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BACKGROUND Vascular comorbidity (VC) is associated with multiple sclerosis (MS) disease progression and visual dysfunction. The longitudinal effect of VC in people with secondary progressive MS (SPMS) is unclear. This study explored the impact of VC on standard clinical, MRI, and visual outcomes in people with SPMS enrolled in a clinical trial. METHODS Data were extracted from a 2-year randomized controlled trial (N = 51) testing the supplement lipoic acid in people with SPMS who underwent annual Expanded Disability Status Scales, Timed 25-Foot Walk tests, MRIs, visual acuity testing, and retinal nerve fiber layer (RNFL) and ganglion cell/inner plexiform layer (GCIPL) thicknesses per optical coherence tomography (OCT). Post hoc linear mixed-effects regression analysis compared baseline and annualized outcomes between participants without VC (VC−) and with 1 or more VCs (VC+) (hypertension, dyslipidemia, obesity, diabetes, peripheral or cardiovascular disease, tobacco use). RESULTS The VC− (n = 19) and VC+ (n = 28) participants were similar in age, sex, and MS disease duration and had comparable MS disability, mobility, and brain atrophy at baseline and throughout the 2-year parent study. The VC+ participants had worse baseline visual acuity than those in the VC− group by 0.13 logMAR (P = .041). No significant differences were detected in RNFL or GCIPL baseline thickness or atrophy between groups. CONCLUSIONS In an SPMS cohort, VC had an inconsistent effect on standard clinical, MRI, and exploratory OCT outcomes, suggesting that the effect of VC may not be evident in smaller cohort studies. Using a more refined definition of VC in future, adequately powered investigations may help effectively elucidate and account for the interaction between vascular risk burden and MS disability.

Proteomic studies utilizing postmortem human brain tissue samples have yielded robust assessments of the aging and neurodegenerative disease(s) proteomes. While these analyses provide lists of molecular alterations in human conditions, like Alzheimer’s disease (AD), identifying individual proteins that affect biological processes remains a challenge. To complicate matters, protein targets may be highly understudied and have limited information on their function. To address these hurdles, we sought to establish a blueprint to aid selection and functional validation of targets from proteomic datasets. A cross-platform pipeline was engineered to focus on synaptic processes in the entorhinal cortex of human patients, including controls, preclinical AD, and AD cases. Label-free quantification mass spectrometry data (n=2,260 proteins) was generated on synaptosome fractionated tissue from Brodmann area 28 (n=58 samples). In parallel, dendritic spine density and morphology was measured in the same individuals. Weighted gene co-expression network analysis was used to construct a network of protein co-expression modules that were correlated with dendritic spine metrics. Module-trait correlations were used to guide unbiased selection of Twinfilin-2 (TWF2), which was the top hub protein of a module that positively correlated with thin spine length. Using CRISPR-dCas9 activation strategies, we demonstrated that boosting endogenous TWF2 protein levels in primary hippocampal neurons increased thin spine length, thus providing experimental validation for the human network analysis. Collectively, this study describes alterations in dendritic spine density and morphology as well as synaptic proteins and phosphorylated tau from the entorhinal cortex of preclinical and advanced stage AD patients.Significance Statement:Proteomic studies can yield vast lists of molecules that are altered under various experimental or disease conditions. Here, we provide a blueprint to facilitate mechanistic validation of protein targets from human brain proteomic datasets. We conducted a proteomic analysis of human entorhinal cortex samples spanning cognitively normal and Alzheimer's disease cases with a comparison of dendritic spine morphology in the same samples. Network integration of proteomics with dendritic spine measurements allowed for unbiased discovery of Twinfilin-2 as a regulator of dendritic spine length. A proof-of-concept experiment in cultured neurons demonstrated that altering Twinfilin-2 protein level induced corresponding changes in dendritic spine length, thus providing experimental validation for the computational framework.

Background: Accurate longitudinal modelling of cognitive decline is a major goal of Alzheimer’s disease and related dementia (ADRD) research. However, the impact of subject-specific effects is not well characterized and may have implications for data generation and prediction. Objective: This study seeks to address the impact of subject-specific effects, which are a less well-characterized aspect of ADRD cognitive decline, as measured by the Alzheimer’s Disease Assessment Scale’s Cognitive Subscale (ADAS-Cog). Methods: Prediction errors and biases for the ADAS-Cog subscale were evaluated when using only population-level effects, robust imputation of subject-specific effects using model covariances, and directly known individual-level effects fit during modelling as a natural control. Evaluated models included pre-specified parameterizations for clinical trial simulation, analogous mixed-effects regression models parameterized directly, and random forest ensemble models. Assessment used a meta-database of Alzheimer’s disease studies with validation in simulated synthetic cohorts. Results: All models observed increases in variance under imputation leading to increased prediction error. Bias decreased with imputation except under the pre-specified parameterization, which increased in the meta-database, but was attenuated under simulation. Known fitted subject effects gave the best prediction results. Conclusion: Subject-specific effects were found to have a profound impact on predicting ADAS-Cog. Reductions in bias suggest imputing random effects assists in calculating results on average, as when simulating clinical trials. However, reduction in error emphasizes population-level effects when attempting to predict outcomes for individuals. Forecasting future observations greatly benefits from using known subject-specific effects.

Lactate is an important cellular metabolite that is present at high concentrations in the brain, both within cells and in the extracellular space between cells. Small animal studies demonstrated high extracellular concentrations of lactate during wakefulness with reductions during sleep and/or anesthesia with a recent study suggesting the glymphatic activity as the mechanism for the reduction of lactate concentrations. We have recently developed a rigorous non-invasive imaging approach combining simultaneous magnetic resonance spectroscopy (MRS) and polysomnography (PSG) measurements, and here, we present the first in-vivo evaluation of brain lactate levels during sleep-wake cycles in young healthy humans. First, we collected single voxel proton MRS (1H-MRS) data at the posterior cingulate with high temporal resolution (every 7.5 sec), and simultaneously recorded PSG data while temporally registering with 1H-MRS time-series. Second, we evaluated PSG data in 30 s epochs, and classified into four stages Wake (W), Non-REM sleep stage 1 (N1), Non-REM sleep stage 2 (N2), and Non-REM sleep stage 3 (N3). Third, we determined lactate signal intensity from each 7.5-s spectrum, normalized to corresponding water signal, and averaged over 30-s for each PSG epoch. In examinations of nine healthy participants (four females, five males; mean age 24.2 (±2; SD) years; age range: 21-27 years) undergoing up to 3-hour simultaneous MRS/PSG recordings, we observed a group mean reduction of [4.9 ± 4.9] % in N1, [10.4 ± 5.2] % in N2, and [24.0 ± 5.8] % in N3 when compared to W. Our finding is consistent with more than 70 years of invasive lactate measurements from small animal studies. In addition, reduced brain lactate was accompanied by a significant reduction the apparent diffusion coefficient of brain lactate. Taken together, these findings are consistent with the loss of lactate from the extracellular space during sleep while suggesting lactate metabolism is altered and/or lactate clearance via glymphatic exchange is increased during sleep.Significance StatementThis study describes a non-invasive magnetic resonance spectroscopy/polysomnography technique that allows rigorous measurement of brain metabolite levels together with simultaneous characterization of brain arousal state as either wakeful or one of the several sleep states. The results provide the first in-vivo demonstration of reductions in brain lactate concentration and diffusivity during sleep versus wakefulness in young healthy human brain. These findings are consistent with invasive small-animal studies showing the loss of extracellular lactate during sleep, and support the notion of altered lactate metabolism and/or increased glymphatic activity in sleeping human brain.