Valuing the importance of sex differences in prodromal Alzheimer's disease based on structural magnetic resonance imaging

Abstract

Background

Alzheimer's disease (AD) can be optimally managed from a healthcare point of view if detected at a prodromal stage. Amnestic mild cognitive impairment (MCI) is known as prodromal AD, has attracted extensive attention and research.

Objective

To identify the differences in cognitive function and structural magnetic resonance imaging (MRI) features between men and women with MCI on the basis of A/T/N classification system (“A” means amyloid-β biomarker, “T” means tau biomarker, and “N” means neurodegeneration biomarker as determined by clinical imaging (e.g., positron emission tomography, magnetic resonance imaging (MRI)) or by the measurement of total tau protein (T-tau) in the cerebrospinal fluid (CSF)) and to further explore the correlation between them.

Methods

406 MCI subjects were selected from the Alzheimer's Disease Neuroimaging Initiative database and divided into male and female MCI groups. Differences in demographic characteristics, biomarkers, cognitive assessment performance, and regions of interest (ROIs) of structural MRI were compared between the two groups. The correlations between brain structural changes quantified by MRI and cognitive abilities were investigated through linear regression models.

Results

Compared with male MCI subjects, females had significantly higher T-tau concentration in CSF. There were significant differences in ROIs between the sex groups. In the male MCI group, the average cortical thicknesses of the right posterior cingulate, right anterior cingulate and right supramarginal gyrus were more closely correlated with cognitive function. In the female MCI group, the volume of the right rostral anterior cingulate, and the surface area and average cortical thickness of the right isthmus of the cingulate gyrus were more closely correlated with cognitive function.

Conclusions

Based on A/T/N classification system, the structural MRI data analysis was closely correlated with the difference of cognitive function from patients with prodromal AD in a sex-dependent manner.

Keywords

Alzheimer's disease A/T/N classification system sex difference structural MRI

Introduction

Alzheimer's disease (AD) is a degenerative disease of the central nervous system (CNS) and is characterized by progressive cognitive dysfunction and behavioral damage. Its main pathological features are amyloid-β (Aβ) plaques, neurofibrillary tangles and neurodegeneration. Mild cognitive impairment (MCI) is an intermediate stage between cognitive normality and AD. MCI is further divided into amnestic MCI (aMCI) and nonamnestic MCI (naMCI).¹ aMCI refers to cognitive impairment affecting the memory domain, whereas naMCI refers to impairment of domains other than the memory domain, such as executive function, visual space, and language. The risk of aMCI developing to AD is approximately 10 times that of normal elderly people. As some aMCI cases can convert to AD in clinical diagnosis, this type of aMCI is also known as prodromal AD.² Therefore, as a pointcut for the prevention and early intervention of AD, prodromal AD has attracted extensive attention and research.

Combining clinical diagnosis with biomarkers and imaging examination, the identification of subjects at a high risk to develop AD at a prodromal stage is improved. For example, the recent studies with the Alzheimer's Disease Neuroimaging Initiative (ADNI) datasets have reported a modified brain function of hippocampus in MCI and AD, as well as the changes of genetic biomarkers.^3–6 Thus, based on A/T/N classification system (“A” means Aβ biomarker, “T” means tau biomarker, and “N” means neurodegeneration biomarker as determined by clinical imaging (e.g., positron emission tomography (PET), magnetic resonance imaging (MRI)) or by the measurement of total tau protein (T-tau) in the cerebrospinal fluid (CSF)), the clinical and structural neuroimaging characteristics of prodromal AD, defined as A + T + MCI, are considered to be predictive for the identification of individuals at risk to develop AD.²

Affected by multiple physiological factors and social conditions, there are apparent sex differences in the occurrence and clinical manifestations of AD.⁷ The identification of differences in cognitive impairment, biomarkers and brain imaging between male and female patients with prodromal AD according to A/T/N classification system will have important implications for the clinical selection of inclusion populations and for the development of treatment plans for different sex groups. It is worth noting that the study of differences in brain structure has always been a hot topic. The differences in brain structure between normal males and females are known, and whether these sex differences will change in different diseases has also received attention. Up to now, many studies have shown that the above differences do indeed change in diseases and are closely related to the occurrence and development of diseases.^8,9 Although many MRI-based studies have explored the differences between male and female brains,¹⁰ its research on prodromal AD according to A/T/N classification system is insufficient, which will be the key problem to be explored in this study.

Materials and methods

Study samples

Data used in the preparation of this article were obtained from the ADNI database (http://adni.loni.usc.edu). The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial MRI, PET, other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of MCI and early AD.

Screening

We downloaded the following information from ADNI in August 2016, including patients’ age, sex, years of education, apolipoprotein E ε4 (APOE ε4) status, CSF biomarkers, standardized uptake value ratio (SUVR) of ¹⁸F-AV-45 PET, structural MRI and cognitive assessment scores. In this study, we used the Logical memory II (Delayed Recall) subscale of the Wechsler Memory Scale (Clinical Dementia Rating (CDR) = 0.5). Based on the basic criteria of maintaining daily living activities and no dementia, we selected 406 aMCI cases with subjective memory impairment and objective memory loss from the ADNI-2 and ADNI-Grand Opportunities (GO) groups. Then, subjects with unknown or uncertain etiologies, caused by aging, microvascular diseases, stress, depression, drugs, and demyelinating diseases, or with incomplete information were excluded from the study. According to A/T/N classification system, SUVR of ¹⁸F-AV-45 PET > 1.1 (¹⁸F-AV-45 refers to the commonly used clinical Aβ tracer Florbetapir. At present, there is no internationally recognized SUVR value for diagnosing MCI and AD patients by ¹⁸F-AV-45 PET. The ¹⁸F-AV-45 PET > 1.1 we used is a continuation of the standard adopted by our research group in our published article (reference)²) was identified as Aβ plaque positive (A+), and phosphorylated tau threonine 181 (P-tau_181p) > 23 pg/mL in CSF was identified as fibrous tau positive (T+), which were both used as screening criteria for prodromal AD.^11–14 Subsequently, the subjects were divided into male and female A + T + MCI groups.

