The study of metabolic comorbidities in psychiatric disorders may lead to new insights into common mechanisms of disease. It could help identify modifiable risk factors for brain alterations. Diabetes (DM) or prediabetes (pre-DM) frequently co-occur with schizophrenia (Sch) and present with similar neuroanatomical and cognitive impairments as psychosis. Yet, no studies have investigated pre-DM/DM as risk factors for brain and cognitive alterations in Sch. We will collect MRI and cognitive data from 220 participants in four groups, i.e. with and without Sch and with and without pre-DM/DM. We expect that, frontal lobe, hippocampal volumes, connectivity and memory performance will be highest in controls, intermediate in subjects with either condition and lowest in participants with both Sch and pre-DM/DM. Identifying pre-DM/DM as risk factors for brain/cognitive changes in Sch would be the first step toward their prevention. Results of this study could allow for personalized treatment, could improve the low standards of diabetes care in Sch and may suggest novel treatment options.

Výzkum metabolických poruch v psychiatrii může pomoci identifikovat léčitelné rizikové faktory pro změny mozku a kognitivních funkcí u duševních poruch. Prediabetes nebo diabetes je častý u pacientů se schizofrenií a podobně jako psychotické onemocnění je spojený s poškozením mozku a paměti. Žádná studie zatím nezkoumala diabetes/prediabetes jako modifikovatelný rizikový faktor pro atrofii mozku a poruchy pameti u schizofrenie. Abychom vyplnili tuto mezeru, hodláme shromáždit neurozobrazovací a kognitivní data od 220 osob ve 4 skupinách, včetně pacientů s a bez schizofrenie a s a bez prediabetu/diabetu. Očekáváme, že paměťové funkce a objem a konektivita frontálního laloku a hipokampu budou největší u kontrol a nejmenší u pacientů s oběma nemocemi. Identifikace prediabetu/diabetu jako modifikovatelného rizikového faktoru pro mozkovou atrofii a kognitivní deficit u schizofrenie by byla prvním krokem k prevenci nebo léčbě těchto změn. Výsledky této studie by mohly přispět k novým léčebným postupům a personalizované léčbě schizofrenie.

• MeSH
• diabetes mellitus 2. typu komplikace   MeSH
• komplikace diabetu MeSH
• lidé MeSH
• nemoci mozku etiologie   MeSH
• neurozobrazování metody   MeSH
• poruchy paměti etiologie   MeSH
• prediabetes komplikace   MeSH
• progrese nemoci MeSH
• rizikové faktory MeSH
• schizofrenie etiologie   MeSH
• svalová atrofie etiologie   MeSH
• Check Tag
• lidé MeSH

• Konspekt
• Patologie. Klinická medicína
• NLK Obory
• psychiatrie
• neurologie
• diabetologie
• NLK Publikační typ
• závěrečné zprávy o řešení grantu AZV MZ ČR

• MeSH
• Bryophyta * MeSH
• druhová specificita MeSH
• půda MeSH
• rašeliníky * MeSH
• voda MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

• MeSH
• duševní poruchy * MeSH
• lidé MeSH
• toxoplazmóza * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• dopisy MeSH
• komentáře MeSH

Background: The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia. Methods: We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age. Results: Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen's d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age. Conclusions: Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.

• MeSH
• bipolární porucha diagnostické zobrazování   MeSH
• diferenciální diagnóza MeSH
• dospělí MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mladiství MeSH
• mladý dospělý MeSH
• psychotické poruchy diagnostické zobrazování   MeSH
• riziko MeSH
• schizofrenie diagnostické zobrazování   MeSH
• strojové učení * MeSH
• věkové faktory MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH

• MeSH
• duševní poruchy diagnostické zobrazování   MeSH
• důvěrnost informací etika   zákonodárství a právo   MeSH
• lidé MeSH
• magnetická rezonance kinematografická etika   metody   MeSH
• rozpoznávání automatizované etika   metody   zákonodárství a právo   MeSH
• umělá inteligence * MeSH
• výzkum zákonodárství a právo   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• úvodníky MeSH

• MeSH
• hornictví MeSH
• kongresy jako téma MeSH
• lithium * farmakologie   terapeutické užití   MeSH
• neuroprotektivní látky MeSH
• těžební a zpracovatelský průmysl MeSH
• Geografické názvy
• Chile MeSH

PURPOSE OF REVIEW: Type 2 diabetes mellitus (T2DM) negatively affects brain structure and function. Meta-analytical data show that relative to age and sex matched non-psychiatric controls, patients with bipolar disorders have double the risk of T2DM. We review the evidence for association between T2DM and adverse clinical and brain imaging changes in bipolar disorders and summarize studies investigating effects of diabetes treatment on psychiatric and brain outcomes. RECENT FINDINGS: Participants with bipolar disorders and T2DM or insulin resistance demonstrate greater morbidity, chronicity and disability, and lower treatment response to Li. Bipolar disorders complicated by insulin resistance/T2DM are associated with smaller hippocampal and cortical gray matter volumes and lower prefrontal N-acetyl aspartate (neuronal marker). Treatment of T2DM yields preservation of brain gray matter and insulin sensitizers, such as pioglitazone, improve symptoms of depression in unipolar or bipolar disorders. SUMMARY: T2DM or insulin resistance frequently cooccur with bipolar disorders and are associated with negative psychiatric clinical outcomes and compromised brain health. This is clinically concerning, as patients with bipolar disorders have an increased risk of metabolic syndrome and yet often receive suboptimal medical care. At the same time treatment of T2DM and insulin resistance has positive effects on psychiatric and brain outcomes. These findings create a rich agenda for future research, which could enhance psychiatric pharmacopeia and directly impact patient care.

• MeSH
• bipolární porucha krev   metabolismus   patologie   psychologie   MeSH
• deprese farmakoterapie   etiologie   MeSH
• diabetes mellitus 2. typu farmakoterapie   patologie   patofyziologie   psychologie   MeSH
• hypoglykemika terapeutické užití   MeSH
• inzulinová rezistence * MeSH
• lidé MeSH
• mozek patologie   patofyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

A monolithic sulfobetaine polymethacrylate micro-column BIGDMA-MEDSA designed in our laboratory, shows dual retention mechanism: In acetonitrile-rich mobile phase, hydrophilic interactions control the retention (HILIC system), whereas in more aqueous mobile phases the column shows essentially reversed-phase behavior with major role of hydrophobic interactions. The zwitterionic polymethacrylate micro-column can be used in the first dimension of two-dimensional LC in alternating reversed-phase (RP) and HILIC modes, coupled with an alkyl-bonded core-shell or silica-based monolithic column in the second dimension, for HILIC×RP and RP×RP comprehensive two-dimensional separations. During the HILIC×RP period, a gradient of decreasing acetonitrile gradient is used for separation in the first dimension, so that at the end of the gradient the polymeric monolithic micro-column is equilibrated with a highly aqueous mobile phase and is ready for repeated sample injection, this time for separation under reversed-phase gradient conditions with increasing concentration of acetonitrile in the first dimension. The fast repeating reversed-phase gradients on a short silica-monolithic or core-shell column in the second dimension can be optimized independently of the actual running first-dimension gradient program. As the alternating HILIC and RP separations on the first-dimension zwitterionic methacrylate column are based on complementary retention mechanisms, the instrumental setup essentially represents two coupled two-dimensional systems. It is first time that such an automated dual LCxLC approach is reported. The novel system allows obtaining three-dimensional data in a relatively short time and can be applied not only to multidimensional gradient separations of flavones and related polyphenolic compounds.

• MeSH
• acetonitrily MeSH
• betain analogy a deriváty   MeSH
• chromatografie kapalinová přístrojové vybavení   metody   MeSH
• chromatografie s reverzní fází přístrojové vybavení   metody   MeSH
• flavony izolace a purifikace   MeSH
• hydrofobní a hydrofilní interakce MeSH
• hydroxybenzoáty izolace a purifikace   MeSH
• kyseliny polymethakrylové * MeSH
• oxid křemičitý * MeSH
• rozpouštědla MeSH
• voda MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Neuroimaging changes in bipolar disorder (BD) may be secondary to the presence of certain clinical factors. Type 2 diabetes mellitus (T2DM) damages the brain and frequently co-occurs with BD. Studying patients with both T2DM and BD could help identify preventable risk factors for neuroimaging changes in BD. METHODS: We used 1.5T magnetic resonance spectroscopy to measure prefrontal N-acetylaspartate (NAA), which is mainly localized in neurons, and total creatine (tCr), an energy metabolite, in 19 BD patients with insulin resistance/glucose intolerance (BD + IR/GI), 14 BD subjects with T2DM (BD + T2DM), 15 euglycemic BD participants, and 11 euglycemic, nonpsychiatric control. RESULTS: The levels of NAA and tCr were lowest among BD + T2DM, intermediate in the BD + IR/GI, and highest among the euglycemic BD and control subjects (F₃,₅₅ = 4.57, p = .006; F₃,₅₅ = 2.92, p = .04, respectively). Even the BD + IR/GI subjects had lower NAA than the euglycemic participants (t₄₃ = 2.13, p = .04). Total Cr was associated with NAA (β = .52, t₅₆ = 5.57, p = .000001). Both NAA and tCr correlated with Global Assessment of Functioning scores (r₄₆ = .28, p = .05; r₄₆ = .48, p = .0004, respectively). CONCLUSIONS: T2DM, but also prediabetes, may be risk factors for prefrontal neurochemical alterations in BD. These changes were associated with poor psychosocial functioning and could indicate impaired energy metabolism. The findings emphasize the importance of improving diabetes care in BD and suggest potential options for treatment of neuroimaging alterations.

• MeSH
• bipolární porucha komplikace   metabolismus   MeSH
• diabetes mellitus 2. typu komplikace   metabolismus   MeSH
• dospělí MeSH
• kreatin metabolismus   MeSH
• kyselina asparagová analogy a deriváty   metabolismus   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční spektroskopie MeSH
• mozek metabolismus   MeSH
• průřezové studie MeSH
• psychiatrické posuzovací škály MeSH
• rizikové faktory MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: Brain imaging is of limited diagnostic use in psychiatry owing to clinical heterogeneity and low sensitivity/specificity of between-group neuroimaging differences. Machine learning (ML) may better translate neuroimaging to the level of individual participants. Studying unaffected offspring of parents with bipolar disorders (BD) decreases clinical heterogeneity and thus increases sensitivity for detection of biomarkers. The present study used ML to identify individuals at genetic high risk (HR) for BD based on brain structure. METHODS: We studied unaffected and affected relatives of BD probands recruited from 2 sites (Halifax, Canada, and Prague, Czech Republic). Each participant was individually matched by age and sex to controls without personal or family history of psychiatric disorders. We applied support vector machines (SVM) and Gaussian process classifiers (GPC) to structural MRI. RESULTS: We included 45 unaffected and 36 affected relatives of BD probands matched by age and sex on an individual basis to healthy controls. The SVM of white matter distinguished unaffected HR from control participants (accuracy = 68.9%, p = 0.001), with similar accuracy for the GPC (65.6%, p = 0.002) or when analyzing data from each site separately. Differentiation of the more clinically heterogeneous affected familiar group from healthy controls was less accurate (accuracy = 59.7%, p = 0.05). Machine learning applied to grey matter did not distinguish either the unaffected HR or affected familial groups from controls. The regions that most contributed to between-group discrimination included white matter of the inferior/middle frontal gyrus, inferior/middle temporal gyrus and precuneus. LIMITATIONS: Although we recruited 126 participants, ML benefits from even larger samples. CONCLUSION: Machine learning applied to white but not grey matter distinguished unaffected participants at high and low genetic risk for BD based on regions previously implicated in the pathophysiology of BD.

• MeSH
• bílá hmota anatomie a histologie   patologie   MeSH
• bipolární porucha diagnóza   genetika   MeSH
• dospělí MeSH
• genetická predispozice k nemoci * MeSH
• kohortové studie MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mladiství MeSH
• mladý dospělý MeSH
• neurozobrazování * MeSH
• prefrontální mozková kůra anatomie a histologie   patologie   MeSH
• rizikové faktory MeSH
• šedá hmota anatomie a histologie   patologie   MeSH
• spánkový lalok anatomie a histologie   patologie   MeSH
• strojové učení * MeSH
• support vector machine MeSH
• temenní lalok anatomie a histologie   patologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH
• Geografické názvy
• Česká republika MeSH
• Kanada MeSH