Association of Common Variation in the HNF1 Gene Region With Risk of Type 2 Diabetes
http://www.100md.com
糖尿病学杂志 2005年第8期
1 Department of Molecular Biology, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
2 Department of Genetics, Harvard Medical School, Boston, Massachusetts
3 Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
4 Department of Endocrinology, University Hospital MAS, Lund University, Malm, Sweden
5 Department of Medicine, Helsinki University Central Hospital, Folkhalsan Genetic Institute, Folkhalsan Research Center, and Research Program for Molecular Medicine, University of Helsinki, Helsinki, Finland
6 University of Montreal Community Genomic Center, Chicoutimi Hospital, Montreal, Quebec, Canada
7 McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada
8 Genomics Collaborative, Inc., Cambridge, Massachusetts
9 Divisions of Genetics and Endocrinology, Children’s Hospital, Boston, Massachusetts
10 Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
11 Department of Medicine, Harvard Medical School, Boston, Massachusetts
ABSTRACT
It is currently unclear how often genes that are mutated to cause rare, early-onset monogenic forms of disease also harbor common variants that contribute to the more typical polygenic form of each disease. The gene for MODY3 diabetes, HNF1, lies in a region that has shown linkage to late-onset type 2 diabetes (12q24, NIDDM2), and previous association studies have suggested a weak trend toward association for common missense variants in HNF1 with glucose-related traits. Based on genotyping of 79 common SNPs in the 118 kb spanning HNF1, we selected 21 haplotype tag single nucleotide polymorphisms (SNPs) and genotyped them in >4,000 diabetic patients and control subjects from Sweden, Finland, and Canada. Several SNPs from the coding region and 5' of the gene demonstrated nominal association with type 2 diabetes, with the most significant marker (rs1920792) having an odds ratio of 1.17 and a P value of 0.002. We then genotyped three SNPs with the strongest evidence for association to type 2 diabetes (rs1920792, I27L, and A98V) in an additional 4,400 type 2 diabetic and control subjects from North America and Poland and compared our results with those of the original sample and of Weedon et al. None of the results were consistently observed across all samples, with the possible exception of a modest association of the rare (3eC5%) A98V variant. These results indicate that common variants in HNF1 either play no role in type 2 diabetes, a very small role, or a role that cannot be consistently observed without consideration of as yet unmeasured genetic or environmental modifiers.
Type 2 diabetes is a common human disease that is influenced by both genetic and environmental factors. As in most common diseases, very few variants have been rigorously proven to play a role in the common form of type 2 diabetes. Well-demonstrated examples of late-onset diabetes genes include the Pro12Ala polymorphism in the peroxisome proliferatoreCactivated receptor , the E23K polymorphism in the Kir6.2 gene (both rev. in 1) (2), and single nucleotide polymorphism (SNP) 44 in the region of calpain-10 (3,4). Experience with these and other complex diseases suggests that gene effects may often be modest, so very large study populations are required to achieve statistically significant, reproducible results (5eC9).
Maturity-onset diabetes of the young (MODY) is a rare autosomal-dominant form of type 2 diabetes that is characterized by early onset and a defect in the function of the -cells in the pancreas (10). Six genes are known to cause MODY (11eC16), with mutations in the MODY3 gene (HNF1) accounting for the majority of MODY families. In addition to its role in monogenic diabetes, several lines of evidence suggest that HNF1 is a particularly interesting candidate gene to influence the common, late-onset form of type 2 diabetes. It is located directly under linkage peaks in two genome-wide linkage scans for the common form of type 2 diabetes (17,18). The G319S missense variant (common in the Canadian Oji-Cree, although not found elsewhere) is strongly associated with a late-onset form of type 2 diabetes in that population (19). Additionally, the common I27L missense variant in HNF1 was reported to be an independent determinant of -cell function in healthy individuals (20). HNF1 has been resequenced in many diabetic patients, but published studies have yet to show a strong and consistent genetic effect on the common form of type 2 diabetes (21eC26). However, these studies were typically modest in size, and thus could not validate or rule out small effects of individual variants. Additionally, to our knowledge only the coding region had previously been surveyed, leaving open the possibility that noncoding (presumably regulatory) variants in HNF1 might play a role.
To more comprehensively characterize genotype-phenotype correlation at this gene locus with regard to the common form of type 2 diabetes, we characterized linkage disequilibrium (LD) patterns in a reference panel, selected tag SNPs that capture the vast majority of common variants at this locus, and genotyped these markers in a large collection of type 2 diabetic and control subjects.
RESEARCH DESIGN AND METHODS
The characteristics of our patient samples have been described elsewhere (2,9,27,28). They include 321 type 2 diabetic trios, 1,189 siblings discordant for type 2 diabetes, two Scandinavian case-control samples containing 942 and 1,028 subjects, respectively, and 254 subjects from the Saguenay LaceCSt. Jean region in Quebec. These case-control samples were individually matched for age, BMI, and geographic region. The type 2 diabetic patients met the 1998 World Health Organization criteria for type 2 diabetes. In the trios and discordant sibling collections, severe impaired glucose tolerance was defined as >10.0 mmol/l at 120 min, with blood glucose 8.5 mmol/l.
The case-control samples from Genomics Collaborative, Inc. (GCI) are comprised of 2,452 individuals of U.S. Caucasian ancestry and 2,018 subjects from Poland. These samples were matched for sex, age, and ethnicity/geographic origin (for three generations). The phenotypic characteristics of all samples are described in Table 1. Plasma glucose (fasting and during an oral glucose tolerance test) was measured by a glucose oxidase method with a Beckman Glucose analyzer (Beckman Instruments, Fullerton, CA).
Meta-analysis.
Previous association studies were found through review citations and by searching PubMed for the following queries: "polymorphism, tcf1, diabetes" and "polymorphism, hnf1, diabetes." To be included in our analysis, patients must have been defined as late onset and non-MODY. Results for the subsamples were combined using Mantel-Haenszel meta-analysis of the odds ratios (ORs) (29).
Genotyping.
Genotyping was performed as previously described by primer extension of multiplex products with detection by matrix-assisted laser desorption ionization time-of-flight mass spectroscopy using a Sequenom platform. (30,31). Most tag SNPs were genotyped twice, and the average genotype completeness for working assays was 96%. The genotyping consensus error was determined to be 0.6%, using both duplicate genotypes (69,611 comparisons) and errors in Mendelian inheritance.
Statistical analysis.
To determine the association of each particular SNP with type 2 diabetes, we used simple 2 analyses in the case-control samples: the transmission disequilibrium test (32) for the trios and the discordant allele test (33) for the sibling pairs (using the oldest unaffected sib and a random affected sib). For multimarker analyses, the frequency of each combination was estimated in the individual sample using an expectation maximization algorithm (N. Patterson, unpublished software). Results for the subsamples were combined using Mantel-Haenszel meta-analysis of the ORs (29). Homogeneity among studies was tested using a Pearson 2 goodness-of-fit test, as previously described (29).
Haplotype structure.
To evaluate the haplotype structure of the HNF1 region, we genotyped 158 SNPs from dbSNP (all available SNPs through build 118) and Celera in a multigenerational panel of 12 Centre d’Etude du Polymorphisme Humain (CEPH) pedigrees containing 96 chromosomes. We also included nine SNPs discovered by resequencing (34) 11 kb in 32 diabetic patients (targeted regions include the HNF1 promoter, AK096009 mRNA, and upstream mouse conserved regions). In total, these SNPs span 118 kb, from 49 kb upstream of the gene start site to 45 kb downstream of the end of the HNF1 3' untranslated region. SNPs were initially selected based on an evenly spaced grid across the region, with additional SNPs added based on the extent of LD. Thirty-nine of the SNPs attempted (25%) were technical failures (failing either Hardy-Weinberg equilibrium or to attain a 75% genotyping percentage), and 49 of the remaining 128 SNPs (38%) were either monomorphic in this population or had a minor allele frequency <5%, totaling a final set of 79 working, high-frequency SNPs. The average spacing between these 79 SNPs is 1.5 kb. Haplotype blocks were determined as described in 2.
Tag SNPs.
This study was performed over a period of 3 years, and as dbSNP coverage improved and methods for tag SNP selection evolved, additional tag SNPs were added. The final tag SNP set was selected using the program Tagger (P.I.W.D., M.J.D., D.A., unpublished software). Tagger combines the simplicity of pairwise methods (35) with the potential for added efficiency of using multimarker predictors. Specific multimarker tests (combinations of alleles) that predict another site are explicitly recorded and included as hypothesis tests in the association analysis. We avoid overfitting by constraining markers of such specific haplotypes to be in strong LD with one other. Tagger is available as a web server at http://www.broad.mit.edu/mpg/tagger/.
To determine how well the final tag SNP set captured variation in the HNF1 region, SNPs were evaluated for their correlation to one another in the CEPH samples described above. Specifically, we recorded the maximal pairwise r2 of each tag SNP to the complete set of other variants typed in the region. On the hypothesis that any of these variants could be a putative causal variant or proxy thereof, we selected a final set of tag SNPs (>5% frequency), which had an r2 > 0.8, to all of the markers typed in the CEPH panel. We note that this is a nonconservative estimate of power, since we have not determined the LD patterns for all SNPs in the region but rather for the one common SNP per 1.5 kb found in dbSNP. Since the total number of SNPs with >5% frequency is 1 per 500 bp on average across the human genome, our tags likely capture about one-third of all such sites already in dbSNP. In addition, by choosing a set of tags from such a dense set of SNPs, most (but not all) of the remaining sites will likely also show a high r2 value to one of the tags (P.I.W.D., M.J.D., D.A., unpublished observations).
RESULTS
We began our study of common variation in the HNF1 gene region by performing a meta-analysis of previously published literature on this gene in late-onset type 2 diabetes (21eC26) (Table 2). None of these studies were individually significant, but there was some consistency in both magnitude and direction of ORs for two common missense polymorphisms, I27L and S487N. The most common missense SNP, I27L, had a suggestive association with type 2 diabetes when all samples were combined (OR 1.25, P = 0.005). The A98V missense polymorphism had a slightly higher estimated effect size, but given its lower frequency, the statistical significance was weaker (1.54, two-tailed P = 0.03).
To see whether we could replicate any of these hypotheses and to extend the analysis to noncoding regulatory regions, we started by evaluating LD patterns across a 118-kb region spanning the HNF1 gene, genotyping 167 SNPs in a panel composed of 30 CEPH trios. The promoter and mouse-conserved regions were also resequenced in 32 diabetic patients, and all discovered SNPs were genotyped in the CEPH panel. (Since the gene has been deeply studied in many labs for a role in MODY, including in one of our labs [L.G.], we did not believe it was necessary to sequence the exons any further.) In total, 79 SNPs were in Hardy-Weinberg equilibrium, with a minimum of 95% genotyping and 5% minor allele frequency (Fig. 1). The gene region shows extensive LD and limited haplotype diversity, with 94% of the sequence in regions of strong and consistent LD (haplotype "blocks") (31). The combination of strong LD and high marker density suggests that most undiscovered SNPs are likely to be highly correlated to the SNPs already studied in the region.
We chose 21 SNPs from the 79 SNPs in the CEPH LD map to use in association studies, including the three common missense variants. (These 21 SNPs are not an efficient set, as they were chosen over time and contain partially redundant markers.) They provide an r2 > 0.9 to all other (untyped) markers in the CEPH panel, indicating that the tag SNPs should provide strong power for both untyped reference panel SNPs and any undiscovered common SNPs when genotyped in the disease panel.
The 21 tag SNPs were genotyped in 2,042 type 2 diabetic patients from Scandinavia and Canada, plus their matched control subjects (family based or unrelated) (Table 1). Eleven tests showed a nominally significant association to type 2 diabetes in this initial panel (Table 3). This includes the I27L missense variant, for which we observed a similar-sized effect as in the meta-analysis (Table 1) (current study: OR 1.13, one-tailed P = 0.01). The most statistically significant result observed was for rs1920792, located 12 kb upstream of the HNF1 start site, which had an OR of 1.17 (two-tailed P = 0.002). The largest OR was observed for the rare missense variant A98V (OR 1.24), although due to its low frequency, this resulted in a one-tailed P value of 0.07.
In light of the prior functional and genetic data surrounding this gene, these initial results were quite encouraging: common variants in HNF1 might play a role in type 2 diabetes. To more conclusively address whether any of the positive common variants in our study are associated with type 2 diabetes, we performed two additional analyses. First, we genotyped the most strongly supported hypotheses from our study (rs1920792, I27L, and A98V) in an additional 4,470 Caucasian type 2 diabetic patients and matched control subjects of U.S. and Polish ancestry. Second, we collaborated with Weedon et al. (36), who were already studying the same gene locus, to align our tag SNPs so that we could directly compare the results of the two studies.
In the Polish and U.S. samples, none of the previously implicated SNPs show evidence for association with type 2 diabetes (Table 4). Similarly, neither the I27L nor the rs1920792 associations were seen by Weedon et al. (36). Of the SNPs evaluated jointly in our complete sample and by Weedon et al., the Val variant of A98V was most consistently associated with increased risk of diabetes in both studies and in the previous literature. However, the suggested OR was very modest, as was the frequency of the SNP (3eC6% in our European populations), such that even if the effect turns out to be correct, it will explain very little individual or population risk and be difficult to prove even with collections of 5,000eC10,000 samples.
DISCUSSION
HNF1 is the gene responsible for the most common form of MODY and is found in a region implicated by linkage results in multiple studies, and meta-analysis of previous studies suggests that missense SNPs might be associated with late-onset type 2 diabetes. Thus, before our study and that of Weedon et al. (36), the Bayesian prior probability was quite high that common variation in HNF1 might play a role in late-onset type 2 diabetes. Moreover, in our initial >4,000 patient/control samples, we saw encouraging evidence for association of several variants in the region. When studied in two large, independent samples, however, none of these putative associations were consistently observed. The most conservative conclusion of this study, therefore, is that common variation in the HNF1 region either has no role in late-onset type 2 diabetes, a very modest role (e.g., a modest effect of the quite rare SNP A98V), or a role that cannot be consistently observed without consideration of currently unmeasured genetic or environmental modifiers.
It is not unusual that an initial study will show modest signals for association (as in our initial screen with 21 SNPs in 4,100 people) that fails to be replicated in additional samples. Many explanations can be invoked to explain the lack of replication of our initial reports. First, the initial association may have been a statistical fluctuation. The P values in the initial study were modest after correction for the number of variants studied (on the order of 0.01), and HNF1 is one of many genes being studied by ours and other groups. Thus, encountering such a result by chance is not unexpected, and the similarity to the published literature could reflect past publication bias toward positive results.
A second potential explanation is that common variation at this locus does have an effect on diabetes risk, but that it is even more modest than seen in previous studies and our original panel of patients. That is, the apparent effect sizes for the most promising variants could be inflated by the so-called "winner’s curse" (29). However, given the large sizes of the two nonreplicating studies, any such true effect would have to be quite modest; for example, our analysis places the upper bound on the OR for the minor allele of I27L at 1.15 based on the upper 95% CI of a meta-analysis for all published studies.
A third possibility is that the initial association signal is real (at least in those samples), but that there is heterogeneity among populations, and the variant in question is not associated with risk in our GCI sample or the Weedon et al. (36) sample due to an unmeasured environmental or genetic modifier. We note that a formal test for heterogeneity across the three studies was negative and that such an explanation remains speculative unless such a genetic or environmental modifier is found and a gene-gene or gene-environment interaction is demonstrated. We also note that two widely replicated associations in type 2 diabetes, peroxisome proliferatoreCactivated receptor P12A and Kir6.2 E23K, are observed as statistically significant in both the Scandinavian/Canadian and the GCI subsamples (2,9,37,38). However, it could be that the relationship between genotype and particular disease phenotypes varies for different SNPs such that some SNPs will be consistently observed, whereas others may be more sensitive to specifics of case ascertainment and/or phenotypic measurement in each study.
Excepting a consistent and reproducible association, the most straightforward interpretation is that although rare variants in HNF1 can cause an early-onset, autosomal-dominant form of type 2 diabetes, no common variants exist that contribute more modestly to the disease in its typical form. The case of MODY3 is a subset of a question of general importance: whether genes implicated in monogenic forms of disease also explain the heritability of the common form of the disease. Over the last decade, there have been many genes identified that cause Mendelian forms of common diseases, including MODY, maternally inherited diabetes and deafness (39), 20 inherited forms of blood pressure regulation (40), early-onset breast cancer (BRCA1, BRCA2, and ATM), Alzheimer’s (APP, PS1, and PS2), and others. To the extent that genes for common and rare forms of disease turn out to be nonoverlapping, it will suggest that the selective impact of these different forms of the disease, and/or the underlying pathogenic mechanisms, can be less similar than suggested by the shared clinical end point. Furthermore, it will mean that other methods (beyond positional cloning of rare, highly inherited subtypes) will be required to find those genes that explain the evident heritability of the disease.
ACKNOWLEDGMENTS
J.N.H. is a recipient of a Burroughs Wellcome Career Award in Biomedical Sciences. D.A. is a Charles E. Culpeper Scholar of the Rockefeller Brothers Fund and a Burroughs Wellcome Fund Clinical Scholar in Translational Research, the latter of which supported this work. L.G. and the Botnia Study are principally supported by the Sigrid Juselius Foundation, the Academy of Finland, the Finnish Diabetes Research Foundation, The Folkhalsan Research Foundation, the European Community (BM4-CT95-0662, GIFT), the Swedish Medical Research Council, the JDF Wallenberg Foundation, and the Novo Nordisk Foundation.
We thank T. Frayling and colleagues for sharing their unpublished data, the Botnia research team for clinical contributions, and the members of the Altshuler, Hirschhorn, Daly, and Groop labs for helpful discussions.
FOOTNOTES
D.A. and L.G. jointly supervised this project.
J.N.H. has received consulting fees from Correlagen. D.A. has served on advisory panels for and received consulting fees from Genomics Collaborative, Inc. L.G. has served on advisory panels for and received consulting fees from Aventis-Sanofi, Bristol-Myers Squibb, Kowa, and Roche.
CEPH, Centre d’Etude du Polymorphisme Humain; GCI, Genomics Collaborative, Inc; LD, linkage disequilibrium; MODY, maturity-onset diabetes of the young; SNP, single nucleotide polymorphism
REFERENCES
Florez JC, Hirschhorn J, Altshuler D: The inherited basis of diabetes mellitus: implications for the genetic analysis of complex traits. Annu Rev Genomics Hum Genet4 :257 eC291,2003
Florez JC, Burtt N, de Bakker PI, Almgren P, Tuomi T, Holmkvist J, Gaudet D, Hudson TJ, Schaffner SF, Daly MJ, Hirschhorn JN, Groop L, Altshuler D: Haplotype structure and genotype-phenotype correlations of the sulfonylurea receptor and the islet ATP-sensitive potassium channel gene region. Diabetes53 :1360 eC1368,2004
Song Y, Niu T, Manson JE, Kwiatkowski DJ, Liu S: Are variants in the CAPN10 gene related to risk of type 2 diabetes A quantitative assessment of population and family-based association studies. Am J Hum Genet74 :208 eC222,2004
Weedon MN, Schwarz PE, Horikawa Y, Iwasaki N, Illig T, Holle R, Rathmann W, Selisko T, Schulze J, Owen KR, Evans J, Del Bosque-Plata L, Hitman G, Walker M, Levy JC, Sampson M, Bell GI, McCarthy MI, Hattersley AT, Frayling TM: Meta-analysis and a large association study confirm a role for calpain-10 variation in type 2 diabetes susceptibility. Am J Hum Genet73 :1208 eC1212,2003
Sklar P, Schwab SG, Williams NM, Daly M, Schaffner S, Maier W, Albus M, Trixler M, Eichhammer P, Lerer B, Hallmayer J, Norton N, Williams H, Zammit S, Cardno AG, Jones S, McCarthy G, Milanova V, Kirov G, O’Donovan MC, Lander ES, Owen MJ, Wildenauer DB: Association analysis of NOTCH4 loci in schizophrenia using family and population-based controls. Nat Genet28 :126 eC128,2001
Rioux JD, Daly MJ, Silverberg MS, Lindblad K, Steinhart H, Cohen Z, Delmonte T, Kocher K, Miller K, Guschwan S, Kulbokas EJ, O’Leary S, Winchester E, Dewar K, Green T, Stone V, Chow C, Cohen A, Langelier D, Lapointe G, Gaudet D, Faith J, Branco N, Bull SB, McLeod RS, Griffiths AM, Bitton A, Greenberg GR, Lander ES, Siminovitch KA, Hudson TJ: Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease. Nat Genet29 :223 eC228,2001
Laitinen T, Daly MJ, Rioux JD, Kauppi P, Laprise C, Petays T, Green T, Cargill M, Haahtela T, Lander ES, Laitinen LA, Hudson TJ, Kere J: A susceptibility locus for asthma-related traits on chromosome 7 revealed by genome-wide scan in a founder population. Nat Genet28 :87 eC91,2001
Martin ER, Lai EH, Gilbert JR, Rogala AR, Afshari AJ, Riley J, Finch KL, Stevens JF, Livak KJ, Slotterbeck BD, Slifer SH, Warren LL, Conneally PM, Schmechel DE, Purvis I, Pericak-Vance MA, Roses AD, Vance JM: SNPing away at complex diseases: analysis of single-nucleotide polymorphisms around APOE in Alzheimer disease. Am J Hum Genet67 :383 eC394,2000
Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, Lane CR, Schaffner SF, Bolk S, Brewer C, Tuomi T, Gaudet D, Hudson TJ, Daly M, Groop L, Lander ES: The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet26 :76 eC80,2000
Fajans SS, Bell GI, Polonsky KS: Molecular mechanisms and clinical pathophysiology of maturity-onset diabetes of the young. N Engl J Med345 :971 eC980,2001
Yamagata K, Furuta H, Oda N, Kaisaki PJ, Menzel S, Cox NJ, Fajans SS, Signorini S, Stoffel M, Bell GI: Mutations in the hepatocyte nuclear factor-4alpha gene in maturity-onset diabetes of the young (MODY1). Nature384 :458 eC460,1996
Yamagata K, Oda N, Kaisaki PJ, Menzel S, Furuta H, Vaxillaire M, Southam L, Cox RD, Lathrop GM, Boriraj VV, Chen X, Cox NJ, Oda Y, Yano H, Le Beau MM, Yamada S, Nishigori H, Takeda J, Fajans SS, Hattersley AT, Iwasaki N, Hansen T, Pedersen O, Polonsky KS, Bell GI: Mutations in the hepatocyte nuclear factor-1alpha gene in maturity-onset diabetes of the young (MODY3). Nature384 :455 eC458,1996
Vionnet N, Stoffel M, Takeda J, Yasuda K, Bell GI, Zouali H, Lesage S, Velho G, Iris F, Passa P, et al.: Nonsense mutation in the glucokinase gene causes early-onset non-insulin-dependent diabetes mellitus. Nature356 :721 eC722,1992
Malecki MT, Jhala US, Antonellis A, Fields L, Doria A, Orban T, Saad M, Warram JH, Montminy M, Krolewski AS: Mutations in NEUROD1 are associated with the development of type 2 diabetes mellitus. Nat Genet23 :323 eC328,1999
Stoffers DA, Ferrer J, Clarke WL, Habener JF: Early-onset type-II diabetes mellitus (MODY4) linked to IPF1. Nat Genet17 :138 eC139,1997
Horikawa Y, Iwasaki N, Hara M, Furuta H, Hinokio Y, Cockburn BN, Lindner T, Yamagata K, Ogata M, Tomonaga O, Kuroki H, Kasahara T, Iwamoto Y, Bell GI: Mutation in hepatocyte nuclear factor-1 beta gene (TCF2) associated with MODY. Nat Genet17 :384 eC385,1997
