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Identification of a Polycystic Ovary Syndrome Susceptibility Variant in Fibrillin-3 and Association with a Metabolic Phenotype

Division of Endocrinology, Metabolism, and Molecular Medicine (M.U., S.S., A.D.), Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611; and Department of Obstetrics and Gynecology (R.S.L.), Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033

Address all correspondence and requests for reprints to: Margrit Urbanek, Division of Endocrinology, Metabolism, and Molecular Medicine, 303 East Chicago Avenue, Tarry 15-717, Chicago, Illinois 60611. E-mail: m-urbanek{at}northwestern.edu.

	Abstract

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Context: Polycystic ovary syndrome (PCOS), the most common reproductive endocrine disorder of premenopausal women, is also associated with metabolic abnormalities including insulin resistance and an increased risk for diabetes mellitus. We previously mapped a PCOS susceptibility locus to chromosome 19p13.2 near the dinucleotide repeat marker D19S884.

Objective: Our objective is to localize the chromosome 19p13.2 PCOS susceptibility locus and determine its impact on metabolic features of PCOS.

Design: Resequencing and family-based association testing were used to examine the effect of sequence variation within 100 kb of D19S884 on the reproductive and metabolic phenotypes of PCOS.

Setting: The study was conducted in an academic medical center.

Subjects: Genetic analyses were performed on DNA obtained from1723 individuals in 412 families with 412 index cases and 43 affected sisters of predominantly European origin (>94%). Genotype-phenotype associations were assessed in 601 women with PCOS and 168 brothers of affected women.

Results: D19S884 allele 8 (A8) within intron 55 of the fibrillin-3 (FBN3) gene showed the strongest evidence for association with PCOS of 53 variants tested (P_corrected = 0.0037). A8 was also associated with higher levels of fasting insulin and homeostasis model assessment for insulin resistance in women with PCOS and higher fasting levels of proinsulin and proinsulin/insulin ratio in brothers.

Conclusions: These findings strongly suggest that A8 of D19S884 is the chromosome 19p13.2 PCOS susceptibility locus. The association of D19S884 with markers of insulin resistance and pancreatic ß-cell dysfunction suggests that the same variant contributes to the reproductive and metabolic abnormalities of PCOS in affected women and their brothers.

	Introduction

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POLYCYSTIC OVARY SYNDROME (PCOS) is among the most common endocrine disorders of reproductive age women, affecting about 7% of this population (1). It has important metabolic features including insulin resistance, pancreatic ß-cell dysfunction, and an increased prevalence of obesity; these abnormalities confer about a 7-fold increased risk of developing type 2 diabetes mellitus (T2DM) in affected women (2). The etiology of PCOS remains unknown; however, heritability studies suggest that there is a strong genetic susceptibility to the disorder (3). Male and female first-degree relatives of women with PCOS have hyperandrogenemia consistent with defects in steroidogenic pathways common to the gonads and the adrenals (4, 5). Metabolic abnormalities of PCOS are tightly associated with hyperandrogenemia in female first-degree relatives, suggesting that these findings are causally related, reflect a common pathogenesis (e.g. same gene product), or are due to perturbations of genes within one pathway. Limited studies have suggested that male relatives also have metabolic abnormalities including insulin resistance and glucose intolerance (6, 7, 8). Therefore, identifying susceptibility genes for PCOS will not only provide insight into the pathogenesis of its reproductive abnormalities but will also elucidate an important precursor of T2DM.

We mapped a PCOS susceptibility gene to chromosome 19p13.2 with the strongest evidence for association with D19S884 allele 8 (A8) (9, 10). Evidence for association between D19S884 A8 and PCOS was replicated in two independent sets of families collected by us and in an independent case-control study (11). There was also nominal evidence for linkage between chromosome 19p13.2 and PCOS in our families (10). No other PCOS candidate gene has met these criteria. In this study, we report the sequence analysis and fine mapping of the chr19p13.2 PCOS susceptibility locus and demonstrate that D19S884 A8 is associated with a metabolic phenotype in women with PCOS and their first-degree male relatives.

	Subjects and Methods

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Subjects

The study was approved by the Institutional Review Boards of Brigham and Women’s Hospital, Northwestern University Feinberg School of Medicine, The Pennsylvania State University College of Medicine, and University of Pennsylvania Medical Center. Written informed consent was obtained from all participants. PCOS was diagnosed by a history of six or fewer menses per year and elevated levels of total testosterone or non-SHBG-bound testosterone (uT) (4, 9, 12, 13). Pituitary, adrenal, and ovarian disorders were excluded by appropriate tests (12, 14). Seven hundred nine women with PCOS (cases) were studied in the family-based association studies and/or the genotype-phenotype association studies (5, 9, 10, 13, 15, 16, 17, 18). Genotype-phenotype association studies included 601 probands of whom 315 subjects were also included in the family-based association studies. The family-based association studies also included 97 probands not included in the genotype-phenotype association studies.

