2016
DOI: 10.3945/jn.116.239145
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Metabolomic Changes in Serum of Children with Different Clinical Diagnoses of Malnutrition

Abstract: Background: Mortality in children with severe acute malnutrition (SAM) remains high despite standardized rehabilitation protocols. Two forms of SAM are classically distinguished: kwashiorkor and marasmus. Children with kwashiorkor have nutritional edema and metabolic disturbances, including hypoalbuminemia and hepatic steatosis, whereas marasmus is characterized by severe wasting. The metabolic changes underlying these phenotypes have been poorly characterized, and whether homeostasis is achieved during hospit… Show more

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Cited by 65 publications
(82 citation statements)
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“…This therefore provides an opportunity for scientists to look back at diseases that are currently being neglected, and yet still affecting millions of lives. Metabolomics, as appropriately titled in a 2015 paper “enter the battle against the neglected tropical diseases” 4 , is now being used as an important tool in studying severe acute malnutrition in children 17 , 18 and many other diseases in low-resource areas 4 . However, although one must aim to achieve the highest level of quality, the storage and cold-chain logistical requirements of samples for metabolomics analysis is sometimes limiting the opportunity for this technique to be used in applications where the source of the biological material has limited resources.…”
Section: Discussionmentioning
confidence: 99%
“…This therefore provides an opportunity for scientists to look back at diseases that are currently being neglected, and yet still affecting millions of lives. Metabolomics, as appropriately titled in a 2015 paper “enter the battle against the neglected tropical diseases” 4 , is now being used as an important tool in studying severe acute malnutrition in children 17 , 18 and many other diseases in low-resource areas 4 . However, although one must aim to achieve the highest level of quality, the storage and cold-chain logistical requirements of samples for metabolomics analysis is sometimes limiting the opportunity for this technique to be used in applications where the source of the biological material has limited resources.…”
Section: Discussionmentioning
confidence: 99%
“…Typically, marasmus results from an insufficient intake of energy required to meet the body’s demands, whereas kwashiorkor can result from an insufficient intake of protein despite adequate intake of carbohydrates. To understand the pathophysiologic mechanisms underlying the clinical phenotypes of severe acute undernutrition, Giovanni et al investigated the serum metabolomes of Malawian children aged 9–29 months [ 48 ]. These investigators used a targeted LC–MS/MS approach to measure 141 metabolites including sugars, amino acids, biogenic amines, sphingomyelins, acylcarnitines, and phosphatidylcholines.…”
Section: Metabolic Phenotyping Of Malnutrition During the First 1000 mentioning
confidence: 99%
“…Additionally, the synthesis of sphingomyelins, which are essential for myelination, depends on phosphatidylcholines. In a study by Di Giovanni et al children with severe acute malnutrition demonstrated delayed phosphatidylcholine recovery even after nutritional rehabilitation [9]. This could suggest that the 36-month phosphatidylcholines are biomarkers of a chronic process occurring later in childhood.…”
mentioning
confidence: 97%
“…Acylcarnitines and aminoacids were generally not associated with neurocognitive outcomes, with one exception; the amino acid Threonine measured at both 9 and 36 months was positively associated with neurocognitive outcomes.The study of Moreau et al is one of the first studies that demonstrated that separate metabolic pathways might relate to stunting and neurocognition [7]. The wide range of metabolites associated with growth outcomes could be related to factors such as insufficient diet and environmental enteric dysfunction and have been identified in other studies [9]. Although growth parameters were measured longitudinallyonly some children had neurocognition outcomes measured at two time points.…”
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confidence: 99%
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