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In anxiety, depression and psychosis, there has been frustratingly slow progress in developing novel therapies that make a substantial difference in practice, as well as in predicting which treatments will work for whom and in what contexts. To intervene early in the process and deliver optimal care to patients, we need to understand the underlying mechanisms of mental health conditions, develop safe and effective interventions that target these mechanisms, and improve our capabilities in timely diagnosis and reliable prediction of symptom trajectories. Better synthesis of existing evidence is one way to reduce waste and improve efficiency in research towards these ends. Living systematic reviews produce rigorous, up-to-date and informative evidence summaries that are particularly important where research is emerging rapidly, current evidence is uncertain and new findings might change policy or practice. Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS) aims to tackle the challenges of mental health science research by cataloguing and evaluating the full spectrum of relevant scientific research including both human and preclinical studies. GALENOS will also allow the mental health community-including patients, carers, clinicians, researchers and funders-to better identify the research questions that most urgently need to be answered. By creating open-access datasets and outputs in a state-of-the-art online resource, GALENOS will help identify promising signals early in the research process. This will accelerate translation from discovery science into effective new interventions for anxiety, depression and psychosis, ready to be translated in clinical practice across the world.

Previous late-stage randomized controlled trials (RCTs) failed to identify effective medications for the core symptoms of autism spectrum disorder (ASD), i.e., social-communication difficulties and repetitive behaviors, and as a consequence, there is still no approved medication. Thus, I conducted a systematic review of 203 RCTs with 12111 participants in order to inform evidence-based pharmacotherapy and drug development in ASD. The thesis consists of three parts: First, I conducted a network meta-analysis to investigate the efficacy and tolerability of pharmacological and dietary-supplement treatments. Some medications, e.g., the antipsychotics aripiprazole and risperidone, might be effective for the core symptoms and/or co-occurring difficulties (e.g., irritability), albeit associated with adverse events. Nevertheless, the evidence was generally preliminary and with low certainty. Therefore, routine prescription of medications for the core symptoms cannot be recommended and further investigation is warranted. Second, I conducted a meta-analysis of placebo-effects. The magnitude of placebo-effects was considerable and predictors of higher placebo-effects were identified, e.g., caregiver-ratings and larger trials. However, there were limited and scattered data for participant-level factors, e.g., age, sex, and baseline severity of symptoms. Third, I validated an imputation method to estimate the number of responders from continuous data of the Clinical Global Impression Improvement (CGI-I) scale. This method could facilitate the comparability and combination of findings across RCTs in ASD. However, sensitivity analyses are necessary given the relatively wide limits of agreement between imputed and original values. The findings and future implications of my thesis would hopefully facilitate a better support and care for individuals with ASD and their families. Es gibt noch keine offiziell zugelassenen Medikamente für die Kernsymptome von Autismus-Spektrum-Störungen (ASD), d. h. Schwierigkeiten in der sozialen Interaktion und Kommunikation sowie repetitive Verhaltensmuster. Daher habe ich eine systematische Überprüfung von 203 randomisiert-kontrollierten Studien (RCTs) mit 12111 Teilnehmern durchgeführt, mit dem Ziel eine evidenzbasierte Arzneimittelentwicklung und Pharmakotherapie bei ASD zu unterstützen. Die Arbeit umfasst drei Teile: Erstens führte ich eine Netzwerk-Metaanalyse über die Wirksamkeit und Verträglichkeit von pharmakologischen Behandlungen und Nahrungsergänzungsmitteln bei ASD durch. Einige Medikamente, z.B. die Antipsychotika Aripiprazol und Risperidon, waren gegen die Kernsymptome und/oder die damit einhergehende Begleitsymptome (z.B. Aggressivität) Placebo überlegen, aber sie verursachten auch Nebenwirkungen. Ferner waren die Ergebnisse vorläufig und noch wenig verläßlich. Daher kann die routinemäßige Verschreibung von Medikamenten gegen die Kernsymptome aktuell noch nicht empfohlen werden und weitere Untersuchungen sind erforderlich. Zweitens habe ich eine Metaanalyse der Placeboeffekte (Ansprechen auf Placebo) durchgeführt. Das Ausmaß der Placeboeffekte war beträchtlich, und ich konnte verschiedene Prädiktoren für höhere Placeboeffekte identifizieren. Insbesondere waren die Placeboeffekte größer, wenn Eltern- anstatt Behandlerfragebögen eingesetzt wurden und wenn die Studien größer waren. Für patientenbezogene Faktoren gab es nur begrenzte Daten, wie Alter, Geschlecht und Schweregrad der Symptome bei Studienbeginn. Drittens validierte ich eine Imputationsmethode zur Schätzung der Anzahl der Responder aus kontinuierlichen Daten der Clinical Global Impression of Improvement (CGI-I) Skala. Diese Methode kann die Vergleichbarkeit und Kombination von Ergebnissen verschiedener RCTs bei ASD erleichtern. Allerdings sind bei ihrer Anwendung Sensitivitätsanalysen erforderlich, da die Grenzen der Übereinstimmung zwischen den geschätzten und den ursprünglichen Werten relativ groß sind. Die Ergebnisse und die sich aus ihnen ergebenden Implikationen meiner Dissertation werden hoffentlich einen Beitrag zur Behandlung von Menschen mit ASD und ihren Familien leisten.

