Emily Goard Jacobs

Menopause is a hallmark process in biological aging that has been implicated in later neurodegenerative risk, but the pathways underlying this connection remain unclear. Here we used blood proteomics data from several cohorts to identify biological changes associated with menopause and its links to brain aging. In n = 80 rigorously staged (STRAW+10) pre-, peri- and postmenopausal women (aged 43–58 years) with serum NULISAseq proteomics, we show that spontaneous menopause is characterized by dysregulation in inflammatory, synaptic, metabolic and Alzheimer’s disease biologic processes, which tracked more strongly with hormones than with age. Validation analyses in age-matched pre-/peri- and postmenopausal women ( n = 2,814) with plasma Olink proteomics replicated the observed proteomic shifts and revealed broader menopause-related upregulation of inflammatory and catabolic processes plus accelerated organ and cell aging, including brain aging. In four independent cohorts of older women (average age, 60.7–72.1 years; total n = 11,925), higher menopause proteomic scores associated consistently with cognitive aging and dementia risk. The molecular signatures of menopause may inform the selection of biomarkers or therapeutic targets for brain health in midlife women.

Earlier menopause is a risk factor for several age-related diseases, including dementia. The biological pathways linking menopause timing to later-life brain aging are not understood. Leveraging large-scale plasma proteomics in postmenopausal women from the UK Biobank (N=15,012), earlier menopause was associated with upregulation of pro-inflammatory and extracellular matrix degradation pathways, plus accelerated aging across proteomic clocks of organ and cellular aging, including brain and oligodendrocyte aging. Elevated GDF15, a canonical aging marker, was the top protein correlate of earlier menopause. We observed robust replication of menopause timing proteomic shifts in the Women’s Health Initiative Long Life Study (N=1,210). In UKB, proteins associated with earlier menopause, including GDF15, exhibited concordant associations with incident dementia risk and brain atrophy, cerebral small vessel disease burden, and white matter microstructural integrity. Collectively, our findings identify proteomic signatures linking ovarian aging to brain aging, providing a framework to inform interventions to reduce dementia risk.

Menopause is a hallmark process in biological aging that has been associated with later life neurodegenerative risk. We leveraged proteomics data from multiple cohorts (N>3,000) to identify biological changes underlying menopause and its links to brain aging. In N=80 rigorously-phenotyped pre-, peri-, and postmenopausal women with serum NULISAseq proteomics, spontaneous menopause was characterized by dysregulation in inflammatory, synaptic, metabolic, and Alzheimer’s disease (AD) biologic processes, which tracked with hormones and not age. Pro-inflammatory protein upregulation was especially pronounced in women with vasomotor symptoms. In two cohorts of older women (N=94; N=100), menopause-related proteomic elevations associated with poorer cognitive outcomes and plasma AD biomarkers. Finally, validation analyses in age-matched pre- and postmenopausal women with plasma Olink proteomics (N=2,814) replicated the observed proteomic shifts and revealed menopause-related upregulation of additional inflammatory and hormone signaling processes. The molecular signatures of menopause may inform biomarkers or therapeutic targets for brain health in women.

Sex differences in brain connectivity are well documented, yet how these differences evolve across the human lifespan remains poorly understood. Rigorously assessing sex-dependent trajectories of brain network organization is challenging due to difficulty in acquiring, processing, and modeling high-dimensional connectomes. Here, we analyzed 15 types of functional and structural connectivity networks from 1286 healthy individuals aged 8–100+ years, using our new AI-based Krakencoder to derive a low-dimensional multimodal “fusion” connectome representation. Sex differences were minimal in early childhood, pronounced in young to mid-adulthood, and diverged across modalities in later life: functional connectivity grew less distinct and structural connectivity grew more distinct from midlife onward. Functional differences were driven predominantly by higher-order association networks (default mode, control), while structural differences concentrated in lower-order cerebellar and subcortical pathways. These findings provide a lifespan-wide, multimodal map of sex differences in brain networks which may help inform sex-specific vulnerability and resilience to brain disorders.

Endometriosis affects approximately 10% of reproductive-age women worldwide and is associated with substantial pain and mental health burden, yet its neurobiological correlates remain poorly characterized. Neuroimaging studies of endometriosis are particularly limited. Here we present a comprehensive, multidimensional investigation of the neurobiology of endometriosis, integrating structural and diffusion neuroimaging, biofluid measures, neuropsychological testing, and detailed health and psychosocial phenotyping in individuals with and without endometriosis. Compared with controls, individuals with endometriosis exhibited higher levels of pain, depression, and anxiety and performed worse across multiple cognitive domains. Global and regional brain morphometric measures did not differ between groups; however, endometriosis-specific pain was associated with altered gray matter volume and white matter microstructure across distributed pain-related neural circuits. These findings identify pain-related neurobiological signatures of endometriosis and establish a foundation for mechanistic and translational studies of its central nervous system effects.

Gonadal hormone receptors are widely distributed across the brain, yet their influence on brain structure remains understudied. Here, using precision imaging, we examined four females, including one with endometriosis and one using oral contraceptives (OC), across a monthly period. Whole-brain analyses revealed spatiotemporal patterns of brain volume changes, with substantial variations across the monthly period. In typical cycles, spatiotemporal patterns were associated with serum progesterone levels, while in cycles with endometriosis and during OC intake, patterns were associated with serum estradiol levels. The volume changes were widely distributed rather than region-specific, suggesting a widespread but coordinated influence of hormonal fluctuations. These findings underscore the importance of considering diverse hormonal milieus beyond typical menstrual cycles in understanding structural brain dynamics and suggest that hormonal rhythms may drive widespread structural brain changes.

Neuroendocrinology has received little attention in human neuroscience research, resulting in a dearth of knowledge surrounding potent and dynamic modulators of cognition and behavior, as well as brain structure and function. This work addresses one such phenomenon by studying functional connectomics related to ovarian hormone fluctuations throughout the adult menstrual cycle. To do so, we used fMRI and hormone assessments from two dense, longitudinal datasets to assess variations in functional connectivity with respect to endogenous and exogenous endocrine factors throughout the menstrual cycle. First, we replicated prior findings that common, group-level, and individual-specific factors have similar relative contributions to functional brain network organization. Second, we found widespread connectivity related to hormonal contraceptive (HC) use, in addition to sparser estradiol- and progesterone-related connectivity. Differential generalizability of these connectivity patterns suggests progestin-specific impacts on functional brain organization in HC users. These results provide novel insight into within-individual changes in brain organization across the menstrual cycle and the extent to which these changes are shared between individuals, illuminating understudied phenomena in reproductive health and important information for all neuroimaging studies that include participants who menstruate.

Background: Menopausal hormone therapy (MHT) is generally thought to be neuroprotective, yet results have been inconsistent. Here, we present a comprehensive study of MHT use and brain characteristics in females from the UK Biobank.Methods: 19,846 females with magnetic resonance imaging data were included. Detailed MHT prescription data from primary care records was available for 538. We tested for associations between the brain measures (i.e. gray/white matter brain age, hippocampal volumes, white matter hyperintensity volumes) and MHT user status, age at first and last use, duration of use, formulation, route of administration, dosage, type, and active ingredient. We further tested for the effects of a history of hysterectomy ± bilateral oophorectomy among MHT users and examined associations by APOE ε4 status.Results: Current MHT users, not past users, showed older gray and white matter brain age, with a difference of up to 9 mo, and smaller hippocampal volumes compared to never-users. Longer duration of use and older age at last use post-menopause was associated with older gray and white matter brain age, larger white matter hyperintensity volume, and smaller hippocampal volumes. MHT users with a history of hysterectomy ± bilateral oophorectomy showed younger gray matter brain age relative to MHT users without such history. We found no associations by APOE ε4 status and with other MHT variables.Conclusions: Our results indicate that population-level associations between MHT use and female brain health might vary depending on duration of use and past surgical history.Funding: The authors received funding from the Research Council of Norway (LTW: 223273, 249795, 273345, 298646, 300768), the South-Eastern Norway Regional Health Authority (CB: 2023037, 2022103; LTW: 2018076, 2019101), the European Research Council under the European Union’s Horizon 2020 research and innovation program (LTW: 802998), the Swiss National Science Foundation (AMGdL: PZ00P3_193658), the Canadian Institutes for Health Research (LAMG: PJT-173554), the Treliving Family Chair in Women’s Mental Health at the Centre for Addiction and Mental Health (LAMG), womenmind at the Centre for Addiction and Mental Health (LAMG, BHL), the Ann S. Bowers Women’s Brain Health Initiative (EGJ), and the National Institutes of Health (EGJ: AG063843).