Supplementary Figure 1. (a) A Q-Q plot of all the 310,520 uncorrected (red crosses) and corrected (blue star) chi-square statistics from the

Transcription

1 a b Supplementary Figure 1. (a) A Q-Q plot of all the 310,520 uncorrected (red crosses) and corrected (blue star) chi-square statistics from the single-point association. (b) Same as a except results for chromosome 8 have been omitted. The equiangular line (green) is displayed for reference purposes

2 Supplementary Methods Illumina Genome-Wide Genotyping All Icelandic case- and control-samples were assayed with the Infinium HumanHap300 SNP chips (Illumina, SanDiego, CA, USA), containing 317,503 haplotype tagging SNPs derived from phase I of the International HapMap project. Of the SNPs assayed on the chip, 2,906 SNPs had yield lower than 95%, 271 SNPs had the minor allele frequency, in the combined set of cases and controls, below 0.01 or were monomorphic. An additional 4,632 SNPs showed a significant distortion from Hardy-Weinberg equilibrium in the controls (P < 1x10-3 ). In total, 6,983 unique SNPs were removed from the study. Thus, the analyses reported in the main text utilizes 310,520 SNPs. Any samples with a call rate below 98% were excluded from the analysis. Single SNP Genotyping. Single SNP genotyping for all samples was carried out at decode genetics in Reykjavik, Iceland applying the same platform to all populations studied. SNP genotyping was carried out by the Centaurus (Nanogen) platform 1 (see Supplementary Table 2a for assays used for genotyping of SNPs in Tables 2-5). The quality of each Centaurus SNP assay was evaluated by genotyping each assay in the CEU and/or YRI HapMap samples and comparing the results with the HapMap data. Assays with >1.5% mismatch rate were not used and a linkage disequilibrium (LD) test was used for markers known to be in LD. For key markers we re-genotyped more than 10% of samples and observed a mismatch rate lower than 0.5%. Association Analysis. For both single-marker and haplotype analyses, the main results were calculated assuming a multiplicative model for risk, i.e., that the risks of the two alleles/haplotypes a person carries multiply. For example, if RR is the risk of A relative to a, then the risk of a person homozygote AA will be RR times that of a heterozygote Aa and RR 2 times that of a homozygote aa. The multiplicative model has a nice property that simplifies analysis and computations haplotypes are independent, i.e., in Hardy-Weinberg equilibrium, within the affected population as well as within the control population. As a consequence, allele/haplotype counts of the affecteds and controls each have multinomial distributions, but with different 1

3 haplotype frequencies under the alternative hypothesis. Specifically, for two haplotypes h i and h j, risk(h i )/risk(h j ) = (f i /p i )/(f j /p j ), where f and p denote frequencies in the affected population and in the control population, respectively. While there is some power loss if the true model is not multiplicative, the loss tends to be mild except for extreme cases. Most importantly, p-values are always valid since they are computed with respect to the null hypothesis. In general, haplotype frequencies are estimated by maximum likelihood and tests of differences between cases and controls are performed using a generalized likelihood ratio test 2. As demonstrated below, this method could also be used in situations where single marker association is of interest, but there are some missing genotypes for the marker of interest and genotypes of another marker are used to provide some partial information. Our haplotype analysis program called NEMO, which stands for NEsted MOdels, was used to calculate all the haplotype results presented. To handle uncertainties with phase and missing genotypes, it is emphasized that we do not use a common two-step approach to association tests, where haplotype counts are first estimated, possibly with the use of the EM algorithm, and then tests are performed treating the estimated counts as though they are true counts, a method that can sometimes be problematic and may require randomization to properly evaluate statistical significance. Instead, with NEMO, maximum likelihood estimates, likelihood ratios and p-values are computed directly for the observed data, and hence the loss of information due to uncertainty in phase and missing genotypes is automatically captured by the likelihood ratios. Haplotype Groups and Nested Models. When investigating haplotypes constructed from multiple markers, apart from looking at each haplotype individually, meaningful summaries often require more complex risk models. A series of bipartitions, that each assigns risk 1 to one part of the haplotype space and a risk different from 1 to the other part, form a model by assigning to each haplotype risk equaling the product of the risks associated with the part of each bipartition which the haplotype belongs. More precisely, let A 1, A 2,, A n be proper non-empty subsets of the haplotype space and r 1, r 2,, r n be the corresponding risk values, then for each haplotype h the model assigns risk s 1 s 2 s n to h, where, for i = 1, 2,, n, s i is r i if h is in A i and 1 otherwise,. Two models, each defined by a series of bipartitions and risk values, are nested when one series, the null 2

