Association of back pain with all-cause and cause-specific mortality among older men: a cohort study.

OBJECTIVE: We evaluated whether more severe back pain phenotypes-persistent, frequent or disabling back pain-are associated with higher mortality among older men. METHODS: In this secondary analysis of a prospective cohort, the Osteoporotic Fractures in Men (MrOS) study, we evaluated mortality rates by back pain phenotype among 5215 older community-dwelling men (mean age, 73 years, SD = 5.6) from six U.S. sites. The primary back pain measure used baseline and year five back pain questionnaire data to characterize participants as having: no back pain; non-persistent back pain; infrequent persistent back pain; or frequent persistent back pain. Secondary measures of back pain from year five questionnaire included disabling back pain phenotypes. The main outcomes measured were all-cause and cause-specific mortality. RESULTS: After the year five exam, during up to 18 years of follow-up (mean follow-up=10.3 years), there were 3513 deaths (1218 cardiovascular, 764 cancer, 1531 other). A higher proportion of men with frequent persistent back pain versus no back pain died (78% versus 69%; sociodemographic-adjusted HR = 1.27, 95%CI=1.11-1.45). No association was evident after further adjusting for health-related factors such as self-reported general health and comorbid chronic health conditions (fully-adjusted HR = 1.00; 95%CI=0.86-1.15). Results were similar for cardiovascular mortality and other mortality, but we observed no association of back pain with cancer mortality. Secondary back pain measures including back-related disability were associated with increased mortality risk that remained statistically significant in fully-adjusted models. CONCLUSION: While frequent persistent back pain was not independently associated with mortality in older men, additional secondary disabling back pain phenotypes were independently associated with increased mortality. Future investigations should evaluate whether improvements in disabling back pain effect general health and well-being or mortality.

Prospective Back Pain Trajectories or Retrospective Recall-Which Tells Us Most About the Patient?

In patients with low back pain (LBP), a visually identified retrospective pain trajectory often mismatches with a trajectory derived from prospective repeated measures. To gain insight into the clinical relevance of the 2 trajectory types, we investigated which showed a higher association with clinical outcomes. Participants were 724 adults seeking care for LBP in Danish chiropractic primary care. They answered weekly short-message-services on pain intensity and frequency over 52 weeks, which we translated into 8 trajectory classes. After 52 weeks, participants selected a retrospective visual pain trajectory from the same 8 trajectory classes. Clinical outcomes included disability, back/leg pain intensity, back beliefs, and work ability. The patient-selected pain trajectory classes were more strongly associated with clinical outcomes than the short-message-service trajectory classes at baseline, at follow-up, and with outcome changes between baseline and follow-up. This held across all 5 clinical outcomes, with the strongest associations observed at week 52 and the weakest at baseline. Patients' retrospective assessment of their LBP is more strongly associated with their clinical status than their prospective assessments translated into trajectory classes. This suggests that retrospective assessments of pain trajectories may provide valuable information not captured by prospective assessments. Researchers collecting prospective pain data should know that the captured pain trajectories are not strongly reflected in patients' perceptions of clinical status. Patients' retrospective assessments seem to offer an interpretation of their pain course that is likely more clinically relevant in understanding the perceived impact of their condition than trajectories based on repeated measures. PERSPECTIVE: Prospective pain data inadequately reflect patients' clinical status. Retrospective assessments provide a more clinically valuable understanding of the impact of their condition.

Association of Alzheimer's Disease and Other Neuropathologies with Functional Disability in Persons With and Without Dementia.

BACKGROUND: Dementia results from multiple neuropathologies causing cognitive impairment sufficiently severe to impact functional status. However, these pathologies and functional impairment are common in persons without dementia. We examined the association of AD and multiple other neuropathologies with instrumental and basic activities of daily living in persons with and without dementia. METHODS: Participants were 1,509 deceased from the Religious Orders Study or Rush Memory and Aging Project. Pathologic AD and three other AD indices were examined, in addition to four non-AD neurodegenerative pathologies: cerebral amyloid angiopathy (CAA), hippocampal sclerosis, TDP-43 and Lewy bodies, and four cerebrovascular pathologies: gross- and microinfarctions, athero- and arteriolosclerosis. Functional assessment included Lawton and Katz Index Instrumental and Basic Activities of Daily Living (IADL and BADL). Ordinal regression models adjusted for age, sex, and education were used to examine the association of neuropathologies with IADL and BADL. RESULTS: AD and the other neuropathologies were associated with impaired IADL (all Ps<0.001) and with impaired BADL (Ps<0.01), except for atherosclerosis and CAA which were not associated with BADL. The effects of most neuropathologies were largely affected by dementia. However, small effects on IADL remained for PHFtau tangles after adjusting models for dementia. Direct effects of gross infarcts on IADL and BADL, and of microinfarcts on BADL remained unchanged after adjusting the models for dementia. CONCLUSION: AD and all other neuropathologies are strongly associated with functional disability. The association of most neuropathologies with disability was eliminated or attenuated by dementia, except for gross infarcts and microinfarcts.

Automated Gait Detection in Older Adults during Daily-Living using Self-Supervised Learning of Wrist-Worn Accelerometer Data: Development and Validation of ElderNet.

Progressive gait impairment is common in 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 1,000 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 < 0.05). In an initial evaluation of construct validity, ElderNet identified differences in estimated daily walking durations across cohorts with different clinical characteristics, such as mobility disability (p < 0.001) and parkinsonism (p < 0.001). The proposed self-supervised gait detection method has the potential to serve as a valuable tool for remote phenotyping of gait function during daily living in aging adults.

Digital quantification of the MMSE interlocking pentagon areas: a three-stage algorithm.

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.

The time course of motor and cognitive decline in older adults and their associations with brain pathologies: a multicohort study.

BACKGROUND: Many studies have reported that impaired gait precedes cognitive impairment in older people. We aimed to characterise the time course of cognitive and motor decline in older individuals and the association of these declines with the pathologies of Alzheimer's disease and related dementias. METHODS: This multicohort study used data from three community-based cohort studies (Religious Orders Study, Rush Memory and Aging Project, and Minority Aging Research Study, all in the USA). The inclusion criteria for all three cohorts were no clinical dementia at the time of enrolment and consent to annual clinical assessments. Eligible participants consented to post-mortem brain donation and had post-mortem pathological assessments and three or more repeated annual measures of cognition and motor functions. Clinical and post-mortem data were analysed using functional mixed-effects models. Global cognition was based on 19 neuropsychological tests, a hand strength score was based on grip and pinch strength, and a gait score was based on the number of steps and time to walk 8 feet and turn 360°. Brain pathologies of Alzheimer's disease and related dementias were assessed at autopsy. FINDINGS: From 1994 to 2022, there were 1570 eligible cohort participants aged 65 years or older, 1303 of whom had cognitive and motor measurements and were included in the analysis. Mean age at death was 90·3 years (SD 6·3), 905 (69%) participants were female, and 398 (31%) were male. Median follow-up time was 9 years (IQR 5-11). On average, cognition was stable from 25 to 15 years before death, when cognition began to decline. By contrast, gait function and hand strength declined during the entire study. The combinations of pathologies of Alzheimer's disease and related dementias associated with cognitive and motor decline and their onsets of associations varied; only tau tangles, Parkinson's disease pathology, and macroinfarcts were associated with decline of all three phenotypes. Tau tangles were significantly associated with cognitive decline, gait function decline, and hand function decline (p<0·0001 for each); however, the association with cognitive decline persisted for more than 11 years before death, but the association with hand strength only began 3·57 years before death and the association with gait began 3·49 years before death. By contrast, the association of macroinfarcts with declining gait function began 9·25 years before death (p<0·0001) compared with 6·65 years before death (p=0·0005) for cognitive decline and 2·66 years before death (p=0·024) for decline in hand strength. INTERPRETATION: Our findings suggest that average motor decline in older adults precedes cognitive decline. Macroinfarcts but not tau tangles are associated with declining gait function that precedes cognitive decline. This suggests the need for further studies to test if gait impairment is a clinical proxy for preclinical vascular cognitive impairment. FUNDING: National Institutes of Health.

Purpose in Life and Its Association to Parkinsonism.

OBJECTIVES: Purpose in life has been associated with diverse health outcomes; however, few studies have examined its associations with progressive motor decline in older adults. We tested if higher purpose would be associated with lower likelihood of incident parkinsonism as well as with lower levels and slower rates of increase in parkinsonian signs. METHODS: Participants were 2,626 older adults from the Rush Memory and Aging Project and Minority Aging Research Study followed for an average of 7.2 years (standard deviation [SD] = 4.6). Purpose was measured using the purpose in life subscale of the modified Ryff's and Keyes's measure of psychological well-being. Four parkinsonian signs (i.e., parkinsonian gait, rigidity, bradykinesia, and tremor) were assessed using the United Parkinson's Disease Rating Scale. We examined purpose with risk of developing incident parkinsonism using Cox proportional hazards models. We also used linear mixed-effect models to assess the association between purpose and parkinsonian sign trajectories. RESULTS: After including demographics, health conditions, and health behaviors in the model, for a 1-SD increase in purpose, the hazards ratio for incident parkinsonism was 0.88 (95% confidence interval [CI] 0.80, 0.97). A 1-SD increase in purpose was associated with a -0.19 (95% CI -0.24, -0.15) point lower score in the global parkinsonian summary score at baseline but no differences in rate of change were evident. DISCUSSION: Higher purpose was associated with lower hazards of incident parkinsonism and lower levels of parkinsonian signs at baseline. Associations were seen even after adjustment for a wide range of covariates. Findings suggest higher purpose may contribute to maintenance of healthy physical function among older adults.

