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Autism Exome: Lessons for Schizophrenia?

16 April 2012. Spontaneously occurring, protein-altering mutations likely contribute to some cases of autism, according to a trio of the largest-to-date exome sequencing studies of the disorder, published April 4 in Nature. The three independent studies led by Matthew State of Yale University in New Haven, Connecticut; Evan Eichler of the University of Washington in Seattle; and Mark Daly of The Broad Institute of Harvard and MIT in Cambridge, Massachusetts, scoured the protein-coding part of the genome, called the exome, to find non-inherited “de-novo” single base pair mutations in individuals with autism. This fingered some new genes (CHD8, KATNAL2, and SCN2A), but also has cast autism as a heterogeneous disorder caused by glitches in at least many hundreds of different genes.

Though schizophrenia and autism may share some genetic liability (see SRF related news story), the studies hold lessons for schizophrenia, not so much for the particular genes they turn up, but for how to make sense of the contributions of rare variants to disease. Just a few years ago, rare genetic abnormalities like copy number variants evoked a smoking gun for some (see SRF related news story). More recently, sequencing has turned up rare events that seem particularly nasty: protein-altering variants in the exome that were also “de novo”—that is, arising spontaneously and not inherited from parents, and so their phenotypic consequences have not yet been tempered by natural selection. Eichler’s group recently used this exome-de novo approach to identify some potentially causal variants in a small autism sample (O’Roak et al., 2012), and two other studies last year did the same for schizophrenia (see SRF related news story and SRF news story).

But the interpretive obstacle here is that rare events are common—that is, everyone carries some kind of protein-coding variant (Pelak et al., 2010). As the sequencers ratchet up their output, researchers are getting a better estimate of the frequency of these sorts of variants in controls, and the three new studies use these estimates, and other approaches, to gauge a particular variant’s role in autism.

And in schizophrenia, even targeted resequencing of those genes with a long history of association with the disorder does not necessarily produce the goods. A fourth study published online April 3 in Molecular Psychiatry from Patrick Sullivan of the University of North Carolina in Chapel Hill and Richard Gibbs of Baylor University in Houston, Texas, re-sequenced portions of the genes considered to be classic schizophrenia players, and found no variants associated with the disorder.

Trios and quartets
In State’s study, first author Stephan Sanders and colleagues sequenced the exomes of 928 individuals from 238 families in the Simons Simplex Collection (SSC), which consists of “sporadic” cases of autism without a family history of the disorder. The families consisted of an individual with autism, two unaffected parents, and in 200 families, an unaffected sibling—making for an extensive quartet dataset. The researchers identified 125 de-novo, disruptive single nucleotide variants that either introduced a stop codon or altered a splice site; this number was significantly greater than the 87 of such variants found in the unaffected siblings. Restricting this count to only those variants landing in genes expressed in the brain enhanced this difference, with 13 in cases and three in unaffected siblings, suggesting elevated rates of de-novo mutations in autism.

To identify genes likely to confer risk, the researchers looked for variants from unrelated individuals with autism converging on the same gene. Two individuals each carried a stop codon mutations in SCN2A (sodium channel, voltage-gated, type II, alpha subunit), a gene implicated in epilepsy, and by Sanders and colleagues' calculations, this convergence was unlikely to occur by chance. When the researchers combined their data with that from Eichler’s study, they found two more genes that were each hit by two disruptive mutations in two unrelated individuals with autism: KATNAL2 (katanin p60 subunit A-like 2) and CHD8 (chromodomain helicase DNA binding protein 8). Other ways of establishing an association of these events with autism did not pan out for State’s dataset: there was no difference in the number of de-novo mutations per person between cases and controls; mutations in cases were not necessarily more disruptive than those in controls; and the genes hit in autism cases were not particularly enriched for gene sets related to autism or other disorders, nor did they belong to functionally related sets of genes, according to pathway analysis. Despite the convergences onto three genes, the researchers’ models predicted about 1,000 risk-promoting ASD genes.

Eichler’s study surveyed 677 individual exome sequences from a different group of 209 families from the SSC that mostly consisted of parent-child trios, but also included 50 unaffected siblings. First author Brian O’Roak and colleagues found 126 de-novo point mutations that were either stop codons or judged to be “severely” protein altering. Pathway analysis indicated that a substantial 39 percent of the mutations landed in genes belonging to a protein network enriched for autism candidates, and important for β-catenin and chromatin remodeling—key processes in brain development. Four times as many mutations occurred in DNA from the father as from the mother, and the number of mutations correlated with paternal age, consistent with the increased risk of autism in children with older fathers.

The study led by Mark Daly sequenced the exomes of 175 autism trios from five different centers. First author Benjamin Neale and colleagues found 161 point mutations in all, including 101 amino acid changes and 10 premature stop codons. Only 46.3 percent of cases carried such variants, however, suggesting that these kinds of variants couldn’t account for a majority of autism. The researchers calculated a mutation rate of 0.92 de-novo events per person, per exome in their trios, which was slightly (but not significantly) elevated over the rate expected to occur by chance. These findings tempered the researchers’ views on the role of de-novo coding mutations in autism.

Still, the protein-protein interaction and pathway analyses conducted by Neale and colleagues suggested that at least some of these point mutations contribute to autism risk: the genes hit by mutation seemed biologically related, and the gene networks to which they belonged were enriched for autism candidates. When Daly’s group looked specifically at the loss-of-function mutations (nonsense, splice, or frameshift) uncovered by all three studies, they found that multiple mutations of this type at SCN2A, KATNAL2, and CHD8 were unlikely to have occurred by chance. These three genes were further evaluated in exome sequencing of 935 autism cases and 870 controls, which produced three more loss-of-function variants in CHD8 and KATNAL2 in cases, and none in controls. This strongly implicates these two genes as genuine risk factors, but they are two of many as-yet unresolved genes, which the Daly’s group estimates to be in the hundreds, each increasing risk 10-20 times.

Known unknowns
The schizophrenia study focused on 10 classic candidate genes: COMT, DAOA, DISC1, DRD2, DRD3, DTNBP1, HTR2A, NRG1, SLC6A3, and SLC6A4. Genomewide association studies do not find evidence for common variants in these genes in schizophrenia, but the researchers hypothesized that these genes may still harbor rare variants. First author JJ Crowley and colleagues re-sequenced selected regions of these genes (amounting to 16.8 kb total) in 727 cases and 733 controls, and identified 782 single nucleotide variants, 587 of which hadn’t been seen before. Of these, 92 were novel protein-altering variants (nonsense, missense, or splice site) or variants observed in more than one case. When the researchers genotyped a second sample of 2,191 cases and 2,659 controls for these variants, none were found to be overrepresented in cases compared to controls with genomewide significance. This suggests to the authors that rare coding variants in these well-known genes are not at work in schizophrenia.

The findings beg further scrutiny of the regions harboring the signals that implicated these genes in the first place. This kind of approach can lead to the vast, uncharted spaces between genes, as reported in a study published April 4 in Science Translational Medicine. The study investigates a gene-poor region of chromosome 5 that harbors a genomewide significant signal in autism GWAS, and finds evidence of involvement of a noncoding RNA (Kerin et al., 2012). The molecule is antisense to the transcripts of the gene encoding moesin (MSN), which encodes a protein regulator of neuronal shape, and it was elevated 12-fold in postmortem brain samples from individuals with autism.

As the pace of sequencing findings increases, this sort of work marks just the beginning. Larger sample sizes will need to confirm these first findings, which need to be interpreted with a better understanding of the full extent of human genetic variation. Together, the studies lurch toward ways of considering the different kinds of evidence for ruling in or ruling out a variant in disease, a process that will be informative for future genetic studies of schizophrenia and other mental disorders.—Michele Solis.

References:
Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, Ercan-Sencicek AG, DiLullo NM, Parikshak NN, Stein JL, Walker MF, Ober GT, Teran NA, Song Y, El-Fishawy P, Murtha RC, Choi M, Overton JD, Bjornson RD, Carriero NJ, Meyer KA, Bilguvar K, Mane SM, Sĕstan N, Lifton RP, Günel M, Roeder K, Geschwind DH, Devlin B, State MW. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 2012 April 5. Abstract

O’Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm N, Coe BP, Levy R, Ko A, Lee C, Smith JD, Turner EH, Stanaway IB, Vernot B, Malig M, Baker C, Reilly B, Akey JM, Borenstein E, Rieder MJ, Nickerson DA, Bernier R, Shendure J, Eichler EE. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 2012 April 5. Abstract

Neale BM, Kou Y, Liu L, Ma’ayan A, Samocha KE, Sabo A, Lin CF, Stevens C, Wang LS, Makarov V, Polak P, Yoon S, Maguire J, Crawford EL, Campbell NG, Geller ET, Valladares O, Schafer C, Liu H, Zhao T, Cai G, Lihm J, Dannenfelser R, Jabado O, Peralta Z, Nagaswamy U, Muzny D, Reid JG, Newsham I, Wu Y, Lewis L, Han Y, Voight BF, Lim E, Rossin E, Kirby A, Flannick J, Fromer M, Shakir K, Fennell T, Garimella K, Banks E, Poplin R, Gabriel S, DePristo M, Wimbish JR, Boone BE, Levy SE, Betancur C, Sunyaev S, Boerwinkle E, Buxbaum JD, Cook Jr EH, Devlin B, Gibbs RA, Roeder K, Schellenberg GD, Sutcliffe JS, Daly MJ. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 2012 April 5. Abstract

Crowley JJ, Hilliard CE, Kim Y, Morgan MB, Lewis LR, Muzny DM, Hawes AC, Sabo A, Wheeler DA, Lieberman JA, Sullivan PF, Gibbs RA. Deep resequencing and association analysis of schizophrenia candidate genes. Mol Psychiatry. 2012 Apr 3. Abstract

Comments on News and Primary Papers
Comment by:  Patrick Sullivan, SRF Advisor
Submitted 20 April 2012
Posted 23 April 2012
  I recommend the Primary Papers

Fascinating papers that likely presage work in the pipeline from multiple groups for schizophrenia. Truly groundbreaking work by some of the best groups in the business. Required reading for those interested in psychiatric genomics.

The identified loci provide important new windows into the neurobiology of ASD.

The results also pertain to the longstanding debate about the nature of ASD: does it result from many individually rare, Mendelian-like variants (potentially a different one in each person) and/or from the summation of the effects of many different common variants of subtle effects?

The multiple rare variant model now seems unlikely for ASD as, contrary to the expectations of some, ASD did not readily resolve into a handful of Mendelian-like diseases. (This comment is of course qualified by the limits of the technologies - which have, however, identified causal mutations for many monogenetic disorders.)

Readers might also want to read Ben Neale's comments on these papers at the Genomes Unzipped website.

View all comments by Patrick Sullivan

Comments on Related News


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

View all comments by William Honer

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

View all comments by Todd Lencz
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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

View all comments by Ben Pickard

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: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

Comment by:  Katie Rodriguez
Submitted 7 November 2009
Posted 7 November 2009

If schizophrenia and autism are on a spectrum, how can there be people who are both autistic and schizophrenic? I know of a few people who suffer from both diseases.

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Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

Comment by:  Bernard Crespi
Submitted 12 November 2009
Posted 12 November 2009

One Hundred Years of Insanity: The Relationship Between Schizophrenia and Autism
The great Colombian author Gabriel García Márquez reified the cyclical nature of history in his Nobel Prize-winning 1967 book, One Hundred Years of Solitude. Eugen Bleuler’s less-famous book Dementia Præcox or the Group of Schizophrenias, originally published in 1911, saw first use of the term “autism,” a form of solitude manifest as withdrawal from reality in schizophrenia. This neologism, about to celebrate its centenary, epitomizes an astonishing cycle of reification and change in nosology, a cycle only now coming into clear view as molecular-genetic data confront the traditional, age-old categories of psychiatric classification.

The term autism was, of course, redefined by Leo Kanner (1943) for a childhood psychiatric condition first considered as a subset of schizophrenia, then regarded as quite distinct (Rutter, 1972) or even opposite to it (Rimland, 1964; Crespi and Badcock, 2008), and most recently seen by some researchers as returning to its original Bluelerian incarnation (e.g., Carroll and Owen, 2009). An outstanding new paper by McCarthy et al. (2009), demonstrating that duplications of the CNV locus 16p11.2 are strongly associated with increased risk of schizophrenia, has brought this question to the forefront of psychiatric inquiry, because deletions of this same CNV are one of the most striking recently-characterized risk factors for autism. Additional CNVs, such as those at 1q21.1 and 22q11.21 have also been associated with autism and schizophrenia in one or more studies (e.g., Mefford et al., 2008; Crespi et al., 2009; Glessner et al., 2009), which has led some authors to infer that since an overlapping set of loci mediates risk of both conditions, autism and schizophrenia must be more similar than previously conceived (e.g., Carroll and Owen, 2009; Guilmatre et al., 2009). Similar considerations apply to several genes, such as CNTNAP2 and NRXN1, various disruptions of which have likewise been linked with both conditions (Iossifov et al., 2008; Kirov et al., 2008; Burbach and van der Zwaag, 2009).

So does this plethora of new molecular-genetic data imply that Blueler was indeed correct, if not prescient, that autism and schizophrenia are manifestations of similar disease processes? The answer may appear tantalizingly close, but will likely remain inaccessible without explicit consideration of alternative hypotheses and targeted tests of their differentiating predictions. This approach is simply Platt’s (1964) classic method of strong inference, which has propelled molecular biology so far and fast but left psychiatry largely by the wayside (Cannon, 2009). The alternative hypotheses in this case are clear: with regard to causation from specific genetic and genomic risk factors, autism and schizophrenia are either: 1) independent and discrete, 2) partially yet broadly overlapping, 3) subsumed with autism as a subset of schizophrenia, or 4) diametrically opposite, with normality in the centre. CNVs are especially useful for testing among such alternative hypotheses, because they naturally involve highly-penetrant perturbations in two opposite directions, due to deletions vs duplications of more or less the same genomic regions. Hypotheses 2), 3) and 4) thus predict that autism and schizophrenia should share CNV risk loci, but 2) and 3) predict specific rearrangements (deletions, duplications, or both) shared across both conditions; by contrast, hypothesis (4) predicts that, as highlighted by McCarthy et al. (2009), reciprocal CNVs at the same locus should mediate risk of autism versus schizophrenia. This general approach was pioneered by Craddock et al. (2005, 2009), in their discussion of explicit alternative hypotheses for the relationship between schizophrenia and bipolar disorder, which are now known to share a notable suite of risk alleles.

A key assumption that underlies tests of hypotheses for the relationship between autism and schizophrenia is accuracy of diagnoses. For schizophrenia, this is seldom at issue. However, diagnoses of autism, or autism spectrum disorders such as PDD-NOS, are normally made at an age well before the first manifestations of schizophrenia in adolescence or early adulthood, which generates a risk for false-positive diagnoses of premorbidity to schizophrenia as autism or autism spectrum (e.g., Eliez, 2007). The tendencies for males to exhibit worse premorbidity to schizophrenia than females (Sobin et al., 2001; Tandon et al., 2009), for CNVs to exert severe effects on diverse aspects of early neurodevelopment (Shinawi et al., 2009), and for schizophrenia of earlier onset to exhibit a higher male sex-ratio bias and a stronger tendency to be associated with CNVs rather than other causes (Remschmidt et al., 1994; Rapoport et al., 2009), all suggest a high risk for false-positive diagnoses of autistic spectrum conditions in individuals with these genomic risk factors (Feinstein and Singh, 2007; Reaven et al., 2008; Sugihara et al., 2008; Starling and Dossetor, 2009). Possible evidence of such risk comes from diagnoses of autism spectrum conditions in children with deletions at 15q11.2, 15q13.3, and 22q11.21, and duplications of 16p11.2, CNVs for which schizophrenia risk has been well established from studies of adults (Antshel et al., 2007; Stefansson et al., 2008; Weiss et al., 2008; Ben-Shachar et al., 2009; Doornbos et al., 2009; McCarthy et al., 2009). By contrast, autism-associated CNVs, such as deletions at 16p11.2 (Kumar et al., 2008), or duplications at 22q11.21 (Glessner et al., 2009; Crespi et al., 2009) have seldom also been reported in individuals diagnosed with schizophrenia, which suggests that false-positive diagnoses of schizophrenia as autism are uncommon.

Differentiating between a hypothesis of false-positive diagnoses of premorbidity to schizophrenia as autism, compared to a hypothesis of specific deletions or duplications shared between autism and schizophrenia, requires some combination of longitudinal studies, judicious use of endophenotypes, and adoption of relatively new diagnostic categories such as multiple complex developmental disorder (Sprong et al., 2008). Moreover, to the degree that such false positives are not uncommon, and autism and schizophrenia are underlain by diametric genetically based risk factors, inclusion of children premorbid for schizophrenia in studies on the genetic bases of autism will substantially dilute the probability of detecting significant results.

Ultimately, robust evaluation of alternative hypotheses for the relationship of autism with schizophrenia will require evidence from studies of common and rare SNP variants as well as CNVs, in-depth analyses of the neurodevelopmental and neuronal-function effects of different alterations to genes such as NRXN1, CNTNAP2, and SHANK3, and integrative data from diverse disciplines other than genetics, especially the neurosciences and psychology. Unless such interdisciplinary studies are deployed—in hypothesis-testing frameworks that use strong inference—we should expect to remain, as penned by García Márquez, in “permanent alternation between excitement and disappointment, doubt and revelation, to such an extreme that no one knows for certain where the limits of reality lay”—for yet another 100 years.

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Carroll LS, Owen MJ. Genetic overlap between autism, schizophrenia and bipolar disorder. Genome Med. 2009 Oct 30;1(10):102. Abstract

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Craddock N, O'Donovan MC, Owen MJ. Psychosis genetics: modeling the relationship between schizophrenia, bipolar disorder, and mixed (or "schizoaffective") psychoses. Schizophr Bull. 2009 May;35(3):482-90. Abstract

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View all comments by Bernard Crespi

Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

Comment by:  Suzanna Russell-SmithDonna BaylissMurray Maybery
Submitted 9 February 2010
Posted 10 February 2010

The Diametric Opposition of Autism and Psychosis: Support From a Study of Cognition
As has been noted previously, Crespi and Badcock’s (2008) theory that autism and schizophrenia are diametrically opposed disorders is certainly a novel and somewhat controversial one. In his recent blog on Psychology Today, Badcock states that the theory stands on two completely different foundations: one in evolution and genetics, and one in psychiatry and cognitive science (Badcock, 2010). While most of the comments posted before ours have addressed the relationship between autism and schizophrenia from a genetic perspective, coming from a psychology background, we note that it is the aspects of Crespi and Badcock’s theory that relate to cognition which have particularly caught our attention. While we can therefore contribute little to the discussion of a relationship between autism and schizophrenia from a genetic standpoint, we present the findings from our recent study (Russell-Smith et al., 2010), which provided the first test of Crespi and Badcock’s claim that autism and psychosis are at opposite ends of the cognitive spectrum.

In placing autism and psychosis at opposite ends of the cognitive spectrum, Crespi and Badcock (2008) propose that autistic and positive schizophrenia traits contrastingly affect preference for local versus global processing, with individuals with autism displaying a preference for local processing and individuals with positive schizophrenia displaying a preference for global processing. That is, these authors claim that while individuals with autism show a tendency to focus on detail or process features in their isolation, individuals with positive schizophrenia show a tendency to look at the bigger picture or process features as an integrated whole. Importantly, since Crespi and Badcock argue for a continuum stretching all the way from autism to psychosis, the same diametric pattern of cognition should be seen in individuals who display only mild variants of autistic and positive schizophrenia traits. This includes typical individuals who score highly on measures such as the Autism Spectrum Quotient (AQ; Baron-Cohen et al., 2001) and the Unusual Experiences subscale of the Oxford-Liverpool Inventory of Experiences (O-LIFE:UE; Mason et al., 2005). These are both reliable and commonly used measures which have been specifically designed to assess the levels of “autistic-like” traits and positive schizotypy traits in typical individuals. Since Crespi and Badcock actually argue their theory is best evaluated with reference to individuals with milder traits of autism and positive schizophrenia, it is with these populations that we investigated their claims.

A task often used to determine whether an individual has a preference for local over global processing is the Embedded Figures Test (EFT; Witkin et al., 1971), which requires individuals to detect hidden shapes within complex figures. As the test requires one to resist experiencing an integrated visual stimulus or gestalt in favor of seeing single elements, it is argued that a local processing style aids successful (i.e., faster) completion of this task (Bolte et al., 2007). Accordingly, from Crespi and Badcock’s (2008) theory, one would expect that relative to individuals with low levels of these traits, individuals with high levels of autistic-like traits should perform better on the EFT, while individuals with positive schizotypy traits should perform worse. To test this claim, our study obtained the AQ and O-LIFE:UE scores for 318 students completing psychology as part of a broader degree (e.g., a BSc or BA). Two pairs of groups (i.e., four groups in total), each consisting of 20 students, were then formed. One of these pairs consisted of High and Low AQ groups, which were selected such that they were separated substantially in their AQ scores but matched as closely as possible on their O-LIFE:UE scores. The other pair of groups, the High and Low O-LIFE:UE groups, were selected such that they were separated in their O-LIFE:UE scores, but matched as closely as possible on their AQ scores. The gender ratio was matched closely across the four groups.

To test the prediction that higher levels of autistic-like traits are associated with more skilled EFT performance, the High and Low AQ groups were compared in terms of their mean response time to accurately locate each of the embedded figures. Individuals in the High AQ group did display more skilled EFT performance than individuals in the Low AQ group, consistent with a greater preference for local over global processing in relation to higher levels of autistic-like traits (see also Almeida et al., 2010; Bolte and Poustka, 2007; Grinter et al., 2009; Grinter et al., 2009). We then compared EFT performance for the O-LIFE:UE groups to test the prediction that higher levels of positive schizotypy traits are associated with less skilled performance on this task. Consistent with a preference for global over local processing in relation to higher levels of positive schizotypy traits, individuals in the High O-LIFE:UE group displayed less skilled EFT performance than individuals in the Low O-LIFE:UE group. Therefore, results from both pairs of groups together provide support for Crespi and Badcock’s (2008) claim that autistic and positive schizophrenia traits are diametrically opposed with regard to their effect on local versus global processing.

However, the support our study offers for Crespi and Badcock’s (2008) theory was tempered slightly by our failure to find the expected contrasting patterns of non-verbal relative to verbal ability for our two pairs of groups. To display the expected patterns, relative to individuals with low levels of these traits, individuals with high levels of autistic-like traits should have displayed higher non-verbal ability relative to verbal ability, whereas individuals with high levels of positive schizotypy traits should have displayed lower non-verbal relative to verbal ability. While visual inspection of mean verbal and non-verbal scores for the O-LIFE:UE groups revealed a trend consistent with what would be expected based on Crespi and Badcock’s theory, none of the group differences was statistically significant. However, as we pointed out in our article, a study which offers a more complete assessment of this aspect of the theory is warranted. In particular, since the use of a student sample in our study no doubt led to a restriction in the range of IQ scores (especially with reference to verbal IQ), a test of community-based samples would be useful.

Therefore, while Crespi and Badcock’s (2008) theory has passed its first major test at the level of cognition, with our results indicating a contrasting effect of autistic-like and positive schizotypy traits with regard to preference for local versus global processing, further investigation of these authors’ theory at both the cognitive and genetic levels is required.

References:

Almeida, R., Dickinson, J., Maybery, M., Badcock, J., Badcock, D. A new step toward understanding Embedded Figures Test performance in the autism spectrum: The radial frequency search task. Neuropsychologia. 2010 Jan;48(2):374-81. Abstract

Badcock, C. (2010). Diametric cognition passes its first lab test. Psychology Today. Retrieved February 8, from http://www.psychologytoday.com/blog/the-imprinted-brain/201002/diametric-cognition-passes-its-first-lab-test.

Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., Clubley, E. (2001). The Autism-Spectrum Quotient (AQ): Evidence from Asperger Syndrome/High-Functioning Autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 5-17. Abstract

Bolte, S., Holtmann, M., Poustka, F., Scheurich, A., Schmidt, L. (2007). Gestalt perception and local-global processing in High-Functioning Autism. Journal of Autism and Developmental Disorders, 37, 1493-1504. Abstract

Bolte, S., Poustka, F. (2006). The broader cognitive phenotype of autism in parents: How specific is the tendency for local processing and executive function. Journal of Child Psychology and Psychiatry, 47, 639-645. Abstract

Crespi, B., Badcock, C. (2008). Psychosis and autism as diametrical disorders of the social brain. Behavioral and Brain Sciences, 31, 241-261. Abstract

Grinter, E., Maybery, M., Van Beek, P., Pellicano, E., Badcock, J., Badcock, D. (2009). Global visual processing and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 1278-1290. Abstract

Grinter, E., Van Beek, P., Maybery, M., Badcock, D. (2009). Brief Report: Visuospatial analysis and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 670–677. Abstract

Mason, O., Linney, Y., Claridge, G. (2005). Short scales for measuring schizotypy. Schizophrenia Research, 78, 293-296. Abstract

Russell-Smith, S., Maybery, M., Bayliss, D. Are the autism and positive schizotypy spectra diametrically opposed in local versus global processing? Journal of Autism and Developmental Disorders. 2010 Jan 28. Abstract

Witkin, H., Oltman, P., Raskin, E., Karp, S. (1971). A manual for the Embedded Figures Test. Palo Alto, CA: Consulting Psychologists Press.

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Related News: Chromosomal Mishaps in Autism Harbor Schizophrenia Candidate Genes

Comment by:  Ben Pickard
Submitted 23 May 2012
Posted 24 May 2012

The paper by Talkowski and colleagues describes the application of cutting edge genomics techniques to the molecular characterisation of multiple balanced chromosomal abnormalities (BCAs) linked to autism, autism spectrum disorders, and general neurodevelopmental disorders. In a single publication it has probably assigned more candidate genes than the entire conventional cytogenetic output from schizophrenia and autism in the preceding 15 years.

The authors carry out a great deal of complementary genomic analyses which add to the strength of their argument that these genes are indeed causally involved in illness. Without these additional data there would be one potential criticism of the paper in that the same power of analysis was not applied to BCAs in healthy controls. This is an important ascertainment issue because previous studies have not only identified disrupted genes in the healthy population (Baptista et al., 2005) but also shown that CNVs deregulating specific genes may only show an increased—as opposed to exclusive—representation in the ill population.

The observed overlaps between some of the identified BCA genes in ASD/neurodevelopmental disorders and those identified in GWAS studies of schizophrenia and bipolar disorder is fascinating but may be a double-edged sword. On the one hand, support for rare genetic contributors (CNVs/sequence variants/BCAs) to complex genetic disorders has often been drawn from those that are co-incident between studies. In that respect, this study is remarkable for highlighting the same genes from methods that detect very different mutation types. I’m genuinely surprised that there appears to be a convergence of ancient (read subject to evolutionary selection/population effects) and recent (meaning random) mutations. On the other hand, there is the disconcerting possibility that schizophrenia GWAS are only powered to detect the causes of blunt neurodevelopmental disturbances (which are perhaps less sensitive to issues of diagnostic categorisation) and not the fine-grained genetic hits that determine a precise clinical endpoint. If this is the case then we could end up with a situation where the genotypic distance between disorders is apparently much less than the phenotypic distance. This is most likely an extreme outcome that will be remedied once the genomic analysis of complex genetic disorders is able to factor in the composite effects of BCAs, CNVs, rare SNPs, and common SNPs—at the level of the single individual, and perhaps conditioned on the presence of big neurodevelopmental hits.

Quite logically, the presence of genes spanning diagnoses has been explained in terms of shared predisposition derived from early neurodevelopmental insults that are subsequently pushed down diagnostic pathways by other genetic or environmental factors. However, this assumption needs formal testing. The problem is reminiscent of the debate that circled the early use of constitutive mouse knockouts: how is it possible to disentangle developmental from adult functional phenotypes in a null? The advent of inducible Cre-LoxP technologies allowed that question to be directly addressed and may be the means to test the neurodevelopmental contribution of diagnosis-spanning candidate genes such as TCF4.

Could the approach detailed in this paper be applied directly to schizophrenia? It would certainly add substantially to the ‘confirmed’ gene list and would detect any reciprocal relationships with ASD/neurodevelopmental disorders. One issue is that ASD appears to have a higher overall incidence of chromosomal and genomic structural rearrangements than schizophrenia, but perhaps the greater question is availability of an appropriate sample set. The concerted cytogenetic screening that took place in Scotland coupled with an ability to cross-reference these findings with incidence of psychiatric disorder was instrumental in the discovery of DISC1 and other genes in Scotland (Muir et al., 2008) but this resource is now largely exhausted of relevant BCAs. To my knowledge, the Danish registry represents the best bet for such an approach to succeed for schizophrenia (Bache et al., 2006).

References:

Baptista J, Prigmore E, Gribble SM, Jacobs PA, Carter NP, Crolla JA. Molecular cytogenetic analyses of breakpoints in apparently balanced reciprocal translocations carried by phenotypically normal individuals. Eur J Hum Genet. 2005 Nov;13(11):1205-12. Abstract

Muir WJ, Pickard BS, Blackwood DH. Disrupted-in-Schizophrenia-1. Curr Psychiatry Rep. 2008 Apr;10(2):140-7. Abstract

Bache I, Hjorth M, Bugge M, Holstebroe S, Hilden J, Schmidt L, Brondum-Nielsen K, Bruun-Petersen G, Jensen PK, Lundsteen C, Niebuhr E, Rasmussen K, Tommerup N. Systematic re-examination of carriers of balanced reciprocal translocations: a strategy to search for candidate regions for common and complex diseases. Eur J Hum Genet. 2006 Apr;14(4):410-7. Abstract

View all comments by Ben Pickard

Related News: Chromosomal Mishaps in Autism Harbor Schizophrenia Candidate Genes

Comment by:  Patrick Sullivan, SRF AdvisorJin Szatkiewicz
Submitted 29 May 2012
Posted 29 May 2012
  I recommend the Primary Papers

In this exceptional paper, the authors combined new technology with old-school genomics to deliver convergent data about the genomic regions that predispose to neuropsychiatric disorders. The first goal of psychiatric genetics is to identify the “parts list,” an enumeration of the genes and genetic loci whose alteration clearly and unequivocally alters risk. The results of this intriguing paper connect rare and powerful genomic disruptions with loci identified via common variant genomewide association screens.

A classical approach in human genetics is to study affected individuals with balanced translocations. Using next-generation sequencing, these authors identified the precise locations of 38 rare balanced chromosomal abnormalities in subjects with neurodevelopmental disorders. They identified 33 disrupted genes, of which 22 were novel risk loci for autism and neurodevelopmental disorders. The other disrupted genes included many that had previously been identified by genomic searches for rare variation and common variation (e.g., AUTS2, CHD8, TCF4, and ZNF804A).

The authors then sought secondary genomic support for disease association with these 33 risk loci by analyzing a large collection of psychiatric GWAS data. They found an increased burden of copy number variants (CNVs) among cases as well as a significant enrichment of common risk alleles among both autism and schizophrenia cases. This research suggests that autism and neurodevelopmental disorders may have commonalities with psychiatric disorders such as schizophrenia at the molecular level, underscoring the complexity of genetic contribution to these conditions.

CNVs discovered from microarrays are mainly large, rare CNVs spanning multiple genes. Exome sequencing is limited to coding regions of the genome. In contrast, as illustrated in Talkowski et al. (2012), it is possible to identify individual lesions with nucleotide resolution in both coding and non-coding regions. Thus, this research suggests that sequencing individuals with pathogenic balanced translocations could provide a complementary strategy for mutation identification and gene discovery.

The experimental procedures were technically well done; all BCA breakpoints were confirmed by PCR and capillary sequencing. In seeking the secondary genomic support, the authors were keen on evaluating and eliminating the possibility for any confounding factors that may cause spurious association. For example, CNV burden analysis was conducted with respect to differential sensitivities from microarrays, and all results remained robust to various subset analyses and to one million simulations designed to establish empirical significance. To examine the potential for spurious enrichment of common risk alleles, the authors additionally conducted identical analysis in phenotype-permuted datasets from well-powered GWAS data for schizophrenia and autism as well as in well-powered GWAS data for eight unrelated traits, and therefore eliminated unforeseen confounders.

Impressively, many of the loci identified here now have convergent genomic results with support across multiple different samples and technical approaches. For example, TCF4 harbors common variation identified via GWAS, a Mendelian disorder, and now a gene disruption. These convergent genomic results markedly increase confidence that TCF4 is truly in the “parts list” for neurodevelopmental disorders. In contrast, there remain multiple questions about the genomic evidence for DISC1, where such convergence has not been achieved.

This paper also provides important results relevant to resolving the rare “versus” common variation debate. This appears to be a false dichotomy where, often, both rare and common variations contribute to the parts lists for these disorders.

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Related News: Chromosomal Mishaps in Autism Harbor Schizophrenia Candidate Genes

Comment by:  Bernard Crespi
Submitted 29 May 2012
Posted 29 May 2012
  I recommend the Primary Papers

Balanced chromosomal abnormalities (BCAs) provide extremely useful alterations for linking of specific loci with psychiatric conditions, because they exert penetrant effects and localize to specific genes. The recent study by Talkowski et al. (2012) used direct sequencing of breakpoints, based on 38 subjects, to generate a set of genes with putative links to different neurodevelopmental disorders, broadly construed as including autism spectrum disorders, intellectual disability, and/or developmental and other delays.

One of the most striking results from their study was the presence, in their set of breakpoint-altered genes, of five genes that have been associated from other work with schizophrenia and related psychotic-affective spectrum disorders (such as bipolar disorder and major depression), including TCF4, ZNF804A, PDE10A, GRIN2B, and ANK3. These results suggest, according to the authors, the presence of shared genetic etiology for ASD, schizophrenia, and other neurodevelopmental disorders (mainly developmental delays). The authors also show overlap of their gene list with results from CNV and GWAS of autism and schizophrenia, further suggesting genetic links between these two conditions.

Do these results mean that autism and schizophrenia share genetic risk factors? Perhaps, but also perhaps not. Two important caveats apply.

First, schizophrenia involves well-documented premorbidity, in a substantial proportion of cases, that centers on developmental, social, and language deficits and delays (e.g., Saracco-Alvarez et al., 2009; Gibson et al., 2010). In children, premorbidity to schizophrenia most commonly involves "negative" symptoms, including deficits in social interaction (Remschmidt et al., 1994; Tandon et al., 2009), which can overlap with symptoms of autism spectrum disorders (Goldstein et al., 2002; Sheitman et al., 2004; Tjordman, 2008; King and Lord, 2011). Males are more severely affected, as in autism (Sobin et al., 2001; Rapoport et al., 2009; Tandon et al., 2009). Schizophrenia mediated by CNVs, or BCAs, is likely to exhibit relatively high levels of premorbidity, due to the penetrant, syndromic, and deleterious nature of these alterations (Bassett et al., 2010; Vassos et al., 2010). A recent study by Sahoo et al. (Sahoo et al., 2011) provides evidence consistent with such premorbidity, in that of over 38,000 individuals (predominantly children) referred for developmental delay, intellectual disability, autism spectrum disorders, or multiple congenital anomalies, 704 exhibited one of seven CNVs (del 1q21.1, dup 1q21.1, del 15q11.2, del 15q13.3, dup 16p11.2, dup 16p13.11, and del 22q11.2) that have been statistically associated with schizophrenia in studies of adults (Levinson et al., 2011).

These findings suggest that the subjects in Talkowski et al. (Talkowski et al., 2012), (most of them children, for individuals with age data given) who harbor alterations to schizophrenia-associated genes may, in fact, be severely premorbid for schizophrenia. Diagnoses of ASD (commonly PDD-NOS) in such individuals may represent either false positives (Eliez, 2007 ; Feinstein and Singh, 2007), or true positives, with ASD as a developmental stage followed, in some individuals, by schizophrenia. This latter conceptualization considers autism as akin to childhood schizophrenia, a view which contrasts sharply with the classic criteria derived from Kanner (Kanner, 1943), Asperger (1991) and Rutter (Rutter, 2000, Rutter, 1972, Rutter, 1978), who consider autism as a lifelong condition present from early childhood. Of course, diagnosing premorbidity to schizophrenia as such is challenging, but if any data can help, it is data from highly penetrant alterations such as CNVs and BCAs, as well as from biological and neurological (rather than just behavioral) phenotypes.

Second, association to an overlapping set of genes need not make two disorders similar, or similar in their genetic etiology. For example, as noted by Talkowski et al. (Talkowski et al., 2012), variation in TCF4 has been associated with both Pitt-Hopkins syndrome and schizophrenia, but these conditions show essentially no overlap in phenotypes. Similar considerations apply to CACNA1C, linked to the autism-associated Timothy syndrome (via an apparent gain of function) as well as to schizophrenia and bipolar disorder. A key to sorting out the huge clinical and genetic heterogeneity in autism, and in schizophrenia, is subsetting of cases by similarity in alterations to pathways and phenotypes. Lumping of autism with schizophrenia, based on overlap in risk loci without consideration of the nature of the overlap, will make such subsetting all the more difficult.

Data on genes disrupted by balanced translocations are tremendously useful, but their usefulness will, as for other data such as CNVs, be circumscribed by diagnostic considerations, especially when the subjects are children. Bearing in mind the possibility that some childhood diagnoses may represent false positives, and that overlap in genes need not mean overlap in causation, should help in moving the study of both autism and schizophrenia forward.

References:

Asperger H; translated and annotated by Frith U (1991) [1944]. Autistic psychopathy' in childhood. In Frith, U. Autism and Asperger syndrome. Cambridge University Press. pp. 37-92.

Bassett AS, Scherer SW, Brzustowicz LM. Copy number variations in schizophrenia: critical review and new perspectives on concepts of genetics and disease. Am J Psychiatry. 2010;167(8):899-914. Abstract

Eliez S. Autism in children with 22q11.2 deletion syndrome. J Am Acad Child Adolesc Psychiatry. 2007;46(4):433-4. Abstract

Feinstein C, Singh S. Social phenotypes in neurogenetic syndromes. Child Adolesc Psychiatr Clin N Am. 2007;16(3):631-47. Abstract

Gibson CM, Penn DL, Prinstein MJ, Perkins DO, Belger A. Social skill and social cognition in adolescents at genetic risk for psychosis. Schizophr Res. 2010;122(1-3):179-84. Abstract

Kanner L. 1968;2:217–250. Abstract

King BH, Lord C. Is schizophrenia on the autism spectrum? Brain Res. 2011;1380:34-41. Abstract

Levinson DF, Duan J, Oh S, Wang K, Sanders AR, Shi J, et al., Copy number variants in schizophrenia: confirmation of five previous findings and new evidence for 3q29 microdeletions and VIPR2 duplications. Am J Psychiatry. 2011;168(3):302-16. Abstract

Rapoport J, Chavez A, Greenstein D, Addington A, Gogtay N. Autism spectrum disorders and childhood-onset schizophrenia: clinical and biological contributions to a relation revisited. J Am Acad Child Adolesc Psychiatry. 2009;48(1):10-8. Abstract

Remschmidt HE, Schulz E, Martin M, Warnke A, Trott GE. Childhood-onset schizophrenia: history of the concept and recent studies. Schizophr Bull. 1994;20(4):727-45. Abstract

Rutter ML. Relationships between child and adult psychiatric disorders. Some research considerations. Acta Psychiatr Scand. 1972;48(1):3-21. Abstract

Rutter M. Diagnosis and definition of childhood autism. J Autism Child Schizophr. 1978;8(2):139-61. Abstract

Rutter M. Genetic studies of autism: from the 1970s into the millennium. J Abnorm Child Psychol. 2000;28(1):3-14. Abstract

Saracco-Alvarez R, Rodríguez-Verdugo S, García-Anaya M, Fresán A. Premorbid adjustment in schizophrenia and schizoaffective disorder. Psychiatry Res. 2009;165(3):234-40. Abstract

Sahoo T, Theisen A, Rosenfeld JA, Lamb AN, Ravnan JB, Schultz RA, et al., Copy number variants of schizophrenia susceptibility loci are associated with a spectrum of speech and developmental delays and behavior problems. Genet Med. 2011; 13(10):868-80. Abstract

Sheitman BB, Kraus JE, Bodfish JW, Carmel H. Are the negative symptoms of schizophrenia consistent with an autistic spectrum illness? Schizophr Res. 2004;69(1):119-20. Abstract

Sobin C, Blundell ML, Conry A, Weiller F, Gavigan C, Haiman C, et al., Early, non-psychotic deviant behavior in schizophrenia: a possible endophenotypic marker for genetic studies. Psychiatry Res. 2001;101(2):101-13. Abstract

Talkowski ME, Rosenfeld JA, Blumenthal I, Pillalamarri V, Chiang C, Heilbut A, Ernst C, Hanscom C, Rossin E, Lindgren AM, Pereira S, Ruderfer D, Kirby A, Ripke S, Harris DJ, Lee JH, Ha K, Kim HG, Solomon BD, Gropman AL, Lucente D, Sims K, Ohsumi TK, Borowsky ML, Loranger S, Quade B, Lage K, Miles J, Wu BL, Shen Y, Neale B, Shaffer LG, Daly MJ, Morton CC, Gusella JF. Sequencing Chromosomal Abnormalities Reveals Neurodevelopmental Loci that Confer Risk across Diagnostic Boundaries. Cell. 2012;149(3):525-37. Abstract

Tandon R, Nasrallah HA, Keshavan MS. Schizophrenia, "just the facts" 4. Clinical features and conceptualization. Schizophr Res. 2009;110(1-3):1-23. Abstract

Tjordman S Reunifying autism and early-onset schizophrenia in terms of social communication disorders. Behav Brain Sci. 2008;31(3):278-9.

Vassos E, Collier DA, Holden S, Patch C, Rujescu D, St Clair D, et al., Penetrance for copy number variants associated with schizophrenia. Hum Mol Genet. 2010;19(17):3477-81. Abstract

View all comments by Bernard Crespi

Related News: New Mutations Mount as Fathers Age

Comment by:  Dolores Malaspina
Submitted 27 August 2012
Posted 27 August 2012

The new report by Kong et al. (2012) demonstrates that paternal age is likely to be an important source of mutations that are relevant for schizophrenia, as we earlier hypothesized (Malaspina, 2001). Kong et al. demonstrated that the diversity in human mutation rates for offspring is dominated by the paternal age at conception. Following our initial observation that advancing paternal age was substantially associated with an increasing risk for schizophrenia, explaining a quarter of the population's attributable risk for schizophrenia (Malaspina et al., 2001), many scientists found it difficult to accept that the father’s age could be a risk pathway for schizophrenia. By contrast, the hypothesis that paternal age explained the risk for achondroplastic dwarfism achieved far greater immediate acceptance over 20 years ago (i.e., Thompson et al., 1986). While these new findings will surely advance our understanding of many de novo neuropsychiatric conditions, they also substantiate biological versus psychosocial causation theories for severe neuropsychiatric conditions.

References:

Malaspina D. Paternal factors and schizophrenia risk: de novo mutations and imprinting. Schizophr Bull . 2001 ; 27(3):379-93. Abstract

Malaspina D, Harlap S, Fennig S, Heiman D, Nahon D, Feldman D, Susser ES. Advancing paternal age and the risk of schizophrenia. Arch Gen Psychiatry . 2001 Apr ; 58(4):361-7. Abstract

Thompson JN Jr, Schaefer GB, Conley MC, Mascie-Taylor CG. Achondroplasia and parental age. N Engl J Med. 1986 Feb 20;314(8):521-2. Abstract

View all comments by Dolores Malaspina

Related News: New Mutations Mount as Fathers Age

Comment by:  Patrick Sullivan, SRF Advisor
Submitted 27 August 2012
Posted 27 August 2012

Kong et al. sequenced 78 pedigree clusters (mostly parent-offspring trios) to around 30x coverage. After careful quality control, they identified an average of 63 new mutations per trio. These mutations were “de novo” in that they were absent in the parents but present in an offspring and assumed to have occurred during gametogenesis.

Intriguingly, more of these mutations occurred in older parents. The authors present several lines of evidence to implicate fathers rather than mothers, and estimated that there were about two extra de novo mutations per year of increase in paternal age. This conclusion is consistent with several of the exome sequencing papers published in Nature a few months ago.

Increased paternal age is an epidemiological risk factor for schizophrenia and autism, with relative risks on the order of two and five, respectively. This paper suggests a potential mechanism for the paternal age effect that might eventually prove to be relevant for some fraction of cases.

It is important to note that advanced paternal age is a risk factor, not a determining feature. Risk is increased, but not in a deterministic manner.

View all comments by Patrick Sullivan

Related News: New Mutations Mount as Fathers Age

Comment by:  John McGrath, SRF Advisor
Submitted 28 August 2012
Posted 28 August 2012
  I recommend the Primary Papers

In 2001, Dolores Malaspina alerted the research community to the link between advanced paternal age and increased risk of schizophrenia—she suggested that this may be due to de novo mutations in the male germ line (Malaspina et al., 2001). The study BY Kong et al. provides compelling evidence in support of this hypothesis (Kong et al., 2012). A related paper in Nature Genetics also demonstrates an association between paternal age and changes in microsatellite properties across generations (Sun et al., 2012).

While the hypothesis that de novo mutations accumulate due to copy error mutations in the production of germ cells in older males is compelling, it is still possible (albeit unlikely) that this association may be due to unmeasured confounding. For example, older men might be exposed to more environmental toxins that accumulate over time and subsequently cause mutations in the offspring of older dads as a byproduct of the greater exposure. There is also the evidence from Denmark indicating that, when adjusted for age of first child, the association between paternal age and risk of schizophrenia fades out (Petersen et al., 2011). This finding suggests that selective factors may also operate (e.g., perhaps related to personality of schizotypal men, etc.).

However, animal experiments can provide useful clues to this puzzle (Foldi et al., 2011). Mouse models of advanced paternal age indicate that the offspring of older sires differ from control animals on behavior and brain structure (Smith et al., 2009; Foldi et al., 2010). Of particular relevance for the study by Kong et al., a mouse experiment found that the offspring of older sires were significantly more likely to have de novo copy number variants (Flatscher-Bader et al., 2011).

We now have convergent evidence from risk factor epidemiology, animal experiments, and genetic studies. The evidence supports an increased risk of schizophrenia in the offspring of older fathers, and points to age-related mutagenesis in the male germ cell. It is still not clear why these age-related events seem to differentially impact on neurodevelopmental disorders (e.g., autism is also linked to paternal age). Perhaps neocortical development is less well "buffered" (compared to more phylogenetically ancient organs); thus, de novo mutations can more readily "decanalize" certain features of brain development (McGrath et al., 2011). From an evolutionary developmental biology perspective (evo-devo), the dictum goes “Last in, first to break.”

It is rare that different fields of research converge in such an obedient fashion. It is time that we pause and reflect on this important milestone—and also offer a rousing “three cheers for Dolores Malapsina!”

References:

Flatscher-Bader T, Foldi CJ, Chong S, Whitelaw E, Moser RJ, Burne TH, Eyles DW, McGrath JJ. Increased de novo copy number variants in the offspring of older males. Transl Psychiatry. 2011 Aug 30;1:e34. Abstract

Foldi CJ, Eyles DW, McGrath JJ, Burne TH. Advanced paternal age is associated with alterations in discrete behavioural domains and cortical neuroanatomy of C57BL/6J mice. Eur J Neurosci. 2010 Feb;31(3):556-64. Abstract Foldi CJ, Eyles DW, Flatscher-Bader T, McGrath JJ, Burne TH. New perspectives on rodent models of advanced paternal age: relevance to autism. Front Behav Neurosci . 2011 ; 5():32. Abstract

Kong A, Frigge ML, Masson G, Besenbacher S, Sulem P, Magnusson G, Gudjonsson SA, Sigurdsson A, Jonasdottir A, Jonasdottir A, Wong WS, Sigurdsson G, Walters GB, Steinberg S, Helgason H, Thorleifsson G, Gudbjartsson DF, Helgason A, Magnusson OT, Thorsteinsdottir U, Stefansson K. Rate of de novo mutations and the importance of father's age to disease risk. Nature. 2012 Aug 23;488(7412):471-5. Abstract

Malaspina D, Harlap S, Fennig S, Heiman D, Nahon D, Feldman D, Susser ES. Advancing paternal age and the risk of schizophrenia. Arch Gen Psychiatry. 2001 Apr ; 58(4):361-7. Abstract

McGrath JJ, Hannan AJ, Gibson G. Decanalization, brain development and risk of schizophrenia. Transl Psychiatry. Abstract

Petersen L, Mortensen PB, Pedersen CB. Paternal age at birth of first child and risk of schizophrenia. Am J Psychiatry. 2011 Jan;168(1):82-8. Abstract

Smith RG, Kember RL, Mill J, Fernandes C, Schalkwyk LC, Buxbaum JD, Reichenberg A. Advancing paternal age is associated with deficits in social and exploratory behaviors in the offspring: a mouse model. PLoS One. 2009 Dec 30;4(12):e8456. Abstract

Sun JX, Helgason A, Masson G, Ebenesersdóttir SS, Li H, Mallick S, Gnerre S, Patterson N, Kong A, Reich D, Stefansson K. A direct characterization of human mutation based on microsatellites. Nat Genet. 2012 Aug 23. Abstract

View all comments by John McGrath

Related News: New Mutations Mount as Fathers Age

Comment by:  Georg Winterer (Disclosure)
Submitted 28 August 2012
Posted 28 August 2012
  I recommend the Primary Papers

Just a few thoughts:

One question is whether it is just age per se that produces de novo mutations or an accumulation of environmental effects like drug abuse, alcohol, or other potentially harmful toxic environments, etc. What I also would like to know is whether it is the number of sperm cycles; in that case, men who are sexually more active should have a greater risk to produce more de novo mutations.

View all comments by Georg Winterer

Related News: New Mutations Mount as Fathers Age

Comment by:  Michael O'Donovan, SRF AdvisorGeorge Kirov
Submitted 31 August 2012
Posted 31 August 2012

In a genomic sequencing study of 78 parent-proband trios (21 probands with schizophrenia, 44 with autism spectrum disorder [ASD]), Kong and colleagues (2012) identify almost 5,000 DNA single base changes that occurred as a result of new mutations. For five of the trios, the proband had a child who was also sequenced, and in this subset with three generations of data, Kong and colleagues were able to determine if the mutations had arisen on the paternal or maternal chromosomes. Although this subsample was small, paternal chromosomes showed much greater variance in the number of mutations than maternal chromosomes, suggesting that paternal variables are more relevant to variance in the overall de novo mutation rate than maternal variables. In the larger sample as a whole, although the parental origin of the mutations could not be determined, the number of new mutations carried by an individual could be almost completely explained by a combination of random variation and paternal age. Models of linear and of exponential increases in the number of mutations by paternal age both described the data well, the ability to distinguish between the two being constrained by a lack of fathers at the higher age. Children of fathers aged 40 had approximately twice the number of mutations as those aged 20. After accounting for random variation and paternal age, in this sample, there was very little residual variation to be explained by other factors, including maternal age and within-population environmental exposures. A possible impact of cross-population environmental exposures was not addressed, since all the subjects came from Iceland.

Overall, the findings from what is yet another impressive paper from the deCODE group support the proposition that paternal age is an important factor in determining the probability that a child might inherit a new mutation (see Goriely and Wilkie, 2012, for a wider discussion of earlier data on paternal age and mutation rates, particularly in sperm) and additionally quantify this effect in the context of other possible unexplained variables.

This is clearly an important paper for understanding factors dictating the rate by which new mutations occur, and is therefore a paper that will have wide relevance to diseases to which such mutations make a substantial contribution. But from the perspective of most readers of this Forum, it is more important to note what the study is not about.

There is good evidence that risk of schizophrenia increases with paternal age (Malaspina et al., 2001; Zammit et al., 2003; Frans et al., 2011). This is certainly compatible with the involvement of new mutations of the sort described in the paper by Kong and colleagues, but there are several alternative explanations. For example, fathers with high trait liability for schizophrenia might have subclinical characteristics making them less effective at reproduction (e.g., they may find it more difficult to find a partner) and, as a result, elderly fathers might be enriched for transmissible schizophrenia alleles. Consistent with this (and other explanations not dependent on new mutations), one large Danish study found that the paternal age effect was best explained by age at which fathers first reproduce, not the age (which is more relevant to new mutations) when the affected offspring was conceived (Petersen et al., 2011). Of general importance as it is, the study by Kong and colleagues makes no contribution to resolving to what extent the paternal age effect observed in schizophrenia (and autism) is explained by new mutations, or indeed to what extent new mutations are involved in these disorders at all. Indeed, as the authors point out, the fact that they have studied probands, the majority of whom are affected by schizophrenia or ASD, is an irrelevance; essentially identical findings would be expected if they had studied other types of families. This is because the average proband carries over 60 de novo mutations, of which, even under an extreme model in which all schizophrenia is caused by de novo mutations, at most, one or two (if any) might be schizophrenia or ASD relevant. Consequently, de novo mutations related to the phenotype of the proband cannot substantially contribute to the overall pattern of results.

Overall, this study provides empirical evidence for a mechanism by which some of the paternal age effects might be explained by de novo point mutations, but it is worth stressing that the fact that the authors have studied schizophrenia and ASD is incidental, and this study does not address the extent by which, if at all, mutations of this type make any contribution to schizophrenia (or autism). Finally, since the results of this paper have been widely reported (at least in the UK), we think it is important to note for the general reader that, while the paternal age effect of risk of schizophrenia (and autism) seems to be real, the vast majority of people with schizophrenia are not born to elderly fathers. More importantly, since the causal direction of the paternal age effect on schizophrenia risk is unknown, there is currently no strong reason to urge potential fathers to consider earlier reproduction as a strategy for reducing risk of this particular disorder.

References:

Zammit S, Allebeck P, Dalman C, Lundberg I, Hemmingson T, Owen MJ, Lewis G. Paternal age and risk for schizophrenia. Br J Psychiatry. 2003 Nov;183:405-8. Abstract

Malaspina D, Harlap S, Fennig S, Heiman D, Nahon D, Feldman D, Susser ES. Advancing paternal age and the risk of schizophrenia. Arch Gen Psychiatry. 2001 Apr;58(4):361-7. Abstract

Goriely A, Wilkie AO. Paternal age effect mutations and selfish spermatogonial selection: causes and consequences for human disease. Am J Hum Genet. 2012 Feb 10;90(2):175-200. Review. Abstract

Frans EM, McGrath JJ, Sandin S, Lichtenstein P, Reichenberg A, Långström N, Hultman CM. Advanced paternal and grandpaternal age and schizophrenia: a three-generation perspective. Schizophr Res. 2011 Dec;133(1-3):120-4. Epub 2011 Oct 14. Abstract

Petersen L, Mortensen PB, Pedersen CB. Paternal age at birth of first child and risk of schizophrenia. Am J Psychiatry. 2011 Jan;168(1):82-8. Epub 2010 Oct 15. Abstract

View all comments by Michael O'Donovan
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Related News: New Mutations Mount as Fathers Age

Comment by:  Bernard Crespi
Submitted 3 September 2012
Posted 5 September 2012
  I recommend the Primary Papers

Kong et al. (2012) is an outstanding paper that provides the first detailed quantification of how human de novo mutations in sperm and eggs vary with parental age. The paper and its aftermath provide a number of important lessons for researchers studying neurodevelopmental disorders and parental age:

1. The work demonstrates directly that CpG dinucleotides contribute the lion's share of new mutations. CpG sites are of particular interest in understanding effects of de novo mutations because they differentially create new transcription factor binding sites (Zemojtel et al., 2011), as well as mediate the effects of methylation and genomic imprinting. Such findings might help to focus efforts at interpreting the functional importance of the myriad de novo variants that pepper each genome.

2. The work generates an apparent paradox: if, as the authors claim, paternal age so strongly predominates over maternal age in its de novo mutational effects, why do so many parental-age studies of autism and schizophrenia show clear effects of maternal age as well (e.g., Lopez-Castroman et al., 2010; Parner et al., 2012; Rahbar et al., 2012; Sandin et al., 2012)? Might maternal-age effects be mediated by different processes?

3. The X chromosome was not included in the analysis, despite its expected contribution to de novo mutational effects being much stronger than for autosomes, due to its hemizygosity (as found, e.g., in intellectual disability). A recent study also strikingly implicates the X chromosome in psychosis risk, perhaps involving epigenetic mechanisms (Goldstein et al., 2011).

4. It is important to avoid neurodevelopmental tunnel vision with regard to parental age effects. Advanced maternal age, for example, has been documented as a risk factor for a suite of other conditions, including hypertension, diabetes, cancer, and Alzheimer's (for a review, see Myrskylä and Fenelon, 2012), as expected if it exerts effects on all polygenic conditions.

5. As anyone following popular media accounts will have noticed, the paper has been fundamentally misinterpreted in translation from the scientific to popular literature. Contrary to almost all reports in the popular press (including, e.g., The New York Times), the paper clearly does not show that higher paternal age is associated with mutations that increase the risk of autism or schizophrenia. As noted by other commentators, to do so would require that the authors link paternal age with the number of new mutations that are actually known to contribute to autism or schizophrenia. This muddle should caution authors to be as clear in explaining what their findings do not show as they are in explaining what they actually demonstrate. If subsequent work shows that age-dependent point mutations themselves do not mediate increased autism or schizophrenia risk, scientific credibility will unjustifiably suffer.

6. Finally, the press has jumped on advanced parental age as an important possible factor in the increased diagnoses of autism over the past 30 or so years. But if increased mutation load has increased rates of autism, why haven't rates of schizophrenia increased in lockstep, albeit with a 20-year delay?

Parental age has been suspected as an important factor in genetically based, de novo conditions since Weinberg (of Hardy-Weinberg fame) noticed in 1912 that children with achondroplasia (a form of dwarfism) were later-born in sibships. One hundred years later, we are one large step closer to understanding why. Let us help to ensure that this step is free of de novo errors of interpretation and implication, and move forward with speed.

References:

Goldstein JM, Cherkerzian S, Seidman LJ, Petryshen TL, Fitzmaurice G, Tsuang MT, Buka SL. Sex-specific rates of transmission of psychosis in the New England high-risk family study. Schizophr Res. 2011 May;128(1-3):150-5. Abstract

Kong A, Frigge ML, Masson G, Besenbacher S, Sulem P, Magnusson G, Gudjonsson SA, Sigurdsson A, Jonasdottir A, Jonasdottir A, Wong WS, Sigurdsson G, Walters GB, Steinberg S, Helgason H, Thorleifsson G, Gudbjartsson DF, Helgason A, Magnusson OT, Thorsteinsdottir U, Stefansson K. Rate of de novo mutations and the importance of father's age to disease risk. Nature. 2012 Aug 22; 488: 471-5. Abstract

Lopez-Castroman J, Gómez DD, Belloso JJ, Fernandez-Navarro P, Perez-Rodriguez MM, Villamor IB, Navarrete FF, Ginestar CM, Currier D, Torres MR, Navio-Acosta M, Saiz-Ruiz J, Jimenez-Arriero MA, Baca-Garcia E. Differences in maternal and paternal age between schizophrenia and other psychiatric disorders. Schizophr Res. 2010 Feb;116(2-3):184-90. Abstract

Myrskylä M, Fenelon A. Maternal Age and Offspring Adult Health: Evidence From the Health and Retirement Study. Demography . 2012 Aug 28. Abstract

Parner ET, Baron-Cohen S, Lauritsen MB, Jørgensen M, Schieve LA, Yeargin-Allsopp M, Obel C. Parental age and autism spectrum disorders. Ann Epidemiol. 2012 Mar;22(3):143-50. Abstract

Rahbar MH, Samms-Vaughan M, Loveland KA, Pearson DA, Bressler J, Chen Z, Ardjomand-Hessabi M, Shakespeare-Pellington S, Grove ML, Beecher C, Bloom K, Boerwinkle E. Maternal and Paternal Age are Jointly Associated with Childhood Autism in Jamaica. J Autism Dev Disord. 2012 Sep;42(9):1928-38. Abstract

Sandin S, Hultman CM, Kolevzon A, Gross R, MacCabe JH, Reichenberg A. Advancing maternal age is associated with increasing risk for autism: a review and meta-analysis. J Am Acad Child Adolesc Psychiatry. 2012 May;51(5):477-486.e1. Abstract

Zemojtel T, Kielbasa SM, Arndt PF, Behrens S, Bourque G, Vingron M. CpG deamination creates transcription factor-binding sites with high efficiency. Genome Biol Evol. 2011;3:1304-11. Abstract

View all comments by Bernard Crespi

Related News: Exome Sequencing Hints at Prenatal Genes in Schizophrenia

Comment by:  Sven CichonMarcella RietschelMarkus M. Nöthen
Submitted 5 October 2012
Posted 5 October 2012

The new exome sequencing study by Xu et al. confirms previous results by the same research group (Xu et al., 2011) and by an independent group (Girard et al., 2011) that a significantly higher frequency of protein-altering de novo single nucleotide variants (SNVs) and in/dels is found in sporadic patients with schizophrenia. It is certainly reassuring that this observation has now been confirmed in an independent and considerably larger sample (134 patient-parent trios and 34 control-parent trios).

A closer look also reveals differences between this study and the study by Girard et al.: Xu et al. do not find a significantly higher overall de novo mutation rate per base per generation when comparing schizophrenia and control trios (1.73 x 10-08 vs. 1.28 x 10-08). In contrast, the Girard study found 2.59 x 10-08 de novo mutations in schizophrenia trios as opposed to the 1.1 x 10-08 events reported in the general population by the 1000 Genomes Project. The larger sample size in the new study by Xu et al., however, suggests that their estimation of the de novo mutation rates may be more precise now.

What eventually seems to count is the quality of the de novo mutations in the sporadic schizophrenia patients. The function of the genes hit by the non-synonymous/deleterious (as defined by in-silico scores) mutations is diverse and shows similarity with functions reported for common risk genes for schizophrenia identified by GWAS. Interestingly, there is an overrepresentation of genes that are predominantly expressed during embryogenesis, strongly highlighting a possible effect of neurodevelopmental disturbances in the etiology of schizophrenia (and nicely supporting what has already been concluded from GWAS).

It would probably be very interesting to estimate the penetrance of such de novo mutations to get a feeling for their individual impact on the development of the disease. In the absence of a reasonable number of individuals with the same mutation, however, this will be a difficult task.

Another aspect that is missing in the current paper, but is accessible to investigation, is the frequency/quality of de novo mutations in trios with a family history of schizophrenia and comparison to the figures seen in the sporadic trios. That might (or might not) support the authors’ conclusion that de novo events play a strong role in sporadic cases (and not in familial cases).

References:

Xu B, Roos JL, Dexheimer P, Boone B, Plummer B, Levy S, Gogos JA, Karayiorgou M. Exome sequencing supports a de novo mutational paradigm for schizophrenia. Nat Genet . 2011 Sep ; 43(9):864-8. Abstract

Girard SL, Gauthier J, Noreau A, Xiong L, Zhou S, Jouan L, Dionne-Laporte A, Spiegelman D, Henrion E, Diallo O, Thibodeau P, Bachand I, Bao JY, Tong AH, Lin CH, Millet B, Jaafari N, Joober R, Dion PA, Lok S, Krebs MO, Rouleau GA. Increased exonic de novo mutation rate in individuals with schizophrenia. Nat Genet . 2011 Sep ; 43(9):860-3. Abstract

View all comments by Sven Cichon
View all comments by Marcella Rietschel
View all comments by Markus M. Nöthen

Related News: Exome Sequencing Hints at Prenatal Genes in Schizophrenia

Comment by:  Patrick Sullivan, SRF Advisor
Submitted 5 October 2012
Posted 5 October 2012

This paper by the productive group at Columbia increases our knowledge of the role of rare exon mutations in schizophrenia. The authors applied exome sequencing—a newish high-throughput sequencing technology—to trios consisting of both parents plus an offspring with schizophrenia. The authors focused on a subset of the genome (the “exome,” genetic regions believed to code for protein) on a subset of genetic variants (SNPs and insertion/deletion variants) of predicted functional significance, and on one type of inheritance (“de novo“ mutations, those absent in both parents and present in the offspring with schizophrenia).

The sample sizes are the largest yet reported for schizophrenia—231 affected trios and 34 controls. About 28 percent of these samples were reported in 2011 (Xu et al., 2011). A recent schizophrenia sequencing study (N = 166) from the Duke group was unrevealing (Need et al., 2012). The numbers in the Xu, 2012 paper are small compared to the three Nature trio studies for autism (see SRF related news story), an approximately threefold larger trio study for schizophrenia (in preparation), a case-control exome sequencing study for schizophrenia (total N ~5,000, in preparation), and a case-control exome chip study for schizophrenia (total N ~11,000, in preparation).

The authors reported:

more mutations with older fathers, as has been reported before (see SRF related news story). Note that advanced paternal age is an established risk factor for schizophrenia.

more de novo/predicted functional/exonic mutations in schizophrenia than in controls. However, the difference was slight, one-sided P = 0.03. One can quibble with the use of a one-tailed test (should never be used, in my opinion), but it is difficult to interpret this result unless paternal age is included as a covariate in this critical test.

an impressive set of bioinformatic and integrative analyses—see the paper for the large amount of work they did.

as might be predicted given the small sample size and the rarity of these sorts of mutations, there was no statistically significant pile-up of variants in specific genes. Hence, to my reading, the authors do not compellingly implicate any specific genes in the pathophysiology of schizophrenia. This conclusion is consistent with Need et al., 2012, and I note that the autism work implicated only a few genes (e.g., CHD8 and KATNAL2).

Note that the authors would disagree with the above, as they chose to focus on a set of genes that they thought stood out (reporting an aggregate P of 0.002), and the last third of the paper focuses on these genes. However, the human genetics community now insists on two critical points for implicating specific genes in associations with a disorder. The first is statistical significance, and the critical P value for an exome sequencing study is on the order of 1E-6. The second is replication. In my view, neither of these standards are achieved. However, their observations are intriguing, and may well eventually move us forward.

The key observation in this paper is the increased rate of de novo variation in schizophrenia cases. Is the increased rate indeed part of an etiological process? In other words, older fathers have an increased chance of exonic mutations, and these, in turn, increase risk for schizophrenia? Or are these merely hitch-hikers of no particularly biological import?

A major issue with exome studies is that there are so many predicted functional variants in apparently normal people. We all carry on the order of 100 exonic variants of predicted functional consequences with on the order of 20 genes that are probable knockouts. If part of the risk for schizophrenia indeed resides in the exome, very large studies will be required to identify such loci confidently. Moreover, published work on autism and unpublished work for type 2 diabetes, coronary artery disease, and schizophrenia suggest that this will require very large sample sizes, on the order of 100 times more than reported here. And, it is possible that the exome is not all that important for schizophrenia.

References:

Xu B, Roos JL, Dexheimer P, Boone B, Plummer B, Levy S, Gogos JA, Karayiorgou M. Exome sequencing supports a de novo mutational paradigm for schizophrenia. Nat Genet . 2011 Sep ; 43(9):864-8. Abstract

Need AC, McEvoy JP, Gennarelli M, Heinzen EL, Ge D, Maia JM, Shianna KV, He M, Cirulli ET, Gumbs CE, Zhao Q, Campbell CR, Hong L, Rosenquist P, Putkonen A, Hallikainen T, Repo-Tiihonen E, Tiihonen J, Levy DL, Meltzer HY, Goldstein DB. Exome sequencing followed by large-scale genotyping suggests a limited role for moderately rare risk factors of strong effect in schizophrenia. Am J Hum Genet . 2012 Aug 10 ; 91(2):303-12. Abstract

View all comments by Patrick Sullivan

Related News: Deciphering Themes for Schizophrenia’s Genetic Variation

Comment by:  Patrick Sullivan, SRF AdvisorDanielle Posthuma
Submitted 16 November 2012
Posted 16 November 2012

Gilman et al. pose exceptionally important and salient questions: given that increasingly detailed genomic data have established that many genes are now strongly implicated in the etiology of schizophrenia, how do we understand this? How can these different components of the “parts list” for schizophrenia be pieced together to derive a cogent etiological hypothesis for further testing?

The authors use a new computational approach to address these questions, and derive lists related to axon guidance, neuronal cell mobility, synaptic function, and chromosomal remodeling. Additional analyses suggest the coherence of their lists. These are good clues that deserve further evaluation.

It was intriguing that the authors included multiple types of genetic variation—rare but potent copy number variants (e.g., Kirov et al., 2012), rare exonic mutations (Xu et al., 2012), and common variations from genomewide association studies (Ripke et al., 2011)—as most authors have tended to conduct these analyses separately.

In sum, a nice contribution to the literature and initial steps towards tackling a tough problem in human genetics. But, there are four issues for readers to bear in mind in evaluating the results.

First, we hope that the authors make their program freely available. This is the standard in the field. Many of us are interested in evaluating the capacities of their program. To our knowledge, it is not now available, although it has been used in multiple published papers. We could find no link in the paper or on the senior author’s lab page.

Second, readers need to remember that this was an in-silico analysis. It produces hypotheses but does not (and cannot) provide proof. The methods are subject to multiple biases, and it was not clear how well these were controlled (see point 4 as well). We wondered whether known biases like gene size and LD patterns were well controlled.

Third, we would have liked to see greater scholarship. There is an unfortunate trend for computational biologists to produce tools without benchmarking them against existing tools or rigorously determining power and error rates. The lack of finding significant clusters in control sets is insufficient in showing the validity of their program. Are the authors’ claims that their new tool represents superiority truly justified?

Moreover, there are a lot of tools for performing analyses of these sorts (e.g., INRICH, FORGE, MAGENTA, Ingenuity, ALIGATOR, among many others). Indeed, these sorts of analyses are in the toolkits of most psychiatric genetics groups and are routinely applied. Given that there are many papers reporting results, a scholarly treatment of how their results compare to those of others and what the added value of their program is would have been useful.

Fourth, and most importantly, pathway analysis is completely dependent on the input—the genetic findings and the pathways. The findings that the authors used had issues. The CNV list is likely to change soon as the PGC CNV group completes its integrated analyses of tens of thousands of subjects. The exome list was based on a small and atypical sample, and much larger studies are in preparation (see SRF comment). The authors did not seem to confront the issue that all humans contain a lot of deleterious exonic variation. And (spoiler alert), the GWAS list is soon to increase markedly. More and more precise findings are sure to alter the results.

The pathways used were pretty standard—GO, KEGG, protein-protein interaction databases. Unfortunately, although widely used, these pathways have multiple issues. The content of many GO annotations and KEGG pathways have not been constructed by experts in the area. As one salient example, synaptic gene lists in standard pathway databases were quite imperfectly related to lists created by experts (Ruano et al., 2010). The authors also relied somewhat uncritically on the PPI databases. These have multiple issues, and some (unpublished) data suggest substantial error (i.e., large fractions of the predicted interactions are not, in fact, real or biologically meaningful). The fraction of the proteome screened adequately by these methods is small. Some interactions in these databases are non-specific, or occur between molecules that are never in the same place at the same time.

Indeed, the genes overrepresented in PPI databases were selected due to disease relevance or biological importance (e.g., there is a lot of work on P53). In general, the more a gene is investigated, the more interactions are found.

Still, this is a key paper, albeit a snapshot based on imperfect input data, and we look forward to seeing whether additional analyses confirm a role in schizophrenia of the networks identified currently with their program.

References:

Kirov G, Pocklington AJ, Holmans P, Ivanov D, Ikeda M, Ruderfer D, Moran J, Chambert K, Toncheva D, Georgieva L, Grozeva D, Fjodorova M, Wollerton R, Rees E, Nikolov I, van de Lagemaat LN, Bayés A, Fernandez E, Olason PI, Böttcher Y, Komiyama NH, Collins MO, Choudhary J, Stefansson K, Stefansson H, Grant SG, Purcell S, Sklar P, O'Donovan MC, Owen MJ. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol Psychiatry. 2012 Feb; 17(2):142-53. Abstract

Xu B, Ionita-Laza I, Roos JL, Boone B, Woodrick S, Sun Y, Levy S, Gogos JA, Karayiorgou M. De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia. Nat Genet. 2012 Oct 3. Abstract

Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA, Lin DY, Duan J, Ophoff RA, Andreassen OA, Scolnick E, Cichon S, St Clair D, Corvin A, Gurling H, Werge T, Rujescu D, Blackwood DH, Pato CN, Malhotra AK, Purcell S, Dudbridge F, Neale BM, Rossin L, Visscher PM, Posthuma D, Ruderfer DM, Fanous A, Stefansson H, Steinberg S, Mowry BJ, Golimbet V, de Hert M, Jönsson EG, Bitter I, Pietiläinen OP, Collier DA, Tosato S, Agartz I, Albus M, Alexander M, Amdur RL, Amin F, Bass N, Bergen SE, Black DW, Børglum AD, Brown MA, Bruggeman R, Buccola NG, Byerley WF, Cahn W, Cantor RM, Carr VJ, Catts SV, Choudhury K, Cloninger CR, Cormican P, Craddock N, Danoy PA, Datta S, de Haan L, Demontis D, Dikeos D, Djurovic S, Donnelly P, Donohoe G, Duong L, Dwyer S, Fink-Jensen A, Freedman R, Freimer NB, Friedl M, Georgieva L, Giegling I, Gill M, Glenthøj B, Godard S, Hamshere M, Hansen M, Hansen T, Hartmann AM, Henskens FA, Hougaard DM, Hultman CM, Ingason A, Jablensky AV, Jakobsen KD, Jay M, Jürgens G, Kahn RS, Keller MC, Kenis G, Kenny E, Kim Y, Kirov GK, Konnerth H, Konte B, Krabbendam L, Krasucki R, Lasseter VK, Laurent C, Lawrence J, Lencz T, Lerer FB, Liang KY, Lichtenstein P, Lieberman JA, Linszen DH, Lönnqvist J, Loughland CM, Maclean AW, Maher BS, Maier W, Mallet J, Malloy P, Mattheisen M, Mattingsdal M, McGhee KA, McGrath JJ, McIntosh A, McLean DE, McQuillin A, Melle I, Michie PT, Milanova V, Morris DW, Mors O, Mortensen PB, Moskvina V, Muglia P, Myin-Germeys I, Nertney DA, Nestadt G, Nielsen J, Nikolov I, Nordentoft M, Norton N, Nöthen MM, O'Dushlaine CT, Olincy A, Olsen L, O'Neill FA, Orntoft TF, Owen MJ, Pantelis C, Papadimitriou G, Pato MT, Peltonen L, Petursson H, Pickard B, Pimm J, Pulver AE, Puri V, Quested D, Quinn EM, Rasmussen HB, Réthelyi JM, Ribble R, Rietschel M, Riley BP, Ruggeri M, Schall U, Schulze TG, Schwab SG, Scott RJ, Shi J, Sigurdsson E, Silverman JM, Spencer CC, Stefansson K, Strange A, Strengman E, Stroup TS, Suvisaari J, Terenius L, Thirumalai S, Thygesen JH, Timm S, Toncheva D, van den Oord E, van Os J, van Winkel R, Veldink J, Walsh D, Wang AG, Wiersma D, Wildenauer DB, Williams HJ, Williams NM, Wormley B, Zammit S, Sullivan PF, O'Donovan MC, Daly MJ, Gejman PV. Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011 Oct ; 43(10):969-76. Abstract

Ruano D, Abecasis GR, Glaser B, Lips ES, Cornelisse LN, de Jong AP, Evans DM, Davey Smith G, Timpson NJ, Smit AB, Heutink P, Verhage M, Posthuma D. Functional gene group analysis reveals a role of synaptic heterotrimeric G proteins in cognitive ability. Am J Hum Genet. 2010 Feb 12;86(2):113-25. Abstract

View all comments by Patrick Sullivan
View all comments by Danielle Posthuma

Related News: Ambitious Genetic Integration Analysis of Schizophrenia Points to Early Brain Development

Comment by:  Roger Boshes
Submitted 10 August 2013
Posted 20 August 2013

These data suggest a "stem" circuit that may be common to many patients with schizophrenia, but subsequent de novo mutations may explain the protean manifestations of the disorder. Alternatively, this prefrontal perturbation may be related to a heritable, i.e., not a somatic, mutation that explains 80 percent heritability but not the protean phenotypic expression of the condition. Finally, it may be the link between schizophrenia and some flavors of autism.

References:

Boshes RA, Manschreck TC, Konigsberg W. Genetics of the schizophrenias: a model accounting for their persistence and myriad phenotypes. Harv Rev Psychiatry. 2012 May-Jun; 20(3):119-29. Abstract

View all comments by Roger Boshes

Related News: New Exome Evidence Points to Old Suspect in Schizophrenia

Comment by:  Francis McMahon, SRF Advisor
Submitted 23 January 2014
Posted 28 January 2014

I think these studies do represent real progress. Finding genetic support for particular pathways provides unique evidence for a causative role of these pathways in disease. Why didn't the case-control study point to individual genes? Disorders such as schizophrenia may be more like a plane crash than a typical inherited disease: Since many things can go wrong, each crash is different, but damage to key systems is very likely to lead to a bad outcome. The finding in Fromer et al. that there are 18 genes with recurrent deleterious de novo events should allow scientists to focus on these genes as especially important. The overlaps with autism and intellectual disability are interesting, though not entirely unexpected. Will we also see gene overlaps with illnesses such as bipolar disorder? It wouldn't surprise me if some of the same genes are involved, but with fewer, less deleterious hits.

View all comments by Francis McMahon