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Abstract Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data. Validation involved two diverse cohorts, including over 1000 participants without gait labels, as well as 83 participants with labeled data: older adults with Parkinson's disease, proximal femoral fracture, chronic obstructive pulmonary disease, congestive heart failure, and healthy adults. ElderNet presented high accuracy (96.43 ± 2.27), specificity (98.87 ± 2.15), recall (82.32 ± 11.37), precision (86.69 ± 17.61), and F1 score (82.92 ± 13.39). The suggested method yielded superior performance compared to two state-of-the-art gait detection algorithms, with improved accuracy and F1 score (p

Abstract Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies show that SR-TWAS improves power, due to increased training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real studies identify 6 independent significant risk genes for Alzheimer’s disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson’s disease (PD) for substantia nigra tissue. Relevant biological interpretations are found for these significant risk genes.

Abstract The Mini-Mental State Examination (MMSE) is a widely employed screening tool for the severity of cognitive impairment. Among the MMSE items, the pentagon copying test (PCT) requires participants to accurately replicate a sample of two interlocking pentagons. While the PCT is traditionally scored on a binary scale, there have been limited developments of granular scoring scale to assess task performance. In this paper, we present a novel three-stage algorithm, called Quantification of Interlocking Pentagons (QIP) which quantifies PCT performance by computing the areas of individual pentagons and their intersection areas, and a balance ratio between the areas of the two individual pentagons. The three stages of the QIP algorithm include: (1) detection of line segments, (2) unraveling of the interlocking pentagons, and (3) quantification of areas. A set of 497 PCTs from 84 participants including their baseline and follow-up PCTs from the Rush Memory and Aging Project was selected blinded about their cognitive and clinical status. Analysis of the quantified data revealed a significant inverse relationship between age and balance ratio (beta = − 0.49, p = 0.0033), indicating that older age was associated with a smaller balance ratio. In addition, balance ratio was associated with perceptual speed (r = 0.71, p = 0.0135), vascular risk factors (beta = − 3.96, p = 0.0269), and medical conditions (beta = − 2.78, p = 0.0389). The QIP algorithm can serve as a useful tool for enhancing the scoring of performance in the PCT.

Abstract Frailty is characterized by diminished resilience to stressor events. It is associated with adverse future health outcomes and impedes healthy aging. The circadian system orchestrates ~24-h rhythms in bodily functions in synchrony with the day-night cycle, and disturbed circadian regulation plays an important role in many age-related health consequences. We investigated prospective associations of circadian disturbances with incident frailty in over 1000 older adults who had been followed annually for up to 16 years. We found that decreased rhythm strength, reduced stability, or increased variation were associated with a higher risk of incident frailty and faster progress of frailty over time. Perturbed circadian rest-activity rhythms may be an early sign or risk factor for frailty in older adults.

Abstract Differential gene expression (DGE) analysis has been widely employed to identify genes expressed differentially with respect to a trait of interest using RNA sequencing (RNA-Seq) data. Recent RNA-Seq data with large samples pose challenges to existing DGE methods, which were mainly developed for dichotomous traits and small sample sizes. Especially, existing DGE methods are likely to result in inflated false positive rates. To address this gap, we employed a linear mixed model (LMM) that has been widely used in genetic association studies for DGE analysis of quantitative traits. We first applied the LMM method to the discovery RNA-Seq data of dorsolateral prefrontal cortex (DLPFC) tissue (n = 632) with four continuous measures of Alzheimer’s Disease (AD) cognitive and neuropathologic traits. The quantile–quantile plots of p-values showed that false positive rates were well calibrated by LMM, whereas other methods not accounting for sample-specific mixed effects led to serious inflation. LMM identified 37 potentially significant genes with differential expression in DLPFC for at least one of the AD traits, 17 of which were replicated in the additional RNA-Seq data of DLPFC, supplemental motor area, spinal cord, and muscle tissues. This application study showed not only well calibrated DGE results by LMM, but also possibly shared gene regulatory mechanisms of AD traits across different relevant tissues.

Abstract Hand drawing, which requires multiple neural systems for planning and controlling sequential movements, is a useful cognitive test for older adults. However, the conventional visual assessment of these drawings only captures limited attributes and overlooks subtle details that could help track cognitive states. Here, we utilized a deep-learning model, PentaMind, to examine cognition-related features from hand-drawn images of intersecting pentagons. PentaMind, trained on 13,777 images from 3111 participants in three aging cohorts, explained 23.3% of the variance in the global cognitive scores, 1.92 times more than the conventional rating. This accuracy improvement was due to capturing additional drawing features associated with motor impairments and cerebrovascular pathologies. By systematically modifying the input images, we discovered several important drawing attributes for cognition, including line waviness. Our results demonstrate that deep learning models can extract novel drawing metrics to improve the assessment and monitoring of cognitive decline and dementia in older adults.

Abstract Background Spinal manipulative therapy (SMT) is a guideline-recommended treatment option for spinal pain. The recommendation is based on multiple systematic reviews. However, these reviews fail to consider that clinical effects may depend on SMT “application procedures” (i.e., how and where SMT is applied). Using network meta-analyses, we aim to investigate which SMT “application procedures” have the greatest magnitude of clinical effectiveness for reducing pain and disability, for any spinal complaint, at short-term and long-term follow-up. We will compare application procedural parameters by classifying the thrust application technique and the application site (patient positioning, assisted, vertebral target, region target, Technique name, forces, and vectors, application site selection approach and rationale) against: 1. Waiting list/no treatment; 2. Sham interventions not resembling SMT (e.g., detuned ultrasound); 3. Sham interventions resembling SMT; 4. Other therapies not recommended in clinical practice guidelines; and 5. Other therapies recommended in clinical practice guidelines. Secondly, we will examine how contextual elements, including procedural fidelity (whether the SMT was delivered as planned) and clinical applicability (whether the SMT is similar to clinical practice) of the SMT. Methods We will include randomized controlled trials (RCT) found through three search strategies, (i) exploratory, (ii) systematic, and (iii) other known sources. We define SMT as a high-velocity low-amplitude thrust or grade V mobilization. Eligibility is any RCT assessing SMT against any other type of SMT, any other active or sham intervention, or no treatment control on adult patients with pain in any spinal region. The RCTs must report on continuous pain intensity and/or disability outcomes. Two authors will independently review title and abstract screening, full-text screening, and data extraction. Spinal manipulative therapy techniques will be classified according to the technique application and choice of application sites. We will conduct a network-meta analysis using a frequentist approach and multiple subgroup and sensitivity analyses. Discussion This will be the most extensive review of thrust SMT to date, and will allow us to estimate the importance of different SMT application procedures used in clinical practice and taught across educational settings. Thus, the results are applicable to clinical practice, educational settings, and research studies. PROSPERO registration: CRD42022375836.

While the concept of cognitive resilience is well-established it has not been defined in a way that can be measured. This has been an impediment to studying its underlying biology and to developing instruments for its clinical assessment. This perspective highlights recent work that has quantified the expression of cortical proteins associated with cognitive resilience, thus facilitating studies of its complex underlying biology and the full range of its clinical effects in aging adults. These initial studies provide empirical support for the conceptualization of resilience as a continuum. Like other conventional risk factors, some individuals manifest higher-than-average cognitive resilience and other individuals manifest lower-than-average cognitive resilience. These novel approaches for advancing studies of cognitive resilience can be generalized to other aging phenotypes and can set the stage for the development of clinical tools that might have the potential to measure other mechanisms of resilience in aging adults. These advances also have the potential to catalyze a complementary therapeutic approach that focuses on augmenting resilience via lifestyle changes or therapies targeting its underlying molecular mechanisms to maintain cognition and brain health even in the presence of untreatable stressors like brain pathologies that accumulate in aging adults.

ObjectiveTo determine the extent to which the regional brain volumes associated with slow gait speed can inform subsequent cognitive decline in older adults from the Rush Memory and Aging Project.ApproachWe utilized deformation-based morphometry (DBM) in a whole-brain exploratory approach to identify the regional brain volumes associated with gait speed assessed over a short distance during an in-home assessment. We created deformation scores to summarize the gait-associated regions and entered the scores into a series of longitudinal mixed effects models to determine the extent to which deformation predicted change in cognition over time, controlling for associations between gait and cognition.ResultsIn 438 older adults (81 ± 7; 76% female), DBM revealed that slower gait speed was associated with smaller volumes across frontal white matter, temporal grey matter, and subcortical areas and larger volumes in the ventricles during the same testing cycle. When a subset was followed over multiple (5 ± 2) years, slower gait speed was also associated with annual declines in global cognition, executive functioning, and memory abilities. Several of the gait-related brain structures were associated with these declines in cognition; however, larger ventricles and smaller medial temporal lobe volumes proved most robust and attenuated the association between slow gait and cognitive decline.ConclusionRegional brain volumes in the ventricles and temporal lobe associated with both slow gait speed and faster cognitive decline have potential to improve risk stratification for cognitive decline in older adults.

Summary: Existing methods for integrating functional annotations in genome-wide association studies (GWASs) to fine-map and prioritize potential causal variants are limited to using non-overlapped categorical annotations or limited by the computation burden of modeling genome-wide variants. To overcome these limitations, we propose a scalable Bayesian functional GWAS method to account for multivariate quantitative functional annotations (BFGWAS_QUANT), accompanied by a scalable computation algorithm enabling joint modeling of genome-wide variants. Simulation studies validated the performance of BFGWAS_QUANT for accurately quantifying annotation enrichment and improving GWAS power. Applying BFGWAS_QUANT to study five Alzheimer disease (AD)-related phenotypes using individual-level GWAS data (n = ∼1,000), we found that histone modification annotations have higher enrichment than expression quantitative trait locus (eQTL) annotations for all considered phenotypes, with the highest enrichment in H3K27me3 (polycomb regression). We also found that cis-eQTLs in microglia had higher enrichment than eQTLs of bulk brain frontal cortex tissue for all considered phenotypes. A similar enrichment pattern was also identified using the International Genomics of Alzheimer’s Project (IGAP) summary-level GWAS data of AD (n = ∼54,000). The strongest known APOE E4 risk allele was identified for all five phenotypes, and the APOE locus was validated using the IGAP data. BFGWAS_QUANT fine-mapped 32 significant variants from 1,073 genome-wide significant variants in the IGAP data. We also demonstrated that the polygenic risk scores (PRSs) using effect size estimates by BFGWAS_QUANT had a similar prediction accuracy as other methods assuming a sparse causal model. Overall, BFGWAS_QUANT is a useful GWAS tool for quantifying annotation enrichment and prioritizing potential causal variants.

Purpose: To explore the immunogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in patients with breast cancer based on type of anticancer treatment. Methods: Patients with breast cancer had anti-spike antibody concentrations measured ⩾14 days after receiving a full SARS-CoV-2 vaccination series. The primary endpoint was IgA/G/M anti-spike antibody concentration. Multiple regression analysis was used to analyze log 10 -transformed antibody titer concentrations. Results: Between 29 April and 20 July 2021, 233 patients with breast cancer were enrolled, of whom 212 were eligible for the current analysis. Patients who received mRNA-1273 (Moderna) had the highest antibody concentrations [geometric mean concentration (GMC) in log 10 : 3.0 U/mL], compared to patients who received BNT162b2 (Pfizer) (GMC: 2.6 U/mL) (multiple regression adjusted p = 0.013) and Ad26.COV2.S (Johnson & Johnson/Janssen) (GMC: 2.6 U/mL) ( p = 0.071). Patients receiving cytotoxic therapy had a significantly lower antibody titer GMC (2.5 U/mL) compared to patients on no therapy or endocrine therapy alone (3.0 U/mL) ( p = 0.005). Patients on targeted therapies (GMC: 2.7 U/mL) also had a numerically lower GMC compared to patients not receiving therapy/on endocrine therapy alone, although this result was not significant ( p = 0.364). Among patients who received an additional dose of vaccine ( n = 31), 28 demonstrated an increased antibody response that ranged from 0.2 to >4.4 U/ mL. Conclusion: Most patients with breast cancer generate detectable anti-spike antibodies following SARS-CoV-2 vaccination, though systemic treatments and vaccine type impact level of response. Further studies are needed to better understand the clinical implications of different antibody levels, the effectiveness of additional SARS-CoV-2 vaccine doses, and the risk of breakthrough infections among patients with breast cancer.

Abstract Motor resilience proteins may be a high value therapeutic target that offset the negative effects of pathologies on motor function. This study sought to identify cortical proteins associated with motor decline unexplained by brain pathologies that provide motor resilience. We studied 1226 older decedents with annual motor testing, postmortem brain pathologies and quantified 226 proteotypic peptides in prefrontal cortex. Twenty peptides remained associated with motor decline in models controlling for ten brain pathologies (FDR

Muscle weakness has been associated with morbidity and mortality in older people. Here, the authors have investigated this trait further by performing a genome-wide meta-analysis of grip strength and Mendelian randomization to discover causal relationships between muscle weakness and other diseases.

Abstract Background The assessment of spinal stiffness by manual palpation in clinical settings has demonstrated both poor accuracy and reliability. More recently, mechanical methods for assessment of spinal stiffness have demonstrated superior accuracy and reliability. However, mechanical methods of spinal stiffness assessment can be expensive, time consuming and/or unsuited to clinical practice. While a new device has been designed to address these issues (VerteTrack), its benchtop performance remains unknown. Aim To measure the bench-top performance of VerteTrack. Methods A series of laboratory-based experiments were conducted in February 2018 to investigate the accuracy (precision and bias) of load and displacement measurements obtained by VerteTrack and then were compared against an appropriate reference standard. Measurements of both multiple-level continuous assessment (multiple spinal levels measured), and single-level assessment (single spinal level measured) were performed on a viscoelastic foam medium (AIREX® balance beam, Switzerland) and the resulting stiffness calculated. Results VerteTrack demonstrated high precision at all loads and displacements. There was minimal systematic measurement bias identified for applied versus reference load (mean bias = − 0.123 N; 95%CI − 0.182 to 0.428 N, p

PurposeThis study aimed to investigate the association of the cardiovascular risk burden assessed by the Framingham General Cardiovascular Risk Score (FGCRS) with the trajectories of motor function over time and to assess the mediating effects of cardiovascular diseases (CVDs) accumulation and cognitive decline in such association.MethodsIn Rush Memory and Aging Project, a total of 1,378 physical health participants (mean age: 79.3 ± 7.3 years) were followed up for up to 22 years. FGCRS at baseline was assessed and categorized into tertiles (lowest, middle, and highest). Global motor function (including dexterity, gait, and hand strength) was assessed annually with 10 motor tests. CVDs (including stroke, congestive heart failure, and other heart diseases) were ascertained at baseline and follow-ups, and the number of CVDs accumulation over time was assessed. Global cognitive function was tested annually by 19 tests. Data were analyzed using the linear mixed-effects models and mediation analysis.ResultsAt baseline, FGCRS ranged from 4 to 28 (mean score: 15.6 ± 3.7). Over the follow-up (median: 5.3 years; interquartile range: 2.9–9.0 years), in multi-adjusted mixed-effects models, the highest FGCRS was associated with faster decline in global motor function (β = −0.0038; 95% confidence interval [CI]: −0.0069 to −0.0008), dexterity (β = −0.0056; 95% CI: −0.0093 to −0.0020), gait (β = −0.0039; 95% CI: −0.0077 to −0.0001), and hand strength (β = −0.0053; 95% CI: −0.0098 to −0.0008) compared with the lowest tertile. In mediation analysis, CVDs accumulation and cognitive decline mediated 8.4% and 42.9% of the association between FGCRS and global motor function over time, respectively.ConclusionHigher cardiovascular risk burden is associated with a faster decline in motor function including dexterity, gait, and hand strength. CVDs accumulation and cognitive decline may partially mediate the association between cardiovascular risk burden and global motor function decline.

By age 85, most adults manifest some degree of motor impairment. However, in most individuals a specific etiology for motor decline and treatment to modify its inexorable progression cannot be identified. Recent clinical-pathologic studies provide evidence that mixed-brain pathologies are commonly associated with late-life motor impairment. Yet, while nearly all older adults show some degree of accumulation of Alzheimer’s disease and related dementias (ADRD) pathologies, the extent to which these pathologies contribute to motor decline varies widely from person to person. Slower or faster than expected motor decline in the presence of brain injury and/or pathology has been conceptualized as more or less “resilience” relative to the average person This suggests that other factors, such as lifestyles or other neurobiologic indices may offset or exacerbate the negative effects of pathologies via other molecular pathways. The mechanisms underlying neural motor resilience are just beginning to be illuminated. Unlike its cousin, cognitive resilience which is restricted to neural mechanisms above the neck, the motor system extends the total length of the CNS and beyond the CNS to reach muscle and musculoskeletal structures, all of which are crucial for motor function. Building on prior work, we propose that by isolating motor decline unrelated to neuropathologies and degeneration, investigators can identify genes and proteins that may provide neural motor resilience. Elucidating these molecular mechanisms will advance our understanding of the heterogeneity of late-life motor impairment. This approach will also provide high value therapeutic targets for drug discovery of therapies that may offset the negative motor consequences of CNS pathologies that are currently untreatable.

This study characterized person-specific rates of change of total daily physical activity (TDPA) and identified correlates of this change. TDPA metrics were extracted from multiday wrist-sensor recordings from 1083 older adults (average age 81 years; 76% female). Thirty-two covariates were collected at baseline. A series of linear mixed-effect models were used to identify covariates independently associated with the level and annual rate of change of TDPA. Though, person-specific rates of change varied during a mean follow-up of 5 years, 1079 of 1083 showed declining TDPA. The average decline was 16%/year, with a 4% increased rate of decline for every 10 years of age older at baseline. Following variable selection using multivariate modeling with forward and then backward elimination, age, sex, education, and 3 of 27 non-demographic covariates including motor abilities, a fractal metric, and IADL disability remained significantly associated with declining TDPA accounting for 21% of its variance (9% non-demographic and 12% demographics covariates). These results show that declining TDPA occurs in many very old adults. Few covariates remained correlated with this decline and the majority of its variance remained unexplained. Further work is needed to elucidate the biology underlying TDPA and to identify other factors that account for its decline.

We tested the hypothesis that dividing attention would strengthen the ability to detect mild cognitive impairment (MCI) and specific cognitive abilities from Timed Up and Go (TUG) performance in the community setting. While wearing a belt-worn sensor, 757 dementia-free older adults completed TUG during two conditions, with and without a concurrent verbal serial subtraction task. We segmented TUG into its four subtasks (i.e., walking, turning, and two postural transitions), and extracted 18 measures that were summarized into nine validated sensor metrics. Participants also underwent a detailed cognitive assessment during the same visit. We then employed a series of regression models to determine the combinations of subtask sensor metrics most strongly associated with MCI and specific cognitive abilities for each condition. We also compared subtask performances with and without dividing attention to determine whether the costs of divided attention were associated with cognition. While slower TUG walking and turning were associated with higher odds of MCI under normal conditions, these and other subtask associations became more strongly linked to MCI when TUG was performed under divided attention. Walking and turns were also most strongly associated with executive function and attention, particularly under divided attention. These differential associations with cognition were mirrored by performance costs. However, since several TUG subtasks were more strongly associated with MCI and cognitive abilities when performed under divided attention, future work is needed to determine how instrumented dual-task TUG testing can more accurately estimate risk for late-life cognitive impairment in older adults.

Epigenetic clocks are calculated by combining DNA methylation states across select CpG sites to estimate biologic age, and have been noted as the most successful markers of biologic aging to date. Yet, limited research has considered epigenetic clocks calculated in brain tissue. We used DNA methylation states in dorsolateral prefrontal cortex specimens from 721 older participants of the Religious Orders Study and Rush Memory and Aging Project, to calculate DNA methylation age using four established epigenetic clocks: Hannum, Horvath, PhenoAge, GrimAge, and a new Cortical clock. The four established clocks were trained in blood samples (Hannum, PhenoAge, GrimAge) or using 51 human tissue and cell types (Horvath); the recent Cortical clock is the first trained in postmortem cortical tissue. Participants were recruited beginning in 1994 (Religious Orders Study) and 1997 (Memory and Aging Project), and followed annually with questionnaires and clinical evaluations; brain specimens were obtained for 80–90% of participants. Mean age at death was 88.0 (SD 6.7) years. We used linear regression, logistic regression, and linear mixed models, to examine relations of epigenetic clock ages to neuropathologic and clinical aging phenotypes, controlling for chronologic age, sex, education, and depressive symptomatology.Hannum, Horvath, PhenoAge and Cortical clock ages were related to pathologic diagnosis of Alzheimer's disease (AD), as well as to Aβ load (a hallmark pathology of Alzheimer's disease). However, associations were substantially stronger for the Cortical than other clocks; for example, each standard deviation (SD) increase in Hannum, Horvath, and PhenoAge clock age was related to approximately 30% greater likelihood of pathologic AD (all p

Objective: Late-life cognitive impairment is heterogeneous. This study examined to what extent varied motor performances are differentially associated with incident Alzheimer’s dementia (AD) and incident mild cognitive impairment (MCI) in older adults.Design: Nested substudy.Setting: Communities across metropolitan Chicago.Participants: African American (N = 580) and European American (N = 580) adults without dementia, propensity-balanced by age (mean = 73.2; SD = 6.0), sex (78.4% women), education (mean = 15.6; SD = 3.3) and number of follow ups.Measurements: Cognitive status was assessed annually and based in part on a composite measure of global cognition including 17 cognitive tests. A global motor score was based on 10 motor performances from which 4 motor domains were computed including hand dexterity, hand strength, gait function, and leg strength.Results: During 7 years of follow-up, 166 of 1,160 (14.3%) developed AD. In a proportional hazards model controlling for age, sex, education, and race, each 1-SD higher baseline global motor score was associated with about a 20% reduction in the risk of AD (hazard ratio: 0.81; 95% CI: 0.68, 0.97). Higher baseline motor function was also associated with decreased risk of incident MCI (hazard ratio: 0.79; 95% CI: 0.68, 0.92). Hand dexterity, hand strength and gait function but not leg strength were associated with incident AD and MCI. When including all four motor domains in the same model, results remained the same for incident MCI, while for incident AD, the association with hand strength remained significant.Conclusion: Diverse motor performances are associated with late-life cognitive impairment. Further work is needed to identify specific motor performances that may differentiate adults at risk for future MCI or AD dementia.

Abstract Background Otologic diseases are often difficult to diagnose accurately for primary care providers. Deep learning methods have been applied with great success in many areas of medicine, often outperforming well trained human observers. The aim of this work was to develop and evaluate an automatic software prototype to identify otologic abnormalities using a deep convolutional neural network. Material and methods A database of 734 unique otoscopic images of various ear pathologies, including 63 cerumen impactions, 120 tympanostomy tubes, and 346 normal tympanic membranes were acquired. 80% of the images were used for the training of a convolutional neural network and the remaining 20% were used for algorithm validation. Image augmentation was employed on the training dataset to increase the number of training images. The general network architecture consisted of three convolutional layers plus batch normalization and dropout layers to avoid over fitting. Results The validation based on 45 datasets not used for model training revealed that the proposed deep convolutional neural network is capable of identifying and differentiating between normal tympanic membranes, tympanostomy tubes, and cerumen impactions with an overall accuracy of 84.4%. Conclusion Our study shows that deep convolutional neural networks hold immense potential as a diagnostic adjunct for otologic disease management.

Remote assessment of the gait of older adults (OAs) during daily living using wrist-worn sensors has the potential to augment clinical care and mobility research. However, hand movements can degrade gait detection from wrist-sensor recordings. To address this challenge, we developed an anomaly detection algorithm and compared its performance to four previously published gait detection algorithms. Multiday accelerometer recordings from a wrist-worn and lower-back sensor (i.e., the “gold-standard” reference) were obtained in 30 OAs, 60% with Parkinson’s disease (PD). The area under the receiver operator curve (AUC) and the area under the precision–recall curve (AUPRC) were used to evaluate the performance of the algorithms. The anomaly detection algorithm obtained AUCs of 0.80 and 0.74 for OAs and PD, respectively, but AUPRCs of 0.23 and 0.31 for OAs and PD, respectively. The best performing detection algorithm, a deep convolutional neural network (DCNN), exhibited high AUCs (i.e., 0.94 for OAs and 0.89 for PD) but lower AUPRCs (i.e., 0.66 for OAs and 0.60 for PD), indicating trade-offs between precision and recall. When choosing a classification threshold of 0.9 (i.e., opting for high precision) for the DCNN algorithm, strong correlations (r > 0.8) were observed between daily living walking time estimates based on the lower-back (reference) sensor and the wrist sensor. Further, gait quality measures were significantly different in OAs and PD compared to healthy adults. These results demonstrate that daily living gait can be quantified using a wrist-worn sensor.

