Mitochondria-Dependent Cellular Toxicity of α-synuclein Modeled in Yeast

Parkinson’s disease is the second most common neurodegenerative disease. This disease is caused by the degeneration of dopaminergic neurons, leading to debilitating motor symptoms and early mortality. The protein α-synuclein (α-syn), encoded by SNCA, misfolds and forms inclusions in Parkinson’s disease brains. When α-syn is overexpressed in yeast, it causes cellular toxicity and an increased number of aggregates, recapitulating the toxic phenotypes observed in humans and animal models. Yeast models are a powerful tool to perform high-throughput overexpression screening to identify modifiers of α-syn toxicity. α-syn causes mitochondrial dysfunction by inhibiting complex I and inducing mitochondrial fragmentation. Prior screening of α-syn were limited to only the galactose condition, where mitochondrial function is dispensable. Previous screening was performed exclusively with the GAL1 promoter, restricting the genes to only those induced by galactose. We have validated an overexpression system using GAL3 alleles that can induce genes under mitochondrial-dependent glycerol-ethanol condition and other non-galactose conditions (calorie restriction, nitrogen starvation and raffinose). α-syn showed discrepancy in the correlation of toxicity and aggregation in non-galactose conditions. Compared to galactose, under glycerol-ethanol condition, α-syn exhibited higher toxicity, formed more aggregates, and decreased viability and respiratory competency despite having similar expression under the two conditions. We screened 14,827 human gene clones and identified 87 that can suppress α-syn toxicity in glycerol-ethanol. Genes involved in RNA polymerase II function, anterior-posterior axis and nucleoplasm were overrepresented. Among the suppressor hits, we identified four 14-3-3 protein isotypes (β, γ, θ, and ζ). None of the four suppressors suppressed the toxicity under galactose. However, the 14-3-3 suppressors did not reduce aggregates under glycerol-ethanol. No increase in respiratory competency was observed; however, 14-3-3β was seen to effectively reduce the number of cells that accumulate ROS. Overall, we have created an overexpression system that describes a new path for performing screening in non-galactose conditions. Our results based on novel phenotypes of α-syn show that screening in these conditions is indeed important. We have identified previously unknown suppressors of α-syn toxicity and ruled out underlying mechanisms of action

The Singapore heart failure outcomes and phenotypes (SHOP) study and prospective evaluation of outcome in patients with heart failure with preserved left ventricular ejection fraction (PEOPLE) study: Rationale and design

10.1016/j.cardfail.2013.01.007Journal of Cardiac Failure193156-16

Predicting heart failure with preserved and reduced ejection fraction: The international collaboration on heart failure subtypes

Background Heart failure (HF) is a prevalent and deadly disease, and preventive strategies focused on at-risk individuals are needed. Current HF prediction models have not examined HF subtypes. We sought to develop and validate risk prediction models for HF with preserved and reduced ejection fraction (HFpEF, HFrEF). Methods and Results Of 28,820 participants from 4 community-based cohorts, 982 developed incident HFpEF and 909 HFrEF during a median follow-up of 12 years. Three cohorts were combined, and a 2:1 random split was used for derivation and internal validation, with the fourth cohort as external validation. Models accounted for multiple competing risks (death, other HF subtype, and unclassified HF). The HFpEF-specific model included age, sex, systolic blood pressure, body mass index, antihypertensive treatment, and previous myocardial infarction; it had good discrimination in derivation (c-statistic 0.80; 95% confidence interval [CI], 0.78–0.82) and validation samples (internal: 0.79; 95% CI, 0.77–0.82 and external: 0.76; 95% CI: 0.71–0.80). The HFrEF-specific model additionally included smoking, left ventricular hypertrophy, left bundle branch block, and diabetes mellitus; it had good discrimination in derivation (c-statistic 0.82; 95% CI, 0.80–0.84) and validation samples (internal: 0.80; 95% CI, 0.78–0.83 and external: 0.76; 95% CI, 0.71–0.80). Age was more strongly associated with HFpEF, and male sex, left ventricular hypertrophy, bundle branch block, previous myocardial infarction, and smoking with HFrEF (P value for each comparison ≤0.02). Conclusions We describe and validate risk prediction models for HF subtypes and show good discrimination in a large sample. Some risk factors differed between HFpEF and HFrEF, supporting the notion of pathogenetic differences among HF subtypes

Growth differentiation factor 15, ST2, high-sensivity troponin T, and N-terminal pro brain natriuretic peptide in heart failure with preserved vs. reduced ejection fraction

10.1093/eurjhf/hfs130European Journal of Heart Failure14121338–134