Background: Subarachnoid Hemorrhage (SAH) accounts for 2-7% of strokes and has high mortality and morbidity. We sought to identify peripheral blood transcriptome changes in the acute SAH phase that associated with 90-day outcome, as measured by the modified Rankin Scale (mRS), to gain insights about potential mechanisms contributing to long term outcome. Methods: We sequenced the peripheral blood transcriptome of SAH patients within 3 days post ictus and stratified the patients into patients with Good (mRS≤2, n=37) and Poor (mRS≥3, n=23) outcomes at 90-day follow up. We generated the co-expression networks using the Weighted Gene Co-Expression Network Analysis (WGCNA) package to determine modules (groups of co-expressed genes) associated with 90-day SAH outcome. The outcome-significant modules (p<0.05) were further analyzed for their biological relevance using pathway analysis. Results: We identified two outcome-significant modules, the Pink module and the Purple module. The Pink module was enriched (corrected p<0.05) in Monocyte- and Granulocyte-specific genes, while the Purple module and its hubs were enriched in Monocyte-specific genes. The hub genes are the most interconnected genes in each module, which are therefore potential master regulators. The Pink module was enriched (corrected p<0.05) in Neutrophil Degranulation, an inflammatory pathway which was predicted to be activated in patients with worse outcome, in Histone Modification Signaling, which is involved in epigenetic control of gene expression, and in SUMOylation of transcriptional cofactors, which confers post-transcriptional modifications of these cofactors. The Purple module was enriched in 45 canonical biological pathways, including numerous inflammatory pathways predicted to be activated in SAH patients with worse outcomes, such as Neutrophil Degranulation, Phagosome Formation, IL-8 Signaling, and Macrophage Classical Activation Signaling. Conclusions: Early peripheral blood changes in the transcriptome architecture following SAH are associated with long-term outcome. The identified genes and networks may guide the search for potential biomarkers of outcome and novel treatment targets.

Prenatal exposure to a heightened maternal immune response, such as that triggered by viral infection in the mother, can alter fetal brain development and increase risk of neurodevelopmental disorders in offspring, including autism (ASD) and schizophrenia. However, the cellular and molecular mechanisms linking early inflammatory signals to long-term changes in brain function remain unclear. While rodent models of maternal immune activation (MIA) display brain and behavioral disruptions, their translational relevance to humans is limited. To address this gap, we utilized a nonhuman primate (NHP) MIA model to examine how transient maternal immune responses in early gestation alter gene expression in the amygdala—a brain region essential for socioemotional behavior and implicated many neurodevelopmental disorders. Pregnant macaques were administered the viral mimic Poly(I:C) during the late first trimester, and amygdala samples were collected from 4-year-old male offspring for single-nucleus RNA sequencing (>71,000 nuclei). We identified 2768 unique differentially expressed genes (DEGs), concentrated in excitatory and inhibitory neurons of the lateral nucleus and microglia of the central nucleus. These DEGs converge on synaptic structure, neurotransmission, and neuroimmune signaling—core processes in circuit assembly and behavioral regulation. MIA-associated DEGs significantly overlap with high-confidence ASD- and psychosis-risk gene sets, directly linking prenatal immune events to human disease pathways. This study provides the first region- and cell-type-specific evidence in a primate model that transient prenatal maternal immune responses lead to lasting transcriptomic dysregulation. These findings reveal how early immune insults may alter neurodevelopment and offer a translational framework for identifying molecular targets for early intervention.

BackgroundPrevious clinical, radiological and machine learning studies have predicted 90-day outcomes following subarachnoid hemorrhage (SAH). The present study was designed to determine whether early changes in mRNA expression of immune, clotting and other genes expressed in peripheral blood can predict patient outcomes at 90 days after SAH and possibly provide insights into the molecular factors that promote good versus poor outcomes.MethodsPeripheral blood was drawn after SAH and from vascular risk factor controls (VRFC) and RNAseq performed to measure mRNA expression. A mixed effects regression model identified potential predictors and machine learning algorithms derived the best predictors of 90-day SAH outcome as measured by modified Rankin Score (mRS) for a derivation cohort (23 Poor and 37 Good SAH Outcome patients, 48 VRFC). The model trained on the derivation cohort was then used to predict 90-day SAH outcome in an independent validation cohort (15 Poor and 23 Good SAH Outcome). Enrichment analyses for cell-type specific genes, canonical pathways, and biological processes were performed for the predictor genes.ResultsThe mixed effects regression on the derivation cohort yielded 94 genes from which 20 were selected through feature reduction. Machine learning algorithms were optimized to generate a model that predicted SAH 90-day outcome with AUC = 0.85, sensitivity = 87%, and specificity = 84% on cross-validation. Application of this model to the independent validation cohort yielded AUC = 0.84, sensitivity = 93%, and specificity = 74%. The 20 predictors were significantly enriched in genes from neutrophils and erythroblasts and in nine pathways including the Unfolded Protein Response, Neutrophil Degranulation, and Neutrophil Extracellular Trap Signaling.ConclusionsThis discovery study demonstrates that a small panel of 20 genes expressed in peripheral blood after SAH has the potential for predicting 90-day outcomes following SAH. It also shows that neutrophils may be important drivers of SAH outcomes and could represent therapeutic targets.

Objective: Theories of amygdala function are central to our understanding of psychiatric and neurodevelopmental disorders. However, limited knowledge of the molecular and cellular composition of the amygdala impedes translational research aimed at developing new treatments and interventions. The aim of this study was to characterize and compare the composition of amygdala cells to help bridge the gap between preclinical models and human psychiatric and neurodevelopmental disorders. Methods: Tissue was dissected from multiple amygdala subnuclei in both humans (N=3, male) and rhesus macaques (N=3, male). Single-nucleus RNA sequencing was performed to characterize the transcriptomes of individual nuclei. Results: The results reveal substantial heterogeneity between regions, even when restricted to inhibitory or excitatory neurons. Consistent with previous work, the data highlight the complexities of individual marker genes for uniquelytargeting specific celltypes. Cross-species analyses suggest that the rhesus monkey model is well-suited to understanding the human amygdala, but also identify limitations. For example, a cell cluster in the ventral lateral nucleus of the amygdala (vLa) is enriched in humans relative to rhesus macaques. Additionally, the data describe specific cell clusters with relative enrichment of disorder-related genes. These analyses point to the human-enriched vLa cell cluster as relevant to autism spectrum disorder, potentially highlighting a vulnerability to neurodevelopmental disorders that has emerged in recent primate evolution. Further, a cluster of cells expressing markers for intercalated cells is enriched for genes reported in human genome-wide association studies of neuroticism, anxiety disorders, and depressive disorders. Conclusions: Together, these findings shed light on the composition of the amygdala and identify specific cell types that can be prioritized in basic science research to better understand human psychopathology and guide the development of potential treatments.

Peripheral blood gene expression profiles can distinguish ischemic stroke from intracerebral hemorrhage and controls. However, it can be difficult to clinically distinguish “mimics” of transient ischemic attacks (TIA) and minor strokes from true TIAs and minor strokes. Even with imaging this can be a challenging differential diagnosis in the ED and other acute settings. Hence, there is a need for defining a molecular profile from blood that could guide triage of TIA mimics to reduce ED burden. This multi-site project collected peripheral blood from the participants and generated gene-level data from RNA sequencing. The cohort was composed of patients with a) TIA mimic presentation (n= 142 TIA mimics: an acute onset of neurological symptoms lasting <24h, that can be explained by some identifiable process other than cerebral ischemia including migraine, seizure, peripheral vestibular disease, brain tumors, syncope, root or peripheral nerve disease, and others); b) patients with transient ischemic attacks (n= 181 TIA: acute onset of neurological symptoms and signs that last <24h with a likely underlying cause of either large vessel atherosclerosis or cardioembolic origin but with a negative brain DWI-MRI); c) controls (n= 172 VRFC: no acute brain event, usually with one or more vascular risk factors including diabetes, hypertension or hypercholesterolemia). Differential expression (DE) analyses (fold change >

OBJECTIVE:Approximately half of ischemic strokes (IS) in cancer patients are cryptogenic, with many presumed cardioembolic. We evaluated whether there were specific miRNA and mRNA transcriptome architectures in peripheral blood of IS patients with and without comorbid cancer, and between cardioembolic versus noncardioembolic IS etiologies in comorbid cancer. METHODS:We studied patients with cancer and IS (CS; n = 42), stroke only (SO; n = 41), and cancer only (n = 28), and vascular risk factor-matched controls (n = 30). mRNA-Seq and miRNA-Seq data, analyzed with linear regression models, identified differentially expressed genes in CS versus SO and in cardioembolic versus noncardioembolic CS, and miRNA-mRNA regulatory pairs. Network-level analyses identified stroke etiology-specific responses in CS. RESULTS:A total of 2,085 mRNAs and 31 miRNAs were differentially expressed between CS and SO. In CS, 122 and 35 miRNA-mRNA regulatory pairs, and 5 and 3 coexpressed gene modules, were associated with cardioembolic and noncardioembolic CS, respectively. Complement, growth factor, and immune/inflammatory pathways showed differences between IS etiologies in CS. A 15-gene biomarker panel assembled from a derivation cohort (n = 50) correctly classified 81% of CS and 71% of SO participants in a validation cohort (n = 33). Another 15-gene panel correctly identified etiologies for 13 of 13 CS-cardioembolic and 11 of 11 CS-noncardioembolic participants upon cross-validation; 11 of 16 CS-cryptogenic participants were predicted cardioembolic. INTERPRETATION:We discovered unique mRNA and miRNA transcriptome architecture in CS and SO, and in CS with different IS etiologies. Cardioembolic and noncardioembolic etiologies in CS showed unique coexpression networks and potential master regulators. These may help distinguish CS from SO and identify IS etiology in cryptogenic CS patients. ANN NEUROL 2024;96:565-581.

Autism spectrum disorder (ASD) is a highly heterogeneous disorder, yet transcriptomic profiling of bulk brain tissue has identified substantial convergence among dysregulated genes and pathways in ASD. However, this approach lacks cell-specific resolution. We performed comprehensive transcriptomic analyses on bulk tissue and laser-capture microdissected (LCM) neurons from 59 postmortem human brains (27 ASD and 32 controls) in the superior temporal gyrus (STG) of individuals ranging from 2 to 73 years of age. In bulk tissue, synaptic signaling, heat shock protein-related pathways, and RNA splicing were significantly altered in ASD. There was age-dependent dysregulation of genes involved in gamma aminobutyric acid (GABA) (GAD1 and GAD2) and glutamate (SLC38A1) signaling pathways. In LCM neurons, AP-1-mediated neuroinflammation and insulin/IGF-1 signaling pathways were upregulated in ASD, while mitochondrial function, ribosome, and spliceosome components were downregulated. GABA synthesizing enzymes GAD1 and GAD2 were both downregulated in ASD neurons. Mechanistic modeling suggested a direct link between inflammation and ASD in neurons, and prioritized inflammation-associated genes for future study. Alterations in small nucleolar RNAs (snoRNAs) associated with splicing events suggested interplay between snoRNA dysregulation and splicing disruption in neurons of individuals with ASD. Our findings supported the fundamental hypothesis of altered neuronal communication in ASD, demonstrated that inflammation was elevated at least in part in ASD neurons, and may reveal windows of opportunity for biotherapeutics to target the trajectory of gene expression and clinical manifestation of ASD throughout the human lifespan.

