Pathophysiology of cerebral small vessel disease: a journey through recent discoveries

Cerebral small vessel disease (cSVD) encompasses a heterogeneous group of age-related small vessel pathologies that affect multiple regions. Disease manifestations range from lesions incidentally detected on neuroimaging (white matter hyperintensities, small deep infarcts, microbleeds, or enlarged perivascular spaces) to severe disability and cognitive impairment. cSVD accounts for approximately 25% of ischemic strokes and the vast majority of spontaneous intracerebral hemorrhage and is also the most important vascular contributor to dementia. Despite its high prevalence and potentially long therapeutic window, there are still no mechanism-based treatments. Here, we provide an overview of the recent advances in this field. We summarize recent data highlighting the remarkable continuum between monogenic and multifactorial cSVDs involving NOTCH3, HTRA1, and COL4A1/A2 genes. Taking a vessel-centric view, we discuss possible cause-and-effect relationships between risk factors, structural and functional vessel changes, and disease manifestations, underscoring some major knowledge gaps. Although endothelial dysfunction is rightly considered a central feature of cSVD, the contributions of smooth muscle cells, pericytes, and other perivascular cells warrant continued investigation.

In recent years, increasing numbers of genes have been associated with cSVDs (8–18). Notably, mutations in four genes — NOTCH3, HTRA1 (high-temperature requirement A serine peptidase 1), COL4A1 (collagen type IV α1), and COL4A2 — account for the vast majority of monogenic adult-onset cSVDs (Table 1) (19–22). Among these monogenic forms, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), caused by dominant missense mutations that alter the number of cysteines in one of the 34 EGF repeats in the extracellular domain of the NOTCH3 protein (NOTCH3^ECD), is the most frequent (23). NOTCH3 is a transmembrane receptor predominantly expressed in mural cells — smooth muscle cells (SMCs) and pericytes — of small vessels. CADASIL mutations stereotypically lead to abnormal aggregation and accumulation of NOTCH3 and other extracellular matrix (ECM) proteins around mural cells, and cause pathology likely through a gain-of-function mechanism (24–26). Interestingly, recessive loss-of-function mutations in NOTCH3 are associated with a rare and severe form of cSVD with a childhood onset (27–29). Pathogenic mutations in HTRA1 can manifest as the rare recessive disease, cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy (CARASIL), or a more frequent autosomal dominant cSVD through a loss-of-function or haploinsufficiency mechanism, respectively (10, 11). Notably, two different classes of pathogenic mutations have been identified in collagen type IV, producing radically different effects on collagen type IV expression and very different clinical presentations. Glycine-altering COL4A1/A2 variants produced by glycine substitutions within the triple-helical collagenous domain of COL4A1 or COL4A2 impair collagen IV folding and secretion into the basement membrane and manifest predominantly as spontaneous ICH in deep brain regions (30). In contrast, mutations within the 3′-untranslated region of COL4A1 disrupt the binding site of the microRNA miR-29, resulting in increased COL4A1 expression. This in turn causes pontine autosomal dominant microangiopathy with leukoencephalopathy (PADMAL), an cSVD characterized by ischemic lesions (14).

Table 1

List of genes mutated in monogenic forms of adult-onset cSVD and their prevalence

Although monogenic cSVDs are thought to account for a small proportion (~5%) of cSVDs, variants in NOTCH3, COL4A1/A2, and HTRA1 genes identical to those that cause monogenic cSVDs were recently found to be present at an unexpectedly high frequency in the general population and shown to increase the risk of stroke or dementia, with an additive interaction between cardiovascular risk factor burden and carrier status (Table 2) (31–39). The reason variants in these genes are associated with so broad a phenotypic spectrum is not yet fully understood. Nevertheless, for NOTCH3 and COL4A1/A2, there is emerging evidence that the position of variants affects the penetrance and expressivity of disease manifestations (40–42). Furthermore, common variants near or in NOTCH3, HTRA1, or COL4A1/A2 loci have been shown to be associated with cSVD features (Table 3) (8, 39, 43–51). In summary, these studies highlight a striking continuum between monogenic and multifactorial cSVDs. From an experimental perspective, these findings support the validity of genetically engineered animals carrying Notch3, Col4a1, Col4a2, or Htra1 pathogenic variants as clinically relevant cSVD models.

Table 2

Pathogenic variants in NOTCH3, COL4A1/A2, and HTRA1 genes can lead to rare monogenic cSVD or increase the risk of stroke and dementia in the general population

Table 3

Association between common variants (minor allele frequency >5%) in or near NOTCH3, COL4A1/A2, or HTRA1 loci and cSVD features

Establishing the nature of structural and functional changes in brain vessels in cSVDs and the sequence and timeline linking these changes to brain lesions and clinical symptoms is fundamental to understanding the pathobiology of these complex diseases. Combining the complementary information gained from studies in patients and clinically relevant mouse models of cSVD is a powerful approach for illuminating these mechanisms.

Brain arteriolosclerosis, a hallmark of cSVDs, affects small parenchymal arteries and arterioles and is defined by the degeneration and loss of SMCs, the concentric fibrohyalinotic (glassy-looking acellular) thickening of the arterial wall, the accumulation of ECM components, and subsequent narrowing of the lumen (52, 53). Arteriolosclerosis is highly prevalent in autopsy specimens from individuals over 70 years old, and its severity is significantly associated with the odds of lacunes, subcortical microinfarcts, and WM degeneration (54–56). Arteriole thrombosis and obliteration are only occasionally detected, although they are likely the cause of lacunar stroke (57). Arterial pathology is qualitatively similar between sporadic and hereditary cSVDs, but is quantitatively more aggressive in hereditary forms. In particular, degeneration and loss of arteriolar SMCs is especially severe in CADASIL and CARASIL patients (53). Although pericyte coverage was not specifically examined, a recent study reported a significant reduction in the number of capillary pericytes in the frontal deep WM, a region most frequently afflicted by cSVD, in postmortem tissues from patients with vascular dementia (58). Cerebral venules, which are often overlooked, can also display collagenosis (thickening of the walls with collagen), which has been associated with WM lesions (55, 56).

Brain arteries of aged rodents exhibit increased tortuosity (59–61). Age-related focal loss and degeneration of arterial SMCs can be detected in the superficial vascular network of the retina, a developmental extension of the brain that enables robust quantification at cellular resolution thanks to its stereotypical and planar angioarchitecture (62). Extensive, early loss of arterial SMCs is a feature of brains and retinas of mice completely lacking Notch3, a model of a very severe form of human cSVD (63–65). Interestingly, a recent study suggested that age-related arterial SMC loss might be attributable to a decline in NOTCH3 signaling (66). The cerebroretinal vasculature of Col4a1-mutant mice expressing heterozygous missense mutations that substitute critical glycine residues (G498V, G1064D, or G1344D) within the triple helical domain of COL4A1 also exhibits arterial SMC loss (65, 67, 68). Patients and mice with COL4A1 glycine-altering variants develop spontaneous ICHs in deep brain regions; importantly, pathological analyses of mutant mice indicate that ICHs originate from arteries with reduced SMC coverage, and demonstrate a strong correlation between ICH burden and the severity of arterial SMC loss (67). In contrast, spontaneous ICH is not observed in patients and mice completely lacking NOTCH3 protein, suggesting that loss of arterial SMCs is necessary but not sufficient to cause ICH (65). A major difference in vascular structural integrity between Notch3-KO and Col4a1-mutant mice resides at the level of the arteriole-capillary transition (ACT) zone that lacks an elastic lamina and is surrounded by contractile mural cells that possess more irregular ensheathing processes and a more rounded nucleus than SMCs (Figure 2) (65, 69–72). Here, Notch3-KO mice exhibit a loss of mural cells, whereas Col4a1-mutant mice show an increased number of mural cells in this zone with higher contractile protein content, a defect called “hypermuscularization.” Further genetic, functional, and computational modeling studies in Col4a1-mutant mice provided evidence that arteriole SMC loss and hypermuscularization of the ACT zone act as mutually reinforcing vascular defects to cause ICH, with the excessive ACT zone muscularization raising intravascular pressure in the upstream feeding arteriole and promoting arteriolar rupture at the site of SMC loss (Figure 3) (65). Molecular studies in Col4a1-mutant mice suggest that arterial SMC loss is driven by increased TGF-β activity, whereas the hypermuscularization of the ACT zone arises from increased NOTCH3 activity (65, 68). Regarding the capillary bed, 2D and 3D imaging in rodents revealed a small reduction in vascular length, branching density, and pericyte number, particularly in deep cortical layers and WM, in aged brains (59, 60). Pericyte coverage is reduced in Htra1-KO mice but, in striking contrast, pericyte density and/or coverage are preserved in Notch3-KO mice, Col4a1-mutant mice, and mice carrying an Arg169Cys mutation in NOTCH3 (hereafter referred to as CADASIL mice) (64, 67, 73, 74).

Figure 2

Integrated representation of the anatomy, cellular composition, and physiology of brain vessels. (A) Schematic of the arteriovenous axis with the four main vascular compartments, including the artery/arteriole, the arteriole-capillary transition (ACT) zone, the capillary bed and the venule/vein, and their associated cells: arterial endothelial cells (aECs), arterial SMCs (aSMCs), transitional cells (trans cells, orange), capillary endothelial cells (capECs), venous endothelial cells (vECs), and venous SMCs (vSMCs). Penetrating arteries and arterioles are separated from the brain parenchyma by a fluid-filled space (light green) that disappears as arterioles morph into capillaries and then reappears around veins. The perivascular space (inset) contains resident cells (PVMs and perivascular fibroblasts, PVFBs) and is delimited on the parenchymal side by the glia limitans formed by astrocytic endfeet. (B) Simplified depiction of the main brain vessel functions with respect to each vascular compartment. From top to bottom: (i) CBF autoregulation increases or decreases vessel diameter in response to BP decreases and increases, respectively. aSMCs are the primary sensors of BP changes and the primary effector cells driving changes in vessel diameter. (ii) Neurovascular coupling starts with the increase in local neural activity that leads to capEC hyperpolarization. Hyperpolarizing signal is propagated to upstream arterioles/arteries and transmitted to aSMCs, resulting in retrograde vasodilation. (iii) The BBB is formed by ECs, mural cells with their basement membrane, and astrocytic endfeet. Tight junctions between ECs prevent free paracellular transport of molecules; ECs express specific influx transporters and efflux pumps, which drive the active transport of specific solutes and metabolites into or out of the brain, respectively, and are enriched for the lipid transporter MFSD2A, which inhibits the rate of transcytosis (113, 166). (iv) The glymphatic system involves (a) CSF influx along the periarterial spaces, driven mainly by arterial pulsatility; (b) CSF entry into the brain supported by aquaporin 4 (AQP4) channel expression on the astrocytic endfeet, subsequent mix with the ISF, and flow through the extracellular spaces; and (c) the efflux of extracellular fluid and wastes along perivenous spaces.

Figure 3

Opposite changes in mural cells in the arteriole-capillary transition zone are associated with distinct cSVD features. Schematic representation of brain vessels in (A) the collagen IV–related cSVD, which manifests as recurrent spontaneous ICHs, and in (B) the NOTCH3 null–driven cSVD, which is characterized by recurrent deep infarcts. (A) In the collagen IV disease, the ACT zone shows an increased number of mural cells with higher contractile protein content, raising intravascular pressure in the upstream feeding arteriole, which exhibits loss of SMCs, and promoting arteriolar rupture at the site of SMC loss and hemorrhage (red). (B) In the NOTCH3 null–driven cSVD, the combination of loss of arterial SMCs and loss of mural cells in the ACT zone is predicted to decrease perfusion pressure and promote ischemic lesions in the deep brain regions (gray).

In summary, pathological changes can affect all microvascular compartments. Remarkably, however, structural defects can differ from one microvascular segment to another for a given cSVD and can differ between cSVDs for a given microvascular compartment. Loss and degeneration of arterial SMCs, which is often overlooked, is a key feature of cSVDs and not just an end-stage lesion. Loss of SMCs is especially prominent in severe cSVDs, suggesting that it is likely an important contributing mechanism.

Arteriolosclerosis is hypothesized to stiffen the arterial wall and reduce the ability of arteries to dilate. Using ultra-high-field (7T) quantitative flow MRI, two small case-control studies showed an increased pulsatility index in perforating arteries of the basal ganglia and the WM beneath the cortex in patients with sporadic cSVD or CADASIL compared with controls, suggestive of increased arterial stiffness (75, 76). Hypercapnia, likely through effects on both endothelial cells and SMCs, is a potent vasodilatory stimulus that is commonly used in clinics to assess the capacity of cerebral vessels to dilate (77). CO₂-induced vasodilation is assessed by measuring cerebral blood flow (CBF) increases in response to breathing CO₂ with functional MRI using blood O₂ level–dependent (BOLD) response or arterial spin labeling, which can directly measure CBF. Two recent, large cross-sectional cohort studies showed that a reduced CO₂ response in the WM or subcortical gray matter is associated with more severe cSVD burden (WMHs, lacunes, microbleeds, enlarged PVSs, and brain atrophy) and impaired cognition (78, 79). In a 1-year longitudinal study performed in patients with age-related WMHs, regions of normal-appearing WM that progress to WMHs over time had a lower baseline response to hypercapnia compared with normal-appearing WM (80).

In pharmacological and genetic models of hypertension, cross-sectional area and wall thickness are generally increased, which is considered an adaptive response to increased intravascular pressure that serves to reduce wall stress (81). These changes are associated with stiffening of large pial arteries, but increased distensibility of small pial arterioles. They also occur rapidly (within ~1 week) after the development of hypertension and can recover with blood pressure (BP) normalization (82). In angiotensin II–induced (AngII-induced) hypertensive models, a reduction in lumen diameter (inward remodeling) also develops slowly (over weeks) and does not recover with BP normalization (82). Inward remodeling is considered a maladaptive response to hypertension that is predicted to profoundly reduce CBF. Strikingly, pial arteries of CADASIL mice also exhibit inward remodeling, despite the fact that these mice are normotensive. This defect occurs very early, prior to any other functional changes (83, 84). Furthermore, Htra1-KO mice develop age-dependent accumulation of matrisome proteins, abnormal internal elastica lamina, and decreased distensibility at the level of pial arteries, again in the context of normal BP (74).

In summary, vessel wall remodeling and stiffening of large brain arteries appears to be a consistent feature across cSVDs, and these defects can occur very early in the disease process, even in a context of normal BP. Studies in patients suggest that the reduced capacity of brain vessels to dilate precedes the appearance of WMHs, one of the earliest types of damage in the brain parenchyma of cSVD patients. Moreover, this reduced dilatory capacity is correlated with the severity of cSVD brain lesions and thus may functionally contribute to them.

Autoregulation maintains relatively stable CBF in the face of moment-to-moment fluctuations in arterial BP. SMCs of arteries and arterioles are the primary sensors of changes in BP and the primary effector cells that drive intravascular pressure–dependent changes in diameter, increasing or decreasing vessel diameter in response to BP decreases and increases, respectively (Figure 2B) (85).

Dynamic CBF autoregulation (dCA) can be assessed in humans by quantifying how spontaneous fluctuations in BP are transferred to CBF from simultaneous recording of BP and CBF velocity using transcranial Doppler (85). A recent case-control study (n = 113 cSVD patients and 83 controls) showed that dCA was altered bilaterally in patients and that the degree of impairment was positively associated with the burden of cSVD MRI markers (86).

Experimental studies have shown that pressure-induced constriction (myogenic tone) and CBF autoregulation are impaired in hypertensive mice and in several models of monogenic cSVD. In young hypertensive mice, pial arteries exhibit increased myogenic tone and the autoregulation curve is right-shifted toward higher BP. However, this increase in myogenic constriction, which is thought to protect the distal portion of the vascular network from pressure overload, is lost in aged hypertensive mice (87). In mice carrying a G1344D or G394V glycine mutation in Col4a1, pial arteries exhibit an age-dependent reduction in myogenic tone caused by decreased activity of transient receptor potential melastatin 4 (TRPM4) channels, which are positive regulators of arterial tone (88, 89). Myogenic tone in Col4a1-mutant mice can be restored by improving COL4A1-COL4A2 trafficking using the chemical chaperone 4-phenylbutyrate (88). Interestingly, restoration of myogenic tone is associated with a reduction in the occurrence of ICH, an observation concordant with the current view that myogenic tone protects the vascular bed from pressure overload and ICH (88). In pial arteries of Notch3-KO mice, which exhibit arterial SMC loss, myogenic tone is strongly reduced and CBF autoregulation is severely compromised, with extreme narrowing of the autoregulated range (63, 90). In CADASIL mice, myogenic tone is reduced in pial arteries and penetrating arteries in the absence of overt SMC loss, and the lower limit of CBF autoregulation is right-shifted toward higher BP (83, 91). Decreased myogenic tone and impaired CBF autoregulation in CADASIL mice are attributable to the pathological accumulation of tissue inhibitor of metalloproteinase 3 (TIMP3) protein in NOTCH3^ECD deposits that results in increased density of voltage-gated potassium (K⁺) (K_V) channels, which are powerful negative regulators of arterial tone, in arterial SMCs (92, 93).

In summary, there is some evidence that CBF autoregulation is compromised in patients and experimental models with cSVD, although the intrinsic mechanism — increased or decreased myogenic tone, loss or dysfunction of arterial SMCs — appears to differ among diseases. A key unanswered question is whether a rightward shift in the lower limit of CBF autoregulation to higher BP actually renders the brain, particularly its deep regions, more sensitive to low BP and its potential ischemic consequences.

