#METABOLOMICS WORKBENCH kcontrep_20200927_172835_mwtab.txt DATATRACK_ID:2182 STUDY_ID:ST001491 ANALYSIS_ID:AN002473 PROJECT_ID:PR001009 VERSION 1 CREATED_ON September 28, 2020, 12:31 pm #PROJECT PR:PROJECT_TITLE Untargeted urine metabolomics to predict gestational age in term and preterm PR:PROJECT_TITLE pregnancies PR:PROJECT_SUMMARY Multi-site collection of urine early in pregnancy (8-19 weeks) and untargeted PR:PROJECT_SUMMARY LC-MS metabolomics to predict gestational age in term and preterm pregnancies PR:INSTITUTE Stanford University PR:DEPARTMENT Genetics PR:LAST_NAME Contrepois PR:FIRST_NAME Kevin PR:ADDRESS 300 Pasteur Dr, ALWAY bldg M302, STANFORD, California, 94305, USA PR:EMAIL kcontrep@stanford.edu PR:PHONE 6507239914 #STUDY ST:STUDY_TITLE Global Urine Metabolic Profiling to Predict Gestational Age in Term and Preterm ST:STUDY_TITLE Pregnancies ST:STUDY_SUMMARY Assessment of gestational age (GA) is key to provide optimal care during ST:STUDY_SUMMARY pregnancy. However, its accurate determination remains challenging in low- and ST:STUDY_SUMMARY middle-resource countries, where access to obstetric ultrasound is limited. ST:STUDY_SUMMARY Hence, there is an urgent need to develop clinical approaches that allow ST:STUDY_SUMMARY accurate and inexpensive estimation of GA. We investigated the ability of ST:STUDY_SUMMARY urinary metabolites to predict GA at time of collection in a diverse multi-site ST:STUDY_SUMMARY cohort (n = 99) using a broad-spectrum liquid chromatography coupled with mass ST:STUDY_SUMMARY spectrometry (LC-MS) platform. Our approach detected a myriad of steroid ST:STUDY_SUMMARY hormones and their derivatives including estrogens, progesterones, ST:STUDY_SUMMARY corticosteroids and androgens that associated with pregnancy progression. We ST:STUDY_SUMMARY developed a prediction model that predicted GA with high accuracy using the ST:STUDY_SUMMARY levels of three metabolites (rho = 0.87, .RMSE = 1.58 weeks). These predictions ST:STUDY_SUMMARY were robust irrespective of whether the pregnancy went to term or ended ST:STUDY_SUMMARY prematurely. Overall, we demonstrate the feasibility of implementing urine ST:STUDY_SUMMARY collection for metabolomics analysis in large-scale multi-site studies and we ST:STUDY_SUMMARY report a predictive model of GA with a potential clinical value. ST:INSTITUTE Stanford University ST:LAST_NAME Contrepois ST:FIRST_NAME Kevin ST:ADDRESS 300 Pasteur Dr ST:EMAIL kcontrep@stanford.edu ST:PHONE 6506664538 #SUBJECT SU:SUBJECT_TYPE Human SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 SU:GENDER Female #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 30-06183 1 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:10 RAW_FILE_NAME=pHILIC_1;nHILIC_1;pRPLC_1 nRPLC_1 SUBJECT_SAMPLE_FACTORS 20UE01401 2 Site:Tanzania | GA_delivery:31 | GA_sampling:16 RAW_FILE_NAME=pHILIC_2;nHILIC_2;pRPLC_2 nRPLC_2 SUBJECT_SAMPLE_FACTORS 20UE00635 3 Site:Tanzania | GA_delivery:39 | GA_sampling:10 RAW_FILE_NAME=pHILIC_3;nHILIC_3;pRPLC_3 nRPLC_3 SUBJECT_SAMPLE_FACTORS 20-37618 4 Site:Bangladesh_GAPPS | GA_delivery:33 | GA_sampling:13 RAW_FILE_NAME=pHILIC_4;nHILIC_4;pRPLC_4 nRPLC_4 SUBJECT_SAMPLE_FACTORS 20UE01817 5 Site:Tanzania | GA_delivery:32 | GA_sampling:9 RAW_FILE_NAME=pHILIC_5;nHILIC_5;pRPLC_5 nRPLC_5 SUBJECT_SAMPLE_FACTORS 20UE02184 6 Site:Tanzania | GA_delivery:33 | GA_sampling:18 RAW_FILE_NAME=pHILIC_6;nHILIC_6;pRPLC_6 nRPLC_6 SUBJECT_SAMPLE_FACTORS 17-UE00413 7 Site:Pakistan | GA_delivery:28 | GA_sampling:9 RAW_FILE_NAME=pHILIC_7;nHILIC_7;pRPLC_7 nRPLC_7 SUBJECT_SAMPLE_FACTORS 30-08014 8 Site:Zambia_GAPPS | GA_delivery:33 | GA_sampling:17 RAW_FILE_NAME=pHILIC_8;nHILIC_8;pRPLC_8 nRPLC_8 SUBJECT_SAMPLE_FACTORS 17-UE00679 9 Site:Pakistan | GA_delivery:40 | GA_sampling:16 RAW_FILE_NAME=pHILIC_9;nHILIC_9;pRPLC_9 nRPLC_9 SUBJECT_SAMPLE_FACTORS 20UE00867 10 Site:Tanzania | GA_delivery:26 | GA_sampling:19 RAW_FILE_NAME=pHILIC_10;nHILIC_10;pRPLC_10 nRPLC_10 SUBJECT_SAMPLE_FACTORS 17-UE01059 11 Site:Pakistan | GA_delivery:33 | GA_sampling:16 RAW_FILE_NAME=pHILIC_11;nHILIC_11;pRPLC_11 nRPLC_11 SUBJECT_SAMPLE_FACTORS 11UE01127 12 Site:Bangladesh | GA_delivery:33 | GA_sampling:17 RAW_FILE_NAME=pHILIC_12;nHILIC_12;pRPLC_12 nRPLC_12 SUBJECT_SAMPLE_FACTORS 30-06482 13 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:18 RAW_FILE_NAME=pHILIC_13;nHILIC_13;pRPLC_13 nRPLC_13 SUBJECT_SAMPLE_FACTORS 11UE00971 14 Site:Bangladesh | GA_delivery:31 | GA_sampling:11 RAW_FILE_NAME=pHILIC_14;nHILIC_14;pRPLC_14 nRPLC_14 SUBJECT_SAMPLE_FACTORS 17-UE00922 15 Site:Pakistan | GA_delivery:33 | GA_sampling:17 RAW_FILE_NAME=pHILIC_15;nHILIC_15;pRPLC_15 nRPLC_15 SUBJECT_SAMPLE_FACTORS 20UE00071 16 Site:Tanzania | GA_delivery:33 | GA_sampling:14 RAW_FILE_NAME=pHILIC_16;nHILIC_16;pRPLC_16 nRPLC_16 SUBJECT_SAMPLE_FACTORS 20-27695 17 Site:Bangladesh_GAPPS | GA_delivery:33 | GA_sampling:13 RAW_FILE_NAME=pHILIC_17;nHILIC_17;pRPLC_17 nRPLC_17 SUBJECT_SAMPLE_FACTORS 17-UE00283 18 Site:Pakistan | GA_delivery:33 | GA_sampling:12 RAW_FILE_NAME=pHILIC_18;nHILIC_18;pRPLC_18 nRPLC_18 SUBJECT_SAMPLE_FACTORS 11UE00066 19 Site:Bangladesh | GA_delivery:41 | GA_sampling:16 RAW_FILE_NAME=pHILIC_19;nHILIC_19;pRPLC_19 nRPLC_19 SUBJECT_SAMPLE_FACTORS 11UE01855 20 Site:Bangladesh | GA_delivery:29 | GA_sampling:15 RAW_FILE_NAME=pHILIC_20;nHILIC_20;pRPLC_20 nRPLC_20 SUBJECT_SAMPLE_FACTORS 20UE02184 21 Site:Tanzania | GA_delivery:33 | GA_sampling:18 RAW_FILE_NAME=pHILIC_21;nHILIC_21;pRPLC_21 nRPLC_21 SUBJECT_SAMPLE_FACTORS 11UE00631 22 Site:Bangladesh | GA_delivery:30 | GA_sampling:13 RAW_FILE_NAME=pHILIC_22;nHILIC_22;pRPLC_22 nRPLC_22 SUBJECT_SAMPLE_FACTORS 20-01475 23 Site:Bangladesh_GAPPS | GA_delivery:39 | GA_sampling:19 RAW_FILE_NAME=pHILIC_23;nHILIC_23;pRPLC_23 nRPLC_23 SUBJECT_SAMPLE_FACTORS 30-00423 24 Site:Zambia_GAPPS | GA_delivery:41 | GA_sampling:18 RAW_FILE_NAME=pHILIC_24;nHILIC_24;pRPLC_24 nRPLC_24 SUBJECT_SAMPLE_FACTORS 20UE00285 25 Site:Tanzania | GA_delivery:39 | GA_sampling:16 RAW_FILE_NAME=pHILIC_25;nHILIC_25;pRPLC_25 nRPLC_25 SUBJECT_SAMPLE_FACTORS 11UE00066 26 Site:Bangladesh | GA_delivery:41 | GA_sampling:16 RAW_FILE_NAME=pHILIC_26;nHILIC_26;pRPLC_26 nRPLC_26 SUBJECT_SAMPLE_FACTORS 20UE00701 27 Site:Tanzania | GA_delivery:39 | GA_sampling:11 RAW_FILE_NAME=pHILIC_27;nHILIC_27;pRPLC_27 nRPLC_27 SUBJECT_SAMPLE_FACTORS 30-07271 28 Site:Zambia_GAPPS | GA_delivery:31 | GA_sampling:11 RAW_FILE_NAME=pHILIC_28;nHILIC_28;pRPLC_28 nRPLC_28 SUBJECT_SAMPLE_FACTORS 11UE00848 29 Site:Bangladesh | GA_delivery:41 | GA_sampling:17 RAW_FILE_NAME=pHILIC_29;nHILIC_29;pRPLC_29 nRPLC_29 SUBJECT_SAMPLE_FACTORS 20-23828 30 Site:Bangladesh_GAPPS | GA_delivery:34 | GA_sampling:11 RAW_FILE_NAME=pHILIC_30;nHILIC_30;pRPLC_30 nRPLC_30 SUBJECT_SAMPLE_FACTORS 17-UE00384 31 Site:Pakistan | GA_delivery:39 | GA_sampling:17 RAW_FILE_NAME=pHILIC_31;nHILIC_31;pRPLC_31 nRPLC_31 SUBJECT_SAMPLE_FACTORS 20UE00691 32 Site:Tanzania | GA_delivery:39 | GA_sampling:13 RAW_FILE_NAME=pHILIC_32;nHILIC_32;pRPLC_32 nRPLC_32 SUBJECT_SAMPLE_FACTORS 17-UE00283 33 Site:Pakistan | GA_delivery:33 | GA_sampling:12 RAW_FILE_NAME=pHILIC_33;nHILIC_33;pRPLC_33 nRPLC_33 SUBJECT_SAMPLE_FACTORS 17-UE01072 34 Site:Pakistan | GA_delivery:39 | GA_sampling:9 RAW_FILE_NAME=pHILIC_34;nHILIC_34;pRPLC_34 nRPLC_34 SUBJECT_SAMPLE_FACTORS 20UE01639 35 Site:Tanzania | GA_delivery:39 | GA_sampling:15 RAW_FILE_NAME=pHILIC_35;nHILIC_35;pRPLC_35 nRPLC_35 SUBJECT_SAMPLE_FACTORS 30-00472 36 Site:Zambia_GAPPS | GA_delivery:28 | GA_sampling:8 RAW_FILE_NAME=pHILIC_36;nHILIC_36;pRPLC_36 nRPLC_36 SUBJECT_SAMPLE_FACTORS 17-UE00922 37 Site:Pakistan | GA_delivery:33 | GA_sampling:17 RAW_FILE_NAME=pHILIC_37;nHILIC_37;pRPLC_37 nRPLC_37 SUBJECT_SAMPLE_FACTORS 20UE00071 38 Site:Tanzania | GA_delivery:33 | GA_sampling:14 RAW_FILE_NAME=pHILIC_38;nHILIC_38;pRPLC_38 nRPLC_38 SUBJECT_SAMPLE_FACTORS 20-37431 39 Site:Bangladesh_GAPPS | GA_delivery:33 | GA_sampling:15 RAW_FILE_NAME=pHILIC_39;nHILIC_39;pRPLC_39 nRPLC_39 SUBJECT_SAMPLE_FACTORS 20UE00700 40 Site:Tanzania | GA_delivery:26 | GA_sampling:12 RAW_FILE_NAME=pHILIC_40;nHILIC_40;pRPLC_40 nRPLC_40 SUBJECT_SAMPLE_FACTORS 17-UE00848 41 Site:Pakistan | GA_delivery:33 | GA_sampling:18 RAW_FILE_NAME=pHILIC_41;nHILIC_41;pRPLC_41 nRPLC_41 SUBJECT_SAMPLE_FACTORS 11UE00742 42 Site:Bangladesh | GA_delivery:41 | GA_sampling:16 RAW_FILE_NAME=pHILIC_42;nHILIC_42;pRPLC_42 nRPLC_42 SUBJECT_SAMPLE_FACTORS 20-01444 43 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:12 RAW_FILE_NAME=pHILIC_43;nHILIC_43;pRPLC_43 nRPLC_43 SUBJECT_SAMPLE_FACTORS 30-08712 44 Site:Zambia_GAPPS | GA_delivery:36 | GA_sampling:16 RAW_FILE_NAME=pHILIC_44;nHILIC_44;pRPLC_44 nRPLC_44 SUBJECT_SAMPLE_FACTORS 11UE01104 45 Site:Bangladesh | GA_delivery:29 | GA_sampling:15 RAW_FILE_NAME=pHILIC_45;nHILIC_45;pRPLC_45 nRPLC_45 SUBJECT_SAMPLE_FACTORS 30-05663 46 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:15 RAW_FILE_NAME=pHILIC_46;nHILIC_46;pRPLC_46 nRPLC_46 SUBJECT_SAMPLE_FACTORS 11UE00631 47 Site:Bangladesh | GA_delivery:30 | GA_sampling:13 RAW_FILE_NAME=pHILIC_47;nHILIC_47;pRPLC_47 nRPLC_47 SUBJECT_SAMPLE_FACTORS 11UE00742 48 Site:Bangladesh | GA_delivery:41 | GA_sampling:16 RAW_FILE_NAME=pHILIC_48;nHILIC_48;pRPLC_48 nRPLC_48 SUBJECT_SAMPLE_FACTORS 20UE02238 49 Site:Tanzania | GA_delivery:39 | GA_sampling:9 RAW_FILE_NAME=pHILIC_49;nHILIC_49;pRPLC_49 nRPLC_49 SUBJECT_SAMPLE_FACTORS 11UE00455 50 Site:Bangladesh | GA_delivery:41 | GA_sampling:13 RAW_FILE_NAME=pHILIC_50;nHILIC_50;pRPLC_50 nRPLC_50 SUBJECT_SAMPLE_FACTORS 30-00423 51 Site:Zambia_GAPPS | GA_delivery:41 | GA_sampling:18 RAW_FILE_NAME=pHILIC_51;nHILIC_51;pRPLC_51 nRPLC_51 SUBJECT_SAMPLE_FACTORS 17-UE00374 52 Site:Pakistan | GA_delivery:39 | GA_sampling:10 RAW_FILE_NAME=pHILIC_52;nHILIC_52;pRPLC_52 nRPLC_52 SUBJECT_SAMPLE_FACTORS 17-UE00384 53 Site:Pakistan | GA_delivery:39 | GA_sampling:17 RAW_FILE_NAME=pHILIC_53;nHILIC_53;pRPLC_53 nRPLC_53 SUBJECT_SAMPLE_FACTORS 30-04509 54 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:19 RAW_FILE_NAME=pHILIC_54;nHILIC_54;pRPLC_54 nRPLC_54 SUBJECT_SAMPLE_FACTORS 17-UE00208 55 Site:Pakistan | GA_delivery:32 | GA_sampling:8 RAW_FILE_NAME=pHILIC_55;nHILIC_55;pRPLC_55 nRPLC_55 SUBJECT_SAMPLE_FACTORS 30-05696 56 Site:Zambia_GAPPS | GA_delivery:32 | GA_sampling:17 RAW_FILE_NAME=pHILIC_56;nHILIC_56;pRPLC_56 nRPLC_56 SUBJECT_SAMPLE_FACTORS 30-04510 57 Site:Zambia_GAPPS | GA_delivery:28 | GA_sampling:17 RAW_FILE_NAME=pHILIC_57;nHILIC_57;pRPLC_57 nRPLC_57 SUBJECT_SAMPLE_FACTORS 20-20993 58 Site:Bangladesh_GAPPS | GA_delivery:36 | GA_sampling:11 RAW_FILE_NAME=pHILIC_58;nHILIC_58;pRPLC_58 nRPLC_58 SUBJECT_SAMPLE_FACTORS 11UE01294 59 Site:Bangladesh | GA_delivery:24 | GA_sampling:17 RAW_FILE_NAME=pHILIC_59;nHILIC_59;pRPLC_59 nRPLC_59 SUBJECT_SAMPLE_FACTORS 20UE00700 60 Site:Tanzania | GA_delivery:26 | GA_sampling:12 RAW_FILE_NAME=pHILIC_60;nHILIC_60;pRPLC_60 nRPLC_60 SUBJECT_SAMPLE_FACTORS 11UE02004 61 Site:Bangladesh | GA_delivery:31 | GA_sampling:15 RAW_FILE_NAME=pHILIC_61;nHILIC_61;pRPLC_61 nRPLC_61 SUBJECT_SAMPLE_FACTORS 20-30636 62 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:12 RAW_FILE_NAME=pHILIC_62;nHILIC_62;pRPLC_62 nRPLC_62 SUBJECT_SAMPLE_FACTORS 20UE01401 63 Site:Tanzania | GA_delivery:31 | GA_sampling:16 RAW_FILE_NAME=pHILIC_63;nHILIC_63;pRPLC_63 nRPLC_63 SUBJECT_SAMPLE_FACTORS 20-20311 64 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:11 RAW_FILE_NAME=pHILIC_64;nHILIC_64;pRPLC_64 nRPLC_64 SUBJECT_SAMPLE_FACTORS 20UE00754 65 Site:Tanzania | GA_delivery:26 | GA_sampling:11 RAW_FILE_NAME=pHILIC_65;nHILIC_65;pRPLC_65 nRPLC_65 SUBJECT_SAMPLE_FACTORS 17-UE01243 66 Site:Pakistan | GA_delivery:32 | GA_sampling:9 RAW_FILE_NAME=pHILIC_66;nHILIC_66;pRPLC_66 nRPLC_66 SUBJECT_SAMPLE_FACTORS 17-UE00789 67 Site:Pakistan | GA_delivery:32 | GA_sampling:17 RAW_FILE_NAME=pHILIC_67;nHILIC_67;pRPLC_67 nRPLC_67 SUBJECT_SAMPLE_FACTORS 20UE01240 68 Site:Tanzania | GA_delivery:39 | GA_sampling:19 RAW_FILE_NAME=pHILIC_68;nHILIC_68;pRPLC_68 nRPLC_68 SUBJECT_SAMPLE_FACTORS 17-UE00208 69 Site:Pakistan | GA_delivery:32 | GA_sampling:8 