Prevalence of polymorphisms in the ANKK1, DRD2, DRD3 genes and metabolic syndrome in refractory schizophrenia

ABSTRACT

Objective:

to estimate the prevalence of TaqIA, -141C and rs6280 polymorphisms of the ANKK1, DRD2 and DRD3 genes and evaluate their association with the occurrence of metabolic syndrome in patients with refractory schizophrenia.

Method:

cross-sectional study conducted in the Extended Western Region of Minas Gerais, with refractory schizophrenic patients using the antipsychotic clozapine. Sociodemographic, clinical, anthropometric, biochemical and genetic data were collected. Univariate analysis of the data was performed.

Results:

seventy-two patients participated in the study and the occurrence of Metabolic Syndrome was observed in 47.2% of them. There was no association between Metabolic Syndrome and the studied polymorphisms. There was a statistically significant difference in the low HDL parameter with homozygous genotype for the C allele of the -141C polymorphism of the DRD2 gene.

Conclusion:

a high prevalence of MS was evidenced. The -141C polymorphism was associated with low HDL. Genetic analysis and identification of metabolic alterations in this group of patients can guide drug treatment and provide a better quality of life.

Descriptors:
Nursing; Schizophrenia; Genetic Polymorphism; Metabolic X Syndrome; Clozapine; Health Profile

RESUMO

Objetivo:

estimar a prevalência dos polimorfismos TaqIA, -141C e rs6280 dos genes ANKK1, DRD2 e DRD3 e avaliar sua associação com a ocorrência de síndrome metabólica em pacientes com esquizofrenia refratária.

Método:

estudo de delineamento transversal, realizado na Região Ampliada Oeste de Minas Gerais, que incluiu pacientes com esquizofrenia refratária em uso do antipsicótico clozapina. Foram coletados dados sociodemográficos, clínicos, antropométricos, bioquímicos e genéticos. Realizou-se análise univariada dos dados.

Resultados:

participaram 72 pacientes e observou-se a ocorrência de Síndrome Metabólica em 47,2%, não sendo encontrada associação da Síndrome Metabólica com os polimorfismos estudados. Houve diferença estatisticamente significante com o parâmetro do baixo HDL com genótipo homozigoto para alelo C do polimorfismo -141C do gene DRD2.

Conclusão:

evidenciou-se prevalência de SM elevada. O polimorfismo -141C associou-se ao baixo HDL. A análise genética e a identificação de alterações metabólicas, neste grupo de pacientes, podem nortear o tratamento medicamentoso e propiciar melhor qualidade de vida.

Descritores:
Enfermagem; Esquizofrenia; Polimorfismo Genético; Síndrome X Metabólica; Clozapina; Perfil de Saúde

RESUMEN

Objetivo:

estimar la prevalencia de los polimorfismos TaqIA, -141C y rs6280 de los genes ANKK1, DRD2 y DRD3 y evaluar su asociación con el síndrome metabólico en pacientes con esquizofrenia refractária.

Método:

estudio de delineamiento transversal, realizado en la Región Ampliada Oeste de Minas Gerais, que incluye pacientes con esquizofrenia refractária usando el antipsicótico clozapina. Fueron recogidos datos sociodemográficos, clínicos, antropométricos, bioquímicos y genéticos. Se realizó um análisis univariada de los datos.

Resultados:

participaron 72 pacientes y se observó el Síndrome Metabólico en 47,2%, no siendo encontrada una asociación del Síndrome Metabólico con los polimorfismos estudiados. Hubo diferencia estadísticamente significante con el parámetro del bajo HDL con genotipo homozigoto para alelo C del polimorfismo -141C del gen DRD2.

Conclusión:

se vio una prevalencia de SM elevada. El polimorfismo -141C se asoció al bajo HDL. El análisis genético y la identificación de alteraciones metabólicas, en este grupo de pacientes, pueden guiar al tratamiento medicamentoso y propiciar mejor calidad de vida.

