Publications by authors named "Adam D Kennedy"

Multi-omics approaches, which integrate genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools in the diagnosis of rare diseases. We used untargeted metabolomics and whole-genome sequencing (WGS) to gain a more comprehensive understanding of a rare disease with a complex presentation affecting female twins from a consanguineous family. The sisters presented with polymicrogyria, a Dandy-Walker malformation, respiratory distress, and multiorgan dysfunctions.

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  • - We analyze a case of a 20-year-old male with an unidentified neurodegenerative disease who had a severe deficiency in nicotinamide intermediates, crucial for NAD(H) biosynthesis.
  • - Metabolic profiling tests showed that the patient's nicotinamide N-methyltransferase (NNMT) enzyme was not active during normal feeding or fasting but became functional after a specific nicotinamide intake.
  • - This case represents a unique instance of adult-onset NNMT deficiency linked to neurodegenerative disease, highlighting the role of metabolomics in identifying rare metabolic disorders.
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  • Recent advancements in newborn screening have improved the detection of inborn errors of metabolism (IEMs), but many treatable conditions are still not included in standard panels or testing.* -
  • This study compares the effectiveness of traditional metabolic screening with untargeted metabolomics for diagnosing IEMs by analyzing data from two groups of clinical samples over several years.* -
  • Results showed a low diagnostic rate (1.3%) for traditional screening, while untargeted metabolomics identified additional IEMs not part of standard protocols, highlighting its potential as a more comprehensive screening method.*
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Introduction: Analysis of blood for the evaluation of clinically relevant biomarkers requires precise collection and sample handling by phlebotomists and laboratory staff. An important consideration for the clinical application of metabolomics are the different anticoagulants utilized for sample collection. Most studies that have characterized differences in metabolite levels in various blood collection tubes have focused on single analytes.

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  • Clinical metabolomics can help identify inborn errors of metabolism and classify genetic variants in patients with rare diseases, making it essential to understand preanalytical factors that affect testing accuracy.
  • The study assessed the effects of thawing human EDTA plasma samples on ice for different durations, as well as the impact of repeated freeze-thaw cycles on metabolomic analysis.
  • Results showed that while thawing samples on ice caused minimal changes (<1% of biochemicals), repeated freeze-thaw cycles led to a higher percentage of changes (~2%), but overall, less than 3% of metabolites should be excluded due to these handling conditions.
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Inborn errors of metabolism (IEM) involving the non-oxidative pentose phosphate pathway (PPP) include the two relatively rare conditions, transketolase deficiency and transaldolase deficiency, both of which can be difficult to diagnosis given their non-specific clinical presentations. Current biochemical testing approaches require an index of suspicion to consider targeted urine polyol testing. To determine whether a broad-spectrum biochemical test could accurately identify a specific metabolic pattern defining IEMs of the non-oxidative PPP, we employed the use of clinical metabolomic profiling as an unbiased novel approach to diagnosis.

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  • Whole-exome sequencing has enhanced the diagnosis of genetic diseases, leading to the development of a clinical metabolomics method that uses mass spectrometry to screen for metabolic disorders by measuring hundreds of metabolites in a single sample.
  • A precision study was conducted on human plasma to assess the reliability of four high-throughput metabolomics platforms, revealing a range of laboratory and inter-assay coefficient of variations (CVs) indicating good precision across samples.
  • The evaluation confirms that the method is robust and reproducible for identifying key metabolites related to inborn errors of metabolism (IEMs), demonstrating its effectiveness in patient screening through consistent analytical results.
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  • The text refers to a correction of an article published with the DOI 10.3389/fnins.2019.00394.
  • This correction indicates that there were errors or updates needed for the original publication.
  • It emphasizes the importance of accuracy and transparency in scientific literature.
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"Children are not tiny adults" is an adage commonly used in pediatrics to emphasize the fact that children often have different physiological responses to sickness and trauma compared to adults. However, despite widespread acceptance of this concept, diagnostic blood testing is an excellent example of clinical care that is not yet customized to the needs of children, especially newborns. Cumulative blood loss resulting from clinical testing does not typically impact critically ill adult patients, but can quickly escalate in children, leading to iatrogenic anemia and related comorbidities.

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Broad-scale untargeted biochemical phenotyping is a technology that supplements widely accepted assays, such as organic acid, amino acid, and acylcarnitine analyses typically utilized for the diagnosis of inborn errors of metabolism. In this study, we investigate the analyte changes associated with 4-aminobutyrate aminotransferase (ABAT, GABA transaminase) deficiency and treatments that affect GABA metabolism. GABA-transaminase deficiency is a rare neurodevelopmental and neurometabolic disorder caused by mutations in and resulting in accumulation of GABA in the cerebrospinal fluid (CSF).

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Purpose: Untargeted metabolomic analysis is increasingly being used in the screening and management of individuals with inborn errors of metabolism (IEM). We aimed to test whether untargeted metabolomic analysis in plasma might be useful for monitoring the disease course and management of urea cycle disorders (UCDs).

Methods: Untargeted mass spectrometry-based metabolomic analysis was used to generate z-scores for more than 900 metabolites in plasma from 48 individuals with various UCDs.

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Article Synopsis
  • - Metabolomics involves the untargeted analysis of small molecules in biological samples, revealing a global biochemical profile influenced by genetics, environment, and microbiomes, linking it to health outcomes.
  • - The technology, used for over a decade in research, holds promise for clinical diagnostics across various fields, but its application must consider distinct challenges compared to research settings to ensure meaningful results.
  • - Future advancements are needed to integrate metabolomics into clinical practice and gain recognition in the medical and regulatory fields, focusing on aspects like test design, data accuracy, and individual biochemical analysis.
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Purpose: Peroxisome biogenesis disorders-Zellweger spectrum disorders (PBD-ZSD) are metabolic diseases with multisystem manifestations. Individuals with PBD-ZSD exhibit impaired peroxisomal biochemical functions and have abnormal levels of peroxisomal metabolites, but the broader metabolic impact of peroxisomal dysfunction and the utility of metabolomic methods is unknown.

Methods: We studied 19 individuals with clinically and molecularly characterized PBD-ZSD.

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This study focused on the hypothesis that cognitive decline in aged dogs could be attenuated by dietary supplementation with a nutrient blend consisting of antioxidants, B vitamins, fish oil and l-arginine, referred to hereafter as the Brain Protection Blend (BPB). Baseline cognitive assessment before the start of treatment was used to establish cognitively equivalent control (10·464+2·33 kg) and treatment (12·118+3·386 kg) groups of aged dogs between 9·1 and 11·5 years of age and with body condition score of 5. After an initial wash-in period, all dogs were tested over a 6-month period on cognitive test protocols that assessed four phases of a landmark discrimination learning protocol, which assessed a spatial learning skill based on utilisation of external cues, and egocentric discrimination task, which assessed spatial learning based on internal body-centred cues.

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Serine biosynthesis defects are autosomal recessive metabolic disorders resulting from the deficiency of any of the three enzymes involved in de novo serine biosynthesis, specifically phosphoglycerate dehydrogenase (PGDH), phosphoserine aminotransferase (PSAT), and phosphoserine phosphatase (PSP). In this study, we performed metabolomic profiling on 4 children with serine biosynthesis defects; 3 with PGDH deficiency and 1 with PSAT deficiency. The evaluations were performed at baseline and with serine and glycine supplementation.

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Introduction: The domesticated dog, , has been selectively bred to produce extreme diversity in phenotype and genotype. Dogs have an immense diversity in weight and height. Specific differences in metabolism have not been characterized in small dogs as compared to larger dogs.

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Global metabolomic profiling offers novel opportunities for the discovery of biomarkers and for the elucidation of pathogenic mechanisms that might lead to the development of novel therapies. GLUT1 deficiency syndrome (GLUT1-DS) is an inborn error of metabolism due to reduced function of glucose transporter type 1. Clinical presentation of GLUT1-DS is heterogeneous and the disorder mirrors patients with epilepsy, movement disorders, or any paroxysmal events or unexplained neurological manifestation triggered by exercise or fasting.

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Background: Phenotyping technologies featured in the diagnosis of inborn errors of metabolism, such as organic acid, amino acid, and acylcarnitine analyses, recently have been supplemented by broad-scale untargeted metabolomic phenotyping. We investigated the analyte changes associated with aromatic amino acid decarboxylase (AADC) deficiency and dopamine medication treatment.

Methods: Using an untargeted metabolomics platform, we analyzed ethylenediaminetetraacetic acid plasma specimens, and biomarkers were identified by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort.

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Objective: To interrogate the metabolic profile of five subjects from three families with rare, nonsense and missense mutations in SLC13A5 and Early Infantile Epileptic Encephalopathies (EIEE) characterized by severe, neonatal onset seizures, psychomotor retardation and global developmental delay.

Methods: Mass spectrometry of plasma, CSF and urine was used to identify consistently dysregulated analytes in our subjects.

Results: Distinctive elevations of citrate and dysregulation of citric acid cycle intermediates, supporting the hypothesis that loss of SLC13A5 function alters tricarboxylic acid cycle (TCA) metabolism and may disrupt metabolic compartmentation in the brain.

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Article Synopsis
  • The study aimed to analyze the molecular composition of human cerebrospinal fluid (CSF) to enhance untargeted screening for inborn errors of metabolism (IEMs) using advanced metabolomics techniques.
  • Utilizing an integrated workflow involving chromatographic methods and mass spectrometry, researchers identified 435 different biochemicals in CSF, noting that a significant portion of these were also found in urine and plasma samples.
  • The findings highlighted how CSF metabolomics could effectively reveal disrupted metabolic patterns, demonstrated through a case study on a patient with dihydropteridine reductase (DHPR) deficiency, paving the way for better screening methods for metabolic disorders in pediatrics.
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Background: Delaying plasma separation after phlebotomy (processing delay) can cause perturbations of numerous small molecule analytes. This poses a major challenge to the clinical application of metabolomics analyses. In this study, we further define the analyte changes that occur during processing delays and generate a model for the post hoc detection of this preanalytical error.

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Aims: We wished to determine the efficacy of using urine as an analyte to screen for a broad range of metabolic products associated with multiple different types of inborn errors of metabolism (IEMs), using an automated mass spectrometry-based assay. Urine was compared with plasma samples from a similar cohort analyzed using the same assay. Specimens were analyzed using two different commonly utilized urine normalization methods based on creatinine and osmolality, respectively.

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Recent studies have implicated trimethylamine N-oxide (TMAO) in atherosclerosis, raising concern about L-carnitine, a common supplement for patients with inborn errors of metabolism (IEMs) and a TMAO precursor metabolized, in part, by intestinal microbes. Dietary meat restriction attenuates carnitine-to-TMAO conversion, suggesting that TMAO production may not occur in meat-restricted individuals taking supplemental L-carnitine, but this has not been tested. Here, we mine a metabolomic dataset to assess TMAO levels in patients with diverse IEMs, including organic acidemias.

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