Gender differences in white matter pathology and mitochondrial dysfunction in Alzheimer’s disease with cerebrovascular disease
© Gallart-Palau et al. 2016
Received: 30 October 2015
Accepted: 22 February 2016
Published: 17 March 2016
Dementia risk in women is higher than in men, but the molecular neuropathology of this gender difference remains poorly defined. In this study, we used unbiased, discovery-driven quantitative proteomics to assess the molecular basis of gender influences on risk of Alzheimer’s disease with cerebrovascular disease (AD + CVD).
We detected modulation of several redox proteins in the temporal lobe of AD + CVD subjects, and we observed sex-specific alterations in the white matter (WM) and mitochondria proteomes of female patients. Functional proteomic analysis of AD + CVD brain tissues revealed increased citrullination of arginine and deamidation of glutamine residues of myelin basic protein (MBP) in female which impaired degradation of degenerated MBP and resulted in accumulation of non-functional MBP in WM. Female patients also displayed down-regulation of ATP sub-units and cytochromes, suggesting increased severity of mitochondria impairment in women.
Our study demonstrates that gender-linked modulation of white matter and mitochondria proteomes influences neuropathology of the temporal lobe in AD + CVD.
KeywordsAlzheimer’s disease Cerebrovascular disease Dementia Temporal lobe White matter Citrullination Deamidation Proteomics iTRAQ
Dementia prevalence and severity in women are significantly higher than in men after controlling for expected lifespans [1, 2], but the neuropathological basis of this gender bias is currently unknown. Alzheimer’s disease is the most common form of dementia in the elderly, the majority of whom also undergo variable cerebrovascular disease (AD + CVD) . Affected individuals display a complex brain pathology characterized by senile plaques with microinfarcts, as well as a poorly understood degeneration of the small vessels that supply blood to the brain [4–7]. While vascular involvement appears to be closely linked with the extent of white matter (WM) pathology [8–10], it remains poorly defined how small vessel disease influences the clinical course of AD + CVD.
Restriction of blood flow to the brain results in WM tissue damage, leading to neurodegeneration and eventual dementia [11–15]. WM pathology contributes to cognitive impairment and long-term disability in elderly subjects via multiple mechanisms that do not depend on amyloid formation [16, 17]. Indeed, brain WM exhibits a complex composition of different molecules that can be modified to influence brain function, including both lipid molecules and proteins such as 2′,3′-cyclic nucleotide 3′-phosphodiesterase (CNP), myelin proteolipid protein (PLP), and myelin basic protein (MBP) . CNP and PLP, are involved on the maturation of oligodendrocytes [19, 20], while MBP regulates myelination and initiates essential signaling pathways in brain cells . Brain MBP is known to be susceptible to degenerative protein modifications (DPMs) including deamidation and citrullination [22, 23], and myelin degeneration can directly impair cognitive function due to disruption of neuronal circuits [24, 25], but the molecular profile of brain myelin proteins in AD + CVD has yet to be deciphered.
Degeneration of myelin sheaths causes axon disintegration, leading to impaired mitochondrial function and decreased provision of the essential molecules needed to maintain WM integrity [26–28]. Previous studies have also identified that changes in the molecular composition of MBP influence white matter pathology in vascular dementia (VaD) [15, 22, 29], and that excess DPMs promote proteinopathy and neurodegeneration in both AD and VaD . However, it remains unclear to what extent white matter pathology depends on DPM-induced proteinopathy in AD-related human dementias. Intriguingly, a previous study reported gender-specific differences on the accumulation of deamidation in rodent brain proteins . Similarly, prevalence and severity of citrullination-associated diseases in the central nervous system is significantly higher in women than in men  what suggests that these two DPMs could also underpin the increased dementia risk observed in human females. We therefore used discovery-driven quantitative proteomics  to investigate the molecular basis of gender influences on the pathology of AD + CVD.
White matter pathology is influenced by gender in AD + CVD
In order to assess the molecular basis of gender influences on risk of Alzheimer’s disease with cerebrovascular disease (AD + CVD), we first assessed the extent of myelin rarefaction/density loss in post-mortem brain tissues from male and female patients.
Demographic and clinical data of dementia subjects and age-matched control subjects. 1. Post-mortem delay
Age-matched control subjects
Mild AD-like pathology
Scattered microinfarcts (in right hemisphere: hippocampal CA2/3, putamen, caudate, external medullary lamina) and SVD: Foci of arteriosclerosis mainly in white matter
Mild cerebral amyloid angiopathy. A right frontal microinfarct and small lacunar infarct in the left putamen. Infarcts in both cortex and basal ganglia
Mild AD-like pathology
No detected AD or CVD pathology
Low mean density of neocortical tangles = 2.5 per mm2.
No detected AD or CVD pathology
No detected AD or CVD pathology
No detected AD or CVD pathology
No detected AD or CVD pathology
80.3 ± 8.9
31.6 ± 19
AD + CVD subjects
1 y. cog imp.
M.M.S.E = 18
Mixed pathology - AD and SVD (predominantly microinfarcts in frontal lobe & perivascular lacunae in basal ganglia). Cavernous hemangioma in right ventrolateral posterior centrum semiovale. Loss of myelin in brain capsules.
7 y. cog imp.
M.M.S.E = 20
Mixed AD and CVD. Microinfarcts in putamen. Loss of myelin in internal capsule
8 y. cog imp.
M.M.S.E = 13
Mixed pathology AD with vascular dementia and severe cerebral amyloid angiopathy.
