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HDL Proteome and Alzheimer’s Disease: Evidence of a Link
review-article
Author(s):
Judit Marsillach
1 ,
Maria Pia Adorni
2 ,
Francesca Zimetti
3
,
* ,
Bianca Papotti
3 ,
Giovanni Zuliani
4 ,
Carlo Cervellati
4
Publication date (Electronic):
03 December 2020
Journal:
Antioxidants
Publisher:
MDPI
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Abstract
Several lines of epidemiological evidence link increased levels of high-density lipoprotein-cholesterol (HDL-C) with lower risk of Alzheimer’s disease (AD). This observed relationship might reflect the beneficial effects of HDL on the cardiovascular system, likely due to the implication of vascular dysregulation in AD development. The atheroprotective properties of this lipoprotein are mostly due to its proteome. In particular, apolipoprotein (Apo) A-I, E, and J and the antioxidant accessory protein paraoxonase 1 (PON1), are the main determinants of the biological function of HDL. Intriguingly, these HDL constituent proteins are also present in the brain, either from in situ expression, or derived from the periphery. Growing preclinical evidence suggests that these HDL proteins may prevent the aberrant changes in the brain that characterize AD pathogenesis. In the present review, we summarize and critically examine the current state of knowledge on the role of these atheroprotective HDL-associated proteins in AD pathogenesis and physiopathology.
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Most cited references176
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ApoE4 markedly exacerbates tau-mediated neurodegeneration in a mouse model of tauopathy
Yang Shi, Shane Liddelow, Scott T. Smith … (2017)
APOE4 is the strongest genetic risk factor for late-onset Alzheimer disease. ApoE4 increases brain amyloid-β pathology relative to other ApoE isoforms. However, whether APOE independently influences tau pathology, the other major proteinopathy of Alzheimer disease and other tauopathies, or tau-mediated neurodegeneration, is not clear. By generating P301S tau transgenic mice on either a human ApoE knock-in (KI) or ApoE knockout (KO) background, here we show that P301S/E4 mice have significantly higher tau levels in the brain and a greater extent of somatodendritic tau redistribution by three months of age compared with P301S/E2, P301S/E3, and P301S/EKO mice. By nine months of age, P301S mice with different ApoE genotypes display distinct phosphorylated tau protein (p-tau) staining patterns. P301S/E4 mice develop markedly more brain atrophy and neuroinflammation than P301S/E2 and P301S/E3 mice, whereas P301S/EKO mice are largely protected from these changes. In vitro, E4-expressing microglia exhibit higher innate immune reactivity after lipopolysaccharide treatment. Co-culturing P301S tau-expressing neurons with E4-expressing mixed glia results in a significantly higher level of tumour-necrosis factor-α (TNF-α) secretion and markedly reduced neuronal viability compared with neuron/E2 and neuron/E3 co-cultures. Neurons co-cultured with EKO glia showed the greatest viability with the lowest level of secreted TNF-α. Treatment of P301S neurons with recombinant ApoE (E2, E3, E4) also leads to some neuronal damage and death compared with the absence of ApoE, with ApoE4 exacerbating the effect. In individuals with a sporadic primary tauopathy, the presence of an ε4 allele is associated with more severe regional neurodegeneration. In individuals who are positive for amyloid-β pathology with symptomatic Alzheimer disease who usually have tau pathology, ε4-carriers demonstrate greater rates of disease progression. Our results demonstrate that ApoE affects tau pathogenesis, neuroinflammation, and tau-mediated neurodegeneration independently of amyloid-β pathology. ApoE4 exerts a ‘toxic’ gain of function whereas the absence of ApoE is protective.
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APOE4 leads to blood-brain barrier dysfunction predicting cognitive decline
Axel Montagne, Daniel Nation, Abhay Sagare … (2020)
Introductory Paragraph Vascular contributions to dementia and Alzheimer’s disease are increasingly recognized 1–6 . Recent studies have suggested that blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction 7 , including the early clinical stages of Alzheimer’s disease 5,8–10 . Apolipoprotein E4 (APOE4), the major Alzheimer’s disease susceptibility gene 11–14 , leads to accelerated blood-brain barrier breakdown and degeneration of brain capillary pericytes 15–19 that maintain blood-brain barrier integrity 20–22 . Whether APOE4 cerebrovascular effects contribute to cognitive impairment remains, however, largely unknown. Here we show that APOE4 carriers (ε3/ε4 and ε4/ε4) are distinguished from non-carriers (ε3/ε3) by blood-brain barrier breakdown in the hippocampus and medial temporal lobe. This finding is apparent in cognitively unimpaired APOE4 carriers, more severe in those with cognitive impairment, but not related to cerebrospinal fluid or positron emission tomography measurements of Alzheimer’s amyloid-β or tau pathology 23 . Indeed, high baseline cerebrospinal fluid levels of the blood-brain barrier pericyte injury biomarker soluble platelet-derived growth factor receptor-β 7,8 predicted future cognitive decline in APOE4 carriers but not in non-carriers, even after controlling for amyloid-β and tau status, and were correlated with increased activity of blood-brain barrier degrading cyclophilin A-matrix metalloproteinase-9 pathway 19 in cerebrospinal fluid. Our findings suggest that blood-brain barrier breakdown contributes to APOE4 associated cognitive decline, does so independently of Alzheimer’s disease pathology, and might be a therapeutic target in APOE4 carriers. The analysis of blood-brain barrier (BBB) permeability by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) 7,8 (Fig. 1a; see Methods) in 245 participants (Extended Data Table 1) indicated BBB breakdown in the hippocampus (HC) and parahippocampal gyrus (PHG) in cognitively normal APOE4 (ε3/ε4 and ε4/ε4) carriers compared to cognitively normal APOE3 homozygotes (ε3/ε3) both with clinical dementia rating (CDR) score of 0. The BBB breakdown in HC and PHG in APOE4 carriers further increases with cognitive impairment at CDR=0.5 (Fig. 1b–d). This increase was independent of cerebrospinal fluid (CSF) Aβ and tau changes (Fig. 1e–h), i.e., whether individuals were Aβ+ or Aβ− and pTau+ or pTau− using the accepted cut-off values 7,24,25 (see Methods), where Aβ+ and pTau+ status indicates classical AD pathways 23 . In contrast, APOE3 carriers developed less pronounced BBB changes in HC and PHG with cognitive impairment (Fig. 1b–d). No significant BBB changes were found in other gray or white matter brain regions in APOE4 carriers compared to APOE3 homozygotes, except for increased BBB permeability in the caudate nucleus, and minor leaks in the frontal cortex and corpus callosum in cognitively normal APOE4 carriers (Extended Data Fig. 1). These findings hold when cognitive dysfunction was evaluated by neuropsychological performance (see Methods) (Extended Data Figs. 2 and 3). HC and PHG volumes decreased with cognitive impairment in APOE4, but not APOE3 carriers (Fig. 1i–k). The BBB breakdown in HC and PHG in APOE4 carriers, but not APOE3 homozygotes, remained a highly significant predictor of cognitive impairment after statistically controlling for age, sex, education, CSF Aβ and pTau status, and HC and PHG volumes, as shown by the estimated marginal means from the analysis of covariance (ANCOVA) models (Fig. 1l,m), and confirmed by logistic regression models (Supplementary Information Table 1). The BBB dysfunction (Fig. 1c,d,l,m) preceded brain atrophy (Fig. 1j,k) and was independent of systemic vascular risk factors (Extended Data Fig. 4). Because Aβ and tau can both lead to blood vessel abnormalities and BBB breakdown 3,26,27 , in a subset of 74 and 96 participants (Extended Data Tables 2a,b), respectively, we studied whether BBB disruption in APOE4 carriers is downstream to amyloid and tau accumulation. Voxel-based analysis of brain uptake of amyloid by positron emission tomography (PET) indicated a substantially higher accumulation in the orbital frontal cortex (OFC) in cognitively normal APOE4 carriers compared to APOE3 homozygotes, as reported 28 , but failed to detect accumulation of tau tracer in either APOE4 or APOE3 carriers (Extended Data Fig. 5a–d). To determine how BBB permeability relates to amyloid and tau accumulation, we selected 5-mm thick coronal slices in regions of interest including the HC and PHG, where BBB disruption is seen first in APOE4 carriers compared to APOE3 homozygotes (Fig. 1b,d,e), OFC, where amyloid accumulation develops initially in APOE4 carriers, and inferior temporal gyrus (ITG), a region affected early by tau pathology 29 (Extended Data Fig. 5b,d,e). Brain uptake of amyloid and tau tracers (after correction for the choroid plexus off-target binding for tau tracer; see Methods and Extended Data Fig. 5f,g) indicated no difference between APOE4 and APOE3 carriers in HC, although uptake of both tracers was modestly increased (Fig. 2a,b). BBB disruption in HC in APOE4 carriers compared to APOE3 homozygotes (Fig. 2c) was consistent with our findings in the larger cohort (Fig. 1b,c). There was no difference in amyloid and tau accumulation in PHG between APOE4 carriers and APOE3 homozygotes, despite BBB disruption in APOE4 carriers (Fig. 2d–f). There was a higher amyloid accumulation in OFC in cognitively normal APOE4 compared to APOE3 carriers (Fig. 2g,h), but no changes in BBB integrity (Fig. 2g,i). There was no change in ITG tau accumulation or BBB integrity in APOE4 compared to APOE3 carriers (Fig. 2j–l). Altogether, these data suggest that BBB disruption in HC and PHG in APOE4 carriers is independent of AD pathology, and that BBB breakdown in APOE4 carriers starts in the medial temporal lobe, a region responsible for memory encoding and other cognitive functions. Elevated cerebrospinal fluid (CSF) levels of soluble platelet-derived growth factor receptor-β (sPDGFRβ) in humans and animal models indicate pericyte injury linked to BBB breakdown 7,8,30 and cognitive dysfunction 7,30 . Using a median split for visual display of the CSF sPDGFRβ baseline levels from 350 participants (see Methods), we stratified all participants into two groups, with low CSF sPDGFRβ levels (0-600 ng/mL, grey), and high sPDGFRβ levels (600-2,000 ng/mL, blue) (Fig. 3a). Our data in 146 APOE4 carriers and APOE3 homozygotes evaluated by cognitive exams over two-year intervals up to 4.5 years from baseline show that participants with higher baseline CSF sPDGFRβ levels exhibited accelerated cognitive decline on global mental status exam and global cognitive composite z-scores, which remained significant after controlling for CSF Aβ and tau status (Fig. 3b,c; Supplementary Information Table 2). When stratified by APOE status, higher baseline CSF sPDGFRβ levels in APOE4 carriers predicted cognitive decline after controlling for CSF Aβ and pTau status (Fig. 3d,e; Supplementary Information Table 3), but did not predict decline in APOE3 homozygotes (Fig. 3f,g; Supplementary Information Table 4). The increase in CSF sPDGFRβ with cognitive impairment was also found on cross-sectional CDR analysis in APOE4, but not APOE3 carriers (Fig. 4a–b; Extended Data Table 3; Supplementary Information Table 5). Increased CSF levels of sPDGFRβ in APOE4 carriers correlated with increases in BBB permeability in HC and PHG (Fig. 4c,d), and elevated levels of molecular biomarkers of BBB breakdown including albumin CSF/plasma quotient, and CSF fibrinogen and plasminogen (Fig. 4e–g). Next, we focused on proinflammatory cyclophilin A-matrix metalloproteinase-9 (CypA-MMP9) pathway that when activated by brain capillary pericytes in APOE4, but not APOE3, knock-in mice leads to MMP9-mediated BBB breakdown, which in turn leads to neuronal stress related to leaked blood-derived neurotoxic proteins followed by neuronal dysfunction and loss of synaptic proteins 19 . Activation of CypA-MMP9 pathway was also noted by brain issue analysis in degenerating brain capillary pericytes in APOE4 compared to APOE3 AD carriers 16 . Here, we found that living APOE4 carriers, but not APOE3 homozygotes, develop an increase in CypA CSF levels with cognitive impairment (Fig. 4h,i), which correlated with elevated CSF sPDGFRβ (Fig. 4j). APOE4, but not APOE3 carriers, had also elevated MMP9 CSF levels with cognitive impairment (Fig. 4k), which correlated with elevated CSF CypA levels (Fig. 4l), suggesting that activation of CypA-MMP9 