No abstract

Transcobalamin (TC) transports cobalamin from blood into cells. TC deficiency is a rare autosomal recessive disorder usually presenting in early infancy with failure to thrive, weakness, diarrhoea, pallor, anemia, and pancytopenia or agammaglobulinemia. It can sometimes resemble neonatal leukemia or severe combined immunodeficiency disease. Diagnosis of TC deficiency is suspected based on megaloblastic anemia, elevation of total plasma homocysteine, and blood or urine methylmalonic acid. It is confirmed by studying the synthesis of TC in cultured fibroblasts, or by molecular analysis of the TCN2 gene. TC deficiency is treatable with supplemental cobalamin, but the optimal type, route and frequency of cobalamin administration and long term patient outcomes are unknown. Here we present a series of 30 patients with TC deficiency, including an update on multiple previously published patients, in order to evaluate the different treatment strategies and provide information about long term outcome. Based on the data presented, current practice appears to favour treatment of individuals with TC deficiency by intramuscular injections of hydroxy- or cyanocobalamin. In most cases presented, at least weekly injections (1 mg IM) were necessary to ensure optimal treatment. Most centres adjusted the treatment regimen based on monitoring CBC, total plasma homocysteine, plasma and urine methylmalonic acid, as well as, clinical status. Finally, continuing IM treatment into adulthood appears to be beneficial.

BackgroundPatient-centered health care for children with inborn errors of metabolism (IEM) and their families is important and requires an understanding of patient experiences, needs, and priorities. IEM-specific patient groups have emerged as important voices within these rare disease communities and are uniquely positioned to contribute to this understanding. We conducted qualitative interviews with IEM patient group representatives to increase understanding of patient and family experiences, needs, and priorities and inform patient-centered research and care.MethodsWe developed a sampling frame of patient groups representing IEM disease communities from Canada, the United States, and United Kingdom. With consent, we interviewed participants to explore their views on experiences, needs, and outcomes that are most important to children with IEM and their families. We analyzed the data using a qualitative descriptive approach to identify key themes and sub-themes.ResultsWe interviewed 18 organizational representatives between February 28 and September 17, 2014, representing 16 IEMs and/or disease categories. Twelve participants voluntarily self-identified as parents and/or were themselves patients. Three key themes emerged from the coded data: managing the uncertainty associated with raising and caring for a child with a rare disease; challenges associated with the affected child’s life transitions, and; the collective struggle for improved outcomes and interventions that rare disease communities navigate.ConclusionHealth care providers can support children with IEM and their families by acknowledging and reducing uncertainty, supporting families through children’s life transitions, and contributing to rare disease communities’ progress toward improved interventions, experiences, and outcomes.

Background: We sought to understand the experiences of parents/caregivers of children with inherited metabolic diseases (IMD) in order to inform strategies for supporting patients and their families. We investigated their experiences regarding the management of disease, its impact on child and family life, and interactions with the health care system. Methods: From four Canadian centres, we conducted semi-structured telephone interviews with parents/caregivers of children with an IMD who were born between 2006 and 2015 and who were participating in a larger cohort study. Participants were selected with the aim of achieving a diverse sample with respect to treatment centre, IMD, and age of the child. Interviews emphasized the impacts of the disease and its treatment on the child and family and explicitly queried perceptions of interactions with the health care system. We identified emergent themes from the interview data. Results: We completed interviews with 21 parents/caregivers. The 21 children were aged <1 to 7 years old with IMD that included amino acid disorders, urea cycle disorders, fatty acid oxidation disorders, and organic acid disorders or 'other' IMD. Most parents reported that they and their families had adapted well to their child's diagnosis. Parents used proactive coping strategies to integrate complex disease management protocols into routine family life. An important source of stress was concern about the social challenges faced by their children. Participants reported positive interactions with their most involved health care providers within the metabolic clinic. However, they reported challenges associated with the health care system outside of disease-specific metabolic care, when encountering systems and providers unfamiliar with the child's disease. Conclusions: The successful use of proactive coping strategies among parents of children with IMD in this study suggests the potential value of promoting positive coping and is an important direction for future study. Parents' social concerns for their children were important stressors that warrant consideration by health care providers positioned to support families. Our results with respect to experiences with care highlight the important role of specialized metabolic clinics and point to a need for better coordination of the care that takes place outside the disease-specific management of IMD.

Major depressive disorder (MDD) and bipolar disorder (BD) lack robust biomarkers useful for screening purposes in a clinical setting. A systematic review of the literature was conducted on metabolomic studies of patients with MDD or BD through the use of analytical platforms such as in vivo brain imaging, mass spectrometry, and nuclear magnetic resonance. Our search identified a total of 7,590 articles, of which 266 articles remained for full-text revision. Overall, 249 metabolites were found to be dysregulated with 122 of these metabolites being reported in two or more of the studies included. A list of biomarkers for MDD and BD established from metabolites found to be abnormal, along with the number of studies supporting each metabolite and a comparison of which biological fluids they were reported in, is provided. Metabolic pathways that may be important in the pathophysiology of MDD and BD were identified and predominantly center on glutamatergic metabolism, energy metabolism, and neurotransmission.Using online drug registries, we also illustrate how metabolomics can facilitate the discovery of novel candidate drug targets. K E Y W O R D Sbiochemical, biomarker panel, mood disorders, omics

BackgroundWe propose a phenotype-driven analysis of encrypted exome data to facilitate the widespread implementation of exome sequencing as a clinical genetic screening test.Twenty test-patients with varied syndromes were selected from the literature. For each patient, the mutation, phenotypic data, and genetic diagnosis were available. Next, control exome-files, each modified to include one of these twenty mutations, were assigned to the corresponding test-patients. These data were used by a geneticist blinded to the diagnoses to test the efficiency of our software, PhenoVar. The score assigned by PhenoVar to any genetic diagnosis listed in OMIM (Online Mendelian Inheritance in Man) took into consideration both the patient’s phenotype and all variations present in the corresponding exome. The physician did not have access to the individual mutations. PhenoVar filtered the search using a cut-off phenotypic match threshold to prevent undesired discovery of incidental findings and ranked the OMIM entries according to diagnostic score.ResultsWhen assigning the same weight to all variants in the exome, PhenoVar predicted the correct diagnosis in 10/20 patients, while in 15/20 the correct diagnosis was among the 4 highest ranked diagnoses. When assigning a higher weight to variants known, or bioinformatically predicted, to cause disease, PhenoVar’s yield increased to 14/20 (18/20 in top 4). No incidental findings were identified using our cut-off phenotypic threshold.ConclusionThe phenotype-driven approach described could render widespread use of ES more practical, ethical and clinically useful. The implications about novel disease identification, advancement of complex diseases and personalized medicine are discussed.

ABBREVIATIONSaCDH Array-based comparative genomic hybridization FISH Fluorescence in situ hybridization GDD Global developmental delay WTP Willingness to pay AIM Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with array-based comparative genomic hybridization (aCGH) would have on the total cost of the workup for GDD.METHOD We evaluated the cost-effectiveness of aCGH compared with karyotyping by retrospectively analysing the cost of workup in a cohort of 114 children (69 males; 45 females) representing a consecutive series of children diagnosed with GDD. Anomalies of chromosome number and structure are considered to be the most frequent cause of unexplained nonsyndromic global developmental delay (GDD). RESULTS1 Until recently, karyotyping has been accepted as the standard for genetic evaluation of individuals with GDD.2,3 However this technique cannot detect chromosomal imbalances smaller than 5 to 10 Mb. 4 Fluorescence in situ hybridization (FISH) and multiplex ligation-dependent probe amplification can identify smaller chromosomal gains and losses, but they are targeted approaches useful only for confirming a specific clinical suspicion or for the analysis of subtelomeric regions of the genome known to be frequently affected in GDD. Array-based comparative genomic hybridization (aCGH) technology allows for whole-genome analysis at a resolution much higher than that of conventional karyotyping. aCGH can test many known clinically important loci and identify known syndromes in individuals who would test positive on FISH testing. In children with undiagnosed non-syndromal GDD, aCGH has an aetiological yield of 6.4% after non-diagnostic systematic evaluation (detailed history, physical examination, and targeted or screening laboratory testing). 6 According to Siggberg et al.,7 in individuals with idiopathic intellectual disability and ⁄ or dysmorphic features and ⁄ or malformations, the average detection rate of aCGH after a negative karyotype is 10.8% with low-resolution (1Mb or targeted) arrays and 15.8% with high-resolution arrays (23.6-35kb). Hochstenbach et al.8 reviewed 29 array-based studies of individuals with GDD and concluded that, based on their cohort of 36 325 consecutive karyotyped individuals, aCGH as a single test would detect more than 99% of all pathogenic abnormalities detected by karyotype in individuals with GDD.Current guidelines recommend aCGH as a first genetic test for individuals with unexplained GDD or autism after a thorough history and physical examination. Karyotype analysis is currently recommended over aCGH only for individuals with obvious chromosomal syndromes (e.g. Down syndrome) or a known family history of chromosomal rearrangement. 9-11However, aCGH is still not widely accepted as a first-tier test ...

The purpose of this article is to provide a comprehensive review of metabolomics studies for psychosis, as a means of biomarker discovery. Manuscripts were selected for review if they involved discovery of metabolites using high-throughput analysis in human subjects and were published in the last decade. The metabolites identified were searched in Human Metabolome Data Base (HMDB) for a link to psychosis. Metabolites associated with psychosis based on evidence in HMBD were then searched using PubMed to explore the availability of further evidence. Almost all of the studies which underwent full review involved patients with schizophrenia. Ten biomarkers were identified. Six of them were reported in two or more independent metabolomics studies: N-acetyl aspartate, lactate, tryptophan, kynurenine, glutamate, and creatine. Four additional metabolites were encountered in a single metabolomics study but had significant evidence (two supporting articles or more) for a link to psychosis based on PubMed: linoleic acid, D-serine, glutathione, and 3-hydroxybutyrate. The pathways affected are discussed as they may be relevant to the pathophysiology of psychosis, and specifically of schizophrenia, as well as, constitute new drug targets for treatment of related conditions. Based on the biomarkers identified, early diagnosis of schizophrenia and/or monitoring may be possible.