The Epidemiology of the Genetic Liability for Schizophrenia

Abstract

Objective

The low incidence of schizophrenia prohibits large scale prevention trials, and the question arises whether such studies become more feasible by taking into account genetic factors. The aim of the paper was to inform preventive endeavours with an account of the genetic background to schizophrenia.

Method

The family, twin and adoptive studies of schizophrenia are reviewed and recent molecular genetic data presented.

Results

Children of a parent diagnosed with schizophrenia have a ten-fold increased risk of developing the disorder. Twin and adoption studies strongly suggest the risk increase is mainly due to genetic factors. On an individual level, a positive family history is the strongest known risk factor for schizophrenia. For a prevention study, very large numbers of families have to be screened in order to reach a sufficient sample size.

Conclusions

One obvious way to increase the accuracy of predicting who is at high risk of developing schizophrenia would be to find specific mutations in the human genome. Attempts to isolate specific genes by means of linkage and association studies have been unsuccessful so far and, given the number of genes involved, it is extremely unlikely that the predictive value of individual genes will be high enough to warrant intervention. Genetic studies also suggest the genetic liability extends beyond the traditional clinical phenotypes. Prevention trials might become possible by adopting a broader approach.

Keywords

genetic risk prediction prevention schizophrenia specificity

Prevention strategies are either targeted at the population as a whole or at subgroups with a high risk of developing the disorder. The latter strategy requires a measurable way to identify individuals at risk, a risk factor that precedes outcomes and allows for the division of the population into high-risk and low-risk categories. Risk factors that precede outcomes can be divided into two categories: (i) fixed markers, which are risk factors that cannot be changed; and (ii) variable risk factors, which can change or be altered [1]. If the manipulation of a variable risk factor changes the outcome of a disorder, it is a causal risk factor; if not, it is merely a correlate. For an intervention to be successful, it must target a causal risk factor.

At the present stage, genes have to be considered fixed markers. Genetic factors can define a subgroup of the population at high risk of developing a disorder. There are no widely accepted causal risk factors in schizophrenia that can be targeted for prevention and genetic factors are currently within the domain of research rather than prevention. The low incidence of schizophrenia makes studies into causal risk factors without defining high-risk groups practically impossible. From a practical standpoint the sample sizes required to determine the significance of a factor are far too large. The question therefore arises whether such studies based on genetic factors will become more feasible and lead to a targeted intervention.

The genetic risk to develop schizophrenia: results from twin and family studies

The first large genetic study was carried out by Rüdin in 1916, which demonstrated that siblings and offspring have an increased risk for schizophrenia [2]. A review of the schizophrenia genetic studies using modern diagnostic criteria places the risk in first-degree relatives (Table 1) between 3.1% and 16%, compared to controls where the risk is between 0.2% and 1.1% [3].

Table 1

Lifetime expectancy of schizophrenia in the relatives of probands with schizophrenia (modified from Gottesman and Shields [4])

Type of relative	Lifetime expectancy (%)
Population	1.0
First degree
Parent	5.6
Siblings	10.1
Siblings with one parent schizophrenic	16.7
Children	12.9
Children with both parents schizophrenic	46.3
Second degree
Half siblings	4.2
Uncles/aunts	2.4
Nephews/nieces	3.0
Grandchildren	3.7
Third degree
First cousins	2.4

Family studies clearly show that schizophrenia clusters in families; however, they do not allow any conclusions about the causes of this familial aggregation. Twin studies estimate the contribution of genetic factors to the observed familial aggregation. They are based on the fact that monozygotic (MZ) twins are genetically identical while dizygotic (DZ) twins only share half of their genes and genetically no different from siblings. Greater concordance of MZ twins compared to DZ twins reflects genetic influence. There are a number of underlying assumptions; most importantly, both types of twins share their environment to approximately the same degree. Early studies of schizophrenia applying clinical diagnoses demonstrated consistently higher concordance rates in MZ twins compared to DZ twins [5]. The introduction of operationalised criteria instigated the reassessment of this material [6,7] as well as new studies [8]. The proband-wise concordance rate for MZ twins is about 45–50%, compared to 5–15% in DZ twins [9]. Not surprisingly, the ratio of concordance rates between MZ and DZ twins is dependent on the diagnostic criteria [7]. However, heritability estimates using RDC, DSM-III-R, and ICD-10 [10] were similar. Farmer and coworkers found pairs of MZ twins, one with affective disorder and a cotwin with schizophrenia [7]. Based on this, the authors added other psychiatric diagnoses to that of schizophrenia in order to further explore the boundaries of the phenotype. The addition of affective disorder with mood-incongruent delusions to the schizophrenia spectrum produced the largest increase in the ratio and, by implication, a ‘more genetic’ combination than schizophrenia alone. Schizophrenia, plus affective disorder with mood-incongruent delusions, plus schizotypal personality disorder, plus atypical psychosis produced the maximum MZ : DZ concordance ratio (7.68).

