Journal Identification = JAD Article Identification = 140720 Date: February 7, 2015 Time: 10:57 am

Journal of Alzheimer’s Disease xx (20xx) x–xxDOI 10.3233/JAD-140720IOS Press

1

Observational and Ecological Studiesof Dietary Advanced Glycation EndProducts in National Diets and Alzheimer’sDisease Incidence and Prevalence

Lorena Perronea and William B. Grantb,∗aEA 3808, Medical School, University of Poitiers, Poitiers, FrancebSunlight, Nutrition, and Health Research Center, San Francisco, CA, USA

Accepted 8 January 2015

Abstract.Background: Considerable evidence indicates that diet is an important risk-modifying factor for Alzheimer’s disease (AD).Evidence is also mounting that dietary advanced glycation end products (AGEs) are important risk factors for AD.Objective: This study strives to determine whether estimated dietary AGEs estimated from national diets and epidemiologicalstudies are associated with increased AD incidence.Methods: We estimated values of dietary AGEs using values in a published paper. We estimated intake of dietary AGEs from theWashington Heights-Inwood Community Aging Project (WHICAP) 1992 and 1999 cohort studies, which investigated how theMediterranean diet (MeDi) affected AD incidence. Further, AD prevalence data came from three ecological studies and includeddata from 11 countries for 1977–1993, seven developing countries for 1995–2005, and Japan for 1985–2008. The analysis useddietary AGE values from 20 years before the AD prevalence data.Results: Meat was always the food with the largest amount of AGEs. Other foods with significant AGEs included fish, cheese,vegetables, and vegetable oil. High MeDi adherence results in lower meat and dairy intake, which possess high AGE content.By using two different models to extrapolate dietary AGE intake in the WHICAP 1992 and 1999 cohort studies, we showed thatreduced dietary AGE significantly correlates with reduced AD incidence. For the ecological studies, estimates of dietary AGEsin the national diets corresponded well with AD prevalence data even though the cooking methods were not well known.Conclusion: Dietary AGEs appear to be important risk factors for AD.

Keywords: Advanced glycation end products, Alzheimer’s disease, cheese, diet, ecological, fish, Japan, meat, mediterraneandiet, MeDi

INTRODUCTION

Alzheimer’s disease (AD) is the main cause ofdementia among the elderly, affecting more than 25million people in the world [1]. A major healthproblem, this progressive neurodegenerative disorder

∗Correspondence to: William B. Grant, PhD, Sunlight, Nutrition,and Health Research Center, P.O. Box 641603, San Fran-cisco, CA 94164-1603, USA. Tel.: +1 415 409 1980; E-mail:wbgrant@infionline.net.

associated with cognitive impairment and neuronal cellloss represents a heavy economic burden in industrial-ized countries. The pathology is characterized by thepresence of several kinds of amyloid plaques and neu-rofibrillary tangles in the brain, which consist mostlyof the amyloid-� (A�) protein, derived from the pro-teolytic cleavage of the amyloid-� protein precursor(A�PP), and hyperphosphorylated tau [2]. FamiliarAD is caused by mutations in A�PP and presenilins,which lead to A� overproduction [3, 4]. By contrast,

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2 L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease

sporadic AD represents 95% of cases and its ultimatecause remains controversial [5]. Recent studies showthat most cases of AD probably involve a combinationof genetic and environmental risk factors, such as nutri-tion [6]. Identifying and validating these risk factorsremains one of the most critical scientific challengesto prevent AD.

Evidence is increasing that diet plays an importantrole in AD. Several studies have linked the Mediter-ranean diet (MeDi) to lower risk of AD [7–10]. TheMeDi consists of “high consumption of plant foods(i.e., vegetables, fruits, legumes, and cereals), a highintake of olive oil as the main source of fat, a moderateintake of fish, low-to-moderate intake of dairy prod-ucts and low consumption of meat and poultry, withwine consumed in low-to-moderate amounts duringmeals” [6, 11]. Research has also linked the tradi-tional Japanese diet to lower risk of AD [12, 13].The traditional Japanese diet derived only 10% of itsenergy from animal products in 1961–1963, with fishand seafood making up almost half that amount [14].Cereals, primarily rice, made up 59% of the dietarysupply.

Cai and colleagues recently suggested a newapproach on how to relate dietary factors to risk ofAD: consideration of food-derived advanced glycationend products (AGEs), also called glycotoxins becausethey contribute to the progression of various chronicdiseases [15]. AGEs are a group of compounds deriv-ing from the nonenzymatic addition of reducing sugarsto proteins and other macromolecules [16]. AGEs areformed both endogenously and during food processing[16]. Larger amounts are found in foods cooked at hightemperatures, such as by broiling or frying, or by aginga long time, such as for hard cheese [17]. Studies havelinked AGEs to increased risk of or exacerbation of dia-betes [18, 19], cardiovascular disease [20], and severalother aging-related diseases [1, 21], including AD [1].AGEs are a heterogeneous family of compounds. Someformed in food are pyrrolines and dicarbonyl com-pounds such as methylglyoxal (MG), which appearsto be the most toxic [16]. Several experimental stud-ies show that dietary AGE intake enhances circulatingblood AGE content [16]. Conversely, dietary restric-tion of AGEs decreases concentration of circulatingAGEs [16]. These data show that dietary AGEs con-tribute substantially to the body’s AGE pool [16].

AGEs induce protein cross-linking and precipita-tion, affecting cellular function [16]. AGEs’ toxiceffects are also attributed to their prooxidant andinflammatory action [16]. AGEs induce cell deathby causing oxidative stress and endoplasmic reticu-

lum stress [22]. Besides their intrinsic toxicity, AGEsinduce cellular dysfunction by binding and activatingthe receptor for AGEs (RAGE). RAGE is a multi-ligand receptor involved in inflammatory disorders,tumor growth, diabetic complications, and AD [1,23]. RAGE transports circulating A� toxins acrossthe blood–brain barrier, where RAGE–A� interactionleads to oxidative stress, causes inflammation, andreduces cerebral blood flow [1, 23, 24]. One studyshowed RAGE immunoactivity in neurons of agedmice, but not in nonneuronal cells other than astro-cytes present in hippocampal area CA1 [25]. Severalstudies strongly indicate that RAGE mediates how riskfactors promote AD [1, 23]. Indeed, RAGE is impli-cated in the pathophysiology of risk diseases for AD,including type 2 diabetes, vascular diseases, and cere-bral ischemia [1, 23]. Because of the intrinsic toxicityof AGEs, their ability to activate RAGE, and nutrition’srole as an environmental risk factor for AD, investi-gating the role of dietary AGEs in promoting AD isessential.

