To the Editor: Coronary artery disease (CAD), the most prevalent form of cardiovascular disease (CVD), poses a significant threat to global health, leading to high mortality rates and substantial economic costs. The incidence of CAD in China is 10.2‰ and is increasing steadily.1,2 CAD is a chronic inflammatory disease based on atherosclerosis. One of the most frequently activated inflammatory pathways involved in atherosclerosis is the nucleotide-binding domain and leucine-rich repeat-containing protein 3 (NLRP3) inflammasome.3 Given the crucial impact of NLRP3 on CAD, we aimed to evaluate the correlation between the NLRP3 gene variant and CAD by a case-control association study in a Chinese Han population Supplementary Figure 1, https://links.lww.com/CM9/C596. This study was approved by the Ethics Committee of Wuhan Union Hospital (No. 0157-01), and all participants provided written informed consent. Ultimately, we enrolled 1824 CAD patients alongside 1824 control subjects from Wuhan Union Hospital Supplementary Methods, https://links.lww.com/CM9/C596. Considering many aspects, the rs10754555 variant of NLRP3 (with a minor allele frequency MAF of 0.38 in the East Asian population) was preferentially included in our research Supplementary Methods, Supplementary Figures 2, 3 and 4, https://links.lww.com/CM9/C596. Allelic identification of the genetic variant rs10754555 of NLRP3 (a C→G substitution) was performed by real-time polymerase chain reaction (PCR) on a QuantStudio 6 Pro (Applied Biosystems, Singapore) using a TaqMan single nucleotide polymorphism (SNP) assay Supplementary Methods, https://links.lww.com/CM9/C596. Hardy–Weinberg equilibrium (HWE) assessment was performed using PLINK software (version 1.07, Broad institute, USA). Associations were analyzed at both the allelic and genotypic levels by applying chi-squared tests and logistic regression methods. Gensini score P–P plots were generated to test for normal distribution. Linear regression models were used to explore the connection between rs10754555 and the severity of CAD. Multiple logistic regression was applied to account for conventional risk factors associated with CAD. Two specific models were implemented to adjust for these risk factors: Model 1 accounted for age and gender; and Model 2 included adjustments for age, gender, body mass index (BMI), smoking status, hypertension, diabetes mellitus, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c). Odds ratios (ORs) and 95% confidence intervals (CIs) were computed using the statistical software SPSS (version 26.0, Inc., Chicago, IL). Statistical significance was established at P <0.05. A comparative examination of the clinical features between CAD patients and control subjects was conducted Supplementary Table 1, https://links.lww.com/CM9/C596. Our analysis indicated that factors such as mean age, mean BMI, the proportion of males, and the prevalence of smoking were considerably higher in the CAD group than those in the control group (P <0.05). In addition, the incidence of diabetes mellitus and hypertension was obviously higher in the CAD group than in the control group (P <0.05). Levels of total cholesterol, triglycerides, and LDL-c were substantially higher in patients with CAD when compared to those in controls (P <0.05). In contrast, HDL-c levels were obviously lower in patients with CAD relative to their control counterparts (P <0.05). Genetic variant rs10754555 of NLRP3 passed the HWE test in controls (P = 0.119) Supplementary Table 2, https://links.lww.com/CM9/C596. Rs10754555-G allele accounted for 35.4% (1285/3631) for the CAD group and 36.4% (1321/3631) for the control group Supplementary Table 2, https://links.lww.com/CM9/C596. Furthermore, analysis of allelic and genotypic associations suggested that rs10754555 was not associated with CAD before the adjustment for conventional risk factors Supplementary Table 3, https://links.lww.com/CM9/C596. Analysis of allelic association revealed that after adjusting for age and gender, rs10754555 was not associated with CAD (Padj = 0.357, OR = 0.951 95% CI, 0.855–1.058). After adjusting for age, gender, BMI, smoking, hypertension, diabetes mellitus, total cholesterol, triglyceride, HDL-c, and LDL-c, rs10754555 was not associated with CAD (Padj = 0.449, OR = 0.939 95% CI, 0.799–1.105), either. In addition, genotypic association analysis demonstrated that rs10754555 did not exhibit an association with CAD in either model. The P-values before and after calibration were not significant. Considering that age is an important factor in CAD, we next investigated the distribution of the rs10754555 allele and genotypes according to age categories in the study population. However, no significant distribution changes with age were observed Supplementary Table 4, https://links.lww.com/CM9/C596. Furthermore, the CAD group was classified into two categories. Early-onset CAD was defined as an age of first onset at or before 55 years for male and at or before 65 years for female, whereas late-onset CAD was defined as an age of first onset after 55 years for male and after 65 years for female. Late-onset CAD was characterized by older age, a larger number of male patients, a higher prevalence of hypertension and diabetes mellitus, and a higher concentration of HDL-c, whereas patients with early-onset CAD had higher concentrations of total cholesterol, triglyceride, and LDL-c Supplementary Table 5, https://links.lww.com/CM9/C596. Moreover, the average age and the proportion of males of the early-onset CAD group were similar to that of the control group Supplementary Table 6, https://links.lww.com/CM9/C596. Next, association analyses were conducted to investigate the specific relationship between rs10754555 and both early- and late-onset CAD. Before correction, allelic association analysis indicated that rs10754555 was related to early-onset CAD (Pobs = 0.043), whereas genotypic association analysis demonstrated a prominent association between rs10754555 and early-onset CAD in a recessive pattern (GG/GC+CC) (Pobs = 0.035). After adjusting for age and gender, allelic association analysis indicated that rs10754555 was associated with early-onset CAD (Padj = 0.043, OR = 0.870 95% CI, 0.760–0.995). Genotypic association analysis indicated that rs10754555 was related to early-onset CAD in a recessive pattern (GG/GC+CC) (Padj = 0.036, OR = 0.739 95% CI, 0.557–0.980) and an additive mode (GG/GC/CC) (Padj = 0.045, OR = 0.873 95% CI, 0.764–0.997). Following adjustment for age, gender, BMI, smoking status, hypertension, diabetes mellitus, total cholesterol, triglyceride, HDL-c, and LDL-c, a recessive pattern of correlation was observed (GG/GC+CC) (Padj = 0.045, OR = 0.633 95% CI, 0.404–0.989), yet no correlation was identified in the allelic analyses Supplementary Table 7, https://links.lww.com/CM9/C596. However, the results of the allelic and genotypic association analysis indicated that rs10754555 was not associated with late-onset CAD before correction, and that the association between rs10754555 and late-onset CAD remained non-significant in both correction modes Supplementary Table 8, https://links.lww.com/CM9/C596. We also ascertained the association between rs10754555 and CAD in distinct gender cohorts Supplementary Table 9, https://links.lww.com/CM9/C596. In males, there was no correlation between rs10754555 and CAD in the pre- and post-correction allelic analyses. In addition, genotypic association analysis demonstrated that rs10754555 was associated with CAD in a recessive pattern (GG/GC+CC) before correction (Pobs = 0.034). However, no correlation was observed after adjusting for covariates. In females, allelic and genotypic analyses revealed no correlation between rs10754555 and CAD, regardless of whether an adjustment was applied. We also investigated the associations in other risk subgroups, such as smoking, hypertension, and diabetes mellitus subgroups. However, no significant association was observed in these subgroups Supplementary Tables 10–12, https://links.lww.com/CM9/C596. Furthermore, we analyzed the association between rs10754555 and the severity of CAD. The correlation between rs10754555 and CAD severity was determined by linear regression analysis in additive, recessive, and dominant modes, as well as the allelic model. However, no association was observed between rs10754555 and CAD severity before and after correction Supplementary Table 13, https://links.lww.com/CM9/C596. In addition, by applying Mann–Whitney U-tests and Kruskal–Wallis tests, we found no difference between the loge-transformation (LN) of Gensini scores and rs10754555 genotypes Supplementary Figure 5, https://links.lww.com/CM9/C596. We further performed a quartile case-control association analysis to explore the associations between rs10754555 and the severity of CAD. The first quartile featured the lowest LN of Gensini scores, whereas the fourth quartile featured the highest LN of Gensini scores. Nevertheless, the findings indicated that rs10754555 did not show any association with the severity of CAD, regardless of whether assessed in allele or genotype mode, either before or after correction Supplementary Table 14, https://links.lww.com/CM9/C596. We also explored the relationship between rs10754555 and the severity of CAD in the early-onset CAD group; however, we found no association between them Supplementary Table 15, https://links.lww.com/CM9/C596. The present study sought to detect the association between the genetic variant rs10754555 of the NLRP3 gene and CAD in the Chinese Han population. Analysis found no evidence of an association between rs10754555 and CAD. Nevertheless, a nominal significance association was detected between rs10754555 and the early-onset CAD, whereas no correlation was evident with the late-onset form. Furthermore, rs10754555 showed no correlation with CAD in the risk subgroups and the severity of CAD. Our study highlights that the stratified management of patients with CAD based on the rs10754555 genotype may have an important guiding significance for the anti-inflammatory treatment of CAD. The genetic variant rs10754555 of NLRP3 has been shown to affect the mRNA levels of NLRP3 in peripheral blood mononuclear cells (PBMCs)and is related to the activation of the NLRP3 inflammasome, along with increased systemic inflammation.4 Our research indicates that rs10754555 is linked to early-onset CAD. The secretion of cytokines by inflammatory cells is selective and occurs at different disease stages, thereby rendering cytokine activity a dynamic process. The NLRP3 pathway may be activated at an early stage of the disease, thus resulting in the release of downstream inflammatory factors and an enhancement in the development of CAD.5 Recent research has found that carriers of the rs10754555-G allele have significantly elevated levels of interleukin (IL)-18 and IL-1β in their plasma.4 A previous study showed that the effects of rs10754555 on NLRP3 mRNA expression and plasma IL-12 levels differed between age groups.6 It had found that the expression levels of NLRP3 mRNA were reduced in individuals carrying the rs10754555-G allele when compared to non-carriers with the age ≤56 years. Furthermore, lower plasma levels of IL-12 were detected in individuals carrying the rs10754555-G allele when compared to non-carriers with an age ≤56 years.6 Although our study identified a correlation between rs10754555 and early-onset CAD, we did not examine the expression levels of IL-1β, IL-12, and IL-18 mRNA, or the concentration of IL-6, IL-12, IL-18, and high-sensitivity C-reactive protein (hsCRP) downstream of NLRP3, thus limiting our ability to clarify the potential molecular mechanism involved. Besides, it has been shown that the G allele of NLRP3 rs10754558 susceptibility to CAD may be related to elevated serum levels of IL-1β.7 Whether rs10754555 acts directly on NLRP3 activation or indirectly on downstream inflammatory factors has not been clarified. In addition, the impact of NLRP3 on early-onset CAD has not been previously investigated from the perspective of multiple variants. Furthermore, the lack of follow-up data precludes the use of our study based on age stratification as a clinical reference for primary prevention. Given the homogeneous nature of our study population, it is not possible to extend our results to other races. Although our study has some limitations, we successfully identified a preliminary association between the genetic variant rs10754555 of NLRP3 and early-onset CAD. This will provide design ideas and a theoretical basis for our future clinical studies on the anti-inflammatory therapy of CAD targeting the NLRP3 inflammasome. For example, is there a difference in the efficacy of anti-inflammatory therapy between patients carrying different genotypes of the NLRP3 gene? Do medications for carriers of different ages and genotypes need to be personalized? In conclusion, genetic variant rs10754555 of NLRP3 is associated with early-onset CAD. Our results provide a new theoretical basis for anti-inflammatory therapy targeting the NLRP3 inflammasome in CAD and for the individual treatment of patients with CAD. However, additional research is required to elucidate the mechanisms and significance of these clinical interventions. Funding This work was supported by grants from the National Key Research and Development Program (No. 2022YFC2503501), Chinese Society of Cardiology's Foundation (No. CSCF2023A04), Hubei Technology Innovation Project (No. 2024BCB046), and Key Research and Development Program of Wuhan (No. 2024020702030092) and the National Natural Science Foundation of China (No. 82200319). Conflicts of interest None.
Zha et al. (Fri,) studied this question.
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