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 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

Effect of electro-ejaculation on the serum cortisol response of Criollo goats (Capra hircus)

Concern has been expressed on animal welfare in the use of electro-ejaculation (EE) as a semen collection technique. Furthermore, even though breed differences in stress response have been demonstrated in goats, a lack of background information characterizes the Criollo genotype. Therefore, in the present experiment, changes in concentrations of serum cortisol in serial blood samples were used to quantify stress response to EE in Criollo goats. Twenty intact Criollo bucks aged 1.5-3 years and weighing between 33 and 40 kg were randomly assigned to one of two treatments: bucks that were electro-ejaculated (T1) compared to males that a rectal probe was inserted without EE (T0). Blood samples were collected by venipuncture at 0 (immediately before inserting the rectal probe), 20, 40, 60 and 90 min after the onset of the experiment. To compare blood cortisol concentrations between treatments and the sequential data recorded on the same set of animals, a repeated measures analysis of variance model was used. The increases in concentrations of serum cortisol were significantly higher (P 350% increase in serum cortisol concentration 20 min after EE indicates an acute stress response despite the peak values being only slightly above the basal serum cortisol levels found in other goat breeds. (c) 2006 Elsevier B.V. All rights reserved

Strength of Axial Water Ligation in Substrate-Free Cytochrome P450s Is Isoform Dependent

[Image: see text] The heme-containing cytochrome P450s exhibit isoform-dependent ferric spin equilibria in the resting state and differential substrate-dependent spin equilibria. The basis for these differences is not well understood. Here, magnetic circular dichroism (MCD) reveals significant differences in the resting low spin ligand field of CYPs 3A4, 2E1, 2C9, 125A1, and 51B1, which indicates differences in the strength of axial water ligation to the heme. The near-infrared bands that specifically correspond to charge-transfer porphyrin-to-metal transitions span a range of energies of nearly 2 kcal/mol. In addition, the experimentally determined MCD bands are not entirely in agreement with the expected MCD energies calculated from electron paramagnetic resonance parameters, thus emphasizing the need for the experimental data. MCD marker bands of the high spin heme between 500 and 680 nm were also measured and suggest only a narrow range of energies for this ensemble of high spin Cys(S(–)) → Fe(3+) transitions among these isoforms. The differences in axial ligand energies between CYP isoforms of the low spin states likely contribute to the energetics of substrate-dependent spin state perturbation. However, these ligand field energies do not correlate with the fraction of high spin vs low spin in the resting state enzyme, suggestive of differences in water access to the heme or isoform-dependent differences in the substrate-free high spin states as well