Csf1r-mediated depletion of midbrain microglia prevents dopaminergic neuron loss during chronic colitis

Csf1r-mediated depletion of midbrain microglia prevents dopaminergic neuron loss during chronic colitis | Research Square Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Csf1r-mediated depletion of midbrain microglia prevents dopaminergic neuron loss during chronic colitis Rebecca Katharina Kutscherauer, Marie Andert, Iris Stolzer, Emely Elisa Neumaier, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8976432/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jun, 2026 Read the published version in Journal of Neuroinflammation → Version 1 posted 15 You are reading this latest preprint version Abstract Inflammatory bowel disease (IBD) predisposes to neuropsychiatric comorbidity and increases the risk of Parkinson’s Disease (PD). Although the gut-immune-brain axis was proposed as a link between IBD and PD and a driver of PD immunopathogenesis, the regional pattern and single-cell landscape of the brain immune response during colitis and its contribution to PD pathology remain poorly defined. Here, we observe a loss of dopaminergic neurons and synuclein pathology in the substantia nigra pars compacta of adult mice with chronic colitis. By confocal microscopy and integrated multi-omics, we reveal a complex midbrain-centered immune response to chronic colitis. Single-cell mapping of the midbrain immune landscape showed an inflammatory shift of microglial clusters including an expansion of interferon-response microglia, CD8 + T cell extravasation, and increased numbers of vessel-associated neutrophils. Selective myeloid cell depletion using a colony stimulating factor 1 receptor (Csf1r) inhibitor after colitis onset reduced midbrain microglia by 67% and led to a complete rescue of dopaminergic neuron loss, without affecting mucosal pathology or T cell and neutrophil migration to the midbrain. Collectively, within the complex midbrain immune response to chronic colitis, we demonstrate a causal role of Csf1r-dependent microglia for dopaminergic neurodegeneration. Thus, Csf1r inhibition in IBD may not locally ameliorate colitis, but provide neuroprotection to dopaminergic neurons. These results reveal a novel cellular link between chronic gut-derived peripheral inflammation and midbrain vulnerability and thereby substantially enhance our understanding of the risk for PD related to the gut-immune-brain axis. Microglia colony-stimulating factor 1 receptor gut-immune-brain axis inflammatory bowel disease Parkinson’s Disease Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The gut-immune-brain axis describes a vivid immune crosstalk between the gut and the brain and has been proposed to play a fundamental role in numerous brain disorders [ 1 – 3 ]. Importantly, inflammatory bowel disease (IBD) is linked to neuroinflammation and neuropsychiatric comorbidity [ 4 ], and specifically associated with Parkinson’s Disease (PD) by both genetic and epidemiological evidence [ 5 ]. Vice versa, PD may be driven by early microbial and inflammatory stimuli originating from the gut [ 6 , 7 ]. However, underlying cellular mechanisms linking chronic intestinal inflammation to PD-related neuropathology are not fully understood. A stepwise cascade was proposed, initialized by propagation of microbial and inflammatory cues across a leaky gut vascular barrier leading to systemic inflammation [ 4 , 8 ]. This, in turn, can drive neuroinflammation, characterized by the infiltration of blood-derived immune cells into the brain parenchyma and the activation of brain-resident microglia, which are highly responsive to gut-derived stimuli [ 9 , 10 ]. Yet, whether and how gut-induced neuroinflammation can drive neurodegeneration remains to be elucidated. While rodent models of IBD, particularly based on dextran sulfate sodium (DSS) colitis, have demonstrated neuroinflammation [ 11 – 13 ] and suggested a loss of dopaminergic neurons and synuclein pathology in the midbrain [ 12 ], a cellular link between these findings remains elusive. Importantly, the precise cellular composition of the midbrain immune response to chronic colitis has not been resolved yet. In this study, we hypothesize that adult-onset relapsing-remitting experimental colitis drives PD-related neurodegeneration dependent on microglia. We show that chronic DSS colitis results in a systemic inflammation propagating into the brain, where microglial activation is present in the midbrain, but not the striatum, hippocampus, and cortex. This corresponds to an inflammatory signature in bulk tissue RNA-sequencing and proteomics of the midbrain compared to the striatum. The mapping of the midbrain immune cell response to chronic DSS colitis at the single-cell level reveals an expansion of inflammatory microglia clusters including interferon response microglia, parenchymal CD8 + T cell infiltration, and vessel-associated neutrophils. Within this complex midbrain immune response, integrated multi-omic analysis predominantly links microglial clusters to alterations along the gut-immune-midbrain axis during colitis. Finally, we show that myeloid cell targeting using the colony-stimulating factor 1 receptor (Csf1r) antagonist PLX5622 after the first cycle of chronic DSS colitis leads to a significantly reduced number of microglia and prevents the observed inflammation-driven loss of dopaminergic neurons in the substantia nigra pars compacta. Of note, Csf1r inhibition does not ameliorate mucosal pathology or prevent the migration of T cells and neutrophils to the midbrain, indicating a microglia-dependent neuroprotective effect. Collectively, we provide an integrated multi-omic characterization and single-cell resolution of the neuroinflammatory midbrain response to chronic colitis. Within a complex neuroinflammatory pattern, we identify Csf1r-dependent microglia as a treatment target to protect dopaminergic neurons in chronic gut-derived inflammation, with potential relevance for both IBD and PD. Materials and methods Animals Experiments were performed with C57BL/6J mice (Charles River Laboratories, Sulzfeld, Germany; The Jackson Laboratory, Bar Harbor, ME, USA) and Hexb tdTomato mice [ 14 ]. Mice were housed in individually ventilated cages under conventional animal housing conditions (12-hour light/dark cycle, 22°C) and were provided sterile water and standard laboratory chow ad libitum . All animal experiments were approved by the Government of Lower Franconia, Würzburg, Germany (RUF-55.2.2-2532-2-1638) and were performed in accordance to the EU Directive on the Protection of Animals Used for Scientific Purposes (2010/63/EU) in the preclinical experimental animal center in the Franz-Penzoldt-Center in Erlangen, Germany. Colitis induction and scoring Starting at an age of 20 weeks, chronic colitis was induced in three cycles, each consisting of ad libitum provision of 2% (w/v) dextran sodium sulfate (DSS; colitis grade, 36–50 kDa, MP Biomedicals) in drinking water for 5 days followed by normal drinking water for 10 days. Control mice received normal drinking water throughout the study period. Disease severity was monitored on a daily basis by scoring changes in bodyweight, grooming and nesting behavior as well as clinical symptoms, which were combined to yield the disease associated index. On day 36 of 45, colonoscopy was performed under continuous anaesthesia with 2% isofluorane and by using a 1.9 mm telescope (Karl Storz, Tuttlingen, Germany) connected to an air pump. Colitis scoring was performed according to the modified murine endoscopic index of colitis severity described by Becker C, Fantini MC, Wirtz S, Nikolaev A, Kiesslich R, Lehr HA, Galle PR and Neurath MF [ 15 ]. Additionally, colitis severity was scored by histopathological analysis of hematoxylin and eosin (H&E) stained colon sections as previously described [ 16 ]. The sum scores for (a) intestinal integrity (0–3), (b) extent of mucosal inflammation (0–3), and (c) submucosal pathological changes (0–3) of each mouse were taken as an indicator for disease severity. PLX5622 treatment Microglia were depleted by feeding 1200 ppm PLX5622 supplemented chow (Hycultec, Beutelsbach, Germany; ssniff Spezialdiäten, Soest, Germany) while control mice were fed ingredient-matched PLX5622-free placebo chow starting at day 11 for 35 days. Mice were randomly distributed into four groups: (1) control mice receiving placebo chow, (2) control mice receiving PLX5622-supplemented chow, (3) chronic DSS colitis mice receiving placebo chow, and (4) chronic DSS colitis mice receiving PLX5622-supplemented chow. Tissue collection Mice were anesthetized with 2% isofluorane and blood was collected by cardiac puncture, followed by immediate transcardiac perfusion using ice-cold phosphate buffered saline (PBS). The colon and intestine were flushed with PBS to remove content and samples from the distal colon and ileum, liver, and lung were either snap-frozen or fixed in 4.5% formaldehyde and embedded in paraffin. The brain was isolated and hemispheres or regions were dissected. For bulk and single-cell RNA-sequencing experiments, the choroid plexus from the lateral and fourth ventricles was removed before dissecting the midbrain and striatum to prevent sample contamination as previously reported [ 17 ]. Isolated midbrain and striatum tissue from contralateral brain hemispheres were used for proteome and transcriptome analyses. Serum multiplex ELISA Serum cytokine levels were measured using the V-PLEX Mouse Cytokine 19-Plex Kit (Meso Scale Diagnostics, Rockville, MD, USA) according to the manufacturer’s protocol. Briefly, serum was prepared by centrifugation (2,000 g, 10 min, 4°C) of blood collected by cardiac puncture, and was snap-frozen in liquid nitrogen and stored at -80°C until further analysis. Samples were measured in duplicates at a MESO QuickPlex SQ 120MM (Meso Scale Diagnostics) and analyzed with the software MSD DISCOVERY WORKBENCH® (v4.0, Meso Scale Diagnostics). Flow cytometry Immune cells were isolated from PBS-perfused whole brain tissue as described by Masuda T, Amann L, Sankowski R, Staszewski O, Lenz M, d´Errico P, Snaidero N, Costa Jordão MJ, Böttcher C, Kierdorf K, Jung S, Priller J, Misgeld T, Vlachos A, Meyer-Luehmann M, Knobeloch K-P and Prinz M [ 14 ] with minor modifications. In brief, one brain hemisphere was manually homogenized in ice-cold Hanks’ balanced salt solution containing 15 mM HEPES buffer and 0.54% glucose using a dounce tissue grinder and filtered through a 70 µm cell strainer before centrifugation (200 g, 5 min, 4°C). Cells were separated in 37% Percoll by gradient centrifugation (800 g, 35 min, 4°C, no break), washed in ice-cold PBS and transferred to a 94-well plate. Single-cell suspensions were stained with LIVE/DEAD™ Aqua Dye (Thermo Fisher Scientific, Waltham, MA, USA; 1:1,000 in PBS) for 10 min at 4°C, washed and stained with fluorophore-conjugated surface antibodies diluted in PBS for 30 min at 4°C. Data were acquired on a Cytek Northern Lights (Cytek Biosciences, Fremont, CA, USA) using the SpectroFlo software (v3.3.0, Cytek Biosciences) and analyzed using OMIQ (Dotmatics, Boston, MA, USA). Detailed information on anti-mouse antibodies used for flow cytometry is provided in Table S1. Immunofluorescence stainings Free-floating immunofluorescence staining was performed as previously described [ 16 ]. Brain hemispheres and colon tissue were fixed in 4% paraformaldehyde and rehydrated in 30% sucrose solution, followed by serially cutting into 20 µm (brain) sagittal or coronal sections or 40 µm (colon) sections on a Leica SM2010 R sliding microtome (Leica Biosystems, Nussloch, Germany). Antigen retrieval by pre-treatment in citrate buffer (0.1 M citric acid, 0.1 M Tris-sodium citrate in ddH 2 O) for 30 min at 80°C was performed prior to all antibody exposures except for CD68 and phospho-alpha-synuclein (Ser129). Tissue sections were incubated in blocking solution (3% donkey serum, 0.3% Triton™ X-100 in tris-based saline (TBS)) and stained overnight at 4°C with specific primary antibodies (detailed information provided in Table S1). Samples were washed with TBS and counterstained with respective fluorophore-conjugated secondary antibodies (Thermo Fisher Scientific). After washing with TBS, cell nuclei were stained using 4’,6-Diamino-2-phenylindole (DAPI) and tissue slices were mounted with ProLong Gold Antifade Mountant (Thermo Fisher Scientific). Image acquisition and analysis Immunofluorescence-stained sections were imaged using either a laser scanning confocal microscope LSM 780 (Carl Zeiss Microscopy, Jena, Germany) on an inverted Axio Observer with a Plan-Apochromat 20x/0.8 M27, a Plan-Apochromat 40/1.46 Oil DIC M27, or alpha Plan-Apochromat 63x/1.46 Oil Korr M27 objective (Carl Zeiss Microscopy). Maximum intensity projections were generated using the Zeiss Zen 2012 (black edition) software (v8.1.0.484), and cells were counted using the Zeiss Zen 2012 (blue edition) software (v1.1.2.0). All analyses were performed blinded to group allocation. Analysis of microglia activation Microglia activation was assessed based on the morphology and expression of the lysosomal protein CD68 as previously described [ 16 , 18 ]. From each animal, four images were acquired per brain region from 2–3 brain sections under a 40x oil objective (scan mode: plane, stack, z: 20 µm, scaling: 0.5 µm, pixel dwell time: 1.54 µs). Scoring was performed on maximum intensity projections covering a total number of Iba1 + cells (cDSS/control) in the cortex (277/300), hippocampus (223/277), striatum (294/315), and substantia nigra (436/459). Microglia morphology was investigated both by Sholl analysis and analysis of microglial processes from 3D-reconstructed images in Imaris (v7.6.4, Oxford Instruments, Belfast, UK). Quantification of immune cells Microglia (Iba1 + ), neutrophils (Ly6G + ), and T cells (CD3 + ) were quantified from 3–4 images per brain region in 2–3 brain sections per mouse under a 40x oil objective (scan mode: plane, stack, z: 20 µm, scaling: 1.0 µm, pixel dwell time: 1.54 µs). Counterstaining with collagen IV allowed to distinguish CD3 + CD8 + T cells inside vessels (vascular), in the perivascular space (perivascular), and in the brain parenchyma (parenchymal). Ly6G + cells adjacent to collagen IV + basal laminae were considered as vessel-associated neutrophils. Myeloid cells (Iba1 + ) in the colon were quantified in the mucosa, submucosa, and muscularis from 3 tile scan images (2x2) in three colon sections per mouse taken with a 20x objective (scan mode: tile, stack, z: 40 µm, scaling: 2.0 µm, pixel dwell time: 4.10 µs). Counting was performed on maximum intensity projections. Quantification of dopaminergic neurons The total number of dopaminergic neurons in the substantia nigra pars compacta was analyzed from tyrosine hydroxylase (TH) staining on every 12th coronal brain section from each animal. Images were acquired from each brain section covering the total substantia nigra under a 20x objective (scan mode: tile, stack, z: 20 µm, scaling: 1 µm, pixel dwell time: 4.01 µs) and the substantia nigra pars compacta was identified from maximum intensity projections using the Allen Brain Atlas of the mouse brain as reference[ 19 ]. All TH + cells were manually counted, and the number of cells was multiplied by 12 to determine the total number of TH + cells in the substantia nigra pars compacta of one brain hemisphere. Protein extraction and preparation for mass spectrometry Isolated midbrain and striatum tissue from contralateral brain hemispheres were used for proteome and transcriptome analysis. Total protein was isolated from snap frozen tissue by homogenization in 1:6 w/v homogenization buffer (50 mM Tris/HCl, 150 mM NaCl, pH 8.0) supplemented with 1x cOmplete™ EDTA-free Protease Inhibitor Cocktail (Roche Diagnostics, Mannheim, Germany) and mechanical dissociation using a Potter S Homogenizer (800 U/min; Sartorius Stedim Biotech, Göttingen, Germany). Homogenous samples were centrifuged (10,000 g, 10 min, 4°C) and protein concentration was quantified using the Pierce BCA Protein Assay Kit according to the manufacturers protocol (Thermo Fisher Scientific). Colorimetric absorbance was measured at a CLARIOstar PLUS high-performance microplate reader (BMG Labtech, Ortenberg, Germany). Samples were stored at -80°C until mass spectrometric analysis. Mass spectrometry Protein analysis was performed using the Single-Pot Solid-Phase-enhanced Sample Preparation method [ 20 , 21 ]. In brief, 20 µg protein were mixed with Sera-Mag™ SpeedBeads A and B (Cytiva, formerly GE Healthcare Life Sciences, Marlborough, MA, USA) and binding was initiated by adding absolute ethanol. After incubation, beads were washed with 80% ethanol and resuspended in 100 mM ammonium acetate buffer at a Hamilton Microlab Prep automated liquid handling platform (Hamilton Company, Reno, NV, USA) before on-bead digestion with trypsin. Resulting peptides were eluted in 1% formic acid and stored at -20°C until measurement. Samples were measured on an Orbitrap Eclipse Tribrid Mass Spectrometer coupled to an UltiMate 3000 Nano-High-performance liquid chromatography (Thermo Fisher Scientific) via a Nanospray Flex Ion Source equipped with a Sonation column oven and front-end High Field Asymmetric Waveform Ion Mobility Spectrometry interface. Raw files were processed using the ProteoWizard software [ 22 ] and proteins were identified using the data independent acquisition neural network software [ 23 ]. Data was further processed using the software Perseus (v2.0.11) [ 24 ] and visualized using the ggplot2 package built in R [ 25 ]. RNA isolation and reverse transcription-quantitative PCR RNA for reverse transcription-quantitative PCR (RT-qPCR) was isolated from fresh-frozen tissue using the RNeasy Mini Kit (Qiagen, Hilden, Germany) and reversely transcribed using the GoScript™ Reverse Transcription System (Qiagen) according to the manufacturer’s protocols. Gene expression on mRNA level was assessed using the SsoFast™ EvaGreen® Supermix (Bio-Rad, Hercules, CA, USA) according to the manufacturer’s protocol and samples were measured at a LightCycler® 96 System (Roche Diagnostics) and analyzed using the LightCycler® 96 Software (v1.10.1320, Roche Diagnostics). Primer sequences used for RT-qPCR are listed in Table S2. Bulk tissue RNA-sequencing Midbrain and striatum tissue were dissected from PBS-perfused brains on ice and homogenized in QIAzol™ Lysis Reagent. Libraries were prepared as previously described [ 9 ]. In brief, total RNA was isolated using the Direct-zol RNA Microprep Kit (Zymo Research Europe, Heilbronn, Germany) and polyadenylated mRNA was enriched by incubation with Oligo d(T) 25 Magnetic Beads (New England Biolabs, Ipswich, MA, USA). The SuperScript™ III First-Strand Synthesis SuperMix (Thermo Fisher Scientific) was used for first-strand cDNA synthesis and PCR products were purified using RNAClean XP beads according to the manufacturer’s instruction (Beckman Coulter Life Sciences, Indianapolis, IN, USA). The RNA/cDNA double-stranded hybrid was labeled with dNTP/dUTP and dsDNA was purified using Sera-Mag™ SpeedBeads B (GE Healthcare Life Sciences). The purified dsDNA underwent end repair by blunting, A-tailing, and adaptor ligation using NEXTflex™ DNA Barcodes (Revvity, Waltham, MA, USA) as previously described [ 26 ]. The libraries were PCR amplified for 16 cycles, selected for fragments (size 200–500 bp) by gel extraction, and were quantified using a Qubit dsDNA High Sensitivity Assay Kit (Thermo Fisher Scientific), and sequenced on a NovaSeq 6000 for 51 cycles according to the manufacturer’s instructions (Illumina, San Diego, CA, USA). RNA sequencing reads from FASTQ files were mapped to the mus musculus reference genome (mm10) using Spliced Transcript Alignment to a Reference (STAR, v2.7.9a) with default parameters and further analyzed using HOMER (v5.1) as previously described [ 27 , 28 ]. Differential gene expression was assessed using DESeq2 (v1.48.2) and defined by adjusted p-value < 0.05 and log 2 fold change > 0.5 or < -0.5 [ 29 ]. Data normalization and visualization was done using R. Pathway analyses were performed using clusterProfiler (v4.16.0) [ 30 ]. Single-cell RNA-sequencing Immune cells were isolated from midbrain tissue by enzymatic digestion as described by Scheyltjens I, Van Hove H, De Vlaminck K, Kancheva D, Bastos J, Vara-Pérez M, Pombo Antunes AR, Martens L, Scott CL, Van Ginderachter JA, Saeys Y, Guilliams M, Vandamme N and Movahedi K [ 31 ] with minor modifications. The transcriptional inhibitor actinomycin D (ActD) was added in decreasing concentrations to media and buffers to prevent induction of immediate early genes during the dissociation process [ 32 ]. Briefly, midbrain tissue isolated from PBS-perfused brains was cut in 1–2 mm pieces in collection buffer (30 µM ActD in RPMI) and incubated with enzyme stock solution (90 U/ml DNase, 30 U/ml Collagenase I, 1200 U/ml Collagenase IV, 15 µM ActD in 1x HBSS) for 35 min (37°C, 300 rpm). Cell homogenates were filtered through a 100 µm mesh filter, pooling tissue from two mice. Cells were separated by gradient centrifugation using 37% Percoll (800 g, 35 min, 4°C, no acceleration, no deceleration) and washed in FACS buffer (5 mM EDTA, 2% BSA in 1x HBSS) before staining for CD11b and CD45 (20 min, 4°C). Cells were washed in FACS buffer and pooled, resulting in one sample per group. CD45-positive cells were sorted into 1x PBS on a MoFlo™ XDP flow cytometer (Beckman Coulter) in the Core Unit Cell Sorting and Immunomonitoring of the Medical Faculty, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. The yield of CD45-positive cells sorted from pooled tissue of 6 mice, was 221,880 (Control) and 180,660 (cDSS). The cell concentration of each sample was adjusted to 1000 cells/µl using 1x PBS. Libraries were prepared using the Chromium Next GEM Single Cell 3’ Reagent Kits v3.1 CG000315 Rev E according to the manufacturer’s protocol (10x Genomics) with a targeted cell recovery of 10,000 cells. The Chromium Single Cell 3’ Gene Expression Dual Index library was sequenced using a NovaSeq 6000 instrument (Illumina) at Genewiz, Leipzig, Germany. RNA sequencing reads from FASTQ files were mapped to the mus musculus reference genome (mm10) using the 10x Genomics Software Cell Ranger (10x Genomics, Pleasanton, CA, USA). Subsequent analysis was performed in R (v4.5.1). Quality control, data normalization and scaling, and subsequent clustering was performed using Seurat (v5.3.0) [ 33 ]. The median was calculated for nCount_RNA, nFeature_RNA and percent.mt and 1.5 times the interquartile range from the first and third quartile were taken as thresholds. In detail, cells with > 500 and < 7500 nFeature_RNA, > 1000 and < 30000 nCount_RNA and < 5% of the detected molecular identifiers mapped to mitochondrial genes were included, resulting in 7070 cells (cDSS) and 6591 cells (Control) post filtering. Principal component analysis (PCA) was performed on the top 2000 highly variable genes prior to clustering using clusterProfiler [ 30 ]. Clusters were visualized using uniform manifold approximation and projection for dimension reduction (UMAP) and annotated based on the top 10 identified marker genes per cluster using the FindAllMarkers function in Seurat. Pathway analyses were performed using clusterProfiler. Microglia subclusters were named according to previously published guidelines for microglia cell state annotation [ 34 ]. Multi-Omics Factor Analysis (MOFA) An integrated analysis of different data modalities (bulk RNA-sequencing and proteomics of midbrain tissue, qPCR data of genes expressed in the colon, ELISA of serum cytokines) was conducted using the MOFA2 R package (v1.18.0) [ 35 ]. Cytokine concentrations were log2 transformed and qPCR data were scaled prior to model training. The identified latent factors were correlated with the 50 top markers per cell type from midbrain single-cell RNA-sequencing data (cell-type signatures) to identify cell types enriched per factor. Fast Gene Set Enrichment Analysis (FGSEA) was conducted to identify cell-type signatures associated with MOFA factors using the FGSEA R package (v1.34.2) [ 36 ]. Gene weights were extracted from the ‘Transcriptomics midbrain’ view of the trained MOFA+ model and ranked according to their factor loadings. Cell type specific gene signatures were tested for enrichment against this pre-ranked gene list. Normalized enrichment scores and Benjamini-Hochberg adjusted p-values were used to assess significance and correct for multiple testing. Statistical analysis Statistical analyses were performed using R (v4.5.1), RStudio (v2025.09.1), or Prism 10 (v10.2.0). All data are shown as mean ± standard deviation (s.d.). Statistical test performed for individual data analysis are indicated in the respective figure legends. Results Cyclic DSS treatment induces chronic relapsing-remitting colitis accompanied by systemic inflammation To induce chronic relapsing-remitting colitis, we treated male and female C57BL/6J mice aged 20 weeks with DSS in three cycles, each consisting of 5 days of DSS + 10 days of recovery (Fig. 1 A, Fig. S1A). Colitis induction by DSS ingestion was confirmed by increased mucosal granularity, adhesive stool residues, thickened, non-translucent colon walls, and fibrin deposition observed by colonoscopy on day 36, quantified by the increased colonoscopy score in chronic DSS colitis mice (Fig. S1B). Post dissection, the DSS group showed a significant shortening of colon length (Fig. S1C). An increased expression of Il1b , Cxcl13 , and Tnf in the colon, but not in the small intestine was measured by reverse transcription-quantitative PCR (RT-qPCR), confirming the spatial nature of DSS-mediated induction of inflammation within the large intestine (Fig. S1D). Next, we investigated systemic inflammation in peripheral organs and the blood during chronic DSS colitis as previously reported [ 13 , 37 ].This is considered as an important prerequisite for inflammatory propagation from the gut into the CNS [ 4 ]. Indeed, we found signs of extraintestinal inflammation during the chronic phase of experimental colitis, indicated by an increased spleen length and relative weight in proportion to bodyweight (Fig. S1E, F). In addition, we detected a significantly higher expression of Il1b and Tnf in the lung, and of Cxcl13 and Tnf in the liver by RT-qPCR analyses (Fig. S1G). Moreover, increased serum levels of the inflammation-associated cytokines IFNγ, TNFα, IL-1β, IL-2, IL-6, IL-10, and CXCL10 confirmed a systemic immune cell activation as a response to chronic mucosal inflammation (Fig. S1H). Serum levels of the CXCL2 were reduced in chronic DSS colitis mice, while comparable levels between mice with chronic DSS colitis and controls were measured for IL-4, IL-5, IL-27p28/IL-30, IL-33, CCL2, CCL3, and CXCL1 (Fig. S1H). In sum, cyclic DSS administration resulted in a moderate relapsing-remitting colitis associated with systemic inflammation. Chronic colitis causes dopaminergic neuron loss and neuroinflammation in the midbrain Given the link of IBD to PD, we next investigated whether chronic experimental colitis causes PD-related neuropathology. Indeed, we observed a significant loss of tyrosine hydroxylase (TH) expressing dopaminergic neurons in the substantia nigra pars compacta during chronic DSS colitis (Fig. 1 B). Moreover, the persisting TH + dopaminergic neurons expressed alpha-synuclein phosphorylated at serine 129 (pSer129), a central post-translational modification of pathological alpha-synuclein associated with PD pathology [ 38 , 39 ] in a predominantly nuclear intracellular distribution pattern (Fig. 1 C). To unravel the underlying cellular immune mechanism behind this neuronal loss, we next aimed to characterize the CNS immune landscape during with a particular focus on parenchymal microglia. We therefore induced chronic colitis in the microglia-specific Hexb tdTomato mouse model [ 14 ] to distinguish tdTomato + microglia from tdTomato − infiltrating monocyte-derived macrophages and to define their responses to chronic colitis (Fig. S2A). Hexb tdTomato mice showed similar pathophysiological features in response to chronic colitis compared to non-transgenic C57BL/6J mice, including increased colonoscopy scores, reduced colon length, and increased spleen length and weight (Fig. S2B-E). We first investigated the cellular CNS immune response in whole brain tissue of Hexb tdTomato mice by flow cytometry (Fig. S2F-H, Fig. S3). While we found similar levels of CD45 + immune cells in the brain of chronic DSS colitis and control mice (Fig. S2F), we detect a decreased percentage of CD45 int CD11b + microglia and increased percentages of T cells, B cells, and neutrophils among all CD45 + immune cells in whole brain homogenates of chronic DSS colitis mice (Fig. S2G). Notably, the percentages of CD4 + T cells, CD8 + T cells, and double negative CD4 − CD8 − T cells were all higher in chronic DSS colitis mice (Fig. S2H). As we determined similar densities of Iba1 + cells in the cortex, hippocampus, striatum, and substantia nigra by regional immunofluorescence analysis (Fig. S4A), the relative decrease in the microglial frequency determined by flow cytometry (Fig. S2G) rather results from peripheral immune cell infiltration than from a decrease of cell numbers within the microglial compartment. The identity of Iba1 + cells as microglia was confirmed based on tdTomato-expression using immunofluorescence and flow cytometry of brain tissue of Hexb tdTomato mice with chronic colitis (Fig. S2I-K). Semi-quantitative scoring of microglial cells based on morphology and CD68 expression as previously described [ 16 , 18 ] indicated lower numbers of resting microglia (score 1) and a tendency towards increased numbers of moderately phagocytic microglia (score 3) in the substantia nigra, but not in the striatum, hippocampus, and cortex in chronic DSS colitis mice (Fig. 1 D). As microglial morphology did not differ between chronic colitis and controls based on Sholl analysis and other morphometric measures (Fig. S4B, C), these changes were mainly related to CD68 expression. To determine whether the increase in T cells and granulocytes found by flow cytometry was also prominent in the midbrain and specifically the substantia nigra, we performed immunofluorescence staining together with collagen IV to localize peripheral immune cells to the vascular, perivascular or parenchymal compartment. We observed significantly increased numbers of CD3 + T cells in the substantia nigra of mice with chronic DSS colitis (Fig. 1 E), primarily accounted for by CD8 + cytotoxic T cells (Fig. 1 F). Co-staining with the basement membrane marker collagen IV showed parenchymal localization of some CD8 + T cells, though most CD8 + T cells were localized inside vessels or in the perivascular space (Fig. 1 G). The increased numbers of neutrophils previously detected in flow cytometry of the whole brain were exclusively located within close proximity to blood vessels, but not in the midbrain parenchyma of chronic DSS colitis mice (Fig. 1 H). In conclusion, relapsing-remitting colitis induced by cyclic DSS intake led to PD-related neuropathology including dopaminergic neuron loss and synuclein pathology in the substantia nigra. This was accompanied by a mixed innate and adaptive cellular immune response in the midbrain, including parenchymal infiltration of CD8 + T cells, neutrophil adhesion to brain vessels, and propagation of microglia towards an activated phagocytic phenotype. The midbrain-specific transcriptional and proteomic inflammatory signature in chronic colitis Next, we more precisely characterized the regional CNS response to chronic colitis by bulk RNA-sequencing of the midbrain and striatum alongside proteomic analysis of the contralateral side (Fig. 2 A). We observed 129 significantly differentially expressed genes (DEGs) in the midbrain in chronic DSS colitis mice compared to littermate controls (Fig. 2 B, C). The 79 upregulated genes were associated with complement activation, humoral immune response, and synapse pruning, whereas the 50 downregulated genes were linked to nervous system development, neurogenesis, and synapse assembly (Fig. 2 D). KEGG pathway enrichment analysis identified an association with pathways of neurodegeneration (Fig. 2 E). We confirmed the significantly higher expression of microglia-related genes CD68 and C1qa, C1qb, and C1qc in the midbrain of chronic DSS colitis mice by immunofluorescence (Fig. 1 D, 2 F). In line with transcriptional alterations, proteomics analysis revealed 367 proteins differentially expressed in the midbrain of chronic DSS colitis mice compared to control mice (Fig. 2 G). Pathways associated with the 178 upregulated proteins included cellular response to reactive oxygen species and adaptive immune response, whereas the 189 downregulated proteins were linked to mitochondrial gene expression and cell morphogenesis (Fig. 2 H). KEGG pathway enrichment revealed an association with multiple pathways including tryptophan metabolism, phagosome, and neutrophil extracellular trap formation (Fig. 2 I). In contrast to the prominent transcriptional and translational changes in the midbrain, gene and protein expression were largely unchanged in the striatum, revealing only two upregulated genes and one downregulated gene as well as 30 upregulated and 42 downregulated proteins in chronic DSS colitis vs. control mice (Fig. S5A-D). In summary, we found clear evidence for a regional susceptibility of the midbrain to chronic colitis-induced systemic inflammation on gene and protein level. Chronic colitis causes a complex cellular immune response including disease-associated microglia in the midbrain To contextualize the inflammatory to chronic colitis-induced systemic inflammation in the midbrain and to dissect alterations in the cellular composition of midbrain microglia, we sorted CD45 + immune cells from the midbrain of mice with chronic DSS colitis and controls and performed single-cell RNA-sequencing (Fig. 3 A). After quality control, we conducted uniform manifold approximation and projection (UMAP) analyses from 7070 and 6591 CD45 + cells from the midbrain of chronic DSS colitis and control mice, respectively (Fig. 3 B, Fig. S6A). Based on gene marker analysis using FindMarkers in Seurat, we identified six microglial clusters (Clusters 0, 1, 2, 3, 4, 10), B cells (Cluster 9), T cells (Cluster 6), NK/NK T cells (Cluster 11), neutrophils (Cluster 5), monocytes (Cluster 8), and CNS-associated macrophages (CAMs)/dendritic cells (Cluster 7, Fig. 3 C-F). Compared to the homeostatic midbrain of control mice, non-microglial immune cells were represented at higher levels in the midbrain of chronic DSS mice (cDSS vs control: 24.69% vs 5.90%, thereof B cells (2.76% vs 0.50%), T cells (4.50% vs 1.47%), NK/NK T cells (1.22% vs 0.56%), monocytes (2.60% vs 1.00%), neutrophils (5.77% vs 0.56%), and CAMs/Dendritic cells (1.47% vs 1.04%) while the relative proportion of microglia was lower (75.31% vs 94.10%), pointing towards a complex multicellular inflammatory response in the midbrain (Fig. 3 D). Interestingly, some bone marrow-derived immune cell clusters predominantly found in mice with chronic DSS colitis expressed adhesion and migration molecules such as Itgal , Itga4 , and Cd44 as well as the Peyer patches-specific homing receptor Itgb7 (Fig. S6B), indicating their priming in the gut and capacity to subsequently migrate into the CNS. The joint cluster of CAMs and dendritic cells could be segregated by expression of Mrc1 and CD209a , respectively (Fig. S6B). In line with our immunohistological findings, most T cells were CD8 + and showed high expression of Nkg7 and Ccl5 . To a smaller extent, CD4 + cells were also present in the midbrain of chronic DSS colitis mice (Fig. S6B). Sub-analysis of microglia revealed differential representation of six clusters in chronic DSS colitis and control mice, which were classified based on Gene Ontology Biological Process enrichment and previously published microglia cluster defining genes [ 34 ] (Fig. 4 A-D). The homeostatic microglial clusters 0 and 2 were lower represented in chronic DSS colitis mice (Fig. 4 A; cDSS vs control, Cluster 0: 33.46% vs 37.82%, Cluster 2: 15.52% vs 19.31%). They were characterized by high expression of the established homeostatic microglial markers Hexb and Tmem119 and linked to oxidative phosphorylation (Fig. 4 C, D). Similarly, Cluster 1 was associated with homeostatic marker expression and the Gene Ontology terms developmental cell growth and transforming growth factor beta receptor superfamily signaling pathway, but was more strongly represented in control mice (Fig. 4 A, C, D; cDSS vs control, Cluster 1: 38.10% vs 31.28%). Clusters 3 and 4 were equally represented in mice with chronic colitis and controls, and linked to inflammation related terms (Fig. 4 A, D; cDSS vs control, Cluster 3: 6.31% vs 6.27%, Cluster 4: 4.11% vs 3.95%). Cluster 3 was characterized by increased expression of Mertk and reduced expression of Csf1r compared to the other microglial clusters (Fig. 4 C). Ccl3 and CCl4 were specifically enriched in Cluster 4 (Fig. 4 A-C). Interestingly, Cluster 10 was strongly induced in mice with chronic DSS colitis and identified as an interferon response microglia cluster with specific expression of Ifit3 , Isg15 , and Irf7 (Fig. 4 A-D; cDSS vs control, Cluster 10: 2.50% vs 1.37%). Taken together, chronic colitis-induced systemic inflammation leads to complex alterations in the midbrain immune cell composition characterized by parenchymal infiltration of CD8 + T cells, vascular adhesion of neutrophils, and a shift of microglia subpopulations from homeostatic to disease-associated subtypes, including interferon response microglia. Multi-Omics Factor Analysis links microglia to the midbrain fingerprint in colitis Having dissected a complex midbrain immune response to chronic colitis, we next aimed to identify major cellular drivers of midbrain signatures in colitis as potential therapeutic targets to alleviate dopaminergic neuron loss. To identify major sources of cross-modal variation in our multi-omics dataset along the gut-immune-brain axis and to relate these factors to disease state and midbrain immune cells, we applied a comprehensive preprocessing, integration, and harmonization workflow across all data modalities and performed Multi-Omics Factor Analysis v2 (MOFA+). Data of multiple types (views) were integrated, including (1) midbrain bulk RNA sequencing (RNA) and (2) midbrain proteomics (Proteomics) data, (3) qPCR analysis of inflammation-associated genes expressed in the colon (qPCR_colon), and (4) circulating cytokines (ELISA) (Fig. 4 E). MOFA+ captured both shared and modality-specific variation across the multi-omics dataset. Importantly, MOFA+ Factor 1 explained shared variance across all data