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D R Goldstein

Publications and source records attributed to D R Goldstein.

24 records · Page 2Linked to original sources
PubMed1995

Asymptotic distributions of polylocus test statistics.

Polylocus linkage analysis methods are modified two-point analyses which aim to approach the information gain of multilocus analysis. Terwilliger and Ott [(1992) Am J Hum Genet 51:A202, (1993) Genet Epidemiol 10:477-482] put forth two such methods. This paper presents asymptotic approximations to the null distribution of the likelihood ratio statistics for these two methods, correcting earlier reports [Terwilliger and Ott (1993) Genet Epidemiol 10:477-482; Schaid and Elston (1994) Genet Epidemiol 11:1-17]. The performance of the approximations is then assessed for finite samples of fully informative meioses.

Chromosome Mapping↗
PubMed1995

Overexpression of protein kinase C beta 1 in the SW480 colon cancer cell line causes growth suppression.

Using a retroviral vector system we have established derivatives of the E8 subclone of the human colon cancer cell line SW480 that stably overproduce a full-length rat cDNA encoding the beta 1 isoform of protein kinase C (PKC beta 1). In contrast to vectrol control cells, when treated with the tumor promoter 12-O-tetradecanoyl phorbol-13-acetate (TPA), the overexpressing cell lines displayed a striking increase in doubling time, and a decrease in saturation density. Western blot analysis indicated that treatment with TPA was also associated with translocation and partial downregulation of the exogenous PKC beta 1 in the over-expressor cell lines. These results extend previous evidence that PKC beta 1 can inhibit the growth of the HT29 human colon cancer cell line. The HT29 cells have a normal c-k-ras oncogene but the SW480 cells used in the present study have an activating mutation in this oncogene. Thus PKC beta 1 can function as a suppressor in both types of colon cancer cells.

Animals↗
PubMed1994

A combined test of linkage heterogeneity.

This paper focuses on the problem of testing for heterogeneity once linkage is established. In an investigation of genetic linkage, Morton first proposed a general purpose test to detect heterogeneity in the recombination fraction. Two more commonly used tests of linkage heterogeneity are the admixture test (A-test) of Smith, Ott, and Risch and Baron, and the B-test of Risch. All are likelihood-ratio tests, but they differ in the models specifying the heterogeneity. A new test of heterogeneity in the presence of linkage is presented here. I propose a mixture model of heterogeneity, which allows the recombination fraction to vary among families, as does the B-model, yet also allows some families to be unlinked, as the A-model does. This model contains the A and B models as special cases and thus allows a direct test (D-test), which can provide justification for choosing one of these extremes.

Family↗
PubMedDate not supplied

A familial risk profile for osteoporosis.

PURPOSE: To describe genetic epidemiologic aspects of osteoporosis. METHODS: 69 patients with osteoporosis were interviewed regarding personal and family histories of osteoporosis and related fractures. Family history information was obtained on 421 first degree and 748 second degree relatives. RESULTS: 45% of cases reported a family history of osteoporosis. Familial cases were characterized neither by an earlier age of diagnosis nor by a greater degree of phenotypic severity. Empiric risks for osteoporosis were highest for mothers, 33%, and were 19% for sisters. CONCLUSION: These results provide an initial genetic epidemiologic profile for osteoporosis and information useful for genetic counseling.

Adult↗
PubMedDate not supplied

The effects of genotyping errors and interference on estimation of genetic distance.

Analysis of linkage data has typically been carried out assuming genotyping errors are absent. Recent studies have shown, however, that the impact of ignoring genotyping errors can be great, especially in dense marker maps [Buetow, Am J Hum Genet 1991; 49:985-994; Lincoln and Lander, Genomics 1992; 14:604-610]. Because most organisms exhibit positive chiasma interference, we use the chi 2 model [Foss et al., Genetics 1993; 144:681-691] to examine the role interference plays in the estimation of genetic distance in the presence of genotyping errors. For simplicity, we confine our analyses to samples of 1,000 fully informative gametes. Our results support previous findings that ignoring errors inflates distance estimates. The larger the error rate, the greater the inflation. For a given error rate, the relative error in estimated genetic distance is greatest when interference is known to be weak or absent. An approximation to relative error which quantifies the relation to distance, error rate, and interference is provided. Robustness of estimation to error misspecification is also investigated. When the assumed error rate is too low, distance is overestimated while interference is underestimated. The situation is reversed when too large an error rate is assumed (interference is overestimated, and distance underestimated). Unfortunately, the joint estimation of distance and interference is not very robust to error misspecification.

Genetic Linkage↗