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  • Figure X. A. Profiles of indicated amino acids in non-diabetic lean (n=4), laproscopic gastric banding (LAGB, n=5) or Roux-en-Y gastric bypass (GABP, n=7) following ingestion of 180 ml of Boost. Plots show mean +/- S.D. (shaded areas). Note, lean is duplicated for comparison purposes. B. Relationship between baseline amino acid levels, amino acid excursions and area under the curve (AUC) following Boost administration.
  • ncibi-rcmi-2010-workshop-burant.pptx - PowerPoint Presentation

    1. 1. Metabolomics and the Molecular Phenotype of Obesity<br />Burant Lab<br />Mary Treutelaar<br />JinghuaXu<br />Sydney Bridges<br />Joe Dosch<br />Cristina Lara-Castro<br />Julian Munoz<br />Erin Shellman<br />Katie Overmyer<br />Charles Evans<br />Arun Das<br />Jane Cao<br />Angela Subauste<br />TanuSoni<br />Internal Medicine<br />Sub Pennathur<br />Jaimen Byun<br />NCIBI/CCMB<br />Alla Karnovsky<br />Maureen Sartor<br />H V Jagadish<br />Terry Weymouth<br />Tim Hull<br />Glenn Tarcea<br />Jing Gao<br />Brian Athey<br />Jim Cavalcoli<br />Chemistry<br />Bob Kennedy<br />Matt Lorenz<br />ChunhaiRuan<br />MCRU<br />Theresa Han-Markey<br />Bionutrition Support<br />Metabolic Kitchen<br />Funding<br />DK072380  <br />DK077200<br />DK089503 <br />Robert C. and Veronica Atkins Foundation <br />Endowment for the Biological Sciences <br />Washington University<br />Sam Klein<br />University of Wisconsin<br />Alan Attie<br />Columbia University<br />Sharon Wardlaw<br />Judith Korner<br />IWMC<br />Amy Rothberg<br />MitaliKapila<br />ChritineFowler<br />Andrew Miller<br />1<br />
    2. 2. Predictive Model<br />of the System<br />Clinical and Molecular Phenotyping<br />Biological Data<br />Transcriptomics<br />Proteomics<br />Metabolomics<br />2<br />
    3. 3. Systems Roles<br />Material<br />Information<br />DNA<br />The ultimate potential of a cell<br />RNA<br />The current direction of a cell<br />The functional capabilities of a cell<br />Proteins<br />Metabolites<br />The limiting currency of a cell<br />3<br />
    4. 4. The ‘omic’s<br />Genome<br />~30,000 genes<br />~100,000 transcripts<br />Transcriptome<br />~1,000,000 protein forms?<br />Proteome<br />~2000 to 5,000 metabolites<br />Metabolome<br />4<br />
    5. 5. What is a Metabolite?<br />Any organic molecule detectable in the body with a MW < ~2000 Da<br />Includes peptides, oligonucleotides, sugars, nucleosides, organic acids, ketones, aldehydes, amines, amino acids, lipids, steroids, alkaloids and drugs (xenobiotics)<br />Includes human & microbial products<br />Concentration > 1nM*<br />5<br />
    6. 6. 50<br />45<br />40<br />35<br />30<br />25<br />20<br />15<br />10<br />5<br />0<br />0<br />200<br />400<br />600<br />800<br />1000<br />1200<br />1400<br />1600<br />1800<br />Mass Distribution of Compounds in the Human Metabolome<br /><ul><li>Metabolome
    7. 7. natively biosynthesized
    8. 8. monomeric
    9. 9. Complex metabolites
    10. 10. Xenobiome</li></ul>Number of cmpds per 20 daltons <br />Mass <br />6<br />
    11. 11. Why Are Metabolites Relevant?<br /><ul><li>Generate metabolic “signatures”
    12. 12. Monitor/measure metabolite flux
    13. 13. Monitor enzyme/pathway kinetics
    14. 14. Assess/identify phenotypes
    15. 15. Monitor gene/environment interactions
    16. 16. Track effects from toxins/drugs/surgery
    17. 17. Monitor consequences from gene KOs
    18. 18. Identify functions of unknown genes</li></ul>Metabolites are the Canaries of the Genome<br />7<br />
    19. 19. Why Are Metabolites Relevant?<br />Generate metabolic “signatures” for disease states or host responses<br />Obtain a more “holistic” view of metabolism (and treatment)<br />Accelerate assessment & diagnosis<br />More rapidly and accurately (and cheaply) assess/identify disease phenotypes<br />Monitor gene/environment interactions<br />Rapidly track effects from drugs/surgery<br />8<br />
    20. 20. 1<br />2<br />3<br />4<br />5<br />6<br />7<br />ppm<br />TMAO<br />creatinine<br />hippurate<br />allantoin<br />creatinine<br />citrate<br />taurine<br />urea<br />hippurate<br />2-oxoglutarate<br />water<br />succinate<br />fumarate<br />1<br />2<br />3<br />4<br />5<br />6<br />7<br />ppm<br />2 Routes to Metabolomics<br />Quantitative<br />Methods<br />Chemometric (Pattern)<br />Methods<br />25<br />20<br />15<br />Condition 1<br />10<br />5<br />PC2<br />0<br />-5<br />Control<br />-10<br />-15<br />Condition 2<br />-20<br />-25<br />9<br />-30<br />-20<br />-10<br />0<br />10<br />PC1<br />
    21. 21. chromatogram<br />mass spectrum<br />mass spectrum<br />The Technology of Metabolomics<br />10<br />
    22. 22. 11<br />Separations Based Metabolomics Platforms<br /><ul><li>ALL ESI-MS Methods Are Subject to Ion Suppression
    23. 23. Response Factors of Analytes are Not Equal</li></ul> Adapted From: Want, E. J.; Cravatt, B. F.; Siuzdak, G., ChemBioChem2005, 6, 1941 – 1951<br />Adapted From: Villas-Boas, S. G.; Mas, S.; Akesson, M.; Smedsgaard, J.; Nielsen, J., Mass Spectrom Rev 2005, 24, (5), 613-46 <br />
    24. 24. Moderately increased<br />Slightly increased<br />Greatly increased<br />(relative risk 2-3)<br />(relative risk 1-2)<br />(relative risk >>3)<br />Relative risk of health problems associated with obesity<br />Cancer (breast cancer in <br />Coronary heart disease<br />Diabetes <br />postmenopausal women, <br />Osteoarthritis (knees)<br />Gall bladder disease<br />endometrial cancer, colon <br />cancer)<br />Hyperuricemia and <br />Hypertension<br />gout<br />Reproductive hormone <br />Dyslipidemia<br />abnormalities<br />Insulin resistance<br />Polycystic ovary <br />Breathlessness<br />syndrome<br />Sleep apnea<br />Impaired fertility<br />Low back pain<br />Increased anesthetic risk<br />Fetal defects arising <br />from maternal obesity <br />12<br />
    25. 25. Excess U.S. Medical Costs Related to Abnormal Body Weight<br />Int J Obesity 2005;29:334-339<br />13<br />
    26. 26. Behavior<br />Genetics<br />Environment<br />Causes of Obesity<br />14<br />
    27. 27. Environmental effects…<br />Keith SW, et al. Int J Obes. 2006;30:1585-1594.<br />15<br />
    28. 28. DBP: Metabolomics and Obesity<br />Investigational Weight Management Clinic<br />Nutrition Obesity Research Center Demonstration Unit<br /><ul><li>Primary goal: Develop tools for multiscalar integration of clinical, behavioral and molecular phenotyping data in a clinical setting.
    29. 29. Insurance-supported clinical care for 400 obese patient
    30. 30. Undertaking a variety of studies related to nutrition and obesity
    31. 31. Michigan Nutrition Obesity Center Demonstration Unit project: Broad phenotypingat baseline, 3 months, 24 months for 400 obese and baseline studies in100 lean (BMI < 27).</li></ul>16<br />
    32. 32. Phenotypic response to diets<br />Lipid Level (mg/dl)<br />17<br />
    33. 33. Lipomic assessment of plasma<br />Principal Component Analysis<br />(% of total lipid in fraction)<br /><ul><li>18:2 and 14:0 predicts PUFA at day 2, 7, 21
    34. 34. 14:1 and 16:1 in TG and PL predicts day 2, 7, 21 CHO
    35. 35. 18:2 and 16:1 in CE predict day 21 CHO</li></ul>Can macronutrient consumption be detected in fatty acid profiles?<br />18<br />
    36. 36. Palmitoleate, Glucose and Insulin Sensitivity<br />Palmitoleate<br />16:1 (%)<br />Glucose<br />16:1 (%)<br />HOMA<br />19<br />
    37. 37. Phenotyping of Patients<br />Phenotyping: Investigational Weight Management Clinic (Rothberg) <br />and Analysis Laboratory for Physical Activity and Exercise Intervention Research (Gordon) <br />MMOC Human Phenotyping Core (Horowitz)<br /> MMOC Molecular Phenotyping Core (Burant) <br /> NCIBI/CCMB (Athey, Cavalcoli)<br /><ul><li>Anthropometric tests. Height, weight, blood pressure, heart rate, temperature, skin fold thickness, waist-to-hip ratio, skin fold thickness. Dual Energy X-Ray Absorptiometery (DEXA, new).
    38. 38. Metabolic Assessment. VO2peak, resting metabolic rate (RMR) and R/Q measurement. Oral glucose tolerance tests (for those without a diagnosis of diabetes), Total cholesterol, LDL, HDL, triglycerides, free fatty acid, insulin (at 0 and 30 and 120 minutes of oGTT), leptin, adiponectin, C-Reactive Protein.
    39. 39. Peripheral Blood Metabolomic Assessment (including lipomics). The pattern of metabolite levels will be determined, including fatty acid profiles of lipid subclasses in EDTA collected plasma
    40. 40. Peripheral Blood Transcriptomic Assessment. Fasting blood collected for RNA expression will be collected in PaxGene tube
    41. 41. Genomic Assessment. DNA will be isolated from peripheral blood for assessment of DNA polymorphisms related to obesity and ability to lose weight (Boehnke, not funded).
    42. 42. Muscle and adipose tissue biopsy metabolite and transcript analysis. Biopsies will be performed on the vastuslateralis muscle and anterior abdominal fat.
    43. 43. Behavioral assessment. 4-Day Food Intake Record. A Depression inventory ( Beck Depression (BD-II) 21 item questionnaire or Zung Self-Rating Questionnaire). </li></ul>20<br />
    44. 44. Pre-operative Medications Post-operative Medications<br />Gastric Bypass and Gastric Banding<br />21<br />
    45. 45. Weight Maintenance after Bariatric Surgery<br />N Engl J Med. 2004;351:26<br />22<br />
    46. 46. Gastric Bypass and Gastric Banding<br />Early Clinical Effects<br />Int J Obes (Lond). 34:462-471, 2010<br />23<br />
    47. 47. RnY/GB<br />Before Sx<br />RnY/GB<br />After Sx<br />Metabolite<br />Differentiating Roux-en-Y and Gastric Banding-30 min of MMTT<br />Administer 250 cc Ensure<br />+ 650 mg acetaminophen<br />60<br />0<br />15<br />30<br />90<br />120<br />150<br />180<br />24<br />
    48. 48. Potential effects of increased dietary protein to enhance weight loss<br />Amino Acid Effects<br /><ul><li> Postprandial meal-induced visceral signals
    49. 49. Release of PYY and other enteric hormones
    50. 50. Vagal nerve stimulation
    51. 51. Direct action of amino acids in the brain</li></ul>Tome et al. Am J Clin Nutr 2009;90(suppl):838S–43<br />25<br />
    52. 52. Mixed Meal Tolerance Test:<br />Pre and Post Weight Loss<br />Leucine (mM)<br />Obese<br />Post VLCD<br />Obese<br />Pre VLCD<br />Lean<br />Obese<br />PostSx<br />Obese<br />PreSx<br />Each represents the time course of the indicated metabolite/hormone following administration of 250 ml of Ensure as a mixed meal tolerance test (0,30,60,90,150 minutes)<br />26<br />
    53. 53. Mixed Meal Tolerance Test:<br />Pre and Post Weight Loss<br />27<br />
    54. 54. Mixed Meal Tolerance Test: Amino Acid Dynamics<br />28<br />
    55. 55. Change in Amino Acid dynamics following<br />Roux-en-Y gastric bypass<br />AUC<br />Peak<br />29<br />
    56. 56. Cerebral Spinal Fluid Amino Acids<br />MEAL<br />SNACK<br />Bateman et al. Nat. Med. 12:856-861, 2006<br />Clock Time<br />30<br />
    57. 57. Can the CSF protect its amino acid levels?<br /><ul><li>Assess Plasma and CSF Amino Acid and Lipid Profiles at baseline and following 10% weight loss.
    58. 58. Defined Diet for 72 hrs. prior to sampling.</li></ul>2.5<br />26.6<br />Baseline<br />BMI<br />30.8<br />2.0<br />D<br />42.7<br />/Plasma <br />57.3<br />1.5<br />D<br />1.0<br />Ratio CSF <br />0.5<br />0.0<br />Valine<br />Leucine<br />Threonine<br />Isoleucine<br />Amino Acid<br />Fats<br />Proline<br />31<br />
    59. 59. Obese individuals have elevated plasma levels of amino acids (and other nutrients)<br />Hypothesis<br />1.The brain requires a certain amount of nutrients to feel ‘sated’. <br />2. Amino acids and/or lipids may provide part of the signal. <br />3. People eat until the nutrient level in the brain is adequate.<br />4. Overweight and obese individuals need to eat more to get to the ‘ok’ level in the brain…thus have higher nutrient levels in the blood.<br />5. Weight loss decreases brain levels of nutrients, increasing appetite<br />Amino Acid<br />Fats<br />Amino Acid<br />Fats<br />32<br />
    60. 60. Summary<br />Metabolomicmeasurements can provide clues to the dynamic relationship between genes and environment in people<br />The metabolome is complex and changes appear coordinated<br />Statistical and visualization methods can provide otherwise hidden relationships between phenotypic characteristics<br />33<br />

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