John Q Trojanowski's research works | University of Pennsylvania and other places

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MSUT2 expression is associated with human tau pathology. a Immunofluorescence co-staining of frontal cortical human brain sections with antibodies against neurons (NeuN), astrocytes (GFAP), microglia (IBA1), oligodendrocytes (SOX10) and MSUT2. Scale bar = 50 µm. b Measurement of MSUT2 and cellular fluorescent signal co-localization in a. *P < 0.05 by one-way ANOVA followed by Tukey’s post hoc test, n = 3. The error bars represent the standard deviation. c Representative images of non-tauopathy control (CTR), Alzheimer’s disease (AD), Corticobasal degeneration (CBD), and Progressive supranuclear palsy (PSP) patient brain sections (frontal cortex) co-stained with MSUT2 and p-tau (PHF1) antibodies to reveal MSUT2 protein and tau pathology. Scale bar = 5 µm. d–f Quantification of MSUT2 immunoreactivity (MFI = mean fluorescence intensity) in non-tauopathy control (CTR) vs. diseased brain sections as exemplified in c. MSUT2 area is normalized to the neuron counts. Four random images of the cortical region were used for the quantification of each case. *P < 0.05, **P < 0.01, n.s., not significant, by t-test when comparing CTR (n = 9) vs. AD (n = 17), CBD (n = 6), or PSP (n = 5). The error bars represent the standard deviation. g Correlation of MSUT2 expression and tau pathology (PHF1 immunoreactivity) quantified from sections as exemplified in c. R² = 0.2256, P = 0.0030 by normal linear regression. Four random images of the cortical region/case were used for the quantification of both MSUT2 and PHF1. Each dot represents the mean value from one individual case. Both MSUT2 and tau pathology level was presented by the integrated mean fluorescence intensity of PHF1 staining. h Representative immunoblots of MSUT2 and p-tau levels in human brains and cellular homogenates probed with MSUT2, PHF1, and GAPDH antibodies. Samples include CTR, MCI (mild cognitive impairment), AD, CBD, and PSP brains. The CTR, MCI, and AD cases were separated and run on separate blots due to lane limitations. In addition, for the gels involving CTR cases in CBD and PSP, the control (CTR) cases were randomly selected from within the same CTR group. Three isoforms of MSUT2 are indicated using QBI HEK-293 cell lysate samples. i–l Quantification of MSUT2 immunoreactivity in immunoblot samples as depicted in h. All samples were normalized to GAPDH to gain the relative quantity (RQ). All three isoforms were included for quantification. n.s., not significant, *P < 0.05, **P < 0.01 by t-test, n = 14 CTR vs. 12 MCI, n = 14 CTR vs. 12 AD, n = 7 CTR vs. 6 CBD, n = 8 CTR vs. 5 PSP. The error bars represent the standard deviation

MSUT2 modulates the spatiotemporal spreading of tau pathology induced by human-derived AD-tau seeds. a Schematic picture of the experimental paradigm: AD-tau seeds were enriched from postmortem AD brains and stereotactically injected into the hippocampi of MSUT2 KO mice and wild-type (WT) littermates at 3 months of age. Mouse brains were collected at different time points (from 3 days to 12 months post-injection time; m.p.i.) and analyzed by immunohistochemistry and biochemistry. b Representative images of AD-tau-injected mouse hippocampi at 1 to 12 m.p.i. AD-tau-seeded MSUT2 KO and WT mouse tau pathology was revealed with a S199/T205-p-tau antibody (AT8). Scale bar = 60 and 15 (inset) µm. c Quantification of neurofibrillary tangles (NFTs) in the ipsilateral hippocampal region of the AD-tau-injected MSUT2 KO and WT mouse brains. **P < 0.01, ***P < 0.001 by two-way ANOVA followed by Bonferroni’s post hoc test, n = 6 per group. The error bars represent the standard deviation. d MSUT2 KO and WT mouse brains were injected with AD-tau and analyzed at 3 m.p.i. Proteins were extracted and fractionated from the ipsilateral hippocampi. Soluble fractions were probed with a mouse tau (m-tau) antibody T49 and GAPDH antibody as the loading control. Insoluble fractions were probed with T49 antibody. e, f Quantification of T49-positive optical density from immunoblots in d. Relative Quantities (RQ) were determined by normalizing T49 to GAPDH signals in the soluble fraction. n.s., not significant, ***P < 0.001 by t-test, WT vs. MSUT2 KO n = 4 per group. The error bars represent the standard deviation. g Representative images showing T231-p-tau pathology in the AD-tau-injected (12 m.p.i.) WT and MSUT2 KO mouse brains. Mouse brain sections were stained with a p-tau antibody (AT180). Scale bar = 60 and 15 (inset) µm. h Quantification of AT180-positive area in the ipsilateral hippocampi of the mice as depicted in g. *P < 0.05 by t-test, WT vs. MSUT2 KO, n = 6 per group. The error bars represent the standard deviation. i Representative images showing S396/S404-p-tau pathology in the AD-tau-injected (12 m.p.i.) WT and MSUT2 KO mouse brains. Mouse brain sections were stained with a p-tau antibody (PHF1). Scale bar = 60 and 15 (inset) µm. j Quantification of PHF1-positive area in the ipsilateral hippocampi of the mice as depicted in i. *P < 0.05 by t-test, WT vs. MSUT2 KO, n = 6 per group. The error bars represent the standard deviation. k Heatmap of tau pathology at 12 m.p.i. in different brain regions of MSUT2 KO and WT mice aligned in high (top) to low (bottom) anterograde connectivity strength to the injection site. Color hue indicates the abundance of tau pathology (Tau). n = 4 per group. l Heatmap of tau pathology at 12 m.p.i. in different brain regions of MSUT2 KO and WT mice aligned in high (top) to low (bottom) retrograde connectivity strength to the injection site. Color hue indicates the abundance of tau pathology (Tau). n = 4 per group. m, n Fold-change (WT/KO) in tau pathology based on different levels of anterograde and retrograde connectivity strength. High = 1st–25th ranked regions, Medium = 26th–50th ranked regions, Low = 89th–113th ranked regions (lowest 25 regions). n.s., not significant, *P < 0.05 by one-way ANOVA followed by Tukey’s post hoc test, high vs. medium vs. low connectivity region, n = 25 per connectivity category. The error bars represent the standard deviation

MSUT2 modulates tau pathology but not Aβ or α-synuclein pathology. a Representative images of AT8-positive tau pathology in CBD-tau-injected MSUT2 KO (KO) and wild-type (WT) mouse brains. Mice were injected with CBD-tau at 3 months of age and brains were collected, sectioned, and stained with AT8 antibody for tau pathology at 6 m.p.i. iHP = ipsilateral hippocampus; NFTs = neurofibrillary tangles; APs = astrocytic plaques (arrows). Scale bar = 50 μm. b, c Quantification of NFTs and APs (count) in sections stained as in a. *P < 0.05, n.s., not significant by t-test, MSUT2 KO (KO) vs. wild-type (WT) mouse, n = 6 mice per group. Error bars represent the standard deviation. d Representative images of AT8-positive tau pathology in PSP-tau-injected MSUT2 KO (KO) and wild-type (WT) mouse brains. Mice were injected with PSP-tau at 3 months of age and brains were collected, sectioned, and stained with AT8 antibody for tau pathology at 6 m.p.i. iHP = ipsilateral hippocampus; NFTs = neurofibrillary tangles; TAs = tufted astrocytes (arrowheads). Scale bar = 50 μm. e, f Quantification of NFTs and TAs (count) in sections stained as in d. *P < 0.05, n.s., not significant by t-test, MSUT2 KO (KO) vs. wild-type (WT) mouse, n = 6 mice per group. Error bars represent the standard deviation. g Representative images of Aβ plaque pathology in the brains of 5xFAD/MSUT2 KO (5xKO) and 5xFAD/MSUT2 wild-type (5xWT) mice. Mice were sacrificed at 8 months of age. Mouse brain sections were stained with H31L21 (Aβ42) antibody to reveal the Aβ plaques. Scale bar = 100 µm. h Quantification of Aβ plaque-positive area (H31L21 immunoreactivity) in 5xKO and 5xWT mouse brains in sections stained as in g. n.s., not significant by t-test, 5xFAD vs. 5xKO, n = 6 mice per group. Error bars represent the standard deviation. i Counts of Aβ plaque numbers in 5xKO and 5xWT mice in sections stained as in g. n.s., not significant by t-test, 5xFAD vs. 5xKO, n = 6 mice per group. Error bars represent the standard deviation. j Representative images of ipsilateral hippocampal regions of MSUT2 KO (KO) mice and wild-type (WT) littermates injected with mouse-α-synuclein preformed fibrils (mSyn-pffs) at 1 m.p.i. Mouse brain sections were stained with EP1536Y antibody to reveal α-synuclein pathology. Scale bar = 200 μm. k Quantification of α-synuclein pathology area (EP1536Y immunoreactivity) in the ipsilateral hippocampal regions of mSyn-pffs-injected MSUT2 KO (KO) mice and wild-type (WT) littermates in sections stained as in j. n.s., not significant by t-test, MSUT2 KO (KO) vs. wild-type (WT) mouse, n = 4 mice per group. Error bars represent the standard deviation. l 5xKO and 5xWT were injected with AD-tau at 7 months of age. Mouse brains were collected, sectioned and stained for neuritic plaque (NP) tau pathology with AT8 antibody at 1 m.p.i. representative images show ipsilateral hippocampal regions of injected mouse brains. Scale bar = 500 µm. m Quantification of NP tau pathology area in AD-tau-injected 5xKO and 5xWT mice at 1 m.p.i. in sections stained as in l. *P < 0.05 by t-test, 5xFAD vs. 5xKO, n = 6 mice per group. Error bars represent the standard deviation. n Brain sections from aged (12–15-month-old) AD-tau-injected MSUT2 KO (KO) and wild-type (WT) littermates at 3 m.p.i. were probed with AT8 antibody for tau pathology. Representative images show AT8-positive staining in the caudal hilus regions of the injected mouse brains. Scale bar = 500 µm. o Neurofibrillary tangles were counted in the ipsilateral hippocampal regions of AD-tau-injected aged MSUT2 and wild-type littermates at 3 m.p.i. in sections stained as in n. *P < 0.05, ***P < 0.001 by one-way ANOVA followed by Newman-Keuls’ post hoc test, MSUT2 KO (KO) vs. wild-type (WT) mouse, n = 6 mice per group. Error bars represent the standard deviation. p AT8-positive tau pathology area was quantified in the ipsilateral hippocampal regions of AD-tau-injected aged MSUT2 KO (KO) and wild-type (WT) littermates in sections stained as in n. n.s., not significant, *P < 0.05 by one-way ANOVA followed by Newman-Keuls’ post hoc test, WT vs. KO, n = 6 mice per group. Error bars represent the standard deviation

MSUT2 modulates the internalization of pathogenic tau seeds in neurons. a Representative images showing wild-type mouse primary neurons that were immunocytochemically stained with R2295M antibody (mouse tau, green) and DAPI (blue) to assess the amount of mouse tau pathology induced by human tau seeds. Wild-type mouse primary neurons were pretreated with antisense oligonucleotides (ASOs) against MSUT2 or scrambled control ASO (SCR) at DIV2 and human-derived tau seeds or mSyn-pffs were added at DIV7. Cells were extracted with detergent to remove soluble proteins and fixed at DIV21. Scale bar = 250 µm. b Quantification of R2295M immunoreactivity of each condition represented in a. Data were quantified using the fluorescent density x area of occupancy/DAPI count and normalized to the PBS-treated samples (as 100%). *P < 0.05, **P < 0.01, ***P < 0.001, n.s., not significant by two-way ANOVA followed by Tukey’s multiple comparisons test, n = 3 biologic repeats per group. Data were normalized to PBS-treated neurons in each group. Error bars represent the standard deviation. c Representative images showing neurons treated with MSUT2 ASOs (ASOs) or scrambled control ASO (SCR) at DIV2 and treated with pHrodo red dye (PhR)-labeled amplified AD-tau seeds (ADT40P1) at DIV7. PhR dye was detected at 2, 8, 18, and 48 h after the addition of ADT40P1. Scale bar = 5 µm. d Quantification of pHrodo red signal intensities from neurons treated as in c. Data are present as density x area/neuron count (DxA/Neuron count). The dashed line delineates the region corresponding to the neuron’s outline, as indicated by the brightfield channel. **P < 0.01, ***P < 0.001 by two-way ANOVA followed by Tukey’s multiple comparisons test, n = 3 biologic repeats per group. Error bars represent the standard deviation. e Representative images show MSUT2 KO and wild-type mouse primary neurons treated with pHrodo red (PhR)-labeled ADT40P1 at DIV7 and live imaged at 24 h post-treatment time. Scale bar = 25 µm. f Quantification of pHrodo red signal in neurons treated as in e. Data are present as density x area coverage/neuron count and normalized to WT neurons. **P < 0.01 by t-test, wild-type (WT) vs. MSUT2 KO (KO), n = 5 biologic repeats per group. Error bars represent the standard deviation. g Representative images show the uptake of fluorescently labeled tau seeds in MSUT2 KO and wild-type mouse brains in vivo. Mice were stereotactically-injected with pHrodo red-labeled ADT40P1 at 3 months of age. Mouse brains were quickly dissected at 2 d.p.i., sectioned, and imaged using live imaging microscopy. Representative images show the dorsal hippocampal regions of injected mice. Scale bar = 500 µm (overview) and 100 µm (insets). h Quantification of pHrodo red signal density x area of occupancy (DxA) in the hippocampal regions of the ADT40P1-injected MSUT2 KO and wild-type mice in sections stained as in g. **P < 0.01 by t-test, wild-type (WT) vs. MSUT2 KO (KO), n = 5 mice per group. Error bars represent the standard deviation. i Representative images showing wild-type primary neurons that were treated with MSUT2 ASOs (ASOs) or scramble controls (SCR) at DIV2 and treated with bodipy (BDY)-labeled mSyn-pffs (mSyn-pffs), Alexa594 (A594)-labeled transferrin, or fluorescein (FL)-labeled dextran (500 kDa) at DIV7, with imaging 24 h later. Internalized proteins were revealed using live cell microscopy. Extracellular bodipy and fluorescein fluorescence were quenched by 500 mM trypan blue before imaging. Representative images show fluorescent signals for bodipy, Alexa594, and fluorescein as well as fluorescence images merged with bright field images. Scale bar = 5 µm. j–l Quantification of fluorescent signal intensities (DxA) in each condition in neurons stained as in i. n.s., not significant, *P < 0.05 by t-test, MSUT2 ASOs (ASOs) vs. scramble controls (SCR), n = 4–5 biologic repeats per group. Error bars represent the standard deviation

