Choroid plexus volume differentiates MS from its mimics.

This study aimed to determine whether choroid plexus volume (CPV) could differentiate multiple sclerosis (MS) from its mimics. A secondary analysis of two previously enrolled studies, 50 participants with MS and 64 with alternative diagnoses were included. CPV was automatically segmented from 3T magnetic resonance imaging (MRI), followed by manual review to remove misclassified tissue. Mean normalized choroid plexus volume (nCPV) to intracranial volume demonstrated relatively high specificity for MS participants in each cohort (0.80 and 0.76) with an area under the receiver-operator characteristic curve of 0.71 (95% confidence interval (CI) = 0.55-0.87) and 0.65 (95% CI = 0.52-0.77). In this preliminary study, nCPV differentiated MS from its mimics.

Detection of Medication Taking Using a Wrist-Worn Commercially Available Wearable Device.

PURPOSE: Medication nonadherence is a persistent and costly problem across health care. Measures of medication adherence are ineffective. Methods such as self-report, prescription claims data, or smart pill bottles have been used to monitor medication adherence, but these are subject to recall bias, lack real-time feedback, and are often expensive. METHODS: We proposed a method for monitoring medication adherence using a commercially available wearable device. Passively collected motion data were analyzed on the basis of the Movelet algorithm, a dictionary learning framework that builds person-specific chapters of movements from short frames of elemental activities within the movements. We adapted and extended the Movelet method to construct a within-patient prediction model that identifies medication-taking behaviors. RESULTS: Using 15 activity features recorded from wrist-worn wearable devices of 10 patients with breast cancer on endocrine therapy, we demonstrated that medication-taking behavior can be predicted in a controlled clinical environment with a median accuracy of 85%. CONCLUSION: These results in a patient-specific population are exemplar of the potential to measure real-time medication adherence using a wrist-worn commercially available wearable device.

Associations between affective factors and high-frequency heart rate variability in primary care patients with depression.

OBJECTIVE: Depression is a risk factor for cardiovascular disease (CVD), and subgroups of people with depression may be at particularly elevated CVD risk. Lower high-frequency heart rate variability (HF HRV), which reflects diminished parasympathetic activation, is a candidate mechanism underlying the depression-CVD relationship and predicts cardiovascular events. Few studies have examined whether certain depression subgroups - such as those with co-occurring affective factors - exhibit lower HF HRV. The present study sought to assess associations between co-occurring affective factors and HF HRV in people with depression. METHODS: Utilizing baseline data from the 216 primary care patients with depression in the eIMPACT trial, we examined cross-sectional associations of depression's co-occurring affective factors (i.e., anxiety symptoms, hostility/anger, and trait positive affect) with HF HRV. HF HRV estimates were derived by spectral analysis from electrocardiographic data obtained during a supine rest period. RESULTS: Individual regression models adjusted for demographics and depressive symptoms revealed that anxiety symptoms (standardized regression coefficient ß = -0.24, p = .002) were negatively associated with HF HRV; however, hostility/anger (ß = 0.02, p = .78) and trait positive affect (ß = -0.05, p = .49) were not. In a model further adjusted for hypercholesterolemia, hypertension, diabetes, body mass index, current smoking, CVD prevention medication use, and antidepressant medication use, anxiety symptoms remained negatively associated with HF HRV (ß = -0.19, p = .02). CONCLUSION: Our findings suggest that, in adults with depression, those with comorbid anxiety symptoms have lower HF HRV than those without. Co-occurring anxiety may indicate a depression subgroup at elevated CVD risk on account of diminished parasympathetic activation.

Voxel-wise intermodal coupling analysis of two or more modalities using local covariance decomposition.

When individual subjects are imaged with multiple modalities, biological information is present not only within each modality, but also between modalities - that is, in how modalities covary at the voxel level. Previous studies have shown that local covariance structures between modalities, or intermodal coupling (IMCo), can be summarized for two modalities, and that two-modality IMCo reveals otherwise undiscovered patterns in neurodevelopment and certain diseases. However, previous IMCo methods are based on the slopes of local weighted linear regression lines, which are inherently asymmetric and limited to the two-modality setting. Here, we present a generalization of IMCo estimation which uses local covariance decompositions to define a symmetric, voxel-wise coupling coefficient that is valid for two or more modalities. We use this method to study coupling between cerebral blood flow, amplitude of low frequency fluctuations, and local connectivity in 803 subjects ages 8 through 22. We demonstrate that coupling is spatially heterogeneous, varies with respect to age and sex in neurodevelopment, and reveals patterns that are not present in individual modalities. As availability of multi-modal data continues to increase, principal-component-based IMCo (pIMCo) offers a powerful approach for summarizing relationships between multiple aspects of brain structure and function. An R package for estimating pIMCo is available at: https://github.com/hufengling/pIMCo.

Social functioning in schizotypy: How affect influences social behavior in daily life.

OBJECTIVE: Social deficits are already exhibited by people at risk for schizophrenia-spectrum disorders. Technological advances have made passive detection of social deficits possible at granular levels. METHOD: In this real-world study, we tested if schizotypy status (high/low) predicted two types of social behavior: (1) being around other people; and (2) actively socializing with others. We also examined if schizotypy influences relationships between social behavior and affect using subjective and objective instruments. RESULTS: Our findings revealed that socializing with others was significantly decreased in the high schizotypy group. Positive affect increased in social situations and predicted later social behavior in those low, but not high, in schizotypy. CONCLUSION: Decreased social behavior in schizotypy may be explained, in part, by these individuals being less incentivized than their peers to pursue social situations. Future studies should test this explanation in larger samples exhibiting elevated positive, negative, and disorganized schizotypy traits.

Using lexical analysis to identify emotional distress in psychometric schizotypy.

Through the use of lexical analysis software, researchers have demonstrated a greater frequency of negative affect word use in those with schizophrenia and schizotypy compared to the general population. In addition, those with schizotypy endorse greater emotional distress than healthy controls. In this study, our aim was to expand on previous findings in schizotypy to determine whether negative affect word use could be linked to emotional distress. Schizotypy (n=33) and non-schizotypy groups (n=33) completed an open-ended, semi-structured interview and negative affect word use was analyzed using a validated lexical analysis instrument. Emotional distress was assessed using subjective questionnaires of depression and psychological quality of life (QOL). When groups were compared, those with schizotypy used significantly more negative affect words; endorsed greater depression; and reported lower QOL. Within schizotypy, a trend level association between depression and negative affect word use was observed; QOL and negative affect word use showed a significant inverse association. Our findings offer preliminary evidence of the potential effectiveness of lexical analysis as an objective, behavior-based method for identifying emotional distress throughout the schizophrenia-spectrum. Utilizing lexical analysis in schizotypy offers promise for providing researchers with an assessment capable of objectively detecting emotional distress.