Nascholing Diëtisten Netwerk

Nutrition et Sante4 October 2014

Wim H.M. SarisNutrition Research Institute NUTRIM

Faculty of Health, Medicine and Life ScienceMaastricht University

The Netherlands

• Veel aandacht voor Microbiota en metabole consequenties.

• Discussie over rol macronutrienten in het bijzonder van eiwit en eiwit/koolhydraat ratio tijdens gewichts behoud.

• Lange termijn effecten en succes• Nudging• Micronutrienten status bij obesitas• De nieuwe generatie medicijnen; GLP-1 analogen

zoals liraglutide

Update obesitas onderzoek

ICO Kuala Lumpur March, ECO Sofia May 2014 en nieuwe studies

Microbiome and metabolism

• Metagenome; 150 x more genes compare to Human genome and 10x more cells

• In Humans 3 enterotypes; 3 major types of gut microbiota

• Stable over time (~80 %)• Animal models showed clear effect on

metabolism.• Human studies gives indications but no proof

on relation between enterotypes and obesity.

Phylogenetic diversity

5

Diversity of the gut ecosystem is of importance

6

7

Genotype – microbiome interacties

8

9

10

Relation microbiota and human health

De Vos nature 2013

12

Nature 2013

conclusion

14

15

Proposed Balance of Gut Microbiota in Metabolic Health and Disease

BacteroidetesFirmicutes

Normal Energy Balance, Insulin Sensitivity, No

Systemic Inflammation

Gordon JI. Nature

Firmicutes Bacteroidetes

Obesity, Insulin Resistance, Pro-

inflammatory State

Gut microbiota in Human adults

Bacteroidetes

(Beta)proteobacteria

Firmicutes

Diabetes

Bacteroidetes/Firmicutes correlated positively with plasma glucose

• Increased Firmicutes/Bacteroidetes (Ley et al, nature, 2006, Turnbaugh et al, 2009)

• Decreased Fimicutes/Bacteroidetes(Collado et al,2008,Schwiertz A, Obesity, 2010)

Weight loss and bacteroidetes related taxa, relationship:-positive (Nadal J, IJO, 2009)-neutral (Duncan SH, IJO, 2008)-negative (SantaCruz, obesity,

2009)

• Differences in other phyla and species (i.e bifidobacteria), novel diversity with each study

• Higher SCFA, in particular proprionate in obese subjects (Schwiertz A, Obesity, 2010)

Outcome in human studies is more complex

18

-30

-25

-20

-15

-10

-5

0

5

Maintaining weight loss is challenging

Mann et al. Am Psychol 2007;62:220‒33

Weig

ht

change, K

g

Mean changefrom baseline toend of diet (kg)

Mean changefrom baseline tofollow-up (kg)

Follow up range from 4 to 7 years

Anderson et al.

Fosteret al.

Graham et al.

Hensrudet al.

Jordanet al.

Krameret al.

Lantzet al.

Murphyet al.

Stalonaset al.

Waddenet al.

Walsh &Flynn

Wadden & Frey

Pekkarinen & Mustajoki

Stunkard & Penik

• Resting Metabolic Rate, Total Energy expenditure • Leptin, ghrelin, GLP-1

• Appetite• Preference for energy dense foods (high fat/sugary foods)

• Insulin sensitivity• Adipose tissue TG lipolysis• Pro-inflammatory cytokines• Adipose tissue lipoprotein lipase• Skeletal muscle lipoprotein lipase• CHO oxidation and fat storage

The physiological responses to weight loss favour weight regain

Eckel RH. N Engl J Med 2008;358:1941‒50

CHO, carbohydrate; GLP-1, glucagon-like peptide 1; TG, triglycerides

The macronutrient debate and weight control

• 1980 – 2000 Fat intake • 2000 - 2010 Carbohydrate intake • 2000 – 2013 Protein intake

Hierarchy of satiety

mct, medium chain triglycerides R.Cottrell, 1995. Weight control – the current perspective. (Champman & Hall, London)

Leucine

Fructose

mct

Sucrose

Fiber

Protein

Carbohydrate

Fat

Arguments to reduce total fat intake

• Strong level of evidence for overfeeding from animal studies• High fat diets are associated with overeating compared to high

carbohydrate diets in Humans• Excess energy as fat is stored more efficiently compared to

carbohydrate• RCT’s with Ad lib low fat diets show clear weight loss effect (~3.0 kg)

Weight loss difference (kg)

+10 0 –10 –20

Saris et al. CCHO (2001)Saris et al. SCHO (2001)Skov et al. LP (1999)Skov et al. HP (1999)Stefanick et al. M (1998)Stefanick et al. F (1998)Weststrate et al. (1998)Simon et al. (1997)Siggaard et al. (1996)Pritchard et al. (1996)Raben et al. (1995)Kasim et al. (1993)Hunninghake et al. (1993)Baer (1993)Sheppard et al. (1991)Bloemberg et al. (1991)Buzzard et al. (1990)Boyd et al. (1990)Lee-Han et al. (1988)

Weighted overall (fixed effects)

Weighted overall (random effects)

Astrup, Hill and Saris. Int J Obes 2000;24:1545‒52

Meta-analysis of low-fat diets: effect on body weight

High protein and low glycaemic index foods improve weight loss maintenance

Larsen et al. N Engl J Med. 2010;363:2102-13.

