Abstract
Positive selection for inherited mutations in breast and ovarian cancer predisposing genes, BRCA1 and BRCA2, may contribute to the high frequency of BRCA mutations among the Ashkenazi Jewish population. Impact of BRCA mutations on fertility has not been generally explored in epidemiologic studies. There are reports of distorted sex ratios in BRCA carrier families but these findings have been attributed to bias. We investigated the effect of BRCA mutations on female fertility and offspring sex ratio in a study of 260 Ashkenazi Jewish women with ovarian cancer and 331 controls, unselected for age or family history of the disease. Pregnancy success was similar for 96 mutation carrier (0.84) and 164 noncarrier cases (0.87) and controls (0.83). After adjusting for covariates, there were no significant differences between BRCA carrier and noncarrier cases and controls with regards to fertility, despite lower pregnancy rates among all cases compared to controls (P = 0.0049). Male/female sex ratios were significantly lower among offspring of carriers (0.71) than offspring of noncarriers (0.95) or those of the controls (0.99). Comparisons among the three groups yielded statistically significant distortion against males among the offspring of known and obligate BRCA carriers compared to noncarriers (OR = 0.74, 95% CI:0.55–0.99) and controls (OR = 0.71, 95% CI:0.54–0.94). In conclusion, we did not find evidence for an effect of BRCA mutations on female fertility. We found a significant excess of females among the offspring of female carriers of BRCA1 and BRCA2 mutations. Potential contribution of observed sex ratio distortions to positive selection for BRCA mutations may warrant further investigation.
The high frequency of BRCA mutations among certain populations such as Ashkenazi Jews (2.4% overall frequency for BRCA1 185delAG and 5382insC and BRCA2 6174delT mutations) (Oddoux et al., 1996; Roa et al., 1996), mostly attributed to founder effects (Szabo and King, 1997), may also be suggestive of positive selection for these mutations. Our interest lies in two potential mechanisms influencing positive selection. One is a potential effect for BRCA mutations on female fertility. The other is an effect for BRCA mutations on altering sex ratios among the offspring of mutation carriers towards females, who have been suggested as having a higher effective population size historically (Wilder et al., 2004) and an evolutionary advantage over males for becoming population founders following sex-biased genetic bottlenecks (Hammer et al., 2008; Singh et al. 2007).
The impact of BRCA mutations on human fertility has not been generally explored in epidemiologic studies. Recent reports that BRCA1 protein is upregulated in human male and female germ cells and in preimplantation embryos (Giscard d’Estaing et al., 2005), and that it may regulate estrogen receptor (ER) α activity through ubiquitination (Eakin et al., 2007), suggest an effect for BRCA mutations on human fertility and/or prenatal survival or pregnancy success.
Studies of the impact of BRCA mutations on offspring sex ratios have produced equivocal results. While an earlier study reported distorted sex ratios against male births in BRCA1 families (de la Hoya et al., 2003), subsequent studies either failed to verify the initial findings of skewed sex ratios or attributed the observed distortions to bias (Domchek et al., 2005; Feunteun et al., 2004; Mealiffe, 2003). Ascertainment bias (ascertainment through female probands and/or based on a family history) and/or selection bias (higher likelihood of females with daughters participating in cancer genetic studies) were suggested to be responsible for findings of excess females in BRCA1 families (Domchek et al., 2005; Feunteun et al., 2004; Mealiffe, 2003).
We investigated the impact of BRCA1 and BRCA2 mutations on female fertility and offspring sex ratio using data collected as part of a hospital-based case-control study of Ashkenazi Jewish women with ovarian cancer, designed to reduce ascertainment and selection biases, with the objective of genetic characterization of the BRCA genes (Moslehi et al., 2000).
METHODS
Cases were 260 Ashkenazi Jewish women with ovarian cancer unselected for age or a family history of the disease and included 51 BRCA1 185delAG, 15 BRCA1 5382insC, and 30 BRCA2 6174delT carriers. Controls were 331 Ashkenazi Jewish women without a personal history of ovarian cancer. Detailed epidemiologic and family history information obtained at the time of ascertainment was available on all participants.
