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Published in final edited form as: Environ Mol Mutagen. 2011 Dec 15;53(2):145–151. doi: 10.1002/em.21675

Polymorphisms in Complement System Genes and Risk of Non-Hodgkin Lymphoma

Bryan A Bassig 1,*, Tongzhang Zheng 2, Yawei Zhang 2, Sonja I Berndt 1, Theodore R Holford 3, H Dean Hosgood III 1, Wei Hu 1, Brian Leaderer 2, Meredith Yeager 4, Idan Menashe 5, Peter Boyle 6, Jun Xu 1, Kaiyong Zou 7, Yong Zhu 2, Stephen Chanock 4, Nathaniel Rothman 1, Qing Lan 1
PMCID: PMC3391498  NIHMSID: NIHMS385731  PMID: 22170086

Abstract

The complement system plays an important role in inflammatory and immune responses, and recent evidence has suggested that it may also play a role in lymphomagenesis. We evaluated the association between genetic variation in complement system genes and risk of non-Hodgkin lymphoma (NHL) in a population-based case–control study conducted among women in Connecticut. Tag SNPs in 30 complement genes were genotyped in 432 Caucasian incident cases and 494 frequency-matched controls. A gene-based analysis that adjusted for the number of tag SNPs genotyped in each gene showed a significant association with NHL overall (P = 0.04) as well as with diffuse large B-cell lymphoma (DLBCL) (P = 0.01) for the C1RL gene. A SNP-based analysis showed that a C>T base substitution for C1RL rs3813729 (odds ratio (OR)CT = 0.60, 95% confidence interval (CI) = 0.42–0.87, Ptrend = 0.0062) was associated with a decreased risk of overall NHL, as well as for DLBCL (ORCT = 0.39, 95% CI = 0.20–0.73; Ptrend = 0.0034). Additionally, SNPs (C2 rs497309, A>C and C3 rs344550, G>C) in two complement genes were positively associated with marginal zone lymphoma (MZL) and C1QG was associated with CLL/SLL, but these results were based on a limited number of cases. Our results suggest a potential role of the complement system in susceptibility to NHL; however, our results should be viewed as exploratory and further replication is needed to clarify these preliminary findings.

Keywords: lymphoma, C1RL, innate immunity, SNP

INTRODUCTION

Infections and autoimmune disorders have been shown to be positively associated with non-Hodgkin lymphoma (NHL), supporting the potential connection between immune status and lymphomagenesis [Cuttner et al., 2005; Smedby et al., 2006; Engels, 2007]. There is preliminary evidence from association studies that genetic variation in immune response and innate immunity genes are associated with NHL [Forrest et al., 2006; Lan et al., 2006; Rothman et al., 2006; Purdue et al., 2007; Wang et al., 2007].

The complement system plays a vital role in the immune response, particularly in innate immunity. Specifically, complement aids to regulate and coordinate inflammatory responses through the facilitation of leukocyte extravasation, chemotactic response mechanisms, and clearance of apoptotic cells and immune complexes [Markiewski and Lambris, 2007]. While the complement system in general may be involved in immune surveillance and thereby mediate protection from cancer, other evidence has challenged this notion [Markiewski et al., 2008; Markiewski and Lambris, 2009b; Rutkowski et al., 2010]. In particular, complement may also facilitate sustained angiogenesis and cellular proliferation, as well as the dysregulation of mitogenic signaling pathways [Rutkowski et al., 2010]. Moreover, complement protein C5a specifically has been demonstrated to enhance tumor growth through the recruitment and activation of myeloid-derived suppressor cells [Markiewski et al., 2008], and other experimental evidence has suggested an association between complement activation and specific tumor types [Markiewski and Lambris, 2009a].

Few epidemiological studies have directly assessed the relationship between variation in complement genes and cancer. Variant genotypes in the C3 gene were recently positively associated with lung cancer mortality [Suadicani et al., 2011], and a previous study found an increased and decreased risk of NHL for single nucleotide polymorphisms (SNPs) in complement genes C5 (rs7026551, rs2416810) and C9 (rs187875), respectively [Cerhan et al., 2009]. Given the involvement of the complement system in infectious and inflammatory processes, and its association with autoimmune disease [Chen et al., 2010], further examination of the potential association between NHL and genetic variation in complement system genes is warranted. Here, we report the associations between NHL and genetic polymorphisms in 30 complement genes using data from a population-based case–control study conducted in Connecticut.

METHODS

Study Population

The methods for this case–control study of NHL have been previously described [Morton et al., 2003]. Briefly, cases were identified through the Yale Comprehensive Cancer Center’s Rapid Case Ascertainment Shared Resource between 1996 and 2000 and included female patients aged 21–84 years with histologically confirmed, incident NHL (ICD-O, M-9590–9642, 9690–9701, 9740–9750). Pathology slides (or tissue blocks) from all cases were obtained from the original pathology departments and specimens were classified using the World Health Organization NHL classification system by central review. Patients with a previous history of cancer besides nonmelanoma skin cancer were not eligible. Of 832 eligible cases, 601 (72%) completed in-person interviews. Population-based controls with a Connecticut address were identified through random digit dialing (< 65 years of age) or via files from the Health Care Financing Administration (≥ 65 years of age; currently known as The Centers for Medicare and Medicaid Services), and were enrolled over the same time period as cases. Study controls were frequency matched to cases by age in five year strata. Participation rates for study controls were 69% for those contacted via random digit dialing, and 47% among those identified through health care records.

Informed consent was obtained for each participant, and the study was reviewed and approved by the Institutional Review Board at Yale University, the Connecticut Department of Public Health, and the National Cancer Institute (NCI).

Blood Samples and Genotyping

At the time of the interview, blood samples were obtained from 461 (76.7%) consenting cases and from 535 (74.6%) consenting controls. DNA was extracted from samples using a phenol-chloroform extraction method. Genotyping was conducted at the NCI Core Genotyping Facility (Advanced Technology Center, Gaithersburg, MD) using an Illumina GoldenGate platform. DNA from 448 cases and 525 controls was successfully submitted for genotyping. Duplicate samples from 100 study participants and 40 replicate samples from each of two groups of non-Hispanic white volunteer blood donors who were not enrolled in the study were interspersed throughout the plates used for genotype analysis for quality control purposes. In total, 225 SNPs from 30 complement genes or genes in the same region were considered. Genes involved in the activation of the complement system as well as those previously suggested to influence lymphoma risk were evaluated (Supporting Information Table S1). The completion rate for all SNPs was greater than 95%, and the concordance rate for quality control samples was greater than 94% for all assays.

Statistical Analysis

Hardy–Weinberg equilibrium (HWE) was assessed in non-Hispanic white controls for each SNP using a chi-square test; SNPs with a P-value > 0.01 from the chi-square test were considered to be in HWE. To test for an association with NHL at the gene level, a minimum P-test (“minP”) based on permutation resampling was conducted to assess the true statistical significance of the smallest P-trend within each gene region [Chen et al., 2006]. This approach adjusts for the number of tag SNPs tested within each gene region as well as the underlying linkage disequilibrium pattern [Chen et al., 2006]. The minP test was additionally conducted for the most prevalent NHL subtypes in the study population, including diffuse large B-cell lymphoma (DLBCL) (32%), follicular lymphoma (FL) (24%), marginal zone lymphoma (MZL) (7%), and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) (11%).

Unconditional logistic regression was used to estimate odds ratios (ORs) and calculate 95% confidence intervals (CIs) for individual SNPs and NHL, adjusted for age. The models compared the variant allele homozygote and heterozygote to the common allele homozygote, which served as the referent group. A linear trend test assuming an additive genetic model was conducted by assigning an ordinal value of 1, 2, or 3 corresponding to the homozygous wild-type, heterozygote, and homozygous variant genotype, respectively. These scores were then modeled as a continuous variable.

Stratified analyses by NHL subtype were conducted for DLBCL, FL, MZL, and CLL/SLL, using all controls in order to maximize statistical power. The False Discovery Rate (FDR) was applied to the minP test in order to account for multiple comparisons (P < 0.2 considered significant). We examined the haplotype block structure for complement genes that were significant in the overall or subtype analysis using Haploview 4.2. Individual haplotype frequencies were estimated using the Expectation-Maximization algorithm [Excoffier and Slatkin, 1995], and unconditional logistic regression was used to estimate the effect of individual haplotypes, using the most frequent haplotype as the reference group. We limited analyses to Caucasians for a final sample size of 432 cases and 494 controls. Statistical analysis was conducted using Statistical Analysis Software version 9.1.3 (Cary, NC).

RESULTS

Of the 225 SNPs considered, 4 were not in HWE (Supporting Information Table SII). However, none of our significant findings were located in these genes or gene regions. Cases and controls were similar with respect to age, level of education, and having a family history of cancer (Table I).

TABLE I.

Demographic Characteristics of Cases and Controls in a Case–Control Study of NHL in Connecticut Women

Demographic characteristic Cases, n = 432 Controls, n = 494
Age (years)
 <50 86 (20%) 93 (19%)
 50–70 210 (49%) 212 (43%)
 >70 136 (31%) 189 (38%)
Education
 <12 years 53 (12%) 55 (11%)
 12 years-College 327 (76%) 368 (74%)
 Graduate or other 52 (12%) 71 (14%)
Family history of cancera
 No 88 (20%) 122 (25%)
 NHL 9 (2%) 2 (0.4%)
 Other cancer 335 (78%) 370 (75%)
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a

Family history of cancer in first degree relatives.

At the gene level, the C1RL gene region was significantly associated with overall NHL (P = 0.04), as well as with DLBCL (P = 0.01) (Supporting Information Table SI). In addition, there was evidence of an association with CLL/SLL for C1QG (P = 0.04), and with MZL for the C2 (P = 0.02) and C3 (P = 0.03) gene regions (Supporting Information Table SI). However, none of these significant associations at the gene level remained after accounting for the FDR. The most significant SNPs within these genes are shown in Tables II and III. Within the C1RL gene, a C>T base substitution for C1RL rs3813729 was associated with a significantly decreased risk of overall NHL (ORCT = 0.60, 95% CI = 0.42–0.87; Ptrend = 0.0062), as well as a decreased risk of DLBCL (ORCT = 0.39, 95% CI = 0.20–0.73; Ptrend = 0.0034; Table II) adjusted for age. An increased risk of the CLL/SLL subtype was associated with an A>G base substitution for C1QG rs12756603 (ORAG/GG = 2.35, 95% CI = 1.29–4.26; Ptrend = 0.0048; Table III), and two SNPs in the C2 (rs497309; A>C) and C3 (rs344550; G>C) gene regions were significantly associated with an increased risk of MZL (Table III). Stratified analyses by menopausal status, family history of cancer, and having a history of an inflammatory disorder were explored for our positive SNP results and overall NHL but these analyses did not meaningfully impact our findings (data not shown).

TABLE II.

Logistic Regression Analysis of Selected SNPs and Risk of Overall NHL, Diffuse Large B-cell Lymphoma (DLBCL), and Follicular Lymphoma (FL)

SNP Genotype Controls (%) Overall NHL
DLBCL
FL
Cases (%) OR (95% CI) P Cases (%) OR (95% CI) P Cases (%) OR (95% CI) P
C1RL rs3813729 CC 375 80) 362 (87) 1.0 (ref) 123 (91) 1.0 (ref) 83 (84) 1.0 (ref)
CT 94 (20) 56 (13) 0.60 (0.42–0.87) 0.0062 12 (9) 0.39 (0.20–0.73) 0.0034 16 (16) 0.71 (0.40–1.28) 0.26
TT 0 0 — — 0 — — 0 — —
CT or TT 94 (20) 56 (13) 0.60 (0.42–0.87) 0.0062 12 (9) 0.39 (0.20–0.73) 0.0034 16 (16) 0.71 (0.40–1.28) 0.26
Trend 469 418 0.60 (0.42–0.87) 0.0062 135 0.39 (0.20–0.73) 0.0034 99 0.71 (0.40–1.28) 0.26
C1QG rs12756603 AA 350 (73) 302 (71) 1.0 (ref) 92 (67) 1.0 (ref) 75 (74) 1.0 (ref)
AG 120 (25) 110 (26) 1.06 (0.78–1.43) 0.72 42 (31) 1.30 (0.85–1.98) 0.23 22 (22) 0.84 (0.50–1.41) 0.51
GG 12 (2) 11 (3) 1.01 (0.44–2.34) 0.98 3 (2) 1.03 (0.28–3.75) 0.96 4 (4) 1.36 (0.42–4.39) 0.61
AG or GG 132 (27) 121 (29) 1.05 (0.79–1.41) 0.74 45 (33) 1.27 (0.84–1.92) 0.25 26 (26) 0.89 (0.54–1.46) 0.64
Trend 482 423 1.04 (0.80–1.34) 0.77 137 1.20 (0.84–1.73) 0.32 101 0.96 (0.63–1.45) 0.83
C2 rs497309 AA 405 (84) 341 (80) 1.0 (ref) 106 (77) 1.0 (ref) 87 (86) 1.0 (ref)
AC 75 (16) 80 (19) 1.29 (0.91–1.83) 0.15 30 (22) 1.55 (0.96–2.50) 0.07 13 (13) 0.86 (0.45–1.63) 0.64
CC 2 (0.4) 3 (0.7) 1.58 (0.26–9.55) 0.62 1 (0.7) 1.68 (0.15–18.86) 0.68 1 (0.99) 1.89 (0.17–21.17) 0.61
AC or CC 77 (16) 83 (20) 1.30 (0.92–1.83) 0.13 31 (23) 1.56 (0.97–2.49) 0.07 14 (14) 0.89 (0.48–1.66) 0.72
Trend 482 424 1.29 (0.93–1.79) 0.13 137 1.52 (0.97–2.37) 0.07 101 0.94 (0.52–1.67) 0.82
C3 rs344550 GG 198 (41) 170 (40) 1.0 (ref) 49 (36) 1.0 (ref) 49 (49) 1.0 (ref)
CG 220 (46) 190 (45) 1.00 (0.75–1.33) 0.99 65 (47) 1.18 (0.78–1.80) 0.43 41 (41) 0.74 (0.46–1.17) 0.20
CC 64 (13) 62 (15) 1.15 (0.77–1.73) 0.50 23 (17) 1.44 (0.81–2.57) 0.21 11 (11) 0.72 (0.35–1.47) 0.37
CG or CC 284 (59) 252 (60) 1.03 (0.79–1.35) 0.81 88 (64) 1.24 (0.84–1.84) 0.29 52 (51) 0.73 (0.47–1.13) 0.16
Trend 482 422 1.05 (0.87–1.27) 0.59 137 1.20 (0.91–1.58) 0.20 101 0.81 (0.58–1.12) 0.20
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TABLE III.

Logistic Regression Analysis of Selected SNPs and Risk of Marginal Zone Lymphoma (MZL) and Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma (CLL/SLL)

SNP Genotype Controls (%) MZL
CLL/SLL
Cases (%) OR (95% CI) P Cases (%) OR (95% CI) P
C1RL rs3813729 CC 375 (80) 24 (83) 1.0 (ref) 41 (85) 1.0 (ref)
CT 94 (20) 5 (17) 0.76 (0.28–2.07) 0.60 7 (15) 0.66 (0.29–1.52) 0.33
TT 0 0 — — 0 — —
CT or TT 94 (20) 5 (17) 0.76 (0.28–2.07) 0.60 7 (15) 0.66 (0.29–1.52) 0.33
Trend 469 29 0.76 (0.28–2.07) 0.60 48 0.66 (0.29–1.52) 0.33
C1QG rs12756603 AA 350 (73) 22 (79) 1.0 (ref) 26 (53) 1.0 (ref)
AG 120 (25) 6 (21) 0.81 (0.32–2.05) 0.65 20 (41) 2.27 (1.22–4.21) 0.0097
GG 12 (2) 0 — — 3 (6) 3.09 (0.81–11.82) 0.10
AG or GG 132 (27) 6 (21) 0.71 (0.28–1.81) 0.48 23 (47) 2.35 (1.29–4.26) 0.0051
Trend 482 28 0.67 (0.29–1.57) 0.36 49 2.01 (1.24–3.26) 0.0048
C2 rs497309 AA 405 (84) 17 (59) 1.0 (ref) 44 (90) 1.0 (ref)
AC 75 (16) 12 (41) 4.21 (1.91–9.31) 0.00038 5 (10) 0.62 (0.24–1.63) 0.34
CC 2 (0.4) 0 — — 0 — —
AC or CC 77 (16) 12 (41) 4.09 (1.85–9.03) 0.00049 5 (10) 0.61 (0.23–1.59) 0.31
Trend 482 29 3.52 (1.67–7.43) 0.00093 49 0.61 (0.24–1.56) 0.30
C3 rs344550 GG 198 (41) 5 (18) 1.0 (ref) 23 (47) 1.0 (ref)
CG 220 (46) 15 (54) 2.85 (1.01–8.03) 0.047 20 (41) 0.80 (0.42–1.50) 0.48
CC 64 (13) 8 (29) 5.80 (1.80–18.64) 0.0032 6 (12) 0.85 (0.33–2.18) 0.73
CG or CC 284 (59) 23 (82) 3.45 (1.28–9.29) 0.014 26 (53) 0.81 (0.45–1.46) 0.48
Trend 482 28 2.37 (1.36–4.15) 0.0024 49 0.88 (0.57–1.37) 0.57
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Haplotype analyses were consistent with the results of the individual SNP analyses and did not provide additional insight into these associations (data not shown).

DISCUSSION

Our results suggest a potential role of the C1RL gene in overall NHL risk as well as for DLBCL. Although the observed associations did not withstand adjustment for multiple testing, these genes were chosen for analysis based on high prior with risk of NHL. Our results extend previous preliminary evidence concerning a potential role of the complement system in susceptibility to NHL, and warrant replication in future studies including in different ethnic groups.

C1RL (complement component 1, r-subcomponent like) is a serine protease which is homologous to complement component C1r [Ligoudistianou et al., 2005]; however, its precise function has not been fully elucidated. C1RL has been shown to possess catalytic activity against pro-C1s and therefore may be involved in the activation of the classical complement pathway; however, this activity has not been observed in all studies [Wicher and Fries, 2004; Ligoudistianou et al., 2005]. C1RL also appears to mediate the proteolytic cleavage of a proform of haptoglobin in the endoplasmic reticulum [Wicher and Fries, 2004]. Haptoglobin is a glycoprotein whose concentration increases during inflammation, and in addition has several immunomodulatory functions including regulation of T-cell mediated immune responses [Arredouani et al., 2003; Quaye, 2008].

Interestingly, serum levels of haptoglobin-related protein have been shown to be higher in lymphoma patients relative to controls, and distinct haptoglobin phenotypes contribute to several infectious, inflammatory, and hematologic disorders [Epelbaum et al., 1998; Sadrzadeh and Bozorgmehr, 2004]. No association between C1RL and NHL was observed in the previous study which considered this relationship. However, only one SNP (rs3782928) from this gene was genotyped resulting in 5% coverage for this locus [Cerhan et al., 2009]. Consistent with this study, our analysis revealed no association between this SNP and overall NHL or specific subtypes.

We observed an association at the gene level for C1QG with CLL/SLL, and for C2 and C3 with MZL. However, given the small number of cases of each of these subtypes, future studies with a larger number of subtype specific cases (i.e., pooling studies) should evaluate these associations more closely. Cerhan et al. [2009] found one SNP (rs7746553) in the C2 gene that was positively associated with NHL, but there was no association with the C3 gene. Each of these genes is involved in the activation of the classical pathway of the complement system, and thus may have important implications for the immune response. Deficiencies in C2 protein, in particular, have long been associated with autoimmune disease, including systemic lupus erythematosus, and infections [Jonsson et al., 2005; Truedsson et al., 2007]. Similarly, genetic variation in the C3 gene has been associated with several inflammatory conditions [Hasegawa et al., 2004; Miyagawa et al., 2008; Purwar et al., 2009].

Given common associations with autoimmune disease and infections, the associations with overall NHL and particular subtypes observed in our study for specific complement genes are biologically plausible, but require further investigation and replication in order to rule out the possibility of chance findings. To date, several small genome-wide association studies (GWAS) of specific NHL subtypes have been conducted [Di Bernardo et al., 2008; Skibola et al., 2009; Conde et al., 2010; Crowther-Swanepoel et al., 2010]. These and future large scale GWAS of NHL will help clarify our findings and provide further insight into the role of the complement system in susceptibility to overall NHL and NHL subtypes. Moreover, while our study had limited power to conduct stratified analyses, further investigation of potential interactions between complement genes and conditions related to inflammatory status are warranted. It is plausible that the risk of NHL associated with complement genes may be higher in patients with a history of certain infections or autoimmune diseases, or in the case of differences in inflammatory status due to factors such as menopausal state, although this was not apparent in our exploratory analyses.

In summary, our results suggest a potential role of the complement system in susceptibility to NHL, particularly for C1RL. This is one of only two studies to comprehensively evaluate genetic variation in complement genes and risk of NHL. However, due to the small sample size for NHL subtypes, additional studies are needed to clarify this relationship.

Supplementary Material

Supp Data 1

Acknowledgments

Grant sponsor: Intramural Research Program of the NIH, National Cancer Institute; Grant sponsor: NIH from National Cancer Institute; Grant Number: CA62006.

Authors gratefully acknowledge the assistance of Peter Hui (Information Management Services, Inc., Silver Spring, MD) for programming support.

Footnotes

Additional Supporting Information may be found in the online version of this article.

References

  1. Arredouani M, Matthijs P, Van Hoeyveld E, Kasran A, Baumann H, Ceuppens JL, Stevens E. Haptoglobin directly affects T cells and suppresses T helper cell type 2 cytokine release. Immunology. 2003;108:144–151. doi: 10.1046/j.1365-2567.2003.01569.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Cerhan JR, Novak AJ, Fredericksen ZS, Wang AH, Liebow M, Call TG, Dogan A, Witzig TE, Ansell SM, Habermann TM, Kay NE, Slager SL. Risk of non-Hodgkin lymphoma in association with germline variation in complement genes. Br J Haematol. 2009;145:614–623. doi: 10.1111/j.1365-2141.2009.07675.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Chen BE, Sakoda LC, Hsing AW, Rosenberg PS. Resampling-based multiple hypothesis testing procedures for genetic case–control association studies. Genet Epidemiol. 2006;30:495–507. doi: 10.1002/gepi.20162. [DOI] [PubMed] [Google Scholar]
  4. Chen M, Daha MR, Kallenberg CG. The complement system in systemic autoimmune disease. J Autoimmun. 2010;34:J276–J286. doi: 10.1016/j.jaut.2009.11.014. [DOI] [PubMed] [Google Scholar]
  5. Conde L, Halperin E, Akers NK, Brown KM, Smedby KE, Rothman N, Nieters A, Slager SL, Brooks-Wilson A, Agana L, Riby J, Liu J, Adami HO, Darabi H, Hjalgrim H, Low HQ, Humphreys K, Melbye M, Chang ET, Glimelius B, Cozen W, Davis S, Hartge P, Morton LM, Schenk M, Wang SS, Armstrong B, Kricker A, Milliken S, Purdue MP, Vajdic CM, Boyle P, Lan Q, Zahm SH, Zhang Y, Zheng T, Becker N, Benavente Y, Boffetta P, Brennan P, Butterbach K, Cocco P, Foretova L, Maynadie M, de Sanjose S, Staines A, Spinelli JJ, Achenbach SJ, Call TG, Camp NJ, Glenn M, Caporaso NE, Cerhan JR, Cunningham JM, Goldin LR, Hanson CA, Kay NE, Lanasa MC, Leis JF, Marti GE, Rabe KG, Rassenti LZ, Spector LG, Strom SS, Vachon CM, Weinberg JB, Holly EA, Chanock S, Smith MT, Bracci PM, Skibola CF. Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32. Nat Genet. 2010;42:661–664. doi: 10.1038/ng.626. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Crowther-Swanepoel D, Broderick P, Di Bernardo MC, Dobbins SE, Torres M, Mansouri M, Ruiz-Ponte C, Enjuanes A, Rosenquist R, Carracedo A, Jurlander J, Campo E, Juliusson G, Montserrat E, Smedby KE, Dyer MJ, Matutes E, Dearden C, Sunter NJ, Hall AG, Mainou-Fowler T, Jackson GH, Summerfield G, Harris RJ, Pettitt AR, Allsup DJ, Bailey JR, Pratt G, Pepper C, Fegan C, Parker A, Oscier D, Allan JM, Catovsky D, Houlston RS. Common variants at 2q37.3, 8q24.21, 15q21.3 and 16q24.1 influence chronic lymphocytic leukemia risk. Nat Genet. 2010;42:132–136. doi: 10.1038/ng.510. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cuttner J, Spiera H, Troy K, Wallenstein S. Autoimmune disease is a risk factor for the development of non-Hodgkin’s lymphoma. J Rheumatol. 2005;32:1884–1887. [PubMed] [Google Scholar]
  8. Di Bernardo MC, Crowther-Swanepoel D, Broderick P, Webb E, Sellick G, Wild R, Sullivan K, Vijayakrishnan J, Wang Y, Pittman AM, Sunter NJ, Hall AG, Dyer MJ, Matutes E, Dearden C, Mainou-Fowler T, Jackson GH, Summerfield G, Harris RJ, Pettitt AR, Hillmen P, Allsup DJ, Bailey JR, Pratt G, Pepper C, Fegan C, Allan JM, Catovsky D, Houlston RS. A genome-wide association study identifies six susceptibility loci for chronic lymphocytic leukemia. Nat Genet. 2008;40:1204–1210. doi: 10.1038/ng.219. [DOI] [PubMed] [Google Scholar]
  9. Engels EA. Infectious agents as causes of non-Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev. 2007;16:401–404. doi: 10.1158/1055-9965.EPI-06-1056. [DOI] [PubMed] [Google Scholar]
  10. Epelbaum R, Shalitin C, Segal R, Valansi C, Arselan I, Faraggi D, Leviov M, Ben-Shahar M, Haim N. Haptoglobin-related protein as a serum marker in malignant lymphoma. Pathol Oncol Res. 1998;4:271–276. doi: 10.1007/BF02905217. [DOI] [PubMed] [Google Scholar]
  11. Excoffier L, Slatkin M. Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol. 1995;12:921–927. doi: 10.1093/oxfordjournals.molbev.a040269. [DOI] [PubMed] [Google Scholar]
  12. Forrest MS, Skibola CF, Lightfoot TJ, Bracci PM, Willett EV, Smith MT, Holly EA, Roman E. Polymorphisms in innate immunity genes and risk of non-Hodgkin lymphoma. Br J Haematol. 2006;134:180–183. doi: 10.1111/j.1365-2141.2006.06141.x. [DOI] [PubMed] [Google Scholar]
  13. Hasegawa K, Tamari M, Shao C, Shimizu M, Takahashi N, Mao XQ, Yamasaki A, Kamada F, Doi S, Fujiwara H, Miyatake A, Fujita K, Tamura G, Matsubara Y, Shirakawa T, Suzuki Y. Variations in the C3, C3a receptor, and C5 genes affect susceptibility to bronchial asthma. Hum Genet. 2004;115:295–301. doi: 10.1007/s00439-004-1157-z. [DOI] [PubMed] [Google Scholar]
  14. Jonsson G, Truedsson L, Sturfelt G, Oxelius VA, Braconier JH, Sjoholm AG. Hereditary C2 deficiency in Sweden: Frequent occurrence of invasive infection, atherosclerosis, and rheumatic disease. Medicine (Baltimore) 2005;84:23–34. doi: 10.1097/01.md.0000152371.22747.1e. [DOI] [PubMed] [Google Scholar]
  15. Lan Q, Zheng T, Rothman N, Zhang Y, Wang SS, Shen M, Berndt SI, Zahm SH, Holford TR, Leaderer B, Yeager M, Welch R, Boyle P, Zhang B, Zou K, Zhu Y, Chanock S. Cytokine polymorphisms in the Th1/Th2 pathway and susceptibility to non-Hodgkin lymphoma. Blood. 2006;107:4101–4108. doi: 10.1182/blood-2005-10-4160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Ligoudistianou C, Xu Y, Garnier G, Circolo A, Volanakis JE. A novel human complement-related protein, C1r-like protease (C1r-LP), specifically cleaves pro-C1s. Biochem J. 2005;387 (Part 1):165–173. doi: 10.1042/BJ20041196. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Markiewski MM, Lambris JD. The role of complement in inflammatory diseases from behind the scenes into the spotlight. Am J Pathol. 2007;171:715–727. doi: 10.2353/ajpath.2007.070166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Markiewski MM, Lambris JD. Is complement good or bad for cancer patients? A new perspective on an old dilemma. Trends Immunol. 2009a;30:286–292. doi: 10.1016/j.it.2009.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Markiewski MM, Lambris JD. Unwelcome complement. Cancer Res. 2009b;69:6367–6370. doi: 10.1158/0008-5472.CAN-09-1918. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Markiewski MM, DeAngelis RA, Benencia F, Ricklin-Lichtsteiner SK, Koutoulaki A, Gerard C, Coukos G, Lambris JD. Modulation of the antitumor immune response by complement. Nat Immunol. 2008;9:1225–1235. doi: 10.1038/ni.1655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Miyagawa H, Yamai M, Sakaguchi D, Kiyohara C, Tsukamoto H, Kimoto Y, Nakamura T, Lee JH, Tsai CY, Chiang BL, Shimoda T, Harada M, Tahira T, Hayashi K, Horiuchi T. Association of polymorphisms in complement component C3 gene with susceptibility to systemic lupus erythematosus. Rheumatology (Oxford) 2008;47:158–164. doi: 10.1093/rheumatology/kem321. [DOI] [PubMed] [Google Scholar]
  22. Morton LM, Holford TR, Leaderer B, Zhang Y, Zahm SH, Boyle P, Flynn S, Tallini G, Owens PH, Zhang B, Zheng T. Alcohol use and risk of non-Hodgkin’s lymphoma among Connecticut women (United States) Cancer Causes Control. 2003;14:687–694. doi: 10.1023/a:1025626208861. [DOI] [PubMed] [Google Scholar]
