Reduced progranulin increases tau and α-synuclein inclusions and alters mouse tauopathy phenotypes via glucocerebrosidase

Comorbid proteinopathies are observed in many neurodegenerative disorders including Alzheimer's disease (AD), increase with age, and influence clinical outcomes, yet the mechanisms remain ill-defined. Here, we show that reduction of progranulin (PGRN), a lysosomal protein associated with TDP-43 proteinopathy, also increases tau inclusions, causes concomitant accumulation of α-synuclein and worsens mortality and disinhibited behaviors in tauopathy mice. The increased inclusions paradoxically protect against spatial memory deficit and hippocampal neurodegeneration. PGRN reduction in male tauopathy attenuates activity of β-glucocerebrosidase (GCase), a protein previously associated with synucleinopathy, while increasing glucosylceramide (GlcCer)-positive tau inclusions. In neuronal culture, GCase inhibition enhances tau aggregation induced by AD-tau. Furthermore, purified GlcCer directly promotes tau aggregation in vitro. Neurofibrillary tangles in human tauopathies are also GlcCer-immunoreactive. Thus, in addition to TDP-43, PGRN regulates tau- and synucleinopathies via GCase and GlcCer. A lysosomal PGRN-GCase pathway may be a common therapeutic target for age-related comorbid proteinopathies.

Differences in the immune microenvironment and genomic characteristics of TNBC in African American women compared to other races

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Background: African American (AA) women are more likely to be diagnosed with triple negative breast cancer (TNBC) compared to other races and have lower pathologic complete response rate to neoadjuvant therapy. Our goal was to assess differences in the immune microenvironment and genomic characteristics of TNBC by race using the TCGA data set. Methods: We compared the expression levels of 13 previously reported immune metagenes (CTL, Mphages, MHC1, Tregs, IF1, NK, STAT1, MHC2, Giam, Tfh, Tinh, Tstim, LCK), histologic tumor infiltrating lymphocyte (TIL) count and overall mutational load, neoantigen load, clonal heterogeneity assessed using the MATH score, amplification and deletion loads of between AA (n = 58) and non-AA TNBC (n = 114). Data was downloaded from the TCGA website, immune metagene expression and MATH scores were calculated as previously reported. Distributions between cohorts were compared using the Mann-Whitney U-test. Results: Among the immune metagenes only the cytotoxic T cell (CTL) metagene showed lower expression in AA patients (3.64 versus 4.08, unadjusted p = 0.046). TIL count was available in 51 of 58 AA and 91 of 114 of non-AA cases, and no significant difference was observed between the racial groups (p = 0.55). We also did not observe statistically significant differences in the mutational load (p = 0.36), neoantigen load (p = 0.38), clonal heterogeneity represented by the MATH score (p = 0.54), and amplification and deletion loads (p = 0.23 and 0.83 respectively) between the two TNBC race groups. We also assess the expression distribution of the immune signatures in an independent Affymetrix gene expression dataset including 40 AA and 323 non-AA patients with TNBC. Similar to the TCGA, there were no significant race differences in the immune signatures, including in the CTL metagene. Conclusions: These results suggest that the differences in prevalence and treatment response seen between TNBC in AA and non-AA patients are unlikely to be due to differences in the immune microenvironment and the genomic landscape of TNBC. However, more subtle comparison in the immune biology of these cancers can only be studies with more focused methods.