A Kong

D Jawaheer

GR Abecasis

JL Newton

JM Biernacka

Joanna Biernacka

K MacKay

L Sun

Lingwei Sun

M Pascual

P Armitage

Richard Sherva

Rosalind Neuman

W Brintnell

W Klitz

BMC Proceedings

Crossref

BioMed CentralBMC Proceedings
ssOpen AcceProceedings
No evidence for multiple loci affecting rheumatoid arthritis risk on 
chromosome 6p21
Richard Sherva*†1, Lingwei Sun†1, Joanna Biernacka†2 and 
Rosalind Neuman†1
Address: 1Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, Missouri 63104, USA and 
2Institute of Human Genetics, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, NE1 3BZ, UK
Email: Richard Sherva* - shervar@wustl.edu; Lingwei Sun - lsun@hardy.wustl.edu; Joanna Biernacka - joanna.biernacka@mayo.edu; 
Rosalind Neuman - roz@psychiatry.wustl.edu
* Corresponding author    †Equal contributors
Abstract
The influence of certain alleles of the HLA-DRB1 locus on risk for rheumatoid arthritis has been
well established through linkage and association studies. In addition, other loci in the HLA region
on 6p21 may also affect an individual's risk profile. Here, we used a method to detect excess
identity-by-descent sharing between affected sib pairs conditional on the observed genotypes at the
hypothesized causal locus to test for the presence of additional arthritis risk loci in the linked
region. We used affected sib pairs from two different studies. Because the test depends heavily on
specifying accurate allele frequency estimates at the proposed causal locus, we used HLA-DRB1
allele frequency estimates from a large, population-based sample. We also discuss an alternate form
of the test in which we could condition on parental genotypes, thereby eliminating the need for
actual allele frequencies. The test showed no evidence for the presence of additional arthritis risk
loci in the region in the British or North American samples made available for Genetic Analysis
Workshop 15. Given the prior knowledge that there likely are arthritis risk loci other than HLA-
DRB1 in the region, it appears the tests may have inadequate power to detect the presence of these
loci in certain cases.
from Genetic Analysis Workshop 15
St. Pete Beach, Florida, USA. 11–15 November 2006
Published: 18 December 2007
BMC Proceedings 2007, 1(Suppl 1):S42
<supplement> <title> <p>Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci</p> </title> <editor>Heather J Cordell, Mariza de Andrade, Marie-Claude Babron, Christopher W Bartlett, Joseph Beyene, Heike Bickeböller, Robert Culverhouse, Adrienne Cupples, E Warwick Daw, Josée Dupuis, Catherine T Falk, Saurabh Ghosh, Katrina A Goddard, Ellen L Goode, Elizabeth R Hauser, Lisa J Martin, Maria Martinez, Kari E North, Nancy L Saccone, Silke Schmidt, William Tapper, Duncan Thomas, David Tritchler, Veronica J Vieland, Ellen M Wijsman, Marsha A Wilcox, John S Witte, Qio g Yang, Andreas Ziegler, Laura Almasy a d Jean W MacCluer</editor> <note>Proce dings</note> <url>http://www.biomedc ntral.com/content/pdf/1753-6561-1-S1-info.pdf</url> </supplement>
This article is available from: http://www.biomedcentral.com/1753-6561/1/S1/S42
© 2007 Sherva et al; licensee BioMed Central Ltd. 
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), 
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 4
(page number not for citation purposes)
BMC Proceedings 2007, 1(Suppl 1):S42 http://www.biomedcentral.com/1753-6561/1/S1/S42Background
There is substantial evidence from linkage and association
studies for a locus contributing to rheumatoid arthritis
(RA) risk on chromosome 6p21. The HLA-DRB1 locus
may be the sole cause of this linkage signal, but given the
complexity of the HLA region and autoimmune function,
other polymorphisms in the region could also influence
RA risk. In addition, previous research suggests the pres-
ence of other RA risk loci in the region [1-3]. The analysis
presented in this paper uses the method proposed by Sun
et al. [4] to test the null hypothesis that HLA-DRB1 geno-
type is the sole cause of the observed linkage signal.
Methods
For these analyses we used data from two RA studies, the
North American Rheumatoid Arthritis Consortium
(NARAC), and The Arthritis and Rheumatism Council's
UK National Repository of family material. Details about
the designs of these studies are published elsewhere [5-7],
but briefly, the NARAC investigators recruited and geno-
typed families with two or more siblings with RA, and the
UK repository pooled a cohort of Caucasian, RA-affected
sibling pairs (ASPs).
We initially used Merlin [8] to confirm the RA linkage sig-
nal on chromosome 6 with a nonparametric linkage
(NPL) statistic [9] in the NARAC and UK data. We also
confirmed the association between HLA-DRB1 genotype
and RA in the NARAC data set using correlated data cor-
rected logistic regression in SAS PROC GENMOD with
HLA-DRB1 modeled as the number of "high-risk" alleles
(0, 1, or 2). High-risk alleles were identified based on the
work of Newton et al. [10]. This analysis could not be per-
formed in the UK data because all genotyped sibs are
affected. An Armitage trend test [11] in SAS Genetics was
used to test for association between SNPs in the region
and RA. Linkage disequilibrium between the HLA-DRB1
locus and surrounding markers was estimated using
MIDAS http://www.genes.org.uk/software/midas.
We used the method described by Sun et al. [4] to deter-
mine whether the HLA-DRB1 locus is the sole cause of the
observed linkage in the region. The test is designed to
detect excess identity-by-descent (IBD) sharing between
ASPs conditional on the observed genotypes at the
hypothesized causal locus. The method is based on the
fact that under the null hypothesis that the candidate
marker is the sole causal site in the region,
PrH0(I|GC, ASP) = Pr(I|GC), (1)
where PrH0 is the probability that the hypothesized causal
marker is the sole cause of the linkage signal, I is the IBD
sharing for a sib pair at the candidate locus, and GC indi-
cates the sibs' genotype configuration at the locus. Sun et
al. use the distribution of IBD sharing between affected
sibs given the sibs' genotypes at the candidate locus, GC,
(which depends on allele frequencies at the candidate
locus) to obtain the null conditional mean sharing, μG,
which is equal to EH0[S], and variance, σG2, which is equal
to VarH0[S] for some IBD sharing statistic S. A variation of
the usual NPL score statistic or the linear or exponential
likelihood of Kong and Cox [9] based on the standardized
family score statistics Z = {S - μG}/σG is then used to assess
evidence against H0. We used population allele frequen-
cies from published results by Klitz et al. [12] from a study
of 1000 randomly selected North American Caucasian
donors. When multiple ASP were present in a family, one
was randomly chosen from each family in the NARAC and
UK data set for this analysis, and pairs with informative
genotypes (at least one shared DRB1 allele) were given
weights based on σG. To obtain the actual sharing between
sibs, we used Merlin [8] to calculate IBD probabilities at
the DRB1 locus based on DRB1 genotype as well as the
genotypes at flanking markers. To compute S, we summed
the products of the probabilities and the number of alleles
shared IBD.
We also considered a modified version of the method of
Sun et al. proposed by Biernacka et al. [13]. In this modi-
fied method, conditioning on the parental genotypes
avoids the problem having to specify allele frequencies in
the analysis. In the modified method, GC in Eq. (1) is
replaced by the parental and ASP genotypes, {GP, GC},
and μG and σG are based on the IBD distribution given the
ASP and parental candidate SNP genotypes.
Results
Using both the NARAC and UK data, we confirmed the
evidence for linkage to RA on chromosome 6. The peak
LOD score in NARAC families was at marker D6S1629
(47.7 cM, LOD = 14.36, p = 4.28 × 10-16), and the peak
score in the UK families was at marker D6S276 (44.4 cM,
LOD = 4.28, p = 9.01 × 10-6). We also confirmed the asso-
ciation of HLA-DRB1 alleles with RA in the NARAC data
set. In NARAC families, the odds ratio for each additional
risk allele was 18.2, (p < 0.0001). One SNP, rs910516, is
located approximately 5 Mb from D6S1629 and suggests
association with RA in the NARAC data (p = 0.01). There
is significant LD between D6S1629 and HLA-DRB1 alle-
les; only one high-risk allele (1402), however, is in signif-
icant LD with an allele (3) of D6S1629 (D' = 0.64).
The Sun et al. test in the HLA-DRB1 region, computed in
452 Caucasian ASPs from the NARAC data failed to reject
the null (T = -0.2, p = 0.58), suggesting that the HLA-DRB1
locus may be the sole contributor to the linkage signal. We
got a similar result in the 309 ASP from the UK data (T =
-0.6, p = 0.73). Table 1 summarizes the results from the
analyses in both data sets.Page 2 of 4
(page number not for citation purposes)
BMC Proceedings 2007, 1(Suppl 1):S42 http://www.biomedcentral.com/1753-6561/1/S1/S42Discussion
The results of our analyses provided no evidence for the
presence of genetic sharing in excess of what could be
explained by the DRB1 locus, making it unclear whether
DRB1 is the sole RA causal locus in the HLA region on
chromosome 6. The analyses may have had insufficient
power to detect the effects of additional loci near the
DRB1 locus. First, the samples used in these analyses are
not particularly large. More importantly, the method of
Sun et al. is known to have low power for highly inform-
ative candidate loci [4]. The fact that the DRB1 locus is
highly polymorphic decreases the power of the Sun et al.
test statistic due to the fact that power depends highly on
the value of EA[S|G] - EH0[S|G], where E is the conditional
expected value under the true genetic model, S is the shar-
ing statistic, and G is the siblings' genotype configuration
at the hypothesized causal locus. When G provides close
to complete information on S, as is more likely with a
highly polymorphic marker, power to detect sharing in
excess of that due to the hypothesized causal locus is low.
In the simulated Genetic Analysis Workshop 15 data,
Biernacka et al. found that their modified version of the
Sun method had little power to detect effects of additional
loci after accounting for the effect of DRB1 [13]. For a
detailed discussion of factors that affect the power of the
Sun method, see [4].
We did a simple calculation to determine the effect size
that would have allowed us to reject H0 in the NARAC
data. Using the actual null conditional variances of the
observed allele sharing in the sibs, we would need an aver-
age difference between the actual and null conditional
sharing of 0.04 across the 452 ASP to reject H0 at p = 0.05.
In the NARAC families, only 178 out of 452 selected ASP
provide evidence against H0. The remaining pairs show
less sharing than expected under the null, and therefore
diminished the magnitude of the overall test statistic.
We also considered a modified version of the Sun et al.
method proposed by Biernacka et al. [13]. Although too
few parental genotypes were available in this data set to
make direct comparisons between methods, this
approach might be useful in situations in which parents
are genotyped and no reliable population allele frequency
estimates are available.
It should also be noted that the coding system used for
HLA-DRB1 alleles in this data set was not identical to that
used in other published literature. Several alleles found in
these families were coded differently than in published lit-
erature and more refined typing was performed in some
families than in others. In these cases, alleles had to be
combined into broader categories to make use of the pub-
lished [12] allele frequencies. This has implications for
our results because the accuracy of sharing information is
diminished when alleles are combined. Clarification and/
or consistency in the genotyping methods and allele cod-
ing used would be needed to make full use of the data.
Conclusion
Given the previous evidence suggesting additional RA risk
loci on 6p21, it appears that the Sun et al. test for over-
sharing may be underpowered to detect additional genetic
effects in the region containing the DRB1 locus in these
data.
Competing interests
The author(s) declare that they have no competing inter-
ests.
Acknowledgements
This article has been published as part of BMC Proceedings Volume 1 Sup-
plement 1, 2007: Genetic Analysis Workshop 15: Gene Expression Analysis 
and Approaches to Detecting Multiple Functional Loci. The full contents of 
