Association between Insertion-Deletion Polymorphism of the Angiotensin-Converting Enzyme Gene and Treatment Response to Antipsychotic Medications: A Study of Antipsychotic-Naïve First-Episode Psychosis Patients and Nonadherent Chronic Psychosis Patients
by
, ,
Sergej Nadalin
1,2, 
Sanja Dević Pavlić
3,
Vjekoslav Peitl
2,4,
Dalibor Karlović
2,4,
Lena Zatković
5,
Smiljana Ristić
3,
Alena Buretić-Tomljanović
3 and
Hrvoje Jakovac
6,* 1
Department of Psychiatry, General Hospital “Dr. Josip Benčević”, 35000 Slavonski Brod, Croatia
2
School of Medicine, Catholic University of Croatia, 10000 Zagreb, Croatia
3
Department of Medical Biology and Genetics, Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia
4
Department of Psychiatry, Sestre Milosrdnice University Hospital Center, 10000 Zagreb, Croatia
5
Hospital Pharmacy, Clinical Hospital Center Rijeka, 51000 Rijeka, Croatia
6
Department of Physiology, Immunology and Pathophysiology, Faculty of Medicine, University of Rijeka, 51000 Rijeka, Croatia
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(20), 12180; https://doi.org/10.3390/ijms232012180
Submission received: 26 September 2022
/
Revised: 9 October 2022
/
Accepted: 10 October 2022
/
Published: 12 October 2022
(This article belongs to the Collection Feature Papers in Molecular Neurobiology)
Abstract
We investigated whether a functional insertion/deletion (I/D) polymorphism of angiotensin-converting enzyme (ACE) influenced antipsychotic treatment. At baseline, and after 8 weeks of treatment with various antipsychotic medications, we assessed patients’ Positive and Negative Syndrome Scale (PANSS) scores, PANSS factors, and metabolic-syndrome-related parameters (fasting plasma lipid and glucose levels, and body mass index). A total of 186 antipsychotic-naïve first-episode psychosis patients or nonadherent chronic psychosis individuals (99 males and 87 females) were genotyped by polymerase chain reaction analysis. The ACE-I/D polymorphism was significantly associated with changes in PANSS psychopathology only (p < 0.05). Compared to ACE-II homozygous males, ACE-DD homozygous and ACE-ID heterozygous males manifested significantly greater decreases in PANSS positive score, PANSS excitement factor, and PANSS cognitive factor. ACE-DD homozygous females manifested higher decreases in PANSS depression factor compared to ACE-II homozygous and ACE-ID heterozygous females. The polymorphism’s effect size was estimated as moderate to strong, while its contribution to the PANSS psychopathology ranged from ~5.4 to 8.7%, with the lowest contribution observed for PANSS positive score changes and the highest for PANSS depressive factor changes. Our results indicate that ACE-I/D polymorphism had a statistically significant but weak gender-specific impact on psychopathology data, and showed no association between ACE-I/D polymorphism and metabolic-syndrome-related parameters.
1. Introduction
Angiotensin-converting enzyme (ACE) catalyzes the conversion of angiotensin I to angiotensin II in the renin–angiotensin system, and inactivates bradykinin via the kinin–kallikrein system [1,2]. A functional 287-base-pair ACE-insertion/deletion (I/D) polymorphism is the most well-studied genetic alteration that influences ACE expression in humans. ACE-DD homozygous individuals exhibit the highest ACE plasma activity, ACE-II homozygous individuals show the lowest activity, and those who are ACE-ID heterozygous exhibit intermediate activity [3,4]. ACE and angiotensin II have been suggested to play important roles in brain dopaminergic neurotransmission [5,6,7]; therefore, the ACE-I/D polymorphism has been investigated in schizophrenia etiology and clinical expression, as assessed using the Positive and Negative Syndrome Scale (PANSS) [4,8,9,10,11,12,13].
We previously investigated whether the ACE-I/D polymorphism might influence schizophrenia risk and severity of PANSS psychopathology among chronic patients taking antipsychotic medication, from the Croatian population [8]. While we did not find evidence that the ACE-I/D polymorphism was associated with elevated schizophrenia risk, we did observe several significant associations between the ACE-I/D polymorphism and PANSS scores. Specifically, we found that patients carrying the D allele (ACE-DD homozygous and ACE-ID heterozygous) manifested higher negative and general psychopathology PANSS scores, compared to patients who were ACE-II homozygous. Additionally, after adjustment for sex, we found that the presence of the D allele in the ACE genotype contributed to increased general PANSS scores among males with schizophrenia.
We also investigated whether ACE-I/D polymorphism might influence plasma lipid and glucose levels among schizophrenia patients receiving antipsychotic treatment [14]. Schizophrenia patients (specifically those taking antipsychotic medication) are more likely to exhibit weight gain, lipid disturbance, and glucose dysregulation, which makes them an interesting group in which to study the genetic basis of dyslipidemia and diabetes [15,16]. Furthermore, among individuals from the general population, ACE-I/D polymorphism has been extensively linked to dyslipidemia, diabetes, and metabolic syndrome [17,18,19,20]. We found that the ACE-I/D polymorphism had an intriguing gender-specific effect on the investigated metabolic parameters. Specifically, we found that ACE-ID heterozygous females exhibited significantly higher glucose levels compared to ACE-DD homozygous and ACE-II homozygous females. On the other hand, males carrying the D allele (ACE-DD homozygous and ACE-ID heterozygous) tended to show elevated triglyceride levels compared to ACE-II homozygous males. To our knowledge, no other published study has addressed the potential association between ACE-I/D polymorphism and metabolic-syndrome-related parameters among schizophrenia patients.
Only sparse data are available regarding the potential association between ACE-I/D polymorphism and antipsychotic treatment. In one study among antipsychotic-naïve first-episode psychosis patients from the Brazilian population, researchers investigated whether ACE-I/D polymorphism-associated changes in plasma ACE activity upon treatment with the antipsychotic risperidone might influence symptom improvement, as measured by total PANSS scores [4]. Indeed, that group had previously reported increased ACE activity in chronic schizophrenia patients compared to healthy controls, and suggested the potential of using combined ACE genotype and activity for predicting schizophrenia [10]. Their current findings indicate that risperidone treatment significantly increased the ACE activity among ACE-DD homozygous patients, while only a trend of increased ACE activity was observed among ACE-ID heterozygous and ACE-II homozygous individuals. However, their study demonstrated no significant correlation between increases of ACE activity and symptom improvement [4].
Available data indicate that antipsychotic treatment increases ACE activity [4], and our previous work suggests the potential relevance of ACE-I/D polymorphism in the severity of PANSS psychopathology and metabolic-syndrome-related parameters, among chronic schizophrenia patients taking antipsychotic medication [8,14]. Therefore, in the present study we hypothesized that ACE-I/D polymorphism might influence antipsychotic treatment-related changes in PANSS psychopathology, plasma lipid and glucose levels, and BMI values. Many findings indicate that determining PANSS factors provides a more robust understanding of the structure of schizophrenia symptom change upon antipsychotic treatment [21,22]. Accordingly, here we assessed PANSS psychopathology by determining PANSS scores plus PANSS factors. Based on our previous observation of gender-specific differences in the effects of ACE-I/D polymorphism in schizophrenia [8,14,23]—and similar findings in other diseases/conditions, such as multiple sclerosis [24] and lung cancer [25]—we performed separate analyses for male and female patients. This is the first study to investigate the association of ACE-I/D polymorphism with metabolic-syndrome-related parameters upon antipsychotic treatment. Our sample comprised antipsychotic-naïve first-episode psychosis patients and nonadherent chronic psychosis patients who were treated for 8 weeks with various, mainly atypical, antipsychotic medications.
2. Results
Males and females significantly differed in age, age of onset, plasma total cholesterol, HDL cholesterol, triglyceride levels, and BMI values (Table 1). Specifically, compared to females, males exhibited lower age, earlier onset, lower HDL cholesterol levels, higher total cholesterol, higher triglycerides, and higher BMI values (p < 0.01 and p < 0.05). For both genders, total cholesterol, LDL cholesterol, HDL cholesterol, triglyceride, and glucose levels were within the reference range [26]. Females had BMI values within the normal range, while males were slightly in the overweight range [27,28].
The allele and genotype frequencies of the ACE-I/D polymorphism were similar to those reported previously [8,14,23], and did not significantly deviate from that reported in the overall European population [29]. The ACE genotype distributions among males and females were consistent with Hardy–Weinberg equilibrium, and the genotype and allele distributions did not significantly differ between genders (Table 2).
The ACE-I/D polymorphism was significantly associated with changes in PANSS psychopathology only (Table 3). Specifically, compared to ACE-II homozygous males, males positive for the ACE-D allele (ACE-DD homozygous and ACE-ID heterozygous) exhibited significantly greater decreases in PANSS positive score (−8.7 ± 9.5 vs. −1.0 ± 12.4, z = −1.96, p = 0.049, Cohen’s d = 0.78), PANSS excitement factor (−4.3 ± 2.7 vs. −2.0 ± 1.8, z = −2.62, p = 0.007, Cohen’s d = 0.89), and PANSS cognitive factor (−2.0 ± 1.6 vs. −0.9 ± 1.4, z = −2.21, p = 0.030, Cohen’s d = 0.70). On the other hand, ACE-DD homozygous females exhibited greater decreases in PANSS depression factor compared to ACE-II homozygous and ACE-ID heterozygous females: −8.4 ± 2.8 vs. −6.6 ± 2.8, z = −2.53, p = 0.010, Cohen’s d = 0.64.
Among males, the ACE-D allele significantly predicted changes in PANSS positive symptom score (β = −0.23, p = 0.035), and PANSS excitement factor (β = −0.26, p = 0.017). Among females, the ACE-I allele appeared as a significant predictor of changes in PANSS depression factor (β = 0.30, p = 0.008) (Table 4). In males, changes in PANSS cognitive factor were significantly predicted by the number of psychotic episodes only (β = 0.25, p = 0.023). Compared to ACE-II homozygous males, among ACE-DD homozygous and ACE-ID heterozygous males, negative β values for PANSS positive symptom score and PANSS excitement factor indicated higher decreases of these variables. Compared to ACE-II homozygous and ACE-ID heterozygous females, among ACE-DD homozygous females, positive β values for PANSS depression factor indicated greater decreases of this variable. The contribution of ACE-I/D polymorphism to PANSS psychopathology ranged from ~5.4% to 8.7%, with the lowest contribution observed for PANSS positive score changes (R2 change = 0.054) and the highest for PANSS depressive factor changes (R2 change = 0.087) (Table 4).
3. Discussion
The primary finding of the current study is that ACE-I/D polymorphism influence on changes in PANSS psychopathology upon antipsychotic treatment. We found no association between ACE-I/D polymorphism and metabolic-syndrome-related parameters in male or female patients. Specifically, our results suggest that compared to ACE-II homozygous males, males positive for the ACE-D allele (ACE-DD homozygous and ACE-ID heterozygous) exhibit greater improvement in PANSS positive symptom score and PANSS excitement factor. On the other hand, ACE-DD homozygous females exhibited greater improvement in PANSS depression factor, compared to females positive for the ACE-I allele (ACE-II homozygous and ACE-ID heterozygous) (Table 3 and Table 4). Although the contribution of ACE-I/D polymorphism to PANSS psychopathology was weak (~5.4% to 8.7%), the Cohen’s d values indicated that the polymorphism had moderate-to-strong effect sizes (0.64 to 0.89).
Our current findings indicate that the ACE-D allele had a protective effect towards the improvement of clinical psychopathology upon antipsychotic treatment. In contrast, our previous findings among chronic schizophrenia patients under antipsychotic treatment suggested that patients positive for the ACE-D allele (ACE-DD homozygous and ACE-ID heterozygous) exhibited greater severity of PANSS psychopathology compared to ACE-II homozygous patients [8]. Moreover, our current findings indicated no association between ACE-I/D polymorphism and changes in metabolic-syndrome-related parameters upon antipsychotic treatment (Table 3). In contrast, our previous data suggest that ACE-I/D polymorphism might influence plasma glucose and lipid levels among chronic patients under antipsychotic treatment [14]. Importantly, in our previous work, PANSS psychopathology and metabolic-syndrome-related parameters were assessed at a single point, during hospital admission due to clinical deterioration, and we did not consider whether patients were adherent to antipsychotic medications. Additionally, in our previous work, when assessing PANSS psychopathology, we only determined PANSS scores, while PANSS scores and PANSS factors were also considered in the current study [8,14]. The favorable effect of the ACE-DD homozygous genotype on PANSS depression factor upon antipsychotic treatment, which was observed among female patients in the current study, might be explained by data previously reported by Nani et al. [4], indicating that risperidone treatment increases ACE activity, mainly among ACE-DD homozygous individuals (Table 3 and Table 4). In this context, the presence of ACE-DD homozygous genotypes may have contributed to the improvements of PANSS positive symptom score and PANSS factor upon antipsychotic treatment among males positive for the ACE-D allele. Intriguingly, Nani et al. [4] reported that ACE-I/D polymorphism-associated increases in plasma ACE activity were not correlated with symptom improvement in their study. Therefore, other yet-undefined factors may affect the relationship between ACE-I/D polymorphism and response to antipsychotic treatment. For instance, noncanonical ACE substrates, such as substance P and neurotensin, have been shown to play important roles in dopaminergic neurotransmission and response to antipsychotic treatment [30,31,32,33].
Several findings may explain the gender-specific differences in ACE-I/D polymorphism observed in the current study [34,35,36,37,38]. Estrogen replacement therapy has been associated with genotype-associated changes in ACE activity among postmenopausal women [34,35]. One study showed significantly reduced plasma ACE activity in women with the ACE-ID and ACE-II genotypes [34], and another study showed ACE reductions in women with the ACE-ID and ACE-DD genotypes [35]. Furthermore, estrogen reportedly exerts favorable effects on brain dopaminergic neurotransmission: estrogen increases dopamine synthesis; decreases dopamine degradation, reuptake, and recapture; and upregulates dopaminergic receptors [36,37,38].
Our results suggest that compared to PANSS scores, PANSS factors indicate more subtle changes in PANSS psychopathology upon antipsychotic treatment (Table 3 and Table 4). This finding is consistent with previous reports that the determination of PANSS factors may enable more sensitive assessment of how gene polymorphisms affect therapeutic outcomes among psychotic patients [39,40]. Indeed, it has been established that a change in PANSS factor structure does not necessarily indicate a flaw in the PANSS scores [21,22]. Moreover, the PANSS factor structure might also reflect latent dimensions of psychosis and/or other mental illnesses [22,41].
We speculate that ACE-I/D polymorphism, by affecting ACE activity, might directly influence dopamine homeostasis and contribute to changes in PANSS psychopathology without peripheral metabolic changes. Interestingly, many studies indicate that polymorphisms of the genes encoding dopamine and other neurotransmitter receptors are frequently associated with metabolic changes, regardless of antipsychotic treatment [42,43]. Accordingly, we further speculate that altered ACE activity might affect neuronal signaling, even without changes in the neurotransmitter–receptor axis [44,45].
The limitations of our study include the relatively small sample, which leaves open the possibility that some effects were not detected. Additionally, nonadherence to antipsychotic medications was assessed via anamnestic information, and we only assessed a single polymorphism of the ACE gene. Furthermore, in contrast to the previous study assessing the role of ACE-I/D polymorphism in response to risperidone [4], our study comprised patients who were rather heterogeneous regarding antipsychotic medications. Nevertheless, the use of various antipsychotic medications has been shown to affect ACE activity, and there is evidence of both increased ACE activity [46,47] and decreased ACE activity [48] among patients treated with these medications.
In conclusion, the current data indicate that ACE-I/D polymorphism had a statistically significant but weak gender-specific impact on changes of PANSS psychopathology data upon antipsychotic treatment. We also found no association between ACE-I/D polymorphism and metabolic-syndrome-related parameters in male or female patients.
4. Materials and Methods
We recruited a total of 186 antipsychotic-naïve first-episode psychosis patients or nonadherent chronic psychosis individuals. All participants were Croatian citizens, who were treated at the Department of Psychiatry in the University Hospital Center Sestre Milosrdnice, Zagreb between 2016 and 2021. Each patient gave written informed consent. This study was approved by the appropriate Ethics Committee, and was conducted in accordance with the ethical standards expressed in the latest version of the Declaration of Helsinki. Diagnoses were assessed by at least two psychiatrists, according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) criteria, using a structured clinical interview. Among the participants, 163 (87.7%) were diagnosed with schizophrenia, 9 (4.8%) with schizoaffective disorder, and 14 (7.5%) with psychotic disorder not otherwise specified.
Antipsychotic-naïve patients had never previously been treated with antipsychotic medications. Nonadherent chronic patients were—according to auto-anamnestic and hetero-anamnestic information—non-compliant with their antipsychotic medication usage, or had been off antipsychotic depot injections for at least 1 month. Both patient groups received one or more of the following medications for 8 weeks: clozapine (n = 84), risperidone (n = 45), aripiprazole (n = 45), paliperidone (n = 40), aripiprazole depo (n = 28), haloperidol (n = 28), fluphenazine (n = 14), and olanzapine (n = 13). When anxiolytic or hypnotic medications were not sufficiently effective, the antipsychotic promazine was also prescribed to many patients (n = 64), usually at smaller doses (75 to 150 mg per day). Antipsychotic-naïve first-episode patients and nonadherent chronic patients presented with similar PANSS psychopathology data, and did not significantly differ in most metabolic-syndrome-related parameters (p > 0.05). Therefore, we combined these two groups of participants for statistical analyses. Table 1 presents the patients’ characteristics at baseline according to gender.
Age at onset was defined as the patient’s age at their first hospital admission due to a psychotic episode, at which the diagnosis of schizophrenia was used. Evaluation of PANSS psychopathology at baseline was performed during a psychotic state of the illness requiring hospitalization. PANSS scales were divided into five symptom factors: positive (P1, P3, P6, and G9), negative (N2, N3, N4, N6, and G7), excitement (P4, P7, and G1), depression (G2, G3, and G6), and cognitive (G10 and G12) [49,50,51]. Fasting plasma total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, and glucose levels were measured using an Abbott Architect c8000 analyzer, at the Department of Clinical Chemistry in the University Hospital Center Sestre Milosrdnice, Zagreb. The following values were considered elevated: total cholesterol > 5.0 mmol/L, LDL > 3.0 mmol/L, triglycerides > 2.0 mmol/L, and glucose > 6.1 mmol/L, while HDL < 1.0 mmol/L was considered decreased [26]. BMI was calculated as weight (kg) divided by height squared (m2). Patients were classified as obese with BMI values > 30, or as non-obese if overweight (BMI: 25–30) or of normal body weight (BMI: 18.5–25) [27,28]. From whole blood samples, genomic DNA was extracted using the FlexiGene DNA kit 250 (QIAGEN GmbH, Hilden, Germany) according to the manufacturer’s instructions. Polymerase chain reaction-based genotyping was performed in the Department of Medical Biology and Genetics, in the Faculty of Medicine, University of Rijeka, using previously described protocols [3]. To exclude mistyping of ACE-ID heterozygotes as ACE-DD homozygotes, all ACE-DD genotypes were confirmed using insertion-specific PCR [52].
Statistical Analyses
Statistical analyses were conducted using Statistica for Windows, version 12 (StatSoft, Inc., Tulsa, OK, USA). To compare the characteristics of male and female patients, we used nonparametric Mann–Whitney U tests or chi-square (χ2) tests. We used Mann–Whitney U tests to examine associations between ACE-I/D polymorphism and changes in mean PANSS psychopathology data, plasma lipid and glucose levels, and BMI values after antipsychotic treatment. The Cohen’s d method was used to calculate the standardized effect size [53]. Associations that appeared significant (p < 0.05) were further examined by multiple regression analyses, with adjustment for age and number of psychotic episodes.
Author Contributions
S.N. conceived and designed the experiment, analyzed data, prepared the manuscript, and was responsible for funding acquisition; S.D.P. performed the experiment, analyzed data and prepared the manuscript; V.P. and D.K. recruited the patients, performed the medical examinations and prepared the manuscript; L.Z. performed the experiment; S.R. and A.B.-T. prepared the manuscript; H.J. prepared the manuscript and was responsible for funding acquisition. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by grants 17.07.2.1.10, uniri-biomed-18-251, and uniri-biomed-18-187 from the University of Rijeka, Croatia. The University had no further role in the study design; data collection, analysis, or interpretation; or the decision to submit this paper for publication.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of Clinical Hospital Center Rijeka, Rijeka (protocol code: 003-05/20-1/82, number: 2170-29-02/1-20-2, 13 July 2020), Ethics Committee of Medical Faculty, University of Rijeka, Rijeka (protocol code: 003-08/20-01/15, number: 2170-24-09-8-20-2, 26 June 2020), and Ethics Committee of Clinical Hospital Center Sestre Milosrdnice, Zagreb (protocol code: 003-06/20-03/013, number: 251-29-11-20-01-5, 4 June 2020).
Informed Consent Statement
Written informed consent has been obtained from the patients to publish this paper.
Data Availability Statement
The data presented in this study are available on request from the corresponding author if data sharing is approved by ethics committee. The data are not publicly available due to data protection laws and adherence to ethical principles.
Acknowledgments
We would like to thank Ivana Pleša for her excellent technical assistance.
Conflicts of Interest
The authors declare that they have no competing interest.
References
- Nawaz, S.K.; Hasnain, S. Pleiotropic effects of ACE polymorphism. Biochem. Med. 2008, 19, 36–49. [Google Scholar] [CrossRef]
- Riordan, J.F. Angiotensin-I-converting enzyme and its relatives. Genome Biol. 2003, 4, 225. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Rigat, B.; Hubert, C.; Alhenc-Gelas, F.; Cambien, F.; Corvol, P.; Soubrier, F. An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J. Clin. Investig. 1990, 86, 1343–1346. [Google Scholar] [CrossRef]
- Nani, J.V.; Dal Mas, C.; Yonamine, C.M.; Ota, V.K.; Noto, C.; Belangero, S.I.; Mari, J.J.; Bressan, R.; Cordeiro, Q.; Gadelha, A.; et al. A study in first-episode psychosis patients: Does angiotensin I-converting enzyme (ACE) activity associated with genotype predict symptoms severity reductions after treatment with the atypical antipsychotic risperidone? Int. J. Neuropsychopharmacol. 2020, 22, 721–730. [Google Scholar] [CrossRef]
- Jenkins, T.A.; Allen, A.M.; Chai, S.Y.; MacGregor, D.P.; Paxinos, G.; Mendelsohn, F.A. Interactions of angiotensin II with central dopamine. Adv. Exp. Med. Biol. 1996, 396, 93–103. [Google Scholar] [CrossRef]
- Jenkins, T.A.; Mendelsohn, F.A.; Chai, S.Y. Angiotensin-converting enzyme modulates dopamine turnover in the striatum. J. Neurochem. 1997, 68, 1304–1311. [Google Scholar] [CrossRef] [PubMed]
- Obata, T.; Takahashi, S.; Kashiwagi, Y.; Kubota, S. Protective effect of captopril and enalaprilat, angiotensin-converting enzyme inhibitors, on para-nonylphenol-induced OH generation and dopamine efflux in rat striatum. Toxicology 2008, 250, 96–99. [Google Scholar] [CrossRef] [PubMed]
- Nadalin, S.; Buretić-Tomljanović, A.; Rubeša, G.; Jonovska, S.; Tomljanović, D.; Ristić, S. Angiotensin-converting enzyme gene insertion/deletion polymorphism is not associated with schizophrenia in a Croatian population. Psychiatr. Genet. 2012, 22, 267–268. [Google Scholar] [CrossRef]
- Hui, L.; Wu, J.Q.; Zhang, X.; Lv, J.; Du, W.L.; Kou, C.G.; Yu, Y.Q.; Lv, M.H.; Chen, D.C.; Zhang, X.Y. Association between the angiotensin-converting enzyme gene insertion/deletion polymorphism and first-episode patients with schizophrenia in a Chinese Han population. Hum. Psychopharmacol. 2014, 29, 274–279. [Google Scholar] [CrossRef] [PubMed]
- Gadelha, A.; Yonamine, C.M.; Ota, V.K.; Oliveira, V.; Sato, J.R.; Belangero, S.I.; Bressan, R.A.; Hayashi, M.A. ACE I/D genotype-related increase in ACE plasma activity is a better predictor for schizophrenia diagnosis than the genotype alone. Schizophr. Res. 2015, 164, 109–114. [Google Scholar] [CrossRef] [PubMed]
- Hui, L.; Wu, J.Q.; Ye, M.J.; Zheng, K.; He, J.C.; Zhang, X.; Liu, J.H.; Tian, H.J.; Gong, B.H.; Chen, D.C.; et al. Association of angiotensin-converting enzyme gene polymorphism with schizophrenia and depressive symptom severity in a Chinese population. Hum. Psychopharmacol. 2015, 30, 100–107. [Google Scholar] [CrossRef] [PubMed]
- Mazaheri, H.; Saadat, M. Association between insertion/deletion polymorphism in angiotension converting enzyme and susceptibility to schizophrenia. Iran. J. Public Health 2015, 44, 369–373. [Google Scholar] [PubMed]
- Song, G.G.; Lee, Y.H. The insertion/deletion polymorphism in the angiotensin-converting enzyme and susceptibility to schizophrenia or Parkinson’s disease: A meta-analysis. J. Renin-Angiotensin-Aldosterone Syst. 2015, 16, 434–442. [Google Scholar] [CrossRef] [PubMed]
- Nadalin, S.; Buretić-Tomljanović, A.; Ristić, S.; Jonovska, S.; Tomljanović, D. The impact of ACE gene I/D polymorphism on plasma glucose and lipid concentrations in schizophrenia patients. Psychiatry Res. 2015, 227, 71–72. [Google Scholar] [CrossRef] [PubMed]
- Carli, M.; Kolachalam, S.; Longoni, B.; Pintaudi, A.; Baldini, M.; Aringhieri, S.; Fasciani, I.; Annibale, P.; Maggio, R.; Scarselli, M. Atypical Antipsychotics and Metabolic Syndrome: From Molecular Mechanisms to Clinical Differences. Pharmaceuticals 2021, 14, 238. [Google Scholar] [CrossRef]
- Goh, K.K.; Chen, C.Y.; Wu, T.H.; Chen, C.H.; Lu, M.L. Crosstalk between schizophrenia and metabolic syndrome: The role of oxytocinergic dysfunction. Int. J. Mol. Sci. 2022, 23, 7092. [Google Scholar] [CrossRef]
- Alvarez-Aguilar, C.; Enríquez-Ramírez, M.L.; Figueroa-Nuñez, B.; Gómez-García, A.; Rodríguez-Ayala, E.; Morán-Moguel, C.; Farias-Rodriguez, V.M.; Mino-Leon, D.; Lopez-Meza, J.E. Association between angiotensin-1 converting enzyme gene polymorphism and the metabolic syndrome in a Mexican population. Exp. Mol. Med. 2007, 39, 327–334. [Google Scholar] [CrossRef]
- Niu, W.; Qi, Y.; Gao, P.; Zhu, D. Angiotensin converting enzyme D allele is associated with an increased risk of type 2 diabetes: Evidence from a meta-analysis. Endocr. J. 2010, 57, 431–438. [Google Scholar] [CrossRef]
- Mittal, G.; Gupta, V.; Haque, S.F.; Khan, A.S. Effect of angiotensin converting enzyme gene I/D polymorphism in patients with metabolic syndrome in North Indian population. Chin. Med. J. 2011, 124, 45–48. [Google Scholar]
- Zhong, W.; Jiang, Z.; Zhou, T.B. Association between the ACE I/D gene polymorphism and T2DN susceptibility: The risk of T2DM developing into T2DN in the Asian population. J. Renin-Angiotensin-Aldosterone Syst. 2015, 16, NP35. [Google Scholar] [CrossRef]
- Herrera-Estrella, M.; Apiquian, R.; Fresan, A.; Sanchez-Torres, I. The effects of amisulpride on five dimensions of psychopathology in patients with schizophrenia: A prospective open-label study. BMC Psychiatry 2005, 5, 22. [Google Scholar] [CrossRef] [PubMed]
- Anderson, A.; Wilcox, M.; Savitz, A.; Chung, H.; Li, Q.; Salvadore, G.; Wang, D.; Nuamah, I.; Riese, S.P.; Bilder, R.M. Sparse factors for the positive and negative syndrome scale: Which symptoms and stage of illness? Psychiatry Res. 2015, 225, 283–290. [Google Scholar] [CrossRef] [PubMed]
- Nadalin, S.; Ristić, S.; Rebić, J.; Šendula Jengić, V.; Kapović, M.; Buretić-Tomljanović, A. The insertion/deletion polymorphism in the angiotensin-converting enzyme gene and nicotine dependence in schizophrenia patients. J. Neural Transm. 2017, 124, 511–518. [Google Scholar] [CrossRef] [PubMed]
- Ristić, S.; Lovrecić, L.; Starcević-Cizmarević, N.; Brajenović-Milić, B.; Jazbec, S.S.; Barac-Latas, V.; Vejnović, D.; Sepcić, J.; Kapović, M.; Peterlin, B. No association of CCR5D32 gene mutation with multiple sclerosis in Croatian and Slovenian patients. Mult. Scler. 2006, 12, 360–362. [Google Scholar] [CrossRef] [PubMed]
- Nadalin, S.; Flego, V.; Pavlić, S.D.; Volarić, D.; Radojčić Badovinac, A.; Kapović, M.; Ristić, S. Association between the ACE-I/D polymorphism and nicotine dependence amongst patients with lung cancer. Biomed. Rep. 2020, 13, 58. [Google Scholar] [CrossRef] [PubMed]
- Bergovec, M.; Reiner, Z.; Milicić, D.; Vrazić, H. Differences in risk factors for coronary heart disease in patients from continental and Mediterranean regions of Croatia. Wien Klin. Wochenschr. 2008, 120, 684–692. [Google Scholar] [CrossRef] [PubMed]
- Fister, K.; Vuletić, S.; Kern, J. Paving the way for personalised behaviourally based prevention of obesity: Systematic search of the literature. Coll. Antropol. 2012, 36, 201–210. [Google Scholar] [CrossRef][Green Version]
- Milanović, S.M.; Ivanković, D.; Uhernik, A.I.; Fister, K.; Peternel, R.; Vuletić, S. Obesity-new threat to Croatian longevity. Coll. Antropol. 2012, 36, 113–116. [Google Scholar]
- National Library of Medicine. Available online: http://www.ncbi.nlm.nih.gov/snp/?term=rs1799752 (accessed on 14 August 2022).
