Cardiovascular Psychiatry and NeurologyVolume 2012 (2012), Article ID 204043, 8 pagesdoi:10.1155/2012/204043

Clinical Study

Are Cardiovascular Risk Factors Associated with Verbal Learning and Memory Impairment in Patients with Schizophrenia? A Cross-Sectional Study

Christophe Lancon,1,2,3 Daniel Dassa,⁴ Jessica Fernandez,¹ Raphaelle Richieri,1,2 Romain Padovani,1,2 and Laurent Boyer¹

¹EA 3279—Public Health, Chronic Disease, and Quality of Life Research Unit, Aix-Marseille University, 13005 Marseille, France²Department of Psychiatry, Sainte-Marguerite University Hospital, 13009 Marseille, France³Department of Addiction, Sainte-Marguerite University Hospital, 13009 Marseille, France⁴Department of Psychiatry, La Conception University Hospital, 13009 Marseille, France

Received 11 July 2012; Revised 25 September 2012; Accepted 20 October 2012

Academic Editor: Kenji Hashimoto

Copyright © 2012 Christophe Lancon et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Objective. The aim of this study is to assess the relationships of cardiovascular risk factors with verbal learning and memory in patients with schizophrenia. Methods and Design. cross-sectional study. Inclusion Criteria. Diagnosis of schizophrenia according to the DSM-IV-TR criteria. Data Collection. Sociodemographic information, clinical characteristics, anthropometric measurements, blood tests, and episodic memory using the California Verbal Learning Test (CVLT). Analysis. A multivariate analysis using multiple linear regressions was performed to determine variables that are potentially associated with verbal learning and memory. Results. One hundred and sixty-eight outpatients participated in our study. An association was found between the metabolic syndrome (MetS) and memory impairment on measures of verbal learning, and short- and long-term memory. Among the different components of MeTS, hypertriglycerides, abdominal obesity, and low HDL cholesterol were the only factors associated with memory impairment. Alcohol dependence or abuse was associated with a higher rate of forgetting. Conclusion. Our findings suggest that MetS and alcohol use may be linked with memory impairment in schizophrenia. These findings provide important insights into the interdependencies of cardiovascular risk factors and cognitive disorders and support novel strategies for treating and preventing cognitive disorders in patients with schizophrenia.

1. Introduction

Schizophrenia is characterized by significant abnormalities in multiple neurocognitive processes [1]. Cognitive impairment, especially in verbal learning and memory [2], is considered to be a primary reason for functional disability even after successful treatment and reduction of psychotic symptoms [3]. This area of investigation demands thus attention. Identification of potentially modifiable determinants of verbal learning and memory in schizophrenia is of importance for developing effective interventions that can improve the cognitive performance of patients. Interestingly, evidence suggests that cardiovascular risk factors affect cognitive functions in older patients [4–7]. Moreover, the prevalence of metabolic syndrome (MetS) is higher in individuals with schizophrenia than in the general population, with an overall rate ranging from 30 to 35% [8]. Atypical or second-generation antipsychotics are especially associated with obesity and other components of metabolic syndrome, particularly abnormal glucose and lipid metabolism [9]. Individuals with a psychiatric disorder consume approximately 46% of all cigarettes smoked in the United States [10]. Recent studies also suggest that 20–50% of schizophrenia patients have a comorbid alcohol use disorder [11]. Unfortunately, data are scarce on the links between cardiovascular risk factors and verbal learning and memory in schizophrenia [12, 13]. The most recent work suggested that hypertension and a body mass index >25 were associated to memory impairment [13]. Therefore, in the present study, our aim was to investigate the relationships of MetS, alcohol use disorder, and tobacco use with verbal learning and memory in patients with schizophrenia.

2. Methods

2.1. Study Participants

The study evaluated all prospective patients attending daytime hospital hours in our university and psychiatric hospital (Sainte-Marguerite University Hospital, Marseille, France) over a period of 12 months, from January 2011 to December 2011. 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 [14], and speaking French as one’s native language. The exclusion criteria included the following: reduced capacity to consent, diagnosis other than schizophrenia on Axis I of the DSM-IV, decompensated organic disease (i.e., appearance or exacerbation of organic disease which does not allow the patient to have a clinical interview), mental retardation (Intelligence Quotient <70), and primary neurologic conditions such as traumatic brain injury, cerebrovascular accident, or transient ischemic attack. All clinical assessments are performed in routine practice in our university psychiatric center. According to the Article L1121-1, Loi n°2011-2012 du 29 décembre 2011 - art. 5, ethical approval is not needed in France for researches in which all actions are performed and products used routinely. This study was conducted in accordance with the Declaration of Helsinki and French Good Clinical Practices.

