| 2. |
- Emmert, David B., et al.
(författare)
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Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample : The CHRIS Study
- 2021
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Ingår i: Biomolecules. - : MDPI. - 2218-273X. ; 11:11
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Tidskriftsartikel (refereegranskat)abstract
- Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 x 10(-8)) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.
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| 3. |
- Emmert, Kirsten, et al.
(författare)
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Meta-analysis of real-time fMRI neurofeedback studies using individual participant data : How is brain regulation mediated?
- 2016
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Ingår i: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 124:Part A, s. 806-812
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Tidskriftsartikel (refereegranskat)abstract
- An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first-(single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-ofinterest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.
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