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Copy Number Variation, Genetic Interactions, and Disease

Adapted from a story that originally appeared on the Alzheimer Research Forum.

2 February 2009. Understanding how genetic variation contributes to human disease has become a major thrust of modern science. For example, considerable effort currently goes into genomewide association studies, which aim to identify markers that associate with a given disease. But the effort is not paying off too well just yet. When it comes to teasing apart complex genetic traits driven by multiple genetic variations, many strategies fall woefully short. Likewise, the contribution to human disease of copy number variation, where duplication or deletions of whole sections of chromosomes can add or subtract complete genes, remains poorly understood. Two recent papers address these challenges—and reveal some surprises. In the January 21 American Journal of Human Genetics online, researchers led by Howard Hughes Investigator Evan Eichler at the University of Washington, Seattle, report that single copy number variants (CNV) may predispose individuals to a broad range of neurologic diseases, including schizophrenia, autism, and forms of mental retardation, suggesting that these variants may interact with other genetic and environmental factors to yield particular pathologies. And in the January 23 Science, researchers led by Barak Cohen at the University of Washington School of Medicine, St. Louis, Missouri, describe how different genetic variations can interact to influence expression of specific phenotypes in the model organism brewer’s yeast. Such epistatic interactions are thought to play a major role in human diseases, such as Alzheimer’s and schizophrenia, but little headway has been made in deciphering those relationships.

Variations on a theme
Eichler and colleagues used array-based analysis of DNA samples from about 2,500 healthy people to estimate copy number variation in the human population as a whole. This study stands out for its large sample size, which enables it to give an overview of this type of genetic idiosyncrasy in the population at large. First author Andy Itsara and colleagues report that most individuals (extrapolated to 65 to 85 percent of the general population) harbor a CNV that is at least 100 kb of DNA long. Much larger (>500 kb) variants occur in 5 to 10 percent of individuals, while at least 1 percent of the population carries a CNV exceeding 1 Mb. CNVs longer than 100 kb are rare, while those topping 500 kb tend to be found in only one individual. These findings are in keeping with the idea that huge CNVs are bad for your health. Counted from the other side, any given CNV is present in the population at a frequency of 0.2 to 1.0 percent.

Previous analysis of a sample set designed to measure human genome diversity on a global scale (see Cann et al., 2002) suggested that certain world populations carry more than their fair share of CNVs—20 to 30 per person compared to the average of seven to nine (see Jakobsson et al., 2008). Itsara and colleagues examined the same sample set, and while they confirmed that two of those three populations, Melanesian and Papuan, did have a higher prevalence (11.9, and 10.3 CNV per individual) than other populations, the difference was marginal. The third group, the Kalash of Pakistan, had fewer CNVs than average. “Deeper population screens to assess the distribution of large and rare CNVs in the human population are clearly warranted, because although such variants may segregate within specific populations because of genetic drift, others may contribute disproportionately to disease susceptibility or alternatively be adaptive within those populations,” write the authors.

CNVs are clearly linked to disease. The deletion of one copy of the region at chromosome 22q11.2 is well-known to schizophrenia researchers as giving rise to significant risk for schizophrenia, and several recent studies have reported an increase in CNVs in patients with schizophrenia (see SRF related news story and SRF news story). Furthermore, triplication of the entire chromosome 21 gives rise to Down syndrome, which is accompanied by a much greater risk for dementia. Duplication of the amyloid precursor protein gene on chromosome 21 leads to early-onset, familial AD, while duplication or triplication of the α-synuclein gene causes familial Parkinson disease (see Ibanez et al., 2009)

To assess the impact of CNVs on some neurologic diseases, Itsara and colleagues combined their data with those from nine genomewide association studies of schizophrenia, autism, and mental retardation, assembling CNV data on 6,860 affected individuals and 5,674 controls. Their analysis recovered known associations (e.g., deletions at chromosome 22q11 in some schizophrenia patients) and also revealed new, unexpected relationships.

The Seattle geneticists found that a chromosome 17p11.2 microdeletion normally associated with a disease called heredity neuropathy with liability to pressure palsies (HNPP) is also deleted in patients with schizophrenia and autism. At a locus on chromosome 16p12 that is predicted to be a risk candidate for schizophrenia (see Stone et al., 2008), Itsara and colleagues found a deletion in one autistic patient and no deletions in any controls, again suggesting some overlap between autism and schizophrenia risk factors. And their data suggest that at chromosome 3q29, where a microdeletion leads to a syndrome that includes mental retardation and other neurologic abnormalities (see Willatt et al., 2005), deletions again increase the risk for schizophrenia. The findings tie clinically separate disorders together through the same CNV, leading the authors to suggest that these loci render their carriers generally vulnerable to mental illness such that the specific manifestation in a particular person depends on genetic modifier or environmental effects (see http://www.schizophreniaforum.org/new/detail.asp?id=1475 related SRF news story, as well as Q&A with Eichler and Heather Mefford).

Just a simple change?
Exactly such genetic modification is what Barak Cohen and colleagues tried to come to grips with in their yeast study, which focused on a widely variable trait—sporulation. In Saccharomyces cerevisiae sporulation is a complex, heritable trait. It is subject to environmental influence, and believed to fall under different selection pressure in different environments, such as the oak grove in a forest and the oak wine barrel. Yeast from the former sporulate at near 100 percent efficiency, but those from the latter, perhaps not surprisingly, are much less competent. Sporulation serves as a model for complex traits, including susceptibility to disease and resistance to pharmacological intervention, exhibited by humans.

First author Justin Gerke and colleagues identified four nucleotide changes among three transcription factors that explain the natural variation in yeast sporulation efficiency. The researchers crossed two parent strains, one from the North American oak and one from a California wine barrel, and looked for quantitative trait loci in the offspring that match their sporulation efficiency.

The researchers identified five loci that accounted for most of the variation among the different offspring. Three of these loci, all of which turned out to harbor transcription factors, had large effects. By sequencing the different strains, the researchers found four nucleotide substitutions that account for almost 80 percent of the sporulation variation: a single nucleotide change in the regulatory region of RME1, a transcription factor that can suppress sporulation in certain cell types; two non-synonymous substitutions in the coding region of IME1, a master regulator that initiates sporulation; and a single coding change in RSF1, transcriptional activator of mitochondrial genes essential for respiration. By replacing nucleotides one, two, three, and four at a time, Gerke and colleagues found that all four alleles interact to alter the phenotype.

“Knowing how individual genetic polymorphisms combine to produce phenotypic change could strengthen evolutionary theory and advance applications such as personalized medicine,” write the authors. In general, epistatic interactions between genes are poorly understood and this study highlights the effect that even single nucleotides can have on a given trait. “This emphasizes the need to incorporate genetic interactions into models that seek to accurately predict phenotype from genotype,” write the authors, adding that “if prevalent, genetic interactions between nucleotides will be a major hurdle in the endeavor to connect genetic and phenotypic variation in humans.”—Tom Fagan.

References:
Itsara A, Cooper GM, Baker C, Girirajan S, Li J, Absher D, Krauss RM, Myers RM, Ridker PM, Chasman DI, Mefford H, Ying P, Nickerson DA, Eichler EE. Population analysis of large copy number variants. Am. J. Hum. Genet. 2009, Jan 21. Abstract

Gerke J, Lorenz K, Cohen B. Genetic interactions between transcription factors cause natural variation in yeast. Science. 2009, Jan. 23; 323:498-501. Abstract

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Daniel Weinberger, SRF Advisor
Submitted 27 March 2008
Posted 27 March 2008

The paper by Walsh et al. is an important addition to the expanding literature on copy number variations in the human genome and their potential role in causing neuropsychiatric disorders. It is clear that copy number variations are important aspects of human genetic variation and that deletions and duplications in diverse genes throughout the genome are likely to affect the function of these genes and possibly the development and function of the human brain. So-called private variations, such as those described in this paper, i.e., changes in the genome found in only a single individual, as all of these variations are, are difficult to establish as pathogenic factors, because it is hard to know how much they contribute to the complex problem of human behavioral variation in a single individual. If the change is private, i.e., only in one case and not enriched in cases as a group, as are common genetic polymorphisms such as SNPs, how much they account for case status is very difficult to prove.

An assumption implicit in this paper is that these private variations may be major factors in the case status of the individuals who have them. The data of this paper suggest, however, this is actually not the case, at least for the childhood onset cases. Here’s why: mentioned in the paper is a statement that only two of the CNVs in the childhood cases are de novo, i.e., spontaneous and not inherited (and one of these is on the Y chromosome, making its functional implications obscure). If most of the CNVs are inherited, they can’t be causing illness per se as major effect players because they are coming from well parents.

Also, if you add up all CNVs in transmitted and non-transmitted chromosomes of the parents, it’s something like 31 gene-based CNVs in 154 parents (i.e., 20 percent of the parents have a gene-based deletion or duplication in the very illness-related pathways that are highlighted in the cases), which is at least as high a frequency as in the adult-onset schizophrenia sample in this study…and three times the frequency as found in the adult controls. This is not to say that such variants might not represent susceptibility genetic factors, or show variable penetrance between individuals, like other polymorphisms, and contribute to the complex genetic risk architecture, like other genetic variations that have been more consistently associated with schizophrenia. However, the CNV literature has tended to seek a more major effect connotation to the findings.

View all comments by Daniel Weinberger

Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  William Honer
Submitted 28 March 2008
Posted 28 March 2008
  I recommend the Primary Papers

As new technologies are applied to understanding the etiology and pathophysiology of schizophrenia, considering the clinical features of the cases studied and the implications of the findings is of value. The conclusion of the Walsh et al. paper, “these results suggest that schizophrenia can be caused by rare mutations….“ is worth considering carefully.

What evidence is needed to link an observation in the laboratory or clinic to cause? Recent recommendations for the content of papers in epidemiology (von Elm et al., 2008) remind us of the suggestions of A.V. Hill (Hill, 1965). To discern the implications of a finding, or association, for causality, Hill suggests assessment of the following:

1. Strength of the association: this is not the observed p-value, but a measure of the magnitude of the association. In the Walsh et al. study, the primary outcome measure, structural variants duplicating or deleting genes was observed in 15 percent of cases, and 5 percent of controls. But what is the association with? The diagnostic entity of schizophrenia, or some risk factor for the illness? Of interest, and noted in the Supporting Online Material, these variants were present in 7/15 (47 percent) of the cases with presumed IQ <80, but only 15/135 (11 percent) of the cases with IQ >80. Are the structural variants more strongly associated with mental retardation (within schizophrenia 47 percent vs. 11 percent) than with diagnosis (11 percent vs. 5 percent of controls, assuming normal IQ)? This is of particular interest in the context of the speculation in the paper concerning the importance of genes putatively involved with brain development in the etiology of schizophrenia.

2. Consistency of results in the literature across studies and research groups: there are now several papers examining copy number variation in schizophrenia, including a report from our group (Wilson et al., 2006). The authors of the present paper state that each variant observed was unique, and so consistency of the specific findings could be argued to be irrelevant, if the model is of novel mutations (more on models below). Undoubtedly, future meta-analyses and accumulating databases help determine if there is anything consistent in the findings, other than a higher frequency of any abnormalities in cases rather than controls.

3. Specificity of the findings to the illness in question: this was not addressed experimentally in the paper. However, the findings of more abnormalities in the putative low IQ cases, and the similarity of the findings to reports in autism and mental retardation, suggest that this criterion for supporting causality is unlikely to be met.

4. Temporality: the abnormalities should precede the illness. If DNA from terminally differentiated neurons harbors the same variants as DNA from constantly renewed populations of lymphocytes, then clearly this condition is met. While it seems highly likely that this is the case, it is worthwhile considering the possibility that DNA structure may vary between tissue types, or between cell populations. Even within human brain there is some evidence for chromosomal heterogeneity (Rehen et al., 2005).

5. Biological gradient: presence of a “dose-response” curve strengthens the likelihood of a causal relationship. This condition is not met within cases: only 1/115 appeared to have more than one variant. However, in the presumably more severe childhood onset form of schizophrenia, four individuals carried multiple variants, and the observation of a higher prevalence of variants overall. Still, the question of what the observations of CNV are associated with is relevant, since one of the inclusion/exclusion criteria for COS allowed IQ 65-80, and it is uncertain how many of these cases had some degree of intellectual deficit.

6. Plausibility: biological likelihood—quite difficult to satisfy as a criterion, in the context of the limits of knowledge concerning the mechanisms of illness of schizophrenia.

7. Coherence of the observation with known facts about the illness: the genetic basis of schizophrenia is quite well studied, and there is no dearth of theories concerning genetic architecture. However, a coherent model remains lacking. As examples, the suggestion is made that the observations concerning inherited CNVs in the COS cases are linked with a severe family history in this type of illness. This appears inconsistent with a high penetrance model for CNVs as suggested in the opening of the paper (presuming the parents in COS families are unaffected, as would seem likely). Elsewhere, CNVs are proposed by the authors to be related to de novo events, and an interaction with an environmental modifier, folate (and exposure to famine), is posited (McClellan et al., 2006). A model of the effects of CNVs, which generates falsifiable hypotheses is needed.

8. Experiment: the ability to intervene clinically to modify the effects of CNVs disrupting genes seems many years away.

9. Analogy: the novelty of the CNV findings is both intriguing, but limiting in understanding the likelihood of causal relationships.

The intersection of clinical realities and novel laboratory technologies will fuel the need for better translational research in schizophrenia for many, many more years.

References:

von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008 Apr 1;61(4):344-349. Abstract

HILL AB. THE ENVIRONMENT AND DISEASE: ASSOCIATION OR CAUSATION? Proc R Soc Med. 1965 May 1;58():295-300. Abstract

Wilson GM, Flibotte S, Chopra V, Melnyk BL, Honer WG, Holt RA. DNA copy-number analysis in bipolar disorder and schizophrenia reveals aberrations in genes involved in glutamate signaling. Hum Mol Genet. 2006 Mar 1;15(5):743-9. Abstract

Rehen SK, Yung YC, McCreight MP, Kaushal D, Yang AH, Almeida BSV, Kingsbury MA, Cabral KMS, McConnell MJ, Anliker B, Fontanoz M, Chun J: Constitutional aneuploidy in the normal human brain. J Neurosci 2005; 25:2176-2180. Abstract

McClellan JM, ESusser E, King M-C: Maternal famine, de novo mutations, and schizophrenia. JAMA 2006; 296:582-584. Abstract

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Todd LenczAnil Malhotra (SRF Advisor)
Submitted 30 March 2008
Posted 30 March 2008

The new study by Walsh et al. (2008), as well as recent data from other groups working in schizophrenia, autism, and mental retardation, make a strong case for including copy number variants as an important source of risk for neurodevelopmental phenotypes. These findings raise several intriguing new questions for future research, including: the degree of causality/penetrance that can be attributed to individual CNVs; diagnostic specificity; and recency of their origins. While these questions are difficult to address in the context of private mutations, one potential source of additional information is the examination of common, recurrent CNVs, which have not yet been systematically studied as potential risk factors for schizophrenia.

Still, the association of rare CNVs with schizophrenia provides additional evidence that genetic transmission patterns may be a complex hybrid of common, low-penetrant alleles and rare, highly penetrant variants. In diseases ranging from Parkinson's to colon cancer, the literature demonstrates that rare penetrant loci are frequently embedded within an otherwise complex disease. Perhaps the most well-known example involves mutations in amyloid precursor protein and the presenilins in Alzheimer’s disease (AD). Although extremely rare, accounting for <1 percent of all cases of AD, identification of these autosomal dominant subtypes greatly enhanced understanding of pathophysiology. Similarly, a study of consanguineous families in Iran has very recently identified a rare autosomal recessive form of mental retardation (MR) caused by glutamate receptor (GRIK2) mutations, thereby opening new avenues of research (Motazacker et al., 2007). In schizophrenia, we have recently employed a novel, case-control approach to homozygosity mapping (Lencz et al., 2007), resulting in several candidate loci that may harbor highly penetrant recessive variants. Taken together, these results suggest that a diversity of methodological approaches will be needed to parse genetic heterogeneity in schizophrenia.

References:

Motazacker MM, Rost BR, Hucho T, Garshasbi M, Kahrizi K, Ullmann R, Abedini SS, Nieh SE, Amini SH, Goswami C, Tzschach A, Jensen LR, Schmitz D, Ropers HH, Najmabadi H, Kuss AW. (2007) A defect in the ionotropic glutamate receptor 6 gene (GRIK2) is associated with autosomal recessive mental retardation. Am J Hum Genet. 81(4):792-8. Abstract

Lencz T, Lambert C, DeRosse P, Burdick KE, Morgan TV, Kane JM, Kucherlapati R,Malhotra AK (2007). Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia. Proc Natl Acad Sci U S A. 104(50):19942-7. Abstract

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Ben Pickard
Submitted 31 March 2008
Posted 31 March 2008

In my mind, the study of CNVs in autism (and likely soon in schizophrenia/bipolar disorder, which are a little behind) is likely to put biological meat on the bones of illness etiology and finally lay to rest the annoyingly persistent taunts that genetics hasn’t delivered on its promises for psychiatric illness.

I don’t think it’s necessary at the moment to wring our hands at any inconsistencies between the Walsh et al. and previous studies of CNV in schizophrenia (e.g., Kirov et al., 2008). There are a number of factors which I think are going to influence the frequency, type, and identity of CNVs found in any given study.

