Journal: Nature Communications

Article Title: Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer’s disease retina

doi: 10.1038/s41467-026-68580-4

Figure Lengend Snippet: A Schematic of Retinal isolation and cross-section preparation. Red puncta (red) indicate putative Chlamydia pneumoniae (Cpn) inclusions. Analyses workflow summarizes cohort sizes. Numbers in parentheses indicate brain subsets for Cpn histology. B Immunofluorescence using anti-Cpn polyclonal antibody (pAb, green, white arrow; 3 repetitions) in 3 AD versus 3 normal cognition (NC) retinas. C Peroxidase-based immunohistochemistry using anti-Cpn monoclonal antibody (mAb, brown, red arrows) in 6 MCI and 9 AD versus 3 NC retinas; hematoxylin (purple) and IgG negative control (3 repetitions). D Retinal Cpn mAb immunofluorescence (red; white arrows, 3-repetition); cytosolic inclusions at higher magnification. E Quantification of retinal Cpn⁺ cell count (21 NC, 14 MCI, 34 AD). F Quantification of Cpn immunoreactivity (%IR area) in same retinal cohort (21 NC, 14 MCI, 34 AD) and paired brain tissues (5 NC, 5 MCI, 6 AD). Subjects with %IR area above the NC mean (red line) were classified as Cpn-positive. G Giemsa staining visualizes retinal Cpn-like inclusions (dark-blue, red arrows; BV, blood vessel; n = 8 donors, 4 repetitions). H FISH confirms retinal Cpn-specific genomic material (green, white arrow; n = 11 donors, 3 repetitions). I qPCR curves (Ct values) for the Cpn argR gene in 2 NC, 1 MCI, and 2 AD retinas. Pearson’s correlation ( r P ) between retinal Cpn and ( J ) brain Cpn, ( K ) retinal Aβ 42 , or ( L ) PHF-tau. M Spearman’s correlation ( r s ) between retinal Cpn and brain NFT severity. Retinal Cpn stratified by ( N ) Braak stage ( n = 12 Braak 0–II, 17 Braak III–IV, 31 Braak V–VI), ( O ) APOEɛ4 genotype ( n = 12 carriers, 25 non-carriers), and ( P ) MMSE score ( n = 26 MMSE ≥ 24, 9 MMSE 17–23, 16 MMSE ≤ 16). Q Correlation ( r s ) between retinal Cpn burden and CDR score. M-male, F-female, and age (y-years) are shown). All scale bars, 10 μm. Data are shown as individual values with means ± SEMs. Fold changes are shown in red. p values were determined by one-way ANOVA with Tukey’s post-hoc test ( E , F , N , P ), two-sided unpaired t -test ( P ), or Mann–Whitney U -test ( O ). Illustration A was created in Biorender.com. Fuchs, D. (2026) https://BioRender.com/msadzfx . Source data are provided as a file.

Article Snippet: Mice were intranasally infected with 1 × 10 6 Chlamydia pneumoniae titer [+Cpn; strain CM-1 (VR-1360, ATCC)] along with uninfected (PBS-treated; -Cpn) controls.

Techniques: Isolation, Immunofluorescence, Immunohistochemistry, Negative Control, Cell Characterization, Staining, MANN-WHITNEY

Journal: Nature Communications

Article Title: Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer’s disease retina

