|Published in Volume
119, Issue 4
(April 1, 2009)J Clin Invest.
Copyright © 2009, American Society for Clinical
Kallikrein genes are associated with lupus and glomerular basement
membrane–specific antibody–induced nephritis in mice and
1Department of Immunology and Department of Medicine, University of Texas
Southwestern Medical Center, Dallas, Texas, USA.
2Department of Genetics
and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden.
3Instituto de Biomedicina y Parasitología López
Neyra, CSIC, Granada, Spain.
4Oklahoma Medical Research Foundation,
Oklahoma City, Oklahoma, USA.
5UCSF, San Francisco, California, USA.
6Sanatorio Parque, Rosario, Argentina.
Medical School, Hannover, Germany.
8Servicio de Medicina Interna,
Hospital Carlos Haya, Malaga, Spain.
9Department of Rheumatology,
Hospital for Rheumatic Diseases, Hanyang University, Seoul, Republic of Korea.
10Department of Medical Sciences and IRCAD, University of Eastern
Piedmont, Novara, Italy.
11U.O.C. di Reumatologia Azienda Ospedaliera San
Camillo-Forlanini, Rome, Italy.
12Feinstein Institute for Medical
Research, Long Island Jewish Health System, Manhasset, New York, USA.
13Medical University of South Carolina, Charleston, South Carolina, USA.
14University of Alabama at Birmingham, Birmingham, Alabama, USA.
15Section of Medical Genetics and Rheumatology, Hammersmith Hospital,
Imperial College London, London, United Kingdom.
groups are detailed at the end of this article.
Address correspondence to: Chandra Mohan, Room Y8.204, MC 8884, University of
Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, Texas 75390-8884,
USA. Phone: (214) 648-9675; Fax: (214) 648-7995; E-mail:
email@example.com. Or to: Edward Wakeland,
University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas,
Texas 75390-8884, USA. Phone: (214) 648-7332; Fax: (214) 648-7995; E-mail:
firstname.lastname@example.org. Or to: Marta
Alarcón-Riquelme, Department of Genetics and Pathology, Unit for Medical
Genetics, Uppsala University, Dag Hammarsjkölds väg 20, 75185
Uppsala, Sweden. Phone: 46-18-4714805; Fax: 46-18-4714808; E-mail:
First published March 23, 2009
Received for publication July 9,
2008, and accepted in revised form February 4,
Immune-mediated nephritis contributes to disease in systemic lupus erythematosus,
Goodpasture syndrome (caused by antibodies specific for glomerular basement membrane
[anti-GBM antibodies]), and spontaneous lupus nephritis. Inbred mouse strains differ
in susceptibility to anti-GBM antibody–induced and spontaneous lupus
nephritis. This study sought to clarify the genetic and molecular factors that may be
responsible for enhanced immune-mediated renal disease in these models. When the
kidneys of 3 mouse strains sensitive to anti-GBM antibody–induced
nephritis were compared with those of 2 control strains using microarray analysis,
one-fifth of the underexpressed genes belonged to the kallikrein gene family, which
encodes serine esterases. Mouse strains that upregulated renal and urinary
kallikreins exhibited less evidence of disease. Antagonizing the kallikrein pathway
augmented disease, while agonists dampened the severity of anti-GBM
antibody–induced nephritis. In addition, nephritis-sensitive mouse
strains had kallikrein haplotypes that were distinct from those of control strains,
including several regulatory polymorphisms, some of which were associated with
functional consequences. Indeed, increased susceptibility to anti-GBM
antibody–induced nephritis and spontaneous lupus nephritis was achieved
by breeding mice with a genetic interval harboring the kallikrein genes onto a
disease-resistant background. Finally, both human SLE and spontaneous lupus nephritis
were found to be associated with kallikrein genes, particularly KLK1
and the KLK3 promoter, when DNA SNPs from independent cohorts of SLE
patients and controls were compared. Collectively, these studies suggest that
kallikreins are protective disease-associated genes in anti-GBM
antibody–induced nephritis and lupus.
Immune-mediated nephritis is an important pathogenic determinant in SLE and Goodpasture
syndrome (anti–glomerular basement membrane [anti-GBM] disease). In
spontaneous lupus nephritis, both Ab-mediated and Ab-independent mechanisms lead to
renal pathology (1–4). In particular, anti-DNA and anti-glomerular Abs,
as well a few other specificities, have been implicated in the pathogenesis of lupus
nephritis, in both mice and humans (1–8). A useful experimental
tool for dissecting out the molecular mechanisms leading to immune-mediated nephritis in
lupus and Goodpasture disease is the experimental anti-GBM Ab–induced
glomerulonephritis (AIGN) model, wherein the transfer of anti-GBM Abs elicits
glomerulonephritis (GN) with reproducible kinetics. Although the specificities of the
inciting Abs may differ in experimental AIGN and spontaneous lupus nephritis, the
downstream pathogenic cascades that lead to disease in the 2 scenarios appear to be
shared, as reviewed recently (9).
Hence, the AIGN experimental model may be a useful tool for dissecting out the molecular
and genetic basis of lupus nephritis. Notably, of more than 20 inbred mouse strains
challenged with anti-GBM Abs, severe renal disease was noted in only 5 strains,
including DBA/1, NZW, and 129/SvJ (10–12). Coincidentally,
the latter 2 strains are known to develop spontaneous lupus nephritis (13–16). We had previously reported that the strain differences in AIGN
susceptibility cannot be simply attributed to differences in systemic immune response
(to the administered rabbit anti-mouse GBM Abs) or to differences in Th1 skewing (10, 11). On
the other hand, the degree to which differences in renal-intrinsic processes may
contribute to the observed strain differences in AIGN susceptibility remains to be
Given the possibility that renal-intrinsic differences may be contributory, we undertook
a microarray-based transcriptomic analysis of the renal cortex from 3 AIGN-sensitive
strains and 2 control strains, after anti-GBM challenge. Surprisingly, we found that a
significant fraction of the differentially expressed genes that distinguish the
nephritis-sensitive strains from the control strains belong to the kallikrein
(Klk) gene family. Importantly, this gene complex is encoded within
an interval on chromosome 7 that had previously been associated with spontaneous lupus
nephritis (14–21). Kallikreins constitute a multigene family of serine esterases
with a wide spectrum of biological functions (22–39). These reported
functions include the regulation of inflammation, apoptosis, redox balance, and fibrosis
within the kidneys, as well as local blood pressure. In further genetic and functional
studies, we demonstrate that Klk genes are renoprotective in
immune-mediated renal disease and may constitute important disease susceptibility genes
for experimental anti-glomerular Ab–induced nephritis as well as spontaneous
lupus nephritis in mice and in humans.
Displayed in Figure 1 are all genes that were
significantly upregulated or downregulated (at least 2-fold difference, P
< 0.001) in the strains that were highly sensitive to AIGN disease
(i.e., NZW, DBA/1, and 129/SvJ) compared with either of the control strains (C57BL/6
[B6] or BALB/c), following challenge with anti-GBM serum. Though several strain-specific
gene differences were also noted within this panel of genes, a subset of 50 genes within
this panel were consistently downregulated in all 3 of the highly disease-sensitive
strains compared with the control strains (shown enlarged on the right, Figure 1A). Intriguingly, 10 of these genes belonged to the
kallikrein (Klk) family, with the highest expression levels and
differences being noted in Klk1, Klk1b3,
Klk1b5, Klk1b26, and Klk1b27, as
summarized in Table 1. In addition to the
Klk genes displayed in Table 1 (all of which were found to be different between the 2 sets of strains at
P < 0.001), a few other Klk genes, notably
Klk1b9 and Klk1b21, exhibited similar expression
differences between the disease-sensitive strains and the control strains, though these
differences did not reach statistical P values of 0.001 (data not
shown). Hence, in total, 12 Klk genes were underexpressed in the
kidneys of AIGN-sensitive strains, following anti-GBM challenge, compared with the
Strain-dependent gene expression differences in the renal cortex in AIGN. (A) Anti-GBM disease was induced in 3 disease-sensitive strains
(DBA1, NZW, and 129/SvJ) and 2 control strains (BALB/c and B6), after which renal
cortex RNA was analyzed using DNA microarrays on day 10 of disease (i.e., 5 days
after injection of anti-GBM Abs). Three biological replicates were included for
each strain. The left panel shows that a total of 360 gene transcripts were
differentially expressed between the study strains (>2 fold,
P < 0.001). The right panel (a higher-magnification view
of the boxed region on the left) shows a cluster of gene transcripts that were
increased in all control strains but not in the AIGN-sensitive strains
(>2-fold difference, P < 0.001), including 10
Klk genes. (B) Renal cortex gene expression
differences in Klk1, Klk1b3,
Klk1b5, Klk1b26, and Klk1b27
were confirmed by real-time PCR in the indicated strains, before (day 0) and after
(day 10) anti-GBM Ab challenge. Each bar represents the mean of 6 samples. Similar
changes were seen between B6 and NZW mice (data not shown). P
values pertain to comparisons with BALB/c day 10 values. Error bars denote SD.
Several kallikrein gene messages were significantly upregulated in the kidneys of
B6 and BALB/c mice compared with NZW, DBA1, and 129/SvJ mice, upon anti-GBM Ab
Next, renal Klk gene expression was examined before and after induction
of AIGN, using real-time PCR as an orthogonal approach. Real-time PCR analyses validated
the above microarray results, indicating that whereas the B6 and BALB/c control strains
successfully upregulated Klk following anti-GBM Ab challenge, the
DBA/1, 129/SvJ, and NZW strains were ineffective at doing so (Figure 1B). In contrast, the basal, predisease levels of
renal Klk were similar in all strains (Figure 1B). These differences were also confirmed at the protein level by
Western blot analysis of renal cortex samples from these 5 strains, as illustrated for
Klk1 (Figure 2A and data not
shown). Parallel differences in Klk enzymatic activity were also noted in urine samples
from the same mice following anti-GBM Ab challenge (Figure 2B). Thus, whereas the BALB/c control strain exhibited a robust increase in
urinary Klk activity 10–14 days after challenge, in the AIGN-sensitive
strains DBA/1 and 129/SvJ, Klk was not significantly upregulated over the same period
The differential renal expression of Klk in the
AIGN-sensitive versus control strains was confirmed at the protein level. BALB/c, DBA1, and 129/SvJ mice were subjected to AIGN. (A) Fourteen
days after anti-GBM challenge, kallikrein protein expression was assayed in the
renal cortex by Western blotting, using a rabbit anti–mouse Klk1 Ab.
The bar chart below (n = 3 mice per group) shows Klk expression
normalized to GAPDH (AU). *P < 0.001, compared with all
other study groups. (B) Twenty-four-hour urine samples collected from
these mice on days 0, 10, and 14 after anti-GBM insult were also assayed for
kallikrein enzymatic activity, using the synthetic chromogenic substrate
HD-Val-Leu-Arg-pNA (S-2266), as detailed in Methods. Similar differences in renal
and urinary kallikrein levels were noted between B6 and
B6.Sle3z mice (data not shown). Error bars in
A denote SD. In B, each dot represents data from a
single mouse, and the horizontal bars denote arithmetic group means.
Given that Klk upregulation in the kidneys and urine of anti-GBM
Ab–challenged mice correlated well with the subdued nephritis noted in the
B6 and BALB/c control strains, we next asked whether Klk might have a disease-protective
role in immune nephritis. Kallikreins act through the generation of bradykinins (BKs),
which in turn exert their biological effects by binding BK (BK B1 and B2) receptors on
various cells (25, 26). Selective receptor blockade using pharmacological inhibitors
further indicated that the biological effects of BK (and Klk) were mediated by the BK B2
receptor, since blocking this receptor aggravated proteinuria, azotemia, and GN
following anti-GBM Ab challenge in BALB/c mice (Figure 3, A–D). Importantly, the mice in which BK B2 receptor was blocked
exhibited significantly more severe GN compared with the other groups of mice (average
GN score of 2.1 versus 0.2, P < 0.001, as partly illustrated in
Figure 3, C and D). Similar differences were noted
when the BK B2 receptor blockers were administered to anti-GBM–challenged B6
mice (data not shown). Conversely, the administration of BK dampened the severity of
anti-GBM disease in 129/SvJ mice, which otherwise develop severe AIGN following the
experimental insult (Figure 3E and data not shown).
Impact of BK receptor blockade or activation on the severity of AIGN. BALB/c mice were treated with BK receptor antagonists (B1 receptor blocker H158
[B1-R] or B2 receptor blocker H157) or PBS vehicle alone as placebo (None), using
osmotic pumps, for the 14-day duration of an anti-GBM challenge and phenotyped for
proteinuria (A), azotemia (B), and GN (C,
B1-R blocked; and D, B2-R blocked). Original magnification,
×400. (E) Conversely, the administration of BK into
129/SvJ mice using osmotic pumps ameliorated disease after anti-GBM challenge,
compared with mice treated with vehicle placebo. In A,
B, and E, each dot represents data from a single mouse,
and the horizontal bars denote arithmetic group means.
With respect to the 3 AIGN-sensitive strains, DBA/1, 129/SvJ, and NZW, it is already
known that several genomic intervals in the latter 2 strains (including loci on
chromosomes 1 and 7) also contribute to spontaneous lupus nephritis (13–16). Indeed, the entire Klk gene complex is encoded within a
lupus susceptibility interval on chromosome 7. The NZW-derived lupus susceptibility
locus on chromosome 7, Sle3z (which includes the
Klk gene complex), has previously been introgressed onto the B6 genome
as a congenic interval, and this locus had already been shown to facilitate development
of spontaneous lupus nephritis (17–19). Through recursive
backcrossing of B6.Sle3z congenic mice to B6 parents and
microsatellite-assisted selection, we generated
harboring the NZW-derived Klk gene complex within a 4-Mb interval, with
termini at D7mit157 and D7mit158, as diagramed in
The Sle3z locus, particularly the
on chromosome 7, may be responsible for the reduced Klk and
enhanced nephritis susceptibility seen in NZW mice. (A) Shown are the Sle3z lupus
susceptibility interval on chromosome 7 (Chr. 7; black denotes the interval
derived from NZM2410/NZW; gray denotes B6 origin); the 4-Mb subinterval spanning
D7mit157 to D7mit158 (denoted by the dashed
line on right); and the cluster of Klk genes harbored within the
indicated subinterval. The numbers on the right refer to the positions of
respective microsatellite markers (e.g., 157 represents
D7mit157). Shown also are the 24-hour urine protein excretion
profiles (B), blood urea nitrogen (BUN) (C), GN
pathology score (D), and renal Klk message levels
(E), 14 days after anti-GBM challenge of B6,
(n = 5 each). The data shown in
B–D were reproduced in at least 2
additional experiments. In the second study, for example, the
exhibited significantly higher 24-hour protein levels in urine (P
< 0.045) and GN score (P < 0.013) and more severe
tubulo-intersitial disease (P < 0.001), compared with the
B6 control (data not plotted). All statistical comparisons were made with the
respective B6 controls, using the Mann-Whitney U test. In
B–D, each dot represents data from a
single mouse, and the horizontal bars denote arithmetic group means. Error bars in
E denote SD.
Importantly, B6.Sle3z mice and the newly generated
recombinants both displayed heightened sensitivity to AIGN, marked by elevated
proteinuria and severe nephritis (Figure 4,
B–D). Moreover, the renal cortex of both these congenics failed to
efficiently upregulate Klk following anti-GBM Ab challenge, compared
with the B6 controls (Figure 4E), as assessed by
real-time PCR. Taken together with the functional data presented above, these findings
suggest that the z allele of Klk positioned within the
Sle3z157–158 subinterval may
harbor important culprit genes for the heightened experimental anti-GBM disease (and
spontaneous lupus nephritis) seen in NZW (and related strains of) mice.
Five of the most differentially expressed Klk genes,
Klk1, Klk1b3, Klk1b5,
Klk1b26, and Klk1b27 were sequenced (GenBank accession
numbers EU597301–EU597324). Klk4 and
Klk1b8, though differentially expressed, were not studied further
because of their relatively low expression levels in all strains (Table 1). Several strain-specific differences were noted
in the promoter regions of the 5 sequenced genes, as summarized in Table 2. The B6 and BALB/c Klk genes were
almost identical, while the Klk genes from the AIGN-sensitive strains
NZW and DBA/1 were closely related to each other, as illustrated by the phylogenetic
trees in Figure 5A and the promoter region sequence
exemplified in Figure 5B. The Klk
genes from the 129/SvJ strain clustered more closely with the B6/BALB/c genes in some
cases, and with the NZW/DBA/1 genes in others; despite repeated attempts, we could not
amplify some of the critical regions of the 129/SvJ Klk1b26 gene (Table
2). In contrast to the promoter regions, no
sequence differences were noted in the coding regions or the 3′ untranslated
regions of these Klk genes, when the 5 strains were compared (data not
Sequence analysis of the 5′-regulatory regions of
Klk genes reveals nucleotide polymorphisms that distinguish the
AIGN-sensitive strains from the control strains. When 2 kb of the 5′-regulatory regions of Klk1,
Klk1b3, Klk1b5, Klk1b26, and
Klk1b27 from the indicated strains were sequenced, several
SNPs/deletions were identified, as detailed in Table 2 (GenBank accession numbers EU597301–EU597324).
(A) Phylogenetic analysis revealed the sequence of the
AIGN-sensitive strains to be closely related, compared with the sequences of the 2
control strains. Bars represent the fraction of sequence variation.
(B) Part of the nucleotide sequence of the Klk1b3
promoter (up to 200 bp upstream of transcription start site) from the different
study strains indicated. Note that the B6.Sle3z strain
bears the NZW allele at Klk. (C) One kilobase of the
promoter region of Klk1b3 from both BALB/c and DBA/1 strains was
inserted into the pGL4 luciferase vector and transfected into COS-7 cells, and
luciferase activity was assayed 24 hours later, as detailed in Methods. Each bar
represents the median of triplicate values, and the error bars denote SD. Cells
transfected with vectors carrying the BALB/c-derived Klk1b3
promoter showed significantly increased luciferase activity compared with cells
with vectors bearing the DBA/1 promoter or vector alone (P
< 0.01). Similar differences were noted when the B6 Klk1b3
promoter was compared with the B6.Sle3zKlk1b3 promoter (data not shown).
Sequence polymorphisms in the promoter region of the mouse Klk
Some of the observed strain-specific promoter sequence differences in
Klk fell within putative transcription factor binding sites. In the
promoter region of Klk1b3, for example, SNPs were noted in potential
transcription factor binding sites for PBF, TFIID, HoxD9, TCF-4E, NF-S, NF-E, and LBP-1,
which distinguished the AIGN-sensitive strains from the controls. In particular, the
GGCTT[C→G]AAAAT SNP in the promoter region of Klk1b3 is
predicted to abrogate TFIID binding. Importantly, promoter-luciferase studies indicated
that sequence differences in the promoter region of Klk1b3 may
contribute in part to the reduced expression of this gene in the disease-sensitive
strains (Figure 5C). Given that more than 200
sequence variations have been noted in the regulatory regions of the
Klk genes (Table 2), each
difference has to be systematically evaluated for its potential functional relevance.
As in murine lupus, the orthologous human interval encompassing the KLK
genes on human chromosome 19q13 has also been implicated in human SLE
susceptibility in previous genome scans (40–43). To ascertain
whether KLK might also be a culprit gene in human SLE, we examined
several SNPs in the renal-expressed KLK genes encoded within this
interval, specifically human KLK1, KLK5,
KLK6, and KLK7. We first genotyped a set of German SLE
patients (n = 340) and a set of controls matched for ethnicity, age,
and sex (n = 400). As detailed in Table 3, association to two KLK1 SNPs, rs1054713
(a synonymous coding SNP) and rs2740502 (an intronic SNP), but not to
the nonsynonymous substitution rs5517, was observed, with the strongest
associations being noted in SLE patients with nephritis (KLK1 SNP,
rs2740502; P = 0.007 compared with non-nephritic
SLE patients and P = 0.01 compared with healthy controls). A weak
association was also observed for SNP rs1897604 located in
KLK5; however, this SNP was not in Hardy-Weinberg equilibrium in the
controls (data not shown). No disease association was detected for any of the other
KLK genes analyzed in this preliminary study.
Association analysis of KLK SNPs in German SLE patients and controls
To validate these preliminary associations, we genotyped 6 more cohorts of patients,
including additional European, European-American, and Korean patients with SLE, as
detailed in Tables 4 and 5. For the KLK1 SNP rs2740502, we
could replicate the genetic association to lupus nephritis compared with controls in the
German and Italian samples but not in the remaining patient sets (Table 5). Likewise, the German SLE patients exhibited
association to another KLK1 SNP, rs5516 (Table 4). Due to likely heterogeneity in haplotype distribution and
potential differences in linkage disequilibrium between the analyzed SNPs and functional
SNPs in the different ethnic groups, we were unable to perform a Mantel-Haenszel
metaanalysis with these data sets.
Genotypic and allelic association of KLK1 rs5516 in 6 additional
sets of SLE patients with nephritis (cases) and healthy controls
Genotypic and allelic association of KLK1 rs2740502 in 6
additional sets of SLE patients with nephritis (cases) and healthy controls
For further independent validation, we gained access to the genotype data for SNPs of
the entire KLK region typed in 689 SLE patients and 3,718 healthy controls from the
International Consortium for Systemic Lupus Erythematosus Genetics (SLEGEN) and 595 SLE
patients from the UCSF Lupus Genetics Project cohort, both of which had been assembled
for genome-wide association studies. Although the sets of SNPs spanning the entire KLK
locus utilized in these studies were not completely overlapping, 56 SNPs were, and these
were examined further for disease association. The strongest association with SLE was
again noted to SNPs close to KLK1, in an intergenic region bordered at
the centromeric end by KLK1 and KLK15 and at the
telomeric end by KLK3 and KLK2 (Figure 6A and Supplemental Table 1; supplemental material
available online with this article; doi:10.1172/JCI36728DS1). Additional associations to
SNPs in KLK4 promoter, KLK5, KLK7,
KLK11, and KLK12 were also uncovered when cases
with nephritis were compared with cases without nephritis (Figure 6B and Supplemental Table 2). Next, we defined the haplotype blocks
across the KLK locus (Figure 6A)
and examined them for association to SLE. Again, the haplotype blocks harboring the
promoter region of KLK3 (block 1) displayed the strongest association,
followed by the haplotype containing KLK8 to KLK11
genes (block 8) (Figure 6C and
Supplemental Table 3). However, when only the patients with nephritis were considered as
cases, the association to the KLK3 promoter region was weaker; instead,
the haplotypes harboring the KLK4 promoter, KLK5, and
the KLK8–KLK11 block yielded stronger
association. Of note, the 2 strongest associations observed corresponded to haplotypes
with significantly lower frequencies in patients, reflecting a protective effect
conferred by the KLK polymorphism.
KLK association in SLE patients — second validation study. (A) The Haploview plot shows the genotyped markers in the KLK locus,
from KLK1 at the centromeric limit until KLK14
at the telomeric end, as well as the linkage disequilibrium between them measured
by the D prime coefficient. Blocks were defined by the solid spine method
implemented in Haploview version 4.1. Dataset: UCSF (n = 595 SLE
patients) plus SLEGEN (n = 689 SLE patients and
n = 3,718 controls). (B) In the indicated numbers of
SLE patients and healthy controls, 56 KLK SNPs were tested for disease association
using logistic regression analysis, with the phenotype
“SLE” as the outcome variable (shown in blue). To examine
whether the risks conferred by the KLK polymorphisms were influenced by the
presence of nephritis, we tested the KLK SNPs for association, considering the
phenotype “nephritis” as the outcome variable. Red
indicates significant differences compared with controls; green indicates
significant differences between cases with nephritis and cases without nephritis
calculated by a metaanalysis, in order to control for heterogeneity among the
contributing clinical centers. (C) The observed linkage
disequilibrium blocks across the KLK locus were tested for
haplotype association, using both omnibus and haplotype-specific association
statistics (T test) as implemented in PLINK. Shown are significant haplotype
associations when SLE patients were compared with controls (blue), when patients
with lupus nephritis were compared with controls (red), and the case-only analysis
(green). Besides the SNPs indicated in B and the blocks indicated in
C, none of the other SNPs/blocks shown in A showed
significant disease associations. For a larger version of this figure, see
Supplemental Figure 1.
Overall, these 3 sets of independent findings support a likely genetic association of
the human KLK1 gene and the KLK3 promoter region with
lupus and lupus nephritis.
AIGN is an experimental tool that shares downstream molecular cascades with spontaneous
lupus nephritis, as recently reviewed (9). Over
the past decade, the roles of about 25 different molecules (including various complement
proteins and TLR ligands, FcR, B7/CD28/CTLA4, LFA1/ICAM1, P-selectin, TNF-α,
IL-1, IL-6, IL-12, IL-18, IFN-γ, M-CSF, PDGF, MCP-1, and NO) have been
directly assessed (using gene knockouts or by deliberate experimental modulation of the
molecules) in 2 disease settings — anti-GBM disease and lupus nephritis.
Importantly, the effects of each of these molecules were consistent in both disease
settings (9). In other words, molecules documented
to influence the progression of experimental anti-GBM disease also impacted the
development of lupus nephritis in the same direction. Hence, although experimental
anti-GBM nephritis and spontaneous lupus nephritis differ in the nature of the inciting
Abs and the localization of the immune deposits, pathology in both settings may be
mediated by a shared network of downstream molecular pathways, including complement- and
FcR-dependent activation of resident renal cells and infiltrating leukocytes, T cell
help, proinflammatory mediators initially, and profibrotic molecules later in disease
(9). In the present study, we have identified
kallikrein as an additional molecule that appears to impact both diseases concordantly.
Of more than 20 inbred strains tested for AIGN susceptibility, DBA/1, 129/SvJ, and NZW
are particularly sensitive to disease in this model. Though the genetic and molecular
origins of increased disease susceptibility may vary among these strains, it is
remarkable that all 3 strains shared approximately 50 genes that were underexpressed in
their renal cortex during disease, compared with other strains. Even more remarkable is
the finding that one-fifth of these 50 genes belonged to the same family of genes, the
kallikreins. This strain difference in Klk gene expression may
originate from polymorphisms in the Klk genes themselves or they may be
the consequence of yet other candidate genes in the AIGN-susceptible strains. The
finding that a similar renal Klk expression profile was recapitulated
in B6 mice bearing a 4-Mb congenic interval harboring the NZW allele of
Klk (Figure 4) suggests that the
observed strain differences are likely to originate from sequence differences in the
Klk locus itself. The observation that the AIGN-sensitive strains
have Klk sequences that are related to each other but diverge from the
Klk sequences of the 2 control strains, B6 and BALB/c, offers
further evidence that the strain differences in renal Klk upregulation must be
intrinsically encoded within the Klk genetic locus.
Though many sequence polymorphisms in the promoter regions of the Klk
genes were uncovered in this study, with several falling within transcription factor
binding sites, the functional relevance of these regulatory sequence differences to the
observed expression differences warrants systematic study. At the very least, our
completed studies indicate that sequence polymorphisms within the promoter region of
Klk1b3 may be contributing to the observed expression differences in
this gene, when B6.Sle3z/NZW kidneys are compared with the
B6 control (Figure 5B). Alternatively, the entire
Klk gene complex may be differentially regulated in the 2 haplotypes
by polymorphic regulatory regions located within or perhaps even outside this gene
complex. Further sequencing of both haplotypes and Klk
allele–specific knock-in studies are warranted to obtain definitive evidence
that the observed Klk polymorphisms are indeed responsible for the
strain-specific phenotypic differences.
Having established that the reduced Klk observed in the AIGN-sensitive strains is
genetically encoded by the Klk locus, we next examined whether reduced
Klk may be responsible for the increased severity of immune-mediated nephritis seen in
these susceptible strains. This indeed appears to be the case, given that subduing Klk
action (using B2 receptor blockers) rendered BALB/c control mice AIGN susceptible, while
the administration of BK ameliorated nephritis in AIGN-susceptible 129/SvJ mice (Figure
3). These findings resonate well with previous
genetic and pharmacological studies that also reveal a renoprotective role for Klk and
BKs in nephritis following other insults, including hypertension, ischemic stroke, salt
imbalance, and diabetes (26–35). Previous studies suggest that Klk may be
playing a protective role in nephritis by modulating several different parameters,
including local blood pressure, the inflammatory milieu, redox balance, and/or signaling
within various cell types (25, 26, 31, 36–39).
The observation that the NZW-derived Sle3z
lupus-susceptibility locus confers susceptibility to spontaneous lupus nephritis raises
the interesting possibility that polymorphisms in Klk may also confer
susceptibility to spontaneous lupus nephritis. Though it is formally possible that
additional genes within the Sle3z interval may be
contributing to the increased susceptibility to lupus nephritis associated with this
locus (14, 17–19), the observation
that a recombinant congenic harboring a 4-Mb interval spanning the Klk
locus confers susceptibility to experimental immune nephritis (Figure 4) suggests that the Klk genes are
likely to be major players in spontaneous lupus nephritis as well. Efforts are underway
to evaluate whether long-term modulation of Klk levels in vivo can impact the severity
of spontaneous lupus nephritis.
The corresponding interval on human chromosome 19q13 bearing the
KLK gene complex has also been implicated in human SLE
susceptibility in previous genome scans, particularly in patients of European descent
(40–43). The observation that SNPs in KLK1 show
significant association to lupus nephritis in European-descent SLE patients suggests
that KLK gene polymorphisms may also influence human lupus nephritis,
at least in some ethnic groups. The observed heterogeneity among different populations
in some of our earlier studies (as summarized in Tables 4 and 5) may be due to haplotype
differences among the populations. However, the larger and more comprehensive SNP and
haplotype analysis conducted in the SLEGEN and UCSF studies clearly validates the
existence of a disease locus in KLK1. It is intriguing that most of the
disease-associated SNPs are located in the regulatory region between
KLK1 and KLK3, with these genes being transcribed in
opposite orientations to each other (Figure 6A).
This region possesses many regulatory elements sensitive to steroid hormones extensively
studied in prostate cancer, which have been shown to affect KLK3
(prostate-specific antigen) transcription. Incidentally, the murine
Klk genes that are most differentially expressed in disease-prone
kidneys (as listed in Table 1) are most
homologous to human KLK1 and KLK3, raising the
interesting possibility that regulatory polymorphisms shared by the two species could be
at play in dictating reduced kallikrein production, which could potentially lead to
enhanced nephritis in mice and patients with lupus.
In follow-up studies, it would be important to study SLE patients with clearly defined
and graded nephritis (as determined using uniformly applied diagnostic criteria across
different patient sets originating from different collaborative groups) to further
validate the association to KLK1/KLK3, to elucidate any corresponding
promoter polymorphisms, and to define the functional consequences of any such
polymorphisms. Interestingly, familial clustering of reduced renal Klk expression as
well as African American hypertensive patients with reduced renal Klk have been reported
(44, 45). Given that African American ethnicity and coexisting hypertension are both
risk factors for severe lupus nephritis (46,
47), it would be important to establish the
potential role of KLK gene polymorphisms in driving disease severity in
human SLE. Along these lines, there is some evidence that promoter polymorphisms in
human KLK1 may be associated with reduced renal and urinary Klk, as
well as with hypertension and nephritis (48,
Whereas some lupus susceptibility genes may impact the adaptive arm of the immune
system, others appear to augment innate immunity (50–52). The present study
uncovers yet another class of lupus susceptibility genes — those that may
potentially modulate end-organ disease. Besides their central relevance to the genetics
of lupus nephritis, these findings have additional clinical implications. Monitoring
urinary kallikreins as a marker of renal disease in lupus and developing
kallikrein-based therapeutics for modulating renal lupus may be future directions worthy
Mice and AIGN. BALB/c, DBA/1, 129/SvJ, B6, and NZW mice were purchased from The Jackson Laboratory.
B6.Sle3z congenic mice, described previously (17, 18),
were bred in-house. Recursive backcrossing of B6.Sle3z
mice to B6 parents and microsatellite-assisted selection were used to generate
harboring the NZW-derived Klk gene complex within a 4-Mb interval,
with termini at D7mit157 and D7mit158. All
mice were maintained in a specific pathogen–free colony. Two- to
3-month-old females were used for all studies. To induce nephritis, we first
sensitized mice on day 0 with rabbit IgG (250 μg/mouse, i.p.), in
adjuvant, as described previously (10, 11). On day 5, the mice were challenged i.v. with
rabbit anti-GBM Ig (200 μg per 25 g body weight, in a 300-μl
volume). The source and preparation of the anti-GBM serum/Ig have been detailed
previously (10, 11). Twenty-four-hour urine samples were collected from
experimental mice on days 0, 10, and 14, using metabolic cages, with free access to
drinking water. Urinary protein concentration was determined using the Coomassie Plus
protein assay kit (Pierce, Thermo Scientific). Serum was collected on days 0, 10, and
14 for measurement of blood urea nitrogen (BUN), using a urea nitrogen kit
(Sigma-Aldrich). Animals were sacrificed on day 10 or 14, and the kidneys were
processed for histopathological examination by light microscopy, as detailed
previously (10, 11).
Microarray and real-time PCR analysis. Kidneys collected on day 10 of experimental nephritis were used for gene expression
analysis by microarray. Total RNA was isolated from renal cortex using RNeasy
(QIAGEN) and quality-checked using an Agilent Bioanalyzer (Agilent Technologies).
Sentrix Mouse-6 Whole Genome Expression BeadChips (Sentrix Mouse-6 v1_1; Illumina)
were used for the microarray analysis, according to the manufacturer’s
instructions. Microarray data were extracted using BeadStudio v3.1,
background-subtracted, and normalized using a cubic spline algorithm. Genes
differentially expressed between groups were identified using the Illumina custom
error model implemented in BeadStudio. Genes were considered significantly
differentially expressed when P values were less than 0.001
and the change was greater than 2-fold. Supervised hierarchical clustering of
transcripts that were differentially expressed between the groups was performed. Data
were median centered; in Figure 1A, green
represents expression below median; red represents above-median expression; and gray
represents missing data.
Renal cortex Klk gene expression differences were validated by
quantitative RT-PCR using validated TaqMan assays (Applied Biosystems) and
Mm00834006_g1 for klk1, Mm01203825_gH for klk1b3,
Mm00833453_g1 for klk1b5, Mm01702809_m1 for
klk1b26, and Mm00834759_gH for klk1b27.
Transcription of eukaryotic 18S rRNA (assay ID Hs99999901_s1) was used as an internal
Generation of rabbit anti-mouse Klk1 Ab. Rabbit Abs against mouse Klk1 were developed by Abgent, using a peptide sequence from
mouse Klk1, EKNSQPWQVAVYRFTKYQC, conjugated to keyhole limpet hemocyanin (KLH). The
peptide was used to immunize rabbits (5 mg per rabbit, 3 injections administered 21
days apart). Sera obtained from the rabbits 2 months following the primary
immunization reacted strongly with recombinant mouse Klk1 protein (titer,
>1:4,000). Immune rabbit sera were harvested 2 weeks after the third
injection, protein G purified, aliquoted, and stored at
Assaying Klk protein. BALB/c, DBA1, and 129/SvJ mice were subjected to AIGN, as described above. Mice (3
per group) were sacrificed on day 0 or 14. Renal cortex was homogenized in lysis
buffer (25 mM Tris-HCl, pH 7.4, 1% Triton X-100, 0.1% SDS, 2 mM EDTA) containing
1:100 protease inhibitor cocktail (Sigma-Aldrich) and centrifuged at 4°C
for 30 minutes. The supernatants were stored at –80°C.
Protein concentrations were determined by Lowry’s method. These
homogenates were subjected to Western blot analysis using the custom-generated rabbit
anti–mouse Klk1 Ab (1:1,000; described above) and chemiluminescence
detection (Pierce, Thermo Scientific). Urinary kallikrein enzymatic activity was
assayed using the synthetic chromogenic substrate HD-Val-Leu-Arg-pNA (S-2266).
Briefly, 50 μl of urine was added to 50 μl of assay buffer
(0.2 M Tris-HCl, pH 8.2, containing 300 μg/l soybean trypsin inhibitor
and 375 μg/l EDTA) and incubated at 37°C for 30 minutes.
Then, 50 μl of S-2266 was added and incubated at 37°C for 3
hours, and the absorbance was read at 405 nm. A standard curve was constructed using
purified kallikrein (human urinary kallikrein [HUK]; Calbiochem), and the optical
densities were converted to activity units.
In vivo studies using BK agonists and antagonists. Two- to 3-month-old female BALB/c mice were divided into 3 groups (10 mice per
group), and subjected to anti-GBM Ab challenge. The mice in the first 2 groups were
infused with either kinin B2 receptor antagonist H157 (HOE140 or icatibant) or B1
receptor antagonist H158, using subcutaneous osmotic minipumps (DURECT; dosage, 0.74
μg/h) from day 3 to day 14. The third group was infused with PBS vehicle
as control. Urine and sera were collected on days 0 and 14 for proteinuria and BUN
assessment. All mice were sacrificed on day 14, and kidneys were scored for
pathology. For the in vivo agonist studies, 129/SvJ mice were subjected to anti-GBM
disease, as described above. One group received BK (Sigma-Aldrich; 0.5
μg/h released by osmotic minipumps, from day 3 to day 14), while the
other group received PBS. All mice were phenotyped for disease as detailed above.
Amplification and sequencing of the 5′-flanking region of the Klk
genes. Two-kilobase fragments of the 5′-flanking region of various
Klk genes were sequenced after amplifying with the following
5′-AGAAAGACTCCTGGAAGAGTGG-3′, and Klk1b27-R:
5′-GTGAACTTGGAGCTGTTGAGGA-3′. The DNA sequences of these PCR
fragments were analyzed on an ABI 3100 sequence analyzer (Applied Biosystems) and
deposited into GenBank (accession numbers EU597301–EU597324). Based on
the sequence information, phylogenetic trees were constructed using publicly
available software (Protein Information Resource,
Promoter function studies. One kilobase of the promoter sequence upstream of Klk1b3 was PCR
amplified from B6, BALB/c, DBA/1, and NZW/B6.Sle3z mice
using the primers 5′-CCGGTACCGCCACCAAGCTTAACCCTGA-3′ and
5′-CCCTCGAGGCTTGGAGCTGTTGAGGCAC-3′, cloned separately into
pGL4.10[luc2] luciferase reporter vector (Promega), and sequence verified. COS-7
cells (2 × 105 to 5 × 105 cells in
96-well plates) were transfected with 0.1 μg of pGL4.10[luc2]-promoter
luciferase construct or vector using PolyFect (QIAGEN), together with 0.01
μg of an internal control plasmid, pGL4.73[hRluc/SV40] (Promega). Cells
were lysed after 48 hours of LPS stimulation, using 1× passive lysis
buffer (Promega) and assayed for luciferase activity, according to the
manufacturer’s instructions. Each construct was measured in at least 8
replicates. The results were normalized against Renilla luciferase
control and presented as median values.
Human KLK genetics. Several independent sets of cases and controls were used in this study, originating
from Germany, Italy, Spain, Argentina, the United States, Mexico, and Korea (53). The European sets and the Latin American
sets have been previously described (54, 55). All patients fulfilled American College of
Rheumatology criteria for the classification of SLE (56). All human studies were approved by the Central Ethical Review Board,
Sweden, and the local ethical review boards of Instituto de Biomedicina y
Parasitología López Neyra; Sanatorio Parque; Hospital Carlos
Haya; Hospital for Rheumatic Diseases, South Korea; University of Hannover;
University of Eastern Piedmont; U.O.C. di Reumatologia Azienda Ospedaliera San
Camillo-Forlanini; Oklahoma Medical Research Foundation; University of Alabama at
Birmingham; Feinstein Institute for Medical Research; Medical University of South
Carolina; and Hammersmith Hospital. For the initial analysis, SNPs on human
renal-expressed KLK genes KLK1,
KLK5, KLK6, and KLK7 were selected
from the HapMap-CEU genotype data (http://www.hapmap.org) using Haploview version 3.2
(Broad Institute of MIT and Harvard), and were genotyped using protocols described
earlier (55). Differences between patients and
controls were statistically analyzed using c2 test. Odds ratio (OR) with
95% CI was calculated using StatsDirect software for allelic differences and using
UNPHASED software (http://www.mrc-bsu.cam.ac.uk/personal/frank/software/unphased/)
for genotypic differences.
Validation of KLK associations using SLEGEN and UCSF datasets. We extracted the genotype data for the human KLK locus (Chr19:56014125-56277428) from
2 different genome-wide association studies (GWASs) conducted recently in SLE
patients of European ancestry (57, 58). The patients and controls included in those
studies, as well as their contributing centers and the genotyping platforms used,
have been described in detail in the original publications. All patients fulfilled
the American College of Rheumatology’s revised criteria for
classification of SLE (56) and were matched to
healthy controls by sex, age, and ethnic origin (i.e., only individuals of European
ancestry were included). From the GWAS performed by the SLEGEN, we obtained data for
63 KLK SNPs genotyped in 689 cases and 3,718 controls. From the UCSF
Lupus Genetics Project, we added 595 patients who had genotype data for 113
KLK SNPs, of which 56 were also present in the SLEGEN dataset.
Hence, in total, we had access to genotype data for 56 KLK SNPs
pertaining to 1,284 (689 SLEGEN plus 595 UCSF) SLE patients and 3,718 controls, drawn
from the 2 GWAS studies.
Statistics. For the murine studies, Student’s t test (1-tailed) was
used for statistical analysis, unless otherwise indicated. Error bars shown in
figures represent standard deviations. For the human genetic studies, statistical
analysis was performed using Haploview version 4.1 (59) and PLINK version 1.04 (60). We
first verified that all the SNPs/alleles were concordant in terms of positive or
negative strand. Then, quality control filters were applied to remove individuals and
SNPs with more than 5% of data missing, differential missing rate between cases and
controls (P < 0.05), significant deviation from
Hardy-Weinberg equilibrium in controls (P < 0.001), or a
minor allele frequency of less than 1%. After this filtering step, we had 56 SNPs in
1,241 cases and 3,664 controls, with a total genotyping rate of 0.996054. Clinical
data regarding the presence or absence of nephritis was available for 1,122 patients,
of whom 319 had nephritis (28.4%).
In this filtered sample, we tested the allelic frequencies for significant
association by logistic regression analysis using the phenotype
“SLE” as the outcome variable. To examine whether the risk
conferred by the KLK polymorphism on SLE was influenced by the presence of nephritis,
we also performed the analysis considering the phenotype
“nephritis” as the outcome variable. OR and 95% CI limits
(L95, lower limit; U95, upper limit) were calculated controlling by the covariate
“sex.” We also performed a case-only
χ2 test to determine whether there were significant
differences in allelic frequencies between the subsets of patients with and without
nephritis. Since the patient samples had originated from different centers, combined
ORs were estimated by Cochran-Mantel-Haenszel metaanalysis, including a Breslow-Day
test for homogeneity of the OR between centers. Multiple testing was corrected by
adjusting the P values using the false discovery rate (FDR) control.
Finally, we examined the linkage disequilibrium (LD) structure of the region in
Haploview, and the observed blocks were tested for haplotype association. The data
were analyzed using the omnibus test and haplotype-specific association statistics (T
test) as implemented in PLINK. The case/control omnibus test is an H – 1
degree of freedom test, where H is the number of different haplotypes. We compared
the haplotype frequencies in patients with SLE versus controls, patients with lupus
nephritis versus controls, and patients with lupus nephritis versus patients without
Note on authors. The members of the collaborative groups are as follows.
