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Declining estrogen levels before, during, and after menopause can affect memory and risk for Alzheimer's disease. Undesirable side effects of hormone variations emphasize a role for hormone therapy (HT) where possible benefits include a delay in the onset of dementia-yet findings are inconsistent. Effects of HT may be mediated by estrogen receptors found throughout the brain. Effects may also depend on lifestyle factors, timing of use, and genetic risk. We studied the impact of self-reported HT use on brain volume in 562 elderly women (71-94 years) with mixed cognitive status while adjusting for aforementioned factors. Covariate-adjusted voxelwise linear regression analyses using a model with 16 predictors showed HT use as positively associated with regional brain volumes, regardless of cognitive status. Examinations of other factors related to menopause, oophorectomy and hysterectomy status independently yielded positive effects on brain volume when added to our model. One interaction term, HTxBMI, out of several examined, revealed significant negative association with overall brain volume, suggesting a greater reduction in brain volume than BMI alone. Our main findings relating HT to regional brain volume were as hypothesized, but some exploratory analyses were not in line with existing hypotheses. Studies suggest lower levels of estrogen resulting from oophorectomy and hysterectomy affect brain volume negatively, and the addition of HT modifies the relation between BMI and brain volume positively. Effects of HT may depend on the age range assessed, motivating studies with a wider age range as well as a randomized design., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Secondhand smoke exposure is a major public health risk that is especially harmful to the developing brain, but it is unclear if early exposure affects brain structure during middle age and older adulthood. Here we analyzed brain MRI data from the UK Biobank in a population-based sample of individuals (ages 44-80) who were exposed (n = 2510) or unexposed (n = 6079) to smoking around birth. We used robust statistical models, including quantile regressions, to test the effect of perinatal smoke exposure (PSE) on cortical surface area (SA), thickness, and subcortical volumes. We hypothesized that PSE would be associated with cortical disruption in primary sensory areas compared to unexposed (PSE-) adults. After adjusting for multiple comparisons, SA was significantly lower in the pericalcarine (PCAL), inferior parietal (IPL), and regions of the temporal and frontal cortex of PSE+ adults; these abnormalities were associated with increased risk for several diseases, including circulatory and endocrine conditions. Sensitivity analyses conducted in a hold-out group of healthy participants (exposed, n = 109, unexposed, n = 315) replicated the effect of PSE on SA in the PCAL and IPL. Collectively our results show a negative, long term effect of PSE on sensory cortices that may increase risk for disease later in life., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Objective: Impaired empathy is a diagnostic feature of behavioral variant frontotemporal dementia (bvFTD), but it is not clear whether it is caused by a primary impairment in empathy or by general emotional blunting., Methods: Patients with bvFTD who met criteria for loss of empathy (N=10) and patients with Alzheimer's disease (N=15) were assessed with a measure for empathy (Socioemotional Dysfunction Scale [SDS]) and a measure for general emotion (Scale for Emotional Blunting [SEB]). All patients underwent neuroimaging. Both patient groups and a healthy control group (N=18) were evaluated by using autonomic responses (skin conductance responses [SCR]) to pictures from the Internal Affective Picture System (IAPS) (presence or absence of empathy stimuli and high versus low emotion)., Results: All participants reported understanding the content and others' perspectives on the empathy pictures; however, only patients with bvFTD showed impaired empathic behavior on the SDS, which persisted after adjusting for measures from the emotion scale (SEB). Patients with bvFTD had significantly lower SCR for all the IAPS stimuli, including for empathy pictures, which also persisted after adjusting for emotional content. On MRI analysis, SCR across groups significantly correlated with the volume of the dorsal anterior cingulate gyrus (dACC)., Conclusions: These results indicate that patients with bvFTD have decreased empathic behavior with or without emotional blunting, and they exhibit decreased psychophysiological responses to empathy stimuli, independent of general emotion. These preliminary findings suggest a specific impairment in emotional empathy, possibly related to impairment of the emotional appraisal role of the dACC.

Background and Purpose: Posttraumatic stress disorder (PTSD) is a heterogeneous condition associated with a range of brain imaging abnormalities. Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here, we used a novel machine learning method - evolving partitions to improve classification (EPIC) - to identify shared and unique structural neuroimaging markers of ELS and PTSD in 97 combat-exposed military veterans., Methods: We used EPIC with repeated cross-validation (CV) to determine how combinations of cortical thickness, surface area, and subcortical brain volumes could contribute to classification of PTSD (n = 40) versus controls (n = 57), and classification of ELS within the PTSD (ELS + n = 16; ELS - n = 24) and control groups (ELS + n = 16; ELS - n = 41). Additional inputs included intracranial volume, age, sex, adult trauma, and depression., Results: On average, EPIC classified PTSD with 69% accuracy (SD = 5%), and ELS with 64% accuracy in the PTSD group (SD = 10%), and 62% accuracy in controls (SD = 6%). EPIC selected unique sets of individual features that classified each group with 75-85% accuracy in post hoc analyses; combinations of regions marginally improved classification from the individual atlas-defined brain regions. Across analyses, surface area in the right posterior cingulate was the only variable that was repeatedly selected as an important feature for classification of PTSD and ELS., Conclusions: EPIC revealed unique patterns of features that distinguished PTSD and ELS in this sample of combat-exposed military veterans, which may represent distinct biotypes of stress-related neuropathology., (© 2019 by the American Society of Neuroimaging.)

