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Porges, E. C.

Publications and source records attributed to Porges, E. C..

8 recordsLinked to original sources

Your Brain Doesn't Look a Day Past 70! Cross-Sectional Associations with Brain-Predicted Age in the Cognitively-Intact Oldest-Old

The cognitively-intact oldest-old (85+) may be the most-resilient members of their birth cohort; due to survivorship effects (e.g., depletion of susceptibles), risk factors associated with brain aging biomarkers in younger samples may not generalize to the oldest-old. We evaluated associations between established aging-related risk factors and brain-predicted age difference (brainPAD) in a cross-sectional cognitively-intact oldest-old sample. Additionally, we evaluated brainPAD-cognition associations to characterize brain maintenance vs. cognitive reserve in our sample. Oldest-old adults (N = 206; 85-99 years; MoCA > 22 or neurologist evaluation) underwent T1-weighted MRI; brainPAD was generated with brainageR, such that more-positive brainPAD reflected relatively advanced brain aging. Sex, educational attainment, alcohol and smoking history, exercise history, BMI, cardiovascular and metabolic disease history, and anticholinergic medication burden were self-reported. Global cognitive z-score and coefficient of variation were derived from the NACC UDS 3.0 cognitive battery; crystallized-fluid discrepancy was derived from the NIH Toolbox Cognitive Battery. Mean brainPAD was -7.99 (SD: 5.37; range: -24.50, 6.03). Women showed more-delayed brain aging than men (B = -2.35, 95% CI = - 4.28, -0.41, p = 0.018). No other exposures were associated with brainPAD. BrainPAD was not associated with any cognitive variable. These findings suggest that cognitively-intact oldest-old adults may be atypically-resistant to risk factors associated with aging in younger samples, consistent with survivorship effects in aging. Furthermore, brainPAD may have limited explanatory value for cognitive performance in cognitively-intact oldest-old adults, potentially due to high cognitive reserve. Overall, our findings highlight the impact of survivorship effects on brain aging research. HighlightsO_LIBrain-predicted age difference was assessed in cognitively-intact oldest-old ([≥]85) C_LIO_LIMean brain-predicted age corresponded to an 8-year delay in brain aging C_LIO_LIBrain age in oldest-old was not associated with self-reported health history C_LIO_LIBrain age was not associated with cognitive performance C_LI

neuroscience↗

Age dependency of neurometabolite T1 relaxation times

PurposeTo measure T1 relaxation times of metabolites at 3T in a healthy aging population and investigate age dependence. MethodsA cohort of 101 healthy adults were recruited with approximately 10 male and 10 female participants in each decade band: 18-29, 30-39, 40-49, 50-59, and 60+ years old. Inversion-recovery PRESS data (TE/TR: 30/2000 ms) were acquired at 8 inversion times (TIs) (300, 400, 511, 637, 780, 947, 1148 and 1400 ms) from voxels in white-matter-rich centrum semiovale (CSO) and gray-matter-rich posterior cingulate cortex (PCC). Modeling of TI-series spectra was performed in Osprey 2.5.0. Quantified metabolite amplitudes for total N-acetylaspartate (tNAA2.0), total creatine at 3.0 ppm (tCr3.0) and 3.9 ppm (tCr3.9), total choline (tCho), myo-inositol (mI), and the sum of glutamine and glutamate (Glx) were modeled to calculate T1 relaxation times of metabolites. ResultsT1 relaxation times of tNAA2.0 in CSO and tNAA2.0, tCr3.0, mI and Glx in PCC decreased with age. These correlations remained significant when controlling for cortical atrophy. T1 relaxation times were significantly different between PCC and CSO for all metabolites except tCr3.0. We also propose linear models for predicting metabolite T1s at 3T to be used in future aging studies. ConclusionMetabolite T1 relaxation times change significantly with age, an effect that will be important to consider for accurate quantitative MRS, particularly in studies of aging.

neuroscience↗

Metabolite T2 relaxation times decrease across the adult lifespan in a large multi-site cohort

PurposeRelaxation correction is crucial for accurately estimating metabolite concentrations measured using in vivo magnetic resonance spectroscopy (MRS). However, the majority of MRS quantification routines assume that relaxation values remain constant across the lifespan, despite prior evidence of T2 changes with aging for multiple of the major metabolites. Here, we comprehensively investigate correlations between T2 and age in a large, multi-site cohort. MethodsWe recruited approximately 10 male and 10 female participants from each decade of life: 18-29, 30-39, 40-49, 50-59, and 60+ years old (n=101 total). We collected PRESS data at 8 TEs (30, 50, 74, 101, 135, 179, 241, and 350 ms) from voxels placed in white-matter-rich centrum semiovale (CSO) and gray-matter-rich posterior cingulate cortex (PCC). We quantified metabolite amplitudes using Osprey and fit exponential decay curves to estimate T2. ResultsOlder age was correlated with shorter T2 for tNAA, tCr3.0, tCr3.9, tCho, Glx, and tissue water in CSO and PCC; rs = -0.21 to -0.65, all p<0.05, FDR-corrected for multiple comparisons. These associations remained statistically significant when controlling for cortical atrophy. T2 values did not differ across the adult lifespan for mI. By region, T2 values were longer in the CSO for tNAA, tCr3.0, tCr3.9, Glx, and tissue water and longer in the PCC for tCho and mI. ConclusionThese findings underscore the importance of considering metabolite T2 changes with aging in MRS quantification. We suggest that future 3T work utilize the equations presented here to estimate age-specific T2 values instead of relying on uniform default values.

