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Association of metabolic syndrome and inflammation with neurocognition in patients with schizophrenia
Psychiatry Research 210 (2013) 381–386
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Association of metabolic syndrome and inflammation with neurocognition in patients with schizophrenia Laurent Boyer a,n, Raphaëlle Richieri b, Daniel Dassa c, Mohamed Boucekine a, Jessica Fernandez a, Florence Vaillant b, Romain Padovani b, Pascal Auquier a, Christophe Lancon a,b,d a
Aix-Marseille University, EA 3279 – Public Health, Chronic Diseases and Quality of Life – Research Unit, 13005 Marseille, France Department of Psychiatry, Sainte-Marguerite University Hospital, 13009 Marseille, France c Department of Psychiatry, La Conception University Hospital, 13009 Marseille, France d Department of Addiction, Sainte-Marguerite University Hospital, 13009 Marseille, France b
art ic l e i nf o
a b s t r a c t
Article history: Received 10 September 2012 Received in revised form 13 May 2013 Accepted 14 June 2013
The aim of this study is to assess the relationships of metabolic syndrome (MetS) and inflammation with neurocognition in schizophrenia. In this cross-sectional study, we included patients with diagnosis of schizophrenia according to the DSM-IV-TR criteria. We collected socio-demographic information, clinical characteristics, anthropometric measurements, blood tests, and neurocognition measures. A multivariate analysis using multiple linear regressions was performed to determine variables that are potentially associated with neurocognition. The analyses were repeated using MetS as a dichotomised variable ( o and ≥3 MetS criteria), a continuous variable (number of MetS criteria present), and for each component of MetS. One hundred and sixty-eight outpatients participated in our study. The prevalence of MetS was 27.4%. An association was found between the number of MetS criteria present and cognitive impairment. Among the different components of MetS, hypertriglycerides and abdominal obesity were the only factors associated with cognitive impairment. Other factors, such as smoking and alcohol dependence or abuse, also revealed a significant relationship, whereas inflammation was not associated with cognitive impairment. In conclusion, our findings suggest that MetS, alcohol use and non-smoking status are associated with cognitive impairment. These findings may support complementary therapeutic approaches in cognitive remediation that lessen the severity of cognitive impairment in schizophrenia. & 2013 Elsevier Ireland Ltd. All rights reserved.
Keywords: Schizophrenia Metabolic Syndrome Inflammation Neurocognition
1. Introduction Metabolic syndrome (MetS) is defined as a clustering of interrelated abnormalities, including at least three of the following criteria: abdominal adiposity, dyslipidaemia (high triglycerides or low HDL cholesterol levels), hypertension and hyperglycaemia (National Cholesterol Education Program's ATP-III—NCEP ATP III) (Grundy et al., 2005). The prevalence of MetS is higher in individuals with schizophrenia than in the general population, with an overall rate ranging from 30% to 35% (Mitchell et al., 2011). The links between MetS and an increased risk of morbidity (i.e., cardiovascular diseases, diabetes) and mortality are now well established (Lakka et al., 2002; Goff et al., 2005). Recent evidence suggests that MetS also affects cognitive functions in older patients, especially among those with high levels of inflammation (Yaffe et al., 2004; Dik et al., 2007; Liu et al., 2009; van den Berg
n
Corresponding author. Tel.: +33 686936276; fax+33 491433516. E-mail address: [email protected] (L. Boyer).
0165-1781/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2013.06.020
et al., 2009). The MetS might contribute to accelerate the atherosclerosis process that is associated with an inflammatory response and both phenomena could then contribute to cognitive decline (Yaffe et al., 2004). This area of investigation is important to the study of schizophrenia for two main reasons: (1) cognitive impairment is considered to be a primary reason for functional disability even after successful treatment and reduction of psychotic symptoms (Nasrallah, 2010), and (2) inflammation has been suggested to play an important role in the psychopathology of schizophrenia (Leonard et al., 2012; Meyer et al., 2012; Nawa and Yamada, 2012; Sommer et al., 2012). Unfortunately, data are scarce on the links between metabolic syndrome, inflammation and neurocognition in schizophrenia. Three studies have documented the impact of metabolic syndrome on neurocognition in schizophrenia and have contradictory results (Meyer et al., 2005; Friedman et al., 2010; Lindenmayer et al., 2012). The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study did not find any relationship between MetS and cognitive impairment (Meyer et al., 2005). According to Friedman et al. (2010), one explanation for this negative finding could be partially due to the use of a
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dichotomised definition for MetS (oand ≥3 criteria). Although this cut-off is considered as a means of assisting the front-line practitioner in identifying risk factors that require clinical attention (Citrome et al., 2006), some authors have pointed out that it is seemingly arbitrary (Kahn et al., 2005). Cognitive function may be impaired progressively together with increasing numbers of MetS criteria, and the use of a continuous variable appears more appropriate (Wijndaele et al., 2006). In contrast, the study of Friedman et al. (2010) found that hypertension and body mass index (BMI) 425 exerted a significant, negative effect on neurocognition (i.e. memory). Not all of the components of MetS, however, were included in these analyses. More recently, Lindenmayer et al. (2012) have reported a link between MetS and processing speed, attention/vigilance, working memory and problem solving/reasoning. Concerning inflammation, one study proved that the C-reactive protein was associated with the cognitive impairment severity in patients with schizophrenia (Dickerson et al., 2007). Moreover, experimental studies in animals and investigations in non-schizophrenic individuals have suggested that inflammation may affect cognitive functions (i.e. executive functions, attention and working memory) which have been implicated in schizophrenia (Meyer et al., 2012). To our knowledge, no study has considered the influence of both metabolic syndrome and inflammation on neurocognition in schizophrenia. Therefore, in the present study, our aim was to investigate the relationships of MetS and inflammation with neurocognition in patients with schizophrenia. For this purpose, the MetS was analysed in three different ways using a dichotomised ( o and ≥3 criteria NCEP ATP III) or continuous (number of criteria) variable and each component of MetS in isolation.
and was not involved in the treatment of the individuals, administered the tests in a standardised manner. The same instructions were given to the individuals prior to each trial. 5. Metabolic syndrome: diagnosis of MetS was defined according to the National Cholesterol Education Program's ATP-III criteria (Grundy et al., 2005), including three or more of the following criteria: waist circumference 488 cm in women and 4102 cm in men, fasting serum triglycerides ≥150 mg/dL; serum HDL o 50 mg/dL in women and o 40 mg/dL in men, blood pressure ≥130/85 mmHg and fasting blood glucose levels ≥110 mg/dL. Waist circumference was measured at the midpoint between the lower rib margins and the iliac crest. Arterial blood pressure was recorded using a standard mercury sphygmomanometer. Glucose and lipoprotein concentrations were analysed in fasting venous blood samples using standard enzymatic techniques. All the measures were performed at the same time. 6. Inflammatory marker: serum levels of C-reactive protein (CRP) were determined using sensitive regular immunoassays (ELISA). The results are expressed as micrograms per millilitre. The detection limit was 0.08 mg/mL.
2.3. Statistical analyses Data were expressed as proportions, means or standard deviations. First, chi-squared or t-tests were conducted to compare the characteristics of the study sample in terms of MetS status (absence or presence). We then performed unadjusted and multivariate-adjusted (age, sex, education level, smoking and alcohol usage) linear regression analyses to determine whether MetS and inflammation were associated with cognitive impairment. We added an interaction term to these models to assess whether inflammation modified the association between metabolic syndrome and cognitive outcomes. The analyses were repeated using MetS as a dichotomised variable (o and ≥3 criteria NCEP ATP III), a continuous variable (number of the MetS criteria present), and for each component of MetS (waist circumference, triglycerides, HDL cholesterol levels, blood pressure, and glycaemia). All the tests were two-sided. Statistical significance was defined as p o0.05. The statistical analyses were performed using the SPSS version 18.0 software package (SPSS Inc., Chicago, IL, USA).
2. Methods
3. Results
2.1. Study participants
The mean age of the patients was 36.62 years ( 712.09), and 73.8% of them (n ¼124) were male. The patients showed moderate severity of symptoms, with a total PANSS score corresponding to 69.5 (720.0) and sub-scores of 14.3 75.4, 19.8 77.3, and 35.8 710.2, respectively, for positive, negative, and general psychopathology factors. Of the total number of patients, 86.7% had been taking second-generation antipsychotics. The prevalence rates for individual components of MetS were 46.4% for abdominal obesity, 22.6% for high triglycerides, 35.7% for low HDL cholesterol, 39.9% for hypertension, and 16.7% for hyperglycaemia. According to our results, 27.4% of patients met one, 17.9% met two, 14.9% met three, 8.9% met four, and 3.6% met five of the MetS criteria. Table 1 presents the characteristics of the study sample using MetS status. Compared to patients without MetS (n ¼122), those with MetS (n ¼46) did not differ statistically regarding sociodemographic, clinical, antipsychotic treatment and inflammatory characteristics, except for age (35.5 and 39.6 years, respectively; p¼ 0.047). Patients with MetS had significantly lower cognitive performance in the D2 attention task (p ¼0.005), and TMT A (p ¼0.016) and B (p¼ 0.029). Multivariate analyses results are reported in Tables 2–4. Our models were all adjusted on age, sex, education level, smoking and alcohol usage. In the models using MetS as a dichotomised variable, MetS and inflammation were not significantly associated with cognitive performance (all p-values 40.05). Significant associations were found between lower cognitive performance and older age, male gender, lower education levels, non-smoking status and alcohol dependence or abuse. In the models using MetS as a continuous variable, the number of MetS criteria was associated with lower cognitive performance for CVLT (β¼−0.231; p¼0.043), D2 attention (β¼ −0.255 p¼0.016) and TMT A (β¼0.198; p¼0.032) and B (β¼ 0.226; p¼0.033). Significant associations were also found with
The study evaluated all prospective patients attending daytime hospital hours in our university and psychiatric hospital over a period of 12 months, from January 2011 to December 2011. One hundred and sixty-eight outpatients with schizophrenia participated in our study, and the MetS prevalence rate was 27.4% (n¼ 46). All patients provided written informed consent. The inclusion criteria were the following: being over 18 years of age, having a diagnosis of schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV-TR) criteria (APA, 2000), and speaking French as one's native language. The exclusion criteria included the following: diagnosis other than schizophrenia on Axis I of the DSM-IV, decompensated organic disease and mental retardation. The data collection was approved by the Commission nationale de l'informatique et des libertés (CNIL number: 1223715). 2.2. Data collection The following data were collected: 1. Socio-demographic information: age, gender, and educational level. 2. Clinical characteristics: duration of disease; psychotic symptoms based on the Positive and Negative Syndrome Scale (PANSS), which comprises three different subscales such as positive, negative and general psychopathology (Kay et al., 1986); depression based on the Calgary Depression Scale for Schizophrenia (CDSS) (Addington et al., 1993); smoking status assessed by the Fagerstrom Test for Nicotine Dependence (FTND) (Heatherton et al., 1991); and alcohol dependence or abuse determined by the DSM-IV-TR (during the past year) (APA, 2000). 3. Drug information: antipsychotic medications (first-generation antipsychotics – FGAs, second-generation antipsychotics – SGAs). 4. Neurocognitive assessment: based on previous research, several measures were selected to test memory, attention, and executive functions (Szoke et al., 2008; Szoke et al., 2009). Memory was tested using the California Verbal Learning Test (CVLT), attention was tested using the D2 attention task, and executive functions were tested using the Stroop color-word test for inhibition capacity, the verbal fluency test (category domains) for spontaneous flexibility, the Trail Making Test A and B (TMT) for reactive flexibility, and the Wechsler Adult Intelligence Scale – Third Edition (WAIS-III symbol coding) for updating. The same senior psychologist, who was trained intensively in test administration
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Table 1 Sample characteristics and metabolic syndrome status (N ¼168). No metabolic syndrome N¼ 122
Metabolic syndrome N¼ 46
p-Value
Socio-demographic characteristics Age in years: Mean ( 7 SD) Sex ratio (men) (%) Education level (%): ≥12 y
35.48 712.10 74.6% 61.9%
39.63 7 11.67 71.7% 46.2%
0.047 0.708 0.089
Clinical characteristics Disease duration in years: Mean ( 7S.D.) PANSSn total score: Mean ( 7 S.D.) Positive factor Negative factor General psychopathology factor Calgary score: Mean ( 7S.D.)
11.28 79.49 68.107 20.80 13.99 7 5.54 18.85 7 7.55 35.26 7 10.49 3.94 74.34
14.3579.03 72.98 717.53 15.147 5.17 20.56 7 6.49 37.28 79.35 4.20 7 3.92
0.081 0.175 0.241 0.192 0.271 0.747
Metabolic syndrome criteria Hyperglycaemia (%) Low HDL cholesterol (%) High triglycerides (%) Hypertension (%) Abdominal obesity (%)
5.7% 18.0% 8.2% 24.6% 30.3%
45.7% 82.6% 60.9% 80.4% 89.1%
– – – – –
CRP (lg/mL): Mean ( 7 S.D.)
4.26 77.24
6.497 6.57
0.161
Fagerstrom Test: Mean ( 7 S.D.)
3.377 3.26
3.87 7 3.31
0.464
Alcohol consumption (%)
24.3%
35.7%
0.160
Cognitive assessment: Mean ( 7 S.D.) CVLT List A – 1–5 D2 attention task TMT-A (time) TMT-B (time) Stroop interference Category fluency WAIS III – Digit Symbol-Coding
44.74 713.02 133.457 43.90 42.02 724.97 100.83 7 52.16 38.157 14.19 25.09 78.69 6.39 73.25
39.80 7 11.80 106.197 50.25 53.23 7 22.93 139.277 92.48 35.877 11.95 22.767 7.61 5.337 3.06
0.052 0.005 0.016 0.029 0.432 0.152 0.083
Second Generation Antipsychotics (%)
85.4%
90.0%
0.756
Table 2 Factors associated with neurocognitive test scores: multivariate analyses.
Age Sex (women/men) Education level ( o 12/≥12 y) MetS (yes/no) CRP Fagerstrom Test Alcohol consumption (yes/ no)
CVLT List A – 1–5 βa D2 attention task
TMT-A (time)
TMT-B (time)
Stroop interference
Category fluency
WAIS III – Digit SymbolCoding
−0.374nn 0.267n −0.322nn −0.205 0.112 0.064 −0.039
0.527nn −0.006 0.288nn 0.173 0.089 −0.171n 0.077
0.386nn 0.102 0.254n 0.175 0.020 −0.145 0.162
−0.510nn −0.034 −0.362nn 0.028 0.107 0.220n −0.203
−0.019 −0.187 −0.275n −0.087 0.005 0.012 0.064
−0.002 0.124 −0.413nn −0.159 −0.156 0.000 −0.159
−0.248n −0.207 −0.309nn −0.179 −0.121 −0.067 −0.229n
MetS is included as a dichotomised variable in the analysis ( o and ≥3 criteria NCEP ATP III). PANSS: Positive and Negative Syndrome Scale. a β: standardised beta coefficient (β represents the change of the standard deviation in neurocognition scores resulting from a change of one standard deviation in the independent variable). n p≤0.05. nn p≤0.01.
older age, male gender, lower education levels, non-smoking status and alcohol dependence or abuse. As found in the previous models, inflammation was not associated with cognitive performance. An investigation of the individual components of MetS, in relation to cognition, revealed that high triglycerides and abdominal obesity were the only factors that were associated with poor cognitive performance. Lastly, the interaction terms MetS inflammation were not statistically significant in the different models.
4. Discussion For the first time, this study investigated the relationships of the metabolic syndrome, using different definitions, and
inflammation with neurocognition among patients suffering from schizophrenia. Our findings provide evidence for a correlation between MetS and more severe cognitive impairment in schizophrenia. Other factors, such as smoking and alcohol dependence or abuse, also showed a significant relationship, whereas inflammation was not associated with cognitive impairment. These findings may have important clinical implications. First, we have found a relationship between the number of MetS criteria present and cognitive impairment (i.e. memory, attention and reactive flexibility); however, we did not find any significant relationship between dichotomised MetS (absence or presence) and cognitive impairment. This finding may support the differences found in the two previous studies on patients with schizophrenia (described at the end of the introduction)
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Table 3 Factors associated with neurocognitive test scores: multivariate analyses.
Age Sex (women/men) Educational level ( o 12/≥12 y) Number of criteria of the MetS CRP Fagerstrom Test Alcohol consumption (yes/no)
CVLT List A – 1–5 βa
D2 attention task
TMT-A (time)
TMT-B (time)
Stroop i nterference
Category fluency
WAIS III – Digit Symbol-Coding
−0.358nn 0.266n −0.299nn −0.231n 0.119 0.073 −0.037
−0.225n −0.209n −0.265n −0.255n −0.112 −0.058 −0.224n
0.512nn 0.004 0.266nn 0.198n 0.084 −0.173n 0.075
0.381nn 0.102 0.225n 0.226n 0.009 −0.149 0.157
−0.509nn −0.031 −0.362nn 0.015 0.109 0.221n −0.201
−0.015 −0.193 −0.269n −0.079 0.003 0.012 0.063
0.009 0.118 −0.396nn −0.165 −0.156 0.002 −0.156
MetS is included as a continuous variable in the analysis (number of MetS criteria). a β: standardised beta coefficient (β represents the change of the standard deviation in neurocognition score resulting from a change of one standard deviation in the independent variable). n p≤0.05. nn p≤0.01.
