Summary of Study ST000877
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000608. The data can be accessed directly via it's Project DOI: 10.21228/M83105 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
Study ID | ST000877 |
Study Title | Micronutrient deficiencies, environmental exposures and severe malaria: Risk factors for adverse neurodevelopmental outcomes in Ugandan children |
Study Type | Untargeted high-resolution mass spectrometry profiling |
Study Summary | Micronutrient deficiencies and environmental exposures have been to known to adversely impact brain and nervous system functions in adults and children worldwide. However, few studies have examined the short and long-term impact of these risk factors on neurodevelopmental outcomes in children in low-income countries, where the effects are likely to be more pronounced due to limited resources for monitoring and insufficient regulations. Biological risk factors of relevance include micronutrient deficiencies such as zinc and exposure to heavy metals such as lead and mercury. Studies have suggested an association between neurodevelopmental impairment and micronutrient deficiency as well as exposure to a number of heavy metals and environmental toxins. Moreover, findings also suggest that risk factors for adverse developmental outcomes that are independently significant may have the potential for causing cumulative increases in adverse effects. In Sub-Saharan Africa, severe malaria is a leading risk factor for long-term neurocognitive impairment in children. Zinc deficiency or exposure to heavy metals could influence risk of severe malaria, modify the risk of neurocognitive impairment in children with severe malaria, or independently affect risk of neurocognitive impairment. Untargeted analyses for potential environmental exposures or metabolomic changes in children with cerebral malaria vs. without cognitive impairment or in children with higher vs. lower cognitive scores, could also identify new risk factors for neurodevelopmental impairment in Ugandan children with cerebral malaria.In our completed study in Kampala, we assessed neurologic and developmental impairment in children with cerebral malaria [CM] or severe malarial anemia [SMA], as compared to health community children from the same extended household as the children with CM or SMA. As an extension of this study, we are interested in determining levels of micronutrients such as zinc in the population, and in addition, determining exposure levels of heavy metals (lead, mercury, copper, manganese etc.) in samples collected from children with severe malaria and community controls. The primary hypotheses of this study is that nutrient deficiencies or exposure to heavy metals influence short and long term neurocognitive outcomes in healthy community children and in children with severe malaria, and that children with cerebral malaria have specific metabolomic changes that relate to long-term neurocognitive impairment. The specific aims of our study are:Aim 1: To determine levels of zinc, heavy metals, and biomarkers associated with inflammation in children presenting with different forms of severe malaria (SM) and in healthy community children (CC). The working hypothesis of this aim is that 1) children with SM will have lower zinc levels compared to CC; 2) children with SM will present with higher toxic metal exposure and higher levels of biomarkers associated with inflammation than CC.Aim 2: To investigate how micronutrient deficiency, toxic metal exposure and inflammatory biomarkers affect short and long term neurodevelopmental outcomes and growth in children with severe malaria and community children (CC).The working hypothesis