Correction: High-resolution DNA size enrichment using a magnetic nano-platform and application in non-invasive prenatal testing.

Correction for 'High-resolution DNA size enrichment using a magnetic nano-platform and application in non-invasive prenatal testing' by Bo Zhang et al., Analyst, 2020, 145, 5733-5739, DOI: 10.1039/D0AN00813C.

Efficient detection and post-surgical monitoring of colon cancer with a multi-marker DNA methylation liquid biopsy.

Multiplex assays, involving the simultaneous use of multiple circulating tumor DNA (ctDNA) markers, can improve the performance of liquid biopsies so that they are highly predictive of cancer recurrence. We have developed a single-tube methylation-specific quantitative PCR assay (mqMSP) that uses 10 different methylation markers and is capable of quantitative analysis of plasma samples with as little as 0.05% tumor DNA. In a cohort of 179 plasma samples from colorectal cancer (CRC) patients, adenoma patients, and healthy controls, the sensitivity and specificity of the mqMSP assay were 84.9% and 83.3%, respectively. In a head-to-head comparative study, the mqMSP assay also performed better for detecting early-stage (stage I and II) and premalignant polyps than a published SEPT9 assay. In an independent longitudinal cohort of 182 plasma samples (preoperative, postoperative, and follow-up) from 82 CRC patients, the mqMSP assay detected ctDNA in 73 (89.0%) of the preoperative plasma samples. Postoperative detection of ctDNA (within 2 wk of surgery) identified 11 of the 20 recurrence patients and was associated with poorer recurrence-free survival (hazard ratio, 4.20; P = 0.0005). With subsequent longitudinal monitoring, 14 patients (70%) had detectable ctDNA before recurrence, with a median lead time of 8.0 mo earlier than seen with radiologic imaging. The mqMSP assay is cost-effective and easily implementable for routine clinical monitoring of CRC recurrence, which can lead to better patient management after surgery.

ANERGY TO SYNERGY-THE ENERGY FUELING THE RXCOVEA FRAMEWORK.

We write to introduce our novel group formed to confront some of the issues raised by the COVID-19 pandemic. Information about the group, which we named "cure COVid for Ever and for All" (RxCOVEA), its dynamic membership (changing regularly), and some of its activities-described in more technical detail for expert perusal and commentary-are available upon request.

High-resolution DNA size enrichment using a magnetic nano-platform and application in non-invasive prenatal testing.

Precise DNA sizing can boost sequencing efficiency, reduce cost, improve data quality, and even allow sequencing of low-input samples, while current pervasive DNA sizing approaches are incapable of differentiating DNA fragments under 200 bp with high resolution (<20 bp). In non-invasive prenatal testing (NIPT), the size distribution of cell-free fetal DNA in maternal plasma (main peak at 143 bp) is significantly different from that of maternal cell-free DNA (main peak at 166 bp). The current pervasive workflow of NIPT and DNA sizing is unable to take advantage of this 20 bp difference, resulting in sample rejection, test inaccuracy, and restricted clinical utility. Here we report a simple, automatable, high-resolution DNA size enrichment workflow, named MiniEnrich, on a magnetic nano-platform to exploit this 20 bp size difference and to enrich fetal DNA fragments from maternal blood. Two types of magnetic nanoparticles were developed, with one able to filter high-molecular-weight DNA with high resolution and the other able to recover the remaining DNA fragments under the size threshold of interest with >95% yield. Using this method, the average fetal fraction was increased from 13% to 20% after the enrichment, as measured by plasma DNA sequencing. This approach provides a new tool for high-resolution DNA size enrichment under 200 bp, which may improve NIPT accuracy by rescuing rejected non-reportable clinical samples, and enable NIPT earlier in pregnancy. It also has the potential to improve non-invasive screening for fetal monogenic disorders, differentiate tumor-related DNA in liquid biopsy and find more applications in autoimmune disease diagnosis.

Noninvasive diagnosis of urothelial cancer in urine using DNA hypermethylation signatures-Gender matters.

Urothelial cancer (UCa) is the most predominant cancer of the urinary tract and noninvasive diagnosis using hypermethylation signatures in urinary cells is promising. Here, we assess gender differences in a newly identified set of methylation biomarkers. UCa-associated hypermethylated sites were identified in urine of a male screening cohort (n = 24) applying Infinium-450K-methylation arrays and verified in two separate mixed-gender study groups (n = 617 in total) using mass spectrometry as an independent technique. Additionally, tissue samples (n = 56) of mixed-gender UCa and urological controls (UCt) were analyzed. The hypermethylation signature of UCa in urine was specific and sensitive across all stages and grades of UCa and independent on hematuria. Individual CpG sensitivities reached up to 81.3% at 95% specificity. Albeit similar methylation differences in tissue of both genders, differences were less pronounced in urine from women, most likely due to the frequent presence of squamous epithelial cells and leukocytes. Increased repression of methylation levels was observed at leukocyte counts ≥500/µl urine which was apparent in 30% of female and 7% of male UCa cases, further confirming the significance of the relative amounts of cancerous and noncancerous cells in urine. Our study shows that gender difference is a most relevant issue when evaluating the performance of urinary biomarkers in cancer diagnostics. In case of UCa, the clinical benefits of methylation signatures to male patients may outweigh those in females due to the general composition of women's urine. Accordingly, these markers offer a diagnostic option specifically in males to decrease the number of invasive cystoscopies.

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study we demonstrate for the first time that smoking status can be predicted using blood biochemistry and cell count results andthe recent advances in artificial intelligence (AI). By employing age-prediction models developed using supervised deep learning techniques, we found that smokers exhibited higher aging rates than nonsmokers, regardless of their cholesterol ratios and fasting glucose levels. We further used those models to quantify the acceleration of biological aging due to tobacco use. Female smokers were predicted to be twice as old as their chronological age compared to nonsmokers, whereas male smokers were predicted to be one and a half times as old as their chronological age compared to nonsmokers. Our findings suggest that deep learning analysis of routine blood tests could complement or even replace the current error-prone method of self-reporting of smoking status and could be expanded to assess the effect of other lifestyle and environmental factors on aging.

miR-34a directly targets tRNAiMet precursors and affects cellular proliferation, cell cycle, and apoptosis.

It remains unknown whether microRNA (miRNA/miR) can target transfer RNA (tRNA) molecules. Here we provide evidence that miR-34a physically interacts with and functionally targets tRNAiMet precursors in both in vitro pulldown and Argonaute 2 (AGO2) cleavage assays. We find that miR-34a suppresses breast carcinogenesis, at least in part by lowering the levels of tRNAiMet through AGO2-mediated repression, consequently inhibiting the proliferation of breast cancer cells and inducing cell cycle arrest and apoptosis. Moreover, miR-34a expression is negatively correlated with tRNAiMet levels in cancer cell lines. Furthermore, we find that tRNAiMet knockdown also reduces cell proliferation while inducing cell cycle arrest and apoptosis. Conversely, ectopic expression of tRNAiMet promotes cell proliferation, inhibits apoptosis, and accelerates the S/G2 transition. Moreover, the enforced expression of modified tRNAiMet completely restores the phenotypic changes induced by miR-34a. Our results demonstrate that miR-34a directly targets tRNAiMet precursors via AGO2-mediated cleavage, and that tRNAiMet functions as an oncogene, potentially representing a target molecule for therapeutic intervention.

Deuterium-reinforced linoleic acid lowers lipid peroxidation and mitigates cognitive impairment in the Q140 knock in mouse model of Huntington's disease.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease which has no effective treatment and is characterized by psychiatric disorders, motor alterations, and dementia, with the cognitive deficits representing a devastating aspect of the disorder. Oxidative stress and elevated levels of lipid peroxidation (LPO) products are found in mouse models and patients with HD, suggesting that strategies to reduce LPO may be beneficial in HD. In contrast with traditional antioxidants, substituting hydrogen with deuterium at bis-allylic sites in polyunsaturated fatty acids (D-PUFA) decreases the rate-limiting initiation step of PUFA autoxidation, a strategy that has shown benefits in other neurodegenerative diseases. Here, we investigated the effect of D-PUFA treatment in a knock-in mouse model of HD (Q140) which presents motor deficits and neuropathology from a few months of age, and progressive cognitive decline. Q140 knock-in mice were fed a diet containing either D- or H-PUFAs for 5 months starting at 1 month of age. D-PUFA treatment significantly decreased F2 -isoprostanes in the striatum by approximately 80% as compared to H-PUFA treatment and improved performance in novel object recognition tests, without significantly changing motor deficits or huntingtin aggregation. Therefore, D-PUFA administration represents a promising new strategy to broadly reduce rates of LPO, and may be useful in improving a subset of the core deficits in HD.

Vive la radiorésistance!: converging research in radiobiology and biogerontology to enhance human radioresistance for deep space exploration and colonization.

While many efforts have been made to pave the way toward human space colonization, little consideration has been given to the methods of protecting spacefarers against harsh cosmic and local radioactive environments and the high costs associated with protection from the deleterious physiological effects of exposure to high-Linear energy transfer (high-LET) radiation. Herein, we lay the foundations of a roadmap toward enhancing human radioresistance for the purposes of deep space colonization and exploration. We outline future research directions toward the goal of enhancing human radioresistance, including upregulation of endogenous repair and radioprotective mechanisms, possible leeways into gene therapy in order to enhance radioresistance via the translation of exogenous and engineered DNA repair and radioprotective mechanisms, the substitution of organic molecules with fortified isoforms, and methods of slowing metabolic activity while preserving cognitive function. We conclude by presenting the known associations between radioresistance and longevity, and articulating the position that enhancing human radioresistance is likely to extend the healthspan of human spacefarers as well.

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data.

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

Pro-fibrotic pathway activation in trabecular meshwork and lamina cribrosa is the main driving force of glaucoma.

While primary open-angle glaucoma (POAG) is a leading cause of blindness worldwide, it still does not have a clear mechanism that can explain all clinical cases of the disease. Elevated IOP is associated with increased accumulation of extracellular matrix (ECM) proteins in the trabecular meshwork (TM) that prevents normal outflow of aqueous humor (AH) and has damaging effects on the fine mesh-like lamina cribrosa (LC) through which the optic nerve fibers pass. Applying a pathway analysis algorithm, we discovered that an elevated level of TGFß observed in glaucoma-affected tissues could lead to pro-fibrotic pathway activation in TM and in LC. In turn, activated pro-fibrotic pathways lead to ECM remodeling in TM and LC, making TM less efficient in AH drainage and making LC more susceptible to damage from elevated IOP via ECM transformation in LC. We propose pathway targets for potential therapeutic interventions to delay or avoid fibrosis initiation in TM and LC tissues.

Deep biomarkers of human aging: Application of deep neural networks to biomarker development.

One of the major impediments in human aging research is the absence of a comprehensive and actionable set of biomarkers that may be targeted and measured to track the effectiveness of therapeutic interventions. In this study, we designed a modular ensemble of 21 deep neural networks (DNNs) of varying depth, structure and optimization to predict human chronological age using a basic blood test. To train the DNNs, we used over 60,000 samples from common blood biochemistry and cell count tests from routine health exams performed by a single laboratory and linked to chronological age and sex. The best performing DNN in the ensemble demonstrated 81.5 % epsilon-accuracy r = 0.90 with R(2) = 0.80 and MAE = 6.07 years in predicting chronological age within a 10 year frame, while the entire ensemble achieved 83.5% epsilon-accuracy r = 0.91 with R(2) = 0.82 and MAE = 5.55 years. The ensemble also identified the 5 most important markers for predicting human chronological age: albumin, glucose, alkaline phosphatase, urea and erythrocytes. To allow for public testing and evaluate real-life performance of the predictor, we developed an online system available at http://www.aging.ai. The ensemble approach may facilitate integration of multi-modal data linked to chronological age and sex that may lead to simple, minimally invasive, and affordable methods of tracking integrated biomarkers of aging in humans and performing cross-species feature importance analysis.

An interview with Charles Cantor: achievements and advice from 50 years of biotechnology expertise.

Interview with Professor Charles Cantor PhD by Claire Raison (Commissioning Editor) Professor Charles Cantor was awarded his PhD from the University of California, Berkeley (CA, USA), in 1966, and via professorships at Columbia University (New York, NY, USA), UC Berkeley and Boston University (Boston, MA, USA), went on to be Chief Scientific Officer of Sequenom (San Diego, CA, USA) and now retired, continues to act as consultant for more than 16 biotechnology companies. His research focused on inventing new techniques for solving biological problems, including faster DNA sequencing, better DNA amplification and advanced methods: for nucleic acid separation.

