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1.
J Pediatr ; 202: 143-149, 2018 11.
Article in English | MEDLINE | ID: mdl-30146113

ABSTRACT

OBJECTIVE: To evaluate cardiovascular and metabolic function in youths adopted internationally from orphanages/institutions (postinstitutionalized) who were height-stunted at adoption. STUDY DESIGN: A total of 30 postinstitutionalized youths (age, 9-18 years; body mass index [BMI] percentile, 7.2-90.4) who were height-stunted at adoption were compared with age- and BMI percentile-matched youths (n = 90). Measurements included total body fat and visceral adipose tissue (dual radiograph absorptiometry), arterial stiffness (augmentation index and pulse wave velocity), cardiac autonomic function (heart rate variability), blood pressure, and fasting lipid, glucose, and insulin levels. Linear regression analyses were computed controlling for parent education, age, trunk tissue fat, height-for-age, sex, and race. RESULTS: Compared with controls of the same age, sex, and BMI, the postinstitutionalized children had higher systolic blood pressure (P = .018), augmentation index (P= .033), total cholesterol (P= .047), low-density lipoprotein cholesterol (P= .03), triglycerides (P= .048), insulin (P= .005), and HOMA-IR (P= .01) values. The postinstitutionalized children had a lower low-frequency to high-frequency ratio (P = .008), indicating lower sympathetic tone, as well as a lower total lean mass (P = .016), a lower gynoid lean mass (P = .039), and a higher proportion of trunk tissue fat (P = .017). The postinstitutionalized and control children did not differ in any other body composition measures. CONCLUSIONS: Early life stress, as represented by height-stunted growth in institutional care, may be associated with early pathways to cardiovascular and metabolic risk in youths even after moving into well-resourced homes early in life and in the absence of increased adiposity. These findings suggest that postinstitutionalized youths with a history of height stunting may need to be closely monitored for emergent cardiometabolic risk factors.


Subject(s)
Body Mass Index , Cardiovascular Diseases/etiology , Growth Disorders/complications , Metabolic Syndrome/etiology , Adolescent , Body Height/physiology , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/physiopathology , Child , Cross-Sectional Studies , Female , Follow-Up Studies , Growth Disorders/diagnosis , Humans , Hypercholesterolemia/diagnosis , Hypercholesterolemia/epidemiology , Hypertension/diagnosis , Hypertension/epidemiology , Incidence , Longitudinal Studies , Male , Metabolic Syndrome/epidemiology , Metabolic Syndrome/physiopathology , Orphanages , Reference Values , Risk Assessment , Stress, Physiological , Stress, Psychological , Time Factors , United States/epidemiology
2.
Front Aging Neurosci ; 14: 872867, 2022.
Article in English | MEDLINE | ID: mdl-35527740

ABSTRACT

Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.

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