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Adiposity and Alzheimer’s Disease
Abstract
The objective of this manuscript is to provide a comprehensive review of the relation between adiposity and Alzheimer’s disease (AD), its potential mechanisms, and issues in its study. Adiposity represents the body fat tissue content. When the degree of adiposity increases it can be defined as being overweight or obese by measures such as the body mass index. Being overweight or obese is a cause of hyperinsulinemia and diabetes, both of which are risk factors for AD. However, the epidemiologic evidence linking the degree of adiposity and AD is conflicting. Traditional adiposity measures such as body mass index have decreased validity in the elderly. Increased adiposity in early or middle adult life leads to hyperinsulinemia which may lead to diabetes later in life. Thus, the timing of ascertainment of adiposity and its related factors is critical in understanding how it might fit into the pathogenesis of AD. We believe that the most plausible mechanism relating adiposity to AD is hyperinsulinemia, but it is unclear whether specific products of adipose tissue also have a role. Being overweight or obese is increasing in children and adults, thus understanding the association between adiposity and AD has important public health implications.
Burden and pathophysiology of Alzheimer’s disease
Alzheimer’s disease (AD) is the most common form of dementia, accounting for between 70% to over 90% of all cases [1], and its prevalence is expected to quadruple by the year 2047 [2]. As much as 50 % of the population aged 85 years and older, the fastest growing segment of the population, have AD [3]. There is consensus that AD results from the deposition of amyloid beta (Aß) in the brain [4], and risk factors for AD are thought to increase this deposition. The risk factors for AD can be classified as genetic and non-genetic. Three genes have been identified in Familial AD, Amyloid Precursor Protein (APP), Presenillin 1 (PS1), and 2 (PS2) [5]. These genes affect less than 5% of cases of AD, have full penetrance and expressivity, and usually affect persons in middle age [6]. Allelic variation in Apolipoprotein E (APOE) is also associated with familial AD beginning later in life, but neither the penetrance nor the mechanism by which this gene increases the risk of disease is understood. Interestingly, APOE variants are also related to risk of sporadic AD, that is, cases without an apparent familial history of the disease. Importantly, APOEe4 has been found to modulate the effect of other putative risk factors [7], such as diabetes and hyperinsulinemia [8, 9]. This review will focus primarily on non-genetic aspects of AD, which may be more frequent, occur in older people, and are potentially modifiable. In this review, we will discuss the link between adiposity and AD in the context of the current understanding of its pathophysiology.
Definition and burden of high adiposity
Adiposity refers to the amount of adipose (fat) tissue in the body [10]. Others refer to adiposity as “fatness” or obesity. In this review we restrict the use of the term obesity to one possible way to quantify elevated adiposity (Figure 1). Adiposity results from the balance of energy intake in the form of calories in the diet, energy expenditure from physical activity, and basal metabolic rate, which are influenced by individual genetic factors [11]. The contribution of genetic factors to adiposity is estimated to be 30 to 40%, while the contribution of the environment (diet and physical activity) is estimated to be 60 to 70% [11]. Adiposity is a continuum, and the normal or ideal threshold of adiposity is not clear. However, as adiposity increases it is associated with higher risk of insulin resistance, diabetes, hypertension, dyslipidemia, cardiovascular disease, degenerative joint disease, cancer, and respiratory diseases [11, 12]. Definitions of a high level of adiposity have been devised using existing measures and according to their relationship with adverse outcomes [13]. Adiposity is usually measured indirectly with anthropological measures [14] such as the body mass index (BMI), defined as weight in kilograms divided by height in meters squared (k/m2). BMI is strongly correlated with total body fat tissue and is a good indirect measure of adiposity[11], although this correlation decreases in older age [15]. A commonly used classification of BMI in the United States is the National Heart Lung and Blood Institute (NHLBI) [13] classification which classifies persons as underweight (BMI < 18.5), normal (BMI 18.5–25.9), overweight (26–29.9), and obese (≥ 30). Implicit in this classification is that overweight and obese persons have elevated adiposity compared to persons classified as normal that is related to increased morbidity and mortality [13]. Another commonly used measure of adiposity is waist circumference (WC). WC is meant to measure the accumulation of adipose tissue in the abdomen, the largest depot of adipose tissue, and thus, perhaps a more direct measure of adiposity [14, 16]. Elevated WC is also related to a higher risk of diabetes, hypertension, dyslipidemia, and heart disease, and some studies have shown that it is a better predictor of adverse cardiovascular outcomes compared to BMI [17], and some have advocated its use as the best measure of adiposity [14]. A commonly used cutoff to define elevated WC is 102 cm for men and 88 cm for women [17]. Other less frequently used anthropologic measures of adiposity include skinfolds and waist to hip ratio [14]. Whatever the measure used, BMI, WC, or other, it is important to understand that these are meant to correlate linearly with adiposity, and attempt to compare a higher and detrimental level of adiposity with a desirable level that in the case of the NHLBI BMI criteria has been defined as “normal” (Figure 1). Existing cutoffs are somewhat arbitrary and adiposity measures can be examined as continuous variables, or with different cutoffs such as tertiles, quartiles, or quintiles. For this review, we will use Figure 1 as a guide to the various definitions described in the literature.
