Based on the Gut Microbiome A journey to better health with - PDF document

6/12/2019 Personalized Dietary Treatment Based on the Gut Microbiome A journey to better health with Microbiome Solutions. Conflict of Interest Disclosure Statement Susan Yake is a paid consultant for DayTwo 1

6/12/2019 Objectives Objective 1: Discuss the degree of variation in personal glycemic response to meals among different individuals Describe the role the gut microbiome plays in the development and management of diabetes and Objective 2: other diseases Explain that machine learning algorithms can be used to personalize diets to normalize blood glucose Objective 3: levels in people with diabetes and pre-diabetes “If you think you are too small to make a difference, try sleeping in a closed room with a mosquito .” (African Proverb) 2

6/12/2019 Andromeda Galaxy Compared to Microbes in the Gut There are 100 Billion Stars in the Andromeda Galaxy There are 390 x as many microbes in the human body - 39 Trillion This is 1.3 x more than the 30 Trillion human cells in the human body It is estimated that 3 to 4 lbs . of our weight is from bacteria Sender R, Fuchs S, Milo R. Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans. Cell 2016;164:337 – 40. pmid:26824647 https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002533 Intervent ervention ion Study dy Muesli Eggs gs & Bread Sushi Pita & Hummus mmus Can you guess ess the good d diet et? Marzipan Edama mame me Corn & Nuts ts Noodles Coffee & Chocolate te Ice Cream 3

6/12/2019 Intervent ervention ion Study dy Muesli Eggs gs & Bread Sushi Pita & Hummus mmus Can you guess ess the good d diet et? Marzipan Edama mame me Corn & Nuts ts Noodles Coffee & Chocolate te Ice Cream Initial tial Intervention ervention Result ults 200 200 150 150 (mg/dl) 100 100 50 50 Spiking Diet Non-Spiking Diet 4

6/12/2019 Weizmann Institute Research Eran Elinav, M.D. Ph.D Prof. Eran Segal, Ph.D What is the best diet for humans? An apple a day keeps the doctor away? 5

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6/12/2019 Post-Prandial Glucose Response as a Measure of Healthy Nutrition The Personalized Nutrition Project: Clinical and Microbiome Data Collected 7

6/12/2019 People e Have e a Widel ely y Diff fferent erent Glucose se Respo pons nse e to the Same Food Carl Carl Nancy Phil Phil Jill 160 160 160 160 Glucose levels (mg/dl) 120 120 120 120 80 80 80 80 40 40 40 40 0 1 2 0 1 2 0 1 2 0 1 2 Time (hours) Time (hours) Time (hours) Time (hours) 8

6/12/2019 People e Have e a Widel ely y Diff fferent erent Glucose se Respo pons nse e to the Same Food Population Responses to Opposite Responses to Standardized Meals Bananas and Cookies 115 Participant nt 445 8 22 22 29 29 33 33 0.03 100 85 Participants (density) 0.02 Blood glucose (mg/dl) 0 30 60 90 120 Banana Cookie 0.01 115 Participant nt 644 100 0.00 0 20 30 40 50 60 70 80 10 85 Standardized meal PPGR (iAUC, mg/dl ∙ h) 0 30 60 90 120 Glucose Bread Bread & butter Fructose Time (Min) Zeevi et al., Cell, in press Thera rape peutic utic Potentia ential l of The Microbio obiome me Microbiome was important in explaining the difference in meal glucose responses Glucose responses were modifiable by changing what was eaten This lead to exploring if the microbiome could accurately predict glucose response for a food or meal 9

6/12/2019 How do we use trends to make predictions? Machin ine e Learn rnin ing Proces ess Inputs AI & ML Output Measure personal features Design personalized diet to Predict personal lower glycemic responses glycemic responses Microbiome Blood tests and CGMS Questionnaires / Lifestyles Anthropometrics Personalized Food diary Nutrition Predictor 10

6/12/2019 David Zeevi, Tal Korem, Niv Zmora, David Israeli, Daphna Rothschild, Adina Weinberger, Orly Ben-Yacov, Dar Lador, Tali Avnit-Sagi, Maya Lotan-Pompan, Jotham Suez, Jemal Ali Mahdi, Elad Matot, Gal Malka, Noa Kosower, Michal Rein, Gili Zilberman-Schapira, Lenka Dohnalová, Meirav Pevsner-Fischer, Rony Bikovsky, Zamir Halpern, Eran Elinav, Eran Segal Cell Volume 163, Issue 5, Pages 1079-1094 (November 2015) DOI: 10.1016/j.cell.2015.11.001 Dietary interventions targeting post-meal glucose responses induce consistent changes in microbiota • Bifidobacterium adolescentis decreases following the ‘good’ diet week • Low levels associate with greater weight loss (Santacruz et al., 2009) • Roseburia inulinivorans increases following the ‘good’ diet week • Low levels associate with TIIDM (Qin et al., 2012) Zeevi et al., Cell, 2015 11