1 y. dementia
M.M.S.E = 16
Mixed pathology AD with old infarcts in the temporal cortex right hemisphere. CVD affecting parietal and occipital lobes. Microinfarcts in caudate and putamen. Focal loss of myelin in brain capsules.
1 y. dementia
M.M.S.E = 20
Mixed pathology AD + CVD affecting middle temporal gyrus, parietal and occipital lobes. Myelin affectation in brain capsules.
77 ± 8.7
41 ± 18
2 y. dementia
S.I.B = 75/100
Mixed pathology AD + CVD affecting parietal and temporal lobes. Myelin affectation in brain capsules.
4 y. cog. imp.
M.M.S.E = 16
Mixed pathology AD + CVD affecting temporal lobes and brainstem. Severe myelin affectation in medial and internal temporal gyrus.
3 y. cog. imp.
M.T.S = 5/37
Mixed pathology AD + CVD. Severe changes in hippocampus. Neurofibrillary tangles in raphe nucleus.
5 y. dementia
M.M.S.E = 20
Mixed pathology AD + CVD affecting middle temporal gyrus and parietal/occipital lobes. Severe myelin affectation in temporal cortex.
2 y. dementia
M.M.S.E = 20
Mixed pathology AD + CVD. Moderate temporoparietal infarcts.
89.8 ± 2.8
46.6 ± 37.5
Intriguingly, we observed down-regulation of the myelin-associated protein Cathepsin D in women with dementia while the rest of myelin proteins identified in that group were significantly upregulated (Fig. 1a). Furthermore, the protein neural cell adhesion molecule (NCAM1) involved on functional response to white matter injury was only up-regulated in male patients (Fig. 1a). These data indicated that unbiased quantitative profiling of the human brain proteome can detect gender-specific differences in white matter pathology from patients with AD + CVD that were not apparent from conventional post-mortem evaluation.
The brain protein myelin associated glycoprotein (MAG) is highly susceptible to ischemia-induced degradation and its levels do not vary in the mammal’s brain by the effect of gender . Similarly, PLP positively correlates with severity of white matter pathology in small vessel disease , hence MAG/PLP ratio can be used as a proxy measure of disease severity in affected patients [35, 36]. Using this approach in our dementia samples, we observed that MAG/PLP ratio was significantly lower in females (0.2) than in males (0.5), indicating greater severity of WM pathology in women with AD + CVD. Since both genders exhibited comparable expression levels of MAG protein, which is readily degraded under ischemic conditions , these data suggested that both men and women may undergo a similar extent of ischemic injury in AD + CVD, but that subsequent effects on the myelin proteome and PLP expression differ between genders.
Sex-influenced modification of myelin basic protein in AD + CVD
Sex-influenced degradation of myelin basic protein in AD + CVD
Female AD + CVD is associated with specific modifications of the temporal lobe and mitochondria proteomes
In the current study, we used discovery-driven quantitative proteomics to uncover gender influences on myelin neuropathology and dysfunctional mitochondria proteomes in the temporal lobe of patients with AD + CVD. The data from this study provide novel insight into the molecular basis of the increased dementia risk and disease severity observed in women that develop AD + CVD.
Despite that post-mortem evaluation of myelin density failed to detect gender differences on white matter pathology in patients with AD + CVD, the data from quantitative profiling of the brain proteome clearly revealed the gender-specific molecular pathology of the affected WM. While we detected similar levels of MAG protein in men and women with dementia, suggesting a comparable extent of ischemic injury in both genders based on MAG/PLP ratio [35, 36], the severity of WM pathology observed in women was greater than that observed in men. Accumulation of dMBP in the temporal lobe is a key indicator of WM pathology in dementia [15, 49]. In disease settings, hyper-citrullination of MBP is thought to increase protein degradation by cathepsin D and other enzymes, leading to axonal dysfunction and progressive loss of neuronal function [43, 50, 51]. In-line with predictions, our functional proteomics study confirmed that MBP was hyper-citrullinated in women with dementia, but we also observed an unexpected impairment of dMBP degradation, which was associated with reduced cathepsin D expression and increased MBP deamidation at Gln residues (particularly in the degenerative epitope QDENPVV) [15, 41, 42]. Deamidation of Gln residues favors the proteolysis of dysfunctional proteins via the ubiquitin proteasome system , but Gln deamidation of brain proteins including MBP is also strongly associated with proteinopathy [51, 53, 54] which may resist the degradation of dMBP by the ubiquitin proteasome system. This impaired clearance of dMBP leads to accumulation of dysfunctional protein in the female brain. Our data now indicate that gender influences on the dementia-associated deamidation of MBP may alter protein degradation in the temporal lobe of AD + CVD patients.
We also observed marked up-regulation of several different myelin proteins in the temporal lobe of AD + CVD subjects, suggestive of an ongoing yet dysfunctional remyelination process . Our data are therefore consistent with a previous report that WM pathology is associated with accumulation of HPLN2, which inhibits axonal remyelination in the brain . Abnormal remyelination may also account for the counterintuitive increase in several myelin proteins including CNP and PLP in the temporal lobe of AD + CVD subjects. Impaired remyelination has previously been characterized to be associated with WM lesions , and may also be a feature of patients with AD + CVD, in whom the putative remyelination defect was closely associated with Gln deamidation of MBP.
In a recent study of mice that lack the enzyme L-isoaspartyl methyltransferase (PIMT) which repairs damaged proteins, female animals were reported to exhibit greater accumulation of IsoAsp-type DPMs in the brain  . PIMT knock-out mice have also been shown to exhibit increased deamidation and imbalance of the glutamate-glutamine cycle in the brain . These data are consistent with the current report, which suggests that gender-associated increases on deamidation of specific brain proteins may contribute to the increased severity of AD + CVD observed in women. While gender influences on enzymatic citrullination of Arg residues were less marked than effects on Gln deamidation by NADPH1, both processes can liberate ammonia byproducts thought to contribute to WM damage in human dementia [48, 58]. Accordingly, we also detected increased NADPH1 levels together with down-regulation of GS in the temporal lobe of women with AD + CVD. GS are astrocytic enzymes able to efficiently capture free ammonia during the Gln synthesis in the brain [59, 60]. Down-regulation of GS in the temporal lobe of women with dementia may indicate abnormal production of Gln in the brain, in-turn leading to increased expression of NADPH1 enzymes that enhance production of glutamate from Gln residues. Further research will now be required to assess this possibility.
Whether mitochondria dysfunction precedes changes in the WM proteome or vice versa remains unclear. Other colleagues have reported that an increase in ammonia byproducts during neurodegeneration can exacerbate glutamate toxicity and impair mitochondria function . Here we observed that AD + CVD patients displayed down-regulation of mitochondrial kinase-U-type protein, which is known to be dysregulated in ischemia-induced mitochondrial impairment . We further observed that cytochromes and ATP subunits were significantly altered only in women with AD + CVD, consistent with increased severity of mitochondria dysfunction in this group. According to our findings, perturbation of the mitochondrial proteome appears to be proportional to the severity of WM pathology in human AD + CVD. This result suggests that mitochondria dysfunction in AD-related disorders may be a product of early alterations in the WM proteome by vascular dysfunction, hence as recently suggested the vascular component of disease is likely to exert a major influence on the clinical course of human dementias.
While several epidemiological and clinical studies have showed that women exhibit higher risk of dementia than men, the molecular neuropathology of this gender difference remains elusive. In the current study, we used unbiased quantitative proteomics to assess the molecular basis of gender influences on risk of AD + CVD. For the first time, we report sex-specific molecular differences in white matter pathology and mitochondrial proteomes in the temporal lobe of AD + CVD patients. In particular, we observed that hyper-citrullination and hyper-deamidation of MBP were prevalent in female dementia patients. Specifically, deamidation of the glutamine residue 82 in the MBP degenerative epitope was associated with impaired degradation and accumulation of degenerated protein in the temporal lobe of women with dementia. This study uncovers the gender influences on the neuropathology of AD + CVD, and may pave the way for future clinical interventions that can reduce dementia risk in both male and female patients.
Autopsied brain specimens were carefully evaluated for the presence of senile plaques and CVD at the Newcastle Brain Tissue Resource (NBTR, UK). The temporal cortex region BA21 was used in all experiments (both control and dementia samples). All dementia brain samples met histological criteria for AD + CVD, whereas control subjects lacked features of either dementia or AD + CVD. Brain samples in each experimental group were closely matched for key variables including post-mortem delay, cognitive assessment data, age at death, and histological evaluation (Table 1) . Finally, BA21 tissues for western blot validation of the PLP level were generously provided by the Harvard brain tissue resource center (HBTRC). Informed consent was obtained from all participants or their legal representatives. All experimental procedures were approved by the ethical boards at Nanyang Technological University (NTU, Singapore) and NBTR, and were performed in accordance with NTU guidelines.
All reagents were purchased from Sigma-Aldrich (St. Louis, MO, USA) unless specified otherwise.
Tissue processing and protein extraction
In order to minimize potential confounding factors and to efficiently limit the excessive cost of iTRAQ experiments, we adopted a pooling strategy for our proteomic analyses [64–66]. Approximately 10 milligrams of brain tissue from each subject was homogenized in 1 % SDS buffer using the tissue homogenizer bullet blender (Next Advance, NY, USA) and then pooled into one of the following three groups: age-matched controls (10 subjects), male dementia subjects (5 subjects), and female dementia subjects (5 subjects). Experiments were performed in triplicate, and only those proteins that were confidently identified in all three experiments are reported here (see detailed description of statistical analyses below).
Proteins were acetone-precipitated and quantified by bicinchoninic acid assay. Two-hundred micrograms of protein were resolved by SDS-PAGE and visualized using Coomassie Blue staining. Protein bands were cut and destained in 75 % acetonitrile containing 25 mM triethylammonium bicarbonate (TEAB). Gel cubes were reduced with Tris 2-carboxyethyl phosphine hydrochloride (5 mM), alkylated with methyl methanethiosulfonate (10 mM), and then dehydrated using acetonitrile. Proteins were digested overnight at 37 °C in sequencing-grade modified trypsin (Promega, Madison, WI, USA). Peptides were extracted using 50 % acetonitrile in 5 % acetic acid solution under ultrasound sonication, then dried and concentrated using a vacuum concentrator (Eppendorf AG, Hamburg, Germany).
iTRAQ labelling and shotgun mass spectrometry
Labeling of dried peptides was performed as previously reported [38, 39, 67]. Briefly, 4-plex iTRAQ reagent Multiplex kits (Applied Biosystems, Foster City, CA) were used according to the manufacturer’s protocol. Tags were distributed as follows; 114 = controls; 116 = women; 117 = men. The iTRAQ-labeled peptides were desalted using Sep-Pak C18 cartridges (Waters, UK) and fractionated by high-performance liquid chromatography (HPLC) (Shimadzu, Kyoto, Japan) on a PolyWAX LP column (4.6 × 200 mm, 5 μm, 300 Å) (PolyLC, Columbia, MD, USA). Buffer A (10 mM ammonium acetate, 85 % acetonitrile, 0.1 % acetic acid) and buffer B (30 % acetonitrile, 0.1 % formic acid) were used to establish a 60 min HPLC-gradient at 1 ml/min flow rate. Chromatograms were recorded at 280 nm. A total of 60 fractions were collected and subsequently combined into 26 fractions according to peak intensities.
LC-MS/MS analysis of the brain peptides was performed using a QSTAR Elite mass spectrometer (Applied Biosystems/MDS Sciex, Foster City, CA, USA) coupled with online nanoflow multidimensional liquid chromatography system (MDLC). A custom-made nanobore C18 column with a picofrit nanospray tip (75 μm ID × 15 cm, 5 μm particles) was used to separate the iTRAQ-labeled peptides. The QSTAR Elite was set to positive ion mode using Analyst QS 2.0 software for data acquisition (Applied Biosystems, Foster City, CA, USA). The precursors with a mass range of 300–1600 m/z and calculated charge from +2 to +5 were selected for fragmentation. Peptides above a 5-count threshold were selected for MS/MS and each selected target ion was dynamically excluded for 20 s with a mass tolerance of 0.1 Da. Smart information-dependent acquisition was activated with automatic collision energy and automatic MS/MS accumulation. The fragment intensity multiplier was set to 20, and the maximum accumulation time was 2 s.
LC-MS/MS data search
MS/MS data searching was performed using the concatenated target-decoy Uniprot database in ProteinPilot software 3.0 (revision number 114732; Applied Biosystems, Foster City, CA, USA) with Paragon (126.96.36.199, 113442) and Pro Group algorithms implemented. Digestion enzyme was set as semi-trypsin. User-defined parameters and false discovery rate (FDR) for assignation of peptides and proteins in the software were set as previously specified . Briefly FDR <1 % (FDR = 2.0 × [decoy hits/total hits] × 100 %) and unused Protein Score value ≥2 were used as qualification criteria (corresponding to a confidence limit of 99 %). These criteria enabled the identification of over 2400 total proteins.
Regulation of protein levels and statistical inference
In this equation, CtrlA refers to iTRAQ reporter area in the control group, DemA refers to iTRAQ reporter area of the respective dementia group, and ‘ln’ refers to the natural logarithm. G-values fit well to the x 2 distribution with one degree of freedom , and accordingly, we were able to calculate the corresponding p-value for each G-value obtained. Finally, the calculated p-values were corrected for multiple comparisons using the Benjamini-Hochberg FDR correction at 0.05α  to obtain a corrected p-value of 0.014. Following this approach, we considered only those proteins confidently identified in all three experiments (i.e. those containing at least one unique peptide identified with >99 % confidence in each group, and displaying a G-test p-value lower than 0.014). A total of 321 proteins satisfied these stringent criteria (Additional file 4) and (Additional file 3: Figure S1C). We then assessed the influence of gender on expression of the 321 proteins identified by analyzing the %CV of the iTRAQ ratios in both the male and female dementia groups. The cut-off for protein differential expression between men and women with dementia was set at ≥0.2 (based on %CV <20 % ([116:114] – [117:114]) (Additional file 3: Figure S1D). Combining all the statistical approaches described above, we observed that a total of 59 proteins were significantly modulated in the dementia groups compared with controls (Additional file 5), including 38 proteins that were differentially expressed between male and female dementia patients (Additional file 6).
Quantification of peptide modifications and statistical inference
To confidently quantify the level of modified peptides in our profiled AD + CVD brain tissues we assessed influence of age and disease on the increase of deamidation and citrullination in temporal lobe proteins performing spectral counting in peaks . This analysis confirmed the exacerbate increase of DPTMs in temporal lobe proteins as a disease-associated process (Additional file 3: Figure S1E and S1F). Analysis of modified peptides (deamidation and citrullination) was performed using unique peptide iTRAQ reporter peak areas. Only those peptides identified with ≥ 99 % confidence were included in this analysis. Mean peptide reporter peak areas in each of the three groups (age-matched controls, men with dementia, women with dementia) were compared by One-Way ANOVA, and p-values were corrected for multiple comparisons using Bonferroni. Data were reported as mean and SD unless stated otherwise.
Molecular bioinformatics and MBP functional proteomics
In this equation, “exact match” refers to the identified MBP degradation byproducts described above. “Partial match” refers to longer tryptic peptides that included the exact match sequence of the degradation byproducts. Total iTRAQ reporter area refers to the sum of all identified iTRAQ reporter peak areas for the peptide. The calculation was performed in each group including age-matched controls, women with dementia, and men with dementia. Finally, the degradation ratio was obtained by dividing the MBP percentage degradation values for the women and men dementia groups by that calculated for age-matched controls.
