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Jürg Ott

Publications and source records attributed to Jürg Ott.

13 recordsLinked to original sources
PubMed2006

Are molecular haplotypes worth the time and expense? A cost-effective method for applying molecular haplotypes.

Because current molecular haplotyping methods are expensive and not amenable to automation, many researchers rely on statistical methods to infer haplotype pairs from multilocus genotypes, and subsequently treat these inferred haplotype pairs as observations. These procedures are prone to haplotype misclassification. We examine the effect of these misclassification errors on the false-positive rate and power for two association tests. These tests include the standard likelihood ratio test (LRTstd) and a likelihood ratio test that employs a double-sampling approach to allow for the misclassification inherent in the haplotype inference procedure (LRTae). We aim to determine the cost-benefit relationship of increasing the proportion of individuals with molecular haplotype measurements in addition to genotypes to raise the power gain of the LRTae over the LRTstd. This analysis should provide a guideline for determining the minimum number of molecular haplotypes required for desired power. Our simulations under the null hypothesis of equal haplotype frequencies in cases and controls indicate that (1) for each statistic, permutation methods maintain the correct type I error; (2) specific multilocus genotypes that are misclassified as the incorrect haplotype pair are consistently misclassified throughout each entire dataset; and (3) our simulations under the alternative hypothesis showed a significant power gain for the LRTae over the LRTstd for a subset of the parameter settings. Permutation methods should be used exclusively to determine significance for each statistic. For fixed cost, the power gain of the LRTae over the LRTstd varied depending on the relative costs of genotyping, molecular haplotyping, and phenotyping. The LRTae showed the greatest benefit over the LRTstd when the cost of phenotyping was very high relative to the cost of genotyping. This situation is likely to occur in a replication study as opposed to a whole-genome association study.

Cost-Benefit Analysis↗
PubMed2005

The TRP2 allele of COL9A2 is an age-dependent risk factor for the development and severity of intervertebral disc degeneration.

STUDY DESIGN: Low back pain (LBP) and sciatica are usually caused by degenerative disc disease (DDD). Although they are common, the etiology of these conditions is poorly understood. A large population case-control study in the Southern Chinese was performed to study genetic risk factors to DDD. OBJECTIVES: To gain a better understanding of the etiology of DDD in relation to structural defects of the intervertebral disc. SUMMARY OF BACKGROUND DATA: A Finnish study found an association between LBP and sciatica with two variants of the alpha-chains of collagen IX, encoded by the Trp2 and Trp3 alleles, representing Gln326Trp and Arg103Trp amino acid substitutions in the COL9A2 and COL9A3 genes, respectively. Trp2 was found only in affected individuals (4%), whereas Trp3 was present in both affected (24%) and unaffected (9%) individuals. Because of the low frequency of the Trp2 allele in whites, the significance and contribution of this allele to DDD are not known. Using more objective criteria to define the disease by magnetic resonance imaging (MRI), we tested these alleles for association with DDD in a large population study. METHODS: Lumbar DDD, the presence of anular tears, and disc and endplate herniations were defined by MRI in 804 Southern Chinese volunteers 18 to 55 years of age. These were correlated with the frequencies of the Trp2 and Trp3 alleles. RESULTS: The Trp2 allele was present in 20% of the population and was associated with a fourfold increase in the risk of developing anular tears at 30 to 39 years and a 2.4-fold increase in the risk of developing DDD and endplate herniations at 40 to 49 years. Affected Trp2 individuals had more severe degeneration. The Trp3 allele was absent from the Southern Chinese population. CONCLUSION: This largest-ever population study using MRI to define DDD demonstrates for the first time that the Trp2 allele is a significant risk factor for the development and severity of degeneration. The association is age- dependent as it is more prevalent in some age groups than in others. The contrasting Trp allele frequencies between the Finns and the Chinese are the first indication that the genetic risk factors for DDD varies between ethnic groups.

Adolescent↗
PubMed2005

Genetic variations in IL6 associate with intervertebral disc disease characterized by sciatica.

Intervertebral disc disease (IDD) characterized by sciatica is a common disorder affecting about 5% of individuals. Environmental factors can predispose to this disease, but IDD has a strong genetic background. Recent evidence suggests that inflammation is one of the key factors in the etiology of IDD. Here, a possible role of the inflammatory mediator genes was studied in 155 patients with IDD-related sciatica and 179 controls. Forty-eight patients were analyzed for mutations in the IL1A, IL1B, IL6 and TNFA genes, and 16 polymorphisms in 10 candidate cytokine genes (IL1A, IL1B, IL1RN, TNFA, IL2, IL4, IL4R, IL6, IL10, IFNG) were genotyped from all subjects. No disease-causing mutations were identified in IL1A, IL1B, IL6 or TNFA. Allele frequencies were, however, significantly different between the two groups for IL6 SNP, T15A in exon 5 (P=0.007). Furthermore, the genotypes AA and AT of the exon 5 SNP were more common in the patients (P=0.011; OR=4.4, 95% CI=1.2-15.7; AR=7.5%, 1.6-13.1%). Haplotypes were then generated for four IL6 SNPs, G-597A, G-572C, G-174C, and T15A in exon 5. Haplotype GGGA was more common in the patients (P=0.011; OR=4.8, 95% CI=1.6-14.5). To evaluate attributable risk, haplotype pairs were assigned for the individuals. The presence of GGGA/GGGA or GGGA/other genotypes had an OR of 5.4 (95% CI=1.5-19.2). Association of GGGA with disease was highly significant (P=0.0033), and the associated AR was 6.8% (1.9-11.5%). These findings support the role of IL-6 genetic variations in discogenic pain.

