Rethinking the genetic basis for comorbidity of schizophrenia and type 2 diabetes

Schizophrenia Research 123 (2010) 234–243

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Schizophrenia Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c h r e s

Review

Rethinking the genetic basis for comorbidity of schizophrenia and type 2 diabetes P.I. Lin a,b,⁎, A.R. Shuldiner c a b c

Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan Division of Endocrinology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States

a r t i c l e

i n f o

Article history: Received 23 December 2009 Received in revised form 29 July 2010 Accepted 12 August 2010 Available online 15 September 2010 Keywords: Type 2 diabetes Schizophrenia Genome-wide association study Endophenotype

a b s t r a c t The co-occurrence of schizophrenia (SCZ) and type 2 diabetes mellitus (T2D) has been well documented. This review article focuses on the hypothesis that the co-occurrence of SCZ and T2D may be, at least in part, driven by shared genetic factors. Previous genetic studies of T2D and SCZ evidence have disclosed a number of overlapped risk loci. However, the putative common genetic factors for SCZ and T2D remain inconclusive due to inconsistent findings. A systemic review of methods of identifying genetic loci contributing to the comorbidity link between SCZ and T2D is hence needed. In the current review article, we have discussed several different approaches to localizing the shared susceptibility genes for these two diseases. To begin with, one could start with probing the gene involved in both glucose and dopamine metabolisms. Additionally, hypothesis-free genome-wide association studies (GWAS) may provide more clues to the common genetic basis for these two diseases. Genetic similarities inferred from GWAS may shed some light on the genetic mechanism underlying the comorbidity link between SCZ and T2D. Meanwhile, endophenotypes (e.g., adiponectin level in T2D and working memory in SCZ) may serve as alternative phenotypes that are more directly influenced by genes than target diseases. Hence, endophenotypes of these diseases may be more tractable to identification. To summarize, novel approaches are needed to dissect the complex genetic basis of the comorbidity of SCZ and T2D. © 2010 Elsevier B.V. All rights reserved.

1. Introduction The risk of T2D has been found to be increased in schizophrenic patients across different ethnic groups. For instance, a recent study reported that T2D is more common in schizophrenics than normal controls in Canada, especially in young males (ages 30–39; odds ratio = 1.57; 95% CI: 1.30– 1.91) and females (ages 30–39; odds ratio = 1.72; 95% C.I.: 1.44–2.04) (Bresee et al., 2010). Another recent study also reported an elevated risk of T2D in schizophrenic individuals in Taiwan (odds ratio = 1.81; 95% C.I.: 1.61–2.03) (Chien et al., 2009). T2D manifests with persistent hyperglycemia due to pancreatic beta-cell dysfunction, which leads to long-term ⁎ Corresponding author. Tel.: + 886 972 653409. E-mail address: [email protected] (P.I. Lin). 0920-9964/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2010.08.022

complications, such as cardiovascular diseases, chronic renal failure, retinal, and nerve damage. Hence, T2D is one of the leading causes of morbidity and mortality in individuals affected with SCZ-related disorders (i.e., SCZ, schizoaffective disorder, and schizophreniform disorder) (Newcomer, 2007; Auquier et al., 2007). Therefore, it is critical to unravel the underlying mechanisms for the comorbidity link between T2D and SCZ-related disorders. 2. Hypotheses for the co-occurrence of T2D and SCZ Several models concerning the increase in risk of T2D in schizophrenic patients have been proposed (see Fig. 1). Overall, these models illustrate different hypotheses that do not necessarily refute each other. The hypotheses are listed as follows:

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circulating active form of Vitamin D, 1,25-OHD, to the ß-cell vitamin D receptor, or 1-α-hydroxylase enzyme that activates vitamin D within the ß-cell (Bland et al., 2004). 2.2. Hypothesis II: causal pathway

Fig. 1. The diagram presents three models for hypotheses concerning the comorbidity between SCZ and T2D. The dashed arrow indicates the causal relationship arising from the medical treatment rather than pathophysiological relationship.

2.1. Hypothesis I: common etiological factors The hypothesis in the first model proposes that T2D and SCZ are caused by shared etiological factors (i.e., genetic variants, environmental, and socioeconomic factors, etc.). Previous evidence has strongly suggested that T2D and SCZ are caused by multiple genetic variants (Gough and O'Donovan, 2005). Therefore, the comorbidity link between these two diseases may be influenced by shared susceptibility genetic variants that exert pleiotropic effects (i.e., the same DNA sequence causing various phenotypic products). In other words, each of these putative susceptibility genes may play a role in two different pathological pathways simultaneously, one associated with psychopathology inherent to SCZ and the other pertaining to glucose metabolism. For example, one may search for variants in the genes that connect the dopamine and insulin pathways in order to identify common susceptibility genetic loci for T2D and SCZ. Such putative common risk genes may increase the risks of these two diseases in the same individual. It may be reasonable to assume that this set of common susceptibility genes accounts for a fraction of individuals affected with SCZ and T2D, respectively. Hence, individuals affected with both SCZ and T2D may constitute a subgroup of patients with different etiological networks reflected by different clinical manifestations from individuals affected with SCZ without T2D or T2D without SCZ, respectively. In addition to genetic factors, environmental factors may also influence susceptibility to both SCZ and T2D. For example, poverty and lower educational attainment are associated with SCZ and increase the risk of obesity (Dixon et al., 2000). The cohort born during the Dutch famine in 1944–1945 was found to have elevated risks of both glucose tolerance impairment and SCZ (Kyle and Pichard, 2006). Therefore, prenatal and perinatal exposures to famine may be associated with some risk factors, such as malnutrition, for both T2D and SCZ. There have been several lines of evidence for associations of nutritional components with risks of SCZ and T2D. For instance, low vitamin D during early life has been found to be associated with risk of SCZ (McGrath et al., 2004; Brown and Susser, 2008). Vitamin D also influences the insulin response to glucose stimulation, although vitamin D has little impact on basal insulinemia (Zeitz et al., 2003; Bourlon et al., 1999). Previous evidence indicates that vitamin D modulates insulin response through either the binding of

The second model hypothesizes that T2D is one of complications of SCZ (Dynes, 1969). Schizophrenic patients may have some predisposing factors for metabolic syndrome. For instance, schizophrenic patients may be more prone to T2D because of risk factors such as limited access to appropriate primary care screening or treatment (Goldman, 1999) and psychological stress (Avignon and Monnier, 2001), compared with mentally healthy individuals. Additionally, hospitalization and negative symptoms (e.g., social withdrawal and psychomotor retardation) in schizophrenic individuals may lead to sedentary lifestyles (Gury, 2004), which may result in obesity associated with insulin resistance predisposing to T2D. Additionally, poor judgment associated with cognitive deficits inherent to SCZ may also play a role in poor health care (e.g., irregular health examination and unsatisfactory diet control, etc.) correlated with risk of T2D. 2.3. Hypothesis III: collateral damage — T2D induced by antipsychotics The third hypothesis proposes that the comorbidity link between T2D and SCZ is triggered by anti-psychotic medications. The increase in risk of T2D associated with the firstgeneration anti-psychotic use with phenothiazine was first reported in the late 1950s (Thonnard-Neumann, 1968; Lindenmayer et al., 2001). Recently, first-generation antipsychotics have been largely replaced by second-generation antipsychotics (a.k.a., atypical antipsychotics) in the treatment regimen of SCZ. However, atypical antipsychotics still pose a threat of metabolic syndrome. One of the atypical antipsychotics, clozapine, has been found to cause hyperglycemia (Sernyak et al., 2003; Lindenmayer et al., 2003; Newcomer et al., 2002; Haupt and Newcomer, 2001). Another atypical antipsychotic, olanzapine, has also been found to cause an increased risk of T2D. A recent study also reported that olanzapine and clozapine are associated with significant weight gain with concomitant increases in HOMA-IR, levels of insulin, total cholesterol, TG, LDL-C and leptin (Tschoner et al., 2009). How these atypical antipsychotics enhance the risk of T2D has remained unclear, while a number of explanations have been proposed. One of the putative mechanisms is that atypical antipsychotics may influence the risk of glucose metabolism by alternating the level of adiponectin, an adipocyte-derived hormone moderating lipid and carbohydrate metabolism. Yang et al. (2007) found that olanzapine could increase triacylglyceride accumulation during peripheral adipogenesis regulated by sterol regulatory element binding protein-1 (SREBP-1). Cooper et al. (2007) reported that olanzapine did not affect plasma levels of insulin, leptin, or glucose in male rats, but it might trigger the elevation of adiponectin. In addition to adipogenesis, sympathetic regulation may modulate the effect of atypical antipsychotics on the risk of T2D. Savoy et al. (2008) found that pretreatment with either the ganglionic blocker hexamethonium, or the α2 adrenergic receptor antagonist

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yohimbine, may hinder the hyperglycemic effect induced by clozapine and chlorpromazine. In this review article, a special interest has been placed on the first model, in which we focus on common susceptibility genes of these two diseases. The hypothesis that the comorbidity between T2D and SCZ is driven by common genetic components is posited based on two observations. First, previous evidence has strongly suggested the role of genetic variants in liabilities to T2D and SCZ, respectively. Second, both T2D and SCZ are reckoned as complex diseases since multiple genes are involved in their etiological pathways. Therefore, shared risk genes for T2D and SCZ may account for the comorbidity of these two diseases. To test this hypothesis, we need to assess whether the putative gene(s) can modulate the co-occurrence of these two diseases independent of the underlying mechanisms specific to the other two models. For example, to remove the confounding effect arising from environmental risk factors of T2D, such as sedentary life style associated with negative symptoms in schizophrenia, one needs to adjust for these factors in the genetic analysis. Another factor that may need to be taken into account is the use of antipsychotics. Since the comorbidity of SCZ and T2D was first reported before the era of antipsychotics, the increased risk of T2D cannot be entirely attributed to hyperglycemic effect of antipsychotics (Rouillon and Sorbara, 2005; Haddad, 2004). To remove the confounding effect of antipsychotics, one may consider recruiting medication-naïve individuals in the study, such as first-episode schizophrenic patients. Saddichha et al. (2008) reported that drug-naïve individuals affected with first-episode psychosis (FEP) have higher fasting 2-hour plasma glucose level, compared with healthy control subjects. Another study found that drug-naïve individuals with FEP have higher body mass index and higher plasma LDL cholesterol level, compared to healthy controls (Verma et al., 2009). They also found that the incidence of T2D is elevated in drug-naïve individuals with FEP than healthy controls (5.0% vs. 0.5%, p b 0.05). Taken together, these findings suggest that drug-naïve psychotic individuals are more likely to have risk factors for T2D than healthy individuals. Alternatively, first-degree relatives of schizophrenic patients may constitute another group of drug-naïve individuals at risk of SCZ. One study found that the risk of glucose intolerance is increased in siblings of schizophrenics compared to healthy controls (Fernandez-Egea et al., 2008). Spelman et al. (2007) also reported that first-degree relatives of schizophrenics have a higher risk of T2D than healthy controls (18.2% vs. 0%, p b 0.05). These approaches may help us circumvent the confounding effect of antipsychotics. 3. Common susceptibility genes of SCZ and T2D The most straightforward method to identify risk genes for comorbidity of SCZ and T2D is searching for overlapped candidate genes across genetic studies of these two individual diseases. One of the limitations of such approaches arises from inconsistent findings due to genetic heterogeneity reflected by clinical heterogeneity. In other words, studies focused on each individual disease may be conducted for subjects with only one diagnosis. Such studies may tend to identify genetic variants responsible for only SCZ or T2D. Table 1 summarizes the

common genetic linkage and association findings shared by studies of SCZ and T2D. According to the data queried from Genetic Association Database (http://geneticassociationdb.nih. gov/) (Becker et al., 2004) as of now, there are at least 338 candidate genes associated with T2D and 268 candidate genes associated with SCZ (both were queried based on the broad phenotypes). A total of 37 common genes are found across these susceptibility genes of two diseases. Hence, approximately 11% and 14% of putative risk genes for T2D and SCZ, respectively, may partially account for the comorbidity between these two diseases. Although linkages to both T2D and SCZ have been detected in chromosomes 2p22-13 and 6q21-14, no common candidate genes have been conclusively identified in these regions. Linkage studies also suggest that chromosome 1q may harbor genes influencing working memory (Gasperoni et al., 2003) and T2D-related traits (Zeggini et al., 2006; Ma et al., 2007; Hsueh et al., 2000). Association studies have suggested that chromosome 1q21-24 may harbor risk genes for T2D (Wolford et al., 2001). The chromosome 1q23 region contains a candidate gene, NOS1AP (nitric oxide synthase 1 (neuronal) adapter, aka, CAPON) gene, which has been suggested to play a role in SCZ (Zheng et al., 2005; Brzustowicz et al., 2004; Miranda et al., 2006; Lencz et al., 2007). The NOS1AP gene is overexpressed in the prefrontal cortex in schizophrenic patients (Xu et al., 2005). Additionally, a recent report found that the NOS1AP gene polymorphisms were strongly associated with electrocardiographic QT interval duration in a predominately diabetic population (Lehtinen et al., 2008). A recent study reported that human endogenous retrovirus K-18 located on chromosome 1q22-23 might be associated with T2D in schizophrenic patient (Dickerson et al., 2008). The DISC1 (disrupted in SCZ 1) gene on 1q42, another risk gene for SCZ, is also associated with working memory (Hennah et al., 2005). Another report found that the 1q42 region may contain genetic variants associated with T2D (Li et al., 2005). Therefore, these findings have suggested that chromosome 1q may harbor several genetic loci associated with the co-occurrence of T2D and SCZ. Genes involved in both glucose metabolism and cognitive function may increase the risk of T2D in schizophrenic patients and vice versa. For example, the glycogen synthase kinase 3 (GSK-3) gene is found to play a key role in dopamine pathways, wnt and insulin signal pathways (Lovestone et al., 2007). GSK-3 regulatory pathways are perturbed in schizophrenic patients, and many of the susceptibility genes of SCZ, such as DISC1 gene (Camargo et al., 2007), are found to directly regulate the GSK-3 activity. Other dopamine-related genes associated with risk of SCZ, such as catecholamine O-transferase gene (COMT), are also indirectly involved in the GSK-3 regulatory pathway since the AKT and GSK-3 genes regulate the physiological effects of dopamine signaling (Chen et al., 2007; Beaulieu et al., 2007). The link between dopamine and SCZ has been well documented (Di et al., 2007; Murray et al., 2008; Howes and Kapur, 2009), while insulin plays a pivotal role in pathogenesis of T2D. Taken together, GSK-3 gene may be responsible for the co-occurrence of T2D and SCZ. Another candidate gene, tyrosine hydroxylase (TH), may also contribute to the genetic basis for the co-occurrence of SCZ and T2D in light of robust biological evidence. The TH polymorphism has also been found to be associated with insulin resistance (Sten-Linder et al., 1993; Chiba et al., 2000)

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Table 1 Summary of shared genetic findings for SCZ and T2D. Chromosome Candidate genes regions

Functions

Associated diseases/traits

1p13.3 1p36.3 1q25 1q25.2– q25.3 1q24-21 a

GSM1 MTHFR PLA2G4A PTGS2

Glutathione S-transferase mu 1 5,10-methylenetetrahydrofolate reductase (NADPH) Phospholipase A2, group IVA Prostaglandin-endoperoxide synthase 2

SCZ, SCZ, SCZ, SCZ,

NOS1AP HERV-18 K No reported common candidate genes IL1B CTLA4 IRS1 GSK3B

1. Encoding nitric oxide synthase 1 (neuroal) adapter 2. Human endogenous retrovirus K-18

1. QT interval, sudden cardiac death, SCZ 2. Type 1 diabetes, type 2 diabetes

Interleukin 1 beta Cytotoxic T-lymphocyte-associated antigen 4 Insulin receptor substrate 1 Plays a role in Wnt signaling pathway; dopamine pathway; insulin signaling pathway Apolipoprotein D Cholescystokinin preproprotein Encoding transmembrane protein Epidermal growth factor Cocaine and amphetamine-regulated transcript 1. Major histocompatibility complex, class I, A 2. Major histocompatibility complex, class II, DQ α1 3. Major histocompatibility complex, class II, DQ β1 4. Major histocompatibility complex, class II, DR β1 5. Heat shock 70 kDa protein 1B 6. Tumor necrosis factor

SCZ, diabetic nephropathy SCZ, T2D SCZ, T2D Bipolar disorder, Alzheimer's disease,

Superoxide dismutase 2, mitochondrial Neuropeptide Y Interleukin 6 Paraoxonase 1 Leptin Solute carrier family 1, member 1 Encoding tyrosine hydroxylase

SCZ, T2D SCZ, T2D SCZ, T2D SCZ, T2D SCZ, T2D SCZ, T2D Bipolar disorder, body mass index, insulin resistance, type 1 diabetes (neighboring INS gene) SCZ, T2D

