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1 Type 2 diabetes og fedme: arv og/eller miljø? Torben Hansen Steno Diabetes Center

2 Epidemiology of diabetes Burden of the problem (WHO) Adults with diabetes Developed countries Developing countries MIO 84 MIO MIO 100 MIO MIO 228 MIO 42% increase 170% increase

3 DIABETES Top three countries in the world 60 Diabetic patients in Millions million 38 million U.S. CHINA INDIA U.S. CHINA INDIA King et al, Diabetes Care, 1998

4 But why?

5 Global epidemic of type 2 diabetes Size of the population Genetic constitution of the population Age Residence (urban/rural ratio) Physical activity (industrialisation) Obesity

6 Obesity increases the risk of developing type 2 diabetes Prevalence (%) 60% 50% 40% 30% 20% 10% 0% BMI/ One diabetic parent No family history kg/m2

7 Obesity* Trends Among U.S. Adults BRFSS, 1991, 1995 and 2000 (*BMI 30, or ~ 30 lbs overweight for 5 4 person) No Data <10% 10%-14% 15-19% 20% Source: Mokdad A H, et al. JAMA 1999;282:16, 2001;286:10.

8 Diabetes in USA

9 What would a giraf look like if it was living in America?

10 Why spend time on finding genes causing diabetes? Molecular understanding New targets Novel drugs Gene therapy Improved dissection of environmental factors Increased motivation for prevention Rational nosological classification and pharmacogenomics Personalized treatment and prevention Individual genetic prediction

11 Genetics: the inherited contribution to phenotypic variation aattggaagc aaatgacatc acagcaggtc agagaaaaag ggttgagcgg caggcaccca gagtagtagg tctttggcat taggagcttg agcccagacg gccctagcag ggaccccagc gcccgagaga ccatgcagag gtcgcctctg gaaaaggcca gcgttgtctc caaacttttt ttcagctgga ccagaccaat tttgaggaaa ggatacagac agcgcctgga attgtcagac atataccaaa tcccttctgt tgattctgct gacaatctat ctgaaaaatt ggaaagagaa agaatttcat tgggatagag agctggcttc aaagaaaaat cctaaactca ttaatgccct tcggcgatgt tttttctgga gatttatgtt ctatggaatc tttttatatt taggggaagt caccaaagca gtacagcctc tcttactggg aagaatcata gcttcctatg at[t/c]gtg acccggataa caaggaggaa cgctctatcg cgatttatct aggcataggc ttatgccttc tctttattgt gaggacactg ctcctacacc cagccatttt tggccttcat cacattggaa tgcagatgag aatagctatg tttagtttga tttataagaa gactttaaag ctgtcaagcc gtgttctaga taaaataagt attggacaac ttgttagtct cctttccaac aacctgaaca aatttgatga aggacttgca ttggcacatt tcgtgtggat cgctcctttg caagtggcac tcctcatggg gctaatctgg gagttgttac aggcgtctgc cttctgtgga cttggtttcc tgatagtcct tgcccttttt caggctgggc tagggagaat gatgatgaag tacagagatc agagagctgg gaagatcagt gaaagacttg tgattacctc agaaatgatt gaaaatatcc aatctgttaa ggcatactgc tgggaagaag caatggaaaa aatgattgaa aacttaagac aaacagaact gaaactgact cggaaggcag cctatgtgag atacttcaat agctcagcct tcttcttctc agggttcttt gtggtgtttt tatctgtgct tccctatgca ctaatcaaag gaatcatcct ccggaaaata ttcaccacca tctcattctg cattgttctg cgcatggcgg tcactcggca atttccctgg gctgtacaaa catggtatga ctctcttgga gcaataaaca aaatacagga tttcttacaa aagcaagaat ataagacatt ggaatataac ttaacgacta cagaagtagt gatggagaat gtaacagcct tctgggagga gggatttggg gaattatttg agaaagcaaa acaaaacaat aacaatagaa aaacttctaa tggtgatgac agcctcttct tcagtaattt ctcacttctt ggtactcctg tcctgaaaga tattaatttc aagatagaaa gaggacagtt gttggcggtt gctggatcca ctggagcagg caagacttca cttctaatga tgattatggg agaactggag ccttcagagg gtaaaattaa gcacagtgga agaatttcat tctgttctca gttttcctgg attatgcctg gcaccattaa agaaaatatc atctttggtg tttcctatga tgaatatag tacagaagcg tcatcaaagc atgccaacta gaagaggaca tctccaagtt tgcagagaaa gacaatatag ttcttggaga aggtggaatc acactgagtg gaggtcaacg agcaagaatt gaagaggaca 3.2 billion letters of human DNA

12 38:320-3, 3, 2006

13 January 7, 2007 In studies of 3,549 middle-aged Danes the common risk allelle (rs ) of TCF7L2 was associated with type 2 diabetes: odds ratio 1.49; p =

14 GWA in short Case-control pairs; typically 1500 cases and 1500 controls Type for ~500,000 SNPs Obtain information about strength of association genome wide (within limits of sample size, allele frequency, LD etc) Validation in independent samples of what looks interesting followed by combined analyses UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

15 Example of a GWA with 389,000 SNPs successfully genotyped By courtesy of

16 French-Canadian GWA in T2D

17 Online April 26, 2007 The Icelandic, Danish, Scottish, North American, Dutch and Chinese GWA contribution

18 CDKAL1 rs risk allele (freq. about 0.25) associates with type 2 diabetes: The discovery of a novel type 2 diabetes gene Iceland with 1,399 T2D cases and 5,275 controls OR= 1.23 ( ); p = Denmark with 1,359 T2D cases and 4,825 controls and OR= 1.21 ( ); p= Nature Genetics Online April 26, 2007

19 a) In a population-based sample of 3,982 Danish middle-aged whites the CDKAL1 rs risk allele is associated with impaired insulin secretion rs p< 1.0 x 10-7 p<0.001 p< All Males Females log CIR b) log CIR rs (2027) (1557) (354) (952) (742) (187) (1075) (815) (167) AA AG GG AA AG GG AA AG GG The OGTT-related insulin response for homozygotes was % lower than for heterozygotes or noncarriers, 6.4 suggesting that this variant confers risk of type 2 diabetes 6.2 through reduced insulin secretion 5.8 (462) (1658) (1806) (237) (777) (865) (225) (881) (941) TT CT CC TT CT CC TT CT CC Nature genetics Online April 26, 2007

20 The contributions from: BROAD/LUND+Finland LUND+Finland/ / NOVARTIS, WELLCOME TRUST Case Control Consortium UK FUSION Online April 26, 2007

21 COMBINED ANALYSES: BROAD/LUND+Finland LUND+Finland/ / NOVARTIS = Diabetes Genetics Initiative, WELLCOME TRUST Case Control Consortium, UK and FUSION UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

22 FTO an obesity and T2D gene 30,081 adults from 13 studies P=3x % of the population who are homozygous for risk allele are ~3 kg heavier UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

23 At least 11 validated type 2 diabetes genes/loci on July 1 Six entirely novel diabetes-susceptibility susceptibility genes/loci (p<10-10 ) discovered in 2007 PPARG 1998 KCNJ TCF7L HHEX SLC30A8 Jan 07 CDKAL1 IGF2BP2 CDKN2A FTO April 07 WFS1 TCF2 July 07 What are the encoded proteins of these 6 novel genes doing? UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

24 UK-MVA Bioscience Alliance, Malmo By courtesy of Dr. Mark McCarthy Apr 23, 2007

25 FTO: Obesogenic/diabetogenic mechanisms? UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

26 Association with type 2 diabetes The FTO rs variant associates with type 2 diabetes n (men/women) TT TA AA MAF (95%CI) p GD p AF Odds Ratio NGT 4,861 (2,259/2,602) Type 2 diabetes 3,856 (2,286/1,567) 1,676 (35) 1,210 (31) 2,391 (49) 1,907 (50) 794 (16) 9 (19) 40.9 ( ) 43.9 ( ) ( ) p (Add) 1 = / OR 1.17 ( ) p (Add) 2 = 0.2 / OR 1.06 ( ) 1 Adjusted for sex and age 2 Adjusted for sex, age and BMI

