Abstract Autism is marked by overgrowth of the brain at the earliest ages but not at older ages when decreases in structural volumes and neuron numbers are observed instead. This has led to the ...theory of age-specific anatomic abnormalities in autism. Here we report age-related changes in brain size in autistic and typical subjects from 12 months to 50 years of age based on analyses of 586 longitudinal and cross-sectional MRI scans. This dataset is several times larger than the largest autism study to date. Results demonstrate early brain overgrowth during infancy and the toddler years in autistic boys and girls, followed by an accelerated rate of decline in size and perhaps degeneration from adolescence to late middle age in this disorder. We theorize that underlying these age-specific changes in anatomic abnormalities in autism, there may also be age-specific changes in gene expression, molecular, synaptic, cellular, and circuit abnormalities. A peak age for detecting and studying the earliest fundamental biological underpinnings of autism is prenatal life and the first three postnatal years. Studies of the older autistic brain may not address original causes but are essential to discovering how best to help the older aging autistic person. Lastly, the theory of age-specific anatomic abnormalities in autism has broad implications for a wide range of work on the disorder including the design, validation, and interpretation of animal model, lymphocyte gene expression, brain gene expression, and genotype/CNV-anatomic phenotype studies.
Autism spectrum disorder (ASD) is a largely heritable, multistage prenatal disorder that impacts a child’s ability to perceive and react to social information. Most ASD risk genes are expressed ...prenatally in many ASD-relevant brain regions and fall into two categories: broadly expressed regulatory genes that are expressed in the brain and other organs, and brain-specific genes. In trimesters one to three (Epoch-1), one set of broadly expressed (the majority) and brain-specific risk genes disrupts cell proliferation, neurogenesis, migration, and cell fate, while in trimester three and early postnatally (Epoch-2) another set (the majority being brain specific) disrupts neurite outgrowth, synaptogenesis, and the ‘wiring’ of the cortex. A proposed model is that upstream, highly interconnected regulatory ASD gene mutations disrupt transcriptional programs or signaling pathways resulting in dysregulation of downstream processes such as proliferation, neurogenesis, synaptogenesis, and neural activity. Dysregulation of signaling pathways is correlated with ASD social symptom severity. Since the majority of ASD risk genes are broadly expressed, many ASD individuals may benefit by being treated as having a broader medical disorder. An important future direction is the noninvasive study of ASD cell biology.
ASD begins in prenatal life.In Epoch-1 (first to third trimesters), cell proliferation, neurogenesis, cell fate, and migration are disrupted. In Epoch-2 (third trimester and early postnatal life), cortical wiring is disrupted, including neurite outgrowth, synaptogenesis, and neural network organization.ASD is highly heritable. Most ASD risk genes are expressed in prenatal life and fall into two major groups, broadly expressed regulatory genes and brain-specific ones.Broadly expressed regulatory risk genes are the majority of ASD risk genes. In combination with brain-specific risk genes, they drive aberrant proliferation, neurogenesis, cell fate, and migration in Epoch-1. A different set of broadly expressed and brain-specific risk genes disrupt synaptogenesis and cortical wiring in Epoch-2.Broadly expressed risk genes may impact the development and function of other organs as well as the brain.A new hypothesis proposes how Epoch-1 and Epoch-2 ASD risk genes operate to cause prenatal-age abnormalities: the effects of genetic aberrations in broadly expressed genes propagate through regulatory networks and the key signaling pathways of PI3K/AKT, RAS/ERK, and WNT/β-catenin to converge on and dysregulate multiple downstream core prenatal processes.
Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking and unexplained clinical heterogeneity. Here we ...review genetic, genomic, cellular, postmortem, animal model, and cell model evidence that shows ASD begins in the womb. This evidence leads to a new theory that ASD is a multistage, progressive disorder of brain development, spanning nearly all of prenatal life. ASD can begin as early as the 1st and 2nd trimester with disruption of cell proliferation and differentiation. It continues with disruption of neural migration, laminar disorganization, altered neuron maturation and neurite outgrowth, disruption of synaptogenesis and reduced neural network functioning. Among the most commonly reported high-confidence ASD (hcASD) genes, 94% express during prenatal life and affect these fetal processes in neocortex, amygdala, hippocampus, striatum and cerebellum. A majority of hcASD genes are pleiotropic, and affect proliferation/differentiation and/or synapse development. Proliferation and subsequent fetal stages can also be disrupted by maternal immune activation in the 1st trimester. Commonly implicated pathways, PI3K/AKT and RAS/ERK, are also pleiotropic and affect multiple fetal processes from proliferation through synapse and neural functional development. In different ASD individuals, variation in how and when these pleiotropic pathways are dysregulated, will lead to different, even opposing effects, producing prenatal as well as later neural and clinical heterogeneity. Thus, the pathogenesis of ASD is not set at one point in time and does not reside in one process, but rather is a cascade of prenatal pathogenic processes in the vast majority of ASD toddlers. Despite this new knowledge and theory that ASD biology begins in the womb, current research methods have not provided individualized information: What are the fetal processes and early-age molecular and cellular differences that underlie ASD in each individual child? Without such individualized knowledge, rapid advances in biological-based diagnostic, prognostic, and precision medicine treatments cannot occur. Missing, therefore, is what we call ASD Living Biology. This is a conceptual and paradigm shift towards a focus on the abnormal prenatal processes underlying ASD within each living individual. The concept emphasizes the specific need for foundational knowledge of a living child's development from abnormal prenatal beginnings to early clinical stages. The ASD Living Biology paradigm seeks this knowledge by linking genetic and in vitro prenatal molecular, cellular and neural measurements with in vivo post-natal molecular, neural and clinical presentation and progression in each ASD child. We review the first such study, which confirms the multistage fetal nature of ASD and provides the first in vitro fetal-stage explanation for in vivo early brain overgrowth. Within-child ASD Living Biology is a novel research concept we coin here that advocates the integration of in vitro prenatal and in vivo early post-natal information to generate individualized and group-level explanations, clinically useful prognoses, and precision medicine approaches that are truly beneficial for the individual infant and toddler with ASD.
Failure to develop normal language comprehension is an early warning sign of autism, but the neural mechanisms underlying this signature deficit are unknown. This is because of an almost complete ...absence of functional studies of the autistic brain during early development. Using functional magnetic resonance imaging, we previously observed a trend for abnormally lateralized temporal responses to language (i.e. greater activation on the right, rather than the expected left) in a small sample (n = 12) of sleeping 2-3 year olds with autism in contrast to typically developing children, a finding also reported in autistic adults and adolescents. It was unclear, however, if findings of atypical laterality would be observed in a larger sample, and at even earlier ages in autism, such as around the first birthday. Answers to these questions would provide the foundation for understanding how neurofunctional defects of autism unfold, and provide a foundation for studies using patterns of brain activation as a functional early biomarker of autism. To begin to examine these issues, a prospective, cross-sectional design was used in which brain activity was measured in a large sample of toddlers (n = 80) during the presentation of a bedtime story during natural sleep. Forty toddlers with autism spectrum disorder and 40 typically developing toddlers ranging in age between 12-48 months participated. Any toddler with autism who participated in the imaging experiment prior to final diagnosis was tracked and diagnoses confirmed at a later age. Results indicated that at-risk toddlers later diagnosed as autistic display deficient left hemisphere response to speech sounds and have abnormally right-lateralized temporal cortex response to language; this defect worsens with age, becoming most severe in autistic 3- and 4-year-olds. Typically developing children show opposite developmental trends with a tendency towards greater temporal cortex response with increasing age and maintenance of left-lateralized activation with age. We have now demonstrated lateralized abnormalities of temporal cortex processing of language in autism across two separate samples, including a large sample of young infants who later are diagnosed with autism, suggesting that this pattern may reflect a fundamental early neural developmental pathology in autism.
In higher functioning individuals with autism, a striking disparity exists between impaired social and emotional abilities and relatively preserved sustained attention and goal-directed cognitive ...abilities. As these two functional domains appear to map onto two distinct large-scale brain networks, the Task-Negative Network and the Task-Positive Network, respectively, we examined their intrinsically defined functional organization in individuals with autism. Using resting functional connectivity MRI (fcMRI), we found that, in autism, there was altered functional organization of the network involved in social and emotional processing, but no group difference in the functional organization of the network involved in sustained attention and goal-directed cognition. We suggest that these findings might serve to relate the seemingly disparate strengths and weaknesses of the autistic behavioral, perceptual, and cognitive phenotype into a tractable neurofunctional framework. These results also highlight the usefulness of resting fcMRI for studying the brain in neuropsychiatric and neurodevelopmental disorders.
Multiple studies have reported increased brain size in autism, while others have found no difference from normal. These conflicting results may be due to a lack of accounting for age-related changes ...in brain enlargement, use of small sample sizes, or differences in data acquisition methods.
Reports of autism head circumference (HC), magnetic resonance imaging (MRI), and post-mortem brain weight (BW) that met specific criteria were identified and analyzed. Percent difference from normal values (%Diff) and standardized mean differences (SMD) were calculated to compare brain size across studies and measurement methods. Curve fitting, analysis of variance, and heterogeneity analyses were applied to assay the effects of age and measurement type on reported brain size in autism.
A fitted curve of HC and MRI %Diff values from 15 studies revealed a largely consistent pattern of brain size changes. Specifically, brain size in autism was slightly reduced at birth, dramatically increased within the first year of life, but then plateaued so that by adulthood the majority of cases were within normal range. Analysis of variance of MRI and post-mortem %Diff values by age group (young child, older child, adult) and measurement type (MRI, BW) revealed a significant main effect of both age and measurement type, with the youngest ages (2–5) showing the greatest deviation from normal. Random effects heterogeneity analysis revealed a significant effect of age on HC and MRI SMD.
These findings reveal a period of pathological brain growth and arrest in autism that is largely restricted to the first years of life, before the typical age of clinical identification. Study of the older autistic brain, thus, reflects the outcome, rather than the process, of pathology. Future research focusing on this early process of brain pathology will likely be critical to elucidate the etiology of autism.
Universal early screening for autism spectrum disorder (ASD) in primary care is becoming increasingly common and is believed to be a pivotal step toward early treatment. However, the diagnostic ...stability of ASD in large cohorts from the general population, particularly in those younger than 18 months, is unknown. Changes in the phenotypic expression of ASD across early development compared with toddlers with other delays are also unknown.
To examine the diagnostic stability of ASD in a large cohort of toddlers starting at 12 months of age and to compare this stability with that of toddlers with other disorders, such as developmental delay.
In this prospective cohort study performed from January 1, 2006, to December 31, 2018, a total of 2241 toddlers were referred from the general population through a universal screening program in primary care or community referral. Eligible toddlers received their first diagnostic evaluation between 12 and 36 months of age and had at least 1 subsequent evaluation.
Diagnosis was denoted after each evaluation visit as ASD, ASD features, language delay, developmental delay, other developmental issue, typical sibling of an ASD proband, or typical development.
Diagnostic stability coefficients were calculated within 2-month age bands, and logistic regression models were used to explore the associations of sex, age, diagnosis at first visit, and interval between first and last diagnosis with stability. Toddlers with a non-ASD diagnosis at their first visit diagnosed with ASD at their last were designated as having late-identified ASD.
