GLP-1 receptor agonists have reshaped obesity therapeutics, but their impact on neuropsychiatric outcomes remains poorly characterized. From 29 million patients in a large federated data platform across the USA, including 489,785 semaglutide treated patients, we conducted an observational study integrating longitudinal neuropsychiatric outcomes. From this population, we assembled a cohort of 63,215 patients with baseline neuropsychiatric conditions before treatment initiation and evaluated 24 incident neuropsychiatric outcomes. In propensity-matched comparator analyses, during the 2 year time-period from treatment initiation, semaglutide was associated with broadly lower neuropsychiatric event risk than metformin, SGLT2 inhibitors, and DPP-4 inhibitors. Within the semaglutide-treated cohort, higher attained dose during the first two years after the first prescription ("pre-landmark period") was associated with significantly lower incidence during the following two years ("post-landmark period") of diagnostic codes associated with substance-related disorders (P<0.001), mood disorders (P<0.001), anxiety- and stress-related disorders (P<0.001), CNS atrophies (P<0.001), neuromuscular disorders (P=0.013), eating/sleep/behavioral disorders (P=0.022), and personality/impulse-control disorders (P=0.028). Consistent with previous clinical trials, the post-landmark incidence of dementia or CNS degenerative diseases was similar between the high-dose and low-dose semaglutide cohorts (P=0.15). For most neuropsychiatric diagnoses, post-landmark incidence was strongly associated with the maximum attained semaglutide dose during the pre-landmark period, but incident cognitive symptoms and speech/language symptoms were more closely linked to the pre-landmark weight-loss magnitude (p<0.001 and p<0.003, respectively). Bulk and single-cell transcriptomic analyses demonstrated GLP1R expression in CNS tissues (hypothalamus, caudate, putamen, nucleus accumbens, cerebellum) and peripheral nerves. Age-associated heterogeneity in GLP1R expression was evident in several of these compartments including the caudate nucleus, suggesting dynamic changes in the availability of the neurobiological substrate for semaglutide response. Together, these data support a model in which semaglutide confers a sustained, dose-dependent, weight loss-independent benefit across multiple neuropsychiatric conditions via direct CNS target engagement. This observational study motivates prospective clinical studies and mechanistic analyses to clarify the impact of GLP-1 receptor agonists on human neuropsychiatric pathways and disease processes.
Competing Interest StatementThe authors are employees of nference, inc., which conducts research collaborations with various biopharmaceutical companies whose therapeutic products are included in this study. None of these companies, nor any other nference collaborator, funded, supported, or had any role in the independent study design, data acquisition, analysis, interpretation, manuscript preparation, or the decision to submit this work for publication. All analyses were conducted by the authors using de-identified electronic health record data. The authors declare no additional competing interests.
Funding StatementThis study did not receive any funding.
Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
This study analyzed de-identified EHR data from academic medical centers in the United States via the nference nSights Analytics Platform. Prior to analysis, all data underwent expert determination de-identification satisfying HIPAA Privacy Rule requirements (45 CFR 164.514(b)(1)), employing a multi-layered transformation approach for both structured data (cryptographic hashing of identifiers, date-shifting, geographic truncation) and unstructured clinical text (ensemble deep learning and rule-based methods with >99% recall for personally identifiable information detection). nference established secure data environments within each participating center, housing these de-identified patient data governed by expert determination. These de-identified data environments were specifically designed to enable data access and analysis without requiring Institutional Review Board oversight, approval, or exemption confirmation. Accordingly, informed consent and IRB review were not required for this study. 37. Murugadoss, K. et al. Building a best-in-class automated de-identification tool for electronic health records through ensemble learning. Patterns (N Y) 2, 100255 (2021).
I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.
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Data AvailabilityThis study involves the analysis of de-identified Electronic Health Record (EHR) data via the nference nSights Federated Clinical Analytics Platform (nSights). Data shown and reported in this manuscript were extracted from this environment using an established protocol for data extraction, aimed at preserving patient privacy. The data has been de-identified pursuant to an expert determination in accordance with the HIPAA Privacy Rule. Any data beyond what is reported in the manuscript, including but not limited to the raw EHR data, cannot be shared or released due to the parameters of the expert determination to maintain the data de-identification. The corresponding author should be contacted for additional details regarding nSights.
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