Tissues from two AD + CVD women (68y and 79y respectively), two AD + CVD men (74y and 63y respectively), one male control (77y) and one female control (77y) were homogenized as described above in 1 % SDS buffer. Western blot was performed as previously reported . Briefly, proteins were reduced by 2-mercaptoethanol (5 %) in 95 °C during five minutes and subsequently mixed with BioRad 2× Laemmli sample buffer (CA, USA). Protein amount was quantified by Bradford assay and equal amount of protein was loaded in a 15 % SDS-PAGE gel. Resolved proteins were then blotted onto a nitrocellulose membrane and detected using the polyclonal goat anti-PLP (SC-23570) primary antibody (1:1000 dilution) and the rabbit anti-goat (SC-2768) secondary antibody (1:3000 dilution). Ponceau staining was used as loading control . Densitometry of Western blot signal was mesured using ImageJ (Rasband W.S., ImageJ. U.S. National Institutes of Health, MD., U.S.A. http://imagej.nih.gov/ij/ 1997-2016) and Student's t-test analysis of data was performed.
Proteomics data have been made publicly available through ProteomeXchange consortium  via the partner repository PRIDE under the following identifier PXD003027.
This work was funded by the Singapore Ministry of Health (NMRC/CBRG/0004/2012), Singapore Ministry of Education (Tier1: RGT15/13) and NTU-NHG Ageing Research Grant (ARG/14017). Tissues for this study were provided by Newcastle Brain Tissue Resource as part of the UK Brains for Dementia Research initiative and by Harvard Brain Tissue Resource Center (HBTRC) which is supported in part by a PHS contract and by HHSN-271-2013-00030C. We thank Louis Fernandes from HBTRC for his kind help and consideration. We also thank Dr. Bamaprasad Dutta for his help with the staining experiments. The authors feel greatly indebted to all the subjects and their families that have participated in this study.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- de Leeuw FE, de Groot JC, Achten E, Oudkerk M, Ramos LM, Heijboer R, et al. Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam scan study. J Neurol Neurosurg Psychiatry. 2001;70(1):9–14.View ArticlePubMedPubMed CentralGoogle Scholar
- van den Heuvel DM, Admiraal-Behloul F, ten Dam VH, Olofsen H, Bollen EL, Murray HM, et al. Different progression rates for deep white matter hyperintensities in elderly men and women. Neurology. 2004;63(9):1699–701.View ArticlePubMedGoogle Scholar
- Kalaria R. Similarities between Alzheimer’s disease and vascular dementia. J Neurol Sci. 2002;203-204:29-34.Google Scholar
- Gold G, Giannakopoulos P, Bouras C. Re-evaluating the role of vascular changes in the differential diagnosis of Alzheimer’s disease and vascular dementia. Eur Neurol. 1998;40(3):121–9.View ArticlePubMedGoogle Scholar
- Iadecola C. The pathobiology of vascular dementia. Neuron. 2013;80:844–66.View ArticlePubMedGoogle Scholar
- Prins ND, Scheltens P. White matter hyperintensities, cognitive impairment and dementia: an update. Nat Rev Neurol. 2015;11(3):157–65. doi:10.1038/nrneurol.2015.10.View ArticlePubMedGoogle Scholar
- Attems J, Jellinger KA. The overlap between vascular disease and Alzheimer’s disease--lessons from pathology. BMC Med. 2014;12:206.View ArticlePubMedPubMed CentralGoogle Scholar
- Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke. 1997;28(3):652–9.View ArticlePubMedGoogle Scholar
- Kalaria RN. The role of cerebral ischemia in Alzheimer’s disease. Neurobiol Aging. 2000;21:321–30.View ArticlePubMedGoogle Scholar
- Kalaria RN, Ihara M. Dementia: vascular and neurodegenerative pathways[mdash]will they meet? Nat Rev Neurol. 2013;9(9):487–8.View ArticlePubMedGoogle Scholar
- Fernando MS, Simpson JE, Matthews F, Brayne C, Lewis CE, Barber R, et al. White matter lesions in an unselected cohort of the elderly: molecular pathology suggests origin from chronic hypoperfusion injury. Stroke. 2006;37(6):1391–8.View ArticlePubMedGoogle Scholar
- Haight TJ, Landau SM, Carmichael O, et al. DIssociable effects of Alzheimer disease and white matter hyperintensities on brain metabolism. JAMA Neurol. 2013;70(8):1039–45.View ArticlePubMedPubMed CentralGoogle Scholar
- Vermeer SE, Prins ND, den Heijer T, Hofman A, Koudstaal PJ, Breteler MM. Silent brain infarcts and the risk of dementia and cognitive decline. N Eng J Med. 2003;348(13):1215–22.View ArticleGoogle Scholar
- Brickman AM, Zahodne LB, Guzman VA, Narkhede A, Meier IB, Griffith EY, et al. Reconsidering harbingers of dementia: progression of parietal lobe white matter hyperintensities predicts Alzheimer’s disease incidence. Neurobiol Aging. 2015;36(1):27–32.View ArticlePubMedPubMed CentralGoogle Scholar
- Ihara M, Polvikoski TM, Hall R, Slade JY, Perry RH, Oakley AE, et al. Quantification of myelin loss in frontal lobe white matter in vascular dementia, Alzheimer’s disease, and dementia with Lewy bodies. Acta Neuropathol. 2010;119(5):579–89.View ArticlePubMedPubMed CentralGoogle Scholar
- Vemuri P, Lesnick TG, Przybelski SA, Knopman DS, Preboske GM, Kantarci K, et al. Vascular and amyloid pathologies are independent predictors of cognitive decline in normal elderly. Brain. 2015;138:761–71.View ArticlePubMedPubMed CentralGoogle Scholar
- Inzitari D, Pracucci G, Poggesi A, Carlucci G, Barkhof F, Chabriat H, et al. Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS study cohort. BMJ. 2009;339:b2477.View ArticlePubMedPubMed CentralGoogle Scholar
- Boggs JM. Myelin basic protein: a multifunctional protein. Cell Mol Life Sci. 2006;63(17):1945–61.View ArticlePubMedGoogle Scholar
- Gravel M, Peterson J, Yong VW, Kottis V, Trapp B, Braun PE. Overexpression of 2',3'-cyclic nucleotide 3'-phosphodiesterase in transgenic mice alters oligodendrocyte development and produces aberrant myelination. Mol Cell Neurosci. 1996;7(6):453–66.View ArticlePubMedGoogle Scholar
- Readhead C, Schneider A, Griffiths I, Nave KA. Premature arrest of myelin formation in transgenic mice with increased proteolipid protein gene dosage. Neuron. 1994;12(3):583–95.View ArticlePubMedGoogle Scholar
- Lutz D, Loers G, Kleene R, Oezen I, Kataria H, Katagihallimath N, et al. Myelin basic protein cleaves cell adhesion molecule L1 and promotes neuritogenesis and cell survival. J Biochem. 2014;289(19):13503–18.Google Scholar
- Zhang C, Walker AK, Zand R, Moscarello MA, Yan JM, Andrews PC. Myelin basic protein undergoes a broader range of modifications in mammals than in lower vertebrates. J Proteome Res. 2012;11(10):4791–802.View ArticlePubMedPubMed CentralGoogle Scholar
- Wood DD, Moscarello MA. The isolation, characterization, and lipid-aggregating properties of a citrulline containing myelin basic protein. J Biol Chem. 1989;264(9):5121–7.PubMedGoogle Scholar
- Bartzokis G. Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease. Neurobiol Aging. 2004;25(1):5–18.View ArticlePubMedGoogle Scholar
- Kalaria RN. Cerebrovascular disease and mechanisms of cognitive impairment: evidence from clinicopathological studies in humans. Stroke. 2012;43(9):2526–34.View ArticlePubMedGoogle Scholar
- Chen H, Chan DC. Critical dependence of neurons on mitochondrial dynamics. Curr Opin Cell Biol. 2006;18(4):453–9.View ArticlePubMedGoogle Scholar
- Funfschilling U, Supplie LM, Mahad D, Boretius S, Saab AS, Edgar J, et al. Glycolytic oligodendrocytes maintain myelin and long-term axonal integrity. Nature. 2012;485(7399):517–21.PubMedPubMed CentralGoogle Scholar
- Morato L, Bertini E, Verrigni D, Ardissone A, Ruiz M, Ferrer I, et al. Mitochondrial dysfunction in central nervous system white matter disorders. Glia. 2014;62(11):1878–94.View ArticlePubMedGoogle Scholar
- Gudmann NS, Hansen NU, Jensen AC, Karsdal MA, Siebuhr AS. Biological relevance of citrullinations: diagnostic, prognostic and therapeutic options. Autoimmunity. 2015;48(2):73–9.View ArticlePubMedGoogle Scholar
- Gallart-Palau X, Serra A, Sze SK. Uncovering neurodegenerative protein modifications via proteomic profiling. Int Rev Neurobiol. 2015;121:87–116.View ArticlePubMedGoogle Scholar
- Qin Z, Kaufman RS, Khoury RN, Khoury MK, Aswad DW. Isoaspartate accumulation in mouse brain is associated with altered patterns of protein phosphorylation and acetylation, some of which are highly sex-dependent. PLoS One. 2013;8, e80758.View ArticlePubMedPubMed CentralGoogle Scholar
- Harbo HF, Gold R, Tintore M. Sex and gender issues in multiple sclerosis. Ther Adv Neurol Disor. 2013;6(4):237–48.View ArticleGoogle Scholar
- Choudhary J, Grant SG. Proteomics in postgenomic neuroscience: the end of the beginning. Nat Neurosci. 2004;7(5):440–5.View ArticlePubMedGoogle Scholar
- Cao J, Wang J, Dwyer JB, Gautier NM, Wang S, Leslie FM, et al. Gestational nicotine exposure modifies myelin gene expression in the brains of adolescent rats with sex differences. Transl Psychiatry. 2013;3, e247.View ArticlePubMedPubMed CentralGoogle Scholar
- Barker R, Wellington D, Esiri MM, Love S. Assessing white matter ischemic damage in dementia patients by measurement of myelin proteins. J Cereb Blood Flow Metab. 2013;33(7):1050–7.View ArticlePubMedPubMed CentralGoogle Scholar
- Aboul-Enein F, Rauschka H, Kornek B, Stadelmann C, Stefferl A, Bruck W, et al. Preferential loss of myelin-associated glycoprotein reflects hypoxia-like white matter damage in stroke and inflammatory brain diseases. J Neuropathol Exp Neurol. 2003;62(1):25–33.View ArticlePubMedGoogle Scholar
- Ishigami A, Maruyama N. Importance of research on peptidylarginine deiminase and citrullinated proteins in age-related disease. Geriatr Gerontol Int. 2010;10 Suppl 1:S53–8.View ArticlePubMedGoogle Scholar
- Gallart-Palau X, Serra A, Qian J, Chen CP, Kalaria RN, Sze SK. Temporal lobe proteins implicated in synaptic failure exhibit differential expression and deamidation in vascular dementia. Neurochem Int. 2015;80:87–98.View ArticlePubMedGoogle Scholar
- Adav SS, Qian J, Ang YL, Kalaria RN, Lai MK, Chen CP, et al. iTRAQ quantitative clinical proteomics revealed role of Na(+)K(+)-ATPase and its correlation with deamidation in vascular dementia. J Proteome Res. 2014;13(11):4635–46.View ArticlePubMedGoogle Scholar
- Hamada K, Terauchi A, Nakamura K, Higo T, Nukina N, Matsumoto N, et al. Aberrant calcium signaling by transglutaminase-mediated posttranslational modification of inositol 1,4,5-trisphosphate receptors. Proc Natl Acad Sci U S A. 2014;111(38):E3966–75.View ArticlePubMedPubMed CentralGoogle Scholar
- Tomimoto H, Akiguchi I, Matsuo A, Terai K, Wakita H, Kimura J, et al. Encephalitogenic peptide (EP) in human cerebrovascular white matter lesions. Neuroreport. 1997;8(17):3727–30.View ArticlePubMedGoogle Scholar
- Matsuo A, Lee GC, Terai K, Takami K, Hickey WF, McGeer EG, et al. Unmasking of an unusual myelin basic protein epitope during the process of myelin degeneration in humans: a potential mechanism for the generation of autoantigens. Am J Pathol. 1997;150(4):1253–66.PubMedPubMed CentralGoogle Scholar
- Bacheva AV, Belogurov AA, Kuzina ES, Serebryakova MV, Ponomarenko NA, Knorre VD, et al. Functional degradation of myelin basic protein. The proteomic approach. Russ J Bioorg Chem. 2011;37(1):39–47.View ArticleGoogle Scholar
- Takata T, Oxford JT, Brandon TR, Lampi KJ. Deamidation alters the structure and decreases the stability of human lens betaA3-crystallin. Biochemistry. 2007;46(30):8861–71.View ArticlePubMedPubMed CentralGoogle Scholar
- Liu B, Wang G, Gao D, Gao F, Zhao B, Qiao M, et al. Alterations of GABA and glutamate-glutamine levels in premenstrual dysphoric disorder: a 3 T proton magnetic resonance spectroscopy study. Psychiatry Res. 2015;231(1):64–70.View ArticlePubMedGoogle Scholar
- Yucel M, Wood SJ, Wellard RM, Harrison BJ, Fornito A, Pujol J, et al. Anterior cingulate glutamate-glutamine levels predict symptom severity in women with obsessive-compulsive disorder. Aust N Z J Psychiatry. 2008;42(6):467–77.View ArticlePubMedGoogle Scholar
- Long J, He P, Shen Y, Li R. New evidence of mitochondria dysfunction in the female Alzheimer’s disease brain: deficiency of estrogen receptor-beta. J Alzheimers Dis. 2012;30(3):545–58.PubMedPubMed CentralGoogle Scholar
- De Ingeniis J, Kazanov MD, Shatalin K, Gelfand MS, Osterman AL, Sorci L. Glutamine versus ammonia utilization in the NAD synthetase family. PLoS One. 2012;7(6), e39115.View ArticlePubMedPubMed CentralGoogle Scholar
- Yamamoto Y, Ihara M, Tham C, Low RW, Slade JY, Moss T, et al. Neuropathological correlates of temporal pole white matter hyperintensities in CADASIL. Stroke. 2009;40(6):2004–11.View ArticlePubMedPubMed CentralGoogle Scholar
- D’Souza CA, Wood DD, She YM, Moscarello MA. Autocatalytic cleavage of myelin basic protein: an alternative to molecular mimicry. Biochemistry. 2005;44(38):12905–13.View ArticlePubMedGoogle Scholar
- Wood DD, Ackerley CA, Brand B, Zhang L, Raijmakers R, Mastronardi FG, et al. Myelin localization of peptidylarginine deiminases 2 and 4: comparison of PAD2 and PAD4 activities. Lab Invest. 2008;88(4):354–64.View ArticlePubMedGoogle Scholar
- Dudek EJ, Lampi KJ, Lampi JA, Shang F, King J, Wang Y, et al. Ubiquitin proteasome pathway-mediated degradation of proteins: effects due to site-specific substrate deamidation. Invest Ophthalmol Vis Sci. 2010;51(8):4164–73.View ArticlePubMedPubMed CentralGoogle Scholar
- Robinson NE, Robinson AB. Deamidation of human proteins. Proc Natl Acad Sci U S A. 2001;98(22):12409–13.View ArticlePubMedPubMed CentralGoogle Scholar
- Boggs JM, Yip PM, Rangaraj G, Jo E. Effect of posttranslational modifications to myelin basic protein on its ability to aggregate acidic lipid vesicles. Biochemistry. 1997;36(16):5065–71.View ArticlePubMedGoogle Scholar
- Sherman LS, Back SA. A ‘GAG’ reflex prevents repair of the damaged CNS. Trends Neurosci. 2008;31(1):44–52.View ArticlePubMedGoogle Scholar
- Jonsson M, Zetterberg H, Rolstad S, Edman A, Gouw AA, Bjerke M, et al. Low cerebrospinal fluid sulfatide predicts progression of white matter lesions – the LADIS study. Dement Geriatr Cogn Disord. 2012;34(1):61–7.View ArticlePubMedGoogle Scholar