pathway in APOE4 carriers correlates with pericyte injury similarly as shown in animal models 19 . There were no differences in glia, other inflammatory, and endothelial cell injury CSF biomarkers between impaired and unimpaired APOE4 and APOE3 participants, but there was an increase in neuron-specific enolase with cognitive impairment in APOE4 carriers confirming neuronal stress (Extended Data Fig. 6), consistent with HC and PHG atrophy (Fig. 1j,k). Studies in APOE knock-in mice and mouse pericytes have shown that apoE3, but not apoE4, inhibits CypA via low-density lipoprotein receptor-related protein 1 transcriptionally, which in turn inhibits MMP9 transcriptionally 19 . Consistent with the mouse data, human induced pluripotent stem cells-derived APOE4 (ε4/ε4) compared to APOE3 (ε3/ε3) pericytes had substantially higher levels of CypA and secreted MMP9 (Fig. 4m,n) suggesting that apoE may control the CypA-MMP9 pathway in human pericytes in an isoform-specific manner similar as in mouse models 19 . APOE4 compared to APOE3 reduced CSF Aβ1-42 and increased CSF pTau levels with cognitive impairment (Extended Data Fig. 7) as reported 23 , which remained significant after controlling for CSF sPDGFRβ levels (Extended Data Fig. 7). All together these findings support that Aβ and tau pathways operate independently of the BBB breakdown pathway during early stages of cognitive impairment in APOE4 carriers. In summary, we show that 1) BBB breakdown contributes to cognitive decline in APOE4 carriers independent of AD pathology; 2) high baseline CSF levels of sPDGFRβ can predict future cognitive decline in APOE4 carriers; and 3) APOE4, but not APOE3, activates the CypA-MMP9 pathway in CSF, which may lead to accelerated BBB breakdown causing neuronal and synaptic dysfunction 19 . Since blockade of the CypA-MMP9 pathway in APOE4 knock-in mice restores BBB integrity followed by normalization of neuronal and synaptic functions 19 , one can consider that CypA inhibitors (some of which have been used in humans for non-neurological applications 31 ) might also suppress the CypA pathway in cerebral blood vessels in APOE4 carriers that should improve cerebrovascular integrity, and the associated neuronal and synaptic deficits, slowing down cognitive impairment. Methods Study Participants Participants were recruited from three sites, including the University of Southern California (USC), Los Angeles, CA, Washington University (WashU), St. Louis, MO, and Banner Alzheimer’s Institute Phoenix, AZ and Mayo Clinic Arizona, Scottsdale, AZ as a single site. At the USC site, participants were recruited through the USC Alzheimer’s Disease Research Center (ADRC): combined USC and the Huntington Medical Research Institutes (HMRI), Pasadena, CA. At the WashU site, participants were recruited through the Washington University Knight ADRC. At Banner Alzheimer’s Institute and Mayo Clinic Arizona site, participants were recruited through the Arizona Apolipoprotein E (APOE) cohort. The study and procedures were approved by the Institutional Review Boards of USC ADRC, Washington University Knight ADRC, and Banner Good Samaritan Medical Center and Mayo Clinic Scottsdale indicating compliance with all ethical regulations. Informed consent was obtained from all participants prior to study enrollment. All participants (n=435) underwent neurological and neuropsychological evaluations performed using the Uniform Data Set (UDS) 32 and additional neuropsychological tests, as described below, and received a venipuncture for collection of blood for biomarker studies. A lumbar puncture (LP) was performed in 350 participants (81%) for collection of cerebrospinal fluid (CSF). The dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for assessment of blood-brain barrier (BBB) permeability was performed in 245 participants (56%) who had no contraindications for contrast injection. Both LP and DCE-MRI were conducted in 172 participants. Among the 245 DCE-MRI participants, 74 and 96 were additionally studied for brain uptake of amyloid and tau PET radiotracers, respectively, as described below. All biomarker assays, MRI, and PET scans were analyzed by investigators blinded to the clinical status of the participant. Participant Inclusion and Exclusion Criteria Included participants (≥45 years of age) were confirmed by clinical and cognitive assessments to be either cognitively normal or at the earliest symptomatic stage of Alzheimer disease. A current or prior history of any neurological or psychiatric conditions that might confound cognitive assessment, including organ failure, brain tumors, epilepsy, hydrocephalus, schizophrenia, and major depression, was exclusionary. Participants were stratified by APOE genotype as APOE4 carriers (ε3/ε4 and ε4/ε4) and APOE4 non-carriers (ε3/ε3) also defined as APOE3 homozygotes who were cognitively normal or with mild cognitive dysfunction, as determined by clinical dementia rating (CDR) scores 33 and the presence of cognitive impairment in one or more cognitive domains based on comprehensive neuropsychological evaluation including performance on ten neuropsychological tests assessing memory, attention/executive function, language and global cognition. For all analyses individuals with ε3/ε4 and ε4/ε4 alleles were pooled together in a single APOE4 group, as we did not find in the present cohort consisting of 82-86% ε3/ε4 and 14-18% ε4/ε4 participants (depending on the outcome measure) a significant difference between the two versus one ε4 allele for the studied parameters including the BBB permeability unidirectional transfer constant Ktrans values and sPDGFRβ CSF values (see statistical section below). Individuals have been additionally stratified by Aβ and pTau CSF analysis as either Aβ-positive (Aβ1-42+, 190 pg/mL), or pTau-positive (pTau+, >78 pg/mL) or pTau-negative (pTau−, 1 standard deviation (SD) below norm-referenced values on two or more tests within a single cognitive domain or three or more tests across cognitive domains 36 . Prior studies have established improved sensitivity and specificity of these criteria relative to those employing a single test score, as well as adaptability of this diagnostic approach to various neuropsychological batteries 36,37 . Participants were excluded from cognitive domain analyses if they had less than 