Autism with intellectual disability related to dynamics of head circumference growth during early infancy

The early life growth of head circumference, weight, and height in infants with autism spectrum disorders: a systematic review

BACKGROUNDS

The Autism spectrum disorder (ASD) prevalence has increased significantly over the past two decades. This review summarizes the current knowledge of the association between the early life growth of head circumference (HC), weight, and height with ASD in infants.

METHODS

PubMed, Scopus, Science Direct, and Google Scholar databases were searched up to November 2021 using relevant keywords. All original articles are written in English evaluating the early life growth of HC, weight, and height in infants with ASD were eligible for the present review.

RESULTS

Totally, 23 articles involving 4959 infants were included in this review. Of 13 studies that evaluated HC of infants at birth, 10 studies (83.33%) showed that the HC at the birth of autistic children was similar to that of the average found in the control group. Among 21 studies that evaluated the HC and weight status in infants, 19 studies (90.47%) showed that autistic children had larger HC and weight than the control group or abnormal acceleration of head growth during infancy. Height growth of infants was investigated in 13 studies, of which 10 cases (76.92%) reported that infants with ASD were significantly longer than control groups. Most of he included studies had a good quality.

CONCLUSIONS

The findings suggest that in infants with ASD, without the contribution of birth growth factors and sex of the child, the growth of HC, weight, and height probably was faster than in infants with normal development, in early life. Therefore, these measurements might be useful as initial predictive biomarkers for the risk of developing ASD.

Phenotypic Subtyping and Re-Analysis of Existing Methylation Data from Autistic Probands in Simplex Families Reveal ASD Subtype-Associated Differentially Methylated Genes and Biological Functions

Autism spectrum disorder (ASD) describes a group of neurodevelopmental disorders with core deficits in social communication and manifestation of restricted, repetitive, and stereotyped behaviors. Despite the core symptomatology, ASD is extremely heterogeneous with respect to the severity of symptoms and behaviors. This heterogeneity presents an inherent challenge to all large-scale genome-wide omics analyses. In the present study, we address this heterogeneity by stratifying ASD probands from simplex families according to the severity of behavioral scores on the Autism Diagnostic Interview-Revised diagnostic instrument, followed by re-analysis of existing DNA methylation data from individuals in three ASD subphenotypes in comparison to that of their respective unaffected siblings. We demonstrate that subphenotyping of cases enables the identification of over 1.6 times the number of statistically significant differentially methylated regions (DMR) and DMR-associated genes (DAGs) between cases and controls, compared to that identified when all cases are combined. Our analyses also reveal ASD-related neurological functions and comorbidities that are enriched among DAGs in each phenotypic subgroup but not in the combined case group. Moreover, relational gene networks constructed with the DAGs reveal signaling pathways associated with specific functions and comorbidities. In addition, a network comprised of DAGs shared among all ASD subgroups and the combined case group is enriched in genes involved in inflammatory responses, suggesting that neuroinflammation may be a common theme underlying core features of ASD. These findings demonstrate the value of phenotype definition in methylomic analyses of ASD and may aid in the development of subtype-directed diagnostics and therapeutics.

Association of Maternal Insecticide Levels With Autism in Offspring From a National Birth Cohort

OBJECTIVE

Autism is a complex neurodevelopmental disorder with a largely unknown etiology. To date, few studies have investigated prenatal exposure to toxins and risk of autism by using maternal biomarkers of exposure. Persistent organic pollutants are lipophilic halogenated organic compounds and include the insecticide dichlorodiphenyltrichloroethane (DDT), as well as its metabolite p,p'-dichlorodiphenyl dichloroethylene (p,p'-DDE), and polychlorinated biphenyls (PCBs). The objective of this study was to test whether elevated maternal levels of persistent organic pollutants are associated with autism among offspring.

METHOD

The investigation was derived from the Finnish Prenatal Study of Autism, a national birth cohort study based on a nested case-control design. Cases of autism among children born between 1987 and 2005 were ascertained by national registry linkages. In cases of childhood autism and matched control subjects (778 matched case-control pairs), maternal serum specimens from early pregnancy were assayed for levels of p,p'-DDE and total levels of PCBs.

RESULTS

The odds of autism among offspring were significantly increased with maternal p,p'-DDE levels that were in the highest 75th percentile, with adjustment for maternal age, parity, and history of psychiatric disorders (odds ratio=1.32, 95% CI=1.02, 1.71). The odds of autism with intellectual disability were increased by greater than twofold with maternal p,p'-DDE levels above this threshold (odds ratio=2.21, 95% CI=1.32, 3.69). There was no association between total levels of maternal PCBs and autism.

CONCLUSIONS

These findings provide the first biomarker-based evidence that maternal exposure to insecticides is associated with autism among offspring. Although further research is necessary to replicate this finding, this study has implications for the prevention of autism and may provide a better understanding of its pathogenesis.

Derivative estimation for longitudinal data analysis: Examining features of blood pressure measured repeatedly during pregnancy

Estimating velocity and acceleration trajectories allows novel inferences in the field of longitudinal data analysis, such as estimating change regions rather than change points, and testing group effects on nonlinear change in an outcome (ie, a nonlinear interaction). In this article, we develop derivative estimation for 2 standard approaches-polynomial mixed models and spline mixed models. We compare their performance with an established method-principal component analysis through conditional expectation through a simulation study. We then apply the methods to repeated blood pressure (BP) measurements in a UK cohort of pregnant women, where the goals of analysis are to (i) identify and estimate regions of BP change for each individual and (ii) investigate the association between parity and BP change at the population level. The penalized spline mixed model had the lowest bias in our simulation study, and we identified evidence for BP change regions in over 75% of pregnant women. Using mean velocity difference revealed differences in BP change between women in their first pregnancy compared with those who had at least 1 previous pregnancy. We recommend the use of penalized spline mixed models for derivative estimation in longitudinal data analysis.

Altered growth trajectory of head circumference during infancy and schizophrenia in a National Birth Cohort

Identification of abnormalities in the developmental trajectory during infancy of future schizophrenia cases offers the potential to reveal pathogenic mechanisms of this disorder. Previous studies of head circumference in pre-schizophrenia were limited to measures at birth. The use of growth acceleration of head circumference (defined as the rate of change in head circumference) provides a more informative representation of the maturational landscape of this measure compared to studies based on static head circumference measures. To date, however, no study has examined whether HC growth acceleration differs between pre-schizophrenia cases and controls. In the present study, we employed a nested case control design of a national birth cohort in Finland. Cases with schizophrenia or schizoaffective disorder (N=375) and controls (N=375) drawn from the birth cohort were matched 1:1 on date of birth (within 1month), sex, and residence in Finland at case diagnosis. Longitudinal data were obtained on head circumference from birth through age 1. Data were analyzed using a new nonparametric Bayesian inversion method which allows for a detailed understanding of growth dynamics. Adjusting for growth velocity of height and weight, and gestational age, there was significantly accelerated growth of head circumference in females with schizophrenia from birth to 2months; the findings remained significant following Bonferroni correction (p<0.0125). This is the first study to report abnormal HC growth acceleration, a more sensitive measure of somatic developmental deviation of this measure, in schizophrenia.