Understanding individual differences in the development of metabolic side effects as a response to antipsychotic therapy is essential to individualize the treatment of schizophrenia. In this study we performed GWAS on 12 quantitative metabolic side effect indicators including variables related to weight gain, a blood lipid panel, glucose, hemoglobin A1c, blood pressure and heart rate. We detected 21 SNPs, which, according to our pre-identified criteria (FDR controlled at 0.1 level), can be considered genomewide significant. For each of these markers the estimated posterior probability indicated a reasonable chance of a true finding.
Our top finding involved rs1568679 in MEIS2
reaching genomewide significance mediating the effect of risperidone on both hip and waist circumference and showing secondary associations with BMI, diastolic and systolic blood pressure. There was also some evidence that this SNP mediated olanzapine's effect on glucose. MEIS2
(Meis homeobox 2) is the second member of the human gene family with homology to the murine myeloid ecotropic viral integration site genes, involved in murine myeloid leukemia. The MEIS2
gene encodes a homeobox protein belonging to the TALE (Three Amino acid Loop Extension) family of homeodomain-containing proteins. TALE homeobox proteins are highly conserved transcription regulators and several members have been shown to be essential contributors to many developmental programs46
. In addition to critical roles in early development, usually acting as a Hox cofactor, MEIS2
has a transcriptional regulatory function in adults47
and is widely expressed in many tissues48
. Of particular note is its role in regulating the activity of PDX1, a transcription factor active in pancreatic β and acinar cells49
. It has been shown that MEIS2
switches the activity of PDX1 by forming the trimeric complex PDX1-PBX1b-MEIS250;51
. The full trimeric complex is necessary to activate a promoter for ELA1
in pancreatic acinar cells, while unbound PDX1 is necessary to activate insulin-producing β cells. Thus, the transcriptional activity of variants of MEIS2
may be differentially influenced by second generation antipsychotics (particularly risperidone), causing downstream changes in insulin and/or digestive enzyme production. Further, it is also clear that not every function of MEIS2
has yet been determined, as it is a highly complex locus, known to exist as at least 27 distinct splice variants (AceView). Given the robustness of the current association finding across multiple metabolic outcomes and the plausible mechanism suggested by former research, MEIS2
should be considered a promising candidate for further study.
The second and third most significant findings were with GPR98
, which were indicated to mediate the effects of olanzapine on hemoglobin A1c levels. GPR98
is a member of the G protein-coupled receptor superfamily of 7 transmembrane domain receptors52
. It binds calcium and is expressed in the central nervous system, although it is also expressed in a wide range of other tissues. GPR98
was originally known as VLGR1
, or very large G protein-coupled receptor, because it is comprised of over 90 exons that span approximately 600kb, with the largest transcript variant encoding a peptide of 6307 amino acid residues, making it the largest known cell surface protein53
has been previously implicated in some forms of epilepsy54
and in Usher syndrome55
(a disorder involving congenital hearing loss and progressive retinitis pigmentosa). There is no current evidence linking it mechanistically with hemoglobin A1c or glucose levels.
SNP rs13224682 in PRKAR2B
(Protein kinase, cyclic adensine monophosphate-dependent, regulatory, type II beta) was found to mediate clozapine's and, to a lesser extent, olanzapine's effects on triglyceride levels. The cAMP-dependent protein kinase system controls the cellular effects of cAMP, which acts as a second messenger in many signaling cascades. The kinase holoenzyme consists of two regulatory and two catalytic subunits that dissociate upon binding of cAMP molecules. The free, activated catalytic subunits then phosphorylate downstream proteins, thereby altering their activity or function. PRKAR2B
, also known as RII beta, is one of several regulatory subunit proteins56
RII beta has previously been strongly implicated in metabolic phenotypes and, in separate studies, antipsychotic effects in laboratory animals. First, RII beta knockout mice appear healthy but have markedly diminished white adipose tissue despite normal food intake. They are protected against developing diet-induced obesity and fatty livers57
. Furthermore, disruption of RII beta reverses the obesity syndrome of Agouti lethal yellow mice58
. One possible mechanism by which RII beta regulates weight is via its known role in the thyroid, where its as an important mediator of thyroid-stimulating hormone (TSH) receptor and cAMP signals to downstream membrane and nuclear substrates59
. Another potentially relevant mechanism is suggested by a search with the SLEP bioinformatic tool60
, which indicated that the marker is <1 kb from an expression QTL (eQTL) for liver, within the same gene, PRKAR2B61
. Second, in relation to antipsychotic effects, mice harboring a targeted disruption of RII beta have a profound deficit in cAMP-stimulated kinase activity in the striatum. When treated with haloperidol, RII beta mutant mice fail to induce either c-fos or neurotensin mRNA and the acute cataleptic response of haloperidol is blocked62
. These effects appear to arise because of the importance of cAMP, both in the regulation of metabolism and the transducing of the antipsychotic effect. Our association findings implicating this gene as a mediator of multiple related antipsychotic-induced metabolic outcomes, in addition to ample functional evidence indicating both metabolic function and antipsychotic mediation, make PRKAR2B
a compelling candidate for additional investigation.