Considering that WM receives its blood supply from the distal end of long medullary arteries (94), that WM lesions first start in brain areas that are furthest from the origin of the perforating arteries, and that brain arteriolosclerosis is characterized by stenosis of these arteries, it has long been thought that cSVD-related WM lesions are caused by chronic hypoperfusion. Consistent with this idea is the seminal observation of WM rarefaction in a mouse model of chronic hypoperfusion induced by bilateral common carotid artery stenosis (95). Numerous studies have explored the relationship between resting CBF and WMHs at the cross-sectional level. A recent meta-analysis including 2,180 participants from 34 studies showed that WMH burden in patients was worse and CBF was lower in regions with WMHs than in regions with normal-appearing WM. However, the few available longitudinal studies have yielded contradictory results (96); thus, whether reduction in resting CBF precedes or follows WMH progression remains in dispute. Concurrent measurement of the O₂ extraction fraction (OEF), which can now be quantified using noninvasive MRI-based techniques, may be a promising approach for disentangling whether hypoperfusion is a cause or consequence of WMHs, since low CBF and elevated OEF are signatures of hypoxia/ischemia, whereas low CBF and low OEF indicate matched low O₂ supply and demand (97).

Widespread reduction in resting CBF has been reported in Notch3-KO, CADASIL, and Htra1-KO mice, although the mechanism(s) are not fully understood (66, 74, 83). Interestingly, treatment with an AngII receptor type 1 (AT1) blocker improved CBF in Htra1-KO mice in association with reduced accumulation of matrisome proteins and amelioration of pial artery distensibility defects.

In summary, whereas chronic hypoperfusion is an indisputable feature in both cSVD mouse models and patients, whether it is a cause or consequence of brain damage and whether brain hypoperfusion contributes to disease manifestations remain unclear. In humans, recently developed approaches can disentangle this “chicken and egg” question. In mouse models, an in-depth characterization of brain lesions combined with a detailed analysis of the time course of CBF changes might be informative.

Neurovascular coupling (NVC) — the ensemble of mechanisms that mediate activity-dependent increases in blood perfusion (functional hyperemia) — ensures appropriate delivery of nutrients and O₂ in response to changes in local neural activity. Multiple redundant pathways and molecules are involved in linking neural activity to vessel dilation. A recent new paradigm envisions the vast capillary network within the brain acting as a sensory web capable of detecting increases in neuronal activity and sending rapid signals that dilate upstream arteries. In this conceptualization, extracellular K⁺ and nitric oxide (NO) are viewed as the most important neurovascular coupling mediators (98). Endothelial cells sense neural activity–derived K⁺ through the inward-rectifying K⁺ channel, Kir2.1, which is activated by modest elevations in extracellular K⁺ (produced during each action potential), resulting in endothelial cell hyperpolarization. This hyperpolarizing signal rapidly propagates retrogradely from cell to cell through the capillary network via gap junctions, ultimately reaching upstream arterioles and pial arteries. There, the signal passes to SMCs through myoendothelial projections, dilating arteries/arterioles and increasing blood flow to the site of signal initiation (Figure 2B) (99). More distally located thin-strand pericytes have also been reported to regulate capillary blood flow, but with slower kinetics than arteriolar SMCs and mural cells of the ACT zone (100). Besides supplying the metabolic needs of active neurons, NVC may serve additional purposes, such as removing metabolic waste through a vascular route, homogenizing flow in the capillary network, preventing capillary stalls by leucocytes, regulating brain temperature, facilitating cerebrospinal fluid (CSF) movement, and stabilizing the vascular network (101).

NVC can be assessed in humans by monitoring responses to a motor or visual stimulus using functional MRI to measure BOLD responses or through application of arterial spin labeling techniques. But despite the availability of such approaches, there are few studies on cSVD patients. Two independent case-control studies reported significant changes in NVC in CADASIL patients, demonstrating reduced amplitude or a time-shifted decrease in the hemodynamic response (75, 102). However, one caveat with human studies is that the altered blood flow response might be related to a reduction in the neural response due to brain lesions rather than a decrease in NVC efficiency originating in the vascular bed.

Mouse studies have pointed to vascular rather than neural causes of NVC deficiencies. Among these, one recent report provided convincing evidence that aging-related deterioration is caused by an age-dependent decrease in vasoresponsivity that is most pronounced at precapillary sphincters (a novel structure identified in the cortex at the transition between some arterioles and the ACT zone; ref. 103), rather than caused by reduced neuronal activity (104). Hypertension also impairs NVC (105). In AngII-induced chronic hypertension, activation of AT1 receptors in perivascular macrophages (PVMs, a population of resident macrophages in the PVS) is involved in NVC deficits and leads to the production of reactive oxygen species, which impair endothelium-dependent responses (106). NVC is also disrupted in the BPH/2 mouse model of neurogenic hypertension (107). The underlying mechanisms involve PVMs, as described above, as well as defective capillary-to-arteriole signaling caused by a diminished activity of the capillary endothelial cell Kir2.1 channel (108). Strikingly, Col4a1-mutant and CADASIL mice, like hypertensive mice, exhibit an age-dependent reduction in functional hyperemia that also results from defective capillary-to-arteriole signaling as a consequence of diminished capillary endothelial cell Kir2.1 channel activity. Remarkably, the fundamental defect underlying this channelopathy (depletion of the minor membrane phospholipid phosphatidylinositol 4,5-bisphosphate (PIP₂), a key activator of the Kir2.1 channel) is similar in Col4a1-mutant and CADASIL mice, although the intrinsic mechanisms differ (25, 88, 92, 93, 109–111). Interestingly, restoring functional hyperemia by depleting PVMs in hypertensive mice and by chronic inhibition of phosphoinositide-3-kinase (PI3K) in Col4a1-mutant mice improved memory deficits (106, 111). Although these findings support the hypothesis that a chronic reduction in NVC could account for cognitive deficits, further studies are needed to substantiate this relationship and rule out possible confounding effects of specific experimental maneuvers, which may have additional effects on the brain or brain vessels.

In summary, deterioration of NVC is a recurrent theme in mouse models of sporadic and genetic cSVDs. Remarkably, experimental studies have identified shared mechanisms between sporadic and genetic cSVDs, pointing to dysfunction of a single endothelial cell ion channel (Kir2.1) in both cases. Studies in CADASIL patients and mouse models of CADASIL suggest that NVC is impaired prior to the development of subcortical infarcts (93, 102). Additional human studies are needed to assess the reproducibility of BOLD responses in cSVD patients (112) and study the timeline of NVC dysfunction with respect to the appearance of brain lesions and clinical manifestations. Further experimental studies are warranted to better understand whether and how chronic dysfunction of such an important mechanism impairs brain functioning.

The blood-brain barrier (BBB) limits the movement of ions, amino acids, molecules, and cells into and out of the brain (Figure 2B) (113). The glymphatic system is a fluid-clearance pathway thought to primarily serve the function of nonselectively clearing metabolic waste from the brain interstitial space (114). This process, which is primarily active during sleep, is initiated by the flow of CSF along the PVS-surrounding arteries and its entry into the brain. CSF mixes with the interstitial fluid (ISF) in the parenchyma, leaves the brain along perivenular spaces, and is ultimately exported by meningeal lymphatic vessels and along cranial and spinal nerve sheaths toward the cervical lymph nodes (Figure 2B) (114, 115). The flow of CSF in the spaces around pial arteries is pulsatile, reflecting dynamic changes in arterial diameter caused by cardiac impulse waves (arterial pulsatility), which are important physiological drivers that pump CSF inward along these spaces (116). Recent work has further implicated PVMs as important regulators of CSF flow dynamics through their involvement in arterial motion and remodeling of the vascular ECM (117).

Leakage of fibrinogen and other plasma proteins into the brain parenchyma has harmful effects that affect microglial activation, cause neuronal and axonal loss, and promote demyelination and inhibition of remyelination (118, 119). Moreover, this leakage can increase interstitial fluid and cause WM edema. Two studies, using diffusion MRI and a 2-compartment model, support the possibility of increased extracellular free water in WM in patients with sporadic cSVD or CADASIL (120, 121). On the basis of these observations, it has been proposed that cSVD-related brain lesions (WMHs or infarcts) could arise from a leaky BBB. Alternatively, Benveniste and Nedergaard recently crafted the novel hypothesis that failure of fluid transport via the glymphatic system could cause enlargement of PVSs, accumulation of interstitial fluid in WM, and ultimately, demyelination (122).

