Obstetrics & Gynecology:
Identification of Six Loci Associated With Pelvic Organ Prolapse Using Genome-Wide Association Analysis
Allen-Brady, Kristina PhD; Cannon-Albright, Lisa PhD; Farnham, James M. MS; Teerlink, Craig PhD; Vierhout, Mark E. MD, PhD; van Kempen, Léon C. L. PhD; Kluivers, Kirsten B. MD, PhD; Norton, Peggy A. MD
From the Departments of Medicine and Obstetrics and Gynecology, University of Utah, and the George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah; the Department of Obstetrics and Gynecology, Radboud University Nijmegen Medical Centre; Nijmegen, the Netherlands; and the Department of Pathology, McGill University/Jewish General Hospital, Montreal, Canada.
Funded by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development R01 HD003438 (Peggy A. Norton) and RO1 HD061821 (Lisa Cannon-Albright and Peggy A. Norton).
The authors thank Shirley Ranke, RN, for help with recruitment and Kim Nguyen and Jeroen R. Dijkstra for their assistance in the laboratory.
Presented at the American Urogynecology Society 2010 annual meeting, September 29-October 2, 2010, Long Beach, California.
Corresponding author: Kristina Allen-Brady, 391 Chipeta Way, Suite D, Salt Lake City, UT 84108; e-mail: email@example.com.
Financial Disclosure The authors did not report any potential conflicts of interest.
OBJECTIVE: There is evidence that both environmental and genetic factors contribute to pelvic organ prolapse. We conducted a genome-wide association study to investigate whether common genetic variants modify the risk of pelvic organ prolapse.
METHODS: We recruited women who had been evaluated and treated for pelvic organ prolapse at the University of Utah from 1996 to 2008 and their affected female relatives. Those in the case group were genotyped on the Illumina 550K platform. We genetically matched 2,976 white control participants available from Illumina as the control group. Association tests were adjusted for related participants using two different software programs: EMMAX and Genie. Confirmation of findings was performed in a cohort of Dutch women (n=76) with recurrent pelvic organ prolapse and family history of pelvic organ prolapse.
RESULTS: The Utah study sample included 115 case group participants treated for pelvic organ prolapse, in most case group participants with surgery (n=78) or repeat surgery (n=35). Results from association analyses using EMMAX software identified five single-nucleotide polymorphisms (SNPs) significantly associated with pelvic organ prolapse (P<1×10−7). Independent association analysis with Genie software identified three of the same SNPs and one additional SNP. The six SNPs were located at 4q21 (rs1455311), 8q24 (rs1036819), 9q22 (rs430794), 15q11 (rs8027714), 20p13 (rs1810636), and 21q22 (rs2236479). Nominally significant findings (P<.05) or findings trending toward significance (P<.1) were observed for five of the six SNPs in the Dutch cohort.
CONCLUSION: Six SNPs have been identified that are significantly associated with pelvic organ prolapse in high-risk familial case group participants and that provide evidence for a genetic contribution to pelvic organ prolapse.
LEVEL OF EVIDENCE: II
Pelvic floor disorders including stress incontinence, urge incontinence, and pelvic organ prolapse are common conditions that have been shown to affect approximately 27–50% of women aged 40 years and older.1 Approximately 3–6% of women have pelvic organ prolapse that descends beyond the vaginal opening on routine pelvic examination,2 and an estimated 11% of women will undergo surgery for pelvic organ prolapse sometime in their lifespan.3 The etiology of pelvic organ prolapse is thought to be multifactorial, with contributions from both genetic and environmental risk factors. Environmental factors that contribute to pelvic organ prolapse include vaginal delivery, chronic increases in intra-abdominal pressure, obesity, advanced age, and estrogen deficiency.4,5
Evidence for a genetic contribution to pelvic organ prolapse has been found in family-based studies, candidate gene association studies, expression studies, and linkage studies.6 Family studies have shown an increased risk of pelvic organ prolapse when mothers and sisters are affected with the disease7,8; after menopause, familial risk may be more important than contributions from child birth.8 A segregation analysis of early onset pelvic organ prolapse suggested a dominant mode of inheritance with incomplete penetrance that can involve either maternal or paternal transmission.9 Candidate gene studies have focused on collagen and elastin biosynthesis,10–12 extracellular matrix metabolism,13 and hormone receptors,14–16 with encouraging results. Expression studies have found a number of genes that are overexpressed and underexpressed in women with pelvic organ prolapse compared with women without pelvic organ prolapse.17–21 Linkage studies have implicated a region near the LAMC1 gene in a single Filipino family,22 and our group has found significant genome-wide linkage evidence on chromosome 9q21 in 70 women with pelvic organ prolapse from 32 families.23
To further understand pelvic organ prolapse genetics, we performed a genome-wide association study for pelvic organ prolapse to identify common genetic variants that contribute to pelvic organ prolapse. Association is tested by comparing allele frequency differences between case group participants and control group participants for thousands of single-nucleotide polymorphisms (SNPs). The purpose of this study was to identify SNPs associated with pelvic organ prolapse in a cohort of women with a family history of pelvic floor disorders who have been treated for moderate-to-severe pelvic organ prolapse.
MATERIALS AND METHODS
Participants included in this study had been evaluated and treated for pelvic organ prolapse, usually with surgery. Individuals in the proband group underwent surgery for pelvic organ prolapse at the University of Utah between 1996 and 2008. To be included in our original Utah Pelvic Floor Disorder Genetic Resource, a participant in the proband group was required to have a sister who also had moderate to severe pelvic organ prolapse, to have received treatment for pelvic organ prolapse, and was willing to participate in the study. The Utah Pelvic Floor Disorder Genetic Resource since has been expanded to include more distant affected relatives. Documentation of surgical management was required for women who had surgery outside our system. Participants were white and of Northern European descent, similar to Utah demographics. We included three participant groups for this analysis: 1) women who were treated for pelvic organ prolapse, had a close female family member who was similarly affected, and were originally part of our linkage analysis (n=70, 32 families);23 2) women treated for pelvic organ prolapse who were part of pedigrees of interest identified in the linkage analysis and recruited after the linkage analysis (n=33, sampled from 11 of the linkage families); and 3) individuals who were the only pelvic organ prolapse case sampled from their family, although other members of their family had a pelvic floor disorder (n=23). Exclusion criteria were genetic diseases with a known increased risk of pelvic organ prolapse (such as Ehlers Danlos, Marfan, and Steinert disease) or neurologic conditions (eg, multiple sclerosis or stroke) that might affect tissue weakness or incontinence. This study was approved by the University of Utah Institutional Review Board, and informed consent was obtained from all study participants.
We selected the control group from 3,293 control individuals from Illumina iControlDB who had available Illumina 550K array genotype data (both Illumina, Inc.) and who self-reported as white. These control participants are submitted as anonymous individuals from various different groups; information on presence of pelvic floor disorders is not available for these individuals. Because phenotype status is unknown, we would expect results using these control participants to be conservative but not biased. We checked for evidence of duplicate samples and closely related participants (ie, parent–offspring relationships) using the pair-wise estimated proportion of alleles shared identity-by-descent in the genetic association analysis software tool, PLINK24; 20 individuals who fit this criterion were removed from the control group list.
We identified a cohort of 76 independent white women from a Dutch genetic resource with recurrent pelvic organ prolapse and who had a mother, a sister, or a daughter who also had pelvic organ prolapse. Blood samples were collected from consecutive Dutch women with pelvic organ prolapse who presented at the Department of Obstetrics and Gynecology of the Radboud University Nijmegen Medical Centre between January 2007 and August 2008. Only women with pelvic organ prolapse case group individuals reporting a positive family history of pelvic organ prolapse were included in the present study. Exclusion criteria were genetic diseases with a known increased risk of pelvic organ prolapse (such as Ehlers Danlos, Marfan, and Steinert disease). Control data for the Dutch pelvic organ prolapse samples were not available; hence, association results were compared with Utah pelvic organ prolapse case group individuals, Utah-matched control group selected from iControlDB, and HapMap Centre d'Etude du Polymorphisme Humain Utah independent individuals who are Utah residents with Northern and Western European ancestry from the Centre d'Etude du Polymorphisme Humain collection and selected as one of the populations genotyped for the International HapMap project. The Centre d'Etude du Polymorphisme Humain Utah cohort consists of a set of 30 trios (mother-father-offspring); only the 60 independent parents were included in this analysis. All individuals from the Dutch cohort gave informed consent and the study was approved by the Medical Ethics Review Committee Arnhem/Nijmegen.
DNA was extracted from all Utah study participants and genome-wide genotyping was performed at deCODE Genetics (Iceland). Samples were genotyped on the Illumina HumanHap550 (approximately 550,000 SNPs) or 610Q platforms (approximately 610,000 SNPs). The Illumina 610Q contains the majority of the HumanHap 550 set of SNP markers plus additional copy number variants. We identified a set of SNP markers common to both the Illumina 610Q platform and the HumanHap 550 platform as our genotype set. All samples had a minimum call rate of 98%. We started with 126 strictly defined pelvic organ prolapse case group individuals; 10 case group individuals were not included because they failed to reach the minimum call rate.
For quality-control purposes, SNPs were required to have a call rate of 95%, minor allele frequency of 0.01, and Hardy-Weinberg equilibrium P<.001. Call rate for a SNP refers to the percent of participants for whom genotypes can be assigned. The final number of SNP markers analyzed that met all of the quality-control thresholds was 499,948.
Single-nucleotide polymorphisms that met the significance criterion in the genome-wide association analyses then were studied in the confirmation set of recurrent familial pelvic organ prolapse case group participants from Holland. Genotyping of SNPs was performed using the fluorogenic 5′ nuclease TaqMan Assay (Applied Biosystems) and polymerase chain reaction amplification was performed according to Applied Biosystems protocol. The 7900HT Sequence Detection System (Applied Biosystems) was used to measure each fluorescent dye-labeled probe specific for each allele studied, and results were analyzed with the Sequence Detection Software (Applied Biosystems). One of the SNPs (rs8027714) was custom-ordered from Applied Biosystems because it was not available in their resource of predesigned TaqMan assays; quality-control measures for custom SNPs are not as rigorous as the Applied Biosystem predesigned assays.
Spurious association results can be attained because of population stratification or systematic differences in ancestry between those in the case group and those in the control group if not taken into account. Details of our method to control for population stratification are supplied in the Appendix. To control for population stratification, we removed one pelvic organ prolapse case and 297 control participants. Our genomic inflation factor (λGC), or a measure of population stratification, was 1.05, as calculated using the software package EMMAX (Efficient Mixed-Model Association eXpedited).25 Levels of population stratification are generally considered acceptable for λGC 1.05 or less.26 Hence, our working Utah sample size was 115 case group participants and 2,976 control participants.
Standard association methods typically assume independence of case participants and of control participants. Our inclusion of related individuals necessitates the use of methodology that adjusts for relatedness. Two different analytical methods were used. The software program EMMAX uses linear mixed-model regression and a variance component matrix approach to account for the relatedness, even cryptic relatedness, between pairs of individuals.25 For the second method, we performed an initial naïve genome-wide screen ignoring family relationships using the program PLINK.24 Single-nucleotide polymorphisms meeting an initial P<5×10−7 in PLINK were then reanalyzed using Genie, a Monte-Carlo simulation platform that performs association analyses and accounts for complete pedigree structure by computing an empirical P value.27 These two methods both perform association tests among related individuals, but the method used is not the same. EMMAX accounts for relatedness through analysis of pairs of individuals, whereas Genie accounts for relatedness by genotype simulation through the known pedigree structure, which can take considerable computing time. Only markers meeting an initial naïve threshold were analyzed using Genie. Because standard methodology for analyzing related data does not exist, we have opted to report results using these two different methodologies. Any SNP meeting a genome-wide significance threshold of 1×10−7 for either method was considered significant after accounting for multiple testing by Bonferroni correction (ie, 0.05 divided by 499,948 tests). To search for systematic bias (eg, unrecognized population stratification), we plotted a quantile–quantile plot. Genome-wide significance results were graphed using a Manhattan plot. The following R codes were used to generate the plots.28,29 For the validation arm of the study using the Dutch pelvic organ prolapse case group participants, we considered a threshold of P<.05 for significance and considered P<.1 to be a trend toward significance.
Characteristics of the Utah pelvic organ prolapse participants are presented in Table 1. We analyzed 115 Utah pelvic organ prolapse case group participants and 2,976 in the control group. Most case group participants had been treated for pelvic organ prolapse with surgery (98.2%); however, many also had been treated for stress urinary incontinence (62.6%) or overactive bladder (32.2%). Approximately 30% of the Utah case group participants had recurrent pelvic organ prolapse and required repeat surgery.
The quantile–quantile plot in Figure 1 showed little evidence of inflation of the test statistic after correction for relatedness using EMMAX. Results of the genome-wide association analyses using EMMAX are shown in Figure 2. Five SNPs met genome-wide significance at P<1×10−7 (see list of SNPs in Table 2) using EMMAX. For the second genome-wide association analysis, we identified 133 unique markers from the naïve association analysis performed using PLINK with a P<5×10−7. After analysis using Genie to account for relatedness, four markers remained significant at P<1×10−7. Three of the markers from the Genie analysis also were found to be significant using EMMAX (rs1455311, rs1036819, and rs8027714). Genie identified one SNP that was not found to be significant using EMMAX (rs430794). These six SNPs were considered of interest for validation. Results for these six SNPs are shown in Table 2 and Figure 3.
Validation results of the six associated SNPs in the Dutch pelvic organ prolapse case set are shown in Table 3. For results to be of interest, we would expect similar results between the Utah pelvic organ prolapse case group participants and the Dutch pelvic organ prolapse case group participants (ie, no significant association difference), and we would expect significant differences between the Dutch pelvic organ prolapse case group participants and the control populations (ie, the Utah matched control individuals and the HapMap Centre d'Etude du Polymorphisme Humain Utah individuals. We observed that five of the six SNPs showed nominally significant findings (P<.05) or trending toward significance (P<.1) for one of the three comparison groups. For example, Dutch pelvic organ prolapse case group participants were significantly different from Utah matched control group participants for SNP rs2236479 at 21q22.3 (P=.029). One SNP was not significantly different than that of the Utah pelvic organ prolapse case group individuals; that SNP was rs430794 (P=.892), which is expected for validation using the Utah pelvic organ prolapse case group individuals as the comparison group. We note, however, that all of these results were observed for only one comparison group; there were no results that were consistent across all three comparison groups.
We have identified six SNPs that are significantly associated with pelvic organ prolapse in a dataset of 115 women with a strong family history of pelvic floor disorders and with strictly defined pelvic organ prolapse diagnosed. Genome-wide association studies test the hypothesis that common variants in the population (ie, variants with typically 1%–5% frequency) increase the susceptibility to a common disease such as pelvic organ prolapse. An association study using large pedigrees that segregate a small set of variants increases the likelihood that some of these more rare variants become detectable. Whereas our case group sample size in this study is small compared with the thousands of individuals typically used in a genome-wide association study, the use of women from high-risk pelvic organ prolapse families increases the likelihood that these case group participants have a genetic component to their disease and, hence, increases the likelihood that rare disease-contributing variants could be detected in an association analysis.
We previously performed a linkage analysis using some of the same affected individuals who were included in this genome-wide association study and reported significant linkage of pelvic organ prolapse to chromosome region 9q21.23 One of 6 SNPs identified in the association analysis at 9q22 (rs430794) is just outside this previous significant linkage region. Linkage analysis is most ideal for detecting highly penetrant rare loci in high-risk families, whereas association analysis is most useful for detecting common loci in a case-control cohort. We assume that a complex disease such as pelvic organ prolapse involves multiple loci, some common and some rare. Linkage analysis and an association analysis have different strengths and can provide complementary information for study of a complex disease such pelvic organ prolapse.
Two of the six SNPs were located within genes; rs1036819 is located in the ZFAT gene (Mendelian Inheritance in Man: 610931) and rs2236479 is located in the COL18A1 gene (Mendelian Inheritance in Man: 120328). The ZFAT gene has been found to play a transcriptional regulator role for immune regulation and apoptosis.30 The ZFAT gene might be involved in development of mesodermal cells31 and, hence, may affect development of muscle and connective tissue of the pelvic floor. The collagen XVIII (COL18A1) gene is another interesting candidate gene for pelvic organ prolapse. Endostatin, the C-terminal fragment of collagen XVIII, and its precursor collagen XVIII may play a role in the structural organization of basement membranes.32,33 In mouse models of wound healing, mice overexpressing endostatin showed delayed healing, delayed formation of the epidermal basement membrane, and a more disorganized epidermal and capillary basement membrane structure.34 In the pelvic floor, endostatin and collagen XVIII may play a role in basement membrane organization and response to both minor and major insults.
The other four SNPs identified are intergenic, but one of them is also close to a gene of interest for pelvic organ prolapse. The SNP rs1455311 at 4q21 is approximately 0.85 Mb away from the anthrax toxin receptor 2 (ANTXR2) gene (Mendelian Inheritance in Man: 608041), which binds to collagen intravenously and laminin, suggesting that it may be involved in extracellular matrix adhesion.35
Although we were unable to conclusively validate the Utah findings, we obtained some nominally significant results in the validation set from Holland. There are a number of factors that might explain the lack of strong validation findings, including lack of available control data matched to the Dutch pelvic organ prolapse case group participants, a small sample size for the Dutch cohort, and phenotype differences between the Utah and the Dutch pelvic organ prolapse case group participants (eg, Utah case group individuals were more likely to have a mixed pelvic floor disorder phenotype). Another explanation for the lack of strong validation findings is that some or all of the Utah results may be false-positives; the Utah sample size is small relative to most other genome-wide association study. Despite these limitations, we note that the Dutch Genetic Resource is a close match to the Utah participants used in this study: the majority of Utah residents are of Northern European descent, similar to the white residents of Holland, and the Dutch resource included familial pelvic organ prolapse case group individuals, as did the Utah cohort. There are few investigators in the world who are collecting blood from pelvic organ prolapse case group participants for genetic studies and even fewer who are collecting blood from families with an excess of pelvic organ prolapse case group participants. Future replication studies will need to include more familial case group participants and use appropriate control group participants.
Although these results still require additional replication, it is likely that one day genetic screening tests will be available to assess genetic risk for pelvic organ prolapse. Understanding more about the genetic etiology of pelvic organ prolapse could improve prevention and treatment of this condition, such as studying at-risk groups for preventive strategies (eg, managing constipation or changing delivery modes). Patients might benefit from changing management algorithms, such as whether surgery is considered early or late in an individual woman's clinical course.
In conclusion, this work provides evidence for a genetic contribution to pelvic organ prolapse. We have identified six SNPs that are significantly associated with pelvic organ prolapse in women with a strong family history of pelvic floor disorders. Although we were unable to conclusively replicate our results, we have identified at least three strong candidate genes for pelvic organ prolapse that warrant follow-up. This association study furthers our understanding of the genetic underpinnings of pelvic organ prolapse.
1. Nygaard I, Barber MD, Burgio KL, Kenton K, Meikle S, Schaffer J, et al.. Prevalence of symptomatic pelvic floor disorders in US women. JAMA 2008;300:1311–6.
2. Swift S, Woodman P, O'Boyle A, Kahn M, Valley M, Bland D, et al.. Pelvic Organ Support Study (POSST): the distribution, clinical definition, and epidemiologic condition of pelvic organ support defects. Am J Obstet Gynecol 2005;192:795–806.
3. Olsen AL, Smith VJ, Bergstrom JO, Colling JC, Clark AL. Epidemiology of surgically managed pelvic organ prolapse and urinary incontinence. Obstet Gynecol 1997;89:501–6.
4. Brown JS, Waetjen LE, Subak LL, Thom DH, Van den Eeden S, Vittinghoff E. Pelvic organ prolapse surgery in the United States, 1997. Am J Obstet Gynecol 2002;186:712–6.
5. Rortveit G, Brown JS, Thom DH, Van Den Eeden SK, Creasman JM, Subak LL. Symptomatic pelvic organ prolapse: prevalence and risk factors in a population-based, racially diverse cohort. Obstet Gynecol 2007;109:1396–403.
6. Norton P, Milsom I. Genetics and the lower urinary tract. Neurourol Urodyn 2010;29:609–11.
7. Chiaffarino F, Chatenoud L, Dindelli M, Meschia M, Buonaguidi A, Amicarelli F, et al.. Reproductive factors, family history, occupation and risk of urogenital prolapse. Eur J Obstet Gynecol Reprod Biol 1999;82:63–7.
8. Buchsbaum GM, Duecy EE, Kerr LA, Huang LS, Perevich M, Guzick DS. Pelvic organ prolapse in nulliparous women and their parous sisters. Obstet Gynecol 2006;108:1388–93.
9. Jack GS, Nikolova G, Vilain E, Raz S, Rodriguez LV. Familial transmission of genitovaginal prolapse. Int Urogynecol J Pelvic Floor Dysfunct 2006;17:498–501.
10. Chen HY, Chung YW, Lin WY, Wang JC, Tsai FJ, Tsai CH. Collagen type 3 alpha 1 polymorphism and risk of pelvic organ prolapse. Int J Gynaecol Obstet 2008;103:55–8.
11. Kluivers KB, Dijkstra JR, Hendriks JC, Lince SL, Vierhout ME, van Kempen LC. COL3A1 2209G>A is a predictor of pelvic organ prolapse. Int Urogynecol J Pelvic Floor Dysfunct 2009;20:1113–8.
12. Ferrell G, Lu M, Stoddard P, Sammel MD, Romero R, Strauss JF 3rd, et al.. A single nucleotide polymorphism in the promoter of the LOXL1 gene and its relationship to pelvic organ prolapse and preterm premature rupture of membranes. Reprod Sci 2009;16:438–46.
13. Chen HY, Lin WY, Chen YH, Chen WC, Tsai FJ, Tsai CH. Matrix metalloproteinase-9 polymorphism and risk of pelvic organ prolapse in Taiwanese women. Eur J Obstet Gynecol Reprod Biol 2010;149:222–4.
14. Chen HY, Chung YW, Lin WY, Chen WC, Tsai FJ, Tsai CH. Estrogen receptor alpha polymorphism is associated with pelvic organ prolapse risk. Int Urogynecol J Pelvic Floor Dysfunct 2008;19:1159–63.
15. Chen HY, Chung YW, Lin WY, Chen WC, Tsai FJ, Tsai CH. Progesterone receptor polymorphism is associated with pelvic organ prolapse risk. Acta Obstet Gynecol Scand 2009;88:835–8.
16. Chen HY, Wan L, Chung YW, Chen WC, Tsai FJ, Tsai CH. Estrogen receptor beta gene haplotype is associated with pelvic organ prolapse. Eur J Obstet Gynecol Reprod Biol 2008;138:105–9.
17. Connell KA, Guess MK, Tate A, Andikyan V, Bercik R, Taylor HS. Diminished vaginal HOXA13 expression in women with pelvic organ prolapse. Menopause 2009;16:529–33.
18. Bukovsky A, Copas P, Caudle MR, Cekanova M, Dassanayake T, Asbury B, et al.. Abnormal expression of p27kip1 protein in levator ani muscle of aging women with pelvic floor disorders - a relationship to the cellular differentiation and degeneration. BMC Clin Pathol 2001;1:4.
19. Hundley AF, Yuan L, Visco AG. Skeletal muscle heavy-chain polypeptide 3 and myosin binding protein H in the pubococcygeus muscle in patients with and without pelvic organ prolapse. Am J Obstet Gynecol 2006;194:1404–10.
20. Hundley AF, Yuan L, Visco AG. Gene expression in the rectus abdominus muscle of patients with and without pelvic organ prolapse. Am J Obstet Gynecol 2008;198:220 e1–7.
21. Visco AG, Yuan L. Differential gene expression in pubococcygeus muscle from patients with pelvic organ prolapse. Am J Obstet Gynecol 2003;189:102–12.
22. Nikolova G, Lee H, Berkovitz S, Nelson S, Sinsheimer J, Vilain E, et al.. Sequence variant in the laminin gamma1 (LAMC1) gene associated with familial pelvic organ prolapse. Hum Genet 2007;120:847–56.
