Suggestive Evidence for Association of Human Chromosome 18q12-q21 and Its Orthologue on Rat and Mouse Chromosome 18 With Several Autoimmune Diseases
Tony R. Merriman,
Heather J. Cordell,
Iain A. Eaves,
Patrick A. Danoy,
Francesca Coraddu,
Rachael Barber,
Francesco Cucca,
Simon Broadley,
Stephen Sawcer,
Alastair Compston,
Paul Wordsworth,
Jane Shatford,
Steve Laval,
Johan Jirholt,
Rikard Holmdahl,
Argyrios N. Theofilopoulos,
Dwight H. Kono,
Jaakko Tuomilehto,
Eva Tuomilehto-Wolf,
Raffaella Buzzetti,
Maria Giovanna Marrosu,
Dag E. Undlien,
Kjersti S. Rønningen,
C. Ionesco-Tirgoviste,
Julian P. Shield,
Fleming Pociot,
Jorn Nerup,
Chaim O. Jacob,
Constantin Polychronakos,
Steve C. Bain, and
John A. Todd
From the Wellcome Trust Centre for Molecular Mechanisms in Disease
(T.R.M., H.J.C., I.A.E., R.Ba., J.A.T.), University of Cambridge, Cambridge,
U.K.; the Department of Biochemistry (T.R.M.), University of Otago, Dunedin,
New Zealand; the University of Cambridge Neurology Unit (F.Co., S.B., S.S.,
A.C.), Addenbrooke's Hospital, Cambridge, U.K.; the Clinica Pediatrica (F.Cu.)
and Chair of Neurophysiopathology (M.G.M.), University of Cagliari, Cagliari,
Italy; the Wellcome Trust Centre for Human Genetics (T.R.M., P.A.D., P.W.,
J.S., S.L.), University of Oxford, Oxford, U.K.; Department of Genetics and
Pathology (J.J., R.H.), Biomedical Center, Uppsala University, Uppsala,
Sweden; the Department of Immunology (A.N.T., D.H.K.), the Scripps Research
Institute, La Jolla, California; the Department of Epidemiology and Health
Promotion (J.T., E.T.-W.), National Public Health Institute, Helsinki,
Finland; Istituto Clinica Medica II (R.Bu.), University of Rome `La Sapienza,
Rome, Italy; the Institute of Transplantation Immunology (D.E.U.), the
National Hospital, Oslo, Norway; the Department of Population Health Sciences
(K.S.R.), National Institute of Public Health, Oslo, Norway; the Clinic of
Nutrition and Metabolic Diseases (C.I.-T.), Bucharest, Romania; the Institute
of Child Health (J.P.S.), University of Bristol, Royal Hospital for Sick
Children, Bristol, U.K.; Steno Diabetes Center (F.P., J.N.), Gentofte,
Denmark; the Department of Medicine (C.O.J.), University of Southern
California School of Medicine, Los Angeles, California; Montreal Children's
Hospital (C.P.), Montréal,
Québec, Canada; and the Department of Medicine
(S.C.B.), University of Birmingham, Birmingham Heartlands Hospital,
Birmingham, U.K.
Address correspondence reprint requests to Tony R. Merriman, PhD, Department
of Biochemistry, University of Otago, Box 56, Dunedin, New Zealand. E-mail:
tony.merriman{at}stonebow.otago.ac.nz
.
 |
ABSTRACT
|
---|
Some immune system disorders, such as type 1 diabetes, multiple sclerosis
(MS), and rheumatoid arthritis (RA), share common features: the presence of
autoantibodies and self-reactive T-cells, and a genetic association with the
major histocompatibility complex. We have previously published evidence, from
1,708 families, for linkage and association of a haplotype of three markers in
the D18S487 region of chromosome 18q21 with type 1 diabetes. Here,
the three markers were typed in an independent set of 627 families and,
although there was evidence for linkage (maximum logarithm of odds score [MLS]
= 1.2; P = 0.02), no association was detected. Further linkage
analysis revealed suggestive evidence for linkage of chromosome 18q21 to type
1 diabetes in 882 multiplex families (MLS = 2.2;
s = 1.2; P =
0.001), and by meta-analysis the orthologous region (also on chromosome 18) is
linked to diabetes in rodents (P = 9 x 10-4). By
meta-analysis, both human chromosome 18q12-q21 and the rodent orthologous
region show positive evidence for linkage to an autoimmune phenotype
(P = 0.004 and 2 x 10-8, respectively, empirical
P = 0.01 and 2 x 10-4, respectively). In the
diabetes-linked region of chromosome 18q12-q21, a candidate gene, deleted in
colorectal carcinoma (DCC), was tested for association with human autoimmunity
in 3,380 families with type 1 diabetes, MS, and RA. A haplotype
("2-10") of two newly characterized microsatellite markers within
DCC showed evidence for association with autoimmunity (P = 5
x 10-6). Collectively, these data suggest that a locus (or
loci) exists on human chromosome 18q12-q21 that influences multiple autoimmune
diseases and that this association might be conserved between species.
 |
INTRODUCTION
|
---|
As much as 5% of the population suffers from autoimmune disease, a failure
of the homeostatic regulation of the immune system to prevent tissue damage
and maintain self-tolerance. Predisposition to autoimmune disease is
universally associated with alleles of the major histocompatibility complex
(MHC) genes on chromosome 6p21
(1). However, the MHC is not
sufficient to explain disease occurrence, and non-MHC susceptibility genes are
predicted. In type 1 diabetes in humans, the evidence for non-MHC genes is
incomplete
(2,3),
owing to the small, statistically underpowered data sets analyzed so far. In
rodent models of disease, however, the existence and location of several
non-MHC loci are established
(1). It has also been shown in
humans and mice that autoimmunity loci, mapped in a variety of autoimmune
disease models, including those for type 1 diabetes and multiple sclerosis
(MS), cluster significantly
(1,4,5).
Furthermore, congenic strains conclusively show that Idd3, a mouse
non-MHC type 1 diabetes susceptibility locus, also influences susceptibility
to experimental allergic encephalomyelitis (EAE), a model of MS
(6), and iddm4 in rats
may be a universal autoimmunity locus
(7). In addition to the
well-established linkage and association of the MHC region to multiple
autoimmune phenotypes, the CTLA-4 gene locus on human chromosome 2 has been
reported to be either linked or associated with type 1 diabetes, Graves'
disease, and MS
(8,9,10).
Previously, we reported some positive evidence of linkage (P =
0.005) and association (Pc = 0.01) of diabetes to
chromosome 18q21 in the vicinity of D18S487 (provisionally designated
IDDM6)
(11,12,13).
In the present study, we were unable to replicate the D18S487
association result, but we have consolidated evidence of linkage of the region
to type 1 diabetes by analysis of 882 families and by metaanalyses of other
linkage studies of a variety of autoimmune diseases in humans and rodents.
Finally, a large family-based study suggests that the human deleted in
colorectal carcinoma (DCC) gene region of chromosome 18q21 is associated with
autoimmune disease.
 |
RESEARCH DESIGN AND METHODS
|
---|
Families with type 1 diabetes, MS, and rheumatoid arthritis. The
families used for the association analysis were white European or
European-derived with both parents and at least one affected sibling per
family. The 2,359 type 1 diabetic families are summarized in
Table 1. In the Sardinian,
Finnish, Canadian, and Italian data sets, ages of diagnoses were <17 years,
<15 years, <18 years, and <29 years, respectively.
Table 1 summarizes the
composition of the 1,708-family diabetes data set
(13), the independent 627
families studied here, and the combined 2,335 and 2,359 families.
The 229 Sardinian MS families have been previously described
(18). The 667 U.K. simplex MS
families had a clinical diagnosis of disease based on the Poser criteria
(19). The 125-family U.K.
rheumatoid arthritis (RA) data set consisted of simplex and multiplex
families, and all cases satisfied the 1987 American College of Rheumatology
criteria for disease and were recruited from the Arthritis Research Campaign
Epidemiology Unit in Manchester University and the Rheumatology Department at
the Nuffield Orthopaedic Centre in Oxford. Healthy siblings were collected in
all data sets except the U.K. MS families. In all cases, sample collection was
approved by the appropriate institutional review board. The total 3,380-family
autoimmune data set comprised the 2,359 type 1 diabetes families, 896 MS
families, and 125 RA families.
The 882 affected sib-pair pedigrees available to us that were tested for
linkage to disease consisted of 415 of the 423 U.K. families used in the
association study, 284 U.S. families including the 241 used in the association
study, 58 Italian families of which 57 were used in the association study, 54
of the 55 Danish multiplex families, 32 Finnish affected sib-pair families
including the 24 used in the association study, and 39 Norwegian multiplex
families from the previously described 420 families.
