Advanced glycation endproducts, dityrosine and arginine transporter dysfunction in autism - a source of biomarkers for clinical diagnosis

Abstract

Background: Clinical chemistry tests for autism spectrum disorder (ASD) are currently unavailable. The aim of this study was to explore the diagnostic utility of proteotoxic biomarkers in plasma and urine, plasma protein glycation, oxidation, and nitration adducts, and related glycated, oxidized, and nitrated amino acids (free adducts), for the clinical diagnosis of ASD.

Methods: Thirty-eight children with ASD (29 male, 9 female; age 7.6 ± 2.0 years) and 31 age-matched healthy controls (23 males, 8 females; 8.6 ± 2.0 years) were recruited for this study. Plasma protein glycation, oxidation, and nitration adducts and amino acid metabolome in plasma and urine were determined by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry. Machine learning methods were then employed to explore and optimize combinations of analyte data for ASD diagnosis.

Results: We found that children with ASD had increased advanced glycation endproducts (AGEs), N_ε-carboxymethyl-lysine (CML) and N_ω-carboxymethylarginine (CMA), and increased oxidation damage marker, dityrosine (DT), in plasma protein, with respect to healthy controls. We also found that children with ASD had increased CMA free adduct in plasma ultrafiltrate and increased urinary excretion of oxidation free adducts, alpha-aminoadipic semialdehyde and glutamic semialdehyde. From study of renal handling of amino acids, we found that children with ASD had decreased renal clearance of arginine and CMA with respect to healthy controls. Algorithms to discriminate between ASD and healthy controls gave strong diagnostic performance with features: plasma protein AGEs-CML, CMA-and 3-deoxyglucosone-derived hydroimidazolone, and oxidative damage marker, DT. The sensitivity, specificity, and receiver operating characteristic area-under-the-curve were 92%, 84%, and 0.94, respectively.

Conclusions: Changes in plasma AGEs were likely indicative of dysfunctional metabolism of dicarbonyl metabolite precursors of AGEs, glyoxal and 3-deoxyglucosone. DT is formed enzymatically by dual oxidase (DUOX); selective increase of DT as an oxidative damage marker implicates increased DUOX activity in ASD possibly linked to impaired gut mucosal immunity. Decreased renal clearance of arginine and CMA in ASD is indicative of increased arginine transporter activity which may be a surrogate marker of disturbance of neuronal availability of amino acids. Data driven combination of these biomarkers perturbed by proteotoxic stress, plasma protein AGEs and DT, gave diagnostic algorithms of high sensitivity and specificity for ASD.

Keywords: Advanced glycation endproducts (AGEs); Amino acid metabolome; Autism spectrum disorder (ASD); Machine learning; Oxidative stress.

Fig. 1

Protein glycation, oxidation, and nitration free adducts. Ionization status at physiological pH is shown. For related adduct residues of proteins, alpha-amino-NH₃⁺ and terminal carboxylate –CO₂⁻ groups are moieties of as peptide bonds –NH–CO– with amino acid residues immediately before and after in the peptide backbone

Fig. 2

Training and validation subject groups of diagnostic algorithms for detection of autistic spectrum disorder

Fig. 3

Heat map of changes in glycated, oxidized, and nitrated proteins and amino acids in plasma and urine of subjects with autistic spectrum disorder. a Trace level protein glycation, oxidation, and nitration adducts. b Amino acid metabolome. Key: CTRL control, PP plasma protein (adduct residues), PF plasma filtrate (free adducts), and UF urine filtrate (free adducts). Data are given in Tables 2, 3, 4, and 5

Fig. 4

Scatter plots for protein damage biomarker variables changed in children with ASD. Protein adduct residues: a CML, b CMA, and c DT. Plasma free adduct: d CMA. Urine free adduct and amino acids: e DT, f GSA, g Asn, h Pro, i Ser, and j Val. Renal clearance: k CMA and l Arg (an outlier point, 0.0565, was excluded from the ASD data). Significance: One asterisk, two asterisks, and three asterisks indicate P < 0.05, P < 0.01, and P < 0.001, respectively

Fig. 5

Receiver operating characteristic plots of diagnostic algorithms for detection of autistic spectrum disorder by protein glycation and oxidation adducts. a Algorithm-1, plasma protein adduct residues. AUROC = 0.96. b Algorithm-2, plasma free adducts. AUROC = 0.78. c Algorithm-3, plasma protein adduct residues and free adducts. AUROC = 0.99. d Algorithm-4, urine free adducts. AUROC = 0.78. ROC plots are representative results from one run of the classification experiment. A random outcome is AUROC = 0.50

Fig. 6

Schematic explanation for changes found in protein damage and amino acids in ASD. a Proposed mechanism for observed changes found in plasma protein glycation and oxidation adducts. b Transport of arg and CMA across the renal tubular epithelium and proposed mechanism for increased renal CL (increased arg and CMA reuptake). Key: yellow-filled arrows show processes; black-filled arrows show changes observed (a) and changes expected (b) in ASD