A Subset of Patients With Autism Spectrum Disorders Show a Distinctive Metabolic Profile by Dried Blood Spot Analyses

Unraveling the metabolomic architecture of autism in a large Danish population-based cohort

BACKGROUND

The prevalence of autism in Denmark has been increasing, reaching 1.65% among 10-year-old children, and similar trends are seen elsewhere. Although there are several factors associated with autism, including genetic, environmental, and prenatal factors, the molecular etiology of autism is largely unknown. Here, we use untargeted metabolomics to characterize the neonatal metabolome from dried blood spots collected shortly after birth.

METHODS

We analyze the metabolomic profiles of a subset of a large Danish population-based cohort (iPSYCH2015) consisting of over 1400 newborns, who later are diagnosed with autism and matching controls and in two Swedish population-based cohorts comprising over 7000 adult participants. Mass spectrometry analysis was performed by a timsTOF Pro operated in QTOF mode, using data-dependent acquisition. By applying an untargeted metabolomics approach, we could reproducibly measure over 800 metabolite features.

RESULTS

We detected underlying molecular perturbations across several metabolite classes that precede autism. In particular, the cyclic dipeptide cyclo-leucine-proline (FDR-adjusted p = 0.003) and the carnitine-related 5-aminovaleric acid betaine (5-AVAB) (FDR-adjusted p = 0.03), were associated with an increased probability for autism, independently of known prenatal and genetic risk factors. Analysis of genetic and dietary data in adults revealed that 5-AVAB was associated with increased habitual dietary intake of dairy (FDR-adjusted p < 0.05) and with variants near SLC22A4 and SLC22A5 (p < 5.0e - 8), coding for a transmembrane carnitine transporter protein involved in controlling intracellular carnitine levels.

CONCLUSIONS

Cyclo-leucine-proline and 5-AVAB are associated with future diagnosis of autism in Danish neonates, both representing novel early biomarkers for autism. 5-AVAB is potentially modifiable and may influence carnitine homeostasis.

Biomarkers of mitochondrial dysfunction in autism spectrum disorder: A systematic review and meta-analysis

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting 1 in 36 children and is associated with physiological abnormalities, most notably mitochondrial dysfunction, at least in a subset of individuals. This systematic review and meta-analysis discovered 204 relevant articles which evaluated biomarkers of mitochondrial dysfunction in ASD individuals. Significant elevations (all p < 0.01) in the prevalence of lactate (17%), pyruvate (41%), alanine (15%) and creatine kinase (9%) were found in ASD. Individuals with ASD had significant differences (all p < 0.01) with moderate to large effect sizes (Cohen's d' ≥ 0.6) compared to controls in mean pyruvate, lactate-to-pyruvate ratio, ATP, and creatine kinase. Some studies found abnormal TCA cycle metabolites associated with ASD. Thirteen controlled studies reported mitochondrial DNA (mtDNA) deletions or variations in the ASD group in blood, peripheral blood mononuclear cells, lymphocytes, leucocytes, granulocytes, and brain. Meta-analyses discovered significant differences (p < 0.01) in copy number of mtDNA overall and in ND1, ND4 and CytB genes. Four studies linked specific mtDNA haplogroups to ASD. A series of studies found a subgroup of ASD with elevated mitochondrial respiration which was associated with increased sensitivity of the mitochondria to physiological stressors and neurodevelopmental regression. Lactate, pyruvate, lactate-to-pyruvate ratio, carnitine, and acyl-carnitines were associated with clinical features such as delays in language, social interaction, cognition, motor skills, and with repetitive behaviors and gastrointestinal symptoms, although not all studies found an association. Lactate, carnitine, acyl-carnitines, ATP, CoQ10, as well as mtDNA variants, heteroplasmy, haplogroups and copy number were associated with ASD severity. Variability was found across biomarker studies primarily due to differences in collection and processing techniques as well as the intrinsic heterogeneity of the ASD population. Several studies reported alterations in mitochondrial metabolism in mothers of children with ASD and in neonates who develop ASD. Treatments targeting mitochondria, particularly carnitine and ubiquinol, appear beneficial in ASD. The link between mitochondrial dysfunction in ASD and common physiological abnormalities in individuals with ASD including gastrointestinal disorders, oxidative stress, and immune dysfunction is outlined. Several subtypes of mitochondrial dysfunction in ASD are discussed, including one related to neurodevelopmental regression, another related to alterations in microbiome metabolites, and another related to elevations in acyl-carnitines. Mechanisms linking abnormal mitochondrial function with alterations in prenatal brain development and postnatal brain function are outlined. Given the multisystem complexity of some individuals with ASD, this review presents evidence for the mitochondria being central to ASD by contributing to abnormalities in brain development, cognition, and comorbidities such as immune and gastrointestinal dysfunction as well as neurodevelopmental regression. A diagnostic approach to identify mitochondrial dysfunction in ASD is outlined. From this evidence, it is clear that many individuals with ASD have alterations in mitochondrial function which may need to be addressed in order to achieve optimal clinical outcomes. The fact that alterations in mitochondrial metabolism may be found during pregnancy and early in the life of individuals who eventually develop ASD provides promise for early life predictive biomarkers of ASD. Further studies may improve the understanding of the role of the mitochondria in ASD by better defining subgroups and understanding the molecular mechanisms driving some of the unique changes found in mitochondrial function in those with ASD.

Human-derived fecal microbiota transplantation alleviates social deficits of the BTBR mouse model of autism through a potential mechanism involving vitamin B6 metabolism

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by social communication deficiencies and stereotypic behaviors influenced by hereditary and/or environmental risk factors. There are currently no approved medications for treating the core symptoms of ASD. Human fecal microbiota transplantation (FMT) has emerged as a potential intervention to improve autistic symptoms, but the underlying mechanisms are not fully understood. In this study, we evaluated the effects of human-derived FMT on behavioral and multi-omics profiles of the BTBR mice, an established model for ASD. FMT effectively alleviated the social deficits in the BTBR mice and normalized their distinct plasma metabolic profile, notably reducing the elevated long-chain acylcarnitines. Integrative analysis linked these phenotypic changes to specific Bacteroides species and vitamin B6 metabolism. Indeed, vitamin B6 supplementation improved the social behaviors in BTBR mice. Collectively, these findings shed new light on the interplay between FMT and vitamin B6 metabolism and revealed a potential mechanism underlying the therapeutic role of FMT in ASD.IMPORTANCEAccumulating evidence supports the beneficial effects of human fecal microbiota transplantation (FMT) on symptoms associated with autism spectrum disorder (ASD). However, the precise mechanism by which FMT induces a shift in the microbiota and leads to symptom improvement remains incompletely understood. This study integrated data from colon-content metagenomics, colon-content metabolomics, and plasma metabolomics to investigate the effects of FMT treatment on the BTBR mouse model for ASD. The analysis linked the amelioration of social deficits following FMT treatment to the restoration of mitochondrial function and the modulation of vitamin B6 metabolism. Bacterial species and compounds with beneficial roles in vitamin B6 metabolism and mitochondrial function may further contribute to improving FMT products and designing novel therapies for ASD treatment.

Spatial Heterogeneity of Brain Lipids in SIV-Infected Macaques Treated with Antiretroviral Therapy

Human immunodeficiency virus (HIV) infection continues to promote neurocognitive impairment, mood disorders, and brain atrophy, even in the modern era of viral suppression. Brain lipids are vulnerable to HIV-associated energetic strain and may contribute to HIV-associated neurologic dysfunction due to alterations in lipid breakdown and structural lipid composition. HIV neuropathology is region dependent, yet there has not been comprehensive characterization of the spatial heterogeneity of brain lipids during infection that possibly impacts neurologic function. To address this gap, we evaluated the spatial lipid distribution using matrix laser desorption/ionization imaging mass spectrometry (MALDI-IMS) across four brain regions (parietal cortex, midbrain, thalamus, and temporal cortex), as well as the kidney for a peripheral tissue control, in a simian immunodeficiency virus (SIV)-infected rhesus macaque treated with a course of antiretroviral therapies (ARTs). We assessed lipids indicative of fat breakdown [acylcarnitines (CARs)] and critical structural lipids [phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs)] across fatty acid chain lengths and degrees of unsaturation. CARs with very long-chain, polyunsaturated fatty acids (PUFAs) were more abundant across all brain regions than shorter chain, saturated, or monounsaturated species. We observed distinct brain lipid distribution patterns for the CARs and PCs. However, no clear expression patterns emerged for PEs. Surprisingly, the kidney was nearly devoid of ions corresponding to PUFAs common in brain. PEs and PCs with PUFAs had little intensity and less density than other species, and only one CAR species was observed in kidney at high intensity. Overall, our study demonstrates the stark variation in structural phospholipids and lipid-energetic intermediates present in the virally suppressed SIV-macaque brain. These findings may be useful for identifying regional vulnerabilities to damage due to brain lipid changes in people with HIV.

Cord blood lipid correlation network profiles are associated with subsequent attention-deficit/hyperactivity disorder and autism spectrum disorder symptoms at 2 years: a prospective birth cohort study

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental conditions with early life origins. Alterations in blood lipids have been linked to ADHD and ASD; however, prospective early life data are limited. This study examined (i) associations between the cord blood lipidome and ADHD/ASD symptoms at 2 years of age, (ii) associations between prenatal and perinatal predictors of ADHD/ASD symptoms and cord blood lipidome, and (iii) mediation by the cord blood lipidome.

METHODS

From the Barwon Infant Study cohort (1074 mother-child pairs, 52.3% male children), child circulating lipid levels at birth were analysed using ultra-high-performance liquid chromatography-tandem mass spectrometry. These were clustered into lipid network modules via Weighted Gene Correlation Network Analysis. Associations between lipid modules and ADHD/ASD symptoms at 2 years, assessed with the Child Behavior Checklist, were explored via linear regression analyses. Mediation analysis identified indirect effects of prenatal and perinatal risk factors on ADHD/ASD symptoms through lipid modules.

FINDINGS

The acylcarnitine lipid module is associated with both ADHD and ASD symptoms at 2 years of age. Risk factors of these outcomes such as low income, Apgar score, and maternal inflammation were partly mediated by higher birth acylcarnitine levels. Other cord blood lipid profiles were also associated with ADHD and ASD symptoms.

INTERPRETATION

This study highlights that elevated cord blood birth acylcarnitine levels, either directly or as a possible marker of disrupted cell energy metabolism, are on the causal pathway of prenatal and perinatal risk factors for ADHD and ASD symptoms in early life.

FUNDING

The foundational work and infrastructure for the BIS was sponsored by the Murdoch Children's Research Institute, Deakin University, and Barwon Health. Subsequent funding was secured from the Minderoo Foundation, the European Union's Horizon 2020 research and innovation programme (ENDpoiNTs: No 825759), National Health and Medical Research Council of Australia (NHMRC) and Agency for Science, Technology and Research Singapore [APP1149047], The William and Vera Ellen Houston Memorial Trust Fund (via HOMER Hack), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O'Brien Memorial Asthma Foundation, the Our Women Our Children's Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Ilhan Food Allergy Foundation, Geelong Medical and Hospital Benefits Association, Vanguard Investments Australia Ltd, the Percy Baxter Charitable Trust, and Perpetual Trustees.

Metabolic and proteostatic differences in quiescent and active neural stem cells

Adult neural stem cells are neurogenesis progenitor cells that play an important role in neurogenesis. Therefore, neural regeneration may be a promising target for treatment of many neurological illnesses. The regenerative capacity of adult neural stem cells can be characterized by two states: quiescent and active. Quiescent adult neural stem cells are more stable and guarantee the quantity and quality of the adult neural stem cell pool. Active adult neural stem cells are characterized by rapid proliferation and differentiation into neurons which allow for integration into neural circuits. This review focuses on differences between quiescent and active adult neural stem cells in nutrition metabolism and protein homeostasis. Furthermore, we discuss the physiological significance and underlying advantages of these differences. Due to the limited number of adult neural stem cells studies, we referred to studies of embryonic adult neural stem cells or non-mammalian adult neural stem cells to evaluate specific mechanisms.

Cord Blood Metabolite Profiles and Their Association with Autistic Traits in Childhood

Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental condition. Gene-environmental interactions in early stages of life might alter metabolic pathways, possibly contributing to ASD pathophysiology. Metabolomics may serve as a tool to identify underlying metabolic mechanisms contributing to ASD phenotype and could help to unravel its complex etiology. In a population-based, prospective cohort study among 783 mother-child pairs, cord blood serum concentrations of amino acids, non-esterified fatty acids, phospholipids, and carnitines were obtained using liquid chromatography coupled with tandem mass spectrometry. Autistic traits were measured at the children's ages of 6 (n = 716) and 13 (n = 648) years using the parent-reported Social Responsiveness Scale. Lower cord blood concentrations of SM.C.39.2 and NEFA16:1/16:0 were associated with higher autistic traits among 6-year-old children, adjusted for sex and age at outcome. After more stringent adjustment for confounders, no significant associations of cord blood metabolites and autistic traits at ages 6 and 13 were detected. Differences in lipid metabolism (SM and NEFA) might be involved in ASD-related pathways and are worth further investigation.

Altered markers of mitochondrial function in adults with autism spectrum disorder

Previous research suggests potential mitochondrial dysfunction and changes in fatty acid metabolism in a subgroup of individuals with autism spectrum disorder (ASD), indicated by higher lactate, pyruvate levels, and mitochondrial disorder prevalence. This study aimed to further investigate potential mitochondrial dysfunction in ASD by assessing blood metabolite levels linked to mitochondrial metabolism. Blood levels of creatine kinase (CK), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate, pyruvate, free and total carnitine, as well as acylcarnitines were obtained in 73 adults with ASD (47 males, 26 females) and compared with those of 71 neurotypical controls (NTC) (44 males, 27 females). Correlations between blood parameters and psychometric ASD symptom scores were also explored. Lower CK (pcorr  = 0.045) levels were found exclusively in males with ASD compared to NTC, with no such variation in females. ALT and AST levels did not differ significantly between both groups. After correction for antipsychotic and antidepressant medication, CK remained significant. ASD participants had lower serum lactate levels (pcorr  = 0.036) compared to NTC, but pyruvate and carnitine concentrations showed no significant difference. ASD subjects had significantly increased levels of certain acylcarnitines, with a decrease in tetradecadienoyl-carnitine (C14:2), and certain acylcarnitines correlated significantly with autistic symptom scores. We found reduced serum lactate levels in ASD, in contrast to previous studies suggesting elevated lactate or pyruvate. This difference may reflect the focus of our study on high-functioning adults with ASD, who are likely to have fewer secondary genetic conditions associated with mitochondrial dysfunction. Our findings of significantly altered acylcarnitine levels in ASD support the hypothesis of altered fatty acid metabolism in a subset of ASD patients.

Metabolomic biomarkers in autism: identification of complex dysregulations of cellular bioenergetics

Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case-control study of 499 autistic and 209 typically developing (TYP) children, ages 18-48 months, enrolled in the Children's Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5-11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants' biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.

The Role of Acyl-CoA β-Oxidation in Brain Metabolism and Neurodegenerative Diseases

This review highlights the complex role of fatty acid β-oxidation in brain metabolism. It demonstrates the fundamental importance of fatty acid degradation as a fuel in energy balance and as an essential component in lipid homeostasis, brain aging, and neurodegenerative disorders.

Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder

Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.

Topic modeling for multi-omic integration in the human gut microbiome and implications for Autism

While healthy gut microbiomes are critical to human health, pertinent microbial processes remain largely undefined, partially due to differential bias among profiling techniques. By simultaneously integrating multiple profiling methods, multi-omic analysis can define generalizable microbial processes, and is especially useful in understanding complex conditions such as Autism. Challenges with integrating heterogeneous data produced by multiple profiling methods can be overcome using Latent Dirichlet Allocation (LDA), a promising natural language processing technique that identifies topics in heterogeneous documents. In this study, we apply LDA to multi-omic microbial data (16S rRNA amplicon, shotgun metagenomic, shotgun metatranscriptomic, and untargeted metabolomic profiling) from the stool of 81 children with and without Autism. We identify topics, or microbial processes, that summarize complex phenomena occurring within gut microbial communities. We then subset stool samples by topic distribution, and identify metabolites, specifically neurotransmitter precursors and fatty acid derivatives, that differ significantly between children with and without Autism. We identify clusters of topics, deemed "cross-omic topics", which we hypothesize are representative of generalizable microbial processes observable regardless of profiling method. Interpreting topics, we find each represents a particular diet, and we heuristically label each cross-omic topic as: healthy/general function, age-associated function, transcriptional regulation, and opportunistic pathogenesis.

Metabolomic analysis of maternal mid-gestation plasma and cord blood in autism spectrum disorders

The discovery of prenatal and neonatal molecular biomarkers has the potential to yield insights into autism spectrum disorder (ASD) and facilitate early diagnosis. We characterized metabolomic profiles in ASD using plasma samples collected in the Norwegian Autism Birth Cohort from mothers at weeks 17-21 gestation (maternal mid-gestation, MMG, n = 408) and from children on the day of birth (cord blood, CB, n = 418). We analyzed associations using sex-stratified adjusted logistic regression models with Bayesian analyses. Chemical enrichment analyses (ChemRICH) were performed to determine altered chemical clusters. We also employed machine learning algorithms to assess the utility of metabolomics as ASD biomarkers. We identified ASD associations with a variety of chemical compounds including arachidonic acid, glutamate, and glutamine, and metabolite clusters including hydroxy eicospentaenoic acids, phosphatidylcholines, and ceramides in MMG and CB plasma that are consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission and neurotoxicity. Girls with ASD have disruption of ether/non-ether phospholipid balance in the MMG plasma that is similar to that found in other neurodevelopmental disorders. ASD boys in the CB analyses had the highest number of dysregulated chemical clusters. Machine learning classifiers distinguished ASD cases from controls with area under the receiver operating characteristic (AUROC) values ranging from 0.710 to 0.853. Predictive performance was better in CB analyses than in MMG. These findings may provide new insights into the sex-specific differences in ASD and have implications for discovery of biomarkers that may enable early detection and intervention.

Intestinal Barrier Dysfunction and Microbiota–Gut–Brain Axis: Possible Implications in the Pathogenesis and Treatment of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with multifactorial etiology, characterized by impairment in two main functional areas: (1) communication and social interactions, and (2) skills, interests and activities. ASD patients often suffer from gastrointestinal symptoms associated with dysbiotic states and a “leaky gut.” A key role in the pathogenesis of ASD has been attributed to the gut microbiota, as it influences central nervous system development and neuropsychological and gastrointestinal homeostasis through the microbiota–gut–brain axis. A state of dysbiosis with a reduction in the Bacteroidetes/Firmicutes ratio and Bacteroidetes level and other imbalances is common in ASD. In recent decades, many authors have tried to study and identify the microbial signature of ASD through in vivo and ex vivo studies. In this regard, the advent of metabolomics has also been of great help. Based on these data, several therapeutic strategies, primarily the use of probiotics, are investigated to improve the symptoms of ASD through the modulation of the microbiota. However, although the results are promising, the heterogeneity of the studies precludes concrete evidence. The aim of this review is to explore the role of intestinal barrier dysfunction, the gut–brain axis and microbiota alterations in ASD and the possible role of probiotic supplementation in these patients.

Neuroactive Amino Acid Profile in Autism Spectrum Disorder: Results from a Clinical Sample

Biological bases of autism spectrum disorder (ASD) include both genetic and epigenetic causes. Patients with ASD show anomalies in the profile of certain plasma amino acids, including neuroactive amino acids. Monitoring plasma amino acids may be relevant for patient care and interventions. We evaluated the plasma amino acid profile in samples extracted from dry blood spots by electrospray ionization-tandem mass spectrometry. Fourteen amino acids and eleven amino acid ratios were examined in patients with ASD and intellectual disability (ID), and neurotypical control subjects (TD). The amino acid profile in the ASD group showed reduced levels of ornithine (p = 0.008), phenylalanine (p = 0.042) and tyrosine (p = 0.013). The statistically significant amino acid ratios were Leu+Val/Phe+Tyr (p = 0.002), Tyr/Leu (p = 0.007) and Val/Phe (p = 0.028), such differences remaining significant only in the comparison between ASD and TD. Finally, a positive correlation emerged between the score of the restricted and repetitive behavior on ADOS-2 and the citrulline levels in the ASD group (p = 0.0047). To conclude, patients with ASD may show a distinguishable metabolic profile useful for studying their metabolic pathways in order to develop screening tests and targeted therapies.

Metabolomic Signatures of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is associated with many variations in metabolism, but the ex-act correlates of these metabolic disturbances with behavior and development and their links to other core metabolic disruptions are understudied. In this study, large-scale targeted LC-MS/MS metabolomic analysis was conducted on fasting morning plasma samples from 57 children with ASD (29 with neurodevelopmental regression, NDR) and 37 healthy controls of similar age and gender. Linear model determined the metabolic signatures of ASD with and without NDR, measures of behavior and neurodevelopment, as well as markers of oxidative stress, inflammation, redox, methylation, and mitochondrial metabolism. MetaboAnalyst ver 5.0 (the Wishart Research Group at the University of Alberta, Edmonton, Canada) identified the pathways associated with altered metabolic signatures. Differences in histidine and glutathione metabolism as well as aromatic amino acid (AAA) biosynthesis differentiated ASD from controls. NDR was associated with disruption in nicotinamide and energy metabolism. Sleep and neurodevelopment were associated with energy metabolism while neurodevelopment was also associated with purine metabolism and aminoacyl-tRNA biosynthesis. While behavior was as-sociated with some of the same pathways as neurodevelopment, it was also associated with alternations in neurotransmitter metabolism. Alterations in methylation was associated with aminoacyl-tRNA biosynthesis and branched chain amino acid (BCAA) and nicotinamide metabolism. Alterations in glutathione metabolism was associated with changes in glycine, serine and threonine, BCAA and AAA metabolism. Markers of oxidative stress and inflammation were as-sociated with energy metabolism and aminoacyl-tRNA biosynthesis. Alterations in mitochondrial metabolism was associated with alterations in energy metabolism and L-glutamine. Using behavioral and biochemical markers, this study finds convergent disturbances in specific metabolic pathways with ASD, particularly changes in energy, nicotinamide, neurotransmitters, and BCAA, as well as aminoacyl-tRNA biosynthesis.

