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J M Kwon

Publications and source records attributed to J M Kwon.

20 records · Page 2Linked to original sources

Genetic analysis of kifafa, a complex familial seizure disorder.

Kifafa is the Swahili name for an epileptic seizure disorder, first reported in the early 1960s, that is prevalent in the Wapogoro tribe of the Mahenge region of Tanzania in eastern Africa. A 1990 epidemiological survey of seizure disorders in this region reported a prevalence in the range of 19/1,000-36/1,000, with a mean age at onset of 11.6 years; 80% of those affected had onset prior to 20 years of age. A team of investigators returned to Tanzania in 1992 and collected data on > 1,600 relatives of 26 probands in 20 kifafa families. We have undertaken a genetic analysis of these data in order to detect the presence of familial clustering and whether such aggregation could be attributed to genetic factors. Of the 127 affected individuals in these pedigrees, 23 are first-degree relatives (parent, full sibling, or offspring) of the 26 probands; 20 are second-degree relatives (half-sibling, grandparent, uncle, or aunt). When corrected for age, the risk to first-degree relatives is .15; the risk to second-degree relatives is .063. These risks are significantly higher than would be expected if there were no familial clustering. Segregation analysis, using PAP (rev.4.0), was undertaken to clarify the mode of inheritance. Among the Mendelian single-locus models, an additive model was favored over either a dominant, recessive, or codominant model. The single-locus model could be rejected when compared with the mixed Mendelian model (inclusion of a polygenic background), although the major-gene component tends to be recessive.(ABSTRACT TRUNCATED AT 250 WORDS)

Adolescent↗

Commingling and segregation analyses: comparison of results from a simulation study of a quantitative trait.

Commingling analysis is commonly used to provide preliminary evidence for a single genetic locus with a major effect on the quantitative trait of interest. In this paper, the effectiveness of commingling analysis as a screening technique to identify samples for segregation analysis is assessed by applying both commingling and segregation analyses to samples of simulated pedigree data in which a major locus is segregating in the presence of polygenes and an individual-specific environmental effect. Under the circumstances simulated here, there is evidence for a single locus from segregation analysis but not from commingling analysis in at least 20% of the samples. No more than 2% of the samples provided evidence for commingling but not for segregation of a single locus. Comparisons of the samples that give evidence for both commingling and segregation, evidence for one but not the other, and no evidence for either show that evidence for commingling depends on the distributional characteristics of the trait in the sample, while support for the single locus from segregation analysis depends on both the distributional characteristics as well as the transmission of the rarer allele from parents to offspring. Since lack of commingling does not rule out the existence of a single locus in the realistic situations considered here, commingling analysis has limited usefulness as a screening technique for the presence for a single locus. In contrast, evidence for commingling does suggest the possibility that a single locus has a major effect on the trait and commingling analysis can provide guidance in the choice of initial parameter estimates for segregation analysis.

Chi-Square Distribution↗