2.2. Data Collection

Clinical assessments were performed by a multidisciplinary team including a psychiatrist, a clinical psychologist, a nurse, and a social worker if appropriate. The following data were collected.(1)Sociodemographic 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 [15]; smoking status assessed by the Fagerstrom Test for Nicotine Dependence (FTND) [16]; and alcohol dependence or abuse determined by the DSM-IV-TR (during the past year) [14].(3)Drug information: antipsychotic medications (first-generation antipsychotics (FGAs), second-generation antipsychotics (SGAs)).(4)Memory assessment: all participants completed the California Verbal Learning Test (CVLT). Administration procedures for the CVLT [17] are as follows: List A, a 16-word list, is presented five consecutive times (Trials 1–5). This list is comprised of words equally divided among four semantic categories (spices and herbs, clothing, tools, and fruits). Word order is consistent over each trial and is not related to semantic category membership. At the end of each presentation, the subject is instructed to repeat as many words as possible, in any order. After completion of Trial 5, a second 16-item List, List B, is presented once. List B is comprised of words in similar (i.e., spices and herbs, fruits) and different (i.e., fish, cooking utensils) semantic categories. After presentation of List B, the subject is asked to repeat as many words as possible from that list, in any order. After recall of List B, the subject is asked to repeat as many words as possible from List A in a short-delay free recall trial. Next, in the short-delay cued recall trial, the subject is provided with descriptors, or semantic cues, for each of the four categories of List A words (e.g., “Tell me all the words on the list that are tools.”) to help the subject recall words not initially remembered. After approximately 20 min, the subject is asked to repeat List A, both in free and cued long-delay recall conditions. The same senior psychologist, who was trained intensively in test administration 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 [18], including 3 or more of the following criteria: waist circumference >88 cm in women and >102 cm in men, fasting serum triglycerides ≥150 mg/dL; serum HDL <50 mg/dL in women and <40 mg/dL in men, blood pressure ≥130/85 mmHg (or treatment of previously diagnosed hypertension) 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.

2.3. Statistical Analyses

Data were expressed as proportions, means or standard deviations. We performed unadjusted and multivariate-adjusted linear regression analyses, including age, sex, education level, MetS, smoking, and alcohol usage to determine variables potentially associated with memory impairments on measures of span of apprehension (List A, trial 1), verbal learning (total recall trials 1–5, List A), short-term memory (short delay free recall, short delay cued recall), long-term memory (long delay free recall, long delay cued recall), rate of forgetting (difference between short and long-delay free recall), and interference (proactive: difference between List B and List A, trial 1; retroactive: difference between short delay free recall and List A, trial 5). The analyses were repeated using MetS as a continuous variable (number of the MetS criteria present) according to Friedman et al. [13], 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 . The statistical analyses were performed using the SPSS version 18.0 software package (SPSS Inc., Chicago, IL, USA).

3. Results

One hundred and sixty-eight outpatients with schizophrenia participated in our study. The characteristics of the patients are listed in Table 1. The MetS prevalence rate among the 168 patients was 27.4%. The prevalence rate for individual components of MeTS was 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: Sample characteristics ().

Socio-demographic characteristics

Age in years: Mean (± SD)

Sex ratio (men) (%)
73.8%

Education level (%): 12 y
57.6%

Clinical characteristics

Disease duration in years: Mean (± SD)

PANSS* total score: Mean (± SD)

Positive factor

Negative factor

General psychopathology factor

Second generation antipsychotics (%)
86.7%

Metabolic syndrome criteria

Hyperglycemia (%)
16.7%

Low HDL cholesterol (%)
35.7%

High triglycerides (%)
22.6%

Hypertension (%)
39.9%

Abdominal obesity (%)
46.4%

Fagerstrom Test: Mean (± SD)

Alcohol dependence or abuse (%)
27.5%

Cognitive assessment: Mean (± SD)