Wiltshire S, Frayling TM, Groves CJ, Levy JC, Hitman GA, Sampson M, Walker M, Menzel S, Hattersley AT, Cardon LR, McCarthy MI: Evidence from a large U.K. family collection that genes influencing age of onset of type 2 diabetes map to chromosome 12p and to the MODY3/NIDDM2 locus on 12q24. Diabetes53 :855 eC860,2004
Mahtani MM, Widen E, Lehto M, Thomas J, McCarthy M, Brayer J, Bryant B, Chan G, Daly M, Forsblom C, Kanninen T, Kirby A, Kruglyak L, Munnelly K, Parkkonen M, Reeve-Daly MP, Weaver A, Brettin T, Duyk G, Lander ES, Groop LC: Mapping of a gene for type 2 diabetes associated with an insulin secretion defect by a genome scan in Finnish families. Nat Genet14 :90 eC94,1996
Hegele RA CH, Harris SB, Hanleys AJG, Zinman B: The hepatic nuclear factor-1alpha G319S variant is associated with early-onset type 2 diabetes in Canadian Oji-Cree. J Clin Endocrinol Metab84 :1077 eC1082,1999
Chiu KC, Chuang LM, Ryu JM, Tsai GP, Saad MF: The I27L amino acid polymorphism of hepatic nuclear factor-1alpha is associated with insulin resistance. J Clin Endocrinol Metab85 :2178 eC2183,2000
Yamada S, Nishigori H, Onda H, Takahashi K, Kitano N, Morikawa A, Takeuchi T, Takeda J: Mutations in the hepatocyte nuclear factor-1 gene (MODY3) are not a major cause of late-onset NIDDM in Japanese subjects. Diabetes46 :1512 eC1513,1997
Urhammer SA, Rasmussen SK, Kaisaki PJ, Oda N, Yamagata K, Moller AM, Fridberg M, Hansen L, Hansen T, Bell GI, Pedersen O: Genetic variation in the hepatocyte nuclear factor-1 alpha gene in Danish Caucasians with late-onset NIDDM. Diabetologia40 :473 eC475,1997
Rissanen J, Wang H, Miettinen R, Karkkainen P, Kekalainen P, Mykkanen L, Kuusisto J, Karhapaa P, Niskanen L, Uusitupa M, Laakso M: Variants in the hepatocyte nuclear factor-1 and -4 genes in Finnish and Chinese subjects with late-onset type 2 diabetes. Diabetes Care23 :1533 eC1538,2000
Jackson AE, Cassell PG, North BV, Vijayaraghavan S, Gelding SV, Ramachandran A, Snehalatha C, Hitman GA: Polymorphic variations in the neurogenic differentiation-1, neurogenin-3, and hepatocyte nuclear factor-1 genes contribute to glucose intolerance in a South Indian population. Diabetes53 :2122 eC2125,2004
Behn PS, Wasson J, Chayen S, Smolovitch I, Thomas J, Glaser B, Permutt MA: Hepatocyte nuclear factor 1 coding mutations are an uncommon contributor to early-onset type 2 diabetes in Ashkenazi Jews. Diabetes47 :967 eC969,1998
Babaya N, Ikegami H, Kawaguchi Y, Fujisawa T, Nakagawa Y, Hamada Y, Hotta M, Ueda H, Shintani M, Nojima K, Kawabata Y, Ono M, Yamada K, Shen GQ, Fukuda M, Ogihara T: Hepatocyte nuclear factor-1alpha gene and non-insulin-dependent diabetes mellitus in the Japanese population. Acta Diabetol35 :150 eC153,1998
Winckler W, Graham RR, de Bakker PIW, Sun M, Almgren P, Tuomi T, Gaudet D, Hudson TJ, Ardlie KG, Daly MJ, Hirschhorn JN, Groop L, Altshuler D: Association testing of variants in the hepatocyte nuclear factor 4 gene with risk of type 2 diabetes in 7,883 people. Diabetes54 :886 eC892,2005
Florez JC, Sjogren M, Burtt N, Orho-Melander M, Schayer S, Sun M, Almgren P, Lindblad U, Tuomi T, Gaudet D, Hudson TJ, Daly MJ, Ardlie KG, Hirschhorn JN, Altshuler D, Groop L: Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes. Diabetes53 :3313 eC3318,2004
Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN: Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet33 :177 eC182,2003
Tang K, Fu DJ, Julien D, Braun A, Cantor CR, Koster H: Chip-based genotyping by mass spectrometry. Proc Natl Acad Sci U S A96 :10016 eC10020,1999
Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D: The structure of haplotype blocks in the human genome. Science296 :2225 eC2229,2002
Spielman RS, McGinnis RE, Ewens WJ: Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet52 :506 eC516,1993
Boehnke M, Langefeld CD: Genetic association mapping based on discordant sib pairs: the discordant-alleles test. Am J Hum Genet62 :950 eC961,1998
Cargill M, Altshuler D, Ireland J, Sklar P, Ardlie K, Patil N, Shaw N, Lane CR, Lim EP, Kalyanaraman N, Nemesh J, Ziaugra L, Friedland L, Rolfe A, Warrington J, Lipshutz R, Daley GQ, Lander ES: Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nat Genet22 :231 eC238,1999
Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA: Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet74 :106 eC120,2004
Weedon MN, Owen, KR, Shields B, Hitman G, Walker M, McCarthy MI, Hattersley AT, Frayling TM: A large-scale association analysis of common variation of the HNF1 gene with type 2 diabetes in the U.K. Caucasian population (Brief Genetics Report). Diabetes54 :2487 eC2491,2005
Florez JC, Sjogren M, Burtt N, Orho-Melander M, Schayer S, Sun M, Almgren P, Lindblad U, Tuomi T, Gaudet D, Hudson TJ, Daly MJ, Ardlie KG, Hirschhorn JN, Altshuler D, Groop L: Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes. Diabetes54 :3313 eC3318,2004
Ardlie KG, Lunetta KL, Seielstad M: Testing for population subdivision and association in four case-control studies. Am J Hum Genet71 :304 eC311,2002
van den Ouweland JM, Lemkes HHPJ, Trembath RC, Ross R, Velho G, Cohen D, Froguel P, Maassen JA: Maternally inherited diabetes and deafness is a distinct subtype of diabetes and associates with a single point mutation in the mitochondrial tRNALeu(UUR) gene. Diabetes43 :746 eC751,1994
Wilson FH, Disse-Nicodeme S, Choate KA, Ishikawa K, Nelson-Williams C, Desitter I, Gunel M, Milford DV, Lipkin GW, Achard JM, Feely MP, Dussol B, Berland Y, Unwin RJ, Mayan H, Simon DB, Farfel Z, Jeunemaitre X, Lifton RP: Human hypertension caused by mutations in WNK kinases. Science293 :1107 eC1112,2001(Wendy Winckler, Nol P. Bu)
2 Department of Genetics, Harvard Medical School, Boston, Massachusetts
3 Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
4 Department of Endocrinology, University Hospital MAS, Lund University, Malm, Sweden
5 Department of Medicine, Helsinki University Central Hospital, Folkhalsan Genetic Institute, Folkhalsan Research Center, and Research Program for Molecular Medicine, University of Helsinki, Helsinki, Finland
6 University of Montreal Community Genomic Center, Chicoutimi Hospital, Montreal, Quebec, Canada
7 McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada
8 Genomics Collaborative, Inc., Cambridge, Massachusetts
9 Divisions of Genetics and Endocrinology, Children’s Hospital, Boston, Massachusetts
10 Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts
11 Department of Medicine, Harvard Medical School, Boston, Massachusetts
ABSTRACT
It is currently unclear how often genes that are mutated to cause rare, early-onset monogenic forms of disease also harbor common variants that contribute to the more typical polygenic form of each disease. The gene for MODY3 diabetes, HNF1, lies in a region that has shown linkage to late-onset type 2 diabetes (12q24, NIDDM2), and previous association studies have suggested a weak trend toward association for common missense variants in HNF1 with glucose-related traits. Based on genotyping of 79 common SNPs in the 118 kb spanning HNF1, we selected 21 haplotype tag single nucleotide polymorphisms (SNPs) and genotyped them in >4,000 diabetic patients and control subjects from Sweden, Finland, and Canada. Several SNPs from the coding region and 5' of the gene demonstrated nominal association with type 2 diabetes, with the most significant marker (rs1920792) having an odds ratio of 1.17 and a P value of 0.002. We then genotyped three SNPs with the strongest evidence for association to type 2 diabetes (rs1920792, I27L, and A98V) in an additional 4,400 type 2 diabetic and control subjects from North America and Poland and compared our results with those of the original sample and of Weedon et al. None of the results were consistently observed across all samples, with the possible exception of a modest association of the rare (3eC5%) A98V variant. These results indicate that common variants in HNF1 either play no role in type 2 diabetes, a very small role, or a role that cannot be consistently observed without consideration of as yet unmeasured genetic or environmental modifiers.