Descriptores:
Enfermería; esquizofrenia; El polimorfismo genético; Síndrome X Metabólico; Clozapina; Perfil de Salud

Introduction

Schizophrenia is considered one of the most serious mental disorders nowadays, since its progression affects the quality of life of individuals who experience the disease and also of their relatives¹. Schizophrenia affects more than 21 million people worldwide and is considered a major public health problem^1-2. This disease is manifested mainly by the presence of positive symptoms (change in the thinking process, perceptions and affection) and negative symptoms (affective-volitional blunting, cognitive losses and depressive symptoms)².

Approximately 40% of people with schizophrenia do not present adequate response to drug treatment and persist with symptoms of the disease; they are known as refractory schizophrenic people^1-3. Although there is no single, globally accepted consensus, refractory schizophrenia can be characterized by partial response, for at least five years, to three different types of antipsychotics (at least two with different chemical structures); intolerance to adverse effects; and relapses or symptomatic deterioration despite the use of appropriate doses of the drugs^3-4. The atypical antipsychotic clozapine is considered the gold standard for the drug treatment of refractory schizophrenia, being associated with clinical improvement and decreased hospitalizations^4-5.

In this context, studies have indicated that genetic polymorphisms of dopaminergic pathways are related to etiopathogenesis and drug response to treatment, as well as to a greater susceptibility to clinical alterations. Unique or Single Nucleotide Polymorphisms (SNPs) consist in a variation of the DNA sequence caused by a single nucleotide exchange in the genome sequence. Some SNPs alter the amino acid composition of the protein and the expression of the receptor, which may have an effect on the phenotype of an individual, and can also serve as molecular markers of predisposition to certain types of diseases. The ability to detect polymorphisms at the DNA level is the basis of several studies that aim to identify whether this variation causes or contributes to a specific phenotype^5-6.

Among the genetic polymorphisms of the most studied dopaminergic pathway are the TaqIA, -141C and rs6280. These variants are located in the ANKK1, DRD2 and DRD3 genes, respectively, which have already been addressed by other authors in the literature, relating them to the response to antipsychotics and metabolic alterations of the individuals making use of this drug treatment^4-5. However, further in-depth analyses of how these variants in the DNA sequence can influence metabolic alterations in the carriers of these polymorphisms are necessary, as this theme is still little elucidated⁷.

The abovementioned polymorphisms occur in genes encoding proteins that contribute to adequate signaling of neurotransmitters in the mesocorticolimbic pathway or ventral tegmental area. These regions play an important role in motivation, guided thinking, affective balance and in the reward system, the latter being responsible for the feeling of satiety and appetite. Psychotropic drugs act primarily in these regions by lowering dopamine (DA) levels and therefore reducing psychotic symptoms. However, at very low levels, they can lead to cognitive impoverishment, depression and metabolic alterations⁸.

One of the potential consequences of this biochemical process is a condition known as Metabolic Syndrome (MS)^6-9. MS is characterized by a set of risk factors that include abdominal obesity, insulin resistance, dyslipidemia and hypertension. The prevalence of MS in patients with refractory schizophrenia compared to patients with other forms of schizophrenia is higher and has more drastic repercussions, reaching 69%⁹. Although the causal relationship between refractory schizophrenia and MS is not fully understood, there is evidence of the association between second-generation antipsychotics and the development of this syndrome. It has been suggested that the presence of negative symptoms may increase the risk, which may be associated with the sedentary lifestyle and the poor quality of life resulting from this condition^10-11.

The genetic analysis of refractory schizophrenic patients can become an essential tool in the perspective of a care plan using genetic counseling, which can serve as a basis to guide the drug treatment and consequently provide a better quality of life for these notably more severe patients. In view of the above, the present study aims to estimate the prevalence of TaqIA, -141C and rs6280 polymorphisms of the ANKK1, DRD2 and DRD3 genes and to evaluate their association with the occurrence of MS in refractory schizophrenic patients.

Method

This is a cross-sectional and analytical study carried out in the Extended Western Region of Minas Gerais with patients diagnosed with refractory schizophrenia using the antipsychotic clozapine. The following inclusion criteria were observed: medical diagnosis of refractory schizophrenia with use of the atypical antipsychotic clozapine, male or female patients older than 18 years and with understanding capacity attested by the Mini-Mental State Examination (MMSE)¹². Pregnant women, participants who were not fasting, and those who had any condition that could interfere with the collection and measurement of data, such as the presence of physical disability that could impair the measurement of anthropometric characteristics, were excluded. The need for fasting was due to the performance of laboratory tests to verify the presence of MS.

The sample calculation was performed using the OpenEpi version 3.03a, considering a population of 169 individuals for an expected proportion of the event of 50%, a significance level of 5% and a margin of error of 10%. A sample of approximately 62 individuals was estimated. The final sample consisted of 72 participants.

All individuals who made up the eligible population were previously invited to collect data by sending letters and making a telephone contact, when they received all the necessary guidelines for the research. Data were collected from December 2014 to June 2015.

Data were collected at the Psychosocial Care Center type III of the municipality-polo of the Great West Region in scheduled date and time. The sociodemographic and clinical profile of the subjects of this study was surveyed through a semi-structured questionnaire prepared by the authors, including the following data: gender, age, marital status, number of children, family income, schooling, and people with whom they reside. The following clinical data was surveyed: time of psychiatric treatment, previous psychiatric hospitalization, time of use of clozapine, number of consultations per year, clinical diseases, use of medications, smoking, alcohol use, physical activity, perception about the effect of the medication and satisfaction with health.

For biochemical and genetic analyses, venous blood samples were taken from the cubital vein of the forearm after a 12-hour fast. The analysis was done in the biochemistry and genetics laboratory of the Federal University of São João Del-Rei/Center - Dona Lindu West Campus.

In the biochemical evaluation, laboratory tests of fasting glycemia (FG), high-density lipoprotein-cholesterol (HDL-c) and triglycerides (TG) were performed. MS was determined according to the criteria of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP-III), which defines the MS as the presence of three or more of the following risk factors: central obesity (abdominal circumference > 102cm in men or > 88cm in women); high blood pressure (> 130/85mmHg) or on antihypertensive treatment; hyperglycemia (fasting blood glucose > 100mg/dL) or treatment with hypoglycemic drugs; high triglyceride concentration (>150mg/dL) or use of medication to reduce it; low HDL-c (< 40mg/dL in men or < 50mg/dL in women) or on use of low HDL-c medication¹¹.

The genetic analysis of peripheral blood samples consisted of five steps: the first one was the extraction of genomic DNA using the QIAamp Mini Blood Kit (Qiagen) according to the manufacturer’s protocol; the second step was the amplification ofthe DNA target sequences of each of the genes involved in the study using Polymerase Chain Reaction (PCR); then, each sample of PCR product was subjected to electrophoresis to confirm the amplification of the regions of interest; for genotyping, the Restriction Fragment Length Polymorphism (RFLP) technique was used; and, finally, the samples digested in the previous step were submitted to an 8% polyacrylamide gel for separation of DNA bands, which are expected and identified by their respective sizes (number of nitrogenous bases).

Data processing and analysis were performed in the Statistical Package for Social Science (SPSS), version 20.0. To describe the results, frequency distribution tables were used for categorical variables. In the analysis of categorical variables, the Pearson chi-square of and Fisher’s exact test were used for the univariate analysis to evaluate the MS factors associated to the polymorphisms. A p-value < 0.20 was adopted for inclusion of variables in the model. The adjusted odds ratio (OR) with a respective 95% confidence interval (95% CI) was estimated. The goodness of fit of the model was assessed using the Hosmer-Lemeshow test.

Hardy-Weinberg equilibrium was analyzed through the Pearson chi-square test, comparing the frequencies of the genotypes observed with those expected for this population. This calculation was performed using the Hardy-Weinberg equilibrium calculator software including analysis for ascertainment bias (13).

The study was approved by the Research Ethics Committee under Protocol nº 1,406,658, in compliance with the recommendations of Resolution 466/2012 of the National Health Council.

Results

An unintentional finding of the study was that both genders were equally represented among the 72 patients with refractory schizophrenia in use of clozapine (50%). The average age of the participants was approximately 43 years.

It was verified that the prevalence of MS in the studied population was 47.2%, being more frequent among females (58.8%), but it was also observed that males also had a high incidence rate (41.2%). Patients in the age group below 40 years were those with the highest prevalence of MS (38.2%). Another characteristic identified was the time of treatment with clozapine, in which a prevalence of 65.6% of MS was found in those who had used this medication for more than 5 years.

Table 1 below shows the percentage distribution of the occurrence of each variant, detailed according to genotypic and allelic frequencies. The Hardy-Weinberg equilibrium, as tested through the chi-square value, found at each genotype frequency is shown in the table. No deviation was identified. The chi-square table was used as reference.

Table 1:
Prevalence of the analyzed polymorphisms (n = 72). Extended Western Region of Minas Gerais, MG, Brazil, 2015

	Percentage	N	p-value*
TaqIA polymorphism
Genotypes
Homozygous for the C allele	51.4	37	0.0454
Heterozygous	41.7	30
Homozygous for the T allele	6.9	5
Alleles
C	72.2	104
T	28.0	40
-141C polymorphism
Genotypes
Homozygous for the Del C allele	68.1	49	0.0000
Heterozygous	25.0	18
Homozygous for the Ins C allele	6.9	5
Alleles
Del C	80.5	116
Ins C	19.4	28
rs6280 polymorphism
Genotypes
Homozygous for the C allele	23.6	17	0.0032
Heterozygous	41.7	30
Homozygous for the T allele	34.7	25
Alleles
C	55.5	80
T	44.4	64

• N: observed frequencies * p-value: chi-square test

Table 2 shows the association of the studied polymorphisms with MS. Regarding genotypic and allelic analyses, there was no statistically significant difference with MS (p > 0.05).

Table 2:
Analysis of association of polymorphisms in patients with and without metabolic syndrome* (n = 72). Extended Western Region of Minas Gerais, MG, Brazil, 2015

Polymorphism	Without MS*		With MS*		p†
	N	%	N	%
TaqIA genotypes
Homozygous for the C allele	21	55.3	16	47.1	0.708
Heterozygous	15	39.5	15	44.1
Homozygous for the T allele	2	5.3	3	8.8
TaqIA alleles
C	36	67.9	31	63.3	0.620
T	17	32.1	18	36.7
-141C genotypes
Homozygous for the Del C allele	25	65.8	24	70.6	0.184
Heterozygous	12	31.6	6	17.6
Homozygous for the Ins C allele	1	2.6	4	11.8
-141C alleles
Del C	37	74.0	30	75.0	0.914
Ins C	13	26.0	10	25.0
rs6280 genotypes
Homozygous for the T allele	16	42.1	9	26.5	0.311
Heterozygous	13	34.2	17	50.0
Homozygous for the C allele	9	23.7	8	23.5
rs6280 alleles
C	45	40.8	25	41.7	0.551
T	29	59.2	35	58.3

• *Metabolic Syndrome †χ² Test; level of significance: p < 0.05.

There was no association considering the three components of MS, high blood pressure, central obesity and hypertriglyceridemia according to the polymorphisms of interest in this study. Low HDL showed a significant association with homozygous genotype for the Ins C allele of the -141C polymorphism of the DRD2 gene (p < 0.05), as described in Table 3.

Table 3:
Analysis of association of polymorphisms according to the metabolic syndrome component - Low HDL* (n = 72). Extended Western Region of Minas Gerais, MG, Brazil, 2015

Polymorphism	Without low HDL*		With low HDL*		p†
	N	%	N	%
TaqIA genotypes
Homozygous for the C allele	30	52.6	7	46.7	0.901
Heterozygous	23	40.4	7	46.7
Homozygous for the T allele	4	7.0	1	6.7
TaqIA alleles
W	83	72.8	21	70.0	0.819
T	31	27.2	9	30.0
-141C genotypes
Homozygous for the Del C allele	38	66.7	11	73.3	0.032
Heterozygous	17	29.8	1	6.7
Homozygous for the Ins C allele	2	3.5	3	20.0
-141C alleles
Del C	93	81.6	23	76.7	0.545
Ins C	21	18.4	7	23.3
rs6280 genotypes
Homozygous for the T allele	20	35.1	5	33.3	0.952
Heterozygous	24	42.1	6	40.0
Homozygous for the C allele	13	22.8	4	26.7
rs6280 alleles
W	50	43.9	14	46.7	0.874
T	64	56.1	16	53.3

• *High-Density Lipoprotein †χ² Test; level of significance: p < 0.05.

