PDF(Pubmed)
Abstract：
UNASSIGNED: The aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders.
UNASSIGNED: We applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR < 0.05.
UNASSIGNED: Our results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10-2.06, pFDR = 0.033, pIVW = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13-1.98, pFDR = 0.027, pIVW = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06-1.43, pFDR = 0.041, pIVW = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08-1.36, pFDR = 0.007, pIVW = 0.001). No evidence of pleiotropy was determined.
UNASSIGNED: Our findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.
UNASSIGNED: We applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR < 0.05.
UNASSIGNED: Our results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10-2.06, pFDR = 0.033, pIVW = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13-1.98, pFDR = 0.027, pIVW = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06-1.43, pFDR = 0.041, pIVW = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08-1.36, pFDR = 0.007, pIVW = 0.001). No evidence of pleiotropy was determined.
UNASSIGNED: Our findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.
摘要：
■这项研究的目的是调查循环细胞性状与肾脏疾病风险之间的因果关系。
■我们应用了全面的双样本孟德尔随机化（MR）分析。利用来自公开可用的全基因组关联研究(GWAS)数据库的单核苷酸多态性(SNP)。从血细胞联盟（BCX）中提取了人类血细胞性状的遗传预测工具变量，而肾脏疾病的数据则从Finngen联盟获得。主要MR分析使用逆方差加权(IVW)方法进行，使用加权中位数(WM)和MR-Egger模型作为额外的方法。敏感性分析，包括MR-PRESSO,采用径向回归和MR-Egger截距检测异常值并评估水平多效性.我们进一步利用留一法分析来评估结果的稳健性。根据误码率校正(FDR)，因果关系被认为是显著的，特别是当IVW方法提供pFDR<0.05时。
■我们的结果表明，白细胞（WBC）计数（OR=1.50，95％CI=1.10-2.06，pFDR=0.033，pIVW=0.011）和淋巴细胞计数（OR=1.50，95％CI=1.13-1.98，pFDR=0.027，pIVW=0.005）与IgA肾病的高风险相关。此外，WBC计数被确定为肾脏恶性肿瘤的重要遗传危险因素（OR=1.23，95％CI=1.06-1.43，pFDR=0.041，pIVW=0.007）。此外,研究发现,基因预测的嗜酸性粒细胞水平升高与糖尿病肾病风险升高有因果关系(OR=1.21,95%CI=1.08~1.36,pFDR=0.007,pIVW=0.001).没有确定多效性的证据。
■我们的发现提供了循环白细胞计数因果关系的证据，淋巴细胞计数和IgA肾病，白细胞计数和肾恶性肿瘤，嗜酸性粒细胞计数和糖尿病肾病。这些结果有可能有助于开发新的肾脏疾病的诊断选择和治疗策略。
■我们应用了全面的双样本孟德尔随机化（MR）分析。利用来自公开可用的全基因组关联研究(GWAS)数据库的单核苷酸多态性(SNP)。从血细胞联盟（BCX）中提取了人类血细胞性状的遗传预测工具变量，而肾脏疾病的数据则从Finngen联盟获得。主要MR分析使用逆方差加权(IVW)方法进行，使用加权中位数(WM)和MR-Egger模型作为额外的方法。敏感性分析，包括MR-PRESSO,采用径向回归和MR-Egger截距检测异常值并评估水平多效性.我们进一步利用留一法分析来评估结果的稳健性。根据误码率校正(FDR)，因果关系被认为是显著的，特别是当IVW方法提供pFDR<0.05时。
■我们的结果表明，白细胞（WBC）计数（OR=1.50，95％CI=1.10-2.06，pFDR=0.033，pIVW=0.011）和淋巴细胞计数（OR=1.50，95％CI=1.13-1.98，pFDR=0.027，pIVW=0.005）与IgA肾病的高风险相关。此外，WBC计数被确定为肾脏恶性肿瘤的重要遗传危险因素（OR=1.23，95％CI=1.06-1.43，pFDR=0.041，pIVW=0.007）。此外,研究发现,基因预测的嗜酸性粒细胞水平升高与糖尿病肾病风险升高有因果关系(OR=1.21,95%CI=1.08~1.36,pFDR=0.007,pIVW=0.001).没有确定多效性的证据。
■我们的发现提供了循环白细胞计数因果关系的证据，淋巴细胞计数和IgA肾病，白细胞计数和肾恶性肿瘤，嗜酸性粒细胞计数和糖尿病肾病。这些结果有可能有助于开发新的肾脏疾病的诊断选择和治疗策略。