90% complete neuropsychological test data (i.e., 53, 24, and 82 participants were excluded for MRI, PET, and CSF analyses, respectively). Included participants were classified as 0, 1, or 2+ based on the number of cognitive domains with two or more impaired test scores. Test battery specifics for each UDS version and recruitment site are as follows. i) Global cognition: MMSE for UDS version 2 38 and MoCA for UDS version 3 39 . ii) Memory: The Logical Memory Story A Immediate and Delayed free recall tests [modified from the original Wechsler Memory Scales – Third Edition (WMS-III)] for UDS version 2 and the Craft Stories Immediate and Delayed free recall for UDS version 3. For supplemental tests the USC participants underwent the California Verbal Learning Test – Second Edition (CVLT-II) and the Selective Reminding Test (SRT) sum of free recall trials. Norm-referenced scores for these supplemental test scores were derived from a nationally representative sample published with the test manual (CVLT-II) 40 and in studies of normally aging adults (SRT). iii) Attention and executive function: The Trails A, Trails B, and Wechsler Adult Intelligence Scale - Revised (WAIS-R) Digit Span Backwards tests for UDS version 2 and the Trails A, Trails B and Digit Span Backwards tests for UDS version 3. iv) Language: The Animal Fluency, Vegetable Fluency, and Boston Naming Tests for UDS version 2 and Animal Fluency, Vegetable Fluency, and Multilingual Naming Test (MINT) for UDS version 3. Magnetic Resonance Imaging and Analysis The MRI data sets were obtained at Mark and Mary Stevens Neuroimaging and Informatics Institute of USC and Washington University of St. Louis. We developed a standardized high-resolution 3T MR imaging brain scan protocol. For USC site, a Siemens 3T Prisma scanner was used with a product 32-channel head receive coil and body transmit coil. For WashU site, a Siemens 3T mMR with 20-channel head coil and Siemens 3T Vida with 64-channel head coil were used. Anatomical coronal spin echo T2-weighted scans were first obtained through the hippocampi (TR/TE 8020/50 ms, NEX = 1, slice thickness 2 mm with 2 mm gap between slices, FOV = 175 x 175 mm, matrix size = 448 x 448). Baseline coronal T1-weighted maps were then acquired using a T1-weighted 3D volumetric interpolated breath-hold sequence (VIBE) sequence and variable flip angle method using flip angles of 2°, 5°, 10°, 12°, and 15°. Coronal DCE-MRI covering the hippocampi and temporal lobes were acquired using a T1-weighted 3D VIBE sequence (FA = 15°, TR/TE = 5.14/2.18 ms, NEX = 1, slice thickness 5 mm with no gap, FOV 175 x 175 mm, matrix size 320 x 320, voxel size was 0.550 x 0.550 x 5 mm3). This sequence was repeated for a total of 16 min with an approximate time resolution of 15.4 sec. Gadolinium-based contrast agent (GBCA), Gadoterate meglumine (Dotarem®, Guerbet, France) (0.05 mmol/kg), was administered intravenously into the antecubital vein using a power injector, at a rate of 3 mL/s followed by a 25 mL saline flush, 30 s into the DCE scan. The standardization and optimization of the MRI protocol required several tests performed on a phantom. Specifically, scanner characterization and calibration sequences including B0, T1, and variable flip-angle mapping were implemented, optimized, and applied. After the achievement of good results in terms of quality control and reproducibility, we standardized and employed the same pre-contrast and dynamic T1-weighted protocols at both USC and Washington University sites. Of note, all the other MR sequences were identical too on both scanners. In order to minimize the inter-site variability, the entire MRI protocol including the anatomical and DCE pulse sequences were 100% mirrored from one site to another. To minimize inter-site variability, the same contrast agent Gadoterate meglumine (Dotarem®) were injected to participants at the same concentration (0.05 mmol/kg). Finally, the same exact pre- and post-processing analysis pipeline was applied for both sites which includes T1 multi-FA mapping using linear fitting and Patlak-based DCE modeling using the arterial input function determined in each individual from the internal carotid artery. Applying all the above cited factors significantly limited inter-site variability. The consistency of the results from the two sites has been additionally confirmed by our previous publication 7 . In brief, we performed the analysis of the combined DCE datasets from both USC and WashU sites, and additionally site-specific analysis for each of the two sites separately, which showed no statistically significant differences across sites. Recently, we invited a subset of 52 participants for an additional T1-weighted scan without contrast (using the same scanner and same MR pulse sequences) after their first DCE-MRI 41 and measured both B0 and T1 values at 2-year interval. This study showed that the results were unchanged and consistent across the scans, supporting minimal intra-site variability. Quantification of the Blood-Brain Barrier Permeability See Supplementary Information, Supplementary Methods. Quantification of Regional Brain Volumes HC and PHG morphometry were performed using the FreeSurfer (v5.3.0) software package 42 (http://surfer.nmr.mgh.harvard.edu/), as previously performed 7 . HC and PHG were segmented using FreeSurfer Desikan-Killiany and subcortical atlases 43,44 . Then, regional volumes (mm3) were derived accordingly. The technical details of this procedure are described in previous publications 45,46 . Data processing and visualization were performed using the Laboratory of Neuro Imaging (LONI) pipeline system (http://pipeline.loni.usc.edu) and Quantitative Imaging Toolkit 47–49 . Positron Emission Tomography and Analysis The PET image acquisition was performed at the Molecular Imaging Center of USC or Mallinckrodt Institute of Radiology of WashU. Amyloid and tau PET studies were conducted using 18F-Florbetaben (FBB) or 18F-Florbetapir (FBP) and 18F-Flortaucipir (AV1451), respectively. FBB (Life Molecular Imaging, Inc.) was obtained from SOPHIE, Inc. for USC site, while FBP was provided by Eli Lilly and Company for WashU site. For all amyloid PET analysis FBP and FBB datasets were combined. AV1451 was provided by Avid Radiopharmaceuticals, Inc. for USC site and was produced by the Mallinckrodt