Span of apprehension

List A, trial 1

Verbal learning

Total recall Trials 1–5, List A

Short-term memory

Short delay free recall

Short delay cued recall

Long-term memory

Long delay free recall

Long delay cued recall

Rate of forgetting

Short-long-delay free recall

Interference

Proactive
−

Retroactive
−

In the multivariate analyses reported in Tables 2 and 3, the relationships between poor cognitive performance and MetS remained significant even after adjusting for other confounders potentially affecting memory (age, alcohol, education, and smoking). In the models using MetS as a continuous variable, the number of MetS criteria was associated with lower cognitive performance for verbal learning ( = −0.213; ), short-term memory (short delay free recall: = −0.256, ; and short delay cued recall: = −0.211, ), and long-term memory (long delay free recall: = −0.326, ; and long delay cued recall: = −0.231, ). Significant associations were also found between older age, male gender, lower education levels, alcohol dependence or abuse, and memory impairment. An investigation of the individual components of MetS revealed that high triglycerides, abdominal obesity, and low HDL cholesterol were the only factors that were associated with poor memory performance.

Table 2: Factors associated with memory test scores: multivariate analyses (β #).

List A, trial 1
Total recall Trials 1–5, List A
Short delay free recall
Short delay cued recall
Long delay free recall
Long delay cued recall
Rate of forgetting
ProactiveInterference
Retroactive interference

Age
−.056
−.332**
−.163
−.189
−.159
−.233*
−.028
−.154
.362**

Sex (women/men)
.100
.318**
.123
.176
.223*
.197
.289**
.073
−.318*

Educational level (<12/ y)
−.052
−.338**
−.361**
−.350**
−.333**
−.328**
−.066
−.088
−.053

Number of criteria of the MetS
−.184
−.213*
−.256*
−.211*
−.326**
−.231*
−.216
.062
−.023

Fagerstrom Test
−.070
.110
.126
.167
.145
.125
.062
−.022
−.118

Alcohol dependence or abuse (yes/no)
−.010
−.038
−.123
.013
.018
.091
.279**
−.007
−.162

#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); *P ≤ 0.05; **P ≤ 0.01. MetS is included as a continuous variable in the analysis (number of MetS criteria).

Table 3: Individual components of MetS associated with memory test scores: multivariate analyses (β #).

List A, trial 1
Total recall Trials 1–5, List A
Short delay free recall
Short delay cued recall
Long delay free recall
Long delay cued recall
Rate of forgetting
Proactiveinterference
Retroactive interference

Abdominal obesity
−.081
−.237**
−.274*
−.276*
−.308**
−.273*
−.149
−.043
.032

Low HDL cholesterol
−.094
−.153
−.193
−132
−.211*
−.152
−.100
.069
.011

High triglycerides
−.159
−.237*
−.202*
−.195
−.240*
−.196
−.146
.056
.165

Hypertension
−.136
−.046
−.047
−.016
−.124
−.058
−.167
.110
−.104

Hyperglycaemia
−.083
.004
−.028
−.041
−.111
−.019
−.163
−.044
−.101

#: Adjusted for age, sex, education, smoking and alcohol use. *P ≤ 0.05; **P ≤ 0.01.

4. Discussion

This study investigated the relationships of cardiovascular risk factors with verbal learning and memory in patients with schizophrenia. Our findings provide evidence for a link between MetS and more severe memory impairment in schizophrenia. In addition, alcohol dependence or abuse also showed a significant relationship, whereas tobacco was not associated with memory impairment. These findings suggest that modifiable risk factors should be sought in patients with schizophrenia, as their optimal treatment may improve these patients’ cognitive performance or keep the existing deficits from progressing.

First, we have found an association between the number of MeTS criteria present and memory impairment. Our findings confirm the link between cognitive impairments associated with MeTS in schizophrenia [3, 13], and suggest that interventions to reduce cardiovascular risk factors may have positive effects on memory deficits. Our results are also in line with previous studies’ findings showing that metabolic syndrome contributes to cognitive impairment in elders [4–7]. Indeed, we found that among the different components of MeTS, hypertriglycerides, abdominal obesity, low HDL cholesterol were the most important features associated with memory impairment. These three factors are well-established risk factors for atherosclerosis [19], suggesting that atherosclerosis may be linked to cognitive impairment in schizophrenia. Several authors have also proposed nonvascular mechanisms involving actions of adiposity on neuronal tissue through neurochemical mediators, such as leptin [20–23]. Surprisingly, other factors such as hyperglycaemia and hypertension were not statistically associated with cognitive impairment in our study. These results contradict some previous studies [6, 24], specifically the study performed by Friedman et al., who found that hypertension increased the risk for cognitive impairment [13]. 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 memory impairment.

In accordance with several previous studies, alcohol dependence or abuse [25, 26] was associated with cognitive impairment. Alcohol may worsen the already decreased cholinergic transmission involved in cognitive impairment in schizophrenia [27, 28]. The neurotoxic action of alcohol, which is exerted via accelerated cerebral atrophy and reduced acetylcholine synthesis, has been described previously [29]. Interestingly, a recent study supports that alcohol use may exacerbate an existing neurobiological alteration associated with schizophrenia [30]. 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 [31, 32]. 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.

Surprisingly, our findings did not support the existence of a relationship between smoking and memory. Nicotine is a cholinergic agonist that can counteract the cholinergic dysfunction in cognitive impairment [33]. However, previous studies found a relationship with smoking only for working memory, spatial organization, attention, and inhibitory function [28, 34]. In addition, nicotine can also desensitize/inactivate nicotinic acetylcholine receptors induced by repeated nicotine exposure [35]. Our findings should however be interpreted with caution because nicotine consumption was not precisely measured in our study (i.e., amount consumed, duration of consumption/abstinence, passive smoking).

Limitations and Perspectives(1)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. (2)This study is limited by being cross-sectional in design rather than prospective in design. No causal inference can be made formally between MeTS, alcohol and memory, and our models should be interpreted from an associational point of view. Future longitudinal studies are needed to confirm that the sequence MeTS/alcohol→Memory is temporally verified. (3)We only studied memory function because it is among the most commonly affected cognitive domains in patients with schizophrenia. Future studies should investigate other cognitive composites such as attention and executive function. Considering just one composite would not have been a perfect reflection of a global cognitive function. It would have been misleading to assume that our patients were not suffering from other neuropsychological deficits.(4)Several important data were not available, such as eating habits, alcohol use, and smoking details (i.e., amount and duration of consumption). Another potential weakness is related to the different medications used by patients. It appears that antipsychotics may have an impact on metabolic syndrome and cognition [36, 37]. In particular, atypical antipsychotics differ markedly in their potential to cause metabolic disturbances [38] or to improve cognition [39]. Further studies should thus investigate the complex interactions of antipsychotics, MeTS, and cognition, and examine the role of antipsychotics precisely. (5)Future studies will need to address whether preventing or lowering MeTS and alcohol use will improve cognitive impairment. (6)Finally, multiple tests were performed in our study and we cannot exclude false-positive results.

5. Conclusion

Our findings suggest that MetS and alcohol use may be linked to memory impairment in patients with schizophrenia. If replicated in longitudinal approaches, these findings may support novel strategies for treating and preventing cognitive disorders in patients with schizophrenia. The prevention or reduction of metabolic syndrome and alcohol use may lessen the severity of cognitive impairment in patients with schizophrenia.

Authors’ Contributions

Conception and design: C. Lancon, L. Boyer Study’s coordination: C. Lancon, D. Dassa Inclusion and clinical data collection: R. Richieri, R. Padovani Analysis of data: J. Fernandez Interpretation of data: C. Lancon, D. Dassa, L. Boyer Drafting and writing the paper C. Lancon, L. Boyer.

Conflict of Interests

The authors report that there is no conflict of interests.

References

B. E. Kopald, K. M. Mirra, M. F. Egan, D. R. Weinberger, and T. E. Goldberg, “Magnitude of impact of executive functioning and IQ on episodic memory in Schizophrenia,” Biological Psychiatry, vol. 71, pp. 545–551, 2012.

K. H. Nuechterlein, D. M. Barch, J. M. Gold, T. E. Goldberg, M. F. Green, and R. K. Heaton, “Identification of separable cognitive factors in schizophrenia,” Schizophrenia Research, vol. 72, no. 1, pp. 29–39, 2004.

H. A. Nasrallah, “Linkage of cognitive impairments with metabolic disorders in schizophrenia,” American Journal of Psychiatry, vol. 167, no. 10, pp. 1155–1157, 2010.

K. Yaffe, A. Kanaya, K. Lindquist et al., “The metabolic syndrome, inflammation, and risk of cognitive decline,” The Journal of the American Medical Association, vol. 292, no. 18, pp. 2237–2242, 2004.

M. G. Dik, C. Jonker, H. C. Comijs et al., “Contribution of metabolic syndrome components to cognition in older individuals,” Diabetes Care, vol. 30, no. 10, pp. 2655–2660, 2007.

C. Y. Liu, H. D. Zhou, Z. Q. Xu, W. W. Zhang, X. Y. Li, and J. Zhao, “Metabolic syndrome and cognitive impairment amongst elderly people in Chinese population: a cross-sectional study,” European Journal of Neurology, vol. 16, no. 9, pp. 1022–1027, 2009.

E. van den Berg, R. P. Kloppenborg, R. P. C. Kessels, L. J. Kappelle, and G. J. Biessels, “Type 2 diabetes mellitus, hypertension, dyslipidemia and obesity: a systematic comparison of their impact on cognition,” Biochimica et Biophysica Acta, vol. 1792, no. 5, pp. 470–481, 2009.

A. J. Mitchell, D. Vancampfort, K. Sweers, R. van Winkel, W. Yu, and M. De Hert, “Prevalence of metabolic syndrome and metabolic abnormalities in schizophrenia and related disorders—a systematic review and meta-analysis,” Schizophrenia Bulletin. In press

P. Pramyothin and L. Khaodhiar, “Metabolic syndrome with the atypical antipsychotics,” Current Opinion in Endocrinology, Diabetes and Obesity, vol. 17, no. 5, pp. 460–466, 2010.

B. F. Grant, D. S. Hasin, S. P. Chou, F. S. Stinson, and D. A. Dawson, “Nicotine dependence and psychiatric disorders in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions,” Archives of General Psychiatry, vol. 61, no. 11, pp. 1107–1115, 2004.

J. Koskinen, J. Löhönen, H. Koponen, M. Isohanni, and J. Miettunen, “Prevalence of alcohol use disorders in schizophrenia—a systematic review and meta-analysis,” Acta Psychiatrica Scandinavica, vol. 120, no. 2, pp. 85–96, 2009.

J. M. Meyer, H. A. Nasrallah, J. P. McEvoy et al., “The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) Schizophrenia Trial: clinical comparison of subgroups with and without the metabolic syndrome,” Schizophrenia Research, vol. 80, no. 1, pp. 9–18, 2005.

J. I. Friedman, S. Wallenstein, E. Moshier et al., “The effects of hypertension and body mass index on cognition in schizophrenia,” American Journal of Psychiatry, vol. 167, no. 10, pp. 1232–1239, 2010.

APA: DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, American Psychiatric Association, Washington, DC, USA, 4th edition, 2000.

S. R. Kay, L. A. Opler, and A. Fiszbein, “Significance of positive and negative syndromes in chronic schizophrenia,” British Journal of Psychiatry, vol. 149, pp. 439–448, 1986.

T. F. Heatherton, L. T. Kozlowski, R. C. Frecker, and K. O. Fagerstrom, “The Fagerstrom test for nicotine dependence: a revision of the Fagerstrom Tolerance Questionnaire,” British Journal of Addiction, vol. 86, no. 9, pp. 1119–1127, 1991.

D. C. Delis, J. H. Kramer, E. Kaplan, and B. A. Ober, California Verbal Learning Test: Research Edition-Adult Version, The Psychological Corporation, New York, NY, USA, 1987.

S. M. Grundy, J. I. Cleeman, S. R. Daniels et al., “Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement,” Circulation, vol. 112, no. 17, pp. 2735–2752, 2005.

A. Cheng, J. B. Braunstein, C. Dennison, C. Nass, and R. S. Blumenthal, “Reducing global risk for cardiovascular disease: using lifestyle changes and pharmacotherapy,” Clinical Cardiology, vol. 25, no. 5, pp. 205–212, 2002.

G. A. Bray, “Obesity is a chronic, relapsing neurochemical disease,” International Journal of Obesity, vol. 28, no. 1, pp. 34–38, 2004.

K. F. Holden, K. Lindquist, F. A. Tylavsky, C. Rosano, T. B. Harris, and K. Yaffe, “Serum leptin level and cognition in the elderly: findings from the Health ABC Study,” Neurobiology of Aging, vol. 30, no. 9, pp. 1483–1489, 2009.

X. L. Li, S. Aou, Y. Oomura, N. Hori, K. Fukunaga, and T. Hori, “Impairment of long-term potentiation and spatial memory in leptin receptor-deficient rodents,” Neuroscience, vol. 113, no. 3, pp. 607–615, 2002.

