#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