BAG1 restores formation of functional DJ-1 L166P dimers and DJ-1 chaperone activity

The L166P mutation in DJ-1 is associated with Parkinson’s disease. DJ-1–interacting protein BAG1 chaperones mutant DJ-1 and reverses its mutant phenotype

Function of hyperekplexia-causing alpha(1)R271Q/L glycine receptors is restored by shifting the affected residue out of the allosteric signaling pathway

BACKGROUND AND PURPOSE Glycine receptor a1 subunit R271Q and R271L (a1R271Q/L) mutations cause the neuromotor disorder, hereditary hyperekplexia. Studies suggest that the 271 residue is located within the allosteric signalling pathway linking the agonist binding site to the channel gate. The present study aimed to investigate a possible mechanism for restoring the function of the a1R271Q/L glycine receptor

Mutations reveal voltage gating of CNGA1 channels in saturating cGMP

Activity of cyclic nucleotide–gated (CNG) cation channels underlies signal transduction in vertebrate visual receptors. These highly specialized receptor channels open when they bind cyclic GMP (cGMP). Here, we find that certain mutations restricted to the region around the ion selectivity filter render the channels essentially fully voltage gated, in such a manner that the channels remain mostly closed at physiological voltages, even in the presence of saturating concentrations of cGMP. This voltage-dependent gating resembles the selectivity filter-based mechanism seen in KcsA K+ channels, not the S4-based mechanism of voltage-gated K+ channels. Mutations that render CNG channels gated by voltage loosen the attachment of the selectivity filter to its surrounding structure, thereby shifting the channel's gating equilibrium toward closed conformations. Significant pore opening in mutant channels occurs only when positive voltages drive the pore from a low-probability open conformation toward a second open conformation to increase the channels' open probability. Thus, the structure surrounding the selectivity filter has evolved to (nearly completely) suppress the expression of inherent voltage-dependent gating of CNGA1, ensuring that the binding of cGMP by itself suffices to open the channels at physiological voltages

Structure and Molecular Evolution of CDGSH Iron-Sulfur Domains

The recently discovered CDGSH iron-sulfur domains (CISDs) are classified into seven major types with a wide distribution throughout the three domains of life. The type 1 protein mitoNEET has been shown to fold into a dimer with the signature CDGSH motif binding to a [2Fe-2S] cluster. However, the structures of all other types of CISDs were unknown. Here we report the crystal structures of type 3, 4, and 6 CISDs determined at 1.5 Å, 1.8 Å and 1.15 Å resolution, respectively. The type 3 and 4 CISD each contain one CDGSH motif and adopt a dimeric structure. Although similar to each other, the two structures have permutated topologies, and both are distinct from the type 1 structure. The type 6 CISD contains tandem CDGSH motifs and adopts a monomeric structure with an internal pseudo dyad symmetry. All currently known CISD structures share dual iron-sulfur binding modules and a β-sandwich for either intermolecular or intramolecular dimerization. The iron-sulfur binding module, the β-strand N-terminal to the module and a proline motif are conserved among different type structures, but the dimerization module and the interface and orientation between the two iron-sulfur binding modules are divergent. Sequence analysis further shows resemblance between CISD types 4 and 7 and between 1 and 2. Our findings suggest that all CISDs share common ancestry and diverged into three primary folds with a characteristic phylogenetic distribution: a eukaryote-specific fold adopted by types 1 and 2 proteins, a prokaryote-specific fold adopted by types 3, 4 and 7 proteins, and a tandem-motif fold adopted by types 5 and 6 proteins. Our comprehensive structural, sequential and phylogenetic analysis provides significant insight into the assembly principles and evolutionary relationship of CISDs

Lineage-Specific Biology Revealed by a Finished Genome Assembly of the Mouse

A finished clone-based assembly of the mouse genome reveals extensive recent sequence duplication during recent evolution and rodent-specific expansion of certain gene families. Newly assembled duplications contain protein-coding genes that are mostly involved in reproductive function

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries