Personalized Medicine Tests and Approaches to Select the Appropriate Diet for Optimal Health Michael Nova, M.D. PH.D Chief Innovation Officer Pathway Genomics
TRENDS
Healthcare Costs DRIVEN BY OBESITY 74% of all costs are confined to OBESITY and related condi7ons: The United States spends about $1.8 trillion a year in medical costs associated with chronic diseases such as diabetes, heart disease and cancer, and all three are linked to smoking and OBESITY, POOR DIET, AND LACK OF EXERCISE which are na7on s largest risk factors.
Precision MEDICINE OVERVIEW Precision Medicine Overview Data Genera7on Duffy, Oxford, 2015 Medical History Omics Environmental Factors Connected Health Follow- up & Con7nuous Monitoring Individualized t Pa2ent Data Cloud Predic2ve Modeling Basic & Applied Research PERSONALIZED THERAPY & LIFESTYLE RECOMMENDATIONS
The Human GENOME AND MEDICAL DATA 22,000 GENES 6 BILLION DNA LETTERS 49 CHROMOSOMES $1,000 COST TO SEQUENCE 70 % TEST DATA OF PATIENT S PERMANENT HEALTH RECORD IS MADE UP OF CLINICAL LABORATORY
Human Genomic FEATURES About 40 million common polymorphic sites in the genome of Homo sapiens An individual carries 3-4 million common variant alleles An individual carries 200,000-500,000 rare variants Copy number variants of repeat sequences are common and cover about 10% of the human genome Less than 21,000 protein-coding genes About 1000 mirnas, 9000 other small RNAs and 10,000 long RNAs are transcribed About 1800 transcription factors binding at about 8% of the genome: an average of about 12 per protein-coding gene
Genes AND DIET GENOTYPE NUTRITION INTAKE NUTRIGENOMICS Personalized Nutri2on Dietary Chemicals (Proteins, Lipids, Nutrients, Vitamins) NUTRIGENETICS Risk Factors Modifica2on of Single Nucleo2de Polymorphic Genes GENES
Precision Medicine with NUTRIGENOMICS Weight Management/control Diabetes control CV Disease Management Cogni2on/Elderly GI/Celiac Sports Performance CA
Actionable GENETICS Obesity: Diet plans for weight loss, behavior modifica2on Behavioral gene7cs Diabetes: Sugar/carbohydrate management Megormin metabolism FFA metabolism CV: Diet plans Triglyceride/FFA metabolism Cogni2ve: Micronutrients Omega s, Vit D
NUTRIGENOMICS
NUTRITION & GENETIC METABOLIC PATHWAYS Sample Genes and Func/ons FTO Sa$ety AGRP CHO Metabolism Lep$nR Snacking Behavior IGF Insulin Resistance Nerexin Neuro Obesity GhrelinR Hunger CCK Meal Size APO2A Lipidemia POMC Stress ACE Endurance Vo2 TIR2 Taste (biter, sweat) MTHFR Vitamin B metabolism NPY Feeding S$mula$on DRD2 Addic$ve Behavior FABP2 Fat Metabolism PPARg Fat Storage ADIPOQ Central Obesity SIRT Resveratrol and CR PATHWAY FIT screens all these genes and more
CARDIOMETABOLIC PM Nutrigene2cs and Nutrigenomics of Atherosclerosis Aksam J. Merched Lawrence Chan (2014) Gene2c determinants of cardiometabolic risk: A proposed model for phenotype associa2on and interac2on Piers R. Blacke;, MD. Dharambir K. Sanghera, PhD* (2014) t Polyunsaturated Fafy Acids and Cardiovascular Disease: Implica2ons for Nutrigene2cs Hooman Allayee a,b, Nitzan Roth a, Howard N. Hodis a,c (2015) a Department of Preven9ve Medicine, b Ins9tute for Gene9c Medicine and c Atherosclerosis Research Unit, Keck School of Medicine, University of Southern California, Los Angeles, Calif., USA
Metabolic Syndrome AND GENES HEPATIC FAT STORAGE (NAFLD) HYPOTHAMAMIC (Obesity) MC4R CIRCADIAN (Obesity, diabetes) PER2 MTTP (Diabetes, fas7ng, glucose) PPARG METABOLIC SYNDROME TRAITS INSULIN SECRETION (Type 2 diabetes) LIPID TRANSPORT BLOOD PRESSURE (Atherosclerosis) INSULIN ACTION AND METABOLISM (Hypertension) CETP CASR WFS1