¹⁸F-AV-45 PET

¹⁸F-AV-45 PET positivity/negativity was designated according to the appearance of amyloid neuritic plaques by comparing the radioactivity of the cortical gray matter with the activity of the adjacent white matter.¹⁵ In the ADNI database, we obtained the average SUVRs of ¹⁸F-AV-45 PET (including the frontal lobe, orbitofrontal lobe, parietal lobe, temporal lobe, anterior cingulate cortex and posterior cingulate cortex), which were used to calculate Aβ deposition.^15,16 Details about ADNI image acquisition and processing are available at https://www.adniinfo.org/methods. The cortical Aβ deposition data derived by ¹⁸F-AV-45 PET SUVR originated from the ADNI file “UCBERKELEYAV45_06_15_16.csv”. ¹⁸F-AV-45 PET SUVR > 1.1 was considered Aβ positive.¹²

CSF data

CSF Aβ_1–42, total tau (T-tau) and P-tau_181p had been measured by an Innogenetics (INNO-BIA AlzBio3)-based immunoassay kit on the multiplex xMAPLuminex platform (Luminex). The CSF data used in this study were obtained from the ADNI file “upennbiomk5-8.csv”. Detailed methods of CSF collection, measurement and quality control procedures are described in https://www.adni-info.org. A cutoff value of 23 pg/mL of P-tau_181p was used to select the T + subjects.¹⁴

Neuropsychological evaluations

In this study, all MCI subjects underwent 31 neuropsychological evaluations. The general cognitive level was evaluated by the Clinical Dementia Rating Sum of Boxes (CDR-SB), Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Functional Assessment Questionnaire (FAQ). The Rey Auditory Verbal Learning Test (RAVLT) and ADNI-MEM were used to assess memory function. The ADNI-EF was used to assess executive function. The Boston Naming Test (BNT) and Category Fluency Test (CFT) were used to assess language function. In addition to the above psychological evaluations, we also used Informant-report and Self-report data to evaluate cognitive complaints through the Everyday Cognition (ECog) Questionnaire. Note: The data for neuropsychological evaluations can be obtained for free after applying for corresponding permissions and passing the permission.

MRI

A total of 197 A + T + MCI subjects were scanned with 1.5T MRI using the sagittal MPRAGE sequence under the following parameters: repetition time (TR) = 2400 ms, inversion time (TI) = 1000 ms, flip angle = 8°, field of view (FOV) = 24 cm (matrix in x-, y-, and z-dimensions was 256 × 256 × 170 and voxel size was 1.25 × 1.261 × 2). The MRI data of the 197 subjects were preprocessed by standard procedures, and the whole brain was automatically segmented into 107 ROIs using the FreeSurfer image analysis suite.¹⁷ Structural MRI neuroimaging data were obtained from ADNI documents “UCSFFSL_11_02_15” and “UCSFFSX51_11_02_15_v2”, and the data exploited in the work are based on post-processed image files provided by the ADNI database. In the process of statistical analysis, the data were standardized using the Z-score due to their different dimensions and orders of magnitude.¹⁸ Then, we compared and analyzed the ROIs between the male and female A + T + MCI groups. Finally, according to the existing research results, 67 ROIs with significant differences were selected for analysis between sexes. Based on a corresponding authorization granted by ADNI database to our group, the ROI were placed automatically and allowed to directly obtain the values of surface area, thickness and volume.^19,20 Examples of MRI measurement of volume, thickness and surface area of brain structures can be found in the reference.^21,22

Statistical analysis

SPSS software version 21.0 was used for statistical analysis. Categorical variables were compared using the chi-square test, and quantitative data were compared using the independent-sample t-test for continuous variables. If normality or homogeneity of variance was not satisfied, the Wilcoxon rank-sum test was used. Linear regression models were used to evaluate the beta coefficients that reflect the correlation between ROIs of structural MRI and cognitive ability. A linear regression model (with sex as the independent variable and structural MRI or cognitive assessment as the dependent variable) was established to compare structural MRI or cognitive assessment. p < 0.05 was considered statistically significant.

Results

Comparison of demographic characteristics and biomarkers between male and female MCI subjects

Table 1 summarizes the demographics, APOE ε4 status and biomarker characteristics of the male and female MCI groups. In general, no significant difference was found between the male and female MCI groups in the APOE ε4 status ratio, CSF Aβ_1–42, P-tau_181p, or ¹⁸F-AV-45 PET SUVR. As compared with males, females developed MCI at earlier age (p = 0.005) and presented shorter period of education (p = 0.003) and higher CSF levels of T-tau (p = 0.001).

Table 1.

Comparison of demographic characteristics and biomarkers of the male and female MCI groups.

Project	Male (n = 110)	Female (n = 87)	p
Age (y)	74.03 ± 6.40	71.30 ± 6.97	0.005*
Education (y)	16.65 ± 2.68	15.48 ± 2.78	0.003*
APOE ε4, n (%)			0.830
APOE ε4 (−/−)	34 (30.91)	24 (27.59)
APOE ε4 (+/−)	56 (50.91)	48 (55.17)
APOE ε4 (+/+)	20 (18.18)	15 (17.24)
Aβ_1–42	134.87 ± 27.03	140.42 ± 27.34	0.156
T-tau	104.74 ± 46.31	131.59 ± 60.96	0.001*
P-tau_181p	53.69 ± 21.01	60.24 ± 27.97	0.062
¹⁸F-AV-45 PET SUVR	1.39 ± 0.16	1.40 ± 0.17	0.594

t-test and χ² test were used for statistical analysis. *p < 0.05. APOE ε4: apolipoprotein E ε4; T-tau: total tau; Aβ: amyloid-β; P-tau_181p: threonine 181-phosphorylated tau; ¹⁸F-AV-45 PET SUVR: standardized uptake value ratio of ¹⁸florbetapir PET-AV45.

Comparison of cognitive assessment results between male and female MCI groups

As shown in Table 2, the male MCI group and female MCI group showed significant differences in neuropsychological evaluation scores. On the memory subscale, male MCI subjects performed significantly worse than female MCI subjects in RAVLT-immediate memory, learning, forgetting and ADNI-MEM (RAVLT-immediate: 30.79 ± 8.42 versus 35.80 ± 10.36, p = 0.001; RAVLT-learning: 3.55 ± 2.30 versus 4.52 ± 2.63, p = 0.006; RAVLT-forgetting: 4.79 ± 2.15 versus 5.70 ± 2.42, p = 0.011, ADNI-MEM: −0.02 ± 0.57 versus 0.16 ± 0.67, p = 0.042), indicating that male MCI patients are more susceptible to damage in immediate memory and learning than female MCI patients. On the other hand, female MCI patients have worse permanent memory than males. The scores of Informant-report planning and Self-report language in the female MCI group were significantly lower than those in the male MCI group (EcogPtPlanning: 1.59 ± 0.65 versus 1.42 ± 0.50, p = 0.041; EcogSPLanguage: 1.95 ± 0.78 versus 1.73 ± 0.69, p = 0.029). There were differences in other aspects of Informant-report (everyday memory, language, visuospatial abilities, organization, and divided attention) and Self-report (everyday memory, visuospatial abilities, planning, organization, and divided attention) between the two groups, however, with no statistical significance. In CDR-SB and its subscales (ADAS11, ADAS13), ADNI-EF, MMSE, MoCA, FAQ, BNT, CFT, Clock Test, and Trail Making Test A, B (TMT-A, B), there was no significant difference between the two groups.

Table 2.

Comparison of cognitive assessment scores between male and female MCI groups.

Cognitive assessment	Male (n = 110)	Female (n = 87)	p	Adjusted p
CDR-SB	1.68 ± 0.92	1.73 ± 0.97	0.723	0.697
ADAS11	11.17 ± 4.93	10.34 ± 4.60	0.230	0.446
ADAS13	18.16 ± 6.99	17.06 ± 7.13	0.276	0.479
MMSE	27.41 ± 1.85	27.72 ± 1.90	0.242	0.153
FAQ	4.06 ± 4.41	3.38 ± 4.07	0.269	0.330
MoCA	22.67 ± 2.99	22.51 ± 3.09	0.713	0.635
RAVLT-immediate	30.79 ± 8.42	35.80 ± 10.36	<0.001**	0.001*
RAVLT-learning	3.55 ± 2.30	4.52 ± 2.63	0.006*	0.006*
RAVLT-forgetting	4.79 ± 2.15	5.70 ± 2.42	0.007*	0.011*
RAVLT-perc-forgetting	66.75 ± 29.85	69.30 ± 29.18	0.548	0.597
EcogPtMemory	2.41 ± 0.65	2.37 ± 0.68	0.628	0.434
EcogPtLanguage	1.91 ± 0.69	1.80 ± 0.61	0.216	0.301
EcogPtVisuospatial abilities	1.47 ± 0.59	1.52 ± 0.57	0.592	0.688
EcogPtPlanning	1.59 ± 0.65	1.42 ± 0.50	0.044*	0.041*
EcogPtOrganization	1.65 ± 0.65	1.55 ± 0.57	0.283	0.434
EcogPtDivided attention	1.94 ± 0.69	1.89 ± 0.80	0.672	0.640
EcogPtTotal	1.86 ± 0.56	1.79 ± 0.49	0.355	0.354
EcogSPMemory	2.46 ± 0.81	2.48 ± 0.83	0.884	0.975
EcogSPLanguage	1.95 ± 0.78	1.73 ± 0.69	0.038*	0.029*
EcogSPVisuospatial abilities	1.54 ± 0.65	1.65 ± 0.73	0.252	0.199
EcogSPPlanning	1.75 ± 0.75	1.68 ± 0.76	0.509	0.365
EcogSPOrganization	1.82 ± 0.77	1.77 ± 0.88	0.723	0.673
EcogSPDivided attention	2.09 ± 0.92	2.05 ± 0.86	0.729	0.495
EcogSPTotal	1.96 ± 0.66	1.90 ± 0.69	0.553	0.448
ADNI-MEM	− 0.02 ± 0.57	0.16 ± 0.67	0.038*	0.042*
ADNI-EF	4.30 ± 0.90	4.47 ± 0.85	0.176	0.355
CFT (Animals and Vegetables)	43.26 ± 22.03	39.11 ± 14.02	0.128	0.527
Clock Test	25.99 ± 3.83	25.77 ± 3.67	0.683	0.476
BNT	17.61 ± 5.62	17.15 ± 5.11	0.554	0.647
TMT-A	122.24 ± 71.78	111.33 ± 58.38	0.254	0.961
TMT-B	8.60 ± 3.55	8.51 ± 3.13	0.846	0.960

CDR-SB: Clinical Dementia Rating Sum of Boxes; ADAS: Alzheimer's Disease Assessment Scale; MMSE: Mini-Mental State Examination; FAQ: Functional Assessment Questionnaire; MoCA: Montreal Cognitive Assessment; RAVLT: Rey Auditory Verbal Learning Test; Ecog: Everyday Cognition Questionnaire; ADNI: Alzheimer's Disease Neuroimaging Initiative database; CFT: Category Fluency Test; BNT: Boston Naming Test; TMT” Trail Making Test. A linear regression model and t test were used for statistical analysis. *p < 0.05, **p < 0.001. Adjusted p was obtained by adjusting for age and education level.