4 model, is a sub-series of the other, the alternative model, i.e., the alternative model allows some haplotypes assumed to have the same risk in the null model to have different risks. The models are nested in the classical sense that the null model is a special case of the alternative model. Hence traditional generalized likelihood ratio tests can be used to test the null model against the alternative model. The degrees of freedom of the test are the difference of the number of elements in the series under the alternative hypothesis and the null hypothesis. Note that, with a multiplicative model, if haplotypes h i and h j are assumed to have the same risk, it corresponds to assuming that f i /p i = f j /p j where f and p denote haplotype frequencies in the affected population and the control population respectively. PCR screening of cdna libraries. To confirm the expression of the TCF2 and the spliced ESTs (BC039327) within the kb LD block at 17q24.3, we screened commercially available cdna libraries and libraries generated at decode. The commercial libraries screened were Prostate Marathon-Ready cdna library (Clontech Cat ) and Bone marrow-ready cdna library (Clontech Cat ). In addition cdna libraries were constructed for fresh frozen normal- and tumor prostate tissue, whole blood and EBV-transformed human lymphoblastoid cells. Total RNA was isolated from the lymphoblastoid cell lines and whole blood, using the RNeasy RNA isolation kit from Qiagen (Cat ) and the RNeasy RNA isolation from whole blood kit (Cat ), respectively. RNA was isolated from fresh-frozen prostate tissue sections by homogenizing 30 mg of tissue in Tri Reagent from Molecular Research Centre (Cat. TR 118) followed by RNA isolation according to the manufacturer s instructions. RNA was subsequently analyzed and quantified using the Agilent 2001 Bioanalyser. cdna libraries were prepared at decode using a random hexamer protocol from the RevertAidTM H Minus First Strand cdna Synthesis Kit (Fermentas Cat. K1631). Taqman expression assays from ABI were used to confirm the expession of TCF2 (Hs _m1) but to screen for expression of the spliced EST (BC039327) we used the Advantage 2 PCR Enzyme RT _PCR System (Clontech) according to manufacturers instructions and PCR primers from Operon Biotechnologies. The PCR reactions were done in 10ul volume at a final concentration of 3,5 µm of forward and reverse primers, 2mM dntp, 1x Advantage 2 PCR buffer and 0,5ul of cdna library (See Supplementary Table 2b). 3

5 REFERENCES 1. Kutyavin, I.V. et al. A novel endonuclease IV post-pcr genotyping system. Nucleic Acids Research 34, e128 (2006). 2. Rice, J. Mathematical Statistics and Data Analysis, (Wadsworth Inc., Belmont, CA, 1995). 3. Gretarsdottir, S. et al. The gene encoding phosphodiesterase 4D confers risk of ischemic stroke. Nat Genet 35, (2003). 4. Pritchard, J.K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, (2000). 4

6 Supplementary Note Results for Icelandic prostate cancer-cases after removing individuals with type 2 diabetes To eliminate the concern that the associations of rs and rs to prostate cancer were in part a by-product of an association to T2D, we repeated the prostate cancer association analysis after removing all known diabetics from the Icelandic prostate cancer case-control group. For the resulting 1,444 cases and 9,917 controls, the association for rs C and rs A was practically unchanged; rs had an OR of 1.16 for the Icelandic samples alone (P = ), and 1.19 (P = ) when results of all four case-control groups were combined; whereas rs had an OR of 1.18 (P = ) in the Icelandic samples and an OR of 1.21 (P = ) in the combined group. Description of the type 2 diabetes study populations Icelandic study population The Icelandic type 2 diabetes case-control group has been described previously 1. A total of 1500 type 2 diabetes patients were recruited for this genome-wide association study, using the Infinium II assay method and the Sentrix HumanHap300 BeadChip (Illumina, San Diego, CA, USA). Thereof, 1399 were successfully genotyped according to our quality control criteria (see Supplementary Methods) and used in the present case control-analysis; 531 of the genotyped cases were obese (BMI 30). The controls were the same as for the prostate cancer study but all known type 2 diabetes cases were excluded. The study was approved by the Data Protection Commission of Iceland and the National Bioethics Committee of Iceland. Written informed consent was obtained from all cases and controls. Personal identifiers associated with medical information and blood samples were encrypted with a third-party encryption system as previously described 2. Other study populations The Danish female study group of 282 cases and 629 controls, herein termed Denmark A, was selected from the Prospective Epidemiological Risk Factor (PERF) study in Denmark 3. The original study population of 8502 postmenopausal women, years old (a mean age of

7 63.7±8.1 years) was recruited between 1977 to 1997 using large questionnaire surveys that invited women to participate in screening for various placebo-controlled clinical trials and epidemiological studies performed at the Center for Clinical and Basic Research. In , a follow-up examination was performed on 5847 women. At the follow-up, medical history including diabetes type I and type II, family history, and current or previous long-term use of drugs were gathered during personal interviews using a preformed questionnaire. If subject was diagnosed as diabetes of either type I or type II, the time of diagnosis or treatment was also collected. The second Danish study population of 1359 type 2 diabetes cases and 4858 control individuals with normal glucose tolerance was from the Steno Diabetes Center in Copenhagen and from the Inter99 population-based sample of 30- to 60-year-old individuals living in the greater Copenhagen area and sampled at Research Centre for Prevention and Health 4. This data set is referred to in the text as Denmark B. Diabetes and pre-diabetes categories were diagnosed according to the 1999 World Health Organization (WHO) criteria. Informed written consent was obtained from all subjects before participation. The study was approved by the Ethical Committee of Copenhagen County and was in accordance with the principles of the Helsinki Declaration. The Philadelphia study population consisted of 468 type 2 diabetes cases and 1024 control individuals. The study population was selected from the PENN CATH study, a cross-sectional study of the association of biochemical and genetic factors to coronary atherosclerosis in a study population of consecutive individuals undergoing cardiac catheterization at the University of Pennsylvania Medical Center. Type 2 diabetes was defined as a history of fasting blood glucose 126 mg dl -1, 2 h postprandial glucose 200 mg dl -1, use of oral hypoglycemic agents, or use of insulin and oral hypoglycemic in a subject older than age 40. The University of Pennsylvania Institutional Review Board approved the study protocol, and all subjects gave written informed consent. All cases and controls were of European ancestry. Ethnicity was determined through self-report. The Dutch Breda study population consisted of 370 type 2 diabetes cases and 916 control individuals. The cases were recruited in in collaboration with the Diabetes Service Breda and 80 general practitioners from the region around Breda. All patients are diagnosed according to WHO criteria (plasma glucose levels >11.1 mmol/l or a fasting plasma glucose

8 level 7.0 mmol/l), and undergo clinical and laboratory evaluations for their diabetes at regular 3-month intervals. The Medical Ethics Committee of the University Medical Centre in Utrecht approved the study protocol. All probands filled out an informed consent and a questionnaire on clinical data, including their diabetes related medication, height and weight at present and at the age of 20 year. The controls are Dutch blood bank donors of white Dutch origin. The Scottish study population consisted of type 2 diabetic cases and non-diabetic controls from the Wellcome Trust UK type 2 diabetes case-control collection (Go-DARTS2) which is a sub-study of Diabetes Audit and Research Tayside (DARTS) 5. All type 2 diabetes patients were physician-diagnosed type 2 diabetes cases recruited at primary or secondary care diabetes clinics, or invited to participate from primary care registers and have not been characterized for GAD anti-bodies or MODY gene mutations. The controls were invited to participate through the primary care physicians or through their workplace occupational health departments. Controls did not have a previous diagnosis of diabetes, but the glucose tolerance status of the controls is unknown. All individuals in this ongoing study were recruited in Tayside between October 2004 and July This study was approved by the Tayside Medical Ethics Committee and informed consent was obtained from all subjects. All subjects in the Hong Kong study population were of southern Han Chinese ancestry residing in Hong Kong. The cases consisted of 1500 cases with type 2 diabetes selected from the Prince of Wales Hospital Diabetes Registry 6. Of these, 682 patients were selected for having young-onset diabetes (age-at-diagnosis 40 years) with positive family history. An additional 818 cases were randomly selected from the same registry irrespective of age-atdiagnosis. A total of 776 patients had young-onset diabetes. A previous study in a group of young onset diabetic patients with nephropathy found that TCF2 mutations were rare in this population 7. The controls consisted of 1000 subjects with normal glucose tolerance (fasting plasma glucose < 6.1 mmol/l). Of these, 617 were recruited from the general population participating in a community-based cardiovascular risk screening program as well as hospital staff. In addition, 383 subjects were recruited from a cardiovascular risk screening program for adolescents. Informed consent was obtained for each participating subject. This study was approved by the Clinical Research Ethics Committee of the Chinese University of Hong Kong.

9 The African study population comes from the Africa America Diabetes Mellitus study, which was originally designed as an affected sibling pair study with enrollment of available spouses as controls. It has since been expanded to include other family members of the affected pairs and population controls. Recruitment strategies and eligibility criteria for the families enrolled in this report have been described previously 8. This West African case-control series consisted of individuals from the Yoruba (233 affected individuals, 432 controls) and Igbo (237 affected individuals, 276 controls) groups from Nigeria and the Akan (257 affected individuals, 248 controls), Ewe (22 affected individuals, 30 controls) and Gaa-Adangbe (123 affected individuals, 141 controls) groups from Ghana. With the exception of the Scottish Go-DARTS study population the DNA used for genotyping in all replication study populations was the product of whole-genome amplification (GenomiPhi Amplification kit, Amersham) of DNA isolated from the peripheral blood.

10 Characteristics of the eight T2D case-controls groups used in the paper have been summarized in a table below. The table includes the number of males and females, mean age, mean BMI and mean age of diagnosis (Aod) for the T2D cases and the controls separately. As information on BMI and age of diagnosis is not available for all study participants, the number of individuals for whom this information is available is included in parenthesis. Note that no information is available on BMI for the controls from the Netherlands, and information on age of diagnosis is not available for the T2D cases from Denmark A, Philadelphia and from West-Africa. Study population Males/Females Mean Age ± SD Mean BMI ± SD (n) a Mean Aod ± SD (n) a Iceland T2D 832/ ± ± 5.4 (1231) 56.2 ± 12.3 (688) Controls 2743/ ± ± 4.9 (1751) Denmark A T2D 0/ ± ± 4.1 (263) na Controls 0/ ± ± 3.7 (596) Denmark B T2D 821/ ± ± 5.3 (1343) 52.1 ± 10.3 (1013) Controls 2249/ ± ± 4.1 (4824) Philadelphia T2D 288/ ± ± 5.8 (380) na Controls 629/ ± ± 4.8 (861) The Netherlands T2D 169/ ± ± 4.2 (363) 63.2 ± 11.5 (356) Controls b 553/ ± 12.7 na Scotland T2D 2076/ ± ± 6.2 (3714) 57.4 ± 11.5 (3616) Controls 1937/ ± ± 4.5 (3715) Hong Kong T2D 604/ ± ± 4.1 (1451) 43.8 ± 13.7 (1443) Controls 423/ ± ± 3.5 (979) West Africa T2D 345/ ± ± 5.5 (862) na Controls 471/ ± ± 5.9 (1091) a The number in parenthesis (n) indicates the number of individuals for which information on BMI or age of diagnosis is available. b Information on gender is missing for 9 of the controls from the Netherlands.

11 References 1. Reynisdottir, I. et al. Localization of a susceptibility gene for type 2 diabetes to chromosome 5q34-q35.2. Am J Hum Genet 73, (2003). 2. Gulcher, J.R., Kristjansson, K., Gudbjartsson, H. & Stefansson, K. Protection of privacy by third-party encryption in genetic research in Iceland. Eur J Hum Genet 8, (2000). 3. Tanko, L.B., Bagger, Y.Z., Nielsen, S.B. & Christiansen, C. Does serum cholesterol contribute to vertebral bone loss in postmenopausal women? Bone 32, 8-14 (2003). 4. Jorgensen, T. et al. A randomized non-pharmacological intervention study for prevention of ischaemic heart disease: baseline results Inter99. Eur J Cardiovasc Prev Rehabil 10, (2003). 5. Morris, A.D. et al. The diabetes audit and research in Tayside Scotland (DARTS) study: electronic record linkage to create a diabetes register. DARTS/MEMO Collaboration. Bmj 315, (1997). 6. Yang, X. et al. Development and validation of stroke risk equation for Hong Kong Chinese patients with type 2 diabetes: the Hong Kong Diabetes Registry. Diabetes Care 30, (2007). 7. So, W.Y. et al. Genetic variants of hepatocyte nuclear factor-1beta in Chinese youngonset diabetic patients with nephropathy. J Diabetes Complications 17, (2003). 8. Rotimi, C.N. et al. In search of susceptibility genes for type 2 diabetes in West Africa: the design and results of the first phase of the AADM study. Ann Epidemiol 11, 51-8 (2001).

12 Supplementary Table 1. Linkage disequilibrium characteristics between markers located on 17q12 and 17q q12 17q24.3 Location Name rs rs rs rs rs rs rs q12 17q24.3 r 2 D' r 2 D' r 2 D' r 2 D' r 2 D' r 2 D' r 2 D' rs rs rs rs rs rs rs Values show correlation results for markers both within and between the two loci. Results are based on the 11,290 Icelandic control samples.

13 Supplementary Table 2a. Centaurus assays used for individual genotyping of SNPs reported in the main text SNP Name rs Forward primer: GGGAAAACTAGTTTCAGGTGAA Reverse primer: GACATATTTAAAGGCGCCATTTAG VIC-Probe: GAAATAGATACAGT FAM-Probe: GAAATAGATACAGC Enhancer: TTGCAACATAATAAGCAAT SNP Name Forward primer: Reverse primer: VIC-Probe: FAM-Probe: Enhancer: SNP Name Forward primer: Reverse primer: VIC-Probe: FAM-Probe: Enhancer: SNP Name Forward primer: Reverse primer: VIC-Probe: FAM-Probe: Enhancer: SNP Name Forward primer: Reverse primer: VIC-Probe: FAM-Probe: Enhancer: SNP Name Forward primer: Reverse primer: VIC-Probe: FAM-Probe: Enhancer: rs GCACTATTGGAGTTTCACCTGCTT AGCAAAGAAGCCCCTTTCCCTGTT CCCAAACCG GCCCAAACCT CAAGCTAGGACCT rs GCCCCATTATTAGAAATCTTGGGACCTT GAACACCTTGGACCAGTTCTTGAT GTTCATCACAC GTTCATCCCAC GGCAGGGATTTG rs GGAACCTACAGAAGGGTGCCAAAT CTGGGTTCTCGTTAGATTCAGCCAA TCCTCGTTATCA TCCTCGTCATCA TAATCTGCCAAGCCT rs GTACCACCTATTACTACTGTATATAAACAT CTGGATCCCACAAAGTAAGTCTG TCAAGTGTGGTA GTCAAGTATGGTA AAATATTTTCACCTCATTAG rs CATTGAATACAGAGAGGCAGCACAG TCAGGAGCCATTGTCTCCAAAGAC TGGAGATGCTG CTGGAAATGCTG ATAAAGCTTAAATTGGG Supplementary Table 2b. Primers used for PCR screening of cdna libraries ESTs* Forward primer Reverse primer BC st PCR TGAGGAGGTGGCTATGATGGTAGAA GCCAGAGAATGAGTGTGAATCTTCC BC nested AACACAGAAGGAAACAATGCCAAGA PCR *EST names are from NCBI BUILD 35. CTTCCTGCTCAGATTAGAGGCTTGG

14 Supplementary Table 3a. Genotype counts for rs , rs and rs in all prostate cancer study populations Marker Study population Cases Controls rs C/C C/T T/T C/C C/T T/T Iceland ,709 5,579 1,955 The Netherlands Spain Chicago, U.S rs A/A A/G G/G A/A A/G G/G Iceland The Netherlands Spain Chicago, U.S rs G/G G/T T/T G/G G/T T/T Iceland ,334 5,487 3,394 The Netherlands Spain Chicago US Supplementary Table 3b. Genotype counts for rs and rs in all type 2 diabetes study populations Marker Cases Controls Study population rs C/C C/T T/T C/C C/T T/T Iceland ,299 4,903 1,682 Denmark A Denmark B ,684 2, Philadelphia The Netherlands Scotland 1,368 1, ,390 1, Hong Kong West Africa rs A/A A/G G/G A/A A/G G/G Iceland Denmark A Denmark B ,322 2,298 1,038 Philadelphia The Netherlands Scotland 994 1, ,037 1, Hong Kong West Africa