BRCA carriers, noncarriers and controls were compared with respect to the distribution of demographic variables using Chi-square statistics. The three groups were also compared with respect to pregnancy success, pregnancy rate, and fertility. Pregnancy success was defined as the ratio of number of liveborn offspring per woman to number of pregnancies per woman excluding induced abortions. Fertile person-time for each woman was calculated taking into account the reproductive period between 18 and 44 years of age, excluding the time when the subject was on contraception and 2 months after each pregnancy. Pregnancy rate was defined as number of all known pregnancies (regardless of outcome) divided by fertile person-years. Fertility was defined as pregnancy during the reproductive period, modeled as a Poisson outcome while adjusting for covariates (age, oral contraceptive use, body mass index, regularity of menstrual cycle, history and treatment for infertility, and age at menarche). For fertility analysis, we censored the person-time for a subject if she had tubal ligation, hysterectomy, or menopause before 44 years of age. Comparison of Poisson rates for different groups was done by using PROC GENMOD of the Statistical Analysis System (SAS) software (version 9.1; SAS Institute, Cary, NC).
Male/female sex ratios among the liveborn offspring of two generations of women (proband’s generation and proband’s mother’s generation) who were known and obligate mutation carriers, noncarriers, and controls were determined and compared by calculating odds ratios (OR) and 95% confidence intervals (95%CI). Obligate mutation carriers were restricted to the mothers of the probands and to reduce ascertainment bias, all probands were excluded as offspring from the sex ratio analyses.
RESULTS
Distribution of demographic variables was similar between BRCA carrier and noncarrier ovarian cancer cases and controls (Table 1).
TABLE 1.
Distribution of demographic variables among probands
BRCA 1/2 carriers [n = 96 (%)] | Noncarriers [n = 164 (%)] | Controls [n = 331 (%)] | |
---|---|---|---|
Average age (years) | 57.9 | 60.1 | 52.2 |
Age (years) | |||
≤30 | 0 | 6 (3.7) | 3 (0.9) |
31–40 | 7 (7.3) | 7 (4.3) | 49 (14.8) |
41–50 | 21 (21.9) | 36 (21.9) | 115 (34.7) |
51–60 | 31 (32.3) | 32 (19.5) | 97 (29.3) |
61–70 | 23 (24.0) | 39 (23.8) | 35 (10.6) |
>70 | 14 (14.6) | 44 (26.9) | 32 (9.7) |
Average age of diagnosis of ovarian cancer | 54.6 | 57.1 | N/A |
BRCA Mutations | |||
BRCA1 185delAG | 51 (52.6) | ||
BRCA1 5382insC | 15 (15.5) | N/A | N/A |
BRCA2 6174delT | 30 (30.9) | ||
Average BMI (kg m−2) | 21.8 | 21.9 | 22.2 |
Oral Contraceptive use for regulating periods | |||
Yes | 11 (11.5) | 11 (6.7) | 52 (15.7) |
Oral Contraceptive use for birth control | |||
Yes | 42 (43.7) | 56 (34.1) | 203 (61.3) |
Tubal ligation | |||
Yes | 13 (13.5) | 11 (6.7) | 75 (22.7) |
Periods always/usually regular | |||
Yes | 84 (87.5) | 133 (81.1) | 262 (79.1) |
Medication to become pregnant | |||
Yes | 10 (10.4) | 16 (9.8) | 34 (10.3) |
Education (Last degree obtained) | |||
College/University/Professional School | 76 (79.2) | 103 (62.8) | 225 (68.0) |
High school | 13 (13.5) | 41 (25.0) | 67 (20.2) |
Less than high school | 4 (4.2) | 12 (7.3) | 12 (3.6) |
Regular consumption of alcohol | |||
Yes | 16 (16.7) | 19 (11.6) | 42 (12.7) |
Smoking history | |||
Yes (Ever smoker) | 45 (46.9) | 78 (47.6) | 153 (46.2) |
Median pack years of smoking | 14.6 | 13.9 | 8.5 |
Family history of breast and/or ovarian cancer among first-degree relatives | |||
Yes | 20 (20.8) | 15 (9.1) | 11 (3.3) |
No statistically significant differences were observed in the frequency of induced abortions, spontaneous abortions, or stillbirths between carrier and noncarrier cases and controls (Table 2). Pregnancy success was nearly equal for mutation carriers (0.84), non-carriers (0.87) and controls (0.83). Pregnancy success was lower for BRCA2 carriers (0.78) compared to BRCA1 carriers (0.88), but the difference did not reach statistical significance (Table 2).
