Impact of an online multicomponent very-low-carbohydrate program in women with polycystic ovary syndrome: a pilot study.

OBJECTIVE: To study the impact of a very-low-carbohydrate (VLC) diet for 16 weeks in overweight or obese women with polycystic ovary syndrome (PCOS). DESIGN: Single-arm prospective pilot study. SETTING: We recruited participants using medical records from an academic medical center. PATIENTS: Twenty-nine overweight or obese women (body mass index, 25-50 kg/m2) with PCOS. INTERVENTIONS: We taught participants to follow a VLC diet and provided information about a variety of behavioral skills including mindfulness and positive affect using an online 16-week intervention. MAIN OUTCOME MEASURES: Changes in body weight, glycated hemoglobin, and PCOS-related quality of life. RESULTS: The intervention led to positive health outcomes including decreases in percent weight (mean difference = -7.67, SD = 6.10) and glycated hemoglobin level (mean difference = -0.21%, SD = 0.27), an increase in sex hormone binding globulin level (mean difference = 9.24 nmol/L, SD = 16.34), and increases in PCOS-related quality of life measures, including menstrual predictability (mean difference = 2.10, SD = 2.76) and body hair (mean difference = 1.14, SD = 1.04). The low-density lipoprotein cholesterol level increased (mean difference = 0.23 mmol/L, SD = 0.49). CONCLUSIONS: The results suggest that a VLC dietary intervention has potential to promote both weight loss and glycemic control in overweight and obese adults with PCOS, two key components in the prevention of type 2 diabetes. TRIAL REGISTRATION NUMBER: NCT03987854.

Using optimal combined moderators to define heterogeneity in neural responses to randomized conditions: Application to the effect of sleep loss on fear learning.

Comparing the neural outcomes of two randomized experimental groups is a primary aim of many functional neuroimaging studies. However, between-group effects can be obscured by heterogeneity in neural responses. Optimal Combined Moderator (OCM) approaches have previously been used to clarify heterogeneity in clinical outcomes following treatment randomization. We show that OCMs can also be used to clarify heterogeneity in the effect of a randomized experimental condition on neural responses. In 78 healthy adults aged 18-30 from the Effects of Dose-Dependent Sleep Disruption on Fear and Reward (SFeRe) study, we used demographic, clinical, genetic, and polysomnographic characteristics to develop OCMs for the effect of a randomized sleep restriction (SR) versus normal sleep (NS) condition on blood-oxygen-level dependent responses in the right amygdala (RAmyg) and subgenual anterior cingulate cortex (sgACC) during fear conditioning (FC) and extinction (FE) paradigms. The OCM for the RAmyg during FE was strongest [r (95% CI) = 0.52 (0.42, 0.68)], withstood cross-validation, and divided the sample into two subgroups with opposing experimental effects. Among N = 48 participants ("SR < NS"), those with SR exhibited less RAmyg activation during FE than those with NS [d (95%CI) = -1.10 (-1.86, -0.77)]. Among the remaining N = 30 participants ("SR > NS"), those with SR exhibited greater RAmyg activation during FE following SR than those with NS [d (95%CI) = 0.87 (0.37,1.78)]. SR > NS participants were more likely to be female, white, l/l genotype carriers, and have a psychiatric history. They had less sleep (overall and in REM), lower REM density, and lower spindle activity (12-16 Hz). Applying OCMs to randomized studies with neural outcomes can clarify neural heterogeneity and jumpstart mechanistic research; with further validation they also offer promise for personalized brain-based treatments and interventions.

The AVPR1A gene and substance use disorders: association, replication, and functional evidence.

BACKGROUND: The liability to addiction has been shown to be highly genetically correlated across drug classes, suggesting nondrug-specific mechanisms. METHODS: In 757 subjects, we performed association analysis between 1536 single nucleotide polymorphisms (SNPs) in 106 candidate genes and a drug use disorder diagnosis (DUD). RESULTS: Associations (p ≤ .0008) were detected with three SNPs in the arginine vasopressin 1A receptor gene, AVPR1A, with a gene-wise p value of 3 × 10(-5). Bioinformatic evidence points to a role for rs11174811 (microRNA binding site disruption) in AVPR1A function. Based on literature implicating AVPR1A in social bonding, we tested spousal satisfaction as a mediator of the association of rs11174811 with the DUD. Spousal satisfaction was significantly associated with DUD in males (p < .0001). The functional AVPR1A SNP, rs11174811, was associated with spousal satisfaction in males (p = .007). Spousal satisfaction was a significant mediator of the relationship between rs11174811 and DUD. We also present replication of the association in males between rs11174811 and substance use in one clinically ascertained (n = 1399) and one epidemiologic sample (n = 2231). The direction of the association is consistent across the clinically-ascertained samples but reversed in the epidemiologic sample. Lastly, we found a significant impact of rs11174811 genotype on AVPR1A expression in a postmortem brain sample. CONCLUSIONS: The findings of this study call for expansion of research into the role of the arginine vasopressin and other neuropeptide system variation in DUD liability.

Consideration of optimal time window for Pittsburgh compound B PET summed uptake measurements.

UNLABELLED: The standardized uptake value ratio (SUVR, or summed tissue ratio) has been used effectively in Pittsburgh compound B (PiB) PET studies to distinguish subjects who have significant amyloid-beta deposition in their brain from those who do not. Relative to quantitative measurements, advantages of the SUVR are improved study feasibility and low test-retest variation; disadvantages include inherent bias (PiB retention overestimation) and potential for time-varying outcomes. The PiB SUVR has proven to be highly correlated with quantitative outcomes and to allow reliable detection of significant group differences (or effective contrasts). In this work, regional PiB SUVRs were examined across 9 time windows to select the window that provided the best trade-offs between bias, correlation, and effective contrast. METHODS: A total of 40 dynamic PiB PET studies were performed on controls (n = 16), patients with Alzheimer disease (AD; n = 11), and patients with mild cognitive impairment (MCI; n = 13) (555 MBq [15 mCi], 90-min scan, and arterial blood sampling). The SUVR was computed for five 20-min and four 30-min windows that spanned the 30- to 90-min postinjection period. The SUVRs were compared with Logan graphical distribution volume ratio (DVR) measurements (35-90 min), determined with arterial blood as input and without arterial blood as input (cerebellum as reference). RESULTS: Greater correlation and more bias were generally observed for the SUVR measurement at later times than at earlier times (relative to DVR). The effective contrast between the control and AD PiB SUVRs was slightly better for earlier data than for later data. The temporal dynamics of the SUVR measurement indicated greater stability in the measurement at 40 min after injection. CONCLUSION: The 50- to 70-min time window provided a good compromise between physiologic validity, stability, sensitivity, and clinical feasibility across the control, MCI, and AD subject data examined in this study. The 40- to 60-min period demonstrated many advantages and should be used in studies limited by low injected dose. Although more biased than the 40- to 60-min SUVR, the 50- to 70-min SUVR was thought to be optimal because of greater measurement stability, which may prove to be important for longitudinal multisite studies performed in control, MCI, and AD subjects that are not dose-limited.

Brain activation, response inhibition, and increased risk for substance use disorder.

BACKGROUND: Youth at high risk for developing substance use disorders (SUDs) often exhibit differences which suggest inhibitory impairments when compared to average risk youth. METHODS: To examine the underlying neural activity related to these impairments, functional MRI (fMRI) was employed in adolescents during an antisaccade task requiring inhibition of an eye movement response. Each subject's level of neurobehavioral disinhibition (ND) was assessed using a multi-informant, multi-method approach, which has been shown to be highly predictive of SUD onset. The fMRI data was categorized into neural regions of interest according to total frontal, parietal, occipital, and temporal lobe activation. RESULTS: Results demonstrated that ND score was negatively correlated with total amount of frontal activation, but was not significantly correlated with total activation in any other neural region. CONCLUSIONS: These results indicate deficits in frontal activation in youth with high amounts of ND, suggesting a possible developmental delay of executive processes in high-risk youth.

Assessment of risk for substance use disorder consequent to consumption of illegal drugs: psychometric validation of the neurobehavior disinhibition trait.

Previous research has shown that the trait neurobehavior disinhibition (ND), which consists of affect, behavior, and cognitive indicators of self-regulation, is a significant predictor of substance use disorder (SUD) between childhood and young adulthood. The authors evaluated the psychometric properties of the ND trait in 278 boys evaluated at ages 10-12 and 16 years. ND score significantly predicted SUD and outcomes that commonly manifest in tandem with SUD by age 19, such as violence, arrests, committing crime while intoxicated, and concussion injury. In addition to predictive validity, the ND trait was found to have good construct, discriminative, and concurrent validity, as well as good test-retest and internal reliability. The ND trait may be useful for detecting youths at high risk for developing SUD and related outcomes.

A neuro-fuzzy inference system for modeling and prediction of heart rate variability in the neuro-intensive care unit.

In the neurological intensive care unit (NICU), prediction of impending changes in patient condition would be highly beneficial. In this paper, we employ a neuro-fuzzy inference system (NFIS) for short-term prediction of heart rate variability in the NICU. An NFIS was selected because it allows for a "gray-box" approach through which a system identification procedure is used in conjunction with fuzzy modeling. The NFIS is described in detail and is compared to an auto-regressive moving average (ARMA) model for its ability to model both simulated and measured data from NICU patients. We found that the NFIS is capable of predicting changes in heart rate to a reasonable extent, and that the NFIS has both advantages and limitations over the ARMA model. The NFIS may therefore be a reasonable technique to consider for more extensive prediction purposes in ICU settings.

Assessing the sensitivity of fMRI group maps.

Group maps created from individual functional maps provide useful summaries of patterns of brain activation. Different methods for combining information have been proposed in the statistical literature and have been recently applied to fMRI data. Since these group maps are statistics, it is natural to ask how robust they are, that is, are they sensitive to the effects of unusual subjects? "Unusual" might be in terms of extent, location, or strength of activation. Our approach in this paper is to jackknife group maps formed by different combining procedures; the jackknife method, which involves deleting each observation (subject) in turn and recalculating the statistic (the group map), is commonly used for the purpose of assessing sensitivity. We examine the theoretical properties of four combining methods. In addition, via a collection of measures defined on the difference between group maps based on the entire sample and based on the jackknifed samples, we evaluate the robustness of these same methods on data from an fMRI experiment. Results indicate that there is a type of tradeoff in the combining techniques we consider, between robustness and conservativeness: methods that are liberal, in that they allow for the discovery of many active voxels, tend also to be more sensitive to the influences of individual subjects.