Quantitative structural MRI

The 107 ROIs obtained from structural MRI data were statistically analyzed, and 67 of them were found to be significantly different between the male and female MCI groups. The male MCI group had significantly greater surface areas of bilateral anterior cingulate (AC), posterior cingulate (PC), upper AC, entorhinal region (ER), paracentralis, and isthmus of the cingulate gyrus (ICG), and significantly greater volumes of AC, accumbens, PC, choroid plexus (CP), lateral ventricle (LV), ER, paracentralis, caudate nucleus (CN), ICG, inferior lateral ventricle (RLV), and amygdala than the female MCI group. The average cortical thicknesses of bilateral PC, upper AC, and ICG were smaller in the male MCI group than in the female MCI group. The volume of the right hippocampus and thalamus and the surface area and volume of the parahippocampal gyrus (PHG), frontal pole, orbit, supramarginal gyrus (SG), frontal lobe, and frontal orbit in the male MCI group were larger than those in the female MCI group, whereas the average cortical thicknesses of the corresponding compartments were smaller than those in the female MCI group. The surface area and volume of the left superior temporal lobe (STL), medial temporal lobe (MTL), and precentral gyrus (PCG) were also larger in the male MCI group than in the female MCI group, and the average cortical thicknesses of the corresponding compartments were also smaller than those in the female MCI group. Table 3 lists the details of the ROIs of more than two groups.

Table 3.

Comparison of structural MRI of males and females MCI patients.

Regions of interest (ROIs)	Male (n = 110)	Female (n = 87)	p	Adjusted p
Right RAC SA	670.81 ± 133.79	602.25 ± 126.15	<0.001**	<0.001**
Left RAC SA	868.28 ± 160.49	743.15 ± 127.91	<0.001**	<0.001**
Right RAC Vol	2131.25 ± 389.81	1912.3 ± 379.69	<0.001**	<0.001**
Left RAC Vol	2735.47 ± 454.23	2423.57 ± 385.19	<0.001**	<0.001**
Right accumbens Vol	503.86 ± 97.03	460.49 ± 96.29	0.002*	<0.001**
Left accumbens Vol	468.38 ± 93.63	431.46 ± 85.43	0.005*	0.001*
Right PC SA	1158.92 ± 167.79	1019.01 ± 155.91	<0.001**	<0.001**
Left PC SA	1150.4 ± 164.79	1017.07 ± 127.08	<0.001**	<0.001**
Right PC Th	2.41 ± 0.17	2.46 ± 0.17	0.048*	0.046*
Left PC Th	2.46 ± 0.17	2.53 ± 0.17	0.006*	0.011*
Right PC Vol	3031.64 ± 460.63	2723.02 ± 421.82	<0.001**	<0.001**
Left PC Vol	3062.33 ± 479.73	2764.51 ± 386.62	<0.001**	<0.001**
Upper right AC SA	765.94 ± 146.01	704.44 ± 144.12	0.004*	0.002*
Upper left AC SA	667.05 ± 122.96	569.28 ± 84.89	<0.001**	<0.001**
Upper right AC Th	2.50 ± 0.30	2.65 ± 0.28	<0.001**	<0.001**
Upper left AC Th	2.66 ± 0.31	2.81 ± 0.34	0.002*	0.002*
Right CP Vol	2568.90 ± 511.12	2039.45 ± 437.94	<0.001**	<0.001**
Left CP Vol	2111.6 ± 348.13	1686.43 ± 311.50	<0.001**	<0.001**
Right ventricle Vol	20,856.63 ± 10,078.55	13,466.31 ± 6748.46	<0.001**	<0.001**
Left ventricle Vol	23,567.24 ± 11,693.37	14,497.38 ± 6885.2	<0.001**	<0.001**
Right ER SA	374.34 ± 85.73	328.10 ± 61.09	<0.001**	<0.001**
Left ER SA	428.6 ± 78.04	378.33 ± 63.45	<0.001**	<0.001**
Right ER Vol	1775.98 ± 405.42	1518.97 ± 362.29	<0.001**	<0.001**
Left ER Vol	1891.69 ± 444.12	1686.76 ± 351.06	<0.001**	<0.001**
Right paracentralis SA	1515.56 ± 185.28	1364.68 ± 178.99	<0.001**	<0.001**
Left paracentralis SA	1346.31 ± 222.36	1201.98 ± 133.16	<0.001**	<0.001**
Right paracentralis Vol	3565.22 ± 683.87	3375.86 ± 531.93	0.035*	<0.001**
Left paracentralis Vol	3294.96 ± 562.12	2983.54 ± 397.6	<0.001**	<0.001**
Right CN Vol	3875.19 ± 726.40	3398.11 ± 471.12	<0.001**	<0.001**
Left CN Vol	3693.43 ± 689.3	3285.49 ± 422.66	<0.001**	<0.001**
Right ICG SA	966.92 ± 157.08	834.51 ± 124.67	<0.001**	<0.001**
Left ICG SA	1058.72 ± 158.96	883.15 ± 114.24	<0.001**	<0.001**
Right ICG Th	2.35 ± 0.22	2.42 ± 0.24	0.046*	0.039*
Left ICG Th	2.36 ± 0.21	2.44 ± 0.21	0.010*	0.007*
Right ICG Vol	2432.08 ± 387.60	2155.28 ± 318.49	<0.001**	<0.001**
Left ICG Vol	2661.95 ± 431.73	2274.31 ± 298.53	<0.001**	<0.001**
Right ILV Vol	1036.34 ± 605.25	639.9 ± 555.52	<0.001**	<0.001**
Left ILV Vol	1278.37 ± 793.81	699.84 ± 517.5	<0.001**	<0.001**
Right amygdala Vol	1451.53 ± 229.95	1254.70 ± 246.67	<0.001**	<0.001**
Left amygdala Vol	1349.75 ± 249.06	1223.43 ± 241.21	<0.001**	<0.001**
Right hippocampus Vol	3510.06 ± 538.66	3300.61 ± 585.24	0.010*	<0.001**
Left hippocampus Vol	3386.35 ± 554.59	3275.90 ± 564.75	0.172	0.051
Right PHG SA	674.14 ± 105.93	584.26 ± 78.80	<0.001**	<0.001**
Right PHG Th	2.59 ± 0.29	2.68 ± 0.31	0.040*	0.032*
Right PHG Vol	2017.29 ± 333.89	1806.93 ± 277.25	<0.001**	<0.001**
Right thalamus Vol	6348.68 ± 574.71	5850.08 ± 616.54	<0.001**	<0.001**
Right frontal pole SA	282.69 ± 44.94	251.15 ± 41.92	<0.001**	<0.001**
Right frontal pole Th	2.51 ± 0.25	2.61 ± 0.27	0.006*	0.015*
Right frontal pole Vol	968.07 ± 196.74	897.53 ± 162.81	0.008*	0.021*
Right orbit SA	767.54 ± 87.75	671.64 ± 81.32	<0.001**	<0.001**
Right orbit Th	2.47 ± 0.22	2.58 ± 0.20	<0.001**	0.010*
Right orbit Vol	2366.44 ± 323.35	2182.53 ± 323.35	<0.001**	<0.001**
Right SG SA	3699.88 ± 461.66	3251.1 ± 375.42	<0.001**	<0.001**
Right SG Th	2.36 ± 0.15	2.41 ± 0.15	0.026*	0.017*
Right SG Vol	9661.74 ± 1443.39	8619.48 ± 1139.50	<0.001**	<0.001**
Right MFL SA	5973.34 ± 713.9	5130.64 ± 464.87	<0.001**	<0.001**
Right MFL Th	2.15 ± 0.13	2.19 ± 0.13	0.019*	0.023*
Right MFL Vol	14,844.49 ± 1884.51	13,057.18 ± 1303.5	<0.001**	<0.001**
Right MFL SA	1846.98 ± 193.86	1661.34 ± 198.20	<0.001**	<0.001**
Right middle orbital front Vol	4836.24 ± 587.12	4351.17 ± 497.13	<0.001**	<0.001**
Left STL SA	3773.34 ± 412.21	3377.00 ± 322.37	<0.001**	<0.001**
Left STL SA	10,703.21 ± 1379.89	10,049.40 ± 1263.98	0.001*	<0.001**
Left STL Th	2.49 ± 0.21	2.59 ± 0.19	0.001*	0.013*
Left MTL SA	3014.91 ± 370.8	2628.78 ± 321.78	<0.001**	<0.001**
Left MTL Vol	9813.59 ± 1458.68	8670.38 ± 1237.48	<0.001**	<0.001**
Left PCG SA	5042.69 ± 534.99	4411.41 ± 370.18	<0.001**	<0.001**
Left PCG Th	2.35 ± 0.19	2.42 ± 0.16	0.004*	0.032*
Left PCG Vol	12,818.06 ± 1610.56	11,630.06 ± 1296.53	<0.001**	<0.001**

SA: surface area; Vol: volume; Th: average cortical thickness; RAC: rostral anterior cingulate; PC: posterior cingulate; AC: anterior cingulate; CP: choroid plexus; ER: entorhinal region; CN: caudate nucleus; ICG: isthmus of the cingulate gyrus; ILV: inferior lateral ventricle; PHG: parahippocampal gyrus; SG: supramarginal gyrus; MFL: medial frontal lobe; STL: superior temporal lobe; MTL: middle temporal lobe; PCG: precentral gyrus. A linear regression model and t-test were used for statistical analysis. *p < 0.05; **p < 0.001. Adjusted p was obtained by adjusting for age and education level.

Correlation between ROIs and cognitive functions

Table 4 shows the correlation between the ROIs of all subjects in the male MCI group and their cognitive functions, of which 13 ROIs were significantly correlated with 6 cognitive assessments. The results showed that the average cortical thickness of the right PC and the upper right AC, the surface area and volume of the left ER and right PHG, and the surface area, volume and average cortical thickness of the right SG were closely related to RAVLT-immediate. The volume of the right RAC, the surface area and volume of the left ER, and the surface area, volume and average cortical thickness of the right SG were closely related to ADNI-MEM. These changes had a significant impact on memory assessment performance and were the main cause of memory impairment in male MCI patients. Second, there were also close correlations between the volume of the left ER and EcogPtPlanning and between the surface area of the upper left AC, the volume of the left ventricle and left paracentralis and EcogSPLanguage, which also had certain impacts on the cognitive function of male MCI patients.

Table 4.

Correlation between ROIs and cognitive function in male MCI group.

ROIs	Coefficient /p	RAVLT_immediate	RAVLT_learning	RAVLT_forgetting	EcogPtPlan	EcogSPLang	ADNI_MEM
Right RAC Vol	β	0.442	0.557	0.171	0.228	−0.132	0.550
Right RAC Vol	p	0.141	0.110	0.637	0.526	0.644	0.049*
Right PC Th	β	−0.748	−0.163	0.356	−0.392	0.026	−0.568
Right PC Th	p	0.037*	0.688	0.404	0.356	0.938	0.083
Upper left AC SA	β	0.086	0.030	0.148	−0.190	−0.607	−0.001
Upper left AC SA	p	0.726	0.916	0.620	0.523	0.014*	0.997
Upper right AC Th	β	0.418	0.265	0.108	0.264	−0.063	0.337
Upper right AC Th	p	0.036*	0.243	0.646	0.263	0.737	0.065
Left ventricle Vol	β	−0.478	0.321	0.022	−0.641	−0.959	−0.105
Left ventricle Vol	p	0.253	0.506	0.966	0.206	0.020*	0.785
Left ER SA	β	−0.536	−0.349	−0.003	−0.144	0.052	−0.633
Left ER SA	p	0.021*	0.185	0.990	0.597	0.809	0.004*
Left ER Vol	β	0.582	0.222	−0.204	0.721	0.143	0.587
Left ER Vol	p	0.046*	0.502	0.556	0.041*	0.603	0.030*
Left paracentralis Vol	β	0.056	−0.166	0.414	0.100	1.155	−0.118
Left paracentralis Vol	p	0.887	0.718	0.395	0.835	0.004*	0.748
Right PHG SA	β	1.252	−0.066	0.524	0.221	−0.090	0.744
Right PHG SA	p	0.031*	0.920	0.448	0.747	0.868	0.158
Right PHG Vol	β	−1.673	0.004	−0.265	−0.533	0.195	−0.980
Right PHG Vol	p	0.014*	0.995	0.739	0.501	0.757	0.109
Right SG SA	β	2.052	1.157	−0.028	1.121	−0.774	1.950
Right SG SA	p	0.010*	0.196	0.976	0.228	0.296	0.008*
Right SG Th	β	1.087	0.724	−0.034	0.666	−0.493	1.164
Right SG Th	p	0.023*	0.183	0.952	0.238	0.273	0.009*
Right SG Vol	β	−2.296	−1.336	0.362	−1.365	0.732	−2.255
Right SG Vol	p	0.011*	0.191	0.733	0.200	0.386	0.007*

