DSM-III pathological personality cluster traits were measured on a community sample of 235 people. Traits in the schizoid cluster (schizoid, schizotypal, and paranoid) showed no change with age while traits in the dramatic cluster (antisocial, narcissistic, borderline, and histrionic) and to some extent the anxious cluster (avoidant, dependent, compulsive, and passive/aggressive) showed similar significant associations with age. This pattern was a reverse "J" shaped curve, with mean number of traits declining from younger to older groups and a slight upturn in the oldest age group (60 years plus). Women aged 31 to 40 years had a higher mean number of traits than their male counterparts, with a corresponding increase in impairment. The highest levels of personality traits in men were found at ages 18 to 30, while in women the 31 to 40 year group was highest.

Adolescent↗

PubMedDate not supplied

Distinguishing mixed anxiety/depression from anxiety and depressive groups using the family history method.

The relationship between anxiety and depression has long been discussed and studied. Although it appears that there are pure forms of these disorders, several investigators have suggested that there is a separate combined anxiety/depression disorder distinct from either individual disorder. Several attempts have been made to investigate this distinction using family history methods. This report compares an anxiety/depression group to a depression-only group and anxiety-only group in a veteran population (n = 71) using the family history method. The depression group was clearly differentiated from the anxiety/depression group on the variables of generalized anxiety disorder and alcohol abuse. There was also discrimination between the anxiety and anxiety/depression groups on the DSM-III-R anxious personality disorder cluster. This is the first report in this area of the literature to use standardized family history methods that include personality disorder clusters.

Adult↗

PubMedDate not supplied

Paranoid personality traits in a panic disorder population: a pilot study.

To better understand the relationship between panic disorder and paranoid personality, panic disorder patients (N = 28) who were referred to an anxiety disorder clinic in a community mental health center were evaluated for paranoid personality traits on a standardized personality self-report instrument. Paranoid personality disorder was found in 54% of subjects. Paranoid subjects were found to have an earlier age of onset, longer duration of illness, and more psychopathology. Possible etiologies and implications for treatment of these findings are discussed.

Adult↗

PubMedDate not supplied

Personality disorder traits in generalized anxiety and panic disorder patients.

Eight-four panic disorder (PD) and 29 generalized anxiety disorder (GAD) patients were compared with respect to abnormal personality traits assessed by a structured interview (Structured Interview for DSM-III Personality [SIDP]) and a self-report inventory (Personality Diagnostic Questionnaire [PDQ]). An earlier study using many of the same patients by Noyes et al. found PD patients to have more extensive axis I psychopathology than GAD patients. However, in this study it was the GAD patients who appeared to have greater axis II pathology. In particular, when using a subset of patients who had been matched for age and gender, the GAD patients reported more antisocial traits. This finding is particularly interesting, since the matched samples consisted primarily of women in their forties and fifties.

Adult↗

PubMedDate not supplied

Multi-locus nonparametric linkage analysis of complex trait loci with neural networks.

Complex traits are generally taken to be under the influence of multiple genes, which may interact with each other to confer susceptibility to disease. Statistical methods in current use for localizing such genes essentially work under single-gene models, either implicitly or explicitly. In genomic screens for complex disease genes, some of the marker loci must be in tight linkage with disease susceptibility genes. We developed a general multi-locus approach to identify sets of such marker loci. Our approach focuses on affected sib pair data and employs a nonparametric pattern recognition technique using artificial neural networks. This technique analyzes all markers simultaneously in order to detect patterns of locus interactions. When applied to previously published sib pair data on type I diabetes, our approach finds the same genes as in the published report in addition to some new loci. For a specific two-locus model of inheritance, the power of our approach is higher than that of the currently used analysis standard.

Chromosome Mapping↗

PubMedDate not supplied

A complete enumeration and classification of two-locus disease models.

There are 512 two-locus, two-allele, two-phenotype, fully penetrant disease models. Using the permutation between two alleles, between two loci, and between being affected and unaffected, one model can be considered to be equivalent to another model under the corresponding permutation. These permutations greatly reduce the number of two-locus models in the analysis of complex diseases. This paper determines the number of nonredundant two-locus models (which can be 102, 100, 96, 51, 50, or 58, depending on which permutations are used, and depending on whether zero-locus and single-locus models are excluded). Whenever possible, these nonredundant two-locus models are classified by their property. Besides the familiar features of multiplicative models (logical AND), heterogeneity models (logical OR), and threshold models, new classifications are added or expanded: modifying-effect models, logical XOR models, interference and negative interference models (neither dominant nor recessive), conditionally dominant/recessive models, missing lethal genotype models, and highly symmetric models. The following aspects of two-locus models are studied: the marginal penetrance tables at both loci, the expected joint identity-by-descent (IBD) probabilities, and the correlation between marginal IBD probabilities at the two loci. These studies are useful for linkage analyses using single-locus models while the underlying disease model is two-locus, and for correlation analyses using the linkage signals at different locations obtained by a single-locus model.

Animals↗

PubMedDate not supplied