BBB integrity in humans can be assessed by quantifying the dynamic extravasation (paracellular leakage) of small contrast agent molecules (~550 Da for gadolinium) into the brain parenchyma using dynamic contrast-enhanced MRI. Cross-sectional case-control studies have generally shown changes consistent with widespread, but subtle (i.e., detectable after noise filtering) BBB leakage as well as hotspots of increased BBB permeability in patients with sporadic cSVD (123–125). Cohort studies have shown an association between WMH volume and increased BBB permeability (126, 127). Moreover, longitudinal studies have identified a link between BBB leakage at baseline and the loss of microstructural integrity over time in the perilesional zones around WMHs and further showed that greater BBB leakage at baseline was associated with more severe decline in cognitive functions, especially executive function. Taken together, these data suggest that BBB impairment might play an early role in subsequent WM lesions (128, 129). Nonetheless, studies in CADASIL patients have produced contradictory results (125, 130). Analyzing water exchange across the BBB using arterial spin labeling MRI is another promising approach for assessing subtle BBB dysfunction since water’s molecular weight (~18 Da) is much smaller than that of gadolinium-based contrast agents (131, 132). Using arterial spin labeling MRI, Yang and colleagues recently reported a diffuse alteration (in the whole brain) in the water exchange rate across the BBB in patients with CADASIL or HTRA1-related cSVD, suggestive of an increase in the BBB’s permeability to water (133). BBB integrity in the mouse is compromised upon aging (134). It has also been reported that AngII-induced hypertension enhances BBB permeability by reducing endothelial tight junctions and increasing transcytosis, mainly in arterioles and venules. The mechanism underlying this enhanced BBB permeability primarily involves cooperative interactions of AT1-expressing endothelial cells with PVMs (135). In contrast, the BBB was reported to be preserved in the deoxycorticosterone acetate salt hypertensive model, as well as in adult Col4a1-mutant, CADASIL, or CARASIL mice (67, 73, 74, 136).

How might these human and mouse BBB studies be reconciled? One possibility is the presence of widespread, but subtle, BBB dysfunction in cSVDs, mainly manifesting as increased permeability to water and ions; permeability to water has not yet been assessed in mouse models. On the other hand, a number of confounding factors that could mimic or mask BBB leakage can affect dynamic contrast-enhanced MRI measurements (137). Moreover, hotspot sites of BBB leakage may reflect the presence of recent microinfarcts (73).

DTI along the PVS (DTI-ALPS) around deep medullary veins is an emerging noninvasive technique for evaluating the glymphatic system in humans. The ALPS index represents the CSF efflux function along the perivenous spaces, although additional validation studies are needed (138). Three recent studies performed in population-based cohorts or in patients with sporadic cSVD showed that the DTI-ALPS index was negatively related to the presence and severity of cSVD MRI markers (WMH, lacunes, microbleeds, visible PVS in the basal ganglia, and brain atrophy), suggestive of a declined glymphatic function (139–141). Another small case-control study reported a lower DTI-ALPS index in CADASIL patients compared with controls and an association between the DTI-ALPS index and disease (neuroimaging and clinical) severity (142). However, one potential limitation of these studies is that the DTI-ALPS index is derived from the DTI signal, which is particularly sensitive to WM damages in cSVD and that none of these studies controlled for conventional DTI measures. Studies in mice have shown that aging is associated with progressive glymphatic system dysfunction, manifesting as reductions in both glymphatic influx and efflux. Two factors are primarily responsible for reduced glymphatic influx: decreased arterial wall compliance, which reduces the perivascular pumping of CSF, and depolarization of aquaporin 4, which decreases the transport of fluid across astrocytic endfeet into the brain (143). Glymphatic efflux is likely reduced because of a decrease in the number and diameter of meningeal lymphatics (144). Acute hypertension strongly slows CSF influx in PVSs by increasing backflow (116) and glymphatic transport, both influx and efflux, is altered in spontaneously hypertensive rats (145). A recent study suggested a reduction in glymphatic influx in Notch3-KO mice, possibly because of decreased contractility of cerebral arteries or a reduced number of PVMs (66, 146).

In summary, emerging evidence suggests that the glymphatic system is compromised in cSVD and that impaired CSF/ISF dynamics may participate in the pathogenesis, but this warrants further studies.

Studies in patients and experimental models suggest that functional vascular changes appear years (in humans) or weeks/months (in mice) after exposure to risk factors, but before the appearance of brain lesions. These changes may include stiffening of large arteries, a reduction in dilation capacity and blood flow, attenuation of NVC, subtle BBB leakage, and glymphatic system dysfunction. Nevertheless, much work is still needed to finely map the time course of these changes and assess the causal relationships between these changes and disease manifestations. Going forward, studies in patients with monogenic cSVDs may overcome the confounding issue of heterogeneity of patients with sporadic cSVDs, who may simultaneously display comorbidities and other neurodegenerative processes. It is also worth noting that research to date has tended to focus on WM lesions, with small subcortical infarcts and lacunes receiving less notice, despite the fact that lacune count is a strong predictor of disability and cognitive impairment (147, 148).

Although experimental studies have highlighted candidate mechanisms, elucidating the mechanistic chains linking risk factors, vascular changes, and brain lesions remains a daunting challenge. A first issue to clarify is which cell type(s) are involved and at what steps of the pathogenic process. The endothelial cell is the cornerstone in the regulation of CBF and BBB, and endothelium-dependent functions, such as NVC, are affected early during aging and hypertension or in the setting of pathogenic variants. On the basis of these observations, it has been proposed that cSVDs are initiated in the endothelium and that endothelial dysfunction is a key driver of vascular pathology (149). However, mural cells are also critical effector cells of major brain vessel functions and are certainly key contributors that must not be overlooked. In particular, human and rodent studies indicate that loss of arterial SMCs is a common denominator in many cSVDs, a linkage underscored by the observation that the most aggressive cSVD forms are associated with more severe loss of arterial SMCs. Several recent studies have also highlighted PVMs and perivascular fibroblasts, another major resident cell of PVS, as additional important candidate cellular mediators. A second question pertains to the molecular pathways that lead to vascular cell loss or dysfunction. Genetic, molecular, proteomic, and functional studies point to an important role for proteins of the microvascular ECM as a convergent mechanism in cSVDs (8, 150). Identifying shared molecular pathways among cSVDs would trigger a quantum leap in the development of therapeutic strategies. Another issue relates to the respective contributions of different microvascular compartments. The observation that the ACT zone is hypermuscularized in ICH-related cSVDs and less muscularized in cSVDs with a mostly ischemic presentation suggests that changes in the properties or density of mural cells in this segment could influence the hemorrhagic versus ischemic presentation of cSVDs (Figure 3). Therefore, in-depth molecular, structural, and functional characterizations of each microvascular compartment in distinct cSVD models could potentially provide insight into the relationship between vessel changes and brain damage.

As noted above, cSVDs are especially prevalent with aging. cSVDs and neurodegenerative diseases share similar risk factors and often co-occur. Consequently, other neurodegenerative pathologies can contribute to the clinical presentation. Another major challenge will thus be to clarify whether these two pathologies progress independently of each other or exhibit synergistic interactions.

In conclusion, cSVDs have an enormous impact on human health. Fortunately, the field is now advancing rapidly. Large collaborative research networks that bring together complementary expertise from basic science laboratories to clinics dedicated to cSVDs should enable further breakthroughs in the near future, bringing us closer to the development of therapeutics that can slow the progression of these devastating diseases.

We thank David Hill-Eubank (University of Vermont, Burlington, Vermont, USA) for critical reading and editing of the manuscript. We apologize to all our colleagues whose work has not been mentioned owing to space constraints. The Joutel lab is supported by the National Research Agency, France (grants ANR-16-RHUS-0004 and ANR-22-NEU2-0004-01), the US NIH (grant 1RF1NS128963), the Leducq Foundation for Cardiovascular Research (Leducq Transatlantic Network of Excellence 22CVD01 BRENDA), and Fondation pour la Recherche Médicale (PROJET EQU202203014672).

Address correspondence to: Anne Joutel, Inserm U1266, Institute of Psychiatry and Neurosciences of Paris, 102-108 rue de la Santé, 75014 Paris, France. Phone: 33.1.40.78.92.96; Email: anne.joutel@inserm.fr.

Conflict of interest: The authors have declared that no conflict of interest exists.

Copyright: © 2024, Dupré et al. This is an open access article published under the terms of the Creative Commons Attribution 4.0 International License.

Reference information: J Clin Invest. 2024;134(10):e172841. https://doi.org/10.1172/JCI172841.

1. Pantoni L. Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol. 2010;9(7):689–701.
   View this article via: CrossRef PubMed Google Scholar
2. Wardlaw JM, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 2013;12(8):822–838.
   View this article via: CrossRef PubMed Google Scholar
3. Duering M, et al. Neuroimaging standards for research into small vessel disease-advances since 2013. Lancet Neurol. 2023;22(7):602–618.
   View this article via: CrossRef PubMed Google Scholar
4. Markus HS, de Leeuw FE. Cerebral small vessel disease: Recent advances and future directions. Int J Stroke. 2023;18(1):4–14.
   View this article via: CrossRef PubMed Google Scholar
5. Clancy U, et al. Neuropsychiatric symptoms associated with cerebral small vessel disease: a systematic review and meta-analysis. Lancet Psychiatry. 2021;8(3):225–236.
   View this article via: CrossRef PubMed Google Scholar
6. Ter Telgte A, et al. Cerebral small vessel disease: from a focal to a global perspective. Nat Rev Neurol. 2018;14(7):387–398.
   View this article via: CrossRef PubMed Google Scholar
7. Chabriat H, et al. Cadasil. Lancet Neurol. 2009;8(7):643–653.
   View this article via: CrossRef PubMed Google Scholar
8. Bordes C, et al. Genetics of common cerebral small vessel disease. Nat Rev Neurol. 2022;18(2):84–101.
   View this article via: CrossRef PubMed Google Scholar
9. Joutel A, et al. Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia. Nature. 1996;383(6602):707–710.
   View this article via: CrossRef PubMed Google Scholar
10. Hara K, et al. Association of HTRA1 mutations and familial ischemic cerebral small-vessel disease. N Engl J Med. 2009;360(17):1729–1739.
    View this article via: CrossRef PubMed Google Scholar
11. Verdura E, et al. Heterozygous HTRA1 mutations are associated with autosomal dominant cerebral small vessel disease. Brain. 2015;138(pt 8):2347–2358.
    View this article via: CrossRef PubMed Google Scholar
12. Gould DB, et al. Mutations in Col4a1 cause perinatal cerebral hemorrhage and porencephaly. Science. 2005;308(5725):1167–1171.
    View this article via: CrossRef PubMed Google Scholar
13. Gould DB, et al. Role of COL4A1 in small-vessel disease and hemorrhagic stroke. N Engl J Med. 2006;354(14):1489–1496.
    View this article via: CrossRef PubMed Google Scholar
14. Verdura E, et al. Disruption of a miR-29 binding site leading to COL4A1 upregulation causes pontine autosomal dominant microangiopathy with leukoencephalopathy. Ann Neurol. 2016;80(5):741–753.
    View this article via: CrossRef PubMed Google Scholar
15. Richards A, et al. C-terminal truncations in human 3’-5’ DNA exonuclease TREX1 cause autosomal dominant retinal vasculopathy with cerebral leukodystrophy. Nat Genet. 2007;39(9):1068–1070.
    View this article via: CrossRef PubMed Google Scholar
16. Bugiani M, et al. Cathepsin A-related arteriopathy with strokes and leukoencephalopathy (CARASAL). Neurology. 2016;87(17):1777–1786.
    View this article via: CrossRef PubMed Google Scholar
17. Ding X, et al. Mutations in ARHGEF15 cause autosomal dominant hereditary cerebral small vessel disease and osteoporotic fracture. Acta Neuropathol. 2023;145(5):681–705.
    View this article via: CrossRef PubMed Google Scholar
18. Aloui C, et al. End-truncated LAMB1 causes a hippocampal memory defect and a leukoencephalopathy. Ann Neurol. 2021;90(6):962–975.
    View this article via: CrossRef PubMed Google Scholar
19. Coste T, et al. Heterozygous HTRA1 nonsense or frameshift mutations are pathogenic. Brain J Neurol. 2021;144(9):2616–2624.
    View this article via: CrossRef PubMed Google Scholar
20. Mancuso M, et al. Monogenic cerebral small-vessel diseases: diagnosis and therapy. Consensus recommendations of the European Academy of Neurology. Eur J Neurol. 2020;27(6):909–927.
    View this article via: CrossRef PubMed Google Scholar
21. Guey S, et al. Hereditary cerebral small vessel diseases and stroke: a guide for diagnosis and management. Stroke. 2021;52(9):3025–3032.
    View this article via: CrossRef PubMed Google Scholar
22. Uemura M, et al. High frequency of HTRA1 and ABCC6 mutations in Japanese patients with adult-onset cerebral small vessel disease. J Neurol Neurosurg Psychiatry. 2023;94(1):74–81.
    View this article via: CrossRef PubMed Google Scholar
23. Joutel A, et al. Strong clustering and stereotyped nature of Notch3 mutations in CADASIL patients. Lancet. 1997;350(9090):1511–1515.
    View this article via: CrossRef PubMed Google Scholar
24. Joutel A, et al. The ectodomain of the Notch3 receptor accumulates within the cerebrovasculature of CADASIL patients. J Clin Invest. 2000;105(5):597–605.
    View this article via: JCI CrossRef PubMed Google Scholar
25. Monet-Leprêtre M, et al. Abnormal recruitment of extracellular matrix proteins by excess Notch3 ECD: a new pathomechanism in CADASIL. Brain. 2013;136(pt 6):1830–1845.
    View this article via: CrossRef PubMed Google Scholar
26. Dupré N, et al. Protein aggregates containing wild-type and mutant NOTCH3 are major drivers of arterial pathology in CADASIL. J Clin Invest. 2024;134(8):e175789.
    View this article via: JCI CrossRef PubMed Google Scholar
27. Greisenegger EK, et al. A NOTCH3 homozygous nonsense mutation in familial Sneddon syndrome with pediatric stroke. J Neurol. 2021;268(3):810–816.
    View this article via: CrossRef PubMed Google Scholar
28. Pippucci T, et al. Homozygous NOTCH3 null mutation and impaired NOTCH3 signaling in recessive early-onset arteriopathy and cavitating leukoencephalopathy. EMBO Mol Med. 2015;7(6):848–858.
    View this article via: CrossRef PubMed Google Scholar
29. Stellingwerff MD, et al. Early-onset vascular leukoencephalopathy caused by bi-allelic NOTCH3 variants. Neuropediatrics. 2022;53(2):115–121.
    View this article via: CrossRef PubMed Google Scholar
30. Jeanne M, Gould DB. Genotype-phenotype correlations in pathology caused by collagen type IV alpha 1 and 2 mutations. Matrix Biol. 2017;57-58:29–44.
    View this article via: CrossRef PubMed Google Scholar
31. Hack RJ, et al. Cysteine-altering NOTCH3 variants are a risk factor for stroke in the elderly population. Stroke. 2020;51(12):3562–3569.
    View this article via: CrossRef PubMed Google Scholar
32. Cho BPH, et al. NOTCH3 variants are more common than expected in the general population and associated with stroke and vascular dementia: an analysis of 200 000 participants. J Neurol Neurosurg Psychiatry. 2021;92(7):694–701.
    View this article via: CrossRef PubMed Google Scholar
33. Cho BPH, et al. Association of vascular risk factors and genetic factors with penetrance of variants causing monogenic stroke. JAMA Neurol. 2022;79(12):1303–1311.
    View this article via: CrossRef PubMed Google Scholar
34. Kang CH, et al. Pathogenic NOTCH3 variants are frequent among the Korean general population. Neurol Genet. 2021;7(6):e639.
    View this article via: CrossRef PubMed Google Scholar
35. Liu JY, et al. Rare NOTCH3 variants in a Chinese population-based cohort and its relationship with cerebral small vessel disease. Stroke. 2021;52(12):3918–3925.
    View this article via: CrossRef PubMed Google Scholar
36. Cheng S, et al. The STROMICS genome study: deep whole-genome sequencing and analysis of 10K Chinese patients with ischemic stroke reveal complex genetic and phenotypic interplay. Cell Discov. 2023;9(1):75.
    View this article via: CrossRef PubMed Google Scholar
37. Rutten JW, et al. Archetypal NOTCH3 mutations frequent in public exome: implications for CADASIL. Ann Clin Transl Neurol. 2016;3(11):844–853.
    View this article via: CrossRef PubMed Google Scholar
38. Lee YC, et al. NOTCH3 cysteine-altering variant is an important risk factor for stroke in the Taiwanese population. Neurology. 2020;94(1):e87–e96.
    View this article via: CrossRef PubMed Google Scholar
39. Dichgans M, et al. Genetically proxied HTRA1 protease activity and circulating levels independently predict risk of ischemic stroke and coronary artery disease [preprint]. https://doi.org/10.21203/rs.3.rs-3523612/v1 Posted on Res Sq November 7, 2023.
40. Jeanne M, et al. Molecular and genetic analysis of collagen type IV mutant mouse models of spontaneous intracerebral hemorrhage identify mechanisms for stroke prevention. Circulation. 2015;131(8):1555.
    View this article via: CrossRef Google Scholar
41. Gravesteijn G, et al. NOTCH3 variant position is associated with NOTCH3 aggregation load in CADASIL vasculature. Neuropathol Appl Neurobiol. 2022;48(1):e12751.
    View this article via: CrossRef PubMed Google Scholar
42. Hack RJ, et al. Three-tiered EGFr domain risk stratification for individualized NOTCH3-small vessel disease prediction. Brain. 2023;146(7):2913–2927.
    View this article via: CrossRef PubMed Google Scholar
43. Mishra A, et al. Association of variants in HTRA1 and NOTCH3 with MRI-defined extremes of cerebral small vessel disease in older subjects. Brain. 2019;142(4):1009–1023.