MSUT2 modulates tau pathogenesis via adenosine signaling. a UMAP plot shows distinct cell populations in scNT-sequencing of wild-type and MSUT2 KO primary neuron cultures at DIV 10. Cell populations were determined by expression levels of multiple genes in each cell type. Ex = excitatory neurons, Inh = inhibitory neurons, MG = microglia, OPC = oligodendrocyte precursor cells, RG_Astro = radial glia astrocytes. b Volcano plot showing differentially expressed genes (DEGs) in wild-type (WT) and MSUT2 KO (KO) excitatory neurons identified by scNT-seq. WT and KO primary neurons were cultured and collected at DIV10 in single-cell resuspension and sequenced using scNT-seq. DEGs are shown as WT vs. KO neurons. DEGs with adjusted p < 0.01 are shown on the graph. Increased DEGs (KO greater than WT) are in red while decreased DEGs are in blue. c Heatmaps showing the total RNA level, synthesis rate (syn) and degradation rate (deg) changes of DEGs in excitatory neurons with (WT) or without (KO) expression of MSUT2. Values of DEGs in WT neurons were set as 0. The color hue indicates the level of changes, with red indicating increases (greater in KO than WT) and blue indicating decreases. d Immunoblots show VCP, HSP70 and A1AR protein expression levels in MSUT2 KO (KO) and wild-type (WT) littermates at 3 months of age. GAPDH was used as the loading control. n = 5 mice per group. e–g Quantification of VCP, HSP70, A1AR optical density from immunoblots as depicted in d. Data were normalized to the GAPDH signal. *P < 0.05 by t-test, MSUT2 KO (KO) vs. wild-type (WT) mice, n = 5 mice per group. Error bars represent the standard deviation. h Representative images showing mouse tau pathology induced by AD-tau in neurons treated with PBS, ASOs for A1AR, or scrambled control ASO. Primary neurons were transfected with ASOs at DIV2 and treated with AD-tau at DIV7. Insoluble mouse tau aggregates were revealed with R2295M antibody. DAPI reveals nuclei. Scale bar = 50 µm. i Quantification of mouse tau pathology (area x density/DAPI count) in primary neurons as depicted in h. *P < 0.05, **P < 0.01, ***P < 0.001 by one-way ANOVA followed by Tukey’s multiple comparison, n = 4 biologic repeats/condition. Error bars represent the standard deviation. j Representative time-lapse live images of internalized tau seeds in primary neurons treated with PBS, scrambled control ASOs (SCR), MSUT2 ASOs (MSUT2), A1AR ASOs (A1AR) at DIV2, or adenosine at DIV6, with pHrodo red-labeled ADT40P1 added at DIV7. Time in the figures is the interval after the addition of labeled ADT40P1. Scale bar = 5 µm. k Quantification of internalized pHrodo red signal (area x density/cell count) as a function of time, as depicted in j. n = 4 biologic repeats/condition. Error bars show standard errors

MSUT2 regulates tau spreading via adenosinergic signaling mediated ASAP1 pathway in neurons

March 2024

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Acta Neuropathologica

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Inclusions comprised of microtubule-associated protein tau (tau) are implicated in a group of neurodegenerative diseases, collectively known as tauopathies, that include Alzheimer’s disease (AD). The spreading of misfolded tau “seeds” along neuronal networks is thought to play a crucial role in the progression of tau pathology. Consequently, restricting the release or uptake of tau seeds may inhibit the spread of tau pathology and potentially halt the advancement of the disease. Previous studies have demonstrated that the Mammalian Suppressor of Tauopathy 2 (MSUT2), an RNA binding protein, modulates tau pathogenesis in a transgenic mouse model. In this study, we investigated the impact of MSUT2 on tau pathogenesis using tau seeding models. Our findings indicate that the loss of MSUT2 mitigates human tau seed-induced pathology in neuron cultures and mouse models. In addition, MSUT2 regulates many gene transcripts, including the Adenosine Receptor 1 (A1AR), and we show that down regulation or inhibition of A1AR modulates the activity of the “ArfGAP with SH3 Domain, Ankyrin Repeat, and PH Domain 1 protein” (ASAP1), thereby influencing the internalization of pathogenic tau seeds into neurons resulting in reduction of tau pathology. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-024-02703-3.

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Polypathologic Associations with Gray Matter Atrophy in Neurodegenerative Disease

Article

November 2023

13 Reads

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

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Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer’s pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid- ${\bi \beta }$ , tau, TDP-43, and ${\bi \alpha }$ -synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient’s primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and ${\bi \alpha }$ -synuclein burden were inversely associated with regional volumes, but amyloid- ${\bi \beta }$ was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and ${\bi \alpha }$ -synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology.

Lewy body amplification increases αSyn pathology induced in WT mice
a Schematic representation of experimental design. b Immunohistochemistry with an anti-pSyn antibody (EP1536Y). Arrows indicate pSyn-positive neuronal somatic inclusions. Motor Ctx, Motor cortex; SNpc, substantia nigra pars compacta. Scale bar 50 µm. c Heat-map colors represent the extent of pSyn-positive pathology. d Number of pSyn-positive neuronal somatic inclusions in the entire brains (LB-αSyn 50 ng and 170 ng, n = 3; ampLB 100 ng, n = 2, 2, 3; ampLB 500 ng, n = 2, 3, 3 biologically independent samples). e Western blot analysis of AD1 brain lysate immunodepleted with a control mouse IgG or an anti-human αSyn antibody 9027. Immunoblots with anti-human αSyn (HuA) and pSyn (81 A) antibodies. Images are representative of two independent experiments. f Left panels: Mouse primary hippocampal neurons treated with hPFF, immunodepleted (ID) AD1 brain lysate mixed with hPFF, LB-αSyn (AD1), and ampLB (AD1). Note that the ID brain lysate mixed with hPFF and LB-αSyn contains almost the same contaminants. Scale bars 100 µm, 20 µm (inset). Immunocytochemistry with anti-MAP2 and pSyn (81 A) antibodies. Right panel: Percent of total pSyn-positive pathology in neuronal somatic inclusions (n = 3 independent wells per group). One-way ANOVA with a Tukey’s post hoc test was performed (hPFF vs. LB-αSyn, ampLB p = 0.0038, <0.0001; ID brain lysate + hPFF vs. LB-αSyn, ampLB p = 0.0057, <0.0001). g Upper panel: Heat-map colors represent the extent of pSyn-positive pathology at 6MPI. Lower panel: Number of pSyn-positive neuronal somatic inclusions in the entire brains (hPFF 500 ng, ID brain lysate + hPFF 500 ng, and LB-αSyn 25 ng, n = 4; ampLB 500 ng, n = 3 biologically independent samples). One-way ANOVA with a Tukey’s post hoc test was performed (hPFF 500 ng, ID brain lysate + hPFF 500 ng, LB-αSyn 25 ng vs. ampLB 500 ng p < 0.0001). Data are represented as mean ± SEM. Source data are provided as a Source Data file.

Differences in seeding activity and distribution of αSyn pathology between hPFF and ampLB in WT mice
a Schematic representation of experimental design. b Immunohistochemistry with an anti-pSyn antibody (EP1536Y) at 6MPI. Motor Ctx, motor cortex; SNpc, substantia nigra pars compacta. Scale bar 50 µm. c, d Number of pSyn-positive neuronal somatic inclusions in the entire brain (hPFF 500 ng, n = 4; hPFF 5 µg, n = 4, 5, 5; AD1, AD2 500 ng, n = 2, 3, 3; PDD1, PDD2, DLB1, DLB2i 500 ng, n = 3 biologically independent samples). d Ratio of numbers of pSyn-positive neuronal somatic inclusions normalized with those at 6MPI (3MPI, n = 4, 4, 2, 2, 3, 3, 3, 3; 6MPI, n = 4, 5, 3, 3, 3, 3, 3, 3; 9MPI, n = 4, 5, 3, 3, 3, 3, 3, 3 biologically independent samples). One-way ANOVA with a Tukey’s post hoc test was performed (3MPI: hPFF 500 ng vs. AD1, AD2, PDD1, PDD2, DLB1, DLB2i 500 ng p = 0.0093, 0.0055, 0.0016, 0.0068, 0.0038, 0.0016; hPFF 5 µg vs. AD1, AD2, PDD1, PDD2, DLB1, DLB2i 500 ng, p < 0.0001; 9MPI: hPFF 500 ng vs. AD2, PDD1, PDD2, DLB1 500 ng p = 0.0371, 0.0478, 0.0041, 0.0005; hPFF 5 µg vs. PDD2, DLB1 500 ng p = 0.0362, 0.0038). e Heat-map colors represent the extent of pSyn-positive pathology at 9MPI. f Heat-map colors represent the proportion of pSyn-positive area in each brain region shown in Supplementary Fig. 5b at 9MPI. g Primary component analysis of the distribution of pSyn-positive pathology at 9MPI. h Distribution of pSyn-positive pathology in the brain systems at 9MPI (hPFF, n = 5; AD, PDD, DLB, n = 6 biologically independent samples). Olf Sys, olfactory system; Motor Ctx, motor cortex; Sensory Ctx, sensory cortex; Limbic Sys, limbic system; Th, thalamus; vMB, ventral midbrain; RF, reticular formation. Two-way ANOVA with Sidak’s post hoc test was performed (interaction p < 0.0001, Motor Ctx: hPFF vs. AD p = 0.0017; AD vs. DLB p = 0.0103; Limbic Sys: hPFF vs. PDD p = 0.0054; Other Ctx: hPFF vs. DLB p < 0.0001; Striatum: hPFF vs. AD, PDD, DLB p < 0.0001). Data are represented as mean ± SEM. Source data are provided as a Source Data file.