Y. Oomura, N. Hori, T. Shiraishi et al., “Leptin facilitates learning and memory performance and enhances hippocampal CA1 long-term potentiation and CaMK II phosphorylation in rats,” Peptides, vol. 27, no. 11, pp. 2738–2749, 2006.

C. Reitz, M. X. Tang, J. Manly, R. Mayeux, and J. A. Luchsinger, “Hypertension and the risk of mild cognitive impairment,” Archives of Neurology, vol. 64, no. 12, pp. 1734–1740, 2007.

V. Manning, S. Betteridge, S. Wanigaratne, D. Best, J. Strang, and M. Gossop, “Cognitive impairment in dual diagnosis inpatients with schizophrenia and alcohol use disorder,” Schizophrenia Research, vol. 114, no. 1–3, pp. 98–104, 2009.

C. R. Bowie, M. R. Serper, S. Riggio, and P. D. Harvey, “Neurocognition, symptomatology, and functional skills in older alcohol-abusing schizophrenia patients,” Schizophrenia Bulletin, vol. 31, no. 1, pp. 175–182, 2005.

A. Olincy, J. G. Harris, L. L. Johnson et al., “Proof-of-concept trial of an α7 nicotinic agonist in schizophrenia,” Archives of General Psychiatry, vol. 63, no. 6, pp. 630–638, 2006.

M. S. D'Souza and A. Markou, “Schizophrenia and tobacco smoking comorbidity: nAChR agonists in the treatment of schizophrenia-associated cognitive deficits,” Neuropharmacology, vol. 62, pp. 1564–1573, 2012.

R. A. Whitmer, S. Sidney, J. Selby, S. C. Johnston, and K. Yaffe, “Midlife cardiovascular risk factors and risk of dementia in late life,” Neurology, vol. 64, no. 2, pp. 277–281, 2005.

M. J. Smith, L. Wang, W. Cronenwett et al., “Alcohol use disorders contribute to hippocampal and subcortical shape differences in schizophrenia,” Schizophrenia Research, vol. 131, pp. 174–183, 2011.

R. E. Drake, S. M. Essock, A. Shaner et al., “Implementing dual diagnosis services for clients with severe mental illness,” Psychiatric Services, vol. 52, no. 4, pp. 469–476, 2001.

S. M. Essock, R. E. Drake, and B. J. Burns, “A research network to evaluate assertive community treatment: introduction,” The American Journal of Orthopsychiatry, vol. 68, no. 2, pp. 176–178, 1998.

M. R. Picciotto and M. Zoli, “Nicotinic receptors in aging and dementia,” Journal of Neurobiology, vol. 53, no. 4, pp. 641–655, 2002.

R. Jurado-Barba, I. Morales-Muñoz, B. A. del Manzano et al., “Relationship between measures of inhibitory processes in patients with schizophrenia: role of substance abuse disorders,” Psychiatry Research, vol. 190, pp. 187–192, 2011.

E. L. M. Ochoa and J. Lasalde-Dominicci, “Cognitive deficits in schizophrenia: focus on neuronal nicotinic acetylcholine receptors and smoking,” Cellular and Molecular Neurobiology, vol. 27, no. 5, pp. 609–639, 2007.

H. Adachi, H. Yanai, and Y. Hirowatari, “The underlying mechanisms for olanzapine-induced hypertriglyceridemia,” Journal of Clinical Medicine Research, vol. 4, pp. 206–208, 2012.

C. Garcia-Rizo, E. Fernandez-Egea, C. Oliveira, A. Justicia, M. Bernardo, and B. Kirkpatrick, “Inflammatory markers in antipsychotic-naïve patients with nonaffective psychosis and deficit vs. nondeficit features,” Psychiatry Research, vol. 198, no. 2, pp. 212–215, 2012.

H. A. Nasrallah and J. W. Newcomer, “Atypical antipsychotics and metabolic dysregulation: evaluating the risk/benefit equation and improving the standard of care,” Journal of Clinical Psychopharmacology, vol. 24, no. 5, supplement 1, pp. S7–S14, 2004.

H. Y. Meltzer and S. R. McGurk, “The effects of clozapine, risperidone, and olanzapine on cognitive function in schizophrenia,” Schizophrenia Bulletin, vol. 25, no. 2, pp. 233–255, 1999.