Hostname: page-component-89b8bd64d-5bvrz Total loading time: 0 Render date: 2026-05-07T01:45:39.702Z Has data issue: false hasContentIssue false
  • English
  • Français

Potential protective role of GLP-1 receptor agonists for lithium-induced nephrotoxicity: a population-based observational study

Published online by Cambridge University Press:  12 November 2025

Roger S. McIntyre Open the ORCID record for Roger S. McIntyre [Opens in a new window]  and
Angela T.H. Kwan
Roger S. McIntyre*
Affiliation:
Department of Psychiatry, University of Toronto, Toronto, ON, Canada Department of Pharmacology and Toxicology, University of Toronto, ON, Canada
Angela T.H. Kwan
Affiliation:
Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
*
Corresponding author: Roger S. McIntyre; Email: roger.mcintyre@bcdf.org
Rights & Permissions [Opens in a new window]

Abstract

Objectives

We hypothesized that semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1 RA) and treatment currently U.S. Food and Drug Administration (FDA) approved to reduce worsening of kidney disease and kidney failure may protect against lithium-induced nephrotoxicity.

Methods

Renal adverse events (AEs) reported to the FDA Adverse Event Reporting System (FAERS) between December 2003 and December 2024 were analyzed using the validated OpenVigil 2.1 platform. Reporting odds ratios (RORs) were computed for the MedDRA terms renal impairment, renal failure, chronic kidney disease (CKD), end-stage renal disease (ESRD), and acute kidney injury (AKI) in association with lithium, semaglutide, and their co-reporting. A disproportionality signal was considered statistically significant when p < 0.05, and the lower bound of the information component (IC025) was greater than 0.

Results

Lithium was associated with significantly elevated reporting odds across all renal AEs, with each outcome exceeding statistical signal thresholds (p < 0.0001, IC025 > 0). In contrast, semaglutide demonstrated inverse associations for renal impairment, renal failure, CKD, and ESRD (RORs = 0.25–0.54), and a neutral association for AKI (ROR = 0.96); however, none met the criteria for a disproportionality signal (IC025 < 0). Co-reported use of lithium and semaglutide did not yield a significant signal for any renal outcome, including AKI (ROR = 5.81, p = 0.015, IC025 < 0).

Conclusions

This observation, provides impetus to conduct adequate, thorough, mechanistic, clinical, and observational studies to determine whether semaglutide (and/or other incretin receptor agonists) could possibly mitigate the risk for, and/or modify the trajectory of, lithium-induced nephrotoxicity.

Keywords

Lithiumsemaglutideglucagon-like peptide-1 receptor agonists (GLP-1RA)lithium-induced nephrotoxicityrenal adverse eventsbipolar disorderpharmacovigilancedepressionkidneymood stabilizer

Information

Type
Original Research
Information
CNS Spectrums , Volume 31 , Issue 1 , 2026 , e5
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press

Introduction

Lithium remains a first-line treatment for acute mania and for preventing relapse in bipolar disorder.Reference McIntyre, Berk and Brietzke 1 , Reference Yatham, Chakrabarty and Bond 2 However, long-term use carries a significant risk of kidney injury, with lithium-induced nephrotoxicity estimated to affect up to 20% of patients receiving chronic therapy.Reference Qian, Sud and Lee 3 –Reference Davis, Desmond and Berk 5 This complication is often progressive with continued lithium exposure and a not infrequent reason for treatment discontinuation. Pathology results typically show chronic tubulointerstitial nephropathy with evidence of tubular atrophy, interstitial nephritis and fibrosis as well as cortical microcysts.Reference Gong, Wang and Dworkin 6 , Reference Markowitz, Radhakrishnan, Kambham, Valeri, Hines and D’Agati 7 The mechanisms implicated are hypothesized to include inflammatory and oxidative stress pathways.Reference Ossani, Uceda and Acosta 8 Although treatments exist for lithium-induced nephrogenic diabetes insipidus, no therapy has yet been established to meaningfully prevent or slow the disease trajectory of lithium-induced nephrotoxicity.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are FDA approved in the treatment of multiple medical conditions including, but not limited to, type 2 diabetes mellitus and obesity with acute- and long-term effects that have exceeded traditional agents. In addition to their metabolic effects, GLP-1 RAs have received U.S. Food and Drug Administration (FDA) approval for metabolic-dysfunction-associated steatohepatitis, obstructive sleep apnea, and reducing the progression of chronic kidney disease (CKD), end-stage kidney disease, and cardiovascular mortality in adults with type 2 diabetes and CKD.Reference Drucker 9 Mechanisms implicated in the renal protective effects of GLP-1 RAs include suppression of activated inflammatory effectors; decreased renal immune cell infiltration; regulation of innate immune activity; decreased receptor expression for advanced glycation end product (RAGE); inhibition of nuclear factor κB (NF-κB) signaling; and reductions in fibrosis, oxidative stress, and autophagy. Beneficial effects in microvasculature function and neural signaling are also implicated.Reference J, Me and Mt 10

The nephroprotective mechanisms of GLP-1 RAs introduce a testable and viable hypothesis that we preliminarily address in this study, ie, whether semaglutide, a GLP-1 RA currently approved by the FDA for reducing the risk of worsening kidney disease and kidney failure in adults with type 2 diabetes, may also exert protective and/or illness-modifying effects against lithium-induced nephrotoxicity. The aforementioned hypothesis derives from overlapping molecular mechanisms implicated in diabetic nephropathy and lithium-induced nephrotoxicity. A separate and related hypothesis is whether protective effects may be direct cytoprotective actions on molecular and cellular renal systems and/or indirectly by improvements in microvascular and metabolic function.Reference J, Me and Mt 10

Methods

Data source and extraction

Adverse event (AE) data were systematically retrieved from the U.S. FDA Adverse Event Reporting System (FAERS), a global post-marketing surveillance database that aggregates voluntary reports from healthcare professionals, manufacturers, and consumers. Reports submitted between December 2003 and December 2024 were analyzed using OpenVigil 2.1, a validated pharmacovigilance platform that interfaces with the openFDA API to provide structured access to FAERS. 11 –Reference Dores, Bryant-Genevier and Perez-Vilar 20 This system enables standardized data retrieval, filtering, deduplication, and preprocessing of large-scale safety datasets in alignment with international pharmacovigilance guidelines.

Data cleaning and curation

Drug names were standardized according to the United States Adopted Name (USAN) convention, with cross-references to DrugBank and Drugs@FDA to resolve brand and generic discrepancies as well as abbreviations. Automated mapping and error-correction algorithms were used to harmonize terminology across entries. Reports that were incomplete, structurally invalid, or internally inconsistent were excluded. Potential duplicate cases were identified through matching of demographic and case-level variables and verified against the FDA DEMO table before removal.

AE coding and case selection

All AEs were standardized using Preferred Terms (PTs) from the Medical Dictionary for Regulatory Activities (MedDRA) to ensure consistent classification of renal outcomes. 21 Primary endpoints included the MedDRA terms renal impairment, renal failure, CKD, end-stage renal disease (ESRD), and acute kidney injury (AKI), selected for their documented association with lithium-induced nephrotoxicity. The final dataset underwent clinical review by experts from the FDA’s Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER) to confirm completeness, clinical plausibility, and coding accuracy. 22 , 23

Analyses were limited to reports identifying lithium or semaglutide as the primary suspect drug to ensure accurate attribution of AEs to the drug of interest. In contrast, co-reported cases involving both lithium and semaglutide were queried without suspect filters to maximize sensitivity for detecting potential interaction signals, regardless of reporter designation.

Signal detection and statistical analysis

Disproportionality analysis was performed using the reporting odds ratio (ROR), defined as the odds of a renal AE event occurring with a given drug relative to all other drugs in the FAERS database. To strengthen signal detection accuracy, a multitiered analytic framework was applied, consistent with validated pharmacovigilance methodologies from prior studies.Reference Lakhani, Kwan, Mihalache, Popovic, Hurley and Muni 13 , Reference Lakhani, Kwan, Nguyen, Popovic, McIntyre and Wu 17 Reference McIntyre, Mansur, Rosenblat and Kwan 24 , Reference Kwan, Lakhani and Teopiz 25Specifically, the Evans criteria (n > 2, χ2 > 4, ROR > 2) were used alongside calculation of the lower bound of the 95% credibility interval (IC025).Reference Evans, Waller and Davis 26 A signal was considered statistically significant when IC025 > 0 and p < 0.05. In addition to ROR, proportional reporting ratio (PRR) and relative risk ratio (RRR) were calculated as secondary validation metrics.

