408 research outputs found
High-resolution analysis of observed thermal growing season variability over northern Europe
Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural and forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions and their past changes. Here, we deployed a large network of weather stations, high-resolution geospatial environmental data and semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day sum [GDDS, base temperature + 5 degrees C]) and their intra-annual variability and temporal trends in respect to geographical location, topography, water and forest cover, and urban land use variables over northern Europe. Our analyses revealed substantial spatial variability in average GS conditions (1990-2019) and consistent temporal trends (1950-2019). We showed that there have been significant changes in thermal GS towards earlier beginnings (on average 15 days over the study period), increased length (23 days) and GDDS (287 degrees C days). By using a spatial interpolation of weather station data to a regular grid we predicted current GS conditions at high resolution (100 m x 100 m) and with high accuracy (correlation >= 0.92 between observed and predicted mean GS values), whereas spatial variation in temporal trends and interannual variability were more demanding to predict. The spatial variation in GS variables was mostly driven by latitudinal and elevational gradients, albeit they were constrained by local scale variables. The proximity of sea and lakes, and high forest cover suppressed temporal trends and inter-annual variability potentially indicating local climate buffering. The produced high-resolution datasets showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe. They are valuable in various forest management and ecosystem applications, and in adaptation to climate change.Peer reviewe
High-resolution analysis of observed thermal growing season variability over northern Europe
Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural and forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions and their past changes. Here, we deployed a large network of weather stations, high-resolution geospatial environmental data and semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day sum [GDDS, base temperature + 5 degrees C]) and their intra-annual variability and temporal trends in respect to geographical location, topography, water and forest cover, and urban land use variables over northern Europe. Our analyses revealed substantial spatial variability in average GS conditions (1990-2019) and consistent temporal trends (1950-2019). We showed that there have been significant changes in thermal GS towards earlier beginnings (on average 15 days over the study period), increased length (23 days) and GDDS (287 degrees C days). By using a spatial interpolation of weather station data to a regular grid we predicted current GS conditions at high resolution (100 m x 100 m) and with high accuracy (correlation >= 0.92 between observed and predicted mean GS values), whereas spatial variation in temporal trends and interannual variability were more demanding to predict. The spatial variation in GS variables was mostly driven by latitudinal and elevational gradients, albeit they were constrained by local scale variables. The proximity of sea and lakes, and high forest cover suppressed temporal trends and inter-annual variability potentially indicating local climate buffering. The produced high-resolution datasets showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe. They are valuable in various forest management and ecosystem applications, and in adaptation to climate change.Peer reviewe
Maize for silage II. The effect of urea and acid as preservative treament on rumen fermentations and on feeding values of silages
The rumen fermentations and N-balances of rumen fistulated sheep were studied on diets of silages treated with urea and acid preservative. The digestibilities and feeding values of the silages were also calculated. The experiment was performed according to 5 x 5 Latin-square design. The digestibilities were determined by total collection the collection period lasting seven days. The rumen samples were taken on the last two days during the collection periods before and 1.5, 3.0, 4.5 and 6.0 hours after feeding. Besides the silages the animals received mineral mixture and water ad libitum. Urea or acid treatment had no effect (P > 0.05) on the consumption of silage DM. The consumption ranged from 1.7 to 1.9 kg DM/100 kg liveweight. Urea did not have a clear effect on the VFA production in the rumen. It tended, however, to decrease the proportions of C3 and C4—C5 acids in the rumen. Acid preservative decreased the production of VFA and the proportion of C3-acid (P 0.05) were found between the energy values, which varied between 0,12—0.14 f.u./kg of silage. There were no differences in the N-balances of the animals on different diets. The balances were positive on all diets
Use of antihypertensive medication after ischemic stroke in young adults and its association with long-term outcome
Background: Knowledge on the use of secondary preventive medication in young adults is limited. Methods: We included 936 first-ever ischemic stroke 30-day survivors aged 15-49, enrolled in the Helsinki Young Stroke Registry, 1994-2007. Follow-up data until 2012 came from Finnish Care Register, Statistics Finland, and Social Insurance Institution of Finland. Usage thresholds were defined as non-users, low (prescription coverage 80%). Adjusted Cox regression allowed assessing the association of usage with all-cause mortality and recurrent vascular events. Results: Of our patients, 40.5% were non-users, 7.8% had low usage, 11.8% intermediate usage and 40.0% high usage. Median follow-up was 8.3 years. Compared to non-users, risk of mortality and recurrent stroke or TIA was lower for patients with low-intermediate (HR 0.40, 95% CI 0.22-0.65; HR 0.31, 95% CI 0.18-0.53) and high usage (HR 0.25, 95% CI 0.15-0.42; HR 0.30, 95% CI 0.19-0.46), after adjustment for confounders. Conclusions: Use of antihypertensives was suboptimal in one-third of patients in whom antihypertensives were initially prescribed. Users were at lower risk of mortality and recurrent stroke or TIA compared to non-users.Key Messages The use of antihypertensive medication is suboptimal in one-third of patients in whom antihypertensive medication was initially prescribed after ischemic stroke at young age. The risk of mortality and recurrent stroke or TIA is lower for users of antihypertensive medication after ischemic stroke at young age compared to non-users, after adjustment for relevant confounders including pre-existing hypertension and prior use of antihypertensive medication. Specific guidelines on antihypertensive medication use after ischemic stroke at young age are lacking. However, our results may motivate doctors and patients in gaining better usage of antihypertensive medication, since better usage was associated with more favorable outcome in this study.Peer reviewe
C9orf72 hexanucleotide repeat allele tagging SNPs : Associations with ALS risk and longevity
Peer reviewe
Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland
Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.Peer reviewe
Genetic risk factors have a substantial impact on healthy life years
The impact of genetic variation on overall disease burden has not been comprehensively evaluated. We introduce an approach to estimate the effect of genetic risk factors on disability-adjusted life years (DALYs; 'lost healthy life years'). We use genetic information from 735,748 individuals and consider 80 diseases. Rare variants had the highest effect on DALYs at the individual level. Among common variants, rs3798220 (LPA) had the strongest individual-level effect, with 1.18 DALYs from carrying 1 versus 0 copies. Being in the top 10% versus the bottom 90% of a polygenic score for multisite chronic pain had an effect of 3.63 DALYs. Some common variants had a population-level effect comparable to modifiable risk factors such as high sodium intake and low physical activity. Attributable DALYs vary between males and females for some genetic exposures. Genetic risk factors can explain a sizable number of healthy life years lost both at the individual and population level.Peer reviewe
Lack of cardiac and high-fat diet induced metabolic phenotypes in two independent strains of Vegf-b knockout mice
Peer reviewe
Genetic analyses implicate complex links between adult testosterone levels and health and disease
BackgroundTestosterone levels are linked with diverse characteristics of human health, yet, whether these associations reflect correlation or causation remains debated. Here, we provide a broad perspective on the role of genetically determined testosterone on complex diseases in both sexes.MethodsLeveraging genetic and health registry data from the UK Biobank and FinnGen (total N = 625,650), we constructed polygenic scores (PGS) for total testosterone, sex-hormone binding globulin (SHBG) and free testosterone, associating these with 36 endpoints across different disease categories in the FinnGen. These analyses were combined with Mendelian Randomization (MR) and cross-sex PGS analyses to address causality.ResultsWe show testosterone and SHBG levels are intricately tied to metabolic health, but report lack of causality behind most associations, including type 2 diabetes (T2D). Across other disease domains, including 13 behavioral and neurological diseases, we similarly find little evidence for a substantial contribution from normal variation in testosterone levels. We nonetheless find genetically predicted testosterone affects many sex-specific traits, with a pronounced impact on female reproductive health, including causal contribution to PCOS-related traits like hirsutism and post-menopausal bleeding (PMB). We also illustrate how testosterone levels associate with antagonistic effects on stroke risk and reproductive endpoints between the sexes.ConclusionsOverall, these findings provide insight into how genetically determined testosterone correlates with several health parameters in both sexes. Yet the lack of evidence for a causal contribution to most traits beyond sex-specific health underscores the complexity of the mechanisms linking testosterone levels to disease risk and sex differences.Plain language summaryHormones, such as testosterone, travel around the body communicating between the different parts. Testosterone is present at higher levels in men, but also present in women. Variable testosterone levels explain some differences in human traits and disease prevalence. Here, we study how adult testosterone levels relate to health and disease. Genetic, i.e. inherited, differences in testosterone levels contribute to many traits specific to men or women, such as women's reproductive health, hormonal cancers, and hair growth typical in males. However, testosterone levels do not appear as a major cause of most traits studied, including psychiatric diseases and metabolic health. Normal variation in baseline testosterone levels thus seems to have a relatively minor impact on health and disease.Leinonen et al. investigate correlations between testosterone levels and disease using genetic and health registry data from the UK Biobank and FinnGen. There is a lack of evidence for normal variation in testosterone levels having a causal contribution to most non-sex-specific traits.Peer reviewe
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