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There is mounting evidence that aerobic exercise has a positive effect on cognitive functions in older adults. To date, little is known about the neurometabolic and molecular mechanisms underlying this positive effect. The present study used magnetic resonance spectroscopy and quantitative MRI to systematically explore the effects of physical activity on human brain metabolism and grey matter (GM) volume in healthy aging. This is a randomised controlled assessor-blinded two-armed trial (n=53) to explore exercise-induced neuroprotective and metabolic effects on the brain in cognitively healthy older adults. Participants (age >65) were allocated to a 12-week individualised aerobic exercise programme intervention (n=29) or a 12-week waiting control group (n=24). The main outcomes were the change in cerebral metabolism and its association to brain-derived neurotrophic factor (BDNF) levels as well as changes in GM volume. We found that cerebral choline concentrations remained stable after 12 weeks of aerobic exercise in the intervention group, whereas they increased in the waiting control group. No effect of training was seen on cerebral N-acetyl-aspartate concentrations, nor on markers of neuronal energy reserve or BDNF levels. Further, we observed no change in cortical GM volume in response to aerobic exercise. The finding of stable choline concentrations in the intervention group over the 3 month period might indicate a neuroprotective effect of aerobic exercise. Choline might constitute a valid marker for an effect of aerobic exercise on cerebral metabolism in healthy aging.
An increasing body of evidences from preclinical as well as epidemiological and clinical studies suggest a potential beneficial role of dietary intake of omega-3 fatty acids for cognitive functioning. In this narrative review, we will summarize and discuss recent findings from epidemiological, interventional and experimental studies linking dietary consumption of omega-3 fatty acids to cognitive function in healthy adults. Furthermore, affective disorders and schizophrenia (SZ) are characterized by cognitive dysfunction encompassing several domains. Cognitive dysfunction is closely related to impaired functioning and quality of life across these conditions. Therefore, the current review focues on the potential influence of omega-3 fatty acids on cognition in SZ and affective disorders. In sum, current data predominantly from mechanistic models and animal studies suggest that adjunctive omega-3 fatty acid supplementation could lead to improved cognitive functioning in SZ and affective disorders. However, besides its translational promise, evidence for clinical benefits in humans has been mixed. Notwithstanding evidences indicate that adjunctive omega-3 fatty acids may have benefit for affective symptoms in both unipolar and bipolar depression, to date no randomized controlled trial had evaluated omega-3 as cognitive enhancer for mood disorders, while a single published controlled trial suggested no therapeutic benefit for cognitive improvement in SZ. Considering the pleiotropic mechanisms of action of omega-3 fatty acids, the design of well-designed controlled trials of omega-3 supplementation as a novel, domain-specific, target for cognitive impairment in SZ and affective disorders is warranted.
Substantial evidence shows that physical activity and fitness play a protective role in the development of stress related disorders. However, the beneficial effects of fitness for resilience to modern life stress are not fully understood. Potentially protective effects may be attributed to enhanced resilience via underlying psychosocial mechanisms such as self-efficacy expectations. This study investigated whether physical activity and fitness contribute to prospectively measured resilience and examined the mediating effect of general self-efficacy. 431 initially healthy adults participated in fitness assessments as part of a longitudinal-prospective study, designed to identify mechanisms of resilience. Self-efficacy and habitual activity were assessed in parallel to cardiorespiratory and muscular fitness, which were determined by a submaximal step-test, hand strength and standing long jump test. Resilience was indexed by stressor reactivity: mental health problems in relation to reported life events and daily hassles, monitored quarterly for nine months. Hierarchical linear regression models and bootstrapped mediation analyses were applied. We could show that muscular and self-perceived fitness were positively associated with stress resilience. Extending this finding, the muscular fitness–resilience relationship was partly mediated by self-efficacy expectations. In this context, self-efficacy expectations may act as one underlying psychological mechanism, with complementary benefits for the promotion of mental health. While physical activity and cardiorespiratory fitness did not predict resilience prospectively, we found muscular and self-perceived fitness to be significant prognostic parameters for stress resilience. Although there is still more need to identify specific fitness parameters in light of stress resilience, our study underscores the general relevance of fitness for stress-related disorders prevention.
Introduction: The influence of our diet on mental health is of increasing importance in current research. Study results on the gut-brain axis suggest that the gut microbiome can influence mental processes via neuronal, hormonal and immune signaling pathways [1]. The gut microbiome is largely influenced by our diet. Some studies provide evidence that a "Western diet" rich in saturated fat and sugar may promote mental disorders [2]. There is evidence, that dietary behaviour in individuals with Attention Deficit Hyperactivity Disorder (ADHD) is characterized by an increased intake of sugar and saturated fat [3]. So far, it is unclear whether this dietary pattern contributes to ADHD symptoms such as impulsivity. The aim of this study is to investigate the influence of certain macronutrients such as fats and mono/disaccharides on impulsivity in individuals with ADHD. Using our APPetite-mobile-app [4] enabled us to study dietary behaviour and momentary impulsiveness in everyday life of our participants.
Methods: 43 participants with ADHD (mean age 36.0 ± 12.3 years, 21 females) and 186 healthy controls (mean age 28.5 ± 7.7 years, 133 females) without any psychiatric condition were included into the study. Food intake was recorded over a period of three days using the APPetite-mobile-app via a 6 step process: (1) Selection of meal type, (2) Entry of time of meal, (3) Selection of consumed foods and drinks, (4) Specification of consumed amounts, (5) Presentation of reminder for commonly forgotten foods, and (6) Indication of predominant reason for eating. In addition to entering consumed foods in the APPetite-mobile-app, subjects completed an online food log for the last 24 hours (myfood 24) at the beginning of the study. After the data collection period, a detailed analysis of the ingested nutrients was performed for each subject. Trait impulsivity was assessed using the UPPS-P, a self-assessment questionnaire. Momentary impulsiveness was assessed via the mHealth APP by means of the Momentary Impulsiveness scale (MIS). The MIS consists of 4 questions capturing different aspects of impulsivity. The participants were prompted to answer these questions at 8 semi-random times per day between 8 AM and 10 PM. The minimum time between 2 prompts was 1 hour. Thereby participants could not predict the exact time of the next prompt and the assessed situations are a better reflection of the participant’s real life.
Results: ANOVA revealed higher levels of both, trait and momentary impulsivity in individuals with ADHD compared to controls (p < 0,01). After preprocessing of data that was sampled via the mHealth APP is completed, a regression analysis with different macronutrients as predictors and impulsivity as dependent variable will be computed. To assess the association between momentary impulsiveness and dietary intake, generalized linear multilevel modelling will be used. Results of these analyses will be presented.
In psychiatry, there has been a growing focus on identifying at-risk populations. For schizophrenia, these efforts have led to the development of early recognition and intervention measures. Despite a similar disease burden, the populations at risk of bipolar disorder have not been sufficiently characterized. Within the BipoLife consortium, we used magnetic resonance imaging (MRI) data from a multicenter study to assess structural gray matter alterations in N = 263 help-seeking individuals from seven study sites. We defined the risk using the EPIbipolar assessment tool as no-risk, low-risk, and high-risk and used a region-of-interest approach (ROI) based on the results of two large-scale multicenter studies of bipolar disorder by the ENIGMA working group. We detected significant differences in the thickness of the left pars opercularis (Cohen’s d = 0.47, p = 0.024) between groups. The cortex was significantly thinner in high-risk individuals compared to those in the no-risk group (p = 0.011). We detected no differences in the hippocampal volume. Exploratory analyses revealed no significant differences in other cortical or subcortical regions. The thinner cortex in help-seeking individuals at risk of bipolar disorder is in line with previous findings in patients with the established disorder and corresponds to the region of the highest effect size in the ENIGMA study of cortical alterations. Structural alterations in prefrontal cortex might be a trait marker of bipolar risk. This is the largest structural MRI study of help-seeking individuals at increased risk of bipolar disorder.
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.
Insulin resistance and working memory exploring the role of blood glucose levels and lifestyle
(2023)
vIntroduction: Type 2 diabetes mellitus and dementia are among the leading causes for reduced quality of life and life expectancy worldwide and often occur comorbidly. Both diseases are linked by altered insulin signaling. Lifestyle factors and blood glucose monitoring play an essential role in the prevention and treatment of type 2 diabetes. So far, a relationship between blood glucose levels, lifestyle, and cognitive performance – a main symptom of dementia - has mainly been established in laboratory settings which reduces its ecological validity.
Objectives: This study uses ambulatory assessment and continuous glucose monitoring to explore the link between blood glucose levels, lifestyle and working memory in an ecological setting. We hypothesize that glycemic variations affect working memory performance in daily life. Second, we hypothesize that a high variance in blood glucose levels has a higher impact on working memory in insulin resistant participants. With this study, we aim to expand the knowledge on the relationship of insulin resistance and cognitive performance from the laboratory setting to everyday life.
Methods: This prospective, exploratory study will include 80 subjects with insulin resistance and 80 healthy controls. At baseline, blood indicators of insulin resistance will be measured to determine group assignment. Our ambulatory assessment includes smartphone-based sampling and sensor-based assessment. Therefore, cognitive performance will be recorded over three consecutive days using a smartphone. Four times a day, a numerical working memory task is prompted by signal-based alarms on the smartphone. Blood glucose levels are recorded in parallel by continuous glucose monitoring. In addition, lifestyle factors such as diet ad physical activity are examined. Diet is assessed by 24-h dietary protocols and movement acceleration by accelerometery.
Multilevel modelling will be used to map the relationship between blood glucose levels and working memory at the within- and between-person level. Diet and exercise are included in the analyses as additional predictors.
Results: Data collection started in March 2021 and is ongoing. Up to now, 40 insulin resistant participants and 36 healthy controls have been measured. Our preliminary results indicate a positive association between blood glucose levels and working memory performance at the within-person level (estimate = .48, 95% CI [.07, .89], p =0.022). At the between-person level the analysis revealed an inverse association between blood glucose levels and working memory performance (estimate = -.45, 95 % CI [-.86 - -.05], p = 0.029).
Conclusion: Our preliminary results are in line with studies showing that an acute rise in blood glucose levels leads to short-term improvements, while stable glucose profiles are beneficial in the long term. This might expand the understanding of the impact of insulin resistance on working memory and represent a target for early interventions. Our preliminary analysis needs to be repeated in our final dataset to confirm our results.
Risk stratification for bipolar disorder using polygenic risk scores among young high-risk adults
(2020)
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.