SA: surface area; Vol: volume; Th: average cortical thickness. RAC: rostral anterior cingulate; PC: posterior cingulate; AC: anterior cingulate; ER: entorhinal region; PHG: parahippocampal gyrus; SG: supramarginal gyrus. A linear regression model was used for statistical analysis. *p < 0.05. β: regression coefficient. The correlation plots with p < 0.05 in the table can be found in the Supplemental Material.

In the female MCI group (Table 5), we found that the volume of the right RAC, right/left CN and right/left ICG, the surface area of the right ER, right/left paracentralis, right/left ICG and left MTL, and the average cortical thickness of the right/left ICG and right frontal pole were closely correlated with memory function. The surface area of left RAC, left ICG and left PCG, the volume of left ICG and left PCG, and the average cortical thickness of left PCG were closely correlated with Self-report language.

Table 5.

Correlation between ROIs and cognitive function in female MCI group.

ROIs	Coefficient/p	RAVLT_immediate	RAVLT_learning	RAVLT_forgetting	EcogPtPlan	EcogSPLang	ADNI_MEM
Left RAC SA	β	0.105	−0.174	0.224	0.270	1.062	0.063
Left RAC SA	p	0.815	0.722	0.665	0.629	0.038*	0.882
Right RAC Vol	β	−1.379	−1.134	0.048	−0.352	−0.246	−1.115
Right RAC Vol	p	0.011*	0.047*	0.934	0.570	0.644	0.025*
Left PC Vol	β	1.341	0.105	−0.624	−0.213	0.419	1.929
Left PC Vol	p	0.172	0.92	0.574	0.858	0.686	0.043*
Right ER SA	β	−0.546	−0.344	−0.061	0.010	−0.16	−0.328
Right ER SA	p	0.025*	0.176	0.816	0.972	0.528	0.136
Right paracentralis SA	β	−1.773	−1.804	−1.423	−0.167	0.272	−0.963
Right paracentralis SA	p	0.016*	0.024*	0.083	0.844	0.711	0.146
Left paracentralis SA	β	0.978	0.472	0.335	−0.057	−0.073	0.295
Left paracentralis SA	p	0.030*	0.313	0.494	0.913	0.875	0.462
Right CN Vol	β	−0.996	−0.738	0.157	−0.320	0.217	−1.05
Right CN Vol	p	0.017*	0.093	0.726	0.509	0.605	0.009*
Left CN Vol	β	0.974	0.720	−0.067	0.315	−0.359	1.191
Left CN Vol	p	0.041*	0.154	0.898	0.576	0.462	0.010*
Right ICG SA	β	3.565	2.677	2.692	0.891	1.258	2.473
Right ICG SA	p	0.003*	0.029*	0.036*	0.498	0.272	0.020*
Left ICG SA	β	−2.758	−1.893	−1.418	0.025	−2.32	−1.728
Left ICG SA	p	0.007*	0.074	0.195	0.982	0.030*	0.059
Right ICG Th	β	2.188	2.06	2.155	0.532	1.263	1.453
Right ICG Th	p	0.005*	0.014*	0.015*	0.546	0.109	0.039*
Left ICG Th	β	−1.741	−1.424	−1.253	−0.062	−1.237	−1.176
Left ICG Th	p	0.010*	0.045*	0.091	0.936	0.075	0.054
Right ICG Vol	β	−3.339	−2.41	−2.518	−0.935	−1.408	−2.167
Right ICG Vol	p	0.004*	0.043*	0.045*	0.469	0.212	0.035*
Left ICG Vol	β	2.319	1.537	1.49	−0.24	2.407	1.306
Left ICG Vol	p	0.013*	0.115	0.146	0.823	0.017*	0.120
Right frontal pole Th	β	−0.926	−0.514	−0.859	0.408	0.39	−0.618
Right frontal pole Th	p	0.023*	0.225	0.062	0.394	0.359	0.096
Left MTL SA	β	−1.073	−0.493	−0.194	−0.612	0.108	−0.54
Left MTL SA	p	0.037*	0.359	0.730	0.319	0.837	0.247
Left PCG SA	β	1.066	−0.592	−2.699	−2.061	−3.159	1.814
Left PCG SA	p	0.351	0.633	0.050	0.155	0.017*	0.100
Left PCG Th	β	0.397	−0.824	−2.487	−1.981	−2.975	1.348
Left PCG Th	p	0.706	0.477	0.052	0.142	0.015*	0.184
Left PCG Vol	β	−0.963	1.011	3.303	2.521	3.717	−2.014
Left PCG Vol	p	0.514	0.531	0.063	0.179	0.028*	0.157

SA: surface area; Vol: volume; Th: average cortical thickness; RAC: rostral anterior cingulate; PC: posterior cingulate; ER: entorhinal region; CN: caudate nucleus; ICG: isthmus of the cingulate gyrus; MTL: middle temporal lobe; PCG: precentral gyrus. A linear regression model was used for statistical analysis. *p < 0.05. β: regression coefficient.

