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      Association of social isolation, loneliness and genetic risk with incidence of dementia: UK Biobank Cohort Study

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          Abstract

          Background

          Social isolation and loneliness have been associated with increased risk of dementia, but it is not known whether this risk is modified or confounded by genetic risk of dementia.

          Methods

          We used the prospective UK Biobank study with 155 070 participants (mean age 64.1 years), including self-reported social isolation and loneliness. Genetic risk was indicated using the polygenic risk score for Alzheimer’s disease and the incident dementia ascertained using electronic health records.

          Results

          Overall, 8.6% of participants reported that they were socially isolated and 5.5% were lonely. During a mean follow-up of 8.8 years (1.36 million person years), 1444 (0.9% of the total sample) were diagnosed with dementia. Social isolation, but not loneliness, was associated with increased risk of dementia (HR 1.62, 95% CI 1.38 to 1.90). There were no interaction effects between genetic risk and social isolation or between genetic risk and loneliness predicting incident dementia. Of the participants who were socially isolated and had high genetic risk, 4.4% (95% CI 3.4% to 5.5%) were estimated to developed dementia compared with 2.9% (95% CI 2.6% to 3.2%) of those who were not socially isolated but had high genetic risk. Comparable differences were also in those with intermediate and low genetic risk levels.

          Conclusions

          Socially isolated individuals are at increased risk of dementia at all levels of genetic risk.

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          Most cited references42

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          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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            Is Open Access

            The UK Biobank resource with deep phenotyping and genomic data

            The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
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              Dementia prevention, intervention, and care

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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2022
                23 February 2022
                : 12
                : 2
                : e053936
                Affiliations
                [1 ]departmentDepartment of Psychology and Logopedics , University of Helsinki , Helsinki, Finland
                [2 ]departmentResearch Program Unit, Faculty of Medicine , University of Helsinki , Helsinki, Finland
                [3 ]Finnish Institute for Health and Welfare , Helsinki, Finland
                [4 ]departmentDepartment of Public Health , University of Helsinki , Helsinki, Finland
                [5 ]departmentInstitute for Molecular Medicine Finland, Helsinki Institute of Life Sciences , University of Helsinki , Helsinki, Finland
                [6 ]departmentHelsinki Institute for Information Technology and Department of Mathematics and Statistics , University of Helsinki , Helsinki, Finland
                [7 ]departmentResearch Centre of Child Psychiatry, Faculty of Medicine , University of Turku , Turku, Finland
                [8 ]departmentSchool of Educational Sciences and Psychology , University of Eastern Finland , Joensuu, Finland
                [9 ]departmentDepartment of Epidemiology and Public Health , University College London , London, UK
                Author notes
                [Correspondence to ] Dr Marko Elovainio; marko.elovainio@ 123456helsinki.fi
                Author information
                http://orcid.org/0000-0002-1401-1910
                http://orcid.org/0000-0001-8361-3301
                Article
                bmjopen-2021-053936
                10.1136/bmjopen-2021-053936
                8867309
                35197341
                827f666b-2dbb-4539-9a80-1d7d1c424c36
                © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                History
                : 28 May 2021
                : 30 January 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 310591(CH)
                Award ID: 311492
                Award ID: 339390
                Funded by: FundRef http://dx.doi.org/10.13039/501100004785, NordForsk;
                Award ID: 70521
                Funded by: Federal Ministry of Education and Research (BMBF);
                Award ID: 01GI0102
                Award ID: 01GI0420
                Award ID: 01GI0711
                Funded by: NHLBI;
                Award ID: R01 HL105756
                Funded by: NIA;
                Award ID: AG081220
                Award ID: N01–AG–12100
                Award ID: R01 AG033193
                Award ID: R01AG056477
                Award ID: U01 AG016976
                Award ID: U01 AG032984
                Award ID: U24 AG021886
                Funded by: MRC;
                Award ID: S011676
                Funded by: FundRef http://dx.doi.org/10.13039/100000957, Alzheimer's Association;
                Award ID: ADGC–10–196728
                Funded by: Alzheimer's Research UK;
                Award ID: 503176
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 082604/2/07/Z
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: 503480
                Categories
                Epidemiology
                1506
                1692
                Original research
                Custom metadata
                unlocked

                Medicine
                dementia,public health,genetics,geriatric medicine
                Medicine
                dementia, public health, genetics, geriatric medicine

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