Skip to main content
  • More from ADA
    • Diabetes Care
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care in Diabetes
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care
  • Subscribe
  • Log in
  • My Cart
  • Follow ada on Twitter
  • RSS
  • Visit ada on Facebook
Diabetes

Advanced Search

Main menu

  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • ADA Scientific Sessions Abstracts
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • ADA Scientific Sessions Abstracts
    • Diabetes COVID-19 Article Collection
    • Diabetes Symposium 2020
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Submit Cover Art
    • ADA Journal Policies
    • Instructions for Authors
    • ADA Peer Review
  • More from ADA
    • Diabetes Care
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care in Diabetes
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care

User menu

  • Subscribe
  • Log in
  • My Cart

Search

  • Advanced search
Diabetes
  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • ADA Scientific Sessions Abstracts
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • ADA Scientific Sessions Abstracts
    • Diabetes COVID-19 Article Collection
    • Diabetes Symposium 2020
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Submit Cover Art
    • ADA Journal Policies
    • Instructions for Authors
    • ADA Peer Review
Brief Genetics Reports

A Synonymous Coding Polymorphism in the α2-Heremans-Schmid Glycoprotein Gene Is Associated With Type 2 Diabetes in French Caucasians

  1. Afshan Siddiq1,
  2. Frederic Lepretre12,
  3. Serge Hercberg3,
  4. Philippe Froguel12 and
  5. Fernando Gibson1
  1. 1Section of Genomic Medicine, Imperial College, Hammersmith Campus, London, United Kingdom
  2. 2Institut de Biologie de Lille, Institut Pasteur, CHU, Lille, France
  3. 3U557 INSERM and Unite de Surveillance et d’Epidemiologie Nutritionnelle, InVS/CNAM, Institut Scientifique et Technique de la Nutrition et de l’Alimentation/CNAM, Paris, France
  1. Address correspondence and reprint requests to Fernando Gibson, Section of Genomic Medicine, 2nd Floor, 233 L Block, Imperial College, Hammersmith Campus, Du Cane Rd., London, W12 0NN U.K. E-mail: fernando.gibson{at}imperial.ac.uk
Diabetes 2005 Aug; 54(8): 2477-2481. https://doi.org/10.2337/diabetes.54.8.2477
PreviousNext
  • Article
  • Figures & Tables
  • Info & Metrics
  • PDF
Loading

Abstract

α2-Heremans-Schmid glycoprotein (AHSG) is an abundant plasma protein synthesized predominantly in the liver. The AHSG gene, consisting of seven exons and spanning 8.2 kb of genomic DNA, is located at chromosome 3q27, a susceptibility locus for type 2 diabetes and the metabolic syndrome. AHSG is a natural inhibitor of the insulin receptor tyrosine kinase, and AHSG-null mice exhibit significantly enhanced insulin sensitivity. These observations suggested that the AHSG gene is a strong positional and biological candidate for type 2 diabetes susceptibility. Direct sequencing of the AHSG promoter region and exons identified nine common single nucleotide polymorphisms (SNPs) with a minor allele frequency ≥5%. We carried out a detailed genetic association study of the contribution of these common AHSG SNPs to genetic susceptibility of type 2 diabetes in French Caucasians. The major allele of a synonymous coding SNP in exon 7 (rs1071592) presented significant evidence of association with type 2 diabetes (P = 0.008, odds ratio 1.27 [95% CI 1.06–1.52]). Two other SNPs (rs2248690 and rs4918) in strong linkage disequilibrium with rs1071592 showed evidence approaching significance. A haplotype carrying the minor allele of SNP rs1071592 was protective against type 2 diabetes (P = 0.014). However, our analyses indicated that rs1071592 is not associated with the evidence for linkage of type 2 diabetes to 3q27.

