Clinical, socio-demographic, and parental correlates of early autism traits

Gale-Grant, O.; Chew, A.; Falconer, S.; Franca, L. G. S.; Fenn-Moltu, S.; Hadaya, L.; Harper, N.; Ciarrusta, J.; Charman, T.; Murphy, D.; Arichi, T.; McAlonan, G.; Nosarti, C.; Edwards, D.; Batalle, D.

doi:10.1101/2022.09.26.508121

bioRxiv · 10.1101/2022.09.26.508121

Clinical, socio-demographic, and parental correlates of early autism traits

Gale-Grant, O.·Chew, A.·Falconer, S.·Franca, L. G. S.·Fenn-Moltu, S.·Hadaya, L.·Harper, N.·Ciarrusta, J.·Charman, T.·Murphy, D.·Arichi, T.·McAlonan, G.·Nosarti, C.·Edwards, D.·Batalle, D.

View original source ↗Export metadata ↓

Abstract

BackgroundAutism traits emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits in the general population may improve our understanding of the mechanisms underlying atypical neurodevelopment. MethodsClinical, socio-demographic, and parental information was collected at birth from 536 toddlers in London, UK (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA). ResultsA multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 36% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, parenting style and social deprivation were positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score. LimitationsThe Q-CHAT is parent rated and is therefore a subjective opinion rather than a clinical assessment. We measured Q-CHAT at a single timepoint, and to date no participant has been followed up in later childhood, so we are focused purely on emerging traits rather than clinical autism diagnoses. ConclusionsAutism traits are common at age 18 months, and greater emergence is specifically related to exposure to early life adversity.

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Gale-Grant, O., Chew, A., Falconer, S., Franca, L. G. S., Fenn-Moltu, S., Hadaya, L., Harper, N., Ciarrusta, J., Charman, T., Murphy, D., Arichi, T., McAlonan, G., Nosarti, C., Edwards, D., Batalle, D.. 2022-09-27. Clinical, socio-demographic, and parental correlates of early autism traits. https://doi.org/10.1101/2022.09.26.508121

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

A systems-level model of sleep-dependent memory-consolidation failure in neurodegeneration: the spindle-slow-oscillation decoupling cascade dissociates amyloid and tau

During non-rapid-eye-movement (NREM) sleep, the temporal coupling of cortical slow oscillations (SOs), thalamic spindles, and hippocampal sharp wave ripples drives the consolidation of declarative memories. This coupling degrades in ageing and Alzheimers disease (AD), and although A{beta} and tau leave dissociable signatures in human sleep, the mechanisms by which progressive pathology dismantles the consolidation machinery are difficult to isolate experimentally, and have not to our knowledge been reproduced in a model that can be perturbed directly. We built a systems-level model in which cortical SOs and thalamic spindles are generated by reduced oscillators, hippocampal ripples replay encoded spike sequences, and the measured per-event SO-spindle timing alignment causally gates spike-timing dependent plasticity on cortical sequence synapses. A post-sleep cued-recall test reads out consolidation. Five neurodegeneration parameters (amyloid, tau, synaptic density, GABAergic inhibition, cholinergic tone) map to dis tinct mechanisms grounded in the human and animal literature. The model reproduces graded healthy consolidation and a progressive collapse in which coupling, slow-wave power, spindle power and recall fall monotonically and the overnight memory effect flips from consolidation to net forgetting, with weak memories failing first. Scrambling SO-spindle timing while holding oscillation power fixed abolishes consolidation, establishing that coupling timing, rather than oscillation power, is what the plasticity gate depends on within the model. A{beta} and tau impair memory through orthogonal signatures (A{beta} collapses slow-wave power while sparing replay order, tau the reverse) and this orthogonality holds across the entire A{beta} x tau plane and survives simultaneous {+/-}50% resampling of every mapping coefficient (40/40 samples), so it is not an artefact of a single calibration point. The model yields a falsifiable clinical prediction: closed-loop slow-oscillation enhancement rescues memory only when the deficit is amplitude/coupling-dominated, not when it is replay(tau)-dominated, despite normalising slow-wave power in both cases. Because the therapy arms dissociate coupling from memory benefit, the model also cautions against adopting SO-spindle coupling as a standalone surrogate endpoint.

neuroscience↗

bioRxiv2026

Toxicity of MAPT 4R RNA Contributes to Motor Neuron Degeneration in ALS

MAPT (Tau) dysregulation is implicated in several neurodegenerative diseases, but its contribution to amyotrophic lateral sclerosis (ALS) is poorly understood. Here we show that mRNA isoforms encoding 4-repeat (4R) Tau are upregulated and cytoplasmically enriched in iPSC-derived motor neurons (MNs) from VCP-mutant and sporadic ALS, without a corresponding change in Tau protein. Using splice-switching antisense oligonucleotides and isoform-specific siRNAs, we find that enhanced 4R expression reduces MN viability, whereas its selective knockdown improves survival, with kinetics more consistent with an RNA-intrinsic effect than altered protein synthesis. Exon 10-containing MAPT RNA shows increased predicted secondary structure, self-association and altered Tau biocondensation in vitro. In post-mortem ALS cervical spinal cord, increased relative exon 10 usage is associated with a higher-risk clinical phenotype and shorter disease duration These findings identify an isoform-specific contribution of MAPT to MN vulnerability in ALS and nominate 4R MAPT RNA as a therapeutic target.

neuroscience↗

bioRxiv2026

State dependant modulation of optic flow-processing lobula plate cells in butterflies

Increasing experimental evidence suggests that biological systems cancel predictable components of sensory signals while maintaining sensitivity to externally induced state changes. This strategy provides task-specific sensor responses for posture, locomotion, and gaze control. A prime example is found in interneurons that respond to visual image shifts resulting from the relative motion between an animal's eyes and its visual surroundings. Such optic flow-processing interneurons, found across phyla and are particularly well characterized in Dipteran and other flying insects. We studied optic flow-processing interneurons in the Monarch butterfly whose large and highly contrasted wings sweep through the visual field with every wing-beat cycle, potentially obscuring interneuron output signals. Our results show baseline spiking activity increases when animals flap their wings, and individual spikes are phase-locked to the wing-beat cycle, even in the dark, when no visual motion input is available. A qualitative estimate of the interneurons' response to directional wing motion through its receptive field is not sufficient to explain the recorded activity patterns. Our results suggest that an additional internal signal suppresses responses to wing-induced visual motion to support effective vision-based stabilization reflexes. These findings support the principle that self-generated signals are suppressed while sensitivity to external modulation is preserved.

neuroscience↗