Institute of Radiology for WashU site. A Siemens Biograph 64 PET scanner was used at USC site. At WashU site, FBP scans were acquired on a Siemens mMR and AV1451 scans were acquired on a Siemens Biograph mCT. The mCT session was used for attenuation correction of the mMR scans. Participants were injected with 300 MBq (±10%) of FBB or 370 MBq (±10%) of FBP. FBB and FBP images were acquired from 90 to 110 min and 50 to 70 min, respectively, after injection in accordance with the manufacturers’ recommendation. Individuals who participated in amyloid and tau PET studies also had their DCE-MRI scan within a 2.2 ± 0.9 and 2.1 ± 0.6 month period of their amyloid and tau PET scans, respectively. Briefly, a computed tomography (CT) scan was performed first for attenuation correction before each PET imaging session. The downloaded PET images from FBB, FBP, and AV1451 tracers were processed by using standard uptake value maps (SUV in g/mL). All PET images were co-registered to structural high-resolution 3D T1-weighted Magnetization Prepared Rapid Acquisition Gradient Echo (MP-RAGE) MRI images using FSL-FLIRT (FMRIB’s Linear Image Registration Tool) 50 . FreeSurfer-segmented cerebellum was used as a reference tissue to normalize for both amyloid and tau 51 . After co-registration of PET images into an anatomical reference image (MNI152 standard-space), the Statistical Parametric Mapping (SPM12) was used for group comparison in a voxel-by-voxel basis. Age at time of PET imaging session, sex, and education were introduced in a multiple regression model as covariates. Level of significance was set to p 190 pg/mL) using the accepted cutoff values as previously reported for the MSD 6E10 Aβ peptide assay 24 . Tau Phosphorylated tau (pT181) was determined by ELISA (Cat. No. 81581, Innotest®, Fujirebio US, Inc., Malvern, PA). Participants were stratified based on CSF analysis as either pTau181-positive (pTau+, >78 pg/mL) or pTau181-negative (pTau−, <78 pg/mL), using the accepted cutoff value as previously reported 25 . Human Induced Pluripotent Stem Cells (iPSCs) iPSC lines were generated by reprogramming of APOE ε4/ε4 and APOE ε3/ε3 control and AD donor skin fibroblasts as recently reported 54 . Reprogramming was performed using integration-free Sendai virus vectors and passaged cells to passage 15 and confirmed normal karyotype. hiPSCs were maintained on Matrigel (Corning) in mTeSR1 (Catalog no. 85850, StemCell Technologies, Vancouver, BC, Canada) supplemented with 10 ng/mL FGF2 StemBeads (StemCultures) or mTeSR plus (StemCell Technologies) every other day. Differentiation of iPSCs into Pericytes Differentiation of iPSCs into pericytes was carried out as described previously 55 . Briefly, iPSCs were dissociated with ReLeSR (catalog no. 05872, StemCell Technologies) and seeded at 55,000 cells/cm2 in Essential 8 medium (Catalog no. A1517001, ThermoFisher, Waltham, MA, USA) supplemented with ROCK inhibitor Y-27632 (10 μM, catalog no. 72304, StemCell Technologies) on Matrigel (0.5 mg/6-well plate, Catalog no. 354230, Corning, NY, USA). After 24 hours incubation, the iPSCs were switched into STEMdiff Mesoderm Induction Medium (MIM, Catalog no. 05221, StemCell Technologies) for 5 days with daily medium change. On day 6 of MIM treatment, the cells were plated on Matrigel at 25,000 cells/cm2 in Pericyte Medium (Catalog no. 1201, ScienCell, Carlsbad, CA, USA) for an additional 7 days. The differentiated cells were dissociated with Accutase (catalog no. 07920, Stemcell Technologies). Following incubation with human PDGFRβ biotinylated antibody (Catalog no. BAF385, R&D Systems, Minneapolis, MN, USA), the cells were incubated with anti-biotin microbeads (Catalog no. 130-090-485, Miltenyi Biotec, Bergisch Gladbach, NRW, Germany) and magnetically sorted using MACS LS columns (Catalog no. 130-042-401, Miltenyi Biotec) following the manufacturer’s instructions. Sorted pericytes were plated at a density of 25,000 cells/cm2 on Matrigel-coated coverslips for immunocytochemistry analyses or ploy-L-lysine-coated six-well culture plates for Western blot analyses. Differentiated pericytes were positive for pericyte markers PDGFRβ, CD13, and NG2, and negative for endothelial marker CD31, astrocytic marker GFAP, and microglial marker CD11b. Statistical Analyses Prior to performing statistical analyses, we first screened for outliers using the Grubbs’ test, also called the ESD method (Extreme Studentized Deviate), applying a significance level of α=0.01 (https://www.graphpad.com/quickcalcs/grubbs1/). For each of the outliers identified, a secondary index of outlier influence was applied using the degree of deviation from the mean (greater than +/− 3 SDs) 56 . Using these stringent criteria, a total of 5 outliers one each in main Figure panels 1j, 1k and 2j, and one each in Extended Data Figs. 6a and 6b, were removed from analyses, as indicated in the legends of these figures. Continuous variables were also evaluated for departures from normality through quantitative examination of skewness and kurtosis, in addition to visual inspection of frequency distributions. Where departures of normality were identified, log10-transformations were applied, and distribution normalization was confirmed prior to parametric analyses. This has been done for main Figs. 4h and 4k, and Extended Data Figs. 7a, 7b, 7d, and 7e. Since use of log10-transformations accounts for any non-normality this obviated the need for outliers exclusion. DCE-MRI Ktrans, and CSF sPDGFRβ and CypA Regional DCE-MRI Ktrans values and CSF sPDGFRβ, CypA and MMP9 levels were compared across the entire sample stratified by APOE status. Since in APOE4 group relatively small number of participants were homozygous ε4/ε4 compared to heterozygous ε3/ε4, i.e., 14% for DCE-MRI analysis, and 18% for sPDGFRβ analysis, and initial comparisons between ε4/ε4 and ε3/ε4 carriers did not show any significant differences in regional HC and PHG DCE-MRI Ktrans values (CDR 0, p HC=0.19 and p PHG=0.54 (PHG); CDR 0.5, p HC=0.22 and p PHG=0.84) or CSF sPDGFRβ levels (CDR 0, p=0.23; CDR 0.5, p=0.47), all subsequent analyses combined APOE4 carriers (ε3/ε4 and ε4/ε4), and compared these participants to APOE3 carriers (ε3/ε3) stratified by cognitive impairment status (CDR 0 vs 0.5 and 0 vs 1 vs 2+ cognitive domains impairment using analysis of