Background Disrupted nighttime sleep has been associated with heart failure (HF). However, the relationship between daytime napping, an important aspect of sleep behavior commonly seen in older adults, and HF remains unclear. We sought to investigate the association of objectively assessed daytime napping and risk of incident HF during follow‐up. Methods and Results We studied 1140 older adults (age, 80.7±7.4 [SD] years; female sex, 867 [76.1%]) in the Rush Memory and Aging Project who had no HF at baseline and were followed annually for up to 14 years. Motor activity (ie, actigraphy) was recorded for ≈10 days at baseline. We assessed daytime napping episodes between 9 am and 7 pm objectively from actigraphy using a previously published algorithm for sleep detection. Cox proportional hazards models examined associations of daily napping duration and frequency with incident HF. Eighty‐six participants developed incident HF, and the mean onset time was 5.7 years (SD, 3.4; range, 1–14). Participants who napped longer than 44.4 minutes (ie, the median daily napping duration) showed a 1.73‐fold higher risk of developing incident HF than participants who napped 1.7 times/day (ie, the median daily napping frequency) showed a 2.20‐fold increase compared with participants who napped

Background: Patients with Parkinson's disease (PD) and progressive supranuclear palsy Richardson's syndrome (PSP-RS) often show overlapping clinical features, leading to misdiagnoses. The objective of this study was to investigate the feasibility and utility of using multi-modal MRI datasets for an automatic differentiation of PD patients, PSP-RS patients, and healthy control (HC) subjects.Material and Methods: T1-weighted, T2-weighted, and diffusion-tensor (DTI) MRI datasets from 45 PD patients, 20 PSP-RS patients, and 38 HC subjects were available for this study. Using an atlas-based approach, regional values of brain morphology (T1-weighted), brain iron metabolism (T2-weighted), and microstructural integrity (DTI) were measured and employed for feature selection and subsequent classification using combinations of various established machine learning methods.Results: The optimal machine learning model using regional morphology features only achieved a classification accuracy of 65% (67/103 correct classifications) differentiating PD patients, PSP-RS patients, and HC subjects. The optimal machine learning model using only quantitative T2 values performed slightly better and achieved an accuracy of 75.7% (78/103). The optimal classifier using DTI features alone performed considerably better with 95.1% accuracy (98/103). The optimal multi-modal classifier using all features also achieved an accuracy of 95.1% but required more features and achieved a slightly lower F1-score compared to the optimal model using DTI features alone.Conclusion: Machine learning models using multi-modal MRI perform significantly better than uni-modal machine learning models using morphological parameters based on T1-weighted MRI datasets alone or brain iron metabolism markers based on T2-weighted MRI datasets alone. However, machine learnig models using regional brain microstructural integrity metrics computed from DTI datasets perform similar to the optimal multi-modal machine learning model. Thus, given the results from this study cohort, it appears that morphology and brain iron metabolism markers may not provide additional value for classification compared to using DTI metrics alone.

Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, traditional two-stage TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Traditional TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL's estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS methods based on a two-stage Burden test, especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer's dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs, which also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use.

BackgroundMobility disability and parkinsonism are associated with decreased survival in older adults. This study examined the transition from no motor impairment to mobility disability and parkinsonism and their associations with death.Methods867 community-dwelling older adults without mobility disability or parkinsonism at baseline were examined annually. Mobility disability was based on annual measured gait speed. Parkinsonism was based on the annual assessment of 26 items from the motor portion of the Unified Parkinson's Disease Rating Scale. A multistate Cox model simultaneously examined the incidences of mobility disability and parkinsonism and their associations with death.ResultsAverage age at baseline was 75 years old and 318 (37%) died during 10 years of follow-up. Mobility disability was almost 2-fold more common than parkinsonism. Some participants developed mobility disability alone (42%), or parkinsonism alone (5%), while many developed both (41%). Individuals with mobility disability or parkinsonism alone had an increased risk of death, but their risk was less than the risk in individuals with both impairments. The risk of death did not depend on the order in which impairments occurred.ConclusionThe varied patterns of transitions from no motor impairment to motor impairment highlights the heterogeneity of late-life motor impairment and its contribution to survival. Further studies are needed to elucidate the underlying biology of these different transitions and how they might impact survival.

BackgroundThis study tested the hypothesis that sarcopenia and its constituent components, reduced lean muscle mass and impaired motor function, are associated with reduced survival and increased risk of incident disabilities.Methods1466 community-dwelling older adults underwent assessment of muscle mass with bioelectrical impedance analysis (BIA), grip strength, gait speed and other components of physical frailty and annual self-report assessments of disability. We used Cox proportional hazards models that controlled for age, sex, race, education and height to examine the associations of a continuous sarcopenia metric with the hazard of death and incident disabilities.ResultsMean baseline age was about 80 years old and follow-up was 5.5 years. In a proportional hazards model controlling for age, sex, race, education and baseline sarcopenia, each 1-SD higher score on a continuous sarcopenia scale was associated with lower hazards of death (HR 0.70, 95%CI [0.62, 0.78]), incident IADL (HR 0.80,95%CI [0.70, 0.93]), incident ADL disability (HR 0.80 95%CI [71, 91]) and incident mobility disability (HR 0.81, 95%CI [0.70, 0.93]). Further analyses suggest that grip strength and gait speed rather than muscle mass drive the associations with all four adverse health outcomes. Similar findings were observed when controlling for additional measures used to assess physical frailty including BMI, fatigue and physical activity.ConclusionsMotor function is the primary driver of the associations of sarcopenia and physical frailty with diverse adverse health outcomes. Further work is needed to identify other facets of muscle structure and motor function which together can identify adults at risk for specific adverse health outcomes.

The inflammatory hypothesis posits that sustained neuroinflammation is sufficient to induce neurodegeneration and the development of Alzheimer's disease (AD) and Alzheimer's dementia. One potential source of inflammation is the intestine which harbors pro-inflammatory microorganisms capable of promoting neuroinflammation. Systemic inflammation is robustly associated with neuroinflammation as well as low levels of brain derived neurotrophic factor (BDNF) in the systemic circulation and brain. Thus, in this pilot study, we tested the hypothesis that intestinal barrier dysfunction precedes risk of death, incident AD dementia and MCI, cognitive impairment and neuropathology. Serum BDNF was associated with changes in global cognition, working memory, and perceptual speed but not risk of death, incident AD dementia, incident MCI, or neuropathology. Neither of the markers of intestinal barrier integrity examined, including lipopolysaccharide binding protein (LBP) nor intestinal fatty acid binding protein (IFABP), were associated with risk of death, incident AD dementia, incident mild cognitive impairment (MCI), change in cognition (global or domains), or neuropathology. Taken together, the data in this pilot study suggest that intestinal barrier dysfunction does not precede diagnosis of AD or MCI, changes in cognition, or brain pathology. However, since MCI and AD are related to global cognition, the findings with BDNF and the contiguous cognitive measures suggest low power with the trichotomous cognitive status measures. Future studies with larger sample sizes are necessary to further investigate the results from this pilot study.

ObjectiveTo test whether postmortem MRI captures brain tissue characteristics that mediate the association between physical activity and cognition in older adults.MethodsParticipants (N = 318) were older adults from the Rush Memory and Aging Project who wore a device to quantify physical activity and also underwent detailed cognitive and motor testing. Following death, cerebral hemispheres underwent MRI to quantify the transverse relaxation rate R2, a metric related to tissue microstructure. For analyses, we reduced the dimensionality of the R2 maps from approximately 500,000 voxels to 30 components using spatial independent component analysis (ICA). Via path analysis, we examined whether these R2 components attenuated the association between physical activity and cognition, controlling for motor abilities and indices of common brain pathologies.ResultsTwo of the 30 R2 components were associated with both total daily physical activity and global cognition assessed proximate to death. We visualized these components by highlighting the clusters of voxels whose R2 values contributed most strongly to each. One of these spatial signatures spanned periventricular white matter and hippocampus, while the other encompassed white matter of the occipital lobe. These two R2 components partially mediated the association between physical activity and cognition, accounting for 12.7% of the relationship (p = .01). This mediation remained evident after controlling for motor abilities and neurodegenerative and vascular brain pathologies.ConclusionThe association between physically activity and cognition in older adults is partially accounted for by MRI-based signatures of brain tissue microstructure. Further studies are needed to elucidate the molecular mechanisms underlying this pathway.

Abstract Introduction Physical activity (PA) is associated with better cognitive and brain health. However, it remains unclear whether PA relates to accumulation of disease pathology (“resistance”) or indirectly moderates adverse effects of pathology on cognition (“cognitive resilience”). Methods Five hundred thirteen Rush Memory and Aging Project (MAP) decedents completed longitudinal actigraphy monitoring, cognitive testing, and neuropathological examination. Cross‐sectional models tested the relationship between average PA and pathology, and the moderating effect of baseline PA on the association between pathology and cognition. Longitudinal models examined whether changes in PA moderated associations between pathology and cognition. Results PA was negatively associated with Lewy body disease (LBD), but positively associated with Alzheimer's disease (AD) burdens. Baseline PA attenuated the association between cerebrovascular pathology and cognition, whereas longitudinal change in PA attenuated associations between AD, cerebral amyloid angiopathy, TAR DNA‐binding protein 43, and atherosclerosis on cognitive decline. Discussion Whereas PA relates to “cognitive resilience” against cerebrovascular disease, AD, and other neuropathologies, “resistance” effects were limited.

Summary: Background: Circadian disturbances are commonly seen in people with Alzheimer's disease and have been reported in individuals without symptoms of dementia but with Alzheimer's pathology. We aimed to assess the temporal relationship between circadian disturbances and Alzheimer's progression. Methods: We did a prospective cohort study of 1401 healthy older adults (aged >59 years) enrolled in the Rush Memory and Aging Project (Rush University Medical Center, Chicago, IL, USA) who had been followed up for up to 15 years. Participants underwent annual assessments of cognition (with a battery of 21 cognitive performance tests) and motor activities (with actigraphy). Four measures were extracted from actigraphy to quantify daily and circadian rhythmicity, which were amplitude of 24-h activity rhythm, acrophase (representing peak activity time), interdaily stability of 24-h activity rhythm, and intradaily variability for hourly fragmentation of activity rhythm. We used Cox proportional hazards models and logistic regressions to assess whether circadian disturbances predict an increased risk of incident Alzheimer's dementia and conversion of mild cognitive impairment to Alzheimer's dementia. We used linear mixed-effects models to investigate how circadian rhythms changed longitudinally and how the change integrated to Alzheimer's progression. Findings: Participants had a median age of 81·8 (IQR 76·3–85·7) years. Risk of developing Alzheimer's dementia was increased with lower amplitude (1 SD decrease, hazard ratio [HR] 1·39, 95% CI 1·19–1·62) and higher intradaily variability (1 SD increase, 1·22, 1·04–1·43). In participants with mild cognitive impairment, increased risk of Alzheimer's dementia was predicted by lower amplitude (1 SD decrease, HR 1·46, 95% CI 1·24–1·72), higher intradaily variability (1 SD increase, 1·36, 1·15–1·60), and lower interdaily stability (1 SD decrease, 1·21, 1·02–1·44). A faster transition to Alzheimer's dementia in participants with mild cognitive impairment was predicted by lower amplitude (1 SD decrease, odds ratio [OR] 2·08, 95% CI 1·53–2·93), increased intradaily variability (1 SD increase, 1·97, 1·43–2·79), and decreased interdaily stability (1 SD decrease, 1·35, 1·01–1·84). Circadian amplitude, acrophase, and interdaily stability progressively decreased over time, and intradaily variability progressively increased over time. Alzheimer's progression accelerated these aging effects by doubling or more than doubling the annual changes in these measures after the diagnosis of mild cognitive impairment, and further doubled them after the diagnosis of Alzheimer's dementia. The longitudinal change of global cognition positively correlated with the longitudinal changes in amplitude and interdaily stability and negatively correlated with the longitudinal change in intradaily variability. Interpretation: Our results indicate a link between circadian dysregulation and Alzheimer's progression, implying either a bidirectional relation or shared common underlying pathophysiological mechanisms. Funding: National Institutes of Health, and the BrightFocus Foundation.

ABSTRACT Age‐related bone loss is common in older adults. However, the association of low bone mass with incident disability and mortality is not well established. A sample of 738 participants in the Rush Memory and Aging Project (MAP) was evaluated at baseline for bone mineral density (BMD) using quantitative ultrasound at the calcaneus. An annual interview assessed basic activities of daily living (BADL), instrumental activities of daily living (IADL), mobility disability, and history of hip fracture. The associations between baseline BMD and risk of death; incident BADL, IADL, and mobility disability; and hip fracture were investigated using Cox hazard models, adjusting for age, sex, education, race, and body mass index (BMI). The robustness of our findings was evaluated by adjusting for confounding factors and health conditions including joint pain, musculoskeletal medications, smoking status, motor function, global cognition, falls, cardiovascular events, and diabetes. Participants were on average (mean ± SD) 80.9 ± 7.0 years old, 72% female, and 3.8% black, with a baseline BMI of 27.3 ± 5.4 kg/m2, and a baseline of BMD of 0.44 ± 0.14 g/cm2. In models adjusted for age, sex, education, race, and BMI, lower BMD was associated with a higher rate of death (hazard ratio [HR] 1.20; 95% confidence interval [CI], 1.08–1.33), incident BADL disability (HR 1.20; 95% CI, 1.05–1.37), and hip fracture (HR 2.57; 95% CI, 1.72–3.82), but not of IADL disability (HR 1.00; 95% CI, 0.85–1.17) or mobility disability (HR 1.13; 95% CI, 0.97–1.32). The association between BMD and mortality was not significant in fully adjusted models, but the BMD and BADL associations remained significant in models adjusting for both demographic variables and BMD‐modifying health conditions. BMD is associated with incident disability in older adults. © 2020 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Background Cardiovascular risk burden has been linked to cardiovascular disease (CVD) and cognitive decline, but its association with disability is unclear. We aimed to examined the association of cardiovascular risk burden assessed by the Framingham general cardiovascular risk score (FGCRS) with the risk and progression of disability and estimated the extent to which CVD and cognitive decline mediate this association. Methods and Results A total of 1480 older adults with no disabilities (mean age=79.32±7.38 years) from the Rush Memory and Aging Project were followed for up to 21 years. FGCRS at baseline was calculated and categorized into tertiles. Disability was assessed annually with activities of daily living. The number of CVDs was calculated by summing up the CVD events. Global cognitive function was assessed annually with a battery of 19 tests. Data were analyzed using the Cox model, linear mixed effects model, and mediation analysis. At the end of the follow‐up, 713 (48.2%) participants developed disability. Compared with the lowest tertile of the FGCRS, the multiadjusted hazards ratios of disability were 1.34 (95% CI, 1.11–1.62) for the highest tertile. In addition, the highest FGCRS was associated with a change in activities of daily living score over time (β=0.057; 95% CI, 0.021–0.093). The association between FGCRS and change in activities of daily living was 13.8% mediated by the accumulation of CVDs and 25.1% by cognitive decline, respectively. Conclusions Higher cardiovascular risk burden increased the risk of disability and accelerated its progression over time. CVD accumulation and cognitive decline may partially mediate the association.

Abstract The use of routine spinal X-rays within chiropractic has a contentious history. Elements of the profession advocate for the need for routine spinal X-rays to improve patient management, whereas other chiropractors advocate using spinal X-rays only when endorsed by current imaging guidelines. This review aims to summarise the current evidence for the use of spinal X-ray in chiropractic practice, with consideration of the related risks and benefits. Current evidence supports the use of spinal X-rays only in the diagnosis of trauma and spondyloarthropathy, and in the assessment of progressive spinal structural deformities such as adolescent idiopathic scoliosis. MRI is indicated to diagnose serious pathology such as cancer or infection, and to assess the need for surgical management in radiculopathy and spinal stenosis. Strong evidence demonstrates risks of imaging such as excessive radiation exposure, overdiagnosis, subsequent low-value investigation and treatment procedures, and increased costs. In most cases the potential benefits from routine imaging, including spinal X-rays, do not outweigh the potential harms. The use of spinal X-rays should not be routinely performed in chiropractic practice, and should be guided by clinical guidelines and clinician judgement.

Background: Parkinson's disease (PD) and progressive supranuclear palsy – Richardson's syndrome (PSP-RS) are often represented by similar clinical symptoms, which may challenge diagnostic accuracy. The objective of this study was to investigate and compare regional cerebral diffusion properties in PD and PSP-RS subjects and evaluate the use of these metrics for an automatic classification framework. Material and methods: Diffusion-tensor MRI datasets from 52 PD and 21 PSP-RS subjects were employed for this study. Using an atlas-based approach, regional median values of mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were measured and employed for feature selection using RELIEFF and subsequent classification using a support vector machine. Results: According to RELIEFF, the top 17 diffusion values consisting of deep gray matter structures, the brainstem, and frontal cortex were found to be especially informative for an automatic classification. A MANCOVA analysis performed on these diffusion values as dependent variables revealed that PSP-RS and PD subjects differ significantly (p

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Alzheimer's disease (AD) involves changes in both lipid and RNA metabolism, but it remained unknown if these differences associate with AD's cognition and/or post-mortem neuropathology indices. Here, we report RNA-sequencing evidence of inter-related associations between lipid processing, cognition level, and AD neuropathology. In two unrelated cohorts, we identified pathway-enriched facilitation of lipid processing and alternative splicing genes, including the neuronal-enriched NOVA1 and hnRNPA1. Specifically, this association emerged in temporal lobe tissue samples from donors where postmortem evidence demonstrated AD neuropathology, but who presented normal cognition proximate to death. The observed changes further associated with modified ATP synthesis and mitochondrial transcripts, indicating metabolic relevance; accordingly, mass-spectrometry-derived lipidomic profiles distinguished between individuals with and without cognitive impairment prior to death. In spite of the limited group sizes, tissues from persons with both cognitive impairment and AD pathology showed elevation in several drug-targeted genes of other brain, vascular and autoimmune disorders, accompanied by pathology-related increases in distinct lipid processing transcripts, and in the RNA metabolism genes hnRNPH2, TARDBP, CLP1 and EWSR1. To further detect 3′-polyadenylation variants, we employed multiple cDNA primer pairs. This identified variants that showed limited differences in scope and length between the tested cohorts, yet enabled superior clustering of demented and non-demented AD brains versus controls compared to total mRNA expression values. Our findings indicate inter-related cognition-associated differences in AD's lipid processing, alternative splicing and 3′-polyadenylation, calling for pursuing the underlying psychological and therapeutics implications.

Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Abstract A method for capturing gait signatures in neurological conditions that allows comparison of human gait with animal models would be of great value in translational research. However, the velocity dependence of gait parameters and differences between quadruped and biped gait have made this comparison challenging. Here we present an approach that accounts for changes in velocity during walking and allows for translation across species. In mice, we represented spatial and temporal gait parameters as a function of velocity and established regression models that reproducibly capture the signatures of these relationships during walking. In experimental parkinsonism models, regression curves representing these relationships shifted from baseline, implicating changes in gait signatures, but with marked differences between models. Gait parameters in healthy human subjects followed similar strict velocity dependent relationships which were altered in Parkinson’s patients in ways that resemble some but not all mouse models. This novel approach is suitable to quantify qualitative walking abnormalities related to CNS circuit dysfunction across species, identify appropriate animal models, and it provides important translational opportunities.

ObjectiveWe examined the association of physical activity, postmortem brain pathologies, and parkinsonism proximate to death in older adults.MethodsWe studied the brains of 447 older decedents participating in a clinical-autopsy cohort study. We deployed a wrist worn activity monitor to record total daily physical activity during everyday living in the community-setting. Parkinsonism was assessed with 26 items of a modified motor portion of Unified Parkinson's Disease Rating Scale (UPDRS). We used linear regression models, controlling for age and sex, to examine the association of physical activity with parkinsonism with and without indices of Alzheimer's disease and related disorders (ADRD) pathologies. In separate models, we added interaction terms to examine if physical activity modified the associations of brain pathologies with parkinsonism.ResultsMean age at death was 90.9 (SD, 6.2), mean severity of parkinsonism was 14.1 (SD, 9.2, Range 0-59.4), and 350 (77%) had evidence of more than one ADRD pathologies. Higher total daily physical activity was associated with less severe parkinsonism (Estimate, -0.315, S.E., 0.052, pConclusionThe association of higher physical activity with less severe parkinsonism may be independent of the presence of ADRD brain pathologies. Further work is needed to identify mechanisms through which physical activity may maintain motor function in older adults.

Abstract An important series of papers have been published in the Lancet. These papers provide a comprehensive update for the major global problem of low back pain, and the challenges that low back pain presents to healthcare practitioners and policy makers. Chiropractors are well placed to reduce the burden of low back pain, but not all that chiropractors do is supported by robust, contemporary evidence. This commentary summarises the Lancet articles. We also make suggestions for how the chiropractic profession should most effectively help people with low back pain by implementing practices supported by high quality evidence.

A genome-wide association meta-analysis study here shows novel genetic loci to be associated to body fat percentage, and describes cross-phenotype association that further demonstrate a close relationship between adiposity and cardiovascular disease risk.

BackgroundCurrently, it is not feasible to obtain laboratory-based measures of joint motion in large numbers of older adults. We assessed the utility of a portable depth-sensing camera for quantifying hip and knee joint motion of older adults during mobility testing in the community.MethodsParticipants were 52 older adults enrolled in the Rush Memory and Aging Project, a community-based cohort study of aging. In a subset, we compared dynamic hip and knee flexion/extension obtained via the depth-sensing camera with that obtained concurrently using a laboratory-based optoelectronic motion capture system. Then we recorded participants' annual instrumented gait assessment in the community setting with the depth-sensing camera and examined the inter-relationships of hip and knee range of motion (ROM) with mobility metrics derived from a wearable sensor and other mobility-related health measures.ResultsIn the community, we successfully acquired joint motion from 49/52 participants using the depth-sensing camera. Hip and knee ROMs were related to diverse sensor-derived metrics of mobility performance (hip: Pearson's r = 0.31 to 0.58; knee: Pearson's r = 0.29 to 0.51), as well as daily physical activity, conventional motor measures, self-report hip and knee pain and dysfunction, mobility disability, and falls.ConclusionsThe depth-sensing camera's high rate of successful data acquisition and correlations of its hip and knee ROMs with other mobility measures suggest that this device can provide a cost-efficient means of quantifying joint motion in large numbers of community-dwelling older adults who span the health spectrum.

Alzheimer's disease and related disorders (ADRD) may manifest cognitive and non-cognitive phenotypes including motor impairment, suggesting a shared underlying biology. We tested the hypothesis that five cortical proteins identified from a gene network that drives AD and cognitive phenotypes are also related to motor function in the same individuals. We examined 1208 brains of older adults with motor and cognitive assessments prior to death. Cortical proteins were quantified with SRM proteomics and we collected indices of AD and other related pathologies. A higher level of IGFBP5 was associated with poorer motor function proximate to death but AK4, HSPB2, ITPK1 and PLXNB1 were unrelated to motor function. The association of IGFBP5 with motor function was unrelated to the presence of indices of brain pathologies. In contrast, the addition of a term for cognition attenuated the association of IGFBP5 with motor function by about 90% and they were no longer related. These data lend support for the idea that unidentified cortical proteins like IGFBP5, which may not manifest a known pathologic footprint, may contribute to motor and cognitive function in older adults.

BackgroundThere are few data concerning the association between season and cognition and its neurobiological correlates in older persons-effects with important translational and therapeutic implications for the diagnosis and treatment of Alzheimer disease (AD). We aimed to measure these effects.Methods and findingsWe analyzed data from 3,353 participants from 3 observational community-based cohort studies of older persons (the Rush Memory and Aging Project [MAP], the Religious Orders Study [ROS], and the Minority Aging Research Study [MARS]) and 2 observational memory-clinic-based cohort studies (Centre de Neurologie Cognitive [CNC] study at Lariboisière Hospital and the Sunnybrook Dementia Study [SDS]). We performed neuropsychological testing and, in subsets of participants, evaluated cerebrospinal fluid AD biomarkers, standardized structured autopsy measures, and/or prefrontal cortex gene expression by RNA sequencing. We examined the association between season and these variables using nested multiple linear and logistic regression models. There was a robust association between season and cognition that was replicated in multiple cohorts (amplitude = 0.14 SD [a measure of the magnitude of seasonal variation relative to overall variability; 95% CI 0.07-0.23], p = 0.007, in the combined MAP, ROS, and MARS cohorts; amplitude = 0.50 SD [95% CI 0.07-0.66], p = 0.017, in the SDS cohort). Average composite global cognitive function was higher in the summer and fall compared to winter and spring, with the difference equivalent in cognitive effect to 4.8 years' difference in age (95% CI 2.1-8.4, p = 0.002). Further, the odds of meeting criteria for mild cognitive impairment or dementia were higher in the winter and spring (odds ratio 1.31 [95% CI 1.10-1.57], p = 0.003). These results were robust against multiple potential confounders including depressive symptoms, sleep, physical activity, and thyroid status and persisted in cases with AD pathology. Moreover, season had a marked effect on cerebrospinal fluid Aβ 42 level (amplitude 0.30 SD [95% CI 0.10-0.64], p = 0.003), which peaked in the summer, and on the brain expression of 4 cognition-associated modules of co-expressed genes (m6: amplitude = 0.44 SD [95% CI 0.21-0.65], p = 0.0021; m13: amplitude = 0.46 SD [95% CI 0.27-0.76], p = 0.0009; m109: amplitude = 0.43 SD [95% CI 0.24-0.67], p = 0.0021; and m122: amplitude 0.46 SD [95% CI 0.20-0.71], p = 0.0012), which were in phase or anti-phase to the rhythms of cognition and which were in turn associated with binding sites for several seasonally rhythmic transcription factors including BCL11A, CTCF, EGR1, MEF2C, and THAP1. Limitations include the evaluation of each participant or sample once per annual cycle, reliance on self-report for measurement of environmental and behavioral factors, and potentially limited generalizability to individuals in equatorial regions or in the southern hemisphere.ConclusionsSeason has a clinically significant association with cognition and its neurobiological correlates in older adults with and without AD pathology. There may be value in increasing dementia-related clinical resources in the winter and early spring, when symptoms are likely to be most pronounced. Moreover, the persistence of robust seasonal plasticity in cognition and its neurobiological correlates, even in the context of concomitant AD pathology, suggests that targeting environmental or behavioral drivers of seasonal cognitive plasticity, or the key transcription factors and genes identified in this study as potentially mediating these effects, may allow us to substantially improve cognition in adults with and without AD.