bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association analyses of predicted loss-of-function variants prioritized 15 genes as blood pressure regulators
Authors: Lecluze Estelle , Lettre Guillaume 
Published: March 2023

ABSTRACTBackgroundHypertension, clinically defined by elevated blood pressure (BP), is an important cause of mortality and morbidity worldwide. Many risk factors for hypertension are known, including a positive family history, which suggests that genetics contribute to inter-individual BP variation. Genome-wide association studies (GWAS) have identified >1000 loci associated with BP, yet the identity of the genes responsible for these associations remains largely unknown.MethodsTo pinpoint genes that causally impact BP variation in humans, we analyzed predicted loss-of-function (pLoF) variants in the UK Biobank whole-exome sequencing dataset (n=454,709 participants, 6% non-European ancestry). We analyzed genetic associations between systolic or diastolic BP (SBP/DBP) and single pLoF variants (additive and recessive genetic models) as well as with the burden of very rare pLoF variants (minor allele frequency [MAF] <0.01%).ResultsSingle pLoF variants in ten genes associated with BP (ANKDD1B,ENPEP,PNCK, BTN3A2, C1orf145 [OBSCN-AS1],CASP9,DBH,KIAA1161 [MYORG],OR4X1, andTMC3). We also found a burden of rare pLoF variants in five additional genes associated with BP (TTN, NOS3, FES, SMAD6, COL21A1). Except forPNCK, which is located on the X-chromosome, these genes map near variants previously associated with BP by GWAS, validating the study of pLoF variants to prioritize causal genes at GWAS loci.ConclusionsOur study highlights 15 genes that likely modulate BP in humans, including five genes that harbor pLoF variants associated with lower BP.
Mapping the dynamic genetic regulatory architecture ofHLAgenes at single-cell resolution
Authors: Kang Joyce B. , Shen Amber Z. , Sakaue Saori , Luo Yang , Gurajala Saisriram , Nathan Aparna , Rumker Laurie , Aguiar Vitor R. C. , Valencia Cristian , Lagattuta Kaitlyn , Zhang Fan , Jonsson Anna Helena , Yazar Seyhan , Alquicira-Hernandez Jose , Khalili Hamed , Ananthakrishnan Ashwin N. , Jagadeesh Karthik , Dey Kushal ,   Accelerating Medicines Partnership Program: Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Network, Daly Mark J. , Xavier Ramnik J. , Donlin Laura T. , Anolik Jennifer H. , Powell Joseph E. , Rao Deepak A. , Brenner Michael B. , Gutierrez-Arcelus Maria , Raychaudhuri Soumya 
Published: March 2023

AbstractThe human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation inHLAgenes has been extensively documented, regulatory genetic variation modulatingHLAexpression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classicalHLAgenes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specificcis-eQTLs for every classicalHLAgene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type.HLA-DQgenes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. DynamicHLAregulation may underlie important interindividual variability in immune responses.
Serum lipidome associates with neuroimaging features in patients with traumatic brain injury
Authors: Thomas Ilias , Newcombe Virginia F. J. , Dickens Alex M. , Richter Sophie , Posti Jussi P. , Maas Andrew I. R. , Tenovuo Olli , Hyötyläinen Tuulia , Büki András , Menon David K. , Orešič Matej ,   CENTER-TBI MR subgroup Participants and Investigators
Published: March 2023

