#METABOLOMICS WORKBENCH Qianlab_20240714_001423 DATATRACK_ID:5008 STUDY_ID:ST003368 ANALYSIS_ID:AN005520 PROJECT_ID:PR002091 VERSION 1 CREATED_ON August 2, 2024, 12:37 pm #PROJECT PR:PROJECT_TITLE Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints PR:PROJECT_TITLE and Machine Learning PR:PROJECT_SUMMARY Moyamoya disease (MMD) is a progressive cerebrovascular disorder that raises the PR:PROJECT_SUMMARY risk of intracranial ischemia and hemorrhage. For a non-invasive diagnostic PR:PROJECT_SUMMARY approach to MMD, we used nanoparticle-enhanced laser desorption/ionization mass PR:PROJECT_SUMMARY spectrometry (LDI-MS) to analyze serum metabolic fingerprints (SMFs) in a PR:PROJECT_SUMMARY validation cohort (MMD: 115/HC: 115) and a discovery cohort (MMD: 29/HC: 29). PR:INSTITUTE Shanghai Jiao Tong University affiliated Renji Hospital PR:LAST_NAME Xu PR:FIRST_NAME Yudian PR:ADDRESS Shanghai, 200127, P. R. China, Shanghai, Shanghai, 200127, China PR:EMAIL xuyd9r@sjtu.edu.cn PR:PHONE 19370718762 #STUDY ST:STUDY_TITLE Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints ST:STUDY_TITLE and Machine Learning ST:STUDY_SUMMARY Moyamoya disease (MMD) is a progressive cerebrovascular condition that elevates ST:STUDY_SUMMARY the risk of intracranial ischemia and hemorrhage. Timely diagnosis and ST:STUDY_SUMMARY intervention can considerably lower the chances of new stroke occurrences in MMD ST:STUDY_SUMMARY patients. However, existing diagnostic techniques are both invasive and costly, ST:STUDY_SUMMARY with few reports on non-invasive diagnosis using MMD biomarkers. To tackle this ST:STUDY_SUMMARY challenge, we conducted non-targeted metabolomics analysis using LDI-MS on serum ST:STUDY_SUMMARY from 288 samples (validation cohort: MMD/HC: 115/115; discovery cohort: MMD/HC: ST:STUDY_SUMMARY 29/29) to identify patients with MMD. We then created a diagnostic model ST:STUDY_SUMMARY leveraging deep learning algorithms, which demonstrated remarkable accuracy in ST:STUDY_SUMMARY distinguishing the MMD group from the HC group (AUC = 0.977, 95% CI of 0.945 to ST:STUDY_SUMMARY 1.000). This method represents a promising new approach for MMD diagnosis. ST:STUDY_SUMMARY Additionally, our findings may have wider implications for the diagnosis of ST:STUDY_SUMMARY other neurological disorders. ST:INSTITUTE Shanghai Jiao Tong University affiliated Renji Hospital ST:LAST_NAME Xu ST:FIRST_NAME Yudian ST:ADDRESS Shanghai, 200127, P. R. China, Shanghai, Shanghai, 200127, China ST:EMAIL xuyd9r@sjtu.edu.cn ST:PHONE 19370718762 #SUBJECT SU:SUBJECT_TYPE Human SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 SU:GENDER Male and female #FACTORS #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Raw file names and additional sample data SUBJECT_SAMPLE_FACTORS - Discovery_1 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_2 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_3 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_4 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_5 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_6 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_7 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_8 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_9 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - Discovery_10 Sample source:Serum | Factor:HC SUBJECT_SAMPLE_FACTORS - 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Validation_42 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_43 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_44 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_45 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_46 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_47 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_48 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_49 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_50 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_51 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_52 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_53 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_54 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_55 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_56 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_57 