Phenomenome Discoveries (Canada)

BackgroundRhizomelic chondrodysplasia punctata (RCDP) is an inherited ultra-rare disease which results in severely impaired physical and mental development. Mutations in one of five genes involved in plasmalogen biosynthesis have been reported to drive disease pathology. Estimates of disease incidence have been extremely challenging due to the rarity of the disorder, preventing an understanding of the unmet medical need. To address this, we have prepared a disease incidence and prevalence model based on genetic epidemiology approaches to estimate the total number of RCDP patients affected, and their demographic characteristics.ResultsExtraction of allelic frequencies for known and predicted pathogenic variants in PEX7, GNPAT, AGPS, FAR1, PEX5 (limited to the PTS2 domain encoding region) genes, from large-scale human genetic diversity datasets (TopMed and gnomAD) revealed the mutational landscape contributing to the RCDP patient population in the US and Europe. We computed genetic prevalence to derive birth incidence for RCDP and modeled the impact to life expectancy to obtain high confidence estimates of disease prevalence. Our population genetics-based model indicates PEX7 variants are expected to contribute to the majority of RCDP cases in both the US and Europe; closely aligning with clinical reports. Furthermore, this model provides estimates for RCDP subtypes due to mutations in other genes, including exceedingly rare subtypes.ConclusionIn total, the estimated number of RCDP patients in the US and the five largest European countries (UK, Germany, France, Italy and Spain) is between 516 and 847 patients, all under the age of 35 years old. This model provides a quantitative framework for better understanding the unmet medical need in RCDP, to help guide disease awareness and diagnosis efforts for this specific patient group.

ABSTRACTRhizomelic chondrodysplasia punctata (RCDP) is a rare genetic disorder caused by mutations in peroxisomal genes essential for plasmalogen biosynthesis. Plasmalogens are a class of membrane glycerophospholipids containing a vinyl-ether-linked fatty alcohol at the sn-1 position that affect functions including vesicular transport, membrane protein function and free radical scavenging. A logical rationale for the treatment of RCDP is therefore the therapeutic augmentation of plasmalogens. The objective of this work was to provide a preliminary characterization of a novel vinyl-ether synthetic plasmalogen, PPI-1040, in support of its potential utility as an oral therapeutic option for RCDP. First, wild-type mice were treated with 13C6-labeled PPI-1040, which showed that the sn-1 vinyl-ether and the sn-3 phosphoethanolamine groups remained intact during digestion and absorption. Next, a 4-week treatment of adult plasmalogen-deficient Pex7hypo/null mice with PPI-1040 showed normalization of plasmalogen levels in plasma, and variable increases in plasmalogen levels in erythrocytes and peripheral tissues (liver, small intestine, skeletal muscle and heart). Augmentation was not observed in brain, lung and kidney. Functionally, PPI-1040 treatment normalized the hyperactive behavior observed in the Pex7hypo/null mice as determined by open field test, with a significant inverse correlation between activity and plasma plasmalogen levels. Parallel treatment with an equal amount of ether plasmalogen precursor, PPI-1011, did not effectively augment plasmalogen levels or reduce hyperactivity. Our findings show, for the first time, that a synthetic vinyl-ether plasmalogen is orally bioavailable and can improve plasmalogen levels in an RCDP mouse model. Further exploration of its clinical utility is warranted.This article has an associated First Person interview with the joint first authors of the paper.

A regional bedrock map provides a foundation from which to build geological interpretations. However, rapid and accurate bedrock mapping in an area that lacks outcrop is a common problem, especially in regions with sparse data. A historic bedrock map from an Au and base metal project in the Kerkasha district, Eritrea, is significantly improved by predicting bedrock distribution in areas previously mapped as transported overburden. Publicly-available remote sensing data (DTM and ASTER) were combined with airborne geophysical data (magnetics and radiometrics) to provide features for bedrock prediction. Remote sensing data were pre-processed using Principal Components Analysis (PCA) to yield an equal number of principal components (PC) as input features. Four iterations were trialled, using different combinations of remote sensing PC features. The two initial trials used all available remote sensing data but compared results when feature ranking and selection is applied to reduce the number of PCs used for training and classification. The subsequent two trials used subsets of available remote-sensing data, selected based on domain expertise (i.e., the domain-specific knowledge of a geologist), with all respective PCs were retained. Five-fold cross-validation scores were highest when a DTM, magnetics, and radiometrics data were included as input features. However, qualitative visual appraisal of predicted results across trials, complemented by maps of class membership uncertainty (using a measure of entropy), indicate that geologically-meaningful results are also produced when radiometrics are omitted and only the DTM and magnetics are used. The study concludes with a generalised workflow to assist geologists who are seeking to improve the bedrock interpretation of areas under cover in a single area of interest. Domain expertise is shown to be critical for the selection of appropriate input features and validation of results during predictive lithologic mapping.