Differences in morphology of neuronal inclusions and cell-type preference between hPFF and ampLB in WT mice
a High-magnification image of pSyn-positive neuronal inclusions in the SN of hPFF-, ampLB-, and LB-αSyn-injected mice at 6MPI. Images are representative of 9, 18, and 7 biologically independent samples, respectively. Scale bar 20 µm. b Upper panels: Representative images of diffuse, compact, and granular pSyn-positive inclusions. Lower panels: Comparison of the proportions of diffuse, compact, and granular inclusions (hPFF, n = 50 from 9 biologically independent samples; ampLB, n = 959 from 18 biologically independent samples; LB-αSyn, n = 29 from 7 biologically independent samples). Neuronal inclusions with visible nuclei were evaluated. A two-sided Fisher’s exact test was performed between two groups for differences in the percentages of diffuse and non-diffuse inclusions (hPFF vs. ampLB, LB-αSyn p < 0.0001). Scale bar 20 µm. c Percent of diffuse inclusions in hPFF- and ampLB-injected mice (hPFF n = 5; AD1, AD2, PDD1, PDD2, DLB1, DLB2i, n = 3 biologically independent samples). One-way ANOVA with a Tukey’s post hoc test was performed (hPFF vs. AD1, AD2, PDD1, PDD2, DLB1, DLB2i p < 0.0001). d Immunohistochemistry and z-stack confocal microscopy images showing pSyn-positive intranuclear inclusions in hPFF-injected mice. Images are representative of two independent experiments. Scale bars 10 µm. e Immunohistochemistry with a pSyn antibody (EP1536Y) in the corpus callosum at 9MPI. Scale bar 20 µm. f Double immunofluorescence for Olig2 (green) and pSyn (81 A, red), GFAP (green) and pSyn (EP1536Y, red), and Iba1 (green) and pSyn (81 A, red). Scale bar 10 µm. g Number of pSyn-positive oligodendroglial inclusions in the corpus callosum (hPFF 500 ng, n = 4; hPFF 5 µg, n = 4, 5, 5 biologically independent samples). Two-way ANOVA with Sidak’s post hoc test was performed (interaction p = 0.0001, hPFF 500 ng 3, 6, 9MPI, hPFF 5 µg 3, 6MPI vs. hPFF 5 µg 9MPI p < 0.0001). h Number of pSyn-positive oligodendroglial inclusions in the corpus callosum at 9MPI (hPFF 5 µg, n = 5; hPFF 500 ng, n = 4; AD1, AD2, PDD1, PDD2, DLB1, DLB2i, n = 3 biologically independent samples). A two-tailed Mann–Whitney test was performed (hPFF 5 µg vs. hPFF 500 ng p = 0.0159). One-way ANOVA with a Tukey’s post hoc test was performed (hPFF 500 ng vs. AD1, PDD1, PDD2, DLB1, DLB2i p < 0.0001; hPFF 500 ng vs. AD2 p = 0.0002). Data are represented as mean ± SEM. Source data are provided as a Source Data file.

Modeling LBD in Thy1:SNCA/Snca–/– mice
A Schematic representation of experimental design. B Immunohistochemistry with an anti-pSyn antibody (EP1536Y) on the ipsilateral side. Images for 3, 6, and 9MPI are representative of 2, 3, and 2 biologically independent samples, respectively. Ventral DG, ventral dentate gyrus; RF, reticular formation; PRN, pontine reticular formation. Scale bar 50 µm. C Heat-map colors represent the extent of pSyn-positive pathology. D Left panels: Immunohistochemistry with anti-NeuN, GFAP, and Iba1 antibodies in the ipsilateral ventral dentate gyrus. Scale bar 200 µm. Right panels: Number of NeuN-positive cells, GFAP-positive area, and Iba1-positive area in the ipsilateral ventral dentate gyrus (n = 4 biologically independent samples per group). One-way ANOVA with a Tukey’s post hoc test was performed (Number of NeuN-positive cells: PBS-9MPI vs. ampLB-3, 6, 9MPI p = 0.0249, 0.0004, <0.0001; ampLB-3MPI vs. ampLB-9MPI p = 0.0052; GFAP-positive area: PBS-9MPI vs. ampLB-3, 6, 9MPI p = 0.0324, 0.0237, 0.0051). One-way ANOVA with a Dunnett’s post hoc test was performed (PBS-9MPI vs. ampLB-3, 9MPI p = 0.0303, 0.0476). E Barnes maze probe test at 7MPI (WT-PBS, n = 10; Thy1:SNCA/Snca–/–-PBS, n = 12; Thy1:SNCA/Snca–/–-ampLB, n = 11 biologically independent samples). Left panel: Time spent in a target zone on day 1 and day 10. One-way ANOVA with a Tukey’s post hoc test was performed for day 10 (WT-PBS vs. Thy1:SNCA/Snca–/–-ampLB p = 0.0299). Middle panels: Time spent in a target zone between day 1 and day 10. A two-tailed paired t-test was performed (Thy1:SNCA/Snca–/–-ampLB p = 0.0342). Right panel: Difference in time spent in a target zone between day 1 and day 10. A two-tailed unpaired Student’s t-test was performed (p = 0.161). F Cued fear conditioning test at 8MPI (WT-PBS, n = 9; Thy1:SNCA/Snca–/–-PBS, n = 12; Thy1:SNCA/Snca–/–-ampLB, n = 11 biologically independent samples). Left panel: Freezing time during auditory cue at day and day. Middle panels: freezing time between day 1 and day 10. A two-tailed paired t-test was performed (Thy1:SNCA/Snca–/–-ampLB p = 0.0249). Right panel: Difference in freezing time between day 1 and day 10. A two-tailed unpaired Student’s t-test was performed (p = 0.0356). Data are represented as mean ± SEM. Source data are provided as a Source Data file.

HPFF injection into Thy1:SNCA/Snca–/– mice induces pathological and phenotypic features distinct from ampLB
a Schematic representation of experimental design. b Survival curve of hPFF-injected Thy1:SNCA/Snca–/– mice (n = 5 biologically independent samples). c Immunohistochemistry with an anti-pSyn antibody EP1536Y on the ipsilateral side. Ventral DG, ventral dentate gyrus; Cerebellar N, cerebellar nuclei; RF, reticular formation; PRN, pontine reticular nucleus. Scale bar 50 µm. d Heat-map colors represent the extent of pSyn-positive pathology. e Schematic representation of age and severity of αSyn pathology. Each box represents one Thy1:SNCA/Snca–/– mouse (n = 35 biologically independent samples). The color indicates the severity of αSyn pathology (gray, sample without αSyn inclusions; green, mildly affected sample; orange, moderately affected sample; red, severely affected sample). f Immunohistochemistry with an anti-pSyn antibody EP1536Y on the ipsilateral side. Arrows indicate pSyn-positive inclusions. Scale bar 50 µm. g Heat-map colors represent the extent of pSyn-positive pathology.

α-Synuclein aggregates amplified from patient-derived Lewy bodies recapitulate Lewy body diseases in mice

October 2023

156 Reads

5 Citations

Nature Communications

[...]

Extraction of α-Synuclein (αSyn) aggregates from Lewy body disease (LBD) brains has been widely described yet templated fibrillization of LB-αSyn often fails to propagate its structural and functional properties. We recently demonstrated that aggregates amplified from LB-αSyn (ampLB) show distinct biological activities in vitro compared to human αSyn preformed fibrils (hPFF) formed de novo. Here we compare the in vivo biological activities of hPFF and ampLB regarding seeding activity, latency in inducing pathology, distribution of pathology, inclusion morphology, and cell-type preference. Injection of ampLB into mice expressing only human αSyn (male Thy1: SNCA / Snca –/– mice) induced pathologies similar to those of LBD subjects that were distinct from those induced by hPFF-injection or developing spontaneously with aging. Importantly, αSyn aggregates in ampLB-injected Thy1: SNCA / Snca –/– mice maintained the unique biological and conformational features of original LB-αSyn. These results indicate that ampLB-injection, rather than conventional PFF-injection or αSyn overexpression, faithfully models key aspects of LBD.

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Author Correction: Post-translational modifications of soluble α-synuclein regulate the amplification of pathological α-synuclein

October 2023

17 Reads

1 Citation

Nature Neuroscience

[...]

Perceptual judgments of features of AOS in naPPA by 2 judges, rated on a scale of 0 to 4 1 : Mean (SD)

Interrater reliability of judgments of features of AOS in naPPA by two judges

Apraxia of Speech in the Spontaneous Speech of Nonfluent/Agrammatic Primary Progressive Aphasia

June 2023

71 Reads

Journal of Alzheimer s Disease Reports

[...]

Background: Apraxia of speech (AOS) is a core feature of nonfluent/agrammatic primary progressive aphasia (naPPA), but its precise characteristics and the prevalence of AOS features in spontaneous speech are debated. Objective: To assess the frequency of features of AOS in the spontaneous, connected speech of individuals with naPPA and to evaluate whether these features are associated with an underlying motor disorder such as corticobasal syndrome or progressive supranuclear palsy. Methods: We examined features of AOS in 30 patients with naPPA using a picture description task. We compared these patients to 22 individuals with behavioral variant frontotemporal dementia and 30 healthy controls. Each speech sample was evaluated perceptually for lengthened speech segments and quantitatively for speech sound distortions, pauses between and within words, and articulatory groping. We compared subgroups of naPPA with and without at least two features of AOS to assess the possible contribution of a motor impairment to speech production deficits. Results: naPPA patients produced both speech sound distortions and other speech sound errors. Speech segmentation was found in 27/30 (90%) of individuals. Distortions were identified in 8/30 (27%) of individuals, and other speech sound errors occurred in 18/30 (60%) of individuals. Frequent articulatory groping was observed in 6/30 (20%) of individuals. Lengthened segments were observed rarely. There were no differences in the frequencies of AOS features among naPPA subgroups as a function of extrapyramidal disease. Conclusion: Features of AOS occur with varying frequency in the spontaneous speech of individuals with naPPA, independently of an underlying motor disorder.

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Apraxia of Speech in the Spontaneous Speech of Nonfluent/Agrammatic Primary Progressive Aphasia

May 2023

59 Reads

[...]

Antemortem network analysis of spreading pathology in autopsy-confirmed frontotemporal degeneration

May 2023

58 Reads

2 Citations

Brain Communications

[...]

Despite well-articulated hypotheses of spreading pathology in animal models of neurodegenerative disease, the basis for spreading neurodegenerative pathology in humans has been difficult to ascertain. In this study, we used graph theoretic analyses of structural networks in antemortem, multimodal MRI from autopsy-confirmed cases to examine spreading pathology in sporadic frontotemporal lobar degeneration. We defined phases of progressive cortical atrophy on T1-weighted MRI using a published algorithm in autopsied frontotemporal lobar degeneration with tau inclusions (FTLD-tau) or with TDP-43 inclusions (FTLD-TDP). We studied global and local indices of structural networks in each of these phases, focusing on the integrity of gray matter hubs and white matter edges projecting between hubs. We found that global network measures are compromised to an equal degree in patients with FTLD-tau and FTLD-TDP compared to healthy controls. While measures of local network integrity were compromised in both FTLD-tau and FTLD-TDP, we discovered several important characteristics that distinguished between these groups. Hubs identified in controls were degraded in both patient groups, but degraded hubs were associated with the earliest phase of cortical atrophy (i.e. epicenters) only in FTLD-tau. Degraded edges were significantly more plentiful in FTLD-tau than in FTLD-TDP, suggesting that the spread of tau pathology involves more significant white matter degeneration. Weakened edges were associated with degraded hubs in FTLD-tau more than in FTLD-TDP, particularly in the earlier phases of disease, and phase-to-phase transitions in FTLD-tau were characterized by weakened edges in earlier phases projecting to diseased hubs in subsequent phases of disease. When we examined the spread of pathology from a region diseased in an earlier phase to physically adjacent regions in subsequent phases, we found greater evidence of disease spreading to adjacent regions in FTLD-TDP than in FTLD-tau. We associated evidence of degraded gray matter hubs and weakened white matter edges with quantitative measures of digitized pathology from direct observations of patients’ brain samples. We conclude from these observations that spread of pathology from diseased regions to distant regions via weakened long-range edges may contribute to spreading disease in FTD-tau, while spread of pathology to physically adjacent regions via local neuronal connectivity may play a more prominent role in spreading disease in FTLD-TDP.

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Correction to: Isoform-specific patterns of tau burden and neuronal degeneration in MAPT-associated frontotemporal lobar degeneration

March 2023

23 Reads

Acta Neuropathologica

Lucia A A Giannini

Daniel Ohm

Annemiek J M Rozemuller

[...]

David J Irwin

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Soluble α-Syn phosphorylation modulates pathological α-Syn amplification
a, Schematic representation of experiment design. b, α-Syn variants show similar expression levels. (Repeated three times.) c, Densitometric quantification of α-Syn variants for experiments in b. (n = 3 different samples. Y39E, P = 0.9763; S87E, P = 0.724; Y125E, P = 0.0512 and Y133E, P = 0.724). d, Cells expressing α-Syn variants were transduced with α-Syn PFFs (40 ng per well). The induced α-Syn pathologies were stained with anti-pS129 α-Syn antibody (81A). (Repeated > 5 times.) e, Quantification of α-Syn pathology for experiments in d. (WT, n = 10; Y39E, S87E and Y133E, n = 8; Y125E, n = 7 and PBS, n = 4. Three different batches of PFF were tested. Y39E, P = 0.5633; S87E, P = 0.052; Y125E, P = 0.0883; Y133E, P = 0.120 and PBS, P < 0.0001). f, Cells expressing α-Syn variants were transduced with LB-α-Syn (4 ng per well) and stained with 81A. (Repeated > 7 times.) g, Quantification of α-Syn pathology for experiments in f. (PBS, n = 7; WT, n = 33; Y39E, n = 27; S87E, n = 30; Y125E, n = 25 and Y133E, n = 26. LB-α-Syn from eight cases were tested. Y39E, P < 0.0001; S87E, P = 0.0018; Y125E, P = 0.0018; Y133E, P = 0.0015 and PBS, P < 0.0001). h, Cells expressing α-Syn variants were transduced with low amount of α-Syn PFFs (4 ng per well) and the induced α-Syn pathology are quantified. (n = 3 different PFFs. Y39E, P = 0.0105; S87E, P = 0.0034; Y125E, P = 0.0313 and Y133E, P = 0.0034). i, Cells expressing α-Syn variants were transduced with GCI-α-Syn (40 pg per well) and stained with 81A. (Repeated > 7 times.) j, Quantification of α-Syn pathology for experiments in i. (WT, n = 14; Y39E and Y133E, n = 10; S87E and Y125E, n = 11 and PBS, n = 7. GCI-α-Syn from six cases was tested. Y39E, P = 0.0092; S87E, P < 0.0001; Y125E, P = 0.2446; Y133E, P = 0.0113 and PBS, P < 0.0001). k, Combining the data in e, g and j. (The n are the same as in e, g and j. Y39E LB versus PFF, P < 0.0001; Y39E LB versus GCI, P = 0.0359; S87E LB versus PFF, P = 0.0368; S87E LB versus GCI, P < 0.0001; Y125E LB versus GCI, P = 0.0297 and Y133E LB versus PFF, P = 0.0300). Results are shown as mean ± s.e.m. Statistics in c, e, g, h and j are one sample t-test (for normally distributed data) or one sample Wilcoxon test (for non-normally distributed data) against one. Statistics in k are one-way ANOVA with Tukeyʼs multiple comparison test (for normally distributed data) or Kruskal–Wallis test with Dunnʼs multiple comparison test (for non-normally distributed data) in each variant group. The P values in c, e, g, h and j are FDR corrected. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; NS, not significant. Scale bar, 100 µm.
Source data

Soluble α-Syn phosphorylation modulates GCI-α-Syn and LB-α-Syn amplification
a, Schematic diagram showing the seeding assay. Equal amounts of pY39 and pS87 α-Syn monomer mixture were seeded with PFF, LB-α-Syn or GCI-α-Syn. After fibrilization, the amount of pS87 and pY39 α-Syn in the fibril fraction were analyzed by sedimentation assay and WB, to evaluate which monomer is more easily seeded by pathological α-Syn. b–d, Representative WB results with antibodies against pY39 or pS87 α-Syn for experiment in a. P, pellet; s, supernatant in the sedimentation assay. (Repeated nine times for b and c, ten times for d.) e–g, Quantification results for experiments in b–d. e, PFF seed pY39 or pS87 α-Syn monomer equally (n = 9 different samples, P = 0.9414). f, LB-α-Syn preferentially seeds pS87 over pY39 α-Syn (n = 9 different samples, P = 0.0176). g, GCI-α-Syn preferentially seeds pY39 over pS87 α-Syn (n = 10 different samples, P = 0.0195). h, WT α-Syn was expressed in cells with or without c-Abl. pY39 α-Syn, total α-Syn and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were evaluated by WB (repeated > 5 times). i, Densitometric quantification of pY39 α-Syn versus total α-Syn for experiments in h (n = 7 different samples, P = 0.0038). j, Densitometric quantification of total α-Syn versus GAPDH for experiments in h. (n = 5 different samples, P = 0.2366). k,l, α-Syn was expressed in cells with or without c-Abl and seeded by PFF. The cells were stained with anti-pS129 α-Syn to evaluate α-Syn pathology (k) or extracted with 1%HDTA and stained with anti total α-Syn to evaluate insoluble α-Syn (l). (n = 6, three different PFF were tested; k, P = 0.4552; l, P = 0.1891). m,n, Similar to k and l, but seeded with LB-α-Syn. (n = 5, LB-α-Syn from three cases were tested; m, P = 0.0034; n, P = 0.0275). o,p, Similar to k and l, but seeded with GCI-α-Syn (n = 6 for o, n = 5 for p, GCI-α-Syn from three cases were tested; o, P = 0.0193; p, P = 0.0096). Results are shown as mean ± s.e.m. Statistics in e, f and g are two-tailed Wilcoxon matched-pairs signed rank test t-test. Statistics in i–p are one sample t-test against 1. *P < 0.05; **P < 0.01; ***P < 0.001; NS, not significant.
Source data

Systematically identify PTMs on soluble α-Syn from different α-synucleinopathies
a, Schematic diagram showing the purification of soluble α-Syn from disease brains. b, IP-purified soluble α-Syn from various α-synucleinopathy and control brains and recombinant α-Syn monomers were resolved on 12% Bis-Tris gel and stained with Coomassie Blue. (Repeated three times.) c, Summary of PTMs identified on soluble α-Syn purified from different α-synucleinopathy and control brains. WM, white matter.

Soluble α-Syn acetylation modulates pathological α-Syn amplification
a, Acetylation mimetic α-Syn variants showed similar expression levels in cells. (Repeated five times.) b, Densitometric quantification of α-Syn for experiment in a. (n = 4 for K96Q, n = 5 for the other groups; K6Q, P = 0.0544; K21Q, P = 0.268; K34Q, P = 0.658; K43Q, P = 0.772; K45Q, P = 0.539; K60Q, P = 0.088; K96Q, P = 0.0544; K102Q, P = 0.0776.) c, Cells expressing α-Syn variants were transduced with α-Syn PFFs (40 ng per well) and stained with anti-pS129 α-Syn (81A). (Repeated > 7 times.) d, Quantification of α-Syn pathology for c. (PBS, n = 7; WT, n = 21; K21Q, K43Q, K60Q, K96Q and K102Q, n = 18; K34Q and K45Q, n = 17. Four different PFF were tested. K21Q, P = 0.0029; K34Q, P = 0.1768; K43Q, P = 0.0012; K45Q, P = 0.543; K60Q, P = 0.2264; K96Q, P = 0.6397; K102Q, P = 0.543; PBS, P < 0.0001). e, Cells expressing α-Syn variants were transduced with LB-α-Syn (4 ng per well) and stained with 81A. (Repeated > 7 times.) f, Quantification of α-Syn pathology for e (PBS, n = 7; WT, n = 25; K21Q, K43Q and K96Q, n = 19; K34Q and K45Q, n = 17; K60Q and K102Q, n = 20. LB-α-Syn from eight cases were tested. K21Q, P < 0.0001; K34Q, P = 0.0539; K43Q, P < 0.0001; K45Q, P < 0.0001; K60Q, P = 0.0002; K96Q, P = 0.0783; K102Q, P = 0.7282; PBS, P < 0.0001). g, Cells expressing α-Syn variants were transduced with GCI-α-Syn (40 pg per well) and stained with 81A. (Repeated > 7 times). h, Quantification of α-Syn pathology for g. (PBS, n = 6; WT, n = 18; K21Q, K34Q, K43Q, K45Q and K96Q, n = 13; K60Q and K102Q, n = 15. GCI-α-Syn from six cases were tested. K21Q, P = 0.0114; K34Q, P = 0.103; K43Q, P = 0.002; K45Q, P = 0.0112; K60Q, P = 0.0245; K96Q, P = 0.6425; K102Q, P = 0.362; PBS, P < 0.0001). i, Combining the data in d, f and h. (The n is the same as d, f and h. K21Q PFF versus LB, P = 0.0184; K21Q LB versus GCI, P = 0.0385; K34Q PFF versus LB, P = 0.0234; K34Q LB versus GCI, P = 0.0174; K43Q PFF versus GCI, P = 0.0130; K45Q PFF versus LB, P = 0.0248; K45Q PFF versus GCI, P = 0.0379; K60Q PFF versus LB, P = 0.0088; K60Q LB versus GCI, P < 0.0001) Results shown as mean ± s.e.m. N represents biological replicates. Statistics in b, d, f and h are one sample t-test (for normally distributed data) or one sample Wilcoxon test (for non-normally distributed data) against one. Statistics in i are one-way ANOVA with Tukeyʼs multiple comparison test (for normally distributed data) or Kruskal–Wallis test with Dunnʼs multiple comparison test (for non-normally distributed data) in each variant group. The P values in b, d, f and h are FDR corrected. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; NS, not significant. Scale bar, 100 µm.
Source data

The effect of soluble α-Syn PTMs on pathological α-Syn transmission is conformation dependent
a, Schematic representation showing the passaging of GCI-α-Syn in primary neurons. b, HEK293 cells expressing phosphorylation mimetic α-Syn variants were transduced with GCI-α-Syn that was passaged in primary neurons (GCI-N) (40 pg per well) and stained with anti-pS129 α-Syn antibody (81A). (Repeated seven times.) c, Quantification of α-Syn pathology (pSyn normalized with total DAPI counts) for experiments in b. (n = 11 for WT and Y39E, n = 8 for S87E, Y125E and Y133E. Seven different GCI-N were tested. Y39E, P = 0.0079; S87E, P = 0.00011; Y125E, P = 0.8138; Y133E, P = 0.0072). d, HEK293 cells expressing acetylation mimetic α-Syn variants were transduced with GCI-N and stained with 81A. (Repeated ten times.) e, Quantification of α-Syn pathology for experiments in d. (n = 10 for K21Q and K34Q, n = 11 for the other groups. Seven different GCI-N were tested. K21Q, P < 0.0001; K34Q, P = 0.3223; K43Q, P < 0.0001; K45Q, P = 0.0007; K60Q, P = 0.0623; K96Q, P = 0.0638; K102Q, P = 0.0714.) f,g, Both phosphorylation and acetylation of soluble α-Syn showed similar effects on the transmission of GCI-N and GCI-α-Syn. (For GCI-α-Syn group in f, n = 11 for WT, n = 7 for Y39E, n = 8 for S87E, Y125E and Y133E. For GCI-N group in f, n = 10 for WT and Y39E, n = 7 for S87E, Y125E and Y133E. For GCI-α-Syn group in g, n = 18 for WT, n = 13 for K21Q, K34Q, K43Q, K45Q and K96Q, n = 15 for K60Q and K102Q. For GCI-N group in g, n = 11 for WT, n = 10 for K21Q and K34Q, n = 11 for K43Q, K45Q, K60Q, K96Q and K102Q.) Results are shown as mean ± s.e.m. N represents biological replicates. Statistics in c and e are one sample t-test (for normally distributed data) or one sample Wilcoxon test (for non-normally distributed data) against one. Statistics in f and g are unpaired two-tailed t-test (for normally distributed data; if variances are substantially different, perform Welchʼs correction) or Mann–Whitney test (for non-normally distributed data) in each variant group. The P values in c and e are FDR corrected. *P < 0.05; ****P < 0.0001; NS, not significant. Scale bar, 100 µm.
Source data

Post-translational modifications of soluble α-synuclein regulate the amplification of pathological α-synuclein

January 2023

354 Reads

36 Citations

Nature Neuroscience

[...]

Cell-to-cell transmission and subsequent amplification of pathological proteins promote neurodegenerative disease progression. Most research on this has focused on pathological protein seeds, but how their normal counterparts, which are converted to pathological forms during transmission, regulate transmission is less understood. Here we show in cultured cells that phosphorylation of soluble, nonpathological α-synuclein (α-Syn) at previously identified sites dramatically affects the amplification of pathological α-Syn, which underlies Parkinsonʼs disease and other α-synucleinopathies, in a conformation- and phosphorylation site-specific manner. We performed LC–MS/MS analyses on soluble α-Syn purified from Parkinsonʼs disease and other α-synucleinopathies, identifying many new α-Syn post-translational modifications (PTMs). In addition to phosphorylation, acetylation of soluble α-Syn also modified pathological α-Syn transmission in a site- and conformation-specific manner. Moreover, phosphorylation of soluble α-Syn could modulate the seeding properties of pathological α-Syn. Our study represents the first systematic analysis how of soluble α-Syn PTMs affect the spreading and amplification of pathological α-Syn, which may affect disease progression. Pathological α-synuclein (α-Syn) spreading is critical for the progression of many neurodegenerative diseases. The authors demonstrate that soluble α-Syn post-translational modifications (PTMs) dramatically modulate pathological α-synuclein spreading.

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Multinomial logistic regression analyses for CSF cholesterol efflux capacity (CEC). The predictions were evaluated for MCI and AD groups against CN. CSF cholesterol efflux capacity was measured in CN (n = 50), MCI (n = 18), and AD (n = 40). The CEC values were normalized to a standard CSF sample that was run on each plate to account for inter-assay variability. We then log normalized the data prior to regression analysis. A Multinomial logistic regression analysis showed N9 CEC has a significant prediction of MCI. B Multinomial logistic regression analysis showed SHSY-5Y CEC has a significant prediction of MCI Detailed statistics are shown in the lower part of the figure. CN, cognitively normal; MCI, mild cognitive impairment; AD, Alzheimer’s disease; CSF, cerebrospinal fluid; CEC, cholesterol efflux capacity

Multivariate linear regression of CSF CEC and apolipoproteins CSF. CSF cholesterol efflux capacity was measured in CN (n = 50), MCI (n = 18), and AD (n = 40). Association between ApoA1, ApoE, and ApoJ with both CEC in human microglial and neuronal cells (N9 and SH-SY5Y, respectively). Association between ApoA1 significantly associated with N9 microglial and SH-SY5Yneuronal cell CEC (**P < 8.96e−11 and ***P < 3.244e−06, respectively), ApoJ is significantly associated with N9 microglial and SH-SY5Yneuronal cell CEC (**P < 2.22e−05 and *P < 1.22e−02, respectively). ApoE is not associated with either CEC measurement

Heat map and hierarchical clustering of CSF CEC with apolipoproteins and biomarkers of AD. CSF CEC is closely associated with ApoA-I and Clusterin. Aβ1-42 is associated with ApoE, and pTau, TTau, and pTau/Aβ1-42 ratio

Multinomial logistic regression analyses for CSF apolipoproteins and AD diagnosis. Apolipoproteins were measured in CN (n = 50), MCI (n = 18), and AD (n = 40). A Apo A1 displayed significant prediction of MCI diagnosis. B ApoE is significantly lower in AD (**P < 0.01). C ApoJ (Clusterin) is significantly lower in MCI (**P < 0.01) AD denotes Alzheimer’s disease, CSF cerebrospinal fluid, ApoA1 apolipoprotein A-I, ApoE apolipoprotein E, ApoJ/Clusterin, PL phosphorylated lipid, and Aβ1-42 42 amino acid form of beta amyloid

ApoJ/Clusterin concentrations are determinants of cerebrospinal fluid cholesterol efflux capacity and reduced levels are associated with Alzheimer’s disease

December 2022

53 Reads

5 Citations

Alzheimer's Research & Therapy

[...]

Background Alzheimer’s disease (AD) shares risk factors with cardiovascular disease (CVD) and dysregulated cholesterol metabolism is a mechanism common to both diseases. Cholesterol efflux capacity (CEC) is an ex vivo metric of plasma high-density lipoprotein (HDL) function and inversely predicts incident CVD independently of other risk factors . Cholesterol pools in the central nervous system (CNS) are largely separate from those in blood, and CNS cholesterol excess may promote neurodegeneration. CEC of cerebrospinal fluid (CSF) may be a useful measure of CNS cholesterol trafficking. We hypothesized that subjects with AD and mild cognitive impairment (MCI) would have reduced CSF CEC compared with Cognitively Normal (CN) and that CSF apolipoproteins apoA-I, apoJ, and apoE might have associations with CSF CEC. Methods We retrieved CSF and same-day ethylenediaminetetraacetic acid (EDTA) plasma from 108 subjects (40 AD; 18 MCI; and 50 CN) from the Center for Neurodegenerative Disease Research biobank at the Perelman School of Medicine, University of Pennsylvania. For CSF CEC assays, we used N9 mouse microglial cells and SH-SY5Y human neuroblastoma cells, and the corresponding plasma assay used J774 cells. Cells were labeled with [ ³ H]-cholesterol for 24 h, had ABCA1 expression upregulated for 6 h, were exposed to 33 μl of CSF, and then were incubated for 2.5 h. CEC was quantified as percent [ ³ H]-cholesterol counts in medium of total counts medium+cells, normalized to a pool sample. ApoA-I, ApoJ, ApoE, and cholesterol were also measured in CSF. Results We found that CSF CEC was significantly lower in MCI compared with controls and was poorly correlated with plasma CEC. CSF levels of ApoJ/Clusterin were also significantly lower in MCI and were significantly associated with CSF CEC. While CSF ApoA-I was also associated with CSF CEC, CSF ApoE had no association with CSF CEC. CSF CEC is significantly and positively associated with CSF Aβ. Taken together, ApoJ/Clusterin may be an important determinant of CSF CEC, which in turn could mitigate risk of MCI and AD risk by promoting cellular efflux of cholesterol or other lipids. In contrast, CSF ApoE does not appear to play a role in determining CSF CEC.

