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.     

Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes

The Wellcome Trust Case Control Consortium (WTCCC) primary genome-wide association (GWA) scan on seven diseases, including the multifactorial autoimmune disease type 1 diabetes (T1D), shows associations at P < 5 x 10(-7) between T1D and six chromosome regions: 12q24, 12q13, 16p13, 18p11, 12p13 and 4q27. Here, we attempted to validate these and six other top findings in 4,000 individuals with T1D, 5,000 controls and 2,997 family trios independent of the WTCCC study. We confirmed unequivocally the associations of 12q24, 12q13, 16p13 and 18p11 (P(follow-up) 相似文献   

David Hume's no-miracles argument begets a valid No-Miracles Argument

Hume's essay ‘Of Miracles’ has been a focus of controversy ever since its publication. The challenge to Christian orthodoxy was only too evident, but the balance-of-probabilities criterion advanced by Hume for determining when testimony justifies belief in miracles has also been a subject of contention among philosophers. The temptation for those familiar with Bayesian methodology to show that Hume's criterion determines a corresponding balance-of-posterior probabilities in favour of miracles is understandable, but I will argue that their attempts fail. However, I show that his criterion generates a valid form of the so-called No-Miracles Argument appealed to by modern realist philosophers, whose own presentation of it, despite their possession of the probabilistic machinery Hume himself lacked, is invalid.     

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods-recursive partitioning and regression-to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; P(combined) = 2.01 x 10(-19) and 2.35 x 10(-13), respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes.     

Hume’s Theorem

A common criticism of Hume’s famous anti-induction argument is that it is vitiated because it fails to foreclose the possibility of an authentically probabilistic justification of induction. I argue that this claim is false, and that on the contrary, the probability calculus itself, in the form of an elementary consequence that I call Hume’s Theorem, fully endorses Hume’s argument. Various objections, including the often-made claim that Hume is defeated by de Finetti’s exchangeability results, are considered and rejected.     

Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease

Genes and mechanisms involved in common complex diseases, such as the autoimmune disorders that affect approximately 5% of the population, remain obscure. Here we identify polymorphisms of the cytotoxic T lymphocyte antigen 4 gene (CTLA4)--which encodes a vital negative regulatory molecule of the immune system--as candidates for primary determinants of risk of the common autoimmune disorders Graves' disease, autoimmune hypothyroidism and type 1 diabetes. In humans, disease susceptibility was mapped to a non-coding 6.1 kb 3' region of CTLA4, the common allelic variation of which was correlated with lower messenger RNA levels of the soluble alternative splice form of CTLA4. In the mouse model of type 1 diabetes, susceptibility was also associated with variation in CTLA-4 gene splicing with reduced production of a splice form encoding a molecule lacking the CD80/CD86 ligand-binding domain. Genetic mapping of variants conferring a small disease risk can identify pathways in complex disorders, as exemplified by our discovery of inherited, quantitative alterations of CTLA4 contributing to autoimmune tissue destruction.