| 1. |
- Lahrouchi, Najim, et al.
(författare)
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Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome
- 2020
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 0009-7322 .- 1524-4539. ; 142:4, s. 324-338
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Tidskriftsartikel (refereegranskat)abstract
- Background: Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility. Methods: We conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score. Results: Genome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance (P<5x10(-8)) nearNOS1AP,KCNQ1, andKLF12, and 1 missense variant inKCNE1(p.Asp85Asn) at the suggestive threshold (P<10(-6)). Heritability analyses showed that approximate to 15% of variance in overall LQTS susceptibility was attributable to common genetic variation (h2SNP0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (r(g)=0.40;P=3.2x10(-3)). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls (P<10-13), and it is notable that, among patients with LQTS, this polygenic risk score was greater in patients who were genotype negative compared with those who were genotype positive (P<0.005). Conclusions: This work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.
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| 2. |
- Walsh, Roddy, et al.
(författare)
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Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of consortium disease cohorts and population controls
- 2021
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Ingår i: Genetics in Medicine. - : Nature Publishing Group. - 1098-3600 .- 1530-0366. ; 23:1, s. 47-58
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Stringent variant interpretation guidelines can lead to high rates of variants of uncertain significance (VUS) for genetically heterogeneous disease like long QT syndrome (LQTS) and Brugada syndrome (BrS). Quantitative and disease-specific customization of American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines can address this false negative rate.Methods: We compared rare variant frequencies from 1847 LQTS (KCNQ1/KCNH2/SCN5A) and 3335 BrS (SCN5A) cases from the International LQTS/BrS Genetics Consortia to population-specific gnomAD data and developed disease-specific criteria for ACMG/AMP evidence classes-rarity (PM2/BS1 rules) and case enrichment of individual (PS4) and domain-specific (PM1) variants.Results: Rare SCN5A variant prevalence differed between European (20.8%) and Japanese (8.9%) BrS patients (p = 5.7 x 10(-18)) and diagnosis with spontaneous (28.7%) versus induced (15.8%) Brugada type 1 electrocardiogram (ECG) (p = 1.3 x 10(-13)). Ion channel transmembrane regions and specific N-terminus (KCNH2) and C-terminus (KCNQ1/KCNH2) domains were characterized by high enrichment of case variants and >95% probability of pathogenicity. Applying the customized rules, 17.4% of European BrS and 74.8% of European LQTS cases had (likely) pathogenic variants, compared with estimated diagnostic yields (case excess over gnomAD) of 19.2%/82.1%, reducing VUS prevalence to close to background rare variant frequency.Conclusion: Large case-control data sets enable quantitative implementation of ACMG/AMP guidelines and increased sensitivity for inherited arrhythmia genetic testing.
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| 3. |
- Castiglione, Alessandro, et al.
(författare)
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Docosahexaenoic acid normalizes QT interval in long QT type 2 transgenic rabbit models in a genotype-specific fashion
- 2022
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Ingår i: Europace. - : OXFORD UNIV PRESS. - 1099-5129 .- 1532-2092. ; 24:3, s. 511-522
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Tidskriftsartikel (refereegranskat)abstract
- Aim Long QT syndrome (LQTS) is a cardiac channelopathy predisposing to ventricular arrhythmias and sudden cardiac death. Since current therapies often fail to prevent arrhythmic events in certain LQTS subtypes, new therapeutic strategies are needed. Docosahexaenoic acid (DHA) is a polyunsaturated fatty acid, which enhances the repolarizing I-Ks current. Methods and results We investigated the effects of DHA in wild type (WT) and transgenic long QT Type 1 (LQT1; loss of I-Ks), LQT2 (loss of I-Kr), LQT5 (reduction of I-Ks), and LQT2-5 (loss of I-Kr and reduction of I-Ks) rabbits. In vivo ECGs were recorded at baseline and after 10 mu M/kg DHA to assess changes in heart-rate corrected QT (QTc) and short-term variability of QT (STVQT). Ex vivo monophasic action potentials were recorded in Langendorff-perfused rabbit hearts, and action potential duration (APD(75)) and triangulation were assessed. Docosahexaenoic acid significantly shortened QTc in vivo only in WT and LQT2 rabbits, in which both alpha- and beta-subunits of I-K(s)-conducting channels are functionally intact. In LQT2, this led to a normalization of QTc and of its short-term variability. Docosahexaenoic acid had no effect on QTc in LQT1, LQT5, and LQT2-5. Similarly, ex vivo, DHA shortened APD(75) in WT and normalized it in LQT2, and additionally decreased AP triangulation in LQT2. Conclusions Docosahexaenoic acid exerts a genotype-specific beneficial shortening/normalizing effect on QTc and APD(75) and reduces pro-arrhythmia markers STVQT and AP triangulation through activation of I-Ks in LQT2 rabbits but has no effects if either alpha- or beta-subunits to I-Ks are functionally impaired. Docosahexaenoic acid could represent a new genotype-specific therapy in LQT2.
