Influence of genotype on the response to a caloric restriction program (nutrigenetics) and the effect of caloric restriction on gene expression (nutrigenomics)
Is Sugar a New Fat: Genetics, Environment and Gut Microbiota Perspective
Safarina G. Malik [email protected] Lembaga Biologi Molekuler Eijkman Jl Diponegoro 69, Jakarta 10430
Indonesia
Dynamic relationship:
gene-environment-development
Nutritio nLifestyle Culture Econom y
Social See: Simopoulos, Annu Rev Public Health, 2010
Infuence of genotype on the response to a
caloric restriction program (nutrigenetics)
and the efect of caloric restriction on gene
expression (nutrigenomics)Abete et al, Prog Mol Biol Transl Sci 2012
Lifestyle and obesity
- Industrialization has changed lifestyle, diet, and health of individuals living in urban areas
• Correlated with the rise of obesity and the number
of associated deaths- Lifestyle modifications aim to reduce the burden of obesity and reduce the associated conditions
Genetic association with adiposity
appeared to be more pronounced with
greater intake of sugar-sweetened
beverages
Qi et al, N Engl J Med 2012 Sugary drinks in the pathogenesis of obesity and cardiovascular diseases
Glucose; Fructose
Brown et al, Int J Obes 2008
Changes in water and beverage intake and long-term weight changes
Pan et al, Int J Obes (Lond). 2013
Non-caloric artificial (NAS)
sweeteners and the microbiome:
findings and challenges
NAS-Bacteria interactions
Suez et al, Gut Microbes 2015 Diverse infuences on the epidemic lifestyle disease – what to do and how? Host Factors
(Genetic background, immunological
The problem: An
state)
epidemic of obesity driven by lifestyle Human change. Health
Socio-economic, environment Gut Microbiota
(in-utero exposure, diet, (composition, pharmaceuticals, exercise) activity)
Greater understanding of the tripartite infuence of on
the host state is needed
IMELDA: Indonesian Model for Epidemic Lifestyle Disease
Associations Bali in transition: 30 years ago
economy was largely agricultural-
based
Islet in the terraced rice fields of Bali, Indonesia. Photo copyright: Yann Arthus-Bertrand.
Bali in transition: today tourism is
the largest single industry in BaliRice fields were converted to villas and cottages, souvenir shops can be found everywhere. From: various sources
Why study the Balinese?
1. Impact of lifestyle changes for the Balinese (urban vs rural environment)
2. Susceptibility gene(s) associated with disease traits
3. Genes-environment interaction in infuencing disease manifestation
The Bali Study: Genes-environment
interactions – demonstrated diferences
Variable Urban Rural P-value
metabolism in urban vs rural
N 580 492 Age (years)
43.4 45.6 0.110
12.7
16.6 BMI 24.1 4.6 21.7 4.0 <0.001 (kg/m2) WC (cm)
89.2 76.9 <0.001 9.8
10.4 SBP 0.061
117.3 119.4 (mmHg)
16.8
18.6 DBP 76.4 76.3 0.845 (mmHg)
10.8
11.2 FPG (mg/dl)
93.6 99.2 <0.001
30.1
37.4 TG (mg/dl) 139.1 115.4 <0.001
84.7
57.9 Suastika et al, 2011; Saraswati et al, 2011; Malik et al, 2011; Oktavianthi HDL
52.0 55.6 <0.001
et al, 2012; Suastika et al, 2012; Dwipayana et al, 2013
(mg/dl)
12.5
12.2
Bali North Kalimantan Mt. Kidul West Sumba Biometric s (incl.
BMI) Fecal Microbiot a
Diet Data 40 samples: All females, Age 18 – 27
Febinia CA et al, manuscript in prep
The IMELDA Project:
Linking genetic diversity, gut microbiota and
lifestyle-disease
MtDNA genetic background is
associated with waist-hip biometrics
MtDNA macro-haplogroup M: higher WC and WHR
Febinia CA et al, manuscript in prep Famil y
Balinese gut microbiota: 2 types of
communitiesFebinia CA et al, manuscript in prep Associations of Balinese gut
microbiota with mtDNA and obesity
Balinese gut microbiota is Prevotella-type in Balinese gut
associated with mtDNA microbiota is associated with haplotype obesityBacteroides T1 Cluster T2 Cluster
Prevotella
Febinia CA et al, manuscript in prep
Protein Intake Ratio in Balinese is Associated with
Obesity and Prevotella abundance
Febinia CA et al, manuscript in prep obese vs.
lean obese lean
Diet diferences
Diet Components (n = 38) (n = 8) p-value % kcal
by Obesity
51 ± 11 53 ± 13 0.692 Carbohydrate % kcal Fat 30 ± 11 32 ± 13 0.723 % kcal Protein 19 ± 5 15 ± 3 0.035 Rank-based Linear
Diet Association
Models
with Microbiota
Estimate Std. Error t.value p.value Balinese (n = 40) Carbohydrate (% kcal) (Intercept) 43.74319 4.62134 9.4655 < 0.001 Prevotella 0.15099 0.17701 0.853 0.39916 Bacteroides 0.31629 0.15856 1.9947 0.05348
Fat (% kcal) (Intercept) 36.604416 4.871993 7.5132 < 0.001 Prevotella -0.034228 0.170677 -0.2005 0.84215 Bacteroides -0.300355 0.152888 -1.9645 0.05701 Protein (% kcal) (Intercept) 19.400851 1.540659 12.5926 < 0.001 Prevotella -0.150416 0.062606 -2.4026 0.02141 Bacteroides -0.044671 0.056081 -0.7965 0.4308
SUMMARY
• Obesity is tightly linked to interaction of genetics with
environment• An epidemic of obesity is driven by lifestyle changes –
increase intake of sugar- Gut microbiota might be infuenced by genetic background
- There is an indication of gut microbiota infuence on obesity
- Gut microbiota is modulated by diet, including sugar, that in turn will infuence general health
- Greater understanding of the tripartite (host factors, socio-economic-environment, gut microbiota) infuence on the host state is needed
Acknowledgement
Eijkman Institute for Molecular Biology Hidayat Trimarsanto Clarissa A. Febinia Sukma Oktavianthi Herawati Sudoyo Lidwina Priliani, MSc Ria Hasnita Artricia Rasyid Rut C. Inggriani Asri Sulfianti Rahma Fitri Hayati Faculty of Medicine, Udayana University Ketut Suastika Made Ratna Saraswati I Wayan Weta Desak Made Wihandani Pande Dwipayana Students of Faculty of
Medicine Faculty of Public Health, Universitas Indonesia Ratna Djuwita Hatma Rizka Maulida Charles Perkins Centre, the University of Sydney Gene hunter @ Eijkman Institute
Thank you