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The Journal of Clinical Endocrinology & Metabolism Vol. 87, No. 6 2606-2610
Copyright © 2002 by The Endocrine Society

The Impact of the Human Genome on Endocrinology: Original Articles

Variation within the Type 2 Diabetes Susceptibility Gene Calpain-10 and Polycystic Ovary Syndrome

Lema Haddad, Julie C. Evans, Neda Gharani, Carole Robertson, Karen Rush, Steven Wiltshire, Timothy M. Frayling, Terence J. Wilkin, Andrew Demaine, Ann Millward, Andrew T. Hattersley, Gerry Conway, Nancy J. Cox, Graeme I. Bell, Steve Franks and Mark I. McCarthy

Complex Traits Analysis Group (L.H., N.G., S.W., M.I.M.), Department of Medicine, Imperial College Genetics and Genomics Research Institute, and Medical Research Council Clinical Sciences Centre, Imperial College School of Medicine, London W12 0NN, United Kingdom; Department of Diabetes and Vascular Medicine (J.C.E., T.M.F., A.T.H.), School of Postgraduate Medicine and Health Sciences, University of Exeter, Exeter EX2 5AX, United Kingdom; Department of Reproductive Science and Medicine (C.R., K.R., S.F.), Institute of Reproductive and Developmental Biology, Imperial College of Science Technology and Medicine, Hammersmith Hospital, London W12 0NN, United Kingdom; Wellcome Trust Centre for Human Genetics (S.W.), Oxford OX3 7BN, United Kingdom; Plymouth Postgraduate Medical School (T.J.W., A.D., A.M.), Plymouth University, Plymouth PL6 8BH, United Kingdom; Department of Diabetes & Endocrinology (G.C.), the Middlesex Hospital, London W1T 3AA, United Kingdom; Department of Medicine and Human Genetics (N.J.C.), The University of Chicago, Chicago, Illinois 60637; Howard Hughes Medical Institute and Departments of Biochemistry and Molecular Biology (G.I.B.), Medicine and Human Genetics, the University of Chicago, Chicago, Illinois 60637

Address all correspondence and requests for reprints to: Prof. Mark I. McCarthy, Complex Traits Analysis Group, Imperial College Genetics and Genomics Research Institute, Imperial College School of Medicine, London W12 0NN, United Kingdom. E-mail: . m.mccarthy{at}ic.ac.uk

Abstract

Variation within the calpain-10 gene (CAPN10) has been proposed to account for linkage to type 2 diabetes on chromosome 2q in Mexican-Americans, and associations with diabetes have been reported in several other populations. Given the epidemiological, physiological, and genetic overlap between type 2 diabetes and polycystic ovary syndrome (PCOS), CAPN10 represents a strong candidate gene for a role in PCOS susceptibility. Using both family based and case-control association resources (146 parent-offspring trios; 185 additional PCOS cases; 525 control subjects, all of European ancestry), we sought association between CAPN10 variation and PCOS, focusing on four single nucleotide polymorphism (SNP) variants (SNP-44, SNP-43; SNP-19; SNP-63). On single-locus transmission disequilibrium analysis in the 146 trios, there was nominal evidence (P = 0.03) of excess transmission of the more common allele at SNP-63. This association was not, however, replicated in the case-control analysis. No other significant associations were observed at the single-locus or haplotype level in either the transmission-disequilibrium or case-control analyses. The relative risk for the high-risk diabetes susceptibility 112/121 genotype (SNPs 43–19-63) was 0.84 (95% confidence intervals, 0.40–1.71). No associations were seen with intermediate traits of relevance to diabetes and PCOS pathogenesis. We have found no evidence from these analyses that CAPN10 gene variation influences susceptibility to PCOS.

POLYCYSTIC OVARY SYNDROME (PCOS) is a heterogeneous endocrine disorder of premenopausal women and the commonest cause of anovulatory infertility and hirsutism (1, 2). In addition to these important endocrine and reproductive manifestations, PCOS has metabolic characteristics that include prominent defects in both insulin action (3) and ß-cell function (4). These metabolic derangements are similar to those seen in groups at increased risk of future type 2 diabetes, such as offspring of diabetic parents and women with previous gestational diabetes (5). Indeed, the frequent co-occurrence of polycystic ovaries and type 2 diabetes strongly suggests shared aetiological determinants underlying the two conditions. There is both a higher incidence of impaired glucose tolerance among women with a past history of PCOS compared with control populations (6, 7) and an increased prevalence of polycystic ovarian morphology in women with frank (8) and gestational (9) diabetes.

