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Published in final edited form as: Prog Neuropsychopharmacol Biol Psychiatry. 2010 Aug 26;34(8):1515–1519. doi: 10.1016/j.pnpbp.2010.08.015

Association analysis between polymorphisms in the myo-inositol monophosphatase 2 (IMPA2) gene and bipolar disorder

Paul J Bloch 1, Andrew E Weller 1, Glenn A Doyle 1, Thomas N Ferraro 2, Wade H Berrettini 2, Rachel Hodge 1, Falk W Lohoff 1,2,*
PMCID: PMC12046621  NIHMSID: NIHMS232141  PMID: 20800640

Abstract

Linkage studies in bipolar disorder (BPD) suggest that a susceptibility locus exists on chromosome 18p11. The myo-inositol monophosphatase 2 gene (IMPA2) maps to this genomic region. Myo-inositol monophosphatase dephosphorylates inositol monophosphate, regenerating free inositol. Lithium, a common treatment for BPD, has been shown to inhibit IMPA2 activity and decrease levels of inositol. It is hypothesized that lithium conveys its therapeutic effect for BPD patients partially through inositol regulation. Hence, dysfunction of inositol caused by IMPA2 irregularity may contribute to the pathophysiology of BPD. In this study, we hypothesize that genetic variations in the IMPA2 gene contributes to increased susceptibility to BPD. We tested this hypothesis by genotyping 9 SNPs (rs1787984; rs585247; rs3974759; rs650727; rs589247; rs669838; rs636173; rs3786285; rs613993) in BPD patients (n=556) and controls (n=735). Genotype and allele frequencies were compared between groups using Chi square contingency analysis. Linkage disequilibrium (LD) between markers was calculated and estimated haplotype frequencies were compared between groups. Single marker analysis revealed several associations between IMPA2 variations and BPD, which were subsequently rendered non-significant after correction for multiple testing. Although our study did not show strong support for an association between the tested IMPA2 polymorphisms and susceptibility to BPD, additional larger studies are necessary to comprehensively investigate a role of the IMPA2 gene in the pathophysiology of BPD.

Keywords: bipolar disorder, linkage, association, polymorphism, chromosome 18

INTRODUCTION

Linkage studies in bipolar disorder (BPD) suggest that a susceptibility locus exists on chromosome 18p11 (Berrettini et al., 1994; Stine et al., 1995; McInnes et al., 1996; Bowen et al., 1999; Detera-Wadleigh et al., 1999; Nothen et al., 1999; Bennett et al., 2002; Mukherjee et al., 2006). Many genes in that region have been investigated previously but results are inconclusive and no functional variations of major effect have been identified so far (Tsiouris et al., 1996; Esterling et al., 1997; Yoshikawa et al., 1997; Berrettini et al., 1998; Rojas et al., 2000; Yoshikawa et al., 2000; Ishiguro et al., 2001; Reyes et al., 2002; Washizuka et al., 2003; Washizuka et al., 2004; Corradi et al., 2005; Lohoff and Berrettini, 2005; Weller et al., 2006; Chavarria-Siles et al., 2007; Lohoff et al., 2008; Lohoff et al., 2009). Difficulties in elucidating BPD susceptibility factors in the 18p region might be due to the complex mode of inheritance, clinical and locus heterogeneity, and the use of underpowered samples. Another hypothesis is that several genes with small effects might contribute to the linkage peak, complicating the detection of risk alleles by the classic single candidate gene approach. This hypothesis is supported by findings of 18p genes in which alleles are weakly associated with BPD. In an attempt to further investigate the 18p region in BPD, we selected the myo-inositol monophosphatase 2 gene (IMPA2) as another candidate.

The myo-inositol monophosphatase (IMPase) protein catalyzes inositol recycling by converting inositol monophosphate into free inositol through dephosphorylasation. Inositol is an important intracellular signaling molecule involved in the expression regulation of more than 712 genes (Jesch et al., 2005). Several inositol-dependent processes include phospholipid metabolism and UPR (unfolded protein response), both of which are seen to be altered in bipolar patients (Konradi et al., 2004; Stork and Renshaw, 2005; Deranieh and Greenberg, 2009; Hayashi et al., 2009). Furthermore, it has been observed that lithium, a common pharmacological treatment for BPD, inhibits IMPase activity resulting in lower inositol levels. This is the basis for the “inositol-depletion hypothesis” of lithium’s therapeutic action (Berridge et al., 1989; Seelana et al., 2004). Given the critical role of regulation of the inositol pathway, it is feasible to hypothesize that higher levels of inositol caused by IMPase deregulation may contribute to the underlying pathology of BPD. In fact, two previous genetic association studies have investigated the IMPA2 gene (Sjøholt et al., 2004; Ohnishi et al., 2007). Sjøholt et al showed in a family based association study in a Palestinian-Arab sample that variants in the promoter region were associated with disease. This finding was replicated by Ohnishi et al in a Japanese population and further substantiated by functional studies that suggest transcriptional effects of a promoter haplotype in vitro. In this study we tested whether variants in the IMPA2 gene confer risk to BPD amongst individuals of European descent.

MATERIALS AND METHODS

Subjects

Five hundred and fifty six unrelated bipolar I patients (mean age: 41.6 years, 38% male) participated in this study. Patients were collected at centers participating in the NIMH Genetics Initiative on Bipolar Disorder and carried a diagnosis of bipolar I disorder (BPI) defined by DSM-IV criteria. The key criterion for admission of a family to the study was a working diagnosis of BPI in two or more siblings. Background and detailed methodology for the NIMH Genetics Initiative are described elsewhere (Nurnberger, 1997). All subjects were assessed with the Diagnostic Instrument for Genetic Studies (DIGS) (Nurnberger et al., 1994). Family history information was obtained through the FIGS (Family Interview for Genetic Studies) and medical records were requested. Final best estimate diagnosis was made using all available information including medical records, information from relatives, and the DIGS interview, by two independent senior diagnosticians adhering to DSM-IV criteria. Seven hundred and thirty five control samples (mean age: 38.5 years, 51% male) were ascertained by the NIMH Genetic Initiative (www.nimhgenetics.org). These participants were screened online using a self-report instrument based on the Composite International Diagnostic Interview Short-Form (CIDI-SF) (Kessler et al., 1998). Only individuals with no history of psychiatric or chronic neurological disease were included as controls. All cases and controls were of European descent. Informed consent was obtained from all individuals in accordance with Institutional Review Board (IRB) procedures. Peripheral blood samples were obtained and genomic DNA was extracted from peripheral leukocytes by standard procedures.

DNA Analyses

The IMPA2 gene is located on chromosome 18p11.2, spanning 49,449bp and consists of 8 exons (Ensembl Human Exon View accession ENST00000383673). SNPs for genotyping were selected using the tagging SNP algorithm based on available HapMap data with a minor allele frequency (MAF) greater than 0.15 in Caucasian European and a pairwise linkage disequilibrium (LD) r2 cutoff of >0.8 (SNP1: rs1787984; SNP2: rs585247; SNP3: rs3974759; SNP4: rs650727; SNP5: rs589247; SNP6: rs669838; SNP7: rs636173; SNP8: rs3786285; SNP9: rs613993). Genotyping was performed using the Applied Biosystems Inc. (ABI) “Assays-on-demand” (ABI, Foster City, CA, USA) SNP genotyping assay as per manufacturers protocol. Genotyping success rates were greater than 95% for all SNPs. Genotyping quality control was assured by genotyping 10% duplicates for cases and controls.

Statistical Analyses

Genotypes and allele frequencies were compared between groups using Chi square contingency analysis. A two-tailed type I error rate of 5% was chosen for the analysis. Linkage disequilibrium (LD) and haplotype frequencies were estimated using the Haploview software (version 4.0). Haplotype blocks were identified using the solid spine of LD method in Haploview (Barrett et al., 2005). Correction for multiple testing was performed using permutation correction by the Haploview program (Barrett et al., 2005). This approach corrects for multiple testing but takes into account the correlation between markers. It is thus less conservative than a Bonferroni correction, which is appropriate for independent tests such as unlinked markers. For the single-marker analyses, 10000 permutations were carried out to estimate the significance of the best results, correcting for the six loci tested. Haplotype analysis was performed using the Haploview software and P-values were corrected by permutation analysis as described above. Hardy-Weinberg equilibrium (HWE) was calculated separately for cases and controls. Our sample size had reasonable power to detect a disease association at a P-value ≤ 0.05, assuming an odds ratio of 1.5 and a MAF of 15% (99% for a log additive mode of inheritance, 96% for a dominant and 25% for a recessive mode of inheritance). Power analysis was performed using the Quanto program (Gauderman, 2002).