Two SNPs at FHOD3
were shown to mediate perphenazine's effect on triglycerides at the q<0.1 level. FHOD3
(Formin homology-2 domain-containing protein 3) appears to be expressed in the kidney, heart and brain with little to no expression in other tissues. Its function appears to be as an actin-organizing protein in the cellular cytoskeleton63
. Very little else is known of this gene and its function, with only two articles concerning it published to date. Clearly, given this lack of information no firm conclusions about its putative drug-metabolism interaction can be drawn.
A small number of candidate genes have been previously implicated in mediating the metabolic side effects of antipsychotic drugs. These studies have typically focused on weight gain as the outcome measure for second generation antipsychotics. A recent review by Arranz and de Leon64
catalogued previous findings, suggesting positive associations with ADRA2A
. A recent large candidate gene study in CATIE65
also suggestively implicated HTR2A
. As the current study examined the same sample using different methods and a wider SNP panel, we examined the influence of these two candidate genes, as well as the six indicated by Arranz and de Leon. Additionally, we investigated five candidates indicated in a more recent pharmacogenetic study of antipsychotic-induced weight gain in a German sample66
, as well as several general metabolic candidates indicated in recent large meta-analyses of non-medicated samples67-73
. In total, 1338 SNPs within 45 candidate genes were selected on the basis of either being within the gene boundary or within 50kb flanking either end, leading to a total of 82,956 tests (1338 SNPs×62 outcomes). Numbers of SNPs per gene, a summary of analysis results and QQ plot are given in Supplemental Material A
. The most significant findings were rs1962882 in ABCA1
, mediating the effects of ziprasidone on waist-hip ratio (p
=0.99), followed by rs6449050 at SLC2A9
, mediating the effects of olanzapine on glucose levels (p
=0.99). These poor q
-values, coupled with the fact that none of the genes showed more significant findings than expected by chance, suggests limited support for these as true effects.
While CATIE remains the largest, most comprehensive clinical trial of antipsychotic treatment for schizophrenia with whole genome data, it was not principally designed as a pharmacogenomics study and, consequently, has several limitations in this context. Chief among these is the fact that most subjects were non-naïve to antipsychotic treatment at baseline and were often taking other, potentially confounding, medications with metabolic effects, including antidepressants and mood stabilizers. Moreover, DNA collection took place after the clinical trial and only included a subsample of CATIE participants (51%). As previously described, the genomic subsample had lower symptom severity, less current drug/alcohol abuse/dependence and were less likely to identify as African-American than CATIE subjects not contributing DNA25
. Despite statistical adjustment for these factors, inference would be stronger if the trial had a more ideal pharmacogenomics design. Thus, we recommend that future data collection efforts consider the merits of enrolling antipsychotic-naïve subjects, employing stricter recruitment criteria for confounding medications and implementing a more representative sampling frame. Additionally, future research can extend this line of research through incorporating dosage information into the calculation of treatment effects.
As with any genetic associations, our findings will require replication and functional validation. To facilitate this process we provide all p
) as a resource for investigators with the requisite samples to advance this line of research. However, the present study demonstrates the potential of GWAS to discover genes and pathways that mediate adverse effects of antipsychotic medication. A better understanding of these mechanisms and the role of specific polymorphisms may eventually help to personalize antipsychotic medication in order to minimize these adverse drug reactions for patients with schizophrenia.