Imputation for Lipidomics and Metabolomics (ImpLiMet): a web-based application for optimization and method selection for missing data imputation.

Motivation: Missing values are prevalent in high-throughput measurements due to various experimental or analytical reasons. Imputation, the process of replacing missing values in a dataset with estimated values, plays an important role in multivariate and machine learning analyses. The three missingness patterns, including missing completely at random, missing at random, and missing not at random, describe unique dependencies between the missing and observed data.

MAGPIE: A Machine Learning Approach to Decipher Protein-Protein Interactions in Human Plasma.

Immunoprecipitation coupled to tandem mass spectrometry (IP-MS/MS) methods are often used to identify protein-protein interactions (PPIs). While these approaches are prone to false positive identifications through contamination and antibody nonspecific binding, their results can be filtered using negative controls and computational modeling. However, such filtering does not effectively detect false-positive interactions when IP-MS/MS is performed on human plasma samples.

Multivariate analyses and machine learning link sex and age with antibody responses to SARS-CoV-2 and vaccination.

Prevention of negative COVID-19 infection outcomes is associated with the quality of antibody responses, whose variance by age and sex is poorly understood. Network approaches identified sex and age effects in antibody responses and neutralization potential of infection and vaccination throughout the COVID-19 pandemic. Neutralization values followed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific receptor binding immunoglobulin G (RIgG), spike immunoglobulin G (SIgG) and spike and receptor immunoglobulin G (S, and RIgA) levels based on COVID-19 status.

Loss of Dnajc21 leads to cytopenia and altered nucleotide metabolism in zebrafish.

Mutations in the DNAJC21 gene were recently described in Shwachman-Diamond syndrome (SDS), a bone marrow failure syndrome with high predisposition for myeloid malignancies. To study the underlying biology in hematopoiesis regulation and disease, we generated the first in vivo model of Dnajc21 deficiency using the zebrafish. Zebrafish dnajc21 mutants phenocopy key SDS patient phenotypes such as cytopenia, reduced growth, and defective protein synthesis.

The SARS-CoV-2 spike glycoprotein interacts with MAO-B and impairs mitochondrial energetics.

SARS-CoV-2 infection is associated with both acute and post-acute neurological symptoms. Emerging evidence suggests that SARS-CoV-2 can alter mitochondrial metabolism, suggesting that changes in brain metabolism may contribute to the development of acute and post-acute neurological complications. Monoamine oxidase B (MAO-B) is a flavoenzyme located on the outer mitochondrial membrane that catalyzes the oxidative deamination of monoamine neurotransmitters.

Choline metabolism underpins macrophage IL-4 polarization and RELMα up-regulation in helminth infection.

Type 2 cytokines like IL-4 are hallmarks of helminth infection and activate macrophages to limit immunopathology and mediate helminth clearance. In addition to cytokines, nutrients and metabolites critically influence macrophage polarization. Choline is an essential nutrient known to support normal macrophage responses to lipopolysaccharide; however, its function in macrophages polarized by type 2 cytokines is unknown.

Signed Distance Correlation (SiDCo): an online implementation of distance correlation and partial distance correlation for data-driven network analysis.

Motivation: There is a need for easily accessible implementations that measure the strength of both linear and non-linear relationships between metabolites in biological systems as an approach for data-driven network development. While multiple tools implement linear Pearson and Spearman methods, there are no such tools that assess distance correlation.

Results: We present here SIgned Distance COrrelation (SiDCo).

Dementia with Lewy bodies post-mortem brains reveal differentially methylated CpG sites with biomarker potential.

Dementia with Lewy bodies (DLB) is a common form of dementia with known genetic and environmental interactions. However, the underlying epigenetic mechanisms which reflect these gene-environment interactions are poorly studied. Herein, we measure genome-wide DNA methylation profiles of post-mortem brain tissue (Broadmann area 7) from 15 pathologically confirmed DLB brains and compare them with 16 cognitively normal controls using Illumina MethylationEPIC arrays.

The clinical spectrum of SMA-PME and in vitro normalization of its cellular ceramide profile.

Objective: The objectives of this study were to define the clinical and biochemical spectrum of spinal muscular atrophy with progressive myoclonic epilepsy (SMA-PME) and to determine if aberrant cellular ceramide accumulation could be normalized by enzyme replacement.

Methods: Clinical features of 6 patients with SMA-PME were assessed by retrospective chart review, and a literature review of 24 previously published cases was performed. Leukocyte enzyme activity of acid ceramidase was assessed with a fluorescence-based assay.

Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.

Computational cell metabolism models seek to provide metabolic explanations of cell behavior under different conditions or following genetic alterations, help in the optimization of in vitro cell growth environments, or predict cellular behavior in vivo and in vitro. In the extremes, mechanistic models can include highly detailed descriptions of a small number of metabolic reactions or an approximate representation of an entire metabolic network. To date, all mechanistic models have required details of individual metabolic reactions, either kinetic parameters or metabolic flux, as well as information about extracellular and intracellular metabolite concentrations.

METAbolomics data Balancing with Over-sampling Algorithms (META-BOA): an online resource for addressing class imbalance.

Motivation: Class imbalance, or unequal sample sizes between classes, is an increasing concern in machine learning for metabolomic and lipidomic data mining, which can result in overfitting for the over-represented class. Numerous methods have been developed for handling class imbalance, but they are not readily accessible to users with limited computational experience. Moreover, there is no resource that enables users to easily evaluate the effect of different over-sampling algorithms.

Differences in Sex-Specific Frequency of Glucocerebrosidase Variant Carriers and Familial Parkinsonism.

Background: Although men and women with the LRRK2 G2019S variant appear to be equally likely to have Parkinson's disease (PD), the sex-distribution among glucocerebrosidase (GBA) variant carriers with PD, including limited to specific variant severities of GBA, is not well understood. Further, the sex-specific genetic contribution to PD without a known genetic variant is controversial.

Objectives: To better understand sex differences in genetic contribution to PD, especially sex-specific frequencies among GBA variant carriers with PD (GBA PD) and LRRK2-G2019S variant carriers with PD (LRRK2 PD).

Generation of the human iPSC line AKOSi010-A from fibroblasts of a female FAHN patient, carrying the compound heterozygous mutation p.Gly45Arg/p.His319Arg.

Fatty acid hydroxylase-associated neurodegeneration (FAHN) is a rare childhood onset neurodegenerative disease caused by mutations in the FA2H gene. Patients display abnormal myelination, cerebellar atrophy and some have iron deposition in the central nervous system. Here we describe the generation of AKOSi010-A, a human induced pluripotent stem cell (hiPSC) line derived from fibroblasts of a female patient carrying the compound heterozygous p.

BATL: Bayesian annotations for targeted lipidomics.

Motivation: Bioinformatic tools capable of annotating, rapidly and reproducibly, large, targeted lipidomic datasets are limited. Specifically, few programs enable high-throughput peak assessment of liquid chromatography-electrospray ionization tandem mass spectrometry data acquired in either selected or multiple reaction monitoring modes.

Results: We present here Bayesian Annotations for Targeted Lipidomics, a Gaussian naïve Bayes classifier for targeted lipidomics that annotates peak identities according to eight features related to retention time, intensity, and peak shape.

Relative Ratios of Human Seasonal Coronavirus Antibodies Predict the Efficiency of Cross-Neutralization of SARS-CoV-2 Spike Binding to ACE2.

Background: Antibodies raised against human seasonal coronaviruses (sCoVs), which are responsible for the common cold, are known to cross-react with SARS-CoV-2 antigens. This prompts questions about their protective role against SARS-CoV-2 infections and COVID-19 severity. However, the relationship between sCoVs exposure and SARS-CoV-2 correlates of protection are not clearly identified.

Serine palmitoyltransferase assembles at ER-mitochondria contact sites.

The accumulation of sphingolipid species in the cell contributes to the development of obesity and neurological disease. However, the subcellular localization of sphingolipid-synthesizing enzymes is unclear, limiting the understanding of where and how these lipids accumulate inside the cell and why they are toxic. Here, we show that SPTLC2, a subunit of the serine palmitoyltransferase (SPT) complex, catalyzing the first step in de novo sphingolipid synthesis, localizes dually to the ER and the outer mitochondrial membrane.

Metabolomics and computational analysis of the role of monoamine oxidase activity in delirium and SARS-COV-2 infection.

Delirium is an acute change in attention and cognition occurring in ~ 65% of severe SARS-CoV-2 cases. It is also common following surgery and an indicator of brain vulnerability and risk for the development of dementia. In this work we analyzed the underlying role of metabolism in delirium-susceptibility in the postoperative setting using metabolomic profiling of cerebrospinal fluid and blood taken from the same patients prior to planned orthopaedic surgery.

Identification of pannexin 1-regulated genes, interactome, and pathways in rhabdomyosarcoma and its tumor inhibitory interaction with AHNAK.

Rhabdomyosarcoma (RMS), the most common soft tissue sarcoma in children, is an aggressive cancer with a poor prognosis. Despite current management, the 5-year survival rate for patients with metastatic RMS is ∼30%; underscoring the need to develop better treatment strategies. We have recently reported that pannexin 1 (PANX1) levels are downregulated in RMS and that restoring its expression inhibits RMS progression.

Computational Identification of Human Biological Processes and Protein Sequence Motifs Putatively Targeted by SARS-CoV-2 Proteins Using Protein-Protein Interaction Networks.

While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK 293 cells published by Gordon et al.

A variant near DHCR24 associates with microstructural properties of white matter and peripheral lipid metabolism in adolescents.

Visceral adiposity has been associated with altered microstructural properties of white matter in adolescents. Previous evidence suggests that circulating phospholipid PC(16:0/2:0) may mediate this association. To investigate the underlying biology, we performed a genome-wide association study (GWAS) of the shared variance of visceral fat, PC(16:0/2:0), and white matter microstructure in 872 adolescents from the Saguenay Youth Study.