Biology subjects

Natarajan, P.

Publications and source records attributed to Natarajan, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations

High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKBs original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.

bioinformatics↗

bioRxiv2025

B cell transcriptomics reveals lasting dysregulation and rapid decline of protective memory after hepatitis C cure

O_FIG O_LINKSMALLFIG WIDTH=187 HEIGHT=200 SRC="FIGDIR/small/664545v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@d12426org.highwire.dtl.DTLVardef@9c54daorg.highwire.dtl.DTLVardef@186d559org.highwire.dtl.DTLVardef@120f2f3_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG HighlightsO_LIB cells in CHC patients retained dysregulated transcriptional profiles despite successful DAA treatment C_LIO_LIB cell dysregulation is marked by global B cell hyperactivation and antigen-specific atypical MBC expansion C_LIO_LISustained upregulation of TNF- signaling via NF-{kappa}B (TNF-/NF-{kappa}B) is a central driver of persistent B cell dysregulation and chronic inflammation C_LIO_LIViral clearance leads to restoration of IFN responses and IFN-stimulated gene (ISG) signatures in B cells but not TNF-/NF-{kappa}B C_LIO_LIHCV IGHV1-69 bnAb-producing B cells are enriched within the CD86hi IgG MBC subset before treatment C_LIO_LICD86hi IgG MBC subset contracts rapidly post-cure in parallel with the rapid decline of cross-nAb responses and loss of protective immune memory against HCV reinfection C_LI Chronic hepatitis C (CHC) disrupts host humoral immune response by impairing the timely generation of neutralizing antibody (nAb) and durable immune memory. However, the underlying mechanisms and their reversibility after viral clearance remain poorly defined. Here, through integrated single-cell transcriptomics and antibody repertoire characterization, we show that B cells from CHC patients retain transcriptional dysregulation even after successful antiviral therapy. Sustained TNF- signaling emerged as a central driver of chronic B cell hyperactivation, persistent dysregulation and unresolved inflammation following cure. Furthermore, a CD86hi memory B cell subset, responsible for an IGHV1-69-encoded multi-donor class recall nAb response, declined rapidly following viral clearance, compromising immune memory against reinfection. Together, these findings reveal how CHC imprints lasting B cell dysregulation, impairs nAb memory, and sustains inflammation in the B cell compartment, after viral clearance. The insights underscore the need for strategies aimed at restoring B cell homeostasis to achieve durable immune protection.

immunology↗

bioRxiv2025

Mechanism of age-related accumulation of mitochondrial DNA mutations in human blood

One of the strongest signatures of aging is an accumulation of mutant mitochondrial DNA (mtDNA) heteroplasmy. Here we investigate the mechanism underlying this phenomenon by calling mtDNA sequence, abundance, and heteroplasmic variation in human blood using whole genome sequences from [~]750,000 individuals. Our analyses reveal a simple, two-step mechanism: first, individual cells randomly accumulate low levels of "cryptic" mtDNA mutations; then, when a cell clone proliferates, the cryptic mtDNA variants are carried as passenger mutations and become detectable in whole blood. Four lines of evidence support this model: (1) the mutational spectrum of age-accumulating mtDNA variants is consistent with a well-established model of mtDNA replication errors, (2) these mutations are found primarily at low levels of heteroplasmy and do not show evidence of positive selection, (3) high mtDNA mutation burden tends to co-occur in samples harboring somatic driver mutations for clonal hematopoiesis (CH), and (4) nuclear GWAS reveals that germline variants predisposing to CH (such as those near TERT, TCL1A, and SMC4) also increase mtDNA mutation burden. We propose that the high copy number and high mutation rate of mtDNA make it a particularly sensitive blood-based marker of CH. Importantly, our work helps to mechanistically unify three prominent signatures of aging: common germline variants in TERT, clonal hematopoiesis, and observed mtDNA mutation accrual.

genetics↗

bioRxiv2025

Catalyzing computational biology research at an academic institute through an interest network

Biology has been transformed by the rapid development of computing and the concurrent rise of data-rich approaches such as -omics or high-resolution imaging. However, there is a persistent computational skills gap in the biomedical research workforce. Inherent limitations of classroom teaching and institutional core support highlight the need for accessible ways for researchers to explore developments in computational biology. An analysis of the Scripps Research Genomics Core revealed an increasingly diverse set of experiments: the share of experiments other than bulk RNA- or DNA-seq increased from 34% to 60% within 10 years, requiring more tailored computational analyses. These challenges were tackled by forming a volunteer-led affinity group of over 300 academic biomedical researchers interested in computational biology referred to as the Computational Biology and Bioinformatics (CBB) affinity group. This adaptive group has provided continuing education and networking opportunities through seminars, workshops and coding sessions while evolving along with the needs of its members. A survey of CBBs impact confirmed the groups events increased the members exposure to computational biology educational and research events (79% respondents) and networking opportunities (61% respondents). Thus, volunteer-led affinity groups may be a viable complement to traditional institutional resources for enhancing the application of computing in biomedical research.

