Search PubMed⌕ Search

Biomedical subjects

J D Terwilliger

Publications and source records attributed to J D Terwilliger.

At least 19 recordsLinked to original sources
PubMed2001

Genome-wide scan in a nationwide study sample of schizophrenia families in Finland reveals susceptibility loci on chromosomes 2q and 5q.

We have previously carried out two genome-wide scans in samples of Finns ascertained for schizophrenia from national epidemiological registers. Here, we report data from a third genome scan in a nationwide Finnish schizophrenia study sample of 238 pedigrees with 591 affected individuals. Of the 238 pedigrees, 53 originated from a small internal isolate (IS) on the eastern border of Finland with a well established genealogical history and a small number of founders, who settled in the community 300 years ago. The total study sample of over 1200 individuals were genotyped, using 315 markers. In addition to the previously identified chromosome 1 locus, two new loci were identified on chromosomes 2q and 5q. The highest LOD scores were found in the IS families with marker D2S427 (Z(max) = 4.43) and in the families originating from the late settlement region with marker D5S414 (Z(max) = 3.56). In addition to 1q, 2q and 5q, some evidence for linkage emerged at 4q, 9q and Xp, the regions also suggested by our previous genome scans, whereas, in the nationwide study sample, the region at 7q failed to show further evidence of linkage. The chromosome 5q finding is of particular interest, since several other studies have also shown evidence for linkage in the vicinity of this locus.

Chromosomes, Human, Pair 1↗
PubMed2001

Large upward bias in estimation of locus-specific effects from genomewide scans.

The primary goal of a genomewide scan is to estimate the genomic locations of genes influencing a trait of interest. It is sometimes said that a secondary goal is to estimate the phenotypic effects of each identified locus. Here, it is shown that these two objectives cannot be met reliably by use of a single data set of a currently realistic size. Simulation and analytical results, based on variance-components linkage analysis as an example, demonstrate that estimates of locus-specific effect size at genomewide LOD score peaks tend to be grossly inflated and can even be virtually independent of the true effect size, even for studies on large samples when the true effect size is small. However, the bias diminishes asymptotically. The explanation for the bias is that the LOD score is a function of the locus-specific effect-size estimate, such that there is a high correlation between the observed statistical significance and the effect-size estimate. When the LOD score is maximized over the many pointwise tests being conducted throughout the genome, the locus-specific effect-size estimate is therefore effectively maximized as well. We argue that attempts at bias correction give unsatisfactory results, and that pointwise estimation in an independent data set may be the only way of obtaining reliable estimates of locus-specific effect-and then only if one does not condition on statistical significance being obtained. We further show that the same factors causing this bias are responsible for frequent failures to replicate initial claims of linkage or association for complex traits, even when the initial localization is, in fact, correct. The findings of this study have wide-ranging implications, as they apply to all statistical methods of gene localization. It is hoped that, by keeping this bias in mind, we will more realistically interpret and extrapolate from the results of genomewide scans.

Bias↗
PubMed2001

A follow-up linkage study supports evidence for a bipolar affective disorder locus on chromosome 21q22.

Evidence for linkage between bipolar affective disorder (BP) and 21q22 was first reported by our group in a single large pedigree with a lod score of 3.41 with the PFKL locus. In a subsequent study, with denser marker coverage in 40 multiplex BP pedigrees, we reported supporting evidence with a two-point lod score of 2.76 at the D21S1260 locus, about 6 cM proximal to PFKL. For cost-efficiency, the individuals genotyped in that study comprised a subset of our large pedigree sample. To augment our previous analysis, we now report a follow-up study including a larger sample set with an additional 331 typed individuals from the original 40 families, improved marker coverage, and an additional 16 pedigrees. The analysis of all 56 pedigrees (a total of 862 genotyped individuals vs. the 372 genotyped previously), the largest multigenerational BP pedigree sample reportedly analyzed to date, supports our previous results, with a two-point lod score of 3.56 with D21S1260. The 16 new pedigrees analyzed separately gave a maximum two-point lod score of 1.89 at D21S266, less than 1 cM proximal to D21S1260. Our results are consistent with a putative BP locus on 21q22.

Bipolar Disorder↗
PubMed2001

Roles of growth hormone and insulin-like growth factor 1 in mouse postnatal growth.

To examine the relationship between growth hormone (GH) and insulin-like growth factor 1 (IGF1) in controlling postnatal growth, we performed a comparative analysis of dwarfing phenotypes manifested in mouse mutants lacking GH receptor, IGF1, or both. This genetic study has provided conclusive evidence demonstrating that GH and IGF1 promote postnatal growth by both independent and common functions, as the growth retardation of double Ghr/Igf1 nullizygotes is more severe than that observed with either class of single mutant. In fact, the body weight of these double-mutant mice is only approximately 17% of normal and, in absolute magnitude ( approximately 5 g), only twice that of the smallest known mammal. Thus, the growth control pathway in which the components of the GH/IGF1 signaling systems participate constitutes the major determinant of body size. To complement this conclusion mainly based on extensive growth curve analyses, we also present details concerning the involvement of the GH/IGF1 axis in linear growth derived by a developmental study of long bone ossification in the mutants.

Animals↗
PubMed2001

GAW12: simulated genome scan, sequence, and family data for a common disease.

The Genetic Analysis Workshop (GAW) 12 simulated data involves a common disease defined by imposing a threshold on a quantitative liability distribution. Associated with the disease are five quantitative risk factors, a quantitative environmental exposure, and a dichotomous environmental variable. Age at disease onset and household membership were also simulated. Genotype data, including 2,855 microsatellites on 22 autosomes, were simulated for 1,497 individuals in 23 families. Phenotype data and sequence data for seven candidate genes were provided for 1,000 of these individuals who were "living" and available for study. Data were simulated for 50 replicate samples in each of two populations, a general population and a population isolate formed from a small group of founders.

Adolescent↗
PubMed2001

Cystathionine beta-synthase deficiency in Central Europe: discrepancy between biochemical and molecular genetic screening for homocystinuric alleles.

Recent reports suggested that homocystinuria due to cystathionine beta-synthase (CBS) deficiency is a more common inborn error of metabolism than originally thought. In this study we compared the prevalence of homocystinuric alleles ascertained by two different approaches. First, the incidence of homocystinuria estimated by selective biochemical screening in the Czech and Slovak Republics was 1:349,000 (95% CI 1:208,000-1:641,000). The two most common pathogenic mutant alleles found subsequently in these patients, IVS11-2A>C and c.833T>C, had a calculated population prevalence of 0.00042 (95% CI 0.00031-0.00055) and 0.00018 (95% CI 0.00013-0.00023), respectively. Second, to examine the possible negative detection bias of mildly affected patients we determined the prevalence of these two pathogenic mutations in a sample of 1284 unselected newborns. Indeed, the observed prevalence of the c.833T>C allele (0.00195, 95% CI 0.00063-0.00454) was 11x higher than in the previous group suggesting that many homozygotes for the c.833T>C had not been diagnosed by selective biochemical screening. The IVS11-2A>C allele was not detected among 2,568 newborn CBS alleles. The estimated incidence of homocystinuria of 1:83,000, calculated in a combined model, suggests that selective biochemical screening may ascertain only approximately 25% of all homocystinuric patients. In conclusion, homocystinuria in Central Europe may be sufficiently common to consider sensitive newborn screening programs for this disease.

Alleles↗
PubMed2001

On the resolution and feasibility of genome scanning approaches.

