Effects of long-term antipsychotics treatment on body weight: A population-based cohort study

Predicting maintenance lithium response for bipolar disorder from electronic health records-a retrospective study

Background

Optimising maintenance drug treatment selection for people with bipolar disorder is challenging. There is some evidence that clinical and demographic features may predict response to lithium. However, attempts to personalise treatment choice have been limited.

Method

We aimed to determine if machine learning methods applied to electronic health records could predict differential response to lithium or olanzapine. From electronic United Kingdom primary care records, we extracted a cohort of individuals prescribed either lithium (19,106 individuals) or olanzapine (12,412) monotherapy. Machine learning models were used to predict successful monotherapy maintenance treatment, using 113 clinical and demographic variables, 8,017 (41.96%) lithium responders and 3,831 (30.87%) olanzapine responders.

Results

We found a quantitative structural difference in that lithium maintenance responders were weakly predictable in our holdout sample, consisting of the 5% of patients with the most recent exposure. Age at first diagnosis, age at first treatment and the time between these were the most important variables in all models.

Discussion

Even if we failed to predict successful monotherapy olanzapine treatment, and so to definitively separate lithium vs. olanzapine responders, the characterization of the two groups may be used for classification by proxy. This can, in turn, be useful for establishing maintenance therapy. The further exploration of machine learning methods on EHR data for drug treatment selection could in the future play a role for clinical decision support. Signals in the data encourage further experiments with larger datasets to definitively separate lithium vs. olanzapine responders.

Aripiprazole dose associations with metabolic adverse effect: Results from a longitudinal study

OBJECTIVE

Weight gain, blood lipids and/or glucose dysregulation can follow aripiprazole treatment onset. Whether aripiprazole dosage is associated with an increase in these metabolic parameters remains uncertain. The present study investigates aripiprazole dose associations with weight change, blood glucose, lipids, and blood pressure.

METHODS

422 patients taking aripiprazole for a minimum of three weeks to one year were selected from PsyMetab and PsyClin cohorts. Associations between aripiprazole dose and metabolic outcomes were examined using linear mixed-effect models.

RESULTS

Aripiprazole dose was associated with weight change when considering its interaction with treatment duration (interaction term: -0.10, p < 0.001). This interaction resulted in greater weight gain for high versus low doses at the beginning of the treatment, this result being overturned at approximately five months, with greater weight increase for low versus high doses thereafter. LDL and HDL cholesterol levels were associated with aripiprazole dose over five months independently of treatment duration, with an average of 0.06 and 0.02 mmol/l increase for each 5 mg increment, respectively (p = 0.033 and p = 0.016, respectively). Furthermore, mean dose increases were associated with greater odds (+30 % per 5 mg increase) of clinically relevant weight gain (i.e., ≥7 %) over one year (p = 0.025).

CONCLUSION

Aripiprazole dose was associated with one-year weight changes when considering its interaction with treatment duration. Increasing its dose could lead to metabolic worsening over the first five months of treatment, during which minimum effective doses should be particularly preferred.

Effects of Combined Therapy of Olanzapine and Samidorphan on Safety and Metabolic Parameters in Schizophrenia Patients: A Meta-Analysis

Purpose

This meta-analysis intended to evaluate the safety and metabolic effects of the combination of olanzapine (OLZ) and samidorphan (SAM) in the treatment of schizophrenia (SCZ) patients.

Patients and Methods

We searched for the English and Chinese databases for randomized controlled trials (RCTs) on the OLZ combined with SAM for SCZ. The English databases included PubMed, Web of Science, EMbase, and Cochrane Library, however, Chinese databases included Chinese Biology Medicine (CBM), VIP, Wanfang, and China National Knowledge Infrastructure (CNKI). All database searches were due by May 31, 2023. Using Review Manager 5.4 software, a meta-analysis was conducted following a literature review and data extraction.

Results

This study included five RCTs involving 1781 patients. Regarding safety, the meta-analysis revealed that the probability of weight gain was reduced in the OLZ and SAM group than in the OLZ group (RR = 0.83, 95% CI (0.69, 0.99), P < 0.05). Statistically, the incidence of severe adverse safety events, dry mouth, headache, drowsiness, death, and suicidal perception events was insignificant (P > 0.05); in terms of metabolism, compared with the OLZ group, the OLZ plus SAM group reduced total cholesterol (TC) levels (MD = -3.58, 95% CI (-6.81, -0.34), P < 0.05). However, it had no significant effect on metabolic indices, including low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, glucose, and insulin index (P > 0.05).

Conclusion

In patients with SCZ, treatment with the combination of OLZ and SAM decreased the incidence of weight gain adverse events and TC levels; nevertheless, it did not affect other adverse events or metabolic parameters. These findings provide clinicians with evidence-based guidance and support for drug selection. However, it is crucial to confirm these findings through further high-quality research.

Metabolic side effects in persons with schizophrenia during mid- to long-term treatment with antipsychotics: a network meta-analysis of randomized controlled trials

Metabolic side effects of antipsychotic drugs can have serious health consequences and may increase mortality. Although persons with schizophrenia often take these drugs for a long time, their mid- to long-term metabolic effects have been studied little so far. This study aimed to evaluate the mid- to long-term metabolic side effects of 31 antipsychotics in persons with schizophrenia by applying a random-effects Bayesian network meta-analysis. We searched the Cochrane Schizophrenia Group's Study-Based Register of Trials (up to April 27, 2020) and PubMed (up to June 14, 2021). We included published and unpublished, open and blinded randomized controlled trials with a study duration >13 weeks which compared any antipsychotic in any form of administration with another antipsychotic or with placebo in participants diagnosed with schizophrenia. The primary outcome was weight gain measured in kilograms. Secondary outcomes included "number of participants with weight gain", fasting glucose, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. We identified 137 eligible trials (with 35,007 participants) on 31 antipsychotics, with a median follow-up of 45 weeks. Chlorpromazine produced the most weight gain (mean difference to placebo: 5.13 kg, 95% credible interval, CrI: 1.98 to 8.30), followed by clozapine (4.21 kg, 95% CrI: 3.03 to 5.42), olanzapine (3.82 kg, 95% CrI: 3.15 to 4.50), and zotepine (3.87 kg, 95% CrI: 2.14 to 5.58). The findings did not substantially change in sensitivity and network meta-regression analyses, although enriched design, drug company sponsorship, and the use of observed case instead of intention-to-treat data modified the mean difference in weight gain to some extent. Antipsychotics with more weight gain were often also among the drugs with worse outcome in fasting glucose and lipid parameters. The confidence in the evidence ranged from low to moderate. In conclusion, antipsychotic drugs differ in their propensity to induce metabolic side effects in mid- to long-term treatment. Given that schizophrenia is often a chronic disorder, these findings should be given more consideration than short-term data in drug choice.

The metabolic adverse effects of antipsychotic use in individuals with intellectual and/or developmental disability: A systematic review and meta-analysis

OBJECTIVE

Individuals with intellectual and/or developmental disability (IDD) are often prescribed antipsychotics (APs). However, despite their known propensity to cause metabolic adverse effects, including weight gain, diabetes, and increased risk of cardiovascular events, there is currently a limited body of literature describing the metabolic consequences of AP use in this population.

METHODS

We searched MEDLINE, EMBASE, PsychINFO, CENTRAL, and CINAHL databases to identify all randomized trials that reported on the metabolic effects of APs in individuals with IDD. Random effects meta-analyses were used to examine weight gain as both a continuous and dichotomous outcome.

RESULTS

Eighteen randomized trials met our inclusion criteria with a total of 1376 patients across a variety of IDDs. AP use was associated with significantly greater weight gain compared with placebo (Continuous: mean difference = 1.10 kg, [0.79, 1.40], p < 0.00001, I²  = 54%; Dichotomous: odds ratio = 3.94, [2.15, 7.23], p < 0.00001, I²  = 0). Sub-group analysis revealed no significant effect of AP type. Data regarding the effects of APs on other metabolic outcomes were limited.

CONCLUSION

This review (PROSPERO # CRD42021255558) demonstrates that AP use is associated with significant weight gain among patients with IDD. Concerningly, most reported studies were in children and adolescents, which sets up an already vulnerable population for adverse medical sequalae at an early age. There was also a lack of long-term studies in adults with IDD. Further studies are required to better understand how AP use affects metabolic parameters in this group of individuals.

Antipsychotic-Induced Weight Gain: Dose-Response Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Weight gain is among the most important side-effects of antipsychotics. It is, however, unclear whether it is associated with antipsychotic doses. We aimed to fill this gap with a dose-response meta-analysis.

METHODS

We searched multiple electronic databases (last update search June 2021) for all fixed-dose studies that investigated 16 second-generation antipsychotics and haloperidol in adults with acute exacerbation of schizophrenia or with negative symptoms. We estimated the dose-response curves by conducting random-effects dose-response meta-analyses. We used the restricted cubic spline to model the dose-response relationship. The primary outcome was mean weight gain in kg from baseline to endpoint, the secondary outcome was the number of patients with clinically important weight gain.

FINDINGS

Ninety-seven studies with 333 dose arms (36 326 participants) provided data for meta-analyses. Most studies were short-term with median duration of 6 weeks (range 4 to 26 weeks). In patients with acute exacerbation, amisulpride, aripiprazole, brexpiprazole, cariprazine, haloperidol, lumateperone, and lurasidone produced mild weight gain in comparison to placebo (mean difference at any dose≤1 kg), while more significant weight gain was observed by all other drugs. For most drugs, dose-response curves showed an initial dose-related increase in weight which plateaued at higher doses, while for others there was no plateau and some even had bell-shaped curves, meaning less weight gain to be associated with higher doses.

INTERPRETATION

Second-generation antipsychotics do not only differ in their propensity to produce weight gain, but also in the shapes of their dose-response curves. This information is important for dosing decisions in clinical practice.

Low Rates of Clinician Monitoring for Second Generation Antipsychotic Medications in Community Pediatric Practice

Second generation antipsychotic (SGA) medications are frequently prescribed to pediatric patients in the United States. This retrospective observational study sought to ascertain the extent of adherence to established pediatric SGA monitoring guidelines in community practice. The team used the electronic health record to determine clinician adherence to SGA monitoring guidelines at baseline, 12-week, and annual times relative to prescribing an SGA. At the time of their SGA prescription, 5.5% of pediatric patients had received all of the orders according to the monitoring guidelines. Annually, 2.5% of patients had received the necessary orders to completely adhere to monitoring guidelines; 42% of patients received no monitoring orders. Monitoring was more likely for children who had multiple types of providers and interacted with the healthcare system beyond a traditional office visit. This research informs healthcare providers about the gap between prescribing and monitoring for SGA medications in community practice for pediatric populations.

Previous exposure to antipsychotic drug treatment is an effective predictor of metabolic disturbances experienced with current antipsychotic drug treatments

BACKGROUND

Antipsychotic drugs are associated with adverse events, but serious side effects are not frequent. This study aimed to ascertain whether previous exposure to antipsychotic treatment was associated with metabolic disturbances induced by current antipsychotic medication.

METHODS

A total of 115 antipsychotic-naïve patients, 65 patients with previous exposure to low-metabolic-risk antipsychotics, and 88 patients with previous exposure to high-metabolic-risk antipsychotics were enrolled in our case-control study. All patients were administered olanzapine. Body weight, body mass index (BMI), biochemical indicators of blood glucose and lipids, the proportion of patients who gained more than 7% of their body weight at baseline, and the percentage of dyslipidemia were evaluated. All assessments were conducted at baseline and at 4 and 6 weeks after treatment.

RESULTS

Olanzapine treatment resulted in a significant increase in body weight and BMI in antipsychotic-naïve patients compared with the other two groups (both p < 0.05). However, increases in lipid levels in the high-metabolic-risk antipsychotics group were significantly higher than that in the other two groups (both p < 0.05). A history of antipsychotics use was not associated with weight gain (all p > 0.05). Higher low-density lipoprotein cholesterol ≥3.37 mmol/L^-1 was observed in antipsychotics exposure group compared with no history of antipsychotics exposure (aOR, 1.75; 95% CI, 1.07-3.52). Particularly, a history of high-metabolic-risk antipsychotics use was associated with a higher risk of LDL-C ≥3.37 mmol/L-1(aOR, 2.18; 95% CI, 1.03-3.32) compare with other two groups.

CONCLUSIONS

A history of exposure to antipsychotics, particularly high-metabolic-risk antipsychotics, is associated with current antipsychotic-induced metabolic disturbances.

Opioid antagonism mitigates antipsychotic-associated weight gain: focus on olanzapine

BACKGROUND

The endogenous opioid system affects metabolism, including weight regulation. Evidence from preclinical and clinical studies provides a rationale for targeting this system to mitigate weight-related side effects of antipsychotics. This review describes the role of the opioid system in regulating weight and metabolism, examines the effects of opioid receptor antagonism on those functions, and explores the use of opioid antagonists to mitigate antipsychotic-associated weight gain and/or metabolic effects.

