[P2-212]: EUROPEAN MEDICAL INFORMATION FRAMEWORK FOR ALZHEIMER's DISEASE (EMIF-AD): THE BIOMARKER DISCOVERY STUDY

2017 ◽  
Vol 13 (7S_Part_14) ◽  
pp. P691-P692 ◽  
Author(s):  
Isabelle Bos ◽  
Stephanie J.B. Vos ◽  
Rik Vandenberghe ◽  
Philip Scheltens ◽  
Sebastiaan Engelborghs ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Medical Information ◽  
Biomarker Discovery ◽  
Information Framework

scholarly journals Sex-Specific Metabolic Pathways Were Associated with Alzheimer’s Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1610
Author(s):  
Jin Xu ◽  
Rebecca Green ◽  
Min Kim ◽  
Jodie Lord ◽  
Amera Ebshiana ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Metabolic Pathways ◽  
Medical Information ◽  
Biomarker Discovery ◽  
Plasma Metabolites ◽  
Csf Biomarkers ◽  
Tryptophan Pathway ◽  
Personalised Treatment ◽  
Information Framework

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.

scholarly journals A metabolite-based machine learning approach to diagnose Alzheimer’s-type dementia in blood: Results from the European Medical Information Framework for Alzheimer’s Disease biomarker discovery cohort

2019 ◽  
Author(s):  
Daniel Stamate ◽  
Min Kim ◽  
Petroula Proitsi ◽  
Sarah Westwood ◽  
Alison Baird ◽  
...  
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Medical Information ◽  
Biomarker Discovery ◽  
Gradient Boosting ◽  
Plasma Metabolites ◽  
Csf Biomarkers ◽  
Extreme Gradient Boosting ◽  
And Gender

AbstractINTRODUCTIONMachine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer’s Disease (AD). Here we set out to test the performance of metabolites in blood to categorise AD when compared to CSF biomarkers.METHODSThis study analysed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n=883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).RESULTSOn the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.DISCUSSIONThis study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders

P4-046: A EUROPEAN MEDICAL INFORMATION FRAMEWORK FOR ALZHEIMER'S DISEASE (EMIF-AD)

2014 ◽  
Vol 10 ◽  
pp. P799-P799 ◽  
Author(s):  
Pieter Jelle Visser ◽  
Johannes Rolf Streffer ◽  
Simon Lovestone
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Medical Information ◽  
Information Framework

scholarly journals TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer’s disease biomarker levels

2020 ◽  
Author(s):  
Shengjun Hong ◽  
Valerija Dobricic ◽  
Isabelle Bos ◽  
Stephanie J. B. Vos ◽  
Dmitry Prokopenko ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Medical Information ◽  
Genome Wide Association Study ◽  
Biomarker Discovery ◽  
Csf Biomarkers ◽  
Sequence Of Events ◽  
Genome Wide ◽  
Csf Levels

AbstractBackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimer’s disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome.MethodsDNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals. GWAS analyses applied linear regression models adjusting for relevant covariates.FindingsWe identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1.InterpretationOur study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

scholarly journals Epigenome-wide meta-analysis of DNA methylation differences in prefrontal cortex implicates the immune processes in Alzheimer’s disease

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Lanyu Zhang ◽  
Tiago C. Silva ◽  
Juan I. Young ◽  
Lissette Gomez ◽  
Michael A. Schmidt ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Prefrontal Cortex ◽  
Biomarker Discovery ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Braak Stage ◽  
Polycomb Repressive Complex 2 ◽  
Differentially Methylated Genes

AbstractDNA methylation differences in Alzheimer’s disease (AD) have been reported. Here, we conducted a meta-analysis of more than 1000 prefrontal cortex brain samples to prioritize the most consistent methylation differences in multiple cohorts. Using a uniform analysis pipeline, we identified 3751 CpGs and 119 differentially methylated regions (DMRs) significantly associated with Braak stage. Our analysis identified differentially methylated genes such as MAMSTR, AGAP2, and AZU1. The most significant DMR identified is located on the MAMSTR gene, which encodes a cofactor that stimulates MEF2C. Notably, MEF2C cooperates with another transcription factor, PU.1, a central hub in the AD gene network. Our enrichment analysis highlighted the potential roles of the immune system and polycomb repressive complex 2 in pathological AD. These results may help facilitate future mechanistic and biomarker discovery studies in AD.

scholarly journals Proteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Bing Bai ◽  
David Vanderwall ◽  
Yuxin Li ◽  
Xusheng Wang ◽  
Suresh Poudel ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Rna Splicing ◽  
Biomarker Discovery ◽  
Meta Analysis ◽  
Treatment Strategies ◽  
Cell Types ◽  
Synaptic Function ◽  
Mitochondrial Activity ◽  
Cellular Markers

AbstractMass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer’s disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in “amyloidome” (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

scholarly journals Genome-wide association study of Alzheimer’s disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

2019 ◽  
Author(s):  
Shengjun Hong ◽  
Dmitry Prokopenko ◽  
Valerija Dobricic ◽  
Fabian Kilpert ◽  
Isabelle Bos ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Biomarker Discovery ◽  
Case Control ◽  
Genome Wide Association ◽  
Great Promise ◽  
Phenotypic Traits ◽  
Genome Wide

AbstractAlzheimer’s disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures of amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

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