Genetic and phenotypic heterogeneity in early neurodevelopmental traits in the Norwegian Mother, Father and Child Cohort Study

Abstract

Background: Autism and different neurodevelopmental conditions frequently co-occur, as do their symptoms at sub-diagnostic threshold levels. Overlapping traits and shared genetic liability are potential explanations.

Methods: In the population-based Norwegian Mother, Father, and Child Cohort study (MoBa), we leverage item-level data to explore the phenotypic factor structure and genetic architecture underlying neurodevelopmental traits at age 3 years (N = 41,708-58,630) using maternal reports on 76 items assessing children's motor and language development, social functioning, communication, attention, activity regulation, and flexibility of behaviors and interests.

Results: We identified 11 latent factors at the phenotypic level. These factors showed associations with diagnoses of autism and other neurodevelopmental conditions. Most shared genetic liabilities with autism, ADHD, and/or schizophrenia. Item-level GWAS revealed trait-specific genetic correlations with autism (items r_g range = - 0.27-0.78), ADHD (items r_g range = - 0.40-1), and schizophrenia (items r_g range = - 0.24-0.34). We find little evidence of common genetic liability across all neurodevelopmental traits but more so for several genetic factors across more specific areas of neurodevelopment, particularly social and communication traits. Some of these factors, such as one capturing prosocial behavior, overlap with factors found in the phenotypic analyses. Other areas, such as motor development, seemed to have more heterogenous etiology, with specific traits showing a less consistent pattern of genetic correlations with each other.

Conclusions: These exploratory findings emphasize the etiological complexity of neurodevelopmental traits at this early age. In particular, diverse associations with neurodevelopmental conditions and genetic heterogeneity could inform follow-up work to identify shared and differentiating factors in the early manifestations of neurodevelopmental traits and their relation to autism and other neurodevelopmental conditions. This in turn could have implications for clinical screening tools and programs.

Fig. 1

Outline of study design and main analyses at the phenotypic and genotypic levels. Grey boxes outline the steps where questionnaire items were removed with the exclusion thresholds listed to the right. Boxes indicate an analysis with the arrows denoting analyses which are based on (i.e., factor structure) or used results (i.e., summary statistics) from a previous analysis. Analyses conducted at the phenotypic level with no sample size listed were conducted in the full sample (N = 58,630). Half-samples for the EFA/CFA conducted in the phenotypic level were randomly selected halves of the full sample. Estimating rg refers to estimation of genetic correlations of the items/factors with neurodevelopmental conditions. 1 With the assumptions of an OR of 1.2, MAF of 0.01, and alpha of 0.01 in a logistic model with additive genetic effects. 2 Only common factor models with 3+ items run. 3 Common factor GWAS only run on models with good fits and significant factor loadings

Fig. 2

A correlation matrix of the 11 factors from the correlated factor model in the full population. Factors include prosocial behavior (prosocial), motor development (motor), nonverbal communication and joint attention (NVcom), social attention and interest (Social Att), language and verbal communication (language), play, repetitive and restricted behaviors and interests (RepBehavior), repetitive and idiosyncratic speech (RepSpeech), waiting, inattention and overactivity (inattention), and impulsivity. An example item from the factor is listed for each factor

Fig. 3

Estimated effects of factors from the correlated factor model in a multivariate regression controlling for the effects of all factors on the outcome for 5 selected diagnostic outcomes. Effects are presented as odds ratios calculated from the exponential of the standardized beta value from the logistic regression in the measurement models. 95% percent confidence intervals are shown. Due to high correlations amongst domains in the broad areas of social communication (the language & verbal communication, nonverbal communication and joint attention, play, and social attention and interest factors), ADHD-associated traits (the inattention and overactivity, waiting, impulsivity factors), and repetitive and restricted behaviors (the repetitive and idiosyncratic speech and repetitive and restricted behaviors and interests factors) effects of these factors were constrained to be equal to avoid collinearity issues. “*”, “**”, “***” denote adjusted p < 0.05, < 0.01, and < 0.001 respectively, after multiple testing correction. For full results of the outcome models, see the supplementary results (Additional file 2)

Fig. 4

Estimated item and factor loading GWAS genetic correlation with PGS GWAS. 95% percent confidence intervals are presented. Results of multiple testing corrections are presented in Additional file 1: Tables S21 and S22 as a reference for the strength of statistical significance. Items are represented by points and factors are represented by bars. Bar width only reflects the number of items from the factor that were included. (R) denotes reversed coded items. The inattention factor had an estimated genetic correlation above one but is shown just below 1.0. This factor as well as the impulsivity factor had upper bounds of the confidence interval estimated over 1. Item-level estimates were removed if confidence intervals were estimated as having a range larger than 1.5

Fig. 5

The estimated smoothed genetic correlations matrix for the 22 neurodevelopmental items used in the EFA and genetic factor modeling. Items order using angular order of the eigenvectors (AOE). "*”, “**”, “***” denote uncorrected p < 0.05, < 0.01, and < 0.001 respectively