As for hyperglycemia, the only polymorphism that presented a statistically significant association was the rs6280 of the DRD3 gene, in which the homozygous genotype for the T allele had a higher prevalence and was associated with non-hyperglycemia, as shown in the table below (Table 4).

Table 4:
Analysis of association of polymorphisms according to the metabolic syndrome component - Hyperglycemia (n = 72). Extended Wester Region of Minas Gerais, MG, Brazil, 2015

Polymorphism	Without Hyperglycemia		With Hyperglycemia		p*
	N	%	N	%
TaqIA genotypes
Homozygous for C allele	15	62.5	22	45.8	0.084
Heterozygous	6	25.0	24	50.0
Homozygous for T allele	3	12.5	2	4.2
TaqIA alleles
W	36	75.0	68	70.8	0.554
T	12	25.0	28	29.2
-141C genotypes
Homozygous for C allele	15	62.5	34	70.8	0.098
Heterozygous	9	37.5	9	18.8
Homozygous for Ins C allele	0	0	5	10.4
-141C alleles
Del C	39	81.3	77	80.2	0.776
Ins C	9	18.8	19	19.8
rs6280 genotypes
Homozygous for T allele	13	54.2	12	25.0	0.040
Heterozygous	6	25.0	24	50.0
Homozygous for C allele	5	20.8	12	25.0
rs6280 alleles
W	16	33.3	48	50.0	0.021
T	32	66.7	48	50.0

• *χ² Test; significance level: p <0.05.

The result of the analysis of the factor associated with the -141C variant of the DRD2 and rs6280 genes, component of the syndrome, low HDL, is shown in Table 5. The homozygous genotype for the Ins C allele of the -141C polymorphism (OR: 19.8) was associated with low HDL, that is, in this study, it was evidenced that a patient diagnosed with refractory schizophrenia who presented the -141C variant of the DRD2 gene and had the homozygous genotype for the Ins C allele was almost 20-fold more likely to present a low HDL level when compared to the heterozygous genotype.

Table 5:
Odds Ratio Calculation* (OR) with respective 95%Confidence Interval (95% CI). Extended Western Region of Minas Gerais, MG, Brazil, 2015

	OR*	CI 95%† for OR
		Low limit	Upper limit
-141C polymorphism	Low HDL
Genotypes
Heterozygous	1.00	-	-
Homozygous for the Ins C allele	19.8	1.51	701.1

• * Odds Ratio †95% CI - 95% Confidence Interval.

Discussion

This investigation brings as one result the non-association of the TaqIA, -141C and rs6280 polymorphisms of the dopaminergic system with MS. However, it is a very relevant investigation because it showed the components that can lead to MS. In addition, a better elucidation of these factors is important to avoid other disastrous complications in the health of these patients¹⁴.

Metabolic disturbances are more prevalent in schizophrenic patients than in the general population and this may translate into an increased risk of chronic degenerative diseases and even mortality in this group¹⁴. According to Papanastasiou (2013), women tend to have increased rates of MS compared to men, a datum corroborated in the present study. However, that data must be carefully interpreted; men are likely to be at increased risk of developing cardiovascular disease as the possible result of a combination of unhealthy lifestyles and lack of health care when compared to women^15-16.

The present study revealed a statistically significant difference in the genotypic distribution of the SNP -141C Ins/Del of the DRD2 gene, with association of the homozygous Ins C genotype when analyzed with the low HDL levels. Some studies that have investigated the association of this polymorphism with schizophrenia found an increased frequency of this allele (Ins) in this group of patients^17-18. A study conducted in 2010 found that significant weight gain was confirmed after 6 weeks of treatment with risperidone or olanzapine in the population of patients with the -141C Del allele. ¹⁹. In the present investigation, the Del C allele was also observed to have the highest frequency.