- Yang H, Lowenson JD, Clarke S, Zubarev RA. Brain proteomics supports the role of glutamate metabolism and suggests other metabolic alterations in protein l-isoaspartyl methyltransferase (PIMT)-knockout mice. J Proteome Res. 2013;12(10):4566–76.View ArticlePubMedGoogle Scholar
- Lu X, Galkin A, Herzberg O, Dunaway-Mariano D. Arginine deiminase uses an active-site cysteine in nucleophilic catalysis of L-arginine hydrolysis. J Am Chem Soc. 2004;126(17):5374–5.View ArticlePubMedGoogle Scholar
- Suarez I, Bodega G, Fernandez B. Glutamine synthetase in brain: effect of ammonia. Neurochem Int. 2002;41(2-3):123–42.View ArticlePubMedGoogle Scholar
- Kosenko E, Llansola M, Montoliu C, Monfort P, Rodrigo R, Hernandez-Viadel M, et al. Glutamine synthetase activity and glutamine content in brain: modulation by NMDA receptors and nitric oxide. Neurochem Int. 2003;43(4-5):493–9.View ArticlePubMedGoogle Scholar
- Bobermin LD, Wartchow KM, Flores MP, Leite MC, Quincozes-Santos A, Goncalves CA. Ammonia-induced oxidative damage in neurons is prevented by resveratrol and lipoic acid with participation of heme oxygenase 1. Neurotoxicology. 2015;49:28–35.View ArticlePubMedGoogle Scholar
- Karpati G, Carpenter S, Melmed C, Eisen AA. Experimental ischemic myopathy. J Neurol Sci. 1974;23(1):129–61.View ArticlePubMedGoogle Scholar
- Hynd MR, Lewohl JM, Scott HL, Dodd PR. Biochemical and molecular studies using human autopsy brain tissue. J Neurochem. 2003;85(3):543–62.View ArticlePubMedGoogle Scholar
- Allison DB, Cui X, Page GP, Sabripour M. Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet. 2006;7(1):55–65.View ArticlePubMedGoogle Scholar
- Weinkauf M, Hiddemann W, Dreyling M. Sample pooling in 2-D gel electrophoresis: a new approach to reduce nonspecific expression background. Electrophoresis. 2006;27(22):4555–8.View ArticlePubMedGoogle Scholar
- Kendziorski CM, Zhang Y, Lan H, Attie AD. The efficiency of pooling mRNA in microarray experiments. Biostatistics. 2003;4(3):465–77.View ArticlePubMedGoogle Scholar
- Datta A, Qian J, Chong R, Kalaria RN, Francis P, Lai MK, et al. Novel pathophysiological markers are revealed by iTRAQ-based quantitative clinical proteomics approach in vascular dementia. J Proteomics. 2014;99:54–67.View ArticlePubMedPubMed CentralGoogle Scholar
- Lu H, Yang Y, Allister EM, Wijesekara N, Wheeler MB. The identification of potential factors associated with the development of type 2 diabetes: a quantitative proteomics approach. Mol Cell Proteomics. 2008;7(8):1434–51.View ArticlePubMedPubMed CentralGoogle Scholar
- Shilov IV, Seymour SL, Patel AA, Loboda A, Tang WH, Keating SP, et al. The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Mol Cell Proteomics. 2007;6(9):1638–55.View ArticlePubMedGoogle Scholar
- Bai B, Hales CM, Chen P-C, Gozal Y, Dammer EB, Fritz JJ, et al. U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer’s disease. Proc Natl Acad Sci U S A. 2013;110(41):16562–7.View ArticlePubMedPubMed CentralGoogle Scholar
- Ghosh D. Incorporating the empirical null hypothesis into the Benjamini-Hochberg procedure. Stat Appl Genet Mol Biol. 2012;11(4):doi: 10.1515/1544-6115.1735.
- Ma B, Zhang K, Hendrie C, Liang C, Li M, Doherty-Kirby A, et al. PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun Mass Spectrom. 2003;17(20):2337–42.View ArticlePubMedGoogle Scholar
- Smith AC, Blackshaw JA, Robinson AJ. MitoMiner: a data warehouse for mitochondrial proteomics data. Nucleic Acids Res. 2012;40:1160–7.View ArticleGoogle Scholar
- Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y. The I-TASSER suite: protein structure and function prediction. Nat Methods. 2015;12(1):7–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Bramucci E, Paiardini A, Bossa F, Pascarella S. PyMod: sequence similarity searches, multiple sequence-structure alignments, and homology modeling within PyMOL. BMC Bioinformatics. 2012;13 Suppl 4:S2.View ArticlePubMedGoogle Scholar
- Li W, Cowley A, Uludag M, Gur T, McWilliam H, Squizzato S, et al. The EMBL-EBI bioinformatics web and programmatic tools framework. Nucleic Acids Res. 2015;43(W1):580–4.View ArticleGoogle Scholar
- Gallart-Palau X, Serra A, Wong AS, Sandin S, Lai MK, Chen CP, et al. Extracellular vesicles are rapidly purified from human plasma by PRotein Organic Solvent PRecipitation (PROSPR). Sci Rep. 2015;5:14664.View ArticlePubMedPubMed CentralGoogle Scholar
- Romero-Calvo I, Ocón B, Martínez-Moya P, Suárez MD, Zarzuelo A, Martínez-Augustin O, et al. Reversible Ponceau staining as a loading control alternative to actin in Western blots. Anal Biochem. 2010;401(2):318–20.View ArticlePubMedGoogle Scholar
- Vizcaino JA, Deutsch EW, Wang R, Csordas A, Reisinger F, Rios D, et al. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol. 2014;32(3):223–6.View ArticlePubMedPubMed CentralGoogle Scholar