the supplement are available online at http://www.biomedcentral.com/
1753-6561/1?issue=S1.
References
1. Brintnell W, Zeggini E, Barton A, Thomson W, Eyre S, Hinks A, Sil-
man AJ, Worthington J: Evidence for a novel rheumatoid arthri-
tis susceptibility locus on chromosome 6p.  Arthritis Rheum
2004, 50:3823-3830.
2. Jawaheer D, Li W, Graham RR, Chen W, Damle A, Xiao X, Monteiro
J, Khalili H, Lee A, Lundsten R, Begovich A, Bugawan T, Erlich H, Elder
JT, Criswell LA, Seldin MF, Amos CI, Behrens TW, Gregersen PK:
Dissecting the genetic complexity of the association
between human leukocyte antigens and rheumatoid arthri-
tis.  Am J Hum Genet 2002, 71:585-594.
3. Pascual M, Mataran L, Jones G, Shing D, van der Slik AR, Giphart MJ,
Schreuder GM, de Vries RR, Breedveld FC, Roovers E, Zanelli E, Mar-
tin J: HLA haplotypes and susceptibility to rheumatoid arthri-
tis. More than class II genes.  Scand J Rheumatol 2002, 31:275-278.
Table 1: Results from linkage and association tests between DRB1 and RA, and for oversharing on 6p21
Sample
NARAC (452 ASP) UK (309 ASP)
LOD score at DRB1 locus (p-value) 14.36 (p = 4.28 × 10-16) 4.28 (p = 9.01 × 10-6)
RA odds ratio for each DRB1 high-risk allele (p-value) 18.2 (p < 0.0001) N/Aa
Sun method T statistic (p-value) T = -0.2 (p = 1) T = -0.6 (p = 1)
aNot applicable because all genotyped individuals in the UK sample are affected.Page 3 of 4
(page number not for citation purposes)
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4. Sun L, Cox N, McPeek S: A statistical method for identification
of polymorphisms that explain a linkage result.  Am J Hum
Genet 2002, 70:399-411.
5. Jawaheer D, Seldin MF, Amos CI, Chen WV, Shigeta R, Etzel C, Damle
A, Xiao X, Chen D, Lum RF, Monteiro J, Kern M, Criswell LA, Albani
S, Nelson JL, Clegg DO, Pope R, Schroeder HW Jr, Bridges SL Jr, Pis-
etsky DS, Ward R, Kastner DL, Wilder RL, Pincus T, Callahan LF,
Flemming D, Wener MH, Gregersen PK, North American Rheuma-
toid Arthritis Consortium: Screening the genome for rheuma-
toid arthritis susceptibility genes: a replication study and
combined analysis of 512 multicase families.  Arthritis Rheum
2003, 48:906-916.
6. Jawaheer D, Seldin MF, Amos CI, Chen WV, Shigeta R, Monteiro J,
Kern M, Criswell LA, Albani S, Nelson JL, Clegg DO, Pope R,
Schroeder HW Jr, Bridges SL Jr, Pisetsky DS, Ward R, Kastner DL,
Wilder RL, Pincus T, Callahan LF, Flemming D, Wener MH,
Gregersen PK: A genomewide screen in multiplex rheumatoid
arthritis families suggests genetic overlap with other
autoimmune diseases.  Am J Hum Genet 2001, 68:927-936.
7. MacKay K, Eyre S, Myerscough A, Milicic A, Barton A, Laval S, Barrett
J, Lee D, White S, John S, Brown MA, Bell J, Silman A, Ollier W,
Wordsworth P, Worthington J: Whole-genome linkage analysis
of rheumatoid arthritis susceptibility loci in 252 affected sib-
ling pairs in the United Kingdom.  Arthritis Rheum 2002,
46:632-639.
8. Abecasis GR, Cherny SS, Cookson WO, Cardon LR: Merlin – rapid
analysis of dense genetic maps using sparse gene flow trees.
Nat Genet 2002, 30:97-101.
9. Kong A, Cox NJ: Allele-sharing models: LOD scores and accu-
rate linkage tests.  Am J Hum Genet 1997, 61:1179-1188.
10. Newton JL, Harney SM, Wordsworth BP, Brown MA: A review of
the MHC genetics of rheumatoid arthritis.  Genes Immun 2004,
5:151-157.
11. Armitage P: Tests for linear trends in proportions and frequen-
cies.  Biometrics 1955, 11:375-386.
12. Klitz W, Maiers M, Spellman S, Baxter-Lowe LA, Schmeckpeper B,
Williams TM Fernandez-Viña M: New HLA haplotype frequency
reference standards: High-resolution and large sample typ-
ing of HLA DR-DQ haplotypes in a sample of European
Americans.  Tissue Antigens 2003, 62:296-307.
13. Biernacka JM, Charoen P, Cordell HJ: Joint linkage and associa-
tion analysis for identification of potentially causal polymor-
phisms in GAW15 data.  BMC Proc 2007, 1(Suppl 1):S36.Page 4 of 4
(page number not for citation purposes)


No evidence for multiple loci affecting rheumatoid arthritis risk on chromosome 6p21

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No evidence for multiple loci affecting rheumatoid arthritis risk on chromosome 6p21

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