Augmenting Exposure Therapy for Social Anxiety with tDCS

Purpose/Background: Exposure therapy is one of the most potent techniques available to treat social anxiety. However, studies suggest that exposure therapy only produces full remission in 20-50% of patients. Furthermore, laboratory conditioning and extinction studies suggest that fear responses toward individuals who differ from one\u27s own ethnicity/race may be more resistant to extinction. Because activation of the medial prefrontal cortex has been associated with facilitating fear reduction during exposure therapy, we expect that targeting activation of this region with a stimulation technique called transcranial direct current stimulation (tDCS) may improve outcomes from exposure therapy for social anxiety. The present study will therefore test the hypotheses that (1) fear responding at baseline will be greater toward an audience that does not match (vs matches) the participant\u27s own ethnicity, (2) pairing exposure therapy with active (vs sham) tDCS will facilitate alleviation of social anxiety symptoms, and (3) pairing exposure therapy with active (vs sham) tDCS facilitates extinction of fear response toward individuals who differ from the participant\u27s own ethnicity. Materials & Methods: We are recruiting Latino and non-Latino/Caucasian undergraduates with a fear of public speaking, the most commonly feared situation among individuals with social anxiety. Participants (N = 128) will receive either active/anodal (n = 64) or sham (n = 64) tDCS stimulation targeting the mPFC during an exposure therapy session delivered through virtual reality (VR). During exposure therapy, participants will complete six, 3-minute public speaking trials, alternating in a randomized order between audiences that are 75% matched to the participant\u27s ethnicity and 75% unmatched to the participant\u27s ethnicity. At one-month follow up, participants will complete two behavioral avoidance tests (BATs) parallel to therapy procedures, with one ethnic-matched trial and one ethnic-unmatched trial. Fear response during each BAT will be assessed behaviorally (duration of speech), physiologically (heart rate variability and electrodermal response), and subjectively (peak fear rating, on a 0 to 100 scale). At baseline and one-month follow-up, participants will also complete a battery of social anxiety questionnaires. Results: We will present methods and preliminary findings from the study. Results will include a preliminary examination of whether fear responding is greater toward individuals who differ from (vs match) the participant\u27s own ethnicity, whether pairing exposure therapy with active (vs sham) tDCS facilitates alleviation of social anxiety symptoms overall, and whether pairing exposure therapy with active (vs sham) tDCS facilitates alleviation of social anxiety responding toward individuals who differ from (vs match) the participant\u27s own ethnicity. Discussion/Conclusion: Findings point to key strategies to improve outcomes from exposure therapy for social anxiety, and could also have implications for improving response to exposure-based therapies for other anxiety disorders. Furthermore, if tDCS facilitates reductions in fear response toward ethnic/racial out-groups, minority/Latino individuals may experience better generalization of treatment effects for daily-life scenarios (in which they are surrounded by outgroup members), and ethnic/racial majority individuals will be better able to contribute to an inclusive social environment

Quantitative and qualitative differences in subcutaneous adipose tissue stores across lipodystrophy types shown by magnetic resonance imaging

BACKGROUND: Lipodystrophies are characterized by redistributed subcutaneous fat stores. We previously quantified subcutaneous fat by magnetic resonance imaging (MRI) in the legs of two patients with familial partial lipodystrophy subtypes 2 and 3 (FPLD2 and FPLD3, respectively). We now extend the MRI analysis across the whole body of patients with different forms of lipodystrophy. METHODS: We studied five subcutaneous fat stores (supraclavicular, abdominal, gluteal, thigh and calf) and the abdominal visceral fat stores in 10, 2, 1, 1 and 2 female subjects with, respectively, FPLD2, FPLD3, HIV-related partial lipodystrophy (HIVPL), acquired partial lipodystrophy (APL), congenital generalized lipodystrophy (CGL) and in six normal control subjects. RESULTS: Compared with normal controls, FPLD2 subjects had significantly increased supraclavicular fat, with decreased abdominal, gluteal, thigh and calf subcutaneous fat. FPLD3 subjects had increased supraclavicular and abdominal subcutaneous fat, with less severe reductions in gluteal, thigh and calf fat compared to FPLD2 subjects. The repartitioning of fat in the HIVPL subject closely resembled that of FPLD3 subjects. APL and CGL subjects had reduced upper body, gluteal and thigh subcutaneous fat; the APL subject had increased, while CGL subjects had decreased subcutaneous calf fat. Visceral fat was markedly increased in FPLD2 and APL subjects. CONCLUSION: Semi-automated MRI-based adipose tissue quantification indicates differences between various lipodystrophy types in these studied clinical cases and is a potentially useful tool for extended quantitative phenomic analysis of genetic metabolic disorders. Further studies with a larger sample size are essential for confirming these preliminary findings

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects