DOI: 10.5061/dryad.ghx3ffbwj
title: Data from: Infant microbes and metabolites point to childhood neurodevelopmental disorders

description: This study has followed a birth cohort for over twenty years to find
 factors associated with neurodevelopmental disorder (ND) diagnosis.
 Detailed, early-life longitudinal questionnaires captured infection and
 antibiotic events, stress, prenatal factors, family history, and more.
 Biomarkers including cord serum metabolome and lipidome, HLA genotype,
 infant microbiota, and stool metabolome were assessed. Among the 16,440
 Swedish children followed across time, 1,197 developed an ND. Significant
 associations emerged for future ND diagnosis in general and for specific
 ND subtypes, spanning intellectual disability, speech disorder, attention
 deficit hyperactivity disorder, and autism. This investigation revealed
 microbiome connections to future diagnosis, as well as early-emerging mood
 and gastrointestinal problems. The findings suggest links to
 immunodysregulation and metabolism, compounded by stress, early-life
 infection, and antibiotics. The convergence of infant biomarkers and risk
 factors in this prospective, longitudinal study on a large-scale
 population establishes a foundation for early-life prediction and
 intervention in neurodevelopment.
description: For this investigation, we analyzed the earliest questionnaires
 derived from parents of ABIS children at one, three, and five years of
 age. The latest diagnoses considered in this investigation were obtained
 when the children were 21 to 23 years of age. All families provided
 informed consent to be included in this study. The ABIS study was approved
 by the Research Ethics Committee, Linköping University and Lund
 University, approval numbers Dnr 03-092; LiU 287.96, LU 83-97, LiU
 321-99.and Linköping University Dnr 36287, Dnr 03-513, Dnr 2018/380-32.
  In-depth methodology for the microbiome and metabolomic datasets is
 provided in our accompanying manuscript in <em>Cell</em>.
 (https://doi.org/10.1016/j.cell.2024.02.035)
description: # Infant microbes and metabolites point to childhood neurodevelopmental
 disorders
 [https://doi.org/10.5061/dryad.ghx3ffbwj](https://doi.org/10.5061/dryad.ghx3ffbwj) ABIS is a prospective, general population-based cohort study to which parents of all children born in southeast Sweden during the period 1 October 1997–1 October 1999 were invited. Of the 21,700 families asked, 17,055 agreed to participate (78.6%), giving informed consent after receiving oral and written information. The children have been followed from birth. The ABIS study was approved by the Research Ethics Committee, Linköping University and Lund University, approval numbers Dnr 03-092; LiU 287.96, LU 83-97, LiU 321-99.and Linköping University Dnr 36287, Dnr 03-513, Dnr 2018/380-32. ## Description of the data and file structure The data analyzed in this investigation involve ABIS Questionnaires (at birth, one year, three years, and five years of age), microbiome (16S rRNA sequencing on Illumina MiSeq V3-V4 on stool samples collected at one year of age), and metabolomic datasets (cord serum and stool collected at one year of age). Processed datasets corresponding to these datasets are provided, along with descriptions, below. Results and the corresponding analytical methods employed to capture these differences are elaborated upon in our accompanying manuscript published in *Cell*. #### 1- ABIS Questionnaires & HLA This investigation focuses on analyzing early-life factors and genetic markers associated with future ND diagnoses in ABIS. The earliest questionnaires, obtained at ages one, three, and five, were analyzed, and the latest diagnoses were obtained when the children were 21 to 23 years old. The cohort consists of 14,869 controls and 1,179 children with a future ND diagnosis as of December 2022. Human leukocyte antigen (HLA) class II genotype was determined for 3,783 children using sequence-specific hybridization. Given the known association of autoimmune disease with neurodevelopment, this investigation also compared the prevalence of risk alleles for autoimmunity across future NDs and controls. ###### File Descriptions The cohort is represented across five CSV files, each containing data from controls and children with future diagnosis of the following: * **1.1- ND_DRYAD_v2.csv** contains data from controls and all children with a future ND diagnosis. * **1.2- ADHD_DRYAD_v2.csv** contains data from controls and all children with a future ADHD diagnosis. * **1.3- ASD_DRYAD_v2.csv** contains data from controls and all children with a future ASD diagnosis. * **1.4- IntDis_DRYAD_v2.csv** contains data from controls and all children with a future intellectual disability diagnosis. * **1.5- SpeechDis_DRYAD_v2.csv** contains data from controls and all children with a future speech disorder diagnosis. Data in each file represents a combination of factors based on their significance with the respective outcome: | Variable | Description | Timepoint | Values | | :------------------- | :---------------------------------------------------------------------------------------------------------------------------------- | :----------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | ID | ID of child within diagnosis group comparison |   | | | ASD\_20 | ASD Diagnosis by Dec 2020 |   | 0=Control (no future ND); 1=ASD diagnosis by Dec 2020 | | IntDis\_20 | MR Diagnosis by Dec 2020 |   | 0=Control (no future ND); 1=Intellectual disability diagnosis by Dec 2020 | | Speech\_20 | Speech Diagnosis by December 2020 |   | 0=Control (no future ND); 1=Speech disorder diagnosis by Dec 2020 | | ADHD\_20 | ADHD Diagnosis by Dec 2020 |   | 0=Control (no future ND); 1=ADHD diagnosis by Dec 2020 | | fr\_12\_week\_4cat | Week of delivery - categories consolidated | Birth questionnaire | 36=preterm (less than 37); 37=early term (37-38); 39=full term (39-40); 41=late to post term (41+) | | | | | | | fr\_15f\_4 | Inheritance, T1D grandparents | Birth questionnaire | 0=no; 1=yes | | fr\_15i\_4 | Inheritance, celiac disease, mother-grandparents | Birth questionnaire | 0=no; 1=yes | | fr\_16d\_1 | Mother has asthma | Birth questionnaire | 0=no; 1=yes | | fr\_16d\_2 | Father had asthma | Birth questionnaire | 0=no; 1=yes | | fr\_17b | Did you use cortisone during your pregnancy | Birth questionnaire | 1=yes; 2=no; 3=do not know | | fr\_17e | Did you use analgesics during your pregnancy | Birth questionnaire | 1=yes; 2=no; 3=do not know | | fr\_18 | Did you smoke during your pregnancy? | Birth questionnaire | 0=no; 1=yes | | fr\_18a\_3cat | If yes, how many cigarettes per day? | Birth questionnaire | 1=1-5 cigarettes/day; 2=6-10 cigarettes/day; 36=10 or more cigarettes/day | | fr\_18a\_2cat\_1\_36 | If yes, how many cigarettes per day? | Birth questionnaire | 1=1-5 cigarettes/day; 36=10 or more cigarettes/day | | | | | | | fr\_33 | What type of home did the mother live in during the first 3 months of pregnancy? | Birth questionnaire | 1=villa; 2=apartment; 3=other | | fr\_40 | What type of home did the mother live in during the 4-10 months of pregnancy? | Birth questionnaire | 1=villa; 2=apartment; 3=other | | b\_4b | Otitis | One year questionnaire | 1=yes; 2=no; 3=do not know | | b\_42c | Infection requiring penicillin | One year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | b\_42f | Eczema | One year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | | | | | | c\_10b | Has the child suffered from tonsillitis during the period from 12 months old until now? | Three year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | c\_10c | Has the child suffered from otitis during the period from 12 months old until now? | Three year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | c\_10f | Has the child suffered from an infection that required antibiotics during the period from 12 months old until now? | Three year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | c\_10g | Has the child suffered from gastroenteritis the period from 12 months old until now? | Three year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | c\_16a | Do you think that the child suffers from or is affected by poor growth? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16b | Do you think that the child suffers from or is affected by poor weight gain? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16c | Do you think that the child suffers from or is affected by poor appetite? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16d | Do you think that the child suffers from or is affected by stomachache? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16e | Do you think that the child suffers from or is affected by a bloated / gassy stomach? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16f | Do you think that the child suffers from or is affected by diarrhea 3 times or more / day? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16g | Do you think that the child suffers from or is affected by vomiting 3 times or more / day? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16h | Do you think that the child suffers from or is affected by constipation? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16i | Do you think that the child suffers from or is affected by fatigue? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16j | Do you think that the child suffers from or is affected by a general irritation? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16k | Do you think that the child suffers from or is affected by a cranky mood, screaming a lot? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | c\_16l | Do you think that the child suffers from or is affected by poor sleep quality? | Three year questionnaire | 1=yes; 2=no; 3=do not know | | | | | | | c\_57a | Mother smoking (2.5 years follow-up) | Three year questionnaire | 1=yes; 2=no | | c\_57b | If, yes how many cigarettes / day? | Three year questionnaire | 1=1-5 cigarettes/day; 2=6-10  cigarettes/day; 3= 10-15  cigarettes/day; 4= 16-20  cigarettes/day; 5= 21-40  cigarettes/day; 6= more than 40 cigarettes/day | | c\_58a | Father smoking (2.5 years follow-up) | Three year questionnaire | 1=yes; 2=no | | c\_58b | If, yes how many cigarettes / day? | Three year questionnaire | 1=1-5 cigarettes/day; 2=6-10  cigarettes/day; 3= 10-15  cigarettes/day; 4= 16-20  cigarettes/day; 5= 21-40  cigarettes/day; 6= more than 40 cigarettes/day | | c\_59a | Have someone smoked in your home during the last two years? | Three year questionnaire | 1=yes; 2=no | | c\_59b | If, yes how many cigarettes (or corresponding) have adults smoked in your home on an average (the total amount) the last two year? | Three year questionnaire | 1=occasionally; 2=1-5 cigarettes/day; 3= 6-10 cigarettes/day; 4=11-15 cigarettes/day; 5=16-20 cigarettes/day; 6=21-40 cigarettes/day; 7=41-60 cigarettes/day; 8= more than 60 cigarettes/day | | e\_8c | Has the child suffered from otitis during the period from 2.5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_8f | Has the child suffered from an infection that required antibiotics, during the period from 2.5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_8g | Has the child suffered from gastroenteritis the period from 2.5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_8h | Has the child suffered from gastroenteritis (bacterial) the period from 2,5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_8i | Has the child suffered from influenza during the period from 2,5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_14a | Do you think that the child suffers from or is affected by poor growth? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14b | Do you think that the child suffers from or is affected by poor weight gain? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14c | Do you think that the child suffers from or is affected by stomach ache? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14d | Do you think that the child suffers from or is affected by poor appetite? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14e | Do you think that the child suffers from or is affected by a bloated / gassy stomach? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14f | Do you think that the child suffers from or is affected by diarrhea 3 times or more / day? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14g | Do you think that the child suffers from or is affected by vomiting 3 times or more / day? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14h | Do you think that the child suffers from or is affected by constipation? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14i | Do you think that the child suffers from or is affected by fatigue? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14j | Do you think that the child suffers from or is affected by a general irritation? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_14k | Do you think that the child suffers from or is affected by poor sleep quality? (5 year visit) | Five year questionnaire | 1=yes; 2=no; 3=do not know | | e\_23a | Has the child suffered from an accident that required medical care? | Five year questionnaire | 1=yes; 2=no | | e\_28b | Has the child been using antipyretic medication (Paracetamol) during the period from 2.5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_28d | Has the child been using penicillin during the period from 2.5 years of age until now? | Five year questionnaire | 1=never; 2=1-2 times; 3=3-5 times; 4=6 times or more | | e\_45 | In what kind of accommodation did the child live in, most of the time, from 2.5 years of age until now? | Five year questionnaire | 1=detached house; 2=apartment; 3=other | | e\_58a | Mother smoke (5 years follow-up) | Five year questionnaire | 1=yes; 2=no | | e\_58b | If yes, how many cigarettes / day | Five year questionnaire | 1=1-5 cigarettes/day; 2=6-10  cigarettes/day; 3= 10-15  cigarettes/day; 4= 16-20  cigarettes/day; 5= 21-40  cigarettes/day; 6= more than 40 cigarettes/day | | e\_59a | Father smoke (5 years follow-up) | Five year questionnaire | 1=yes; 2=no | | e\_59b | If yes, how many cigarettes / day | Five year questionnaire | 1=1-5 cigarettes/day; 2=6-10  cigarettes/day; 3= 10-15  cigarettes/day; 4= 16-20  cigarettes/day; 5= 21-40  cigarettes/day; 6= more than 40 cigarettes/day | | e\_60a | Has anyone smoked in your home during the last two years? | Five year questionnaire | 1=yes; 2=no | | e\_60b | If yes, how many cigarettes (or corresponding) have adults smoked in your home on average in the last two years (the total number)? | Five year questionnaire | 1=less than 1 cigarette/day; 2=1-5 cigarette/day; 3= 6-10 cigarette/day; 4=11-15 cigarette/day; 5=16-20 cigarette/day; 6=21-40 cigarette/day; 7=41-60 cigarette/day; 8=more than 60 cigarette/day | | | | | | | | | | | | DR4DQ8\_0\_1\_2 | Dosage of HLA Class II allele DR4-DQ8: 0, 1, or 2 |   | 0= no DR4DQ8 alleles; 1= DR4DQ8 heterozygote; 2 = DR4DQ8 homozygote | #### 2- Infant Microbiome Datasets & Files Extraction of DNA from fecal samples collected at one year of age, followed by amplification of the V3-V4 region using 16S rRNA-PCR, was performed. A total of 1,748 samples underwent sequencing in ten pools through Illumina MiSeq 2x300 bp at the Interdisciplinary Center for Biotechnology Research (ICBR) at the University of Florida, Gainesville, Florida, USA. Amplicons for targeted V3-V4 16S rRNA sequencing were generated using standard Illumina Read 1 sequencing/indexing primers: 341F (NNNNCCTACGGGAGGCAGCAG) and 806R (GGGGACTACVSGGGTATCTAAT). Exclusion criteria led to the removal of five samples exhibiting markedly low reads. Sample inference employed the dada function with multithreading, and sequence tables from the ten pools were amalgamated prior to applying the consensus-method chimera removal. Environmental factor analysis considered all ABIS samples, excluding those with low counts (n=1,743). * **2.1- Factors_Data_Dryad.csv** contains factors associated with increased risk or protection from NDs, along with raw counts for the 500 most prevalent amplicon sequence variants (ASVs). These factors were investigated to understand their correlation with microbial taxa at one year of age. The examined factors include experiences such as gastroenteritis, antibiotic treatment, and ear infections during the first year of life, psychosocial vulnerability, maternal smoking during pregnancy, durations of total/exclusive breastfeeding, consumption frequency of chocolate, fries, and chips in the first year, and mode of delivery. All factors underwent dichotomization for subsequent differential analysis. Breastfeeding durations (total/exclusive) were categorized into one to four months versus five or more months, while psychosocial vulnerability was dichotomized into high and low risk based on the total index. | **Variable** | **Description and Labels** | | :----------------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | ASD\_20 | future ASD diagnosis: 0= control with no future ND; 1=yes | | ND\_20 | future ND diagnosis: 0= control with no future ND; 1=yes | | fr\_10 | infectious disease during pregnancy: 1=yes; 2=no; 3=do not know | | fraga12b | birth week, divided into 5 bins: 1=25-30; 2=31-35; 3=36-40; 4=41-42; 5=43 or more weeks | | fr\_12\_week\_4cat | week of delivery: 36= preterm (less than 37); 37=early term (37-38); 39=full term (39-40); 41=late to post term (41+) | | fr\_18 | smoking by the mother during pregnancy: 0=no; 1=yes | | fr\_18b | how often the mother drank coffee during pregnancy: 1=never; 2=seldom (&lt;1 /mnd); 3=sometimes (&gt;1 /mnd); 4=often (2-6 /v); 5=always (every day) | | fr\_20a | whether the mother drank cow's milk during pregnancy: 1=yes; 2=no; 3=do not know | | fr\_20b | whether the mother consumed dairy products, sour milk, yogurt, etc. during pregnancy: 1=yes; 2=no; 3=do not know | | educationma | education of the mother at baseline | | educationpa | education of the father at baseline | | fr\_29 | severe life event during pregnancy: 1=yes; 2=no | | fr\_81 | whether the mother used vitamins or mineral supplement during pregnancy: 1=yes; 2=no; 3=do not know | | fr\_82 | whether the mother used iron tables or supplements during pregnancy: 1=yes; 2=no; 3=do not know | | fr\_94 | how often the mother ate eggs during pregnancy: 1=every day; 2=3-5 times/week; 3= 1-2times/week; 4=more seldom than 1-2 times/week | | fr\_109 | whether the mother had another infection during pregnancy: 1=yes; 2=no; 3=do not know | * **2.2- Sym_Data_Dryad.csv** contains symptom data at 3 and 5 years, as well as the raw counts for the 500 most prevalent ASVs. At the child's three and five years of age, parents involved in the ABIS study provided responses to 11-12 binary-response questions related to growth, mood, and gastrointestinal issues on the questionnaire. They answered the following question: 'Do you think that the child suffers from or is affected by...'. Subsequent symptoms encompassed poor growth, poor weight gain, poor appetite, stomachache, bloated/gassy stomach, diarrhea three times or more per day, vomiting three times or more per day, constipation, fatigue, general irritation, cranky mood/screaming, and poor sleep quality. Presence of these symptoms, as reported by the parent on the ABIS questionnaire, is marked with a “1” in the dataset.  Significant differences in the accompanying manuscript in *Cell* were determined using DESeq2 with FDR correction, on all taxa at the ASV and species level that passed filtering thresholds. Symptoms reflected in the 3-year and 5-year questionnaires are coded as the following. The letters preceding each symptom in the variable name are also used in the symptom clusters, defined in the section below: | Symptoms at 3 years | Symptoms at 5 years | | :------------------ | :------------------ | | a\_growth | a\_growth.5 | | b\_weight | b\_weight.5 | | c\_appetite | c\_stomachache.5 | | d\_stomachache | d\_appetite.5 | | e\_bloated | e\_gassy.5 | | f\_diarrhea | f\_diarrhea.5 | | g\_vomiting | g\_vomiting.5 | | h\_constipation | h\_constipation.5 | | i\_fatigue | i\_fatigue.5 | | j\_irritation | j\_irritation.5 | | k\_cranky | k\_sleep.5 | | l\_sleepquality | | * *Calculated Sums and Cumulative Symptom Variables:* * The sum of the 12 symptoms on the 3-year questionnaire was calculated. Subsequently, the sums of symptoms corresponding to principal components analysis are denoted as [c16_sum_agijkl], [c16_sum_deh], [c_16abc], where each letter corresponds to the symptom on the 3-year questionnaire. * The sum of the 11 symptoms on the 5-year questionnaire was also calculated. Subsequently, the sums of symptoms corresponding to principal components analysis are denoted as [e_14ijk], [e_14abd], [e_14ce], where each letter corresponds to the symptom on the 5-year questionnaire. * Cumulative symptoms were dichotomized as “0” or “1” based on whether the child had any of the symptoms in that symptom cluster. Dichotomization of symptoms clusters in this data file is defined as follows: * Three years of age * c16_sum_1plus: 0= no symptoms reported by the parent at 3 years; 1= one or more symptoms * c16_sum_agijkl_1plus: 0= no symptoms in the agijkl symptom cluster; 1= one or more symptoms in the agijkl symptom cluster * c16_sum_deh_1plus: 0= no symptoms in the deg symptom cluster; 1= one or more symptoms in the deg symptom cluster * c16_sum_abc_1plus: 0= no symptoms in the abc symptom cluster; 1= one or more symptoms in the abc symptom cluster * Five years of age * e_sum_1plus: 0= no symptoms reported by the parent at 5 years; 1= one or more symptoms * e_14ijk_1plus: 0= no symptoms in the ijkl symptom cluster; 1= one or more symptoms in the ijkl symptom cluster * e_14abd_1plus: 0= no symptoms in the abd symptom cluster; 1= one or more symptoms in the abd symptom cluster * e_14ce_1plus: 0= no symptoms in the ce symptom cluster; 1= one or more symptoms in the ce symptom cluster * **2.3- Microbiome_ASD_earlylatediagnosis_Dryad.csv** contains the designations for early and late ASD diagnoses for the 39 ABIS children included in the infant microbiome analysis, along with their biological sex and the relative abundances of the 500 most prevalent ASVs. Differential analysis was conducted separately for males and females due to variations in the average age of diagnosis (13.4 ±4.0 years for males; 17.6 ±2.6 years for females). The distinction between early and late diagnoses was based on the mean age of diagnosis, stratified by biological sex. * **2.4- Microbiome_NDOutcomes_Dryad_short.csv** contains the future neurodevelopment (ND) outcomes (ASD, Intellectual Disability, Speech Disorder, or ADHD) for ABIS children with 16S rRNA data at one year of age, as well as the relative abundances of the 500 most prevalent ASVs. Diagnoses up until Dec 2020 were considered in this manuscript. The sum of future ND diagnoses per child [Sum_ND] is provided, while [NDev] demonstrates whether the child was considered a future case or control. Significant differences in the manuscript were determined using DESeq2 with FDR correction, on all taxa at the ASV and species level that passed filtering thresholds. * **2.5- TopGen_StoolNegativeMode_Dryad.csv** contains the relative abundances of *Bifidobacterium*, *Coprococcus*, *Roseburia*, *Akkermansia*, and *Faecalibacterium* at one year of age. This dataset also includes peak heights derived from untargeted mass spectrometry analysis of fecal samples from individuals with future ASD (n=23) and their matched controls (n=23). In the negative ionization mode, a total of 300 known metabolites were identified. Employing random forest regressors in Python, the top twenty stool metabolites in the negative-ion mode that most effectively predicted the relative abundance of *Bifidobacterium*, *Roseburia*, *Faecalibacterium*, *Akkermansia*, or *Coprococcus* were determined. #### 3- Infant Stool Metabolomics Datasets & Files Untargeted LC-MS metabolomic analysis was conducted on 23 individuals with future ASD diagnosis and 23 controls, matched by propensity score on biological sex and municipality, and with no difference in child age at stool collection. Stool samples underwent cellular extraction and pre-normalization before comprehensive metabolomics profiling at the Southeast Center for Integrated Metabolomics (SECIM) at the University of Florida, Gainesville, FL. A Thermo Q-Exactive Oribtrap mass spectrometer, coupled with Dionex UHPLC and autosampler, was used for both positive and negative heated electrospray ionization, achieving a mass resolution of 35,000 at m/z 200 in separate injections. Metabolomic features were cross-referenced with SECIM's internal retention time metabolite library (containing 1,414 compounds) for identification based on established metabolomic databases. Fatty acids were quantified using LipidMatch. * **3.1, 3.2- NegIonStool_CodeBook_Dryad.csv** and **PosIonStool_CodeBook_Dryad.csv** contain the mass to charge ratio (m/z), retention time, molecular formula, and identification for each stool metabolite identified by the negative and position ionization modes, respectively. * **3.3, 3.4- Untargeted_Negative_Dryad.csv** and **Untargeted_Positive_Dryad.csv** contain the peak heights resulting from untargeted mass spectrometry analysis of future ASD (n=23) and control samples (n=23), representing a total of 300 metabolites identified in the negative ionization mode and 271 in the positive ionization mode. * **3.5- equol_Dryad.csv** contains the peak heights of equol (m/z 241.0866), by future ASD diagnosis [ASD_20]. * **3.6- StoolMetabolites_Fattyacids_Dryad.csv** contains the sum of all peaks [peak_Sum], total moles of 16.1 [moles_16.1], and molar percentages of the 22 fatty acids that were identified, by future ASD outcome [ASD_20]. * **3.7- StoolMetabolites_SCFAs_Dryad.csv** contains the peak heights identified for butyrate and citrate, based on future ASD status [ND]. #### 4- Cord Serum Metabolomics Dataset & Files Cord serum samples were obtained from maternal donations. Samples were analyzed using an ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOFMS from Agilent Technologies; Santa Clara, CA, USA). In this investigation, lipidome and metabolome differences were investigated after controlling for various prenatal risk factors, education of the parents, and gestational age using propensity score matching to select matched controls (n=27) for future ASD cases (n=27). Correlation analysis between * **4.1- Identification_CordBloodMetabolites_Dryad.csv** contains the m/z and retention time for each of the known polar metabolites in cord serum. * **4.2- CordBlood_ProMatch_Metadata_Dryad.csv** contains the maternal factors from the birth questionnaire, upon which samples were propensity-score balanced and selected for differential analysis, along with the peak heights from the 112 known polar metabolites identified in cord serum. The variables included are described below. | Variable | Description and Labels | | :----------------- | :--------------------------------------------------------------------------------------------------------------------------------------------- | | ASD\_20 | future ASD diagnosis: 0= control with no future ND; 1=yes | | ND\_20 | future ND diagnosis: 0= control with no future ND; 1=yes | | fr\_10 | infectious disease during pregnancy: 1=yes; 2=no; 3=do not know | | fraga12b | birth week, divided into 5 bins: 1=25-30; 2=31-35; 3=36-40; 4=41-42; 5=43 or more weeks | | fr\_12\_week\_4cat | week of delivery: 36= preterm (less than 37); 37=early term (37-38); 39=full term (39-40); 41=late to post term (41+) | | fr\_18 | smoking by the mother during pregnancy: 0=no; 1=yes | | fr\_18b | how often the mother drank coffee during pregnancy: 1=never; 2=seldom (&lt;1 /mnd); 3=sometimes (&gt;1 /mnd); 4=often (2-6 /v); 5=always (every day) | | fr\_20a | whether the mother drank cow's milk during pregnancy: 1=yes; 2=no; 3=do not know | | fr\_20b | whether the mother consumed dairy products, sour milk, yogurt, etc. during pregnancy: 1=yes; 2=no; 3=do not know | | educationma | education of the mother at baseline | | educationpa | education of the father at baseline | | fr\_29 | severe life event during pregnancy: 1=yes; 2=no | | fr\_81 | whether the mother used vitamins or mineral supplement during pregnancy: 1=yes; 2=no; 3=do not know | | fr\_82 | whether the mother used iron tables or supplements during pregnancy: 1=yes; 2=no; 3=do not know | | fr\_94 | how often the mother ate eggs during pregnancy: 1=every day; 2=3-5 times/week; 3= 1-2times/week; 4=more seldom than 1-2 times/week | | fr\_109 | whether the mother had another infection during pregnancy: 1=yes; 2=no; 3=do not know | * **4.3- CordBlood_Microbiome_Dryad.csv** contains the relative abundances of 13 microbial species and seven ASVs that were consistently associated with NDs in our investigation, along with seven polar cord serum metabolites and 16 lipids of interest due to the identified association with NDs in the ABIS material. Correlation analysis between the relative abundances and these selected features in the cord serum metabolome and lipidome were carried out. ## Sharing/Access information Any additional information required to reanalyze the data reported in our paper is available from the lead contact upon request and an appropriate institutional collaboration agreement. Indirect identifiers were kept at 3 maximum within each dataset to satisfy Dryad human subjects data requirements.