Abstract
BACKGROUND:
Females may have a higher risk of dementia than males. It is not clear if sex differences in Alzheimer’s disease (AD) neuropathology explain the higher risk of dementia in females. Sex differences in AD neuropathology might begin in middle age, decades before the sex differences in dementia are apparent.
OBJECTIVE:
To examine sex differences in in-vivo AD neuropathology in late middle age.
METHODS:
We conducted a cross-sectional comparison of AD biomarkers among 266 Hispanic males and females (mean age: 64.0; 71.8% females) without dementia. Amyloid burden was measured as global standardized uptake value ratio (SUVR) with 18F-Florbetaben Positron Emission Tomography (PET). Neurodegeneration was ascertained as cortical thickness in AD signature areas using brain magnetic resonance imaging. Tau burden was measured as tau SUVR in the middle/inferior temporal gyri and medial temporal cortex with 18F-MK-6240 in 75 of the 266 participants.
RESULTS:
Females had higher amyloid SUVR and tau SUVR in the middle/inferior temporal gyri than males. However, females had higher cortical thickness than males and performed better in a test of verbal memory despite having higher AD neuropathology burden.
CONCLUSION:
Higher amyloid and tau in females compared to males in late middle-age may explain the reported higher dementia risk in elderly females compared to males. Longitudinal follow-up is necessary to examine whether higher amyloid and tau burden in late middle age is followed by increased neurodegeneration and cognitive decline in females as compared with males.
Keywords: sex differences, Hispanics, amyloid, tau, neurodegeneration, cognition
INTRODUCTION
The prevalence of dementia doubled worldwide between 1990 and 2016, and the majority of individual affected were females [1]. One in 10 persons over the age of 65 years in the United States has dementia due to Alzheimer’s disease (AD), and this prevalence is higher for females as compared with males [2]. The causes for sex differences in dementia risk are unclear, and could include differences in brain structure, biochemistry, function, and susceptibility to developing AD in response to genetic and other factors [3]. Examining sex differences in AD requires a lifespan approach because AD neuropathology begins to appear in middle age, decades before dementia manifests [4]. Current theoretical frameworks posit that brain accumulation of amyloid and tau, the neuropathologic hallmarks of AD, precede neurodegeneration by years to decades, and neurodegeneration in turn leads to cognitive impairment [4]. However, there is a paucity of data on in-vivo AD neuropathology in late middle-age. Most studies of in-vivo AD neuropathology have been conducted in clinic referral samples and elderly community-based samples. Moreover, there is paucity of data on in-vivo AD neuropathology in non-White samples [4]. We examined sex differences in-vivo AD neuropathology in a community based-cohort of late middle-aged Hispanics in New York City.
MATERIALS AND METHODS
Study Design and Population:
This was a cross-sectional analysis of 266 middle-aged Hispanics in New York City with measured in-vivo AD neuropathology, recruited between 02/01/2016 and 08/30/2018. This study was based at Columbia University Irving Medical Center (CUIMC). Hispanics are the most common ethnic group in the community surrounding CUIMC [5, 6], and this study was restricted to Hispanics. Inclusion criteria included any sex, aged 55–69 years, willing and able to undergo phlebotomy, clinical and neuropsychological assessments, 3T brain magnetic resonance imaging (MRI), and Positron Emission Tomography (PET) with injection of 18F-Florbetaben. Exclusion criteria included: diagnosis of dementia, cancer other than non-melanoma skin cancer, and MRI contraindications. We screened 538 participants; 94 (17.47%) declined participation, 173 (32.16%) were ineligible, and 5 (40.93%) were eligible but did not complete study procedures (see Supplemental Figure 1). Seventy-five participants in the cohort of 266 participants with MRI and amyloid PET also underwent tau PET between 07/01/2018 and 04/31/2019 using the radioligand 18F-MK-6240. The interval between amyloid PET and MRI was 4.17 ± 8.43 days. The interval between MRI and tau PET was 210 ± 86 days. This study was approved by the Institutional Review Board and the Joint Radiation Safety Commission at CUIMC. All study participants provided written informed consent.
Study measures:
The exposure was sex, ascertained at the time of screening by self-report with the question “Are you female or male?”. Possible answers included: female, male, unknown, declines, not applicable. Thus, we used the terms “female” and “male” to classify sex in this report.
We focused on outcomes following the National Institute on Aging (NIA)/Alzheimer’s Association (AA) 2018 research framework [4], which emphasizes a biological definition of AD focused on amyloid, tau, and neurodegeneration. The main outcomes were brain amyloid burden ascertained as global brain amyloid standardized uptake value ratio (SUVR) measured with 18F-Florbetaben PET, tau burden ascertained as tau SUVR in the middle/inferior temporal gyri and medial temporal cortex measured with 18F-MK-6240 PET, and neurodegeneration, measured as cortical thickness in areas affected by AD[7] obtained from 3T brain MRI. Global amyloid SUVR has a bimodal distribution [8]. Thus, AD research has traditionally focused on amyloid positivity as an outcome using cutoffs that vary by study [9]. Amyloid positivity in our cohort has a prevalence of less than 15% [9], and there is recent recognition that sub-threshold amyloid is clinically significant [10]. Thus, amyloid burden as a continuous variable was our primary outcome. Amyloid levels were examined as a secondary outcome. There are different methods for the determination of amyloid positivity [4]. Thus, we examined two cutoffs for amyloid positivity: one determined by the K-means method [11], and another using a median cutoff, which has been used in other studies to define amyloid positivity [12].”
Tau aggregation is limited to medial temporal cortex in older adults and does not spread into neocortical regions until after AD symptoms become apparent [13]. Thus, we used medial temporal cortex and middle/inferior temporal gyri for the primary analysis of tau imaging. We examined cerebrovascular disease, ascertained as white matter hyperintensity volume (WMH) on MRI, and memory performance using the Bushke Selective Reminding Test [14], as secondary outcomes.
MRI Methods:
Our primary outcome measure of neurodegeneration was cortical thickness obtained by averaging values from AD-related regions as specific patterns of cortical thinning are found in AD [7] derived with FreeSurfer v6.0 (http://surfer.nmr.mgh.harvard.edu/). These regions included entorhinal cortex, parahippocampus, inferior parietal lobule, pars opercularis, pars orbitalis, pars triangularis, inferior temporal pole, supramarginal gyrus, superior parietal lobe, and superior frontal lobe.
Amyloid PET:
The dose of 18F-Florbetaben was 300 MBq (8.1 mCi), maximum 30 mcg mass dose, administered as a single slow intravenous bolus. Images were acquired over 20 minutes starting 90 minutes after injection. Dynamic PET frames (4 scans) were aligned to the first frame using rigid-body registration and a static PET image was obtained by averaging the four registered frames. Information on the amyloid PET scan processing protocol has been previously published [11]. The standardized uptake value (SUV), defined as the decay-corrected brain radioactivity concentration normalized for injected dose and body weight, was calculated in all FreeSurfer regions. The SUV in each region as well as each voxel was also normalized to the SUV in cerebellar gray matter to derive the regional and voxel-wise SUVR. Analyses incorporated voxel-based, individual region of interest (ROI) based (lateral temporal cortex, parietal cortex, cingulate cortex, and frontal cortex), and an overall mean value of amyloid burden, our main outcome. We examined categories of amyloid levels as a secondary outcome using two methods: (1) amyloid positivity using a SUVR threshold of 1.34, which was determined using the K-means clustering method, and (2) amyloid positivity using a median split.
Tau PET:
The 18F-MK-6240 injected activity was 185 MBq (5 mCi), and images were acquired 80–100 minutes post-injection. PET was performed without arterial sampling. Dynamic PET frames (4 scans) were aligned to the first frame using rigid-body registration and a static tau PET image was obtained by averaging the four registered frames. The static tau PET image was then co-registered to the corresponding static amyloid PET image space. The same Freesurfer-derived ROIs from the amyloid PET processing steps above were then applied to the tau PET image. Regional concentration of radioactivity was then extracted from the static tau PET images. 18F-MK-6240 SUVRs were calculated using an eroded cerebellar gray matter reference region, consisting of posterior cerebellum to avoid spill-over of the 18F-MK-6240 signal from tentorium cerebelli and ventral temporal/occipital cortex [15].
