Methods for detecting anesthetic induced neurotoxicity

Abstract

Disclosed are methods, compositions, and kit, systems, and platforms for detecting anesthetic induced neurotoxicity (AIN). The inventors discovered several biomarkers indicative of AIN, e.g., in pediatric subjects. The disclosed methods detect at least one of the disclosed biomarkers including, but not limited to, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1.

Description

Atty. Dkt. No.650053.01228 METHODS FOR DETECTING ANESTHETIC INDUCED NEUROTOXICITY CROSS REFERENCE TO RELATED PATENT APPLICATIONS

[0001] This application claims priority benefit from U.S. Application Ser. No. 63 / 684,113, filed August 16, 2024, the entirety of which is incorporated herein by reference. STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under R35 GM148177, R01 GM112696, and P01 GM066730 awarded by the National Institutes of Health. The government has certain rights in the invention. BACKGROUND

[0003] Existing evidence from animal studies has demonstrated well-known detrimental effects of general anesthesia on the developing brain. These effects include acute neuroapoptosis, long-term memory deficits, learning disabilities, and behavioral issues. Such data have raised significant concerns about the safety of pediatric anesthesia. Consequently, in 2016, the FDA issued a warning regarding the potential impact of general anesthesia on the brain development of children. However, there is a need in the art for technologies to detect anesthetic neurotoxicity. SEQUENCE LISTING

[0004] A Sequence Listing accompanies this application and is submitted as an xml of the sequence listing named “650053_01128.xml” which is 23,736 bytes in size and was created on August 6, 2025. The sequence listing is electronically submitted and is incorporated herein by reference in its entirety. SUMMARY

[0005] In an aspect of the current disclosure, methods are provided. In some embodiments, the methods comprise detecting a level of one or more markers selected from brain-derived neurotrophic factor (BDNF), neuron specific enolase (NSE), S100 Calcium Binding Protein B (S100B), Rho GTPase Activating Protein 8 (ARHGAP8), BCL2-associated athanogene 1 (BAG1), Fucosyltransferase 11 (FUT11), Interleukin 17 Receptor C (IL17RC), Leucine Rich Repeat Containing 36 (LRRC36), Myeloperoxidase (MPO), alpha-actinin-1 (ACTN1), Protein Tyrosine Phosphatase Receptor Type N2 (PTPRN2), Creatine Kinase, Mitochondrial 1B (CKMT1B), Serine Incorporator 1 (SERINC1), BAG family molecular chaperone regulator 3Atty. Dkt. No.650053.01228 (BAG3), Doublecortin Domain Containing 2C (DCDC2C), Family With Sequence Similarity 120 Member A (FAM120A), GTPase Activating Protein And VPS9 Domains 1 (GAPVD1), Histone acetyltransferase KAT2A (KAT2A), Nucleoporin 188 (NUP188), Rhomboid Domain Containing 3 (RHBDD3), telomere elongation helicase 1 (RTEL1), RWD Domain Containing 4 (RWDD4), Sodium Channel Epithelial 1 Subunit Delta (SCNN1D), SHC Adaptor Protein 2 (SHC2), CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1 in a sample from a subject.

[0006] In an aspect of the current disclosure, methods of detecting anesthetic-induced neurotoxicity (AIN) in a subject are provided. In some embodiments, the methods comprise detecting a level of one or more markers selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1 in a sample from a subject.

[0007] In an aspect of the current disclosure, kits, systems, and platforms are provided. In some embodiments, the kits, systems, or platforms comprise reagents for detecting one or more markers selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1. BRIEF DESCRIPTION OF THE FIGURES

[0008] FIGS.1A, 1B, 1C, 1D, 1E, 1F, 1G, and 1I show characterization of cerebral organoids over the 60-day differentiation process from human induced pluripotent stem cells (iPSCs) and analysis of the neurotoxic effect of propofol on day 60 organoids. (a) iPSC characterization. Phase contrast and confocal images of the iPSCs stained with stem cell markers OCT4 (green) and SSEA4 (red) and nuclei stained with Hoechst 33342 (blue). Scale bar = 50 or 10 µm. (b) The scheme for generating cerebral organoids over the 60-day differentiation period (Created with Biorender.com). (c) Images of day 60 single iPSC-derived 3D sphere-like cerebral organoids with scale bar=500 μm or multiple organoids cultured in a petri dish with a ruler asAtty. Dkt. No.650053.01228 calibrator. (d) Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis of the expression of the following genes related to various types of brain cells: paired box 6 (PAX6), nestin, neurofilament heavy chain (NEFH), neurofilament medium chain (NEFM), glial fibrillary acidic protein (GFAP), and galactosylceramidase (GALC) over time during the 60-day differentiation process. n=4 (n=four independently differentiated tissue samples used in each group, with each n sample pooled from 2 organoids). *: p < 0.05. (e) Confocal images of the day 60 organoid tissue sections with Immunofluorescent staining, showing the presence of various types of brain cells within the organoids, using specific markers for neurons, astrocytes, oligodendrocytes, microglia, endothelial cells, smooth muscle cells. Nuclei were stained in blue. Scale bar: 5μm. (f) Caspase 3 activity, an indicator of apoptosis, was analysed in cerebral organoids with multiple single (10 μg ml-1) propofol exposure for 1 to 6 hours, and (g) 5 or 10 μg ml-1) propofol for 1 and 2 hours per day over three consecutive days by an enzyme assay kit. (h) Western blot assay displays the LC3 I / II ratio (16kD to 14kD) in organoids treated with 10 μg ml-1) propofol for 6 hours. Beta-actin (ACTB) served as an internal control. n=4, *: p < 0.05 vs. DMSO control. (i) Electron microscopy images display autophagosome formation following a 6-hour propofol treatment (10 μg ml-1)—scale bar: 500 nm. See Supplementary Materials and Data for more details.

[0009] FIGS. 2A, 2B, 2C, 2D, 2E, and 2F show (a) RNA integrity assessment using agarose gel electrophoresis of RNA extracted from control and propofol-treated organoids. (b) Box and scatter plots show normalised gene expression intensity values distribution for propofol-treated and control organoids. (c) Scatter plot comparing normalised gene expression values between propofol-treated and control organoids. (d) Heatmap representing hierarchical clustering of 553 propofol-dysregulated mRNAs (307 upregulated and 246 downregulated, p < 0.05, fold change > ±1.2) in propofol-treated organoids compared to control. (e) IPA reveals the propofol- dysregulated mRNA-associated canonical pathways with -log(p-value) above 1.30 (p < 0.05) displayed. (f) List of top diseases and functions linked to the dysregulated mRNAs. Note: The dysregulated mRNAs are listed in Table 3.

[0010] FIGS.3A, 3B, 3C, 3D, 3E, 3F, 3G, 3H, 3I, 3J, 3K, 3L, 3M, 3N, and 3O show propofol (10 μg ml-1, 6 hours)-induced dysregulation of synaptic, mitochondrial, and inflammatory genes in human cerebral organoids: integrated bioinformatic, biochemical, and ultrastructural analysis. (a) Bioinformatic analysis using the SynGO database identified 44 propofol-dysregulated synaptic mRNAs compared to other 509 dysregulated genes. (b) Sunburst plots represent the gene counts per term for cell components of synapse-related genes as identified in the SynGOAtty. Dkt. No.650053.01228 database. (c) Sunburst plots represent the gene counts per term for biological processes of synapse-related genes as identified in the SynGO database. (d) IPA analysis predicted top diseases and disorders, and top molecular and cellular functions associated with the dysregulated synaptic mRNAs, highlighting their links to various types of cognition, behaviour, and nervous system development. (e) IPA analysis highlights their links to various types of cognition, behaviour, and nervous system development. (f) Network analysis using IPA predicts the mechanistic regulatory networks of propofol-induced dysregulated synaptic genes. (g) Western blot analysis showed that propofol exposure decreased the protein expression of postsynaptic density protein 95 (PSD95) and cFOS, markers of synaptogenesis / synaptic integrity and neuronal activity, respectively. (h) Bioinformatic analysis using the mitoXplorer database identified 39 propofol-dysregulated mitochondrial genes. (i) These genes are involved in 20 mitochondrial pathways, as calculated using the mitoXplorer database. (j) IPA analysis predicted the top diseases and disorders related to the dysregulated mitochondrial genes. (k–m) Propofol impairs mitochondrial ultrastructure and function in human cerebral organoids. (k) Transmission electron microscopy images show representative mitochondrial morphology in control and propofol-treated organoids. In controls, mitochondria exhibit intact double membranes and densely packed cristae (black arrows), indicating preserved structure. In contrast, mitochondria in propofol-treated organoids display marked swelling, cristae disruption, and matrix rarefaction (orange arrows), consistent with mitochondrial degeneration. Scale bar: 100 nm. (l) Propofol exposure significantly reduced ATP levels in organoids. (m) Western blot analysis revealed decreased protein expression of creatine kinase, mitochondrial 1B (CKMT1B) in propofol-treated organoids. Consistently, CKMT1B mRNA levels were also reduced, as shown in Table S6. n = 3–4 per group. p < 0.05 (*), p < 0.01 (**), vs. DMSO control. (n) Bioinformatics analysis using NCBI identified 23 propofol-dysregulated inflammatory mRNAs among the total dysregulated genes. (o) IPA analysis predicted top diseases, disorders, and functions related to the dysregulated inflammatory mRNAs. Note: The dysregulated synaptic, mitochondrial, and inflammatory genes are included in Tables 5-7. See Supplementary Materials and Data for more details.

[0011] FIGS. 4A, 4B, 4C, 4D, and 4E show propofol (10 μg ml-1, 6 hours) exposure dysregulated expression profile of lncRNAs in day 60 organoids, coexpression with dysregulated synaptic, mitochondrial, and inflammatory mRNAs in multiple pathways. (a) Heatmap representing the differential expression (fold change > 1.2 and p < 0.05) of propofol- dysregulated lncRNAs in organoids. (b) Correlation coefficient heatmap between propofol-Atty. Dkt. No.650053.01228 dysregulated lncRNAs and synaptic mRNAs in organoids. The coexpression network and related pathways of dysregulated lncRNA with their co-expressing mRNA transcripts were analysed using the Cytoscape 3.10.2 platform. (c) The network demonstrates the coexpression relationships between propofol-dysregulated lncRNAs and synaptic mRNAs in organoids, with a cutoff of coexpression efficiency > 0.9 and p < 0.05 from Fig.4b. Metascape platform-based Enriched Ontology Clusters of the propofol-dysregulated synaptic mRNAs that were co- expressed with dysregulated lncRNAs are shown alongside the coexpression network. (d and e) Coexpression network between the propofol-deregulated lncRNAs and inflammation mrNAs or mitochondrial mRNA.

[0012] FIGS. 5A, 5B, 5C, 5D, 5E, and 5F show general anaesthesia / surgery (>3 hours) in paediatric patients (< 4 years) resulted in abnormal levels of serum brain injury markers and dysregulated profiles of mRNAs and lncRNAs. (a) Schematic depicting the experimental design for clinical studies, including patient information on anaesthesia / surgery duration (< 1 hour or > 3 hours), anaesthetics used, age, and blood sample collection time points (pre- and post- surgery). (b) ELISA quantified protein levels of brain injury biomarkers in serum collected from paediatric patients undergoing non-cardiac and neuronal surgeries before (pre-surgery) and after (post-surgery) with anaesthesia / surgery < 1 hour or > 3 hours: brain-derived neurotrophic factor (BDNF), neuron serum enolase (NSE), and S100 calcium-binding protein B (S100B). n=3, with each n representing serum samples from 3 to 4 patient-derived pooled samples, totaling 10 patients. *: p < 0.05. (c) Volcano plot showing dysregulated mRNA and lncRNA profiles in serum from paediatric patients with anaesthesia / surgery duration longer than 3 hours compared with pre-surgery control samples. Green and red dots represent downregulated and upregulated mRNAs and lncRNAs (above 1.2-fold change and p < 0.05). (d) Pie chart displaying dysregulated synaptic, mitochondrial, and inflammatory mRNAs in patients’ serum (> 3-hour anaesthesia). (e) Pie chart displaying the sorted 116 brain cell type-specific anaesthesia / surgery (> 3 hours)-dysregulated mRNA counts from the total dysregulated 1492 mRNAs in patients’ serum based on Zhang’s data set (f) IPA analysis of neuron- and oligodendrocyte-associated anaesthesia / surgery- dysregulated genes.29, 30

[0013] FIGS. 6A, 6B, 6C, 6D, 6E, 6F, 6G, 6H, 6I, 6J, and 6K show the shared dysregulated mRNAs and lncRNAs identified in paediatric patient serum following general anaesthesia (>3 hours) and in day-60 cerebral organoids treated with propofol (10 µg ml-1for 6 hours), along with the associated signalling pathways. (a) Venn plot displaying the 21 differentially modulated mRNAs overlapping in both cerebral organoids and paediatric serum samples afterAtty. Dkt. No.650053.01228 anaesthetic exposure. (b) List of the 21 overlapping mRNAs, including their gene symbols and the direction of regulation (up or down) in both organoids and serum. (c) Pie chart illustrating the 21 overlapping mRNAs, highlighting 2 synaptic genes (ACTN1 and PTPRN2) and 1 mitochondrial gene (CKMT1B) among the overlapping transcripts. (d) Venn plot shows 12 differentially modulated lncRNAs overlap between cerebral organoids and paediatric serum samples after anaesthetic exposure. (e) Top canonical pathways and enriched biological processes (p < 0.05) associated with the 21 overlapping mRNAs identified via IPA-based pathway analysis. (f) Top canonical pathways and enriched biological processes (p<0.05) associated with the 21overlapping mRNAs identified via IPA-based pathway analysis. (g) Metascape enrichment analysis of 21 overlapping mRNAs in various other pathways, including regulating cell activities such as cell division, organelle fusion and organization, and vesicle- mediated transport. (h) List of the 12 overlapping lncRNAs, including their gene symbols and the direction of regulation (up or down) in both organoids and serum. (i) Coexpression analysis between the overlapping anaesthesia-dysregulated lncRNAs and mRNAs in serum and organoids using Cytoscape 3.10.2 platform identified 7 lncRNAs and 11 mRNAs coexpressed, forming a regulative network. A cutoff of coexpression efficiency > 0.9 and p < 0.05 was used. (j) IPA predicted the top network of mRNAs listed in Fig. 6h, suggesting the involvement of the lncRNAs in these pathways through regulation of the mRNAs in the coexpression network. (k) Table summarizing the top disease pathways and functions associated with the mRNAs included in Fig.6h, i.

