Evidence map›Paper›PMID 37038187›Full record

ArticleMalaria journal2023

Genome-wide association testing in malaria studies in the presence of overdominance.

Morine Akoth, John Odhiambo, Bernard Omolo

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 3 countries.

Morine AkothStrathmore Institute of Mathematical Sciences, Strathmore University, Ole Sangale Road, Nairobi, Kenya. makoth@strathmore.edu.
John OdhiamboStrathmore Institute of Mathematical Sciences, Strathmore University, Ole Sangale Road, Nairobi, Kenya.
Bernard OmoloStrathmore Institute of Mathematical Sciences, Strathmore University, Ole Sangale Road, Nairobi, Kenya.
Strathmore University · KE

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundIn human genetics, heterozygote advantage (heterosis) has been detected in studies that focused on specific genes but not in genome-wide association studies (GWAS). For example, heterosis is believed to confer resistance to certain strains of malaria in patients heterozygous for the sickle-cell gene, haemoglobin S (HbS). Yet the power of allelic tests can be substantially diminished by heterosis. Since GWAS (and haplotype-associations) also utilize allelic tests, it is unclear to what degree GWAS could underachieve because heterosis is ignored.

methodsIn this study, a two-step approach to genetic association testing in malaria studies in a GWAS setting that may enhance the power of the tests was proposed, by identifying the underlying genetic model first before applying the association tests. Generalized linear models for dominant, recessive, additive, and heterotic effects were fitted and model selection was performed. This was achieved via tests of significance using the MAX and allelic tests, noting the minimum p-values across all the models and the proportion of tests that a given genetic model was deemed the best. An example dataset, based on 17 SNPs, from a robust genetic association study and simulated genotype datasets, were used to illustrate the method. Case-control genotype data on malaria from Kenya and Gambia were used for validation. RESULTS AND

conclusionResults showed that the allelic test returned some false negatives under the heterosis model, suggesting reduced power in testing genetic association. Disparities were observed for some chromosomes in the Kenyan and Gambian datasets, including the sex chromosomes. Thus, GWAS and haplotype associations should be treated with caution, unless the underlying genetic model had been determined.

Indexed as

Genome-Wide Association StudyMalariaGenotypeHeterozygoteHumansKenyaPolymorphism, Single NucleotideAllelic testCase–control studyGenome-wide associationMalariaMAX test

Identifiers

PMID37038187
PMCPMC10084622
OpenAlexW4363678017

What OpenQuestion holds

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LicenceCC BY
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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.