Type 2 diabetes is a common human disease that is influenced by both genetic and environmental factors. As in most common diseases, very few variants have been rigorously proven to play a role in the common form of type 2 diabetes. Well-demonstrated examples of late-onset diabetes genes include the Pro12Ala polymorphism in the peroxisome proliferatoreCactivated receptor , the E23K polymorphism in the Kir6.2 gene (both rev. in 1) (2), and single nucleotide polymorphism (SNP) 44 in the region of calpain-10 (3,4). Experience with these and other complex diseases suggests that gene effects may often be modest, so very large study populations are required to achieve statistically significant, reproducible results (5eC9).
Maturity-onset diabetes of the young (MODY) is a rare autosomal-dominant form of type 2 diabetes that is characterized by early onset and a defect in the function of the -cells in the pancreas (10). Six genes are known to cause MODY (11eC16), with mutations in the MODY3 gene (HNF1) accounting for the majority of MODY families. In addition to its role in monogenic diabetes, several lines of evidence suggest that HNF1 is a particularly interesting candidate gene to influence the common, late-onset form of type 2 diabetes. It is located directly under linkage peaks in two genome-wide linkage scans for the common form of type 2 diabetes (17,18). The G319S missense variant (common in the Canadian Oji-Cree, although not found elsewhere) is strongly associated with a late-onset form of type 2 diabetes in that population (19). Additionally, the common I27L missense variant in HNF1 was reported to be an independent determinant of -cell function in healthy individuals (20). HNF1 has been resequenced in many diabetic patients, but published studies have yet to show a strong and consistent genetic effect on the common form of type 2 diabetes (21eC26). However, these studies were typically modest in size, and thus could not validate or rule out small effects of individual variants. Additionally, to our knowledge only the coding region had previously been surveyed, leaving open the possibility that noncoding (presumably regulatory) variants in HNF1 might play a role.
To more comprehensively characterize genotype-phenotype correlation at this gene locus with regard to the common form of type 2 diabetes, we characterized linkage disequilibrium (LD) patterns in a reference panel, selected tag SNPs that capture the vast majority of common variants at this locus, and genotyped these markers in a large collection of type 2 diabetic and control subjects.
RESEARCH DESIGN AND METHODS
The characteristics of our patient samples have been described elsewhere (2,9,27,28). They include 321 type 2 diabetic trios, 1,189 siblings discordant for type 2 diabetes, two Scandinavian case-control samples containing 942 and 1,028 subjects, respectively, and 254 subjects from the Saguenay LaceCSt. Jean region in Quebec. These case-control samples were individually matched for age, BMI, and geographic region. The type 2 diabetic patients met the 1998 World Health Organization criteria for type 2 diabetes. In the trios and discordant sibling collections, severe impaired glucose tolerance was defined as >10.0 mmol/l at 120 min, with blood glucose 8.5 mmol/l.
The case-control samples from Genomics Collaborative, Inc. (GCI) are comprised of 2,452 individuals of U.S. Caucasian ancestry and 2,018 subjects from Poland. These samples were matched for sex, age, and ethnicity/geographic origin (for three generations). The phenotypic characteristics of all samples are described in Table 1. Plasma glucose (fasting and during an oral glucose tolerance test) was measured by a glucose oxidase method with a Beckman Glucose analyzer (Beckman Instruments, Fullerton, CA).
Meta-analysis.
Previous association studies were found through review citations and by searching PubMed for the following queries: "polymorphism, tcf1, diabetes" and "polymorphism, hnf1, diabetes." To be included in our analysis, patients must have been defined as late onset and non-MODY. Results for the subsamples were combined using Mantel-Haenszel meta-analysis of the odds ratios (ORs) (29).
Genotyping.
Genotyping was performed as previously described by primer extension of multiplex products with detection by matrix-assisted laser desorption ionization time-of-flight mass spectroscopy using a Sequenom platform. (30,31). Most tag SNPs were genotyped twice, and the average genotype completeness for working assays was 96%. The genotyping consensus error was determined to be 0.6%, using both duplicate genotypes (69,611 comparisons) and errors in Mendelian inheritance.
Statistical analysis.
To determine the association of each particular SNP with type 2 diabetes, we used simple 2 analyses in the case-control samples: the transmission disequilibrium test (32) for the trios and the discordant allele test (33) for the sibling pairs (using the oldest unaffected sib and a random affected sib). For multimarker analyses, the frequency of each combination was estimated in the individual sample using an expectation maximization algorithm (N. Patterson, unpublished software). Results for the subsamples were combined using Mantel-Haenszel meta-analysis of the ORs (29). Homogeneity among studies was tested using a Pearson 2 goodness-of-fit test, as previously described (29).
Haplotype structure.
To evaluate the haplotype structure of the HNF1 region, we genotyped 158 SNPs from dbSNP (all available SNPs through build 118) and Celera in a multigenerational panel of 12 Centre d’Etude du Polymorphisme Humain (CEPH) pedigrees containing 96 chromosomes. We also included nine SNPs discovered by resequencing (34) 11 kb in 32 diabetic patients (targeted regions include the HNF1 promoter, AK096009 mRNA, and upstream mouse conserved regions). In total, these SNPs span 118 kb, from 49 kb upstream of the gene start site to 45 kb downstream of the end of the HNF1 3' untranslated region. SNPs were initially selected based on an evenly spaced grid across the region, with additional SNPs added based on the extent of LD. Thirty-nine of the SNPs attempted (25%) were technical failures (failing either Hardy-Weinberg equilibrium or to attain a 75% genotyping percentage), and 49 of the remaining 128 SNPs (38%) were either monomorphic in this population or had a minor allele frequency <5%, totaling a final set of 79 working, high-frequency SNPs. The average spacing between these 79 SNPs is 1.5 kb. Haplotype blocks were determined as described in 2.