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| 4. |
- Plogmann, J., et al.
(författare)
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Farm growth and land concentration
- 2022
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Ingår i: Land use policy. - : Elsevier. - 0264-8377 .- 1873-5754. ; 115
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Tidskriftsartikel (refereegranskat)abstract
- Structural change in agriculture is characterized by the interdependency of farms’ growth decisions due to the scarcity of agricultural land. This paper adds to the sparse empirical literature on the relation between land market concentration and farm size changes, considering different definitions of the relevant market. Using data from the Integrated Administrative Control System (IACS) from 2005 until 2017 for Brandenburg, Germany, we find that about half of the land transactions occur beyond municipality borders. This emphasizes the importance of carefully defining the relevant market. The descriptive analysis shows that although concentration rates, on average, did not increase over time, spatial differences are present. In the econometric analysis, we apply a two-stage model to analyze how competition for agricultural land impacts the probability and relative level of expansion. For farms that remained active between 2005 and 2017, we find a negative relation between farm size and relative growth. Our conjecture that higher inequality of land distribution fosters the expansion of large farms was not confirmed.
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| 5. |
- Plogmann, J., et al.
(författare)
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Farmland sales under returns and price uncertainty
- 2022
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Ingår i: Economic Modelling. - : Elsevier. - 0264-9993 .- 1873-6122. ; 117
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Tidskriftsartikel (refereegranskat)abstract
- This paper investigates the observed heterogeneity in the liquidity of agricultural land markets. We adopt a real options model to determine the value of an opportunity to sell farmland and derive the optimal disinvestment triggers. A proportional hazards model is applied to estimate the duration between land sales in Germany and test the implications of the real options model. In contrast to expectations, we find an ambiguous effect of returns and price volatility on the optimal timing of land sales. There is no evidence that non-agricultural investors buy and sell land more frequently than farmers. Our results contribute to the current discussion on land market regulations, one major point of which is capping land prices. According to our results, such policies could increase the rent–price ratio and thus discourage land sales. In turn, the land supply would be reduced, causing further price pressure on farmland markets.
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| 6. |
- Ritter, Matthias, et al.
(författare)
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A New Approach to Assess Wind Energy Potential
- 2015
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Ingår i: Energy Procedia. - : Elsevier. ; , s. 671-676
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Konferensbidrag (refereegranskat)abstract
- To meet the increasing global demand for renewable energy, such as wind energy, an increasing number of wind parks are being constructed worldwide. Finding a suitable location requires a detailed and often costly analysis of local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. We suggest a novel, globally feasible approach to assess the local wind energy potential: First, meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at specific turbine locations and hub heights. Second, the relation between wind data and energy production is for the first time determined via a five parameter logistic function using actual high-frequency energy production data. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of the wind power potential for Germany exemplifies our approach.
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| 7. |
- Schmidt, L., et al.
(författare)
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Exploring the weather-yield nexus with artificial neural networks
- 2022
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Ingår i: Agricultural Systems. - : Elsevier. - 0308-521X .- 1873-2267. ; 196
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Tidskriftsartikel (refereegranskat)abstract
- CONTEXT: Weather is a pivotal factor for crop production as it is highly volatile and can hardly be controlled by farm management practices. Since there is a tendency towards increased weather extremes in the future, understanding weather-related yield factors becomes increasingly important not only for yield prediction, but also for the design of insurance products. Although insurance products mitigate financial losses for farmers, they suffer from considerable basis risk, i.e., a discrepancy between losses and the indemnity payment. OBJECTIVE: The objective of this paper was to explore the potential of machine learning for estimating the relationship between crop yield and weather conditions at the farm level and to use it as a tool for reducing basis risk in index insurance applications. METHODS: An artificial neural network was set up and calibrated to a rich set of farm-level yield data in Germany, covering the period from 2003 to 2018. A nonlinear regression model, which uses rainfall, temperature, and soil moisture as explanatory variables for yield deviations, served as a benchmark. RESULTS AND CONCLUSIONS: The empirical application revealed that compared with traditional estimation approaches, the gain in forecasting precision by using machine learning techniques was substantial. Moreover, the use of regionalized models and disaggregated high-resolution weather data improved the performance of artificial neural networks. A considerable part of yield variability at the farm level, however, could not be captured by statistical methods which solely use “big weather data”. SIGNIFICANCE: Our findings have important implications for the design of weather-index based insurance because they document that a rather high level of basis risk remains if insurance products are based on an estimation of the weather-yield relationship.
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