Twins share both prenatal and postnatal environments. One way of eliminating the postnatal environmental component is to study the offspring of twins with schizophrenia and their normal cotwins. Fisher found in 1971 that the risk of schizophrenia is equal in the offspring of MZ twins diagnosed with schizophrenia compared to their normal cotwins [11]. Gottesman and Bertelsen investigated the same sample 18 years later and reported the morbid risks (age-corrected) for schizophrenia and schizophrenia-related disorders in the offspring of the MZ twins with schizophrenia to be 16.8%, compared to 17.4% in their normal cotwins' offspring [12]. The risks in the offspring of DZ twins diagnosed with schizophrenia and their normal cotwins were 17.4% and 2.1%, respectively.

Adoption studies allow further disentangling of environmental and genetic factors. There are numerous methodological variations. The first adoption study of schizophrenia was carried out by Heston in 1966 [13]. He compared the adopted-away offspring of mothers with schizophrenia to a control group of adopted-away offspring of mothers without a psychiatric diagnosis. Schizophrenia was diagnosed in five offspring, all of whom had a biological mother with schizophrenia. Similar results were obtained by Rosenthal et al. [14]. Kety and coworkers studied the biological relatives of adopted-away individuals diagnosed with schizophrenia and found a higher rate of schizophrenia spectrum disorders in this group compared to both adoptive parents and parents of control adoptees [15,16]. A re-examination of this sample by Kendler et al. [17] applying DSM-III criteria confirmed the original results by Kety et al. [15,16]

The most recent adoption study by Tienari et al. found that the adopted-away offspring of parents with schizophrenia had a 7.8% rate of development of a ‘spectrum psychosis’ (DSM-III-R schizophrenia; schizophreniform; delusional disorder) [18] compared to only 0.5% in the control group [19]. A more detailed investigation of environmental factors showed a very interesting gene–environment interaction [20]. High-risk offspring; that is, children with a biological parent diagnosed with schizophrenia, developed thought disorder at a higher rate when they were raised by adoptive parents with high levels of communication deviance. In contrast, high-risk offspring raised by adoptive parents with low levels of communication deviance had a lower proportion of thought disorder. These findings suggest a significant gene–environment interaction and, more specifically, a genetic control of sensitivity to the environment.

Considered together, family, twin and adoption studies strongly support a genetic aetiology of schizophrenia. They also clearly suggest that environmental factors play a substantial role. Model fitting using schizophrenia twin data has yielded high heritabilities with no or little contribution from the common environment. Non-shared environmental factors are therefore most likely to contribute to the susceptibility to schizophrenia. Adoption studies provide some evidence for gene–environment interaction.

The results also clearly demonstrate that the genotypes for schizophrenia can remain clinically unexpressed. Based on family data, this is the case in the majority (80–90%) of first-degree relatives of someone with schizophrenia.

The genetic data presented above poses two major problems for prevention studies:

(1)

There is a need to screen a large number of first-degree relatives. Only the MZ cotwin of an affected individual and children of two affected parents have a risk increase that is large enough to warrant intervention.

(2)

Given the low prevalence of schizophrenia, it is extremely difficult to recruit an appropriate sample. Mortensen et al. for example, identified 2669 cases of schizophrenia in a population-based cohort of 1.74 million persons in Denmark; 112 cases had one parent and another four had both parents diagnosed with schizophrenia [21].

Any prevention attempt is faced with the need to screen very large numbers. Despite family history of schizophrenia being the best established and, on an individual level, the strongest risk factor, it is not feasible to base large-scale prevention trials on this alone.

Genome wide scans and the search for schizophrenia susceptibility genes

One obvious way to increase the accuracy of predicting who is at high risk of developing schizophrenia would be to find specific mutations in the human genome. Identification of such mutations has become possible through linkage analysis. Linkage analysis tests for the cosegregation of a genetic marker and a putative disease gene. In classical linkage analysis [22], the distance between a gene and a genetic marker is estimated by observing the number of recombinations. Linkage analysis requires the specification of the mode of inheritance. The degree to which results are influenced by incorrect estimations of gene frequencies and penetrance values is controversial. A large number of disease-causing genes have been detected using this methodology. The majority of these code for simple Mendelian traits. The success for more complex disorders has been limited.

