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Record W7161950076 · doi:10.82308/4507

Unravelling the behavioural and genetic associations between social isolation and Alzheimer’s disease risk: insights from population-scale studies

2024· dissertation· en· W7161950076 on OpenAlexaboutno aff
Kimia Shafighi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsSocial isolationLonelinessBiobankDementiaDiseaseContext (archaeology)Genetic architectureGenome-wide association studySocial epidemiology

Abstract

fetched live from OpenAlex

Alzheimer’s disease and related dementias (ADRD) represent a significant and growing public health burden, exacerbated by increased longevity. Recent clinical evidence suggests that social isolation may expedite dementia onset. This thesis combines findings from two population-scale studies to explore the genetic and behavioural associations between social isolation and ADRD risk. We analyzed data from 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, revisiting traditional dementia risk factors within the context of loneliness and lack of social support. By employing a tailored Bayesian hierarchical framework, our objective was to directly quantify the probabilistic association of traditional ADRD risk to social isolation, while providing coherent estimates of associated uncertainty. Our results reveal strong links between individuals' social capital and various ADRD risk indicators. These associations replicated across both cohorts and highlighted the deep connections between daily social encounters and key aetiopathological factors of ADRD, including personal habits, lifestyle factors, physical health, mental health, and societal and external factors. Our findings underscore the importance of social lifestyle determinants as promising targets for preventive clinical action. We further investigated the genetic underpinnings of social isolation and ADRD risk using genetic data from 361,129 UK Biobank participants. Through cell-type- and tissue-specific analyses, we identified genetic variants associated with both social isolation and ADRD risk factors. By integrating genome-wide association studies (GWAS) from 80 well-established ADRD risk phenotypes and 10 GWAS on ADRD and examining gene expression in specific cell types and tissues, we uncovered overlaps between the genetic architecture underlying ADRD risk and social isolation across multiple body systems, not just the brain. This genetic interlocking suggests that social lifestyle determinants are intertwined with ADRD-related neurodegeneration risk factors, providing crucial insights into potential intervention points. Overall, our population-scale assessments suggest that social isolation is intricately connected to ADRD risk through both behavioural and genetic pathways. These findings highlight the modifiability of social behaviours as a strategic avenue for reducing ADRD risk

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.318
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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