Immunostimulation associated with environmental enteric...
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Immunostimulation associated with
environmental enteric dysfunction in children
from a dual burden environment
Kelly M. Houck¹, Amanda L. Thompson¹ ², Margaret E. Bentley²
¹Department of Anthropology, University for North Carolina, Chapel Hill
²Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill
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Faculty Disclosure
No conflicts to disclose.
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Immunostimulation Associated with Environmental Enteric Dysfunction
Exposures:
Pathogens
Diet
Genetics
Stress
Toxins/Drugs
Balanced Gut Microbiota
Gut Dysbiosis Chronic intestinal
inflammation
Poor intestinal barrier
function (leaky gut)
Endotoxemia
Lipopolysaccharides (LPS) or
endotoxins initiate inflammation &
humoral immune responses.Immune Measures:
Inflammation: C-reactive Protein (CRP)
Endotoxemia: Endotoxin Core IgG Antibodies
(EndoCAb)(E. coli, P. aeruginosa, K. aerogenes, S. typhimurium)
Microbial
translocation of
gram-negative
bacteria
LABORATORY
HUMANBIOLOGY
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Immunostimulation in Galápagos & Comparisons
Galápagos setting- Dual Burden Environment
Are both pathogenic and dietary factors increasing immunostimulation?
Data sources:
US: National Health and Nutrition Survey 2009/2010 (US Center for Disease Control); China: China Health and Nutrition Survey 2009
(Carolina Population Center, UNC); Malawi: Benzoni et al. 2015; Bangladesh: Lin et al. 2013
0
2
4
6
8
10
Galapagos USA China
(2-10 yrs) (3-10 yrs) (6-10 yrs)
Pre
va
len
ce
%
Moderate and Acute Inflammation in Children
High risk CVD 3-10 mg/L CRP
Acute >10 mg/L CRP
0
50
100
150
200
250
Galapagos Malawi Bangladesh Bangladesh
(2-5 yrs) (2-5 yrs) (<4 yrs; cleanhouseholds)
(<4 yrs;contaminatedhouseholds)E
nd
oC
Ab
Ig
G (
MU
/mL
)
Mean Endotoxemia Levels in Young Children
LABORATORY
HUMANBIOLOGY
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Sample and Key Measures 164 children 2-10 years old
Mother’s interviews: Household information, children’s relevant
birth and health information, hygiene practices, illness histories
and diets, anthropometric assessments were conducted
Diet: Food frequency questionnaires were taken to determine
very high, high, moderate, rare consumption patterns of local
food items.
Fecal pathogen exposure: A household water sample was
collected and quantified for E. coli levels using Colilert1 reagents.
Inflammation: Two dried blood spots were collected
approximately 10 days apart and analyzed for high sensitivity C-
reactive protein (CRP) using Quantikine ELISA kits2.
Endotoxemia: One dried blood spot analyzed for Endotoxin
Core IgG antibodies (EndoCAb IgG) using Hycult Biotech ELISA
kits3.
1 IDEXX Laboratories, Inc. Westbrook, MA.2 R&D Systems, Inc. Minneapolis, MN.3 Hycult Biotech, Inc. Plymouth Meeting, PA. LABORATORY
HUMANBIOLOGY
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Single Pathogen ExposuresExposure Percent of Sample CRP Models EndoCAb Models
Fecal
contaminated
household water
High E. coli levels (>100 bacteria per
100mL) 12%
Low E.coli levels (<100 bacteria per
100mL) 88%
Brushed teeth
with tap water
Yes 87% No 13%
Hand washing
frequency
Sometimes-Rare
37%
Always 64%
Location of bath Outside 15% Inside 85%
Presence of pets
or animals
Yes 55% No 45%
Attended school Yes 78% No 22%
Swam in ocean Yes 38% No 62%
p<.05 in all reported relationships. Adjusted for field season, sex, and age for all models, and
obesity and infectious symptoms for the CRP only.