Review question To systematically assess the clinical efficacy and safety of long-acting injectable second-generation antipsychotics compared to their oral formulations or placebo for people with acute schizophrenia. Searches The following sources will be searched without restrictions for language or publication period: 1. Cochrane Schizophrenia Group’s Study-Based Register(we will search Cochrane Schizophrenia Group’s Study-Based Register). This register is compiled by regular searches in the following databases. 2. Excerpta Medica Database (EMBASE) 3. Cumulative Index to Nursing and Allied Health Literature (CINAHL) 4. American Psychological Association (PsycINFO) 5. PubMed 6. US National Institute of Health Ongoing Trials Register (ClinicalTrials.gov) 7. World Health Organization International Clinical Trials Registry Platform (www. who. int/ictrp) Searching other resources 1. Cited reference searching We will inspect the references of all identified trials for other published reports and citations of unpublished studies 2. Search of other systematic reviews We will also check previously published relevant systematic reviews to check if some studies meet our inclusion criteria. 3. Personal contact We will contact the primary authors of all studies initially selected for inclusion and the responsible drug companies if there is some missing information. Types of study to be included We will include randomized controlled trials (RCTs) in which patients with schizophrenia received an intervention as defined below (see Types of interventions section). We will accept open, single, and double-blinded trials. In the case of cross-over studies, the first cross-over phase will be included to avoid the problem of carryover effects which are very likely in drugs for schizophrenia (Elbourne, et al. 2002). We will accept studies with the duration of treatment over three weeks; this choice is mainly related to there is evidence from previous trials that a substantial effect of antipsychotics needs at least three weeks. No language restriction will be in the present study to minimize “language bias”(Egger, et al. 1997). We will exclude studies from mainland China for which major quality concerns have been raised(Woodhead 2016), except for studies conducted by international pharmaceutical companies in mainland China . Condition or domain being studied Schizophrenia and schizophrenia-like disorders (schizoaffective disorder, schizophreniform disorder, delusion disorder). Participants/population We will include individuals diagnosed with schizophrenia and related disorders (at least 80%) in an acute phase by any criteria irrespective of gender, age, or race. There is no clear, unified diagnostic standard for the acute phase of schizophrenia. To select this population, we operationalized the inclusion criteria as follows. We considered people to be in the acute phase of schizophrenia if they were experiencing an exacerbation in their baseline level of symptoms or if they had active symptoms and were currently hospitalized. In addition, if the authors described the patients in the study as acute or did not mention that patients were stable, we will assume them as acute. We will exclude maintenance studies in stable patients (relapse prevention studies) or dose reduction studies. Intervention(s), exposure(s) We only include SGA LAI given in 2 weeks or longer intervals. To the best of our knowledge, the SGAs with licensed LAI formulations include aripiprazole, olanzapine, risperidone, and paliperidone, because other oral antipsychotics do not exist by injection. We will exclude FGA LAI because these studies are older. After all, the clinical applications of FGA LAI are less common than SGA LAI (Janzen, et al. 2020). In addition, a recent article has revealed that older studies showed larger intervention effects than that of recent RCTs; thus, the authors suggest that meta-analyses including older trials should be interpreted cautiously(Smail-Faugeron, et al. 2022). Type of comparators 1. Olanzapine LAI (any dose) versus olanzapine oral or placebo 2. Paliperidone LAI (any dose) versus paliperidone oral or placebo 3. Risperidone LAI (any dose) versus risperidone oral or placebo 4. Aripiprazole LAI (any dose) versus aripiprazole oral or placebo 5. Any second-generation LAI (any dose) from the four antipsychotics in 1.-4.vs oral antipsychotics (always same counterpart to the LAIs) or placebo. 6. The four antipsychotics in 1.-4. as oral compound vs. placebo. These comparisons shall provide an estimate of the effect with oral compounds, which can then be compared to the effect with LAI applications in 1.-4. The studies comparing a SG LAI with its oral formulation (same compound) or placebo will be included in the review. We will exclude studies comparing a SG LAI to a different oral drug (different compound) or a different LAI. Context There are no restrictions in terms of setting, for example, we will include in- and outpatients. Types of outcome measures Primary outcome 1. Change in overall symptoms, measured by rating scales such as the PANSS (Kay, et al. 1987) or the BPRS (Overall and Gorham 1988) total score, or any other published scale (e.g., the Manchester Scale) to assess overall schizophrenic symptomatology. The results of other rating scales will only be used if the instrument has been published in a peer-reviewed journal. Secondary outcomes 1. Response to treatment. We will accept the original author’s decisions, but if different options are available we will prefer rating scale defined criteria in the following hierarchy: At least 50% reduction on PANSS or BPRS, CGI (Guy 1976) much improved, 20% reduction on PANSS or BPRS, 20% reduction on PANSS or BPRS, CGI minimally improved. 2. Change in PANSS positive scale score. 3. Change in PANSS negative scale score 4. Dropout due to any reason. 5. Dropout due to specific reasons. Dropout due to inefficacy of treatment will be considered as an additional outcome of the efficacy of treatment. Dropout due to the occurrence of adverse events will be used as a measure of overall tolerability. 6. Depression, measured by the Calgary Depression Scale for Schizophrenia, the Hamilton Depression Rating Scale(Williams 1988), the Montgomery Asberg Depression Scale(Davidson, et al. 1986), or other published symptom scales. 7. Quality of life, measured by any published rating scale (e.g Quality of Life Scale (Heinrichs, et al. 1984) 8. Functioning, measured by any published rating scale (e.g. global assessment of functioning (Hall 1995), Personal and Social Performance scale PSP REF). 9. Mortality: we will examine this outcome in terms of (A) death for any reason, (B) death due to natural causes, and (C) due to suicide. 10. The following major side effects will be examined: using antiparkinson drugs as a measure of extrapyramidal side-effects akathisia, weight gain in kg, number of participants with 7% weight gain or more, prolactin levels, sedation or somnolence, QTc prolongation, and at least one anticholinergic side-effect. Measures of effect 1. Continuous outcomes: We will use the standardized mean difference (SMD) between two groups and its 95% confidence intervals (CIs) if some studies employ different scales. Nevertheless, we will use mean differences (MD) for weight gain (kg), prolactin levels (ng/ml) and QTc prolongation (ms), since we can convert values of these outcomes into the same metric. The trials may report the results either as endpoint means or using changes in mean values from the baseline assessment. We will give preference to the mean change from baseline to endpoint measures, and, if not available, we will take the mean values at the endpoint. 2. Dichotomous outcomes: The effect size for dichotomous outcomes will be odds ratios (OR) and 95% confidence intervals (CIs), because the odds ratio has better mathematical properties than the relative risk. But we will convert back to relative risks (RRs) and percentages in treatment and control groups for presentation of the results. Dose‐ranging studies If a study has multiple arms with the same medication administered at different doses or administered for a different time length, we will pool these intervention groups into a single one, as recommended by the Cochrane Handbook for Systematic Reviews of Interventions, section 16.5.4 (Higgins, et al. 2019). In fixed dose studies, only those doses which are listed in the summary of product characteristics of the drugs will be included. We will include all doses from flexible dose studies in which physicians can adapt the dose to the individual patient. Dealing with missing data To some extent, missing outcome data is common, influencing credibility (Xia, et al. 2009). Among the methods that attempt to take attrition into account, we will prefer more sophisticated approaches such as multiple imputations or mixed-effects models (MMRM) to simple last-observation carried forward. Completer analyses will be included only if no other data are available. Moreover, we will address this issue in the' Incomplete outcome data' item of the RoB 2. If some studies did not report SDs, we would calculate SDs from reporting statistics, e.g., SE (Higgins, et al. 2019). If these are not available, we will contact authors, and if there is no reply, we will impute them from the other studies (Higgins, et al. 2019). Data extraction (selection and coding) Two authors will independently inspect the titles and abstracts from the search results. Full texts of included references will be obtained and independently accessed by two authors for eligible studies. Discrepancies will be resolved by discussion and SL will be involved if needed. Again, two authors will independently extract data into Access in duplicate. They will compare the two copies and resolve discrepancies. When they cannot reach consensus, SL will help clarify the issues, and these final decisions will be recorded. Where necessary, we will attempt to contact the author via open-ended request to obtain missing information or clarification. Risk of bias (quality) Two review authors will evaluate the risk of bias using Cochrane risk-of-bias tool for randomized trials (RoB 2) (Sterne, et al. 2019) for included LAI studies (comparisons 1.-4.). Discrepancies will be resolved by discussion and SL will be involved if needed. Strategy for data synthesis 1. we will do pairwise meta-analysis with random‐effects model inverse variance models . The random‐effects method incorporates an assumption that the different studies are estimating different, yet related, intervention effects. We feel that in schizophrenia which is a very heterogeneous disorder this is likely to be more appropriate. For dichotomous outcomes with rare Events we will use fixed effects Mantel-Haenszel models as recommended by Efthimiou et (Efthimiou 2018). because heterogeneity cannot be estimated well in the presence of rare events. 2. Assessment of heterogeneity: We will initially consider all included studies to judge methodological heterogeneity without seeing comparison data. We will simply inspect all studies for clearly outlying methods that we had not predicted would arise and discuss any such methodological outliers. In addition, we plan to investigate heterogeneity by visual inspection of forest plots and estimating the I2 statistic. Analysis of subgroups or subsets The following potential effect moderators of the primary outcome will be explored by subgroup analyses: 1. Different kinds of LAI formulations with same compounds, for example, there are two kinds of Aripiprazole LAI, Aripiprazole monohydrate (AM) and Aripiprazole lauroxil (AL). 2. Different dosing schedules for the same LAI. For example, olanzapine could be monthly or two weekly. 3. First-episode vs non-first-episode study populations. Sensitivity analyses of the primary outcome will be performed as follow: 1. Exclusion of non-double-blind studies (open and single-blind studies) 2. Exclusion of studies that presented only completer analyses 3. Exclusion of studies with an overall assessment of high risk of bias 4. Time point of outcome measurement in studies of LAIs vs placebo close to the Primary time point used in acute phase studies of oral compounds vs placebo (i.e. comparison 6), which is typically 6-8 weeks, whereas the LAI-studies typically have a primary time point of outcome measurement of => 12 weeks. References: Davidson, Jonathan, et al. 1986 The Montgomery‐Åsberg Depression Scale: reliability and validity. Acta psychiatrica scandinavica 73(5):544-548. Efthimiou, Orestis 2018 Practical guide to the meta-analysis of rare events. Evidence-based mental health 21(2):72-76. Egger, Matthias, et al. 1997 Language bias in randomised controlled trials published in English and German. The Lancet 350(9074):326-329. Elbourne, Diana R, et al. 2002 Meta-analyses involving cross-over trials: methodological issues. International journal of epidemiology 31(1):140-149. Guy, WBRR 1976 CGI. Clinical global impressions. ECDEU assessment manual for psychopharmacology. Hall, Richard CW 1995 Global assessment of functioning: a modified scale. Psychosomatics 36(3):267-275. Heinrichs, Douglas W, Thomas E Hanlon, and William T Carpenter Jr 1984 The Quality of Life Scale: an instrument for rating the schizophrenic deficit syndrome. Schizophrenia bulletin 10(3):388-398. Higgins, Julian PT, et al. 2019 Cochrane handbook for systematic reviews of interventions: John Wiley & Sons. Janzen, Donica, et al. 2020 Trends in the use of long-acting injectable antipsychotics in the province of Manitoba, Canada. Journal of Clinical Psychopharmacology 40(1):6-13. Kay, Stanley R, Abraham Fiszbein, and Lewis A Opler 1987 The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia bulletin 13(2):261-276. Overall, John E, and Donald R Gorham 1988 The Brief Psychiatric Rating Scale (BPRS): recent developments in ascertainment and scaling. Psychopharmacology bulletin. Smail-Faugeron, Violaine, et al. 2022 Meta-analyses frequently include old trials that are associated with a larger intervention effect: a meta-epidemiological study. Journal of Clinical Epidemiology. Sterne, Jonathan AC, et al. 2019 RoB 2: a revised tool for assessing risk of bias in randomised trials. bmj 366. Williams, Janet BW 1988 A structured interview guide for the Hamilton Depression Rating Scale. Archives of general psychiatry 45(8):742-747. Woodhead, Michael 2016 80% of China’s clinical trial data are fraudulent, investigation finds: British Medical Journal Publishing Group. Xia, Jun, et al. 2009 Losing participants before the trial ends erodes credibility of findings. Psychiatric Bulletin 33(7):254-257.

Version of the draft protocol 22.08.2022 Background Antipsychotic drugs are the mainstay treatment of schizophrenia, yet they can cause multiple side-effects (1, 2). Weight gain and metabolic side-effects are among the most important side-effects (3). Antipsychotic drugs differ in their receptor binding profiles and subsequently in their propensity of causing weight gain, e.g., olanzapine and clozapine are among the worst while dopamine partial agonists, lurasidone and ziprasidone among the most benign (1, 4-6). There is currently only one recently approved medication aiming to prevent antipsychotic-induced weight, i.e., the opioid antagonist samidorphan combined with olanzapine into one formulation (7). A few more medications have also been found effective in preventing or ameliorating antipsychotic-induced , e.g., metformin and topiramate (8). A clinically relevant reversibility of antipsychotic-induced weight gain has also been questioned (9). Therefore, there is a certain need to develop metabolically benign antipsychotics and/or medications that could prevent and/or ameliorate antipsychotic-induced metabolic side-effects. Rodent models could facilitate bridging this gap by providing unique mechanistic insights in antipsychotic-induced metabolic side-effects, as well as provide a basis for the development of treatments and antipsychotics with a lower liability. However, their results are often inconsistent and their translational validity has been questioned (5, 10). Thus, the proposed systematic review will synthesize evidence from rodent models of antipsychotic-induced weight gain in order to investigate: 1. Factors that could influence antipsychotic-induced weight change in order to improve the design of future preclinical studies. 2. Differences among antipsychotics and the agreement with randomized-controlled trials (RCTs) and real-world data in humans. 3. The efficacy of medications that could prevent metabolic-side effects in order to provide candidates for testing in future RCTs. 4. Dose-effects and trajectories of antipsychotic-induced weight change. 