The above results showed that there were both differences and similarities between the male and female MCI groups in the relationship between ROIs and cognitive functions. In order to more intuitively highlight the meaningful results in Tables 4 and 5, according to reference we drew the correlation plots (Supplemental Figures 1 and 2) between variables that presented a significant beta coefficient with a p-value of at least p < 0.05.²³

Discussion

Current research progress on AD and MCI

AD is the most common cause of dementia, accounting for 60%-70% of all cases.^24–26 MCI is the transition stage between normal cognitive function and dementia (especially dementia in AD) and generally refers to cognitive impairment that is worse than normal age-related cognitive decline.^27–29 Compared with people with normal cognition, MCI patients suffer a higher risk of dementia. The prevalence of MCI in people older than 65 years varies from 10% to 20%, compared with 1–2% in healthy controls, depending on the population studied and the diagnostic criteria used.³⁰ The hallmark neuropathological features of AD and MCI are Aβ deposition and intracellular tau neuronal tangles. A study found that MCI patients with a positive Aβ scan had a greater risk of disease progression to AD than Aβ-negative patients.³¹ There are both similarities and unique characteristics in the pathogenesis and diagnosis between MCI and AD. Old age is the strongest predictive factor of AD, but sex also has a significant influence on the prevalence, clinical manifestations, disease course and prognosis.³² Framingham et al. followed 2611 patients for 20 years and found that in males >65 years, in their remaining lifetime, the risk of AD was 6.3%, and the risk of dementia was 10.9%, whereas the corresponding risk in women >65 years was 12% and 19%, which were approximately twice the risks in men in the same age group.²⁶ Through the application of ¹⁸F fluorodeoxyglucose PET and resting-state functional MRI, significant differences were found in brain metabolism and brain connectivity between male and female AD patients. In females, cerebral blood flow and connectivity were higher in the parietal commissural cortex but lower in the visual and motor cortex, which provided strong evidence for brain function and behavior differences between sexes.³³ A series of studies have shown that sex is an important factor in the phenotypic variation of AD, and there is huge room for research. Ignoring sex differences will hinder the understanding and treatment of AD. In general, older women have a higher incidence of MCI.³⁴ Since sex is an important factor in the phenotypic variation of AD, can it also play a regulatory role in MCI? The results of this study confirmed that sex is also an important influencing factor of MCI. This finding will inevitably lead to changes in the diagnostic criteria and therapeutic regimens of MCI, which will be the focus of our next stage of research in the future.

Significant differences between sexes in biomarkers, cognitive functions, and brain imaging of prodromal AD

In this study, we comprehensively evaluated the clinical cognitive performance and brain structural MRI scans between male and female MCI groups of patients based on the AT (N) system, all of whom had Aβ deposition and positive biomarkers of fibrous tau. Previous studies have defined prodromal AD as a typical phenotype of multidomain amnestic dementia, and the diagnosis of MCI was mainly based on clinical classification and manifestations but ignored the pathological changes of AD at autopsy.³⁵ Nelson et al. found that 10–30% of individuals clinically diagnosed with dementia in AD did not show AD neuropathological changes at autopsy.³⁶ Another study has also shown that amnestic multidomain dementia is neither sensitive nor specific to AD neuropathological changes, and cognitive symptoms are not ideal in defining AD.³⁷ The application of structural MRI in the analysis and evaluation of AD is of great research and clinical value. Based on the above considerations, this study conducted a comprehensive analysis combining patients’ pathological changes, clinical cognitive assessment performance and imaging data, which was not only more consistent with the pathological changes of AD but also more accurately grasped the clinical characteristics of MCI patients.

Based on the NIA-AA research framework, in AD, the A and T values represent specific neuropathological changes, whereas neurodegeneration/nerve injury biomarkers (N) and cognitive symptoms are used to determine the severity of AD.³⁸ In this study, we found that the female MCI group had significantly higher levels of T-tau (a biomarker of neuronal injury) than the male MCI group, which was consistent with the difference in pathological changes between men and women among AD patients.^39,40 In addition, by analyzing the clinical cognitive assessment results, we confirmed that female MCI patients performed worse in permanent memory ability but better in immediate memory and learning ability than male MCI patients, which was consistent with the idea that females are protected relative to males during the prodromal phase.^41,42 In this study, the male MCI group had significantly higher age and education level than the female MCI group. Compared with females of the same severity of disease, the average age of male MCI patients with higher education levels was also higher, indirectly confirming the previous finding that females with less education are more likely to suffer from MCI.^43,44

For many years, research has been focusing on single structures of the medial temporal lobe (such as the hippocampus and entorhinal cortex) for the early diagnosis of AD. However, the measurement of cortical thickness (such as medial temporal lobe) by MRI alone is still not accurate enough and cannot be used as an absolute standard for the clinical diagnosis of AD in the MCI stage. In this study, we utilized the FreeSurfer image analysis suite to perform longitudinal and cross-sectional processing (each scan was segmented according to the defined Atlas of FreeSurfer), resulting in regional volume, cortical thickness, cortical volume, and surface area, which were used to study the different change patterns of quantitative structural MRI. Through the analysis of structural MRI images, we found significant differences in multiple ROIs between the male and female MCI groups. The male group had a higher surface area and volume of ROIs, but the female group had a higher average cortical thickness. The above results suggested that the quantitative structural MRI change degree of some brain regions in the female MCI group was greater than that in the male MCI group, which is consistent with the difference in clinical symptoms between male and female AD patients.^39,40 Especially in the right hippocampus, the volume and surface area of the male MCI group were significantly larger than those of the female MCI group; however, there was no significant difference in the left hippocampus. Differences in quantitative structural MRI of the right hippocampus may lead to differences in acquisition of novel information abilities. Based on these observations, we speculate that cognitive disabilities in female MCI group may be related to these structural and functional characteristics of the right hippocampus.