Tag SNPs.
This study was performed over a period of 3 years, and as dbSNP coverage improved and methods for tag SNP selection evolved, additional tag SNPs were added. The final tag SNP set was selected using the program Tagger (P.I.W.D., M.J.D., D.A., unpublished software). Tagger combines the simplicity of pairwise methods (35) with the potential for added efficiency of using multimarker predictors. Specific multimarker tests (combinations of alleles) that predict another site are explicitly recorded and included as hypothesis tests in the association analysis. We avoid overfitting by constraining markers of such specific haplotypes to be in strong LD with one other. Tagger is available as a web server at http://www.broad.mit.edu/mpg/tagger/.
To determine how well the final tag SNP set captured variation in the HNF1 region, SNPs were evaluated for their correlation to one another in the CEPH samples described above. Specifically, we recorded the maximal pairwise r2 of each tag SNP to the complete set of other variants typed in the region. On the hypothesis that any of these variants could be a putative causal variant or proxy thereof, we selected a final set of tag SNPs (>5% frequency), which had an r2 > 0.8, to all of the markers typed in the CEPH panel. We note that this is a nonconservative estimate of power, since we have not determined the LD patterns for all SNPs in the region but rather for the one common SNP per 1.5 kb found in dbSNP. Since the total number of SNPs with >5% frequency is 1 per 500 bp on average across the human genome, our tags likely capture about one-third of all such sites already in dbSNP. In addition, by choosing a set of tags from such a dense set of SNPs, most (but not all) of the remaining sites will likely also show a high r2 value to one of the tags (P.I.W.D., M.J.D., D.A., unpublished observations).
RESULTS
We began our study of common variation in the HNF1 gene region by performing a meta-analysis of previously published literature on this gene in late-onset type 2 diabetes (21eC26) (Table 2). None of these studies were individually significant, but there was some consistency in both magnitude and direction of ORs for two common missense polymorphisms, I27L and S487N. The most common missense SNP, I27L, had a suggestive association with type 2 diabetes when all samples were combined (OR 1.25, P = 0.005). The A98V missense polymorphism had a slightly higher estimated effect size, but given its lower frequency, the statistical significance was weaker (1.54, two-tailed P = 0.03).
To see whether we could replicate any of these hypotheses and to extend the analysis to noncoding regulatory regions, we started by evaluating LD patterns across a 118-kb region spanning the HNF1 gene, genotyping 167 SNPs in a panel composed of 30 CEPH trios. The promoter and mouse-conserved regions were also resequenced in 32 diabetic patients, and all discovered SNPs were genotyped in the CEPH panel. (Since the gene has been deeply studied in many labs for a role in MODY, including in one of our labs [L.G.], we did not believe it was necessary to sequence the exons any further.) In total, 79 SNPs were in Hardy-Weinberg equilibrium, with a minimum of 95% genotyping and 5% minor allele frequency (Fig. 1). The gene region shows extensive LD and limited haplotype diversity, with 94% of the sequence in regions of strong and consistent LD (haplotype "blocks") (31). The combination of strong LD and high marker density suggests that most undiscovered SNPs are likely to be highly correlated to the SNPs already studied in the region.
We chose 21 SNPs from the 79 SNPs in the CEPH LD map to use in association studies, including the three common missense variants. (These 21 SNPs are not an efficient set, as they were chosen over time and contain partially redundant markers.) They provide an r2 > 0.9 to all other (untyped) markers in the CEPH panel, indicating that the tag SNPs should provide strong power for both untyped reference panel SNPs and any undiscovered common SNPs when genotyped in the disease panel.
The 21 tag SNPs were genotyped in 2,042 type 2 diabetic patients from Scandinavia and Canada, plus their matched control subjects (family based or unrelated) (Table 1). Eleven tests showed a nominally significant association to type 2 diabetes in this initial panel (Table 3). This includes the I27L missense variant, for which we observed a similar-sized effect as in the meta-analysis (Table 1) (current study: OR 1.13, one-tailed P = 0.01). The most statistically significant result observed was for rs1920792, located 12 kb upstream of the HNF1 start site, which had an OR of 1.17 (two-tailed P = 0.002). The largest OR was observed for the rare missense variant A98V (OR 1.24), although due to its low frequency, this resulted in a one-tailed P value of 0.07.
In light of the prior functional and genetic data surrounding this gene, these initial results were quite encouraging: common variants in HNF1 might play a role in type 2 diabetes. To more conclusively address whether any of the positive common variants in our study are associated with type 2 diabetes, we performed two additional analyses. First, we genotyped the most strongly supported hypotheses from our study (rs1920792, I27L, and A98V) in an additional 4,470 Caucasian type 2 diabetic patients and matched control subjects of U.S. and Polish ancestry. Second, we collaborated with Weedon et al. (36), who were already studying the same gene locus, to align our tag SNPs so that we could directly compare the results of the two studies.
In the Polish and U.S. samples, none of the previously implicated SNPs show evidence for association with type 2 diabetes (Table 4). Similarly, neither the I27L nor the rs1920792 associations were seen by Weedon et al. (36). Of the SNPs evaluated jointly in our complete sample and by Weedon et al., the Val variant of A98V was most consistently associated with increased risk of diabetes in both studies and in the previous literature. However, the suggested OR was very modest, as was the frequency of the SNP (3eC6% in our European populations), such that even if the effect turns out to be correct, it will explain very little individual or population risk and be difficult to prove even with collections of 5,000eC10,000 samples.
DISCUSSION
HNF1 is the gene responsible for the most common form of MODY and is found in a region implicated by linkage results in multiple studies, and meta-analysis of previous studies suggests that missense SNPs might be associated with late-onset type 2 diabetes. Thus, before our study and that of Weedon et al. (36), the Bayesian prior probability was quite high that common variation in HNF1 might play a role in late-onset type 2 diabetes. Moreover, in our initial >4,000 patient/control samples, we saw encouraging evidence for association of several variants in the region. When studied in two large, independent samples, however, none of these putative associations were consistently observed. The most conservative conclusion of this study, therefore, is that common variation in the HNF1 region either has no role in late-onset type 2 diabetes, a very modest role (e.g., a modest effect of the quite rare SNP A98V), or a role that cannot be consistently observed without consideration of currently unmeasured genetic or environmental modifiers.
It is not unusual that an initial study will show modest signals for association (as in our initial screen with 21 SNPs in 4,100 people) that fails to be replicated in additional samples. Many explanations can be invoked to explain the lack of replication of our initial reports. First, the initial association may have been a statistical fluctuation. The P values in the initial study were modest after correction for the number of variants studied (on the order of 0.01), and HNF1 is one of many genes being studied by ours and other groups. Thus, encountering such a result by chance is not unexpected, and the similarity to the published literature could reflect past publication bias toward positive results.
A second potential explanation is that common variation at this locus does have an effect on diabetes risk, but that it is even more modest than seen in previous studies and our original panel of patients. That is, the apparent effect sizes for the most promising variants could be inflated by the so-called "winner’s curse" (29). However, given the large sizes of the two nonreplicating studies, any such true effect would have to be quite modest; for example, our analysis places the upper bound on the OR for the minor allele of I27L at 1.15 based on the upper 95% CI of a meta-analysis for all published studies.
