Aripiprazole as protector against COVID-19 mortality

1 Vol.:(0123456789) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports Aripiprazole as protector against COVID‑19 mortality C. Loucera‑Muñecas 1,2,9, M. Canal‑Rivero 3,4,5,9*, M. Ruiz‑Veguilla 3,4,5,6, R. Carmona 1,2, G. Bostelmann 1,2, N. Garrido‑Torres 3,4,5, J. Dopazo 1,2,7,8 & B. Crespo‑Facorro 3,4,5,6 The relation of antipsychotics with severe Coronavirus Disease 19 (COVID‑19) outcomes is a matter of debate since the beginning of the pandemic. To date, controversial results have been published on this issue. We aimed to prove whether antipsychotics might exert adverse or protective effects against fatal outcomes derived from COVID‑19. A population‑based retrospective cohort study (January 2020 to November 2020) comprising inpatients (15,968 patients) who were at least 18 years old and had a laboratory‑confirmed COVID‑19 infection. Two sub‑cohorts were delineated, comprising a total of 2536 inpatients: individuals who either had no prescription medication or were prescribed an antipsychotic within the 15 days preceding hospitalization. We conducted survival and odds ratio analyses to assess the association between antipsychotic use and mortality, reporting both unadjusted and covariate‑adjusted results. We computed the average treatment effects, using the untreated group as the reference, and the average treatment effect on the treated, focusing solely on the antipsychotic‑treated population. Among the eight antipsychotics found to be in use, only aripiprazole showed a significant decrease in the risk of death from COVID‑19 [adjusted odds ratio (OR) = 0.86; 95% CI, 0.79–0.93, multiple‑testing adjusted p‑value < 0.05]. Importantly, these findings were consistent for both covariate‑adjusted and unadjusted analyses. Aripiprazole has been shown to have a differentiated beneficial effect in protecting against fatal clinical outcome in COVID‑19 infected individuals. We speculate that the differential effect of aripiprazole on controlling immunological pathways and inducible inflammatory enzymes, that are critical in COVID19 illness, may be associated with our findings herein. Keywords COVID-19, Antipsychotics, Mortality, SARS-CoV-2 The outbreak originated by Severe Acute Respiratory Syndrome due to Coronavirus-2 (SARS-CoV-2) started at the end of 2019 in Wuhan, China. The World Health Organization declared it a global pandemic in March 20201. At the time this article was written, a new SARS-CoV-2 variant concerns the scientific and health authorities2. As a result, it has been observed an increase in infections and hospitalizations due to COVID-19 across worldwide3–5 and some World Health Organization (WHO) regions such as Western Pacific Regions have experienced an increase in the number of deaths6. The new COVID-19 waves as well as the potential mutations of the virus represent a new risk for the general population and particularly for those at high risk7. It has been suggested that the psychosocial effects of SARS-CoV-2 on the population will lead to an increase in the use of medication in treating mental health conditions, thus the potential effects of these medications should be considered in the light of COVID-19 treatment8. A risen in the prescription of antipsychotics in at-risk populations after the pandemic caused by COVID-19 has been recently described9. Controversial results have been published on the potential role of antipsychotics in COVID-19. While some studies pointed out possible adverse effects10,11, others have reported protective effects against infection and prognosis of the disease caused by SARS-CoV-212,13. During SARS-CoV-2 infection multiple inflammatory pathways are activated that promotes secretion of proinflammatory cytokines14. Antipsychotics exert anti-inflammatory effects via reducing proinflammatory cytokines production, modulating monocytes response through Toll-Like OPEN 1Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain. 2Computational Systems Medicine, Institute of Biomedicine of Seville (IBiS), University Hospital Virgen del Rocío, Consejo Superior de Investigaciones Científicas, University of Seville, Seville, Spain. 3Hospital Universitario Virgen del Rocío, Av. Manuel Siurot, s/n, 41013 Sevilla, Spain. 4Centro Investigación Biomédica en Red Salud Mental, CIBERSAM, Madrid, Spain. 5Instituto de Biomedicina de Sevilla (IBiS), HUVR/CSIC/Universidad de Sevilla, Seville, Spain. 6Department of Psychiatry, Universidad de Sevilla, Seville, Spain. 7Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Seville, Spain. 8FPS, ELIXIR-Es, Hospital Virgen del Rocío, Seville, Spain. 9 These authors contributed equally: C. Loucera-Muñecas and M. Canal-Rivero. *email: [email protected] 2 Vol:.(1234567890) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ Receptors (TLR) and inhibiting microglial activation15–17. In humans, the immunomodulatory effect of risperidone and aripiprazole has been demonstrated18, with aripiprazole demonstrating a greater anti-inflammatory effect on TNF-α, IL-13, IL-17α and fractalkine. Nevertheless, important limitations have been highlighted in these studies such as the need to explore specific types of antipsychotics, doses, or the inclusion of relevant covariables in the analyses19. In fact, it has been emphasized the necessity of combining experimental and clinical studies to elucidate the relevance and repercussions that could have the use of antipsychotics during COVID-19 era20. The aim of this study was to investigate if antipsychotic treatments have a protective or adverse impact on COVID-19 related deaths. We leveraged the Andalusian Public Health System’s Health Population Base (BPS), a vast electronic health record (EHR) resource established in 2001. Encompassing over 13 million users, the BPS represents one of the world’s most extensive clinical data repositories21. The BPS’s size and comprehensiveness create an exceptional environment for conducting large-scale real-world evidence (RWE) studies. Based on our previous studies22,23 we hypothesized that persons under aripiprazole treatment will show reductions in the risk of death by COVID-19. Materials Study design The study was approved by the Ethics Committee for the Coordination of Biomedical Research in Andalusia (29 September 2020, Acta 09/20) and by the Local Ethics Committee of Virgen del Rocío University Hospital (PI- 2578-N-20). Informed consent was not required for the secondary use of clinical data for research. For secure real-world data analysis, the study utilized the Infrastructure for secure generation of Real-World Evidence from Real World Data from the Andalusian Health Population Database (iRWD) managed by the Foundation for Progress and Health of the Andalusian Public Health System. The data was securely transferred from the BPS to the iRWD, thereby ensuring the safety and integrity of the information throughout the process. The study consists of a retrospective cohort of Andalusian patients hospitalized with a COVID-19 diagnosis from January 2020 to November 2020, as registered in the BPS. The sample (n = 2.536) consisted of inpatients who met the following criteria: age of 18years or older, having a laboratory-confirmed COVID-19 infection (either PCR or antigen test) and who were either not prescribed any medication or were prescribed an antipsychotic during the 15days prior to the hospitalization event. We identified 15,968 inpatients who met the inclusion criteria before selecting the antipsychotic-treated and untreated subcohort. Covariate, event, and endpoint definition To reduce the high dimensionality induced by the ICD codes we grouped the conditions as: obesity and other associated conditions (E66), diabetes mellitus (E11), circulatory (I00–I99), respiratory (J00–J99), neoplasms (C00–D49), dementia (F00–F03), anxiety or mood disorders (F30–F48), and other mental diseases (F04–F29 and F50–F99). In addition, we obtained the following data for each patient: sex, age categorized as [18, 41), [41, 68) and [68, 99), flu vaccination status, and pneumococcal vaccination status. This categorization follows24 and25. Finally, we used death from COVID-19 as the primary outcome, defined as the endpoint by a certified death event during the first 30days of a COVID-19 hospitalization, based on26. Treatment definition The seven antipsychotics examined in this analysis are Quetiapine, Sulpiride, Paliperidone, Aripiprazole, Haloperidol, Olanzapine, and Risperidone (all the antipsychotics found in the population under study). A patient was considered to be under a specific treatment if they received a dispensation of that treatment between 15days prior to the index date and the index date itself. In addition to antipsychotic medications, we investigated whether each patient had received any anticoagulant medications during the same timeframe (between 15days before and the index date). To reduce the dimensionality introduced by the variety of anti-inflammatory treatments used by the cohort, we categorized patients into two groups: those receiving any anti-inflammatory medication and those not receiving any (See Supplementary