Prediction of estimated risk for bipolar disorder using machine learning and structural MRI features.

BACKGROUND: Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features. METHODS: Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar). RESULTS: For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11-0.361) and a balanced accuracy of 63.1% (95% CI 55.9-70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI -0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6-67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance. CONCLUSIONS: Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.

Efficacy of a synbiotic in the management of adults with Attention-Deficit and Hyperactivity Disorder and/or Borderline Personality Disorder and high levels of irritability: Results from a multicenter, randomized, placebo-controlled, "basket" trial.

Irritability worsens prognosis and increases mortality in individuals with Attention-Deficit and Hyperactivity Disorder (ADHD) and/or Borderline Personality Disorder (BPD). However, treatment options are still insufficient. The aim of this randomized, double blind, placebo-controlled study was to investigate the superiority of a synbiotic over placebo in the management of adults with ADHD and/or BPD and high levels of irritability. The study was conducted between February 2019 and October 2020 at three European clinical centers located in Hungary, Spain and Germany. Included were patients aged 18-65 years old diagnosed with ADHD and/or BPD and high levels of irritability (i.e., an Affectivity Reactivity Index (ARI-S) ≥ 5, plus a Clinical Global Impression-Severity Scale (CGI-S) score ≥ 4). Subjects were randomized 1(synbiotic):1(placebo); the agent was administered each day, for 10 consecutive weeks. The primary outcome measure was end-of-treatment response (i.e., a reduction ≥ 30 % in the ARI-S total score compared to baseline, plus a Clinical Global Impression-Improvement (CGI-I) total score of < 3 (very much, or much improved) at week 10). Between-treatment differences in secondary outcomes, as well as safety were also investigated. Of the 231 included participants, 180 (90:90) were randomized and included in the intention-to-treat-analyses. Of these, 117 (65 %) were females, the mean age was 38 years, ADHD was diagnosed in 113 (63 %), BPD in 44 (24 %), both in 23 (13 %). The synbiotic was well tolerated. At week 10, patients allocated to the synbiotic experienced a significantly higher response rate compared to those allocated to placebo (OR: 0.2, 95 % CI:0.1 to 0.7; P = 0.01). These findings suggest that that (add-on) treatment with a synbiotic may be associated with a clinically meaningful improvement in irritability in, at least, a subgroup of adults with ADHD and/or BPD. A superiority of the synbiotic over placebo in the management of emotional dysregulation (-3.6, 95 % CI:-6.8 to -0.3; P = 0.03), emotional symptoms (-0.6, 95 % CI:-1.2 to -0.05; P = 0.03), inattention (-1.8, 95 % CI: -3.2 to -0.4; P = 0.01), functioning (-2.7, 95 % CI: -5.2 to -0.2; P = 0.03) and perceived stress levels (-0.6, 95 % CI: -1.2 to -0.05; P = 0.03) was also suggested. Higher baseline RANK-L protein levels were associated with a significantly lower response rate, but only in the synbiotic group (OR: 0.1, 95 % CI: -4.3 to - 0.3, P = 0.02). In the placebo group, higher IL-17A levels at baseline were significantly associated with a higher improvement in in particular, emotional dysregulation (P = 0.04), opening a door for new (targeted) drug intervention. However, larger prospective studies are warranted to confirm the findings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03495375.

Exploring weight-related self-monitoring as a potential risk factor for eating disorder symptoms in adults - A systematic review and meta-analysis.

OBJECTIVE: Weight-related self-monitoring (WRSM), which involves the intentional tracking of body weight metrics, has been considered a potential risk factor for eating disorders. Therefore, the aim of this study was to systematically summarize the current state of the literature and to quantify the possible association between WRSM and eating disorder symptoms in adults. METHOD: Preregistration was carried out using PROSPERO (ID CRD42022366133). The PubMed, PsycInfo, and Web of Science databases were searched until December 21, 2023. A study had to be 1) be available in English or German, 2) be peer-reviewed and quantitative, 3) include adult participants (age ≥18 years) from the general population, 4) assess eating disorder symptoms via at least one of the following questionnaires: EDI, EAT, FEV, TFEQ, DEBQ, EDE-Q, Munich ED-Quest or IEG, and 5) include WRSM. Data analyses included descriptive analyses and three-level meta-analysis, corrected for correlations, for the global score and the different subscales of the eating disorder questionnaires. RESULTS: A total of 28 studies (n = 17,370 participants), with an overall fair methodological quality, were included in the systematic review. Out of these studies, nine studies with n = 13,507 participants were ultimately analyzed in the meta-analysis. The three-level meta-analysis did not reveal a significant association between WRSM and the eating disorder global score (r = 0.13, 95% CI [-0.02, 0.28]; p = 0.08), with this pattern also being evident in the subgroup analysis (diet monitoring). DISCUSSION: WRSM alone does not generally translate into an increased risk of disordered eating symptoms in the general population. We assume that individual factors are likely to determine whether the use of WRSM could lead to eating disorder symptoms. These factors should be accounted for in future research.

Regulation of CD4+ and CD8+ T Cell Biology by Short-Chain Fatty Acids and Its Relevance for Autoimmune Pathology.

The gut microbiota encodes a broad range of enzymes capable of synthetizing various metabolites, some of which are still uncharacterized. One well-known class of microbiota-derived metabolites are the short-chain fatty acids (SCFAs) such as acetate, propionate, butyrate and valerate. SCFAs have long been considered a mere waste product of bacterial metabolism. Novel results have challenged this long-held dogma, revealing a central role for microbe-derived SCFAs in gut microbiota-host interaction. SCFAs are bacterial signaling molecules that act directly on host T lymphocytes by reprogramming their metabolic activity and epigenetic status. They have an essential biological role in promoting differentiation of (intestinal) regulatory T cells and in production of the anti-inflammatory cytokine interleukin-10 (IL-10). These small molecules can also reach the circulation and modulate immune cell function in remote tissues. In experimental models of autoimmune and inflammatory diseases, such as inflammatory bowel disease, multiple sclerosis or diabetes, a strong therapeutic potential of SCFAs through the modulation of effector T cell function was observed. In this review, we discuss current research activities toward understanding a relevance of microbial SCFA for treating autoimmune and inflammatory pathologies from in vitro to human studies.

Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application.

BACKGROUND: Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor's importance may differ across these two facets. Distinguishing between these two facets, hence, studying dietary intake as a dual process is conceptually promising and not only allows further insights, but also solves a statistical issue. When assessing the association between a predictor (e.g. momentary affect) and subsequent dietary intake in daily life through ecological momentary assessment (EMA), the outcome variable (e.g. energy intake within a predefined time-interval) is semicontinuous. That is, one part is equal to zero (i.e. no dietary intake occurred) and the other contains right-skewed positive values (i.e. dietary intake occurred, but often only small amounts are consumed). However, linear multilevel modelling which is commonly used for EMA data to account for repeated measures within individuals cannot be applied to semicontinuous outcomes. A highly informative statistical approach for semicontinuous outcomes is multilevel two-part modelling which treats the outcome as generated by a dual process, combining a multilevel logistic/probit regression for zeros and a multilevel (generalized) linear regression for nonzero values. METHODS: A multilevel two-part model combining a multilevel logistic regression to predict whether an individual eats and a multilevel gamma regression to predict how much is eaten, if an individual eats, is proposed. Its general implementation in R, a widely used and freely available statistical software, using the R-package brms is described. To illustrate its practical application, the analytical approach is applied exemplary to data from the Eat2beNICE-APPetite-study. RESULTS: Results highlight that the proposed multilevel two-part model reveals process-specific associations which cannot be detected through traditional multilevel modelling. CONCLUSIONS: This paper is the first to introduce multilevel two-part modelling as a novel analytical approach to study dietary intake in daily life. Studying dietary intake through multilevel two-part modelling is conceptually as well as methodologically promising. Findings can be translated to tailored nutritional interventions targeting either the occurrence or the amount of dietary intake.