To minimize reporting biases, we combined frequentist and Bayesian disproportionality methods with standardized signal thresholds to enhance the accuracy and stability of signal detection. The Bayesian IC025 metric helps reduce the impact of notoriety bias—where increased awareness temporarily boosts reporting—and the Weber effect, which reflects early post-marketing spikes in AE submissions. This stabilization occurs through Bayesian shrinkage, which adjusts observed-to-expected ratios toward the overall reporting mean, reducing the influence of random variation, small sample sizes, and short-term reporting fluctuations.Reference Goligher, Heath and Harhay 27 , Reference Röver and Friede 28 Visualization of RORs, including forest plots, was performed using RStudio (version 2023.06.1 + 524, “Desert Sunflower” release).

Ethical considerations

Institutional review board (IRB) approval was not required because FAERS is a publicly accessible de-identified database.

Results

Lithium was consistently associated with significantly elevated reporting across all renal AEs. Disproportionality estimates were robust and exceeded signal thresholds for every endpoint: renal impairment (ROR = 4.98, 95%CI = 4.03–6.15, p < 0.0001, IC025 = 1.91), renal failure (ROR = 4.11, 95%CI = 3.43–4.92, p < 0.0001, IC025 = 1.69), CKD (ROR = 8.15, 95%CI = 7.02–9.45, p < 0.0001, IC025 = 2.70), ESRD (ROR = 9.55, 95%CI = 7.14–12.77, p < 0.0001, IC025 = 2.62), and AKI (ROR = 8.17, 95%CI = 7.28–9.17, p < 0.0001, IC025 = 2.74), as summarized in Table 1 and illustrated in Figure 1.

Table 1.

Renal Adverse Events Associated with Lithium, Semaglutide, and Their Combination Compared to All Other Drugs in FAERS

Figure 1.

Forest plots of RORs were generated for lithium, semaglutide, and their combination across key renal adverse events.

In contrast, semaglutide showed inverse associations for renal impairment (ROR = 0.54, 95%CI = 0.43–0.69, p < 0.0001, IC025 = −1.29), renal failure (ROR = 0.51, 95%CI = 0.42–0.62, p < 0.0001, IC025 = −1.30), CKD (ROR = 0.42, 95%CI = 0.33–0.53, p < 0.0001, IC025 = −1.67), and ESRD (ROR = 0.25, 95%CI = 0.13–0.50, p = 0.0001, IC025 = −3.14), while the association with AKI was neutral (ROR = 0.96, 95%CI = 0.85–1.09, p = 0.51, IC025 = −0.27). None of the semaglutide outcomes met the disproportionality signal threshold (IC025 < 0).

Co-reporting of lithium and semaglutide produced no estimable RORs for renal impairment, renal failure, CKD, or ESRD because of zero reported cases. For AKI, 2 co-reported cases were identified (ROR = 5.81, 95%CI = 1.41–24.01, p = 0.015, IC025 = −1.05); however, this also did not meet the statistical signal threshold (IC025 < 0).

Discussion

In this large population-based pharmacovigilance study, and in accordance with lithium’s known nephrotoxic effects, lithium use was associated with significantly elevated reporting odds of renal impairment, acute renal failure, CKD, and ESRD. We also observed that concomitant administration of semaglutide with lithium did not yield a corresponding increase in nephrotoxicity signals. This observation potentially provides preliminary support for the hypothesis that GLP-1 RAs may exert a potentially protective effect on lithium-associated renal injury. Over the past 2 decades, longitudinal studies and registry analyses have revised prior estimates of lithium-induced nephropathy, indicating that while the absolute risk may be lower than historically reported, lithium exposure remains a cause and contributor to CKD progression and a not infrequent reason for treatment discontinuation.Reference Qian, Sud and Lee 3 , Reference Roxanas, Grace and George 29 –Reference McIntyre, Mancini, Parikh and Kennedy 31

GLP-1 RAs are increasingly prescribed for metabolic conditions that differentially affect individuals living with bipolar disorder, including obesity, type 2 diabetes mellitus, obstructive sleep apnea, and CKD.Reference McIntyre, Alda and Baldessarini 32 –Reference Liu, Ling and Lui 34 Beyond their metabolic benefits, GLP-1 RAs have demonstrated reductions in cardiovascular morbidity and mortality, which is the leading contributor to excess and premature mortality in bipolar disorder.Reference Goldstein, Baune and Bond 35 Moreover, GLP-1 RAs have been investigated for use in psychotropic-drug-related weight gain, binge eating, metabolic liver disease, and substance- or alcohol-use disorders, all of which are clinical presentations that are frequently encountered in the bipolar population.Reference McIntyre, Kwan, Rosenblat, Teopiz and Mansur 36 –Reference Zheng, Soegiharto and Au 40

The molecular and cellular dynamics affected by GLP-1 RAs have separately introduced a hypothesis that these agents may hold therapeutic potential in the treatment and prevention of mental disorders and progressive cognitive impairment.Reference McIntyre, Rasgon and Goldberg 41 For example, GLP-1 RAs are known to promote neurogenesis, neuroplasticity, and autophagy while reducing inflammation, oxidative stress, and neuronal apoptosis within critical neural circuits.Reference McIntyre, Rasgon and Goldberg 41 –Reference Au, Zheng and Le 43 The molecular, cellular, and circuit-level effects attributed to GLP1-RAs may confer neuroprotective effects against the progression of illness, particularly with respect to cognitive functioning.Reference Au, Lam, Lim and McIntyre 44

However, our findings must be carefully and cautiously interpreted, as they are regarded as highly exploratory and hypothesis-generating. The overarching reason for a measured interpretation of our findings is that analyzing data in a pharmacovigilance dataset (eg, FAERS) is not capable of establishing causality, and such databases are not intended to inform deliberation as to whether protective effects exist. Disproportionality analyses, including ROR and IC025, quantify reporting patterns relative to background rates and do not measure clinical risk or incidence.Reference Prieto-Merino, Quartey, Wang and Kim 45 Accordingly, an IC025 value below zero indicates an absence of disproportionality rather than a signal of protection.Reference Prieto-Merino, Quartey, Wang and Kim 45 These metrics are meant to detect safety signals, not infer benefit; an inverse IC025 reflects a reporting trend rather than therapeutic protection and requires validation in patient-level studies.Reference Böhm, Bulin, Waetzig, Cascorbi, Klein and Herdegen 46 These findings, therefore, cannot be interpreted as evidence that GLP-1 RAs confer a true renoprotective effect.

The limitations of our analysis, as well as any inference, interpretation, or implementation messaging derive from our methodology. Herein, we used the US FAERS, which relies on spontaneous reporting from the general population as well as industry sponsors (for whom reporting is mandatory). 47 Spontaneous reporting of any AE cannot be considered a comprehensive estimate of its occurrence. Moreover, FAERS does not include information related to variables that would be required before cause and effect can be established (ie, the Bradford Hill criteria).Reference Shimonovich, Pearce, Thomson, Keyes and Katikireddi 48 In addition, we are not able to know, in the general population, what percentage of persons prescribed lithium have also been prescribed a GLP-1 RA, including semaglutide. Notwithstanding this limitation, the prescription of GLP-1 RAs has increased approximately 700% in the US during the past 4 y, and approximately 12% of US adults have been prescribed GLP-1 RAs, with 6% of the population prescribed semaglutide.Reference Mahase 49 , Reference Harris 50 In addition, as stated earlier, GLP-1 RAs are indicated and/or prescribed off-label for many conditions known to differentially affect persons living with depressive and bipolar disorders.Reference McIntyre, Kwan, Rosenblat, Teopiz and Mansur 36 Consequently, it can be assumed that a percentage (albeit unknown percentage) of persons prescribed lithium may also have been co-prescribed a GLP-1 RA.

In addition to the aforementioned points, multiple other limitations should be acknowledged. First, the absence of denominator data precludes estimation of event incidence or risk ratios, as the total number of exposed individuals (to lithium, GLP-1 RAs, or both) is unknown. Second, confounding by indication is likely, as GLP-1 RAs are prescribed primarily to individuals with type 2 diabetes or obesity, who differ from lithium-treated patients in metabolic risk, renal surveillance intensity, and access to nephrology care. Third, confounding by indication may introduce channeling bias, since patients with advanced renal disease are often excluded from GLP-1 RA therapy, potentially creating an artificial appearance of protection. Fourth, FAERS is inherently susceptible to multiple reporting biases—including notoriety bias, where regulatory or media attention increases reporting; the Weber effect, characterized by heightened reporting shortly after drug approval; and surveillance bias due to differential clinical monitoring. Fifth, co-reporting cases were extremely limited, yielding low statistical power and wide uncertainty intervals that preclude meaningful inference.

Furthermore, the broader limitations of spontaneous reporting systems must be recognized. FAERS data depend on voluntary submissions from clinicians, patients, and manufacturers, resulting in underreporting and variable data completeness. The database also lacks patient-level covariates such as baseline renal function, diabetes severity, medication dose, duration of exposure, and comorbid conditions—all of which are essential for causal inference. Temporal trends in drug utilization and awareness may further influence reporting frequency, adding uncertainty to observed associations. Consequently, these results should be regarded strictly within the descriptive and hypothesis-generating scope of pharmacovigilance rather than as confirmatory evidence.

The hypothesis that semaglutide and/or other GLP-1 RAs are protective against lithium-induced nephrotoxicity cannot be considered proven by our results. Instead, our results provide preliminary support for the viable and testable hypothesis of renal protection, and it is our hope that they provide impetus for comprehensive mechanistic, histopathologic, and clinical studies with adequate methodology. It also needs to be clearly stated that GLP-1 RAs have multiple AEs and safety concerns, which reduce acceptability and have been difficult to access for eligible persons due to acquisition cost barriers. In addition, early reports of suicidality associated with these agents resulted in regulatory investigations concluding that cause and effect cannot be established but should continue to be a variable for further evaluation.Reference McIntyre, Mansur, Rosenblat and Kwan 24 , Reference McIntyre, Mansur and Rosenblat 51 –Reference Wang, Volkow, Berger, Davis, Kaelber and Xu 53

In conclusion, our overarching aim is to encourage comprehensive assessments of whether semaglutide (and/or other incretin receptor agonists) is capable of exerting nephroprotective effects in persons exposed to lithium. Definitive evidence would require triangulation of histopathologic, clinical, and observational studies with adequate methodology to determine cause and effect. Analyses based on pharmacovigilance data are inadequate to address causality and can neither confirm nor refute potential benefits of incretin receptor agonists in this context. Nonetheless, the absence of significant co-reporting of lithium nephrotoxicity and semaglutide—though potentially unrelated—could be aligned with an as yetunconfirmed hypothesis that incretin receptor agonists may be renally protective against lithium-associated injury.

Data availability statement

All data relevant to the study are included in the article.

Author contribution

Both authors (R.S.M. and A.K.) conceptualized, designed, and drafted the manuscript, as well as provided critical review for important intellectual concepts and approved the final version to be published. R.S.M. and A.K. analyzed and interpreted the data. Both authors agree to be accountable for all aspects of the work.

Financial support

This study was not funded. The FAERS database is publicly available without restriction.

Disclosure

R.S.M. has received research grant support from CIHR/GACD/National Natural Science Foundation of China (NSFC). RSM has also received and the Milken Institute; speaker/consultation fees from Lundbeck, Janssen, Alkermes, Neumora Therapeutics, Boehringer Ingelheim, Sage, Biogen, Mitsubishi Tanabe, Purdue, Pfizer, Otsuka, Takeda, Neurocrine, Neurawell, Sunovion, Bausch Health, Axsome, Novo Nordisk, Kris, Sanofi, Eisai, Intra-Cellular, NewBridge Pharmaceuticals, Viatris, Abbvie, and Atai Life Sciences. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

References

McIntyre, RS, Berk, M, Brietzke, E, et al. Bipolar disorders. Lancet. 2020;396(10265):1841–1856.10.1016/S0140-6736(20)31544-0CrossRefGoogle ScholarPubMed
Yatham, LN, Chakrabarty, T, Bond, DJ, et al. Canadian network for mood and anxiety treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) recommendations for the management of patients with bipolar disorder with mixed presentations. Bipolar Disord. 2021;23(8):767–788.10.1111/bdi.13135CrossRefGoogle Scholar
Qian, E, Sud, K, Lee, V. Lithium-associated kidney failure: predictors and outcomes. Kidney Int Rep. 2024;9(5):1276–1283.10.1016/j.ekir.2024.01.047CrossRefGoogle ScholarPubMed
Kerckhoffs, APM, Hartong, EGTM, Grootens, KP. The perspectives of patients with lithium-induced end-stage renal disease. Int J Bipolar Disord. 2018;6(1):13.10.1186/s40345-018-0121-0CrossRefGoogle ScholarPubMed
Davis, J, Desmond, M, Berk, M. Lithium and nephrotoxicity: a literature review of approaches to clinical management and risk stratification. BMC Nephrol. 2018;19(1):305.Google ScholarPubMed
Gong, R, Wang, P, Dworkin, L. What we need to know about the effect of lithium on the kidney. Am J Physiol Renal Physiol. 2016;311(6):F1168–F1171.10.1152/ajprenal.00145.2016CrossRefGoogle ScholarPubMed
Markowitz, GS, Radhakrishnan, J, Kambham, N, Valeri, AM, Hines, WH, D’Agati, VD. Lithium nephrotoxicity: a progressive combined glomerular and tubulointerstitial nephropathy. J Am Soc Nephrol.. 2000;11(8):1439–1448.Google ScholarPubMed
Ossani, GP, Uceda, AM, Acosta, JM, et al. Role of oxidative stress in lithium-induced nephropathy. Biol Trace Elem Res. 2019;191(2):412–418.Google ScholarPubMed
Drucker, DJ. GLP-1 physiology informs the pharmacotherapy of obesity. Mol Metab. 2022;57:101351.Google ScholarPubMed
J, C, Me, C, Mt, C. Renoprotective mechanisms of glucagon-like peptide-1 receptor agonists. Diabetes Metab. 2025;51(3):101641.10.1016/j.diabet.2025.101641CrossRefGoogle Scholar
OpenVigil - open tools for data-mining and analysis of pharmacovigilance data. https://openvigil.sourceforge.net/ (accessed 8 May 2025).Google Scholar
Lakhani, M, Kwan, ATH, Mihalache, A, et al. Association of glucagon-like peptide-1 receptor agonists with optic nerve and retinal adverse events: a population-based observational study across 180 countries. Am J Ophthalmolo. 2025;277:148–168.10.1016/j.ajo.2025.05.007CrossRefGoogle ScholarPubMed
Lakhani, M, Kwan, ATH, Mihalache, A, Popovic, MM, Hurley, B, Muni, RH. Drugs associated with floppy iris syndrome: a real-world population-based study. Am J Ophthalmol. 2025;275:36–46.10.1016/j.ajo.2025.03.023CrossRefGoogle ScholarPubMed
Lakhani, M, Kwan, ATH, Kundapur, D, Popovic, MM, Damji, KF, Hurley, BR. Association of anti-VEGF therapy with reported ocular adverse events: a global pharmacovigilance analysis. Ophthalmol Retina. Published online September. 2025;1S2468-6530(25)00393-8. https://doi.org/10.1016/j.oret.2025.08.018.CrossRefGoogle ScholarPubMed
McIntyre, RS, Wong, S, Kwan, ATH, et al. Association between dual orexin receptor antagonists (DORAs) and suicidality: reports to the United States Food and Drug Administration adverse event reporting system (FAERS). Expert Opin Drug Saf. 2024;24(6):1–5.10.1080/14740338.2024.2430306CrossRefGoogle Scholar
Lakhani, M, Kwan, ATH, Chaudry, E, et al. A real-world population-based study on the association between cataracts and antipsychotics. Can J Ophthalmol. 2025;23:S0008-4182(25)00266-2 https://www.canadianjournalofophthalmology.ca/article/S0008-4182(25)00266-2/fulltext (accessed 21 June 2025).Google Scholar
Lakhani, M, Kwan, ATH, Nguyen, AXL, Popovic, MM, McIntyre, RS, Wu, AY. Association of ocular adverse events with varenicline solution use: a population-based study. Expert Opin Drug Saf. Published online February. 2025;8:1–9.Google Scholar
Kwan, ATH, Lakhani, M, Rosenblat, JD, et al. A global population-based study on the association between ketamine and esketamine with suicidality using WHO VigiBase. J Clin Psychiatry. 2025;86(3):24m15534.Google Scholar
Rushovich, T, Gompers, A, Lockhart, JW, et al. Adverse drug events by sex after adjusting for baseline rates of drug use. JAMA Netw Open. 2023;6(8):e2329074.10.1001/jamanetworkopen.2023.29074CrossRefGoogle ScholarPubMed
Dores, GM, Bryant-Genevier, M, Perez-Vilar, S. Adverse events associated with the use of sipuleucel-T reported to the US food and drug administration’s adverse event reporting system, 2010-2017. JAMA Netw Open. 2019;2(8):e199249.10.1001/jamanetworkopen.2019.9249CrossRefGoogle Scholar
MedDRA. accessed May 8, 2025. https://www.meddra.org/.Google Scholar
Accessed May 8, 2025. https://aws.amazon.com/marketplace/pp/prodview-dtj4qudubgmca#overview.Google Scholar
Food and Drug Administration. Providing regulatory submissions in electronic format: investigational new drug application safety reports; guidance for industry; availability. Federal Register. https://www.federalregister.gov/documents/2024/04/01/2024-06736/providing-regulatory-submissions-in-electronic-format-investigational-new-drug-application-safety.Google Scholar
McIntyre, RS, Mansur, RB, Rosenblat, JD, Kwan, ATH. The association between glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and suicidality: reports to the Food and Drug Administration adverse event reporting system (FAERS). Expert Opin Drug Safety. 2024;23(1):47–55.10.1080/14740338.2023.2295397CrossRefGoogle Scholar
Kwan, ATH, Lakhani, M, Teopiz, KM, et al. Hepatic adverse events associated with ketamine and esketamine: a population-based disproportionality analysis. J Affect Disord. 2025;1(374):390–396 https://doi.org/10.1016/j.jad.2025.01.054.Google Scholar
Evans, SJ, Waller, PC, Davis, S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf. 2001;10(6):483–486.10.1002/pds.677CrossRefGoogle ScholarPubMed
Goligher, EC, Heath, A, Harhay, MO. Bayesian statistics for clinical research. Lancet. 2024;404(10457):1067–1076.10.1016/S0140-6736(24)01295-9CrossRefGoogle ScholarPubMed
Röver, C, Friede, T. Dynamically borrowing strength from another study through shrinkage estimation. Stat Methods Med Res. 2020;29(1):293–308.Google ScholarPubMed
Roxanas, M, Grace, BS, George, CRP. Renal replacement therapy associated with lithium nephrotoxicity in Australia. Med J Aust. 2014;200(4):226–228.10.5694/mja13.10435CrossRefGoogle ScholarPubMed
Presne, C, Fakhouri, F, Noël, LH, et al. Lithium-induced nephropathy: rate of progression and prognostic factors. Kidney Int. 2003;64(2):585–592.Google ScholarPubMed
McIntyre, RS, Mancini, DA, Parikh, S, Kennedy, SH. Lithium revisited. Can J Psychiatr. 2001;46(4):322–327.Google ScholarPubMed
McIntyre, RS, Alda, M, Baldessarini, RJ, et al. The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management. World Psychiatry. 2022;21(3):364–387.10.1002/wps.20997CrossRefGoogle ScholarPubMed
Jawad, MY, Meshkat, S, Tabassum, A, et al. The bidirectional association of nonalcoholic fatty liver disease with depression, bipolar disorder, and schizophrenia. CNS Spectrums. 2023;28(5):541–560.Google Scholar
Liu, YK, Ling, S, Lui, LMW, et al. Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: a systematic review and meta-analysis. J Affect Disord. 2022;300:449–461.10.1016/j.jad.2021.12.110CrossRefGoogle ScholarPubMed
Goldstein, BI, Baune, BT, Bond, DJ, et al. Call to action regarding the vascular-bipolar link: a report from the vascular task force of the International Society for Bipolar Disorders. Bipolar Disord. 2020;22(5):440–460.10.1111/bdi.12921CrossRefGoogle Scholar
McIntyre, RS, Kwan, ATH, Rosenblat, JD, Teopiz, KM, Mansur, RB. Psychotropic drug–related weight gain and its treatment. AJP.. 2024;181(1):26–38.Google ScholarPubMed
McIntyre, RS, Mancini, DA, McCann, S, Srinivasan, J, Kennedy, SH. Valproate, bipolar disorder and polycystic ovarian syndrome. Bipolar Disord. 2003;5(1):28–35.Google ScholarPubMed
Liu, J, Teng, Z, Xie, H, et al. Prevalence and characteristics of polycystic ovarian syndrome in patients with bipolar disorder. J Affect Disord. 2023;340:387–395.Google ScholarPubMed
Himmerich, H, Bentley, J, McElroy, SL. Pharmacological treatment of binge eating disorder and frequent comorbid diseases. CNS Drugs. 2024;38(9):697–718.Google ScholarPubMed
Zheng, YJ, Soegiharto, C, Au, HCT, et al. A systematic review on the role of glucagon-like peptide-1 receptor agonists on alcohol-related behaviors: potential therapeutic strategy for alcohol use disorder. Acta Neuropsychiatrica. 2025;37:e51.Google ScholarPubMed
McIntyre, RS, Rasgon, N, Goldberg, J, et al. The effect of glucagon-like peptide-1 and glucose dependent insulinotropic polypeptide receptor agonists on neurogenesis, differentiation, and plasticity (neuro-GDP): potential mechanistically informed therapeutics in the treatment and prevention of mental disorders. CNS Spectrums. 2025;30(1):e23.10.1017/S1092852925000124CrossRefGoogle ScholarPubMed
Au, HCT, Zheng, YJ, Le, GH, et al. Association of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and neurogenesis: a systematic review. Acta Neuropsychiatrica. 2025;37:e50.10.1017/neu.2025.4CrossRefGoogle ScholarPubMed
Au, HCT, Zheng, YJ, Le, GH, et al. A systematic review in effects of glucagon-like peptide-1 (GLP-1) mono-agonists on functional connectivity: target engagement and rationale for the development in mental disorders. J Affect Disord. 2025;370:321–327.10.1016/j.jad.2024.11.019CrossRefGoogle ScholarPubMed
Au, HCT, Lam, PH, Lim, PK, McIntyre, RS. Role of glucagon-like Peptide-1 on amyloid, tau, and α-synuclein: target engagement and rationale for the development in neurodegenerative disorders. Neurosci Biobehav Rev. 2025;173(106159):106159.10.1016/j.neubiorev.2025.106159CrossRefGoogle ScholarPubMed
Prieto-Merino, D, Quartey, G, Wang, J, Kim, J. Why a Bayesian approach to safety analysis in pharmacovigilance is important. Pharm Stat. 2011;10(6):554–559.10.1002/pst.524CrossRefGoogle Scholar
Böhm, R, Bulin, C, Waetzig, V, Cascorbi, I, Klein, HJ, Herdegen, T. Pharmacovigilance-based drug repurposing: the search for inverse signals via OpenVigil identifies putative drugs against viral respiratory infections. Br J Clin Pharmacol. 2021;87(11):4421–4431.10.1111/bcp.14868CrossRefGoogle ScholarPubMed
[No title]. https://open.fda.gov/data/faers/ (accessed 10 October 2025).Google Scholar
Shimonovich, M, Pearce, A, Thomson, H, Keyes, K, Katikireddi, SV. Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking. Eur J Epidemiol. 2021;36(9):873–887.10.1007/s10654-020-00703-7CrossRefGoogle Scholar
Mahase, E. GLP-1 agonists: US sees 700% increase over four years in number of patients without diabetes starting treatment. BMJ. 2024;386:q1645.Google ScholarPubMed
Harris, E. Poll: roughly 12% of US adults have used a GLP-1 drug, even if unaffordable. JAMA. 2024;332(1):8.Google ScholarPubMed
McIntyre, RS, Mansur, RB, Rosenblat, JD, et al. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and suicidality: a replication study using reports to the World Health Organization pharmacovigilance database (VigiBase®). J Affect Disord. 2025;369:922–927.10.1016/j.jad.2024.10.062CrossRefGoogle Scholar
Valentino, K, Teopiz, KM, Cheung, W, et al. The effect of glucagon-like peptide-1 receptor agonists on measures of suicidality: a systematic review. J Psychiatr Res. 2025;183:112–126.10.1016/j.jpsychires.2025.02.008CrossRefGoogle ScholarPubMed
Wang, W, Volkow, ND, Berger, NA, Davis, PB, Kaelber, DC, Xu, R. Association of semaglutide with risk of suicidal ideation in a real-world cohort. Nat Med. 2024;30(1):168–176.10.1038/s41591-023-02672-2CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Renal Adverse Events Associated with Lithium, Semaglutide, and Their Combination Compared to All Other Drugs in FAERS

Figure 1

Figure 1. Forest plots of RORs were generated for lithium, semaglutide, and their combination across key renal adverse events.