23. Allen-Brady K, Norton PA, Farnham JM, Teerlink C, Cannon-Albright LA. Significant linkage evidence for a predisposition gene for pelvic floor disorders on chromosome 9q21. Am J Hum Genet 2009;84:678–82.
24. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al.. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–75.
25. Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, et al.. Variance component model to account for sample structure in genome-wide association studies. Nat Genet 2010;42:348–54.
26. Price AL, Zaitlen NA, Reich D, Patterson N. New approaches to population stratification in genome-wide association studies. Nat Rev Genet 2010;11:459–63.
27. Allen-Brady K, Wong J, Camp NJ. PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size. BMC Bioinformatics 2006;7:209.
30. Koyanagi M, Nakabayashi K, Fujimoto T, Gu N, Baba I, Takashima Y, et al.. ZFAT expression in B and T lymphocytes and identification of ZFAT-regulated genes. Genomics 2008;91:451–7.
31. Tsunoda T, Takashima Y, Tanaka Y, Fujimoto T, Doi K, Hirose Y, et al.. Immune-related zinc finger gene ZFAT is an essential transcriptional regulator for hematopoietic differentiation in blood islands. Proc Natl Acad Sci U S A 2010;107:14199–204.
32. Utriainen A, Sormunen R, Kettunen M, Carvalhaes LS, Sajanti E, Eklund L, et al.. Structurally altered basement membranes and hydrocephalus in a type XVIII collagen deficient mouse line. Hum Mol Genet 2004;13:2089–99.
33. Elamaa H, Sormunen R, Rehn M, Soininen R, Pihlajaniemi T. Endostatin overexpression specifically in the lens and skin leads to cataract and ultrastructural alterations in basement membranes. Am J Pathol 2005;166:221–9.
34. Seppinen L, Sormunen R, Soini Y, Elamaa H, Heljasvaara R, Pihlajaniemi T. Lack of collagen XVIII accelerates cutaneous wound healing, while overexpression of its endostatin domain leads to delayed healing. Matrix Biol 2008;27:535–46.
35. Bell SE, Mavila A, Salazar R, Bayless KJ, Kanagala S, Maxwell SA, et al.. Differential gene expression during capillary morphogenesis in 3D collagen matrices: regulated expression of genes involved in basement membrane matrix assembly, cell cycle progression, cellular differentiation and G-protein signaling. J Cell Sci 2001;114(Pt 15):2755–73.
Appendix Population Stratification
To account for population stratification and to select a set of genetically matched control individuals for our case population, we selected a random pelvic organ prolapse case group participant with genotype data from each pedigree to represent our case population. Using these independent individuals, we then performed multidimensional scaling in PLINK25 to produce two-dimensional coordinates for each individual. We calculated the mean of each of the two dimensions for case group individuals only and then computed a Euclidean distance from this case centroid measurement for each individual (ie, both case and control group individuals). The genomic inflation factor (λGC) indicates the level of population stratification in the dataset. A value of λGC approximately equal to 1 indicates no stratification and values of λGC more than 1 indicate population stratification or other confounders. One pelvic organ prolapse case group individual and 297 control group individuals were considered outliers based on their distance from the case centroid measurement and were removed from the analysis. Our initial unadjusted-for-relatedness λGC was 1.15 using one pelvic organ prolapse case group individual per pedigree and all control group individuals. However, after removal of the outliers, our λGC was reduced to 1.05, as calculated using the software package EMMAX, which does account for relatedness of individuals.26 Levels of population stratification are generally considered acceptable for λGC 1.05 or less.
This article has been cited 2 time(s).
Nature Reviews GeneticsMining electronic health records: an additional perspectiveNature Reviews Genetics
American Journal of Obstetrics and GynecologyPhenotyping clinical disorders: lessons learned from pelvic organ prolapseAmerican Journal of Obstetrics and Gynecology
© 2011 by The American College of Obstetricians and Gynecologists.
Looking for ABOG articles? Visit our ABOG MOC II collection. The selected Green Journal articles are free from October through December
ACOG MEMBER SUBSCRIPTION ACCESS
If you are an ACOG Fellow and have not logged in or registered to Obstetrics & Gynecology, please follow these step-by-step instructions to access journal content with your member subscription.