RESULTS

Single marker analysis revealed several associations between variants in the IMPA2 gene and BPD on both the genotypic and allelic level (Table 1); however; no associations remained statistically significant after correction for multiple testing. LD measures and haplotype blocks across the IMPA2 gene are shown in Figure 1. We observed LD patterns across the gene consistent with LD HapMap data and previous reports (Ohnishi et al., 2007). Haplotype analysis did not show any statistically significant associations (Table 2). The case population genotype counts were out of HWE for all SNPs comprising haploblock 2 (SNP4, SNP5, SNP6, and SNP7). The control population genotype counts were out of HWE for SNP2 (Table 1). Genotyping success rates were between 96.3% and 100%. The mean concordance rate for all the markers was 99.5% with respect to the 10% of samples that were genotyped twice for quality control.

Table 1:

Genotype and Allele frequencies of variations in the IMPA2 gene.

SNP Sample n Genotype frequency P* Allele frequency P** HWE P-Value
A/A A/G G/G f(G)
SNP 1 Bipolar 535 0.52 0.41 0.07 0.165 0.278 0.082 0.788
rs1787984 Controls 735 0.57 0.36 0.07 0.25 0.578
T/T T/C C/C f(C)
SNP 2 Bipolar 533 0.66 0.3 0.04 0.0218 a 0.193 0.069 0.681
rs585247 Controls 735 0.69 0.3 0.02 0.165 0.037
T/T T/A A/A f(A)
SNP 3 Bipolar 541 0.5 0.4 0.09 0.397 0.297 0.168 0.213
rs3974759 Controls 734 0.54 0.38 0.08 0.272 0.413
C/C C/T T/T f(T)
SNP 4 Bipolar 555 0.54 0.36 0.1 0.257 0.28 0.384 0.031
rs650727 Controls 729 0.55 0.38 0.08 0.265 0.503
G/G G/A A/A f(A)
SNP 5 Bipolar 548 0.53 0.38 0.1 0.383 0.286 0.242 0.021
rs589247 Controls 733 0.55 0.38 0.08 0.264 0.501
G/G G/T T/T f(T)
SNP 6 Bipolar 546 0.45 0.41 0.15 0.0300 a 0.352 0.0487 a 0.007
rs669838 Controls 729 0.46 0.44 0.1 0.32 0.978
G/G G/A A/A f(A)
SNP 7 Bipolar 541 0.44 0.41 0.15 0.0522 0.358 0.0933 0.003
rs636173 Controls 735 0.45 0.44 0.11 0.326 1.000
T/T T/C C/C f(C)
SNP 8 Bipolar 556 0.59 0.36 0.05 0.708 0.232 0.944 0.865
rs3786285 Controls 728 0.6 0.34 0.06 0.231 0.226
A/A A/G G/G f(G)
SNP 9 Bipolar 556 0.4 0.45 0.15 0.737 0.376 0.699 0.270
rs613993 Controls 733 0.38 0.48 0.15 0.383 0.988
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*

P values for comparison of genotype frequencies between bipolar individuals and controls.

**

P values for comparison of allele frequencies between bipolar individuals and controls.

a

Global P value after 10,000 permutation correction for multiple testing was not statistically significant.

Figure 1.

Figure 1

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Linkage disequilibrium measures (D’) across a schematic diagram of the IMPA2 gene. White boxes denote untranslated regions while black boxes denote exons. From left to right, the SNPs are alligned from 5’ to 3’. LD patterns and haplotype blocks were defined by the “solid spine of LD” using the Haploview software. A standard color scheme is used to display LD pattern, with dark red for very strong LD, white for no LD, and shades of red for intermediate LD. Increasing intensity of red indicates increasing degrees of LD.

Table 2:

Analysis of common haplotypes in the IMPA2 gene.