2p22-13

a

2q14 2q33 2q36 3q13 a 3q29 3p22.1 4p16 4q25 5q13.2 6p21.3

6q25.3 7p15.1 7p21 7q21.3 7q31.3 9p24 11p15

APOD CCK WFS1 EGF CARTPT 1. HLA-A 2. HLA-DQA1 3. HLA-DQB1 4. HLA-DRB1 5. HSPA1B 6. TNF No reported common candidate genes SOD2 NPY IL6 PON1 LEP SLC1A1 TH

Xq12

AR

6q21-24.1 a

a

Androgen receptor

T2D T2D T2D T2D

SCZ, T2D SCZ, T2D Bipolar disorder, Parkinson's disease, hearing loss SCZ, T2D SCZ, T2D SCZ, T2D

Evidence for linkage that has been reported by more than one study for either SCZ or T2D.

and schizophrenia (Wei et al., 1995; Meloni et al., 1995; Thibaut et al., 1997). TH is a tetrahydrobiopterin-requiring, ironcontaining monooxygenase. This enzyme catalyses the conversion of L-tyrosine to L-dopa, which is the rate-limiting step in the biosynthesis of catecholamines such as dopamine (Nagatsu, 1995). The TH gene is located near the insulin gene and insulinlike growth factor gene on the short arm of chromosome 11. Insulin has been found to modulate the expression of the TH gene at locus coeruleus and the adrenal medulla of rats (Vietor et al., 1996; Rusnák et al., 1998). Therefore, the TH gene may bridge the link between SCZ and T2D via the interplay between TH and other insulin-related genes. Another candidate gene, the DRD2 gene that encodes D2 subtype of dopamine receptor, has also been found to be associated with insulin and dopamine metabolism. Previous evidence indicates that DRD2 gene polymorphisms are associated with the risk of T2D. For instance, two nonsynonymous single nucleotide polymorphisms, Ser311Cys and Taq1A, located in the DRD2 gene, may contribute to the risk of T2D and obesity in Pima Indians (Jenkinson et al., 2000). Another study found that knockdown of the DRD2 gene by siRNA silencing may enhance glucose-dependent insulin secretion in pancreatic beta cells (Wu et al., 2008). Additionally, bromocriptine, a DRD2 agonist, could inhibit glucose-

dependent insulin secretion by direct activation of the alpha2adrenergic receptors in pancreatic beta cells (de Leeuw van Weenen et al., 2010). A recent study also shows that DRD2knockout mice may have attenuated glucose-stimulated insulin secretion instead of insulin resistance, which leads to glucose intolerance (García-Tornadú et al., 2010). The link between DRD2 gene and SCZ has been well documented. Two single nucleotide polymorphisms within the DRD2 gene, C957T and SER311Cys, have been consistently reported to be associated with risk of schizophrenia in different ethnic populations (see the review of Nobel, 2003). The C957T polymorphism has also been found to be involved in working memory (Jacobsen et al., 2006; Xu et al., 2007). Taken together, the dopamine pathway associated with D2 receptor may modulate insulin secretion in T2D and working memory in SCZ, respectively. Therefore, the DRD2 gene may contribute to the comorbidity link between SCZ and T2D. 4. Alternative strategy I: parsing genetic similarities through multiple genome-wide association studies Recent genome-wide association studies have provided a panoramic view of genetic architectures of complex diseases, including SCZ and T2D. Here, we used a web-based catalog for

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published genome-wide association studies (GWAS) to search for overlapped findings from these two diseases (Hindorff et al., 2009). The query was limited to traitassociated single nucleotide polymorphisms (SNPs) with a significance level of p b 10− 5 from GWAS published before January 1st of 2010, while the search did not yield any shared genetic association hits. Hence, the putative overlapped genetic findings for SCZ and T2D may be either (1) combinatorial rare variants, (2) variants other than SNPs, (3) variants with small effect, or (4) multiple variants acting in concert to cause the comorbidity link. Other alternative methods have been proposed to identify shared genetic risk factors across multiple diseases. For instance, Torkamani and colleagues exploited the results from GWAS of seven diseases to assess the resemblance between genetic architectures of two diseases. They examined the correlations of association signals between each SNP and disease, and found type I diabetes (T1D) to be genetically correlated with rheumatoid arthritis (RA) and T2D to be genetically associated with bipolar disorder (BD), respectively (Torkamani et al., 2008). Schaub and colleagues further proposed a classifier-based method to identify shared genetic risk factors. They trained a classifier that distinguishes a reference disease from a comparison set of diseases using “disease-class probability” derived from SNP-disease association information, and found genetic similarities between two disease pairs: T1D/RA and T2D/BD (Schaub et al., 2009). Therefore, novel bioinformatics methods may facilitate the identification of shared genetic pathways between T2D and SCZ. 5. Alternative strategy II: mapping the genes for endophenotypes T2D and SCZ are characterized by few overlapped clinical manifestations. As a result, the pathological link between these two diseases might be elusive if we only focus on the disease endpoints. Endophenotypes, which refer to associated pathological changes not yet reaching the threshold for diagnostic criteria, are thought to be influenced by genes of greater effects (Goldman and Ducci, 2007). Endophenotypes in psychiatric diseases may include neuropsychological, biochemical, endocrinological, neuroanatomical, cognitive, or neuropsychological components associated with the target disorder (Gottesman and Gould, 2003). The genetic loci modulating an endophenotype may need to interact with other genetic and environmental factors to further move towards to the disease endpoint. Hence, such an endophenotype is more proximal to a causative gene than the end stage disease state and thus may be more tractable to genetic study than the disease syndrome itself. 5.1. Endophenotypes related to SCZ Many of candidate endophenotypes in SCZ are neuropsychological markers. Although cognitive function deficits are not part of the diagnostic criteria based on DSM IV (American Psychiatric Association, 1994) and ICD-10 (WHO, 1993), most individuals affected with SCZ also suffer from cognitive deficits. Such neuropsychological problems may arise independent of medications since cognitive deficits can be found in medica-

tion-naïve schizophrenic patients (Bilder et al., 2000; Saykin et al., 1994). Among the cognitive functions, working memory, the cognitive capacity of storing temporary information for subsequent cognitive processing or to guide response selection (Baddeley, 1992), is a highly heritable trait (Ando et al., 2001; Kremen et al., 2007). The association between working memory deficits and SCZ has been well established (Goldman-Rakic, 1994; Barch, 2006; Honey and Fletcher, 2006). Additionally, it has been well documented that unaffected biological relatives of schizophrenic patients are more likely to suffer from impaired working memory than the general population (Myles-Worsley and Park, 2002; Thermenos et al., 2004; Hintze et al., 2004; Conklin et al., 2005; Brahmbhatt et al., 2006; Karlsgodt et al., 2007). Taken together, these lines of evidence suggest that working memory may serve as an intermediate phenotype associated with SCZ. Previous studies have suggested that candidate genes for SCZ, such as dopamine betahydroxylase (DBH) gene, CHRNA4, a nicotinic receptor subunit gene, (Parasuraman et al., 2005), and COMT gene, (Ho et al., 2005; Bertolino et al., 2006), may influence working memory. Another interesting endophenotype is smooth pursuit eye movement (SPEM), which refers to the movement of the eyes in tracking a slowly moving target, a process initiated by visual processing of motion signals (i.e., extraretinal motion). Deficits in SPEM may reflect defective visual spatial working memory (Park et al., 1995; Park and Holzman, 1993). SPEM has turned out to be a very useful endophenotype for SCZ. First, one of the major SPEM sub-measurements, predictive pursuit gain, is highly heritable (heritability estimate = 0.90) (Hong et al., 2006), indicating that this trait is under substantial genetic control. Second, both schizophrenic patients and their unaffected relatives are more likely than healthy individuals to have deficits in SPEM, suggesting that this trait co-segregates with SCZ. Genetic analysis of SPEMrelated phenotypes has provided further insights into underlying genetic mechanisms for SCZ. For example, two studies have reported evidence for linkage of SPEM phenotypes to 6p23-21, suggesting that this chromosomal region may harbor one (or more) genes influencing variation in SPEM (Arolt et al., 1996; Matthysse et al., 2004). Interestingly, the same region also harbors two genes, ATXN1 (SCA1) and NOTCH4 gene, which are associated with risk of SCZ (Waterworth et al., 2002). Chromosome 6p21-23 has been also reported to contain several genes such as KIAA0319 and DCDC2 associated with dyslexia (Brkanac et al., 2007; Harold et al., 2006; Cope et al., 2005). Dyslexic adults manifest with reading difficulty, which is thought to be caused by abnormalities in visuospatial/motor coordination in working memory. Hence, dyslexia and SPEM may share a similar genetic liability. Other candidate genes associated with SPEM include dopamine D3 receptor gene (DRD3), (Rybakowski et al., 2001) DISC1 (Hennah et al., 2005), and COMT genes (Rybakowski et al., 2002). 5.2. Endophenotypes related to type 2 diabetes Biomarkers related to glucose metabolism, such as fasting plasma glucose level, fasting plasma insulin level, and insulin resistance, play a critical role in the pathogenesis of T2D, and hence they may serve as endophenotypes for T2D. (Ferrannini et al., 1991; Reaven, 1988). All of these predisposing factors for

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T2D have been found to be at least moderately heritable (heritability estimate 0.3–0.6) (Edwards et al., 1997; Hsueh et al., 2000; Freeman et al., 2002; Mills et al., 2004; Poulsen et al., 2005; Lehtovirta et al., 2005; Bayoumi et al., 2007). A number of whole genome association scans for T2D identified several well-replicated genes/loci, several of which are also associated with glucose-homeostasis-related quantitative traits, including insulin secretion. These include CDKAL1, SLC30A8, IGF2BP2 and LOC387761 loci (Palmer et al., 2008). Other genes/loci associated with serum glucose levels include G6PC2 (Chen et al., 2008) and MTNR1B (Bouatia-Naji et al., 2009). Other well established risk factors associated with T2D, such as body mass index (BMI), might also serve as intermediate phenotypes or endophenotypes for T2D. Recent genome-wide association scans have revealed that the FTO is associated with increased BMI, hip circumference, and weight (Scuteri et al., 2007; Frayling et al., 2007). The FTO gene has also been found to be associated with risk of T2D from recent genome-wide association scans (Scott et al., 2007; Pascoe et al., 2007). Therefore, these quantitative biomarkers directly or indirectly involved in glucose metabolism may serve as endophenotypes for T2D. Studying these biomarkers may help ameliorate the problem of complex phenotype–genotype relationship. 5.3. Molecular link between glucose metabolism and working memory Plasma glucose level has been found to be associated with brain functions, such as learning and memory. A great body of evidence indicates that glucose may act as an enhancer for cognitive functions (Wenk, 1989; Gold, 1995; Benton et al., 1996; Greenwood, 2003). However, it has also been well documented that hyperglycemia is associated with poorer cognitive functions, such as working memory (Sommerfield et al., 2004; Papanikolaou et al., 2006). In addition, improving metabolic control may improve working memory in patients affected with T2D (Ryan et al., 2006). Furthermore, cognitive

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function impairment in childhood may be associated with the risk of T2D in adulthood (Olsson et al., 2008). Therefore, the mechanism underlying both working memory and glucose metabolism may bridge the comorbidity link between T2D and SCZ. To assess the causal relationship between working memory and glucose metabolism, one might need to take into consideration the temporal relationship between SCZ and T2D. The age of onset in SCZ is usually several years earlier than the age of onset in T2D. Therefore, glucose metabolism imbalance predisposing to T2D may, at best, modulate cognitive deficits in the prodromal period of SCZ. Additionally, cognitive deficits may worsen blood sugar control, and hence increase the risk of T2D. Here, we postulate a model that incorporates multiple pathways connecting genetic loci with endophenotypes and phenotypes in Fig. 2. In this model, shared susceptibility genetic loci (GCom in Fig. 2) may contribute to SCZ (through working memory deficits) and T2D (through glucose metabolism imbalance). Another two sets of genes: GT2D that denotes loci primarily associated with T2D and GSCZ that denotes loci primarily associated with SCZ, may also contribute to the coexistence of these two diseases. Once working memory deficits progresses to more severe cognitive deficits, mild glucose metabolism dysfunction may be more likely to be converted to T2D (effect e1 in Fig. 2). On the other hand, glucose metabolism impairment may expedite the process of cognitive function declining, and hence increase the susceptibility to SCZ for at-risk individuals (effect d1 in Fig. 2). In summary, the comorbidity between SCZ and T2D may be modulated by the interplay of the common genetic pathway and other loci directly influencing glucose metabolism or cognitive function related to SCZ. 6. Conclusions Studying the common genetic pathway for SCZ and T2D will yield significant implications. First, unraveling the genetic basis for comorbidity between these two diseases will shed some light on the biological mechanism underlying

Fig. 2. The diagram illustrates multiple theoretical pathways leading to SCZ and T2D. GT2D denotes genetic variants primarily linked to T2D, GSCZ denotes genetic variants primarily linked to SCZ, and GCom denotes genetic variants causing both T2D and SCZ. The open circles indicate mild prodromal changes predisposing to either T2D or SCZ; the grey circles indicate more severe prodromal changes predisposing to either T2D or SCZ; the black circles indicate the target diseases. The thick arrows indicate the pathways directly involved in the comorbidity between SCZ and T2D; the thin arrows indicate pathways not directly involved in the comorbidity between the two diseases; the broken arrows indicate the effects of interactions (i.e., d1 may modulate c2, and e1 may modulate c2).

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the elevated risk of T2D in schizophrenia. A better understanding of the pathological substrate may lead to the development of novel treatments. Second, genetic findings may lay out the foundation for gene–environment interaction, and hence help us clarify the role of environmental factors in the link between SCZ and T2D. Third, pharmacogenomic studies will facilitate the development of personalized treatment and prevention modalities for schizophrenics affected with T2D. Needless to say, the identification of genetic loci associated with the co-occurrence of T2D and SCZ is complicated by several factors, such as environmental and iatrogenic factors (e.g., antipsychotics). In addition, both T2D and SCZ are thought to be caused by multiple genetic variants that exert pleiotropic and epistatic effects. Therefore, one needs to take these issues into account to dissect the common genetic basis for these two disorders. Meanwhile, genome-wide association studies have promised to deliver a more complete array of susceptibility genetic variants for complex diseases. Genetic similarities between T2D and SCZ might be parsed through the overwhelming genetic association information, and thus provide us with better clues to shared genetic pathways. Lastly, endophenotypes may open an alternative avenue for study of molecular pathogenesis for the cooccurrence of T2D and SCZ. Careful assessment of appropriate T2D-related endophenotypes associated with SCZ-related endophenotypes may help discover novel risk genes for the comorbidity of these two diseases. Role of funding source The role of the funding source is to provide partial salary support for the authors. Contributors The contributors include P.I. Lin (first author and corresponding author) and A.R. Shuldiner. P.I. Lin designed the framework of this article and wrote the whole manuscript, and A.R. Shuldiner made substantial comments and edited the whole manuscript. Conflict of interest The authors have no conflict of interest to claim. Acknowledgement The corresponding author is currently supported by the NIH grant 1R01 MH77852.

References American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. American Psychiatric Press, Wasington, DC. text revised. Ando, J., Ono, Y., Wright, M.J., 2001. Genetic structure of spatial and verbal working memory. Behav. Genet. 31, 615–624. Arolt, V., Lencer, R., Nolte, A., Muller-Myhsok, B., Purmann, S., Schurmann, M., Leutelt, J., Pinnow, M., Schwinger, E., 1996. Eye tracking dysfunction is a putative phenotypic susceptibility marker of schizophrenia and maps to a locus on chromosome 6p in families with multiple occurrence of the disease. Am. J. Med. Genet. 67, 564–579. Auquier, P., Lancon, C., Rouillon, F., Lader, M., 2007. Mortality in schizophrenia. Pharmacoepidemiol. Drug Saf. 16, 1308–1312. Avignon, A., Monnier, L., 2001. Insulin sensitivity and stress. Diabetes Metab. 27, 233–238. Baddeley, A., 1992. Working memory. Science 255, 556–559. Barch, D.M., 2006. What can research on schizophrenia tell us about the cognitive neuroscience of working memory? Neuroscience 139, 73–84. Bayoumi, R.A., Al Yahyaee, S.A., Albarwani, S.A., Rizvi, S.G., Al Hadabi, S., Al Ubaidi, F.F., Al Hinai, A.T., Al Kindi, M.N., Adnan, H.T., Al Barwany, H.S., Comuzzie, A.G., Cai, G., Lopez-Alvarenga, J.C., Hassan, M.O., 2007.

Heritability of determinants of the metabolic syndrome among healthy Arabs of the Oman family study. Obesity (Silver Spring). 15, 551–556. Beaulieu, J.M., Gainetdinov, R.R., Caron, M.G., 2007. The Akt-GSK-3 signaling cascade in the actions of dopamine. Trends Pharmacol. Sci. 28 (4), 166–172. Becker, K.G., Barnes, K.C., Bright, T.J., Wang, S.A., 2004. The genetic association database. Nat. Genet. 36, 431–432. Benton, D., Parker, P.Y., Donohoe, R.T., 1996. The supply of glucose to the brain and cognitive functioning. J. Biosoc. Sci. 28, 463–479. Bertolino, A., Caforio, G., Petruzzella, V., Latorre, V., Rubino, V., Dimalta, S., Torraco, A., Blasi, G., Quartesan, R., Mattay, V.S., Callicott, J.H., Weinberger, D.R., Scarabino, T., 2006. Prefrontal dysfunction in schizophrenia controlling for COMT Val158Met genotype and working memory performance. Psychiatry Res. 147, 221–226. Bilder, R.M., Goldman, R.S., Robinson, D., Reiter, G., Bell, L., Bates, J.A., Pappadopulos, E., Willson, D.F., Alvir, J.M., Woerner, M.G., Geisler, S., Kane, J.M., Lieberman, J.A., 2000. Neuropsychology of first-episode schizophrenia: initial characterization and clinical correlates. Am. J. Psychiatry 157, 549–559. Bland, R., Markovic, D., Hills, C.E., Hughes, S.V., Chan, S.L., Squires, P.E., Hewison, M., 2004. Expression of 25-hydroxyvitamin D3-1alphahydroxylase in pancreatic islets. J. Steroid Biochem. Mol. Biol. 89–90, 121–125. Bouatia-Naji, N., Bonnefond, A., Cavalcanti-Proenca, C., Sparso, T., Holmkvist, J., Marchand, M., Delplanque, J., Lobbens, S., Rocheleau, G., Durand, E., De, G.F., Chevre, J.C., Borch-Johnsen, K., Hartikainen, A.L., Ruokonen, A., Tichet, J., Marre, M., Weill, J., Heude, B., Tauber, M., Lemaire, K., Schuit, F., Elliott, P., Jorgensen, T., Charpentier, G., Hadjadj, S., Cauchi, S., Vaxillaire, M., Sladek, R., Visvikis-Siest, S., Balkau, B., Levy-Marchal, C., Pattou, F., Meyre, D., Blakemore, A.I., Jarvelin, M.R., Walley, A.J., Hansen, T., Dina, C., Pedersen, O., Froguel, P., 2009. A variant near MTNR1B is associated with increased fasting plasma glucose levels and type 2 diabetes risk. Nat. Genet. 41, 89–94. Bourlon, P.M., Faure-Dussert, A., Billaudel, B., 1999. The de novo synthesis of numerous proteins is decreased during vitamin D3 deficiency and is gradually restored by 1, 25-dihydroxyvitamin D3 repletion in the islets of langerhans of rats. J. Endocrinol. 162, 101–109. Brahmbhatt, S.B., Haut, K., Csernansky, J.G., Barch, D.M., 2006. Neural correlates of verbal and nonverbal working memory deficits in individuals with schizophrenia and their high-risk siblings. Schizophr. Res. 87, 191–204. Bresee, L.C., Majumdar, S.R., Patten, S.B., Johnson, J.A., 2010. Prevalence of cardiovascular risk factors and disease in people with schizophrenia: a population-based study. Schizophr. Res. 117, 75–82. Brkanac, Z., Chapman, N.H., Matsushita, M.M., Chun, L., Nielsen, K., Cochrane, E., Berninger, V.W., Wijsman, E.M., Raskind, W.H., 2007. Evaluation of candidate genes for DYX1 and DYX2 in families with dyslexia. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144, 556–560. Brown, A.S., Susser, E.S., 2008. Prenatal nutritional deficiency and risk of adult schizophrenia. Schizophr. Bull. 34, 1054–1063. Brzustowicz, L.M., Simone, J., Mohseni, P., Hayter, J.E., Hodgkinson, K.A., Chow, E.W., Bassett, A.S., 2004. Linkage disequilibrium mapping of schizophrenia susceptibility to the CAPON region of chromosome 1q22. Am. J. Hum. Genet. 74, 1057–1063. Camargo, L.M., Collura, V., Rain, J.C., Mizuguchi, K., Hermjakob, H., Kerrien, S., Bonnert, T.P., Whiting, P.J., Brandon, N.J., 2007. Disrupted in Schizophrenia 1 Interactome: evidence for the close connectivity of risk genes and a potential synaptic basis for schizophrenia. Mol. Psychiatry 12, 74–86. Chen, W.M., Erdos, M.R., Jackson, A.U., Saxena, R., Sanna, S., Silver, K.D., Timpson, N.J., Hansen, T., Orru, M., Grazia, P.M., Bonnycastle, L.L., Willer, C.J., Lyssenko, V., Shen, H., Kuusisto, J., Ebrahim, S., Sestu, N., Duren, W.L., Spada, M.C., Stringham, H.M., Scott, L.J., Olla, N., Swift, A.J., Najjar, S., Mitchell, B.D., Lawlor, D.A., Smith, G.D., Ben-Shlomo, Y., Andersen, G., Borch-Johnsen, K., Jorgensen, T., Saramies, J., Valle, T.T., Buchanan, T.A., Shuldiner, A.R., Lakatta, E., Bergman, R.N., Uda, M., Tuomilehto, J., Pedersen, O., Cao, A., Groop, L., Mohlke, K.L., Laakso, M., Schlessinger, D., Collins, F.S., Altshuler, D., Abecasis, G.R., Boehnke, M., Scuteri, A., Watanabe, R.M., 2008. Variations in the G6PC2/ABCB11 genomic region are associated with fasting glucose levels. J. Clin. Invest. 118, 2620–2628. Chen, P.C., Lao, C.L., Chen, J.C., 2007. Dual alteration of limbic dopamine D1 receptor-mediated signalling and the Akt/GSK3 pathway in dopamine D3 receptor mutants during the development of methamphetamine sensitization. J. Neurochem. 100(1), 225–241. Chiba, M., Suzuki, S., Hinokio, Y., Hirai, M., Satoh, Y., Tashiro, A., Utsumi, A., Awata, T., Hongo, M., Toyota, T., 2000. Tyrosine hydroxylase gene microsatellite polymorphism associated with insulin resistance in depressive disorder. Metabolism 49, 1145–1149. Chien, I.C., Hsu, J.H., Lin, C.H., Bih, S.H., Chou, Y.J., Chou, P., 2009. Prevalence of diabetes in patients with schizophrenia in Taiwan: a population-based National Health Insurance study. Schizophr. Res. 111, 17–22.

P.I. Lin, A.R. Shuldiner / Schizophrenia Research 123 (2010) 234–243 Conklin, H.M., Curtis, C.E., Calkins, M.E., Iacono, W.G., 2005. Working memory functioning in schizophrenia patients and their first-degree relatives: cognitive functioning shedding light on etiology. Neuropsychologia 43, 930–942. Cooper, G.D., Pickavance, L.C., Wilding, J.P., Harrold, J.A., Halford, J.C., Goudie, A.J., 2007. Effects of olanzapine in male rats: enhanced adiposity in the absence of hyperphagia, weight gain or metabolic abnormalities. J. Psychopharmacol. 21, 405–413. Cope, N., Harold, D., Hill, G., Moskvina, V., Stevenson, J., Holmans, P., Owen, M. J., O'Donovan, M.C., Williams, J., 2005. Strong evidence that KIAA0319 on chromosome 6p is a susceptibility gene for developmental dyslexia. Am. J. Hum. Genet. 76, 581–591. de Leeuw van Weenen, J.E., Parlevliet, E.T., Maechler, P., Havekes, L.M., Romijn, J.A., Ouwens, D.M., Pijl, H., Guigas, B., 2010. The dopamine receptor D2 agonist bromocriptine inhibits glucose-stimulated insulin secretion by direct activation of the alpha2-adrenergic receptors in beta cells. Biochem. Pharmacol. 79 (12), 1827–1836. Di, F.M., Lappin, J.M., Murray, R.M., 2007. Risk factors for schizophrenia—all roads lead to dopamine. Eur. Neuropsychopharmacol. 17 (Suppl 2), S101–S107. Dickerson, F., Rubalcaba, E., Viscidi, R., Yang, S., Stallings, C., Sullens, A., Origoni, A., Leister, F., Yolken, R., 2008. Polymorphisms in human endogenous retrovirus K-18 and risk of type 2 diabetes in individuals with schizophrenia. Schizophr. Res. 104, 121–126. Dixon, L., Weiden, P., Delahanty, J., Goldberg, R., Postrado, L., Lucksted, A., Lehman, A., 2000. Prevalence and correlates of diabetes in national schizophrenia samples. Schizophr. Bull. 26, 903–912. Dynes, J.B., 1969. Diabetes in schizophrenia and diabetes in non-psychotic medical patients. Dis. Nerv. Syst. 30, 341–344. Edwards, K.L., Newman, B., Mayer, E., Selby, J.V., Krauss, R.M., Austin, M.A., 1997. Heritability of factors of the insulin resistance syndrome in women twins. Genet. Epidemiol. 14, 241–253. Fernandez-Egea, E., Bernardo, M., Parellada, E., Justicia, A., Garcia-Rizo, C., Esmatjes, E., Conget, I., Kirkpatrick, B., 2008. Glucose abnormalities in the siblings of people with schizophrenia. Schizophr. Res. 103, 110–113. Ferrannini, E., Haffner, S.M., Mitchell, B.D., Stern, M.P., 1991. Hyperinsulinaemia: the key feature of a cardiovascular and metabolic syndrome. Diabetologia 34, 416–422. Frayling, T.M., Timpson, N.J., Weedon, M.N., Zeggini, E., Freathy, R.M., Lindgren, C.M., Perry, J.R., Elliott, K.S., Lango, H., Rayner, N.W., Shields, B., Harries, L.W., Barrett, J.C., Ellard, S., Groves, C.J., Knight, B., Patch, A.M., Ness, A.R., Ebrahim, S., Lawlor, D.A., Ring, S.M., Ben Shlomo, Y., Jarvelin, M.R., Sovio, U., Bennett, A.J., Melzer, D., Ferrucci, L., Loos, R.J., Barroso, I., Wareham, N.J., Karpe, F., Owen, K.R., Cardon, L.R., Walker, M., Hitman, G.A., Palmer, C.N., Doney, A.S., Morris, A.D., Smith, G.D., Hattersley, A.T., McCarthy, M.I., 2007. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894. Freeman, M.S., Mansfield, M.W., Barrett, J.H., Grant, P.J., 2002. Heritability of features of the insulin resistance syndrome in a community-based study of healthy families. Diabet. Med. 19, 994–999. García-Tornadú, I., Ornstein, A.M., Chamson-Reig, A., Wheeler, M.B., Hill, D.J., Arany, E., Rubinstein, M., Becu-Villalobos, D., 2010. Disruption of the dopamine d2 receptor impairs insulin secretion and causes glucose intolerance. Endocrinology 51 (4), 1441–1450. Gasperoni, T.L., Ekelund, J., Huttunen, M., Palmer, C.G., Tuulio-Henriksson, A., Lonnqvist, J., Kaprio, J., Peltonen, L., Cannon, T.D., 2003. Genetic linkage and association between chromosome 1q and working memory function in schizophrenia. Am. J. Med. Genet. B Neuropsychiatr. Genet. 116, 8–16. Gold, P.E., 1995. Role of glucose in regulating the brain and cognition. Am. J. Clin. Nutr. 61, 987S–995S. Goldman, L.S., 1999. Medical illness in patients with schizophrenia. J. Clin. Psychiatry 60 (Suppl 21), 10–15. Goldman, D., Ducci, F., 2007. Deconstruction of vulnerability to complex diseases: enhanced effect sizes and power of intermediate phenotypes. Sci.World J. 7, 124–130. Goldman-Rakic, P.S., 1994. Working memory dysfunction in schizophrenia. J. Neuropsychiatry Clin. Neurosci. 6, 348–357. Gottesman, I.I., Gould, T.D., 2003. The endophenotype concept in psychiatry: etymology and strategic intentions. Am. J. Psychiatry 160, 636–645. Gough, S.C., O'Donovan, M.C., 2005. Clustering of metabolic comorbidity in schizophrenia: a genetic contribution? J. Psychopharmacol. 19, 47–55. Greenwood, C.E., 2003. Dietary carbohydrate, glucose regulation, and cognitive performance in elderly persons. Nutr. Rev. 61, S68–S74. Gury, C., 2004. Schizophrenia, diabetes mellitus and antipsychotics. Encephale 30, 382–391. Haddad, P.M., 2004. Antipsychotics and diabetes: review of non-prospective data. Br. J. Psychiatry Suppl. 47, S80–S86.

241

Harold, D., Paracchini, S., Scerri, T., Dennis, M., Cope, N., Hill, G., Moskvina, V., Walter, J., Richardson, A.J., Owen, M.J., Stein, J.F., Green, E.D., O'Donovan, M.C., Williams, J., Monaco, A.P., 2006. Further evidence that the KIAA0319 gene confers susceptibility to developmental dyslexia. Mol. Psychiatry 11 (1085–91), 1061. Haupt, D.W., Newcomer, J.W., 2001. Hyperglycemia and antipsychotic medications. J. Clin. Psychiatry 62 (Suppl 27), 15–26. Hennah, W., Tuulio-Henriksson, A., Paunio, T., Ekelund, J., Varilo, T., Partonen, T., Cannon, T.D., Lonnqvist, J., Peltonen, L., 2005. A haplotype within the DISC1 gene is associated with visual memory functions in families with a high density of schizophrenia. Mol. Psychiatry 10, 1097–1103. Hindorff, L.A., Sethupathy, P., Junkins, H.A., Ramos, E.M., Mehta, J.P., Collins, F.S., Manolio, T.A., 2009. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA 106, 9362–9367. Hintze, B., Bembenek, A., Kuhn-Dymecka, A., Wronska, A., Wciorka, J., 2004. Working memory dysfunction in patients suffering from schizophrenia and their first-degree relatives. Psychiatr. Pol. 38, 847–860. Ho, B.C., Wassink, T.H., O'Leary, D.S., Sheffield, V.C., Andreasen, N.C., 2005. Catechol-O-methyl transferase Val158Met gene polymorphism in schizophrenia: working memory, frontal lobe MRI morphology and frontal cerebral blood flow. Mol. Psychiatry 10 (229), 287–298. Honey, G.D., Fletcher, P.C., 2006. Investigating principles of human brain function underlying working memory: what insights from schizophrenia? Neuroscience 139, 59–71. Hong, L.E., Mitchell, B.D., Avila, M.T., Adami, H., McMahon, R.P., Thaker, G.K., 2006. Familial aggregation of eye-tracking endophenotypes in families of schizophrenic patients. Arch. Gen. Psychiatry 63, 259–264. Howes, O.D., Kapur, S., 2009. The dopamine hypothesis of schizophrenia: version III—the final common pathway. Schizophr. Bull. 35, 549–562. Hsueh, W.C., Mitchell, B.D., Aburomia, R., Pollin, T., Sakul, H., Gelder, E.M., Michelsen, B.K., Wagner, M.J., St Jean, P.L., Knowler, W.C., Burns, D.K., Bell, C.J., Shuldiner, A.R., 2000. Diabetes in the Old Order Amish: characterization and heritability analysis of the Amish Family Diabetes Study. Diab. Care 23, 595–601. Jacobsen, L.K., Pugh, K.R., Mencl, W.E., Gelernter, J., 2006. C957T polymorphism of the dopamine D2 receptor gene modulates the effect of nicotine on working memory performance and cortical processing efficiency. Psychopharmacology (Berl). 188 (4), 530–540. Jenkinson, C.P., Hanson, R., Cray, K., Wiedrich, C., Knowler, W.C., Bogardus, C., Baier, L., 2000. Association of dopamine D2 receptor polymorphisms Ser311Cys and TaqIA with obesity or type 2 diabetes mellitus in Pima Indians. Int. J. Obes. Relat. Metab. Disord. 24 (10), 1233–1238. Karlsgodt, K.H., Glahn, D.C., van Erp, T.G., Therman, S., Huttunen, M., Manninen, M., Kaprio, J., Cohen, M.S., Lonnqvist, J., Cannon, T.D., 2007. The relationship between performance and fMRI signal during working memory in patients with schizophrenia, unaffected co-twins, and control subjects. Schizophr. Res. 89, 191–197. Kremen, W.S., Jacobsen, K.C., Xian, H., Eisen, S.A., Eaves, L.J., Tsuang, M.T., Lyons, M.J., 2007. Genetics of verbal working memory processes: a twin study of middle-aged men. Neuropsychology 21, 569–580. Kyle, U.G., Pichard, C., 2006. The Dutch Famine of 1944–1945: a pathophysiological model of long-term consequences of wasting disease. Curr. Opin. Clin. Nutr. Metab. Care 9, 388–394. Lehtinen, A.B., Newton-Cheh, C., Ziegler, J.T., Langefeld, C.D., Freedman, B.I., Daniel, K.R., Herrington, D.M., Bowden, D.W., 2008. Association of NOS1AP genetic variants with QT interval duration in families from the Diabetes Heart Study. Diabetes. Lehtovirta, M., Kaprio, J., Groop, L., Trombetta, M., Bonadonna, R.C., 2005. Heritability of model-derived parameters of beta cell secretion during intravenous and oral glucose tolerance tests: a study of twins. Diabetologia 48, 1604–1613. Lencz, T., Lambert, C., DeRosse, P., Burdick, K.E., Morgan, T.V., Kane, J.M., Kucherlapati, R., Malhotra, A.K., 2007. Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia. Proc. Natl Acad. Sci. USA 104, 19942–19947. Li, Y., Wu, G.D., Zuo, J., Meng, Y., Fang, F.D., 2005. Screening susceptibility genes of type 2 diabetes in Chinese population by single nucleotide polymorphism analysis. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 27, 274–279. Lindenmayer, J.P., Nathan, A.M., Smith, R.C., 2001. Hyperglycemia associated with the use of atypical antipsychotics. J. Clin. Psychiatry 62 (Suppl 23), 30–38. Lindenmayer, J.P., Czobor, P., Volavka, J., Citrome, L., Sheitman, B., McEvoy, J.P., Cooper, T.B., Chakos, M., Lieberman, J.A., 2003. Changes in glucose and cholesterol levels in patients with schizophrenia treated with typical or atypical antipsychotics. Am. J. Psychiatry 160, 290–296. Lovestone, S., Killick, R., Di Forti, M., Murray, R., 2007. Schizophrenia as a GSK-3 dysregulation disorder. Trends Neurosci. 30, 142–149. Ma, L., Hanson, R.L., Que, L.N., Cali, A.M., Fu, M., Mack, J.L., Infante, A.M., Kobes, S., Bogardus, C., Shuldiner, A.R., Baier, L.J., 2007. Variants in ARHGEF11, a

242

P.I. Lin, A.R. Shuldiner / Schizophrenia Research 123 (2010) 234–243

candidate gene for the linkage to type 2 diabetes on chromosome 1q, are nominally associated with insulin resistance and type 2 diabetes in Pima Indians. Diabetes 56, 1454–1459. Matthysse, S., Holzman, P.S., Gusella, J.F., Levy, D.L., Harte, C.B., Jorgensen, A., Moller, L., Parnas, J., 2004. Linkage of eye movement dysfunction to chromosome 6p in schizophrenia: additional evidence. Am. J. Med. Genet. B Neuropsychiatr. Genet. 128, 30–36. McGrath, J., Saari, K., Hakko, H., Jokelainen, J., Jones, P., Jarvelin, M.R., Chant, D., Isohanni, M., 2004. Vitamin D supplementation during the first year of life and risk of schizophrenia: a Finnish birth cohort study. Schizophr. Res. 67, 237–245. Meloni R., Laurent, C., Campion, D., Ben Hadjali, B., Thibaut, F., Dollfus, S., Petit, M., Samolyk, D., Martinez, M., Poirier, M.F., et al., 1995. A rare allele of a microsatellite located in the tyrosine hydroxylase gene found in schizophrenic patients. C. R. Acad. Sci. III 318(7), 803–809. Mills, G.W., Avery, P.J., McCarthy, M.I., Hattersley, A.T., Levy, J.C., Hitman, G.A., Sampson, M., Walker, M., 2004. Heritability estimates for beta cell function and features of the insulin resistance syndrome in UK families with an increased susceptibility to type 2 diabetes. Diabetologia 47, 732–738. Miranda, A., Garcia, J., Lopez, C., Gordon, D., Palacio, C., Restrepo, G., Ortiz, J., Montoya, G., Cardeno, C., Calle, J., Lopez, M., Campo, O., Bedoya, G., RuizLinares, A., Ospina-Duque, J., 2006. Putative association of the carboxyterminal PDZ ligand of neuronal nitric oxide synthase gene (CAPON) with schizophrenia in a Colombian population. Schizophr. Res. 82, 283–285. Murray, R.M., Lappin, J., Di, F.M., 2008. Schizophrenia: from developmental deviance to dopamine dysregulation. Eur. Neuropsychopharmacol. 18 (Suppl 3), S129–S134. Myles-Worsley, M., Park, S., 2002. Spatial working memory deficits in schizophrenia patients and their first degree relatives from Palau, Micronesia. Am. J. Med. Genet. 114, 609–615. Nagatsu, T., 1995. Tyrosine hydroxylase: human isoforms, structure and regulation in physiology and pathology. Essays Biochem. 30, 15–35. Newcomer, J.W., 2007. Metabolic syndrome and mental illness. Am. J. Manag. Care. 13, S170–S177. Newcomer, J.W., Haupt, D.W., Fucetola, R., Melson, A.K., Schweiger, J.A., Cooper, B.P., Selke, G., 2002. Abnormalities in glucose regulation during antipsychotic treatment of schizophrenia. Arch. Gen. Psychiatry 59, 337–345. Nobel, P., 2003. D2 dopamine receptor gene in psychiatric and neurologic disorders and its phenotypes. Am. J. Med. Genet. B Neuropsychiatr. Genet. 116B (1), 103–125. Olsson, G.M., Hulting, A.L., Montgomery, S.M., 2008. Cognitive function in children and subsequent type 2 diabetes. Diab. Care 31, 514–516. Palmer, N.D., Goodarzi, M.O., Langefeld, C.D., Ziegler, J., Norris, J.M., Haffner, S.M., Bryer-Ash, M., Bergman, R.N., Wagenknecht, L.E., Taylor, K.D., Rotter, J.I., Bowden, D.W., 2008. Quantitative trait analysis of T2D susceptibility loci identified from whole genome association studies in the IRAS Family Study. Diabetes 57, 1093–1100. Papanikolaou, Y., Palmer, H., Binns, M.A., Jenkins, D.J., Greenwood, C.E., 2006. Better cognitive performance following a low-glycaemic-index compared with a high-glycaemic-index carbohydrate meal in adults with type 2 diabetes. Diabetologia 49, 855–862. Parasuraman, R., Greenwood, P.M., Kumar, R., Fossella, J., 2005. Beyond heritability: neurotransmitter genes differentially modulate visuospatial attention and working memory. Psychol. Sci. 16, 200–207. Park, S., Holzman, P.S., 1993. Association of working memory deficit and eye tracking dysfunction in schizophrenia. Schizophr. Res. 11, 55–61. Park, S., Holzman, P.S., Goldman-Rakic, P.S., 1995. Spatial working memory deficits in the relatives of schizophrenic patients. Arch. Gen. Psychiatry 52, 821–828. Pascoe, L., Tura, A., Patel, S.K., Ibrahim, I.M., Ferrannini, E., Zeggini, E., Weedon, M.N., Mari, A., Hattersley, A.T., McCarthy, M.I., Frayling, T.M., Walker, M., 2007. Common variants of the novel type 2 diabetes genes CDKAL1 and HHEX/IDE are associated with decreased pancreatic betacell function. Diabetes 56, 3101–3104. Poulsen, P., Levin, K., Petersen, I., Christensen, K., Beck-Nielsen, H., Vaag, A., 2005. Heritability of insulin secretion, peripheral and hepatic insulin action, and intracellular glucose partitioning in young and old Danish twins. Diabetes 54, 275–283. Reaven, G.M., 1988. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 37, 1595–1607. Rouillon, F., Sorbara, F., 2005. Schizophrenia and diabetes: epidemiological data. Eur. Psychiatry 20 (Suppl 4), S345–S348. Rusnák, M,. Jeloková, J., Vietor, I., Sabban, E.L., Kvetnanský, R., 1998. Different effects of insulin and 2-deoxy-D-glucose administration on tyrosine hydroxylase gene expression in the locus coeruleus and the adrenal medulla in rats. Brain. Res. Bull. 46(5), 447–452. Ryan, C.M., Freed, M.I., Rood, J.A., Cobitz, A.R., Waterhouse, B.R., Strachan, M.W., 2006. Improving metabolic control leads to better working memory in adults with type 2 diabetes. Diab. Care 29, 345–351.

Rybakowski, J.K., Borkowska, A., Czerski, P.M., Hauser, J., 2001. Dopamine D3 receptor (DRD3) gene polymorphism is associated with the intensity of eye movement disturbances in schizophrenic patients and healthy subjects. Mol. Psychiatry 6, 718–724. Rybakowski, J.K., Borkowska, A., Czerski, P.M., Hauser, J., 2002. Eye movement disturbances in schizophrenia and a polymorphism of catechol-O-methyltransferase gene. Psychiatry Res. 113, 49–57. Saddichha, S., Manjunatha, N., Ameen, S., Akhtar, S., 2008. Diabetes and schizophrenia — effect of disease or drug? Results from a randomized, double-blind, controlled prospective study in first-episode schizophrenia. Acta Psychiatr. Scand. 117, 342–347. Savoy, Y.E., Ashton, M.A., Miller, M.W., Nedza, F.M., Spracklin, D.K., Hawthorn, M.H., Rollema, H., Matos, F.F., Hajos-Korcsok, E., 2008. Differential effects of various typical and atypical antipsychotics on plasma glucose and insulin levels in the mouse: evidence for the involvement of sympathetic regulation. Schizophr. Bull. Saykin, A.J., Shtasel, D.L., Gur, R.E., Kester, D.B., Mozley, L.H., Stafiniak, P., Gur, R.C., 1994. Neuropsychological deficits in neuroleptic naive patients with first-episode schizophrenia. Arch. Gen. Psychiatry 51, 124–131. Schaub, M.A., Kaplow, I.M., Sirota, M., Do, C.B., Butte, A.J., Batzoglou, S., 2009. A classifier-based approach to identify genetic similarities between diseases. Bioinformatics 25, i21–i29. Scott, L.J., Mohlke, K.L., Bonnycastle, L.L., Willer, C.J., Li, Y., Duren, W.L., Erdos, M.R., Stringham, H.M., Chines, P.S., Jackson, A.U., Prokunina-Olsson, L., Ding, C.J., Swift, A.J., Narisu, N., Hu, T., Pruim, R., Xiao, R., Li, X.Y., Conneely, K.N., Riebow, N.L., Sprau, A.G., Tong, M., White, P.P., Hetrick, K.N., Barnhart, M.W., Bark, C.W., Goldstein, J.L., Watkins, L., Xiang, F., Saramies, J., Buchanan, T.A., Watanabe, R.M., Valle, T.T., Kinnunen, L., Abecasis, G.R., Pugh, E.W., Doheny, K.F., Bergman, R.N., Tuomilehto, J., Collins, F.S., Boehnke, M., 2007. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316, 1341–1345. Scuteri, A., Sanna, S., Chen, W.M., Uda, M., Albai, G., Strait, J., Najjar, S., Nagaraja, R., Orru, M., Usala, G., Dei, M., Lai, S., Maschio, A., Busonero, F., Mulas, A., Ehret, G.B., Fink, A.A., Weder, A.B., Cooper, R.S., Galan, P., Chakravarti, A., Schlessinger, D., Cao, A., Lakatta, E., Abecasis, G.R., 2007. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet. 3, e115. Sernyak, M.J., Gulanski, B., Leslie, D.L., Rosenheck, R., 2003. Undiagnosed hyperglycemia in clozapine-treated patients with schizophrenia. J. Clin. Psychiatry 64, 605–608. Sommerfield, A.J., Deary, I.J., Frier, B.M., 2004. Acute hyperglycemia alters mood state and impairs cognitive performance in people with type 2 diabetes. Diab. Care 27, 2335–2340. Spelman, L.M., Walsh, P.I., Sharifi, N., Collins, P., Thakore, J.H., 2007. Impaired glucose tolerance in first-episode drug-naive patients with schizophrenia. Diabet. Med. 24, 481–485. Sten-Linder, M., Wedell, A., Iselius, L., Efendic, S., Luft, R., Luthman, H., 1993. DNA polymorphisms in the human tyrosine hydroxylase/insulin/insulinlike growth factor II chromosomal region in relation to glucose and insulin responses. Diabetologia 36, 25–32. Thermenos, H.W., Seidman, L.J., Breiter, H., Goldstein, J.M., Goodman, J.M., Poldrack, R., Faraone, S.V., Tsuang, M.T., 2004. Functional magnetic resonance imaging during auditory verbal working memory in nonpsychotic relatives of persons with schizophrenia: a pilot study. Biol. Psychiatry 55, 490–500. Thibaut, F., Ribeyre, J.M., Dourmap, N., Meloni, R., Laurent, C., Campion, D., Ménard, J.F., Dollfus, S., Mallet, J., Petit, M., 1997. Association of DNA polymorphism in the first intron of the tyrosine hydroxylase gene with disturbances of the catecholaminergic system in schizophrenia. Schizophr. Res. 23(3), 259–264. Thonnard-Neumann, E., 1968. Phenothiazines and diabetes in hospitalized women. Am. J. Psychiatry 124, 978–982. Torkamani, A., Topol, E.J., Schork, N.J., 2008. Pathway analysis of seven common diseases assessed by genome-wide association. Genomics 92, 265–272. Tschoner, A., Engl, J., Rettenbacher, M., Edlinger, M., Kaser, S., Tatarczyk, T., Effenberger, M., Patsch, J.R., Fleischhacker, W.W., Ebenbichler, C.F., 2009. Effects of six second generation antipsychotics on body weight and metabolism — risk assessment and results from a prospective study. Pharmacopsychiatry 42, 29–34. Verma, S.K., Subramaniam, M., Liew, A., Poon, L.Y., 2009. Metabolic risk factors in drug-naive patients with first-episode psychosis. J. Clin. Psychiatry 70, 997–1000. Vietor, I., Rusnak, M., Viskupic, E., Blazicek, P., Sabban, E.L., Kvetnansky, R., 1996. Glucoprivation by insulin leads to trans-synaptic increase in rat adrenal tyrosine hydroxylase mRNA levels. Eur. J. Pharmacol. 313(1-2), 119-127. Waterworth, D.M., Bassett, A.S., Brzustowicz, L.M., 2002. Recent advances in the genetics of schizophrenia. Cell. Mol. Life Sci. 59, 331–348.

P.I. Lin, A.R. Shuldiner / Schizophrenia Research 123 (2010) 234–243 Wei, J., Ramchand, C.N., Hemmings, G.P., 1995. Association of polymorphic VNTR region in the first intron of the human TH gene with disturbances of the catecholamine pathway in schizophrenia. Psychiatr. Genet. 5(2), 83-88. Wenk, G.L., 1989. An hypothesis on the role of glucose in the mechanism of action of cognitive enhancers. Psychopharmacology (Berl). 99, 431–438. WHO, 1993. The ICD10 Classification of Mental and Behavioural Disorders. Diagnostic criteria for research World Health Organization, Geneva. Wolford, J.K., Hanson, R.L., Kobes, S., Bogardus, C., Prochazka, M., 2001. Analysis of linkage disequilibrium between polymorphisms in the KCNJ9 gene with type 2 diabetes mellitus in Pima Indians. Mol. Genet. Metab. 73, 97–103. Wu, W., Shang, J., Feng, Y., Thompson, C.M., Horwitz, S., Thompson, J.R., MacIntyre, E.D., Thornberry, N.A., Chapman, K., Zhou, Y.P., Howard, A.D., Li, J., 2008. Identification of glucose-dependant insulin secretion targets in pancreatic beta cells by combining defined-mechanism compound library screening and siRNA gene silencing. J. Biomol. Screen. 13 (2), 128–134. Xu, B., Wratten, N., Charych, E.I., Buyske, S., Firestein, B.L., Brzustowicz, L.M., 2005. Increased expression in dorsolateral prefrontal cortex of CAPON in schizophrenia and bipolar disorder. PLoS Med. 2, e263.

243

Xu, H., Kellendonk, C.B., Simpson, E.H., Keilp, J.G., Bruder, G.E., Polan, H.J., Kandel, E.R., Gilliam, T.C., 2007. DRD2 C957T polymorphism interacts with the COMT Val158Met polymorphism in human working memory ability. Schizophr. Res. 90 (1–3), 104–107. Yang, L.H., Chen, T.M., Yu, S.T., Chen, Y.H., 2007. Olanzapine induces SREBP1-related adipogenesis in 3 T3-L1 cells. Pharmacol. Res. 56, 202–208. Zeggini, E., Damcott, C.M., Hanson, R.L., Karim, M.A., Rayner, N.W., Groves, C.J., Baier, L.J., Hale, T.C., Hattersley, A.T., Hitman, G.A., Hunt, S.E., Knowler, W.C., Mitchell, B.D., Ng, M.C., O'Connell, J.R., Pollin, T.I., Vaxillaire, M., Walker, M., Wang, X., Whittaker, P., Xiang, K., Jia, W., Chan, J.C., Froguel, P., Deloukas, P., Shuldiner, A.R., Elbein, S.C., McCarthy, M.I., 2006. Variation within the gene encoding the upstream stimulatory factor 1 does not influence susceptibility to type 2 diabetes in samples from populations with replicated evidence of linkage to chromosome 1q. Diabetes 55, 2541–2548. Zeitz, U., Weber, K., Soegiarto, D.W., Wolf, E., Balling, R., Erben, R.G., 2003. Impaired insulin secretory capacity in mice lacking a functional vitamin D receptor. FASEB J. 17, 509–511. Zheng, Y., Li, H., Qin, W., Chen, W., Duan, Y., Xiao, Y., Li, C., Zhang, J., Li, X., Feng, G., He, L., 2005. Association of the carboxyl-terminal PDZ ligand of neuronal nitric oxide synthase gene with schizophrenia in the Chinese Han population. Biochem. Biophys. Res. Commun. 328, 809–815.