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Complex segregation analysis of restless legs syndrome provides evidence for an autosomal dominant mode of inheritance in early age at onset families.

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Complex Segregation Analysis of Restless
Legs Syndrome Provides Evidence for an
Autosomal Dominant Mode of Inheritance
in Early Age at Onset Families
Juliane Winkelmann, MD,1 Bertram Muller-Myhsok, MD,2 Hans-Ulrich Wittchen, PhD,3 Bettina Hock,1
Muriel Prager,1 Hildegard Pfister,3 Andreas Strohle, MD,4 Ilonka Eisensehr, MD,5 Martin Dichgans, MD,4
Thomas Gasser, MD,4 and Claudia Trenkwalder, MD1
A strong familial component of restless legs syndrome (RLS) is known. The objective of this study therefore was to
investigate the likely mode of inheritance of RLS. RLS patients and their first-degree relatives were investigated and
classified in RLS affected and RLS nonaffected subjects. Assessments were based on direct, personal standardized diagnostic interviews. Complex segregation analysis was performed with the families stratified according to the mean age at
onset of the disease within the families. Two hundred thirty-eight RLS patients, 537 first-degree relatives, and 133
spouses were interviewed. Two groups of families were stratified: mean age at onset up to 30 years of age (Group A) and
older than 30 years (Group B; p < 0.005). In Group A, segregation analysis strongly favored a single major gene acting
autosomal dominant with a multifactorial component. Parameter estimates were 0.003 for the allele frequency, 1.0 for
the penetrance, and 0.005 for the phenocopy rate. In Group B, no evidence for a major gene could be elucidated. The
segregation pattern found in our families argues for an autosomal allele acting dominantly in RLS families with an early
age at onset of symptoms and suggests that RLS is a causative heterogeneous disease.
Ann Neurol 2002;52:297–302
The restless legs syndrome (RLS) is characterized by
dysesthesias that usually are located in the lower limbs,
mainly the calves, and are associated with an irresistible
urge to move these limbs. Moving the affected leg or
walking leads to a temporary relief of the symptoms.
These occur predominantly at rest in the evening or at
night, interfering with sleep onset and disrupting
sleep.1–3 The diagnosis of the disease is based on the
clinical description of these symptoms by the patient.1
A recent population-based study reported a high
prevalence of 9.8% in individuals older than 65 years.4
A survey in the general population has confirmed this,
pointing to marked age effects ranging from 3% in individuals aged younger than 30 years to approximately
20% in those aged 80 years and older.5 Clinical surveys
of idiopathic RLS patients showed that up to 60%6 – 8
report a positive family history. Investigations of single
families with RLS have suggested an autosomal domi-
nant mode of inheritance9 –13 with variable expressivity.11–13 In addition, a younger age at onset was consistently found in familial compared with sporadic
cases.6 – 8,14,15
In a single French-Canadian family, evidence for
linkage of RLS to chromosome 12 recently has been
found.16 Interestingly, this finding was obtained using
an autosomal recessive model with very high allele frequency (q ⫽ 0.75), which is unlikely to be representative for RLS as a whole. The mode of inheritance in
RLS and related genetic parameters such as penetrance
and the rate of phenocopies are not yet known. An
accurate assumption of these parameters, however, is
an essential prerequisite for linkage studies. The objective of this study therefore was to investigate the likely
mode of inheritance of RLS by examining a clinical
population of RLS patients and their family members.
From the 1Section of Neurology, Max Planck Institute of Psychiatry, Munich; 2Bernhard Nocht Institute for Tropical Medicine,
Hamburg; Departments of 3Clinical Psychology and 4Psychiatry,
Max Planck Institute of Psychiatry; 5Department of Neurology,
Ludwig Maximilians University of Munich, Klinikum Grosshadern,
Munich, Germany.
Received Oct 22, 2001, and in revised form Mar 25, 2002. Accepted for publication Apr 20, 2002.
Current address for Dr Wittchen: Institute of Clinical Psychology
and Psychotherapy, Technical University of Dresden, Dresden, Germany.
Published online Jun 7, 2002, in Wiley InterScience
(www.interscience.wiley.com). DOI: 10.1002/ana.10282
Address correspondence to Dr Trenkwalder, Department of Clinical
Neurophysiology, Georg-August-Universität Göttingen, Robert-KochStr. 40, D-37075, Göttingen, Germany. E-mail: ctrenkw@gwdg.de
© 2002 Wiley-Liss, Inc.
297
Patients and Methods
Study Population
RLS, and no positive RLS family history information was
obtained for any relatives.
All inpatients and outpatients of the Movement Disorder
Unit at the Section of Neurology, Max Planck Institute of
Psychiatry, between January 1996 and March 1999 who received a diagnosis of idiopathic RLS2 were included in the
study as index patients. This sample was enriched by patients
of the Department of Neurology, Klinikum Grosshadern,
Ludwig Maximilian University, Munich who met the same
study criteria. We excluded secondary cases of RLS, except
for five uremic patients who had an onset of their RLS
symptoms before the onset of their dialysis treatment.
Study Design
All index patients were contacted by letter describing the aim
and design (see below) of the study. Patients were asked to
contact as many first-degree relatives (parents, siblings, children) as possible to participate in the study and were requested to send back a prepaid envelope containing a list of
all family members who had agreed to participate. We excluded family members younger than the age of 18 years.
One subject aged 12 years was included as an exception because she presented as an index patient. Written consent was
obtained from all subjects (Ludwig Maximilians University,
ref. no. 97/99).
Diagnostic Interview
All subjects (index patients, spouses, and first-degree relatives) were contacted by telephone and assessed by means of
a direct standardized computer-assisted personal interview
using the Composite International Diagnostic Interview17 as
a model. The subjects were randomly assigned to interviewers. In each family, the index patient was interviewed first, a
pedigree then was constructed, and the participating relatives
were contacted.
The interview started with a section on demographic data,
followed by a second section on the four diagnostic criteria.2
Questions pertaining to criteria 1 to 3 were coded with “yes”
or “no.” The fourth criterion (circadian rhythm) had multiple response options: symptoms in the morning, afternoon,
evening, night, or no specific time. Only the answers “afternoon,” “evening,” and “night” were counted as “positive” toward RLS diagnosis. Only if all questions referring to the
minimal criteria were answered in the positive was the subject classified as RLS “affected.” The third section included
data on clinical characteristics of the disease (eg, age at onset
of the first symptom experienced).
Frequency of Familial Restless Legs Syndrome
The index patients were divided into the following subgroups. Patients with RLS were classified as “definite familial
RLS” if at least one family member in addition to the index
patient was classified as RLS affected by interview. Patients
were classified as having “probable familial RLS” if family
members were classified as nonaffected in the direct interview, but a positive RLS family history was ascertained (indirect assessment) in at least one additional first-degree family member. Patients were classified “nonfamilial RLS” if no
directly interviewed family members met the criteria for
298
Annals of Neurology
Vol 52
No 3
September 2002
Likely Mode of Inheritance
Only probands in whom the phenotype information was assessed by direct interview were included in the following
analysis.
STRATIFICATION OF THE FAMILIES BY THE MEAN AGE AT
ONSET OF THE DISEASE. A test for admixture (commin-
gling analysis)18 was performed to assess whether the distribution of the mean ages at onset in the families could be
better explained as a mixture of two (or more) distributions
rather than a single distribution. In the case of significant
admixture, the resulting groups were used for delineation of
strata for complex segregation analysis.
COMPLEX SEGREGATION ANALYSIS. In each of the resulting strata (see above), as well as for the whole sample, a complex segregation analysis was performed (program pedigree
analysis package),19,20 and an ascertainment correction was
applied.21 For each model, the likelihood and Akaike’s information criterion (AIC) were calculated.22 Significance testing
was performed by the method of nested hypothesis testing.
The specific principle of testing for a major gene consists of
two steps.
First, the most parsimonious major gene-containing
model (MPMG) is tested against a multifactorial model (no
MPMG). If this test shows that the MPMG is significantly
better than the multifactorial model, a second step is performed. Here, the MPMG model is tested against the model
of free transmission probabilities (⫽ general model). If the
MPMG cannot be rejected and if, in addition, the environmental transmission hypothesis is rejected against the general
model, it is possible to conclude that a major gene exists.
A test for heterogeneity between the results of the segregation analysis was performed.23,24 Gender differences between both groups were tested using a contingency table ␹2
test for heterogeneity of proportions.
Results
Response Rate and Study Population
Recruitment letters were sent out to 397 RLS index
patients. Eighty-six failed to respond: 9 patients had
died, and 77 could not be contacted on at least 2 attempts. Three hundred eleven patients sent back the
prepaid envelope: 239 agreed (1 patient died after his
agreement; n ⫽ 238) and 72 patients refused to participate in the study. Of the 238 patients, 196 allowed
us to contact their relatives (537 of 772 living firstdegree relatives and 133 spouses), and for 42 patients
no family members were available for direct contact.
Altogether, 908 interviews were conducted within 196
families and with an additional 42 index patients (Fig).
Frequency of Familial Restless Legs Syndrome
According to our classification, 89 of the 196 (45.4%)
index patients showed “definite familial RLS.” Forty-
Fig. Study design, response rate, participating subjects, and frequency of familial restless legs syndrome (RLS). Patients were classified
as “definite familial RLS” if at least one family member in addition to the index patient was classified as having definite RLS by
interview. They were only classified having “probable familial RLS” if family members interviewed were classified RLS nonaffected,
but an additional first-degree family member was classified as having RLS by family history. They were classified “nonfamilial RLS”
if no family members interviewed showed RLS and, additionally, no other family member was known to have symptoms of RLS by
family history.
three (21.9%) families showed “probable familial RLS”
(indirect assessment) and 64 (32.7%) had a “nonfamilial RLS.” In the group in which only the index patients
were interviewed, 16 (38.1%) index patients showed
“probable familial RLS” (indirect assessment) and 26
(61.9%) had a “nonfamilial RLS” (see Fig).
Demographic Data
Of the 908 subjects interviewed, 513 were women and
395 were men. The mean age of respondents at the
time of the evaluation was 54.7 ⫾ 16.8 years (mean ⫾
standard deviation [SD]; range, 12–93 years) in
women and 53.6 ⫾ 16.5 years (mean ⫾ SD; range,
18 –91 years) in men. Of the 513 women, 240 were
RLS positive (46.8%), and 273 (53.2%) were RLS
negative. Of the 395 men, 153 were RLS positive
(38.7%) and 242 (61.3%) were RLS negative.
Commingling Analysis
The distribution of the mean ages at onset in the families was better explained by a mixture of two normal
distributions than a single normal one ( p ⬍ 0.005).
The first distribution (mean age at onset in the families, 23.5 years; SD ⫽ 10.9 years) accounted for 38%;
the second distribution (mean, 45.9 years; SD ⫽ 15
years) accounted for the remaining 62% of the cases.
There was no significant evidence for additional admixture in the age at onset data. Using a Bayesian type
of analysis, we found that a mean age at onset within
the families of 30 years corresponds to a 50% chance
of belonging to either the first or the second group.
According to this analysis, two groups were defined:
mean age at onset up to 30 years of age (Group A, n ⫽
75 pedigrees) and older than 30 years (Group B, 163
pedigrees). There was no significant difference between
Groups A and B for the gender of the interviewed persons (␹2 test for heterogeneity of proportions, ␹2 ⫽
0.035; df ⫽ 1; p ⫽ 0.85).
Complex Segregation Analysis of Groups A and B
GROUP A. The MPMG is an autosomal dominant
model (AIC, 230.34) with a significant multifactorial
component (⫽ mixed model, dominant). This model
is equivalent to the codominant mixed model that
converged to identical parameter values (AIC,
232.34). Comparing the MPMG with a simple multifactorial model (AIC, 238.03), we found that the
MPMG is significantly more likely (␹2 ⫽ 11.69;
df ⫽ 2; p ⬍ 0.003). In contrast, the MPMG could
not be rejected against the general model (␹2 ⫽ 2.90;
df ⫽ 3; p ⬍ 0.4080). The hypothesis of environmental transmission is less likely than the general model
(␹2 ⫽ 14.59; df ⫽ 2; p ⬍ 0.0007). The MPMG
explains the segregation in Group A significantly better than a corresponding autosomal dominant model
Winkelmann et al: Restless Legs Syndrome
299
without a multifactorial (h2 ⫽ 0) component (␹2 ⫽
4.19; df ⫽ 1; p ⬍ 0.0407). The hypotheses of no
major gene, a recessive gene, and environmental
transmission converge to an identical model. The simultaneous failure to reject mendelian transmission
probabilities and the successful rejection of environmental transmission as well as the rejection of the nomajor-gene hypothesis fulfills the criteria required for
the conclusion that a single major gene exists (Table).
The genetic model found in Group A consists of an
allele frequency of 0.003, complete penetrance in heterozygotes and homozygotes, and a phenocopy rate of
0.005. The estimation of the portion of intragenotype
(at the major locus) variability (h2) attributable to multiple genes is maximized at 100% (h2 ⫽ 1). This implies that an additional genetic (multifactorial) influence besides the single major gene in determining
disease status must be allowed for.
GROUP B. Group B stands in contrast with Group A.
The most parsimonious model is the general model
(AIC, 354.46). All other models are rejected at a significance level of 0.01 or better. Therefore, there is no
evidence for a major gene effect.
Table. Genetic Models Tested in Group A, Group B, and in Whole Sample
Model
Group A
Mean age at onset up to 30 yr
of age
No major gene
Mixed model, dominant
Mixed model, recessive
Mixed model, codominant
Dominant
Recessive
Codominant
Environmental
Environmental ⫹ multifactorial
General (dominant)
Group B
Mean age at onset older than
30 yr
No major gene
Mixed model, dominant
Mixed model, recessive
Mixed model, codominant
Dominant
Recessive
Codominant
Environmental
Environmental ⫹ multifactorial
General (dominant)
Whole sample
No major gene
Mixed model, dominant
Mixed model, recessive
Mixed model, codominant
Dominant
Recessive
Codominant
Environmental
Environmental ⫹ multifactorial
General (dominant)
f2
␶AA
␶AB
⫽f1
⫽f2
⫽f1
1d
⫽f2
⫽f1
0.868
0.271
0.068
⫽f2
⫽f1
1d
—e
1d
0.868
0.738
0.868
0.271
0.068
1d
—c
[1]b
[1]b
1b
[1]b
[1]b
[1]b
⫽p
⫽p
1d
—c
[0.5]
[0.5]
[0.5]
[0.5]
[0.5]
[0.5]
⫽p
⫽p
0.652
0.031
1E-04
0d
0.01
1E-04
0.008
1E-04
1d
0
0.016
⫽f1
⫽f2
⫽f1
1d
⫽f2
⫽f1
0.723
0.61
0d,e
⫽f2
⫽f1
0.576
—e
1d
0.721
0.971
1d
0.136
§0.031d,e
1d
—c
[1]b
[1]b
[1]b
[1]b
[1]b
[1]b
⫽p
⫽p
1d
0.042
0.007
0.042
0.007
5E-05
0d
7E-05
0.171
—e
0.023
⫽f1
⫽f2
⫽f1
1d
⫽f2
⫽f1
0.774
0d
—e
⫽f2
⫽f1
1d
—e
1d
0.773
0.803
1d
0.877
0.042
1d
—c
[1]b
[1]b
[1]b
[1]b
[1]b
[1]b
⫽p
⫽p
1d
q
f0
f1
[1]b
0.003
0d
0.003
0.001
0.376
0.001
0.05
0.399
0.001
0.068
0.005
0.068
0.005
0.001
0d
0.001
0.271
0.068
0d
[1]b
2E-04
0d
0.001
1E-04
0.206
2E-04
0.935
0d
0.032
[1]b
0.002
0d
0.002
2E-04
0.28
1E-04
0.439
1d
0.042
␶BB
h2
Parameter
⫺2InL⫹C
AIC⫹Ca
—c
[0]
[0]
[0]
[0]
[0]
[0]
⫽p
⫽p
*0
1d
1d
1d
1d
[0]
[0]
[0]
[0]
1d
1d
2
4
4
5
3
3
4
4
5
7
234.03
222.34
234.03
222.34
226.53
244.67
226.53
262.96
234.03
219.44
238.03
230.34
242.03
232.34
232.53
250.67
234.53
270.96
244.03
233.44
—c
[0.5]
[0.5]
[0.5]
[0.5]
[0.5]
[0.5]
⫽p
⫽p
1d
—c
[0]
[0]
[0]
[0]
[0]
[0]
⫽p
⫽p
0d
1d
1d
1d
1d
[0]
[0]
[0]
[0]
1d
1d
2
4
4
5
3
3
4
4
5
7
362.75
371.82
362.75
358.28
380.39
377.39
380.34
440.71
362.75
340.46
366.75
379.82
370.75
368.28
386.39
383.39
388.34
448.71
372.75
354.46
—c
[0.5]
[0.5]
[0.5]
[0.5]
[0.5]
[0.5]
⫽p
⫽p
1d
—c
[0]
[0]
[0]
[0]
[0]
[0]
⫽p
⫽p
0.142
1d
1d
1d
1d
[0]
[0]
[0]
[0]
1d
1d
2
4
4
5
3
3
4
4
5
7
600.38
585.73
600.38
585.73
610.32
625.52
610.32
706.48
600.38
577.95
604.38
593.73
608.38
595.73
616.32
631.52
618.32
714.48
610.38
591.95
Column 1 shows all genetic models tested for each of the groups considered. The first is the no-major-gene hypothesis (equivalent to a
multifactorial hypothesis), in which all the variation for the trait is concentrated on the intragenotype variation parameter h2. Next are mixed
models in which in addition to a major gene, there is a multifactorial component (h2 is freely estimated within its boundaries, ranging from
0 to 1). These models are followed by major gene models without a multifactorial component (h2 ⫽ 0). These are followed by the models on
environmental transmission (h2 ⫽ 0) and environmental ⫹ multifactorial component (h2 estimated freely). The final model is the general
model, the most prominent feature of which is that the transmission probabilities are allowed to vary unrestrained.
a
AIC serves as a weighted measure of the fit of any given model. The lower the AIC, the more parsimonious is the hypothesis.22
Parameter values in brackets are values fixed because of the specification of the model.
c
Parameter value irrelevant for the model.
d
Parameter value estimated at a boundary of its possible range.
e
The particular value of a parameter due to the fixation of another parameter at a boundary is no longer needed for the calculation of the
likelihood. In this case, the last value obtained before the fixation is given.
b
q ⫽ frequency of deleterious allele; f0, f1, f2⫽ the penetrances for carriers of 0, 1, and 2 copies of the deleterious allele, respectively; ␶AA, ␶AB,
␶BB ⫽ transmission probabilities; h2 ⫽ proportion of intragenic variance attributable to polygenic effects. AIC ⫽ Akaike information criteria.
300
Annals of Neurology
Vol 52
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Whole Sample
The most parsimonious model is a general model
(AIC, 591.95). All other models are rejected at the 5%
level, although note that the rejection of the dominant
mixed model is borderline (␹2 ⫽ 7.78; df ⫽ 3; p ⫽
0.0508).
An overall test for heterogeneity between the results
of the segregation analysis in the different age strata
was highly significant (␹2 ⫽ 18.05; df ⫽ 7; p ⬍
0.0118).
Discussion
This study provides strong evidence for a difference in
the mode of inheritance of RLS between families with
an early versus a late age at onset in a series of consecutive, unselected RLS index patients. Families with a
mean age at onset of up to 30 years of age showed
strong evidence for an autosomal dominant mode of
inheritance transmitted by a single major gene acting
in a highly penetrant fashion. Besides a single major
gene in the early age at onset families, an additional
multifactorial component is a part of this model. This
implies that further genetic susceptibility factors determine whether nonallele carriers (phenocopies) also may
become affected. The codominant model, in which
heterozygote and homozygote effects can be distinguished, cannot be excluded but is less plausible. In
contrast, in families with a mean age at onset above 30
years, the familial occurrence of RLS did not follow
either a clear Mendelian or a multifactorial mode of
inheritance. This suggests either an oligogenic mode of
inheritance with an involvement of a few major genes
or much stronger environmental influences. We excluded secondary RLS index patients, but because of
the nature of the study we cannot exclude the occurrence of secondary RLS in family members. However,
secondary RLS patients are more likely to have an
older age at onset,8 and their families would be represented in Group B of our analysis. This further supports the exclusive existence of a single major gene
transmitted by an autosomal dominant mode of inheritance in early age at onset families.
The frequency of 45% definite and an additional
22% probable familial RLS cases is in line with previous studies displaying a positive family history in
43%6,7 to 64%.8 To our knowledge, this is the first
study, however, that investigated all available firstdegree relatives by personal direct interview even if the
index patients were primarily not aware of RLS symptoms in their relatives.6 – 8 We cannot exclude an ascertainment bias of the relatives depending on their degree of affection and their awareness of the disease.
This also might explain the reluctance of family members to participate. Furthermore, none of the spouses
received a diagnosis of RLS that would not have been
expected in view of its prevalence in recent populationbased studies. We ourselves cannot explain this. Conclusions such as “assortative mating in RLS” are too
speculative at the moment and need to be investigated
in more detail. Besides the known variable expressivity
of the symptoms within a single family,11–13 an earlier
age at onset of the disease in the younger generation
has been reported in three large RLS families, suggesting the possibility of anticipation.11,13 Comparing all
these studies, one has to consider that recalling sensory
symptoms retrospectively depends on subjective factors
and may affect the ascertainment of the age at onset of
the disease.
For the penetrance of RLS, a twin study showed a
high concordance rate of approximately 83%.25 Investigation of the parents suggested an autosomal dominant inheritance with a high penetrance.25 In our
study, however, the clear difference in the mode of inheritance between early- and late-onset RLS families argues for causative heterogeneity between these two age
groups. Similar patterns of inheritance have been found
in other diseases with “complex” inheritance, for example, in breast cancer,26 Alzheimer’s disease,27 or Parkinson’s disease.28 An age at onset–related differentiation of probands provides a new approach for future
linkage studies that may shed more light on the genetics and the pathophysiology of this disorder.
This work was supported by a Habilitations Förderpreis grant from
the Bavarian Ministry of Science, Culture and Art (J.W.).
We are indebted to all patients and family members who participated in this study and to Dr Catherine Bonaiti-Pellie for her valuable comments on this manuscript.
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autosomal, complex, mode, restless, syndrome, dominantly, inheritance, early, onset, familie, legs, segregation, evidence, provider, analysis, age
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