A predictive ensemble classifier for the gene expression diagnosis of ASD at ages 1 to 4 years

The Impact of Microglia on Neurodevelopment and Brain Function in Autism

Microglia, as one of the main types of glial cells in the central nervous system (CNS), are widely distributed throughout the brain and spinal cord. The normal number and function of microglia are very important for maintaining homeostasis in the CNS. In recent years, scientists have paid widespread attention to the role of microglia in the CNS. Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder, and patients with ASD have severe deficits in behavior, social skills, and communication. Most previous studies on ASD have focused on neuronal pathological changes, such as increased cell proliferation, accelerated neuronal differentiation, impaired synaptic development, and reduced neuronal spontaneous and synchronous activity. Currently, more and more research has found that microglia, as immune cells, can promote neurogenesis and synaptic pruning to maintain CNS homeostasis. They can usually reduce unnecessary synaptic connections early in life. Some researchers have proposed that many pathological phenotypes of ASD may be caused by microglial abnormalities. Based on this, we summarize recent research on microglia in ASD, focusing on the function of microglia and neurodevelopmental abnormalities. We aim to clarify the essential factors influenced by microglia in ASD and explore the possibility of microglia-related pathways as potential research targets for ASD.

Validation of plasma protein glycation and oxidation biomarkers for the diagnosis of autism

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder in children. It is currently diagnosed by behaviour-based assessments made by observation and interview. In 2018 we reported a discovery study of a blood biomarker diagnostic test for ASD based on a combination of four plasma protein glycation and oxidation adducts. The test had 88% accuracy in children 5-12 years old. Herein, we present an international multicenter clinical validation study (N = 478) with application of similar biomarkers to a wider age range of 1.5-12 years old children. Three hundred and eleven children with ASD (247 male, 64 female; age 5.2 ± 3.0 years) and 167 children with typical development (94 male, 73 female; 4.9 ± 2.4 years) were recruited for this study at Sidra Medicine and Hamad Medical Corporation hospitals, Qatar, and Hospital Regional Universitario de Málaga, Spain. For subjects 5-12 years old, the diagnostic algorithm with features, advanced glycation endproducts (AGEs)-Nε-carboxymethyl-lysine (CML), Nω-carboxymethylarginine (CMA) and 3-deoxyglucosone-derived hydroimidazolone (3DG-H), and oxidative damage marker, o,o'-dityrosine (DT), age and gender had accuracy 83% (CI 79 - 89%), sensitivity 94% (CI 90-98%), specificity 67% (CI 57-76%) and area-under-the-curve of receiver operating characteristic plot (AUROC) 0.87 (CI 0.84-0.90). Inclusion of additional plasma protein glycation and oxidation adducts increased the specificity to 74%. An algorithm with 12 plasma protein glycation and oxidation adduct features was optimum for children of 1.5-12 years old: accuracy 74% (CI 70-79%), sensitivity 75% (CI 63-87%), specificity 74% (CI 58-90%) and AUROC 0.79 (CI 0.74-0.84). We conclude that ASD diagnosis may be supported using an algorithm with features of plasma protein CML, CMA, 3DG-H and DT in 5-12 years-old children, and an algorithm with additional features applicable for ASD screening in younger children. ASD severity, as assessed by ADOS-2 score, correlated positively with plasma protein glycation adducts derived from methylglyoxal, hydroimidazolone MG-H1 and Nε(1-carboxyethyl)lysine (CEL). The successful validation herein may indicate that the algorithm modifiable features are mechanistic risk markers linking ASD to increased lipid peroxidation, neuronal plasticity and proteotoxic stress.

Exploring the correlation between genetic transcription and multi-temporal developmental autism spectrum disorder using resting-state functional magnetic resonance imaging

Introduction

The present investigation aimed to explore the neurodevelopmental trajectory of autism spectrum disorder (ASD) by identifying the changes in brain function and gene expression associated with the disorder. Previous studies have indicated that ASD is a highly inherited neurodevelopmental disorder of the brain that displays symptom heterogeneity across different developmental periods. However, the transcriptomic changes underlying these developmental differences remain largely unknown.

Methods

To address this gap in knowledge, our study employed resting-state functional magnetic resonance imaging (rs-fMRI) data from a large sample of male participants across four representative age groups to stratify the abnormal changes in brain function associated with ASD. Partial least square regression (PLSr) was utilized to identify unique changes in gene expression in brain regions characterized by aberrant functioning in ASD.

Results

Our results revealed that ASD exhibits distinctive developmental trajectories in crucial brain regions such as the default mode network (DMN), temporal lobe, and prefrontal lobes during critical periods of neurodevelopment when compared to the control group. These changes were also associated with genes primarily located in synaptic tissues.

Discussion

The findings of this study suggest that the neurobiology of ASD is uniquely heterogeneous across different ages and may be accompanied by distinct molecular mechanisms related to gene expression.