Allelic Variants of Complement Genes Associated with Dense Deposit Disease

Abstract

The alternative pathway of the complement cascade plays a role in the pathogenesis of dense deposit disease (DDD). Deficiency of complement factor H and mutations in CFH associate with the development of DDD, but it is unknown whether allelic variants in other complement genes also associate with this disease. We studied patients with DDD and identified previously unreported sequence alterations in several genes in addition to allelic variants and haplotypes common to patients with DDD. We found that the likelihood of developing DDD increases with the presence of two or more risk alleles in CFH and C3. To determine the functional consequence of this finding, we measured the activity of the alternative pathway in serum samples from phenotypically normal controls genotyped for variants in CFH and C3. Alternative pathway activity was higher in the presence of variants associated with DDD. Taken together, these data confirm that DDD is a complex genetic disease and may provide targets for the development of disease-specific therapies.

Full text

Allelic Variants of Complement Genes Associated with
Dense Deposit Disease
Maria Asuncion Abrera-Abeleda,*
†
Carla Nishimura,
†
Kathy Frees,
†
Michael Jones,
†
Tara Maga,*
†
Louis M. Katz,
§
Yuzhou Zhang,
†
and Richard J.H. Smith*
†‡
*Interdisciplinary PhD Program in Genetics,
†
Department of Otolaryngology–Head and Neck Surgery, and
‡
Department of Medicine, University of Iowa, Iowa City, Iowa; and
§
Mississippi Valley Regional Blood Center,
Davenport, Iowa
ABSTRACT
The alternative pathway of the complement cascade plays a role in the pathogenesis of dense deposit
disease (DDD). Deficiency of complement factor H and mutations in CFH associate with the development
of DDD, but it is unknown whether allelic variants in other complement genes also associate with this
disease. We studied patients with DDD and identified previously unreported sequence alterations in
several genes in addition to allelic variants and haplotypes common to patients with DDD. We found that
the likelihood of developing DDD increases with the presence of two or more risk alleles in CFH and C3.
To determine the functional consequence of this finding, we measured the activity of the alternative
pathway in serum samples from phenotypically normal controls genotyped for variants in CFH and C3.
Alternative pathway activity was higher in the presence of variants associated with DDD. Taken together,
these data confirm that DDD is a complex genetic disease and may provide targets for the development
of disease-specific therapies.
J Am Soc Nephrol 22: 1551–1559, 2011. doi: 10.1681/ASN.2010080795
The complement system is an integral arm of innate
immunity that facilitates lysis, opsonization, and
clearance of pathogens.
1
Its three initiating arms—
the classical, lectin, and alternative pathways—re-
spond to different triggers to generate an amplify-
ing complex known as the C3 convertase (C3bBb).
The classical pathway typically requires antibodies
for activation, whereas the mannose-binding lectin
and alternative pathways are activated by antigens
and C3 hydrolysis, respectively.
C3 hydrolysis is the reaction of a thioester on C3
with water to form C3(H
2
O). The process occurs
spontaneously, and consequently the alternative path-
way (AP) is continuously active, albeit at a low rate.
2
Unchecked, C3(H
2
O) reacts with complement factor
B (fB) to generate the initial C3 convertase C3(H
2
O)B,
which is converted to C3(H
2
O)Bb in the presence of
complement factor D (fD). Additional cleavage of C3
to C3b leads to formation of C3 convertase, which
continues to catalyze the cleavage of C3 to C3a and
C3b in a potent amplification loop.
3
C3b molecules
that associate with C3 convertase form C5 convertase
(C3bBbC3b), which cleaves C5 to initiate the terminal
complement cascade (TCC). The TCC culminates in
formation of membrane attack complex, a multimeric
transmembrane channel comprised of C5b, C6, C7,
C8, and polymeric C9 that causes osmotic lysis of tar-
get pathogens.
4,5
Because the AP does not recognize target-spe-
cific activators and is constitutively active, a num-
ber of strategies have evolved to regulate AP activity
and discriminate between activating (pathogenic)
Received August 2, 2010. Accepted April 3, 2011.
Published online ahead of print. Publication date available at
www.jasn.org.
Correspondence: Dr. Richard J.H. Smith, Departments of Oto-
laryngology–Head and Neck Surgery and Medicine, Caver Col-
lege of Medicine, The University of Iowa, 5270 CBRB Building,
Iowa City, IA 52242. Phone: ⫹319 335 6501; Fax: ⫹613 353 5869;
E-mail: richard-smith@uiowa.edu
Copyright © 2011 by the American Society of Nephrology
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www.jasn.org
J Am Soc Nephrol 22: 1551–1559, 2011
ISSN : 1046-6673/2208-1551
1551

and nonactivating (self) surfaces.
6
The major regulator of AP
in plasma is complement factor H (fH). fH accelerates the de-
cay of C3bBb, acts as a cofactor for complement factor I (fI)-
mediated proteolytic inactivation of C3b, and competes with
fB for binding to C3b.
7,8
When fH has high affinity for a surface
or for surface-bound C3b, AP activation is stopped; if affinity is
low, AP activation proceeds, and opsonization and lysis occur.
The AP has been implicated in the pathogenesis of dense
deposit disease (DDD), a rare renal disease that affects two of
1,000,000 persons and progresses to end-stage renal failure in
half of patients within 10 years of diagnosis.
9–13
DDD is named
for the pathognomonic amorphous electron-dense deposits
that must be present in the glomerular basement membranes
on renal biopsy to make the diagnosis. Affected patients typically
present with nonspecific signs and symptoms of glomerular dam-
age such as nephrotic syndrome, hypertension, hematuria, and
proteinuria; however, evidence of AP dysregulation is also pres-
ent.
14
C3 serum levels are often exceedingly low, and in most
patients, autoantibodies to C3 convertase known as C3 ne-
phritic factors (C3Nefs) are found.
15,16
A few DDD patients
also have autoantibodies to fH (FHAA) or fB (FBAA).
17–19
Over the long term, DDD patients develop visual impairment
secondary to ocular deposits known as drusen in Bruch’s
membrane.
20
Mutations and polymorphisms in CFH have been associ-
ated with DDD, and on that basis we hypothesized that novel
alterations and known polymorphisms in other complement
genes may play a role in DDD.
21,22
Because the AP is continu-
ously activated at a low rate in human plasma, we also hypoth-
esized that AP activity among individuals differs and that con-
trols carrying DDD “risk” alleles have intrinsically higher AP
activity compared with other controls.
RESULTS
DDD Cases and Controls
Sixty-six patients with biopsy-proven DDD were ascertained
in nephrology divisions and enrolled in this study. The control
group was comprised of 165 age-, gender-, and ethnicity-
matched individuals. The status of the control group with re-
spect to age-related macular degeneration and/or other com-
plement-mediated disease was unknown (Table 1). All patients
and controls were American Caucasians who identified them-
selves as of Northern European heritage. Patients with ambig-
uous/unknown race were excluded from the analysis. All pro-
cedures were approved by the Institutional Review Board of
the University of Iowa, Carver College of Medicine.
Novel Sequence Alterations
Genomic DNA extracted from blood samples of patients and
controls (PAXgene Blood DNA Kit, Qiagen, Valencia, Califor-
nia) was used to amplify and bidirectionally sequence the cod-
ing regions and intron-exon boundary junctions of C3
(NM_000064), CFH (NM_000186), CFHR5 (NM_030787), C3aR1
(NM_004054), C5aR1 (NM_001736), CR1 (NM_000651), and
ADAM19 (NM_033274). Novel missense variants in DDD patients
were identified in four genes: C3 p.K1203R, C3aR1 p.L84S, CR1
p.V1222L, and ADAM19 p.G507S (Table 2). These changes
were not found in any controls and are not reported in single
nucleotide polymorphism (SNP) databases. Each variant was
found in a single DDD patient except C3aR1 p.L84F, which
was found in two patients. PolyPhen predicted this sequence
change to be possibly damaging; SIFT predicted C3 p.K1203R
to be possibly damaging; and Align GVGD predicted that
ADAM19 p.G507S is likely to interfere with protein function.
CR1 p.V1222L was classified as benign by PolyPhen, SIFT, and
Align GVGD.
Association Analyses
A CNV in C4A, which renders a null allele, and 18 SNPs were
selected for association analysis based on possible function and
data from other complement-mediated diseases like age-re-
lated macular degeneration and atypical hemolytic uremic syn-
drome (aHUS). The SNPs included four in C3 (rs2230199,
rs2230201, rs1047286, and rs2230203), five in CFH (rs3753394,
rs800292, rs1061170, rs3753396, and rs1065489), three in CFHR5
(rs9427661, rs9427662, and rs800292), two in C5aR1 (rs4467185 and
rs11008897), three in CR1 (rs3738467, rs2274567, and rs3811381)
and one in ADAM19 (rs1422795). Five SNPs were eliminated
from further consideration because they were in linkage dis-
equilibrium with nearby SNPs included in the analysis (C3
rs2230203; CFHR5 rs9427661; CR1 rs2274567 and rs3811381;
and C5aR1 rs11008897).
Using a chi-squared test of independence without correc-
tion, the C4A CNV and five SNPs with a P-value ⬍0.05 were
Table 1. Demographics of DDD cases and controls
DDD Cases Controls
Number 66 165
Males (%) 25 (38%) 60 (37%)
Females (%) 41 (62%) 102 (63%)
Ethnicity Caucasians Caucasians
Average age ⫾ SD 19.48 ⫾ 9.48 18.44 ⫾ 1.37
Table 2. Novel sequence variants found in DDD patients
Gene Variant Patients ConSeq PolyPhen SIFT Align GVGD
C3 c0.3607 A⬎G p.K1203R 1 1 Benign Affects protein
function
Least likely to interfere with function
C3aR1 c0.250 C⬎T p.L84F 2 4 Possibly damaging Tolerated Least likely to interfere with function
CR1 c0.3664 G⬎T p.V1222L 1 2 Benign Tolerated Least likely to interfere with function
ADAM19 c0.1522 G⬎A p.G507S 1 1 Benign Tolerated Most likely to interfere with function
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1552 Journal of the American Society of Nephrology J Am Soc Nephrol 22: 1551–1559, 2011

considered nominally associated with the DDD phenotype
[CFH p.Y402H (rs1061170), C3 p.R102G (rs2330199), C3
p.P314L (rs1047286), CFHR5 ⫺20 T⬎C (rs9427662), and
ADAM19 p.S284G (rs1422795)]. With Bonferroni correction
(
␣
⫽ 0.004), ADAM19 SNP rs1422795 (P ⫽ 5.49E-05), C4A
CNV (P ⫽ 3.29E-05), and C3 SNP rs1047286 (P ⫽ 0.0018)
were associated with DDD. With correction for multiple test-
ing using the false discovery rate method described by Benja-
mini and Hochberg to minimize the likelihood of rejecting
false negatives, C3 SNP rs2330199 (P ⫽ 0.0065), CFH SNP
rs1061170 (P ⫽ 0.019), and CFHR5 SNP rs9427662 (P ⫽ 0.02)
were also associated with DDD (
␣
⫽ 0.021).
23
The Cochran-
Armitage trend test gave nearly identical results. For each vari-
ant, the minor allele was the risk allele with the exception of
CFHR5, where the minor allele was protective (Table 3).
Haplotype Analyses
Haplotype analyses were performed using an expectation-
maximization (EM) algorithm for all genes. In CFH, four
SNPs—⫺331 T⬎C (rs3753394), p.V62I (rs800292), p.Y402H
(rs1061170), and p.Q673 (rs3753396)— define a low-risk
(protective) haplotype: CATA or haplotype 2 (odds ratio [OR],
0.58; confidence interval [CI], 0.33 to 1.00) (Table 4). A hap-
lotype analysis by Pickering and colleagues using the same
SNPs produced similar results (OR, 0.42; CI, 0.14 to 1.24).
24
For C3, a linkage disequilibrium analysis was done to identify
haploblocks. Haplotype analysis was then performed using
SNPs in the haplotype block p.R102G (rs2230199), p.R304
G⬎A (rs2230201), p.P314L (rs1047286), and p.P518 C⬎A
(rs1047286). The “at-risk” haplotype was GGTA (haplotype 2)
(Table 5).
Gene-Gene Interaction
To evaluate SNP-based gene-gene interactions, we selected
SNPs based on known protein interactions (i.e., C3 binds to
fH and CFHR5) and applied multifactor dimensionality re-
duction. This process predicted a synergistic interaction be-
tween CFH p.V62I and C3 p.P314L (Figure 1). Main effect
and two- and three-variant combination analyses were per-
formed using CFH p.Y402H, CFH p.V62I, C3 p.R102G, and
C3 p.P314L, and the EM algorithm to predict allele combi-
nation frequencies (Table 6). To determine significant allele
combinations in DDD patients, we computed ORs,95% CIs,
and P-values. The most significant SNP combination was
CFH p.Y402H ⫻ CFH p.V62I ⫻ C3 p.P314L, which had the
highest OR. CFH p.Y402H ⫻ C3 p.P314L had the second
Table 3. Risk and protective alleles for developing DDD
Gene Variant
DDD Controls
Chi-squared
P-value
a
Cochran
Armitage
P-value
a
OR 95% CI
Minor
Allele
Allele
Frequency
Minor
Alleles
Allele
Frequency
CFHR5 ⫺20 T⬎C 6 0.045 37 0.11 0.020 0.020 0.38 0.16 to 0.92
CFH Y402H 64 0.48 121 0.37 0.019 0.029 1.63 1.08 to 2.45
C3 R102G 43 0.36 68 0.21 0.0065 0.0091 1.86 1.19 to 2.92
C3 P314L 44 0.33 65 0.20 0.0018 0.0021 2.04 1.30 to 3.20
ADAM19 S284G 58 0.44 82 0.25 5.49E-05 0.00012 1.61 1.04 to 2.51
C4A Deletion 24 0.18 19 0.06 3.29E-05 1.17E-05 1.88 1.00 to 3.51
a
Significant P-values: P ⬍ 0.05 (uncorrected); P ⬍ 0.021 (FDR); P ⬍ 0.004 (Bonferroni); DDD, n ⫽ 66; controls, n ⫽ 165.
Table 4. Haplotype analysis of CFH SNPs using SNPStats
Haplotype ⴚ331 T>C V62I (G>A) Y402H (T>C) Q673 (A>G)
Control
Frequency
DDD
Frequency
OR (95% CI) P-value
1 C G C A 0.3218 0.4048 1.00 —
2 C A T A 0.2420 0.1743 0.58 (0.33 to 1.00) 0.05
3 T G T G 0.1050 0.1084 — NS
4 C G T A 0.1193 0.1050 — NS
5 T G C A 0.0159 0.0180 — NS
6 C G T G 0.0065 0.0246 — NS
The reference haplotype, which is the most common haplotype in both groups, has OR ⫽ 1; the protective haplotype is in bold type. P-values ⬍ 0.05 are
significant.
Table 5. Haplotype analysis for C3 SNPs using SNPStats
Haplotype R102G (C>G) R304 (A>G) P314L (C>T) P518 (C>A)
Control
Frequency
DDD
Frequency
OR (95%CI) P-value
1 C G C C 0.6417 0.5004 1.00 —
2 G G T A 0.1354 0.2389 2.12 (1.24 to 3.60) 0.0061
3 C A C C 0.1305 0.1095 1.13 (0.63 to 2.03) 0.54
4 C G T A 0.0218 0.0565 — NS
The reference haplotype, which is the most common haplotype in both groups, has OR ⫽ 1; the risk haplotype is in bold type. P-values ⬍ 0.05 are significant.
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Complement Genes and DDD
1553

highest OR. These data mean that likelihood of developing
DDD increases with the presence of two or more risk alleles
in CFH and C3.
Complement Activity
To determine whether the fH-C3 interaction had a functional
consequence, we tested AP activity in genotyped controls. Us-
ing unconditional logistic regression, a significant association
was noted between APH50 and CFH p.V62I, C3 p.R102G, and
C3 p.P314L (P ⫽ 0.0193, 0.0166, 0.0054, respectively). Pearson
goodness-of-fit P-values indicated that the predicted model
was a good model for the observed data (P ⬎ 0.05), and the OR
indicated that the presence of risk allele CFH p.V62, C3
p.G102, or C3 p.L314 doubled the risk of a low APH50 (high
complement activity).
The association between APH50 and C3 p.R102G and C3
p.P314L was verified using a Mann-Whitney U-test by com-
paring the medians between controls homozygous for C3 R102
or C3 P314 with controls either homozygous or heterozygous
for C3 G102 or C3 L314. Controls carrying either C3 G102 or
C3 L314 (in heterozygosity or homozygosity) had significantly
lower APH50 values and therefore higher AP activity than con-
trols homozygous for either C3 R102 or C3 P314 (P ⫽ 0.045
and 0.0176, respectively). There were no differences in protein
levels between groups (C3 G102 or C3 L314 C3 levels,
1.29 ⫾ 0.95 and 1.34 ⫾ 0.95 mg/ml, respectively; C3 R102 or
C3 P314 C3 levels, 1.19 ⫾ 0.92 and 1.15 ⫾ 0.92 mg/ml, respec-
tively; P ⬎ 0.05) (Figure 2, A and B).