  • AHSG, α2-Heremans-Schmid glycoprotein
  • ASP, affected sibpair
  • IBD, identical by descent
  • SNP, single nucleotide polymorphism
  • UTR, untranslated region

α2-Heremans-Schmid glycoprotein (AHSG) is an abundant 49-kDa plasma protein synthesized predominantly in the liver (1). The AHSG gene is located at chromosome 3q27, a susceptibility locus for type 2 diabetes and the metabolic syndrome (2–4). Originally described as the major globulin in FCS (5), AHSG is also known as fetuin-A to distinguish it from the product of the adjacent paralogous gene, FETUB (fetuin-B).

AHSG is a multifunctional protein with diverse biological functions that include the regulation of calcium homeostasis (6,7). A possible role for AHSG in influencing genetic susceptibility to type 2 diabetes was first suggested by in vitro work demonstrating that AHSG inhibits, in a dose-dependent manner, the insulin-stimulated tyrosine kinase activity of the insulin receptor, insulin receptor autophosphorylation, and insulin substrate 1 phosphorylation (1,8). These effects were corroborated in vivo in rat liver and skeletal muscle following acute injection of human recombinant AHSG (9). AHSG-null mice exhibit significantly enhanced insulin sensitivity and are resistant to weight gain on a high-fat diet (10). In humans, serum AHSG levels have been reported to be significantly higher in patients with gestational diabetes than in healthy pregnant women and to be correlated with indirect measures of insulin resistance (11). A single nucleotide polymorphism (SNP) in the promoter region of AHSG was recently associated with insulin-mediated inhibition of lipolysis and stimulation of lipogenesis in adipocytes (12). These observations indicated that AHSG may play a physiological role in the regulation of insulin signaling and energy homeostasis. Taking into consideration its location at the 3q27 type 2 diabetes susceptibility locus, the AHSG gene suggested itself as a strong positional and biological candidate gene for type 2 diabetes susceptibility. Therefore, we have evaluated the contribution of common SNPs in the AHSG gene to type 2 diabetes susceptibility in the French Caucasian population.

RESEARCH DESIGN AND METHODS

American Diabetes Association 2003 criteria (13) for the classification of subjects as diabetic or normoglycemic were applied. The subset of 55 French families with early-onset type 2 diabetes (age at diagnosis <46 years) that produced the linkage result at chromosome 3q27 was described previously (3). The type 2 diabetes case-control study was carried out with a cohort of 682 unrelated type 2 diabetic subjects (age 60 ± 12 years, BMI 27.0 ± 3.5 kg/m2, men/women 55/45%) and 918 unrelated normoglycemic subjects (age 54 ± 11 years, BMI 24.6 ± 3.9 kg/m2, men/women, 41/59%). The type 2 diabetic cases were composed of 310 probands from type 2 diabetic families, recruited by P. Froguel’s CNRS Institute Pasteur Unit in Lille, and 372 singleton patients with a family history of type 2 diabetes recruited at the Endocrinology-Diabetology Department of the Corbeil-Essonne Hospital. The control subjects were composed of 372 normoglycemic husbands or wives from type 2 diabetic families, and 560 normoglycemic subjects from the SUVIMAX prospective population-based cohort study (14). The morbidly obese case-control study was carried out with a cohort of 575 unrelated morbidly obese patients (age 46 ± 12 years, BMI 47.3 ± 7.4 kg/m2, men/women 23/77%) (15) using the same control subjects as for the type 2 diabetes case-control study. Subjects were all of French Caucasian ancestry. With the exception of plasma insulin levels, a number of quantitative clinical phenotypes (including plasma levels of glucose, triglycerides, and cholesterol) were assayed in >95% of our normoglycemic cohort. Plasma insulin levels were only available for the 372 normoglycemic husbands or wives. The homeostasis model assessment of insulin resistance (HOMA-IR) index was calculated as fasting insulin (μU/ml) × fasting glucose (mmol/l)/22.5 (16). Informed consent was obtained from all subjects, and the study was approved by the local ethics committees.

Screening the AHSG gene for SNPs.

We carried out SNP detection by PCR followed by direct sequencing of the PCR products. PCR primer sequences are available on request. Genomic DNA sequence spanning the AHSG gene was obtained from the National Center for Biotechnology Information (NCBI) website (available from http://www.ncbi.nlm.nih.gov/; Entrez GeneID, 197). PCRs were performed with 100 ng human genomic DNA and Taq Gold polymerase (Applied Biosystems, Foster City, CA) using standard PCR conditions in a total volume of 25 μl. Sequencing reactions were performed with the BigDye Terminator v.3 cycle sequencing kit (Applied Biosystems) and electrophoresed on the Applied Biosystems 3700 Genetic Analyzer according to the manufacturer’s instructions. Sequence analysis and SNP identification were carried out using the Phred/Phrap/Consed system (17,18). We sequenced ∼1 kb upstream of the ATG codon, each exon together with ∼200 bp flanking intronic sequence and 500 bp of the 3′ untranslated region (UTR) in 24 unrelated probands (48 chromosomes) taken from the 24 type 2 diabetic families with the strongest evidence of linkage at 3q27 (a nonparametric linkage score ≥0.816). SNPs identified in two or less heterozygote subjects of 24 (allele frequency ≤4%) were designated rare SNPs.

SNP genotyping.

Genotyping was performed with the Sequenom MassARRAY system, as previously described (19).

Statistical analyses.

Comparisons of SNP allele and haplotype frequencies in case and control groups were performed using the χ2 test, with P values presented uncorrected for multiple testing. The SNPspD method (20) for correction of multiple SNP testing was employed. The basis of this method is the use of spectral decomposition of matrices of pairwise SNP linkage disequilibrium to generate an adjusted significance threshold. Testing SNP alleles for association with quantitative traits was carried out with the Wilcoxon–Kruskal-Wallis. Pairwise SNP linkage disequilibrium was calculated with the GOLD software package (21) from the haplotype counts output by PHASE (22). The Haplotype Trend Regression program (23) was used to test inferred haplotypes for association with quantitative phenotypes. Associations with the evidence for linkage analyses were carried out as described previously (24). Briefly, this involved comparing the expected and observed allele-sharing proportions for affected sibpairs (ASPs) with concordant 1/x–1/x genotypes, where one is the major allele and x is either the major or minor allele, conditional on the identical-by-descent (IBD) allele-sharing distribution of the original genome scan dataset (3).

RESULTS

The AHSG gene, consisting of seven exons and spanning 8.2 kb of genomic DNA, was screened for SNPs by direct sequencing. We identified nine common SNPs within the AHSG gene with a minor allele frequency ≥5% and six rare SNPs (Table 1). The same common SNPs were identified in a recent study of the effect of AHSG gene variation on obesity and insulin action in the Swedish population (12). Since the aim of this study was to evaluate common variation in the AHSG gene, the rare SNPs were not subjected to any further analysis. In addition, no further analysis was carried out on SNP rs4831 due to failure to successfully genotype it using either the Sequenom (19) or Taqman methods (25).

The other eight common AHSG SNPs were genotyped in our type 2 diabetic case-control cohort with an average success rate of 88%. The genotype distribution was in accordance with Hardy-Weinberg equilibrium for all SNPs (data not shown). We first evaluated the extent of pairwise linkage disequilibrium, as quantified by the metrics D′ and Δ2 (Fig. 1). The average D′ and Δ2 values across the AHSG gene were 0.92 and 0.28, respectively. SNPs rs4917 and rs4918 exhibited almost complete linkage disequilibrium (Δ2 = 0.95), whereas SNPs rs2248690 and rs1071592, at opposite ends of the gene, were also in strong linkage disequilibrium (Δ2 = 0.86). The results of evaluating each of the common SNPs for association with type 2 diabetes are presented in Table 2. The major allele of SNP rs1071592, a synonymous SNP in exon 7, presented evidence of association with type 2 diabetes (P = 0.008, odds ration [OR] 1.27 [95% CI 1.06–1.52]). We also observed borderline association for SNPs rs2248690 (P = 0.06) and rs4918 (P = 0.09). These results are consistent with the high level of linkage disequilibrium between these three SNPs, as measured by Δ2. Note that P values are presented uncorrected for multiple testing. Using the SNPSpD correction method of Nyholt (20), which accounts for intermarker linkage disequilibrium, a significance threshold of 0.009 was obtained for the eight AHSG SNPs tested. The rs1071592 association result fell just under this threshold.

