Question

Based on the article below:

Title: High fat diet and Endocannabiods.

Question: Please write a summary of the article, with a deeper understanding of the important informations on the high fat diet and endcannabiods. And list the Advantage and disavantage of a high fat diet and endocannabiods.

Article:

1. Introduction

Obesity is a growing public health concern that increases the risk of

inflammatory and metabolic disorders such as type 2 diabetes, fatty

liver, and pulmonary inflammation [1,2]. The incidence of obesity has

drastically increased over the past few decades. In a nationally representative

survey (National Health and Nutrition Examination

Survey, 2014) of adults in the US, the prevalence of obesity was 35%

among men and 40% among women, where linear trends significantly

increased for women between 2005 and 2014 [3]. The prolonged and

excessive inflammation associated with obesity has also been associated

with increases in certain cancers, cardiovascular disease, and Alzheimer's

disease [4,5]. While the mechanisms linking obesity and metabolic

disorders are not fully understood, several studies suggest that

alterations in lipid-mediated metabolism play a significant role [1,2,6].

These studies have led to the hypothesis that change in the blood lipidome

can be exploited to identify lipid markers as prognostic indicators

for obesity and type 2 diabetes [7].

Lipids are a diverse subset of biomolecules that are not only responsible

for energy storage and structural regulation, but also participate in complex signaling networks whose disruption results in

the pathogenesis of obesity and other ailments. A few studies have

identified several lipid and lipoprotein abnormalities among obese

patients [8,9]. For example, Hu, et al. reported decreases in HDL cholesterol

along with altered triglyceride levels in nondiabetic obese patients

[9]. Additionally, the role of dietary fat in obesity and influence

of fatty food intake on inflammatory responses are well-established

[4,10]. Obesity-associated inflammation is not restricted to impaired

lipid metabolism, but is also strongly linked with type 2 diabetes, as

obesity is associated with insulin resistance, which heightens the risk

for metabolic syndrome [11,12].

The higher prevalence of type 2 diabetes among adults supports the

assertion that aging is the precursor to insulin resistance [13–16]. While

insulin resistance, type 2 diabetes, and metabolic syndrome have been

studied within the context of age to some extent, including by us [17],

the effect of age on the lipidome and/or age-obesity interactions have

not received significant attention. However, two more recent studies

demonstrate that age exerts appreciable, lipid species-specific effects on

the brain lipidome [18] and, importantly, that age has profound effects

on the female reproductive system (oocytes) lipidome [19]. These

studies support the hypothesis that age-obesity interactions alter the

lipidome. In comparison to the lack of knowledge on the effect of

obesity and/or age on the plasma lipidome as a whole, it is known that

obesity can alter the levels of select lipid species. For example, increased

circulating endocannabinoids, especially 2-arachidonoylglycerol

(2-AG), have been associated with obesity in both humans and

laboratory animals, i.e [20,21]; however, it is not known how the endocannabinoid

system is altered within the context of age in the face of

high-fat diet consumption. The endocannabinoid (EC) system participates

in the control of lipid and glucose metabolism and dysregulation

of this system can occur following unbalanced energy intake [22]. Such

dysregulation often results in overactivity across various organs involved

in energy homeostasis such as intra-abdominal adipose tissue

[23]. Over-activation of the endocannabinoid system has been shown to

promote insulin resistance [6]. Additionally, the essential role of the EC

system in adipogenesis and lipogenesis has been reviewed in detail by

Silvestri and Marzo, et al. [22,23].

In this study, we further investigated the effects of dietary fat consumption,

age, and their interaction at the level of the lipidome using

shotgun lipidomics with electrospray ionization-mass spectrometry

(ESI-MS). Because of the paucity of data and the linear increase of female

obesity among US women in the most recent decade [3], we assessed

the blood lipid profiles of female C57BL/6 mice following HFDconsumption

for short (6 weeks), long (22 weeks), and prolonged

(36 weeks) periods to evaluate the persisting effects of feeding. To

compare lipid alterations with metabolic and liver regulation, markers

of liver homeostasis were assessed and correlations between them and

indices of glucose tolerance and insulin sensitivity with the blood lipidome

were determined. Circulating and liver levels of the two major

endocannabinoids, 2-arachidonoylglycerol (2-AG) and anandamide

(AEA), were also measured to determine the effects of HFD-consumption

and age on the endocannabinoid system.

2. Materials and methods

2.1. Animals

Experiments were performed with female C57BL/6 mice (Harlan,

Indianapolis, IN). The mice were housed (4–5/cage) and maintained at

22–24 °C with food and water available ad libitum on a 12 h light/dark

cycle in an AAALAC accredited facility throughout the study. All experimental

procedures were in accord with the latest National Institutes

of Health (NIH) guidelines and the study was approved prior to initiation

by the Institutional Animal Care and Use Committee (IACUC) of

the University of Georgia.

2.2. Dietary treatment

The diets and dietary treatment are described in detail in our recent

publication [17], where the body weight changes, metabolic and behavioral

effects of the same experimental paradigm are reported.

Briefly, 6–7 weeks old female mice weighing 16.0 ± 0.20 g

(mean ± SEM) were randomly divided into two groups (n = 8/group/

time point) and placed on either a low-fat diet (LFD; 10% kcal from fat,

D12450J, Research Diets, Inc., New Brunswick, NJ) or a high-fat diet

(HFD; 60% kcal from fat, D12492, Research Diets) for either 6, 22, or

36 weeks. The LFD diet (3.85 kcal/g) consisted of 70% carbohydrate,

20% protein, 10% fat, of which 23.5% were saturated fatty acids [SFA],

29.7% monounsaturated fatty acids [MUFA], and 46.8% polyunsaturated

fatty acids [PUFA]) (Suppl. Table 4). The HFD diet

(5.24 kcal/g) consisted of 20% carbohydrate, 20% protein, 60% fat, of

which 32.2% were SFA, 35.9% MUFA, 31.9% PUFA (Suppl. Table 4).

