Optimal selection of sib pairs from random samples for linkage analysis of a QTL using the EDAC test

Percentages of extremely concordant and extremely discordant sib pairs are calculated that maximize the power to detect a quantitative trait locus (QTL) under a variety of circumstances using the EDAC test. We assume a large fixed number of randomly sampled sib pairs, such as one would hope to find in the large twin registries, and limited resources to genotype a certain number of selected sib pairs. Our aim is to investigate whether optimal selection can be achieved when prior knowledge concerning the QTL gene action, QTL allele frequency, QTL effect size, and background (residual) sib correlation is limited or absent. To this end we calculate the best selection percentages for a large number of models, which differ in QTL gene action allele frequency, background correlation, and QTL effect size. By averaging these percentages over gene action, over allele frequency, over gene action, and over allele frequencies, we arrive at general recommendations concerning selection percentages. The soundness of these recommendations is subsequently in a number of test cases

A comparison of early and late respondents in a twin-family survey study.

Differences between early (within 30 days) and late (after 30 days) respondents in a survey study were analyzed in twins and siblings registered with the Netherlands Twin Register. We compared early and late respondents on personality traits, health, lifestyle, and demographic variables. The odds of being a late respondent were significantly higher for men (OR 1.14), alcohol use on a daily/weekly basis (OR 1.20), having a relationship (OR 1.40), higher score on experience seeking scale (OR 1.02), and criticizing the questionnaire as too long (OR 1.27). The odds of being a late respondent were significantly lower for nontwin subjects (OR 0.71), regular cycling (OR 0.83), and judging the questionnaire to be fun (OR 0.80). There were no significant interactions with sex. To examine to what extent early and late response is influenced by genetic factors, twin and sibling data of 5040 subjects were analyzed. The best model includes genetic factors (31%), shared environmental influences (36%), and unique environmental influences (43%) on variation in response time

Religious upbringing and neuroticism in Dutch twin families.

Evidence for a relation between neuroticism and religion is scarce and inconsistent. The aims of the present study were to determine the association of religious upbringing with adult neuroticism scores and to examine the effect of religious upbringing on the heritability of neuroticism. As part of a longitudinal survey of twin families from the Netherlands Twin Register, data were collected on neuroticism and religious upbringing. Restricting the sample to persons aged 25 and over resulted in a sample of 4369 twins and 1304 siblings from 2698 families. Religious upbringing was significantly associated with neuroticism; in both men and women neuroticism levels were lower in those who had received a religious upbringing. There were no sex or twin-sibling differences in neuroticism variances and covariances. Structural equation modeling showed differences in heritability between those with and without religious upbringing. In the group with religious upbringing, variation in neuroticism was determined for 41 % by additive genetic factors and for the remaining 59% by unique environmental factors. In the group who had not received a religious upbringing, variation in neuroticism was determined for 55% by genetic factors, with evidence for both additive and nonadditive factors, and for the remaining 45% by unique environmental influences. In conclusion, having received a religious upbringing is associated with lower neuroticism scores and a lower heritability in adulthood

The genetic analysis of repeated measures I. Simplex models

The well-known simplex model is extended to a model that may be used for the genetic and environmental analysis of covariance structures. This "double " simplex structure can be specified as a LISREL model. It is shown that data which give rise to a simplex correlation structure, such as repeated-measures data, do not fit a factor-analysis model. The parameter estimation of the simplex model is illustrated with computersimulated twin data. KEY WORDS: repeated measures; longitudinal data; simplex models; genetic correlations; environmental correlations; twin data; LISREL

A comparison of power to detect a QTL in sib-pair data using multivariate phenotypes, mean phenotypes, and factor scores

In linkage analysis of non-Mendelian, complex, traits the detection of loci that explain a small to medium amount of the genetic variance remain

The genetic analysis of repeated measures II. The Karhunen-Loève expansion

A new approach to the genetic analysis of time series of arbitrary length and with arbitrary covariance function is outlined. This approach is based on the simultaneous eigenvalue decomposition of the covariance matrices of the original time series obtained from monozygotic (MZ) and dizygotic (DZ) twins. The method is illustrated with computer-simulated twin data. © 1987 Plenum Publishing Corporation