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Presents a diagnosis of the acute perforation of the upper gastrointestinal tract. Conditions in which air is present under the diaphragm; Sample cases of perforated peptic ulcer.

In the post-genomic era, the laboratory mouse will excel as a premier mammalian system to study normal and disordered biological processes, in part because of low cost, but largely because of the rich opportunities that exist for exploiting genetic tools and technologies in the mouse to systematically determine mammalian gene function. Many robust models of human disease may therefore be developed, and these in turn will provide critical clues to understanding gene function. The full potential of the mouse for understanding many of the neural and behavioral phenotypes of relevance to neuroscientists has yet to be realized. With the full anatomy of the mouse genome at hand, researchers for the first time will be able to move beyond traditional gene-by-gene approaches and take a global view of gene expression patterns crucial for neurobiological processes. In response to an action plan for mouse genomics developed on the basis of recommendations from the scientific community, seven institutes of the National Institutes of Health (NIH) initiated in 1999 a mouse genetics research program that specifically focused on neurobiology and complex behavior. The specific goals of these neuroscience initiatives are to develop high-throughput phenotyping assays and to initiate genome-wide mutagenesis projects to identify hundreds of mutant strains with heritable abnormalities of high relevance to neuroscientists. Assays and mutants generated in these efforts will be made widely available to the scientific community, and such resources will provide neuroscientists unprecedented opportunities to elucidate the molecular mechanisms of neural function and complex behavior. Such research tools ultimately will permit the manipulation and analysis of the mouse genome, as a means of gaining insight into the genetic bases of the mammalian nervous system and its complex disorders.

As the new millennium approaches, research into the genetic aspects of schizophrenia has already made an impressive start toward an integrated model which is discovering roles for genetic agents, environmental agents and experiences, and chance factors. The best model follows that proposed for understanding such complex diseases as coronary artery disease and diabetes. Genetic information has come from both genetic epidemiology and molecular genetics. Evidence for gene regions on 6p and 8p gives the strongest support for harboring schizophrenia susceptibility genes, based on international collaborative studies that "generally" replicate one another; evidence for regions on 3p, 5q, 9p, 20p, and 22q, while less compelling, will encourage focused work. Determining the steps between the regions and the phenotype will challenge the next generation of scientists.

Genetic factors make important contributions to the etiologies of schizophrenia. The mode of familial inheritance remains unknown, but it is highly likely that multiple genes and idiosyncratic environmental factors are involved. Rapidly evolving genetic technologies have been applied in the genetic analysis of schizophrenia, and several genomic regions have been posited as harboring susceptibility genes. Currently, the strongest evidence implicates chromosomes 6 and 8, but these linkages are not yet confirmed. In this article we discuss genetic risk factors, gene-environment interaction, the feasibility of genetic testing, psychiatric genetic counseling, and the dangers of genetic discrimination as they apply to schizophrenia. We also address and correct specific misconceptions about the genetics of schizophrenia held by many in the scientific community and in the media, and discuss a blueprint for future genetic research and informed dissemination of findings to the public and to lawmakers.

Efforts to map susceptibility loci for complex human diseases frequently result in weak evidence for linkage, followed by failures to convincingly replicate. If a disease locus influences both affection status (AF) and a quantitative trait, a variant of the extreme discordant sib pair (EDSP) strategy may be used to judiciously sample families for a replication study. This approach was evaluated by conducting joint segregation and linkage analysis of four bivariate phenotypes, each comprising AF and one quantitative trait (Q2, Q3, Q4, Q5), and undertaking a genomic scan of the GAW10 Problem 2B data set. Suggestive evidence was found for linkage of AF/Q2 to marker D8G26 (lod = 1.63, chi 2 = 7.52, p = 3.05 x 10(-3)). Sets of 23 EDSP families were selected based on Q2 values that demarcated the bottom 1%, 2%, 5%, 10%, or 20% of the distribution. Highly significant evidence for linkage was found when the 1% or 2% cutoffs were used (lod > 4, chi 2 > 20, p < 4 x 10(-6)), but more than 1,000 families had to be screened. Significant evidence for linkage (lod = 3.24, chi 2 = 14.91, p = 5.63 x 10(-5)) was found in the EDSP sample obtained using a 5% cutoff: about 300 families had to be screened. Only suggestive evidence for linkage (lod = 1.65, chi 2 = 7.59, p = 2.93 x 10(-3)) was found in non-EDSP families. Use of EDSP sampling variants can permit convincing replications not otherwise obtainable in the genetic analysis of complex diseases.

Joint multivariate segregation and linkage analysis provides a method for simultaneously analyzing data on affection status, correlated phenotypic traits, environmental risk factors, and other covariates. The power of this approach for mapping disease susceptibility loci of small effect (oligogenes) was evaluated by analyzing the GAW9 Problem 2 data set. The program REGRESS, which assumes a pleiotropy model in which one locus influences both affection status (AF) and a quantitative trait, was used to conduct joint segregation and linkage analysis of bivariate phenotypes, each comprising AF and one quantitative trait (Q2, Q3, Q4). A genome-wide search using markers spaced approximately 10 cM apart was conducted and regions on chromosomes 1, 2, and 5 were identified as demonstrating linkage with three respective bivariate phenotypes at the following markers: AF/Q2-D1G2; AF/Q3-D2G10; and AF/Q4-D5G18. The effects of other loci were included in a general model by specifying the quantitative traits they influenced as covariates along with age, sex, and an environmental effect. Use of covariate and quantitative trait data in each analysis resulted in respective chi 2 values with 1 df of 38.4, 65.4, and 22.0 to reject the no linkage hypothesis at theta = 0, with respective equivalent lod scores of 8.3, 14.2, and 4.8. Rejection at p < 0.0002 occurred using markers as far away as 20 cM. These loci were not detected when AF alone was analyzed.

The Personality Disorder Examination was administered to 302 normal controls in the New York High-Risk Project in order to elicit Axis II diagnoses (revised 3rd edition of the Diagnostic and Statistical Manual of Mental Disorders; American Psychiatric Association, 1987) and quantitative dimensions of psychopathology. LISREL confirmatory factor analysis was used to evaluate the Axis II hypothesis of 3 orthogonal factors. There was considerable overlap among personality disorders. The best fitting LISREL model was of 3 oblique factors that were different for male and female subjects. Given that our choice of variables to constrain in order to mathematically identify our models was partially based on analysis of intercorrelations in our data set, our methods were not purely confirmatory. We present our results not to confirm specific hypotheses but to generate explicit hypotheses that can be tested in independent samples.

Objective: The authors' goals are to use scales from the MMPI hypothesized in their previous research to be correlates of liability to schizophrenia to differentiate DSM-III schizophrenia from bipolar and unipolar affective illness and to cross-validate these correlates in an independently ascertained sample of patients with Research Diagnostic Criteria (RDC) schizophrenia or affective disorder., Method: The criterion sample consisted of 83 patients consecutively admitted to a state-operated community mental health center. Diagnosis of schizophrenia; bipolar disorder, manic; and major depression were assigned by using DSM-III. The replication sample consisted of 60 adults with RDC diagnoses of schizophrenia, schizoaffective disorder, bipolar disorder, and unipolar disorder who were parents of children in two samples collected for a study of offspring at high risk for schizophrenia and other psychopathology. After the patients in the criterion sample were classified by logistic regression analysis, the results were used to classify patients in the replication sample., Results: The MMPI indicators had adequate sensitivity, specificity, and predictive power for classifying schizophrenia, and there was a moderately high rate of diagnostic agreement between the MMPI and DSM-III. Cross-validation in the replication sample was successful. Overall, the MMPI index was an adequate inclusion and exclusion criterion not only for DSM-III-defined but also for RDC-defined schizophrenia., Conclusions: A psychometric index composed of the paranoid schizophrenia, psychoticism, and manifest hostility scales from the MMPI would be a cost-effective measure to increase diagnostic efficacy in future schizophrenia research and clinical practice.

