Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify its “Epidemic Rates”

Torres, Elizabeth B.

doi:10.1101/2021.07.28.454081

Cited by 5 publications

(6 citation statements)

References 98 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is supported by extended research showing biorhythmic patterns in autism with a unique signature of noise-to-signal ratio. This motor code is bound to impact the kinesthetic reafferent feedback from the periphery to centers of central control [10; 13; 29; 30; 31]. Here we observed the origins of such departures at these early embryonic stages of neuronal cells’ differentiation, whereby the genes associated to ASD manifested the smallest shift in dependency index value from the initial to the final state, accompanied by the smallest increase in genes’ statistical dependency.…”

Section: Discussionmentioning

confidence: 72%

“…A recent revival of this debate underscores the side of the argument that psychiatric disorders are not just “mental” but are physical, too, identifying neurobiological substrates of mental illness [4]. These substrates are in line with the current US National Institute of Mental Health Research Domain Criteria (RDoC), a framework that cuts across research domains [5] but still has room for improvement [6; 7; 8; 9; 10].…”

Section: Introductionmentioning

confidence: 99%

“…First, we identified genes associated with a plurality of psychiatric and neurological disorders, and which also overlapped, thus being associated with phenotypes that are considered comorbid with, for example, autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), cerebral palsy (CP), etc . [9; 10]. Then, we considered the cumulative expression of the genes across four readings through 54 days, as the cells transitioned to neuronal classes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Neuropsychiatric Disorders

Thodoros

Schäfer

Gage

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The advent of open access to genomic data offers new opportunities to revisit old clinical debates while approaching them from a different angle. We examine anew the question of whether psychiatric and neurological disorders are different from each other by assessing the pool of genes associated with disorders that are understood as psychiatric or as neurological. We do so in the context of transcriptome data tracked as human embryonic stem cells differentiate and become neurons. Building upon probabilistic layers of increasing complexity, we describe the dynamics and stochastic trajectories of the full transcriptome and the embedded genes associated with psychiatric and/or neurological disorders. From marginal distributions of a gene's expression across hundreds of cells, to joint interactions taken globally to determine degree of pairwise dependency, to networks derived from probabilistic graphs along maximal spanning trees, we have discovered two fundamentally different classes of genes underlying these disorders and differentiating them. One class of genes boasts higher variability in expression and lower dependencies ("active genes"); the other has lower variability and higher dependencies ("lazy genes"). They give rise to different network architectures and different transitional states. Active genes have large hubs and a fragile topology, whereas lazy genes show more distributed code during the maturation toward neuronal state. Lazy genes boost differentiation between psychiatric and neurological disorders also at the level of tissue across the brain, spinal cord, and glands. These genes, with their low variability and asynchronous ON/OFF states that have been treated as gross data and excluded from traditional analyses, are helping us settle this old argument at more than one level of inquiry.

show abstract

Section: Discussionmentioning

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Neuropsychiatric Disorders

Thodoros

Schäfer

Gage

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recent biological evidence supports the notion that at least some forms (and probably the majority) of the broad, heterogeneous developmental disorders within the autism spectrum (ASD) are atypical prior to birth, many linked to genetic origins (11)(12)(13). These in turn, may have significant effects on postnatal development (14)(15)(16)(17).…”

Section: Introductionmentioning

confidence: 91%

Sensing Echoes: Temporal Misalignment in Auditory Brainstem Responses as the Earliest Marker of Neurodevelopmental Derailment

Torres

Varkey

Vero

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Sensory transduction and transmission delays operate and propagate along different time scales. From microseconds in the auditory domain, to hundreds of milliseconds in the visual, and kinesthetic domains, the brain must successfully align disparate delays arising from endogenously self-generated streams of motor and visceral sensorial information, with exogenous sensory inputs. To produce a cohesive response to environmental goals, constantly explore, adapt, and develop a sense of simultaneity, the brain must resolve this major feat and compensate for excessive delays in any sensory modality. Disruption in these processes may lead to altered perception of the self and others, and inadvertently affect social interactions. But how early such issues may emerge and be reliably detectable, remains a challenge. Here we assess in neonates, the transmission latencies of a sound wave that travels from the cochlear nerve to the brainstem on its way to the primary auditory cortex. Already at birth, we find systematic and cumulative delays in the propagation of this wave in neonates that later received a diagnosis of autism. Furthermore, we discover that the distributions of such temporal delays have far narrower bandwidth than those from neonates who did not receive the autism diagnosis. We identify associated codependent genes' networks and define a reliable marker of neurodevelopment derail, detectable at birth. Under the precision autism model, we propose that the brainstem contains an endogenous clock anchoring and aligning disparate timescales critical for the emergence and maintenance of congruent percepts of the self and others.

show abstract

“…In the future, we may also define our "diagnostic" moderation terms not based on current behavioral syndromes, such as those defined by DSM, but by empirically derived clusters derived from data at different levels of analysis, such as the genetic level (Torres, 2021), the "imaging" level (Clementz et al, 2016) or via modern artificial intelligence approaches that capture delimited clusters of behavioral performance (Mottron and Bzdok, 2020).…”

Section: Sampling and Diagnostic Moderation Effectsmentioning

confidence: 99%

Evaluating Causal Psychological Models: A Study of Language Theories of Autism Using a Large Sample

Ewen¹

2022

Preprint

View full text Add to dashboard Cite

Many of the psychological theories that attempt to explain key behavioral features of autism have histories that go back decades. The psychological literature around autism is primarily descriptive, and we propose that the field will generate the greatest traction when empirical work is designed to evaluate theories. Using a large-scale convenience dataset, we formalized as statistical models several theoretical claims around language/communicative theories of autism, as well as those of directly competing theories that posit primary roles of abstraction/prediction abilities and social abilities. The statistical evidence developed speaks against language/communicative theories of autism. We draw from historical analysis of the autism psychology literature, classic and recent “theoretical reform” efforts in the philosophy of psychology, as well as causal statistical modeling approaches to reflect on limitations of the current work and to design a strategy for enhanced traction. In addition to careful explication and formalization of theoretical accounts, we propose three principles for future work: specification, quantification, and integration. Specification refers to constraining models with pre-existing data, both within and outside autism research, with more elaborate models and more veridical measures, and with longitudinal data collection. Quantification refers to using continuous measures of both psychological causes and effects, as well as weighted graphs. It avoids “universality and uniqueness” assumptions that a single cognitive difference would be responsible for a heterogeneous and complex behavioral phenotype. Integration of multiple explanatory paths within a single model helps the field examine for multiple contributors to a single behavioral feature or to multiple behavioral features. It also allows integration of explanatory theories across multiple current-day diagnoses and as well as typical development.

show abstract

Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify its “Epidemic Rates”

Cited by 5 publications

References 98 publications

Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Neuropsychiatric Disorders

Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Neuropsychiatric Disorders

Sensing Echoes: Temporal Misalignment in Auditory Brainstem Responses as the Earliest Marker of Neurodevelopmental Derailment

Evaluating Causal Psychological Models: A Study of Language Theories of Autism Using a Large Sample

Contact Info

Product

Resources

About