of this aim is that the lower levels of zinc, and presence of toxic metals in high concentrations will independently contribute to worsening neurodevelopmental outcomes and worsening growth over time in children with severe malaria and in community children. An alternate hypothesis is that micronutrient deficiency, toxic metal exposure and inflammatory states may interact with each other and with severe malaria to produce greater neurodevelopmental impairment, i.e., that the contribution is not independent but interactive.Aim 3: To determine whether the CSF metabolome differs according to level of neurodevelopmental impairment in children with cerebral malaria. The working hypothesis of this aim is that neurodevelopmental impairment in children with cerebral malaria is associated with changes in the CSF metabolome. |
Institute | Emory University |
Department | School of Medicine, Division of Pulmonary, Allergy, Critical Care Medicine |
Laboratory | Clincal Biomarkers Laboratory |
Last Name | Walker |
First Name | Douglas |
Address | 615 Michael St. Ste 225, Atlanta, GA, 30322, USA |
douglas.walker@emory.edu | |
Phone | (404) 727 5984 |
Submit Date | 2017-09-27 |
Total Subjects | 141 |
Study Comments | CSF pools from elderly individuals included for QA/QC. Study specific pools were not created due to limited sample volumes provided (<100uL). |
Raw Data Available | Yes |
Raw Data File Type(s) | raw(Thermo) |
Chear Study | Yes |
Analysis Type Detail | LC-MS |
Release Date | 2021-08-31 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR000608 |
Project DOI: | doi: 10.21228/M83105 |
Project Title: | Micronutrient deficiencies, environmental exposures and severe malaria: Risk factors for adverse neurodevelopmental outcomes in Ugandan children |
Project Type: | NIH/NINDS R01 NS055349 |
Project Summary: | Micronutrient deficiencies and environmental exposures have been to known to adversely impact brain and nervous system functions in adults and children worldwide. However, few studies have examined the short and long-term impact of these risk factors on neurodevelopmental outcomes in children in low-income countries, where the effects are likely to be more pronounced due to limited resources for monitoring and insufficient regulations. Biological risk factors of relevance include micronutrient deficiencies such as zinc and exposure to heavy metals such as lead and mercury. Studies have suggested an association between neurodevelopmental impairment and micronutrient deficiency as well as exposure to a number of heavy metals and environmental toxins. Moreover, findings also suggest that risk factors for adverse developmental outcomes that are independently significant may have the potential for causing cumulative increases in adverse effects. In Sub-Saharan Africa, severe malaria is a leading risk factor for long-term neurocognitive impairment in children. Zinc deficiency or exposure to heavy metals could influence risk of severe malaria, modify the risk of neurocognitive impairment in children with severe malaria, or independently affect risk of neurocognitive impairment. Untargeted analyses for potential environmental exposures or metabolomic changes in children with cerebral malaria vs. without cognitive impairment or in children with higher vs. lower cognitive scores, could also identify new risk factors for neurodevelopmental impairment in Ugandan children with cerebral malaria.In our completed study in Kampala, we assessed neurologic and developmental impairment in children with cerebral malaria [CM] or severe malarial anemia [SMA], as compared to health community children from the same extended household as the children with CM or SMA. As an extension of this