connecting the dots in the pathogenesis of type 2 diabetes : the need for systems biology pierre de...
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![Page 1: Connecting the dots in the pathogenesis of type 2 diabetes : the need for systems biology Pierre De Meyts, MD, PhD Receptor Systems Biology Laboratory](https://reader036.vdocuments.site/reader036/viewer/2022062407/56649d585503460f94a37bec/html5/thumbnails/1.jpg)
Connecting the dots in the pathogenesis of Connecting the dots in the pathogenesis of type 2 diabetes : the need for systems biologytype 2 diabetes : the need for systems biology
Pierre De Meyts, MD, PhDPierre De Meyts, MD, PhDReceptor Systems Biology LaboratoryReceptor Systems Biology Laboratory
Hagedorn Research InstituteHagedorn Research Institute
Novo Nordisk A/SNovo Nordisk A/S
TNO WorkshopTNO Workshop
Zeist, December 4, 2008Zeist, December 4, 2008
?
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Islet of Islet of LangerhansLangerhans
Beta cellBeta cell
GlucoseGlucose
INSULININSULIN
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INSULININSULIN
INSULIN RECEPTORINSULIN RECEPTOR
Target cell (muscle, Target cell (muscle, liver, fat)liver, fat)
GLUCOSE GLUCOSE TRANSPORTERTRANSPORTER
GLUCOSEGLUCOSE
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Theme of the talk:
Reductionist approaches have failed to provide an understanding of the pathogenesis of diabetes mellitus, methods to prevent it or cure it, and an adequate pipeline of drugs to treat it optimally.
A systems biology approach is warranted.
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AgendaAgenda
Towards a systems understanding of T2DTowards a systems understanding of T2D
• What is systems biology?What is systems biology?
• Insulin resistance versus beta cell defect in T2DInsulin resistance versus beta cell defect in T2D
• Is there an insulin signal transduction defect in T2D?Is there an insulin signal transduction defect in T2D?
• The beta cell defect in type 2 diabetesThe beta cell defect in type 2 diabetes
• Insights from genome-wide scans for association (GWSA)Insights from genome-wide scans for association (GWSA)
• Epigenetic aspects of T2DEpigenetic aspects of T2D
• Tissue interactions, metabonomics and the microbiomeTissue interactions, metabonomics and the microbiome
Conclusion: need for an integrative approach in Conclusion: need for an integrative approach in order to understand the multi-layered complexity of order to understand the multi-layered complexity of
diabetes mellitusdiabetes mellitus
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What is systems biology?What is systems biology?
A scientific discipline that endeavours to A scientific discipline that endeavours to quantify all the molecular elements of a quantify all the molecular elements of a
biological system to assess their biological system to assess their interactions and to integrate that interactions and to integrate that
information into models that explain and information into models that explain and predict emergent behaviours that cannot be predict emergent behaviours that cannot be understood by looking at the properties of understood by looking at the properties of the individual components of the system. the individual components of the system.
Disease like diabetes mellitusDisease like diabetes mellitus
Candidate genes
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Traditional thinking about diabetes mellitusTraditional thinking about diabetes mellitus
• Find ”the” causeFind ”the” cause
• Find ”the” cureFind ”the” cure
Current statusCurrent status
• Pathogenesis unknownPathogenesis unknown
• Few drugsFew drugs
• No cureNo cure
• No predictionNo prediction
• No preventionNo prevention
• Type 2 epidemicsType 2 epidemics
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What causes type 2 diabetes?What causes type 2 diabetes?
The beta cells do not produce enough insulin
The target cells (muscle, fat, liver) do not
respond well to insulin
Genes
Nutrition
Lifestyle
Environment
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Type 2Type 2DiabetesDiabetes
It’s the fat cell
It’sGLUT4!
It’sthe liver!
It’s the insulin
receptor!
It’sglucokinase!
It’s themuscle!
It’s the betacell!
De Meyts, P. The diabetogenes concept of NIDDM. Adv. Exp. Med. Biol. 334:89 (1993)De Meyts, P. The diabetogenes concept of NIDDM. Adv. Exp. Med. Biol. 334:89 (1993)
the brain!
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Etiology of T2DEtiology of T2D
• Multiple genes (”diabetogenes”)Multiple genes (”diabetogenes”)
• Unfavorable combination of common Unfavorable combination of common allelesalleles
De Meyts, P. The diabetogenes concept of NIDDM. Adv. Exp. Med. De Meyts, P. The diabetogenes concept of NIDDM. Adv. Exp. Med. Biol. 334:89 (1993)Biol. 334:89 (1993)
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Conventional wisdom regarding the respective roles of Conventional wisdom regarding the respective roles of insulin resistance and beta cell function in insulin resistance and beta cell function in type 2 diabetestype 2 diabetes
INSULIN RESISTANCE -CELL FUNCTION
STARLING LAW OF THE BETA CELLSTARLING LAW OF THE BETA CELL
INS
ULI
NIN
SU
LIN
FASTING GLYCEMIAFASTING GLYCEMIANORMAL ELEVATED
NORMOGLYCEMIA NORMOGLYCEMIA IGTIGT TYPE 2 DIABETESTYPE 2 DIABETES
DIABETOGENES DIABETOGENES
Lifestyle/nutrition/exerciseObesityEnvironment
EnvironmentGlucose toxicityLipotoxicityLipotoxicity
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Biddinger SB and Kahn CR. Ann Rev Physiol 68:123-158 (2006)
The ”insulin resistance-centric” view of T2D
The ptolemaic geocentric view of the Universe
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Frayling TM. Nat Rev Gen 8:657-662 (2007)
The distributions of obesity and T2D overlap but do not coincide
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Development of obesity and diabetes in NZO mice
CFD: 68% fat, 20% prot.
