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OBEKON Consortium. Investigation of the genomic background of obesity using single nucleotide polymorphism analysis in candidate genes. Csaba Szalai, Á gnes F. Semsei, Ildik ó Ungv á ri, Petra Kiszel, P é ter Antal, Andr á s Falus. Genetics of obesity. The majority is multifactorial - PowerPoint PPT Presentation
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Investigation of the genomic background of obesity using single nucleotide polymorphism analysis
in candidate genes
OBEKONOBEKONConsortium
02 October 2009 1CECON II. Budapest
Csaba Szalai, Ágnes F. Semsei, Ildikó Ungvári, Petra Kiszel, Péter Antal, András
Falus
Genetics of obesity
The majority is multifactorialConcordance in monozygotic twins: 0.7-0.9In dizygotic twins: 0.35-0.45λs = 3.5Heritability rate of fat mass and fat
distribution: 40-70%Food preference, activity etc.Most associated genes expressed in CNS
Aim of the study
What SNPs can contribute to the susceptibility to obesity in the Hungarian population?
Candidate gene association study.
Patients1337 Hungarian adults (873 women and 464 men)838 obese (BMI>30) 500 controls (BMI<25)
Some examples of the selected
candidate genes
Genes Function
ADIPOQAdiponectin modulates glucose regulation and fatty acid catabolism.
ADRB2Delay digestion during fight-or-flight response
AGRPIncreases appetite and decreases metabolism and energy expenditure
FTO Fat mass and obesity associated
GHRELIN increases food intake and increases fat mass
INSIG2 insulin induced gene 2
LEP, LEPR leptin levels reflect individual energy balance
MC4Rinvolved in feeding behaviour, the regulation of metabolism
NPYincreases food intake and decreases physical activity
POMC
polypeptide hormone precursor giving rise to peptides with roles in pain and energy homeostasis
PPARGregulates fatty acid storage and glucose metabolism.
PYY In humans it appears to reduce appetite.
SLC6A14 Tryptophan transporter in the brain
TNF Suppressing appetite in the hypothalamus
UCP1,2,3generate heat by non-shivering thermogenesis
Selection of 55 candidate genes for obesity
Gene rs PositionAllele
sFunction Panels
ADIPOQ rs17300539 chr3:188042162 A/G -514CT 48_plex_AG_panel1
ADIPOQ rs266729 chr3:188042176 C/G -11377G>C 12plex C/G
ADIPOQ rs1501299 chr3:188053825 A/C intron (boundary) 12plex A/C
ADRB1 rs2484294 chr10:115782052 A/G 512C>T 48_plex_AG_panel2
ADRB2 rs1042711 chr5:148186541 C/T 5' UTR 48_plex_AG_panel2
ADRB2 rs1042713 chr5:148186633 A/G Gln223Arg 48_plex_AG_panel2
ADRB2 rs1042714 chr5:148186666 C/G Gln27Glu 12plex C/G
ADRB2 rs1800888 chr5:148187078 C/T Thr164Tyr 48_plex_AG_panel1
AGRP rs5030980 chr16:66074446 A/G 5' UTR 48_plex_AG_panel1
COMT rs4680 chr22:18325825 A/G Val158Met 48_plex_AG_panel2
DRD2 rs1801028 chr11:112788694 C/G Cys282Ser 12plex C/G
DRD2 rs2471857 chr11:112803539 A/G intron 48_plex_AG_panel1
ENPP1 rs1044498 chr6:132214061 A/C Lys121Gln 12plex A/C
ENPP1 rs7754561 chr6:132254387 A/G Downstream 48_plex_AG_panel2
ESR1 rs2234693 chr6:152255449 C/T intron 48_plex_AG_panel2
FABP2 rs1799883 chr4:120599505 C/T Pro55Ser 48_plex_AG_panel2
FOXC2 rs34221221 chr16:85157931 C/T 5' near gene 48_plex_AG_panel1
FTO rs1421085 chr16:52358454 C/T intron 48_plex_AG_panel2
FTO rs17817288 chr16:52365264 A/G intron 48_plex_AG_panel2
FTO rs8050136 chr16:52373776 A/C intron 12plex A/C
FTO rs7201850 chr16:52379362 C/T intron 48_plex_AG_panel2
GAD2 rs2236418 chr10:26545502 A/G intron 48_plex_AG_panel1
GAD2 rs992990 chr10:26607187 A/C intron 12plex A/C
GHRELIN rs696217 chr3:10306457 G/T Leu72Met 12plex A/C
GHRELIN rs34911341 chr3:10306519 C/T intron 48_plex_AG_panel1
Selection of 120 SNPs in the candidate genes
Genotyping method
Multiplex PCR, single base extensionBeckman GenomeLab SNPstream Genotyping System
Anneal Extend Detect
Beckman GenomeLab SNPstream Genotyping System
Throughput 4,608 to 800,000 genotypes in 24 hours (12 plex) 18,432 to 3,200,000 genotypes in 24 hours (48 plex)Multiplex level 12 –48 plex PCR and Primer extension
Gedeon Richter Ltd.-Semmelweis University SNP Core facility (http://www.dgci.sote.hu/en )
Statistical analysisTwo steps:Standard statistical methods: logistic
regression, chi squareBayesian Multilevel Analysis
ResultsGenes and SNPs associated with obesity in the
whole population (9 SNPs in 6 genes)
Gene rs Position Allele Function
ALOX5 rs7913948 chr10:45188895 A/G 5-lipoxygenase
ALOX5 rs745986 chr10:45198914 A/G 5-lipoxygenase
FTO rs17817288chr16:5236526
4A/G Fat mass and obesity associated
FTO rs8050136chr16:5237377
6A/C
Fat mass and obesity associated
FTO rs7201850chr16:5237936
2C/T
Fat mass and obesity associated
HSD11B1 rs2235543 chr1:206249063 C/T hydroxysteroid 11-beta dehydrogenase 1
IGF2 rs680 chr11:2110210 A/G Insulin like growth factor 2
TNF rs361525 chr6:31651080 A/G Tumor necrosis factor
ZFP90 rs864741 chr16:67134078 A/G Zinc finger protein 90
Different results in men and
women Only in women: ALOX5, ALOX5AP, ZFP90,
ACE, UCP3Only in men: HSD11B In both: FTO
Heritability is gender specificGirls whose mothers are classified as clinically
obese are significantly more likely obese in childhood, with a similar relationship existing between obese fathers and their sons.
Trend does not exist between mothers and their sons and fathers and their daughters
FTO = fat mass and obesity associated
OR = 3.0 (2.1-4.2) P<5x10-10!OR = 0.33 (0.23-0.47)
All obesity GWA identified FTOExact function is not knownExpressed in CNS (esp.: hippocampus, cerebellum
and hypothalamus)FTO mutant mice:
reduced fat massincreased energy expenditureunchanged physical activity.
ALOX5 OR=1.5 (1.1-1.9); OR = 0.43 (0.,25-0.74)
Synthesis of leukotrienes from arachidonic acid.
Alox5 −/− mice had significantly increased fat mass, plasma leptin levels and fasting glucose levels, but lower fasting insulin levels
IGF2OR = 1.5 (1.1-2.2)
This gene encodes a member of the insulin family of polypeptide growth factors that is involved in development and growth.
It is an imprinted gene and is expressed only from the paternally inherited allele.
It is a candidate gene for eating disorders
Zfp90OR = 1.72 (1.03-2.88)
These preliminary data suggest that Zfp90 may have an uncharacterized role in the regulation of obesity traits.
Mice with extra copies of ZFP90 had higher overall fat levels than wild-type controls.
ZFP90 could be antagonized to treat obesity
NextBayesian Multilevel
Analysis (BMLA)BMLA enables the
analysis of relevance at different abstraction levels: model-based pairwise relevance, relevance of variable sets, and interaction models of relevant variables.
50 clinical parameters , 120 SNPs and expression data
Summary
Genetic polymorphisms play an important role in the susceptibility of obesity in the Hungarian population.
There are considerable differences between men and women in the genetic background.
Those genes and pathways associated with obesity are potential targets for tailoring therapy for a healthier body weight.
Thank you for your attention!
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