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来自多个队列的遗传分析表明,2200 个可用药基因、端粒长度与白血病之间存在因果关系。

Genetic analysis from multiple cohorts implies causality between 2200 druggable genes, telomere length, and leukemia.

机构信息

Department of Oncology and Hematology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China; Graduate School of Beijing University of Chinese Medicine, Beijing, 100700, China.

Department of Oncology and Hematology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, China.

出版信息

Comput Biol Med. 2024 Oct;181:109064. doi: 10.1016/j.compbiomed.2024.109064. Epub 2024 Aug 30.

Abstract

BACKGROUND

Clinical therapeutic targets for leukemia remain to be identified and the causality between leukemia and telomere length is unclear.

METHODS

This work employed cis expression quantitative trait locus (eQTL) for 2,200 druggable genes from the eQTLGen Consortium and genome-wide association studies (GWAS) summary data for telomere length in seven blood cell types from the UK Biobank, Netherlands Cohort as exposures. GWAS data for lymphoid leukemia (LL) and myeloid leukemia (ML) from FinnGen and Lee Lab were used as outcomes for discovery and replication cohorts, respectively. Robust Mendelian randomization (MR) findings were generated from seven MR models and a series of sensitivity analyses. Summary-data-based MR (SMR) analysis and transcriptome-wide association studies (TWAS) were further implemented to verify the association between identified druggable genes and leukemia. Single-cell type expression analysis was employed to identify the specific expression of leukemia casual genes on human bone marrow and peripheral blood immune cells. Multivariable MR analysis, linkage disequilibrium score regression (LDSC), and Bayesian colocalization analysis were performed to further validate the relationship between telomere length and leukemia. Mediation analysis was used to assess the effects of identified druggable genes affecting leukemia via telomere length. Phenome-wide MR (Phe-MR) analysis for assessing the effect of leukemia causal genes and telomere length on 1,403 disease phenotypes.

RESULTS

Combining the results of the meta-analysis for MR estimates from two cohorts, SMR and TWAS analysis, we identified five LL causal genes (TYMP, DSTYK, PPIF, GDF15, FAM20A) and three ML causal genes (LY75, ADA, ABCA2) as promising drug targets for leukemia. Univariable MR analysis showed genetically predicted higher leukocyte telomere length increased the risk of LL (odds ratio [OR] = 2.33, 95 % confidence interval [95 % CI] 1.70-3.18; P = 1.33E-07), and there was no heterogeneity and horizontal pleiotropy. Evidence from the meta-analysis of two cohorts strengthened this finding (OR = 1.88, 95 % CI 1.06-3.05; P = 0.01). Multivariable MR analysis showed the causality between leukocyte telomere length and LL without interference from the other six blood cell telomere length (OR = 2.72, 95 % CI 1.88-3.93; P = 1.23E-07). Evidence from LDSC supported the positive genetic correlation between leukocyte telomere length and LL (r = 0.309, P = 0.0001). Colocalization analysis revealed that the causality from leukocyte telomere length on LL was driven by the genetic variant rs770526 in the TERT region. The mediation analysis via two-step MR showed that the causal effect from TYMP on LL was partly mediated by leukocyte telomere length, with a mediated proportion of 12 %.

CONCLUSION

Our study identified several druggable genes associated with leukemia risk and provided new insights into the etiology and drug development of leukemia. We also found that genetically predicted higher leukocyte telomere length increased LL risk and its potential mechanism of action.

摘要

背景

白血病的临床治疗靶点仍有待确定,白血病与端粒长度之间的因果关系尚不清楚。

方法

本研究采用 cis 表达数量性状基因座 (eQTL) 分析了来自 eQTLGen 联盟的 2200 个可成药基因,以及来自 UK Biobank、荷兰队列的 7 种血细胞的全基因组关联研究 (GWAS) 端粒长度汇总数据作为暴露因素。FinnGen 和 Lee 实验室的淋系白血病 (LL) 和髓系白血病 (ML) 的 GWAS 数据分别作为发现和复制队列的结果。从七个 MR 模型和一系列敏感性分析中生成了稳健的孟德尔随机化 (MR) 结果。基于汇总数据的 MR (SMR) 分析和全转录组关联研究 (TWAS) 进一步验证了鉴定出的可成药基因与白血病之间的关联。单细胞类型表达分析用于鉴定白血病因果基因在人类骨髓和外周血免疫细胞中的特异性表达。多变量 MR 分析、连锁不平衡得分回归 (LDSC) 和贝叶斯共定位分析进一步验证了端粒长度与白血病之间的关系。中介分析用于评估鉴定出的可成药基因通过端粒长度影响白血病的效应。表型广泛的 MR (Phe-MR) 分析用于评估白血病因果基因和端粒长度对 1403 种疾病表型的影响。

结果

通过对来自两个队列的 MR 估计值的荟萃分析、SMR 和 TWAS 分析的结果相结合,我们确定了五个 LL 因果基因 (TYMP、DSTYK、PPIF、GDF15、FAM20A) 和三个 ML 因果基因 (LY75、ADA、ABCA2) 作为白血病的有希望的药物靶点。单变量 MR 分析表明,遗传预测的较高白细胞端粒长度增加了 LL 的风险 (比值比 [OR] = 2.33,95%置信区间 [95%CI] 1.70-3.18;P = 1.33E-07),且不存在异质性和水平性偏倚。来自两个队列的荟萃分析结果进一步证实了这一发现 (OR = 1.88,95%CI 1.06-3.05;P = 0.01)。多变量 MR 分析表明,白细胞端粒长度与 LL 之间存在因果关系,不受其他六种血细胞端粒长度的干扰 (OR = 2.72,95%CI 1.88-3.93;P = 1.23E-07)。LDSC 的证据支持白细胞端粒长度与 LL 之间存在正遗传相关性 (r = 0.309,P = 0.0001)。共定位分析表明,白细胞端粒长度对 LL 的因果关系是由 TERT 区域的遗传变异 rs770526 驱动的。通过两步 MR 的中介分析表明,TYMP 对 LL 的因果效应部分通过白细胞端粒长度介导,介导比例为 12%。

结论

本研究确定了几个与白血病风险相关的可成药基因,并为白血病的病因学和药物开发提供了新的见解。我们还发现,遗传预测的较高白细胞端粒长度增加了 LL 的风险,其潜在的作用机制。

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