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Abstract Climate change is imposing new selective pressures on forest tree populations. Evolutionary responses may be important for trees, despite long generation times, since many populations harbor significant genetic variation in environmentally relevant traits. However, the heritability of climate responses (e.g., how much growth differs under drought) has been investigated in only one tree species previously. Here, we quantify heritable variation in environmental response traits of Pinus ponderosa using a greenhouse trial. Five seedlings from each maternal family were exposed to either wet or dry treatments for four months. Traits measured include height and root length, root:shoot mass ratios, and stomatal density and number of rows. Narrow‐sense heritability for all traits was estimated using a half‐sib analysis. Many traits varied by treatment, and some also differed along gradients of “home” climate. Dry treatment root‐to‐shoot dry mass ratio was associated with survival in that treatment. Estimated heritability for drought responsiveness ranged from 0.15 to 0.65, with the highest values occurring in height growth responses. Variation was particularly high for shoot growth under drought conditions. Our results suggest that increasingly arid conditions could result in strong responses to selection.

Objectives Obstructive sleep apnea (OSA) is typically diagnosed by polysomnography (PSG). However, PSG is time-consuming and has some clinical limitations. This study thus aimed to establish machine learning models to screen for the risk of having moderate-to-severe and severe OSA based on easily acquired features. Methods We collected PSG data on 3529 patients from Taiwan and further derived the number of snoring events. Their baseline characteristics and anthropometric measures were obtained, and correlations among the collected variables were investigated. Next, six common supervised machine learning techniques were utilized, including random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor (kNN), support vector machine (SVM), logistic regression (LR), and naïve Bayes (NB). First, data were independently separated into a training and validation dataset (80%) and a test dataset (20%). The approach with the highest accuracy in the training and validation phase was employed to classify the test dataset. Next, feature importance was investigated by calculating the Shapley value of every factor, which represented the impact on OSA risk screening. Results The RF produced the highest accuracy (of >70%) in the training and validation phase in screening for both OSA severities. Hence, we employed the RF to classify the test dataset, and results showed a 79.32% accuracy for moderate-to-severe OSA and 74.37% accuracy for severe OSA. Snoring events and the visceral fat level were the most and second most essential features of screening for OSA risk. Conclusions The established model can be considered for screening for the risk of having moderate-to-severe or severe OSA.

ObjectivesObstructive sleep apnea (OSA) may increase the risk of Alzheimer's disease (AD). However, potential associations among sleep-disordered breathing, hypoxia, and OSA-induced arousal responses should be investigated. This study determined differences in sleep parameters and investigated the relationship between such parameters and the risk of AD.MethodsPatients with suspected OSA were recruited and underwent in-lab polysomnography (PSG). Subsequently, blood samples were collected from participants. Patients' plasma levels of total tau (T-Tau) and amyloid beta-peptide 42 (Aβ42) were measured using an ultrasensitive immunomagnetic reduction assay. Next, the participants were categorized into low- and high-risk groups on the basis of the computed product (Aβ42 × T-Tau, the cutoff for AD risk). PSG parameters were analyzed and compared.ResultsWe included 36 patients in this study, of whom 18 and 18 were assigned to the low- and high-risk groups, respectively. The average apnea–hypopnea index (AHI), apnea, hypopnea index [during rapid eye movement (REM) and non-REM (NREM) sleep], and oxygen desaturation index (≥3%, ODI-3%) values of the high-risk group were significantly higher than those of the low-risk group. Similarly, the mean arousal index and respiratory arousal index (R-ArI) of the high-risk group were significantly higher than those of the low-risk group. Sleep-disordered breathing indices, oxygen desaturation, and arousal responses were significantly associated with an increased risk of AD. Positive associations were observed among the AHI, ODI-3%, R-ArI, and computed product.ConclusionsRecurrent sleep-disordered breathing, intermittent hypoxia, and arousal responses, including those occurring during the NREM stage, were associated with AD risk. However, a longitudinal study should be conducted to investigate the causal relationships among these factors.