Table 4 Individual components of MetS associated with neurocognitive test scores: multivariate analysesa. CVLT List A – 1–5 βb D2 attention task TMT-A (time) TMT-B (time) Stroop interference Category fluency WAIS III – Digit Symbol-Coding Abdominal obesity Low HDL cholesterol High triglycerides Hypertension Hyperglycaemia
−0.224 −0.153 −0.303nn −0.043 0.014
−0.123 −0.160 −0.256n 0.012 −0.211
0.206n 0.138 0.248nn −0.027 0.097
0.166 0.039 0.226n 0.150 0.120
−0.005 0.135 0.001 −0.019 −0.079
−0.093 −0.007 −0.204 0.069 −0.043
−0.131 −0.089 −0.122 0.018 −0.153
a
Adjusted for age, sex, education, smoking and alcohol use. β: standardised beta coefficient (β represents the change of the standard deviation in neurocognition scores resulting from a change of one standard deviation in the independent variable). n p≤0.05. nn p≤0.01. b
(Meyer et al., 2005; Friedman et al., 2010). This finding suggests that cognitive performance is a function of the number of MetS criteria present, and it appears unjustified to assume that optimal predictive power should be obtained using arbitrary dichotomies (Kahn et al., 2005). In our study, the use of a binary definition of MetS (≥3 criteria) has resulted in the non-inclusion of 45.3% of patients with one or two cardiovascular risk factors in the group designated as having MetS. This binary definition may have diluted the effects of MetS on cognitive performance. MetS should be considered a progressive risk factor for cognitive impairment and cannot simply be regarded as present or absent. Pre-metabolic syndrome ( o3 criteria) could also be considered a potential risk factor for compromising cognitive performance. Our findings confirm the link between cognitive impairments associated with MetS in schizophrenia (Nasrallah, 2010; Lindenmayer et al., 2012), and suggest that interventions to reduce cardiovascular risk factors, especially hyperlipidaemia and obesity, may have positive effects on cognitive deficits. Indeed, we found that among the different components of MetS, hypertriglycerides and abdominal obesity were the most important features associated with cognitive impairment. These two factors are well-established risk factors for atherosclerosis (Cheng et al., 2002), suggesting that atherosclerosis may be linked to cognitive impairment in schizophrenia. Metabolic changes may have caused micro- and macrocerebrovascular alterations which may underlie impaired neural transmission and lead to cognitive impairments such as memory, attention and executive functions (Lindenmayer et al., 2012). Several authors have also proposed non-vascular mechanisms involving actions of adiposity on neuronal tissue through neurochemical mediators, such as leptin (Li et al., 2002; Bray, 2004; Oomura et al., 2006; Holden et al., 2009). Surprisingly, other factors such as hyperglycaemia and hypertension were not statistically associated with cognitive impairment in our study. These
results contradict some previous studies (Reitz et al., 2007; Liu et al., 2009), specifically the study performed by Friedman et al. (2010) who found that hypertension increased the risk for cognitive impairment. One explanation could be the differences between populations, especially the relatively young average age in our study (36.6 years) compared with previous studies (47.3 years in Friedman's study). Future studies are necessary to explore the influence of the length of exposure to each component of MetS on cognitive impairment. In accordance with several previous studies, non-smoking (Amitai and Markou, 2009; D'Souza and Markou, 2012) and alcohol dependence or abuse (Bowie et al., 2005; Manning et al., 2009) were associated with cognitive impairment. These two factors may worsen the already decreased cholinergic transmission involved in cognitive impairment in schizophrenia (Olincy et al., 2006; D'Souza and Markou, 2012). The neurotoxic action of alcohol, which is exerted via accelerated cerebral atrophy and reduced acetylcholine synthesis, has been described previously (Whitmer et al., 2005). In practice, patients with coexisting mental and substance use disorders, such as alcohol abuse, have rarely received necessary treatments and have generally experienced poor outcomes (Essock et al., 1998; Drake et al., 2001). Hence, doctors should consider the possible existence of alcohol dependence or abuse when planning cognitive rehabilitation programs with these patients, and they should develop better coordination between addiction and mental health services in the treatment of these patients. Concerning smoking, a recent study has shown that tobacco use is associated with a better inhibitory function in schizophrenia, as found in our own study (Jurado-Barba et al., 2011). Nicotine is a cholinergic agonist that can counteract the cholinergic dysfunction in cognitive impairment (Picciotto and Zoli, 2002). Interestingly, pre-clinical studies have suggested that administration of nicotine or nicotine acetylcholine receptors
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(nAChR) agonists results in beneficial cognitive effects (D'Souza and Markou, 2012). Treatment strategies for tobacco dependence using nicotine administration and nAChR agonists may be considered in smoking cessation treatments for schizophrenic patients and for the remediation of cognitive deficits associated with schizophrenia itself (Wing et al., 2012). Unlike previous studies on elderly patients (Yaffe et al., 2004; Dik et al., 2007), inflammation was not associated with cognitive impairment and did not modify the association between metabolic syndrome and cognitive impairment. We expected the opposite findings because inflammation has been suggested to be involved in the pathogenesis of schizophrenia (Muller and Schwarz, 2010), and one study has shown that increased inflammatory response was associated with cognitive decline in schizophrenia patients (Dickerson et al., 2007). A study performed by Dickerson et al., however, did not consider several important confounding factors such as education level and MetS. However, our findings should be reviewed with caution. Our sample was smaller than that of the study performed by Dickerson et al., and we cannot exclude the possibility that the absence of association is due to lack of power. Future studies should confirm our results using larger samples.
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strategies for tobacco dependence could be considered as important targets in the remediation of cognitive impairments.
Role of funding source None.
Contributors Conception and design: LB, CL. Study's coordination: RR, FV, RP. Inclusion and clinical data collection: RR, RP. Acquisition of cognitive data: FV. Analysis of data: MB, JF. Interpretation of data: LB, RR, DD, PA, CL. Drafting and writing the manuscript: LB, RR, PA.
Acknowledgements None. References
4.1. Limitations and perspectives First, the sample size was relatively small, especially for the MetS group (n ¼46). When attempting to identify linked factors using the multivariate approach, moderate associations may have been missed due to low statistical power. Second, the sample may not be representative of the entire population of patients with schizophrenia. Patients were mostly middle-aged males with more than 5 years of illness duration. Thus, we need confirmation for more diverse and larger groups of patients. Third, this study is limited by being cross-sectional in design rather than prospective in design. No causal inference can be made formally between MetS and cognition, and our models should be interpreted from an associational point of view. Future longitudinal studies are needed to confirm that the sequence MetS-cognition is temporally verified. Fourth, several important data were not available, such as alcohol use and smoking details (i.e., amount and duration of consumption). Another potential weakness is related to the different medications used by patients and the duration of treatment. It appears that antipsychotics may have an impact on inflammation, metabolic syndrome and neurocognition (Adachi et al., 2012). Further studies should integrate these parameters to examine their role precisely. Fifth, an important methodological problem remains in the definition of MetS. Currently, several different definitions of MetS exist (Kassi et al., 2011). Although we have chosen one of the most widely used definitions in the scientific literature, ATP-III criteria seems more suitable for American than European populations and the International Diabetes Federation criteria might have been more suitable in our study. Finally, future studies will need to address whether preventing or lowering MetS and alcohol use and treating tobacco dependence will improve cognitive impairment.
