This systematic review aims to offer an updated understanding of the relationship between gastrointestinal symptoms (GIS) and autism spectrum disorder (ASD) in children and adolescents. The databases PsycINFO, Medline, Cinahl, and ERIC were searched using keywords, and relevant literature was hand-searched. Papers (n = 3319) were systematically screened and deemed eligible if they were empirical studies published in English since 2014 and measured the GIS of individuals with ASD who were under 18 years old. Thirty studies were included in the final review. The study findings were synthesized under eight themes, including the prevalence and nature of GIS and their relationship with developmental regression, language and communication, ASD severity, challenging behavior, comorbid psychopathology, sleep problems, and sensory issues. The review found that GIS were common and that there was contradictory evidence concerning their relationship with co-occurring conditions. It also identified evidence of some causal relationships that support the existence of the gut–immune–brain pathways. Future research needs to use large prospective designs and objective and standardized GIS measurements to provide a nuanced understanding of GIS in the context of ASD.

Autism Spectrum Disorder (ASD) affects approximately 1 child in 54, with a 35-fold increase since 1960. Selected studies suggest that part of the recent increase in prevalence is likely attributable to an improved awareness and recognition, and changes in clinical practice or service availability. However, this is not sufficient to explain this epidemiological phenomenon. Research points to a possible link between ASD and intestinal microbiota because many children with ASD display gastro-intestinal problems. Current large-scale datasets of ASD are limited in their ability to provide mechanistic insight into ASD because they are predominantly cross-sectional studies that do not allow evaluation of perspective associations between early life microbiota composition/function and later ASD diagnoses. Here we describe GEMMA (Genome, Environment, Microbiome and Metabolome in Autism), a prospective study supported by the European Commission, that follows at-risk infants from birth to identify potential biomarker predictors of ASD development followed by validation on large multi-omics datasets. The project includes clinical (observational and interventional trials) and pre-clinical studies in humanized murine models (fecal transfer from ASD probands) and in vitro colon models. This will support the progress of a microbiome-wide association study (of human participants) to identify prognostic microbiome signatures and metabolic pathways underlying mechanisms for ASD progression and severity and potential treatment response.

Glycosylation, being the most abundant post-translational modification, plays a profound role affecting expression, localization and function of proteins and macromolecules in immune response to infection. Presented are the findings of a transcriptomic analysis performed using high-throughput functional genomics data from public repository to examine the altered transcription of the human glycosylation machinery in response to SARS-CoV-2 stimulus and infection. In addition to the conventional in silico functional enrichment analysis methods we also present results from the manual analysis of biomedical literature databases to bring about the biological significance of glycans and glycan-binding proteins in modulating the host immune response during SARS-CoV-2 infection. Our analysis revealed key immunomodulatory lectins, proteoglycans and glycan epitopes implicated in exerting both negative and positive downstream inflammatory signaling pathways, in addition to its vital role as adhesion receptors for SARS-CoV-2 pathogen. A hypothetical correlation of the differentially expressed human glycogenes with the altered host inflammatory response and the cytokine storm-generated in response to SARS-CoV-2 pathogen is proposed. These markers can provide novel insights into the diverse roles and functioning of glycosylation pathways modulated by SARS-CoV-2, provide avenues of stratification, treatment, and targeted approaches for COVID-19 immunity and other viral infectious agents.

In addition to the psychological depressive phenotype, major depressive disorder (MDD) patients are also associated with underlying immune dysregulation that correlates with metabolic syndrome prevalent in depressive patients. A robust integrative analysis of biological pathways underlying the dysregulated neural connectivity and systemic inflammatory response will provide implications in the development of effective strategies for the diagnosis, management and the alleviation of associated comorbidities. In the current study, focusing on MDD, we explored an integrative network analysis methodology to analyze transcriptomic data combined with the meta-analysis of biomarker data available throughout public databases and published scientific peer-reviewed articles. Detailed gene set enrichment analysis and complex protein–protein, gene regulatory and biochemical pathway analysis has been undertaken to identify the functional significance and potential biomarker utility of differentially regulated genes, proteins and metabolite markers. This integrative analysis method provides insights into the molecular mechanisms along with key glycosylation dysregulation underlying altered neutrophil-platelet activation and dysregulated neuronal survival maintenance and synaptic functioning. Highlighting the significant gap that exists in the current literature, the network analysis framework proposed reduces the impact of data gaps and permits the identification of key molecular signatures underlying complex disorders with multiple etiologies such as within MDD and presents multiple treatment options to address their molecular dysfunction.

The potential for psychedelic molecules in impacting cognitive flexibility has long been supported and acknowledged across scientific reports. In the current study, an approach leveraging knowledge-based gene-set information analysis has been adopted to explore the potential impact of psychedelic molecules on both glycosylation, (a post-translational modifications (PTM)) and on neuro-regulatory pathways. Though limitations and restrictions rise from the scarcity of publicly available ‘omics’ data, targeted analysis enabled us to identify a number of key glycogenes (Hexb, Hs6st2, Col9a2, B3gat2, Mgat5, Bgn) involved the structural organization of extracellular matrix and neuroprotective factors (Kl, Pomc, Oxt, Gal, Avp, Cartpt) which play vital roles in neuron protection, development as well as synaptic stability. In response to psychedelic molecules, we found that these genes and associated pathways are transcriptional altered in rodent models. The approach used indicates the potential to exploit existing datasets for hypothesis generation and testing for the molecular processes which play a role in the physiological response to psychedelic molecule effects. These reported findings, which focused on alterations in glycogenes and neuro-regulatory factors may provide a novel range of biomarkers to track the beneficial, as well as potential toxicological effects of psychedelic molecules.