Comprehensive proteomics of CSF, plasma, and urine identify DDC and other biomarkers of early Parkinson's disease

Parkinson's disease (PD) starts at the molecular and cellular level long before motor symptoms appear, yet there are no early-stage molecular biomarkers for diagnosis, prognosis prediction, or monitoring therapeutic response. This lack of biomarkers greatly impedes patient care and translational research-L-DOPA remains the standard of care more than 50 years after its introduction. Here, we performed a large-scale, multi-tissue, and multi-platform proteomics study to identify new biomarkers for early diagnosis and disease monitoring in PD. We analyzed 4877 cerebrospinal fluid, blood plasma, and urine samples from participants across seven cohorts using three orthogonal proteomics methods: Olink proximity extension assay, SomaScan aptamer precipitation assay, and liquid chromatography-mass spectrometry proteomics. We discovered that hundreds of proteins were upregulated in the CSF, blood, or urine of PD patients, prodromal PD patients with DAT deficit and REM sleep behavior disorder or anosmia, and non-manifesting genetic carriers of LRRK2 and GBA mutations. We nominate multiple novel hits across our analyses as promising markers of early PD, including DOPA decarboxylase (DDC), also known as L-aromatic acid decarboxylase (AADC), sulfatase-modifying factor 1 (SUMF1), dipeptidyl peptidase 2/7 (DPP7), glutamyl aminopeptidase (ENPEP), WAP four-disulfide core domain 2 (WFDC2), and others. DDC, which catalyzes the final step in dopamine synthesis, particularly stands out as a novel hit with a compelling mechanistic link to PD pathogenesis. DDC is consistently upregulated in the CSF and urine of treatment-naïve PD, prodromal PD, and GBA or LRRK2 carrier participants by all three proteomics methods. We show that CSF DDC levels correlate with clinical symptom severity in treatment-naïve PD patients and can be used to accurately diagnose PD and prodromal PD. This suggests that urine and CSF DDC could be a promising diagnostic and prognostic marker with utility in both clinical care and translational research.

A TrkB and TrkC partial agonist restores deficits in synaptic function and promotes activity-dependent synaptic and microglial transcriptomic changes in a late-stage Alzheimer's mouse model

Introduction

TrkB and TrkC receptor signaling promotes synaptic plasticity and interacts with pathways affected by amyloid-β (Aβ)-toxicity. Upregulating TrkB/C signaling could reduce Alzheimer's disease (AD)-related degenerative signaling, memory loss, and synaptic dysfunction.

Methods

PTX-BD10-2 (BD10-2), a small molecule TrkB/C receptor partial agonist, was orally administered to aged London/Swedish-APP mutant mice (APP L/S ) and wild-type controls (WT). Effects on memory and hippocampal long-term potentiation (LTP) were assessed using electrophysiology, behavioral studies, immunoblotting, immunofluorescence staining, and RNA-sequencing.

Results

Memory and LTP deficits in APP L/S mice were attenuated by treatment with BD10-2. BD10-2 prevented aberrant AKT, CaMKII, and GLUA1 phosphorylation, and enhanced activity-dependent recruitment of synaptic proteins. BD10-2 also had potentially favorable effects on LTP-dependent complement pathway and synaptic gene transcription.

Conclusions

BD10-2 prevented APP L/S /Aβ-associated memory and LTP deficits, reduced abnormalities in synapse-related signaling and activity-dependent transcription of synaptic genes, and bolstered transcriptional changes associated with microglial immune response.

Limited Proteolysis-Mass Spectrometry Reveals Aging-Associated Changes in Cerebrospinal Fluid Protein Abundances and Structures

Cerebrospinal fluid (CSF) proteins and their structures have been implicated repeatedly in aging and neurodegenerative diseases. Limited proteolysis-mass spectrometry (LiP-MS) is a method that enables proteome-wide screening for changes in both protein abundance and structure. To screen for novel aging-associated changes in the CSF proteome, we performed LiP-MS on CSF from young and old mice with a modified analysis pipeline. We found 38 protein groups change in abundance with aging, most dominantly immunoglobulins of the IgM subclass. We discovered six high-confidence candidates that appeared to change in structure with aging, of which Kng1, Itih2, Lp-PLA₂, and 14-3-3 proteins have binding partners or proteoforms known previously to change in the brain with Alzheimer's disease. Intriguingly, using orthogonal validation by Western blot we found the LiP-MS hit Cd5l forms a covalent complex with IgM in mouse and human CSF whose abundance increases with aging. SOMAmer probe signals for all six LiP-MS hits in human CSF, especially 14-3-3 proteins, significantly associate with several clinical features relevant to cognitive function and neurodegeneration. Together, our findings show that LiP-MS can uncover age-related structural changes in CSF with relevance to neurodegeneration.