5. Conclusion In conclusion, our findings suggest that MetS, alcohol use, and smoking may be linked to neurocognition in patients with schizophrenia. After replications with longitudinal approaches, these findings may support complementary therapeutic approaches, such as cognitive remediation combined with interventions to reduce cardiovascular risk factors. The prevention or reduction of metabolic syndrome and alcohol use may lessen the severity of cognitive impairment in patients with schizophrenia. Treatment
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Psychiatry Research journal homepage: www.elsevier.com/locate/psychres
Association of metabolic syndrome and inflammation with neurocognition in patients with schizophrenia Laurent Boyer a,n, Raphaëlle Richieri b, Daniel Dassa c, Mohamed Boucekine a, Jessica Fernandez a, Florence Vaillant b, Romain Padovani b, Pascal Auquier a, Christophe Lancon a,b,d a
Aix-Marseille University, EA 3279 – Public Health, Chronic Diseases and Quality of Life – Research Unit, 13005 Marseille, France Department of Psychiatry, Sainte-Marguerite University Hospital, 13009 Marseille, France c Department of Psychiatry, La Conception University Hospital, 13009 Marseille, France d Department of Addiction, Sainte-Marguerite University Hospital, 13009 Marseille, France b
art ic l e i nf o
a b s t r a c t
Article history: Received 10 September 2012 Received in revised form 13 May 2013 Accepted 14 June 2013
The aim of this study is to assess the relationships of metabolic syndrome (MetS) and inflammation with neurocognition in schizophrenia. In this cross-sectional study, we included patients with diagnosis of schizophrenia according to the DSM-IV-TR criteria. We collected socio-demographic information, clinical characteristics, anthropometric measurements, blood tests, and neurocognition measures. A multivariate analysis using multiple linear regressions was performed to determine variables that are potentially associated with neurocognition. The analyses were repeated using MetS as a dichotomised variable ( o and ≥3 MetS criteria), a continuous variable (number of MetS criteria present), and for each component of MetS. One hundred and sixty-eight outpatients participated in our study. The prevalence of MetS was 27.4%. An association was found between the number of MetS criteria present and cognitive impairment. Among the different components of MetS, hypertriglycerides and abdominal obesity were the only factors associated with cognitive impairment. Other factors, such as smoking and alcohol dependence or abuse, also revealed a significant relationship, whereas inflammation was not associated with cognitive impairment. In conclusion, our findings suggest that MetS, alcohol use and non-smoking status are associated with cognitive impairment. These findings may support complementary therapeutic approaches in cognitive remediation that lessen the severity of cognitive impairment in schizophrenia. & 2013 Elsevier Ireland Ltd. All rights reserved.
Keywords: Schizophrenia Metabolic Syndrome Inflammation Neurocognition
1. Introduction Metabolic syndrome (MetS) is defined as a clustering of interrelated abnormalities, including at least three of the following criteria: abdominal adiposity, dyslipidaemia (high triglycerides or low HDL cholesterol levels), hypertension and hyperglycaemia (National Cholesterol Education Program's ATP-III—NCEP ATP III) (Grundy et al., 2005). The prevalence of MetS is higher in individuals with schizophrenia than in the general population, with an overall rate ranging from 30% to 35% (Mitchell et al., 2011). The links between MetS and an increased risk of morbidity (i.e., cardiovascular diseases, diabetes) and mortality are now well established (Lakka et al., 2002; Goff et al., 2005). Recent evidence suggests that MetS also affects cognitive functions in older patients, especially among those with high levels of inflammation (Yaffe et al., 2004; Dik et al., 2007; Liu et al., 2009; van den Berg
n
Corresponding author. Tel.: +33 686936276; fax+33 491433516. E-mail address: [email protected] (L. Boyer).
0165-1781/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2013.06.020
et al., 2009). The MetS might contribute to accelerate the atherosclerosis process that is associated with an inflammatory response and both phenomena could then contribute to cognitive decline (Yaffe et al., 2004). This area of investigation is important to the study of schizophrenia for two main reasons: (1) cognitive impairment is considered to be a primary reason for functional disability even after successful treatment and reduction of psychotic symptoms (Nasrallah, 2010), and (2) inflammation has been suggested to play an important role in the psychopathology of schizophrenia (Leonard et al., 2012; Meyer et al., 2012; Nawa and Yamada, 2012; Sommer et al., 2012). Unfortunately, data are scarce on the links between metabolic syndrome, inflammation and neurocognition in schizophrenia. Three studies have documented the impact of metabolic syndrome on neurocognition in schizophrenia and have contradictory results (Meyer et al., 2005; Friedman et al., 2010; Lindenmayer et al., 2012). The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study did not find any relationship between MetS and cognitive impairment (Meyer et al., 2005). According to Friedman et al. (2010), one explanation for this negative finding could be partially due to the use of a
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dichotomised definition for MetS (oand ≥3 criteria). Although this cut-off is considered as a means of assisting the front-line practitioner in identifying risk factors that require clinical attention (Citrome et al., 2006), some authors have pointed out that it is seemingly arbitrary (Kahn et al., 2005). Cognitive function may be impaired progressively together with increasing numbers of MetS criteria, and the use of a continuous variable appears more appropriate (Wijndaele et al., 2006). In contrast, the study of Friedman et al. (2010) found that hypertension and body mass index (BMI) 425 exerted a significant, negative effect on neurocognition (i.e. memory). Not all of the components of MetS, however, were included in these analyses. More recently, Lindenmayer et al. (2012) have reported a link between MetS and processing speed, attention/vigilance, working memory and problem solving/reasoning. Concerning inflammation, one study proved that the C-reactive protein was associated with the cognitive impairment severity in patients with schizophrenia (Dickerson et al., 2007). Moreover, experimental studies in animals and investigations in non-schizophrenic individuals have suggested that inflammation may affect cognitive functions (i.e. executive functions, attention and working memory) which have been implicated in schizophrenia (Meyer et al., 2012). To our knowledge, no study has considered the influence of both metabolic syndrome and inflammation on neurocognition in schizophrenia. Therefore, in the present study, our aim was to investigate the relationships of MetS and inflammation with neurocognition in patients with schizophrenia. For this purpose, the MetS was analysed in three different ways using a dichotomised ( o and ≥3 criteria NCEP ATP III) or continuous (number of criteria) variable and each component of MetS in isolation.
and was not involved in the treatment of the individuals, administered the tests in a standardised manner. The same instructions were given to the individuals prior to each trial. 5. Metabolic syndrome: diagnosis of MetS was defined according to the National Cholesterol Education Program's ATP-III criteria (Grundy et al., 2005), including three or more of the following criteria: waist circumference 488 cm in women and 4102 cm in men, fasting serum triglycerides ≥150 mg/dL; serum HDL o 50 mg/dL in women and o 40 mg/dL in men, blood pressure ≥130/85 mmHg and fasting blood glucose levels ≥110 mg/dL. Waist circumference was measured at the midpoint between the lower rib margins and the iliac crest. Arterial blood pressure was recorded using a standard mercury sphygmomanometer. Glucose and lipoprotein concentrations were analysed in fasting venous blood samples using standard enzymatic techniques. All the measures were performed at the same time. 6. Inflammatory marker: serum levels of C-reactive protein (CRP) were determined using sensitive regular immunoassays (ELISA). The results are expressed as micrograms per millilitre. The detection limit was 0.08 mg/mL.
2.3. Statistical analyses Data were expressed as proportions, means or standard deviations. First, chi-squared or t-tests were conducted to compare the characteristics of the study sample in terms of MetS status (absence or presence). We then performed unadjusted and multivariate-adjusted (age, sex, education level, smoking and alcohol usage) linear regression analyses to determine whether MetS and inflammation were associated with cognitive impairment. We added an interaction term to these models to assess whether inflammation modified the association between metabolic syndrome and cognitive outcomes. The analyses were repeated using MetS as a dichotomised variable (o and ≥3 criteria NCEP ATP III), a continuous variable (number of the MetS criteria present), and for each component of MetS (waist circumference, triglycerides, HDL cholesterol levels, blood pressure, and glycaemia). All the tests were two-sided. Statistical significance was defined as p o0.05. The statistical analyses were performed using the SPSS version 18.0 software package (SPSS Inc., Chicago, IL, USA).
2. Methods
3. Results
2.1. Study participants
The mean age of the patients was 36.62 years ( 712.09), and 73.8% of them (n ¼124) were male. The patients showed moderate severity of symptoms, with a total PANSS score corresponding to 69.5 (720.0) and sub-scores of 14.3 75.4, 19.8 77.3, and 35.8 710.2, respectively, for positive, negative, and general psychopathology factors. Of the total number of patients, 86.7% had been taking second-generation antipsychotics. The prevalence rates for individual components of MetS were 46.4% for abdominal obesity, 22.6% for high triglycerides, 35.7% for low HDL cholesterol, 39.9% for hypertension, and 16.7% for hyperglycaemia. According to our results, 27.4% of patients met one, 17.9% met two, 14.9% met three, 8.9% met four, and 3.6% met five of the MetS criteria. Table 1 presents the characteristics of the study sample using MetS status. Compared to patients without MetS (n ¼122), those with MetS (n ¼46) did not differ statistically regarding sociodemographic, clinical, antipsychotic treatment and inflammatory characteristics, except for age (35.5 and 39.6 years, respectively; p¼ 0.047). Patients with MetS had significantly lower cognitive performance in the D2 attention task (p ¼0.005), and TMT A (p ¼0.016) and B (p¼ 0.029). Multivariate analyses results are reported in Tables 2–4. Our models were all adjusted on age, sex, education level, smoking and alcohol usage. In the models using MetS as a dichotomised variable, MetS and inflammation were not significantly associated with cognitive performance (all p-values 40.05). Significant associations were found between lower cognitive performance and older age, male gender, lower education levels, non-smoking status and alcohol dependence or abuse. In the models using MetS as a continuous variable, the number of MetS criteria was associated with lower cognitive performance for CVLT (β¼−0.231; p¼0.043), D2 attention (β¼ −0.255 p¼0.016) and TMT A (β¼0.198; p¼0.032) and B (β¼ 0.226; p¼0.033). Significant associations were also found with
The study evaluated all prospective patients attending daytime hospital hours in our university and psychiatric hospital over a period of 12 months, from January 2011 to December 2011. One hundred and sixty-eight outpatients with schizophrenia participated in our study, and the MetS prevalence rate was 27.4% (n¼ 46). All patients provided written informed consent. The inclusion criteria were the following: being over 18 years of age, having a diagnosis of schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV-TR) criteria (APA, 2000), and speaking French as one's native language. The exclusion criteria included the following: diagnosis other than schizophrenia on Axis I of the DSM-IV, decompensated organic disease and mental retardation. The data collection was approved by the Commission nationale de l'informatique et des libertés (CNIL number: 1223715). 2.2. Data collection The following data were collected: 1. Socio-demographic information: age, gender, and educational level. 2. Clinical characteristics: duration of disease; psychotic symptoms based on the Positive and Negative Syndrome Scale (PANSS), which comprises three different subscales such as positive, negative and general psychopathology (Kay et al., 1986); depression based on the Calgary Depression Scale for Schizophrenia (CDSS) (Addington et al., 1993); smoking status assessed by the Fagerstrom Test for Nicotine Dependence (FTND) (Heatherton et al., 1991); and alcohol dependence or abuse determined by the DSM-IV-TR (during the past year) (APA, 2000). 3. Drug information: antipsychotic medications (first-generation antipsychotics – FGAs, second-generation antipsychotics – SGAs). 4. Neurocognitive assessment: based on previous research, several measures were selected to test memory, attention, and executive functions (Szoke et al., 2008; Szoke et al., 2009). Memory was tested using the California Verbal Learning Test (CVLT), attention was tested using the D2 attention task, and executive functions were tested using the Stroop color-word test for inhibition capacity, the verbal fluency test (category domains) for spontaneous flexibility, the Trail Making Test A and B (TMT) for reactive flexibility, and the Wechsler Adult Intelligence Scale – Third Edition (WAIS-III symbol coding) for updating. The same senior psychologist, who was trained intensively in test administration
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Table 1 Sample characteristics and metabolic syndrome status (N ¼168). No metabolic syndrome N¼ 122
Metabolic syndrome N¼ 46
p-Value
Socio-demographic characteristics Age in years: Mean ( 7 SD) Sex ratio (men) (%) Education level (%): ≥12 y
35.48 712.10 74.6% 61.9%
39.63 7 11.67 71.7% 46.2%
0.047 0.708 0.089
Clinical characteristics Disease duration in years: Mean ( 7S.D.) PANSSn total score: Mean ( 7 S.D.) Positive factor Negative factor General psychopathology factor Calgary score: Mean ( 7S.D.)
11.28 79.49 68.107 20.80 13.99 7 5.54 18.85 7 7.55 35.26 7 10.49 3.94 74.34
14.3579.03 72.98 717.53 15.147 5.17 20.56 7 6.49 37.28 79.35 4.20 7 3.92
0.081 0.175 0.241 0.192 0.271 0.747
Metabolic syndrome criteria Hyperglycaemia (%) Low HDL cholesterol (%) High triglycerides (%) Hypertension (%) Abdominal obesity (%)
5.7% 18.0% 8.2% 24.6% 30.3%
45.7% 82.6% 60.9% 80.4% 89.1%
– – – – –
CRP (lg/mL): Mean ( 7 S.D.)
4.26 77.24
6.497 6.57
0.161
Fagerstrom Test: Mean ( 7 S.D.)
3.377 3.26
3.87 7 3.31
0.464
Alcohol consumption (%)
24.3%
35.7%
0.160
Cognitive assessment: Mean ( 7 S.D.) CVLT List A – 1–5 D2 attention task TMT-A (time) TMT-B (time) Stroop interference Category fluency WAIS III – Digit Symbol-Coding
44.74 713.02 133.457 43.90 42.02 724.97 100.83 7 52.16 38.157 14.19 25.09 78.69 6.39 73.25
39.80 7 11.80 106.197 50.25 53.23 7 22.93 139.277 92.48 35.877 11.95 22.767 7.61 5.337 3.06
0.052 0.005 0.016 0.029 0.432 0.152 0.083
Second Generation Antipsychotics (%)
85.4%
90.0%
0.756
Table 2 Factors associated with neurocognitive test scores: multivariate analyses.
Age Sex (women/men) Education level ( o 12/≥12 y) MetS (yes/no) CRP Fagerstrom Test Alcohol consumption (yes/ no)
CVLT List A – 1–5 βa D2 attention task
TMT-A (time)
TMT-B (time)
Stroop interference
Category fluency
WAIS III – Digit SymbolCoding
−0.374nn 0.267n −0.322nn −0.205 0.112 0.064 −0.039
0.527nn −0.006 0.288nn 0.173 0.089 −0.171n 0.077
0.386nn 0.102 0.254n 0.175 0.020 −0.145 0.162
−0.510nn −0.034 −0.362nn 0.028 0.107 0.220n −0.203
−0.019 −0.187 −0.275n −0.087 0.005 0.012 0.064
−0.002 0.124 −0.413nn −0.159 −0.156 0.000 −0.159
−0.248n −0.207 −0.309nn −0.179 −0.121 −0.067 −0.229n
MetS is included as a dichotomised variable in the analysis ( o and ≥3 criteria NCEP ATP III). PANSS: Positive and Negative Syndrome Scale. a β: standardised beta coefficient (β represents the change of the standard deviation in neurocognition scores resulting from a change of one standard deviation in the independent variable). n p≤0.05. nn p≤0.01.
older age, male gender, lower education levels, non-smoking status and alcohol dependence or abuse. As found in the previous models, inflammation was not associated with cognitive performance. An investigation of the individual components of MetS, in relation to cognition, revealed that high triglycerides and abdominal obesity were the only factors that were associated with poor cognitive performance. Lastly, the interaction terms MetS inflammation were not statistically significant in the different models.
4. Discussion For the first time, this study investigated the relationships of the metabolic syndrome, using different definitions, and
inflammation with neurocognition among patients suffering from schizophrenia. Our findings provide evidence for a correlation between MetS and more severe cognitive impairment in schizophrenia. Other factors, such as smoking and alcohol dependence or abuse, also showed a significant relationship, whereas inflammation was not associated with cognitive impairment. These findings may have important clinical implications. First, we have found a relationship between the number of MetS criteria present and cognitive impairment (i.e. memory, attention and reactive flexibility); however, we did not find any significant relationship between dichotomised MetS (absence or presence) and cognitive impairment. This finding may support the differences found in the two previous studies on patients with schizophrenia (described at the end of the introduction)
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Table 3 Factors associated with neurocognitive test scores: multivariate analyses.
Age Sex (women/men) Educational level ( o 12/≥12 y) Number of criteria of the MetS CRP Fagerstrom Test Alcohol consumption (yes/no)
CVLT List A – 1–5 βa
D2 attention task
TMT-A (time)
TMT-B (time)
Stroop i nterference
Category fluency
WAIS III – Digit Symbol-Coding
−0.358nn 0.266n −0.299nn −0.231n 0.119 0.073 −0.037
−0.225n −0.209n −0.265n −0.255n −0.112 −0.058 −0.224n
0.512nn 0.004 0.266nn 0.198n 0.084 −0.173n 0.075
0.381nn 0.102 0.225n 0.226n 0.009 −0.149 0.157
−0.509nn −0.031 −0.362nn 0.015 0.109 0.221n −0.201
−0.015 −0.193 −0.269n −0.079 0.003 0.012 0.063
0.009 0.118 −0.396nn −0.165 −0.156 0.002 −0.156
MetS is included as a continuous variable in the analysis (number of MetS criteria). a β: standardised beta coefficient (β represents the change of the standard deviation in neurocognition score resulting from a change of one standard deviation in the independent variable). n p≤0.05. nn p≤0.01.