covariance (ANCOVA) with false discovery rate (FDR) correction for multiple comparisons (see details below). For CDR analyses, model covariates included age, sex, and education. Cognitive domain impairment was determined using age, sex, and education-corrected values, so these covariates were not additionally included in the analyses. Additional post-hoc ANCOVA analyses evaluated whether observed differences remained significant after stratifying APOE4 carriers by CSF Aβ1-42 and pTau status, and after statistically controlling for CSF Aβ1-42 and pTau status and regional brain volume in APOE4 non-carriers and carriers. These findings were also confirmed by hierarchical logistic regression models using the same covariates. PET AD Biomarkers In a subset of participants who underwent amyloid and tau PET imaging together with DCE-MRI studies, we used ANCOVA models controlled for age, sex and education to compare regional amyloid and tau ligand binding and DCE-MRI values in a set of APOE4 non-carriers and carriers within a priori regions of interest, based on prior imaging studies, to determine whether distinct regional pathologies were observed by APOE4 carrier status. Baseline CSF sPDGFRβ as a continuous predictor of cognitive decline For linear mixed model analysis, baseline CSF sPDGFRβ was a continuous predictor of demographically-corrected global cognitive change over 2-year follow up intervals, controlling for CSF Aβ1-42 and CSF pTau status. Global cognition was indexed by age-, sex-, and education-corrected z-scores on mental status exam (MMSE or MoCA) and as the global cognitive composite of all age-, sex-, and education-corrected neuropsychological test z-scores (see above for list of neuropsychological tests). Time was modeled with date of lumbar puncture as baseline (T0) with two follow up intervals of 2 years each (T1-2). Additional analyses confirmed all findings when time was modeled as time since baseline, with date of lumbar puncture as baseline (T0) and follow up as annual intervals (T1-n). All longitudinal mixed models treated CSF sPDGFRβ as a continuous predictor. Although we have previously established CSF sPDGFRβ as a marker of pericyte injury 7,8,57 , the optimal cutoff value for abnormal CSF sPDGFRβ levels indicative of pericyte injury remains unknown. Autopsy studies are required to determine optimal in vivo biomarker cutoff values predictive of gold-standard neuropathological measures, such as studies conducted for CSF and PET markers of amyloid and tau. Given the lack of available autopsy data relating CSF sPDGFRβ to neuropathological markers of pericyte injury, we chose to divide participants by CSF sPDGFRβ values using median split for the purposes of visual display only (higher CSF sPDGFRβ was above sample median and lower CSF sPDGFRβ was below sample median). The median split was not used in statistical analyses and was only used for the purpose of visual display (see Figure 3a) for statistical parameters from analyses using CSF sPDGFRβ as a continuous predictor of cognitive decline). Correlational Analyses Pearson product moment correlations were used to evaluate relationships among CSF sPDGFRβ, CypA, MMP9, fibrinogen, plasminogen and hippocampal and parahippocampal BBB Ktrans levels among APOE4 carriers. Multiple Comparison Correction and Missing Data Given the large number of analyses, FDR-correction was applied to p-values for primary study outcomes (i.e., DCE-MRI, sPDGFRβ) evaluated in the entire sample by APOE4 carrier status and CDR status using the Benjamini-Hochberg method 58 in ANCOVA and logistic regression models controlling for age, sex, education, brain volume, and CSF Aβ1-42 and pTau status (for DCE-MRI analyses). Post-hoc confirmatory analyses in participant subsets further evaluating independence of CSF and PET markers of amyloid and tau, evaluation of mechanistic markers (i.e., CypA and MMP9), and longitudinal analysis of predictive value of CSF sPDGFRβ were not multiple comparison corrected. For longitudinal data with variable follow up, we utilized linear mixed model analyses with the account for missing data via the missing at random assumption. Extended Data Extended Data Figure 1. Regional BBB Ktrans constant in eight additional brain regions in APOE4 carriers and non-carriers (APOE3) with CDR status 0 and 0.5. DCE-MRI BBB permeability, Ktrans constant, in the inferior temporal gyrus (ITG, a), superior frontal gyrus (SFG, b), caudate nucleus (CN, c), thalamus (Thal, d), striatum (Str, e), subcortical watershed normal-appearing white matter (Subcort. WS NAWM, f), corpus callosum (CC, g), and internal capsule (IC, h) in CDR 0 APOE3 (black, n=128) and APOE4 (red, n=68) carriers, CDR 0.5 APOE3 (black, n=14) and APOE4 (red, n=25) carriers. Violin plot continuous lines indicate median values and dotted lines indicate interquartile range. Significance by ANCOVAs for main effects and post-hoc comparisons controlling for age, sex, and education. Extended Data Figure 2. BBB breakdown in the hippocampus and parahippocampal gyrus in APOE4 carriers increases with cognitive domain impairment. (a,b) DCE-MRI BBB permeability, Ktrans constant, in the hippocampus (HC, a) and parahippocampal gyrus (PHG, b) in individuals with 0 cognitive domain impaired that are APOE3 (black, n=70) and APOE4 (red, n=40) carriers, 1 cognitive domain impaired that are APOE3 (black, n=18) and APOE4 (red, n=21) carriers, and 2+ cognitive domains impaired that are APOE3 (black, n=7) and APOE4 (red, n=12) carriers. (c,d) Ktrans (estimated marginal means ± SEM from ANCOVA models corrected for age, sex, education, CSF Aβ1-42 and pTau status, and HC and PHG volumes) in the HC (c) and PHG (d) in individuals with 0 cognitive domain impaired that are APOE3 (black, n=70) and APOE4 (red, n=40) carriers, 1 cognitive domain impaired that are APOE3 (black, n=18) and APOE4 (red, n=21) carriers, and 2+ cognitive domains impaired that are APOE3 (black, n=7) and APOE4 (red, n=12) carriers. Panels a and b: Violin plot continuous lines indicate median values and dotted lines indicate interquartile range. Significance by ANCOVA for main effects and post-hoc comparisons controlling for age, sex, and education. All ANCOVA omnibus tests remained significant at false discovery rate threshold of 0.05. Extended Data Figure 3. Regional BBB Ktrans constant