- Nagamine, T. Serum substance P levels in patients with chronic schizophrenia treated with typical or atypical antipsychotics. Neuropsychiatr. Dis. Treat. 2008, 4, 289–294. [Google Scholar] [CrossRef]
- Fawaz, C.S.; Martel, P.; Leo, D.; Trudeau, L.E. Presynaptic action of neurotensin on dopamine release through inhibition of D2 receptor function. BMC Neurosci. 2009, 10, 96. [Google Scholar] [CrossRef]
- Servonnet, A.; Minogianis, E.A.; Bouchard, C.; Bédard, A.M.; Lévesque, D.; Rompré, P.P.; Samaha, A.N. Neurotensin in the nucleus accumbens reverses dopamine supersensitivity evoked by antipsychotic treatment. Neuropharmacology 2017, 123, 10–21. [Google Scholar] [CrossRef] [PubMed]
- Heath, E.; Chieng, B.; Christie, M.J.; Balleine, B.W. Substance P and dopamine interact to modulate the distribution of delta-opioid receptors on cholinergic interneurons in the striatum. Eur. J. Neurosci. 2018, 47, 1159–1173. [Google Scholar] [CrossRef] [PubMed]
- Sanada, M.; Higashi, Y.; Nakagawa, K.; Sasaki, S.; Kodama, I.; Tsuda, M.; Nagai, N.; Ohama, K. Relationship between the angiotensin-converting enzyme genotype and the forearm vasodilator response to estrogen replacement therapy in postmenopausal women. J. Am. Coll. Cardiol. 2001, 37, 1529–1535. [Google Scholar] [CrossRef]
- Sumino, H.; Ichikawa, S.; Ohyama, Y.; Nakamura, T.; Kanda, T.; Sakamoto, H.; Sakamaki, T.; Mizunuma, H.; Kurabayashi, M. Effects of hormone replacement therapy on serum angiotensin-converting enzyme activity and plasma bradykinin in postmenopausal women according to angiotensin-converting enzyme-genotype. Hypertens. Res. 2003, 26, 53–58. [Google Scholar] [CrossRef]
- Jacobs, E.; D’Esposito, M. Estrogen shapes dopamine-dependent cognitive processes: Implications for women’s health. J. Neurosci. 2011, 31, 5286–5293. [Google Scholar] [CrossRef] [PubMed]
- Barth, C.; Villringer, A.; Sacher, J. Sex hormones affect neurotransmitters and shape the adult female brain during hormonal transition periods. Front. Neurosci. 2015, 9, 37. [Google Scholar] [CrossRef] [PubMed]
- Del Río, J.P.; Alliende, M.I.; Molina, N.; Serrano, F.G.; Molina, S.; Vigil, P. Steroid hormones and their action in women’s brains: The importance of hormonal balance. Front. Public Health. 2018, 6, 141. [Google Scholar] [CrossRef]
- van der Gaag, M.; Hoffman, T.; Remijsen, M.; Hijman, R.; de Haan, L.; van Meijel, B.; van Harten, P.N.; Valmaggia, L.; de Hert, M.; Cuijpers, A.; et al. The five-factor model of the Positive and Negative Syndrome Scale II: A ten-fold cross-validation of a revised model. Schizophr. Res. 2006, 85, 280–287. [Google Scholar] [CrossRef]
- Giesbrecht, C.J.; O’Rourke, N.; Leonova, O.; Strehlau, V.; Paquet, K.; Vila-Rodriguez, F.; Panenka, W.J.; MacEwan, G.W.; Smith, G.N.; Thornton, A.E.; et al. The positive and negative syndrome scale (PANSS): A three-factor model of psychopathology in marginally housed persons with substance dependence and psychiatric illness. PLoS ONE 2016, 11, e0151648. [Google Scholar] [CrossRef][Green Version]
- Cuthbert, B.N.; Insel, T.R. Toward the future of psychiatric diagnosis: The seven pillars of RDoC. BMC Med. 2013, 11, 126. [Google Scholar] [CrossRef]
- Postolache, T.T.; Del Bosque-Plata, L.; Jabbour, S.; Vergare, M.; Wu, R.; Gragnoli, C. Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 2019, 180, 186–203. [Google Scholar] [CrossRef]
- Paderina, D.Z.; Boiko, A.S.; Pozhidaev, I.V.; Mednova, I.A.; Goncharova, A.A.; Bocharova, A.V.; Fedorenko, O.Y.; Kornetova, E.G.; Semke, A.V.; Bokhan, N.A.; et al. The Gender-Specific Association of DRD2 Polymorphism with Metabolic Syndrome in Patients with Schizophrenia. Genes. 2022, 13, 1312. [Google Scholar] [CrossRef] [PubMed]
- Wincewicz, D.; Braszko, J.J. Validation of brain angiotensin system blockade as a novel drug target in pharmacological treatment of neuropsychiatric disorders. Pharmacopsychiatry 2017, 50, 233–247. [Google Scholar] [CrossRef] [PubMed]
- Trieu, B.H.; Remmers, B.C.; Toddes, C.; Brandner, D.D.; Lefevre, E.M.; Kocharian, A.; Retzlaff, C.L.; Dick, R.M.; Mashal, M.A.; Gauthier, E.A.; et al. Angiotensin-converting enzyme gates brain circuit-specific plasticity via an endogenous opioid. Science 2022, 375, 1177–1182. [Google Scholar] [CrossRef] [PubMed]
- Wahlbeck, K.; Ahokas, A.; Miettinen, K.; Nikkilä, H.; Rimón, R. Higher cerebrospinal fluid angiotensin-converting enzyme levels in neuroleptic-treated than in drug-free patients with schizophrenia. Schizophr. Bull. 1998, 24, 391–397. [Google Scholar] [CrossRef] [PubMed]
- Wahlbeck, K.; Rimón, R.; Fyhrquist, F. Elevated angiotensin-converting enzyme (kininase II) in the cerebrospinal fluid of neuroleptic-treated schizophrenic patients. Schizophr. Res. 1993, 9, 77–82. [Google Scholar] [CrossRef]
- Beckmann, H.; Saavedra, J.M.; Gattaz, W.F. Low angiotensin-converting enzyme activity (kininase II) in cerebrospinal fluid of schizophrenics. Biol. Psychiatry 1984, 19, 679–684. [Google Scholar] [PubMed]
- Wallwork, R.S.; Fortgang, R.; Hashimoto, R.; Weinberger, D.R.; Dickinson, D. Searching for a consensus five-factor model of the Positive and Negative Syndrome Scale for schizophrenia. Schizophr. Res. 2012, 137, 246–250. [Google Scholar] [CrossRef]
- Jiang, J.; See, Y.M.; Subramaniam, M.; Lee, J. Investigation of cigarette smoking among male schizophrenia patients. PLoS ONE. 2013, 8, e71343. [Google Scholar] [CrossRef] [PubMed]
- Misiak, B.; Kiejna, A.; Frydecka, D. Assessment of cigarette smoking status with respect to symptomatic manifestation in first-episode schizophrenia patients. Compr. Psychiatry 2015, 58, 146–151. [Google Scholar] [CrossRef] [PubMed]
- Shanmugam, V.; Sell, K.W.; Saha, B.K. Mistyping ACE heterozygotes. PCR Methods Appl. 1993, 3, 120–121. [Google Scholar] [CrossRef] [PubMed]
- Computation of Effect Sizes. Available online: http://www.psychometrica.de/effect_size.html (accessed on 14 August 2022).
Table 1.
Patients’ characteristics at baseline.
