The neurotransmitter glutamate facilitates neuronal signalling at excitatory synapses. Glutamate is released from the presynaptic membrane into the synaptic cleft. Across the synaptic cleft glutamate binds to both ion channels and metabotropic glutamate receptors at the postsynapse, which expedite downstream signalling in the neuron. The postsynaptic density, a highly specialized matrix, which is attached to the postsynaptic membrane, controls this downstream signalling. The postsynaptic density also resets the synapse after each synaptic firing. It is composed of numerous proteins including a family of Discs large associated protein 1, 2, 3 and 4 (DLGAP1-4) that act as scaffold proteins in the postsynaptic density. They link the glutamate receptors in the postsynaptic membrane to other glutamate receptors, to signalling proteins and to components of the cytoskeleton. With the central localisation in the postsynapse, the DLGAP family seems to play a vital role in synaptic scaling by regulating the turnover of both ionotropic and metabotropic glutamate receptors in response to synaptic activity. DLGAP family has been directly linked to a variety of psychological and neurological disorders. In this review we focus on the direct and indirect role of DLGAP family on schizophrenia as well as other brain diseases.

Background: Self-treatment with glaucoma medication (eye drops) has been associated with adherence challenges. Poor adherence results in worse outcomes in terms of visual field loss. Objective: To investigate patterns in medication adherence among Danish patients with glaucoma in relation to selected predictors of adherence, long-term adherence patterns, and long-term societal economic consequences of poor adherence. Methods and analysis: This register-based study included 30 100 glaucoma patients followed for 10 years between 2000 and 2018. Glaucoma was identified from the Danish national registers by diagnosis of Open Angle Glaucoma and/or by redeemed prescriptions of glaucoma medication. Logistic regression models were applied to estimate patient characteristics related to medical adherence. Diagnosis-related group fees were applied to estimate healthcare costs. Results: High adherence in the first year(s) of treatment was less likely among men (OR_{first year}: 0.78, 95% CI: 0.75 to 0.82), younger individuals and among those with a positive Charlson Comorbidity Index (CCI) score (OR_{first year/CCI≥3}: 0.71, 95% CI: 0.63 to 0.80). Adherence in the first year and in the first two years was associated with adherence in the fifth (OR_{first year}: 4.55, 95% CI: 4.30 to 4.82/OR_{first two years}: 6.47, 95% CI: 6.10 to 6.86) as with adherence in the 10th year with slightly lower estimates. Being medical adherent was related to higher costs related to glaucoma medication after 5 and 10 years comparing with poor adherence, whereas poor adherence was associated with a marked increase in long-term costs for hospital contacts. Conclusion: Increasing age, female sex and low comorbidity score are correlated with better adherence to glaucoma treatment. Adherence in the first years of treatment may be a good predictor for future adherence. In the long term, patients with poor adherence are overall more expensive to society in terms of hospital contacts.

Background: Familial hemiplegic migraine (FHM) is a rare form of migraine with aura that often has an autosomal dominant mode of inheritance. Rare mutations in the CACNA1A, ATP1A2 and SCN1A genes can all cause FHM revealing genetic heterogeneity in the disorder. Furthermore, only a small subset of the affected individuals has a causal mutation. We set out to investigate what differentiates patients with FHM with no mutation in any known FHM gene from patients with common types of migraine in both familial and sporadic cases. Methods: 2558 male and female participants from a migraine cohort from the Danish Headache Center were included. 112 had FHM; 743 had familial migraine; and 1703 had sporadic migraine. Using a linear regression model, we analysed for over-representation of rare functional variants in FHM versus familial migraine and sporadic migraine. Post hoc analyses included pathway analysis and testing for tissue specificity. Results: We found that patients with FHM have significantly more rare frameshift indels compared with patients with familial migraine and sporadic migraine. Pathway analysis revealed that the ‘ligand-gated ion channel activity’ and ‘G protein-coupled receptor downstream signalling’ pathways were significantly associated with mutated genes. We moreover found that the mutated genes showed tissue specificity towards nervous tissue and muscle tissue. Conclusion: We show that patients with FHM compared with patients with common types of migraine suffer from a higher load of rare frameshift indels in genes associated with synaptic signalling in the central nervous system and possibly in muscle tissue contributing to vascular dysfunction.

The Vps10p domain receptor SorCS2 is crucial for the development and function of the nervous system and essential for brain-derived neurotrophic factor (BDNF)-induced changes in neuronal morphology and plasticity. SorCS2 regulates the subcellular trafficking of the BDNF signaling receptor TrkB as well as selected neurotransmitter receptors in a manner that is dependent on the SorCS2 intracellular domain (ICD). However, the cellular machinery and adaptor protein (AP) interactions that regulate receptor trafficking via the SorCS2 ICD are unknown. We here identify four splice variants of human SorCS2 differing in the insertion of an acidic cluster motif and/or a serine residue within the ICD. We show that each variant undergoes posttranslational proteolytic processing into a one- or two-chain receptor, giving rise to eight protein isoforms, the expression of which differs between neuronal and nonneuronal tissues and is affected by cellular stressors. We found that the only variants without the serine were able to rescue BDNF-induced branching of SorCS2 knockout hippocampal neurons, while variants without the acidic cluster showed increased interactions with clathrin-associated APs AP-1, AP-2, and AP-3. Using yeast two-hybrid screens, we further discovered that all variants bound dynein light chain Tctex-type 3; however, only variants with an acidic cluster motif bound kinesin light chain 1. Accordingly, splice variants showed markedly different trafficking properties and localized to different subcellular compartments. Taken together, our findings demonstrate the existence of eight functional SorCS2 isoforms with differential capacity for interactions with cytosolic ligands dynein light chain Tctex-type 3 and kinesin light chain 1, which potentially allows cell-type specific SorCS2 trafficking and BDNF signaling.

Background: Post-market pharmacovigilance relies predominantly on single-database disproportionality analysis of spontaneous adverse event reports, which lacks corroboration across independent evidence streams and cannot integrate randomised trial evidence. No publicly accessible platform has previously combined European national pharmacovigilance registries, the US FDA Adverse Event Reporting System (FAERS), and clinical trial meta-analyses into a unified, continuously scored signal detection framework. Methods: We describe the Signal Consensus Index (SCI), a composite 0-100 pharmacovigilance signal score integrating disproportionality evidence from the Danish National Pharmacovigilance Database, the UK MHRA Yellow Card scheme, and FAERS, with DerSimonian-Laird meta-analytic risk ratios from ClinicalTrials.gov , across 6,905,874 drug-adverse event pairs. Each source contributes a continuous score derived from the lower bounds of three complementary disproportionality metrics (ROR, PRR, IC025) for spontaneous reporting sources, and from the pooled risk ratio lower confidence bound for clinical trials. The SCI is publicly accessible via the Adverse Event Atlas ( aeatlas.com ). We report reference set validation against the EU-ADR reference standard, a single-source comparison with discordance characterisation, temporal stability analysis across eight cumulative data windows (2015-2023), and a weight sensitivity analysis across seven pre-specified weighting schemes. Results: The SCI generated 129,176 Moderate-or-Strong signals (SCI ≥ 50, confidence ≥ 50) and 7,290 Strong signals (SCI ≥ 70, confidence ≥ 70). Reference set validation against 88 classifiable drug-event pairs (44 positive controls, 44 negative controls) yielded 18 true positives, 0 false positives, 44 true negatives, and 26 false negatives (sensitivity 40.9%, specificity 100.0%, PPV 100.0%, NPV 62.9%). Zero false positives were observed across all 44 classifiable negative controls, with five false negatives attributable to the confidence gate correctly suppressing single-source signals pending multi-source corroboration. Single-source comparison demonstrated that FAERS alone generated 1,438,246 disproportionality signals, of which 94.8% were not confirmed by the SCI, while 54,184 SCI-detected signals were absent from FAERS, of which 8.3% involved drugs absent from the US reporting system. Discordance analysis showed that 99.8% of Danish non-confirmation reflected data availability constraints. Temporal stability was high: 98.5% of pairs received identical classifications across all seven weight scenarios, and 57.0% of final Strong signals were already detectable as Moderate or Strong in the earliest data window (2015-2016). Strong classifications were stable across weight scenarios (94.0% of Strong observations remaining Strong). Conclusions: The SCI provides a transparent, openly accessible framework for cross-source pharmacovigilance signal prioritisation with 100% specificity and PPV against an established reference standard and stable classifications across weighting schemes. Progressive signal emergence through the Moderate tier supports its use as an early detection layer. The platform is available at aeatlas.com .