95 research outputs found

    Effect of Head Removal on Leaf Senescence of Sunflower

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    Efficiency of Nitrogen Assimilation by N 2

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    Mutations in Potassium Channel KCND3 Cause Spinocerebellar Ataxia Type 19

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    OBJECTIVE: To identify the causative gene for the neurodegenerative disorder spinocerebellar ataxia type 19 (SCA19) located on chromosomal region 1p21-q21. METHODS: Exome sequencing was used to identify the causal mutation in a large SCA19 family. We then screened 230 ataxia families for mutations located in the same gene (KCND3, also known as Kv4.3) using high-resolution melting. SCA19 brain autopsy material was evaluated, and in vitro experiments using ectopic expression of wild-type and mutant Kv4.3 were used to study protein localization, stability, and channel activity by patch-clamping. RESULTS: We detected a T352P mutation in the third extracellular loop of the voltage-gated potassium channel KCND3 that cosegregated with the disease phenotype in our original family. We identified 2 more novel missense mutations in the channel pore (M373I) and the S6 transmembrane domain (S390N) in 2 other ataxia families. T352P cerebellar autopsy material showed severe Purkinje cell degeneration, with abnormal intracellular accumulation and reduced protein levels of Kv4.3 in their soma. Ectopic expression of all mutant proteins in HeLa cells revealed retention in the endoplasmic reticulum and enhanced protein instability, in contrast to wild-type Kv4.3 that was localized on the plasma membrane. The regulatory β subunit Kv channel interacting protein 2 was able to rescue the membrane localization and the stability of 2 of the 3 mutant Kv4.3 complexes. However, this either did not restore the channel function of the membrane-located mutant Kv4.3 complexes or restored it only partially. INTERPRETATION: KCND3 mutations cause SCA19 by impaired protein maturation and/or reduced channel function

    rs5888 Variant of SCARB1 Gene Is a Possible Susceptibility Factor for Age-Related Macular Degeneration

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    Major genetic factors for age-related macular degeneration (AMD) have recently been identified as susceptibility risk factors, including variants in the CFH gene and the ARMS2 LOC387715/HTRA1locus. Our purpose was to perform a case-control study in two populations among individuals who did not carry risk variants for CFHY402H and LOC387715 A69S (ARMS2), called “study” individuals, in order to identify new genetic risk factors. Based on a candidate gene approach, we analyzed SNP rs5888 of the SCARB1 gene, coding for SRBI, which is involved in the lipid and lutein pathways. This study was conducted in a French series of 1241 AMD patients and 297 controls, and in a North American series of 1257 patients with advanced AMD and 1732 controls. Among these individuals, we identified 61 French patients, 77 French controls, 85 North American patients and 338 North American controls who did not carry the CFH nor ARMS2 polymorphisms. An association between AMD and the SCARB1 gene was seen among the study subjects. The genotypic distribution of the rs5888 polymorphism was significantly different between cases and controls in the French population (p<0.006). Heterozygosity at the rs5888 SNP increased risk of AMD compared to the CC genotypes in the French study population (odds ratio (OR) = 3.5, CI95%: 1.4–8.9, p<0.01) and after pooling the 2 populations (OR = 2.9, 95% CI: 1.6–5.3, p<0.002). Subgroup analysis in exudative forms of AMD revealed a pooled OR of 3.6 for individuals heterozygous for rs5888 (95% CI: 1.7–7.6, p<0.0015). These results suggest the possible contribution of SCARB1, a new genetic factor in AMD, and implicate a role for cholesterol and antioxidant micronutrient (lutein and vitamin E) metabolism in AMD

    Identifying subtypes of patients with neovascular age-related macular degeneration by genotypic and cardiovascular risk characteristics

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    <p>Abstract</p> <p>Background</p> <p>One of the challenges in the interpretation of studies showing associations between environmental and genotypic data with disease outcomes such as neovascular age-related macular degeneration (AMD) is understanding the phenotypic heterogeneity within a patient population with regard to any risk factor associated with the condition. This is critical when considering the potential therapeutic response of patients to any drug developed to treat the condition. In the present study, we identify patient subtypes or clusters which could represent several different targets for treatment development, based on genetic pathways in AMD and cardiovascular pathology.</p> <p>Methods</p> <p>We identified a sample of patients with neovascular AMD, that in previous studies had been shown to be at elevated risk for the disease through environmental factors such as cigarette smoking and genetic variants including the complement factor H gene (<it>CFH</it>) on chromosome 1q25 and variants in the <it>ARMS2</it>/HtrA serine peptidase 1 (<it>HTRA1</it>) gene(s) on chromosome 10q26. We conducted a multivariate segmentation analysis of 253 of these patients utilizing available epidemiologic and genetic data.</p> <p>Results</p> <p>In a multivariate model, cigarette smoking failed to differentiate subtypes of patients. However, four meaningfully distinct clusters of patients were identified that were most strongly differentiated by their cardiovascular health status (histories of hypercholesterolemia and hypertension), and the alleles of <it>ARMS2</it>/<it>HTRA1 </it>rs1049331.</p> <p>Conclusions</p> <p>These results have significant personalized medicine implications for drug developers attempting to determine the effective size of the treatable neovascular AMD population. Patient subtypes or clusters may represent different targets for therapeutic development based on genetic pathways in AMD and cardiovascular pathology, and treatments developed that may elevate CV risk, may be ill advised for certain of the clusters identified.</p

    SCORE2-Diabetes: 10-year cardiovascular risk estimation in type 2 diabetes in Europe

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    Aims: To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in individuals with type 2 diabetes in Europe. Methods and results: SCORE2-Diabetes was developed by extending SCORE2 algorithms using individual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further individuals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on individuals' levels of diabetes-related factors. For example, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m2, and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m2, and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively. Conclusion: SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in individuals with type 2 diabetes, enhances identification of individuals at higher risk of developing CVD across Europe
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