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Editorial
Published Online: 1 June 2009

New Hope for Pharmacogenetic Testing

In this issue, readers will find an article by Perlis et al. (which includes data from the Broad Institute of Harvard and Massachusetts Institute of Technology, the Systematic Treatment Enhancement Program for Bipolar Disorder [STEP-BD] Consortium, and University College London) that targets lithium response using genomewide association methods (1) . The STEP-BD cohort included 1,177 bipolar patients, of whom 458 were treated with lithium. The University College London sample added lithium response data for 359 patients. These are sizable samples for pharmacologic studies. The results do not meet formal criteria for genomewide significance. However, there are a number of areas of interest, including single nucleotide polymorphisms (SNPs) in and near GRIA2, which codes for a glutamate receptor subunit. A particular polymorphism in the GRIA2 region, rs9784453, appears to be associated with time to recurrence of a mood episode while on lithium (Kaplan-Meier log rank: p=0.001). By my reading of Figure 3, the median time to recurrence is about 230 days for homozygote carriers with the “poor response” allele and about 520 days for homozygote carriers with the “good response” allele, with heterozygote carriers falling in between. Differences such as this are of clinical interest.
Of course there are many caveats to this study as it presently stands, and I summarize the results not to describe a test that should be considered useful today, but to indicate that work in bipolar pharmacogenetics is no longer arcane and is increasingly clinically oriented. Forty years after the wide availability of lithium therapy for bipolar illness in the United States, we still do not really know which patients should be receiving it. As our populations of bipolar patients age, we see more who are discomfited or endangered by side effects of maintenance mood stabilizers, such as weight-gain related to lithium or valproate, chronic renal insufficiency or diabetes insipidus related to lithium, or complaints of memory impairment or poor muscular coordination that may be related to lithium. We still must hesitate when prescribing mood stabilizers for women of childbearing age who have bipolar disorder. And despite a series of groundbreaking investigations of mechanisms of action involving glycogen synthase kinase, the inositol triphosphate system, and adenyl cyclase, we still cannot specify the key cellular events related to the therapeutic action of lithium or any other mood stabilizer.
Genetic studies promise to change the continuing reliance of psychiatric therapeutics on serendipity. By all measures, we have benefited from careful observations of behavioral changes in patients taking drugs developed for other purposes. We have then used initial theories, based on monoamine regulation, to design new generations of drugs for mood disorder and schizophrenia. These “bootstrapped” studies have revolutionized the field of psychiatry in a generation. We now require rational therapeutics.
The obstacles are many, but a number have been overcome. We have agreed to criterion-based diagnosis in the clinic as well as in the research ward. We increasingly accept the necessity for standardized symptom measurement in clinical practice. In clinical research, we have agreed to work together and to share data across national and international consortia. That this is necessary for genetic studies cannot now be doubted. The genomewide association studies (GWAS) of bipolar disorder have recently been summarized in an article published in the Journal (2) . Individual samples in the range of 1,000 patients and 1,000 comparison subjects have not been successful at identifying genomewide significant loci (37) . However, a combination of samples (8), with over 4,000 patients and 6,000 comparison subjects, has identified one locus that clearly meets genomewide criteria (ANK3, which codes for a sodium channel modulatory protein) and one locus that may meet such criteria (CACNA1C, which codes for a calcium channel subunit). In comparison, the studies of type 2 diabetes went from one locus identified to 10 loci identified as their sample numbers approached 20,000 case subjects and 20,000 comparison subjects. The National Institute of Mental Health is fully aware of the need for massive samples in order to maximally utilize such studies, and these efforts are under way for bipolar disorder and schizophrenia.