• Overweight adults (n=773) who had lost ≥8% of their initial body weight through diet were assigned to five different diets

• A modest increase in protein content and reduction in the glycaemic index helped to prevent weight regain

Coloured boxes indicate change in body weight from randomisation to Week 26 among participants who completed the interventionHGI, high glycaemic index; HP, high protein; LGI, low glycaemic index; LP, low protein

2.0

1.5

1.0

0.5

0.0

‒0.5

0 102 4 6 14 18 22 26

Week

Chang

e in b

ody w

eig

ht

(kg)

LP-HGI

HP-HGI

Control

LP-LGI

HP-LGI

27

28

29

30

The macronutrient debate and weight control

• 1980 – 2000 Fat intake • 2000 - 2010 Carbohydrate intake • 2000 – 2013 Protein intake

• 2014 Back to energy intake control ?

Editorial Nature 13 March 2014

32JAMA Sept 2014

33Johnston et al JAMA 2014

Second law of thermodynamics

a calorie is still a calorie

- 600 Kcal deficit diet

• High fat diet (40 En% fat, 43 En% Carb)

• Low fat diet (25 En% fat, 57 En% Carb)

Petersen et al IJO 2005

Randomised, multi- centre trial of two hypo-energetic diets with different fat content in obese subjects

Body weight loss during the 10 week – 600 Kcal intervention in the

high (n=312) and low-fat group (n=336)

Week

10

9

8

7

6

5

4

3

2

1

0

Weig

ht

loss (

kg) 0

-2

-4

-6

-8

-10

DIET

mod

low

- 6.6 ± 0.2

-6..9 ± 0.2ns

36

AJCN 2014

37

Germany

The Netherlands

United States

United Kingdom

Source: Troesch et al BJN 2012

Micronutrient intake in Western countries

39

Dietary quality and 6 years weight changesSuvimax cohort France N = 1469

Assmann et al Plosone 2014

• Based on PNNS score (Program National Nutrition et Sante

Six year change in Body weight (%)

Low PNNS

Medium PNNS

HighPNNS

Males +3.35 +2.23 +1.76 *

Females +1.70 +2.63 +3.58 #

* P<.005, # NS

Fig. 1 Prevalence of serum 25 OHD 30 ng/mL or greater for different BMI categories across difference ethnicities in NHANES 2001–2006. N = 12927

Samuel and Borrell Annals of Epidemiology, Volume 23, Issue 7, 2013, 409 - 414

The effect of body mass index on optimal vitamin D status in U.S. adults: The National Health and Nutrition

Examination Survey 2001–2006

41

Serum Micronutrient level before weight loss

Damms- Machado et al Nutr J.2012

42

• The satiating effects of meals with varying protein contents were examined in 25 men:• Normal, medium‒high and high protein: 14%, 25% and 50% of energy from

protein, respectively

• Protein dose-dependently: • Increased satiety and fullness• Decreased hunger and prospective food consumption• Increased glucagon, PYY3-36 and GLP-1

The effects of protein on satiety appears to involve glucagon and the gut hormones PYY3-36 and GLP-1

Belza et al. Am J Clin Nutr 2013;97:980–9

PYY, peptide YY

30

70

4-h

VA

S s

ati

ety

(m

m) 60

50

40

20

10

0

0 30 60 90 120 150 180 210 240

Time (min)

The effects of protein on satiety are partially mediated by GLP-1

GLP-1, glucagon-like peptide-1; HP, high protein; MHP, medium‒high protein; NP, normal protein; VAS, visual analogue scale

Belza et al. Am J Clin Nutr 2013;97:980–9

HPNP MHP50

40

30

20

10

0

–10

–20

GLP

-1 (

pm

ol/L)

Time (min)

150 2400 30 60 90 120 180 210

Series10

1000

2000

3000

4000

5000

3592

3004 3024

Effect of liraglutide on ad libitum energy intake

Data are estimated means. Treatment differences are calculated using the parametric linear mixed effect model on the original outcome values The model included effects of subject, period and treatment group; subject effect was included as a random effect ETD, estimated treatment difference

Energ

y inta

ke (

kJ)

ETD (95% CI): 19.4 (–339; 378)

ETD (95% CI): –588 (–951; –224) p=0.002

ETD (95% CI): –568 (–937; –199) p=0.003

Liraglutide 3.0 mg

Placebo

Liraglutide 1.8 mg

van Can et al. Int J Obes (Lond) 2013. doi: 10.1038/ijo.2013.162

Series10

250

500

750

492.9 478.3 468.8

Effect of liraglutide on 24-hour energy expenditure

Data are estimated means. Treatment differences were calculated using the parametric linear mixed-effect model including effects of period and treatment group. Subject was included as a random effect. EE, energy expenditure

Food e

xpendit

ure

(kJh

our-

1)

ETD (95% CI): -9.6 (–20.8; 1.7)

ETD (95% CI): –14.6 (–26.7; –2.5) p=0.02

ETD (95% CI): –24.2 (–35.4; –12.9) p=0.0001 Post hoc analysisexplains most of thereduction in 24h EEdue to the 2.1 Kg weight loss

van Can et al. Int J Obes (Lond) 2013. doi: 10.1038/ijo.2013.162

Liraglutide 3.0 mg

Placebo

Liraglutide 1.8 mg

Schiphol

Nudge to nobesity

Change default choice

Middle vs. edge, spoon or plier

• Fluor toothpaste• Lowering salt, fat and sugar• Lowering trans fat• Adaptations in food ingredients to get a healthy logo

Big challenges for the food industry

Making the healthier choice the easy choice

‘Stealth’ changes without consumer notice

Finally

Nature editorial 17 sept 2014

Microbiota in responders and non-responders

53Editorial Nature August 2014