Assessment of Changes over Time of Lipid Profile, C-Reactive Protein Level and Body Mass Index in Teenagers and Young Adults on Different Diets Belonging to Autism Spectrum Disorder

Metabolomic changes in children with autism

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and repetitive behaviors. Metabolomic profiling has emerged as a valuable tool for understanding the underlying metabolic dysregulations associated with ASD.

AIM

To comprehensively explore metabolomic changes in children with ASD, integrating findings from various research articles, reviews, systematic reviews, meta-analyses, case reports, editorials, and a book chapter.

METHODS

A systematic search was conducted in electronic databases, including PubMed, PubMed Central, Cochrane Library, Embase, Web of Science, CINAHL, Scopus, LISA, and NLM catalog up until January 2024. Inclusion criteria encompassed research articles (83), review articles (145), meta-analyses (6), systematic reviews (6), case reports (2), editorials (2), and a book chapter (1) related to metabolomic changes in children with ASD. Exclusion criteria were applied to ensure the relevance and quality of included studies.

RESULTS

The systematic review identified specific metabolites and metabolic pathways showing consistent differences in children with ASD compared to typically developing individuals. These metabolic biomarkers may serve as objective measures to support clinical assessments, improve diagnostic accuracy, and inform personalized treatment approaches. Metabolomic profiling also offers insights into the metabolic alterations associated with comorbid conditions commonly observed in individuals with ASD.

CONCLUSION

Integration of metabolomic changes in children with ASD holds promise for enhancing diagnostic accuracy, guiding personalized treatment approaches, monitoring treatment response, and improving outcomes. Further research is needed to validate findings, establish standardized protocols, and overcome technical challenges in metabolomic analysis. By advancing our understanding of metabolic dysregulations in ASD, clinicians can improve the lives of affected individuals and their families.

Investigation of Liver X Receptor Gene Variants and Oxysterol Dysregulation in Autism Spectrum Disorder

The NR1H2 gene produces the Liver X Receptor Beta (LXRB) protein, which is crucial for brain cholesterol metabolism and neuronal development. However, its involvement in autism spectrum disorder (ASD) remains largely unexplored, aside from animal studies. This study is the first to explore the potential link between autism and rs2695121/rs17373080 single nucleotide polymorphisms (SNPs) in the regulatory regions of NR1H2, known for their association with neuropsychiatric functions. Additionally, we assessed levels of oxysterols (24-Hydroxycholesterol, 25-Hydroxycholesterol, 27-Hydroxycholesterol), crucial ligands of LXR, and lipid profiles. Our cohort comprised 107 children with ASD and 103 healthy children aged 2-18 years. Clinical assessment tools included the Childhood Autism Rating Scale, Autistic Behavior Checklist, and Repetitive Behavior Scale-Revised. Genotyping for SNPs was conducted using PCR-RFLP. Lipid profiles were analyzed with Beckman Coulter kits, while oxysterol levels were determined through liquid chromatography-tandem mass spectrometry. Significantly higher total cholesterol (p = 0.003), LDL (p = 0.008), and triglyceride (p < 0.001) levels were observed in the ASD group. 27-Hydroxycholesterol levels were markedly lower in the ASD group (p ≤ 0.001). ROC analysis indicated the potential of 27-Hydroxycholesterol to discriminate ASD diagnosis. The SNP genotype and allele frequencies were similar in both groups (p > 0.05). Our findings suggest that disturbances in oxysterol metabolism, previously linked to neurodegeneration, may constitute a risk factor for ASD and contribute to its heterogeneous phenotype.

Nerve growth factor and angiotensin converting enzyme 2 levels in children with neurodevelopmental disorders

OBJECTIVE

Neurodevelopmental disorders (NDDs) are the most common psychiatric disorders in childhood, and there are many factors in their etiology. In recent years, many biomarkers have been studied to elucidate the etiology of these disorders. In this study, it was aimed to investigate the levels of nerve growth factor (NGF) and angiotensin converting enzyme 2 (ACE2) in attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and intellectual disability (ID).

METHODS

The study included 74 children with NDDs (the number of patients in ADHD, ASD and ID groups were 24, 25 and 25 respectively) and 30 healthy controls (HCs). Serum NGF and ACE2 levels were studied with ELISA kits, also complete blood count (CBC), levels of fasting glucose and serum lipids were assessed.

RESULTS

ACE2 levels were found to be lower in NDD group than HCs in girls. In boys with ASD, triglyceride levels were significantly higher than other groups. Also a positive correlation was found between ACE2 and NGF levels when all sample assessed together.

CONCLUSIONS

This study is a premise for investigating ACE2 and NGF in NDDs. The role of these markers in ADHD, ASD, ID and other NDDs and their associations with gender should be assessed by studies in which both larger sample groups and more disorders.

The use of data independent acquisition based proteomic analysis and machine learning to reveal potential biomarkers for autism spectrum disorder

Autism spectrum disorder (ASD) is a complex neurological developmental disorder in children, and is associated with social isolation and restricted interests. The etiology of this disorder is still unknown. There is neither any confirmed laboratory test nor any effective therapeutic strategy to diagnose or cure it. We performed data independent acquisition (DIA) and multiple reaction monitoring (MRM) analysis of plasma from children with ASD and controls. The result showed that 45 differentially expressed proteins (DEPs) were identified between autistic subjects and controls. Among these, only one DEP was down-regulated in ASD; other DEPs were up-regulated in ASD children's plasma. These proteins are found associated with complement and coagulation cascades, vitamin digestion and absorption, cholesterol metabolism, platelet degranulation, selenium micronutrient network, extracellular matrix organization and inflammatory pathway, which have been reported to be related to ASD. After MRM verification, five key proteins in complement pathway (PLG, SERPINC1, and A2M) and inflammatory pathway (CD5L, ATRN, SERPINC1, and A2M) were confirmed to be significantly up-regulated in ASD group. Through the screening of machine learning model and MRM verification, we found that two proteins (biotinidase and carbonic anhydrase 1) can be used as early diagnostic markers of ASD (AUC = 0.8, p = 0.0001). SIGNIFICANCE: ASD is the fastest growing neurodevelopmental disorder in the world and has become a major public health problem worldwide. Its prevalence has been steadily increasing, with a global prevalence rate of 1%. Early diagnosis and intervention can achieve better prognosis. In this study, data independent acquisition (DIA) and multiple reaction monitoring (MRM) analysis was applied to analyze the plasma proteome of ASD patients (31 (±5) months old), and 378 proteins were quantified. 45 differentially expressed proteins (DEPs) were identified between the ASD group and the control group. They mainly were associated with platelet degranulation, ECM proteoglycar, complement and coagulation cascades, selenium micronutrient network, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), cholesterol metabolism, vitamin metabolism, and inflammatory pathway. Through the integrated machine learning methods and the MRM verification of independent samples, it is considered that biotinidase and carbon anhydrase 1 have the potential to become biomarkers for the early diagnosis of ASD. These results complement proteomics database of the ASD patients, broaden our understanding of ASD, and provide a panel of biomarkers for the early diagnosis of ASD.

Association Between Autism Spectrum Disorders and Cardiometabolic Diseases: A Systematic Review and Meta-analysis

Importance

Although the increased risk of obesity among individuals with autism has been well established, evidence on the association between autism, cardiometabolic disorders, and obesity remains inconclusive.

Objective

To examine the association between autism spectrum disorders and cardiometabolic diseases in a systematic review and meta-analysis.

Data Sources

PubMed, Scopus, Web of Science, ProQuest, Embase, and Ovid databases were searched from inception through July 31, 2022, without restrictions on date of publication or language.

Study Selection

Observational or baseline data of interventional studies reporting the prevalence of cardiometabolic risk factors (ie, diabetes, hypertension, dyslipidemia, atherosclerotic macrovascular disease) among children and/or adults with autism and matched with participants without autism were included.

Data Extraction and Synthesis

Screening, data extraction, and quality assessment were performed independently by at least 2 researchers. DerSimonian-Laird random-effects meta-analyses were performed using the meta package in R.

Main Outcomes and Measures

Relative risks (RRs) of diabetes, hypertension, dyslipidemia, and atherosclerotic macrovascular disease among individuals with autism were the primary outcomes. Secondary outcomes included the RR of type 1 and type 2 diabetes, heart disease, stroke, and peripheral vascular disease.

Results

A total of 34 studies were evaluated and included 276 173 participants with autism and 7 733 306 participants without autism (mean [range] age, 31.2 [3.8-72.8] years; pooled proportion [range] of female individuals, 47% [0-66%]). Autism was associated with greater risks of developing diabetes overall (RR, 1.57; 95% CI, 1.23-2.01; 20 studies), type 1 diabetes (RR, 1.64; 95% CI, 1.06-2.54; 6 studies), and type 2 diabetes (RR, 2.47; 95% CI, 1.30-4.70; 3 studies). Autism was also associated with increased risks of dyslipidemia (RR, 1.69; 95% CI, 1.20-2.40; 7 studies) and heart disease (RR, 1.46; 95% CI, 1.42-1.50; 3 studies). Yet, there was no significantly associated increased risk of hypertension and stroke with autism (RR, 1.22; 95% CI, 0.98-1.52; 12 studies; and RR, 1.19; 95% CI, 0.63-2.24; 4 studies, respectively). Meta-regression analyses revealed that children with autism were at a greater associated risk of developing diabetes and hypertension compared with adults. High between-study heterogeneity was a concern for several meta-analyses.

Conclusions and Relevance

Results suggest that the associated increased risk of cardiometabolic diseases should prompt clinicians to vigilantly monitor individuals with autism for potential contributors, signs of cardiometabolic disease, and their complications.

Retinol-binding protein 4 in combination with lipids to predict the regression phenomenon of autism spectrum disorders

BACKGROUND

About 20-40 % of autistic people experience a phenomenon of regression. Retinol binding protein 4 (RBP4) plays an important role as an inflammatory neurotrophic adipokine and is a promising mediator of the fat-brain axis. Abnormal fatty acid metabolism and lipid mediators have been reported to be related to the etiological mechanism in autism, and amelioration of impaired lipid metabolism can be recognized as a treatment strategy for autism. The purpose of this study is to explore the relationship between RBP4, lipids, and the autistic regression phenomenon, and to discuss their potentials as biomarkers for the autistic regression phenomenon.

METHODS

A total of 60 autistic individuals (18 with regression phenomenon, 42 without regression phenomenon) (ASD group) and 36 healthy controls were enrolled in this case-control study. The levels of RBP4, total cholesterol (TC), high-density lipoprotein (HDLC), low-density lipoprotein (LDLC), and triglyceride (TG) were measured. Childhood Autism Rating Scale (CARS) is used to assess the severity of autism. Ethical measures were performed in compliance with the current Declaration of Helsinki and written informed consent was obtained from the parents before enrollment of the children and adolescents.

RESULTS

Compared with control subjects, autistic individuals had lower levels of TC (P = 0.007), RBP4 (P = 0.001), and HDLC (P = 0.027). The levels of RBP4 in ASD group were positively correlated with TG (r = 0.355, P = 0.005), HDLC (r = 0.257, P = 0.047), TG/TC (r = 0.376, P = 0.003) and TG/LDLC (r = 0.363, P = 0.004), and were negatively correlated with CARS (r=-0.296, P = 0.003). Further logistic regression demonstrated that decreased RBP4 concentration was associated with the presentation of the autistic regression phenomenon even after the adjustment of the potential confounding factors.

CONCLUSIONS

Serum RBP4 is associated with the autistic regression phenomenon and the severity of ASD. Further studies are needed to expound whether decreased RBP4 participates in the development of the autistic regression phenomenon.

The Role of Cholesterol and Fatty Acids in the Etiology and Diagnosis of Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders whose pathogenesis seems to be related to an imbalance of excitatory and inhibitory synapses, which leads to disrupted connectivity during brain development. Among the various biomarkers that have been evaluated in the last years, metabolic factors represent a bridge between genetic vulnerability and environmental aspects. In particular, cholesterol homeostasis and circulating fatty acids seem to be involved in the pathogenesis of ASDs, both through the contribute in the stabilization of cell membranes and the modulation of inflammatory factors. The purpose of the present review is to summarize the available data about the role of cholesterol and fatty acids, mainly long-chain ones, in the onset of ASDs. A bibliographic research on the main databases was performed and 36 studies were included in our review. Most of the studies document a correlation between ASDs and hypocholesterolemia, while the results concerning circulating fatty acids are less univocal. Even though further studies are necessary to confirm the available data, the metabolic biomarkers open to new treatment options such as the modulation of the lipid pattern through the diet.

Are Obese Patients with Autism Spectrum Disorder More Likely to Be Selenium Deficient? Research Findings on Pre- and Post-Pubertal Children

Selenium is involved in many metabolic pathways that are critical for life. Information concerning the metabolic effects of selenium in autism spectrum disorder (ASD) and obesity is still conflicting and incomplete. The pre- and post-pubertal selenium profiles of patients with ASD and obesity have not yet been investigated. The goal of the study was to examine selenium content before and after puberty in euthyroid children diagnosed with ASD, compared to age-matched neurotypical controls, with respect to overweight or obesity as a co-existing pathology. Serum, toenail, and 24h urine selenium levels were determined by inductively coupled plasma mass spectrometry in 287 prepubertal children (mean age 8.09 years), divided into groups: ASD with overweight/obesity (ASD+/Ob+); ASD without overweight/obesity (ASD+/Ob-); non-ASD with overweight/obesity (ASD-/Ob+); and non-ASD without overweight/obesity (ASD-/Ob-). The assessment was repeated in 258 of the children after puberty (mean age 14.26 years).The lowest serum (p < 0.001), urine (p < 0.001) and toenail (p < 0.001) selenium levels before and after puberty were observed in ASD+/Ob+ patients, and the highest in ASD-/Ob-. There were no differences in serum/toenail selenium levels between ASD+/Ob- and ASD-/Ob+ groups. The presence of ASD was associatedwith lower serum (p < 0.001) and toenail (p < 0.001) selenium in BMI-matched groups. In neurotypical patients, post-pubertal serum selenium levels were lower (p < 0.001) than pre-pubertal levels. In the multiple linear regression analyses, selenium levels showed inverse relationships with BMI (p < 0.001) and male gender (p < 0.001), irrespective of the sample type. The serum (p = 0.002) and toenail (p < 0.001) selenium levels were inversely associated with the presence of ASD. ASD, obesity/overweight, and male gender have independent impacts on selenium levels in children. Puberty may affect selenium content in neurotypical children of both genders, but not in ASD patients.