    View this article via: CrossRef PubMed Google Scholar
44. Traylor M, et al. Genetic basis of lacunar stroke: a pooled analysis of individual patient data and genome-wide association studies. Lancet Neurol. 2021;20(5):351–361.
    View this article via: CrossRef PubMed Google Scholar
45. Schmidt H, et al. Genetic variants of the NOTCH3 gene in the elderly and magnetic resonance imaging correlates of age-related cerebral small vessel disease. Brain. 2011;134(pt 11):3384–3397.
    View this article via: CrossRef PubMed Google Scholar
46. Rannikmäe K, et al. COL4A2 is associated with lacunar ischemic stroke and deep ICH: Meta-analyses among 21,500 cases and 40,600 controls. Neurology. 2017;89(17):1829–1839.
    View this article via: CrossRef PubMed Google Scholar
47. Chung J, et al. Genome-wide association study of cerebral small vessel disease reveals established and novel loci. Brain. 2019;142(10):3176–3189.
    View this article via: CrossRef PubMed Google Scholar
48. Sargurupremraj M, et al. Cerebral small vessel disease genomics and its implications across the lifespan. Nat Commun. 2020;11(1):6285.
    View this article via: CrossRef PubMed Google Scholar
49. Persyn E, et al. Genome-wide association study of MRI markers of cerebral small vessel disease in 42,310 participants. Nat Commun. 2020;11(1):2175.
    View this article via: CrossRef PubMed Google Scholar
50. Rannikmäe K, et al. Common variation in COL4A1/COL4A2 is associated with sporadic cerebral small vessel disease. Neurology. 2015;84(9):918–926.
    View this article via: CrossRef PubMed Google Scholar
51. Li J, et al. Replication of top loci from COL4A1/2 associated with white matter hyperintensity burden in patients with ischemic stroke. Stroke. 2020;51(12):3751–3755.
    View this article via: CrossRef PubMed Google Scholar
52. Blevins BL, et al. Brain arteriolosclerosis. Acta Neuropathol. 2021;141(1):1–24.
    View this article via: CrossRef PubMed Google Scholar
53. Craggs LJL, et al. Microvascular pathology and morphometrics of sporadic and hereditary small vessel diseases of the brain. Brain Pathol. 2014;24(5):495–509.
    View this article via: CrossRef PubMed Google Scholar
54. Dozono K, et al. An autopsy study of the incidence of lacunes in relation to age, hypertension, and arteriosclerosis. Stroke. 1991;22(8):993–996.
    View this article via: CrossRef PubMed Google Scholar
55. Cao Y, et al. Arteriolosclerosis differs from venular collagenosis in relation to cerebrovascular parenchymal damages: an autopsy-based study. Stroke Vasc Neurol. 2023;8(4):267–275.
    View this article via: CrossRef PubMed Google Scholar
56. Black S, et al. Understanding white matter disease: imaging-pathological correlations in vascular cognitive impairment. Stroke. 2009;40(3 suppl):S48–S52.
    View this article via: PubMed Google Scholar
57. Wardlaw JM, et al. Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging. Lancet Neurol. 2013;12(5):483–497.
    View this article via: CrossRef PubMed Google Scholar
58. Ding R, et al. Loss of capillary pericytes and the blood-brain barrier in white matter in poststroke and vascular dementias and Alzheimer’s disease. Brain Pathol. 2020;30(6):1087–1101.
    View this article via: CrossRef PubMed Google Scholar
59. Bennett HC, et al. Aging drives cerebrovascular network remodeling and functional changes in the mouse brain [preprint]. https://doi.org/10.1101/2023.05.23.541998 Posted on bioRxiv May 24, 2023.
60. Schager B, Brown CE. Susceptibility to capillary plugging can predict brain region specific vessel loss with aging. J Cereb Blood Flow Metab. 2020;40(12):2475–2490.
    View this article via: CrossRef PubMed Google Scholar
61. Lowerison MR, et al. Aging-related cerebral microvascular changes visualized using ultrasound localization microscopy in the living mouse. Sci Rep. 2022;12(1):619.
    View this article via: CrossRef PubMed Google Scholar
62. Reagan AM, et al. Age-related focal loss of contractile vascular smooth muscle cells in retinal arterioles is accelerated by caveolin-1 deficiency. Neurobiol Aging. 2018;71:1–12.
    View this article via: CrossRef PubMed Google Scholar
63. Domenga V, et al. Notch3 is required for arterial identity and maturation of vascular smooth muscle cells. Genes Dev. 2004;18(22):2730–2735.
    View this article via: CrossRef PubMed Google Scholar
64. Henshall TL, et al. Notch3 is necessary for blood vessel integrity in the central nervous system. Arterioscler Thromb Vasc Biol. 2015;35(2):409–420.
    View this article via: CrossRef PubMed Google Scholar
65. Ratelade J, et al. Reducing hypermuscularization of the transitional segment between arterioles and capillaries protects against spontaneous intracerebral hemorrhage. Circulation. 2020;141(25):2078–2094.
    View this article via: CrossRef PubMed Google Scholar
66. Romay MC, et al. Age-related loss of Notch3 underlies brain vascular contractility deficiencies, glymphatic dysfunction, and neurodegeneration in mice. J Clin Invest. 2023;134(2):e166134.
    View this article via: JCI CrossRef PubMed Google Scholar
67. Ratelade J, et al. Severity of arterial defects in the retina correlates with the burden of intracerebral haemorrhage in COL4A1-related stroke. J Pathol. 2018;244(4):408–420.
    View this article via: CrossRef PubMed Google Scholar
68. Branyan K, et al. Elevated TGFβ signaling contributes to cerebral small vessel disease in mouse models of Gould syndrome. Matrix Biol. 2023;115:48–70.
    View this article via: CrossRef PubMed Google Scholar
69. Gonzales AL, et al. Contractile pericytes determine the direction of blood flow at capillary junctions. Proc Natl Acad Sci U S A. 2020;117(43):27022–27033.
    View this article via: CrossRef PubMed Google Scholar
70. Hill RA, et al. Regional blood flow in the normal and ischemic brain is controlled by arteriolar smooth muscle cell contractility and not by capillary pericytes. Neuron. 2015;87(1):95–110.
    View this article via: CrossRef PubMed Google Scholar
71. Hartmann DA, et al. Pericyte structure and distribution in the cerebral cortex revealed by high-resolution imaging of transgenic mice. Neurophotonics. 2015;2(4):041402.
    View this article via: CrossRef PubMed Google Scholar
72. Mughal A, et al. The post-arteriole transitional zone: a specialized capillary region that regulates blood flow within the CNS microvasculature. J Physiol. 2023;601(5):889–901.
    View this article via: CrossRef PubMed Google Scholar
73. Rajani RM, et al. Blood brain barrier leakage is not a consistent feature of white matter lesions in CADASIL. Acta Neuropathol Commun. 2019;7(1):187.
    View this article via: CrossRef PubMed Google Scholar
74. Kato T, et al. Candesartan prevents arteriopathy progression in cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy model. J Clin Invest. 2021;131(22):e140555.
    View this article via: JCI CrossRef PubMed Google Scholar
75. van den Brink H, et al. CADASIL affects multiple aspects of cerebral small vessel function on 7T-MRI. Ann Neurol. 2023;93(1):29–39.
    View this article via: CrossRef PubMed Google Scholar
76. Geurts LJ, et al. Higher pulsatility in cerebral perforating arteries in patients with small vessel disease related stroke, a 7T MRI study. Stroke. 2019;50(1):62–68.
    View this article via: CrossRef PubMed Google Scholar
77. Liu P, et al. Cerebrovascular reactivity (CVR) MRI with CO₂ challenge: A technical review. NeuroImage. 2019;187:104.
    View this article via: CrossRef PubMed Google Scholar
78. Blair GW, et al. Intracranial hemodynamic relationships in patients with cerebral small vessel disease. Neurology. 2020;94(21):e2258–e2269.
    View this article via: CrossRef PubMed Google Scholar
79. Sleight E, et al. Cerebrovascular reactivity in patients with small vessel disease: a cross-sectional study. Stroke. 2023;54(11):2776–2784.
    View this article via: CrossRef PubMed Google Scholar
80. Sam K, et al. Development of white matter hyperintensity is preceded by reduced cerebrovascular reactivity. Ann Neurol. 2016;80(2):277–285.
    View this article via: CrossRef PubMed Google Scholar
81. Iadecola C, Davisson RL. Hypertension and cerebrovascular dysfunction. Cell Metab. 2008;7(6):476–484.
    View this article via: CrossRef PubMed Google Scholar
82. Sabharwal R, et al. Plasticity of cerebral microvascular structure and mechanics during hypertension and following recovery of arterial pressure. Am J Physiol Heart Circ Physiol. 2022;323(6):H1108–H1117.
    View this article via: CrossRef PubMed Google Scholar
83. Joutel A, et al. Cerebrovascular dysfunction and microcirculation rarefaction precede white matter lesions in a mouse genetic model of cerebral ischemic small vessel disease. J Clin Invest. 2010;120(2):433–445.
    View this article via: JCI CrossRef PubMed Google Scholar
