1008 Brain Age Based on Sleep Encephalography is Elevated in HIV+ Adults on ART

Abstract Introduction Sleep EEG is a promising tool to measure brain aging in vulnerable populations such as people with HIV, who are high risk of brain aging due to co-morbidities, increased inflammation, and antiretroviral neurotoxicity. Our lab previously developed a machine learning model that estimates age from sleep EEG (brain age, BA), which reliably predicts chronological age (CA) in healthy adults. The difference between BA and CA, the brain age index (BAI), independently predicts mortality, and is increased by cardiovascular co-morbidities. Here, we assessed BAI in HIV+ compared to matched HIV- adults. Methods Sleep EEGs from 43 treated HIV+ adults were gathered and matched to controls (HIV-, n=284) by age, gender, race, alcoholism, smoking and substance use history. We compared BAI between groups and used additional causal interference methods to ensure robustness. Individual EEG features that underlie BA prediction were also compared. We performed a sub-analysis of BAI between HIV+ with or without a history of AIDS. Results After matching, mean CA of HIV+ vs HIV- adults were 49 and 48 years, respectively (n.s.). The mean HIV+ BAI was 3.04 years higher than HIV- (4.4 vs 1.4 yr; p=0.048). We found consistent and significant results with alternative causal inference methods. Several EEG features predictive of BA were different in the HIV+ and HIV- cohorts. Most notably, non-REM stage 2 sleep (N2) delta power (1-4Hz) was decreased in HIV+ vs. HIV- adults, while theta (4-8Hz) and alpha (8-12Hz) power were increased. Those with AIDS (n=19, BAI=4.40) did not have significantly different BAI than HIV+ without AIDS (n=23, BAI=5.22). HIV+ subjects had higher rates of insomnia (56% vs 29%, p<0.001), obstructive apnea (47% vs 30%, p=0.03), depression (49% vs 23%, p<0.001), and bipolar disorder (19% vs 4%, p<0.001). Conclusion HIV+ individuals on ART have excess sleep-EEG based brain age compared to matched controls. This excess brain age is partially due to reduction in delta power during N2, suggesting decreased sleep depth. These results suggest sleep EEG could be a valuable brain aging biomarker for the HIV population. Support This research is supported by the Harvard Center for AIDS Research HU CFAR NIH/NIAID 5P30AI060354-16.

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0348 Sleep EEG-Based Brain Age Index is Reduced Under Continuous Positive Airway Pressure Treatment

SLEEP ◽

10.1093/sleep/zsaa056.345 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A132-A132

Author(s):

H Sun ◽

K Dunham ◽

L Cunningham ◽

Y Ni ◽

M Westover ◽

...

Keyword(s):

Continuous Positive Airway Pressure ◽

Airway Pressure ◽

Positive Airway Pressure ◽

Sleep Eeg ◽

Alpha Power ◽

Delta Power ◽

Age Features ◽

Brain Age ◽

The Brain ◽

Cpap Failure

Abstract Introduction Continuous positive airway pressure (CPAP) is a treatment for apnea. With long-term CPAP, changes in electroencephalogram (EEG) include increased delta power (1 - 4Hz) and sigma power (11 - 15Hz, spindle). However, the short-term EEG response to CPAP in a split-night study is less quantified. We recently developed a “brain age” model using sleep EEG features. The brain age index (BAI) is defined as the difference between chronological age and brain age (BA - CA). Here we first quantify how BAI changes during CPAP in the same patient, and then investigate how much brain age features during the diagnostic part can predict the reduction in apnea-hypopnea index (AHI) during CPAP. Methods The dataset consisted of 160 subjects. The average age was 59 years with 53% male, 24% female and 23% unknown. We extracted 480 features including band powers, and then computed the BAIs for both diagnostic and CPAP parts. To predict the reduction in AHI during CPAP, we fit a Bayesian regression model using the brain age features, demographics, and sleep parameters during the diagnostic part, and assessed the feature importance using dominance analysis. Results The BAI from the diagnostic part is significantly reduced compared to BAI during CPAP for the same subject (paired t-test, p < 0.01). The diagnostic part has an average BAI 2.24 years; and the CPAP part -4.75 years. The brain age features that are increased during CPAP include sigma powers in N2 and N3. The prediction of AHI reduction has Pearson’s correlation 0.85. The features predictive of reduced AHI are the diagnostic AHI (explained variance 69%), followed by high/low waveforms during N2 (e.g. K-complex, measured by kurtosis) (8.6%), delta power during REM (4.5%) and N1 (2%). The feature predictive of increased AHI is frontal alpha power during quiet awake (2.6%). Conclusion The average BAI is reduced during CPAP. BAI provides a novel view of the acute response to CPAP in sleep EEG. Future study with more CPAP failure patients has the potential of predicting CPAP failure. Support MBW is supported by Glenn Foundation for Medical Research. RJT is supported by Category I AASM Foundation.

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History of childbirths relates to region-specific brain aging patterns in middle and older-aged women

10.1101/2020.05.08.084616 ◽

2020 ◽

Cited By ~ 1

Author(s):

Ann-Marie G. de Lange ◽

Claudia Barth ◽

Tobias Kaufmann ◽

Melis Anatürk ◽

Sana Suri ◽

...

Keyword(s):

Brain Aging ◽

Reward System ◽

Regional Brain ◽

Pregnancy And Postpartum ◽

Maternal Brain ◽

History Of ◽

Novel Applications ◽

Prospective Longitudinal ◽

Brain Age ◽

Age Prediction

AbstractPregnancy involves maternal brain adaptations, but little is known about how parity influences women’s brain aging trajectories later in life. In this study, we replicated previous findings showing less apparent brain aging in women with a history of childbirths, and identified regional brain aging patterns linked to parity in 19,787 middle and older-aged women. Using novel applications of brain-age prediction methods, we found that a higher number of previous childbirths was linked to less apparent brain aging in striatal and limbic regions. The strongest effect was found in the accumbens – a key region in the mesolimbic reward system, which plays an important role in maternal behavior. While only prospective longitudinal studies would be conclusive, our findings indicate that subcortical brain modulations during pregnancy and postpartum may be traceable decades after childbirth.

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Functional brain age prediction suggests accelerated aging in preclinical familial Alzheimer’s disease, irrespective of fibrillar amyloid-beta pathology

10.1101/2020.05.06.076745 ◽

2020 ◽

Author(s):

Julie Gonneaud ◽

Alex T. Baria ◽

Alexa Pichet Binette ◽

Brian A. Gordon ◽

Jasmeer P. Chhatwal ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Brain Aging ◽

Accelerated Aging ◽

Chronological Age ◽

Resting State Functional Connectivity ◽

Functional Brain ◽

Preclinical Ad ◽

The Difference ◽

Brain Age

AbstractWe aimed at developing a model able to predict brain aging from resting state functional connectivity (rs-fMRI) and assessing whether genetic risk/determinants of Alzheimer’s disease (AD) and amyloid (Aβ) pathology contributes to accelerated brain aging. Using data collected in 1340 cognitively unimpaired participants from 18 to 94 years old selected across multi-site cohorts, we showed that chronological age can be predicted across the whole lifespan from topological properties of graphs constructed from rs-fMRI. We subsequently used the difference between the model-predicted age and the chronological age in pre-symptomatic autosomal dominant AD (ADAD) mutation carriers and asymptomatic individuals at risk of sporadic AD and assessed the influence of genetics and Aβ pathology on brain age. Applying our predictive model in the context of preclinical AD revealed that the pre-symptomatic phase of ADAD is characterized by accelerated functional brain aging. This phenomenon is independent from, and might precede, detectable fibrillar Aβ deposition.

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Long-term anabolic androgenic steroid use is associated with deviant brain aging

10.1101/2020.08.19.20177832 ◽

2020 ◽

Author(s):

Astrid Bjørnebekk ◽

Tobias Kaufmann ◽

Lisa E. Hauger ◽

Sandra Klonteig ◽

Ingunn R. Hullstein ◽

...

Keyword(s):

Cognitive Abilities ◽

Brain Aging ◽

Group Differences ◽

High Dose ◽

Cross Sectional ◽

Brain Volumes ◽

History Of ◽

History Of Use ◽

Brain Age

AbstractBackgroundHigh-dose long-term use of anabolic-androgenic steroids (AAS) may bring a range of health consequences, including brain and cognitive abnormalities. We performed age prediction based on brain scans to test whether prolonged AAS use is associated with accentuated brain aging.MethodsT1-weighted MRI (3D MPRAGE) scans were obtained from male weightlifters with a history of prolonged (n=130) or no (n=99) AAS use. We trained machine learning models on combinations of regional brain volumes, cortical thickness and surface area in an independent training set of 1838 healthy males (18-92 years) and predicted brain age for each participant in our study. Including cross-sectional and longitudinal (mean interval 3.5 years, n=76) MRI data, we used linear mixed effects (LME) models to compare the gap between chronological age and predicted brain age (the brain age gap, BAG) between the two groups, and tested for group differences in the change rate of BAG. We tested for associations between apparent brain aging and AAS use duration, administration pattern and dependence.ResultsAAS users had higher BAG compared to weightlifting controls, associated with dependency and longer history of use. Group differences in BAG could not be explained by other substance use, general cognitive abilities or depression. Longitudinal data revealed no evidence of accelerated brain aging in the overall AAS group, though accelerated brain aging was seen with longer AAS exposure.ConclusionsThe findings suggest that long-term high dose AAS use may have adverse effects on brain aging, potentially linked to dependency and exaggerated use of AAS.

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Trajectory of brain maturation in adolescent individuals at familial risk of mood disorder

10.1101/537951 ◽

2019 ◽

Author(s):

Laura de Nooij ◽

Mathew A. Harris ◽

Emma L. Hawkins ◽

Xueyi Shen ◽

Toni-Kim Clarke ◽

...

Keyword(s):

Mood Disorder ◽

Longitudinal Research ◽

Familial Risk ◽

Structural Mri ◽

Brain Maturation ◽

History Of ◽

The Difference ◽

Prospective Longitudinal ◽

Brain Age

AbstractBackgroundAccelerated biological ageing has been proposed as a mechanism underlying mood disorder, but has been predominantly studied cross-sectionally in adult populations. It remains unclear whether differential ageing/maturation trajectories emerge earlier in life, in particular during the neurodevelopmental period of adolescence, and whether they are associated with onset of mood disorder and/or presence of familial risk.MethodsParticipants were young individuals (16-25 years) from the prospective longitudinal Scottish Bipolar Family Study (SBFS) with and without family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, individual maturational trajectories were captured by the difference between predicted brain age and chronological age (brain-PAD) at baseline and two-year follow-up. Based on clinical assessment at follow-up, individuals were categorised into three groups: (i) controls who remained well (C-well,n=94), (ii) high familial risk who remained well (HR-well,n=73) and (iii) high familial risk who developed a mood disorder (HR-MD,n=38).ResultsResults showed no differences in brain-PAD between groups at baseline or follow-up. However, we found negative trajectories of brain-PAD for HR-MD versus C-well (β= −0.68 years,p<.001) and versus HR-well (β= −0.38 years,p=.01), and for HR-well versus C-well (β= −0.30 years,p=.03).ConclusionsThese findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain maturation trajectory. However, without significantly differential status of brain maturation at follow-up, extended longitudinal research will need to show whether this marks the emergence of maturational lag.

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Harsdörffers Geschirr

Zeitschrift für Medien- und Kulturforschung ◽

10.28937/1000108230 ◽

2019 ◽

Vol 10 (1) ◽

pp. 23-37

Author(s):

Natalie Binczek

Keyword(s):

Design History ◽

History Of ◽

The Difference

Der deutsche Barockdichter Georg Philipp Harsdörffer skizziert eine Theorie der Emblematik, die vor allem dessen Anwendungsvielfalt hervorhebt. Er hebt dabei besonders den Unterschied zwischen buchinterner und buchexterner Verwendung auf, indem er sich nicht nur für die Aufnahme der Embleme in Büchern, sondern auch auf Geschirr und Tapeten ausspricht. Der Beitrag liest Harsdörffers extensive Überlegungen nicht nur als Beiträge zur Theorie und Geschichte der Embleme als ›Sinn-Bilder‹, sondern auch als Beitrag zur Designgeschichte. German Baroque poet Georg Philipp Harsdörffer delineates a theory of emblematics that clearly sets itself apart from other contemporary theories, especially by its versatility. In particular, the author negates the difference between internal and external usage of emblems in books not only by promoting the incorporation of emblems into printed works but also by supporting their depiction on dishes and tapestries. This article strives to read Harsdörffer’s extensive thoughts on the matter of emblems not simply as another work on the theory and history of emblematics but rather as a contribution to design history as well

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Introduction

10.1093/oso/9780198803430.003.0001 ◽

2017 ◽

Author(s):

Simon Kirchin

Keyword(s):

Hilary Putnam ◽

Bernard Williams ◽

General Methodology ◽

Thick Concepts ◽

History Of ◽

Philippa Foot ◽

The Difference

This chapter introduces the distinction between thin and thick concepts and then performs a number of functions. First, two major accounts of thick concepts—separationism and nonseparationism—are introduced and, in doing so, a novel account of evaluation is indicated. Second, each chapter is outlined as is the general methodology, followed, third, by a brief history of the discussion of thick concepts, referencing Philippa Foot, Hilary Putnam, Gilbert Ryle, and Bernard Williams among others. Fourth, a number of relevant contrasts are introduced, such as the fact–value distinction and the difference between concepts, properties, and terms. Lastly, some interesting and relevant questions are raised that, unfortunately, have to be left aside.

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A history of previous childbirths is linked to women's white matter brain age in midlife and older age

Human Brain Mapping ◽

10.1002/hbm.25553 ◽

2021 ◽

Author(s):

Irene Voldsbekk ◽

Claudia Barth ◽

Ivan I. Maximov ◽

Tobias Kaufmann ◽

Dani Beck ◽

...

Keyword(s):

White Matter ◽

Older Age ◽

History Of ◽

Brain Age

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The Early History of Financial Economics, 1478–1776. By Geoffrey Poitras. Cheltenham and Northampton: Edward Elgar, 2000. Pp. x, 522.

The Journal of Economic History ◽

10.1017/s0022050702006344 ◽

2002 ◽

Vol 62 (1) ◽

pp. 268-269

Author(s):

Larry Neal

Keyword(s):

Economic History ◽

Financial Analysis ◽

Adam Smith ◽

Economic Thought ◽

Financial History ◽

X 522 ◽

History Of ◽

The Difference ◽

Wealth Of Nations ◽

Simon Fraser University

Economic historians usually have to explain to their economist colleagues the difference between economic history, which focuses on facts, and history of economic thought, which focuses on ideas. Our colleagues in finance departments, typically fascinated by episodes in financial history treated by economic historians, are bound to be disappointed in the lack of attention given to the development of ideas in finance by historians of economic thought. Geoffrey Poitras, a professor of finance at Simon Fraser University, makes a valiant effort to remedy these oversights in his collection of vignettes that highlight the sophistication of financial instruments and analysts of financial markets well before the time of Adam Smith. Starting in 1478 with the publication of the Treviso Arithmetic, a typical textbook of commercial arithmetic for Italian merchants, and ending with brief snippets from the Wealth of Nations, Poitras treats the reader to a fascinating potpourri of excerpts from various manuals, brief biographies of pioneers in financial analysis, and historical discursions on foreign-exchange and stock markets.

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Statistical Estimation of Accelerated Biological Brain Aging After Mild Traumatic Brain Injury in Older Adults

Innovation in Aging ◽

10.1093/geroni/igaa057.3282 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 890-890

Author(s):

Andrei Irimia ◽

Jun Kim ◽

Shania Wang ◽

Hyung Jun Lee ◽

Van Ngo ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Mild Traumatic Brain Injury ◽

Brain Aging ◽

Rate Of Change ◽

Time Period ◽

Weighted Magnetic Resonance Imaging ◽

Neurological Conditions ◽

Magnetic Resonance Imaging Mri ◽

Brain Age

Abstract Estimating biological brain age (BA) has the potential of identifying individuals at relatively high risk for accelerated neurodegeneration. This study compares the brain’s chronological age (CA) to its BA and reveals the BA rate of change after mild traumatic brain injury (mTBI) in an aging cohort. Using T1-weighted magnetic resonance imaging (MRI) volumes and cortical thickness, volume, surface area, and Gaussian curvature obtained using FreeSurfer software; we formulated a multivariate linear regression to determine the rate of BA increase associated with mTBI. 95 TBI patients (age in years (y): μ = 41 y, σ = 17 y; range = 18 to 83) were compared to 462 healthy controls (HCs) (age: μ = 69 y, σ = 18 y; range = 25 to 95) over a 6-month time period following mTBI. Across the initial ~6 months following injury, patients’ BAs increased by ~3.0 ± 1.2 years due to their mTBIs alone, i.e., above and beyond typical brain aging. The superior temporal and parahippocampal gyri, two structures involved in memory formation and retrieval, exhibited the fastest rates of TBI-related BA. In both hemispheres, the volume of the hippocampus decreased (left: μ=0.28%, σ=4.40%; right: μ=0.12%, σ=4.84%). These findings illustrate BA estimation techniques’ potential to identify TBI patients with accelerated neurodegeneration, whose rate is strongly associated with the risk for dementia and other aging-related neurological conditions.

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