This is another good postmortem study from the Haroutunian laboratory. Although the studies are somewhat limited in scope and the conclusions are quite speculative (linking genetic, clinical, and cognitive disturbances to the dysfunction of the node of Ranvier), they are still a breeze of fresh air in schizophrenia research. They offer a new explanation of myelination deficits in schizophrenia, linking it to genetics and disturbed connectivity across the brain regions. We need such new hypotheses, new ideas. Is this one correct? It is certainly plausible, and supported by some data. However, if the past is a predictor of the future, we can be almost certain that the answer will be much more complicated than we think.

View all comments by Karoly Mirnics

Roussos and colleagues conducted a study that, in part, follows up findings from large-scale genetic association studies.

They hypothesized that there is a failure in saltatory conduction in schizophrenia and therefore potential dysfunction in the nodes of Ranvier (NOR) in schizophrenia. To evaluate this hypothesis, they performed microarray transcription analysis on multiple cortical regions in postmortem brain tissue from schizophrenia patients and controls. They selectively analyzed these transcriptome data for changes in genes which play a role in the NOR. They state that they identified dysregulation of genes known to be involved in development, organization, and maintenance of NOR across multiple brain regions. They were able to validate four of the genes using quantitative PCR, and to verify that these genes were not altered in brains of rats treated with haloperidol (i.e., less likely to be an effect of drug treatment).

Given the association of ANK3 in bipolar disorder, some evidence of association in schizophrenia, and the evidence of etiological overlap...  Read more

Roussos and colleagues conducted a study that, in part, follows up findings from large-scale genetic association studies.

They hypothesized that there is a failure in saltatory conduction in schizophrenia and therefore potential dysfunction in the nodes of Ranvier (NOR) in schizophrenia. To evaluate this hypothesis, they performed microarray transcription analysis on multiple cortical regions in postmortem brain tissue from schizophrenia patients and controls. They selectively analyzed these transcriptome data for changes in genes which play a role in the NOR. They state that they identified dysregulation of genes known to be involved in development, organization, and maintenance of NOR across multiple brain regions. They were able to validate four of the genes using quantitative PCR, and to verify that these genes were not altered in brains of rats treated with haloperidol (i.e., less likely to be an effect of drug treatment).

Given the association of ANK3 in bipolar disorder, some evidence of association in schizophrenia, and the evidence of etiological overlap between the disorders, they decided to follow up specifically on ANK3. They looked at whether genetic variants in ANK3 showed any functional effects. Their findings indicated that rs9804190 had expression changes in schizophrenia patients, but not controls, and a weak but consistent genetic association with disease in a small sample. They also demonstrated an association of the rs9804190*C with differences in performance on neurocognition, personality, and fMRI activation in the frontal gyrus in unaffected individuals.

The tests of their major hypothesis of NOR dysfunction in schizophrenia were indirect, and the findings somewhat equivocal (few genes were significantly altered in their findings, and their handling of multiple testing was worrying). However, given the previous evidence for ANK3 in psychiatric disease and its role as a key player in NOR function, Roussos et al. followed up on an intriguing and potentially important risk factor and delved into multiple levels of functional evidence. While ANK3 has certainly shown more evidence of association in bipolar disease than in schizophrenia, the choice of this gene for follow-up is sensible, given the evidence of etiological overlap between these two diseases.

Additionally, this level of functional work will be critical to future understanding of the role that individual risk factors play in psychiatric disease. The authors consistently found evidence for functional effects of one SNP, rs9804190. Either the C allele or CC homozygotes showed functional or genetic effects in each of the experiments. However, several of these tests did not directly pertain to schizophrenia; their genetic findings for schizophrenia were weak and from a small sample set; there were functional findings in healthy individuals, despite the lack of findings of expression changes in controls (which could be due to lack of power); and it is unclear whether this SNP is truly functional or simply in high LD with a functional variant. Nonetheless, it seems clear that either this variant or a variant in high LD may have a functional effect on ANK3 and specific brain functions. While the support of overall NOR dysfunction was not conclusive, the findings are consistent with ANK3 as an intriguing candidate for contributions to the etiology of psychiatric disease.

The work by Ferreira et al. exemplifies the growing enthusiasm for collaborative work among investigators and marks the new era of collaborative genetic research in complex disorders. The LD data found in the extant HapMap SNPs allow investigators to use sophisticated computational approaches to impute genotypes based on these HapMap data sets and the data generated from the experimental sample, thereby maximizing the utility of the actual genotyping itself. Nothing short of brilliant. Correlates between imputed and true genotypes were estimated to be 0.987, which is quite good. The significance estimates of the combined data analyses of the three data sets identifies two genes (ANK3 and CACNA1C) in the genomewide significance range with a p value of 10^-8, which is most reassuring and even more so considering that the CACNA1C gene was identified previously. The humbling fact in the mix is that the odds ratios are modest, ranging from 1.2 to 1.4, which is nonetheless in a similar arena as other complex genetic disorders such as diabetes. It is further humbling (and...  Read more

The work by Ferreira et al. exemplifies the growing enthusiasm for collaborative work among investigators and marks the new era of collaborative genetic research in complex disorders. The LD data found in the extant HapMap SNPs allow investigators to use sophisticated computational approaches to impute genotypes based on these HapMap data sets and the data generated from the experimental sample, thereby maximizing the utility of the actual genotyping itself. Nothing short of brilliant. Correlates between imputed and true genotypes were estimated to be 0.987, which is quite good. The significance estimates of the combined data analyses of the three data sets identifies two genes (ANK3 and CACNA1C) in the genomewide significance range with a p value of 10^-8, which is most reassuring and even more so considering that the CACNA1C gene was identified previously. The humbling fact in the mix is that the odds ratios are modest, ranging from 1.2 to 1.4, which is nonetheless in a similar arena as other complex genetic disorders such as diabetes. It is further humbling (and consistent with the modest ORs) to consider that the frequency of the risk allele for the CACNA1C gene is 7.5 percent in the BP cases and 5.6 percent in the unaffected control individuals. Finally, there was no effect of the sub-diagnostic categories, age of onset, presence of psychosis, or sex. The highly encouraging point is that these genes appear to be in pathways that are affected by lithium, the gold standard of care for BP disorder. The anchorage of a genetic finding within a mechanism of an established treatment for BP disorder (lithium) lends substantial credibility to overall results. The next questions of research will relate to the efficacy of lithium relative to genotypes of these genes and others within their pathways. These findings raise several clinical questions, and integration of clinical outcome patterns with genetic data can be expected to shed further light on the etiology of the disease and the genetics of treatment response. Long live lithium.

Ferreira et al. propose two specific genes to be related to bipolar disorder, ANK3, which is indirectly related to sodium channels, and CACNA1C, which is a calcium channel subunit. They hypothesize that bipolar disorder is, at least in part, a channelopathy. This hypothesis is consistent with a number of physiological observations made over the past several decades, as reviewed elsewhere.

The genetic data these authors present is certainly suggestive. They have analyzed three independent data sets, STEP-UCL (Sklar et al., 2008), Wellcome Trust (Wellcome Trust Case Control Consortium, 2007), and a third set called ED-DUB-STEP2 (not yet published). Their total sample exceeds 4,000 cases and 6,000 controls. They have direct genotype data on >300,000 SNPs and have imputed nearly 1.5 million additional. Their highest significance values (10^-7 to 10^-9) include a combination of genotyped and imputed SNPs. For each of these, the combined p value is a product of...  Read more

Ferreira et al. propose two specific genes to be related to bipolar disorder, ANK3, which is indirectly related to sodium channels, and CACNA1C, which is a calcium channel subunit. They hypothesize that bipolar disorder is, at least in part, a channelopathy. This hypothesis is consistent with a number of physiological observations made over the past several decades, as reviewed elsewhere.

The genetic data these authors present is certainly suggestive. They have analyzed three independent data sets, STEP-UCL (Sklar et al., 2008), Wellcome Trust (Wellcome Trust Case Control Consortium, 2007), and a third set called ED-DUB-STEP2 (not yet published). Their total sample exceeds 4,000 cases and 6,000 controls. They have direct genotype data on >300,000 SNPs and have imputed nearly 1.5 million additional. Their highest significance values (10^-7 to 10^-9) include a combination of genotyped and imputed SNPs. For each of these, the combined p value is a product of modest but consistent associations in the three independent data sets.

ANK3 features rs10994336 at 9x10e^-9 and rs1938526 at 1x10e^-8. By my reading, these two polymorphisms are both slightly distal to the gene but the second is within 10-20 kB. The first of these is imputed, and thus the p value should probably be judged as more imprecise. Both of these polymorphisms are associated with an odds ratio of ~1.4 and a minor allele frequency of ~5 percent in controls.

The CACNA1C data is based on more common polymorphisms (~30 percent in controls) and an OR~1.2. Again two SNPs are featured (rs1006737 at 7x10e^-8, genotyped, and rs1024582 at 2x10^-7, imputed). A third region near an uncharacterized gene (on 15q14) is also featured.

Examination of available published data from STEP-UCL and WTCCC on ANK3 and CACNA1C does not show obvious evidence of association among SNPs across each of the named genes, but reasonably consistent signals of modest significance, which is what one might expect, and this does suggest that the featured SNPs are not completely anomalous, but may represent a pattern of genotype deviation across the two genes.

Needless to say, our investigators in the GAIN (Genetic Analysis Information Network) bipolar group are extremely interested in this report and are avidly following the lead provided by Ferreira to attempt to confirm these signals in our own data. I am also pleased to say that GAIN has provided the stimulus for an international consortium that includes representatives from the Ferreira group as well as many other investigators, dedicated to assembling yet larger samples of bipolar cases and controls to elucidate the genetics of this condition through genomewide methods.

