ArticleGenetic epidemiology2014
Genome-wide association and network analysis of lung function in the Framingham Heart Study.
Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Genetic association and causal inference between lung function and venous thromboembolism.Respiratory research · 2023Pooled it
- Susceptibility to Childhood Pneumonia: A Genome-Wide Analysis.American journal of respiratory cell and molecular biology · 2017Trial
- The Causal Relationship Between Gastroesophageal Reflux Disease and Chronic Obstructive Pulmonary Disease: A Bidirectional Two-Sample Mendelian Randomization Study.International journal of chronic obstructive pulmonary disease · 2024Article
- Causal Relationship Between Lung Function and Atrial Fibrillation: A Two Sample Univariable and Multivariable, Bidirectional Mendelian Randomization Study.Frontiers in cardiovascular medicine · 2021Article
- Genetic regulation of gene expression of MIF family members in lung tissue.Scientific reports · 2020Article
- Lung Function in African American Children with Asthma Is Associated with Novel Regulatory Variants of the KIT LigandGenetics · 2020Article
- Pneumonia: host susceptibility and shared genetics with pulmonary function and other traits.Clinical and experimental immunology · 2019Article
- Genetic underpinnings of lung function and COPD.Journal of genetics · 2019Review
- Article
- Identifying novel protein phenotype annotations by hybridizing protein-protein interactions and protein sequence similarities.Molecular genetics and genomics : MGG · 2016Article
- Interactions between the otitis media gene, Fbxo11, and p53 in the mouse embryonic lung.Disease models & mechanisms · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Single nucleotide polymorphisms have been found to be associated with pulmonary function using genome-wide association studies. However, lung function is a complex trait that is likely to be influenced by multiple gene-gene interactions besides individual genes. Our goal is to build a cellular network to explore the relationship between pulmonary function and genotypes by combining SNP level and network analyses using longitudinal lung function data from the Framingham Heart Study. We analyzed 2,698 genotyped participants from the Offspring cohort that had an average of 3.35 spirometry measurements per person for a mean length of 13 years. Repeated forced expiratory volume in one second (FEV1 ) and the ratio of FEV1 to forced vital capacity (FVC) were used as outcomes. Data were analyzed using linear-mixed models for the association between lung function and alleles by accounting for the correlation among repeated measures over time within the same subject and within-family correlation. Network analyses were performed using dmGWAS and validated with data from the Third Generation cohort. Analyses identified SMAD3, TGFBR2, CD44, CTGF, VCAN, CTNNB1, SCGB1A1, PDE4D, NRG1, EPHB1, and LYN as contributors to pulmonary function. Most of these genes were novel that were not found previously using solely SNP-level analysis. These novel genes are involving the transforming growth factor beta (TGFB)-SMAD pathway, Wnt/beta-catenin pathway, etc. Therefore, combining SNP-level and network analyses using longitudinal lung function data is a useful alternative strategy to identify risk genes.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.