Per Svenningsson’s research while affiliated with Karolinska University Hospital and other places

Here, we introduce Met-ID, a graphical user interface software designed to efficiently identify metabolites from MALDI-MSI data sets. Met-ID enables annotation of m/z features from any type of MALDI-MSI experiment, involving either derivatizing or conventional matrices. It utilizes structural information for derivatizing matrices to generate a subset of targets that contain only functional groups specific to the derivatization agent. The software is able to identify multiple derivatization sites on the same molecule, facilitating identification of the derivatized compound. This ability is exemplified by FMP-10, a reactive matrix that assists the covalent charge-tagging of molecules containing phenolic hydroxyl and/or primary or secondary amine groups. Met-ID also permits users to recalibrate data with known m/z ratios, boosting confidence in mass match results. Furthermore, Met-ID includes a database featuring MS2 spectra of numerous chemical standards, consisting of neurotransmitters and metabolites derivatized with FMP-10, alongside peaks for FMP-10 itself, all accessible directly through the software. The MS2 spectral database supports user-uploaded spectra and enables comparison of these spectra with user-provided tissue MS2 spectra for similarity assessment. Although initially installed with basic data, Met-ID is designed to be customizable, encouraging users to tailor the software to their specific needs. While several MSI-oriented software solutions exist, Met-ID combines both MS1 and MS2 functionalities. Developed in alignment with the FAIR Guiding Principles for scientific software, Met-ID is freely available as an open-source tool on GitHub, ensuring wide accessibility and collaboration.

Background Individual variability in clinical response to dopamine replacement therapy (DRT) is a key barrier to efficacious treatment for patients with Parkinson's disease (PD). A better understanding of the neurobiological sources of such interindividual differences is necessary to personalize DRT prescribing, inform future clinical interventions, and motivate translational research. Objective One potential source of this variability is an unintended secondary activation of extra‐nigrostriatal dopamine systems by DRT, particularly in the neocortex. Our goal was to determine the clinical effects of cortical dopamine system activation by DRT in patients with PD. Methods We used pharmaco‐magnetoencephalography data collected from patients with PD (N PD = 17, N HC = 20) before and after DRT to map their cortical neurophysiological responses to dopaminergic pharmacotherapy. By combining these DRT response maps with normative atlases of cortical dopamine system densities, we linked the variable enhancement of rhythmic cortical activity by DRT to dopamine‐rich cortical regions and determined its clinical relevance. Results We found beta‐rhythmic responses to DRT in dopamine‐rich regions of the cortex that are expressed variably across individuals. Importantly, patients who exhibited a larger dopaminergic beta cortical enhancement showed a smaller clinical improvement from DRT, indicating a potential source of individual variability in medication response for patients with PD. Conclusions We conclude that these findings inform our understanding of the dopaminergic basis of neurophysiological variability often seen in patients with PD, and indicate that our methodological approach may be useful for data‐driven contextualization of medication effects on cortical neurophysiology in future research and clinical applications. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

G protein-coupled receptors (GPCRs) control numerous physiological processes and are important therapeutic targets. Despite major research efforts, rational design of drugs that stimulate GPCR signaling is challenging because the molecular basis of activation remains poorly understood. Here, a combination of molecular dynamics simulations and pharmacological assays was used to study the activation mechanism of the D2 dopamine receptor (D2R), a major drug target for central nervous system diseases. Enhanced sampling simulations were performed to identify the key conformational changes involved in D2R activation by dopamine, and a computational platform for ligand profiling based on free energy calculations was developed. Simulations and experimental characterization of a series of dopamine derivatives showed that free energy calculations can predict the effect of small chemical modifications on ligand affinity and efficacy. Furthermore, simulations of D2 dopamine and β2 adrenergic receptor activation revealed that ligand-induced activation of these GPCRs is driven by different molecular mechanisms despite recognizing chemically similar catecholamine agonists. Whereas dopamine interactions with the sixth transmembrane helix primarily drive activation of the D2R, hydrogen bonding with the fifth helix is the key interaction for activation of the β2 adrenergic receptor. Our results highlight the complexity of GPCR activation and illustrate how molecular simulations can provide mechanistic insight and quantitative predictions of ligand activity, enabling structure-based drug design.

G protein-coupled receptors (GPCRs) can signal in the absence of agonists through constitutive activity. This activity can be enhanced by mutations, resulting in receptors known as constitutively active mutants (CAMs). Such receptors can be implicated in various physiological and pathophysiological conditions, and also offer significant therapeutic potential. However, the molecular basis of their constitutive activity remains unknown. To investigate how CAMs affect receptor activation, we employed enhanced sampling simulations to study the dopamine D2 receptor (D2R), a key target in central nervous system therapies. Free energy landscape analyses revealed that CAMs promote a conformational shift favoring an active state similar to the agonist-bound receptor. To then identify novel CAMs, we developed a comprehensive strategy combining structural comparison, in-silico residue scanning, and free energy calculations, validated by luminescence-complementation-based assays. Applied to D2R, this approach uncovered a new single-point CAM, D2R-I48 1.46 W, which was functionally validated. Further investigation revealed that this mutation activates allosteric communication pathways primarily involving transmembrane helix 5, particularly Ser194 5.43 , underscoring its role in transmitting activation signals to the intracellular domain. These findings deepen our understanding of constitutive GPCR activity and demonstrate the utility of this framework for identifying CAMs as ligand-independent models for structural, cellular, and physiological studies.

Magnetic Resonance Elastography (MRE) is a method capable of mapping the brain's mechanical properties, however, the microstructural mechanisms responsible for these biomechanical properties remain largely unknown. For this reason, the present study utilized multidimensional diffusion-MRI (MD-dMRI), apart from MRE, to extract microstructural parameters for a cohort of Parkinson's disease (PD) patients and healthy controls. Significant softening effects in the temporal and occipital lobes in PD were associated with an increase in mean diffusivity, whereas other microstructural properties, e.g. microscopic FA (μFA), largely remained unchanged. Across most regions, stiffness declined with age, which was correlated with a decrease in μFA and an increase in MD. We hypothesize that age softening effects mostly can be explained by neuronal atrophy, whereas PD effects involve additional mechanisms.

Memory is a crucial cognitive function that deteriorates with age. However, this ability is normally assessed using cognitive tests instead of the architecture of brain networks. Here, we use reservoir computing, a recurrent neural network computing paradigm, to assess the linear memory capacities of neural-network reservoirs extracted from brain anatomical connectivity data in a lifespan cohort of 636 individuals. The computational memory capacity emerges as a robust marker of aging, being associated with resting-state functional activity, white matter integrity, locus coeruleus signal intensity, and cognitive performance. We replicate our findings in an independent cohort of 154 young and 72 old individuals. By linking the computational memory capacity of the brain network with cognition, brain function and integrity, our findings open new pathways to employ reservoir computing to investigate aging and age-related disorders.

Background Levodopa‐induced dyskinesia (LID) in Parkinson's disease (PD) is associated with ‘false neurotransmitter’ release of dopamine from serotonin (5‐HT) neurons. NLX‐112 is a first‐in‐class, highly selective 5‐HT 1A receptor agonist which counteracts LIDs in experimental PD models. Objectives The primary objective was to evaluate the safety and tolerability of NLX‐112 compared with placebo in people with PD. The secondary objective was to assess the preliminary efficacy of NLX‐112 in reducing LID and its effects on PD symptoms. Methods Participants received NLX‐112 or placebo (2:1 ratio) alongside stable Parkinson's medications, with 22 participants completing the study. Dosing was up‐titrated over 28 days to 2 mg/day (1 mg twice daily), stabilized for 14 days (to day 42), and down‐titrated for 14 days. Efficacy was measured using the Unified Dyskinesia Rating Scale (UDysRS), Unified Parkinson's Disease Rating Scale (UPDRS), and Clinical Global Impression of Change (CGI‐C) following a levodopa challenge (150% of usual dose). Results Adverse events (AEs) were mainly central nervous system (CNS)‐related and mostly occurred during up‐titration, with no serious AEs in the NLX‐112 group. There were no treatment‐induced clinically significant changes in vital signs, electrocardiogram, or laboratory parameters. NLX‐112 reduced LID from baseline levels: at day 42, UDysRS total score decreased by 6.3 points, whereas placebo group changes were not significant (−2.4). NLX‐112 also reduced parkinsonism from baseline values: UPDRS Part 3 scores decreased by 3.7 points, whereas placebo group changes were non‐significant (+0.1). In CGI‐C assessment, the NLX‐112 group showed greater improvement than the placebo group (53% vs. 29%). Conclusion These results support further clinical investigation of NLX‐112 for treatment of PD LID. © 2025 Neurolixis SAS. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The atypical antipsychotic clozapine targets multiple receptor systems beyond the dopaminergic pathway and influences prepulse inhibition (PPI), a critical translational measure of sensorimotor gating. Since PPI is modulated by atypical antipsychotics such as risperidone and clozapine, we hypothesized that p11—an adaptor protein associated with anxiety- and depressive-like behaviors and G-protein-coupled receptor function—might modulate these effects. In this study, we assessed the role of p11 in clozapine’s PPI-enhancing effect by testing wild-type and global p11 knockout (KO) mice in response to haloperidol, risperidone, and clozapine. We also performed structural and functional brain imaging. Contrary to our expectation that anxiety-like p11-KO mice would exhibit an augmented startle response and heightened sensitivity to clozapine, PPI tests showed that p11-KO mice were unresponsive to the PPI-enhancing effects of risperidone and clozapine. Imaging revealed distinct regional brain volume differences and reduced hippocampal connectivity in p11-KO mice, with significantly blunted clozapine-induced connectivity changes in the CA1 region. Our findings highlight a novel role for p11 in modulating clozapine’s effects on sensorimotor gating and hippocampal connectivity, offering new insight into its functional pathways.

Background Dysregulated leukotriene signaling is proposed to be involved in pathogenesis of Parkinson's disease (PD). Objective The objective was to examine the safety and tolerability of montelukast, a cysteinyl‐leukotriene receptor1 and GPR17 antagonist, in patients with PD. Secondary outcomes were target engagement, effects on PD signs/symptoms, and central neuroinflammation. Methods Fifteen PD patients were recruited to a 12‐week open‐label trial of 20 mg bi‐daily montelukast treatment. Patients underwent ratings with the Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS‐UPDRS), the Montreal Cognitive Assessment (MoCA), Beck's Depression Inventory (BDI), Parkinson's Disease Questionnaire‐39 (PDQ‐39), [ ¹¹ C]PBR28‐PET, and lumbar punctures before and during montelukast treatment. Results All patients completed the study. Three patients reported loose stool. No serious adverse events related to treatment were reported. MDS‐UPDRS‐Total scores improved by 6.9 points. Very low levels of montelukast were detected in all cerebrospinal fluid (CSF) samples and resulted in a reduction in inflammation/metabolism markers. [ ¹¹ C]PBR28 binding was lowered in high, but not mixed, affinity binders after montelukast. Conclusions Montelukast crosses the blood–brain barrier at very low levels and is well tolerated and safe in PD patients. Preliminary effects on neuroinflammation and clinical scores motivate a future randomized controlled trial (RCT) in PD. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.