Shi Patrick, Baranova Ancha, Cao Hongbao
School of Systems Biology, George Mason University, Manassas, VA, USA.
Research Centre for Medical Genetics, Moscow, Russia.
Discov Oncol. 2025 Jul 13;16(1):1324. doi: 10.1007/s12672-025-03101-1.
The genetic mechanisms underlying non-Hodgkin lymphoma (NHL) and Hodgkin lymphoma (HL) remain understudied. While numerous genes associated with these lymphoid tumors have been identified, little research has focused on the genetic networks that directly drive NHL and HL pathogenesis.
We conducted integrative genomic analyses, including a transcriptome-wide association study (TWAS), a proteome-wide association study (PWAS), and a summary-data-based Mendelian randomization (SMR), to identify causal genes for NHL and HL. TWAS and PWAS were performed using FUSION software by integrating GWAS data with gene and protein expression weights from large-scale datasets. The SMR analysis utilized cis-eQTL data to assess causal relationships between gene expression and lymphoma risk. Associations were deemed significant at p < 0.05.
The PWAS identified 106 proteins associated with NHL and 67 proteins associated with HL. The TWAS revealed 172 genes linked to NHL risk and 448 genes linked to HL risk. Finally, the SMR analysis highlighted 270 genes associated with NHL risk; there was with no evidence of heterogeneity in the HEIDI test, which supports pleiotropic effects. Key genes that influence NHL risk include KRT1, ERAP2, RMDN1, FAS, and C5, while UNC5B was identified as a significant causal gene for HL. Locus and effect plots were used to validate these findings by highlighting causal variants associated with lymphoma risks.
In this study, KRT1, ERAP2, RMDN1, FAS, C5, and UNC5B were identified as potential causal factors in lymphoma risk, underscoring mechanisms such as immune modulation and tumor suppression and providing insights into future therapeutic targets.
非霍奇金淋巴瘤(NHL)和霍奇金淋巴瘤(HL)的遗传机制仍未得到充分研究。虽然已经鉴定出许多与这些淋巴肿瘤相关的基因,但很少有研究关注直接驱动NHL和HL发病机制的遗传网络。
我们进行了综合基因组分析,包括全转录组关联研究(TWAS)、全蛋白质组关联研究(PWAS)和基于汇总数据的孟德尔随机化(SMR),以确定NHL和HL的因果基因。TWAS和PWAS使用FUSION软件,通过将全基因组关联研究(GWAS)数据与来自大规模数据集的基因和蛋白质表达权重相结合来进行。SMR分析利用顺式表达数量性状基因座(cis-eQTL)数据来评估基因表达与淋巴瘤风险之间的因果关系。当p < 0.05时,关联被认为具有统计学意义。
PWAS鉴定出106种与NHL相关的蛋白质和67种与HL相关的蛋白质。TWAS揭示了172个与NHL风险相关的基因和448个与HL风险相关的基因。最后,SMR分析突出了270个与NHL风险相关的基因;在HEIDI检验中没有异质性的证据,这支持了多效性效应。影响NHL风险的关键基因包括角蛋白1(KRT1)、内质网氨肽酶2(ERAP2)、核糖体修饰蛋白1(RMDN1)、凋亡相关因子(FAS)和补体成分5(C5),而UNC5B被确定为HL的一个重要因果基因。基因座和效应图用于通过突出与淋巴瘤风险相关的因果变异来验证这些发现。
在本研究中,KRT1、ERAP2、RMDN1、FAS、C5和UNC5B被确定为淋巴瘤风险的潜在因果因素,强调了免疫调节和肿瘤抑制等机制,并为未来的治疗靶点提供了见解。