Italian Collaborative Group: Maria Giovanna Danieli, Clinica Medica, Dipartimento di
Scienze Mediche e Chirurgiche, Università Politecnica delle Marche,
Ancona; Mauro Galeazzi, Department of Clinical Medicine, Rheumatology Unit, Siena
University; Patrizia Rovere Querini, IRCCS San Raffaele Scientific Institute, Milan;
Sergio Migliaresi, Rheumatology Unit Second University of Naples.
Argentine Collaborative Group: Hugo R. Scherbarth, Jorge A. Lopez, and Estela L.
Motta, Servicio de Reumatología, Hospital Interzonal General de Agudos,
Oscar Alende, Mar del Plata; Susana Gamron, Cristina Drenkard, Emilia Menso, Servicio
de Reumatología de la UHMI 1, Hospital Nacional de Clínicas,
Universidad Nzacional de Córdoba; Alberto Allievi and Guillermo A. Tate,
Organización Médica de Investigación, Buenos
Aires; José L. Presas, Hospital General de Agudos Dr. Juán A.
Fernandez, Buenos Aires; Simon A. Palatnik, Marcelo Abdala, and Mariela Bearzotti,
Facultad de Ciencias Medicas, Universidad Nacional de Rosario y Hospital Provincial
del Centenario, Rosario; Alejandro Alvarellos, Francisco Caeiro, and Ana Bertoli,
Servicio de Reumatología, Hospital Privado, Centro Medico de
Córdoba; Sergio Paira and Susana Roverano, Hospital José M.
Cullen, Santa Fe; Cesar E. Graf and Estela Bertero, Hospital San Martín,
Paraná; Cesar Caprarulo and Griselda Buchanan, Hospital Felipe Heras,
Concordia, Entre Ríos; Carolina Guillerón, Sebastian
Grimaudo, and Jorge Manni, Departamento de Inmunología, Instituto de
Investigaciones Médicas “Alfredo Lanari,” Buenos
Aires; Luis J. Catoggio, Enrique R. Soriano, and Carlos D. Santos,
Sección Reumatología, Servicio de Clínica Medica,
Hospital Italiano de Buenos Aires y Fundación Pedro M. Catoggio para el
Progreso de la Reumatología, Buenos Aires; Cristina Prigione, Fernando A.
Ramos, and Sandra M. Navarro, Servicio de Reumatología, Hospital
Provincial de Rosario; Guillermo A. Berbotto, Marisa Jorfen, and Elisa J. Romero,
Servicio de Reumatología Hospital Escuela Eva Perón,
Granadero Baigorria, Rosario; Mercedes A. Garcia, Juan C. Marcos, and Ana I. Marcos,
Servicio de Reumatología, Hospital Interzonal General de Agudos General
San Martín, La Plata; Carlos E. Perandones and Alicia Eimon, Centro de
Educación Médica e Investigaciones Clínicas
(CEMIC), Buenos Aires; and Cristina G. Battagliotti, Hospital de Niños
Dr. Orlando Alassia, Santa Fe.
German Collaborative Group: K. Armadi-Simab and Wolfgang L. Gross, Abteilung
Rheumatologie, University Hospital of Schleswig-Holstein, Campus Luebeck,
Rheumaklinik Bad Bramstedt; Erika Gromnica-Ihle, Rheumaklinik Berlin-Buch;
Hans-Hartmut Peter, Medizinische Universitaetsklinik, Abteilung Rheumatologie und
Klinische Immunologie, Freiburg; Karin Manger, Medizinische Klinik III der FAU
Erlangen-Nuernberg; Sebastian Schnarr, Henning Zeidler, Abteilung Rheumatologie,
Medizinische Hochschule Hannover; Reinhold E. Schmidt, Abteilung Klinische
Immunologie, Medizinische Hochschule Hannover.
Spanish Collaborative Group: Norberto Ortego and José L Callejas,
Servicio Medicina Interna, Hospital Clínico San Cecilio, Granada; Juan
Jiménez-Alonso and Mario Sabio, Servicio de Medicina Interna, Hospital
Virgen de las Nieves, Granada; Julio Sánchez-Román and
Francisco J. Garcia-Hernandez, Servicio de Medicina Interna, Hospital Virgen del
Rocio, Seville; Mayte Camps, Servicio Medicina Interna, Hospital Carlos Haya, Malaga;
Miguel Angel López-Nevot, Servicio de Inmunología, Hospital
Virgen de las Nieves, Granada; Maria F. González-Escribano, Servicio de
Inmunología, Hospital Virgen de las Nieves, Seville.
SLEGEN consortium: John H. Harley, Oklahoma Medical Research Foundation, Oklahoma
City, Oklahoma, USA; Marta Alarcon Riquelme, Uppsala University, Sweden, and Oklahoma
Medical Research Foundation; Robert Kimberly, University of Alabama, Birmingham, USA;
Lindsey Criswell, UCSF, San Francisco, California, USA; Carl Langefeld, Wake Forest
University, Winston-Salem, North Carolina, USA; Betty Tsao, UCLA, Los Angeles,
California, USA; and Chaim Jacob, University of Southern California, Los Angeles,
View Supplemental data
View Supplemental figure 1
The following funding sources are acknowledged: the Alliance for Lupus Research; the NIH
(grant R01 AR50812); the Swedish Research Council (grant 12673); the Torsten och Ragnar
Söderbergs stiftelser; the Gustaf V 80-Year Jubilee Foundation; the National
Arthritis Foundation (Arthritis Investigator Award to K. Liu); the Swedish Association
Against Rheumatism; the Knut and Alice Wallenberg Foundation through the Royal Swedish
Academy of Sciences (to M.E. Alarcón-Riquelme); the Spanish Ministerio de
Educacion y Ciencia (grant SAF2006-00398); and the Regione Piemonte (grants 2003 and
Authorship note: Kui Liu, Quan-Zhen Li, Angelica M. Delgado-Vega,
Anna-Karin Abelson, Elena Sánchez, and Jennifer A. Kelly are
co–first authors. Edward K. Wakeland, Marta E.
Alarcón-Riquelme, and Chandra Mohan are co–senior authors.
Conflict of interest: The authors have declared that no conflict of
Nonstandard abbreviations used: AIGN, anti-GBM Ab–induced
glomerulonephritis; B6, C57BL/6; BK, bradykinin; GBM, glomerular basement membrane;
GN, glomerulonephritis; OR, odds ratio.
Citation for this article:J. Clin. Invest.119:911–923 (2009). doi:10.1172/JCI36728
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