Secondary outcomes:
WMH was derived by fitting a Gaussian curve to FLAIR voxel intensity values and labeling voxels that are 2 standard deviations (SD) above the mean value [16, 17]. Total WMH was defined as the sum of the number of voxels that are labeled multiplied by voxel dimensions. We used the ratio of total WMH and TCV for analyses. Cognitive performance in the domain of verbal learning was ascertained using total recall in the Buschke Selective Reminding test (SRT) [14]. The SRT is a standard tool in the assessment of verbal memory and dementia and has been used as a sensitive longitudinal measure of changes in memory function. Several studies attest to its predictive value for dementia [18–20]. Scores reflect words recalled, with higher scores reflecting better performance. We focused on verbal learning because this is the cognitive domain that tends to be affected earliest in AD [21].
Characteristics considered as potential covariates included age, education, Hispanic subgroup, body mass index (BMI), hemoglobin A1c (HbA1c), lipids (high density lipoprotein [HDL] and low-density lipoprotein [LDL]), and mean arterial blood pressure (MAP). Hispanic subgroup was classified following the format of the 2010 Census by country or region of origin (e.g. Mexican, Puerto Rican, Cuban, Dominican) [22]. BMI was estimated as weight in kg divided by height in meters squared. MAP was estimated using the formula (systolic blood pressure + 2*[diastolic blood pressure])/3). APOE-ε4 genotype was available in 249 participants. Participants were classified as APOE-ε4 carriers if they were homozygous or heterozygous for APOE-ε4. HbA1c was measured using a turbidimetric inhibition immunoassay on the automated analyzer Cobas Integra 400 plus (Roche Diagnostics, Indianapolis, IN). Cholesterol, HDL, and triglycerides was measured on an automated immunochemistry analyzer, Integra 400 plus (Roche Diagnostics, Indianapolis, IN) using an enzymatic colorimetric assay with a lower limit of quantitation of 3.09 mg/dL for HDL and 0.1mmol/L for cholesterol and triglycerides. LDL was calculated using the Friedewald formula. APOE-ε4 genotyping was conducted by LGC genomics (Beverly, MA) using single nucleotide polymorphisms rs429358 and rs7412.
Statistical analyses:
Global amyloid SUVR and the ratio of WMH and TCV were not normally distributed. Global amyloid SUVR had a bimodal distribution as expected [8], and no transformation approximated a normal distribution. However, SUVR values under the positivity threshold had a normal distribution. The ratio of WMH and total cranial volume required a logarithmic transformation to approximate a normal distribution. Bivariate comparisons between males and females and between APOE-ε4 carriers and non-carriers were made using analysis of variance for continuous variables, and chi-squared for categorical variables. Comparisons adjusting for covariates were made using analysis of covariance (ANCOVA). Results for the main outcomes are reported as adjusted means comparing males and females. Model 1 was unadjusted, model 2 adjusted for age, and APOE-ε4, and model 3 adjusted for MAP, HDL, and LDL, which were the covariates that differed between males and females. Given that amyloid had a bimodal distribution, we conducted sensitivity analyses comparing sex and APOE-ε4 categories with a non-parametric Mann-Whitney U test, comparing crude and adjusted means with ANCOVA restricting the sample to amyloid negative individuals, comparing amyloid positivity using the SUVR threshold of 1.34, and defining high amyloid with a median split using chi-squared. We examined effect modification by APOE-ε4, the strongest determinant of brain amyloid burden [9], by examining an interaction term of sex and APOE-ε4 in ANCOVA models. We also compared the main outcomes across strata of sex and APOE-ε4. Statistical significance was considered at p<0.05. Analyses were conducted using SAS version 9.4.
RESULTS
Participant characteristics are shown in Table 1. The mean age was 64.00 ± 3.43 years, and 71.80% reported being female. Among 249 participants with APOE-ε4 data, 34.14% were APOE-ε4 carriers. The majority of participants were Caribbean Hispanics of Dominican descent. There were no significant differences between males and females in age, education, APOE genotype, HbA1c, and BMI. Females had higher HDL and LDL and lower MAP compared with males.
Table 1.
