Unipolar relatives in bipolar pedigrees: a search for elusive indicators of underlying bipolarity

In an effort to identify features indicative of underlying bipolarity within the unipolar relatives of bipolar probands, we compared unipolar relatives of bipolars with unipolar relatives of controls. Using data from the Yale-NIMH Collaborative Study of Depression, we compared a number of demographic and clinical features individually, and then developed a logistic regression model for the differences found. Unipolar relatives of bipolars were generally similar to relatives of controls, but they were older and more likely to suffer from more severe, even psychotic, depression, and somewhat less likely to report a brief transition into their illness. A multiple logistic regression model for observed differences was highly statistically significant, but had limited ability to discriminate effectively between the two groups. These findings suggest that more stringent diagnostic criteria might be beneficial if unipolar relatives are counted as affected in linkage studies of bipolar disorder. The ability of this strategy to improve the "clinical phenotype" is limited, however, and other approaches may be needed to identify features of underlying bipolarity and thus to define "caseness" for unipolar relatives in linkage analyses of bipolar disorder.

Schizophrenia: a genome scan targets chromosomes 3p and 8p as potential sites of susceptibility genes

Using a systematically ascertained sample of 57 families, each having 2 or more members with a consensus diagnosis of schizophrenia (DSM-III-R criteria), we have carried out linkage studies of 520 loci, covering approximately 70% of the genome for susceptibility loci for schizophrenia. A two-stage strategy based on lod score thresholds from simulation studies of our sample identified regions for further exploration. In each region, a dense map of highly informative dinucleotide repeat polymorphisms (heterozygosity greater than .70) was analyzed using dominant, recessive, and "affected only" models and nonparametric sib pair identity-by-descent methods. For one region, 8p22-p21, affected sib-pair analyses gave a P value = .0001, corresponding to a lod score approximately equal to 3.00. For 8p22-p21, the maximum two-point lod score occurred using the "affected only" recessive model (ZMAX = 2.35; theta M = theta F); allowing for a constant sex difference in recombination fractions found in reference pedigrees, ZMAX = 2.78 (theta M/theta F = 3). For a second region, 3p26-p24, the maximum two-point lod score was 2.34 ("affected only" dominant model), and the affected sib-pair P value was .01. These two regions are worthy of further exploration as potential sites of susceptibility genes for schizophrenia.

Turning point in the design of linkage studies of schizophrenia

Despite extensive genomic scans, linkage studies of multiplex pedigrees have been unable to produce replicable evidence of genes predisposing to schizophrenia. This indicates that it is unlikely that a single gene accounts for a majority of cases of schizophrenia, even in multiplex pedigrees. It is most likely that schizophrenia is caused by the nonlinear interaction of multiple genetic and environmental factors influencing brain development and function. This conclusion has strong implications for the design of linkage and association studies. Recently designed linkage studies involve several improvements to deal with extensive locus heterogeneity and multiplicative interaction. These improvements include much larger samples of pedigrees, systematic ascertainment and sequential extension rules, and standardized procedures at multiple sites to facilitate collaboration and replication. Future improvements are likely to require advances in the assessment of clinical and neurobiological variability in multiplex pedigrees, more systematic environmental assessment, and advances in analytic methods to deal with multiplicative interaction. Rather than focusing only on schizophrenia as one or more discrete disorders, future linkage efforts should also consider the etiology of individual clinical syndromes or dimensional components of risk that interact to cause the complex pattern of syndromal comorbidity observed within schizophrenics and their families.

Follow-up of a report of a potential linkage for schizophrenia on chromosome 22q12-q13.1: Part 2

A collaboration involving four groups of investigators (Johns Hopkins University/Massachusetts Institute of Technology; Medical College of Virginia/The Health Research Board, Dublin; Institute of Psychiatry, London/University of Wales, Cardiff; Centre National de la Recherche Scientifique, Paris) was organized to confirm results suggestive of a schizophrenia susceptibility locus on chromosome 22 identified by the JHU/MIT group after a random search of the genome. Diagnostic, laboratory, and analytical reliability exercises were conducted among the groups to ensure uniformity of procedures. Data from genotyping of 3 dinucleotide repeat polymorphisms (at the loci D22S268, IL2RB, D22S307) for a combined replication sample of 256 families, each having 2 or more affected individuals with DNA, were analysed using a complex autosomal dominant model. This study provided no evidence for linkage or heterogeneity for the region 22q12-q13 under this model. We conclude that if this region confers susceptibility to schizophrenia, it must be in only a small proportion of families. Collaborative efforts to obtain large samples must continue to play an important role in the genetic search for clues to complex psychiatric disorders such as schizophrenia.

Unipolar relatives in bipolar pedigrees: a search for indicators of underlying bipolarity

In an effort to identify features indicative of underlying bipolarity within the unipolar relatives of bipolar probands, we compared unipolar relatives of bipolars with unipolar relatives of unipolars. Using data from the Collaborative Study of the Psychobiology of Depression, we compared a number of demographic and clinical features individually, and then developed a logistic regression model for the differences found. Unipolar relatives of bipolars were somewhat more likely to be male and to have subthreshold bipolar features, and less likely to have panic symptoms. In addition, they had a small but significant decrease in the number of depressive symptoms and a large decrease in all treatment indicators. A multiple logistic regression model for these differences was highly significant, but had limited ability to discriminate between the two groups. These differences are not large enough to effectively discriminate between the groups for the purposes of classification. These particular results may result from a number of factors, most likely the choice of comparison group. Nonetheless, the work demonstrates a potential method for the construction of caseness indices for use in genetic studies of bipolar and other psychiatric disorders.

Genetic linkage and schizophrenia: methods, recent findings and future directions

Family, twin and adoption studies have shown that familial clustering in schizophrenia is predominantly due to genetic factors. On the basis of segregation analyses of the illness distribution in relatives of patients, various models of the mode of transmission have been put forward but as yet there is no consensus. Linkage analysis based on molecular genetic techniques provides a more direct approach to discovering precisely what is inherited (one gene, a small number of genes or many genes?) that generates vulnerability to schizophrenia. To date there has been no sufficiently replicated finding of one or more linked genes and many methodological complexities remain. However, the rate of progress in addressing these issues gives hope that genetic linkage analysis of schizophrenia will provide some answers.

Identification of the phenotype in psychiatric genetics

Statistical procedures and molecular genetic techniques have attained a fine degree of resolution. Their ability to find disease genes has revolutionized medicine and raised hopes for breakthroughs in psychiatry. However, such breakthroughs may require an equally discriminating nosology. A psychiatric genetic nosology seeks to classify patients into categories that correspond to distinct genetic entities by addressing the problem of diagnostic accuracy: the degree to which a diagnosis correctly classifies people with and without a putative genetic illness. We review methods that deal with misclassification in genetic studies. These are clinical and epidemiological approaches that deal directly with how to define the observable manifestation of a putative genotype. We discuss two groups of methods: those that use known phenotypes and those that design new phenotypes.

Extensions to sib-pair linkage tests applicable to disorders characterized by delayed onset

Extensions of the approach to sib-pair linkage tests developed by Haseman and Elston [Behav Genet 2:3-19, 1972] are proposed which incorporate information on age of onset and age at examination. Alternate sources for the age of onset corrections are described, including models for the estimation of parameters associated with the age of onset distribution. Simulation is used to examine the performance of the approach when applied to a dominant disorder of late onset for a range of recombination fractions ranging from very tight linkage to free recombination. For each set of genetic parameters, 2,000 samples of 50 four-member sibships were generated under a complete ascertainment model to investigate power and Type I error, and to compare variants of the proposed technique. Results with and without age-of-onset correction are compared to each other and to those obtainable if penetrance were complete, i.e., if there were no intervening age-of-onset phenomenon. Results from simulation studies show that significance probabilities are enhanced in the presence of linkage when age-of-onset extensions are used. The proposed methods are associated with acceptable levels of Type I error, and substantive gains in power are obtained when data related to age of onset and age at examination are incorporated into the analysis.