study, we are interested in determining levels of micronutrients such as zinc in the population, and in addition, determining exposure levels of heavy metals (lead, mercury, copper, manganese etc.) in samples collected from children with severe malaria and community controls. The primary hypotheses of this study is that nutrient deficiencies or exposure to heavy metals influence short and long term neurocognitive outcomes in healthy community children and in children with severe malaria, and that children with cerebral malaria have specific metabolomic changes that relate to long-term neurocognitive impairment. The specific aims of our study are:Aim 1: To determine levels of zinc, heavy metals, and biomarkers associated with inflammation in children presenting with different forms of severe malaria (SM) and in healthy community children (CC). The working hypothesis of this aim is that 1) children with SM will have lower zinc levels compared to CC; 2) children with SM will present with higher toxic metal exposure and higher levels of biomarkers associated with inflammation than CC.Aim 2: To investigate how micronutrient deficiency, toxic metal exposure and inflammatory biomarkers affect short and long term neurodevelopmental outcomes and growth in children with severe malaria and community children (CC).The working hypothesis of this aim is that the lower levels of zinc, and presence of toxic metals in high concentrations will independently contribute to worsening neurodevelopmental outcomes and worsening growth over time in children with severe malaria and in community children. An alternate hypothesis is that micronutrient deficiency, toxic metal exposure and inflammatory states may interact with each other and with severe malaria to produce greater neurodevelopmental impairment, i.e., that the contribution is not independent but interactive.Aim 3: To determine whether the CSF metabolome differs according to level of neurodevelopmental impairment in children with cerebral malaria. The working hypothesis of this aim is that neurodevelopmental impairment in children with cerebral malaria is associated with changes in the CSF metabolome. |
Institute: | Emory University |
Department: | Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine |
Laboratory: | Clinical Biomarkers Laboratory |
Last Name: | Walker |
First Name: | Douglas |
Address: | 615 Michael St. Ste 225, Atlanta, GA, 30322, USA |
Email: | douglas.walker@emory.edu |
Phone: | (404) 727 5984 |
Funding Source: | NIEHS ES026560 |
Contributors: | Chandy C. John, Indiana University School of Medicine; Dibyadyuti Datta, Indiana University; Robert Opoka, Makerere University-Mulago Hospital; Dean P. Jones, Emory University School of Medicine; Karan Uppal, Emory University School of Medicine |
Subject:
Subject ID: | SU000911 |
Subject Type: | Cerebrospinal Fluid |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Age Or Age Range: | Pediatric samples |
Human Trial Type: | Observational |
Species Group: | Human |
Factors:
Subject type: Cerebrospinal Fluid; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Sample Type |
---|---|---|
SA050837 | chearplasma_2c | CHEAR Plasma |
SA050838 | chearplasma_3a | CHEAR Plasma |
SA050839 | chearplasma_2b | CHEAR Plasma |
SA050840 | chearplasma_2a | CHEAR Plasma |
SA050841 | chearplasma_1d | CHEAR Plasma |
SA050842 | chearplasma_3b | CHEAR Plasma |
SA050843 | chearplasma_3d | CHEAR Plasma |
SA050844 | chearplasma_4c | CHEAR Plasma |
SA050845 | chearplasma_4d | CHEAR Plasma |
SA050846 | chearplasma_4b | CHEAR Plasma |
SA050847 | chearplasma_4a | CHEAR Plasma |
SA050848 | chearplasma_1c | CHEAR Plasma |
SA050849 | chearplasma_3c | CHEAR Plasma |
SA050850 | chearplasma_2d | CHEAR Plasma |
SA050851 | chearplasma_1a | CHEAR Plasma |
SA050852 | chearplasma_1b | CHEAR Plasma |
SA050853 | csfpool_4d | CSF Pool |
SA050854 | csfpool_4c | CSF Pool |
SA050855 | csfpool_2e | CSF Pool |
SA050856 | csfpool_4a | CSF Pool |
SA050857 | csfpool_3c | CSF Pool |
SA050858 | csfpool_2f | CSF Pool |
SA050859 | csfpool_1e | CSF Pool |
SA050860 | csfpool_2a | CSF Pool |
SA050861 | csfpool_2b | CSF Pool |
SA050862 | csfpool_1f | CSF Pool |
SA050863 | csfpool_1a | CSF Pool |
SA050864 | csfpool_3d | CSF Pool |
SA050865 | csfpool_4b | CSF Pool |
SA050866 | csfpool_2c | CSF Pool |
SA050867 | csfpool_1b | CSF Pool |
SA050868 | csfpool_3f | CSF Pool |
SA050869 | csfpool_3e | CSF Pool |
SA050870 | csfpool_4f | CSF Pool |
SA050871 | csfpool_4e | CSF Pool |
SA050872 | csfpool_1d | CSF Pool |
SA050873 | csfpool_1c | CSF Pool |
SA050874 | csfpool_3b | CSF Pool |
SA050875 | csfpool_3a | CSF Pool |
SA050876 | csfpool_2d | CSF Pool |
SA050877 | C-XBVS6-CF-00 | CSF Study Sample |
SA050878 | C-XBXF3-CF-00 | CSF Study Sample |
SA050879 | C-XCU28-CF-00 | CSF Study Sample |
SA050880 | C-X7R50-CF-00 | CSF Study Sample |
SA050881 | C-XB7F6-CF-00 | CSF Study Sample |
SA050882 | C-XA7K7-CF-00 | CSF Study Sample |
SA050883 | C-XAKS9-CF-00 | CSF Study Sample |
SA050884 | C-XA870-CF-00 | CSF Study Sample |
SA050885 | C-X7WK7-CF-00 | CSF Study Sample |
SA050886 | C-XLGH4-CF-00 | CSF Study Sample |
SA050887 | C-XR6V7-CF-00 | CSF Study Sample |
SA050888 | C-XR6R6-CF-00 | CSF Study Sample |
SA050889 | C-XQQ05-CF-00 | CSF Study Sample |
SA050890 | C-XS193-CF-00 | CSF Study Sample |
SA050891 | C-XSRV6-CF-00 | CSF Study Sample |
SA050892 | C-XUWS3-CF-00 | CSF Study Sample |
SA050893 | C-XUJF5-CF-00 | CSF Study Sample |
SA050894 | C-XTRX9-CF-00 | CSF Study Sample |
SA050895 | C-XPYG9-CF-00 | CSF Study Sample |
SA050896 | C-XP6C3-CF-00 | CSF Study Sample |
SA050897 | C-XGTT5-CF-00 | CSF Study Sample |
SA050898 | C-XEA72-CF-00 | CSF Study Sample |
SA050899 | C-XDCN1-CF-00 | CSF Study Sample |
SA050900 | C-XHD99-CF-00 | CSF Study Sample |
SA050901 | C-XKRU6-CF-00 | CSF Study Sample |
SA050902 | C-XM3V1-CF-00 | CSF Study Sample |
SA050903 | C-XM0D3-CF-00 | CSF Study Sample |
SA050904 | C-X7AU7-CF-00 | CSF Study Sample |
SA050905 | C-XCVE5-CF-00 | CSF Study Sample |
SA050906 | C-X70K6-CF-00 | CSF Study Sample |
SA050907 | C-WXAL5-CF-00 | CSF Study Sample |
SA050908 | C-WX0F5-CF-00 | CSF Study Sample |
SA050909 | C-WWY21-CF-00 | CSF Study Sample |
SA050910 | C-WXGE4-CF-00 | CSF Study Sample |
SA050911 | C-WXJQ5-CF-00 | CSF Study Sample |
SA050912 | C-X0LF4-CF-00 | CSF Study Sample |
SA050913 | C-WYEH8-CF-00 | CSF Study Sample |
SA050914 | C-WXNN7-CF-00 | CSF Study Sample |
SA050915 | C-WW0Q4-CF-00 | CSF Study Sample |
SA050916 | C-WV7M8-CF-00 | CSF Study Sample |
SA050917 | C-WRW40-CF-00 | CSF Study Sample |
SA050918 | C-WQZA0-CF-00 | CSF Study Sample |
SA050919 | C-WPSW1-CF-00 | CSF Study Sample |
SA050920 | C-WRZP5-CF-00 | CSF Study Sample |
SA050921 | C-WSMA8-CF-00 | CSF Study Sample |
SA050922 | C-WUS96-CF-00 | CSF Study Sample |
SA050923 | C-WTKE9-CF-00 | CSF Study Sample |
SA050924 | C-X0RN0-CF-00 | CSF Study Sample |
SA050925 | C-X1BV7-CF-00 | CSF Study Sample |
SA050926 | C-X6NS0-CF-00 | CSF Study Sample |
SA050927 | C-X66K2-CF-00 | CSF Study Sample |
SA050928 | C-X65W7-CF-00 | CSF Study Sample |
SA050929 | C-X6UX2-CF-00 | CSF Study Sample |
SA050930 | C-XUXR5-CF-00 | CSF Study Sample |
SA050931 | C-Z6TH7-CF-00 | CSF Study Sample |
SA050932 | C-Z9710-CF-00 | CSF Study Sample |
SA050933 | C-X5XU8-CF-00 | CSF Study Sample |
SA050934 | C-X5P15-CF-00 | CSF Study Sample |
SA050935 | C-X2G11-CF-00 | CSF Study Sample |
SA050936 | C-X2C64-CF-00 | CSF Study Sample |
Collection:
Collection ID: | CO000905 |
Collection Summary: | Please contact project PI, Chandy John (chjohn@iu.edu), for sample collection details. |
Sample Type: | Cerebrospinal Fluid |
Treatment:
Treatment ID: | TR000925 |
Treatment Summary: | Samples were received frozen in aliquouts of <100uL. Freeze-thaw history for study samples prior to receipt by the Emory URR is provided in the Study Design section. Prior to analysis, samples were thawed and prepared for HRM analysis using the standard protocols described in the Sample Preparation section. |
Sample Preparation:
Sampleprep ID: | SP000918 |
Sampleprep Summary: | Samples were prepared for metabolomics analysis using established methods (Johnson et al. (2010). Analyst; Go et al. (2015). Tox Sci). Prior to analysis, urine aliquots were removed from storage at -80°C and thawed on ice. Each cryotube was then vortexed briefly to ensure homogeneity, and 50 μL was transferred to a clean microfuge tube. Immediately after, the urine was treated with 100 μL of ice-cold LC-MS grade acetonitrile (Sigma Aldrich) containing 2.5 μL of internal standard solution with eight stable isotopic chemicals selected to cover a range of chemical properties. Following addition of acetonitrile, urine was equilibrated for 30 min on ice, upon which precipitated proteins were removed by centrifuge (16.1 ×g at 4°C for 10 min). The resulting supernatant (100 μL) was removed, added to a low volume autosampler vial and maintained at 4°C until analysis (<22 h). |
Sampleprep Protocol ID: | HRM_SP_082016_01 |
Sampleprep Protocol Filename: | EmoryUniversity_HRM_SP_082016_01.pdf |
Sampleprep Protocol Comments: | Date effective: 30 July 2016 |
Extraction Method: | 2:1 acetonitrile: sample followed by vortexing and centrifugation |
Sample Spiking: | 2.5 uL [13C6]-D-glucose, [15N,13C5]-L-methionine, [13C5]-L-glutamic acid, [15N]-L-tyrosine, [3,3-13C2]-cystine, [trimethyl-13C3]-caffeine, [U-13C5, U-15N2]-L-glutamine, [15N]-indole |
Combined analysis:
Analysis ID | AN001426 | AN001427 |
---|---|---|
Analysis type | MS | MS |
Chromatography type | HILIC | Reversed phase |
Chromatography system | Thermo Dionex Ultimate 3000 | Thermo Dionex Ultimate 3000 |
Column | Waters XBridge Amide (50 x 2.1mm,2.5um) | Thermo Higgins C18 (50 x 2.1mm,3um) |
MS Type | ESI | ESI |
MS instrument type | Orbitrap | Orbitrap |
MS instrument name | Thermo Q Exactive HF hybrid Orbitrap | Thermo Q Exactive HF hybrid Orbitrap |
Ion Mode | POSITIVE | NEGATIVE |
Units | Peak intensity | Peak intensity |
Chromatography:
Chromatography ID: | CH000997 |
Chromatography Summary: | The HILIC column is operated parallel to reverse phase column for simultaneous analytical separation and column flushing through the use of a dual head HPLC pump equipped with 10-port and 6-port switching valves. During operation of HILIC separation method, the MS is operated in positive ion mode and 10 μL of sample is injected onto the HILIC column while the reverse phase column is flushing with wash solution. Flow rate is maintained at 0.35 mL/min until 1.5 min, increased to 0.4 mL/min at 4 min and held for 1 min. Solvent A is 100% LC-MS grade water, solvent B is 100% LC-MS grade acetonitrile and solvent C is 2% formic acid (v/v) in LC-MS grade water. Initial mobile phase conditions are 22.5% A, 75% B, 2.5% C hold for 1.5 min, with linear gradient to 77.5% A, 20% B, 2.5% C at 4 min, hold for 1 min, resulting in a total analytical run time of 5 min. During the flushing phase (reverse phase analytical separation), the HILIC column is equilibrated with a wash solution of 77.5% A, 20% B, 2.5% C. |
Methods ID: | 2% formic acid in LC-MS grade water |
Methods Filename: | 20160920_posHILIC120kres5min_ESI_c18negwash.meth |
Chromatography Comments: | Triplicate injections for each chromatography mode |
Instrument Name: | Thermo Dionex Ultimate 3000 |
Column Name: | Waters XBridge Amide (50 x 2.1mm,2.5um) |
Column Temperature: | 60C |
Flow Gradient: | A= water, B= acetontrile, C= 2% formic acid in water; 22.5% A, 75% B, 2.5% C hold for 1.5 min, linear gradient to 77.5% A, 20% B, 2.5% C at 4 min, hold for 1 min |
Flow Rate: | 0.35 mL/min for 1.5 min; linear increase to 0.4 mL/min at 4 min, hold for 1 min |
Sample Injection: | 10 uL |
Solvent A: | 100% water |
Solvent B: | 100% acetonitrile |
Analytical Time: | 5 min |
Sample Loop Size: | 15 uL |
Sample Syringe Size: | 100 uL |
Chromatography Type: | HILIC |
Chromatography ID: | CH000998 |
Chromatography Summary: | The C18 column is operated parallel to the HILIC column for simultaneous analytical separation and column flushing through the use of a dual head HPLC pump equipped with 10-port and 6-port switching valves. During operation of the C18 method, the MS is operated in negative ion mode and 10 μL of sample is injected onto the C18 column while the HILIC column is flushing with wash solution. Flow rate is maintained at 0.4 mL/min until 1.5 min, increased to 0.5 mL/min at 2 min and held for 3 min. Solvent A is 100% LC-MS grade water, solvent B is 100% LC-MS grade acetonitrile and solvent C is 10mM ammonium acetate in LC-MS grade water. Initial mobile phase conditions are 60% A, 35% B, 5% C hold for 0.5 min, with linear gradient to 0% A, 95% B, 5% C at 1.5 min, hold for 3.5 min, resulting in a total analytical run time of 5 min. During the flushing phase (HILIC analytical separation), the C18 column is equilibrated with a wash solution of 0% A, 95% B, 5% C until 2.5 min, followed by an equilibration solution of 60% A, 35% B, 5% C for 2.5 min. |
Methods ID: | 10mM ammonium acetate in LC-MS grade water |
Methods Filename: | 20160920_negC18120kres5min_ESI_HILICposwash.meth |
Chromatography Comments: | Triplicate injections for each chromatography mode |
Instrument Name: | Thermo Dionex Ultimate 3000 |
Column Name: | Thermo Higgins C18 (50 x 2.1mm,3um) |
Column Temperature: | 60C |
Flow Gradient: | A= water, B= acetontrile, C= 10mM ammonium acetate in water; 60% A, 35% B, 5% C hold for 0.5 min, linear gradient to 0% A, 95% B, 5% C at 1.5 min, hold for 3 min |
Flow Rate: | 0.4 mL/min for 1.5 min; linear increase to 0.5 mL/min at 2 min held for 3 min |
Sample Injection: | 10 uL |
Solvent A: | 100% water |
Solvent B: | 100% acetonitrile |
Analytical Time: | 5 min |
Sample Loop Size: | 15 uL |
Sample Syringe Size: | 100 uL |
Chromatography Type: | Reversed phase |
MS:
MS ID: | MS001316 |
Analysis ID: | AN001426 |
Instrument Name: | Thermo Q Exactive HF hybrid Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
Ion Mode: | POSITIVE |
Capillary Temperature: | 250C |
Collision Gas: | N2 |
Dry Gas Flow: | 45 |
Dry Gas Temp: | 150C |
Mass Accuracy: | < 3ppm |
Spray Voltage: | +3500 |
Activation Parameter: | 5e5 |
Activation Time: | 118ms |
Interface Voltage: | S-Lens RF level= 55 |
Resolution Setting: | 120,000 |
Scanning Range: | 85-1275 |
Analysis Protocol File: | EmoryUniversity_HRM_QEHF-MS_092017_v1.pdf |
MS ID: | MS001317 |
Analysis ID: | AN001427 |
Instrument Name: | Thermo Q Exactive HF hybrid Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
Ion Mode: | NEGATIVE |
Capillary Temperature: | 250C |
Collision Gas: | N2 |
Dry Gas Flow: | 45 |
Dry Gas Temp: | 150C |
Mass Accuracy: | < 3ppm |
Spray Voltage: | -4000 |
Activation Parameter: | 5e5 |
Activation Time: | 118ms |
Interface Voltage: | S-Lens RF level= 55 |
Resolution Setting: | 120,000 |
Scanning Range: | 85-1275 |
Analysis Protocol File: | EmoryUniversity_HRM_QEHF-MS_092017_v1.pdf |