Capturing essential physiological aspects of interacting cartilage and bone tissue with osteoarthritis pathophysiology: a human osteochondral unit-on-a-chip model

Given the multi-tissue aspects of osteoarthritis (OA) pathophysiology, translation of OA susceptibility genes towards underlying biological mechanism and eventually drug target discovery requires appropriate human in vitro OA models that incorporate both functional bone and cartilage tissue units. Therefore, a microfluidic chip is developed with an integrated fibrous polycaprolactone matrix in which neo-bone and cartilage are produced, that could serve as a tailored human in vitro disease model of the osteochondral unit of joints. The model enables to evaluate OA-related environmental perturbations to (individual) tissue units by controlling environmental cues, for example by adding biochemical agents. After establishing the co-culture in the system, a layer of cartilaginous matrix is deposited in the chondrogenic compartment, while a bone-like matrix is deposited between the fibers, indicated by both histology and gene expression levels of collagen type 2 and osteopontin, respectively. As proof-of-principle, the bone and cartilaginous tissue are exposed to active thyroid hormone, creating an OA disease model. This results in increased expression levels of hypertrophy markers integrin-binding sialoprotein and alkaline phosphatase in both cartilage and bone, as expected. Altogether, this model could contribute to enhanced translation from OA risk genes towards novel OA therapies.Molecular Epidemiolog

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

The original version of the Supplementary Information associated with this Article included an incorrect Supplementary Data 1 file, in which additional delimiters were included in the first column for a number of rows, resulting in column shifts for some of these rows. The HTML has been updated to include a corrected version of Supplementary Data 1; the original incorrect version of Supplementary Data 1 can be found as Supplementary Information associated with this Correction. In addition, the original version of this Article contained an error in the author affiliations. An affiliation of Abdel Abdellaoui with Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands was inadvertently omitted. This has now been corrected in both the PDF and HTML versions of the Article

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2 Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2 Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.</p

TCTEX1D1 is a genetic modifier of disease progression in Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is caused by pathogenic variants in the DMD gene leading to the lack of dystrophin. Variability in the disease course suggests that other factors influence disease progression. With this study we aimed to identify genetic factors that may account for some of the variability in the clinical presentation. We compared whole-exome sequencing (WES) data in 27 DMD patients with extreme phenotypes to identify candidate variants that could affect disease progression. Validation of the candidate SNPs was performed in two independent cohorts including 301 (BIO-NMD cohort) and 109 (CINRG cohort of European ancestry) DMD patients, respectively. Variants in the Tctex1 domain containing 1 (TCTEX1D1) gene on chromosome 1 were associated with age of ambulation loss. The minor alleles of two independent variants, known to affect TCTEX1D1 coding sequence and induce skipping of its exon 4, were associated with earlier loss of ambulation. Our data show that disease progression of DMD is affected by a new locus on chromosome 1 and demonstrate the possibility to identify genetic modifiers in rare diseases by studying WES data in patients with extreme phenotypes followed by multiple layers of validation

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify > 800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h(total)(2)), and the proportion of heritability captured by known metabolite loci (h(Metabolite-hits)(2)) for 309 lipids and 52 organic acids. Our study reveals significant differences in h(Metabolite-hits)(2) among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h(Metabolite-hits)(2) estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.Cardiolog

Skewed X-inactivation is common in the general female population

Pathophysiology, epidemiology and therapy of agein

Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug–metabolite atlas

Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug–metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug–metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).</p

Author Correction: Heritability estimates for 361 blood metabolites across 40 genome-wide association studies (Nature Communications, (2020), 11, 1, (39), 10.1038/s41467-019-13770-6)

The original version of the Supplementary Information associated with this Article included an incorrect Supplementary Data 1 file, in which additional delimiters were included in the first column for a number of rows, resulting in column shifts for some of these rows. The HTML has been updated to include a corrected version of Supplementary Data 1; the original incorrect version of Supplementary Data 1 can be found as Supplementary Information associated with this Correction. In addition, the original version of this Article contained an error in the author affiliations. An affiliation of Abdel Abdellaoui with Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands was inadvertently omitted. This has now been corrected in both the PDF and HTML versions of the Article