A third possibility is that the initial association signal is real (at least in those samples), but that there is heterogeneity among populations, and the variant in question is not associated with risk in our GCI sample or the Weedon et al. (36) sample due to an unmeasured environmental or genetic modifier. We note that a formal test for heterogeneity across the three studies was negative and that such an explanation remains speculative unless such a genetic or environmental modifier is found and a gene-gene or gene-environment interaction is demonstrated. We also note that two widely replicated associations in type 2 diabetes, peroxisome proliferatoreCactivated receptor P12A and Kir6.2 E23K, are observed as statistically significant in both the Scandinavian/Canadian and the GCI subsamples (2,9,37,38). However, it could be that the relationship between genotype and particular disease phenotypes varies for different SNPs such that some SNPs will be consistently observed, whereas others may be more sensitive to specifics of case ascertainment and/or phenotypic measurement in each study.
Excepting a consistent and reproducible association, the most straightforward interpretation is that although rare variants in HNF1 can cause an early-onset, autosomal-dominant form of type 2 diabetes, no common variants exist that contribute more modestly to the disease in its typical form. The case of MODY3 is a subset of a question of general importance: whether genes implicated in monogenic forms of disease also explain the heritability of the common form of the disease. Over the last decade, there have been many genes identified that cause Mendelian forms of common diseases, including MODY, maternally inherited diabetes and deafness (39), 20 inherited forms of blood pressure regulation (40), early-onset breast cancer (BRCA1, BRCA2, and ATM), Alzheimer’s (APP, PS1, and PS2), and others. To the extent that genes for common and rare forms of disease turn out to be nonoverlapping, it will suggest that the selective impact of these different forms of the disease, and/or the underlying pathogenic mechanisms, can be less similar than suggested by the shared clinical end point. Furthermore, it will mean that other methods (beyond positional cloning of rare, highly inherited subtypes) will be required to find those genes that explain the evident heritability of the disease.
ACKNOWLEDGMENTS
J.N.H. is a recipient of a Burroughs Wellcome Career Award in Biomedical Sciences. D.A. is a Charles E. Culpeper Scholar of the Rockefeller Brothers Fund and a Burroughs Wellcome Fund Clinical Scholar in Translational Research, the latter of which supported this work. L.G. and the Botnia Study are principally supported by the Sigrid Juselius Foundation, the Academy of Finland, the Finnish Diabetes Research Foundation, The Folkhalsan Research Foundation, the European Community (BM4-CT95-0662, GIFT), the Swedish Medical Research Council, the JDF Wallenberg Foundation, and the Novo Nordisk Foundation.
We thank T. Frayling and colleagues for sharing their unpublished data, the Botnia research team for clinical contributions, and the members of the Altshuler, Hirschhorn, Daly, and Groop labs for helpful discussions.
FOOTNOTES
D.A. and L.G. jointly supervised this project.
J.N.H. has received consulting fees from Correlagen. D.A. has served on advisory panels for and received consulting fees from Genomics Collaborative, Inc. L.G. has served on advisory panels for and received consulting fees from Aventis-Sanofi, Bristol-Myers Squibb, Kowa, and Roche.
CEPH, Centre d’Etude du Polymorphisme Humain; GCI, Genomics Collaborative, Inc; LD, linkage disequilibrium; MODY, maturity-onset diabetes of the young; SNP, single nucleotide polymorphism
REFERENCES
Florez JC, Hirschhorn J, Altshuler D: The inherited basis of diabetes mellitus: implications for the genetic analysis of complex traits. Annu Rev Genomics Hum Genet4 :257 eC291,2003
Florez JC, Burtt N, de Bakker PI, Almgren P, Tuomi T, Holmkvist J, Gaudet D, Hudson TJ, Schaffner SF, Daly MJ, Hirschhorn JN, Groop L, Altshuler D: Haplotype structure and genotype-phenotype correlations of the sulfonylurea receptor and the islet ATP-sensitive potassium channel gene region. Diabetes53 :1360 eC1368,2004
Song Y, Niu T, Manson JE, Kwiatkowski DJ, Liu S: Are variants in the CAPN10 gene related to risk of type 2 diabetes A quantitative assessment of population and family-based association studies. Am J Hum Genet74 :208 eC222,2004
Weedon MN, Schwarz PE, Horikawa Y, Iwasaki N, Illig T, Holle R, Rathmann W, Selisko T, Schulze J, Owen KR, Evans J, Del Bosque-Plata L, Hitman G, Walker M, Levy JC, Sampson M, Bell GI, McCarthy MI, Hattersley AT, Frayling TM: Meta-analysis and a large association study confirm a role for calpain-10 variation in type 2 diabetes susceptibility. Am J Hum Genet73 :1208 eC1212,2003
Sklar P, Schwab SG, Williams NM, Daly M, Schaffner S, Maier W, Albus M, Trixler M, Eichhammer P, Lerer B, Hallmayer J, Norton N, Williams H, Zammit S, Cardno AG, Jones S, McCarthy G, Milanova V, Kirov G, O’Donovan MC, Lander ES, Owen MJ, Wildenauer DB: Association analysis of NOTCH4 loci in schizophrenia using family and population-based controls. Nat Genet28 :126 eC128,2001
Rioux JD, Daly MJ, Silverberg MS, Lindblad K, Steinhart H, Cohen Z, Delmonte T, Kocher K, Miller K, Guschwan S, Kulbokas EJ, O’Leary S, Winchester E, Dewar K, Green T, Stone V, Chow C, Cohen A, Langelier D, Lapointe G, Gaudet D, Faith J, Branco N, Bull SB, McLeod RS, Griffiths AM, Bitton A, Greenberg GR, Lander ES, Siminovitch KA, Hudson TJ: Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease. Nat Genet29 :223 eC228,2001
Laitinen T, Daly MJ, Rioux JD, Kauppi P, Laprise C, Petays T, Green T, Cargill M, Haahtela T, Lander ES, Laitinen LA, Hudson TJ, Kere J: A susceptibility locus for asthma-related traits on chromosome 7 revealed by genome-wide scan in a founder population. Nat Genet28 :87 eC91,2001
Martin ER, Lai EH, Gilbert JR, Rogala AR, Afshari AJ, Riley J, Finch KL, Stevens JF, Livak KJ, Slotterbeck BD, Slifer SH, Warren LL, Conneally PM, Schmechel DE, Purvis I, Pericak-Vance MA, Roses AD, Vance JM: SNPing away at complex diseases: analysis of single-nucleotide polymorphisms around APOE in Alzheimer disease. Am J Hum Genet67 :383 eC394,2000
Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, Lane CR, Schaffner SF, Bolk S, Brewer C, Tuomi T, Gaudet D, Hudson TJ, Daly M, Groop L, Lander ES: The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet26 :76 eC80,2000
Fajans SS, Bell GI, Polonsky KS: Molecular mechanisms and clinical pathophysiology of maturity-onset diabetes of the young. N Engl J Med345 :971 eC980,2001
Yamagata K, Furuta H, Oda N, Kaisaki PJ, Menzel S, Cox NJ, Fajans SS, Signorini S, Stoffel M, Bell GI: Mutations in the hepatocyte nuclear factor-4alpha gene in maturity-onset diabetes of the young (MODY1). Nature384 :458 eC460,1996
Yamagata K, Oda N, Kaisaki PJ, Menzel S, Furuta H, Vaxillaire M, Southam L, Cox RD, Lathrop GM, Boriraj VV, Chen X, Cox NJ, Oda Y, Yano H, Le Beau MM, Yamada S, Nishigori H, Takeda J, Fajans SS, Hattersley AT, Iwasaki N, Hansen T, Pedersen O, Polonsky KS, Bell GI: Mutations in the hepatocyte nuclear factor-1alpha gene in maturity-onset diabetes of the young (MODY3). Nature384 :455 eC458,1996
Vionnet N, Stoffel M, Takeda J, Yasuda K, Bell GI, Zouali H, Lesage S, Velho G, Iris F, Passa P, et al.: Nonsense mutation in the glucokinase gene causes early-onset non-insulin-dependent diabetes mellitus. Nature356 :721 eC722,1992
Malecki MT, Jhala US, Antonellis A, Fields L, Doria A, Orban T, Saad M, Warram JH, Montminy M, Krolewski AS: Mutations in NEUROD1 are associated with the development of type 2 diabetes mellitus. Nat Genet23 :323 eC328,1999
Stoffers DA, Ferrer J, Clarke WL, Habener JF: Early-onset type-II diabetes mellitus (MODY4) linked to IPF1. Nat Genet17 :138 eC139,1997
Horikawa Y, Iwasaki N, Hara M, Furuta H, Hinokio Y, Cockburn BN, Lindner T, Yamagata K, Ogata M, Tomonaga O, Kuroki H, Kasahara T, Iwamoto Y, Bell GI: Mutation in hepatocyte nuclear factor-1 beta gene (TCF2) associated with MODY. Nat Genet17 :384 eC385,1997
Wiltshire S, Frayling TM, Groves CJ, Levy JC, Hitman GA, Sampson M, Walker M, Menzel S, Hattersley AT, Cardon LR, McCarthy MI: Evidence from a large U.K. family collection that genes influencing age of onset of type 2 diabetes map to chromosome 12p and to the MODY3/NIDDM2 locus on 12q24. Diabetes53 :855 eC860,2004
Mahtani MM, Widen E, Lehto M, Thomas J, McCarthy M, Brayer J, Bryant B, Chan G, Daly M, Forsblom C, Kanninen T, Kirby A, Kruglyak L, Munnelly K, Parkkonen M, Reeve-Daly MP, Weaver A, Brettin T, Duyk G, Lander ES, Groop LC: Mapping of a gene for type 2 diabetes associated with an insulin secretion defect by a genome scan in Finnish families. Nat Genet14 :90 eC94,1996
Hegele RA CH, Harris SB, Hanleys AJG, Zinman B: The hepatic nuclear factor-1alpha G319S variant is associated with early-onset type 2 diabetes in Canadian Oji-Cree. J Clin Endocrinol Metab84 :1077 eC1082,1999
Chiu KC, Chuang LM, Ryu JM, Tsai GP, Saad MF: The I27L amino acid polymorphism of hepatic nuclear factor-1alpha is associated with insulin resistance. J Clin Endocrinol Metab85 :2178 eC2183,2000
Yamada S, Nishigori H, Onda H, Takahashi K, Kitano N, Morikawa A, Takeuchi T, Takeda J: Mutations in the hepatocyte nuclear factor-1 gene (MODY3) are not a major cause of late-onset NIDDM in Japanese subjects. Diabetes46 :1512 eC1513,1997
Urhammer SA, Rasmussen SK, Kaisaki PJ, Oda N, Yamagata K, Moller AM, Fridberg M, Hansen L, Hansen T, Bell GI, Pedersen O: Genetic variation in the hepatocyte nuclear factor-1 alpha gene in Danish Caucasians with late-onset NIDDM. Diabetologia40 :473 eC475,1997
Rissanen J, Wang H, Miettinen R, Karkkainen P, Kekalainen P, Mykkanen L, Kuusisto J, Karhapaa P, Niskanen L, Uusitupa M, Laakso M: Variants in the hepatocyte nuclear factor-1 and -4 genes in Finnish and Chinese subjects with late-onset type 2 diabetes. Diabetes Care23 :1533 eC1538,2000
Jackson AE, Cassell PG, North BV, Vijayaraghavan S, Gelding SV, Ramachandran A, Snehalatha C, Hitman GA: Polymorphic variations in the neurogenic differentiation-1, neurogenin-3, and hepatocyte nuclear factor-1 genes contribute to glucose intolerance in a South Indian population. Diabetes53 :2122 eC2125,2004
Behn PS, Wasson J, Chayen S, Smolovitch I, Thomas J, Glaser B, Permutt MA: Hepatocyte nuclear factor 1 coding mutations are an uncommon contributor to early-onset type 2 diabetes in Ashkenazi Jews. Diabetes47 :967 eC969,1998
Babaya N, Ikegami H, Kawaguchi Y, Fujisawa T, Nakagawa Y, Hamada Y, Hotta M, Ueda H, Shintani M, Nojima K, Kawabata Y, Ono M, Yamada K, Shen GQ, Fukuda M, Ogihara T: Hepatocyte nuclear factor-1alpha gene and non-insulin-dependent diabetes mellitus in the Japanese population. Acta Diabetol35 :150 eC153,1998
Winckler W, Graham RR, de Bakker PIW, Sun M, Almgren P, Tuomi T, Gaudet D, Hudson TJ, Ardlie KG, Daly MJ, Hirschhorn JN, Groop L, Altshuler D: Association testing of variants in the hepatocyte nuclear factor 4 gene with risk of type 2 diabetes in 7,883 people. Diabetes54 :886 eC892,2005
Florez JC, Sjogren M, Burtt N, Orho-Melander M, Schayer S, Sun M, Almgren P, Lindblad U, Tuomi T, Gaudet D, Hudson TJ, Daly MJ, Ardlie KG, Hirschhorn JN, Altshuler D, Groop L: Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes. Diabetes53 :3313 eC3318,2004
Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN: Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet33 :177 eC182,2003
Tang K, Fu DJ, Julien D, Braun A, Cantor CR, Koster H: Chip-based genotyping by mass spectrometry. Proc Natl Acad Sci U S A96 :10016 eC10020,1999
Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D: The structure of haplotype blocks in the human genome. Science296 :2225 eC2229,2002
Spielman RS, McGinnis RE, Ewens WJ: Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet52 :506 eC516,1993
Boehnke M, Langefeld CD: Genetic association mapping based on discordant sib pairs: the discordant-alleles test. Am J Hum Genet62 :950 eC961,1998
Cargill M, Altshuler D, Ireland J, Sklar P, Ardlie K, Patil N, Shaw N, Lane CR, Lim EP, Kalyanaraman N, Nemesh J, Ziaugra L, Friedland L, Rolfe A, Warrington J, Lipshutz R, Daley GQ, Lander ES: Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nat Genet22 :231 eC238,1999
Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA: Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet74 :106 eC120,2004
Weedon MN, Owen, KR, Shields B, Hitman G, Walker M, McCarthy MI, Hattersley AT, Frayling TM: A large-scale association analysis of common variation of the HNF1 gene with type 2 diabetes in the U.K. Caucasian population (Brief Genetics Report). Diabetes54 :2487 eC2491,2005
Florez JC, Sjogren M, Burtt N, Orho-Melander M, Schayer S, Sun M, Almgren P, Lindblad U, Tuomi T, Gaudet D, Hudson TJ, Daly MJ, Ardlie KG, Hirschhorn JN, Altshuler D, Groop L: Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes. Diabetes54 :3313 eC3318,2004
Ardlie KG, Lunetta KL, Seielstad M: Testing for population subdivision and association in four case-control studies. Am J Hum Genet71 :304 eC311,2002
van den Ouweland JM, Lemkes HHPJ, Trembath RC, Ross R, Velho G, Cohen D, Froguel P, Maassen JA: Maternally inherited diabetes and deafness is a distinct subtype of diabetes and associates with a single point mutation in the mitochondrial tRNALeu(UUR) gene. Diabetes43 :746 eC751,1994
Wilson FH, Disse-Nicodeme S, Choate KA, Ishikawa K, Nelson-Williams C, Desitter I, Gunel M, Milford DV, Lipkin GW, Achard JM, Feely MP, Dussol B, Berland Y, Unwin RJ, Mayan H, Simon DB, Farfel Z, Jeunemaitre X, Lifton RP: Human hypertension caused by mutations in WNK kinases. Science293 :1107 eC1112,2001(Wendy Winckler, Nol P. Bu)