On the performance of multiple imputation based on chained equations in tackling missing data of the African α3.7 -globin deletion in a malaria association study

Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α 3.7I form of α-thalassaemia using genome-wide microarray data

Background: The -α ^3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations.

Methods: In this study, we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR.

Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha ( HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results.

Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.

Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data

Background: The -α3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha (HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.

Most associations of early-life environmental exposures and genetic risk factors poorly differentiate between eczema phenotypes: the Generation R Study

Background

Childhood eczema is variable in onset and persistence.

Objectives

To identify eczema phenotypes during childhood, and their associations with early‐life environmental and genetic factors.

Methods

In this study of 5297 children from a multiethnic population‐based prospective cohort study, phenotypes based on parent‐reported physician‐diagnosed eczema from age 6 months to 10 years were identified using latent class growth analysis. Information on environmental factors was obtained using postal questionnaires. Four filaggrin mutations were genotyped and a risk score was calculated based on 30 genetic variants. Weighted adjusted multinomial models were used for association analyses.

Results

We identified the following five eczema phenotypes: never (76%), early transient (8%), mid‐transient (6%) and late transient (8%) and persistent eczema (2%). Early transient and persistent eczema were most common in first‐born children, those with a parental history of eczema, allergy or asthma and those with persistent wheezing [range of odds ratio (OR): 1.37, 95% confidence interval (CI) 1.07–1.74 and OR 3.38, 95%CI 1.95–5.85]. Early transient eczema was most common in male children only (OR 1·49, 95% CI 1·18–1·89). Children with late transient or persistent eczema were more often of Asian ethnicity (OR 2·04, 95% CI 1·14–3·65 and OR 3·08, 95% CI 1·34–7·10, respectively). Children with early, late transient and persistent eczema more often had a filaggrin mutation or additional risk alleles (range OR: 1.07, 95%CI 1.02–1.12 and OR 2.21, 95%CI 1.39–3.50). Eczema phenotypes were not associated with maternal education, breastfeeding, day care attendance and pet exposure.

Conclusions

Five eczema phenotypes were identified in a multiethnic paediatric population with limited differences in risk profiles, except for sex and ethnicity.

What's already known about this topic?

Two previous studies in longitudinal birth cohorts identified four and six different eczema phenotypes, predominantly in children of European ethnicity.

What does this study add?

Five eczema phenotypes were identified in a multiethnic paediatric population using latent class growth analysis.

Children with early transient and persistent eczema were most often first‐born children and had persistent wheezing, filaggrin mutation or additional risk alleles.

Previously known eczema risk factors had limited differentiating capabilities for eczema phenotypes, except for the association of early transient eczema with male children, and late transient and persistent eczema with Asian ethnicity.

https://doi.org/10.1111/bjd.18575 available online

https://www.bjdonline.com/article/most-associations-of-early-life-environmental-exposures-and-genetic-risk-factors-poorly-differentiate-between-eczema-phenotypes-the-generation-r-study/

Malaria Host Candidate Genes Validated by Association With Current, Recent, and Historical Measures of Transmission Intensity

Background

Human malaria susceptibility is determined by multiple genetic factors. It is unclear, however, which genetic variants remain important over time.

Methods

Genetic associations of 175 high-quality polymorphisms within several malaria candidate genes were examined in a sample of 8096 individuals from northeast Tanzania using altitude, seroconversion rates, and parasite rates as proxies of historical, recent, and current malaria transmission intensity. A principal component analysis was used to derive 2 alternative measures of overall malaria propensity of a location across different time scales.

Results

Common red blood cell polymorphisms (ie, hemoglobin S, glucose-6-phosphate dehydrogenase, and α-thalassemia) were the only ones to be associated with all 3 measures of transmission intensity and the first principal component. Moderate associations were found between some immune response genes (ie, IL3 and IL13) and parasite rates, but these could not be reproduced using the alternative measures of malaria propensity.

Conclusions

We have demonstrated the potential of using altitude and seroconversion rate as measures of malaria transmission capturing medium- to long-term time scales to detect genetic associations that are likely to persist over time. These measures also have the advantage of minimizing the deleterious effects of random factors affecting parasite rates on the respective association signals.

Sample size and power calculations for detecting changes in malaria transmission using antibody seroconversion rate

BACKGROUND

Several studies have highlighted the use of serological data in detecting a reduction in malaria transmission intensity. These studies have typically used serology as an adjunct measure and no formal examination of sample size calculations for this approach has been conducted.

METHODS

A sample size calculator is proposed for cross-sectional surveys using data simulation from a reverse catalytic model assuming a reduction in seroconversion rate (SCR) at a given change point before sampling. This calculator is based on logistic approximations for the underlying power curves to detect a reduction in SCR in relation to the hypothesis of a stable SCR for the same data. Sample sizes are illustrated for a hypothetical cross-sectional survey from an African population assuming a known or unknown change point.

RESULTS

Overall, data simulation demonstrates that power is strongly affected by assuming a known or unknown change point. Small sample sizes are sufficient to detect strong reductions in SCR, but invariantly lead to poor precision of estimates for current SCR. In this situation, sample size is better determined by controlling the precision of SCR estimates. Conversely larger sample sizes are required for detecting more subtle reductions in malaria transmission but those invariantly increase precision whilst reducing putative estimation bias.

CONCLUSIONS

The proposed sample size calculator, although based on data simulation, shows promise of being easily applicable to a range of populations and survey types. Since the change point is a major source of uncertainty, obtaining or assuming prior information about this parameter might reduce both the sample size and the chance of generating biased SCR estimates.