Linking Brain, Hormones, and Metabolism: Pathophysiology and Treatment of Antipsychotic-Induced Cardiometabolic Side Effects

Walter Milano ¹, Roberta Campanile ¹, Magda Marchese ², Maria Francesca Milano ¹, Ludovica Ragozino ¹, Biancamaria Saetta ¹, Anna Capasso ^3,*

1. UOSD Eating Disorder Unit, Mental Health Department, ASL Napoli 2 Nord, 80027 Napoli, Italy

2. Clinical Pathology Services, Santa Maria Delle Grazie Hospital Pozzuoli, Asl Napoli 2 Nord, 80027 Napoli, Italy

3. Department of Pharmacy, University of Salerno, Fisciano, 84084 Salerno, Italy

* Correspondence: Anna Capasso

Academic Editor: Bart Ellenbroek

Collection: New Developments in Brain Injury

Received: October 22, 2025 | Accepted: March 18, 2026 | Published: April 09, 2026

OBM Neurobiology 2026, Volume 10, Issue 2, doi:10.21926/obm.neurobiol.2602330

Recommended citation: Milano W, Campanile R, Marchese M, Milano MF, Ragozino L, Saetta B, Capasso A. Linking Brain, Hormones, and Metabolism: Pathophysiology and Treatment of Antipsychotic-Induced Cardiometabolic Side Effects. OBM Neurobiology 2026; 10(2): 330; doi:10.21926/obm.neurobiol.2602330.

© 2026 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

1. Introduction

Schizophrenia is a significant psychiatric disorder characterized by a chronic and debilitating trajectory, leading to substantial personal suffering and considerable social implications. This condition is marked by enduring symptoms that affect cognitive and perceptual abilities, disrupt behavior and language organization, and result in emotional blunting and overall maladjustment. As a result, individuals with schizophrenia often face challenges in both occupational and social settings.

In addition to the significant psychiatric picture, for several years, it has been demonstrated that individuals with schizophrenia have a notably reduced life expectancy, ranging between 15 and 20 years less than that of the general population, accompanied by a 2-3-fold increase in the standard all-cause mortality rate [1,2,3]. Individuals with schizophrenia experience double the rates of morbidity and mortality due to cardiovascular disease (CVD) compared to the general population [4].

Regarding metabolic diseases, relative risk for obesity and type 2 diabetes mellitus (T2DM), 1.5-fold and 2-fold, respectively [5,6,7] compared to healthy controls, with an even increased risk among subjects with multi-episode schizophrenia in comparison to those with first-episode schizophrenia [8].

Importantly, the gap in mortality between individuals with schizophrenia and the general population is markedly increasing, indicating a need for a better understanding of the factors that contribute to cardiovascular and metabolic diseases in these patients [9]. The elevated morbidity and mortality among schizophrenia patients may also be partly linked to unhealthy behaviors commonly observed in these individuals, such as smoking, substance misuse, physical inactivity, and poor dietary habits [10].

In recent years, however, investigations in first-episode patients have revealed the existence of cardiometabolic, immune, and hypothalamic-pituitary-adrenal (HPA) axis dysfunction. This indicates that psychotic disorders affect multiple systems and should, therefore, be viewed as a genuine systemic pathology [11].

Antipsychotics serve as the primary treatment for individuals with schizophrenia, although some antipsychotics (APs) are also authorized for the management of bipolar disorder, treatment-resistant depression, autism, or Tourette syndrome. Various antipsychotics are prescribed, albeit off-label, for individuals with other disorders, including borderline personality disorder, obsessive-compulsive disorder, anorexia nervosa, insomnia, delusions, and several dementia-related syndromes, including Alzheimer’s disease [12].

However, because the use of APs can lead to a range of side effects, some of which are serious from a medical standpoint, resulting in reduced adherence or complete discontinuation of treatment by patients, it is essential to thoroughly assess the potential occurrence of internal complications [12,13].

This is also demonstrated in all guidelines that advise selecting antipsychotic medications based on the profiles of potential associated side effects, which differ greatly, rather than solely on efficacy, which is viewed as largely comparable among the different compounds. For nonpsychotic conditions and off-label applications, where evidence supporting the advantages of antipsychotics is frequently ambiguous, the assessment of side effects holds great significance, as the benefit-to-risk ratio is lower and substantially affects the choice to utilize these medications [14,15].

In general, therefore, it can be stated that individuals with psychosis experience a broad spectrum of medical complications stemming from the severity and variability of the disorder, unhealthy behaviors and lifestyles, as well as the possible negative effects of antipsychotic medications. Consequently, patients with schizophrenia face a heightened risk of cardiometabolic issues compared to those without psychiatric disorders. Furthermore, while the use of multiple antipsychotics elevates cardiometabolic risk factors, mortality rates are increased in untreated individuals compared to those receiving antipsychotics. This suggests that the advantages, both direct and indirect, of properly managed illness leads to reduced cardiometabolic risk factors and comorbidities [16,17]. The use of antipsychotics has been linked to a lower risk of all-cause cardiovascular mortality in comparison to the absence of antipsychotic treatment in individuals with schizophrenia [18,19]. This apparently contradictory effect of antipsychotics on cardiovascular morbidity and mortality is likely attributable to improved adherence to secondary and tertiary prevention measures, supported by suitable antipsychotic treatment [20], which is vital in reducing both natural and unnatural death causes (e.g., suicide and accidents) [21].

A prospective study involving a cohort of 1230 first-episode patients indicated that both lack of treatment and higher doses of antipsychotic medications were correlated with an increased risk of cardiovascular mortality compared to lower or moderate doses, presenting a typical U-shaped curve that underscores the need for proper dosing [22].

A thorough risk-benefit evaluation regarding the prescription of an antipsychotic medication should be conducted for each specific antipsychotic, rather than by “class” or “generation,” ensuring an appropriate assessment of the patient’s overall condition, not just their psychiatric status, as the advantages of antipsychotics may sometimes be overshadowed by adverse effects, allowing for the avoidance or management of any risks to maximize the use of these essential medications [14].

This review synthesizes current evidence linking antipsychotic pharmacodynamics with cardiometabolic outcomes, emphasizing receptor-level mechanisms, neurohormonal signaling, and potential therapeutic strategies.

2. Methods

PubMed was searched in 2025 from database inception. We included population-based, longitudinal, comparative studies that report the outcomes of interest for adult participants, including diabetes, weight gain/obesity, dyslipidemia, hypertension, metabolic syndrome, schizophrenia, use of antipsychotic drugs, and their effects.

3. Metabolic Events

The negative effects of antipsychotic medications can vary from relatively minor tolerability issues (e.g., mild sedation or dry mouth) to very uncomfortable ones (e.g., constipation, akathisia, sialorrhea, sexual dysfunction), to painful symptoms (e.g., acute dystonias), to adverse reactions that may not have significant short-term clinical consequences (e.g., increased prolactin or serum lipid levels) but could present a long-term medical danger, to chronic issues (e.g., tardive dyskinesia, osteoporosis, weight gain, diabetes, dyslipidemia, MetS) and conditions associated with a high risk of sudden mortality (e.g., cardiovascular disease, myocarditis, and agranulocytosis) [23].

Various antipsychotic medications are linked to differing degrees of moderate weight gain, hypertension, and detrimental impacts on lipid and glucose metabolism. Conversely, some antipsychotics are linked with considerable weight gain, and nearly all antipsychotics can encourage body weight gain among younger patients [24].

A noteworthy meta-analysis revealed that, in comparison to placebo, the majority of antipsychotic medications are connected with weight gain [25]. Weight gain is considered one of the most significant side effects of antipsychotics, not only because it is undesirable for patients and heightens social stigma, leading to decreased treatment adherence but also significantly raises the risk of serious health conditions associated with being overweight and obese: degenerative joint diseases, T2DMand its complications, cardiovascular and cerebrovascular diseases, liver and kidney diseases, and specific types of neoplasms [23].

Weight gain in individuals with schizophrenia is influenced not only by the use of antipsychotic medications but also by the fact that these drugs worsen a series of factors often already present in patients with schizophrenia, which are characterized by inadequate self-care and an overall unhealthy lifestyle. Individuals with psychosis tend to consume more saturated fats, more refined sugars, less fiber, and fewer fruits and vegetables compared to the general population. Many individuals with psychotic disorders largely lead sedentary lifestyles and engage in less physical activity than the general population. Furthermore, there is a higher occurrence of smoking and alcohol dependence [25]. Lastly, it must be noted that individuals with schizophrenia, to a large extent, experience lower incomes and possess fewer economic resources, reducing their ability to care for themselves and often receiving less medical attention than the general population [24].

In general, weight gain can be recognized as early as 6 to 8 weeks after initiating antipsychotic therapy [26], and initial weight gain seems to be an accurate predictor of long-term weight gain. A prospective study indicated that an increase of over 5% following one month of treatment was the most reliable predictor of long-term weight gain [27]. In the EUFEST (European First Episode Schizophrenia Trial) research among first-episode schizophrenic patients, a rise of 7% or more in initial body weight was observed in 65% of participants during one-year follow-up [28]. In a study involving individuals in the early phases of treatment for their first episode of psychosis, an increase in various metabolic risk factors was evidenced after an average of 47 days of antipsychotic treatment [29].

Although weight gain is frequently associated with several negative metabolic outcomes, changes in lipid metabolism and decreased insulin sensitivity can also occur without weight gain [23]; in fact, evidence suggests that metabolic changes may sometimes occur before weight gain. Notably, T2DM is not strongly connected to adiposity. Specifically, 25% of patients may experience hyperglycemia within the initial weeks of antipsychotic treatment, even before any weight gain [30].

The likelihood of additional metabolic issues substantially rises with the duration of the disease. Individuals suffering from chronic conditions demonstrate significantly higher rates of metabolic dysfunction in comparison to first-episode and drug-naïve patients [12].

The mechanisms that lead to metabolic dysregulation are intricate and involve various neurotransmitter and hormonal systems, which interact with genetic predisposition and the user’s lifestyle, as well as the specific antipsychotic medication prescribed. This complex interplay ultimately determines the degree of potential adverse events associated with each particular drug [10].

Thus, each antipsychotic medication possesses its own largely unique side effect profile, which impacts individuals differently, primarily depending on how it interacts with the various receptors targeted by the drug.

The various mechanisms of action of the different medications do not strictly fit into the categories of First-Generation Antipsychotics (FGA) and Second-Generation Antipsychotics (SGA). With the notable exception of dyskinesia, which tends to be more prevalent among patients treated with older (first-generation) medications such as chlorpromazine and haloperidol, no adverse effects are specifically tied to any class. Nevertheless, weight gain is not exclusive to newer medications and is not universal to all second-generation drugs. Likewise, akathisia and Parkinsonism are commonly observed with older medications, but also in some newer ones. Several adverse effects, including seizures, neutropenia, and sialorrhea, are mainly associated with the use of clozapine [23].

3.1 Schizophrenic Illness and Metabolic Alterations

Analysis of data from the pre-antipsychotic era, regarding patients diagnosed with schizophrenia, indicates that signs of glucose metabolism abnormalities existed long before the potential influences of pharmacological treatment.

Many years before the advent of antipsychotics, certain cohort studies [31,32] identified a heightened frequency of glucose metabolism irregularities in individuals with schizophrenia and a greater occurrence of diabetes in those with schizophrenia compared to the healthy population [33].

Notably, a study from 1922 involving individuals with schizophrenia reported elevated fasting and postprandial blood glucose levels among these patients, and it discovered that blood glucose values were partially correlated with the severity of their condition. In fact, individuals with catatonic schizophrenia exhibited blood glucose levels that were twice as high in the postprandial assessment relative to those with disorganized schizophrenia. Blood glucose observed after a 12-hour fasting period was consistently greater in catatonic patients than in those with other types of schizophrenia [34].