[0014] FIGs. 7A, 7B, 7C, and 7D show microarray and Bioinformatic analysis of serum mRNA and lncRNAs. Box and scatter plots for mRNA (A&B); and lncRNAs (C&D); showing the distribution of normalized gene expression intensity values for mRNA in serum of paediatric patients undergoing general anaesthesia (> 3 hours; n=3 from 10 pooled patient serum samples).

[0015] FIG. 8 shows RT-qPCR validation of microarray data of mRNAs from the serum of pediatric patients (> 3-hour anesthesia / surgery). qRT-PCR validation of four mRNAs (upregulated: NDUFA11; PGAM5; and downregulated: DRD1; and APC2) from array data from serum of pediatric patients (n=3 from 10 pooled patient serum samples; *P < 0.05).

[0016] FIG. 9 shows RT-qPCR validation of microarray data of lncRNAs from the serum of pediatric patients (> 3-hour anesthesia / surgery). RT-qPCR validation of two anesthesia / surgery-altered lncRNAs (upregulated: SMCR5; downregulated: DUBR) from array data in pediatric patients (n=3 from 10 pooled patient serum samples; *P < 0.05).Atty. Dkt. No.650053.01228

[0017] FIGS. 10A and 10B show coexpression relationships between propofol-dysregulated lncRNAs and inflammatory mRNAs in organoids, with a cutoff of coexpression efficiency > 0.9 and p < 0.05. (b) Metascape platform-based Enriched Ontology Clusters of the propofol- dysregulated inflammatory mRNAs that were co-expressed with dysregulated lncRNAs.

[0018] FIG. 11 shows Table 1 which describes the characteristics of patients in the clinical study in Example 1.

[0019] FIG.12 shows a flowchart of design of the human study in Example 1. This flowchart outlines the recruitment, screening, and enrollment process for the paediatric clinical study. Patients scheduled for surgery with general anaesthesia were screened based on inclusion and exclusion criteria. Eligible participants (n = 10 per group) were enrolled with informed consent. Peripheral blood samples were collected before and after anaesthesia / surgery, and brain injury marker and transcriptomic analysis was subsequently performed on serum samples. DETAILED DESCRIPTION

[0020] Provided herein are methods of detecting markers of anesthetic-induced neurotoxicity (AIN) and kits for performing the disclosed methods. Methods

[0021] The inventors discovered that several biomarkers are altered in subjects and cells that have been exposed to anesthesia. Further, the inventors used a dual-model strategy combining advanced human organoid systems with serum samples from pediatric patients exposed to anesthesia to discover novel biomarkers of AIN.

[0022] Accordingly, in an aspect of this disclosure, methods are provided. In some embodiments, the methods comprise detecting a level of one or more markers selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1 in a sample from a subject. The one or more marker may be selected from those in Table 8.

[0023] As used herein, “marker” refers to a protein marker, including a peptide fragment of a protein, an RNA marker, or a DNA marker. A “level” of a marker, as used herein, may refer to a protein level, e.g., concentration, an RNA level, e.g., copies, relative expression, FPKM, etc. or a DNA level, e.g., copies, relative concentration.Atty. Dkt. No.650053.01228

[0024] Detecting may comprise using any known method, e.g., detecting polynucleotides may be accomplished using sequencing, e.g., Sanger or next-generation sequencing, or quantitative PCR (qPCR) and detecting protein or peptide biomarkers may be accomplished by, e.g., enzyme-linked immunosorbent assay (ELISA), ELISPOT, or lateral flow immunoassay, chemiluminescent immunoassay (CLIA).

[0025] The disclosed biomarkers may be detected by detecting RNA, or protein level of the biomarker. In the case of non-coding RNAs, the RNAs themselves are typically directly detected.

[0026] A “subject,” as used herein, may refer to a mammal, e.g., a human, e.g., a pediatric human subject. The subject may have been exposed to a particular stimulus or event, e.g., exposed to general anesthesia for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more. A pediatric subject may be a subject less than about 18 years old, less than about 17 years old, less than about 16 years old, less than about 15 years old, less than about 14 years old, less than about 13 years old, less than about 12 years old, less than about 11 years old, less than about 10 years old, less than about 9 years old, less than about 8 years old, less than about 7 years old, less than about 6 years old, less than about 5 years old, less than about 4 years old, less than about 3 years old, less than about 2 years old, less than about 1 year old, and / or between 0 days old (newborn infant) and about 18 years old, and any subrange or value therein.

[0027] A “reference sample” may refer to a sample from a subject that has not experienced a particular stimulus or event, e.g., a reference sample may be from a subject that has not been exposed to general anesthesia for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more.

[0028] The methods may further comprise treating the subject for anesthetic-induced neurotoxicity (AIN). In some embodiments, the treatment comprises administering at least one therapeutic agent selected from:

[0029] (i) anti-inflammatory agents including, but not limited to, inhibitors of IL-1β, TNF-α, IL-6, NF-κB pathway inhibitors, and microglia activation inhibitors (e.g., minocycline, ibudilast);Atty. Dkt. No.650053.01228

[0030] (ii) neuroprotective agents including, but not limited to, synaptic stabilizers (e.g., PSD- 95 inhibitors, AMPA / NMDA receptor modulators), neurotrophic factors or their mimetics (e.g., BDNF, GDNF, NGF analogs), and agents promoting synaptic plasticity;

[0031] (iii) mitochondrial protectants including, but not limited to, antioxidants (e.g., N- acetylcysteine, edaravone, vitamin E), mitochondrial-targeted peptides (e.g., SS-31), coenzyme Q10, L-carnitine, reactive oxygen species scavengers, and mitophagy modulators (e.g., urolithin A); or

[0032] (iv) cell type-specific therapies including, but not limited to, those targeted to neurons, astrocytes, oligodendrocytes, or microglia, which may be delivered via nanoparticles, viral vectors, antibody-drug conjugates, or other targeted delivery systems.

[0033] In certain embodiments, the treatment is administered pre-operatively, peri-operatively, or post-operatively, and via a route selected from intravenous, oral, intranasal, intrathecal, or combinations thereof. In some embodiments, the treatment is initiated within a defined therapeutic window, such as within 6, 12, or 24 hours following anesthetic exposure.

[0034] In further embodiments, if the subject is identified as having AIN, the method may comprise modifying the anesthetic regimen to reduce further neurotoxic exposure, including reducing the duration of anesthesia, avoiding or minimizing use of agents with high neurotoxic potential, employing regional or local anesthesia where feasible, and implementing perioperative neuroprotective measures such as hemodynamic, oxygenation, and glycemic optimization. If the subject is not found to have AIN, anesthesia may proceed according to standard clinical practice while minimizing unnecessary anesthetic exposure.

[0035] Administration, as used herein, may refer to administering a compound or other therapy by any appropriate route, as determined by a physician. Illustrative, but not limiting, routes of administration comprise oral, intravenous, intramuscular, subcutaneous, intrathecal, sublingual, buccal, nasal, inhalation, ocular, otic, nebulization, cutaneous, or transdermal routes. Kits, systems, and platforms

[0036] Also disclosed herein are kits, systems, and platforms for detecting the disclosed biomarkers. The disclosed kits, systems, or platforms may comprise reagents for detecting one or more markers selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1,Atty. Dkt. No.650053.01228 LINC00685, and LIPE-AS1. The kits may comprise reagents for detecting 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, or more of the disclosed biomarkers in any combination.

[0037] The reagents may comprise a suitable detection reagent, e.g., a biomarker-specific antibody or cocktail of antibodies, probes for detecting expression of the disclosed biomarkers.

[0038] Exemplary probe sets for detecting a selection of the disclosed biomarkers are provided as SEQ ID NOs: 1-26. However, design and use of additional or alternative probes for detecting the disclosed biomarkers is within the skill of the ordinary artisan.

[0039] The reagents may further be linked to a detectable marker. As used herein “detectable marker” refers to a compound that is detectable by one or more physical properties of the compound. Exemplary detectable markers include, but are not limited to, fluorescent molecules, e.g., fluorescent proteins, e.g., green fluorescent protein (GFP), red fluorescent protein (RFP), and variants thereof, luminescent tags, e.g., luciferase, epitope tags, e.g., histidine tag, FLAG tag, HA tag, etc., haptens, and radioactive moieties. The detectable marker may be linked to, e.g., a primary antibody specific for one of the disclosed biomarkers, or a secondary antibody that binds to a primary antibody. The detectable marker may be linked to a probe, e.g., DNA probe, RNA probe, hybrid DNA / RNA probe, peptide nucleic acid (PNA), for detecting one of the disclosed biomarkers.

[0040] Background: The adverse effects of pediatric general anesthetics (GA) on brains have been controversial due to inconsistent epidemiological findings and the lack of direct pathological evidence. Using 3D human cerebral organoids derived from induced pluripotent stem cells (iPSCs) offers a novel model for studying anesthetic-induced developmental neurotoxicity (AIN). The inventors utilized iPSC-derived organoids to analyze phenotypic and gene profile changes, focusing on mRNAs and lncRNAs. Findings were validated with clinical serum samples from pediatric patients who received GA during surgery.

[0041] Methods: Organoids were generated from iPSCs and exposed to the anesthetic propofol at various doses for 1 to 6 hours, with single or repeated exposures. Pathological changes were assessed using chemical assays, electron microscopy, and Western blot analysis. Blood samples were collected from pediatric patients (<4 years) before and after surgery. Neurotoxicity was measured by protein expression of brain injury markers in the serum using ELISA. Microarray assays analyzed genome-wide expression profiles of 18,855 mRNAs and 27,427 lncRNAs in organoids and serum, followed by bioinformatics analyses.

[0042] Findings: Higher anesthetic doses, longer exposure, and repeated exposures caused more apoptosis in cerebral organoids. Six-hour exposure to propofol promoted autophagy, withAtty. Dkt. No.650053.01228 553 mRNAs and 792 lncRNAs abnormally expressed. Pediatric serum revealed overlapping abnormal organoid brain cell injury phenotypes and transcriptomic profiles, as well as brain cell type-specific gene profiles. Bioinformatics showed dysregulated mRNAs, correlated with dysregulated lncRNAs, involved in neurodegeneration via mitochondrial, synaptic, inflammatory, and neuronal pathways.

[0043] Interpretation: This study provides the first direct pathological evidence of AIDN in a dose- and exposure-dependent manner in iPSC-derived brain tissue. Over 48% of 58,648 lncRNAs are brain specific. The dysregulated lncRNA genes and co-expressed mRNAs suggest complex mechanisms for AIDN. Overlapping gene expressions in organoids and patient serum highlight iPSC-derived organoids and patient serum as complementary platforms for identifying neurotoxic effects and underlying mechanisms, and serum biomarker for neurotoxicity. This approach may lead to novel therapeutic and prognostic targets for AIDN.

[0044] The inventors envision that the disclosed methods may be used in the following technologies.

[0045] Diagnostic Kits: Development of blood tests, or tests using other tissues as samples, that detect specific serum biomarkers (e.g., BDNF, NSE, S100B, specific mRNAs, and lncRNAs) associated with anesthesia neurotoxicity. These kits could be used in hospitals and clinics to identify patients at risk of neurotoxicity from prolonged anesthesia, enabling earlier intervention and personalized treatment plans.

[0046] Therapeutic Products: 1) Drugs targeting the dysregulated pathways identified in the study, such as those involved in various brain functions such as cell injury, synapse function, mitochondrial health, and inflammation. For instance, medications could be designed to protect synaptic structure, support mitochondrial function, or reduce inflammation. These could serve as neuroprotective and treatment strategies for patients exposed to anesthesia, potentially mitigating adverse effects. 2) Gene therapy approaches, possibly delivered via viral vectors, that modulate the expression of the identified dysregulated mRNAs and lncRNAs, offering a personalized medicine approach to mitigate neurotoxic effects.

[0047] The present invention is described herein using several definitions, as set forth below and throughout the application.

[0048] Definitions

[0049] The disclosed subject matter may be further described using definitions and terminology as follows. The definitions and terminology used herein are for the purpose of describing particular embodiments only and are not intended to be limiting.Atty. Dkt. No.650053.01228

[0050] As used in this specification and the claims, the singular forms “a,” “an,” and “the” include plural forms unless the context clearly dictates otherwise. For example, the term “a substituent” should be interpreted to mean “one or more substituents,” unless the context clearly dictates otherwise.

[0051] As used herein, “about”, “approximately,” “substantially,” and “significantly” will be understood by persons of ordinary skill in the art and will vary to some extent on the context in which they are used. If there are uses of the term which are not clear to persons of ordinary skill in the art given the context in which it is used, “about” and “approximately” will mean up to plus or minus 10% of the particular term and “substantially” and “significantly” will mean more than plus or minus 10% of the particular term.

[0052] As used herein, the terms “include” and “including” have the same meaning as the terms “comprise” and “comprising.” The terms “comprise” and “comprising” should be interpreted as being “open” transitional terms that permit the inclusion of additional components further to those components recited in the claims. The terms “consist” and “consisting of” should be interpreted as being “closed” transitional terms that do not permit the inclusion of additional components other than the components recited in the claims. The term “consisting essentially of” should be interpreted to be partially closed and allowing the inclusion only of additional components that do not fundamentally alter the nature of the claimed subject matter.

[0053] The phrase “such as” should be interpreted as “for example, including.” Moreover, the use of any and all exemplary language, including but not limited to “such as”, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed.

[0054] Furthermore, in those instances where a convention analogous to “at least one of A, B and C, etc.” is used, in general such a construction is intended in the sense of one having ordinary skill in the art would understand the convention (e.g., “a system having at least one of A, B and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together.). It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description or figures, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or ‘B or “A and B.”Atty. Dkt. No.650053.01228

[0055] All language such as “up to,” “at least,” “greater than,” “less than,” and the like, include the number recited and refer to ranges which can subsequently be broken down into ranges and subranges. A range includes each individual member. Thus, for example, a group having 1-3 members refers to groups having 1, 2, or 3 members. Similarly, a group having 6 members refers to groups having 1, 2, 3, 4, or 6 members, and so forth.

[0056] The modal verb “may” refers to the preferred use or selection of one or more options or choices among the several described embodiments or features contained within the same. Where no options or choices are disclosed regarding a particular embodiment or feature contained in the same, the modal verb “may” refers to an affirmative act regarding how to make or use and aspect of a described embodiment or feature contained in the same, or a definitive decision to use a specific skill regarding a described embodiment or feature contained in the same. In this latter context, the modal verb “may” has the same meaning and connotation as the auxiliary verb “can.” Illustrative Embodiments 1. A method comprising detecting a level of one or more markers selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1 in a sample from a subject. 2. A method of detecting anesthetic-induced neurotoxicity (AIN) in a subject, the method comprising detecting a level of one or more markers selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1 in a sample from a subject. 3. A method of detecting anesthetic-induced neurotoxicity (AIN) in a subject, the method comprising detecting a level of one or more markers selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394,Atty. Dkt. No.650053.01228 LACTB2-AS1, LINC00685, and LIPE-AS1 in a sample from a subject; wherein the level of the one or more markers are altered as compared to a level of the one or more markers in a reference sample, thereby detecting AIN. 4. The method of embodiment 3, wherein the one or more markers are selected from BDNF, NSE, and S100B and the level of the one or more markers are increased as compared to a reference sample. 5. The method of any one of embodiments 1-4, wherein detecting a level comprises detecting a level of BDNF, NSE, or S100B protein in a sample from the subject, optionally, by ELISA. 6. The method of any one of embodiments 1-3, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1. 7. The method of any one of embodiments 1-3, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, and SHC2. 8. The method of any one of embodiments 1-3, wherein the one or more markers are selected from CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1. 9. The method of embodiment 3, wherein the markers are selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, PTPRN2, CKMT1B, SERINC1, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, and XLOC_004632 and the level of the one or more markers are reduced as compared to the level of the one or more markers in the reference sample. 10. The method of embodiment 3, wherein the markers are selected from ACTN1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1 and the level of the one or more markers are increased as compared to the level of the one or more markers in the reference sample.Atty. Dkt. No.650053.01228 11. The method of any one of embodiments 6-10, wherein the level of the one or more markers is detected by microarray, quantitative reverse transcription PCR (qRT-PCR), next generation sequencing, or northern blot. 12. The method of any one of embodiments 2-11, wherein the subject has been exposed to general anesthetic for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more. 13. A method of detecting anesthetic-induced neurotoxicity (AIN) in a subject, the method comprising detecting a level of one or more markers selected from the markers disclosed herein in a sample from a subject; wherein the level of the one or more markers are altered as compared to a level of the one or more markers in a reference sample, thereby detecting AIN. 14. The method of any one of embodiments 3-13, wherein the subject is a pediatric subject, optionally, wherein the subject is less than 4, less than 3, less than 2, or less than 1 year of age. 15. A kit, system, or platform comprising reagents for detecting one or more markers disclosed herein. 16. The kit, system, or platform of embodiment 15, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1. 17. The kit, system, or platform of embodiment 15 or 16, wherein the reagents comprise nucleotide probes for detecting the presence of the one or more markers in a sample from a subject. 18. The kit, system, or platform of embodiment 17, wherein the sample is a sample of serum, blood, or other tissue. 19. The kit, system, or platform of embodiment 17 or 18, wherein the subject is suffering from AIDN or is suspected of suffering from AIDN or wherein the subject has been exposed to an anesthetic for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8Atty. Dkt. No.650053.01228 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more. EXAMPLES

[0057] The following Examples are illustrative and should not be interpreted to limit the scope of the claimed subject matter. Example 1: Bridging Stem Cell Models and Medicine: Integrated 3D Human Cerebral Organoids and Pediatric Serum Reveal Mechanisms and Biomarkers of Anesthetic- Induced Neurotoxicity

[0058] Background: General anaesthetics are essential for paediatric surgery but have been associated with neuronal injury and long-term cognitive deficits, raising concerns over neurodevelopmental safety. However, the molecular mechanisms underlying anaesthetic- induced developmental neurotoxicity (AIDN) remain poorly understood.

[0059] Methods: Human cerebral organoids derived from induced pluripotent stem cells were exposed to propofol (1–6 hours; single or repeated exposures). In parallel, serum samples were collected from paediatric patients (<4 years old; n = 10 per group) undergoing short (<1 hour) or prolonged (>3 hours) anaesthesia. Organoid pathology and mitochondrial function were assessed using chemical assays, electron microscopy, and western blotting. Genome-wide profiling of 18,855 mRNAs and 27,427 lncRNAs was performed via microarray analysis.

[0060] Results: Propofol exposure increased apoptosis (1.93 ± 0.28 vs. 1 ± 0.07; P = 0.173) and autophagy (0.779 ± 0.125 vs.0.448 ± 0.086; P = 0.028) in organoids and dysregulated 553 mRNAs and 792 lncRNAs linked to synaptic function, mitochondrial activity, and inflammation. ATP production (P = 0.045), CKMT1B expression (P = 0.002), and synaptic markers PSD95 and c-Fos were reduced. Serum from children exposed to prolonged anaesthesia showed elevated neuronal injury markers (e.g., NSE) and 33 overlapping dysregulated RNAs (21 mRNAs, 12 lncRNAs), including CKMT1B. Bioinformatics revealed enrichment of these dysregulated lncRNA-mRNA networks in pathways related to cell injury, neurodevelopment, and cognition.

[0061] Conclusions: This study establishes a human-relevant model of AIDN by integrating human organoids with clinical serum profiling. Propofol exposure led to mitochondrial dysfunction and disruption of coding RNA and lncRNA networks involved in neuronal development and injury. Concordant gene signatures (e.g., CKMT1B) across models highlight their potential as translational biomarkers and therapeutic targets.Atty. Dkt. No.650053.01228

[0062] Keywords: paediatric anaesthesia, developmental neurotoxicity, cerebral organoids, stem cells, mitochondria, lncRNAs, biomarkers

[0063] Background

[0064] Each year in the USA, approximately 6 million children—including 1.5 million infants undergo surgery requiring exposure to general anaesthesia.1While necessary for surgical procedures, compelling evidence from animal studies, including those on neonatal rodents and non-human primates, indicates that prolonged (e.g., >3 hours) or repeated anaesthetic exposures during brain development can induce acute molecular and cellular pathologies, followed by long-term cognitive deficits and behavioural problems.2-4These include neuroapoptosis, inhibition of neurogenesis, inflammation, and dysregulated intracellular calcium homeostasis.5-7Several retrospective and prospective clinical studies have examined to explore the potential adverse effects of general anesthetics on the developing human brains. Notably, the General Anesthesia vs. Spinal Anesthesia (GAS) study, the Pediatric Anesthesia and Neurodevelopment Assessment (PANDA) study, and the Mayo Anesthesia Safety in Kids (MASK) study concluded that a single, short anaesthetic exposure (45–84 minutes) in children under 3 years does not result in measurable neurocognitive or behavioural deficits at follow-up between 5 and 15 years of age.8-10However, the MASK study reported that children with multiple exposures performed significantly worse in processing speed and motor ability tests9. Additionally, parents in all three studies noted worse behavioural, socio-affective, and executive functions outcomes in anaesthesia-exposed children.9

[0065] Despite these compelling epidemiological findings, direct investigation of anaesthetic- induced neuropathology in the human brain remains unfeasible due to ethical and logistical constraints. This challenge highlights the need alternative human-relevant models, such as human induced pluripotent stem cell (iPSC)-derived cerebral organoids, which recapitulate key features of early human brain development and cellular responses to anaesthetic exposure.11-14

[0066] Although extensive preclinical studies have demonstrated anaesthetic-induced neurotoxicity in developing animal brains, translation to human context remains inconsistent. Additionally, ethical and practical barriers preclude direct assessment of anesthetic-induced developmental brain injury in human brains. The emergence of iPSC technology, particularly the development of three-dimensional (3D) human cerebral organoids has transformed neurodevelopmental research. We and others have demonstrated that these organoids faithfully mimic several aspects of early human brain development, including cellular composition, tissue architecture, neurogenesis, neuronal migration, and functional responses to neurotransmitters,Atty. Dkt. No.650053.01228 alcohol, and intravenous anesthetic propofol. Recent studies further support their utility in modeling various developmental neurological disorders, including autism spectrum disorders, offering valuable insights into disease mechanisms, and potential therapeutic strategies.15, 16Given these advantages, iPSC-derived cerebral organoids represent a powerful, physiologically relevant model for investigating anesthetic-induced developmental neurotoxicity (AIDN).

[0067] Building on prior findings and our own research, we hypothesized that anaesthetic exposure during neurodevelopment disrupts coding and non-coding RNA signalling pathways, leading to pathological changes that contribute to developmental neurotoxicity in the paediatric brain. Shared molecular signatures, detectable in both human cerebral organoids and serum from paediatric patients exposed to anaesthesia, may serve as translational biomarkers and therapeutic targets for AIDN. We examined anesthetic-induced pathological and molecular changes in 2-month-old human iPSC-derived cerebral organoids and the matched clinical serum samples from paediatric patients. By integrating high-throughput RNA profiling with bioinformatics, we investigated the roles of coding RNAs (mRNAs) and long non-coding RNAs (lncRNAs) in mediating anaesthesia-related neurotoxicity. LncRNA research is rapidly evolving, with over 100,000 human lncRNA transcripts identified, approximately 40% of which are brain-specific and exhibit distinct spatiotemporal expression patterns.17, 18These molecules are known to regulate key neurodevelopment processes, including synaptic plasticity, and mitochondrial function. Given their roles in maintaining brain homeostasis, dysregulation of lncRNA may contribute to AIDN pathogenesis.

[0068] To enhance our translational relevance, we employed a dual-model strategy that integrates human organoid systems with serum samples from paediatric patients. By linking anaesthesia-induced pathological changes to dysregulated lncRNA and mRNA networks, we aim to provide novel insights into the molecular mechanisms underlying AIDN. The findings may facilitate the discovery of serum biomarkers and neuroprotective targets, ultimately contributing to safer anesthetic practices in children.

[0069] Methods

[0070] Human iPSCs derived cerebral organoid and characterization

[0071] All the experiments in the present study utilized a healthy donor-derived iPSC line (101311, 19) and were approved by the Medical College of Wisconsin Institutional Review Board (Protocol number PRO00027064). The 3D cerebral organoids were generated from iPSCs and further characterized as depicted in (Fig. 1a-e) following the previously established protocols from our laboratory.11, 14, 19Detailed methods are provided below.Atty. Dkt. No.650053.01228

[0072] Anaesthetic exposure of 3D cerebral organoids

[0073] Intravenous anaesthetic propofol (2,6-diisopropylphenol; Sigma Aldrich) is commonly used in paediatric anaesthesia. In children, blood concentrations of propofol vary substantially, typically ranging from approximately 1 to 10 μg ml⁻¹. Due to its high lipophilicity, propofol preferentially accumulates in lipid-rich tissues such as the brain, where estimated concentrations range from 4 to 20 μg ml⁻¹.20-22In this study, day 60 human cerebral organoids were exposed to propofol under varying conditions to simulate clinical anaesthetic exposure scenarios. Organoids were treated with either: 1) a single exposure to 10 μg ml⁻¹ propofol for 1, 2, 3, or 6 hours, to model short or prolonged anaesthesia during lengthy paediatric surgeries; 2) or repeated exposures to 5 or 10 μg ml⁻¹ propofol for 1 or 2 hours per day over three consecutive days, mimicking repeated short-duration anaesthetic exposure in children undergoing multiple procedures within a short timeframe. Dimethyl sulfoxide (DMSO; Sigma Aldrich, 0.1%) served as the vehicle control, as it is the solvent for propofol. To evaluate the effects of propofol concentration, exposure duration, and frequency, apoptosis assays were first conducted. Additional analyses—including transcriptomic profiling, protein expression, mitochondrial ultrastructure, and intracellular ATP measurements—were performed under the single 10 μg ml⁻¹, 6-hour exposure condition.

[0074] Assessment of anaesthetic-induced pathologies and mitochondrial function

[0075] Anaesthetic-induced changes, including apoptosis, ultrastructural alterations, ATP depletion, and protein expression of mitochondrial and synaptic markers, were assessed according to our previously established protocols.11, 19, 23, 24Anaesthetic-induced changes, including apoptosis, ultrastructural alterations, ATP depletion, and protein expression of mitochondrial and synaptic markers, were assessed according to our previously established protocols.11, 19, 23, 24Detailed experimental procedures are provided in the Supplementary file- Materials and Data.

[0076] Patient characteristics and demographics

[0077] The study was approved by the Institutional Review Board of the Medical College of Wisconsin (Protocol Number: 1077311). The study included blood samples obtained from paediatric patients under 4 years of age, regardless of sex. The flowchart of human clinical study (Figure S4) and detailed patient profiles, along witFh the inclusion and exclusion criteria are provided in the Materials and Data below and Fig.11 (Table 1).

[0078] Clinical study design and analysis of neurotoxicity in paediatric patientsAtty. Dkt. No.650053.01228

[0079] Whole blood samples were collected from each patient at two time points (1 mL per time point per patient): 1) Prior to administration of intravenous (IV) fluids pre-surgery.2) Post- surgery, immediately before the patient awoke, and the IV was removed. Collected blood was immediately placed on ice and allowed to clot undisturbed for 20-30 minutes; then centrifuged at 4°C at 300g for 15-20 minutes. The resulting serum was aliquoted into 100 µL potions in plastic cap screw vials and immediately stored at -80°C. All patient serum samples were thawed on the same day to minimize batch effects. Ten serum samples from patients receiving either less than one hour or more than 3 hours of anaesthesia were divided into three replicate pools (3+3+4 samples) for protein analysis. Levels of brain-derived neurotrophic factor (BDNF), neuron-specific enolase (NSE), and S100 calcium-binding protein B (S100B), established serum markers of brain cell injury or stress25, were quantified using enzyme-linked immunosorbent assay (ELISA) kits: BDNF (DBNT00, R&D Systems, US), NSE (DENL20, R&D Systems, US), and S100B (DY1820-05, R&D Systems, US), following the manufacturer's instructions.

[0080] Transcriptional and bioinformatic analysis of dysregulated lncRNA and mRNA

[0081] The microarray and bioinformatics analyses for the anaesthetic-dysregulated lncRNA and mRNA transcripts in cerebral organoids and serum were performed as described in detail in the Supplementary Materials and Data and in our previous publications.14, 26-28To further identify the brain cellular origins of the anaesthesia / surgery-dysregulated mRNAs, we utilized the dataset of Zhang et al.29, 30to map dysregulated mRNAs in patient serum to specific brain cell types, including (neuron, astrocyte, microglial, oligodendrocyte, and endothelial cell).

[0082] Reverse transcription-quantitative PCR (RT-qPCR)

[0083] The RT-qPCR was performed to evaluate the expression of neuronal markers and validate microarray results. The primer sequences are listed in the Table S2. Additional details regarding the RT-qPCR assay are provided in the Supplementary Materials and Data.

[0084] Statistical analysis

[0085] All the statistical analyses were performed using GraphPad Prism 8 (GraphPad Software, Inc., La Jolla, CA, USA). The data are presented as mean ± standard error of mean (SEM). The sample sizes were determined based on prior experience and established standards in neurotoxicity, stem cell, and organoid research, where sample sizes of n=3 to 4 per group have consistently yielded statistically significant results.11, 14, 22, 31, 32To further support our approach, we conducted a power analysis using pilot data from the apoptosis assay. The analysis indicated that a sample size of at least 3 per group was sufficient to detect significant differencesAtty. Dkt. No.650053.01228 between control and propofol groups at a significance level of 0.05 with 80% power. In this study, data were collected from n = 3 samples per group for serum studies and n = 4 samples per group for organoid studies. Each serum sample was pooled from 3 to 4 patients, resulting in a total of 10 patient serum samples per group. Each organoid sample was derived from independent differentiations and pooled from two individual organoids, totaling in 8 organoids per group, unless otherwise noted. Statistical comparisons between two groups were made using Student’s t-test or the non-parametric Mann–Whitney test, depending on the data distribution. ANOVA was used for comparing the means of three or more groups. A p-value ≤0.05 was considered statistically significant.

[0086] Results

[0087] Characterization of iPSC-derived 3D cerebral organoids and anaesthetic-induced neurotoxicity on cerebral organoids

[0088] Human iPSCs grew as colonies in the mTeSR1 stem cell culture medium and expressed pluripotent stem cell markers, OCT4 and SSEA4 (Fig.1a, b). The 3D cerebral organoids derived from iPSCs exhibited a sphere-like shape (Fig.1b, c). The expression level of neuronal markers was found to be remarkably high in day 60-cerebral organoids (Fig. 1d, e). RT-qPCR analysis showed that the gene expression of nestin, a neural stem cell marker, increased by 2.8-fold on day 30 following the initiation of iPSC differentiation, then decreased on day 60. The gene expression of PAX6, a transcription factor involved in neural development, increased dramatically on days 30 and 60 (430.5- and 431.6-fold vs. day 0 group, respectively). The expression of NEFH and NEFM, which comprise the cytoskeleton in mature neurons, showed slight increases on days 20 and 60. The expression of GFAP, an astrocyte marker, increased slightly by 3.3-fold on day 30 and significantly by 42.1-fold on day 60. The GALC, an oligodendrocyte marker, gradually increased by 7.8-and 9.5-fold on days 30 and 60, respectively (Fig. 1d). These results demonstrate that organoids develop over time in culture, showing the presence of various types of brain cells. Immunofluorescent staining and confocal imaging of cerebral organoids revealed widespread positive staining for MAP2, a neuronal marker, along with sporadic positive staining for S100B, MBP, IBA-1, VWF, and SMA, markers of astrocytes, oligodendrocytes, microglia, endothelial cells, and smooth muscle cells, respectively, further confirming the presence of various types of brain cells within the organoids. Additionally, neurons in organoids on day 60 expressed the immature neuronal marker doublecortin (Fig. 1e). Therefore, in this study, we used day 60-cerebral organoids to studyAtty. Dkt. No.650053.01228 whether the intravenous anaesthetic propofol induced pathological changes and the underlying mechanisms.

[0089] The studies of anaesthetic-dose (0, 5, or 10 µg ml-1), exposure duration (1, 2, 3, or 6 hours), and exposure frequency (single or multiple) showed that either single 10 µg ml-1propofol exposure for 6 hours or three exposures for 2 hours per day over three consecutive days increased the activity of caspase 3, an apoptotic marker, in the day 60-cerebral organoids (Fig. 1f, g). Western blotting results (Fig.1h) demonstrated that single propofol (10 µg ml-1) exposure for 6 hours also increased LC3B I / II, an autophagy marker, in organoids. The propofol-increased autophagy was further confirmed by the electron microscopy images, displaying autophagosomes in the organoids compared to controls (Fig.1i).

[0090] Microarray and bioinformatic analysis of anaesthetic-induced dysregulated mRNA in organoids

[0091] The integrity of RNA isolated from the day 60-organoids treated with either propofol (10 µg ml-1for 6 hours) or control DMSO was confirmed to be suitable for further microarray assay, as indicated by clear and distinct 28S and 18S rRNA bands on agarose gels (Fig. 2a). The box and scatter plot results of the microarray detection signals demonstrated a similar distribution of normalised intensity between the propofol and control groups, suggesting that the gene expression signal intensity is reproducible, and the microarray results are suitable for further analysis (Fig. 2b, c). The hierarchical clustering showed that 553 mRNAs was dysregulated by propofol with 307 upregulated and 246 downregulated (P<0.05, fold change>±1.2) (Fig. 2d) documented in detail in (Table 3). Ingenuity pathway analysis (IPA)- based bioinformatic analysis of the dysregulated mRNA transcripts in propofol-treated cerebral organoids revealed associations with several critical signaling pathways. These pathways include: 1) Inflammation: Involving cytokines such as IL-2, IL-4, and IL-13.2) Mitochondrial Function: Pathways linked to mitochondrial activities. 3) Stress Responses: Including autophagy and unfolded protein response.3) Cellular Damage and Repair: Encompassing DNA damage, telomere maintenance, and apoptosis (Fig.2e).4) Cellular Function: Various pathways affecting normal cell operations. 5) Neurological Diseases and Disorders: Developmental and psychological disorders (Fig. 2f). These signaling pathways corroborate our observations of propofol-induced apoptosis and autophagy in the cerebral organoids (Fig. 1f-i) and align with previous findings from animal studies.3, 33Notably, the propofol-increased expression (2.3-fold) of CRH, the gene encoding corticotropin-releasing hormone, was linked to four neuralAtty. Dkt. No.650053.01228 phenotypes and activities: neurite morphology, hippocampus CA3 neuron excitation, abnormal neurotransmitter release, and the initiation of apoptosis (Table 4).

[0092] Anaesthetic-induced dysregulation of synaptic, mitochondrial, and inflammatory pathways in organoids

[0093] To further dissect the IPA-analysed signalling above (Fig. 2e, f), we used various bioinformatic tools and databases to enrich the dysregulated synaptic, mitochondrial, and inflammatory genes from the total propofol-induced 553 abnormally expressed genes. The SynGO database analysis revealed that the propofol-induced dysregulated mRNAs include 44 synaptic genes (Fig.3a), and these synaptic genes (CALB2, ATP2B4, NRP2, DNAJB1, NPY2R, SLC17A8, ERC2, and FILIP1) are specifically localized to the presynaptic and postsynaptic regions and are known to play crucial role in various synaptic activities, including intracellular calcium (Ca2+) homeostasis, presynaptic cytosolic Ca2+levels, and postsynaptic organization (Fig. 3b, c, and Table 5). Further IPA-based analysis showed that these synapse-related genes are associated with: 1) behaviour-related networks (e.g., anxiety-like behaviour, fear, spatial, associative, and motor learning), 2) neurodevelopment and function (e.g., synaptic transmission, morphology, and development of neurons (Fig. 3d, e) calcium handling (Fig. 3f). Supporting these transcriptomic findings, Western blot analysis demonstrated that propofol exposure significantly reduced the protein expression of PSD-95 and cFOS—key markers of synaptic integrity and neuronal activity, respectively (Fig.3g).

[0094] The mitoXplorer database identified a total of 39 propofol-dysregulated mitochondrial genes, with 21 up-regulated and 18 down-regulated in organoids (Fig. 3h, and Table 6). Most of these genes are linked to mitochondrial protein translation (e.g., WARS2, CCDC58, MRPL12, AURKAIP1, PUS1, PTRH2, and EARS2), while other mitochondrial genes were implicated in essential mitochondrial functions, mainly involving oxidative phosphorylation (OXPHOS), Fe-S cluster biosynthesis, importing and sorting, and mitochondrial dynamics (Fig. 3i). Additionally, IPA analysis of these mitochondrial genes strongly implicates their role in neurological diseases and psychological disorders (Fig.3j). Transmission electron microscopy further revealed marked mitochondrial structural abnormalities in propofol-treated organoids, including membrane disruption, cristae loss, and matrix rarefaction (Fig.3k). Additionally, IPA analysis of these mitochondrial genes strongly implicates their roles in neurological diseases and psychological disorders (Fig. 3j). Consistent with the dysregulated mitochondrial gene singling findings, propofol exposure significantly reduced intracellular ATP levels (Fig.3l) and downregulated creatine kinase, mitochondrial 1B (CKMT1B) at both the transcript (Table 6)Atty. Dkt. No.650053.01228 and protein levels (Fig.3m). Further, through the inflammation gene lists included in the NCBI database, we identified 23 propofol-induced dysregulated mRNA transcripts (Fig.3n, and Table 7). These genes are related to distinct immune cell functions such as cell migration, activation, attachment, chemotaxis, and homing involved in processes related to neurological diseases including loss of neurons, neurogenic atrophy, and cerebrovascular dysfunction (Fig.3o).