1. CNVs are going to be found at the rare/penetrant/familial end of the disease allele spectrum—in direct contrast to the common risk variants which are the targets of recent GWAS studies. In the short term, we are likely to see a large number of different CNVs identified. The nature of this spectrum, however, is that there will be more common pathological CNVs which should be replicated sooner—NRXN1, APBA2 (Kirov et al., 2008), CNTNAP2 (Friedman et al., 2008)—and may be among some of these “low hanging fruit.” For the rarer CNVs, proving a pathological role is going to be a real headache. Large studies or meta-analyses are never going to yield significant p-values for rare CNVs which, nevertheless, may be the chief causes of illness for those few individuals who carry them. Showing clear segregation with illness in families is likely to be the only means to judge their role. However, we must not expect a pure cause-and-effect role for all CNVs: even in the Scottish t(1;11) family disrupting the DISC1 gene, there are several instances of healthy carriers.

2. Sample selection is also likely to be critical. In the Kirov paper, samples were chosen to represent sporadic and family history-positive cases equally. In the Walsh paper, samples were taken either from hospital patients (the majority) or a cohort of childhood onset schizophrenia. Detailed evidence for family history on a case-by-case basis was not given but appeared far stronger in the childhood onset cases. CNVs appeared to be more prevalent, and as expected, more familial, in the latter cohort. A greater frequency was also observed in the Kirov study familial subset.

3. Inclusion criteria are likely to be important—particularly in the more sporadic cases without family history. This is because CNVs found in this group may be commoner and less penetrant—they will be more frequent in cases than in controls but not exclusively found in cases. Any strategy, such as that used in the Kirov paper, which discounts a CNV based on its presence—even singly—in the control group is likely to bias against this class.

4. Technical issues. Certainly, the coverage/sensitivity of the method of choice for the “event discovery” stage is going to influence the minimum size of CNV detectable. However, a more detailed coverage often comes with a greater false-positive rate. Technique choice may also have more general issues. In both of the papers, the primary detection method is based on hybridization of case and pooled control genomes prior to detection on a chip. Thus, a more continuously distributed output may result—and the extra round of hybridization might bias against certain sequences. More direct primary approaches such as Illumina arrays or a second-hand analysis of SNP genotyping arrays may provide a more discrete copy number output, but these, too, can suffer from interpretational issues.

The other major implication of these and other CNV studies is the observation that certain genes “ignore” traditional disease boundaries. For example, NRXN1 CNVs have now been identified in autism and schizophrenia, and CNTNAP2 translocations/CNVs have been described in autism, Gilles de la Tourette syndrome, and schizophrenia/epilepsy. This mirrors the observation of common haplotypes altering risk across the schizophrenia-bipolar divide in numerous association studies. It might be the case that these more promiscuous genes are likely to be involved in more fundamental CNS processes or developmental stages—with the precise phenotypic outcome being defined by other variants or environment. The presence of mental retardation comorbid with psychiatric diagnoses in a number of CNV studies suggests that this might be the case. I look forward to the Venn diagrams of the future which show us the shared neuropsychiatric and disease-specific genes/gene alleles. It will also be interesting to see if the large deletions/duplications involving numerous genes give rise to more severe, familial, and diagnostically more defined syndromes or, alternatively, a more diffuse phenotype. Certainly, it has not been easy to dissect out individual gene contributions to phenotype in VCFS or the minimal region in Down syndrome.

References:

Friedman JI, Vrijenhoek T, Markx S, Janssen IM, van der Vliet WA, Faas BH, Knoers NV, Cahn W, Kahn RS, Edelmann L, Davis KL, Silverman JM, Brunner HG, van Kessel AG, Wijmenga C, Ophoff RA, Veltman JA. CNTNAP2 gene dosage variation is associated with schizophrenia and epilepsy. Mol Psychiatry. 2008 Mar 1;13(3):261-6. Abstract

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Christopher RossRussell L. Margolis
Submitted 3 April 2008
Posted 3 April 2008

We agree with the comments of Weinberger, Lencz and Malhotra, and Pickard, and the question raised by Honer about the extent to which the association may be more to mental retardation than schizophrenia. These new studies of copy number variation represent important advances, but need to be interpreted carefully.

We are now getting two different kinds of data on schizophrenia, which can be seen as two opposite poles. The first is from association studies with common variants, in which large numbers of people are required to see significance, and the strengths of the associations are quite modest. These kinds of vulnerability factors would presumably contribute a very modest increase in risk, and many taken together would cause the disease. By contrast, the “private” mutations, as identified by the Sebat study, could potentially be completely causative, but because they are present in only single individuals or very small numbers of individuals, it is difficult to be certain of causality. Furthermore, since some of them in the early-onset schizophrenia patients were present in unaffected parents, one might have to assume the contribution of a common variant vulnerability (from the other parent) as well.

If a substantial number of the private structural mutations are causal, then one might expect to have seen multiple small Mendelian families segregating a structural variant. The situation would then be reminiscent of the autosomal dominant spinocerebellar ataxis, in which mutations (currently about 30 identified loci) in multiple different genes result in similar clinical syndromes. The existence of many small Mendelian families would be less likely if either 1) structural variants that cause schizophrenia nearly always abolish fertility, or 2) some of the SVs detected by Walsh et al. are risk factors, but are usually not sufficient to cause disease. The latter seems more likely.

We think these two poles highlight the continued importance of segregation studies, as have been used for the DISC1 translocation. In order to validate these very rare “private” copy number variations, we believe that it would be important to look for sequence variations in the same genes in large numbers of schizophrenia and control subjects, and ideally to do so in family studies.

One very exciting result of the new copy number studies is the implication of whole pathways rather than just single genes. This highlights the importance of a better understanding of pathogenesis. The study of candidate pathways should help facilitate better pathogenic understanding, which should result in better biomarkers and potentially improve classification and treatment. In genetic studies, development of pathway analysis will be fruitful. Convergent evidence can come from studies of pathogenesis in cell and animal models, but this will need to be interpreted with caution, as it is possible to make a plausible story for so many different pathways (Ross et al., 2006). The genetic evidence will remain critical.

References:

Ross CA, Margolis RL, Reading SA, Pletnikov M, Coyle JT. Neurobiology of schizophrenia. Neuron. 2006 Oct 5;52(1):139-53. Abstract

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Michael Owen, SRF AdvisorMichael O'Donovan (SRF Advisor)George Kirov
Submitted 15 April 2008
Posted 15 April 2008

The idea that a proportion of schizophrenia is associated with rare chromosomal abnormalities has been around for some time, but it has been difficult to be sure whether such events are pathogenic given that most are rare. Two instances where a pathogenic role seems likely are first, the balanced ch1:11 translocation that breaks DISC1, where pathogenesis seems likely due to co-segregation with disease in a large family, and second, deletion of chromosome 22q11, which is sufficiently common for rates of psychosis to be compared with that in the general population. This association came to light because of the recognizable physical phenotype associated with deletion of 22q11, and the field has been waiting for the availability of genome-wide detection methods that would allow the identification of other sub-microscopic chromosomal abnormalities that might be involved, but whose presence is not predicted by non-psychiatric syndromal features. This technology is now upon us in the form of various microarray-based methods, and we can expect a slew of studies addressing this hypothesis in the coming months.

Structural chromosomal abnormalities can take a variety of forms, in particular, deletions, duplication, inversions, and translocations. Generally speaking, these can disrupt gene function by, in the case of deletions, insertions and unbalanced translocations, altering the copy number of individual genes. These are sometimes called copy number variations (CNVs). Structural chromosomal abnormalities can also disrupt a gene sequence, and such disruptions include premature truncation, internal deletion, gene fusion, or disruption of regulatory or promoter elements.

It is, however, worth pointing out that structural chromosomal variation in the genome is common—it has been estimated that any two individuals on average differ in copy number by a total of around 6 Mb, and that the frequency of individual duplications or deletions can range from common through rare to unique, much in the same way as other DNA variation. Also similar to other DNA variation, many structural variants, indeed almost certainly most, may have no phenotypic effects (and this includes those that span genes), while others may be disastrous for fetal viability. Walsh and colleagues have focused upon rare structural variants, and by rare they mean events that might be specific to single cases or families. For this reason, they specifically targeted CNVs that had not previously been described in the published literature or in the Database of Genomic Variants. The reasonable assumption was made that this would enrich for CNVs that are highly penetrant for the disorder. Indeed, Walsh et al. favor the hypothesis that genetic susceptibility to schizophrenia is conferred not by relatively common disease alleles but by a large number of individually rare alleles of high penetrance, including structural variants. As we have argued elsewhere (Craddock et al., 2007), it seems entirely plausible that schizophrenia reflects a spectrum of alleles of varying effect sizes including common alleles of small effect and rare alleles of larger effect, but data from genetic epidemiology do not support the hypothesis that the majority of the disorder reflects rare alleles of large effect.

Walsh et al. found that individuals with schizophrenia were >threefold more likely than controls to harbor rare CNVs that impacted on genes, but in contrast, found no significant difference in the proportions of cases and controls carrying rare mutations that did not impact upon genes. They also found a similar excess of rare structural variants that deleted or duplicated one or more genes in an independent series of cases and controls, using a cohort with childhood onset schizophrenia (COS).

The results of the Walsh study are important, and clearly suggest a role for structural variation in the etiology of schizophrenia. There are, however, a number of caveats and issues to consider. First, it would be unwise on the basis of that study to speculate on the likely contribution of rare variants to schizophrenia as a whole. It is likely correct that, due to selection pressures, highly penetrant alleles for disorders (like schizophrenia) that impair reproductive fitness are more likely to be of low frequency than they are to be common, but this does not imply that the converse is true. That is, one cannot assume that the penetrance of low frequency alleles is more likely to be high than low. Thus, and as pointed out by Walsh et al., it is not possible to know which or how many of the unique events observed in their study are individually pathogenic. Whether individual loci contribute to pathogenesis (and their penetrances) is, as we have seen, hard to establish. Estimating penetrance by association will require accurate measurement of frequencies in case and control populations, which for rare alleles, will have to be very large. Alternatively, more biased estimates of penetrance can be estimated from the degree of co-segregation with disease in highly multiplex pedigrees, but these are themselves fairly rare in schizophrenia, and pedigrees segregating any given rare CNV obviously even more so.

As Weinberger notes, the case for high penetrance (at the level of being sufficient to cause the disorder) is also undermined by their data from COS, where the majority of variants were inherited from unaffected parents. This accords well with the observation that 22q11DS, whilst conferring a high risk of schizophrenia, is still only associated with psychosis in ~30 percent of cases. It also accords well with the relative rarity of pedigrees segregating schizophrenia in a clearly Mendelian fashion, though the association of CNVs with severe illness of early onset might be expected to reduce the probability of transmission.

Third, there are questions about the generality of the findings. Cases in the case control series were ascertained in a way that enriched for severity and chronicity. Perhaps more importantly, the CNVs were greatly overrepresented in people with low IQ. Thus, one-third of all the potentially pathogenic CNVs in the case control series were seen in the tenth of the sample with IQ less than 80. The association between structural variants and low IQ is well known, as is the association between low IQ and psychotic symptoms, and it seems plausible to assume that forms of schizophrenia accompanied by mental retardation (MR) are likely to be enriched for this type of pathogenesis. The question that arises is whether the CNVs in such cases act simply by influencing IQ, which in turn has a non-specific effect on increasing risk of schizophrenia, or whether there are specific CNVs for MR plus schizophrenia, and some which may indeed increase risk of schizophrenia independent of IQ. In the case of 22q11 deletion, risk of schizophrenia does not seem to be dependent on risk of MR, but more work is needed to establish that this applies more generally.

Another reason to caution about the generality of the effect is that Walsh et al. found that cases with onset of psychotic symptoms at age 18 or younger were particularly enriched for CNVs, being greater than fourfold more likely than controls to harbor such variants. There did remain an excess of CNVs in cases with adult onset, supporting a more general contribution, although it should be noted that even in this group with severe disorder, this excess was not statistically significant (Fisher’s exact test, p = 0.17, 2-tailed, our calculation). The issue of age of onset clearly impacts upon assessing the overall contribution CNVs may make upon psychosis, since onset before 18, while not rare, is also not typical. A particular contribution of CNVs to early onset also appears supported by the second series studied, which had COS. However, this is a particularly unusual form of schizophrenia which is already known to have high rates of chromosomal abnormalities. Future studies of more typical samples will doubtless bear upon these issues.

Even allowing for the fact that many more CNVs may be detected as resolution of the methodology improves, the above considerations suggest it is premature to conclude a substantial proportion of cases of schizophrenia can be attributed to rare, highly penetrant CNVs. Nevertheless, even if it turns out that only a small fraction of the disorder is attributable to CNVs, as seen for other rare contributors to the disorder (e.g., DISC1 translocation), such uncommon events offer enormous opportunities for advancing our knowledge of schizophrenia pathogenesis.

References:

Craddock N, O'Donovan MC, Owen MJ. Phenotypic and genetic complexity of psychosis. Invited commentary on ... Schizophrenia: a common disease caused by multiple rare alleles.Br J Psychiatry. 2007 90:200-3. Abstract

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Ridha JooberPatricia Boksa
Submitted 2 May 2008
Posted 4 May 2008

Walsh et al. claim that rare and severe chromosomal structural variants (SVs) (i.e., not described in the literature or in the specialized databases as of November 2007) are highly penetrant events each explaining a few, if not singular, cases of schizophrenia.

However, their definition of rareness is questionable. Indeed, it is unclear why SVs that are rare (<1 percent) but previously described should be omitted from their analysis. In addition, contrary to their own definition of rareness, the authors included in the COS sample several SVs that have been previously mentioned in the literature (e.g. “115 kb deletion on chromosome 2p16.3 disrupting NRXN1”). Furthermore, some of these SVs (entire Y chromosome duplication) are certainly not rare (by the authors’ definition), nor highly penetrant with regard to psychosis (Price et al., 1967). Finally, as their definition of rareness depends on a specific date, the results of this study will change over time.

As to the assessment of severity, it can equally be concluded from table 2 and using their statistical approach that "patients with schizophrenia are significantly more likely to harbor rare structural variants (6/150) that do not disrupt any gene compared to controls(2/268) (p = 0.03)", thus contradicting their claim. In fact, had they used criteria in the literature (Lee et al., 2007; (Brewer et al., 1999) (i.e., deletion SVs are more likely than duplications to be pathogenic) and appropriate statistical contrasts, deletions are significantly (p = 0.02) less frequent in patients (5/23) than in controls (9/13) who have SVs. In addition, the assumption of high penetrance is questionable given the high level (13 percent) of non-transmitted SVs in parents of COS patients. Is the rate of psychosis proportionately high in the parents? From the data presented, we know that only 2/27 SVs in COS patients are de novo and that “some” SVs are transmitted. Adding this undetermined number of transmitted SVs to the reported non-transmitted SVs will lead to an even larger proportion of parents carrying SVs. Disclosing the inheritance status of SVs in COS patients along with information on diagnoses in parents from this “rigorously characterised cohort,” represents a major criterion for assessing the risk associated with these SVs.

Consequently, it appears that the argument of rareness is rather idiosyncratic and contains inconsistencies, and the one of severity is very open to interpretation. Most importantly, it should be emphasized that amalgamated gene effects at the population level do not allow one to conclude that any single SV actually contributes to schizophrenia in an individual. Thus it is unclear how this study of grouped events differs from the thousands of controversial and underpowered association studies of single genes.

References:

Price WH, Whatmore PB. Behaviour Disorders and Pattern of Crime among XYY males Identified at a Maximum Security Hospital. Brit Med J 1967;1:533-6.

Lee C, Iafrate AJ, Brothman AR. Copy number variations and clinical cytogenetic diagnosis of constitutional disorders. Nat Genet 2007 July;39(7 Suppl):S48-S54.

Brewer C, Holloway S, Zawalnyski P, Schinzel A, FitzPatrick D. A chromosomal duplication map of malformations: regions of suspected haplo- and triplolethality--and tolerance of segmental aneuploidy--in humans. Am J Hum Genet 1999 June;64(6):1702-8.

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Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  David J. Porteous, SRF Advisor
Submitted 11 February 2009
Posted 12 February 2009

The answer is unequivocally, “yes”
In co-highlighting the papers from Need et al., 2009, and Tomppo et al., 2009, you pose the question “CNV’s, interacting loci or both?” to which my immediate answer is an unequivocal “yes,” but it actually goes further than that. These two studies, interesting in their own rights, add just two more pieces of evidence now accumulated from case only, case-control, and family-based linkage on the genetic architecture of schizophrenia. Thus, we can reject with confidence a single evolutionary and genetic origin for schizophrenia. If it were so, it would have been found already by the plethora of genomewide studies now completed, studies specifically designed to detect causal variants, should they exist, which are both common to most if not all subjects and ancient in origin—the Common Disease, Common Variant (CDCV) hypothesis.

Moreover, for DISC1, NRG1, NRXN1, and a few others, the criteria for causality are met in some subjects, but none of these is the sole cause of schizophrenia. Their net contributions to individual and population risk remain uncertain and await large scale resequencing as well as SNP and CNV studies to capture the totality of genetic variation and how that contributes to the incidence of major mental illness. Meanwhile, nosological and epidemiological evidence has also forced a re-evaluation of the categorical distinction between schizophrenia and bipolar disorder, let alone schizoaffective disorder (Lichtenstein et al., 2009).

In this regard, DISC1 serves again as an instructive paradigm, with good evidence for genetic association to schizophrenia, BP, schizoaffective disorder, and beyond (Chubb et al., 2008). The study by Hennah et al. (2008) added a further nuance to the DISC1 story by demonstrating intra-allelic interaction. Tomppo et al. (2009) now build upon their earlier evidence to show that DISC1 variants affect subcomponents of the psychiatric phenotype, treated now as a quantitative than a dichotomous trait. In much the same way and just as would be predicted, DISC1 variation also contributes to normal variation in human brain development and behavior (e.g., Callicott et al., 2005). Self-evidently, different classes of genetic variants (SNP or CNV, regulatory or coding) will have different biological and therefore psychiatric consequences (Porteous, 2008).

That Need et al. (2009) failed to replicate previous genomewide association studies (or find support for DISC1, NRG1, and the rest) is just further proof, if any were needed, that there is extensive genetic heterogeneity and that common variants of ancient origin are not major determinants of individual or population risk (Porteous, 2008). Variable penetrance, expressivity, and gene-gene interaction (epistasis) all need to be considered, but these intrinsic aspects of genetic influence are best addressed by family studies (currently lacking for CNV studies) and poorly addressed by large-scale case-control genomewide association studies. Power to test the CDCV hypothesis may increase with increasing numbers of subjects, but so does the inherent heterogeneity, both genetic and diagnostic.

That said, genetics is without doubt the most incisive tool we have to dissect the etiology of major mental illness. The criteria for success (and certainly for causality, rather than mere correlation) must be less about the number of noughts after the “p” and much more about the connection between candidate gene, gene variant, and the biological consequences for brain development and function. In this regard, both studies have something to say and offer.

References:

Lichtenstein P, Yip BH, Björk C, Pawitan Y, Cannon TD, Sullivan PF, Hultman CM. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. 2009 Lancet 373:234-9. Abstract

Chubb JE, Bradshaw NJ, Soares DC, Porteous DJ, Millar JK. Mol Psychiatry. The DISC locus in psychiatric illness. 2008 Jan;13(1):36-64. Epub 2007 Oct 2. Abstract

Callicott JH, Straub RE, Pezawas L, Egan MF, Mattay VS, Hariri AR, Verchinski BA,Meyer-Lindenberg A, Balkissoon R, Kolachana B, Goldberg TE, Weinberger DR. Variation in DISC1 affects hippocampal structure and function and increases risk for schizophrenia. 2005 Proc Natl Acad Sci U S A. 2005 102:8627-32. Abstract

Porteous D. Genetic causality in schizophrenia and bipolar disorder: out with the old and in with the new. 2008 Curr Opin Genet Dev. 18:229-34. Abstract

View all comments by David J. Porteous

Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  Pamela DeRosseAnil Malhotra (SRF Advisor)
Submitted 19 February 2009
Posted 22 February 2009

The results reported by Tomppo et al. and Need et al. collectively instantiate the complexities of the genetic architecture underlying risk for psychiatric illness. Paradoxically, however, while the results of Need et al. suggest that the answer to the complex question of risk genes for schizophrenia (SZ) may be found by searching a very select population for rare changes in genetic sequence, the results of Tomppo et al. suggest that the answer may be found by searching for common variants in large heterogeneous populations. So which is it? Is SZ the result of rare, novel genetic mutations or an accumulation of common ones? Such a conundrum is not a novel predicament in the process of scientific inquiry and such conundrums are often resolved by the reconciliation of both opposing views. Thus, if we allow history to serve as our guide it seems reasonable that the answer to the current question of what genetic mechanisms are responsible for SZ, is that SZ is caused by both rare and common variants.

Although considerable efforts, by our lab and others, are currently being directed towards seeking the type of rare variants that Need et al. suggest may be responsible for risk for SZ, a less concerted effort is being directed towards parsing the effects of more specific, common genetic variations. To date, there are limited data seeking to elucidate the effects of previously identified risk variants for SZ on phenotypic variation within the diagnostic group. The data that are available, however, suggest that risk variants do influence phenotypic variation. Our work with DISC1, for example, has produced relatively robust, and replicated findings linking variation in the gene to cognitive dysfunction (Burdick et al., 2005) as well as an increased risk for persecutory delusions in SZ (DeRosse et al., 2007). Similarly, our work with DTNBP1 indicates a strong association between variants in the gene and both cognitive dysfunction (Burdick et al., 2006) and negative symptoms in SZ (DeRosse et al., 2006). Moreover, the risk for cognitive dysfunction associated with the DTNBP1 risk genotype was also observed in a sample of healthy individuals. Thus, it seems conceivable that genetic variation associated with phenotypic variation within a diagnostic group may also be associated with similar, sub-syndromal phenotypes in non-clinical samples.

The data reported by Tomppo et al. provide support for the utility of parsing the specific effects of genetic variants on phenotypic variation and extend this approach to populations with sub-syndromal psychiatric symptoms. Such an approach is attractive in that it allows us to study the effects of genotype on phenotype without the confound imposed by psychotropic medications. Although the current data linking genes to specific dimensions of psychiatric illness are provocative, the study groups utilized are comprised of patients undergoing varying degrees of pharmacological intervention. Thus, in these analyses quantitative assessment of psychosis is to some extent confounded by treatment history and response. By measuring lifetime history of symptoms, which for most patients includes substantial periods without effective medication, many studies (including our own) may partially overcome this limitation. Still, assessment of the relation between genetic variation and dimensions of psychosis in study groups not undergoing treatment with pharmacological agents would be a compelling source of confirmation for these preliminary findings.

Perhaps most importantly, the data reported by Tomppo et al. suggest that previously identified risk genes should not be marginalized but rather, should be studied in non-clinical samples to identity phenotypic variation that may be related to the signs and symptoms of psychiatric illness.

References:

Burdick KE, Hodgkinson CA, Szeszko PR, Lencz T, Ekholm JM, Kane JM, Goldman D, Malhotra AK. DISC1 and neurocognitive function in schizophrenia. Neuroreport. 2005; 16(12):1399-402. Abstract

Burdick KE, Lencz T, Funke B, Finn CT, Szeszko PR, Kane JM, Kucherlapati R, Malhotra AK. Genetic variation in DTNBP1 influences general cognitive ability. Hum Mol Genet. 2006; 15(10):1563-8. Abstract

DeRosse P, Hodgkinson CA, Lencz T, Burdick KE, Kane JM, Goldman D, Malhotra AK. Disrupted in schizophrenia 1 genotype and positive symptoms in schizophrenia. Biol Psychiatry. 2007; 61(10):1208-10. Abstract

DeRosse P, Funke B, Burdick KE, Lencz T, Ekholm JM, Kane JM, Kucherlapati R, Malhotra AK. Dysbindin genotype and negative symptoms in schizophrenia. Am J Psychiatry. 2006; 163(3):532-4. Abstract

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Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  James L. Kennedy, SRF Advisor (Disclosure)
Submitted 25 February 2009
Posted 25 February 2009

Has anyone considered the possibility that the CNVs found to be elevated in schizophrenia versus controls could be a peripheral effect and perhaps not present in brain tissue? For example, the diet of the typical schizophrenia patient is poor, and it is conceivable that chronic folate deficiency could predispose to problems in DNA structure or repair in lymphocytes. Thus, the CNVs could be an effect of the illness, and not a cause. Someone needs to do the experiment that compares CNVs in blood to those in the brain of the same individual. And then we need studies of the stability of CNVs over the lifetime of an individual.