PCOS, like type 2 diabetes, displays strong familial aggregation (10). The etiology is multifactorial, individual susceptibility being determined by the action of multiple genetic and environmental risk factors. Studies at the insulin gene are consistent with the hypothesis that shared genetic susceptibility effects contribute to the physiological and epidemiological overlap between type 2 diabetes and PCOS. In both conditions, susceptibility is associated with the paternal transmission of class III insulin-variable number of tandem repeats alleles (11, 12, 13, 14). On this basis, any gene known to influence susceptibility effects to type 2 diabetes merits evaluation as a candidate for involvement in PCOS.

Recent work has identified the calpain-10 gene (CAPN10) on chromosome 2q37 as such a candidate. This chromosomal region was initially highlighted in a genome-wide scan for linkage to type 2 diabetes conducted in Mexican-American families (15). Subsequent positional cloning efforts (16, 17) revealed that variants in the CAPN10 gene displayed the most robust associations with diabetes and were uniquely able to account for the original evidence for linkage. In Mexican-Americans, SNP-43 was the variant most strongly associated with the evidence for linkage (17). However, inclusion of genotype data from other CAPN10 polymorphisms strengthened the association with type 2 diabetes in both Mexican-American and European populations (17, 18). It appears that CAPN10-encoded susceptibility to type 2 diabetes is best described in terms of haplotypes including several different polymorphic sites. It has been estimated that variation within CAPN10 explains 14% of type 2 diabetes risk in Mexican-Americans. Studies that have sought replication of these associations in other populations have produced somewhat conflicting results, with some reports strongly positive (19, 20), others providing more guarded support (21, 22, 23), and others negative (24, 25).

The biological mechanisms relating variation in expression or function of CAPN10, a ubiquitously expressed protease (26, 27), to the development of type 2 diabetes, remain to be determined. Neither is it known whether the susceptibility effects of CAPN10 variation extend to other phenotypes associated with diabetes and insulin resistance. In this study, we have used both family based and case-control methodologies to explore the relationship between variation in the CAPN10 gene and the development of polycystic ovarian syndrome.

Materials and Methods

Subjects

Cases. All subjects in this study were of European, predominantly (>80%) British, ancestry. Women with PCOS (n = 331) were ascertained from infertility and endocrine clinics at St. Mary’s and the Middlesex Hospitals (London, UK). The criteria for diagnosis of PCOS were as previously described (10) and rely on the combination of clinical symptoms, ultrasonographic examination, and biochemical data. The essential criteria for the diagnosis of PCOS in the proband were the presence of polycystic ovaries on ultrasound in a patient presenting with hyperandrogenism (hirsutism, acne and/or elevated serum T) and/or symptoms of anovulation (amenorrhoea or oligomenorrhoea). For 146 of these 331 women (designated probands), DNA was available from both parents such that parent-offspring trios could be generated: the remaining 185 without parental DNA are designated PCOS cases. Family relationships in the trios were confirmed by genotyping with a panel of highly polymorphic microsatellite markers (combined heterozygosity >99%). Clinical characteristics are given in Table 1Go. All subjects gave fully informed consent.


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  		Table 1. Clinical characteristics of subjects with PCOS

 
Population sample (control subjects). Population allele and haplotype frequencies for the case-control analyses were derived from a population-based sample of 525 British Europid subjects. These represent cord bloods from a consecutive series of unrelated births, collected as part of the EarlyBird Study Cohort (Plymouth, UK) as described elsewhere (28).

Assays. In all PCOS women, fasting samples were used for the analysis of plasma cholesterol, high density lipoprotein (HDL)-cholesterol, triglycerides, insulin, and glucose. Glucose and lipids were measured enzymatically on an AU5200 analyzer (Olympus Corp. Opticals UK Ltd., London, UK). Selective precipitation of non-HDL lipoproteins using dextran sulfate and magnesium was used to assay levels of HDL-cholesterol. Insulin levels were measured by ELISA (29). Androstenedione, 17-hydroxyprogesterone, dihydrotestosterone, and T were measured using in-house RIAs employing ether extraction and dextran-coated charcoal separation. Mean coefficients of variation were <10% for androstenedione and 17-hydroxyprogesterone and <15% for dihydrotestosterone. SHBG was measured using the Immulite method (Diagnostic Products, Llanberis, UK) (1, 30). Genomic DNA was extracted from whole blood using the PUREGENE kit (Gentra Systems, Minneapolis, MN) as described previously (31).

