A longitudinal study of pupillary light reflex in 6- to 24-month children.

Pupillary light reflex (PLR) is an involuntary response where the pupil size changes with luminance. Studies have shown that PLR response was altered in children with autism spectrum disorders (ASDs) and other neurological disorders. However, PLR in infants and toddlers is still understudied. We conducted a longitudinal study to investigate PLR in children of 6-24 months using a remote pupillography device. The participants are categorized into two groups. The 'high risk' (HR) group includes children with one or more siblings diagnosed with ASDs; whereas the 'low risk' (LR) group includes children without an ASD diagnosis in the family history. The participants' PLR was measured every six months until the age of 24 months. The results indicated a significant age effect in multiple PLR parameters including resting pupil radius, minimal pupil radius, relative constriction, latency, and response time. In addition, the HR group had a significantly larger resting and minimal pupil size than the LR group. The experimental data acquired in this study revealed not only general age-related PLR changes in infants and toddlers, but also different PLRs in children with a higher risk of ASD.

Ensemble statistical and subspace clustering model for analysis of autism spectrum disorder phenotypes.

Heterogeneity in Autism Spectrum Disorder (ASD) is complex including variability in behavioral phenotype as well as clinical, physiologic, and pathologic parameters. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) now diagnoses ASD using a 2-dimensional model based social communication deficits and fixated interests and repetitive behaviors. Sorting out heterogeneity is crucial for study of etiology, diagnosis, treatment and prognosis. In this paper, we present an ensemble model for analyzing ASD phenotypes using several machine learning techniques and a k-dimensional subspace clustering algorithm. Our ensemble also incorporates statistical methods at several stages of analysis. We apply this model to a sample of 208 probands drawn from the Simon Simplex Collection Missouri Site patients. The results provide useful evidence that is helpful in elucidating the phenotype complexity within ASD. Our model can be extended to other disorders that exhibit a diverse range of heterogeneity.

Facial structure analysis separates autism spectrum disorders into meaningful clinical subgroups.

Varied cluster analysis were applied to facial surface measurements from 62 prepubertal boys with essential autism to determine whether facial morphology constitutes viable biomarker for delineation of discrete Autism Spectrum Disorders (ASD) subgroups. Earlier study indicated utility of facial morphology for autism subgrouping (Aldridge et al. in Mol Autism 2(1):15, 2011). Geodesic distances between standardized facial landmarks were measured from three-dimensional stereo-photogrammetric images. Subjects were evaluated for autism-related symptoms, neurologic, cognitive, familial, and phenotypic variants. The most compact cluster is clinically characterized by severe ASD, significant cognitive impairment and language regression. This verifies utility of facially-based ASD subtypes and validates Aldridge et al.'s severe ASD subgroup, notwithstanding different techniques. It suggests that language regression may define a unique ASD subgroup with potential etiologic differences.

Atypical pupillary light reflex and heart rate variability in children with autism spectrum disorder.

We investigated pupillary light reflex (PLR) in 152 children with ASD, 116 typically developing (TD) children, and 36 children with non-ASD neurodevelopmental disorders (NDDs). Heart rate variability (HRV) was measured simultaneously to study potential impairments in the autonomic nervous system (ANS) associated with ASD. The results showed that the ASD group had significantly longer PLR latency, reduced relative constriction amplitude, and shorter constriction/redilation time than those of the TD group. Similar atypical PLR parameters were observed in the NDD group. A significant age effect on PLR latency was observed in children younger than 9 years in the TD group, but not in the ASD and NDD groups. Atypical HRV parameters were observed in the ASD and NDD groups. A significant negative correlation existed between the PLR constriction amplitude and average heart rate in children with an ASD, but not in children with typical development.

Facial phenotypes in subgroups of prepubertal boys with autism spectrum disorders are correlated with clinical phenotypes.

BACKGROUND: The brain develops in concert and in coordination with the developing facial tissues, with each influencing the development of the other and sharing genetic signaling pathways. Autism spectrum disorders (ASDs) result from alterations in the embryological brain, suggesting that the development of the faces of children with ASD may result in subtle facial differences compared to typically developing children. In this study, we tested two hypotheses. First, we asked whether children with ASD display a subtle but distinct facial phenotype compared to typically developing children. Second, we sought to determine whether there are subgroups of facial phenotypes within the population of children with ASD that denote biologically discrete subgroups. METHODS: The 3dMD cranial System was used to acquire three-dimensional stereophotogrammetric images for our study sample of 8- to 12-year-old boys diagnosed with essential ASD (n = 65) and typically developing boys (n = 41) following approved Institutional Review Board protocols. Three-dimensional coordinates were recorded for 17 facial anthropometric landmarks using the 3dMD Patient software. Statistical comparisons of facial phenotypes were completed using Euclidean Distance Matrix Analysis and Principal Coordinates Analysis. Data representing clinical and behavioral traits were statistically compared among groups by using χ2 tests, Fisher's exact tests, Kolmogorov-Smirnov tests and Student's t-tests where appropriate. RESULTS: First, we found that there are significant differences in facial morphology in boys with ASD compared to typically developing boys. Second, we also found two subgroups of boys with ASD with facial morphology that differed from the majority of the boys with ASD and the typically developing boys. Furthermore, membership in each of these distinct subgroups was correlated with particular clinical and behavioral traits. CONCLUSIONS: Boys with ASD display a facial phenotype distinct from that of typically developing boys, which may reflect alterations in the prenatal development of the brain. Subgroups of boys with ASD defined by distinct facial morphologies correlated with clinical and behavioral traits, suggesting potentially different etiologies and genetic differences compared to the larger group of boys with ASD. Further investigations into genes involved in neurodevelopment and craniofacial development of these subgroups will help to elucidate the causes and significance of these subtle facial differences.

Development and validation of a measure of dysmorphology: useful for autism subgroup classification.

Autism spectrum disorders (ASD) comprise a class of neurodevelopmental disorders that can originate from a variety of genetic and environmental causes. To delineate autism's heterogeneity we have looked for biologically-based phenotypes found in consistent proportions of ASD individuals. One informative phenotype is that of generalized dysmorphology, based on whole body examinations by medical geneticists trained in the nuances of anomalous embryologic development. We identified a need for a dysmorphology measure that could be completed by medical clinicians not extensively trained in dysmorphology that would still retain the level of sensitivity and specificity of the comprehensive dysmorphology examination. Based on expert-derived consensus dysmorphology designation of 222 autism patients and a classification validation study of 30 subjects by four dysmorphologists, we determined that dysmorphology designations based on body areas provided superior inter-rater reliability. Using 34 body area designations, we performed a classification and regression tree (CART) analysis to construct a scoring algorithm. Compared to the consensus classification, the model performed with 81% sensitivity and 99% specificity, and classification of a replication dataset of 31 ASD individuals performed well, with 82% sensitivity and 95% specificity. The autism dysmorphology measure (ADM) directs the clinician to score 12 body areas sequentially to arrive at a determination of "dysmorphic" or "nondysmorphic." We anticipate the ADM will permit clinicians to differentiate accurately between dysmorphic and nondysmorphic individuals-allowing better diagnostic classification, prognostication, recurrence risk assessment, and laboratory analysis decisions-and research scientists to better define more homogeneous autism subtypes.

Defining autism subgroups: a taxometric solution.

The purpose of the present study was to determine which behavioral and physical phenotypes would be most likely to divide the ASD population into discrete subgroups. The taxometric methods of Maximum Covariance (MAXCOV) and Minus Mean Below A Cut (MAMBAC) were employed to test for categorical versus continuous variation of each phenotype across the ASD population. Data was retrieved from the Autism Genetic Resource Exchange and the University of Missouri Autism Database. The results of our analyses support subgrouping subjects based on variation in social interaction/communication, intelligence, and essential/complex phenotype; in contrast, subjects varied continuously in insistence on sameness, repetitive sensory motor actions, language acquisition, and, tentatively, adaptive functioning. Stratifying ASD samples based on taxometric results should increase power in gene-finding studies and aid in treatment efficacy research.

Lack of association between Rh status, Rh immune globulin in pregnancy and autism.

Though causes of autism are considered largely genetic, considerable concern remains that exposure to Rh immune globulin (RhIg), which until 2001 in the United States contained the preservative thimerosal, can cause autism. To determine whether mothers of children with autism are more likely to be Rh negative (Rh(-)) or to have received RhIg preserved with thimerosal, which is 49.6% ethyl mercury, we surveyed families of children with an autism spectrum disorder (ASD) ascertained through a University-based autism clinic considered free of ascertainment biases related to type of autism or severity. Between 2004 and 2006, 305 mothers of 321 children with an ASD agreed to participate in a telephone interview. Analysis of complete records including the blood group status and RhIg exposure of 214 families showed that Rh(-) status is no higher in mothers of children with autism than in the general population, exposure to antepartum RhIg, preserved with thimerosal is no higher for children with autism and pregnancies are no more likely to be Rh incompatible. This was also true for autism subgroups defined by behavioral phenotype, gender, IQ, regressive onset, head circumference, dysmorphology, birth status, essential, or complex phenotype. These findings support the consensus that exposure to ethylmercury in thimerosal is not the cause of the increased prevalence of autism. These data are important not only for parents in this country but also for the international health community where thimerosal continues to be used to preserve multi-dose vials which in turn makes vaccines affordable.

Autism families with a high incidence of alcoholism.

To determine the significance of neuropsychiatric disorders in autism families, we analyzed 167 pedigrees ascertained through an autistic child; 39% had alcoholism in patterns consistent with transmission of a genetic trait. Children from high alcoholism families were more likely to have the onset of their autistic behavior occur with a loss of language (52.5% vs. 35.8%, p = 0.04). This occurred primarily in families where the mother was alcoholic (80% vs. 40%, p = 0.05), suggesting an association between maternal alcoholism and regressive onset autism. Children from high alcoholism families were less likely to be macrocephalic (14.7% vs. 40.6%, p = 0.0006). Children from high alcohol and low alcohol families did not differ in dysmorphology status, IQ, sex ratio or sib recurrence risk.