Complex Genetics and Implications for PsychiatryBasic concepts in the study of diseases with complex genetics
Section snippets
How do we know that predisposition to a disease is genetic?
Most diseases run in families—but that is not enough to conclude that genetic factors are involved, since infectious diseases or nongenetic traits such as malnutrition or attendance of medical school also run in families. Twin and adoption studies discriminate between familiality due to genetic or due to environmental influences (geneticists mean with the latter any nongenetic factor, including chance and measurement error). Adoption studies have shown that the risk of an adoptee of having a
Alleles—the variations in the genome
In general, an allele is one of several forms of any defined DNA sequence in the genome, whether it is a gene or an anonymous DNA sequence. Such a defined place in the genome is called a locus [plural loci, please see also the glossary (Appendix 1) for a summary of terms explained in this section]. If a disease is inherited in a simple manner, the inheritance of disease alleles can be followed in pedigrees.
Although any base pair change is caused molecularly by mutation, the word mutation is now
Diseases can have a complex genetics for many reasons
A Mendelian disease runs in families in a strict dominant, recessive, or X-linked fashion. Hundreds of such disease loci have been mapped, and over 600 genes involved in genetic diseases have already been identified (Gelehrter et al 1998); however, so far there are only very few examples of psychiatric illnesses inherited in a strictly Mendelian fashion (see Brunner et al 1993 for such an example). Since there is some variation in onset and clinical course even in strictly Mendelian disorders
Mapping and cloning of mendelian disease genes: parametric linkage analysis
Before going into the problems of complex disorders, let us review how Mendelian disease genes were mapped so successfully in the past 10 years (Collins 1995). To identify such genes, families are ascertained, preferentially large pedigrees, DNA is isolated from blood, and linkage analysis is performed in which SSLPs from all over the genome are tested—i.e., PCR reactions are performed on DNA from each member of the pedigree with 200–500 SSLP markers. The logic of linkage analysis is
Heterogeneity
One complication in linkage mapping is if a disease runs in a Mendelian fashion in families, but in each family a different gene, usually on a different chromosome, causes the disease. This is called heterogeneity. One prime example is deafness, for which so far over 30 different loci have been identified (Petit 1996). Deafness can be inherited in a recessive, dominant, or X-linked fashion, and each runs in families in a fairly Mendelian fashion, so that it seems often (but not always) to be a
Nonparametric linkage analysis
To avoid some of the problems of selecting a very specific model, while still using some of the power of linkage analysis, nonparametric, i.e., mode-of-inheritance-independent, methods of linkage analysis were developed, called affected sib pair (ASP) methods or the more general affected pedigree member method (APM) (Weeks and Lange 1988). In these methods, only sibpairs or other pairs of affected relatives are studied, which means the power of seeing alleles segregating in large pedigrees is
Case–control association studies
Linkage-based studies are based on following marker alleles that are close to a mutation on a specific chromosomal segment. These approaches do not make any biological assumptions about the disease, in fact they are performed in exactly the same fashion for diabetes, hypertension, or alcoholism. Once a location is found, the nature of the linked marker is irrelevant, all it does is “mark” the region of the chromosome. Popular press releases often confuse identification of linkage with finding a
Family-based association studies
A better way to overcome the population-stratification problem in case–control studies, however, are newer, family-based approaches, called haplotype relative risk (HRR) and transmission disequilibrium test (TDT) (see Figure 2B–D). The idea in these studies is to use the nontransmitted allele from the parents of an affected proband as internal controls (Figure 2B). In this manner, the same individuals, parents of affected subjects, provide both the test and the control sample, and thus the
Which method might work for which disease?
How can we decide between the methods mentioned above for our particular interest (see Table 1 for a simplified summary) ? When the disease is inherited in a clearly Mendelian fashion, there is no question that parametric linkage analysis is by far the most powerful method to locate a gene. Several pedigrees have been identified in which bipolar disorder segregates in an apparently Mendelian dominant fashion, and other pedigrees in which it seems X-linked; however, since a disease such as
Genome-wide association studies
In any form of linkage study, with a few hundred markers we can search blindly, without biological hypotheses, over the whole genome. In contrast, in TDT, specific alleles of a candidate gene are tested for association with the disease, and even different alleles within the same gene may be independent. Although the candidate gene approach seems appealing when we have a good hypothesis about the disease, genetic studies often identified genes that were never thought of as candidate genes: a
Summary
In summary, at the present time, there is no recipe for how to proceed to identify genes involved in complex diseases such as psychiatric illnesses. Currently, mixed approaches using linkage, association, and linkage disequilibrium are most often performed; for example, once a few chromosomal regions have been tentatively found to be linked, linkage disequilibrium is tested if suitable, and used to narrow down the region, and candidate genes in the most promising regions are scrutinized for
Acknowledgements
Research on Mental Illness in my laboratory is funded by the National Association for Research on Schizophrenia and Affective Disorders (NARSAD), the Nancy Pritzker Network on Depression Research, and the NIAAA.
I thank Adele Barres for help with figures, Huda Akil for many useful discussions, and Michael Boehnke, Scott Stoltenberg, Stanley Watson, James Meador-Woodruff, and Elizabeth Young for critical reading.
This work was presented in December 1997, at the American College of
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