Obstructive sleep apnea (OSA) is a risk factor for neurodegenerative diseases. This study determined whether continuous positive airway pressure (CPAP), which can alleviate OSA symptoms, can reduce neurochemical biomarker levels. Thirty patients with OSA and normal cognitive function were recruited and divided into the control (n = 10) and CPAP (n = 20) groups. Next, we examined their in-lab sleep data (polysomnography and CPAP titration), sleep-related questionnaire outcomes, and neurochemical biomarker levels at baseline and the 3-month follow-up. The paired t-test and Wilcoxon signed-rank test were used to examine changes. Analysis of covariance (ANCOVA) was performed to increase the robustness of outcomes. The Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index scores were significantly decreased in the CPAP group. The mean levels of total tau (T-Tau), amyloid-beta-42 (Aβ42), and the product of the two (Aβ42 × T-Tau) increased considerably in the control group (ΔT-Tau: 2.31 pg/mL; ΔAβ42: 0.58 pg/mL; ΔAβ42 × T-Tau: 48.73 pg2/mL2), whereas the mean levels of T-Tau and the product of T-Tau and Aβ42 decreased considerably in the CPAP group (ΔT-Tau: −2.22 pg/mL; ΔAβ42 × T-Tau: −44.35 pg2/mL2). The results of ANCOVA with adjustment for age, sex, body mass index, baseline measurements, and apnea–hypopnea index demonstrated significant differences in neurochemical biomarker levels between the CPAP and control groups. The findings indicate that CPAP may reduce neurochemical biomarker levels by alleviating OSA symptoms.

Obstructive sleep apnea (OSA) is a global health concern and is typically diagnosed using in-laboratory polysomnography (PSG). However, PSG is highly time-consuming and labor-intensive. We, therefore, developed machine learning models based on easily accessed anthropometric features to screen for the risk of moderate to severe and severe OSA. We enrolled 3503 patients from Taiwan and determined their PSG parameters and anthropometric features. Subsequently, we compared the mean values among patients with different OSA severity and considered correlations among all participants. We developed models based on the following machine learning approaches: logistic regression, k-nearest neighbors, naïve Bayes, random forest (RF), support vector machine, and XGBoost. Collected data were first independently split into two data sets (training and validation: 80%; testing: 20%). Thereafter, we adopted the model with the highest accuracy in the training and validation stage to predict the testing set. We explored the importance of each feature in the OSA risk screening by calculating the Shapley values of each input variable. The RF model achieved the highest accuracy for moderate to severe (84.74%) and severe (72.61%) OSA. The level of visceral fat was found to be a predominant feature in the risk screening models of OSA with the aforementioned levels of severity. Our machine learning models can be employed to screen for OSA risk in the populations in Taiwan and in those with similar craniofacial structures.

[This corrects the article DOI: 10.1371/journal.pone.0221750.].

Background: As the disease progresses to moderate to advanced stages, people with Parkinson's disease (PwP) are likely to have various degrees of disability due to the motor and non-motor symptoms, such as ambulatory difficulty and cognitive impairment. The objective of this study was to investigate the impact of cognition and ambulation status on the functioning and disability of PwP using the World Health Orgnaization Disability Assessment Schedule 2.0 (WHODAS 2.0).Materials and Methods: A group of 10,581 PwP with Hoehn and Yahr Staging 3 and above were collected from a database of disability evaluation and functional assessment using the Taiwan Data Bank of Persons with Disability between July 2012 and October 2018. WHODAS 2.0 was administered and all PwP were grouped based on their ambulatory status, which was assessed by 3-m back and forth walk and cognitive ability, assessed by WHODAS 2.0 first domain with cut-off level at 58.Results: Non-ambulation and cognitive disability contributed independently to disability in all aspects of WHODAS 2.0 survey, including self-care, getting along with others, performing life activities and participation in society. Compared to ambulation status, cognitive disability had a greater negative impact on functioning in all aspects.Conclusion: Cognitive disability was associated with greater disability in moderate to advanced PwP than non-ambulatory status. The results of this study may indicate that cognition preservation is essential to ameliorate functional impairment and disability in moderate to advanced PwP.

Neurodegenerative diseases, such as dementia, Parkinson's disease, and parkinsonism, are due to the gradual and progressive loss of neural cells, leading to nervous system dysfunction. Increasing epidemiological and toxicological evidence has demonstrated the possible association between neurological diseases and particulate air pollution. Chronic exposure to particulate matter (PM) of < 2.5 μm in aerodynamic size (PM2.5) is related to reductions in white matter and gray matter in brains of older women. Alterations of the structural integrity of the brain were reported for particulate air pollution-induced neurological disorders. Clinically, intraneuronal accumulation of tau proteins is considered to be an important hallmark of the development of neurodegenerative diseases. In Alzheimer's disease brains, for example, hyperphosphorylated levels of tau are around 3–4 times higher than levels in normal adult brains. Tau overexpression in neuroblastoma cells can lead to tau aggregations and the appearance of smaller proteolytic fragments. Degradative mechanisms, such as autophagy that remove tau from cells are considered essential functions for maintaining the brain's health. Notably, increasing numbers of reports have indicated that autophagy dysfunction occurs due to particulate air pollution in vitro and in vivo. Dysfunction of autophagy can lead to tau accumulation in the brain. We reviewed the effects of particulate air pollution on neurological diseases and the underlying mechanisms (i.e., tau and autophagy). Further toxicological evidence is required to fill in the gaps between epidemiological and clinical observations.

Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear. We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over three subsequent nights. Scores on OSA indices—namely, the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into three groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons, and their correlations were examined by Pearson’s correlation coefficient. The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All three groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment, compared with the hospital-based assessment. The percentage of supine sleep time (∆Supine%) exhibited a significant but weak to moderate positive correlation with each of the OSA indices. A significant but weak-to-moderate correlation between the ∆Supine% and ∆Rx index was still observed among the patients with high sleep efficiency (≥80%), who could reduce the effect of short sleep duration, leading to underestimation of the patients’ OSA severity. The high supine percentage of sleep may cause OSA indices’ overestimation in the hospital-based examination. Sleep recording at home with patch-type wearable devices may aid in accurate OSA diagnosis.

Insomnia disorder (ID) and obstructive sleep apnea (OSA) with respiratory arousal threshold (ArTH) phenotypes often coexist in patients, presenting similar symptoms. However, the typical diagnosis examinations (in-laboratory polysomnography (lab-PSG) and other alternatives methods may therefore have limited differentiation capacities. Hence, this study established novel models to assist in the classification of ID and low- and high-ArTH OSA. Participants reporting insomnia as their chief complaint were enrolled. Their sleep parameters and body profile were accessed from the lab-PSG database. Based on the definition of low-ArTH OSA and ID, patients were divided into three groups, namely, the ID, low- and high-ArTH OSA groups. Various machine learning approaches, including logistic regression, k-nearest neighbors, naive Bayes, random forest (RF), and support vector machine, were trained using two types of features (Oximetry model, trained with oximetry parameters only; Combined model, trained with oximetry and anthropometric parameters). In the training stage, RF presented the highest cross-validation accuracy in both models compared with the other approaches. In the testing stage, the RF accuracy was 77.53% and 80.06% for the oximetry and combined models, respectively. The established models can be used to differentiate ID, low- and high-ArTH OSA in the population of Taiwan and those with similar craniofacial features.

Introduction: Dizziness and balance impairment are common symptoms of mild traumatic brain injury (mTBI). Acid-sensing ion channel 3 (ASIC3) is expressed in the vestibular and proprioceptive systems and associated with balance functions. However, whether the genetic variants of ASIC3 are associated with people who suffer dizziness and balance impairment after mTBI remained unknown.Materials and methods: A total of 200 people with mTBI and 109 non-mTBI controls were recruited. Dizziness, balance functions, and the ability to perform daily activities were assessed by Dizziness Handicap Inventory (DHI), and objective balance functions were investigated by the postural stability test. Three diseases-related genetic variants of ASIC3 were determined through polymerase chain reaction and followed by restriction fragment length polymorphism. The Student's t-test and Mann-Whitney U-test were used for normal and abnormal distributed data, respectively. The regression was applied to adjust gender and age. The normality of continuous data was evaluated by Shapiro-Wilk test.Results: In the mTBI people, the rs2288645-A allele carriers exhibited a significantly worse physical domain DHI score (A-allele carriers: 11.39 ± 8.42, non-A carriers: 8.76 ± 7.87, p = 0.03). The rs4148855-GTC deletion carriers an exhibited significantly worse overall postural stability (GTC deletion carriers: 0.53 ± 0.33, non-carriers: 0.46 ± 0.20, p = 0.03). In the controls, rs2288646-A allele carriers were significant worse in the medial-to-lateral postural stability (A-allele carriers: 0.31 ± 0.17, non-A carriers: 0.21 ± 0.10, p = 0.01).Conclusion: The present study demonstrated that ASIC3 genetic variants were associated with certain aspects of balance functions and dizziness questionnaires in people of mTBI and non-mTBI. It provides a possible evidence that ASIC3 could be a new target for the management of the balancing disorders. However, further investigations are warranted to elucidate the underlying mechanisms and clinical significance.

Introduction: Autonomic nervous system (ANS) dysfunction contributes to several non-motor symptoms of Parkinson's disease (PD). In addition, ANS plays a role in the genesis and maintenance of atrial fibrillation (AF). This study investigated the temporal association between PD and AF.Methods: Data were obtained from the National Health Insurance Research Database of Taiwan. In total, 15,375 patients with newly diagnosed PD were matched with four controls each based on the propensity score. This study was bidirectional. A case-control study for the odds ratio (OR) of AF before PD and within 2 years of PD diagnosis was evaluated through conditional logistic regression. Furthermore, a cohort study on the subdistribution hazard ratio (SHR) for new-onset AF 2 years after PD diagnosis was evaluated using competing risk analysis.Results: In the case-control study, PD was found to be significantly comorbid with AF (adjusted OR: 1.15, 95% confidence interval [CI]: 1.04–1.28). Subgroup analysis demonstrated that this association consistently presented in the absence of confounding factors of AF. In the cohort study, people with PD were found to have a lower risk of AF (adjusted SHR: 0.92, 95% CI: 0.86–0.98). However, a consistent association was not observed between the confounding factors of AF and PD during the subgroup analysis.Conclusions: This study demonstrated that the premotor and early stages of PD were comorbid with AF, whereas the risk of AF was lower in the later stages. Thus, AF might be a premotor predictive biomarker and comorbidity of early PD.

BackgroundSeveral clinical trials reported that clopidogrel was superior to aspirin in secondary stroke prevention by reducing the risk of major adverse cardiovascular events (MACE). We aimed to compare the efficacy of clopidogrel with aspirin in reducing one-year risk of MACE based on real-world evidence from Taiwan Health Insurance Database.MethodsWe identified ischemic stroke patients between 2000 and 2012 who took aspirin or clopidogrel within 7 days of stroke onset for 1-year follow-up. The primary outcome was one-year MACE including recurrent stroke, acute myocardial infarction, and death. Propensity score matching and conditional Cox proportional hazards regression were conducted to control the confounding factors.ResultsFrom 9,089 ischemic stroke patients, we found 654 patients on aspirin and 465 patients on clopidogrel who met the selective inclusion criteria. After propensity score matching, 379 patients were selected from each group. The clopidogrel group had a 1.78-fold MACE risk compared with the aspirin group at one-year follow-up (95% CI = 1.41-2.26, pConclusionsAmong first-ever ischemic stroke patients, secondary stroke prevention using clopidogrel was associated with higher rates of MACE than aspirin. Aspirin might have better efficacy in secondary stroke prevention and was associated with lower risk of MACE. The real-world evidence raises the need to re-assess the current therapeutic options in secondary stroke prevention applying aspirin vs. clopidogrel.

Objectives: Association between net vertebral artery flow volume (NVAFV) and stroke types remains unclear. We hypothesize NVAFV is low in patients with posterior circulation infarction (PCI) and an ideal cut-off value for discriminating PCI from anterior circulation infarction (ACI) and controls may be present.Materials and Methods: As study candidates, we retrospectively enrolled hospitalized patients with first-time non-AF stroke within 2-years period. Consecutive non-AF, non-stroke subjects were enrolled as the control group. We compared NVAFV values among the PCI, ACI, and control groups.Results: Overall, 866 candidates—213, 418, and 235 candidates in the PCI, ACI, and control groups, respectively—were enrolled. NVAFV (mean ± SD) values were 134.8 ± 52.7, 152.3 ± 59.2, and 172.0 ± 54.7 mL/min in the PCI, ACI, and control groups, respectively. Statistics revealed significant difference (p < 0.001) among three groups. To use NVAFV as a diagnostic parameter, the AUC of any two groups should be between 0.58 and 0.69. Most (93.6%) of the controls had NVAFV above 100 mL/min. The odds ratio of any non-AF stroke is 3.48 if the NVAFV is below 100 mL/min.Conclusions: NVAFV is lowest in non-AF PCI group. Low NVAFV is associated with both non-AF ACI and PCI. No ideal cut-off value is available to discriminate PCI from other two conditions. We agree that an NVAFV of 100 mL/min is the lower limit of a normal value. Any value below 100 mL/min indicates high stroke risk and implies diffuse cerebral atherosclerosis and impaired cerebral perfusion.

