Effects of Diet and Genetic Factors on Gut Dysbiosis in IBS Chung Owyang, MD Professor of Medicine Department of Gastroenterology University of Michigan Li-ping Duan*, MD Professor of Medicine Department of Gastroenterology Peking University Third Hospital
Gut Microbita---an important Organ Gut Microbita Bacteria, viruses, fungi About 3 pounds weight About 10 times as many cells as human About 100 times as many genes as humans Many diseases are associated with gut dysbiosis Metabolic diseases Allergies Autoimmune diseases IBD,IBS Tumors Mental disorders 2
BACKGROUND Gut microbiota altered in IBS patients IBS differed from controls with the ratio of Firmicutes/Bacteroidetes Diet may significantly affect gut microbiota Studies are carried in western countries mainly Genus Phylum Health IBS GASTROENTEROLOGY 2011;141:1792 1801; Gut 2012;61:997-1006 Clin Gastroenterol Hepatol Liu YX, Duan LP, et al., 2016;14(11):1602-1611.
AIM To examine the impacts of diet and racial factors (parallel studies conducted in Beijing and Ann Arbor) on the development of gut dysbiosis To identify differences in gut microbiota between healthy and 2 groups of IBS subjects on either a vegetarian or red meat diet To demonstrate that gut microbial alterations are responsible for IBS symptoms and increasing plasma cytokine ratios as well as gut permeability index
PROGRAM PLAN 30 health subjects 100 IBS patients 1.No GI symptoms 2. No antibiotic in one month 3. No chronic diseases 4. No SIBO 1. No organic GI conditions 2. No antibiotic in one month 3. Rome III subgrouping criteria 4. No SIBO 15 vegetarian & 15 meat eaters 50 vegetarian & 50 meat eaters GI and psychological questionnaire: The Hospital Anxiety and Depression (HAD) Scale Gastrointestinal Symptom Rating Scale-IBS (GSRS-IBS) Bristol Stool Form Scale (BSF) Short-Form 36 (SF-36) Diet questionnaire Physiological testing: Intestinal membrane permeability testing (lactulose/mannitol) Visceral pain testing PBMC cytokine levels Both at Ann Arbor and Peking 16s rdna sequencing and analysis: DNA Isolation MiSeq Illumina sequencing OTUS, Phylotype Assignment, Diversity Measurements
PROGESS IRB approval on Mar. 19, 2015 in Beijing UMHS-PUHSC Joint Institute for Translational and Clinical Research Fifth Sixth and Seventh Annual Joint Institute Two PUHSC PhD students received extensive training in microbome research at UMMS mentored by Dr. Owyang
Study Calendar and Progress-IBS PKUSC/UM Evaluations/Tests Visit 1 Visit 2 Interim Visit 3 Off Study ROME III Criteria 135/380 Medication review Assess Eligibility 98/360 Sign Informed Consent CRF & Surveys 61/46 Blood Collection Diet Recalls Stool Collection 59/26 6 hour urine collection Visceral Pain Testing 45/17 Completed the study 58/28 7
Study Calendar and Progress -Health Control PKUSC/UM Evaluations/Tests Visit 1 Visit 2 Interim Visit 3 Off Study GI symptoms screening Medication review 74/153 Assess Eligibility 50/122 Sign Informed Consent CRF & Surveys Blood Collection 38/57 Diet Recalls Stool Collection 38/44 6 hour urine collection Visceral Pain Testing 36/44
RESULTS PUHSC/UM Subject Type Demographic Comparison DEMOGRAPHIC HC (N = 30) IBS (N = 58) AGE 34.1±12.2 yrs. 33.7±10.5 yrs. NS SEX Female: 36.7% Male: 63.3% Female:25.9% Male: 74.1% NS RACE MONGOLOID=100% MONGOLOID=100% DIET DEMOGRAPHIC HIGH FAT : LOW FAT DIET = 33.3% : 66.7% MEAT = 100% HC (N = 26) HIGH FAT : LOW FAT DIET = 17.2% : 82.8% MEAT = 100% IBS (N = 19) AGE 48.4 ± 14.8 yrs. 46.3 ± 15.6 yrs. NS SEX Female: 73.0% Male: 27.0% Female: 94.7% Male: 5.3% NS RACE CAUCASIAN = 84.6% AFR.-AMERI. = 15.4% DIET MEAT = 50.0% VEGE. = 50.0% CAUCASIAN = 94.7% AFR.-AMERI. = 5.3% MEAT = 89.5% VEGE. = 10.5% P NS P NS NS?
RESULTS PUHSC/UM Gender Demographic Comparison Beijing HC IBS Female Male Ann Arbor
RESULTS PUHSC/UM Diet Demographic Comparison 90 80 70 60 50 HFD LFD 100 90 80 70 60 50 HFD LFD 40 40 30 30 20 20 10 0 IBS HC 10 0 IBS HC Beijing Ann Arbor
RESULTS PUHSC/UM Barostat Rectal Sensation RECTAL SENSATION HEALTHY CONTROL (N = 29) IBS (N = 44) P-VALUE FIRST SENSATION FIRST URGE-TO- DEFECATE STRONG URGE-TO- DEFECATE MAXIMUM TOLERATED MEAN =12.1 MMHG/ SD = 4.3MMHG MEAN =22.0 MMHG/ SD = 6.MMHG MEAN = 31.8MMHG/ SD = 8.5MMHG MEAN = 41.8MMHG/ SD = 9.5MMHG MEAN = 8.6MMHG/ SD = 3.1 MMHG 0.000 MEAN = 16.8MMHG/ SD = 4.8MMHG 0.001 MEAN = 25.0MMHG/ SD = 7.0MMHG 0.005 MEAN = 34.6MMHG/ SD = 9.1MMHG 0.047 RECTAL SENSATION HEALTHY CONTROL (N = 26) IBS (N = 19) P-VALUE 1 = In itia l fe e lin g FIRST SENSATION (MMHG) MEAN = 15.5 MMHG/ SD = 6.6 MMHG MEAN = 11.1/ SD = 6.0 MMHG 0.14 50 2= Initial feeling to defecate 3= U rge to defecate 4= M axim um tolerance HC FIRST URGE-TO- DEFECATE MMHG STRONG URGE-TO- DEFECATE MMHG MEAN = 21.5 MMHG/ SD = 7.1 MMHG MEAN = 29.3 MMHG/ SD = 9.9 MMHG MEAN = 18.9/ SD =7.2 MMHG MEAN = 27.1 MMHG/ SD = 10.9 MMHG 0.12 0.31 m m Hg 40 30 20 10 IB S MAXIMUM TOLERATED MMHG MEAN = 36.1 MMHG/ SD = 10.8 MMHG MEAN = 39.0 MMHG/ SD = 12.7 MMHG 0.21 1 2 3 4 0
FIRST SENSATION DIET RESULTS PUHSC LINEAR REGRESSION MODEL OF BAROSTAT PREDICTOR VARIBALE Β 95% CI LOWER 95% CI UPPER P-VALUE STRONG URGE-TO-DEFECATE DIET PREDICTOR VARIBALE Β 95% CI LOWER 95% CI UPPER P-VALUE HIGH FAT DIEAT -0.095-2.271 2.082 0.931 LOW FAT DIET 0 FIRST URGE-TO-DEFECATE DIET PREDICTOR VARIBALE Β 95% CI LOWER 95% CI UPPER P-VALUE HIGH FAT DIEAT -1.505-4.404 1.393 0.303 LOW FAT DIEAT 0 HIGH FAT DIEAT -1.304-5.580 2.971 0.544 LOW FAT DIEAT 0 MAXIMUM TOLERATED DIET PREDICTOR VARIBALE Β 95% CI LOWER 95% CI UPPER P-VALUE HIGH FAT DIEAT -0.337-5.322 4.647 0.893 LOW FAT DIEAT 0 Even though a non-significant difference, the subjects reporting with the identification of a high-fat diet showed trend of more hypersensitive compared to the subjects reporting with the identification of a low-fat diet in Beijing.
RESULTS UM LINEAR REGRESSION MODEL OF BAROSTAT FIRST SENSATION PREDICTOR VARIBALE Β 95% CI LOWER 95% CI UPPER P-VALUE DIET MEAT -.860-6.04 4.32 0.745 VEGETARIAN 0 FIRST URGE-TO-DEFECATE PREDICTOR VARIBALE Β 95% CI LOWER DIET 95% CI UPPER P-VALUE MEAT -.203-5.68 5.27 0.942 VEGETARIAN 0 Even though a non-significant difference, the subjects reporting with the identification of a meat diet were more hypersensitive related to First Sensation (mmhg) and First Urge-to-Defecate (mmhg) compared to the subjects reporting with the identification of a vegetarian diet in Ann Arbor
RESULTS PUHSC Permeability HC IBS P Lactulose 6h(ug/ml) 2.645(0.975,2.762) 4.805(1.325,5.405) 0.062 Mannitol 6h(ug/ml) 53.713(24.200,59.125) 66.528(27.475,78.300) 0.289 Lactulose/Mannitol 6h 0.045(0.035,0.056) 0.078(0.057,0.098) 0.021
RESULTS PUHSC IL-12 and IL-10 PBMC Cytokine Levels Beijing Ann Arbor IL-12(p40) in PBMC supernatant ( pg/ml) 6 5 4 3 2 1 0 Control (JC) p=0.04 IBS (J) IL-10 in PBMC supernatant (pg/ml) 8 7 6 5 4 3 2 1 0 Healthy control p=0.011 IBS
RESULTS PUHSC Inflammation correlates with visceral hypersensitivity R 2 =0.511,p<0.05 R 2 =0.43,p<0.05 Serum IL10/12 positively correlated with mmhg urge to defecation (suggesting lower inflammatory tone is correlated with less visceral hypersensitivity)
SUMMARY The IBS group has a significantly more female compared to the HC group in the Michigan; while more male subjects in Beijing, raising the possibility that different pathophysiology between IBS patients from the two countries. There was significantly higher visceral hypersensitivity in IBS group compared to HC in Beijing patient but no significant difference at UM. There is increased inflammatory tone in IBS patients both in Beijing and at UM and correlates with degree of visceral hypersensitivity. We observed few vegetarians among IBS patients at UM suggesting vegetarian diet may be a protective factor in IBS. In Beijing, IBS patients consume higher carbohydrate and protein diet compared to HC.
IMPACT First clinical IBS study with well-phenotyped cohorts (distinct racial populations and dietary habits) to determine the effects of diet and racial factors on gut dysbiosis in IBS Provide unique and novel information to develop hypothesisdriven studies, to compete for future external fundings including NSFC in China and NIH in USA
FUTURE PLAN Completing enrollment (15 more vegetarian IBS subjects and sample collections) Complete analysis the gut microbiome of the stool samples (16s RNA sequencing and metabolomics) Perform detail dietary analysis to assess correlations between dietary composition, visceral hypersensitivity and permeability as well as inflammatory tone. High quality publications
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