Studying Microtemporal, Within-Person Processes of Diet, Physical Activity, and Related Factors Using the APPetite-Mobile-App: Feasibility, Usability, and Validation Study.

BACKGROUND: Diet and physical activity (PA) have a major impact on physical and mental health. However, there is a lack of effective strategies for sustaining these health-protective behaviors. A shift to a microtemporal, within-person approach is needed to capture dynamic processes underlying eating behavior and PA, as they change rapidly across minutes or hours and differ among individuals. However, a tool that captures these microtemporal, within-person processes in daily life is currently not present. OBJECTIVE: The APPetite-mobile-app is developed for the ecological momentary assessment of microtemporal, within-person processes of complex dietary intake, objectively recorded PA, and related factors. This study aims to evaluate the feasibility and usability of the APPetite-mobile-app and the validity of the incorporated APPetite-food record. METHODS: The APPetite-mobile-app captures dietary intake event-contingently through a food record, captures PA continuously through accelerometers, and captures related factors (eg, stress) signal-contingently through 8 prompts per day. Empirical data on feasibility (n=157), usability (n=84), and validity (n=44) were collected within the Eat2beNICE-APPetite-study. Feasibility and usability were examined in healthy participants and psychiatric patients. The relative validity of the APPetite-food record was assessed with a subgroup of healthy participants by using a counterbalanced crossover design. The reference method was a 24-hour recall. In addition, the energy intake was compared with the total energy expenditure estimated from accelerometry. RESULTS: Good feasibility, with compliance rates above 80% for prompts and the accelerometer, as well as reasonable average response and recording durations (prompt: 2.04 min; food record per day: 17.66 min) and latencies (prompts: 3.16 min; food record: 58.35 min) were found. Usability was rated as moderate, with a score of 61.9 of 100 on the System Usability Scale. The evaluation of validity identified large differences in energy and macronutrient intake between the two methods at the group and individual levels. The APPetite-food record captured higher dietary intakes, indicating a lower level of underreporting, compared with the 24-hour recall. Energy intake was assessed fairly accurately by the APPetite-food record at the group level on 2 of 3 days when compared with total energy expenditure. The comparison with mean total energy expenditure (2417.8 kcal, SD 410) showed that the 24-hour recall (1909.2 kcal, SD 478.8) underestimated habitual energy intake to a larger degree than the APPetite-food record (2146.4 kcal, SD 574.5). CONCLUSIONS: The APPetite-mobile-app is a promising tool for capturing microtemporal, within-person processes of diet, PA, and related factors in real time or near real time and is, to the best of our knowledge, the first of its kind. First evidence supports the good feasibility and moderate usability of the APPetite-mobile-app and the validity of the APPetite-food record. Future findings in this context will build the foundation for the development of personalized lifestyle modification interventions, such as just-in-time adaptive interventions.

Association of dietary fat composition with cognitive performance and brain morphology in cognitively healthy individuals.

BACKGROUND: Dietary lipids (omega-3 polyunsaturated fatty acids (n-3) PUFAs) and saturated fatty acids (SFA) seem to play an important role in brain health. (n-3) PUFAs have been shown to improve cerebral perfusion and to promote synaptogenesis. In this study, we investigated the relationship between dietary fat composition, cognitive performance and brain morphology in cognitively healthy individuals. METHODS: A total of 101 cognitively healthy participants (age: 42.3 ± 21.3 years, 62 females) were included in this study. Verbal memory was assessed using the California Verbal Learning Test (CVLT). Intake of (n-3) PUFA and SFA was calculated from food-frequency questionnaire-derived data (EPIC-FFQ). Magnetic resonance imaging (MRI) data were obtained (Siemens Trio 3T scanner) and grey matter volumes (GMV) were assessed by voxel-based morphometry (VBM/SPM8). We examined the association of SFA/(n-3) PUFA ratio and memory performance as well as GMV using regression models adjusted for age, sex, education, body mass index, apolipoprotein E (APOE) status and alcohol consumption. For VBM data, a multiple regression analysis was performed using the same covariates as mentioned before with intracranial volume as an additional covariate. RESULTS: A high SFA/(n-3) PUFA ratio was significantly (p < 0.05) correlated with poorer verbal memory performance and with lower GMV in areas of the left prefrontal cortex that support memory processes. CONCLUSIONS: These findings suggest that a diet rich in PUFAs is likely to exert favourable effects on brain morphology in brain areas important for memory and executive functions. This could constitute a possible mechanism for maintaining cognitive health in older age.

Exercise and microstructural changes in the motor cortex of older adults.

Exercise has been shown to counteract age-related volume decreases in the human brain, and in this imaging study, we ask whether the same holds true for the microstructure of the cortex. Healthy older adults (n = 47, 65-90 years old) either exercised three times a week on a stationary bike or maintained their usual physical routine over a 12-week period. Quantitative longitudinal relaxation rate (R1 ) magnetic resonance imaging (MRI) maps were made at baseline and after the 12-week intervention. R1 is commonly taken to reflect cortical myelin density. The change in R1 (ΔR1 ) was significantly increased in a region of interest (ROI) in the primary motor cortex containing motor outputs to the leg musculature in the exercise group relative to the control group (p = .04). The change in R1 in this ROI correlated with an increase in oxygen consumption at the first ventilatory threshold (VT1) (p = .04), a marker of improvement in submaximal aerobic performance. An exploratory analysis across the cortex suggested that the correlation was predominately confined to the leg representation in the motor cortex. This study suggests that microstructural declines in the cortex of older adults may be staved off by exercise.

Intrinsic functional connectivity, CSF biomarker profiles and their relation to cognitive function in mild cognitive impairment.

Mild cognitive impairment (MCI) often precedes Alzheimer's Dementia (AD), and in a high proportion of individuals affected by MCI, there are already neuropathological processes ongoing that become more evident when patients progress to AD. Accordingly, there is a need for reliable biomarkers to distinguish between normal aging and incipient AD. Recent research suggests that, in addition to established biomarkers such as CSF Aß42, total tau and hyperphosphorylated tau, resting state connectivity established by functional magnetic resonance imaging might also be a feasible biomarker for prodromal stages of AD. In order to explore this possibility, we investigated resting state functional connectivity as well as cerebrospinal fluid (CSF) biomarker profiles in patients with MCI (n = 30; age 66.43 ± 7.06 years) and cognitively healthy controls (n = 38; age 66.89 ± 7.12 years). CSF Aß42, total tau and hyperphosphorylated tau concentrations were correlated with measures of cognitive performance (immediate and delayed recall, global cognition, processing speed). Moreover, MCI-related alterations in intrinsic functional connectivity within the default mode network were investigated using functional resting state MRI. As expected, MCI patients showed decreased CSF Aß42 and increased total tau concentrations. These alterations were associated with cognitive performance. However, there were no differences between MCI patients and cognitively healthy controls regarding intrinsic functional connectivity. In conclusion, our results indicate that CSF protein profiles seem to be more closely related to cognitive decline than alterations in resting state activity. Thus, resting state connectivity might not be a reliable biomarker for early stages of AD.

Lifespan leisure physical activity profile, brain plasticity and cognitive function in old age.

OBJECTIVES: Despite the evidence suggesting physical activity (PA) as a major factor for the prevention of age-related cognitive decline, only a few studies have systematically investigated the impact of leisure PA during the lifespan (LLPA). This study investigates the effects of LLPA on cognitive function (CF) and brain plasticity (BP) in old age. METHOD: Participants' (n = 50, 72 ± 5 yrs, 27 females) LLPA energy expenditure and volume was assessed via a validated questionnaire investigating five epochs (14-80 yrs). Using current WHO PA recommendations as reference, participants were stratified into energy expenditure and volume groups. CF outcomes were attention, executive functions, working memory and memory. BP was assessed using magnetic resonance spectroscopy (MRSI) and brain derived neurotropic factor (BDNF). RESULTS: Correlation analysis revealed associations of mean LLPA energy expenditure with attention (CF) and N-acetylaspartate to choline ratios (NAA/Cho) (MRSI). ANOVA revealed higher interference control performance (CF) and NAA/Cho in participants complying with current PA recommendations (2-3 h per week) compared to non-compliers. Further CF and BP outcomes including BDNF were not associated with LLPA. CONCLUSION: Lifelong adherence to minimum recommended PA seems to be associated with markers of cognitive function and neuronal integrity in old age.

Differential effects of the ApoE4 genotype on brain structure and function.

The apolipoprotein E ε4 allele is a well established genetic risk factor for sporadic Alzheimer's disease. It is associated with structural and functional brain changes in healthy young, middle-aged and elderly subjects. In the current study, we assessed the impact of the ApoE genotype on brain macro- and microstructure, cognitive functioning and brain activity in fifty healthy young subjects (25 ApoE ε4 (ε4+) carriers and 25 non-carriers (ε4-), mean age 26.4±4.6years). We used diffusion tensor imaging (DTI) and voxel based morphometry (VBM) to assess brain structure, an extensive neuropsychological battery to test cognitive functioning and event-related functional magnetic resonance imaging (fMRI) to capture brain activity during episodic memory encoding and retrieval. ApoE ε4 carriers differed from non-carriers in fMRI activations but not in cognitive performance nor in brain micro- and macrostructure. These results suggest functional alterations in the episodic memory network that are modulated by the ε4 allele and might precede clinical or structural neurodegeneration.

Recognition memory is associated with altered resting-state functional connectivity in people at genetic risk for Alzheimer's disease.

The apolipoprotein E ε4 (ApoE ε4) allele not only represents the strongest single genetic risk factor for sporadic Alzheimer's disease, but also imposes independent effects on brain function in healthy individuals where it has been shown to promote subtle memory deficits and altered intrinsic functional brain network connectivity. Based on previous work showing a potential relevance of the default mode network (DMN) functional connectivity for episodic memory function, we hypothesized that the ApoE ε4 genotype would affect memory performance via modulation of the DMN. We assessed 63 healthy individuals (50-80 years old), of which 20 carried the ε4 allele. All participants underwent resting-state functional magnetic resonance imaging (fMRI), high-resolution 3D anatomical MRI imaging and neuropsychological assessment. Functional connectivity analysis of resting-state activity was performed with a predefined seed region located in the left posterior cingulate cortex (PCC), a core region of the DMN. ApoE ε4 carriers performed significantly poorer than non-carriers in wordlist recognition and cued recall. Furthermore, ε4 carriers showed increased connectivity relative to ε4 non-carriers between the PCC seed region and left-hemispheric middle temporal gyrus (MTG). There was a positive correlation between recognition memory scores and resting-state connectivity in the left MTG in ε4 carriers. These results can be interpreted as compensatory mechanisms strengthening the cross-links between DMN core areas and cortical areas involved in memory processing.

Assessing the Accuracy of Smartwatch-Based Estimation of Maximum Oxygen Uptake Using the Apple Watch Series 7: Validation Study.

BACKGROUND: Determining maximum oxygen uptake (VO2max) is essential for evaluating cardiorespiratory fitness. While laboratory-based testing is considered the gold standard, sports watches or fitness trackers offer a convenient alternative. However, despite the high number of wrist-worn devices, there is a lack of scientific validation for VO2max estimation outside the laboratory setting. OBJECTIVE: This study aims to compare the Apple Watch Series 7's performance against the gold standard in VO2max estimation and Apple's validation findings. METHODS: A total of 19 participants (7 female and 12 male), aged 18 to 63 (mean 28.42, SD 11.43) years were included in the validation study. VO2max for all participants was determined in a controlled laboratory environment using a metabolic gas analyzer. Thereby, they completed a graded exercise test on a cycle ergometer until reaching subjective exhaustion. This value was then compared with the estimated VO2max value from the Apple Watch, which was calculated after wearing the watch for at least 2 consecutive days and measured directly after an outdoor running test. RESULTS: The measured VO2max (mean 45.88, SD 9.42 mL/kg/minute) in the laboratory setting was significantly higher than the predicted VO2max (mean 41.37, SD 6.5 mL/kg/minute) from the Apple Watch (t18=2.51; P=.01) with a medium effect size (Hedges g=0.53). The Bland-Altman analysis revealed a good overall agreement between both measurements. However, the intraclass correlation coefficient ICC(2,1)=0.47 (95% CI 0.06-0.75) indicated poor reliability. The mean absolute percentage error between the predicted and the actual VO2max was 15.79%, while the root mean square error was 8.85 mL/kg/minute. The analysis further revealed higher accuracy when focusing on participants with good fitness levels (mean absolute percentage error=14.59%; root-mean-square error=7.22 ml/kg/minute; ICC(2,1)=0.60 95% CI 0.09-0.87). CONCLUSIONS: Similar to other smartwatches, the Apple Watch also overestimates or underestimates the VO2max in individuals with poor or excellent fitness levels, respectively. Assessing the accuracy and reliability of the Apple Watch's VO2max estimation is crucial for determining its suitability as an alternative to laboratory testing. The findings of this study will apprise researchers, physical training professionals, and end users of wearable technology, thereby enhancing the knowledge base and practical application of such devices in assessing cardiorespiratory fitness parameters.

Exploring the Link between Lifestyle, Inflammation, and Insulin Resistance through an Improved Healthy Living Index.

Lifestyle factors-such as diet, physical activity (PA), smoking, and alcohol consumption-have a significant impact on mortality as well as healthcare costs. Moreover, they play a crucial role in the development of type 2 diabetes mellitus (DM2). There also seems to be a link between lifestyle behaviours and insulin resistance, which is often a precursor of DM2. This study uses an enhanced Healthy Living Index (HLI) integrating accelerometric data and an Ecological Momentary Assessment (EMA) to explore differences in lifestyle between insulin-sensitive (IS) and insulin-resistant (IR) individuals. Moreover, it explores the association between lifestyle behaviours and inflammation. Analysing data from 99 participants of the mPRIME study (57 women and 42 men; mean age 49.8 years), we calculated HLI scores-ranging from 0 to 4- based on adherence to specific low-risk lifestyle behaviours, including non-smoking, adhering to a healthy diet, maximally moderate alcohol consumption, and meeting World Health Organization (WHO) PA guidelines. Insulin sensitivity was assessed using a Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and C-reactive protein (CRP) levels were used as a proxy for inflammation. Lifestyle behaviours, represented by HLI scores, were significantly different between IS and IR individuals (U = 1529.0; p = 0.023). The difference in the HLI score between IR and IS individuals was mainly driven by lower adherence to PA recommendations in the IR group. Moreover, reduced PA was linked to increased CRP levels in the IR group (r = -0.368, p = 0.014). Our findings suggest that enhancing PA, especially among individuals with impaired insulin resistance, holds significant promise as a preventive strategy.

Impact of blood glucose on cognitive function in insulin resistance: novel insights from ambulatory assessment.

BACKGROUND/OBJECTIVES: Insulin resistance (IR)-related disorders and cognitive impairment lead to reduced quality of life and cause a significant strain on individuals and the public health system. Thus, we investigated the effects of insulin resistance (IR), and blood glucose fluctuations on cognitive function under laboratory and free-living conditions, using ecological momentary assessment (EMA). SUBJECTS/METHODS: Baseline assessments included neuropsychological tests and blood analysis. Individuals were classified as either insulin-sensitive (<2) or insulin-resistant (≥2), based on their Homeostatic Model Assessment (HOMA-IR) values. Continuous glucose monitoring (CGM) using a percutaneous sensor was performed for 1 week. Using multiple linear regression, we examined the effects of HOMA-IR and CGM metrics on cognitive domains. Working memory (WM) performance, which was assessed using EMA, 4 times a day for 3 consecutive days, was matched to short-term pre-task CGM metrics. Multilevel analysis was used to map the within-day associations of HOMA-IR, short-term CGM metrics, and WM. RESULTS: Analyses included 110 individuals (mean age 48.7 ± 14.3 years, 59% female, n = 53 insulin-resistant). IR was associated with lower global cognitive function (b = -0.267, P = 0.027), and WM (b = -0.316; P = 0.029), but not with executive function (b = -0.216; P = 0.154) during baseline. EMA showed that higher HOMA-IR was associated with lower within-day WM performance (ß = -0.20, 95% CI -0.40 to -0.00). CGM metrics were not associated with cognitive performance. CONCLUSIONS: The results confirm the association between IR and decrements in global cognitive functioning and WM, while no effects of CGM metrics were observed, making IR a crucial time point for intervention. Targeting underlying mechanisms (e.g., inflammation) in addition to glycemia could be promising to minimize adverse cognitive effects. Registered under https://drks.de/register/de identifier no. DRKS00022774.

Age-related changes in energy metabolism in peripheral mononuclear blood cells (PBMCs) and the brains of cognitively healthy seniors.

Mitochondrial dysfunction is a hallmark of cellular senescence and many age-related neurodegenerative diseases. We therefore investigated the relationship between mitochondrial function in peripheral blood cells and cerebral energy metabolites in young and older sex-matched, physically and mentally healthy volunteers. Cross-sectional observational study involving 65 young (26.0 ± 0.49 years) and 65 older (71.7 ± 0.71 years) women and men recruited. Cognitive health was evaluated using established psychometric methods (MMSE, CERAD). Blood samples were collected and analyzed, and fresh peripheral blood mononuclear cells (PBMCs) were isolated. Mitochondrial respiratory complex activity was measured using a Clarke electrode. Adenosine triphosphate (ATP) and citrate synthase activity (CS) were determined by bioluminescence and photometrically. N-aspartyl-aspartate (tNAA), ATP, creatine (Cr), and phosphocreatine (PCr) were quantified in brains using 1H- and 31P-magnetic resonance spectroscopic imaging (MRSI). Levels of insulin-like growth factor 1 (IGF-1) were determined using a radio-immune assay (RIA). Complex IV activity (CIV) (- 15%) and ATP levels (- 11%) were reduced in PBMCs isolated from older participants. Serum levels of IGF-1 were significantly reduced (- 34%) in older participants. Genes involved in mitochondrial activity, antioxidant mechanisms, and autophagy were unaffected by age. tNAA levels were reduced (- 5%), Cr (+ 11%), and PCr (+ 14%) levels were increased, and ATP levels were unchanged in the brains of older participants. Markers of energy metabolism in blood cells did not significantly correlate with energy metabolites in the brain. Age-related bioenergetic changes were detected in peripheral blood cells and the brains of healthy older people. However, mitochondrial function in peripheral blood cells does not reflect energy related metabolites in the brain. While ATP levels in PBMCs may be be a valid marker for age-related mitochondrial dysfunction in humans, cerebral ATP remained constant.

The German research consortium for the study of bipolar disorder (BipoLife): a quality assurance protocol for MR neuroimaging data.

BACKGROUND: The German multicenter research consortium BipoLife aims to investigate the mechanisms underlying bipolar disorders. It focuses in particular on people at high risk of developing the disorder and young patients in the early stages of the disease. Functional and structural magnetic resonance imaging (MRI) data was collected in all participating centers. The collection of neuroimaging data in a longitudinal, multicenter study requires the implementation of a comprehensive quality assurance (QA) protocol. Here, we outline this protocol and illustrate its application within the BipoLife consortium. METHODS: The QA protocol consisted of (1) a training of participating research staff, (2) regular phantom measurements to evaluate the MR scanner performance and its temporal stability across the course of the study, and (3) the assessment of the quality of human MRI data by evaluating a variety of image metrics (e.g., signal-to-noise ratio, ghosting level). In this article, we will provide an overview on these QA procedures and show exemplarily the influence of its application on the results of standard neuroimaging analysis pipelines. DISCUSSION: The QA protocol helped to characterize the various MR scanners, to record their performance over the course of the study and to detect possible malfunctions at an early stage. It also assessed the quality of the human MRI data systematically to characterize its influence on various analyses. Furthermore, by setting up and publishing this protocol, we define standards that must be considered when analyzing data from the BipoLife consortium. It further promotes a systematic evaluation of data quality and a definition of subject inclusion criteria. In the long term, it will help to increase the chance of achieving clinically relevant results.

Young people at risk for developing bipolar disorder: Two-year findings from the multicenter prospective, naturalistic Early-BipoLife study.

Early identification and intervention of individuals with an increased risk for bipolar disorder (BD) may improve the course of illness and prevent long­term consequences. Early-BipoLife, a multicenter, prospective, naturalistic study, examined risk factors of BD beyond family history in participants aged 15-35 years. At baseline, positively screened help-seeking participants (screenBD at-risk) were recruited at Early Detection Centers and in- and outpatient depression and attention-deficit/hyperactivity disorder (ADHD) settings, references (Ref) drawn from a representative cohort. Participants reported sociodemographics and medical history and were repeatedly examined regarding psychopathology and the course of risk factors. N = 1,083 screenBD at-risk and n = 172 Ref were eligible for baseline assessment. Within the first two years, n = 31 screenBD at-risk (2.9 %) and none of Ref developed a manifest BD. The cumulative transition risk was 0.0028 at the end of multistep assessment, 0.0169 at 12 and 0.0317 at 24 months (p = 0.021). The transition rate with a BD family history was 6.0 %, 4.7 % in the Early Phase Inventory for bipolar disorders (EPIbipolar), 6.6 % in the Bipolar Prodrome Interview and Symptom Scale-Prospective (BPSS-FP) and 3.2 % with extended Bipolar At-Risk - BARS criteria). In comparison to help-seeking young patients from psychosis detection services, transition rates in screenBD at-risk participants were lower. The findings of Early-BipoLife underscore the importance of considering risk factors beyond family history in order to improved early detection and interventions to prevent/ameliorate related impairment in the course of BD. Large long-term cohort studies are crucial to understand the developmental pathways and long-term course of BD, especially in people at- risk.

Medical comorbidities in bipolar disorder (BIPCOM): clinical validation of risk factors and biomarkers to improve prevention and treatment. Study protocol.

BACKGROUND: BIPCOM aims to (1) identify medical comorbidities in people with bipolar disorder (BD); (2) examine risk factors and clinical profiles of Medical Comorbidities (MC) in this clinical group, with a special focus on Metabolic Syndrome (MetS); (3) develop a Clinical Support Tool (CST) for the personalized management of BD and medical comorbidities. METHODS: The BIPCOM project aims to investigate MC, specifically MetS, in individuals with BD using various approaches. Initially, prevalence rates, characteristics, genetic and non-genetic risk factors, and the natural progression of MetS among individuals with BD will be assessed by analysing Nordic registers, biobanks, and existing patient datasets from 11 European recruiting centres across 5 countries. Subsequently, a clinical study involving 400 participants from these sites will be conducted to examine the clinical profiles and incidence of specific MetS risk factors over 1 year. Baseline assessments, 1-year follow-ups, biomarker analyses, and physical activity measurements with wearable biosensors, and focus groups will be performed. Using this comprehensive data, a CST will be developed to enhance the prevention, early detection, and personalized treatment of MC in BD, by incorporating clinical, biological, sex and genetic information. This protocol will highlight the study's methodology. DISCUSSION: BIPCOM's data collection will pave the way for tailored treatment and prevention approaches for individuals with BD. This approach has the potential to generate significant healthcare savings by preventing complications, hospitalizations, and emergency visits related to comorbidities and cardiovascular risks in BD. BIPCOM's data collection will enhance BD patient care through personalized strategies, resulting in improved quality of life and reduced costly interventions. The findings of the study will contribute to a better understanding of the relationship between medical comorbidities and BD, enabling accurate prediction and effective management of MetS and cardiovascular diseases. TRIAL REGISTRATION: ISRCTN68010602 at https://www.isrctn.com/ISRCTN68010602 . Registration date: 18/04/2023.