Showing papers by "Michael Boehnke published in 2004"

Genetic Variation Near the Hepatocyte Nuclear Factor-4α Gene Predicts Susceptibility to Type 2 Diabetes

Abstract: The Finland-United States Investigation Of NIDDM Genetics (FUSION) study aims to identify genetic variants that predispose to type 2 diabetes by studying affected sibling pair families from Finland. Chromosome 20 showed our strongest initial evidence for linkage. It currently has a maximum logarithm of odds (LOD) score of 2.48 at 70 cM in a set of 495 families. In this study, we searched for diabetes susceptibility variant(s) at 20q13 by genotyping single nucleotide polymorphism (SNP) markers in case and control DNA pools. Of 291 SNPs successfully typed in a 7.5-Mb interval, the strongest association confirmed by individual genotyping was with SNP rs2144908, located 1.3 kb downstream of the primary beta-cell promoter P2 of hepatocyte nuclear factor-4 alpha (HNF4A). This SNP showed association with diabetes disease status (odds ratio [OR] 1.33, 95% CI 1.06-1.65, P = 0.011) and with several diabetes-related traits. Most of the evidence for linkage at 20q13 could be attributed to the families carrying the risk allele. We subsequently found nine additional associated SNPs spanning a 64-kb region, including the P2 and P1 promoters and exons 1-3. Our results and the independent observation of association of SNPs near the P2 promoter with diabetes in a separate study population of Ashkenazi Jewish origin suggests that variant(s) located near or within HNF4A increases susceptibility to type 2 diabetes.

Ordered subset analysis in genetic linkage mapping of complex traits

Abstract: Etiologic heterogeneity is a fundamental feature of complex disease etiology; genetic linkage analysis methods to map genes for complex traits that acknowledge the presence of genetic heterogeneity are likely to have greater power to identify subtle changes in complex biologic systems. We investigate the use of trait-related covariates to examine evidence for linkage in the presence of heterogeneity. Ordered-subset analysis (OSA) identifies subsets of families defined by the level of a trait-related covariate that provide maximal evidence for linkage, without requiring a priori specification of the subset. We propose that examining evidence for linkage in the subset directly may result in a more etiologically homogeneous sample. In turn, the reduced impact of heterogeneity will result in increased overall evidence for linkage to a specific region and a more distinct lod score peak. In addition, identification of a subset defined by a specific trait-related covariate showing increased evidence for linkage may help refine the list of candidate genes in a given region and suggest a useful sample in which to begin searching for trait-associated polymorphisms. This method provides a means to begin to bridge the gap between initial identification of linkage and identification of the disease predisposing variant(s) within a region when mapping genes for complex diseases. We illustrate this method by analyzing data on breast cancer age of onset and chromosome 17q [Hall et al., 1990, Science 250:1684-1689]. We evaluate OSA using simulation studies under a variety of genetic models.

Variation in the resistin gene is associated with obesity and insulin-related phenotypes in Finnish subjects.

Abstract: Aims/hypothesis Resistin is a peptide hormone produced by adipocytes that is present at high levels in sera of obese mice and may be involved in glucose homeostasis through regulation of insulin sensitivity. Several studies in humans have found associations between polymorphisms in the resistin gene and obesity, insulin sensitivity and blood pressure. An association between variation in the resistin gene and Type 2 diabetes has been reported in some, but not all studies. The aim of this study was to analyse variants of the resistin gene for association with Type 2 diabetes and related traits in a Finnish sample.

A Large Set of Finnish Affected Sibling Pair Families with Type 2 Diabetes Suggests Susceptibility Loci on Chromosomes 6, 11, and 14

Abstract: The aim of the Finland-United States Investigation of NIDDM Genetics (FUSION) study is to identify genes that predispose to type 2 diabetes or are responsible for variability in diabetes-related traits via a positional cloning and positional candidate gene approach. In a previously published genome-wide scan of 478 Finnish affected sibling pair (ASP) families (FUSION 1), the strongest linkage results were on chromosomes 20 and 11. We now report a second genome-wide scan using an independent set of 242 Finnish ASP families (FUSION 2), a detailed analysis of the combined set of 737 FUSION 1 + 2 families (495 updated FUSION 1 families), and fine mapping of the regions of chromosomes 11 and 20. The strongest FUSION 2 linkage results were on chromosomes 6 (maximum logarithm of odds score [MLS] = 2.30 at 95 cM) and 14 (MLS = 1.80 at 57 cM). For the combined FUSION 1 + 2 families, three results were particularly notable: chromosome 11 (MLS = 2.98 at 82 cM), chromosome 14 (MLS = 2.74 at 58 cM), and chromosome 6 (MLS = 2.66 at 96 cM). We obtained smaller FUSION 1 + 2 MLSs on chromosomes X (MLS = 1.27 at 152 cM) and 20p (MLS = 1.21 at 20 cM). Among the 10 regions that showed nominally significant evidence for linkage in FUSION 1, four (on chromosomes 6, 11, 14, and X) also showed evidence for linkage in FUSION 2 and stronger evidence for linkage in the combined FUSION 1 + 2 sample.

Increasing the Power and Efficiency of Disease-Marker Case-Control Association Studies through Use of Allele-Sharing Information

Abstract: Case-control disease-marker association studies are often used in the search for variants that predispose to complex diseases. One approach to increasing the power of these studies is to enrich the case sample for individuals likely to be affected because of genetic factors. In this article, we compare three case-selection strategies that use allele-sharing information with the standard strategy that selects a single individual from each family at random. In affected sibship samples, we show that, by carefully selecting sibships and/or individuals on the basis of allele sharing, we can increase the frequency of disease-associated alleles in the case sample. When these cases are compared with unrelated controls, the difference in the frequency of the disease-associated allele is therefore also increased. We find that, by choosing the affected sib who shows the most evidence for pairwise allele sharing with the other affected sibs in families, the test statistic is increased by >20%, on average, for additive models with modest genotype relative risks. In addition, we find that the per-genotype information associated with the allele sharing–based strategies is increased compared with that associated with random selection of a sib for genotyping. Even though we select sibs on the basis of a nonparametric statistic, the additional gain for selection based on the unknown underlying mode of inheritance is minimal. We show that these properties hold even when the power to detect linkage to a region in the entire sample is negligible. This approach can be extended to more-general pedigree structures and quantitative traits.

Assessing Whether an Allele Can Account in Part for a Linkage Signal: The Genotype-IBD Sharing Test (GIST)

Abstract: To fine map genes, investigators often test for disease-marker association in chromosomal regions with evidence for linkage. Given a marker allele tentatively associated with disease, one would ask if this allele, or one in linkage disequilibrium (LD) with it, could account in part for the observed linkage signal. This question can be addressed by determining if families selected on the basis of the presence of the tentatively associated allele show stronger evidence of linkage as measured by increased allele sharing identical by descent (IBD) by affected family members. However, common selection strategies can be biased for or against linkage in the marker region, even given no disease-marker association. We define unbiased selection schemes and extend the definition to allow weighted selection on the basis of all genotyped family members. For affected-sibship data, we describe three genotype-based weight variables, corresponding to dominant, recessive, and additive models. We then introduce a test for association of a family weight variable with excess IBD sharing. This test allows us to determine if the linkage signal in a region can be attributed in part to the presence of a marker allele, either because of direct involvement in disease etiology or because of LD with a predisposing genetic variant. For samples of 500 affected sib pairs, the tests are powerful in detection of genotype-IBD sharing association, even for disease models with sib relative risk as low as λS=1.1, or when evidence for linkage is absent because of sampling variation. This makes our method a new tool for detecting linkage as well as association, especially in regions harboring a candidate gene. We have implemented these methods in the software package GIST (Genotype-IBD Sharing Test).

A locus for Posterior Polymorphous Corneal Dystrophy (PPCD3) maps to chromosome 10

Abstract: Posterior polymorphous corneal dystrophy (PPCD) is an autosomal dominant disorder characterized by corneal endothelial abnormalities, which can lead to blindness due to loss of corneal transparency and sometimes glaucoma. We mapped a new locus responsible for PPCD in a family in which we excluded the previously reported PPCD locus on 20q11, and the region containing COL8A2 on chromosome 1. Results of a 317-marker genome scan provided significant evidence of linkage of PPCD to markers on chromosome 10, with single-point LOD scores of 2.63, 1.63, and 3.19 for markers D10S208 (at (circumflex)theta = 0.03), D10S1780 (at (circumflex)theta = 0.00), and D10S578 (at (circumflex)theta = 0.06). A maximum multi-point LOD score of 4.35 was found at marker D10S1780. Affected family members shared a haplotype in an 8.55 cM critical interval that was bounded by markers D10S213 and D10S578. Our finding of another PPCD locus, PPCD3, on chromosome 10 indicates that PPCD is genetically heterogeneous. Guttae, a common corneal finding sometimes observed along with PPCD, were found among both affected and unaffected members of the proband's sib ship, but were absent in the younger generations of the family. Evaluation of phenotypic differences between family members sharing the same affected haplotype raises questions about whether differences in disease severity, including differences in response to surgical interventions, could be due to genetic background or other factors independent of the PPCD3 locus.

The haplotype runs test: the parent-parent-affected offspring trio design.

Abstract: The increasing availability of maps of dense polymorphic markers makes use of haplotype data in family-based association analyses an attractive alternative to single marker association tests We describe a novel class of statistics designed to test for an association between marker haplotypes and a qualitative trait using the parent-parent-affected-offspring trio design Our haplotype runs test (HRT) is based on consecutive allele-sharing between pairs of haplotypes We assign weights according to the relative frequencies of the alleles for which the two haplotypes match Herein, we compare the HRT to the maximum-identity-length-contrast (MILC) statistic, the single-locus transmission/disequilibrium test (TDT), and the generalized test of transmission disequilibrium for haplotype data, as implemented in the software TRANSMIT, using both simulated data and published haplotype data from the recessive disorder ataxia-telangiectasia Our simulation results suggest that the HRT outperforms the MILC and that the HRT provides comparable power to the TDT and TRANSMIT when the number of distinct founder haplotypes with a disease susceptibility allele is small but substantially outperforms the TDT and TRANSMIT when the number of distinct founder haplotypes with a disease susceptibility allele is even of modest size