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. Author manuscript; available in PMC: 2025 Aug 28.
Published in final edited form as: Pregnancy (Hoboken). 2025 Apr 24;1(3):e70020. doi: 10.1002/pmf2.70020

Hypertensive disorders of pregnancy and neuroimaging markers of dementia risk: A pilot study

Mohamad J Alshikho 1, Noora Haghighi 2, Rupa Ravi 3, Victoria A Solomon 4, Elizabeth Rangel 5, Jeffrey D Pyne 1, Kelsang C Bista 1, Julia F Chang 1, Rafael V Lippert 1, Dejania Cotton-Samuel 1, Sheica Cedano 3, Nathalie De La Cruz Vasquez 3, Carla A Haro 3, Jeremy Chiu 3, Yufen J Chen 6, Uma Reddy 1, Becky McNeil 7, Victoria L Pemberton 8, Lynn M Yee 5, Todd Parrish 6,9, Adam M Brickman 1,2, Eliza C Miller 2,10, for the nuMoM2b Heart Health Study and nuMoM2b-BraiN Investigators
PMCID: PMC12383491  NIHMSID: NIHMS2084495  PMID: 40881303

Abstract

Background and Objectives:

Hypertensive disorders of pregnancy (HDP) are associated with a long-term risk of maternal cognitive decline. Limited data exist regarding maternal brain structure in midlife after HDP. We examined the association between prior HDP and neuroimaging markers associated with microvascular brain injury, detected on high-resolution brain MRI.

Methods:

We conducted a pilot study embedded within the nuMoM2b Heart Health Study, a multicenter prospective cohort of nulliparous US individuals recruited between 2010 and 2013 in the first trimester of pregnancy. Participants with no history of HDP, preterm birth, small-for-gestational age infant, or stillbirth in any pregnancy, and participants with HDP in the index or any subsequent pregnancy were invited to undergo brain MRI at two study sites between December 21, 2021 and September 30, 2023, using a standardized protocol on identical scanners. Imaging outcomes of interest included white matter hyperintensity (WMH) volume, regional cerebral blood flow (CBF), fractional anisotropy (FA), radial diffusivity (RD), regional grey matter volume (GMV), and cortical thinning.

Results:

A total of 81 participants (mean age 39 years; 27% White, 9% non-Hispanic Black, 52% Hispanic, 10% Asian) had brain MRI, of whom 27 (33%) had a history of HDP. The median time from index delivery to MRI was 11 years. Participants with HDP had lower CBF in the left medial orbitofrontal, left inferior temporal, and right superior temporal lobes (Cohen’s d = 0.3, cluster-wise corrected p = 0.0002 for all subregions); lower FA in the left superior frontal lobe, right lateral occipital lobe, and right precuneus (d = 0.2–0.3, p ≤ 0.01 for all regions); and higher RD in the bilateral medial orbitofrontal lobes (d = 0.2–0.3, p < 0.001). Cortical thickness, regional GMV, and total WMH volume did not differ between groups. A subgroup analysis including only participants with preeclampsia in the exposed group showed similar results.

Discussion:

Midlife individuals who experienced HDP had lower regional CBF and reduced white matter microstructural integrity, compared with those with no adverse pregnancy outcomes. Our results suggest that HDP are associated with long-term impairment of white matter structure and cerebrovascular function, potentially suggesting a mechanism underlying the association of HDP with risk of cognitive decline, and requiring further study.

Keywords: Alzheimer’s disease, dementia, hypertensive disorders of pregnancy, neuroimaging, pregnancy

1 |. INTRODUCTION

Hypertensive disorders of pregnancy (HDP) are leading causes of maternal morbidity and mortality, and their incidence continues to rise, currently complicating 15% of all pregnancies in the United States [1, 2]. HDP are recognized as multisystem vascular disorders, which exist along a spectrum that includes gestational hypertension, preeclampsia, eclampsia, and the HELLP (hemolysis, elevated liver enzymes, low platelets) syndrome. In severe cases, HDP can result in widespread end-organ damage in multiple organs, including kidneys [3, 4], liver [5], heart [6], and brain [7, 8]. Historically, the effects of HDP were thought to resolve with delivery of the placenta [9]; however, HDP are now recognized as an important risk factor for cardiovascular disease [10] and stroke [11–13] later in life.

A growing body of literature suggests that HDP are associated with elevated midlife stroke risk, as well as long-term cognitive dysfunction and a higher risk of vascular dementia [14–18]. HDP may contribute to maternal cerebrovascular risk through biological processes such as vascular endothelial dysfunction and angiogenic dysregulation [19, 20], leading to changes in cerebral blood flow [21, 22] and vasoreactivity [23] and ultimately promoting neurodegeneration and associated cognitive decline. However, data are limited regarding brain structure after HDP. Prospective studies of aging and dementia that included high-resolution brain imaging have rarely collected information regarding pregnancy outcomes; therefore, little is known about the long-term impact of HDP on brain structure, particularly with regard to cerebral microvasculature. Microvascular disease in the brain, also termed cerebral small vessel disease, is a major cause of stroke and dementia [24, 25]. Late markers indicating advanced cerebral small vessel disease include white matter hyperintensities and small (“lacunar”) cerebral infarcts [26]. However, cerebral small vessel disease is a slowly developing process that begins many decades prior to symptom onset [27, 28]. Early cerebral small vessel disease can be detected and quantified with advanced brain MRI techniques that demonstrate subtle structural changes to the white and gray matter [29], as well as alterations in regional cerebral blood flow which may precede structural changes.