There is compelling evidence to the theory that the 5-HT2B receptor plays a direct and crucial role in the mechanisms of actions of methamphetamine (METH) and of 3,4-methylenedioxy- methamphetamine (MDMA) leading to addiction. The involvement of 5-HT1A receptors in all of the biochemical and behavioural consequences such as anxiety, depression, memory impairment, and cognitive dysfunction, resulting from long-term METH/MDMA abuse, has also been unequivocally established. On the basis of these facts, a dual receptor hypothesis based on postsynaptic 5-HT2B receptor antagonist and 5-HT1A receptor agonist activities in the central nervous system (CNS), is proposed.

IntroductionDocosahexaenoic acid (DHA) and DHA-containing ethanolamine plasmalogens (PlsEtn) are decreased in the brain, liver and the circulation in Alzheimer's disease. Decreased supply of plasmalogen precursors to the brain by the liver, as a result of peroxisomal deficits is a process that probably starts early in the AD disease process. To overcome this metabolic compromise, we have designed an orally bioavailable DHA-containing ether lipid precursor of plasmalogens. PPI-1011 is an alkyl-diacyl plasmalogen precursor with palmitic acid at sn-1, DHA at sn-2 and lipoic acid at sn-3. This study outlines the oral pharmacokinetics of this precursor and its conversion to PlsEtn and phosphatidylethanolamines (PtdEtn).MethodsRabbits were dosed orally with PPI-1011 in hard gelatin capsules for time-course and dose response studies. Incorporation into PlsEtn and PtdEtn was monitored by LC-MS/MS. Metabolism of released lipoic acid was monitored by GC-MS. To monitor the metabolic fate of different components of PPI-1011, we labeled the sn-1 palmitic acid, sn-2 DHA and glycerol backbone with13C and monitored their metabolic fates by LC-MS/MS.ResultsPPI-1011 was not detected in plasma suggesting rapid release of sn-3 lipoic acid via gut lipases. This conclusion was supported by peak levels of lipoic acid metabolites in the plasma 3 hours after dosing. While PPI-1011 did not gain access to the plasma, it increased circulating levels of DHA-containing PlsEtn and PtdEtn. Labeling experiments demonstrated that the PtdEtn increases resulted from increased availability of DHA released via remodeling at sn-2 of phospholipids derived from PPI-1011. This release of DHA peaked at 6 hrs while increases in phospholipids peaked at 12 hr. Increases in circulating PlsEtn were more complex. Labeling experiments demonstrated that increases in the target PlsEtn, 16:0/22:6, consisted of 2 pools. In one pool, the intact precursor received a sn-3 phosphoethanolamine group and desaturation at sn-1 to generate the target plasmalogen. The second pool, like the PtdEtn, resulted from increased availability of DHA released during remodeling of sn-2. In the case of sn-1 18:0 and 18:1 plasmalogens with [13C3]DHA at sn-2, labeling was the result of increased availability of [13C3]DHA from lipid remodeling. Isotope and repeated dosing (2 weeks) experiments also demonstrated that plasmalogens and/or plasmalogen precursors derived from PPI-1011 are able to cross both the blood-retinal and blood-brain barriers.ConclusionsOur data demonstrate that PPI-1011, an ether lipid precursor of plasmalogens is orally bioavailable in the rabbit, augmenting the circulating levels of unesterified DHA and DHA-containing PlsEtn and PtdEtn. Other ethanolamine plasmalogens were generated from the precursor via lipid remodeling (de-acylation/re-acylation reactions at sn-2) and phosphatidylethanolamines were generated via de-alkylation/re-acylation reactions at sn-1. Repeated oral dosing for 2 weeks with PPI-1011 resulted in dose-dependent increases in circulating DHA and DHA-containing plasmalogens. These products and/or precursors were also able to cross the blood-retinal and blood-brain barriers.

Nutrition is known to interact with genotype in human metabolic syndromes, obesity, and diabetes, and also in Drosophila metabolism. Plasticity in metabolic responses, such as changes in body fat or blood sugar in response to changes in dietary alterations, may also be affected by genotype. Here we show that variants of the foraging (for) gene in Drosophila melanogaster affect the response to food deprivation in a large suite of adult phenotypes by measuring gene by environment interactions (GEI) in a suite of food-related traits. for affects body fat, carbohydrates, food-leaving behavior, metabolite, and gene expression levels in response to food deprivation. This results in broad patterns of metabolic, genomic, and behavioral gene by environment interactions (GEI), in part by interaction with the insulin signaling pathway. Our results show that a single gene that varies in nature can have far reaching effects on behavior and metabolism by acting through multiple other genes and pathways.

All organisms contain a finite set of genes. However, the expression of these genes under varying developmental and environmental conditions results in an almost infinite number of possible phenotypes. To properly study and understand an organism we need to know more than its genetic identity (i.e. its genome) and how its genome responds to developmental and environmental challenges. We need to know how these responses either benefit or harm the organism. To study properly the events leading to, and the effects resulting from, the expression of a gene we need to be able to characterize the corresponding phenotypic changes in an objective and quantifiable manner. Metabolomics is the science of phenotype analysis through the measurement of the small molecules (metabolites) that interact with, are used by, and are created by, the functionally active proteins of a biological system.