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The general psychopathology factor from early to middle childhood: Longitudinal genetic and risk analyses.

Reut AvinunAriel KnafoSalomon Israel
Published in: Journal of psychopathology and clinical science (2022)
Accumulating research suggests the structure of psychopathology is best represented by continuous higher-order dimensions, including a general dimension, "p," and more specific dimensions, for example, externalizing and internalizing factors. Here, we aimed to (a) replicate p in early childhood, (b) examine stability and change of genetic and environmental influences on the psychopathology factors from early to midchildhood, (c) externally validate the factors with key constructs of psychological functioning, and (d) test whether the factors can be predicted by early-life measures (e.g., neonatal complications). Data are based on the Longitudinal Israeli Study of Twins. Mothers reported on pregnancy and neonatal conditions and repeatedly filled in questionnaires on each twin's externalizing and internalizing symptoms from ages 3 to 9. Cognitive ability was assessed in the lab at age 6.5, and personality traits, self-esteem, and life satisfaction were self-reported by the twins at ages 11-13. A bifactor model that included p and externalizing and internalizing factors fit the data best, and associations between p, cognitive ability, and personality were replicated. Longitudinal twin analyses indicated that p is highly heritable (64-73%) with a substantial proportion of the genetic influences stable from age 3. The specific internalizing and externalizing factors (net of p) were also highly heritable. Higher p predicted lower self-esteem at age 11. Early-life measures were not strongly associated with psychopathology. Our results show that p is discernible in early childhood, highly heritable, and prospectively associated with negative outcomes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Keyphrases
  • early life
  • genome wide
  • anorexia nervosa
  • pregnant women
  • dna methylation
  • adipose tissue
  • insulin resistance
  • big data
  • artificial intelligence
  • weight loss
  • childhood cancer