Browsing by Subject "REGRESSION"

Sort by: Order: Results:

Now showing items 1-20 of 45
  • Manninen, Antti J.; O'Connor, Ewan J.; Vakkari, Ville; Petäjä, Tuukka (2016)
    Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50% after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.
  • Nivette, Amy E.; Zahnow, Renee; Aguilar, Raul; Ahven, Andri; Amram, Shai; Ariel, Barak; Burbano, Maria Jose Arosemena; Astolfi, Roberta; Baier, Dirk; Bark, Hyung-Min; Beijers, Joris E. H.; Bergman, Marcelo; Breetzke, Gregory; Concha-Eastman, I. Alberto; Curtis-Ham, Sophie; Davenport, Ryan; Diaz, Carlos; Fleitas, Diego; Gerell, Manne; Jang, Kwang-Ho; Kääriäinen, Juha; Lappi-Seppala, Tapio; Lim, Woon-Sik; Revilla, Rosa Loureiro; Mazerolle, Lorraine; Mesko, Gorazd; Pereda, Noemi; Peres, Maria F. T.; Poblete-Cazenave, Ruben; Rose, Simon; Svensson, Robert; Trajtenberg, Nico; van der Lippe, Tanja; Veldkamp, Joran; Perdomo, Carlos J. Vilalta; Eisner, Manuel P. (2021)
    The implementation of COVID-19 stay-at-home policies was associated with a considerable drop in urban crime in 27 cities across 23 countries. More stringent restrictions over movement in public space were predictive of larger declines in crime. The stay-at-home restrictions to control the spread of COVID-19 led to unparalleled sudden change in daily life, but it is unclear how they affected urban crime globally. We collected data on daily counts of crime in 27 cities across 23 countries in the Americas, Europe, the Middle East and Asia. We conducted interrupted time series analyses to assess the impact of stay-at-home restrictions on different types of crime in each city. Our findings show that the stay-at-home policies were associated with a considerable drop in urban crime, but with substantial variation across cities and types of crime. Meta-regression results showed that more stringent restrictions over movement in public space were predictive of larger declines in crime.
  • Syrjälä, Essi; Nevalainen, Jaakko; Peltonen, Jaakko; Takkinen, Hanna-Mari; Hakola, Leena; Åkerlund, Mari; Veijola, Riitta; Ilonen, Jorma; Toppari, Jorma; Knip, Mikael; Virtanen, Suvi M. (2019)
    Several dietary factors have been suspected to play a role in the development of advanced islet autoimmunity (IA) and/or type 1 diabetes (T1D), but the evidence is fragmentary. A prospective population-based cohort of 6081 Finnish newborn infants with HLA-DQB1-conferred susceptibility to T1D was followed up to 15 years of age. Diabetes-associated autoantibodies and diet were assessed at 3-to 12-month intervals. We aimed to study the association between consumption of selected foods and the development of advanced IA longitudinally with Cox regression models (CRM), basic joint models (JM) and joint latent class mixed models (JLCMM). The associations of these foods to T1D risk were also studied to investigate consistency between alternative endpoints. The JM showed a marginal association between meat consumption and advanced IA: the hazard ratio adjusted for selected confounding factors was 1.06 (95% CI: 1.00, 1.12). The JLCMM identified two classes in the consumption trajectories of fish and a marginal protective association for high consumers compared to low consumers: the adjusted hazard ratio was 0.68 (0.44, 1.05). Similar findings were obtained for T1D risk with adjusted hazard ratios of 1.13 (1.02, 1.24) for meat and 0.45 (0.23, 0.86) for fish consumption. Estimates from the CRMs were closer to unity and CIs were narrower compared to the JMs. Findings indicate that intake of meat might be directly and fish inversely associated with the development of advanced IA and T1D, and that disease hazards in longitudinal nutritional epidemiology are more appropriately modeled by joint models than with naive approaches.
  • Alghamdi, Mansour A.; Al-Hunaiti, Afnan; Arar, Sharif; Khoder, Mamdouh; Abdelmaksoud, Ahmad S.; Al-Jeelani, Hisham; Lihavainen, Heikki; Hyvärinen, Antti; Shabbaj, Ibrahim I.; Almehmadi, Fahd M.; Zaidan, Martha A.; Hussein, Tareq; Dada, Lubna (2019)
    Ground level ozone (O-3) plays an important role in controlling the oxidation budget in the boundary layer and thus affects the environment and causes severe health disorders. Ozone gas, being one of the well-known greenhouse gases, although present in small quantities, contributes to global warming. In this study, we present a predictive model for the steady-state ozone concentrations during daytime (13:00-17:00) and nighttime (01:00-05:00) at an urban coastal site. The model is based on a modified approach of the null cycle of O-3 and NOx and was evaluated against a one-year data-base of O-3 and nitrogen oxides (NO and NO2) measured at an urban coastal site in Jeddah, on the west coast of Saudi Arabia. The model for daytime concentrations was found to be linearly dependent on the concentration ratio of NO2 to NO whereas that for the nighttime period was suggested to be inversely proportional to NO2 concentrations. Knowing that reactions involved in tropospheric O-3 formation are very complex, this proposed model provides reasonable predictions for the daytime and nighttime concentrations. Since the current description of the model is solely based on the null cycle of O-3 and NOx, other precursors could be considered in future development of this model. This study will serve as basis for future studies that might introduce informing strategies to control ground level O-3 concentrations, as well as its precursors' emissions.
  • He, Liang; Pitkaniemi, Janne; Silventoinen, Karri; Sillanpaa, Mikko J. (2017)
    Estimating dynamic effects of age on the genetic and environmental variance components in twin studies may contribute to the investigation of gene-environment interactions, and may provide more insights into more accurate and powerful estimation of heritability. Existing parametric models for estimating dynamic variance components suffer from various drawbacks such as limitation of predefined functions. We present ACEt, an R package for fast estimating dynamic variance components and heritability that may change with respect to age or other moderators. Building on the twin models using penalized splines, ACEt provides a unified framework to incorporate a class of ACE models, in which each component can be modeled independently and is not limited by a linear or quadratic function. We demonstrate that ACEt is robust against misspecification of the number of spline knots, and offers a refined resolution of dynamic behavior of the genetic and environmental components and thus a detailed estimation of age-specific heritability. Moreover, we develop resampling methods for testing twin models with different variance functions including splines, log-linearity and constancy, which can be easily employed to verify various model assumptions. We evaluated the type I error rate and statistical power of the proposed hypothesis testing procedures under various scenarios using simulated datasets. Potential numerical issues and computational cost were also assessed through simulations. We applied the ACEt package to a Finnish twin cohort to investigate age-specific heritability of body mass index and height. Our results show that the age-specific variance components of these two traits exhibited substantially different patterns despite of comparable estimates of heritability. In summary, the ACEt R package offers a useful tool for the exploration of age-dependent heritability and model comparison in twin studies.
  • Savilahti, Emma M.; Lintula, Sakari; Häkkinen, Laura; Marttunen, Mauri; Granö, Niklas (2021)
    Background The COVID-19-pandemic and especially the physical distancing measures drastically changed the conditions for providing outpatient care in adolescent psychiatry. Methods We investigated the outpatient services of adolescent psychiatry in the Helsinki University Hospital (HUH) from 1/1/2015 until 12/31/2020. We retrieved data from the in-house data software on the number of visits in total and categorized as in-person or remote visits, and analysed the data on a weekly basis. We further analysed these variables grouped according to the psychiatric diagnoses coded for visits. Data on the number of patients and on referrals from other health care providers were available on a monthly basis. We investigated the data descriptively and with a time-series analysis comparing the pre-pandemic period to the period of the COVID-19 pandemic. Results The total number of visits decreased slightly at the early stage of the COVID-19 pandemic in Spring 2020. Remote visits sharply increased starting in 3/2020 and remained at a high level compared with previous years. In-person visits decreased in Spring 2020, but gradually increased afterwards. The number of patients transiently fell in Spring 2020. Conclusions Rapid switch to remote visits in outpatient care of adolescent psychiatry made it possible to avoid a drastic drop in the number of visits despite the physical distancing measures during the COVID-19 pandemic.
  • Cardoso, Pedro; Branco, Vasco V.; Borges, Paulo A.; Carvalho, Jose C.; Rigal, Francois; Gabriel, Rosalina; Mammola, Stefano; Cascalho, Jose; Correia, Luis (2020)
    Ecological systems are the quintessential complex systems, involving numerous high-order interactions and non-linear relationships. The most used statistical modeling techniques can hardly accommodate the complexity of ecological patterns and processes. Finding hidden relationships in complex data is now possible using massive computational power, particularly by means of artificial intelligence and machine learning methods. Here we explored the potential of symbolic regression (SR), commonly used in other areas, in the field of ecology. Symbolic regression searches for both the formal structure of equations and the fitting parameters simultaneously, hence providing the required flexibility to characterize complex ecological systems. Although the method here presented is automated, it is part of a collaborative human-machine effort and we demonstrate ways to do it. First, we test the robustness of SR to extreme levels of noise when searching for the species-area relationship. Second, we demonstrate how SR can model species richness and spatial distributions. Third, we illustrate how SR can be used to find general models in ecology, namely new formulas for species richness estimators and the general dynamic model of oceanic island biogeography. We propose that evolving free-form equations purely from data, often without prior human inference or hypotheses, may represent a very powerful tool for ecologists and biogeographers to become aware of hidden relationships and suggest general theoretical models and principles.
  • Khan, Suleiman A.; Leppaaho, Eemeli; Kaski, Samuel (2016)
    We introduce Bayesian multi-tensor factorization, a model that is the first Bayesian formulation for joint factorization of multiple matrices and tensors. The research problem generalizes the joint matrix-tensor factorization problem to arbitrary sets of tensors of any depth, including matrices, can be interpreted as unsupervised multi-view learning from multiple data tensors, and can be generalized to relax the usual trilinear tensor factorization assumptions. The result is a factorization of the set of tensors into factors shared by any subsets of the tensors, and factors private to individual tensors. We demonstrate the performance against existing baselines in multiple tensor factorization tasks in structural toxicogenomics and functional neuroimaging.
  • Peltola, Tomi; Marttinen, Pekka; Jula, Antti; Salomaa, Veikko; Perola, Markus; Vehtari, Aki (2012)
  • Guo, Qi; Burgess, Stephen; Turman, Constance; Bolla, Manjeet K.; Wang, Qin; Lush, Michael; Abraham, Jean; Aittomäki, Kristiina; Andrulis, Irene L.; Apicella, Carmel; Arndt, Volker; Barrdahl, Myrto; Benitez, Javier; Berg, Christine D.; Blomqvist, Carl; Bojesen, Stig E.; Bonanni, Bernardo; Brand, Judith S.; Brenner, Hermann; Broeks, Annegien; Burwinkel, Barbara; Caldas, Carlos; Campa, Daniele; Canzian, Federico; Chang-Claude, Jenny; Chanock, Stephen J.; Chin, Suet-Feung; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Cybulski, Cezary; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Diver, W. Ryan; Dunning, Alison M.; Earl, Helena M.; Eccles, Diana M.; Ekici, Arif B.; Eriksson, Mikael; Evans, D. Gareth; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Flyger, Henrik; Gapstur, Susan M.; Gaudet, Mia M.; Giles, Graham G.; Muranen, Taru A.; Nevanlinna, Heli; kConFab-AOCS Investigators (2017)
    There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13,P = 0.95). Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.