Multivariate Analysis of Metabolomic and Nutritional Profiles among Children with Autism Spectrum Disorder

There have been promising results regarding the capability of statistical and machine-learning techniques to offer insight into unique metabolomic patterns observed in ASD. This work re-examines a comparative study contrasting metabolomic and nutrient measurements of children with ASD (n = 55) against their typically developing (TD) peers (n = 44) through a multivariate statistical lens. Hypothesis testing, receiver characteristic curve assessment, and correlation analysis were consistent with prior work and served to underscore prominent areas where metabolomic and nutritional profiles between the groups diverged. Improved univariate analysis revealed 46 nutritional/metabolic differences that were significantly different between ASD and TD groups, with individual areas under the receiver operator curve (AUROC) scores of 0.6–0.9. Many of the significant measurements had correlations with many others, forming two integrated networks of interrelated metabolic differences in ASD. The TD group had 189 significant correlation pairs between metabolites, vs. only 106 for the ASD group, calling attention to underlying differences in metabolic processes. Furthermore, multivariate techniques identified potential biomarker panels with up to six metabolites that were able to attain a predictive accuracy of up to 98% for discriminating between ASD and TD, following cross-validation. Assessing all optimized multivariate models demonstrated concordance with prior physiological pathways identified in the literature, with some of the most important metabolites for discriminating ASD and TD being sulfate, the transsulfuration pathway, uridine (methylation biomarker), and beta-amino isobutyrate (regulator of carbohydrate and lipid metabolism).

Central Nervous System Metabolism in Autism, Epilepsy and Developmental Delays: A Cerebrospinal Fluid Analysis

Neurodevelopmental disorders are associated with metabolic pathway imbalances; however, most metabolic measurements are made peripherally, leaving central metabolic disturbances under-investigated. Cerebrospinal fluid obtained intraoperatively from children with autism spectrum disorder (ASD, n = 34), developmental delays (DD, n = 20), and those without known DD/ASD (n = 34) was analyzed using large-scale targeted mass spectrometry. Eighteen also had epilepsy (EPI). Metabolites significantly related to ASD, DD and EPI were identified by linear models and entered into metabolite–metabolite network pathway analysis. Common disrupted pathways were analyzed for each group of interest. Central metabolites most involved in metabolic pathways were L-cysteine, adenine, and dodecanoic acid for ASD; nicotinamide adenine dinucleotide phosphate, L-aspartic acid, and glycine for EPI; and adenosine triphosphate, L-glutamine, ornithine, L-arginine, L-lysine, citrulline, and L-homoserine for DD. Amino acid and energy metabolism pathways were most disrupted in all disorders, but the source of the disruption was different for each disorder. Disruption in vitamin and one-carbon metabolism was associated with DD and EPI, lipid pathway disruption was associated with EPI and redox metabolism disruption was related to ASD. Two microbiome metabolites were also detected in the CSF: shikimic and cis-cis-muconic acid. Overall, this study provides increased insight into unique metabolic disruptions in distinct but overlapping neurodevelopmental disorders.

Studying Autism Using Untargeted Metabolomics in Newborn Screening Samples

Main risk factors of autism spectrum disorder (ASD) include both genetic and non-genetic factors, especially prenatal and perinatal events. Newborn screening dried blood spot (DBS) samples have great potential for the study of early biochemical markers of disease. To study DBS strengths and limitations in the context of ASD research, we analyzed the metabolomic profiles of newborns later diagnosed with ASD. We performed LC-MS/MS-based untargeted metabolomics on DBS from 37 case-control pairs randomly selected from the iPSYCH sample. After preprocessing using MZmine 2.41, metabolites were putatively annotated using mzCloud, GNPS feature-based molecular networking, and MolNetEnhancer. A total of 4360 mass spectral features were detected, of which 150 (113 unique) could be putatively annotated at a high confidence level. Chemical structure information at a broad level could be retrieved for 1009 metabolites, covering 31 chemical classes. Although no clear distinction between cases and controls was revealed, our method covered many metabolites previously associated with ASD, suggesting that biochemical markers of ASD are present at birth and may be monitored during newborn screening. Additionally, we observed that gestational age, age at sampling, and month of birth influence the metabolomic profiles of newborn DBS, which informs us on the important confounders to address in future studies.

The role of ethanolamine phosphate phospholyase in regulation of astrocyte lipid homeostasis

Dietary lipid composition has been shown to impact brain morphology, brain development, and neurologic function. However, how diet uniquely regulates brain lipid homeostasis compared with lipid homeostasis in peripheral tissues remains largely uncharacterized. To evaluate the lipid response to dietary changes in the brain, we assessed actively translating mRNAs in astrocytes and neurons across multiple diets. From this data, ethanolamine phosphate phospholyase (Etnppl) was identified as an astrocyte-specific fasting-induced gene. Etnppl catabolizes phosphoethanolamine (PEtN), a prominent headgroup precursor in phosphatidylethanolamine (PE) also found in other classes of neurologically relevant lipid species. Altered Etnppl expression has also previously been associated with humans with mood disorders. We evaluated the relevance of Etnppl in maintaining brain lipid homeostasis by characterizing Etnppl across development and in coregulation with PEtN-relevant genes, as well as determining the impact to the brain lipidome after Etnppl loss. We found that Etnppl expression dramatically increased during a critical window of early brain development in mice and was also induced by glucocorticoids. Using a constitutive knockout of Etnppl (EtnpplKO), we did not observe robust changes in expression of PEtN-related genes. However, loss of Etnppl altered the phospholipid profile in the brain, resulting in increased total abundance of PE and in polyunsaturated fatty acids within PE and phosphatidylcholine species in the brain. Together, these data suggest that brain phospholipids are regulated by the phospholyase action of the enzyme Etnppl, which is induced by dietary fasting in astrocytes.

Mitochondrial Fatty Acid β-Oxidation and Resveratrol Effect in Fibroblasts from Patients with Autism Spectrum Disorder

Patients with autism spectrum disorder (ASD) may have an increase in blood acyl-carnitine (AC) concentrations indicating a mitochondrial fatty acid β-oxidation (mtFAO) impairment. However, there are no data on systematic mtFAO analyses in ASD. We analyzed tritiated palmitate oxidation rates in fibroblasts from patients with ASD before and after resveratrol (RSV) treatment, according to methods used for the diagnosis of congenital defects in mtFAO. ASD participants (N = 10, 60%; male; mean age (SD) 7.4 (3.2) years) were divided in two age-equivalent groups based on the presence (N = 5) or absence (N = 5) of elevated blood AC levels. In addition, electron transport chain (ETC) activity in fibroblasts and muscle biopsies and clinical characteristics were compared between the ASD groups. Baseline fibroblast mtFAO was not significantly different in patients in comparison with control values. However, ASD patients with elevated AC exhibited significantly decreased mtFAO rates, muscle ETC complex II activity, and fibroblast ETC Complex II/III activity (p < 0.05), compared with patients without an AC signature. RSV significantly increased the mtFAO activity in all study groups (p = 0.001). The highest mtFAO changes in response to RSV were observed in fibroblasts from patients with more severe symptoms on the Social Responsiveness Scale total (p = 0.001) and Awareness, Cognition, Communication and Motivation subscales (all p < 0.01). These findings suggested recognition of an ASD patient subset characterized by an impaired mtFAO flux associated with abnormal blood AC. The study elucidated that RSV significantly increased fibroblast mtFAO irrespective of plasma AC status, and the highest changes to RSV effects on mtFAO were observed in the more severely affected patients.

Potential Role of L-Carnitine in Autism Spectrum Disorder

L-carnitine plays an important role in the functioning of the central nervous system, and especially in the mitochondrial metabolism of fatty acids. Altered carnitine metabolism, abnormal fatty acid metabolism in patients with autism spectrum disorder (ASD) has been documented. ASD is a complex heterogeneous neurodevelopmental condition that is usually diagnosed in early childhood. Patients with ASD require careful classification as this heterogeneous clinical category may include patients with an intellectual disability or high functioning, epilepsy, language impairments, or associated Mendelian genetic conditions. L-carnitine participates in the long-chain oxidation of fatty acids in the brain, stimulates acetylcholine synthesis (donor of the acyl groups), stimulates expression of growth-associated protein-43, prevents cell apoptosis and neuron damage and stimulates neurotransmission. Determination of L-carnitine in serum/plasma and analysis of acylcarnitines in a dried blood spot may be useful in ASD diagnosis and treatment. Changes in the acylcarnitine profiles may indicate potential mitochondrial dysfunctions and abnormal fatty acid metabolism in ASD children. L-carnitine deficiency or deregulation of L-carnitine metabolism in ASD is accompanied by disturbances of other metabolic pathways, e.g., Krebs cycle, the activity of respiratory chain complexes, indicative of mitochondrial dysfunction. Supplementation of L-carnitine may be beneficial to alleviate behavioral and cognitive symptoms in ASD patients.

Enhanced childhood diseases treatment using computational models: Systematic review of intelligent experiments heading to precision medicine

INTRODUCTION

Precision or personalized Medicine (PM) is used for the prevention and treatment of diseases by considering a huge amount of information about individuals variables. Due to high volume of information, AI-based computational models are required. A large set of studies conducted to examine the PM approach to improve childhood clinical outcomes. Thus, the main goal of this study was to review the application of health information technology and especially artificial intelligence (AI) methods for the treatment of childhood disease using PM.

METHODS

PubMed, Scopus, Web of Science, and EMBASE databases were searched up to December 18, 2019. Articles that focused on informatics applications for childhood disease PM included in this study. Included papers were classified for qualitative analysis and interpreting results. The results were analyzed using Microsoft Excel 2019.

RESULTS

From 341 citations, 62 papers met our inclusion criteria. The number of published papers that used AI methods to apply for PM in childhood diseases increased from 2010 to 2019. Our results showed that most applied methods were related to machine learning discipline. In terms of clinical scope, the largest number of clinical articles are devoted to oncology. Besides, the analysis showed that genomics was the most PM approach used regarding childhood disease.

CONCLUSION

This systematic review examined papers that used AI methods for applying PM approaches in childhood diseases from medical informatics perspectives. Thus, it provided new insight to researchers who are interested in knowing research needs in this field.

Diagnostic Approach to Pediatric Autoimmune Neuropsychiatric Disorders Associated With Streptococcal Infections (PANDAS): A Narrative Review of Literature Data

Pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS) are clinical conditions characterized by the sudden onset of obsessive-compulsive disorder and/or tics, often accompanied by other behavioral symptoms in a group of children with streptococcal infection. PANDAS-related disorders, including pediatric acute-onset neuropsychiatric syndrome (PANS), childhood acute neuropsychiatric symptoms (CANS), and pediatric infection triggered autoimmune neuropsychiatric disorders (PITANDs), have also been described. Since first defined in 1998, PANDAS has been considered a controversial diagnosis. A comprehensive review of the literature was performed on PubMed and Scopus databases, searching for diagnostic criteria and diagnostic procedures of PANDAS and related disorders. We propose a test panel to support clinicians in the workout of PANDAS/PANS patients establishing an appropriate treatment. However, further studies are needed to improve our knowledge on these acute-onset neuropsychiatric conditions.

Exploring cellular markers of metabolic syndrome in peripheral blood mononuclear cells across the neuropsychiatric spectrum

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements

An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.

Determining the Bioenergetic Capacity for Fatty Acid Oxidation in the Mammalian Nervous System

The metabolic state of the brain can greatly impact neurologic function. Evidence of this includes the therapeutic benefit of a ketogenic diet in neurologic diseases, including epilepsy. However, brain lipid bioenergetics remain largely uncharacterized. The existence, capacity, and relevance of mitochondrial fatty acid β-oxidation (FAO) in the brain are highly controversial, with few genetic tools available to evaluate the question. We have provided evidence for the capacity of brain FAO using a pan-brain-specific conditional knockout (KO) mouse incapable of FAO due to the loss of carnitine palmitoyltransferase 2, the product of an obligate gene for FAO (CPT2B-/-). Loss of central nervous system (CNS) FAO did not result in gross neuroanatomical changes or systemic differences in metabolism. Loss of CPT2 in the brain did not result in robustly impaired behavior. We demonstrate by unbiased and targeted metabolomics that the mammalian brain oxidizes a substantial quantity of long-chain fatty acids in vitro and in vivo Loss of CNS FAO results in robust accumulation of long-chain acylcarnitines in the brain, suggesting that the mammalian brain mobilizes fatty acids for their oxidation, irrespective of diet or metabolic state. Together, these data demonstrate that the mammalian brain oxidizes fatty acids under normal circumstances with little influence from or on peripheral tissues.

Metabolomics and adductomics of newborn bloodspots to retrospectively assess the early-life exposome

PURPOSE OF REVIEW

Exposomics studies can measure health-relevant chemical exposures during a lifetime and estimate the 'internal' environment. However, sampling limitations make these features difficult to capture directly during the critical neonatal time period.

RECENT FINDINGS

We review the use of newborn dried bloodspots (DBS) archived from newborn screening programs for exposomic analysis in epidemiological children's health studies. Emerging 'omics technologies such as adductomics and metabolomics have been adapted for DBS analysis, and these technologies can now provide valuable etiological information on the complex interplay between exposures, biological response, and population phenotypes.

SUMMARY

Adductomics and metabolomics of DBS can provide robust measurements for retrospective epidemiological investigations. With extensive bioarchiving programs in the United States and other countries, DBS are poised to substantially aid epidemiological studies, particularly for rare and low-frequency childhood diseases and disorders.

Metal and essential element levels in hair and association with autism severity

BACKGROUND

Autism Spectrum Disorder (ASD) is a complex disorder with heterogeneous etiology and wide clinical severity which supports the needs of recognizing biological and clinical features in patient subsets. The present study aimed to understand possible associations between the hair levels of metals and essential elements and some specific features of ASD measured by the Autism Diagnostic Observation Schedule (ADOS) that represents the gold-standard instrument to objectively confirm ASD diagnosis.

METHODS

A cross-sectional study was performed in the province of Catania (Sicily, South Italy). Forty-eight subjects with ASD (70.8% male), aged from 2 to 17 years were studied. Metals (Li, Be, Al, Ni, As, Mo, Cd, Hg, U, Pb) and essential trace elements (Cr, Co, Mn, Zn, Cu, Se) were quantified in hair by inductively coupled plasma mass spectrometry analysis. Participants were characterized by measuring the severity of autism symptoms and cognitive levels.

RESULTS

A significant and positive correlation was found between hair metal burden (lead, aluminum, arsenic and cadmium levels) and severity of ASD symptoms (social communication deficits and repetitive, restrictive behaviors). Hair zinc level were inversely related with age while there was a negative, significant association between hair zinc level and severity of autistic symptoms (defective functional play and creativity and increase of stereotyped behavior). Lead, molybdenum and manganese hair levels were inversely correlated with cognitive level (full intelligence quotient) in ASD individuals.

CONCLUSIONS

The present study suggests the importance to combine metallomics analysis with pertinent disease features in ASD to identify potential environmental risk factors on an individual level possibly in the early developmental period.

Emerging biomarkers in autism spectrum disorder: a systematic review

Autism spectrum disorder (ASD) affects approximately 2% of children in the United States (US) yet its etiology is unclear and effective treatments are lacking. Therapeutic interventions are most effective if started early in life, yet diagnosis often remains delayed, partly because the diagnosis of ASD is based on identifying abnormal behaviors that may not emerge until the disorder is well established. Biomarkers that identify children at risk during the pre-symptomatic period, assist with early diagnosis, confirm behavioral observations, stratify patients into subgroups, and predict therapeutic response would be a great advance. Here we underwent a systematic review of the literature on ASD to identify promising biomarkers and rated the biomarkers in regards to a Level of Evidence and Grade of Recommendation using the Oxford Centre for Evidence-Based Medicine scale. Biomarkers identified by our review included physiological biomarkers that identify neuroimmune and metabolic abnormalities, neurological biomarkers including abnormalities in brain structure, function and neurophysiology, subtle behavioral biomarkers including atypical development of visual attention, genetic biomarkers and gastrointestinal biomarkers. Biomarkers of ASD may be found prior to birth and after diagnosis and some may predict response to specific treatments. Many promising biomarkers have been developed for ASD. However, many biomarkers are preliminary and need to be validated and their role in the diagnosis and treatment of ASD needs to be defined. It is likely that biomarkers will need to be combined to be effective to identify ASD early and guide treatment.

Effects of l-Carnitine in Patients with Autism Spectrum Disorders: Review of Clinical Studies

Carnitine is an amino acid derivative, which plays several important roles in human physiology, in the central nervous system, and for mitochondrial metabolism, in particular. Altered carnitine metabolic routes have been associated with a subgroup of patients with autism spectrum disorders (ASD) and could add to the pathophysiology associated with these disorders. We review the current evidence about the clinical effects of carnitine administration in ASD in both non-syndromic forms and ASD associated with genetic disorders. Two randomized clinical trials and one open-label prospective trial suggest that carnitine administration could be useful for treating symptoms in non-syndromic ASD. The effect of carnitine administration in ASD associated with genetic disorders is not conclusive because of a lack of clinical trials and objectives in ASD evaluation, but beneficial effects have also been reported for other comorbid disorders, such as intellectual disability and muscular strength. Side effects observed with a dose of 200 mg/kg/day consisted of gastro-intestinal symptoms and a strong, heavy skin odor. Doses of about 50–100 mg/kg/day are generally well tolerated. Further clinical trials with the identification of the subgroup of ASD patients that would benefit from carnitine administration are warranted.

Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy

Current diagnosis of autism spectrum disorder (ASD) is based on assessment of behavioral symptoms, although there is strong evidence that ASD affects multiple organ systems including the gastrointestinal (GI) tract. This study used Fisher discriminant analysis (FDA) to evaluate plasma metabolites from 18 children with ASD and chronic GI problems (ASD + GI cohort) and 20 typically developing (TD) children without GI problems (TD − GI cohort). Using three plasma metabolites that may represent three general groups of metabolic abnormalities, it was possible to distinguish the ASD + GI cohort from the TD − GI cohort with 94% sensitivity and 100% specificity after leave-one-out cross-validation. After the ASD + GI participants underwent Microbiota Transfer Therapy with significant improvement in GI and ASD-related symptoms, their metabolic profiles shifted significantly to become more similar to the TD − GI group, indicating potential utility of this combination of plasma metabolites as a biomarker for treatment efficacy. Two of the metabolites, sarcosine and inosine 5′-monophosphate, improved greatly after treatment. The third metabolite, tyramine O-sulfate, showed no change in median value, suggesting it and correlated metabolites to be a possible target for future therapies. Since it is unclear whether the observed differences are due to metabolic abnormalities associated with ASD or with GI symptoms (or contributions from both), future studies aiming to classify ASD should feature TD participants with GI symptoms and have larger sample sizes to improve confidence in the results.

[Dysfunctions of mitochondrial fatty acid β-oxidation in rare and common diseases]

Dysfunctions of mitochondrial fatty acid ß-oxidation (ß-FAO) in various tissues represent a hallmark of many common disorders, and are acknowledged to play an essential role in the pathogenesis of diabetes, obesity, and cardiac diseases. Moreover, inborn defects in ß-FAO form a large family of rare diseases with variable phenotypes, ranging from fatal multi-organ failure in the newborn to isolated adult onset myopathy. These pathologies highlight the critical role of ß-FAO in many tissues with high-energy demand (heart, muscle, liver, kidney). Furthermore, and unexpectedly, very recent data unveiled the possible involvement of ß-FAO in instructing complex non energy-related functions, such as chromatin modification, control of neural stem cell activity, or survival and fate of cancer cells. Pharmacological targeting of ß-FAO by small molecules might therefore open new avenues for the treatment of various rare or common diseases.

First Case Report of Primary Carnitine Deficiency Manifested as Intellectual Disability and Autism Spectrum Disorder

Systemic primary carnitine deficiency (PCD) is a genetic disorder caused by decreased or absent organic cation transporter type 2 (OCTN2) carnitine transporter activity, resulting in low serum carnitine levels and decreased carnitine accumulation inside cells. In early life, PCD is usually diagnosed as a metabolic decompensation, presenting as hypoketotic hypoglycemia, Reye syndrome, or sudden infant death; in childhood, PCD presents with skeletal or cardiac myopathy. However, the clinical presentation of PCD characterized by autism spectrum disorder (ASD) with intellectual disability (ID) has seldom been reported in the literature. In this report, we describe the clinical features of a seven-year-old girl diagnosed with PCD who presented atypical features of the disease, including a developmental delay involving language skills, concentration, and attention span, as well as autistic features and brain alterations apparent in magnetic resonance imaging. We aim to highlight the difficulties related to the diagnostic and therapeutic approaches used to diagnose such patients. The case reported here presented typical signs of PCD, including frequent episodes of hypoglycemia, generalized muscle weakness, decreased muscle mass, and physical growth deficits. A molecular genetic study confirmed the definitive diagnosis of the disease (c.1345T>G (p.Y449D)) in gene SLC22A5, located in exon 8. PCD can be accompanied by less common clinical signs, which may delay its diagnosis because the resulting global clinical picture can closely resemble other metabolic disorders. In this case, the patient was prescribed a carnitine-enriched diet, as well as oral carnitine at a dose of 100 mg/kg/day. PCD has a better prognosis if it is diagnosed and treated early; however, a high level of clinical suspicion is required for its timely and accurate diagnosis.

Nuclear Peroxisome Proliferator-Activated Receptors (PPARs) as Therapeutic Targets of Resveratrol for Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by defective social communication and interaction and restricted, repetitive behavior with a complex, multifactorial etiology. Despite an increasing worldwide prevalence of ASD, there is currently no pharmacological cure to treat core symptoms of ASD. Clinical evidence and molecular data support the role of impaired mitochondrial fatty acid oxidation (FAO) in ASD. The recognition of defects in energy metabolism in ASD may be important for better understanding ASD and developing therapeutic intervention. The nuclear peroxisome proliferator-activated receptors (PPAR) α, δ, and γ are ligand-activated receptors with distinct physiological functions in regulating lipid and glucose metabolism, as well as inflammatory response. PPAR activation allows a coordinated up-regulation of numerous FAO enzymes, resulting in significant PPAR-driven increases in mitochondrial FAO flux. Resveratrol (RSV) is a polyphenolic compound which exhibits metabolic, antioxidant, and anti-inflammatory properties, pointing to possible applications in ASD therapeutics. In this study, we review the evidence for the existing links between ASD and impaired mitochondrial FAO and review the potential implications for regulation of mitochondrial FAO in ASD by PPAR activators, including RSV.