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Biomedical subjects

Jürg Ott

Publications and source records attributed to Jürg Ott.

6 recordsLinked to original sources
PubMed2002

Cold-induced sweating syndrome is caused by mutations in the CRLF1 gene.

In 1978, Sohar et al. described a strikingly peculiar syndrome in two Israeli sisters. These young women responded to environmental temperatures of 18 degrees C-7 degrees C with profuse sweating on large segments on their back and chest. Both had additional abnormalities, including a high-arched palate, nasal voice, depressed nasal bridge, inability to fully extend their elbows, and kyphoscoliosis. We have observed this disorder in two Norwegian brothers. Genome-wide screening in the two families, followed by saturation marker studies and linkage analysis, identified a 1.4-Mb homozygous candidate region on chromosome 19p12. The maximum multipoint LOD score was 4.22. In both families, DNA sequencing of 25 genes within the candidate region identified potentially deleterious CRLF1 sequence variants that were not found in unaffected control individuals. Our findings confirm that the cold-induced sweating syndrome is an autosomal recessive disorder that is probably caused by impaired function of the CRLF1 gene, and they suggest important developmental functions for human CRLF1.

Adolescent↗
PubMed2002

A susceptibility locus for migraine with aura, on chromosome 4q24.

Migraine is a complex neurovascular disorder with substantial evidence supporting a genetic contribution. Prior attempts to localize susceptibility loci for common forms of migraine have not produced conclusive evidence of linkage or association. To date, no genomewide screen for migraine has been published. We report results from a genomewide screen of 50 multigenerational, clinically well-defined Finnish families showing intergenerational transmission of migraine with aura (MA). The families were screened using 350 polymorphic microsatellite markers, with an average intermarker distance of 11 cM. Significant evidence of linkage was found between the MA phenotype and marker D4S1647 on 4q24. Using parametric two-point linkage analysis and assuming a dominant mode of inheritance, we found for this marker a maximum LOD score of 4.20 under locus homogeneity (P=.000006) or locus heterogeneity (P=.000011). Multipoint parametric (HLOD = 4.45; P=.0000058) and nonparametric (NPL(all) = 3.43; P=.0007) analyses support linkage in this region. Statistically significant linkage was not observed in any other chromosomal region.

Chromosome Mapping↗
PubMed2002

Pharmacogenetic analysis of adverse drug effect reveals genetic variant for susceptibility to liver toxicity.

A retrospective pharmacogenetic study was conducted to identify possible genetic susceptibility factors in patients in whom the administration of the anti-Parkinson drug, tolcapone (TASMAR), was associated with hepatic toxicity. We studied 135 cases of patients with elevated liver transaminase levels (ELT) of >/=1.5 times above the upper limit of normal, in comparison with matched controls that had also received the drug but had not experienced ELT. DNA samples were genotyped for 30 previously described or newly characterized bi-allelic single nucleotide polymorphisms (SNPs), representing 12 candidate genes selected based on the known metabolic pathways involved in the tolcapone elimination. SNPs located within the UDP-glucuronosyl transferase 1A gene complex, which codes for the enzymes involved in the main elimination pathway of the drug, were found to be significantly associated with the occurrence of tolcapone-associated ELTs.

Benzophenones↗
PubMed2002

Log-linear models for gene mapping with affected sib pair data.

In genome-wide screens of genetic marker loci, non-mendelian inheritance of a marker is taken to indicate its vicinity to a disease locus. Heritable complex traits are thought to be under the influence of multiple possibly interacting susceptibility loci yet the most frequently used methods of linkage and association analysis focus on one susceptibility locus at a time. Here we introduce log-linear models for the joint analysis of multiple marker loci and interaction effects between them. Our approach focuses on affected sib pair data and identical by descent (IBD) allele sharing values observed on them. For each heterozygous parent, the IBD values at linked markers represent a sequence of dependent binary variables. We develop log-linear models for the joint distribution of these IBD values. An independence log-linear model is proposed to model the marginal means and the neighboring interaction model is advocated to account for associations between adjacent markers. Under the assumption of conditional independence, likelihood methods are applied to simulated data containing one or two susceptibility loci. It is shown that the neighboring interaction log-linear model is more efficient than the independence model, and incorporating interaction in the two-locus analysis provides increased power and accuracy for mapping of the trait loci.

Alleles↗
PubMed2002

Power and sample size calculations for case-control genetic association tests when errors are present: application to single nucleotide polymorphisms.

The purpose of this work is to quantify the effects that errors in genotyping have on power and the sample size necessary to maintain constant asymptotic Type I and Type II error rates (SSN) for case-control genetic association studies between a disease phenotype and a di-allelic marker locus, for example a single nucleotide polymorphism (SNP) locus. We consider the effects of three published models of genotyping errors on the chi-square test for independence in the 2 x 3 table. After specifying genotype frequencies for the marker locus conditional on disease status and error model in both a genetic model-based and a genetic model-free framework, we compute the asymptotic power to detect association through specification of the test's non-centrality parameter. This parameter determines the functional dependence of SSN on the genotyping error rates. Additionally, we study the dependence of SSN on linkage disequilibrium (LD), marker allele frequencies, and genotyping error rates for a dominant disease model. Increased genotyping error rate requires a larger SSN. Every 1% increase in sum of genotyping error rates requires that both case and control SSN be increased by 2-8%, with the extent of increase dependent upon the error model. For the dominant disease model, SSN is a nonlinear function of LD and genotyping error rate, with greater SSN for lower LD and higher genotyping error rate. The combination of lower LD and higher genotyping error rates requires a larger SSN than the sum of the SSN for the lower LD and for the higher genotyping error rate.

Case-Control Studies↗