Path analysis and sib-pair linkage

When the distance between linked loci is expressed in terms of the correlation between the identity-by-descent (idb) values of the loci, then a path model may be used to order loci with data on sib-pairs and their parents. The relationship between the recombination fraction and the correlation coefficient is developed and a method for fitting a covariance matrix predicted by a specific ordering of loci to an observed covariance matrix is proposed.

Identifying children in the Colorado Adoption Project at risk for conduct disorder

Clustering techniques were used to identify a subsample of young adopted and nonadopted children in the Colorado Adoption Project at risk for conduct disorder. Although data from both boys and girls were analyzed, a cluster of girls large enough for subsequent statistical analysis could not be identified; therefore, results are reported for boys only. Identifying measures were selected based on the DSM-III-R diagnostic criteria. Cluster analyses confirmed the existence of a small group of boys who appeared to be significantly at risk. Subsequent parental and teacher ratings of these children verified the stability over time of the classification. The poor conduct group was significantly associated with difficult temperament in infancy, with poor conduct on the part of parents when they were youths, and with high achievement orientation in the home environment.

Simulated twin data on substance abuse

Twin data were simulated for use of a new illegal substance. The twin cohort was "measured" yearly at 10 time intervals during the diffusion of the substance throughout the nation. The models used to generate the data are discussed.

Twin imitation for antisocial behavior: implications for genetic and family environment research

When twin pairs influence each other's behavior, observed variance is greater for MZ twins than for DZ twins under at least 1 of 2 conditions: (a) the trait has some heritability and (b) MZ twins influence each other more than do DZ twins. Applied to a trait that has an underlying continuous distribution but is measured as a dichotomy, the presence of reciprocal twin influence predicts that if the base rate for the trait is not exactly 50%, then the prevalence of the trait should differ in MZ and DZ twin pairs. This prediction held for registered criminality in a large twin cohort. Methods of analysis that permit reciprocal twin interaction not only provide better statistical fits to the data but also yield estimates of heritability that agree with adoption data. The results suggest that the genetic influence on registered criminality may be more modest than previously thought.

Twin imitation for antisocial behavior: Implications for genetic and family environment research

When twin pairs influence each other's behavior, observed variance is greater for MZ twins than for DZ twins under at least 1 of 2 conditions: (a) the trait has some heritability and (b) MZ twins influence each other more than do DZ twins. Applied to a trait that has an underlying continuous distribution but is measured as a dichotomy, the presence of reciprocal twin influence predicts that if the base rate for the trait is not exactly 50%, then the prevalence of the trait should differ in MZ and DZ twin pairs. This prediction held for registered criminality in a large twin cohort. Methods of analysis that permit reciprocal twin interaction not only provide better statistical fits to the data but also yield estimates of heritability that agree with adoption data. The results suggest that the genetic influence on registered criminality may be more modest than previously thought.

Parent-offspring and sibling adoption analyses of parental ratings of temperament in infancy and childhood

A first step toward understanding the etiology of personality is to investigate the relative impact of genetic and environmental factors using twin and adoption designs. Twin studies of infants and young children indicate substantial genetic influence for parental ratings of temperament in the preschool years. Adoption studies, however, have not previously been reported during the early years of life. We present parent-offspring comparisons for temperament (emotionality, activity, sociability, and impulsivity) for adopted and nonadopted children yearly from 1 to 7 years of age and their biological, adoptive, and nonadoptive parents. Also presented are correlations for adoptive and nonadoptive siblings when each child was 1, 2, 3, and 4 years of age. In contrast with twin results, little evidence is found for genetic influence. The average correlation between biological parents and their adopted-away children for data averaged over the 7 years is only .03. Similarly, the average parent-offspring correlation in nonadoptive families (.08) is no greater than in adoptive families (.12). Results for nonadoptive and adoptive siblings also indicate little genetic influence. The difference between the twin and adoption results may be due to environmental effects or to nonadditive genetic variance.

Codistribution of a sensory gating deficit and schizophrenia in multi-affected families

Because the clinical diagnosis of schizophrenia has not generally been an adequate phenotypic marker to detect the genes that convey risk for schizophrenia, efforts have been directed toward the identification of more elementary neuronal dysfunctions in schizophrenic patients and their families. Psychophysiological studies of sensory gating and selective attention suggest that defects in these brain functions are present in schizophrenic patients and some of their relatives. This study examines one of these defects in sensory gating, failure to suppress the P50 evoked response to repeated auditory stimuli. Six pedigrees, chosen because of the presence of large sibships containing several cases of schizophrenia, were studied. A mathematical model was developed to assess the familial association of the P50 defect with schizophrenia. The model preserves the quantitative nature of the data and is suitable for use in a sample with small numbers of pedigrees comprising many individuals. It is thus suitable for the evaluation of putative phenotypes in families to be studied by linkage analysis with polymorphic genetic markers. The results suggest that the P50 defect is familially associated with schizophrenia.

Linkage analysis of quantitative traits: increased power by using selected samples

Although a number of methods have been developed for linkage analysis of quantitative traits, power is relatively poor unless there is a single major locus of very large effect. Here it is demonstrated that the use of selected samples (i.e., ascertainment of a proband with an extreme score on the quantitative measure) can dramatically increase power, especially when proband selection is performed on the tail of a distribution with an infrequent recessive gene. Depending on gene action and allele frequency, selected samples permit detection of a major locus that accounts for as little as 10%-20% of the phenotypic variation. The judicious use of selected samples can make an appreciable difference in the feasibility of linkage studies for quantitative traits.