Single nucleotide polymorphism (SNP) genotyping. For this study, four CAPN10 variants were typed. Three of these (SNP-43; SNP-19; SNP-63) define the high-risk haplotypes for diabetes susceptibility in Mexican-American and two Northern European populations (from Botnia, Finland and Saxony, Germany) (17). The fourth (SNP-44), which lies 11 bp proximal to SNP-43, was included on the basis of: 1) proven functional effects on CAPN10 expression (17); and 2) data suggesting that SNP-44 might play an independent type 2 diabetes-susceptibility role in British families (21).

Details of typing methods for these SNPs are provided in Table 2Go. SNP-44 (CAPN10-g.4841T/C) and SNP-43 (CAPN10-g.4852G/A) were typed using mutagenically separated PCR assays that employ one common and two size-differentiated allele-specific primers. Nucleotide mismatches were introduced to improve allele specificity where necessary (32) and allele-specific primer concentrations adjusted to compensate for the different PCR efficiencies of the two amplifications (typically, a ratio of long to short primer of 15:1). SNP-63 (CAPN10-g.1637C/T) was typed using a forced HhaI (New England Biolabs, Inc., Beverly, MA) PCR-restriction fragment length polymorphism assay. SNP-19 (CAPN10-g.7920indel32bp) is, in fact, a 32-bp insertion/deletion polymorphism and was typed directly after PCR amplification.


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  		Table 2. Details of genotyping methods for CAPN10 variants

 
In all cases, PCR were carried out in a total volume of 20 µl containing 5% dimethylsulfoxide vol/vol; 0.2 U Taq polymerase (Bioline, London, UK), 200 µl each deoxy-nucleotide triphosphate (Amersham Biosciences, Little Chalfont, UK), 1x PCR buffer (16 mmol/liter (NH4)2SO4; 67 mmol/liter Tris-HCl, pH 8.4; 0.01% Tween 20) and 50 ng DNA. Final MgCl2 concentration (mmol/liter) was 1.5 for SNP-44, -43, and -19 and 1.0 for SNP-63. Optimal PCR conditions included an initial denaturation of 12 min at 96 C, followed by 35 cycles of denaturation (96 C x 30 sec); annealing (30 s at 56 C for SNP-43, 60 C for SNP-44 and SNP-19 and 62 C for SNP63); extension (72 C x 30 sec); and final extension of 10 min at 72 C. The SNP-63 HhaI digestion required incubation of PCR product with 3 U enzyme at 37 C for 2 h.

All PCRs were analyzed by polyacrylamide microplate diagonal gel electrophoresis (33). Alleles are labeled in line with the nomenclature previously devised (17). Thus, allele 1 corresponds to allele G for SNP-43, allele T for SNP-44, allele C for SNP-63, and to the deletion allele for SNP-19.

Statistical analyses

In the parent-offspring trios, single and multilocus transmission disequilibrium analyses (34) were performed using the TRANSMIT software (35, 36). Proportions of heterozygous parents and percentage transmissions from heterozygous parents were derived from the TRANSMIT output, under the assumption of Hardy-Weinberg equilibrium. When computing global tests for the multilocus analyses, all rare haplotypes (frequency <5%) were pooled.

The primary analysis of the single-locus case-control data applied the Kruskal-Wallis test to individual genotypes, exact significance values being obtained using STATXACT (Cytel, Cambridge, MA). For case-control analyses comparing haplotype frequencies, we performed likelihood-ratio tests based on the haplotype frequency likelihoods derived from TRANSMIT. Due to the low numbers of observations of certain haplotypes (making asymptotic assumptions invalid) empirical significance values were determined from 20,000 permutations of case/control status and likelihood recalculation.

Haplotype counts for estimation of the odds ratios for the high-risk haplotype (112/121 at SNP-43, -19, and -63) (17) were derived from phased (trios) and nonphase (cases and controls) genotype data, the latter on the assumption that all individuals homozygous at SNP-43 and heterozygous at SNP-19 and SNP-63 carried this configuration. The low frequency of the 122 haplotype in Europeans means this is true in >90% of such individuals. Similar assumptions were used to estimate absolute haplotype counts for odds ratio analyses for other observed genotype combinations. Significance testing of the odds ratio was performed using exact probabilities implemented by STATXACT.

Results

Single-locus analyses

Genotypes at all loci were in Hardy-Weinberg equilibrium with the exception of a marginal departure (uncorrected P = 0.045) seen in PCOS cases at SNP-44. Results from the single-locus transmission disequilibrium tests of CAPN10 variants in the 146 trios are shown in Table 3Go. No deviations from Mendelian expectation were detected at SNP-44 (54.9% transmission of allele 1; P = 0.38); SNP-43 (51.3% transmission; P = 0.78); or SNP-19 (46.7% transmission, P = 0.44). At SNP-63, there was nominally significant excess transmission of the common allele from heterozygous parents to PCOS offspring (67.2% transmission; P = 0.03). However, single-locus tests in the independent case-control cohort of 185 cases and a population sample of 525 subjects (Table 4Go) revealed no association at any of the variants. In particular, there were no genotype (P = 0.62) or allele (P = 0.73) frequency differences at SNP-63, nor was there evidence for association at SNP-63 when all PCOS subjects (cases and probands, n = 331) were included in the case-control comparison (genotype-wise P = 0.64; allele-wise P = 0.56).


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  		Table 3. Single locus transmission disequilibrium testing of CAPN 10 variants in 146 PCOS parent-offspring trios

 

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  		Table 4. Single-locus case-control association study of CAPN10 variants

 
Multilocus analyses

We observed strong linkage disequilibrium between these variants (P < 0.001), and significantly reduced haplotype diversity (Table 5Go). Five of the 16 possible haplotypes accounted for >98% of all chromosomes observed, reflecting the haplotype distribution previously observed in other European populations (17, 21). Compared with Mexican-American and Asian populations (17), European populations show more (43–19-63) 111 haplotypes (0.31 in our UK population sample compared with 0.17 in Mexican-Americans, 0.08 in Chinese and 0.14 in Japanese) and fewer 112 haplotypes (0.07 in the UK vs. 0.23 in Mexican-Americans, 0.31 in Chinese, and 0.25 in Japanese).


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  		Table 5. CAPN10 haplotype frequencies in subject groups

 
Comparison of haplotype frequencies between probands and control subjects suggested a preponderance of 1111 haplotypes in the probands (Table 5Go), but the empirical significance of the proband vs. control comparison was not significant (P = 0.082; 20,000 replicates). No association was observed in the comparison of cases and controls (P = 0.40), nor when all (n = 331) PCOS individuals were pooled and compared with control subjects (P = 0.097). Neither was any significant excess transmission of 1111 (or any other haplotype) observed using the multilocus family based association studies in the trios (Table 6Go: global chisquare = 7.68. df5, P = 0.18).


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  		Table 6. Multi-locus transmission disequilibrium analysis of 146 PCOS parent-offspring trios

 
In both Mexican-Americans and Northern Europeans (Finnish and German), the 112/121 (SNP-43, -19, -63) multilocus genotype has been reported as displaying the highest risk, approximately 3-fold, for type 2 diabetes (17). There was no evidence that this haplotype combination was associated with an increased risk for PCOS in our data set (odds ratio 0.84 (95% CI 0.40–1.71) for pooled PCOS cases and probands vs. control subjects, P = 0.61). In fact, no haplotype combination (of the fifteen possible derived from the five common haplotypes) was associated with an increased odds ratio for PCOS, the only nominally significant result being obtained for the 2111/2111 genotype [odds ratio 0.12 (0.02–0.82), P = 0.019].

Intermediate trait analysis

To detect any relationship between CAPN10 variation and intermediate and quantitative traits relevant to the pathogenesis of type 2 diabetes and PCOS, we looked for genotype-dependent differences within the PCOS subjects. Variables considered included anthropometric (BMI, waist-hip ratio); metabolic (fasting glucose, fasting insulin, total and HDL cholesterol, triglycerides); and endocrine (testosterone, androstenedione, LH, FSH) parameters. No association with genotype was observed at any of the CAPN10 variants (data not shown).

