Causes and consequences of vascular dementia across the life course: Evidence from a UK Biobank phenome-wide and Mendelian randomization study

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This study used UK Biobank data (334,758 participants) to develop a vascular dementia polygenic risk score (VaD PRS), run an age-stratified phenome-wide association study across 9,319 phenotypes, and then perform two-sample Mendelian randomization to test causal relationships. The VaD PRS showed age-dependent associations, strengthening with older ages, with vascular and Alzheimer’s dementias, cerebrovascular traits (including white matter hyperintensities and stroke), adverse lipid profiles, higher systolic blood pressure and glucose measures, reduced brain volumes, and poorer cognitive function, alongside associations with depression and other neurological/neuroinflammatory conditions. MR supported causal effects of several exposures on VaD risk, including white matter hyperintensities, depression, lipid traits, HbA1c, and both diastolic and systolic blood pressure, while years of schooling and certain metabolic measures appeared protective; the paper’s caveat is that PRS-based analyses and MR rely on the available genetic instruments and phenotyping in UK Biobank. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Background Vascular dementia (VaD) is the second most common cause of dementia, yet its risk factors and biological mechanisms remain poorly understood. Objective To identify causes and consequences of VaD by developing a polygenic risk score (PRS) for VaD and conducting a phenome-wide association study (PheWAS), followed by Mendelian randomization (MR) analyses using data from the UK Biobank. Methods Using data from 334,758 UK Biobank participants, we first constructed a VaD PRS based on the most recent genome-wide association study (GWAS). We then performed an age-stratified PheWAS (39–53, 53–62, 62–72 years), examining 9,319 phenotypes associated with the VaD PRS. We followed up PheWAS hits with two-sample MR to evaluate causal relationships with VaD risk. Results Our PheWAS revealed age-dependent associations, with many relationships strengthening as age increased. Associations were found with vascular and Alzheimer’s dementias; cerebrovascular traits such as white matter hyperintensities (WMH), stroke, and intracerebral haemorrhage; adverse lipid profiles; elevated systolic blood pressure and glucose levels; reduced brain volumes (subcortical and hippocampal); and poorer cognitive function. The VaD PRS was also associated with higher risk of depression, Parkinson’s disease, neuroinflammatory disorders, and decreased basal metabolic rate and fat-free mass. MR analyses supported causal effects for WMH (OR: 1.83, 95% CI: 1.39–2.40), depression (1.25, 1.02–1.54), lipid traits (e.g., apolipoprotein B/A1 ratio: 1.31, 1.06–1.62), HbA1c (1.14, 1.02–1.28), and diastolic (1.03, 1.01–1.04) and systolic (1.01, 1.01–1.02) blood pressure. Protective factors included years of schooling (0.76, 0.64–0.90), apolipoprotein A (0.74, 0.59–0.92), fat-free mass (0.84, 0.71–0.99), and basal metabolic rate (0.82, 0.69–0.97). Conclusions Our findings highlight the central role of cardiometabolic and educational factors in the development of vascular dementia. Several modifiable risk factors—particularly blood pressure, glucose regulation, lipid levels, and years of schooling—showed evidence of causal effects on VaD risk. Age-stratified results suggest that early intervention, ideally from midlife, may offer the greatest preventive benefit by mitigating the progressive accumulation of vascular damage contributing to dementia risk.
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Abstract

Background Vascular dementia (VaD) is the second most common cause of dementia, yet its risk factors and biological mechanisms remain poorly understood.

Objective

To identify causes and consequences of VaD by developing a polygenic risk score (PRS) for VaD and conducting a phenome-wide association study (PheWAS), followed by Mendelian randomization (MR) analyses using data from the UK Biobank.

Methods

Using data from 334,758 UK Biobank participants, we first constructed a VaD PRS based on the most recent genome-wide association study (GWAS). We then performed an age-stratified PheWAS (39–53, 53–62, 62–72 years), examining 9,319 phenotypes associated with the VaD PRS. We followed up PheWAS hits with two-sample MR to evaluate causal relationships with VaD risk.

Results

Our PheWAS revealed age-dependent associations, with many relationships strengthening as age increased. Associations were found with vascular and Alzheimer’s dementias; cerebrovascular traits such as white matter hyperintensities (WMH), stroke, and intracerebral haemorrhage; adverse lipid profiles; elevated systolic blood pressure and glucose levels; reduced brain volumes (subcortical and hippocampal); and poorer cognitive function. The VaD PRS was also associated with higher risk of depression, Parkinson’s disease, neuroinflammatory disorders, and decreased basal metabolic rate and fat-free mass. MR analyses supported causal effects for WMH (OR: 1.83, 95% CI: 1.39–2.40), depression (1.25, 1.02–1.54), lipid traits (e.g., apolipoprotein B/A1 ratio: 1.31, 1.06–1.62), HbA1c (1.14, 1.02–1.28), and diastolic (1.03, 1.01–1.04) and systolic (1.01, 1.01–1.02) blood pressure. Protective factors included years of schooling (0.76, 0.64–0.90), apolipoprotein A (0.74, 0.59–0.92), fat-free mass (0.84, 0.71–0.99), and basal metabolic rate (0.82, 0.69–0.97).

Conclusions

Our findings highlight the central role of cardiometabolic and educational factors in the development of vascular dementia. Several modifiable risk factors—particularly blood pressure, glucose regulation, lipid levels, and years of schooling—showed evidence of causal effects on VaD risk. Age-stratified results suggest that early intervention, ideally from midlife, may offer the greatest preventive benefit by mitigating the progressive accumulation of vascular damage contributing to dementia risk. Competing Interest Statement The authors have declared no competing interest. Funding Statement ELA is supported by a UKRI Future Leaders Fellowship (MR/W011581/1). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The North West Multi-centre Research Ethics Committee of the National Health Service gave ethical approval for this work (reference 11/NW/0382). The University College London Research Ethics Committee of University College London gave ethical approval for this work. This research was conducted using the UK Biobank resource under application number 123335. All participants provided informed consent for participation in UK Biobank studies. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability Data are available from the UK Biobank (application ID: 123335) and can be accessed through the UK Biobank Access Management System (https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access). GWAS summary statistics are available from MEGAVCID consortium and FinnGen. Analysis code is available upon reasonable request.

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