Introduction
Alzheimer’s disease (AD) is the leading cause of dementia, chiefly marked by amyloid plaques and neurofibrillary tangles [
1,
2]. However, several large anti-amyloid trials for mild-to-moderate AD have yielded disappointing results [
2,
3], which made researchers gradually move away from simple assumptions to more broad causality. Substantial evidence showed that the vascular hypothesis might be an alternative theory for AD etiology [
4]. Cerebral small vessel disease (CSVD) is a disorder of cerebral microvessels that always leads to white matter lesions and other abnormalities [
5]. As an assessment, CSVD contributed to about 50% of dementia worldwide [
5‐
7]. Recent meta-analyses have investigated and suggested that white matter hyperintensities (WMH) at baseline conferred a 25% elevated risk of AD, and periventricular WMH conferred a 1.51-fold excess risk for dementia [
8]. Besides, diffusion tensor imaging (DTI) measures and assesses white matter microstructure integrity and white matter damage via estimation of fractional anisotropy (FA) and mean diffusivity (MD) [
9]. Observational studies reported abnormalities in DTI, such as decreased fractional anisotropy (FA) and increased mean diffusivity (MD), in AD and mild cognitive impairment within a diversity of white matter regions [
10‐
12]. Moreover, AD pathology was more likely to have a detrimental impact on WM lesions. Previous studies detected that Aβ pathology developed early cerebral blood flow reductions [
13] and brain amyloid could increase the posterior WMH loads [
14]. Amyloid accumulation also had a worse effect on white matter integrity in the absence of cognitive impairment, particularly in amyloid stage I–II [
15]. Current evidence about a possible relationship between AD and WM damage was mainly based on observational studies, but a direct clue of causation between white matter lesions and AD remained uncertain.
Mendelian randomization (MR) is an alternative means to obtain unconfounded causal inference for the association between white matter change and Alzheimer’s disease as the MR approach takes advantage of genetic variants as instruments [
16]. To this end, we extracted instruments from summary statistics of genome-wide association studies (GWAS) for white matter MRI markers and AD and applied a bidirectional two-sample MR design to assess the potential causal relationship of white matter lesions with the risk of AD, and vice versa.
Discussion
In this bidirectional MR study, a comprehensive MR analysis was performed to assess the association between AD and white matter lesions using a large sample size of GWAS pooled data involving more than 63,000 subjects in AD cohorts and over 17,000 individuals for WMH load and WM microstructural changes. Regrettably, we did not observe that WM injuries were associated with a higher risk of AD. Likewise, genetically predicted AD did not result in a causal effect on white matter damage. However, our research suggested that underlying mechanisms linking AD and white matter lesions might be related to the SNPs near APOE.
Some lines of evidence suggested the comorbidity of abnormalities in the brain microvascular system and AD [
1,
13,
27,
28]. In the general population, the prevalence of white matter lesions increased exponentially with age, ranging from 11% to 21% at age 64 and 94% aged 82 [
29]. Current findings indicated that WMH might predict AD a decade before the clinical stage [
30]. In addition to the positive association between WMH and clinical AD [
8], systematic reviews and meta-analysis studies also have shown a relationship between WMH and a higher risk of specific cognitive domains in patients with AD or MCI [
31]. Moreover, a recent review has suggested colocalized widespread disrupted white matter integrity and AD predominant pathologies (Aβ
42 or tau) in patients with subjective cognitive impairment (SCI), MCI, or AD [
32]. Furthermore, oxidative stress and microglia-mediated inflammation might be common possible pathogenesis of AD progression and white matter damage [
33‐
41]. However, observational studies could not exactly distinguish consequences from causes because of the influence of confounding, as accumulating evidence suggested that cardiovascular disease and other lifestyle-related disorders, including diabetes, smoking, and obesity, might contribute to the progression of dementia and WM lesions [
2,
34].
Using MR approaches, our results suggested that white matter damage containing WMH and white matter integrity could not elevate the risk of AD, which was consistent with a previous randomized controlled trial (RCT) showing that hypertension treatment with nilvadipine did not slow the decline in cognition or function in patients with mild- and moderate-stage AD [
42], although a meta-analysis of RCT studies suggested blood pressure control prevented WMH progression [
43,
44]. Moreover, intensive blood pressure control did not result in a significant reduction in the risk of probable dementia relative to standard blood pressure [
45]. However, these findings were less consistent with a recent MR study showing a positive association of WMH volume with AD [
46]. This inconsistency might be due to the selection bias because the population recruited in our study was limited to European ancestry and the age seemed to be more severe when at recruitment. Similarly, a recent MR analysis leveraging GWAS summary statistics for 110 DTI measurement revealed that the higher risk of AD was causally associated with genetically determined WM integrity in the corpus callosum [
47], but not overall contribution of white matter connectivity. Therefore, white matter changes that increased the risk of AD from the observational study might be better explained by other factors rather than the direct effect. For example, underlying conditions with cardiovascular disease [
48] could interfere with WM lesions and cause AD.
For the relationship between AD and white matter damage, the true causal relationship of AD to the risk of WM injuries was obscured by
APOE. In our research, we observed a false positive result that AD could increase the WMH load and damage the WM microstructural integrity when we included all the instruments of AD, whereas the positive result disappeared when we removed the SNPs in the
APOE region. On the basis of this, we reasonably inferred that SNPs near
APOE might explain the genetic correlation of AD with WM pathologies. As we all know, the presence of the ε4 allele of
APOE had the strongest association with sporadic AD [
49]. Meanwhile,
APOE has been reported to destroy blood–brain barrier integrity, affect cerebral blood flow, and cause neuronal-vascular coupling disorders [
50,
51]. In line with our results, a recent study confirmed that a higher genetic risk score for AD, especially driven by
APOE, was associated with WM lesion burden by examining the polygenic overlap between AD and vascular pathologies. Additionally, the effect of
APOE on memory and global cognition might be partly mediated by WM damage in the mediation analysis [
26]. Additionally, the
APOE ε4 allele could modulate brain WM structure before any impending cognitive or clinical manifestations of the disease [
52] in an age-independent manner [
53]. Besides,
APOE genotype might influence the interaction of WM function with AD pathology. WMH was correlated with amyloid burden especially in the posterior brain regions in
APOE ε4 non-carriers but not in the
APOE ε4 carriers, suggesting that the influence of
APOE might override the effect of WMH on amyloid burden [
54]. However, our MR analyses might not be powerful enough to detect the small effect of impact of AD on WMH after removing the SNPs near the
APOE regions, which needs expanded future discovery GWAS. More evidence is needed to further investigate the mechanisms that underline the influence of AD on white matter.
Limitations
A typical MR study should be designed following three core assumptions [
55]: (1) instruments should be associated with exposure; (2) instruments should influence the outcome only through the exposure, rather than any other pathways; (3) instruments should not be associated with any confounders. To completely rule out all confounders was still a challenge for an MR study as it might not be possible to measure all confounders in the absence of an exact understanding of the complex biology of their relationship with the exposure [
55]. In our study, in addition to the conventional IVW method, we applied four methods as sensitivity analysis, namely the MR-Egger method, weighted median, weighted mode-base method, and MR-PRESSO. A potential bias in our MR study was the presence of horizontal pleiotropy mainly caused by
APOE when we assessed the causal effect of AD on the risk of white matter injuries. To solve this, we removed the instruments in the
APOE regions. In addition, the causal relationship of genetically determined AD with white matter lesions was null after removing the SNPs near the
APOE regions. However, the low power might be the reason for the null results. As population stratification might affect the genetic associations, we restricted the population to European ancestry.
Acknowledgements
This work was made possible by the generous sharing of GWAS summary statistics. We thank the participants, researchers, and staff associated with the many other studies from which we used data for this report. We thank the Hugh Markus group for providing summary data for MRI markers. We also thank the IGAP for providing summary results data for AD. We thank the China Scholarship Council (CSC) [No.201906270200] to fund Li Yaqing to visit the University of Cambridge through the PhD Exchange Scheme.