Brain aging is a multifaceted process that remains poorly understood. Despite significant advances in technology, progress toward identifying reliable risk factors for suboptimal brain health requires realistically complex analytic methods to explain relationships between genetics, biology, and environment. Here we show the utility of a novel unsupervised machine learning technique - Correlation Explanation (CorEx) - to discover how individual measures from structural brain imaging, genetics, plasma, and CSF markers can jointly provide information on risk for Alzheimer's disease (AD). We examined 829 participants ( M age : 75.3 ± 6.9 years; 350 women and 479 men) from the Alzheimer's Disease Neuroimaging Initiative database to identify multivariate predictors of cognitive decline and brain atrophy over a 1-year period. Our sample included 231 cognitively normal individuals, 397 with mild cognitive impairment (MCI), and 201 with AD as their baseline diagnosis. Analyses revealed latent factors based on data-driven combinations of plasma markers and brain metrics, that were aligned with established biological pathways in AD. These factors were able to improve disease prediction along the trajectory from normal cognition and MCI to AD, with an area under the receiver operating curve of up to 99%, and prediction accuracy of up to 89.9% on independent "held out" testing data. Further, the most important latent factors that predicted AD consisted of a novel set of variables that are essential for cardiovascular, immune, and bioenergetic functions. Collectively, these results demonstrate the strength of unsupervised network measures in the detection and prediction of AD.

Impaired attribution of animacy (state of living or being sentient) and of agency (capability of intrinsically-driven action) may underlie social behavior disturbances in behavioral variant frontotemporal dementia (bvFTD). We presented the Heider and Simmel film of moving geometric shapes to 11 bvFTD patients, 11 Alzheimer's disease (AD) patients, and 12 healthy controls (HCs) and rated their recorded verbal responses for animacy attribution and agency attribution. All participants had skin conductance (SC) continuously recorded while viewing the film, and all dementia participants underwent magnetic resonance imaging (MRI) for regions of interest. The bvFTD patients, but not the AD patients, were impaired in animacy attribution, compared to the HCs. In contrast, both bvFTD and AD groups were impaired in agency attribution, compared to the HCs, and only the HCs had increasing SC responsiveness during viewing of the film. On MRI analysis of cortical thicknesses, animacy scores significantly correlated across groups with the right pars orbitalis and opercularis; agency scores with the left inferior and superior parietal cortices and the supramarginal gyrus; and both scores with the left cingulate isthmus involved in visuospatial context. These findings suggest that bvFTD is specifically associated with impaired animacy attribution from right inferior frontal atrophy. In contrast, both dementias may have impaired agency attribution from left parietal cortical atrophy and absent SC increases during the film, a sympathetic indicator of attribution of a social "story" to the moving shapes. These findings clarify disease-related changes in social attribution and corroborate the neuroanatomical origins of animacy and agency., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Autism Spectrum Disorder is a complex developmental disorder affecting 1 in 68 children in the United States. While the prevalence may be on the rise, we currently lack a firm understanding of the etiology of the disease, and diagnosis is made purely on behavioral observation and informant report. As one method to improve our understanding of the disease, the current study took a systems-level approach by assessing the causal interactions among the frontoparietal and default mode networks using structural covariance of a large Autism dataset. Although preliminary, we report diffuse yet subtle changes throughout these networks when comparing age and sex matched controls to ASD patients.

Age, apolipoprotein E ε4 (APOE) and chromosomal sex are well-established risk factors for late-onset Alzheimer's disease (LOAD; AD). Over 60% of persons with AD harbor at least one APOE-ε4 allele. The sex-based prevalence of AD is well documented with over 60% of persons with AD being female. Evidence indicates that the APOE-ε4 risk for AD is greater in women than men, which is particularly evident in heterozygous women carrying one APOE-ε4 allele. Paradoxically, men homozygous for APOE-ε4 are reported to be at greater risk for mild cognitive impairment and AD. Herein, we discuss the complex interplay between the three greatest risk factors for Alzheimer's disease, age, APOE-ε4 genotype and chromosomal sex. We propose that the convergence of these three risk factors, and specifically the bioenergetic aging perimenopause to menopause transition unique to the female, creates a risk profile for AD unique to the female. Further, we discuss the specific risk of the APOE-ε4 positive male which appears to emerge early in the aging process. Evidence for impact of the triad of AD risk factors is most evident in the temporal trajectory of AD progression and burden of pathology in relation to APOE genotype, age and sex. Collectively, the data indicate complex interactions between age, APOE genotype and gender that belies a one size fits all approach and argues for a precision medicine approach that integrates across the three main risk factors for Alzheimer's disease., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Objective. To understand who dementia patients identify as their family and how dementia affects family life. Background. Dementia care is often delivered in family settings, so understanding the constituency and needs of the family unit involved in care is important for determining contributors to family quality of life. Design/Methods. Seventy-seven families receiving care at an academic dementia clinic completed questionnaires regarding the affected person and the family. Responses were categorized as focused on an individual's needs or the family's needs. Results. Respondents identified a mean of 3.77 family members involved in care. Spouse (80.5%), daughter (58.4%), son (46.8%), and stepchild or child-in-law (37.7%) were the most frequently listed family members. Questions regarding the effect of dementia-related changes in cognition and mood were most likely to elicit a family-focused response. Questionnaire items that inquired about specific medical questions and strategies to improve family function were least likely to elicit a family-focused response. Conclusions. Both caregivers and persons with dementia frequently provided family-focused responses, supporting the construct of dementia as an illness that affects life in the family unit. This finding reinforces the potential utility of family-centered quality of life measures in assessing treatment success for people with dementia.