  • Thomson, Katariina; Eskola, Katarina; Eklund, Marjut; Suominen, Kristiina; Maatta, Merita; Junnila, Jouni; Nykasenoja, Suvi; Niinisto, Kati; Gronthal, Thomas; Rantala, Merja (2022)
    Background Extended-spectrum beta-lactamase producing Enterobacterales (ESBL-E) are important causative agents for infections in humans and animals. At the Equine Veterinary Teaching Hospital of the University of Helsinki, the first infections caused by ESBL-E were observed at the end of 2011 leading to enhanced infection surveillance. Contact patients were screened for ESBL-E by culturing infection sites and rectal screening. This study was focused on describing the epidemiology and microbiological characteristics of ESBL-E from equine patients of the EVTH during 2011-2014, and analysing putative risk factors for being positive for ESBL-E during an outbreak of Klebsiella pneumoniae ST307. Results The number of ESBL-E isolations increased through 2012-2013 culminating in an outbreak of multi-drug resistant K. pneumoniae ST307:bla(CTX-M-1):bla(TEM):bla(SHV) during 04-08/2013. During 10/2011-05/2014, altogether 139 ESBL-E isolates were found from 96 horses. Of these, 26 were from infection-site specimens and 113 from rectal-screening swabs. A total of 118 ESBL-E isolates from horses were available for further study, the most numerous being K. pneumoniae (n = 44), Escherichia coli (n = 31) and Enterobacter cloacae (n = 31). Hospital environmental specimens (N = 47) yielded six isolates of ESBL-E. Two identical E. cloacae isolates originating from an operating theatre and a recovery room had identical or highly similar PFGE fingerprint profiles as five horse isolates. In the multivariable analysis, mare-foal pairs (OR 4.71, 95% CI 1.57-14.19, P = 0.006), length of hospitalisation (OR 1.62, 95% CI 1.28-2.06, P < 0.001) and passing of a nasogastric tube (OR 2.86, 95% CI 1.03-7.95, P = 0.044) were associated with being positive for ESBL-E during the K. pneumoniae outbreak. Conclusions The occurrence of an outbreak caused by a pathogenic ESBL-producing K. pneumoniae ST307 strain highlights the importance of epidemiological surveillance of ESBL-E in veterinary hospitals. Limiting the length of hospitalisation for equine patients may reduce the risk of spread of ESBL-E. It is also important to acknowledge the importance of nasogastric tubing as a potential source of acquiring ESBL-E. As ESBL-E were also found in stomach drench pumps used with nasogastric tubes, veterinary practices should pay close attention to appropriate equipment cleaning procedures and disinfection practices.
  • Picazo, Felix; Vilmi, Annika; Aalto, Juha; Soininen, Janne; Casamayor, Emilio O.; Liu, Yongqin; Wu, Qinglong; Ren, Lijuan; Zhou, Jizhong; Shen, Ji; Wang, Jianjun (2020)
    Background Understanding the large-scale patterns of microbial functional diversity is essential for anticipating climate change impacts on ecosystems worldwide. However, studies of functional biogeography remain scarce for microorganisms, especially in freshwater ecosystems. Here we study 15,289 functional genes of stream biofilm microbes along three elevational gradients in Norway, Spain and China. Results We find that alpha diversity declines towards high elevations and assemblage composition shows increasing turnover with greater elevational distances. These elevational patterns are highly consistent across mountains, kingdoms and functional categories and exhibit the strongest trends in China due to its largest environmental gradients. Across mountains, functional gene assemblages differ in alpha diversity and composition between the mountains in Europe and Asia. Climate, such as mean temperature of the warmest quarter or mean precipitation of the coldest quarter, is the best predictor of alpha diversity and assemblage composition at both mountain and continental scales, with local non-climatic predictors gaining more importance at mountain scale. Under future climate, we project substantial variations in alpha diversity and assemblage composition across the Eurasian river network, primarily occurring in northern and central regions, respectively. Conclusions We conclude that climate controls microbial functional gene diversity in streams at large spatial scales; therefore, the underlying ecosystem processes are highly sensitive to climate variations, especially at high latitudes. This biogeographical framework for microbial functional diversity serves as a baseline to anticipate ecosystem responses and biogeochemical feedback to ongoing climate change.
  • van der Wal, Jessica E. M.; Thorogood, Rose; Horrocks, Nicholas P. C. (2021)
    Collaboration and diversity are increasingly promoted in science. Yet how collaborations influence academic career progression, and whether this differs by gender, remains largely unknown. Here, we use co-authorship ego networks to quantify collaboration behaviour and career progression of a cohort of contributors to biennial International Society of Behavioral Ecology meetings (1992, 1994, 1996). Among this cohort, women were slower and less likely to become a principal investigator (PI; approximated by having at least three last-author publications) and published fewer papers over fewer years (i.e. had shorter academic careers) than men. After adjusting for publication number, women also had fewer collaborators (lower adjusted network size) and published fewer times with each co-author (lower adjusted tie strength), albeit more often with the same group of collaborators (higher adjusted clustering coefficient). Authors with stronger networks were more likely to become a PI, and those with less clustered networks did so more quickly. Women, however, showed a stronger positive relationship with adjusted network size (increased career length) and adjusted tie strength (increased likelihood to become a PI). Finally, early-career network characteristics correlated with career length. Our results suggest that large and varied collaboration networks are positively correlated with career progression, especially for women.
  • Liao, Wenfei; Venn, Stephen; Niemelä, Jari (2022)
    Context: Structural and functional connectivity, as subconcepts of landscape connectivity, are key factors in biodiversity conservation and management. Previous studies have focused on the consequences of connectivity for populations of terrestrial organisms, which may not be appropriate for aquatic organisms. Objectives: As landscape connectivity critically affects the potential value of ponds for biodiversity, here we used diving beetles (Dytiscidae), an indicator taxon of wetland biodiversity, to investigate how structural connectivity affects functional connectivity to aquatic invertebrates in an urban landscape. Methods: We assessed pairwise similarities of dytiscid community, i.e. the variation of species composition between clustered and isolated ponds in the Helsinki Metropolitan Area, Finland. We investigated how dytiscid community similarity is affected by Euclidean distances between ponds, as an indicator of structural connectivity. Results: We found that clustered ponds shared more species than isolated ponds. Dytiscid species community similarity responded negatively to increasing Euclidean distance between ponds. Effectively dispersing species were widely distributed across the landscape, while poor dispersers were scarcely distributed in the same landscape. Conclusions: Structural connectivity determines which species are able to disperse successfully, with poor dispersers restricted to well-connected ponds. The different responses of effective dispersers and poor dispersers to the same structural connectivity indicate that functional connectivity determines species composition. We recommend providing well-connected aquatic habitats in urban landscapes and the implementation of measures to reduce isolation of wetland assemblages. Even clustered ponds need dispersal from other habitats to ensure their contribution to urban biodiversity.
  • Fung, Pak L.; Zaidan, Martha A.; Timonen, Hilkka; Niemi, Jarkko V.; Kousa, Anu; Kuula, Joel; Luoma, Krista; Tarkoma, Sasu; Petäjä, Tuukka; Kulmala, Markku; Hussein, Tareq (2021)
    Air quality prediction with black-box (BB) modelling is gaining widespread interest in research and industry. This type of data-driven models work generally better in terms of accuracy but are limited to capture physical, chemical and meteorological processes and therefore accountability for interpretation. In this paper, we evaluated different white-box (WB) and BB methods that estimate atmospheric black carbon (BC) concentration by a suite of observations from the same measurement site. This study involves data in the period of 1st January 2017–31st December 2018 from two measurement sites, from a street canyon site in Mäkelänkatu and from an urban background site in Kumpula, in Helsinki, Finland. At the street canyon site, WB models performed (R² = 0.81–0.87) in a similar way as the BB models did (R² = 0.86–0.87). The overall performance of the BC concentration estimation methods at the urban background site was much worse probably because of a combination of smaller dynamic variability in the BC values and longer data gaps. However, the difference in WB (R²= 0.44–0.60) and BB models (R² = 0.41–0.64) was not significant. Furthermore, the WB models are closer to physics-based models, and it is easier to spot the relative importance of the predictor variable and determine if the model output makes sense. This feature outweighs slightly higher performance of some individual BB models, and inherently the WB models are a better choice due to their transparency in the model architecture. Among all the WB models, IAP and LASSO are recommended due to its flexibility and its efficiency, respectively. Our findings also ascertain the importance of temporal properties in statistical modelling. In the future, the developed BC estimation model could serve as a virtual sensor and complement the current air quality monitoring.
  • Kaikkonen, Laura; Virtanen, Elina A.; Kostamo, Kirsi; Lappalainen, Juho; Kotilainen, Aarno T. (2019)
    Ferromanganese (FeMn) concretions are mineral precipitates found on soft sediment seafloors both in the deep sea and coastal sea areas. These mineral deposits potentially form a three-dimensional habitat for marine organisms, and contain minerals targeted by an emerging seabed mining industry. While FeMn concretions are known to occur abundantly in coastal sea areas, specific information on their spatial distribution and significance for marine ecosystems is lacking. Here, we examine the distribution of FeMn concretions in Finnish marine areas. Drawing on an extensive dataset of 140,000 sites visited by the Finnish Inventory Programme for the Underwater Marine Environment (VELMU), we examine the occurrence of FeMn concretions from seabed mapping, and use spatial modeling techniques to estimate the potential coverage of FeMn concretions. Using seafloor characteristics and hydrographical conditions as predictor variables, we demonstrate that the extent of seafloors covered by concretions in the northern Baltic Sea is larger than anticipated, as concretions were found at similar to 7000 sites, and were projected to occur on over 11% of the Finnish sea areas. These results provide new insights into seafloor complexity in coastal sea areas, and further enable examining the ecological role and resource potential of seabed mineral concretions.
  • Domènech, Marc; Wangensteen, Owen S.; Enguídanos, Alba; Malumbres-Olarte, Jagoba; Arnado, Miquel A. (2022)
    Although arthropods are the largest component of animal diversity, they are traditionally underrepresented in biological inventories and monitoring programmes. However, no biodiversity assessment can be considered informative without including them. Arthropod immature stages are often discarded during sorting, despite frequently representing more than half of the collected individuals. To date, little effort has been devoted to characterising the impact of discarding nonadult specimens on our diversity estimates. Here, we used a metabarcoding approach to analyse spiders from oak forests in the Iberian Peninsula, to assess (1) the contribution of juvenile stages to local diversity estimates, and (2) their effect on the diversity patterns (compositional differences) across assemblages. We further investigated the ability of metabarcoding to inform on abundance. We obtained 363 and 331 species as adults and juveniles, respectively. Including the species represented only by juveniles increased the species richness of the whole sampling in 35% with respect to those identified from adults. Differences in composition between assemblages were greatly reduced when immature stages were considered, especially across latitudes, possibly due to phenological differences. Moreover, our results revealed that metabarcoding data are to a certain extent quantitative, but some sort of taxonomic conversion factor may be necessary to provide accurate informative estimates. Although our findings do not question the relevance of the information provided by adult-based inventories, they also reveal that juveniles provide a novel and relevant layer of knowledge that, especially in areas with marked seasonality, may influence our interpretations, providing more accurate information from standardised biological inventories.
  • Batllori, Enric; Lloret, Francisco; Aakala, Tuomas; Anderegg, William R. L.; Aynekulu, Ermias; Bendixsen, Devin P.; Bentouati, Abdallah; Bigler, Christof; Burk, C. John; Camarero, J. Julio; Colangelo, Michele; Coop, Jonathan D.; Fensham, Roderick; Floyd, M. Lisa; Galiano, Lucia; Ganey, Joseph L.; Gonzalez, Patrick; Jacobsen, Anna L.; Kane, Jeffrey Michael; Kitzberger, Thomas; Linares, Juan C.; Marchetti, Suzanne B.; Matusick, George; Michaelian, Michael; Navarro-Cerrillo, Rafael M.; Pratt, Robert Brandon; Redmond, Miranda D.; Rigling, Andreas; Ripullone, Francesco; Sanguesa-Barreda, Gabriel; Sasal, Yamila; Saura-Mas, Sandra; Suarez, Maria Laura; Veblen, Thomas T.; Vila-Cabrera, Albert; Vincke, Caroline; Ben Zeeman (2020)
    Forest vulnerability to drought is expected to increase under anthropogenic climate change, and drought-induced mortality and community dynamics following drought have major ecological and societal impacts. Here, we show that tree mortality concomitant with drought has led to short-term (mean 5 y, range 1 to 23 y after mortality) vegetation-type conversion in multiple biomes across the world (131 sites). Self-replacement of the dominant tree species was only prevalent in 21% of the examined cases and forests and woodlands shifted to nonwoody vegetation in 10% of them. The ultimate temporal persistence of such changes remains unknown but, given the key role of biological legacies in long-term ecological succession, this emerging picture of postdrought ecological trajectories highlights the potential for major ecosystem reorganization in the coming decades. Community changes were less pronounced under wetter postmortality conditions. Replacement was also influenced by management intensity, and postdrought shrub dominance was higher when pathogens acted as codrivers of tree mortality. Early change in community composition indicates that forests dominated by mesic species generally shifted toward more xeric communities, with replacing tree and shrub species exhibiting drier bioclimatic optima and distribution ranges. However, shifts toward more mesic communities also occurred and multiple pathways of forest replacement were observed for some species. Drought characteristics, species-specific environmental preferences, plant traits, and ecosystem legacies govern post drought species turnover and subsequent ecological trajectories, with potential far-reaching implications for forest biodiversity and ecosystem services.
  • FinnGen research group; Strausz, Satu; Ruotsalainen, Sanni; Ollila, Hanna M.; Karjalainen, Juha; Kiiskinen, Tuomo; Reeve, Mary; Kurki, Mitja; Mars, Nina; Havulinna, Aki S.; Luonsi, Elina; Mansour-Aly, Dina; Ahlqvist, Emma; Teder-Laving, Maris; Palta, Priit; Groop, Leif; Magi, Reedik; Mäkitie, Antti; Salomaa, Veikko; Bachour, Adel; Tuomi, Tiinamaija; Palotie, Aarno; Palotie, Tuula; Ripatti, Samuli (2021)
    There is currently limited understanding of the genetic aetiology of obstructive sleep apnoea (OSA). We aimed to identify genetic loci associated with OSA risk, and to test if OSA and its comorbidities share a common genetic background. We conducted the first large-scale genome-wide association study of OSA using the FinnGen study (217955 individuals) with 16761 OSA patients identified using nationwide health registries. We estimated 0.08 (95% CI 0.06-0.11) heritability and identified five loci associated with OSA (p < 5.0x10(-8)): rs4837016 near GAPVD1 (GTPase activating protein and VPS9 domains 1), rs10928560 near CXCR4 (C-X-C motif chemokine receptor type 4), rs185932673 near CAMK1D (calcium/calmodulindependent protein kinase ID) and rs9937053 near FTO (fat mass and obesity-associated protein; a variant previously associated with body mass index (BMI)). In a BMI-adjusted analysis, an association was observed for rs10507084 near RMST/NEDD1 (rhabdomyosarcoma 2 associated transcript/NEDD1 gamma tubulin ring complex targeting factor). We found high genetic correlations between OSA and BMI (r(g)=0.72 (95% CI 0.62-0.83)), and with comorbidities including hypertension, type 2 diabetes, coronary heart disease, stroke, depression, hypothyroidism, asthma and inflammatory rheumatic disease (rg > 0.30). The polygenic risk score for BMI showed 1.98-fold increased OSA risk between the highest and the lowest quintile, and Mendelian randomisation supported a causal relationship between BMI and OSA. Our findings support the causal link between obesity and OSA, and the joint genetic basis between OSA and comorbidities.
  • Genetics DNA Methylation Consort; NHLBI Trans-Omics Precision Med; McCartney, Daniel L.; Min, Josine L.; Richmond, Rebecca C.; Palviainen, Teemu; Ollikainen, Miina; Kaprio, Jaakko (2021)
    Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.