[0095] Anaesthetic-dysregulated lncRNA profiles in organoids

[0096] Out of 27,427 lncRNAs examined, a total of 792 lncRNA were dysregulated (above ±1.2-fold difference, p < 0.05) by propofol, including 330 upregulated and 462 downregulated lncRNAs (Table 8). Hierarchical clustering suggests high dissimilarity of lncRNA profiles between propofol-treated and control organoids (Fig. 4a). The lncRNA differential expression analysis was performed between propofol-treated and control organoids (Fig.4a, and Table 8), and by calculating the correlation coefficients between 792 dysregulated lncRNAs and abnormally expressed synaptic, mitochondrial, and inflammatory mRNA transcripts (Fig. 4b), we identified networks between abnormally expressed lncRNAs and dysregulated synaptic, mitochondrial, and inflammatory mRNAs involved in regulating crucial mechanisms associated with neurotoxicity in organoids (Fig.4c-e).

[0097] Anaesthesia-induced increase of brain injury-associated protein levels and dysregulated transcriptomic profiles in the serum of paediatric patients

[0098] The serum samples were collected pre- and post-surgery from paediatric patients under 4 years old (10 patient serum samples per group) who underwent anaesthesia (<1 hour or >3 hours) with propofol, ketamine, isoflurane, or sevoflurane at the Children’s Hospital of Wisconsin between September 2018 and October 2019. The studies from the patient serums, as a complementary models of stem cell-derived human cerebral organoids (Fig.5a), showed that less than one-hour anaesthesia / surgery did not change the protein levels of BDNF, NSE, and S100B, serum markers of brain cell injury or stress.25However, prolonged (> 3 hours) exposure to general anaesthesia / surgery significantly altered the levels of these proteins in serum (Fig. 5b), suggesting the brain injury of the patients with longer surgery and anaesthesia.

[0099] The microarray assay also detected the mRNA and lncRNA expression profiling for paediatric patients who underwent anaesthesia (>3 hours). The box and scatter plot for serum samples showed that the mRNA and lncRNA normalised gene expression intensity values were consistent for all the samples, confirming data integrity and consistency (Fig.7). Our microarray analysis further showed that compared with the pre-surgery control samples of paediatric patients, 1492 mRNA transcripts (Fig.5c, and Table S12) and 2809 lncRNAs (Fig.5c) wereAtty. Dkt. No.650053.01228 dysregulated (above 1.2-fold change and p < 0.05) in the post-surgery serum samples. Consistent with prior report bioinformatic analysis showed that anaesthesia / surgery- dysregulated mRNA had enrichment of transcripts related to the pathways associated with initiation and progression of neurodegeneration. Further, the SynGO, mitoXplorer, and NCBI database-based analysis identified that 1492 dysregulated mRNAs include 124 synaptic genes, 89 mitochondrial genes, and 110 inflammatory genes (Fig.5d). The microarray assay was further validated by RT-qPCR analysis of randomly selected mRNAs (NDUFA11, PGAM5, DRD1, and APC2) and two lncRNAs in serum, showing the same expression trend (up or down) for these genes (Fig.8 and 9) as we observed in the microarray results.

[0100] Anaesthesia / surgery-dysregulated brain cell type-specific mRNAs in serum

[0101] Through the dataset of Zhang et al.29, 30we sorted brain cell type-specific mRNAs from the 1,492 anaesthesia / surgery-induced dysregulated mRNAs. We identified 116 brain cell- specific mRNAs in the serum from patients with >3-hour anaesthesia / surgery: 38 genes associated with oligodendrocytes, 24 with neurons, 14 with microglia, 20 with astrocytes, and 20 with endothelial cells (Fig. 5e and Table 8). IPA analysis indicates that the neuron- and oligodendrocyte-associated anaesthesia / surgery-dysregulated genes were mainly enriched for emotional behavior, learning, sensory disorders, and brain development (e.g., axon genesis, axon guidance, and sprouting). In contrast, microglia-, astrocyte-, and endothelial cell- associated genes were mainly enriched in immune responses, phagosome maturation, metabolism, neovascularization, myelination, and angiogenesis (Fig.5f).

[0102] Overlapping anaesthetic-dysregulated mRNAs and lncRNAs in anaesthetic- exposed cerebral organoids and patient serum

[0103] To investigate the therapeutic and prognostic applications of cerebral organoids in the clinical setting, we characterised the overlapping anaesthesia-dysregulated mRNAs and lncRNAs between cerebral organoids and patient serum samples. The results showed a relatively low overlap of anaesthetic-induced dysregulated mRNAs and lncRNAs between the organoid and patient samples. Specifically, we identified 21 overlapping mRNAs (Fig. 6a, b) between the organoid dataset (553 total) and the patient serum dataset (1492 total). Among these, two mRNAs were related to synaptic function (ACTN1 and PTPRN2), and one was associated with mitochondrial function (CKMT1B) (Fig. 6c). Additionally, 12 overlapping lncRNAs were identified between the organoid dataset (792 total) and the patient serum dataset (2,809 total) (Fig. 6d, e). Notably, all 21 overlapping mRNAs and 12 lncRNAs exhibited consistent expression trends (either upregulated or downregulated) across both datasets (Fig.Atty. Dkt. No.650053.01228 6a–e). IPA analysis indicates that these 21 dysregulated overlapping mRNAs are associated with top canonical pathways, including response to stress, melatonin degradation (involved in the regulation of sleep and circadian rhythms), angiogenesis, energy metabolism, and inflammation (Fig. 6f). Metascape enrichment analysis also suggests the involvement of these dysregulated mRNAs in various other pathways, including the regulation of cell activities such as cell division, organelle fusion and organization, and vesicle-mediated transport (Fig. 6g). Notably, seven of the 12 overlapping lncRNAs and 11 of the 21 overlapping mRNAs were found to co-express (Pearson correlation > 0.9 or < −0.9, p < 0.05), forming crucial regulatory networks (Fig. 6h, i). The top network is related to cell morphology, neurological diseases, organismal injury, and abnormalities (Fig. 6j), and disease pathways and functions related to various neuronal activities and functions, tissue development, cell compromise, cell injury and death, inflammation, and the quantity of phagocytes (Fig.6k).

[0104] Discussion

[0105] This study leverages two complementary, human-relevant systems—stem cell-derived cerebral organoids and serum from anaesthetised paediatric patients—to investigate the cellular and molecular mechanisms underlying AIDN. The cerebral organoids recapitulate key features of the developing human brain, including structural organization, cell type diversity (Fig. 1a– e), and functional responsiveness, allowing controlled analysis of direct neurotoxic effects of propofol. In parallel, serum profiling from anaesthetised children provides translational context for the organoid findings. Through a multifaceted approach—including imaging, protein assays, transcriptomic profiling, and bioinformatics—we demonstrate that propofol induces dose-, duration-, and frequency-dependent cellular injury in human-relevant cerebral organoid models (Fig.1f, g). The observed increase in apoptosis aligns with prior in vivo and in vitro studies,31,34-36supporting the validity of our organoid model and confirming established anaesthetic effects on early neurodevelopment. Furthermore, transcriptomic analysis revealed dysregulation of 23 inflammatory genes (Figs. 2, 3n, 3o), consistent with activation of neuroinflammatory pathways previously reported in animal models.33, 37While these responses are anticipated, they provide a robust and biologically relevant foundation for mechanistic investigation. Importantly, these findings validate our organoid model and establish a critical framework for uncovering novel insights into anaesthetic-induced synaptic impairment, mitochondrial dysfunction, and their molecular interplay, as discussed in the following sections.

[0106] Synaptic and mitochondrial mechanisms in AIDNAtty. Dkt. No.650053.01228

[0107] Beyond the anticipated apoptotic and inflammatory responses, our organoid study revealed previously uncharacterized and mechanistically novel effects of anaesthetic exposure on synaptic and mitochondrial integrity. Using transcriptomic profiling of human cerebral organoids, we identified 45 dysregulated synaptic genes and 39 mitochondrial genes following propofol treatment (Fig. 3a, 3h). Among the affected synaptic genes, ATP2B4, CALB2, and NRP2 are critical regulators of calcium signalling, synaptic organization, and neuronal excitability—functions essential for neurodevelopment and cognitive performance. Notably, propofol exposure also significantly decreased the protein expression of PSD95 and cFOS (Fig. 3g). PSD95 is a postsynaptic scaffolding protein essential for anchoring NMDA and AMPA receptors, maintaining synaptic architecture, and supporting synaptic plasticity.38cFOS, an immediate early gene, is widely used as a marker of neuronal activation and plays a central role in activity-dependent synaptic regulation.39Their downregulation indicates impaired synaptogenesis and reduced neuronal responsiveness, representing a critical axis of synaptic vulnerability in AIDN. In parallel, propofol-induced mitochondrial disruption emerged as a major injury mechanism of AIDN. Mitochondria are essential for neuronal ATP generation, calcium buffering, and support of synaptic activity. Propofol exposure led to decreased intracellular ATP levels (Fig. 3l), mitochondrial swelling, cristae disruption (Fig. 3k), and upregulated autophagy (Fig. 1g–i), indicative of mitochondrial stress and compensatory clearance of damaged organelles. A key finding was the consistent downregulation of CKMT1B, a mitochondrial isoform of creatine kinase, at both transcript and protein levels (Table S6 and Fig. 3m, respectively). CKMT1B plays a critical role in buffering cellular ATP levels and supporting synaptic energy demands, especially during stress. Its impaired expression may indicate a breakdown in bioenergetic homeostasis, contributing to deficits in neuronal differentiation, synaptic transmission, and neuroplasticity.40To our knowledge, this is the first report implicating CKMT1B as a molecular target in AIDN. Together, these data support a novel mechanistic framework for AIDN, in which mitochondrial dysfunction directly impairs synaptogenesis through disrupted energy homeostasis and signalling. The identification of CKMT1B and synaptic structural proteins (PSD95, c-FOS) as converging targets strengthens the biological plausibility and translational relevance of our model. These findings extend beyond known injury pathways and position mitochondrial–synaptic crosstalk as a central axis of vulnerability in the developing brain.

[0108] LncRNA mechanisms in anaesthetic neurotoxicityAtty. Dkt. No.650053.01228

[0109] LncRNAs are a diverse class of RNA molecules that do not encode proteins but play essential roles in regulating gene expression and a wide range of cellular processes. Notably, lncRNAs exhibit very low sequence conservation across species compared to protein-coding genes, limiting the translational relevance of animal models for understanding their function. Importantly, over 48% of known lncRNAs are specifically expressed in the brain, suggesting a critical role in neurodevelopment and brain function. Accumulating evidence implicates lncRNAs in the pathogenesis of various neurodevelopmental and neurodegenerative disorders, including Alzheimer’s disease and schizophrenia.18, 41Despite their recognised importance, the role of lncRNAs in AIDN remains largely unexplored, particularly in human brain tissue. This knowledge gap underscores the need to investigate lncRNA-mediated regulatory mechanisms in human-relevant models. Human cerebral organoids offer a physiologically relevant 3D platform to study lncRNAs within the context of developing brain tissue. LncRNAs are known to regulate nearby (cis) or distant (trans) protein-coding genes, forming intricate co-expression networks that may drive tissue-specific responses to environmental insults. To explore these networks, we identified propofol-dysregulated lncRNAs and assessed their co-expression with differentially expressed mRNAs in human cerebral organoids. Our analysis revealed that propofol exposure induced widespread changes in lncRNA expression, with 462 lncRNAs downregulated and 330 upregulated (Fig. 4a; Table S8). Co-expression network analysis showed that many of these dysregulated lncRNAs were closely associated with disrupted synaptic, mitochondrial, and inflammatory gene expression programs (Fig. 4b–d), implicating them in key pathways involved in mitochondrial metabolism, neuronal signalling, and brain development. These findings represent the first evidence that anaesthetic exposure alters lncRNA expression in human brain models and suggest that lncRNAs may serve as central regulators of anaesthetic-induced molecular dysregulation. By participating in complex interactions with protein-coding genes, dysregulated lncRNAs may contribute to neurodevelopmental vulnerability and long-term functional impairment following early-life anaesthetic exposure.