The family-based analysis was performed in DNA obtained from 1723 individuals in 412 families with 412 index cases, 400 fathers, 403 mothers, 332 sisters, and 162 brothers. The sisters included 43 with PCOS, 39 who were hyperandrogenic, 117 who were unaffected, and 129 who had an unknown phenotype. Data from 327 of these families have been reported previously (9, 10, 13, 15, 18). Both parents were available for genotyping in 392 families, one parent was available for 19 families, and no parents were available for one family. The 412 families were of European (389), Hispanic (12), African-American (six), Native American (one), Asian (two), or unknown origin (two).

Genotype-phenotype associations were assessed in non-Hispanic white subjects to control for the potential confounding effects of ethnicity on insulin sensitivity (19): 601 women with PCOS, aged 18–44 yr, and 168 brothers of affected women, aged 18–55 yr. None of the subjects were receiving medications known to alter reproductive hormone levels or glucose homeostasis for at least 1 month before study, contraceptive steroids were stopped at least 3 months before study. A morning fasting blood sample was obtained for testoserone, uT, dehydroepiandrosterone sulfate (DHEAS), SHBG, insulin, proinsulin, and glucose levels. Anthropometric measurements were taken as reported (5, 12). Four hundred nineteen subjects (368 PCOS and 51 brothers) were studied on site at one of the four study sites, and 350 subjects (233 PCOS and 117 brothers) had samples obtained at a local laboratory and shipped to the central laboratory; the phenotyping methods have been reported in detail elsewhere (4, 9, 12). Hormone and glucose assays were performed as previously reported (5, 12). Insulin and proinsulin levels were determined by RIA using reagents obtained from Linco Research (St. Charles, MO). The intra- and interassay coefficients of variation were less than 10% for both assays (5).

Sequencing

To generate sequencing templates, 50–100 ng genomic DNA was amplified with the Applied Biosystems XL kit to generate 2- to 6-kb fragments (Applied Biosystems, Foster City CA). Templates were purified using 96-well Millipore PCR clean up-plates (Millipore, Billerica, MA). Both strands were sequenced, and forward and reverse sequencing primers were staggered to give maximal overlap of sequencing results. Approximately 50 ng template PCR product was sequenced using standard techniques and analyzed with the Applied Biosystems 3100 sequencer. Sequencing results were assembled and analyzed using the SeqMan II software program (DNASTAR Inc., Madison, WI). All assembled sequences were also checked manually.

Genotyping

SNPs were genotyped using the Applied Biosystems Assays by Design 5'-nuclease TaqMan technology as recommended by the manufacturer and the 7900HT DNA analysis system (Applied Biosystems). D19S884 was genotyped as previously described (9). Because our interest in D19S884 is with A8, the multiallelic D19S884 locus was collapsed to a biallelic system of A8 vs. non-A8. The CEPH HAPMAP DNAs were purchased from Coriell Institute for Medical Research (Camden, NJ) and genotyped at D19S884 as described above.

For the physiological studies, subjects with one or two A8 alleles were denoted as A8+ and subjects with all other alleles were denoted as A8–; there were too few subjects homozygous for A8 to examine the effect of gene dosage.

Data analysis

The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated according to the HOMA model, a structural computer model of the glucose-insulin feedback system in the homeostatic state (www.dtu.ox.ac.uk/homa/index.html) (21). Continuous variables were summarized using means and SD and compared by analysis of covariance adjusted for age and body mass index (BMI). Data were log-transformed to achieve homogeneity when necessary. Categorical variables were compared by ² analysis. Predictors of fasting insulin levels and HOMA-IR in women with PCOS were determined using general linear model with age, body mass index (BMI), uT, and A8 status as the independent variables. Predictors of proinsulin and proinsulin to insulin ratio (PIR) in brothers were assessed using general linear model with age, BMI, DHEAS, and A8 status as independent variables. Odds ratios were calculated for association of A8 with higher fasting insulin levels using the upper quartile of fasting insulin (insulin 34 µU/ml) in this cohort. Statistical analyses were performed using the SAS 8.2 (SAS Institute, Cary, NC) and SPSS 12.0 (SPSS, Inc., Chicago, IL) data analysis software. P values < 0.05 were considered statistically significant.

Genetic analysis

We tested for association between PCOS and single variants and haplotypes using the transmission disequilibrium test (TDT) (22). Permutation analysis was used to generate significance levels for the association studies. Analyses were implemented using the Haploview 3.2 software (haploview{at}broad.mit.edu) (23). Pairwise linkage disequilibrium (LD) plots of r² were generated using Haploview 3.2.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Sequencing

We sequenced in 12 A8+ women with PCOS the coding region, 200-bp flanking intronic regions, and about 1–2 kb of the putative proximal promoter regions of the three genes (ELAVL1, CCL25, and FBN3) mapping within 100 kb of D19S884. We sequenced only women who inherited at least one A8-containing chromosome and shared at least one A8-containing chromosome identical-by-descent with an affected sister to enrich the sample for the A8-associated susceptibility gene. We identified 107 variants including 23 coding sequence variants (13 missense, 10 silent, and zero nonsense variants) and 93 noncoding variants. The most informative single-nucleotide polymorphisms (SNPs), based on sequence location, heterozygosity, and type of mutation, were selected for genotyping. The initial selection of SNPs focused on variants spaced about 2000 bp apart. Because the area of interest focused on the region closer to D19S884, we genotyped all variants in the vicinity of D19S884. We genotyped 47 SNPs (Table 1) in our complete dataset. Variants were not included in the final analysis if the SNP 1) mapped within 30 bp of an already genotyped variant (n = 16), Applied Biosystems was not able to design an assay (n = 6), the minor allele frequency was less than 0.01 in our families (n = 3), or the PCR failed and/or the genotyping calls were not reproducible (n = 6). Variants were not genotyped because initial association studies showed that they mapped a significant distance from any region in LD with D19S884 (n = 29).

The Haploview program (23) was used to generate haplotypes, identify haplotype blocks, and calculate pair-wise LD r² statistics. There was only limited LD in the region of D19S884 (Fig. 1A). Seven haplotype blocks consisting of 24 haplotypes were identified using the method developed by Gabriel et al. (24) and the solid spline method.

View larger version (51K): [in this window] [in a new window]   FIG. 1. Analysis of chromosome 19p13.2 sequence variation in PCOS families. A, Pairwise LD (r2) plot. The graphic display was generated with Haploview. The relative position of each SNP on chromosome 19p13.2 is indicated by the vertical lines. The names of each SNP are shown above the LD map. Dark gray indicates strong LD. White indicates no LD. Dark lines mark the location of haploblocks. The absence of dark gray blocks flanking D19S884 is indicative of the low degree of LD around the marker. B, Summary of TDT results of SNPs in coding regions, flanking intronic sequences, and proximal putative promoter sequences of genes in the vicinity of D19S884. The SNPs are listed on the x-axis. A schematic of each of the sequenced genes is shown below TDT results. The horizontal lines indicate the position of the genes. The vertical lines indicate the location of each SNP.

All SNPs and haplotypes were tested for association with PCOS using the TDT (Fig. 1B). The strongest evidence for associations was seen with D19S884 A8 (147 transmissions and 86 nontransmissions; 63% transmission; ² = 15.97). The second strongest evidence for association was with F9 (138 transmissions and 95 nontransmissions; 59% transmissions; ² = 7.94). This SNP maps 1654 bp 3' to D19S884. Both variants are located within FBN3 intron 55. None of the haplotype blocks encompass the D19S884/F9 region, nor do they show evidence for association with PCOS. A third nominally significant finding is with F25 (106 transmissions and 79 nontransmissions; 57% transmissions; ² = 3.94), which maps in FBN3 intron 33.

Sequencing of FBN3 exons 55/56 region

Because both D19S884 and F9 map to FBN3 intron 55, and we did not sequence the middle of the introns in our initial sequencing screen, we sequenced exon 55, exon 56, and the intervening intron in its entirety in 24 PCOS probands with at least one D19S884 A8 and one F9 T allele-containing chromosome (i.e. those chromosomes most likely to carry the relevant variants) and identified seven additional SNPs. Applied Biosystems was unable to design a genotyping assay for two variants. None of the five genotyped SNPs showed evidence for association with PCOS (Fig. 2A), nor did they form haplotypes that are associated with PCOS (Fig 2B).

View larger version (31K): [in this window] [in a new window]   FIG. 2. Analysis of FBN3 intron 55 variation. A, TDT results of FBN3 intron 55 variation. Exons are shown with black boxes. Vertical lines indicate location of each SNP. The sequenced region is indicated by the shaded bar. The vertical lines indicate the location of each SNP. B, Pairwise LD (r2) plot of FBN3 intron 55 region in PCOS families.

We corrected for multiple testing using the Haploview permutation function on all markers and haplotypes tested. We performed 10,000 permutations, and only the D19S884 A8 association remained statistically significant after correction (P_corrected = 0.0037). Because we previously showed that there is linkage between the D19S884-containing region of chr19p13.2 and PCOS in our families, transmissions to affected siblings are not independent. We, therefore, corrected for this dependence using the method developed by Suarez and Hodge (25). After correction, there is still evidence for association between D19S884 A8 and PCOS (141 transmissions and 92 nontransmissions; 61% transmissions; ² = 10.3).

LD analysis of chromosome 19p13.2 region in CEPH HAPMAP trios

To demonstrate that relevant variation was not missed by genotyping variants that were identified in subjects with PCOS rather than the publicly available variants, D19S884 was genotyped in 30 Caucasian CEPH parent offspring trios, and we tested for association between D19S884 and the 156 polymorphic HAPMAP markers mapping within 100 kb of D19S884. The LD map in the CEPH DNAs is virtually identical to that observed within the PCOS families (Fig. 1A vs. 3A). Modest evidence for LD is observed between D19S884 and rs17160149, which we identified in our sequencing efforts (F9) and showed the strongest evidence for association after D19S884. When using the solid spline method (data not shown) for calculating haplotype, D19S884 makes a very small haplotype with Fin55e, but given the low degree of LD between D19S884 and Fin55e and the absence of association between Fin55e and PCOS in our cohort, it is not very likely that Fin55e has a strong if any relevant contribution to the etiology of PCOS (Figs. 2B and 3B).

View larger version (61K): [in this window] [in a new window]   FIG. 3. Pairwise LD (r2) plot of chr19p13.2 HAPMAP SNPs and D19S884 in CEPH trios. A, Pairwise LD (r2) plot of all informative HAPMAP SNPs mapping within 100 kb of D19S884. The location of D19S884 is indicated by an arrow. B, Pairwise LD (r2) plot of all informative HAPMAP SNPs mapping within 10 kb of D19S884. Polymorphisms that were also genotyped in the PCOS families are shown within boxes.

Age, BMI, waist circumference, or blood pressure did not differ in A8+ compared with A8– PCOS or in A8+ compared with A8– brothers (Table 2). The majority of PCOS were obese (30 kg/m²) regardless of genotype: 68% of A8+ and 71% of A8–. Thirty-eight percent of A8+ and 30% of A8– brothers were obese. There were no differences in androgen or SHBG levels in women with PCOS or their brothers based on A8 (data not shown).

A8 of D19S884 was associated with higher levels of fasting insulin and HOMA-IR in PCOS and higher levels of fasting proinsulin and PIR in brothers (Table 2). Fasting insulin levels (17 ± 11 µU/ml for A8+ vs. 12 ± 4 µU/ml for A8–, P = 0.008) and HOMA-IR (1.94 ± 1.1 for A8+ vs. 1.49 ± 0.55 for A8–, P = 0.02) remained elevated in association with A8 in an analysis limited to nonobese (BMI < 25 kg/m²) PCOS (n = 29 A8+; n = 48 A8–). The odds ratio for association of A8 with higher fasting insulin levels was 1.44 (confidence interval = 1.02–2.03; P = 0.04).

In a multivariate regression analysis, independent predictors of fasting insulin levels and HOMA-IR in women with PCOS were BMI, uT, and A8 status (r² = 0.30 for the overall model for both fasting insulin levels and HOMA-IR). The presence of A8 was associated with an increase of about 3.6 µU/ml in fasting insulin levels and 0.4 in HOMA-IR after adjustment for age, BMI, and uT levels (Table 3). The strongest predictors of fasting proinsulin levels in brothers were BMI and A8 status and of fasting PIR in brothers was A8 status (Table 3). The presence of A8 was associated with an increase of about 7 pmol/liter in fasting proinsulin levels and 0.04 in fasting PIR after adjustment for age, BMI, and DHEAS levels in brothers (Table 3). In a similar analysis, the A8+ and A8– unaffected sisters have the same insulin and glucose levels and HOMA-IR (data not shown). Therefore, A8 is not associated any metabolic profile in unaffected sisters with PCOS.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

Multiple lines of evidence suggest that D19S884 is the functional variant. Of the 53 variants that were characterized in this study, the strongest evidence for association remains with D19S884. Limited levels of LD near D19S884 make it unlikely that the observed association between PCOS and D19S884 is due to a susceptibility allele that maps outside of the tested region. Mapping of D19S884 in the HAPMAP CEPH DNAs also indicates that there is limited LD within the vicinity of D19S884 and supports the possibility that D19S884 is the functional variant.

Dinucleotide repeat polymorphisms like D19S884 have been shown to act as transcriptional (26, 27, 28) and splicing enhancers (29, 30); therefore, variation at D19S884 is likely to have functional consequences. For instance, dinucleotide repeat polymorphisms in intron 2 of the human cardiac Na⁺Ca²⁺ exchanger gene and in intron 13 of the eNOS gene are important regulators of splicing. In the eNOS gene, the mechanism for this differential splicing is due to differential binding of mRNA stabilizing heterogeneous nuclear ribonucleoproteins to different CA repeat lengths (29, 30). Although the genomic sequence containing D19S884 has modest promoter/enhancer activity in luciferase activity assays, this activity does not appear to be allele specific, and D19S884 A8 has the same level of activity as A9 and A13, which are not associated with PCOS (18). It therefore is unlikely that D19S884 A8 acts as a PCOS-specific promoter or transcriptional enhancer element and more likely to play a role in the regulation of splicing.

D19S884 maps to intron 55 of FBN3, 105 bp 3' to exon 55. FBN3 encodes fibrillin-3, the third member of the fibrillin family of extracellular matrix proteins. In addition to their structural function in connective tissue, fibrillins are believed to regulate the activity of members of the TGFß family (31, 32). Members of the TGFß superfamily implicated in the etiology of PCOS based on functional data include activin, inhibin, their receptors, follistatin, and SMADs (9, 13). Members of this superfamily have also been shown to affect metabolism. For instance Mukherjee et al. (33) have shown that homozygous knockout mice of follistatin-like 3 (FSTL3), an activin and myostatin antagonist, have increased islet number and size, ß-cell hyperplasia, decreased visceral mass, improved glucose tolerance, and enhanced insulin sensitivity. Given these findings, any gene whose product regulates the expression of members of the TGFß signaling pathway is a logical PCOS susceptibility gene.

A8 of D19S884 was identified in association with the reproductive phenotype of PCOS. We now show that this marker locus is also associated with higher fasting insulin levels and HOMA-IR in women with PCOS, independent of obesity. The presence of A8 was associated with an approximately 40% increased risk for fasting insulin levels in the upper quartile of the cohort. In a multivariate analysis, A8 was associated with an approximately 3.6 µU/ml increase in fasting insulin levels independent of age, BMI, and uT levels. These observations suggest that A8 increases the risk for insulin resistance, an early and predictive step in the pathogenesis of T2DM (34), in non-Hispanic white women with PCOS. A8 was also associated with a metabolic phenotype in brothers of women with PCOS (increased fasting proinsulin levels and PIR), suggesting the presence of pancreatic ß-cell dysfunction (35). However, this phenotype differed from that in affected women, suggesting that some metabolic abnormalities are sex specific. No effect on any metabolic profile by A8 was observed in unaffected sisters of women with PCOS. Therefore, A8 is associated with a metabolic profile only in individuals with PCOS and has no metabolic effect in the absence of PCOS. We are currently testing this hypothesis by examining the role of A8 in non-PCOS (control) populations.

It is not customary to correct for multiple testing in studies reporting phenotypic differences associated with genotypes, and we also report uncorrected P values for the phenotype-genotype correlation studies (see Results). Nevertheless, in the present study, the a priori hypothesis was that A8 would be associated with markers of insulin resistance. Five analyses were performed to test this hypothesis: comparison of fasting glucose, insulin, proinsulin, PIR, and HOMA-IR; the P value adjusted for five comparisons would be P 0.01. The results remained significant in both PCOS and brothers with this correction for multiple testing. Furthermore, using a separate methodology, multivariate regression analysis, A8 genotype was a highly significant (all P < 0.01) independent predictor of the parameters that differed in the two-group analyses. Taken together, this information suggests that these differences did not reflect a type II error. However, replication in other populations would be important to further substantiate these results.

The elevation in fasting insulin levels associated with A8 is similar in magnitude (15–20% change) to that reported with an accepted diabetes susceptibility gene PPAR (36). The PPAR risk allele has only a modest impact on individual risk for T2DM (odds ratio 1.25) but has a dramatic effect on population risk because it occurs at high frequency in the population (36). This example highlights the potential importance of common alleles with weak effect. Considering the close association between PCOS and T2DM, any susceptibility gene for PCOS may also be a susceptibility gene for T2DM. Indeed, calpain 10 as well as PPAR have been associated with various features of PCOS (20, 37, 38). The role of A8 in T2DM is unknown and merits investigation.

The mapping of susceptibility genes for complex diseases has been notoriously difficult. We previously presented reproducible evidence of a susceptibility locus for the reproductive phenotype of PCOS that maps to chromosome 19p13.2 in three individual cohorts (9, 10, 18). In this report, we characterized the genetic variation in the region of D19S884 in women with PCOS by resequencing the coding regions of genes mapping within 100 kb of D19S884 in women with PCOS and testing for association between the newly identified variants and PCOS in our cohort. The strongest evidence for association with PCOS remains with our initial variant D19S884. LD analysis makes it unlikely that the PCOS susceptibility allele maps outside of the genomic regions screened in this analysis, and we excluded the possibility of other genetic variants on chr19p13.2 as playing a major role in PCOS susceptibility.

We, therefore, conclude that the most likely PCOS susceptibility locus is the dinucleotide repeat D19S884 itself, which maps to intron 55 of the fibrillin 3 gene. The susceptibility allele, A8, identified based on the reproductive phenotype of PCOS, is also associated with the metabolic features of PCOS in affected women and in their brothers, suggesting that the same gene contributes to both abnormalities of this complex disorder and thus plays a fundamental role in the pathogenesis of PCOS. Within families of women with PCOS, it may be possible to use A8 to identify individuals, including brothers, at greater metabolic risk.

	Acknowledgments

 
We thank all of the women and their families for participating in this study. We also thank Drs. R. Spielman, K. Ewens, D. Stewart, and R. N. Bergman for their helpful discussions and support and Janine D’Souza, Melissa Miller, Eleanor Harrison, and Adam Edelstein for technical assistance. We also thank the study coordinators (B. Scheetz, S. Ward, J. Schindler, E. Podczerwinski, and J. Steel) and the nursing staff of Penn State, Brigham and Women’s Hospital, and Northwestern University General Clinical Research Center (GCRC) for help with the family studies.

	Footnotes

 
This work was supported by National Institutes of Health Grants P50 HD44405 (M.U. and A.D.), U54 HD34449 (A.D.), RR10732 and C06 RR016499 (The Pennsylvania State University GCRC), M01 RR00048 (Northwestern University GCRC), M01 RR10732, and M01 RR02635 (Brigham and Women’s Hospital GCRC), and K12 RR17707 (S.S. and A.D.).

Current address for S.S.: Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Illinois in Chicago.

Disclosure Statement: M.U., S.S., R.S.L., and A.D. have nothing to declare.

First Published Online September 4, 2007

¹ M.U. and S.S. contributed equally.

Abbreviations: A8, Allele 8; BMI, body mass index; DHEAS, dehydroepiandrosterone sulfate; HOMA-IR, homeostasis model assessment for insulin resistance; LD, linkage disequilibrium; PCOS, polycystic ovary syndrome; PIR, proinsulin to insulin ratio; SNP, single-nucleotide polymorphism; T2DM, type 2 diabetes mellitus; TDT, transmission/disequilibrium test; uT, non-SHBG-bound testosterone.

Received April 4, 2007.

Accepted August 28, 2007.

	References

Top Abstract Introduction Subjects and Methods Results Discussion References

 

