Publications by authors named "J M Budde"

Background: Current challenges in meningioma treatment, including post-surgical complications and cognitive impairments, highlight the need for new treatment alternatives. Immunological interventions have shown promise. However, there is a knowledge gap in characterizing infiltrating immune cells in meningioma and their interplay.

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Introduction: In the research setting, obtaining accurate established biomarker measurements and maximizing use of the precious samples is key. Accurate technologies are available for Alzheimer's disease (AD), but no platform can measure all the established and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA) is a technology that requires 15 µL of sample to measure more than 100 analytes.

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Article Synopsis
  • A genome-wide association study was conducted to analyze cerebrospinal fluid (CSF) and brain metabolite levels, revealing 205 associations for CSF metabolites and 32 for brain metabolites, with a significant portion being new signals.
  • The research found that most new signals for CSF (96.9%) and brain metabolites (71.4%) were related to previously studied metabolites in blood and urine.
  • The study identified 71 metabolite-trait associations linked to various neurological and psychiatric conditions, enhancing understanding of how brain metabolism may influence human traits and diseases.
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The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples.

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In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups.

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