This is an important report, and it may represent a breakthrough in bipolar genetic studies. The signals for ANK3 and CACNA1C appear very promising, and we hope that they prove to be consistently observed in other data sets as well. We anticipate that additional confirmed single genes will emerge soon as well, and that the genetic structure of these disorders will be elucidated using similar methods in large data sets in the coming years.

Are we there yet? Have we in the field of bipolar genetics finally been delivered to the promised land by GWAS? For the past year or so since GWAS burst on the scene, we have had to watch with envy as an impressive list of genes were convincingly implicated in a range of other complex diseases like type 2 diabetes, the apparent poster child for GWAS. Now, is it our turn?

The first attempts at individual-level GWAS of bipolar disorder by WTCCC and STEP-UCL were exciting because of their novelty, but the results were not particularly overwhelming. None of the findings withstood correction for the massive multiple testing inherent in GWAS, and those at the top were of ambiguous relevance to bipolar disorder. Confronted with such uninspiring findings, one could not be faulted for experiencing pangs of doubt that maybe for psychiatric disorders, GWAS would prove no better than its dusty old predecessor, the genomewide linkage study, in illuminating the underlying genetic architecture.

Nevertheless, encouraged by the lessons learned from GWAS of type 2 diabetes that the...  Read more

Are we there yet? Have we in the field of bipolar genetics finally been delivered to the promised land by GWAS? For the past year or so since GWAS burst on the scene, we have had to watch with envy as an impressive list of genes were convincingly implicated in a range of other complex diseases like type 2 diabetes, the apparent poster child for GWAS. Now, is it our turn?

The first attempts at individual-level GWAS of bipolar disorder by WTCCC and STEP-UCL were exciting because of their novelty, but the results were not particularly overwhelming. None of the findings withstood correction for the massive multiple testing inherent in GWAS, and those at the top were of ambiguous relevance to bipolar disorder. Confronted with such uninspiring findings, one could not be faulted for experiencing pangs of doubt that maybe for psychiatric disorders, GWAS would prove no better than its dusty old predecessor, the genomewide linkage study, in illuminating the underlying genetic architecture.

Nevertheless, encouraged by the lessons learned from GWAS of type 2 diabetes that the road to the promised land is not paved in individual glory but in collaborations and consortiums, the investigators of WTCCC and STEP-UCL combined samples with a third previously unstudied collection (dubbed ED-DUB-STEP2) to assemble one of the largest samples in bipolar disorder yet to be analyzed by GWAS. The combined sample included 4,387 cases and 6,209 controls genotyped at 325,690 overlapping SNPs, which after imputation yielded data on 1.8 million variants. The results from this effort were recently reported in a manuscript by Ferreira and colleagues published in the latest edition of Nature Genetics.

Despite potential concerns about the genetic and/or clinical heterogeneity of the combined sample (e.g., the genomic inflation factor was estimated to be 1.11, even after controlling for two quantitative indices of population ancestry, which might suggest residual stratification or other unaccounted biases), the results from this effort are encouraging and provide some hope to those who may have been losing their faith. The most notable findings were in ANK3 on chromosome 10q21 and CACNA1C on chromosome 12p13. Multiple SNPs were associated across a 195-kb region of ANK3, and the top SNPs had p-values <5 x 10^-8 which is often invoked as an appropriate threshold for genomewide significance in GWAS. Multiple nearby SNPs were also reassuringly associated in CACNA1C, although the top SNP just missed the threshold for genomewide significance. In both ANK3 and CACNA1C the top SNPs were consistently associated in the same direction across all three individual samples, lending credence to the claim that these associations are real. Lending further credence is the fact that ANK3 and CACNA1C are biologically plausible candidates for bipolar disorder, and indeed highlight the possibility that this disorder is an ion channelopathy. Interestingly, the associations with ANK3 and CACNA1C in each of the individual samples were relatively modest and became remarkable only in the combined sample, thus providing support for the rationale to combine samples in order to increase the power to detect those more modest signals that are presumably real but buried amidst the noise of a single study.

Although the evidence is promising, more samples will be needed to confirm the findings before we can say with confidence that we have in hand our first real bipolar susceptibility genes. Fortunately, several such samples have been or will soon be GWASed, including one from GAIN, and it will be of great interest to see whether the current findings are sustained in these new samples. Moreover, there are plans to combine all existing GWAS of bipolar disorder, as part of the initiative referred to as the Psychiatric GWAS Consortium, which should provide an even more definitive picture of the role of ANK3 and CACNA1C, as well as reveal other genes with more modest relative risks whose identities up until now have been obscured.

So, are we there yet? Maybe not just yet, but we are headed in the right direction and I think I can see the promised land.