Influence of kynurenine 3-monooxygenase (KMO) gene polymorphism on cognitive function in schizophrenia

Abstract

Background

Cognitive deficits compromise quality of life and productivity for individuals with schizophrenia and have no effective treatments. Preclinical data point to the kynurenine pathway of tryptophan metabolism as a potential target for pro-cognitive drug development. We have previously demonstrated association of a kynurenine 3-monooxygenase (KMO) gene variant with reduced KMO gene expression in postmortem schizophrenia cortex, and neurocognitive endophenotypic deficits in a clinical sample. KMO encodes kynurenine 3-monooxygenase (KMO), the rate-limiting microglial enzyme of cortical kynurenine metabolism. Aberration of the KMO gene might be the proximal cause of impaired cortical kynurenine metabolism observed in schizophrenia. However, the relationship between KMO variation and cognitive function in schizophrenia is unknown. This study examined the effects of the KMO rs2275163C>T C (risk) allele on cognitive function in schizophrenia.

Methods

We examined the association of KMO polymorphisms with general neuropsychological performance and P50 gating in a sample of 150 schizophrenia and 95 healthy controls.

Results

Consistent with our original report, the KMO rs2275163C>T C (risk) allele was associated with deficits in general neuropsychological performance, and this effect was more marked in schizophrenia compared with controls. Additionally, the C (Arg⁴⁵²) allele of the missense rs1053230C>T variant (KMO Arg⁴⁵²Cys) showed a trend effect on cognitive function. Neither variant affected P50 gating.

Conclusions

These data suggest that KMO variation influences a range of cognitive domains known to predict functional outcome. Extensive molecular characterization of this gene would elucidate its role in cognitive function with implications for vertical integration with basic discovery.

Introduction

Cognitive deficits profoundly reduce the quality of life of individuals with schizophrenia, and have no effective treatments (Green, 1996, Gold et al., 2000, Green et al., 2000, Harvey et al., 2003, Jaaskelainen et al., 2013). Cognitive impairments predict functional outcomes (Green et al., 2000, Prouteau et al., 2005, Martinez-Aran et al., 2007), including unemployment status (Gold et al., 2002, Caspi et al., 2003, Goldberg and Gomar, 2009, Harvey et al., 2012, Sheffield et al., 2013), which partly underlie the high healthcare costs associated with schizophrenia (Insel, 2008, Kessler et al., 2008, Soni, 2009). Elucidating the neurobiological substrates of cognition could identify targets for developing rational pro-cognitive pharmacology for schizophrenia (Hyman and Fenton, 2003, Gold, 2004, Tamminga, 2006, Millan et al., 2012).

Preclinical evidence indicates that the kynurenine pathway (KP) of tryptophan metabolism is a valuable target for pro-cognitive drug development (Shepard et al., 2003, Erhardt et al., 2004, Chess et al., 2007, Chess et al., 2009, Potter et al., 2010, Wonodi and Schwarcz, 2010, Pocivavsek et al., 2012, Stone and Darlington, 2013). In the brain as in the periphery (Wolf, 1974, Stone, 1993, Guillemin et al., 1999), the KP generates two neuroactive metabolites – kynurenic acid (KYNA) and quinolinic acid (QUIN) – shown to modulate critical glutamatergic and cholinergic systems that regulate cognitive processes (Morris et al., 1986, Davis et al., 1992, Buffalo et al., 1994, Krystal et al., 1994, Newcomer and Krystal, 2001, Stone and Darlington, 2013) (Fig. 1). The excitotoxin QUIN is an agonist at glutamatergic N-methyl-d-aspartate receptors (NMDAR) (Stone and Perkins, 1981, Schwarcz et al., 1983), while KYNA is a competitive, broad-spectrum antagonist at ionotropic glutamate receptors, with its greatest affinity at the allosteric site on NMDAR (Perkins and Stone, 1982, Birch et al., 1988, Moroni et al., 1988, Foster et al., 1992, Stone, 1993, Parsons et al., 1997, Scharfman et al., 2000, Carpenedo et al., 2001, Erhardt et al., 2001b, Rassoulpour et al., 2005, Stone et al., 2013).

Another action attributed to KYNA is antagonism of α7 nicotinic acetylcholine receptors (α7nAChR) (Hilmas et al., 2001, Alkondon et al., 2004, Lopes et al., 2007, Alkondon et al., 2011a, Alkondon et al., 2011b), although some studies failed to demonstrate this (Mok et al., 2009, Dobelis et al., 2012). Notwithstanding, the emerging hypothesis of KYNA's role in cognition is based on the established roles of NMDAR (Krystal et al., 1994, Malhotra et al., 1996, Newcomer et al., 1999, Lahti et al., 2001) and α7nAChR (Kim and Levin, 1996, Newhouse et al., 1997, Levin and Simon, 1998, Rusted et al., 2000) in fundamental cognitive processes.

Elevated KYNA levels have been demonstrated in several psychiatric diseases marked by cognitive dysfunction, including schizophrenia (Schwarcz et al., 2001, Erhardt et al., 2001a, Nilsson et al., 2005, Linderholm et al., 2012 May; Sathyasaikumar et al., 2011), psychotic bipolar disorder (Olsson et al., 2010, Olsson et al., 2012, Lavebratt et al., 2014), HIV-associated neurocognitive disorders (Baran et al., 2000, Baran et al., 2012), and Alzheimer's disease (Baran et al., 1999). Relevant to schizophrenia, KYNA's role as an endogenous primary NMDAR antagonist converges with the established hypoglutamatergic hypothesis of schizophrenia (see reviews, Coyle, 1996, Coyle et al., 2003, Javitt, 2007). Evidence from our group suggests that downregulation of the KMO gene (OMIM 603538), which encodes kynurenine 3-monooxygenase (KMO) (EC 1.14.13.9), the rate-limiting microglial enzyme of the KP, might be the proximal cause of elevated KYNA levels observed in schizophrenia (Sathyasaikumar et al., 2011, Wonodi et al., 2011), a relationship recently investigated in KMO knockout mice (Giorgini et al., 2013). We previously showed an association between the CC genotype of KMO single nucleotide polymorphism (SNP) rs2275163C>T and significantly reduced KMO gene expression in postmortem schizophrenia prefrontal cortex from a region related to cognitive function; and in a clinical sample, the KMO risk allele (C) was associated with poor performance on oculomotor measures of predictive pursuit and visuospatial working memory (Wonodi et al., 2011). However, the relationship between KMO variation and cognitive function in humans is unknown. In the present study, we hypothesized that the rs2275163C>T risk allele, which was associated with reduced KMO messenger RNA (mRNA) expression (which would shunt KP metabolism towards enhanced KYNA formation) in our original report, would be associated with poor cognitive performance. Because a second non-synonymous variant in KMO, the C (Arg⁴⁵²) allele of rs1053230C>T (Arg⁴⁵²Cys) has also recently been associated with reduced KMO mRNA expression in brain and lymphoblastoid tissues, and with increased KYNA levels in cerebrospinal fluid (Holtze et al., 2012, Lavebratt et al., 2014), we additionally tested as a secondary aim, the association of this SNP with cognitive function in our sample. Lastly, we explored the effect of the KMO risk allele on P50 gating. Since P50 gating has been shown to not be correlated with general cognitive abilities, we anticipated association between the risk allele and cognitive function, but not necessarily with P50 suppression.