RAW_FILE_NAME=pHILIC_69;nHILIC_69;pRPLC_69 nRPLC_69 SUBJECT_SAMPLE_FACTORS 11UE00374 70 Site:Bangladesh | GA_delivery:31 | GA_sampling:8 RAW_FILE_NAME=pHILIC_70;nHILIC_70;pRPLC_70 nRPLC_70 SUBJECT_SAMPLE_FACTORS 30-07165 71 Site:Zambia_GAPPS | GA_delivery:31 | GA_sampling:19 RAW_FILE_NAME=pHILIC_71;nHILIC_71;pRPLC_71 nRPLC_71 SUBJECT_SAMPLE_FACTORS 17-UE00401 72 Site:Pakistan | GA_delivery:39 | GA_sampling:18 RAW_FILE_NAME=pHILIC_72;nHILIC_72;pRPLC_72 nRPLC_72 SUBJECT_SAMPLE_FACTORS 11UE01476 73 Site:Bangladesh | GA_delivery:41 | GA_sampling:18 RAW_FILE_NAME=pHILIC_73;nHILIC_73;pRPLC_73 nRPLC_73 SUBJECT_SAMPLE_FACTORS 11UE00490 74 Site:Bangladesh | GA_delivery:41 | GA_sampling:8 RAW_FILE_NAME=pHILIC_74;nHILIC_74;pRPLC_74 nRPLC_74 SUBJECT_SAMPLE_FACTORS 20UE01639 75 Site:Tanzania | GA_delivery:39 | GA_sampling:15 RAW_FILE_NAME=pHILIC_75;nHILIC_75;pRPLC_75 nRPLC_75 SUBJECT_SAMPLE_FACTORS 11UE00971 76 Site:Bangladesh | GA_delivery:31 | GA_sampling:11 RAW_FILE_NAME=pHILIC_76;nHILIC_76;pRPLC_76 nRPLC_76 SUBJECT_SAMPLE_FACTORS 30-06436 77 Site:Zambia_GAPPS | GA_delivery:35 | GA_sampling:19 RAW_FILE_NAME=pHILIC_77;nHILIC_77;pRPLC_77 nRPLC_77 SUBJECT_SAMPLE_FACTORS 11UE01266 78 Site:Bangladesh | GA_delivery:41 | GA_sampling:13 RAW_FILE_NAME=pHILIC_78;nHILIC_78;pRPLC_78 nRPLC_78 SUBJECT_SAMPLE_FACTORS 20UE00157 79 Site:Tanzania | GA_delivery:39 | GA_sampling:14 RAW_FILE_NAME=pHILIC_79;nHILIC_79;pRPLC_79 nRPLC_79 SUBJECT_SAMPLE_FACTORS 17-UE00789 80 Site:Pakistan | GA_delivery:32 | GA_sampling:17 RAW_FILE_NAME=pHILIC_80;nHILIC_80;pRPLC_80 nRPLC_80 SUBJECT_SAMPLE_FACTORS 11UE01104 81 Site:Bangladesh | GA_delivery:29 | GA_sampling:15 RAW_FILE_NAME=pHILIC_81;nHILIC_81;pRPLC_81 nRPLC_81 SUBJECT_SAMPLE_FACTORS 17-UE01047 82 Site:Pakistan | GA_delivery:33 | GA_sampling:10 RAW_FILE_NAME=pHILIC_82;nHILIC_82;pRPLC_82 nRPLC_82 SUBJECT_SAMPLE_FACTORS 17-UE00394 83 Site:Pakistan | GA_delivery:39 | GA_sampling:9 RAW_FILE_NAME=pHILIC_83;nHILIC_83;pRPLC_83 nRPLC_83 SUBJECT_SAMPLE_FACTORS 20UE02257 84 Site:Tanzania | GA_delivery:33 | GA_sampling:15 RAW_FILE_NAME=pHILIC_84;nHILIC_84;pRPLC_84 nRPLC_84 SUBJECT_SAMPLE_FACTORS 20UE00867 85 Site:Tanzania | GA_delivery:26 | GA_sampling:19 RAW_FILE_NAME=pHILIC_85;nHILIC_85;pRPLC_85 nRPLC_85 SUBJECT_SAMPLE_FACTORS 30-00472 86 Site:Zambia_GAPPS | GA_delivery:28 | GA_sampling:8 RAW_FILE_NAME=pHILIC_86;nHILIC_86;pRPLC_86 nRPLC_86 SUBJECT_SAMPLE_FACTORS 20UE01197 87 Site:Tanzania | GA_delivery:39 | GA_sampling:12 RAW_FILE_NAME=pHILIC_87;nHILIC_87;pRPLC_87 nRPLC_87 SUBJECT_SAMPLE_FACTORS 20-23895 88 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:11 RAW_FILE_NAME=pHILIC_88;nHILIC_88;pRPLC_88 nRPLC_88 SUBJECT_SAMPLE_FACTORS 11UE01121 89 Site:Bangladesh | GA_delivery:29 | GA_sampling:13 RAW_FILE_NAME=pHILIC_89;nHILIC_89;pRPLC_89 nRPLC_89 SUBJECT_SAMPLE_FACTORS 30-07113 90 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:19 RAW_FILE_NAME=pHILIC_90;nHILIC_90;pRPLC_90 nRPLC_90 SUBJECT_SAMPLE_FACTORS 30-00472 91 Site:Zambia_GAPPS | GA_delivery:28 | GA_sampling:8 RAW_FILE_NAME=pHILIC_91;nHILIC_91;pRPLC_91 nRPLC_91 SUBJECT_SAMPLE_FACTORS 11UE00904 92 Site:Bangladesh | GA_delivery:41 | GA_sampling:11 RAW_FILE_NAME=pHILIC_92;nHILIC_92;pRPLC_92 nRPLC_92 SUBJECT_SAMPLE_FACTORS 20UE00831 93 Site:Tanzania | GA_delivery:32 | GA_sampling:10 RAW_FILE_NAME=pHILIC_93;nHILIC_93;pRPLC_93 nRPLC_93 SUBJECT_SAMPLE_FACTORS 20-32883 94 Site:Bangladesh_GAPPS | GA_delivery:39 | GA_sampling:13 RAW_FILE_NAME=pHILIC_94;nHILIC_94;pRPLC_94 nRPLC_94 SUBJECT_SAMPLE_FACTORS 11UE01391 95 Site:Bangladesh | GA_delivery:41 | GA_sampling:15 RAW_FILE_NAME=pHILIC_95;nHILIC_95;pRPLC_95 nRPLC_95 SUBJECT_SAMPLE_FACTORS 20-30035 96 Site:Bangladesh_GAPPS | GA_delivery:35 | GA_sampling:11 RAW_FILE_NAME=pHILIC_96;nHILIC_96;pRPLC_96 nRPLC_96 SUBJECT_SAMPLE_FACTORS 17-UE00873 97 Site:Pakistan | GA_delivery:39 | GA_sampling:12 RAW_FILE_NAME=pHILIC_97;nHILIC_97;pRPLC_97 nRPLC_97 SUBJECT_SAMPLE_FACTORS 20UE00285 98 Site:Tanzania | GA_delivery:39 | GA_sampling:16 RAW_FILE_NAME=pHILIC_98;nHILIC_98;pRPLC_98 nRPLC_98 SUBJECT_SAMPLE_FACTORS 30-01421 99 Site:Zambia_GAPPS | GA_delivery:37 | GA_sampling:16 RAW_FILE_NAME=pHILIC_99;nHILIC_99;pRPLC_99 nRPLC_99 SUBJECT_SAMPLE_FACTORS 20-23876 100 Site:Bangladesh_GAPPS | GA_delivery:36 | GA_sampling:11 RAW_FILE_NAME=pHILIC_100;nHILIC_100;pRPLC_100 nRPLC_100 SUBJECT_SAMPLE_FACTORS 20UE00701 101 Site:Tanzania | GA_delivery:39 | GA_sampling:11 RAW_FILE_NAME=pHILIC_101;nHILIC_101;pRPLC_101 nRPLC_101 SUBJECT_SAMPLE_FACTORS 11UE00848 102 Site:Bangladesh | GA_delivery:41 | GA_sampling:17 RAW_FILE_NAME=pHILIC_102;nHILIC_102;pRPLC_102 nRPLC_102 SUBJECT_SAMPLE_FACTORS 30-01421 103 Site:Zambia_GAPPS | GA_delivery:37 | GA_sampling:16 RAW_FILE_NAME=pHILIC_103;nHILIC_103;pRPLC_103 nRPLC_103 SUBJECT_SAMPLE_FACTORS 17-UE00787 104 Site:Pakistan | GA_delivery:39 | GA_sampling:8 RAW_FILE_NAME=pHILIC_104;nHILIC_104;pRPLC_104 nRPLC_104 SUBJECT_SAMPLE_FACTORS 11UE01266 105 Site:Bangladesh | GA_delivery:41 | GA_sampling:13 RAW_FILE_NAME=pHILIC_105;nHILIC_105;pRPLC_105 nRPLC_105 SUBJECT_SAMPLE_FACTORS 11UE01876 106 Site:Bangladesh | GA_delivery:31 | GA_sampling:16 RAW_FILE_NAME=pHILIC_106;nHILIC_106;pRPLC_106 nRPLC_106 SUBJECT_SAMPLE_FACTORS 17-UE00374 107 Site:Pakistan | GA_delivery:39 | GA_sampling:10 RAW_FILE_NAME=pHILIC_107;nHILIC_107;pRPLC_107 nRPLC_107 SUBJECT_SAMPLE_FACTORS 20UE00635 108 Site:Tanzania | GA_delivery:39 | GA_sampling:10 RAW_FILE_NAME=pHILIC_108;nHILIC_108;pRPLC_108 nRPLC_108 SUBJECT_SAMPLE_FACTORS 17-UE00848 109 Site:Pakistan | GA_delivery:33 | GA_sampling:18 RAW_FILE_NAME=pHILIC_109;nHILIC_109;pRPLC_109 nRPLC_109 SUBJECT_SAMPLE_FACTORS 20UE02100 110 Site:Tanzania | GA_delivery:39 | GA_sampling:18 RAW_FILE_NAME=pHILIC_110;nHILIC_110;pRPLC_110 nRPLC_110 SUBJECT_SAMPLE_FACTORS 20UE00754 111 Site:Tanzania | GA_delivery:26 | GA_sampling:11 RAW_FILE_NAME=pHILIC_111;nHILIC_111;pRPLC_111 nRPLC_111 SUBJECT_SAMPLE_FACTORS 11UE00099 112 Site:Bangladesh | GA_delivery:41 | GA_sampling:16 RAW_FILE_NAME=pHILIC_112;nHILIC_112;pRPLC_112 nRPLC_112 SUBJECT_SAMPLE_FACTORS 20-27607 113 Site:Bangladesh_GAPPS | GA_delivery:32 | GA_sampling:11 RAW_FILE_NAME=pHILIC_113;nHILIC_113;pRPLC_113 nRPLC_113 SUBJECT_SAMPLE_FACTORS 11UE00455 114 Site:Bangladesh | GA_delivery:41 | GA_sampling:13 RAW_FILE_NAME=pHILIC_114;nHILIC_114;pRPLC_114 nRPLC_114 SUBJECT_SAMPLE_FACTORS 20UE01197 115 Site:Tanzania | GA_delivery:39 | GA_sampling:12 RAW_FILE_NAME=pHILIC_115;nHILIC_115;pRPLC_115 nRPLC_115 SUBJECT_SAMPLE_FACTORS 30-06158 116 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:14 RAW_FILE_NAME=pHILIC_116;nHILIC_116;pRPLC_116 nRPLC_116 SUBJECT_SAMPLE_FACTORS 30-00423 117 Site:Zambia_GAPPS | GA_delivery:41 | GA_sampling:18 RAW_FILE_NAME=pHILIC_117;nHILIC_117;pRPLC_117 nRPLC_117 SUBJECT_SAMPLE_FACTORS 20-34360 118 Site:Bangladesh_GAPPS | GA_delivery:29 | GA_sampling:12 RAW_FILE_NAME=pHILIC_118;nHILIC_118;pRPLC_118 nRPLC_118 SUBJECT_SAMPLE_FACTORS 17-UE00873 119 Site:Pakistan | GA_delivery:39 | GA_sampling:12 RAW_FILE_NAME=pHILIC_119;nHILIC_119;pRPLC_119 nRPLC_119 SUBJECT_SAMPLE_FACTORS 17-UE01072 120 Site:Pakistan | GA_delivery:39 | GA_sampling:9 RAW_FILE_NAME=pHILIC_120;nHILIC_120;pRPLC_120 nRPLC_120 SUBJECT_SAMPLE_FACTORS 30-07248 121 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:17 RAW_FILE_NAME=pHILIC_121;nHILIC_121;pRPLC_121 nRPLC_121 SUBJECT_SAMPLE_FACTORS 11UE01876 122 Site:Bangladesh | GA_delivery:31 | GA_sampling:16 RAW_FILE_NAME=pHILIC_122;nHILIC_122;pRPLC_122 nRPLC_122 SUBJECT_SAMPLE_FACTORS 20UE00691 123 Site:Tanzania | GA_delivery:39 | GA_sampling:13 RAW_FILE_NAME=pHILIC_123;nHILIC_123;pRPLC_123 nRPLC_123 SUBJECT_SAMPLE_FACTORS 17-UE00253 124 Site:Pakistan | GA_delivery:40 | GA_sampling:17 RAW_FILE_NAME=pHILIC_124;nHILIC_124;pRPLC_124 nRPLC_124 SUBJECT_SAMPLE_FACTORS 20UE02238 125 Site:Tanzania | GA_delivery:39 | GA_sampling:9 RAW_FILE_NAME=pHILIC_125;nHILIC_125;pRPLC_125 nRPLC_125 SUBJECT_SAMPLE_FACTORS 11UE01121 126 Site:Bangladesh | GA_delivery:29 | GA_sampling:13 RAW_FILE_NAME=pHILIC_126;nHILIC_126;pRPLC_126 nRPLC_126 SUBJECT_SAMPLE_FACTORS 17-UE00563 127 Site:Pakistan | GA_delivery:40 | GA_sampling:18 RAW_FILE_NAME=pHILIC_127;nHILIC_127;pRPLC_127 nRPLC_127 SUBJECT_SAMPLE_FACTORS 20UE00831 128 Site:Tanzania | GA_delivery:32 | GA_sampling:10 RAW_FILE_NAME=pHILIC_128;nHILIC_128;pRPLC_128 nRPLC_128 SUBJECT_SAMPLE_FACTORS 20UE01817 129 Site:Tanzania | GA_delivery:32 | GA_sampling:9 RAW_FILE_NAME=pHILIC_129;nHILIC_129;pRPLC_129 nRPLC_129 SUBJECT_SAMPLE_FACTORS 30-00472 130 Site:Zambia_GAPPS | GA_delivery:28 | GA_sampling:8 RAW_FILE_NAME=pHILIC_130;nHILIC_130;pRPLC_130 nRPLC_130 SUBJECT_SAMPLE_FACTORS 20UE02257 131 Site:Tanzania | GA_delivery:33 | GA_sampling:15 RAW_FILE_NAME=pHILIC_131;nHILIC_131;pRPLC_131 nRPLC_131 SUBJECT_SAMPLE_FACTORS 20-20374 132 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:12 RAW_FILE_NAME=pHILIC_132;nHILIC_132;pRPLC_132 nRPLC_132 SUBJECT_SAMPLE_FACTORS 30-07248 133 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:17 RAW_FILE_NAME=pHILIC_133;nHILIC_133;pRPLC_133 nRPLC_133 SUBJECT_SAMPLE_FACTORS 17-UE00253 134 Site:Pakistan | GA_delivery:40 | GA_sampling:17 RAW_FILE_NAME=pHILIC_134;nHILIC_134;pRPLC_134 nRPLC_134 SUBJECT_SAMPLE_FACTORS 11UE00490 135 Site:Bangladesh | GA_delivery:41 | GA_sampling:8 RAW_FILE_NAME=pHILIC_135;nHILIC_135;pRPLC_135 nRPLC_135 SUBJECT_SAMPLE_FACTORS 30-07113 136 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:19 RAW_FILE_NAME=pHILIC_136;nHILIC_136;pRPLC_136 nRPLC_136 SUBJECT_SAMPLE_FACTORS 11UE01391 137 Site:Bangladesh | GA_delivery:41 | GA_sampling:15 RAW_FILE_NAME=pHILIC_137;nHILIC_137;pRPLC_137 nRPLC_137 SUBJECT_SAMPLE_FACTORS 20UE02136 138 Site:Tanzania | GA_delivery:32 | GA_sampling:13 RAW_FILE_NAME=pHILIC_138;nHILIC_138;pRPLC_138 nRPLC_138 SUBJECT_SAMPLE_FACTORS 17-UE00563 139 Site:Pakistan | GA_delivery:40 | GA_sampling:18 RAW_FILE_NAME=pHILIC_139;nHILIC_139;pRPLC_139 nRPLC_139 SUBJECT_SAMPLE_FACTORS 17-UE00413 140 Site:Pakistan | GA_delivery:28 | GA_sampling:9 RAW_FILE_NAME=pHILIC_140;nHILIC_140;pRPLC_140 nRPLC_140 SUBJECT_SAMPLE_FACTORS 20UE02100 141 Site:Tanzania | GA_delivery:39 | GA_sampling:18 RAW_FILE_NAME=pHILIC_141;nHILIC_141;pRPLC_141 nRPLC_141 SUBJECT_SAMPLE_FACTORS 30-04431 142 Site:Zambia_GAPPS | GA_delivery:40 | GA_sampling:17 RAW_FILE_NAME=pHILIC_142;nHILIC_142;pRPLC_142 nRPLC_142 SUBJECT_SAMPLE_FACTORS 20-29287 143 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:12 RAW_FILE_NAME=pHILIC_143;nHILIC_143;pRPLC_143 nRPLC_143 SUBJECT_SAMPLE_FACTORS 17-UE00401 144 Site:Pakistan | GA_delivery:39 | GA_sampling:18 RAW_FILE_NAME=pHILIC_144;nHILIC_144;pRPLC_144 nRPLC_144 SUBJECT_SAMPLE_FACTORS 20UE02136 145 Site:Tanzania | GA_delivery:32 | GA_sampling:13 RAW_FILE_NAME=pHILIC_145;nHILIC_145;pRPLC_145 nRPLC_145 SUBJECT_SAMPLE_FACTORS 11UE01855 146 Site:Bangladesh | GA_delivery:29 | GA_sampling:15 RAW_FILE_NAME=pHILIC_146;nHILIC_146;pRPLC_146 nRPLC_146 SUBJECT_SAMPLE_FACTORS 17-UE01059 147 Site:Pakistan | GA_delivery:33 | GA_sampling:16 RAW_FILE_NAME=pHILIC_147;nHILIC_147;pRPLC_147 nRPLC_147 SUBJECT_SAMPLE_FACTORS 30-00423 148 Site:Zambia_GAPPS | GA_delivery:41 | GA_sampling:18 RAW_FILE_NAME=pHILIC_148;nHILIC_148;pRPLC_148 nRPLC_148 SUBJECT_SAMPLE_FACTORS 30-07165 149 Site:Zambia_GAPPS | GA_delivery:31 | GA_sampling:19 RAW_FILE_NAME=pHILIC_149;nHILIC_149;pRPLC_149 nRPLC_149 SUBJECT_SAMPLE_FACTORS 30-08712 150 Site:Zambia_GAPPS | GA_delivery:36 | GA_sampling:16 RAW_FILE_NAME=pHILIC_150;nHILIC_150;pRPLC_150 nRPLC_150 SUBJECT_SAMPLE_FACTORS 30-07249 151 Site:Zambia_GAPPS | GA_delivery:33 | GA_sampling:13 RAW_FILE_NAME=pHILIC_151;nHILIC_151;pRPLC_151 nRPLC_151 SUBJECT_SAMPLE_FACTORS 20UE00157 152 Site:Tanzania | GA_delivery:39 | GA_sampling:14 RAW_FILE_NAME=pHILIC_152;nHILIC_152;pRPLC_152 nRPLC_152 SUBJECT_SAMPLE_FACTORS 11UE00904 153 Site:Bangladesh | GA_delivery:41 | GA_sampling:11 RAW_FILE_NAME=pHILIC_153;nHILIC_153;pRPLC_153 nRPLC_153 SUBJECT_SAMPLE_FACTORS 20-31519 154 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:12 RAW_FILE_NAME=pHILIC_154;nHILIC_154;pRPLC_154 nRPLC_154 SUBJECT_SAMPLE_FACTORS 17-UE01243 155 Site:Pakistan | GA_delivery:32 | GA_sampling:9 RAW_FILE_NAME=pHILIC_155;nHILIC_155;pRPLC_155 nRPLC_155 SUBJECT_SAMPLE_FACTORS 20UE01240 156 Site:Tanzania | GA_delivery:39 | GA_sampling:19 RAW_FILE_NAME=pHILIC_156;nHILIC_156;pRPLC_156 nRPLC_156 SUBJECT_SAMPLE_FACTORS 20-20961 157 Site:Bangladesh_GAPPS | GA_delivery:40 | GA_sampling:12 RAW_FILE_NAME=pHILIC_157;nHILIC_157;pRPLC_157 nRPLC_157 SUBJECT_SAMPLE_FACTORS 20-02340 158 Site:Bangladesh_GAPPS | GA_delivery:33 | GA_sampling:12 RAW_FILE_NAME=pHILIC_158;nHILIC_158;pRPLC_158 nRPLC_158 SUBJECT_SAMPLE_FACTORS 11UE00099 159 Site:Bangladesh | GA_delivery:41 | GA_sampling:16 RAW_FILE_NAME=pHILIC_159;nHILIC_159;pRPLC_159 nRPLC_159 SUBJECT_SAMPLE_FACTORS 17-UE01047 160 Site:Pakistan | GA_delivery:33 | GA_sampling:10 RAW_FILE_NAME=pHILIC_160;nHILIC_160;pRPLC_160 nRPLC_160 SUBJECT_SAMPLE_FACTORS 17-UE01292 161 Site:Pakistan | GA_delivery:33 | GA_sampling:18 RAW_FILE_NAME=pHILIC_161;nHILIC_161;pRPLC_161 nRPLC_161 SUBJECT_SAMPLE_FACTORS 11UE01294 162 Site:Bangladesh | GA_delivery:24 | GA_sampling:17 RAW_FILE_NAME=pHILIC_162;nHILIC_162;pRPLC_162 nRPLC_162 SUBJECT_SAMPLE_FACTORS 11UE02004 163 Site:Bangladesh | GA_delivery:31 | GA_sampling:15 RAW_FILE_NAME=pHILIC_163;nHILIC_163;pRPLC_163 nRPLC_163 SUBJECT_SAMPLE_FACTORS 17-UE00679 164 Site:Pakistan | GA_delivery:40 | GA_sampling:16 RAW_FILE_NAME=pHILIC_164;nHILIC_164;pRPLC_164 nRPLC_164 SUBJECT_SAMPLE_FACTORS 11UE01127 165 Site:Bangladesh | GA_delivery:33 | GA_sampling:17 RAW_FILE_NAME=pHILIC_165;nHILIC_165;pRPLC_165 nRPLC_165 SUBJECT_SAMPLE_FACTORS 17-UE00394 166 Site:Pakistan | GA_delivery:39 | GA_sampling:9 RAW_FILE_NAME=pHILIC_166;nHILIC_166;pRPLC_166 nRPLC_166 SUBJECT_SAMPLE_FACTORS 17-UE00787 167 Site:Pakistan | GA_delivery:39 | GA_sampling:8 RAW_FILE_NAME=pHILIC_167;nHILIC_167;pRPLC_167 nRPLC_167 SUBJECT_SAMPLE_FACTORS 30-07249 168 Site:Zambia_GAPPS | GA_delivery:33 | GA_sampling:13 RAW_FILE_NAME=pHILIC_168;nHILIC_168;pRPLC_168 nRPLC_168 SUBJECT_SAMPLE_FACTORS 11UE01476 169 Site:Bangladesh | GA_delivery:41 | GA_sampling:18 RAW_FILE_NAME=pHILIC_169;nHILIC_169;pRPLC_169 nRPLC_169 SUBJECT_SAMPLE_FACTORS 17-UE01292 170 Site:Pakistan | GA_delivery:33 | GA_sampling:18 RAW_FILE_NAME=pHILIC_170;nHILIC_170;pRPLC_170 nRPLC_170 SUBJECT_SAMPLE_FACTORS 30-08014 171 Site:Zambia_GAPPS | GA_delivery:31 | GA_sampling:11 RAW_FILE_NAME=pHILIC_171;nHILIC_171;pRPLC_171 nRPLC_171 SUBJECT_SAMPLE_FACTORS 11UE00374 172 Site:Bangladesh | GA_delivery:31 | GA_sampling:8 RAW_FILE_NAME=pHILIC_172;nHILIC_172;pRPLC_172 nRPLC_172 #COLLECTION CO:COLLECTION_SUMMARY The study comprises a single urine sample for each participant (n = 99) that was CO:COLLECTION_SUMMARY collected at a prenatal visit after ultrasound confirmed a gestation < 20 weeks. CO:COLLECTION_SUMMARY Ultrasound imaging was performed by trained sonologists in compliance with CO:COLLECTION_SUMMARY standard-of-care. All study sites employed a uniform method of GA assessment, CO:COLLECTION_SUMMARY urine collection and handling. Urine samples were aliquoted and frozen at -80°C CO:COLLECTION_SUMMARY within 2 hours. Deidentified urine aliquots were shipped on dry ice from each CO:COLLECTION_SUMMARY biorepository to Stanford University as a single batch and under continuous CO:COLLECTION_SUMMARY temperature monitoring. Urine samples from 20 healthy pregnancies collected CO:COLLECTION_SUMMARY between 8 and 19 weeks of gestation at the Lucile Packard Children’s Hospital CO:COLLECTION_SUMMARY at Stanford University, served as the validation cohort. CO:SAMPLE_TYPE Urine CO:STORAGE_CONDITIONS -80℃ #TREATMENT TR:TREATMENT_SUMMARY There was no treatment. #SAMPLEPREP SP:SAMPLEPREP_SUMMARY Urine aliquots were prepared and analyzed in a random order as previously SP:SAMPLEPREP_SUMMARY described (Contrepois et al., 2015). Briefly, frozen urine samples were thawed SP:SAMPLEPREP_SUMMARY on ice and centrifuged at 17,000g for 10 min at 4°C. Supernatants (25 µl) were SP:SAMPLEPREP_SUMMARY then diluted 1:4 with 75% acetonitrile and 100% water for HILIC- and