Alternative approaches to linkage analysis have been suggested. Studying affected sibling pairs [23] is appealing because: (i) no specification of the mode of inheritance is required; (ii) collection of families is less complicated; and (iii) problems of diagnostic classification are confined to the affected siblings.

In the case of schizophrenia, several genome scans have been completed [37,41,49,53–56]. Regions on more than half of the 23 chromosomes have been implicated [57]. The strongest evidence of linkage to date supports the existence of schizophrenia susceptibility loci on chromosomes 6p, 8p, 10p and 22q (Table 2). Evidence for other areas of vulnerability converge on specific chromosomal sites on 5q, 13q and 18p. None of these findings has yet been consistently replicated [58] and for each individual result there are more non-replications than replications. Controversy also exists about what constitutes a replication. The regions implicated are very large and often the overlap between the original and the replicated finding is small. In very few instances has the highest Lod score been found in the identical location.

Table 2

Major linkage findings

Chromosome region	No. families	Param. Lod score	Non-param. P-value	Non-param. Lod score	Reference
5q	15/44	1.9/–	–/0.005	–/1.8	Schwab et al. [24]
	265	3.22	–	2.8	Straub et al. [25]
6q	53/69	–	0.00024/0.0004	3.06/2.35	Cao et al. [26]
	40		0.013	1.07	Martinez et al. [27]
6p24-p22	186	3.9	0.009	–	Wang et al. [28]
	265	3.51	0.005	–	Straub et al. [29]
	54	2.0	0.0012	2.2	Schwab et al. [30]
	5/65	–	0.05/0.005	–	Moises et al. [31]
	57	1.17	0.004	–	Antonarakis et al. [32]
	713	2.35	–	2.68	Schizophrenia Collaborative Linkage Group for Chromosomes 3,6,8 [33]
8p22-p12	57	2.35	–	3.0	Pulver et al. [34]
	265	2.4	–	–	Kendler et al. [35]
	713	3.06	–	2.73	Schizophrenia Collaborative Linkage Group for Chromosomes 3,6,8 [33]
	21	2.13	–	–	Brzustovicz et al. [36]
10p14-p11	43	–	0.0004	3.4	Faraone et al. [37]
	88	3.2	0.03	–	Straub et al. [38]
	72	–	0.0007	3.2	Schwab et al. [39]
(Bipolar)	97	–	–	2.5	Rice et al. [40]
13q14-q32	57/51	3.19/–	0.00002/0.007	4.18/2.36	Blouin et al. [41]
	13	2.0	–	–	Lin et al. [42]
	21	3.92	–	–	Brzustovicz et al. [36]
18p (bipolar)	22	2.38	< 0.01	–	Berrettini et al. [43]
	28	1.45	0.0006	–	Stine et al. [44]
	57	2.54	0.03	1.34	Nöthen et al. [45]
18p (schizo.)	32	–	0.02	–	DeLisi et al. [46]
	59	3.1	0.002	2.9	Schwab et al. [47]
22q12-q13.1	39	2.82	–	–	Pulver et al. [48]
	9	2.09	0.016	–	Coon et al. [49]
	–	–	0.017	–	Polymeropoulos et al. [50]
	54	1.07	0.002	1.9	Wildenauer et al. [51]
	296	–	0.001	–	Schizophrenia Collaborative Linkage Group (Chromosome 22) [52]

Explanations for the difficulties detecting consistent linkage are manifold: diagnostic reliability, heterogeneity (i.e. two or more independent loci resulting in the same phenotype), population differences, lack of power and a large number of interacting loci involved. Risch showed that the power to detect linkage is dependent on the contribution of the individual gene to the familiality of the disorder [59,60]. If the effect of an individual gene is small, association studies can be more powerful [61]. As the majority of genes are expressed in the brain, the number of candidate genes is extremely large. Positive associations have been reported; however, none has been replicated consistently. There is some suggestive evidence implicating the serotonin 5HT2a and the dopamine DRD3 receptor genes [62].

Schizophrenia susceptibility genes: many genes of small effect

The picture emerging from family, twin and adoption studies, as well as from linkage and association studies, suggests that no single locus or pair of loci can account for the disease in a substantial fraction of cases. The lack of positive findings of linkage studies even in individual large families [63] or isolated populations such as Finland [55], argues against a model of heterogeneity with several single dominant genes segregating in the population. It cannot be excluded that such major genes exist; however, they most likely account only for a small proportion of the familiality observed. A model of many different, relatively common variations in a number of susceptibility genes best explains the findings. A combination of these alleles in an individual predisposes one to the development of schizophrenia. Each predisposing disease allele on its own contributes only a small increase in risk. This notion is confirmed by results from sib pair analysis. In this analysis, the degree of sharing two alleles is dependent on the risk ratio λ_s; that is, increase in risk to siblings compared with the population prevalence [59,60]. Williams et al. carried out a systematic search for linkage in 196 affected sibling pairs with DSM-IV schizophrenia [56]. None of their findings approached a genome-wide significance of 0.05. They estimated the power of this study to be > 0.95 to detect a susceptibility locus of λ_s = 3 and concluded that common genes of major effect (λ_s > 3) are unlikely to exist for schizophrenia.

The liability to develop schizophrenia arises from polygenic effects. Mathematically, the distribution of the liability takes the shape of a normal distribution [64]. Each gene has only a small effect on the trait variation. The expression of the trait depends much less on which polygenes a specific person carries than on the number of genes. Each individual has a number of susceptibility alleles and a certain ‘risk’ associated with them of developing schizophrenia and what is inherited is a predisposition to develop schizophrenia. The genotype affects the probability of expressing the clinical symptoms of schizophrenia. This liability can be modified by many factors and individuals who exceed a certain threshold value at a point in time are clinically diagnosed with schizophrenia.

The model described has been termed ‘multifactorial threshold model’ and was first introduced by Gottesman and Shields [65]. It has major implications for our ability to detect susceptibility genes. For genome scans to be successful, hundreds, if not thousands, of pedigrees with several affected family members need to be screened. Presently, none of the research groups has sufficient numbers. Even if this strategy (or association studies) should identify susceptibility genes, elucidating their predictive values will be another major problem. The risk increase for an individual carrying a mutation is low and strongly influenced by gene–gene as well as gene–environment interactions. This scenario will not facilitate prevention trials based on genetics alone.

Schizophrenia: what is inherited?

A major problem in studying genetics of schizophrenia, as well as of other psychiatric disorders, is our limited understanding of how genetic variation is translated into behaviour. Kandel argues that we are naïve if we think in terms of genetic determinism at the level of behaviour [66]. To put it in its most simple form, genes do not code for behaviour, they code for proteins. Proteins, the gene products, are the building blocks of the neurones in the brain and they determine neuronal functioning. Genes influence the susceptibility to schizophrenia by changing the expression pattern of proteins in the brain, most likely during certain stages of development. Gene expression is highly regulated at all levels. Gene– gene interaction and gene–environment interaction are an integral part of this process. In terms of behaviour, genes are non-specific. Put simply, in order to understand how genes affect behaviour, we must have an understanding of how genes are translated into brains and how this resulting brain produces behaviour.

Given the complexity of the relationship between genes and resulting behaviour, it is no surprise that pleiotropy is the rule rather than the exception [67]. Pleiotropy is the property of a gene whereby it affects two or more characteristics, so that if the gene is segregating, it causes simultaneous variation in the characteristics it affects. For example, the APOE4 genotype influences both the risk of developing late-onset Alzheimer's and cardiovascular disease [68]. The notion of pleiotropy suggests that genetically complex disorders, such as schizophrenia, can be characterised by multiple intermediate correlated traits [69]. Taking such correlated traits into account might not only dramatically enhance our chance of detecting linkage, but might also allow a more precise prediction of schizophrenia. Examples include neuropsychological risk indicators, such as attentionspan task; neurophysiological deficits in sensory gaiting (P50 response); neuroanatomic abnormalities; and changes in catecholamine metabolism [70]. Using both parametric and non-parametric (sib-pair) analysis on 104 members from nine families phenotyped for the auditory evoked potential P50, Freedman et al. reported a multipoint lod score of 5.29 for a marker on chromosome 15 (15q13–14) [71], which falls within the region coding for the α-7 nicotinic cholinergic receptor.