Recent research supported findings from the pre-antipsychotic period. It confirmed diminished glucose tolerance, dyslipidemia, and elements related to MetS in individuals with drug-naïve schizophrenia, in contrast to healthy controls [35]. In a 2016 examination of drug-naïve schizophrenic participants, almost 25% of patients presented with impaired glucose tolerance at baseline when compared with controls. In modern drug-naïve studies, schizophrenic patients also demonstrated elevated fasting glucose levels and significant insulin resistance (IR); additionally, when compared to controls, patients with schizophrenia had increased body mass index, LDL cholesterol levels, triglyceride levels, waist circumference, and hip circumference [36].

Even very young patients, aged 12 to 17 years, experiencing their first episode of psychosis, who were still not receiving drug treatment, exhibited greater waist circumference, total cholesterol, and LDL cholesterol. In contrast, HDL cholesterol was lower than that of healthy peers of the same age [37]. A compelling systematic review indicated that individuals with nonaffective psychosis had elevated triglyceride levels and reduced HDL cholesterol levels at the start of their illness compared to control subjects. Ultimately, the research proposed that this might indicate a state of subclinical dyslipidemia and theorized a potential presence of a distinct metabolic phenotype in psychotic patients owing to a potential gene interaction [38]. Another investigation involving first-episode psychosis patients, not undergoing drug treatment, demonstrated elevated levels of insulin and peptide C alongside decreased HDL cholesterol values compared to matching controls, at the same BMI. These findings imply the possible influence that schizophrenia as a condition might have on weight gain, hyperinsulinemia, and consequently insulin resistance [39]. For individuals diagnosed with schizophrenia, the administration of antipsychotics (APs) could potentially heighten the overall metabolic risk. A recent study conducted in Denmark revealed that while schizophrenia patients who had never been treated with APs had a diabetes risk rate three times higher than the general population, those who began AP treatment had a diabetes risk rate of 3.64 compared to patients not receiving drug therapy. This study also noted that both first- and second-generation APs elevated the risk, without any statistically significant difference between the two classes of medication [40]. Moreover, it is important to note that even among those taking medications with the greatest metabolic risk, such as olanzapine and clozapine, there remains a significant percentage, over 15-20%, who do not experience weight gain. Collectively, all these pieces of evidence complicate the identification of a specific mechanism that could explain the potential metabolic dysfunction, while also suggesting the likely presence of a metabolic phenotype inherent to schizophrenia [41]. Impaired glucose tolerance has also been shown in first-degree, nonpsychotic relatives of individuals with schizophrenia, further indicating the potential of an inherited phenotype, irrespective of the actual onset of a psychotic disorder. This further supports the idea of a unique metabolic endophenotype linked to schizophrenia, with varying penetrance between affected individuals and their unaffected relatives [12].

3.2 Metabolic Syndrome

This phrase is not meant to indicate a singular illness, but instead refers to a group of illnesses and/or contributing factors. The National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATPIII), along with the International Diabetes Foundation (IDF), has defined the term MetS, with agreement from the American Heart Association and the National Heart, Lung, and Blood Institute [42].

At least three of the following risk factors or conditions must exist concurrently to describe MetS:

• Blood pressure above 130/85 mmHg;
• Fasting blood triglycerides above 150 mg/dl;
• Fasting blood glucose above 110 mg/dl; and
• HDL cholesterol below 40 mg/dl in men or 50 mg/dl in women;
• Waist circumference exceeding 102 centimeters for men or 88 centimeters for women.

Note: It is noteworthy that the increase in waist circumference does not always correlate with weight gain alone but rather with the visceral distribution of fat, which is metabolically more harmful.

It is essential to understand that, according to these standards, an individual with MetS might have values slightly above the normal range and therefore may not be evidently ill; In fact:

• To identify hypertension, blood pressure must consistently surpass 140/90 mmHg;
• In the case of hypertriglyceridemia, blood triglycerides exceed the threshold value of 180/200 mg/dl;
• diabetes can be diagnosed if, after fasting, blood glucose is higher than 126 mg/dl, but even with slightly lower values, one might still suspect insulin resistance, fasting hyperglycemia, and prediabetes.
• Having an HDL cholesterol level lower than 40 mg/dl (for males) or 50 mg/dl (for females) alone is not adequate to classify the patient in a high cardiovascular risk category;
• If the waist circumference is over 102 (for males) or 88 centimeters (for females), the individual may actually be overweight. Yet, their fat mass is primarily concentrated in the abdominal region (android or apple-shaped obesity).

But the mere simultaneous existence of at least three of the aforementioned factors leads to the diagnosis of MetS.

The existence of MetS categorizes an individual into a high-risk category, concerning both the exacerbation of specific disorders, such as the progression from hyperglycemia/insulin resistance to T2DM, and the consequent complications, particularly those related to cardiovascular health, including heart attack and stroke, as well as organ function issues, like hepatic steatosis and cirrhosis.

Consequently, besides deteriorating quality of life, there is a heightened occurrence of premature death and lasting disability.

Individuals receiving treatment with antipsychotic medications are 2 to 3 times more likely to satisfy the criteria for MetS compared to the general population. But MetS has been linked to individuals with schizophrenia, even treatment naive [35].

Mitchell et al. conducted a meta-analysis involving 78 studies, which encompassed nearly 25,000 participants, and found that 35.3% of individuals on antipsychotic drugs exhibited clinical indicators associated with MetS [43]; data confirmed in a 2017 investigation, when Vancampfort et al. observed that roughly one-third of individuals with schizophrenia suffer from MetS, with prevalence rates rising to 65% among those with chronic conditions, while obesity, T2DM, and hypercholesterolemia among individuals with schizophrenia is thought to be 3-5 times higher than that of the general population [44].

Furthermore, MetS could contribute to poor treatment adherence and discontinuation of medication, leading to relapse and suboptimal clinical outcomes.

The connection between MetS and schizophrenia is intricate and influenced by multiple factors.

Besides the side effects of medication, other elements are at play, including unhealthy lifestyle choices, decreased physical activity, smoking, inadequate diet, and genetic susceptibility to the development of metabolic conditions [45].

Concerning MetS, numerous reviews and meta-analyses have systematically evaluated atypical APs against typical APs for efficacy and side effects and have found evidence supporting the superior efficacy of atypicals in multiple areas, but with a heightened risk of developing MetS [46,47]. Literature evidence shows that AP treatment undoubtedly raises the risk of metabolic disorders, yet there is also a significant baseline risk for MetS in individuals with schizophrenia, even without treatment. A meta-analysis involving 48 studies revealed a prevalence of approximately 10% of MetS in patients not exposed to antipsychotics; however, during treatment, the prevalence rate rose to 19.4% for those on aripiprazole and as high as 47.2% for patients receiving clozapine. This further indicates that the condition of psychotic illness itself influences metabolic changes, but treatment with certain APs may exacerbate these dysmetabolisms [44]. It is rather surprising that such notable side effects have been considerably underestimated historically; nevertheless, in recent years, greater attention has been given, albeit still insufficiently, to addressing these critical complications during the management of psychotic disorders [45].

3.3 Antipsychotics and Metabolic Diseases

3.3.1 Drug Classes and Metabolic Profiles

APs are typically categorized into typical antipsychotics (TAPs) or first-generation APs and atypical antipsychotics (AAPs) or second-generation APs, grounded in the understanding that atypicals seldom cause motor side effects. However, this classification has been challenged by numerous experts, leading to a recent proposal for a new categorization within AAPs that introduces the concept of the atypical spectrum, beginning with risperidone (the least atypical) and culminating with clozapine (the most atypical), which remains the gold standard for patients with treatment-resistant schizophrenia [48]. Since clozapine’s discovery in the 1970s, the notion of atypia was established, signifying a new category of medications that were better tolerated, particularly concerning motor side effects. Nonetheless, over the years, it became evident that the advantages of this new category of drugs were somewhat masked by frequent metabolic side effects, such as obesity and diabetes. Clinical evidence also indicated substantial variation within the AAP class concerning both efficacy and side effects, including motor and endocrine-metabolic, emphasizing that each AAP was distinct, and questioning the differences between typical and atypical; specifically, risperidone and amisulpride may forfeit their atypicality at elevated doses [45,48].

The molecular and cellular mechanisms that underlie metabolic changes are intricate and encompass nearly all organs pertinent to metabolism, including the central and peripheral nervous system via the interaction among diverse neurochemical and hormonal systems, alongside genetic influences and lifestyle risk factors.

Indeed, APs are medications that act on numerous receptors and profoundly impact various hormones and neuromodulators. The varying affinities of APs for dopaminergic, serotonergic, muscarinic, adrenergic, histamine receptors, and other specific molecular targets (e.g., AMPK) account for their distinct clinical profiles. These receptor targets are found not only in central nervous pathways but also in hypothalamic centers, the pancreas, liver, adipose tissue, and skeletal muscle tissue, where they influence glucose and lipid homeostasis throughout the body [45,47].

3.3.2 Meta-Analytic Evidence

Antipsychotics are linked, to varying extents, with a range of metabolic irregularities. Aside from inducing weight gain, another undesirable effect of AP treatment is fasting hyperglycemia, which may later contribute to the development of T2DM. So much so that a meta-analysis involving 270,000 participants found that clozapine and olanzapine were connected with an elevated risk of T2D. At the same time, risperidone or quetiapine presented a moderate risk, and the prevalence of T2D with AP use was overall evaluated between 3% and 28% [11,40].

When obesity arises during antipsychotic (AP) treatment, tissues that are sensitive to insulin become less effective at responding to it; as a result, pancreatic beta cells enhance their secretion in a bid to augment the hypoglycemic impact of insulin. Over the long term, this adaptive mechanism may lead to the decline of beta cells, thereby heightening the probability of developing T2DM (T2D) [45]. AP treatment is also linked to dyslipidemia, with prevalence rates between 15 and 50%. Saari et al. examined a group of 5654 Finnish patients and identified that the likelihood of dyslipidemia in individuals undergoing AP treatment was increased by 2.8 times for hypercholesterolemia, 2.3 times for hypertriglyceridemia, and the risk for elevated LDL cholesterol was 1.6 times higher [49]. A systematic review evaluating the metabolic effects of various atypical antipsychotics (AAPs) revealed that olanzapine and clozapine pose the highest risks for elevating cholesterol levels, alongside weight gain [50]. Another study indicated that olanzapine led to the largest increase in cholesterol and waist circumference among various APs [51]. Despite the importance of dyslipidemia and hyperglycemia in patients with schizophrenia, the majority of them are not treated with medications. For instance, Mackin et al. discovered that merely 7% of patients were receiving hypolipidemic treatment [52]. While clinical observations have concentrated on the most frequently prescribed AAPs, newer medications like cariprazine, brexpiprazole, and lumateperone have demonstrated a lesser effect on metabolic parameters (BMI, weight variation, LDL levels) than clozapine or olanzapine [53]. Regarding the likelihood of altering the glycid profile, both clozapine and olanzapine showed the highest propensity to induce insulin resistance. They significantly elevated the risk of serious cardiovascular issues (e.g., coronary syndrome, ischemic stroke, and peripheral artery disease) with a risk factor of 2.8 [54]. Approximately 32% of individuals on olanzapine treatment experience insulin resistance, along with a minimum 15% increase in body weight from their baseline [55]. AP-induced insulin resistance is a pivotal element in the escalated risk of coronary artery disease, which stands as a primary contributor to morbidity and early mortality in this demographic [12]. In contrast, other medications such as ziprasidone and lurasidone exhibit lower cardiometabolic risks, although the possibility of other metabolic disturbances, including Nonalcoholic Fatty Liver Disease (NAFLD), remains significantly high [56]. It is important to note, however, that even first-generation medications such as haloperidol or chlorpromazine have been linked to weight gain and insulin resistance [12]. Some researchers have proposed that haloperidol may cause weight gain and metabolic issues due to its effects on hypothalamic centers and its potential to induce hyperprolactinemia [45].

In fact, during the prominent European EUFEST (European First Episode Schizophrenia Trial) study, while olanzapine led to a weight increase of 13.9 kg from baseline, haloperidol also resulted in a notable weight gain of 7.3 kg [57]. The METEOR (Evaluation of METabolic disordErs in schizOphRenic patients) study found no meaningful differences between patients taking first- or second-generation APs in the prevalence of glycemic disorders, dyslipidemia, and MetS [58]. These findings indicate that the majority, if not all, APs can lead to or worsen metabolic changes and related health issues. Data from the Clinical Antipsychotics Trials of Intervention Efficacy (CATIE) also highlighted significant metabolic effects in individuals using APs [59]. In the initial CATIE study, olanzapine exhibited a weight increase of nearly 1 kg/month; a comparable conclusion was reached in a follow-up one-year study where olanzapine and clozapine caused a weight gain of approximately 12 kg, while quetiapine and risperidone resulted in a weight increase of 2-3 kg [60]. Aripiprazole and asenapine presented relatively minor weight gain, under 2 kg/year, and ultimately, no weight increase was observed with ziprasidone [61].

In a separate study involving healthy volunteers, Fountaine et al. reported that olanzapine led to an increased caloric intake of around 350 kcal daily and the subsequent weight gain of approximately 2.5 kg after only 4 to 6 weeks. A comparable study was conducted in adolescents experiencing psychosis who were treated with olanzapine for 4 weeks, verifying the drug-induced rise in appetite and caloric consumption, which was also linked to increased water retention [62].

When compared to a matched sample of individuals without psychiatric disorders who were monitored in the National Health and Nutrition Examination Survey (NHANES), individuals with schizophrenia receiving AP treatment had the highest metabolic risk of any other patient category. These findings affirm that irrespective of the impacts of various medications, schizophrenia seems to entail an innate risk of metabolic dysfunction, and AP treatment amplifies this vulnerability. Consequently, the combination of metabolic risks inherent to the condition, genetics, and lifestyle, when paired with AP treatment, leads to the maximum possible metabolic risk among schizophrenia patients receiving treatment [12].

A recent meta-analysis, published in Lancet Psychiatry (2020), sought to evaluate antipsychotics based on their metabolic side effects, involving over 100 randomized controlled trials with almost 30,000 patients, revealing significant differences among antipsychotics concerning metabolic side effects, with olanzapine and clozapine presenting the least favorable profiles while aripiprazole, brexpiprazole, cariprazine, lurasidone, and ziprasidone ranked more favorably [53].

Below are the modifications for individual metabolic parameters reported in the study [53]:

For changes in Body Mass Index (BMI), 22 studies evaluated nine different antipsychotics (4196 patients) against placebo (900 patients). Compared with placebo, neither haloperidol nor aripiprazole resulted in a change in BMI. BMI showed an increase, in ascending order of effect, with lurasidone, risperidone, paliperidone, quetiapine, sertindole, clozapine, and olanzapine. Ranking based on the extent of BMI modification, haloperidol was identified as the best and olanzapine as the worst.

For changes in total cholesterol, 36 studies assessed 14 different antipsychotics (11762 patients) compared to placebo (2998 patients). In comparison to placebo, there was no indication of change in total cholesterol with iloperidone, cariprazine, sertindole, ziprasidone, lurasidone, brexpiprazole, aripiprazole, risperidone, paliperidone, haloperidol, and amisulpride. Total cholesterol increased with quetiapine, olanzapine, and clozapine. Ranking by the degree of cholesterol change, cariprazine was identified as the best and clozapine as the worst.

For the change in LDL cholesterol, 24 studies compared nine different antipsychotics (7439 patients) against placebo (2419 patients). Compared to placebo, no change in LDL cholesterol was detected with ziprasidone, lurasidone, risperidone, paliperidone, aripiprazole, and brexpiprazole. In contrast, cariprazine reduced LDL cholesterol. Increases in LDL cholesterol were linked to the use of quetiapine and olanzapine. Based on the degree of LDL cholesterol modification, cariprazine was designated the best, and olanzapine the worst.

For the change in HDL cholesterol, 22 studies examined 10 different antipsychotics (7073 patients) compared with placebo (2189 patients). In comparison to placebo, no alteration in HDL cholesterol was found with amisulpride, olanzapine, quetiapine, risperidone, paliperidone, lurasidone, cariprazine, or ziprasidone. HDL cholesterol levels increased with aripiprazole and brexpiprazole. Ranking changes in HDL cholesterol classified brexpiprazole as the best and amisulpride as the worst.

For the change in triglycerides, 34 studies analyzed 15 different antipsychotics (10965 patients) compared with placebo (3021 patients). Compared to placebo, no changes in triglyceride concentrations were found with brexpiprazole, lurasidone, sertindole, cariprazine, ziprasidone, aripiprazole, risperidone, paliperidone, amisulpride, haloperidol, and iloperidone. Triglyceride levels increased with quetiapine, olanzapine, zotepine, and clozapine. Ranking according to the degree of triglyceride modification, determined brexpiprazole as the best and clozapine as the worst.

For the change in fasting glucose, 37 studies compared 16 different antipsychotics (10681 patients) against placebo (3032 patients). Compared to placebo, no changes in glucose concentrations were observed with amisulpride, asenapine, sertindole, ziprasidone, brexpiprazole, quetiapine, risperidone, paliperidone, aripiprazole, haloperidol, cariprazine, and iloperidone. Glucose levels decreased with lurasidone and increased with olanzapine, zotepine, and clozapine. Ranking according to the degree of glycemic changes classified lurasidone as the best and clozapine as the worst.

Of note, the most significant increases in fasting glucose levels due to antipsychotics were linked to higher initial values of weight and were more prevalent among male participants. The largest increases in total cholesterol attributed to antipsychotics were more common among nonwhite participants. Interestingly, subjects who experienced the most significant increases in body weight, BMI, total cholesterol, and LDL cholesterol also showed greater improvements in psychotic symptomatology, along with greater reductions in HDL cholesterol (Table 1). Additionally, there is unique evidence indicating that some of the medications have demonstrated better performance than placebo on certain metabolic measures: for instance, in comparison to placebo, lurasidone resulted in decreased glucose levels, cariprazine led to lower LDL cholesterol levels, and both aripiprazole and brexpiprazole were associated with increased HDL cholesterol, which is a protective factor.

Table 1 Comparative metabolic parameter changes by antipsychotic (vs. placebo).

3.3.3 Dose-Response Relationships

Two recent studies have investigated how various antipsychotic medications might influence a patient’s weight, both regarding the specific medication used and concerning dosage [63,64]. By identifying the varying outcomes along a curve, the researchers could illustrate the effects of each antipsychotic on body weight. These evaluations could help select the most suitable medication and dosage for the individual patient.

In a 2023 meta-analysis [62] that incorporated 52 randomized trials with 22,588 participants, it was demonstrated that, excluding aripiprazole LAI, all antipsychotics studied showed significant dose-response relationships with weight, ranging from lurasidone with a nearly parabolic-shaped curve (0.53 kg/6 weeks) to olanzapine LAI, which maintained an increasing curve with larger doses (4.29 kg/8 weeks). Overall, the analysis uncovered three distinct shapes of the dose-response curves, categorizing them as follows:

Quasi-parabolic: Along this curve, the antipsychotics brexpiprazole, cariprazine, haloperidol, lurasidone, and quetiapine IR (Immediate release) caused an initial weight increase at relatively low doses that grew with higher doses, but at some point the weight values leveled off, even as the dosage was increased further. Except for quetiapine, the authors indicated that these medications should be viewed as “metabolically neutral”, resulting in low weight gain (0.45 to 1.3 kg) and minor metabolic issues compared to other antipsychotics.

Plateau: For the drugs in this category, there was a dosage level beyond which weight gain did not further increase; weight rose to a specific point, but the later addition of more medication did not lead to additional weight gain. The average weight gain for these medications, including asenapine, iloperidone, paliperidone LAI, quetiapine IR (immediate release), and risperidone, ranged from 0.9 to 2.7 kg. Even at very low doses, quetiapine was associated with considerable metabolic changes.

Ascending: In the last group, weight gain continued to climb with each increased dose, with an average rise from 0.9 to 4.5 kg. Medications in this curve consisted of aripiprazole, olanzapine, risperidone, and paliperidone, available in both oral and LAI formulations. Aripiprazole resulted in the least weight gain, approximately 1.2 kg, while olanzapine led to the most, over 5.2 kg.

Wu’s 2022 meta-analysis [64], which encompassed ninety-seven studies, also included 36,326 participants, with an average observation duration of 6 weeks (ranging from 4 to 26 weeks), discovered that amisulpride, aripiprazole, brexpiprazole, cariprazine, haloperidol, lumateperone, and lurasidone resulted in slight weight gain compared to placebo (mean difference for any dose ≤1 kg). In contrast, a more substantial weight gain was noted with all other medications. In the majority of the drugs, the dose-response curves exhibited an initial dose-related weight gain that stabilized at the highest dose. In contrast, for others, no plateau was observed, and some also exhibited bell-shaped curves, indicating less weight gain at higher doses (Table 2).

Table 2 Dose-response curve patterns of weight gain associated with antipsychotics.

Second-generation antipsychotics vary not only in their tendency for weight gain but also in their dose-response curves. This data provides crucial information for dosing choices in clinical practice to refine treatment plans for individual patients. For operational reference, we present data that can enhance our clinical understanding of the impact of potential metabolic changes triggered by antipsychotics on morbidity.

In the general population, for each kg increase in body weight, the likelihood of cardiovascular disease increases by 3.1%, and for each unit of BMI (kg/m²), the likelihood of heart failure increases by 5.7% and the likelihood of T2DM increases by 8.4%. Furthermore, a 1 mmol/L rise (equivalent to approximately 88 mg/dl) in triglyceride levels relates to a 32-76% augmented risk for cardiovascular disease. Consequently, around 6 weeks of treatment with antipsychotics such as olanzapine and clozapine, which elevate body weight by roughly 3 kg, one unit of BMI, and about 1 mmol/L of triglycerides, may result in a significant rise in the risk of cardiovascular disease. Therefore, the usage of certain antipsychotics, even after just a few weeks, could deteriorate metabolic homeostasis in an already vulnerable individual, which supports international guidelines that metabolic monitoring should consistently accompany antipsychotic prescriptions [53] (Table 1).

4. Mechanisms of Action of Antipsychotics on Metabolic Regulation

The metabolic changes associated with antipsychotic medication have become an emerging challenge for healthcare providers. While the specific mechanisms underlying these metabolic abnormalities are not fully understood, they are thought to arise from a complex interplay of various factors. Hypotheses have been proposed to explain these mechanisms, which include increased appetite and food intake, physical inactivity, unhealthy lifestyle choices, as well as individual patient traits such as gender and genetic predispositions. Additionally, the diverse profiles of different antipsychotic medications interact uniquely with these patient characteristics, leading to a range of metabolic side effects that can vary both qualitatively and quantitatively [65].

4.1 Receptor Actions

Antipsychotic drugs are primarily known for their role as weak antagonists of the D2 dopamine receptor. However, beyond this action, they often target various other receptors, including serotonin (5-HT) receptors. The relationship between the affinity of certain serotonin receptor subtypes (5-HT2A/D2 and 5-HT2C/D2) and their rapid dissociation from the D2 receptor plays a significant role in the differences in efficacy and side effects experienced with various antipsychotic medications.

Moreover, each antipsychotic may engage multiple receptor sites, such as partial antagonism at 5-HT1, antagonism at histamine (H1) receptors, α2 adrenergic receptors, M3 muscarinic receptors, and even influence brain-derived neurotrophic factor (BDNF) production and glycine transport (GlyT). Particularly, clozapine exhibits a distinctive receptor profile among these targets, which contributes to its status as the gold standard treatment for resistant cases of schizophrenia.

Emerging evidence indicates that the molecular targets of antipsychotics extend beyond the central nervous system to include peripheral organs vital for metabolic regulation, such as the pancreas, adipose tissue, skeletal muscle, and the gastrointestinal tract. These organs, together with specific structures in the central nervous system, are crucial in regulating appetite, body weight, and glucose/insulin balance-all essential factors contributing to metabolic disturbances. For instance, pancreatic beta cells, responsible for insulin secretion, not only produce dopamine but also express D2 receptors, which are a primary target of antipsychotic drugs [12].

4.2 Intestinal Microbiota

Recent research highlights the intricate communication between the central nervous system (CNS) and peripheral organs, particularly through hypothalamic and brainstem neurons. These neurons have been shown to impact the metabolism of various cells, including beta cells, hepatocytes, and adipocytes, creating a complex interplay of influences (Figure 1) [12].

Figure 1 Gut microbiota–brain axis [66].

The intestinal microbiota (IM), consisting of over 100 trillion microorganisms mainly residing in the colon, including bacteria, fungi, protozoa, and viruses, also plays a significant role in the metabolic changes associated with acute pancreatitis (AP) [67]. In recent years, mounting evidence has linked shifts in gut microbiota composition to the onset and persistence of several mental health conditions, such as depression [68], bipolar disorder [69], and schizophrenia [70]. A recent study in Nature revealed that, through mechanisms not yet fully understood, various medications produce effects on the gut microbiome similar to those of antibiotic therapies. This includes not only proton pump inhibitors but also chemotherapeutic agents, immunosuppressants, and antipsychotics, all of which can induce dysbiosis. This disruption of the microbiota can impair gut-brain communication and alter the metabolic functions of peripheral organs [71].

The microorganisms that comprise the gut microbiota are vital for the digestion, fermentation, and absorption of essential nutrients and metabolites, such as carbohydrates, lipids, proteins, and amino acids. They produce secondary metabolites such as short-chain fatty acids (SCFAs), which serve as an important energy source [72]. Moreover, the IM can synthesize and utilize neurotransmitters and neuroactive substances such as serotonin (5-HT), dopamine, norepinephrine, and γ-aminobutyric acid (GABA), all of which can influence behavioral changes [67].

Furthermore, the proper functioning of the IM is crucial for developing and regulating neuro-immune-endocrine pathways and the hypothalamic-pituitary-adrenal (HPA) axis [73]. The brain communicates with the gut through bidirectional channels involving neuroendocrine and neuro-immune pathways and directly via the vagus nerve. These pathways are meticulously regulated by the IM, forming the microbiota-gut-brain (MGB) axis. This axis allows for a dynamic exchange of influence; alterations in microbiota composition can affect behavior, while changes in behavior can, in turn, modify the IM [74].

Animal studies have shown that metabolic alterations induced by antipsychotics (APs) are linked to changes in IM. For instance, one study observed that treatment with olanzapine in both male and female rats resulted in increased body weight and fat accumulation, as well as elevated plasma levels of interleukin IL-6, IL-8, IL-1β, leptin, and free fatty acids in adipose tissue. Additionally, olanzapine administration led to enhanced expression of fatty acid synthase (FAS) and CD68 (a macrophage marker that triggers the release of pro-inflammatory cytokines from adipocytes) in both liver and adipose tissue [75,76].

These metabolic changes were linked to a shift in the Firmicutes/Bacteroidetes ratio, where olanzapine treatment led to an obesiogenic profile characterized by an increased prevalence of Firmicutes and Proteobacteria, alongside a decrease in Bacteroidetes. This treatment also enhanced antimicrobial activity against common enteric bacteria, including Escherichia coli and Enterococcus faecalis [76,77].

Recent human and animal studies show that antipsychotic-induced dysbiosis involves changes beyond phylum-level ratios. Altered abundances of Parabacteroides distasonis, Akkermansia, Roseburia, and Lactobacillus have been linked to weight gain and insulin resistance. A multi-omics study in schizophrenia found reduced Bacteroides, Parabacteroides, Akkermansia, and Clostridium in antipsychotic-treated patients with obesity, while a meta-analysis identified changes in Lactobacillus, Roseburia, and Dialister in antipsychotic-treated participants versus controls [78,79].

In studies involving patients with schizophrenia, although the sample sizes were limited, those undergoing prolonged AP treatment exhibited metabolic comorbidities, including diabetes, weight gain, and hypertension, which were associated with changes in intestinal microbiome (IM) composition. For instance, after 24 weeks of risperidone treatment, participants experienced significant increases in body weight, body mass index (BMI), blood glucose levels, and lipid profiles, as well as heightened levels of antioxidant markers like superoxide dismutase, C-peptide, and high-sensitivity C-reactive protein (hs-CRP) [80].

Moreover, these metabolic shifts were correlated with an increased abundance of Bifidobacterium spp. and Escherichia coli, alongside a reduction in Lactobacillus spp. and Clostridium coccoides compared to the control group [81]. Another investigation found that six months of risperidone treatment led to a notable decrease in Bacteroidetes, Christensenellaceae, Enterobacteriaceae, and Proteobacteria, which was associated with changes in several metabolic parameters, including increased BMI, HOMA index, and serum lipid levels [82].

4.3 Involvement of Neurotransmitters

Research on the metabolic effects of antipsychotics (APs) has predominantly focused on specific areas of the central nervous system integral to metabolic regulation, particularly the hypothalamus. Within the central nervous system, various neurotransmitters and neuropeptides are believed to play crucial roles in mediating these metabolic phenomena, with monoamines such as dopamine, serotonin, and histamine being among the most significant.

4.3.1 Dopamine

A consistent characteristic shared by all antipsychotics is their interaction with dopamine receptors, specifically the D2 and D3 receptors (D2R and D3R). A growing body of evidence indicates that the engagement of D2Rs and D3Rs within the central nervous system is essential for both the therapeutic effects and potential metabolic side effects of these medications [83].

D2 receptors are abundantly located in anatomical regions of the central nervous system that regulate glucose metabolism. Notably, D2R is expressed on lactotrope cells in the pituitary gland, which are responsible for synthesizing and release prolactin, a hormone that plays a significant role in systemic glucose homeostasis [84].

Dopamine also influences appetite regulation through its signaling in striatal reward circuits. Variations or mutations in D2Rs, along with reduced receptor expression, are linked to cravings, increased appetite, and weight gain. Moreover, alterations in dopamine modulation within the hypothalamus, particularly in the areas such as the suprachiasmatic nucleus, can disrupt circadian rhythms that govern metabolic functions, including insulin sensitivity [85].

As previously mentioned, dopamine’s effects extend beyond the central nervous system to various peripheral organs crucial for metabolic homeostasis, such as the pancreas. Dopamine interacts with beta cells, exerting its influence through both autocrine and paracrine mechanisms to regulate glucose-stimulated insulin secretion (GSIS). Notably, sulpiride, a selective antipsychotic that targets D2R/D3R, has been shown to enhance GSIS by 40% in pancreatic beta cells [12].

Importantly, this increase in insulin secretion induced by antipsychotics aligns with the chronic hyperinsulinemia observed clinically in cases of antipsychotic-induced insulin resistance. Interestingly, D2R and D3R agonists may offer therapeutic advantages for insulin resistance. For example, bromocriptine, a rapid-release D2R/D3R agonist, has received FDA approval for the treatment of T2DM [86]. These findings suggest that dopamine D2 receptors play a critical role in modulating insulin secretion peripherally. Furthermore, any disruption in this regulatory mechanism-whether due to genetic variants in patients with schizophrenia or the effects of antipsychotics-could contribute to the diverse metabolic disturbances commonly observed in clinical settings [12].

4.3.2 Serotonin

One of the primary neurotransmitters found in the neural systems of almost all metazoan phyla is serotonin. Memory, cognition, sleep, emotion, hunger, learning, social behaviors, and whole-body homeostasis are all significantly regulated by it [87].

In addition to its role in dopamine signaling, the serotonin circuit is also crucial for maintaining metabolic homeostasis and may serve as a potential target for antipsychotics (APs) in their impact on metabolic changes.

Apart from the endogenous 5-HT, the 5-HT2a receptors are targeted by a number of antipsychotics, psychedelics, and antidepressants. While 5-HT2a receptor agonists have psychedelic and cognition-enhancing effects, preclinical and clinical research indicates that 5-HT2a receptor antagonists, including mirtazapine, mianserin, and trazodone, have antidepressant qualities [88]. Many mental illnesses, such as schizophrenia, depression, anxiety, and substance use disorders, are linked to abnormalities in 5-HT2a receptors. According to pharmacological research, high-affinity 5-HT2AR antagonists like risperidone and clozapine are useful atypical antipsychotics [87].

Research has shown that single-nucleotide polymorphisms in the serotonin 5HT2a and 5HT2c receptors are linked to various metabolic dysfunctions, including obesity, glucose intolerance, and weight gain [89]. In mouse models, mutations that lead to a loss-of-function of the 5HT2c receptor result in insulin resistance and increased appetite. These findings suggest that disruptions in brain serotonin signaling may influence both glycemic control related to T2DM and the pathophysiology of schizophrenia [90].

Furthermore, serotonin receptors in the central nervous system are significant targets for antipsychotics, particularly atypical ones such as clozapine and olanzapine. While different antipsychotics exhibit varying affinities for serotonin receptors, it has been proposed that their interaction with the 5HT2a and 5HT2c receptors, particularly within the hypothalamus, plays a substantial role in iatrogenic weight gain [83].

4.3.3 Histamine

Histamine plays a significant role in the brain, particularly through histaminergic neurons located just behind the hypothalamus, which extend their influence throughout the brain, including the corpus striatum. Emerging evidence indicates that histaminergic signaling is crucial for regulating eating behaviors, largely through its effects on reward circuits.

Research has demonstrated that histamine exerts an anorectic effect on food intake by interacting with H1 receptors (H1R) [91]. For instance, when rodents receive intracerebroventricular infusions of histamine, their food intake decreases, likely due to the activation of H1R [91]. Supporting these findings, atypical antipsychotic (AP) medications with strong H1R antagonism, such as clozapine and olanzapine, stimulate hypothalamic AMP-activated protein kinase (AMPK), potentially leading to increased appetite and food consumption.

Moreover, H1 receptors in the hypothalamus are linked to the regulation of systemic energy balance. Thus, when AP medications block these histamine receptors, they can enhance the activation of downstream AMPK signaling pathways, specifically involving carnitine palmitoyltransferase 1. This ultimately leads to a significant increase in appetite [92]. Additionally, prolonged blockage of histamine receptors may lead to fat accumulation by reducing lipolysis in adipose tissue [12,92].

4.3.4 Acetylcholine

There is still much to learn about the role of the muscarinic M3 receptor in metabolic function. The majority of what is now known comes from research on rodents.

Cholinergic neurons of the dorsomedial hypothalamus (DMH) may mediate the effect of acetylcholine on food intake. In fact, the selective M3 receptor antagonist 4-DAMP inhibits the activation of cholinergic DMH neurons, which increases food intake [93]. GABAergic axon terminals on ARC-POMC neurons receive projections from cholinergic DMH neurons. Here, the stimulation of presynaptic M3 receptors by acetylcholine stimulates the release of GABA, which inhibits ARC-POMC neurons and increases hunger. However, the current study indicates that antagonistic interactions between 5-HT2C and H1 receptors may be the main mechanism behind weight gain linked to olanzapine and clozapine. As a result, efforts are underway to investigate novel approaches to treating obesity by developing selective antagonists targeting the M3 muscarinic receptor subtype [94,95].

4.4 Neurohormonal Mechanisms

Weight gain results fundamentally from an energy imbalance where energy intake exceeds energy expenditure. This surplus is stored primarily in adipose tissue. Atypical antipsychotics (APs), particularly second-generation antipsychotics (SGAs), influence various neuropeptides that regulate appetite and food consumption.

The hypothalamus serves as the primary sensor for blood nutrient levels and plays a crucial role in regulating both glucose and lipid metabolism. It manages glucose and lipid homeostasis by coordinating multiple organs-including the liver, pancreas, adipose tissue, and skeletal muscle-through the autonomic nervous system and the neuroendocrine system. Sympathetic activation leads to increased levels of norepinephrine and adrenaline, enhanced glucagon secretion, elevated glucose production, and increased lipolysis, while reducing insulin secretion, resulting in a temporary spike in blood glucose levels. Conversely, parasympathetic activation promotes insulin secretion and inhibits glucose production [45].

Several SGAs, such as olanzapine and risperidone, have been shown to elevate the levels of appetite-stimulating neuropeptides like neuropeptide Y (NPY) and agouti-related peptide (AgRP), which work in conjunction with their action on H1 receptors to amplify these effects. Olanzapine may also boost appetite by influencing ghrelin, an orexigenic peptide [12,96].

Additionally, APs can further enhance appetite by lowering the levels of proopiomelanocortin (POMC), a neuropeptide that inhibits appetite. Notably, various metabolically significant molecules-including β-endorphins, melanocyte-stimulating hormone (MSH), and adrenocorticotropic hormone (ACTH)-are processed from POMC and its precursor, pre-POMC [97]. Recent findings suggest that one derivative, α-MSH, which typically suppresses appetite, is diminished during risperidone treatment, contributing to the observed increase in appetite [98]. The melanocortin 4 receptor (MC4R), which is activated by MSH, is also closely linked to metabolic changes and weight fluctuations induced by antipsychotics [99].

H1 receptor antagonism is not the sole mechanism affecting metabolic regulation in the hypothalamus. Dopaminergic and serotonergic antagonism induced by AP action significantly impacts hypothalamic function, particularly affecting neurons in the arcuate nucleus (ARC) [45]. The ARC contains a high concentration of D2 and D3 receptors, and blockade of these AP effects may disrupt glucose and lipid metabolism.

Dopamine influences the hypothalamus by regulating the expression of α-MSH and orexin, meaning that D2 receptor antagonism can lead to increased hunger and subsequent weight gain. Moreover, D2 antagonism can cause hyperprolactinemia, which may further affect dietary and metabolic regulation [100]. Serotonin also plays a vital role in the hypothalamic centers that regulate energy metabolism. Serotonergic neurons can enhance POMC production through 5-HT2A/2C receptor activation, subsequently reducing appetite by increasing α-MSH secretion from POMC [42].

The ARC core is a critical sensor for energy homeostasis, sensitive to a range of peripheral signals such as leptin, orexin, insulin, GLP-1, cholecystokinin, and ghrelin. Clozapine and olanzapine are also potent antagonists of 5-HT2A/2C in the hypothalamus, which may influence their effects on glucose and lipid metabolism as well as weight gain [45]. Another significant factor affected by antipsychotic (AP) use is hypothalamic AMPK, or 5’AMP-activated protein kinase. This family of proteins is present in nearly all human cells and serves as a “sensor” for the cell’s energy status. AMPK activates in response to high energy demands, such as during extended fasting or intense physical exertion. It triggers a cascade of reactions aimed at producing ATP to restore critical energy levels (with caloric surplus leading to AMPK inhibition and energy expenditure leading to AMPK activation). Thus, AMPK plays a pivotal role in regulating energy balance and metabolism and is influenced by various neurotransmitters and neuropeptides via distinct receptors, many of which are also affected by antipsychotic medications [45].

AMPK is particularly abundant in the arcuate nucleus (ARC) and the ventromedial hypothalamus. When glucose levels in the brain decline, AMPK activation replenishes these vital levels for neuronal activity. As a result, AMPK stimulates hepatic gluconeogenesis and glycogenolysis by activating the sympathetic nervous system, which, in turn, boosts the secretion of hormones such as glucagon, corticosterone, and adrenaline. The activity of AMPK is modulated by circulating nutrient levels as well as anorexigenic signals like leptin and orexigenic signals. However, antipsychotics, especially second-generation antipsychotics (SGAs), can disrupt these sensory mechanisms.

Specifically, antipsychotics are shown to increase hypothalamic AMPK activity, primarily due to their antagonistic effects on H1 receptors. Antipsychotics with a strong affinity for H1 receptors, such as clozapine and olanzapine, are the most effective in activating AMPK, while others, like ziprasidone or lurasidone, have minimal impact [101].

4.5 Adiponectin

As discussed earlier, atypical antipsychotics (APs) interact with peripheral organs that regulate energy balance. This interaction occurs through various hormones and cytokines, which influence the central nervous system’s responses to energy demands by activating pathways that either suppress or stimulate appetite.

Adiponectin is a cytokine secreted by adipose tissue and is a member of the adipokine family of proteins. It serves as a crucial messenger, connecting adipose tissue with other organs. Notably, adiponectin receptors are widely expressed in the central nervous system (CNS). Adiponectin can cross the blood-brain barrier, allowing it to directly influence receptors located in the cortex, hypothalamus, and pituitary gland [102].

Adiponectin levels are inversely related to obesity; lower circulating levels of this cytokine are associated with insulin resistance (IR), and reduced adiponectin expression significantly correlates with both obesity and MetS. Conversely, elevated adiponectin levels are associated with improved insulin sensitivity, enhanced adipose tissue fat oxidation, decreased circulating fatty acid concentrations, and diminished intracellular triglyceride content in both the liver and muscle. Additionally, adiponectin exhibits strong anti-inflammatory properties, reducing the expression of adhesion molecules in endothelial cells and inhibiting the release of pro-inflammatory cytokines from macrophages. This action diminishes the cardiovascular risks associated with metabolic changes [12,103].

Beyond its insulin-sensitizing and anti-inflammatory effects, adiponectin also demonstrates anti-apoptotic, pro-angiogenic, anti-atherogenic, pro-adipogenic, and even antidepressant properties [103,104]. In animal studies, adiponectin treatment resulted in reduced blood levels of free fatty acids, triglycerides, and glucose [105]. Furthermore, higher adiponectin levels are associated with improvements in executive function and overall cognitive abilities, as well as a decreased risk of myocardial infarction and other cardiovascular events. These vital attributes position adiponectin as a promising biomarker for predicting cardiovascular and metabolic diseases [10].

Among various adipokines, adiponectin may significantly influence dysmetabolic conditions in individuals with schizophrenia receiving treatment with atypical antipsychotics, although findings across studies are not always consistent. Several factors may contribute to these discrepancies, including the specific antipsychotic medications used, the duration of treatment, and the demographic characteristics such as age, gender, and ethnicity of the participants [10].

The relationship between non-drug-naïve schizophrenia and adiponectin levels remains unclear. One study noted lower circulating adiponectin levels in normal-weight, first-episode, drug-naïve individuals with schizophrenia [106]. Another investigation by Lee et al. found that patients with schizophrenia had lower adiponectin concentrations compared to healthy controls. In both the schizophrenia and non-psychiatric groups, low levels of adiponectin-especially high molecular weight (HMW) adiponectin-were correlated with a higher body mass index, greater insulin resistance, decreased levels of HDL cholesterol, elevated levels of high-sensitivity C-reactive protein (hs-CRP), and an increased risk of coronary artery disease [107].

A recent meta-analysis indicated a trend toward reduced adiponectin levels in individuals with untreated schizophrenia. However, some heterogeneity within the sample suggests that a subset of individuals with schizophrenia may already have low baseline levels of adiponectin, placing them at a heightened risk for metabolic side effects induced by antipsychotic treatment [108].

Research has consistently demonstrated that antipsychotic medications (AP) lead to decreased blood levels of adiponectin [82]. The drugs most strongly linked to this reduction are clozapine (p < 0.001) and olanzapine (p = 0.04), both of which are also known for causing significant metabolic side effects. Additionally, the production and secretion of adiponectin are influenced by the presence of D2 and D3 receptors in fat cells. Antagonism of these receptors due to the use of antipsychotics can lead to changes in circulating adiponectin levels, ultimately resulting in metabolic dysfunction [108]. Furthermore, hyperprolactinemia, caused by antipsychotic blockade of dopamine inhibition on pituitary lactotrope cells, may also contribute to decreased adiponectin production in adipocytes, thereby disrupting energy homeostasis [10].

4.6 Leptin and the Leptin/Adiponectin Ratio

Leptin, an essential adipokine produced and secreted by adipose cells, plays a significant role in regulating body weight and is closely associated with obesity, insulin resistance, and the risk of MetS. Elevated leptin levels in the bloodstream, a condition known as hyperleptinemia, may also increase the risk of cardiovascular disease [10].

In patients with schizophrenia, particularly those undergoing treatment with atypical antipsychotics (SGA), heightened blood leptin levels have been observed. Hyperleptinemia might contribute to weight gain and increased adiposity related to antipsychotic medication [108]. While both leptin and adiponectin levels have traditionally been regarded as valuable biomarkers for predicting MetS, emerging research indicates that the leptin/adiponectin (L/A) ratio may serve as a more significant indicator than either hormone evaluated independently [109].

The L/A ratio shows a positive correlation with various metabolic parameters, such as body weight, body mass index (BMI), waist circumference, total cholesterol, triglycerides, LDL cholesterol, insulin levels, and, crucially, insulin resistance. Additionally, the L/A ratio is linked to inflammatory markers associated with obesity, such as blood levels of PCR and serum amyloid apoprotein A (SAA). Therefore, changes in the L/A ratio may be a vital biomarker for assessing the severity of adipose tissue dysfunction and associated cardiometabolic risks.

4.7 Ghrelin

Ghrelin is another key player in regulating energy balance. This orexigenic peptide, consisting of 28 amino acids, is primarily produced in the stomach. In humans, ghrelin triggers the release of growth hormone, enhances appetite, and promotes weight gain. Moreover, elevated levels of ghrelin in the bloodstream can influence adiponectin and other cytokine secretion, modify hepatic lipolysis, and increase the release of free fatty acids from adipose tissue [110]. Such actions contribute to the onset of MetS and T2DM.

A study by Zhang et al. highlighted the fluctuating effects of SGAs on serum ghrelin levels over time. Initially, there is an increase in ghrelin levels during the first few weeks of treatment, followed by a down-regulation linked to the negative feedback caused by drug-induced weight gain over the subsequent 2 to 6 weeks. Eventually, ghrelin levels may return to baseline or even exceed initial values during prolonged treatment. The impact of antipsychotics on ghrelin varies depending on the specific medication as well as factors related to the patient, including age, sex, dietary habits, lifestyle, physical and psychiatric comorbidities, and the use of other medications [111].