in eight additional brain regions in APOE4 carriers and non-carriers (APOE3) with different degree of cognitive domain impairment. DCE-MRI BBB permeability, Ktrans constant, in the inferior temporal gyrus (ITG, a), superior frontal gyrus (SFG, b), caudate nucleus (CN, c), thalamus (Thal, d), striatum (Str, e), subcortical watershed normal-appearing white matter (Subcort. WS NAWM, f), corpus callosum (CC, g), and internal capsule (IC, h) in individuals with 0 cognitive domain impaired that are APOE3 (black, n=70) and APOE4 (red, n=40) carriers, 1 cognitive domain impaired that are APOE3 (black, n=18) and APOE4 (red, n=21) carriers, and 2+ cognitive domains impaired that are APOE3 (black, n=7) and APOE4 (red, n=12) carriers. Violin plot continuous lines indicate median values and dotted lines indicate interquartile range. Significance tests from ANCOVAs for main effects and post-hoc comparisons controlling for age, sex, and education. Extended Data Figure 4. Regional BBB Ktrans constant in all studied brain regions in APOE4 carriers and non-carriers (APOE3) in relation to vascular risk factors. DCE-MRI BBB permeability, Ktrans constant, in the hippocampus (HC, a), parahippocampal gyrus (PHG, b), inferior temporal gyrus (ITG, c), superior frontal gyrus (SFG, d), caudate nucleus (CN, e), thalamus (Thal, f), striatum (Str, g), subcortical watershed normal-appearing white matter (Subcort. WS NAWM, h), corpus callosum (CC, i), and internal capsule (IC, j) in APOE3 (black, n=80) and APOE4 (red, n=42) carriers with 0-1 vascular risk factors (VRFs), and APOE3 (black, n=58) and APOE4 (red, n=51) carriers with 2+ VRFs. Violin plot continuous lines indicate median values and dotted lines indicate interquartile range. Significance by ANCOVAs for main effects and post-hoc comparisons controlling for age, sex, and education (ns=non-significant). Extended Data Figure 5. Amyloid and tau PET analysis in APOE4 carriers and correction of 18F-AV1451 off-target binding in the choroid plexus. All studies were performed in individuals with clinical dementia rating score 0. Amyloid and tau PET studies were conducted using 18F-Florbetaben (FBB) or 18F-Florbetapir (FBP), and 18F-Flortaucipir (AV1451), respectively. For amyloid PET data analysis, FBP and FBB datasets were combined. (a) Uptake of amyloid tracers by the orbital frontal cortex (OFC) in APOE4 (n=29) relative to APOE3 (n=45) carriers (voxel-wise 2-sample one-tailed t-tests). (b) Representative amyloid PET Standardized Uptake Value Ratios (SUVR) maps from APOE3 homozygote (APOE3) (upper) and APOE4 carrier (APOE4) (lower). Slices 1 and 2, regions-of-interest (ROIs) for amyloid PET and BBB DCE-MRI scans (see e). Arrow, amyloid tracer uptake by OFC. The APOE3 and APOE4 representative images used FBP. (c) Uptake of tau tracer shows undetectable tau accumulation in APOE3 (n=60) or APOE4 (n=37) carriers (voxel-wise 2-sample one-tailed t-tests). (d) Representative tau PET SUVR maps from APOE3 (upper) and APOE4 (lower) carriers. Slice 1 and slice 1’, ROIs for tau PET and BBB DCE-MRI scans (see e). (e) Coronal 3D scans of regions studied in main Figure 2: hippocampus (HC; red), parahippocampal gyrus (PHG; green), medial orbital frontal cortex (OFC; yellow), and inferior temporal gyrus (ITG; blue). (f) Correction of 18F-AV1451 off-target binding in the choroid plexus: Step 1) Hippocampus (HC) masks were generated from the 3D T1-weighted MP-RAGE; Step 2) Choroid plexus (CP) masks were generated from the T1-weighted VIBE image post-GBCA (flip angle = 15°) image; Step 3) HC and CP masks were overlaid (arrowheads, red); and Step 4) CP overlap with HC masks (arrowheads, yellow) were subtracted to obtain CP-corrected HC tau PET signal after adding 6-mm voxel size on top of CP mask generated from DCE data. (g) Representative images of HC tau PET signal before (left) and after (right) applying the CP correction (arrows and white dotted lines = overlap between HC and CP). Extended Data Figure 6. CSF biomarkers of glia and inflammatory response and endothelial and neuronal cell injury in APOE4 carriers and non-carriers (APOE3). (a) CSF astrocytic S100 calcium-binding protein B (S100B) levels in CDR 0 APOE3 (black, n=77) and APOE4 (red, n=41) carriers, and CDR 0.5 APOE3 (black, n=39) and APOE4 (red, n=32) carriers. (b) CSF interleukin 6 (IL6) levels in CDR 0 APOE3 (black, n=71) and APOE4 (red, n=47) carriers, and CDR 0.5 APOE3 (black, n=34) and APOE4 (red, n=32) carriers. (c) CSF interferon gamma (IFNγ) levels in CDR 0 APOE3 (black, n=54) and APOE4 (red, n=29) carriers, and CDR 0.5 APOE3 (black, n=25) and APOE4 (red, n=17) carriers. (d) CSF interleukin 1β (IL1β) levels in CDR 0 APOE3 (black, n=43) and APOE4 (red, n=18) carriers, and CDR 0.5 APOE3 (black, n=17) and APOE4 (red, n=13) carriers. (e) CSF tumor necrosis factor α (TNFα) levels in CDR 0 APOE3 (black, n=70) and APOE4 (red, n=46) carriers, and CDR 0.5 APOE3 (black, n=34) and APOE4 (red, n=32) carriers. (f) CSF soluble intercellular adhesion molecule 1 (sICAM1) levels in CDR 0 APOE3 (black, n=77) and APOE4 (red, n=40) carriers, and CDR 0.5 APOE3 (black, n=39) and APOE4 (red, n=33) carriers. (g) CSF Neuron-Specific Enolase (NSE) levels in CDR 0 APOE3 (black, n=47) and APOE4 (red, n=32) carriers, and CDR 0.5 APOE3 (black, n=29) and APOE4 (red, n=29) carriers. Violin plot continuous lines indicate median values and dotted lines indicate interquartile range. Panels a and b had one outlier each, which were removed prior to statistical analysis using methods described in Statistical Analyses section. Significance by ANCOVAs for main effects and post-hoc comparisons controlling for age, sex, and education (ns=non-significant). Extended Data Figure 7. Lower CSF Aβ1-42 and increased pTau levels in APOE4 carriers with cognitive impairment. (a) CSF Aβ1-42 levels in CDR 0 APOE3 (black, n=141) and APOE4 (red, n=83) and CDR 0.5 APOE3 (black, n=39) and APOE4 (red, n=41) carriers. (b) CSF Aβ1-42 levels in APOE3 (black, n=89) and APOE4 (red, n=55) carriers with 0 cognitive domain impaired, APOE3 (black, n=29) and APOE4 (red, n=31) carriers with 1 cognitive domain impaired, and APOE3 (black, n=17) and APOE4 (red, n=14) carriers with 2+ cognitive domains impaired. (c) CSF Aβ1-42 levels (estimated marginal means ± SEM from ANCOVA models corrected for age, sex, education, and CSF sPDGFRβ levels) in CDR 0 APOE3 (black, n=141) and APOE4 (red, n=83) and CDR 0.5 APOE3 (black, n=39) and APOE4 (red, n=41) carriers. (d) CSF pTau levels in CDR 0 APOE3 (black, n=141) and APOE4 (red, n=82) and CDR 0.5 APOE3 (black, n=39) and APOE4 (red, n=43) carriers. (e) CSF pTau levels in APOE3 (black, n=89) and APOE4 (red, n=56) carriers with 0 cognitive domain impaired, APOE3 (black, n=29) and APOE4 (red, n=30) carriers with 1 cognitive domain impaired, and APOE3 (black, n=17) and APOE4 (red, n=15) carriers with 2+ cognitive domains impaired. (f) CSF pTau levels (estimated marginal means ± SEM from ANCOVA models corrected for age, sex, education, and CSF sPDGFRβ levels) in CDR 0 APOE3 (black, n=141) and APOE4 (red, n=82) and CDR 0.5 APOE3 (black, n=39) and APOE4 (red, n=43) carriers. Violin plot continuous lines indicate median values and dotted lines indicate interquartile range. CSF Aβ1-42 and pTau values were log10-transformed due to non-normal distribution prior to statistical analysis. Significance tests from ANCOVAs for main effects and post-hoc comparisons controlling for age, sex, and education. Extended Data Figure 8. Full scans of western blots. Full scans of western blots for CypA shown in Figure 4 panel m (top). Extended Data Table 1. APOE3 and APOE4 participants studied for regional blood-brain barrier permeability changes by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). APOE Genotype APOE3 APOE4 APOE3 APOE4 Clinical Dementia Rating (CDR) 0 0 0.5 0.5 No. of participants 130 76 14 25 Age at MRI, years, Mean (SD) 69.9 (7.9) 67.3 (8.7) 73.8 (8.3) 69.4 (8.7) Female, % 62.3 57.9 42.9 56 Education, years, Mean (SD) 16.6 (2.7) 16.7 (2.0) 16.4 (2.5) 17.1 (2.1) Cognitive domain impairment, No. 0,1, 2+ 78, 17, 2 38, 16,4 6, 2,6 6, 8,9 Vascular risk factors, No. 0-1, 2+ 77, 53 38, 38 8,6 10, 15 Extended Data Table 2 a. APOE3 and APOE4 participants studied for regional amyloid brain accumulation by PET and blood-brain barrier permeability changes by DCE-MRI. FBB, participants who received 18F-Florbetaben; FBP, participants who received 18F-Florbetapir. b. APOE3 and APOE4 participants studied for regional tau brain accumulation by PET and blood-brain barrier permeability changes by DCE-MRI. APOE Genotype APOE3 APOE4 Clinical Dementia Rating (CDR) 0 0 No. of participants 45 29 No. of participants (FBB, FBP) 5, 40 9, 20 Age at amyloid PET, years, Mean (SD) 68.4 (7.5) 65.7 (8.8) Female, % 73.3 65.5 Education, years, Mean (SD) 16.7 (2.7) 16.5 (2.1) Cognitive domain impairment, No. 0,1, 2+ 24, 4, 0 17, 4, 1 Vascular risk factors, No. 0-1, 2+ 23, 22 19, 10 APOE Genotype APOE3 APOE4 Clinical Dementia Rating (CDR) 0 0 No. of participants 60 37 Age at tau PET, years, Mean (SD) 68.7 (7.9) 64.0 (8.4) Female, % 66.6 37.8 Education, years, Mean (SD) 16.5 (2.7) 16.6 (2.1) Cognitive domain impairment, No. 0,1, 2+ 27, 5, 1 15, 6, 1 Vascular risk factors, No. 0-1, 2+ 36, 24 23, 14 Extended Data Table 3. APOE3 and APOE4 participants studied for CSF sPDGFRβ levels. APOE Genotype APOE3 APOE4 APOE3 APOE4 Clinical Dementia Rating (CDR) 0 0 0.5 0.5 No. of participants 157 105 40 48 Age at LP, years, Mean (SD) 70.2 (8.9) 67.3 (9.9) 76.5 (7.3) 72.8 (8.1) Female, % 64 61 39 37 Education, years, Mean (SD) 16.5 (2.7) 16.3 (2.3) 15.7 (2.8) 16.2 (2.8) Cognitive domain impairment, No. 0,1, 2+ 91,20,2 62, 17,2 9, 8, 14 12, 16, 15 Vascular risk factors, No. 0-1, 2+ 100, 57 57, 48 22, 18 18, 30 Supplementary Material 1
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Apolipoprotein E and Alzheimer disease: pathobiology and targeting strategies
Yu Yamazaki, Na Zhao, Thomas Caulfield … (2019)
Polymorphism in the apolipoprotein E ( APOE ) gene is a major genetic risk determinant of late-onset Alzheimer disease (AD), with the APOE*ε4 allele conferring an increased risk and the APOE*ε2 allele conferring a decreased risk, relative to the common APOE*ε3 allele. Strong evidence from clinical and basic research suggests that a major pathway by which APOE4 increases the risk of AD is by driving earlier and more abundant amyloid pathology in the brains of APOE*ε4 carriers. The list of amyloid-β (Aβ)-dependent and Aβ-independent pathways that are known to be differentially modulated by APOE isoforms is increasing. For example, evidence is accumulating that APOE influences tau pathology, tau-mediated neurodegeneration, and microglial responses to AD-related pathologies. In addition, APOE4 is either pathogenic or shows reduced efficiency in multiple brain homeostatic pathways, including lipid transport, synaptic integrity and plasticity, glucose metabolism, and cerebrovascular function. Here, we review the recent progress in clinical and basic research into the role of APOE in AD pathogenesis. We also discuss how APOE can be targeted for AD therapy using a precision medicine approach.
Author and article information
Journal
Journal ID (nlm-ta): Antioxidants (Basel)
Journal ID (iso-abbrev): Antioxidants (Basel)
Journal ID (publisher-id): antioxidants
Title:
Antioxidants
Publisher:
MDPI
ISSN
(Electronic):
2076-3921
Publication date
(Electronic):
03
December
2020
Publication date Collection:
December
2020
Volume: 9
Issue: 12
Electronic Location Identifier: 1224
Affiliations
[1
]Department of Environmental & Occupational Health Sciences, University of Washington,
Seattle, WA 98195, USA;
jmarsi@
123456uw.edu
[2
]Unit of Neurosciences, Department of Medicine and Surgery, University of Parma, 43126
Parma, Italy;
mariapia.adorni@
123456unipr.it
[3
]Department of Food and Drug, University of Parma, 43124 Parma, Italy;
bianca.papotti@
123456unipr.it
[4
]Department of Morphology, Surgery and Experimental Medicine, University of Ferrara,
44121 Ferrara, Italy;
giovanni.zuliani@
123456unife.it
(G.Z.);
crvcrl@
123456unife.it
(C.C.)
Author notes
Author information
Judit Marsillach
https://orcid.org/0000-0002-3061-6266
Francesca Zimetti
https://orcid.org/0000-0002-6665-263X
Carlo Cervellati
https://orcid.org/0000-0003-4777-6300
Article
Publisher ID: antioxidants-09-01224DOI: 10.3390/antiox9121224
PMC ID: 7761753
PubMed ID: 33287338
SO-VID: 66936dc4-5730-438b-ab09-b73732f235fe
Copyright © © 2020 by the authors.
License:
Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).
History
Date
received
: 23
October
2020
Date
accepted
: 30
November
2020
Categories
Subject:
Review
Data availability: