NREM delta power and AD-relevant tauopathy are associated with shared cortical gene networks

AbstractReduced NREM sleep in humans is associated with AD neuropathology. Recent work has demonstrated a reduction in NREM sleep in preclinical AD, pointing to its potential utility as an early marker of dementia. We test the hypothesis that reduced NREM delta power and increased tauopathy are associated with shared underlying cortical molecular networks in preclinical AD. We integrate multi-omics data from two extensive public resources, a human Alzheimer’s disease cohort from the Mount Sinai Brain Bank (N = 125) reflecting AD progression and a (C57BL/6J × 129S1/SvImJ) F2 mouse population in which NREM delta power was measured (N = 98). Two cortical gene networks, including a CLOCK-dependent circadian network, are associated with NREM delta power and AD tauopathy progression. These networks were validated in independent mouse and human cohorts. Identifying gene networks related to preclinical AD elucidate possible mechanisms associated with the early disease phase and potential targets to alter the disease course.

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Comparison between instrumental variable and mediation-based approaches for reconstructing causal gene networks in yeast

Molecular Omics ◽

10.1039/d0mo00140f ◽

2021 ◽

Author(s):

Adriaan-Alexander Ludl ◽

Tom Michoel

Keyword(s):

Instrumental Variable ◽

Gene Networks ◽

Omics Data ◽

Causal Gene ◽

Causal Networks ◽

Transcriptomics Data ◽

A Cell ◽

Flow Of Information

Causal gene networks model the flow of information within a cell. Reconstructing causal networks from omics data is challenging because correlation does not imply causation. When genomics and transcriptomics data...

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The Road towards Polyclonal Anti-SARS-CoV-2 Immunoglobulins (Hyperimmune Serum) for Passive Immunization in COVID-19

Life ◽

10.3390/life11020144 ◽

2021 ◽

Vol 11 (2) ◽

pp. 144

Author(s):

Daniele Focosi ◽

Marco Tuccori ◽

Massimo Franchini

Keyword(s):

Neutralizing Antibodies ◽

Passive Immunization ◽

Spike Protein ◽

Controlled Trials ◽

Disease Course ◽

Early Disease ◽

Hyperimmune Serum ◽

The Road ◽

Randomized Controlled ◽

Pros And Cons

Effective treatments specific for COVID-19 are still lacking. In the setting of passive immunotherapies based on neutralizing antibodies (nAbs), randomized controlled trials of COVID-19 convalescent plasma (CCP) anti-SARS-CoV-2 Spike protein monoclonal antibodies (mAb), which have been granted emergency use authorization, have suggested benefit in early disease course (less than 72 hours from symptoms and seronegative). Meanwhile, polyclonal immunoglobulins (i.e., hyperimmune serum), derived either from CCP donations or from animals immunized with SARS-CoV-2 antigens, are likely to become the next nAb-derived candidate. We here discuss the pros and cons of hyperimmune serum versus CCP and mAb, and summarize the ongoing clinical trials of COVID-19 hyperimmune sera.

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A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research

International Journal of Molecular Sciences ◽

10.3390/ijms22062822 ◽

2021 ◽

Vol 22 (6) ◽

pp. 2822

Author(s):

Efstathios Iason Vlachavas ◽

Jonas Bohn ◽

Frank Ückert ◽

Sylvia Nürnberg

Keyword(s):

Cancer Research ◽

Clinical Information ◽

Disease Diagnosis ◽

Molecular Data ◽

Molecular Networks ◽

Biological Knowledge ◽

Omics Data ◽

Translational Cancer Research ◽

Using Data ◽

Biological Entities

Recent advances in sequencing and biotechnological methodologies have led to the generation of large volumes of molecular data of different omics layers, such as genomics, transcriptomics, proteomics and metabolomics. Integration of these data with clinical information provides new opportunities to discover how perturbations in biological processes lead to disease. Using data-driven approaches for the integration and interpretation of multi-omics data could stably identify links between structural and functional information and propose causal molecular networks with potential impact on cancer pathophysiology. This knowledge can then be used to improve disease diagnosis, prognosis, prevention, and therapy. This review will summarize and categorize the most current computational methodologies and tools for integration of distinct molecular layers in the context of translational cancer research and personalized therapy. Additionally, the bioinformatics tools Multi-Omics Factor Analysis (MOFA) and netDX will be tested using omics data from public cancer resources, to assess their overall robustness, provide reproducible workflows for gaining biological knowledge from multi-omics data, and to comprehensively understand the significantly perturbed biological entities in distinct cancer types. We show that the performed supervised and unsupervised analyses result in meaningful and novel findings.

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Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

Scientific Reports ◽

10.1038/s41598-021-83585-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Soo Hyun Cho ◽

Sookyoung Woo ◽

Changsoo Kim ◽

Hee Jin Kim ◽

Hyemin Jang ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Disease Progression ◽

Disease Assessment ◽

Time Interval ◽

Disease Course ◽

Preclinical Alzheimer’S Disease ◽

Apoe Ε4 ◽

Preclinical Ad ◽

Cognitive Subscale

AbstractTo characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.

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0327 NREM Sleep EEG in Typically Developing and Drug-Naïve ADHD Adolescents: Data from a Longitudinal Study

SLEEP ◽

10.1093/sleep/zsaa056.324 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A124-A124

Author(s):

T Basishvili ◽

M Eliozishvili ◽

T Oniani ◽

T Tchintcharauli ◽

I Sakhelashvili ◽

...

Keyword(s):

Longitudinal Study ◽

Nrem Sleep ◽

Sleep Eeg ◽

Brain Maturation ◽

Adhd Group ◽

Typically Developing ◽

Eeg Activity ◽

Theta Power ◽

Delta Power ◽

Drug Naïve

Abstract Introduction Structural MRI studies suggest delayed brain maturation in children with attention deficit hyperactivity disorder (ADHD). The steep adolescent decline in sleep slow wave EEG activity provides an opportunity to investigate brain electrophysiological evidence for this maturational delay. Most ADHD sleep EEG studies have been cross-sectional. Here we present data from an ongoing longitudinal study of the maturational trajectories of sleep EEG in drug-naïve ADHD and typically developing adolescents. Methods Nine children diagnosed with ADHD (combined subtype, DSM-V criteria, mean age 12.39±0.61 years), and nine typically developing controls (12.07±0.35 years) were recruited. Subjects underwent an adaptation night and all night polysomnography twice yearly at the Laboratory. Sleep EEG was analyzed using fast Fourier transform. NREM delta and theta EEG activity were compared across first two recordings. Results Group effects (ADHD vs. control) on all night delta and theta energy, and delta power were not significant (p>0.2 for all). All night theta power was lower (p=0.035) for the ADHD group, and all night NREM sleep duration trended (p=0.060) toward being lower for the ADHD group. Controlling for sleep duration differences by examining only the first 5 h of NREM sleep showed no group effect on delta power (p=0.77) and a trend toward lower theta power (p=0.057) for the ADHD group. Conclusion At age 12 to 13 years, NREM sleep delta EEG did not differ between ADHD and control subjects. Theta power, which declines at a younger age than delta, was lower in control subjects. The two recordings thus far differ only by 6 months. The entire study will provide 5 semiannual recordings and allow us to determine if the higher theta power in the ADHD group will hold and if delta power will be greater as well, and thus provide electrophysiological support for the delayed brain maturation suggested by MRI findings. Support Shota Rustaveli National Science Foundation Grant FR17_94; Subjects Recruitment Support - Mental Health Service in Tbilisi “Kamara”.

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Novel cancer subtyping method based on patient-specific gene regulatory network

10.1101/2021.03.24.436731 ◽

2021 ◽

Author(s):

Mai Adachi Nakazawa ◽

Yoshinori Tamada ◽

Yoshihisa Tanaka ◽

Marie Ikeguchi ◽

Kako Higashihara ◽

...

Keyword(s):

Gene Networks ◽

Regulatory Networks ◽

The Cancer Genome Atlas ◽

Patient Specific ◽

Specific Gene ◽

Omics Data ◽

Cancer Subtypes ◽

Molecular Systems ◽

Molecular Features ◽

Cancer Genome Atlas

The identification of cancer subtypes is important for the understanding of tumor heterogeneity. In recent years, numerous computational methods have been proposed for this problem based on the multi-omics data of patients. It is widely accepted that different cancer subtypes are induced by different molecular regulatory networks. However, only a few incorporate the differences between their molecular systems into the classification processes. In this study, we present a novel method to classify cancer subtypes based on patient-specific molecular systems. Our method quantifies patient-specific gene networks, which are estimated from their transcriptome data. By clustering their quantified networks, our method allows for cancer subtyping, taking into consideration the differences in the molecular systems of patients. Comprehensive analyses of The Cancer Genome Atlas (TCGA) datasets applied to our method confirmed that they were able to identify more clinically meaningful cancer subtypes than the existing subtypes and found that the identified subtypes comprised different molecular features. Our findings show that the proposed method, based on a simple classification using the patient-specific molecular systems, can identify cancer subtypes even with single omics data, which cannot otherwise be captured by existing methods using multi-omics data.