[0110] Serum biomarkers and therapeutic targets for anaesthesia-induced neurotoxicity

[0111] Identifying reliable biomarkers for brain injury caused by general anaesthetic exposure remains a major challenge in clinical practice. Emerging evidence suggests that changes in circulating mRNAs and lncRNAs following anaesthetic exposure may be detectable in serum samples, offering a minimally invasive opportunity for early detection and risk stratification in paediatric patients. This concept is supported by recent studies showing that circulating proteins,Atty. Dkt. No.650053.01228 mRNAs, and lncRNAs in serum and plasma of patients correlate with brain injury in various diseases, including traumatic brain injury, neuroinflammation, and Alzheimer’s disease.42-46In our studies we identified the following classes of potential serum biomarkers for AIDN: 1) Serum proteins BDNF, NSE, and S100B, which are well-established serum biomarkers of brain cell injury,42-44were significantly altered in children exposed to prolonged anaesthesia (> 3 hours). 2) a total of 21 dysregulated mRNAs and 12 lncRNAs found to overlap between anaesthetic-treated cerebral organoids and serum from paediatric patients (Fig. 6a-e). 3) 116 abnormally expressed serum mRNAs mapped to brain cell-type specific genes, including those expressed in neurons, astrocytes, oligodendrocytes, microglial, and endothelial cells (Fig. 5e, and Table 8). These potential biomarkers were justified as follow:

[0112] Serum proteins associated with brain cell injury. We observed significant alterations in serum biomarkers associated with brain injury in paediatric patients under 4 years of age who underwent general anaesthesia lasting more than 3 hours. Specifically, levels of S100B and NSE were significantly elevated, whereas BDNF levels were markedly reduced compared to children who received anaesthesia for less than one hour (Fig. 5b). S100B is a calcium-binding protein predominantly produced by astrocytes and is widely recognised as a marker of astrocyte activation and central nervous system injury. NSE, a neuron-specific glycolytic enzyme, serves as a sensitive indicator of neuronal damage when elevated in the serum. Conversely, BDNF is a key neurotrophin essential for neuronal survival, synaptic plasticity, and brain development. Its reduced expression suggests compromised neurotrophic support and increased vulnerability to anaesthetic-induced neurotoxicity. These serum biomarker changes closely mirror the cellular damage observed in cerebral organoids, particularly the increase in apoptosis. Both animal studies and human stem cell-based in vitro models have shown that volatile anaesthetics (e.g., isoflurane, sevoflurane) and intravenous agents such as propofol can disrupt the integrity of the blood-brain barrier (BBB) by impairing its structural and transport properties.47 48Additionally, emerging evidence suggests that extracellular vesicles may serve as alternative carriers for transporting intracellular contents— such as proteins and RNAs—into the systemic circulation. It is therefore plausible that the observed brain injury protein biomarkers and overlapping RNAs detected in patient serum originate from BBB leakage and / or extracellular vesicle-mediated transport. Additionally, emerging evidence suggests that extracellular vesicles may serve as alternative carriers for transporting intracellular contents—such as proteins and RNAs—into the systemic circulation. It is therefore plausible that the observed brain injury protein biomarkers and overlapping RNAsAtty. Dkt. No.650053.01228 detected in patient serum originate from BBB leakage and / or extracellular vesicle-mediated transport.

[0113] Overlap of dysregulated genes between organoids and serum samples. In addition to altered serum protein markers of brain injury, we identified 21 mRNAs and 12 lncRNAs that overlapped between cerebral organoids and patient serum (Fig. 6). Although the number of shared transcripts is limited, their enrichment in critical pathways—including synaptic function, mitochondrial metabolism, neurodevelopment, inflammation, and neurological disease— highlights their biological relevance. Among these, two synaptic genes (ACTN1 and PTPRN2) and one mitochondrial gene (CKMT1B) were consistently dysregulated (Fig. 6b). ACTN1 encodes alpha-actinin 1, a cytoskeletal protein essential for maintaining synaptic structure and plasticity; its upregulation may reflect synaptic remodeling or cellular stress responses. PTPRN2, involved in synaptic vesicle trafficking and neurotransmitter release, was downregulated, suggesting impaired synaptic signaling that may contribute to cognitive deficits. As we mentioned earlier, CKMT1B is a mitochondrial creatine kinase responsible for ATP buffering and neuronal energy homeostasis. It was downregulated at both the transcript and protein level in organoids (Table 6, Fig. 3m). Its suppression coincided with reduced ATP production and mitochondrial damage (Fig. 3k and i), positioning CKMT1B as a novel biomarker and potential therapeutic target for AIDN. Furthermore, among the 12 overlapping lncRNAs, 7 were co-expressed with 11 of the 21 protein-coding genes, forming putative regulatory networks in response to anaesthesia. These lncRNA–mRNA pairs were associated with gene pathways implicated in brain cell injury, neurodevelopment, and cognition (Fig.6h– k). This integrative analysis not only supports the involvement of these genes in AIDN but also identifies circulating serum-derived RNA markers with potential clinical utility for assessing anaesthetic-related neurotoxicity.

[0114] Serum biomarkers mapped to brain cell-type specific genes. In our analysis, 116 dysregulated serum mRNAs were mapped to brain cell-type–specific genes, including those potentially expressed in neurons (24 genes), astrocytes (20), oligodendrocytes (38), microglia (14), and endothelial cells (20) (Fig.5e; Table 8). Functional enrichment analysis revealed that these cell-type–associated transcripts were significantly involved in critical neurodevelopmental and physiological pathways, such as synaptic transmission, axonogenesis, myelination, neuroinflammation, and blood-brain barrier regulation (Fig. 5f). These findings suggest that serum-derived transcripts may serve as non-invasive biomarkers reflecting cell- type–specific brain injury following prolonged anaesthetic exposure, further supporting theAtty. Dkt. No.650053.01228 translational relevance of our cerebral organoid model. Together, our findings from human cerebral organoids and paediatric patient serum samples underscore the multifaceted nature of AIDN, encompassing apoptosis, mitochondrial dysfunction, synaptic disruption, and neuroinflammation. These cellular processes are accompanied by the dysregulation of both coding and lncRNAs, including several mapped to brain cell type–specific pathways. By integrating brain-specific and systemic analyses, this study provides mechanistic insight and lays a foundation for translational applications such as serum-based diagnostics and RNA- targeted therapeutic strategies, including anti-inflammatory agents, mitochondrial stabilizers, and RNA-modulating therapies. While the dual-model approach enhances our understanding of AIDN, it is important to acknowledge its inherent limitations. First, the biological differences between tissue types—namely, cerebral organoids and peripheral blood—likely account for the relatively low number of overlapping dysregulated genes. Organoids reflect localised, cell-type- specific responses within developing neural tissues (e.g., neurons, astrocytes, glial cells), whereas serum reflects broader systemic alterations shaped by physiological stressors such as inflammation and immune activation. Moreover, the BBB restricts molecular exchange between the central nervous system and circulation, further contributing to divergent gene expression profiles across compartments. In addition, the paediatric patient serum data were obtained in a real-world clinical setting that involved not only anaesthetic exposure but also surgical procedures a—introducing confounding factors that are absent in the controlled organoid model. Despite these challenges, the shared dysregulation of key genes such as CKMT1B across both models strengthens the translational significance of our findings. Finally, we recognise the statistical limitations imposed by the modest clinical sample size (n = 10 per group). Future studies involving larger, independent patient cohorts will be essential to confirm and expand upon these findings and to better understand their clinical significance.

