The human neuroblastoma cell line, SH-SY5Y, is a commonly used cell line in studies related to neurotoxicity, oxidative stress, and neurodegenerative diseases. Although this cell line is often used as a cellular model for Parkinson’s disease, the relevance of this cellular model in the context of Parkinson’s disease (PD) and other neurodegenerative diseases has not yet been systematically evaluated.

Objective Higher gluten intake, frequent gastrointestinal infections and adenovirus, enterovirus, rotavirus and reovirus have been proposed as environmental triggers for coeliac disease. However, it is not known whether an interaction exists between the ingested gluten amount and viral exposures in the development of coeliac disease. This study investigated whether distinct viral exposures alone or together with gluten increase the risk of coeliac disease autoimmunity (CDA) in genetically predisposed children. Design The Environmental Determinants of Diabetes in the Young study prospectively followed children carrying the HLA risk haplotypes DQ2 and/or DQ8 and constructed a nested case–control design. From this design, 83 CDA case–control pairs were identified. Median age of CDA was 31 months. Stool samples collected monthly up to the age of 2 years were analysed for virome composition by Illumina next-generation sequencing followed by comprehensive computational virus profiling. Results The cumulative number of stool enteroviral exposures between 1 and 2 years of age was associated with an increased risk for CDA. In addition, there was a significant interaction between cumulative stool enteroviral exposures and gluten consumption. The risk conferred by stool enteroviruses was increased in cases reporting higher gluten intake. Conclusions Frequent exposure to enterovirus between 1 and 2 years of age was associated with increased risk of CDA. The increased risk conferred by the interaction between enteroviruses and higher gluten intake indicate a cumulative effect of these factors in the development of CDA.

Background: Hyperlipidemia is a highly heritable risk factor for coronary artery disease (CAD). While monogenic familial hypercholesterolemia associates with severely increased CAD risk, it remains less clear to what extent a high polygenic load of a large number of LDL (low-density lipoprotein) cholesterol (LDL-C) or triglyceride (TG)-increasing variants associates with increased CAD risk. Methods: We derived polygenic risk scores (PRSs) with ≈6M variants separately for LDL-C and TG with weights from a UK Biobank–based genome-wide association study with ≈324K samples. We evaluated the impact of polygenic hypercholesterolemia and hypertriglyceridemia to lipid levels in 27 039 individuals from the National FINRISK Study (FINRISK) cohort and to CAD risk in 135 638 individuals (13 753 CAD cases) from the FinnGen project (FinnGen). Results: In FINRISK, median LDL-C was 3.39 (95% CI, 3.38–3.40) mmol/L, and it ranged from 2.87 (95% CI, 2.82–2.94) to 3.78 (95% CI, 3.71–3.83) mmol/L between the lowest and highest 5% of the LDL-C PRS distribution. Median TG was 1.19 (95% CI, 1.18–1.20) mmol/L, ranging from 0.97 (95% CI, 0.94–1.00) to 1.55 (95% CI, 1.48–1.61) mmol/L with the TG PRS. In FinnGen, comparing the highest 5% of the PRS to the lowest 95%, CAD odds ratio was 1.36 (95% CI, 1.24–1.49) for the LDL-C PRS and 1.31 (95% CI, 1.19–1.43) for the TG PRS. These estimates were only slightly attenuated when adjusting for a CAD PRS (odds ratio, 1.26 [95% CI, 1.16–1.38] for LDL-C and 1.24 [95% CI, 1.13–1.36] for TG PRS). Conclusions: The CAD risk associated with a high polygenic load for lipid-increasing variants was proportional to their impact on lipid levels and partially overlapping with a CAD PRS. In contrast with a PRS for CAD, the lipid PRSs point to known and directly modifiable risk factors providing additional guidance for clinical translation.

Aim: Current attempts to modulate the human microbiota and immune responses are based on probiotics or human-derived bacterial transplants. We investigated microbial modulation by soil and plant-ba...

We set out to explore associations between the stool bacteriome profiles and early-onset islet autoimmunity, taking into account the interactions with the virus component of the microbiome. Serial stool samples were longitudinally collected from 18 infants and toddlers with early-onset islet autoimmunity (median age 17.4 months) followed by type 1 diabetes, and 18 tightly matched controls from the Finnish Diabetes Prediction and Prevention (DIPP) cohort. Three stool samples were analyzed, taken 3, 6, and 9 months before the first detection of serum autoantibodies in the case child. The risk of islet autoimmunity was evaluated in relation to the composition of the bacteriome 16S rDNA profiles assessed by mass sequencing, and to the composition of DNA and RNA viromes. Four operational taxonomic units were significantly less abundant in children who later on developed islet autoimmunity as compared to controls—most markedly the species of Bacteroides vulgatus and Bifidobacterium bifidum. The alpha or beta diversity, or the taxonomic levels of bacterial phyla, classes or genera, showed no differences between cases and controls. A correlation analysis suggested a possible relation between CrAssphage signals and quantities of Bacteroides dorei. No apparent associations were seen between development of islet autoimmunity and sequences of yet unknown origin. The results confirm previous findings that an imbalance within the prevalent Bacteroides genus is associated with islet autoimmunity. The detected quantitative relation of the novel “orphan” bacteriophage CrAssphage with a prevalent species of the Bacteroides genus may exemplify possible modifiers of the bacteriome.

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraint-based modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) γ, CCAAT/enhancer binding protein (CEBP) α, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-3-phosphate acyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions.