No association of three GRIN2B polymorphisms with lithium response in bipolar patients

Szczepankiewicz, Aleksandra; Skibińska, Maria; Suwalska, Aleksandra; Hauser, Joanna; Rybakowski, Janusz

doi:10.1016/s1734-1140(09)70085-4

Cited by 34 publications

(30 citation statements)

References 16 publications

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“…Although no other studies investigating the role of the genes analyzed in the present study have been found, a previous report analyzing several genetic variability at the glucocorticoid receptor gene (NR3C1) showed association between this gene and Li response. 29 The results from the allele and genotype associations comparing the 3 different groups of Li responders (ER, PR, and NR) did not survive multiple testing in our sample. However, when we analyzed these SNPs comparing PR+NR versus ER, we found significant association surviving multiple testing for all of them except the polymorphism in the GRIK2 gene.…”

Section: Discussionmentioning

confidence: 79%

Exploring Genetic Variability at PI, GSK3, HPA, and Glutamatergic Pathways in Lithium Response

Mitjans¹,

Arias²,

Jiménez³

et al. 2015

Journal of Clinical Psychopharmacology

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Lithium is considered the first-line treatment in bipolar disorder, although response could range from an excellent response to a complete lack of response. Response to lithium is a complex phenotype in which different factors, part of them genetics, are involved. In this sense, the aim of this study was to investigate the potential association of genetic variability at genes related to phosphoinositide, glycogen synthetase kinase-3 (GSK3), hypothalamic-pituitary-adrenal, and glutamatergic pathways with lithium response. A sample of 131 bipolar patients (99 type I, 32 type II) were grouped and compared according to their level of response: excellent responders (ER), partial responders (PR), and nonresponders (NR). Genotype and allele distributions of the rs669838 (IMPA2), rs909270 (INNP1), rs11921360 (GSK3B), and rs28522620 (GRIK2) polymorphisms significantly differed between ER, PR, and NR. When we compared the ER versus PR+NR, the logistic regression showed significant association for rs669838-C (IMPA2; P = 0.021), rs909270-G (INPP1; P = 0.009), and rs11921360-A (GSK3B; P = 0.004) with lithium nonresponse. Haplotype analysis showed significant association for the haplotypes rs3791809-rs4853694-rs909270 (INPP1) and rs1732170-rs11921360-rs334558 (GSK3B) and lithium response. Our study is in line with previous studies reporting association between genetic variability at these genes and lithium response, pointing to an effect of IMPA2, INPP1, and GSK3B genes to lithium response in bipolar disorder patients. Further studies with larger samples are warranted to assess the strength of the reported associations.

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Section: Discussionmentioning

confidence: 79%

Exploring Genetic Variability at PI, GSK3, HPA, and Glutamatergic Pathways in Lithium Response

Mitjans¹,

Arias²,

Jiménez³

et al. 2015

Journal of Clinical Psychopharmacology

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“…Encodes inositol polyphosphate-1-phosphatase, one of the enzymes involved in phosphatidylinositol signaling pathways [90] A polymorphism in INPP1 C973A might be associated with the efficacy of lithium [110]. Significant interactions were also found between lithium response and INPP1 SNP rs206472 [14] CREB1 cAMP responsive element binding protein 1…”

Section: Inositol Polyphosphate-1--phosphatasementioning

confidence: 99%

Pharmacogenomics in the treatment of mood disorders: Strategies and Opportunities for personalized psychiatry

2017

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Personalized medicine (personalized psychiatry in a specific setting) is a new model towards individualized care, in which knowledge from genomics and other omic pillars (microbiome, epigenomes, proteome, and metabolome) will be combined with clinical data to guide efforts to new drug development and targeted prescription of the existing treatment options. In this review, we summarize pharmacogenomic studies in mood disorders that may lay the foundation towards personalized psychiatry. In addition, we have discussed the possible strategies to integrate data from omic pillars as a future path to personalized psychiatry. So far, the progress of uncovering single nucleotide polymorphisms (SNPs) underpinning treatment efficacy in mood disorders (e.g., SNPs associated with selective serotonin re-uptake inhibitors or lithium treatment response in patients with bipolar disorder and major depressive disorder) are encouraging, but not adequate. Genetic studies have pointed to a number of SNPs located at candidate genes that possibly influence response to; (a) antidepressants COMT, HTR2A, HTR1A, CNR1, SLC6A4, NPY, MAOA, IL1B, GRIK4, BDNF, GNB3, FKBP5, CYP2D6, CYP2C19, and ABCB1 and (b) mood stabilizers (lithium) 5-HTT, TPH, DRD1, FYN, INPP1, CREB1, BDNF, GSK3β, ARNTL, TIM, DPB, NR3C1, BCR, XBP1, and CACNG2. We suggest three alternative and complementary strategies to implement knowledge gained from pharmacogenomic studies. The first strategy can be to implement diagnostic, therapeutic, or prognostic genetic testing based on candidate genes or gene products. The second alternative is an integrative analysis (systems genomics approach) to combine omics data obtained from the different pillars of omics investigation, including genomics, epigenomes, proteomics, metabolomics and microbiomes. The main goal of system genomics is an identification and understanding of biological pathways, networks, and modules underlying drug-response. The third strategy aims to the development of multivariable diagnostic or prognostic algorithms (tools) combining individual's genomic information (polygenic score) with other predictors (e.g., omics pillars, neuroimaging, and clinical characteristics) to finally predict therapeutic outcomes. An integration of molecular science with that of traditional clinical practice is the way forward to drug discoveries and novel therapeutic approaches and to characterize psychiatric disorders leading to a better predictive, preventive, and personalized medicine (PPPM) in psychiatry. With future advances in the omics technology and methodological developments for data integration, the goal of PPPM in psychiatry is promising.

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“…The gene was a promising candidate based on its chromosomal location (12p12) and evidence of altered protein expression in bipolar disorder; however, no significant associations were found [32]. In a different study published recently, the same authors found a putative association with two SNPs of the glutamatergic FYN oncogene related to SRC, FGR, YES (FYN) with bipolar disorder in a cohort of 425 bipolar disorder patients and 518 controls [33].…”

Section: Candidate Gene Studiesmentioning

confidence: 99%

“…Szczepankiewicz et al [32] investigated the role of glutamatergic neurotransmission in Li response by investigating SNPs in the N-methyl D-aspartate (NMDA) receptor 2B subunit gene (GRIN2B) in a sample of 105 bipolar disorder patients treated with Li for at least 5 years and assessed for positive response. The gene was a promising candidate based on its chromosomal location (12p12) and evidence of altered protein expression in bipolar disorder; however, no significant associations were found [32].…”

Section: Candidate Gene Studiesmentioning

confidence: 99%

“…This protein kinase is functionally related to NMDA receptors involved in signal transduction mediation in the brain-derived neurotrophic factor (BDNF)/neurotrophic tyrosine kinase, receptor, type 2 (TrkB) pathway commonly altered in bipolar disorder [34]. When analyzing specifically Li prophylaxis in a follow-up study of the same SNPs, the group found no association with the rs6916861 SNPs and only a marginal association with rs3730353 [35].…”

Section: Candidate Gene Studiesmentioning

confidence: 99%

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Response to treatment in bipolar disorder

Cruceanu

Alda

Rouleau

et al. 2011

Current Opinion in Psychiatry

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Purpose of review-Bipolar disorder is a complex psychiatric condition that has been shown to carry a great degree of genetic loading. This review addresses current research in the genetics of treatment response in bipolar disorder, with a focus on findings that have shaped our understanding of the changing direction of this field in light of recent technological advancements.Recent findings-The recent publications in bipolar disorder treatment response have helped consolidate or improve upon knowledge of susceptibility loci and genes in the field. There seems to be an increasing trend toward functionally assessing the role played by putative candidate genes and molecular factors modulating expression in bipolar disorder, as well as a movement toward more global, pathway and genome-wide-oriented research.Summary-Genetic and molecular research to date in bipolar disorder treatment response has not completely answered all the lingering questions in the field, but has contributed to the development of a more patient-based understanding of treatment. In order to apply these findings at a clinical level, more comprehensive treatment response studies are imperative, combining recent advances in high-throughput genomics with functional molecular research.

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No association of three GRIN2B polymorphisms with lithium response in bipolar patients

Cited by 34 publications

References 16 publications

Exploring Genetic Variability at PI, GSK3, HPA, and Glutamatergic Pathways in Lithium Response

Exploring Genetic Variability at PI, GSK3, HPA, and Glutamatergic Pathways in Lithium Response

Pharmacogenomics in the treatment of mood disorders: Strategies and Opportunities for personalized psychiatry

Response to treatment in bipolar disorder

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