So far, only one study has investigated how dietaryAGEs affected AD progression in mice [15]. Micefed with MG derivatives (MG+) showed higherbody weight and lower protein levels of SIRT1and of the NAD+/NADH-regulating nicotinamide-phosphoribosyl-transferase than MG– mice [15].MG+ mice could travel shorter straight-line distances,had reduced latency until fall, and were slower thanMG– mice as well as having poorer object recogni-tion. SIRT1 limits A� accumulation by directing A�PPprocessing via ADAM10 and �-secretase transcription[26]. Notably, a high-MG diet correlated with brainchanges and enhanced A� accumulation in old MG+mice, as well as impaired learning and memory func-tion [15], showing that dietary AGEs impair cognitivefunction. A high level of circulating MG also correlateswith impaired cognition in humans [15]. However, sofar no cohort study or ecological study has investi-gated the association between dietary AGEs and ADincidence.

On the basis of this new appreciation for the role ofdietary AGEs in risk of AD, we extrapolated the level ofdietary AGEs in various cohort studies analyzing howfollowing the MeDi affected AD incidence. We alsorevisited previous ecological studies of AD prevalencewith respect to national dietary supply factors [12, 13].We show that the MeDi’s beneficial effect in reduc-ing AD incidence strongly correlates with a decreaseddietary AGE content. Ecological studies confirm thisresult, showing the relevance of dietary AGEs as riskfactors for AD.

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MATERIALS AND METHODS

MeDi score

The cohort studies we used to extrapolate dietaryAGE content used the MeDi score to calculate adher-ence to that diet [6, 27]. The MeDi score includes sevendifferent food groups: vegetables, fruits, legumes, cere-als, meat, dairy products, and fish. TheMeDi scoreconsists of the sum of nine individual binary compo-nents (the seven food groups mentioned above, plusthe alcohol intake and the dietary unsaturared/saturatedratio), ranging from 0 (lower adherence) to 9 (higheradherence) points. For each group a value of 0 or 1is assigned on the basis of a cutoff derived on medi-ans of consumption in the population. These medianswere calculated in grams [27] or in servings [7]. Forfood groups considered beneficial (vegetables, fruits,legumes, cereals, and fish) individuals with consump-tion below the median are given a value of 0, whereasa value of 1 is assigned when consumption equals orexceeds the median. For food groups considered detri-mental (meat and dairy products), individuals whoseconsumption is below the median are assigned a valueof 1 point, whereas others get a value of 0. Scoreswere then further divided into tertiles based on MeDiadherence: low (0–3), moderate (4–5), and high (6–9).

Extrapolating dietary AGEs in the WashingtonHeights-Inwood Community Aging Project(WHICAP) 1992 and 1999 cohort studies

We extrapolated AGE content in each categoryof food by using data from Uribarri and colleagues[17]. For the WHICAP 1992 and 1999 cohort studies,Scarmeas and colleagues indicate the cutoff dietaryintake (in grams/day) of each category of food ineach MeDi tertile [27]. We used two models to calcu-late the dietary AGE intake. We excluded two factorsbecause calculating their AGE content was not pos-sible: the unsaturated/saturated fat ratio, since it doesnot represent an absolute measure, and alcohol intake,since the data did not specify the beverage consid-ered. In the first model, we assigned the average AGEcontent for a defined food category derived from theUribarri study at three different cooking temperatures[17] (Table 2A). For each cooking temperature, theMeDi tertile representing high MeDi adherence showslower AGE content (Table 2A). In the second model,we assigned a lower AGE value to meat and dairyand higher value to the other food groups than in thefirst model (Table 2B). Also, the MeDi tertile repre-

senting high MeDi adherence shows the lower AGEcontent (Table 2B). Thus, using two opposite modelsto extrapolate AGE content yielded the same results:high MeDi adherence leads to fewer AGEs. This resultvalidates the data we obtained from analyzing the cor-relation between dietary AGEs and AD incidence inthe WHICAP 1992 and 1999 cohort studies.

Extrapolating dietary AGEs in the Three-Citystudy

The Three-City cohort study expresses the averageand standard deviation of each group of food in eachMeDi tertile in servings/week, as Feart and colleaguesindicated [7]. We converted servings/week (averagebetween women and men) to grams/week accordingto the conversion method of Nothlings and colleagues[28] (Table 4A). In this conversion, we considered veg-etables and legumes together as “vegetables,” since thelegumes do not appear as a food group in the conver-sion from servings to grams [28] (Table 4A). Then weused the two models described above to extrapolateAGEs/week (Table 4B).

Statistical analysis of the correlation betweendietary intake and AD incidence

We used KaleidaGraph version 4.2 (Synergy Soft-ware, Reading, PA) to create graphs and maderegression analyses by using IBM SPSS Statistics ver-sion 20 (Armonk, NY).

Ecological studies

Grant supplied AD prevalence values for peopleolder than 65 years in 1983–1993 [12] and for thoseolder than 65 years in seven countries in 1995–2005[13]. We obtained AD prevalence data for those olderthan 65 years in Japan in 1985–2007 from Dodge andcolleagues [29].

We used dietary supply data from the United NationsFood and Agriculture Organization (FAO) [14] todetermine the level of AGEs in national diets. Sincethe correlation between diet and AD prevalence wasstrongest for a lag of 15–25 years [13],we obtaineddata for dietary supply factors from 20 years beforethe AD prevalence data. We derived the AGE con-tent of the dietary supply data from values in Table 1in the report by Uribarri and colleagues [17]. In thatstudy, foods were boiled, broiled, deep fried, ovenfried, and roasted. They determined AGE content byusing an enzyme-linked immunosorbent assay based

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4 L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease

Table 1Longitudinal cohorts studies of Mediterranean diet and incident AD

Country [ref] Cohort inceptionyear

n Age mean (SD) ormedian (IQR)

Follow-up yearsmean (SD) ormedian (IQR)

Subjectsselection

MeDi measure-MediScore(continuous),Tertiles: Low(0–3), middle(4–5), high(6–9)

Outcomedefinition (n)

USA [27] WHICAP 1992 &WHICAP 1999

2226 77.2 (6.6) 4.0 (3.0) CN (≥65) Continuous &Tertiles

AD (262)

USA [37] WHICAP 1992 &WHICAP 1999

1790 76.3 (6.6)75.8 (6.2)

4.0 (3.0) CN (≥65) Continuous &Tertiles

AD (194)

USA [35] WHICAP 1992 &WHICAP 1999

192 76.3 (6.6)75.8 (6.2)

4.4 (3.6) AD Continuous &Tertiles

AD mortality (85)

Greece [41] EPIC-Greece1993–1999

732 NN 6–13 year laterfollow up

CN (≥60) Continuous MMSE score

France [11] 1999–2000 1410 75.9 Median:4.1 CN (≥65) Continuous &Tertiles

AD (66)

USA [38] WHICAP 1992 &WHICAP 1999

482 77.5 (6.6) 4.3 (2.7) MCI(≥65)

Continuous &Tertiles

AD (106)

USA [38] WHICAP 1992 &WHICAP 1999

1393 76.7 (6.5) 4.5 (2.7) CN (≥65) Continuous &Tertiles

MCI (275)

USA [36] WHICAP 1992 &WHICAP 1999

1880 77.2 (6.6) Median:1.5 CN (≥65) Continuous &Tertiles

Time to incidentAD (282)

USA [34] WHICAP 1992 &WHICAP 1999

1219 76.7 (6.4) 4.0 (3.0) CN (≥65) Continuous &Tertiles

AD (118)

Australia [8] AIBL 2006 970 71.7 (7.86) Median:4.5 CN, MCI,AD ≥60

Continuous &Tertiles

CN versus AD orMCIAD: 149 AD 77.50 (8.2)

MCI:98 MCI 76.01 (7.78)CN:723 CN 69.94 (6.95)

Sweden [40] UppsalaLongitudinalStudy, Sweden

1038 ≥70 Median:11.6 CN ≥70 MeDi score (0–8points).Continuous andTertiles low(0–2), moderate(3–5), high (≥6)

AD (84)

AD, Alzheimer’s disease; CN, control; IQR, interquartile range; MCI, mild cognitive impairment; MeDi, Mediterranean diet; MMSE, Mini-Mental State Examination; SD, standard deviation.

on monoclonal anti-N�-(carboxymethyl) lysine anti-body. Because this is not the only AGE, reported valueshave some uncertainty.

AGE values in this study were based on categoriesof foods commonly eaten in large enough quantitiesto contribute appreciably to the total for some coun-tries. We estimated values on the basis of assumptionsregarding cooking methods [17]. As tabulated AGEvalues for the various national diets show, meat con-tributes most—as much as 80%—to the national AGEvalues. Thus, examining the basis for the AGE valuefor meat is worthwhile. For beef, the AGE value rangedfrom 707 kU/100 g for raw beef to 4,928 kU/100 g forground beef, 20% fat, pan browned, to 10,058 kU/100 gfor beef steak pan fried with olive oil. For chicken,values ranged from 957 kU/100 g when boiled withlemon; 4,938 kU/100 g for breast, pan fried; to 9,961kU/100 g for breast, breaded, oven fried with skin.Values for pork ranged from 633 kU/100 g for liv-

erwurst to 91,577 for bacon, fried. For lamb, valuesranged from 1,029 kU/100 g microwaved to 2,431kU/100 g broiled. The value adopted, 5,000 kU/100 g,is an estimate. Using a lower value, such as 4,000kU/100 g, probably would not change the rankings ofnational diets appreciably. For fish, the value used wasone-third of that based on cooking alone since manytypes of fish have omega-3 fatty acids and vitamin D,which reduce risk of AD [30, 31]. Data on cheeseconsumption are from the Helgi Library [32], whichobtained the data from FAO. If cheese consumptiondata were not available, we estimated from the ratio ofcheese to milk supply for similar countries.

Values used for the various dietary factors were asfollows, in kilounits (kU) of AGEs/100 g: cheese, 5.0;eggs, 0.4; fish, 0.5; fruit, 0.1; legumes, 0.20; meat,4.0; milk, 0.005 (omitted); rice, 0.03; soya beans, 1.5;starchy roots, 0.07; tree nuts, 5.5; vegetable oil, 10.0;vegetables, 0.10; and wheat and other nonrice cereals,

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0.1. The value for fish was reduced from 1.5 on the basisof estimated cooking methods to 0.5 on the basis of thebeneficial effect of omega-3 fatty acids and possiblyvitamin D in many types of fish.

RESULTS

Cohort clinical studies correlating adherence tothe MeDi with AD incidence

A recent study showed how increasing dietary AGEintake promoted brain changes leading to impairedcognition in mice [15]. The same study correlatedincreased serum level of AGEs with memory decline inhumans in an observational clinical study [15]. How-ever, serum AGEs are not predictive of AD [33]. Thus,a clinical study that investigates the effect of dietaryAGEs intake on AD incidence is still lacking. Sinceseveral studies in animal models strongly suggest acorrelation between dietary AGEs and enhanced ADincidence, analyzing the effect of dietary AGEs in

AD incidence in prospective cohort clinical studiesis essential. Several reports show that MeDi adher-ence inversely correlates with AD incidence [7, 8,27, 34–38]. Since the MeDi score defines the dietaryintake of different food categories [27], these prospec-tive cohort studies can be used to extrapolate the dietaryAGE content and correlate it with AD incidence. Tothis end, we first further expanded a previous system-atic review and meta-analysis study [39] to find in theliterature all prospective cohort clinical studies cor-relating adherence to the MeDi with AD. We found10 studies [7, 8, 27, 34–38, 40, 41], whose parametersinvestigated are illustrated in Table 1. Six of these stud-ies analyze data obtained during the WHICAP 1992and WHICAP 1999 cohort studies [27, 34–38]. TheWHICAP studies also define the grams/day for eachcategory of food in the three MeDi tertiles [27], rep-resenting degree of MeDi adherence (low, moderate,high). We used these studies to extrapolate the AGEcontent in the MeDi tertiles and correlate them withAD incidence.

