Presentation is loading. Please wait.

Presentation is loading. Please wait.

Common Disease Findings (case study on diabetes) GWAS Workshop Francis S. Collins, M.D., Ph.D. National Human Genome Research Institute May 1, 2007.

Published byViolet Todd Modified over 9 years ago

Similar presentations

Presentation on theme: "Common Disease Findings (case study on diabetes) GWAS Workshop Francis S. Collins, M.D., Ph.D. National Human Genome Research Institute May 1, 2007."— Presentation transcript:

1 Common Disease Findings (case study on diabetes) GWAS Workshop Francis S. Collins, M.D., Ph.D. National Human Genome Research Institute May 1, 2007

2 No Data <4% 4-4.9% 5-5.9% ≥6% 1994 2004 Estimates of Diagnosed Diabetes Among Adults in the U.S.

3 Diabetes Pathophysiology Genetic Predisposition Environment genetic defects Beta-cell Dysfunction Insulin Resistance impaired insulin secretion poor glucose utilization obesity TYPE 2 DIABETES BETA-CELL EXHAUSTION HYPERGLYCEMIA

4 Type 2 Diabetes: “The geneticist’s nightmare” Family history as a substantial risk factor –Relative risk to a sibling ~3 Environment as a major contributor Family linkage studies relatively disappointing Validated genes prior to 2007: –PPARG (candidate gene) –KCNJ11 (candidate gene) –TCF7L2 (linkage study)

5 Applying Genome Wide Association to Type 2 Diabetes Three groups, each with 1000 – 1500 cases and 1000 – 3000 controls in Stage 1: –FUSION (Boehnke, Bergman, Collins, Mohlke, Tuomilehto) –Diabetes Genetics Initiative of Broad, Novartis, and Lund (Altshuler, Groop) –Wellcome Trust Case Control Consortium/UK Type 2 Diabetes Consortium (McCarthy, Hattersley, Donnelly) Genotyped with Illumina 317K or Affy 500K panel Compared results across all three studies Followed up promising signals in Stage 2 validation set

6 FUSION Two-Stage GWA Study of T2D Stage 1: GWA Stage 2: Validation of best hits Cases NGT ControlsTotal Familial / population-based cases (%) Stage 111611174233568/32 Stage 21215125824890/100 Total23922432482427/73 80% power to detect: Stage 1: OR = 1.4 - 1.5 Stage 1 + 2: OR = 1.3 - 1.4

7 317,503 SNPs genotyped on Illumina HumanHap300 BeadChip at the Center for Inherited Disease Research (CIDR) Dropped 1,868 SNPs from analysis Failed to meet expectations for Hardy-Weinberg < 90% successful genotypes > 3 Mendelian or duplicate sample errors < 10 detections of the rare allele GWA Genotyping of Stage 1 Samples

8 FUSION Stage 1 Association Results -log 10 (p-value) 1161 Finnish T2D cases + 1174 Finnish normal glucose tolerant controls No results meet genome-wide significance (p < 1.7 x 10 -7 )

9 Known associations can serve as positive controls -log 10 (p-value) TCF7L2KCNJ11PPARG 1161 Finnish T2D cases + 1174 Finnish normal glucose tolerant controls

10 Three Groups Working Together Sweden Poland United States (off map) # cases + controls FUSION S1: 1161 + 1174 S2: 1215 + 1258 DGI S1: 1464 + 1467 S2: 5065 + 5785 WTCCC/UKT2D S1: 1924 + 2938 S2: 3757 + 5346 Totals S1 = 4549 + 5579 S2 = 10053 + 12389 (n=32,554)

11 Combined Results Now Highly Significant -log 10 (p-value) Chromosome 15 10 5 0 49 TCF7L2 KCNJ11 PPARG //

12 Top 10 Results From Combined Analysis FUSIONDGIWTCCC/UKT2DAll Samples GeneORp-valueORp-valueORp-valueORp-value TCF7L21.341.3 x 10 -8 1.382.3 x 10 -31 1.376.7 x 10 -13 1.371.0 x 10 -48 IGF2BP21.182.1 x 10 -4 1.171.7 x 10 -9 1.111.6 x 10 -4 1.148.9 x 10 -16 CDKN2A/B1.20.00221.205.4 x 10 -8 1.194.9 x 10 -7 1.207.8 x 10 -15 FTO1.110.0161.030.251.237.3 x 10 -14 1.171.3 x 10 -12 CDKAL11.120.00951.080.00241.161.3 x 10 -8 1.124.1 x 10 -11 KCNJ111.110.0131.151.0 x 10 -7 1.150.00131.146.7 x 10 -11 HHEX1.100.0261.141.7 x 10 -4 1.134.6 x 10 -6 1.135.7 x 10 -10 SLC30A81.187.0 x 10 -5 1.070.0471.127.0 x 10 -5 1.125.3 x 10 -8 Chr 111.485.7 x 10 -8 1.160.121.130.0681.234.3 x 10 -7 PPARG1.200.00141.090.0191.230.00131.141.7 x 10 -6

13

14

15 Top 10 Results From Combined Analysis FUSIONDGIWTCCC/UKT2DAll Samples GeneORp-valueORp-valueORp-valueORp-value TCF7L21.341.3 x 10 -8 1.382.3 x 10 -31 1.376.7 x 10 -13 1.371.0 x 10 -48 IGF2BP21.182.1 x 10 -4 1.171.7 x 10 -9 1.111.6 x 10 -4 1.148.9 x 10 -16 CDKN2A/B1.20.00221.205.4 x 10 -8 1.194.9 x 10 -7 1.207.8 x 10 -15 FTO1.110.0161.030.251.237.3 x 10 -14 1.171.3 x 10 -12 CDKAL11.120.00951.080.00241.161.3 x 10 -8 1.124.1 x 10 -11 KCNJ111.110.0131.151.0 x 10 -7 1.150.00131.146.7 x 10 -11 HHEX1.100.0261.141.7 x 10 -4 1.134.6 x 10 -6 1.135.7 x 10 -10 SLC30A81.187.0 x 10 -5 1.070.0471.127.0 x 10 -5 1.125.3 x 10 -8 Chr 111.485.7 x 10 -8 1.160.121.130.0681.234.3 x 10 -7 PPARG1.200.00141.090.0191.230.00131.141.7 x 10 -6

16

17 Top 10 Results From Combined Analysis FUSIONDGIWTCCC/UKT2DAll Samples GeneORp-valueORp-valueORp-valueORp-value TCF7L21.341.3 x 10 -8 1.382.3 x 10 -31 1.376.7 x 10 -13 1.371.0 x 10 -48 IGF2BP21.182.1 x 10 -4 1.171.7 x 10 -9 1.111.6 x 10 -4 1.148.9 x 10 -16 CDKN2A/B1.20.00221.205.4 x 10 -8 1.194.9 x 10 -7 1.207.8 x 10 -15 FTO1.110.0161.030.251.237.3 x 10 -14 1.171.3 x 10 -12 CDKAL11.120.00951.080.00241.161.3 x 10 -8 1.124.1 x 10 -11 KCNJ111.110.0131.151.0 x 10 -7 1.150.00131.146.7 x 10 -11 HHEX1.100.0261.141.7 x 10 -4 1.134.6 x 10 -6 1.135.7 x 10 -10 SLC30A81.187.0 x 10 -5 1.070.0471.127.0 x 10 -5 1.125.3 x 10 -8 Chr 111.485.7 x 10 -8 1.160.121.130.0681.234.3 x 10 -7 PPARG1.200.00141.090.0191.230.00131.141.7 x 10 -6

18

19 How could IGF2BP2 be related to diabetes? IGF2BP2 codes for the insulin-like growth factor 2 mRNA binding protein 2 But we know very little about what this does A related gene, IGF2BP1, codes for a protein that binds to the upstream leader sequence of the insulin- like growth factor 2 (IGF2) mRNA and regulates IGF2 protein production IGF2 is involved in development, growth, and stimulation of insulin action

20 rs13266634 is in the coding region of SLC30A8, and changes a highly conserved arginine to a tryptophan

21 SLC30A8 - Beta Cell Zinc Transporter Chimienti (2005) BioMetals 18:313

22 SNPs Upstream of CDKN2A/B Cyclin-dependent kinase inhibitors CDKN2A and CDKN2B, also known as p16INK4a and p15INK4b Inhibit the activity of cyclin-dependent protein kinases CDK4 and CDK6, have been implicated repeatedly in cancer. Cdk4 activity also influences beta cell proliferation and mass in mice; loss of Cdk4 leads to diabetes

23

24 Embargoed until 5 PM Thursday May 3!

25

26

27

28

29 SNPs Within Introns of CDKAL1 CDK5 regulatory subunit associated protein 1-like 1 Shares protein domain similarity with CDK5RAP1, which inhibits CDK5 CDK5 activity is influenced by glucose, stimulates insulin gene transcription, and may influence other beta cell processes Over activity of CDK5 in pancreas may lead to beta cell degeneration

Download ppt "Common Disease Findings (case study on diabetes) GWAS Workshop Francis S. Collins, M.D., Ph.D. National Human Genome Research Institute May 1, 2007."

Similar presentations

Global Drug Development To Bridge or Not to Bridge.