2.3. Blood, plasma, and liver tissue collection

Mice were sacrificed at three time points (6, 22 and 36 weeks);

considerations for the selection of these time points are explained in

detailed in Krishna, et al., body weights (BW) were recorded and liver

was collected and quickly frozen at −80 °C [17]. Blood (1 ml) was

collected via cardiac puncture and immediately split into two aliquots:

500 μl was placed in Na citrate-containing tubes, mixed thoroughly,

and the plasma was separated by centrifugation (3500 Å~g; 10 min;

4 °C). Harvested plasma was then aliquoted and placed at −80 °C until

its use for endocannabinoid and esterase activity analyses as described

in detail below. The other 500 μl of blood was immediately mixed, by

vortexing, with 1 ml of methanol:water (1.0:0.4 v/v) and then placed at

−80 °C until lipid extraction as described below. Liver (6, 22, and

36 weeks) samples were used for qPCR and endocannabinoid analyses.

2.4. Glucose tolerance test (GTT) and insulin sensitivity test (IST) areas

under the curve (AUCs)

Glucose tolerance (GTT) and insulin sensitivity (IST) tests were

performed after 5, 20 and 33 weeks on respective diets as described in

our recent study [17]. We used the blood glucose integrated areas

under the curve (AUC) in the GTT and IST tests, as calculated using the

trapezoidal method [24], to determine if mice's response to oral glucose

challenge or to insulin correlates with specific lipid metabolites (described

below).

2.5. Bligh-dyer blood lipid extraction

Phospholipids were extracted using chloroform and methanol according

to the method of Bligh and Dyer [25]. Briefly, blood samples

designated for lipidomics analysis were suspended in 1.25 ml of methanol

and 1.25 ml of chloroform. Tubes were vortexed for 30 s, allowed

to sit for 10 min on ice, centrifuged (213 Å~g; 5 min), and the

bottom chloroform layer was transferred to a new test tube. The extraction

steps were repeated a second time and the chloroform layers

combined. The collected chloroform layers were dried under nitrogen,

reconstituted with 50 μl of methanol: chloroform (3:1 v/v), and stored

at −80 °C until analysis.

2.6. Lipid phosphorus assay

Lipid phosphorus was quantified using the phosphorus assay [26].

400 μl of sulfuric acid (5 M) was added to lipid extracts (10 μl) in a glass

test tube, and heated at 180–200 °C for 1 h. 100 μl of 30% H2O2 was

then added to the tube while vortexing, and heated at 180–200 °C for

1.5 h. 4.6 ml of reagent (1.1 g ammonium molybdate tetrahydrate in

12.5 ml sulfuric acid in 500 ml ddH20) was added and vortexed,

followed by 100 μl of 15% ascorbic acid and vortexing. The solution

was heated for 7–10 min at 100 °C, and a 150 μl aliquot was used to

measure the absorbance at 830 nm.

2.7. Phospholipid characterization with electrospray ionization-mass

spectrometry (ESI-MS)

Lipid extract samples (500 pmol/μl) were prepared by reconstitution

in chloroform: methanol (2:1, v/v). ESI-MS was performed as described

previously [27–29] using a Trap XCT ion-trap mass spectrometer

(Agilent Technologies, Santa Clara, CA) with a nitrogen drying

gas flow-rate of 8 l/min at 350 °C and a nebulizer pressure of 30 psi.

The scanning range was from 200 to 1000 m/z on 5 μl of the sample

scanned in positive and negative ion mode for 2.5 min with a mobile

phase of acetonitrile: methanol: water (2:3:1) in 0.1% ammonium formate.

As described previously [30], qualitative identification of individual

phospholipid molecular species was based on their calculated

theoretical monoisotopic mass values, subsequent MS/MS analysis, and

their level normalized to either the total ion count (TIC) or the most

abundant phospholipid.

MSnth fragmentation was performed on an Agilent Trap XCT iontrap

mass spectrometer equipped with an ESI source. Direct injection

from the HPLC system was used to introduce the analyte. The nitrogen

drying gas flow-rate was 8.0 l/min at 350 °C. The ion source and ion

optic parameters were optimized with respect to the positive molecular

ion of interest. Initial identification was typically based on the loss of

the parent head group followed by subsequent analysis of the lysophospholipid.

In the event that neutral loss scanning could not confirm

the species, the tentative ID was assigned based on the m/z value and

the LIPIDMAPS database (http://www.lipidmaps.org).

2.8. Multivariate statistical analysis of blood lipids

Multivariate principal component analysis (PCA) was performed

using MetaboAnalyst 3.0 (http://www.metaboanalyst.ca/). Automatic

peak detection and spectrum deconvolution was performed using a

peak width set to 0.5. Analysis parameters consisted of interquartile

range filtering and sum normalization with no removal of outliers from

the dataset. Features were selected based on volcano plot analysis and

were further identified using MS/MS analysis. Significance for volcano

plot analysis was determined based on a fold change threshold of 2.00

and p ≤0.05. Following identification, total ion count was used to

normalize each parent lipid level, and the change in the relative

abundance of that phospholipid species as compared to its control was

determined. This method is standard for lipidomic analysis as reported

in our previous studies [27,29].

2.9. Liver endocannabinoid (2-AG and AEA) levels

2-AG and AEA were extracted from liver using a modification of the

method of Kingsley and Marnett (2007) [74]. In brief, ~0.05–0.1 g of

frozen liver tissue (exact weight recorded) was Dounce homogenized in

2:2:1 v/v/v ethyl acetate:hexane:0.1 M potassium phosphate (pH 7.0)

[total volume 5 ml; supplemented with butylated hydroxytoluene and

triphenylphosphine, 0.05% w/v each (antioxidants)] containing deuterated

standards for 2-AG and AEA (5.6 pmol d8-AEA and 518 pmol d8-

2-AG). The mixture was vortexed (1 min) and centrifuged to separate

organic and aqueous phases (1400 Å~g, 10 min). The organic layer was

removed, dried under a stream of N2 and residues dissolved in 2:2:1 v/

v/v water:methanol:isopropanol (200 μl). After filtration (0.1 μm),

10 μl of the resolubilized lipid was injected onto a Acquity UPLC BEH

C18 column (2.1Å~ 50 mm, 1.7 μm) equipped with VanGuard precolumn

(2.1 Å~ 5 mm, 1.7 μm). The mobile phase was a blend of solvent

A (2 mM ammonium acetate/0.1% acetic acid in water) and solvent B

(2 mM ammonium acetate/0.1% acetic acid in methanol). Analytes are

eluted with the following gradient program: 0 min (95% A, 5% B),

0.5 min (95% A, 5% B), 5 min (5% A, 95% B), 6 min (5% A, 95% B),

7 min (95% A, 5% B), 8 min (95% A, 5% B). The flow rate was 0.4 ml/

min and the entire column eluate was directed into a Thermo Quantum

Access triple quadrupole mass spectrometer (heated electrospray ionization

in positive ion mode). Single reaction monitoring (SRM) of each

analyte was as follows: 2-AG, [M +NH4]+ m/z 396.3 > 287.3; 2-AGd8,

[M+NH4]+ m/z 404.3 > 295.3; AEA, [M+ H]+ m/z 348 > 62;

AEA-d8, [M+H]+ m/z 356 > 63. Endocannabinoids were quantified

by measuring the area under each peak in comparison to the deuterated

standards and normalized on tissue weight.

2.10. Plasma endocannabinoid (2-AG and AEA) levels

Plasma levels of the two endocannabinoids 2-arachidonoylglycerol

(2-AG) and anandamide (N-arachidonoylethanolamine; AEA) were determined

using mass spectrometry. First, 50 μl of mouse plasma was

placed into a glass vial. Deuterated standards, 6 pmol AEA-d8 and

52 pmol 2-AG-d8 were added to each sample, followed by 2 ml of ethyl

acetate for extraction. The mixture was vortexed (1 min) and centrifuged

at 1400 g for 10 min. The organic layer (~1.5 ml) was transferred

into a clean glass vial and was dried under a stream of N2. The

residues were reconstituted in 1:1 v/v water: methanol (100 μl). After

filtration (0.1 μm), 10 μl of samples was injected onto an Acquity UPLC

system (Waters, Milford, MA) coupled to a TSQ Quantum Ultra tandem

mass spectrometer equipped with a heated electrospray (H-ESI) source

(Thermo Fisher). Chromatographic separation was carried out using an

Acquity UPLC BEH C18 column (2.1 mmÅ~ 100 mm, 1.7 μm) equipped

with a VanGuard precolumn (2.1 mmÅ~ 5 mm, 1.7 μm) at 40 °C using

column oven. The mobile phases used were water containing 0.1%

acetic acid (A) and methanol containing 0.1% acetic acid (B). Mobile

phase gradient conditions were as follows: hold at 15% A and 85% B for

0.5 min, linear increase of B to 95% in 2 min, hold at 95% B for 4 min,

decrease of B to 5% in 1 min and re-equilibrate for 2 min at the starting

conditions. The overall run time was 10 min and flow rate was 0.2 ml/

min. Eluate from the LC was directly electrosprayed into the mass

spectrometer using an electrospray ionization interface in the positive

mode. MS conditions were set as follows: spray voltage = 3500 V, vaporizer

temperature =350 °C, sheath gas= 25 units, auxiliary gas =2

and capillary temperature = 350 °C. Samples were run in positive

single reaction monitoring (SRM) mode and the following precursor-toproduct

ion transitions were used for quantification: 2-AG, [M+ H]+

m/z 379.2 > 287.1; AEA, [M+ H]+ m/z 348.2 > 287.2; 2-AG-d8,

[M + H]+ m/z 387.2 > 292.3; AEA-d8, [M+H]+ m/z 356.2 > 294.2. Scan time was

0.2 s per SRM, and the scan width was

m/z 0.01. Optimum collision energy and S-lenses conditions were determined

for each compound by using autotune software for each

analyte by post-column infusion of the individual compounds into a

50% A/50% B blend of the mobile phase being pumped at a flow rate of

0.2 ml/min. Xcalibur software was employed for data acquisition and

processing. For quantification, each calibration standard was prepared

ranging from 1 to 1000 nM by fortifying phosphate-buffered saline with

stock standards of 2-AG or AEA prepared in methanol. Quality control

samples were prepared at a concentration of 50 nM for each endocannabinoid

in triplicate. Weighted calibration curves were constructed

using 1/x as a weighting factor for 2-AG and AEA, respectively.

2.11. Plasma esterase activity

Plasma esterase activity was determined using the substrate paranitrophenyl

valerate, as previously described [31]. Production of p-nitrophenol

liberated from pNPV was monitored at 405 nm on a spectrophotometer

[32]. An extinction coefficient of 13 cm−1 mM−1 [33]

was used to convert the slopes of each activity curve to specific enzyme

activities. All enzymatic reaction rates were corrected for non-enzymatic

hydrolysis rates as we have described previously [31].

2.12. Real-time quantitative PCR (qPCR)

qPCR was performed on liver samples as described in [17,34].

Briefly, total liver RNA (20 mg tissue) was isolated using a GeneJET ™

RNA Purification Kit (Thermo Fisher Scientific, Pittsburgh, PA) and

quantified using a Take 3 plate and an Epoch microplate spectrophotometer

(Bio-Tek, Winooski, VT). RNA was converted to cDNA

using qScript cDNA SuperMix (Quanta Bioscience, Gaithersburg, MD)

and a Peltier thermal cycler (Bio-Rad, Hercules, CA). Using 3 ng of

cDNA per sample (with each sample run in duplicate), expression of

peroxisome proliferator-activated receptor alpha (PPARα), peroxisome

proliferator-activated receptor gamma (PPARγ), hepatic fatty acid

transporter (CD36), fatty acid synthase (FAS), acetyl-CoA carboxylase

(ACC), stearoyl-CoA desaturase (SCD), monoacylglycerol lipase (MGL),

cannabinoid receptor type 1 (CB1), cannabinoid receptor type 2 (CB2)

and 18S, was determined by qPCR using mouse-specific primers (Real

Time Primers, Elkins Park, PA) and SYBR Green-based master mix

(Qiagen, Valencia, CA). Amplifications were performed on a Mx3005P

qPCR machine (Stratagene) and treatment differences were calculated

as a fold change by the ΔΔ Ct method with 18S used as a house-keeping

gene (HKG) as previously reported [17,34]. Correlation between the

results from the liver qPCR and the blood lipidome was investigated as

described below.

2.13. Regression analysis between lipid features, GTT/IST, plasma

endocannabinoids, and liver homeostasis

GraphPad Prism for windows version 5.04 (GraphPad Software,

Inc., La Jolla, CA) was used for all correlation analyses comparing the

differential lipid expression via the relative abundance of features to

multiple endpoints used in the study such as liver mRNA expression

values, plasma endocannabinoid levels, and AUC values from GTT/IST.

Reported correlations meet the fairly stringent cutoff correlation coefficient

criteria of R2 ≥0.6.

2.14. Statistical analysis

All statistical analyses were compiled using GraphPad Prism for

windows version 5.04 (GraphPad Software, Inc., La Jolla, CA). For all

analysis, the experimental unit was individual animals and samples

from a total of 6–8 animals/diet/time point were assessed. For all

analyses, significance was set at p ≤ 0.05 where data are expressed as

mean ± SEM based on t-test for pairwise analysis and/or ANOVA

analysis (two-factor repeated-measures with Bonferroni post hoc test).

3. Results

3.1. Morphometric, GTT, IST, and intestinal permeability data

The lipid changes reported below were correlated to glucose tolerance

(GTT) and insulin sensitivity (IST) outcomes, which were recently

reported [17]. Briefly, HFD-fed mice were significantly heavier than

LFD mice at all three time points, and had impaired glucose tolerance.

Interestingly, HFD-feeding had the greatest effect on glucose tolerance

rather than insulin sensitivity [17]. On the other hand, while HFD decreased

IST at the earlier time points, this trend was not seen at the end

of the study due to age-dependent decreases in IST in LFD-fed mice

[17]. HFD-consumption by the female C57BL/6 mice also increased the

gastrointestinal permeability, more so after longer feeding durations

[17].

3.2. Multivariate analysis of lipidome

Multivariate, unsupervised principal component analysis (PCA) of

spectral data comparing high-fat diet (HFD) and low-fat diet (LFD)

consumption showed distinct clustering within the blood lipidome

where diet and age were the major effectors (Fig. 1, Fig. 2). Scores plots

of all groups, for both positive (Fig. 1A) and negative ion mode

(Fig. 2A), demonstrated a striking separation between 6-week vs. 22-

and 36-week treatment groups. The separation of populations occurred

regardless of dietary treatment indicating a significant role for age on

the lipidome. However, HFD-consumption altered lipid profiles within

each respective time point where 6-week treatment (Fig. 1C, Fig. 2C)

had the most pronounced effect. Urine lipid profiles demonstrated a

similar trend (Suppl. Fig. 1). The baseline lipidome was also assessed

with PCA analysis comparing blood lipid profiles of ~5–6-week-old

mice to 6-week HFD/LFD-fed mice, indicating group differences along

with variability in the baseline lipidome, which diminished following

6 weeks of dietary treatment (Suppl. Fig. 4).

Volcano plots identified and ranked potentially important features

based on fold change and statistical significance level for age- (Fig. 3,

Suppl. Fig. 2) and diet-related (Fig. 4, Suppl. Fig. 3) effects. Age-related

pairwise comparisons within dietary treatment groups for short vs.

long/prolonged (6-week vs. 22- and 36-week) (Fig. 3A-3B, Suppl.

Fig. 2A–B) yielded the greatest number of features while 22-week vs.

36-week (Fig. 3C, Suppl. Fig. 2C) resulted in very few. Based on the

number of features altered, diet-related pairwise comparisons of LFDvs.

HFD-consumption indicated that HFD-induced alterations were

most robust following a short consumption period (Fig. 4A) with fewer

alterations following longer periods of exposure (Fig. 4B, C).

3.3. Phospholipid species

Diet- and age-dependent alterations elevated the relative abundances

of phospholipid (PL) species in blood lipid profiles of HFD-fed

mice after 6 weeks of consumption (Fig. 5A), and presented the most

changes following 22 weeks of treatment where HFD-fed mice had

decreased relative abundances of various PL species, differing from

those species affected after 6 weeks on the diet (Fig. 5A). None of the

age−/diet- changes persisted after 36 weeks of HFD feeding (Fig. 5A).

Significance analysis of lipid features was performed for all time

points within each dietary group (i.e. 6 weeks vs. 22 weeks of LFD

feeding) to identify age−/diet- alterations. These age−/diet- features

were subsequently excluded during analysis of LFD vs. HFD treatment

to characterize the effects of HFD feeding alone. Interestingly, the effects

of HFD-consumption alone did not appear following 6 weeks of

feeding (Fig. 6A). 22-week consumption demonstrated the greatest effect,

much like that observed in features altered due to diet−/age-,

although differences in PL relative abundances were bidirectional and

did not show a class-specific uniform trend (Fig. 6A). Following

36 weeks of feeding, the relative abundance of only one feature (m/z

578.3) changed due to HFD-consumption alone (Fig. 6A). MS/MS

analysis and neutral loss scanning was performed to validate phospholipid

class identities (Suppl. Table 1–2).

3.4. Fatty acyl species

Fatty acyl (FA) species altered based on diet- and age-related effects

demonstrated bidirectional effects at all three time points where the

majority of features identified were in blood profiles of mice following

22 weeks of treatment (Fig. 5B). One feature (m/z 562.8) persisted

between short- and long-term feeding, demonstrating an increase in

relative abundance in HFD-fed animals after 6-weeks followed by a

decrease after 22-weeks (Fig. 5B).

Diet alone altered the blood lipidome of the 6-week treatment group

in which HFD-consumption decreased the relative abundances of FAs

by ~2-fold (Fig. 6B). This was also observed in urine lipid profiles of

the 6-week treatment group where three features (m/z 337, m/z 385,

m/z 381) detected and altered in blood were also detected in urine with

comparable magnitudes of differences between LFD- and HFD-fed mice

(Fig. 6B). The effects of HFD-consumption alone did not persist after 22-

weeks and 36-weeks (Fig. 6B). MS/MS analysis and neutral loss scanning

was performed to validate fatty acyl class identities (Suppl.

Table 1–2).

3.5. Glycerolipid species

Most diet- and age-dependent feature alterations in glycerolipids

occurred after short- (6 weeks) and long-term feeding (22 weeks) where

changes were primarily bidirectional across groups (Fig. 5C). 22-week

feeding displayed a trend of general decreases in glycerolipid (GL) relative

abundances in HFD-fed mice (Fig. 5C). We identified one feature

that was altered after 36-weeks of dietary treatment, (m/z 708.6),

which was decreased in HFD-mice (Fig. 5C).

Resembling the pattern observed across FA species (Fig. 6B), the

majority of features altered due to HFD-consumption alone were

identified in the 6-week treatment group. Further, GL features demonstrated

species-specific increases and decreases in both blood and

urine profiles (Fig. 6C). Long-term feeding affected a few GL features

with net decreases in HFD-mice, which were no longer present after

36 weeks (Fig. 6C). MS/MS analysis and neutral loss scanning was

performed to validate glycerolipid class identities (Suppl. Table 1–2).

3.6. Liver endocannabinoids

Given that many of the species altered in HFD-fed mice were

phospholipids containing polyunsaturated fatty acids (PUFAs), and

because many of the fatty acyls correlated to derivatives of fatty acids,

we focused on arachidonic acid-containing metabolites, including 2-

arachidonoylglycerol (2-AG) and N-arachidonoylethanolamide (AEA).

Upon release, these endocannabinoids target cannabinoid receptors

(CB1 and CB2) and work together to play a role in energy homeostasis

[22]. Liver 2-AG levels decreased after 6 and 36 weeks of HFDconsumption

(Fig. 7A). Interestingly, an age-related effect was observed

where 36 weeks of HFD-feeding decreased liver 2-AG levels (Fig. 7A).

The decrease of 2-AG levels on the liver after 36 weeks was accompanied

by a significant increase of AEA (Fig. 7B). The only significant

effect of HFD on liver AEA levels was a significant decrease after

6 weeks on the diet (Fig. 7B). CB1 expression did not change while CB2

expression showed time-dependent increases in HFD-fed mice, although

these were not significant (Fig. 7C).

3.7. Plasma endocannabinoids

Plasma levels of 2-AG and AEA in the LFD-fed mice were quite

stable, apart from a slight increase after 36 weeks of feeding (Fig. 8). In

contrast, HFD-consumption increased plasma levels of 2-AG, but the

effects were bi-phasic where a significant increase was only observed at

6 and 36 weeks, but not after 22 weeks of HFD-consumption (Fig. 8A).

There also appeared to be an effect of age on plasma 2-AG within the

HFD-fed mice as shown by an increase in 2-AG levels following

36 weeks compared to 22 weeks of feeding (Fig. 8A). The effects of

HFD-consumption on the other endocannabinoid, AEA, resembled the

diet's effects on plasma 2-AG, with the only significant effect being an

increase of plasma AEA levels after 36 weeks on HFD (Fig. 8B).

3.8. Plasma esterase activity

The increase in fatty acyls and lysophospholipid species suggests

increased esterase activity. This hypothesis was addressed by assessing

esterase activity at all time points in the plasma. HFD-consumption

increased plasma esterase activity at all time points, with the most

pronounced effect following 6 weeks of feeding (Fig. 9). Although

plasma esterase activity increased following both 22 and 36 weeks, the

effect at 36 weeks was not significant (Fig. 9). It appeared that age

alone affected plasma esterase activity, indicated by heightened esterase

activity after 6 weeks of HFD-consumption followed by lower

levels at later time points (Fig. 9).

3.9. Liver qPCR data of key lipid homeostasis genes

There are many genes that encode for protein regulating energy

balance and lipid metabolism, including peroxisome proliferator-activated

receptors (PPARs) [35,36]. PPARα is best known for its major

role in lipid and lipoprotein metabolism while PPARγ is involved in

adipogenesis and insulin sensitivity [35,37]. HFD-consumption increased

expression of liver mRNA levels of PPARα, PPARγ, and CD36, a

known target of PPARγ [38], significantly at 6 weeks of HFD (Fig. 10A).

Interestingly, PPARα and PPARγ levels increased after 36 weeks of

HFD-consumption, but not after 22 weeks. Liver CD36 mRNA was elevated

at all three time points (Fig. 10A), with the magnitude of elevation

greatest after 36 weeks on HFD.

PPARγ has been shown to increase during lipogenesis, thus we assessed

the expression of fatty acid synthase (FAS), acetyl-CoA carboxylase

(ACC), and stearoyl-CoA desaturase (SCD) (Fig. 10B). HFD-fed

mice demonstrated a numerical trend of time-dependent increases

although not significant, in SCD, ACC, and FAS expression (Fig. 10B).

MGL demonstrated increased expression in mice fed HFD for 6 weeks;

however, this effect was tapered after long- and prolonged-feeding

(Fig. 10B).

3.10. Correlation between lipids, GTT/IST, plasma endocannabinoids, liver

homeostasis

We performed regression analysis to determine if changes in the

blood lipidome correlated to changes in GTT or IST, plasma endocannabinoid

levels, or gene expression of liver homeostasis markers.

Table 1A lists correlations (R2 ≥0.6) between several lipid features and

the expression of CD36, PPARα, and PPARγ mRNA in the liver. There

were only a few lipid species whose abundance correlated to changes in

these genes, including two unidentifiable FA species. Correlations occurred

at all time points with increases in TG (52:4 or 52:5) [PPARγ] in

HFD-mice at 6 weeks, decreases of DG (40:6) [CD36], PE (42:7)

[CD36], and FA (m/z 562.8) [PPARα] at 22 weeks, and an increase in

FA (m/z 438.8) [PPARα] at 36 weeks (Fig. 11). Lipid species indicated

by only their m/z value were unable to be fully characterized by subsequent

MS/MS analysis.

Regression analyses also demonstrated quite a few relationships

between changes in select blood lipids and changes in AUC from glucose

tolerance and insulin sensitivity tests after 6 weeks (Table 1B).

Fewer correlations were identified for changes in the blood lipidome at

22 or 36 weeks (Suppl. Table 3), which is not surprising given the robust

differences observed after 6-weeks of treatment. Interestingly,

several lipids such as PC (44:3) and DG (34:3), which correlated to

glucose tolerance, also demonstrated inverse correlates to insulin sensitivity.

Regarding plasma endocannabinoids, GL species (m/z 734.6, m/z

760.5) and FA species (m/z 353.2) correlated to changes in in 2-AG

exclusively within HFD-mice, whereas AEA did not correlate to any

lipid features (Table 1C).

4. Discussion

The association between increased high-fat consumption and excess

adiposity poses a major global health problem that heightens the risk of

metabolic disorders, diabetes, heart disease, fatty liver, and some forms

of cancer [39]. Growing evidence implicating a role for impaired lipid

metabolism, coupled with the advent of bioinformatics tools has

prompted efforts in characterizing the obese lipidome [40–42]. While

these studies have highlighted alterations in the plasma and/or serum

lipidome, there have been few studies examining the effects of age on

the lipidome and/or the interaction between age and obesity. Further,

the number of studies that address diet-induced obesity within female

models is quite limited, although an increased linear trend of female

obesity among US women within the last decade demonstrates the

significant need [3,43,44]. Here, we used shotgun lipidomics to assess

the effects of dietary fat consumption, age, and their interaction at the

level of the blood lipidome. We correlated changes in the blood lipidome

to changes in metabolic regulation, endocannabinoid levels, and

plasma esterase activity.

One of the most interesting findings of this study is that the effect of

age superseded the effect of HFD with regard to alterations in the blood

lipidome. These data emphasize the need to characterize and stratify

lipidomic alterations not only to diet, but also to age. The accentuated

effect of age on the lipidome between 12-week-old (6-weeks on the

diet) vs. 28-week-old (22 weeks on the diet) and 42-week-old (36 weeks

on the diet) mice indicated distinct shifts in lipid composition and/or

regulation, an interesting note since all ages fall within the mature adult

phase of C57BL/6 mice. Although multivariate analysis indicated a

slight difference between 28- and 42-week-old animals, the separation

was not as robust. With regard to dietary treatment, younger animals

presented striking lipidomic responses to HFD-consumption while older

animals had a more tapered shift, possibly a result of time-dependent

homeostatic mechanisms in response from long-term feeding. In this

regard, as we reported recently, it is interesting to note that in terms of

insulin sensitivity, but not glucose tolerance, age appears to be a major

driver of decreased insulin sensitivity to the point that the effects of

prolonged HFD feeding are overpowered by the effects of age [17].

Given the limitations of the shotgun approach along with the sheer

number of features identified in this study, we report general lipidomic

changes in terms of lipid class with alterations falling into three classes:

glycerolipids (GL), fatty acyls (FA), and phospholipids (PL). MS/MS

analysis was employed to verify these lipid species (Suppl. Table 1).

Features changing at only a few time points showed a class-specific

trend in terms of differential lipid expression; however, most changes

indicated species-specific alterations.

A few studies have demonstrated alterations in lipid classes within

rodent obesity where the majority of reported changes encompass

ceramides, cholesterols, triglycerides, and phospholipids. For example,

changes in lipid species such as lysophosphatidylcholines have been

associated with obesity, insulin resistance, and type 2 diabetes [45–47].

In agreement with some of these studies, we report elevations in PC

(38:5), PC (44:3), and PC (38:3) in the blood of HFD-fed mice, also

reported in Eisinger et al. [40]. Changes in GL and FA reported in the

current study are not in line with another study [48], but it should be

noted that the sex of the mice, feeding durations, and importantly, the

dietary composition in [48] and our study are different. It should also

be pointed out that several studies have demonstrated that HFD typically

increases the levels of TAGs and DAGs [49]. The fact that not

many of these lipids were detected in our own study is most likely a

limitation of the shotgun approach used.

As mentioned above, lipidomic alterations identified by shotgun

analysis revolved around three major lipid classes (GL, FA, and PL),

which also happen to constitute the endocannabinoid system.

Quantification of both 2-AG and AEA demonstrated several correlations

with specific blood lipids. AEA and 2-AG, both derivatives of arachidonic

acid, are signaling lipids that mediate their action via activation

of cannabinoid receptors. Further, changes in plasma levels of 2-AG and

AEA after 6 and 36 weeks associated with decreases in liver 2-AG. This

suggests that increased 2-AG levels in circulation are due to increased

mobilization from the liver, with/without concomitant decreased 2-AG

breakdown [50]. In a study by Caraceni, et al., 2-AG levels were reported

to be higher in the hepatic veins of cirrhosis patients when

compared to peripheral blood, supporting the hypothesis that the liver

contributes to circulating 2-AG levels [51]. This may also suggest that

the source of the increase in plasma 2-AG is non-hepatic, i.e. dietary

[20].

Plasma AEA levels were most affected by the diet after 36 weeks;

however, as opposed to the decreases of liver 2-AG, liver AEA was increased

after 36 weeks irrespective of diet. Together, these data indicate

that in female C57BL/6 mice plasma 2-AG is more sensitive to

HFD-consumption. Further, similar to other endpoints in this study, the

effects of HFD diet are most prominent during early (6 weeks) and late

phases (36 weeks) of the feeding trial. Circulating endocannabinoids

also appear to be more sensitive to non-dietary liver pathology than

their liver levels. For example, in certain conditions, i.e. hepatitis C,

plasma, but not liver, 2-AG was increased [52]. On the other hand,

circulating AEA was significantly higher in cirrhotic patients [51].

A novel finding is the fact that age was associated with decreased 2-

AG and increased AEA in the liver. At the end of the study (36 weeks on

the diet, 42-43-week-old), the mice were middle-aged and close to

becoming reproductively senescent [53]. While liver-specific

endocannabinoid data for female C57BL/6 mice within the context of

age are lacking, it is interesting that a recent study reported decreased

2-AG, but not AEA, levels in the hippocampus of aged mice [54]. In this

study, the decrease in hippocampal 2-AG was attributed to a concomitant

decrease of local 2-AG synthesis and increase of its breakdown

[54]. With that in mind, our data suggest that the age-dependent metabolic

changes in the 2-AG pathway that operate in the brain (hippocampus)

do so in the liver as well. In addition, the increase in liver AEA

levels at the end of the study highlights endocannabinoid metabolitespecific

effects of age. Although Osei-Hyiaman, et al. previously showed

that liver AEA levels increase following HFD, our data indicate lower

levels of hepatic AEA in HFD-fed mice [55,56]. However, it is important

to note that the dietary feeding regimen in Osei-Hyiaman, et al. was

initiated in slightly older mice, which may play a large role given our

data demonstrating the interaction of age and diet. Moreover, the

findings in the above study were based on the use of a combination of

male and female mice and thus, does not reflect the effects within females

alone. This would not be surprising since gender-specific responses

to HFD-intake have been reported in rodents, and it has even

been suggested that females are more susceptible to developing the

secondary effects of HFD-induced obesity [57]. It should also be mentioned

that adipose distribution and function differs across males and

females, so differences are expected to exist in mediators produced by

adipocytes such as endocannabinoids [57–59].

The increased circulating 2-AG levels in the female C57BL/6 mice in

our study are in line with multiple studies in obese human subjects. For

example, obese men, especially those with increased intra-abdominal

adiposity, have increased plasma 2-AG [60]. Interestingly, direct correlation

between plasma endocannabinoids, insulin resistance and

dyslipidemia has been suggested [61]. Moreover, chronic cannabinoid

receptor 1 (CB1) stimulation exacerbates the metabolic dysregulation

caused by HFD-consumption, suggesting key role for the endogenous

endocannabinoids in the process [62]. Circulating endocannabinoids

might contribute to obesity by their central and/or peripheral actions

[20]. The key role of CB1-specific over-activation by excessive endocannabinoids

is further emphasized by the fact that global CB1−/−

mice are not susceptible to HFD and liver-specific CB1−/− mice are

protected from some, but not all, of the adverse effects of HFD intake

[63]. Treatments aimed at reducing plasma endocannabinoids are

beneficial in re-balancing the metabolic dysregulation [64] and obesityrelated

inflammation [65], but not for reducing the body weight in

obese subjects [64]. Interestingly, and in line with our current data,

circulating 2-AG levels were significantly elevated in insulin-resistant

obese women [66].

Peroxisome proliferator-activated receptors (PPARs) are members

of the steroid hormone receptor superfamily of nuclear transcription

factors that are involved in the regulation of various genes encoding

proteins involved in energy balance and lipid metabolism [35,36].

PPARα is best known for its major role in lipid and lipoprotein metabolism

while PPARγ is involved in adipogenesis and insulin sensitivity

[35,37]. It has also been suggested that hepatic PPARγ may mediate the

accumulation of fat via the regulation of genes essential for de novo

lipogenesis, i.e. fatty acid synthase (FAS), acetyl-CoA carboxylase (ACC),

and stearoyl-CoA desaturase (SCD) [67]. Further, it is possible that

glycerolipid alterations can be attributed to changes in lipolysis via

monoacylglycerol lipase (MGL), one of the main lipases involved in the

catabolism of TG.

In our study, we also observed HFD-induced increases in liver

PPARα, PPARγ, and CD36. The increases in PPARα and PPARγ were

biphasic (6 and 22 weeks) and more prominent after 6 weeks of HFD

feeding, indicating that the activation of the PPAR pathways are timedependent.

PPARα regulates fatty acid β-oxidation, is activated by the

AEA analogue oleoylethanolamide (OEA), and pharmacological increases

of OEA are beneficial to diet-induced obese mice [68]. While we

have not measured OEA in our study, it is conceivable that the lack of

significant increase in liver PPARα after 22 weeks of HDF feeding was

due to sensitization-dependent downregulation. Liver PPARγ, which

showed similar kinetics to PPARα, regulates lipid and glucose homeostasis,

is elevated by a HFD [69], and approaches aimed at curbing its

activation are beneficial in obesity and type 2 diabetes [70]. Together,

the changes in liver PPAR levels are in line with the time-dependent

metabolic dysregulation of these mice, especially the sensitivity to insulin

challenge, and reflects the changes in the blood lipidome reported

here [17].

CD36 was the sole lipid homeostasis/inflammation molecule whose

expression was increased by HFD throughout the study. Increases in

CD36 were greatest at the end (36 weeks) of the experiment. CD36 is

associated with obesity, diabetes, and liver dysfunction; hence, our

findings are not surprising. Liver CD36 was previously shown to increase

due to aging [71]. Thus, the marked increase in liver CD36 at the

end of the feeding duration could be a sum of the effects of age and HFD

on its expression or, due to increased demand for hepatic lipid uptake in

the face of continued HFD-consumption. In this regard, CD36 plays a

major role on hepatic fat uptake [71].

Circulating esterases are predominantly investigated for their role in

the metabolism of drugs and toxicants, though they also metabolize

endogenous, i.e. dietary, and exogenous lipids [72]. The early robust

increase in plasma esterase that we observed in the current study might

be the result of host's attempt to maintain lipid homeostasis in the face

of excessive dietary fat. Over time, the increases in esterase activity

were still present, but less robust. This may reflect saturation of this

likely protective mechanism. In support of this hypothesis, esterasedeficient

mice are not only more susceptible to pesticides that are detoxified

by it, but also to diet-induced metabolic dysregulation and

atherosclerosis [73]. Our data indicating an age effect, i.e. decreased

plasma esterase due to age, further supports the notion that this mechanism

of metabolizing excessive dietary fat is less robust in older

mice.

In conclusion, we demonstrated an interaction between dietary fat

consumption and aging with widespread effects on the blood lipidome

in female mice. This study indicates that the effects of HFD feeding

occur in an age-dependent manner with robust responses at a younger

age. Further, we identified several associations between lipids and

metabolic and liver regulation, providing a basis for female-specific

obesity- and age-related lipid biomarkers. These findings highlight the

need for additional age-dependent tracking studies, prior to sexual

maturity into advanced age, to obtain comprehensive understanding of

the evolving lipidome with regard to dietary changes.

Answer 1

                 Obesity is a growing public health concern. As obesity increase the risk of type 2 diabetes, fatty liver and pulmonary inflammation is also increase. The prevalence of obesity was 35% in younger men and 40% in younger females, observed in US. Obesity has also been associated with several types of cancer, cardiovascular disease and Alzimer’s disease. In addition, increased circulation endocannabinoids has been involve in obesity. In the present study, the glucose tolerance and insulin sensitivity test performed after 5, 20, 33 weeks. Phospholipids were extracted using chloroform and methanol method. Lipid phosphorus was quantified using phosphorus assay. Phospholipid characterization was performed using ESI-MS. Liver endocannabinoids were extracted using the method of Kingsley and Marnett and plasma 2-AG and AEA level were determined by mass spectroscopy. Total liver RNA extracted and real-time qPCR was performed to determine the level of expression of gene associated with obesity. The result indicates that high fat diet feeding will probably increase the risk factor at younger age. Hence it is occurred in an age dependent manner. Additional studies on age dependent tracking are required prior to sexual maturing for understanding lipid metabolism and the evolving lipidome with regards to dietary changes.

Advantages of HFD

Monounsaturated fat and polyunsaturated fat are good for health

Healthy fat like omega-3 helps to lose fat, increase metabolism and balances the activity of enzyme.

Fat compensate or balance the calories intact with low carbohydrate diet (if your carbohydrate level is low that is compensate by fat)

Fat present in fish, olives and nuts are helpful to remove cholesterol which is bad fat, from body.

Healthy fat intake increase androgen level hence it increase reproductive health.

DHA and omega-3 like fatty acids increase brain function

It also decreases risk of cancer.

Disadvantages of HFD

Unhealthy fat (saturated fat) increase cholesterol level in body and leads to heart disease.

It decreases the metabolism rate and increase obesity.

Obesity is a cause of type 2 diabetes, cardiovascular disorders and heart disease.it is also involve in cancer and Alzimer’s like disease.

Advantages of Endocannabinoids

It prevents aging of brain and increased brain’s functionality.

It increase growth hormones, prevent anxiety and increase ACTH.

It lowers the stress level and help in insomnia (increase sleep).

It decreases prolactine level and increases PPARγ expression.

It also helps in lowering inflammation.

Disadvantages of Endocannabinoids

Studies indicate that it may involve in tumor formation inside brain.

It decreases acetyle choline and glutamine

Decrease bone density

May increase liver fat

It inhibits cAMP pathway.