Citations

AbstractBeing a woman is one of the strongest risk factors for multiple sclerosis. The natural reproductive period from menarche to natural menopause corresponds to the active inflammatory disease period in multiple sclerosis. The fifth decade marks both the peri-menopausal transition in the reproductive aging and a transition from the relapsing-remitting to the progressive phase in multiple sclerosis. A short reproductive period with premature/early menopause and/or low number of pregnancies may be associated with an earlier onset of the progressive multiple sclerosis phase. A cross-sectional study of survey-based reproductive history in a multiple sclerosis clinical series enriched for patients with progressive disease, and a case–control study of multiple sclerosis and age/sex matched controls from a population-based cohort were conducted. Menarche age, number of complete/incomplete pregnancies, menopause type and menopause age were compared between 137 cases and 396 control females. Onset of relapsing-remitting phase of multiple sclerosis, progressive disease onset and reaching severe disability (expanded disability status scale 6) were studied as multiple sclerosis-related outcomes (n = 233). Menarche age was similar between multiple sclerosis and control females (P = 0.306). Females with multiple sclerosis had fewer full-term pregnancies than the controls (P < 0.001). Non-natural menopause was more common in multiple sclerosis (40.7%) than in controls (30.1%) (P = 0.030). Age at natural menopause was similar between multiple sclerosis (median, interquartile range: 50 years, 48–52) and controls (median, interquartile range: 51 years, 49–53) (P = 0.476). Nulliparous females had earlier age at progressive multiple sclerosis onset (mean ± standard deviation: 41.9 ± 12.5 years) than females with ≥1 full-term pregnancies (mean ± standard deviation: 47.1 ± 9.7 years) (P = 0.069) with a pregnancy-dose effect [para 0 (mean ± standard deviation: 41.9 ± 12.5 years), para 1–3 (mean ± standard deviation: 46.4 ± 9.2 years), para ≥4 (mean ± standard deviation: 52.6 ± 12.9 years) (P = 0.005)]. Menopause age was associated with progressive multiple sclerosis onset age (R2 = 0.359, P < 0.001). Duration from onset of relapses to onset of progressive multiple sclerosis was shorter for females with premature/early menopause (n = 26; mean ± standard deviation: 12.9 ± 9.0 years) than for females with normal menopause age (n = 39; mean ± standard deviation: 17.8 ± 10.3 years) but was longer than for males (mean ±standard deviation: 10.0 ± 9.4 years) (P = 0.005). There was a pregnancy-dose effect of age at expanded disability status scale 6 (para 0: 43.0 ± 13.2 years, para 1–3: 51.7 ± 11.3 years, para ≥4: 53.5 ± 4.9 years) (P = 0.013). Age at menopause was associated with age at expanded disability status scale 6 (R2 = 0.229, P < 0.003). Premature/early menopause or nulliparity was associated with earlier onset of progressive multiple sclerosis with a ‘dose effect’ of pregnancies on delaying progressive multiple sclerosis and severe disability. Although causality remains uncertain, our results suggest a beneficial impact of oestrogen in delaying progressive multiple sclerosis. If confirmed in prospective studies, our findings have implications for counselling women with multiple sclerosis about pregnancy, surgical menopause and menopausal hormone therapy.

AbstractBackgroundWhile β‐amyloid and tau PET imaging are widely studied in cognitive aging and Alzheimer’s disease (AD), little is known about findings in aging multiple sclerosis (MS) patients. As aging is an essential factor in developing neurodegeneration in MS, β‐amyloid and tau biomarkers may be utilized to understand the influence of AD pathophysiology on cognitive aging in MS.MethodWe studied patients with MS (n=16) and controls (n=80) matched for age, sex and APOE ε4 status from the population‐based Mayo Clinic Study of Aging who underwent Pittsburgh compound‐B (PiB) PET imaging. Twelve of the 16 patients with MS and 60 matching controls also underwent flortaucipir (AV1451) tau PET. Cortical PiB and AV1451 standard uptake value ratios (SUVr) from previously determined AD signature regions and from the entire cortex were calculated for group comparisons and testing for associations with age.ResultAD signature PiB SUVr (p=0.044), total cortical PiB SUVr (p=0.048) and the frequency of abnormal PiB SUVrs (p=0.040) were lower in patients with MS than controls. Although AD signature and total cortical AV1451 SUVrs were not different between the groups, the frequency of abnormal AV1451 SUVrs was higher (p=0.041) in patients with MS than controls. The association of AD signature PiB SUVr with age was steeper in the controls compared to patients with MS (p=0.002). Similarly, the association of total cortical PiB SUVr with age was steeper in the controls compared to patients with MS (p=0.002). There was no difference in the association of AV1451 SUVr findings with age between the MS patients and controls (Figure 1). The AD signature PiB SUVr increased more with increasing AD signature AV1451 SUVr in controls than in patients with MS (p=0.03) (Figure 2).ConclusionIn patients with MS, cortical β‐amyloid deposition was lower than age‐matched controls, while cortical tau deposition was not different between the groups. This suggests that some aspect of MS pathobiology retards the accumulation of β‐amyloid, but not the accumulation of tau.

AbstractBackgroundFamilial frontotemporal dementia (f‐FTLD) is typically caused by mutations in one of three genes: microtubule‐associated protein tau (MAPT), progranulin (GRN), and a repeat expansion in the chromosome 9 open reading frame 72 (C9orf72) gene. Accurate characterization of the natural history of each mutation is important for clinical prognostication and clinical trial design, and it could shed light on disease biology. Such models have not been thoroughly developed using participants that represent all disease stages, with longitudinal data. We characterized the trajectory of atrophy in each gene by using longitudinal voxel‐wise analyses of gray matter volume, and we assessed whether functional independence declined in tandem.MethodF‐FTLD participants (n=100) with a known mutation (MAPT+ (n=28), GRN+ (n=33), C9orf72+ (n=39)) were grouped according to disease stage (CDR®+NACC FTLD module). We included participants with at least two structural MRIs at a given disease stage: presymptomatic (CDR®+NACC‐FTLD=0, n=57), mild/questionable (CDR®+NACC‐FTLD=0.5, n=15), and symptomatic (CDR®+NACC‐FTLD ≥1, n=28). We fitted longitudinal linear mixed effects models to extract mean atrophy rates in each lobe compared to longitudinal imaging from family members without mutations (n=60). All results presented below were significant at p<.001.ResultUsing the left frontal lobe as an exemplar, in the presymptomatic stage, MAPT mutation carriers showed the greatest rate of atrophy compared to controls (88 mm3/year more volume loss than controls), followed by GRN+ (65 mm3/year) and then C9orf72+ (49 mm3/year). In the mild/questionable stage, MAPT+ showed a greater divergence from controls (374 mm3/year) than did GRN+ (107 mm3/year) or C9orf72+ (223 mm3/year). In the symptomatic stage, MAPT+ again lost volume at the fastest rate (2,099 mm3/year), followed by GRN+ (1,360 mm3/year). C9orf72 expansion carriers showed a much slower rate of volume loss (115 mm3/year). Similar patterns were observed for other brain regions. In contrast to the imaging results, C9orf72+ exhibited similar rates of functional decline compared to GRN+ and MAPT+ at all levels of disease severity.ConclusionThe primary f‐FTLD genes show divergent atrophy trajectories as a function of disease stage, with C9orf72 expansion carriers exhibiting a slow degeneration throughout the disease course, possibly due to unique pathophysiological mechanisms.

AbstractBackgroundMultiple imaging modalities have been individually shown to be useful in diagnosing Dementia with Lewy Bodies (DLB). Reduced striatonigral uptake on ioflupane‐SPECT reflects striatonigral dopamine dysfunction observed in DLB, while other imaging modalities assess different aspects of DLB, which potentially work complementarily when used together. We assessed how well ioflupane‐SPECT differentiates DLB from Alzheimer’s Disease Dementia (ADem) and whether adding another imaging modality to ioflupane‐SPECT would provide additional value.MethodIoflupane‐SPECT, MRI, FDG‐PET, and PiB‐PET were assessed on 35 DLB and 14 ADem patients (including 12 patients with eventual autopsy confirmation). Striatonigral dopamine transporter uptake was evaluated semi‐quantitatively with ioflupane‐SPECT using DaTQUANT software (GE Healthcare) to calculate z‐scores of putamen uptake. Hippocampal volume was calculated with structural MRI, cingulate island sign (CIS) ratio with FDG‐PET, and global cortical PiB retention with PiB‐PET.ResultLower DaTQUANT z‐scores of putamen were observed in DLB patients compared to ADem patients (c‐statistic 0.896, p<0.001). Ioflupane‐SPECT showed higher c‐statistic in differentiating DLB from ADem than hippocampal volume on MRI (c‐statistic 0.718, p=0.034), CIS on FDG‐PET (c‐statistic 0.869, p=0.003), or global cortical PiB retention on PiB‐PET (c‐statistic 0.869, p=0.002), but some overlap between two diagnostic groups was still observed with the single imaging modality. Among these imaging modalities, ioflupane‐SPECT was the only modality correlated with the Unified Parkinson Disease Rating Scale (UPDRS) part III, while only PiB‐PET correlated with Montreal Cognitive Assessment (MoCA) test score. Adding another imaging modality to ioflupane‐SPECT enhanced c‐statistics (+MRI c‐statistic 0.931, p<0.001; +FDG‐PET c‐statistic 0.957, p=0.005; +PiB‐PET c‐statistic 0.955, p=0.007), and ioflupane‐SPECT in combination with both FDG‐PET and PiB‐PET showed the highest c‐statistic of 0.974 (p=0.043).ConclusionIoflupane‐SPECT is an excellent imaging modality to identify DLB by detecting striatonigral dopamine dysfunction which is strongly associated with motor impairment in DLB. Correlative neuroimaging with MRI, FDG‐PET, or PiB‐PET may add small incremental value in differentiation of DLB and ADem. Supported by NIH grants (AG016574, AG006786, AG015866, NS100620, AG062677), grant from GE Healthcare, the Mayo Clinic Dorothy and Harry T. Mangurian Jr. Lewy Body Dementia Program, the Deal Family Foundation, and the Little Family Foundation.

AbstractBackgroundNeurodegeneration of the substantia nigra in dementia with Lewy bodies is associated with iron deposition, which increases the magnetic susceptibility of the substantia nigra on MRI. The objective of this study was to measure the magnetic susceptibility of the substantia nigra in patients with dementia with Lewy bodies (DLB) and patients with mild cognitive impairment with at least one core feature of DLB (MCI‐DLB) compared to cognitively unimpaired controls (CU) by quantitative susceptibility mapping (QSM).MethodWe studied clinically diagnosed patients with DLB (n=36), patients with MCI‐DLB (n=16), and age‐, gender‐matched CU (n=104) in a case‐control study. MR images used for QSM were performed on 3T MRI with a multi‐echo (5 echoes) 3D gradient recalled echo sequence with a bipolar‐readout. Three‐dimensional regions of interest (ROIs) of bilateral substantia nigra, based on the DISTAL atlas, were propagated from the Mayo Clinic Adult Lifespan Template (MCALT) to each subject’s T1 image using ANTs nonlinear registration. The mean susceptibility values of the substantia nigra were extracted by aligning each subjects QSM image to their T1 image and corresponding ROIs with a 6 DOF rigid registration.ResultThe mean susceptibility values of the substantia nigra bilaterally was 0.110 ± 0.026 for DLB, 0.099 ± 0.028 for MCI‐DLB and 0.091 ± 0.025 for controls (Figure 1). No difference was found across the mean susceptibility from left, right and combined bilateral substantia nigra. Compared to controls, patients with DLB had higher susceptibility in the substantia nigra (p<0.001). The susceptibility of substantia nigra showed an increasing trend from controls to MCI‐DLB and to DLB (p<0.001). There was no correlation between the Unified Parkinson's Disease Rating Scale (UPDRS) and the mean susceptibility in the substantia nigra in patients with MCI‐DLB and DLB (r=0.03; p=0.82).ConclusionQuantitative susceptibility mapping is sensitive to the increased magnetic susceptibility due to higher iron content in the substantia nigra in DLB. The trend of increasing susceptibility from CU to MCI‐DLB and to DLB suggests that iron deposition in the substantia nigra starts to increase as early as the prodromal stage in DLB and continues to increase as the disease progresses independent of the severity of Parkinsonism.

AbstractBackgroundData shared for research use must be de‐identified to protect participant confidentiality. A recent study has shown that face imagery from brain imaging studies could be used to re‐identify anonymous participants via automatic face recognition, linking them with all study‐collected protected health information. Here we measure how well existing software for removing MRI face imagery protects against this privacy threat.MethodWe recruited 153 participants with existing 3D FLAIR MRI and photographed their face from 5 varying angles. We used surf_ice to reconstruct each participant’s face from their MRI and tested whether free, publicly‐available face recognition software (Microsoft Azure) could match their photos to their correct MRI. We tested two existing programs for removing face voxels in MRI: mri_deface (FreeSurfer) and pydeface (python package), and one in‐house implementation. We observed that existing methods often left participants’ eyes intact while removing most of their nose/mouth/chin. This prevented Azure from detecting the reconstructions as faces, therefore preventing its attempt of face recognition. We hypothesized that the retained eye imagery alone could be sufficient for face recognition, if a face were detected. Therefore, we also reconstructed each de‐faced MRI after applying novel pre‐processing that replaced any removed/missing face voxels with those from our population‐average template, e.g. replacing missing noses/mouths/chins with population‐average noses/mouths/chins, before testing face recognition.ResultsWithout any MRI de‐facing, Microsoft Azure correctly matched 78% of participants’ photos to their MRI. After mri_deface and pydeface, 8% and 6% were still identified, respectively. After preprocessing the de‐faced MRI to replace missing areas with those from a population‐average template prior to face reconstruction, the face imagery remaining in the de‐faced images was enough to allow re‐identification of 23% and 20% of participants, respectively. With an in‐house face removal implementation that removes the whole face from every image, 0% of faces were re‐identified from the standard reconstructions, and 5% were identified from the “missing‐parts‐replacement” reconstructions.ConclusionsEven after applying popular MRI de‐facing software, Microsoft Azure face recognition automatically re‐identified up to 23% of participants. Better de‐facing software is needed to remove more of the face more reliably, without affecting brain measurements from de‐faced images.

AbstractBackgroundPatients with dementia with Lewy bodies (DLB) are characterized by hypometabolism in the parieto‐occipital cortex and the cingulate island sign on F18‐fluorodeoxyglucose (FDG) PET, lower medial temporal F18‐Flortaucipir uptake on tau PET, and lower volumes of the basal forebrain gray matter nuclei on MRI. Whether this pattern of imaging findings is present as early as the prodromal stage of DLB is unknown. We investigated the pattern of hypometabolism, atrophy, and Flortaucipir uptake in patients with mild cognitive impairment (MCI) who progressed to DLB and compared them to MCI patients who progressed to Alzheimer’s disease dementia (ADdem).MethodPatients with MCI who underwent FDG PET (n=17), Flortaucipir PET (n=9) and MRI (n=28) at baseline and progressed to probable DLB were included. We also included a cognitively unimpaired cohort of controls and MCI patients who progressed to probable ADdem (MCI‐AD) for comparison. Voxel‐base analysis on SPM12 and region‐based analysis were performed to compare the clinical groups.ResultPatients with MCI‐DLB had profound hypometabolism in the parieto‐occipital region extending into the temporal lobes, substantia nigra and thalamus. When compared to MCI‐AD, the hippocampal and posterior cingulate metabolism were relatively preserved in patients with MCI‐DLB, accompanied by greater hypometabolism in the substantia nigra in MCI‐DLB than MCI‐AD. MCI‐DLB patients were also characterized by greater atrophy in the substantia innominata (nucleus basalis of Meynert and the diagonal band) on MRI. F‐18 Flortaucipir uptake in MCI‐DLB was comparable to the control group, but significantly lower than MCI‐AD particularly in the medial temporal lobes.ConclusionImaging biomarkers can identify neurodegenerative changes associated with the prodromal phase of DLB. Prodromal DLB patients are characterized by greater atrophy in basal forebrain nuclei, suggesting that the degeneration of the cholinergic system occur as early as the prodromal stage in DLB. Preservation of medial temporal metabolism, the cingulate island sign, and substantia nigra hypometabolism on FDG PET and lower medial temporal F18‐ Flortaucipir uptake can be used to distinguish prodromal DLB and prodromal ADdem.

AbstractBackgroundThe abrupt loss of ovarian hormones before menopause, induced by oophorectomy, has been associated with accelerated aging, multimorbidity, and Alzheimer’s disease (AD). We investigated the impact of prolonged loss of ovarian hormones on AD progression in a transgenic mouse model of amyloid pathology using in vivo diffusion tensor MRI, resting‐state functional MRI (rsfMRI) and spectroscopy (MRS).MethodFemale 3.5‐month‐old TG2576 (TG) (N=27) and wild‐type (WT) (N=27) mice were ovariectomized (TGOVX) or sham‐operated (TGSHAM). When they became 18‐month‐old, 1‐H MRS (ROIs: hypothalamus, hippocampus, and cerebral cortex), DTI and rsfMRI was performed. ROI based analysis was performed on rsfMRI and DTI (Fractional anisotropy (FA), axial diffusivity (AxD), mean diffusivity, and radial diffusivity). The brain samples were then evaluated by histology and ELISA to assess Aβ load and activated glial cells. The loss of ovarian hormones via OVX was validated with elevated plasma luteinizing hormone level: OVX>SHAM (p<0.05). Two‐way ANOVA and post‐hoc (Student’s‐t) tests were used for statistical analysis. P values were adjusted for multiple comparisons (FDR‐p).ResultThe multimodel imaging data showed that there was a significant increase in taurine and total creatine (markers for inflammation and energy metabolism) in the hypothalamus, decrease in FA and AxD (markers for white matter integrity) in the white matter regions, and decrease in the functional connectivity between the prefrontal cortex and the hippocampus and dorsal and ventral hippocampus regions (a neural marker of network activity and integrity) (FDR‐p <0.05 (Figure 1)) in TGOVX mice compared to TGSHAM mice (post‐hoc t‐test). rsFMRI showed a significant increase in rsfMRI connectivity in WTOVX mice compared to WTSHAM mice. Complementary histological (and ELISA) analysis revealed no differences in Aβ load (plaque and soluble) and activated glial cells between the TG groups.ConclusionThe MRI results suggest that inflammatory response was elevated, energy metabolism was disrupted and white matter and network integrity decreased after prolonged ovarian hormone loss. These MRI results support other data from human and animal studies suggesting that abrupt hormonal changes associated with premenopausal removal of ovaries may increase the risk factors of AD, and accelerate the disease progression by causing abnormalities in brain structure, function and metabolism.

AbstractBackgroundThe critical‐period theory of menopausal hormone therapy (mHT) suggests that if menopausal hormone therapy begins shortly after menopause, it may have beneficial effects on brain structure and cognitive health. We investigated white matter integrity with diffusion tensor MRI (DTI) 3 years after the end of mHT trial in recently menopausal women who were randomized shortly after menopause.MethodParticipants of this study were enrolled in the Kronos Early Estrogen Prevention Study (aged 42–56 years; 5–36 months past menopause). Participants received the following treatments: 0.45 mg/d oral conjugated equine estrogen (oCEE, n=19); 50 μg/d transdermal 17β‐estradiol (tE2, n=22); or placebo (n=33) for 4 years. Oral progesterone (200 mg/d) was given to hormone therapy groups for 12 days each month. DTI was performed 3 years after the end of 4 years of hormone therapy (n=75), which corresponded to 7 years after randomization. Voxel‐based analysis was performed on DTI to evaluate fractional anisotropy (FA) and mean diffusivity (MD) differences between treatment groups (uncorrected p<0.001).ResultVoxel based analysis showed higher FA, a measure of white matter integrity, in the superior corona radiata, anterior limb of the internal capsule and splenium of the corpus callosum of participants treated with oCEE compared to placebo (p <0.001, Figure 1A). Furthermore, higher FA was observed in the superior corona radiata, anterior limb of internal capsule and thalamus in participants treated with tE2 compared to placebo (p <0.001, Figure 1B). There were no differences in FA findings between oCEE and tE2 groups, and no MD differences between treatments groups.ConclusionA relatively higher FA in a variety of white matter regions in the oCEE and tE2 groups compared to placebo suggest that mHT may have long‐term protective effects on white matter integrity. Previously, we had shown that women in the tE2 group preserved their dorsolateral prefrontal cortex volumes better than the placebo group over 7 years. Our findings suggest that the tracts that connect the dorsolateral prefrontal cortex and the thalamus such as the superior corona radiata and the anterior limb of internal capsule may particularly benefit from mHT.