Amino acid position 11 of HLA-DRß1 is a major determinant of chromosome 6p association with ulcerative colitis.

The major histocompatibility complex (MHC) on chromosome 6p is an established risk locus for ulcerative colitis (UC) and Crohn's disease (CD). We aimed to better define MHC association signals in UC and CD by combining data from dense single-nucleotide polymorphism (SNP) genotyping and from imputation of classical human leukocyte antigen (HLA) types, their constituent SNPs and corresponding amino acids in 562 UC, 611 CD and 1428 control subjects. Univariate and multivariate association analyses were performed, controlling for ancestry. In univariate analyses, absence of the rs9269955 C allele was strongly associated with risk for UC (P = 2.67 × 10(-13)). rs9269955 is a SNP in the codon for amino acid position 11 of HLA-DRß1, located in the P6 pocket of the HLA-DR antigen binding cleft. This amino acid position was also the most significantly UC-associated amino acid in omnibus tests (P = 2.68 × 10(-13)). Multivariate modeling identified rs9269955-C and 13 other variants in best predicting UC vs control status. In contrast, there was only suggestive association evidence between the MHC and CD. Taken together, these data demonstrate that variation at HLA-DRß1, amino acid 11 in the P6 pocket of the HLA-DR complex antigen binding cleft is a major determinant of chromosome 6p association with UC.

Compliance to adjuvant therapy in breast cancer patients.

During recent years a continuous reduction of mortality from breast cancer has taken place in the Western countries. We wanted to verify whether the actual therapy for our own cases deviates from our recommendations, although the surgeon, radiotherapist and gynaecological oncologist are on the same premises. We sent out questionnaires to all newly diagnosed breast cancer patients in the last seven years regarding their adjuvant therapy. Comparing these answers to our own recommendation showed a very good compliance regarding chemotherapy and radiation therapy. Adjuvant endocrine therapy showed a very poor compliance with an adherence of 77%. Overall we can conclude that endocrine therapy causes many side-effects that seem to burden the patients. In combination with the duration of the therapy this causes a severe reduction in compliance and length of the therapy.

Genetic analysis of vertebral trabecular bone density and cross-sectional area in older men.

We investigated 383 bone candidate genes for associations between single nucleotide polymorphisms and vertebral trabecular volumetric bone mineral density (vBMD) and cross-sectional area (CSA) in 2,018 Caucasian men aged ≥ 65 years. SNPs in TGFBR3, SOST, KL, CALCR, LEP, CSF1R, PTN, GNRH2, FGFR2, and MEPE were associated with vBMD and SNPs in CYP11B1, DVL2, DLX5, WNT4, and PAX7 were associated with CSA in independent study samples (p < 0.005). INRODUCTION: Vertebral bone mineral density and cross-sectional area are important determinants of vertebral bone strength. Little is known about the specific genetic variants that influence these phenotypes in humans. METHODS: We investigated the potential genetic variants associated with vertebral trabecular volumetric BMD and CSA measured by quantitative computed tomography. We initially tested for association between these phenotypes and 4608 tagging and potentially functional single nucleotide polymorphisms (SNPs) in 383 candidate genes in 862 community-dwelling Caucasian men aged ≥ 65 years in the Osteoporotic Fractures in Men Study. RESULTS: SNP associations were then validated by genotyping an additional 1,156 randomly sampled men from the same cohort. We identified 11 SNPs in 10 genes (TGFBR3, SOST, KL, CALCR, LEP, CSF1R, PTN, GNRH2, FGFR2, and MEPE) that were consistently associated with trabecular vBMD and five SNPs in five genes (CYP11B1, DVL2, DLX5, WNT4, and PAX7) that were consistently associated with CSA in both samples (p < 0.005). CONCLUSION: None of the SNPs associated with trabecular vBMD were associated with CSA. Our findings raise the possibility that at least some of the loci for vertebral trabecular BMD and bone size may be distinct.

Cladistic analysis of human apolipoprotein a4 polymorphisms in relation to quantitative plasma lipid risk factors of coronary heart disease.

Genetic variation in several genes involved in lipid metabolism is known to affect population variation in quantitative lipid risk factor profiles for coronary heart disease (CHD). The apolipoprotein A-IV gene (APOA4) is one such candidate gene. We genotyped five polymorphisms in the APOA4 gene (codon 127, codon 130, codon347, codon 360 and 3' VNTR) and investigated their impact on plasma lipid trait levels in three populations comprising 604 U.S. non-Hispanic Whites (NHWs), 408 U.S. Hispanics and 708 Nigerian Blacks. Cladistic analysis was carried out to identify 5-site haplotypes that were associated with significant phenotypic differences in each population. The distribution of APOA4 genotypes was significantly different between ethnic groups. The Africans were monomorphic for two of the five sites (codons 130 and 360), but possess a unique 12 bp insertion that was not observed in NHWs and Hispanics. Due to linkage disequilibrium between the sites, only 6 haplotypes were observed in NHWs and Hispanics, and 4 in Africans. Several gender-and ethnic-specific associations between genotypes and plasma lipid traits were observed when single sites were used. Several haplotypes were identified by cladistic analysis that may carry functional mutations that affect plasma lipid trait levels.

Genome-wide multipoint linkage analyses of multiplex schizophrenia pedigrees from the oceanic nation of Palau.

The oceanic nation of Palau has been geographically and culturally isolated over most of its 2000 year history. As part of a study of the genetic basis of schizophrenia in Palau, we genotyped five large, multigenerational schizophrenia pedigrees using markers every 10 cM (CHLC/Weber screening set 6). The number of affected/unaffected individuals genotyped per family ranged from 11/21 to 5/5. Thus the pedigrees varied in their information for linkage, but each was capable of producing a substantial LOD score. We fitted a simple dominant and recessive model to these data using multipoint linkage analysis implemented by Simwalk2. Predictably, the most informative pedigrees produced the best linkage results. After genotyping additional markers in the region, one pedigree produced a LOD = 3.4 (5q distal) under the dominant model. Seven of nine schizophrenics in the pedigree, mostly 3rd-4th degree relatives, share a 15-cM, 7-marker haplotype. For a different pedigree, another promising signal occurred on distal 3q, LOD = 2.6, for the recessive model. For two other pedigrees, the best LODs were modest, slightly better than 2.0 on 5q and 9p, while the fifth pedigree produced no noteworthy linkage signal. Similar to the results for other populations, our results suggest there are multiple genes conferring liability to schizophrenia even in the small population of Palau (roughly 21,000 individuals) in remote Oceania.

Genome-wide distribution of linkage disequilibrium in the population of Palau and its implications for gene flow in Remote Oceania.

Linkage disequilibrium (LD) between alleles on the same human chromosome results from various evolutionary processes and is thus telling about the history of populations. Recently, LD has garnered substantial interest for its value to map and fine-map disease genes. We examine the distribution of LD between short tandem repeat alleles on autosomes and sex chromosomes in the Remote Oceanic population of Palau to evaluate whether the data are consistent with a recent hypothesis about the origins of genetic variation in Palau, specifically that the population experienced extensive male-biased gene flow following initial settlement. Consistent with evolutionary theory based on effective population size, LD between X-linked alleles is stochastically greater than LD between autosomal alleles, however, small but detectable LD occurs for autosomal markers separated by substantial distances. By contrast, while Y-linked alleles experience only one-third the effective population size of X-linked alleles, their mean value for pairwise LD is only slightly larger than X-linked alleles. For a small population known to experience at least two extreme bottlenecks, 56 six-locus Y haplotypes exhibit remarkable diversity (0.96), comparable to Y diversity of Europeans, however, autosomal and X-linked markers display significantly less diversity, as measured by heterozygosity (4.1% less). Palauan Y haplotypes also fall into distinct clusters, again unlike that of Europe. We argue these data are consistent with waves of male-biased gene flow.

Transmission/disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes.

Family data teamed with the transmission/disequilibrium test (TDT), which simultaneously evaluates linkage and association, is a powerful means of detecting disease-liability alleles. To increase the information provided by the test, various researchers have proposed TDT-based methods for haplotype transmission. Haplotypes indeed produce more-definitive transmissions than do the alleles comprising them, and this tends to increase power. However, the larger number of haplotypes, relative to alleles at individual loci, tends to decrease power, because of the additional degrees of freedom required for the test. An optimal strategy would focus the test on particular haplotypes or groups of haplotypes. In this report we develop such an approach by combining the theory of TDT with that of measured haplotype analysis (MHA). MHA uses the evolutionary relationships among haplotypes to produce a limited set of hypothesis tests and to increase the interpretability of these tests. The theory of our approach, called the "evolutionary tree" (ET)-TDT, is developed for two cases: when haplotype transmission is certain and when it is not. Simulations show the ET-TDT can be more powerful than other proposed methods under reasonable conditions. More importantly, our results show that, when multiple polymorphisms are found within the gene, the ET-TDT can be useful for determining which polymorphisms affect liability.

A Bayesian hierarchical model for allele frequencies.

Genetic epidemiological methodologies, such as linkage analysis, often require accurate estimates of allele frequencies. When studies involve multiple sub-populations with different evolutionary histories, accurate estimates can be difficult to obtain because the number of subjects per sub-population tends to be limited. Given allele counts for a collection of loci and sub-populations, we propose a Bayesian hierarchical model that extends existing empirical Bayesian approaches by allowing for explicit inclusion of prior information about both allele frequencies and inter-population divergence. We describe how such information can be derived from published data and then incorporated into the model via prior distributions for model parameters. By analysis of simulated data, we highlight how the hierarchical model, as implemented in the publicly available program AllDist, combines prior information with the observed data to refine allele frequency estimates.

Unbiased methods for population-based association studies.

Large, population-based samples and large-scale genotyping are being used to evaluate disease/gene associations. A substantial drawback to such samples is the fact that population substructure can induce spurious associations between genes and disease. We review two methods, called genomic control (GC) and structured association (SA), that obviate many of the concerns about population substructure by using the features of the genomes present in the sample to correct for stratification. The GC approach exploits the fact that population substructure generates "over dispersion" of statistics used to assess association. By testing multiple polymorphisms throughout the genome, only some of which are pertinent to the disease of interest, the degree of overdispersion generated by population substructure can be estimated and taken into account. The SA approach assumes that the sampled population, although heterogeneous, is composed of subpopulations that are themselves homogeneous. By using multiple polymorphisms throughout the genome, this "latent class method" estimates the probability sampled individuals derive from each of these latent subpopulations. GC has the advantage of robustness, simplicity, and wide applicability, even to experimental designs such as DNA pooling. SA is a bit more complicated but has the advantage of greater power in some realistic settings, such as admixed populations or when association varies widely across subpopulations. It, too, is widely applicable. Both also have weaknesses, as elaborated in our review.

Genomic control, a new approach to genetic-based association studies.

During the past decade, mutations affecting liability to human disease have been discovered at a phenomenal rate, and that rate is increasing. For the most part, however, those diseases have a relatively simple genetic basis. For diseases with a complex genetic and environmental basis, new approaches are needed to pave the way for more rapid discovery of genes affecting liability. One such approach exploits large, population-based samples and large-scale genotyping to evaluate disease/gene associations. A substantial drawback to such samples is the fact that population heterogeneity can induce spurious associations between genes and disease. We describe a method called genomic control (GC), which obviates many of the concerns about population substructure by using the features of the genomes present in the sample to correct for stratification. Two such approaches are now available. The GC approach exploits the fact that population substructure generate "overdispersion" of statistics used to assess association. By testing multiple polymorphisms throughout the genome, only some of which are pertinent to the disease of interest, the degree of overdispersion generated by population substructure can be estimated and taken into account. The other approach, called Structured Association (SA), assumes that the sampled population, while heterogeneous, is composed of subpopulations that are themselves homogeneous. By using multiple polymorphisms throughout the genome, SA probabilistically assigns sampled individuals to these latent subpopulations. We review in detail the overdispersion GC. In addition to outlining the published ideas on this method, we describe several extensions: quantitative trait studies and case-control studies with haplotypes and multiallelic markers. For each study design our goal is to achieve control similar to that obtained for a family-based study, but with the convenience found in a population-based design.