High-fat diet aggravates amyloid-beta and tau pathologies in the 3×Tg-AD mouse model

Article (PDF Available)inNeurobiology of aging 31(9):1516-31 · November 2008with179 Reads
DOI: 10.1016/j.neurobiolaging.2008.08.022 · Source: PubMed
Abstract
To investigate potential dietary risk factors of Alzheimer's disease (AD), triple transgenic (3xTg-AD) mice were exposed from 4 to 13 months of age to diets with a low n-3:n-6 polyunsaturated fatty acid (PUFA) ratio incorporated in either low-fat (5% w/w) or high-fat (35% w/w) formulas and compared with a control diet. The n-3:n-6 PUFA ratio was decreased independently of the dietary treatments in the frontal cortex of 3xTg-AD mice compared to non-transgenic littermates. Consumption of a high-fat diet with a low n-3:n-6 PUFA ratio increased amyloid-beta (Abeta) 40 and 42 concentrations in detergent-insoluble extracts of parieto-temporal cortex homogenates from 3xTg-AD mice. Low n-3:n-6 PUFA intake ratio increased insoluble tau regardless of total fat consumption, whereas high-fat diet incorporating a low n-3:n-6 PUFA ratio also increased soluble tau compared to controls. Moreover, the high-fat diet decreased cortical levels of the postsynaptic marker drebrin, while leaving presynaptic proteins synaptophysin, SNAP-25 and syntaxin 3 unchanged. Overall, these results suggest that high-fat consumption combined with low n-3 PUFA intake promote AD-like neuropathology.
Author's personal copy
Neurobiology of Aging 31 (2010) 1516–1531
High-fat diet aggravates amyloid-beta and tau pathologies
in the 3xTg-AD mouse model
Carl Julien
a,b
, Cyntia Tremblay
a,b
, Alix Phivilay
a,b
, Line Berthiaume
c
,
Vincent Émond
a,b
, Pierre Julien
c
, Frédéric Calon
a,b,
a
Faculty of Pharmacy, Laval University, Quebec, QC, Canada
b
Molecular Endocrinology and Oncology Research Center, Centre Hospitalier de l’Université Laval (CHUL) Research Center, Quebec, QC, Canada
c
Quebec Lipid Research Centre, CHUL, Quebec, QC, Canada
Received 20 June 2008; received in revised form 22 August 2008; accepted 29 August 2008
Available online 15 October 2008
Abstract
To investigate potential dietary risk factors of Alzheimer’s disease (AD), triple transgenic (3xTg-AD) mice were exposed from 4 to 13
months of age to diets with a low n-3:n-6 polyunsaturated fatty acid (PUFA) ratio incorporated in either low-fat (5% w/w) or high-fat (35%
w/w) formulas and compared with a control diet. The n-3:n-6 PUFA ratio was decreased independently of the dietary treatments in the frontal
cortex of 3xTg-AD mice compared to non-transgenic littermates. Consumption of a high-fat diet with a low n-3:n-6 PUFA ratio increased
amyloid-! (A!) 40 and 42 concentrations in detergent-insoluble extracts of parieto-temporal cortex homogenates from 3xTg-AD mice. Low
n-3:n-6 PUFA intake ratio increased insoluble tau regardless of total fat consumption, whereas high-fat diet incorporating a low n-3:n-6
PUFA ratio also increased soluble tau compared to controls. Moreover, the high-fat diet decreased cortical levels of the postsynaptic marker
drebrin, while leaving presynaptic proteins synaptophysin, SNAP-25 and syntaxin 3 unchanged. Overall, these results suggest that high-fat
consumption combined with low n-3 PUFA intake promote AD-like neuropathology.
© 2008 Elsevier Inc. All rights reserved.
Keywords: Polyunsaturated fatty acid; Dietary fat; Amyloid-beta; tau; Drebrin; PAK; Cofilin; LR11; Docosahexaenoic acid; GFAP; Synaptophysin
Abbreviations: 3xTg-AD, triple transgenic mouse model of Alzheimer’s
disease; ApoE, apolipoprotein E; APP, amyloid precursor protein; ARA,
arachidonic acid; CTF, C-terminal fragment; DHA, docosahexaenoic acid;
Diet A, low-fat control diet; Diet B, low-fat with low n-3:n-6 PUFA ratio
diet; Diet C, high-fat with low n-3:n-6 PUFA ratio diet (high-fat diet); GFAP,
glial fibrillary acidic protein; DPA, docosapentaenoic acid; DTA, docosate-
traenoic acid; EPA, eicosapentaenoic acid; LA, linoleic acid; LNA, linolenic
acid; LR11, sortilin-related receptor SorLA/LR11; MUFA, monounsatu-
rated fatty acids; NonTg, non-transgenic; n.s., non significant; O.D., relative
optical density; PAK, p21-activated kinase; PSD-95, postsynaptic density-
95; PUFA, polyunsaturated fatty acids; SNAP-25, synaptosome-associated
protein-25; SFA, saturated fatty acid.
Corresponding author at: Molecular Endocrinology and Oncology
Research Center, Centre Hospitalier de l’Université Laval (CHUL) Research
Center, 2705 Laurier Boulevard, Quebec, QC, Canada G1V 4G2.
Tel.: +1 418 654 2296; fax: +1 418 654 2761.
E-mail address: frederic.calon@crchul.ulaval.ca (F. Calon).
1. Introduction
From a therapeutic point of view, environmental fac-
tors are easier to modify than genetic factors. Dietary fats
have been shown to influence the risk of developing cardio-
vascular diseases, peripheral metabolic diseases and, more
recently, Alzheimer’s disease (AD) (Mattson, 2004; Pasinetti
et al., 2007). Epidemiological studies have first established
an association between a high intake of saturated fats an
increased risk of developing cognitive impairment and AD
(Luchsinger et al., 2002; Morris et al., 2003a; Parrott and
Greenwood, 2007). The most useful animal models of AD
include transgenic mice modeling amyloid-! (A!
40
and
A!
42
) accumulation caused by the overexpression of a mutant
amyloid precursor protein (APP) gene (ex: Tg2576 mouse
line with APP
K670N,M671L
) or the combination of mutant
APP with mutant PS1 (McGowan et al., 2006). Studies in the
Tg2576 mouse model of AD have evidenced the deleterious
0197-4580/$ see front matter © 2008 Elsevier Inc. All rights reserved.
doi:10.1016/j.neurobiolaging.2008.08.022
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C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531 1517
effect of high caloric intake (based on saturated fat) on cogni-
tive performance and A! burden in the brain (Ho et al., 2004;
Li et al., 2003) or inthe small intestinal enterocytes (Galloway
et al., 2008). Conversely, dietary calorie restriction is associ-
ated with improved cognitive performance and reduced A!
pathologies in old monkeys (Qin et al., 2006). High choles-
terol consumption also leads to increased A! burden in the
APP
K670N,M671L
/PS1
M146V
transgenic animal model of AD
(Refolo et al., 2000).
Later on, epidemiological analyses based on semiquanti-
tative food frequency questionnaire showed that individuals
reporting a reduced consumption of n-3 polyunsaturated fatty
acid (PUFA) had an increased risk of developing AD (Morris
et al., 2003a; Morris et al., 2003b). This is also supported by
a prospective follow-up analysis of blood n-3 PUFA con-
tent (Schaefer et al., 2006). A recent randomized clinical
trial has shown a beneficial effect of n-3 PUFA on cognitive
functions limited to patient with very mild AD (Freund-
Levi et al., 2006). In animal models, A! deposition, synaptic
marker defects and cognitive impairment were all shown to
be reduced after exposure to a diet enriched in docosahex-
aenoic acid (DHA), a n-3 PUFA commonly found in fatty
fish (Calon et al., 2004, 2005; Lim et al., 2005). Detrimental
effects of high-fat diet and the protective effect of DHA on
A! pathology are supported by a more recent analysis in the
APP
K670N,M671L
/PS1
dE9
mouse model of AD (Oksman et al.,
2006). Taken together, these data suggest that dietary lipids
regulate AD neuropathology, at least in terms of A! content.