By studying the correlation between structural MRI and cognitive functions, we found that in the male MCI group, the regions significantly associated with cognitive functions were the right cingulate gyrus, right PHG, right SG, and left ER, whereas in the female MCI group, the regions were the bilateral cingulate gyrus, right ER, bilateral paracentralis, bilateral CN, left PCG, and left MTL. Anomalous change of these structures is considered a typical finding in AD.⁴⁵ Grothe et al. demonstrated that episodic memory decline in MCI patients was associated with the structural changes in the hippocampus and basal forebrain after degeneration in Aβ (+) patients.^46,47

In addition, we found that in males with MCI, the right cingulate gyrus, left ER, right PHG, and right SG mainly affected immediate memory and instant memory abilities, and the right cingulate gyrus, left ER, and right SG mainly affected memory function. In female MCI patients, the right cingulate gyrus, right ER, bilateral paracentralis, bilateral CN volume, right frontal pole, left MTL, and left PCG were closely related to immediate memory and instant memory. The left RAC surface area, left ICG surface area, left ICG volume, left PCG surface area, average left PCG cortical thickness, and left PCG volume were closely correlated with Self-reported language. These results demonstrated the different clinical characteristics between sexes, and the relationship between ROIs and cognitive function was dependent on sex. This indicates that in the diagnosis and treatment of MCI, the diagnostic criteria and therapeutic regimens need to be tailored according to the sex of patients. Although our research has some limitations, it at least reflects the suggestive and indicative role of structural MRI in guiding the diagnosis of male and female MCI and AD, especially in primary medical institutions where PET and CSF tau testing cannot be performed.

Clinical significance of sex differences in prodromal AD

Based on A/T/N classification system, male and female MCI patients showed significant differences in biomarkers, cognitive domains, and structural MRI. Sex differences are important regulators of prodromal AD. ROIs from structural MRI analysis were correlated with cognitive function, and the closeness of correlation was different between sexes, which has important reference value for the development of different diagnostic criteria and therapy regimens for different sex groups. This study was based on A/T/N classification system, which is a novel comprehensive evaluation of male and female MCI populations based on the analysis of clinical cognitive status and structural MRI findings. These results will support the correct understanding of the nature of prodromal AD, emphasize the sex differences in future AD research, and provide more precise diagnostic criteria and treatment options.

Deficiencies in this research

There are some potential limitations in this study. First, although we included all A + T + MCI subjects in ADNI-2 in this study and performed PET scan and CSF P-tau_181p analysis, our sample size was still relatively small, which might lead to bias. Second, in the ADNI-2 study, subjects were recruited from memory clinics or through advertisements, and the inclusion criteria of MCI were highly selective, which might produce unpredictable selection bias; therefore, the samples might not represent the general population. Finally, because most of the subjects in the ADNI database came from North American countries and regions, the conclusions drawn need further validation in the other ethnic population, such as yellow race people.

Perspectives and significance

In summary, sex is an important influencing factor of prodromal AD based on A/T/N classification system. ROIs from structural MRI analysis were closely correlated with cognitive function, and the closeness varied between different sexes, which has important reference value for the development of different diagnostic criteria and therapy regimens for different sex groups.

Supplemental Material

sj-docx-1-alz-10.1177_13872877241289790 - Supplemental material for Valuing the importance of sex differences in prodromal Alzheimer's disease based on structural magnetic resonance imaging

Supplemental material, sj-docx-1-alz-10.1177_13872877241289790 for Valuing the importance of sex differences in prodromal Alzheimer's disease based on structural magnetic resonance imaging by Chao Ren, Wen-Qian Wang, Hui-Hua Li, Bing-Yu Li, Ke-Ning Shi, Li-Na Yang, Li-Na Guan, Min Kong, Mao-Wen Ba and in Journal of Alzheimer's Disease

Footnotes

Acknowledgments

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; BristolMyers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

ORCID iD

Mao-Wen Ba

Author contributions

Chao Ren (Data curation; Formal analysis; Funding acquisition; Writing—original draft; Writing—review & editing); Wenqian Wang (Formal analysis; Visualization; Writing—review & editing); Huihua Li (Formal analysis; Visualization; Writing—review & editing); Bingyu Li (Formal analysis; Writing—review & editing); Kening Shi (Formal analysis; Writing—review & editing); Lina Yang (Validation; Writing—review & editing); Lina Guan (Validation; Writing—review & editing); Min Kong (Conceptualization; Methodology; Validation; Writing—review & editing); Maowen Ba (Conceptualization; Supervision; Project administration; Funding acquisition; Writing—review & editing).

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded by the Taishan Scholar Project (No. tsqn202312392), the Key Research and Development Program of Shandong Province (Competitive Innovation Platform Project: No. 2024CXPT091), Shandong Provincial key research and development project (No.2018GSF118235) and Chinese National Natural Science Foundation (No.81571234).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The data that support the findings of this study are available from the ADNI database (http://adni.loni.usc.edu).

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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Valuing the importance of sex differences in prodromal Alzheimer's disease based on structural magnetic resonance imaging

Abstract

Background

Objective

Methods

Results

Conclusions

Keywords

Introduction

Materials and methods

Study samples

Screening

18F-AV-45 PET

CSF data

Neuropsychological evaluations

MRI

Statistical analysis

Results

Comparison of demographic characteristics and biomarkers between male and female MCI subjects

Comparison of cognitive assessment results between male and female MCI groups

Quantitative structural MRI

Correlation between ROIs and cognitive functions

Discussion

Current research progress on AD and MCI

Significant differences between sexes in biomarkers, cognitive functions, and brain imaging of prodromal AD

Clinical significance of sex differences in prodromal AD

Deficiencies in this research

Perspectives and significance

Supplemental Material

sj-docx-1-alz-10.1177_13872877241289790 - Supplemental material for Valuing the importance of sex differences in prodromal Alzheimer's disease based on structural magnetic resonance imaging

Footnotes

Acknowledgments

ORCID iD

Author contributions

Funding

Declaration of conflicting interests

Data availability

Supplemental material

References

Supplementary Material

¹⁸F-AV-45 PET