  23. Purdue MP, Lan Q, Kricker A, Grulich AE, Vajdic CM, Turner J, Whitby D, Chanock S, Rothman N, Armstrong BK. Polymorphisms in immune function genes and risk of non-Hodgkin lymphoma: findings from the New South Wales non-Hodgkin Lymphoma Study. Carcinogenesis. 2007;28:704–712. doi: 10.1093/carcin/bgl200. [DOI] [PubMed] [Google Scholar]
  24. Purwar R, Langer K, Werfel T. Polymorphisms within the C3 gene are associated with specific IgE levels to common allergens and super-antigens among atopic dermatitis patients. Exp Dermatol. 2009;18:30–34. doi: 10.1111/j.1600-0625.2008.00759.x. [DOI] [PubMed] [Google Scholar]
  25. Quaye IK. Haptoglobin, inflammation and disease. Trans R Soc Trop Med Hyg. 2008;102:735–742. doi: 10.1016/j.trstmh.2008.04.010. [DOI] [PubMed] [Google Scholar]
  26. Rothman N, Skibola CF, Wang SS, Morgan G, Lan Q, Smith MT, Spinelli JJ, Willett E, De Sanjose S, Cocco P, Berndt SI, Brennan P, Brooks-Wilson A, Wacholder S, Becker N, Hartge P, Zheng T, Roman E, Holly EA, Boffetta P, Armstrong B, Cozen W, Linet M, Bosch FX, Ennas MG, Holford TR, Gallagher RP, Rollinson S, Bracci PM, Cerhan JR, Whitby D, Moore PS, Leaderer B, Lai A, Spink C, Davis S, Bosch R, Scarpa A, Zhang Y, Severson RK, Yeager M, Chanock S, Nieters A. Genetic variation in TNF and IL10 and risk of non-Hodgkin lymphoma: A report from the InterLymph Consortium. Lancet Oncol. 2006;7:27–38. doi: 10.1016/S1470-2045(05)70434-4. [DOI] [PubMed] [Google Scholar]
  27. Rutkowski MJ, Sughrue ME, Kane AJ, Mills SA, Parsa AT. Cancer and the complement cascade. Mol Cancer Res. 2010;8:1453–1465. doi: 10.1158/1541-7786.MCR-10-0225. [DOI] [PubMed] [Google Scholar]
  28. Sadrzadeh SM, Bozorgmehr J. Haptoglobin phenotypes in health and disorders. Am J Clin Pathol. 2004;121 (Suppl):S97–S104. doi: 10.1309/8GLX5798Y5XHQ0VW. [DOI] [PubMed] [Google Scholar]
  29. Skibola CF, Bracci PM, Halperin E, Conde L, Craig DW, Agana L, Iyadurai K, Becker N, Brooks-Wilson A, Curry JD, Spinelli JJ, Holly EA, Riby J, Zhang L, Nieters A, Smith MT, Brown KM. Genetic variants at 6p21.33 are associated with susceptibility to follicular lymphoma. Nat Genet. 2009;41:873–875. doi: 10.1038/ng.419. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Smedby KE, Hjalgrim H, Askling J, Chang ET, Gregersen H, Porwit-MacDonald A, Sundstrom C, Akerman M, Melbye M, Glimelius B, Adami HO. Autoimmune and chronic inflammatory disorders and risk of non-Hodgkin lymphoma by subtype. J Natl Cancer Inst. 2006;98:51–60. doi: 10.1093/jnci/djj004. [DOI] [PubMed] [Google Scholar]
  31. Suadicani P, Hein H, Gyntelberg F. Complement C3 Genotype Variants and Risk of Lung Cancer Mortality. ISRN Pulmonology. 2011;2011(Article ID 423571):1–4. [Google Scholar]
  32. Truedsson L, Bengtsson AA, Sturfelt G. Complement deficiencies and systemic lupus erythematosus. Autoimmunity. 2007;40:560–566. doi: 10.1080/08916930701510673. [DOI] [PubMed] [Google Scholar]
  33. Wang SS, Cozen W, Cerhan JR, Colt JS, Morton LM, Engels EA, Davis S, Severson RK, Rothman N, Chanock SJ, Hartge P. Immune mechanisms in non-Hodgkin lymphoma: Joint effects of the TNF G308A and IL10 T3575A polymorphisms with non-Hodgkin lymphoma risk factors. Cancer Res. 2007;67:5042–5054. doi: 10.1158/0008-5472.CAN-06-4752. [DOI] [PubMed] [Google Scholar]
  34. Wicher KB, Fries E. Prohaptoglobin is proteolytically cleaved in the endoplasmic reticulum by the complement C1r-like protein. Proc Natl Acad Sci USA. 2004;101:14390–14395. doi: 10.1073/pnas.0405692101. [DOI] [PMC free article] [PubMed] [Google Scholar]

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