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Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.
Methods
T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).
Results
PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).
Conclusions
PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.
Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.
Posttraumatic stress disorder (PTSD) has been associated with advanced epigenetic age cross-sectionally, but the association between these variables over time is unclear. This study conducted meta-analyses to test whether new-onset PTSD diagnosis and changes in PTSD symptom severity over time were associated with changes in two metrics of epigenetic aging over two time points.
Methods
We conducted meta-analyses of the association between change in PTSD diagnosis and symptom severity and change in epigenetic age acceleration/deceleration (age-adjusted DNA methylation age residuals as per the Horvath and GrimAge metrics) using data from 7 military and civilian cohorts participating in the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (total N = 1,367).
Results
Meta-analysis revealed that the interaction between Time 1 (T1) Horvath age residuals and new-onset PTSD over time was significantly associated with Horvath age residuals at T2 (meta β = 0.16, meta p = 0.02, p-adj = 0.03). The interaction between T1 Horvath age residuals and changes in PTSD symptom severity over time was significantly related to Horvath age residuals at T2 (meta β = 0.24, meta p = 0.05). No associations were observed for GrimAge residuals.
Conclusions
Results indicated that individuals who developed new-onset PTSD or showed increased PTSD symptom severity over time evidenced greater epigenetic age acceleration at follow-up than would be expected based on baseline age acceleration. This suggests that PTSD may accelerate biological aging over time and highlights the need for intervention studies to determine if PTSD treatment has a beneficial effect on the aging methylome.
The nature and extent of interactions between the distant regions and cultures of Mesoamerica remain open to much debate. Close economic and political ties developed between Teotihuacan and the lowland Maya during the Early Classic period (AD 250–550), yet the relationship between these cultures continues to perplex scholars. This article presents an elaborately painted altar from an elite residential group at the lowland Maya centre of Tikal, Guatemala. Dating to the fifth century AD, the altar is unique in its display of Teotihuacan architectural and artistic forms, adding to evidence not only for cultural influence during this period, but also for an active Teotihuacan presence at Tikal.
We provide an assessment of the Infinity Two fusion pilot plant (FPP) baseline plasma physics design. Infinity Two is a four-field period, aspect ratio $A = 10$, quasi-isodynamic stellarator with improved confinement appealing to a max-$J$ approach, elevated plasma density and high magnetic fields ($ \langle B\rangle = 9$ T). Here $J$ denotes the second adiabatic invariant. At the envisioned operating point ($800$ MW deuterium-tritium (DT) fusion), the configuration has robust magnetic surfaces based on magnetohydrodynamic (MHD) equilibrium calculations and is stable to both local and global MHD instabilities. The configuration has excellent confinement properties with small neoclassical transport and low bootstrap current ($|I_{bootstrap}| \sim 2$ kA). Calculations of collisional alpha-particle confinement in a DT FPP scenario show small energy losses to the first wall (${\lt}1.5 \,\%$) and stable energetic particle/Alfvén eigenmodes at high ion density. Low turbulent transport is produced using a combination of density profile control consistent with pellet fueling and reduced stiffness to turbulent transport via three-dimensional shaping. Transport simulations with the T3D-GX-SFINCS code suite with self-consistent turbulent and neoclassical transport predict that the DT fusion power$P_{{fus}}=800$ MW operating point is attainable with high fusion gain ($Q=40$) at volume-averaged electron densities $n_e\approx 2 \times 10^{20}$ m$^{-3}$, below the Sudo density limit. Additional transport calculations show that an ignited ($Q=\infty$) solution is available at slightly higher density ($2.2 \times 10^{20}$ m$^{-3}$) with $P_{{fus}}=1.5$ GW. The magnetic configuration is defined by a magnetic coil set with sufficient room for an island divertor, shielding and blanket solutions with tritium breeding ratios (TBR) above unity. An optimistic estimate for the gas-cooled solid breeder designed helium-cooled pebble bed is TBR $\sim 1.3$. Infinity Two satisfies the physics requirements of a stellarator fusion pilot plant.
Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).
Aims
We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.
Method
Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.
Results
Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.