84. Baron-Menguy C, et al. Increased Notch3 activity mediates pathological changes in structure of cerebral arteries. Hypertension. 2017;69(1):60–70.
    View this article via: CrossRef PubMed Google Scholar
85. Claassen JAHR, et al. Regulation of cerebral blood flow in humans: physiology and clinical implications of autoregulation. Physiol Rev. 2021;101(4):1487–1559.
    View this article via: CrossRef PubMed Google Scholar
86. Liu Z, et al. Impaired dynamic cerebral autoregulation is associated with the severity of neuroimaging features of cerebral small vessel disease. CNS Neurosci Ther. 2022;28(2):298–306.
    View this article via: CrossRef PubMed Google Scholar
87. Toth P, et al. Role of 20-HETE, TRPC channels, and BKCa in dysregulation of pressure-induced Ca²⁺ signaling and myogenic constriction of cerebral arteries in aged hypertensive mice. Am J Physiol Heart Circ Physiol. 2013;305(12):H1698–H1708.
    View this article via: CrossRef PubMed Google Scholar
88. Yamasaki E, et al. Impaired intracellular Ca²⁺ signaling contributes to age-related cerebral small vessel disease in Col4a1 mutant mice. Sci Signal. 2023;16(811):eadi3966.
    View this article via: CrossRef PubMed Google Scholar
89. Yamasaki E, et al. Faulty TRPM4 channels underlie age-dependent cerebral vascular dysfunction in Gould syndrome. Proc Natl Acad Sci U S A. 2023;120(5):e2217327120.
    View this article via: CrossRef PubMed Google Scholar
90. Belin de Chantemele EJ, et al. Notch3 is a major regulator of vascular tone in cerebral and tail resistance arteries. Arterioscler Thromb Vasc Biol. 2008;28(12):2216–2224.
    View this article via: CrossRef PubMed Google Scholar
91. Dabertrand F, et al. Potassium channelopathy-like defect underlies early-stage cerebrovascular dysfunction in a genetic model of small vessel disease. Proc Natl Acad Sci U S A. 2015;112(7):E796–E805.
    View this article via: CrossRef PubMed Google Scholar
92. Capone C, et al. Mechanistic insights into a TIMP3-sensitive pathway constitutively engaged in the regulation of cerebral hemodynamics. eLife. 2016;5:e17536.
    View this article via: CrossRef PubMed Google Scholar
93. Capone C, et al. Reducing Timp3 or vitronectin ameliorates disease manifestations in CADASIL mice. Ann Neurol. 2016;79(3):387–403.
    View this article via: CrossRef PubMed Google Scholar
94. Smirnov M, et al. Cerebral white matter vasculature: still uncharted? Brain. 2021;144(12):3561–3575.
    View this article via: CrossRef PubMed Google Scholar
95. Shibata M, et al. White matter lesions and glial activation in a novel mouse model of chronic cerebral hypoperfusion. Stroke. 2004;35(11):2598–2603.
    View this article via: CrossRef PubMed Google Scholar
96. Stewart CR, et al. Associations between white matter hyperintensity burden, cerebral blood flow and transit time in small vessel disease: an updated meta-analysis. Front Neurol. 2021;12:647848.
    View this article via: CrossRef PubMed Google Scholar
97. Kang P, et al. Oxygen metabolic stress and white matter injury in patients with cerebral small vessel disease. Stroke. 2022;53(5):1570–1579.
    View this article via: CrossRef PubMed Google Scholar
98. Schaeffer S, Iadecola C. Revisiting the neurovascular unit. Nat Neurosci. 2021;24(9):1198–1209.
    View this article via: CrossRef PubMed Google Scholar
99. Longden TA, et al. Capillary K⁺-sensing initiates retrograde hyperpolarization to increase local cerebral blood flow. Nat Neurosci. 2017;20(5):717–726.
    View this article via: CrossRef PubMed Google Scholar
100. Hartmann DA, et al. Brain capillary pericytes exert a substantial but slow influence on blood flow. Nat Neurosci. 2021;24(5):633–645.
     View this article via: CrossRef PubMed Google Scholar
101. Drew PJ. Neurovascular coupling: motive unknown. Trends Neurosci. 2022;45(11):809–819.
     View this article via: CrossRef PubMed Google Scholar
102. Huneau C, et al. Altered dynamics of neurovascular coupling in CADASIL. Ann Clin Transl Neurol. 2018;5(7):788–802.
     View this article via: CrossRef PubMed Google Scholar
103. Grubb S, et al. Precapillary sphincters maintain perfusion in the cerebral cortex. Nat Commun. 2020;11(1):395.
     View this article via: CrossRef PubMed Google Scholar
104. Cai C, et al. Impaired dynamics of precapillary sphincters and pericytes at first-order capillaries predict reduced neurovascular function in the aging mouse brain. Nat Aging. 2023;3(2):173–184.
     View this article via: CrossRef PubMed Google Scholar
105. Santisteban MM, et al. Hypertension, neurovascular dysfunction, and cognitive impairment. Hypertension. 2023;80(1):22–34.
     View this article via: CrossRef PubMed Google Scholar
106. Faraco G, et al. Perivascular macrophages mediate the neurovascular and cognitive dysfunction associated with hypertension. J Clin Invest. 2016;126(12):4674–4689.
     View this article via: JCI CrossRef PubMed Google Scholar
107. Jackson KL, et al. Mechanisms responsible for genetic hypertension in Schlager BPH/2 mice. Front Physiol. 2019;10:1311.
     View this article via: CrossRef PubMed Google Scholar
108. Koide M, et al. Differential restoration of functional hyperemia by antihypertensive drug classes in hypertension-related cerebral small vessel disease. J Clin Invest. 2021;131(18):e149029.
     View this article via: JCI CrossRef PubMed Google Scholar
109. Dabertrand F, et al. PIP₂ corrects cerebral blood flow deficits in small vessel disease by rescuing capillary Kir2.1 activity. Proc Natl Acad Sci U S A. 2021;118(17):e2025998118.
     View this article via: CrossRef PubMed Google Scholar
110. Ferris HR, et al. Epidermal growth factor receptors in vascular endothelial cells contribute to functional hyperemia in the brain. Int J Mol Sci. 2023;24(22):16284.
     View this article via: CrossRef PubMed Google Scholar
111. Thakore P, et al. PI3K block restores age-dependent neurovascular coupling defects associated with cerebral small vessel disease. Proc Natl Acad Sci U S A. 2023;120(35):e2306479120.
     View this article via: CrossRef PubMed Google Scholar
112. Lawrence AJ, et al. A comparison of functional and tractography based networks in cerebral small vessel disease. Neuroimage Clin. 2018;18:425–432.
     View this article via: CrossRef PubMed Google Scholar
113. Profaci CP, et al. The blood-brain barrier in health and disease: Important unanswered questions. J Exp Med. 2020;217(4):e20190062.
     View this article via: CrossRef PubMed Google Scholar
114. Rasmussen MK, et al. Fluid transport in the brain. Physiol Rev. 2022;102(2):1025–1151.
     View this article via: CrossRef PubMed Google Scholar
115. Louveau A, et al. Structural and functional features of central nervous system lymphatic vessels. Nature. 2015;523(7560):337–341.
     View this article via: CrossRef PubMed Google Scholar
116. Mestre H, et al. Flow of cerebrospinal fluid is driven by arterial pulsations and is reduced in hypertension. Nat Commun. 2018;9(1):4878.
     View this article via: CrossRef PubMed Google Scholar
117. Drieu A, et al. Parenchymal border macrophages regulate the flow dynamics of the cerebrospinal fluid. Nature. 2022;611(7936):585–593.
     View this article via: CrossRef PubMed Google Scholar
118. Petersen MA, et al. Fibrinogen in neurological diseases: mechanisms, imaging and therapeutics. Nat Rev Neurosci. 2018;19(5):283–301.
     View this article via: CrossRef PubMed Google Scholar
119. Montagne A, et al. Pericyte degeneration causes white matter dysfunction in the mouse central nervous system. Nat Med. 2018;24(3):326–337.
     View this article via: CrossRef PubMed Google Scholar
120. Duering M, et al. Free water determines diffusion alterations and clinical status in cerebral small vessel disease. Alzheimers Dement J Alzheimers Assoc. 2018;14(6):764–774.
     View this article via: CrossRef PubMed Google Scholar
121. Yu X, et al. Increased extracellular fluid is associated with white matter fiber degeneration in CADASIL: in vivo evidence from diffusion magnetic resonance imaging. Fluids Barriers CNS. 2021;18(1):29.
     View this article via: CrossRef PubMed Google Scholar
122. Benveniste H, Nedergaard M. Cerebral small vessel disease: A glymphopathy? Curr Opin Neurobiol. 2022;72:15–21.
     View this article via: CrossRef PubMed Google Scholar
123. Topakian R, et al. Blood-brain barrier permeability is increased in normal-appearing white matter in patients with lacunar stroke and leucoaraiosis. J Neurol Neurosurg Psychiatry. 2010;81(2):192–197.
     View this article via: CrossRef PubMed Google Scholar
124. Zhang CE, et al. Blood-brain barrier leakage is more widespread in patients with cerebral small vessel disease. Neurology. 2017;88(5):426–432.
     View this article via: CrossRef PubMed Google Scholar
125. Walsh J, et al. Microglial activation and blood-brain barrier permeability in cerebral small vessel disease. Brain. 2021;144(5):1361–1371.
     View this article via: CrossRef PubMed Google Scholar
126. Wardlaw JM, et al. Lacunar stroke is associated with diffuse blood-brain barrier dysfunction. Ann Neurol. 2009;65(2):194–202.
     View this article via: CrossRef PubMed Google Scholar
127. Li Y, et al. Higher blood-brain barrier permeability is associated with higher white matter hyperintensities burden. J Neurol. 2017;264(7):1474–1481.
     View this article via: CrossRef PubMed Google Scholar
128. Kerkhofs D, et al. Baseline blood-brain barrier leakage and longitudinal microstructural tissue damage in the periphery of white matter hyperintensities. Neurology. 2021;96(17):e2192–e2200.
     View this article via: CrossRef PubMed Google Scholar
129. Kerkhofs D, et al. Blood-brain barrier leakage at baseline and cognitive decline in cerebral small vessel disease: a 2-year follow-up study. Geroscience. 2021;43(4):1643–1652.
     View this article via: CrossRef PubMed Google Scholar
130. Uchida Y, et al. Iron leakage owing to blood-brain barrier disruption in small vessel disease CADASIL. Neurology. 2020;95(9):e1188–e1198.
     View this article via: CrossRef PubMed Google Scholar
131. Shao X, et al. Comparison between blood-brain barrier water exchange rate and permeability to gadolinium-based contrast agent in an elderly cohort. Front Neurosci. 2020;14:571480.
     View this article via: CrossRef PubMed Google Scholar
132. Voorter PHM, et al. Blood-brain barrier disruption and perivascular spaces in small vessel disease and neurodegenerative diseases: a review on MRI methods and insights. J Magn Reson Imaging. 2024;59(2):397–411.
     View this article via: CrossRef PubMed Google Scholar
133. Li Y, et al. Decreased water exchange rate across blood-brain barrier in hereditary cerebral small vessel disease. Brain J Neurol. 2023;146(7):3079–3087.
     View this article via: CrossRef PubMed Google Scholar
134. Nyúl-Tóth Á, et al. Demonstration of age-related blood-brain barrier disruption and cerebromicrovascular rarefaction in mice by longitudinal intravital two-photon microscopy and optical coherence tomography. Am J Physiol Heart Circ Physiol. 2021;320(4):H1370–H1392.
     View this article via: CrossRef PubMed Google Scholar
135. Santisteban MM, et al. Endothelium-macrophage crosstalk mediates blood-brain barrier dysfunction in hypertension. Hypertension. 2020;76(3):795–807.
     View this article via: CrossRef PubMed Google Scholar
136. Rodrigues SF, Granger DN. Cerebral microvascular inflammation in DOCA salt-induced hypertension: role of angiotensin II and mitochondrial superoxide. J Cereb Blood Flow Metab. 2012;32(2):368–375.
     View this article via: CrossRef PubMed Google Scholar
137. Manning C, et al. Sources of systematic error in DCE-MRI estimation of low-level blood-brain barrier leakage. Magn Reson Med. 2021;86(4):1888–1903.
     View this article via: CrossRef Google Scholar
138. Kamagata K, et al. Noninvasive magnetic resonance imaging measures of glymphatic system activity. [published online September 1, 2023]. J Magn Reson Imaging. https://doi.org/10.1002/jmri.28977.
     View this article via: PubMed Google Scholar
139. Zhang W, et al. Glymphatic clearance function in patients with cerebral small vessel disease. Neuroimage. 2021;238:118257.
     View this article via: CrossRef PubMed Google Scholar
140. Tang J, et al. The association between glymphatic system dysfunction and cognitive impairment in cerebral small vessel disease. Front Aging Neurosci. 2022;14:916633.
     View this article via: CrossRef PubMed Google Scholar
141. Tian Y, et al. Impaired glymphatic system as evidenced by low diffusivity along perivascular spaces is associated with cerebral small vessel disease: a population-based study. Stroke Vasc Neurol. 2023;8(5):413–423.
     View this article via: CrossRef PubMed Google Scholar
142. Hsu SL, et al. Impaired cerebral interstitial fluid dynamics in cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy. Brain Commun. 2024;6(1):fcad349.
     View this article via: CrossRef PubMed Google Scholar
143. Kress BT, et al. Impairment of paravascular clearance pathways in the aging brain. Ann Neurol. 2014;76(6):845–861.
     View this article via: CrossRef PubMed Google Scholar
144. Da Mesquita S, et al. Functional aspects of meningeal lymphatics in ageing and Alzheimer’s disease. Nature. 2018;560(7717):185–191.
     View this article via: CrossRef PubMed Google Scholar
145. Mortensen KN, et al. Impaired glymphatic transport in spontaneously hypertensive rats. J Neurosci. 2019;39(32):6365–6377.
     View this article via: CrossRef PubMed Google Scholar
146. Masuda T, et al. Specification of CNS macrophage subsets occurs postnatally in defined niches. Nature. 2022;604(7907):740–748.
     View this article via: CrossRef PubMed Google Scholar
147. Jolly AA, et al. Prevalence and predictors of vascular cognitive impairment in patients With CADASIL. Neurology. 2022;99(5):e453–e461.
     View this article via: CrossRef PubMed Google Scholar
148. Ling Y, et al. Predictors and clinical impact of incident lacunes in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. Stroke. 2017;48(2):283–289.
     View this article via: CrossRef PubMed Google Scholar
149. Wardlaw JM, et al. Small vessel disease: mechanisms and clinical implications. Lancet Neurol. 2019;18(7):684–696.
     View this article via: CrossRef PubMed Google Scholar
150. Joutel A, et al. Perturbations of the cerebrovascular matrisome: A convergent mechanism in small vessel disease of the brain? J Cereb Blood Flow Metab. 2016;36(1):143–157.
     View this article via: CrossRef PubMed Google Scholar
151. Liu M, et al. Genetic spectrum and clinical features of adult leukoencephalopathies in a Chinese cohort. Ann Clin Transl Neurol. 2023;10(7):1119–1135.
     View this article via: CrossRef PubMed Google Scholar
152. Wu C, et al. The genetic and phenotypic spectra of adult genetic leukoencephalopathies in a cohort of 309 patients. Brain. 2023;146(6):2364–2376.
     View this article via: CrossRef PubMed Google Scholar
153. Lynch DS, et al. Clinical and genetic characterization of leukoencephalopathies in adults. Brain. 2017;140(5):1204–1211.
     View this article via: CrossRef PubMed Google Scholar
154. Wang Y, et al. Genetic study of cerebral small vessel disease in chinese han population. Front Neurol. 2022;13:829438.
     View this article via: CrossRef PubMed Google Scholar
155. Park HK, et al. Prevalence of mutations in mendelian stroke genes in early onset stroke patients. Ann Neurol. 2023;93(4):768–782.
     View this article via: CrossRef PubMed Google Scholar
156. Yuan WZ, et al. Monogenic basis of young-onset cryptogenic stroke: a multicenter study. Ann Transl Med. 2022;10(9):512.
     View this article via: CrossRef PubMed Google Scholar
157. Härtl J, et al. Exome-based gene panel analysis in a cohort of acute juvenile ischemic stroke patients:relevance of NOTCH3 and GLA variants. J Neurol. 2023;270(3):1501–1511.
     View this article via: CrossRef PubMed Google Scholar
158. Tan RYY, et al. How common are single gene mutations as a cause for lacunar stroke? A targeted gene panel study. Neurology. 2019;93(22):e2007–e2020.
     View this article via: CrossRef PubMed Google Scholar
159. Chabriat H, et al. CADASIL: yesterday, today, tomorrow. Eur J Neurol. 2020;27(8):1588–1595.
     View this article via: CrossRef PubMed Google Scholar
160. Whittaker E, et al. Systematic review of cerebral phenotypes associated with monogenic cerebral small-vessel disease. J Am Heart Assoc. 2022;11(12):e025629.
     View this article via: CrossRef PubMed Google Scholar
161. Romeo G, Migeon BR. Genetic inactivation of the alpha-galactosidase locus in carriers of Fabry’s disease. Science. 1970;170(3954):180–181.
     View this article via: CrossRef PubMed Google Scholar
162. Biegstraaten M, et al. Recommendations for initiation and cessation of enzyme replacement therapy in patients with Fabry disease: the European Fabry Working Group consensus document. Orphanet J Rare Dis. 2015;10:36.
     View this article via: CrossRef PubMed Google Scholar
163. Morel H, et al. Extension of the clinicoradiologic spectrum of newly described end-truncating LAMB1 variations. Neurol Genet. 2023;9(3):e200069.
     View this article via: CrossRef PubMed Google Scholar
164. Nozaki H, et al. Distinct molecular mechanisms of HTRA1 mutants in manifesting heterozygotes with CARASIL. Neurology. 2016;86(21):1964–1974.
     View this article via: CrossRef PubMed Google Scholar
165. Kuo DS, et al. COL4A1 and COL4A2 mutations and disease: insights into pathogenic mechanisms and potential therapeutic targets. Hum Mol Genet. 2012;21(r1):R97–110.
     View this article via: CrossRef PubMed Google Scholar
166. Langen UH, et al. Development and cell biology of the blood-brain barrier. Annu Rev Cell Dev Biol. 2019;35:591–613.
     View this article via: CrossRef PubMed Google Scholar