HFD: 15% fat, 47% carb., 17% prot.
StD: 4% fat, 51% carb., 19% prot.
Jürgens HS et al, Diabetologia 50:1481-1489 (2007)
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Yudkin JS Diabetologia 50:1576-1586 (2007)
The ”inflammation-centric” view of T2D
This review alludes to several problems inherent in the epidemiological method in understanding disease mechanisms. (…) Integrated systems biology needs more
complex approaches to investigate disease mechanisms, involving cell, organ, whole
organism and population studies.
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Nature doi:10.1038/nature06098, 2007
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Biddinger SB and Kahn CR. Ann Rev Physiol 68:123-158 (2006)
The ”brain-centric” view of T2D
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?
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x = constant
Bergman’s disposition index
Review: Bergman RN, Horm Res 64 (suppl. 3) 8-15, 2005
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The hyperbolic law of glucose tolerance
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Bergman’s disposition index
Maps to chromosome 11
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Conventional wisdom regarding the respective roles of Conventional wisdom regarding the respective roles of insulin resistance and beta cell function in insulin resistance and beta cell function in type 2 diabetestype 2 diabetes
INSULIN RESISTANCE -CELL FUNCTION
STARLING LAW OF THE BETA CELLSTARLING LAW OF THE BETA CELL
INS
ULI
NIN
SU
LIN
FASTING GLYCEMIAFASTING GLYCEMIANORMAL ELEVATED
NORMOGLYCEMIA NORMOGLYCEMIA IGTIGT TYPE 2 DIABETESTYPE 2 DIABETES
DIABETOGENES DIABETOGENES
Lifestyle/nutrition/exerciseObesityEnvironment
EnvironmentGlucose toxicityLipotoxicityLipotoxicityType 2 diabetes is a Type 2 diabetes is a
signal transduction signal transduction diseasedisease
Type 2 diabetes is a Type 2 diabetes is a gene transcription gene transcription
diseasedisease
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The signal transduction defect(s) in type 2 diabetes: understanding the combinatorial
nature of signalling
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www.hprd.org
• Binding kinetics
• BRET
• Mathematical modelling
• Phosphoproteomics
• Microarray gene profiling
• siRNAs
Network inference by reverse engineering
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0
500
1000
1500
20000.01
0.1
1
10
100
1,000
10,000
0.25
0.5
0.75
1
0
500
1000
1500
2000
Time
Concentration
Fraction Bound
Modelling of insulin receptor dissociation kinetics and negative cooperativity
Kizelyov VV and De Meyts P, 2008
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Screening for candidate type 2 diabetogenes Screening for candidate type 2 diabetogenes affecting insulin signal transductionaffecting insulin signal transduction
Picture from Jan Nygaard Jensen and Oluf B. Pedersen, Picture from Jan Nygaard Jensen and Oluf B. Pedersen, Steno Diabetes Center, Gentofte, DenmarkSteno Diabetes Center, Gentofte, Denmark
PPARG
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The beta cell defect in type 2 diabetes: The beta cell defect in type 2 diabetes: transcriptional, functional and systemic transcriptional, functional and systemic
aspectsaspects
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Organellar relationships in the Golgi region of a HIT-T15 beta cell by high-Organellar relationships in the Golgi region of a HIT-T15 beta cell by high-resolution electron tomographyresolution electron tomography
Marsh BJ et al, PNAS 98:2399-2406, 2001
The Visible CellTM Project at University of Queensland,
Australia
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Noske AB et al, J Struct Biol 161:298-313, 2008.
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Transcriptional networks controlling beta cell development and functionTranscriptional networks controlling beta cell development and function
Servitja JM and Ferrer J , Diabetologia 47:597-613 (2004)Servitja JM and Ferrer J , Diabetologia 47:597-613 (2004)
MODY 1
MODY 2MODY 3
MODY 4
MODY 6
MODY 5
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Insulin
Positive feedback of insulin secretion on beta cell functionPositive feedback of insulin secretion on beta cell function
Leibiger B et al, Biochem Soc Trans 30:312-317, 2002
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Beta cell differentiation Beta cell differentiation and regenerationand regeneration
Insulin
Beta cell Beta cell secretion and secretion and functionfunction
Peripheral insulin actionPeripheral insulin action
Multi-layered complexity in pathogenesis of type 2 diabetesMulti-layered complexity in pathogenesis of type 2 diabetes
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Time for BetaSys?
Need for in silico beta cell
(”virtual beta cell”)
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Insights from genome-wide scans for Insights from genome-wide scans for association in T2Dassociation in T2D
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Sydney Brenner
Translational medicine:
from bench to bedsideXFrom bedside to bench!
Forget rodents!
There are 6.7 x 109 human
genomes/phenomes on this planet!
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The Tokyo Declaration"Recent advances in Systems Biology indicate that the time is now ripe to initiate a grand challenge project to create over the next thirty years a comprehensive, molecules-based, multi-scale, computational model of the human (‘the virtual human’), capable of simulating and predicting, with a reasonable degree of accuracy, the consequences of most of the perturbations that are relevant to healthcare.The JST and BBSRC are encouraged to join forces in order to create a collaborative program between Japan and the UK to drive this project forward.”
Workshop on Future Challenges in Systems Biology
Tokyo, February 4-6, 2008
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First Individual Diploid Human Genome Published By Researchers at J. Craig Venter Institute
Sequence Reveals that Human to Human Variation is Substantially Greater than Earlier Estimates
Independent sequence and assembly of the six billion base pairs from the genome of one person ushers in
the era of individualized genome-based medicine
ROCKVILLE, MD—September 3, 2007—ROCKVILLE, MD—September 3, 2007—Researchers at the J. Craig Venter Institute (JCVI), along with collaborators at The
Hospital for Sick Children (Sick Kids) in Toronto and the University of California, San Diego (UCSD), have
published a genome sequence of an individual, J. Craig Venter, Ph.D., that covers both of his chromosome pairs (or diploid genome), one set being inherited from each of
his parents.
J. Craig Venter
500.000 dollars reward!
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Apr 23, 2007UK-MVA Bioscience Alliance, Malmo
PPARGPPARG TCF7L2TCF7L2
HHEXHHEXSLC30A8SLC30A8CDKAL1CDKAL1IGF2BP2IGF2BP2CDKN2ACDKN2AFTOFTOWFS1WFS1TCF2TCF2
KCNJ11KCNJ11
19981998
20072007
2006200620032003
At least 18 validated At least 18 validated type 2 diabetes genes/loci on June 2008type 2 diabetes genes/loci on June 2008
Several of the diabetes-Several of the diabetes-associated variants are associated variants are
intronic or intergenic and intronic or intergenic and the actual causal the actual causal variant(s)/gene(s) variant(s)/gene(s)
remains to be identifiedremains to be identified
JAZF1JAZF1CDC123CDC123TSPAN8TSPAN8THADATHADAADAMTS9ADAMTS9NOTCH2NOTCH2KCNQ1KCNQ1
20082008
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Apr 23, 2007UK-MVA Bioscience Alliance, Malmo
PPARGPPARG TCF7L2TCF7L2
HHEXHHEXSLC30A8SLC30A8CDKAL1CDKAL1IGF2BP2IGF2BP2CDKN2ACDKN2AFTOFTOWFS1WFS1TCF2TCF2
KCNJ11KCNJ11
19981998
20072007
2006200620032003
At least 18 validated At least 18 validated type 2 diabetes genes/loci on June 2008type 2 diabetes genes/loci on June 2008
What Do theDiabetes-Associated
Variants Do?
JAZF1JAZF1CDC123CDC123TSPAN8TSPAN8THADATHADAADAMTS9ADAMTS9NOTCH2NOTCH2KCNQ1KCNQ1
20082008
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Apr 23, 2007UK-MVA Bioscience Alliance, Malmo
PPARGPPARG TCF7L2TCF7L2
HHEXHHEXSLC30A8SLC30A8CDKAL1CDKAL1IGF2BP2IGF2BP2CDKN2ACDKN2AFTOFTOWFS1WFS1TCF2TCF2
KCNJ11KCNJ11
19981998
20072007
2006200620032003
At least 1 T2D variantAt least 1 T2D variantassociates with insulin resistance associates with insulin resistance
JAZF1JAZF1CDC123CDC123TSPAN8TSPAN8THADATHADAADAMTS9ADAMTS9NOTCH2NOTCH2KCNQ1KCNQ1
20082008
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Apr 23, 2007UK-MVA Bioscience Alliance, Malmo
PPARGPPARG TCF7L2TCF7L2
HHEXHHEXSLC30A8SLC30A8CDKAL1CDKAL1IGF2BP2IGF2BP2CDKN2ACDKN2A
FTO FTO WFS1WFS1TCF2TCF2
KCNJ11KCNJ11
19981998
20072007
2006200620032003
At least 1 T2D variantAt least 1 T2D variantassociates with increased fat massassociates with increased fat mass
JAZF1JAZF1CDC123CDC123TSPAN8TSPAN8THADATHADAADAMTS9ADAMTS9NOTCH2NOTCH2KCNQ1KCNQ1
20082008
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Apr 23, 2007UK-MVA Bioscience Alliance, Malmo
PPARGPPARG TCF7L2TCF7L2
HHEXHHEXSLC30A8SLC30A8CDKAL1CDKAL1IGF2BP2IGF2BP2CDKN2ACDKN2AFTOFTO
WFS1WFS1TCF2TCF2
KCNJ11KCNJ11
19981998
20072007
2006200620032003
At least 13 T2D variantsAt least 13 T2D variantsassociates with decreased beta-cell functionassociates with decreased beta-cell function
JAZF1JAZF1CDC123CDC123TSPAN8TSPAN8THADATHADAADAMTS9ADAMTS9NOTCH2NOTCH2
KCNQ1KCNQ1
20082008
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Impairedinsulin biosynthesis/
releaseObesity
PPARG2
KCNJ11 KCNJ11 TCF7L2 TCF7L2 HHEX HHEX SLC30A8 SLC30A8 CDKAL1 CDKAL1 IGF2BP2 IGF2BP2 CDKN2A CDKN2A WFSWFSTCF2TCF2JAZF1 CDC123/CAMK1D LGR5THADA ?ADAMTS9 ?NOTCH2 ?KCNQ1
FTO
Impairedinsulin action
Validated type 2 diabetes genesrelative risk 1.10-1.50
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Eighteen confirmed type 2 diabetes associatedEighteen confirmed type 2 diabetes associatedSNPs examined in Danish cases (n=4093)SNPs examined in Danish cases (n=4093)and glucose tolerant controls (n=5302)and glucose tolerant controls (n=5302)
0.8 1.0 1.2 1.4 1.6 1.8
NOTCH2 (rs10923931)
WFS1 (rs10010131)
FTO (rs8050136)
TCF2 (rs7501939)
PPARG (rs1801282)
IGF2BP2 (rs4402960)
SLC30A8 (rs13266634)
ADAMTS9 (rs4607103)
HHEX (rs1111875)
CDC123 (rs12779790)
TSPAN8 (rs7961581)
KCNJ11 (rs5215)
JAZF1 (rs864745)
Chr 11p15 (-)
CDKAL1 (rs10946398)
THADA (rs7578597)
CDKN2A/2B (rs10811661)
TCF7L2 (rs7903146)
0.8 1.0 1.2 1.4 1.6 1.8
OR (CI 95%)
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PPARG Nuclear receptor for thiazolidinediones
KCNJ11 Kir 6.2, ATP-sensitive potassium channel
TCFL2 Transcription factor
HHEX/IDE Homeobox, hematopoietically expressed: Wnt signalling (pancreatic development)
SLC30A8 Zinc transporter ZnT8
CDKAL1 Cyclic dependent kinase5 regulatory subunit associated protein 1-like 1 (regulation of beta cell function)
IGF2BP2 Regulates IGF-2 translation
CDKN2A/B Tumor suppressor (p16INK4a and b)(regulation of beta cell regeneration)
FTO Adiposity gene
WFS1 Wolfram syndrome
T2D associated genes identified in genome-wide association scans
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PNAS 104, 15040-15044, 2007
A24D
G32S
G32R
C43G
G47V
F48C
R89C
G90C
C96Y
Y108C
(proinsulin nomenclature)
(insulin nomenclature)
B8
B8
B19
B23
B24
A1
A7
A19
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Zinc
Zn T8
Zinc
A zinc- and insulin centric vision of the beta cell (and universe)…
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Type 2Type 2DiabetesDiabetes
It’s the fat cell!
It’sGLUT4!
It’sthe liver!
It’s the insulin
receptor!
It’sglucokinase!
It’s themuscle!
It’s the betacell!
De Meyts, P. The diabetogenes concept of NIDDM. Adv. Exp. Med. Biol. 334:89 (1993)De Meyts, P. The diabetogenes concept of NIDDM. Adv. Exp. Med. Biol. 334:89 (1993)
the brain!
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From bedside to bench…
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HUMANC. elegans BLAST or ensembl
score
IMP2 M88.5 (UBRH) E-36, 28% ID
SLC30A8 T13D3.3 (UBRH), Y39E4A.2B/ttm-1
E-71, 48% IDE-59, 40% ID
TCF7L2 W10C8.2/pop-1 E-35, 40% ID (C’)
PKN2 F46F6.2 E-166, 47% ID
KCNJ11 M02A10.2/irk-2R03E9.4/irk-1
E-76, 44% IDE-69, 42% ID
CDKAL1 Y92H12BL.1 Ensembl 1:1
HHEX M6.3/pha-2 Ensembl 1:1
CDKN2A D2021.8Y17G7B.15/cnt-1B0350.2/unc-44
E-7, 35% ID (ankyrin)E-5, 33% ID (ankyrin)E-5, 32% ID (ankyrin)
CDKN2B D2021.8K12C11.4/dapk-1
E-10, 31% ID (ankyrin)E-7, 30% ID (ankyrin)
PPARG nhr-49 and others
GCKR No hits
FLJ39370 No hits
Data from Kaveh Ashrafi, UCSF
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Diabetes susceptibility genes alter C. elegans fat content
Control RNAi ttm-1 RNAi(SLC30A8?)
Zinc transporter
M88.5 RNAi (IMP2)IGF-II mRNA binding
protein
Data from Kaveh Ashrafi, UCSF
112 genes inactivation increases fat storage, many of which have human homologues.
Nature 421:268-272, 2003
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Epigenetic aspects of T2DEpigenetic aspects of T2D
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Genetic versus epigenetic mechanisms in Type 2 diabetesGenetic versus epigenetic mechanisms in Type 2 diabetes
Diabetes/Metabolism Research and Reviews, 21:416-433, 2005.
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Tissue interactions, metabonomics and the microbiomeTissue interactions, metabonomics and the microbiome
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Diabetes, 53 suppl.3: S6-S15, 2004
The gut!G
LP-1
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Metabonomics and the microbiome
Highly complex animals such as humans can be considered ”superorganisms” with an internal ecosystem of diverse symbiotic microbiota and parasites that have interactive metabolic processes.