AD is also characterized by the presence of neurofibrillary
tangles in the brain, formed by insoluble hyperphosphory-
lated tau protein displaying a paired helical filament (PHF)
structure (Binder et al., 2005; Lee et al., 2001; Tremblay et
al., 2007). Interestingly, the conversion of normal tau into
its PHF form usually correlates better with cognitive symp-
toms of AD than measures of A! pathology (Arriagada et
al., 1992; Bennett et al., 2004; Giannakopoulos et al., 2003;
Nagy et al., 1995; Näslund et al., 2000; Tremblay et al.,
2007). For instance, very high post mortem concentrations
of A! can be found in the brain of patients with no detectable
cognitive deficit (Dickson et al., 1992; Forman et al., 2007;
Tremblay et al., 2007). This has led to the generation of the
3xTg-AD mouse model of AD that develops both A! and
tau pathologies consequent to the expression of three mutated
transgenes, namely PS1
M146V
knockin, APP
K670N,M671L
, and
tau
P301L
(Oddo et al., 2003a;Oddo et al., 2003b).A first group
of investigators found that DHA treatment was associated
with reduced accumulation of phosphorylated and total tau
in the soluble fractions of protein extracted from the whole
brain of 3xTg-AD mice (Green et al.,2007).In a second study,
3xTg-AD mice performed better in the Morris water maze
paradigm and accumulated less tau in their brain following
calorie restriction (Halagappa et al., 2007).
Taken together, these data suggest that underconsumption
of n-3 PUFA coupled to ingestion of high level of calories
from fat, which are commonplace in our modern society,
might increase the incidence of AD by accelerating its patho-
genetic process (Calon and Cole, 2007; Calon, 2006; Pasinetti
et al., 2007). Because the effects of dietary fats in AD remain
very hard to demonstrate in clinical trials due to ethical and
financial constraints (Calon, 2006), animal models of AD
provide an opportunity to monitor precisely the intake of
food in relation with subsequent alterations in brain mark-
ers of AD pathology. Since n-3 PUFA and total fats were the
subject of separate studies, which were rather focused on A!
pathology, we exposed the 3xTg-AD animal model of AD
to n-3 PUFA deprivation alone (Diet B) or combined with a
high-fat westernized diet (Diet C) to determine the quantita-
tive impact of these precisely formulated diets on markers of
A!, tau and synaptic pathologies.
2. Materials and methods
2.1. Material
Unless otherwise noted, reagents were obtained from
Sigma–Aldrich (St. Louis, MO). Antibodies used: anti-actin
at 1:5000 dilution (Chemicon International, Temecula, CA),
anti-Amyloid !/A4 Protein Precursor
770
(740–770) (C31)
(1:50; Bachem, Torrance, CA) for C-terminal fragment of
APP (CTF-" and CTF-!), and anti-A! clone 6E10 (1:2000;
Chemicon International) for APP measures, anti-amyloid
oligomers A11 (1:1000; Millipore, Billerica, MA) to detect
soluble amyloid oligomers, anti-Apolipoprotein E (1:2000;
Novus Biologicals, Littleton, CO), anti-Cofilin (1:200; Cell
Signaling Technology, Beverly, MA), anti-Drebrin mono-
clonal clones MX823 (1:500; Progen, Heidelberg, Germany)
and M2F6 (1:1000; MBL, Woburn, MA), anti-glial fib-
rillary acidic protein (GFAP) (1:10,000; Sigma–Aldrich),
anti-LR11/SorLA/gp250 (1:1000; BD Biosciences, San Jose,
CA), anti-PAK1/2/3 (1:1000; Cell Signaling Technology),
anti-PSD-95 clone K28/43 (1:5000; Upstate Biotechnol-
ogy, Lake Placid, NY), anti-synaptosome-associated protein
(1:1000; SNAP-25) (Covance), anti-Synaptophysin clone
SVP-38 (1:10,000; Chemicon International), anti-Syntaxin
3 (1:10,000; Novus Biologicals, Littleton, CO), anti-
total tau clone tau-13 (1:5000; Covance, Berkeley, CA),
and anti-phosphorylated tau clones PHF1 (1:500; Novus
Biologicals), CP13 (1:1000; gift from Dr Peter Davies,
Albert Einstein College of Medicine), and AT270 (1:500;
Pierce). Immunodetection was revealed with Horseradish
Peroxidase-conjugated AffiniPure Donkey Anti-Rabbit or
Goat Anti-Mouse (1:60,000 each; Jackson ImmunoResearch,
West Grove, PA) secondary antibodies and detected by ECL
(GE Healthcare, Baie d’Urfé, QC, Canada).
2.2. Animals and diets
Triple-transgenic mice (3xTg-AD) harboring three mutant
genes, amyloid-beta precursor protein (APPswe), presenilin-
1 (PS1M146V), and tau (P301L), were from a colony
maintained in our animal facilities and generated from
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founder mice obtained from Dr Frank LaFerla (Oddo et al.,
2003b). The non-transgenic (NonTg) mice used here are lit-
termates from the original PS1-knockin mice and are on the
same background as the 3xTg-AD mice (C57BL6/129SvJ).
3xTg-AD mice and non-transgenic age-matched controls
were assigned randomly into three groups according to their
dietary treatment at the age of 4 months. Mice were fed until
the age of 13.2 ± 0.2 months (mean ± S.E.M.) with either:
Diet A, a 5% fat (w/w) control diet similar to laboratory chow
found in most institutions; Diet B, a 5% fat (w/w) diet with a
very low amount of linolenic acid and, thereby, a low n-3:n-
6 PUFA ratio; and Diet C, a high-fat westernized diet with
35% fat (w/w) and a similarly low n-3:n-6 PUFA ratio. Diet
formulas and composition in fatty acids, as confirmed by gas
chromatography, are detailed in Table 1. The formula of each
purified diet (produced in collaboration with Dr Matthew
Ricci from Research Diets Inc.) has been precisely deter-
mined to avoid any batch to batch variations. The diets are
exactly the same in terms of fibers, vitamins, minerals, and
antioxidants and do not contain phytoestrogens.
Table 1
Comparison of dietary treatments.
Diet A (control) Diet B (low fat and low n-3:n-6 ratio) Diet C (high fat and low n-3:n-6 ratio)
5% (w/w) fat 5% (w/w) fat 35% (w/w) fat
% (w/w) % (cal/cal) % (w/w) % (cal/cal) % (w/w) % (cal/cal)
Protein 20 21 20 21 27 21
Carbohydrate 66 68 66 68 25 19
Fat 5 12 5 12 35 60
Total
(kcal/g)
100 kcal 100 kcal 100 kcal
3.9 3.9 5.3
Ingredient g kcal g kcal g kcal
Casein 200 800 200 800 200 800
dl-Methionine 3 12 3 12 3 12
Corn starch 150 600 150 600 125 500
Sucrose 500 2000 500 2000 52.5 210
Cellulose, BW200 50 0 50 0 50 0
Safflower oil 0 0 25 225 125 1125
Soybean oil 10 90 25 225 0 0
Lard 0 0 0 135 1215
Canola oil 40 360 0 0 0 0
Cholesterol, USP 0.6 0 0.6 0 3 0
Ethoxyquin 0.001 0 0.001 0 0.001 0
Minerals (S19101) 35 0 35 0 35 0
Vitamins (V15908) 10 40 10 40 10 40
Choline bitartrate 2 0 2 0 2 0
Total 1000.6 3902 1000.6 3902 740.5 3902
Fatty acid (FA ) content (as determined by gas chromatography in the pelleted diet)
g/kg g/kg g/kg
C18:2n-6 LA 13.44 36.04 140.72
C20:4 n-6 ARA 0 0 0.39
C22:4 n-6 DTA 0 0 0
C22:5 n-6 DPA 0 0 0
Total n-6 PUFA 13.44 36.25 142.56
C18:3 n-3 LNA 3.37 0.47 1.98
C20:5 n-3 EPA 0 0 0
C22:6 n-3 DHA 0 0 0
Total n-3 PUFA 3.37 0.47 1.98
n-3:n6 ratio 0.25 0.01 0.01
Total fatty acids (g per kg of diet) 44 47 247
fatty acid in triglycerides (%w/w) 99% 99% 99%
Abbreviations: ARA, arachidonic acid; DHA, docosahexaenoic acid; DPA, docosapentaenoic acid; DTA, docosatetraenoic acid; EPA, eicosapentaenoic acid;
FA, fatty acids; LA, linoleic acid; LNA, linolenic acid; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acid; USP,
United States Pharmacopeia.
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C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531 1519
Animals were sacrificed under deep anesthesia with
ketamine/xylazine and perfused via transcardiac infusion
with phosphate saline buffer (PBS; 1X: 1 mM KH
2
PO
4
,
10 mM Na
2
HPO
4
, 137 mM NaCl, 2.7 mM KCl, pH 7.4) con-
taining a cocktail of protease inhibitors (SIGMAFAST
TM
Protease Inhibitor Tablets, Sigma–Aldrich, St. Louis, MO)
along with phosphatase inhibitors (50 mM sodium fluoride
and 1 mM sodium pyrophosphate). Frozen extracts of the
frontal cortex and the parieto-temporal cortex were dissected
and kept at 80
C.
2.3. Lipid extraction and gas chromatography
The procedures were similar to previous publications
(Julien et al., 2006; Lepage and Roy, 1986). Approximately
20 mg of frozen frontal cortex tissue was homogenized with
BHT-Methanol (Sigma, St. Louis, MO, USA) and with 22:3
n-3 methyl ester as an internal standard (NuChek Prep com-
pany, Elysian, MN, USA) at a concentration of 500 #g/g of
tissue. Two volumes of chloroform (J.T. Baker, Phillipsburg,
NJ, USA) and NaH
2
PO
4
buffer solution were added to the
resulting homogenate. After centrifugation at 3500 rpm for
7 min, the lower layer was collected (Folch et al., 1957).
This procedure was repeated twice and the two extracts were
pooled and brought to dryness with a stream of nitrogen.
Lipid extracts were transmethylated with BF
3
–MeOH (All-
tech, State college, PA, USA) at 100
C for 60 min. After
cooling down, water and hexane (J.T. Baker, Phillipsburg,
NJ, USA) were added. A 3-min centrifugation allowed sepa-
ration of the phases and the upper layer was collected. These
last steps were performed twice to pool the hexane extracts.
Hexane was dried down to about 100 #l, transferred to a gas
chromatography autosampler vial and capped under nitro-
gen. Fatty acid methyl esters were quantified on a model
6890 series gas chromatograph (Agilent Technologies, Palo
Alto, CA, USA) using a FAST-GC method. One #l of each
sample were injected at a 25:1 split ratio. The identification
of the fatty acid methyl ester peak was performed for each
sample by comparison to the peak retention times of a 28-
component methyl standard (462, Nu-Chek Prep, Elysian,
MN, USA) (Julien et al., 2006).
2.4. Biochemical assessment of tau and Aβ pathologies
After adding 8 volumes of Tris-buffered saline (TBS)
containing Complete
TM
protease inhibitors cocktail (Roche,
Indianapolis, IN), 10 #g/ml of pepstatin A, 0.1 mM EDTA
and phosphatase inhibitors (1 mM each of sodium vana-
date and sodium pyrophosphate, 50 mM sodium fluoride),
frozen samples were sonicated briefly (3 × 10 s) and cen-
trifuged at 100,000 × g for 20 min at 4
C to generate a
TBS-soluble intracellular and extracellular fraction (soluble
fraction). The TBS-insoluble pellet was sonicated in 5 vol-
umes of lysis buffer (150 mM NaCl, 10 mM NaH
2
PO
4
, 1%
Triton X-100, 0.5% SDS, and 0.5% deoxycholate) contain-
ing the same protease and phosphatase inhibitor cocktail.
The resulting homogenate was centrifuged at 100,000 × g
for 20 min at 4
C to produce a lysis buffer-soluble fraction
(detergent-soluble fraction). The pellets (detergent-insoluble
fractions) were homogenized in 175 #l of 90% formic acid
followed by a short sonication (3 × 10 s). The resultant sus-
pension was centrifuged (15,000 × g;4
C; 20 min) and 20 #l
of the supernatant was neutralized with 1:13 dilution of Tris-
base 2 M (pH 10) to be used for ELISA (see below). The
rest of the supernatant was dried out by SpeedVac (Thermo
Savant, Waltham, MA), solubilized in Leammli’s buffer and
processed for Western immunoblotting.
Insoluble A!40 and A!42 were measured by the ! Amy-
loid [1–40] and [1–42] ELISA kits (Biosource, Camarillo,
CA). Soluble A!40 and A!42 were measured using Human
! Amyloid (1–42) ELISA kit WAKO, High Sensitive (WAKO,
Osaka, Japan). The two ELISAs were done according to the
manufacturer recommendations and the plates were read at
450 nm using a Synergy
TM
HT multi-detection microplate
reader (Biotek, Winooski, VT).
2.5. Western Immunoblotting
For Western immunoblotting, protein concentration was
determined using bicinchoninic acid assays (Pierce, Rock-
ford, IL). Equal amounts of protein per sample (15 #g of total
protein per lane) were added to Laemmli’s loading buffer,
heated to 95
C for 5 min before loading, and subjected to
sodium dodecyl sulfate-polyacrylamide gel electrophoresis.
Proteins were electroblotted onto PVDF membranes (Immo-
bilon, Millipore, Massachusetts) before blocking in 5%
nonfat dry milk and 1% bovine serum albumin (BSA) in PBS
-Tween 20 for 1 h. Membranes were immunoblotted with
appropriate primary and secondary antibodies followed by
chemiluminescence reagents (ECL, Amersham/Pharmacia
biotech, Piscataway, NJ or Supersignal, Pierce, Rockford,
IL). Band intensities were quantified using a KODAK Image
Station 4000 MM Digital Imaging System (Molecular Imag-
ing Software version 4.0.5f7, KODAK, New Haven, CT).
2.6. Oxidized proteins
Levels of oxidized proteins were evaluated with an
OxyBlot
TM
protein oxidation detection kit (S7150) from
Chemicon International, as described (Calon et al., 2004; Lim
et al., 2001).
2.7. Soluble amyloid oligomers
A dot blot assay with the A11 antibody was performed to
detect soluble amyloid oligomers in TBS fractions of brain
cortex (Kayed et al., 2003). Briefly, 1 #l aliquots (3 #g) in
duplicates were applied onto a low fluorescence PVDF mem-
brane (GE Healthcare) previously activated with methanol
and equilibrated in TBS. The membrane was blocked (2 h
at room temperature) with SeaBlock buffer (Pierce biotech-
nology, Rockford, IL) and incubated with anti-oligomer
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1520 C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531
antibody (A11, 1:1000) diluted in SeaBlockovernight at 4
C.
Washes were performed in TBS containing 0.01% Tween-20.
The membrane was incubated with anti-rabbit IgG conju-
gated with Qdot
®
705 (Invitrogen, Burlington, ON, Canada)
in SeaBlock (1:1200) for 1 h at room temperature. After wash-
ing, the blot was exposed (ex 465 em 700) with a KODAK
Image Station 4000 MM Digital Imaging System. Fluores-
cent dots were quantified using Molecular Imaging Software
version 4.0.5f7 (Kodak) and data were normalized to actin.
2.8. Data and statistical analyses
Statistical analysis were performed either with an
ANOVA (equal variance) followed by Tukey-Kramer or
Newman–Keuls post-hoc tests or a Welch’s ANOVA (unequal
variance) followed by a Dunnett’s post-hoc test. In addition,
logarithmic transformations were done to reduce variance to
provide more normally distributed measures, when needed.
Coefficients of correlation and significance of the degree of
linear relationship between parameters were determined with
a simple regression model and the threshold for statistical sig-
nificance was set P < 0.05. Logarithmic transformation was
used to establish homogeneity of variance and improve nor-
mality, when necessary. JMP Statistical Analysis Software
(version 5.0.1) or Prism (Macintosh version 4.0c) were used
for all analyses.
3. Results
3.1. A high-fat westernized diet increased animal
weights
Decreasing the n-3:n-6 PUFA dietary ratio alone (Diet
B) had no effect on body weight (Table 2). However,
feeding the animals with a high-fat westernized diet (Diet
C) increased the weight of non-transgenic (NonTg) mice
by 69% (Welsh-ANOVA: P < 0.0001, F(groups)
2,19
= 17.61)
compared to Diet A (P = 0.0001; Dunnett’s test) and by
62% compared to Diet B (P = 0.0009; Dunnett’s test). Inter-
estingly, 3xTg-AD mice were heavier than NonTg on the
same diet, in the case of Diet A (+31%, P = 0.0166) and
Diet B (+26%, P = 0.0098), but not Diet C. This shows
that 3xTg-AD mice fed low-fat diets spontaneously gained
more weight than their non-transgenic age-matched con-
trols. Two-way ANOVA confirmed that the diets (P < 0.0001,
F
2, 59
= 12.4) and the transgenes (P = 0.0286, F
1,59
= 5.3) had
significant separate effects on animal weight, with no inter-
action between the two variables (P = 0.3577, F
2,59
= 1.0).