| Males (N = 99) | Females (N = 87) | p | |
|---|---|---|---|
| Antipsychotic-naïve first-episode patients/nonadherent chronic patients | 41/58 | 26/61 | 0.102 |
| Age, years | 31.9 ± 11.7 | 41.6 ± 14.9 | <0.001 |
| Age of onset, years | 25.6 ± 8.3 | 32.1 ± 12.3 | <0.001 |
| Number of psychotic episodes | 2.7 ± 2.0 | 3.1 ± 2.0 | 0.131 |
| PANSS positive symptom score | 22.4 ± 6.4 | 22.0 ± 5.8 | 0.884 |
| PANSS negative symptom score | 26.6 ± 7.0 | 26.2 ± 8.0 | 0.674 |
| PANSS general psychopathology score | 50.8 ± 9.0 | 49.2 ± 8.7 | 0.238 |
| PANSS total symptom score | 99.8 ± 17.7 | 97.4 ± 18.4 | 0.434 |
| PANSS positive factor | 13.3 ± 4.1 | 12.9 ± 3.8 | 0.445 |
| PANSS negative factor | 19.0 ± 5.2 | 18.9 ± 6.3 | 0.833 |
| PANSS excitement factor | 8.4 ± 2.7 | 8.2 ± 2.7 | 0.645 |
| PANSS depression factor | 9.6 ± 2.7 | 9.1 ± 3.0 | 0.260 |
| PANSS cognitive factor | 5.9 ± 1.8 | 5.8 ± 2.1 | 0.731 |
| Total cholesterol, mmol/L | 4.6 ± 1.0 | 4.9 ± 1.1 | 0.032 |
| LDL cholesterol, mmol/L | 2.7 ± 0.8 | 3.0 ± 1.0 | 0.091 |
| HDL cholesterol, mmol/L | 1.1 ± 0.3 | 1.3 ± 0.4 | <0.001 |
| Triglycerides, mmoL/L | 1.5 ± 1.1 | 1.2 ± 0.5 | 0.024 |
| Glucose, mmol/L | 5.6 ± 1.6 | 5.5 ± 1.0 | 0.878 |
| Body mass index, kg/m2 | 25.6 ± 4.7 | 23.8 ± 4.2 | 0.011 |
Differences were compared using the Mann–Whitney U test, with the exception of antipsychotic-naïve first-episode patients/nonadherent chronic patients ratio (χ2 test). PANSS indicates Positive and Negative Syndrome Scale.
Table 2.
The frequency of ACE genotypes and alleles among male and female patients.
| Genotypes (%) | Alleles (%) | ||||
|---|---|---|---|---|---|
| DD | ID | II | D | I | |
| Males (N = 99) a | 28 (28.3) | 57 (57.6) | 14 (14.1) | 113 (57.1) | 83 (42.9) |
| Females (N = 87) b | 26 (30.2) | 50 (57.0) | 11 (12.8) | 102 (58.6) | 72 (41.4) |
| χ2 = 0.12, df = 2, p = 0.942 | χ2 = 0.04, df = 1, p = 0.851 | ||||
a Hardy–Weinberg: χ2 = 3.03, p = 0.082; b Hardy–Weinberg: χ2 = 2.97, p = 0.085.
Table 3.
PANSS psychopathology data and metabolic-syndrome-related parameters upon antipsychotic treatment according to ACE-I/D polymorphism.
Table 3.
PANSS psychopathology data and metabolic-syndrome-related parameters upon antipsychotic treatment according to ACE-I/D polymorphism.
| Males (N = 99) | Mean ± SD | z | p | Females (N = 87) | Mean ± SD | z | p | |
|---|---|---|---|---|---|---|---|---|
| PANSS positive symptom score | DD, ID II | −8.6 ± 9.5 −1.0 ± 12.4 | −1.96 | 0.049 | DD, ID II | −9.0 ± 8.9 −7.0 ± 7.5 | −1.11 | 0.270 |
| II, ID DD | −8.2 ± 9.4 −7.1 ± 11.5 | −0.18 | 0.858 | II, ID DD | −8.1 ± 9.8 −10.1 ± 5.5 | −0.68 | 0.502 | |
| PANSS negative symptom score | DD, ID II | −6.4 ± 9.5 −6.8 ± 11.0 | −0.17 | 0.864 | DD, ID II | −7.8 ± 8.3 −6.2 ± 11.7 | −0.09 | 0.926 |
| II, ID DD | −6.6 ± 9.1 −6.0 ± 10.8 | −0.11 | 0.909 | II, ID DD | −7.5 ± 9.8 −7.9 ± 5.6 | −0.21 | 0.837 | |
| PANSS general psychopathology score | DD, ID II | −13.5 ± 18.2 −9.4 ± 18.5 | −0.71 | 0.479 | DD, ID II | −14.9 ± 13.7 −8.3 ± 19.2 | −1.10 | 0.296 |
| II, ID DD | −12.5 ± 16.7 −14.5 ± 21.4 | 1.34 | 0.180 | II, ID DD | −12.9 ± 16.0 −16.6 ± 10.1 | −1.33 | 0.185 | |
| PANSS total symptom score | DD, ID II | −28.2 ± 4.7 −17.2 ± 34.1 | −1.19 | 0.235 | DD, ID II | −31.7 ± 28.3 −21.5 ± 37.4 | −0.89 | 0.376 |
| II, ID DD | −27.2 ± 31.9 −26.6 ± 40.5 | 0.30 | 0.765 | II, ID DD | −28.5 ± 33.2 −34.6 ± 18.8 | −1.14 | 0.255 | |
| PANSS positive factor | DD, ID II | −6.4 ± 3.3 −5.6 ± 6.6 | −0.24 | 0.810 | DD, ID II | −5.9 ± 3.9 −6.1 ± 3.5 | −0.24 | 0.813 |
| II, ID DD | −6.2 ± 4.0 −6.6 ± 3.3 | 0.30 | 0.767 | II, ID DD | −5.7 ± 3.9 −6.2 ± 3.8 | −0.86 | 0.391 | |
| PANSS negative factor | DD, ID II | −6.7 ± 4.2 −7.2 ± 5.9 | 0.24 | 0.810 | DD, ID II | −6.8 ± 5.7 −7.0 ± 4.7 | −0.03 | 0.971 |
| II, ID DD | −6.8 ± 4.4 −6.7 ± 4.5 | −0.20 | 0.837 | II, ID DD | −7.2 ± 5.8 −6.2 ± 5.0 | 0.25 | 0.797 | |
| PANSS excitement factor | DD, ID II | −4.3 ± 2.7 −2.0 ± 1.8 | −2.62 | 0.007 | DD, ID II | −3.7 ± 2.9 −2.5 ± 2.7 | −1.90 | 0.059 |
| II, ID DD | −4.1 ± 2.8 −3.9 ± 2.4 | 0.09 | 0.928 | II, ID DD | −3.5 ± 3.1 −3.7 ± 2.2 | −0.54 | 0.591 | |
| PANSS depression factor | DD, ID II | −8.0 ± 2.6 −7.6 ± 2.0 | −0.41 | 0.686 | DD, ID II | −7.3 ± 2.9 −6.3 ± 2.7 | −0.88 | 0.384 |
| II, ID DD | −7.6 ± 2.3 −8.6 ± 2.8 | 1.71 | 0.092 | II, ID DD | −6.6 ± 2.8 −8.4 ± 2.8 | −2.53 | 0.010 | |
| PANSS cognitive factor | DD, ID II | −2.0 ± 1.6 −0.9 ± 1.4 | −2.21 | 0.030 | DD, ID II | −1.7 ± 1.9 −1.0 ± 1.4 | −0.96 | 0.353 |
| II, ID DD | −1.7 ± 1.6 −2.2 ± 1.7 | 1.26 | 0.222 | II, ID DD | −1.7 ± 2.1 −1.5 ± 1.2 | 0.04 | 0.967 | |
| Total cholesterol, mmol/L | DD, ID II | 0.5 ± 0.8 0.0 ± 0.4 | 1.60 | 0.112 | DD, ID II | 0.4 ± 0.9 −0.0 ± 0.6 | 1.34 | 0.182 |
| II, ID DD | 0.4 ± 0.8 0.5 ± 0.7 | −0.91 | 0.367 | II, ID DD | 0.3 ± 0.9 0.5 ± 0.9 | 0.93 | 0.350 | |
| LDL cholesterol, mmol/L | DD, ID II | 0.3 ± 0.6 0.1 ± 0.2 | 0.93 | 0.354 | DD, ID II | 0.2 ± 0.7 0.1 ± 0.6 | 0.36 | 0.718 |
| II, ID DD | 0.3 ± 0.6 0.2 ± 0.6 | 0.59 | 0.558 | II, ID DD | 0.1 ± 0.6 0.3 ± 0.8 | 1.60 | 0.109 | |
| HDL cholesterol, mmol/L | DD, ID II | 0.1 ± 0.3 0.0 ± 0.3 | 0.40 | 0.687 | DD, ID II | 0.1 ± 0.3 0.0 ± 0.3 | 0.39 | 0.706 |
| II, ID DD | −0.0 ± 0.3 0.1 ± 0.3 | −1.23 | 0.219 | II, ID DD | 0.1 ± 0.3 0.1 ± 0.3 | 0.94 | 0.356 | |
| Triglycerides, mmoL/L | DD, ID II | 0.3 ± 1.0 0.1 ± 0.8 | 0.29 | 0.774 | DD, ID II | 0.4 ± 1.0 −0.1 ± 0.6 | 1.10 | 0.276 |
| II, ID DD | 0.2 ± 1.0 0.4 ± 0.8 | −1.40 | 0.161 | II, ID DD | 0.4 ± 1.2 0.2 ± 0.6 | −0.49 | 0.619 | |
| Glucose, mmol/L | DD, ID II | 0.2 ± 1.7 0.1 ± 1.0 | −0.35 | 0.729 | DD, ID II | 0.2 ± 1.6 −0.5 ± 1.1 | 1.37 | 0.169 |
| II, ID DD | 0.3 ± 1.8 −0.0 ± 1.0 | 0.49 | 0.626 | II, ID DD | 0.2 ± 1.8 −0.1 ± 1.0 | 0.10 | 0.921 | |
| Body mass index, kg/m2 | DD, ID II | 0.6 ± 2.0 −0.8 ± 2.2 | 1.86 | 0.062 | DD, ID II | 0.7 ± 1.9 0.8 ± 1.5 | −0.16 | 0.872 |
| II, ID DD | 0.6 ± 1.6 0.1 ± 2.8 | 0.19 | 0.846 | II, ID DD | 0.7 ± 2.0 0.7 ± 1.6 | 0.10 | 0.912 |
Differences were compared using Mann–Whitney U test. PANSS indicates Positive and Negative Syndrome Scale. Changes were compared using Mann–Whitney U test. PANSS indicates Positive and Negative Syndrome Scale.
Table 4.
PANSS psychopathology data after antipsychotic treatment, predicted by ACE-I/D polymorphism.
Table 4.
PANSS psychopathology data after antipsychotic treatment, predicted by ACE-I/D polymorphism.
| Males (N = 99) | |||||
|---|---|---|---|---|---|
| Dependent Variable | Predictor | β | R2 Change | F | p |
| PANSS positive symptom score | ACE-D allele | −0.23 | 0.054 | 4.59 | 0.035 |
| PANSS excitement factor | ACE-D allele | −0.26 | 0.067 | 5.93 | 0.017 |
| PANSS cognitive factor | Number of psychotic episodes | 0.25 | 0.062 | 5.39 | 0.023 |
| Females (N = 87) | |||||
| Dependent Variable | Predictor | β | R2 Change | F | p |
| PANSS depression factor | ACE-I allele | 0.30 | 0.087 | 7.50 | 0.008 |
Candidate predictor variables included ACE-D allele, ACE-I allele, age, and number of psychotic episodes. Criteria used for predictor variable’s entry or removal: F = 3 to enter, F = 1 to remove.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Nadalin, S.; Dević Pavlić, S.; Peitl, V.; Karlović, D.; Zatković, L.; Ristić, S.; Buretić-Tomljanović, A.; Jakovac, H. Association between Insertion-Deletion Polymorphism of the Angiotensin-Converting Enzyme Gene and Treatment Response to Antipsychotic Medications: A Study of Antipsychotic-Naïve First-Episode Psychosis Patients and Nonadherent Chronic Psychosis Patients. Int. J. Mol. Sci. 2022, 23, 12180. https://doi.org/10.3390/ijms232012180
AMA Style
Nadalin S, Dević Pavlić S, Peitl V, Karlović D, Zatković L, Ristić S, Buretić-Tomljanović A, Jakovac H. Association between Insertion-Deletion Polymorphism of the Angiotensin-Converting Enzyme Gene and Treatment Response to Antipsychotic Medications: A Study of Antipsychotic-Naïve First-Episode Psychosis Patients and Nonadherent Chronic Psychosis Patients. International Journal of Molecular Sciences. 2022; 23(20):12180. https://doi.org/10.3390/ijms232012180
Chicago/Turabian StyleNadalin, Sergej, Sanja Dević Pavlić, Vjekoslav Peitl, Dalibor Karlović, Lena Zatković, Smiljana Ristić, Alena Buretić-Tomljanović, and Hrvoje Jakovac. 2022. "Association between Insertion-Deletion Polymorphism of the Angiotensin-Converting Enzyme Gene and Treatment Response to Antipsychotic Medications: A Study of Antipsychotic-Naïve First-Episode Psychosis Patients and Nonadherent Chronic Psychosis Patients" International Journal of Molecular Sciences 23, no. 20: 12180. https://doi.org/10.3390/ijms232012180
APA StyleNadalin, S., Dević Pavlić, S., Peitl, V., Karlović, D., Zatković, L., Ristić, S., Buretić-Tomljanović, A., & Jakovac, H. (2022). Association between Insertion-Deletion Polymorphism of the Angiotensin-Converting Enzyme Gene and Treatment Response to Antipsychotic Medications: A Study of Antipsychotic-Naïve First-Episode Psychosis Patients and Nonadherent Chronic Psychosis Patients. International Journal of Molecular Sciences, 23(20), 12180. https://doi.org/10.3390/ijms232012180
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
