Abstract Background Evidence from observational studies suggests an association between chronic obstructive pulmonary disease (COPD) and lung cancer. The potential interactions between the immune system and the lungs may play a causative role in COPD and lung cancer and offer therapeutic prospects. However, the causal association and the immune-mediated mechanisms between COPD and lung cancer remain to be determined. Methods We employed a two-sample Mendelian randomization (MR) approach to investigate the causal association between COPD and lung cancer. Additionally, we examined whether immune cell signals were causally related to lung cancer, as well as whether COPD was causally associated with immune cell signals. Furthermore, through two-step Mendelian randomization, we investigated the mediating effects of immune cell signals in the causal association between COPD and lung cancer. Leveraging publicly available genetic data, our analysis included 468,475 individuals of European ancestry with COPD, 492,803 individuals of European ancestry with lung cancer, and 731 immune cell signatures of European ancestry. Additionally, we conducted single-cell transcriptome sequencing analysis on COPD, lung cancer, and control samples to validate our findings. Findings We found a causal association between COPD and lung cancer (odds ratio [OR] = 1.63, 95% confidence interval [CI] = 1.31–2.02, P -value &lt; 0.001). We also observed a causal association between COPD and regulatory T cells (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.01–1.40, P -value &lt; 0.05), as well as a causal association between regulatory T cells and lung cancer (odds ratio [OR] = 1.02, 95% confidence interval [CI] = 1.002–1.045, P -value &lt; 0.05). Furthermore, our two-step Mendelian randomization analysis demonstrated that COPD is associated with lung cancer through the mediation of regulatory T cells. These findings were further validated through single-cell sequencing analysis, confirming the mediating role of regulatory T cells in the association between COPD and lung cancer. Interpretation As far as we are aware, we are the first to combine single-celled immune cell data with two-sample Mendelian randomization. Our analysis indicates a causal association between COPD and lung cancer, with regulatory T cells playing an intermediary role. 

Exploring the relationship between Treg-mediated risk in COPD and lung cancer through Mendelian randomization analysis and scRNA-seq data integration.

Background: To construct a meta polygenic risk score (metaPRS) based on PRS of lung cancer and related phenotypes. We also aimed to assess its prediction of lung cancer risk and implication for screening.Methods: A total of 2,180 genetic variants were used to develop a PRS for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer-related risk factors, respectively. These PRSs were then integrated into a meta polygenic risk score (metaPRS) for lung cancer using the elastic-net Cox regression model with data from the UK Biobank (N=442,508). The predictive effects of the metaPRS were assessed in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial (N=108,665).Findings: The metaPRS was associated with lung cancer risk with a hazard ratio of 1·37 (95% confidence interval: 1·33-1·42) per standard deviation increased. The metaPRS showed the highest C-index (0·590) compared with the previous nine PRSs (C-index: 0·531-0·565) in the UK Biobank. Similarly, the metaPRS increased the C-index by 0·016-0·067 over the previous PRSs (C-index: 0·580 vs 0·513-0·564) in the PLCO. Higher metaPRS was associated with younger age at lung cancer diagnosis. Besides, individuals at intermediate predicted risk by clinical risk model (1·34%-1·51%) with the intermediate-high genetic risk had a six-year average absolute lung cancer risk exceeded the threshold clinical risk model risk≥1·51%. The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI=6·50%) in the PLCO cohort.Interpretation: The metaPRS improves the predictive efficiency of lung cancer compared with the previous PRSs, and refines risk stratification for lung cancer.Funding: National Natural Science Foundation of China; Excellent Youth Foundation of Jiangsu Province; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancer, Chinese Academy of Medical Sciences.Declaration of Interest: The authors have no conflicts of interest to declare.Ethical Approval: All participants provided written informed consent, and ethical approval for the UKB was obtained from the NHS National Research Ethics Service. 

Meta Polygenic Risk Score and Lung Cancer Risk Prediction: Two Prospective Cohort Studies

Unveiling the Link between Asthma and Cancer Risk: Shedding New Light through Mendelian Randomization.

Abstract Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer‐related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic‐net Cox regression model in the UK Biobank ( N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial ( N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27–1.39) per standard deviation increased. The metaPRS showed the highest C‐index (0.580) compared with the previous nine PRSs (C‐index: 0.513–0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%–1.51%) with the intermediate‐high genetic risk had a 6‐year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer. 

Development and validation of a lung cancer polygenic risk score incorporating susceptibility variants for risk factors