3.2. Transgene expression and dietary treatments
altered brain fatty acid profiles
The detailed effects of dietary treatment and transgene
expression on brain fatty acid profiles are given in Table 2
along with the results of statistical analyses. As expected,
the reduction of the dietary n-3:n-6 PUFA ratio (Diet B)
was translated into a 33% and 26% increase of n-6 PUFA
in the brain of NonTg (ANOVA, F(groups)
2,25
= 141.6;
P < 0.0001) and 3xTg-AD (ANOVA, F(groups)
2,18
= 59.0;
P < 0.0001), respectively (Table 2). Diet B also led to a
16% and 19% decrease of n-3 PUFA in the brain of NonTg
(ANOVA, F(groups)
2,25
= 47.7; P < 0.0001) and 3xTg-AD
mice (ANOVA, F(groups)
2,18
= 34.8; P < 0.0001), respec-
tively (Table 2). In comparison to Diet A, Diet B led to
a 19% decrease of DHA (ANOVA, F(groups)
2,25
= 46.1;
P < 0.0001) and a 37% decrease of the n-3:n-6 PUFA ratio
(ANOVA, F(groups)
2,25
= 225.9; P < 0.0001) in the brain of
NonTg (Table 2). Compared to Diet A, Diet C also caused
a reduction in DHA of 8% (ANOVA, F(groups)
2,25
= 46.1;
P < 0.01) accompanied by a 23% reduction of the n-3:n-6
PUFA ratio (ANOVA, F(groups)
2,25
= 225.9; P < 0.0001) in
the brain of NonTg (Table 2).
The 3xTg-AD animals differed from NonTg in terms of
basic fatty acid profile and their response to diets. Fig. 1
illustrates the direct comparison between 3xTg-AD mice and
NonTg age-matched controls on the same diet. Concentra-
tions of DHA in the cortex were similar between 3xTg-AD
and NonTg fed Diet A (Fig. 1). Importantly however, the
low dietary intake of n-3 PUFA relative to n-6 PUFA led to
decreased brain DHA in a more marked manner in 3xTg-AD
than in NonTg, indicating that the effect of the n-3 PUFA
dietary depletion on DHA levels were more profound in
3xTg-AD animals (Fig. 1A). This was confirmed by two-
way ANOVA showing a significant interaction between the
two variables (diets and transgenes), underscoring a greater
vulnerability of the transgenic animals to n-3 PUFA depletion
(Table 2). Accordingly, the n-3:n-6 PUFA ratio was signif-
icantly decreased in 3xTg-AD mice compared to NonTg in
all diet groups, although the effect gained in statistical sig-
nificance in the Diet C group. To isolate the transgenes as
a variable, two-way ANOVA were performed and revealed
that transgene expression in 3xTg-AD was associated with
increased levels of docosatetraenoic acid (DTA) and total n-6
PUFA and a decrease in DHA, total n-3 PUFA and n-3:n-6
PUFA ratio (Table 2).
3.3. The high-fat diet increased cortical load of Aβ
40
and Aβ
42
Measurement of A! burden in formic acid extracts from
the detergent-insoluble protein fraction revealed no signifi-
cant effect of n-3 PUFA deprivation (Diet B) whereas Diet C
strikingly increased A!
40
(+871% versus controls; ANOVA
(log), F(groups)
2,19
= 7.52;P = 0.0039; Newman–Keuls post-
hoc test) and A!
42
(+912% versus controls; ANOVA (log),
F(groups)
2,19
= 8.79; P = 0.0020; Newman–Keuls post-hoc
test) in the parietotemporal cortex of 3xTg-AD mice (Fig. 2).
Importantly, the cortical detergent-insoluble A!
42/40
ratio
was higher in the group of 3xTg-AD mice fed with Diet C
compared to Diet B (+154%; ANOVA, F(groups)
2,19
= 3.66;
P = 0.044; Newman–Keuls post-hoc test) (Fig. 2). Dietary
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C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531 1521
Table 2
Animal weight and brain fatty acid profile of 3xTg-AD mice fed with a low n-3:n-6 PUFA ratio incorporated into a low-fat or a high-fat formulation.
Non-transgenic mice 3xTg-AD mice Statistical test Two-way ANOVA (P-values)
Control Low n-3:n-6 ratio Low n-3:n-6 ratio Control Low n-3:n-6 ratio Low n-3:n-6 ratio Diet Transgenes Interaction
5% (w/w) fat 5% (w/w) fat 35% (w/w) fat 5% (w/w) fat 5% (w/w) fat 35% (w/w) fat
(Diet A) (Diet B) (Diet C) (Diet A) (Diet B) (Diet C)
Weight (g) 31.4 ± 1.3 32.8 ± 1.7 53.1 ± 1.9****
†††
41.1 ± 3.3
§
41.4 ± 2.5
§§
52.9 ± 10.2 Welch ANOVA + Dunnett’s <0.0001 0.0286 n.s.
Brain fatty acid (%) n (
;) 13 (4;9) 9 (4;5) 6 (2;4) 7 (4;3) 10 (8;2) 4 (3;1)
C16:0 23.3 ± 0.3 22.4 ± 0.3* 23.3 ± 0.3 22.8 ± 0.3 21.8 ± 0.3 22.2 ± 0.6 ANOVA + Tukey–Kramer 0.0169 0.0169 n.s.
C18:0 20.6 ± 0.2 21.4 ± 0.2** 20.4 ± 0.1 20.7 ± 0.3 21.3 ± 0.2 20.7 ± 0.3 ANOVA + Tukey–Kramer 0.0018 n.s. n.s.
C20:0 0.08 ± 0.03 0.26 ± 0.1 0.08 ± 0.05 0.2 ± 0.2 0.27 ± 0.04 0.09 ± 0.09 ANOVA + Tukey–Kramer n.s. n.s. n.s.
C22:0 0.12 ± 0.04 0.2 ± 0.1 0.21 ± 0.07 0.2 ± 0.2 0.22 ± 0.04 0.2 ± 0.1 ANOVA + Tukey–Kramer n.s. n.s. n.s.
Total SFA 44.2 ± 0.3 44.3 ± 0.5 44.2 ± 0.2 44.2 ± 0.4 43.8 ± 0.3 43.7 ± 0.5 ANOVA + Tukey–Kramer n.s. n.s. n.s.
C18:1n-9 15.4 ± 0.38 13.7 ± 0.3** 14.5 ± 0.2* 14.8 ± 0.3 14.3 ± 0.3 15.1 ± 0.4 ANOVA + Tukey–Kramer 0.0051 n.s. n.s.
Total MUFA 21.7 ± 0.6 20.0 ± 0.4 20.3 ± 0.3 21.1 ± 0.3 21.1 ± 0.6 20.9 ± 0.6 ANOVA + Tukey–Kramer n.s. n.s. n.s.
C18:2n-6 LA 1.2 ± 0.1 1.3 ± 0.2 2.01 ± 0.09* 1.3 ± 0.2 1.1
± 0.1 2.4 ± 0.4**
†††
ANOVA + Tukey–Kramer <0.0001 n.s. n.s.
C20:4 n-6 ARA 9.9 ± 0.2 11.4 ± 0.2**** 10.6 ± 0.1* 10.3 ± 0.2 11.7 ± 0.2**** 10.4 ± 0.l
†††
ANOVA + Tukey–Kramer <0.0001 n.s. n.s.
C22:4n-6 DTA 2.78 ± 0.07 3.65 ± 0.09**** 3.44 ± 0.07**** 3.01 ± 0.05
§
4.00 ± 0.07****
§§
3.7 ± 0.1****
††
ANOVA + Tukey–Kramer <0.0001 0.0005 n.s.
C22:5n-6 DPA 0.20 ± 0.06 2.6 ± 0.2**** 0.50 ± 0.02
††††
0.27 ± 0.05 2.5 ± 0.2**** 0.56 ± 0.02
††††
ANOVA + Tukey–Kramer <0.0001 n.s. n.s.
Total n-6 PUFA 14.6 ± 0.2 19.4 ± 0.2**** 17.6 ± 0.2****
†††
15.6 ± 0.2
§
19.6 ± 0.2**** 18.6 ± 0.6**** ANOVA + Tukey–Kramer <0.0001 0.0016 n.s.
C18:3n-3 LNA 0 ± 00± 00± 00± 00± 00± 0 ANOVA + Tukey–Kramer n.s. n.s. n.s.