RPLC-MS SP:SAMPLEPREP_SUMMARY experiments, respectively. Each sample was spiked-in with 15 analytical-grade SP:SAMPLEPREP_SUMMARY internal standards (IS). Samples for HILIC-MS experiments were further SP:SAMPLEPREP_SUMMARY centrifuged at 21,000g for 10 min at 4°C to precipitate proteins. #CHROMATOGRAPHY CH:CHROMATOGRAPHY_SUMMARY RPLC experiments were performed using a Zorbax SBaq column 2.1 x 50 mm, 1.7 μm, CH:CHROMATOGRAPHY_SUMMARY 100Å (Agilent Technologies) and mobile phase solvents consisting of 0.06% CH:CHROMATOGRAPHY_SUMMARY acetic acid in water (A) and 0.06% acetic acid in methanol (B). (Contrepois et CH:CHROMATOGRAPHY_SUMMARY al., 2015) CH:CHROMATOGRAPHY_TYPE Reversed phase CH:INSTRUMENT_NAME Thermo Dionex Ultimate 3000 RS CH:COLUMN_NAME Hypersil GOLD (2.1 x 150 mm, 1.9 µm) CH:FLOW_RATE 0.6 ml/min CH:COLUMN_TEMPERATURE 60 CH:SOLVENT_A 0.06% acetic acid in water CH:SOLVENT_B 0.06% acetic acid in methanol #ANALYSIS AN:ANALYSIS_TYPE MS AN:OPERATOR_NAME Kevin Contrepois AN:DETECTOR_TYPE Orbitrap AN:DATA_FORMAT .RAW #MS MS:INSTRUMENT_NAME Thermo Q Exactive HF hybrid Orbitrap MS:INSTRUMENT_TYPE Orbitrap MS:MS_TYPE ESI MS:ION_MODE NEGATIVE MS:MS_COMMENTS Data processing. Data from each mode were independently analyzed using MS:MS_COMMENTS Progenesis QI software (v2.3) (Nonlinear Dynamics). Metabolic features from MS:MS_COMMENTS blanks and that did not show sufficient linearity upon dilution in QC samples (r MS:MS_COMMENTS < 0.6) were discarded. Only metabolic features present in > 2/3 of the samples MS:MS_COMMENTS were kept for further analysis. Inter- and intra-batch variations were corrected MS:MS_COMMENTS by applying locally estimated scatterplot smoothing local regression (LOESS) on MS:MS_COMMENTS pooled samples injected repetitively along the batches (span = 0.75). Data were MS:MS_COMMENTS acquired in four batches for HILIC and RPLC modes. Dilution effects were MS:MS_COMMENTS corrected using probabilistic quotient normalization (PQN) (Rosen Vollmar et MS:MS_COMMENTS al., 2019). Missing values were imputed by drawing from a random distribution of MS:MS_COMMENTS low values in the corresponding sample. Data from each mode were then merged, MS:MS_COMMENTS producing a dataset containing 6,630 metabolic features. Metabolite abundances MS:MS_COMMENTS were reported as spectral counts. Metabolic feature annotation. Peak annotation MS:MS_COMMENTS was first performed by matching experimental m/z, retention time and MS/MS MS:MS_COMMENTS spectra to an in-house library of analytical-grade standards. Remaining peaks MS:MS_COMMENTS were identified by matching experimental m/z and fragmentation spectra to MS:MS_COMMENTS publicly available databases including HMDB (http://www.hmdb.ca/), MoNA MS:MS_COMMENTS (http://mona.fiehnlab.ucdavis.edu/) and MassBank (http://www.massbank.jp/) using MS:MS_COMMENTS the R package ‘MetID’ (v0.2.0) (Shen et al., 2019). Briefly, metabolic MS:MS_COMMENTS feature tables from Progenesis QI were matched to fragmentation spectra with a MS:MS_COMMENTS m/z and a retention time window of ± 15 ppm and ± 30 s (HILIC) and ± 20 s MS:MS_COMMENTS (RPLC), respectively. When multiple MS/MS spectra match a single metabolic MS:MS_COMMENTS feature, all matched MS/MS spectra were used for the identification. Next, MS1 MS:MS_COMMENTS and MS2 pairs were searched against public databases and a similarity score was MS:MS_COMMENTS calculated using the forward dot–product algorithm which considers both MS:MS_COMMENTS fragments and intensities (Stein and Scott, 1994). Metabolites were reported if MS:MS_COMMENTS the similarity score was above 0.4. Spectra from metabolic features of interest MS:MS_COMMENTS important in random forest models (see below) were further investigated manually MS:MS_COMMENTS to confirm identification. MS:CAPILLARY_TEMPERATURE 375C MS:CAPILLARY_VOLTAGE 3.4kV MS:COLLISION_ENERGY 25 & 50 NCE MS:COLLISION_GAS N2 MS:DRY_GAS_TEMP 310C MS:MS_RESULTS_FILE ST001491_AN002473_Results.txt UNITS:MS Counts Has m/z:Yes Has RT:Yes RT units:Minutes #END