amelia bartholomew
TRANSCRIPT
Maternal obesity, microbiota, Maternal obesity, microbiota, and childhood obesity- is there a and childhood obesity- is there a
correlation?correlation?
Amelia Bartholomew, MD, FACS
Maternal and childhood obesityMaternal and childhood obesity
TopNews.in, Joshi, 03/11/2008
• Maternal obesity is highest amongst blacks and Hispanics
• Carries increased mortality risk to newborn• Childhood obesity also highest amongst
blacks and Hispanics• High likelihood of progression into
adulthood with associated dysregulation of glucose and lipid metabolism
Morrison, et al, Am J Public Health, 1994
Mother and child, Picasso
Maternal link to obesityMaternal link to obesity
• Vertical transmission of obesity to mother-child dyad presumed due to multiple factors – income level – higher dietary fat content– convenience eating– increased sedentary behavior– cultural acceptance of large
body image
Gut microbiota – Gut microbiota – link for obesity in mother and child dyad ??link for obesity in mother and child dyad ??
1. At birth intestines are sterile (Penders, 2006)
2. Rapid rise of bacterial count within hours (Bezirtzoglou, 1997)
3. Bacterial content from vaginal canal (c-section births) populated with sporulate forms of bacteria (e.g. Clostridium), and bacteria from hospital staff, environment
4. Breastfed infants: higher contents of Micrococcus, Lactobacillus, Staphylococcus, Diptheroids, Bifidobacterium
5. By the second year of life, microbiota of breast-fed and bottle fed infants resemble adult microbiota (Bezirtzoglou, 1997)
6. Microbiota can induce presence or absence of obesity (Backhed, 2004;Ley,2005,Turnbaugh, 2006; Cani, 2007, Turnbaugh, 2009
Measuring gut microbiota: Measuring gut microbiota: ribosomal RNA (rRNA)ribosomal RNA (rRNA)
Domain archaea: 3 phylaDomain bacteria: 27 phylahttp://www.bacterio.cict.fr/classifphyla.html
Ribosomes are cellular polymerases translating the genetic code; 50-60% RNA as part of structure
Bacteria and archaea have three rRNA molecules (5S,16S,23S)
In eucarya, 3 main classes include 5S, 17S or 18S, 26S or 28S; some also have 5.8S and/or 2S. rRNA sequencing distinguishes domain specific life.Noller, 1984
Woese, PNAS, 1990
Host microbiota- originsHost microbiota- origins
www.kscience.co.uk/ as/module1/bacteria.htm
• Bacteria Phyla: – Gemmatimonadetes – Lentisphaerae– Nitrospira– Plantomycetes– Proteobacteria– Spirochaetes– Synergistetes– Tenericutes– Thermodesulfobacteria– Thermomicrobia– Thermotogae– Verrucomicrobia– Unclassified bacteria
• Arachae Phyla:– Crenarchaeota
– Euryarchaeota*Euryarchaeota* – Thaumarchaeota
http://www.bacterio.cict.fr/http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=icnb.
• Bacteria Phyla: – Acidobacteria
– Actinobacteria (<1%)*Actinobacteria (<1%)*– Aquificae
– Bacteroidetes (20-40%)*Bacteroidetes (20-40%)*– Caldiserica– Chlamydiae– Chlorobi– Chloroflexi– Chrysiogenetes– Cyanobacteria– Deferribacteres– Deinococcus-Thermus– Dictyoglomi– Fibrobacteres
– Firmicutes (60-80%)*Firmicutes (60-80%)*– Fusobacteria * Obesity microbiota
• Firmicutes– Classes: Bacilli, Clostridia, Ersipelotrichi, Mollicutes,
Thermolithobacteria– >75% Clostridia
• Bacteroidetes– Classes (CFB): Sphingobacteria (order
cytophagaceae), Flavobacteria, Bacteroidia– >88% Bacteroidetes 4b ( not culturable, only
sequenced)
• Sequencing rRNA has yielded >80% newly discovered bacteria in the gut
• Previous data on newborns limited by culture and PCR specific for strain
Microbiota characteristicsMicrobiota characteristics
Eckburg et al, Science, 2005
Microbiota-obesity mechanismMicrobiota-obesity mechanism
Backhed, Science, 2005
• Mutualistic• Host Energy extraction/balance
– Breakdown polysaccharides
– Ferment into free fatty acids
• Germ-free mice – weight and fat content lower
than conventional mice
– even though conventional mice consume less chow per day
– Microbiota of conventional mice led to weight gain in germ-free mice
• Fat storage due to adipocyte hypertrophy; signaled by fatty acid or increased glucose/insulin
Resident microbiota affect host gene Resident microbiota affect host gene responses responses
• Germ-free mice– Addition of microbiota promotes absorption of
monosaccharides from gut lumen and induction of hepatic lipogenesis (Backhed et al, Science, 2005)
– E.Coli strain mpk developed colitis; co-colonization with E. Coli and B. vulgatus did not (Pataky, et al, Exp Clin Endo Diabetes, 2009)
– Genes activated by microbiota include anti-inflammatory genes such as Reg III-gamma, pancreatitis associated protein, adiponectin
Microbiota-obesity mechanismMicrobiota-obesity mechanism
• Ob/ob mice (homozygous mutation in leptin gene) are obese• Frequency of bacteroidetes when compared to lean
littermates was 50% reduced; firmicutes was increased (Ley et al, PNAS, 2005)
• Mice colonized with ob/ob microbiota became obese• In adult human twins, microbiota correlated with degree of
relatedness despite geographical distance; concordance observed between lean twins and mothers as well as obese twins (Turnbaugh et al, Nature, 2006)
• Weight loss diet changed gut microbiota composition
Microbiota-obesity mechanismMicrobiota-obesity mechanism
Specific AimsSpecific Aims
• Aim Aim 1:1:To measure the type and quantity of intestinal microbiota in a human pregnant sample
• Aim 2: To examine the relationship between maternal microbiota of obese women and their physiological consequences for altered leptin/adiponectin ratio and insulin resistance
• Aim 3:Aim 3: To determine the association between childhood obesity, childhood microbiota and its correlation with the microbiota of obese mothers
Data source: PopulationData source: Population• 1,923 births per annum• 89.5% black• 29.5 median age• 36.4% expected maternal
obesity• $33,663 median household
income• 70.5% WIC enrollment• Expected 441 potential obese
participants; 879 potential non-obese
Study design and measuresStudy design and measuresEnroll 72
WIC Mothers: 36 lean
36 obeseof 37-40 weeks
gestation
Demographics and Genetic ancestry
by mtDNA
anthropometrics
Fecal sample
Dietary records
Fasting blood sugar, leptin, adiponectin
Enroll:WIC toddlers
1 mo old
AnthropometricsMom/tot
Fecal sampleMom/tot
Dietary recordsMom/tot
Study visits:6, 12 months
AnthropometricsMom/tot
Fecal sampleMom/tot
Dietary recordsMom/tot
Final study visit:24 months
AnthropometricsMom/tot
Fecal sampleMom/tot
Dietary recordsMom/tot
ToddlerFasting blood sugar,
leptin, adiponectin
Instruments and measures Instruments and measures Enroll 72
WIC Mothers: 36 lean
36 obeseof 37-40 weeks
gestation
Demographics and Genetic ancestry
by mtDNA
anthropometrics
Fecal sample
Dietary records
Fasting blood sugar, leptin, adiponectin
BMI
16S rRNA sequencing on frozen sample
FFQ, 7-day food diary ( tots=3 day diary only)
Health history,obesity history,age, SESmtDNA to determine degree of racial admixture
Serum anaylzed via MSD Imager
Exclusion criteria:race other than black
Not primigravidaCo-morbidities requiring medications, smokers
Gestational age <37 weeksUnwilling/unable to consent to study activitiesCesarean section, other sources of antibiotics
Statistical analysesStatistical analysesSp. Aim #1• Descriptive statistics of maternal and offspring microbiota to examine the
type and quantity
Sp. Aim #2• Association between maternal obesity and microbial diversity• Association between microbiota type/quantity and
– 1) leptin:adiponectin ratio – 2) HOMA-IR
Sp. Aim #3• Descriptive statistics of Firmicute/ Bacteroidetes ratio change during the first
24 months of life• Correlation of offspring bacterial composition with the development of
toddler obesity• Concordance analysis of maternal-child dyad bacterial composition
InnovationInnovation• New insights on maternal microbiota during
pregnancy in lean and obese cohorts• New insights on the development of toddler
microbiota with new technology allowing increased detection and classification of previously unknown bacteria and archaea
• New insights on the development of toddler obesity and its relationship with change in toddler microbiota
SignificanceSignificance• The development of microbiota from newborn to toddler, role in development of toddler
obesity and altered adipokines and glucose metabolism is not known; it is possible that what has been presently believed regarding the progressive population of toddler microbiota is entirely misrepresented both by quantity and by species variation.
• With present day advances in rRNA sequencing, the newborn gut microbiota can be carefully chronicled over time to determine how fecal microbial residents change with the development of toddler obesity and the degree of concordance of these microbial inhabitants with the lean or obese mother. The link between maternal obesity and obesity/overweight in offspring is well-documented but not well-understood; this investigation may initiate a new area of investigation.
• Demonstration of altered ratios of fecal microbiota could potentially provide new insight on the mechanism of the development of childhood obesity, may provide a new diagnostic measure/biomarker to identify high risk toddlers, and ultimately may provide the basis for the development of new strategies of obesity prevention through the manipulation of gut microbiota.
AcknowledgementsAcknowledgements• Joy Nanda, DSc, MS, MHS, MBA, JHSPH• Laura Caulfield, PhD, JHSPH• Jeffrey I. Gordon, MD, Washington University