SNP rs1071592 was evaluated for association with the evidence for linkage of type 2 diabetes to 3q27, using the linkage partitioning method described previously (24). We found that the observed IBD-sharing proportion of concordant-genotype ASPs carrying the major allele was no higher than that expected under the null hypothesis of no association with the evidence for linkage. The observed IBD-sharing proportion was 0.69 (from a total of 72 ASPs), whereas the expected IBD-sharing proportion for an allele with a frequency equal to that of the major allele of SNP rs1071592 was 0.75 (a total of 69 ASPs). This result argued against the hypothesis that SNP rs1071592 is significantly associated with the evidence for linkage and was corroborated using a simulation-based approach (15) (data not shown).

There were no significant differences in SNP allele or haplotype frequencies between males and females, and no additional type 2 diabetes associations were uncovered by stratifying for sex (data not shown). None of the AHSG SNPs were associated with BMI, HOMA-IR, or with plasma levels of glucose, triglycerides, or cholesterol in our nondiabetic cohort (data not shown).

The AHSG haplotype frequency distribution of type 2 diabetic case and control subjects is shown in Table 3. A total of six common AHSG haplotypes were identified, accounting for 95% of control chromosomes. The average probability of the most likely haplotype pair across the dataset was 0.95 ± 0.13. Haplotype 21122221 was associated with normoglycemia (P = 0.014), indicating a protective effect against type 2 diabetes. This finding is consistent with the SNP association results, since this haplotype is the only one carrying the minor (protective) allele of SNP rs1071592.

The observation that AHSG-null mice are resistant to diet-induced obesity (10) prompted us to examine a possible role for AHSG gene variation in susceptibility to human obesity. An obesity case-control study was carried out in which we genotyped AHSG SNPs in 575 morbidly obese (BMI >40 kg/m2) subjects, using the previously genotyped normoglycemic control subjects as the control set. However, we found no evidence for association of AHSG SNPs or haplotypes with morbid obesity (data not shown).

DISCUSSION

Significant evidence of association with type 2 diabetes was observed for a synonymous coding SNP rs1071592 in exon 7. The data presented here suggests that rs1071592 is a novel candidate polymorphism for modulating susceptibility to type 2 diabetes. However, additional large-scale case-control studies are clearly warranted to confirm the involvement of this variant in the genetic basis of type 2 diabetes susceptibility. This is especially true given that the rs1071592 association result fell just under the significance threshold after accounting for multiple testing.

SNP screening was only carried out in and around the exons and promoter region; therefore, we cannot rule out the possibility that other unassayed type 2 diabetes susceptibility SNPs exist within as yet unidentified regulatory regions within the AHSG gene. With the aim of identifying additional regulatory regions, we examined the human-mouse comparative genomic sequence of the AHSG gene together with 10 kb of flanking sequence on the VISTA website (available from http://pipeline.lbl.gov/cgi-bin/gateway2). Apart from two regions showing ≥70 conservation identities (in the promoter and proximal intron six regions) that were actually included within the sequences screened for SNPs, no other conserved regions were identified.

Although AHSG has been shown to inhibit the activity of the insulin receptor (1,8,9) we failed to find an association between AHSG SNPs and HOMA-IR. However, the number of normoglycemic subjects with fasting insulin levels (n = 372) provided only modest statistical power to detect an association of moderate effect. We also found no evidence for association of rs2077119 with type 2 diabetes, a promoter SNP that had previously been associated with insulin-mediated lipid metabolism in adipocytes (12).

Finally, we found no evidence that SNP rs1071592 is associated with the evidence for linkage of type 2 diabetes to 3q27, indicating that an as yet unidentified gene or genes at 3q27 is responsible for the linkage signal. Our efforts aimed at identifying the “causative” type 2 diabetes gene at 3q27 are ongoing.

