1.
Glial and neuronal markers in bipolar disorder: A meta-analysis testing S100B and NSE peripheral blood levels.
Bartoli, F, Misiak, B, Crocamo, C, Carrà, G
Progress in neuro-psychopharmacology & biological psychiatry. 2020;:109922
Abstract
S100 calcium-binding protein B (S100B) and neuron-specific enolase (NSE) might be peripheral markers reflecting glia and neuronal abnormalities in subjects with bipolar disorder. We carried out a systematic review and meta-analysis, searching for studies indexed in main electronic databases, to clarify whether S100B and NSE blood levels might be increased in bipolar disorder. Eleven studies met eligibility criteria, with data on S100B levels and/or NSE levels in subjects with bipolar disorder and healthy controls, respectively. Random-effects meta-analysis estimated higher levels of S100B in bipolar disorder (standardized mean difference [SMD] = 0.81; p < .001), with some inconsistency across studies (I2 = 81.7%). Findings were confirmed by relevant sensitivity analyses. Meta-regression analyses did not estimate any effect for tested covariates. On the other hand, no differences in NSE levels between individuals with bipolar disorder and healthy controls were estimated (SMD = -0.32; p = .374), with high heterogeneity across studies (I2 = 89.9%). Meta-regression analyses showed that the effect size was influenced by both mean age (p < .001) and illness duration (p = .001) of subjects with bipolar disorders. Our findings support the hypothesis of a possible role of glial abnormalities in the pathophysiology of bipolar disorder.
2.
Influence of feeding state on neurofunctional differences between individuals who are obese and normal weight: a meta-analysis of neuroimaging studies.
Kennedy, J, Dimitropoulos, A
Appetite. 2014;:103-9
Abstract
Obesity is a complex disorder associated with serious health risks. Examining differences in brain activity between normal weight and obese populations in response to food cues may help researchers and clinicians understand the underlying causes of overeating and obesity and help prevent them. Multiple neuroimaging studies have investigated weight differences in functional activity to food cues but have found varying results. We performed six meta-analyses of functional neuroimaging studies of weight differences in response to food images and isolated differences in processing between normal weight and obese participants. Within this study, 7 papers and 3 sets of unpublished data on functional activation to food images were analyzed using an Activation Likelihood Estimation meta-analytic approach. These analyses also addressed how feeding state impacts functional activity between weight groups. Feeding state affected weight related differences in neurofunctional activity triggered by visual food cues. In the premeal state, greater activation in the amygdala/hippocampus was found in obese participants compared to normal weight participants and, in the postmeal state, obese individuals had greater activation in the caudate and medial prefrontal cortex (MPFC) as compared to normal weight individuals. Regions of the brain associated with caloric evaluation, arousal, and memory were more active in the obese before eating, while less activity was found in an area linked to interoceptive processing. In the postmeal state, greater activity was found in the obese in areas related to risk vs. reward evaluation and reward processing. These findings may help researchers and clinicians understand and treat obesity related behaviors by identifying the altered functional regions that lead to obesity, providing a guide for future research on which neural regions need to be the target of further investigation.
3.
Neural bases of food perception: coordinate-based meta-analyses of neuroimaging studies in multiple modalities.
Huerta, CI, Sarkar, PR, Duong, TQ, Laird, AR, Fox, PT
Obesity (Silver Spring, Md.). 2014;(6):1439-46
Abstract
OBJECTIVE The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm and ii) the relative robustness and reliability of responses to each paradigm. METHODS Functional magnetic resonance imaging studies using standardized stereotactic coordinates to report brain responses to food cues were identified using online databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation was used to identify statistically reliable regional responses within each stimulation paradigm. RESULTS Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. CONCLUSIONS These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions.
4.
Meta-analysis of association between obsessive-compulsive disorder and the 3' region of neuronal glutamate transporter gene SLC1A1.
Stewart, SE, Mayerfeld, C, Arnold, PD, Crane, JR, O'Dushlaine, C, Fagerness, JA, Yu, D, Scharf, JM, Chan, E, Kassam, F, et al
American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics. 2013;(4):367-79
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Abstract
The neuronal glutamate transporter gene SLC1A1 is a candidate gene for obsessive-compulsive disorder (OCD) based on linkage studies and convergent evidence implicating glutamate in OCD etiology. The 3' end of SLC1A1 is the only genomic region with consistently demonstrated OCD association, especially when analyzing male-only probands. However, specific allele associations have not been consistently replicated, and recent OCD genome-wide association and meta-analysis studies have not incorporated all previously associated SLC1A1 SNPs. To clarify the nature of association between SLC1A1 and OCD, pooled analysis was performed on all available relevant raw study data, comprising a final sample of 815 trios, 306 cases and 634 controls. This revealed weak association between OCD and one of nine tested SLC1A1 polymorphisms (rs301443; uncorrected P = 0.046; non-significant corrected P). Secondary analyses of male-affecteds only (N = 358 trios and 133 cases) demonstrated modest association between OCD and a different SNP (rs12682807; uncorrected P = 0.012; non-significant corrected P). Findings of this meta-analysis are consistent with the trend of previous candidate gene studies in psychiatry and do not clarify the putative role of SLC1A1 in OCD pathophysiology. Nonetheless, it may be important to further examine the potential associations demonstrated in this amalgamated sample, especially since the SNPs with modest associations were not included in the more highly powered recent GWAS or in a past meta-analysis including five SLC1A1 polymorphisms. This study underscores the need for much larger sample sizes in future genetic association studies and suggests that next-generation sequencing may be beneficial in examining the potential role of rare variants in OCD.