Evidence regarding the heritability of unipolar depression is evaluated. The data reviewed here support the involvement of genetic factors in the etiology of unipolar depression and its suitability for independent genetic inquiry, despite our inability to identify the mode(s) of transmission or identify a candidate locus. Continued progress in testing etiologic hypotheses requires (a) clarification of the mode of transmission; (b) resolution of phenotypic and potential genotypic heterogeneity; (c) general agreement on a "gold standard" for assessment of the unipolar phenotype; (d) the continued application of available quantitative methods to take into account the effects of ascertainment bias, sex effects, cohort effects, and variable/late age at onset; and (e) incorporation of quantitative indicators correlated with liability in multivariate analysis to improve the stability/validity of phenotypic determinations in segregation and linkage analysis. We present several recommendations regarding the extension of current methodologies in human population and quantitative genetics to help resolve these issues.

The application of psychometric procedures to a normal population sample to detect individuals with increased liability for schizophrenia is a useful methodological adjunct to the traditional genetic high-risk strategy. A necessary and reasonable step in the process of establishing the utility of a viable psychometric index of schizotypy is the formal investigation of the latent structure of psychometric values. The present study used admixture analysis to examine the distribution of scores on the Perceptual Aberration Scale (PAS), an objective measure of hypothetical psychosis-proneness, in a randomly ascertained sample of 18-year-old university students (n = 707). We applied parametric methods that assumed normally distributed component distributions; viewed in this context, our results are hypothesis-generating and not definitive confirmation of specific hypotheses. Within our methodological framework, the results provide strong evidence for the commingling of normal distributions, even after allowing for unequal variances across components and after removing skewness. The overall distribution of power-transformed data is consistent with the existence of three qualitatively distinct classes of PAS responders. We discuss our results in light of Meehl's model of schizotaxia, a "mixed model" of inheritance of liability to schizophrenia, and we review the methodological implications of our findings for future research.

The longitudinal and prospective study of offspring at risk for schizophrenia is complicated by within-group heterogeneity in liability, as only a subgroup of those at risk will ultimately become affected. Here, we attempt to resolve such heterogeneity in the New York High-Risk Project by conducting an admixture analysis of values on a psychometric index of liability to schizophrenia derived from the Minnesota Multiphasic Personality Inventory (MMPI). We fit mixtures of components to the overall distribution in 171 children from three criterion groups: offspring at risk (HR) for schizophrenia, psychiatric comparison (PC) offspring at risk for affective illness, and normal comparison (NC) offspring not at increased risk for psychiatric morbidity. The distribution of psychometric scores was bimodal, and separation of two latent classes showed that there is a valid and nonarbitrary distinction between a subgroup of MMPI-deviant (primarily HR) offspring and a larger homogeneous group of MMPI-nondeviant HR, PC, and NC subjects. While continued followup is required to demonstrate a correspondence between these two classes and an underlying taxonomy of liability to schizophrenia, our findings demonstrate the utility of objective psychometric measurement and admixture analysis for resolving within-group heterogeneity in high-risk research. The wider implications of including our MMPI indicators in other genetic investigations of schizophrenia are discussed.

Psychometric signs from the Minnesota Multiphasic Personality Inventory (MMPI), which measure substantive disturbances in thinking, social relatedness, volition, and affective expressivity, were evaluated as possible indicators of transmissible liability specific to schizophrenia. Children of three criterion groups in the New York High-Risk Project--offspring at high risk (HR) for schizophrenia, psychiatric comparison (PC) offspring at risk for affective disorders, and normal comparison (NC) offspring not at augmented risk for psychiatric morbidity--were tested before the expression of schizophrenic psychopathology, when the subjects ranged in age from 13 to 26 years. The rate of psychometric deviance in the HR group (23%) was significantly higher than that in either the PC (7%) or NC (2%) groups, and profile analyses showed that the HR subgroup could be delineated by qualitative distinctions in personality functioning. Our results support the utility of MMPI indicators in etiologic investigations of schizophrenia.

The genetic analysis of schizophrenia would be facilitated by identification of a heritable correlate of liability. Deviance on an index of Minnesota Multiphasic Personality Inventory (MMPI) signs is associated with the disease phenotype; the familial aggregation and mode of transmission of this continuous psychometric indicator have yet to be established. In this paper, we examine the indicator through commingling analysis and segregation analysis with both the mixed and unified models on 65 nuclear families containing 211 normal individuals. Evidence for a high degree of familiality is found. Analysis of untransformed data under a conditional likelihood provides evidence for Mendelian transmission of a major gene with commingling of two distributions. The frequency of the "high index score" allele is 0.15, with the gene accounting for 31% of the total population variance; such a locus would be relevant to the study of psychopathology as 28% of the population would carry at least one deviant allele. When power-transformed scores are used to eliminate skewness, there is evidence for one distribution and it is not possible to distinguish single gene from multifactorial (polygenic or cultural) inheritance. While our findings regarding mode of transmission must be interpreted cautiously and confirmation of a single locus requires further study, demonstration of familiality warrants continued investigation of the index as an indicator of liability for schizophrenia.

Adjunct consideration of both qualitative (affection status) and quantitative (correlated liability indicator) information to define a bivariate phenotype can increase considerably the accuracy and efficiency of disease risk estimation. A general approach for calculating morbid risks to offspring on the basis of parental affection status and an offspring quantitative trait is presented. We also describe two different bivariate models of multifactorial inheritance, as implemented in the computer programs POINTER and YPOINT, and make explicit their assumptions/constraints when estimating the within-person and parent-offspring correlations necessary for calculation of morbid risks. We use psychometric family data on schizophrenia from the New York High-Risk Project to estimate these correlations and illustrate our methods. Our results show that even when a trait is only moderately correlated with liability, incorporation of quantitative trait information can lead to resolution of a range of risk to offspring that is not possible through reliance on parental affection status alone. Bivariate models provide a useful methodology for incorporating quantitative indicators of liability in the investigation of genetically complex diseases.

The authors used the Minnesota Multiphase Personality Inventory (MMPI) to provide convergent validity for Research Diagnostic Criteria (RDC) diagnoses of parents with schizophrenia, mainly schizophrenic schizoaffective disorder (SAS), bipolar affective disorder, and unipolar affective disorder in the New York High-Risk Study. Examination of group profiles, as well as univariate and configural analyses of several MMPI variables, led to successful discrimination of the schizophrenic from both affective groups and a normal control group. The results support the validity of risk assessment for children in the study and also suggest that there is commonality between schizophrenia and SAS. Despite variations in clinical status at testing, the MMPI was useful in exploratory analyses to describe phenomenology specific for schizophrenia that was expressed as the predominance of disturbances in thought, social relations, motivation, and affective expressivity relative to a primary disturbance in mood. The results also suggest that there is some symptomatic overlap between schizophrenia and affective disorders regarding a disturbance in social relatedness predominant over a disturbance in mood (for unipolar states) and a disturbance in thought predominant over a disturbance in mood (for bipolar states).

To determine which dimensions of psychopathology are associated with a greater liability to develop schizophrenia, the authors examined the case histories of 151 monozygotic probands from five twin studies. Proband twins from pairs concordant for schizophrenia had greater numbers of negative symptoms, poorer premorbid adjustment, fewer paranoid symptoms, and earlier ages at onset than probands from discordant pairs. In discriminant analyses, negative symptoms, premorbid social competence, and paranoid symptoms each contributed to the discrimination between concordant and discordant pairs. These results provide support for Strauss et al.'s suggestion that these three types of symptoms reflect three different functional processes in the development of schizophrenia.