A prospective study of fetal head growth, autistic traits and autism spectrum disorder

Fetal brain growth and infant autistic traits

BACKGROUND

Structural differences exist in the brains of autistic individuals. To date only a few studies have explored the relationship between fetal brain growth and later infant autistic traits, and some have used fetal head circumference (HC) as a proxy for brain development. These findings have been inconsistent. Here we investigate whether fetal subregional brain measurements correlate with autistic traits in toddlers.

METHODS

A total of 219 singleton pregnancies (104 males and 115 females) were recruited at the Rosie Hospital, Cambridge, UK. 2D ultrasound was performed at 12-, 20- and between 26 and 30 weeks of pregnancy, measuring head circumference (HC), ventricular atrium (VA) and transcerebellar diameter (TCD). A total of 179 infants were followed up at 18-20 months of age and completed the quantitative checklist for autism in toddlers (Q-CHAT) to measure autistic traits.

RESULTS

Q-CHAT scores at 18-20 months of age were positively associated with TCD size at 20 weeks and with HC at 28 weeks, in univariate analyses, and in multiple regression models which controlled for sex, maternal age and birth weight.

LIMITATIONS

Due to the nature and location of the study, ascertainment bias could also have contributed to the recruitment of volunteer mothers with a higher than typical range of autistic traits and/or with a significant interest in the neurodevelopment of their children.

CONCLUSION

Prenatal brain growth is associated with toddler autistic traits and this can be ascertained via ultrasound starting at 20 weeks gestation.

Pre-autism: What a paediatrician should know about early diagnosis of autism‎

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as "pre-autism" when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

Sex differences in placenta-derived markers and later autistic traits in children

Autism is more prevalent in males and males on average score higher on measures of autistic traits. Placental function is affected significantly by the sex of the fetus. It is unclear if sex differences in placental function are associated with sex differences in the occurrence of autistic traits postnatally. To assess this, concentrations of angiogenesis-related markers, placental growth factor (PlGF) and soluble fms-like tyrosine kinase (sFlt-1) were assessed in maternal plasma of expectant women in the late 1^st (mean= 13.5 [SD = 2.0] weeks gestation) and 2^nd trimesters (mean=20.6 [SD = 1.2] weeks gestation), as part of the Generation R Study, Rotterdam, the Netherlands. Subsequent assessment of autistic traits in the offspring at age 6 was performed with the 18-item version of the Social Responsiveness Scale (SRS). Associations of placental protein concentrations with autistic traits were tested in sex-stratified and cohort-wide regression models. Cases with pregnancy complications or a later autism diagnosis (n = 64) were also assessed for differences in placenta-derived markers. sFlt-1 levels were significantly lower in males in both trimesters but showed no association with autistic traits. PlGF was significantly lower in male pregnancies in the 1^st trimester, and significantly higher in the 2^nd trimester, compared to female pregnancies. Higher PlGF levels in the 2^nd trimester and the rate of PlGF increase were both associated with the occurrence of higher autistic traits (PlGF-2^nd: n = 3469,b = 0.24 [SE = 0.11], p = 0.03) in both unadjusted and adjusted linear regression models that controlled for age, sex, placental weight and maternal characteristics. Mediation analyses showed that higher autistic traits in males compared to females were partly explained by higher PlGF or a faster rate of PlGF increase in the second trimester (PlGF-2^nd: n = 3469, ACME: b = 0.005, [SE = 0.002], p = 0.004). In conclusion, higher PlGF levels in the 2^nd trimester and a higher rate of PlGF increase are associated with both being male, and with a higher number of autistic traits in the general population.

The genetics of autism and steroid-related traits in prenatal and postnatal life

Background

Autism likelihood is a largely heritable trait. Autism prevalence has a skewed sex ratio, with males being diagnosed more often than females. Steroid hormones play a mediating role in this, as indicated by studies of both prenatal biology and postnatal medical conditions in autistic men and women. It is currently unclear if the genetics of steroid regulation or production interact with the genetic liability for autism.