We now need novel approaches to measure and model metabolic compartments in interactive cell types and genomes that are
connected by cometabolic processes in symbiotic mammalian systems.
Nicholson JK, Holmes E, Lindon JC and Wilson D
The challenges of modeling mammalian biocomplexity
Nat Biotechnol 22:1268-1274, 2004
Our body contains 10 times more microbial cells than human cells!
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Turnbaugh PJ, Ley RE, Hamadi M, Fraser-Liggett CM, Knight R and Gordon JI.
Nature 449:18 Oct. 2007 online.
The gut bug-centric view of the universe…
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Sequencing the intestinal flora:
MetaHit
”Intestinal metagenome”
20 million Euros/4 years
European – China project
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Take home messageTake home message
• Avoid unidimensional thinkingAvoid unidimensional thinking
• GWSA will sooner than later establish a complete GWSA will sooner than later establish a complete nomenclature of the common gene alleles that in nomenclature of the common gene alleles that in unfavorable combination predispose to disturbed unfavorable combination predispose to disturbed metabolismmetabolism
• These will reveal new critical nodes/pathways in These will reveal new critical nodes/pathways in metabolic regulationmetabolic regulation
• Connecting the dots = Connecting the dots = systems biologysystems biology
• New drug targets
• Pharmacogenomics
• Biomarkers
• Personalized medicine/prevention
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Biddinger SB and Kahn CR. Ann Rev Physiol 68:123-158 (2006)
The ”insulin resistance-centric” view of T2D
Goh KI et al, PNAS 104:8685-8690, 2007
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Systems biology of diabetes: what is needed?
• Transdisciplinarity
• Computing power
• Sharing/compatibility of data/databases/representations/models
• Resources
• International cooperation
• Rethinking teaching of biology and medicine
• Training new generation of system biologists
• Some success stories
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What is simpleWhat is simple
is wrong, andis wrong, and
what iswhat is
complicatedcomplicated
cannot becannot be
understood.understood.
Paul Valery (1871 – 1945)Paul Valery (1871 – 1945)
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0.0 2.5 5.0 7.5 10.0 12.50.0
0.2
0.4
0.6
0.8
1.0
L1
CR
L1
L2
Fn1
Fn2
Fn3
Fn1
Fn2
Fn3
Site 2Site 2
Site 1
A
Site 2
Site 2
Site 1
Site 1
B C
Figure 1
Energy (kJ/mol)
dP
/dE
(1
/kT
)
Activation energy 5 % fraction of receptor molecules in the active state
D
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S1
S2 S1
S2
r1
S1
S2 S1
S2
r2
S1
S2 S1
S2
r3
S1
S2 S1
S2
r4
S1
S2 S1
S2
r13
S1
S2 S1
S2
r14
S1
S2 S1
S2
r23
S1
S2 S1
S2
r24
Figure 2
S1
S2 S1
S2
r0
S1
S2S1
S2
S1
S2 S1
S2
r1x2 r3x4
S1
S2S1
S2 S1
S2S1
S2 S1
S2S1
S2
S1
S2 S1
S2 S1
S2 S1
S2
S1
S2S1
S2
S1
S2 S1
S2S1
S2 S1
S2
r1x23 r1x24 r1x24d r13x4 r23x4 r2d3x4 r1x234 r123x4
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Figure 3
S1
S2 S1
S2 S1
S2 S1
S2a1
d1S1
S2S1
S2
kcr
d2S1
S2S1
S2
a1
d1
S1
S2 S1
S2
a2d2
d1
S1
S2 S1
S2
S1
S2S1
S2
a1
a2d2
kcr
d2
a1
d1
d2a2
S1
S2S1
S2
a2d2
S1
S2 S1
S2 S1
S2 S1
S2
S1
S2 S1
S2 S1
S2 S1
S2
kcrd1kcrd1
a1
d1
a2d2
a1
d1
a2d2
Simplified scheme of the insulin receptor binding
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10-12 10-11 10-10 10-9 10-8 10-7 10-6
0.00
0.25
0.50
0.75
1.00
Hot
insu
lin b
ound
Cold insulin (M)
10-11 10-10 10-9 10-8 10-7 10-6 10-50
20
40
60
80
100
Hot
insu
lin r
emai
ning
afte
r di
ssoc
iatio
n (%
)
Cold insulin (M)
Dissociation time: 20 min 60 min
0 1 2 3
0
1x109
2x109
3x109
4x109
Bou
nd/fr
ee (
1/M
)
Bound
A B C
D E
Figure 4
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10-13 10-12 10-11 10-10 10-9 10-8 10-7 10-6 10-5
0.0
0.2
0.4
0.6
0.8
1.0
Figure 5
Kd= 0.19 nM, kcr = 0.33 s-1
Kd= 1.8 nM, kcr = 0.033 s-1
Kd= 0.019 nM, kcr = 3.3 s-1
Cold insulin (M)
Ho
t in
sulin
bo
un
d
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Parameter Average SD SD %
Apparent KD 0.19 nM 0.005 nM 2.6
Kcr 0.33 s-1 0.099 s-1 29.7
Site 1 KD 6.41 nM 0.78 nM 12.1
Site 2 KD 399 nM 76 nM 19.0
a1 490 637 s-1 M-1 25 945 s-1 M-1 5.3
d1 0.0031 s-1 0.00031 s-1 10.2
a2 27 890 s-1 M-1 12 125 s-1 M-1 43.5
d2 0.010 s-1 0.0024 s-1 23.3
Endocytosis rate 12.1 % per hour 3.2 % per hour 26.5
Exocytosis rate 8.3 % per hour 12.1 % per hour 145
Table 1
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d 2
r0 r1r3
r2
r4
a1
d1a1
d1
a2 d2
a2d2
1.
r1 r1x2r14
r0
r13
kcr
d2a2
d2
d1 a1
a1d1
2.
r2 r1x2r24
r0
r23
kcr
d1a2
d2
d2 a2
a1d1
3.
r3 r3x4r23
r0
r13
kcr
d2a2
d2
d1 a1
a1d1
4.
r4 r3x4r24
r0
r14
kcr
d1a2
d2
d2 a2
a1d1
5.
r1x2
r1r1x23
r2
r1x24d
d2
k cra1
d1
d1 kcr
a 2
d 2
6.
a 2
d 2
r1x24
r14 r1r13x4
r4
d2
a2kcr
d1
d1 a1
kcrd2
7.
r1x24
r13 r1r13x4
r3
d1
a1kcr
d2
d1a1
kcrd2
8.
r1x23
r23 r2r23x4
r3
d1
a1kcr
d2
d2 a2
kcrd1
9.
r1x23
r24 r2r23x4
r4
d2
a2kcr
d1
d2 a2
kcrd1
10.
r1x24
r3x4
r3r23x4
r4
r13x4
d2
k cra
2
d2
d1 kcr
a 1
d 1
11.
a 2
r2d3x4
r1x23 r1x2r23
r13
d1
a1d1
kcr
d2 kcr
a2d2
12.
r1x234
r1x24
r1x2r24
r14
r1x234
d2
a2d1
kcr
d2 kcr
a 1
d 1
13.
k 4
k 8
r1x24d
r13x4 r3x4r13
r14
d1
a1d2
kcr
d1 kcr
a2d2
14.
r123x4
r23x4
r3x4r23
r24
r123x4
d2
a2d
2
kcr
d1 kcr
a 1
d 1
15.
k 4
k 8
r2d3x4
r1x24d r1x2r1x24
d2
a2k8
k416.
r2d3x4 r3x4r23x4
d2
a2k8
k417.
r1x234 r1x23r1x24
d2
a2d1
a118.
r123x4 r13x4r23x4
d2
a2d1
a119.
Figure S1
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Figure S2
1. r0' -a1r0im+d1r1-a2r0im+d2r4-a1r0im+d1r3-a2r0im+d2r2+kexr0cyt, 2. r1' -kcrr1+d2r1x2-a1r1im+d1r13-a2r1im+d2r14-d1r1+a1r0im, 3. r2' -kcrr2+d1r1x2-a1r2im+d1r23-a2r2im+d2r24-d2r2+a2r0im, 4. r3' -kcrr3+d2r3x4-a1r3im+d1r13-a2r3im+d2r23-d1r3+a1r0im, 5. r4' -kcrr4+d1r3x4-a1r4im+d1r14-a2r4im+d2r24-d2r4+a2r0im, 6. r1x2' -d2r1x2+kcrr1-a2r1x2id+d2r1x24d-a2r1x2im+d2r1x24-a1r1x2im+d1r1x23-d1r1x2+kcrr2-kendr1x2, 7. r14' -d2r14+a2r1im-kcrr14+d2r1x24-kcrr14+d1r13x4-d1r14+a1r4im, 8. r13' -d1r13+a1r1im-kcrr13+d2r1x23-kcrr13+d2r13x4-d1r13+a1r3im, 9. r23' -d1r23+a1r2im-kcrr23+d1r1x23-kcrr23+d2r23x4-d2r23+a2r3im, 10. r24' -d2r24+a2r2im-kcrr24+d1r1x24-kcrr24+d1r23x4-d2r24+a2r4im, 11. r3x4' -d2r3x4+kcrr3-a1r3x4im+d1r13x4-a2r3x4id+d2r2d3x4-a2r3x4im+d2r23x4-d1r3x4+kcrr4-kendr3x4, 12. r1x23' -d1r1x23+a1r1x2im-a2r1x23im+d2r1x234-d1r1x23+kcrr23-d2r1x23+kcrr13-kendr1x23, 13. r1x24' -d2r1x24+a2r1x2im-a1r1x24im+d1r1x234-k4r1x24im+k8r1x24d-d1r1x24+kcrr24-d2r1x24+kcrr14-kendr1x24, 14. r13x4' -d1r13x4+a1r3x4im-a2r13x4im+d2r123x4-d2r13x4+kcrr13-d1r13x4+kcrr14-kendr13x4, 15. r23x4' -d2r23x4+a2r3x4im-a1r23x4im+d1r123x4-k4r23x4im+k8r2d3x4-d2r23x4+kcrr23-d1r23x4+kcrr24-kendr23x4, 16. r1x24d' -d2r1x24d+a2r1x2id-k8r1x24d+k4r1x24im-kendr1x24d, 17. r2d3x4' -d2r2d3x4+a2r3x4id-k8r2d3x4+k4r23x4im-kendr2d3x4, 18. r1x234' -d2r1x234+a2r1x23im-d1r1x234+a1r1x24im-kendr1x234, 19. r123x4' -d2r123x4+a2r13x4im-d1r123x4+a1r23x4im-kendr123x4, 20. r0cyt' -kexr0cyt+kendr1x2+kendr3x4+kendr1x23+kendr1x24+kendr13x4+kendr23x4+kendr1x24d+kendr2d3x4+kendr1x234+kendr123x4, 21. iend' -kexiend+kendr1x2+kendr3x4+2kendr1x23+2kendr1x24+2kendr13x4+2kendr23x4+3kendr1x24d+3kendr2d3x4+3kendr1x234+3kendr123x4
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Figure S3Hot and cold insulin
S1
S2S1
S2
r1x2h
S1
S2S1
S2 S1
S2S1
S2 S1
S2S1
S2
S1
S2 S1
S2 S1
S2 S1
S2
r1x2h4 r1x2h3 r1x2h4d r1h r2h
S1
S2S1
S2
S1
S2 S1
S2 S1
S2 S1
S2
S1
S2 S1
S2 S1
S2 S1
S2
r1x2h34 r1h3 r1h4
r2h3 r2h4
S1
S2 S1
S2 S1
S2 S1
S2
r1h3x4 r2h3x4
S1
S2 S1
S2 S1
S2 S1
S2 S1
S2 S1
S2
r1h23x4 r12h3x4 r2hd3x4
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r1x2h
r1x2h3r1x2h4d
r1x2h4
r2h
a1
d1a2
d2
a2 d2
d 1
k cr
20.d 2
k cr
r1h
r1hr0r1h3
r1h4
d1
a1
d1
kcr d2
a2d2
21.r1x2h
r2h r0r2h3
r2h4
d2
a1
d1
kcr d1
a2d2
22.r1x2h
r1x2h3 r1x2h34r1h3
r2h3
a2
d2
kcr
d1 a1
d1kcr
23.r1x2h
d2
r1x2h4
r1x2h34r1h4
r1x2h
r1x2h4d
a1
d1d2
kcr
d2 a2
k 4
k 8
24.
d 1
k cr
r2h4
r1x2h4d r1x2hr1x2h4
d2
a2k8
k425.
r1x2h34 r1x2h3r1x2h4
d2
a2d1
a126.
r1h4 r4r1h
r1h3x4
d1
d2
a2
kcr d2
kcrd1
27.r1x2h4
r2h4 r4r2h
r2h3x4
d2
d2
a2
kcr d1
kcrd1
28.r1x2h4
r2h3 r3r2h
r2h3x4
d2
d1
a1
kcr d1
kcrd2
29.r1x2h3
r1h3 r3r1h
r1h3x4
d1
d1
a1
kcr d2
kcrd2
30.r1x2h3
r1h3x4 r3x4r1h23x4
r1h4
d1
a2
d2
d2 kcr
d1kcr
31.r1h3
r2h3x4
r3x4r12h3x4
r2h4
r2h3
d2
a1
d1
d1 kcr
d 2
k cr
32.
k 4
k 8
r2hd3x4
r1h23x4 r23x4r1h3x4 d2
a233.
d1 r12h3x4 r13x4r2h3x4 d1
a134.
d2 r2hd3x4 r3x4r2h3x4
k8
k435.
d2
Figure S4
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Figure S51. r0' -a1r0im+d1r1-a2r0im+d2r4-a1r0im+d1r3-a2r0im+d2r2+d1r1h+d2r2h+kexr0cyt, 2. r1' -kcrr1+d2r1x2-a1r1im+d1r13-a2r1im+d2r14-d1r1+a1r0im, 3. r2' -kcrr2+d1r1x2-a1r2im+d1r23-a2r2im+d2r24-d2r2+a2r0im, 4. r3' -kcrr3+d2r3x4-a1r3im+d1r13-a2r3im+d2r23-d1r3+a1r0im+d2r2h3+d1r1h3, 5. r4' -kcrr4+d1r3x4-a1r4im+d1r14-a2r4im+d2r24-d2r4+a2r0im+d1r1h4+d2r2h4, 6. r1x2' -kendr1x2-d2r1x2+kcrr1-a2r1x2id+d2r1x24d-a2r1x2im+d2r1x24-a1r1x2im+d1r1x23-d1r1x2+kcrr2, 7. r14' -d2r14+a2r1im-kcrr14+d2r1x24-kcrr14+d1r13x4-d1r14+a1r4im, 8. r13' -d1r13+a1r1im-kcrr13+d2r1x23-kcrr13+d2r13x4-d1r13+a1r3im, 9. r23' -d1r23+a1r2im-kcrr23+d1r1x23-kcrr23+d2r23x4-d2r23+a2r3im, 10. r24' -d2r24+a2r2im-kcrr24+d1r1x24-kcrr24+d1r23x4-d2r24+a2r4im, 11. r3x4' -kendr3x4-d2r3x4+kcrr3-a1r3x4im+d1r13x4-a2r3x4id+d2r2d3x4-a2r3x4im+d2r23x4-d1r3x4+kcrr4+d1r1h3x4+d2r2h3x4+ d2r2hd3x4, 12. r1x23' -kendr1x23-d1r1x23+a1r1x2im-a2r1x23im+d2r1x234-d1r1x23+kcrr23-d2r1x23+kcrr13, 13. r1x24' -kendr1x24-d2r1x24+a2r1x2im-a1r1x24im+d1r1x234-k4r1x24im+k8r1x24d-d1r1x24+kcrr24-d2r1x24+kcrr14, 14. r13x4' -kendr13x4-d1r13x4+a1r3x4im-a2r13x4im+d2r123x4-d2r13x4+kcrr13-d1r13x4+kcrr14+d2r12h3x4, 15. r23x4' -kendr23x4-d2r23x4+a2r3x4im-a1r23x4im+d1r123x4-k4r23x4im+k8r2d3x4-d2r23x4+kcrr23-d1r23x4+kcrr24+d1r1h23x4, 16. r1x24d' -kendr1x24d-d2r1x24d+a2r1x2id-k8r1x24d+k4r1x24im, 17. r2d3x4' -kendr2d3x4-d2r2d3x4+a2r3x4id-k8r2d3x4+k4r23x4im, 18. r1x234' -kendr1x234-d2r1x234+a2r1x23im-d1r1x234+a1r1x24im, 19. r123x4' -kendr123x4-d2r123x4+a2r13x4im-d1r123x4+a1r23x4im, 20. r1x2h' -kendr1x2h-a1r1x2him+d1r1x2h3-d1r1x2h+kcrr2h-d2r1x2h+kcrr1h-a2r1x2hid+d2r1x2h4d-a2r1x2him+d2r1x2h4, 21. r1h' -d1r1h-a2r1him+d2r1h4-a1r1him+d1r1h3-kcrr1h+d2r1x2h, 22. r2h' -d2r2h-a2r2him+d2r2h4-a1r2him+d1r2h3-kcrr2h+d1r1x2h, 23. r1x2h3' -kendr1x2h3-a2r1x2h3im+d2r1x2h34-d1r1x2h3+kcrr2h3-d2r1x2h3+kcrr1h3-d1r1x2h3+a1r1x2him, 24. r1x2h4' -kendr1x2h4-a1r1x2h4im+d1r1x2h34-k4r1x2h4im+k8r1x2h4d-d1r1x2h4+kcrr2h4-d2r1x2h4+kcrr1h4-d2r1x2h4+a2r1x2him, 25. r1x2h4d' -kendr1x2h4d-d2r1x2h4d+a2r1x2hid-k8r1x2h4d+k4r1x2h4im, 26. r1x2h34' -kendr1x2h34-d2r1x2h34+a2r1x2h3im-d1r1x2h34+a1r1x2h4im, 27. r1h4' -d1r1h4-kcrr1h4+d1r1h3x4-d2r1h4+a2r1him-kcrr1h4+d2r1x2h4, 28. r2h4' -d2r2h4-kcrr2h4+d1r2h3x4-d2r2h4+a2r2him-kcrr2h4+d1r1x2h4, 29. r2h3' -d2r2h3-kcrr2h3+d2r2h3x4-d1r2h3+a1r2him-kcrr2h3+d1r1x2h3, 30. r1h3' -d1r1h3-kcrr1h3+d2r1h3x4-d1r1h3+a1r1him-kcrr1h3+d2r1x2h3, 31. r1h3x4' -kendr1h3x4-d1r1h3x4-d1r1h3x4+kcrr1h4-a2r1h3x4im+d2r1h23x4-d2r1h3x4+kcrr1h3, 32. r2h3x4' -kendr2h3x4-d2r2h3x4-d2r2h3x4+kcrr2h3-k4r2h3x4im+k8r2hd3x4-a1r2h3x4im+d1r12h3x4-d1r2h3x4+kcrr2h4, 33. r1h23x4' -kendr1h23x4-d1r1h23x4-d2r1h23x4+a2r1h3x4im, 34. r12h3x4' -kendr12h3x4-d2r12h3x4-d1r12h3x4+a1r2h3x4im, 35. r2hd3x4' -kendr2hd3x4-d2r2hd3x4-k8r2hd3x4+k4r2h3x4im, 36. r0cyt' -kexr0cyt+kendr1x2+kendr3x4+kendr1x23+kendr1x24+kendr13x4+kendr23x4+kendr1x24d+kendr2d3x4+kendr1x234+kendr123x4+kendr1x2h+ kendr1x2h3+kendr1x2h4+kendr1x2h4d+ kendr1x2h34+ kendr1h3x4+kendr2h3x4+kendr1h23x4+kendr12h3x4+kendr2hd3x4, 37. iend' -kexiend+kendr1x2h+kendr1x2h3+kendr1x2h4+kendr1x2h4d+kendr1x2h34+kendr1h3x4+kendr2h3x4+ kend r1h23x4+kendr12h3x4+ kendr2hd3x4
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n (%
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Cold insulin (M)
Dissociation time: 10 min
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Dissociation time: 20 min
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Cold insulin (M)
Dissociation time: 30 min
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Cold insulin (M)
Dissociation time: 60 min
Figure S6