#METABOLOMICS WORKBENCH yash_thsti_20250908_224927 DATATRACK_ID:6401 STUDY_ID:ST004185 ANALYSIS_ID:AN006950 PROJECT_ID:PR002640 VERSION 1 CREATED_ON September 15, 2025, 7:54 pm #PROJECT PR:PROJECT_TITLE Maternal and fetal Tryptophan-Kynurenine metabolite changes in Preeclampsia and PR:PROJECT_TITLE Gestational Diabetes PR:PROJECT_TYPE Metabolomics PR:PROJECT_SUMMARY Preeclampsia (PE) and gestational diabetes mellitus (GDM) are major pregnancy PR:PROJECT_SUMMARY complications associated with maternal and neonatal morbidity, including fetal PR:PROJECT_SUMMARY growth restriction and preterm birth. Both disorders involve systemic metabolic PR:PROJECT_SUMMARY dysregulation; however, their effects on maternal and neonatal metabolomic PR:PROJECT_SUMMARY profiles, especially in the Indian population, remain underexplored. In this PR:PROJECT_SUMMARY prospective cohort study, maternal serum and neonatal cord blood were analyzed PR:PROJECT_SUMMARY using ultra-high performance liquid chromatography coupled with Orbitrap mass PR:PROJECT_SUMMARY spectrometry. Differential metabolites were identified and subjected to pathway PR:PROJECT_SUMMARY enrichment and correlation analysis with clinical traits. Distinct metabolomic PR:PROJECT_SUMMARY alterations were observed in maternal and neonatal samples from PE and GDM PR:PROJECT_SUMMARY groups, with notable overlap in neonatal profiles despite differing maternal PR:PROJECT_SUMMARY conditions. Dysregulation of tryptophan–kynurenine (TRP–KYN) pathway PR:PROJECT_SUMMARY metabolites, including kynurenine, quinolinic acid, and serotonin, emerged in PR:PROJECT_SUMMARY both groups and correlated with gestational age, placental weight, vitamin D PR:PROJECT_SUMMARY status, and neonatal bone mineral density. Pathway analysis further highlighted PR:PROJECT_SUMMARY disruptions across multiple metabolic pathways. These findings demonstrate PR:PROJECT_SUMMARY metabolic perturbations in PE and GDM, underscoring the TRP–KYN pathway as a PR:PROJECT_SUMMARY shared feature influencing fetal development. This pathway may serve as a PR:PROJECT_SUMMARY biomarker and therapeutic target, warranting validation in larger cohorts and PR:PROJECT_SUMMARY deeper molecular investigation. PR:INSTITUTE Translational Health Science And Technology Institute (THSTI) PR:DEPARTMENT NCD PR:LABORATORY Biomarker lab PR:LAST_NAME Kumar PR:FIRST_NAME Yashwant PR:ADDRESS NCR Biotech Science Cluster,, Faridabad, Haryana, 121001, India PR:EMAIL y.kumar@thsti.res.in PR:PHONE 01292876496 PR:FUNDING_SOURCE THSTI #STUDY ST:STUDY_TITLE Maternal and fetal Tryptophan-Kynurenine metabolite changes in Preeclampsia and ST:STUDY_TITLE Gestational Diabetes ST:STUDY_TYPE Metabolomics ST:STUDY_SUMMARY Preeclampsia (PE) and gestational diabetes mellitus (GDM) are major pregnancy ST:STUDY_SUMMARY complications associated with maternal and neonatal morbidity, including fetal ST:STUDY_SUMMARY growth restriction and preterm birth. Both disorders involve systemic metabolic ST:STUDY_SUMMARY dysregulation; however, their effects on maternal and neonatal metabolomic ST:STUDY_SUMMARY profiles, especially in the Indian population, remain underexplored. In this ST:STUDY_SUMMARY prospective cohort study, maternal serum and neonatal cord blood were analyzed ST:STUDY_SUMMARY using ultra-high performance liquid chromatography coupled with Orbitrap mass ST:STUDY_SUMMARY spectrometry. Differential metabolites were identified and subjected to pathway ST:STUDY_SUMMARY enrichment and correlation analysis with clinical traits. Distinct metabolomic ST:STUDY_SUMMARY alterations were observed in maternal and neonatal samples from PE and GDM ST:STUDY_SUMMARY groups, with notable overlap in neonatal profiles despite differing maternal ST:STUDY_SUMMARY conditions. Dysregulation of tryptophan–kynurenine (TRP–KYN) pathway ST:STUDY_SUMMARY metabolites, including kynurenine, quinolinic acid, and serotonin, emerged in ST:STUDY_SUMMARY both groups and correlated with gestational age, placental weight, vitamin D ST:STUDY_SUMMARY status, and neonatal bone mineral density. Pathway analysis further highlighted ST:STUDY_SUMMARY disruptions across multiple metabolic pathways. These findings demonstrate ST:STUDY_SUMMARY metabolic perturbations in PE and GDM, underscoring the TRP–KYN pathway as a ST:STUDY_SUMMARY shared feature influencing fetal development. This pathway may serve as a ST:STUDY_SUMMARY biomarker and therapeutic target, warranting validation in larger cohorts and ST:STUDY_SUMMARY deeper molecular investigation. ST:INSTITUTE Translational Health Science And Technology Institute (THSTI) ST:DEPARTMENT NCD ST:LABORATORY Biomarker lab ST:LAST_NAME Kumar ST:FIRST_NAME Yashwant ST:ADDRESS NCR Biotech Science Cluster,, Faridabad, Haryana, 121001, India ST:EMAIL y.kumar@thsti.res.in ST:PHONE +911292876496 #SUBJECT SU:SUBJECT_TYPE Human SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 #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 - CB_1 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_1.raw SUBJECT_SAMPLE_FACTORS - CB_2 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_2.raw SUBJECT_SAMPLE_FACTORS - CB_3 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_3.raw SUBJECT_SAMPLE_FACTORS - CB_4 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_4.raw SUBJECT_SAMPLE_FACTORS - CB_5 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_5.raw SUBJECT_SAMPLE_FACTORS - CB_6 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_6.raw SUBJECT_SAMPLE_FACTORS - CB_7 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_7.raw SUBJECT_SAMPLE_FACTORS - CB_8 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_8.raw SUBJECT_SAMPLE_FACTORS - CB_9 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_9.raw SUBJECT_SAMPLE_FACTORS - CB_10 Sample source:Serum | Group:control baby RAW_FILE_NAME(Raw file name)=CB_10.raw SUBJECT_SAMPLE_FACTORS - CM_1 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_1.raw SUBJECT_SAMPLE_FACTORS - CM_2 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_2.raw SUBJECT_SAMPLE_FACTORS - CM_3 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_3.raw SUBJECT_SAMPLE_FACTORS - CM_4 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_4.raw SUBJECT_SAMPLE_FACTORS - CM_5 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_5.raw SUBJECT_SAMPLE_FACTORS - CM_6 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_6.raw SUBJECT_SAMPLE_FACTORS - CM_7 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_7.raw SUBJECT_SAMPLE_FACTORS - CM_8 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_8.raw SUBJECT_SAMPLE_FACTORS - CM_9 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_9.raw SUBJECT_SAMPLE_FACTORS - CM_10 Sample source:Serum | Group:control mother RAW_FILE_NAME(Raw file name)=CM_10.raw SUBJECT_SAMPLE_FACTORS - GB_1 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_1.raw SUBJECT_SAMPLE_FACTORS - GB_2 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_2.raw SUBJECT_SAMPLE_FACTORS - GB_3 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_3.raw SUBJECT_SAMPLE_FACTORS - GB_4 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_4.raw SUBJECT_SAMPLE_FACTORS - GB_5 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_5.raw SUBJECT_SAMPLE_FACTORS - GB_6 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_6.raw SUBJECT_SAMPLE_FACTORS - GB_7 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_7.raw SUBJECT_SAMPLE_FACTORS - GB_8 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_8.raw SUBJECT_SAMPLE_FACTORS - GB_9 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_9.raw SUBJECT_SAMPLE_FACTORS - GB_10 Sample source:Serum | Group:Gestational baby RAW_FILE_NAME(Raw file name)=GB_10.raw SUBJECT_SAMPLE_FACTORS - GM_1 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_1.raw SUBJECT_SAMPLE_FACTORS - GM_2 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_2.raw SUBJECT_SAMPLE_FACTORS - GM_3 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_3.raw SUBJECT_SAMPLE_FACTORS - GM_4 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_4.raw SUBJECT_SAMPLE_FACTORS - GM_5 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_5.raw SUBJECT_SAMPLE_FACTORS - GM_6 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_6.raw SUBJECT_SAMPLE_FACTORS - GM_7 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_7.raw SUBJECT_SAMPLE_FACTORS - GM_8 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_8.raw SUBJECT_SAMPLE_FACTORS - GM_9 