Conclusions
We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.
We sought to compare whether quality of life (QOL) in patients with subjective cognitive impairment (SCI) who performed normally on a neuropsychological battery significantly differed from those diagnosed with mild cognitive impairment (MCI), Alzheimer’s disease (AD) or non-Alzheimer’s dementia (non-AD) at initial assessment in a Rural and Remote Memory Clinic (RRMC).
Methods:
610 patients referred to our RRMC between 2004 and 2019 were included in this study. We compared self-reported and caregiver-reported patient QOL scores in those with SCI (n = 166) to those diagnosed with MCI (n = 98), AD (n = 228) and non-AD (n = 118).
Results:
Patients with SCI self-reported significantly lower QOL compared to patients with AD. Interestingly, the reverse was seen in caregivers: SCI caregivers rated patient QOL higher than AD caregivers. Patients with SCI also reported lower QOL than patients with MCI. SCI caregivers reported higher patient QOL than their non-AD counterparts. Caregiver-rated patient QOL was higher in those with MCI compared to AD. Patients with MCI self-reported higher QOL scores compared to patients with non-AD dementias. Similarly, MCI caregivers reported higher patient QOL than non-AD caregivers. No other comparisons were statistically significant.
Conclusion:
Although they lacked clinically significant cognitive deficits, patients with SCI self-reported significantly lower QOL than patients with MCI and AD. Conversely, caregiver-reported patient QOL was higher for patients with SCI than for patients with AD and non-AD. This shows that SCI seriously impacts QOL. More research is needed on how we can better support patients with SCI to improve their QOL.
Flowering rush (Butomus umbellatus L.) is an emergent perennial monocot that has invaded aquatic systems along the U.S.–Canadian border. Currently, there are two known cytotypes of flowering rush, diploid and triploid, within the invaded range. Although most studies have focused on the triploid cytotype, little information is known about diploid plants. Therefore, phenology and resource allocation were studied on the diploid cytotype of flowering rush in three study sites (Mentor Marsh, OH; Tonawanda Wildlife Management Area, NY; and Unity Island, NY) to understand seasonal resource allocation and environmental influences on growth, and to optimize management strategies. Samples were harvested once a month from May to November at each site from 2021 to 2023. Plant metrics were regressed to air temperature, water temperature, and water depth. Aboveground biomass peaked from July to September and comprised 50% to 70% of total biomass. Rhizome biomass peaked from September to November and comprised 40% to 50% of total biomass. Rhizome bulbil densities peaked from September to November at 3,000 to 16,000 rhizome bulbils m−2. Regression analysis resulted in strong negative relationships between rhizome starch content and air temperature (r2 = 0.52) and water temperature (r2 = 46). Other significant, though weak, relationships were found, including a positive relationship between aboveground biomass and air temperature (r2 = 0.17), a negative relationship between rhizome bulbil biomass and air temperature (r2 = 0.18) and a positive relationship between leaf density and air temperature (r2 = 0.17). Rhizomes and rhizome bulbils combined stored up to 60% of total starch, and therefore, present a unique challenge to management, as these structures cannot be reached directly with herbicides. Therefore, management should target the aboveground tissue before peak production (July) to reduce internal starch storage and aim to limit regrowth over several years.
Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.
Methods
We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.
Results
The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).
Conclusion
The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.
The authors report on ancient DNA data from two human skeletons buried within the chancel of the 1608–1616 church at the North American colonial settlement of Jamestown, Virginia. Available archaeological, osteological and documentary evidence suggest that these individuals are Sir Ferdinando Wenman and Captain William West, kinsmen of the colony's first Governor, Thomas West, Third Baron De La Warr. Genomic analyses of the skeletons identify unexpected maternal relatedness as both carried the mitochondrial haplogroup H10e. In this unusual case, aDNA prompted further historical research that led to the discovery of illegitimacy in the West family, an aspect of identity omitted, likely intentionally, from genealogical records.
This study compared the likelihood of long-term sequelae following infection with SARS-CoV-2 variants, other acute respiratory infections (ARIs) and non-infected individuals. Participants (n=5,630) were drawn from Virus Watch, a prospective community cohort investigating SARS-CoV-2 epidemiology in England. Using logistic regression, we compared predicted probabilities of developing long-term symptoms (>2 months) during different variant dominance periods according to infection status (SARS-CoV-2, other ARI, or no infection), adjusting for confounding by demographic and clinical factors and vaccination status. SARS-CoV-2 infection during early variant periods up to Omicron BA.1 was associated with greater probability of long-term sequalae (adjusted predicted probability (PP) range 0.27, 95% CI = 0.22–0.33 to 0.34, 95% CI = 0.25–0.43) compared with later Omicron sub-variants (PP range 0.11, 95% CI 0.08–0.15 to 0.14, 95% CI 0.10–0.18). While differences between SARS-CoV-2 and other ARIs (PP range 0.08, 95% CI 0.04–0.11 to 0.23, 95% CI 0.18–0.28) varied by period, all post-infection estimates substantially exceeded those for non-infected participants (PP range 0.01, 95% CI 0.00, 0.02 to 0.03, 95% CI 0.01–0.06). Variant was an important predictor of SARS-CoV-2 post-infection sequalae, with recent Omicron sub-variants demonstrating similar probabilities to other contemporaneous ARIs. Further aetiological investigation including between-pathogen comparison is recommended.
Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers).
Methods
Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs).
Results
Smoking (HRs range 1.04–1.10) and physical inactivity (HRs range 1.01–1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03–1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01).
Conclusions
Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.
We report the discovery of a bow-shock pulsar wind nebula (PWN), named Potoroo, and the detection of a young pulsar J1638$-$4713 that powers the nebula. We present a radio continuum study of the PWN based on 20-cm observations obtained from the Australian Square Kilometre Array Pathfinder (ASKAP) and MeerKAT. PSR J1638$-$4713 was identified using Parkes radio telescope observations at frequencies above 3 GHz. The pulsar has the second-highest dispersion measure of all known radio pulsars (1 553 pc cm$^{-3}$), a spin period of 65.74 ms and a spin-down luminosity of $\dot{E}=6.1\times10^{36}$ erg s$^{-1}$. The PWN has a cometary morphology and one of the greatest projected lengths among all the observed pulsar radio tails, measuring over 21 pc for an assumed distance of 10 kpc. The remarkably long tail and atypically steep radio spectral index are attributed to the interplay of a supernova reverse shock and the PWN. The originating supernova remnant is not known so far. We estimated the pulsar kick velocity to be in the range of 1 000–2 000 km s$^{-1}$ for ages between 23 and 10 kyr. The X-ray counterpart found in Chandra data, CXOU J163802.6$-$471358, shows the same tail morphology as the radio source but is shorter by a factor of 10. The peak of the X-ray emission is offset from the peak of the radio total intensity (Stokes $\rm I$) emission by approximately 4.7$^{\prime\prime}$, but coincides well with circularly polarised (Stokes $\rm V$) emission. No infrared counterpart was found.
Clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) for treatment of treatment-resistant depression (TRD) vary widely and there is no mood rating scale that is standard for assessing rTMS outcome. It remains unclear whether TMS is as efficacious in older adults with late-life depression (LLD) compared to younger adults with major depressive disorder (MDD). This study examined the effect of age on outcomes of rTMS treatment of adults with TRD. Self-report and observer mood ratings were measured weekly in 687 subjects ages 16–100 years undergoing rTMS treatment using the Inventory of Depressive Symptomatology 30-item Self-Report (IDS-SR), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item, and Hamilton Depression Rating Scale 17-item (HDRS). All rating scales detected significant improvement with treatment; response and remission rates varied by scale but not by age (response/remission ≥ 60: 38%–57%/25%–33%; <60: 32%–49%/18%–25%). Proportional hazards models showed early improvement predicted later improvement across ages, though early improvements in PHQ and HDRS were more predictive of remission in those < 60 years (relative to those ≥ 60) and greater baseline IDS burden was more predictive of non-remission in those ≥ 60 years (relative to those < 60). These results indicate there is no significant effect of age on treatment outcomes in rTMS for TRD, though rating instruments may differ in assessment of symptom burden between younger and older adults during treatment.
Cognitive training is a non-pharmacological intervention aimed at improving cognitive function across a single or multiple domains. Although the underlying mechanisms of cognitive training and transfer effects are not well-characterized, cognitive training has been thought to facilitate neural plasticity to enhance cognitive performance. Indeed, the Scaffolding Theory of Aging and Cognition (STAC) proposes that cognitive training may enhance the ability to engage in compensatory scaffolding to meet task demands and maintain cognitive performance. We therefore evaluated the effects of cognitive training on working memory performance in older adults without dementia. This study will help begin to elucidate non-pharmacological intervention effects on compensatory scaffolding in older adults.
Participants and Methods:
48 participants were recruited for a Phase III randomized clinical trial (Augmenting Cognitive Training in Older Adults [ACT]; NIH R01AG054077) conducted at the University of Florida and University of Arizona. Participants across sites were randomly assigned to complete cognitive training (n=25) or an education training control condition (n=23). Cognitive training and the education training control condition were each completed during 60 sessions over 12 weeks for 40 hours total. The education training control condition involved viewing educational videos produced by the National Geographic Channel. Cognitive training was completed using the Posit Science Brain HQ training program, which included 8 cognitive training paradigms targeting attention/processing speed and working memory. All participants also completed demographic questionnaires, cognitive testing, and an fMRI 2-back task at baseline and at 12-weeks following cognitive training.
Results:
Repeated measures analysis of covariance (ANCOVA), adjusted for training adherence, transcranial direct current stimulation (tDCS) condition, age, sex, years of education, and Wechsler Test of Adult Reading (WTAR) raw score, revealed a significant 2-back by training group interaction (F[1,40]=6.201, p=.017, η2=.134). Examination of simple main effects revealed baseline differences in 2-back performance (F[1,40]=.568, p=.455, η2=.014). After controlling for baseline performance, training group differences in 2-back performance was no longer statistically significant (F[1,40]=1.382, p=.247, η2=.034).
Conclusions:
After adjusting for baseline performance differences, there were no significant training group differences in 2-back performance, suggesting that the randomization was not sufficient to ensure adequate distribution of participants across groups. Results may indicate that cognitive training alone is not sufficient for significant improvement in working memory performance on a near transfer task. Additional improvement may occur with the next phase of this clinical trial, such that tDCS augments the effects of cognitive training and results in enhanced compensatory scaffolding even within this high performing cohort. Limitations of the study include a highly educated sample with higher literacy levels and the small sample size was not powered for transfer effects analysis. Future analyses will include evaluation of the combined intervention effects of a cognitive training and tDCS on nback performance in a larger sample of older adults without dementia.
Community reintegration and participation have been shown to be significantly correlated to improved Quality of Life (QoL) following moderate to severe traumatic brain injury (msTBI), yet these models often come with significant levels of unaccounted variability (Pierce and Hanks, 2006). Measures for community participation frequently employ objective measures of participation, such as number of outings in a week or current employment status (Migliorini et al., 2016), which may not adequately account for lifestyle differences, especially in aging populations. Less often integrated are subjective measures of an individual’s own belongingness and autonomy within the community (Heineman et al., 2011), also referred to as their participation enfranchisement (PE). The present study examines three questions pertinent to the potential clinical value of PE. First, do measures of objective participation significantly predict an individual’s PE ratings? Second, are both types of measures equally successful predictors of QoL for aging individuals with chronic-stage msTBI. Finally, would controlling for either objective or subjective integration ratings enable neurocognitive assessments to better predict QoL post injury?
Participants and Methods:
41 older-adults (M= 65.32; SD= 7.51) with a history of msTBI were included (M= 12.59 years post-injury;SD= 8.29) for analysis. Subjective community integration was measured through the Participation Enfranchisement Survey. The Participation Assessment with Recombined Tools-Objective (PART-O) provided the objective measurement of participation. Quality of life was assessed through the Quality of Life after Brain Injury (QOLIBRI). An estimate of neurocognitive performance was created through the Brief Test of Adult Cognition by Telephone (BTACT), which includes six domains including: verbal-learning and memory (immediate and delayed recall), working memory (digit-span backwards), reasoning (number sequencing), semantic fluency (category fluency), and processing speed (backwards counting). Performance on the BTACT, PE ratings, and PART-O scores were included as the dependent variables in stepwise, linear regression models predicting QoL ratings to assess the differential contribution of the dependent variables and potential interaction effects.
Results:
While both the PART-O (f(1,39)=5.52;p=.024,n2=.124) and the PE survey (f(1,39)=14.31 ;p<.001,n2=.268) significantly predicted QoL, the addition of PE in the PART-O model resulted in significant (20.9%) reduction in unaccounted variance. Further in the model controlling for PE, PART-O no longer provides a significant (p=.15) contribution to the model estimating QoL (f(2,38)=8.41; p=.001). Performance on the BTACT correlated with PART-O (p<.0001), but not PE (p=.13) ratings. Finally, across two models controlling for BTACT performance, PE (p=.002,partial n2=.23), but not PART-O (p=.28,partial n2=.031) contributed significantly to QoL predictions. No significant interactions between PART-O, PE, and/or BTACT were observed when added to any model.
Conclusions:
MsTBI impacts nearly every facet of an individual’s life, and as such, improving QoL post-injury requires a broad, yet well-considered approach. The objective ratings of participation, subjective PE, BTACT performance, all independently predicted quality of life in this sample. However, after controlling for neurocognitive assessment performance, PE was shown to independently contribute to quality of life, while the PART-O ratings no longer provided significant contribution. While community integration is a vital factor to consider for long-term rehabilitation, tailoring what “integration” means to the patient may hold significant potential to improve long-term quality of life.
Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.
Participants and Methods:
This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.
Results:
The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).
Conclusions:
Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.
Cognitively healthy individuals who complete a neuropsychological test battery can obtain very low scores. These very low scores are not likely indicative of cognitive impairment but are rather considered spuriously low scores. The expected number of low scores varies based on number and type of neuropsychological tests. Typically, base rates have been determined from normative samples, which could differ from samples seen in clinical settings. The current study reports on base rates of spuriously low cognitive scores in older adults presenting to a memory clinic who were diagnosed with subjective cognitive impairment after interprofessional assessment and information from collateral informants ruled out objective cognitive impairment.
Participants and Methods:
Base rates of spuriously low scores for a neuropsychological battery of 12 scores were based on 92 cognitively healthy older adults presenting to a specialist memory clinic (M(age) = 61.00, SD = 12.00; M(edu) = 12.00, SD = 2.74). Crawford’s Monte Carlo simulation algorithm was used to estimate multivariate base rates by calculating the percentage of cognitively healthy memory clinic patients who produced age and education normed scores at or below the 5th percentile. The following tests were used to produce the 12 scores: block design, digit span backwards, and coding from the WAIS-IV; logical memory I and II from the WMS-IV; immediate and delayed memory scores from the California Verbal Learning Test Second Edition short form; immediate and delayed memory scores from the Brief Visuospatial Memory Test Revised; category switching, letter number sequencing, and inhibition switching from the Delis Kaplin Executive Functioning System.
Results:
An estimated 33.58% of the cognitively healthy memory clinic population would have one or more low scores (5th percentile cutoff),14.7% would have two or more low scores, 6.55% would have three or more, 2.94% would have four or more, and 1.31% percent would have 5 or more very low scores due to chance.
Conclusions:
Determining base rates of spuriously low scores on a neuropsychological battery in a clinical sample of referred older adults with subjective memory complaints could assist in the diagnostic process. By understanding base rates of clinical samples, clinicians can use empirical data to adjust for expected low scores rather than using conventional corrections (such as 1/20 test scores expected to be low). In a memory clinic sample, three or more low test scores out of 12 is expected to be relatively rare in those who were later determined to have no objective evidence of cognitive impairment based on interprofessional assessment. Understanding normal frequency of low scores will prevent undue conclusions of cognitive impairment which will minimize false positives in diagnosis.