Correlation between the construct of adiposity, body mass index (and the NHLBI classification), and waist circumference.
There are also techniques to directly assess body composition, that is, the quantity and proportion of the body that is adipose tissue compared to the proportion that is lean (muscle) tissue, such as dual energy X-ray absorptiometry (DEXA)[18], and bioelectrical impedance [19]. These techniques directly measure adipose tissue body content as compared to anthropological measures such as BMI, which are indirect correlates of adiposity. The use of these direct measures may overcome problems with the measurement of adiposity with BMI, particularly in the elderly. They are the ideal way to measure adiposity, but are more costly and cumbersome and are less commonly used in epidemiologic and clinical studies compared to BMI and WC.
Overweight and obesity [20] and waist circumference [21] are increasing in adults in the United States. More concerning, these trends are also observed in children and adolescents [22]. Two thirds of the United States Population are overweight or obese [22]; 30% are obese, and the prevalence of obesity is higher in women than men. Also, the prevalence of overweight and obesity are highest in Blacks and Hispanics compared to Whites [22, 23]. Thus it is necessary to clarify if elevated adiposity is a risk factor for AD and to elucidate the mechanisms.
Aging and measurement of adiposity
The association between increased BMI and both cardiovascular and general mortality is attenuated in older age groups. Curiously, high BMI becomes a predictor of decreased mortality in the oldest old [24], which may be due to survival bias and to decreased value of BMI as an adiposity measure in the oldest old. Aging is characterized by lean body mass loss and adipose tissue increase without weight gain that may not be captured by BMI, making traditional measures of adiposity less useful in the elderly [25]. On this basis, the use of the NHLBI classification for overweight of obesity has also been questioned in the elderly [26]. Thus, it seems that body composition should be assessed directly in the elderly to measure adiposity such as DEXA or bioelectrical impedance. Additionally, adiposity in older age may not reflect adiposity in younger age, and the timing of the exposure to adiposity in lifespan may be important in the pathogenesis of AD.
Non-genetic risk factors for Alzheimer’s disease and their relation to adiposity
Among demographic characteristics, old age [6], low education [27, 28], and being Caribbean-Hispanic or African American [29] have been related to a higher risk of AD. Weight decreases with aging and frailty [30], and BMI in older age may not reflect that of middle age. In the United States, higher adiposity has been related to lower education and socioeconomic position [31]. Being overweight or obese, are an indication of high adiposity, and are more prevalent in Blacks and Hispanics compared to Whites [23, 32]. Thus, it is possible that the association between adiposity and AD is confounded by age, socioeconomic and educational status, and ethnicity.
Among environmental risk factors, diet [33], physical activity [27], and vascular risk factors [34] have attracted increasing interest. The evidence for the link between various dietary factors and AD is conflicting [33] and no solid conclusions can be drawn at this time. In a cohort study of aging in Northern New York City the strongest dietary risk factor for AD is higher caloric and fat intake [35], and higher caloric and fat intake is related to weight gain and increased adiposity [11, 12]. Several studies have found that increased physical activity is inversely related to AD [36]. High physical activity is typically accompanied by low adiposity [11] which may be the explanation for the beneficial effects.