Genome-wide analysis of common and rare variants via multiple knockoffs at biobank scale, with an application to Alzheimer disease genetics

Knockoff-based methods have become increasingly popular due to their enhanced power for locus discovery and their ability to prioritize putative causal variants in a genome-wide analysis. However, because of the substantial computational cost for generating knockoffs, existing knockoff approaches cannot analyze millions of rare genetic variants in biobank-scale whole-genome sequencing and whole-genome imputed datasets. We propose a scalable knockoff-based method for the analysis of common and rare variants across the genome, KnockoffScreen-AL, that is applicable to biobank-scale studies with hundreds of thousands of samples and millions of genetic variants. The application of KnockoffScreen-AL to the analysis of Alzheimer disease (AD) in 388,051 WG-imputed samples from the UK Biobank resulted in 31 significant loci, including 14 loci that are missed by conventional association tests on these data. We perform replication studies in an independent meta-analysis of clinically diagnosed AD with 94,437 samples, and additionally leverage single-cell RNA-sequencing data with 143,793 single-nucleus transcriptomes from 17 control subjects and AD-affected individuals, and proteomics data from 735 control subjects and affected indviduals with AD and related disorders to validate the genes at these significant loci. These multi-omics analyses show that 79.1% of the proximal genes at these loci and 76.2% of the genes at loci identified only by KnockoffScreen-AL exhibit at least suggestive signal (p < 0.05) in the scRNA-seq or proteomics analyses. We highlight a potentially causal gene in AD progression, EGFR, that shows significant differences in expression and protein levels between AD-affected individuals and healthy control subjects.

Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder

Most genetic risk for psychiatric disease lies in regulatory regions, implicating pathogenic dysregulation of gene expression and splicing. However, comprehensive assessments of transcriptomic organization in diseased brains are limited. In this work, we integrated genotypes and RNA sequencing in brain samples from 1695 individuals with autism spectrum disorder (ASD), schizophrenia, and bipolar disorder, as well as controls. More than 25% of the transcriptome exhibits differential splicing or expression, with isoform-level changes capturing the largest disease effects and genetic enrichments. Coexpression networks isolate disease-specific neuronal alterations, as well as microglial, astrocyte, and interferon-response modules defining previously unidentified neural-immune mechanisms. We integrated genetic and genomic data to perform a transcriptome-wide association study, prioritizing disease loci likely mediated by cis effects on brain expression. This transcriptome-wide characterization of the molecular pathology across three major psychiatric disorders provides a comprehensive resource for mechanistic insight and therapeutic development.

The cystic fibrosis lower airways microbial metagenome

Chronic airway infections determine most morbidity in people with cystic fibrosis (CF). Herein, we present unbiased quantitative data about the frequency and abundance of DNA viruses, archaea, bacteria, moulds and fungi in CF lower airways.

Induced sputa were collected on several occasions from children, adolescents and adults with CF. Deep sputum metagenome sequencing identified, on average, approximately 10 DNA viruses or fungi and several hundred bacterial taxa.

The metagenome of a CF patient was typically found to be made up of an individual signature of multiple, lowly abundant species superimposed by few disease-associated pathogens, such as Pseudomonas aeruginosa and Staphylococcus aureus, as major components. The host-associated signatures ranged from inconspicuous polymicrobial communities in healthy subjects to low-complexity microbiomes dominated by the typical CF pathogens in patients with advanced lung disease. The DNA virus community in CF lungs mainly consisted of phages and occasionally of human pathogens, such as adeno- and herpesviruses. The S. aureus and P. aeruginosa populations were composed of one major and numerous minor clone types.

The rare clones constitute a low copy genetic resource that could rapidly expand as a response to habitat alterations, such as antimicrobial chemotherapy or invasion of novel microbes.

The CF lung metagenome is composed of few viruses and fungi and hundreds of bacterial species, clones and subcloneshttp://ow.ly/ZiqUE