bioRxivNeurosciencePreprint
Regional similarity to male-typical brain architecture links childhood ADHD to neurophysiological aging in later adulthood
Raluca PetricaniD, Alex FornitoiD, Amber JohniD, Sophie L. Pendered
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Abstract
Identifying early life biomarkers of suboptimal aging trajectories could help design interventions to delay or even prevent the onset of pathological conditions in older adulthood. To address this issue, we capitalize on evidence that the prevalence rates and presentation of neurodevelopmental and neurodegenerative conditions tend to vary between males and females, thereby raising the possibility that processes involved in sexual differentiation could help connect brain maturation and aging outcomes. Here, we focus on attention deficit hyperactivity disorder (ADHD), a neurodevelopmental condition with male-biased prevalence, and examine the relevance of its genetic risk and functional brain profile to aging outcomes. We analyzed multimodal data from a child sample enriched in ADHD cases and a neurologically intact adult sample. Among 6-to-12-year-olds (N =522), genetic vulnerability to pathological aging, indexed via polygenic risk scores (PRSs) for Alzheimer's Disease (AD), predicted ADHD diagnosis across sexes, regardless of psychiatric history and PRSs for multiple disorders (including ADHD). Irrespective of age, boys and girls diagnosed with ADHD showed preferential alignment with male-, rather than female-, typical functional connectivity patterns in metabolically active transmodal areas which are enriched in 5-HT2,4, D1, and mGLU5 receptors. In an independent sample aged 36-90 years (N = 345), the ADHD brain profile correlated with higher levels of testosterone, physiological markers of reproductive aging and poorer performance on AD-relevant cognitive tasks among older individuals of either sex. Our results imply that neurodevelopmental conditions could provide insights into vulnerability to suboptimal aging trajectories and could help guide early interventions targeting at-risk individuals.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
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