In terms of vascular risk factors, hypertension, dyslipidemia, diabetes, hyperinsulinemia, the metabolic syndrome, homocysteine, smoking, and heart disease are potential risk factors for AD [34]. In our opinion, the most consistent risk factors are diabetes, hyperinsulinemia, and smoking [34]. High adiposity is clearly a risk factor for diabetes, hyperinsulinemia, the metabolic syndrome [37], dyslipidemia [38], and hypertension [39], and these can be reversed or prevented by weight loss [12, 40, 41]. Smoking is related to weight loss and low weight and thus may confound the association between BMI and AD, producing the appearance of a relation between low BMI and AD. This type of confounding may partially explain U-shape associations found between BMI and other outcomes such as mortality [42]
Adiposity is also related to a higher risk of heart disease [12, 43], but heart failure can result in both weight gain due to edema, or weight loss due to cachexia [44]. Thus, adiposity can be a risk factor for heart disease, but heart disease may be followed by weight loss and low weight may be a marker of heart disease [44].
In summary, many of the putative risk factors for AD can be caused by high adiposity, but risk factors such as smoking and heart disease can confound indirect measures of adiposity such as BMI. When studying the relation between adiposity and AD special care should be taken to identify which factors are confounders and which are in the causal pathway to AD.
The continuum of adiposity, hyperinsulinemia, glucose intolerance and diabetes
Adiposity, hyperinsulinemia, glucose intolerance, and diabetes, are often treated as separate constructs, and have been separately related to the risk of AD [34]. However, they are related sequentially and often occur simultaneously, and understanding this relation is fundamental in the study of the role of adiposity and metabolic risk factors in AD. Glucose intolerance and diabetes are abnormal elevations of blood glucose that put people at risk for microvascular (nephropathy, neuropathy, retinopathy) and macrovascular disease (coronary artery disease, cerebrovascular disease, peripheral vascular disease) [45]. The American Diabetes Association currently defines diabetes as a fasting glucose elevation > 126 mg/dl, and glucose intolerance as an elevation > 110 mg/dl [46] It is difficult to establish an absolute threshold for the definition of glucose intolerance and diabetes. Previously, the definition of diabetes was a fasting glucose > 140 mg/dl, and people currently defined as having diabetes were then considered non-diabetic [31]. It is likely that the diabetes definition will change again and persons currently considered to have glucose intolerance will be considered to be diabetic. Keeping glucose in normal levels is achieved by the balance between the ability of peripheral tissues (muscle, adipose tissue, liver) to take glucose into cells, and the pancreas’ ability to secrete insulin, the hormone in charge of glucose tissue uptake [45]. Thus, abnormal glucose levels are caused by a resistance of tissues to the action of insulin (insulin resistance), and by the pancreas’ inability to secrete enough insulin at normal levels or higher than normal insulin levels (hyperinsulinemia) to overcome insulin resistance in tissues [47]. Insulin resistance increases with age, and the organism maintains normal glucose levels as long as it can produce enough insulin (hyperinsulinemia). Some individuals are less capable than others to mount sustained hyperinsulinemia and will develop glucose intolerance and diabetes [47]. Other individuals with insulin resistance will maintain normal glucose levels at the expense of hyperinsulinemia but their pancreas will eventually “burn out”, will not be able to sustain hyperinsulinemia, and will develop glucose intolerance and diabetes [47]. Others will continue having insulin resistance, may have or not have glucose intolerance, will not develop diabetes, but will have hyperinsulinemia and suffer its consequences. The greatest determinant of insulin resistance and hyperinsulinemia is adiposity [10, 48], although adipose tissue is not the only factor. Insulin resistance can reside in other tissues, including muscle, liver, and the pancreas itself [49]. The natural history linking adiposity to insulin resistance to hyperinsulinemia to glucose intolerance and diabetes could be summarized in the following way (Figure 2). Elevations of adiposity, measured as overweight and obesity, result in insulin resistance, causing the pancreas to increase insulin to abnormal levels to sustain normal glucose, and if and when the pancreas can no longer sustain hyperinsulinemia, glucose intolerance and diabetes will ensue. Pancreatic failure resulting in low insulin levels preceded by hyperinsulinemia may explain one report of a U-shape association between fasting insulin and the risk of AD in a prospective study of Japanese-American men [50]- those with low insulin were captured after pancreatic failure and those with high insulin were in the hyperinsulinemia phase. However, the overlap between these processes is not complete [51]. Not all persons with higher adiposity will develop insulin resistance and hyperinsulinemia, but most will. Not all persons with insulin resistance and hyperinsulinemia will develop glucose intolerance and diabetes, and this depends on genetic and other susceptibility factors that are not completely understood [49, 51]. Some adults develop diabetes without going through insulin resistance and hyperinsulinemia, but it is thought that most will.
Natural history of the continuum of adiposity, insulin resistance, hyperinsulinemia, glucose intolerance and diabetes. Increased adiposity causes insulin resistance and hyperinsulinemia. Insulin levels may decrease over time due to pancreatic failure, and glucose intolerance and diabetes ensue. Hypothetically, high insulin levels and then diabetes related processes could increase brain amyloid beta deposition leading to Alzheimer’s disease. It is unclear when this process starts, but it could begin in early adulthood or even childhood. As depicted in the figure, these factors change with time, and the timing of their ascertainment may affect findings in epidemiological and clinical studies.
The susceptibility to adiposity, that is, the risk of developing the above described sequence in response to adiposity, varies by gender [11] and particularly by ethnicity. For example, Chinese and southeast Asians are more susceptible than Europeans to developing insulin resistance with comparable increases of adiposity[10]. The distribution of factors related to insulin resistance and the metabolic syndrome, including adiposity, is different in Whites and Blacks [52]. Thus, conventional ways to classify adiposity may not capture its relation with adverse outcomes and this should be taken into account. High adiposity and hyperinsulinemia are both accompanied by dyslipidemia, hypertension, and inflammation [48], and these should also be taken into account.
An implication of the continuum described above is that what may be important in a putative relation between high adiposity and AD is independent factors related to fatty tissue itself, the hyperinsulinemia resulting from insulin resistance, the consequences of high glucose levels and its by-products, or other risk factors that accompany hyperinsulinemia. The answer is likely to be a combination of all of the above, but we believe given current knowledge on mechanisms (summarized below), that hyperinsulinemia is the main factor, and we have contended that diabetes in this context may be a marker of past hyperinsulinemia [53], and adiposity may also be a marker of hyperinsulinemia. The metabolic syndrome, an increasingly popular term in clinical practice and research, and reported to be associated with a higher risk of cognitive decline [54] is a constellation of adiposity, hypertension, glucose intolerance, dyslipidemia, and inflammation that is associated mainly with insulin resistance and hyperinsulinemia [37, 55]. This concept is an encapsulation of the processes described above and thus we do not elaborate on it.
When studying the relation between adiposity and AD, hyperinsulinemia, glucose intolerance, diabetes and other factors such as hypertension, dyslipidemia, and inflammation, should be considered in the causal pathway and not confounders or independent factors.
Potential mechanisms linking adiposity to Alzheimer’s disease
One way to examine pathways that lead to AD is to classify them in direct and indirect. Direct are those that are directly linked to the amyloid cascade, the putative culprit of AD [4]. Indirect are those that do not affect the amyloid cascade directly but precipitate or accelerate the amyloid cascade, or produce an additive insult that lowers the threshold for clinical diagnosis. One such indirect pathway is cerebrovascular disease [56]. We examine below how processes known to be related to adiposity could affect direct and indirect pathways to AD.
Hyperinsulinemia
As described previously, one of the main consequences of adiposity is insulin resistance and hyperinsulinemia [10]. We list hyperinsulinemia first because we believe that this is the most plausible direct mechanism that could link adiposity and AD. The role of insulin in AD has attracted increasing attention [57]. Insulin can cross the blood brain barrier from the periphery to the central nervous system and compete with Aβ for insulin degrading enzyme (IDE) in the brain, including the hippocampus [58]. Insulin is also produced in the brain, and may have alternatively have a beneficial effect in amyloid clearance [59]. Peripheral hyperinsulinemia may inhibit brain insulin production which, in turn results in impaired amyloid clearance and a higher risk of AD [59]. Thus, it is possible that decreasing peripheral hyperinsulinemia and increasing brain insulin levels have the same beneficial effect on AD. A study found that rosiglitazone, which decreases insulin resistance and decreases peripheral insulin levels used in the treatment of diabetes may also be beneficial in AD [60]. Interestingly, intranasal insulin, delivered with direct access to the brain without accessing the periphery has a similar effect [59]. Hyperinsulinemia is related to a higher risk of AD in epidemiological studies [50, 53, 61, 62] and manipulation of insulin levels in humans has been demonstrated to affect cognition and levels of Aβ in the cerebrospinal fluid [63, 64], supporting the potential direct role of insulin in AD.
Advanced products of glycosilation (AGE)
AGE are direct products of glucose intolerance and diabetes and are responsible for their related end organ damage[65]. AGEs can be identified immunohistochemically in senile plaques and neurofibrillary tangles, the pathologic hallmarks of AD [6]. Glycation of Aß enhances its aggregation in vitro. Furthermore, receptors for AGE have been found to be specific cell surface receptors for Aß, thus potentially causing neuronal damage [65].
Adipokines and cytokines
Adipose tissue used to be conceived as a passive depot of energy in the form of fats. Recent evidence shows that adipose tissue is active and produces a series of substances that are important in metabolism (adipokines), and inflammation (cytokines). The adipokines include adiponectin [66], leptin [67], and resistin [67], and the inflammatory cytokines include TNF-α, and IL-6 [67], all correlated with insulin resistance and hyperinsulinemia. It is unclear at this point whether adipokines and cytokines produced by adipose tissue are directly related to AD or whether they are only markers of insulin resistance and hyperinsulinemia, and this is an area ripe for study. Leptin reduces the activity of beta secretase, one of the enzymes that leads to Aß formation[6], in neurons, increases APOE dependent uptake of Aß in vitro, and its chronic administration to AD transgenic mice can decrease brain Aß, supporting a potentially important role for adipokines in AD in addition or independent of insulin[68].
Vascular risk factors and cerebrovascular disease
Cerebrovascular disease and stroke are related to a higher risk of AD [56, 69]. It is not clear whether cerebrovascular disease has a direct action on the amyloid cascade. It may cause brain damage aggregated to amyloid neurotoxicity that may in turn decrease the threshold for AD clinical manifestation. An autopsy study showed that large vessel cerebrovascular disease, but not small vessel disease or infarcts, were related to a higher frequency of brain neuritic plaques [70], the pathologic hallmark of AD[6]. In the absence of evidence that cerebrovascular disease directly affects the amyloid cascade, we consider it to be an indirect pathway to AD. Adiposity itself [12], and vascular risk factors related to adiposity, including diabetes, hypertension, dyslipidemia, are related to a higher risk of cerebrovascular disease [71]. Thus, adiposity may affect AD risk indirectly through vascular risk factors and cerebrovascular disease.
Review of prospective epidemiological studies linking adiposity to AD
Few studies have explored the association between adiposity and AD and reveal conflicting findings (Table). Elevated BMI (overweight and obesity) in middle age is associated with higher dementia risk [72, 73]. Higher BMI at ages 70, 75 and 79 years also predicts higher dementia risk [74]. However, there have been reports of no association [75] and of lower BMI related to higher AD risk [76]. These paradoxical findings could be explained by different age groups in different studies; those conducted in middle age show a relation of elevated BMI to increased dementia risk, while those in older populations are conflicting. Another potential explanation is ethnicity. One study in Japanese Americans showed no association of adiposity with AD, and as mentioned earlier, Asians may be more susceptible to the effects of relatively small increases in adiposity compared to Europeans [10]. A study in Northern New York City [77] found that in younger elderly (65 to 76 years of age), the association between BMI quartiles and AD resembles a U shaped-curve (Figure 2), while in the oldest old (> 76 years) higher BMI is related to a lower AD risk. This study also found that higher WC is related to higher AD risk in the younger elderly, but not in the oldest (Figure 4). We believe that these findings encapsulate the findings of other studies and some of the issues described in previous sections regarding caveats in measures of adiposity and the effect of aging. In addition, low BMI may be a sign of frailty due to sarcopenia [30, 78], the consequence of AD itself [79], or the consequence of hyperinsulinemia [80], one of the putative mechanisms linking adiposity and AD.
Hazard ratios [16] relating quartiles (Q) of waist circumference (WC) to Alzheimer’s disease in persons < 76 years old and persons ≥ 76 years old, adjusting for age, sex, years of education, ethnic group, and APOEɛ4. The HR for the 4th Q of WC and the p for trend in persons < 76 years were statistically significant. The Washington Heights Inwood Columbia Aging Project, 1992–2003.
Table
Summary of prospective epidemiologic studies relating adiposity to AD.
| Study | Population | Findings |
|---|---|---|
| Kivipelto et al. [72] | 1,449 persons with a mean age of 50 years at baseline in Finland | Non-statistically significant increased risk of dementia for obese at middle age. |
| Whitmer et al[73] | 10,276 persons aged 40 to 45 years at baseline participating in managed care health plan in the United States. | Overweight and obesity at middle age related to a higher risk of dementia. |
| Nourashemi et al. [76] | 3,646 persons aged > 65 years in the PAQUID study, France | Results suggestive of higher risk of AD with lower BMI. |
| Gustafson et al.[74] | 382 women aged 70 years at baseline from Sweden | Higher BMI related to higher risk of dementia at ages 70, 75 and 79 years. |
| Stewart et al.[75] | 1890 Japanese American men living in Hawaii aged 46 to 68 years at baseline | Weight at midlife or late life not associated with risk of dementia. Incident dementia related to weight loss. |
| Luchsinger et al.[77] | 893 persons aged 65 years and older from Northern New York City | BMI has U-shaped relation with AD in persons 65 to 75 years of age; higher BMI related to lower AD risk in persons ≥ 76 years.
Higher waist circumference related to higher AD risk in those 65 to 75 years; no relation in those ≥ 76 years. |
We believe that considering the caveats in the measurement of adiposity in the elderly, the existing literature is not necessarily in conflict with the evidence linking hyperinsulinemia and diabetes to AD. In Northern New York City, hyperinsulinemia [53] and diabetes [53, 81] were strong risk factors for AD, while the association between BMI and AD resembled a U-shape curve in younger elderly, in whom higher WC were related to higher risk. Higher BMI and WC were not related to AD in the oldest old.
Summary, implications, and future directions
Increased adiposity leads to hyperinsulinemia and glucose intolerance and diabetes, which in turn, are antecedent risk factors for AD. These factors occur sequentially but also coexist. We don’t know how early in life adiposity affects AD risk, but given the effect of hyperinsulinemia on brain amyloid metabolism, it is possible that it could start in young adulthood or even childhood. This possibility is devastating given the epidemic of high adiposity in children and adults. Traditional measures such as BMI and WC are better correlated with adiposity in younger persons compared to the elderly, which complicates the study of the relation between adiposity and AD, and may explain conflicting findings in the literature. In addition, adiposity may have differential effects by gender and ethnicity. Thus, arbitrary cutoffs for measures of adiposity may not be useful, and we recommend taking age, gender, and ethnic group into account. Direct measurement of body composition may be a better approach to studying adiposity in the elderly. Based on what is known about the natural history and consequences of increased adiposity and our interpretation of existing evidence, we believe that increased adiposity is important in the pathogenesis and AD. Given current knowledge, the most plausible mechanism linking adiposity and AD is hyperinsulinemia, which has recently attracted great interest and is an area of intense research However, adipose tissue is active in the production of adipokines and cytokines, and it is unclear whether these are just correlates of hyperinsulinemia and antecedents of glucose intolerance and diabetes, or whether they have a direct effect on the amyloid cascade and AD and their specific modification could modify its risk. We believe that this is the most important question to be answered in this area. Fortunately, elevated adiposity is preventable and modifiable, and studies are needed assessing how its prevention and treatment throughout the lifespan affects AD risk.
Hazard ratios relating quartiles (Q) of body mass index (BMI) to Alzheimer’s disease in persons < 76 years old and persons ≥ 76 years old, adjusting for age, sex, years of education, ethnic group, and APOEɛ4. Only the HR for the 3rd and 4th quartiles in persons < 76 years were statistically significant. The Washington Heights Inwood Columbia Aging Project, 1992–2003.
Acknowledgments
Support for this work was provided by grants from the National Institutes of Health AG07232, AG07702, 1K08AG20856-01, RR00645, from the Charles S. Robertson Memorial Gift for research on Alzheimer’s disease, from the Blanchette Hooker Rockefeller Foundation, and from the New York City Council Speaker’s fund for Public Health Research