Browsing by Subject "Birth cohort"

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  • Mustonen, Antti; Alakokkare, Anni-Emilia; Salom, Caroline; Hurtig, Tuula; Levola, Jonna; Scott, James G.; Miettunen, Jouko; Niemelä, Solja (2021)
    Objective: Early onset of alcohol use is associated with an increased risk of substance use disorders (SUD), but few studies have examined associations with other psychiatric disorders. Our aim was to study the association between the age of first alcohol intoxication (AFI) and the risk of psychiatric disorders in a Finnish general population sample. Methods: We utilized a prospective, general population-based study, the Northern Finland Birth Cohort 1986. In all, 6,290 15?16-year old adolescents answered questions on AFI and were followed up until the age of 33 years for psychiatric disorders (any psychiatric disorder, psychosis, SUD, mood disorders and anxiety disorders) by using nationwide register linkage data. Cox-regression analysis with Hazard Ratios (HR, with 95% confidence intervals (CI)) was used to assess the risk of psychiatric disorders associated with AFI. Results: Statistically significant associations were observed between AFI and any psychiatric disorder, psychosis, SUDs, and mood disorders. After adjustments for other substance use, family structure, sex and parental psychiatric disorders, AFIs of 13?14 years and
  • Sen, Partho; Dickens, Alex M.; Lopez-Bascon, Maria Asuncion; Lindeman, Tuomas; Kemppainen, Esko; Lamichhane, Santosh; Rönkkö, Tuukka; Ilonen, Jorma; Toppari, Jorma; Veijola, Riitta; Hyöty, Heikki; Hyötyläinen, Tuulia; Knip, Mikael; Oresic, Matej (2020)
    Aims/hypothesis Previous metabolomics studies suggest that type 1 diabetes is preceded by specific metabolic disturbances. The aim of this study was to investigate whether distinct metabolic patterns occur in peripheral blood mononuclear cells (PBMCs) of children who later develop pancreatic beta cell autoimmunity or overt type 1 diabetes. Methods In a longitudinal cohort setting, PBMC metabolomic analysis was applied in children who (1) progressed to type 1 diabetes (PT1D, n = 34), (2) seroconverted to >= 1 islet autoantibody without progressing to type 1 diabetes (P1Ab, n = 27) or (3) remained autoantibody negative during follow-up (CTRL, n = 10). Results During the first year of life, levels of most lipids and polar metabolites were lower in the PT1D and P1Ab groups compared with the CTRL group. Pathway over-representation analysis suggested alanine, aspartate, glutamate, glycerophospholipid and sphingolipid metabolism were over-represented in PT1D. Genome-scale metabolic models of PBMCs during type 1 diabetes progression were developed by using publicly available transcriptomics data and constrained with metabolomics data from our study. Metabolic modelling confirmed altered ceramide pathways, known to play an important role in immune regulation, as specifically associated with type 1 diabetes progression. Conclusions/interpretation Our data suggest that systemic dysregulation of lipid metabolism, as observed in plasma, may impact the metabolism and function of immune cells during progression to overt type 1 diabetes. Data availability The GEMs for PBMCs have been submitted to BioModels (), under accession number MODEL1905270001. The metabolomics datasets and the clinical metadata generated in this study were submitted to MetaboLights (), under accession number MTBLS1015.
  • Long, Di; Mackenbach, Johan; Martikainen, Pekka; Lundberg, Olle; Brønnum-Hansen, Henrik; Bopp, Matthias; Costa, Giuseppe; Kovács, Katalin; Leinsalu, Mall; Rodríguez-Sanz, Maica; Menvielle, Gwenn; Nusselder, Wilma (BioMed Central, 2021)
    Abstract Purpose To study the trends of smoking-attributable mortality among the low and high educated in consecutive birth cohorts in 11 European countries. Methods Register-based mortality data were collected among adults aged 30 to 79 years in 11 European countries between 1971 and 2012. Smoking-attributable deaths were estimated indirectly from lung cancer mortality rates using the Preston-Glei-Wilmoth method. Rate ratios and rate differences among the low and high-educated were estimated and used to estimate the contribution of inequality in smoking-attributable mortality to inequality in total mortality. Results In most countries, smoking-attributable mortality decreased in consecutive birth cohorts born between 1906 and 1961 among low- and high-educated men and high-educated women, but not among low-educated women among whom it increased. Relative educational inequalities in smoking-attributable mortality increased among both men and women with no signs of turning points. Absolute inequalities were stable among men but slightly increased among women. The contribution of inequality in smoking-attributable mortality to inequality in total mortality decreased in consecutive generations among men but increased among women. Conclusions Smoking might become less important as a driver of inequalities in total mortality among men in the future. However, among women, smoking threatens to further widen inequalities in total mortality.
  • LifeCycle Project Group; Pinot de Moira, Angela; Haakma, Sido; Strandberg-Larsen, Katrine; Eriksson, Johan G.; Mikkola, Tuija M.; Nybo Andersen, Anne-Marie (2021)
    The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network’s core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network’s data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.