Another consequence of pleiotropy is that schizophrenia might be only one of the possible pathological outcomes. What is inherited is not a specific predisposition towards schizophrenia, but a liability to develop a number of different disorders, one of which is schizophrenia. In its extreme form, such a hypothesis leads to the theory of a unitary psychosis [72] or, in its modern form, the ‘continuum model of psychosis’ [73]. While results from family and twin studies argue against a unitary psychosis, they also strongly suggest that the genetic liability to schizophrenia is only partially specific. Family and adoption studies consistently showed increased risks of other psychiatric disorders. Bleuler observed that relatives of patients with schizophrenia displayed milder psychotic symptoms and personality characteristics similar to those found in patients with chronic schizophrenia [74]. The term, schizophrenia spectrum disorders, was coined to describe these disorders. The majority of studies show a higher rate of schizotypal personality disorder, schizophreniform disorder and other non-affective psychotic disorders in first-degree relatives of schizophrenic probands. The relationship between schizophrenia and affective disorders, however, is controversial. A number of findings challenge the notion of a clear-cut genetic boundary between mood disorders and schizophrenia. Increased rates of schizoaffective disorder and recurrent unipolar depression among first-degree relatives have been reported in two family studies of schizophrenia [3,75]. A transition from affective disorder to schizophrenia in MZ twins has been reported [76]. In addition, linkage studies of bipolar disorder and schizophrenia overlap on chromosome 10 [40], chromosome 18 [47] and chromosome 22 [77]. Latent class analysis using data from 343 probands and their 942 relatives [78] corroborated the complex picture of the genetic liability of schizophrenia. The vulnerability to psychosis extended across several syndromes.

A number of studies have concentrated on subjects at risk of developing schizophrenia. The high-risk design is specifically suitable to study gene–environment interactions. In general, genetic risk studies have found that environmental stressors associated with schizophrenia in genetically predisposed subjects are not associated with schizophrenia in those not at genetic risk. Many of the high-risk studies are now in their third or fourth decade, most notably the Copenhagen Project [79], the Israeli High-Risk Study [80] and the New York High-Risk Project [81]. The high-risk method was developed to study aetiology and to identify premorbid characteristics that could be used to select individuals for primary prevention [82]. Most high-risk studies define risk status genetically, especially focusing on children of mothers who have been diagnosed with schizophrenia. Data on diagnostic outcome found consistently higher rates of psychiatric disorders in these children. The disorders found at increased rates include schizophrenia spectrum disorders, but are not restricted to them. The New York High-Risk Project studied the offspring of patients with schizophrenia (HRSz group) or affective illness (HRAff group) and compared them to psychiatrically normal parents (Table 3). The children were followed into adulthood. The total rates of psychosis in these groups were significantly higher than in the normal parents group. Schizophrenia was diagnosed only in the HRSz group whereas schizoaffective and psychotic affective disorders occurred equally in the HRSz and HRAff groups. All groups had similar rates of nonpsychotic affective and substance abuse disorders. The HRAff group, however, had significantly more total affective illness than the normal parents group and tended to have more anxiety disorders than the other groups. The overall lifetime prevalence of an axis I disorder in the high-risk group was about 70%. Similar high rates of psychiatric diagnoses were also reported in the Copenhagen risk project, with 60% of high-risk subjects having a psychiatric diagnosis [83].

Table 3

Lifetime prevalences of axis I disorders in high-risk offspring and their siblings in the New York High-Risk Project (modified from Erlenmeyer-Kimling et al. [81])

	High-risk schiz. (N = 84) % of prevalence (n)	High-risk aff. (N = 67) % of prevalence (n)	Normal parents (N = 136) % of prevalence (n)
No axis 1 disorder	29.8 (25)	29.9 (20)	41.9 (57)
Schizophrenia related psychoses	17.9 (15)	6.0 (4)	0.7 (1)
Affective psychoses	6.0 (5)	7.5 (5)	0.0 (0)
Non-psychotic affective disorder	38.1 (32)	41.8 (28)	35.3 (48)
Anxiety disorders	15.5 (13)	25.4 (17)	11.0 (15)
Substance-abuse disorders	34.5 (29)	38.8 (26)	31.6 (43)

Schiz., schizophrenia; aff., affective disorder; n, calculated from [81].

High-risk studies demonstrated that behavioural problems during childhood could be viewed as antecedents to schizophrenia [84]. Children at risk of schizophrenia have poorer overall social competence and have greater affective deficits. Higher rates of forensic contacts and delinquent behaviour have been described [85]. High-risk subjects performed more poorly than controls in all aspects of intellectual functioning and tests of executive function and memory [86]. In addition, attentional deficits were detected in this group [87]. The attention impairment appeared to be independent of psychotic symptoms and seemed related more to chronic social difficulties. Whether these attentional deficits can be used as a screening tool for subjects susceptible to schizophrenia requires further study.

High-risk studies, family, twin and adoption studies all strongly suggest that the inherited liability goes beyond schizophrenia and encompasses a wide range of behavioural problems and disorders. Some of the neuropsychological deficits might be early antecedents of schizophrenia. Therefore, prevention trials should not be restricted to schizophrenia per se, but take into account these disorders. A broader approach to prevention might also help to overcome the difficulty of sample size.

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