C20:5n-3 EPA 0.03 ± 0.03 0.11 ± 0.04 0.05 ± 0.03 0.11 ± 0.11 0.09 ± 0.04 0.06 ± 0.06 ANOVA + Tukey–Kramer n.s. n.s. n.s.
C22:6n-3 DHA 17.2 ± 0.3 14.0 ± 0.2**** 15.7 ± 0.2**
††
16.9 ± 0.3 13.3 ± 0.2****
§
13.9 ± 0.3****
§§
ANOVA + Tukey–Kramer <0.0001 0.0001 0.0338
Total n-3 PUFA 19.5 ± 0.3 16.3 ± 0.1**** 18.0 ± 0.2*
††
19.2 ± 0.4 15.5 ± 0.3****
§
16.8 ± 0.2**
§§
ANOVA + Tukey–Kramer <0.0001 0.0045 n.s.
n-3:n6 ratio 1.33 ± 0.02 0.84 ± 0.01**** 1.02 ± 0.02****
††††
1.23 ± 0.03
§§
0.79 ± 0.02****
§
0.91 ± 0.02****
§§
ANOVA + Tukey–Kramer <0.0001 <0.0001 n.s.
Total PUFA 341 ± 0.4 35.7 ± 0.1* 35.5 ± 0.22* 34.7 ± 0.4 35.1 ± 0.4 35.4 ± 0.7 ANOVA + Tukey–Kramer 0.0213 n.s. n.s.
Abbreviations: , males; , females; 3xTg-AD, triple transgenic mouse model of Alzheimer’s disease; ARA, arachidonic acid; DHA, docosahexaenoic acid; DPA, docosapentaenoic acid; DTA, docosatetraenoic acid; EPA, eicosapentaenoic acid; LA, linoleic
acid; LNA, linolenic acid; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acid. Values are expressed as means ± S.E.M.
*P < 0.05, **P < 0.01 and ****P < 0.0001 versus control diet (same genotype).
P < 0.05,
††
P < 0.01,
†††
P < 0.001 and
††††
P < 0.0001 versus low fat low n-3:n-6 PUFA diet (same genotype).
§
P < 0.05,
§§
P < 0.01 versus non-transgenic mice (same diet).
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1522 C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531
Fig. 1. Decreased cortical n-3:n-6 PUFA ratio and increased vulnerability of 3xTg-AD mice to n-3 PUFA dietary deprivation. (A) Decreased DHA was found
in the parieto-temporal cortex of 3xTg-AD mice fed with low n-3:n-6 PUFA ratio diets (Diets B and C) compared to NonTg mice, but not in animals fed control
diet (Diet A). (B) The n-3:n-6 PUFA ratio was reduced in the parieto-temporal cortex of 3xTg-AD mice compared to NonTg mice, independently of dietary
intake. Values are expressed as means ± S.E.M. (n = 4–13) and statistical analyses were performed using unpaired Student’s t-test. Abbreviations: 3xTg-AD,
triple transgenic mouse model of Alzheimer’s disease; Ctrl, control diet; DHA, docosahexaenoic acid; NonTg, non-transgenic; n.s., non-significant.
treatments did not alter levels of A!
40
and A!
42
in the frac-
tion containing soluble proteins, although Diet C caused a
trend toward an increase of both A! species (Fig. 2). Over-
all, interindividual variations were important in all animal
groups, as is often the case in samples from human brain as
well (Tremblay et al., 2007).
To investigate whether increased A!
40
and A!
42
were a
consequence of increased production of APP or its process-
ing by "- and !-secretase, we measured both full length APP
and "- and !-APP carboxy terminal fragment (CTF) products
on Western immunoblots. Fig. 3 shows that the dietary treat-
ments did not significantly modulate the protein expression
of APP nor its CTF. Moreover, dietary treatments exerted
no significant effect on soluble A! oligomers as measured
in a dot blot assay with the oligomer-specific antibody A11,
which does not bind to fibrils or monomers (Kayed et al.,
2003)(Fig. 3).
3.4. Low dietary n-3:n-6 PUFA ratio and high-fat diet
increased tau levels in 3xTg-AD mice
Diet B-induced n-3 PUFA dietary depletion led to a statis-
tically significant rise (+97% versus controls; ANOVA (log),
F(groups)
2,18
= 3.79; P = 0.0424; Newman–Keuls post-hoc
test) in the total amount of tau protein found in the formic
acid extract from the cortex of 3xTg-AD mice but not in
the TBS-soluble protein fraction (Fig. 4). However, animals
fed with Diet C diet had higher levels of total tau protein
in both the soluble (+153% versus controls; ANOVA (log),
F(groups)
2,15
= 4.70; P = 0.0120; Newman–Keuls post-hoc
test) and insoluble fractions (+69% versus controls; ANOVA
(log), F(groups)
2,18
= 3.79;P = 0.0424; Newman–Keuls post-
hoc test) compared to 3xTg-AD mice fed Diet A. Diet C also
increased total soluble tau compared to Diet B (+164% ver-
sus controls; ANOVA(log), F(groups)
2,15
= 4.70; P = 0.0173;
Newman–Keuls post-hoc test). On the other hand, phospho-
rylated tau remained unchanged between groups (Fig. 4).
The present data indicate that the impact of high-fat-based
caloric intake on tau pathology was less evident than on A!
accumulation.
3.5. Low dietary n-3:n-6 PUFA ratio combined with a
high-fat westernized diet decreased postsynaptic marker
drebrin
High-fat intake combined with a low n-3:n-6 PUFA ratio
(Diet C) induced a decrease in drebrin compared to Diet
A in 3xTg-AD mice (30.2% versus Diet A; ANOVA,
F(groups)
5,41
= 3.0; P < 0.01; Newman–Keuls post-hoc test)
in homogenates from the parieto-temporal cortex (Fig. 5).
This reduction was observed in the detergent-soluble frac-
tion (membrane) from cortex homogenates, but not in the
TBS-soluble fraction (not shown), in accordance with pre-
vious data (Calon et al., 2004). No significant effects were
detected on the expression of syntaxin 3, PSD-95, synapto-
physin and SNAP-25 (Fig. 5). Two-way ANOVA revealed an
effect of dietary treatments on levels of drebrin (P < 0.01),
and an effect of transgenes on levels of PSD-95 (decrease;
P < 0.05) and syntaxin 3 (increase; P < 0.05).
3.6. The high-fat diet increased glial fibrillary acidic
protein (GFAP) in both NonTg and 3xTg-AD mice
To determine whether the effects of dietary treatments
were related to glial activation, we measured the levels of
GFAP in parieto-temporal cortex of NonTg and 3xTg-AD
mice (Table 3). Although one-way ANOVA did not detect any
significant alteration between individual groups, two-way
ANOVA indicated that the high intake of calories from fats
significantly increased actin-normalized GFAP (P = 0.0095).
This effect of the high-fat diet was thus present in both NonTg
and 3xTg-AD mice.
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C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531 1523
Fig. 2. High-fat diet potentiates the accumulation of A! in the brain cortex of 3xTg-AD mice. Increased A! load was found in the formic acid–soluble protein
fraction from homogenates generated from the parieto-temporal cortex of 3xTg-AD mice fed low-fat and low n-3:n-6 PUFA ratio diet (Diet B) or high-fat
and low n-3:n-6 PUFA ratio diet (Diet C), compared with control diet (Diet A). A! concentrations were determined using ELISA. Values are expressed as
means ± S.E.M. (n = 5–10) and statistical analyses were performed using ANOVA followed by a Newman–Keuls post-hoc test. Abbreviations:A!, amyloid-!
peptide; Ctrl; control diet.
3.7. Altered LR11, cofilin and p21-activated kinase
(PAK) concentrations in 3xTg-AD mice
To identify alterations of AD-related proteins that could
be associated with the accumulation of A!/tau after high-fat
diet intake, we measured by immunoblotting the concen-
trations of LR11, ApoE, cofilin and p21-activated kinase
(PAK) in the parieto-temporal cortex of NonTg and 3xTg-
AD mice (Table 3). Two-way ANOVA of the data showed
that transgene expression downregulated actin-normalized
levels of LR11 (P < 0.0001), cofilin (P < 0.0001) and PAK
(P < 0.0001) (Table 3). Moreover, two-way ANOVA indi-
cated that dietary treatments significantly altered cofilin
(P < 0.0001), but revealed an interaction between transgenes
and diets on cofilin levels (P = 0.0251), showing that dietary
effects on cofilin depended on the transgenic status (Table 3).