modalities, indicating a disease-associated pattern. Factor 1 scores were significantly higher in the chronic DSS colitis group compared to controls (Fig. 4 F, Wilcoxon rank-sum test, p = 0.02 ) and positively correlated with the expression of inflammation-associated genes, i.e. Il1b , Cxcl13 , Tnf (Spearman correlation: Il1b r = 0.717, Cxcl13 r = 0.533, Tnf r = 0.617) in the colon (Fig. 4 F, G). To assess the cellular basis of this latent program, we correlated MOFA+ factors with cell-type specific expression signatures derived from midbrain single-cell RNA sequencing data (cell-type signatures, Fig. 4 H). Of note, MOFA+ Factor 1 scores positively correlated with multiple microglia clusters (Spearman correlation: Cluster 0 r = 0.950, Cluster 2 r = 0.983, Cluster 4 r = 0.683, Cluster 10 r = 0.450), suggesting that this latent factor captures microglia-related variation associated with chronic gut-derived peripheral inflammation (Fig. 4 H, I). Concluding, the integration of multi-omics data revealed a strong correlation between Factor 1, which is significantly elevated in chronic DSS colitis mice, and midbrain microglia. These findings strengthen the above reported findings that microglia may critically contribute to disease pathology and could represent a promising therapeutic target. Chronic colitis persists despite delayed Csf1r inhibition We next applied an interventional approach to delineate the role of microglia in orchestrating the midbrain immune response and potential neurotoxicity in chronic colitis. As all microglial cluster showed high expression levels of Csf1r with only a slight decrease in Cluster 3 (Fig. 4 C), we fed mice with chow supplemented with the Csf1r antagonist PLX5622 to efficiently reduce microglial numbers. To ensure the onset of colitis prior to treatment, PLX5622 administration was started on day 11, after the first of three DSS cycles (Fig. 5 A). PLX5622-fed mice developed colitis and extraintestinal inflammation of similar severity compared to mice receiving placebo chow (Fig. 5 B-I). Histologic assessment of hematoxylin and eosin-stained colon showed excessive immune cell infiltration into the mucosa and loss of epithelial barrier integrity, resulting in mucosal thickening and adding up to a higher histologic score in chronic DSS colitis mice independent of Csf1r inhibition (Fig. 5 F). Colonic Iba1 + myeloid cells showed a trend toward increased abundance, although this change did not reach statistical significance due to substantial interindividual variability. Co-administration of PLX5622 failed to significantly reduce Iba1⁺ cell density (Fig. 5 I). These data indicate that targeting Csf1r-dependent myeloid cells by PLX5622 treatment after the first DSS treatment cycle does not influence major hallmarks of chronic DSS colitis. Csf1r-dependent microglial depletion rescues dopaminergic neuron loss Next, we investigated the impact of PLX5622 treatment on the CNS of mice with chronic DSS colitis and controls. We performed flow cytometry of whole brain tissue and specifically investigated the midbrain using immunofluorescence (Fig. 6 A). PLX5622 treatment for 35 days led to a profound reduction of CD45 int CD11b + cells in the whole brain by 63% or 34% when comparing PLX5622- to placebo-fed control or chronic DSS colitis mice, respectively (Fig. 6 B). Focusing on the midbrain, we detected a significant reduction in Iba1 + microglia numbers by 67% in PLX5622- vs. placebo-fed chronic DSS colitis mice (Fig. 6 C). Assessing the impact of myeloid cell targeting on the mixed midbrain immune cell infiltration, we found unchanged levels of CD3⁺ T cells and CD8⁺ T cells between PLX5622- and placebo-fed chronic DSS colitis mice by flow cytometry and immunofluorescence (Fig. 6 D, E). Also, the percentage of Ly6G + neutrophils of CD45 high cells in whole brain tissue and the number of vessel-associated Ly6G + cells in the midbrain were comparable between chronic DSS colitis mice receiving placebo or PLX5622-supplemented chow (Fig. 6 F, G). Finally, we wondered if dopaminergic neuron loss in the substantia nigra of adult mice with chronic colitis can be alleviated by Csf1r-dependent microglial depletion. Intriguingly, PLX5622 treatment during the second and third cycle of chronic DSS colitis led to a complete rescue of TH-expressing neurons in the substantia nigra pars compacta (Fig. 6 H, J). The numbers of dopaminergic neurons correlated with the severity of colitis (Fig. 6 J). In summary, Csf1r inhibition after colitis onset in the chronic DSS colitis model results in a significant reduction of microglia in the midbrain and prevents an inflammation-mediated loss of dopaminergic neurons in the substantia nigra pars compacta without affecting colitis severity and migration of bone marrow-derived immune cells to the midbrain. Discussion Our study fundamentally advances the understanding of brain disease in the context of gut inflammation. We show a causal link between chronic colitis-induced neuroinflammation and the loss of dopaminergic neurons. Despite the complex neuroinflammatory fingerprint in the midbrain, this neurodegenerative process is predominantly driven by microglia and profoundly rescued by Csf1r inhibition – independent of colitis severity. The potential impact of chronic gut inflammation on the development of neuroinflammation and neurodegenerative diseases is particularly relevant in PD, given its association with IBD and early, prominent gastrointestinal symptoms [ 6 , 40 , 41 ]. To better model the association of chronic colitis with later-onset neurodegeneration, we chose a chronic paradigm in mice at an age of 20 weeks for adult-onset colitis induction, in contrast to most previous studies investigating DSS colitis in 2-3-month-old mice [ 11 , 42 ]. Moreover, we aimed to model a chronic gut inflammation by the relapsing remitting DSS treatment paradigm over three cycles. Our approach led to a 46% loss of dopaminergic neurons in the substantia nigra pars compacta, while previous studies with shorter DSS treatment paradigms reported either a less pronounced loss of approximately 35% [ 12 ] or no reduction of dopaminergic neurons by DSS treatment alone [ 42 ]. The loss of dopaminergic neurons in the present model is also supported by the downregulation of GO terms related to mitochondrial function in midbrain proteomic data of mice with chronic DSS colitis, as a similar signature was recently identified in the substantia nigra of PD patients by spatial transcriptomics [ 43 ]. Moreover, we observed a pronounced expression of pathological alpha-synuclein phosphorylated at Serine 129 in nigral dopaminergic neurons of mice with chronic colitis. The nuclear-predominant intracellular distribution of phosphorylated alpha-synuclein has been described in post-mortem brain tissue of patients with synucleinopathies [ 44 ]. In a previous study, Espinosa-Oliva AM, Ruiz R, Soto MS, Boza-Serrano A, Rodriguez-Perez AI, Roca-Ceballos MA, García-Revilla J, Santiago M, Serres S, Economopoulus V, Carvajal AE, Vázquez-Carretero MD, García-Miranda P, Klementieva O, Oliva-Martín MJ, Deierborg T, Rivas E, Sibson NR, Labandeira-García JL, Machado A, Peral MJ, Herrera AJ, Venero JL and de Pablos RM [ 12 ] found an increased intensity of total alpha-synuclein in the substantia nigra of rats after a 28-day DSS treatment and an increased percentage of neurons positive for phosphorylated alpha-synuclein in the substantia nigra of IBD patients compared to controls. Our findings thus corroborate that chronic DSS colitis can model PD-associated neuropathology caused by chronic gut inflammation and strengthen the pathological link between IBD and PD. As indicated by previous studies, there is mounting evidence of a regional brain immune response to gut inflammation [ 13 ], as well as a central role for inflammatory microglia in neurodegeneration [ 34 ]. Here we performed an in-depth characterization of the neuroimmune response paired with multi-omics analyses and revealed its causal relation to neuropathology in the context of chronic gut inflammation. We identified a susceptibility of the midbrain to chronic gut inflammation on gene and protein level and determined a complex innate and adaptive immune cell response in the midbrain using single-cell RNA-sequencing in the chronic DSS colitis mouse model of IBD. The regional responsiveness of midbrain microglia described here is in line with a study conducted two decades ago reporting an increased activation of microglia in the midbrain upon local administration of lipopolysaccharide, which was accompanied by a loss of dopaminergic neurons, whereas cortical and hippocampal microglia were less reactive to local lipopolysaccharide [ 45 ]. Furthermore, the midbrain was reported to be a preferential entry site for blood-derived immune cells in the context of peripheral inflammation and experimental autoimmune encephalomyelitis [ 46 ]. Our single-cell profiling of the midbrain immune response to chronic gut inflammation revealed a shift from homeostatic to inflammatory microglia including an expansion of an interferon-response cluster (Cluster 10) as well as an increased migration of bone marrow-derived immune cells into the midbrain parenchyma and adjacent compartments. Of note, CD8 + T cells expressing Nkg7 were linked to neurodegeneration in the context of Alzheimer’s Disease (AD) [ 47 ]. Also in PD, CD8 + T cells are present in the substantia nigra early in disease and may co-contribute to dopaminergic neuron loss [ 48 , 49 ]. In addition, neutrophil adhesion to brain capillaries was previously implicated in memory loss via regulation of cerebral blood flow in a mouse model of AD [ 50 ]. However, our integrative analysis points to a predominant role of microglia in the midbrain response to chronic colitis. Indeed, by our interventional approach, we confirm that microglia are essential for dopaminergic neuron loss in chronic gut inflammation, as microglial reduction by 67% using PLX5622 treatment protected dopaminergic neurons without affecting the migratory capacity of CD8 + T cells or neutrophils towards the midbrain and adjacent blood vessels. Apart from direct neurotoxic effects, it is conceivable that microglia signal to CD8 + T cells or neutrophils via direct interaction or secreted molecules, as microglial interaction with T cells and neutrophils were recently implicated with neurodegeneration in AD and tauopathy, respectively [ 51 , 52 ]. Within the microglial compartment, interferon-response microglia are highly conserved in different models of neurodegeneration [ 34 ] and may specifically contribute to dopaminergic neuron loss, as microglial type-I interferon signaling was recently detected on single-cell RNA-sequencing datasets of human PD-patient-derived midbrain samples [ 53 ]. Our data further imply that myeloid cell targeting by Csf1r inhibition directly acts in the CNS to protect dopaminergic midbrain neurons. PLX5622 treatment did not affect endoscopic and structural hallmarks of colitis. In line with this, the oral CSF1R inhibitor PRV-6527 failed to meet clinical endpoints in a Phase 2a clinical trial in patients with Crohn’s Disease [ 54 ]. While we found no significant reduction of total Iba1 + myeloid cells in the colon upon PLX5622 treatment, previous data on the impact of Csf1r inhibition on gut immune cells are heterogenous [ 55 – 57 ]. In contrast, midbrain microglia were strongly reduced upon PLX5622 treatment, which was linked to a rescue of dopaminergic neurons. Thus, Csf1r inhibition may have no substantial impact on gut pathology in IBD, but may effectively protect from IBD-related neurologic comorbidity, particularly PD in later life, by mitigating microglial numbers. Furthermore, our treatment approach with administration of PLX5622 during the second and third DSS treatment cycle suggests that the first cycle of DSS treatment is not sufficient to induce dopaminergic neuron loss, indicating that rather chronic sustained gut-derived inflammation is required to elicit neurodegenerative processes in the midbrain. Collectively, we identified microglia as a potential target to rescue dopaminergic neuron loss in the context of IBD. Our findings are in line with previous epidemiological observations in humans revealing an increased risk for patients with IBD to develop PD, while chronic anti-inflammatory treatment with TNF inhibitors restored the risk in IBD patients [ 41 ]. Future studies comparing midbrain immune signatures of IBD patients and PD patients, in particular those suffering from the recently proposed body-first PD subtype [ 58 , 59 ], will reveal the importance of our findings in human disease by shared and disease-specific mechanisms along the gut-immune-brain axis. Abbreviations AD Alzheimer’s Disease CAM CNS-associated macrophage CNS Central nervous system ColIV Collagen IV CSF1R Colony-stimulating factor 1 receptor DSS Dextran sulfate sodium IBA1 Ionized calcium-binding adaptor molecule 1 IBD Inflammatory bowel disease MOFA Multi-omics factor analysis PD Parkinson’s Disease PLX Plexxikon TH Tyrosine hydroxylase Declarations Ethics declaration Ethics approval and consent to participate All animal experiments were approved by the Government of Lower Franconia, Würzburg, Germany (RUF-55.2.2-2532-2-1638) and were performed in accordance to the EU Directive on the Protection of Animals Used for Scientific Purposes (2010/63/EU) in the preclinical experimental animal center in the Franz-Penzoldt-Center in Erlangen, Germany. Consent for publication Not available. Competing interests The authors declare no competing interests. Funding R.K.K., A.G., C.G., and P.S. were supported by the Interdisciplinary Center for Clinical Research of the Friedrich-Alexander-Universität Erlangen-Nürnberg (Junior Project J94 to R.K.K. and P.S., Clinician Scientist Program and ELAN Project P167 to P.S. and A.G., Jochen-Kalden funding program N5 to C.G.). M.A., E.E.N., V.R., and C.G. were supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 505539112 – KFO5024 (B01, A03). P.K. acknowledges funding by the Boehringer Ingelheim Foundation (Plus 3-Program). W.X. and J.C.M.S are supported by the Bavarian Californian Technology Center (BaCaTeC 9. 2021-2). T.M. is supported by the MEXT Cooperative Research Project Program, Medical Research Center Initiative for High Depth Omics, and CURE:JPMXP1323015486 for MIB, and AMRC, Kyushu University, and by AMED JP23gm1910004, JP23jf0126004, JP24zf0127012, JSPS KAKENHI JP25H01009, JP25K02573, Ono Pharmaceutical Foundation for Oncology, Immunology and Neurology, The Uehara Memorial Foundation and Takeda Science Foundation. K.P.K. was supported by Germany’s Excellence Strategy (CIBSS–EXC-2189 – Project ID 390939984). V.R. was funded by an ERC Starting Grant by the European research Council (HICI 851693), a Heisenberg fellowship and Sachmittel support provided by the DFG (German Research Foundation) – RO4866-3/1, RO4866-4/1; 401772351, transregional and collaborative research centers provided by the DFG (German Research Foundation) – 408885537 – TRR 274; 261193037 – CRC 1181, as well as the collaborative research center TAhRGet provided by the German ministry for education and research (BMBF). S.Z. was supported by the DFG (German Research Foundation) – 505539112 – KFO5024 (B02) and the Else Kröner-Fresenius-Stiftung (Clinician Scientist Professorship, 2021_CS.23). J.W. and P.S. were supported by the DFG (German Research Foundation) – 505539112 – KFO5024 (A04). P.S. was further funded by the Else Kröner-Fresenius-Stiftung (Else Kröner Memorial Fellowship, EKMS_2024.21). Author Contribution R.K.K.: Conceptualization, Formal analysis, Investigation, Project administration, Software, Visualization, Writing – original draft; M.A.: Investigation; I.S.: Investigation; E.E.N.: Investigation; M.D.: Formal analysis, Software; P.K.: Formal analysis, Resources, Software; W.X.: Writing – review & editing; A.G.: Investigation, Writing – review & editing; M.P.: Methodology, Resources; T.M.: Methodology, Resources; K.-P.K.: Methodology, Resources; V.R.: Writing – review & editing; S.Z.: Resources; J.C.M.S.: Conceptualization, Formal analysis, Resources, Software, Writing – review & editing; J.W.: Funding acquisition, Supervision, Writing – review & editing; C.G.: Conceptualization, Writing – review & editing; P.S.: Conceptualization, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Writing – original draft. Acknowledgement We thank the Core Unit für Zellsortierung und Immunomonitoring, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany for performing single cell sorting. We thank Julia Derdau for preparation of single-cell RNA-sequencing libraries. Access to the MESO QuickPlex SQ 120MM instrument was kindly provided by the Translational Radiobiology (Department of Radiation Oncology, Universitätsklinikum Erlangen). Data Availability Bulk proteomics data have been deposited at the Proteomics IDEntifications Database (PRIDE) and are accessible under the accession number PXD069675 upon publication. 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Blockade of colony stimulating factor-1 (CSF-I) leads to inhibition of DSS-induced colitis. Inflamm Bowel Dis. 2007;13:219–24. Horsager J, Andersen KB, Knudsen K, Skjærbæk C, Fedorova TD, Okkels N, Schaeffer E, Bonkat SK, Geday J, Otto M, et al. Brain-first versus body-first Parkinson's disease: a multimodal imaging case-control study. Brain. 2020;143:3077–88. Andersen KB, Krishnamurthy A, Just MK, Van Den Berge N, Skjærbæk C, Horsager J, Knudsen K, Vogel JW, Toledo JB, Attems J, et al. Sympathetic and parasympathetic subtypes of body-first Lewy body disease observed in postmortem tissue from prediagnostic individuals. Nat Neurosci. 2025;28:925–36. Additional Declarations No competing interests reported. Supplementary Files FigureS1.jpg Figure S1. Cyclic DSS treatment induces chronic colitis and systemic inflammation in C57BL/6J mice. A Timeline of colitis induction in male and female C57BL/6J mice aged 20 weeks at the start of the experiment. B Representative colonoscopy images and colonoscopy scores ( n = 23 mice per group; pooled of three independent experiments). CColon length post dissection ( n = 29-30 mice per group; pooled of four independent experiments). D Expression of the inflammation-associated genes Il1b , Cxcl13 , and Tnf in the colon and small intestine ( n = 10-11 mice per group; multiple unpaired t -tests). E, F Spleen length and spleen weight in percentage of bodyweight ( n = 29-31 mice per group; pool of four independent experiments). G Expression of the inflammation-associated genes Il1b , Cxcl13 , and Tnf in the lung and liver ( n = 9-10 mice per group; multiple unpaired t -tests). H Serum concentrations of the inflammation-associated cytokines IFNγ, TNFα, IL-1β, IL-2, IL-6, IL-10, CXCL10, IL-4, IL-5, IL-27p28/IL-30, IL-33, CCL2, CCL3, CXCL1 and CXCL2 ( n = 18 mice per group). Two-tailed, unpaired t -test, if not otherwise indicated. Each point represents the value of one mouse. Data are presented as mean ±s.d. Icons in A were created with BioRender.com. FigureS2.jpg Figure S2. Cyclic DSS treatment induces chronic colitis and immune cell response in the whole brain of Hexb tdTomato mice while microglial Hexb tdTomato expression is maintained. A Timeline of colitis induction in male and female Hexb tdTomato mice aged 20 weeks at the start of the experiment. B Colonoscopy score on day 36. C Colon length post dissection. D Spleen length post dissection. E Spleen weight in percentage of bodyweight. F, G, H Flow cytometry analysis of CD45 + immune cells (F), CD19 + B cells, CD3 + T cells, Ly6G + neutrophils, Ly6C + monocytes, and CD45 int CD11b + microglia as percentage of CD45 + cells (G), and CD3 + CD4 + , CD3 + CD8 + , and CD3 + CD4 - CD8 - T cells as percentage of CD45 + cells (H) in whole brain tissue. I, Immunostaining for Iba1 (white) and Hexb (tdTomato) in brain tissue of Hexb tdTomato mice. Scale bar, 20 µm. J, Quantification of Iba1 + Hexb tdTomato+ cells in percentage of Iba1 + cells in the midbrain. K, Flow cytometry analysis of Hexb tdTomato+ cells in percentage of CD11b + CD45 int cells. The results are from n = 10 (B - H, K) and n = 5 (J) mice per group. Two-tailed, unpaired t -test, if not otherwise indicated. Each point represents the value of one mouse. Data are presented as mean ± s.d. Icons in A were created with BioRender.com. FigureS3.jpg Figure S3. Flow cytometry gating strategy of brain immune cells isolated from cDSS-treated and control Hexb tdTomato mice. Cells were gated on SSC-A and SSC-H to remove doublets. Singlets negative for the Live/Dead fixable Aqua stain were considered as live cells. CD45 + live cells were gated on CD11b to identify CD11b + CD45 int microglia that were further gated on tdTomato to determine tdTomato + microglia. CD11b + CD45 + cells were gated on Ly6G and Ly6C to distinguish Ly6G + neutrophils from Ly6C + monocytes. CD11b - CD45 + cells were gated on CD3 (T cells) and CD19 (B cells), and CD3 + cells were further gated on CD8 and CD4 to identify T cell subpopulations. FigureS4.jpg Figure S4. Regional microglia density and morphology remain unaltered in chronic DSS colitis mice. A Immunostaining for Iba1 in brain tissue of C57BL/6J mice (left) and quantification of Iba1 + cells normalized to mm 3 in the hippocampus (Hc), cortex (Ctx), striatum (str), and substantia nigra (Sn, n = 7 mice per group, two-way ANOVA with Šídák's multiple comparisons test). Scale bars, 20 µm. B Sholl analysis of microglia in the substantia nigra. C Microglial process parameters in the substantia nigra ( n = 6-7 mice per group; two-tailed, unpaired t -test). Each point represents the mean value of one mouse. Data are presented as mean ± s.d. FigureS5.jpg Figure S5. Transcriptome and proteome analyses reveal subtle alterations in the striatum during chronic DSS colitis. A Volcano plot of genes differentially expressed in the striatum of chronic DSS colitis mice vs. control mice. B Volcano plot of proteins differentially expressed in the striatum of chronic DSS colitis mice vs. control mice. C Gene Ontology Biological Process analysis of the 30 proteins significantly higher expressed in the striatum of chronic DSS colitis mice compared to control mice. D KEGG (GSEA) pathway enrichment of proteins differentially expressed in the striatum of chronic DSS colitis mice compared to control mice. FigureS6.jpg Figure S6. UMAPs and feature plots of immune cell type defining genes in the midbrain. A Individual UMAPs of immune cells in the midbrain per group. BFeature plots of cluster defining markers. TableS12.docx Graphicalabstract.docx Cite Share Download PDF Status: Published Journal Publication published 27 Jun, 2026 Read the published version in Journal of Neuroinflammation → Version 1 posted Editorial decision: Revision requested 27 Mar, 2026 Reviews received at journal 27 Mar, 2026 Reviews received at journal 26 Mar, 2026 Reviews received at journal 26 Mar, 2026 Reviews received at journal 11 Mar, 2026 Reviews received at journal 09 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers invited by journal 02 Mar, 2026 Editor assigned by journal 02 Mar, 2026 Submission checks completed at journal 01 Mar, 2026 First submitted to journal 26 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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