Introduction: A better understanding of the earliest stages of Alzheimer's disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among THL Biobank donors according to TWINGEN study criteria.
Methods And Analysis: A multi-centre study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behaviour and sleep. A subcohort is being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. The data collected in TWINGEN will be returned to THL Biobank from where it can later be requested for other biobank studies such as FinnGen that supported TWINGEN.
Ethics And Dissemination: This recall study consists of FTC/THL Biobank/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.
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http://dx.doi.org/10.1136/bmjopen-2023-081947 | DOI Listing |
Br J Ophthalmol
December 2024
Department of Ophthalmology and Medical Research Center, Oulu University Hospital; Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland.
Background/aims: The purpose of this study is to define genetic factors associated with anterior uveitis through genome-wide association study (GWAS).
Methods: In this GWAS meta-analysis, we combined data from the FinnGen, Estonian Biobank and UK Biobank with a total of 12 205 anterior uveitis cases and 917 145 controls. We performed a phenome-wide association study (PheWAS) to investigate associations across phenotypes and traits.
Nat Genet
December 2024
Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam UMC location, University of Amsterdam, Amsterdam, the Netherlands.
Sci Rep
November 2024
Research Group of Intensive Care Medicine, Intensive Care Centre, Oulu University Hospital, University of Oulu and Medical Research Center (MRC), PO BOX 29, 90029, Oulu, Finland.
Background: Sepsis can lead to myocardial depression, playing a significant role in sepsis pathophysiology, clinical care, and outcome. To gain more insight into the pathophysiology of the myocardial response in sepsis, we investigated the expression of microRNA in myocardial autopsy specimens in critically ill deceased with sepsis and non-septic controls.
Materials And Methods: In this retrospective observational study, we obtained myocardial tissue samples collected during autopsy from adult patients deceased with sepsis (n = 15) for routine histological examination.
Nat Genet
December 2024
Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam UMC location, University of Amsterdam, Amsterdam, the Netherlands.
BMC Genomics
November 2024
Precision Medicine & Computational Biology, Sanofi, Cambridge, MA, USA.
Background: Therapeutic targets supported by genetic evidence from genome-wide association studies (GWAS) show higher probability of success in clinical trials. GWAS is a powerful approach to identify links between genetic variants and phenotypic variation; however, identifying the genes driving associations identified in GWAS remains challenging. Integration of molecular quantitative trait loci (molQTL) such as expression QTL (eQTL) using mendelian randomization (MR) and colocalization analyses can help with the identification of causal genes.
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