LSTM Home > LSTM Research > LSTM Online Archive

Causes of variability in latent phenotypes of childhood wheeze.

Downloads

Downloads per month over past year

Oksel, Ceyda, Granell, Raquel, Mahmoud, Osama, Custovic, Adnan and Henderson, A John (2019) 'Causes of variability in latent phenotypes of childhood wheeze.'. Journal of Allergy and Clinical Immunology, Vol 143, Issue 5, pp. 1783-1790.

[img]
Preview
Text
J_All_Clin_Immun_Accepted_YMAI13755_2018.pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

BACKGROUND
Latent class analysis (LCA) has been used extensively to identify (latent) phenotypes of childhood wheezing. However, the number and trajectory of discovered phenotypes differed substantially between studies.
OBJECTIVE
To investigate sources of variability affecting the classification of phenotypes, identify key time points for data collection to understand wheeze heterogeneity, and ascertain the association of childhood wheeze phenotypes with asthma and lung function in adulthood.
METHODS
We used LCA to derive wheeze phenotypes among 3167 participants in the ALSPAC cohort who had complete information on current wheeze recorded at 14 time points from birth to age 16½ years. We examined the effects of sample size, data collection age and intervals on the results, and identified time points. We examined the associations of derived phenotypes with asthma and lung function at age 23-24 years.
RESULTS
A relatively large sample size (>2000) underestimated the number of phenotypes under some conditions (e.g. number of time points <11). Increasing the number of data points resulted in an increase in the optimal number of phenotypes, but an identical number of randomly selected follow-up points led to different solutions. A variable selection algorithm identified 8 informative time points (months 18, 42, 57, 81, 91, 140, 157 and 166). The proportion of asthmatics at age 23-24 years differed between phenotypes, while lung function was lower among persistent wheezers.
CONCLUSIONS
Sample size, frequency, and timing of data collection have a major influence on the number and type of wheeze phenotypes identified by LCA in longitudinal data.

Item Type: Article
Subjects: QU Biochemistry > Genetics > QU 500 Genetic phenomena
QW Microbiology and Immunology > Reference Works. General Immunology > QW 504 General works
QW Microbiology and Immunology > Reference Works. General Immunology > QW 520 Research (General)
WF Respiratory System > Lungs > WF 600 Lungs
WS Pediatrics > WS 20 Research (General)
Faculty: Department: Clinical Sciences & International Health > Clinical Sciences Department
Digital Object Identifer (DOI): https://doi.org/10.1016/j.jaci.2018.10.059
Depositing User: Stacy Murtagh
Date Deposited: 12 Dec 2018 11:40
Last Modified: 24 May 2019 12:53
URI: https://archive.lstmed.ac.uk/id/eprint/9782

Statistics

View details

Actions (login required)

Edit Item Edit Item