Pathway activation profiling reveals new insights into age-related macular degeneration and provides avenues for therapeutic interventions.

Age-related macular degeneration (AMD) is a major cause of blindness in older people and is caused by loss of the central region of the retinal pigment epithelium (RPE). Conventional methods of gene expression analysis have yielded important insights into AMD pathogenesis, but the precise molecular pathway alterations are still poorly understood. Therefore we developed a new software program, "AMD Medicine", and discovered differential pathway activation profiles in samples of human RPE/choroid from AMD patients and controls. We identified 29 pathways in RPE-choroid AMD phenotypes: 27 pathways were activated in AMD compared to controls, and 2 pathways were activated in controls compared to AMD. In AMD, we identified a graded activation of pathways related to wound response, complement cascade, and cell survival. Also, there was downregulation of two pathways responsible for apoptosis. Furthermore, significant activation of pro-mitotic pathways is consistent with dedifferentiation and cell proliferation events, which occur early in the pathogenesis of AMD. Significantly, we discovered new global pathway activation signatures of AMD involved in the cell-based inflammatory response: IL-2, STAT3, and ERK. The ultimate aim of our research is to achieve a better understanding of signaling pathways involved in AMD pathology, which will eventually lead to better treatments.

Surface EMG activity during REM sleep in Parkinson's disease correlates with disease severity.

OBJECTIVES: Over 40% of individuals with Parkinson's disease (PD) have rapid eye movement sleep behavior disorder (RBD). This is associated with excessive sustained (tonic) or intermittent (phasic) muscle activity instead of the muscle atonia normally seen during REM sleep. We examined characteristics of manually-quantitated surface EMG activity in PD to ascertain whether the extent of muscle activity during REM sleep is associated with specific clinical features and measures of disease severity. METHODS: In a convenience sample of outpatients with idiopathic PD, REM sleep behavior disorder was diagnosed based on clinical history and polysomnogram, and severity was measured using the RBD sleep questionnaire. Surface EMG activity in the mentalis, extensor muscle group of the forearms, and anterior tibialis was manually quantitated. Percentage of REM time with excessive tonic or phasic muscle activity was calculated and compared across PD and RBD characteristics. RESULTS: Among 65 patients, 31 had confirmed RBD. In univariate analyses, higher amounts of surface EMG activity were associated with longer PD disease duration (srho = 0.34; p = 0.006) and greater disease severity (p < 0.001). In a multivariate regression model, surface EMG activity was significantly associated with RBD severity (p < 0.001) after adjustment for age, PD disease duration, PD severity and co-morbid sleep abnormalities. CONCLUSION: Surface EMG activity during REM sleep was associated with severity of both PD and RBD. This measure may be useful as a PD biomarker and, if confirmed, may aid in determining which PD patients warrant treatment for their dream enactment to reduce risk of injury.

Alexia due to ischemic stroke of the visual word form area.

The visual word form area (VWFA) is a region in the posterior left occipitotemporal cortex adjacent to the fusiform gyrus hypothesized to mediate word recognition. Evidence supporting the role of this area in reading comes from neuroimaging studies of normal subjects, case-controlled lesion studies, and studies of patients with surgical resection of the VWFA for tumors or epilepsy. Based on these prior reports, a small discrete lesion to the VWFA would be expected to cause alexia in a literate person without prior brain process, but such a case has not previously been reported to our knowledge. Here, we report the case of a previously-healthy 63-year-old man with the acute onset of alexia without other significant impairments. Magnetic resonance imaging (MRI) of the brain revealed a small ischemic stroke localized to the inferior left occipitotemporal cortex, corresponding to the approximate location of the putative VWFA. Characteristic of pure alexia, testing in the weeks following the stroke revealed a letter-by-letter reading strategy and a word length effect on single word reading. Formal visual field testing was normal. There was no color anomia, or object or face recognition deficits, although a mild agraphia may have been present. This case of acute-onset alexia in a previously normal individual due to a small stroke restricted to the VWFA and sparing occipital cortex and white matter pathways supports the conclusion that the VWFA is crucial for reading.