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Teunissen, C. E.

Publications and source records attributed to Teunissen, C. E..

10 recordsLinked to original sources

Data-driven evaluation of suitable immunogens for improved antibody selection

Antibodies are indispensable in laboratory and clinical applications due to their high specificity and affinity for protein antigens. However, selecting the right protein fragments as immunogens for antibody production remains challenging. Leveraging the Human Protein Atlas, this study systematically evaluates immunogen properties aiming to identify key factors that influence their suitability. Antibodies were classified as successful or unsuccessful based on standardized validation experiments, and the structural and functional properties of their immunogens were analyzed. Results indicated that longer immunogens often resulted in more successful but less specific antibodies. Shorter immunogens (50 residues or fewer) with disordered or unfolded regions at the N- or C-terminus and long coil stretches, were more likely to generate successful antibodies. Conversely, immunogens with high beta sheet content, multiple secondary structure elements, transmembrane regions, or disulfide bridges were associated with poorer antibody performance. Post-translational modification sites within immunogens appeared to mark beneficial regions for antibody generation. To support antibody selection, a novel R package, immunogenViewer, was developed, enabling researchers to easily apply these insights when immunogen sequences are disclosed. By providing a deeper understanding of immunogen suitability, this study promotes the development of more effective antibodies, ultimately addressing issues of reproducibility and reliability in antibody-based research. The findings are highly relevant to the research community, as end-users often lack control over the immunogen selection process in antibody production.

bioinformatics↗

Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes

Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanisms in vivo, measuring 5,543 CSF metabolites, the largest panel in CSF to date, in 977 individuals of European ancestry. Individuals originated from two separate cohorts including cognitively healthy subjects (n=490) and a well-characterized memory clinic sample, the Amsterdam Dementia Cohort (ADC, n=487). We performed metabolite quantitative trait loci (mQTL) mapping on CSF metabolomics and found 126 significant mQTLs, representing 65 unique CSF metabolites across 51 independent loci. To better understand the role of CSF mQTLs in brain-related disorders, we performed a metabolome-wide association study (MWAS), identifying 40 associations between CSF metabolites and brain traits. Similarly, over 90% of significant mQTLs demonstrated colocalized associations with brain-specific gene expression, unveiling potential neurobiological pathways.

genomics↗

Proteome encoded determinants of protein sorting into extracellular vesicles

Extracellular vesicles (EVs) are membranous structures released by cells into the extracellular space and are thought to be involved in cell-to-cell communication. While EVs and their cargo are promising biomarker candidates, protein sorting mechanisms of proteins to EVs remain unclear. In this study, we ask if it is possible to determine EV association based on the protein sequence. Additionally, we ask what the most important determinants are for EV association. We answer these questions with explainable AI models, using human proteome data from EV databases to train and validate the model. It is essential to correct the datasets for contaminants introduced by coarse EV isolation workflows and for experimental bias caused by mass spectrometry. In this study, we show that it is indeed possible to predict EV association from the protein sequence: a simple sequence-based model for predicting EV proteins achieved an area under the curve of 0.77{+/-}0.01, which increased further to 0.84{+/-}0.00 when incorporating curated post-translational modification (PTM) annotations. Feature analysis shows that EV associated proteins are stable, polar, and structured with low isoelectric point compared to non-EV proteins. PTM annotations emerged as the most important features for correct classification; specifically palmitoylation is one of the most prevalent EV sorting mechanisms for unique proteins. Palmitoylation and nitrosylation sites are especially prevalent in EV proteins that are determined by very strict isolation protocols, indicating they could potentially serve as quality control criteria for future studies. This computational study offers an effective sequence-based predictor of EV associated proteins with extensive characterisation of the human EV proteome that can explain for individual proteins which factors contribute to their EV association.

