Approximate confidence intervals for heritability from method R estimates

Method R estimates of heritability (h2) and associated confidence intervals (CI) were obtained from simulated data using a single trait, direct effects, full animal model, with 50% subsampling. Five hundred data sets were simulated for each of five levels of h2 (.10, .20, .30, .40, and .50) and two types of pedigree structure (random pedigree structure [N = 2,000] that varied over simulations, or the pedigree structure from a real data set [N = 2,644] that was constant for all simulations). The first 10, 20, and all 50 h2 estimates were used to obtain 80, 90, 95, and 99% CI for each data set. The variance of h2 estimates within data sets approximated the sampling variance of the h2 estimates. The Box-Cox transformation was used to normalize the distribution of estimates from each data set. Confidence intervals were computed on the transformed scale as CI = mu +/- (T x sigma), where mu and sigma = the mean and SD of the N transformed h2 estimates, respectively, and T = the critical value from the T distribution for a 1-alpha CI, with df = N-1. Upper and lower CI bounds were converted back to the original scale by reversing the transformation. The percentages of CI containing the true h2 value, pooled across all levels of h2, types of pedigree, and number of estimates used to obtain CI, for 80, 90, 95, and 99% CI were 81.14, 90.96, 95.27, and 98.76%, respectively. These results suggested that Method R h2 estimates can be used to obtain reliable CI.

A critical discussion of intraclass correlation coefficients

In general, intraclass correlation coefficients (ICC's) are designed to assess consistency or conformity between two or more quantitative measurements. They are claimed to handle a wide range of problems, including questions of reliability, reproducibility and validity. It is shown that care must be taken in choosing a suitable ICC with respect to the underlying sampling theory. For this purpose a decision tree is developed. It may be used to choose a coefficient which is appropriate for a specific study setting. We demonstrate that different ICC's may result in quite different values for the same data set, even under the same sampling theory. Other general limitations of ICC's are also addressed. Potential alternatives are presented and discussed, and some recommendations are given for the use of an appropriate method.

Scope and strategies of genetic epidemiology: analysis of articles published in Genetic Epidemiology, 1984-1991

Genetic epidemiology is a relatively new discipline that seeks to unravel the role of genetic factors and their interactions with environmental factors in the etiology of diseases, using population and family study approaches. To characterize the overall direction and emphasis of research strategies used in this field, we reviewed original research articles published in the journal Genetic Epidemiology since its inception in 1984 until the end of 1991. Of 259 published original articles, 92 (35%) focused primarily on methodologic/statistical developments, most commonly in the area of linkage analysis/gene mapping, and 167 (65%) articles were applied or data-derived. Only 42 articles (16%) were population studies, and 217 (84%) were family studies. Most family studies dealt with genetic analysis of pedigree data using segregation and linkage analyses. Of the 137 applied family studies, 73 (53%) were drawn from well-defined populations, and only 40 (29%) considered specific environmental factors in their analyses. These findings clearly indicate a rapid growth in the methodologic and statistical aspects of genetic epidemiology, and in the emphasis on family-based studies and genetic analysis methods. Further developments in genetic epidemiology will require greater integration of epidemiologic approaches of study design and analyses into population and family studies of disease etiology.

[A computerized follow up system of obstetric and genetic care]

The authors have implemented and introduced a new filing system representing the complexity of obstetric, genetic and neonatal care for the three counties of the Eastern part of Hungary. Data about the pre-, peri- and postnatal management are supplied by the genetic/teratologic, obstetric, neonatal and pathological units and processed at the Department of Obstetrics and Gynaecology, University Medical School of Debrecen with an IBM compatible AT computer. This computerised registry is based on the personal identification number, so it is easy to handle for storing data about the course and outcome of a large number of pregnancies as well as the detection and follow-up of fetal malformations and genetic diseases. The computer register is suitable for easy and systematic storage of the more than 20 thousand pregnancies screened by both maternal serum AFP and ultrasound including nearly 500 prenatal diagnosis cases per year. When devising the system, the classic parameters of the "revised Tauffer statistics" have been taken into consideration, but the emphasis has been put mostly on the assessment of fetal/infantile health status and the prevention of malformations and genetic diseases. This computerised system greatly facilitates the correct assessment of statistical parameters in related medical fields and provides better possibilities for studying the cause and effect relationship between the efficacy of medical care and perinatal events.(ABSTRACT TRUNCATED AT 250 WORDS)