Painful and painless mutations of SCN9A and SCN11A voltage-gated sodium channels

Chronic pain is a global problem affecting up to 20% of the world’s population and has a significant economic, social and personal cost to society. Sensory neurons of the dorsal root ganglia (DRG) detect noxious stimuli and transmit this sensory information to regions of the central nervous system (CNS) where activity is perceived as pain. DRG neurons express multiple voltage-gated sodium channels that underlie their excitability. Research over the last 20 years has provided valuable insights into the critical roles that two channels, NaV1.7 and NaV1.9, play in pain signalling in man. Gain of function mutations in NaV1.7 cause painful conditions while loss of function mutations cause complete insensitivity to pain. Only gain of function mutations have been reported for NaV1.9. However, while most NaV1.9 mutations lead to painful conditions, a few are reported to cause insensitivity to pain. The critical roles these channels play in pain along with their low expression in the CNS and heart muscle suggest they are valid targets for novel analgesic drugs

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

Phenotype-Genotype analysis of dystrophinopathy caused by duplication mutation in Dystrophin gene in an African patient

Background: The dystrophinopathies, duchenne muscular dystrophy (DMD) and Becker muscular dystrophy are common X-linked genetic myopathies resulting from mutations in the dystrophin gene. Duplication is an uncommon mechanism of mutation occurring in about 5% of DMD cases. The global prevalence of DMD is reported as 1/18,000 males. There is little clinical or epidemiological data on African patients.Objective: To present the genotype-phenotype analysis of dystrophinopathy with an exon 8 through 9 duplication mutation in a patient of African/Ghanaian descent and his asymptomatic mother.Methods: Investigations including a biopsy of the vastus lateralis muscle and genetic testing of the patient and his mother.Results: Genetic testing demonstrated a duplication of exons 8 through 9 of the dystrophin gene in both the patient and his mother. The muscle biopsy of the patient showed partial expression of the dystrophin protein. In the absence of a family history of dystrophinopathy, we hypothesize that this is a sporadic mutation occurring in the grand maternal lineage.Conclusion: This case extends the world wide epidemiology of this disease to include the African/Ghanaian population and confirms the vulnerability of the dystrophin gene to recurrent spontaneous mutations at the exon 8 and 9 site

Phenotype-Genotype analysis of dystrophinopathy caused by duplication mutation in duplication mutation in Dystrophin gene in an African patient

Background: The dystrophinopathies, duchenne muscular dystrophy (DMD) and Becker muscular dystrophy are common X-linked genetic myopathies resulting from mutations in the dystrophin gene. Duplication is an uncommon mechanism of mutation occurring in about 5% of DMD cases. The global prevalence of DMD is reported as 1/18,000 males. There is little clinical or epidemiological data on African patients. Objective: To present the genotype-phenotype analysis of dystrophinopathy with an exon 8 through 9 duplication mutation in a patient of African/Ghanaian descent and his asymptomatic mother. Methods: Investigations including a biopsy of the vastus lateralis muscle and genetic testing of the patient and his mother. Results: Genetic testing demonstrated a duplication of exons 8 through 9 of the dystrophin gene in both the patient and his mother. The muscle biopsy of the patient showed partial expression of the dystrophin protein. In the absence of a family history of dystrophinopathy, we hypothesize that this is a sporadic mutation occurring in the grand maternal lineage. Conclusion: This case extends the world wide epidemiology of this disease to include the African/Ghanaian population and confirms the vulnerability of the dystrophin gene to recurrent spontaneous mutations at the exon 8 and 9 site

Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network.

BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P&lt;0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke

Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network.

BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke