Sex Differences in the Association of Age at Hypertension Diagnosis With Brain Structure
Abstract
BACKGROUND:
Sex differences exist in the likelihood of cognitive decline. The age at hypertension diagnosis is a unique contributor to brain structural changes associated with cerebral small vessel disease. However, whether this relationship differs between sexes remains unclear. Therefore, our objective was to evaluate sex differences in the association between the age at hypertension diagnosis and cerebral small vessel disease–related brain structural changes.
METHODS:
We used data from the UK Biobank to select participants with a known age at hypertension diagnosis and brain magnetic resonance imaging (n=9430) and stratified them by sex and age at hypertension diagnosis. Control participants with magnetic resonance imaging scans but no hypertension were chosen at random matched by using propensity score matching. For morphological brain structural changes, generalized linear models were used while adjusting for other vascular risk factors. For the assessment of white matter microstructure, principal component analysis led to a reduction in the number of fractional anisotropy variables, followed by regression analysis with major principal components as outcomes.
RESULTS:
Males but not females with a younger age at hypertension diagnosis exhibited lower brain gray and white matter volume compared with normotensive controls. The volume of white matter hyperintensities was greater in both males and females with hypertension than normotensive controls, significantly higher in older females with hypertension. Compared with normotensive controls, white matter microstructural integrity was lower in individuals with hypertension, which became more prominent with increasing age.
CONCLUSIONS:
Our study demonstrates that the effect of hypertension on cerebral small vessel disease–related brain structure differs by sex and by age at hypertension diagnosis.
Graphical Abstract
NOVELTY AND RELEVANCE
What Is New?
This is the first study that investigates whether sex differences exist in the relationship between age at hypertension diagnosis and changes in brain structure.
We examined known neuroimaging biomarkers of cerebral small vessel disease, that is, brain atrophy, white matter hyperintensities, and white matter microstructural integrity, in males and females with hypertension to establish small vessel disease pathology as a mechanism leading to hypertension-induced brain structural changes.
What Is Relevant?
The younger age at hypertension diagnosis impacted male brains with lower gray and white matter volumes in hypertensive compared with normotensive males but not females.
The volume of white matter hyperintensities was high in both males and females, which became more prominent with increasing age; however, it was the highest in older females with hypertension.
With increasing age at hypertension diagnosis, both males and females with hypertension had reduced microstructural integrity in white matter tracts.
Clinical/Pathophysiological Implications?
Our findings demonstrate the significance of how age at hypertension diagnosis affects cerebrovascular health differentially in males and females via small vessel disease.
It can help identify sex-specific neuroimaging biomarkers that can inform clinical practice and public health guidelines in the management of hypertension and brain structural changes, which could lead to cognitive decline later in life.
Sex differences are known to exist in the likelihood of cognitive decline brought on by cerebral small vessel disease (CSVD).1 Females have been reported to be more susceptible than males to CSVD and its effect on cognition.1,2 Sex-specific variations in how several vascular risk factors such as hypertension affect CSVD have also been reported. Hypertension, which increases with age, is an established risk factor for cerebrovascular conditions, which are prominent causes of morbidity and mortality.3,4 Hypertension has also been linked to cognitive impairment in later life.5–8
Younger age at onset of hypertension, independent of blood pressure control, is predictive of cognitive decline and increased vascular dementia risk in later life.9 Moreover, high blood pressure in early adulthood and into midlife is associated with late life reductions in brain volume and white matter hyperintensities (WMHs), as measured by magnetic resonance imaging (MRI), both of which are hallmarks of CSVD.9,10 Furthermore, hypertension has also been linked to lower white matter microstructural integrity, another indicator of CSVD.11–13 In vivo microstructural integrity can be assessed using diffusion tensor imaging (DTI). Measures derived from DTI are sensitive to the changes in microstructural integrity that are associated with hypertension and CSVD that could also be associated with cognitive decline.14
While the relationship between age at hypertension diagnosis and late life brain and cognitive health has been investigated,9 it remains unclear whether these relationships are the same in females and males. Indeed, sex differences have an impact on the prevalence and outcomes of hypertension.15 For instance, males are more likely than females to have hypertension before menopause, but after age at menopause, females have a steeper rise in blood pressure and a higher risk of cardiovascular events than males.16 Differences in sex can also have an impact on the mechanisms and pathways that link hypertension to brain damage and cognitive decline.15,16 Understanding sex differences is crucial for developing a more precise and inclusive understanding of how hypertension affects brain health and cognition in adulthood.
Therefore, the current work aims to elucidate the relationship between sex, age at hypertension diagnosis, and structural brain changes on MRI, both microvascular (DTI) and gross morphological (brain volume) measures, using the UK Biobank. We hypothesize that there will be sex differences between younger age at hypertension diagnosis and brain structural changes.
METHODS
Data Availability
The data used in the current study are available from the UK Biobank data resources. Permissions are required to gain access to the UK Biobank data resources, subject to successful registration and application process. Further information can be found on the UK Biobank website (https://www.ukbiobank.ac.uk/).
Study Population
Data sets used in this study can be accessed upon application acceptance at the UK Biobank resource (https://www.ukbiobank.ac.uk/). The UK Biobank is a large population-based prospective cohort of 502 505 participants aged 40 to 69 years at the time of their baseline assessment (2006–2010) collected across 22 assessment centers in the United Kingdom. Follow-up assessment for all participants was coupled with admission data from medical institutions in England, Scotland, and Wales and from the national mortality registry. Detailed descriptions of the UK Biobank study design and participant characteristics are presented elsewhere, and all data can be viewed in a public, open access repository.17 Between 2014 and 2016, 42 812 participants from the original UK Biobank study population underwent brain MRI scanning. For the assessment of the effect of age at hypertension and structural brain lesions, only the individuals who had MRI imaging were entered in the study population.
Outcomes
Brain Volumes
The macroscopic anatomic parameters of interest to the present study were obtained from the T1-weighted imaging and include gray matter volume (identifier label 25010), white matter volume (identifier label 25011), and volume of WMHs (identifier label 25012), which were normalized to participant head size.18
Microstructural Integrity
Fractional anisotropy (FA; identifier label 25010)—the most common metric derived from DTI—was used as an indicator of white matter microstructural integrity.19–21 FA represents the extent to which the diffusion of water is constrained in a specific direction, ranging from 0 (isotropic diffusion) to 1 (anisotropic diffusion). Although multiple factors such as fiber orientation and myelination can affect this metric, lower values of FA are thought to reflect poorer white matter microstructural integrity.22
Exposure Assessment: Sex, Hypertension Diagnosis, and Age at Hypertension Diagnosis
Sex of participants was acquired from a central registry at recruitment but in some cases updated by the participant (self-reported). Diagnosis of hypertension was based on hospital admission whereby hypertension was defined according to codes provided by the International Classification of Diseases (Ninth Revision: 401–405; Tenth Revision: I10–I13, I15, and O10) or self-reported data (non–cancer-related illness) reported by participants to a nurse via free text. All participants were asked to report whether they had ever received a diagnosis of hypertension by a health care professional (field code: 1065) at the recruitment visit. Participants with hypertension at baseline were included if they had a valid date of diagnosis. After that, the age at hypertension diagnosis was calculated by subtracting the date of initial diagnosis from the participant’s birth date and dividing the result by 365.2. Participants were then stratified into 5 age groups according to their age at hypertension diagnosis: <35, 35 to 44, 45 to 54, 55 to 64, and ≥65 years (Figure 1).
Covariates
Given the well-substantiated relationship between certain cardiovascular risk factors and brain structure, the following covariates were used: age, education, lifestyle behaviors such as smoking status (calculated as the proportion of life spent smoking), alcohol consumption (never, current, former), sleep duration (<7, 7–9, and >9 hours), cholesterol (LDL [low-density lipoprotein] and HDL [high-density lipoprotein]), and a medical history of diabetes or depression. Participants completed a detailed touch screen questionnaire in which they were asked to report on a variety of sociodemographic and health-related questions at baseline.
A diabetes or depression history was obtained by verifying hospital inpatient admission records and mortality register data. Additionally, covariates obtained from biological samples were included in the present study: HbA1c (glycated hemoglobin) measured using high-performance liquid chromatography and blood lipids from randomly selected EDTA plasma samples using a high-throughput Nuclear Magnetic Resonance-based metabolic biomarker profiling platform. Finally, waist-to-hip ratio was defined as the ratio of the waist circumference to the hip circumference, which were both measured using the Wessex nonstretchable sprung tape measurer. Since the normotensive controls were selected based on not being hypertensive at baseline, we also added systolic and diastolic blood pressure measurements taken during MRI (2014–2016) to our linear regression model.
Statistical Analysis
All analyses in the present study were performed with SAS 9.4 for Windows (SAS Institute, Inc, Cary, NC). Thresholds for statistical significance were set at <0.05 (2 tailed).
To examine the characteristics of the study population, we conducted within sex univariate analyses comparing hypertensive cases to normotensive controls, respectively, using t tests on the continuous and χ2 tests on categorical variables (Table). Further, using the propensity score method, we accounted for age, sex, education, physical activity, sleep duration, smoking, body mass index, waist-to-hip ratio, and depression and matched normotensive controls with MRI, chosen at random, with hypertensive cases with MRI (Table S1). Univariate analyses are presented by sex and age groups (categorized based on the age at hypertension diagnosis) for propensity score–matched hypertensive cases and normotensive controls using t tests and χ2 tests.
| Covariates | Males | Females | ||
|---|---|---|---|---|
| Hypertensive | Normotensive | Hypertensive | Normotensive | |
| n=6070 | n=14 238 | n=4472 | n=18 162 | |
| Age at recruitment, y | 58.1 (6.9) | 54.7 (7.7) | 57 (7.0) | 53.7 (7.3) |
| Smoking status (yes), n (%) | 3863 (63.8) | 8432 (59.3) | 2422 (54.3) | 9716 (53.6) |
| Alcohol consumption (current), n (%) | 5704 (94.7) | 13 364 (94.4) | 4005 (90.4) | 16 773 (92.9) |
| Higher education, n (%) | 2910 (48.8) | 7653 (54.6) | 2042 (46.5) | 9283 (51.9) |
| BMI, kg/m2 | 28.2 (4.2) | 26.4 (3.6) | 28 (5.3) | 25.6 (4.4) |
| Waist-to-hip ratio | 0.9 (0.1) | 0.9 (0.1) | 0.8 (0.07) | 0.8 (0.1) |
| HbA1c, mmol/L | 6.16 (1.8) | 5.91 (4.8) | 6.1 (1.72) | 5.85 (1.4) |
| LDL-C, mmol/L | 3.3 (0.9) | 3.6 (0.8) | 3.6 (0.8) | 3.6 (0.8) |
| HDL-C, mmol/L | 1.3 (0.3) | 1.3 (0.3) | 1.6 (0.4) | 1.6 (0.4) |
| Diabetes, n (%) | 466 (7.7) | 235 (1.7) | 211 (4.73) | 189 (1.0) |
| Depression, n (%) | 380 (6.3) | 722 (5.1) | 381 (8.52) | 1429 (7.9) |
BMI indicates body mass index; HbA1c, glycated hemoglobin; HDL-C, high-density lipoprotein cholesterol; and LDL-C, low-density lipoprotein cholesterol.
For the morphological structural brain MRI analysis, T1-weighted and microstructural integrity (DTI) data from 2014 to 2016 follow-up were used. t tests were used to compare brain volumes between hypertensive cases and normotensive controls. In addition, both males and females were classified into 5 groups separately, based on the age at hypertension diagnosis, that is, <35, 35 to 44, 45 to 54, 55 to 64, and ≥65 years. To investigate for associations between gray matter volume, white matter volume, and volume of WMH between normotensive controls and hypertensive cases, general linear regression models were used within each group, adjusted for covariates measured at baseline: age, waist-to-hip ratio, LDL cholesterol, HDL cholesterol, HbA1c (glycated hemoglobin), diabetes, sleep duration, education, alcohol intake, smoking status, depression, as well as blood pressure measures (systolic and diastolic blood pressure) taken at the time of MRI (2014). β-Coefficients and the 95% CIs were presented using forest plots. We also included a term sex×hypertension to test for interaction effects.
For analysis of microstructural integrity (DTI), FA values from 27 white matter tracts (Figure 2) were reduced via principal component analysis, a technique that has been previously used in analyzing DTI data.23 Regression analysis was then performed with the major principal components as outcomes.23
RESULTS
Study Population
In the unmatched data set (ie, before propensity score matching), both males and females with hypertension had a higher prevalence of comorbidities as compared with normotensive controls. Males and females with hypertension had lower education, higher body mass index, higher HbA1c, higher rate of diabetes, and higher rate of depression (Table). Characteristics of the propensity score–matched data set are provided in Table S1.
Structural Brain Changes
Overall Study Population
Regardless of age at hypertension diagnosis, compared with normotensive controls, hypertensive cases had lower gray matter volumes and higher volumes of WMHs (Figure 3A). In contrast, an increase in white matter volume in hypertensive cases compared with normotensive controls was identified (Figure 3A). These findings persisted in sex-stratified analyses (Figure 3B). WMHs exhibited the largest brain structural changes in both males and females with hypertension compared with normotensive controls in both univariate and multivariate results (Figure 4A). Our interaction analyses suggest that sex and hypertension together had a greater effect on gray matter volume (Pinteraction=0.03), which was significantly lower in males, as well as an increased volume of WMHs (Pinteraction=0.03) in females.
According to the Age at Hypertension Diagnosis
In the case of gray matter volume, males in younger (<35 years) and middle age (45–64 years) groups had lower volume than normotensive males (Figure 4B). No significant gray matter volume differences were identified in hypertensive compared with normotensive females with age at hypertension diagnosis.
In the case of white matter volume, males with hypertension in the younger age group of hypertension diagnosis (<35 years) had lower volume compared with normotensive males. Similar to gray matter volume, no significant white matter volume differences were identified in hypertensive compared with normotensive females with age at hypertension diagnosis (Figure 4C).
The volume of WMH was greater in both males and females with hypertension, compared with their respective normotensive controls. This difference became statistically significant with increasing age at hypertension diagnosis (Figure 4D).
Changes in Microstructural Integrity With Hypertension
PC Analysis: Factor Selection
The 2 most significant principal components for FA were selected based on having an eigenvalue >1, as well as scree plot inspection (elbow criterion). The eigenvalue matrix and scree plot from the principal component analyses are in Figure S1. The details of white matter tract loadings to FA Principal Component (PC) factors 1 and 2 are found in Figure S2A and S2B.
In the overall study population, hypertensive cases had decreased integrity for FA PC factor 1 (−0.09 [1.1]) as compared with normotensive controls (0.09 [0.94]; P<0.0001), but there was no significant difference for FA PC factor 2 in hypertensive cases (−0.008 [1.2]) as compared with normotensive controls (0.008 [0.8]; P=0.3; Table S2).
Principal Component Regression for Age at Hypertension Diagnosis
For FA outcome PC factor 1, both males and females with hypertension had lower integrity of white matter tracts as compared with normotensive males and females, respectively, which became more prominent with increasing age (Figure 5A). We found that hypertensive compared with normotensive females began showing the decrease in FA white matter microstructural integrity at a younger age at hypertension diagnosis, that is, 35 to 44 years; whereas in males with hypertension, the decrease in FA white matter microstructural integrity was seen starting at 45 to 54 years of age at diagnosis. However, there was no relationship between FA outcome PC factor 2 and males and females with hypertension when compared with normotensive controls (Figure 5B).
Additionally, for white matter microstructure, we did not find statistically significant sex differences in the decrease in integrity of white matter tracts for FA PC factor 1 outcome (Pinteraction=0.11).
DISCUSSION
In this study, we found that hypertension was a significant risk factor for poorer brain health with lower brain volumes and higher volumes of WMHs. However, hypertension diagnosis at a younger age and midlife influenced brain volumes in males, which tended to have reduced gray matter and white matter volumes compared with hypertension diagnosis at older age (ie, >65 years) but not in females. Although both males and females with hypertension had increased volume of WMHs, females with hypertension had the highest volume, which became more prominent with increasing age at hypertension diagnosis. For white matter microstructural integrity, we found lower integrity in both males and females with hypertension as compared with normotensive controls. This association appeared greater in females at a younger age at hypertension diagnosis compared with males.
Midlife hypertension is a significant, modifiable factor affecting brain volume.24 Shang et al have shown an association of hypertension diagnosed in young adulthood or midlife with smaller brain volumes but did not investigate for sex differences. In our sex-stratified analysis, we have found that most findings reported in the study by Shang et al applied to males but not females. WMH and a lower total gray matter volume on brain MRIs are both frequent findings in old age and both lead to cognitive decline.25 Some studies have found that brain atrophy is more common or severe in elderly males than females.26 It has also been reported that hypertension is associated with lower gray matter and white matter volumes, especially in subcortical regions despite blood pressure control.27,28 Our findings further demonstrate that sex differences exist in the association between younger age at hypertension diagnosis and lower brain gray matter volume later in life, which was found only in hypertensive compared with normotensive males but not females.
The prevalence of WMH load is known to increase in older population with females having higher WMH volume than males.29 These differences could be attributed to hormonal changes throughout life.30 The Rhineland Study, for example, found that until the age of 59 years, the total volume of WMH is similar in both sexes and grows linearly with age.30 However, the burden of WMH increases at a faster rate in postmenopausal women, indicating that age has a greater impact on WMH in females. Additionally, WMH burden is higher in women with uncontrolled hypertension than in men with uncontrolled hypertension. Therefore, age may also moderate the associations between hypertension, WMHs, and cognitive impairment.31
Similarly, our results show that females with hypertension have a greater volume of WMH compared with males with hypertension, as well as normotensive controls. Furthermore, as the age at hypertension diagnosis increases, the volume of WMHs is greater in females than in males with hypertension. Some of these sex differences might be attributed to hormonal differences.32 For instance, estrogen protects blood vessels, in part, by lowering inflammation. Estrogen levels in females drop after menopause thereby potentially increasing the risk of CSVD.33 Males, on the contrary, have lower estrogen levels throughout life, which may, in comparison with women, increase their risk of developing CSVD earlier in life.
Hypertension is widely recognized as a risk factor for microstructural white matter damage.34,35 Changes in white matter integrity can occur as a result of high blood pressure. Indeed, DTI has been shown to be more receptive to white matter damage–related CSVD than measures of volume.36 Specifically, FA—a measure of diffusion directionality—is sensitive to detection of lesions in white matter tracts and could be associated better with changes in cognition than morphological MRI measures. Previous research has linked hypertension to lower FA values in various white matter tracts, including the anterior thalamic radiations, the superior longitudinal fasciculus, and the forceps minor.37,38 In this study, we found lower FA values not only in the aforementioned tracts but also in forceps major, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, posterior thalamic radiation, and uncinate fasciculus. These changes in brain structure can impair communication between brain regions and affect cognitive functions like memory, executive function, and processing speed.39–44 Therefore, future studies should focus on examining sex differences in the changes in cognition and cognitive impairment in relation to the age at hypertension diagnosis and brain structural changes including brain volumes, WMHs, and microstructural integrity. Moreover, WMHs have been shown to be related to white matter integrity since they are influenced by the same factors such as hypertension.45–48 It has been previously reported that areas containing WMHs had lower FA than normal appearing white matter.45 Given that this study did not mask out WMHs, or adjust for the overall WMH load, we cannot rule out the possibility that the results are related to small vessel disease.
The main limitation of this study is that the participants were relatively young at the time of the MRI measurements. A median age of 61 years at the time of MRI measurement may not have captured all aspects of the long-term impact of hypertension on brain structure through CSVD pathology. Self-reported hypertension and covariates such as smoking, diabetes, and alcohol consumption may be subject to reporting bias. We were also unable to adjust for hypertension treatment/medication. Moreover, we were unable to account whether duration of hypertension (mean duration of 12 years in our study population) could conflate the associations seen with the age at hypertension diagnosis. Additionally, the data set population is relatively healthy and educated and may not be representative of the general population. Nonetheless, even in this select population, we can see sex differences in the brain structure associated with age at hypertension diagnosis through CSVD-related changes on MRI. Finally, because some of the important covariates were missing at the time of MRI measurements (2014–2016), we could only use risk factors reported at baseline (2006–2010) and not at the time of MRI measurements.
PERSPECTIVES
In summary, this study, using the UK Biobank data, underscores the significance of sex differences in the association of age at hypertension diagnosis with CSVD-related brain structural changes. Whereas younger age at hypertension diagnosis affected male brain volumes, WMHs had higher effect on older females with hypertension. With increasing age at hypertension diagnosis, both males and females with hypertension had reduced microstructural integrity in white matter tracts. Consequently, sex-specific analyses are required to determine the effect of hypertension on CSVD-related brain changes in males and females.
Acknowledgments
The authors would like to thank Dr Zahra Azizi, Jasmine Poole, and Chelsea Pozzebon for their help with the project.
Footnote
Nonstandard Abbreviations and Acronyms
- CSVD
- cerebral small vessel disease
- DTI
- diffusion tensor imaging
- FA
- fractional anisotropy
- MRI
- magnetic resonance imaging
- PC
- principal component
- WMH
- white matter hyperintensity
Supplemental Material
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© 2023 American Heart Association, Inc.
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Received: 6 October 2023
Accepted: 4 December 2023
Published online: 19 December 2023
Published in print: February 2024
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This study was supported by the Heart and Stroke Foundation of Canada (grant G-22-0031987).
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- The brain and hypertension: how the brain regulates and suffers from blood pressure, Hypertension Research, (2024).https://doi.org/10.1038/s41440-024-01990-3
- Sex‐Specific Vulnerabilities to Subclinical Vascular Brain Injury in Early Late‐Life: The Framingham Heart Study, Annals of Neurology, (2024).https://doi.org/10.1002/ana.27135
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