The creation of 'consistent areas through time' (CATTs) in Scotland, 1981-2001

Small area analysis of sociodemographic change over time is often impeded by the changing configuration of census zones for each decennial UK census. Approaches for matching zone configurations exist, but these typically require population estimation techniques, which inevitably involve some error. Because of the postcode-based geographical zoning system used in Scottish censuses, it is possible to create a local-area geography which is consistent for recent censuses. Here we present a methodology used to create three sets of consistent areas through time (CATTs) that can be used for analysing comparable small area data output from the 1981, 1991 and 2001 Censuses.     

Negative epistasis between the malaria-protective effects of alpha+-thalassemia and the sickle cell trait

The hemoglobinopathies, disorders of hemoglobin structure and production, protect against death from malaria. In sub-Saharan Africa, two such conditions occur at particularly high frequencies: presence of the structural variant hemoglobin S and alpha(+)-thalassemia, a condition characterized by reduced production of the normal alpha-globin component of hemoglobin. Individually, each is protective against severe Plasmodium falciparum malaria, but little is known about their malaria-protective effects when inherited in combination. We investigated this question by studying a population on the coast of Kenya and found that the protection afforded by each condition inherited alone was lost when the two conditions were inherited together, to such a degree that the incidence of both uncomplicated and severe P. falciparum malaria was close to baseline in children heterozygous with respect to the mutation underlying the hemoglobin S variant and homozygous with respect to the mutation underlying alpha(+)-thalassemia. Negative epistasis could explain the failure of alpha(+)-thalassemia to reach fixation in any population in sub-Saharan Africa.     

Population structure, differential bias and genomic control in a large-scale, case-control association study

The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method by applying a variable downweighting to each SNP.