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Hengenius JB, Ehrenkranz R, Zhu X, Glynn NW, Huppert TJ, Rosano C. Fatigue and perceived energy in a sample of older adults over 10 years: A resting state functional connectivity study of neural correlates. Exp Gerontol 2024; 188:112388. [PMID: 38432051 PMCID: PMC11033705 DOI: 10.1016/j.exger.2024.112388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/19/2024] [Accepted: 02/29/2024] [Indexed: 03/05/2024]
Abstract
PURPOSE Declining energy and increasing fatigue, common in older age, predict neurodegenerative conditions, but their neural substrates are not known. We examined brain resting state connectivity in relation to declining self-reported energy levels (SEL) and occurrence of fatigue over time. METHODS We examined resting-state functional MRI in 272 community dwelling older adults participating in the Health Aging and Body Composition Study (mean age 83 years; 57.4 % female; 40.8 % Black) with measures of fatigue and SEL collected at regular intervals over the prior ten years. Functional connectivity (FC) between cortex and striatum was examined separately for sensorimotor, executive, and limbic functional subregions. Logistic regression tested the association of FC in each network with prior fatigue state (reporting fatigue at least once or never reporting fatigue), and with SEL decline (divided into stable or declining SEL groups) and adjusted for demographic, physical function, mood, cognition, and comorbidities. RESULTS Higher cortico-striatal FC in the right limbic network was associated with lower odds of reporting fatigue (better) at least once during the study period (adjusted odds ratio [95 % confidence interval], p-value: (0.747 [0.582, 0.955], 0.020), independent of SEL. Higher cortico-striatal FC in the right executive network was associated with higher odds of declining SEL (worse) during the study period (adjusted odds ratio [95 % confidence interval], p-value: (1.31 [1.01, 1.69], 0.041), independent of fatigue. Associations with other networks were not significant. CONCLUSIONS In this cohort of older adults, the cortico-striatal functional connectivity of declining SEL appears distinct from that underlying fatigue. Studies to further assess the neural correlates of energy and fatigue, and their independent contribution to neurodegenerative conditions are warranted.
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Affiliation(s)
- James B Hengenius
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rebecca Ehrenkranz
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Xiaonan Zhu
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nancy W Glynn
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Theodore J Huppert
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
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Royse SK, Snitz BE, Hengenius JB, Huppert TJ, Roush RE, Ehrenkranz RE, Wilson JD, Bertolet M, Reese AC, Cisneros G, Potopenko K, Becker JT, Cohen AD, Shaaban CE. Unhealthy white matter connectivity, cognition, and racialization in older adults. Alzheimers Dement 2024; 20:1483-1496. [PMID: 37828730 PMCID: PMC10947965 DOI: 10.1002/alz.13494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 09/06/2023] [Accepted: 09/10/2023] [Indexed: 10/14/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMH) may promote clinical Alzheimer's disease (AD) disparities between Black American (BA) and non-Hispanic White (nHW) populations. Using a novel measurement, unhealthy white matter connectivity (UWMC), we interrogated racialized group differences in associations between WMH in AD pathology-affected regions and cognition. METHODS UWMC is the proportion of white matter fibers that pass through WMH for every pair of brain regions. Individual regression models tested associations of UWMC in beta-amyloid (Aβ) or tau pathology-affected regions with cognition overall, stratified by racialized group, and with a racialized group interaction. RESULTS In 201 older adults ranging from cognitively unimpaired to AD, BA participants exhibited greater UWMC and worse cognition than nHW participants. UWMC was negatively associated with cognition in 17 and 5 Aβ- and tau-affected regions, respectively. Racialization did not modify these relationships. DISCUSSION Differential UWMC burden, not differential UWMC-and-cognition associations, may drive clinical AD disparities between racialized groups. HIGHLIGHTS Unhealthy white matter connectivity (UWMC) in Alzheimer's disease (AD) pathology-affected brain regions is associated with cognition. Relationships between UWMC and cognition are similar between Black American (BA) and non-Hispanic White (nHW) individuals. More UWMC may partially drive higher clinical AD burden in BA versus nHW populations. UWMC risk factors, particularly social and environmental, should be identified.
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Affiliation(s)
- Sarah K. Royse
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Beth E. Snitz
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - James B. Hengenius
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Theodore J. Huppert
- Department of Electrical EngineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Rebecca E. Roush
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - James D. Wilson
- Department of Mathematics and StatisticsUniversity of San FranciscoSan FranciscoCaliforniaUSA
| | - Marnie Bertolet
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of BiostatisticsUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - Geraldine Cisneros
- Department of PsychologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Katey Potopenko
- Department of PsychologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - James T. Becker
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of BiostatisticsUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Ann D. Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
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Ehrenkranz R, Zhu X, Glynn NW, Bertolet M, Berman SB, Hengenius JB, Rosano C. Longitudinal Associations Between Higher Self-Reported Energy, Gait Speed, and Cognition in Older Adults With Fatigue. J Gerontol A Biol Sci Med Sci 2023; 78:2407-2414. [PMID: 37774505 PMCID: PMC10692418 DOI: 10.1093/gerona/glad234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Older adults reporting higher energy levels have better physical function. It is not known if these associations persist among older adults reporting fatigue or if higher energy is associated with cognitive function. We examined longitudinal associations between self-reported energy, gait speed, and cognition, stratified by fatigue, in 2 613 participants (aged 74.6 ± 2.87 years) in the Health, Aging and Body Composition Study. METHODS Self-reported energy (0-10, dichotomized at median) and fatigue (present/absent) were measured at baseline. Usual and rapid-paced gait speed (m/s), modified Mini-Mental State Examination (3MS), and Digit Symbol Substitution Test (DSST) were measured at baseline and annually over 8 years. Linear mixed effect models compared changes in gait speed, 3MS, and DSST between higher and lower energy groups within fatigue strata. RESULTS At baseline, 724 participants (27%) were fatigued; 240 (33%) coreported higher energy (9% of total). The remaining 1 889 participants were fatigue-free (73%); 1 221 (65%) coreported higher energy (47% of total). Those with fatigue and higher energy had average rapid gait declines of 0.007 m/s per year (p = .04) after adjustment for demographics, comorbidities, depressive symptoms, and exercise. DSST declines were found among only fatigue-free participants (β = 0.17, p = .01). No statistically significant associations with energy were found for fatigue-free participants, or for usual gait or 3MS. CONCLUSIONS Asking about older adults' energy levels as well as fatigue may identify a subgroup of older adults protected against physical and cognitive decline, even among those with fatigue.
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Affiliation(s)
- Rebecca Ehrenkranz
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Xiaonan Zhu
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Nancy W Glynn
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Marnie Bertolet
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - James B Hengenius
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
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Hengenius JB, Bohnen NI, Rosso A, Huppert TJ, Rosano C. Cortico-striatal functional connectivity and cerebral small vessel disease: Contribution to mild Parkinsonian signs. J Neuroimaging 2022; 32:352-362. [PMID: 34957653 PMCID: PMC9119198 DOI: 10.1111/jon.12949] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 11/01/2021] [Accepted: 11/01/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND AND PURPOSE Mild Parkinsonian signs (MPS) are common in older adults. We hypothesized that MPS are associated with lower functional connectivity (FC) in dopamine-dependent cortico-striatal networks, and these associations vary with white matter hyperintensity (WMH), a risk factor for MPS. METHODS We examined resting-state functional MRI in 266 participants (mean age 83; 57% female; 41% African American) with data on MPS (Unified Parkinson's Disease Rating Scale), demographics, cognition, muscle-skeletal, and cardiometabolic health. FC between cortex and striatum was examined separately for sensorimotor, executive, and limbic functional subregions. Logistic regression tested the association of FC in each network with MPS, adjusted for covariates. Interactions of FC by WMH were tested; and analyses were repeated stratified by WMH above/below the median. RESULTS Compared to those without MPS, those with MPS had lower cortico-striatal FC in the left executive network (adjusted odds ratio [95% confidence interval], p-value: 0.188 [0.043, 0.824], .027). The interaction with WMH was p = .064; left executive FC was inversely associated with MPS for high WMH (0.077 [0.010, 0.599], .014) but not low WMH participants (1.245 [0.128, 12.132], .850). CONCLUSIONS MPS appear related to lower executive network FC, robust to adjustment for other risk factors, and stronger for those with higher burden of WMH. Future longitudinal studies should examine the interplay between cerebral small vessel disease and connectivity influencing MPS.
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Affiliation(s)
- James B. Hengenius
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Nicolaas I. Bohnen
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Andrea Rosso
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Theodore J. Huppert
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Caterina Rosano
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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Hengenius JB, Connor EG, Crimaldi JP, Urban NN, Ermentrout GB. Olfactory navigation in the real world: Simple local search strategies for turbulent environments. J Theor Biol 2021; 516:110607. [PMID: 33524405 DOI: 10.1016/j.jtbi.2021.110607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 12/30/2020] [Accepted: 01/24/2021] [Indexed: 10/22/2022]
Abstract
Olfaction informs animal navigation for foraging, social interaction, and threat evasion. However, turbulent flow on the spatial scales of most animal navigation leads to intermittent odor information and presents a challenge to simple gradient-ascent navigation. Here we present two strategies for iterative gradient estimation and navigation via olfactory cues in 2D space: tropotaxis, spatial concentration comparison (i.e., instantaneous comparison between lateral olfactory sensors on a navigating animal) and klinotaxis, spatiotemporal concentration comparison (i.e., comparison between two subsequent concentration samples as the animal moves through space). We then construct a hybrid model that uses klinotaxis but utilizes tropotactic information to guide its spatial sampling strategy. We find that for certain body geometries in which bilateral sensors are closely-spaced (e.g., mammalian nares), klinotaxis outperforms tropotaxis; for widely-spaced sensors (e.g., arthropod antennae), tropotaxis outperforms klinotaxis. We find that both navigation strategies perform well on smooth odor gradients and are robust against noisy gradients represented by stochastic odor models and real turbulent flow data. In some parameter regimes, the hybrid model outperforms klinotaxis alone, but not tropotaxis.
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Affiliation(s)
- James B Hengenius
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
| | - Erin G Connor
- Civil, Environmental and Architectural Engineering, University of Colorado at Boulder, Boulder, CO 80309, USA
| | - John P Crimaldi
- Civil, Environmental and Architectural Engineering, University of Colorado at Boulder, Boulder, CO 80309, USA
| | - Nathaniel N Urban
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - G Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, USA
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Hengenius JB, Gribskov M, Rundell AE, Umulis DM. Making models match measurements: model optimization for morphogen patterning networks. Semin Cell Dev Biol 2014; 35:109-23. [PMID: 25016297 DOI: 10.1016/j.semcdb.2014.06.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2013] [Revised: 06/17/2014] [Accepted: 06/24/2014] [Indexed: 01/13/2023]
Abstract
Mathematical modeling of developmental signaling networks has played an increasingly important role in the identification of regulatory mechanisms by providing a sandbox for hypothesis testing and experiment design. Whether these models consist of an equation with a few parameters or dozens of equations with hundreds of parameters, a prerequisite to model-based discovery is to bring simulated behavior into agreement with observed data via parameter estimation. These parameters provide insight into the system (e.g., enzymatic rate constants describe enzyme properties). Depending on the nature of the model fit desired - from qualitative (relative spatial positions of phosphorylation) to quantitative (exact agreement of spatial position and concentration of gene products) - different measures of data-model mismatch are used to estimate different parameter values, which contain different levels of usable information and/or uncertainty. To facilitate the adoption of modeling as a tool for discovery alongside other tools such as genetics, immunostaining, and biochemistry, careful consideration needs to be given to how well a model fits the available data, what the optimized parameter values mean in a biological context, and how the uncertainty in model parameters and predictions plays into experiment design. The core discussion herein pertains to the quantification of model-to-data agreement, which constitutes the first measure of a model's performance and future utility to the problem at hand. Integration of this experimental data and the appropriate choice of objective measures of data-model agreement will continue to drive modeling forward as a tool that contributes to experimental discovery. The Drosophila melanogaster gap gene system, in which model parameters are optimized against in situ immunofluorescence intensities, demonstrates the importance of error quantification, which is applicable to a wide array of developmental modeling studies.
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Affiliation(s)
- J B Hengenius
- Department of Biological Sciences, Purdue University, 247 S. Martin Jischke Drive, West Lafayette, IN 47907, United States
| | - M Gribskov
- Department of Biological Sciences, Purdue University, 247 S. Martin Jischke Drive, West Lafayette, IN 47907, United States
| | - A E Rundell
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907, United States
| | - D M Umulis
- Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Drive, West Lafayette, IN 47907, United States; Department of Agricultural and Biological Engineering, Purdue University, 225 S. University Street, West Lafayette, IN 47907, United States.
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Hengenius JB, Gribskov M, Rundell AE, Fowlkes CC, Umulis DM. Analysis of gap gene regulation in a 3D organism-scale model of the Drosophila melanogaster embryo. PLoS One 2011; 6:e26797. [PMID: 22110594 PMCID: PMC3217930 DOI: 10.1371/journal.pone.0026797] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2011] [Accepted: 10/04/2011] [Indexed: 01/30/2023] Open
Abstract
The axial bodyplan of Drosophila melanogaster is determined during a process called morphogenesis. Shortly after fertilization, maternal bicoid mRNA is translated into Bicoid (Bcd). This protein establishes a spatially graded morphogen distribution along the anterior-posterior (AP) axis of the embryo. Bcd initiates AP axis determination by triggering expression of gap genes that subsequently regulate each other's expression to form a precisely controlled spatial distribution of gene products. Reaction-diffusion models of gap gene expression on a 1D domain have previously been used to infer complex genetic regulatory network (GRN) interactions by optimizing model parameters with respect to 1D gap gene expression data. Here we construct a finite element reaction-diffusion model with a realistic 3D geometry fit to full 3D gap gene expression data. Though gap gene products exhibit dorsal-ventral asymmetries, we discover that previously inferred gap GRNs yield qualitatively correct AP distributions on the 3D domain only when DV-symmetric initial conditions are employed. Model patterning loses qualitative agreement with experimental data when we incorporate a realistic DV-asymmetric distribution of Bcd. Further, we find that geometry alone is insufficient to account for DV-asymmetries in the final gap gene distribution. Additional GRN optimization confirms that the 3D model remains sensitive to GRN parameter perturbations. Finally, we find that incorporation of 3D data in simulation and optimization does not constrain the search space or improve optimization results.
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Affiliation(s)
- James B. Hengenius
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America
| | - Michael Gribskov
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America
| | - Ann E. Rundell
- Department of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America
| | - Charless C. Fowlkes
- Department of Computer Science, University of California Irvine, Irvine, California, United States of America
| | - David M. Umulis
- Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana, United States of America
- * E-mail:
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