Complexities of cerebral small vessel disease, blood pressure, and dementia relationship: new insights from genetics

Abstract

Importance: There is increasing recognition that vascular disease, which can be treated, is a key contributor to dementia risk. However, the contribution of specific markers of vascular disease is unclear and, as a consequence, optimal prevention strategies remain unclear.

Objective: To disentangle the causal relation of several key vascular traits to dementia risk: (i) white matter hyperintensity (WMH) burden, a highly prevalent imaging marker of covert cerebral small vessel disease (cSVD); (ii) clinical stroke; and (iii) blood pressure (BP), the leading risk factor for cSVD and stroke, for which efficient therapies exist. To account for potential epidemiological biases inherent to late-onset conditions like dementia.

Design setting and participants: This study first explored the association of genetically determined WMH, BP levels and stroke risk with AD using summary-level data from large genome-wide association studies (GWASs) in a two-sample Mendelian randomization (MR) framework. Second, leveraging individual-level data from large longitudinal population-based cohorts and biobanks with prospective dementia surveillance, the association of weighted genetic risk scores (wGRSs) for WMH, BP, and stroke with incident all-cause-dementia was explored using Cox-proportional hazard and multi-state models. The data analysis was performed from July 26, 2020, through July 24, 2022.

Exposures: Genetically determined levels of WMH volume and BP (systolic, diastolic and pulse blood pressures) and genetic liability to stroke.

Main outcomes and measures: The summary-level MR analyses focused on the outcomes from GWAS of clinically diagnosed AD (n-cases=21,982) and GWAS additionally including self-reported parental history of dementia as a proxy for AD diagnosis (AD_meta, n-cases=53,042). For the longitudinal analyses, individual-level data of 157,698 participants with 10,699 incident all-cause-dementia were studied, exploring AD, vascular or mixed dementia in secondary analyses.

Results: In the two-sample MR analyses, WMH showed strong evidence for a causal association with increased risk of AD_meta (OR, 1.16; 95%CI:1.05-1.28; P=.003) and AD (OR, 1.28; 95%CI:1.07-1.53; P=.008), after accounting for genetically determined pulse pressure for the latter. Genetically predicted BP traits showed evidence for a protective association with both clinically defined AD and AD_meta, with evidence for confounding by shared genetic instruments. In longitudinal analyses the wGRSs for WMH, but not BP or stroke, showed suggestive association with incident all-cause-dementia (HR, 1.02; 95%CI:1.00-1.04; P=.06). BP and stroke wGRSs were strongly associated with mortality but there was no evidence for selective survival bias during follow-up. In secondary analyses, polygenic scores with more liberal instrument definition showed association of both WMH and stroke with all-cause-dementia, AD, and vascular or mixed dementia; associations of stroke, but not WMH, with dementia outcomes were markedly attenuated after adjusting for interim stroke.

Conclusion: These findings provide converging evidence that WMH is a leading vascular contributor to dementia risk, which may better capture the brain damage caused by BP (and other etiologies) than BP itself and should be targeted in priority for dementia prevention in the population.

Figure 1:. Study workflow

WMH, White matter hyperintensity burden; BP, Blood pressure (Systolic-SBP, Diastolic-DBP, Pulse pressure-PP); AD, clinically diagnosed late-onset Alzheimer’s disease; ADmeta, combination of parental dementia status and AD; ACD, all-cause-dementia; Fstat, F statistics (genetic instrument strength); IVW, Inverse variance weighted; IVs, Instrumental variables; RAPS, Robust adjusted profile score; MVMR, Multivariable mendelian randomization; PGS, Polygenic profile score; *Association analyses in a subset of CHARGE cohorts (3C, AGES).

Figure 2:. Mendelian randomization results of vascular risk factors with ADmeta.

Point estimates and confidence intervals from the inverse-variance weighted (IVW) method are shown. WMH White matter hyperintensity burden. SBP systolic blood pressure, DBP diastolic blood pressure, PP pulse pressure, RAPS Robust adjusted profile score, W-mode Weighted mode, W-median Weighted median.

Figure 3:. Multivariable Mendelian randomization (MVMR) along with the univariable MR for AD as the outcome.

WMH White matter hyperintensity burden. SBP systolic blood pressure, DBP diastolic blood pressure, PP pulse pressure.

Figure 4:. Forest plot showing the meta-analysis results of risk factor wGRSs (per standard deviation increase) with incident ACD.

Circle represents the model not adjusted for education level. Triangle represents the model adjusted for education. Square represents the model after further adjustment for interim stroke (prevalent stroke excluded). Association p-values are shown on the far right. ACD: all-cause-dementia. HUNT: Trøndelag health study, UKB: UK Biobank, RS: Rotterdam study, AGES: Age, Gene/Environment Susceptibility - Reykjavik study, EstBB: Estonian Biobank, 3C: Three-city, CHS: Cardiovascular Health Study, FHS: Framingham Heart Study, Knight-ADRC: Alzheimer’s Disease Research Centre, EPOZ: Epidemiological Prevention Study of Zoetermeer.

Figure 5:. Central role of WMH with dementia outcomes.

VaD: Vascular dementia, B: baseline, P(S): probability of survival bias. Thick background arrows indicate inferences made from observational studies, and solid coloured lines indicate inferences from univariable Mendelian randomization studies. Orange dots and dashed lines represent the multivariable MR setting.