Examination of reproductive aging milestones among
women who carry the FMR1 premutation
E.G. Allen1,4, A.K. Sullivan1, M. Marcus2, C. Small2, C. Dominguez3, M.P. Epstein1,
K. Charen1, W. He1, K.C. Taylor2and S.L. Sherman1
1Department of Human Genetics, Emory University;2Department of Epidemiology, Rollins School of Public Health, Emory University;
3Department of Gynecology and Obstetrics, School of Medicine, Emory University
4Correspondence address. 615 Michael Street, Suite 301, Atlanta, GA 30322, USA. Tel: þ1-404-778-8473; Fax: þ1-404-727-3949;
BACKGROUND: The fragile X premutation is characterized by a large CGG repeat track (55–199 repeats) in the 50
UTR of the FMR1gene. This X-linkedmutationleads toan increased risk forprematureovarianfailure; interestingly,
the association of repeat size with risk is non-linear. We hypothesize that the premutation-associated ovarian insuffi-
ciency is due to a diminished oocyte pool and examined reproductive aging milestones by repeat size group to deter-
mine if the same non-linear association is observed. METHODS: We analyzed cross-sectional reproductive history
questionnaire data from 948 women with a wide range of repeat sizes. RESULTS: We have confirmed the non-
linear relationship among premutation carriers for ovarian insufficiency. The mid-range repeat size group (80–100
repeats), not the highest group, had an increased risk for: altered cycle traits (shortened cycle length, irregular
cycles and skipped cycles), subfertility and dizygotic twinning. Smoking, a modifiable risk, decreased the reproductive
lifespan of womenwith the premutationby about1 year,similarto its effect on non-carriers. Asexpected,premutation
carriers were found to be at an increased risk for osteoporosis. CONCLUSIONS: Possible molecular mechanisms to
explain the non-linear repeat size risk for ovarian insufficiency are discussed.
Keywords: FMRP; infertility; menopause; RNA toxic effect; trinucleotide
The CGG repeat sequence located in the 50untranslated region
(UTR) of the FMR1 gene is now known to lead to three major
clinical phenotypes: (i) fragile X syndrome, (ii) late-onset
fragile X-related tremor/ataxia syndrome (FXTAS) and
(iii) ovarian dysfunction. The expression of each phenotype
depends on the size of repeat expansion and the consequent
molecular outcome. There are essentially four allelic forms
of the gene with respect to the CGG repeat length and stability
during transmission. They are referred to as common, inter-
mediate, premutation and full mutation. The full mutation
form of the FMR1 gene consists of over 200 repeats and is
abnormally hypermethylated. Consequently, no mRNA (or
sometimes very small amounts of mRNA) is produced. The
lack of the gene product, FMRP, an RNA-binding protein
involved in translation suppression, is responsible for fragile
X syndrome-related mental retardation (Ashley et al., 1993).
Approximately 1/4000 males have fragile X syndrome and
by inference, ?1/8000 females have the allele (for review,
see Crawford et al., 2001).
Premutation alleles are defined as such because their long,
unmethylated repeat tracks are unstable when transmitted
from parent to child and have led to a descendent with
fragile X syndrome. Approximately 1/250 females and
1/800 males carry premutation alleles of the range 55–199
repeats. Among women who carry the premutation, ?16%
have premature ovarian failure (POF), or cessation of menses
at least 1 year prior to age 40, compared with only 1% in the
general population, or a relative risk of 16 (for review, see
Sherman et al., 2007). Overall, premutation carriers go
through menopause ?5 years earlier than non-carriers
(Hundscheid et al., 2000; Murray et al., 2000; Sullivan et al.,
2005) and, among those still cycling, have higher FSH levels
(Murray et al., 1999; Hundscheid et al., 2001; Welt et al.,
2004; Sullivan et al., 2005). The risk for ovarian dysfunction
is not increased among full mutation carriers; thus, the molecu-
lar mechanism underlying this premutation-associated disorder
is unrelated to the reduction of FMRP.
Interestingly, in previous work, we (Sullivan et al., 2005)
and others (Ennis et al., 2006) found that FMR1 repeat size
was associated with age of menopause in a non-linear way:
the repeat sizes that led to the highest risk for POF and earlier
age at menopause appear to be in the mid-range of ?80–100,
not the highest premutation repeat sizes. Here, we have
# The Author 2007. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.
All rights reserved. For Permissions, please email: firstname.lastname@example.org
Page 1 of 11
Human Reproduction pp. 1–11, 2007
Hum. Reprod. Advance Access published June 22, 2007
by guest on June 2, 2013
investigated this association further and have examined other
reproductive aging milestones that may be indicative of
As reviewed by Nikolaou and Templeton (2004), there is
growing evidence that the interval between the critical
number of ?25 000 remaining follicles and ?1000, or meno-
pause, is more or less fixed, ?13 years. Assuming the average
age at menopause is 51, these data suggest that this critical
number of follicles is reached around age 37. It follows that
all other reproductive milestones that depend on quantity and
quality of follicles are also fixed; i.e. the timing between men-
strual cycle alteration and menopause should be fixed. As well,
the timing between reduced fertility and menopause should
be fixed. The results of Kok et al. (2003) are consistent with
this hypothesis. They found that measures of subfertility
were correlated with the time of menopause. For example,
for every 5-year increase of age at menopause: (i) the prob-
ability of reporting menstrual cycle irregularity was reduced
by 26%, the probability of ever consulting a physician for fer-
tility problems was reduced by 18%, the probability of staying
nulliparous was reduced by 22% and the probability of having a
spontaneous abortion was reduced by 11%. In another study,
the time interval between the loss of cycle regularity and meno-
pause was found to be ?6 years, irrespective of the age at
menopause (Den Tonkelaar et al., 1998). Richardson et al.
(1987) directly tied such changes to oocyte reserve. They
found that the number of primordial follicles in the ovaries
of women who were cycling regularly was 10 times higher
than those who had irregular cycles.
In this study, we evaluated reproductive aging milestones
(menstrual cycle characteristics and pregnancy outcomes) in
a large sample of women with and without the premutation
allele using self-reported data from structured questionnaires.
We divided premutation women into three groups: low (59–
79 repeats), mid (80–100 repeats) and high (101–199
repeats) repeat sizes. Overall, we found that all reproductive
aging milestones with the exception of spontaneous abortion
rates were present at a higher rate among premutation carriers
with 80–100 repeats compared with all other groups. We
discuss the implications of these findings with respect to the
etiology of the ovarian dysfunction.
Methods and Materials
The study population analyzed here extends that reported in Sullivan
et al. (2005) and was ascertained using the same protocol. Briefly, we
surveyed women in the general population and in families with fragile
X syndrome for alleles that fell roughly into the upper fifth percentile
of the northern European allele distribution, or those with .40
repeats. This strategy enriched the sample for high repeat allele car-
riers. For each woman identified, we enrolled a woman with ,40
repeats ascertained from the same recruitment site, or family,
matched on age and ethnic/racial group. All women were between
the ages of 18 and 75 and had English as their primary language.
All women completed a reproductive history questionnaire and pro-
vided a biological sample to determine repeat size. We also invited
mothers of each participant to be in the study. This strategy provided
us with an additional group of women who had completed most of
their reproductive lifespan. Table 1 shows the frequency of partici-
pants in different repeat size categories for women who were
younger than 40 years at the time of interview and those that were
?40 when they were interviewed.
Women became participants through three avenues. A few women
(n ¼ 13) came into the study because they had POF; for the analyses
outlined here, they were excluded because they would inflate esti-
mates of penetrance and, potentially, severity of reproductive traits.
Otherwise, participants were ascertained without prior knowledge of
ovarian status. However, they fell into two ‘ascertainment’ groups:
(i) those identified without knowledge of their reproductive history
(Group 1) and (ii) those identified through an offspring (i.e. mothers
of participants or mothers ascertained through a child with fragile X
syndrome) (Group 2). Thus, the women in the latter group were
known to be reproductively successful.
There were 329 mother/daughter pairs and 357 sister/sister pairs
ascertained from 311 families with fragile X syndrome. Seventeen
of these women fell into both ascertainment groups described
above. That is, they were identified through the fragile X survey
without knowledge of their reproductive history. In addition, they
were identified as mothers of participants. For Table 1, their demo-
graphic information is included in both groups.
The protocols and consent forms for each enrollment strategy were
approved by the Institutional Review Board at Emory University.
We administered the reproductive history questionnaire in person,
over the telephone or through the mail. We obtained demographic
information including age at interview, date of birth, ethnic/racial
group and education. Information on potential confounders and
effect modifiers was collected and included smoking (1, ever
smoked on a regular basis; 0, otherwise) and hormone use (1,
current hormone use; 0, otherwise).
We obtained menstrual cycle history including age at menarche and
age and date of last menstrual period. If the date of last menstrual
period was more than 2 months prior to the interview, we identified
the cause of menses cessation. We were unable to further assess repro-
ductive traits using hormone levels or ultrasound due to limited
Women completed a pregnancy history, noting dates and outcomes
of each pregnancy. We asked specific questions concerning fertility
problems along with number of months of unprotected intercourse
Lastly, women completed a brief medical history concerning dis-
orders associated with ovarian dysfunction and co-morbid disorders
related to reproductive aging. Although all questions were started
with ‘Has a doctor ever told you that you had...?’, all conditions
were based on self-report. Medical records were not obtained to
verify fertility problems or medical disorders.
To determine if the method of administration (in person, over the
telephone or through the mail) was related to outcome measures, we
determined whether age at menarche or age at menopause was associ-
ated with administration method. There was no association and, there-
fore, we present analyses combining data collected by these three
Study population characteristics
The clinical definition of a premutation allele is defined as 55–199
repeats (Sherman et al., 2005); however, there is no biological foun-
dation for the lower end of this range. We chose to categorize
repeat size based on their potential risk for expansion to the full
mutation. We hypothesize that the property leading to expansion
(e.g. chromatin structure, secondary structure of the repeat sequence)
Allen et al.
Page 2 of 11
by guest on June 2, 2013
Table 1: Demographic characteristics of study populations grouped by ascertainment according to known reproductive success
CharacteristicGroup 1: women identified without knowledge of reproductive historyGroup 2: women identified through a child (known reproductive success)
Non-carriersPremutation carriers Non-carriers Premutation carriers
N of women ,40 years at age of
N of women ?40 years at age of
Age at interview Mean+SD
22383 27 36203 741146 17
140 128 467111 154 15250 7923
Ever smoked (%) 28.9 38.431.5 43.9 35.541.4 39.839.340.0 40.0
Body mass index Mean+SD26.9+7.327.6+6.627.8+6.027.9+7.326.1+5.227.5+6.526.7+5.927.7+4.826.5+5.9 25.8+7.2
Education: completed college or
Current hormone use (%)34.734.1 43.8 25.2 41.939.538.9 39.531.1 45.6
Age at first pregnancy Mean+SD (N)24.2+5.2
Women who were ascertained through both Groups (n ¼ 17, see text) are included twice.
FMR1 premutation and reproductive aging
Page 3 of 11
by guest on June 2, 2013 http://humrep.oxfordjournals.org/ Downloaded from
may be involved in the mechanism leading to the risk for ovarian dys-
function. Thus, we defined premutation carriers as those with ?59
repeats based on the observation that alleles in that range can
expand to the full mutation in one generation (Nolin et al., 2003).
Women with ,59 repeats were designated as non-carriers. We cate-
gorized premutation carriers further by the following categories: low
(59–79 repeats), mid (80–100 repeats) and high premutation alleles
(.100 repeats), these categories being associated with low
(.50%), mid (50%–80%) and high risk (.95%) to expand to the
full mutation (Nolin et al., 2003). We collapsed women who had
alleles with 41–58 repeats (so called intermediate alleles) with non-
carriers, because we did not find evidence for an association of inter-
mediate alleles with increased rates of ovarian dysfunction (Sullivan
et al., 2005).
Table 1 provides a comparison of the general characteristics of
repeat size groups by ascertainment: (i) participants ascertained
without knowledge of reproductive success (Group 1) and (ii) those
ascertained through offspring (Group 2). Age at interview differed
by ascertainment method as well as by repeat size group (P ,
0.0001). Also, non-carriers and carriers differed significantly with
respect to race/ethnicity (P , 0.0001). The former represent the
ethnic/racial group profile of Metropolitan Atlanta, whereas the pre-
mutation group reflects our fragile X clinic population.