An investigation that sought to characterize the metabolic profile of patients who presented the first episode of schizophrenic outbreak reported a higher prevalence of low HDL in this group than the general population, but there was no association with the genetic profile of this population²⁰. Low HDL levels predict increased cardiovascular risk, while high HDL levels are associated with a drop of up to 40% in cardiovascular risk compared to low HDL alone; that is to say, when HDL levels are below the recommended levels, there is risk of complications, especially of cardiac nature^21-22.

There are studies that provide evidence of the association of altered glycemic levels with schizophrenia, but no association with the rs6280 polymorphism of the DRD3 gene has been found in the literature^8-23. A study that analyzed the use of conventional and atypical antipsychotics in schizophrenic patients and correlated this factor with MS and its components showed that clozapine was the second most potent drug in the induction of MS. It also demonstrated that this drug was related with weight gain in patients after 16 weeks of continuous treatment, together with a significant increase in glycemic and lipid parameters²⁴.

The change in glycemic levels in this particular group of patients may have even more harmful repercussions because the disease may induce metabolic alterations and some drug treatments may potentiate this risk. It is therefore necessary to monitor glycemic levels in all patients diagnosed with refractory schizophrenia in order to reduce morbidity and mortality risks. The present study found the association of the genotype of this variant rs6280 to absence of hyperglycemia, and this suggests that the presence of this variant, especially in those who present homozygosis for the T allele, is a protective factor against hyperglycemia.

The monitoring of this metabolic alteration is fundamental for the evaluation of cardiovascular risk. The imbalance of this marker is an indicator of risk for chronic-degenerative diseases and increased mortality. Routine follow-up on a regular basis and education on healthy lifestyle are necessary to minimize the risks of complications^2-15. The hypotheses raised in this study suggest that the health care for refractory schizophrenic patients using clozapine must be comprehensive, and the planning of strategies aimed at minimizing the risk of metabolic alterations should be one of the main goals of the individual therapeutic plan for these patients^2-14.

The findings of this study indicated relevant issues when highlighted the vulnerability to which refractory schizophrenic patients are exposed. Metabolic changes increase the risk for the development of cardiovascular diseases and other health implications, which directly interfere with the quality of life of these patients. Therefore, it is essential to develop planned actions and periodic monitoring of plasma levels of biochemical markers that may lead to MS in order to prevent metabolic alterations.

In this sense, it is important that professionals directly involved in the care of these patients know their different metabolic profiles and the possible adverse effects to which they are exposed, so as to conduct the appropriate treatment for each of them. Awareness of the possibility of these effects must also be raised among patients, allied to promotion of healthy habits, especially regarding a healthy diet and the practice of physical activity.

The limitations of this study are related to its external validity, considering that the sample was not probabilistic and caution is necessary regarding the generalization of the results. The research design allowed estimating the prevalence of the polymorphisms as well as the associated factors, and it is not possible, therefore, to make cause-effect inferences. In addition, we suggest the development of longitudinal researches to improve the understanding of aspects pertinent to the development of MS, establishing associations with the polymorphisms of interest. However, the chosen design provided satisfactory responses to the guiding questions and objectives of the study.

Conclusion

The results of this study indicated that the prevalence of MS in people with refractory schizophrenia using clozapine is high, but there was no association with the polymorphisms of interest. The ancestral genotype appeared to be a protective factor against hyperglycemia in this sample. Therefore, these findings point to the need to carry out further studies involving genetic analyses and MS in patients with refractory schizophrenia in order to guide the drug treatment and promote a better quality of life of this clientele.

Acknowledgements

We thank the Foundation for Research Support of Minas Gerais (FAPEMIG) for the financial support provided to the research.

References

• ¹
  World Health Organization. Mental health. Schizophrenia. Suiça. [cited Fev 22, 2015]. Available from: http://www.who.int/mental_health/management/schizophrenia/en/
  » http://www.who.int/mental_health/management/schizophrenia/en
• ²
  Freitas PHB, Pinto JAF, Nunes FDD, Souza ARS, Machado RM. Refractory schizophrenia: quality of life and associated factors. Acta Paul Enferm. 2016a; 29(1):60-8. doi: http://dx.doi.org/10.1590/1982-0194201600009
  » http://dx.doi.org/10.1590/1982-0194201600009
• ³
  Kane JM, Peters-Strickland T, Baker RA, Hertel P, Eramo A, Jin N, et al. Aripiprazole once-monthly in the acute treatment of schizophrenia: findings from a 12-week, randomized, double-blind, placebo-controlled study. J Clin Psychiatry. 2014; 75(11):1254-60. doi: http://dx.doi.org/10.4088/JCP.14m09168
  » https://doi.org/10.4088/JCP.14m09168
• ⁴
  Stroup T, Gerhard T, Crystal S, Huang C, Olfson M. Comparative effectiveness of clozapine and standard antipsychotic treatment in adults with schizophrenia. Am J Psychiatry. 2016;173(2):166. doi: 10.1176/appi.ajp.2015.15030332
  » https://doi.org/10.1176/appi.ajp.2015.15030332
• ⁵
  Fonseka TM, Tiwari AK, Gonçalves VF, Lieberman JA, Meltzer HY, Goldstein BI, et al. The role of genetic variation across IL-1ß, IL-2, IL-6, and BDNF in antipsychotic-induced weight gain. World J Biol Psychiatry. 2015; 16(1):45-56. doi: 10.3109/15622975.2014.984631
  » https://doi.org/10.3109/15622975.2014.984631
• ⁶
  Kirsti K, Holmen J, Hveem K, Holmen TL. Genetic. Effects on Longitudinal Changes from Healthy to Adverse Weight and Metabolic Status-The HUNT Study. Plos One. 2015; 10(10): e0139632. doi: http://dx.doi.org/10.1371/journal.pone.0139632
  » https://doi.org/10.1371/journal.pone.0139632
• ⁷
  Moran ME, Pol HH, Gogtay N. A family affair: brain abnormalities in siblings of patients with schizophrenia. Brain. 2013; 136 (11):3215-26. doi: https://doi.org/10.1093/brain/awt116
  » https://doi.org/10.1093/brain/awt116
• ⁸
  Kegeles LS, Abi-Dargham A, Frankle WG, Gil R, Cooper TB, Slifstein M, et al. Increased synaptic dopamine function in associative regions of the striatum in schizophrenia. Arch Gen Psychiatry. 2010 Mar;67(3):231-9. doi: 10.1001/archgenpsychiatry.2010.10
  » https://doi.org/10.1001/archgenpsychiatry.2010.10
• ⁹
  Vujic T, Nagorni O, Maric G, Popovic L, Jankovic J. Metabolic syndrome in patients with chronic obstructive pulmonary disease: frequency and relationship with systemic inflammation. Hippokratia. [Internet]. 2016 Apr/Jun [cited Jan 2, 2017]; 20(2):110-4. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388510/
  » https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388510
• ¹⁰
  Sicras-Mainar A, Maurino J, Ruiz-Beato E, Navarro-Artieda R. Prevalence of metabolic syndrome according to the presence of negative symptoms in patients with schizophrenia. Neuropsychiatry. 2015 Dec; 11:51-7. doi: 10.2147/NDT.S75449
  » https://doi.org/10.2147/NDT.S75449
• ¹¹
  Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112(17):2735-52. doi: https://doi.org/10.1161/CIRCULATIONAHA.105.169404
  » https://doi.org/10.1161/CIRCULATIONAHA.105.169404
• ¹²
  Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12:189-198. https://www.ncbi.nlm.nih.gov/pmc/issues/28678\4/
  » https://www.ncbi.nlm.nih.gov/pmc/issues/28678\4
• ¹³
  Rodriguez S, Gaunt TR, Day IN. Hardy-Weinberg Equilibrium Testing of Biological Ascertainment for Mendelian Randomization Studies. Am J Epidemiol. 2009; 169(4):505-14. doi: 10.1093/aje/kwn359
  » https://doi.org/10.1093/aje/kwn359
• ¹⁴
  Freitas PHB, Pinto JAF, Sousa PHA, Enes CL, Machado RM. Metabolic syndrome in patients with refractory schizophrenia: sociodemographic and clinical characteristics. R Enferm Cent O Min. 2016; 1(6):1976-93. doi: http://dx.doi.org/10.19175/recom.v0i0.1179
  » https://doi.org/10.19175/recom.v0i0.1179
• ¹⁵
  Yu W, De Hert M, Moons T, Claes SJ, Correll CU, Van Winkel R. et al. CNR1 gene and risk of the metabolic syndrome in patients with schizophrenia. J Clin Psychopharmacol. 2013; 33(2):186-92. doi: 10.1097/JCP.0b013e318283925e
  » https://doi.org/10.1097/JCP.0b013e318283925e
• ¹⁶
  Papanastasiou E. The prevalence and mechanisms of metabolic syndrome in schizophrenia: a review. Ther Adv Psychopharmacol. 2013; 3(1): 33-51. doi: 10.1177/2045125312464385
  » https://doi.org/10.1177/2045125312464385
• ¹⁷
  Misawa F, Shimizu K, Fujii Y, Miyata R, Koshiishi F, Kobayashi M, et al. Is antipsychotic polypharmacy associated with metabolic syndrome even after adjustment for lifestyle effects?: a cross-sectional study. BMC Psychiatry. 2011; 11(1):118-23. doi: 10.1186/1471-244X-11-118
  » https://doi.org/10.1186/1471-244X-11-118
• ¹⁸
  Cordeiro Q, Siqueira-Roberto J, Zung S, Vallada H. Association between the DRD2-141C Insertion/Deletion Polymorphism and Schizophrenia. Arq Neuropsiquiatr. 2009; 67(2):191-194. doi: http://dx.doi.org/10.1590/S0004-282X2009000200004
  » https://doi.org/10.1590/S0004-282X2009000200004
• ¹⁹
  Xiao L, Shen T, Peng DH, Shu C, Jiang KD, Wang GH. Functional -141C Ins/Del polymorphism in the dopamine D2 receptor gene promoter and schizophrenia in a Chinese Han population. J Int Med Res. 2013; 41(4):1171-8. doi: 10.1177/0300060513483415
  » https://doi.org/10.1177/0300060513483415
• ²⁰
  Lencz T, Robinson DG, Napolitano B, Sevy S, Kane JM, Goldman D, et al. DRD2 promoter region variation predicts antipsychotic induced weight gain in first episode schizophrenia. Pharmacogen Genom. 2010; 20(9):569-72. doi: 10.1097/FPC.0b013e32833ca24b
  » https://doi.org/10.1097/FPC.0b013e32833ca24b
• ²¹
  Zhai D, Robinson DG, Schooler NR, Brunette MF, Mueser KT, Rosenheck RA, et al. Cardiometabolic risk in first-episode schizophrenia (FES) patients with the earliest stages of both illness and antipsychotic treatment. Schizophr Res. 2016; 71(12):1350-63. doi: 10.1001/jamapsychiatry.2014.1314
  » https://doi.org/10.1001/jamapsychiatry.2014.1314
• ²²
  Bartlett J, Predazzi IM, Williams SM, Bush WS, Kim Y, Havas S, et al. Is isolated low high-density lipoprotein cholesterol a cardiovascular disease risk factor? New insights from the Framingham Offspring Study. Circ Cardiovasc Qual Outcomes. 2016; 9(3):206-12. doi:10.1161/circoutcomes.115.002436
  » https://doi.org/10.1161/circoutcomes.115.002436
• ²³
  Banach M, Rysz J, Rizzo M, Otvos J, Toth PP, Pencina MJ, et al. Investigating dysfunctional HDL in selected groups of patients at high risk of cardiovascular events (DYS-HDL study): Protocol and organization. Atherosclerosis. 2014; 235(2):e171-e172. doi: 10.1016/j.atherosclerosis.2014.05.496
  » https://doi.org/10.1016/j.atherosclerosis.2014.05.496
• ²⁴
  Goughari AS, Mazhari S, Pourrahimi AM, Sadeghi MM, Nakhaee N. Associations between components of metabolic syndrome and cognition in patients with schizophrenia. J Psychiatr Pract. 2015; 21(3):190-7. doi: 10.1097/PRA.0000000000000065
  » https://doi.org/10.1097/PRA.0000000000000065

Publication Dates

• Publication in this collection
  2018

History

• Received
  12 May 2017
• Accepted
  03 Nov 2017