We will arguably need to consider sample sizes in this range for other types of studies as well. The treatment effects assignable to specific mood stabilizers in STEP-BD (strategy described in ref. 9), for instance, are still modest, with sample sizes in the range of 1,000 in different subgroups of patients. Clinical therapeutic studies of diabetes and common cardiovascular disorders often use samples 10 to 20 times as large. Neuroimaging studies also suffer from the effects of modest sample size and site-to-site variation in equipment, behavioral protocol, and data analytic methods. We must use our best results to argue for an increased priority for studies of psychiatric brain disorders, which are, as we know, the most disabling disorders in the modern world (10) .
The psychiatric GWAS should start to point us toward biochemical pathways for pathophysiology and therapeutics. Already we may say that they lead toward a greater emphasis on ion channels (from ANK3 and CACNA1C). Recently published pathway studies based on GWAS results emphasize myelination, ion channel structural (11) and regulatory genes (12) and pathways related to adrenergic and dopaminergic receptors (13) . Other such efforts are in progress. Information specifying genes and pathways may be accessible at lower sample sizes than that for the information we are currently seeking through GWAS, i.e., the confirmation of specific gene variants in the form of modified alleles. We need this more specific information for use in genetic counseling and for understanding the molecular mechanisms involved in pertinent mutations, and we will obtain this information through large samples and through careful sequencing of selected case and comparison subjects. But we may already be able to glimpse the broad outlines of genetic structure for complex psychiatric disorders by analyzing the data with an eye toward pathways rather than individual genes or gene variants.
Thus, the Perlis et al. article is the first in what should become a critical series of studies on lithium response and response to other mood stabilizers. It is not perfect, and one may reasonably object that its definition of lithium response does not adequately track a consistent cohort of patients over a period of years. Another notable omission is the lack of lithium blood levels, which are an essential part of clinical practice. The University College London cohort includes only retrospective data on lithium response by global clinician rating. This would ideally be supplemented by prospective controlled observations. Nevertheless, this is a good start, and by presenting the first data it becomes the reference article for the field. One should note that Grof and coworkers (14) have been pioneering the separation of bipolar patients by treatment response for some years now and that Turecki et al. (15) published a genomewide linkage study (less precise methodology than that of current GWAS) identifying a locus at 15q14 as the most likely area for lithium response-related genes (findings in the Perlis et al. article on chromosome 15 are some distance from this). Recent work by Mamdani et al. (16) and Tseng et al. (17) implicates cAMP response element binding and brain-derived neurotrophic factor genes in lithium response using candidate gene methods and functional studies.
The GWAS methodology used by Perlis et al. has the distinct advantage of being a true survey of the genome, with polymorphisms tested in probably more than 90% of the genes in the human genome (the exact figure cannot be calculated because of continuing ambiguities of annotation of the human sequence data). Nevertheless, candidate gene studies are still valuable and are much more practical in modestly sized clinical samples. Functional studies are still necessary supplements to candidate polymorphism identification and to GWAS SNP identification. The way forward for psychiatric pharmacogenetics presumably involves a combination of methods such as this, with an emphasis on the genomewide studies for the “aerial view” and supplementation with candidate and functional studies to hone in one specific gene, gene variants, and mechanisms of action.
The expected output of such studies is twofold: a panel of gene-based tests to help separate lithium responders from nonresponders and 2) an understanding of the mechanism(s) of action of lithium. Both of these outcomes may be anticipated to change psychiatric practice dramatically in the next several decades.

Footnotes

Address correspondence and reprint requests to Dr. Nurnberger, Indiana University Medical Center, Institute of Psychiatric Research, 791 Union Drive, Indianapolis, IN 46202-4887; [email protected] (e-mail). Editorial accepted for publication April 2009 (doi: 10.1176/appi.ajp.2009.09040536).
The author reports no competing interests.

References

1.
Perlis RH, Smoller JW, Ferreira MAR, McQuillin A, Bass N, Lawrence J, Sachs GS, Nimgaonkar V, Scolnick EM, Gurling H, Sklar P, Purcell S: A genomewide association study of response to lithium for prevention of recurrence in bipolar disorder. Am J Psychiatry 2009; 166:718–725
2.
Psychiatric GWAS Consortium Coordinating Committee: Genomewide association studies: history, rationale, and prospects for psychiatric disorders. Am J Psychiatry 2009; 166:540–556
3.
Wellcome Trust Case Control Consortium: Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007; 447:661–678
4.
Baum AE, Akula N, Cabanero M, Cardona I, Corona W, Klemens B, Schulze TG, Cichon S, Rietschel M, Nöthen MM, Georgi A, Schumacher J, Schwarz M, Abou Jamra R, Höfels S, Propping P, Satagopan J, Detera-Wadleigh SD, Hardy J, McMahon FJ: A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder. Mol Psychiatry 2008; 13:197–207
5.
Sklar P, Smoller JW, Fan J, Ferreira MA, Perlis RH, Chambert K, Nimgaonkar VL, McQueen MB, Faraone SV, Kirby A, de Bakker PI, Ogdie MN, Thase ME, Sachs GS, Todd-Brown K, Gabriel SB, Sougnez C, Gates C, Blumenstiel B, Defelice M, Ardlie KG, Franklin J, Muir WJ, McGhee KA, MacIntyre DJ, McLean A, VanBeck M, McQuillin A, Bass NJ, Robinson M, Lawrence J, Anjorin A, Curtis D, Scolnick EM, Daly MJ, Blackwood DH, Gurling HM, Purcell SM: Whole-genome association study of bipolar disorder. Mol Psychiatry 2008; 13:558–569
6.
Smith EN, Bloss CS, Badner JA, Barrett T, Belmonte PL, Berrettini W, Byerley W, Coryell W, Craig D, Edenberg HJ, Eskin E, Foroud T, Gershon E, Greenwood TA, Hipolito M, Koller DL, Lawson WB, Liu C, Lohoff F, McInnis MG, McMahon FJ, Mirel DB, Murray SS, Nievergelt C, Nurnberger J, Nwulia EA, Paschall J, Potash JB, Rice J, Schulze TG, Scheftner W, Panganiban C, Zaitlen N, Zandi PP, Zöllner S, NJ Schork, Kelsoe JR: Genome-wide association study of bipolar disorder in European American and African American individuals. Mol Psychiatry (in press)
7.
Scott L, Li J, Guan W, Absher D, Thompson RC, Meng F, Burmeister M, Akil H, Watson SJ, Myers RM, Boehnke M: Genome-wide association study of bipolar disorder in European-Americans, in the Proceedings of the 15th World Congress of Psychiatric Genetics, New York, 2007
8.
Ferreira MA, O’Donovan MC, Meng YA, Jones IR, Ruderfer DM, Jones L, Fan J, Kirov G, Perlis RH, Green EK, Smoller JW, Grozeva D, Stone J, Nikolov I, Chambert K, Hamshere ML, Nimgaonkar VL, Moskvina V, Thase ME, Caesar S, Sachs GS, Franklin J, Gordon-Smith K, Ardlie KG, Gabriel SB, Fraser C, Blumenstiel B, Defelice M, Breen G, Gill M, Morris DW, Elkin A, Muir WJ, McGhee KA, Williamson R, MacIntyre DJ, MacLean AW, St Clair D, Robinson M, Van Beck M, Pereira AC, Kandaswamy R, McQuillin A, Collier DA, Bass NJ, Young AH, Lawrence J, Ferrier IN, Anjorin A, Farmer A, Curtis D, Scolnick EM, McGuffin P, Daly MJ, Corvin AP, Holmans PA, Blackwood DH, Gurling HM, Owen MJ, Purcell SM, Sklar P, Craddock N; Wellcome Trust Case Control Consortium: Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 2008; 40:1056–1058
9.
Sachs GS, Nierenberg AA, Calabrese JR, Marangell LB, Wisniewski SR, Gyulai L, Friedman ES, Bowden CL, Fossey MD, Ostacher MJ, Ketter TA, Patel J, Hauser P, Rapport D, Martinez JM, Allen MH, Miklowitz DJ, Otto MW, Dennehy EB, Thase ME: Effectiveness of adjunctive antidepressant treatment for bipolar depression. N Engl J Med 2007; 356:1711–1722
10.
World Health Organization: The World Health Report 192-197. Geneva, Switzerland, WHO, 2002
11.
Le-Niculescu H, Patel SD, Bhat M, Kuczenski R, Faraone SV, Tsuang MT, McMahon FJ, Schork NJ, Nurnberger JI Jr, Niculescu AB 3rd: Convergent functional genomics of genome-wide association data for bipolar disorder: comprehensive identification of candidate genes, pathways and mechanisms. Am J Med Genet B Neuropsychiatr Genet 2009; 150B:155–181
12.
Askland K, Read C, Moore J: Pathways-based analyses of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission. Hum Genet 2009; 125:63–79
13.
Torkamani A, Topol EJ, Schork NJ: Pathway analysis of seven common diseases assessed by genome-wide association. Genomics 2008; 92:265–272
14.
Grof P, Duffy A, Cavazzoni P, Grof E, Garnham J, MacDougall M, O"Donovan C, Alda M: Is response to prophylactic lithium a familial trait? J Clin Psychiatry 2002; 63:942–947
15.
Turecki G, Grof P, Grof E, D’Souza V, Lebuis L, Marineau C, Cavazzoni P, Duffy A, Bétard C, Zvolsk P, Robertson C, Brewer C, Hudson TJ, Rouleau GA, Alda M: Mapping susceptibility genes for bipolar disorder: a pharmacogenetic approach based on excellent response to lithium. Mol Psychiatry 2001; 6:570–578
16.
Mamdani F, Alda M, Grof P, Young LT, Rouleau G, Turecki G: Lithium response and genetic variation in the CREB family of genes. Am J Med Genet B Neuropsychiatr Genet 2008; 147B:500–504
17.
Tseng M, Alda M, Xu L, Sun X, Wang JF, Grof P, Turecki G, Rouleau G, Young LT: BDNF protein levels are decreased in transformed lymphoblasts from lithium-responsive patients with bipolar disorder. J Psychiatry Neurosci 2008; 33:449–453

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Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 635 - 638
PubMed: 19487397

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Published online: 1 June 2009
Published in print: June, 2009

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John I. Nurnberger, Jr., M.D., Ph.D.

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