FIG. 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIG. 1.

Pairwise linkage disequilibrium measures for common SNPs spanning the AHSG gene. Pairwise linkage disequilibrium was calculated with the GOLD software package (21) from the combined haplotype counts of the type 2 diabetic case and normoglycemic control subjects output by PHASE (22). P values were all <0.001.

View this table:
  • View inline
  • View popup
TABLE 1

Position of SNPs in the human AHSG gene

View this table:
  • View inline
  • View popup
TABLE 2

AHSG SNP allele frequencies in type 2 diabetic case and normoglycemic control subjects

View this table:
  • View inline
  • View popup
TABLE 3

AHSG haplotype distribution in type 2 diabetic case and normoglycemic control subjects

Acknowledgments

This work is supported by a Wellcome Trust University Award to F.G. (no. GR065414MF), and grants from Diabetes UK (BDA no. RD01/0002308), the Association Française des Diabétologues de Langue Française (ALFEDIAM), the EU-funded GIFT Grant, the Direction de la Recherche Clinique/Assistance Publique-Hopitaux de Paris, and the program Hospitalier de Recherche Clinique (AOM 96088).

We thank Stephan Lobbens for his technical expertise and Andrew Walley and two anonymous referees for critically appraising draft versions of the manuscript.

Footnotes

    • Accepted May 4, 2005.
    • Received March 3, 2005.
  • DIABETES

REFERENCES

  1. ↵
    Auberger P, Falquerho L, Contreres JO, Pages G, Le Cam G, Rossi B, Le Cam A: Characterization of a natural inhibitor of the insulin receptor tyrosine kinase: cDNA cloning, purification, and anti-mitogenic activity. Cell58 :631 –640,1989
    OpenUrlCrossRefPubMedWeb of Science
  2. ↵
    Kissebah AH, Sonnenberg GE, Myklebust J, Goldstein M, Broman K, James RG, Marks JA, Krakower GR, Jacob HJ, Weber J, Martin L, Blangero J, Comuzzie AG: Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc Natl Acad Sci U S A97 :14478 –14483,2000
    OpenUrlAbstract/FREE Full Text
  3. ↵
    Vionnet N, Hani El H, Dupont S, Gallina S, Francke S, Dotte S, De Matos F, Durand E, Lepretre F, Lecoeur C, Gallina P, Zekiri L, Dina C, Froguel P: Genomewide search for type 2 diabetes-susceptibility genes in French whites: evidence for a novel susceptibility locus for early-onset diabetes on chromosome 3q27-qter and independent replication of a type 2-diabetes locus on chromosome 1q21–q24. Am J Hum Genet67 :1470 –1480,2000
    OpenUrlCrossRefPubMedWeb of Science
  4. ↵
    Francke S, Manraj M, Lacquemant C, Lecoeur C, Lepretre F, Passa P, Hebe A, Corset L, Yan SL, Lahmidi S, Jankee S, Gunness TK, Ramjuttun US, Balgobin V, Dina C, Froguel P: A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16p13 and replicates linkage with the metabolic syndrome on 3q27. Hum Mol Genet10 :2751 –2765,2001
    OpenUrlAbstract/FREE Full Text
  5. ↵
    Pedersen KO: Fetuin: a new globin isolated from serum. Nature154 :575 ,1944
    OpenUrl
  6. ↵
    Wang H, Zhang M, Soda K, Sama A, Tracey KJ: Fetuin protects the fetus from TNF (Letter). Lancet350 :861 –862,1997
    OpenUrlPubMedWeb of Science
  7. ↵
    Schafer C, Heiss A, Schwarz A, Westenfeld R, Ketteler M, Floege J, Muller-Esterl W, Schinke T, Jahnen-Dechent W: The serum protein alpha 2-Heremans-Schmid glycoprotein/fetuin-A is a systemically acting inhibitor of ectopic calcification. J Clin Invest112 :357 –366,2003
    OpenUrlCrossRefPubMedWeb of Science
  8. ↵
    Srinivas PR, Wagner AS, Reddy LV, Deutsch DD, Leon MA, Goustin AS, Grunberger G: Serum alpha 2-HS-glycoprotein is an inhibitor of the human insulin receptor at the tyrosine kinase level. Mol Endocrinol7 :1445 –1455,1993
    OpenUrlCrossRefPubMedWeb of Science
  9. ↵
