@article{KopfGloecknerAlthenetal.2023,
  author    = {Kopf, Juliane and Gl{\"o}ckner, Stefan and Althen, Heike and Cevada, Thais and Schecklmann, Martin and Dresler, Thomas and Kittel-Schneider, Sarah and Reif, Andreas},
  title     = {Neural responses to a working memory task in acute depressed and remitted phases in bipolar patients},
  series = {Brain Sciences},
  volume    = {13},
  journal   = {Brain Sciences},
  number    = {5},
  issn      = {2076-3425},
  doi       = {10.3390/brainsci13050744},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-313509},
  year      = {2023},
  abstract  = {(1) Cognitive impairments such as working memory (WM) deficits are amongst the most common dysfunctions characterizing bipolar disorder (BD) patients, severely contributing to functional impairment. We aimed to investigate WM performance and associated brain activation during the acute phase of BD and to observe changes in the same patients during remission. (2) Frontal brain activation was recorded using functional near-infrared spectroscopy (fNIRS) during n-back task conditions (one-back, two-back and three-back) in BD patients in their acute depressive (n = 32) and remitted (n = 15) phases as well as in healthy controls (n = 30). (3) Comparison of BD patients during their acute phase with controls showed a trend (p = 0.08) towards lower dorsolateral prefrontal cortex (dlPFC) activation. In the remitted phase, BD patients showed lower dlPFC and ventrolateral prefrontal cortex (vlPFC) activation (p = 0.02) compared to controls. No difference in dlPFC and vlPFC activation between BD patients' phases was found. (4) Our results showed decreased working memory performance in BD patients during the working memory task in the acute phase of disease. Working memory performance improved in the remitted phase of the disease but was still particularly attenuated for the more demanding conditions.},
  language  = {en}
}
@article{BrunkhorstKanaanTrautmannSchreiberetal.2021,
  author    = {Brunkhorst-Kanaan, Nathalie and Trautmann, Sandra and Schreiber, Yannick and Thomas, Dominique and Kittel-Schneider, Sarah and Gurke, Robert and Geisslinger, Gerd and Reif, Andreas and Tegeder, Irmgard},
  title     = {Sphingolipid and endocannabinoid profiles in adult attention deficit hyperactivity disorder},
  series = {Biomedicines},
  volume    = {9},
  journal   = {Biomedicines},
  number    = {9},
  issn      = {2227-9059},
  doi       = {10.3390/biomedicines9091173},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-246080},
  year      = {2021},
  abstract  = {Genes encoding endocannabinoid and sphingolipid metabolism pathways were suggested to contribute to the genetic risk towards attention deficit hyperactivity disorder (ADHD). The present pilot study assessed plasma concentrations of candidate endocannabinoids, sphingolipids and ceramides in individuals with adult ADHD in comparison with healthy controls and patients with affective disorders. Targeted lipid analyses of 23 different lipid species were performed in 71 mental disorder patients and 98 healthy controls (HC). The patients were diagnosed with adult ADHD (n = 12), affective disorder (major depression, MD n = 16 or bipolar disorder, BD n = 6) or adult ADHD with comorbid affective disorders (n = 37). Canonical discriminant analysis and CHAID analyses were used to identify major components that predicted the diagnostic group. ADHD patients had increased plasma concentrations of sphingosine-1-phosphate (S1P d18:1) and sphinganine-1-phosphate (S1P d18:0). In addition, the endocannabinoids, anandamide (AEA) and arachidonoylglycerol were increased. MD/BD patients had increased long chain ceramides, most prominently Cer22:0, but low endocannabinoids in contrast to ADHD patients. Patients with ADHD and comorbid affective disorders displayed increased S1P d18:1 and increased Cer22:0, but the individual lipid levels were lower than in the non-comorbid disorders. Sphingolipid profiles differ between patients suffering from ADHD and affective disorders, with overlapping patterns in comorbid patients. The S1P d18:1 to Cer22:0 ratio may constitute a diagnostic or prognostic tool.},
  language  = {en}
}
@article{BiereKranzMaturaetal.2020,
  author    = {Biere, Silvia and Kranz, Thorsten M. and Matura, Silke and Petrova, Kristiyana and Streit, Fabian and Chiocchetti, Andreas G. and Grimm, Oliver and Brum, Murielle and Brunkhorst-Kanaan, Natalie and Oertel, Viola and Malyshau, Aliaksandr and Pfennig, Andrea and Bauer, Michael and Schulze, Thomas G. and Kittel-Schneider, Sarah and Reif, Andreas},
  title     = {Risk Stratification for Bipolar Disorder Using Polygenic Risk Scores Among Young High-Risk Adults},
  series = {Frontiers in Psychiatry},
  volume    = {11},
  journal   = {Frontiers in Psychiatry},
  doi       = {10.3389/fpsyt.2020.552532},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-214976},
  year      = {2020},
  abstract  = {Objective: Identifying high-risk groups with an increased genetic liability for bipolar disorder (BD) will provide insights into the etiology of BD and contribute to early detection of BD. We used the BD polygenic risk score (PRS) derived from BD genome-wide association studies (GWAS) to explore how such genetic risk manifests in young, high-risk adults. We postulated that BD-PRS would be associated with risk factors for BD. Methods: A final sample of 185 young, high-risk German adults (aged 18-35 years) were grouped into three risk groups and compared to a healthy control group (n = 1,100). The risk groups comprised 117 cases with attention deficit hyperactivity disorder (ADHD), 45 with major depressive disorder (MDD), and 23 help-seeking adults with early recognition symptoms [ER: positive family history for BD, (sub)threshold affective symptomatology and/or mood swings, sleeping disorder]. BD-PRS was computed for each participant. Logistic regression models (controlling for sex, age, and the first five ancestry principal components) were used to assess associations of BD-PRS and the high-risk phenotypes. Results: We observed an association between BD-PRS and combined risk group status (OR = 1.48, p < 0.001), ADHD diagnosis (OR = 1.32, p = 0.009), MDD diagnosis (OR = 1.96, p < 0.001), and ER group status (OR = 1.7, p = 0.025; not significant after correction for multiple testing) compared to healthy controls. Conclusions: In the present study, increased genetic risk for BD was a significant predictor for MDD and ADHD status, but not for ER. These findings support an underlying shared risk for both MDD and BD as well as ADHD and BD. Improving our understanding of the underlying genetic architecture of these phenotypes may aid in early identification and risk stratification.},
  language  = {en}
}