a healthy gut, a healthy heartd3hip0cp28w2tg.cloudfront.net/uploads/block_files/... · leaky gut...

Fondazione Edmund Mach

A healthy gut, A healthy heart:

The influence of gut microbiota on cardiovascular disease

Francesca Fava, PhD

FOODMATTERSLIVE, 19th November 2014

Non modifiable

Age Genetics/genotype Family history of CVD Sex

Modifiable

High blood pressure Dyslipidemia Diabetes and insulin resistance Smoking Physical inactivity Overwieght and obesity

Risk factors for cardiovascular disease (CVD)

Intestinal transit

Incretins/satiety

Gut:brain axis

Gut:liver axis

Bile acids & cholesterol (enterohepatic BA circulation)

Insulin resistance

1000 species Genome (metagenome) > 100 x human genome

Metabolic endotoxemia

Gut Microbiota

• Currently 300 million people obese world-wide

• Obese adults are up to 80 times more likely to develop type 2 diabetes than non-obese adults

• Obese adults are 2-3 times more likely to develop heart disease

• Obese adults have a 40% increased risk of dieing from cancer

OBESITY EPIDEMIC

Result

•Diets designed for reduced energy intake/slimming, with either reduced fat or reduced carbohydrate •Microbiota approaches lean profile with weight loss – no info on diets (nutrient substitution) Ley et al., Nature (2006)

Obese vs lean gut microbiota

Lean –open diet (LOD ■) Obese open diet (OOD ■) Obese on a saturated fat diet for 1 month (OHSFA ■) n=13

•Bacteroides uniformis and Prevotella copri more common in the microbiota of LOD than OOD – not present in the OHSFA

•Bacteroides vulgatus and Bacteroindes stercoris very frequently found in OHSFA, less frequent in OOD – not present in LOD

-5

0

5

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10

PC

2

PC1

DGGE bands pattern (PCA)

[PC2]/[PC1]

%[1] = 0.092199 %[2] = 0.0642478

LOD

OHS

OOD

Fava et al in preparation

Fermentation end-products

• Faecal SCFA measured by GC

• Higher acetate in obese irrespective of diet

• Higher butyrate in obese (open diet)

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

ACETIC

PRO

PIO

NIC

I-BUTY

RIC

N-B

UTY

RIC

I-VALE

RIC

N-V

ALE

RIC

N-C

APRO

IC

mm

ol/g

faeces

LOD

OOD

OHSFA

TMA/TMAO confirmed strong link with CVD in patients •confirmed microbiota metabolism of L-carnitine/choline → TMA→TMAO •TMA not produced in vegans •confirmed inflammatory activity & linked to macrophage reverse cholesterol transport •TMAO reduced bile acid pool

Wang et al., 2011 Nature

Koeth et al., 2013 Nature Medicine

Δ SCFA and BA

↑ inflammation

Impact of traditional diets rich in fiber,

polyphenols on colonic fermentation

High fiber diets, Paleolitic, Mediterranean, rural African and Asian Enhanced mucosal barrier function and immune homeostasis

Proximal colon ~ saccharolytic

SCFA

Acetate Propionate

Butyrate

Energy source Apoptosis

Differentiation Epigenetics

Gene expression Gut hormones

Gut permeability

Distal colon ~ proteolytic

Amines Indoles

Ammonia Sulphides N-nitroso

DNA damage

Tumours Cytotoxicity

Leaky gut Liver disease

Modified from George Macfarlane

Dietary Pro- and Prebiotics

• PROBIOTICS....“live microorganisms which when administered in adequate amount confer a health benefit on the host” (FAO, 2001). - Lactobacillus - Bifidobacterium - Escherichia coli Nissle 1917, Bacillus sporogenes,

Enteorcoccus faecium, Clostridium butyricum, Saccharomyces ceriviseae

• PREBIOTICS…. a selectively fermented ingredient that

results in specific changes, in the composition and/or activity of the gastrointestinal microbiota, thus conferring benefit(s) upon host health. Gibson et al (2010) – Inulin, oligofructose, fructooligosaccharides,

galactooligosaccharides, lactulose, arabinogalactan, arabinoxylan, pectic-oligosaccharides, glucooligosaccharides

– Resistant starch and certain whole plant foods including whole grain wheat, whole grain oats and red-wine polyphenols

Cani et al., 2007 Diabetes

Plasma endotoxin (LPS) increased

with HF diet

• Upon high fat feeding or LPS injection inflammatory markers increased in liver and adipose tissue

– TNF-α, IL-1, IL-6

– insulin resistance and obesity

• In CD14 mutant mice this inflammatory response was blunted

Prebiotic (OFS) intervention in high-fat fed mice

• To test if the modulation of the intestinal microbiota through dietary intervention with a prebiotic can control the occurrence of high-fat diet-induced inflammation and metabolic disorders in mice.

PREBIOTIC

MICROBIOTA

HIGH FAT DIET LPS

INFLAMMATION

OBESITY and TYPE 2 DIABETES

Cani et al., 2007 Diabetologia

Experimental design


Measurements (T0 and T14weeks):

Microbial enumeration in caecal contents

Plasma LPS

Inflammatory markers

Glucose tolerance

Insulin secretion

Body weight and fat mass

gain

C57bl 6/J mice (n=8/group)

Standard control diet CT

High-fat diet HF

High-fat diet + cellulose HF-Cell

High-fat diet + oligofructose

HF-OFS

Microbiota modulation in high-fat fed mice


Inflammatory markers

(Mean±SEM; p<0.05 post hoc ANOVA)

CT

HF

HF-Cell

HF-OFS


Glucose tolerance & glucose-induced insulin secretion

CT

HF

HF-Cell

HF-OFS

HF-Cell

CT

HF

HF-OFS



Body weight and fat mass gain

0

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4

6

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12

14

CT HF HF-Cell HF-OFSTo

tal B

od

y W

eig

ht

Ga

in (

g)

a

c

b

c


0

1

2

3

4

5

6

7

Visceral Epididymal Subcutaneous

Ad

ipo

se t

issu

e g

ain

(%

of

bo

dy w

eig

ht)

a b

a a

c

b c

b

a a

d c


Plasma LPS levels – correlate with bifidobacteria

(Mean±SEM; p<0.05 post hoc ANOVA).

0

5

10

15

20

CT HF HF-Cell HF-OFS

En

do

to

xin

(E

U/m

l)

a a

b

b

(Pearson’s correlation)

•Reduced inflammation and normalisation of insulin sensitivity


Prebiotic relief of metabolic endotoxemia

through improved mucosal barrier function

LPS LPS LPS

High fat, low CHO diets induce microbiota dysbiosis

Low SCFA

•↑Inflammation •↑Insulin resistance •↑Hepatic fat deposition

Activation of WAT & liver inflammatory pathways

Prebiotic induced bifidogenesis & microbiota biosis

↑GLP-1, GLP-2, PYY ↑Tight junction proteins

High

SCFA

•↑ Satiety •↓Food intake •Maintenance of gut barrier function •Immune homeostasis

Mucosal

barrier

Changing the type and quantity of dietary fat and carbohydrate affects metabolic syndrome

and gut microbial parameters

Diet A: high SFA (run-in & control diet). Energy ~38% fat , SFA~18%, MUFA ~12%, PUFA~6%, CHO ~ 45% Diet B: high MUFA – high GI. Energy ~38% fat , SFA ~10%, MUFA ~20%, PUFA ~6%, CHO ~ 45%) Diet C: high MUFA – low GI. Energy ~38% fat , SFA ~10%, MUFA ~20%, PUFA ~6%, CHO ~ 45%) ~ 11 GI

points lower glycaemic index Diet D: low fat – high GI. Energy ~28% fat , SFA ~10%, MUFA ~11%, PUFA ~6% CHO ~ 55%) Diet E: low fat – low GI. Energy ~28% fat , SFA ~10%, MUFA ~11%, PUFA ~6% CHO ~ 55%) ~ 13 GI points lower glycaemic index

Baseline Treatment

Weeks -4 0 24

Total study n = 650; Reading cohort n = 130 (Powered for insulin sensitivity)

The RISCK study: Reading, Imperial, Surrey, Cambridge, Kings

Jeb et al., 2010 Am J Clin Nutr

Faecal bacterial numbers changed with

quantity of fat or carbohydrate

Bifidobacterium spp

6

6,5

7

7,5

8

8,5

9

9,5

10

HS (n=11) HM/HGI (n=17) HM/LGI (n=22) HC/HGI (n=21) HC/LGI (n=17)

diets

Lo

g[b

acte

ria

l cell

s/g

feces w

et

wt

B

T

Total bacteria

10,2

10,3

10,4

10,5

10,6

10,7

10,8

10,9

11


diets

Lo

g[b

acte

ria

l cell

s/g

feces w

et

wt

B

T

* *

* *

Bacteroides spp

9

9,2

9,4

9,6

9,8

10

10,2


diets

Lo

g[b

acte

ria

l cell

s/g

feces w

et

wt

B

T

*

Faecalibacterium prausnitzii

9

9,2

9,4

9,6

9,8

10


diets

Lo

g[b

ac

teri

al

ce

lls

/g f

ec

es

we

t w

tB

T

* *

Fava et al., 2013 Int J Obesity

Faecal Bacteroides/Prevotella correlated with

BMI and waist circumference

Significant correlation between changes in Bacteroides/Prevotella spp

faecal numbers and body BMI (a), and Waist circumference (b).