The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) Heart Health Study has prospectively followed a diverse cohort of US individuals since the first trimester of their first pregnancy [30]. In an ancillary study, we examined the association between prior HDP and neuroimaging markers associated with early cerebral small vessel disease, detected on high-resolution brain MR. As this was a pilot study undertaken to determine effect size, rather than choose one primary measure a priori, we describe multiple measures of early cerebral small vessel disease, including regional white matter tract integrity [29], regional cerebral blood flow [31, 32], and white matter hyperintensity volume [26]; all of these measures are associated with impairments in cognitive function and higher dementia risk [33].

2 |. MATERIALS AND METHODS

2.1 |. Study design

The study design and detailed methods of the nuMoM2b study and nuMoM2b Heart Health Study have been previously published [30, 34]. The original nuMoM2b study (2010–2013) recruited 10,038 nulliparous participants at eight US academic medical centers, with singleton pregnancies between 6 weeks 0 days to 13 weeks 6 days gestation. Study visits during nuMoM2b included three visits during pregnancy and a fourth at delivery, with the primary aim to identify risk factors for adverse pregnancy outcomes, including HDP. Pregnancy outcomes were adjudicated by maternal-fetal medicine experts.

The follow-up nuMoM2b Heart Health Study (2013-ongoing) was designed to investigate associations between pregnancy outcomes and the development of cardiovascular risk factors and disease. This prospective longitudinal cohort, which is ongoing, currently comprises approximately 6500 of the original nuMoM2b participants. The ancillary nuMoM2b BraiN study (Brain Health and Neurocognition after Pregnancy; R01NS122815, R01AG085475) is an ongoing ancillary aimed at characterizing cognitive function and brain structure in nuMoM2b Heart Health Study participants. As preparation for this study, we conducted a pilot study within this cohort to describe neuroimaging findings associated with dementia risk in individuals with a history of HDP and a comparison group of individuals with no history of adverse pregnancy outcomes. The goal of the pilot was to establish the feasibility of obtaining high-resolution brain imaging in this cohort, and to compare a variety of MRI measures associated with early cerebral small vessel disease to guide the design of future studies in this and other midlife cohorts.

2.2 |. Study population

Beginning in December 2021, English- and Spanish-speaking nuMoM2b Heart Health Study participants at two sites who experienced HDP in any pregnancy were invited to undergo brain MRI without contrast enhancement as part of an ancillary study (nuMoM2b BraiN). A comparison group with a history of healthy pregnancies was recruited from nuMoM2b Heart Health Study participants at the same two study sites. Participants who were currently pregnant or lactating, who reported claustrophobia, or who had metallic implants which were contraindications to MRI, were excluded. Participants with known neurological diagnoses affecting brain structure (e.g., demyelinating disease) were excluded from this analysis. This analysis includes data collected from a total of 81 nuMoM2b Heart Health Study participants who underwent MRI between December 21, 2021, and September 30, 2023. A flow diagram for the analysis sample selection is shown in Figure 1.

FIGURE 1.

FIGURE 1

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Flow diagram of the study sample selection. Participants were recruited between December 2021, and September 2023 from eligible nuMoM2b Heart Health Study participants at two study sites (Northwestern University and Columbia University).

2.3 |. Exposures of interest

The primary exposure of interest for this analysis was HDP in the first or any subsequent pregnancy, defined as gestational hypertension, preeclampsia, eclampsia, or HELLP syndrome. Participants with chronic hypertension diagnosed prior to 20 weeks of the first pregnancy were excluded. HDP were defined according to current American College of Obstetricians and Gynecologists definitions [35]. The comparison group comprised participants with no history of any of the following adverse pregnancy outcomes in any pregnancy: HDP, preterm birth, small-for-gestational age infant, or stillbirth. The additional adverse pregnancy outcomes were chosen as exclusion criteria due to their shared pathophysiological characteristics with HDP, specifically vascular placental dysfunction [36]. This comparison group is hereafter referred to as the “healthy pregnancy” group. In a pre-specified subgroup analysis, only participants with preeclampsia were included in the exposed group, with the same comparison group of individuals with healthy pregnancies. Pregnancy outcomes in the index pregnancy were prospectively collected and adjudicated; for subsequent pregnancies, diagnoses were self-reported with verification by medical chart review by study investigators.

2.4 |. Imaging outcomes

Imaging outcomes of interest included neuroimaging biomarkers associated with neurodegeneration or dementia risk, including the following MRI measures: total and regional (lobar) white matter hyperintensity volume; global and regional cerebral blood flow measured with pseudo-continuous arterial spin labeling (PCASL); white matter microstructural damage measured by diffusion fractional anisotropy and radial diffusivity; and regional cortical thickness and gray matter volume. These specific measures were chosen due to their association with early, subtle brain structural changes which may precede the onset of cognitive impairment or dementia by decades (Table 1).

TABLE 1.

Imaging outcome measures and interpretation.

Imaging measure Explanation Expected direction of effect in cerebral small vessel disease
White matter hyperintensity volume Total and regional volume of white matter lesions seen on T2-weighted FLAIR sequences; indicator of cerebral small vessel damage Higher
Gray matter volume Volume of gray matter, including both cortical and subcortical (e.g., basal ganglia) structures; measure of brain atrophy Lower
Cortical thickness Thickness of gray matter in the cerebral cortex (global and in specific regions); measure of neurodegeneration and brain atrophy Lower
Fractional anisotropy Diffusion imaging measure showing the degree to which water diffuses along white matter tracts; higher diffusion indicates higher white matter tract integrity Lower
Radial diffusivity Diffusion imaging measure showing the degree to which water diffuses radially (perpendicular) from white matter tracts; higher radial diffusion indicates loss of white matter tract integrity Higher
Cerebral blood flow Non-contrast perfusion imaging measure using arterial spin labeling; demonstrates microvascular perfusion in different cerebral regions Lower
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2.5 |. Study procedures

2.5.1 |. Clinical measures

Clinical measures were collected as part of the standard study protocol and are presented for purposes of sample description only. Study participants underwent anthropometric measurements on the day of the MRI including height, weight, and blood pressure. Trained study personnel had previously been certified in all measurements. Blood pressure was measured using a standard automated monitor (Omron HEM907XL). Arm circumference was measured to determine the correct cuff size. Measurements were taken in triplicate after a full 5 min of rest, using the right arm if possible. There was a rest period of 30 s following each reading. The means of the second and third measurements were used for all analyses. Medical, obstetrical, and social histories were updated via standardized interview and survey questionnaires.

2.5.2 |. MRI acquisition and processing

Study participants underwent brain MRI without contrast enhancement, with a standardized and harmonized protocol at both study sites, using 3-Tesla Siemens Prisma scanners equipped with a 64-channel head coil. MRI acquisition parameters and sequences are shown in the Supplementary Methods. Raw MRI data were analyzed centrally at one site. White matter hyperintensity volume was quantified using an in-house developed tool [37]. Cerebral blood flow from PCASL data was derived with the Bayesian Inference for Arterial Spin Labeling MRI (BASIL) toolkit in FSL version 6.0.4 [38]. Standard pipelines in FreeSurfer v7.3.2 were used to generate fractional anisotropy and radial diffusivity maps from diffusion data, and for computing cortical thickness and gray matter volume. Full details of MRI processing for all imaging data are shown in the Supplementary Methods.

2.6 |. Statistical analysis

2.6.1 |. Descriptive statistics

We described demographic and clinical characteristics of interest overall and by exposure groups, including social determinants of health, pregnancy history, and current chronic health conditions. Chronic hypertension was defined as a self-reported diagnosis of hypertension, current use of antihypertensive medication, or a measured systolic blood pressure ≥ 130 or diastolic blood pressure ≥ 80 mmHg at the time of the study visit. All variables were collected or self-reported at the time of MRI acquisition, with the exception of first-trimester BMI and blood pressure, which were collected at the time of the index (nuMoM2b) pregnancy. Characteristics were compared between exposure groups using parametric or non-parametric tests, depending on the distribution, for continuous variables and chi-square for categorical variables, with a p value of 0.05 as the threshold for significance. Descriptive statistics were performed using IBM SPSS, version 27.0, Armonk, NY.

2.6.2 |. Imaging analyses

Violin plots were created to illustrate differences in the distribution of white matter hyperintensity volume between individuals with and without a history of preeclampsia in multiple lobar regions [39]. The Mann-Whitney U test was used to compare white matter hyperintensity volume between individuals with and without a history of HDP. Surface-based outcome measurements of interest, including cerebral blood flow, fractional anisotropy, radial diffusivity, gray matter volume, and cortical thickness, were compared between participants with and without a history of HDP using FreeSurfer version 7.3.2. After processing and quality review (see Supplementary Methods), cerebral blood flow, fractional anisotropy and radial diffusivity data, bi-hemispheric volumetric surfaces, and cortical thickness were compared with generalized linear models. Age was incorporated as a covariate in all models. Results were corrected for multiple comparisons using precomputed Z Monte Carlo simulation [40]. A vertex-wise cluster-forming threshold was set at p < 0.05. To account for the analysis of both brain hemispheres, we adjusted the resulting p values with the Bonferroni procedure.

2.7 |. Standard ethical approvals and informed consent

All study participants were members of the ongoing nuMoM2b Heart Health Study cohort, and written informed consent was obtained from all participants at the time of the MRI study visit. The protocol for this study was approved by the Single Institutional Review Board (IRB) of Record (Advarra, Inc.); each participating institution also provided local IRB approval in accordance with institutional policies.

3 |. RESULTS

3.1 |. Participant characteristics

A total of 81 nuMoM2b-Heart Health Study participants underwent brain MRI during the study period, including 27 (33%) with a history of HDP and 54 with healthy pregnancies. The HDP episode occurred during the index (nuMoM2b) pregnancy in 24 (89%) of the 27 participants in the HDP group. For the three participants who did not have HDP in the index pregnancy, but self-reported HDP in one or more subsequent pregnancies, the diagnosis was confirmed by medical chart review. Among participants with HDP, 19 (70%) met diagnostic criteria for preeclampsia, and the remaining eight had gestational hypertension. There were no participants with eclampsia or the HELLP syndrome.

Characteristics of the study population are shown in Table 2. The mean age at the time of MRI was 39 years (SD = 6) and was similar between groups. The mean age at first birth also did not differ between groups, at 29 years (SD = 6). The median time from index delivery to MRI was 11 years in the HDP group and 10 years in the healthy pregnancy group, a non-significant difference. A total of 44% of participants in each group met criteria for chronic hypertension at the time of the study visit. Among participants with a history of HDP, 22% reported self-identified non-Hispanic Black race, compared with 2% of those with healthy pregnancies (p = 0.03).

TABLE 2.

Characteristics of the study population.

Characteristica Overall (N = 81) HDP (N = 27) No HDP (N = 54) p value
Age, years (mean, SD) 39.0, 6.0 39.4, 6.4 40.0, 5.8 0.95
Age at first birth, years (mean, SD) 29.0, 6.1 28.9, 6.5 29.0, 5.9 0.90
Time, years, from delivery to MRI (median, IQR) 11.0, 1.0 11.0, 2.0 10.0, 1.0 0.74
Race/ethnicity (n, %) 0.03
 White 22, 27.2% 5, 18.5% 17, 31.5%
 Non-Hispanic Black 7, 8.6% 6, 22.2% 1, 1.8%
 Hispanic 42, 51.9% 13, 48.1% 29, 53.7%
 Asian/Pacific Islander 8, 9.9% 2, 7.5% 6, 11.1%
 Multiple race 2, 2.5% 1, 3.7% 1, 1.8%
Primary language (n, %) 0.27
 English 60, 74.1% 22, 81.5% 38, 70.4%
 Spanish 21, 25.9% 5, 18.5% 16, 29.6%
Highest education level (n, %) 0.83
 High school or less 17, 21.0% 7, 25.9% 10, 18.5%
 Did not complete college 7, 8.6% 2, 7.4% 5, 9.3%
 2-year college degree 6, 7.4% 2, 7.4% 4, 7.4%
 4-year college degree 27, 33.3% 10, 37.0% 17, 31.5%
 Advanced degree 24, 29.6% 6, 22.2% 18, 33.3%
Total number of pregnancies (median/IQR) 2.0, 1.0 2.0, 1.0 2.0, 1.0 0.76
Total number of live births (median/IQR) 2.0, 1.0 1.5, 1.0 2.0, 1.0 0.13
Number of pregnancies with adverse outcomeb (median/IQR) 0.0, 1.0 1, 0.0 0.0, 0.0 <0.001
Chronic hypertensionc (n, %) 36, 44.4% 12, 44.4% 24, 44.4% 0.97
Diabetes mellitus (non-gestational) (n, %) 2, 2.5% 0, 0% 2, 3.7% 0.31
Gestational diabetes, any pregnancy (n, %) 11, 13.6% 2, 7.4% 9, 16.7% 0.26
Migraine (n, %) 48, 59.3% 19, 70.4% 29, 53.7% 0.14
Hyperlipidemia (n, %) 7, 8.6% 4, 14.8% 3, 5.6% 0.16
Former or current smoker (n, %) 16, 19.7% 7, 25.9% 9, 16.7% 0.31
BMI, 1st trimester of 1st pregnancy, kg/m2 (mean, SD) 27.0, 7.0 29.1, 6.7 27.0, 7.0 0.18
Current BMI, kg/m2 (mean, SD) 29.0, 7.0 30.7, 6.9 29.0, 7.0 0.20
Systolic blood pressure, 1st trimester of 1st pregnancy, mmHg (mean, SD) 111, 10 114, 11 110, 10 0.18
Diastolic blood pressure, 1st trimester of 1st pregnancy, mmHg (mean, SD) 66, 8 69, 9 66, 8 0.21
Current systolic blood pressure, mmHg (mean, SD) 120, 17 121, 18 119, 16 0.57
Current diastolic blood pressure, mmHg (mean, SD) 78, 12 77, 14 79, 11 0.55
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Abbreviations: BMI, body mass index; HDP, Hypertensive disorders of pregnancy; IQR, interquartile range; SD, standard deviation; USD, United States dollars.

a

All characteristics are at the time of MRI acquisition unless otherwise specified.

b

HDP group only; history of adverse pregnancy outcomes was one of the exclusion criteria for the comparison group. “Adverse pregnancy outcome” was defined as one or more of the following conditions: gestational hypertension, preeclampsia/eclampsia, preterm birth (spontaneous or medically indicated birth prior to 37 weeks gestation), small for gestational age (<5th percentile by Alexander criteria), stillbirth.

c

Chronic hypertension was defined as self-reported diagnosis of hypertension, current use of antihypertensive medication, or a measured systolic BP ≥ 130 and diastolic BP ≥ 80 mmHg at the time of the study visit.