In the hospital, a sleep postures monitoring system is usually adopted to transform sensing signals into sleep behaviors. However, a home-care sleep posture monitoring system needs to be user friendly. In this paper, we present iSleePost—a user-friendly home-care intelligent sleep posture monitoring system. We address the labor-intensive labeling issue of traditional machine learning approaches in the training phase. Our proposed mobile health (mHealth) system leverages the communications and computation capabilities of mobile phones for provisioning a continuous sleep posture monitoring service. Our experiments show that iSleePost can achieve up to 85 percent accuracy in recognizing sleep postures. More importantly, iSleePost demonstrates that an easy-to-wear wrist sensor can accurately quantify sleep postures after our designed training phase. It is our hope that the design concept of iSleePost can shed some lights on quantifying human sleep postures in the future.

In older individuals, hand fine motor skill disability is associated with cognitive levels. Similarly, patients with moderate-to-advanced Parkinson’s disease (PD) often have cognitive dysfunction. Here, we investigated the association between hand fine motor skill and cognitive dysfunction in patients with moderate-to-advanced PD. Moderate and advanced PD patients with and without dementia were identified from the Taiwan Data Bank of Persons with Disability. Hand fine motor capacities, namely pen holding, buttoning, and knotting, were assessed with the World Health Organization Disability Assessment Schedule 2.0. Statistical analyses were performed on Statistical Analysis System (SAS) and a p value of

Cognitive decline is an important issue of global public health. Cognitive aging might begin at middle adulthood, the period particularly vulnerable to stress in lifespan. Essence of chicken (EOC) has consistently demonstrated its beneficial effects on various cognitive domains as nutritional supplementation. This study primarily aimed to examine the cognitive enhancement effects of ProBeptigen® (previously named CMI-168), hydrolyzed peptides extracted from EOC, in healthy middle-aged people under mild stress. Ninety healthy subjects were randomly assigned into the ProBeptigen® or placebo group for eight weeks. Neurocognitive assessment, event-related potentials (ERPs), and blood tests were conducted before, during, and after the treatment. The ProBeptigen® group outperformed placebo group on Logical Memory subtests of Wechsler Memory Scale-third edition (WMS-III) and Spatial Working Memory task in the Cambridge Neuropsychological Test Automated Battery (CANTAB). The anti-inflammatory effects of ProBeptigen® in humans were also confirmed, with progressively declining high-sensitivity C-reactive protein (hs-CRP) levels. Regular dietary supplementation of ProBeptigen® is suggested to improve verbal short- and long-term memory as well as spatial working memory, and reduce inflammation in middle-aged healthy individuals with stress. The effects of ProBeptigen® on cognition warrant further investigation. (NCT03612752)

Background: Insulin resistance (IR), considered a hallmark of diabetes at the cellular level, is implicated in pre-diabetes, results in type 2 diabetes, and negatively affects mitochondrial function. Diabetes is increasingly associated with enhanced risk of developing Parkinson’s disease (PD); however, the underlying mechanism remains unclear. This study investigated the probable culpability of IR in the pathogenesis of PD. Methods: Using MitoPark mice in vivo models, diabetes was induced by a high-fat diet in the in vivo models, and IR was induced by protracted pulse-stimulation with 100 nM insulin treatment of neuronal cells, in vitro to determine the molecular mechanism(s) underlying altered cellular functions in PD, including mitochondrial dysfunction and α-synuclein (SNCA) aberrant expression. Findings: We observed increased SNCA expression in the dopaminergic (DA) neurons of both the wild-type and diabetic MitoPark mice, coupled with enhanced degeneration of DA neurons in the diabetic MitoPark mice. Ex vivo, in differentiated human DA neurons, IR was associated with increased SNCA and reactive oxygen species (ROS) levels, as well as mitochondrial depolarization. Moreover, we demonstrated concomitant hyperactivation of polo-like kinase-2 (PLK2), and upregulated p-SNCA (Ser129) and proteinase K-resistant SNCA proteins level in IR SH-SY5Y cells, however the inhibition of PLK2 reversed IR-related increases in phosphorylated and total SNCA. Similarly, the overexpression of peroxisome proliferator-activated receptor-γ coactivator 1-alpha (PGC)-1α suppressed ROS production, repressed PLK2 hyperactivity, and resulted in downregulation of total and Ser129-phosphorylated SNCA in the IR SH-SY5Y cells. Conclusions: These findings demonstrate that IR-associated diabetes promotes the development and progression of PD through PLK2-mediated mitochondrial dysfunction, upregulated ROS production, and enhanced SNCA signaling, suggesting the therapeutic targetability of PLK2 and/or SNCA as potential novel disease-modifying strategies in patients with PD.

Cerebrospinal fluid (CSF) is a fluidic part of the brain’s microenvironment that isolates the brain from the rest of the body. CSF dilutes metabolites from neuronal activities and removes them from the brain. Its production and resorption are regulated dynamically and are central to maintaining brain homeostasis. We discovered that the major CSF source, the choroid plexus (CP), harbors the brain’s strongest circadian clock. Here, we consider some implications of the CP circadian clock for metabolite clearance in the brain. If the circadian clock contributes to timed production of the CSF, its synchronization with sleep timing can maximize clearance efficiency and help prevent neurodegenerative diseases such as Alzheimer’s disease.

Rapid eye movement sleep behavior disorder (RBD) is a parasomnia, with abnormal dream-enacting behavior during the rapid eye movement (REM) sleep. RBD is either idiopathic or secondary to other neurologic disorders and medications. Dementia with Lewy bodies (DLB) is the third most common cause of dementia, and the typical clinical presentation is rapidly progressive cognitive impairment. RBD is one of the core features of DLB and may occur either in advance or simultaneously with the onset of DLB. The association between RBD with DLB is widely studied. Evidences suggest that both DLB and RBD are possibly caused by the shared underlying synucleinopathy. This review article discusses history, clinical manifestations, possible pathophysiologies, and treatment of DLB and RBD and provides the latest updates.

To develop an applicable prediction for obstructive sleep apnea (OSA) is still a challenge in clinical practice. We apply a modern machine learning method, the support vector machine to establish a predicting model for the severity of OSA. The support vector machine was applied to build up a prediction model based on three anthropometric features (neck circumference, waist circumference, and body mass index) and age on the first database. The established model was then valided independently on the second database. The anthropometric features and age were combined to generate powerful predictors for OSA. Following the common practice, we predict if a subject has the apnea-hypopnea index greater then 15 or not as well as 30 or not. Dividing by genders and age, for the AHI threhosld 15 (respectively 30), the cross validation and testing accuracy for the prediction were 85.3% and 76.7% (respectively 83.7% and 75.5%) in young female, while the negative likelihood ratio for the AHI threhosld 15 (respectively 30) for the cross validation and testing were 0.2 and 0.32 (respectively 0.06 and 0.1) in young female. The more accurate results with lower negative likelihood ratio in the younger patients, especially the female subgroup, reflect the potential of the proposed model for the screening purpose and the importance of approaching by different genders and the effects of aging.

The kidney harbors one of the strongest circadian clocks in the body. Kidney failure has long been known to cause circadian sleep disturbances. Using an adenine-induced model of chronic kidney disease (CKD) in mice, we probe the possibility that such sleep disturbances originate from aberrant circadian rhythms in kidney. Under the CKD condition, mice developed unstable behavioral circadian rhythms. When observed in isolation in vitro, the pacing of the master clock, the suprachiasmatic nucleus (SCN), remained uncompromised, while the kidney clock became a less robust circadian oscillator with a longer period. We find this analogous to the silencing of a strong slave clock in the brain, the choroid plexus, which alters the pacing of the SCN. We propose that the kidney also contributes to overall circadian timekeeping at the whole-body level, through bottom-up feedback in the hierarchical structure of the mammalian circadian clocks.