Serotonin Transporter Gene Polymorphism Modulates Activity and Connectivity within an Emotional Arousal Network of Healthy Men during an Aversive Visceral Stimulus.

Background and aimsThe 5-hydroxytryptamine transporter gene-linked polymorphic region (5-HTTLPR) has been linked to increased stress responsiveness and negative emotional states. During fearful face recognition individuals with the s allele of 5-HTTLPR show greater amygdala activation. We aimed to test the hypothesis that the 5-HTTLPR polymorphism differentially affects connectivity within brain networks during an aversive visceral stimulus.MethodsTwenty-three healthy male subjects were enrolled. DNA was extracted from the peripheral blood. The genotype of 5-HTTLPR was determined using polymerase chain reaction. Subjects with the s/s genotype (n = 13) were compared to those with the l allele (genotypes l/s, l/l, n = 10). Controlled rectal distension from 0 to 40 mmHg was delivered in random order using a barostat. Radioactive H2[15-O] saline was injected at time of distension followed by positron emission tomography (PET). Changes in regional cerebral blood flow (rCBF) were analyzed using partial least squares (PLS) and structural equation modeling (SEM).ResultsDuring baseline, subjects with s/s genotype demonstrated a significantly increased negative influence of pregenual ACC (pACC) on amygdala activity compared to l-carriers. During inflation, subjects with s/s genotype demonstrated a significantly greater positive influence of hippocampus on amygdala activity compared to l-carriers.ConclusionIn male Japanese subjects, individuals with s/s genotype show alterations in the connectivity of brain regions involved in stress responsiveness and emotion regulation during aversive visceral stimuli compared to those with l carriers

Systemic sclerosis is associated with specific alterations in gastrointestinal microbiota in two independent cohorts.

ObjectiveTo compare faecal microbial composition in patients with systemic sclerosis (SSc) from 2 independent cohorts with controls and to determine whether certain genera are associated with SSc-gastrointestinal tract (GIT) symptoms.DesignAdult patients with SSc from the University of California, Los Angeles (UCLA) and Oslo University Hospital (OUH) and healthy controls participated in this study (1:1:1). All participants provided stool specimens for 16S rRNA sequencing. Linear discriminant analysis effect size demonstrated genera with differential expression in SSc. Differential expression analysis for sequence count data identified specific genera associated with GIT symptoms as assessed by the GIT 2.0 questionnaire.ResultsThe UCLA-SSc and OUH-SSc cohorts were similar in age (52.1 and 60.5 years, respectively), disease duration (median (IQR): 6.6 (2.5-16.4) and 7.0 (1.0-19.2) years, respectively), gender distribution (88% and 71%, respectively), and GIT symptoms (mean (SD) total GIT 2.0 scores of 0.7 (0.6) and 0.6 (0.5), respectively). Principal coordinate analysis illustrated significant microbial community differences between SSc and controls (UCLA: p=0.001; OUH: p=0.002). Patients with SSc had significantly lower levels of commensal genera deemed to protect against inflammation, such as Bacteroides (UCLA and OUH), Faecalibacterium (UCLA), Clostridium (OUH); and significantly higher levels of pathobiont genera, such as Fusobacterium (UCLA), compared with controls. Increased abundance of Clostridium was associated with less severe GIT symptoms in both cohorts.ConclusionsThe present analysis detected specific aberrations in the lower GIT microbiota of patients with SSc from 2 geographically and ethnically distinct cohorts. These findings suggest that GIT dysbiosis may be a pathological feature of the SSc disease state

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

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

AbstractBackgroundAlterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks.AimTo apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements.MethodsStructural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals.Results1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69% accuracy in discriminating overweight from normal weight. In both brain signatures regions of the reward, salience, executive control and emotional arousal networks were associated with lower morphological values in overweight individuals compared to normal weight individuals, while the opposite pattern was seen for regions of the somatosensory network.Conclusions1. An increased BMI (i.e., overweight subjects) is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity

The hidden geometry of the brain

The human brain connectome is a topologically complex, spatially embedded network. One of the characteristic, basic, nonrandom rules on which brain topology relies on is the tendency of brain networks nodes to cluster into modules with high efficiency and short path length, thus reflecting an intrinsic small-world behavior, functionally segregated (local clustering) and integrated (global efficiency) [1]. Although network topology seems to be somehow connected to network geometry, one of the most challenging issues of the current network science is to infer the hidden geometry from the mere topology of a complex network. Here in, aiming at disclosing the latent geometry of the brain, we apply coalescent embedding – a novel advanced technique able to map a given network in the hyperbolic space inferring the node angular coordinates - on different structural brain networks [2]. Interestingly, we show that we can unsupervisedly reconstruct the intrinsic brain geometry with an incredible level of accuracy and that it strongly resembles the known brain anatomy. As a matter of fact, the first rule of organization of brain networks emerging in the hyperbolic space is their structural segregation into two distinct sections corresponding to the left and right hemispheres, which is a simple concept yet quite neglected in previous studies on brain connectomics. In addition, we demonstrate that the human structural brain networks exhibited a significant different geometry in two age range-specific groups. Finally, we show that the intrinsic geometry of Parkinson’s Disease patients is significantly altered compared to the healthy subjects as revealed by two novel latent geometry markers. The present study may bridge the gap between brain networks topology and geometry and may open a completely new scenario towards the realization of latent geometry network markers for the evaluation of brain disorders

Gastrointestinal specific anxiety in irritable bowel syndrome: validation of the Japanese version of the visceral sensitivity index for university students

Objective: The visceral sensitivity index (VSI) is a useful self-report measure of the gastrointestinal symptom-specific anxiety (GSA) of patients with irritable bowel syndrome (IBS). Previous research has shown that worsening GSA in IBS patients is related to the severity of GI symptoms, suggesting that GSA is an important endpoint for intervention. However, there is currently no Japanese version of the VSI. We therefore translated the VSI into Japanese (VSI-J) and verified its reliability and validity.Material and methods: Participants were 349 university students aged 18 and 19 years and recruited from an academic class. We analyzed data from the VSI-J, Anxiety Sensitivity Index (ASI), Hospital Anxiety and Depression scale (HAD), and Irritable Bowel Syndrome Severity Index (IBS-SI). The internal consistency, stability, and factor structure of the VSI-J and its associations with anxiety, depression and severity measures were investigated.Results: The factor structure of the VSI-J is unidimensional and similar to that of the original VSI (Cronbach\u27s α = 0.93). Construct validity was demonstrated by significant correlations with ASI (r = 0.43, p < 0.0001), HAD-ANX (r = 0.19, p = 0.0003), and IBS-SI scores (r = 0.45, p < 0.0001). Furthermore, the VSI-J was a significant predictor of severity scores on the IBS-SI and demonstrated good discriminant (p < 0.0001) and incremental (p < 0.0001) validity.Conclusion: These findings suggest that the VSI-J is a reliable and valid measure of visceral sensitivity

A longitudinal analysis of urological chronic pelvic pain syndrome flares in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151272/1/bju14783.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151272/2/bju14783_am.pd