Associations of genetic risk, BMI trajectories, and the risk of non-small cell lung cancer: a population-based cohort study.
Associations of genetic risk, BMI trajectories, and the risk of non-small cell lung cancer: a population-based cohort study.
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遗传风险、BMI轨迹和非小细胞肺癌风险的相关性：一项基于人群的队列研究
DOI：
10.1186/s12916-022-02400-6
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发表时间：
2022-06-06
期刊：
影响因子：
9.3
通讯作者：
Zhao, Yang
中科院分区：
文献类型：
--
作者：
You, Dongfang;Wang, Danhua;Wu, Yaqian;Chen, Xin;Shao, Fang;Wei, Yongyue;Zhang, Ruyang;Lange, Theis;Ma, Hongxia;Xu, Hongyang;Hu, Zhibin;Christiani, David C.;Shen, Hongbing;Chen, Feng;Zhao, Yang
已发现体重指数（BMI）与非小细胞肺癌（NSCLC）风险降低相关;然而，BMI轨迹和与遗传变异的潜在相互作用对NSCLC风险的影响仍未知。应用考克斯比例风险回归模型评估来自前列腺、肺、结直肠和卵巢（PLCO）癌症筛查试验的138，110名受试者队列中BMI轨迹与NSCLC风险之间的相关性。单样本孟德尔随机化（MR）分析进一步用于评估BMI轨迹和NSCLC风险之间的因果关系。此外，多基因风险评分（PRS）和全基因组相互作用分析（GWIA）用于评估BMI轨迹和NSCLC风险中遗传变异之间的乘法相互作用。与保持稳定正常BMI的个体相比（n = 47，982，34.74%），BMI从正常到超重的轨迹（n = 64，498，46.70%），从正常到肥胖（n = 21，259，15.39%），从超重到肥胖（n = 4，371，3.16%）与NSCLC风险降低相关（趋势风险比[HR]= 0.78，P < 2×10−16）。一项使用BMI轨迹与遗传变异相关的MR研究显示，BMI轨迹与NSCLC风险之间无显著相关性。PRS的进一步分析显示，较高的GWAS识别的PRS（PRSGWAS）与NSCLC风险增加相关，而BMI轨迹和PRSGWAS与NSCLC风险之间的相互作用不显著（PsPRS= 0.863和PwPRS= 0.704）。在GWIA分析中，四个独立的易感基因座（P < 1×10 - 6）与BMI轨迹对NSCLC风险的影响相关，包括rs79297227（12q14.1，位于SLC 16 A7，P相互作用= 1.01×10−7），rs 2336652（3p22.3，靠近CLASP 2，Pinteraction = 3.92×10−7）、rs 16018（19p13.2，在CACNA 1A中，Pinteraction = 3.92×10−7）和rs 4726760（7 q34，靠近BRAF，Pinteraction = 9.19×10−7）。功能注释表明，这些基因座可能通过调节细胞生长、分化和炎症而参与NSCLC的发展。我们的研究表明BMI轨迹、遗传因素和NSCLC风险之间存在关联。有趣的是，发现了四个新的遗传位点与BMI轨迹对NSCLC风险的相互作用，为NSCLC的病因学研究提供了更多支持。http://www.clinicaltrials.gov，NCT01696968。在线版本包含补充材料，可通过10.1186/s12916-022-02400-6获得。
Body mass index (BMI) has been found to be associated with a decreased risk of non-small cell lung cancer (NSCLC); however, the effect of BMI trajectories and potential interactions with genetic variants on NSCLC risk remain unknown. Cox proportional hazards regression model was applied to assess the association between BMI trajectory and NSCLC risk in a cohort of 138,110 participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. One-sample Mendelian randomization (MR) analysis was further used to access the causality between BMI trajectories and NSCLC risk. Additionally, polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between BMI trajectories and genetic variants in NSCLC risk. Compared with individuals maintaining a stable normal BMI (n = 47,982, 34.74%), BMI trajectories from normal to overweight (n = 64,498, 46.70%), from normal to obese (n = 21,259, 15.39%), and from overweight to obese (n = 4,371, 3.16%) were associated with a decreased risk of NSCLC (hazard ratio [HR] for trend = 0.78, P < 2×10−16). An MR study using BMI trajectory associated with genetic variants revealed no significant association between BMI trajectories and NSCLC risk. Further analysis of PRS showed that a higher GWAS-identified PRS (PRSGWAS) was associated with an increased risk of NSCLC, while the interaction between BMI trajectories and PRSGWAS with the NSCLC risk was not significant (PsPRS= 0.863 and PwPRS= 0.704). In GWIA analysis, four independent susceptibility loci (P < 1×10−6) were found to be associated with BMI trajectories on NSCLC risk, including rs79297227 (12q14.1, located in SLC16A7, Pinteraction = 1.01×10−7), rs2336652 (3p22.3, near CLASP2, Pinteraction = 3.92×10−7), rs16018 (19p13.2, in CACNA1A, Pinteraction = 3.92×10−7), and rs4726760 (7q34, near BRAF, Pinteraction = 9.19×10−7). Functional annotation demonstrated that these loci may be involved in the development of NSCLC by regulating cell growth, differentiation, and inflammation. Our study has shown an association between BMI trajectories, genetic factors, and NSCLC risk. Interestingly, four novel genetic loci were identified to interact with BMI trajectories on NSCLC risk, providing more support for the aetiology research of NSCLC. http://www.clinicaltrials.gov, NCT01696968. The online version contains supplementary material available at 10.1186/s12916-022-02400-6.
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遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
4.5
作者：
Koning M;Hoekstra T;de Jong E;Visscher TL;Seidell JC;Renders CM
通讯作者：
Renders CM
影响因子：
26.1
作者：
Hellström A;Nilsson AK;Wackernagel D;Pivodic A;Vanpee M;Sjöbom U;Hellgren G;Hallberg B;Domellöf M;Klevebro S;Hellström W;Andersson M;Lund AM;Löfqvist C;Elfvin A;Sävman K;Hansen-Pupp I;Hård AL;Smith LEH;Ley D
通讯作者：
Ley D
影响因子：
30.8
作者：
Huyghe, Jeroen R.;Bien, Stephanie A.;Peters, Ulrike
通讯作者：
Peters, Ulrike
影响因子：
64.5
作者：
Akhmanova, A;Hoogenraad, CC;Galjart, N
通讯作者：
Galjart, N