3.2 |. Comparison of imaging markers

Violin plots of white matter hyperintensity volume comparison analyses for both groups in multiple brain regions are shown in Figure 2. Mean total white matter hyperintensity volume across all lobes did not differ in the HDP compared to the healthy pregnancy group. In addition, no differences in white matter hyperintensity volume were seen in individual lobes (frontal, temporal, parietal, and occipital).

FIGURE 2.

FIGURE 2

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White matter hyperintensity volume comparison between individuals with and without a history of hypertensive disorders of pregnancy. Panel (A) shows overlapping histograms created using kernel density estimation, detailing the distribution of WMH volumes (cm3) across the frontal, parietal, occipital, and temporal lobes for all participants. Panels (B) through (F) show kernel density estimation–derived violin plots illustrating the data distribution for regional (lobar) and total WMH volume by exposure group. Mean values are indicated by a bold horizontal line, median with red dot, and quartiles by dashed lines. p values calculated using the Mann–Whitney U test are displayed at the top of each plot. APO, adverse pregnancy outcome; HDP; hypertensive disorders of pregnancy; WMH, white matter hyperintensity.

Results of MRI surface-based analyses are displayed in Table 3, and Figures 3 and 4. As illustrated in the effect size map (Figure 3), cerebral blood flow, fractional anisotropy, gray matter volume, and cortical thickness were lower in the HDP group compared with the healthy pregnancy group in multiple brain regions, but differences were not statistically significant in most regions. Statistical maps illustrating regions of significant between-group differences after correction for multiple comparisons are shown in Figure 4. Participants in the HDP group had lower cerebral blood flow in the frontal and temporal lobes, specifically in the left medial orbitofrontal, left inferior temporal, and right superior temporal (cluster-wise corrected p = 0.0002 for all regions). Lower fractional anisotropy was seen in the HDP group in the left superior frontal lobe (p = 0.0008), right lateral occipital lobe (p = 0.01), and right precuneus (p = 0.02). HDP participants also had higher RD in the bilateral medial orbitofrontal lobes (p = 0.0002 and p = 0.006 for left and right sides, respectively). Gray matter volume and cortical thickness did not differ significantly between groups.

TABLE 3.

Comparison of MRI-derived metrics between participants with a history of hypertensive disorders of pregnancy and participants with no adverse pregnancy outcomes.

Sublobar region of difference (R = right, L = left) P cw a Cluster sizeb (mm2) 95% CI Effect sizec
Cortical GMV No significant differences between groups
FA L superior frontal 0.0008 83.83 [0.0004–0.0014] −0.2991
R lateral occipital 0.01 64.33 [0.0089–0.0126] −0.2153
R precuneus 0.02 61.23 [0.0153–0.0201] −0.2287
RDd L medial orbitofrontal 0.0002 909.18 [0.00000–0.0004] +0.2899
R medial orbito-frontal 0.0006 889.78 [0.0002–0.0010] +0.1864
CBFd L medial orbito-frontal 0.0002 28123.9 [0.00000–0.0004] −0.2821
L inferior temporal 0.0002 3531.39 [0.00000–0.0004] −0.3018
R superior temporal 0.0002 10720.21 [0.00000–0.0004] −0.2992
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Abbreviations: CBF, cerebral blood flow; FA, fractional anisotropy; GMV, grey matter volume; RD, radial diffusivity.

a

Cluster-wise p value corrected for multiple comparisons using Z Monte Carlo simulation (10,000 iterations).

b

“Cluster size” refers to the number of contiguous voxels where a significant effect is observed.

c

Effect size (EF) is calculated using the formula EF = gamma/sqrt(gammavar*Npilot), where gamma is the observed effect and gammavar is its variance; Npilot is the total number of subjects in the pilot study. Effect size, expressed as Cohen’s d, indicates the magnitude of change in the HDP group, versus the healthy pregnancy group, where a Cohen’s d of 1.0 indicates a one-standard deviation difference between group means.

d

Maps are corrected for partial volume effect using the Muller–Gartner Method and smoothed at fwhm = 5 mm.

FIGURE 3.

FIGURE 3

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Effect size of differences between individuals with and without a history of hypertensive disorders of pregnancy. This figure illustrates the magnitude of effect size (Cohen’s d) differences in MRI-derived metrics between individuals with and without a history of HDP. Variations in cerebral blood flow (A), fractional anisotropy (B), cortical thickness (C), and cortical grey matter volume (D) are visualized on the brain surface to highlight the effect estimates, regardless of statistical significance. The color scale represents effect size and ranges from −0.5 to 0, where positive values indicate an increase and negative values a decrease in the measured metric in individuals with a history of HDP, compared to those with a history of healthy pregnancies. HDP, hypertensive disorders of pregnancy.

FIGURE 4.

FIGURE 4

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Surface-based analyses of differences in MRI-derived metrics between individuals with and without a history of hypertensive disorders of pregnancy. Surface-based analysis was conducted on the pial surface to evaluate differences in cerebral blood flow (A), fractional anisotropy (B), radial diffusivity (C), gray matter volume (D), and cortical thickness (E). Analyses were carried out using FreeSurfer and were corrected for multiple comparisons (p < 0.05). The figures are aggregate anatomical representations of the brain, with regional color coding to indicate an increase (red) or decrease (blue) in the respective metrics in the group with a history of HDP, compared to the group with a history of healthy pregnancies. HDP, hypertensive disorders of pregnancy.

3.3 |. Subgroup analysis

In the subgroup analysis of participants with preeclampsia versus those with healthy pregnancies, results were similar: lower cerebral blood flow, lower fractional anisotropy, and higher radial diffusivity were seen in the preeclampsia group in multiple regions, with similar effect sizes, and gray matter volume and cortical thickness also did not differ between groups (Table 4).

TABLE 4.

Comparison of MRI-derived metrics between participants with a history of preeclampsia (excluding gestational hypertension) and participants with no adverse pregnancy outcomes.

Sublobar region of difference (R = right, L = left) P cw a Cluster sizeb (mm2) 95% CI Effect sizec
Cortical GMV No significant differences between groups
FA L superior frontal 0.0002 120.42 [0.0000–0.0004] −0.1973
L precentral 0.0006 84.64 [0.0002–0.0010] −0.2016
R middle temporal 0.02 62.3 [0.0129–0.0173] −0.2268
RDd L medial orbitofrontal 0.006 661.06 [0.0047–0.0076] +0.1802
CBFd L medial orbitofrontal 0.0002 33243.18 [0.00000–0.0004] −0.2529
R superior temporal 0.0002 4745.2 [0.00000–0.0004] −0.3013
R supramarginal 0.03 1686.47 [0.02326–0.0292] −0.1937
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Abbreviations: CBF, cerebral blood flow; FA, fractional anisotropy; GMV, gray matter volume; RD, radial diffusivity.

a

Cluster-wise p value corrected for multiple comparisons using Z Monte Carlo simulation (10,000 iterations).

b

“Cluster size” refers to the number of contiguous voxels where a significant effect is observed.

c

Effect size (EF) is calculated using the formula EF = gamma/sqrt(gammavar*Npilot), where gamma is the observed effect and gammavar is its variance; Npilot is the total number of subjects in the pilot study. Effect size, expressed as Cohen’s d, indicates the magnitude of change in the HDP group, versus the healthy pregnancy group, where a Cohen’s d of 1.0 indicates a one-standard deviation difference between group means.

d

Maps are corrected for partial volume effect using the Muller–Gartner Method and smoothed at fwhm = 5 mm.

4 |. DISCUSSION

In our study of brain MRI in 81 parous individuals followed prospectively since their first pregnancies approximately 11 years earlier, we found that those with a history of HDP had lower regional cerebral blood flow in the frontal and temporal lobes, lower fractional anisotropy in the frontal and occipital lobes, and higher radial diffusivity in the frontal lobes, compared with those who had a history of healthy pregnancies. These results suggest damage to white matter structural integrity, possibly related to early microvascular disease impairing blood supply to these areas. Cortical thickness and gray matter volume, markers of brain atrophy, were also lower in the HDP group in multiple regions, but the differences were not statistically significant. White matter hyperintensity volume, a late indicator of microvascular disease in the brain, did not differ between groups. When the analysis was restricted to those with a history of preeclampsia compared with those with healthy pregnancies, the results were similar.

The areas where we observed significant differences between groups represent substantial volumes of affected brain tissue and large functional territories rather than small, isolated regions. For cerebral blood flow specifically, the largest cluster in the right superior temporal region (10,720 mm2) is particularly notable. The cerebral blood flow changes in left medial orbitofrontal and left inferior temporal regions also involved substantial clusters (>3500 mm2), suggesting widespread effects across multiple functional networks. The large affected areas in the orbitofrontal and temporal regions are involved in critical cognitive functions including decision-making, emotional processing, language, and memory. The brain regions affected—primarily orbitofrontal, temporal, and parietal cortices—are known to be vulnerable in neurodegenerative processes [41]. This pattern of large, distributed clusters of affected brain tissue aligns with the clinical presentation of vascular cognitive impairment, where early changes are often subtle but widespread, preceding more pronounced focal deficits that emerge later in the disease process.

4.1 |. Results in context of prior literature

Our results generally align with prior studies, suggesting microstructural white matter damage and alterations in cerebrovascular function after HDP. However, previous studies investigating brain structure in midlife after HDP are limited. The largest of these examined associations between HDP, cognitive performance, and brain MRI findings in 1075 women enrolled in the Genetic Epidemiology Network of Arteriopathy (GENOA) study, a multi-racial and multi-ethnic cohort [14]. The authors found that a self-reported history of any HDP was associated with decreased processing speed and smaller brain volumes, even after adjustment for vascular risk factors and duration of hypertension. Of note, the mean age of GENOA participants was 61 years, more than 20 years older than the mean age of our participants, and the index pregnancies occurred decades earlier. A retrospective cohort study in the Netherlands of 138 formerly preeclamptic or eclamptic women and 75 parous controls (mean age 37) found more extensive white matter lesions on brain MRI, predominantly in the frontal lobes, followed by the parietal, insular, and temporal lobes [42]. A follow-up study in the same cohort several years later (mean age 40 years) again found increased severity of subcortical white matter lesions in those with a history of preeclampsia or eclampsia [43]. A study of 80 older women (sixth and seventh decades of life) in the Rochester Epidemiology Project (Olmsted County, Minnesota), of whom 40 had a history of preeclampsia verified with medical chart abstraction, found that those with a history of preeclampsia and current hypertension had lower total gray matter volume compared both to those without a history of preeclampsia (with or without hypertension), and to those with a history of preeclampsia but without current hypertension [44]. This study also reported voxel-based analyses demonstrating that these volume differences were localized to the posterior brain regions.

To our knowledge, no study has previously reported findings showing long-term differences in regional cerebral blood flow after HDP. Prior studies have reported differences in cerebrovascular reactivity, another measure of cerebrovascular health, in individuals with a history of preeclampsia. One transcranial Doppler-based study found decreased cerebrovascular reactivity in the middle cerebral arteries in 40 post-menopausal women with a history of preeclampsia, compared with age- and parity-matched controls with a history of normotensive pregnancies [45]. A different study, using cerebral perfusion imaging in 22 individuals with and without a history of preeclampsia approximately 10 years prior to MRI, found impaired regional cerebrovascular reactivity in the parietal lobes in individuals with a history of preeclampsia and vascular placental lesions [23].

Several studies have reported detailed brain microstructural features in midlife women with a history of preeclampsia. In a 2017 retrospective study in Germany of 83 women, of whom 34 had a history of preeclampsia between 5 and 15 years prior to MRI, those with a history of preeclampsia had lower cortical gray matter volume, higher volume of white matter lesions in the temporal lobes, lower fractional anisotropy in the temporal and occipital lobes, and increased radial diffusivity in the temporal, parietal and occipital lobes [46]. These differences were not explained by between-group differences in cardiovascular risk profiles. Several recently published studies included data collected from participants in the observational Queen of Hearts study of premenopausal women in the Netherlands, with and without a history of preeclampsia (ClinicalTrials.gov identifier: NCT02347540). Those with a history of preeclampsia showed impairment in blood–brain barrier integrity with increased leakage rates, particularly in white matter regions [47], and differences in functional connectivity in the prefrontal and limbic cortices [48]. However, no differences in total and regional brain volume were observed between groups [49].

Our study, in a prospective, racially and ethnically diverse premenopausal US cohort, confirms previously reported differences in regional white matter integrity, and is the first to report regional differences in cerebral blood flow. Of note, we did not identify any differences in white matter hyperintensity volume between groups. This may be due to the younger age of our participants, compared to prior cohorts; white matter lesions may be a later manifestation of cerebral small vessel disease.

4.2 |. Clinical implications

HDP are now well recognized to be associated with a long-term risk of cardiovascular disease [10] and stroke [50]. Accumulating evidence also supports that HDP are associated with a higher risk of all-cause dementia and in particular, vascular dementia [16]. Uncertainty remains regarding whether this association is causal or if HDP represent a “failed stress test” marking an individual who is at higher cardiovascular and cerebrovascular risk [51]. Regardless of whether HDP play a causal role, our results demonstrate that even in early midlife, individuals with a history of HDP show features of brain structure and cerebrovascular function that are associated with cerebral small vessel disease and dementia.

The effect sizes in our study (Cohen’s d ranging from 0.19 to 0.30) fall within the small-to-moderate range, yet they represent detectable differences in cerebral blood flow and white matter integrity approximately 11 years postpartum. These findings emerged despite our relatively small sample size. While modest, these differences may reflect early, subclinical cerebrovascular alterations. To offer a clinical frame of reference, the observed reductions in cerebral blood flow in the HDP group (Cohen’s d ≈ 0.30) are on par with what is typically seen over 5–7 years of healthy aging [52].

Our results suggest a clinical need for long-term follow-up and monitoring for the development of cognitive decline in individuals who experience HDP. Despite widely available and well-validated clinical tools [53], cognitive screening is rarely performed in women’s health clinics, although pilot programs exist [54]. Clinicians should consider incorporating routine cognitive screening into well woman visits for individuals with a history of HDP, with referral to neurology for abnormal findings or reported subjective cognitive decline.

4.3 |. Scientific implications

It is biologically plausible that HDP directly cause microstructural damage in the brain that persists years after the initial insult. Microstructural damage after HDP has been demonstrated in other organ systems [55]. A case control study using high-resolution echocardiography found cardiac remodeling including global diastolic dysfunction and myocardial damage in patients with preeclampsia at term [56]. Similarly, increased left ventricular mass and myocardial scarring, both indicators of microvascular disease, were detected on cardiac MRI in individuals with a history of HDP [57]. Human studies also demonstrated preeclampsia-associated microvascular damage in the kidney [58, 59], placenta [60], and brain [61].

In addition to its manifestations in other organ systems, preeclampsia causes acute neurovascular dysfunction in the peripartum period, which can result in ischemic or hemorrhagic stroke [62–64], cerebral edema [65–67], vasospasm [68], hyperperfusion [69–71], impaired cerebral autoregulation [72], and evidence of neuroinflammation and neuronal injury in the cerebrospinal fluid [7, 73]. A recent study of voxel-based whole brain analyses of oxygen extraction fraction showed higher values in individuals with preeclampsia, compared to healthy pregnant and non-pregnant controls, in specific brain regions including the frontal and parahippocampal gyri, calcarine, cuneus, and precuneus [74], suggesting a compensatory mechanism for low cerebral blood flow in these areas. It is possible that the acute insult of preeclampsia causes irreversible microvascular injury in the brain, resulting in persistent long-term decreases in regional cerebral blood flow, such as those we observed. Of note, our results did not change significantly when we excluded those with gestational hypertension only (without preeclampsia) from the analysis, supporting the concept that gestational hypertension and preeclampsia exist on a continuum and that both conditions are associated with long-term brain microstructural injury.

4.4 |. Strengths and limitations

The major strength of our study is its prospective nature, including detailed pregnancy histories, uniformity and granularity of data collection, uniformity of time from first pregnancy to MRI, and expert-adjudicated pregnancy outcomes. In addition, our study population was ethnically, racially, and socioeconomically diverse. This is especially important since HDP disproportionally affect pregnant individuals of color and those from disadvantaged socioeconomic backgrounds [75, 76]. Furthermore, the use of advanced imaging techniques has allowed the detection of early, subtle markers associated with dementia risk in a largely premenopausal population.

Our study has several limitations. We lack neuroimaging prior to the first pregnancy, making it impossible to know whether MRI findings were present at baseline or developed over time. Our sample size precluded multivariable analysis and adjustment for potential confounders (e.g., smoking, hyperlipidemia), as well as potential mediators of the relationship between HDP and neuroimaging findings (e.g., hypertension). We may have been underpowered to show significant between-group differences, including for subgroups such as participants with and without chronic hypertension at the time of MRI follow-up. Of note, nearly half of the participants in each exposure group met the criteria for chronic hypertension at the time of the MRI visit, a surprising and concerning finding given their mean age of 40 years; thus, between-group differences may have been attenuated by the overall high-risk population. As a preliminary study, our findings should be considered hypothesis-generating. Larger prospective studies are needed to better characterize maternal neurodegenerative changes after HDP.

5 |. CONCLUSION

In a prospective cohort of 81 participants followed for approximately 11 years since their first pregnancies, those who experienced HDP had evidence of regional reductions in cerebral blood flow and white matter microstructural damage compared with those who had no history of adverse pregnancy outcomes. This is the first US prospective cohort study to report evidence of long-term HDP-associated microvascular brain damage using high-resolution MRI. Our results suggest that HDP may be associated with long-term damage to brain structure and cerebrovascular function, potentially partially explaining the association of HDP with risk of cognitive decline and dementia. Our findings suggest that HDP history may represent a sex-specific risk factor for cerebrovascular aging, offering an early window into processes that could precede later cognitive decline. Future longitudinal studies will be critical to assess whether these biomarkers predict long-term clinical outcomes.

Supplementary Material

Supplementary Material

ACKNOWLEDGMENTS

The authors acknowledge the participants of the ongoing nuMoM2b Heart Health Study for their commitment to this research. Funding for this study was received from the National Institutes of Health (NIH) National Heart, Lung, and Blood Institute (U01HL145358) with supplemental support from the NIH National Institute for Neurological Disorders and Stroke (R01NS122815), and the National Institute on Aging (R01AG085475). The original nuMoM2b study was funded by the Eunice Kennedy Shriver, National Institute for Child Health and Development (U10 HD063036; U10 HD063072; U10 HD063047; U10 HD063037; U10 HD063041; U10 HD063020; U10 HD063046; U10 HD063048; U10 HD063053) with additional support provided by Clinical and Translational Science Institutes (UL1TR001108 and UL1TR000153).

Funding information

National Institutes of Health; National Heart, Lung, and Blood Institute, Grant/Award Number: U01HL145358; National Institute on Aging, Grant/Award Number: R01AG085475; National Institute for Neurological Disorders and Stroke, Grant/Award Number: R01NS122815; Eunice Kennedy Shriver; National Institute for Child Health and Development, Grant/Award Numbers: U10 HD063036, U10 HD063072, U10 HD063047, U10 HD063037, U10 HD063041, U10 HD063020, U10 HD063046, U10 HD063048, U10 HD063053; Clinical and Translational Science Institutes, Grant/Award Numbers: UL1TR001108, UL1TR000153)

Footnotes

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

DISCLOSURE

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute, the NIH, or the US Department of Health and Human Services.

SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

DATA AVAILABILITY STATEMENT

Derived data supporting the findings of this study are available from the corresponding author upon reasonable request, pending approval of the nuMoM2b Heart Health Study Steering Committee and execution of an appropriate Data Use Agreement.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material
NIHMS2084495-supplement-Supplementary_Material.docx (39KB, docx)

Data Availability Statement

Derived data supporting the findings of this study are available from the corresponding author upon reasonable request, pending approval of the nuMoM2b Heart Health Study Steering Committee and execution of an appropriate Data Use Agreement.

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