5. Reversibility of antipsychotic-induced weight gain by adding medications that could ameliorate metabolic side-effects, by dose reduction or cessation, or by switching antipsychotics. 6. The mechanisms of antipsychotic-induced metabolic-side effects. There is up to date no relevant systematic review and meta-analysis, as none was found up to 22.08.2022 in Pubmed (using the search in the supplement and restricted to systematic reviews or meta-analysis), SYRF (using the search term antipsychotic) and PROSPERO (using the search term antipsychotic and restricted to reviews of animal studies). Methods Eligibility criteria Animal/population Adult wild-type rodents irrespective of age, sex and species. Non-adult rodents, adult females in perinatal period, genetic models, models of disease will be excluded. Interventions Any antipsychotic drug (ATC code of N05A, except lithium) and any medication administered in combination with an antipsychotic aiming to prevent/ameliorate metabolic side-effects (e.g., metformin, GLP-1 receptor agonists, samidorphan, etc.). No further restriction in terms of dose, dosing schedule, route of administration. The duration of treatment should be at least seven days. Control Placebo, vehicle or no treatment. Study designs Two study designs would be eligible: 1. Acute experimental studies with at least seven days duration of treatment comparing any antipsychotic drug with each other, control conditions or with a medication aiming to prevent metabolic side-effects in adult wild-type rodents. These trials will be considered in most of the analyses of the data synthesis (see i-iv. in “Data synthesis”). 2. Reversibility trials comparing add-on medications, dose cessation/reduction or antipsychotic switch with control conditions in adult wild-type rodents that have already received treatment with antipsychotic. These trials will be considered in the analysis of reversibility of weight gain (see v. in “Data synthesis”). The trials should focus on antipsychotic-induced weight gain (primary outcome of this review) as indicated by title/abstract. There will be no further restriction in terms of treatment allocation and blinding of outcome assessment. Outcomes The primary outcome will be weight change from baseline. Secondary outcomes will include metabolic (e.g., food intake, glucose and lipid levels), endocrinological (e.g., prolactin, leptin, adiponectin levels), immune (e.g., cytokine levels), gene expression (e.g., POMC in hypothalamus) and behavioral outcomes (e.g., locomotion). The preferred effect-sizes will be mean differences and odds ratios. The preferred timepoint will be the closest to 6-8 weeks to align with RCTs in human (1). Data from multiple timepoints will be extracted for the primary outcome. Search strategy We will search for relevant studies in multiple electronic databases. Search strategies will combine terms for antipsychotics, weight gain and appropriate animal search filters of SYRCLE (11), without further restrictions in publication date, publication status, language and country of origin. A preliminary search in Pubmed on 14.05.2021 identified 1960 records (see supplement below for the preliminary search strategy), from which at least 150 studies with data for the primary outcome would be eligible. Study selection and data extraction At least two independent reviewers will screen the records for eligible studies, extract data, and evaluate the risk of bias using the SYRCLE’s risk of bias tool (12). Disagreements will be solved by consulting a third reviewer or by contacting the study authors. Data synthesis It is expected that there will be sufficient data for the primary outcome (i.e., change in weight). However, secondary outcomes might be inconsistently reported and measured across studies, and thus, a quantitative synthesis may not be allowed. For this reason, the quantitative data synthesis as described below is planned for the primary outcome, whereas a more qualitative synthesis and presentation of the findings will be a priori conducted for the secondary outcomes. The data synthesis will consist of: i. Meta-regression analysis First, pairwise random-effects meta-analyses of comparison of antipsychotics vs. control conditions will be conducted. Heterogeneity will be quantified using the between-study variance (tau-squared) and the I-squared statistic. We will explore factors that could explain heterogeneity with meta-regression analysis. We will consider factors related to characteristics of the animal (e.g., age, sex, species), intervention (e.g., type of antipsychotic, dose, route of administration), comparator (e.g., placebo/vehicle, no treatment) and study design (e.g., publication year, sponsorship, risk of bias, study duration). A full multivariable meta-regression will be preferred, and in case of insufficient and inconsistently reported data will perform univariable and multivariable meta-regressions similar to previous analyses, e.g.,(13). ii. Network meta-analysis The comparative effects of individual antipsychotics and preventive medications will be investigated in a network meta-analysis. A two-step procedure will be followed. First, pairwise random-effects meta-analyses for each comparison will be conducted. Second, if the requirements of a network meta-analysis are met, a network meta-analysis in a frequentist framework using graph-theoretical methods and a random-effects model will be conducted. Treatments will be ranked using P-scores (14). Transitivity assumption will be assessed by exploring the distribution of potential effect-modifiers across comparisons and by considering restricting the inclusion criteria for the network meta-analysis (e.g., exclusion of studies with factors that pose concerns in the translational validity as identified in the above-mentioned meta-regression analysis). A common heterogeneity will be assumed across each network (15), and will be quantified using the tau-squared compared with its empirical distributions (16, 17). Incoherence will be evaluated using local (i.e., separating indirect from direct evidence, SIDE) and global approaches (i.e., design-by-treatment interaction test) (18). The robustness of the findings and potential reasons of heterogeneity/incoherence will be investigated in predefined sensitivity (e.g., exclusion of high risk of bias studies) and subgroup analyses (e.g., separate analyses on male and female rodents). Reporting bias will be evaluated with funnel plot analyses, i.e., contour-enhanced (19) and comparison-adjusted funnel plots (20), and the ROB-MEN tool (21). iii. Dose-response meta-analysis The dose effects of antipsychotics and preventive medications will be explored with a one-stage dose-response meta-analysis using a random effects model and restricted cubic splines (22). iv. Time-response meta-analysis The preferred timepoint will be 6-8 weeks (see “Outcomes”), yet data from multiple timepoints will also be extracted. In this analysis, we will explore trajectories of antipsychotic-induced weight gain by conducting a general linear mixed-effects model (23). v. Reversibility of antipsychotic-induced weight change Pairwise random-effects meta-analysis and a network meta-analysis (if the requirements are met and as described above) will investigate strategies aiming to reverse antipsychotic-induced weight gain, e.g., add-on medications, switching antipsychotics, dose reduction or cessation. vi. Qualitative synthesis of mechanisms of antipsychotic-induced weight gain The effects of antipsychotics on weight gain will be considered in parallel with the findings on the secondary outcomes in order to further elucidate the pathogenetic mechanisms. Pairwise random-effects meta-analysis will be conducted for each secondary outcome and parameter, and their findings will be mapped into central and peripheral mechanisms of antipsychotic-induced weight gain (5). The confidence in the evidence will be evaluated using GRADE (24) and for the network meta-analysis using CINEMA (25), and a minimally contextualized framework of GRADE (26). Data analysis will be conducted using metafor (27), meta (28), netmeta (29), dosresmeta (30) in R statistical software (31). Alpha will be set at two-sided 5%, except for heterogeneity/incoherence tests at 10%. Discussion The planned systematic review will employ multiple meta-analytic methods in order to comprehensively synthesize the available evidence from rodent models of antipsychotic-induced metabolic side-effects. It could would be suitable to inform the design of future preclinical studies and identify potential preventive medications that could further be evaluated in RCTs in humans. Systematic review registration The protocol of the systematic review will be registered to PROSPERO. References 1. Huhn M, Nikolakopoulou A, Schneider-Thoma J, Krause M, Samara M, Peter N, et al. Comparative efficacy and tolerability of 32 oral antipsychotics for the acute treatment of adults with multi-episode schizophrenia: a systematic review and network meta-analysis. Lancet. 2019;394(10202):939-51. 2. Schneider-Thoma J, Chalkou K, Dörries C, Bighelli I, Ceraso A, Huhn M, et al. Comparative efficacy and tolerability of 32 oral and long-acting injectable antipsychotics for the maintenance treatment of adults with schizophrenia: a systematic review and network meta-analysis. The lancet. 2022;399(10327):824-36. 3. De Hert M, Detraux J, van Winkel R, Yu W, Correll CU. Metabolic and cardiovascular adverse effects associated with antipsychotic drugs. Nat Rev Endocrinol. 2011;8(2):114-26. 4. Siafis S, Davis JM, Leucht S. Antipsychotic drugs: from 'major tranquilizers' to Neuroscience-based-Nomenclature. Psychol Med. 2021;51(3):522-4. 5. Siafis S, Tzachanis D, Samara M, Papazisis G. Antipsychotic Drugs: From Receptor-binding Profiles to Metabolic Side Effects. Curr Neuropharmacol. 2018;16(8):1210-23. 6. Pillinger T, McCutcheon RA, Vano L, Mizuno Y, Arumuham A, Hindley G, et al. Comparative effects of 18 antipsychotics on metabolic function in patients with schizophrenia, predictors of metabolic dysregulation, and association with psychopathology: a systematic review and network meta-analysis. Lancet Psychiatry. 2020;7(1):64-77. 7. LYBALVI. https://www.accessdata.fda.gov/drugsatfda_docs/label/2021/213378s000lbl.pdf. 2021. 8. Wang Y, Wang D, Cheng J, Fang X, Chen Y, Yu L, et al. Efficacy and tolerability of pharmacological interventions on metabolic disturbance induced by atypical antipsychotics in adults: A systematic review and network meta-analysis. Journal of Psychopharmacology. 2021;35(9):1111-9. 9. Speyer H, Westergaard C, Albert N, Karlsen M, Stürup AE, Nordentoft M, et al. Reversibility of Antipsychotic-Induced Weight Gain: A Systematic Review and Meta-Analysis. Front Endocrinol (Lausanne). 2021;12:577919. 10. van der Zwaal EM, Janhunen SK, la Fleur SE, Adan RA. Modelling olanzapine-induced weight gain in rats. Int J Neuropsychopharmacol. 2014;17(1):169-86. 11. van der Mierden S, Hooijmans CR, Tillema AH, Rehn S, Bleich A, Leenaars CH. Laboratory animals search filter for different literature databases: PubMed, Embase, Web of Science and PsycINFO. Lab Anim. 2021:236772211045485. 12. Hooijmans CR, Rovers MM, de Vries RB, Leenaars M, Ritskes-Hoitinga M, Langendam MW. SYRCLE's risk of bias tool for animal studies. BMC Med Res Methodol. 2014;14:43. 