Untargeted metabolic analysis in dried blood spots reveals metabolic signature in 22q11.2 deletion syndrome

Korteling, Dorinde; Boks, Marco P.; Fiksinski, Ania; Hoek, Ilja N. van; Vorstman, Jacob; Verhoeven‐Duif, Nanda M.; Jans, Judith; Zinkstok, Janneke

doi:10.1038/s41398-022-01859-4

Cited by 5 publications

(13 citation statements)

References 39 publications

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“…These findings expand upon an earlier, more limited study of metabolic and proteomic profiling of patients with a definitive diagnosis of 22qDS (Korteling et al, 2022 ) and in the prefrontal cortex (PFC) and hippocampal (HPC) tissue of the murine model, (Wesseling et al, 2017 ) confirming the involvement of pathways previously identified but now expanded (Table 3 ) as well as the involvement and alterations of several other pathways. To our knowledge, this is the first report of the longitudinal metabolic and proteomic profiling and on the identification of unique biomarkers that might in the future be used for early diagnosis, development, and the progression of 22qDS (Fig.…”

Section: Discussionsupporting

confidence: 81%

“…They also observed changes in sphingomyelin, ceramide phosphoethanolamines, tyrosine derivates, carnitines, and pantothenic acid levels (Wesseling et al, 2017 ). A more recent study identified the metabolic signature for 22qDS in dried blood spots along with the associations of these metabolomic patterns with low intellectual functioning and ASD (Korteling et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome

Zafarullah,

Angkustsiri,

Quach

et al. 2024

Metabolomics

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Introduction The chromosome 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with a wide range of brain-related phenotypes including schizophrenia spectrum disorders (SCZ), autism spectrum disorders (ASD), anxiety disorders and attention deficit disorders (ADHD). The typically deleted region in 22q11.2DS contains multiple genes which haploinsufficiency has the potential of altering the protein and the metabolic profiles. Objectives Alteration in metabolic processes and downstream protein pathways during the early brain development may help to explain the increased prevalence of the observed neurodevelopmental phenotypes in 22q11.2DS. However, relatively little is known about the correlation of dysregulated protein/metabolite expression and neurobehavioral impairments in individuals who developed them over time. Methods In this study, we performed untargeted metabolic and proteomic analysis in plasma samples derived from 30 subjects including 16 participants with 22q11.2DS and 14 healthy controls (TD) enrolled in a longitudinal study, aiming to identify a metabolic and protein signature informing about the underlying mechanisms involved in disease development and progression. The metabolic and proteomic profiles were also compared between the participants with 22q11.2DS with and without various comorbidities, such as medical involvement, psychiatric conditions, and autism spectrum disorder (ASD) to detect potential changes among multiple specimens, collected overtime, with the aim to understand the basic underlying mechanisms involved in disease development and progression. Results We observed a large number of statistically significant differences in metabolites between the two groups. Among them, the levels of taurine and arachidonic acid were significantly lower in 22q11.2DS compared to the TD group. In addition, we identified 16 proteins that showed significant changes in expression levels (adjusted P < 0.05) in 22q11.2DS as compared to TD, including those involved in 70 pathways such as gene expression, the PI3K-Akt signaling pathway and the complement system. Within participants with 22q11.2DS, no significant changes in those with and without medical or psychiatric conditions were observed. Conclusion To our knowledge, this is the first report on plasma metabolic and proteomic profiling and on the identification of unique biomarkers in 22q11.2DS. These findings may suggest the potential role of the identified metabolites and proteins as biomarkers for the onset of comorbid conditions in 22q11.2DS. Ultimately, the altered protein pathways in 22q11.2DS may provide insights of the biological mechanisms underlying the neurodevelopmental phenotype and may provide missing molecular outcome measures in future clinical trials to assess early-diagnosis treatment and the efficacy of response to targeted treatment.

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Section: Discussionsupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome

Zafarullah,

Angkustsiri,

Quach

et al. 2024

Metabolomics

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“…Numerous studies show many diseases resembling ASD-like phenotypes often involve chromosome 15q11-q13 segments ( 12 ). Deletions and duplications of chromosomes 15q11.2, 15q13.3, 16p11.2, 22q11.2, and BP1-BP2 are among the common genetic causes of ASD ( 1 , 13 ).…”

Section: Genetic and Environmental Factorsmentioning

confidence: 99%

Neuroplasticity of children in autism spectrum disorder

Chen,

Wang,

Zhang

et al. 2024

Front. Psychiatry

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Autism spectrum disorder (ASD) is a neurodevelopmental disorder that encompasses a range of symptoms including difficulties in verbal communication, social interaction, limited interests, and repetitive behaviors. Neuroplasticity refers to the structural and functional changes that occur in the nervous system to adapt and respond to changes in the external environment. In simpler terms, it is the brain’s ability to learn and adapt to new environments. However, individuals with ASD exhibit abnormal neuroplasticity, which impacts information processing, sensory processing, and social cognition, leading to the manifestation of corresponding symptoms. This paper aims to review the current research progress on ASD neuroplasticity, focusing on genetics, environment, neural pathways, neuroinflammation, and immunity. The findings will provide a theoretical foundation and insights for intervention and treatment in pediatric fields related to ASD.

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“…The authors suggest untargeted metabolomics as a tool for hypothesis generation and biomarker discovery in complex disease processes, based on potential compounds (urate, methionine sulfone, cortisone and 17α-hydroxypregnanolone glucuronide) and mechanisms found as potentially linked with preterm births. 92 Korteling et al 93 used untargeted metabolomics to analyse DBS samples of children and adolescents with a syndrome associated with increased risk of neurodevelopmental phenotypes including autism spectrum disorders (ASD) and intellectual impairment. The untargeted analysis identified metabolic signatures (the authors highlighted proline as a prominent distinguishing biomarker) and the metabolites were associated with the phenotypic expressions of ASD and intelligence quotient impairment.…”

Section: Very Long-chain Acylcarnitine Dehydrogenase Deficiency [Vlca...mentioning

confidence: 99%

Targeted and untargeted metabolomics and lipidomics in dried blood microsampling: Recent applications and perspectives

Couacault,

Avella,

Londoño‐Osorio

et al. 2024

Analytical Science Advances

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Blood microsampling (BµS) offers an alternative to conventional methods that use plasma or serum for profiling human health, being minimally invasive and cost effective, especially beneficial for vulnerable populations. We present a non‐systematic review that offers a synopsis of the analytical methods, applications and perspectives related to dry blood microsampling in targeted and untargeted metabolomics and lipidomics research in the years 2022 and 2023. BµS shows potential in neonatal and paediatric studies, therapeutic drug monitoring, metabolite screening, biomarker research, sports supervision, clinical disorders studies and forensic toxicology. Notably, dried blood spots and volumetric absorptive microsampling options have been more extensively studied than other volumetric technologies. Therefore, we suggest that a further investigation and application of the volumetric technologies will contribute to the use of BµS as an alternative to conventional methods. Conversely, we support the idea that harmonisation of the analytical methods when using BµS would have a positive impact on its implementation.

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Untargeted metabolic analysis in dried blood spots reveals metabolic signature in 22q11.2 deletion syndrome

Cited by 5 publications

References 39 publications

Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome

Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome

Neuroplasticity of children in autism spectrum disorder

Targeted and untargeted metabolomics and lipidomics in dried blood microsampling: Recent applications and perspectives

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