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Mitochondrial diseases (MD), such as Leigh syndrome (LS), present with severe neurological and muscular phenotypes in patients, but have no known cure and limited treatment options. Based on their neuroprotective effects against other neurodegenerative diseases in vivo and their positive impact as an antioxidant against complex I deficiency in vitro, we investigated the potential protective effect of metallothioneins (MTs) in an Ndufs4 knockout mouse model (with a very similar phenotype to LS) crossed with an Mt1 overexpressing mouse model (TgMt1). Despite subtle reductions in the expression of neuroinflammatory markers GFAP and IBA1 in the vestibular nucleus and hippocampus, we found no improvement in survival, growth, locomotor activity, balance, or motor coordination in the Mt1 overexpressing Ndufs4−/− mice. Furthermore, at a cellular level, no differences were detected in the metabolomics profile or gene expression of selected one-carbon metabolism and oxidative stress genes, performed in the brain and quadriceps, nor in the ROS levels of macrophages derived from these mice. Considering these outcomes, we conclude that MT1, in general, does not protect against the impaired motor activity or improve survival in these complex I–deficient mice. The unexpected absence of increased oxidative stress and metabolic redox imbalance in this MD model may explain these observations. However, tissue-specific observations such as the mildly reduced inflammation in the hippocampus and vestibular nucleus, as well as differential MT1 expression in these tissues, may yet reveal a tissue- or cell-specific role for MTs in these mice

An imbalance in the estrogen metabolism has been associated with an increased risk of breast cancer development. Evaluation of the estrogen biotransformation capacity requires monitoring of various estrogen metabolites. Up to now, only some estrogen metabolites could be measured in urine. However, in order to offer tailor made nutritional support or therapies, a complete estrogen metabolite profile is required in order to identify specific deficiencies in this pathway for each patient individually. Here, we focused on this need to quantify as many as possible of the estrogen-related metabolites excreted in urine. The method was developed to quantify 27 estrogen-related metabolites in small urine quantities. This entailed sample clean-up with a multi-step solid phase extraction procedure, derivatisation of the metabolites in the less water-soluble fraction through dansylation, and analyses using liquid chromatography–tandem mass spectrometry (LC-MS/MS). The metabolites accurately quantified by the method devised included parent estrogens, hydroxylated and methylated forms, metabolites of the 16α-hydroxyestrogen pathway, sulphate and glucuronide conjugated forms, precursors and a related steroid hormone. This method was validated and enabled quantification in the high picograms and low nanograms per millilitre range. Finally, analyses of urine samples confirmed detection and quantification of each of the metabolites

An imbalance in the estrogen metabolism has been associated with an increased risk of breast cancer development. Evaluation of the estrogen biotransformation capacity requires monitoring of various estrogen metabolites. Up to now, only some estrogen metabolites could be measured in urine. However, in order to offer tailor made nutritional support or therapies, a complete estrogen metabolite profile is required in order to identify specific deficiencies in this pathway for each patient individually. Here, we focused on this need to quantify as many as possible of the estrogen-related metabolites excreted in urine. The method was developed to quantify 27 estrogen-related metabolites in small urine quantities. This entailed sample clean-up with a multi-step solid phase extraction procedure, derivatisation of the metabolites in the less water-soluble fraction through dansylation, and analyses using liquid chromatography–tandem mass spectrometry (LC-MS/MS). The metabolites accurately quantified by the method devised included parent estrogens, hydroxylated and methylated forms, metabolites of the 16α-hydroxyestrogen pathway, sulphate and glucuronide conjugated forms, precursors and a related steroid hormone. This method was validated and enabled quantification in the high picograms and low nanograms per millilitre range. Finally, analyses of urine samples confirmed detection and quantification of each of the metabolites

Autism spectrum disorder (ASD) is characterized by phenotypic heterogeneity and a complex genetic architecture which includes distinctive epigenetic patterns. We report differential DNA methylation patterns associated with ASD in South African children. An exploratory whole‐epigenome methylation screen using the Illumina 450 K MethylationArray identified differentially methylated CpG sites between ASD and controls that mapped to 898 genes (P ≤ 0.05) which were enriched for nine canonical pathways converging on mitochondrial metabolism and protein ubiquitination. Targeted Next Generation Bisulfite Sequencing of 27 genes confirmed differential methylation between ASD and control in our cohort. DNA pyrosequencing of two of these genes, the mitochondrial enzyme Propionyl‐CoA Carboxylase subunit Beta (PCCB ) and Protocadherin Alpha 12 (PCDHA12 ), revealed a wide range of methylation levels (9–49% and 0–54%, respectively) in both ASD and controls. Three CpG loci were differentially methylated in PCCB (P ≤ 0.05), while PCDHA12 , previously linked to ASD, had two significantly different CpG sites (P ≤ 0.001) between ASD and control. Differentially methylated CpGs were hypomethylated in ASD. Metabolomic analysis of urinary organic acids revealed that three metabolites, 3‐hydroxy‐3‐methylglutaric acid (P = 0.008), 3‐methyglutaconic acid (P = 0.018), and ethylmalonic acid (P = 0.043) were significantly elevated in individuals with ASD. These metabolites are directly linked to mitochondrial respiratory chain disorders, with a putative link to PCCB , consistent with impaired mitochondrial function. Our data support an association between DNA methylation and mitochondrial dysfunction in the etiology of ASD

The 11th International Conference on Rare Diseases and Orphan Drugs (ICORD), South Africa, included the Africa-Rare initiative launch and facilitated multi-stakeholder engagement in the challenges facing, and opportunities for, Africans living with rare diseases. The following ICORD Global Call to Action, developed in collaboration with the International Rare Diseases Research Consortium, synthesizes the outcomes of the deliberations and emphasizes the international collaborative efforts required to address the global effects of rare diseases on public health

Certain estrogen metabolites have been implicated in the pathophysiology of breast cancer. Moreover, the estrogen metabolite profiles of healthy women and those with (a high risk of) breast cancer differ significantly. The development of an analytical method to determine the relative levels of all the estrogen biotransformation products has been described in van der Berg et al. [1]. An improvement on previously developed methods was the ability to also detect molecules such as sulphate and glucuronide conjugates as well as progesterone, estradiol precursors, and metabolites from the 16-hydroxylation metabolic pathway of estrogens simultaneously with all other estrogen metabolites. The data presented here describe the optimisation of a solid phase extraction method with different fractionation steps for LC-MS/MS analysis of 27 estrogen-related metabolites from small urine volumes. Conditions that were optimised include the elution and washing solvent concentration, the urine, loading, washing, and elution volumes, as well as pH. All raw data used to construct the bar graphs presented in this article are included in the supplementary data file. The data indicated that fractionation was necessary in order to elute estrogen metabolites with different chemical properties at different eluate compositions. Only one of the fractions (containing the less water-soluble metabolites) underwent derivatisation before LC-MS/MS analysis