Pearson’s correlation, r = -0.64(a), r = -0.45 (b).

∆ Bacteroides/Prevotella (Log10 cells/g faeces) ∆ Bacteroides/Prevotella (Log10 cells/g faeces)


RISCK: Changes in metabolic parameters according to diet

-0,2

-0,15

-0,1

-0,05

0

HS HM/HGI HM/LGI HC/HGI HC/LGI

* *

-12

-10

-8

-6

-4

-2

0

2

HS HM/HGI HM/LGI HC/HGI HC/LGI

*

ΔInsulin (pmol/l)

mmol/l,

mean±SD

HS

(n=11)

HM/HGI

(n=17)

HM/LGI

(n=22)

HC/HGI

(n=21)

HC/LGI

(n=17)

B 25.21±10.15 31.36±12.49 33.98±10.56 32.97±14.70 29.21±12.17 acetate

T 30.61±11.93* 31.04±13.79 32.57±14.04 34.79±20.69 31.14±10.60

B 6.28±3.90 7.84±3.09 9.38±4.00 9.21±6.84 7.31±3.79 propionate

T 7.57±3.96** 7.32±3.99 9.19±4.72 7.87±4.30 7.72±3.95

B 6.02±3.43 7.92±5.32 8.60±4.60 8.45±6.17 7.84±5.61 n-butyrate

T 7.76±4.79** 7.12±4.62 9.52±8.99 8.87±7.80 8.13±3.77

ΔGlucose (mmol/l)


SCFA as biomarker of healthy gut Increased faecal SCFA excretion due to decreased SCFA uptake?

MCT transporters

expression and

apical location is

promoted by

luminal SCFA

Increased faecal SCFA excretion could be due to decreased MCT active uptake in high fat/low CHO diets

Borthakur et al., 2012 Am J Physiol Gastrointest Liver Physiol

Goncalves et al., 2012 J Cell Biochemistry

Bile salt CDCA

and E. coli EPEC

inhibit butyrate

uptake

Whole grain cereals

• Epidemiological evidence

– whole grain cereals associated with reduced risk of CHD, diabetes, colon cancer and obesity (epidemiological studies)

• U.S. Food and Drug Administration – health claim

• Diets rich in whole grain foods and other plant foods and low in total fat, saturated fat, and cholesterol, may help reduce the risk of heart disease and certain cancers

• Lack of information on mechanism of action, polyphenols or fermentation or both?

Whole grain oats vs non-whole grain breakfast cereal

dietary intervention in subjects “at risk” of developing the

metabolic syndrome

•Randomized, crossover study, 30 volunteers, male and female with slightly elevated levels of either total cholesterol or fasting glucose at risk of developing metabolic disorders

•Two 6 week treatment periods separated by 4 week washout periods. •Whole oat grain (WGO) vs non-whole grain cereal (NWG) •Samples collected before and after cereal consumption and then 4 weeks following end of consumption. •Blood (fasted), 24 hour urine, saliva and fecal samples Connolly et al. in preparation Supported by Jordans Cereals

WGO Run-in Wash out NWG

NWG Run-in Wash out WGO

Follow up

Follow up

2 weeks 6 weeks 4 weeks 6 weeks 4 weeks

Whole grain oats modified gut microbiota in beneficial

manner compared to non-whole grain cereal

Whole grain oats significantly increased faecal bifidobacteria and lactobacilli.

WGO WGO

Connolly et al. in preparation

Whole grain oats improved blood cholesterol profiles

•Whole grain oats significantly reduced LDL and total cholesterol, reversing a trend towards elevated LDL and TC in the non-whole grain breakfast cereal treatment.

WGO WGO

Connolly et al. in preparation

Impact of wheat bran fibre (WBF) on gut microbiota

& markers of CVD in overweight adults

•Subjects: n=80, BMI > 27

•FEM & Santa Chiara Hospital, TN (Dr Carlo Pedrolli), APSS, Trento

•Biomarkers of CVD risk

•Gut microbiota (454-pyrosequencing, FISH, qPCR)

•MS based metabolomics (targeted and untargeted)

T-1 T0 T1

2 weeks 4 weeks

27 g aleurone/d

Placebo

TREATMENT PERIOD RUN-IN PERIOD

SCREENING

Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome.

Vrieze et al. 2012 Gastroenterology143(4):913-6.e7.

FEM-CRI, Fulvio Mattivi, Marynka Ulasewska, Urska Vrovsek, Duccio Cavalieri and Roberto Viola

•NN Group: Lorenza Conterno, Elena Franciosi, Carlotta de Filippo, Athanasios Koutsos, Ilaria Caraffa, Florencia Ceppa, Andrea Mancini

•University of Reading, Glenn Gibson, Julie Lovegrove, Michael Connolly

Thank you

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