    Mathews ST, Chellam N, Srinivas PR, Cintron VJ, Leon MA, Goustin AS, Grunberger G: Alpha2-HSG: a specific inhibitor of insulin receptor autophosphorylation, interacts with the insulin receptor. Mol Cell Endocrinol164 :87 –98,2000
    OpenUrlCrossRefPubMedWeb of Science
  10. ↵
    Mathews ST, Singh GP, Ranalletta M, Cintron VJ, Qiang X, Goustin AS, Jen KL, Charron MJ, Jahnen-Dechent W, Grunberger G: Improved insulin sensitivity and resistance to weight gain in mice null for the Ahsg gene. Diabetes51 :2450 –2458,2002
    OpenUrlAbstract/FREE Full Text
  11. ↵
    Kalabay L, Cseh K, Pajor A, Baranyi E, Csakany GM, Melczer Z, Speer G, Kovacs M, Siller G, Karadi I, Winkler G: Correlation of maternal serum fetuin/alpha2-HS-glycoprotein concentration with maternal insulin resistance and anthropometric parameters of neonates in normal pregnancy and gestational diabetes. Eur J Endocrinol147 :243 –248,2002
    OpenUrlAbstract
  12. ↵
    Dahlman I, Eriksson P, Kaaman M, Jiao H, Lindgren CM, Kere J, Arner P: alpha(2)-Heremans-Schmid glycoprotein gene polymorphisms are associated with adipocyte insulin action. Diabetologia47 :1974 –1979,2004
    OpenUrlCrossRefPubMedWeb of Science
  13. ↵
    Expert Committee on the Diagnosis and Classification of Diabetes Mellitus: Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care26 (Suppl. 1) :S5 –S20,2003
  14. ↵
    Hercberg S, Preziosi P, Briancon S, Galan P, Triol I, Malvy D, Roussel AM, Favier A: A primary prevention trial using nutritional doses of antioxidant vitamins and minerals in cardiovascular diseases and cancers in a general population: the SU.VI.MAX study: design, methods, and participant characteristics. SUpplementation en VItamines et Mineraux AntioXydants. Control Clin Trials19 :336 –351,1998
    OpenUrlCrossRefPubMedWeb of Science
  15. ↵
    Boutin P, Dina C, Vasseur F, Dubois SS, Corset L, Seron K, Bekris L, Cabellon J, Neve B, Vasseur-Delannoy V, Chikri M, Charles MA, Clement K, Lernmark A, Froguel P: GAD2 on chromosome 10p12 is a candidate gene for human obesity. PLoS Biol1 :E68 ,2003
    OpenUrlPubMed
  16. ↵
    Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC: Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia28 :412 –419,1985
    OpenUrlCrossRefPubMedWeb of Science
  17. ↵
    Ewing B, Hillier L, Wendl MC, Green P: Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res8 :175 –185,1998
    OpenUrlAbstract/FREE Full Text
  18. ↵
    Gordon D, Abajian C, Green P: Consed: a graphical tool for sequence finishing. Genome Res8 :195 –202,1998
    OpenUrlAbstract/FREE Full Text
  19. ↵
    Jurinke C, van den Boom D, Cantor CR, Koster H: Automated genotyping using the DNA MassArray technology. Methods Mol Biol187 :179 –192,2002
    OpenUrlCrossRefPubMed
  20. ↵
    Nyholt DR: A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet74 :765 –769,2004
    OpenUrlCrossRefPubMedWeb of Science
  21. ↵
    Abecasis GR, Cookson WO: GOLD: graphical overview of linkage disequilibrium. Bioinformatics16 :182 –183,2000
    OpenUrlAbstract/FREE Full Text
  22. ↵
    Stephens M, Smith NJ, Donnelly P: A new statistical method for haplotype reconstruction from population data. Am J Hum Genet68 :978 –989,2001
    OpenUrlCrossRefPubMedWeb of Science
  23. ↵
    Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG: Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered53 :79 –91,2002
    OpenUrlCrossRefPubMedWeb of Science
  24. ↵
    Gibson F, Froguel P: Genetics of the APM1 locus and its contribution to type 2 diabetes susceptibility in French Caucasians. Diabetes53 :2977 –2983,2004
    OpenUrlAbstract/FREE Full Text
  25. ↵
    Livak KJ: Allelic discrimination using fluorogenic probes and the 5′ nuclease assay. Genet Anal14 :143 –149,1999
    OpenUrlPubMed
PreviousNext
Back to top

In this Issue

August 2005, 54(8)
  • Table of Contents
  • Index by Author
Sign up to receive current issue alerts
View Selected Citations (0)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word about Diabetes.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
A Synonymous Coding Polymorphism in the α2-Heremans-Schmid Glycoprotein Gene Is Associated With Type 2 Diabetes in French Caucasians
(Your Name) has forwarded a page to you from Diabetes
(Your Name) thought you would like to see this page from the Diabetes web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
A Synonymous Coding Polymorphism in the α2-Heremans-Schmid Glycoprotein Gene Is Associated With Type 2 Diabetes in French Caucasians
Afshan Siddiq, Frederic Lepretre, Serge Hercberg, Philippe Froguel, Fernando Gibson
Diabetes Aug 2005, 54 (8) 2477-2481; DOI: 10.2337/diabetes.54.8.2477

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Add to Selected Citations
Share

A Synonymous Coding Polymorphism in the α2-Heremans-Schmid Glycoprotein Gene Is Associated With Type 2 Diabetes in French Caucasians
Afshan Siddiq, Frederic Lepretre, Serge Hercberg, Philippe Froguel, Fernando Gibson
Diabetes Aug 2005, 54 (8) 2477-2481; DOI: 10.2337/diabetes.54.8.2477
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • RESEARCH DESIGN AND METHODS
    • RESULTS
    • DISCUSSION
    • Acknowledgments
    • Footnotes
    • REFERENCES
  • Figures & Tables
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • The Krüppel-Like Factor 11 (KLF11) Q62R Polymorphism Is Not Associated With Type 2 Diabetes in 8,676 People
  • CHRM3 Gene Variation Is Associated With Decreased Acute Insulin Secretion and Increased Risk for Early-Onset Type 2 Diabetes in Pima Indians
  • Polymorphism in the Transcription Factor 7-Like 2 (TCF7L2) Gene Is Associated With Reduced Insulin Secretion in Nondiabetic Women
Show more Brief Genetics Reports

Similar Articles

Navigate

  • Current Issue
  • Online Ahead of Print
  • Scientific Sessions Abstracts
  • Collections
  • Archives
  • Submit
  • Subscribe
  • Email Alerts
  • RSS Feeds

More Information

  • About the Journal
  • Instructions for Authors
  • Journal Policies
  • Reprints and Permissions
  • Advertising
  • Privacy Policy: ADA Journals
  • Copyright Notice/Public Access Policy
  • Contact Us

Other ADA Resources

  • Diabetes Care
  • Clinical Diabetes
  • Diabetes Spectrum
  • Scientific Sessions Abstracts
  • Standards of Medical Care in Diabetes
  • BMJ Open - Diabetes Research & Care
  • Professional Books
  • Diabetes Forecast

 

  • DiabetesJournals.org
  • Diabetes Core Update
  • ADA's DiabetesPro
  • ADA Member Directory
  • Diabetes.org

© 2021 by the American Diabetes Association. Diabetes Print ISSN: 0012-1797, Online ISSN: 1939-327X.