Before contemplating a genome scan to identify the map position of disease-predisposing genes, an investigator should have prior evidence of the genes' existence. It is therefore logically consistent to evaluate a genome scan experiment as an estimation problem, rather than as a hypothesis-testing problem, since absent prior evidence of the existence of disease genes, it is probably unwise to conduct the experiment at all. Recombination in a single meiosis can be modeled as a point process along the chromosome, and linkage or linkage disequilibrium (LD) mapping statistics are a simple function of the superposition of the recombination processes occurring in all meioses under study. Thus, multipoint lod scores are shown to be step functions, in the absence of ambiguity about the inheritance of chromosomal segments. The ability to map a disease gene is a function of how well the ascertained phenotypes predict the underlying trait locus genotypes. This chapter presents a thorough investigation of the properties of the multipoint lod score and uses results from renewal theory to examine the effects of deviations from a deterministic phenotype-genotype relationship. The quality of estimated gene locations is assessed through computing the mean and variance of the length of the expected 3-lod-unit support interval around the maximum likelihood estimate. The more deterministic the model, the smaller this interval is. A more exact quantification of details of this effect is used to describe the statistical properties of such genome scanning experiments from the perspective of estimation, with appropriately little regard to hypothesis testing. Hypothesis testing, however, is discussed as an appropriate context to describe linkage and LD analysis in situations where candidate genes are being screened, since only there does one have definable null and alternative hypotheses that have not been rejected before the beginning of the experiment. By contrast, it is hoped that the null hypothesis "there is no gene affecting this phenotype" has been rejected by other means before an expensive genome scan is even contemplated (though that this is often not done is probably the main problem!).

Chromosome Mapping↗
PubMed2000

Fine mapping of the SLEB2 locus involved in susceptibility to systemic lupus erythematosus.

We have previously reported linkage of systemic lupus erythematosus to chromosome 2q37 in multicase families from Iceland and Sweden. This locus (SLEB2) was identified by linkage to the markers D2S125 and D2S140. In the present study we have analyzed additional microsatellite markers and SNPs covering a region of 30 cM around D2S125 in an extended set of Nordic families (Icelandic, Swedish, and Norwegian). Two-point linkage analysis in these families gave a maximum lod score at the position of markers D2S2585 and D2S2985 (Z = 4.51, PIC = 0.65), by applying a "model-free" pseudo-marker linkage analysis. Based on multipoint linkage analysis in the Nordic families, the most likely location of the SLEB2 locus is estimated to be in the interval between D2S125 and the position of markers D2S2585 and D2S2985, with a peak multipoint lod score of Z = 6.03, assuming a dominant pseudo-marker model. Linkage disequilibrium (LD) analysis was performed using the data from the multicase families and 89 single-case families of Swedish origin, using the same set of markers. The LD analysis showed evidence for association in the single-case and multicase families with locus GAAT3C11 (P < 0.0003), and weak evidence for association was obtained for several markers located telomeric to D2S125 in the multicase families. Thirteen Mexican families were analyzed separately and found not to have linkage to this region. Our results support the presence of the SLEB2 locus at 2q37.

Base Sequence↗
PubMed2000

Two loci on chromosomes 2 and X for premature coronary heart disease identified in early- and late-settlement populations of Finland.

Coronary heart disease (CHD) is a complex disorder constituting a major health problem in Western societies. To assess the genetic background of CHD, we performed a genomewide linkage scan in two study samples from the genetically isolated population of Finland. An initial study sample consisted of family material from the northeastern part of Finland, settled by a small number of founders approximately 300 years ago. A second study sample originated from the southwestern region of Finland, settled approximately 2,000 years ago. Families were ascertained through probands exhibiting premature CHD, defined as >50% stenosis of at least two coronary arteries at a young age, as verified by coronary angiography. Both study samples and the pooled data set provided evidence for linkage in two chromosomal regions. A region on chromosome 2q21.1-22 yielded two-point LOD scores of 3.2, 1.9, and 3.7, in the affected sib-pair (ASP) analyses of the northeastern, southwestern, and pooled study samples. The corresponding multipoint maximum-likelihood scores (MLSs) for these three study samples were 2.4, 1.3, and 3.0. In addition, a region on chromosome Xq23-26 resulted in two-point LOD scores of 1.9, 3.5, and 2.9 and in multipoint MLSs of 3.4, 3.1, and 2.5, respectively. In conclusion, this study identifies two loci likely to contribute to premature CHD: one on chromosome 2q21.1-22 and another on chromosome Xq23-26.

