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Activation of PPARA-mediated autophagy reduces Alzheimer disease-like pathology and cognitive decline in a murine model.

ABSTRACT: Alzheimer disease (AD) is the most common neurodegenerative disease. An imbalance between the production and clearance of Aβ (amyloid beta) is considered to be actively involved in AD pathogenesis. Macroautophagy/autophagy is a major cellular pathway leading to the removal of aggregated proteins, and upregulation of autophagy represents a plausible therapeutic strategy to combat overproduction of neurotoxic Aβ. PPARA/PPARα (peroxisome proliferator activated receptor alpha) is a transcription factor that regulates genes involved in fatty acid metabolism and activates hepatic autophagy. We hypothesized that PPARA regulates autophagy in the nervous system and PPARA-mediated autophagy affects AD. We found that pharmacological activation of PPARA by the PPARA agonists gemfibrozil and Wy14643 induces autophagy in human microglia (HM) cells and U251 human glioma cells stably expressing the human APP (amyloid beta precursor protein) mutant (APP-p.M671L) and this effect is PPARA-dependent. Administration of PPARA agonists decreases amyloid pathology and reverses memory deficits and anxiety symptoms in APP-PSEN1ΔE9 mice. There is a reduced level of soluble Aβ and insoluble Aβ in hippocampus and cortex tissues from APP-PSEN1ΔE9 mice after treatment with either gemfibrozil or Wy14643, which promoted the recruitment of microglia and astrocytes to the vicinity of Aβ plaques and enhanced autophagosome biogenesis. These results indicated that PPARA is an important factor regulating autophagy in the clearance of Aβ and suggested gemfibrozil be assessed as a possible treatment for AD.Abbreviation: Aβ: amyloid beta; ACTB: actin beta; ADAM10: ADAM metallopeptidase domain 10; AD: Alzheimer disease; AIF1/IBA1: allograft inflammatory factor 1; ANOVA: analysis of variance; APOE: apolipoprotein E; APP: amyloid beta precursor protein; APP-PSEN1ΔE9: APPswe/PSEN1dE9; BAFA1: bafilomycin A₁; BDNF: brain derived neurotrophic factor; BECN1: beclin 1; CD68: CD68 molecule; CREB1: cAMP responsive element binding protein 1; DAPI: 4',6-diamidino-2-phenylindole; DLG4/PSD-95: discs large MAGUK scaffold protein 4; DMSO: dimethyl sulfoxide; ELISA: enzyme linked immunosorbent assay; FDA: U.S. Food and Drug Administration; FKBP5: FK506 binding protein 5; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; gemfibrozil: 5-(2,5-dimethylphenoxy)-2,2-dimethylpentanoic acid; GFAP: glial fibrillary acidic protein; GLI2/THP1: GLI family zinc finger 2; HM: human microglia; IL6: interleukin 6; LAMP1: lysosomal associated membrane protein 1; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; MTOR: mechanistic target of rapamycin kinase; NC: negative control; OQ: opposite quadrant; PPARA/PPARα, peroxisome proliferator activated receptor alpha; PSEN1/PS1: presenilin 1; SEM: standard error of the mean; SQSTM1: sequestosome 1; SYP: synaptophysin; TFEB: transcription factor EB; TNF/TNF-α: tumor necrosis factor; TQ: target quadrant; WT: wild type; Wy14643: 2-[4-chloro-6-(2,3-dimethylanilino)pyrimidin-2-yl]sulfanylacetic acid.

SUBMITTER: Luo R

PROVIDER: S-EPMC6984507 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:As Alzheimer disease (AD) research moves to intervene in presymptomatic phases of the disease, we must develop outcome measures sensitive to the earliest disease-related changes.To demonstrate the feasibility of a cognitive composite outcome for clinically normal elderly participants with evidence of AD pathology using the ADCS Preclinical Alzheimer Cognitive Composite (ADCS-PACC). The ADCS-PACC combines tests that assess episodic memory, timed executive function, and global cognition. The ADCS-PACC is the primary outcome measure for the first clinical trial in preclinical AD (ie, the Anti-Amyloid Treatment in Asymptomatic Alzheimer's study).With the ADCS-PACC, we derive pilot estimates of amyloid-related decline using data from 2 observational studies conducted in North America and another conducted in Australia. The participants analyzed had normal cognition and mean ages of 75.81, 71.37, and 79.42 years across the 3 studies.For the 2 studies that collected data on A? levels (ADNI and AIBL), we estimate decline in a preclinical AD "A?-positive" placebo group and compare them with an "A?-negative" group. For the study that did not include data on A? levels (the ADCS Prevention Instrument [ADCS-PI] study), we grouped participants by the presence of APOE-?4 and by clinical progression.In ADNI, A?-positive participants showed more decline than did A?-negative participants with regard to the ADCS-PACC score at 24 months (mean [SE] difference, -1.239 [0.522] [95% CI, -2.263 to -0.215]; P?=?.02). In AIBL, the mean (SE) difference is significant at both 18 months (-1.009 [0.406] [95% CI, -1.805 to -0.213]; P?=?.01) and 36 months (-1.404 [0.452] [95% CI, -2.290 to -0.519]; P?=?.002). In the ADCS-PI study, APOE-?4 allele carriers performed significantly worse on the ADCS-PACC at 24 months (mean [SE] score, -0.742 [0.294] [95% CI, -1.318 to -0.165]; P?=?.01) and 36 months (-1.531 [0.469] [95% CI, -2.450 to -0.612]; P?=?.001). In the ADCS-PI study, cognitively normal participants who progress from a global Clinical Dementia Rating score of 0 are significantly worse on the ADCS-PACC than cognitively normal participants who are stable with a global Clinical Dementia Rating score of 0 at months 12, 24, and 36 (mean [SE] ADCS-PACC score, -4.471 [0.702] [95% CI, -5.848 to -3.094]; P?<?.001). Using pilot estimates of variance and assuming 500 participants per group with 30% attrition and a 5% ? level, we project 80% power to detect effects in the range of ??=?0.467 to 0.733 on the ADCS-PACC.Analyses of at-risk cognitively normal populations suggest that we can reliably measure the first signs of cognitive decline with the ADCS-PACC. These analyses also suggest the feasibility of secondary prevention trials.

Project description:PurposeBiomarkers used for predicting longitudinal cognitive change in Alzheimer's disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.Patients and methodsA total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.ResultsBaseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.ConclusionOur study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.

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Activation of PPARA-mediated autophagy reduces Alzheimer disease-like pathology and cognitive decline in a murine model.

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