| 51. |
- Westwood, Sarah, et al.
(författare)
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Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort
- 2020
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Ingår i: Journal of Alzheimer's Disease. - : IOS Press. - 1387-2877 .- 1875-8908. ; 74:1, s. 213-225
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Tidskriftsartikel (refereegranskat)abstract
- We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.
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| 52. |
- Zhang, Y. T., et al.
(författare)
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Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks
- 2022
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.Methods: We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid 13 (A13) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with A13, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis.Results: Age and APOE alone predicted A13, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway.Conclusion: Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.
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| 53. |
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| 54. |
- Jansen, Iris E, et al.
(författare)
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Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers.
- 2022
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Ingår i: Acta neuropathologica. - : Springer Science and Business Media LLC. - 1432-0533 .- 0001-6322. ; 144:5, s. 821-842
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Tidskriftsartikel (refereegranskat)abstract
- Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n=8074; replication n=5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.
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| 55. |
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| 56. |
- Kim, Min, et al.
(författare)
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Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort
- 2019
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Ingår i: Alzheimer's & Dementia. - : Elsevier. - 1552-5260 .- 1552-5279. ; 15:6, s. 817-827
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers.METHODS: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis.RESULTS: Eight metabolites were associated with amyloid β and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory.DISCUSSION: PFAMs have been found increased and associated with amyloid β burden in CSF and clinical measures.
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| 57. |
- Konijnenberg, E., et al.
(författare)
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APOE ϵ4 genotype-dependent cerebrospinal fluid proteomic signatures in Alzheimer's disease
- 2020
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Ingår i: Alzheimer's Research and Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Aggregation of amyloid β into plaques in the brain is one of the earliest pathological events in Alzheimer's disease (AD). The exact pathophysiology leading to dementia is still uncertain, but the apolipoprotein E (APOE) ϵ4 genotype plays a major role. We aimed to identify the molecular pathways associated with amyloid β aggregation using cerebrospinal fluid (CSF) proteomics and to study the potential modifying effects of APOE ϵ4 genotype. Methods: We tested 243 proteins and protein fragments in CSF comparing 193 subjects with AD across the cognitive spectrum (65% APOE ϵ4 carriers, average age 75 ± 7 years) against 60 controls with normal CSF amyloid β, normal cognition, and no APOE ϵ4 allele (average age 75 ± 6 years). Results: One hundred twenty-nine proteins (53%) were associated with aggregated amyloid β. APOE ϵ4 carriers with AD showed altered concentrations of proteins involved in the complement pathway and glycolysis when cognition was normal and lower concentrations of proteins involved in synapse structure and function when cognitive impairment was moderately severe. APOE ϵ4 non-carriers with AD showed lower expression of proteins involved in synapse structure and function when cognition was normal and lower concentrations of proteins that were associated with complement and other inflammatory processes when cognitive impairment was mild. Repeating analyses for 114 proteins that were available in an independent EMIF-AD MBD dataset (n = 275) showed that 80% of the proteins showed group differences in a similar direction, but overall, 28% effects reached statistical significance (ranging between 6 and 87% depending on the disease stage and genotype), suggesting variable reproducibility. Conclusions: These results imply that AD pathophysiology depends on APOE genotype and that treatment for AD may need to be tailored according to APOE genotype and severity of the cognitive impairment. © 2020 The Author(s).
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| 58. |
- Rodriguez-Palmero, Agusti, et al.
(författare)
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DLG4-related synaptopathy : a new rare brain disorder
- 2021
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Ingår i: Genetics in Medicine. - : Elsevier BV. - 1098-3600 .- 1530-0366. ; 23:5, s. 888-899
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Tidskriftsartikel (refereegranskat)abstract
- PurposePostsynaptic density protein-95 (PSD-95), encoded by DLG4, regulates excitatory synaptic function in the brain. Here we present the clinical and genetic features of 53 patients (42 previously unpublished) with DLG4 variants.MethodsThe clinical and genetic information were collected through GeneMatcher collaboration. All the individuals were investigated by local clinicians and the gene variants were identified by clinical exome/genome sequencing.ResultsThe clinical picture was predominated by early onset global developmental delay, intellectual disability, autism spectrum disorder, and attention deficit–hyperactivity disorder, all of which point to a brain disorder. Marfanoid habitus, which was previously suggested to be a characteristic feature of DLG4-related phenotypes, was found in only nine individuals and despite some overlapping features, a distinct facial dysmorphism could not be established. Of the 45 different DLG4 variants, 39 were predicted to lead to loss of protein function and the majority occurred de novo (four with unknown origin). The six missense variants identified were suggested to lead to structural or functional changes by protein modeling studies.ConclusionThe present study shows that clinical manifestations associated with DLG4 overlap with those found in other neurodevelopmental disorders of synaptic dysfunction; thus, we designate this group of disorders as DLG4-related synaptopathy.
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| 59. |
- Xu, Jin, et al.
(författare)
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Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort
- 2021
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Ingår i: Biomedicines. - : MDPI. - 2227-9059. ; 9:11
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives.METHODS: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD.RESULTS: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046).CONCLUSIONS: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.
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| 60. |
- Calvin, Katherine, et al.
(författare)
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Bioenergy for climate change mitigation: Scale and sustainability
- 2021
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Ingår i: GCB Bioenergy. - : Wiley. - 1757-1707 .- 1757-1693. ; 13:9, s. 1346-1371
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Forskningsöversikt (refereegranskat)abstract
- Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of bioenergy, often used in conjunction with carbon capture and storage. We review the literature on bioenergy use for climate change mitigation, including studies that use top-down integrated assessment models or bottom-up modelling, and studies that do not rely on modelling. We summarize the state of knowledge concerning potential co-benefits and adverse side effects of bioenergy systems and discuss limitations of modelling studies used to analyse consequences of bioenergy expansion. The implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and how bioenergy alters energy systems and land use. Depending on previous land use, widespread deployment of monoculture plantations may contribute to mitigation but can cause negative impacts across a range of other sustainability criteria. Strategic integration of new biomass supply systems into existing agriculture and forest landscapes may result in less mitigation but can contribute positively to other sustainability objectives. There is considerable variation in evaluations of how sustainability challenges evolve as the scale of bioenergy deployment increases, due to limitations of existing models, and uncertainty over the future context with respect to the many variables that influence alternative uses of biomass and land. Integrative policies, coordinated institutions and improved governance mechanisms to enhance co-benefits and minimize adverse side effects can reduce the risks of large-scale deployment of bioenergy. Further, conservation and efficiency measures for energy, land and biomass can support greater flexibility in achieving climate change mitigation and adaptation.
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