Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision
- Mahidol Oxford Tropical Medicine Research Unit, Thailand
- KEMRI-Wellcome Trust Research Programme, Kenya
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kenya
- Wellcome Trust Centre for Human Genetics, United Kingdom
- Medical Research Council Clinical Trials Unit, United Kingdom
- Mahidol University, Thailand
- Kilifi KEMRI-Wellcome Trust Collaborative Research Programme, Kenya
- Department of Statistics, University of Oxford, United Kingdom
Abstract
Severe falciparum malaria has substantially affected human evolution. Genetic association studies of patients with clinically defined severe malaria and matched population controls have helped characterise human genetic susceptibility to severe malaria, but phenotypic imprecision compromises discovered associations. In areas of high malaria transmission the diagnosis of severe malaria in young children and, in particular, the distinction from bacterial sepsis, is imprecise. We developed a probabilistic diagnostic model of severe malaria using platelet and white count data. Under this model we re-analysed clinical and genetic data from 2,220 Kenyan children with clinically defined severe malaria and 3,940 population controls, adjusting for phenotype mis-labelling. Our model, validated by the distribution of sickle trait, estimated that approximately one third of cases did not have severe malaria. We propose a data-tilting approach for case-control studies with phenotype mis-labelling and show that this reduces false discovery rates and improves statistical power in genome-wide association studies.
Data availability
A curated minimal clinical dataset is currently available alongisde the code on the github repository. This will also be made available at publication via the KEMRI-Wellcome Harvard Dataverse(https://dataverse.harvard.edu/dataverse/kwtrp).Whole genome data are available from European Genome-Phenome Archive (dataset accession ID: EGAD00010001742).Requests for access to appropriately anonymized clinical data and directly typed genetic variants for the Kenyan severe malaria cohort can be made by application to the data access committee at the KEMRI-Wellcome Trust Research Programme by e-mail to mmunene@kemri-wellcome.org.The FEAST trial datasets are available from the principal investigator on reasonable request (k.maitland@imperial.ac.uk).Requests for access to appropriately anonymized clinical data from the AQ and AAV Vietnam study and the Asian paediatric cohort can be made via the Mahidol Oxford Tropical Medicine Research Unit data access committee by emailing the corresponding author JAW (jwatowatson@gmail.com) or Rita Chanviriyavuth (rita@tropmedres.ac).
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A genome-wide study of resistance to severe malaria in 18,000 samples from eleven worldwide populations, including eight populations sub-Saharan Africa.European Genome-Phenome Archive, EGAD00010001742.
Article and author information
Author details
Funding
Wellcome Trust (209265/Z/17/Z)
- Kathryn Maitland
- Nicholas PJ Day
Wellcome Trust (202800/Z/16/Z)
- Thomas Williams
Wellcome Trust (093956/Z/10/C)
- Nicholas J White
Medical Research Council (MC\UU\12023/26)
- Elizabeth C George
Wellcome Trust (WT077383/Z/05/Z)
- Kirk Rockett
Medical Research Council (G0801439)
- Elizabeth C George
- Kathryn Maitland
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Jennifer Flegg, The University of Melbourne, Australia
Ethics
Human subjects: All clinical data are from published studies in which all participants or guardians gave fully informed consent. Access to the human genetic data was approved by the MalariaGen data access committee.
Version history
- Received: April 22, 2021
- Accepted: June 22, 2021
- Accepted Manuscript published: July 6, 2021 (version 1)
- Version of Record published: July 27, 2021 (version 2)
- Version of Record updated: November 22, 2021 (version 3)
Copyright
© 2021, Watson et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision
eLife 10:e69698.
https://doi.org/10.7554/eLife.69698
Further reading
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- Epidemiology and Global Health
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- Epidemiology and Global Health
Background:
Circulating omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) have been associated with various chronic diseases and mortality, but results are conflicting. Few studies examined the role of omega-6/omega-3 ratio in mortality.
Methods:
We investigated plasma omega-3 and omega-6 PUFAs and their ratio in relation to all-cause and cause-specific mortality in a large prospective cohort, the UK Biobank. Of 85,425 participants who had complete information on circulating PUFAs, 6461 died during follow-up, including 2794 from cancer and 1668 from cardiovascular disease (CVD). Associations were estimated by multivariable Cox proportional hazards regression with adjustment for relevant risk factors.
Results:
Risk for all three mortality outcomes increased as the ratio of omega-6/omega-3 PUFAs increased (all Ptrend <0.05). Comparing the highest to the lowest quintiles, individuals had 26% (95% CI, 15–38%) higher total mortality, 14% (95% CI, 0–31%) higher cancer mortality, and 31% (95% CI, 10–55%) higher CVD mortality. Moreover, omega-3 and omega-6 PUFAs in plasma were all inversely associated with all-cause, cancer, and CVD mortality, with omega-3 showing stronger effects.
Conclusions:
Using a population-based cohort in UK Biobank, our study revealed a strong association between the ratio of circulating omega-6/omega-3 PUFAs and the risk of all-cause, cancer, and CVD mortality.
Funding:
Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institute of Health under the award number R35GM143060 (KY). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