1. Ehrmann DA 2005 Polycystic ovary syndrome. N Engl J Med 352:1223–1236[Free Full Text]
2. Legro RS, Kunselman A, Dodson WC, Dunaif A 1999 Prevalence and predictors of risk for type 2 diabetes mellitus and impaired glucose tolerance in polycystic ovary syndrome: a prospective, controlled study in 254 affected women. J Clin Endocrinol Metab 84:165–169[Abstract/Free Full Text]
3. Vink J, Sadrzadeh SM, Lambalk CB, Boomsma DI 2006 Heritability of polycystic ovary syndrome (PCOS) in a Dutch twin-family study. J Clin Endocrinol Metab 91:2100–2104[Abstract/Free Full Text]
4. Legro RS, Spielman R, Urbanek M, Driscoll D, Strauss JF, Dunaif A 1998 Phenotype and genotype in polycystic ovary syndrome. Recent Prog Horm Res 53:217–256[Medline]
5. Legro RS, Bentley-Lewis R, Driscoll D, Wang SC, Dunaif A 2002 Insulin resistance in the sisters of women with polycystic ovary syndrome: association with hyperandrogenemia rather than menstrual irregularity. J Clin Endocrinol Metab 87:2128–2133[Abstract/Free Full Text]
6. Norman RJ, Masters S, Hague W 1996 Hyperinsulinemia is common in family members of women with polycystic ovary syndrome. Fertil Steril 66:942–947[Medline]
7. Sir-Petermann T, Angel B, Maliqueo M, Carvajal F, Santos JL, Pâerez-Bravo F 2002 Prevalence of type II diabetes mellitus and insulin resistance in parents of women with polycystic ovary syndrome. Diabetologia 45:959–964[CrossRef][Medline]
8. Yildiz BO, Yarali H, Oguz H, Bayraktar M 2003 Glucose intolerance, insulin resistance, and hyperandrogenemia in first degree relatives of women with polycystic ovary syndrome. J Clin Endocrinol Metab 88:2031–2036[Abstract/Free Full Text]
9. Urbanek M, Legro RS, Driscoll DA, Azziz R, Ehrmann DA, Norman RJ, Strauss 3rd JF, Spielman RS, Dunaif A 1999 Thirty-seven candidate genes for polycystic ovary syndrome: strongest evidence for linkage is with follistatin. Proc Natl Acad Sci USA 96:8573–8578[Abstract/Free Full Text]
10. Urbanek M, Woodroffe A, Ewens KG, Diamanti-Kandarakis E, Legro RS, Strauss 3rd JF, Dunaif A, Spielman RS 2005 Candidate gene region for polycystic ovary syndrome on chromosome 19p13.2. J Clin Endocrinol Metab 90:6623–6629[Abstract/Free Full Text]
11. Tucci S, Futterweit W, Concepcion ES, Greenberg DA, Villanueva R, Davies TF, Tomer Y 2001 Evidence for association of polycystic ovary syndrome in Caucasian women with a marker at the insulin receptor locus. J Clin Endocrinol Metab 86:446–449[Abstract/Free Full Text]
12. Legro RS, Driscoll D, Strauss 3rd JF, Fox J, Dunaif A 1998 Evidence for a genetic basis for hyperandrogenemia in polycystic ovary syndrome. Proc Natl Acad Sci USA 95:14956–14960[Abstract/Free Full Text]
13. Urbanek M, Wu X, Vickery KR, Kao LC, Christenson LK, Schneyer A, Legro RS, Driscoll DA, Strauss 3rd JF, Dunaif A, Spielman RS 2000 Allelic variants of the follistatin gene in polycystic ovary syndrome. J Clin Endocrinol Metab 85:4455–4461[Abstract/Free Full Text]
14. Legro RS, Kunselman AR, Demers L, Wang SC, Bentley-Lewis R, Dunaif A 2002 Elevated dehydroepiandrosterone sulfate levels as the reproductive phenotype in the brothers of women with polycystic ovary syndrome. J Clin Endocrinol Metab 87:2134–2138[Abstract/Free Full Text]
15. Urbanek M, Du Y, Silander K, Collins FS, Steppan CM, Strauss 3rd JF, Dunaif A, Spielman RS, Legro RS 2003 Variation in resistin gene promoter not associated with polycystic ovary syndrome. Diabetes 52:214–217[Abstract/Free Full Text]
16. Sam S, Legro RS, Bentley-Lewis R, Dunaif A 2005 Dyslipidemia and metabolic syndrome in the sisters of women with polycystic ovary syndrome. J Clin Endocrinol Metab 90:4797–4802[Abstract/Free Full Text]
17. Sam S, Legro RS, Essah PA, Apridonidze T, Dunaif A 2006 Evidence for metabolic and reproductive phenotypes in mothers of women with polycystic ovary syndrome. Proc Natl Acad Sci USA 103:7030–7035[Abstract/Free Full Text]
18. Stewart DR, Dombroski BA, Urbanek M, Ankener W, Ewens KG, Wood JR, Legro RS, Strauss JF, Dunaif A, Spielman RS 2006 Fine mapping of genetic susceptibility to polycystic ovary syndrome on chromosome 19p13.2 and tests of regulatory activity. J Clin Endocrinol Metab 91:4112–4117[Abstract/Free Full Text]
19. Dunaif A, Sorbara L, Delson R, Green G 1993 Ethnicity and polycystic ovary syndrome are associated with independent and additive decreases in insulin action in Caribbean-Hispanic women. Diabetes 42:1462–1468[Abstract]
