The 22q11.2 deletion syndrome (22q11.2DS) is a known risk factor for development of schizophrenia and is characterized by a complex neuropsychological profile. To date, a quantitative meta-analysis examining cognitive functioning in 22q11.2DS has not been conducted. A systematic review of cross-sectional studies comparing neuropsychological performance of individuals with 22q11.2DS with age-matched healthy typically developing and sibling comparison subjects was carried out. Potential moderators were analyzed. Analyses included 43 articles (282 effects) that met inclusion criteria. Very large and heterogeneous effects were seen for global cognition (d = - 1.21) and in specific neuropsychological domains (intellectual functioning, achievement, and executive function; d range = - 0.51 to - 2.43). Moderator analysis revealed a significant role for type of healthy comparison group used (typically developing or siblings), demographics (age, sex) and clinical factors (externalizing behavior). Results revealed significant differences between pediatric and adult samples, with isolated analysis within the pediatric sample yielding large effects in several neuropsychological domains (intellectual functioning, achievement, visual memory; d range = - 0.56 to - 2.50). Large cognitive deficits in intellectual functioning and specific neuropsychological variables in individuals with 22q11.2DS represent a robust finding, but these deficits are influenced by several factors, including type of comparison group utilized, age, sex, and clinical status. These findings highlight the clinical relevance of characterizing cognitive functioning in 22q11.2DS and the importance of considering demographic and clinical moderators in future analyses.
Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer vision-based deep learning model for facial emotion recognition trained on 400.000 faces was utilized to analyze facial emotions expressed during a passive viewing memory test. In addition, this study was conducted on a large number of individuals (n = 493), including healthy controls and individuals with cognitive impairment due to diverse underlying etiologies and across different disease stages. Diagnoses included subjective cognitive impairment, Mild Cognitive Impairment (MCI) due to AD, MCI due to other etiologies, dementia due to Alzheimer’s diseases (AD), and dementia due to other etiologies (e.g., Vascular Dementia, Frontotemporal Dementia, Lewy Body Dementia, etc.). The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance across all participants. A participant with a score of less than or equal to 24 was considered cognitively impaired (CI). Compared to cognitively unimpaired (CU) participants, CI participants expressed significantly less positive emotions, more negative emotions, and higher facial expressiveness during the test. In addition, classification analysis revealed that facial emotions expressed during the test allowed effective differentiation of CI from CU participants, largely independent of sex, race, age, education level, mood, and eye movements (derived from an eye-tracking-based digital biomarker for cognitive impairment). No screening methods reliably differentiated the underlying etiology of the cognitive impairment. The findings provide quantitative and comprehensive evidence that the expression of facial emotions is significantly different in people with cognitive impairment, and suggests this may be a useful tool for passive screening of cognitive impairment.
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