Additional file 1 of Unraveling the metabolomic architecture of autism in a large Danish population-based cohort
Creators: name: Ottosson, Filip
name: Russo, Francesco
name: Abrahamsson, Anna
name: MacSween, Nadia
name: Courraud, Julie
name: Skogstrand, Kristin
name: Melander, Olle
name: Ericson, Ulrika
name: Orho-Melander, Marju
name: Cohen, Arieh S.
name: Grove, Jakob
name: Mortensen, Preben Bo
name: Hougaard, David M.
name: Ernst, Madeleine
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Neuroscience
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Mental Health
subject: Computational Biology

description: Additional file 1: Figure S1. Mirror plot showing the cyclo(leucine-proline) fragmentation spectrum acquired in the neonatal cohort and corresponding library match. Mirror plot generated using the Metabolomics Spectrum Resolver. Figure S2. Mirror plot showing the 5-aminovaleric acid betaine fragmentation spectrum acquired in the neonatal cohort and corresponding library match. Mirror plot generated using the Metabolomics Spectrum Resolver. Figure S3. Associations between neonatal metabolites and genetic risk score for autism. Associations were evaluated using linear regression models adjusted for major factors causing variation in the neonatal dried blood spot metabolome, including gestational age, age at sampling, season and year of birth. Nominally significant associations were defined as P &lt; 0.05, and significant associations as FDR-adjusted p &lt; 0.05. Figure S4. Associations between neonatal metabolite levels and family history of psychiatric disorders. Nominally significant associations were defined as P &lt; 0.05, and significant associations as FDR-adjusted P &lt; 0.05. Figure S5. Mirror plot showing the m/z 160.13 fragmentation spectrum acquired in the Malmö Offspring Study and corresponding library match to 5-AVAB (cosine = 0.81, 4 matching fragments, mass difference &lt; 0.01). Figure S6. Partial Pearson’s correlation coefficients between carnitine-related metabolites in the Malmö Diet and Cancer Study (N = 3833). Figure S7. Partial Pearson’s correlation coefficients between carnitine-related metabolites in the Malmö Offspring Study (N = 3430). Figure S8. Associations between single nucleotide polymorphisms (SNP) located near SLC22A5 and 5-amino valeric acid betaine. Analysis is done in male participants in the Malmö Diet and Cancer Study (N = 1382). Figure S9. Associations between single nucleotide polymorphisms (SNP) located near SLC22A5 and 5-amino valeric acid betaine. Analysis is done in female participants in the Malmö Diet and Cancer Study (N = 2026). Figure S10. Phenome-wide scan for 5-amino valeric acid betaine (5-AVAB). Analysis performed in the Malmö Diet and Cancer Study (N = 3077). (A) Correlation between 5-AVAB and predicted 5-AVAB. 5-AVAB prediction was performed using LASSO regression. R2 indicates the model's explained variance of 5-AVAB. (B) Top 30 variables in prediction of 5-AVAB. LASSO coefficients indicate contribution to the model. Figure S11. Associations between single nucleotide polymorphisms (SNPs) and blood levels of 5-amino valeric acid betaine (5-AVAB) in the Neonatal cohort (N = 1239). The Manhattan plot of the genome-wide association study shows genome-wide significance threshold is indicated at p &lt; 5.0e-8. Figure S12. Associations between single nucleotide polymorphisms (SNPs) and blood levels of cyclo-Leucine-Proline (cLP) in the Neonatal cohort (N = 1239). The Manhattan plot of the genome-wide association study shows genome-wide significance threshold is indicated at p &lt; 5.0e-8. Figure S13. Relative standard deviation (RSD) for metabolite features (N = 281) measured in all external control samples