Age of Onset↗
PubMed2000

A genome scan in families from Australia and New Zealand confirms the presence of a maternal susceptibility locus for pre-eclampsia, on chromosome 2.

Epidemiological studies have shown that genetic factors contribute to the etiology of the common and serious pregnancy-specific disorder pre-eclampsia (PE)/eclampsia (E). Candidate-gene studies have provided evidence (albeit controversial) of linkage to several genes, including angiotensinogen on 1q42-43 and eNOS on 7q36. A recent medium-density genome scan in Icelandic families identified significant linkage to D2S286 (at 94.05 cM) on chromosome 2p12 and suggestive linkage to D2S321 (at 157.5 cM) on chromosome 2q23. In the present article, the authors report the results of a medium-density genome scan in 34 families, representing 121 affected women, from Australia and New Zealand. Multipoint nonparametric linkage analysis, using the GENEHUNTER-PLUS program, showed suggestive evidence of linkage to chromosome 2 (LOD=2.58), at 144.7 cM, between D2S112 and D2S151, and to chromosome 11q23-24, between D11S925 and D11S4151 (LOD=2.02 at 121.3 cM). Given the limited precision of estimates of the map location of disease-predisposing loci for complex traits, the present finding on chromosome 2 is consistent with the finding from the Icelandic study, and it may represent evidence of the same locus segregating in the population from Australia and New Zealand. The authors propose that the PE/E-linked locus on chromosome 2p should be designated the "PREG1" (pre-eclampsia, eclampsia gene 1) locus.

Australia↗
PubMed2000

Genome-wide scan for schizophrenia in the Finnish population: evidence for a locus on chromosome 7q22.

We report the results of a four-stage genome-wide scan in a schizophrenia study sample consisting of 134 affected sib-pairs collected in Finland. In stage I we genotyped 370 markers from the Weber 6 screening set ( N = 52 affected sib-pairs); in stage II we followed up 40 markers by typing first-degree relatives of the sib-pairs; in stage III we genotyped 15 markers in 134 families; and in stage IV we genotyped a denser marker map in the two most promising regions, one on chromosome 1 and another on chromosome 7, in all families. Diagnoses were based on three nationwide health care registers and consensus diagnosis based on review of all medical records. The most significant finding was a two-point lod score of 3.18 with marker D7S486 using a dominant model and treating all individuals with either schizophrenia, schizoaffective disorder or other schizophrenia spectrum disorder as affected. Multipoint analysis with MAPMAKER/SIBS resulted in a MLS of 3.53 between markers D7S501 and D7S523 using the broadest diagnostic model, including major depressive disorder and bipolar type I as affecteds in addition to the aforementioned phenotypes. These results were obtained by including in the analyses only individuals from the late settlement region of Finland settled in the 16th century. Additionally, some support was obtained for linkage to chromosome 1, in a region previously identified in a genome-wide scan of a study sample from a sub-isolate of Finland. Our data demonstrate the importance of genealogical information for studies aiming at identification of predisposing loci in complex diseases.

Adult↗
PubMed2000

Linkage analysis in the presence of errors IV: joint pseudomarker analysis of linkage and/or linkage disequilibrium on a mixture of pedigrees and singletons when the mode of inheritance cannot be accurately specified.

There is a lot of confusion in the literature about the "differences" between "model-based" and "model-free" methods and about which approach is better suited for detection of the genes predisposing to complex multifactorial phenotypes. By starting from first principles, we demonstrate that the differences between the two approaches have more to do with study design than statistical analysis. When simple data structures are repeatedly ascertained, no assumptions about the genotype-phenotype relationship need to be made for the analysis to be powerful, since simple data structures admit only a small number of df. When more complicated and/or heterogeneous data structures are ascertained, however, the number of df in the underlying probability model is too large to have a powerful, truly "model-free" test. So-called "model-free" methods typically simplify the underlying probability model by implicitly assuming that, in some sense, all meioses connecting two affected individuals are informative for linkage with identical probability and that the affected individuals in a pedigree share as many disease-predisposing alleles as possible. By contrast, "model-based" methods add structure to the underlying parameter space by making assumptions about the genotype-phenotype relationship, making it possible to probabilistically assign disease-locus genotypes to all individuals in the data set on the basis of the observed phenotypes. In this study, we demonstrate the equivalence of these two approaches in a variety of situations and exploit this equivalence to develop more powerful and efficient likelihood-based analogues of "model-free" tests of linkage and/or linkage disequilibrium. Through the use of a "pseudomarker" locus to structure the space of observations, sib-pairs, triads, and singletons can be analyzed jointly, which will lead to tests that are more well-behaved, efficient, and powerful than traditional "model-free" tests such as the affected sib-pair, transmission/disequilibrium, haplotype relative risk, and case-control tests. Also described is an extension of this approach to large pedigrees, which, in practice, is equivalent to affected relative-pair analysis. The proposed methods are equally applicable to two-point and multipoint analysis (using complex-valued recombination fractions).

Case-Control Studies↗
PubMed2000

Linkage analysis in the presence of errors III: marker loci and their map as nuisance parameters.

In linkage and linkage disequilibrium (LD) analysis of complex multifactorial phenotypes, various types of errors can greatly reduce the chance of successful gene localization. The power of such studies-even in the absence of errors-is quite low, and, accordingly, their robustness to errors can be poor, especially in multipoint analysis. For this reason, it is important to deal with the ramifications of errors up front, as part of the analytical strategy. In this study, errors in the characterization of marker-locus parameters-including allele frequencies, haplotype frequencies (i.e., LD between marker loci), recombination fractions, and locus order-are dealt with through the use of profile likelihoods maximized over such nuisance parameters. It is shown that the common practice of assuming fixed, erroneous values for such parameters can reduce the power and/or increase the probability of obtaining false positive results in a study. The effects of errors in assumed parameter values are generally more severe when a larger number of less informative marker loci, like the highly-touted single nucleotide polymorphisms (SNPs), are analyzed jointly than when fewer but more informative marker loci, such as microsatellites, are used. Rather than fixing inaccurate values for these parameters a priori, we propose to treat them as nuisance parameters through the use of profile likelihoods. It is demonstrated that the power of linkage and/or LD analysis can be increased through application of this technique in situations where parameter values cannot be specified with a high degree of certainty.

Alleles↗
PubMed2000

A susceptibility locus for human systemic lupus erythematosus (hSLE1) on chromosome 2q.

To identify chromosomal regions containing susceptibility loci for systemic lupus erythematosus (SLE), we performed genome scans in families with multiple SLE patients from Iceland, a geographical and genetic isolate, and from Sweden. A number of chromosomal regions showed maximum lod scores (Z) indicating possible linkage to SLE in both the Icelandic and Swedish families. In the Icelandic families, five regions showed lod scores greater than 2.0, three of which (4p15-13, Z=3.20; 9p22, Z=2.27; 19q13, Z=2.06) are homologous to the murine regions containing the lmb2, sle2 and sle3 loci, respectively. The fourth region is located on 19p13 (D19S247, Z=2.58) and the fifth on 2q37 (D2S125, Z=2.06). Only two regions showed lod scores above 2.0 in the Swedish families: on chromosome 2q11 (D2S436, Z=2. 13) and 2q37 (D2S125, Z=2.18). The combination of both family sets gave a highly significant lod score at D2S125 of Z=4.24 in favor of linkage for 2q37. This region represents a new locus for SLE. Our results underscore the importance of studying well-defined populations for genetic analysis of complex diseases such as SLE.

Animals↗
PubMed2000

A likelihood-based extended admixture model of oligogenic inheritance in 'model-based' and 'model-free' analysis.

The admixture test of linkage heterogeneity is the most often and most successfully applied oligogenic-model linkage and/or LD analysis method. Full two-locus model linkage analysis is possible, but can be computationally intensive and difficult to interpret because of the need to specify so many indeterminate parameters. A novel, computationally efficient method is proposed for combining single locus lod scores which can allow for varying degrees of epistatic interaction. This method can be applied to two-point or multipoint (using complex-valued recombination fractions) linkage and/or linkage disequilibrium analysis to jointly test for multiple unlinked disease loci. Unlike the traditional admixture test, this algorithm permits joint analysis of multiple disease loci with different modes of inheritance for each, and can be applied to 'model-free' analysis as well through the use of 'pseudomarkers'. Software is available for computation of the various likelihood ratio tests described, for comparison of a variety of possible hypotheses regarding locus homogeneity, locus heterogeneity, and epistasis.

Algorithms↗
PubMed2000

Linkage disequilibrium in isolated populations: Finland and a young sub-population of Kuusamo.

Linkage disequilibrium (LD), non-random association of alleles at closely linked chromosomal loci, has been used as a tool in the identification of disease alleles, and this has led to an improved understanding of pathology in many monogenic Mendelian human diseases. We are currently moving from the mapping and identification of monogenic disease loci to attempts at identifying loci involved in predisposition to multifactorial diseases. In the selection of ascertainment strategies in the studies of these complex diseases, the extent of background LD in different populations is an important consideration. Here, we compare the extent of LD among the alleles of linked loci in a randomly ascertained sample of individuals from the Finnish population and a set of individuals ascertained from the region of Kuusamo, a small sub-population, founded some 13 generations ago, which has experienced very little subsequent immigration. Thirty-three microsatellite loci were genotyped in chromosomal regions on 13q, 19q, 21q, Xq, and Xp. The genetic diversity of these loci was determined separately in the general Finnish sample and in the Kuusamo sample. The X-chromosomal loci are characterised by higher levels of LD in the samples from Kuusamo than in the much larger (and older) general population of Finland, whereas in alleles of autosomal loci very little LD was seen in either of these two samples.

Alleles↗
PubMed2000

Linkage analysis in the presence of errors I: complex-valued recombination fractions and complex phenotypes.

Linkage is a phenomenon that correlates the genotypes of loci, rather than the phenotypes of one locus to the genotypes of another. It is therefore necessary to convert the observed trait phenotypes into trait-locus genotypes, which can then be analyzed for coinheritance with marker-locus genotypes. However, if the mode of inheritance of the trait is not known accurately, this conversion can often result in errors in the inferred trait-locus genotypes, which, in turn, can lead to the misclassification of the recombination status of meioses. As a result, the recombination fraction can be overestimated in two-point analysis, and false exclusions of the true trait locus can occur in multipoint analysis. We propose a method that increases the robustness of multipoint analysis to errors in the mode of inheritance assumptions of the trait, by explicitly allowing for misclassification of trait-locus genotypes. To this end, the definition of the recombination fraction is extended to the complex plane, as Theta=straight theta+straightepsiloni; theta is the recombination fraction between actual ("real") genotypes of marker and trait loci, and straightepsilon is the probability of apparent but false ("imaginary") recombinations between the actual and inferred trait-locus genotypes. "Complex" multipoint LOD scores are proven to be stochastically equivalent to conventional two-point LOD scores. The greater robustness to modeling errors normally associated with two-point analysis can thus be extended to multiple two-point analysis and multipoint analysis. The use of complex-valued recombination fractions also allows the stochastic equivalence of "model-based" and "model-free" methods to be extended to multipoint analysis.

Chromosome Mapping↗