ORCID Profile
0000-0001-9276-2720
Current Organisation
University of Oxford
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Publisher: Cold Spring Harbor Laboratory
Date: 10-06-2021
DOI: 10.1101/2021.06.07.21258457
Abstract: The levels of many blood proteins are associated with Alzheimer’s disease or its pathological hallmarks. Elucidating the molecular factors that control circulating levels of these proteins may help to identify proteins causally associated with the disease. Here, genome-wide and epigenome-wide studies (n in iduals ≤1,064) were performed on plasma levels of 281 Alzheimer’s disease-associated proteins, identified by a systematic review of the literature. We quantified the contributions of genetic and epigenetic variation towards inter-in idual variability in plasma protein levels. Sixty-one independent genetic and 32 epigenetic loci were associated with expression levels of 49 proteins eight and 24 of these respective findings are previously unreported. Novel findings included an association between plasma TREM2 levels and a polymorphism and CpG site within the MS4A4A locus. Through Mendelian randomisation analyses, causal associations were observed between higher plasma TBCA and TREM2 levels and lower Alzheimer’s disease risk. Our data inform the regulation of biomarker levels and their relationships with Alzheimer’s disease.
Publisher: Springer Science and Business Media LLC
Date: 09-08-2022
DOI: 10.1038/S41467-022-32319-8
Abstract: Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed ( N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits ( N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.
Publisher: Wiley
Date: 29-04-2019
Publisher: Springer Science and Business Media LLC
Date: 10-12-2020
DOI: 10.1038/S41598-020-78031-9
Abstract: Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between in iduals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.
Publisher: Oxford University Press (OUP)
Date: 26-08-2019
DOI: 10.1093/BRAIN/AWZ241
Abstract: Microglia have been implicated in amyloid beta-induced neuropathology, but their role in tau-induced neurodegeneration remains unclear. Mancuso et al. report that blockade of microglial proliferation by CSF1R inhibitor JNJ-40346527 modifies brain inflammation and ameliorates disease progression in P301S tauopathy mice. CSF1R inhibition may have therapeutic potential in tau-mediated neurodegenerative diseases.
Publisher: Wiley
Date: 22-12-2017
DOI: 10.1002/MPR.1602
Publisher: Wiley
Date: 07-2017
Publisher: Cold Spring Harbor Laboratory
Date: 06-09-2021
DOI: 10.1101/2021.09.03.21263066
Abstract: Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4,058 plasma proteins are performed (N=774), identifying 2,928 CpG-protein associations after adjustment for multiple testing. These were independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N=1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 19-07-2023
DOI: 10.1126/SCITRANSLMED.ADF5681
Abstract: A erse set of biological processes have been implicated in the pathophysiology of Alzheimer’s disease (AD) and related dementias. However, there is limited understanding of the peripheral biological mechanisms relevant in the earliest phases of the disease. Here, we used a large-scale proteomics platform to examine the association of 4877 plasma proteins with 25-year dementia risk in 10,981 middle-aged adults. We found 32 dementia-associated plasma proteins that were involved in proteostasis, immunity, synaptic function, and extracellular matrix organization. We then replicated the association between 15 of these proteins and clinically relevant neurocognitive outcomes in two independent cohorts. We demonstrated that 12 of these 32 dementia-associated proteins were associated with cerebrospinal fluid (CSF) biomarkers of AD , neurodegeneration, or neuroinflammation. We found that eight of these candidate protein markers were abnormally expressed in human postmortem brain tissue from patients with AD, although some of the proteins that were most strongly associated with dementia risk, such as GDF15, were not detected in these brain tissue s les. Using network analyses, we found a protein signature for dementia risk that was characterized by dysregulation of specific immune and proteostasis/autophagy pathways in adults in midlife ~20 years before dementia onset, as well as abnormal coagulation and complement signaling ~10 years before dementia onset. Bidirectional two-s le Mendelian randomization genetically validated nine of our candidate proteins as markers of AD in midlife and inferred causality of SERPINA3 in AD pathogenesis. Last, we prioritized a set of candidate markers for AD and dementia risk prediction in midlife.
Publisher: Society for Neuroscience
Date: 15-09-2010
DOI: 10.1523/JNEUROSCI.0817-10.2010
Abstract: The advance of Parkinson's disease is associated with the existence of abnormal oscillations within the basal ganglia with frequencies in the beta band (13–30 Hz). While the origin of these oscillations remains unknown, there is some evidence suggesting that oscillations observed in the basal ganglia arise due to interactions of two nuclei: the subthalamic nucleus (STN) and the globus pallidus pars externa (GPe). To investigate this hypothesis, we develop a computational model of the STN–GPe network based upon anatomical and electrophysiological studies. Significantly, our study shows that for certain parameter regimes, the model intrinsically oscillates in the beta range. Through an analytical study of the model, we identify a simple set of necessary conditions on model parameters that guarantees the existence of beta oscillations. These conditions for generation of oscillations are described by a set of simple inequalities and can be summarized as follows: (1) The excitatory connections from STN to GPe and the inhibitory connections from GPe to STN need to be sufficiently strong. (2) The time required by neurons to react to their inputs needs to be short relative to synaptic transmission delays. (3) The excitatory input from the cortex to STN needs to be high relative to the inhibition from striatum to GPe. We confirmed the validity of these conditions via numerical simulation. These conditions describe changes in parameters that are consistent with those expected as a result of the development of Parkinson's disease, and predict manipulations that could inhibit the pathological oscillations.
Publisher: Elsevier BV
Date: 02-2012
DOI: 10.1016/J.NEUROIMAGE.2011.08.111
Abstract: In this paper we propose that the dynamic evolution of EEG activity during epileptic seizures may be characterised as a path through parameter space of a neural mass model, reflecting gradual changes in underlying physiological mechanisms. Previous theoretical studies have shown how boundaries in parameter space of the model (so-called bifurcations) correspond to transitions in EEG waveforms between apparently normal, spike and wave and subsequently poly-spike and wave activity. In the present manuscript, we develop a multi-objective genetic algorithm that can estimate parameters of an underlying model from clinical data recordings. A standard approach to this problem is to transform both clinical data and model output into the frequency domain and then choose parameters that minimise the difference in their respective power spectra. Instead in the present manuscript, we estimate parameters in the time domain, their choice being determined according to the best fit obtained between the model output and specific features of the observed EEG waveform. This results in an approximate path through the bifurcation plane of the model obtained from clinical data. We present comparisons of such paths through parameter space from separate seizures from an in idual subject, as well as between different subjects. Differences in the path reflect subtleties of variation in the dynamics of EEG, which at present appear indistinguishable using standard clinical techniques.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 02-2019
Abstract: The untargeted discovery and replication of a blood protein panel shows promise for predicting preclinical Alzheimer’s disease.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Alejo Nevado-Holgado.