doi: 10.1038/s41467-026-68580-4

Figure Lengend Snippet: Gene ontology (GO) analysis of differentially expressed proteins (DEPs) related to bacterial infection ( A ) in the cerebral temporal cortex and ( B ) in the temporal hemi retina from 2 separate cohorts of human donors with AD ( n = 10 brains, 6 retinas) versus NC ( n = 8 brains, 6 retinas). The analysis was carried out in Metascape and included the Reactome, Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways (WikiPath) databases. Red arrows indicate the shared pathways between brain and retina. Bar and symbol graphs represent z-scores, and Benjamini-Hochberg adjusted p -values from Metascape analysis, respectively. Range of p -values is presented as color-coded symbols. Volcano plots display the fold changes [log 2 (FC)] and significance level [-log 10 ( p )] by two-sided t -test in the ( C ) cortex and ( D ) retina of AD versus NC subjects for Chlamydia inclusion interactome. Top 10 DEPs by FC upregulated (orange) and downregulated (purple) interactors are shown. The highlighted proteins, five downregulated and five upregulated, were found in both tissues. E GO network (Metascape) of enriched retinal pathways related to bacterial infection, immune response cell death, and mitochondrial collapse. The size of the nodes represents the number of DEPs, with the inner ring showing the proportion of these DEPs that are downregulated (purple) or upregulated (orange) in AD. The thickness of the green border represents the number of DEPs that interact with Chlamydia inclusion. The thickness of the connection lines between nodes represents the shared DEPs (association score) between pathways. F Heatmaps of upregulated (orange) and downregulated (purple) DEPs [-log 10 ( p ) by two-sided t -test and FC] normalized by unit variance scaling and generated in ClustVis in AD versus NC retina for selected pathways. Only proteins connected to gram-negative bacterial infection (Metascape analysis) and Chlamydia infection ( Chlamydia interactome and literature) are shown for each pathway. Clustering of DEPs was carried out manually based on their involvement in select pathways for visual clarity. Source data are provided as a file.

Article Snippet: Mice were intranasally infected with 1 × 10 6 Chlamydia pneumoniae titer [+Cpn; strain CM-1 (VR-1360, ATCC)] along with uninfected (PBS-treated; -Cpn) controls.

Techniques: Infection, Generated

Journal: Nature Communications

Article Title: Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer’s disease retina

doi: 10.1038/s41467-026-68580-4

Figure Lengend Snippet: Random forest regressor using 80 estimators was trained on the data to predict several brain pathologies. Box plots show the spread of results in quartiles with the same number of samples; the mean is displayed above each box. including A ABC average ( n = 24/25 for train/validation), B Braak stage ( n = 24/25 for train/validation), and C mini-mental state examination (MMSE) score ( n = 20/20 for train/validation). The distributions show the spread of models trained on different folds of the 5-repeated 2-fold cross-validation. Only models performing with a variance coefficient of determination r 2 > 0.15 (gray dotted line) were retained. D Box plots representing the AUC measure for retinal Cpn for each diagnostic groups NC, MCI, and AD. For each model, AUC was measured ( n = 28/28 for train/validation) using features either individually or combined with retinal Aβ 42 , retinal gliosis (IBA1, GFAP, and Vimentin), or retinal atrophy. E The ROC curves for different retinal biomarkers, including Chlamydia pneumoniae (Cpn), Aβ 42 , NLRP3, CCasp3, and retinal atrophy, either individual or combined with retinal Aβ 42 . Each model was obtained by averaging the curves across diagnosis separately in each cross-validation fold. In the ROC curves plot, AUC is listed for each curve and unadjusted. P -values for whether the results were different from baseline dummy models using permutation tests with k = 10,000 iterations (estimated *** p < 0.001). F The models were compared by using a Wilcoxon signed-rank test, and p values were adjusted for multiple comparisons using Benjamini-Hochberg correction. The heat map shows that among the top 5 performing models, we have 3 that are different from one another. The model trained on retinal Cpn + retinal Aβ 42 performed best and was significantly different from the second-best model (retinal NLRP3 + retinal Aβ 42 ) with p < 0.05. The other three models were different from the top 2, but not from one another. Red arrows highlight retinal markers, individually or in combination, which were significantly different among the performance models to predict disease diagnosis. Statistics: * p < 0.05 and ** p < 0.01, adjusted for multiple comparisons with Benjamini-Hochberg procedure. Source data are provided as a file.

Article Snippet: Mice were intranasally infected with 1 × 10 6 Chlamydia pneumoniae titer [+Cpn; strain CM-1 (VR-1360, ATCC)] along with uninfected (PBS-treated; -Cpn) controls.

Techniques: Biomarker Discovery, Diagnostic Assay