27 Association with BMI The FTO rs variant associates strongly with both overweight and obesity n (men/women) TT TA AA MAF (95%CI) p GD p AF Odds Ratio BMI <25 5,148 (2155/2993) 1,901 (37) 2,525 (49) 722 (14) 38.5 ( ) BMI 25 12,014 (6,951/5,063) 3,945 (33) 5,888 (49) 2,181 (18) 42.7 ( ) ( ) BMI 30 4,867 (2,506/2,361) 1,510 (31) 2,406 (49) 951 (20) 44.3 ( ) ( ) Association with overweigth and obesity was determined comparing subjects with BMI<25 and BMI 25, and subjects with BMI<25 and BMI 30 respectively.

28 Association with obesity-related quantitative traits in the Inter99 cohort FTO rs associates with BMI, body weight and waist circumference No association with fasting serum lipids n (men/women) TT TA AA p Add p Dom p Rec 1,977 (969/1,008) 2,783 (1,423/1,360) 962 (461/501) Age (years) 46.2 ± ± ± 8 BMI (kg/m 2 ) 25.9 ± ± ± Height (m) 1.72 ± 0.9 1,73 ± ± Body weight (kg) 76.9 ± ± ± Waist circumference (cm) 85.6 ± ± ± Waist-to-hip ratio 0.85 ± ± ± Subjects with NGT, IFG, IGT and screen detected type 2 diabetes were included p-values were calculated using a general linear model adjusted for age and sex

29 Association with obesity-related quantitative traits in young healthy subjects FTO rs associates with BMI, body weight, waist circumference, fat mass, fat percent and fasting serum leptin No association with fasting serum lipids n (men/women) TT TA AA p Add p Dom p Rec 136 (67/69) 160 (79/81) 50 (19/31) Age (years) 24.7 ± ± ± 3 BMI (kg/m 2 ) 22.8 ± ± ± Height (m) 1.75 ± ± ± Body weight (kg) 69.8 ± ± ± Waist circumference (cm) 75.7 ± ± ± Fat mass (kg) 13.5 (10.1,18.3) 16.9 (11.4,23.1) 18.0 (14.2,24.3) Lean body mass (kg) 54.5 ± ± ± Fat percent 21.4 ± ± ± Fasting serum leptin (pmol/l) 6.5 (3.2,10.7) 6.9 (3.5,13.8) 9.7 (5.4,19.9) p-values were calculated using a general linear model adjusted for age and sex

30 Effect size of the FTO rs variant in groups with different glucose tolerance

31 Physical activity was self-reported by questionnaire. Subjects with NGT, IFG, IGT and screen detected type 2 diabetes were included Interaction between FTO rs and physical activity Number of subjects (TT/TA/AA) P int = 0.007

32 Insulin sensitivity was assessed by the BIGTT-Si index and stratified in tertiles. Subjects with NGT, IFG, IGT and screen detected type 2 diabetes were included Interaction between FTO rs and insulin sensitivity Number of subjects (TT/TA/AA) P int =

33 At least 11 validated type 2 diabetes genes/loci on July 1, 2007

34 Type 2 diabetes gene variants: How do they interrelate?? And do they predict type 2 diabetes? KCNJ11 PPARG TCF7L2

35 The risk of type 2 diabetes increases as a function of the number of risk alleles Studies of the combined effect of TCF7L2 rs , PPARG Pro12Ala and KCNJ11 Glu23Lys in 5,508 Danes T2D (n=1,056); control subjects (n=4,452) frequency Diabetes frequency dia145 Diabetes Odds ratio per risk allele (95 % CI): 1.27 ( ) p add = Odds ratio 0 risk-allele vs 6 risk-alleles: nr of 3 risk alleles number of risk alleles mean ± 95 % CI Numbers in each group (cases/controls): 0+1 risk alleles 55/278 2 risk alleles 207/ risk alleles 369/ risk alleles 303/ risk alleles 122/338

36 The predictive value of type 2 diabetes gene variants is still too modest Receiver Operator Characteristics Curve True positive rate (sensitivity) 1,0 0,8 No discrimination AUC = 0,5 0,6 0,4 ~ 20 gene variants (Yang, Am J Hum Genet 2003) Breast cancer screening AUC ~ 0,9 0,2 3 T2D AUC = 0, ,2 0,4 0,6 0,8 1,0 False positive rate (1 specificity)

37 Type 2 diabetes association statistics from the WELLCOME TRUST Case Control Consortium

38 Shortcommings of the HapMap concept and current chip based technology: rare gene variants, many of which may contribute with a high relative risk to diabetes, are not captured UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

39 Multiple rare risk alleles are involved in complex traits of metabolism Current GWA methods will not capture rare pathogenic variants of complex traits We need high-capacity whole-genome sequencing methods like Solexa in the immediate post-hapmap and post-gwa era UK-MVA Bioscience Alliance, Malmo Apr 23, 2007

40 Studies of the genetics of complex disorders: The march the development of technology of single variant (10 0 SNPs; 10 3 genotypes) detailed study of individual genes (10 2 SNPs; genotypes) regional studies (10 4 SNPs; 10 8 genotypes ) 2005 Post-GWA 2009? genome-wide association (10 6 SNPs; genotypes) complete resequencing (10 8 SNPs / genotypes)

41 And one more major challenge Are obesity and associated type 2 diabetes in part caused by pathogenic interplays between an altered bacterial flora in colon and multiple susceptibility genes in the human genome? Ley et al., Nature 444, 2006 Turnbaugh et al., Nature 444, 2006

42 Academics Torben Hansen Lars Hansen Søren M. Echwald Jakob Ek Yasmin Hamid Gitte Andersen Lesli H. Larsen Anders Johansen Sara K. Post Hansen Eva Maria D. Nielsen Kirstine L. Andersen Christian S. Rose Anette P. Gjesing Dorit P. Jensen Keiko Yanagisawa Lise Wegner Signe K. Torekov Niels Grarup Anders Albrectsen Oluf Pedersen Steno-type type 2 diabetes genetics group Technicians Annemette Formann Lene Aabo Inge Lise Wantzin Marianne Stendal Secretary Grete Lademann

43 Peter Dam, Tine Dalsgaard, Elisabeth Mathiesen, Thorkild I.A. Sørensen, Teis Andersen, Arne Astrup, Søren Toubro, Ole Schmitz, Jens Juul Holst, Thue Schwartz, Bjørn Richelsen, Knut Borch- Johnsen, Allan Vaag, Hans-Henrik Henrik Parving, Jørn Nerup, Thomas Mandrup Poulsen, Torben Jørgensen, J Andi Braun, Philippe Froguel, Mark M Carthy, Andrew Hattersley, Leif Group, M. Alan Permutt, Karsten Kristiansen WanJun Ivan Brandslund Cramer Christensen Aneta Nielsen Hans Eiberg, Pierre de Meyts, Henrik Mortensen, Hennning Beck- Nielsen Sten Madsbad, Ole Madsen, C. Ronald Kahn, Graeme Bell, Søren Urhammer, Hans Lithell, Toni Maasen, Hans Härring, Marku Laakso, Ulf Smith, T. Horikava, Henrik Vestergaard, Claus Ekstøm. Lars Hansen, Søren Echwald, David Alschuler, Joel Hirschorn, Andi Braun, Francis Collins EU research consortia: PARADIGM, GIFT, SINGLE CELL, NUGENOB, EUGENE2 EXGENESIS METAHIT

44 My problems really started when I discovered that burgers gave me just as much strength as spinach. THANK YOU FOR YOUR ATTENTION!!

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