[0115] Conclusion

[0116] This study provides an integrated molecular and pathological characterisation of AIDN using two complementary, human-relevant models: stem cell–derived cerebral organoids and serum samples from paediatric patients. Cerebral organoids enabled us to investigate the direct effects of anaesthetic exposure under controlled conditions, revealing mechanistic insights into apoptosis, synaptic impairment, mitochondrial dysfunction, inflammation, and the dysregulation of both coding and long non-coding RNAs. Importantly, we identified a novel mitochondrial–synaptic signalling axis and highlighted CKMT1B as a potential translational biomarker and therapeutic target. Parallel analysis of serum samples reflected systemicAtty. Dkt. No.650053.01228 responses to anaesthesia in a real-world clinical context. We observed altered levels of established brain injury markers (BDNF, NSE, S100B) and a subset of overlapping dysregulated lncRNAs and mRNAs between serum and organoids, reinforcing the translational relevance of our findings. Serum transcriptomic profiles further revealed gene changes associated with brain cell type–specific pathways, suggesting their potential utility as non- invasive biomarkers for AIDN. Together, these models offer complementary perspectives: organoids model direct, brain-specific injury, while serum analysis captures systemic stress responses. This dual approach supports the development of serum-based diagnostics and RNA- targeted therapeutic strategies for AIDN, including anti-inflammatory agents, mitochondrial stabilisers, and gene modulators. In summary, our findings not only expand current understanding of AIDN pathophysiology but also provide a foundation for biomarker discovery and future therapeutic intervention. Further longitudinal and large-scale human studies are needed to validate these observations and explore the long-term impact of anaesthetic exposure on neurodevelopmental outcomes in children. Table 2: Primer information. Note: bps: base pairs; NEFH: neurofilament heavy chain; NEFM: neurofilament medium chain; GALC: galactosylceramidase; GFAP: glial fibrillary acidic protein; PAX6: paired box 6; NES: nestin; NDUFA11:NADH: ubiquinone oxidoreductase subunit A11; PGAM5: mitochondrial serine / threonine protein phosphatase; DRD1: Dopamine receptor D1;APC2:APC regulator of WNT signaling pathway 2; SMCR5:Smith-Magenis syndrome chromosome region candidate 5; DUBR: DPPA2 upstream binding RNA; GAPDH: glyceraldehyde-3-phosphate dehydrogenase Gene ID SEQ ID NO Primer Sequence (from 5’ to 3’) Product lengthAtty. Dkt. No.650053.01228 Gene ID SEQ ID NO Primer Sequence (from 5’ to 3’) Product length (bps)Atty. Dkt. No.650053.01228 Gene ID SEQ ID NO Primer Sequence (from 5’ to 3’) Product length (bps)Table 3: Dysregulated coding genes (mRNA) in propofol (6h)-treated cerebral organoids. Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value RegulationAtty. Dkt. No.650053.01228 Gene ID Fold P change value Regulation Table 4: IPA aregulated mRNAs transcripts with neural phenotypes in propofol (6 hours)-treated cerebral organoids. The genes expressing more than ±1.2-fold difference between the propofol and vehicle control groups were analyzed by IPA software to predict neural phenotypes. ↑: up-regulated following propofol exposure vs. control group. ↓: downregulated following propofol exposure vs. control group. Phenotype observed Predicted genes involved (vs. control) ↑Atty. Dkt. No.650053.01228 Phenotype observed Predicted genes involved (vs. control) CNS afterhyperpolarization ↓ATP2B4 D ,Table 5: Dysregulated synaptic genes in propofol exposed organoids. Gene ID P value Fold change Regulation ATP2B4 0.026 1.639 DownAtty. Dkt. No.650053.01228 Gene ID P value Fold change Regulation HSP90AA1 0.001 1.338 Up ADGRL2 0004 1354 UTable 6: Dysregulated mitochondrial genes in propofol exposed organoids. Biological Fold Gene ID Gene name Process change RegulationAtty. Dkt. No.650053.01228 Biological Fold Gene ID Gene name Process change RegulationAtty. Dkt. No.650053.01228 Biological Fold Gene ID Gene name Process change RegulationGene ID P Fold value change RegulationAtty. Dkt. No.650053.01228 Gene ID P Fold value change RegulationTable 8 - Brain cell type-specific mRNAs in the serum from pediatric patients < 4 years old with >3-hour anesthesia / surgery Genes Pvalues Fold Change Cell Type FRMPD2 0.028 2.296 astrocytesAtty. Dkt. No.650053.01228 Genes Pvalues Fold Change Cell Type CFI 0.040 2.169 endothelial RBMS2 0.000 5.129 endothelialAtty. Dkt. No.650053.01228 Genes Pvalues Fold Change Cell Type MARCKSL 0.022 5.252 oligodendrocytes 1References 1 Sun L. Early childhood general anaesthesia exposure and neurocognitive development. Br J Anaesth 2010; 105 Suppl 1: i61-8 2 Andropoulos DB, Greene MF. Anesthesia and Developing Brains - Implications of the FDA Warning. N Engl J Med 2017; 376: 905-7 3 Yan Y, Logan S, Liu X, et al. Integrated Excitatory / Inhibitory Imbalance and Transcriptomic Analysis Reveals the Association between Dysregulated Synaptic Genes and Anesthetic-Induced Cognitive Dysfunction. Cells 2022; 11 4 Yan Y, Qiao S, Kikuchi C, et al. Propofol Induces Apoptosis of Neurons but Not Astrocytes, Oligodendrocytes, or Neural Stem Cells in the Neonatal Mouse Hippocampus. Brain Sci 2017; 7 5 Yang H, Liang G, Hawkins BJ, Madesh M, Pierwola A, Wei H. Inhalational anesthetics induce cell damage by disruption of intracellular calcium homeostasis with different potencies. Anesthesiology 2008; 109: 243-50 6 Popic J, Pesic V, Milanovic D, Todorovic S, Kanazir S, Jevtovic-Todorovic V, Ruzdijic S. Propofol-induced changes in neurotrophic signaling in the developing nervous system in vivo. PLoS One 2012; 7: e34396 7 Kahraman S, Zup SL, McCarthy MM, Fiskum G. GABAergic mechanism of propofol toxicity in immature neurons. J Neurosurg Anesthesiol 2008; 20: 233-40Atty. Dkt. No.650053.01228 Sun LS, Li G, Miller TL, et al. Association Between a Single General Anesthesia Exposure Before Age 36 Months and Neurocognitive Outcomes in Later Childhood. JAMA 2016; 315: 2312-20 Warner DO, Zaccariello MJ, Katusic SK, et al. Neuropsychological and Behavioral Outcomes after Exposure of Young Children to Procedures Requiring General Anesthesia: The Mayo Anesthesia Safety in Kids (MASK) Study. Anesthesiology 2018; 129: 89-105 McCann ME, de Graaff JC, Dorris L, et al. Neurodevelopmental outcome at 5 years of age after general anaesthesia or awake-regional anaesthesia in infancy (GAS): an international, multicentre, randomised, controlled equivalence trial. Lancet 2019; 393: 664-77 Logan S, Arzua T, Yan Y, et al. Dynamic Characterization of Structural, Molecular, and Electrophysiological Phenotypes of Human-Induced Pluripotent Stem Cell- Derived Cerebral Organoids, and Comparison with Fetal and Adult Gene Profiles. Cells 2020; 9 Logan S, Arzua T, Canfield SG, Seminary ER, Sison SL, Ebert AD, Bai X. Studying Human Neurological Disorders Using Induced Pluripotent Stem Cells: From 2D Monolayer to 3D Organoid and Blood Brain Barrier Models. Compr Physiol 2019; 9: 565-611 Bai X. Use of induced pluripotent stem cell-derived brain cells, organoids, assembloids, and blood-brain barrier models in understanding alcohol and anesthetic- induced brain injuries: an emerging perspective. Neural Regen Res 2024; 19: 953-4 Arzua T, Yan Y, Jiang C, et al. Modeling alcohol-induced neurotoxicity using human induced pluripotent stem cell-derived three-dimensional cerebral organoids. Transl Psychiatry 2020; 10: 347 Chen X, Birey F, Li MY, et al. Antisense oligonucleotide therapeutic approach for Timothy syndrome. Nature 2024; 628: 818-25 Lu Q, Xie Z, Yan C, et al. SNRK (Sucrose Nonfermenting 1-Related Kinase) Promotes Angiogenesis In Vivo. Arterioscler Thromb Vasc Biol 2018; 38: 373-85 Mattick JS, Amaral PP, Carninci P, et al. Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat Rev Mol Cell Biol 2023; 24: 430-47 Arzua T, Jiang C, Yan Y, Bai X. The importance of non-coding RNAs in environmental stress-related developmental brain disorders: A systematic review of evidence associated with exposure to alcohol, anesthetic drugs, nicotine, and viral infections. Neurosci Biobehav Rev 2021; 128: 633-47 Horikoshi Y, Yan Y, Terashvili M, et al. Fatty Acid-Treated Induced Pluripotent Stem Cell-Derived Human Cardiomyocytes Exhibit Adult Cardiomyocyte-Like Energy Metabolism Phenotypes. Cells 2019; 8 Ludbrook GL, Visco E, Lam AM. Propofol: relation between brain concentrations, electroencephalogram, middle cerebral artery blood flow velocity, and cerebral oxygen extraction during induction of anesthesia. Anesthesiology 2002; 97: 1363-70 Vutskits L, Gascon E, Tassonyi E, Kiss JZ. Clinically relevant concentrations of propofol but not midazolam alter in vitro dendritic development of isolated gamma- aminobutyric acid-positive interneurons. Anesthesiology 2005; 102: 970-6 Liu Y, Yan Y, Inagaki Y, Logan S, Bosnjak ZJ, Bai X. Insufficient Astrocyte-Derived Brain-Derived Neurotrophic Factor Contributes to Propofol-Induced Neuron Death Through Akt / Glycogen Synthase Kinase 3beta / Mitochondrial Fission Pathway. Anesth Analg 2017; 125: 241-54Atty. Dkt. No.650053.01228 Twaroski DM, Yan Y, Zaja I, Clark E, Bosnjak ZJ, Bai X. Altered Mitochondrial Dynamics Contributes to Propofol-induced Cell Death in Human Stem Cell-derived Neurons. Anesthesiology 2015; 123: 1067-83 Twaroski DM, Yan Y, Olson JM, Bosnjak ZJ, Bai X. Down-regulation of microRNA- 21 is involved in the propofol-induced neurotoxicity observed in human stem cell- derived neurons. Anesthesiology 2014; 121: 786-800 Cho E, Granger J, Theall B, et al. Blood and MRI biomarkers of mild traumatic brain injury in non-concussed collegiate football players. Sci Rep 2024; 14: 665 Pant T, Dhanasekaran A, Bai X, et al. Genome-wide differential expression profiling of lncRNAs and mRNAs associated with early diabetic cardiomyopathy. Sci Rep 2019; 9: 15345 Marchiano F, Haering M, Habermann BH. The mitoXplorer 2.0 update: integrating and interpreting mitochondrial expression dynamics within a cellular context. Nucleic Acids Res 2022; 50: W490-W9 Arzua T, Yan Y, Liu X, Dash RK, Liu QS, Bai X. Synaptic and mitochondrial mechanisms behind alcohol-induced imbalance of excitatory / inhibitory synaptic activity and associated cognitive and behavioral abnormalities. Transl Psychiatry 2024; 14: 51 Zhang Y, Sloan SA, Clarke LE, et al. Purification and Characterization of Progenitor and Mature Human Astrocytes Reveals Transcriptional and Functional Differences with Mouse. Neuron 2016; 89: 37-53 Darmanis S, Sloan SA, Zhang Y, et al. A survey of human brain transcriptome diversity at the single cell level. Proc Natl Acad Sci U S A 2015; 112: 7285-90 Bai X, Yan Y, Canfield S, et al. Ketamine enhances human neural stem cell proliferation and induces neuronal apoptosis via reactive oxygen species-mediated mitochondrial pathway. Anesth Analg 2013; 116: 869-80 Lindenhofer D, Haendeler S, Esk C, et al. Cerebral organoids display dynamic clonal growth and tunable tissue replenishment. Nat Cell Biol 2024; 26: 710-8 Useinovic N, Maksimovic S, Liechty C, Cabrera OH, Quillinan N, Jevtovic-Todorovic V. Systemic inflammation exacerbates developmental neurotoxicity induced by sevoflurane in neonatal rats. Br J Anaesth 2022; 129: 555-66 Banerjee P, Rossi MG, Anghelescu DL, et al. Association Between Anesthesia Exposure and Neurocognitive and Neuroimaging Outcomes in Long-term Survivors of Childhood Acute Lymphoblastic Leukemia. JAMA Oncol 2019; 5: 1456-63 McCann ME, Soriano SG. Does general anesthesia affect neurodevelopment in infants and children? BMJ 2019; 367: l6459 Xu L, Shen J, Yu L, Sun J, McQuillan PM, Hu Z, Yan M. Role of autophagy in sevoflurane-induced neurotoxicity in neonatal rat hippocampal cells. Brain Res Bull 2018; 140: 291-8 Xu F, Han L, Wang Y, et al. Prolonged anesthesia induces neuroinflammation and complement-mediated microglial synaptic elimination involved in neurocognitive dysfunction and anxiety-like behaviors. BMC Med 2023; 21: 7 Coley AA, Gao WJ. PSD-95 deficiency disrupts PFC-associated function and behavior during neurodevelopment. Sci Rep 2019; 9: 9486 Sakurai K. Rethinking c-Fos for understanding drug action in the brain. J Biochem 2024; 175: 377-81 Wyss M, Kaddurah-Daouk R. Creatine and creatinine metabolism. Physiol Rev 2000; 80: 1107-213Atty. Dkt. No.650053.01228 41 Srinivas T, Mathias C, Oliveira-Mateos C, Guil S. Roles of lncRNAs in brain development and pathogenesis: Emerging therapeutic opportunities. Mol Ther 2023; 31: 1550-61 42 Goyal A, Failla MD, Niyonkuru C, Amin K, Fabio A, Berger RP, Wagner AK. S100b as a prognostic biomarker in outcome prediction for patients with severe traumatic brain injury. J Neurotrauma 2013; 30: 946-57 43 Cheng F, Yuan Q, Yang J, Wang W, Liu H. The prognostic value of serum neuron- specific enolase in traumatic brain injury: systematic review and meta-analysis. PLoS One 2014; 9: e106680 44 Korley FK, Diaz-Arrastia R, Wu AH, et al. Circulating Brain-Derived Neurotrophic Factor Has Diagnostic and Prognostic Value in Traumatic Brain Injury. J Neurotrauma 2016; 33: 215-25 45 Lei J, Zhang X, Tan R, Li Y, Zhao K, Niu H. Levels of lncRNA GAS5 in Plasma of Patients with Severe Traumatic Brain Injury: Correlation with Systemic Inflammation and Early Outcome. J Clin Med 2022; 11 46 Khodayi M, Khalaj-Kondori M, Hoseinpour Feizi MA, Jabarpour Bonyadi M, Talebi M. Plasma lncRNA profiling identified BC200 and NEAT1 lncRNAs as potential blood-based biomarkers for late-onset Alzheimer's disease. EXCLI J 2022; 21: 772-85 47 Hughes JM, Neese OR, Bieber DD, Lewis KA, Ahmadi LM, Parsons DW, Canfield SG. The Effects of Propofol on a Human in vitro Blood-Brain Barrier Model. Front Cell Neurosci 2022; 16: 835649 48 Thal SC, Luh C, Schaible EV, et al. Volatile anesthetics influence blood-brain barrier integrity by modulation of tight junction protein expression in traumatic brain injury. PLoS One 2012; 7: e50752

[0117] Generation of human cerebral organoids from iPSCs

[0118] In brief, singularized iPSCs were plated at a seeding density of 12,000 cells / well in an ultra-low attachment 96-well plate and cultured with mTeSR1 medium (STEMCELL Technologies, Vancouver, Canada) in the incubator (5% CO2, 21% O2) at 37 °C. The medium was changed every day for 5 days. On Day 6, embryonic bodies were transferred into each well of an ultra-low attachment 24-well plate and cultured with neural induction media for the formation of neuroepithelial tissues. On Day 11, each neuroepithelial tissue was embedded as a Matrigel droplet, and every 16 droplets were cultured with organoid differentiation media without vitamin A in 100-mm Petri dishes. On Day 15, the cerebral organoids were further cultured in the organoid differentiation media with vitamin A on an orbital shaker (at 80 rpm). The media were changed every 3 days. We utilized the MycoAlert® Mycoplasma Detection Kit (Lonza, Basel, Switzerland) to assess potential mycoplasma contamination in our iPSC and organoid cultures. The analysis confirmed that our iPSC cultures were free from mycoplasma contamination. Organoid experiments below were from days 30 and 60 cerebral organoids. Each sample (n = 4) per group was pooled from two organoids for protein and RNA assays.Atty. Dkt. No.650053.01228 Each sample was generated from 4 independent differentiations of iPSCs cultured in separate dishes.

[0119] Immunofluorescence staining

[0120] Briefly, iPSCs cultured on coverslips were fixed and stained with the primary antibodies: anti-stage-specific embryonic antigen 4 (SSEA4, Abcam, Cambridge, MA, USA; ab16287) and anti-octamer-binding transcription factor 4 (OCT4, Sigma Aldrich, St. Louis, MO, USA; AB3209). SSEA4 and OCT4 are pluripotent stem cell markers. Two-month-old cerebral organoids were fixed with 10% zinc formalin (Sigma Aldrich), embedded in paraffin, and sectioned into 4 µm thick slices. The sections were blocked in 10% donkey serum for 30 minutes at room temperature. The tissue sections were then incubated with the following primary antibodies at 4 °C overnight to characterize the presence of the various types of brain cells within organoids: 1) Anti-microtubule-associated protein-2 (MAP2: a neuron marker; Abcam, ab11267), anti-doublecortin (an immature and migrating neuron marker; Abcam ab18723), 2) anti-S100 calcium-binding protein B (S100B: an astrocyte marker; Abcam, ab868), 3) anti-allograft inflammatory factor 1 / Ionized Calcium-Binding Adapter Molecule 1 (AIF- 1 / IBA1: a microglia marker; Novus Biologicals, CO, USA; NB100-1028), 4) anti-von Willebrand Factor (VWF: and endothelial cell marker) (DAKO, CA, USA; A0082), 5) anti- smooth muscle actin (SMA: a smooth muscle cell marker) (Novus Biologicals, MAB343c), and 6) anti-myelin basic protein (MBP: oligodendrocyte marker; Santa Cruz, Dallas, TX, USA; sc- 66064). After washing with phosphate-buffered saline (PBS) three times, the sections were further stained with Alexa Fluor 488-conjugated anti-mouse immunoglobulin G (IgG) or goat IgG and Alexa Fluor 594-conjugated donkey anti-rabbit (Thermo Fisher Scientific, Waltham, MA, USA) for 45 minutes at 37 °C. After three washes with PBS, the nuclei were stained with Hoechst 33342 (Thermo Fisher Scientific). Images of the stained sections were captured using laser scanning confocal microscopy Nikon Eclipse TE2000-U (Nikon, Tokyo, Japan).

[0121] Analysis of anaesthetic-induced pathology and mitochondrial dysfunction on cerebral organoids

[0122] Electron Microscopy: Cerebral organoids were fixed with 2% glutaraldehyde buffer at 4 ℃ and processed into sections with 60 nm thickness for electron microscopy analysis. The sections were stained with lead citrate and uranyl acetate and then imaged with a H600 electron microscope (Hitachi, Japen).