Gene expression changes in peripheral leukocytes display distinctive profiles after intracerebral hemorrhage (ICH) and ischemic stroke (IS), differentiating both conditions at the molecular level. The breadth of data produced by high-throughput transcriptomic analyses can identify groups of genes and main gene expression drivers that have meaningful functional associations with the disease. This can help prioritize the investigation of key genes for diagnosis and treatment. Thus, we performed whole transcriptome analyses on ICH and IS samples and constructed gene networks from a genome-wide perspective. RNA-seq was performed on peripheral blood (WB) and isolated monocytes (MON) and neutrophils (NEU) (n=6 ICH, n=33 IS and n=9 vascular risk factors control (VRFC) subjects). Gene expression results were used to construct separate co-expression networks for all datasets analyzed (ICH + VRFCs, and IS + VRFCs, for MON, NEU and WB) using Weighted Gene Co-expression Network Analysis. Modules of genes significantly associated with ICH in the ICH + VRFCs network, and with IS in the IS + VRFCs network, were identified. The most highly interconnected genes in each of these modules were identified, representing hub genes that are potential master regulators. Functional annotation of the modules and hubs were done using gene ontology. From the significantly associated modules for ICH and IS in all sample types analyzed, there was little overlap in genes between diagnoses (≤2% in MON, ≤21 % in NEU and ≤16% in WB), and no overlap of ICH or IS hub genes from MON and NEU. In WB, ≤2% of the hubs were common to ICH and IS. It is plausible that these potential master regulators drive diagnosis-specific gene expression profiles. ICH hubs were associated with RNA splicing and mRNA processing (MON), cell adhesion (NEU) and NF-κβ signaling (WB). IS hubs were associated with cell migration (MON), T cell chemotaxis (NEU) and transcription factor activity (WB). In addition, most hubs in IS MON were noncoding RNA. The gene networks and their respective hub genes provide novel cell-specific pathophysiological insights and could represent potential key pharmacological targets and biomarkers.

Background This study identified early immune gene responses in peripheral blood associated with 90-day ischemic stroke (IS) outcomes. Methods Peripheral blood samples from the CLEAR trial IS patients at ≤ 3 h, 5 h, and 24 h after stroke were compared to vascular risk factor matched controls. Whole-transcriptome analyses identified genes and networks associated with 90-day IS outcome assessed using the modified Rankin Scale (mRS) and the NIH Stroke Scale (NIHSS). Results The expression of 467, 526, and 571 genes measured at ≤ 3, 5 and 24 h after IS, respectively, were associated with poor 90-day mRS outcome (mRS ≥ 3), while 49, 100 and 35 genes at ≤ 3, 5 and 24 h after IS were associated with good mRS 90-day outcome (mRS ≤ 2). Poor outcomes were associated with up-regulated genes or pathways such as IL-6, IL-7, IL-1, STAT3, S100A12 , acute phase response, P38/MAPK, FGF, TGFA , MMP9 , NF-kB, Toll-like receptor, iNOS, and PI3K/AKT. There were 94 probe sets shared for poor outcomes vs. controls at all three time-points that correlated with 90-day mRS; 13 probe sets were shared for good outcomes vs. controls at all three time-points; and 46 probe sets were shared for poor vs. good outcomes at all three time-points that correlated with 90-day mRS. Weighted Gene Co-Expression Network Analysis (WGCNA) revealed modules significantly associated with 90-day outcome for mRS and NIHSS. Poor outcome modules were enriched with up-regulated neutrophil genes and with down-regulated T cell, B cell and monocyte-specific genes; and good outcome modules were associated with erythroblasts and megakaryocytes. Finally, genes identified by genome-wide association studies (GWAS) to contain significant stroke risk loci or loci associated with stroke outcome including ATP2B , GRK5 , SH3PXD2A , CENPQ , HOXC4, HDAC9, BNC2 , PTPN11 , PIK3CG , CDK6, and PDE4DIP were significantly differentially expressed as a function of stroke outcome in the current study. Conclusions This study suggests the immune response after stroke may impact functional outcomes and that some of the early post-stroke gene expression markers associated with outcome could be useful for predicting outcomes and could be targets for improving outcomes.

BACKGROUND:After ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. Peripheral blood cells display distinctive gene expression signatures post-IS and these transcriptional programs reflect changes in immune responses to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of immune and clotting responses at the molecular and cellular level that are involved in acute brain injury and may assist with time-targeted, cell-specific therapy.METHODS:The transcriptomic profiles from peripheral monocytes, neutrophils, and whole blood from 38 ischemic stroke patients and 18 controls were analyzed with RNA-seq as a function of time and etiology after stroke. Differential expression analyses were performed at 0-24 h, 24-48 h, and >48 h following stroke.RESULTS:Unique patterns of temporal gene expression and pathways were distinguished for monocytes, neutrophils, and whole blood with enrichment of interleukin signaling pathways for different time points and stroke etiologies. Compared to control subjects, gene expression was generally upregulated in neutrophils and generally downregulated in monocytes over all times for cardioembolic, large vessel, and small vessel strokes. Self-organizing maps identified gene clusters with similar trajectories of gene expression over time for different stroke causes and sample types. Weighted Gene Co-expression Network Analyses identified modules of co-expressed genes that significantly varied with time after stroke and included hub genes of immunoglobulin genes in whole blood.CONCLUSIONS:Altogether, the identified genes and pathways are critical for understanding how the immune and clotting systems change over time after stroke. This study identifies potential time- and cell-specific biomarkers and treatment targets.

MicroRNA (miRNA) expression is altered following ischemic stroke. Advances in RNA sequencing and bioinformatic tools allow study of isomiRs, isoforms of miRNA, which can have altered regulatory actions from canonical parent miRNA due to base modifications within the molecule or on the flanking regions. Here, we characterize isomiRs in the blood of ischemic stroke patients compared to vascular risk factor controls (VRFCs) and elucidate diversity of the post-stroke miRNA environment. Total RNA was isolated from peripheral blood of 47 ischemic stroke patients and 31 VRFCs using PAXgene protocol. Small RNA libraries were prepared using QIAseq miRNA Library Kit and sequenced to 14±2 M 1x75 bp reads. Raw sequence reads were trimmed, de-duplicated, and profiled using isomiRmap , which separates isomiRs from canonical miRNA sequences based on 3’ and 5’ miRNA modifications. Analysis of differentially expressed isomiRs was performed with DESeq2. A total of 74,562 unique isomiRs were identified, the majority expressed at very low level. Filtering for low abundance left 2,133 isomiRs (from 335 canonical miRNA) expressed in all subjects. Of these, 505 isomiRs (from 129 canonical miRNA) were differentially expressed (LFC > |0.5|, p adj < 0.05) between stroke and VRFCs. These isomiRs represent significant elevations in 3’ modifications (68.3% of DE isomiRs), 5’ modifications (20.2%) and non-template additions (34.3%). miRNA previously implicated in stroke had diverse isomiR profiles including cases where all isomiRs within a miRNA group were differentially expressed (e.g. let-7i) and cases where multiple isomiRs were present but not differentially expressed (e.g. miR-363). Four of 28 differentially expressed let-7i isomiRs have changes to the seed region that interacts with mRNA. Thus, miRNA-mRNA interactions distinct from the canonical let-7i seed may exist and play an altered role in stroke pathology and neuroinflammation. Analysis of small noncoding RNA sensitive to base-specific variations detects many differentially expressed isomiRs and highlights the complexity of the post-stroke miRNA environment. Further study of these isomiRs within mRNA regulatory networks will deepen our understanding of stroke related neuroinflammation and neural repair.

The amygdala is involved in emotion processing and has been implicated in varied psychiatric disorders, from anxiety and depression to autism and schizophrenia. We sought to characterize and identify similarities and differences between cells of human and macaque amygdala subnuclei with relevant roles in these disorders.

Investigating the short and long-term signaling mechanisms via small extracellular vesicles (sEVs) in peripheral blood following human Ischemic Stroke (IS) and Intracerebral Hemorrhage (ICH) is of great interest. The sEV’s cargo can induce distant responses which can be used to derive potential novel therapeutic targets and biomarkers to differentiate the two brain pathologies. Thus, we sequenced the miRNA cargo derived from peripheral blood sEVs in IS (n=3), ICH (n=3), and Vascular Risk Factor-matched Control (VRFC; n=3) subjects. Subjects were divided into contrast groups (IS vs VRFC, ICH vs VRFC, ICH vs IS), and log2 transformed expression underwent Kruskal-Wallis tests to identify differentially expressed (DE; p<0.05) miRNAs. We found 55 DE miRNAs in IS vs VRFC, 38 in ICH vs VRFC, and 45 in ICH vs IS ( Fig. 1A ). The combination of these miRNAs differentiated the three groups on Principal Components Analysis ( Fig. 1B ). IS associated miRNA included miR-30a, miR-30b, and miR-144. miR-30a is involved in hematopoietic stem cell self-renewal and can impair B cell differentiation. miR-30b may be an immune suppressor via Notch1. In male mice, miR-144 is protective against atherosclerosis. ICH associated miRNA included miR-195, miR-1-3p, and miR-20b-5p. miR-195 can inhibit the pro-inflammatory roles of macrophages. miR-1-3p is involved in cardiomyocyte development, can target TLR1 (Toll-Like Receptor 1), and may regulate autophagy. miR-20b-5p reduces Amyloid Precursor Protein (APP) mRNA and protein levels; vascular accumulation of APP is one cause of Lobar ICH. We show differential expression of sEV-derived miRNAs in peripheral blood of human IS and ICH patients that are involved in relevant signaling processes. sEV cargo profiles pose a largely underexplored intercellular signaling mechanism in IS and ICH with the potential to better characterize long distance signaling from injured brain to peripheral blood leukocytes in these brain disorders.

Objective: Identifying the molecular underpinnings associated with long-term functional outcome after ischemic stroke (IS) could guide search for treatments for improved outcome. Thus, we identified early peripheral immune gene expression (GE) responses associated with 90-day IS outcome, as measured by the Barthel Index (BI). Methods: RNA from 108 samples from three peripheral blood draws (≤3h – before thrombolytic treatment; 5h and 24h - post-treatment) from 36 CLEAR-trial subjects was analyzed on Affymetrix arrays. We performed Analysis of Covariance accounting for treatment (tPA or tPA+eptifibatide), hypercholesterolemia, hypertension, diabetes, age, sex and BI. Genes whose partial correlation with BI was significant ( P <0.005) were identified. Results: There were 206, 865, and 209 genes that significantly correlated with 90-day BI at ≤3h, 5h and 24h post ictus , respectively. The gene lists at all three time-points were enriched in B-cell specific genes (hypergeometric probability p<0.05), while the 5h gene list was also enriched in neutrophil-specific genes, and the 24h gene list was also enriched in monocyte-specific genes. B Cell Receptor Signaling pathway was predicted activated in subjects with better 90-day outcome at the ≤3h time-point, while ICOS-ICOSL Signaling in T Helper Cells and Role of NFAT in Regulation of the Immune Response were predicted activated at the 24h time-point.Immune-related pathways were enriched at three time-points including B cell-related, IL-7, and T cell signaling pathways. Apoptosis was suppressed in patients with better 90-day outcome at 3h and 24h post ictus . Among the genes associated with the 90-day BI were genes important for stroke and repair after stroke, such as KCNG1 , Potassium voltage-gated channel subfamily G member 1, which like other potassium channels could modulate stroke outcome. KCNG1 expression was positively correlated with 90-day BI at ≤3h and 5h. TERML4 , implicated in inflammatory response and human coronary arterial calcification had expression that positively correlated with BI at all three time-points. Conclusion: The findings expand our understanding of the early molecular biology associated with long-term stroke outcome and may serve as potential targets to improve outcome.

The peripheral immune system response to Intracerebral Hemorrhage (ICH) may differ with ICH in different brain locations. Thus, we investigated peripheral blood mRNA expression of Deep ICH, Lobar ICH, and vascular risk factor-matched control subjects (n = 59). Deep ICH subjects usually had hypertension. Some Lobar ICH subjects had cerebral amyloid angiopathy (CAA). Genes and gene networks in Deep ICH and Lobar ICH were compared to controls. We found 774 differentially expressed genes (DEGs) and 2 co-expressed gene modules associated with Deep ICH, and 441 DEGs and 5 modules associated with Lobar ICH. Pathway enrichment showed some common immune/inflammatory responses between locations including Autophagy, T Cell Receptor, Inflammasome, and Neuroinflammation Signaling. Th2, Interferon, GP6, and BEX2 Signaling were unique to Deep ICH. Necroptosis Signaling, Protein Ubiquitination, Amyloid Processing, and various RNA Processing terms were unique to Lobar ICH. Finding amyloid processing pathways in blood of Lobar ICH patients suggests peripheral immune cells may participate in processes leading to perivascular/vascular amyloid in CAA vessels and/or are involved in its removal. This study identifies distinct peripheral blood transcriptome architectures in Deep and Lobar ICH, emphasizes the need for considering location in ICH studies/clinical trials, and presents potential location-specific treatment targets.