Citations

AbstractBackgroundAutomated face recognition can potentially re‐identify de‐identified research brain MRI, PET, and CT, and direct differences of brain measurements from original and de‐faced images are statistically significant but very minor, i.e. below scan‐rescan differences. Their effects on analyses correlating brain imaging biomarkers with clinical variables remain unknown.MethodWe sampled 3 age‐and‐sex‐matched groups (CU, MCI, and clinical AD) from Mayo Clinic aging studies, each with 61 participants with same‐visit 3D T1‐weighted and 3D T2‐FLAIR MRI, PiB amyloid PET, and Flortaucipir tau PET (total n = 183). We automatically measured hippocampal volume, PIB global SUVR, and tau temporal meta‐ROI SUVR using a) our in‐house pipeline with SPM12, MCALT, and ANTs, and b) FreeSurfer 7.3.2 (PETSurfer), and we measured voxels associated with clinical group separation using SPM12. We also measured WMH from FLAIR using a) our in‐house pipeline, b) Lesion Segmentation Tool (LST), and c) FreeSurfer’s Samseg. For each measurement, we calculated pair‐wise group separation AUC values and Spearman’s rho with age and CDR‐SOB. We then de‐faced all PET and MRI using mri_reface, our top‐performing automated de‐facing software that replaces imaged faces with an average face (“re‐facing”), and we repeated all measurements and analyses with de‐faced images. We then compared the magnitudes of clinical correlations with original images and those of de‐faced images.ResultAnalyses of original and de‐faced images had very high agreement. Only 2/55 paired comparisons were significant (Tables 1‐2): FreeSurfer‐measured global PIB SUVR from de‐faced images was more correlated with age (rho 0.003 vs ‐0.227, p = 0.046), and Mayo‐measured WMH volume from original images was more correlated with CDR‐SOB (rho 0.321 vs 0.308, p = 0.020). Another comparison‐pair tested p = 0.041 for an AUC change +0.008, which we consider not practically meaningful. All others had p>0.05. In voxel‐based analyses of CU vs AD participants, all comparisons were qualitatively similar between original and de‐faced variants (Figure 1).ConclusionDe‐facing PET and MRI using mri_reface did not significantly affect 53/55 correlations between imaging and clinical variables; of the two affected, one became stronger with re‐faced images. Stronger correlations with clinical variables may be explained by de‐facing’s standardizing face voxels and artifacts that irrelevantly affect brain segmentations.

AbstractBackgroundHigher blood pressure (BP) is associated with greater white matter hyperintensity (WMH) volume, but research is limited in recently menopausal and postmenopausal women. Postmenopausal women have a greater burden of WMH than men and premenopausal women, but whether hormone therapy (HT) modifies the association between systolic and diastolic BP (SBP, DBP) and WMH is unknown. We investigated the association of SBP and DBP in recently postmenopausal women who participated in an HT trial with WMH volumes measured 14 years later and explored whether HT modified the results.MethodWomen with good cardiovascular (CV) health, who were previously enrolled in a randomized placebo‐controlled HT trial, the Kronos Early Estrogen Prevention Study (KEEPS), participated in the current observational KEEPS continuation (n = 212; median age = 67; range 58‐72). SBP and DBP were measured at KEEPS baseline (median age = 54 years; range 44‐59) and continuation. Antihypertensive users were excluded (baseline, n = 34; continuation, n = 61). Approximately 10 years after the end of KEEPS HT versus placebo 4‐year interventions, automated WMH volumes were measured from 3D‐FLAIR MRI. Associations of KEEPS baseline and continuation SBP and DBP with log WMH volume at KEEPS continuation were tested using linear regression analyses adjusting for covariates in model 1 (age, total intracranial volume, study site) and model 2 (model 1 plus cardiovascular risk factors (CVRF)).ResultHigher KEEPS baseline SBP and DBP were associated with greater WMH volume measured 14 years later, and after adjusting for CVRF (p = 0.01). Similarly, in KEEPS continuation, higher SBP and DBP were associated with greater WMH volume measured concurrently and after adjusting for CVRF (p<0.001). We did not find statistically significant evidence that HT versus placebo modified these associations. Topographically, higher SBP and DBP were associated with greater periventricular WMH in the frontal and parietal lobes after adjusting for age (Figure).ConclusionHigher SBP and DBP in recently menopausal women with good CV health were associated with greater WMH volumes more than a decade later after adjusting for CVRF, independent of randomization to HT. Our results show the importance of blood pressure control in recently menopausal women, that may reduce the white matter injury later in life.