View all comments by James L. Kennedy

Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  Kevin J. Mitchell
Submitted 2 March 2009
Posted 2 March 2009

The papers by Need et al. and Tomppo et al. seem to present conflicting evidence for the involvement of common or rare variants in the etiology of schizophrenia.

On the one hand, Need et al., in a very large and well-powered sample, find no evidence for involvement of any common SNPs or CNVs. Importantly, they show that while any one SNP with a small effect and modest allelic frequency might be missed by their analysis, the likelihood that all such putative SNPs would be missed is vanishingly small. They come to the reasonable conclusion that common variants are unlikely to play a major role in the etiology of schizophrenia, except under a highly specific and implausible genetic model. Does this sound the death knell for the common variants, polygenic model of schizophrenia? Yes and no. These and other empirical data are consistent with theoretical analyses which show that the currently popular purely polygenic model, without some gene(s) of large effect, cannot explain familial risk patterns (Hemminki et al., 2007; Hemminki et al., 2008; Bodmer and Bonilla, 2008). It has been suggested that epistatic interactions may generate discontinuous risk from a continuous distribution of common alleles; however, while comparisons of risk in monozygotic and dizygotic twins are consistent with some contribution from epistasis, they are not consistent with the massive levels that would be required to rescue a purely polygenic mechanism, whether through a multiplicative or (biologically unrealistic) threshold model.

Thus, it seems most parsimonious to conclude that most cases of schizophrenia will involve a variant of large effect. As such variants are likely to be rapidly selected against, they are also likely to be quite rare. The findings of specific, gene-disrupting CNVs or mutations in individual genes in schizophrenia cases by Need et al. and numerous other groups support this idea. Excitingly, they also have highlighted specific molecules and biological pathways that provide molecular entry points to elucidate pathogenic mechanisms. The possible convergence on genes interacting with DISC1, including PCM1 and NDE1 in the current study, provides further support for the importance of this pathway, though, clearly, there may be many other ways to disrupt neural development or function that could lead to schizophrenia. (Conversely, it is becoming clearer that many of the putative causative mutations identified so far predispose to multiple psychiatric or neurological conditions.)

Despite the likely involvement of rare variants in most cases of schizophrenia, it remains possible that common alleles could have a modifying influence on risk—indeed, one early paper commonly cited as supporting a polygenic model for schizophrenia actually provided strong support for a model of a single gene of large effect and two to three modifiers (Risch, 1990). A rare variants/common modifiers model would be consistent with the body of literature on modifying genes in model organisms, where effects of genetic background on the phenotypic expression of particular mutations are quite common and can sometimes be large (Nadeau, 2001). Whether such genetic background effects would be mediated by common or rare variants is another question—there is certainly good reason to think that rare or even private mutations may make a larger contribution to phenotypic variance than previously suspected (Ng et al., 2008; Ji et al., 2008).

Nevertheless, common variants are also likely to be involved, and these effects might be detectable in large association studies, though they would be expected to be diluted across genotypes. This might explain inconsistent findings of association of common variants with disease state for various genes, including COMT, BDNF, and DISC1, for example. This issue has led some to look for association of variants in these genes with endophenotypes of schizophrenia in the general population—psychological or physiological traits that are heritable and affected by the symptoms of the disease, such as working memory, executive function, or, in the study by Tomppo et al., social interaction.

These approaches have tended to lead to statistically stronger and more consistent associations and are undoubtedly revealing genes and mechanisms contributing to normal variation in many psychological traits. How this relates to their potential involvement in disease etiology is far from clear, however. The implication of the endophenotype model is that the disorder itself emerges due to the combination of minor effects on multiple symptom parameters (Gottesman and Gould, 2003; Meyer-Lindenberg and Weinberger, 2006). An alternative interpretation is that these common variants may modify the phenotypic expression of some other rare variant, either due to their demonstrated effect on the psychological trait in question or through a more fundamental biochemical interaction, but that in the absence of such a variant of large effect, no combination of common alleles would lead to disease.

References:

Hemminki K, Försti A, Bermejo JL. The 'common disease-common variant' hypothesis and familial risks. PLoS ONE. 2008 Jun 18;3(6):e2504. Abstract

Hemminki K, Bermejo JL. Constraints for genetic association studies imposed by attributable fraction and familial risk. Carcinogenesis. 2007 Mar;28(3):648-56. Abstract

Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet. 2008 Jun;40(6):695-701. Abstract

Risch N. Linkage strategies for genetically complex traits. I. Multilocus models. Am J Hum Genet. 1990 Feb;46(2):222-8. Abstract

Nadeau JH. Modifier genes in mice and humans. Nat Rev Genet. 2001 Mar;2(3):165-74. Abstract

Ng PC, Levy S, Huang J, Stockwell TB, Walenz BP, Li K, Axelrod N, Busam DA, Strausberg RL, Venter JC. Genetic variation in an individual human exome. PLoS Genet. 2008 Aug 15;4(8):e1000160. Abstract

Ji W, Foo JN, O'Roak BJ, Zhao H, Larson MG, Simon DB, Newton-Cheh C, State MW, Levy D, Lifton RP. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat Genet. 2008 May;40(5):592-9. Abstract

Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003 Apr;160(4):636-45. Abstract

Meyer-Lindenberg A, Weinberger DR. Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat Rev Neurosci. 2006 Oct;7(10):818-27. Abstract

View all comments by Kevin J. Mitchell