Demographic and other relevant characteristics for the entire sample and by sex group.
| Clinical Values | Entire Sample (n = 266) |
Female (n = 191) |
Male (n = 75) |
p Value |
|---|---|---|---|---|
| Age, No. (%), y | 64.00 (3.43) | 63.94 (3.49) | 64.16 (3.28) | 0.63 |
| Ethnicity, No. (%) | ||||
| Dominican | 238 (89.47) | 175 (91.62) | 63 (84.00) | 0.07 |
| Other Caribbean Hispanic | 10 (3.76) | 6 (3.14) | 4 (5.33) | |
| South American | 10 (3.76) | 5 (2.62) | 5 (6.67) | |
| Central American | 4 (1.50) | 3 (1.57) | 1 (1.33) | |
| Unspecified Hispanic | 4 (1.50) | 2 (1.05) | 2 (2.67) | |
| Education, mean (SD), y | 10.43 (3.72) | 10.40 (3.58) | 10.51 (4.10) | 0.83 |
| APOE Genotype, No. (%) | ||||
| APOE-ε4 Carriera | 85 (34.14) | 62 (35.23) | 23 (31.51) | 0.57 |
| ε2ε2 | 1 (0.38) | 0 (0) | 1 (1.33) | |
| ε2ε3 | 26 (9.77) | 18 (9.42) | 8 (10.67) | |
| ε2ε4 | 9 (3.38) | 5 (2.62) | 4 (5.33) | |
| ε3ε3 | 137 (51.50) | 96 (50.26) | 41 (54.67) | |
| ε3ε4 | 69 (25.94) | 52 (27.23) | 17 (22.67) | |
| ε4ε4 | 7 (2.63) | 5 (2.62) | 2 (2.67) | |
| Incomplete genotyping | 17 (6.39) | 15 (7.85) | 2 (2.67) | |
| Hemoglobin A1c, mean (SD), % | 6.20 (1.31) | 6.13 (1.29) | 6.38 (1.36) | 0.15 |
| Body mass index, mean (SD) | 28.77 (4.79) | 29.03 (5.11) | 28.12 (3.80) | 0.16 |
| Low density lipoprotein, mean (SD), mg/dL | 110.01 (35.10) | 112.68 (35.86) | 103.23 (32.33) | 0.04 |
| High density lipoprotein, mean (SD), mg/dL | 54.85 (14.96) | 57.45 (14.62) | 48.28 (13.84) | <0.0001 |
| Mean arterial pressure, mean (SD), mm Hg | 100.66 (11.93) | 99.01 (11.37) | 104.86 (12.37) | 0.0003 |
17 out of 266 patients without APOE-ε4 genotyping. Group sizes are as follows: Females (n = 176), Males (n = 73)
SD = standard deviation
Figure 1 shows the distribution of amyloid for the whole sample and for males and females. As expected [8], amyloid SUVR had a bimodal distribution for the whole sample, and the first peak resembled a normal distribution. The distribution was similar for males and females, but females’s amyloid SUVR distribution was shifted towards higher values (rightward) as compared with males.
Figure 1.
Histograms showing the distribution of global brain amyloid standardized uptake volume ratio (SUVR). The top two histograms show the distribution for the entire sample with a dashed line (top-left) representing a normal density function with the mean and standard deviation of the full-sample amyloid SUVR. The solid line (top-right) represents a non-parametric kernel estimation. The bottom histograms stratify the sample by males (n = 75) and Females (n = 191) with separate normal (bottom-left) and kernel (bottom-right) for each sex.
Table 2 shows the comparison of amyloid, tau, and neurodegeneration measures between males and females. Females had higher global amyloid SUVR compared with males in all models. Sex differences in amyloid burden were also apparent when restricting the analyses to the 248 amyloid negative individuals (mean SUVR 1.14 ± 0.004 in females vs 1.09 ± 0.007 in males; p<0.0001), when comparing amyloid positivity (7.85% vs. 4.00%; p=0.26), and when comparing high amyloid defined by the median (median =1.13; interquartile range: 1.09 – 1.18) split (high amyloid was 59.16% in females vs. 26.7% in males; p<0.0001).
Table 2.
Sex comparison of means obtained from analysis of covariance models for global brain amyloid standardized uptake value ratio (SUVR), tau SUVR in the medial temporal cortex, tau SUVR in the middle/inferior temporal gyri, cortical thickness (in mm) in Alzheimer’s disease signature brain regions, and natural logarithm of the ratio of white matter hyperintensities volume by total cranial volume (%).
| Model 1 | Model 2a | Model 3a | |||||
|---|---|---|---|---|---|---|---|
| Sex | No. | Mean (SD) | p | Mean (SD) | p | Mean (SD) | p |
| Global brain amyloid SUVR | |||||||
| Females | 191 | 1.17 (0.009) | 1.17 (0.009) | 1.17 (0.009) | |||
| Males | 75 | 1.11 (0.01) | 0.00020 | 1.11 (0.01) | <0.0001 | 1.10 (0.01) | 0.00010 |
| Medial temporal cortex Tau SUVR | |||||||
| Females | 50 | 1.02 (0.02) | 1.02 (0.02) | 1.02 (0.02) | |||
| Males | 25 | 0.99 (0.03) | 0.413 | 0.99 (0.03) | 0.404 | 0.99 (0.03) | 0.62 |
| Middle/inferior temporal gyri Tau SUVR | |||||||
| Females | 50 | 1.25 (0.02) | 1.25 (0.02) | 1.25 (0.02) | |||
| Males | 25 | 1.14 (0.03) | 0.0073 | 1.14 (0.03) | 0.0056 | 1.14 (0.04) | 0.015 |
| Cortical thickness in AD signature areas | |||||||
| Females | 191 | 2.70 (0.007) | 2.70 (0.007) | 2.70 (0.007) | |||
| Males | 75 | 2.66 (0.01) | 0.00080 | 2.66 (0.01) | 0.0011 | 2.66 (0.01) | 0.0034 |
| log (ratio of white matter hyperintensities / total cranial volume) | |||||||
| Females | 191 | 0.93 (0.07) | 0.97 (0.08) | 1.00 (0.08) | |||
| Males | 75 | 1.10 (0.12) | 0.23 | 1.11 (0.12) | 0.33 | 1.05 (0.13) | 0.72 |
Model 1 is unadjusted
Model 2 is adjusted for demographics and APOE-ε4 carrier status
Model 3 includes Model 2 + mean arterial pressure, HDL cholesterol, LDL cholesterol
17 patients without APOE-ε4 genotyping. Adjusted group size is n = 249 (all tau SUVR samples had APOE-ε4 genotyping)
SD = standard deviation
Global amyloid SUVR was higher in APOE-ε4 carriers (age and sex adjusted means, 1.21 ± 0.01 vs. 1.13 ± 0.09; p<0.0001). APOE-ε4 differences in amyloid burden were apparent when restricting the analyses to the 248 amyloid negative individuals (unadjusted SUVR 1.14 ± 0.007 in carriers vs. 1.12 ± 0.005 in non-carriers; p=0.004), when comparing amyloid positivity (15.29% positivity in APOE-ε4 carriers vs. 1.83% in non-carriers; p<0.0001), and when comparing high amyloid determined by a median split (61.18% high amyloid in APOE-ε4 carriers vs. 43.29% in non-carriers; p=0.0074).
Tau imaging was available in 75 of the 266 participants with MRI and amyloid PET. Compared with those who did not have tau imaging (Supplemental Table 1), those with tau imaging had similar age, sex distribution, education, APOE-ε4 prevalence, HbA1c, BMI, LDL, and HDL. The only difference between those with and without tau imaging was a modest difference in mean arterial pressure (99.42 ± 11.25 in those without tau PET vs. 103.80 ± 13.08 in those with tau PET, p = 0.0068). The similarities and differences in demographic and clinical variables between female and male for the tau sample of 75 participants were similar to those of the entire sample of 266 participants (supplemental table 2). The sex difference in amyloid SUVR (1.18 ± 0.02 in female vs. 1.13 ± 0.02 in male; p=0.08) and the APOE-ε4 difference (1.21 ± 0.03 for APOE-ε4 carriers vs. 1.15 ± 0.02 for non-carriers; p=0.04) in amyloid SUVR were similar to the complete sample. Females had higher tau SUVR adjusted for age and APOE-ε4 in the middle/inferior temporal gyri (1.25 ± 0.02 vs. 1.14 ± 0.03; p=0.005) as compared with males, while tau SUVR in the medial temporal cortex showed no sex differences (1.02 ± 0.02 vs. 0.99 ± 0.03; p=0.40). There were no significant differences in tau SUVR between APOE-ε4 carriers and non-carriers in the medial temporal cortex (1.02 ± 0.03 vs. 1.01 ± 0.02; p=0.82) and middle/inferior temporal gyri (1.16 ± 0.03 vs. 1.23 vs. 0.02; p=0.084) after adjustment for age and sex.