Discussion

In this study of variation in the CAPN10 gene, we have been unable to detect any consistent evidence for association with PCOS or any of the subphenotypes examined, leading us to conclude that variation within this gene does not play a significant role in susceptibility to PCOS, in this population at least. Although we found nominal association with one variant (SNP-63) in the family-based association tests, this was clearly not confirmed in other analyses. Given the increasing, but as yet inconclusive, evidence supporting the association between CAPN10 variation and type 2 diabetes (17, 18, 19, 20, 21, 22, 23, 24, 25, 37), there are a number of possible reasons for our failure to detect association.

The most likely explanation is that, although variation within the CAPN10 gene may influence susceptibility to type 2 diabetes, it has no influence on PCOS risk. The physiological and epidemiological overlap between PCOS and type 2 diabetes suggests shared etiological mechanisms, and studies of the insulin gene indicate that some of these shared mechanisms are inherited (11, 12, 13, 14). However, in these multifactorial conditions with related but distinct phenotypic patterns, complete concordance of susceptibility effects would not be expected. The mechanisms whereby altered function or regulation of CAPN10 produces type 2 diabetes are unknown, but there are suggestions that this protease plays a role in normal insulin secretion (38, 39, 40, 41). If confirmed, this would be entirely consistent with defective CAPN10 function having a more marked influence on susceptibility to type 2 diabetes than PCOS.

The second related explanation is that our analysis failed to detect a CAPN10 effect on PCOS because it is of modest magnitude and our study lacked the power to detect it. It is clear (42) that very large studies (or meta-analyses of several smaller studies) are needed if alleles of modest effect (relative risks of less than 1.2) are to be completely excluded from a role in disease susceptibility. Certainly, variation at the CAPN10 gene seems to have a lesser effect on susceptibility to type 2 diabetes in Europeans than Mexican-Americans, presumably due to ethnicity-related differences in the frequency of risk-associated haplotypes (17) and of modifier genotypes at other loci (16).

A further possibility is that additional CAPN10 variants are involved in disease-susceptibility. Though we have not conducted a comprehensive analysis of all variants in and around the CAPN10 gene and cannot exclude the role of other variants outside this region, on the available evidence the four variants typed provide the best explanation of susceptibility to type 2 diabetes in European populations (17, 21, 43). Extensive mutational screening of the gene (17, 21), the observation that linkage disequilibrium declines rapidly away from the CAPN10 locus (17), and demonstrable functional correlates of several of these variants (17), combine to suggest that some, at least, play a direct role in disease pathogenesis (18). However, until the inventory of sequence variation in the CAPN10 region in European subjects is complete, it remains conceivable that future work will identify additional disease susceptibility genes or variants, refining and improving our capacity to detect genotype-phenotype correlations to diabetes and related conditions such as PCOS.

The data presented by Horikawa and colleagues (17) suggest a model for CAPN10-related disease susceptibility whereby disease risk is greatest in individuals inheriting different CAPN10 haplotypes from each parent. Although such a model might be expected to reduce the power of transmission disequilibrium analyses, the use of both family-based and case-control methodologies in our study, should help to overcome any possible consequences (44).

In summary, therefore, this study provides no evidence that variation in the CAPN10 gene influences susceptibility to PCOS. Given the accumulating (but not conclusive) evidence that CAPN10 variation influences susceptibility to type 2 diabetes, these data may indicate that CAPN10 acts via pathways that are not common to the two conditions. However, we note that robust evaluation of the role of variants of modest effect in influencing susceptibility to common multifactorial diseases (such as PCOS and type 2 diabetes) remains a challenging task. Definitive confirmation that CAPN10 gene variation has absolutely no effect on PCOS susceptibility will ultimately require studies incorporating thousands rather than hundreds of subjects.

Footnotes

This work was supported by grants from the UK Medical Research Council (G9700020), Diabetes UK, the U.S. Public Health Service (DK-20595, DK-47486, and DK-55889) and the Howard Hughes Medical Institute.

Abbreviations: CAPN10, Calpain-10 gene; HDL, high density lipoprotein; PCOS, polycystic ovary syndrome; SNP, single nucleotide polymorphism.

Received August 6, 2001.

Accepted March 5, 2002.

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