Glycoproteome-Wide Discovery of Cortical Glycoproteins That May Provide Cognitive Resilience in Older Adults.

BACKGROUND AND OBJECTIVES: Molecular omics studies have identified proteins related to cognitive resilience but unrelated to Alzheimer disease and Alzheimer disease-related dementia (AD/ADRD) pathologies. Posttranslational modifications of proteins with glycans can modify protein function. In this study, we identified glycopeptiforms associated with cognitive resilience. METHODS: We studied brains from adults with annual cognitive testing with postmortem indices of 10 AD/ADRD pathologies and proteome-wide data from dorsal lateral prefrontal cortex (DLPFC). We quantified 11, 012 glycopeptiforms from DLPFC using liquid chromatography with tandem mass spectrometry. We used linear mixed-effects models to identify glycopeptiforms associated with cognitive decline correcting for multiple comparisons (p < 5 × 10-6). Then, we regressed out the effect of AD/ADRD pathologies to identify glycopeptiforms that may provide cognitive resilience. RESULTS: We studied 366 brains, average age at death 89 years, and 70% female with no cognitive impairment = 152, mild cognitive impairment = 93, and AD = 121 cognitive status at death. In models adjusting for age, sex and education, 11 glycopeptiforms were associated with cognitive decline. In further modeling, 8 of these glycopeptiforms remained associated with cognitive decline after adjusting for AD/ADRD pathologies: NPTX2a (Est., 0.030, SE, 0.005, p = 1 × 10-4); NPTX2b (Est.,0.019, SE, 0.005, p = 2 × 10-4) NECTIN1(Est., 0.029, SE, 0.009, p = 9 × 10-4), NPTX2c (Est., 0.015, SE, 0.004, p = 9 × 10-4), HSPB1 (Est., -0.021, SE, 0.006, p = 2 × 10-4), PLTP (Est., -0.027, SE, 0.009, p = 4.2 × 10-3), NAGK (Est., -0.027, SE, 0.008, p = 1.4 × 10-3), and VAT1 (Est., -0.020, SE, 0.006, p = 1.1 × 10-3). Higher levels of 4 resilience glycopeptiforms derived through glycosylation were associated with slower decline and higher levels of 4 derived through glycation were related to faster decline. Together, these 8 glycopeptiforms accounted for an additional 6% of cognitive decline over the 33% accounted for the 10 brain pathologies and demographics. All 8 resilience glycopeptiforms remained associated with cognitive decline after adjustments for the expression level of their corresponding protein. Exploratory gene ontology suggested that molecular mechanisms of glycopeptiforms associated with cognitive decline may involve metabolic pathways including pyruvate and NADH pathways and highlighted the importance of molecular mechanisms involved in glucose metabolism. DISCUSSION: Glycopeptiforms in aging brains may provide cognitive resilience. Targeting these glycopeptiforms may lead to therapies that maintain cognition through resilience.

Delineating cognitive resilience using fractal regulation: Cross-sectional and longitudinal evidence from the Rush Memory and Aging Project.

INTRODUCTION: Degradation of fractal patterns in actigraphy independently predicts dementia risk. Such observations motivated the study to understand the role of fractal regulation in the context of neuropathologies. METHODS: We examined associations of fractal regulation with neuropathologies and longitudinal cognitive changes in 533 older participants who were followed annually with actigraphy and cognitive assessments until death with brain autopsy performed. Two measures for fractal patterns were extracted from actigraphy, namely, α1 (representing the fractal regulation at time scales of <90 min) and α2 (for time scales 2 to 10 h). RESULTS: We found that larger α1 was associated with lower burdens of Lewy body disease or cerebrovascular disease pathologies; both α1 and α2 were associated with cognitive decline. They explained an additional significant portion of the variance in the rate of cognitive decline above and beyond neuropathologies. DISCUSSION: Fractal patterns may be used as a biomarker for cognitive resilience against dementia-related neuropathologies.

Inferring Alzheimer's Disease Pathologic Traits from Clinical Measures in Living Adults.

Background: Alzheimer's disease neuropathologic changes (AD-NC) are important to identify people with high risk for AD dementia (ADD) and subtyping ADD. Objective: Develop imputation models based on clinical measures to infer AD-NC. Methods: We used penalized generalized linear regression to train imputation models for four AD-NC traits (amyloid-ß, tangles, global AD pathology, and pathologic AD) in Rush Memory and Aging Project decedents, using clinical measures at the last visit prior to death as predictors. We validated these models by inferring AD-NC traits with clinical measures at the last visit prior to death for independent Religious Orders Study (ROS) decedents. We inferred baseline AD-NC traits for all ROS participants at study entry, and then tested if inferred AD-NC traits at study entry predicted incident ADD and postmortem pathologic AD. Results: Inferred AD-NC traits at the last visit prior to death were related to postmortem measures with R2 = (0.188,0.316,0.262) respectively for amyloid-ß, tangles, and global AD pathology, and prediction Area Under the receiver operating characteristic Curve (AUC) 0.765 for pathologic AD. Inferred baseline levels of all four AD-NC traits predicted ADD. The strongest prediction was obtained by the inferred baseline probabilities of pathologic AD with AUC = (0.919,0.896) for predicting the development of ADD in 3 and 5 years from baseline. The inferred baseline levels of all four AD-NC traits significantly discriminated pathologic AD profiled eight years later with p-values < 1.4×10-10. Conclusions: Inferred AD-NC traits based on clinical measures may provide effective AD biomarkers that can estimate the burden of AD-NC traits in aging adults.

Altered Motor Activity Patterns within 10-Minute Timescale Predict Incident Clinical Alzheimer's Disease.

Background: Fractal motor activity regulation (FMAR), characterized by self-similar temporal patterns in motor activity across timescales, is robust in healthy young humans but degrades with aging and in Alzheimer's disease (AD). Objective: To determine the timescales where alterations of FMAR can best predict the clinical onset of AD. Methods: FMAR was assessed from actigraphy at baseline in 1,077 participants who had annual follow-up clinical assessments for up to 15 years. Survival analysis combined with deep learning (DeepSurv) was used to examine how baseline FMAR at different timescales from 3 minutes up to 6 hours contributed differently to the risk for incident clinical AD. Results: Clinical AD occurred in 270 participants during the follow-up. DeepSurv identified three potential regions of timescales in which FMAR alterations were significantly linked to the risk for clinical AD: <10, 20-40, and 100-200 minutes. Confirmed by the Cox and random survival forest models, the effect of FMAR alterations in the timescale of <10 minutes was the strongest, after adjusting for covariates. Conclusions: Subtle changes in motor activity fluctuations predicted the clinical onset of AD, with the strongest association observed in activity fluctuations at timescales <10 minutes. These findings suggest that short actigraphy recordings may be used to assess the risk of AD.

Proteome-wide Analyses Identified Cortical Proteins Associated With Resilience for Varied Cognitive Abilities.

BACKGROUND AND OBJECTIVES: Prior work suggests that cognitive resilience may contribute to the heterogeneity of cognitive decline. This study examined whether distinct cortical proteins provide resilience for different cognitive abilities. METHODS: Participants were from the Religious Orders Study or the Rush Memory and Aging Project who had undergone annual assessments of 5 cognitive abilities and postmortem assessment of 9 Alzheimer disease and related dementia (ADRD) pathologies. Proteome-wide examination of the dorsolateral prefrontal cortex using tandem mass tag and liquid chromatography-mass spectrometry yielded 8,425 high-abundance proteins. We applied linear mixed-effect models to quantify residual cognitive change (cognitive resilience) of 5 cognitive abilities by regressing out cognitive decline related to age, sex, education, and indices of ADRD pathologies. Then we added terms for each of the individual proteins to identify cognitive resilience proteins associated with the different cognitive abilities. RESULTS: We included 604 decedents (69% female; mean age at death = 89 years) with proteomic data. A total of 47 cortical proteins that provide cognitive resilience were identified: 22 were associated with specific cognitive abilities, and 25 were common to at least 2 cognitive abilities. NRN1 was the only protein that was associated with more than 2 cognitive abilities (semantic memory: estimate = 0.020, SE = 0.004, p = 2.2 × 10-6; episodic memory: estimate = 0.029, SE = 0.004, p = 5.8 × 10-1; and working memory: estimate = 0.021, SE = 0.004, p = 1.2 × 10-7). Exploratory gene ontology analysis suggested that among top molecular pathways, mitochondrial translation was a molecular mechanism providing resilience in episodic memory, while nuclear-transcribed messenger RNA catabolic processes provided resilience in working memory. DISCUSSION: This study identified cortical proteins associated with various cognitive abilities. Differential associations across abilities may reflect distinct underlying biological pathways. These data provide potential high-value targets for further mechanistic and drug discovery studies to develop targeted treatments to prevent loss of cognition.

Untangling a taxonomy of living from the science of the continuum of life.

Medical innovation and technologic advances enrich daily living and occur within our normative worlds, that are socially constructed. These advances confront society with critical questions about the nature of human life, laying bare the inadequacies of extant norms and boundaries. Yet, society has been unable to develop consensus about when life ends. Scientific studies highlight that life is best characterized by continua without natural boundaries. Thus, scientific information alone cannot be employed to justify the socially constructed health categories required for setting norms and boundaries. An iterative process that integrates a broad range of non-scientific data with advancing scientific information is needed to facilitate consensus for updating social norms and boundaries. This can lead to a new taxonomy of living across the measurable continuum of life and align our normative worlds with the dizzying pace of medical innovation and advances in technologies transforming the world in which we live.

SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine Learning.

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 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 showed that SR-TWAS improved power, due to increased effective 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 application studies identified 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 were found for these significant risk genes.

Inferring Alzheimer's disease pathologic traits from clinical measures in living adults.

Background: Alzheimer's disease neuropathologic changes (AD-NC) are important for identify people with high risk for AD dementia (ADD) and subtyping ADD. Objective: Develop imputation models based on clinical measures to infer AD-NC. Methods: We used penalized generalized linear regression to train imputation models for four AD-NC traits (amyloid-ß, tangles, global AD pathology, and pathologic AD) in Rush Memory and Aging Project decedents, using clinical measures at the last visit prior to death as predictors. We validated these models by inferring AD-NC traits with clinical measures at the last visit prior to death for independent Religious Orders Study (ROS) decedents. We inferred baseline AD-NC traits for all ROS participants at study entry, and then tested if inferred AD-NC traits at study entry predicted incident ADD and postmortem pathologic AD. Results: Inferred AD-NC traits at the last visit prior to death were related to postmortem measures with R2=(0.188,0.316,0.262) respectively for amyloid-ß, tangles, and global AD pathology, and prediction Area Under the receiver operating characteristic Curve (AUC) 0.765 for pathologic AD. Inferred baseline levels of all four AD-NC traits predicted ADD. The strongest prediction was obtained by the inferred baseline probabilities of pathologic AD with AUC=(0.919,0.896) for predicting the development of ADD in 3 and 5 years from baseline. The inferred baseline levels of all four AD-NC traits significantly discriminated pathologic AD profiled eight years later with p-values<1.4 × 10-10. Conclusion: Inferred AD-NC traits based on clinical measures may provide effective AD biomarkers that can estimate the burden of AD-NC traits in aging adults.

A prospective study of the association of cognitive and motor function with odds of life space constriction in older adults.

BACKGROUND: Many studies indicate that smaller life space is related to worse cognitive and motor function. It is plausible that cognitive and motor function also predict life space constriction, thus long-term, prospective studies are needed of cognitive and motor function as predictors of life space. METHODS: A total of 1246 participants of the Rush Memory and Aging Project, who reported initial maximal life space and at least one follow-up assessment were included in this prospective study, with up to 19 years follow-up. The outcome of interest was the Modified version of the Life Space Questionnaire; which we categorized into large (beyond community), medium (neighborhood/community), and small (home/yard) life space. Participants also had detailed composite measures of global cognition and motor function as predictors and available at the first life space assessment. Life space transitions over one-year periods were modeled using multistate Markov modeling, including confounders and both predictors simultaneously. RESULTS: Better cognitive and motor function were broadly associated with lower odds of life space constriction (Cognitive: Large ➔ medium: OR = 0.91, 95% CI 0.83-1.00; Large ➔ small: OR = 0.85, 95% CI 0.74-0.97; Medium ➔ small: OR = 1.01, 95% CI 0.82-1.22. Motor: large ➔ medium: OR = 0.76, 95% CI 0.69-0.83; large ➔ small: OR = 0.58, 95% CI 0.51-0.67; medium ➔ small: OR = 0.71, 95% CI = 0.57-0.87). CONCLUSIONS: Combined with previous literature that life space predicts function, these results support the notion of complex inter-relations of cognitive function, motor function, and life space.

Circadian disturbances and frailty risk in older adults.

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.

Volumetric brain correlates of gait associated with cognitive decline in community-dwelling older adults.

Objective: To 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. Approach: We 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. Results: In 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. Conclusion: Regional 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.

Differential gene expression analysis based on linear mixed model corrects false positive inflation for studying quantitative traits.

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.