Females had higher cortical thickness in signature AD areas compared with males in crude and adjusted models (Table 2). Females also had higher mean cortical thickness and larger adjusted hippocampal volumes compared with males in crude and adjusted models. There were no differences between males and females in adjusted WMH (Table 2).
Females showed higher total recall in the SRT compared with males in crude and adjusted models (means adjusted for age, education, and APOE-ε4: 40.14 ± 0.59 words vs. 34.85 ± 0.91 words; p<0.0001).
Although examination of SUVRs does not require adjustment for cranial size, we conducted sensitivity analyses to explore whether cranial size could explain the observed sex differences in amyloid and tau burden (supplemental table 3). The results were similar to those in the main analysis.
DISCUSSION
Females had higher global amyloid burden as compared with males. The differences for amyloid were consistent in sensitivity analyses using amyloid categories, and when restricting the sample to individuals under the threshold of amyloid positivity. There was no statistical evidence of an interaction of sex and APOE-ε4. Females also had higher tau in the middle/inferior temporal gyri as compared with males in a subsample of participants with tau PET imaging. Sex differences in AD amyloid and tau were not accompanied by higher neurodegeneration or lower cognitive performance in females compared with males. It is possible that differences in amyloid and tau were not accompanied by sex differences in neurodegeneration because our sample, aged approximately 64 years on average, is in a lifespan period in which AD neuropathology might be present before neurodegeneration is apparent [4]. Our findings support the hypothesis that females have higher burden of in-vivo AD neuropathology compared with males, evident in the seventh decade of life, which could explain the reported higher risk of dementia in elderly females [1, 2]. Our report focusing on Hispanics in New York City also addresses the need for studies in non-White populations [4]. Our findings may be generalizable to other ethnic groups because APOE-ε4, the most important genetic determinant of amyloid burden [9], was associated with higher amyloid burden as reported in mostly Non-Hispanic White samples [9]. A recent report from a multiethnic elderly cohort in New York City showed differences in the relation of sex and cognitive trajectories by ethnic and racial group [23]. It is possible that these differences are explained by differences in AD neuropathology by sex and ethnic and racial group, but we cannot address this possibility in our study.
Reports of sex differences in AD dementia risk are inconsistent. Over 60% of cases of dementia globally[1] and almost two-thirds of persons diagnosed with AD in the United States are females [2]. The estimated lifetime risk for dementia at age 45 was 20% in females and 10% in males in the Framingham Heart Study [24]. In the Aging, Demographics, and Memory Study (ADAMS) of individuals 71 years and older in the United States, 16% of females had dementia compared with 11% of males [25]. The Rotterdam Study showed similar dementia incidence in females and males until 90 years of age, with a higher incidence in dementia among females thereafter [26]. In the Mayo Clinic Study of Aging the rate of progression from mild cognitive impairment (MCI) to dementia was similar in females and males aged 70–79 years, but higher in females compared with males after 80 years of age [27]. In a study at Kaiser Permanente Northern California, dementia incidence rates were comparable between females and males until age 90 years, and higher thereafter among females for most race-ethnic groups, particularly Whites [28]. The Rochester Epidemiology Project reported no sex differences in dementia incidence [29].
There is some evidence for sex differences in AD neuropathology, primarily in elderly, mostly Non-Hispanic White samples. A study among 193 cognitively normal individuals aged 74 years with amyloid and tau PET from the Harvard Aging Brain study and the Alzheimer’s Disease Neuroimaging Initiative reported that females showed higher tau in the entorhinal cortices as compared with males [30]. A multicohort study of 1,798 individuals aged 70 years with cerebrospinal fluid (CSF) reported that females had a stronger association of APOE-ε4 with CSF tau compared with males among amyloid positive individuals [31]. The same study had autopsy data on 5,109 individuals and no sex differences were observed for the association between APOE-ε4 and AD neuropathology [31]. However, there were no sex differences in amyloid PET positivity in a sample of 483 cognitively normal individuals aged 70–92 years from the Mayo Clinic Study of Aging [32]. Reasons for differences in findings between our study and previous studies may include that our study focused on a narrow age range in late middle age, when in vivo amyloid accumulation first becomes evident [33], before plateauing of amyloid accumulation occurs in older age [34], and differences in amyloid accumulation may not be apparent.
The mechanisms underlying sex differences in AD neuropathology are not clear and need further study [3]. A study of 42 females aged 40 to 60 years reported that perimenopausal and menopausal females showed indicators of an AD endophenotype compared with pre-menopausal females, including hypometabolism on fluorodeoxyglucose PET, increased amyloid burden on PET, and reduced gray and white matter volumes [35], suggesting that endocrine factors related to perimenopause may explain higher AD risk in females. A genome wide association study of CSF Aβ42 and tau in 1527 males and 1509 females aged approximately 73 and 71 years respectively showed sex-specific associations of genetic loci with CSF Aβ42, suggesting that genetic modifiers of AD neuropathology may be sex-specific [36]. Our study cannot address mechanisms directly, but the presence of higher amyloid and tau burden in females compared with males is not due to differences in APOE genotype or a worse cardiovascular risk profile in females. We plan to conduct studies using discovery approaches (genomics, proteomics, and metabolomics) to explore potential mechanisms underlying sex differences in AD neuropathology in our cohort.
The main limitation of our study is the cross-sectional nature. However, our findings of sex differences in amyloid and tau burden without corresponding differences in neurodegeneration and cognition make sense in the context of existing theoretical frameworks that posit that amyloid and tau deposition precede neurodegeneration and cognitive impairment [4], particularly in our relatively young cohort. We found that there were sex differences in tau SUVR in the middle/inferior temporal gyri but not in the medial temporal cortex. A potential explanation for this regional difference may be that tau accumulation in the medial temporal cortex represents age related accumulation, whereas tau accumulation beyond the medial temporal cortex to the middle/inferior temporal gyri occurs with increased amyloid accumulation [15]. Thus, our finding of higher global amyloid SUVR in females as compared with males accompanied by higher tau SUVR in the middle/inferior temporal gyri, but not in the medial temporal cortex, should be expected. The availability of tau PET in only a sub-sample could have led to chance findings. However, variable distribution and the relationship of sex and APOE-ε4 with amyloid SUVR in this sub-sample was similar to the larger sample, suggesting that chance is an unlikely explanation for our tau finding. We cannot rule out that the results of our study are explained by survival bias. Males had a worse cardiovascular risk profile than females, and despite the relatively young age of the cohort, it is possible that higher cardiovascular morbidity and mortality at earlier age among males may impact their participation in our cohort. This may result in bias affecting the results of our study.
The main strength of our study is the availability of state-of-the-art biomarkers of amyloid, tau, and neurodegeneration in a community-based sample of middle-aged Hispanics, in which there is a paucity of information on in-vivo AD neuropathology [4]. In addition, the relatively narrow age range of the sample, and the absence of demographic differences between males and females, make it unlikely that the observed differences between males and females are due to the confounding or biases that could explain sex differences in dementia in epidemiological studies [37]. The only differences in covariates observed between males and females were in lipids and blood pressure, such that females had a more favorable vascular risk profile than males, but adjusting for these differences did not change our results. It is also notable that females showed better cognitive performance than males. Thus, our results are not explained by the inclusion of females who were more cognitively impaired than males.
In conclusion, females in our Hispanic cohort showed higher amyloid burden compared with males in the seventh decade of life. Higher tau was also observed in females compared with males in the middle/inferior temporal gyri in a sub-sample. Further research is needed to replicate our findings, in addition to continued follow-up in order to examine whether differences in amyloid and tau persist and if differences in neurodegeneration and cognitive performance appear. Research is also needed to understand the mechanisms of higher AD neuropathology in females compared with males.
Supplementary Material
ACKNOWLEDGEMENTS:
Support for the reported work was provided by United States National Institutes of Health grants R01AG050440, RF1AG051556, and RF1AG051556-01S2. Partial support was also provided by grants K24AG045334, P30AG059303, ULT1TR001873. P. Palta is supported by grant R00AG052380 from the National Institutes of Health.
Footnotes
CONFLICT OF INTEREST/DISCLOSURES STATEMENT. JA Luchsinger receives a stipend from Wolters Kluwer, N.V. as Editor in Chief of the journal Alzheimer’s Disease and Associated Disorders, and has served as a paid consultant to vTv therapeutics, Inc. and Recruitment Partners. The other authors have no interests to declare.
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