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... Progressive neurodegenerative disease Parkinson's disease (PD) is typified by dopaminergic neuronal death in the substantia nigra pars compacta (Chen et al., 2020). A key clinical feature of the condition, Lewy bodies are intraneuronal collections of fibrillar a-synuclein (Uemura et al., 2023). In the serum of people with Parkinson's disease (PD), Zhou et al., ...
Reference:
Molecular Crossfires between Inflammasome Signalling and Dietary Small Molecule Inhibitors in Neurodegenerative Diseases: Implications for Medical Nutrition Therapy

α-Synuclein aggregates amplified from patient-derived Lewy bodies recapitulate Lewy body diseases in mice

Citing Article
Full-text available
October 2023

Nature Communications

[...]

... These circuits may have particular clinical relevance given that a recent neuroimaging study in FTD found a closer link between long-range white matter tracts and executive dysfunction than shorter-range tracts. 106 Neuroimaging studies and network modeling have implicated long-range neuronal pathways in FTLD-tau previously, 107,108 in addition to histologic studies examining large-scale networks that connect cortex to brainstem and spinal structures. For example, we found a predilection for tau-mediated degeneration of noradrenergic neurons in the locus coeruleus compared to TDP-43 pathology in FTLD, 109 and tau inclusions have been shown to preferentially spread along corticospinal and corticopontine fibers in FTLD. ...
Reference:
Cytoarchitectonic gradients of laminar degeneration in behavioral variant frontotemporal dementia

Antemortem network analysis of spreading pathology in autopsy-confirmed frontotemporal degeneration

Citing Article
Full-text available
May 2023

Brain Communications

[...]

... Epigenetic mechanisms in PD, including post-translational modifications, are receiving increased interest as highlighted in recent studies [4,5,[181][182][183][184]. As PADs may be a promising target in PD therapeutics, roles for the different isozymes must be better understood for the development of therapeutics utilising pan-PAD or PAD isozyme-specific targeting. ...
Reference:
The Brain Region Specific Citrullinome and PAD 1-6 Isozyme Detection in a Pre-motor Parkinson’s Disease Rat Model

Post-translational modifications of soluble α-synuclein regulate the amplification of pathological α-synuclein

Citing Article
Publisher preview available
January 2023

Nature Neuroscience

[...]

... They had been prompted by Previous studies have shown that apoA-1 deficiency contributes to the cerebral accumulation of amyloid and memory deficits, and that the overexpression of apoA-1 attenuates neuroinflammation in vivo 44,45) , implicating the contribution of the role of HDL in Alzheimer's pathogenesis. Their results indicated attenuated CEC in the cerebral fluid of individuals with Alzheimer's disease, suggesting the potential involvement of altered cholesterol homeostasis in this disease 46) . ...
Reference:
Bridging the Gap Between the Bench and Bedside: Clinical Applications of High-density Lipoprotein Function

ApoJ/Clusterin concentrations are determinants of cerebrospinal fluid cholesterol efflux capacity and reduced levels are associated with Alzheimer’s disease

Citing Article
Full-text available
December 2022

Alzheimer's Research & Therapy

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... Whole blood samples were collected and analyzed as previously described. 30,31 Briefly, samples were collected in ethylenediamine tetraacetic acid (EDTA) tubes, spun, and stored at −80 • C prior to analysis using the SiMoA HD-X platform (Quanterix, Billerica, MA, USA). ...
Reference:
Medial temporal lobe gray matter microstructure in preclinical Alzheimer's disease

Plasma phosphorylated tau181 predicts cognitive and functional decline

Citing Article
Full-text available
December 2022

Annals of Clinical and Translational Neurology

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... 12 These and other proteomic studies of neurodegeneration have been biased toward GM, though WM changes are known components of disease pathogenesis. 11,[27][28][29][30] Thus, we aimed to identify and compare GM and WM proteomic alterations in human tauopathy to more fully understand tau-mediated neurodegeneration. We hypothesized that WM would share many changes with GM, while also demonstrating unique disease-associated changes. ...
Reference:
Proteomic networks of gray and white matter reveal tissue‐specific changes in human tauopathy

Digital Histological Study of Neocortical Grey and White Matter Tau Burden Across Tauopathies

Citing Article
October 2022

Journal of Neuropathology and Experimental Neurology

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... Synaptic homeostasis alteration and degeneration are early pathological events common in many neurodegenerative diseases, including AD. This makes synaptic proteins that reflect synaptic dysfunction interesting early biomarkers [22]. Disruption of sleep and circadian rhythm is believed to happen with ageing and contribute to development of neurodegenerative diseases in part through synaptic dysfunction [23]. ...
Reference:
Effects of time of the day at sampling on CSF and plasma levels of Alzheimer’ disease biomarkers

Cerebrospinal fluid biomarker panel of synaptic dysfunction in Alzheimer's disease and other neurodegenerative disorders

Citing Article
Full-text available
October 2022

Alzheimer's & Dementia

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... 3 Traditionally, AD pathology can be assessed using biomarkers such as cerebrospinal fluid assays or neuroimaging techniques like positron emission tomography (PET) and magnetic resonance imaging (MRI). [4][5][6][7] Several studies have explored these modalities to predict conversion from MCI to dementia. [8][9][10][11][12] Although these techniques provide useful information, they are invasive and expensive, limiting their applicability to well-resourced places and lacking the scalability and accessibility needed for low-and middle-income countries. ...
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Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models

Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community‐engaged approach in the Alzheimer's Disease Neuroimaging Initiative 4

Citing Article
Full-text available
October 2022

Alzheimer's & Dementia

Michael W. Weiner

Dallas P. Veitch

Melanie J. Miller

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Alzheimer's Disease Neuroimaging Initiative

... Consistent with a role in our model, TBI induces Rock1-dependent neurodegeneration [65] and phosphorylation at three sites in JIP-3:Ser 318 , Ser 368 , and Ser 369 [66], resulting in JNK activation. Gap43 is well known as a primary JNK-targeted axonal phospho-protein [67] with elevations in AD CSF associated with tauopathy that predict progression [68]. Gab1 is also an adaptor protein with phospho-site-mediated coupling to SHP2 upstream of excitatory neuronal ERK activation and synaptic plasticity [69]; it is implicated in cognitive deficits in AD [69]. ...
Reference:
The Chronic Effects of a Single Low-Intensity Blast Exposure on Phosphoproteome Networks and Cognitive Function Influenced by Mutant Tau Overexpression

Association of CSF GAP-43 With the Rate of Cognitive Decline and Progression to Dementia in Amyloid-Positive Individuals

Citing Article
October 2022

Neurology

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... According to a recent survey, a TREM2 response occurs early in the amyloid cascades [73] . Several rare variants in TREM2, such as TREM2R47H have emerged, which significantly increase the risk by 2-to 4-fold, comparable to the increased risk associated with having one copy of APOEε4, which impairs ligand binding and curtails microglia activation in humans and AD mouse models [74] . From a recent autopsy-confirmed cohort, Kim et al found that TREM2 variant cases were more frequently associated with non-amnestic clinical syndromes and contributed to clinical and pathologic AD heterogeneity by altering the distribution of neurofibrillary degeneration and tau-dependent microglial dystrophy, resulting in hippocampalsparing and non-amnestic AD phenotypes [75] . ...
Reference:
Microglia in brain aging: An overview of recent basic science and clinical research developments

TREM2 risk variants are associated with atypical Alzheimer’s disease

Citing Article
Publisher preview available
September 2022

Acta Neuropathologica

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John Q Trojanowski's research while affiliated with University of Pennsylvania and other places

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