Biomarkers start telling us a story: Autism pathophysiology revisited

Antonio Persico, MD, a recent ARI Research Grant recipient, explores the role of biomarkers in understanding autism pathophysiology. He discusses the complexity inherent to neurodevelopmental conditions and emphasizes the need to combine information from multiple fields of investigation. The presenter discusses contemporary autism research on genomics, methylomics, transcriptomics, proteomics, metabolomics, and functional brain imaging. He highlights the implications of protein transcription regulation and how it appears across groups and generations. Persico reiterates the complexities of neurodevelopmental conditions and the need for interdisciplinary research and understanding before the Q&A.

This is a joint presentation with the World Autism Organisation.

In this webinar:

0:30 – 6:30 – Organization introductions
8:10 – Presentation introduction
12:25 – Genomics
16:00 – Interaction of rare and common gene variants
18:00 – Functional analysis of genetic pathways
21:15 – Neurodevelopmental genes
26:00 – Methylomics
30:00 – Genomic and epigenetic overlap
34:40 – Generational methylation and pathophysiology
41:00 – Transcriptomics
46:30 – Proteomics
50:30 – Metabolomics
55:00 – Functional brain imaging
59:55 – Summary and conclusion
1:03:00 – Q&A

The complexity of autism pathophysiology

Persico considers classic approaches to biomarker research and how they inform diagnosis, risk assessments, and developmental trajectories for neurodevelopmental conditions (8:10). However, focusing on biomarkers alone neglects the complexity of autism pathogenesis. He explains that while genomics closely analyzes the biological mechanisms of autism, it cannot inform brain structure and behavior (12:25). To understand the drivers of autism, the speaker asserts that we must combine knowledge from genetics, methylomics, metabolomics, movement kinetics, and more (11:20). He presents on a variety of these aspects. 

Genomics

The speaker explains how high-effect genes (rare variants) are enough to push beyond the autism risk threshold on their own. Contrastingly, low-to-moderate-effect genes (common variants) must occur in combination with other mutations to reach the genetic threshold (14:15). Persico outlines a recent study revealing only one in five people with autism had a causal gene mutation, rebutting previously held assumptions that rare causal genes are the most common genetic drivers of autism (12:25). He asserts that it is very rare for a single gene to cause autism and notes the increasing number of known common variant genes present in the general population (16:00). Persico states that autism genetics is beginning to resemble that of epilepsy, type 2 diabetes, and other conditions with strong familiality and complex underlying biology (17:35). 

• Genetic Testing in Neurodevelopmental Disorders (Savatt & Myers, 2021)
• The Yin and Yang of autism genetics: how rare de novo and common variations affect liability (Chaste et al., 2017)

Genetic pathways and protein function

The speaker explains how analyzing the function of proteins encoded by common variants/candidate genes can help us understand autism pathogenesis (18:00). He outlines two recent exome sequencing studies that show autism-related genes are generally linked to expression regulation (expressed during gestation) and neuronal communication (expressed in early life) pathways (19:15). These findings are replicated in Italian and Tunisian cohorts (20:15).

• Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism (Satterstrom et al., 2020)
• Synaptic, transcriptional and chromatin genes disrupted in autism (De Rubeis et al., 2014)
• Diagnostic yield and clinical impact of chromosomal microarray analysis in autism spectrum disorder (Cucinotta et al., 2023)
• Yield of array‐CGH analysis in Tunisian children with autism spectrum disorder (Chehbani et al., 2022)

Neurodevelopmental gene pathways

Persico states that there is no such thing as an autism gene because, depending on the affected pathways and protein functions, candidate genes could result in a variety of neurodevelopmental conditions (21:15). He discusses pleiotropy and outlines two studies illustrating the variability in gene expression among supposedly homogenous genetic symptoms (22:00). Another recent investigation found that nearly half of the siblings with a pathogenic/rare variant gene did not evolve toward autism. The speaker asserts that, due to the variability in neurodevelopmental gene pathways and expression, genetics alone is not often sufficient to predict autism. Persico reasserts the need for interdisciplinary research in unraveling the pathophysiology of autism and other neurodevelopmental conditions (24:00). 

• Insufficient evidence for “autism-specific” genes (Myers et al., 2020)
• Predictive impact of rare genomic copy number variations in siblings of individuals with autism spectrum disorders (D’Abate et al., 2019)

Methylomics

Methylomics is an epigenetic mechanism that alters gene expression via transcription pathway regulation. The presenter describes how DNA strands coil themselves around histones to create RNA transcription sites and how, if wrapped too tightly, those transcription regions are repressed (26:00). Persico explains that both transcription pathway repression and gene deletion lead to gene silencing, making it challenging to pinpoint causal mechanisms (27:50). He outlines two studies that illustrate this variability in genetics and methylation across sibling pairs (28:25). 

A 2017 investigation combining data from genetics and epigenetics found that a significant number of common autism-related variants are associated with methylation (39:00). The presenter reminds viewers that methylation influences immune-related pathways, which can affect individuals much later in development (40:22). He underscores the importance of epigenetics, noting a study that used methylomic biomarkers to distinguish between autistic and unaffected siblings with 99.7% accuracy (32:45). He affirms that, although this study may not be replicable, contemporary evidence clearly suggests different patterns of methylation in autistic children and their siblings (33:40). 

• Methylomic analysis of monozygotic twins discordant for autism spectrum disorder and related behavioural traits (Wong et al., 2014) 
• Genomic and epigenetic evidence for oxytocin receptor deficiency in autism (Gregory et al., 2009)
• Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder(Andrews et al., 2017)
• Immune transcriptome alterations in the temporal cortex of subjects with autism (Garbett et al., 2008)
• Detecting Methylomic Biomarkers of Pediatric Autism in the Peripheral Blood Leukocytes (Feng et al., 2019)

Generational methylation and pathophysiology

A 2020 genome sequencing study found sex-specific differentially methylated genes in the cord blood of newborns who later received an autism diagnosis (34:40). Researchers have also recorded methylome differences in the sperm genome of fathers of autistic children (35:57). Persico asserts that these findings suggest that differential methylation and potential autism biomarkers are present before birth. The speaker describes early embryo demethylation, highlighting how some parental methylation sites are maintained through at least early childhood (37:15). He considers how these findings may help broaden the focus of biomarker research to encompass intergenerational drivers and patterns (38:00). 

• Cord blood DNA methylome in newborns later diagnosed with autism spectrum disorder reflects early dysregulation of neurodevelopmental and X-linked genes (Mordaunt et al., 2020)
• Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort (Feinberg et al., 2015)

Transcriptomics

Transcriptomics studies the structure, function, and evolution of genome-wide RNA (transcriptome). The speaker outlines brain imaging studies showing significant overexpression of immune genes and underexpression of neuronal genes across ages and brain regions in autistic participants (41:00). Similarly, a 2023 RNA sequencing analysis found specific co-expressed genes that are regulated differently in autistic siblings of typically developing children (43:15). Persico discusses RACK1 and its role in the translational control of neuroinflammation and neurodevelopment. He asserts that evidence is beginning to point toward specific and significantly different neurodevelopment pathways and reiterates the advantages of combining information from multiple fields (45:00). 

• Autism, the superior temporal sulcus and social perception (Zilbovicius et al., 2006)
• RNA sequencing of blood from sex- and age-matched discordant siblings supports immune and transcriptional dysregulation in autism spectrum disorder (Tomaiuolo et al., 2023)
• Transcriptomic analysis of autistic brain reveals convergent molecular pathology (Voineagu et al., 2011) 
• Structural analysis of ribosomal RACK1 and its role in translational control. Cellular Signalling (Nielsen et al., 2017)

Proteomics

Proteomics is the large-scale study of protein expression in the body and is relatively understudied in autism. Findings to date suggest the presence of inflammation in the periphery and central tissue of autistic participants (46:30). Persico uses a diagram to explain alternative splicing, the mechanism by which proteins are expressed slightly differently across the body. When this process is deranged, expression is incomplete or disrupted in alternatively spliced proteins (47:00). The speaker asks why abnormal alternative splicing and inflammation are common in autism and asserts that adding another level of investigation may provide some answers (50:00). 

• Proteomic explorations of autism spectrum disorder (Szoko et al., 2017)

Metabolomics

Metabolomics is the large-scale study of small molecules in cells and tissues, including the microbiome. Gut health is a critical aspect of overall health and autism risk. Extant literature shows microbiome profiles specific to autism with high levels of inflammatory bacteria and non-human compounds (50:30). Persico outlines an animal model where the offspring of mice colonized with autistic gut bacteria displayed autism-like behaviors (52:08). The offspring microbiome induced abnormal alternative splicing involving at least 52 of the known autism genes. These data, Persico claims, show that offspring are affected by parental microbiome content, further solidifying the intergenerational aspect and complexity of autism pathogenesis (52:20). 

• Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism (Gevi et al., 2016)
• Analysis of gut microbiota profiles and microbe-disease associations in children with autism spectrum disorders in China (Zhang et al., 2018)
• Human gut microbiota from autism spectrum disorder promote behavioral symptoms in mice (Sharon et al., 2019)

Functional brain imaging

Autism is described by altered behavior stemming from differences in brain connectivity. The speaker describes instances of reduced connectivity and hyperconnectivity across brain regions observed in autism, noting the interplay of brain structure and function (55:00). A neurogenetics study of 647 autistic individuals found that brain connectivity varies across individuals, with most experiencing a mixture of hyper and reduced connectivity (57:20). Persico notes that hyperconnected brain regions are linked to genes exhibiting excitation, which demonstrates the relationship between genetics and other fields of investigation (58:35). 

• Autism: reduced connectivity between cortical areas involved in face expression, theory of mind, and the sense of self (Cheng et al., 2015)
• The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder (Hahamy et al., 2015)
• The neurogenetics of functional connectivity alterations in autism: Insights from subtyping in 657 individuals (Rasero et al., 2023)
• mTOR-related synaptic pathology causes autism spectrum disorder-associated functional hyperconnectivity (Pagani et al., 2021)

Conclusion

The speaker discusses the mTOR pathway in autism, noting the implications of immune activation and inflammation associated with hyperconnectivity. Epigenetics and the gut microbiome also contribute to candidate gene regulation via mTOR, beginning in the parental gut and sperm cells (59:55). Persico therefore claims that altered brain connectivity can be due to genetics, epigenetics, neuroinflammation, microbiome composition, and/or altered protein expression. He reiterates that we cannot use biomarker research alone if we want to understand complex conditions. Researchers and clinicians must respect the complexities of neurodevelopment and assemble information to unravel autism pathophysiology and inform proper care (1:02:30). He provides thanks and acknowledgments before the Q&A (1:03:00). 

• Molecular mechanisms of mTOR-mediated translational control (Ma & Blenis, 2009)

Learn more about the mTOR and other signaling pathways in this webinar

Originally published March 26, 2024