Table 4 Individual components of MetS associated with neurocognitive test scores: multivariate analysesa. CVLT List A – 1–5 βb D2 attention task TMT-A (time) TMT-B (time) Stroop interference Category fluency WAIS III – Digit Symbol-Coding Abdominal obesity Low HDL cholesterol High triglycerides Hypertension Hyperglycaemia
−0.224 −0.153 −0.303nn −0.043 0.014
−0.123 −0.160 −0.256n 0.012 −0.211
0.206n 0.138 0.248nn −0.027 0.097
0.166 0.039 0.226n 0.150 0.120
−0.005 0.135 0.001 −0.019 −0.079
−0.093 −0.007 −0.204 0.069 −0.043
−0.131 −0.089 −0.122 0.018 −0.153
a
Adjusted for age, sex, education, smoking and alcohol use. β: standardised beta coefficient (β represents the change of the standard deviation in neurocognition scores resulting from a change of one standard deviation in the independent variable). n p≤0.05. nn p≤0.01. b
(Meyer et al., 2005; Friedman et al., 2010). This finding suggests that cognitive performance is a function of the number of MetS criteria present, and it appears unjustified to assume that optimal predictive power should be obtained using arbitrary dichotomies (Kahn et al., 2005). In our study, the use of a binary definition of MetS (≥3 criteria) has resulted in the non-inclusion of 45.3% of patients with one or two cardiovascular risk factors in the group designated as having MetS. This binary definition may have diluted the effects of MetS on cognitive performance. MetS should be considered a progressive risk factor for cognitive impairment and cannot simply be regarded as present or absent. Pre-metabolic syndrome ( o3 criteria) could also be considered a potential risk factor for compromising cognitive performance. Our findings confirm the link between cognitive impairments associated with MetS in schizophrenia (Nasrallah, 2010; Lindenmayer et al., 2012), and suggest that interventions to reduce cardiovascular risk factors, especially hyperlipidaemia and obesity, may have positive effects on cognitive deficits. Indeed, we found that among the different components of MetS, hypertriglycerides and abdominal obesity were the most important features associated with cognitive impairment. These two factors are well-established risk factors for atherosclerosis (Cheng et al., 2002), suggesting that atherosclerosis may be linked to cognitive impairment in schizophrenia. Metabolic changes may have caused micro- and macrocerebrovascular alterations which may underlie impaired neural transmission and lead to cognitive impairments such as memory, attention and executive functions (Lindenmayer et al., 2012). Several authors have also proposed non-vascular mechanisms involving actions of adiposity on neuronal tissue through neurochemical mediators, such as leptin (Li et al., 2002; Bray, 2004; Oomura et al., 2006; Holden et al., 2009). Surprisingly, other factors such as hyperglycaemia and hypertension were not statistically associated with cognitive impairment in our study. These
results contradict some previous studies (Reitz et al., 2007; Liu et al., 2009), specifically the study performed by Friedman et al. (2010) who found that hypertension increased the risk for cognitive impairment. One explanation could be the differences between populations, especially the relatively young average age in our study (36.6 years) compared with previous studies (47.3 years in Friedman's study). Future studies are necessary to explore the influence of the length of exposure to each component of MetS on cognitive impairment. In accordance with several previous studies, non-smoking (Amitai and Markou, 2009; D'Souza and Markou, 2012) and alcohol dependence or abuse (Bowie et al., 2005; Manning et al., 2009) were associated with cognitive impairment. These two factors may worsen the already decreased cholinergic transmission involved in cognitive impairment in schizophrenia (Olincy et al., 2006; D'Souza and Markou, 2012). The neurotoxic action of alcohol, which is exerted via accelerated cerebral atrophy and reduced acetylcholine synthesis, has been described previously (Whitmer et al., 2005). In practice, patients with coexisting mental and substance use disorders, such as alcohol abuse, have rarely received necessary treatments and have generally experienced poor outcomes (Essock et al., 1998; Drake et al., 2001). Hence, doctors should consider the possible existence of alcohol dependence or abuse when planning cognitive rehabilitation programs with these patients, and they should develop better coordination between addiction and mental health services in the treatment of these patients. Concerning smoking, a recent study has shown that tobacco use is associated with a better inhibitory function in schizophrenia, as found in our own study (Jurado-Barba et al., 2011). Nicotine is a cholinergic agonist that can counteract the cholinergic dysfunction in cognitive impairment (Picciotto and Zoli, 2002). Interestingly, pre-clinical studies have suggested that administration of nicotine or nicotine acetylcholine receptors
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(nAChR) agonists results in beneficial cognitive effects (D'Souza and Markou, 2012). Treatment strategies for tobacco dependence using nicotine administration and nAChR agonists may be considered in smoking cessation treatments for schizophrenic patients and for the remediation of cognitive deficits associated with schizophrenia itself (Wing et al., 2012). Unlike previous studies on elderly patients (Yaffe et al., 2004; Dik et al., 2007), inflammation was not associated with cognitive impairment and did not modify the association between metabolic syndrome and cognitive impairment. We expected the opposite findings because inflammation has been suggested to be involved in the pathogenesis of schizophrenia (Muller and Schwarz, 2010), and one study has shown that increased inflammatory response was associated with cognitive decline in schizophrenia patients (Dickerson et al., 2007). A study performed by Dickerson et al., however, did not consider several important confounding factors such as education level and MetS. However, our findings should be reviewed with caution. Our sample was smaller than that of the study performed by Dickerson et al., and we cannot exclude the possibility that the absence of association is due to lack of power. Future studies should confirm our results using larger samples.
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strategies for tobacco dependence could be considered as important targets in the remediation of cognitive impairments.
Role of funding source None.
Contributors Conception and design: LB, CL. Study's coordination: RR, FV, RP. Inclusion and clinical data collection: RR, RP. Acquisition of cognitive data: FV. Analysis of data: MB, JF. Interpretation of data: LB, RR, DD, PA, CL. Drafting and writing the manuscript: LB, RR, PA.
Acknowledgements None. References
4.1. Limitations and perspectives First, the sample size was relatively small, especially for the MetS group (n ¼46). When attempting to identify linked factors using the multivariate approach, moderate associations may have been missed due to low statistical power. Second, the sample may not be representative of the entire population of patients with schizophrenia. Patients were mostly middle-aged males with more than 5 years of illness duration. Thus, we need confirmation for more diverse and larger groups of patients. Third, this study is limited by being cross-sectional in design rather than prospective in design. No causal inference can be made formally between MetS and cognition, and our models should be interpreted from an associational point of view. Future longitudinal studies are needed to confirm that the sequence MetS-cognition is temporally verified. Fourth, several important data were not available, such as alcohol use and smoking details (i.e., amount and duration of consumption). Another potential weakness is related to the different medications used by patients and the duration of treatment. It appears that antipsychotics may have an impact on inflammation, metabolic syndrome and neurocognition (Adachi et al., 2012). Further studies should integrate these parameters to examine their role precisely. Fifth, an important methodological problem remains in the definition of MetS. Currently, several different definitions of MetS exist (Kassi et al., 2011). Although we have chosen one of the most widely used definitions in the scientific literature, ATP-III criteria seems more suitable for American than European populations and the International Diabetes Federation criteria might have been more suitable in our study. Finally, future studies will need to address whether preventing or lowering MetS and alcohol use and treating tobacco dependence will improve cognitive impairment.
5. Conclusion In conclusion, our findings suggest that MetS, alcohol use, and smoking may be linked to neurocognition in patients with schizophrenia. After replications with longitudinal approaches, these findings may support complementary therapeutic approaches, such as cognitive remediation combined with interventions to reduce cardiovascular risk factors. The prevention or reduction of metabolic syndrome and alcohol use may lessen the severity of cognitive impairment in patients with schizophrenia. Treatment
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