[0123] Caspase 3 activity assay: Whole-cell protein lysates from organoids were used for both Western blotting and Caspase 3 activity assay. Caspase 3 activity was measured using a caspaseAtty. Dkt. No.650053.01228 3 colourimetric assay kit (Sigma Aldrich) following Manufacturer’s protocol. The resulting data were calculated using the following formula: µmol caspase 3 reaction product dilution factor 100%ml sample lysate minutes reaction time mg protein

[0124] Western blotting: Organoid protein lysates were prepared using RIPA buffer (Cell Signaling Technology, Danvers, MA, USA; #9806), freshly supplemented with phosphatase inhibitor cocktails (Roche Diagnostics, Indianapolis, IN, USA) and phenylmethylsulfonyl fluoride. Primary antibodies used included: anti-microtubule associated protein 1 light chain 3 beta (LC3B, Cell Signaling Technology, #3868), anti-PSD95 antibody (abcam, ab18258), CKMT Polyclonal Antibody (Thermo Fisher Scientific, bs-6522R), c-Fos Monoclonal Antibody (2G9C3) (Thermo Fisher Scientific, MA1-21190), and anti-beta actin (Cell Signaling Technology, #4967S). Secondary antibodies included anti-rabbit and anti-mouse IgG conjugated with horseradish peroxidase (Cell Signaling Technology). The signals on the PVDF (polyvinylidene fluoride or polyvinylidene difluoride) membranes (Bio-Rad, Hercules, CA, USA) were developed using an ECL Detection kit (GE Healthcare Life Sciences, Marlborough, MA, USA) and further captured using a ChemiDoc imaging system (Bio-Rad). Beta actin was used as the endogenous control for protein normalization. The relative expression fold change of each protein was calculated by capturing and analyzing the optical densities of specific bands using the ChemiDoc imaging system (Bio-Rad) and normalizing with beta actin as the endogenous control protein.

[0125] ATP assay: Intracellular ATP levels were measured using the CellTiter-Glo® Luminescent Cell Viability Assay (Thermo Fisher Scientific, Cat# A22066). Briefly, organoids were lysed using RIPA buffer (Cell Signaling Technology), and the lysates were added to the freshly prepared reaction solution following the manufacturer’s protocol. Luminescence, which is directly proportional to ATP concentration, was measured using a microplate reader (CLARIOstar®, BMG LABTECH, Ortenberg, Germany). ATP levels for each sample were normalised to the total protein content included in the reaction.

[0126] Patient characteristics and demographics

[0127] The study, as outlined in the flowchart (Figure 12) and described in detail below, was approved by the Institutional Review Board of the Medical College of Wisconsin (Protocol Number: 1077311). The purpose and nature of the research were thoroughly explained to the parents and participants, and informed consent or assent was obtained from all who agreed toAtty. Dkt. No.650053.01228 participate. A total of 20 paediatric patients were enrolled at the Children’s Hospital of Wisconsin between September 2018 and October 2019. The study included two groups: 10 patients who underwent surgery lasting less than one hour, and 10 patients with surgery durations exceeding three hours. Inclusion criteria were as follows: 1) Patients aged under 4 years undergoing non-neurosurgical procedures.2) Exposure to general anaesthetics (propofol, ketamine, isoflurane, or sevoflurane) for either less than one hour or more than three hours, with an existing intravenous (IV) line in place during surgery.3) No prior treatment with medications known to influence brain function. Only anaesthetic agents administered as part of routine care were used.4) Patients exposed to general anaesthesia for more than 3 hours were selected based on prior studies identifying early-life prolonged anaesthesia. 5) as a potential risk factor for neurotoxicity. Patients undergoing anaesthesia for less than one hour served as the control group. Exclusion criteria included: 1) Absence of IV access during surgery.2) Unanticipated extension of anaesthetic duration due to blood draw logistics (e.g., actual surgery duration between 1–3 hours). 3) Patients undergoing brain surgery. 4) A medical history potentially affecting serum biomarker levels.

[0128] Reverse transcription-quantitative PCR (RT-qPCR)

[0129] RT-qPCR was used to quantify the expression of coding genes (mRNAs) related to neural stem cells, neurons, and astrocytes within the organoids and to confirm the expression tendency of the randomly selected mRNAs and lncRNAs from microarray assays. Briefly, cDNA was synthesized from total RNA using the Revert Aid™ First Strand cDNA Synthesis Kit (Thermo Fisher Scientific) according to the manufacturer’s instructions. Each qPCR reaction included the mixed cDNA, PowerUp™ SYBR™ Green Master Mix (Applied Biosystems), primers, and water, and was conducted in the QuantStudio™ 6 Real-Time PCR machine (Applied Biosystems, Foster City, CA, USA). The sequence of the following primers were listed in Table S2: neurofilament heavy chain (NEFH), neurofilament medium chain (NEFM), galactosylceramidase (GALC), glial fibrillary acidic protein (GFAP), paired box 6 (PAX6), nestin (NES), NADH: ubiquinone oxidoreductase subunit A11 (NDUFA11), mitochondrial serine / threonine protein phosphatase (PGAM5), dopamine receptor D1 (DRD1), APC regulator of WNT signaling pathway 2 (APC2), Smith-Magenis syndrome chromosome region candidate 5 (SMCR5), and DPPA2 upstream binding RNA (DUBR). The relative gene expression fold change was calculated with the mean cycle threshold (Ct) of PCR triplicates for each gene using the 2−ΔΔCtformula and further normalized against glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and actin beta (ACTB) endogenous controls.Atty. Dkt. No.650053.01228

[0130] Congruence of the microarray and bioinformatic analyses in organoid and serum studies

[0131] To ensure consistency across datasets, we applied the following uniform methodologies and quality control measures for both organoid and serum studies: 1) Microarray Analysis: Identical microarray assays were performed by Arraystar Inc. to evaluate anaesthetic- induced dysregulation of lncRNAs and mRNAs across organoid and serum samples, ensuring comparable data acquisition. 2) Bioinformatic Analysis: Normalization and filtering: Raw mRNA data were normalized using the quantile normalization method in GeneSpring GX v12.1, and low-intensity mRNAs were filtered to ensure data reliability. Data quality assessment: Quality control of microarray data included Scatter and Box Plot analyses for mRNAs and lncRNAs (Figures 2B-C; Figures 10A-D), confirming data integrity and consistency. Differential expression screening: Differentially expressed mRNAs were identified using Volcano Plot filtering (fold change ≥ 1.2, p-value ≤ 0.05). Hierarchical clustering and pathway analysis: Hierarchical clustering of differentially expressed mRNAs and pathway analyses (using IPA, mitoXplorer, SynGO, Metascape, KEGG, and Cytoscape analysis) provided insights into key pathways affected by anaesthesia exposure. This consistent workflow demonstrated congruence between the organoid and serum analyses, identifying anaesthetic- induced overlapping dysregulated gene profiles and pathways.

[0132] In the foregoing description, it will be readily apparent to one skilled in the art that varying substitutions and modifications may be made to the invention disclosed herein without departing from the scope and spirit of the invention. The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention. Thus, it should be understood that although the present invention has been illustrated by specific embodiments and optional features, modification and / or variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention.

[0133] Citations to a number of patent and non-patent references may be made herein. The cited references are incorporated by reference herein in their entireties. In the event that thereAtty. Dkt. No.650053.01228 is an inconsistency between a definition of a term in the specification as compared to a definition of the term in a cited reference, the term should be interpreted based on the definition in the specification.

Claims

Atty. Dkt. No.650053.01228 CLAIMS 1. A method comprising detecting a level of one or more markers selected from brain- derived neurotrophic factor (BDNF), neuron specific enolase (NSE), S100 Calcium Binding Protein B (S100B), Rho GTPase Activating Protein 8 (ARHGAP8), BCL2-associated athanogene 1 (BAG1), Fucosyltransferase 11 (FUT11), Interleukin 17 Receptor C (IL17RC), Leucine Rich Repeat Containing 36 (LRRC36), Myeloperoxidase (MPO), alpha- actinin-1 (ACTN1), Protein Tyrosine Phosphatase Receptor Type N2 (PTPRN2), Creatine Kinase, Mitochondrial 1B (CKMT1B), Serine Incorporator 1 (SERINC1), BAG family molecular chaperone regulator 3 (BAG3), Doublecortin Domain Containing 2C (DCDC2C), Family With Sequence Similarity 120 Member A (FAM120A), GTPase Activating Protein And VPS9 Domains 1 (GAPVD1), Histone acetyltransferase KAT2A (KAT2A), Nucleoporin 188 (NUP188), Rhomboid Domain Containing 3 (RHBDD3), telomere elongation helicase 1 (RTEL1), RWD Domain Containing 4 (RWDD4), Sodium Channel Epithelial 1 Subunit Delta (SCNN1D), SHC Adaptor Protein 2 (SHC2), CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1 in a sample from a subject.

2. The method of claim 1, wherein detecting a level comprises detecting a level of at least one of BDNF, NSE, S100B, or CKMT1B in a sample from the subject.

3. The method of claim 2, wherein the one or more markers are detected by enzyme linked immunosorbent assay (ELISA).

4. The method of claim 1, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1.

5. The method of claim 1, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, or SHC2.Atty. Dkt. No.650053.01228 6. The method of claim 1, wherein the one or more markers are selected from CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1.

7. The method of claim 1, wherein the one or more markers are selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, PTPRN2, CKMT1B, SERINC1, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, or XLOC_004632 and the level of the one or more markers are reduced as compared to a level of the one or more markers in a reference sample.

8. The method of claim 1, wherein the one or more markers are selected from ACTN1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, G038394, LACTB2-AS1, LINC00685, and LIPE-AS1 and the level of the one or more markers are increased as compared to a level of the one or more markers in a reference sample.

9. The method of claim 1, wherein the level of the one or more markers is detected by microarray, quantitative reverse transcription PCR (qRT-PCR), next generation sequencing, or northern blot.

10. The method of claim 1, wherein the subject has been exposed to general anesthetic for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more.

11. A method of detecting anesthetic-induced neurotoxicity (AIN) in a subject, the method comprising detecting a level of one or more markers selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1 in a sample from a subject.Atty. Dkt. No.650053.01228 12. The method of claim 11, wherein the level of the one or more markers are altered as compared to a level of the one or more markers in a reference sample, thereby detecting AIN.

13. The method of claim 12, wherein the one or more markers comprises BDNFand the level of the one or more markers are decreased as compared to the reference sample.

14. The method of claim 12, wherein detecting a level comprises detecting a level of NSE or S100B in a sample from the subject and the level of NSE or S100B is increased as compared to the reference sample.

15. The method of claim 14, wherein the level of the one or more markers is detected by enzyme linked immunosorbent assay (ELISA).

16. The method of claim 11, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1.

17. The method of claim 11, wherein the one or more markers are selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, or SHC2.

18. The method of claim 11, wherein the one or more markers are selected from CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1.

19. The method of claim 12, wherein the markers are selected from BDNF, NSE, S100B, ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, PTPRN2, CKMT1B, SERINC1, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, or XLOC_004632 and the level of the one or more markers are reduced as compared to the level of the one or more markers in the reference sample.Atty. Dkt. No.650053.01228 20. The method of claim 12, wherein the markers are selected from ACTN1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1 and the level of the one or more markers are increased as compared to the level of the one or more markers in the reference sample.

21. The method of claim 11, wherein the level of the one or more markers is detected by microarray, quantitative reverse transcription PCR (qRT-PCR), next generation sequencing, or northern blot.

22. The method of claim 11, wherein the subject has been exposed to general anesthetic for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more.

23. The method of any one of claims 1-22, wherein the subject is a pediatric subject, optionally, wherein the subject is less than 4, less than 3, less than 2, or less than 1 year of age.

24. A kit, system, or platform comprising reagents for detecting one or more markers selected from ARHGAP8, BAG1, FUT11, IL17RC, LRRC36, MPO, ACTN1, PTPRN2, CKMT1B, SERINC1, BAG3, DCDC2C, FAM120A, GAPVD1, KAT2A, NUP188, RHBDD3, RTEL1, RWDD4, SCNN1D, SHC2, CCDC144NL-AS1, DHRS4-AS1, G061722, HRAT5, LINC00408, LINC00652, LINC01023, XLOC_004632, G038394, LACTB2-AS1, LINC00685, or LIPE-AS1.

25. The kit, system, or platform of claim 24, wherein the reagents comprise nucleotide probes for detecting the presence of the one or more markers in a sample from a subject.

26. The kit, system, or platform of claim 24, wherein the sample is a sample of serum, blood, or other tissue.

27. The kit, system, or platform of claim 24, wherein the subject is suffering from AIDN or is suspected of suffering from AIDN or wherein the subject has been exposed to anAtty. Dkt. No.650053.01228 anesthetic for greater than 1 hour, greater than 2 hours, greater than 3 hours, greater than 4 hours, greater than 5 hours, greater than 6 hours, greater than 7 hours, greater than 8 hours, greater than 9 hours, greater than 10 hours, greater than 11 hours, greater than 12 hours, about 1 hour to about 12 hours, or more.

Images