TABLE 2.
Comparison of pregnancy histories of carrier and noncarrier cases and controls
BRCA1 carriers [n = 66 (%)] | BRCA2 carriers [n = 30 (%)] | BRCA 1/2 carriers [n = 96 (%)] | Noncarriers [n = 164 (%)] | Controls [n = 331 (%)] | |
---|---|---|---|---|---|
Total number of pregnancies | 157 | 94 | 251 | 443 | 829 |
Number of liveborn offspring | 114 (72.6) | 67 (71.3) | 181 (72.1) | 340 (76.7) | 633 (76.4) |
Number of induced abortionsa | 28 (17.8) | 8 (8.5) | 36 (14.3) | 54 (12.2) | 68 (8.2) |
Number of spontaneous abortions and still births | 15 (9.5) | 19 (20.2) | 34 (13.5) | 49 (11.1) | 128 (15.4) |
Pregnancy successb | 0.88 | 0.78 | 0.84 | 0.87 | 0.83 |
Includes therapeutic abortions.
Pregnancy success calculated as the ratio of number of liveborn offspring to number of pregnancies per subject excluding induced abortions.
Information on all reproductive and confounding variables for adjusted analyses of fertility was available on 93 BRCA carriers, 153 noncarriers, and 307 controls. The average numbers of pregnancies among carriers, noncarriers, and controls are shown in Table 3. In adjusted analyses, cases had a significantly lower pregnancy rate than controls (P = 0.0049) (Table 3). There were no significant differences between the carrier and noncarrier cases and controls with regards to fertility after adjusting for covariates (Table 3).
TABLE 3.
Adjusted fertility analysis among carrier and noncarrier cases and controls
BRCA 1/2 carriers [n = 93 (%)] | Noncarriers [n = 153 (%)] | Controls [n = 307 (%)] | |
---|---|---|---|
Number of pregnancies | |||
None | 8 (8.6) | 17 (11.1) | 21 (6.8) |
One | 8 (8.6) | 18 (11.8) | 29 (9.4) |
Two | 35 (37.6) | 44 (28.8) | 105 (34.2) |
Three | 25 (26.9) | 36 (23.5) | 81 (26.4) |
Four | 8 (8.6) | 21 (13.7) | 38 (12.4) |
More than four | 9 (9.8) | 17 (11.1) | 33 (10.7) |
Average number of pregnancies | 2.56 | 2.59 | 2.68 |
Median fertile person-years (18–44 years) | 25.0 | 25.0 | 20.7 |
Average pregnancy rate | 0.13 | 0.13 | 0.18 |
Poisson regression model for fertilitya
| |||
Parameters | Coefficient | Confidence interval | P-values |
| |||
Cases vs. controls | −0.1723 | −0.2922, −0.0524 | 0.0049 |
Carriers vs. Noncarriers and controls | −0.0118 | −0.1726, 0.1489 | 0.8853 |
Carrier vs. Noncarrier Cases | 0.5723b |
Covariates adjusted for: age, oral contraceptive use, body mass index, regularity of periods, history of and treatment for infertility, and age at menarche.
P-value calculated by conditional exact test. The exact test was used because of small numbers in each group.
Male/female sex ratios were significantly lower among the offspring of BRCA carriers (0.71) than the offspring of noncarriers (0.95) or controls (0.99). Comparisons among the three groups yielded statistically significant distortion against males among the offspring of known and obligate BRCA carriers compared to noncarriers (OR = 0.74, 95% CI:0.55–0.99) and controls (OR = 0.71, 95% CI:0.54–0.94) (Table 4).
TABLE 4.
Comparison of sex ratios among the offspring of known and obligate BRCA carriers, noncarriers, and controls in two generations
BRCA 1/2 carriers (n = 133) | Noncarriers (n = 328) | Controls (n = 662) | ORa (95% CI) | ORb (95% CI) | |
---|---|---|---|---|---|
Offspring sex ratio [M/F] | 0.71 [106/150] | 0.95 [323/339] | 0.99 [599/606] | 0.74 (0.55, 0.99) | 0.71 (0.54, 0.94) |
OR: odds ratio for child being male comparing carriers with noncarriers.
OR: odds ratio for child being male comparing carriers with controls.
Similar sex ratio distortions were observed among the offspring of BRCA carriers in the two generations. In the proband’s generation, male/female sex ratios were lower among the 181 offspring of BRCA carrier cases (0.74) compared to 341 offspring of non–carriers (0.92) and 633 offspring of controls (1.00) (Table 5). The reduction in male/female sex ratios were more pronounced among the 114 offspring of BRCA1 (0.68) versus 67 offspring of BRCA2 (0.86) carriers, but the difference was not statistically significant. Analysis of sex ratios among the offspring of probands’ mothers, following exclusion of the probands as offspring, also yielded lower male/female sex ratios for 75 offspring of BRCA carriers (0.63) compared to 321 offspring of noncarriers (0.99) and 572 offspring of controls (0.97) (Table 6).
TABLE 5.
Comparison of sex ratios among the offspring of probands
BRCA 1/2 carriers (n = 96) | Noncarriers (n = 164) | Controls (n = 331) | ORa (95% CI) | ORb (95% CI) | |
---|---|---|---|---|---|
Offspring sex ratio [M/F] | 0.74 [77/104] | 0.92 [163/178] | 1.00 [317/316] | 0.81 (0.56, 1.16) | 0.74 (0.53, 1.03) |
OR: odds ratio comparing carriers with noncarriers.
OR: odds ratio comparing carriers with controls.
TABLE 6.
Comparison of sex ratios among the offspring of probands’ mothersa
BRCA 1/2 carriers (n = 36) | Noncarriers (n = 164) | Controls (n = 331) | ORb (95% CI) | ORc (95%CI) | |
---|---|---|---|---|---|
Offspring sex ratio [M/F] | 0.63 [29/46] | 0.99 [160/161] | 0.97 [282/290] | 0.63 (0.38, 1.06) | 0.65 (0.40, 1.06) |
Probands were excluded as offspring from all analyses.
OR: odds ratio comparing carriers with noncarriers.
OR: odds ratio comparing carriers with controls.
DISCUSSION
We did not find significant differences with respect to fertility among BRCA carriers and noncarriers after adjusting for confounders. Cases in our study had significantly fewer pregnancies compared to controls, even after adjusting for confounders of fertility, but it is likely that this reflects the known protective effect of parity against ovarian cancer (Permuth-Wey and Sellers, 2009). Despite lower pregnancy rates, pregnancy success was similar for mutation carrier and noncarrier cases and controls.
Theoretically, conferring beneficial effect on fertility and/or pregnancy success could lead to positive selection for a mutation. In vitro evidence suggests a role for BRCA1 in embryogenesis and fertility (Eakin et al., 2007; Giscard d’Estaing et al., 2005); however, molecular mechanisms of this putative effect remain to be elucidated. Although we did not find evidence for an effect of BRCA mutations on female fertility or prenatal survival, factors pertaining to the study design may have affected our results. Information on variables included in the fertility analysis model, such as oral contraceptive use and treatment for infertility, was based on self-reports by the subjects; it was not possible to obtain medical records containing such information on all subjects. The size of the sample may have also influenced our results.
We found an excess of females among the offspring of female BRCA1 and BRCA2 mutation carriers in two generations. Our results are in agreement with earlier findings of a large excess of females in BRCA positive families (de la Hoya et al., 2003). de la Hoya et al. (2003) reported sex ratio distortions in BRCA1 families only; we found an excess of females among the offspring of female carriers of both BRCA1 and BRCA2 mutations although the ratios were more skewed among the offspring of BRCA1 carriers. While subsequent studies attributed the observed sex ratio distortions in BRCA families to possible confounding by ascertainment and/or selection biases (Domchek et al., 2005; Feunteun et al., 2004; Mealiffe, 2003), it is unlikely that either of these sources of bias would have influenced our results. Details of our study design have been published elsewhere (Moslehi et al., 2000). Ascertainment bias is unlikely since all prevalent cases of ovarian cancer among Ashkenazi Jewish women identified through the departments of gynecologic oncology of the participating hospitals were invited to participate in our study regardless of age or family history. To further reduce ascertainment bias, all probands were removed as offspring in sex ratio analyses. The possibility of selection bias influencing our results is equally remote. Overall participation rate for our study was ~ 82% and reasons for refusal included severe illness, concerns about insurance implications, and inability to speak English (Moslehi et al., 2000). Furthermore, any potential selection bias would have applied to both carrier and noncarrier cases. Survival bias may exist in our study but that would also apply to both carrier and noncarrier cases and is unlikely to explain or influence the sex ratio distortions observed.
A preponderance of females among the offspring of BRCA mutation carriers, as seen in our study, could contribute to positive selection for BRCA mutations through several mechanisms. Greater fertility and/or pregnancy success, as discussed above, may provide a selective advantage for BRCA1 and BRCA2 mutations. If this effect occurs only in females, then higher number of females who are BRCA carriers would magnify the selective advantage even further.
Another mechanism through which female preponderance among the offspring of mutation carriers could contribute to positive selection for those mutations is related to the proposed historical excess of breeding females over males (Hammer et al., 2008) and the proposed evolutionary advantage of females for becoming population founders during sex-biased genetic bottleneck events (Hammer et al., 2008; Singh et al., 2007). The Ashkenazi Jewish population is believed to have gone through at least one genetic bottleneck event in its two millennia history (Behar et al., 2004; Risch et al., 1995) and there is a debate in the literature with respect to the contribution of recent versus ancient founder effects to the high frequency of several disease alleles in this population (Goldstein et al., 1999; Risch et al., 1995). Recently, a mitochondrial DNA analysis provided evidence for a strong effect of genetic drift on the Ashkenazi Jewish gene pool marked by an early bottleneck event which is estimated to have occurred about 1,500 years ago (Behar et al., 2004). Although no historical evidence has been presented to indicate that this bottleneck event was sex-biased, evolutionary genetic studies suggest a higher female effective population size (Wilder et al., 2004), greater migration, and dispersion of females in earlier societies (Hamilton, 1967; West et al., 2002; Wilder et al., 2004), and evolutionary advantage of females over males for becoming population founders (Hammer et al., 2008; Singh et al., 2007). Thus an increased number of female population founders with BRCA mutations combined with strong genetic drift patterns may have contributed to a higher frequency of BRCA mutations in the Ashkenazi Jewish population. Although this scenario, which is dependent to a large extent on genetic drift, is a possibility, a more plausible explanation for the high frequency of two different mutations, namely, BRCA1 185delAG with an estimated frequency of ~1% and BRCA2 6174delT with an estimated frequency of ~1.4% in this population (Oddoux et al., 1996; Roa et al., 1996), may be positive selection.
The possibility of other nonrandom genetic events, such as nonrandom X chromosome inactivation reported to be associated with BRCA mutations in one study (Buller et al., 1999) and disputed in a more recent study (Helbling-Leclere et al., 2007), and nonrandom transmission of mutant alleles to female offspring of BRCA carriers (Gronwald et al., 2003) contributing to positive selection for BRCA mutations should also be considered. Although these latter processes should contribute to positive selection for BRCA mutations in all populations, their effects could be stronger in founder populations, particularly in those where several synergistic selective forces may be involved.