AbstractBackgroundDisruption of default mode network (DMN) connectivity is common in Alzheimer’s disease. We investigated cross‐sectional and one‐year longitudinal changes in DMN sub‐systems in atypical clinical presentations of AD, in relation to age and tau.MethodSixty‐four amyloid‐positive atypical AD (Aty‐AD) patients diagnosed with posterior cortical atrophy (n = 35) or logopenic progressive aphasia (n = 29) were recruited by the Neurodegenerative Research Group. Patients underwent structural and resting‐state functional MRI, and [18F]flortaucipir PET at baseline and one‐year follow‐up. 140 amyloid‐negative cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging were included as controls. Global tau SUVR was calculated in a meta‐ROI including parietal, temporal, and occipital regions. DMN connectivity was calculated in native space for posterior (pDMN), ventral (vDMN), anterior ventral (avDMN) and anterior dorsal (adDMN) DMN sub‐systems using the dual regression method. A global measure of DMN connectivity, the Network Failure Quotient (NFQ), was calculated as (vDMN_to_pDMN+ adDMN_to_pDMN)/(pDMN+vDMN). Linear mixed‐effects models were computed for each DMN connectivity measure, including diagnosis (Aty‐AD, CU), age, time and their interaction, and a per‐person random effect. SPM paired t‐tests were run to compare baseline and follow‐up images in Aty‐AD and CU separately. Linear mixed‐effect models were run in the Aty‐AD cohort only to investigate the effect of global baseline tau SUVR on each DMN connectivity measure.ResultMixed‐effects models showed evidence of lower cross‐sectional pDMN and higher adDMN connectivity in Aty‐AD relative to CU, with no significant time effects (Fig. 1). While connectivity in all DMN sub‐systems declined with age in CU, connectivity was higher in older Aty‐AD patients relative to younger, particularly in vDMN and pDMN. A similar trend was observed for NFQ, which was significantly higher in Aty‐AD, with a negative age effect (Fig. 1). In Aty‐AD, voxel‐based analyses showed moderate evidence of decline in vDMN connectivity and increase in avDMN connectivity over time (Fig. 2). Greater baseline global tau SUVR was associated with lower vDMN connectivity, cross‐sectionally and longitudinally (Fig. 3).ConclusionDMN connectivity was altered in Aty‐AD, with strongest alterations in younger patients. The vDMN declined over time, suggesting a shift in DMN connectivity with disease progression that was likely related to tau pathology.

AbstractBackgroundPosterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are atypical variants of Alzheimer’s disease which typically show different cross‐sectional patterns of atrophy and tau deposition. Patterns of atrophy remain distinct longitudinally. A direct comparison of rates of atrophy and tau accumulation between these syndromes has not yet been reported.MethodWe evaluated 20 PCA and 20 LPA patients; all were amyloid‐positive on [11C]PiB‐PET. Structural MRI and tau‐PET were performed at baseline and one‐year follow‐up. Annualized rates of change in grey matter volume (log Jacobians from tensor‐based morphometry) and flortaucipir‐PET SUVRs were calculated at the lobar level. A global tau SUVR was calculated using parietal, temporal, and occipital regions. Lobar rates were compared between PCA and LPA with linear models, accounting for education, sex, age, baseline global tau SUVR (for tau‐PET), with significance set at p = 0.05. SPM voxel‐level comparisons were performed, with the same covariates, with significance set at p = 0.001.ResultGroups did not differ in age, Apoe status, baseline global tau SUVR or whole brain volume, or their annualized rates of change. LPA had shorter disease duration. In the lobar models, PCA had faster rates of atrophy in the occipital lobe and there were no significant differences on rates of tau accumulation, but a trend for LPA having faster rates of tau accumulation in all lobes. Baseline global tau SUVR was negatively associated with rate of tau accumulation in parietal and temporal lobes. Age was negatively associated with rates of tau accumulation in frontal, temporal and occipital lobes and with rates of atrophy in frontal and parietal lobes. Voxel‐level analysis confirmed these results, with PCA showing faster rates of occipital atrophy, and LPA showing subtle evidence for diffuse faster rates of tau accumulation (Figure 1).ConclusionLongitudinal patterns of neuroimaging abnormalities differ between PCA and LPA, although with divergent results for tau accumulation and atrophy that may reflect differences in disease stage. Rates of change are strongly influenced by age and severity of baseline tau, with faster rates of tau accumulation in patients with younger age and lower baseline tau deposition.

Background: Lower (worse) left atrial (LA) function is associated with higher dementia risk. It is unclear whether lower LA function is associated with vascular brain injury on brain MRI, an established correlate for higher dementia risk. Using data from the Atherosclerosis Risk in Communities (ARIC) study, we assessed the cross-sectional association between LA function measures and brain MRI markers of vascular brain injury (cerebral microbleeds, brain infarcts). Hypothesis: Participants with lower LA function will be more likely to have presence of > 1 cerebral microbleed or brain infarct. Methods: ARIC participants who had both an echocardiogram and brain MRI at visit 5 (2011-13) were included. We excluded those with prevalent dementia, stroke, or atrial fibrillation. LA function measures were obtained from 2D-echocardiograms and assessed in quartiles (highest quartile was the reference). Brain MRI measures were assessed as the presence or absence of > 1 cerebral microbleed or brain infarct. Logistic regression was used. Results: Of the 1502 participants (mean [SD] age 76 [5], 60% female, 27% Black) in this analysis, 345 (23%) and 351 (23%) had > 1 cerebral microbleed or brain infarct present. Compared to the highest quartile, lower LA reservoir and conduit strain quartiles were associated with higher odds of cerebral microbleeds. LA contractile strain was not associated with cerebral microbleeds. Compared to the highest quartile, the lowest LA conduit strain quartile, but not reservoir strain, was associated with higher odds of brain infarcts. LA contractile strain was inversely associated with brain infarcts. Conclusion: In this community-based cohort, lower LA function was cross-sectionally associated with cerebral microbleeds and brain infarcts. The inverse relationship with LA contractile strain may be due to contractile function compensating for a decrease in early diastolic filling. Prospective studies are needed to confirm these findings.

IMPORTANCE: Meropenem dosing is typically guided by creatinine-based estimated glomerular filtration rate (eGFR), but creatinine is a suboptimal GFR marker in the critically ill. OBJECTIVES: This study aimed to develop and qualify a population pharmacokinetic model for meropenem in critically ill adults and to determine which eGFR equation based on creatinine, cystatin C, or both biomarkers best improves model performance. DESIGN, SETTING, AND PARTICIPANTS: This single-center study evaluated adults hospitalized in an ICU who received IV meropenem from 2018 to 2022. Patients were excluded if they had acute kidney injury, were on kidney replacement therapy, or were treated with extracorporeal membrane oxygenation. Two cohorts were used for population pharmacokinetic modeling: a richly sampled development cohort (n = 19) and an opportunistically sampled qualification cohort (n = 32). MAIN OUTCOMES AND MEASURES: A nonlinear mixed-effects model was developed using parametric methods to estimate meropenem serum concentrations. RESULTS: The best-fit structural model in the richly sampled development cohort was a two-compartment model with first-order elimination. The final model included time-dependent weight normalized to a 70-kg adult as a covariate for volume of distribution (Vd) and time-dependent eGFR for clearance. Among the eGFR equations evaluated, eGFR based on creatinine and cystatin C expressed in mL/min best-predicted meropenem clearance. The mean (se) Vd in the final model was 18.2 (3.5) liters and clearance was 11.5 (1.3) L/hr. Using the development cohort as the Bayesian prior, the opportunistically sampled cohort demonstrated good accuracy and low bias. CONCLUSIONS AND RELEVANCE: Contemporary eGFR equations that use both creatinine and cystatin C improved meropenem population pharmacokinetic model performance compared with creatinine-only or cystatin C-only eGFR equations in adult critically ill patients.

Abstract Transactive response DNA-binding protein 43 (TDP-43) pathology is categorized as type A-E in frontotemporal lobar degeneration and as type α-β in Alzheimer disease (AD) based on inclusion type. We screened amygdala slides of 131 cases with varying ages at death, clinical/neuroimaging findings, and AD neuropathologic changes for TDP-43 pathology using anti-phospho-TDP-43 antibodies. Seven cases (5%) only showed atypical TDP-43 inclusions that could not be typed. Immunohistochemistry and immunofluorescence assessed the atypical star-shaped TDP-43 pathology including its distribution, species, cellular localization, and colocalization with tau. All 7 had died at an extremely old age (median: 100 years [IQR: 94–101]) from nonneurological causes and none had dementia (4 cognitively unimpaired, 3 with amnestic mild cognitive impairment). Neuroimaging showed mild medial temporal involvement. Pathologically, the star-shaped TDP-43-positive inclusions were found in medial (subpial) amygdala and, occasionally, in basolateral regions. Hippocampus only showed TDP-43-positive neurites in the fimbria and subiculum while the frontal lobe was free of TDP-43 inclusions. The star-shaped inclusions were better detected with antibodies against N-terminal than C-terminal TDP-43. Double-labeling studies confirmed deposition of TDP-43 within astrocytes and colocalization with tau. We have identified a novel TDP-43 pathology with star-shaped morphology associated with superaging, with a homogeneous clinicopathologic picture, possibly representing a novel, true aging-related TDP-43 pathology.

Serologic measures of tissue transglutaminase (tTG) immunoglobulin A (IgA) and deamidated gliadin peptide (DGP) IgA and immunoglobulin G (IgG) are hallmark tests utilized when diagnosing individuals for celiac disease (CeD) and for monitoring adherence to a gluten-free diet (GFD), currently the only available treatment for CeD. We address two issues in this study: (i) the relapse to seropositivity for CeD patients who resume a gluten containing diet and (ii) the correlation between two different tTG-IgA assays near the upper limit of normal (ULN) designated thresholds. Regarding the first issue, often a suspected CeD individual is put back on a gluten diet to return to their serologic levels. However, we show it requires a substantial amount of gluten for serology to return to a positive level. For example, in one study of 22 patients treated with placebo and taking 84 g of gluten over 6 weeks, only two converted from seronegative to seropositive for tTG-IgA. Regarding the second topic, we compare the relationship for different serologic assays, namely tTG-IgA AB (recombinant, ULN = 4 units/mL) vs. tTG-IgA (non-recombinant, ULN = 20 units). There is a strong correlation between both measurements as evidenced by a Pearson coefficient of R = 0.8584; however, we observed that the cross-correlation in terms of sensitivity and specificity improved substantially by using an ULN value of three instead of four for the tTG-IgA AB (recombinant) assay. This result suggests that assay thresholds used for initial diagnosis in patients who have not yet started a GFD may need to be adjusted for monitoring and in the setting of a diagnostic gluten challenge.