bioinformatics↗

Testing the link between isoaspartate and Alzheimer's disease etiology

Isoaspartate (isoAsp) is a damaging amino acid residue formed in proteins as a result of spontaneous deamidation. IsoAsp disrupts the secondary and higher order structures of proteins, damaging their functions and making them prone to aggregation. An association has been suggested between isoAsp and Alzheimers Disease (AD). Here we strengthened the link between isoAsp and AD by novel approaches to isoAsp analysis in blood human serum albumin (HSA), the most abundant blood protein, a major carrier of amyloid beta (A{beta}) peptide and phosphorylated tau (pTau) protein in blood and a key participant in their clearance pathway. We discovered a reduced amount of anti-isoAsp antibodies (P < .0001), an elevated isoAsp level in HSA (P < .001), more HSA aggregates (P < .0001) and increased levels of free A{beta} (P < .01) in AD blood compared to healthy controls. We also found that deamidation significantly reduces HSA capacity to bind with A{beta} and pTau (P < .05). These findings support the presence in AD of a bottleneck in clearance of A{beta} and pTau leading to their increased concentrations in brain and facilitating their aggregations there. RESEARCH IN CONTEXTO_LISystematic review: We reviewed the evidence that associates isoaspartate (isoAsp) residue in blood proteins with the etiology of Alzheimers disease (AD). However, the link between isoAsp in blood and aggregation of amyloid beta (A{beta}) peptide and phosphorylated tau (pTau) protein in brain remained unclear. C_LIO_LIInterpretation: For the first time we demonstrate that isoAsp-containing human serum albumin (HSA) forms aggregates with reduced binding capacity toward A{beta} peptide and pTau protein. Using a novel ELISA, we discovered in AD blood elevated levels of isoAsp in HSA, together with reduced endogenous anti-isoAsp antibody levels, suggesting hampered A{beta} and pTau clearance in AD. C_LIO_LIFuture directions: As degradation of the innate anti-isoAsp defenses may take years to develop, investigation of the isoAsp role in early stages of AD is warranted. And enrollment of different neurodegenerative disease cohorts will illustrate if isoAsp is AD-specific or universal to diseases related to aging. C_LI O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

neuroscience↗

In vivo evidence that SORL1, encoding the endosomal recycling receptor SORLA, can function as a causal gene in Alzheimer's Disease

The few established causal genes in Alzheimers disease (AD), mutations in APP and PSENs, have been functionally characterized using biomarkers, capturing an in vivo profile reflecting the diseases initial preclinical phase. SORL1, a gene encoding the endosome recycling receptor SORLA, epidemiologically behaves as a causal gene when truncating mutations lead to partial loss of protein function. Here, in an effort to test whether SORL1 can indeed function as an AD causal gene, we used CRISPR-Cas9-based gene editing to develop a novel model of SORL1 haploinsufficiency in Gottingen Minipigs taking advantage of porcine models for biomarker investigations. SORL1 haploinsufficiency in young minipigs was found to phenocopy the preclinical in vivo profile of AD observed with other causal genes, resulting in spinal fluid abnormalities in A{beta} and tau, with no evident neurodegeneration or amyloid plaque formation. These studies provide functional support that SORL1 is a bona fide causal gene in AD, and when taken together with recent insight on other AD-causal genes, support the idea that dysfunctional endosomal recycling is a dominant pathogenic pathway in the disease.

neuroscience↗

TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels

BackgroundNeurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimers 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.

genomics↗

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

Alzheimers 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 Alzheimers 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 (A{beta}) 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 A{beta}42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A{beta}38 and CSF-A{beta}40 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-A{beta} 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.

genomics↗

PET and CSF amyloid-β status are differently predicted by patient features: Information from discordant cases

BackgroundAmyloid-{beta} PET and CSF A{beta}42 yield discordant results in 10-20% of patients, possibly providing unique information. Although the predictive power of demographic, clinical, genetic and imaging features for amyloid-positivity has previously been investigated, it is unknown whether these features differentially predict amyloid-{beta} status based on PET or CSF, or whether this differs by disease stage.\n\nMethodsWe included 768 patients (subjective cognitive decline (SCD, n=194), mild cognitive impairment (MCI, n=127), dementia (AD and non-AD, n=447) with amyloid-{beta} PET and CSF A{beta}42 measurement within one year. 97(13%) patients had discordant PET/CSF amyloid-{beta} status. We performed parallel random forest models predicting separately PET and CSF status using 17 patient features (demographics, APOE4 positivity, CSF (p)tau, cognitive performance, and MRI visual ratings) in the total patient group and stratified by syndrome diagnosis. Thereafter, we selected features with the highest variable importance measure (VIM) as input for logistic regression models, where amyloid status on either PET or CSF was predicted by (i) the selected patient feature, and (ii) the patient feature adjusted for the status of the other amyloid modality.\n\nResultsAPOE4, CSF tau and p-tau had highest VIM for PET and CSF in all groups. In the amyloid-adjusted logistic regression models, p-tau was a significant predictor for PET-amyloid in SCD (OR=1.02[1.01-1.04], pFDR=0.03), MCI (OR=1.05[1.02-1.07], pFDR<0.01) and dementia (OR=1.04[1.03-1.05], pFDR<0.001), but not for CSF-amyloid. APOE4 (OR=3.07[1.33-7.07], punc<0.01) was associated with CSF-amyloid in SCD, while it was only predictive for PET-amyloid in MCI (OR=9.44[2.93,30.39], pFDR<0.01). Worse MMSE scores (OR=1.21[1.03-1.41], punc=0.02) were associated to CSF-amyloid status in SCD, whereas worse memory (OR=1.17[1.05-1.31], pFDR=0.02) only predicted PET positivity in dementia.\n\nConclusionAmyloid status based on either PET or CSF was predicted by different patient features and this varied by disease stage, suggesting that PET-CSF discordance yields unique information. The stronger associations of both APOE4 carriership and worse memory z-scores with CSF-amyloid in SCD suggests that CSF-amyloid is more sensitive early in the disease course. The higher predictive value of CSF p-tau for a positive PET scan suggests that PET is more specific to AD pathology. These findings can influence the choice between amyloid biomarkers in future studies or trials.

neuroscience↗

Predicting biological age based on the BBMRI-NL 1H-NMR metabolomics repository

The blood metabolome incorporates cues from the environment as well as the hosts genetic background, potentially offering a holistic view of an individuals health status. We have compiled a vast resource of 1H-NMR metabolomics and phenotypic data encompassing over 25,000 samples derived from 26 community and hospital-based cohorts. Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individuals biological age. Exploration in independent cohorts demonstrates that being judged older by ones metabolome, as compared to ones chronological age, confers an increased risk on future cardiovascular disease, mortality and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data. In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardio-metabolic health.

epidemiology↗

Cellular phenotyping of hippocampal progenitors exposed to patient serum predicts conversion to Alzheimer’s Disease

The generation of new neurons persists into adulthood in the human hippocampus and can be modulated by the circulatory systemic environment. Hippocampal neurogenesis is important for learning and memory and is altered in Alzheimers Disease (AD). Evaluating the hippocampal neurogenic process during disease progression could therefore identify neurogenesis as an important target for AD prevention and intervention as well as a biomarker for early disease detection. In this study, we used a human hippocampal progenitor cell line to design an in vitro assay evaluating over time the neurogenic impact of the systemic milieu (i.e. serum) of individuals with mild cognitive impairment (MCI) as they either converted to AD or remained cognitively stable. Cells were exposed to serum collected over several years from the same patients. Cellular phenotyping and linear mixed effects models for repeated measures revealed that decreased proliferation, increased apoptotic hippocampal progenitor cell death and increased hippocampal neurogenesis characterized progression from MCI to AD. Using stepwise logistic regression and machine learning we show that these cellular readouts for the baseline serum sample and years of education of the patient are significant predictors of conversion from MCI to AD, already 3.5 years before AD clinical diagnosis. Finally, serum proteomic analyses indicated pathways linked to the cellular readouts distinguishing MCI to AD converters from non-converters. The proposed assay is thus not only promising for AD pre-clinical diagnosis, but it also provides a proxy into temporal changes of the hippocampal neurogenic process during disease progression.\n\nOne Sentence SummaryIn this study, we demonstrate for the first time that the systemic environment (i.e. blood serum) of mild cognitively impaired patients differentially alters human hippocampal progenitor cell fate to predict conversion to Alzheimers Disease up to 3.5 years before clinical diagnosis.

neuroscience↗