Objective: To investigate the association between chronic lung diseases and the risk of lung cancer. Methods: Using UK Biobank (UKB) survey data, 472 397 participants who had not previously been diagnosed with cancer and whose self-reported sex was consistent with their genetic sex were studied. Information on the prevalence of previous chronic lung diseases, general demographic characteristics and the prevalence of lung cancer was collected using baseline questionnaires and national health system data. The multivariate Cox proportional risk regression model was used to analyze the association between four previous chronic lung diseases (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis and interstitial pulmonary disease) and the risk of lung cancer. A total of 458 526 participants with genotype data in the observational study were selected as research objects, and the closely related and independent genetic loci with four chronic lung diseases were selected as instrumental variables, and the association between four chronic lung diseases and the risk of lung cancer was analyzed by Mendelian randomization (MR). The dose-response relationship between genetic risk score and the risk of lung cancer in different chronic lung diseases was evaluated using a restricted cubic spline function. Results: The age [M (Q1, Q3)] of the subjects was 57 (50, 63) years old, and there were 3 516 new cases of lung cancer (0.74%) during follow-up. The multivariate Cox proportional hazard regression model analysis showed that previous chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis were associated with the risk of lung cancer, about 1.61 (1.49-1.75) and 2.61 (1.24-5.49), respectively. MR Studies showed that genetically predicted chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis were associated with the risk of lung cancer, with HR (95%CI) of 1.10 (1.03-1.19) and 1.04 (1.01-1.08), respectively. The results of restricted cubic spline function analysis showed that the risk of lung cancer increased linearly with the increase of genetic risk scores for chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis (P<0.05). Neither observational studies nor Mendelian randomization analysis found an association between previous asthma or interstitial lung disease and the risk of lung cancer (both P values>0.05). Conclusion: Chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis are potential risk factors for lung cancer.目的： 探讨既往患有慢性肺部疾病与肺癌发病风险的关联情况。 方法： 采用英国生物银行（UKB）调查数据，以既往未被诊断为癌症且自报性别与遗传性别一致的472 397名参与者为研究对象。采用基线问卷和国家健康系统数据收集既往慢性肺部疾病患病情况、一般人口学特征以及肺癌患病情况等信息。采用多因素Cox比例风险回归模型分析哮喘、慢性阻塞性肺病、特发性肺纤维化、间质性肺病等4种既往慢性肺部疾病与肺癌发病风险的关联。以观察性研究中具有基因型数据的458 526名参与者为研究对象，选择与4种慢性肺部疾病密切相关且相互独立的遗传位点作为工具变量，采用孟德尔随机化（MR）分析4种慢性肺部疾病与肺癌发病风险的关联情况。采用限制性立方样条函数评估不同慢性肺部疾病GRS与肺癌发病风险的剂量反应关系。 结果： 研究对象年龄的M（Q1，Q3）为57（50，63）岁，随访期间新发肺癌3 516例（0.74%）。多因素Cox比例风险回归模型分析结果显示：既往患有慢性阻塞性肺病和特发性肺纤维化与肺癌发病风险存在关联，分别为1.61（1.49~1.75）和2.61（1.24~5.49）。MR研究结果显示：遗传预测的慢性阻塞性肺病和特发性肺纤维化与肺癌发病风险存在关联，HR（95%CI）分别为1.10（1.03~1.19）和1.04（1.01~1.08）。限制性立方样条函数分析结果显示：肺癌发病风险随慢性阻塞性肺病和特发性肺纤维化遗传风险评分增加而升高且呈线性关系（P<0.05）。观察性研究和孟德尔随机化分析均未发现既往患有哮喘或间质性肺病与肺癌发病风险存在关联（均P>0.05）。 结论： 既往患有慢性阻塞性肺病和特发性肺纤维化是肺癌发生的潜在危险因素。. 

[Association between chronic lung diseases and the risk of lung cancer in UK Biobank: observational and Mendelian randomization analyses].

Objective: To evaluate the possible mediation effect of smoking and healthy diet score on the association between educational level and the risk of lung cancer incidence. Methods: After excluding individuals with missing educational levels and cancer information at baseline, 446 772 participants in the UK Biobank (UKB) prospective cohort study were included. Cox regression models were used to investigate the associations of educational level and smoking and healthy diet score with the incidence of lung cancer. Mediating effect analysis was conducted to analyze the mediating effect of smoking and healthy diet score on the correlation between educational level and lung cancer. Results: During a median follow-up of 7.13 years, 1 994 new- onset lung cancer cases were observed. Per 1 standard deviation (5 years) increase in educational level was associated with a 12% lower risk of lung cancer (HR=0.88, 95%CI: 0.84-0.92). The corresponding level 1-5 in the International Standard Classification for Education (ISCED) were mapped to UKB self-report highest qualification to estimate the educational level. A higher rank means a higher educational level. Compared with level ISCED-1, the HR(95%CI) of level ISCED-2, ISCED-3, ISCED-4 and ISCED-5 were respectively 0.83 (0.72-0.94), 0.67 (0.53-0.85), 0.76 (0.65-0.89) and 0.72 (0.64-0.80) for lung cancer. Education years were negatively correlated with smoking, with β coefficients (95%CI) being -0.079 (-0.081- -0.077), but positively correlated with healthy diet score (β=0.042, 95%CI: 0.039-0.045). Analysis of mediating effect indicated that the association of educational level with lung cancer risk was mediated by smoking and healthy diet score, the proportions of mediating effect were 38.952% (95%CI: 31.802%-51.659%) and 1.784% (95%CI: 0.405%-3.713%), respectively. Conclusion: Smoking and healthy diet score might mediate the effect of educational level on the incidence of lung cancer, indicating that improving the level of education can reduce the risk of lung cancer by changing lifestyles such as smoking and diet.

[Mediation effect of smoking and healthy diet score on the association between educational level and the risk of lung cancer incidence].

[Association between lung nodules and lung cancer risk in high-risk populations].

[Progress of application of artificial intelligence foundation models in epidemiological research].

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

H. X. Ma

Author Tools

Chat about Author

Papers

[Association between chronic lung diseases and the risk of lung cancer in UK Biobank: observational and Mendelian randomization analyses].

[Mediation effect of smoking and healthy diet score on the association between educational level and the risk of lung cancer incidence].

[Association between lung nodules and lung cancer risk in high-risk populations].

[Progress of application of artificial intelligence foundation models in epidemiological research].