In two variant combinations, controls with at least one copy
of both C3 G102 and C3 L314 demonstrated lower APH50
values (higher AP activity) than controls homozygous for both
C3 R102 and C3 P314 (P ⫽ 0.0329). Again, there were no
differences in protein levels between groups (C3 G102 and C3
L314 C3 serum levels, 1.29 ⫾ 0.93 mg/ml; C3 R102 and C3
P314 (1.18 ⫾ 0.93 mg/ml) (P-value ⫽ 0.5956) (Figure 2C).
Comparison of major and minor alleles of CFH H402Y
showed that higher %AP values (lower AP activity) were pres-
ent in controls homozygous for CFH Y402 (P ⫽ 0.0345) com-
Table 6. ORs of main effects and variant combinations between CFH and C3
Risk Alleles
DDD
Frequency
Control
Frequency
OR 95% CI P-value
Main effects
CFH Y402H H 47 (0.71) 93 (0.56) 1.92 1.04 to 3.54 0.034
CFH V62I V 23 (0.35) 73 (0.44) 0.67 0.37 to 1.22 0.19
C3 R102G G 37 (0.56) 57 (0.36) 2.42 1.35 to 4.33 0.0028
C3 P314L L 37 (0.56) 58 (0.35) 2.35 1.32 to 4.21 0.0037
Two-variant combinations
CFH Y402H ⫻ CFH V62I H ⫻ V 32 (0.49) 56 (0.34) 1.83 1.02 to 3.27 0.039
CFH Y402H ⫻ C3 R102G H ⫻ G 10 (0.15) 14 (0.08) 2.61 1.30 to 5.24 0.0077
CFH Y402H ⫻ C3 P314L H ⫻ L 12 (0.18) 12 (0.07) 3.58 1.72 to 7.45 8.00E-04
CFH V62I ⫻ C3 R102G V ⫻ G 17 (0.27) 27 (0.16) 1.63 0.95 to 2.79 0.075
CFH V62I ⫻ C3 P314L V ⫻ L 21 (0.32) 24 (0.15) 2.47 1.43 to 4.27 0.0014
C3 R102G ⫻ C3 P314L G ⫻ L 18 (0.27) 29 (0.18) 1.87 1.14 to 3.07 0.014
Three-variant combinations
CFH Y402H ⫻ CFH V62I ⫻ C3 R102G H ⫻ V ⫻ G 10 (0.15) 14 (0.09) 2.74 1.26 to 5.94 0.011
CFH Y402H ⫻ CFH V62I ⫻ C3 P314L H ⫻ V ⫻ L 12 (0.18) 12 (0.07) 4.51 2.01 to 10.13 3.00E-04
CFH Y402H ⫻ C3 R102G ⫻ C3 P314L H ⫻ G ⫻ L 7 (0.11) 10 (0.06) 2.49 1.05 to 5.91 0.04
CFH V62I ⫻ C3 R102G ⫻ C3 P314L V ⫻ G ⫻ L 16 (0.24) 22 (0.13) 2.06 1.09 to 3.89 0.026
P ⬍ 0.05 are significant; DDD, n ⫽ 66; controls, n ⫽ 165.
Figure 1. Interaction graph showing the synergistic interaction
between CFH and C3. Red or orange lines indicate strong syner-
gistic interaction; blue or green lines indicate redundant interac-
tion or no interaction. Values inside boxes or nodes indicate
information gain (IG) of individual attribute or main effects,
whereas values between nodes exemplify IG of pairwise combi-
nation of attributes or interaction effects. C3 p.P314L has the
highest IG, whereas CFH p.V62I has the lowest. However, the IG
for the interaction of these two SNPs is the highest among pair-
wise combinations.
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pared with controls carrying at least one copy of CFH H402
(CFH H402 fH serum levels, 2.51 ⫾ 0.91 mg/ml; CFH Y402 fH
serum levels, 2.17 ⫾ 0.84 mg/ml; P ⬎ 0.05) (Figure 2D). Al-
though AP activity in controls homozygous for both CFH
H402 and C3 G102 could not be studied due to the rarity of the
CFH H402 plus C3 G 102 homozygous genotype (approxi-
mately one per 230 persons), we did com-
pare controls homozygous for C3 G102, C3
L314, or CFH H402 (risk alleles) to controls
homozygous for C3 R102, C3 P314, or CFH
Y402 and noted consistently greater AP ac-
tivity associated with DDD risk alleles (P ⬍
0.05). This observation was also true when
AP activity was compared between controls
homozygous for both C3 G102 and C3
L314 versus controls homozygous for both
C3 R102 and C3 P314 (P ⬍ 0.05) (Table 7).
These data confirm that AP activity is
greater in controls with DDD risk alleles
compared with controls without these al-
leles, supporting a genetic basis for differ-
ences in normal AP activity.
DISCUSSION
The AP and TCC form a complex network
of pathways with amplification loops and
cascades. Dysregulation of this system un-
derlies two rare renal diseases: aHUS and
DDD. In aHUS, dysregulation occurs at the
cell surface, and multiple mutations in
complement genes and their functional im-
pact have been characterized in affected pa-
tients.
25–32
DDD is rarer than aHUS and
has not been studied as thoroughly.
13,14,21,33
It is caused by fluid-phase dysregulation of
the C3 and C5 convertases that leads to ac-
cumulation of complement debris—C3b
breakdown products and sMAC—in renal
glomeruli.
34
We identified novel missense sequence
variants in four genes (C3, C3aR1, CR1,
and ADAM19) in DDD patients. Although
we have not determined the effect of these
variants on complement activity, the rarity
of these changes and their presence only in
DDD patients suggests that they may have
functional significance. In testing gene-
gene interactions, we also found that four
SNPs in CFH and C3—namely CFH
p.Y402H, CFH p.V62I, C3 p.R102G, and
C3 p.P314L—are associated with DDD and
that the presence of two or more of these
risk alleles increases the ORs of developing
DDD (Table 6). The additive effect of these SNPs on DDD risk
is consistent with the known interaction of fH and C3 and
defines a predisposing at-risk complement haplotype or “com-
plotype” in DDD patients.
The functional consequence of the DDD at-risk complo-
type is increased AP activity. Functional studies of the first
Figure 2. (A) Box plot shows that controls with the DDD risk allele C3 G102 have lower
APH50 values (n ⫽ 38; mean ⫽ 82.67) than controls who are homozygous for the
protective allele C3 R102 (n ⫽ 64; mean ⫽ 96.17) (P-value ⫽ 0.0450). (B) Controls with
the risk allele C3 L314 (n ⫽ 38; mean ⫽ 80.67) have lower APH50 values than controls
who are homozygous for the protective allele C3 P314 (n ⫽ 64; mean ⫽ 97.35)
(P-value ⫽ 0.0176). (C) Controls with both C3 G102 and L314 (n ⫽ 41; mean ⫽ 82.49)
have lower APH50 values than controls homozygous for both C3 R102 and P314 (n ⫽
61; mean ⫽ 96.95). (D) Controls with the risk allele CFH H402 (n ⫽ 59; mean ⫽ 79.44)
have lower %AP values than controls homozygous for the protective allele CFH Y402
(n ⫽ 43; mean ⫽ 85.95) (P-value ⫽ 0.0345). Legends: (⫹), mean; line in box, median or
50th percentile; lower whisker, lowest data still within 1.5 interquartile range (IQR) of
the lower quartile; upper whisker, highest data still within 1.5 IQR of the upper quartile;
circles, outliers. (A–C, APH50 values; D, %AP values).
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Complement Genes and DDD
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CFH SNP, Y402H, has shown that the H402 variant decreases
binding to C-reactive protein and heparin and alters affinity
for ocular membranes.
35–37
Our data show that it is also asso-
ciated with increased AP activity. The second CFH SNP,
p.V62I, is in SCR1 of fH and contributes to a C3b binding site
important for fluid-phase complement control through fI-me-
diated cofactor activity and fH/fB competition for C3b.
38
It is
interesting to note that despite finding that the protective allele
CFH I62 was more frequently found in controls than DDD
patients, CFH p.V62I was not associated with the DDD phe-
notype in this study (chi-squared test of independence and
Cochran-Armitage trend test). In an earlier study, in contrast,
we found that it was (chi-squared test of independence), a
discrepancy that may be due to the small number of cases and
controls in both studies, which can cause inflated type I or II
errors using a chi-squared test of independence.
22
However, it
is also possible that the main effect of CFH p.V62I is not inde-
pendent but synergistic with another variant, consistent with
our gene-gene interaction analysis, which found that CFH
p.V62I and C3 p.P314L together are associated with DDD.
The associated C3 SNPs are in the macroglobulin (MG)
domains of C3. C3 p.R102G is also known as the C3 F/S allele
and lies in MG1 near the thioester domain (TED).
39,40
Based
on the three-dimensional structure of C3 using SNPs3D, it is
on the protein surface. With arginine at this position, an elec-
tronegative interface is created on MG1 that can interact with the
strong electropositive region on the exposed TED surface to sta-
bilize C3b. In the absence of stabilizing electrostatic interactions,
because glycine is not electronegative, TED binding to target sur-
faces could be affected.
41,42
The second C3 SNP, p.P314L, is also known as the
HAV4 –1⫾ allele and lies in MG3, a binding site for fB.
43
SNPs3D places this SNP on the protein surface, and PolyPhen
and SIFT predict the change to be probably damaging, with an
effect on function. The C3 L314 allele also reacts with the
monoclonal antibody, HAV4 –1, consistent with a structural
alteration that exposes or creates an epitope recognized by the
antibody. Both C3 SNPs are associated with aHUS and sys-
temic lupus erythematosus.
27,44–46
Synergism between CFH p.V62I and C3 p.P314L may occur
because the fH variant decreases binding to C3b, whereas the C3
variant increases binding to fB. These interactions would promote
fB association with C3b to form C3 convertase while simultane-
ously decreasing fH affinity for and regulation of C3b. The pre-
dicted outcome would be a more active AP, which we demon-
strated in functional assays of AP activity using genotyped control
serum. However, it is also possible that the
major effect of these interactions is to expose
novel epitopes on C3 convertase that favor
the development of C3Nefs. Consistent with
this second possibility, Finn and Mathieson
have shown an association between C3 G102
and the presence of C3Nefs in serum.
47
In summary, we have shown that DDD
patients segregate a complotype that is
comprised of risk alleles in CFH and C3. This complotype is
associated with higher AP activity, which is consistent with the
interaction of these two proteins. The DDD complotype may
predispose to disease development by facilitating generation of
autoantibodies like C3Nefs. These data also suggest that deep
sequencing of all complement genes in DDD patients is war-
ranted to better define the complotype of this complex disease.
Determining the complex genotype associated with DDD may
provide insight into the care of affected patients by identifying
complotypes associated with disease progression and clinical
outcome.
CONCISE METHODS
Mutation Screening and Analyses
Genomic DNA was extracted from blood samples of patients and
controls using commercially available kits (PAXgene Blood DNA Kit,
Qiagen, Valencia, California). Coding regions and intron-exon
boundary junctions of C3 (NM_000064), CFH (NM_000186),
CFHR5 (NM_030787), C3aR1 (NM_004054), C5aR1 (NM_001736),
CR1 (NM_000651), and ADAM19 (NM_033274) were amplified and
screened for sequence variants and polymorphisms using bidirec-
tional sequencing.
22
To identify the C4A deletion, two sets of primers
were used that detected a nondeleted C4A (5.4 kb) band and/or a
deleted C4A (5.2 kb) band.
48
The quantitative alleles, H/L, for CR1
were determined by restriction digestion with HindIII. The H allele
generates a 1.8-kb restriction digestion band, whereas the L allele
generates 1.3- and 0.5-kb bands.
49
Possible functional effects of vari-
ants were predicted using ConSeq, PolyPhen, and SIFT,
50–52
Align
GVGD,
53,54
and SNPs3D.
55
Alternative Pathway Functional Studies
Functional studies were completed on 102 anonymized blood and
serum samples obtained from the Mississippi Valley Regional Blood
Center in Davenport, Iowa. Serum was immediately frozen and kept
at ⫺80°C until use. DNA was extracted from leukocytes using stan-
dard techniques (PAXgene Blood DNA Kit, Qiagen, Valencia, Cali-
fornia). Each sample was genotyped and screened for CFH and C3
SNPs associated with DDD (C3 p.R102G, p.R304, p.P314L, p.P518;
CFH ⫺331 T⬎C, p.V62I, p.Y402H, p.Q673).
Alternative Pathway Hemolytic Assay
The AP hemolytic assay was based on a standard hemolytic assay
protocol.
56
Absorbance (Abs) was measured at 415 nm using a micro-
plate reader. Fractional hemolysis for each reading was computed as
Table 7. AP activity associated with homozygosity for the listed genotypes
Comparison
Protective
Genotype
Mean AP
Activity
Risk Genotype
Mean AP
Activity
a
P-value
1 C3 R102 96.17 C3 G102 58.39 0.001
2 C3P314 97.35 C3 L314 60.29 0.004
3 CFH Y402 85.95 CFH H402 78.47 0.05
4 C3 R102 ⫹ P314 82.49 C3 G102 ⫹ L314 60.29 0.005
a
AP activity expressed as APH50 value except comparison 3, which is %AP value.
CLINICAL RESEARCH www.jasn.org
1556 Journal of the American Society of Nephrology J Am Soc Nephrol 22: 1551–1559, 2011

percentage hemolysis (y) ⫽ (Abs sample ⫺ Abs blank)/(Abs positive
control ⫺ Abs blank) ⫻ 100. Each value was plotted against serum
dilution (x-axis) for each individual to create an S-shaped curve,
which was converted to a linear function of serum dilution (x) versus
y/(1 ⫺ y). The volume at which y/(1 ⫺ y) ⫽ 1 was defined as the
APH50, i.e., that volume of serum in which 50% of red blood cells
hemolyze. This definition means that the lower the APH50, the more
active the AP complement activity.
57
Alternative Pathway Functional Immunoassay
The AP functional immunoassay (Wieslab COMPL AP330 kit; AL-
PCO Immunoassays, Salem, New Hampshire) utilizes microtiter
strips coated with specific activators of the AP. We measured absor-
bance at 405 nm and calculated %AP as (Abs
sample
⫺ Abs
negative control
)/
(Abs
positive control
⫺ Abs
negative control
) ⫻100. Lower %APs are associ
-
ated with greater AP complement activity.
58
C3 and Complement fH Serum Levels
Serum levels of C3 and fH were determined using commercially avail-
able kits (Genway Biotech, Inc., San Diego, California, and Hycult
Biotechnology, Uden, The Netherlands, respectively). Serum concen-
trations were calculated from a standard plot using either a linear or a
four-parameter fit.
Statistical Analyses
The chi-squared test of independence was used to detect differences in
allele frequencies between cases and controls; P-values ⬍ 0.05 were
considered significant.
59
The Cochran-Armitage trend test was used
to identify linear trends in genotypes and to compare these trends
between cases and controls.
60
Haplotype analyses for all genes were
performed using an EM algorithm in Haploview and SNPStats pro-
grams.
61,62
For each polymorphism, ORs, 95% CI, and Hardy-Wein-
berg equilibrium were computed using SNPStats.
61
Correction for
multiple hypothesis testing was performed using Bonferroni correc-
tion and false discovery rate at
␣
⫽ 0.05 using the Focused Interaction
Testing Framework program.
63
Possible gene-gene interactions were
determined using MDR (www.epistasis.org).
64
For testing association between C3 and CFH alleles and comple-
ment activity, two control groups were considered: one group con-
sisted of all individuals homozygous for the protective allele; the sec-
ond group consisted of all individuals homozygous or heterozygous
for the risk allele. Unconditional logistic regression analysis using a
full model was performed with P-values ⬍0.05 considered significant.
P-values for Pearson goodness-of-fit test were calculated to determine
if the predicted model described the data well (P ⬎ 0.05, rejected the
null hypothesis and the goodness-of-fit model was a good model for
the observed data). ORs and 95% CIs were computed to determine if
alleles were at-risk or protective. Association was analyzed using a
Mann-Whitney U-test (two variables) or Kruskal-Wallis test (three or
more variables) by comparing mean and SD values between groups of
major and minor alleles. C3 and fH serum levels in genotyped con-
trols were compared using unpaired t test analysis. All statistical anal-
yses were done using SAS 9.1.3.
ACKNOWLEDGMENTS
This work was supported in part by National Institutes of Health
Grant DK074409 to R.J.H.S. We are grateful to those patients with
DDD whose participation made this research possible.
Competing Financial Interests: The authors have no relation-
ships with pharmaceutical firms or other entities (such as employ-
ment contracts, consultancy, advisory boards, speaker bureaus, mem-
bership of Board of Directors, stock ownership) that could be
perceived to represent a financial conflict of interest and declare that
no financial conflict of interest exists.
DISCLOSURES
None.
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