Adult↗
PubMed2005

Use of a combined ex vivo/in vivo population approach for screening of human genes involved in the human immunodeficiency virus type 1 life cycle for variants influencing disease progression.

Humans differ substantially with respect to susceptibility to human immunodeficiency virus type 1 (HIV-1). We evaluated variants of nine host genes participating in the viral life cycle for their role in modulating HIV-1 infection. Alleles were assessed ex vivo for their impact on viral replication in purified CD4 T cells from healthy blood donors (n = 128). Thereafter, candidate alleles were assessed in vivo in a cohort of HIV-1-infected individuals (n = 851) not receiving potent antiretroviral therapy. As a benchmark test, we tested 12 previously reported host genetic variants influencing HIV-1 infection as well as single nucleotide polymorphisms in the nine candidate genes. This led to the proposition of three alleles of PML, TSG101, and PPIA as potentially associated with differences in progression of HIV-1 disease. In a model considering the combined effects of new and previously reported gene variants, we estimated that their effect might be responsible for lengthening or shortening by up to 2.8 years the period from 500 CD4 T cells/mul to <200 CD4 T cells/mul.

Alleles↗
PubMed2004

A transmission disequilibrium test for general pedigrees that is robust to the presence of random genotyping errors and any number of untyped parents.

Two issues regarding the robustness of the original transmission disequilibrium test (TDT) developed by Spielman et al are: (i) missing parental genotype data and (ii) the presence of undetected genotype errors. While extensions of the TDT that are robust to items (i) and (ii) have been developed, there is to date no single TDT statistic that is robust to both for general pedigrees. We present here a likelihood method, the TDT(ae), which is robust to these issues in general pedigrees. The TDT(ae) assumes a more general disease model than the traditional TDT, which assumes a multiplicative inheritance model for genotypic relative risk. Our model is based on Weinberg's work. To assess robustness, we perform simulations. Also, we apply our method to two data sets from actual diseases: psoriasis and sitosterolemia. Maximization under alternative and null hypotheses is performed using Powell's method. Results of our simulations indicate that our method maintains correct type I error rates at the 1, 5, and 10% levels of significance. Furthermore, a Kolmorogov-Smirnoff Goodness of Fit test suggests that the data are drawn from a central chi2 with 2 df, the correct asymptotic null distribution. The psoriasis results suggest two loci as being significantly linked to the disease, even in the presence of genotyping errors and missing data, and the sitosterolemia results show a P-value of 1.5 x 10(-9) for the marker locus nearest to the sitosterolemia disease genes. We have developed software to perform TDT(ae) calculations, which may be accessed from our ftp site.

Computer Simulation↗
PubMed2003

Statistical significance for hierarchical clustering in genetic association and microarray expression studies.

BACKGROUND: With the increasing amount of data generated in molecular genetics laboratories, it is often difficult to make sense of results because of the vast number of different outcomes or variables studied. Examples include expression levels for large numbers of genes and haplotypes at large numbers of loci. It is then natural to group observations into smaller numbers of classes that allow for an easier overview and interpretation of the data. This grouping is often carried out in multiple steps with the aid of hierarchical cluster analysis, each step leading to a smaller number of classes by combining similar observations or classes. At each step, either implicitly or explicitly, researchers tend to interpret results and eventually focus on that set of classes providing the "best" (most significant) result. While this approach makes sense, the overall statistical significance of the experiment must include the clustering process, which modifies the grouping structure of the data and often removes variation. RESULTS: For hierarchically clustered data, we propose considering the strongest result or, equivalently, the smallest p-value as the experiment-wise statistic of interest and evaluating its significance level for a global assessment of statistical significance. We apply our approach to datasets from haplotype association and microarray expression studies where hierarchical clustering has been used. CONCLUSION: In all of the cases we examine, we find that relying on one set of classes in the course of clustering leads to significance levels that are too small when compared with the significance level associated with an overall statistic that incorporates the process of clustering. In other words, relying on one step of clustering may furnish a formally significant result while the overall experiment is not significant.

Cluster Analysis↗
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↗