Methods

To address this, two studies were conducted using publicly available datasets, which focused respectively on rare genetic variants linked to autism and neurodevelopmental conditions (study 1) and common genetic variants (study 2) for autism. In Study 1 an enrichment analysis was conducted, between autism-related genes (SFARI database) and genes that are differentially expressed (FDR<0.1) between male and female placentas, in 1st trimester chorionic villi samples of viable pregnancies (n=39). In Study 2 summary statistics of genome wide association studies (GWAS) were used to investigate the genetic correlation between autism and bioactive testosterone, estradiol and postnatal PlGF levels, as well as steroid-related conditions such as polycystic ovaries syndrome (PCOS), age of menarche, and androgenic alopecia. Genetic correlation was calculated based on LD Score regression and results were corrected for multiple testing with FDR.

Results

In Study 1, there was significant enrichment of X-linked autism genes in male-biased placental genes, independently of gene length (n=5 genes, p<0.001). In Study 2, common genetic variance associated with autism did not correlate to the genetics for the postnatal levels of testosterone, estradiol or PlGF, but was associated with the genotypes associated with early age of menarche in females (b=-0.109, FDR-q=0.004) and protection from androgenic alopecia for males (b=-0.135, FDR-q=0.007).

Conclusion

The rare genetic variants associated with autism appear to interact with placental sex differences, while the common genetic variants associated with autism appear to be involved in the regulation of steroid-related traits. These lines of evidence indicate that the likelihood for autism is partly linked to factors mediating physiological sex differences throughout development.

Prenatal exposure to trans fatty acids and head growth in fetal life and childhood: triangulating confounder-adjustment and instrumental variable approaches

Dietary trans fatty acids (TFAs) are primarily industrially produced and remain abundant in processed food, particularly in low- and middle-income countries. Although TFAs are a cause of adverse cardiometabolic outcomes, little is known about exposure to TFAs in relation to brain development. We aimed to investigate the effect of maternal TFA concentration during pregnancy on offspring head growth in utero and during childhood. In a prospective population-based study in Rotterdam, the Netherlands, with 6900 mother–child dyads, maternal plasma TFA concentration was assessed using gas chromatography in mid-gestation. Offspring head circumference (HC) was measured in the second and third trimesters using ultrasonography; childhood brain morphology was assessed using magnetic resonance imaging at age 10 years. We performed regression analyses adjusting for sociodemographic and lifestyle confounders and instrumental variable (IV) analyses. Our IV analysis leveraged a national policy change that led to a substantial reduction in TFA and occurred mid-recruitment. After adjusting for covariates, maternal TFA concentration during pregnancy was inversely related to fetal HC in the third trimester (mean difference per 1% wt:wt increase: − 0.33, 95% CI − 0.51, − 0.15, cm) and to fetal HC growth from the second to the third trimester (− 0.04, 95% CI − 0.06, − 0.02, cm/week). Consistent findings were obtained with IV analyses, strengthening a causal interpretation. Association between prenatal TFA exposure and HC in the second trimester or global brain volume at age 10 years was inconclusive. Our findings are of important public health relevance as TFA levels in food remain high in many countries.

Maternal age, autistic-like traits and mentalizing as predictors of child autistic-like traits in a population-based cohort

Background

Many empirical studies suggest that higher maternal age increases the likelihood of having an autistic child. However, little is known about factors that may explain this relationship or if higher maternal age is related to the number of autistic-like traits in offspring. One possibility is that mothers who have a higher number of autistic-like traits, including greater challenges performing mentalizing skills, are delayed in finding a partner. The goal of our study is to assess the relationship between maternal age, mentalizing skills and autistic-like traits as independent predictors of the number of autistic-like traits in offspring.

Methods

In a population-based study in the Netherlands, information on maternal age was collected during pre- and perinatal enrolment. Maternal mentalizing skills and autistic-like traits were assessed using the Reading the Mind in the Eyes Test and the Autism Spectrum Quotient, respectively. Autistic-like traits in children were assessed with the Social Responsiveness Scale. A total of 5718 mother/child dyads had complete data (M_agechild = 13.5 years; 50.2% girls).

Results

The relationship between maternal age and autistic-like traits in offspring best fits a U-shaped curve. Furthermore, higher levels of autistic features in mothers are linked to higher levels of autistic-like traits in their children. Lower mentalizing performance in mothers is linked to higher levels of autistic-like traits in their children.

Limitations

We were able to collect data on both autistic-like traits and the mentalizing skills test in a large population of mothers, but we did not collect these data in a large number of the fathers.

Conclusions

The relationships between older and younger mothers may have comparable underlying mechanisms, but it is also possible that the tails of the U-shaped curve are influenced by disparate mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00507-4.

OUP accepted manuscript

Multiple pieces of evidence support the prenatal predisposition of autism spectrum disorder (ASD). Nevertheless, robust data about abnormalities in foetuses later developing into children diagnosed with ASD are lacking. Prenatal ultrasound is an excellent tool to study abnormal foetal development as it is frequently used to monitor foetal growth and identify foetal anomalies throughout pregnancy. We conducted a retrospective case-sibling-control study of children diagnosed with ASD (cases); their own typically developing, closest-in-age siblings (TDS); and typically developing children from the general population (TDP), matched by year of birth, sex and ethnicity to investigate the association between ultrasonography foetal anomalies and ASD. The case group was drawn from all children diagnosed with ASD enrolled at the National Autism Research Center of Israel. Foetal ultrasound data from the foetal anatomy survey were obtained from prenatal ultrasound clinics of Clalit Health Services in southern Israel. The study comprised 659 children: 229 ASD, 201 TDS and 229 TDP. Ultrasonography foetal anomalies were found in 29.3% of ASD cases versus only 15.9% and 9.6% in the TDS and TDP groups [adjusted odds ratio (aOR) = 2.23, 95% confidence interval (CI) = 1.32-3.78, and aOR = 3.50, 95%CI = 2.07-5.91, respectively]. Multiple co-occurring ultrasonography foetal anomalies were significantly more prevalent among ASD cases. Ultrasonography foetal anomalies in the urinary system, heart, and head and brain were the most significantly associated with ASD diagnosis (aORUrinary = 2.08, 95%CI = 0.96-4.50 and aORUrinary = 2.90, 95%CI = 1.41-5.95; aORHeart = 3.72, 95%CI = 1.50-9.24 and aORHeart = 8.67, 95%CI = 2.62-28.63; and aORHead&Brain = 1.96, 95%CI = 0.72-5.30 and aORHead&Brain = 4.67, 95%CI = 1.34-16.24; versus TDS and TDP, respectively). ASD females had significantly more ultrasonography foetal anomalies than ASD males (43.1% versus 25.3%, P = 0.013) and a higher prevalence of multiple co-occurring ultrasonography foetal anomalies (15.7% versus 4.5%, P = 0.011). No sex differences were seen among TDS and TDP controls. ASD foetuses were characterized by a narrower head and a relatively wider ocular-distance versus TDP foetuses (ORBPD = 0.81, 95%CI = 0.70-0.94, and aOROcular distance = 1.29, 95%CI = 1.06-1.57). Ultrasonography foetal anomalies were associated with more severe ASD symptoms. Our findings shed important light on the multiorgan foetal anomalies associated with ASD.

Association Between Abnormal Fetal Head Growth and Autism Spectrum Disorder

OBJECTIVE

Despite evidence for the prenatal onset of abnormal head growth in children with autism spectrum disorder (ASD), studies on fetal ultrasound data in ASD are limited and controversial.

METHOD

We conducted a longitudinal matched case-sibling-control study on prenatal ultrasound biometric measures of children with ASD, and 2 control groups: (1) their own typically developed sibling (TDS) and (2) typically developed population (TDP). The cohort comprised 528 children (72.7% male), 174 with ASD, 178 TDS, and 176 TDP.

RESULTS

During the second trimester, ASD and TDS fetuses had significantly smaller biparietal diameter (BPD) than TDP fetuses (adjusted odds ratio for the z score of BPD [aOR_zBPD] = 0.685, 95% CI = 0.527-0.890, and aOR_zBPD = 0.587, 95% CI = 0.459-0.751, respectively). However, these differences became statistically indistinguishable in the third trimester. Interestingly, head biometric measures varied by sex, with male fetuses having larger heads than female fetuses within and across groups. A linear mixed-effect model assessing the effects of sex and group assignment on fetal longitudinal head growth indicated faster BPD growth in TDS versus both ASD and TDP in male fetuses (β = 0.084 and β = 0.100 respectively; p < .001) but not in female fetuses, suggesting an ASD-sex interaction in head growth during gestation. Finally, fetal head growth showed conflicting correlations with ASD severity in male and female children across different gestation periods, thus further supporting the sex effect on the association between fetal head growth and ASD.

CONCLUSION

Our findings suggest that abnormal fetal head growth is a familial trait of ASD, which is modulated by sex and is associated with the severity of the disorder. Thus, it could serve as an early biomarker for ASD.

Brain morphology, autistic traits, and polygenic risk for autism: A population-based neuroimaging study

Autism spectrum disorders (ASD) are associated with widespread brain alterations. Previous research in our group linked autistic traits with altered gyrification, but without pronounced differences in cortical thickness. Herein, we aim to replicate and extend these findings using a larger and older sample. Additionally, we examined whether (a) brain correlates of autistic traits were associated with polygenic risk scores (PRS) for ASD, and (b) autistic traits are related with brain morphological changes over time in a subset of children with longitudinal data available. The sample included 2400 children from the Generation R cohort. Autistic traits were measured using the Social Responsiveness Scale (SRS) at age 6 years. Gyrification, cortical thickness, surface area, and global morphological measures were obtained from high-resolution structural MRI scans at ages 9-to-12 years. We performed multiple linear regression analyses on a vertex-wise level. Corresponding regions of interest were tested for association with PRS. Results showed that autistic traits were related to (a) lower gyrification in the lateral occipital and the superior and inferior parietal lobes, (b) lower cortical thickness in the superior frontal region, and (c) lower surface area in inferior temporal and rostral middle frontal regions. PRS for ASD and longitudinal analyses showed significant associations that did not survive correction for multiple testing. Our findings support stability in the relationship between higher autistic symptoms and lower gyrification and smaller surface areas in school-aged children. These relationships remained when excluding ASD cases, providing neurobiological evidence for the extension of autistic traits into the general population. LAY SUMMARY: We found that school-aged children with higher levels of autistic traits had smaller total brain volume, cerebellum, cortical thickness, and surface area. Further, we also found differences in the folding patterns of the brain (gyrification). Overall, genetic susceptibility for autism spectrum disorders was not related to these brain regions suggesting that other factors could be involved in their origin. These results remained significant when excluding children with a diagnosis of ASD, providing support for the extension of the relationship between autistic traits and brain findings into the general population.

Does the M-Chat-R Give Important Information for the Diagnosis of the Autism Spectrum Disorder?

Having in mind the rising rates of the incidence for autism worldwide, the early diagnosis of this neuro-developmental disorder is of the high priority. For that purpose, several checklists have been constructed and used. Nevertheless, there are no universal and uniform criteria for assessing and diagnosing autism, and even if there existed, not every country has the resources to manage such an assessment for diagnosis.A recently validated, revised version of the M-CHAT, the M-CHAT-Revised with Follow up (M-CHAT-R/F) has demonstrated strong psychometric properties.The aim of this article is to discuss our results obtained with M-CHAT-R applied in a sample of 131 children aged 31,9 ±9,4 months, recruited for diagnosis and treatment at the University Children's Hospital in Skopje.Our results confirmed that for screening the use of M-CHAT-R/F is currently the very exact instrument which allows the early suspicion, but also possible follow up the symptoms of this disorder. Additionally, we showed the significant negative correlation between age and scores obtained on the checklist.

Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD

To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological measurements of babies diagnosed later with ASD or neurotypical (NT) that are collected routinely during pregnancy and birth. We used a supervised machine learning algorithm with a cross-validation technique to classify NT and ASD babies and performed various statistical tests. With a minimization of the false positive rate, 96% of NT and 41% of ASD babies were identified with a positive predictive value of 77%. We identified the following biomarkers related to ASD: sex, maternal familial history of auto-immune diseases, maternal immunization to CMV, IgG CMV level, timing of fetal rotation on head, femur length in the 3rd trimester, white blood cell count in the 3rd trimester, fetal heart rate during labor, newborn feeding and temperature difference between birth and one day after. Furthermore, statistical models revealed that a subpopulation of 38% of babies at risk of ASD had significantly larger fetal head circumference than age-matched NT ones, suggesting an in utero origin of the reported bigger brains of toddlers with ASD. Our results suggest that pregnancy follow-up measurements might provide an early prognosis of ASD enabling pre-symptomatic behavioral interventions to attenuate efficiently ASD developmental sequels.

Differences in the importance of microcephaly, dysmorphism, and epilepsy in the detection of pathogenic CNVs in ID and ASD patients

Background

Autism spectrum disorders (ASD) and intellectual disabilities (ID) are heterogeneous and complex developmental diseases with significant genetic backgrounds and overlaps of genetic susceptibility loci. Copy number variants (CNVs) are known to be frequent causes of these impairments. However, the clinical heterogeneity of both disorders causes the diagnostic efficacy of CNV analysis to be modest. This could be resolved by stratifying patients according to their clinical features.

Aim

First, we sought to assess the significance of particular clinical features for the detection of pathogenic CNVs in separate groups of ID and ASD patients and determine whether and how these groups differ from each other in the significance of these variables. Second, we aimed to create a statistical model showing how particular clinical features affect the probability of pathogenic CNV findings.

Method

We tested a cohort of 204 patients with ID (N = 90) and ASD (N = 114) for the presence of pathogenic CNVs. We stratified both groups according to their clinical features. Fisher’s exact test was used to determine the significance of these variables for pathogenic CNV findings. Logistic regression was used to create a statistical model of pathogenic CNV findings.

Results

The frequency of pathogenic CNV was significantly higher in the ID group than in the ASD group: 18 (19.78%) versus 8 (7%) (p < 0.004). Microcephaly showed a significant association with pathogenic findings in ID patients (p < 0.01) according to Fisher’s exact test, whereas epilepsy showed a significant association with pathogenic findings in ASD patients (p < 0.01). The probability of pathogenic CNV findings when epilepsy occurred in ASD patients was more than two times higher than if epilepsy co-occurred with ID (29.6%/14.0%). Facial dysmorphism was a significant variable for detecting pathogenic CNVs in both groups (ID p = 0.05, ASD p = 0.01). However, dysmorphism increased the probability of pathogenic CNV detection in the ID group nearly twofold compared to the ASD group (44.4%/23.7%). The presence of macrocephaly in the ASD group showed a 25% probability of pathogenic CNV findings by logistic regression, but this was insignificant according to Fisher’s exact test. The probability of detecting pathogenic CNVs decreases up to 1% in the absence of dysmorphism, macrocephaly, and epilepsy in the ASD group.

Conclusion

Dysmorphism, microcephaly, and epilepsy increase the probability of pathogenic CNV findings in ID and ASD patients. The significance of each feature as a predictor for pathogenic CNV detection differs depending on whether the patient has only ASD or ID. The probability of pathogenic CNV findings without dysmorphism, macrocephaly, or epilepsy in ASD patients is low. Therefore the efficacy of CNV analysis is limited in these patients.

Autism is a prenatal disorder: Evidence from late gestation brain overgrowth

This retrospective study aimed to specify the critical period for atypical brain development in individuals with autism spectrum disorder (ASD) using prenatal and postnatal head growth parameters. The sample consisted of 80 Caucasian, unrelated, idiopathic patients with ASD born after 1995. Fetal ultrasound parameters (head circumference [HC], abdominal circumference, and femur length) were obtained during the second and third trimesters of gestation. HC at birth and postnatal parameters at 12 and 24 months of age were also collected. Head overgrowth, assessed by HC, was highlighted during the second (20-26 weeks of amenorrhea) and third (28-36 weeks of amenorrhea) trimesters. Normal growth of body fetal parameters indicated that head overgrowth was not because of overall body overgrowth. Moreover, postnatal results replicated previously and reported head overgrowth. A critical time window for atypical brain development in autism is hypothesized to begin from the 22nd week of amenorrhea. This period is critical for cortical lamination and glial activation. A pathophysiological cascade is suggested with interactions between candidate genes and environmental factors. Autism Research 2018, 11: 1635-1642. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: It is now widely acknowledged in the scientific community, that autism is a neurodevelopmental disorder. Recent evidence from animal and pathological studies has implicated the in utero period. However, the precise time of onset of abnormal brain development remains unknown. This retrospective study reports novel findings, identifying an atypical head growth trajectory in children with autism, during the in utero period (after the 22nd week of amenorrhea). In the same children, postnatal head overgrowth was also observed. Late gestation is identified as a critical period for atypical brain development underlying autism symptoms.