Unravelling the effects of methylphenidate on the dopaminergic and noradrenergic functional circuits

Functional magnetic resonance imaging (fMRI) can be combined with drugs to investigate the system-level functional responses in the brain to such challenges. However, most psychoactive agents act on multiple neurotransmitters, limiting the ability of fMRI to identify functional effects related to actions on discrete pharmacological targets. We recently introduced a multimodal approach, REACT (Receptor-Enriched Analysis of functional Connectivity by Targets), which offers the opportunity to disentangle effects of drugs on different neurotransmitters and clarify the biological mechanisms driving clinical efficacy and side effects of a compound. Here, we focus on methylphenidate (MPH), which binds to the dopamine transporter (DAT) and the norepinephrine transporter (NET), to unravel its effects on dopaminergic and noradrenergic functional circuits in the healthy brain at rest. We then explored the relationship between these target-enriched resting state functional connectivity (FC) maps and inter-individual variability in behavioural responses to a reinforcement-learning task encompassing a novelty manipulation to disentangle the molecular systems underlying specific cognitive/behavioural effects. Our main analysis showed a significant MPH-induced FC increase in sensorimotor areas in the functional circuit associated with DAT. In our exploratory analysis, we found that MPH-induced regional variations in the DAT and NET-enriched FC maps were significantly correlated with some of the inter-individual differences on key behavioural responses associated with the reinforcement-learning task. Our findings show that main MPH-related FC changes at rest can be understood through the distribution of DAT in the brain. Furthermore, they suggest that when compounds have mixed pharmacological profiles, REACT may be able to capture regional functional effects that are underpinned by the same cognitive mechanism but are related to engagement of distinct molecular targets

Variability in Physical Activity Assessed with Accelerometer Is an Independent Predictor of Mortality in CHF Patients - Fig 4

<p>a) Graphic cox-regression over HFSS on 5-year all cause mortality, low risk (black), intermediate risk (blue) and high risk (red). b) Graphic cox regression on addition of Peak 3h skewness on top of HFSS-risk. Solid line denote skewness below median, dotted line denote skewness above median. Black denotes low risk, blue intermediate risk and red high risk based on calculated HFSS-score</p

Discordant gene expression in subcutaneous adipose and skeletal muscle tissues in response to exercise training

Exercise has different effects on different tissues in the body, the sum of which may determine the response to exercise and the health benefits. In the present study, we aimed to investigate whether physical training regulates transcriptional network communites common to both skeletal muscle (SM) and subcutaneous adipose tissue (SAT). Eight such shared transcriptional communities were found in both tissues. Eighteen young overweight adults voluntarily participated in 7 weeks of combined strength and endurance training (five training sessions per week). Biopsies were taken from SM and SAT before and after training. Five of the network communities were regulated by training in SM but showed no change in SAT. One community involved in insulin- AMPK signaling and glucose utilization was upregulated in SM but downregulated in SAT. This diverging exercise regulation was confirmed in two independent studies and was also associated with BMI and diabetes in an independent cohort. Thus, the current finding is consistent with the differential responses of different tissues and suggests that body composition may influence the observed individual whole-body metabolic response to exercise training and help explain the observed attenuated whole-body insulin sensitivity after exercise training, even if it has significant effects on the exercising muscle

Discordant gene expression in subcutaneous adipose and skeletal muscle tissues in response to exercise training

Exercise has different effects on different tissues in the body, the sum of which may determine the response to exercise and the health benefits. In the present study, we aimed to investigate whether physical training regulates transcriptional network communites common to both skeletal muscle (SM) and subcutaneous adipose tissue (SAT). Eight such shared transcriptional communities were found in both tissues. Eighteen young overweight adults voluntarily participated in 7 weeks of combined strength and endurance training (five training sessions per week). Biopsies were taken from SM and SAT before and after training. Five of the network communities were regulated by training in SM but showed no change in SAT. One community involved in insulin- AMPK signaling and glucose utilization was upregulated in SM but downregulated in SAT. This diverging exercise regulation was confirmed in two independent studies and was also associated with BMI and diabetes in an independent cohort. Thus, the current finding is consistent with the differential responses of different tissues and suggests that body composition may influence the observed individual whole-body metabolic response to exercise training and help explain the observed attenuated whole-body insulin sensitivity after exercise training, even if it has significant effects on the exercising muscle

Principal components analysis (PCA) and biplot of all accelerometer derived variables.

<p>Variables measuring time spent physically active/inactive are colored black whereas novel variables based on periods with high physical activity are colored blue. Patient observations are colored black for censored data (survivors) and red for mortality events. The size of each observation corresponds to time until event, i.e. large circles correspond to early event and worse prognosis. Most of the total variance is captured with the two first principal components (69.15%) and the various variables thus covary to a large extent. The absolute majority of the observations with mortality events, in particular observations with early mortality events, are closely correlated with 1, 3 and 12 h skewness and 1, 3 and 12 h kurtosis.</p

5-year all-cause mortality.

<p>5-year all-cause mortality.</p

Baseline clinical characteristics and clinical characteristics of patients with high vs. low 3 h skewness.

<p>Baseline clinical characteristics and clinical characteristics of patients with high vs. low 3 h skewness.</p

Asymmetric cellular responses in primary human myoblasts using sera of different origin and specification

<div><p>For successful growth and maintenance of primary myogenic cells <i>in vitro</i>, culture medium and addition of sera are the most important factors. At present it is not established as to what extent sera of different origin and composition, supplemented in media or serum-free media conditions influence myoblast function and responses to different stimuli. By assessing markers of proliferation, differentiation/fusion, quiescence, apoptosis and protein synthesis the aim of the current study was to elucidate how primary human myoblasts and myotubes are modulated by different commonly used serum using FCS (foetal calf serum), (CS-FCS charcoal-stripped FCS, a manufacturing process to remove hormones and growth factors from sera), HS (horse serum) as well as in serum free conditions (DMEM). To characterise the biological impact of the different serum, myoblasts were stimulated with Insulin (100 nM) and Vitamin D (100 nM; 1α,25(OH)₂D₃, 1α,25-Dihydroxycholecalciferol, Calcitriol), two factors with characterised effects on promoting fusion and protein synthesis or quiescence, respectively in human myoblasts/myotubes. We demonstrate that sera of different origin/formulation differentially affect myoblast proliferation and myotube protein synthesis. Importantly, we showed that quantifying the extent to which Insulin effects myoblasts <i>in vitro</i> is highly dependent upon serum addition and which type is present in the media. Upregulation of mRNA markers for myogenic fusion, Myogenin, with Insulin stimulation, relative to DMEM, appeared dampened at varying degrees with serum addition and effects on p70S6K phosphorylation as a marker of protein synthesis could not be identified unless serum was removed from media. We propose that these asymmetric molecular and biochemical responses in human myoblasts reflect the variable composition of mitogenic and anabolic factors in each of the sera. The results have implications for both the reproducibility and interpretation of results from experimental models in myoblast cells/myotubes.</p></div

Serum induced activation of p70S6K independent of Insulin action.

<p>Myoblasts were differentiated in low serum media, 2% FCS, containing DMEM-F12 GlutaMAX/1% ABAM for 5-d, forming myotubes. After 5-d myotubes were PBS washed (3 ×) and serum starved overnight in DMEM only (12 h) before exposure to DMEM-F12 GlutaMAX/1% ABAM alone (serum-free, DMEM only) or with the addition of 2% FCS, 2% CS-FCS or 2% HS containing 100nM Insulin, 100nM 1α,25(OH)₂D₃ or vehicle alone for 4 h and protein lysates collected. FCS and HS are sufficiently anabolic such that impact of Insulin treatment on p70S6K phosphorylation cannot be determined unless serum is removed, DMEM only. * P<0.05) from DMEM Control and Vitamin D. × exclusion of n = 1 outlier. For all other from n = 6 blots.</p

Serum induced activation of p70S6K independent of Insulin action.

<p>Myoblasts were differentiated in low serum media, 2% FCS, containing DMEM-F12 GlutaMAX/1% ABAM for 5-d, forming myotubes. After 5-d myotubes were PBS washed (3 ×) and serum starved overnight in DMEM only (12 h) before exposure to DMEM-F12 GlutaMAX/1% ABAM alone (serum-free, DMEM only) or with the addition of 2% FCS, 2% CS-FCS or 2% HS containing 100nM Insulin, 100nM 1α,25(OH)₂D₃ or vehicle alone for 4 h and protein lysates collected. FCS and HS are sufficiently anabolic such that impact of Insulin treatment on p70S6K phosphorylation cannot be determined unless serum is removed, DMEM only. * P<0.05) from DMEM Control and Vitamin D. × exclusion of n = 1 outlier. For all other from n = 6 blots.</p