Global Drug Development To Bridge or Not to Bridge.
Linkage and Genetic Mapping

Linkage and Genetic Mapping
What is an association study? Define linkage disequilibrium

What is an association study? Define linkage disequilibrium
Genome-wide Association Studies John S. Witte. Association Studies Hirschhorn & Daly, Nat Rev Genet 2005 Candidate Gene or GWAS.

Genome-wide Association Studies John S. Witte. Association Studies Hirschhorn & Daly, Nat Rev Genet 2005 Candidate Gene or GWAS.
Genetic Analysis in Human Disease

Genetic Analysis in Human Disease
Four of the many different types of human cells: They all share the same genome. What makes them different?

Four of the many different types of human cells: They all share the same genome. What makes them different?
Office hours Wednesday 3-4pm 304A Stanley Hall. Fig. 11.26 Association mapping (qualitative)

Office hours Wednesday 3-4pm 304A Stanley Hall. Fig Association mapping (qualitative)
Diabetes Genome Wide Association Alessandra C Goulart Ida Hatoum Stalo Karageorgi Mara Meyer EPI293 January 2008 Harvard School of Public Health Alessandra.

Diabetes Genome Wide Association Alessandra C Goulart Ida Hatoum Stalo Karageorgi Mara Meyer EPI293 January 2008 Harvard School of Public Health Alessandra.
Aspects of Genetics and Genomics in Cancer Research Li Hsu Biostatistics and Biomathematics Program Fred Hutchinson Cancer Research Center.

Aspects of Genetics and Genomics in Cancer Research Li Hsu Biostatistics and Biomathematics Program Fred Hutchinson Cancer Research Center.
ISGMW Workshop, Leuven Aug 15, 2008 Thinking big: Finding more and (more) genes influencing glycaemic and anthropometric traits Mark McCarthy, Oxford.

ISGMW Workshop, Leuven Aug 15, 2008 Thinking big: Finding more and (more) genes influencing glycaemic and anthropometric traits Mark McCarthy, Oxford.
Positional Cloning LOD Sib pairs Chromosome Region Association Study Genetics Genomics Physical Mapping/ Sequencing Candidate Gene Selection/ Polymorphism.

Positional Cloning LOD Sib pairs Chromosome Region Association Study Genetics Genomics Physical Mapping/ Sequencing Candidate Gene Selection/ Polymorphism.
Office hours Wednesday 3-4pm 304A Stanley Hall Review session 5pm Thursday, Dec. 11 GPB100.

Office hours Wednesday 3-4pm 304A Stanley Hall Review session 5pm Thursday, Dec. 11 GPB100.
Genomewide Association Studies.  1. History –Linkage vs. Association –Power/Sample Size  2. Human Genetic Variation: SNPs  3. Direct vs. Indirect Association.

Genomewide Association Studies.  1. History –Linkage vs. Association –Power/Sample Size  2. Human Genetic Variation: SNPs  3. Direct vs. Indirect Association.
SNPs DNA differs between humans by 0.1%, (1 in 1300 bases) This means that you can map DNA variation to around 10,000,000 sites in the genome Almost all.

SNPs DNA differs between humans by 0.1%, (1 in 1300 bases) This means that you can map DNA variation to around 10,000,000 sites in the genome Almost all.
Type 2 Diabetes With type 2 diabetes, your body either resists the effects of insulin — a hormone that regulates the movement of sugar into your cells.

Type 2 Diabetes With type 2 diabetes, your body either resists the effects of insulin — a hormone that regulates the movement of sugar into your cells.
Genetics of Diabetes Jan Dorman, PhD University of Pittsburgh

Genetics of Diabetes Jan Dorman, PhD University of Pittsburgh
Low birth weight Zahra N. Sohani Supervisor: Dr. Sonia Anand.

Low birth weight Zahra N. Sohani Supervisor: Dr. Sonia Anand.
GENETIC FACTORS IN DIABETES MELLITUS. Birmingham Study A random sample of 4886 birth. Comparison between the most valid data: 2432North European babies.

GENETIC FACTORS IN DIABETES MELLITUS. Birmingham Study A random sample of 4886 birth. Comparison between the most valid data: 2432North European babies.
Design Considerations in Large- Scale Genetic Association Studies Michael Boehnke, Andrew Skol, Laura Scott, Cristen Willer, Gonçalo Abecasis, Anne Jackson,

Design Considerations in Large- Scale Genetic Association Studies Michael Boehnke, Andrew Skol, Laura Scott, Cristen Willer, Gonçalo Abecasis, Anne Jackson,
Malignant Melanoma and CDKN2A

Malignant Melanoma and CDKN2A

Similar presentations

Ads by Google