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

Wellcome Open Research

article

Carolyne M. Ndila¹  Vysaul Nyirongo²  Alexander W. Macharia¹  Anna E. Jeffreys³  Kate Rowlands³  Christina Hubbart³  George B. J. Busby³  Gavin Band³  Rosalind M. Harding⁶  Kirk A. Rockett³  Thomas N. Williams¹ 

[1] Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme;United Nation Statistics Division;Wellcome Centre for Human Genetics, University of Oxford;Centre for Genomics and Global Health, Big Data Institute, University of Oxford;Parasites and Microbes Programme, Wellcome Sanger Institute, Wellcome Genome Campus;Departments of Zoology and Statistics, University of Oxford;Department of Infectious Diseases, Imperial College Faculty of Medicine

关键词: Malaria;    α-thalassaemia;    Predictive Models;    multinomial regression-model;    Classification and Regression Tree;    GWAS;    haplotypes;   

DOI  :  10.12688/wellcomeopenres.16320.2

学科分类：内科医学

来源: Wellcome

【 摘 要 】

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.

【 授权许可】

CC BY