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Understanding the interplay between psychosocial factors and polygenic risk scores (PRS) may help elucidate the biopsychosocial etiology of high alcohol consumption (HAC). This study examined the psychosocial moderators of HAC, determined by polygenic risk in a 10-year longitudinal study of US military veterans. We hypothesized that positive psychosocial traits (e.g. social support, personality traits, optimism, gratitude) may buffer risk of HAC in veterans with greater polygenic liability for alcohol consumption (AC).
Data were analyzed from 1323 European-American US veterans who participated in the National Health and Resilience in Veterans Study, a 10-year, nationally representative longitudinal study of US military veterans. PRS reflecting genome-wide risk for AC (AUDIT-C) was derived from a Million Veteran Program genome-wide association study (N = 200 680).
Among the total sample, 328 (weighted 24.8%) had persistent HAC, 131 (weighted 9.9%) had new-onset HAC, 44 (weighted 3.3%) had remitted HAC, and 820 (weighted 62.0%) had no/low AC over the 10-year study period. AUDIT-C PRS was positively associated with persistent HAC relative to no/low AC [relative risk ratio (RRR) = 1.43, 95% confidence interval (CI) = 1.23–1.67] and remitted HAC (RRR = 1.63, 95% CI = 1.07–2.50). Among veterans with higher AUDIT-C PRS, greater baseline levels of agreeableness and greater dispositional gratitude were inversely associated with persistent HAC.
AUDIT-C PRS was prospectively associated with persistent HAC over a 10-year period, and agreeableness and dispositional gratitude moderated this association. Clinical interventions designed to target these modifiable psychological traits may help mitigate risk of persistent HAC in veterans with greater polygenic liability for persistent HAC.
An obsessive-compulsive disorder (OCD) subtype has been associated with streptococcal infections and is called pediatric autoimmune neuropsychiatric disorders associated with streptococci (PANDAS). The neuroanatomical characterization of subjects with this disorder is crucial for the better understanding of its pathophysiology; also, evaluation of these features as classifiers between patients and controls is relevant to determine potential biomarkers and useful in clinical diagnosis. This was the first multivariate pattern analysis (MVPA) study on an early-onset OCD subtype.
Fourteen pediatric patients with PANDAS were paired with 14 healthy subjects and were scanned to obtain structural magnetic resonance images (MRI). We identified neuroanatomical differences between subjects with PANDAS and healthy controls using voxel-based morphometry, diffusion tensor imaging (DTI), and surface analysis. We investigated the usefulness of these neuroanatomical differences to classify patients with PANDAS using MVPA.
The pattern for the gray and white matter was significantly different between subjects with PANDAS and controls. Alterations emerged in the cortex, subcortex, and cerebellum. There were no significant group differences in DTI measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity) or cortical features (thickness, sulci, volume, curvature, and gyrification). The overall accuracy of 75% was achieved using the gray matter features to classify patients with PANDAS and healthy controls.
The results of this integrative study allow a better understanding of the neural substrates in this OCD subtype, suggesting that the anatomical gray matter characteristics could have an immune origin that might be helpful in patient classification.
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