6/12/2019 Glycem emic ic Index ex vs Glycem emic ic Respo pons nse Glycemic Index is an Average Glycemic Response is Personal Original study was done with 10 people First study has 1000+ individuals Score is 0 to 100 Score is 1 to 9.9 Score of 55 or lower is good Score of 7 or higher is good Score based on single food item Score can be based on single food or a combination of foods Amount of food scored is set Score changes with amount for meal or snack Glycemic response varies by an average of 20 percent Results of score reproducible The American Journal of Clinical Nutrition , Volume 104, Issue 4, 1 October 2016, Pages 1004 – 1013 12

6/12/2019 Mayo Clinic ic Study Different glycemic response from Carbohydrate sensitivity is measured as the Participants after eating a bagel and correlation between carbohydrates (in grams) cream cheese in the meal consumed and the computed postprandial glycemic response Intervent ervention on Impact act on Time-In In- Range….Interim Results Pre-Diabetes RCT in Weizmann 0 -10 Algori rithm hm Diet 60% 60% avg reduction of time spent >140 mg/dl -20 Time >140 (% reduction, CGM-based) -30 Mediter erra ranea ean Diet et 10% % avg reduction of time spent >140 mg/dl -40 -50 -60 *** P<0.0001 -70 0 1 2 3 4 5 6 Months N=93 participants; Based on CGM Data Algorithm Standard of Care 13

6/12/2019 Intervention Impact on HbA1c….Interim Results 3% HbA1c 1c aver erage e reduction of 0.62% 2% in 3 months hs and 0.92% % in 6 months hs 2% 1% Reduction in HbA1C -1% -2% 2% -3% Algorithm orithm diet t reduc duces s averag age e glucos ucose e levels ls *** P<0.0001 Placebo, Metformin, Lifestyle from Diabetes Prevention Program, NEJM 2002 CGM-based HbA1c% estimate from Nathan et al., Diabetes Care 2008 14

6/12/2019 US Studi dies es of the Microbiom biome e Usin ing g Machin hine e Learnin arning Microbiome Test Samples Ready for Full Spectrum Sequencing Major State Shifts in Microbial Ecology Phyla Between Healthy and Three Forms of IBD Average HE Most Most Common Common Microbial Microbial Phyla Phyla Average Average LS Average Colonic Crohn’s Disease Ulcerative Colitis Ileal Crohn’s Disease 15

6/12/2019 The Adult Healthy Gut Microbiome Is Remarkably Stable Over Time • Average of 200 species in the human gut • Between 300 and 1000 species • Most estimate there are 500 Source: Eric Alm, MIT NASA’s Human Research Program DR. MICHAEL SCHMIDT CHRISTOPHER E. MASON, PH.D. The Twins Study was the first study of its kind to compare molecular profiles of identical twin astronauts with one in space and another on Earth The Twins Study is a supplemental study built upon the framework of the One-Year Mission research investigations The Twins Study explores space through you by using omics (DNA, Gene Expression, Microbiome) to look more closely at individual health 16

6/12/2019 Northwest Biologist with a Ph.D. in chemistry Founder of the Institute for Functional Medicine Leads the Personalized LifeStyle Medicine Institute First member of the Board of Trustees of Bastyr University Over 40 years researching nutrition at the cell level and 35 years as a recognized international leader in nutritional medicine • High insulin levels are associated with increased risk of obesity • Hyperinsulinemia increases the risk of weight regain after weight loss • Higher glucose variability and insulin levels can result in increased hunger level making weight loss difficult Karel A. Erion and Barabara E Corkey Hyperinsulinemia: a Cause of Obesity Current Obesity Reports 2017 May 2 6(2): 178-186 Hyperinsulinemia and Obesity https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5487935/ 17

6/12/2019 • 1/2 of pts with HTN are insulin resistant and have hyperinsulinemia • High insulin levels linked to very-low- density lipoprotein synthesis and plasma triglyceride levels. • Atherosclerotic Heart Disease and Rise in CHF is associated with high insulin levels . Garg A. Insulin resistance in the pathogenesis of dyslipidemia. Diabetes Care . 1996;19:387 – 9. Hyperinsulinemia and Heart Disease Hyperinsulinemia Diabetes doubles the risk of developing cancers of the liver, pancreas and endometrium Clear but smaller increase in risk for colon Sources: and breast cancers in International Diabetes Federation. people who have IDF Diabetes Atlas, 8th edition. diabetes International Diabetes Federation, 2017. http://www.diabetesatlas.org 18