Table 2AModel 1 of advanced glycation end products (AGEs) content extrapolation in each Mediterranean diet (MeDi) tertile

Food kU AGEs MeDi score 0–3 MeDi score 0–3 MeDi score 4–5 MeDi score 4–5 MeDi score 6–9 MeDi score 6–9category 100 g LT gm/day TOT kU AGEs gm/day TOT kU AGEs gm/day TOT kU AGEs

Low temperature cookingDairy 1.5 246 3.69 174 2.61 151 2.27Meat 1 101 0.10 86 0.86 65 0.65Vegetable 0.004 165 0.01 202 0.01 243 0.01Fruit 0.002 406 0.01 471 0.01 556 0.01Legumes 0.1 44 0.04 58 0.06 78 0.08Cereal 0.1 155 0.16 186 0.19 215 0.22Fish 0.5 15 7.50 21 0.11 47 0.24TOTAL AGEs 4.99 3.84 3.46

Food kU AGEs MeDi score 0–3 MeDi score 0–3 MeDi score 4-5 MeDi score 4-5 MeDi score MeDi score 6–9Categorie 100 g MT gm/day TOT kU AGEs gm/day TOT kU AGEs 6–9 gm/day TOT kU AGEs

Medium temperature cookingDairy 3 246 7.38 174 5.22 151 4.53Meat 3 101 3.03 86 2.58 65 1.95Vegetable 0.1 165 0.17 202 0.20 243 0.24Fruit 0.05 406 0.20 471 0.24 556 0.28Legumes 0.2 44 0.09 58 0.12 78 0.16Cereal 0.3 155 0.47 186 0.56 215 0.65Fish 1.5 15 0.23 21 0.32 47 0.71TOTAL AGEs 11.56 9.23 8.51

Food kU AGEs MeDi score 0–3 MeDi score 0–3 MeDi score 4–5 MeDi score 4–5 MeDi score 6–9 MeDi score 6–9Categorie 100 g HT gm/day TOT kU AGEs gm/day TOT kU AGEs gm/day TOT kU AGEs

High temperature cookingDairy 5 246 1230 174 870 151 755Meat 7 101 707 86 602 65 455Vegetable 0.2 165 33 202 40 243 49Fruit 0.1 406 41 471 47 556 56Legumes 0.3 44 13 58 17 78 23Cereal 0.5 155 78 186 93 215 108Fish 3 15 45 21 63 47 141TOTAL AGEs 2146 1733 1586

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6 L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease

Table 2BModel 2 of AGEs content extrapolation in each MeDi tertile

Food kU AGEs MeDi score 0–3 MeDi score 0–3 MeDi score 4–5 MeDi score 4–5 MeDi score 4–5Categorie 100 g M2 gm/day TOT kU AGEs gm/day TOT kU AGEs TOT kU AGEs

Dairy 1.5 246 3.69 174 2.61 2.27Meat 1 101 1.01 86 0.86 0.65Vegetable 0.2 165 0.33 202 0.40 0.49Fruit 0.1 406 0.41 471 0.47 0.56Legumes 0.3 44 0.13 58 0.06 0.08Cereal 0.5 155 0.16 186 0.19 0.22Fish 1.5 15 0.08 21 0.11 0.24Total AGEs 5.80 4.69 4.49

Table 2CExtrapolation of AGEs content compared to AD incidence [27]

MeDi N. N. % N. % TOTAL kU TOTAL kUScore All Nondemented Nondemented Incident AD Incident AD AGEs M1 LT AGEs M2

Low 0–3 422 326 77.3 96 22.8 4.99 5.80Medium 4–5 930 823 88.5 107 11.5 3.84 4.69High 6–9 574 515 89.7 59 10.3 3.46 4.49Total 2226 1964 262

Fig. 1. Correlation between dietary AGEs intake versus AD incidence in the WHICAP prospective cohort studies.

Extrapolating dietary AGEs in the WHICAPcohort studies

Urribarri and colleagues measured the AGE contentin 549 foods cooked at various temperatures [17]. Inthe WHICAP cohort study, the MeDi score–based dietrepresents each food group as grams/day [27]. How-ever, the cooking temperature is not indicated. For thisreason, we used two models to extrapolate dietary AGEcontent in the MeDi tertiles that Scarmeas and col-

leagues described [27]. In both models we derived theAGE content, referring to data from Urribarri and col-leagues [17]. In the first model’s extrapolation of AGEcontent, we assigned to each food category an AGEcontent value that is the average of AGE content foundin foods from the same category (Table 2A). We showthat, independent of cooking temperature, the MeDitertile that represents high adherence shows the low-est AGE content (Table 2A). In model 1, we assumedthat each food category is cooked at one temperature:

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Table 3AAssociations between AGE values and incident AD rates in several studies

MeDi N. N. % N. %Score All Nondemented Nondemented Incident AD Incident AD

STUDY 1: Correlation between AD incidence and MeDi score [27]Low 0–3 422 326 77.3 96 22.7Medium 4–5 930 823 88.5 107 11.5High 6–9 574 515 89.7 59 10.3TOT 2226 1964 262STUDY 2: Correlation between AD incidence and MeDi score [27]Low 0–3 667 574 86.1 93 13.9Medium 4–5 810 740 91.4 70 8.6High 6–9 507 476 93.9 31 6.1TOT 1984 1790 194STUDY 3: Correlation between AD incidence and MeDi score [36]Low 0–3 598 498 83.3 100 16.7Medium 4–5 779 661 84.9 118 15.1High 6–9 503 439 87.3 64 12.2TOT 1880 1598 282STUDY 4: Correlation between AD incidence and MeDi score [34]Low 0–3 400 351 87.8 49 12.3Medium 4–5 500 460 92.0 40 8.0High 6–9 319 290 90.9 29 9.1TOT 1219 1101 118