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Differential modulation of NREM sleep regulation and EEG topography by chronic sleep restriction in mice

Scientific Reports ◽

10.1038/s41598-019-54790-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Bowon Kim ◽

Eunjin Hwang ◽

Robert E. Strecker ◽

Jee Hyun Choi ◽

Youngsoo Kim

Keyword(s):

Nrem Sleep ◽

Brain Regions ◽

Sleep Eeg ◽

Sleep Restriction ◽

Electrode Arrays ◽

Sleep Regulation ◽

Amplitude Analysis ◽

Delta Power ◽

Eeg Topography ◽

Chronic Sleep

AbstractCompensatory elevation in NREM sleep EEG delta power has been typically observed following prolonged wakefulness and widely used as a sleep homeostasis indicator. However, recent evidence in human and rodent chronic sleep restriction (CSR) studies suggests that NREM delta power is not progressively increased despite of accumulated sleep loss over days. In addition, there has been little progress in understanding how sleep EEG in different brain regions responds to CSR. Using novel high-density EEG electrode arrays in the mouse model of CSR where mice underwent 18-h sleep deprivation per day for 5 consecutive days, we performed an extensive analysis of topographical NREM sleep EEG responses to the CSR condition, including period-amplitude analysis of individual slow waves. As previously reported in our analysis of REM sleep responses, we found different patterns of changes: (i) progressive decrease in NREM sleep duration and consolidation, (ii) persistent enhancement in NREM delta power especially in the frontal and parietal regions, and (iii) progressive increases in individual slow wave slope and frontal fast oscillation power. These results suggest that multiple sleep-wake regulatory systems exist in a brain region-specific manner, which can be modulated independently, especially in the CSR condition.

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Arrdc2 and Arrdc3 elicit divergent changes in gene expression in skeletal muscle following anabolic and catabolic stimuli

Physiological Genomics ◽

10.1152/physiolgenomics.00007.2019 ◽

2019 ◽

Vol 51 (6) ◽

pp. 208-217 ◽

Cited By ~ 2

Author(s):

Bradley S. Gordon ◽

Michael L. Rossetti ◽

Alexey M. Eroshkin

Keyword(s):

Skeletal Muscle ◽

Muscle Mass ◽

Tibialis Anterior ◽

Gene Networks ◽

Tibialis Anterior Muscle ◽

The Body ◽

Molecular Networks ◽

Expression Of Genes ◽

Consistent Change ◽

Mechanical Overload

Skeletal muscle is a highly plastic organ regulating various processes in the body. As such, loss of skeletal muscle underlies the increased morbidity and mortality risk that is associated with numerous conditions. However, no therapies are available to combat the loss of muscle mass during atrophic conditions, which is due in part to the incomplete understanding of the molecular networks altered by anabolic and catabolic stimuli. Thus, the current objective was to identify novel gene networks modulated by such stimuli. For this, total RNA from the tibialis anterior muscle of mice that were fasted overnight or fasted overnight and refed the next morning was subjected to microarray analysis. The refeeding stimulus altered the expression of genes associated with signal transduction. Specifically, expression of alpha arrestin domain containing 2 (Arrdc2) and alpha arrestin domain containing 3 (Arrdc3) was significantly lowered 70–85% by refeeding. Subsequent analysis showed that expression of these genes was also lowered 50–75% by mechanical overload, with the combination of nutrients and mechanical overload acting synergistically to lower Arrdc2 and Arrdc3 expression. On the converse, stimuli that suppress growth such as testosterone depletion or acute aerobic exercise increased Arrdc2 and Arrdc3 expression in skeletal muscle. While Arrdc2 and Arrdc3 exhibited divergent changes in expression following anabolic or catabolic stimuli, no other member of the Arrdc family of genes exhibited the consistent change in expression across the analyzed conditions. Thus, Arrdc2 and Arrdc3 are a novel set of genes that may be implicated in the regulation of skeletal muscle mass.

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