The goal of this project was to compare reproductive milestones
among women grouped by their FMR1 repeat size using data obtained
through retrospective questionnaires. ‘Age’ was defined relative to the
particular characteristic analyzed. Age at interview was used in the
fertility analysis, because we did not have an age at the diagnosis of
infertility. The age at the time of each pregnancy was used in analyses
concerning pregnancy outcomes (i.e. time to first pregnancy, twinning
and spontaneous abortion rates). For the menstrual cycle analyses,
women were asked to describe their cycle traits during the last year
that they were cycling naturally and their age at that time was calcu-
lated accordingly. Therefore, women who were cycling at the time of
the interview were asked to describe their cycle characteristics during
the year prior to the interview (n ¼ 470) and their age was the age
at interview. Women who had gone through menopause (defined as
cessation of menses for at least 12 months) were asked to describe
their cycle characteristic during the last year before cessation of
menses (n ¼ 206). Women who were still cycling but on hormone
medications were asked to describe the year before they went on
hormone medications (n ¼ 283).
We first determined whether the continuous menstrual cycle traits
were normally distributed. Age at menarche was normally distributed;
however, self-reported average cycle length and bleed length were not.
Furthermore, self-reported cycle length showed digit preference; e.g.
women more often reported 28 or 30-day cycles than 29-day cycles.
Thus, we categorized cycle and bleed length based on the top and
bottom quartiles of our distribution: .29 days and ,27 days for
cycle length; .6 days and ,5 days for bleed length.
Two questions were utilized to examine cycle regularity. First, we
asked if the woman had regular or irregular cycles in the last year
that she was naturally cycling. We defined regular as meaning that
‘most cycles were about the same length, plus or minus 2 days’.
Next, we asked if the woman ever went 6 weeks or more without a
menstrual period. Both were scored as binary variables.
Several questions were used to assess fertility problems. Each woman
reported whether she ever visited a doctor, clinic or hospital, because
she could not get pregnant. In addition, she reported whether she had
ever had unprotected intercourse for a year or more without getting
pregnant. Finally, each woman reported the number of months of
unprotected intercourse that it took to achieve her first pregnancy.
For the latter variable, only women who achieved pregnancy were
included in the analysis. Time to first pregnancy was dichotomized
based on the top quartile of the distribution, i.e. greater than 8 months.
We were primarily interested in the percentage of spontaneous abor-
tion and the percentage of dizygotic twinning, as both traits are
known to increase with increasing maternal age (for review, see Niko-
laou and Templeton, 2004). We did not compare the average number
of pregnancies, as this measure may differ between premutation and
non-carriers for other reasons than infertility. For example, premuta-
tion carriers may limit their family size due to the risk of having an
offspring with fragile X syndrome.
Additional risk factors for ovarian failure
Women self-reported diagnoses of Lupus, diabetes and/or Graves’
disease. Each was considered as an outcome variable and was tested
in a model with repeat size group, age at interview, smoking and
ethnic/racial group. The effect of smoking on age at menopause
was also investigated (see Statistical analysis below).
Co-morbid medical conditions
Women self-reported diagnoses of osteoporosis and estrogen-related
cancers. Each was considered as an outcome variable and tested in a
model with repeat size group, age at interview, smoking and ethnic/
DNA was extracted from buccal samples or blood using Qiagen
QiAmp DNA Blood Mini Kit. FMR1 CGG repeat sizes were deter-
mined by a fluorescent-sequencer method, as described elsewhere
(Meadows et al., 1996), using the ABI Prism 377 DNA Sequencer.
For females with only one allele, a second PCR-based, hybridization
technique was used to identify a possible high band. The protocol is
a modified version of that developed by Brown et al. (1993). For
females, if no high repeat allele was identified using this follow-up
method, we concluded that the woman was homozygous for the
We examined the age-specific prevalence of POF for women with low,
mid and high repeat size groups, as defined above. We calculated the
prevalence of POF prior to age 15, 20, 25, 30, 35 and 40. For this analy-
sis, we included in the denominator all women who entered the interval
still naturally cycling or had stopped cycling for at least a year prior to
that interval. The numerator included women who had self-reported
menopause at the specified age or earlier. We excluded from the analy-
sis all women who had chemotherapy or radiation therapy, a hyster-
ectomy or eating disorder. We also used survival analysis to
determine the average age at menopause for each group. Hazard
for age at interview, racial/ethnic group and smoking. In addition, we
used the same model in frailty analysis to adjust for the dependency
of related individuals. We report the P-values based on frailty analysis.
Allen et al.
Page 4 of 11
by guest on June 2, 2013
To account for the potential dependency among women ascertained
from the same family, we used generalized-estimating-equation
(GEE) methodology (Zeger and Liang, 1986) to determine whether
repeat size had an effect on reproductive outcomes. For all analyses,
we tested for the potential confounding effects of ethnic/racial
group, the appropriate age variable and smoking, an exposure
known to affect age at menopause (Cooper et al., 1999). If the variable
changed the odds ratio of the repeat size variable by more than 10%,
we included these covariates in the model.
Lastly, we examined the effect of smoking on age at menopause
among premutation carriers to determine if the effect of this endocrine
disruptor was additive or multiplicative (i.e. synergistic). We used the
binary variable of ‘ever smoked regularly’ in the presentation of the
survival curves for premutation and non-carriers. We used frailty
analysis conditioning on family membership to test for significance
where age at menopause was defined as the failure event and age at
interview was defined as the censored event. Covariates included pre-
mutation group, race/ethnicity and age at interview. The interaction
term of smoking status and premutation status was used to examine
a synergistic effect.
We present odds ratios for premutation repeat size groups adjusted
for confounders and 95% confidence interval using non-carriers as the
referent group for each analysis. The authors of this manuscript had
thorough discussions regarding an appropriate correction for multiple
testing within our analyses. A typical multiple-testing correction is
a Bonferroni correction that divides the nominal significance level
(here alpha ¼ 0.05) by the number of tests performed. However, by
using a Bonferroni correction, one implicitly assumes that all tests per-
formed are independent. This assumption is clearly violated in our
analyses, because our tested outcomes are functions of ovarian
aging and are therefore strongly correlated. Application of a Bonfer-
roni correction here would, therefore, lead to conservative inference
(since the effective number of independent tests will be much less
than the number of tests performed), which is unappealing. Therefore,
in efforts to provide a practical solution to the multiple-testing issue,
we adjusted for independent testing of the five main categories of out-
comes (cycle characteristics, fertility, pregnancy outcomes, auto-
reproductive aging). This adjustment, coupled with the fact that all
tests are one sided, led to the conclusion that a nominal level of
approximately alpha ¼ 0.01 is suitable for declaring the significance
of a particular result. Such significant results in our manuscript are
in bold type. All statistical analyses were done using SAS V9 and R.
Age-related prevalence of POF
In previous work, we (Sullivan et al., 2005) and others (Ennis
et al., 2006) found that repeat size was associated with age of
menopause in a non-linear manner: the highest risk for ovarian
dysfunction (defined by both prevalence of POF and age at
menopause) occurred among carriers with mid-range of
repeats (?80–100 repeats). To further examine this associ-
ation, we compared the age-specific prevalence curve for POF
for non-carriers and premutation carriers with low (59–79
repeats), mid (80–100 repeats) and high premutation alleles
(.100 repeats) (Fig. 1). We found the same pattern: women
with the mid-range repeats had a higher frequency of POF
and, moreover, an earlier onset, on average, compared with
definition of POF, the odds ratios for each premutation group
compared with non-carriers are: 3.08 (0.89–10.65), 12.57
(5.27–29.98) and 6.77 (1.86–24.69).
Using survival analysis, the unadjusted mean age at meno-
pause for the four groups were 52.3+0.5, 48.5+0.7,
44.9+0.6 and 47.5+1.2, respectively. In a Cox proportional
hazards model adjusting for age at interview, racial/ethnic
group and smoking, all three premutation groups were signifi-
cantly different from controls [HR ¼ 2.22 (1.5123.26), 5.02
(3.5227.16) and 2.94 (1.6925.11), respectively; P , 0.0001
based on frailty models].
Reproductive aging milestones
Menstrual cycle characteristics
The mean+SD age of menarche for controls, low, mid and
high premutation groups were 12.44+1.51 (n ¼ 521),
12.18+1.38 (n ¼ 127), 12.35+1.57 (n ¼ 237) and 12.53+
1.33 (n ¼ 70), respectively. The difference in age of menarche
for women with 59–79 repeats (low premutation) was signifi-
cantly different from that of non-carriers (P ¼ 0.01) when
adjusted for ethnic/racial group and age at interview.
Low- and mid-premutation carriers were more likely to report
trolling for ethnic/racial group (P ¼ 0.01 and P , 0.001,
respectively; Table 2). To determine if premutation carriers dif-
fered from non-carriers at both ends of the spectrum of cycle
length (shorter or longer), we compared women with short
cycles to those with middle 50% and compared those with
long cycles (.29 days) to those with the middle 50% of the dis-
tribution. There was no association of premutation carriers with
long cycles, only with the short cycles (data not shown). There
was no association between bleed length and repeat size.
Onset of cycle irregularity is another distinctive reproductive
aging milestone that usually follows shortened cycles. Women
with mid-size premutation repeats were more likely to report
irregular cycles (Table 2; OR ¼ 1.49; 95% CI ¼ 1.04–2.14;
P ¼ 0.03).
The next cycle trait in the reproductive timeline is skipped
cycles, eventually leading to cessation of cycles. Women
with low- and mid-size premutations were more likely to
have gone 6 weeks or more without a menstrual period
(OR ¼ 1.66; 95% CI ¼ 1.04–2.66; P ¼ 0.03 and OR ¼ 1.80;
95% CI ¼ 1.25–2.58; P ¼ 0.001, respectively).
To ensure that results were robust against recall bias, we
stratified the sample into two groups: those who were currently
cycling when they reported their cycle characteristics and those
who had gone through menopause and reported cycle traits in
the last year before that event. We did not include women
who were currently on hormones at the time of the interview
as this group is more heterogeneous with respect to their repro-
ductive stage. The pattern among mid-premutation women
showing shortened cycles, irregular cycles and skipped
cycles was similar in menopausal and currently cycling
women, although the odds ratio was only significant among
menopausal women (data not shown).
Loss of fertility
We assessed fertility with three measures: having unprotected
intercourse for a year or more without becoming pregnant,
FMR1 premutation and reproductive aging
Page 5 of 11
by guest on June 2, 2013
having consulted a health care provider because of difficulty
becoming pregnant and among women who became pregnant,
the number of months of unprotected intercourse before
becoming pregnant (i.e. ‘time to pregnancy’). By each
measure, the results from mid-repeat range premutation car-
riers indicated that they had lower fertility than the non-carriers
or the other permutation carrier groups (Table 2). This differ-
ence was most apparent for consultation with a medical pro-
fessional (OR ¼ 1.27;
compared with non-carriers). When we excluded women
with known reproductive success (Group 2), the pattern of
odds ratios was similar to that estimated from the entire
study sample (data not shown).
95% CI ¼ 1.17–2.59;P ¼ 0.006,
Pregnancy outcomes associated with reproductive aging
We found a significant increase in the rate of DZ twinning
among premutation carriers with 80–100 repeats compared
with non-carriers (P ¼ 0.02; Table 2) after adjusting for age
of the mother at the time of the birth. The DZ twinning rate
was also increased for high-repeat carriers but was not statisti-
cally different from non-carriers.
We used spontaneous abortion rates as an indicator of oocyte
quality. There were no statistical differences among groups,
although the rate among the mid-size repeat group of premuta-
tion carriers was increased compared with non-carriers (P ¼
Page 6 of 11
0.16; Table 2). For each pregnancy, the woman was asked to
self-report any associated birth defects. We were particularly
interested in those that may indicate a birth defect resulting
from chromosome non-disjunction. Out of 2140 pregnancies,
only two were reported to involve an extra chromosome.
Both women were premutation carriers (65 and 105 CGG
repeats) and both were age 28 at the time of their baby’s birth.
Additional risk factors that may enhance ovarian failure
We examined two risk factors that are known to be associated
with ovarian dysfunction, autoimmune disorders and smoking.
These factors may exacerbate the effect of the premutation.
In the structured questionnaire, we asked if women had been
diagnosed with Lupus, diabetes and/or Graves disease. There
was no association of Lupus, diabetes or Graves’ disease
with any of the repeat size groups (Table 3).
In contrast, we found that smoking reduced age at meno-
pause among both premutation groups and non-carriers for
smokers. Unadjusted survival curves indicated an additive
effect of smoking on age at menopause (Fig. 2). Formally,
the interaction term was not significant (data not shown).
Table 4 shows the adjusted hazard ratios for carrier status
and smoking. When heavy smoking (defined as ?10 pack
years) was used, the same patterns were seen (data not shown).
Figure 1: Age-specific prevalence of POF by repeat size group
Allen et al.
by guest on June 2, 2013
Co-morbid medical conditions associated with
Estrogen-deficiency is associated with reproductive aging and
can lead to co-morbid conditions. For example, osteoporosis
increases with increasing exposure to estrogen deficiency
while breast and ovarian cancer decrease with earlier exposure
to estrogen-deficiency. Among premutation carriers, women
with mid-range repeats reported a significantly increased fre-
quency of osteoporosis (Table 3). When only women who
had gone through menopause were analyzed, the same
pattern was seen with mid-range repeats having the greatest
OR, although the difference was no longer statistically signifi-
cant. Our sample size was too small to evaluate the frequency
of women with estrogen-related cancers (Table 3).
POF was the first premutation-associated disorder identified in
families with fragile X syndrome (for review, see Sherman
et al., 2007). To identify factors that explain the reduced pene-
trance of POF, we established a cross-sectional study of premu-
tation carriers and non-carriers. In the study by Sullivan et al.
(2005), we first confirmed previous findings that premutation
carriers have an increased risk of ovarian insufficiency: they
have at least a 13-fold higher frequency of POF and a 5-year
earlier age at menopause (by any definition of menopause)
compared with non-carriers. Most importantly, the data
from Sullivan et al. gave us our first hint that repeat size was
strongly associated with ovarian insufficiency, albeit in a
non-linear way: the risk for ovarian dysfunction (defined by
both prevalence of POF and age at menopause) was highest
for mid-range carriers with repeats of ?80–99. These data
were recently confirmed by Ennis et al. (2006). In this
report, we have now followed up this finding in our updated
sample of948 womenand
repeat association with important measures of reproductive
aging as well as the prevalence of POF and age at
With respect to the clinical disorder defined as POF, we
found that the mid-size repeat group has the highest risk and
the earliest onset compared with other repeat groups (Fig. 1).
The prevalence of POF among low repeat and high repeat car-
riers is also increased compared with non-carriers, but not to
the same extent. Of course, this pattern depends on our a
priori definition of repeat size groups. Upon closer examin-
ation of POF within the low repeat premutation group, there
are 0/17 women who have 59–70 repeats with POF and
5/22 of women with 71–79 repeats report POF. Similarly,
among women in the high repeat group, 4/12 women with
101–120 repeats reported POF and 0/3 women with .120
repeats reported POF. Although the sample size in some of
these categories is small, this post hoc analysis suggests that
at-risk alleles may be better defined as those between 70 and
120 repeats. The upper end of this range is less precise than
the lower end due to technical difficulties of accurately defining
repeat sizes in the high range. Nevertheless, the mid-size repeat
alleles exert the greatest risk for POF. This is also evident
based on the mean age at menopause: mid-range repeat size
alleles impose a significant 7-year reduction in the overall
mean age at menopause.
Table 2: Comparison of reproductive aging milestones by repeat size group
Reproductive TraitNon-carriers Premutation carriers
Low (59–79 repeats)Mid (80–100 repeats) High (.100 repeats)
Short cycles (,27 days)a
Irregular cycles (+2 days)a
Skipped cycles (.6 weeks)a
Short bleed length(,5 days)a
1.79 (1.15–2.78) 33.7 (205)
0.92 (0.60–1.42) 35.2 (216)
1.66 (1.04–2.66) 36.6 (216)
1.34 (0.84–2.12) 31.5 (216)
1.94 (1.34–2.82) 22.2 (63)
1.49 (1.04–2.14) 22.4 (67)
1.80 (1.26–2.58) 28.4 (67)
1.21 (0.83–1.77) 28.4 (67)
.1 year of intercourse and not
Visit a doctor for fertility problemsc
Time to first pregnancy (.8 months)d
30.6 (519)–33.1 (127) 1.08 (0.68–1.70) 34.7 (236)1.27 (0.91–1.75) 21.1 (71) 0.69 (0.39–1.24)
1.22 (0.72–2.07) 19.7 (234)
0.90 (0.50–1.61) 20.5 (205)
1.09 (0.68–1.74) 15.0 (60)
9.9 (71)0.86 (0.39–1.88)
0.75 (0.41–1.37) 13.9 (603e) 1.32 (0.90–1.93) 11.2 (152e) 1.10 (0.58–2.06)
0.90 (0.19–4.35) 2.5 (437f) 2.89 (1.19–6.99) 1.7 (118f) 1.74 (0.34–8.85)
Bold signifies that the repeat size group was significantly different from the referent group (non-carriers) at P ? 0.01. Odds ratios were adjusted for the
covariates listed in the footnotes. All analyses were done using GEE methodology to adjust for the potential dependency among women ascertained from the
aAdjusted for racial/ethnic group.
bAdjusted for racial/ethnic group and age at interview.
cAdjusted for age at interview.
dAdjusted for age of mother at the time of pregnancy.
eNumber of pregnancies.
fNumber of live births.
FMR1 premutation and reproductive aging
Page 7 of 11
by guest on June 2, 2013
The increase frequency of POF and the overall reduction in
age at menopause may be due to either a smaller ovarian
reserve established during the development of oocytes or to an
increased rate of follicular atresia. If true, premutation carriers
carriers. They should experience menstrual cycle alterations,
subfertility, increased rates of DZ twinning, increased incidence
of aneuploidy and spontaneous abortion (reviewed in Te Velde
and Pearson, 2002). Moreover, women with repeat sizes in the
mid range should show these traits more frequently based on
the above observations. To test this hypothesis, we measured
the frequency of such milestones during the last year of natural
cycling in a woman’s reproductive life.
We found that premutation carriers and, most significantly,
mid-size repeat premutation carriers reported menstrual cycle
alterations (short, irregular and skipped cycles) more often
than non-carriers. These alterations were perhaps indicators
of subfertility: only the mid-size group with earlier onset of
POF, the 7-year reduction of age at menopause and altered
cycle characteristics had significant infertility problems. We
also found that DZ twinning was increased among the
mid-size repeat group, perhaps indicating reduced ovarian
feedback to the increased secretion of pituitary gonadotrophic
hormone (for review, see Lambalk et al., 1998). Interestingly,
studies in the past have been inconsistent with respect to
observing an increased rate of DZ twinning among premutation
carriers; some finding a significant increase (Fryns, 1986;
Turner et al., 1994; Vianna-Morgante, 1999), whereas others
did not (Sherman et al., 1996; Murray et al., 2000; Hundscheid
et al., 2003). We suggest that the inconsistent data are due
to the difference in the study population with respect to
We did not find an increased rate of spontaneous abortions
among premutation carriers. The finding is consistent with
other studies of premutation-associated ovarian dysfunction
(Murray et al., 2000; Hundscheid et al., 2003). An increased
rate of spontaneous abortion is strongly associated with
maternal aging and primarily the result of chromosome non-
disjunction. Although rate of spontaneous abortion is only a
crude surrogate for rate of non-disjunction, the lack of an
association among premutation carriers suggests that the
quality of the oocyte is not compromised.
Applications to the clinical realm
Many surveys have been conducted to determine the frequency
of premutation carriers among women with idiopathic POF.
Table 3: Examination of disorders associated with POF and/or reproductive aging among repeat size groups
DisorderNon-carriers Premutation carriers
Low (59–79 repeats) Mid (80–100 repeats)High (.100 repeats)
Crude % (N) Referent groupCrude % (N)OR (95% CI)Crude % (N) OR (95% CI)Crude % (N) OR (95% CI)
Co-morbid medical conditions associated with reproductive aging
Ovarian cancer 0.6 (520)
0.91 (0.55–1.52)0.73 (0.45–1.19) 0.97 (0.41–2.27)
Odds ratios compare the frequency of the disorder in the carrier group to non-carriers adjusted for confounders indicated in footnotes. Odds ratios in bold
indicate a significant difference from non-carriers at P ? 0.01.
aAdjusted for age at interview.
bAdjusted for age at interview and ethnic/racial group.
cAdjusted for age at interview and menopause status.
dAdjusted for age at interview and smoking status.
Figure 2: Survival curves comparing all premutation carriers to
non-carriers by smoking status
Table 4: Effect of repeat size and smoking on age at menopause
(from frailty model)
Hazard ratios are adjusted for ethnic/racial group and age at interview.
Allen et al.
Page 8 of 11
by guest on June 2, 2013
Since the original survey by Conway et al. (1995) that showed
an increased frequency of premutation carriers among POF
women, others have examined various series of women with
POF ascertained through infertility clinics, obstetrics and gyne-
cology clinics, genetic laboratories and general surveys (for
review, see Sherman et al., 2007). Using studies that identified
women primarily through a reproductive endocrinology clinic
and that clearly distinguished familial from sporadic POF
(Murray et al., 1998; Marozzi et al., 2000; Mallolas et al.,
2001; Bussani et al., 2004), the estimated percentage of
women who are premutation carriers is 11.5% (familial POF)
and 3.2% (sporadic POF). Based on the data presented here,
we predict that the majority of women identified in such
clinics would have mid-size repeat alleles. Such repeats have
a high risk to expand to the full mutation when transmitted
from the mother to her offspring. Importantly, only a subset
of premutation carriers experience fertility loss. Any environ-
mental exposure that reduces age at menopause can lead to
increased subfertility in this group of women who are at risk
for a shortened reproductive lifespan.
Smoking is a well-known endocrine disruptor and leads to
decreased age at menopause (Cooper et al., 1999). We hypo-
thesized that smoking may significantly reduce the age at
menopause among premutation carriers and, potentially, have
a synergistic effect. Although we did not see a synergistic
effect, smoking reduced age at menopause by 1 year, a signifi-
cant reduction if a woman’s reproductive years are already
Earlier menopause leads to an earlier deficiency in estrogen,
which is associated with several other co-morbid conditions.
First, all premutation carriers showed an increase in risk for
osteoporosis, and for mid-premutation carriers, this increase
was significant. Although the numbers are very small, premu-
tation carriers also show a lower frequency of breast and
Implications for molecular etiology
We have confirmed the non-linear association of premutation
allele size and risk for ovarian insufficiency as measured by
early cessation of menses as well as other reproductive aging
milestones. Thus, any hypothesis proposed to explain the mole-
cular etiology of the premutation-associated disorder must be
put into this context.
There are at least two possible mechanisms that could be
proposed. First, we hypothesize that the premutation effect
occurs during the prenatal development of the oocyte pool,
reducing their numbers in the store. Expression studies indicate
that FMRP may be important at this stage, since it is highly
expressed in the germ cells of the fetal ovary (Bachner et al.,
1993; Rife et al., 2004). We know that FMRP regulates trans-
lation of a subset of mRNAs through a suppression mechanism
(Jin et al., 2004). Perhaps, increased levels of FMRP at specific
times during development can lead to haploinsufficiency of
the proteins needed in oocyte development. Analyses of
X chromosome alterations identified in women with POF
provide support for this model (Bione et al., 2004; Rossetti
et al., 2004; Rizzolio et al., 2006). As Rizzolio et al. (2006)
have shown that the most plausible explanation for POF
identified in women with balanced X-autosome translocations
is a position effect of the breakpoints on flanking genes,
causing them to be either silenced or down-regulated. In
order to fit the non-linear association between severity of
ovarian insufficiency and repeat size, we propose that trans-
lation inefficiency of FMRP is restricted to alleles with
.?100 repeats. Below that repeat length, increasing mRNA
levels produce higher FMRP levels, leading to haploinsuffi-
ciency of FMRP-suppressed transcripts. Model systems
provide some suggestions for candidate genes that may interact
with FMRP. For example, in Drosophila, two genes involved in
oogenesis have been shown to be associated with dFmr1: lgl
and FMRP proteins form a complex in both flies and mice
(Zarnescu et al., 2005). Orb is negatively regulated by dFmr1
(Costa et al., 2005). In a saturating screen with dfmr1, Zarnescu
et al. (2005) also identified two genes that have been linked to
POF, diaphanous and dachshund.
Alternatively, we hypothesize that the large repeat track in
the mRNA produced by the premutation allele causes a toxic
effect over time, leading to an increased rate of follicular
atresia later in a woman’s reproductive life. This dominant
gain-of-function mechanism is well supported for the other
known premutation-associated disorder, FXTAS (Hagerman
and Hagerman, 2002; Jin et al., 2003; Willemsen et al.,
2003). FMR1 expression studies identified transcripts in gran-
ulosa cells of ovarian follicles (Hinds et al., 1993; Hergersberg
et al., 1995). Interestingly, transcripts were present in maturing
follicles only, not those in the early stages (Hergersberg et al.,
1995). One study did fail to identify expression in the older
ovary of a 28-week-old mouse, but that may have been due
to the lack of maturing follicles (Bachner et al., 1993). To
explain the non-linear association of repeat size, we posit
that rCGG repeats take on a different conformation or behavior
when above 100 repeats (Sullivan et al., 2005).
Although we suggested time points for these particular mech-
anisms, they could have their impact at other stages of develop-
ment. Nevertheless, these suggested mechanisms can be used as
a platform for asking specific questions. If the ovarian pool is
indeed diminished during fetal development, we expect that
reproductive aging milestones will occur at the same fixed inter-
vals relative to the start of menopause, but they willoccurearlier
than in non-carriers (Fig. 3). Also, we would expect to observe
diminished ovarian reserve compared with non-carriers at all
ages. Alternatively, if the premutation effect is due to an
accumulation of toxic mRNA, as is the case in FXTAS, we
expect that the interval between the typical reproductive aging
milestones and menopause may be reduced (Fig. 3). Moreover,
we expect that young premutation carriers should have measures
of ovarian reserve that are similar to controls.
This analysis was based on the largest number of premutation
carriers and non-carrier controls collected to date. However,
the data are limited in that they are based on self-report
through a structured questionnaire. Also, not all women were
ascertained at the same time in their reproductive lifespan.
Thus, some reported characteristics of their cycle traits that
were occurring at the time of interview, whereas others were
FMR1 premutation and reproductive aging
Page 9 of 11
by guest on June 2, 2013
reporting on those in the past. Resources were not available to
assess cycle or fertility traits using more sophisticated
measures such as ultrasound imaging or hormone levels.
Lastly, we were unable to abstract medical records to corrobo-
rate medical diagnoses. These limitations were not restricted to
any one repeat size group. Thus, the ‘noise’ or misclassification
will bias results toward the null hypothesis, i.e. it will reduce or
dampen observed differences between the groups.
In conclusion, we have confirmed the non-linear association of
repeat size and ovarian insufficiency: carriers with 80–99
repeats compared with non-carriers have increased rates of
menstrual dysfunction, infertility and dizygotic twinning.
They also have a 7-year reduction in mean age at menopause,
and consequently, an increased prevalence of POF (32% versus
1%) and an increased risk of osteoporosis. Carriers of both
smaller and larger premutation repeat sizes also suffer from
ovarian insufficiency, but not to as great an extent.
Although repeat size can account for much of the variation in
the severity of ovarian insufficiency, most likely other genetic
factors as well as the environment also plays a role. Thus in the
clinical setting, modifiable risk factors such as environmental
exposures (e.g. smoking) should be identified and addressed.
Also, patient education for premutation carriers should be pro-
vided not only on reproductive issues, but also their increased
risk for co-morbidities associated with reproductive aging,
such as osteoporosis.
We would like to thank Johnnie Brown, Mary Leslie, Gloria Novak,
Elizabeth Scott and Lisa Shubeck for their tremendous efforts in
enrollment of participants in this project. We would also like to that
the volunteers and their families whose participation made the work
possible. This work was supported by National Institutes of Health
grants NIH RO1 HD29 909, NIH PO1 HD35 576 and NIH/NCRR
MO1 RR00 039.
Ashley CT, Jr, Wilkinson KD, Reines D, Warren ST. FMR1 protein: conserved
RNP family domains and selective RNA binding. Science 1993;262:563–566.
Bachner D, Manca A, Steinbach P, Wohrle D, Just W, Vogel W, Hameister H,
Poustka A. Enhanced expression of the murine FMR1 gene during germ cell
proliferation suggests a special function in both the male and the female
gonad. Hum Mol Genet 1993;2:2043–2050.
Bione S, Rizzolio F, Sala C, Ricotti R, Goegan M, Manzini MC, Battaglia R,
Marozzi A, Vegetti W, Dalpra L et al. Mutation analysis of two candidate
genes for premature ovarian failure, DACH2 and POF1B. Hum Reprod
Brown WT, Houck GE Jr, Jeziorowska A, Levinson FN, Ding X, Dobkin C,
Zhong N, Henderson J, Brooks SS, Jenkins EC. Rapid fragile X carrier
screening and prenatal diagnosis using a nonradioactive PCR test. JAMA
Bussani C, Papi L, Sestini R, Baldinotti F, Bucciantini S, Bruni V, Scarselli G.
Premature ovarian failure and fragile X premutation: a study on 45 women.
Eur J Obstet Gynecol Reprod Biol 2004;112:189–191.
Conway GS, Hettiarachchi S, Murray A, Jacobs PA. Fragile X premutations in
familial premature ovarian failure. Lancet 1995;346:309–310.
Cooper GS, Sandler DP, Bohlig M. Active and passive smoking and the
occurrence of natural menopause. Epidemiology 1999;10:771–773.
Costa A, Wang Y, Dockendorff TC, Erdjument-Bromage H, Tempst P, Schedl
P, Jongens TA. The Drosophila fragile X protein functions as a negative
regulator in the orb autoregulatory pathway. Dev Cell 2005;8:331–342.
Crawford DC, Acuna JM, Sherman SL. FMR1 and the fragile X syndrome:
human genome epidemiology review. Genet Med 2001;3:359–371.
Den Tonkelaar I, Te Velde ER, Looman CW. Menstrual cycle length preceding
menopause in relation to age at menopause. Maturitas 1998;29:115–123.
Ennis S, Ward D, Murray A. Nonlinear association between CGG repeat
number and age of menopause in FMR1 premutation carriers. Eur J Hum
Fryns JP. The female and the fragile X. A study of 144 obligate female carriers.
Am J Med Genet 1986;23:157–169.
Hagerman RJ, Hagerman PJ. The fragile X premutation: into the phenotypic
fold. Curr Opin Genet Dev 2002;12:278–283.
Hergersberg M, Matsuo K, Gassmann M, Schaffner W, Luscher B, Rulicke T,
Aguzzi A. Tissue-specific expression of a FMR1/beta-galactosidase fusion
gene in transgenic mice. Hum Mol Genet 1995;4:359–366.
Hinds HL, Ashley CT, Sutcliffe JS, Nelson DL, Warren ST, Housman DE,
Schalling M. Tissue specific expression of FMR-1 provides evidence for a
functional role in fragile X syndrome. Nat Genet 1993;3:36–43.
Hundscheid RD, Sistermans EA, Thomas CM, Braat DD, Straatman H,
Kiemeney LA, Oostra BA, Smits AP. Imprinting effect in premature
ovarian failure confined to paternally inherited fragile X premutations. Am
J Hum Genet 2000;66:413–418.
Figure 3: Hypotheses for loss of ovarian function among premutation carriers based on number of oocytes and reproductive stages
Allen et al.
Page 10 of 11
by guest on June 2, 2013
Hundscheid RD, Braat DD, Kiemeney LA, Smits AP, Thomas CM. Increased Download full-text
serum FSH in female fragile X premutation carriers with either regular
menstrual cycles or on oral contraceptives. Hum Reprod 2001;16:457–462.
of fragile X premutations have no increased risk for additional diseases other
than premature ovarian failure. Am J Med Genet 2003;117A:6–9.
Jin P, Zarnescu DC, Zhang F, Pearson CE, Lucchesi JC, Moses K, Warren ST.
RNA-mediated neurodegeneration caused by the fragile X premutation
rCGG repeats in Drosophila. Neuron 2003;39:739–747.
Jin P, Alisch RS, Warren ST. RNA and microRNAs in fragile X mental
retardation. Nat Cell Biol 2004;6:1048–1053.
Kok HS, Van Asselt KM, Van Der Schouw YT, Grobbee DE, Te Velde ER,
Pearson PL, Peeters PH. Subfertility reflects accelerated ovarian ageing.
Hum Reprod 2003;18:644–648.
Lambalk CB, De Koning CH, Braat DD. The endocrinology of dizygotic
twinning in the human. Mol Cell Endocrinol 1998;145:97–102.
Mallolas J, Duran M, Sanchez A, Jimenez D, Castellvi-Bel S, Rife M, Mila M.
Implications of the FMR1 gene in menopause: study of 147 Spanish women.
Marozzi A, Vegetti W, Manfredini E, Tibiletti MG, Testa G, Crosignani PG,
Ginelli E, Meneveri R, Dalpra L. Association between idiopathic premature
ovarian failure and fragile X premutation. Hum Reprod 2000;15:197–202.
Meadows KL, Pettay D, Newman J, Hersey J, Ashley AE, Sherman SL. Survey
of the fragile X syndrome and the fragile X E syndrome in a special
education needs population. Am J Med Genet 1996;64:428–433.
Murray A, Webb J, Grimley S, Conway G, Jacobs P. Studies of FRAXA and
FRAXE in women with premature ovarian failure. J Med Genet
Murray A, Webb J, Macswiney F, Shipley EL, Morton NE, Conway GS. Serum
concentrations of follicle stimulating hormone may predict premature ovarian
failure in FRAXA premutation women. Hum Reprod 1999;14:1217–1218.
Murray A, Ennis S, Macswiney F, Webb J, Morton NE. Reproductive and
menstrual history of females with fragile X expansions. Eur J Hum Genet
Nikolaou D, Templeton A. Early ovarian ageing. Eur J Obstet Gynecol Reprod
Nolin SL, Brown WT, Glicksman A, Houck GE, Jr, Gargano AD, Sullivan A,
Biancalana V, Brondum-Nielsen K, Hjalgrim H, Holinski-Feder E et al.
Expansion of the fragile X CGG repeat in females with premutation or
intermediate alleles. Am J Hum Genet 2003;72:454–464.
Richardson SJ, Senikas V, Nelson JF. Follicular depletion during the
menopausal transition: evidence for accelerated loss and ultimate
exhaustion. J Clin Endocrinol Metab 1987;65:1231–1237.
Rife M, Nadal A, Mila M, Willemsen R. Immunohistochemical FMRP studies
in a full mutated female fetus. Am J Med Genet 2004;124A:129–132.
Rizzolio F, Bione S, Sala C, Goegan M, Gentile M, Gregato G, Rossi E,
Pramparo T, Zuffardi O, Toniolo D. Chromosomal rearrangements in Xq
and premature ovarian failure: mapping of 25 new cases and review of the
literature. Hum Reprod 2006;21:1477–1483.
Rossetti F, Rizzolio F, Pramparo T, Sala C, Bione S, Bernardi F, Goegan M,
Zuffardi O, Toniolo D. A susceptibility gene for premature ovarian failure
(POF) maps to proximal Xq28. Eur J Hum Genet 2004;12:829–834.
Sherman SL, Meadows KL, Ashley AE. Examination of factors that influence
the expansion of the fragile X mutation in a sample of conceptuses from
known carrier females. Am J Med Genet 1996;64:256–260.
Sherman S, Pletcher BA, Driscoll DA. Fragile X syndrome: diagnostic and
carrier testing. Genet Med 2005;7(8):584–587.
Sherman SL, Taylor K, Allen EG. FMR1 premutation: a leading cause of
inherited ovarian dysfunction. In: Arrieta I, Penagarikano O, Telez M
(eds). Fragile Sites: New Discoveries and Changing Perspectives. Nova
Science Publishers, 2007.
Sullivan AK, Marcus M, Epstein MP, Allen EG, Anido AE, Paquin JJ,
Yadav-Shah M, Sherman SL. Association of FMR1 repeat size with
ovarian dysfunction. Hum Reprod 2005;20:402–412.
Te Velde ER, Pearson PL. The variability of female reproductive ageing. Hum
Reprod Update 2002;8:141–154.
Turner G, Robinson H, Wake S, Martin N. Dizygous twinning and premature
menopause in fragile X syndrome. Lancet 1994;344:1500.
Vianna-Morgante AM. Twinning and premature ovarian failure in premutation
fragile X carriers. Am J Med Genet 1999;83:326.
Welt CK, Smith PC, Taylor AE. Evidence of early ovarian aging in fragile X
premutation carriers. J Clin Endocrinol Metab 2004;89:4569–4574.
Willemsen R, Hoogeveen-Westerveld M, Reis S, Holstege J, Severijnen LA,
Nieuwenhuizen IM, Schrier M, Van Unen L, Tassone F, Hoogeveen AT
et al. The FMR1 CGG repeat mouse displays ubiquitin-positive
intranuclear neuronal inclusions; implications for the cerebellar tremor/
ataxia syndrome. Hum Mol Genet 2003;12:949–959.
Zarnescu DC, Jin P, Betschinger J, Nakamoto M, Wang Y, Dockendorff TC,
Feng Y, Jongens TA, Sisson JC, Knoblich JA et al. Fragile X protein
functions with lgl and the par complex in flies and mice. Dev Cell
Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous
outcomes. Biometrics 1986;42:121–130.
Submitted on December 18, 2006; resubmitted on May 1, 2007; accepted on
May 8, 2007
FMR1 premutation and reproductive aging
Page 11 of 11
by guest on June 2, 2013