Evolution and path models in human behavioral genetics

The evolutionary implications of the path-analysis model most often used in human behavior genetics are examined. With directional selection, a model of pure vertical environmental transmission does not respond in a fully adaptive fashion. Unless the coefficients of transmission are exactly 0.50, the population mean will not equilibrate at the selective optimum over time. If there is both genetic and vertical environmental transmission, then the population mean can equilibrate at the selective optimum. In the presence of genetic transmission, vertical environmental transmission increases population fitness and has a strong effect on the rapid movement of the mean toward the selective optimum. This raises the intriguing paradox of why empirical evidence suggests that vertical environmental transmission is usually small when it possesses such important fitness properties.

The Ciba Corning ACS:180 benchtop immunoassay analyzer

We describe a new clinical laboratory instrument, the ACS:180, used to automate heterogeneous immunoassay testing. The ACS:180 automates immunoassays in which paramagnetic particles are the solid phase and changes in chemiluminescence are measured. The system can accommodate both competitive and sandwich-type assay configurations. The microprocessor-based instrument fully automates each step of the assay, including sample and reagent addition, separation and wash of paramagnetic particles, and generation and acquisition of the chemiluminescent signal. The instrument has the flexibility to operate in random-access or batch mode. The time from application of sample to first result is less than 15 min; throughput is as much as 180 tests per hour.

The Ciba Corning ACS:180 benchtop immunoassay analyzer

We describe a new clinical laboratory instrument, the ACS:180, used to automate heterogeneous immunoassay testing. The ACS:180 automates immunoassays in which paramagnetic particles are the solid phase and changes in chemiluminescence are measured. The system can accommodate both competitive and sandwich-type assay configurations. The microprocessor-based instrument fully automates each step of the assay, including sample and reagent addition, separation and wash of paramagnetic particles, and generation and acquisition of the chemiluminescent signal. The instrument has the flexibility to operate in random-access or batch mode. The time from application of sample to first result is less than 15 min; throughput is as much as 180 tests per hour.

A simple method of model fitting for adoption data

Traditional models used with adoption data often make strong assumptions concerning the nature of genetic transmission and assortative mating. A simple model is presented which avoids these assumptions. The model is linearized and, thus, has the further advantage that it can be used with standard statistical packages such as LISREL or EQS. The model allows tests of the internal consistency of the data, in addition to tests of the relative strength of genetic and environmental transmission parameters. To illustrate the model, measures of general cognitive ability in parents and their 7-year-old children from the Colorado Adoption Project (CAP) were fit to the model using the LISREL program. This relatively simple model may be expanded to incorporate more complex designs involving multiple measures or siblings. Although the model will not always allow constraints on the parameter estimates in more complex models, it offers a quick, flexible method for initial exploration of adoption data.

Multivariate path analysis of specific cognitive abilities in the Colorado Adoption Project: conditional path model of assortative mating

A multivariate path model of genetic and environmental transmission employing a conditional path representation of assortative mating was fitted to specific cognitive abilities data from the Colorado Adoption Project and evaluated using a maximum-likelihood estimation procedure. In agreement with results obtained from a previous analysis of a smaller data set, significant genetic covariation among the cognitive variables was indicated and evidence for a general genetic factor was found. However, cultural transmission parameters are nonsignificant and environmental correlations among the measures are relatively small.

Genetic and environmental determinants of musical ability in twins

Analyses of musical ability data from the Loehlin and Nichols National Merit Scholarship study are presented. Musical ability is indexed by four measures: interest in a profession in music, performance in school, performance outside of school, and receiving honors in music. These variables pose a challenge for behavior genetic analysis since they do not conform to the assumptions of traditional linear models. For example, there is a dependent relationship between the honors and the performance variables; one cannot obtain honors without performance. Several methods were employed to deal with these relationships, and the following conclusions appeared regardless of the method used. First, twin correlations were always high, ranging from 0.44 to 0.90 in monozygotic (MZ) twins and from 0.34 to 0.83 in dizygotic (DZ) twins. Second, although there was evidence for heritable variation, the effects of common environment were almost always larger than the effects of heredity. Third, marital assortment was not of sufficient magnitude to account for these common environment effects. In the young adults in this sample, musical ability is influenced more by shared family environment than by shared genes.

Big genes, little genes, affective disorder, and anxiety. A commentary

This article offers a brief explanation of the methods used for studying the genetic epidemiology of psychiatric disorder and comments on three articles in this issue of the Archives. Although the methods have had success in detecting genes of major effect for enzymes involved in neurotransmitter synthesis and degradation, they have not produced compelling evidence for a major locus in affective disorder. At the same time, simpler modes of transmission do not fully explain familial data on bipolar disorder or early-onset unipolar disorder. The problem of familial comorbidity of anxiety and depression is discussed, and an illustration is given of how assumptions about psychiatric classification and familial models can obscure the issue of comorbidity.

A general multivariate approach to linear modeling in human genetics

The general linear structural equation model is applied to problems in human genetics where there may be more than one measured phenotype per individual. A modeling convention, termed conditional associations, is developed to extend the general linear model so that it can handle the unique problems in human genetic models that arise from the pairing up of individuals or families under assortment between mates and the assortative placement of adoptees. Formulas are presented to generate expected covariance matrices for assortment or assortative placement on many variables simultaneously. It is demonstrated that all linear models in human genetics can be reduced in form to two fundamental equations. An algorithm is presented that will allow the application of these two equations to linear modeling in human genetics.