4.8 Emerging Mechanisms

Medications such as olanzapine can significantly reduce motor activity, thereby diminishing energy expenditure. This reduction may disrupt the balance between energy intake and consumption, contributing to weight gain. Research indicates that the sedative effects of antipsychotic medications (APs) also play a crucial role in lowering energy expenditure [112]. Thermogenesis, the process of heat production in organisms, is another critical factor influencing energy expenditure [112]. Studies in animal models have demonstrated that olanzapine can lower body temperature, potentially affecting energy use. Interestingly, individuals with schizophrenia who are not undergoing treatment exhibit a decrease in resting energy expenditure (REE) [113]. Together, these findings suggest a complex interplay between alterations in thermogenesis and REE, with antipsychotics potentially reducing resting energy expenditure by altering internal body temperature [12].

A novel approach has emerged in exploring the metabolic side effects of antipsychotics, particularly second-generation antipsychotics (SGAs). Disruptions in mitochondrial dynamics and insulin signaling are linked to an imbalance in the fusion/fission ratio within the mitochondrial network, resulting in an inefficient mitochondrial phenotype in muscle tissue [114]. This dysfunction impairs the activation of insulin-dependent pathways required for sufficient energy production and overall metabolic stability. Over the past twenty years, numerous studies have highlighted the functional relationship between mitochondrial efficiency and dynamics, which encompasses processes like fusion, fission, mitochondrial movement along the cytoskeleton, mitochondrial biogenesis, and mitophagy-a specialized type of autophagy that targets the selective degradation of mitochondria [114].

The regularity of these processes is directly tied to proper mitochondrial function. It’s essential to note that the majority of intracellular ATP, the energy currency of the cell, is produced within mitochondria, highly specialized organelles crucial for energy generation. Mitochondrial energy production in skeletal muscle relies on lipid metabolism, oxidative phosphorylation, and the Krebs cycle. Extensive research has established that mitochondrial functionality is a sensitive indicator of overall cellular health. Disruptions in insulin signaling and mitochondrial dysfunction are both clear markers of an abnormal metabolic response in skeletal muscle cells. Given these insights, several studies have identified distinct morphological differences in the mitochondrial network of obese and diabetic individuals [114,115].

In vitro evidence also suggests that metabolic changes induced by olanzapine are tissue-specific. By altering insulin sensitivity in the liver, skeletal muscle, and adipose tissue, these findings support the notion that olanzapine may contribute to generalized insulin resistance [116,117]. Additionally, olanzapine has been found to affect lipid metabolism by enhancing the uptake of free fatty acids in peripheral tissues and increasing lipid oxidation in muscle cells [117]. These events driven by olanzapine indicate a reduced availability of acetyl CoA in the mitochondrial matrix, which limits the supply of precursors for the tricarboxylic acid cycle (Krebs cycle)-a critical pathway that converts macronutrients from the diet, including proteins, carbohydrates, and fats, into ATP, the primary energy source for the body [114].

Interestingly, an in vitro study by Contreras-Shannon et al. demonstrated that clozapine, another metabolic-intensive second-generation antipsychotic (SGA), can modify mitochondrial morphology and affect ATP levels in insulin-sensitive cells in a dose-dependent manner [118]. These findings collectively bolster the hypothesis that mitochondrial dysfunction is a significant factor in olanzapine-induced MetS. Consequently, maintaining mitochondrial homeostasis should be considered a potential therapeutic target to mitigate the metabolic side effects associated with SGAs.

Should these findings be validated in human samples, it could reveal that SGAs impact one of the essential functions of living cells-ATP production within the mitochondria. Investigating the mechanisms behind the metabolic toxicity of SGAs, particularly in relation to mitochondrial dynamics, could illuminate the development of MetS, insulin resistance, weight gain, lipid accumulation, and hyperglycemia [114].

5. Interventions for Managing Metabolic Accrual Adverse Events

5.1 General Principles for Prescribing Antipsychotics

Antipsychotic medications (APs) are remarkably effective in managing the primary symptoms of schizophrenia. However, as with all substances listed in the official pharmacopoeia, it is essential to adhere to certain general principles to ensure optimal prescribing.

Firstly, initiate an antipsychotic only when the indication is appropriate, there is a clear expectation of benefit, and no safer or more feasible alternatives exist.

Secondly, select an antipsychotic tailored to the clinical situation and individual needs of the patient. For example, avoid prescribing medications that could cause orthostatic issues or hypotension in the elderly, those that may lead to significant weight gain in patients conscious of their weight, or drugs that prolong the QTc interval in individuals with a history of heart disease, arrhythmia, or syncope.

Thirdly, administer the lowest effective dose to each patient, and make necessary adjustments to the treatment plan. Fourthly, conduct a thorough cost-benefit risk assessment for every patient, particularly when side effects are present. Additionally, consider the patient’s other medications in relation to the antipsychotic, as they might amplify the adverse effects. Whenever possible, it is also advisable to avoid polypharmacy with multiple antipsychotics [23].

Finally, individuals on antipsychotic therapy should be closely monitored to detect potential metabolic side effects early. If such effects arise, lifestyle modifications should be strongly recommended as an initial response for those on antipsychotic medications.

Switching to an antipsychotic with a lower risk of metabolic complications may be an option; however, any decision to transition must consider the possible repercussions on clinical efficacy, including psychotic symptom management and relapse prevention, as well as the potential for new side effects associated with the alternative medication [23].

Before commencing antipsychotic treatment, a comprehensive cardio-metabolic evaluation is essential. The following factors should be included in the patient’s medical history:

• A history of cardiovascular disease, T2DM, or related conditions;
• A family history of early-onset cardiovascular disease, T2DM, or other similar illnesses;
• Lifestyle choices, including smoking, dietary habits, and physical activity levels;
• Measurements of weight and height to calculate body mass index (BMI) and waist circumference;
• Blood pressure readings;
• A detailed medication history, which should also prompt blood chemistry screening, including at least the following:

• Fasting blood glucose and/or glycated hemoglobin (HbA1c), insulin levels, and potentially the HOMA index;
• A lipid panel, measuring total cholesterol, HDL, LDL cholesterol, and triglycerides [8].

If there’s a change in antipsychotic medication, it is imperative to revisit all the steps outlined above.

Even after a diagnosis of T2DM or MetS has been established, many patients struggling with mental health issues still do not receive the appropriate and timely treatment they need. It is essential to understand that routine screening is merely the first step in addressing this gap. To facilitate better care, psychiatric centers should collaborate with diabetes clinics to create shared care pathways, ensuring a unified approach for individuals dealing with both mental illness and T2DM or MetS [8]. Such collaborative efforts would respond to recent calls to move beyond the traditional “silo” approach, where treatment for mental and physical health issues occurs in isolation. Instead, in accordance with the internationally recognized Declaration for Active and Healthy Living, these treatments should be integrated to promote comprehensive patient care (https://www.iphys.org.au/).

5.2 Monitoring Physical Health Risk Factors

National and international guidelines emphasize the importance of regularly monitoring a variety of indicators-both anthropometric and laboratory-based-to assess the clinical and metabolic status of patients undergoing antipsychotic (AP) treatment [8] (Table 3).

Table 3 Suggested monitoring timeline.

5.3 Interventions Targeting Lifestyle Changes

Addressing the risk of AP-induced dysmetabolism through lifestyle interventions is crucial due to its potential long-term effects on patient health. A sedentary lifestyle combined with a high-calorie diet, particularly in the context of AP medication use, can lead to weight gain, T2DM (T2D), and dyslipidemia. This weight gain also heightens social stigma associated with mental illness, often leading patients to discontinue their medication [119].

First-line treatment approaches typically incorporate principles of psychoeducation focused on exercise and balanced nutrition. Numerous studies have demonstrated that strategies based on psychoeducation, cognitive-behavioral components, and health programs can effectively prevent or mitigate metabolic disturbances [120].

A meta-analysis encompassing 17 studies on psychoeducational, cognitive-behavioral, nutritional, and physical activity interventions revealed an average weight reduction of over 3 percent, a notable result considering that the World Health Organization (WHO) and National Institutes of Health (NIH) consider a 5-10% reduction an optimal target [121].

Numerous interventions have been tested in inpatient and outpatient mental health settings to decrease risk factors. Diet and exercise are the mainstays of weight-loss treatment. Several studies demonstrate the effectiveness of psychoeducation, diet, and physical activity interventions in decreasing and managing antipsychotic-induced weight gain. Furthermore, aerobic exercise has been shown to improve cognitive deficits, total symptom severity, including positive and negative symptoms, depression, quality of life, and global functioning. High-intensity interval endurance training is a feasible and effective way to improve cardiorespiratory fitness and metabolic parameters.

Lifestyle and physical activity interventions are safe and effective in promoting weight reduction or maintenance and can be implemented cost-effectively, safely, and improve quality of life [122,123,124].

The NIH offers practical guidance emphasizing the importance of proper nutrition, increased physical activity, and behavioral therapy. Behavioral strategies are designed to enhance executive function, problem-solving abilities, and stress management, and are typically recommended for a minimum of six months [121].

In the literature, interventions range from simple self-help manuals to more structured psychological therapies, differing in format, duration, and session frequency. Each therapy should be tailored to the individual patient, particularly taking into account symptom severity and encouraging small, achievable daily changes, such as eliminating sugary beverages and adding 2,000 to 3,000 steps a day. A case-control study involving 70 patients treated with olanzapine demonstrated success in weight maintenance over a four-month period when they participated in a weight-control intervention [125].

Other successful strategies for preventing or reducing weight gain include a multidisciplinary psychoeducational approach that offers strong motivational support, like maintaining a daily diary to track food intake and exercise, which can help modify poor eating habits [126]. Additionally, psychoeducation plays a vital role in raising patient awareness about their health status and the side effects of medications, ultimately aiming to enhance treatment adherence. More rigorous treatment modalities, such as cognitive-behavioral therapy (CBT), have also shown promise. For instance, Webber et al. reported favorable outcomes from a group cognitive-behavioral intervention (one hour per week for sixteen weeks) as part of a diabetes prevention program for patients on antipsychotics [127].

Most psychological interventions aim to alter dysfunctional beliefs and cognitive biases that contribute to unhealthy eating habits. By improving emotional states and the perceptions of hunger and satiety, these approaches promote healthier food-related behaviors.

Additionally, strategies such as role-playing, problem-solving exercises, motivational support, food diaries, and tailored exercise programs can help patients with psychiatric conditions manage weight gain and prevent metabolic complications.

5.4 Pharmacological Interventions

When dietary management and other established non-pharmacological interventions fail to address weight gain or related metabolic issues, appropriate pharmacotherapy must be considered. It is noteworthy that a significant number of patients with psychotic disorders suffering from MetS, obesity, or T2DM are not receiving the necessary pharmacological treatment for these complications [128].

5.4.1 Metformin

Metformin has emerged as one of the most effective medications for addressing antipsychotic-induced weight gain and T2DM [23]. Its use is suggested when lifestyle modifications do not yield satisfactory outcomes. As part of the biguanide class, Metformin serves as the primary drug for treating T2DM and MetS.

By activating AMP-activated protein kinase (AMPK) in the liver and other tissues, Metformin reduces hepatic glucose production and fat synthesis, enhances fatty acid oxidation, and improves glucose uptake from the bloodstream. Moreover, it aids in weight management and boosts insulin sensitivity. A recent review indicated that Metformin demonstrated significant effectiveness in preventing weight gain and managing insulin resistance, as evidenced in four out of five studies involving patients experiencing metabolic side effects from antipsychotic medication [129].

Furthermore, Metformin may counter some effects of antipsychotics at the hypothalamic level. Prolonged treatment with olanzapine can lead to increased phosphorylation of the AMPK enzyme in hypothalamic centers; however, Metformin appears to reduce the activity of this enzyme, positively influencing food intake and glucose regulation [130].

Oral Metformin administration also enhances postprandial GLP-1 (glucagon-like peptide 1) levels in diabetic patients. Through its AMPK-dependent action on intestinal L-cells that secrete GLP-1, Metformin helps lower blood glucose levels. Additionally, it exhibits cytoprotective properties, stimulating the proliferation of pancreatic beta cells while reducing cell apoptosis [130]. In recent research, it was discovered that metformin treatment could reverse these olanzapine-induced metabolic changes, such as increased body weight, elevated blood glucose, higher triglycerides and LDL levels, and lower HDL levels, while also alleviating intestinal dysbiosis by improving the Firmicutes/Bacteroidetes ratio in rats [131]. Collectively, these preclinical findings underscore the interplay between gut dysbiosis and metabolic alterations induced by antipsychotic (AP) medications.

Despite its benefits, studies suggest that weight loss associated with Metformin therapy tends to be modest, typically ranging from 2 to 4 kg. Clinical experience indicates that patients often do not exceed a weight loss of 5 to 6 kg, particularly if not accompanied by significant lifestyle changes. The side effects of Metformin are generally mild and transient, including metallic taste, nausea, bloating, abdominal discomfort, and diarrhea [14,132].

Metformin is contraindicated for individuals with a glomerular filtration rate below 30 ml/min, and its use is not recommended for those with a filtration rate between 30 and 45 ml/min. Additionally, excessive alcohol consumption and liver failure can increase the risk of lactic acidosis associated with Metformin.

Despite certain limitations, metformin therapy can be particularly beneficial for patients who are on antipsychotic medications and also have prediabetes or diabetes. Even individuals with normal blood glucose levels can safely use metformin for weight management. The recommended dosage range is 500 to 2550 mg per day, though it is advisable to start at a lower dose, between 500 and 1000 mg per day, and gradually increase it.

The optimal duration of metformin treatment varies by individual. According to obesity guidelines from the American College of Cardiology (ACC) and the American Heart Association (AHA), it is recommended to consider discontinuing weight-loss medications after 12 weeks at the maximum dosage if the patient has lost less than 5% of their initial body weight [133]. Based on clinical experience, discontinuation may also be appropriate after 6 months of treatment, particularly for weight loss purposes, if no further benefits are observed. However, if metformin proves effective in mitigating weight gain during antipsychotic treatment and is well tolerated, it may be beneficial to continue its use for the duration of the antipsychotic therapy.

5.4.2 GLP-1 Receptor Agonists

Regarding GLP-1 analogs and GLP-1 receptor agonists, glucagon-like peptide 1 (GLP-1) is a hormone secreted by L-cells in the gut that promotes insulin secretion and inhibits glucagon release from the pancreas, responding to a rise in blood glucose after meals. GLP-1 has several functions, including slowing gastric emptying to enhance feelings of fullness and directly reducing appetite through its action on the central nervous system’s hunger-regulating centers. Additionally, it is believed to offer protective effects on pancreatic beta-cells and the myocardium [84].

GLP-1 analogs and GLP-1 receptor agonists simulate the effects of endogenous GLP-1, enhancing its local and systemic actions. Notably, these medications increase insulin secretion in proportion to blood glucose levels, which helps prevent hypoglycemia. Aside from improving blood glucose levels, they also promote weight loss by influencing appetite and satiety centers [134].

GLP-1 analogs such as lixisenatide, liraglutide, and dulaglutide were approved for T2DM (T2D) treatment in 2006; at higher doses, they facilitate weight reduction. Subsequently, between 2019 and 2023, two additional GLP-1 analogs, semaglutide and tirzepatide, received approval for treating T2D and obesity in individuals with a BMI greater than 30 or a BMI between 27 and 30 with associated conditions such as hypertension, hypercholesterolemia, or T2DM [135].

In a notable study conducted by Lykkegard et al., female rats treated solely with olanzapine for 14 days showed significant changes when subsequently administered liraglutide. The treatment effectively reversed the weight gain associated with olanzapine, reduced food intake, normalized glucose tolerance, and decreased mesenteric and retroperitoneal fat. Similarly, there was a clinical case involving a schizophrenic woman with T2D induced by clozapine. After three months of treatment with liraglutide, she experienced a weight loss of 6 kg, with her glycated hemoglobin stabilizing at 6.1% [136].

A recent meta-analysis conducted in 2022 examined the effectiveness of various medications for treating weight gain in patients with schizophrenia, specifically those experiencing significant weight increases due to antipsychotic treatments. This analysis included three randomized controlled trials-two focusing on liraglutide and one on naltrexone-bupropion-as well as an unpublished open-label study involving naltrexone-bupropion and six observational studies (five with liraglutide and one with semaglutide). The findings indicated that liraglutide led to statistically significant improvements in several measures, including weight, body mass index, waist circumference, HbA1c, total cholesterol, and LDL cholesterol levels. Collectively, these results support the use of liraglutide as a promising option for managing weight gain associated with antipsychotic medications [137].

These findings are noteworthy as they emphasize the necessity for psychiatrists to synchronize better their management of dysmetabolism resulting from psychiatric medications with the guidelines proposed by endocrinologists and cardiologists for treating obesity [137,138].

When considering cost-effectiveness, liraglutide shows better tolerability; however, the requirement for daily subcutaneous injections renders it impractical for many patients. Additionally, liraglutide’s current price is significantly higher than that of commonly used treatments like orlistat and metformin, which may make it financially unfeasible for widespread implementation [138].

On the other hand, semaglutide, which has received approval from the FDA and EMA for obesity treatment, holds promise for psychiatric applications as well. A recent study examined the effectiveness of semaglutide on a modest sample of patients who experienced substantial weight gain while on antipsychotic medication. Treatment with semaglutide, up to 2 mg per week, was initiated for patients whose weight decreased by less than 5% or who continued to meet MetS criteria despite suboptimal metformin treatment at the maximum tolerated dosage (1500-2000 mg/day) for 3 months [138].

The results at the 3, 6, and 12-month marks demonstrated significant weight loss: 4.56 ± 3.15 kg (p < 0.001), 5.16 ± 6.27 kg (p = 0.04), and 8.67 ± 9 kg (p = 0.04), respectively, with side effects being well tolerated [89]. Additionally, a recent case report highlighted the use of semaglutide in a 50-year-old obese woman with T2DM and schizophrenia, who was part of a multidisciplinary treatment team. Upon starting semaglutide at 0.5 mg, the patient reported a marked reduction in hunger. After six months, her HbA1c was well controlled, and she had lost over 10 kg without a decrease in skeletal muscle mass, as measured by impedance. Specifically, her weight decreased from 81.2 kg to 69.3 kg, fat mass from 41.4 kg to 23.8 kg, and muscle mass from 7.3 kg to 8.1 kg-indications of improved insulin sensitivity [139].

Unlike liraglutide, which requires daily administration, semaglutide can be injected subcutaneously once a week, similar to some long-acting injectable (LAI) antipsychotics. This makes it a potentially easier fit for integration into treatment plans for patients with schizophrenia, although current efficacy data on semaglutide remain limited.

5.4.3 Other Drugs

As for alternative medications, it is important to note that antipsychotics often enhance feelings of hunger. A possible pharmacological approach could involve exploring appetite-suppressing medications. Several drugs have been assessed for this purpose, but are not generally recommended due to various concerns: orlistat has high discontinuation rates; the effectiveness of amantadine, melatonin, and zonisamide in patients on antipsychotics remains inadequately documented; and only minimal benefits have been observed with treatments such as atomoxetine, dextroamphetamine, famotidine, and fluvoxamine [23].

One potential solution is reboxetine, which is a serotonin-norepinephrine reuptake inhibitor (SNRI). Increasing norepinephrine levels may help with weight loss by suppressing appetite. A double-blind, placebo-controlled study investigated reboxetine’s effectiveness in preventing or alleviating weight gain associated with olanzapine. Participants in the control group, who received olanzapine alongside a placebo, experienced an average weight gain of 5.5 kg over six weeks. In contrast, those treated with olanzapine and reboxetine gained an average of only 2.5 kg [140].

The effectiveness of fluoxetine, a selective serotonin reuptake inhibitor (SSRI), in alleviating hunger in patients treated with antipsychotics (APs) remains uncertain, as the evidence supporting its efficacy is largely limited to small and often temporary improvements [141].

Topiramate is another medication that has been investigated for its potential to mitigate weight gain, with reports indicating weight reduction in 10-20% of those treated. The extent of weight loss is influenced by several factors, including the patient’s initial body mass index (BMI) and the duration of treatment. The appetite-suppressing effects of topiramate appear to be linked to decreased glutamatergic activity and alterations in hypothalamic neuropeptide Y levels [142]. Although current guidelines do not endorse the use of topiramate for managing weight gain associated with antipsychotic use, there is some evidence supporting its application. Several randomized, double-blind, placebo-controlled studies ranging from 8 to 12 weeks have demonstrated modest weight loss, with reductions between 1.2 and 5.6 kg. However, it is important to note that topiramate has been associated with significant side effects, including psychomotor slowing, paresthesias, dizziness, and headaches [143,144].

Another option for controlling weight loss has been focusing on the histaminergic system. Famotidine, nizatidine, and ranitidine are H2 receptor antagonists used to treat gastroesophageal reflux disease (GERD), which reduces acid production and has related weight-loss effects. Regarding H2 receptor antagonists, it’s uncertain if gastric histamine receptor antagonism directly causes weight loss or if other mechanisms are involved. Histamine is involved in the control of energy and feeding and is known to modulate the activity of leptin [145]. Thus, it is conceivable that H2 receptor antagonists will combine with these drugs to cause weight reduction. A histamine enhancer with H1 agonistic and H3 antagonistic qualities, betahistine has been linked to weight loss [146].

Due to the H1-receptor antagonistic reactivity of numerous antipsychotics, including clozapine, olanzapine, and quetiapine, betahistine may alleviate cognitive symptoms in schizophrenia by reducing the sedative effects of antipsychotics [46,147]. Furthermore, H3 receptors are not affected by the majority of antipsychotics [148].

The use of bupropion for weight management in this patient population is backed by very limited evidence. A small study involving just eight participants reported a 3.4 kg reduction in weight gain with olanzapine plus bupropion treatment [14]. At present, there is no literature supporting the combination of bupropion/naltrexone, which has received FDA and AIFA approval, or phentermine/topiramate, also FDA-approved for obesity treatment, in addressing antipsychotic-induced weight gain. Furthermore, there are warnings regarding the potential risks of suicidal ideation and behavior associated with these medications [14].

In contrast, orlistat is designed to assist with weight management by inhibiting fat absorption from food, thereby reducing caloric intake. While orlistat’s effectiveness in promoting weight loss among patients gaining weight due to antipsychotics is generally modest, clinical trial data indicate that individuals on orlistat combined with lifestyle changes-such as diet and exercise-lose approximately 2-3 kg more per year than those receiving standard treatment [149]. Notably, orlistat tends to be more effective in preventing weight regain than in facilitating weight loss. Gastrointestinal side effects, including bloating, abdominal cramps, and steatorrhea (excessive fat in stools), are particularly noteworthy; however, these issues often diminish over time [150].

When it comes to hyperlipidemia, this common yet often asymptomatic condition is characterized by alterations in plasma lipoproteins, leading to elevated levels of fats-either cholesterol or triglycerides-in the bloodstream. Lipoproteins, including chylomicrons, VLDL, LDL, and HDL, are macromolecules formed by the combination of proteins with various lipids, such as cholesterol, cholesterol esters, phospholipids, and triglycerides.

Low-Density Lipoproteins (LDLs) play a crucial role in transporting cholesterol throughout the bloodstream, delivering it to tissues for cell wall formation and hormone production. Once they have accomplished this task, LDLs are degraded in the liver. However, an excess of LDL cholesterol can lead to the unwanted deposition of cholesterol in the walls of blood vessels, beneath the endothelium, ultimately contributing to the development of atherosclerosis.

In contrast, High-Density Lipoproteins (HDLs) serve a protective function. They work to gather excess cholesterol that has accumulated in artery walls and transport it back to the liver for excretion through bile. Notably, even a modest increase of 1 mg/dl in HDL cholesterol can reduce cardiovascular risk by 2 to 3 percent, and higher HDL levels have been linked to a longer lifespan [14,151].

When it comes to managing hyperlipidemia, statins are widely recognized as the cornerstone of treatment. Statins function by inhibiting the enzyme hydroxymethylglutaryl-CoA reductase, which in turn reduces the liver’s production of endogenous cholesterol. This action reduces intracellular cholesterol levels, leading to increased LDL receptor expression. As a result, there is enhanced uptake and internalization of LDL, which ultimately lowers circulating cholesterol levels [14].

To assess cardiovascular risk, the cardiovascular risk index is calculated by dividing total cholesterol by HDL cholesterol levels, measured from a fasting blood sample. An acceptable risk index is considered to be less than 5 for men and less than 4.5 for women. When evaluating cardiovascular risk, the ratio of total cholesterol to HDL is more informative than the LDL to HDL ratio. This is because total cholesterol is also influenced by VLDL levels, which are high in triglycerides and linked to increased cardiovascular risk (Total cholesterol = HDL + LDL + VLDL) [14].

In contrast, an individual scoring system provides a straightforward yet effective means of estimating the likelihood of experiencing a major cardiovascular event, such as a heart attack or stroke, within the next decade. This estimation is based on eight risk factors: sex, age, diabetes, smoking status, systolic blood pressure, total cholesterol, HDL cholesterol, and any antihypertensive treatment (https://www.cuore.iss.it/valutazione/calc-rischio), (https://tools.acc.org/ascvd-risk-estimator/default.aspx#page_recommendation).

Individuals with a 10-year ASCVD risk score ranging from 7.5% to 20% are classified as being at intermediate risk for a cardiovascular event, for whom a moderate-intensity statin may be advised, especially if additional risk factors are present. These factors include MetS, chronic kidney disease, chronic inflammatory conditions (like rheumatoid arthritis or psoriasis), high triglyceride levels (above 175 mg/dL), elevated LDL-C (≥160 mg/dL), high-sensitivity C-reactive protein (≥2 mg/L), or a family history of hyperlipidemia or atherosclerotic cardiovascular disease [14]. Those with an ASCVD risk score exceeding 20% are deemed high risk, and the goal of statin therapy should be to reduce LDL by at least 50%.

Moderate-intensity statins typically achieve a 30% to 45% reduction in LDL levels, while high-intensity statins, such as atorvastatin and rosuvastatin at their maximum doses, can lower cholesterol levels by more than 50% from baseline. Statins are not only effective in reducing LDL but can also decrease triglyceride levels by 22% to 45% and increase HDL by 5% to 10% [152].

The statin dosage is a crucial consideration, as the greatest LDL reduction generally occurs with the initial dose; doubling the dose can yield an additional 4% to 7% reduction [153].

Recent research by Liu et al. indicates that administering simvastatin alongside olanzapine resulted in lower plasma lipid levels and reduced liver fat concentration in rats. This effect was associated with upregulation of several genes, including SREBP 1 and FASN (fatty acid synthase), as well as CLY (ATP citrate lyase), ACC (acetyl-CoA-carboxylase), and SCD-1 (stearoyl-CoA-desaturase-1), with expression levels increasing following olanzapine treatment. Additionally, statins are known to diminish various inflammatory markers such as C-reactive protein, interleukin-1β, and tumor necrosis factor-α [154].

Fibrates and niacin are two effective medications known for lowering triglyceride levels and slightly reducing LDL cholesterol. For patients who experience persistently high triglyceride levels due to hypertriglyceridemia, it is advisable to add a fibrate or omega-3 fatty acids to their statin therapy to mitigate the risk of pancreatitis [153].

Ezetimibe represents a new class of drugs designed to lower cholesterol by inhibiting its intestinal absorption. In patients with hypercholesterolemia, ezetimibe has been proven to decrease total cholesterol levels by approximately 13 to 15% and LDL cholesterol by around 18% when administered alone. The complementary mechanisms of ezetimibe, which reduce intestinal absorption, and statins, which limit liver production of cholesterol, enhance the overall effectiveness when combined. Furthermore, ezetimibe can be prescribed alone when statins are either contraindicated or poorly tolerated [155].

5.4.4 # Hypertension

According to the 2018 guidelines set by the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH), optimal blood pressure is defined as a systolic level below 120 mmHg and a diastolic pressure below 80 mmHg. Hypertension is diagnosed when systolic pressure exceeds 140 mmHg and/or diastolic pressure exceeds 90 mmHg. Isolated systolic hypertension is noted when only the systolic number is elevated, specifically at or above 140 mmHg [156].

Classification of Hypertension as per 2018 ESC/ESH Guidelines (Table 4):

Table 4 Classification of Hypertension.

For adults at risk of cardiovascular disease, nonpharmacologic interventions are recommended, alongside antihypertensive medication for those with Grade 2 hypertension or Grade 1 hypertension with an annual ASCVD risk of 10% or more. For individuals with Grade 2 hypertension or higher, the combination of two antihypertensive agents from different classes is advised [156].

The overarching goals of treatment include: (1) maximizing long-term reduction in overall cardiovascular risk, (2) lowering blood pressure to below 140/90 mmHg, and ideally to 130/80 mmHg in diabetics and patients at very high risk of complications such as stroke, myocardial infarction, or renal dysfunction [157].

First-line treatments for hypertension typically consist of thiazide diuretics, angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), and calcium channel blockers (CCBs). There is insufficient evidence to recommend beta-blockers as a first-line treatment for hypertension unless accompanied by other cardiovascular conditions like heart failure or ischemic disease. When initiating antihypertensive treatment, it is crucial to consider individual factors such as comorbidities, concurrent medications, age, race, and adherence to medications [157].

The ideal treatment for hypertension in individuals with MetS remains uncertain. Current guidelines from the European Society of Cardiology (ESC) and the European Society of Hypertension suggest that MetS may be a contraindication to the use of thiazide diuretics. These medications can potentially increase insulin resistance, leading to a higher likelihood of developing diabetes mellitus, and may also exacerbate dyslipidemia [119]. In the absence of specific treatment directives, hypertension management for patients with MetS may favor the use of ACE inhibitors, angiotensin II receptor blockers, or calcium channel blockers, as these options are less likely to elevate blood glucose levels.

6. Conclusion

Individuals with psychosis often contend with numerous medical challenges that significantly diminish their quality of life and contribute to higher mortality rates. This situation arises from the severity and diversity of their condition, unhealthy lifestyle choices, and potential side effects of antipsychotic medications. Consequently, patients with schizophrenia are at a greater risk for cardiometabolic disorders compared to those without psychiatric conditions, particularly exhibiting a heightened susceptibility to MetS, which in turn exacerbates their risk for various cardiometabolic diseases.

Certain antipsychotic medications are linked to a range of side effects, including moderate weight gain, hypertension, and adverse impacts on lipid and glucose metabolism. Notably, drugs such as clozapine, olanzapine, and quetiapine are associated with significant weight gain, leading to an elevated risk of serious health issues related to overweight and obesity. These complications may encompass degenerative joint disorders, T2DM and its associated complications, cardiovascular and cerebrovascular diseases, liver and kidney disorders, and specific types of cancer.

The mechanisms driving metabolic dysregulation in these patients are intricate and multifaceted, involving various neurotransmitter and hormonal systems that interact with genetic predispositions and individual lifestyle choices, alongside the particular antipsychotic medication prescribed.

Antipsychotic drugs primarily function as weak D2 receptor blockers, yet their effects extend beyond D2 antagonism, potentially engaging other receptor targets such as serotonin (5-HT) receptors. Notable factors influencing the effectiveness and side effects of different antipsychotic medications include their affinity for 5-HT2A/D2 and 5-HT2C/D2 receptors and their rapid dissociation constants from the D2 receptor. Moreover, various antipsychotics exhibit distinct receptor actions, including partial antagonism of 5-HT1, H1 histamine receptors, α2 adrenergic receptors, and M3 muscarinic receptors. They also impact brain-derived neurotrophic factor (BDNF) production and the glycine transporter (GlyT). The influence of antipsychotics extends beyond the central nervous system, affecting peripheral organs crucial for metabolic regulation, including the pancreas, adipose tissue, skeletal muscle, and the gastrointestinal tract, particularly concerning the gut microbiota, thereby altering the gut-brain axis.

Atypical antipsychotics (APs), particularly second-generation antipsychotics (SGAs), influence a variety of neuropeptides that regulate appetite and food intake. These include neuropeptide Y (NPY), agouti-related peptide (AgRP), α-melanocyte-stimulating hormone (α-MSH), adiponectin, leptin, and ghrelin. Additionally, they affect mechanisms of energy expenditure and metabolic homeostasis through the mitochondrial system. Therefore, it is crucial to select the most appropriate antipsychotic from the available options based on individual patient characteristics. If the patient’s condition allows, it is preferable to avoid the complexity of polypharmacy involving multiple antipsychotics.

Regular monitoring is essential for anyone prescribed antipsychotic medication to detect potential metabolic side effects early on. It is recommended to periodically assess body mass index (BMI), blood glucose levels, insulin resistance, lipid profiles, blood pressure, and cardiovascular health in these patients. Should metabolic side effects arise, lifestyle modifications such as diet and exercise should be the first-line intervention, though these can be challenging to implement for this patient group.

If these nonpharmacological strategies prove insufficient in managing weight gain or other metabolic complications, appropriate medical treatment may be warranted. Interestingly, a significant number of patients with psychotic disorders who experience MetS, obesity, T2DM, or hypertension often remain untreated for these conditions. Among the available options for managing these metabolic issues, metformin is commonly prescribed, while GLP-1 receptor agonists and appetite suppressants may be considered if metformin proves ineffective. However, the existing literature on these alternatives is limited and sometimes inconsistent.

In addition to these treatments, medications for controlling dyslipidemia and hypertension should not be overlooked, even though they are infrequently utilized in patients with psychotic disorders. Statins are a mainstay in the treatment of dyslipidemia, while thiazide diuretics, ACE inhibitors, angiotensin receptor blockers (sartans), and calcium channel blockers are typically first-line antihypertensive therapies. However, caution is advised when using thiazide diuretics in patients with MetS, as they may exacerbate blood glucose levels.

Antipsychotic-associated metabolic dysfunction reflects a complex interplay of central and peripheral mechanisms involving neurotransmitter and neuropeptide signaling, mitochondrial function, and gut-brain axis regulation; however, substantial gaps remain in translating this mechanistic knowledge into effective, routinely implemented clinical strategies, as metabolic comorbidities in patients with psychotic disorders are frequently underrecognized and undertreated. These challenges highlight the need for personalized interventions, including individualized antipsychotic selection and tailored metabolic risk management based on patient-specific biological and clinical profiles. Integrating systematic metabolic monitoring and proactive cardiometabolic care into routine psychiatric practice is therefore essential to reduce long-term morbidity and mortality and to improve overall treatment outcomes.

Abbreviations

Author Contributions

WM: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Validation, Writing – original draft, Writing – review & editing. RC: Data curation, Methodology, Project administration, Writing – original draft, Writing – review & editing. MM: Data curation, Methodology, Project administration, Writing – original draft, Writing – review & editing. MFM: Data curation, Methodology, Project administration, Writing – original draft, Writing – review & editing. LR: Investigation, Visualization, Writing – review & editing. BS: Investigation, Visualization, Writing – review & editing. AC: Supervision, Writing – review & editing.

Competing Interests

The authors have declared that no competing interests exist.