Diet, Genes, and HEALTH OUTCOME LIPIDS DIET INTAKE GENETIC VARIABILITY PHENOTYPE/HEALTH OUTCOME ApoA1 ApoA5 Woman Carriers 75 A/A: é HDL Woman Carriers 75 G/G: ê HDL - 1131 C allele with >6% energy from PUFA: é TG n- 3 PUFA PPARg Subjects with allele 162V with low PUFA é TG ApoE Subjects with APOE4 with >2g fish oil:é LDL- C Genaro, 2014
Nutrigenomic MEDITERRANEAN DIET
GENETIC DIET IMPROVES WEIGHT LOSS Human Clinical Trials FTO Genotype and 2- Year Change in Body Composi<on and Fat Distribu<on in Response to Four Weight- Loss Diets: The POUNDS LOST Trial. Zhang X, Qi Q, Zhang C, Hu FB, Sacks FM, Qi L. Harvard University (2012) Diabetes Nov; 61 (11): 3005-11 Abstract: Recent evidence suggests that the fat mass and obesity- associated gene (FTO) genotype may interact with dietary intakes in rela$on to adiposity. We tested the effect of FTO variant on weight loss in response to 2- year diet interven$ons. FTO rs1558902 was genotyped in 742 obese adults who were randomly assigned to one of four diets differing in the propor$ons of fat, protein, and carbohydrate. Body composi$on and fat distribu$on were measured by dual- energy x- ray absorp$ometry and computed tomography. We found significant modifica$on effects for interven$on varying in dietary protein on 2- year changes in fat- free mass, whole body total percentage of fat mass, total adipose $ssue mass, visceral adipose $ssue mass, and superficial adipose $ssue mass (for all interac$ons, P < 0.05). Carriers of the risk allele had a greater reduc$on in weight, body composi$on, and fat distribu$on in response to a high- protein diet, whereas an opposite gene$c effect was observed on changes in fat distribu$on in response to a low- protein diet. Likewise, significant interac$on paterns also were observed at 6 months. Conclusion: Our data suggest that a high- protein diet may be more beneficial for weight loss and improvement of body composi<on and fat distribu<on in individuals with the risk allele of the FTO variant rs1558902.
Pathway Fit The test analyzes ~100 genetic markers (SNPs, CNV) known to impact metabolism, exercise and energy use within the human body. Weight management Increased mental and physical performance Maximizing energy Metabolic Disease prevention Improved clinical outcomes Better treatment options for weight loss - simple, clear, proven plans Improved performance or overall health of patients Behavioral Modification
Pathway Fit Results and Major Categories
Pathway Fit
Insurance Payments and Contracts on Pathway FIT
VA Medical Center FIT Weight Loss Clinical Trial Change in Weight and Fat Mass in Genomics or Usual Care N=50 per group after 8 weeks Study Lead: Karen L. Herbst Ph.D., M.D. Clinical Professor, UCSD Associate Program Director, Endocrinology Fellowship, UCSD, Director, Weight Control Clinic, VASDHS 3350 La Jolla Village Drive (111G)
Personalized WELLNESS PROGRAM FTO, MC4R, DRD2 genes Steinberg et al, 2015
Weight Loss Partner - Biggest Loser
GENETIC DIET Human Clinical Trials 500 Individuals on a diet iden$fied as appropriate to their genotype lost an average of over 2.5 <mes more weight than those whose diets did not match their genotype Source: Dopler Nelson, M. GeneAc Phenotypes Predict Weight Loss Success: The Right Diet Does MaIer. American Heart AssociaAon 50 th Cardiovascular Disease Epidemiology and PrevenAon Conference, San Francisco, CA, March 3, 2010.
Pathway Fit
Outcomes With NUTRIGENOMICS 33% more weight loss Celiac/Crohn s control Increased cogni2on elderly/children CA preven2on Sugar/BP control Insulin management
I COMBINED A DNA TEST KIT WITH BIG DATA TO PREDICT A PERSON'S FUTURE HEAL TH ISSUES. I.- ---------------- --, THAT DEPRESSING KNOWLEDGE CAUSED i EVERY MEMBER OF THE TEST GROUP TO MAKE i RISKY LIFESTYLE @ CHOICES. NOW HALF OF THEM ARE DEAD. E 8 t i5... --... --... ------ N... ef ca,:, c( 8... en ll') 0 N!:!! r;- AT THE RISK OF BRAGGING., THAT'S EXACTLY WHAT MY MODEL PREDICTED. )