Introduction
About 16% of human cancers are linked to infectious agents, predominantly due to viral and bacterial infections [
1]. Chronic hepatitis C (CHC) virus infection, primarily affecting the liver, also poses systemic risks, significantly increasing the likelihood of developing B-cell lymphomas [
2]. Extensive research, including comprehensive studies and meta-analyses, has underscored an elevated risk of B-cell non-hodgkin’s lymphoma in patients with CHC virus compared to those without the infection [
3,
4].
Pathophysiological processes from hepatitis C virus (HCV) infection to overt lymphoma involve mechanisms like sustained antigenic stimulation leading to monoclonal expansion and direct viral roles in cellular transformation, especially in large B-cell lymphoma [
5,
6]. In vitro studies indicate that the CD81 receptor, crucial for HCV entry, plays a role in B cell infection [
7]. HCV replication in B cells might initiate oncogenic events through intracellular viral proteins [
8]. This process is linked to oxidative stress caused by viral proteins core and NS3, potentially leading to DNA mutations and repair abnormalities, resulting in cell transformation [
9]. Additionally, genomic mutations are also implicated in this process, supported by identified mutations in Neurogenic Locus Notch Homolog Protein (NOTCH) 2, NOTCH1, and Phosphatase and Tensin Homolog (PTEN) in HCV-positive diffuse large B cell lymphoma (DLBCL) patients [
10]. However, the molecular pathology linking HCV infection with lymphoma remains elusive. Advanced studies are essential for a comprehensive understanding of the genetic interplay in HCV-associated B-cell lymphoma [
3].
Our research utilizes Genome-Wide Association Studies (GWAS) data for an advanced Mendelian randomization (MR) analysis [
11‐
14], a robust method that identifies causal relationships between risk factors and health outcomes while effectively minimizing confounding influences, to establish a causal link between CHC virus infection and B-cell lymphomas as well as chronic lymphocytic leukemia (CLL). We further employ colocalization analysis [
15], which plays a pivotal role in uncovering shared molecular mechanisms underlying various diseases and their associated intermediate phenotypes, to discern the causal variants that underlie this association, potentially elucidating the genetic interplay between these conditions. This approach is expected to yield advanced insights into the genetic underpinnings of the relationship between CHC virus infection and B-cell lymphoproliferative disorders.
Discussion
In our own study, we employed MR to investigate the association between CHC and B-cell lymphoma subtypes, along with CLL. Our findings indicated a statistically significant elevation in the risk of DLBCL associated with CHC infection (OR: 1.34; 95% CI: 1.01–1.78;
P = 0.0397). This evidence corroborates the causal inference drawn from prior observational correlations [
24‐
27]. Additionally, previous systematic meta-analysis found that, besides DLBCL, CHC is also associated with other types of B-cell lymphoma such as MZL, lymphoplasmacytic lymphoma (LPL), and follicular lymphoma (FL) [
25,
28‐
30]. However, our study did not establish a causal relationship between CHC and these B-cell lymphoma subtypes as well as CLL. Several factors could account for this observed discrepancy. Firstly, MR utilizes genetic variants as IVs to investigate the causal relationship between exposure and outcome, with a critical assumption being the exclusion of confounders [
11,
12]. For instance, during the selection of the exposure-related IVs, factors such as chronic inflammatory stimuli are intentionally excluded as confounders, given that chronic inflammation is a recognized pathogenic mechanism for lymphoma [
31]. In other words, a known contributing factor to lymphoma pathogenesis is deliberately eliminated. Secondly, the pathogenesis of CHC-related lymphoma involves a complex cascade of molecular and cellular events. The development of HCV-related lymphoma involves ongoing stimulation of lymphocytes by viral antigens, leading to cell proliferation; oncogenic effects from HCV replication in B cells, mediated by viral proteins; and lasting B-cell damage from transient viral presence, a phenomenon known as the “hit and run” theory [
32]. Nevertheless, these critical pathogenic factors are not assessed in MR studies. In a systematic meta-analysis [
33,
34], however, the calculated incidence rate of lymphoma accounts for the possibility of all occurrences of the disease. The exclusion or infeasibility of evaluating these factors may result in MR being less capable to provide as comprehensive and conclusive a result as a systematic meta-analysis might, potentially contributing to the discrepancy between their findings. The last potential reason for inconsistencies might be inadequate statistical power in MR studies, influenced by the prevalence of genetic variants used, their effect size on the risk factor, and the study sample size [
12,
14]. These factors may lead to discrepancies between the conclusions of epidemiological studies and those derived from MR, yet the two sets of findings are not necessarily contradictory.
Recent advancements have decrypted various pathogenic pathways linking CHC to non-Hodgkin lymphoma, emphasizing the significant role of genetic determinants in HCV-associated lymphoproliferative disorders [
9,
10,
35,
36]. In a comprehensive French study with 87 HCV-associated lymphoma patients, the TNF alpha induced protein 3 (TNFAIP3)/A20 gene’s rs2230926G allele was found more frequently in patients exhibiting rheumatoid factor (RF) activity (20%). This correlation suggests that even minimal A20 dysfunction, potentially resulting in heightened NF-kB activity, might be enough to trigger the lymphomatous transformation in autoimmune B cells, particularly under conditions of chronic RF + B cell stimulation [
37]. In our study, we utilized colocalization analysis [
15], which plays a pivotal role in uncovering shared molecular mechanisms underlying various diseases and their associated intermediate phenotypes, we pinpointed two causal variants - rs17208853 and rs482759 - that mediate the correlation between CHC infection and DLBCL, implying a potential shared genetic underpinning for these two traits.
Further VEP analysis suggested that rs17208853 and rs482759 are regulatory variants affecting BTNL2 and NOTCH4genes, with rs17208853 also influencing the lncRNA profile of TSBP1-AS1. The BTNL2 gene functions predominantly as an immune regulator, with high expression in lymphoid tissues and structural homology to B7 co-stimulatory molecules [
38,
39]. It is implicated in dampening T-cell proliferation and cytokine production, thereby modulating T-cell-mediated responses, especially in the gastrointestinal tract [
40]. Research by Waller RG et al. recognizes BTNL2 among genes that elevate the risk of multiple myeloma, indicating potential genetic overlap with other lymphoid malignancies [
41]. Additionally, Vijai J et al. identify loci near BTNL2 linked to MZL, emphasizing its role in lymphoma pathogenesis [
42]. Although no direct genetic link between CHC and MZL was found in our study, it is important to note that MZL carries a risk of transformation into DLBCL [
43]. The NOTCH pathway is recurrently mutated in DLBCL associated with hepatitis C virus infection [
10]. NOTCH2, NOTCH1 and PTEN mutations have been identified in respectively, 20%, 4% and 2% of HCV-positive DLBCL patients [
10]. NOTCH4, a key component of the NOTCH pathway, has been shown to have significant associations with both benign and malignant lymphoproliferative diseases related to HCV [
44,
45]. Our colocalization analysis has identified rs482759 as a regulatory variant located upstream of the NOTCH4 gene. This variant is involved in the encoding of NOTCH4 proteins and may play a role in the pathogenesis of DLBCL related to CHC. The TSBP1-AS1 gene, spanning 139 kb and characterized as a lncRNA, is highly expressed in immune system cells [
46]. It is notable for its partial overlap with the protein-coding genes TSBP1 (also known as C6orf10) and BTNL2, which are transcribed from the opposite strand [
47,
48], and have pleiotropic effects on autoimmune disorders [
49,
50]. The precise function of TSBP1-AS1 in lymphomas remains to be elucidated, necessitating further focused research to unravel its potential roles in lymphomagenesis.
Our research constitutes a pioneering application of MR to investigate the risk association between CHC and B-cell proliferative diseases, establishing CHC as a risk factor for DLBCL and identifying two causal genetic variants. This contributes significantly to understanding the genetic interplay between these pathologies. However, our results also have some limitations. Firstly, the study’s concentration on a European population limits the extension of our findings to other ethnic groups. Additionally, despite the identification of a colocalized signal, the complex underlying genetic mechanisms still require more comprehensive exploration. Furthermore, our analysis, while comprehensive for various B-cell lymphoma subtypes, faced limitations due to data availability, which restricted the inclusion and examination of certain lymphomas, such as FL.
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