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Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches

BACKGROUND: Traditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association. AIMS: We studied the causal association b...

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Autores principales: Jiang, Lin, Sun, Yi-Qian, Brumpton, Ben Michael, Langhammer, Arnulf, Chen, Yue, Mai, Xiao-Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644519/
https://www.ncbi.nlm.nih.gov/pubmed/36348315
http://dx.doi.org/10.1186/s12885-022-10215-0
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author Jiang, Lin
Sun, Yi-Qian
Brumpton, Ben Michael
Langhammer, Arnulf
Chen, Yue
Mai, Xiao-Mei
author_facet Jiang, Lin
Sun, Yi-Qian
Brumpton, Ben Michael
Langhammer, Arnulf
Chen, Yue
Mai, Xiao-Mei
author_sort Jiang, Lin
collection PubMed
description BACKGROUND: Traditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association. AIMS: We studied the causal association between BMI and lung cancer incidence using observational and MR approaches. METHODS: We followed up 62,453 cancer-free Norwegian adults from 1995–97 (HUNT2) until 2017. BMI at baseline in HUNT2 was classified as < 25.0, 25.0–29.9 and ≥ 30.0 kg/m(2). BMI change over ten years between HUNT1 (1984–86) and HUNT2 was calculated and classified into quartiles. Seventy-five genetic variants were included as instruments for BMI (among which 14 also associated with smoking behavior). Incident lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable MR was used to examine the effect of BMI after genetically controlling for smoking. RESULTS: During a median follow-up of 21.1 years, 1009 participants developed lung cancer including 327 with lung adenocarcinoma. The HRs and 95% CIs for incidence of adenocarcinoma were 0.73 (0.58–0.92) for BMI 25.0–29.9 kg/m(2) and 0.53 (0.37–0.76) for BMI ≥ 30 kg/m(2) compared with BMI < 25.0 kg/m(2) in HUNT2 (P for trend < 0.001). However, there was little evidence of a dose–response relationship between the BMI change from HUNT1 to HUNT2 in quartiles and the incidence of adenocarcinoma (P for trend = 0.08). Furthermore, multivariable MR approach suggested a positive association between genetically determined 1 kg/m(2) increase in BMI and the incidence of adenocarcinoma (HR 1.25, 95% CI 1.02–1.53). No associations were found with other lung cancer histologic types. CONCLUSIONS: Our study suggests that the inverse association between baseline BMI and lung adenocarcinoma in observational analysis may not be causal. More MR studies are needed to confirm our finding of a positive association between BMI and lung adenocarcinoma. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10215-0.
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spelling pubmed-96445192022-11-15 Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches Jiang, Lin Sun, Yi-Qian Brumpton, Ben Michael Langhammer, Arnulf Chen, Yue Mai, Xiao-Mei BMC Cancer Research Article BACKGROUND: Traditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association. AIMS: We studied the causal association between BMI and lung cancer incidence using observational and MR approaches. METHODS: We followed up 62,453 cancer-free Norwegian adults from 1995–97 (HUNT2) until 2017. BMI at baseline in HUNT2 was classified as < 25.0, 25.0–29.9 and ≥ 30.0 kg/m(2). BMI change over ten years between HUNT1 (1984–86) and HUNT2 was calculated and classified into quartiles. Seventy-five genetic variants were included as instruments for BMI (among which 14 also associated with smoking behavior). Incident lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable MR was used to examine the effect of BMI after genetically controlling for smoking. RESULTS: During a median follow-up of 21.1 years, 1009 participants developed lung cancer including 327 with lung adenocarcinoma. The HRs and 95% CIs for incidence of adenocarcinoma were 0.73 (0.58–0.92) for BMI 25.0–29.9 kg/m(2) and 0.53 (0.37–0.76) for BMI ≥ 30 kg/m(2) compared with BMI < 25.0 kg/m(2) in HUNT2 (P for trend < 0.001). However, there was little evidence of a dose–response relationship between the BMI change from HUNT1 to HUNT2 in quartiles and the incidence of adenocarcinoma (P for trend = 0.08). Furthermore, multivariable MR approach suggested a positive association between genetically determined 1 kg/m(2) increase in BMI and the incidence of adenocarcinoma (HR 1.25, 95% CI 1.02–1.53). No associations were found with other lung cancer histologic types. CONCLUSIONS: Our study suggests that the inverse association between baseline BMI and lung adenocarcinoma in observational analysis may not be causal. More MR studies are needed to confirm our finding of a positive association between BMI and lung adenocarcinoma. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10215-0. BioMed Central 2022-11-08 /pmc/articles/PMC9644519/ /pubmed/36348315 http://dx.doi.org/10.1186/s12885-022-10215-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Jiang, Lin
Sun, Yi-Qian
Brumpton, Ben Michael
Langhammer, Arnulf
Chen, Yue
Mai, Xiao-Mei
Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches
title Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches
title_full Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches
title_fullStr Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches
title_full_unstemmed Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches
title_short Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches
title_sort body mass index and incidence of lung cancer in the hunt study: using observational and mendelian randomization approaches
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644519/
https://www.ncbi.nlm.nih.gov/pubmed/36348315
http://dx.doi.org/10.1186/s12885-022-10215-0
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