Neuroprotection by the endogenous cannabinoid anandamide and arvanil against in vivo excitotoxicity in the rat: Role of vanilloid receptors and lipoxygenases

Type 1 vanilloid receptors (VR1) have been identified recently in the brain, in which they serve as yet primarily undetermined purposes. The endocannabinoid anandamide (AEA) and some of its oxidative metabolites are ligands for VR1, and AEA has been shown to afford protection against ouabain-induced in vivo excitotoxicity, in a manner that is only in part dependent on the type 1 cannabinoid (CB1) receptor. In the present study, we assessed whether VR1 is involved in neuroprotection by AEA and by arvanil, a hydrolysis-stable AEA analog that is a ligand for both VR1 and CB1. Furthermore, we assessed the putative involvement of lipoxygenase metabolites of AEA in conveying neuroprotection. Using HPLC and gas chromatography/mass spectroscopy, we demonstrated that rat brain and blood cells converted AEA into 12-hydroxy-N-arachidoylethanolamine (12-HAEA) and 15-hydroxy-N-arachidonoylethanolamine (15-HAEA) and that this conversion was blocked by addition of the lipoxygenase inhibitor nordihydroguaiaretic acid. Using magnetic resonance imaging we show the following: (1) pretreatment with the reduced 12-lipoxygenase metabolite of AEA, 12-HAEA, attenuated cytotoxic edema formation in a CB1 receptor-independent manner in the acute phase after intracranial injection of the Na+/K+-ATPase inhibitor ouabain; (2) the reduced 15-lipoxygenase metabolite, 15-HAEA, enhanced the neuroprotective effect of AEA in the acute phase; (3) modulation of VR1, as tested using arvanil, the VR1 agonist capsaicin, and the antagonist capsazepine, leads to neuroprotective effects in this model, and arvanil is a potent neuroprotectant, acting at both CB1 and VR1; and (4) the in vivo neuroprotective effects of AEA are mediated by CB1 but not by lipoxygenase metabolites or VR1.FWN – Publicaties zonder aanstelling Universiteit Leide

Computing linkage disequilibrium aware genome embeddings using autoencoders

Motivation The completion of the genome has paved the way for genome-wide association studies (GWAS), which explained certain proportions of heritability. GWAS are not optimally suited to detect non-linear effects in disease risk, possibly hidden in non-additive interactions (epistasis). Alternative methods for epistasis detection using, e.g. deep neural networks (DNNs) are currently under active development. However, DNNs are constrained by finite computational resources, which can be rapidly depleted due to increasing complexity with the sheer size of the genome. Besides, the curse of dimensionality complicates the task of capturing meaningful genetic patterns for DNNs; therefore necessitates dimensionality reduction. Results We propose a method to compress single nucleotide polymorphism (SNP) data, while leveraging the linkage disequilibrium (LD) structure and preserving potential epistasis. This method involves clustering correlated SNPs into haplotype blocks and training per-block autoencoders to learn a compressed representation of the block’s genetic content. We provide an adjustable autoencoder design to accommodate diverse blocks and bypass extensive hyperparameter tuning. We applied this method to genotyping data from Project MinE, and achieved 99% average test reconstruction accuracy—i.e. minimal information loss—while compressing the input to nearly 10% of the original size. We demonstrate that haplotype-block based autoencoders outperform linear Principal Component Analysis (PCA) by approximately 3% chromosome-wide accuracy of reconstructed variants. To the extent of our knowledge, our approach is the first to simultaneously leverage haplotype structure and DNNs for dimensionality reduction of genetic data

The SOD1-mediated ALS phenotype shows a decoupling between age of symptom onset and disease duration

Superoxide dismutase (SOD1) gene variants may cause amyotrophic lateral sclerosis, some of which are associated with a distinct phenotype. Most studies assess limited variants or sample sizes. In this international, retrospective observational study, we compare phenotypic and demographic characteristics between people with SOD1-ALS and people with ALS and no recorded SOD1 variant. We investigate which variants are associated with age at symptom onset and time from onset to death or censoring using Cox proportional-hazards regression. The SOD1-ALS dataset reports age of onset for 1122 and disease duration for 883 people; the comparator population includes 10,214 and 9010 people respectively. Eight variants are associated with younger age of onset and distinct survival trajectories; a further eight associated with younger onset only and one with distinct survival only. Here we show that onset and survival are decoupled in SOD1-ALS. Future research should characterise rarer variants and molecular mechanisms causing the observed variability