LABORATORY
HUMANBIOLOGY
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Group Percent in
Sample
CRP
Models
EndoCAb
Models
MilkVery High High
Moderate
CheeseHigh
Moderate
Vegetables Moderate Very High
BeansHigh
Moderate
Single Dietary Consumption Factors
Pie Chart
Legend:
Group Percent
in Sample
CRP
Models
EndoCAb
Models
Fried Meats Very High
Empanadas Moderate
Ice Cream High
p<.05 in all reported relationship from adjusted models, low consumption is the referent.
Very High: Every Meal
High: Daily
Moderate: Weekly
Low: Monthly/Rare
LABORATORY
HUMANBIOLOGY
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Predicted Mean Inflammation Levels from Aggregate Model
0
0.2
0.4
0.6
0.8
1
1.2
Hig
h
Low
Ye
s
No
Ve
ry H
igh
Hig
h
Mo
de
rate
Low
Ve
ry H
igh
Hig
h
Mo
de
rate
Low
Very
Hig
h
Hig
h
Mo
de
rate
Low
Fecalpathogens
in H2O
Schoolattendance
Milk consumption Bean consumption Fried meatconsumption
Pre
dic
ted
CR
P (
mg
/mL
) ** ** ****
** ***
****
**
** p<.05
* p<.1
Mixed-effects model of log-transformed CRP with random effects on intra-individual
CRP variability; adjusted for field season, sex, age, obesity, infectious symptoms and
clustering at the household level. LABORATORY
HUMANBIOLOGY
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** p<.05
* p<.1
Predicted Mean Endotoxemia Levels from Aggregate Model
OLS model of log-transformed EndoCAb; adjusted for field season, sex, age and
clustering at the household level.
80
120
160
200
Hig
h
Lo
w
Ye
s
No
Ve
ry H
igh
Hig
h
Mo
de
rate
Lo
w
Fecal pathogensin H2O
Swam in ocean Milk Consumption
Me
an
En
do
CA
b M
U/m
L
*****
LABORATORY
HUMANBIOLOGY
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Discussion Pathogenic and dietary factors can
simultaneously impact immunostimulation
associated with environmental enteric
dysfunction in a dual burden environment
Some pathogenic factors increase immune
activation: school attendance, swimming in
contaminated oceans
Habitual exposure to fecal contaminated water
not causing infection may help to prime humoral
immunity & regulate anti-inflammatory networks- hygiene hypothesis
Dietary endotoxemia and inflammation in populations with overnutrition
– Fried foods & sweets , vegetables and beans immunostimulation
– Elevated milk consumption is associated with both inflammation &
endotoxemia
LABORATORY
HUMANBIOLOGY
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Inflammation & Endotoxemia in Dual Burden Environment
No structural diagnostic measures of environmental enteric dysfunction
LABORATORY
HUMANBIOLOGY
Data sources:
US: National Health and Nutrition Survey 2009/2010 (US Center for Disease Control); China: China Health and Nutrition Survey 2009
(Carolina Population Center, UNC); Malawi: Benzoni et al. 2015; Bangladesh: Lin et al. 2013
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Conclusion
Dual Burden of the Intestinal Microbiome
Future research: mediating factors of gut microbiome
LABORATORY
HUMANBIOLOGYInfographic source: http://www.who.int/nutrition/double-burden-
malnutrition/doubleburdenmalnutrition_infographic.png
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Acknowledgments
Funding Support:
• NSF Doctoral Dissertation Research Improvement Grant
• Wenner-Gren Dissertation Fellowship
• Triangle Center for Evolutionary Medicine, Duke University
• UNC Institute for Global Health and Infectious Disease
• UNC Graduate School
• UNC Carolina Population Center
• Population Research Training Grant (5 T32 HD007168) from the Eunice
Kennedy Shriver National Institute of Child Health and Human
Development (NICHD)
• I thank Gyssell Zapata, the Galápagos Science Center, the Human
Biology Lab at UNC, Universidad San Francisco de Quito, and the
participants and residents of San Cristóbal, Ecuador.
LABORATORY
HUMANBIOLOGY