Microsatellite marker isolation and genotyping. With use of
polymerase chain reaction (PCR) primers for DCC exons 19 and 29 (exon
29 is the 3' exon of DCC)
(20), HPAC 88_h_2 and HBAC
55_g_22, respectively, were isolated from the De Jong libraries (ResGen). HBAC
55_g_22 is telomeric to HPAC 88_h_2. Microsatellite marker 88,21 was cloned
from HPAC 88_h_2 and marker 55,26 from HBAC 55_g_22 using a previously
described PCR-based method
(13). Primer sequences for
amplifying 88,21 are CTGA CAAAACTGGGACTACCTTCC and GAATACATCTCCGTATTTGCATC and
for 55,26 are GGCTAGTGGTTGCCGTATTATAC and AAATCTCAGCATGTCAGT GAA. Primer
sequences for amplifying other microsatellite markers either have been
published elsewhere
(12,13)
or are available from
http://www.gdb.org
. Genotyping PCRs using fluorescently labeled primers were performed and
analyzed as described previously
(21). Haplotypes are given
with the marker genotypes in centromeric to telomeric order.
Comparative mapping. Human, mouse, and rat chromosome 18 orthology
relationships were established using
www3.ncbi.nlm.nih.gov/Homology
,
www.informatics.jax.org/searches/oxfordgrid_form.shtml
,
www.nih.gov/niams/scientific/ratgbase
,
www.otsuka.genome.ad.jp/ratmap
, and
www.well.ox.ac.uk/~bihoreau
. Distances along human chromosome 18 were taken from a combination of
www.cedar.genetics.soton.ac.uk/pub
and
www.genethon.fr
, along mouse chromosome 18 from
www.informatics.jax.org
, and along rat chromosome 18 from
www.well.ox.ac.uk/~bihoreau
and
waldo.wi.mit.edu/rat/public/
.
Meta-analysis: Fisher's method. When there is no justification for
assuming a common population variance between genome scans for linkage to
differing autoimmune phenotypes in differing rodent strains and differing
human populations, the only common measure that can form the basis for
combination is the P value
(22). The sum of
(-2logeP) probability values from m independent
tests of linkage is a
2 statistic with 2m degrees of
freedom (df) (23). Under the
null hypothesis of no linkage of a region to disease, observed P
values from separate studies have a uniform distribution regardless of the
test statistic used or the distribution from which they arise
(24). Thus, Fisher's method is
appropriate even when considering studies that exhibit heterogeneity in the
phenotype measured and test statistics used. Chromosome 18 data used here for
the meta-analyses were derived from whole genome-wide scans and were obtained
either directly from publications or from the corresponding author. P
values were either published values or, when not presented, were determined as
follows. For rodents, P values were calculated by a
2
test of heterogeneity between affected and unaffected animals or, if
unaffected animals were not genotyped, were calculated by a
2
test of heterogeneity against the hypothesis of no linkage. For humans,
P values were calculated for maximum logarithm-of-odds scores (MLS)
and Z scores. If necessary, logarithm of odds scores were converted into
2 (1df) statistics by multiplication by a factor of 4.6
(25) and the resulting
P value included in the analysis. Autoimmune phenotypes that were
characterized by both inflammation and association and/or linkage to the HLA
region were analyzed. Where more than one scan was reported for a rodent
autoimmune disease model, to reduce heterogeneity we chose the most
consistently used end-point phenotype for each model. For type 1 diabetes,
this end point was elevated urinary glucose levels, paralysis for EAE,
swelling and erythema in joints for arthritis, and nephritis (which causes
death) for systemic lupus erythematosus (SLE). Genome scans examining
associated phenotypes (insulitis in diabetes and factors influencing
autoantibody production, for example) were excluded. For two rat arthritis
scans
(26,27),
which assessed linkage to severity of disease, data from severely affected
animals were used and P values calculated by a
2 test
of heterogeneity against the null hypothesis of no linkage to arthritis. For
the (BB x BN)F2 data
(28,29),
animals with a maximal arthritis score (MAS) >33 were compared, using a
2 test for linkage, to animals with MAS <3. In two reports
(30,31),
a two-stage genotyping strategy was used requiring markers showing suggestive
linkage to disease in an initial panel of animals to be genotyped over a
second panel of animals; in the analysis presented here, data from the first
panel of animals only were used. Data from the scans of Butterfield et al.
(32) and Yang et al.
(33) were analyzed using a
2 test for linkage to disease susceptibility. In the (BB
x WF)F1 x BB rat backcross, linkage of diabetes to chromosome 18
was not reported owing to the relative paucity of available polymorphic
markers but tested here by a
2 test of heterogeneity between
affected and unaffected animals using data obtained from the corresponding
author (34).
To meta-analyze linkage of the entire length of chromosome 18 to
autoimmunity, the rodent and human chromosomes were divided into 10-cM
intervals and P values combined as described above to yield a total
P value for each of human and rodent (Tables
2 and
3). The -(log10) of
these values were plotted at intervals of 10 cM
(Fig. 2). Only scans with at
least three markers, each in separate intervals of 10 cM, along the chromosome
length were included. Six genome-wide scans
(77,78,79,80,81,82)
were excluded on this criterion. Scans in which partial data only were
available for chromosome 18
(83,84,85)
were excluded from this analysis (the first two publications reported positive
linkage of the 40- to 50-cM portion of rat chromosome 18 to type 1 diabetes
[P = 0.004 and 0.045, respectively] and the third reported positive
linkage of chromosome 18q21 to Graves' disease [P = 3 x
10-4], but linkage data for other chromosome 18 markers were not
available). When no chromosome 18 data were available either in the published
paper or by request
(36,59),
P = 1.0 was included in each 10-cM window and 2 df added to each
final
2 statistic. Where a scan included no marker in a
particular 10-cM window, no data were included for that window and no degrees
of freedom added to the total
2 statistic.
Meta-analysis: permutation method. A simulation/permutation method
was used to additionally evaluate the pointwise significance of the test
statistic obtained using Fisher's method. Test statistics at a single location
were constructed using data from Tables
2 and
3, in 104 (for human)
or 106 (for rodent) replicates. In each replicate, the P
value contribution from a single study was chosen at random from the
n possible contributions for that study at the n different
locations (n = 6 for rodent and 13 for human). The P values
from the m studies were combined using Fisher's method to give an
overall test statistic for that replicate. Comparison of the observed Fisher's
test statistic to that obtained using simulation allows an empirical
P value for the observed statistic to be calculated. The
-(log10) of these values were plotted at intervals of 10 cM
(Fig. 3). This method relies on
the assumption that at most locations, there is no linkage to disease. If a
high proportion of the locations is, in fact, linked to disease, this method
would give a conservative estimate of the empirical P value. Thus, in
the case of the rodent meta-analysis in which there was a reasonable
expectation of linkage of the 40- to 50-cM bin to disease
(Fig. 2A), P
values from the other five bins only (0-40 cM and 50 cM telomere) were used
for a second permutation. The method would be anticonservative if the number
of studies with missing information (in which the P value
contribution was set to 1.0) was significantly smaller at the test location
than at a random location. In our analyses, the test locations with higher
Fisher's combined statistics did not have significantly fewer missing
P values than other locations.
Genome search meta-analysis method. The genome search meta-analysis
(GSMA) method (86) can be
applied to a wide range of study designs and to studies that differ in family
ascertainment, population sampled, phenotype definition, markers genotyped,
and analysis method used. The method requires ranking the results (test
statistics or P values) at n bins within each study. The
test statistic at each location is the sum (over m studies) of the
ranks. Ten-cM bins were used, meaning 6 bins for rodent chromosome 18 and 13
bins for human chromosome 18. The exact distribution of the ranked statistic
may be calculated (86). The
-(log10) of the P values were plotted at intervals of 10
cM along rodent and human chromosome 18. Because our analysis was on a
specific chromosome rather than from a whole genome scan, and our bins were
smaller in length (and thus more correlated) than the recommended 20-cM bins
(86), the significance of the
test statistics was also evaluated using a simulation/permutation approach as
described above (plotted in Fig.
4). P values using this method were very similar to
theoretical P values.
Analysis of allelic association and linkage. Transmission of
two-marker haplotypes was assessed from heterozygous parents to both affected
and unaffected offspring using the transmission disequilibrium test (TDT)
(87). To take account of the
lack of independence (owing to linkage) between siblings in multiplex families
and obtain a valid estimate of association, the TDT-based statistic
(Tsp) was used
(88). Tsp
has a
2 (1 df) distribution. When both parents were
heterozygous for the same alleles at one marker in the haplotype, the family
was removed from the analysis to prevent bias
(89). Any families with
missing parental data were also removed from the analysis to eliminate bias
either from reconstruction of parental haplotypes or counting transmissions
from a single parent
(90,91).
Transmission of haplotypes and Tsp were calculated
assuming no recombination between 88,21 and 55,26. Percent T is the
number of times an allele or haplotype was transmitted from heterozygous
parents divided by the total of transmissions plus nontransmissions, expressed
as a percentage. To assess linkage disequilibrium between haplotypes, D'
values were calculated (92).
D' values range from 1 (complete disequilibrium) through 0 (complete
equilibrium) to -1 (alleles never found on same haplotype).
For the linkage analysis, up to 33 microsatellite markers spanning a 42-cM
region of 18q12-q21 were typed in 882 affected sib-pair families from six
populations. Centromeric to telomeric, these were as follows: D18S57,
D18S454, D18S474, D18S484,
D18S1156,88,21,55,26,114,1,30T7,129,6,129,12,129,11,IO43,56,
D18S487, A181,2,49,12,49,22, D18S35, D18S69, D18S39, D18S41,
D18S1152, D18S1129, D18S64, D18S38, D18S1134, D18S1148, D18S68, D18S42,
D18S55, D18S483, D18S465, and D18S61. The 10 framework markers
D18S454, D18S474, D18S487, D18S35, D18S69, D18S39, D18S41, D18S64,
D18S38, and D18S42 were typed in all of the populations except
the 39 Norwegian families. A further 11 of the 33 markers were typed in the
Danish, Italian, and Norwegian data sets and 13 additional microsatellites
were typed in the Finnish and U.S. data sets. All 33 were typed in the U.K.
families. Markers were ordered with the Genome Analysis System
(http://users.ox.ac.uk/~ayoung/gas.html
). When a physical map existed
(13), it was used to order
markers instead. Intermarker distances were calculated using the Aspex
software
(ftp://lahmed.stanford.edu/pub/aspex/index.html
) using all available family material. Multipoint MLS values were produced
using Mapmaker/Sibs
(ftp://ftp-genome.wi.mit.edu/distribution/software/sibs
).
 |
RESULTS
|
---|
Previously, we cloned and physically mapped 10 microsatellite markers
within a 650-kb region surrounding D18S487 on chromosome 18q21
(13). In 1,708 families, we
showed that a haplotype ("10-2-4") of three of these markers (129,
11-IO43, 56-D18S487) showed some positive evidence of association
with type 1 diabetes (P = 2 x 10-4)
(13). Here, in an attempt to
replicate this association, we typed the three markers in an independent set
of 627 type 1 diabetes families and examined transmission of the 10-2-4
haplotype from heterozygous parents to affected offspring. The three-marker
haplotype was negatively transmitted in these families (33 T vs. 53 NT),
although there was evidence for linkage of the two markers to disease in the
140 multiplex family subset of the 627 (MLS = 1.2, P = 0.02). In the
combined 2,335 families, there were 249 T vs. 199 NT (%T = 55.6, P =
0.02). In the context of genome-wide levels of statistical significance for
allelic association of P < 5 x 10-8
(93), this is highly unlikely
to be a true positive. This Bonferroni-based threshold may be too stringent,
however, if there is prior evidence of linkage of a chromosome region with
disease. We, therefore, reevaluated the evidence of linkage. Not only did we
analyze linkage of chromosome 18q in 882 type 1 diabetic sib-pairs, but we
also meta-analyzed linkage of the orthologous region of rodent chromosome 18
to type 1 diabetes. First, we typed up to 33 polymorphic microsatellite
markers covering a 44-cM region (D18S57 to D18S61) in 882
type 1 diabetesaffected sib-pair pedigrees and tested for linkage to
disease (Fig. 1). There was a
peak MLS of 2.2 (
s = 1.2; P = 0.001), 3 cM telomeric to
D18S487, suggestive evidence for linkage to disease
(94).

View larger version (10K):
[in this window]
[in a new window]
|
FIG. 1. Linkage of human chromosome 18q to type 1 diabetes in 882 affected
sib-pair families. The approximate positions of SMAD2, SMAD4, and
DCC are shown. SMAD2 has been colocalized to YAC clones
positive for D18S460, SMAD4 to YAC clones positive for
D18S474, and DCC to YAC clones positive for
D18S1156 (95).
Microsatellite markers (represented by ) are listed, centromeric to
telomeric, in RESEARCH DESIGN AND METHODS.
|
|
On the basis of this result, we sought additional support for the
possibility that chromosome 18q21 contains a diabetes gene by meta-analysis of
the published evidence for linkage of the orthologous region to type 1
diabetes in rodent models of disease. A 25-cM segment of human chromosome
18q12-q21 is orthologous with an 8-cM segment of mouse chromosome 18, and
mouse and rat chromosome 18 are also conserved. Gene order is conserved
between SMAD2 (65 cM on human chromosome 18q12.3 and 48 cM on mouse
chromosome 18) and FECH (90 cM on human chromosome 18q21.3 and 40 cM
on mouse chromosome 18). The content and order of mapped genes is also
conserved between mouse and rat chromosome 18 along the entire length, except
for Gja1 (which maps at 59 cM on rat chromosome 18 and 29 cM on mouse
chromosome 10). Four independent genome scans of rodent type 1 diabetes, with
at least three markers along chromosome 18, have been published. The distal
portion of rodent chromosome 18 (40-50 cM), orthologous with human chromosome
18q12-q21, showed evidence of linkage to type 1 diabetes (P = 9
x 10-4; Table
2).
Human 18q12-q23 has also been reported as being linked to Graves' disease,
SLE, and RA
(65,70,85),
and the orthologous region on distal rodent chromosome 18 has been linked to
EAE
(39,95),
to Theiler's virus-induced demyelination in mouse (a model of MS)
(96), and in the murine model
of lupus (45). To test the
hypothesis that the distal end of rodent chromosome 18 and the orthologous
region on human chromosome 18q12-q21 was linked to a phenotype of autoimmunity
rather than to just a single autoimmune disease such as type 1 diabetes, the
meta-analysis was extended to all published genome scans of autoimmune
disease, beginning with the rodent model. Scans for linkage in rodent models
of type 1 diabetes, EAE, lupus, arthritis, orchitis, gastritis, sialadenitis,
and uveoretinitis were available (Table
2; Fig.
2A). Strongest linkage was observed to the 40- to 50-cM
portion of chromosome 18 (P = 2 x 10-8). When
plotted separately, the rat and mouse curves were similar, with linkage
peaking in the 40- to 50-cM window for each
(Fig. 2A; P =
2 x 10-6 and P = 0.001, respectively). Meta-analysis
of human chromosome 18 was then performed on published human autoimmune
disease genome scans of type 1 diabetes, inflammatory bowel disease,
psoriasis, MS, RA, SLE, and Graves' disease. Peak P = 0.004 was
obtained in the chromosome 18q21 region
(Table 3;
Fig. 2B). Note that
three type 1 diabetes studies
(2,3,11)
were excluded owing to overlap in families used.
Genome scans using families or animal cohorts of small size (Tables
2 and
3) may increase the chance of
type 1 error owing to the possibility of the respective test statistics not
being continuous. Therefore, we repeated the human and rodent analyses
excluding the five smallest studies from each. P values by Fisher's
method were 0.004 for the 70- to 80-cM bin of human chromosome 18 and 4
x 10-9 for the 40- to 50-cM bin of rodent chromosome 18.
Excluding these studies did not greatly affect the combined statistic.
To further evaluate the significance of the meta-analysisbased
linkage obtained using Fisher's method, we applied a simulation method to the
data (Fig. 3). For rodents,
P = 2 x 10-4 (with a reasonable expectation of
linkage of the 40- to 50-cM region to disease, this region was excluded from
the permutation, P = 0.005 when this region was included) was
obtained for linkage of the 40- to 50-cM bin of chromosome 18 to autoimmunity
and P = 0.01 for linkage of human chromosome 18q12-q21 to
autoimmunity. If any of the other positions used for the permutation are, in
fact, linked to disease, then P = 2 x 10-4 will be a
conservative estimate of the empirical level of significance in rodent. The
permutation accounts for any residual linkage present on chromosome 18 and
indicates that the linkages observed using Fisher's method are unlikely to
have occurred owing to chance.
A separate method of meta-analysis, the GSMA method
(86), was applied to the data
(Fig. 4). This analysis
supported the results obtained using Fisher's method of combining P
values, with linkage observed both to the distal end of rodent chromosome 18
(40- to 50-cM portion, P = 0.03) and the chromosome 18q12-q21 region
in humans (70- to 80-cM portion, P = 0.02). Simulated P
values were 0.02 and 0.01, respectively
(Fig. 4). The GSMA P
values are less significant than the Fisher's P values
(Fig. 2), probably because the
GSMA method does not take into account the actual P values obtained
in the individual studies.
At this stage of the investigation, we concluded that there was sufficient
justification to commence a functional candidate gene approach to finding the
disease locus (or loci) in the potentially linked region. As a first step, we
chose the DCC gene because it has been well characterized at the genomic
level, its product functions in apoptosis
(97), and apoptosis defects
can cause autoimmune disease. Using two microsatellite markers (88,21 and
55,26) cloned from within introns of DCC, we tested DCC for
association with autoimmunity in the 2,359 type 1 diabetes families
(Table 1), 896 MS families, and
125 RA families (n = 3,380; Table
4). All four haplotypes with a frequency >5% in parental
chromosomes (2-10 [19.5%], 2-11 [10.9%], 7-1 [9.2%], and 2-12 [5.8%]) were
tested for association with autoimmunity in the 3,380 families. The
Tsp statistics were 20.8 (1,332 T, 1,100 NT; P =
5 x 10-6), 1.2 (821 T, 780 NT; P = 0.28), 1.0 (674
T, 643 NT; P = 0.32), and 0.0 (432 T, 500 NT; P = 1.0),
respectively. Thus, only 2-10, the most common haplotype, showed some positive
association with autoimmunity (P = 5 x 10-6;
Pc = 2.1 x 10-4). A correction factor of
42 takes account of the 38 independent tests done in previous association
analyses of the region
(12,13)
and the four separate 88,21-55,26 haplotypes tested here. Even if we
anticipate 5,000 tests within this 20-cM chromosome 18q region, corrected
P would still be <0.05. Association between the 2-10 haplotype and
the separate autoimmune phenotypes was also tested
(Table 4). Evidence for
association with type 1 diabetes (P = 2 x 10-4) and
with MS (P = 0.03) but not with RA (P = 0.09) was obtained.
Transmission of the 2-10 haplotype to unaffected siblings did not differ from
random expectations in the 3,380 families (633 T and 595 NT; % T = 51.5,
P = 0.28).
 |
DISCUSSION
|
---|
A multifaceted approach to study of a non-MHC type 1 diabetes
susceptibility locus on chromosome 18q21 that incorporates all currently
available clinical resources and data is presented here. On the basis of
suggestive evidence for linkage of the chromosome 18q12-q21 region with type 1
diabetes in 882 families (Fig.
1; P = 0.001), a meta-analysis was undertaken providing
evidence for linkage of the orthologous region in rodent to type 1 diabetes
(P = 9 x 10-4). Evidence for linkage of the same
region to an autoimmune phenotype in both rodent and human (P = 2
x 10-8 and 0.004, respectively, simulated P = 2
x 10-4 and 0.01, respectively) was obtained by further
meta-analyses. Finally, with use of a positional candidate gene approach,
association of microsatellite markers within the DCC gene was demonstrated to
an autoimmune phenotype in humans (3,380 families, P = 5 x
10-6; Pc = 2.1 x 10-4).
The markers within DCC associated with autoimmunity (88,21 and
55,26) are within one megabase of D18S487
(98), which is part of the
three-marker 129, 11-IO43, 56-D18S487 haplotype
("10-2-4") that we had previously found to be weakly associated
with type 1 diabetes. The associated 2-10 haplotype of markers 88,21 and 5,26
was not in linkage disequilibrium with any of the five most common haplotypes,
including the weakly associated 10-2-4 haplotype, at 129, 11-IO43,
56-D18S487. The D' values were between -0.19 and 0.21 in the diabetes
families. The 10-2-4 haplotype was positively transmitted to affected
offspring in the 1,708 families previously studied (Tsp =
12.0; P = 5 x 10-4)
(13) but was negatively
transmitted in the second independent set of 627 type 1 diabetes families
studied here (33 T, 53 NT). In contrast, the 2-10 haplotype was associated
with disease in both sets of families (P = 0.003 and 0.01,
respectively). The results for the 129, 11-IO43, 56-D18S487 markers
may represent either a false-positive association, or weaker linkage
disequilibrium with the same locus detected by the DCC markers, or a
very weak disease association distinct from that detected at DCC.
Our conclusion that there is suggestive evidence supporting association and
linkage of human chromosome 18q12-q21 and its orthologue on rat and mouse
chromosome 18 with multiple autoimmune phenotypes was reached only when
considering the sum of the analyses presented here. Considering the
conservation between human, mouse, and rat of association and linkage with
autoimmunity, the results presented here are unlikely to be artifactual but
rather indicate involvement of one ormore likelymore than one
gene on chromosome 18 in susceptibility to autoimmunity. It is important to
note that when examining each of the individual analyses in isolation
(DCC association study in human and the rodent and human
meta-analyses), none provides convincing evidence for involvement of
chromosome 18 in autoimmunityonly the type 1 diabetes linkage analysis
(Fig. 1) can be considered to
provide "stand alone" suggestive evidence. For a number of
reasons, however, our finding of possible involvement of chromosome 18 in
autoimmune susceptibility is unlikely to be a false positive. P = 2
x 10-8 for linkage to rodent autoimmunity was obtained in the
40- to 50-cM portion of distal chromosome 18
(Table 2;
Fig. 2A, empirical
P = 2 x 10-4); the separate mouse and rat chromosome
18 meta-analyses were similar (Fig.
2A); linkage to rodent autoimmunity was replicated in the
70- to 80-cM orthologous region of human chromosome 18q21
(Fig. 2B;
Table 3, P = 0.004;
Fig. 3B, empirical
P = 0.01). The GSMA method (Fig.
4) also supported linkage of the 40- to 50-cM portion of rodent
chromosome 18 and 70- to 80-cM portion of human chromosome 18, to autoimmunity
(P = 0.03 and 0.02, respectively). In addition, markers within
DCC (which maps at 74 cM on human chromosome 18q21) are associated
with autoimmune disease (Table 4;
P = 5 x 10-6, Pc = 2.1 x
10-4), and there is suggestive evidence for linkage of chromosome
18q21 to type 1 diabetes (Fig.
1; P = 0.001).
Several caveats concerning the meta-analyses need to be discussed. Possibly
the most significant problem is the methodology used when combining data from
heterogeneous sources. For example, the rodent meta-analysis combined data
from backcrosses and intercrosses between 17 and 10 independent mouse and rat
crosses, respectively. This represents 22 separate strains, with an unknown
number and origin of allele(s) at the putative chromosome 18 autoimmunity
locus (or loci). Because of this heterogeneity, to obtain an estimate of the
true significance of the combined data, it was necessary to combine P
values by Fisher's method
(22), rather than combine raw
data. It should be noted that, if possible, it is preferable to combine raw
data or parameter estimates; combining P values tends to cause more
false-positive results and miss more true-positive loci than other approaches
(99,100).
In addition, we were unable to control for the fact that genome scan data
might have higher marker density in regions of interest (for example,
IDDM6 may be considered a region of interest in an autoimmune genome
scan), thus biasing the meta-analysis. It is not possible to state whether
evidence supporting linkage of chromosome 18 to autoimmunity in the
meta-analyses reached either suggestive or significant levels; this would
require modeling of the meta-analysis methods presented here, in addition to
performing a genome-wide meta-analysis. Our study took into account all
genome-wide studies irrespective of the significance of the chromosome 18
linkage data. It does not select positive results, as in the work of Becker et
al. (4), and is unlikely to be
affected by publication bias of positive results, since the data for
chromosome 18 come from whole genome scan studies. We excluded available
unpublished data from the following individuals: D. Baker, showing linkage of
the 40- to 50-cM region of mouse chromosome 18 to cyclophosphamide-induced
diabetes in (ABH x NOD) x NOD (personal communication; P
= 0.0015); R. Holmdahl, showing linkage to EAE of markers syntenic to the
mouse 40- to 50-cM region in a (E3 x DA)F2 rat intercross (P =
0.02); J. Otto, showing linkage of proteoglycan-induced arthritis to the mouse
40- to 50-cM region in a (C3H x C57Bl/6)F2 intercross (personal
communication; P = 4 x 10-4); and D. Kono and C.
Teuscher (personal communication), showing no evidence for linkage of the 40-
to 50-cM region of mouse chr 18 to SLE in (BXSB x NZW)F2 (P =
0.93) and to EAE in (SJL/J x B10.S)F1 x B10.S (P = 0.63),
respectively. These unpublished data were excluded from our meta-analysis to
remove any bias owing to the possibility of preferentially obtaining positive
chromosome 18 data over negative data. If these P values were
combined (using Fisher's method) with the total P values presented in
Table 2, and published data not
included in the chromosome 18 meta-analysis owing to availability of only some
chromosome 18 data (see RESEARCH DESIGN AND METHODS), then P for the
40- to 50-cM portion of rodent chromosome 18 would be 7 x
10-13. Similarly, adding P = 0.001 from the partial
linkage map of chromosome 18 in human diabetes
(Fig. 1), in addition to other
partial human chromosome 18 data
(85), to the data presented in
Table 3 gives P = 6
x 10-6 supporting linkage of the 70- to 80-cM portion of
human chromosome 18 to autoimmunity.
Although microsatellites are informative markers for association mapping,
their typing in very large data sets is problematic owing to the failure to
fully automate allele scoring. Therefore, single nucleotide polymorphisms,
because their scoring can be automated in a robust and accurate way, should
improve the feasibility of further characterizing the contribution of human
chromosome 18 to autoimmune susceptibility. Our results also indicate the
importance of animal models in mapping of disease genes. Congenic mapping will
allow further investigation of the role of chromosome 18 in rodent
autoimmunity.
 |
ACKNOWLEDGMENTS
|
---|
This work was funded by the Wellcome Trust, the British Diabetic
Association, the U.K. Medical Research Council, the Juvenile Diabetes
Foundation International (JDFI), the Arthritis Research Campaign, and the New
Zealand Health Research Council. We thank the Finnish Childhood Registry
Group, the Novo Nordisk Foundation, the Finnish Academy, and National
Institutes of Health for their support for the Finnish part of the study.
T.R.M. was a JDFI Postdoctoral Fellow and is currently a Wellcome
TrustNew Zealand Health Research Council Overseas Postdoctoral Fellow.
I.A.E was the recipient of a Wellcome Trust Prize Studentship, and J.A.T. was
a Wellcome Trust Principal Research Fellow.
We acknowledge the following people who generously shared their data for
this study: Marie-Claude Babron, David Baker, Alan Baxter, Elizabeth
Blankenhorn, Jean-Francois Bureau, Russell Butterfield, Judy Cho, Francoise
Clerget-Darpoux, Ingrid Dahlman, Dave Dyment, George Ebers, John Harley,
Michelle Haywood, Jennifer Kelly, Brian Kotzin, Ed Leiter, Joseph Michalski,
John Mordes, Bernie Morley, Jeffrey Otto, Miles Parkes, Luc Reininger, Elaine
Remmers, Marie-Paule Roth, Jennifer Salström,
Jack Satsangi, Pablo Silveira, Cory Teuscher, Yaron Tomer, Richard Trembath,
Colin Veal, and Michael Weil. We also thank all authors who made their entire
genome-wide linkage data publicly available, either in the relevant
publication or electronically. Helen Yates and the Arthritis Research Campaign
Epidemiology Research Unit are thanked for recruiting RA families. Frank
Dudbridge is thanked for help in data analysis.
 |
FOOTNOTES
|
---|
J.A.T. was a paid consultant of Merck Research Laboratories, which provided
grants to his laboratory to conduct studies on the genetics of type 1
diabetes.
DCC, deleted in colorectal carcinoma; df, degrees of freedom; EAE,
experimental allergic encephalomyelitis; GSMA, genome search meta-analysis;
JDFI, Juvenile Diabetes Foundation International; MAS, maximal arthritis
score; MHC, major histocompatibility complex; MLS, maximum logarithm-of-odds
score; MS, multiple sclerosis; PCR, polymerase chain reaction; RA, rheumatoid
arthritis; SLE, systemic lupus erythematosus; TDT, transmission disequilibrium
test; Tsp, TDT-based statistic.
Received for publication April 6, 2000
and accepted in revised form September 8, 2000
 |
REFERENCES
|
---|
-
Vyse TJ, Todd JA: Genetic analysis of autoimmune disease.
Cell 85:311
-318, 1996[Medline]
-
Concannon P, Gogolin-Ewens KJ, Hinds DA, Wapelhorst B, Morrison VA,
Stirling B, Mitra M, Farmer J, Williams SR, Cox NJ, Bell GI, Risch N, Spielman
RS: A second-generation screen of the human genome for susceptibility to
insulin-dependent diabetes mellitus. Nat Genet19
: 292-296,1998[Medline]
-
Mein CA, Esposito L, Dunn MG, Johnson GC, Timms AE, Goy JV, Smith
AN, Sebag-Montefiore L, Merriman ME, Wilson AJ, Pritchard LE, Cucca F, Barnett
AH, Bain SC, Todd JA: A search for type 1 diabetes susceptibility genes in
families from the United Kingdom. Nat Genet19
: 297-300,1998[Medline]
-
Becker KG, Simon RM, Bailey-Wilson JE, Freidlin B, Biddison WE,
McFarland HF, Trent JM: Clustering of non-major histocompatibility complex
susceptibility candidate loci in human autoimmune diseases. Proc
Natl Acad Sci USA 95:9979
-9984, 1998[Abstract/Free Full Text]
-
Becker KG: Comparative genetics of type 1 diabetes and autoimmune
disease: common loci, common pathways? Diabetes48
: 1353-1358,1999[Abstract]
-
Encinas JA, Wicker LS, Peterson LB, Mukasa A, Teuscher C, Sobel R,
Weiner HL, Seidman CE, Seidman JG, Kuchroo VK: QTL influencing autoimmune
diabetes and encephalomyelitis map to a 0.15 cM region containing Il2.Nat Genet 21:158
-160, 1999[Medline]
-
Martin A-M, Maxson MN, Leif J, Mordes JP, Greiner DL, Blakenhorn
EP: Diabetes-prone and diabetes-resistant BB rats share a common major
diabetes susceptibility locus, iddm4. Diabetes48
: 2138-2144,1999[Abstract]
-
Nisticò L, Buzzetti R, Pritchard
LE, Van der Auwera B, Giovannini C, Bosi E, Larrad MTM, Rios MS, Chow CC,
Cockram CS, Jacobs K, Mijovic C, Bain SC, Barnett AH, Vandewalle CL, Schuit F,
Gorus FK, Belgian Diabetes Registry, Tosi R, Pozzilli P, Todd JA: The CTLA-4
gene region of chromosome 2q33 is linked to, and associated with, type 1
diabetes. Hum Mol Genet 5:1075
-1080, 1996[Abstract/Free Full Text]
-
Vaidya B, Imrie H, Perros P, Young ET, Kelly WF, Carr D, Large DM,
Toft AD, McCarthy MI, Kendall-Taylor P, Pearce SHS: The cytotoxic T lymphocyte
antigen-4 is a major Graves' disease locus. Hum Mol
Genet 7:1195
-1199, 1999[Abstract/Free Full Text]
-
Harbo HF, Celius EG, Vartdal F, Spurkland A: CTLA4
promoter and exon 1 dimorphisms in multiple sclerosis. Tissue
Antigens 53:106
-110, 1999[Medline]
-
Davies JL, Kawaguchi Y, Bennett ST, Copeman JB, Cordell HJ,
Pritchard LE, Reed PW, Gough SCL, Jenkins SC, Palmer SM, Balfour KM, Rowe B,
Farrall M, Barnett AH, Bain SC, Todd JA: A genome-wide search for human type 1
diabetes susceptibility genes. Nature371
: 130-136,1994[Medline]
-
Merriman T, Twells R, Merriman M, Eaves I, Cox R, Cucca F, McKinney
P, Shield J, Baum D, Bosi E, Pozzilli P,
Nisticò L, Buzzetti R, Joner G, Ronningen K,
Thorsby E, Undlien D, Pociot F, Nerup J, Bain S, Barnett A, Todd J: Evidence
by allelic association-dependent methods for a type 1 diabetes polygene
(IDDM6) on chromosome 18q21. Hum Mol Genet6
: 1003-1010,1997[Abstract/Free Full Text]
-
Merriman TR, Eaves IA, Twells RC, Merriman ME, Danoy PA, Muxworthy
CE, Hunter KM, Cox RD, Cucca F, McKinney PA, Shield JP, Baum JD, Tuomilehto J,
Tuomilehto-Wolf E, Ionesco-Tirgoviste C, Joner G, Thorsby E, Undlien DE,
Pociot F, Nerup J, Ronningen KS, Bain SC, Todd JA: Transmission of haplotypes
of microsatellite markers rather than single marker alleles in the mapping of
a putative type 1 diabetes susceptibility gene (IDDM6).
Hum Mol Genet 7:517
-524, 1998[Abstract/Free Full Text]
-
Wadsworth EJK, Shield JPH, Hunt LP, Baum JD: A case-control study
of environmental factors associated with diabetes in the under 5s.
Diabet Med 14:390
-396, 1997[Medline]
-
Lernmark A, Ducat L, Eisenbarth G, Ott J, Permutt MA, Rubenstein P,
Spielman R: Family cell lines available for research. Am J Hum
Genet 47:1028
-1030, 1990[Medline]
-
Pociot F, Norgaard K, Hobolth N, Andersen O, Nerup J: A nationwide
population-based study of the familial aggregation of type 1
(insulin-dependent) diabetes mellitus in Denmark.
Diabetologia 36:870
-875, 1993[Medline]
-
Kristiansen OP, Zamani M, Johannesen J, Mandrup-Poulsen T, Cassiman
JJ, Nerup J, Pociot F: Linkage and association between a CD4 gene polymorphism
and IDDM in Danish IDDM patients. Diabetes47
: 281-283,1998[Medline]
-
Marrosu MG, Murru MR, Costa G, Murru R, Muntoni F, Cucca F:
DRB1-DQA1-DQB1 loci and multiple sclerosis predisposition in the Sardinian
population. Hum Mol Genet 7:1235
-1237, 1998[Abstract/Free Full Text]
-
Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC,
Johnson KP, Sibley WA, Silberberg DH, Tourtellotte WW: New diagnostic criteria
for multiple sclerosis: guidelines for research protocols. Ann
Neurol 13:227
-231, 1983[Medline]
-
Kong X-T, Choi SH, Inoue A, Xu F, Chen T, Takita J, Yokota J,
Bessho F, Yanagisawa M, Hanada R, Yamamoto K, Hayashi Y: Expression and
mutational analysis of the DCC, DPC4, and MADR2/JV18-1 genes in neuroblastoma.
Cancer Res 57:3772
-3778, 1997[Abstract]
-
Reed PW, Davies JL, Copeman JB, Bennett ST, Palmer SM, Pritchard
LE, Gough SCL, Kawaguchi Y, Cordell HJ, Balfour KM, Jenkins SC, Powell EE,
Vignal A, Todd JA: Chromosome-specific microsatellite sets for
fluorescence-based, semi-automated genome mapping. Nat
Genet 7: 390-395,1994[Medline]
-
Tippett LHC: The Methods of Statistics. 4th
ed., revised. London, Benn, Williams and Norgate, 1952, p.159
-
Fisher RA: Statistical Methods for Research
Workers. London, Oliver and Boyd, 1932
-
Hedges LV, Olkin I: Statistical Methods for
Meta-Analysis. New York, Academic Press, 1985, p.28
-
Ott J: Analysis of Human Genetic Linkage(revised edition). Baltimore, MD, Johns Hopkins University Press,1991
-
Gulko PS, Kawahito Y, Remmers EF, Reese VR, Wang J, Dracheva SV, Ge
L, Longman RE, Shepard JS, Cannon GW, Sawitzke AD, Wilder RL, Griffiths MM:
Identification of a new non-major histocompatibility complex genetic locus on
chromosome 2 that controls disease severity in collagen-induced arthritis in
rats. Arthritis Rheum 41:2122
-2131, 1998[Medline]
-
Kawahito Y, Cannon GW, Gulko PS, Remmers EF, Longman RE, Reese VR,
Wang J, Griffiths MM, Wilder RL: Localization of quantitative trait loci
regulating adjuvant-induced arthritis in rats: evidence for genetic factors
common to multiple autoimmune diseases. J Immunol161
: 4411-4419,1998[Abstract/Free Full Text]
-
Salström JL, Furuya T, Cannon GW,
Remmers EF, Griffiths MM, Wilder RL: Rat models of autoimmune diseases: the
genetic dissection of complex traits (Abstract). Am J Hum
Genet 65 (Suppl.):A467
, 1999
-
Furuya T, Salström JL, Cannon GW,
Remmers EF, Griffiths MM, Wilder RL: Identification of three new non-MHC
genomic regions controlling collagen-induced arthritis (CIA) in rats with a
shared epitope. Arthritis Rheum42
(Suppl.): S383,1999
-
Dahlman I, Jacobsson L, Glaser A, Lorentzen JC, Andersson M,
Luthman H, Olsson T: Genome-wide linkage analysis of chronic relapsing
experimental autoimmune encephalomyelitis in the rat identifies a major
susceptibility locus on chromosome 9. J Immunol162
: 2581-2588,1999[Abstract/Free Full Text]
-
Mähler M, Bristol IJ, Sundberg JP,
Churchill GA, Birkenmeier EH, Elson CO, Leiter EH: Genetic analysis of
susceptibility to dextran sulfate sodium-induced colitis in mice.
Genomics 55:147
-156, 1999[Medline]
-
Butterfield RJ, Sudweeks JD, Blankenhorn EP, Korngold R, Marini JC,
Todd JA, Roper RJ, Teuscher C: New genetic loci that control susceptibility
and symptoms of experimental allergic encephalomyelitis in inbred mice.
J Immunol 161:1860
-1867, 1998[Abstract/Free Full Text]
-
Yang H-T, Jirholt J, Svensson L, Sundvall M, Jansson L, Pettersson
U, Holmdahl R: Identification of genes controlling collagen-induced arthritis
in mice: striking homology with susceptibility loci previously identified in
the rat. J Immunol 163:2916
-2921, 1999[Abstract/Free Full Text]
-
Martin A-M, Blankenhorn EP, Maxson MN, Zhao M, Leif J, Mordes JP,
Greiner DL: Non-major histocompatibility complex-linked diabetes
susceptibility loci on chromosomes 4 and 13 in a backcross of the DP-BB/Wor
rat to the WF rat. Diabetes 48:50
-58, 1999[Abstract]
-
Ghosh S, Palmer SM, Rodrigues NR, Cordell HJ, Hearne CM, Cornall
RJ, Prins J-B, McShane P, Lathrop GM, Peterson LB, Wicker LS, Todd JA:
Polygenic control of autoimmune diabetes in nonobese mice. Nat
Genet 4: 404-409,1993[Medline]
-
de Gouyon B, Melanitou E, Richard MF, Requart M, Hahn IH, Guenet
JL, Demenais F, Julier C, Lathrop GM, Boitard C, Avner P: Genetic analysis of
diabetes and insulitis in an interspecific cross of the nonobese diabetic
mouse with Mus spretus. Proc Natl Acad Sci U S A90
: 1877-1881,1993[Abstract]
-
Yokoi N, Kanazawa M, Kitada K, Tanaka A, Kanazawa Y, Suda S, Ito H,
Serikawa T, Komeda K: A non-MHC locus essential for autoimmune type 1 diabetes
in the Komeda diabetes-prone rat. J Clin Invest8
: 2015-2021,1997
-
Encinas JA, Lees MB, Sobel RA, Symonowicz C, Greer JM, Shovlin CL,
Weiner HL, Cousin K, Bell RB, Hader W, Paty DW, Hashimoto S, Oger J, Duquette
P, Warren S, Gray T, O'Connor P, Nath A, Auty A, Metz L, Francis G, Paulseth
JE, Murray TJ, Pryse-Phillips W, Nelson R, Freedman M, Brunet D, Bouchard J-P,
Hinds D, Risch N: Genetic analysis of susceptibility to experimental
autoimmune encephalomyelitis in a cross between SJL/J and B10.S mice.
J Immunol 157:2186
-2192, 1996[Abstract]
-
Baker D, Rosenwasser OA, O'Neill JK, Turk JL: Genetic analysis of
experimental allergic encephalomyelitis in mice. J
Immunol 155:4046
-4051, 1995[Abstract]
-
Croxford JL, O'Neill JK, Baker D: Polygenic control of experimental
autoimmune encephalomyelitis in Biozzi ABH and BALB/c mice. J
Neuroimmunol 74:205
-211, 1997[Medline]
-
Sundvall M, Jirholt J, Yang H-T, Jansson L, Engstrom A, Pettersson
U, Holmdahl R: Identification of murine loci associated with susceptibility to
chronic experimental autoimmune encephalomyelitis. Nat
Genet 10:313
-318, 1995[Medline]
-
Roth M-P, Viratelle C, Dolbois L, Delverdier M, Borot N, Pelletier
L, Druet P, Clanet M, Coppin H: A genome-wide search identifies two
susceptibility loci for experimental autoimmune encephalomyelitis on rat
chromosomes 4 and 10. J Immunol162
: 1917-1922,1999[Abstract/Free Full Text]
-
Drake CG, Babcock SK, Palmer E, Kotzin BL: Genetic analysis of the
NZB contribution to lupus-like autoimmune disease in (NZB x
NZW)F1 mice. Proc Natl Acad Sci U S A91
: 4062-4066,1994[Abstract]
-
Vyse TJ, Halterman RK, Rozzo SJ, Izui S, Kotzin BL: Control of
separate pathogenic autoantibody responses marks MHC contributions to murine
lupus. Proc Natl Acad Sci U S A96
: 8098-8103,1999[Abstract/Free Full Text]
-
Kono DH, Burlingame RW, Owens DG, Kuramochi A, Balderas RS,
Balomenos D, Theofilopoulos AN: Lupus susceptibility loci in New Zealand mice.
Proc Natl Acad Sci U S A 91:10168
-10172, 1994[Abstract/Free Full Text]
-
Vidal S, Kono DH, Theofolipoulos AN: Loci predisposing to
autoimmunity in MRL-Faslpr and
C57BL/6-Faslpr mice. J Clin Invest101
: 696-702,1998[Abstract/Free Full Text]
-
Remmers E, Longman RE, Du Y, O'Hare A, Cameron GW, Griffiths MM,
Wilder RL: A genome scan localizes five non-MHC loci controlling
collagen-induced arthritis in rats. Nat Genet14
: 82-85,1996[Medline]
-
Vingsbo-Lundberg C, Nordquist N, Olofsson P, Sundvall M, Saxne T,
Pettersson U, Holmdahl R: Genetic control of arthritis onset, severity and
chronicity in a model for rheumatoid arthritis in rats. Nat
Genet 20:401
-404, 1998[Medline]
-
Jirholt J, Cook A, Emahazion T, Sundvall M, Jansson L, Nordquist N,
Pettersson U, Holmdahl R: Genetic linkage analysis of collagen-induced
arthritis in mouse. Eur J Immunol28
: 3321-3328,1998[Medline]
-
Otto JM, Cs-Szabó G, Gallagher J,
Velins S, Mikecz K, Buzás EI, Enders JT, Olsen
BR, Glant TT: Identification of multiple loci linked to inflammation and
autoantibody production by a genome scan of a murine model of rheumatoid
arthritis. Arthritis Rheum 42:2524
-2531, 1999[Medline]
-
Meeker ND, Hickey WF, Korngold R, Hansen WK, Sudweeks JD, Wardell
BB, Griffith JS, Teuscher C: Multiple loci govern the bone marrow-derived
immuno-regulatory mechanism controlling dominant resistance to autoimmune
orchitis. Proc Natl Acad Sci U S A92
: 5684-5688,1995[Abstract]
-
Sun S-H, Silver PB, Caspi RR, Du Y, Chan C-C, Wilder RL, Remmers
EF: Identification of genomic regions controlling experimental autoimmune
uveoretinitis in rats. Int Immunol11
: 529-534,1999[Abstract/Free Full Text]
-
Nishihara M, Terada M, Kamogawa J, Ohashi Y, Mori S, Nakatsuru S,
Nakamura Y, Nose M: Genetic basis of autoimmune sialadenitis in MRL/lpr
lupus-prone mice: additive and hierarchical properties of polygenic
inheritance. Arthritis Rheum42
: 2616-2623,1999[Medline]
-
Greco L, Corazza G, Babron MC, Clot F, Fulchignoni-Lataud MC,
Percopo S, Zavattari P, Bouguerra F, Dib C, Tosi R, Troncone R, Ventura A,
Mantavoni W, Magazzu G, Gatti R, Lazzari R, Giunta A, Perri F, Iacono G, Cardi
E, de Virgiliis S, Cataldo F, de Angelis G, Musumeci S, Ferrari R, Balli F,
Bardella M-T, Volta U, Catassi C, Torre G, Eliaou J-F, Serre J-L,
Clerget-Darpoux F: Genome search in celiac disease. Am J Hum
Genet 62:669
-675, 1998[Medline]
-
Zhong F, McCombs CC, Olson JM, Elston RC, Stevens FM, McCarthy CF,
Michalski JP: An autosomal screen for genes that predispose to celiac disease
in the western counties of Ireland. Nat Genet14
: 329-333,1996[Medline]
-
Satsangi J, Parkes M, Louis E, Hashimoto L, Kato N, Welsh K,
Terwilliger JD, Lathrop GM, Bell JI, Jewell DP: Two stage genome-wide search
in inflammatory bowel disease provides evidence for susceptibility loci on
chromosomes 3, 7 and 12. Nat Genet14
: 199-202,1996[Medline]
-
Cho JH, Nicolae DL, Gold LH, Fields CT, LaBuda MC, Rohal PM,
Pickles MR, Qin L, Fu Y, Mann JS, Kirschner BS, Jabs EW, Weber J, Hanauer SB,
Bayless TM, Brant SR: Identification of novel susceptibility loci for
inflammatory bowel disease on chromosomes 1p, 3q and 4q: evidence for
epistasis between 1p and IBD1. Proc Natl Acad Sci U S
A 95: 7502-7507,1998[Abstract/Free Full Text]
-
Hampe J, Schreiber S, Shaw SH, Lau KF, Bridger S, Macpherson AJS,
Cardon LR, Sakul H, Harris TJR, Buckler A, Hall J, Stokkers P, van Deventer
SJH, Nürnberg P, Mirza MM, Lee JCW,
Lennard-Jones JE, Mathew CG, Curran ME: A genomewide analysis provides
evidence for novel linkages in inflammatory bowel disease in a large European
cohort. Am J Hum Genet 64:808
-816, 1999[Medline]
-
Hugot J-P, Laurent-Puig P, Gower-Rousseau C, Olson JM, Lee JC,
Beaugerie L, Naom I, Dupas J-L, Gossum AV, Groupe d'Etude
Thérapeutique des Affections Inflammatoires
Digestives, Orholm M, Boniati-Pellie C, Weissenbach J, Mathew CG,
Lennard-Jones JE, Cortot A, Colombel J-F, Thomas G: Mapping of a
susceptibility locus for Crohn's disease on chromosome 16.
Nature 379:821
-823, 1996[Medline]
-
Ma Y, Ohmen JD, Li Z, Bentley LG, McElree C, Pressman S, Targan SR,
Fischel-Ghodsian N, Rotter JI, Yang H: A genome-wide search identifies
potential new susceptibility loci for Crohn's disease. Inflamm
Bowel Dis 5:271
-278, 2000
-
Duerr RH, Barmada MM, Zhang L,
Pfützer R, Weeks DE: High-density genome scan in
Crohn disease shows confirmed linkage to chromosome 14q11-12. Am J
Hum Genet 66:1857
-1862, 2000[Medline]
-
Rioux JD, Silverberg MS, Daly MJ, Steinhart AH, McLeod RS,
Griffiths AM, Green T, Brettin TS, Stone V, Bull SB, Bitton A, Williams CN,
Greenberg GR, Cohen Z, Lander ES, Hudson TJ, Siminovitch KA: Genomewide search
in Canadian families with inflammatory bowel disease reveals two novel
susceptibility loci. Am J Hum Genet66
: 1863-1870,2000[Medline]
-
Gaffney PM, Ortmann WA, Selby SA, Shark KB, Ockenden TC, Rohlf KE,
Walgrave NL, Boyum WP, Malmgren ML, Miller ME, Kearns GM, Messner RP, King RA,
Rich SS, Behrens TW: Genome screening in human systemic lupus erythematosus:
results from a second Minnesota cohort and combined analyses of 187 sib-pair
families. Am J Hum Genet 66:547
-556, 2000[Medline]
-
Moser KL, Neas BR, Salmon JE, Yu H, Gray-McGuire C, Asundi N,
Bruner GR, Fox J, Kelly J, Henshall S, Bacino D, Dietz M, Hogue R, Koelsch G,
Nightingale L, Shaver T, Abdou NI, Albert DA, Carson C, Petri M, Treadwell EL,
James JA, Harley JB: Genome scan of human systemic lupus erythematosus:
evidence for linkage on chromosome 1q in African-American pedigrees.
Proc Natl Acad Sci U S A 95:14869
-14874, 1998[Abstract/Free Full Text]
-
Shai R, Quismorio FP Jr, Li L, Kwon O-J, Morrison J, Wallace DJ,
Neuwelt CM, Brautbar C, Gauderman WJ, Jacob CO: Genome-wide screen for
systemic lupus erythematosus susceptibility genes in multiplex families.
Hum Mol Genet 8:639
-644, 1999[Abstract/Free Full Text]
-
Kuokkanen S, Gschwend M, Rioux JD, Daly MJ, Terwilliger JD, Tienari
PJ, Wikström J, Palo J, Stein LD, Hudson TJ,
Lander ES, Peltonen L: Genome-wide scan of multiple sclerosis in Finnish
multiplex families. Am J Hum Genet61
: 1379-1387,1997[Medline]
-
The Multiple Sclerosis Genetics Group: A complete genomic screen
for multiple sclerosis underscores a role for the major histocompatibility
complex. Nat Genet 13:469
-471, 1996[Medline]
-
Sawcer S, Jones HB, Feakes R, Gray J, Smaldon N, Chataway J,
Robertson N, Clayton D, Goodfellow PN, Compston A: A genome screen in multiple
sclerosis. Nat Genet 13:464
-468, 1996[Medline]
-
Ebers GC, Kukay K, Bulman DE, Sadovnick AD, Rice G, Anderson C,
Armstrong H, Cousin K, Bell RB, Hader W, Paty DW, Hashimoto S, Oger J,
Duquette P, Warren S, Gray T, O'Connor P, Nath A, Auty A, Metz L, Francis G,
Paulseth JE, Murray TJ, Pryse-Phillips W, Nelson R, Freedman M, Brunet D,
Bouchard J-P, Hinds D, Risch N: A full genome search in multiple sclerosis.
Nat Genet 13:472
-476, 1996[Medline]
-
Cornelis F, Faure S, Martinez M, Prud'homme JF, Fritz P, Dib C,
Alves H, Barrera P, de Vries N, Balsa A, Pascual-Salcedo D, Maenaut K,
Westhovens R, Migliorini P, Tran TH, Delaye A, Prince N, Lefevre C, Thomas G,
Poirier M, Soubigou S, Alibert O, Lasbleiz S, Fouix S, Bouchier C, Liote F,
Loste M-N, Lepage V, Charron D, Gyapay G, Lopes-Vaz A, Kuntz D, Bardin T,
Weissenbach J: New susceptibility locus for rheumatoid arthritis suggested by
a genome-wide linkage study. Proc Natl Acad Sci U S A95
: 10746-10750,1998[Abstract/Free Full Text]
-
Jawaheer D, Costello T, Amos C, Monteiro J, Seldin M, Criswell L,
Bridges SL, Schroeder H, Pisetsky D, Kastner D, Wilder R, Pope R, Clegg D,
Ward R, Albani S, Nelson JL, Wener M, Callahan L, Pincus T, Gregersen PK:
Analysis of affected sibling pairs with rheumatoid arthritis: the North
American rheumatoid arthritis consortium (Abstract). Am J Hum
Genet 65 (Suppl.):A276
, 1999
-
Nair RP, Henseler T, Jenisch S, Stuart S, Bichakjian CK, Lenk W,
Westphal E, Guo S-W, Christophers E, Voorhees JJ, Elder JT: Evidence for two
psoriasis susceptibility loci (HLA and 17q) and two novel candidate regions
(16q and 20p) by genome-wide scan. Hum Mol Genet6
: 1349-1356,1997[Abstract/Free Full Text]
-
Trembath RC, Clough RL, Rosbotham JL, Jones AB, Camp RDR, Frodsham
A, Browne J, Barber R, Terwilliger J, Lathrop GM, Barker JNWN: Identification
of a major susceptibility locus on chromosome 6p and evidence for further
disease loci revealed by two stage genome-wide search in psoriasis.
Hum Mol Genet 6:813
-820, 1997[Abstract/Free Full Text]
-
Samuelsson L, Enlund F, Torinsson A, Yhr M, Inerot A,
Enerbäck C,
Wahlström J, Swanbeck G, Martinsson T: A
genome-wide search for genes predisposing to familial psoriasis by using a
stratification approach. Hum Genet105
: 523-529,1999[Medline]
-
Hashimoto L, Habita C, Beressi JP, Delepine M, Besse C,
Cambon-Thomsen A, Deschamps I, Rotter JI, Djoulah S, James MR, Froguel P,
Weissenbach J, Lathrop GM, Julier C: Genetic mapping of a susceptibility locus
for insulin-dependent diabetes mellitus on chromosome 11q.
Nature 371:161
-164, 1994[Medline]
-
Tomer Y, Barbesino G, Greenberg DA, Concepcion E, Davies TF:
Mapping the major susceptibility loci for familial Graves' and Hashimoto's
diseases: evidence for genetic heterogeneity and gene interactions.
J Clin Endocrinol Metab 84:4656
-4664, 1999[Abstract/Free Full Text]
-
Morel L, Rudofsky UH, Longmate J, Schiffenbauer J, Wakeland EK:
Polygenic control of susceptibility to murine systemic lupus erythematosus.
Immunity 1:219
-229, 1994[Medline]
-
McAleer M, Reifsnyder P, Palmer SM, Prochazka M, Love JM, Copeman
JB, Powell EE, Rodrigues NR, Prins J-B, Serreze DV, DeLarato NH, Wicker LS,
Peterson LB, Schork NJ, Todd JA, Leiter EH: Crosses of NOD mice with the
related NON strain: a polygenic model for IDDM.
Diabetes 44:1186
-1195, 1995[Abstract]
-
Drake CG, Rozzo SJ, Hirschfield HF, Smarnworawong NP, Palmer E,
Kotzin BL: Analysis of the New Zealand black contribution to lupus-like renal
disease: multiple genes that operate in a threshold manner. J
Immunol 154:2441
-2447, 1995[Abstract/Free Full Text]
-
Hogarth MB, Slingsby JH, Allen PJ, Thompson EM, Chandler P, Davies
KA, Simpson E, Morley BJ, Walport MJ: Multiple lupus susceptibility loci map
to chromosome 1 in BXSB mice. J Immunol161
: 2753-2761,1998[Abstract/Free Full Text]
-
Santiago M-L, Mary C, Parzy D, Jacquet C, Montagutelli X, Parkhouse
RME, Lemoine R, Izui S, Reininger L: Linkage of a major quantitative trait
locus to Yaa gene-induced lupus-like nephritis in (NZW x
C57BL/6)F1 mice. Eur J Immunol28
: 4257-4267,1998[Medline]
-
Silveira PA, Baxter AG, Cain WE, van Driel IR: A major linkage
region on distal chromosome 4 confers susceptibility to mouse autoimmune
gastritis. J Immunol 162:5106
-5111, 1999[Abstract/Free Full Text]
-
Klöting I, Vogt L, Serikawa T: Locus
on chromosome 18 cosegregates with diabetes in the BB/OK rat subline.
Diabetes Metab 21:338
-344, 1995
-
Klöting I, Schmidt S, Kovacs P:
Mapping of novel genes predisposing or protecting diabetes development in the
BB/OK rat. Biochem Biophys Res Commun245
: 483-486,1998[Medline]
-
Vaidya B, Imrie H, Perros P, Young ET, Kelly WF, Carr D, Large DM,
Toft AD, Kendall-Taylor P, Pearce SHS: Evidence for a new Graves' disease
susceptibility locus at chromosome 18q21. Am J Hum
Genet 66:1710
-1714, 2000[Medline]
-
Wise LH, Lanchbury JS, Lewis CM: Meta-analysis of genome searches.
Ann Hum Genet 63:263
-272, 1999[Medline]
-
Spielman R, McGinnis R, Ewens W: Transmission test for linkage
disequilibrium: the insulin gene region and insulin-dependent diabetes
mellitus (IDDM). Am J Hum Genet52
: 506-516,1993[Medline]
-
Martin ER, Kaplan NL, Weir BS: Tests for linkage and association in
nuclear families. Am J Hum Genet61
: 439-448,1997[Medline]
-
Dudbridge F, Koeleman PC, Todd JA, Clayton DG: Unbiased application
of the transmission/disequilibrium test to multilocus haplotypes.
Am J Hum Genet 66:2009
-2012, 2000[Medline]
-
Curtis D: Use of siblings as controls in case-control association
studies. Ann Hum Genet 61:319
-323, 1997[Medline]
-
Curtis D, Sham PC: A note on the application of the transmission
disequilibrium test when a parent is missing. Am J Hum
Genet 56:811
-812, 1995[Medline]
-
Devlin B, Risch N: A comparison of linkage disequilibrium measures
for finescale mapping. Genomics29
: 311-322,1995[Medline]
-
Risch N, Merikangas K: The future of genetic studies of complex
human diseases. Science 273:1516
-1517, 1996[Medline]
-
Lander E, Kruglyak L: Genetic dissection of complex traits:
guidelines for interpreting and reporting linkage results. Nat
Genet 11:241
-247, 1995[Medline]
-
Dahlman I, Wallström E, Weissert R,
Storch M, Kornek B, Luthman H, Lassman H, Linington C, Olsson T: Linkage
analysis of myelin oligodendrocyte glycoprotein-induced experimental
autoimmune encephalomyelitis in the rat identifies a susceptibility locus for
demyelination on chromosome 18. Hum Mol Genet8
: 2183-2190,1999[Abstract/Free Full Text]
-
Bureau J-F, Montagutelli X, Bihl F, Lefebvre S, Guenet J-L, Brahic
M: Mapping loci influencing the persistence of Theiler's virus in the murine
central nervous system. Nat Genet5
: 87-91,1993[Medline]
-
Mehlen P, Rabizadeh S, Snipas SJ, Assa-Munt N, Salvesen GS,
Bredesen DE: The DCC gene product induces apoptosis by a mechanism requiring
receptor proteolysis. Nature395
: 801-804,1998[Medline]
-
Eppert K, Scherer SW, Ozcelik H, Pirone R, Hoodless P, Kim H, Tsui
L-C, Bapat B, Gallinger S, Andrulis IL, Thomsen GH, Wrana JL, Attisano L:
MADR2 maps to 18q21 and encodes a TGFß-regulated MAD-related
protein that is functionally mutated in colorectal carcinoma.
Cell 86:543
-552, 1996[Medline]
-
Goldstein DR, Sain SR, Guerra R, Etzel CJ: Meta-analysis by
combining parameter estimates: simulated linkage studies. Genet
Epidemiol 17 (Suppl. 1):S581
-S586, 1999[Medline]
-
Guerra R, Etzel CJ, Goldstein DR, Sain SR: Meta-analysis by
combining P-values: simulated linkage studies. Genet
Epidemiol 17 (Suppl. 1):S605
-S609, 1999[Medline]