How the gut talks to the brain: future perspectives of obesity management

Size: px

Start display at page:

Download "How the gut talks to the brain: future perspectives of obesity management"

Quentin Stanley
5 years ago
Views:

1 How the gut talks to the brain: future perspectives of obesity management Carel le Roux Co-Director of the Metabolic Medicine Group, University College Dublin

2 Conflict of interest AstraZeneca Boehringer Ingelheim Consilient Health Covidien Fractyl GI Dynamics Johnson & Johnson Lilly Novo Nordisk ONO Pharmaceutical Roche Image: Adapted for Nurses, 2002.

3 Is obesity a disease?

4 What are the pathognomonic symptoms of obesity?

5 Where are the neurons situated that code for hunger and satiety?

6 -Log 10 (p value) GWAS pathway analyses link CNS genes to obesity Tissues sorted by physiological system genes from CNS showed association (in red) CNS, central nervous system; GWAS, Genome-Wide Association Study. Locke et al. Nature 2015;518: Physiological system

7 Subcortical areas of the brain Courtesy Prof. Licio Velloso le Roux et al. Irish Medical Journal 2016.

8 Physiological range Satiety dose response curve LEAN OBESE Satiety Intervention Meal Size

9 We cannot treat everyone. Who should we prioritise?

10 Johnston L. Express (Home of the Daily and Sunday Express). May 30, [Available from: (Last accessed: Jan 2018)].

11 Should we medicalise this man? BMI: 37 kg/m 2 Physically active Employed Blood pressure: 126/82 mmhg HbA 1c : 5.0 % (31 mmol/mol) BMI, body mass index.

discrimination Fasting glucose: 7.9 mmol/l (142.2 mg/dl) HbA 1c : 8.

12 Should we focus our resources on this man? BMI: 33 kg/m 2 3rd party assistance for ADL Unemployed due to discrimination Fasting glucose: 7.9 mmol/l (142.2 mg/dl) HbA 1c : 8.0 % (64 mmol/mol) Blood pressure: 152/92 mmhg Sleep apnoea Candidate for which intervention? ADL, activities of daily living.

13 Edmonton Obesity Staging System Score Distribution Across BMI Categories, NHANES III ( ) [PERCEN TAGE] [PERCEN TAGE] [PERCEN TAGE] Overweight [PERCEN TAGE] [PERCENTA [PERCENTA GE] GE] [PERCENTA Class GE] I [PERCENTA GE] 23 million [PERCEN [PERCEN TAGE] TAGE] [PERCEN TAGE] Class II [PERCEN TAGE] 10 million [PERCENTA GE] [PERCENTA GE] Class GE] III [PERCENTA GE] 6 million 50 million EOSS, Edmonton obesity staging system. Padwal et al. CMAJ 2011;183:E EOSS Stage 0 EOSS Stage 1 EOSS Stage 2 EOSS Stage 3

14 The benefits of weight loss

Weight loss effects on obesity complications 3 to 10% 3 to >15% 3 to >15% 5 to >15% Maximum benefit at 10% BP still decreasing at >15% TG still decreasing at >15% HbA 1c still decreasing at >15% 5 to

15 Weight loss effects on obesity complications 3 to 10% 3 to >15% 3 to >15% 5 to >15% Maximum benefit at 10% BP still decreasing at >15% TG still decreasing at >15% HbA 1c still decreasing at >15% 5 to 10% 5 to 10% 5 to 10% 10% 10% 10% Improves steatosis, inflammation and mild fibrosis Little benefit at 5% Improves symptoms and joint stress mechanics Lowers androgens, improves ovulation and increases insulin sensitivity 5 to 15% (>10% optimal) *Figure only displays weight loss ranges examined in the studies (i.e. impact of >10% weight on NAFLD, and sleep apnoea symptoms was not reported) BP, blood pressure; TG, triglycerides; GERD, gastroesophageal reflux disease; NAFLD, non-alcoholic fatty liver disease. Cefalu et al. Diabetes Care 2015;38:

16 Mean difference for placebo subtracted QoL improvement Weight loss improves HRQoL * * *significant results Warkentin et al. Obes Rev 2014;15:169 82

17 Cost effectiveness of treating obesity

18 Global burden of obesity Dobbs et al. Overcoming obesity: An initial economic analysis. Mckinsey Global Institute. November 2014

Change in expenditure ($) over one year Medical costs decrease with weight loss Greater savings with higher baseline BMI 5% weight loss 10% weight loss 15% weight loss 20% weight loss Baseline BMI

19 Change in expenditure ($) over one year Medical costs decrease with weight loss Greater savings with higher baseline BMI 5% weight loss 10% weight loss 15% weight loss 20% weight loss Baseline BMI (kg/m 2 ) Estimated costs are based on 2010 data for non-institutionalised US adults aged 18 years. Figure drawn based on data available in the reference Adapted from Cawley et al. PharmacoEconomics 2015;33:

20 Who should have bariatric surgery?

21 Focusing on responders

22 Leptin treatment for congenital leptin deficiency Farooqi et al. N Engl J Med 1999; 341(12): yr old weighing 42 kg 7 yr old weighing 32 kg

Outcomes associated with 10% WL: Look AHEAD post hoc analysis Responder: lost 10% BW in year 1 Primary outcome - 21% lower CV death, non-fatal acute MI, non-fatal stroke, or hospital admission for

23 Outcomes associated with 10% WL: Look AHEAD post hoc analysis Responder: lost 10% BW in year 1 Primary outcome - 21% lower CV death, non-fatal acute MI, non-fatal stroke, or hospital admission for angina Favours responders Favours control p=0.034* Secondary outcome - 24% lower As above plus CABG, carotid endarterectomy, PCI, hospitalisation for CHF, peripheral vascular disease, or total mortality p=0.003* Overall study population (N=4,834) Combined groups ILI and DSE; control (weight gain/stable) HR *p-value refers to pairwise comparison with referent group (gain or stable weight in weight change analyses) Adjusted for sex, age, baseline weight (from weight change models), history of CVD, insulin use, diabetes duration, smoking status, LDL cholesterol, SBP and DBP BW, body weight; CABG, coronary artery bypass grafting; CHF, coronary heart failure; CVD, cardiovascular disease; DSE, diabetes support and education; HR, hazard ratio; ILI, intensive lifestyle intervention; PCI, percutaneous coronary intervention; WL, weight loss. Look AHEAD Research Group. Lancet Diabetes Endocrinol 2016;4:

Individuals (%) Distribution of weight loss with liraglutide 3.0 mg SCALE Obesity and Prediabetes: Week 56 Mean baseline weight: 106.2 kg 92% Liraglutide 3.

24 Individuals (%) Distribution of weight loss with liraglutide 3.0 mg SCALE Obesity and Prediabetes: Week 56 Mean baseline weight: kg 92% Liraglutide 3.0 mg Placebo % 65% 60 33% 14% 27% 11% 4% Weight change (%) The cumulative distribution of changes in body weight (%) after 56 weeks of treatment is shown Pi-Sunyer et al. N Engl J Med 2015;373:11 22.

25 Individuals (%) COR-Diabetes Categorical weight loss at week 56 with Mysimba/Contrave vs placebo Mean baseline weight: 106 kg 100 Contrave 2 tab bd Placebo p< p< % >10% Weight loss 8.0 Proportions of participants are estimated proportions, missing observations were imputed using a regression method, and risk differences are estimates from a regression model using an identity link, except where specified otherwise. Hollander P et al. Diabetes Care. 2013;36(12):

26 Distribution of weight loss after bariatric surgery (n=877) (n=513) RYGBP, Roux-En Y gastric bypass; SG, sleeve gastrectomy. Manning et al. Surg Endosc 2015;29:

27 How and when should we treat our patients?

Using the EOSS to deliver appropriate interventions Stage 2 Stage 1 co-morbidity moderate Stage 3 moderate Stage 0 Obesity Stage 4 Adapted from: Sharma and Kushner.

28 Using the EOSS to deliver appropriate interventions Stage 2 Stage 1 co-morbidity moderate Stage 3 moderate Stage 0 Obesity Stage 4 Adapted from: Sharma and Kushner. Int J Obes (Lond) 2009;33: and NICE. Weight management: lifestyle services for overweight or obese adults (PH53) 2014 [Available from: (Last accessed: Jan 2018)].

29 Using the EOSS to predict mortality 0: No apparent Risk Factors 1: Subclinical risk factors eg: borderline hypertension impaired fasting glucose mild physical symptoms 2:Presence of established obesity-related chronic disease e.g.: Hypertension Type 2 diabetes Moderate limitations of ADL 3: Established end-organ damage 4: Severe (potentially end-stage) disabilities EOSS, Edmonton obesity staging system.; mo, months Padwal et al. CMAJ 2011;183:E

30 The challenge of personalised medicine Weight management Clinic kg Treatment Stop coming Morbid obesity Obese morbidity P1 Weight sensitive? 10 domain assessment P2 P3 Weight resistant? Non-weight related? Therapy specific? Multi-modal Strategy

31 The tools of the future? Early Stage PYY Ligand JNJ-9321 GT-002 NN9747 MC4R Agonist PL-8905 MIC-1 GDF-15 NMUR2-agonist NMU-7005 GLP-1/GIP dual agonist ZP-DI-70 GLP-1/GIP TAK-94 Phase 1 Phase 2a Phase 2b Phase 3 GLP-1/Glucagon dual agonist MOD-6031 JNJ-5111 BI NN9030 NN9277 Amylin BI NN9838 Amylin/Calcitonin Dual agonist KBP-089 GIP/GLP-1/Glucagon triple agonist NN9423 Anti-FGFR1/KLB BFKB8488A NGM313 NPY5 Antagonist S GLP-1R agonist Efpeglenatide Ghrelin analog AZP-531 GOAT inhibitor GLW-01 SGLT1/2i LIK066 GLP-1/Glucagon dual agonist MEDI0382 Amylin/Calcitonin Dual agonist KBP-042 MetAP2 inhibitor KBP-089 Activin T2R mab Bimagrumab SGLT2/Phen Cana/phen MA0I Tesofensine GLP-1R/GCG SAR GLP-1R agonist Semaglutide Regulatory/ approved GLP-1R agonist Liraglutide CNS Combos Qsymia Contrave 5HT2cR agonist lorcaserin Novartis Genentech Takeda Arena Zealand Astra Zeneca Opko Biologics Shionogi Rhythm Lilly/Nordic JandJ Alizé Palatin Novo Nordisk BI/Zealand Sanioni/Medics Zafgen Scohia Sanofi

34 Overall treatment strategy Typical algorithm (progress through algorithm as clinically required) Combination therapies Weight loss surgery Add medications Professionally-directed lifestyle change Self-directed lifestyle change

36 Acknowledgements Funding: Science Foundation Ireland, Vetenskapsrådet, Wellcome Trust, Moulton Foundation, NIHR, EKF Diagnostics, AnaBio Metabolic Medicine Group University College Dublin Neil Docherty, Loai Shakerdi, Meera Nair, Natasha Kapoor, Werd Al-Najim University College Dublin Catherine Godson, Donal O Shea, Ronan O Connell, Ronan Cahill, Donal Brennan Trinity College Dublin John Reynolds, Conor Murphy, Jessie Elliott University of Gothenburg Torsten Olbers, Lars Fandriks, Almantas Maleckas, Lena Carlsson, Per-Arne Svensson Imperial College London Steve Bloom, Mohammad Ghatei, Alex Miras, Andrew Frankel, Julian Teare King s College London Francesco Rubino, Stephanie Amiel, Simon Aylwin, Ameet Patel, Cynthia Borg, Royce Vincent University of Zurich Thomas Lutz, Marco Bueter Musgrove Hospital, Taunton Richard Welbourn, Rob Andrews, Dimitri Pournaras, Alan Osborn Florida State University Alan Spector Oswaldo Hospital, Sao Paulo Ricardo Cohen Catholic University of Chile Camilo Boza Saudi Arabia Al-Qahtani, Ghalia Abdeen

(Who and) When should patients with obesity and impaired glucose regulation undergo metabolic surgery?

(Who and) When should patients with obesity and impaired glucose regulation undergo metabolic surgery? Alex Miras Senior Clinical Lecturer in Endocrinology Disclosures Fractyl Novo Nordisk Astra Zeneka