The causality between telomere length and chronic lung diseases: A Bidirectional Mendelian Randomization Analysis
Bibliographic record
Abstract
Abstract Background Previous studies have observed the abnormality in telomere biology and function during the process of chronic lung diseases (CLDs). However, whether alteration of telomere length (TL) causally facilitates the incidence of CLDs remains to be determined. Therefore, we here aim to estimate the causal effect of TL on the risk of CLDs using mendelian randomization (MR) analysis. Methods Single nucleotide polymorphisms (SNPs) strongly associated with TL and CLDs were selected as genetic variables from the genome-wide association studies (GWAS). A bidirectional two-sample MR analysis primarily based on inverse variance weighted (IVW) method was then conducted to infer the causality between TL and CLDs. Cochran’s Q test and MR-Egger regression analysis were performed to assess the heterogeneity and pleiotropy, and leave-one-out analysis was tested to determine the stability of MR results. Results The forward MR analysis indicated that among non-neoplastic CLDs, elevated TL was causally related to reduced risk of asthma (OR = 0.9986, 95%CI 0.9972–0.9999, P = 0.035), chronic obstructive pulmonary disease (COPD) (OR = 0.9987, 95%CI 0.9975–0.9999, P = 0.040), idiopathic pulmonary fibrosis (IPF) (OR = 0.9971, 95%CI 0.9961–0.9980, P < 0.001), and sarcoidosis (OR = 0.6820, 95%CI 0.5236–0.8884, P = 0.005). For neoplastic CLDs, increased TL genetically predicted higher risk of non-small cell lung cancer (OR = 1.8485, 95%CI 1.4074–2.4279, P < 0.001) and lung adenocarcinoma (OR = 1.9636, 95%CI 1.2275–3.1412, P = 0.005). However, there presented no significant causality between TL and pulmonary arterial hypertension, pneumoconiosis, small cell lung cancer and squamous cell lung cancer. Moreover, reverse MR analysis all showed no obvious causalities of CLDs with TL, except for sarcoidosis (OR = 0.9936, 95%CI 0.9887–0.9984, P = 0.010). Sensitivity analyses suggested the robustness of MR results with no horizonal pleiotropy despite of partial heterogeneity in reverse MR analysis. Conclusions Our study demonstrates that TL is causally associated with decreased risk of several non-neoplastic CLDs (asthma, COPD and IPF), whereas associated with increased risk of non-small cell lung cancer (especially adenocarcinoma). There’s mutual causality between TL attrition and sarcoidosis onset. This study comprehensively elucidated the causal associations between TL and CLDs, and might provide a promising target for the prevention of these CLDs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".