Drinking coffee enhances neurocognitive function by reorganizing brain functional connectivity

Association between caffeine intake and fat free mass index: a retrospective cohort study

BACKGROUND

Caffeine, identified as a central nervous system stimulant in foods, beverages (coffee, tea, chocolate), and medications, has been focused on its ergogenic properties, enhancing physical performance. The aim of this study was to investigate the association between the caffeine intake (from coffee) and fat-free mass index (FFMI).

MATERIALS AND METHODS

We carried out a cohort study that included 3,466 women and 3,145 men aged ≥20 years who were intaking caffeine. Caffeine intake from coffee were obtained from two 24-hour dietary recall interviews. The FFMI was calculated as FFM (kg) divided by height in m2. The caffeine intake was classified into quartiles and combined into 4 groups. Multiple linear regression model analysis and multiple logistic regression model analysis were used to assess associations between the caffeine and FFMI adjusted for potential confounders.

RESULTS

Among the 2,427 participants, males accounted for 52.4%, and females 47.6%. In multiple linear regression model, Model 1 (unadjusted Model (p = 0.041)) and Model 2 (adjusted for age, race, and BMI (p = 0.006)) in women showed a significant relationship between caffeine intake and FFMI. In multivariable models, caffeine intake and FFMI were significantly different (p < 0.05). In sex subgroups, among females, each quartile of caffeine intake was positively correlated with FFMI levels in the average FFMI group in Model 3 (p < 0.001). In age subgroups, each quartile of caffeine intake was positively correlated with FFMI levels in the average FFMI group in Model 3 for individuals aged 20-40 (p = 0.039) and those aged above 40 (p = 0.016). In drinking status subgroups, if they drunk alcohol, each quartile was positively correlated with FFMI levels in the average FFMI group in Model 3 (p < 0.001).

CONCLUSION

Caffeine intake was mainly positively associated with FFMI, especially in women with above levels of FFMI. Longitudinal studies and randomized controlled trials are needed to establish causality and provide evidence-based recommendations regarding caffeine intake to optimize muscle health.

Coffee Consumption Correlates With Better Cognitive Performance in Patients With a High Incidence for Stroke

BACKGROUND

Atrial fibrillation is an independent risk factor for the development of cognitive impairments. Regular coffee consumption has shown cognitive benefits in healthy individuals. Whether regular consumption reduces cognitive decline in vulnerable patients is controversial. We investigated the association in elderly people with atrial fibrillation.

METHODS AND RESULTS

Daily coffee consumption was assessed using a structured nutrition questionnaire, and cognitive function was evaluated by a detailed neurocognitive-test-battery, including the Montreal Cognitive Assessment, Trail-Making Test, semantic fluency, and Digit-Symbol-Substitution Test. The cognitive construct score combines all neurocognitive tests mentioned and provides an overall cognitive performance indicator. Hs-CRP (high-sensitivity C-reactive protein) and IL-6 (interleukin-6) were measured to explore an association with inflammation. Results were estimated using linear mixed-effects-models with detailed adjustments for confounders. The <1 cup/day consumers (reference group) reached a cognitive construct score of -0.24 (95% CI, -0.27 to -0.16), and the group with the highest consumption (>5 cups/day) was at -0.10 (95% CI, -0.10 to 0.04; p=0.048). Montreal Cognitive Assessment score in the reference group was 24.58 (95% CI, 24.58-25.32); the group with the highest intake achieved 25.25 (95% CI, 24.98-26.85; p=0.163). Inflammatory markers decreased with higher coffee consumption (hs-CRP with 5 compared with <1 cup/day by factor 0.78 [95% CI, 0.54-1.13], p= 0.188, IL-6 significantly by factor 0.73 [95% CI, 0.57-0.95], p=0.017).

CONCLUSIONS

Coffee consumption in patients with atrial fibrillation may be associated with improved cognitive performance and reduced inflammatory markers. Further research is needed to confirm these findings and to consider implementation in dietary counseling for atrial fibrillation management.

REGISTRATION

URL: https://www.clinicaltrials.gov; Identifier: NCT02105844.

Coffee's protective mechanisms against neurodegeneration

A widely consumed beverage, coffee has emerged as a potential protective natural agent against neurodegenerative diseases. This chapter explores the intricate mechanisms by which coffee and its bioactive compounds exert neuroprotective effects. The antioxidant properties of coffee polyphenols, such as chlorogenic acid and caffeic acid, mitigate oxidative stress and neuroinflammation. Coffee modulates neurotransmitter systems, including dopaminergic, cholinergic, and glutamatergic pathways implicated in neurodegeneration. Additionally, coffee activates neuroprotective signaling cascades, such as the Nrf2 pathway, and inhibits pro-inflammatory pathways like NF-κB. Coffee components also influence mitochondrial function, biogenesis, and energy metabolism, thereby promoting neuronal survival. Furthermore, coffee suppresses microglial activation and modulates microglial phenotypes, reducing neuroinflammatory responses. Epidemiological studies and clinical trials provide insights into the potential benefits of coffee consumption on cognitive function and neurodegenerative disease risk. However, future research should focus on identifying specific coffee bioactive compounds and their mechanism of action. This chapter highlights the multifaceted neuroprotective mechanisms of coffee, paving the way for future research and potential therapeutic interventions.

From bean to brain: Coffee, gray matter, and neuroprotection in neurological disorders spectrum

Coffee is a popular drink enjoyed around the world, and scientists are very interested in studying how it affects the human brain. This chapter looks at lots of different studies to understand how drinking coffee might change the brain and help protect it from neurodegenerative disorders especially like schizophrenia. With the help of available literature a link between the coffee mechanism and neurodegenerative disorders is established in this chapter. Researchers have found that drinking coffee can change the size of certain parts of the brain that control things like thinking and mood. Scientists also study how coffee's ingredients, especially caffeine, can change how the brain works. They think these changes could help protect the brain from diseases. This chapter focuses on how coffee might affect people with schizophrenia as hallucination is caused during and after excess consumption of caffeine. There's still a lot we don't know, but researchers are learning more by studying how different people's brains respond to coffee over time. Overall, this chapter shows that studying coffee and the brain could lead to new ways to help people with brain disorders. This study also draws ideas for future research and ways to help people stay healthy.

Evaluation of the responsiveness pattern to caffeine through a smart data-driven ECG non-linear multi-band analysis

This study aimed to explore more efficient ways of administering caffeine to the body by investigating the impact of caffeine on the modulation of the nervous system's activity through the analysis of electrocardiographic signals (ECG). An ECG non-linear multi-band analysis using Discrete Wavelet Transform (DWT) was employed to extract various features from healthy individuals exposed to different caffeine consumption methods: expresso coffee (EC), decaffeinated coffee (ED), Caffeine Oral Films (OF_caffeine), and placebo OF (OF_placebo). Non-linear feature distributions representing every ECG minute time series have been selected by PCA with different variance percentages to serve as inputs for 23 machine learning models in a leave-one-out cross-validation process for analyzing the behavior differences between ED/EC and OF_placebo/OF_caffeine groups, respectively, over time. The study generated 50-point accuracy curves per model, representing the discrimination power between groups throughout the 50 min. The best model accuracies for ED/EC varied between 30 and 70 %, (using the decision tree classifier) and OF_placebo/OF_caffeine ranged from 62 to 84 % (using Fine Gaussian). Notably, caffeine delivery through OFs demonstrated effective capacity compared to its placebo counterpart, as evidenced by significant differences in accuracy curves between OF_placebo/OF_caffeine. Caffeine delivery via OFs also exhibited rapid dissolution efficiency and controlled release rate over time, distinguishing it from EC. The study supports the potential of caffeine delivery through Caffeine OFs as a superior technology compared to traditional methods by means of ECG analysis. It highlights the efficiency of OFs in controlling the release of caffeine and underscores their promise for future caffeine delivery systems.

A Subtype Perspective on Cognitive Trajectories in Healthy Aging

Cognitive aging is a complex and dynamic process characterized by changes due to genetics and environmental factors, including lifestyle choices and environmental exposure, which contribute to the heterogeneity observed in cognitive outcomes. This heterogeneity is particularly pronounced among older adults, with some individuals maintaining stable cognitive function while others experience complex, non-linear changes, making it difficult to identify meaningful decline accurately. Current research methods range from population-level modeling to individual-specific assessments. In this work, we review these methodologies and propose that population subtyping should be considered as a viable alternative. This approach relies on early individual-specific detection methods that can lead to an improved understanding of changes in individual cognitive trajectories. The improved understanding of cognitive trajectories through population subtyping can lead to the identification of meaningful changes and the determination of timely, effective interventions. This approach can aid in informing policy decisions and in developing targeted interventions that promote cognitive health, ultimately contributing to a more personalized understanding of the aging process within society and reducing the burden on healthcare systems.

The Clinical Relevance of Autonomic Dysfunction, Cerebral Hemodynamics, and Sleep Interactions in Individuals Living With SCI

A myriad of physiological impairments is seen in individuals after a spinal cord injury (SCI). These include altered autonomic function, cerebral hemodynamics, and sleep. These physiological systems are interconnected and likely insidiously interact leading to secondary complications. These impairments negatively influence quality of life. A comprehensive review of these systems, and their interplay, may improve clinical treatment and the rehabilitation plan of individuals living with SCI. Thus, these physiological measures should receive more clinical consideration. This special communication introduces the under investigated autonomic dysfunction, cerebral hemodynamics, and sleep disorders in people with SCI to stakeholders involved in SCI rehabilitation. We also discuss the linkage between autonomic dysfunction, cerebral hemodynamics, and sleep disorders and some secondary outcomes are discussed. Recent evidence is synthesized to make clinical recommendations on the assessment and potential management of important autonomic, cerebral hemodynamics, and sleep-related dysfunction in people with SCI. Finally, a few recommendations for clinicians and researchers are provided.

Alteration of intracerebral metabolites and subjective sleepiness by acute caffeine administration in adults

Background

Caffeine is the most widely consumed psychostimulant. Despite this, the effects of acute caffeine intake on brain metabolite levels remain largely unknown. We aimed to investigate the effect of acute caffeine intake on brain metabolite concentrations in different caffeine consumption habit groups and to explore the association between metabolite changes and sleepiness.

Methods

Forty-five healthy adults were divided into groups based on their daily caffeine consumption: ≥1 cup/day, <1 cup/day, and no consumption. The exclusion criteria were the presence of neurological disorder, habitual consumption of mind-altering substances, and individuals who were unable to undergo magnetic resonance imaging. Mescher-Garwood point resolved spectroscopy and conventional spectroscopy data were acquired at 3 Tesla from voxels in the thalamus and posterior cingulate cortex (PCC). Subjective sleepiness was measured with the Karolinska Sleepiness Scale.

Results

The results of two-way repeated measures analysis of variance indicated a significant interaction effect between time and group for glutamate, glycerylphosphocholine and phosphocholine (GPC + PCH), myo-inositol, glutamate + glutamine (Glx), and creatine and phosphocreatine (Cr + PCr) of the thalamus (all P<0.01), and glutamate (P<0.0001), GPC + PCH (P=0.016), and Glx (P<0.0001) of the PCC. The change between pre- and post-caffeine intake results with significant reductions in γ-aminobutyric acid-positive macromolecule (GABA+) (thalamus, P=0.011), Glx (thalamus, P=0.002), glutamate (PCC, P<0.0001), and significant increments in GPC + PCH (thalamus, P=0.012 and PCC, P<0.0001), myo-inositol (thalamus, P=0.009), and Glx (PCC, P<0.0001). The change among the groups, with the ≥1 cup/day was significantly higher than the <1 cup/day or no consumption for glutamate (PCC, P=0.028), GPC (thalamus, P=0.001; PCC, P=0.026), and Cr + PCr (PCC, P=0.035); ≥1 cup/day was significantly lower than <1 cup/day and no consumption for glutamate (thalamus, P<0.0001), Cr + PCr (thalamus, P=0.003), Glx (thalamus, P=0.014), and myo-inositol (PCC, P=0.009). Bivariate correlation analysis revealed that GABA+ in the thalamus voxel (r=-0.7676; P<0.0001) was negatively correlated with subjective sleepiness.

Conclusions

Higher caffeine consumption had a significant impact on brain metabolites. Magnetic resonance spectroscopy was sensitive in measuring brain metabolite fluctuations after caffeine intake, particularly the levels of GABA+ in the thalamus, which was significantly correlated with sleepiness.

Taste the emotions: pilot for a novel, sensors-based approach to emotional analysis during coffee tasting

BACKGROUND

Coffee is a natural drink with important properties for the human body and mind, capable of delivering energy and strong emotions, thus being appreciated since ancient times. The qualitative and quantitative assessment of the coffee properties is normally performed by trained panelists, though relying on standardized questionnaires, with possible biases arising. In this study, for the first time in the scientific literature, we applied a technology-based approach, based on the use of wearable sensors, to study the implicit emotional responses of a small cohort of experienced coffee judges, thus taking this chance to assess the feasibility of this approach in such a scenario. The merging of different technologies for capturing biomedical signals, including electrocardiogram, galvanic skin response, and electroencephalogram, was therefore adopted to retrieve results in terms of the relationships between implicit (i.e. psychophysiological) and explicit (i.e. derived from questionnaires) measurements.

RESULTS

Significant correlations were obtained between biomedical signals and data from the questionnaires within all the sensory domains (olfaction, vision, taste) investigated, particularly concerning autonomic-related features.

CONCLUSIONS

The results obtained confirmed the viability of this new approach in the psychophysical and emotional assessment in coffee tasting judges, paving the way for a new perspective into the universe of coffee quality assessment panels, eventually transferable to broader scale investigations, somewhat dealing with consumer satisfaction and neuromarketing at large. © 2023 Society of Chemical Industry.

Differences in functional network between focal onset nonconvulsive status epilepticus and toxic metabolic encephalopathy: application to machine learning models for differential diagnosis

We aimed to compare network properties between focal-onset nonconvulsive status epilepticus (NCSE) and toxic/metabolic encephalopathy (TME) during periods of periodic discharge using graph theoretical analysis, and to evaluate the applicability of graph measures as markers for the differential diagnosis between focal-onset NCSE and TME, using machine learning algorithms. Electroencephalography (EEG) data from 50 focal-onset NCSE and 44 TMEs were analyzed. Epochs with nonictal periodic discharges were selected, and the coherence in each frequency band was analyzed. Graph theoretical analysis was performed to compare brain network properties between the groups. Eight different traditional machine learning methods were implemented to evaluate the utility of graph theoretical measures as input features to discriminate between the two conditions. The average degree (in delta, alpha, beta, and gamma bands), strength (in delta band), global efficiency (in delta and alpha bands), local efficiency (in delta band), clustering coefficient (in delta band), and transitivity (in delta band) were higher in TME than in NCSE. TME showed lower modularity (in delta band) and assortativity (in alpha, beta, and gamma bands) than NCSE. Machine learning algorithms based on EEG global graph measures classified NCSE and TME with high accuracy, and gradient boosting was the most accurate classification model with an area under the receiver operating characteristics curve of 0.904. Our findings on differences in network properties may provide novel insights that graph measures reflecting the network properties could be quantitative markers for the differential diagnosis between focal-onset NCSE and TME.

Coffee consumption decreases the connectivity of the posterior Default Mode Network (DMN) at rest

Habitual coffee consumers justify their life choices by arguing that they become more alert and increase motor and cognitive performance and efficiency; however, these subjective impressions still do not have a neurobiological correlation. Using functional connectivity approaches to study resting-state fMRI data in a group of habitual coffee drinkers, we herein show that coffee consumption decreased connectivity of the posterior default mode network (DMN) and between the somatosensory/motor networks and the prefrontal cortex, while the connectivity in nodes of the higher visual and the right executive control network (RECN) is increased after drinking coffee; data also show that caffeine intake only replicated the impact of coffee on the posterior DMN, thus disentangling the neurochemical effects of caffeine from the experience of having a coffee.

Effects of Chronic Caffeine Consumption on Synaptic Function, Metabolism and Adenosine Modulation in Different Brain Areas

Adenosine receptors mainly control synaptic function, and excessive activation of adenosine receptors may worsen the onset of many neurological disorders. Accordingly, the regular intake of moderate doses of caffeine antagonizes adenosine receptors and affords robust neuroprotection. Although caffeine intake alters brain functional connectivity and multi-omics analyses indicate that caffeine intake modifies synaptic and metabolic processes, it is unclear how caffeine intake affects behavior, synaptic plasticity and its modulation by adenosine. We now report that male mice drinking caffeinated water (0.3 g/L) for 2 weeks were behaviorally indistinguishable (locomotion, mood, memory) from control mice (drinking water) and displayed superimposable synaptic plasticity (long-term potentiation) in different brain areas (hippocampus, prefrontal cortex, amygdala). Moreover, there was a general preservation of the efficiency of adenosine A₁ and A_2A receptors to control synaptic transmission and plasticity, although there was a tendency for lower levels of endogenous adenosine ensuring A₁ receptor-mediated inhibition. In spite of similar behavioral and neurophysiological function, caffeine intake increased the energy charge and redox state of cortical synaptosomes. This increased metabolic competence likely involved a putative increase in the glycolytic rate in synapses and a prospective greater astrocyte-synapse lactate shuttling. It was concluded that caffeine intake does not trigger evident alterations of behavior or of synaptic plasticity but increases the metabolic competence of synapses, which might be related with the previously described better ability of animals consuming caffeine to cope with deleterious stimuli triggering brain dysfunction.

Therapeutic Use and Chronic Abuse of CNS Stimulants and Anabolic Drugs

The available evidence suggests that affective disorders, such as depression and anxiety, increase risk for accelerated cognitive decline and late-life dementia in aging individuals. Behavioral neuropsychology studies also showed that cognitive decline is a central feature of aging impacting the quality of life. Motor deficits are common after traumatic brain injuries and stroke, affect subjective well-being, and are linked with reduced quality of life. Currently, restorative therapies that target the brain directly to restore cognitive and motor tasks in aging and disease are available. However, the very same drugs used for therapeutic purposes are employed by athletes as stimulants either to increase performance for fame and financial rewards or as recreational drugs. Unfortunately, most of these drugs have severe side effects and pose a serious threat to the health of athletes. The use of performance-enhancing drugs by children and teenagers has increased tremendously due to the decrease in the age of players in competitive sports and the availability of various stimulants in many forms and shapes. Thus, doping may cause serious health-threatening conditions including, infertility, subdural hematomas, liver and kidney dysfunction, peripheral edema, cardiac hypertrophy, myocardial ischemia, thrombosis, and cardiovascular disease. In this review, we focus on the impact of doping on psychopathological disorders, cognition, and depression. Occasionally, we also refer to chronic use of therapeutic drugs to increase physical performance and highlight the underlying mechanisms. We conclude that raising awareness on the health risks of doping in sport for all shall promote an increased awareness for healthy lifestyles across all generations.

Differentiating amnestic from non-amnestic mild cognitive impairment subtypes using graph theoretical measures of electroencephalography

The purpose of this study was to explore different patterns of functional networks between amnestic mild cognitive impairment (aMCI) and non-aMCI (naMCI) using electroencephalography (EEG) graph theoretical analysis. The data of 197 drug-naïve individuals who complained cognitive impairment were reviewed. Resting-state EEG data was acquired. Graph analyses were performed and compared between aMCI and naMCI, as well as between early and late aMCI. Correlation analyses were conducted between the graph measures and neuropsychological test results. Machine learning algorithms were applied to determine whether the EEG graph measures could be used to distinguish aMCI from naMCI. Compared to naMCI, aMCI showed higher modularity in the beta band and lower radius in the gamma band. Modularity was negatively correlated with scores on the semantic fluency test, and the radius in the gamma band was positively correlated with visual memory, phonemic, and semantic fluency tests. The naïve Bayes algorithm classified aMCI and naMCI with 89% accuracy. Late aMCI showed inefficient and segregated network properties compared to early aMCI. Graph measures could differentiate aMCI from naMCI, suggesting that these measures might be considered as predictive markers for progression to Alzheimer’s dementia in patients with MCI.