Abstract Bioinformatics methods can be used to quantify mitochondrial DNA copy number from whole genome sequencing (WGS) data. We evaluated mitochondrial DNA copy number from human brain-derived WGS data using the fastMitoCalc tool. 341 Parkinson’s Disease cerebellum samples were compared with 74 age-matched controls from the North American Brain Expression Consortium. Parkinson’s Disease cerebellum had significantly higher mitochondrial DNA copy number compared with controls (P = 4.15e–7), and this effect was reproducible in four of five brain banks when analysis was restricted to each resource that contributed Parkinson’s Disease samples to this genetic dataset. Follow-on analyses of 128 Parkinson’s Disease cerebellum samples and 33 controls that had paired neuropathology data and clinical scores demonstrated a significant increase in mitochondrial DNA copy number with Unified Staging System for Lewy Body disorders stages and Unified Parkinson’s Disease Rating Scale (off meds) motor scores. Analysis of Lewy Body scores from ten brain regions showed cerebellum mitochondrial DNA copy number increased upon pathological infestation of α-synuclein aggregates in the brainstem and limbic system but did not increase after late-stage neocortical involvement. This genetics dataset supports previous observations of cerebellum activation in Parkinson’s Disease and suggests mitochondrial DNA copy number may increase to support this regional activation as a compensatory mechanism to pathology or motor symptoms.
ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics
Abstract Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, with personalized medicine, systems biology, and biomedical applications. The application of MS-based proteomics advances our understanding of protein function, cellular signaling, and complex biological systems. MS data analysis is a critical process that includes identifying and quantifying proteins and peptides and then exploring their biological functions in downstream analyses. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets with DIA-NN preinstalled. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analyses. ProtPipe provides downstream analyses, including protein and peptide differential abundance identification, pathway enrichment analysis, protein–protein interaction analysis, and major histocompatibility complex (MHC)–peptide binding affinity analysis. ProtPipe generates annotated tables and visualizations by performing statistical post-processing and calculating fold changes between predefined pairwise conditions in an experimental design. It is an open-source, well-documented tool available at https://github.com/NIH-CARD/ProtPipe, with a user-friendly web interface.
Association of Variants in the SPTLC1 Gene With Juvenile Amyotrophic Lateral Sclerosis
Objective The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age‐at‐onset of Parkinson's disease. Methods We performed the first genomewide association study of penetrance and age‐at‐onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non‐cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age‐at‐onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genomewide association study of Parkinson's disease was able to explain variability in penetrance and age‐at‐onset in LRRK2 mutation carriers. Results A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; p value = 2.5E‐08, beta = 1.27, SE = 0.23, risk allele: C) met genomewide significance for the penetrance model. Co‐immunoprecipitation analyses of LRRK2 and CORO1C supported an interaction between these 2 proteins. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: p value = 1.1E‐07; age‐at‐onset top variant: p value = 9.3E‐07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age‐at‐onset. Interpretation This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations. ANN NEUROL 2021;90:82–94
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
1