ArticleThe pharmacogenomics journal2005
Association study of myo-inositol monophosphatase 2 (IMPA2) polymorphisms with bipolar affective disorder and response to lithium treatment.
Article in The pharmacogenomics journal, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 36 citations in OpenAlex.
- Multi-omics analysis reveals that knockdown of IMPA2 induces apoptosis in cervical cancer cells through ROS/MYC/CDK1 signaling.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Genetic predictors of lithium response in an ethiopian cohort of patients with bipolar disorder.Annals of general psychiatry · 2026Article
- Genetic and Epigenetic Markers of Lithium Response.International journal of molecular sciences · 2022Review
- The Role of Pharmacogenomics in Bipolar Disorder: Moving Towards Precision Medicine.Molecular diagnosis & therapy · 2018Review
- Molecular actions and clinical pharmacogenetics of lithium therapy.Pharmacology, biochemistry, and behavior · 2014Review
- Response to lithium in bipolar disorder: clinical and genetic findings.ACS chemical neuroscience · 2014Review
- Genetic influences on response to mood stabilizers in bipolar disorder: current status of knowledge.CNS drugs · 2013Review
- Pharmacogenomics of mood stabilizers in the treatment of bipolar disorder.Human genomics and proteomics : HGP · 2010Article
- The genetics of bipolar disorder: genome 'hot regions,' genes, new potential candidates and future directions.Molecular psychiatry · 2008Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lithium is the most effective mood-stabilizing drug in the therapy of bipolar affective disorder (BP). It is thought to exert its effect via the phosphatidylinositol signalling system. Myo-inositol monophosphatase 2 (IMPA2) codes for an enzyme in this system that is inhibited by lithium. It is located on 18p11.2, a region implicated as a BP susceptibility locus. We examined eight single-nucleotide polymorphisms (SNPs) identified within this gene for association with BP, using 237 parents-offspring trios and in 174 cases and 170 controls. No SNP showed association with BP. When good responders to lithium treatment were compared with the poor responders, some statistically significant differences emerged for two SNPs; however, the sample became too small to draw definitive conclusions. We cannot find support for the involvement of variation in IMPA2 in susceptibility to bipolar disorder, but the role of this and other genes from the phosphoinositol signalling pathway in predicting response to lithium treatment merits further investigation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.