bioinformatics↗

bioRxiv2024

RNA gradients can guide condensates toward promoters: implications for enhancer-promoter contacts and condensate-promoter kissing

We study how protein condensates respond to a site of active RNA transcription (i.e., a gene promoter) due to electrostatic protein-RNA interactions. Our results indicate that condensates can show directed motion towards the promoter, driven by gradients in the RNA concentration. Analytical theory, consistent with simulations, predicts that the droplet velocity has a non-monotonic dependence on the distance to the promoter. We explore the consequences of this gradient-sensing mechanism for enhancer-promoter (E-P) communication using polymer simulations of the intervening chromatin chain. Directed motion of enhancer-bound condensates can, together with loop extrusion by cohesin, collaboratively increase the enhancer-promoter contact probability. Finally, we investigate under which conditions condensates can exhibit oscillations in their morphology and in the distance to the promoter. Oscillatory dynamics are caused by a delayed response of transcription to condensate-promoter contact and negative feedback from the accumulation of RNA at the promoter, which results in charge repulsion.

biophysics↗

bioRxiv2024

Active RNA synthesis patterns nuclear condensates

Biomolecular condensates are membraneless compartments that organize biochemical processes in cells. In contrast to well-understood mechanisms describing how condensates form and dissolve, the principles underlying condensate patterning - including their size, number and spacing in the cell - remain largely unknown. We hypothesized that RNA, a key regulator of condensate formation and dissolution, influences condensate patterning. Using nucleolar fibrillar centers (FCs) as a model condensate, we found that inhibiting ribosomal RNA synthesis significantly alters the patterning of FCs. Physical theory and experimental observations support a model whereby active RNA synthesis generates a non-equilibrium state that arrests condensate coarsening and thus contributes to condensate patterning. Altering FC condensate patterning by expression of the FC component TCOF1 impairs ribosomal RNA processing, linking condensate patterning to biological function. These results reveal how non-equilibrium states driven by active chemical processes regulate condensate patterning, which is important for cellular biochemistry and function.

biophysics↗

bioRxiv2024

Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program

The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.

genetics↗

bioRxiv2023

Biodistribution Analysis of Peptide-Coated Magnetic Iron Nanoparticles: A Simple and Quantitative Method

Biodistribution is the tracking of compounds or molecules of interest in the subject which is integral to understanding their anticipated efficacy and safety. Nanoparticles are highly desirable delivery systems which have the ability to deliver higher nucleic acid and drug payloads and they have enhanced tumor permeability due to their unique properties such as high surface area to volume ratio. Studying the biodistribution of nanoparticles is crucial to understand their effectiveness and safety in vivo, facilitate a more application driven approach for nanoparticle development which will lead to their successful translation into clinical use. In this study, we present a relatively simple method to determine the biodistribution of magnetic iron nanoparticles in mice. Branched Amphiphilic Peptide coated Magnetic Nanobeads BAPc-MNBs like their counterpart i.e., Branched Amphiphilic Peptide capsules (BAPCs) with a hollow water-filled core, are readily taken up by cells in vitro and have widespread application as a nanodelivery systems. We evaluated the BAPc-MNBs tissue distribution in wildtype mice injected intravenously (i.v.), intraperitoneally (i.p.) or orally gavaged to understand the biological interactions of the peptide nanoparticles and to further the development of branched amphiphilic peptides-based nanoparticles. BAPc-MNBs were distributed widely to various organs when injected i.v. and were eliminated from the system via the intestines in feces. The spleen was found to accumulate the highest amount of BAPc-MNBs in mice administered the NPs i.v. and i.p. while they were not absorbed into the system via oral gavage. This study not only presents a relatively simple quantification method to determine in vivo biodistribution of magnetic iron nanoparticles that can be widely applied but also demonstrates the potential of Branched Amphiphilic Peptides in the form of BAPCs or BAPc-MNBs as a delivery system.

biochemistry↗

bioRxiv2023

A model for cis-regulation of transcriptional condensates and gene expression by proximal lncRNAs

Long non-coding RNAs (lncRNAs) perform several important functions in cells including cis-regulation of transcription. Barring a few specific cases, the mechanisms underlying transcriptional regulation by lncRNAs remain poorly understood. Transcriptional proteins can form condensates via phase separation at protein-binding loci (BL) on the genome (e.g., enhancers and promoters). lncRNA-coding genes are present at loci in close genomic proximity of these BL and these RNAs can interact with transcriptional proteins via attractive heterotypic interactions mediated by their net charge. Motivated by these observations, we propose that lncRNAs can dynamically regulate transcription in cis via charge-based heterotypic interactions with transcriptional proteins in condensates. To study the consequences of this mechanism, we developed and studied a dynamical phase-field model. We find that proximal lncRNAs can promote condensate formation at the BL. Vicinally localized lncRNA can migrate to the BL to attract more protein because of favorable interaction free energies. However, increasing the distance beyond a threshold leads to a sharp decrease in protein recruitment to the BL. This finding could potentially explain why genomic distances between lncRNA-coding genes and protein-coding genes are conserved across metazoans. Finally, our model predicts that lncRNA transcription can fine-tune transcription from neighboring condensate-controlled genes, repressing transcription from highly expressed genes and enhancing transcription of genes expressed at a low level. This non-equilibrium effect can reconcile conflicting reports that lncRNAs can enhance or repress transcription from proximal genes. SIGNIFICANCELong non-coding RNAs (lncRNAs) form a significant part of the human genome but do not code for any proteins. They have many hypothesized functions in the cell, including the regulation of transcription. Transcriptional condensates are assemblies of transcriptional proteins that concentrate at specific genomic sites through phase separation and can regulate transcription. In this study, we propose that lncRNAs can regulate transcription by interacting with proteins in transcriptional condensates to modulate condensate formation. We find that this model can explain some puzzling observations such as conflicting reports of gene activation and repression by lncRNAs, and conservation of genomic distances between lncRNA-coding genes relative to protein-coding genes in metazoans. Experimentally testable predictions that can further explore our model are discussed.

biophysics↗

bioRxiv2022

Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

The rapid growth of genomic data has led to a new research paradigm where data are stored centrally in Trusted Research Environments (TREs) such as the All of Us Researcher Workbench (AoU RW) and the UK Biobank Research Analysis Platform (RAP). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conducted a Genome-Wide Association Study (GWAS) of standard lipid measures on the UKB RAP and AoU RW using two approaches: meta-analysis and pooled analysis. We curated lipid measurements for 37,754 All of Us participants with whole genome sequence (WGS) data and 190,982 UK Biobank participants with whole exome sequence (WES) data. For the meta-analysis, we performed a GWAS of each cohort in their respective platform and meta-analyzed the results. We separately performed a pooled GWAS on both datasets combined. We identified 490 and 464 significant variants in meta-analysis and pooled analysis, respectively. Comparison of full summary data from both meta-analysis and pooled analysis with an external study showed strong correlation of known loci with lipid levels (R2[~]83-97%). Importantly, 90 variants met the significance threshold only in the meta-analysis and 64 variants were significant only in pooled analysis. These method-specific differences may be explained by differences in cohort size, ancestry, and phenotype distributions in All of Us and UK Biobank. We noted approximately 20% of variants significant in only the pooled analysis or significant in only the meta-analysis were most prevalent in non-European, non-Asian ancestry individuals. Pooled analyses included more variants than meta-analyses. Pooled analysis required about half as many computational steps as meta-analysis. These findings have important implications for both platform implementations and researchers undertaking large-scale cross-cohort analyses, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

genetics↗

bioRxiv2022

Organization and regulation of nuclear condensates by gene activity

Condensation by phase separation has recently emerged as a mechanism underlying many nuclear compartments essential for cellular functions. Nuclear condensates enrich nucleic acids and proteins, localize to specific genomic regions, and often promote gene expression. How diverse properties characteristic of nuclear condensates are shaped by genome organization and activity is poorly understood. Here, we develop a physics-based model to interrogate this interplay between condensation, active transcription, and genome organization. We show that spatial clustering of active genes enables precise localization and de novo nucleation of condensates. We find that strong clustering and activity drives aspherical condensate morphologies. Condensates flow towards distant gene clusters and competition between multiple clusters lead to stretched morphologies and activity-dependent repositioning. Overall, our model predicts and recapitulates morphological and dynamical features of diverse nuclear condensates and offers a unified mechanistic framework to study the interplay between non-equilibrium processes, genome structure, and multicomponent condensates in cell biology.

biophysics↗

bioRxiv2020

Genome-Wide Screening Reveals CSDE1 as a Novel Regulator of the LDL Receptor

The low-density lipoprotein receptor (LDLR) controls cellular delivery of cholesterol and clears LDL from the bloodstream, protecting against atherosclerotic heart disease, the leading cause of death in the United States. We therefore sought to identify regulators of the LDLR beyond the targets of current clinical therapies and known causes of familial hypercholesterolemia. We show that Cold Shock Domain-Containing Protein E1 (CSDE1) enhances hepatic LDLR mRNA decay via its 3 untranslated region to regulate atherogenic lipoproteins in vivo. Using parallel phenotypic genome-wide CRISPR interference screens, we found 40 specific regulators of the LDLR left unidentified by observational human genetics. Among these, we show that CSDE1 regulates the LDLR at least as strongly as the mechanistically distinct pathways exploited by the best available clinical therapies: statins and PCSK9 inhibitors. Additionally, we show that hepatic gene silencing of Csde1 treats diet-induced dyslipidemia in mice better than that of Pcsk9. Our results reveal the therapeutic potential of manipulating a newly identified key factor in the post-transcriptional regulation of the LDLR mRNA for the prevention of cardiovascular disease. We anticipate that our approach of modelling a clinically relevant phenotype in a forward genetic screen, followed by mechanistic pharmacologic dissection and in vivo validation, will serve as a generalizable template for the identification of therapeutic targets in other human disease states. One Sentence SummaryA genome-wide CRISPR screen identifies CSDE1 as a key regulator of hepatic LDLR mRNA decay in vivo, making it a promising target for heart disease. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=137 HEIGHT=200 SRC="FIGDIR/small/235028v2_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@d53b79org.highwire.dtl.DTLVardef@133b48corg.highwire.dtl.DTLVardef@1926d97org.highwire.dtl.DTLVardef@58d863_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2020

A system for phenotype harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 TOPMed studies per phenotype. We discuss the challenges faced in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

genetics↗

bioRxiv2020

Androgen regulates SARS-CoV-2 receptor levels and is associated with severe COVID-19 symptoms in men

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has led to a global health crisis, and yet our understanding of the disease pathophysiology and potential treatment options remains limited. SARS-CoV-2 infection occurs through binding and internalization of the viral spike protein to angiotensin converting enzyme 2 (ACE2) on the host cell membrane. Lethal complications are caused by damage and failure of vital organs that express high levels of ACE2, including the lungs, the heart and the kidneys. Here, we established a high-throughput drug screening strategy to identify therapeutic candidates that reduce ACE2 levels in human embryonic stem cell (hESC) derived cardiac cells. Drug target analysis of validated hit compounds, including 5 alpha reductase inhibitors, revealed androgen signaling as a key modulator of ACE2 levels. Treatment with the 5 alpha reductase inhibitor dutasteride reduced ACE2 levels and internalization of recombinant spike receptor binding domain (Spike-RBD) in hESC-derived cardiac cells and human alveolar epithelial cells. Finally, clinical data on coronavirus disease 2019 (COVID-19) patients demonstrated that abnormal androgen states are significantly associated with severe disease complications and cardiac injury as measured by blood troponin T levels. These findings provide important insights on the mechanism of increased disease susceptibility in male COVID-19 patients and identify androgen receptor inhibition as a potential therapeutic strategy.

cell biology↗

bioRxiv2019

Genetic predisposition to myeloproliferative neoplasms implicates hematopoietic stem cell biology

Myeloproliferative neoplasms (MPNs) are blood cancers characterized by excessive production of mature myeloid cells that result from the acquisition of somatic driver mutations in hematopoietic stem cells (HSCs)1. While substantial progress has been made to define the causal somatic mutation profile for MPNs2, epidemiologic studies indicate a significant heritable component for the disease that is among the highest known for all cancers3. However, only a limited set of genetic risk loci have been identified, and the underlying biological mechanisms leading to MPN acquisition remain unexplained. Here, to define the inherited risk profile, we conducted the largest genome-wide association study of MPNs to date (978,913 individuals with 3,224 cases) and identified 14 genome-wide significant loci, as well as a polygenic signature that increases the odds for disease acquisition by nearly 3-fold between the top and median deciles. Interestingly, we find a shared genetic architecture between MPN risk and several hematopoietic traits spanning distinct lineages, as well as an association between increased MPN risk and longer leukocyte telomere length, collectively implicating HSC function and self-renewal. Strikingly, we find a significant enrichment for risk variants mapping to accessible chromatin in HSCs compared with other hematopoietic populations. Finally, gene mapping identifies modulators of HSC biology and targeted variant-to-function analyses suggest likely roles for CHEK2 and GFI1B in altering HSC function to confer disease risk. Overall, we demonstrate the power of human genetic studies to illuminate a previously unappreciated mechanism for MPN risk through modulation of HSC function.

genetics↗

bioRxiv2019

Heterozygous ATP-binding Cassette Transporter G5 Gene Deficiency and Risk of Coronary Artery Disease

BackgroundFamilial sitosterolemia is a rare, recessive Mendelian disorder characterized by hyperabsorption and decreased biliary excretion of dietary sterols. Affected individuals typically have complete genetic deficiency - homozygous loss-of-function (LoF) variants -- in the ATP-binding cassette transporter G5 (ABCG5) or G8 (ABCG8) genes, and have substantially elevated plasma sitosterol and low-density lipoprotein cholesterol (LDL-C) levels. The impact of partial genetic deficiency of ABCG5 or ABCG8, as occurs in heterozygous carriers of LoF variants, on LDL-C and risk of coronary artery disease (CAD) has remained uncertain.\n\nMethodsWe first recruited nine sitosterolemia families, identified causative LoF variants in ABCG5 or ABCG8, and evaluated the associations of these ABCG5 or ABCG8 LoF variants with plasma phytosterols and lipid levels. We next assessed for LoF variants in ABCG5 or ABCG8 in CAD cases (n=29,361) versus controls (n=357,326). We tested the association of rare LoF variants in ABCG5 or ABCG8 with blood lipids and risk for CAD. Rare LoF variants were defined as protein-truncating variants with minor allele frequency less than 0.1% in ABCG5 or ABCG8.\n\nResultsIn sitosterolemia families, seven pedigrees harbored causative LoF variants in ABCG5 and two pedigrees in ABCG8. Homozygous LoF variants in either ABCG5 or ABCG8 led to marked elevations in sitosterol and LDL-C. Of those sitosterolemia families, heterozygous carriers of ABCG5 LoF variants exhibited increased sitosterol and LDL-C levels compared to non-carriers. Within the large-scale CAD case-control cohorts, prevalence of rare LoF variants in ABCG5 and in ABCG8 were approximately 0.1% each. ABCG5 heterozygous LoF variant carriers had significantly elevated LDL-C levels (24.7 mg/dL; 95% confidence interval [CI] 14 to 35; P=1.1x10-6), and were at two-fold increased risk of CAD (odds ratio 2.06, 95% CI 1.27 to 3.35; P=0.004). By contrast, ABCG8 heterozygous LoF carrier status was not associated with increased LDL-C or risk of CAD.\n\nConclusionsAlthough familial sitosterolemia is traditionally considered as a recessive disorder, we observed that heterozygous carriers of a LoF variant in ABCG5 had significantly increased sitosterol and LDL-C levels and a two-fold increase in risk of CAD.

genetics↗

bioRxiv2019

Highly efficient and specific genome editing in human cells with paired CRISPR-Cas9 nickase ribonucleoproteins

CRISPR technology has opened up many diverse genome editing possibilities in human somatic cells, but has been limited in the therapeutic realm by both potential off-target effects and low genome modification efficiencies. Recent advancements to combat these limitations include delivering Cas9 nucleases directly to cells as highly purified ribonucleoproteins (RNPs) instead of the conventional plasmid DNA and RNA-based approaches. Here, we extend RNP-based delivery in cell culture to a less characterized CRISPR format which implements paired Cas9 nickases. The use of paired nickase Cas9 RNP system, combined with a GMP-compliant non-viral delivery technology, enables editing in human cells with high specificity and high efficiency, a development that opens up the technology for further exploration into a more therapeutic role.

molecular biology↗

bioRxiv2019

Heart Rate Variability with Photoplethysmography in 8 Million Individuals: Results and Scaling Relations with Age, Gender, and Time of Day

Heart rate variability, or the variation in the time interval between consecutive beats, is a non-invasive dynamic metric of the autonomic nervous system and an independent risk factor for cardiovascular death. Prior limitations of use include requirements for continuous electrocardiography and lack of reference standards. Consumer wrist-worn tracking devices using photoplethysmography now provide the unique potential of continuously measuring surrogates of sympathetic and parasympathetic activity through the analysis of interbeat intervals. Here we leverage wrist-worn trackers to present the largest, to our knowledge, analysis of heart rate variability in humans across the time, frequency, and graphical domains. We derive diurnal parasympathetic and sympathetic measures and provide scaling parameters by age, sex, and time of day. Poincare plots graphically summarize heart rate variability metrics and may detect common arrhythmias. Lastly, we observe a strong dose-dependent correlation between daily steps and optimal heart rate variability metrics. Our results provide the ability to interpret continuous heart rate variability for tens of millions of wrist-worn trackers already in use.

physiology↗