth et al (2009)112

106

50 (49·2–52·8) years

Caloric restriction

12 months

BMI 33·7 (range 33·3–34·1)

Decreased bodyweight (13·7 kg [11·9–15·5]), plasma glucose (5·4 mg/dL), and insulin (3·6 µIU/mL)

Improved working memory (digit span backward test)

20*

61·1 (59·5–62·7) years

Dietary intervention

BMI 27–40

Decreased BMI (3·6), waist circumference (4 cm), plasma insulin (1·3 µIU/mL), and FFAs (0·13 mmol/L)

Improved memory performance, and increased hippocampal brain activity observed with the use of MRI

Smith et al (2006)114

32

60 (51·6–68·4) years

Diet and exercise

12 months

Baseline BMI 32·1 (range 27·7–36·5; pre-diabetics selected)

Decreased BMI (1·1 [range –0·3 to 2·5]) and total cholesterol (10·6 mg/dL [–9·5 to 30·7])

Increased intra-epidermal nerve innervation; decreased neuropathic pain

Singleton et al (2014)115

174

30–70 years

Exercise

12 months

Patients with type 2 diabetes Increased HDL (0·2 mg/dL [–5·8 to 6·2])

Increased intra-epidermal nerve innervation

Singleton et al (2015)116

36

55 Exercise (44·9–64·5) years

6 months

Metabolic syndrome

Increased intra-epidermal nerve reinnervation

Zeve et al (2013)117

17

44·9 (18–60) years

Smith et al (2010)109

Boraxbekk et al (2015)113

12 months

6 months

Polyneuropathy

Bariatric surgery

12 months

No significant metabolic improvements

Patients with morbid obesity Improved BMI (15·4 [range 13·7–17·1]), (BMI ≥40) fasting glucose (99·7 mg/dL [85·1–114·3]), HbA1C (2% [1·4–2·6]), C-peptide (1·8 ng/mL [1·3–2·3]), insulin (19·4 μU/mL [15·4–23·4]), and HOMA-insulin resistance

Percentage of patients with neuropathy 12 months after surgery was lower than that at baseline (31·3% vs 52·9%)

BMI=body-mass index. HOMA=Homeostatic Model Assessment. NA=not applicable. CRP=C-reactive protein. FFAs=free fatty acids. HbA1C=glycated haemoglobin A1c. *Study sample included only women.

Table 3: Benefits of lifestyle intervention and surgery on neurological complications

and function by preventing the decline in grey matter volume of the frontal, parietal, and cingulate cortex in these patients. Not only was the grey matter preserved in these areas but there is evidence that the target intervention can lead to an increase in grey matter volume.107 In a non-controlled, observational, prospective study evaluating the effect of lifestyle intervention on polyneuropathy, 32 patients with polyneuropathy who were overweight or obese (mean age of 60 years) were www.thelancet.com/neurology Vol 16 June 2017

assessed for polyneuropathy at baseline and at a 12 month follow-up. Polyneuropathy was assessed by nerve conduction studies, quantitative sensory testing, quantitative sudomotor axon reflex testing, and the Michigan neuropathy screening instrument. In addition to BMI, 2-h oral glucose tolerance tests were done, and serum lipid concentrations were measured. These patients placed on a diet and exercise regimen exhibited increased cutaneous nerve fibres as a marker of 473

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polyneuropathy improvement, along with decreased neuropathic pain.114 Increased exercise alone can increase cutaneous nerve density in patients with type 2 diabetes without neuropathy as shown in a prospective trial evaluating the effect of supervised exercise versus lifestyle counselling on cutaneous nerve density in patients with diabetes but without neuropathy,115 and in patients with metabolic syndrome as shown in a non-controlled, observational, prospective study evaluating the effect of supervised exercise on polyneuropathy in two groups (ie, patients with metabolic syndrome vs patients with metabolic syndrome and type 2 diabetes).116 A randomised, controlled, prospective study showed that the sympathetic and parasympathetic nervous system imbalance that is observed in obesity is also modifiable by dietary intervention.118 Finally, animal studies support the findings in human beings and also show that resolving obesity improves cognitive performance.119–121 Switching mice from a high fat diet to a regular diet to reduce caloric intake results in improved metabolic health, with increased insulin sensitivity and improvement in cognitive function. These improvements are associated with reduced blood–brain barrier leakage, decreased glial activation, and increased vascular perfusion.119–121 Although diet and exercise interventions are the ideal therapeutic regimen, compliance is a concern that supports a role for pharmacotherapy and bariatric surgery in the treatment of obesity-mediated neurological disorders. An observational study of 342 patients with Alzheimer’s disease reported that treatment with lipid-lowering agents (statins or fibrates) was associated with a slower cognitive decline in Alzheimer’s disease.122 The Fremantle Diabetes Study showed that statin or fibrate treatment might protect against the development of polyneuropathy in people with type 2 diabetes,123 and the FIELD study showed that fenofibrate treatment resulted in fewer non-traumatic distal amputations than patients with type 2 diabetes provided with placebo, a consequence attributed to improved polyneuropathy.124 Despite these studies, more definitive clinical trials are Search strategy and selection criteria We searched PubMed and Google Scholar for articles published in English from Nov 2, 2015, to July 1, 2016, and examined original research articles and review articles. The following terms were used in various combinations: “obesity”, “dyslipidemia”, “adipose”, “adipocyte”, “inflammation”, “brain”, “Alzheimer’s disease”, “cognitive impairment”, “hypothalamus”, “hippocampus”, “high fat diet”, “autonomic nervous system”, “peripheral nervous system”, “peripheral neuropathy”, “lifestyle intervention”, “exercise”, and “bariatric surgery”. We used our judgment to select articles to provide a summary of the causes of neurological complications of obesity rather than aiming to provide an exhaustive list of all research.