Among the 1269 toddlers included in the study (918 72.3% male; median age at first evaluation, 17.6 months interquartile range, 14.0-24.4 months; median age at final evaluation, 36.2 months interquartile range, 33.4-40.9 months), the overall diagnostic stability for ASD was 0.84 (95% CI, 0.80-0.87), which was higher than any other diagnostic group. Only 7 toddlers (1.8%) initially considered to have ASD transitioned into a final diagnosis of typical development. Diagnostic stability of ASD within the youngest age band (12-13 months) was lowest at 0.50 (95% CI, 0.32-0.69) but increased to 0.79 by 14 months and 0.83 by 16 months (age bands of 12 vs 14 and 16 months; odds ratio, 4.25; 95% CI, 1.59-11.74). A total of 105 toddlers (23.8%) were not designated as having ASD at their first visit but were identified at a later visit.
The findings suggest that an ASD diagnosis becomes stable starting at 14 months of age and overall is more stable than other diagnostic categories, including language or developmental delay. After a toddler is identified as having ASD, there may be a low chance that he or she will test within typical levels at 3 years of age. This finding opens the opportunity to test the impact of very early-age treatment of ASD.
Autism most commonly appears by 2 to 3 years of life, at which time the brain is already abnormally large. This raises the possibility that brain overgrowth begins much earlier, perhaps before the ...first clinically noticeable behavioral symptoms.
To determine whether pathological brain overgrowth precedes the first clinical signs of autism spectrum disorder (ASD) and whether the rate of overgrowth during the first year is related to neuroanatomical and clinical outcome in early childhood.
Head circumference (HC), body length, and body weight measurements during the first year were obtained from the medical records of 48 children with ASD aged 2 to 5 years who had participated in magnetic resonance imaging studies. Of these children, 15 (longitudinal group) had measurements at 4 periods during infancy: birth, 1 to 2 months, 3 to 5 months, and 6 to 14 months; and 33 (partial HC data group) had measurements at birth and 6 to 14 months (n = 7), and at birth only (n = 28).
Age-related changes in infants with ASD who had multiple-age measurements, and the relationship of these changes to brain anatomy and clinical and diagnostic outcome at 2 to 5 years were evaluated by using 2 nationally recognized normative databases: cross-sectional normative data from a national survey and longitudinal data of individual growth.
Compared with normative data of healthy infants, birth HC in infants with ASD was significantly smaller (z = -0.66, P<.001); after birth, HC increased 1.67 SDs and mean HC was at the 84th percentile by 6 to 14 months. Birth HC was related to cerebellar gray matter volume at 2 to 5 years, although the excessive increase in HC between birth and 6 to 14 months was related to greater cerebral cortex volume at 2 to 5 years. Within the ASD group, every child with autistic disorder had a greater increase in HC between birth and 6 to 14 months (mean SD, 2.19 0.98) than infants with pervasive developmental disorder-not otherwise specified (0.58 0.35). Only 6% of the individual healthy infants in the longitudinal data showed accelerated HC growth trajectories (>2.0 SDs) from birth to 6 to 14 months; 59% of infants with autistic disorder showed these accelerated growth trajectories.
The clinical onset of autism appears to be preceded by 2 phases of brain growth abnormality: a reduced head size at birth and a sudden and excessive increase in head size between 1 to 2 months and 6 to 14 months. Abnormally accelerated rate of growth may serve as an early warning signal of risk for autism.
Several regions of the brain (including medial prefrontal cortex, rostral anterior cingulate, posterior cingulate, and precuneus) are known to have high metabolic activity during rest, which is ...suppressed during cognitively demanding tasks. With functional magnetic resonance imaging (fMRI), this suppression of activity is observed as "deactivations," which are thought to be indicative of an interruption of the mental activity that persists during rest. Thus, measuring deactivation provides a means by which rest-associated functional activity can be quantitatively examined. Applying this approach to autism, we found that the autism group failed to demonstrate this deactivation effect. Furthermore, there was a strong correlation between a clinical measure of social impairment and functional activity within the ventral medial prefrontal cortex. We speculate that the lack of deactivation in the autism group is indicative of abnormal internally directed processes at rest, which may be an important contribution to the social and emotional deficits of autism.
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