Optimizing differential identifiability improves connectome predictive modeling of cognitive deficits from functional connectivity in Alzheimer's disease

Functional connectivity, as estimated using resting state functional MRI, has shown potential in bridging the gap between pathophysiology and cognition. However, clinical use of functional connectivity biomarkers is impeded by unreliable estimates of individual functional connectomes and lack of generalizability of models predicting cognitive outcomes from connectivity. To address these issues, we combine the frameworks of connectome predictive modeling and differential identifiability. Using the combined framework, we show that enhancing the individual fingerprint of resting state functional connectomes leads to robust identification of functional networks associated to cognitive outcomes and also improves prediction of cognitive outcomes from functional connectomes. Using a comprehensive spectrum of cognitive outcomes associated to Alzheimer's disease (AD), we identify and characterize functional networks associated to specific cognitive deficits exhibited in AD. This combined framework is an important step in making individual level predictions of cognition from resting state functional connectomes and in understanding the relationship between cognition and connectivity.

Association of PET-based stages of amyloid deposition with neuropathological markers of Aβ pathology

OBJECTIVE

To determine if PET-based stages of regional amyloid deposition are associated with neuropathological phases of Aβ pathology.

METHODS

We applied data-driven regional frequency-based and a-priori striatum-based PET staging approaches to ante-mortem 18F-Florbetapir-PET scans of 30 cases from the Alzheimer's Disease Neuroimaging Initiative autopsy cohort, and used Bayesian regression analysis to study the associations of these in vivo amyloid stages with neuropathological Thal phases of regional Aβ plaque distribution and with semi-quantitative ratings of neocortical and striatal plaque densities.

RESULTS

Bayesian regression revealed extreme evidence for an association of both PET-based staging approaches with Thal phases, and these associations were about 44 times more likely for frequency-based stages and 89 times more likely for striatum-based stages than for global cortical 18F-Florbetapir-PET signal. Early (i.e., neocortical-only) PET-based amyloid stages also predicted the absence of striatal/diencephalic cored plaques. Receiver operating characteristics curves revealed highly accurate discrimination between low/high Thal phases and the presence/absence of regional plaques. The median areas under the curve were 0.99 for frequency-based staging (95% credibility interval 0.97-1.00), 0.93 for striatum-based staging (0.83-1.00), and 0.87 for global 18F-Florbetapir-PET signal (0.72-0.98).

INTERPRETATION

Our data indicate that both regional frequency- and striatum-based amyloid-PET staging approaches were superior to standard global amyloid-PET signal for differentiating between low and high degrees of regional amyloid pathology spread. Despite this, we found no evidence for the ability of either staging scheme to differentiate between low and moderate degrees of amyloid pathology which may be particularly relevant for early, preclinical stages of Alzheimer's disease.

Discordant Alzheimer's neurodegenerative biomarkers and their clinical outcomes

OBJECTIVE

In the 2018 ATN framework, Alzheimer's neurodegenerative biomarkers comprised cerebrospinal fluid (CSF) total tau, 18 F-fluorodeoxyglucose-positron emission tomography, and brain atrophy. We aimed to assess the clinical outcomes of having discordant Alzheimer's neurodegenerative biomarkers.

METHODS

A total of 721 non-demented individuals from the Alzheimer's Disease Neuroimaging Initiative database were included and then further categorized into concordant-negative, discordant, and concordant-positive groups. Demographic distributions of the groups were compared. Longitudinal changes in clinical outcomes and risk of conversion were assessed using linear mixed-effects models and multivariate Cox proportional hazard models, respectively.

RESULTS

Discordant group was intermediate to concordant-negative and concordant-positive groups in terms of APOE ε4 positivity, CSF amyloid-beta, and phosphorylated tau. Compared with concordant-negative group, discordant group deteriorated faster in cognitive scores (Mini-Mental State Examination, the Clinical Dementia Rating Scale-Sum of Boxes, and the Functional Activities Questionnaire) and demonstrated greater rates of atrophy in brain structures (hippocampus, entorhinal cortex, and whole brain), and concordant-positive group performed worse over time than discordant group. Moreover, the risk of cognitive decline increased from concordant-negative to discordant to concordant-positive. The results from longitudinal analyses were validated in A+T+, cognitively normal, and mild cognitive impairment individuals, and were also validated by applying different cutoffs and neurodegenerative biomarkers.

INTERPRETATION

Discordant neurodegenerative status denotes a stage of cognitive function which is intermediate between concordant-negative and concordant-positive. Identification of discordant cases would provide insights into intervention and new therapy approaches, particularly in A+T+ individuals. Moreover, this work may be a complement to the ATN scheme.

Gray matter volume and estimated brain age gap are not linked with sleep-disordered breathing

Alzheimer's disease (AD) and sleep-disordered breathing (SDB) are prevalent conditions with a rising burden. It is suggested that SDB may contribute to cognitive decline and advanced aging. Here, we assessed the link between self-reported SDB and gray matter volume in patients with AD, mild cognitive impairment (MCI) and healthy controls (HCs). We further investigated whether SDB was associated with advanced brain aging. We included a total of 330 participants, divided based on self-reported history of SDB, and matched across diagnoses for age, sex and presence of the Apolipoprotein E4 allele, from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Gray-matter volume was measured using voxel-wise morphometry and group differences in terms of SDB, cognitive status, and their interaction were assessed. Further, using an age-prediction model fitted on gray-matter data of external datasets, we predicted study participants' age from their structural images. Cognitive decline and advanced age were associated with lower gray matter volume in various regions, particularly in the bilateral temporal lobes. Brains age was well predicted from the morphological data in HCs and, as expected, elevated in MCI and particularly in AD subjects. However, there was neither a significant difference between regional gray matter volume in any diagnostic group related to the SDB status, nor in SDB-by-cognitive status interaction. Moreover, we found no difference in estimated chronological age gap related to SDB, or by-cognitive status interaction. Contrary to our hypothesis, we were not able to find a general or a diagnostic-dependent association of SDB with either gray-matter volumetric or brain aging.

Inflammatory pathway analytes predicting rapid cognitive decline in MCI stage of Alzheimer's disease

OBJECTIVE

To determine the inflammatory analytes that predict clinical progression and evaluate their performance against biomarkers of neurodegeneration.

METHODS

A longitudinal study of MCI-AD patients in a Discovery cohort over 15 months, with replication in the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort over 36 months. Fifty-three inflammatory analytes were measured in the CSF and plasma with a RBM multiplex analyte platform. Inflammatory analytes that predict clinical progression on Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and Mini Mental State Exam scores were assessed in multivariate regression models. To provide context, key analyte results in ADNI were compared against biomarkers of neurodegeneration, hippocampal volume, and CSF neurofilament light (NfL), in receiver operating characteristic (ROC) analyses evaluating highest quartile of CDR-SB change over two years (≥3 points).

RESULTS

Cerebrospinal fluid inflammatory analytes in relation to cognitive decline were best described by gene ontology terms, natural killer cell chemotaxis, and endothelial cell apoptotic process and in plasma, extracellular matrix organization, blood coagulation, and fibrin clot formation described the analytes. CSF CCL2 was most robust in predicting rate of cognitive change and analytes that correlated to CCL2 suggest IL-10 pathway dysregulation. The ROC curves for ≥3 points change in CDR-SB over 2 years when comparing baseline hippocampal volume, CSF NfL, and CCL2 were not significantly different.

INTERPRETATION

Baseline levels of immune cell chemotactic cytokine CCL2 in the CSF and IL-10 pathway dysregulation impact longitudinal cognitive and functional decline in MCI-AD. CCL2's utility appears comparable to biomarkers of neurodegeneration in predicting rapid decline.

Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks

Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a predictor of cognitive performance; however, automated hippocampal segmentation methods are limited because the algorithms are (a) not publicly available, (b) subject to error with significant brain atrophy, cerebrovascular disease and lesions, and/or (c) computationally expensive or require parameter tuning. In this study, we trained a 3D convolutional neural network using 259 bilateral manually delineated segmentations collected from three studies, acquired at multiple sites on different scanners with variable protocols. Our training dataset consisted of elderly cases difficult to segment due to extensive atrophy, vascular disease, and lesions. Our algorithm, (HippMapp3r), was validated against four other publicly available state-of-the-art techniques (HippoDeep, FreeSurfer, SBHV, volBrain, and FIRST). HippMapp3r outperformed the other techniques on all three metrics, generating an average Dice of 0.89 and a correlation coefficient of 0.95. It was two orders of magnitude faster than some of the tested techniques. Further validation was performed on 200 subjects from two other disease populations (frontotemporal dementia and vascular cognitive impairment), highlighting our method's low outlier rate. We finally tested the methods on real and simulated "clinical adversarial" cases to study their robustness to corrupt, low-quality scans. The pipeline and models are available at: https://hippmapp3r.readthedocs.ioto facilitate the study of the hippocampus in large multisite studies.

A selective androgen receptor modulator SARM-2f activates androgen receptor, increases lean body mass, and suppresses blood lipid levels in cynomolgus monkeys

SARM-2f a selective androgen receptor (AR) modulator, increases skeletal muscle mass and locomotor activity in rats. This study aimed to clarify its pharmacological effects in monkeys. In reporter assays, the EC50 values of SARM-2f for rat, monkey, and human AR were 2.5, 3, and 3.6 nmol/L, respectively; those of testosterone were 12, 3.2, and 11 nmol/L, respectively. A single oral administration (10 mg/kg SARM-2f) produced a maximal plasma concentration of 3011 ng/mL, with an area under the 24 hours concentration-time curve of 8152 ng·h/mL in monkeys. Body weight (BW), lean body mass (LBM), and plasma levels of total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, lipoprotein (a), alanine aminotransferase, and asparagine aminotransferase were measured after 4 weeks of treatment with SARM-2f (1, 3, and 10 mg/kg/day, QD, p.o.) or testosterone enanthate (TE; 2 mg/kg/2 weeks, s.c.) in monkeys. BW and LBM were significantly increased by 12% each by SARM-2f at 10 mg/kg, and by 5% and 8%, respectively, by TE, but these effects were not statistically significant. Plasma levels of all lipids were either decreased or showed a tendency to be decreased by SARM-2f. TE decreased the triglyceride level and increased the low-density lipoprotein cholesterol level. Liver marker levels were not changed by either SARM-2f or TE. Our data demonstrated that SARM-2f exerted anabolic effects and produced a lipid profile that differed from that produced by testosterone in monkeys, suggesting that SARM-2f might be useful for diseases such as sarcopenia.

Utilization of novel systemic therapies for multiple myeloma: A retrospective study of front-line regimens using the SEER-Medicare data

The landscape of treatment for multiple myeloma (MM) has significantly changed over the last decade due to novel agents that have shown superiority in efficacy such as proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs) over traditional therapies. However, the real-world utilization of these new agents has not been studied well. This study evaluated year-to-year changes in treatment choices in a cohort of patients aged 66 or older in the Surveillance, Epidemiology, and End Results (SEER) registry linked with Medicare claims (SEER-Medicare) data who were diagnosed with MM between 2007 and 2011. We identified 2477 symptomatic newly diagnosed patients who were followed for 6 months or more postdiagnosis and treated with systemic therapies but not with stem cell transplantation. Symptomatic patients were identified by evidence of hypercalcemia, renal failure, anemia, or bone lesions (CRAB criteria). The minimum follow-up was imposed to ensure sufficient data to characterize treatment. Our analysis found that the proportion of treated patients increased from 75% in the 2007 cohort to 79% in the 2011 cohort. The share of PI-based regimens including PI plus alkylating agents, PI plus IMiD, and PI-only increased from 9% to 21%, 3% to 11%, and 16% to 22%, respectively, between 2007 and 2011. These findings translate to the share of PI-based regimens having increased from 28% to 55% and that of IMiDs-based regimens (excluding PI plus IMiD) having decreased from 43% to 27%. In conclusion, while the usage of PIs among elderly MM patients increased significantly replacing IMiD-based regimens (with or without alkylating agents but not with PI) between 2007 and 2011, this significant shift did not increase the proportion of treated patients.

Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease

Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.