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needed, and no clinical guidelines exist for the use of statins or fibrate in the treatment of CNS or PNS disorders. Bariatric surgical procedures, such as Roux-en-Y gastric bypass, are a highly effective treatment for patients who are morbidly obese.125 Although many patients regain weight and medical complications are frequent, postoperative patients can have profound improvements in metabolic homoeostasis and can show improved cognitive function126 (table 3) possibly due to improvements in adipokine,127 insulin,128 and inflammation signalling.129 One study showed decreased inflammation and reduced β-amyloid precursor protein expression in peripheral blood following bariatric surgery, leading the investigators to speculate that a similar benefit could have occurred in the hippocampus.130 Roux-en-Y gastric bypass surgery also improves poly­ neuropathy 1 year after the procedure.117 These surgical intervention studies support the pathogenic role of obesity in the CNS and PNS, but are not the treatment of choice because of the high prevalence of obesity worldwide. Use of invasive surgical procedures in a large population is not feasible, so alternative interventions focused on lifestyle changes are urgently needed.

Conclusions and future directions Although extensive data exist to support obesity as a mediator of CNS and PNS injury, the ideal intervention to prevent associated cognitive impairment, autonomic neuropathy, and polyneuropathy is not known. Future studies are needed to determine the comparative effectiveness of pharmacological weight loss, surgical weight loss, and exercise interventions using rigorous study designs and patient-oriented outcomes. These studies will also have to evaluate the cost-effectiveness of these different interventions. A combination of approaches might be ideal, but also requires multiple lifestyle changes in behaviour, which makes implementation difficult. Given the available data, clinicians should advise individuals who are obese, especially those that already have early evidence of CNS or PNS injury, to pursue at least one of the obesity interventions aforementioned. Increased visceral adiposity is a risk factor for the development of a wide range of neurological conditions, and obesity and the resulting metabolic disorders are one of the greatest medical challenges of the 21st century. Although the precise mechanisms of obesity-induced nerve and cognitive dysfunction need to be fully elucidated, obesity, insulin resistance, and dyslipidaemia converge as lipotoxicity, resulting in inflammation, neurological dysfunction, and neurodegeneration. While inflammation might play a crucial role in the development of neurological dysfunction, it is also possible that inflammation can be influenced by other pathways linked to obesity, such as oxidative stress, endoplasmic reticulum stress, sympathetic alterations, and metabolic dysfunction. Additional research is needed to identify the best treatment targets and most efficient combination of approaches to ensure positive health outcomes. Although pharmacotherapy and bariatric www.thelancet.com/neurology Vol 16 June 2017

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surgery have shown promising results, more research is necessary as, large-scale application of bariatric surgery is not feasible. On the basis of published reports, we maintain that lifestyle interventions consisting of dietary changes and increased activity should be adopted, because they are inexpensive and easily accessible. Contributors All authors contributed equally to the concept and design of the Review. PDO’B and LMH completed the literature search. PDO’B and LMH drafted and, with ELF, finalised the Review. BCC and ELF provided critical review of the manuscript. PDO’B created the figures. All authors have approved the final version. Declaration of interests BCC has received grants from the National Institutes of Health during the preparation and write-up of this Review; research support from Imepto; personal fees from Advance Medical and Medical Legal consulting; and grants and personal fees from Patient-Centered Outcomes Research Institute. ELF has received grants from the National Institutes of Health during the preparation and write-up of this Review. PDO’B and LMH declare no competing interests. Acknowledgments ELF and BCC received funding support from the National Institutes of Health (R24 DK082841 and R01 DK107956 to ELF; K23 NS079417 to BCC), the Novo Nordisk Foundation (NNF14SA0006), the Program for Neurology Research & Discovery, and the A Alfred Taubman Medical Research Institute. References 1 Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384: 766–81. 2 Grarup N, Sandholt CH, Hansen T, Pedersen O. Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond. Diabetologia 2014; 57: 1528–41. 3 Swinburn BA, Sacks G, Hall KD, et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet 2011; 378: 804–14. 4 NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet 2016; 387: 1377–96. 5 van Vliet-Ostaptchouk JV, Nuotio ML, Slagter SN, et al. The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies. BMC Endocr Disord 2014; 14: 9. 6 Tchoukalova YD, Votruba SB, Tchkonia T, Giorgadze N, Kirkland JL, Jensen MD. Regional differences in cellular mechanisms of adipose tissue gain with overfeeding. Proc Natl Acad Sci USA 2010; 107: 18226–31. 7 Acosta JR, Douagi I, Andersson DP, et al. Increased fat cell size: a major phenotype of subcutaneous white adipose tissue in non-obese individuals with type 2 diabetes. Diabetologia 2016; 59: 560–70. 8 Kloting N, Bluher M. Adipocyte dysfunction, inflammation and metabolic syndrome. Rev Endocr Metab Disord 2014; 15: 277–87. 9 Bartness TJ, Shrestha YB, Vaughan CH, Schwartz GJ, Song CK. Sensory and sympathetic nervous system control of white adipose tissue lipolysis. Mol Cell Endocrinol 2010; 318: 34–43. 10 Anderson EK, Gutierrez DA, Hasty AH. Adipose tissue recruitment of leukocytes. Curr Opin Lipidol 2010; 21: 172–77. 11 Hotamisligil GS, Shargill NS, Spiegelman BM. Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 1993; 259: 87–91. 12 Karpe F, Dickmann JR, Frayn KN. Fatty acids, obesity, and insulin resistance: time for a reevaluation. Diabetes 2011; 60: 2441–49. 13 Anstey KJ, Cherbuin N, Budge M, Young J. Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. Obes Rev 2011; 12: e426–37.

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