In conclusion, we did not find evidence for an effect of BRCA mutations on female fertility; however, we found an excess of females among the offspring of female carriers of both BRCA1 and BRCA2 mutations. Our results indicate that a more careful interpretation of reproductive outcomes and sex ratio distortion among the offspring of BRCA carriers and their potential contribution to positive selection for BRCA mutations is warranted.
Acknowledgments
Contract grant sponsor: State University of New York at Albany
RM conceived the study, helped analyze and interpret the data, and drafted the manuscript. RS and LL helped with data analysis. JMF helped with data analysis, data interpretation, and manuscript preparation. The authors thank Dr. S. Narod, Dr. AH Dzutsev, all collaborators on the parent study, and all study subjects.
Footnotes
There are no conflicts of interest for any of the authors on this manuscript.
LITERATURE CITED
- Behar DM, Hammer MF, Garrigan D, Villems R, Bonne-Tamir B, Richards M, Gurwitz D, Rosengarten D, Kaplan M, Della Pergola S, Quintana-Murci L, Skorecki K. MtDNA evidence for a genetic bottleneck in the early history of the Ashkenazi Jewish population. Eur J Hum Genet. 2004;12:355–364. doi: 10.1038/sj.ejhg.5201156. [DOI] [PubMed] [Google Scholar]
- Buller RE, Sood AK, Lallas T, Buekers T, Skilling JS. Association between nonrandom X-chromosome inactivation and BRCA1 mutation in germline DNA of patients with ovarian cancer. J Natl Cancer Inst. 1999;91:339–346. doi: 10.1093/jnci/91.4.339. [DOI] [PubMed] [Google Scholar]
- de la Hoya M, Fernandez JM, Tosar A, Godino J, Sanchez de Abajo A, Vidart JA, Perez-Segura P, Diaz-Rubio E, Caldes T. Association between BRCA1 mutations and ratio of female to male births in offspring of families with breast cancer, ovarian cancer, or both. JAMA. 2003;290:929–931. doi: 10.1001/jama.290.7.929. [DOI] [PubMed] [Google Scholar]
- Domchek SM, Merillat SL, Tigges J, Tweed AJ, Weinar M, Stopfer J, Weber BL. Sex ratio skewing of offspring in families with hereditary susceptibility to breast cancer. J Med Genet. 2005;42:511–513. doi: 10.1136/jmg.2004.027722. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Eakin CM, Maccoss MJ, Finney GL, Klevit RE. Estrogen receptor alpha is a putative substrate for the BRCA1 ubiquitin ligase. Proc Natl Acad Sci USA. 2007;104:5794–5799. doi: 10.1073/pnas.0610887104. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Feunteun J, Chompret A, Helbling-Leclerc A, Stoppa-Lyonnet D, Belotti M, Nogues C, Bonaiti-Pellie C. Sex ratio among the offspring of BRCA mutation carriers. JAMA. 2004;292:687–688. doi: 10.1001/jama.292.6.687. [DOI] [PubMed] [Google Scholar]
- Giscard d’Estaing S, Perrin D, Lenoir GM, Guerin JF, Dante R. Up-regulation of the BRCA1 gene in human germ cells and in preimplantation embryos. Fertil Steril. 2005;84:785–788. doi: 10.1016/j.fertnstert.2005.02.037. [DOI] [PubMed] [Google Scholar]
- Goldstein DB, Reich DE, Bradman N, Usher S, Seligsohn U, Peretz H. Age estimates of two common mutations causing factor XI deficiency: recent genetic drift is not necessary for elevated disease incidence among Ashkenazi Jews. Am J Hum Genet. 1999;64:1071–1075. doi: 10.1086/302313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gronwald J, Gorski B, Byrski T, Huzarski T, Jakubowska A, Menkiszak J, Narod SA, Lubinski J. Non-random transmission of mutant alleles to female offspring of BRCA1 carriers in Poland. J Med Genet. 2003;40:719–720. doi: 10.1136/jmg.40.9.719. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hamilton WD. Extraordinary sex ratios. A sex-ratio theory for sex linkage and inbreeding has new implications in cytogenetics and entomology. Science. 1967;156:477–488. doi: 10.1126/science.156.3774.477. [DOI] [PubMed] [Google Scholar]
- Hammer MF, Mendez FL, Cox MP, Woerner AE, Wall JD. Sex-biased evolutionary forces shape genomic patterns of human diversity. PLoS Genet. 2008;4:e1000202. doi: 10.1371/journal.pgen.1000202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Helbling-Leclere A, Lenoir GM, Feunteun J. Heterozygote BRCA1 status and skewed chromosome X inactivation. Fam Cancer. 2007;6:153–157. doi: 10.1007/s10689-006-9102-z. [DOI] [PubMed] [Google Scholar]
- Mealiffe ME. Sex ratios in families with BRCA mutations. JAMA. 2003;290:2544. doi: 10.1001/jama.290.19.2544-b. author reply 2544–2545. [DOI] [PubMed] [Google Scholar]
- Moslehi R, Chu W, Karlan B, Fishman D, Risch H, Fields A, Smotkin D, Ben-David Y, Rosenblatt J, Russo D, Schwartz P, Tung N, Warner E, Rosen B, Friedman J, Brunet J-S, Narod S. BRCA1 and BRCA2 mutation analysis of 208 Ashkenazi Jewish women with ovarian cancer. Am J Hum Genet. 2000;66:1259–1272. doi: 10.1086/302853. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Oddoux C, Struewing JP, Clayton CM, Neuhausen S, Brody LC, Kaback M, Haas B, Norton L, Borgen P, Jhanwar S, Goldgar D, Ostrer H, Offit K. The carrier frequency of the BRCA2 6174delT mutation among Ashkenazi Jewish individuals is approximately 1% Nat Genet. 1996;14:188–190. doi: 10.1038/ng1096-188. [DOI] [PubMed] [Google Scholar]
- Permuth-Wey J, Sellers TA. Epidemiology of ovarian cancer. Methods Mol Biol. 2009;472:413–437. doi: 10.1007/978-1-60327-492-0_20. [DOI] [PubMed] [Google Scholar]
- Risch N, de Leon D, Ozelius L, Kramer P, Almasy L, Singer B, Fahn S, Breakefield X, Bressman S. Genetic analysis of idiopathic torsion dystonia in Ashkenazi Jews and their recent descent from a small founder population. Nat Genet. 1995;9:152–159. doi: 10.1038/ng0295-152. [DOI] [PubMed] [Google Scholar]
- Roa BB, Boyd AA, Volcik K, Richards CS. Ashkenazi Jewish population frequencies for common mutations in BRCA1 and BRCA2. Nat Genet. 1996;14:185–187. doi: 10.1038/ng1096-185. [DOI] [PubMed] [Google Scholar]
- Singh ND, Macpherson JM, Jensen JD, Petrov DA. Similar levels of X-linked and autosomal nucleotide variation in African and non-African populations of Drosophila melanogaster. BMC Evol Biol. 2007;7:202. doi: 10.1186/1471-2148-7-202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Szabo CI, King MC. Population genetics of BRCA1 and BRCA2. Am J Hum Genet. 1997;60:1013–1020. [PMC free article] [PubMed] [Google Scholar]
- West SA, Reece SE, Sheldon BC. Sex ratios. Heredity. 2002;88:117–124. doi: 10.1038/sj.hdy.6800018. [DOI] [PubMed] [Google Scholar]
- Wilder JA, Mobasher Z, Hammer MF. Genetic evidence for unequal effective population sizes of human females and males. Mol Biol Evol. 2004;21:2047–2057. doi: 10.1093/molbev/msh214. [DOI] [PubMed] [Google Scholar]