13. Siafis S, Çıray O, Schneider-Thoma J, Bighelli I, Krause M, Rodolico A, et al. Placebo response in pharmacological and dietary supplement trials of autism spectrum disorder (ASD): systematic review and meta-regression analysis. Mol Autism. 2020;11(1):66. 14. Rücker G, Schwarzer G. Ranking treatments in frequentist network meta-analysis works without resampling methods. BMC medical research methodology. 2015;15(1):1-9. 15. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions: John Wiley & Sons; 2019. 16. Rhodes KM, Turner RM, Higgins JPT. Predictive distributions were developed for the extent of heterogeneity in meta-analyses of continuous outcome data. Journal of clinical epidemiology. 2015;68(1):52-60. 17. Turner RM, Davey J, Clarke MJ, Thompson SG, Higgins JPT. Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews. International journal of epidemiology. 2012;41(3):818-27. 18. Efthimiou O, Debray TPA, van Valkenhoef G, Trelle S, Panayidou K, Moons KGM, et al. GetReal in network meta‐analysis: a review of the methodology. Research synthesis methods. 2016;7(3):236-63. 19. Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. Journal of clinical epidemiology. 2008;61(10):991-6. 20. Chaimani A, Higgins JPT, Mavridis D, Spyridonos P, Salanti G. Graphical tools for network meta-analysis in STATA. PloS one. 2013;8(10):e76654. 21. Chiocchia V, Nikolakopoulou A, Higgins J, Page MJ, Papakonstantinou T, Cipriani A, et al. ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis. BMC medicine. 2021;19(1):1-13. 22. Crippa A, Discacciati A, Bottai M, Spiegelman D, Orsini N. One-stage dose-response meta-analysis for aggregated data. Stat Methods Med Res. 2019;28(5):1579-96. 23. Musekiwa A, Manda SO, Mwambi HG, Chen DG. Meta-Analysis of Effect Sizes Reported at Multiple Time Points Using General Linear Mixed Model. PLoS One. 2016;11(10):e0164898. 24. Schunemann H. GRADE handbook for grading quality of evidence and strength of recommendation. Version 3.2. http://www cc-ims net/gradepro. 2008. 25. Nikolakopoulou A, Higgins JPT, Papakonstantinou T, Chaimani A, Del Giovane C, Egger M, et al. CINeMA: an approach for assessing confidence in the results of a network meta-analysis. PLoS medicine. 2020;17(4):e1003082. 26. Brignardello-Petersen R, Florez ID, Izcovich A, Santesso N, Hazlewood G, Alhazanni W, et al. GRADE approach to drawing conclusions from a network meta-analysis using a minimally contextualised framework. Bmj. 2020;371. 27. Viechtbauer W. Conducting meta-analyses in R with the metafor package. Journal of statistical software. 2010;36(3):1-48. 28. Balduzzi S, Rücker G, Schwarzer G. How to perform a meta-analysis with R: a practical tutorial. Evidence-based mental health. 2019;22(4):153-60. 29. Rücker G, Schwarzer G, Krahn U, König J, Schwarzer MG. Package ‘netmeta’. Network Meta-Analysis using Frequentist Methods (Version 07-0). 2015. 30. Crippa A, Crippa MA. Package ‘dosresmeta’. 2017. 31. Team RC. R: A language and environment for statistical computing. 2013. Preliminary Pubmed search strategy: (((Antipsychotic Agents [Mesh] OR ((Antipsychoti* or Anti-psychotic* or Neurolepic* or Neurolept*)) OR ((Acepromazine or Acetophenazine or Amisulpride or Aripiprazole or Asenapine or Benperidol or Blonanserin or Bromperidol or Butaperazine or Carpipramine or Chlorproethazine or Chlorpromazine or Chlorprothixene or Clocapramine or Clopenthixol or Clopentixol or Clothiapine or Clotiapine or Clozapine or Cyamemazine or Cyamepromazine or Dixyrazine or Droperidol or Fluanisone or Flupehenazine or Flupenthixol or Flupentixol or Fluphenazine or Fluspirilen or Fluspirilene or Haloperidol or Iloperidone or Levomepromazine or Levosulpiride or Lithium or Loxapine or Loxapinsuccinate or Lurasidone or Melperone or Mepazine or Mesoridazine or Methotrimeprazine or Molindone or Moperone or Mosapramine or Olanzapine or Oxypertine or Paliperidone or Penfluridol or Perazine or Periciazine or Pericyazine or Perospirone or Perphenazine or Pimozide or Pipamperone or Pipothiazine or Pipotiazine or Prochlorperazine or Promazine or Promethazine or Prothipendyl or Quetiapine or Remoxipiride or Reserpine or Riospirone or Risperdal or Risperidone or Seroquel or Sertindole or Stelazine or Sulpiride or Sultopride or Thiopropazate or Thioproperazine or Thioridazine or Tiospirone or Thiothixene or Tiapride or Tiotixene or Trifluoperazine or Trifluperidol or trifluoperidol or Triflupromazine or trifluperazine or Veralipride or Ziprasidone or Zotepine or Zuclopenthixol)))) AND (("animal experimentation"[MeSH Terms] OR "models, animal"[MeSH Terms] OR "invertebrates"[MeSH Terms] OR "Animals"[Mesh:noexp] OR "animal population groups"[MeSH Terms] OR "chordata"[MeSH Terms:noexp] OR "chordata, nonvertebrate"[MeSH Terms] OR "vertebrates"[MeSH Terms:noexp] OR "amphibians"[MeSH Terms] OR "birds"[MeSH Terms] OR "fishes"[MeSH Terms] OR "reptiles"[MeSH Terms] OR "mammals"[MeSH Terms:noexp] OR "primates"[MeSH Terms:noexp] OR "artiodactyla"[MeSH Terms] OR "carnivora"[MeSH Terms] OR "cetacea"[MeSH Terms] OR "chiroptera"[MeSH Terms] OR "elephants"[MeSH Terms] OR "hyraxes"[MeSH Terms] OR "insectivora"[MeSH Terms] OR "lagomorpha"[MeSH Terms] OR "marsupialia"[MeSH Terms] OR "monotremata"[MeSH Terms] OR "perissodactyla"[MeSH Terms] OR "rodentia"[MeSH Terms] OR "scandentia"[MeSH Terms] OR "sirenia"[MeSH Terms] OR "Cingulata"[Mesh] OR "haplorhini"[MeSH Terms:noexp] OR "strepsirhini"[MeSH Terms] OR "platyrrhini"[MeSH Terms] OR "tarsii"[MeSH Terms] OR "catarrhini"[MeSH Terms:noexp] OR "cercopithecidae"[MeSH Terms] OR "hylobatidae"[MeSH Terms] OR "hominidae"[MeSH Terms:noexp] OR "gorilla gorilla"[MeSH Terms] OR "pan paniscus"[MeSH Terms] OR "pan troglodytes"[MeSH Terms] OR "pongo pygmaeus"[MeSH Terms]) OR ((animals[tiab] OR animal[tiab] OR mice[Tiab] OR mus[Tiab] OR mouse[Tiab] OR murine[Tiab] OR woodmouse[tiab] OR rats[Tiab] OR rat[Tiab] OR murinae[Tiab] OR muridae[Tiab] OR cottonrat[tiab] OR cottonrats[tiab] OR hamster[tiab] OR hamsters[tiab] OR cricetinae[tiab] OR rodentia[Tiab] OR rodent[Tiab] OR rodents[Tiab] OR pigs[Tiab] OR pig[Tiab] OR swine[tiab] OR swines[tiab] OR piglets[tiab] OR piglet[tiab] OR boar[tiab] OR boars[tiab] OR "sus scrofa"[tiab] OR ferrets[tiab] OR ferret[tiab] OR polecat[tiab] OR polecats[tiab] OR "mustela putorius"[tiab] OR "guinea pigs"[Tiab] OR "guinea pig"[Tiab] OR cavia[Tiab] OR callithrix[Tiab] OR marmoset[Tiab] OR marmosets[Tiab] OR cebuella[Tiab] OR hapale[Tiab] OR octodon[Tiab] OR chinchilla[Tiab] OR chinchillas[Tiab] OR gerbillinae[Tiab] OR gerbil[Tiab] OR gerbils[Tiab] OR jird[Tiab] OR jirds[Tiab] OR merione[Tiab] OR meriones[Tiab] OR rabbits[Tiab] OR rabbit[Tiab] OR hares[Tiab] OR hare[Tiab] OR diptera[Tiab] OR flies[Tiab] OR fly[Tiab] OR dipteral[Tiab] OR drosophila[Tiab] OR drosophilidae[Tiab] OR cats[Tiab] OR cat[Tiab] OR carus[Tiab] OR felis[Tiab] OR nematoda[Tiab] OR nematode[Tiab] OR nematodes[Tiab] OR sipunculida[Tiab] OR dogs[Tiab] OR dog[Tiab] OR canine[Tiab] OR canines[Tiab] OR canis[Tiab] OR sheep[Tiab] OR sheeps[Tiab] OR mouflon[Tiab] OR mouflons[Tiab] OR ovis[Tiab] OR goats[Tiab] OR goat[Tiab] OR capra[Tiab] OR capras[Tiab] OR rupicapra[Tiab] OR chamois[Tiab] OR haplorhini[Tiab] OR monkey[Tiab] OR monkeys[Tiab] OR anthropoidea[Tiab] OR anthropoids[Tiab] OR saguinus[Tiab] OR tamarin[Tiab] OR tamarins[Tiab] OR leontopithecus[Tiab] OR hominidae[Tiab] OR ape[Tiab] OR apes[Tiab] OR "pan paniscus"[Tiab] OR bonobo[Tiab] OR bonobos[Tiab] OR "pan troglodytes"[Tiab] OR gibbon[Tiab] OR gibbons[Tiab] OR siamang[Tiab] OR siamangs[Tiab] OR nomascus[Tiab] OR symphalangus[Tiab] OR chimpanzee[Tiab] OR chimpanzees[Tiab] OR prosimian[Tiab] OR prosimians[Tiab] OR "bush baby"[Tiab] OR bush babies[Tiab] OR galagos[Tiab] OR galago[Tiab] OR pongidae[Tiab] OR gorilla[Tiab] OR gorillas[Tiab] OR "pongo pygmaeus"[Tiab] OR orangutan[Tiab] OR orangutans[Tiab] OR lemur[Tiab] OR lemurs[Tiab] OR lemuridae[Tiab] OR horse[Tiab] OR horses[Tiab] OR equus[Tiab] OR cow[Tiab] OR calf[Tiab] OR bull[Tiab] OR chicken[Tiab] OR chickens[Tiab] OR gallus[Tiab] OR quail[Tiab] OR bird[Tiab] OR birds[Tiab] OR quails[Tiab] OR poultry[Tiab] OR poultries[Tiab] OR fowl[Tiab] OR fowls[Tiab] OR reptile[Tiab] OR reptilia[Tiab] OR reptiles[Tiab] OR snakes[Tiab] OR snake[Tiab] OR lizard[Tiab] OR lizards[Tiab] OR alligator[Tiab] OR alligators[Tiab] OR crocodile[Tiab] OR crocodiles[Tiab] OR turtle[Tiab] OR turtles[Tiab] OR amphibian[Tiab] OR amphibians[Tiab] OR amphibia[Tiab] OR frog[Tiab] OR frogs[Tiab] OR bombina[Tiab] OR salientia[Tiab] OR toad[Tiab] OR toads[Tiab] OR "epidalea calamita"[Tiab] OR salamander[Tiab] OR salamanders[Tiab] OR eel[Tiab] OR eels[Tiab] OR fish[Tiab] OR fishes[Tiab] OR pisces[Tiab] OR catfish[Tiab] OR catfishes[Tiab] OR siluriformes[Tiab] OR arius[Tiab] OR heteropneustes[Tiab] OR sheatfish[Tiab] OR perch[Tiab] OR perches[Tiab] OR percidae[Tiab] OR perca[Tiab] OR trout[Tiab] OR trouts[Tiab] OR char[Tiab] OR chars[Tiab] OR salvelinus[Tiab] OR minnow[Tiab] OR cyprinidae[Tiab] OR carps[Tiab] OR carp[Tiab] OR zebrafish[Tiab] OR zebrafishes[Tiab] OR goldfish[Tiab] OR goldfishes[Tiab] OR guppy[Tiab] OR guppies[Tiab] OR chub[Tiab] OR chubs[Tiab] OR tinca[Tiab] OR barbels[Tiab] OR barbus[Tiab] OR pimephales[Tiab] OR promelas[Tiab] OR "poecilia reticulata"[Tiab] OR mullet[Tiab] OR mullets[Tiab] OR eel[Tiab] OR eels[Tiab] OR seahorse[Tiab] OR seahorses[Tiab] OR mugil curema[Tiab] OR atlantic cod[Tiab] OR shark[Tiab] OR sharks[Tiab] OR catshark[Tiab] OR anguilla[Tiab] OR salmonid[Tiab] OR salmonids[Tiab] OR whitefish[Tiab] OR whitefishes[Tiab] OR salmon[Tiab] OR salmons[Tiab] OR sole[Tiab] OR solea[Tiab] OR lamprey[Tiab] OR lampreys[Tiab] OR pumpkinseed[Tiab] OR sunfish[Tiab] OR sunfishes[Tiab] OR tilapia[Tiab] OR tilapias[Tiab] OR turbot[Tiab] OR turbots[Tiab] OR flatfish[Tiab] OR flatfishes[Tiab] OR sciuridae[Tiab] OR squirrel[Tiab] OR squirrels[Tiab] OR chipmunk[Tiab] OR chipmunks[Tiab] OR suslik[Tiab] OR susliks[Tiab] OR vole[Tiab] OR voles[Tiab] OR lemming[Tiab] OR lemmings[Tiab] OR muskrat[Tiab] OR muskrats[Tiab] OR lemmus[Tiab] OR otter[Tiab] OR otters[Tiab] OR marten[Tiab] OR martens[Tiab] OR martes[Tiab] OR weasel[Tiab] OR badger[Tiab] OR badgers[Tiab] OR ermine[Tiab] OR mink[Tiab] OR minks[Tiab] OR sable[Tiab] OR sables[Tiab] OR gulo[Tiab] OR gulos[Tiab] OR wolverine[Tiab] OR wolverines[Tiab] OR mustela[Tiab] OR llama[Tiab] OR llamas[Tiab] OR alpaca[Tiab] OR alpacas[Tiab] OR camelid[Tiab] OR camelids[Tiab] OR guanaco[Tiab] OR guanacos[Tiab] OR chiroptera[Tiab] OR chiropteras[Tiab] OR bat[Tiab] OR bats[Tiab] OR fox[Tiab] OR foxes[Tiab] OR iguana[Tiab] OR iguanas[Tiab] OR xenopus laevis[Tiab] OR parakeet[Tiab] OR parakeets[Tiab] OR parrot[Tiab] OR parrots[Tiab] OR donkey[Tiab] OR donkeys[Tiab] OR mule[Tiab] OR mules[Tiab] OR zebra[Tiab] OR zebras[Tiab] OR shrew[Tiab] OR shrews[Tiab] OR bison[Tiab] OR bisons[Tiab] OR buffalo[Tiab] OR buffaloes[Tiab] OR deer[Tiab] OR deers[Tiab] OR bear[Tiab] OR bears[Tiab] OR panda[Tiab] OR pandas[Tiab] OR "wild hog"[Tiab] OR "wild boar"[Tiab] OR fitchew[Tiab] OR fitch[Tiab] OR beaver[Tiab] OR beavers[Tiab] OR jerboa[Tiab] OR jerboas[Tiab] OR capybara[Tiab] OR capybaras[Tiab] OR canine [tiab] OR bovine [tiab] OR porcine [tiab] OR hog [tiab] OR hogs [tiab]) NOT medline[sb]))) AND ((weight gain[Title/Abstract] OR obesity[Title/Abstract] OR body weight[Title/Abstract] OR weight increase)