20. Yilmaz M, Bukan N, Ersoy R, Karakoc A, Yetkin I, Ayvaz G, Cakir N, Arslan M 2005 Glucose intolerance, insulin resistance and cardiovascular risk factors in first degree relatives of women with polycystic ovary syndrome. Hum Reprod (Oxf) 20:2414–2420[Abstract/Free Full Text]
21. Levy JC, Matthews DR, Hermans MP 1998 Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care 21:2191–2192[Medline]
22. Spielman RS, McGinnis RE, Ewens WJ 1993 Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet 52:506–516[Medline]
23. Barrett JC, Fry B, Maller J, Daly MJ 2005 Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263–265[Abstract/Free Full Text]
24. 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 2002 The structure of haplotype blocks in the human genome. Science 296:2225–2229[Abstract/Free Full Text]
25. Suarez BK, Hodge SE 1979 A simple method to detect linkage for rare recessive diseases: an application to juvenile diabetes. Clin Genet 15:126–136[Medline]
26. Hata R, Akai J, Kimura A, Ishikawa O, Kuwana M, Shinkai H 2000 Association of functional microsatellites in the human type I collagen 2 chain (COL1A2) gene with systemic sclerosis. Biochem Biophys Res Commun 272:36–40[CrossRef][Medline]
27. Fenech AG, Billington CK, Swan C, Richards S, Hunter T, Ebejer MJ, Felice AE, Ellul-Micallef R, Hall IP 2004 Novel polymorphisms influencing transcription of the human CHRM2 gene in airway smooth muscle. Am J Respir Cell Mol Biol 30:678–686[Abstract/Free Full Text]
28. Huang TS, Lee CC, Chang AC, Lin S, Chao CC, Jou YS, Chu YW, Wu CW, Whang-Peng J 2003 Shortening of microsatellite deoxy(CA) repeats involved in GL331-induced down-regulation of matrix metalloproteinase-9 gene expression. Biochem Biophys Res Commun 300:901–907[CrossRef][Medline]
29. Gabellini N 2001 A polymorphic GT repeat from the human cardiac Na⁺Ca²⁺ exchanger intron 2 activates splicing. Eur J Biochem 268:1076–1083[Medline]
30. Hui J, Stangl K, Lane WS, Bindereif A 2003 HnRNP L stimulates splicing of the eNOS gene by binding to variable-length CA repeats. Nat Struct Biol 10:33–37[CrossRef][Medline]
31. Neptune ER, Frischmeyer PA, Arking DE, Myers L, Bunton TE, Gayraud B, Ramirez F, Sakai LY, Dietz HC 2003 Dysregulation of TGF-ß activation contributes to pathogenesis in Marfan syndrome. Nat Genet 33:407–411[CrossRef][Medline]
32. Habashi JP, Judge DP, Holm TM, Cohn RD, Loeys BL, Cooper TK, Myers L, Klein EC, Liu G, Calvi C, Podowski M, Neptune ER, Halushka MK, Bedja D, Gabrielson K, Rifkin DB, Carta L, Ramirez F, Huso DL, Dietz HC 2006 Losartan, an AT1 antagonist, prevents aortic aneurysm in a mouse model of Marfan syndrome. Science 312:117–121[Abstract/Free Full Text]
33. Mukherjee A, Sidis Y, Mahan A, Raher MJ, Xia Y, Rosen ED, Bloch KD, Thomas MK, Schneyer AL 2007 FSTL3 deletion reveals roles for TGF-ß family ligands in glucose and fat homeostasis in adults. Proc Natil Acad Sci USA 104:1348–1353[Abstract/Free Full Text]
34. Lillioja S, Mott DM, Spraul M, Ferraro R, Foley JE, Ravussin E, Knowler WC, Bennett PH, Bogardus C 1993 Insulin resistance and insulin secretory dysfunction as precursors of non-insulin-dependent diabetes mellitus. Prospective studies of Pima Indians. N Engl J Med 329:1988–1992[Abstract/Free Full Text]
35. Mykkèanen L, Zaccaro DJ, Hales CN, Festa A, Haffner SM 1999 The relation of proinsulin and insulin to insulin sensitivity and acute insulin response in subjects with newly diagnosed type II diabetes: the Insulin Resistance Atherosclerosis Study. Diabetologia 42:1060–1066[CrossRef][Medline]
36. Altshuler D, Hirschhorn J, Klannemark M, Lindgren C, Vohl M-C, Nemesh J, Lane C, Schaffner S, Bolk S, Brewer C, Tuomi T, Gaudet D, Hudson T, Daly M, Groop L, Lander E 2000 The common PPAR Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 26:76–80[CrossRef][Medline]
37. Ehrmann DA, Schwarz PE, Hara M, Tang X, Horikawa Y, Imperial J, Bell GI, Cox NJ 2002 Relationship of calpain-10 genotype to phenotypic features of polycystic ovary syndrome. J Clin Endocrinol Metab 87:1669–1673[Abstract/Free Full Text]
38. Gonzalez A, Abril E, Roca A, Aragâon MJ, Figueroa MJ, Velarde P, Ruiz R, Fayez O, Galâan JJ, Herreros JA, Real LM, Ruiz A 2003 Specific CAPN10 gene haplotypes influence the clinical profile of polycystic ovary patients. J Clin Endocrinol Metab 88:5529–5536[Abstract/Free Full Text]

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