neuroscience↗

"Surviving and Thriving": Evidence for Cortical GABA Stabilization in Cognitively-Intact Oldest-Old Adults

Cortical GABA levels are reduced in older age; age-related differences in GABA may be associated with age-related cognitive change. The nature of age-related GABA differences in the highest-functioning stratum of the oldest-old (85+) population is not yet known. We extend our previously-reported Individual Participant Data Meta-Analysis of GABA levels (Porges et al., 2021) across the lifespan with four novel datasets sampling the cognitively-intact oldest-old. The slope of age-related GABA differences in cognitively-intact oldest-old adults flattens after roughly age 80. We interpret these findings as an effect of survivorship: inclusion in the study required intact cognition, and too great a reduction of GABA levels may not be compatible with neurophysiological function needed for intact cognition. This work contributes to a growing body of evidence suggesting that successful cognitive aging may require intact GABAergic function, as well as further characterizing successful aging amongst oldest-old adults.

neuroscience↗

The Macromolecular MR Spectrum in Healthy Aging

PurposeMobile macromolecules (MMs) from amino acids, cytosolic proteins and mobile lipids contribute a significant spectral background underlying the metabolite signals in the MR spectrum. A recent consensus recommends that MM contributions should be removed or included in modeling basis sets for determination of metabolite concentrations and/or metabolite ratios. The purpose of this study was to acquire the MM spectrum from healthy participants at a range of ages, and to investigate changes in the signals with age and sex groups. MethodsInversion time (TI) series were acquired to determine an optimal inversion time to null the metabolite signals. Experiments were carried out using a single adiabatic hyperbolic-secant inversion pulse. After the preliminary experiment, 102 volunteers (49M/53F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). The protocol consisted of a T1-weighted MPRAGE for structural images, followed by PRESS localization using a voxel size of 30 x 26 x 26 mm3 with pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled using a reduced basis set (NAA, Cr, Cho, Glu) and a flexible spline baseline (0.1 ppm knot spacing) followed by subtraction of the modeled metabolite signals to yield a clean MM spectrum, using the Osprey software. Pearsons correlation coefficient was calculated between integrals and age for the 14 MM signals between 0.9-4.2 ppm. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes. Relationships between brain tissues with age and sex groups were also measured. ResultsMM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM integrals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > 0.004). No differences were observed between sex groups. The voxels were segmented as 80 {+/-} 4% white matter, 18 {+/-} 4% gray matter, and 2 {+/-} 1% CSF for CSO and 28 {+/-} 4% white matter, 61 {+/-} 4% gray matter and 11 {+/-} 1% CSF for PCC. WM and GM showed a significant (p < 0.05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions. ConclusionOur findings indicate that the MM spectrum is stable across a large age range and between sexes, suggesting a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups. HighlightsO_LIA large publicly available MM-aging dataset is presented. C_LIO_LIMacromolecule signals do not change with age between 20 and 70. C_LIO_LIThere is no sex difference for macromolecule integrals. C_LI

bioengineering↗

In Vivo Brain Glutathione is Higher in Older Age and Correlates with Mobility

Brain markers of oxidative damage increase with advancing age. In response, brain antioxidant levels may also increase with age, although this has not been well investigated. Here we used edited magnetic resonance spectroscopy to quantify endogenous levels of glutathione (GSH, one of the most abundant brain antioxidants) in 37 young (mean: 21.8 (2.5) years; 19 F) and 23 older adults (mean: 72.8 (8.9) years; 19 F). Accounting for age-related atrophy, we identified higher frontal and sensorimotor GSH levels for the older compared to the younger adults. For the older adults only, higher sensorimotor (but not frontal) GSH was correlated with poorer balance, gait, and manual dexterity. This suggests a regionally-specific relationship between higher brain oxidative stress levels and motor performance declines with age. We suggest these findings reflect a compensatory upregulation of GSH in response to increasing brain oxidative stress with normal aging. Together, these results provide insight into age differences in brain antioxidant levels and implications for motor function.

neuroscience↗

The trajectory of cortical GABA levels across thelifespan: An individual participant datameta-analysis of edited MRS studies

GABA is the principal inhibitory neurotransmitter in the human brain and can be measured with Magnetic Resonance Spectroscopy (MRS). Conflicting accounts report decreases and increases in cortical GABA levels across the lifespan. This incompatibility may be an artifact of the size and age-range of the samples utilized in these studies. No single study to date has included the entire lifespan. In this study, 8 suitable datasets were integrated to generate a model of the trajectory of GABA across the lifespan. Data were fit using both a log-normal curve and a nonparametric spline as regression models using a multi-level Bayesian model utilizing the Stan language. Integrated data show the lifespan trajectory of GABA involves an early period of rapid increase, followed by a period of stability during early adulthood, with a gradual decrease during adulthood and aging that is described well by both spline and log-normal models. The information gained will provide a general framework to inform expectations of future studies based on the age of the population being studied.

neuroscience↗

Smaller limbic structures are associated with greater immunosuppression in over 1000 HIV-infected adults across five continents: Findings from the ENIGMA-HIV Working Group

BackgroundHuman immunodeficiency virus type-1 (HIV) infection can be controlled with combination antiretroviral therapy (cART), but neurocognitive impairment remains common even in chronic and treated HIV-infected (HIV+) cohorts. Identifying the neuroanatomical pathways associated with infection has the potential to delineate novel neuropathological processes underlying persisting deficits, yet individual neuroimaging studies have yielded inconsistent findings. The ENIGMA-HIV Working Group was established to harmonize data from diverse studies to identify the common effects of HIV-infection on brain structure.\n\nMethodsData were pooled from 12 independent neuroHIV studies from Africa, Asia, Australia, Europe, and North America. Volume estimates for eight subcortical brain regions were extracted from T1-weighted MRI from 1,044 HIV+ adults (aged 22-81 years; 72.4% on cART; 70.3% male; 41.6% with detectable viral load (dVL)), to identify associations with plasma markers reflecting current immunosuppression (CD4+ T-cell count) or dVL. Follow-up analyses stratified data by cART status and sex. Bonferroni correction was used to determine statistical significance.\n\nFindingsLower current CD4+ count was associated with smaller hippocampal ({beta} = 20.3 mm3 per 100 cells/mm3; p = 0.0001) and thalamic volumes ({beta} = 29.3; p = 0.003); in the subset of participants not on cART, it was associated with smaller putamen volumes ({beta} = 65.1; p = 0.0009). On average, a dVL was associated with smaller hippocampal (Cohens d = 0.24; p = 0.0003) and amygdala volumes (d = 0.18; p = 0.0058).\n\nInterpretationIn HIV+ individuals across five continents, smaller limbic volumes were consistently associated with current plasma markers. As we assessed cohorts with different inclusion/exclusion criteria and demographic distributions, these deficits may represent a generalizable brain-signature of HIV infection in the cART era. Our findings support the importance of achieving viral suppression and immune restoration for maintaining brain health.\n\nFundingThis work was supported, in part, by NIH grant U54 EB020403.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSHIV type-1 infection can be managed with antiretroviral therapy, however neurocognitive impairment persists even in treated HIV+ individuals. Given the challenges associated with standardized cognitive testing, there is a need to identify quantitative markers of central nervous system impairment. A number of neuroimaging studies have reported brain abnormalities in HIV-infected patients; however, prior studies investigating associations between CD4+ T-cell count or HIV viral load and subcortical brain volume report variable effect sizes and regional distributions of effects, limiting the generalizability of the conclusions drawn to date. We have conducted a literature search for reports in English language journals published until June 2019, using the following search terms: HIV AND subcortical AND neuroimaging AND brain AND viral load AND RNA AND CD4. After removing studies that were not applicable, there were 30 studies investigating CD4+ T-cell count and viral load associations with subcortical brain structure.\n\nAdded value of the studyThe aim of the current study was to investigate structural brain associations with two biomarkers universally used to monitor immune function and treatment response, namely plasma RNA viral load and CD4+ T-cell counts. Prior analyses have been performed in smaller, heterogeneous cohorts, but by combining data across cohorts, we can identify consistent associations between brain volume and indicators of HIV infection across cohorts. The ENIGMA-HIV Working Group was established to identify common neurobiological signatures of the HIV-infected brain by harmonizing data analysis from HIV neuroimaging studies worldwide. The value of this dataset is that it is well-powered and representative of many HIV+ people living in the cART era.\n\nImplications of all the available evidenceOur results provide robust evidence that despite demographic and clinical heterogeneity among HIV-infected individuals, brain abnormalities are consistently linked to HIV viral load and immunosuppression. This supports the importance of achieving viral suppression and immune system restoration in maintaining brain health in people living with HIV. The vulnerability of limbic regions, found in this study, extends beyond the classically implicated regions of the basal ganglia; this suggests that these regions remain an important target of cART era HIV research, especially given their heightened vulnerability to age-associated atrophy and neurodegeneration.

neuroscience↗