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      Elevated gonadotropin levels are associated with increased biomarker risk of Alzheimer’s disease in midlife women

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          Abstract

          Introduction:

          In preclinical studies, menopausal elevations in pituitary gonadotropins, follicle-stimulating hormone (FSH) and luteinizing hormone (LH), trigger Alzheimer’s disease (AD) pathology and synaptic loss in female animals. Herein, we took a translational approach to test whether gonadotropin elevations are linked to AD pathophysiology in women.

          Methods:

          We examined 191 women ages 40–65 years, carrying risk factors for late-onset AD, including 45 premenopausal, 67 perimenopausal, and 79 postmenopausal participants with clinical, laboratory, cognitive exams, and volumetric MRI scans. Half of the cohort completed 11C-Pittsburgh Compound B (PiB) amyloid-β (Aβ) PET scans. Associations between serum FSH, LH and biomarkers were examined using voxel-based analysis, overall and stratified by menopause status. Associations with region-of-interest (ROI) hippocampal volume, plasma estradiol levels, APOE-4 status, and cognition were assessed in sensitivity analyses.

          Results:

          FSH levels were positively associated with Aβ load in frontal cortex (multivariable adjusted P≤0.05, corrected for family wise type error, FWE), an effect that was driven by the postmenopausal group (multivariable adjusted P FWE ≤ 0.044). LH levels were also associated with Aβ load in frontal cortex, which did not survive multivariable adjustment. FSH and LH were negatively associated with gray matter volume (GMV) in frontal cortex, overall and in each menopausal group (multivariable adjusted P FWE ≤ 0.040), and FSH was marginally associated with ROI hippocampal volume (multivariable adjusted P = 0.058). Associations were independent of age, clinical confounders, menopause type, hormone therapy status, history of depression, APOE-4 status, and regional effects of estradiol. There were no significant associations with cognitive scores.

          Discussion:

          Increasing serum gonadotropin levels, especially FSH, are associated with higher Aβ load and lower GMV in some AD-vulnerable regions of midlife women at risk for AD. These findings are consistent with preclinical work and provide exploratory hormonal targets for precision medicine strategies for AD risk reduction.

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          Most cited references66

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          An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

          In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
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            Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

            An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.
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              FreeSurfer.

              FreeSurfer is a suite of tools for the analysis of neuroimaging data that provides an array of algorithms to quantify the functional, connectional and structural properties of the human brain. It has evolved from a package primarily aimed at generating surface representations of the cerebral cortex into one that automatically creates models of most macroscopically visible structures in the human brain given any reasonable T1-weighted input image. It is freely available, runs on a wide variety of hardware and software platforms, and is open source. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                9918787575706676
                53296
                Front Dement
                Front Dement
                Frontiers in dementia
                2813-3919
                20 April 2024
                2023
                23 November 2023
                21 May 2024
                : 2
                : 1303256
                Affiliations
                [1 ]Department of Neurology, Weill Cornell Medicine, New York, NY, United States
                [2 ]Department of Experimental and Clinical Biomedical Sciences, Nuclear Medicine Unit, University of Florence, Florence, Italy
                [3 ]Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
                [4 ]Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, United States
                [5 ]Department of Radiology, Weill Cornell Medicine, New York, NY, United States
                [6 ]Department of Neurology and Pharmacology, University of Arizona, Tucson, AZ, United States
                Author notes

                Author contributions

                MN: Writing—original draft, Writing—review & editing, Formal analysis, Investigation, Visualization. FR: Writing—original draft, Writing—review & editing, Formal analysis. SJ: Writing—review & editing, Data curation. CA: Writing—original draft, Writing—review & editing, Formal analysis, Investigation, Methodology. CB: Writing—review & editing. CZ: Writing—review & editing. CC: Writing—review & editing. SL-Z: Writing—review & editing. YH: Writing—review & editing. SP: Writing—review & editing. SW: Writing—review & editing, Project administration, Supervision. VB: Writing—review & editing. PC: Writing—review & editing, Formal analysis, Supervision. JD: Writing—review & editing, Formal analysis, Investigation, Resources, Software. MF: Writing—review & editing. RB: Writing—review & editing, Conceptualization, Funding acquisition, Resources. LM: Writing—original draft, Writing—review & editing, Conceptualization, Data curation, Funding acquisition, Investigation, Project administration, Resources, Supervision, Visualization.

                [* ] CORRESPONDENCE Lisa Mosconi, lim2035@ 123456med.cornell.edu
                Article
                NIHMS1980366
                10.3389/frdem.2023.1303256
                11108587
                38774256
                396d31e7-6a3c-43ea-983c-36d17de483f3

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Categories
                Article

                gonadotropin (fsh and lh),alzheimer’s disease,neuroimaging,menopause,women,positron emission tomography (pet),magnetic resonance imaging (mri)

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