METHODS

A PubMed literature search was conducted to identify representative opioid antagonists and associated preclinical and clinical studies examining their potential for the regulation of weight and metabolism.

RESULTS

The mu opioid receptor (MOR), delta opioid receptor (DOR), and kappa opioid receptor (KOR) types have overlapping but distinct patterns of central and peripheral expression, and each contributes to the regulation of body weight and metabolism. Three representative opioid antagonists (eg, naltrexone, samidorphan, and LY255582) were identified for illustration. These opioid antagonists differed in their receptor binding and pharmacokinetic profiles, including oral bioavailability, systemic clearance, and half-life, and were associated with varying effects on food intake, energy utilization, and metabolic dysregulation.

CONCLUSIONS

Preclinical and clinical data suggest that antagonism of the endogenous opioid system is a mechanism to address antipsychotic-associated weight gain and metabolic dysregulation. However, evidence suggests that the differing roles of MOR, DOR, and KOR in metabolism, together with the differences in receptor binding, pharmacokinetic, and functional activity profiles of the opioid receptor antagonists discussed in this review, likely contribute to their differential pharmacodynamic effects and clinical outcomes observed regarding antipsychotic-associated weight gain.

Olanzapine-associated dose-dependent alterations for weight and metabolic parameters in a prospective cohort

Metabolic abnormalities have been associated with olanzapine treatment. We assessed if olanzapine has dose‐dependent effects on metabolic parameters with changes for weight, blood pressure, lipid and glucose profiles being modelled using linear mixed‐effects models. The risk of metabolic abnormalities including early weight gain (EWG) (≥5% during first month) was assessed using mixed‐effects logistic regression models. In 392 olanzapine‐treated patients (median age 38.0 years, interquartile range [IQR] = 26.0–53.3, median dose 10.0 mg/day, IQR = 5.0–10.0 for a median follow‐up duration of 40.0 days, IQR = 20.7–112.2), weight gain was not associated with olanzapine dose (p = 0.61) although it was larger for doses versus ≤10 mg/day (2.54 ± 5.55 vs. 1.61 ± 4.51% respectively, p = 0.01). Treatment duration and co‐prescription of >2 antipsychotics, antidepressants, benzodiazepines and/or antihypertensive agents were associated with larger weight gain (p < 0.05). Lower doses were associated with increase in total and HDL cholesterol and systolic and diastolic blood pressure (p < 0.05), whereas higher doses were associated with glucose increases (p = 0.01). Patients receiving >10 mg/day were at higher EWG risk (odds risk: 2.15, 1.57–2.97). EWG might be prominent in high‐dose olanzapine‐treated patients with treatment duration and co‐prescription of other medications being weight gain moderators. The lack of major dose‐dependent patterns for weight gain emphasizes that olanzapine‐treated patients are at weight gain risk regardless of the dose.

An Evidence-Based Review of OLZ/SAM for Treatment of Adults with Schizophrenia or Bipolar I Disorder

Olanzapine effectively treats schizophrenia and bipolar I disorder (BD-I); however, its use is limited by the risk of significant weight gain and metabolic effects. OLZ/SAM, a combination of olanzapine and samidorphan, was recently approved in the United States for the treatment of adults with schizophrenia or BD-I. OLZ/SAM provides the efficacy of olanzapine while mitigating olanzapine-associated weight gain through opioid-receptor blockade. Here, we summarize OLZ/SAM clinical data characterizing pharmacokinetics, antipsychotic efficacy, weight mitigation efficacy, safety, and long-term treatment effects. In an acute exacerbation of schizophrenia, OLZ/SAM and olanzapine provided similar symptom improvements versus placebo at week 4. In stable outpatients with schizophrenia, OLZ/SAM treatment resulted in significantly less weight gain, reducing the risk for clinically significant weight gain and waist circumference increases of ≥5 cm by half, compared with olanzapine at week 24. Based on open-label extension studies, OLZ/SAM is safe and well tolerated for up to 3.5 years of treatment, while maintaining schizophrenia symptom control and stabilizing weight. The olanzapine component of OLZ/SAM was bioequivalent to branded olanzapine (Zyprexa); adjunctive OLZ/SAM had no clinically significant effects on lithium or valproate pharmacokinetics. Additionally, OLZ/SAM had no clinically relevant effect on electrocardiogram parameters in a dedicated thorough QT study. Overall, safety and tolerability findings from clinical studies with OLZ/SAM indicate a similar safety profile to that of olanzapine, with the exception of less weight gain. As OLZ/SAM contains the opioid antagonist samidorphan, it is contraindicated in patients using opioids and in those undergoing acute opioid withdrawal. Clinical trial results from more than 1600 subjects support the use of OLZ/SAM as a new treatment option for patients with schizophrenia or BD-I.

Olanzapine Induces Inflammation and Immune Response via Activating ER Stress in the Rat Prefrontal Cortex

OBJECTIVE

Antipsychotics, in particular olanzapine, are first-line medications for schizophrenia. The prefrontal cortex (PFC) is an important region for antipsychotics' therapeutic effects. The PFC inflammatory and immune pathways are associated with schizophrenia pathogenesis. However, the effect of antipsychotics on the inflammatory and immune pathways in the PFC remains unclear. We aimed to examined the time-dependent effect of olanzapine on inflammatory and immune markers in the PFC of rats. Since the inflammatory and immune pathways are related to endoplasmic reticulum (ER) stress, we further investigated whether or not olanzapine-induced inflammation and immune responses were related to ER stress.

METHODS

Expression of pro-inflammatory markers including IkappaB kinase β (IKKβ), nuclear factor kappa B (NFκB), tumor necrosis factor α (TNF-α), interleukin-6 (IL-6) and IL-1β, and immune-related proteins including inducible nitric oxide synthase (iNOS), toll-like receptor 2 (TLR2) and cluster of differentiation 14 (CD14) were examined by Western blotting.

RESULTS

Olanzapine treatments for 1, 8 and 36 days significantly activated the inflammatory IKKβ/NFκB signaling, and increased the expression of TNF-α, IL-6, IL-1β and immune-related proteins such as iNOS, TLR4 and CD14. Olanzapine treatment for 1 day, 8 and 36 days also induced ER stress in the PFC. Co-treatment with an ER stress inhibitor, 4-phenylbutyrate, inhibited olanzapine-induced inflammation and the immune response in the PFC.

CONCLUSION

These results suggested olanzapine exposure could be a factor that induces central inflammation and immunological abnormities in schizophrenia subjects. Olanzapine induces PFC inflammation and immune response, possibly via activating ER stress signaling.

Effect of Quetiapine, from Low to High Dose, on Weight and Metabolic Traits: Results from a Prospective Cohort Study

INTRODUCTION

The atypical antipsychotic quetiapine is known to induce weight gain and other metabolic complications. The underlying mechanisms are multifactorial and poorly understood with almost no information on the effect of dosage. Concerns were thus raised with the rise in low-dose quetiapine off-label prescription (i. e.,<150 mg/day).

METHODS

In this study, we evaluated the influence of quetiapine dose for 474 patients included in PsyMetab and PsyClin studies on weight and metabolic parameter evolution. Weight, blood pressure, lipid, and glucose profiles were evaluated during a follow-up period of 3 months after treatment initiation.

RESULTS

Significant dose-dependent metabolic alterations were observed. The daily dose was found to influence weight gain and increase the risk of undergoing clinically relevant weight gain (≥7% from baseline). It was also associated with a change in plasma levels of cholesterol (total cholesterol, LDL cholesterol, and HDL cholesterol) as well as with increased odds of developing hypertriglyceridemia, as well as total and LDL hypercholesterolemia. No impact of a dose increase on blood pressure and plasma glucose level was observed.

DISCUSSION

The dose-dependent effect highlighted for weight gain and lipid alterations emphasizes the importance of prescribing the minimal effective dose. However, as the effect size of a dose increase on metabolic worsening is low, the potential harm of low-dose quetiapine should not be dismissed. Prescriptions must be carefully evaluated and regularly questioned in light of side effect onset.

Effects of olanzapine on anxiety-related behaviour in male and female rats assessed after 21-24 and 42-45 days of chronic treatment

Olanzapine can decrease anxiety and impair memory, but there is limited information about length of treatment or sex differences in its effectiveness. Therefore, effects of 21-24 and 41-45 days of treatment and sex differences on anxiety-related behaviour and spatial memory were assessed in PVG/c (PVG/c is the internationally recognised way of referring to this rat strain) male and female rats. From 70 days after birth (PND70), all rats received no drug or 6, 11 or 15 mg/kg/day olanzapine via drinking water. From PND91, they were given four daily tests in an open field, light-dark box, zero maze and Y maze, and then again 21 days later from PND112. At PND91-94, all olanzapine doses decreased open-field ambulation and walking, and 6 and 15 mg/kg/day decreased rearing, increased immobility while 15 mg/kg/day decreased shuttles in the light/dark box (all suggesting higher anxiety). At PND112-115, 11 mg/kg/day increased open-field ambulation, walking, rearing, centre occupancy and light/dark-box shuttles and light-side entries while decreasing open-field immobility and corner occupancy (all suggesting lower anxiety). There were also several results in the open field and light/dark box suggesting olanzapine decreased anxiety for males but increased it for females. A significant olanzapine-related preference for the novel Y-maze arm either improved spatial memory, or decreased anxiety. Olanzapine thus appeared anxiogenic after 21 days' treatment, becoming anxiolytic after 42 days. This could depend on the sex of the rats (females more responsive to lower doses), and the dose (11 mg/kg/day being most effective). Therefore, while olanzapine was generally anxiolytic, it also had some treatment length- and sex-related anxiogenic effects.

Male-Specific Metabolic Considerations Concerning the Prescription of Second-Generation Antipsychotics to Adolescents

Objectives: Although males and females gain comparable weight when prescribed second-generation antipsychotics (SGAs), males may be uniquely vulnerable to an array of endocrinological, inflammatory, and psychosocial adverse drug effects. Methods: This opinion piece reviews work in each of these three areas for consideration. Results: Androgens may decrease both through hypothalamic-pituitary-gonadal axis dysregulation and as a consequence of increased adiposity. Testosterone has anti-inflammatory properties, and declining levels as well as many other factors may influence overall immunological functioning. Psychosocial stressors are gender specific in obesity, and SGA-induced obesity may affect males in unique and severe ways. Conclusion: This opinion piece supports the framework of the World Federation of Societies of Biological Psychiatry's Task Force on Men's Mental Health to advocate for further studies concerning the adverse drug effects of SGAs as unique manifested in male children, adolescents, and young men.

Handling Missing Values in Interrupted Time Series Analysis of Longitudinal Individual-Level Data

BACKGROUND

In the interrupted time series (ITS) approach, it is common to average the outcome of interest at each time point and then perform a segmented regression (SR) analysis. In this study, we illustrate that such 'aggregate-level' analysis is biased when data are missing at random (MAR) and provide alternative analysis methods.

METHODS

Using electronic health records from the UK, we evaluated weight change over time induced by the initiation of antipsychotic treatment. We contrasted estimates from aggregate-level SR analysis against estimates from mixed models with and without multiple imputation of missing covariates, using individual-level data. Then, we conducted a simulation study for insight about the different results in a controlled environment.

RESULTS

Aggregate-level SR analysis suggested a substantial weight gain after initiation of treatment (average short-term weight change: 0.799kg/week) compared to mixed models (0.412kg/week). Simulation studies confirmed that aggregate-level SR analysis was biased when data were MAR. In simulations, mixed models gave less biased estimates than SR analysis and, in combination with multilevel multiple imputation, provided unbiased estimates. Mixed models with multiple imputation can be used with other types of ITS outcomes (eg, proportions). Other standard methods applied in ITS do not help to correct this bias problem.

CONCLUSION

Aggregate-level SR analysis can bias the ITS estimates when individual-level data are MAR, because taking averages of individual-level data before SR means that data at the cluster level are missing not at random. Avoiding the averaging-step and using mixed models with or without multilevel multiple imputation of covariates is recommended.

GDF-15 as a Weight Watcher for Diabetic and Non-Diabetic People Treated With Metformin

Weight gain and obesity are global health concerns contributing to morbidity with increased risks of cardiovascular disease, diabetes, liver steatohepatitis and cancer. Pharmacological therapies or bariatric surgery are often required for those who fail to adhere to diet and lifestyle modifications. Metformin, a widely used antidiabetic agent, seems to have a health benefit beyond its anti-hyperglycemic properties, with few side effects. Emerging evidence shows weight loss to be associated with metformin in both diabetic and non-diabetic individuals. Recently, the growth differentiation factor 15 (GDF-15), a member of the transforming growth factor beta superfamily, has been identified as a key mediator of metformin-induced weight loss. Metformin increases the secretion of GDF-15, which binds exclusively to glial cell-derived neurotrophic factor family receptor alpha-like (GFRAL). This gut-brain cytokine works as a prominent player in reducing food intake and body weight in health and disease, like anorexia nervosa and cancer. Herein, we critically review advances in the understanding of the weight-reducing effects of metformin via the GDF-15 pathway.