Material). General description of the population under study Table1 shows the characteristics of the cohort studied. The cohort is divided into those who died and those who survived. The table reveals several key differences between the two groups. Notably, the deceased group had a significantly higher average age (79.09years) compared to survivors (62.89years). Vaccination rates were also higher among deceased patients, with a greater percentage having received flu and pneumococcal vaccinations. Perhaps most significantly, the table suggests a higher prevalence of underlying medical conditions in the deceased group, including diabetes, circulatory diseases, neoplasms, respiratory diseases, and dementia. Interestingly, the data also shows that Quetiapine (DB01224), an antipsychotic medication, was used more frequently by deceased patients (22.4%) compared to survivors (15.1%), whereas out of the 31 patients that were using Aripiprazole only 1 died, highlighting a potential difference in the impact of these medications on mortality risk. As expected, Table1 shows a cohort where deceased patients were older, had a higher prevalence of vaccinations and underlying health conditions, and were more likely to have used Quetiapine. Drug processing Drug prescription data of Andalusian public health care patients were received in three separate data dumps from the BPS database: the first one on Nov 17, 2020 with 12,009 prescription entries containing any one of the seven antipsychotics, and the second and third ones on Feb 15, 2021 with 13,413 and 19,391 entries, respectively. The data sets were combined into one and parsed as follows: each drug prescription entry was broken down 3 Vol.:(0123456789) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ into its active constituent agents, and for each patient, each of their prescription date and each active agent the following fields were extracted: Encrypted NUHSA code (patient identifier) Description of the prescribed medication Active agent Amount of agent per unit (e.g. per capsule, tablet, solution, or injection) Dose/mode of administration The total amount administered by prescription Prescription date In the case of the seven antipsychotics at hand, there is only one active ingredient per prescription, which is the antipsychotic itself, so the number of entries/rows before and after parsing remains the same. Duplicate entries, which might have resulted from overlaps in the data dumps, were removed. The resulting data set contained 33,348 entries. Next, for each entry the number of days between the prescription date and that of the subsequent entry (same patient, active agent), if there was any, was calculated. Based on this number of days between two given subscriptions and the total amount of active agents administered in the preceding prescription, which had previously been determined, the average daily dose of the preceding prescription was calculated. This was done for all prescriptions followed by a subsequent prescription. Finally, for each patient and each active ingredient occurring in their prescriptions, an average over all the average daily doses was calculated. So, the following three fields were added to the data set: • Days to next prescription • The average daily dose of prescription • Total average of all average doses (patient-wise, per active agent) Drug information is summarized in Table2. Methods The study procedures were in accordance with local legislation and the Declaration of Helsinki27. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies28. To elucidate if any given treatment could potentially reduce the mortality in COVID-19 inpatients we conducted three statistical tests that consider covariates that present an a priori possibility of confounding the Table 1. Covariate associations with end point: Chi-squared tests, p-values, counts, and proportions. Death (no) Death (yes) p-value N 1968 568 Sex (female) (%) 896 (45.5) 249 (43.8) 0.506 Flu vaccine (%) 756 (38.4) 336 (59.2) < 0.001 Pneumococcal vaccine (%) 438 (22.3) 196 (34.5) < 0.001 Obesity (%) 249 (12.7) 80 (14.1) 0.410 Diabetes (%) 461 (23.4) 191 (33.6) < 0.001 Circulatory (%) 991 (50.4) 416 (73.2) < 0.001 Neoplasms (%) 197 (10.0) 85 (15.0) 0.001 Respiratory (%) 323 (16.4) 125 (22.0) 0.003 Dependences (%) 139 (7.1) 30 (5.3) 0.160 Dementia (%) 338 (17.2) 188 (33.1) < 0.001 Anxiety or mood disorders (%) 395 (20.1) 113 (19.9) 0.973 Other mental diseases (%) 644 (32.7) 192 (33.8) 0.666 Age [mean (SD)] 62.89 (18.64) 79.09 (11.94) < 0.001 Other antiinflammatory (%) 1779 (90.4) 507 (89.3) 0.472 Sulpiride (DB00391) (%) 103 (5.2) 29 (5.1) 0.989 Quetiapine (DB01224) (%) 297 (15.1) 127 (22.4) < 0.001 Paliperidone (DB01267) (%) 27 (1.4) 9 (1.6) 0.860 Aripiprazole (DB01238) (%) 30 (1.5) 1 (0.2) 0.018 Haloperidol (DB00502) (%) 155 (7.9) 51 (9.0) 0.447 Olanzapine (DB00334) (%) 63 (3.2) 17 (3.0) 0.909 Risperidone (DB00734) (%) 104 (5.3) 42 (7.4) 0.072 4 Vol:.(1234567890) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ Mode of administration # Patients Mean # prescriptions per patient Mean daily dosea Mean time span between prescriptions NA’sb Min Median Max Aripiprazole 1 IM injection at 300mg 3 17.7 19.7mg/day 17d 27d 31d 0 1 IM injection at 400mg 5 12.4 14mg/day 28d 29d 32d 0 150ml oral solution at 1mg/ml 2 11.5 22.5mg/day 16d 22d 28d 0 28 tablets at 5mg 11 10.3 5.7mg/day 21d 27d 82d 2 28 tablets at 10mg 16 8.3 10mg/day 23d 32d 54d 3 28 tablets at 15mg 7 5.6 15.4mg/day 23d 27d 30d 3 28 tablets at 20mg 2 10 20.7mg/day 28d 28d 28d 0 Haloperidol 5 IM injections at 5mg 11 1.3 0.2mg/day 125d 340d 554d 9 15ml oral solution/dayrops at 2mg/ml 72 5.5 2.6mg/day 8d 20d 222d 38 30ml oral solution/dayrops at 2mg/ml 217 7.2 4.8mg/day 5d 36d 561d 75 30 tablets at 10mg 11 15.7 24.9mg/day 11d 25d 71d 3 Olanzapine 1 IM injection at 10mg 1 2 1mg/day 10d 10d 10d 0 28 capsules at 2.5mg 4 7.8 5.1mg/day 13d 21d 36d 1 28 capsules at 5mg 7 12 11.5mg/day 9d 32d 242d 0 28 capsules at 10mg 5 11.6 15.8mg/day 10d 25d 31d 1 56 capsules at 10mg 7 2.3 8.5mg/day 53d 56d 136d 2 28 capsules at 15mg 6 18.5 23.1mg/day 14d 28d 33d 0 28 capsules at 20mg 3 16 20.4mg/day 28d 28d 28d 0 28 tablets at 2.5mg 15 12.7 3.1mg/day 14d 29d 96d 4 28 tablets at 5mg 22 21.9 9.7mg/day 9d 28d 51d 3 28 tablets at 7.5mg 2 6 13.4mg/day 13d 20d 26d 0 56 tablets at 7.5mg 3 4.7 7.5mg/day 56d 56d 56d 2 28 tablets at 10mg 13 14.1 16.1mg/day 9d 23d 51d 3 56 tablets at 10mg 21 11.7 19.4mg/day 12d 53d 161d 2 28 tablets at 15mg 4 3.5 16.6mg/day 20d 27d 28d 1 28 tablets at 20mg 3 18.3 20.6mg/day 28d 28d 28d 0 Paliperidone 1 prefilled syringe at 75mg 2 12 2.8mg/day 29d 29d 29d 1 1 prefilled syringe at 100mg 6 14.7 3.4mg/day 28d 30d 37d 0 1 prefilled syringe at 150mg 10 13.6 5.8mg/day 20d 28d 52d 0 1 prefilled syringe at 350mg 2 3.5 3.8mg/day 92d 92d 92d 0 1 prefilled syringe at 525mg 1 8 5.6mg/day 97d 97d 97d 0 28 tablets at 3mg 11 16.1 4.8mg/day 14d 28d 44d 0 28 tablets at 6mg 5 16 7.2mg/day 13d 30d 50d 0 28 tablets at 9mg 4 24.5 17.3mg/day 14d 21d 28d 0 Quetiapine 6 tablets at 25mg 6 1.3 14.4mg/day 6d 23d 40d 4 60 tablets at 25mg 296 14.3 82.7mg/day 11d 29d 408d 30 10 tablets at 50mg 3 21.3 90.4mg/day 8d 20d 33d 1 60 tablets at 50mg 137 11.8 157.3mg/day 11d 31d 174d 23 60 tablets at 100mg 64 13.7 328.4mg/day 5d 35d 95d 3 60 tablets at 150mg 17 9.9 302.5mg/day 21d 39d 453d 4 60 tablets at 200mg 27 12.7 643.7mg/day 10d 55d 68d 4 60 tablets at 300mg 23 14 854.3mg/day 15d 32d 126d 3 60 tablets at 400mg 14 8.4 643mg/day 22d 60d 66d 3 Risperidone 1 IM injection at 25mg 2 28 2mg/day 14d 15d 17d 0 1 IM injection at 37.5mg 3 20.3 3mg/day 14d 15d 16d 0 1 IM injection at 50mg 3 20.7 3.5mg/day 14d 14d 25d 0 30ml oral solution at 5mg/5ml 21 10.6 2.7mg/day 6d 18d 76d 7 100ml oral solution at 5mg/5ml 65 10.2 5.3mg/day 12d 44d 166d 19 20 tablets at 500ug 2 1.5 714.3ug/day 14d 14d 14d 1 Continued 5 Vol.:(0123456789) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ association between a treatment and the odds of surviving COVID-19 disease (sex, age, co-morbidities, antiinflammatory medication use, and influenza and pneumococcal vaccination status): • The odds outcome was estimated using a general binomial linear model weighted using the inverse probability of treatment weighting (IPTW) technique, with the weights computed by means of a logistic regression model and adjusted for estimating the average treatment effect on the treated population (ATT), conditioned to the confounders of interest using the whole cohort, using the untreated population as the reference. • In addition, we conducted a similar analysis using the untreated group as the reference. In this case, the covariate adjustment was carried out by estimating the average treatment effect on the population (ATE). • Finally, we obtained the Kaplan–Meier survival curves for each treatment comparing the untreated versus the treated groups. We provide unadjusted curves along with IPTW covariate-adjusted matched survival curves. In both cases, we provide FDR-adjusted p values. Significance is achieved at level 0.05, and we provide 95% confidence intervals. To get an accurate measure of the variability of the marginal odds ratio we used heteroskedasticity-consistent standard errors29. The results have been summarized in Table3. Software To perform the analysis, we used: • R version 3.6.3 (2020-02-29) • Survival analysis: Survival R package (v 3.2.11)30 • Weights computation for IPW: WeightIt R package (v 0.12)31 • General linear models: glm R stats core package32. • Survival plots: survminer R package (v 0.4.9)33. • Table1: tableone R package (v 0.13.2)34. • HC standard errors computation: Sandwich R package (v 3.0.1)35 Ethical standards The study procedures were in accordance with local legislation and the Declaration of Helsinki. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. The protocol was approved by the Local Ethics Committee of Virgen del Rocío University Hospital (PI-2578-N-20). All participants data were anonymized to ensure confidentiality. Mode of administration # Patients Mean # prescriptions per patient Mean daily dosea Mean time span between prescriptions NA’sb Min Median Max 28 tablets at 500ug 6 7.2 679.7mcg/day 10d 24d 28d 2 56 tablets at 500ug 15 10.5 1401.7mcg/day 17d 31d 210d 3 60 tablets at 500ug 8 4.8 1593.6mcg/day 19d 30d 224d 2 20 tablets at 1mg 14 20.9 2.3mg/day 7d 17d 77d 2 28 tablets at 1mg 5 5 1mg/day 27d 28d 29d 3 56 tablets at 1mg 6 20.3 4.9mg/day 9d 25d 56d 1 60 tablets at 1mg 37 10.2 2.4mg/day 15d 32d 71d 10 28 tablets at 2mg 1 4 2.3mg/day 25d 25d 25d 0 56 tablets at 2mg 1 8 2mg/day 56d 56d 56d 0 60 tablets at 2mg 5 19.8 8.9mg/day 16d 19d 53d 0 20 tablets at 3mg 2 19.5 8.4mg/day 10d 23d 36d 0 60 tablets at 3mg 14 13 7.4mg/day 20d 36d 62d 3 30 tablets at 6mg 1 22 5.8mg/day 33d 33d 33d 0 60 tablets at 6mg 5 5.8 6mg/day 56d 60d 95d 0 Sulpiride 12 injections at 100mg 2 1 NA NA NA NA 2 30 capsules at 50mg 153 7.7 86.8mg/day 4d 30d 519d 73 36 tablets at 200mg 10 2.9 199.5mg/day 36d 36d 36d 9 Table 2. Antipsychotic type, mode of administration and dosage. a A given patient may be prescribed more than one mode of administration, so the mean daily dose of the patient includes all modes combined. b NA means a given patient only had one prescription of the drug, hence the mean daily dose and the time span between prescriptions cannot be determined. 6 Vol:.(1234567890) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ Results Aripiprazole is the only antipsychotic treatment that shows a protective effect, as can be evidenced by the 95% confidence intervals for the covariate-adjusted odds-ratio analysis (left side figure). Find a survival curve plot for each treatment in Supplementary material. This finding is further reinforced by the covariate-adjusted survival analysis on the matched population (right side figure). See Fig.1. Discussion The main finding derived from this study is that aripiprazole leads to reduction in the risk of death caused by COVID-19. On the contrary, the rest of the antipsychotic treatments included in the analyses did not significantly reduce the mortality related to COVID-19. Antipsychotics have been shown to exert anti-inflammatory effects through decreased proinflammatory cytokine production, modulation of monocyte response through TLR and inhibition of microglial activation16,17. Table 3. Covariate-adjusted Odds Ratio Estimates, Confidence Intervals and FDR-adjusted p-values for the antipsychotics tested. name n OR OR-CI 5% OR-CI 95% p val p val (fdr) estimand Aripiprazole 31 0.865 0.799 0.936 < 0.001 0.002 ATT 0.796 0.722 0.878 < 0.001 < 0.001 ATE Haloperidol 206 0.967 0.903 1.036 0.338 0.788 ATT 0.959 0.895 1.027 0.226 0.620 ATE Quetiapine 424 1.013 0.948 1.083 0.700 0.788 ATT 1.017 0.957 1.080 0.596 0.834 ATE Olanzapine 80 1.014 0.918 1.120 0.788 0.788 ATT 0.933 0.819 1.063 0.296 0.620 ATE Risperidone 146 1.020 0.941 1.106 0.627 0.788 ATT 1.041 0.956 1.133 0.354 0.620 ATE Paliperidone 36 1.039 0.893 1.210 0.620 0.788 ATT 0.983 0.714 1.354 0.918 0.985 ATE Sulpiride 132 0.947 0.865 1.038 0.246 0.788 ATT 0.998 0.832 1.198 0.985 0.985 ATE Figure1. Antipsychotic’s impact on patient survival. Left: adjusted odds ratios (with 95% confidence intervals) for all treatments before and after FDR correction, to assess the effect on death after hospitalization. OR below 1 indicate protective effects. Right: Kaplan–Meier survival curves for patients who received Aripiprazole compared to those who didn’t, controlling for covariates. 7 Vol.:(0123456789) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ In fact, Chlorpromazine protects mice from severe clinical disease and SARS-CoV-236. Clozapine an atypical antipsychotic, has been revealed to be effective in suppressing proinflammatory cytokine expression by limiting NLRP3 inflammasome activation in an invitro model of schizophrenia37. Our group showed that aripiprazole (marked Phenylpiperazine) reverts the changes caused by COVID-19 in gene expression which could validate aripiprazole as a treatment for COVID-1922. Interestingly, research investigating approximately 12,000 drugs in clinical-stage or Food and Drug Administration (FDA)-approved small molecules to identify candidate drugs to treat COVID-19, reported that Elopiprazole (a never marketed phenylpiperazine antipsychotic drug) was listed among the 21 most potent compounds to inhibit SARS-CoV infection38. A possible explanation for the superiority of aripiprazole, in convergence with a recent publication, is that aripiprazole increases the expression of anti-inflammatory markers compared to other antipsychotics. In particular, aripiprazole induced mTORC1 inhibition, which is an important mechanism of action in microglial cells that leads to an anti-inflammatory shift39. Aripiprazole has been included into the called Functional Inhibition of acid sphingomyelinase (FIASMA) medications40. Carpinteiro etal. (2020) suggested that acid sphingomyelinase (ASM)/ceramide system plays an important role in the infection of cells with SARS-CoV-2 since its activation by SARS-CoV-2 facilitates viral entry into cells41. FIASMA medications would inhibit ASM and reduce the formation of ceramide-enriched membrane platforms, decreasing cell infection with SARS-CoV-2 and subsequent inflammation42. Among the antipsychotics included in the present study, aripiprazole was the only considered FIASMA medication. Aripiprazole property to inhibit ASM as well as its anti-inflammatory effects could explain the superiority showed by the molecule against fatal outcome derived from COVID-19. None of the antipsychotics included in our analysis contribute significantly to the increase in mortality related to COVID-19 in the adjusted analyses. As was noted previously, former publications which have reported adverse effects of antipsychotics against COVID-19 have shown significant limitations such as considering antipsychotics as homogeneous group14. In that sense, previous works that have not differentiated between different types of antipsychotics have reported adverse effects on COVID-1943–45. However, those studies that have explored potential adverse effects of specific antipsychotics have not reported a worse prognosis of COVID-1912,46,47. These results underline the need to study the possible effects of antipsychotics on a one-to-one basis, as different antipsychotics may have very different effects on each other. Some limitations should be considered when interpreting the results. Firstly, we have used preprocessed electronic records that could not include sensitive (uncodified) information. Secondly, our treatment information is based on dispensation records, so unless patients are receiving an injectable medication, which is administered at the time of purchase, we cannot be confident that the patient is using the drug. However, we consider that most patients adhere to their prescribed treatment, as the majority present a mean time span between dispensations below 40days. Finally, aripiprazole resulted to be the least prescribed antipsychotic, which limits the generalizability of the results as well as the performance of complementary analyses that could elucidate which dosage of the drug is more likely to play a protective role for the risk of death. Nevertheless, a strength of the study is that, to the best of our knowledge, this is the first study to examine the mortality of COVID-19 linked to specific antipsychotic drugs, employing a sizable study population for that purpose. In conclusion, our results exploring a population-based case–control cohort pose the potential usefulness of aripiprazole, in COVID-19 infected individuals with psychiatric disorders. Aripiprazole could play an important role in minimizing the fatal outcomes related to COVID-19. The anti-inflammatory properties of aripiprazole against cytokine storm as well as its FIASMA properties may explain its genuine effects in reducing the risk of death associated with COVID-19. Data availability Data is available upon formal request to Carlos Loucera-Muñecas. Received: 21 November 2023; Accepted: 21 April 2024 References 1. Clinical, Biological and Molecular Aspects of COVID-19. Vol. 1321 (2021). 2. Dyer, O. Covid-19: Infections climb globally as EG.5 variant gains ground. BMJ 382, 1900 (2023). 3. Weekly Epidemiological Update on COVID-19—17 August 2023. https:// www. who. int/ publi catio ns/m/ item/ weeklyepide miolo gicalupdate- oncovid- 19--- 17- august- 2023 (2023). 4. Weekly Epidemiological Update on COVID-19—10 August 2023. https:// www. who. int/ publi catio ns/m/ item/ weeklyepide miolo gicalupdate- oncovid- 19--- 10- august- 2023 (2023). 5. Weekly Epidemiological Update on COVID-19—3 August 2023. htt ps:// www. who. int/ publi catio ns/m/ i tem/ weeklyepide miolo gicalupdate- oncovid- 19---3- august- 2023 (2023). 6. Weekly Epidemiological Update on COVID-19—27 July 2023. https:// www. who. int/ publi catio n s/m/ item/ weeklyepide miolo gicalupdate- oncovid- 19--- 27- july- 2023 (2023). 7. Canal-Rivero, M. et al. The impact of COVID-19 pandemic on the psychological well-being among health care workers: A 6-month cohort longitudinal survey study. Rev. Psiquiatr. Salud Ment. 16, 25–37 (2023). 8. Jansen van Vuren, E. et al. The neuropsychiatric manifestations of COVID-19: Interactions with psychiatric illness and pharmacological treatment. Biomed. Pharmacother. 135, 33 (2021). 9. Macdonald, O. et al. Impact of the COVID-19 pandemic on antipsychotic prescribing in individuals with autism, dementia, learning disability, serious mental illness or living in a care home: A federated analysis of 59 million patients’ primary care records insitu using OpenSAFELY. BMJ Ment. Health 26, 300775 (2023). 10. Fico, G. et al. Psychotropic drug repurposing for COVID-19: A systematic review and meta-analysis. Eur. Neuropsychopharmacol. 66, 30 (2023). 8 Vol:.(1234567890) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ 11. Vai, B. et al. Mental disorders and risk of COVID-19-related mortality, hospitalisation, and intensive care unit admission: A systematic review and meta-analysis. Lancet Psychiatry 8, 797–812 (2021). 12. Canal-Rivero, M. et al. Lower risk of SARS-CoV2 infection in individuals with severe mental disorders on antipsychotic treatment: A retrospective epidemiological study in a representative Spanish population. Schizophr. Res. 229, 53–54 (2021). 13. Nemani, K. et al. Association between the use of psychotropic medications and the risk of COVID-19 infection among long-term inpatients with serious mental illness in a New York State-wide Psychiatric Hospital System. JAMA Netw. Open 5, 2210743 (2022). 14. Mangalmurti, N. & Hunter, C. A. Cytokine storms: Understanding COVID-19. Immunity 53, 19 (2020). 15. Dinesh, A. A., Islam, J., Khan, J., Turkheimer, F. & Vernon, A. C. Effects of antipsychotic drugs: Cross talk between the nervous and innate immune system. CNS Drugs 34, 1229–1251 (2020). 16. Obuchowicz, E., Bielecka-Wajdman, A. M., Paul-Samojedny, M. & Nowacka, M. Different influence of antipsychotics on the balance between pro- and anti-inflammatory cytokines depends on glia activation: An invitro study. Cytokine 94, 37–44 (2017). 17. Kato, T., Monji, A., Hashioka, S. & Kanba, S. Risperidone significantly inhibits interferon-gamma-induced microglial activation invitro. Schizophr. Res. 92, 108–115 (2007). 18. Juncal-Ruiz, M. et al. The effect of excess weight on circulating inflammatory cytokines in drug-naïve first-episode psychosis individuals. J. Neuroinflamm. 15, 63 (2018). 19. Boland, X. & Dratcu, L. Antipsychotics and COVID-19: The debate goes on. Lancet Psychiatry 8, 1030 (2021). 20. Canal-Rivero, M. et al. Epidemiology of infection, transmission and COVID-19 outcomes among mental health users and workers in a comprehensive network of long-term mental health facilities: Retrospective observational population-base study. Schizophr. Res. 254, 1 (2023). 21. Muñoyerro-Muñiz, D. et al. Health record linkage: Andalusian health population database. Gac Sanit. 34, 105–113 (2020). 22. Crespo-Facorro, B. et al. Aripiprazole as a candidate treatment of COVID-19 identified through genomic analysis. Front. Pharmacol. 12, 346. https:// doi. org/ 10. 3389/ fphar. 2021. 646701 (2021). 23. Canal-Rivero, M. et al. The role of antipsychotics against COVID-19: A topic for debate. Schizophr. Res. 235, 5–6 (2021). 24. Hoertel, N. et al. Association between antidepressant use and reduced risk of intubation or death in hospitalized patients with COVID-19: Results from an observational study. Mol. Psychiatry 26, 5199–5212 (2021). 25. Loucera, C. et al. Real world evidence of calcifediol or vitamin D prescription and mortality rate of COVID-19 in a retrospective cohort of hospitalized Andalusian patients. Sci. Rep. 11, 23380 (2021). 26. Sterne, J. A. C. et al. Association between administration of systemic corticosteroids and mortality among critically ill patients with COVID-19: A meta-analysis. JAMA 324, 1330–1341 (2020). 27. World Medical Association declaration of Helsinki. Ethical principles for medical research involving human subjects. JAMA. https:// doi. org/ 10. 1001/ jama. 2013. 281053 (2013). 28. von Elm, E. et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. J. Clin. Epidemiol. 61, 344 (2008). 29. Zeileis, A. Object-oriented computation of sandwich estimators. J. Stat. Softw. 16, 1–16 (2006). 30. Therneau, T. M. survival: A Package for Survival Analysis in R. R Package Version 2.38 (2021). 31. Greifer, N. Package ‘ cobalt ’. R Package Version (2016). 32. Therneau, T. M. & Grambsch, P. M. Modeling survival data : Extending the Cox model (2000). 33. Drawing Survival Curves Using ‘ggplot2’ [R package survminer version 0.4.9] (2021). 34. Create ‘Table1’ to Describe Baseline Characteristics with or Without Propensity Score Weights [R package tableone version 0.13.2] (2022). 35. Zeileis, A., Köll, S. & Graham, N. Various versatile variances: An object-oriented implementation of clustered covariances in r. J. Stat. Softw. 95, 1 (2020). 36. Weston, S. et al. Broad anti-coronavirus activity of food and drug administration-approved drugs against SARS-CoV-2 invitro and SARS-CoV invivo. J. Virol. 94, 21 (2020). 37. Giridharan, V. V. et al. Clozapine prevents poly (I:C) induced inflammation by modulating NLRP3 pathway in microglial cells. Cells 9, 577 (2020). 38. Riva, G. et al. COVID-19: More than a cytokine storm. Crit. Care 24, 549 (2020). 39. Racki, V., Marcelic, M., Stimac, I., Petric, D. & Kucic, N. Effects of haloperidol, risperidone, and aripiprazole on the immunometabolic properties of BV-2 microglial cells. Int. J. Mol. Sci. 22, 9 (2021). 40. Hoertel, N. et al. Association between FIASMA psychotropic medications and reduced risk of intubation or death in individuals with psychiatric disorders hospitalized for severe COVID-19: An observational multicenter study. Transl. Psychiatry 12, 1 (2022). 41. Carpinteiro, A. et al. Pharmacological inhibition of acid sphingomyelinase prevents uptake of SARS-CoV-2 by epithelial cells. Cell Rep. Med. 1, 100142 (2020). 42. Kornhuber, J., Hoertel, N. & Gulbins, E. The acid sphingomyelinase/ceramide system in COVID-19. Mol. Psychiatry 27, 307–314 (2021). 43. Harrison, S. L., Buckley, B. J. R., Lane, D. A., Underhill, P. & Lip, G. Y. H. Associations between COVID-19 and 30-day thromboembolic events and mortality in people with dementia receiving antipsychotic medications. Pharmacol. Res. 167, 105534 (2021). 44. McKeigue, P. M. et al. Relation of severe COVID-19 to polypharmacy and prescribing of psychotropic drugs: The REACT-SCOT case–control study. BMC Med. 19, 1–11 (2021). 45. Poblador-Plou, B. et al. Baseline chronic comorbidity and mortality in laboratory-confirmed COVID-19 cases: Results from the PRECOVID study in Spain. Int. J. Environ. Res. Public Health 17, 5171 (2020). 46. Hoertel, N. et al. Observational study of haloperidol in hospitalized patients with COVID-19. PLoS One 16, e0247122 (2021). 47. Ohlis, A. et al. Clozapine treatment and risk of severe COVID-19 infection. Acta Psychiatr. Scand. 145, 79–85 (2022). Acknowledgements MCR works as Clinical Psychologist at Virgen del Rocío University Hospital (Seville, Spain) via Consejería de Salud y Familias (Junta de Andalucía) 2020 grant which covers his salary (RH-0081-2020). Author contributions CLM: Analyses. MCR: Conception of the study, study design, drafting and revising the manuscript. MRV: Conception of the study, study design and revising the manuscript. RC: Analyses. GB: Analyses. NGT: Revising manuscript. JDB: Analyses. BCF: Conception of the study, study design and revising the manuscript. All authors contributed to and have approved of the final version of the manuscript. Fundings This work is supported by grants PID2020-117979RB-I00 and TED2021-132346B-I00 from the Spanish Ministry of Science and Innovation, IMPaCT-Data IMP/00019 from the ISCIII, co-funded with European Regional Development Funds (ERDF). 9 Vol.:(0123456789) Scientific Reports | (2024) 14:12362 | https://doi.org/10.1038/s41598-024-60297-y www.nature.com/scientificreports/ Competing interests The authors declare no competing interests. Additional information Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1038/ s41598- 024- 60297-y. Correspondence and requests for materials should be addressed to M.C.-R. Reprints and permissions information is available at www.nature.com/reprints. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. © The Author(s) 2024