No significant effect of transgenes or dietary treatments on
ApoE or total oxidized proteins was detected (Table 3).
Except for the specific case of GFAP described above, diets
had little effectson markers shown in Table 3, which thus can-
not be readily correlated with the rise in A! and tau levels
induced by the high-fat diet.
4. Discussion
Consumption of high-fat meals containing a low n-3:n-6
PUFA ratio is prevalent in our modern society and has been
reproduced here in an animal model of AD. The present study
shows that a high-fat westernized treatment amplified various
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1524 C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531
Fig. 3. Dietary fats did not alter the production and processing of APP. (A) An immunoblot image is shown where each lane represents an individual 3xTg-AD
mouse fed with either Diet A, B or C. Dietary treatments did not alter the levels of (B) full length APP; (C) 9-kD C-terminal fragment (CTF) produced
by "-secretase; (D) 11-kD CTF produced by !-secretase; and (E) soluble amyloid oligomers. Measurements were made in the detergent-soluble fractions
using antibodies recognizing the C-terminal segment of APP (C31) and in the TBS-soluble fractions for A! oligomers (anti-amyloid oligomer; A11). Values
are expressed as means ± S.E.M. (n = 5–10) and statistical analyses were performed using ANOVA. Abbreviations: APP, amyloid precursor protein; CTF,
C-terminal fragment; C and Ctrl, control; A and Diet A, low-fat control diet; B and Diet B, low-fat with low n-3:n-6 PUFA ratio diet (low-fat diet); C and Diet
C, high-fat with low n-3:n-6 PUFA ratio diet (High-fat diet); O.D., optical density.
aspects of AD neuropathology, supporting the contention that
dietary factors may alter the progression of AD in humans.
4.1. Effects of transgene expression and dietary
treatments on brain fatty acids
Our results first indicated that the brain of 13-month-old
3xTg-AD mice is spontaneously enriched in n-6 PUFA com-
pared to n-3 PUFA. Such a decrease in n-3:n-6 PUFA ratio
is detected in APP
K670N,M671L
mice only when crossed with
animals expressing mutant human PS1
M146L
(Calon et al.,
2005; Yao et al., in press), suggesting that the addition of
PS1 and/or tau transgenes played a role in the modification
of the cortical PUFA profile. Since n-3 PUFA are enriched
in synapses (Breckenridge et al., 1973; Jones et al., 1997),
the decrease in n-3 PUFA may contribute to synapse-related
deficits. Evidence that n-3 PUFA are decreased in AD brain
have also been reported (Lukiw et al., 2005; Prasad et al.,
1998; Söderberg et al., 1991) although this remains a matter
of controversy (Calon and Cole, 2007; Plourde etal., 2007),as
some studies found no changes (Corrigan et al., 1998; Skinner
et al., 1993) or even increased DHA (Pamplona et al., 2005).
Nevertheless, the present observations suggest an important
effect of the transgene expression on the accumulation of
PUFA in the brain.
The present study design allowed the investigation of the
effect of low n-3:n-6 ratio in dietary PUFA when carbohy-
drates:fat calories percentages were fixed at 68:12 (Diet B)
or 20:60 (Diet C). Despite similar n-3:n-6 ratios, the absolute
amount of n-3 PUFA in formulas was under 0.05% (w/w) in
Diet B and close to 0.2% in Diet C (Table 1). This means
that mice fed Diet B were exposed to less dietary n-3 PUFA
than those fed Diet C, as testified by brain fatty acid mea-
surements of PUFA (Table 2). DHA depletion is normally
characterized by a compensatory increase of n-6 DTA and n-
6 DPA (Pawlosky and Salem, 2001). Accordingly, n-6 DTA
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C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531 1525
Fig. 4. Intake of low dietary n-3:n-6 PUFA ratio combined with high-fat increased cortical tau concentrations. Low n-3:n-6 PUFA ratio incorporated into a
high-fat diet (Diet C) increased the levels of soluble tau normalized to actin whereas both the low n-3:n-6 PUFA ratio in both a low-fat (Diet B) or high-fat
diet (Diet C) increased the concentration of insoluble tau in the parieto-temporal cortex of 3xTg-AD mice compared with control diet (Diet A). No change
in phosphorylated tau was detected. Analyses were performed by Western immunoblotting using antibody tau-13 (total tau) and antibodies CP13 and PHF1
(phosphorylated tau). The soluble fraction comprised protein soluble in TBS whereas the insoluble fraction contains proteins solubilized with formic acid
(see Section 2). Animals were fed dietary treatments from 4 to 13 months. Values are expressed as means ± S.E.M. (n = 5–10) and statistical analyses were
performed using ANOVA followed by a Newman–Keuls post-hoc test. Abbreviations: Ctrl, control; A and Diet A, low-fat control diet; B and Diet B, low-fat
with low n-3:n-6 PUFA ratio diet (low-fat diet); C and Diet C, high-fat with low n-3:n-6 PUFA ratio diet (high-fat diet); O.D., optical density; phospho-tau,
phosphorylated tau.
was increased in both animal groups following treatments
diet B or C. Interestingly however, n-6 DPA dropped to con-
trol levels in mice fed Diet C. These analyses suggest that the
massive amount in total fatty acid intake from Diet C (includ-
ing n-3 PUFA) partly prevented the decrease in n-3 PUFA
and the rise in n-6 DPA in the brain, but not the increase in
n-6 DTA. This suggests that brain levels of n-6 DTA depend
on the dietary n-3:n-6 ratio rather than on the n-3 PUFA
intake in absolute terms, as it seems to be the case with n-6
DPA.
It was previously shown that Tg2576 mice were partic-
ularly vulnerable to n-3 PUFA depletion; their brain DHA
levels were lower than NonTg controls following a simi-
lar extent of reduction in n-3 PUFA consumption (Calon et
al., 2004). We observed the same susceptibility in 3xTg-AD
mice, which suggests that these animal models of AD exhibit
a reduced capacity to retain brain DHA following dietary
depletion. This could be explained by an increased turnover,
a decreased synthesis or a reduced incorporation of DHA in
brain phospholipids (Rapoport et al., 2007).
4.2. Effects of dietary treatments on Aβ pathology
One of the most important results of our study is that high
caloric intake from fat increased A!
40
and A!
42
burden in
the cortex of 3xTg-AD mice. This response to the high-fat
diet was more striking in some animals than others, showing
significant interindividual variability. The observed changes
were not correlated with alterations in total APP, C-terminal
fragments (" and ! cleavage products) of APP or soluble
oligomers. These observations are consistent with previous
observations in Tg2576 mice fed with a high-fat diet similar
to present Diet C (Ho et al., 2004) and suggest that high-fat
treatment does not promote the accumulation of A! through
a change in the production and metabolism of APP. Given the
mounting hypothesis that obesity and metabolic disorders are
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1526 C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531
Fig. 5. Selective downregulation of the postsynaptic membrane protein drebrin in 3xTg-AD mice fed a high-fat westernized diet. Effects of low-fat and low
n-3:n-6 PUFA ratio diet (Diet B) or high-fat and low n-3:n-6 PUFA ratio diet (Diet C) on the levels of drebrin, syntaxin 3, PSD-95, synaptophysin and SNAP-25
in detergent-soluble (membrane) fractions from the parieto-temporal cortex of 3xTg-AD mice. Animals were fed dietary treatments from 4 to 13 months. Values
are expressed as means ± S.E.M. normalized to actin (n = 5–10). *P < 0.05 versus control diet (Diet A), same genotype; ANOVA followed by a Newman–Keuls
post-hoc test. Abbreviations: 3xTg-AD, triple transgenic mouse model of Alzheimer’s disease; A, Diet A; B, Diet B; C, Diet C; NonTg, non-transgenic; O.D.,
optical density, PUFA, polyunsaturated fatty acids; PSD-95, postsynaptic density-95; SNAP-25, synaptosome-associated protein-25.
linked to A! accumulation in AD (Erol, 2008; Luchsinger
and Mayeux, 2007), it is tempting to speculate that these
increases in weight and brain A ! following the high-fat diet
share common mechanisms.
Diet C had a more pronounced effect on A!
42
than A!
40
concentrations, an observation relevant to AD because the
A!
42/40
ratio is also increased in AD brain (Ingelsson et
al., 2004; Julien et al., 2008). It was recently shown that all
mutations in presenilins that are linked to early-onset familial
Alzheimer’s disease lead to increased A!
42/40
ratio in post
mortem brain samples and within cultured cells transfected
with the mutant genes (Citron et al., 1997; Kumar-Singh et al.,
2006; Scheuner et al., 1996). Hence, this property of Diet C to
increase A!
42/40
ratio in the cortex of 3xTg-AD mice is likely
to be relevant to AD pathology. Our results also demonstrate
that an 8-month exposure to a low n-3:n-6 dietary PUFA ratio
had no effect on both A!
40
and A!
42
, when given as a part
of a low-fat diet. In line with our data, a previous n-3 PUFA
deprivation study showed that old Tg2576 mice exposed to
a safflower-based diet had increased soluble A!
40
with no
change in concentrations of soluble A!
42
, insoluble A!
40
and insoluble A!
42
(Lim et al., 2005). Similarly, Green et al.
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C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531 1527
Table 3
Levels of GFAP, LR11, ApoE, Cofilin, PAK and oxidized proteins from parieto-temporal cortex of 3xTg-AD fed with low-fat or high-fat diets, incorporating either low n-3:n-6 PUFA ratio.
Non-transgenic mice 3xTg-AD mice Two-way ANOVA (P-values)
Control Low n-3:n-6 ratio Low n-3:n-6 ratio Control Low n-3:n-6 ratio Low n-3:n-6 ratio Diets Transgenes Interaction
5% (w/w) fat 5% (w/w) fat 35% (w/w) fat 5% (w/w) fat 5% (w/w) fat 35% (w/w) fat
(Diet A) (Diet B) (Diet C) (Diet A) (Diet B) (Diet C)
Proteins (relative O.D.) n(;) 10–13 (3–4;7–9) 9 (4;5) 6 (2;4) 7 (4;3) 10 (8;2) 4–5 (3;1–2)
GFAP 0.27 ± 0.02 0.27 ± 0.04 0.34 ± 0.03 0.25 ± 0.02 0.25 ± 0.01 0.5 ± 0.2 0.0095 n.s. n.s.
LR11 0.70 ± 0.03 0.78 ± 0.07 0.64 ± 0.04 0.47 ± 0.04
§§§
0.50 ± 0.06
§§
0.45 ± 0.07
§
n.s. <0.0001 n.s.
ApoE 1.8 ± 0.2 1.30 ± 0.09 1.30 ± 0.33 2.3 ± 0.7 1.5 ± 0.4 1.6 ± 0.4 n.s. n.s. n.s.
Cofilin 1.15 ± 0.08 0.90 ± 0.06
*
1.48 ± 0.04
*††††
0.7 ± 0.1
§§
0.79 ± 0.06 1.0 ± 0.1
§§
<0.0001 <0.0001 0.0251
PAK 0.85 ± 0.05 0.83 ± 0.06 1.01 ± 0.06 0.37 ± 0.06
§§§§
0.43 ± 0.03
§§§§
0.39 ± 0.05
§§§§
n.s. <0.0001 n.s.
Oxidized proteins 2.0 ± 0.1 1.9 ± 0.1 1.7± 0.1 2.2 ± 0.2 2.0 ± 0.1 2.0 ± 0.2 n.s. n.s. n.s.
Abbreviations: , males; , females; 3xTg-AD, triple transgenic mouse model of Alzheimer’s disease; ApoE, apolipoprotein E; GFAP, glial fibrillary acidic protein; LR11, sortilin-related receptor SorLA/LR11;
O.D., optical density; PAK, p21-activated kinase. Values are expressed as means ± S.E.M. normalized to actin.
§
P < 0.05,
§§
P < 0.01,
§§§
P < 0.001 and
§§§§
P < 0.0001 versus non-transgenic mice (same diet).
*
P < 0.05 versus control diet (same genotype).
††††
P < 0.0001 versus low fat low n-3:n-6 PUFA diet (same genotype).
also observed only a weak effect of long-term treatment with
DHA limited to soluble A!
40
(Green et al., 2007). Overall,
this suggests that very high amounts of fat intake has a greater
impact on A! accumulation than the n-3:n-6 dietary PUFA
ratio alone.
4.3. Effects of dietary treatments on tau pathology
The only previous report on the impact of dietary fats on
tau pathology showed that DHA supplementation in 3xTg-
AD mice reduced the levels of total soluble tau (Green et
al., 2007). However, this report did not examine the effect
of lowering the n-3:n-6 PUFA ratio nor increasing fat intake.
Our measures in homogenates from 3xTg-AD mice showed
that a low n-3:n-6 dietary PUFA ratio was sufficient to raise
the levels of insoluble tau whereas high calorie intake from
fat was necessary to increase total tau in TBS-soluble frac-
tions as well. It is likely that tau deposited in the formic acid
extracts better represents the pathogenic form of this micro-
tubule protein. Indeed, massive conversion of tau protein
into its insoluble form is a major feature of AD pathogen-
esis and it correlates well with expression of cognitive deficit
(Arriagada et al., 1992; Ballatore et al., 2007; Julien et al.,
2008; Tremblayet al., 2007). For example, while levels of sol-
uble tau remains unaltered in cortex samples from advanced
AD patients, insoluble tau is increased by over 2000% (Julien
et al., 2008). Thus, the present data, which demonstrate for
the first time that n-3 PUFA deprivation can upregulate insol-
uble tau, might provide an important mechanism by which
dietary fat modulates a pathogenic process tightly related to
the clinical expression of the disease.
4.4. Effects of dietary treatments on synaptic pathology
Drebrin is a dendritic spine protein, which plays an impor-
tant role in synaptic function (Hayashi and Shirao, 1999;
Sekino et al., 2007). Proteic and mRNA levels of drebrin
have been shown to be massively decreased in AD (Calon et
al., 2004; Counts et al., 2006; Harigaya et al., 1996; Hatanpää
et al., 1999; Julien et al., 2008; Shim and Lubec, 2002), an
observation probably explained by deactivation of cell sur-
vival pathways and activation of specific caspases (Calon et
al., 2005; Klaiman et al., 2008). Thus, drebrin loss qualifies
as another important marker of AD neuropathology. Along
with its effect on A! and tau accumulation, Diet C induced
a concomitant decrease in drebrin in detergent-soluble frac-
tions, which contained membrane proteins. Albeit in a less
striking manner, this observation is in agreement with exper-
iments in aged Tg2576 mice where n-3 PUFA depletion
induced a massive translocation of drebrin out of the mem-
brane (Calon et al., 2004, 2005). In addition, the change
in synaptic proteins was selective to membrane drebrin, as
reported (Calon et al., 2004, 2005). Therefore, increased
consumption of fat led to a selective reduction in drebrin,
driving 3xTg-AD mice neuropathology closer to the human
disease.
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1528 C. Julien et al. / Neurobiology of Aging 31 (2010) 1516–1531
4.5. Effect of dietary treatments and transgenes on other
AD-relevant brain markers
Alterations of LR11 (Offe et al., 2006; Scherzer et al.,
2004), cofilin (Zhao et al., 2006), PAK (Zhao et al., 2006)
and GFAP (Panter et al., 1985) have been reported in AD
brain and mechanisms through which these proteins can play
a role in AD are supported by compelling evidence. LR11, a
member of the ApoE/low-densitylipoprotein receptor family,
was identified as a probable genetic risk factor for late-onset
sporadic AD (Rogaeva et al., 2007). LR11 was shown to
downregulate A! production (Offe et al., 2006) and to be
increased by DHA treatment in aged Tg2576 mice (Ma et
al., 2007). Here, we measured a decrease of LR11 in the cor-
tex of 3xTg-AD mice, an observation not reported in other
transgenic mouse models of AD (PS1/APP and Tg2576)
(Dodson et al., 2006; Ma et al., 2007). Our results thus raise
the hypothesis that LR11 reduction in 3xTg-AD is related
to the accumulation of neurofibrillary tangles. On the other
hand, LR11 levels were not influenced by our experimen-
tal dietary treatments. Based on studies on AD brain and
with transgenic models, it has been proposed that drebrin
loss in AD is closely linked to aberrant PAK activity and
cofilin-induced disruption of the actin cytoskeletal network
(Heredia et al., 2006; Nguyen et al., 2008; Zhao et al., 2006).
Cortical PAK and cofilin were both found to be decreased
in 3xTg-AD mice whereas the effects of dietary treatments
on cofilin levels were difficult to interpret. Therefore, these
transgene-induced changes in LR11, cofilin or PAK are
interesting to further characterize the 3xTg-AD model, but
cannot be directly associated with the effect of dietary treat-
ments on the markers of AD neuropathology A!, tau and
drebrin.
GFAP is a commonly used marker of astrocyte activation
occurring in AD and in transgenic animal models (Calon
et al., 2005; Frautschy et al., 1998; Jacobsen et al., 2006;
Lim et al., 2000; Wirths et al., in press; Wyss-Coray, 2006).
Increased GFAP concentrations were detected in the cortex of
mice fed with a high-fat diet, suggesting the presence of glio-
sis following high-fat intake independently of the transgene
status. This observation suggests that excessive consump-
tion of calories from fat may increase reactive astrocytes
in the brain, an event previously shown to be associated
with A! pathology (Wyss-Coray, 2006). Indeed, genetical
or pharmacological induction of microgliosis assessed with
GFAP immunodetection has been shown to increase A!
burden (Kitazawa et al., 2005; Tan et al., 2002). However,
reduction of the accumulation of A! has also been reported
(Wyss-Coray et al., 2001) suggesting that the link between
neuroinflammation and the regulation of A! is complex
(Wyss-Coray, 2006). These inflammatory changes are likely
to appear independently from the accumulation of A! and
tau as they were found in NonTg animals as well. Whether
the rise in GFAP played a role in the aggravation of A!
and tau pathologies or in drebrin loss remains to be deter-
mined.
5. Conclusion
Overall, the present data indicate that the accumulation of
neuropathological markers of AD in 3xTg-AD mice depends
on the dietary intake of PUFA and, more importantly, total
intake of calories from fat. Given the fact that diets combin-
ing low n-3 PUFA and high-fat content are frequent, dietary
interventions aiming at optimizing fat consumption might be
relevant for prevention of AD, at least in people with a genetic
predisposition.
Acknowledgements
This work was supported by grants from the Canadian
Institutes of Health Research (CIHR) (FC MOP74443), the
Alzheimer Society Canada (FC ASC 0516) and the Canada
Foundation for Innovation (10307). C.J. held studentships
from the Alzheimer Society Canada, Fonds de la Recherche
en Santé du Québec (FRSQ) and Laval University “Fonds
d’Enseignement et de Recherche”. The work of F. Calon was
supported by a New Investigator Award from the Clinical
Research Initiative and the CIHR Institute of Aging (CAN-
76833).
Disclosure statement: The authors declare that they have
no actual or potential conflict of interest. The use of animals
was approved by the Laval university animal ethics commit-
tee in accordance with the standards of the Canadian Council
on Animal Care.
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    • "Thus, surprisingly , the significant increase in body weight in the HF groups of mice does not affect speed of movement (Leamy et al., 2009; Zhang and Gershenfeld, 2003), although there is a trend for this group to move the slowest of all, compared to the other diets. While the finding that diets high in fat content have a negative influence on cognition (both in social recognition and water maze) in both the WT and Tg animals was not unexpected (Julien et al., 2010; Kesby et al., 2015; Levin-Allerhand et al., 2002; Maesako et al., 2012; Petrov et al., 2015 ), one should keep in mind that previous studies have indicated that the high-fat induced memory impairments are not necessarily directly related to the Aβ load in Tg AD model mice (El Akoum et al., 2011; Knight et al., 2014 ). Our data, similarly, do not show a HF diet increase in Aβ load in the hippocampus, while we do see cognitive deficits . "
    [Show abstract] [Hide abstract] ABSTRACT: Clinical and epidemiological evidence suggests that lifestyle factors, including nutrition, may influence the chances of developing of Alzheimer's disease (AD), and also likely affect the aging process. Whereas it is clear that high-fat diets are increasing both body weight and the risk of developing Alzheimer's disease, to date, there have been very few studies comparing diets high with different sources of calories (i.e., high fat versus high protein versus high carbohydrates) to determine whether dietary composition has importance beyond the known effect of high caloric intake to increase body weight, AD pathology and cognitive deficits. In the current study we examined the effects that different diets high in carbohydrate, protein or fat content, but similar in caloric value, have on the development of cognitive impairment and brain pathology in wild-type and Tg AD model mice. The results demonstrate that long term feeding with balanced diets similar in caloric content but with significant changes in the source of calories, all negatively influence cognition compared to the control diet, and that this effect is more pronounced in Tg animals with AD pathology.
    Full-text · Article · May 2016
    • "Therefore, the accumulation of A and tau may further exacerbate the adverse effects on synaptic and cognitive function and consequently induce cell death.Table 1. Diabetes promotes amyloid pathology (Abbreviations: intraperitoneal i.p.; intracerebroventricular i.c.v.). (Arancio et al., 2004; Devi et al., 2012; Ho et al., 2004; Jolivalt et al., 2010; Julien et al., 2010; Kim et al., 2013b; Lane et al., 2010; Leuner et al., 2012; Li et al., 2007; Liu et al., 2009a; Macauley et al., 2015; Takeda et al., 2010; Wang et al., 2014) Impaired insulin signaling induced an overactivation of GSK-3 kinase, and the downregulation of O- GlcNAcylation, which resulted in tau and neurofilament hyperphosphorylation, and neurofibrillary degeneration. Kim et al., 2009 Single STZ injection (i.p) of 55 mg/kg in Ntg mice STZ-induced hyperglycemia altered the Akt/GSK- 3/PP2A cascade, and leads to the development of abnormal tau phosphorylate forms. "
    [Show abstract] [Hide abstract] ABSTRACT: Despite intensive research efforts over the past few decades, the mechanisms underlying the etiology of sporadic Alzheimer’s disease (AD) remain unknown. This fact is of major concern because the number of patients affected by this medical condition is increasing exponentially and the existing treatments are only palliative in nature and offer no disease modifying affects. Interestingly, recent epidemiological studies indicate that diabetes significantly increases the risk of developing AD, suggesting that diabetes may play a causative role in the development of AD pathogenesis. Therefore, elucidating the molecular interactions between diabetes and AD is of critical significance because it might offer a novel approach to identifying mechanisms that may modulate the onset and progression of sporadic AD cases. This review highlights the involvement of several novels pathological molecular mechanisms induced by diabetes that increase AD pathogenesis. Furthermore, we discuss novel findings in animal model and clinical studies involving the use of anti-diabetic compounds as promising therapeutics for AD.
    Full-text · Article · Mar 2016
    • "A high level of fat in the diet (60 %) has been demonstrated to induce significant liver and heart alterations and impairment of metabolism in mice [46, 47]. A HF increased AD pathology in 9 months in a 3xTg-AD mouse fed with 35 % fat with low polyunsaturated fatty acids [48]. It is also demonstrated that diabetes leads neurons into metabolic stress. "
    [Show abstract] [Hide abstract] ABSTRACT: Metabolic stress induced by high-fat (HF) diet leads to cognitive dysfunction and aging, but the physiological mechanisms are not fully understood. Senescence-accelerated prone mouse (SAMP8) models were conducted under metabolic stress conditions by feeding HF for 15 weeks, and the preventive effect of resveratrol was studied. This dietary strategy demonstrates cognitive impairment in SAMP8-HF and significant preventive effect by resveratrol-treated animals. Hippocampal changes in the proteins involved in mitochondrial dynamics optic atrophy-1 protein (OPA1) and mitofusin 2 (MFN2) comprised a differential feature found in SAMP8-HF that was prevented by resveratrol. Electronic microscopy showed a larger mitochondria in SAMP8-HF + resveratrol (SAMP8-HF + RV) than in SAMP8-HF, indicating increases in fusion processes in resveratrol-treated mice. According to the mitochondrial morphology, significant increases in the I-NDUFB8, II-SDNB, III-UQCRC2, and V-ATPase complexes, in addition to that of voltage-dependent anion channel 1 (VDAC1)/porin, were found in resveratrol-treated animals with regard to SAMP8-HF, reaching control-animal levels. Moreover, tumor necrosis factor alpha (TNF-α) and interleukin (IL-6) were increased after HF, and resveratrol prevents its increase. Moreover, we found that the HF diet affected the Wnt pathway, as demonstrated by β-catenin inactivation and modification in the expression of several components of this pathway. Resveratrol induced strong activation of β-catenin. The metabolic stress rendered in the cognitive and cellular pathways altered in SAMP8 focus on different targets in order to act on preventing cognitive impairment in neurodegeneration, and resveratrol can offer therapeutic possibilities for preventive strategies in aging or neurodegenerative conditions.
    Article · Feb 2016
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