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_9.raw SUBJECT_SAMPLE_FACTORS - GM_10 Sample source:Serum | Group:Gestational mother RAW_FILE_NAME(Raw file name)=GM_10.raw SUBJECT_SAMPLE_FACTORS - PB_1 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_1.raw SUBJECT_SAMPLE_FACTORS - PB_2 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_2.raw SUBJECT_SAMPLE_FACTORS - PB_3 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_3.raw SUBJECT_SAMPLE_FACTORS - PB_4 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_4.raw SUBJECT_SAMPLE_FACTORS - PB_5 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_5.raw SUBJECT_SAMPLE_FACTORS - PB_6 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_6.raw SUBJECT_SAMPLE_FACTORS - PB_7 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_7.raw SUBJECT_SAMPLE_FACTORS - PB_8 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_8.raw SUBJECT_SAMPLE_FACTORS - PB_9 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_9.raw SUBJECT_SAMPLE_FACTORS - PB_10 Sample source:Serum | Group:preaclamsia baby RAW_FILE_NAME(Raw file name)=PB_10.raw SUBJECT_SAMPLE_FACTORS - PM_1 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_1.raw SUBJECT_SAMPLE_FACTORS - PM_2 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_2.raw SUBJECT_SAMPLE_FACTORS - PM_3 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_3.raw SUBJECT_SAMPLE_FACTORS - PM_4 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_4.raw SUBJECT_SAMPLE_FACTORS - PM_5 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_5.raw SUBJECT_SAMPLE_FACTORS - PM_6 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_6.raw SUBJECT_SAMPLE_FACTORS - PM_7 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_7.raw SUBJECT_SAMPLE_FACTORS - PM_8 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_8.raw SUBJECT_SAMPLE_FACTORS - PM_9 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_9.raw SUBJECT_SAMPLE_FACTORS - PM_10 Sample source:Serum | Group:preaclamsia mother RAW_FILE_NAME(Raw file name)=PM_10.raw #COLLECTION CO:COLLECTION_SUMMARY Study Population and data collection: This prospective cohort study was CO:COLLECTION_SUMMARY conducted at the Department of Obstetrics and Gynaecology, All India Institute CO:COLLECTION_SUMMARY of Medical Sciences (AIIMS), New Delhi. Study subjects were enrolled from the CO:COLLECTION_SUMMARY antenatal clinic from January 2016 to June 2018. GDM cases were diagnosed on CO:COLLECTION_SUMMARY basis of the International Association of Diabetes and Pregnancy Study Groups CO:COLLECTION_SUMMARY (IADPSG) (3) criteria requiring at least one abnormal value from a 75g OGTT, CO:COLLECTION_SUMMARY showing fasting glucose ≥92 mg/dL, 1-hour glucose ≥180 mg/dL, or 2-hour CO:COLLECTION_SUMMARY glucose ≥153 mg/dL. Diagnosis of PE was according to the criteria of the CO:COLLECTION_SUMMARY International Society for the Study of Hypertension in Pregnancy (ISSHP) (9) on CO:COLLECTION_SUMMARY blood pressure >140/90 mm/Hg with at least two separate readings after 20 weeks CO:COLLECTION_SUMMARY of gestation with proteinuria >300 mg/24-h urine or >1+ in dipstick. All CO:COLLECTION_SUMMARY included subjects carried a singleton pregnancy. Any subject with pre-pregnancy CO:COLLECTION_SUMMARY diabetes mellitus, untreated hypo/ hyperthyroidism, chronic liver/renal disease, CO:COLLECTION_SUMMARY or any systemic illness was excluded from the study. Similarly, pregnancies with CO:COLLECTION_SUMMARY congenital malformations in fetuses were also excluded. After a detailed history CO:COLLECTION_SUMMARY and tailored clinical examination, blood samples from mothers were collected CO:COLLECTION_SUMMARY while they were admitted for delivery and cord blood samples were collected CO:COLLECTION_SUMMARY during delivery. Placental weight was measured by a standardized tabletop CO:COLLECTION_SUMMARY digital weighing scale. Informed written consent was secured from all CO:COLLECTION_SUMMARY participants, and ethical approval was obtained from the Institutional Ethics CO:COLLECTION_SUMMARY Committee of All India Institute of Medical Sciences-New Delhi (IEC/414/8/2016). CO:COLLECTION_SUMMARY Sample Collection and Neonatal Assessment After a detailed history and tailored CO:COLLECTION_SUMMARY clinical examination, blood samples from mothers were collected while they were CO:COLLECTION_SUMMARY admitted for delivery and cord blood samples were collected during delivery. CO:COLLECTION_SUMMARY Placental weight was measured by a standardized tabletop digital weighing scale CO:COLLECTION_SUMMARY and stored at -80°C for subsequent analysis. Serum was separated by CO:COLLECTION_SUMMARY centrifugation at 3,000 rpm for 10 minutes, aliquoted and stored at -80°C until CO:COLLECTION_SUMMARY analysis. After milk-feed, neonates were swaddled in a soft, warm cloth and CO:COLLECTION_SUMMARY placed on the platform in the supine position without sedation. DXA scans were CO:COLLECTION_SUMMARY performed within 48 h of birth by Hologic Discovery A 84023, QDR, USA scanner CO:COLLECTION_SUMMARY using pediatric software (Apex System software, version 4.5.2.1) to assess bone CO:COLLECTION_SUMMARY mineral content and body composition. CO:SAMPLE_TYPE Blood (serum) #TREATMENT TR:TREATMENT_SUMMARY NA #SAMPLEPREP SP:SAMPLEPREP_SUMMARY The serum samples were thawed on ice, and 50 µl was aliquoted for metabolite SP:SAMPLEPREP_SUMMARY extraction. 100% chilled LC-MS grade Methanol (Honeywell 34966) was added in a SP:SAMPLEPREP_SUMMARY 1:3 (v/v) ratio to each sample. The suspension was thoroughly mixed by brief SP:SAMPLEPREP_SUMMARY vortexing and incubated on ice for 10 minutes. The samples were then centrifuged SP:SAMPLEPREP_SUMMARY at 12,000rpm for 10 mins at 4° and the supernatant was carefully transferred in SP:SAMPLEPREP_SUMMARY equal volumes, in two fresh MCTs. The methanol extract was evaporated using the SP:SAMPLEPREP_SUMMARY speed vac sample concentrator at room temperature, followed by storage in a SP:SAMPLEPREP_SUMMARY -80℃ freezer till further analysis. For injection into the LC-MS, the samples SP:SAMPLEPREP_SUMMARY were reconstituted in 60 µl of 15% Methanol: water. #CHROMATOGRAPHY CH:CHROMATOGRAPHY_SUMMARY The extracted serum metabolites were separated on Thermo UPLC Ultimate 3000. CH:CHROMATOGRAPHY_SUMMARY ACQUITY HSS T3 (2.1mm x100mm x1.8µm, Waters) column was used for metabolite CH:CHROMATOGRAPHY_SUMMARY separation. RPC Solvent A was 99.9% LC-MS grade water (Honeywell 39253) and 0.1% CH:CHROMATOGRAPHY_SUMMARY of LC-MS grade Formic acid (FA) (Fisher Chemical A117) and Solvent B was 99.9% CH:CHROMATOGRAPHY_SUMMARY LC-MS grade Methanol with 0.1% FA. The 14min elution gradient with a flow rate CH:CHROMATOGRAPHY_SUMMARY of 300 µl/min, started from 0.1%B to 15% B for 1min; 15%B to 35% for 4min; 35%B CH:CHROMATOGRAPHY_SUMMARY to 95%B for 3mins; maintained at 95% for 2mins and brought back to original 1%B CH:CHROMATOGRAPHY_SUMMARY over 4mins. CH:CHROMATOGRAPHY_TYPE Reversed phase CH:INSTRUMENT_NAME Thermo Dionex Ultimate 3000 CH:COLUMN_NAME Waters ACQUITY UPLC HSS T3 (100 x 2.1mm,1.8um) CH:SOLVENT_A 100% Water; 0.1% formic acid CH:SOLVENT_B 100% Methanol; 0.1% formic acid CH:FLOW_GRADIENT Started from 0.1%B to 15% B for 1min; 15%B to 35% for 4min; 35%B to 95%B for CH:FLOW_GRADIENT 3mins; maintained at 95% for 2mins and brought back to original 1%B over 4mins. CH:FLOW_RATE 300 ul/min CH:COLUMN_TEMPERATURE 40°C #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME Thermo Fusion Tribrid Orbitrap MS:INSTRUMENT_TYPE Orbitrap MS:MS_TYPE ESI MS:ION_MODE NEGATIVE MS:MS_COMMENTS For data acquisition, the Orbitrap Fusion mass spectrometer (Thermo Scientific) MS:MS_COMMENTS coupled with a heated electrospray ion source was used. Previously published MS:MS_COMMENTS methods (doi: 10.1021/acs.analchem.7b00925, doi: 10.3389/fcimb.2019.00070.) for MS:MS_COMMENTS data acquisition have been adapted with minor modifications. The data was MS:MS_COMMENTS acquired in both positive and negative ionization modes. The mass ranges for MS:MS_COMMENTS scans were kept between 65 and 1000 Da. The mass resolution for MS1 and MS2 MS:MS_COMMENTS scans was kept at 120,000 and 30,000, respectively. The AGC target was set at MS:MS_COMMENTS 1.0e5. Pool Quality Control (QC) samples were queued after every 10 samples to MS:MS_COMMENTS check for Retention Time (RT) shift, mass error and variation in signal MS:MS_COMMENTS intensity. MS:MS_RESULTS_FILE ST004185_AN006950_Results.txt UNITS:relative intensity Has m/z:Yes Has RT:Yes RT units:Minutes #END