结直肠癌诊断后持续性疲劳的遗传易感性

Elham Kazemian, Qianxing Mo, Marco Matejcic, Ya-Yu Tsai, Daniel Sobieski, Xiaoyin Li, Aasha I Hoogland, Sylvia L Crowder, Brian D Gonzalez, Laura B Oswald, Alix G Sleight, Nathalie Nguyen, Nicole C Loroña, Victoria Damerell, Khaled R Komrokji, Kathi Mooney, Mary C Playdon, Cornelia M Ulrich, Christopher I Li, David Shibata, Adetunji T Toriola, Jennifer Ose, Anita R Peoples, Sheetal Hardikar, Christoph Kahlert, Erin M Siegel, Julienne E Bower, Stephanie L Schmit, Biljana Gigic, Heather S L Jim, Jane C Figueiredo
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Fatigue was assessed at five timepoints using the EORTC QLQ-C30 fatigue subscale and analyzed as (1) a binary summary measure of the trajectory from diagnosis into survivorship (defined as severe: yes, no), (2) a mean score across all time points, and (3) the highest (ie, worst) score across all time points. We genotyped samples using Infinium Global Diversity Array with imputation using the TOPMed reference panel to conduct a genome-wide analysis (GWAS). SuSiE was used to identify independent secondary signals. Transcriptome-wide association studies (TWAS) using S-PrediXcan and MultiXcan were conducted to examine genetic regulation of gene expression. COLOC assessed whether variants identified in the GWAS influence gene expression through colocalization analysis. Results Among 1,219 participants, 31.0% experienced severe fatigue over the course of their diagnosis. A locus near LINC02505 on chromosome 4 was associated with severe fatigue (rs6531463, OR = 3.25, p = 3.88 × 10−8). 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引用次数: 0

摘要

癌症相关性疲劳(疲劳)是癌症治疗后常见且持续的症状,但遗传易感性的作用尚不清楚。方法:我们利用来自前瞻性队列研究ColoCare研究(即美国5个站点和德国)的数据。使用EORTC QLQ-C30疲劳子量表在五个时间点对疲劳进行评估,并分析为(1)从诊断到生存(定义为严重:是,否)轨迹的二元汇总测量,(2)所有时间点的平均得分,(3)所有时间点的最高(即最差)得分。我们使用Infinium Global Diversity Array对样本进行基因分型,并使用TOPMed参考面板进行代入,进行全基因组分析(GWAS)。苏西被用来识别独立的次级信号。使用S-PrediXcan和MultiXcan进行转录组全关联研究(TWAS)以检测基因表达的遗传调控。COLOC通过共定位分析评估GWAS中鉴定的变异是否会影响基因表达。结果在1219名参与者中,31.0%的人在诊断过程中经历了严重的疲劳。4号染色体上LINC02505附近的一个位点与严重疲劳相关(rs6531463, OR = 3.25, p = 3.88 × 10−8)。当建模平均疲劳水平时,在NEK10和SLC4A7中或附近发现了显著相关的变异。综合分析将肝组织中NEK10的预测表达与疲劳风险联系起来(p < 4.36 × 10−6)。共定位分析确定了NEK10附近的遗传位点和基因表达(后验概率&;gt; 0.9)。结论:本研究发现了与CRC患者疲劳相关的新基因位点,可能有助于识别高危人群并制定预防策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic predisposition to persistent fatigue after a diagnosis of colorectal cancer
Background Cancer-related fatigue (fatigue) is a common and persistent symptom after cancer treatment, yet the role of genetic susceptibility remains unclear. Methods We leveraged data from a prospective cohort study, ColoCare Study (ie, five U.S. sites and Germany). Fatigue was assessed at five timepoints using the EORTC QLQ-C30 fatigue subscale and analyzed as (1) a binary summary measure of the trajectory from diagnosis into survivorship (defined as severe: yes, no), (2) a mean score across all time points, and (3) the highest (ie, worst) score across all time points. We genotyped samples using Infinium Global Diversity Array with imputation using the TOPMed reference panel to conduct a genome-wide analysis (GWAS). SuSiE was used to identify independent secondary signals. Transcriptome-wide association studies (TWAS) using S-PrediXcan and MultiXcan were conducted to examine genetic regulation of gene expression. COLOC assessed whether variants identified in the GWAS influence gene expression through colocalization analysis. Results Among 1,219 participants, 31.0% experienced severe fatigue over the course of their diagnosis. A locus near LINC02505 on chromosome 4 was associated with severe fatigue (rs6531463, OR = 3.25, p = 3.88 × 10−8). When modeling mean fatigue levels, significantly associated variants were identified in or near NEK10 and SLC4A7. Integrative analyses linked the predicted expression of NEK10 in liver tissue to risk of fatigue (p &lt; 4.36 × 10−6). Colocalization analysis identified genetic loci and gene expression near NEK10 (posterior probabilities &gt; 0.9). Conclusions This study identified novel genetic loci associated with fatigue in CRC patients and may be useful for identifying high-risk individuals for preventative strategies.
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