Haplotype block Case frequencies Control frequencies Chi square P Value Permutation P value
Block 1
 ATT 0.6652 0.6946 2.567 0.1091 0.6965
 GCA 0.1898 0.1608 3.772 0.0521 0.3893
 GTA 0.0656 0.0539 1.610 0.2044 0.9069
 ATA 0.0449 0.0562 1.680 0.1950 0.8942
 GTT 0.0220 0.0298 1.479 0.2239 0.9358
Block 2
 CGGG 0.6366 0.6657 2.783 0.0953 0.6677
 TATA 0.2835 0.2574 2.071 0.1501 0.8476
 CGTA 0.0717 0.0591 1.627 0.2021 0.9014
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DISCUSSION

In the present study, we show several nominally significant associations between polymorphisms in the 5’ region of the IMPA2 gene on chromosome 18p and BPD; however, none of them remain statistically significant after correction for multiple testing. Markers with significant P-values are located in the 5’ region of the gene near the promoter region. Interestingly, two previous studies have implicated the promoter and 5’ region of the IMPA2 gene in BPD, one study in the Japanese population (Ohnishi et al., 2007) and one in an Arab-Palestinian sample (Sjøholt et al., 2004). While our marker selection differed from the two previous studies, all three studies implicate the 5’ region of the gene. Ohnishi et al (2007) demonstrated that a risk-haplotype spanning the promoter region enhanced transcription in vitro.

While our results are in line with previous linkage studies (Berrettini et al., 1994; Stine et al., 1995; McInnes et al., 1996; Bowen et al., 1999; Detera-Wadleigh et al., 1999; Nothen et al., 1999; Bennett et al., 2002; Mukherjee et al., 2006), recent genome wide association studies (GWAS) have not identified the IMPA2 gene or the 18p region in BPD (Baum et al., 2007; TheWelcomeTrustCaseControlConsortium, 2007; Sklar et al., 2008; Smith et al., 2009); however, it should be noted that the most recent GWAS still have limited coverage for certain genomic regions. The Affymetrix SNP Array 5.0 and 6.0 includes only SNP5, SNP7, and SNP9 while the Illumina Human1M-Duo BeadChip includes just SNP4 of the markers we selected in the IMPA2 gene. In addition, quality control steps in GWAS generally exclude markers that are significantly out of HWE, thus potentially missing true associations. We observed deviation from HWE for the cases in haplotype block 2 (SNP4, SNP6, SNP7) in which all markers are in very strong LD (Figure 1). Although this deviation may be indicative of genotyping error (Hosking et al., 2004), quality control steps that included 10% of samples that were genotyped twice showed high concordance rate for all markers (>99.5%), making genotyping error less likely. We suspect that the HWE deviations in case populations are reflective of detected marker-disease association, which can be indicated by deviations from HWE (Nielsen et al., 1998; Jiang et al., 2001; Lee, 2003). This hypothesis is consistent with the study by Ohnishi et al (2007) that also reported IMPA2 genotype distributions that deviated from HWE; however, other factors might contribute to the HWE deviation as well such as nonrandom mating, chance, inbreeding, differential survival of marker carriers and genetic drift. Hence, our results should be interpreted with caution.

The often observed discrepancy between candidate gene studies and GWAS results could be due to conceptional differences in design. Although the model of a “hypothesis-free” design in GWAS is appealing as a strategy to discover new genes and pathways involved in neuropsychiatric disease, this approach ignores many advances in neuroscience research and disregards a priori biological relevance. It is likely that much larger sample sizes are needed for GWAS, in the ten-thousands, in order to achieve adequate power in the face of multiple testing (Frayling, 2007). Our candidate gene was selected based on prior linkage evidence for BPD on chromosome 18p and two previous positive reports, as well as biological rationale. This approach, including cluster analyses of genes involved in neurobiological pathways, is thus still a reasonable strategy to investigate genetic factors of complex disorders. However, future studies might also have to sequence entire genomic regions of thousands of cases and controls in order to detect biologically relevant susceptibility factors.

Our study has several limitations that should be considered carefully. Spurious positive association findings, including our trend-level association, remain a valid concern as shown recently in a statistical simulation study of the COMT gene by Sullivan (2007). It is possible that our positive findings might be erroneous, as indicated by our correction for multiple testing results, due to population stratification. All cases and controls in this study were of European descent; however, undetected differences in population structure might contribute to false positive results in association studies (Pritchard and Donnelly, 2001; Freedman et al., 2004). Furthermore, cases and controls were not matched for age, gender or regional European ancestry which might result in population stratification effects. Possible strategies to control for these stratification issues are the use of genomic controls (Devlin and Roeder, 1999; Bacanu et al., 2000) and/or the use of a family-based association design, a strategy that matches the genotype of an affected offspring with parental alleles not inherited by the offspring (Spielman and Ewens, 1996). We only investigated bipolar I disorder patients, which might genetically differ from bipolar II patients and have not carried out secondary analyses including clinical subphenotypes, such as age of onset, positive family history, history of psychosis or frequency of mood episodes. These analyses will be important for future large scale studies with sufficient power to detect potential effects of subphenotypes.

In conclusion, we show associations between polymorphisms in the IMPA2 gene and BPD, which are not statistically significant after multiple testing corrections. While the study requires further replication in a larger sample, it does provide additional information on the 18p genomic region and serves to further characterize the complexity of this region that has been implicated in BPD. Additional functional experiments are necessary to investigate a role of the IMPA2 promoter region and implication for inositol pathway regulation.

ACKNOWLEDGEMENTS

This work was supported by the Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania. Financial support is gratefully acknowledged from National Institutes of Health grants K08 MH080372 (to F.W.L.), grants from the National Alliance for Research on Schizophrenia and Depression (F.W.L., W.H.B), and a grant from the Tzedakah Foundation to W.H.B. Most importantly, we thank the families who have participated in and contributed to these studies.

Data and biomaterials utilized in this study were collected as part of ten projects that participated in the National Institute of Mental Health (NIMH) Bipolar Disorder Genetics Initiative. From 1999-03, the Principal Investigators and Co-Investigators were: Indiana University, Indianapolis, IN, R01 MH59545, John Nurnberger, M.D., Ph.D., Marvin Miller, M.D., Elizabeth Bowman, M.D., N. Leela Rau, M.D, P. Ryan Moe, M.D., Nalini Samavedy, M.D., Rif El-Mallakh, M.D, (at University of Louisville), Husseini Manji, M.D. (at Wayne State University), Debra A. Blitz, M.D (at Wayne State University), Eric T. Meyer, M.S., Carrie Smiley, R.N., Tatiana Foroud, Ph.D., Leah Flury, M.S., Danielle M. Dick, Ph.D., Howard Edenberg, Ph.D.; Washington University, St. Louis, MO, R01 MH059534, John Rice, Ph.D., Theodore Reich, M.D., Allison Goate, Ph.D., Laura Bierut, M.D.; Johns Hopkins University, Baltimore, MD, R01 MH59533, Melvin McInnis, M.D., J. Raymond DePaulo, Jr., M.D., Dean F. MacKinnon, M.D., Francis M. Mondimore, M.D., James B. Potash, M.D., Peter P. Zandi, Ph.D, Dimitrios Avramopoulos, Jennifer Payne; University of Pennsylvania, PA, R01 MH59553, Wade Berrettini, M.D., Ph.D.; University of California at Irvine, CA, R01 MH60068, William Byerley, M.D. and Mark Vawter, M.D.; University of Iowa, IA, R01 MH059548, William Coryell, M.D., Raymond Crowe, M.D.; University of Chicago, IL, R01 MH059535, Elliot Gershon, M.D., Judith Badner, Ph.D., Francis McMahon, M.D., Chunyu Liu, Ph.D., Alan Sanders, M.D., Maria Caserta, Steven Dinwiddie, M.D., Tu Nguyen, Donna Harakal; University of California at San Diego, CA, R01 MH59567, John Kelsoe, M.D., Rebecca McKinney, B.A.; Rush University, IL, R01 MH059556, William Scheftner, M.D., Howard M. Kravitz, D.O., M.P.H., Diana Marta, B.S., Annette Vaughn-Brown, M.S.N., R.N., Laurie Bederow, M.A.; NIMH Intramural Research Program, Bethesda, MD, 1Z01MH02810-01, Francis J. McMahon, M.D., Layla Kassem, PsyD., Sevilla Derta-Wadleigh, Ph.D., Lisa Austin, Ph.D., Dennis L. Murphy, M.D.

Footnotes

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CONFLICT OF INTEREST

The authors declare that they have no conflict of interest.

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