Altered functional connectivity within the central reward network in overweight and obese women.

Background/objectivesNeuroimaging studies in obese subjects have identified abnormal activation of key regions of central reward circuits, including the nucleus accumbens (NAcc), in response to food-related stimuli. We aimed to examine whether women with elevated body mass index (BMI) show structural and resting state (RS) functional connectivity alterations within regions of the reward network.Subjects/methodsFifty healthy, premenopausal women, 19 overweight and obese (high BMI=26-38 kg m(-2)) and 31 lean (BMI=19-25 kg m(-2)) were selected from the University of California Los Angeles' Oppenheimer Center for Neurobiology of Stress database. Structural and RS functional scans were collected. Group differences in grey matter volume (GMV) of the NAcc, oscillation dynamics of intrinsic brain activity and functional connectivity of the NAcc to regions within the reward network were examined.ResultsGMV of the left NAcc was significantly greater in the high BMI group than in the lean group (P=0.031). Altered frequency distributions were observed in women with high BMI compared with lean group in the left NAcc (P=0.009) in a medium-frequency (MF) band, and in bilateral anterior cingulate cortex (ACC) (P=0.014, <0.001) and ventro-medial prefrontal cortex (vmPFC) (P=0.034, <0.001) in a high-frequency band. Subjects with high BMI had greater connectivity of the left NAcc with bilateral ACC (P=0.024) and right vmPFC (P=0.032) in a MF band and with the left ACC (P=0.03) in a high frequency band.ConclusionsOverweight and obese women in the absence of food-related stimuli show significant structural and functional alterations within regions of reward-related brain networks, which may have a role in altered ingestive behaviors

Sex differences in the influence of body mass index on anatomical architecture of brain networks.

Background/objectivesThe brain has a central role in regulating ingestive behavior in obesity. Analogous to addiction behaviors, an imbalance in the processing of rewarding and salient stimuli results in maladaptive eating behaviors that override homeostatic needs. We performed network analysis based on graph theory to examine the association between body mass index (BMI) and network measures of integrity, information flow and global communication (centrality) in reward, salience and sensorimotor regions and to identify sex-related differences in these parameters.Subjects/methodsStructural and diffusion tensor imaging were obtained in a sample of 124 individuals (61 males and 63 females). Graph theory was applied to calculate anatomical network properties (centrality) for regions of the reward, salience and sensorimotor networks. General linear models with linear contrasts were performed to test for BMI and sex-related differences in measures of centrality, while controlling for age.ResultsIn both males and females, individuals with high BMI (obese and overweight) had greater anatomical centrality (greater connectivity) of reward (putamen) and salience (anterior insula) network regions. Sex differences were observed both in individuals with normal and elevated BMI. In individuals with high BMI, females compared to males showed greater centrality in reward (amygdala, hippocampus and nucleus accumbens) and salience (anterior mid-cingulate cortex) regions, while males compared to females had greater centrality in reward (putamen) and sensorimotor (posterior insula) regions.ConclusionsIn individuals with increased BMI, reward, salience and sensorimotor network regions are susceptible to topological restructuring in a sex-related manner. These findings highlight the influence of these regions on integrative processing of food-related stimuli and increased ingestive behavior in obesity, or in the influence of hedonic ingestion on brain topological restructuring. The observed sex differences emphasize the importance of considering sex differences in obesity pathophysiology

Altered resting state neuromotor connectivity in men with chronic prostatitis/chronic pelvic pain syndrome: A MAPP: Research Network Neuroimaging Study.

Brain network activity associated with altered motor control in individuals with chronic pain is not well understood. Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) is a debilitating condition in which previous studies have revealed altered resting pelvic floor muscle activity in men with CP/CPPS compared to healthy controls. We hypothesized that the brain networks controlling pelvic floor muscles would also show altered resting state function in men with CP/CPPS. Here we describe the results of the first test of this hypothesis focusing on the motor cortical regions, termed pelvic-motor, that can directly activate pelvic floor muscles. A group of men with CP/CPPS (N = 28), as well as group of age-matched healthy male controls (N = 27), had resting state functional magnetic resonance imaging scans as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. Brain maps of the functional connectivity of pelvic-motor were compared between groups. A significant group difference was observed in the functional connectivity between pelvic-motor and the right posterior insula. The effect size of this group difference was among the largest effect sizes in functional connectivity between all pairs of 165 anatomically-defined subregions of the brain. Interestingly, many of the atlas region pairs with large effect sizes also involved other subregions of the insular cortices. We conclude that functional connectivity between motor cortex and the posterior insula may be among the most important markers of altered brain function in men with CP/CPPS, and may represent changes in the integration of viscerosensory and motor processing

Prediction of Large Events on a Dynamical Model of a Fault

We present results for long term and intermediate term prediction algorithms applied to a simple mechanical model of a fault. We use long term prediction methods based, for example, on the distribution of repeat times between large events to establish a benchmark for predictability in the model. In comparison, intermediate term prediction techniques, analogous to the pattern recognition algorithms CN and M8 introduced and studied by Keilis-Borok et al., are more effective at predicting coming large events. We consider the implications of several different quality functions Q which can be used to optimize the algorithms with respect to features such as space, time, and magnitude windows, and find that our results are not overly sensitive to variations in these algorithm parameters. We also study the intrinsic uncertainties associated with seismicity catalogs of restricted lengths.Comment: 33 pages, plain.tex with special macros include

Pregabalin in fibromyalgia - responder analysis from individual patient data

<p>Abstract</p> <p>Background</p> <p>Population mean changes are difficult to use in clinical practice. Responder analysis may be better, but needs validating for level of response and treatment duration. A consensus group has defined what constitutes minimal, moderate, and substantial benefit based on pain intensity and Patient Global Impression of Change scores.</p> <p>Methods</p> <p>We obtained individual patient data from four randomised double blind trials of pregabalin in fibromyalgia lasting eight to 14 weeks. We calculated response for all efficacy outcomes using any improvement (≥ 0%), minimal improvement (≥ 15%), moderate improvement (≥ 30%), substantial improvement (≥ 50%), and extensive improvement (≥ 70%), with numbers needed to treat (NNT) for pregabalin 300 mg, 450 mg, and 600 mg daily compared with placebo.</p> <p>Results</p> <p>Information from 2,757 patients was available. Pain intensity and sleep interference showed reductions with increasing level of response, a significant difference between pregabalin and placebo, and a trend towards lower (better) NNTs at higher doses. Maximum response rates occurred at 4-6 weeks for higher levels of response, and were constant thereafter. NNTs (with 95% confidence intervals) for ≥ 50% improvement in pain intensity compared with placebo after 12 weeks were 22 (11 to 870) for pregabalin 300 mg, 16 (9.3 to 59) for pregabalin 450 mg, and 13 (8.1 to 31) for pregabalin 600 mg daily. NNTs for ≥ 50% improvement in sleep interference compared with placebo after 12 weeks were 13 (8.2 to 30) for pregabalin 300 mg, 8.4 (6.0 to 14) for pregabalin 450 mg, and 8.4 (6.1 to 14) for pregabalin 600 mg. Other outcomes had fewer respondents at higher response levels, but generally did not discriminate between pregabalin and placebo, or show any dose response. Shorter duration and use of 'any improvement' over-estimated treatment effect compared with longer duration and higher levels of response.</p> <p>Conclusions</p> <p>Responder analysis is useful in fibromyalgia, particularly for pain and sleep outcomes. Some fibromyalgia patients treated with pregabalin experience a moderate or substantial pain response that is consistent over time. Short trials using 'any improvement' as an outcome overestimate treatment effects.</p

Interference with work in fibromyalgia - effect of treatment with pregabalin and relation to pain response

BACKGROUND: Clinical trials in chronic pain often collect information about interference with work as answers to component questions of commonly used questionnaires but these data are not normally analysed separately. METHODS: We performed a meta-analysis of individual patient data from four large trials of pregabalin for fibromyalgia lasting 8-14 weeks. We analysed data on interference with work, inferred from answers to component questions of Fibromyalgia Impact Questionnaire (FIQ), Short Form 36 Health Survey, Sheehan Disability Scale, and Multidimensional Assessment of Fatigue, including "How many days in the past week did you miss work, including housework, because of fibromyalgia?" from FIQ. Analyses were performed according to randomised treatment group (pregabalin 150-600 mg daily or placebo), pain improvement (0-10 numerical pain rating scale scores at trial beginning vs. end), and end of trial pain state (100 mm visual analogue pain scale [VAS]). RESULTS: Comparing treatment group average outcomes revealed modest improvement over the duration of the trials, more so with active treatment than with placebo. For the 'work missed' question from FIQ the change for patients on placebo was from 2.2 (standard deviation [SD] 2.3) days of work lost per week at trial beginning to 1.9 (SD 2.1) days lost at trial end (p &lt; 0.01). For patients on 600 mg pregabalin the change was from 2.1 (SD 2.2) days to 1.6 (SD 2.0) days (p &lt; 0.001). However, the change in days of work lost was substantial in patients with a good pain response: from 2.0 (SD 2.2) days to 0.97 (SD 1.6) days (p &lt; 0.0001) for those experiencing &gt;/= 50% pain improvement and from 1.9 (SD 2.2) days to 0.73 (SD 1.4) days (p &lt; 0.0001) for those achieving a low level of pain at trial end (&lt;30 mm on the VAS). Patients achieving both &gt;/= 50% pain improvement and a pain score &lt;30 mm on the VAS had the largest improvement, from 2.0 (SD 2.2) days to 0.60 (SD 1.3) days (p &lt; 0.0001). Analysing answers to the other questions yielded qualitatively similar results. CONCLUSIONS: Effective pain treatment goes along with benefit regarding work. A reduction in time off work &gt;1 day per week can be achieved in patients with good pain responses

Fine Mapping of Genetic Variants in BIN1, CLU, CR1 and PICALM for Association with Cerebrospinal Fluid Biomarkers for Alzheimer's Disease

Recent genome-wide association studies of Alzheimer's disease (AD) have identified variants in BIN1, CLU, CR1 and PICALM that show replicable association with risk for disease. We have thoroughly sampled common variation in these genes, genotyping 355 variants in over 600 individuals for whom measurements of two AD biomarkers, cerebrospinal fluid (CSF) 42 amino acid amyloid beta fragments (Aβ42) and tau phosphorylated at threonine 181 (ptau181), have been obtained. Association analyses were performed to determine whether variants in BIN1, CLU, CR1 or PICALM are associated with changes in the CSF levels of these biomarkers. Despite adequate power to detect effects as small as a 1.05 fold difference, we have failed to detect evidence for association between SNPs in these genes and CSF Aβ42 or ptau181 levels in our sample. Our results suggest that these variants do not affect risk via a mechanism that results in a strong additive effect on CSF levels of Aβ42 or ptau181