Sample source:Serum | Factor:MMD SUBJECT_SAMPLE_FACTORS - Validation_58 Sample source:Serum | Factor:MMD #COLLECTION CO:COLLECTION_SUMMARY All human peripheral venous blood samples were obtained following the protocols CO:COLLECTION_SUMMARY approved by the Institutional Review Board at Huashan Hospital. Blood samples CO:COLLECTION_SUMMARY were obtained at the same time as regular blood tests after overnight fasting CO:COLLECTION_SUMMARY and then centrifuged for 10 minutes (1500g, 4℃). Serum samples were aliquoted CO:COLLECTION_SUMMARY in sterile centrifuge tubes and stored at -80℃ storage freezer. CO:SAMPLE_TYPE Blood (serum) #TREATMENT TR:TREATMENT_SUMMARY none #SAMPLEPREP SP:SAMPLEPREP_SUMMARY At the beginning, all original serum samples were diluted 10 times by 10ul to SP:SAMPLEPREP_SUMMARY obtain diluted serum, and both the original serum and the diluted serum were SP:SAMPLEPREP_SUMMARY placed at -80℃ for later use. In LDI MS experiments, 1 μL of analyte solution SP:SAMPLEPREP_SUMMARY (prepared standard small metabolites or diluted samples) was first spotted on SP:SAMPLEPREP_SUMMARY the polished steel plate and dried, followed by depositing 1 μL of nanoparticle SP:SAMPLEPREP_SUMMARY suspension or organic matrix solution and dried in air at room temperature. #CHROMATOGRAPHY CH:CHROMATOGRAPHY_TYPE None (Direct infusion) CH:INSTRUMENT_NAME none CH:COLUMN_NAME none CH:SOLVENT_A None CH:SOLVENT_B none CH:FLOW_GRADIENT none CH:FLOW_RATE none CH:COLUMN_TEMPERATURE none #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME Bruker Autoflex speed TOF/TOF MS:INSTRUMENT_TYPE TOF MS:MS_TYPE MALDI MS:ION_MODE POSITIVE MS:MS_COMMENTS In a typical LDI MS experiment, ferric particles were dispersed in deionized MS:MS_COMMENTS water at a concentration of 1mg mL-1 for use as a matrix. The organic matrices MS:MS_COMMENTS of CHCA and DHB were dissolved in TA30 solution (acetonitrile/0.1% TFA in water, MS:MS_COMMENTS 7/3, v/v) at a concentration of 10 mg/mL. For the detection of the standards, MS:MS_COMMENTS 100nL of analyte solution (each standard listed in the part of chemicals and MS:MS_COMMENTS reagents) with different density (100ng mL-1, 1μg mL-1, 10μg mL-1, 100μg MS:MS_COMMENTS mL-1, 1mg mL-1) was mixed with 100nL of matrix slurry on the plate and dried for MS:MS_COMMENTS LDI MS analysis. For plasma sample detection, the samples were firstly prepared MS:MS_COMMENTS through protein precipitation, centrifugation, and supernatant filtration MS:MS_COMMENTS according to a commonly applied procedure. Then, a volume of 100nL of plasma MS:MS_COMMENTS solution was spotted on the plate and dried in air at room temperature, followed MS:MS_COMMENTS by adding 100nL of matrix slurry and drying for LDI MS analysis. Then, mass MS:MS_COMMENTS spectra were performed on a 5800 Proteomics Analyzer (Applied Biosystems, MS:MS_COMMENTS Framingham, MA, USA) equipped with a Nd:YAG laser (2 kHz, 355 nm). The MS:MS_COMMENTS acquisitions were extracted in positive reflector ion mode employing delayed MS:MS_COMMENTS extraction with a repetition rate of 1,000Hz and an acceleration voltage of 20 MS:MS_COMMENTS kV. The delay time for this experiment was optimized to 250 ns. The 2,000 laser MS:MS_COMMENTS shots per analysis were for all LDI MS experiments. All the original mass MS:MS_COMMENTS spectra data were visualized in DataExplorer (Version 4.5). Only the m/z signals MS:MS_COMMENTS within 100–300Da and with a signal-to-noise ratio over 3 were then acquired MS:MS_COMMENTS without smoothing processes. For pre-processing, we applied a MS:MS_COMMENTS “home-developed” program using Python (version 3.9) to normalize and MS:MS_COMMENTS standardize the mass spectra data after peak extraction and alignment59. And MS:MS_COMMENTS standard molecules for the accurate mass measurement (±0.05Da) of both MS:MS_COMMENTS Na+-adducted and K+-adducted signals were used to perform the mass calibration. MS:MS_COMMENTS The detection limit of standard metabolites (listed in chemicals and reagents’ MS:MS_COMMENTS part) obtained by ferric particle, DHB, and CHCA-assisted LDI MS were calculated MS:MS_COMMENTS as previously reported MS:MS_RESULTS_FILE ST003368_AN005520_Results.txt UNITS:Relative intensity Has m/z:Yes Has RT:No RT units:No RT data #END