A population neuroscience approach to the study of cerebral small vessel disease in midlife and late life: an invited review

Abstract

Aging in later life engenders numerous changes to the cerebral microvasculature. Such changes can remain clinically silent but are associated with greater risk for negative health outcomes over time. Knowledge is limited about the pathogenesis, prevention, and treatment of potentially detrimental changes in the cerebral microvasculature that occur with advancing age. In this review, we summarize literature on aging of the cerebral microvasculature, and we propose a conceptual framework to fill existing research gaps and advance future work on this heterogeneous phenomenon. We propose that the major gaps in this area are attributable to an incomplete characterization of cerebrovascular pathology, the populations being studied, and the temporality of exposure to risk factors. Specifically, currently available measures of age-related cerebral microvasculature changes are indirect, primarily related to parenchymal damage rather than direct quantification of small vessel damage, limiting the understanding of cerebral small vessel disease (cSVD) itself. Moreover, studies seldom account for variability in the health-related conditions or interactions with risk factors, which are likely determinants of cSVD pathogenesis. Finally, study designs are predominantly cross-sectional and/or have relied on single time point measures, leaving no clear evidence of time trajectories of risk factors or of change in cerebral microvasculature. We argue that more resources should be invested in 1) developing methodological approaches and basic science models to better understand the pathogenic and etiological nature of age-related brain microvascular diseases and 2) implementing state-of-the-science population study designs that account for the temporal evolution of cerebral microvascular changes in diverse populations across the lifespan.

Fig. 1.

PRISMA flow diagram for the search completed on June 20, 2017. The process of identification for articles is included in the risk factor review.

Fig. 2.

White matter hyperintensities. White matter hyperintensities vary greatly from incomplete infarcts with no tissue loss in patchy areas visible as subcortical punctate white matter hyperintensities (red) to periventricular smooth halos or caps (blue). Images were provided by Dr. Howard Aizenstein (University of Pittsburgh).

Fig. 3.

Deep white matter pathology of age associated with white matter hyperintensities. A and B: low-power paraffin section of the midfrontal cortex from the brain of an 80 yr old. A: hematoxylin and eosin-stained section shows unremarkable gray matter (GM) with adjacent white matter (WM) containing numerous dilated vascular spaces. Overall, the deep white matter staining is more pale than the U-fibers (UF) immediately underlying the gray matter. B: successive section stained with luxol fast blue (LFB), where the gray matter appears pale and white matter a deep blue. Numerous dilated perivascular spaces are noted in the white matter. C and D: high-power micrograph of individual blood vessels within deep white matter. C: the blood vessel lumen (L) is surrounded by mildly thickened media. The adventitia (AD) surrounding the vessel contains macrophages filled with golden hemosiderin. D: special stain for CD68 identifies the hemosiderin laden cells as macrophages (brown cells labeled with arrows). E: medium power micrograph of deep white matter showing a “moth-eaten” pattern imparted by the numerous dilated perivascular spaces. F: the lumen of blood vessels is surrounded by a thickly hyalinized vessel wall. G: some blood vessels have convoluted and collapsed lumina. H: ependymal surface (arrows) of ventricular wall overlay sclerotic vessels. *The ventricular surface focally demonstrates ependymal denudation. Images were provided by Dr. Clayton Wiley (University of Pittsburgh).

Fig. 4.

Lacunar infarction of basal ganglia. A: coronal section through the frontal lobe of the brain of an elderly patient. Ventricles (VEN) are mildly dilated, and there is a lacunar infarct in the head of the caudate on the right side (between arrows). B: hematoxylin and eosin-stained section of the lacune demonstrates a central region of infarction (INF) with tissue loss. C: immunostain for glial fibrillary acidic protein (GFAP) (brown) shows prominent peri-infarct astrocytosis. D: higher-power micrograph of lacunar infarct showing intact ependyma overlying VEN. Tissue surrounding the infarct contains numerous sclerotic blood vessels with dilated perivascular spaces. E: immunostain for GFAP demonstrates pronounced astrocytosis. Images were provided by Dr. Clayton Wiley (University of Pittsburgh).

Fig. 5.

Time-of-flight angiography of arterial tree and susceptibility-weighted image (SWI) of medullary small veins. A: time-of-flight angiography: resolution is 0.32 × 0.32 × 0.32 mm³. This method can be used to visualize small arteries that appear as thin thread-like areas of flow-related contrast. B: SWI. This method can be used to visualize small veins. This is shown here as a thin, smooth, and relatively straight vasculature with moderate branching darker compared with surrounding parenchyma. Resolution is 0.2 × 0.2 × 1.5 mm³. All images are acquired without the use of any contrast agents at 7T. Images are acquired using the Tic Tac Toe Radiofrequency Coil System (http://rf-research-facility.engineering.pitt.edu/). Images were provided by Dr. Tamer Ibrahim (University of Pittsburgh).

Fig. 6.

Associations between risk factors, white matter hyperintensities, and silent brain infarct/lacunes. ⌀, Not a significant association; ↓, significant inverse association; ↑, significant positive association. Red font, <60 yr; black font, ≥60 yr. *Meta-analysis. Studies are cross-sectional unless otherwise noted. L, longitudinal; L¹, predictor precedes outcome, each measured once; L², repeated measures of predictor, outcome measured only at end of followup; L³, predictor measured only once at baseline, repeated measures of the outcome; L⁴, repeated measures of both predictor and outcome.

Fig. 7.

Associations between risk factors and white matter hyperintensities by sample size, study design, and age group. Each circle indicates one study, and the number inside each circle reports the sample size. y-Axis: sample size, scale varies for each risk factor; x-axis: chronological age of the sample. Green, significant association (expected direction, unless otherwise noted); red, not a significant association; square, inverse association of expected direction; solid fill, longitudinal design; no fill, cross-sectional. Lines, case control. *Meta-analysis.

Fig. 8.

Age-related damage to the components of the vessel wall can affect small arterioles and capillaries (red arrows) and/or middle/large caliber arteries (blue arrows). Damage affects endothelial as well as smooth muscle cells and pericytes; these, along with hyalinosis of the basal lamina, can compromise the robustness of the wall, with possible rupture and/or impairment of vasoregulatory ability, resulting in abnormalities in flow and pressure. As they unfold, these events can trigger inflammatory reactions with extravasation of leukocytes, activation of astrocytes, and gliosis. Over time, such events will propagate to other cellular components, affecting oligodendrocytes, neurons, and glial cells.