low, moderate, or high. However, in a diet some foodsin a category can be prepared at a low temperature,whereas others are cooked at a high temperature. Thus,our model 1 might not accurately represent the dietaryAGE content in each MeDi tertile. The tertile denotinghigh MeDi adherence (MeDi score 6–9) is character-ized by a lower intake of meat and dairy than in thetertile of low adherence (MeDi score 0–3). Accordingto Urribarri and colleagues [17], meat has more AGEsthan all the other food categories, independent of cook-ing temperature. MeDi score 6–9 is also characterizedby increased intake of vegetables, cereals, and fish,foods with a low concentration of AGEs [17]. To fur-ther verify that MeDi score 6–9 provides lower dietaryAGEs than the tertiles less adherent to the MeDi, weused our second model to extrapolate the total dietaryAGE content. In model 2, we assigned fish, vegetables,cereals, and fruit a higher AGE content and to meat anddairy products a lower AGE content than in model 1(Table 2B). We used this model to verify whether ourresults depend on an assumption in imposing an AGEvalue to each food category. Using model 2, we alsoshow that MeDi score 6–9 provides the lowest AGEcontent compared with the other MeDi tertiles, whichare less adherent to the MeDi (Table 2B). These resultsshow that the MeDi provides a small amount of AGEs.Our results also indicate that the WHICAP cohort stud-ies, analyzing the association between MeDi and ADincidence, can be used to investigate the correlationbetween dietary AGEs and AD incidence.

In WHICAP cohort studies, lower dietary AGEscorrelates with decreased AD incidence

To study how dietary AGE intake affects AD inci-dence, we analyzed results of the WHICAP 1992and WHICAP 1999 prospective cohort studies thatScarmeas and colleagues described [27]. We calcu-lated AGE content in the MeDi tertiles by using thetwo models described above (Table 2C). Then we ana-lyzed the correlation between dietary AGEs with ADincidence (Fig. 1a). Using model 1, we found a highcorrelation (R = 0.98) between increased dietary AGEsand enhanced AD incidence (Fig. 1a). Model 2 showedalso a high correlation (R = 0.99) between dietary AGEintake and AD incidence (Fig. 1a). These data stronglysupport the hypothesis that elevated intake of dietaryAGEs is a risk factor for AD.

We further analyzed the correlation between dietaryAGEs and AD incidence in the other WHICAP cohortstudies, which consider the effect of risk factors inmodifying AD incidence [27, 34, 36, 37] (Table 3A).Those authors examined various risk factors, such asvascular dysfunction and physical activity [34, 37,38]. We calculated the average of the results obtainedusing the two models of AGE extrapolation (Table 3B)and the correlation between dietary AGE content andAD incidence. Both models of AGE extrapolationshowed a perfect correlation (R = 1) between increaseddietary AGEs and enhanced AD incidence (Fig. 1b).These data further confirm the hypothesis that dietary

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8 L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease

Table 3BAverage of AD incidence correlated to MeDi Score and the extrapolation of AGEs content

MeDi % SD T Student T Student TOTAL TOTALScore Incident AD versus LS versus MS AGEs LT AGEs M2

Low 0–3 16.4 4.0 5.0 5.8Medium 4–5 10.8 2.8 0.04 3.9 4.7High 6–9 9.6 2.4 0.02 0.11 3.5 4.9

Table 4AConversion of MeDi diet servings/week to grams/week according to the conversion method [28]

Food Mean Serving/ SD Conversion g/serving Mean Grams/ SDCategory week week

MeDi score 0–3Dairy 18.4 7.7 Dairy 171.5 3155.6 1320.55Meat 5.4 2.6 Meat 35 190 90Vegetable 15.7 6.2 Vegetable/Legumes 75 1200 510Fruit 10.8 6.3 Fruit 104 1120 660Legumes 0.4 0.7 Cereal 43 860 280Cereal 19.9 6.4 Fish 31 62 43.4Fish 2 1.4MeDi score 4–5Dairy 16 7.2 Dairy 171.5 2744 1234.8Meat 4.8 2.4 Meat 34.7 166.56 83.28Vegetable 19.3 6.9 Vegetable/Legumes 74.5 1482.55 558.75Fruit 13.8 6.7 Fruit 104 1435.2 696.8Legumes 0.6 0.6 Cereal 43 954.6 258Cereal 22.2 6 Fish 31 89.9 52.7Fish 2.9 1.7MeDi score 6–9Dairy 14.2 6.5 Dairy 171.5 2435.3 377.3Meat 4.2 2.2 Meat 34.7 145.74 76.34Vegetable 23.3 6.7 Vegetable/Legumes 74.5 1795.45 543.85Fruit 16.2 6.3 Fruit 104 1684.8 655.2Legumes 0.8 0.6 Cereal 43 1053.5 215Cereal 24.5 5 Fish 31 114.7 52.7Fish 3.7 1.7

AGEs are a risk factor for AD independently from thepresence of other risk factors, suggesting that dietaryAGEs play a major role in promoting AD.

Extrapolating dietary AGEs in the Three-Citycohort study

Results across prospective cohort studies investigat-ing the MeDi and AD incidence have some discrep-ancies [6]. Feart and colleagues suggested that theseinconsistent results may occur because no single MeDiexists, and dietary habits differ across countries [6].Also, studies do not define the three tertiles homoge-neously, use different intake cutoffs for each group,and express the cutoff in different measures (gramsor servings), which makes comparing results difficult.We therefore also analyzed dietary AGE content in theThree-City study, which found a low and not significant

correlationbetweenMeDiadherenceandADincidence[7]. This study showed a significant difference amongthe tertiles only in some food groups [7]. That studyalso expresses the cutoff of each food group in serv-ings/week [7]. We used a published method to convertthe servings in grams [28] (Table 4A). Then we extrap-olated the dietary AGEs/week in each MeDi tertile asdescribed above and in the Materials and Methods sec-tion (Table 4B). We found no significant dietary AGEintake between the low and the moderate MeDi tertiles(p = 0.19for the lowtemperature–LT-methodofextrap-olating AGEs and p = 0.24 for the second extrapolationmethod-M2-).Wealsofoundnosignificantdifferenceindietary AGE intake between the low and high MeDi ter-tiles (p = 0.20 for the LT method and p = 0.28 for the M2method). These data accord with the results of Feart andcolleagues,showingasignificantdifferenceofintakeforonly some food groups [28].

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Table 4BWeekly AGE values for the MeDi

Food kU AGEs Mean kU SD kU AGEs Mean kU SDCategory 100 g LT AGEs/week 100 g M2 AGEs/week

MeDi score 0-3Dairy 1.5 47.3 19.8 1.5 47.3 19.8Meat 1.0 1.9 0.9 1.0 1.9 0.9Vegetable/Legumes 0.1 1.2 0.5 0.5 6.0 2.6Fruit 0.002 0.02 0.01 0.1 1.1 0.7Cereal 0.1 0.9 0.3 0.5 5.6 1.4Fish 0.5 0.31 0.2 1.5 0.93 0.7Tot kU AGEs/Week 51.6 21.8 62.9 26.0MeDi score 4-5Dairy 1.5 41.2 18.5 1.5 41.2 18.5Meat 1.0 1.7 0.8 1.0 1.7 0.8Vegetable/Legumes 0.1 1.5 0.6 0.5 7.4 2.8Fruit 0.002 0.0 0.0 0.1 1.4 0.7Cereal 0.1 1.0 0.3 0.5 4.8 1.3Fish 0.5 0.4 0.3 1.5 1.3 0.8Tot kU AGEs/Week 45.8 20.5 57.8 24.9MeDi score 6-9Dairy 1.5 36.5 5.7 1.5 36.5 5.7Meat 1.0 1.5 0.8 1.0 1.5 0.8Vegetable/Legumes 0.1 1.9 0.6 0.5 9.0 2.7Fruit 0.002 0.0 0.0 0.1 1.7 0.7Cereal 0.1 1.1 0.2 0.5 5.3 1.1Fish 0.5 0.6 0.3 1.5 1.7 0.8Tot kU AGEs/Week 41.5 7.5 55.6 11.7

Correlating dietary AGEs in the Japanese dietwith AD incidence

Our results associate a diet low in meat and dairyproducts with decreased AD incidence. Table 5A givesAGE values for food categories for various years. ForJapan, the AGE value for meat rose from 24% of thetotal in 1961 to 52% in 2005. An incremental increasein cheese and meat intake corresponds to an enhancedtotal dietary AGE intake in the most recent years(Table 5A). Cognitive changes occur at least 10 yearsbefore the clear diagnosis of AD dementia. For this rea-son, one study suggests that imposing a longer delaybetween dietary assessment and the correlation withAD incidence is appropriate [6]. In agreement, we ana-lyzed the correlation between changes in dietary AGEintake with AD prevalence. We considered dietary data25 years before the epidemiological studies investi-gating AD incidence in Japan since diet affects brainfunction several years before AD incidence (Fig. 2).Figure 2 shows changes in AGE values for Japan for1961–2008. A nearly linear increase occurs to about1980, after which the change becomes more gradual.The r value for the second-order fit to the data is 0.998.The estimated AGE value for 1960–1983, precedingthe AD prevalence data by 25 years, changed by abouta factor of three. The AD prevalence for people olderthan 65 years increased from 1% in 1985 to 7% in 2008.

Fig. 2. Dietary AGE versus year for Japan.

Thus, change in AD prevalence is apparently muchgreater than estimated from change in AGE values.

Correlating dietary AGE intake and AD incidencein different countries

Tables 5B and C give AGE values for national dietsfor the two AD data sets. Meat is the largest single

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10 L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease

Table 5BAGE values (´1000 kU/d) for national diets 20 years before AD prevalence data in Ref. [6].

Canada China Finland Italy Japan Nigeria Singapore Spain Sweden UK USAFood 1972 1967 1961 1967 1965 1973 1965 1967 1967 1965 1972

Cheese 0.59 0.00 0.28 1.30 0.04 0.02 0.37 1.09 0.57 0.70Eggs 0.15 0.02 0.08 0.10 0.14 0.02 0.07 0.11 0.12 0.16 0.19Fish 0.20 0.07 0.24 0.18 0.73 0.08 0.50 0.39 0.36 0.30 0.22Fruit 0.24 0.01 0.11 0.34 0.11 0.18 0.10 0.16 0.21 0.16 0.24Legumes 0.01 0.00 0.01 0.03 0.02 0.11 0.02 0.05 0.02 0.02 0.01Meat 10.42 1.11 3.80 5.24 1.26 0.79 3.31 4.26 5.70 7.66 11.86Rice 0.00 0.06 0.00 0.00 0.09 0.00 0.10 0.00 0.00 0.00 0.00Soya beans 0.00 0.23 0.00 0.00 0.28 0.00 0.09 0.00 0.00 0.00 0.00Starchy roots 0.13 0.21 0.22 0.09 0.12 0.25 0.03 0.20 0.17 0.20 0.11Tree nuts 0.35 0.00 0.00 0.82 0.00 0.37 0.27 1.00 0.30 0.16 0.30Vegetable oil 0.58 0.10 0.18 0.94 0.26 0.50 0.02 0.86 0.82 0.48 0.96Vegetables 0.21 0.15 0.05 0.43 0.33 0.13 0.17 0.41 0.11 0.18 0.27Wheat 0.23 0.17 0.38 0.50 0.13 0.27 0.14 0.34 0.23 0.29 0.21Total 13.11 2.13 5.35 9.97 3.51 2.62 4.85 8.54 9.11 10.20 15.07

Table 5CAGE values (´1000 kU/d) for national diets 20 years before AD prevalence data in developing countries [7].

China Cuba Egypt India Korea (Republic) Nigeria Sri LankaFood 1985 1979 1979 1981 1980 1975 1983

Cheese 0.02 0.42 0.68 0.05 0.02Eggs 0.05 0.09 0.02 0.00 0.07 0.02 0.02Fish 0.10 0.18 0.06 0.04 0.56 0.10 0.21Fruit 0.03 0.13 0.11 0.07 0.06 0.18 0.21Legumes 0.00 0.05 0.04 0.07 0.01 0.04 0.02Meat 2.10 3.52 1.22 0.40 1.46 0.72 0.38Rice 0.08 0.04 0.02 0.06 0.12 0.00 0.09Soya beans 0.15 0.00 0.00 0.00 0.48 0.00 0.00Starchy roots 0.13 0.14 0.03 0.04 0.05 0.26 0.08Tree nuts 0.00 0.00 0.00 0.01 0.30 0.34 0.00Vegetable oil 0.96 1.72 0.56 0.30 0.90 0.46 0.18Vegetables 0.22 0.08 0.38 0.13 0.54 0.13 0.08Wheat 0.25 0.21 0.46 0.23 0.16 0.27 0.11Total 3.24 6.48 3.09 1.35 4.76 2.54 1.38

Table 5AAGE values (´1000 kU/d) for the national diet of Japan for various

years.

Food 1961 1965 1971 1981 1992 2005

Cheese 0.04 0.04 0.04 0.15 0.23 0.32Eggs 0.10 0.14 0.18 0.18 0.22 0.21Fish 0.68 0.73 0.93 0.89 0.91 0.84Fruit 0.08 0.11 0.17 0.15 0.14 0.03Legumes 0.02 0.02 0.02 0.01 0.01 0.01Meat 0.83 1.26 2.36 4.19 4.36 5.14Rice 0.10 0.09 0.08 0.06 0.06 0.05Soya beans 0.32 0.28 0.32 0.29 0.35 0.34Starchy roots 0.14 0.12 0.07 0.07 0.07 0.06Vegetable oil 1.04 1.30 1.90 3.00 3.67 4.36Vegetables 0.27 0.33 0.36 0.34 0.34 0.30Wheat 0.12 0.13 0.15 0.17 0.18 0.17Total 3.73 5.06 6.64 9.43 10.55 11.83

contributor to AGEs for all countries, making up from32% of the total for Nigeria to 80% for Canada andthe United States (Table 5B). We plotted values inTables 5B and C against the corresponding AD preva-

lence data 20 years later. Figure 3 shows results for the11 countries considered in the 1997 study [12]. Thesecond-order regression fit is better than the linear fitin that the R value is slightly higher (0.95 versus 0.94)and the regression line goes near the origin.

Figure 4 shows results for seven developing coun-tries from the 2014 study [13]. The graph omits Brazilsince the value Grant used [13], 2.7%, has considerableuncertainty (0.1%–5.2%) and the value when plottedin Fig. 2 is several standard deviations from the regres-sion fit to the other values. For this data set, a linearregression fit suffices (r = 0.91) and the regression linenearly goes through the origin.

DISCUSSION

Several data from different experimental and epi-demiologic studies strongly support the hypothesis thatdiet and dietary AGE intake play a role in AD progres-sion[16].Indeed,highlevelsofdietaryAGEs(measured

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L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease 11

Fig. 3. AD prevalence versus dietary AGE 20 years before ADprevalence for the 11 countries in the 1997 study [12].

as serum level of MG) are associated with faster mem-orydeclineinnondementedelderly[42].Variousstudiesalso investigated the effect of dietary AGEs and serumAGE levels in aging and in diseases that are risk factorsfor AD [43, 44]. However, no epidemiological or cohortstudy has investigated the effect of dietary AGEs in ADincidence. Since Uribarri and colleagues investigatedAGE content in more than 500 dietary compounds [17],cohort studies investigating how defined dietary pat-ternsaffectADincidencemayberevisitedtoextrapolatethe correlation between dietary AGE content and ADprogression.SeveralepidemiologicstudiesinvestigatedtheMeDi’sbeneficial effect inpreventingADincidence[6, 34]. We extrapolated the AGE content in the MeDitertiles diet that Scarmeas and colleague describe in theWHICAP cohort study [27, 34–38, 45]. Two models ofAGE extrapolation showed that a diet highly adherentto the MeDi yields lower AGE content. We also showthathighdietaryAGEscorrelatewithenhancedADinci-dence. These results fully agree with the recent studyshowing that ahigh levelofcirculatingAGEs inhumanscorrelates with temporal alterations in cognition [15].

Oxidative stress is a major risk factor for AD pro-gression [1, 16, 46, 47]. AGEs are risk factors for ADbecause they induce oxidative stress and inflamma-tion [1, 16]. In agreement, our results indicate that theMeDi helps prevent AD also because it leads to lowerAGE content, decreasing oxidative stress. Restrictingdietary AGEs helps prevent diabetes and kidney dys-function [16], whereas no study has investigated how

Fig. 4. AD prevalence versus dietary AGE 20 years before ADprevalence for seven developing countries [13].

restricting dietary AGEs affects AD progression. Ourresults indicate that a low-AGE diet may prevent AD.

Although a general consensus exists about thehow the MeDi helps prevent cognitive dysfunction, adiscrepancy remains among the cohort studies investi-gating how the MeDi affects AD incidence [6]. Theseinconsistent results may be due to differences in defin-ing the cutoff of dietary intake of each food group tocalculate MeDi adherence. We extrapolated the dietaryAGE content from the Three-City cohort study, whichfoundanotsignificantcorrelationbetweenMeDiadher-ence and AD incidence [7]. Those authors also reportedsignificant differences only in some food groups whenconsidering the MeDi tertiles [7]. In agreement, wefound nosignificant difference in the AGE contentacross MeDi tertiles. Our results may explain the dif-ferences reported across studies investigating how theMeDi prevents AD. We also found that when no sig-nificant difference in AGE content exists among theMeDi tertiles, no significant correlation with diet andAD incidence exists either. Indirectly, this finding fur-ther supports our results from revisiting the WHICAPstudy,underlining the roleofdietaryAGEs—especiallythose from meat—in promoting AD.

The MeDi is low in meat and dairy products, whichcontain a high level of AGEs. The traditional Japanesediet, which differs markedly from the MeDi, is also lowin meat and dairy products. Indeed, high adherence tothe traditional Asiatic diet prevents dementia in Asiaticpopulations [48]. Our epidemiological study confirms

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12 L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease

that the traditional Japanese diet helps prevent AD alsobecause of a low AGE content, confirming that dietaryAGEs are a risk factor for AD.

The MeDi also prevents AD incidence by offer-ing more micronutrients, vitamins, and antioxidants[49, 50]. However, our data show that AGE intakehelps modulate AD incidence. In particular, for boththe MeDi and Japanese diet, lower meat intake cor-responds to reduced dietary AGEs and decreased ADincidence. Spain and Italy, which have a MeDi, showless meat intake, thereby decreasing dietary AGEs andlowering AD incidence. Taken together, these resultsindicate that lower dietary AGEs help prevent AD.

Deleterious changes to the brain occur years ordecades before diagnosis of AD. For this reason, inves-tigating the effect of dietary patterns on cognitivedecline in a longer time frame would be more accurate[6, 11]. Indeed, diet may start to affect brain functionseveral years before diagnosis of AD. In agreement, adietary intervention lowering AGE intake for only 6weeks did not modify endothelial function and inflam-mation, which are risk factors for AD [51]. This findingfurther supports the hypothesis that diet and dietaryAGEs must be examined for several years before ADincidence. Therefore, we correlated the dietary AGEintake provided by national dietary supply data withthe data of AD incidence 20 years later.

Estimates of dietary AGE intake based on FAOnational dietary supply data are consistent with sevenstudies that used food diaries to determine AGE intakesin people. Average intake for low-AGE groups in thefirst six studies was 3,900 kU/d [15], whereas thatfor high-AGE groups was 15,000 [52]. In the seventhstudy, values were 6,300 kU/d for Mexicans, 11,600kU/d for Mexican Americans, and 19,800 kU/d forwhite, non-Hispanic Americans [52]. Values for devel-oping countries ∼1975–1985 ranged from 1,330 to5,700 kU/d, whereas values for developed countriesfrom 1965 to 1972 ranged from 9,930 to 14,860 kU/d.However, FAO data reflect food supplied to consumers,of which approximately 30% is lost through wasteor spoilage. Thus, the estimates in Tables 1–3 shouldprobably be reduced by 30%.

The MeDi is often touted as one that would lowerrisk of developing AD. The MeDi generally consideredprobably approaches that of later mid-20th-centuryCyprus. The estimated dietary AGE value for Cyprus in1961, the earliest year for which FAO data are available,is 7,320 kU/d. Although that is less than half the presentU.S. value (18,000 kU/d), it is still about double thosefor the developing countries in the late 1970s to early1980s, values associated with lower rates of AD.

A study of dietary patterns and risk of AD sup-ports these findings. That analysis involved 2,148community-dwelling individuals, 253 of whom devel-oped AD during a 3.0-year follow up. It found lowerrisk “characterized by higher intakes of salad dressing,nuts, fish, tomatoes, poultry, cruciferous vegetables,fruits, and dark and green leafy vegetables and a lowerintake of high-fat dairy products, red meat, organ meat,and butter” [45].

The results of these ecological studies support thework by Cai [15] that AGEs appear to be importantrisk factors for AD. Studies have associated severalfactors with risk of AD. One reason for the incon-sistency among the three studies could be that otherrisk-modifying factors have also changed. Such factorscould include trace minerals in the brain [53], obesityrates [54], 25-hydroxyvitamin D concentrations [55],physical activity levels [56], and alcohol consumptionrates [57]. Researchers recently reviewed these andother factors [13, 23, 58].

Puzzlingly, the AD prevalence data in Figs. 3 and4 have much different relations to the estimated AGEvalues: the slope for the more recent data set is abouttwice that for the older data set out to an AGE valueof about 7,000 kU. The cause of this discrepancy isunknown, although several explanations are possible:

• Different definitions of AD prevalence may havebeen used, including whether the values are age-adjusted.

• Cooking methods may have changed between1963–1973 and 1975–1985.

• Other AD risk factors, such as obesity rates, mayhave increased along with dietary AGE values.Sugar contributes to obesity [59] but not to theAGE value.

Although both the analysis of AGEs content in theWHICAP study and the ecological studies indicate thatdietary AGEs are a risk for AD, these two approachesshow some differences. Indeed, the extrapolation ofAGEs content in the WHICAP study shows that a lowchange in dietary AGEs results in a larger differencein AD incidence compared the ecological studies. Thisdifference can be due to the other beneficial nutrientsprovided by a high adherence to the MeDi. It could alsobe due to using national dietary data from the period 20years prior to the AD prevalence data in the other analy-ses. However, our results clearly indicate that both theWHICAP and the ecological studies show the sametendency, revealing that AGEs are a risk for AD.

Hill’s criteria for causality in a biological systemcan help evaluate whether dietary AGEs are causally

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L. Perrone and W.B. Grant / Dietary AGEs and Alzheimer’s Disease 13

linked to risk of AD [61]. The criteria important fordiet and disease include strength of association, con-sistent findings in different populations, temporality,biological gradient, plausibility (e.g., mechanisms),and experiment (e.g., randomized controlled trials oranimal model studies). Considering confounding fac-tors is also important [62]. From the findings presentedhere, Hill’s criteria seem to be reasonably satisfied.Some analyses found a strong association betweendietary AGEs and prevalence of AD as well as astrong biological gradient. The findings for differentpopulations showed direct correlations, but the magni-tudes of the associations were not the same, probablydue to the approximations used in this study. Possi-ble mechanisms explaining how AGEs cause chronicdisease were previously discussed [16]. Some mecha-nisms related to the MeDi include beneficial effects oninflammation, vascular endothelium, and insulin resis-tance [63]. Animal model studies support the link [15].As for confounding factors, other mechanisms mayexplain some of the findings, such as the link betweenmeat consumption and risk of AD. For example, meatand cheese are sources of cholesterol, which is involvedin AD pathology [64]. Red meat is also a source ofiron, deposition of which in the brain is associated withincreased risk of AD [65, 66].

Thus, several of Hill’s criteria for causality linkingdietary AGEs to risk of AD appear generally satis-fied. However, other mechanisms could explain thelink between consuming meat and risk of AD. Thus,further research is required to sort out the mecha-nisms. Since dietary AGEs depend on cooking method,whereas cholesterol and iron from meat do not, suchexperiments could be designed.

We offer here evidence that dietary AGEs promoteAD, mostly in association with enhanced meat intake.Thus, our results agree with those in all studies inves-tigating how restricting dietary AGEs and serum AGElevels affects diseases that are risk factors for AD[42–44], showing that dietary AGEs play a role in ADincidence. Further dietary AGE restriction studies arenecessary. However, our data strongly underline therelevance of these cohort AGE restriction studies withthe aim to find a nutrition strategy to prevent AD.

ACKNOWLEDGMENTS

WBG receives funding from Bio-Tech Pharmacal(Fayetteville, AR) and MediSun Technology (High-land Park, IL). LP thanks the “Actions iniciatives del’Universite´ de Poitiers” for funding. LP thanks also

the CNRS (CDD Chercheur) and the Marie Curie IRGfunding N. 224892.

Authors’ disclosures available online (http://j-alz.com/manuscript-disclosures/14-0720r2).

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