AbstractAcute traumatic brain injury (TBI) is associated with substantial metabolic abnormalities, both centrally and in the periphery. We have previously reported extensive changes in the circulating metabolome resulting from TBI, including changes proportional to disease severity and associated with patient outcomes. The observed metabolome changes in TBI likely reflect several pathophysiological mechanisms supporting the concept that TBI is a systemic disease after the primary injury. However, one of the main metabolic changes we have observed following a TBI are changes in lipids, including the structural lipids that are known to be present in the myelin in the brain.Here, we conducted a study to investigate the relationship between traumatic microstructural changes in white matter seen on magnetic resonance imaging (MRI) and quantitative lipidomic changes in the blood in a subset of patients with TBI recruited to the MRI sub-study of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study.In total, there were 103 patients who had both a magnetic resonance imaging (MRI) scan and serum samples available for analysis. From serum, 201 known lipids were quantified. Diffusion tensor fitting generated fractional anisotropy (FA) and mean diffusivity (MD) maps for the MRI scans, in addition to volumetric data. Association matrices and partial correlation networks were built to elucidate the connections between the lipid groups and the maps.We found that there are distinct directions of associations between the neuroimage data (FA and MD sets) and the concentrations of circulating lipids after injury. The FA and MD values were in inverse relationship with the severity of TBI (higher MD values, lower FA). We also observed that the lipid associations to FA and MD show different metabolic signatures. Lysophosphatidylcholines (LPC) associate mostly with FA while sphingomyelins (SM) associate with MD. Only phosphatidylcholines(PC) have strong associations with both as well as with the volumetric data. Finally, we found that the lipid changes are not associated with the number of regions with abnormalities.In conclusion, we have identified groups of lipids which assocate with specific MRI imaging metrics following TBI. There appears to be consistent patterns of lipid changes associating with the specific microstructure changes in the CNS white matter. There is also a pattern of lipids with regional specficity, suggesting that blood-based lipidomics may provide an insight into the underlying disease mechanisms in TBI.
Evidence for a shared genetic contribution to loneliness and Borderline Personality Disorder
Authors: Schulze Anna , Streit Fabian , Zillich Lea , Awasthi Swapnil , Hall Alisha S M , Jungkunz Martin , Kleindienst Nikolaus , Frank Josef , Schwarze Cornelia E , Dahmen Norbert , Schott Björn H , Nöthen Markus , Mobascher Arian , Rujescu Dan , Lieb Klaus , Roepke Stefan , Herpertz Sabine C , Schmahl Christian , Bohus Martin , Ripke Stephan , Rietschel Marcella , Lis Stefanie , Witt Stephanie 
Published: March 2023

AbstractLoneliness, influenced by genetic and environmental factors such as childhood maltreatment, is one aspect of interpersonal dysfunction in Borderline Personality Disorder (BPD). Numerous studies link loneliness and BPD and twin studies indicate a genetic contribution to this association. The aim of our study was to investigate whether genetic predisposition for loneliness and BPD risk overlap and whether genetic risk for loneliness contributes to higher loneliness reported by BPD patients, using genome-wide genotype data. We assessed the genetic correlation of genome-wide association studies (GWAS) of loneliness and BPD using linkage disequilibrium score regression and tested whether a polygenic score for loneliness (loneliness-PGS) was associated with case-control status in two independent genotyped samples of BPD patients and healthy controls (HC; Witt2017-sample: 998 BPD, 1545 HC; KFO-sample: 187 BPD, 261 HC). In the KFO-sample, we examined associations of loneliness-PGS with reported loneliness, and whether the loneliness-PGS influenced the association between childhood maltreatment and loneliness. We found a genetic correlation between the GWAS of loneliness and BPD in the Witt2017-sample (rg = .23,p= .015), a positive association of loneliness–PGS with BPD case-control status (Witt2017-sample: NkR² = 2.3%,p= 2.7*10-12; KFO-sample: NkR² = 6.6%,p= 4.4*10-6), and a positive association between loneliness-PGS and loneliness across patient and control groups in the KFO-sample (β= .185,p= .002). The loneliness-PGS did not moderate the association between childhood maltreatment and loneliness in BPD. Our study is the first to use genome-wide genotype data to show that the genetic factors underlying variation in loneliness in the general population and the risk for BPD overlap. The loneliness-PGS was associated with reported loneliness. Further research is needed to investigate which genetic mechanisms and pathways are involved in this association and whether a genetic predisposition for loneliness contributes to BPD risk.
Individual fixel-based white matter abnormalities in the epilepsies
Authors: Mito Remika , Pedersen Mangor , Pardoe Heath , Parker Donna , Smith Robert E. , Cameron Jillian , Scheffer Ingrid E. , Berkovic Samuel F. , Vaughan David N. , Jackson Graeme D. 
Published: March 2023

AbstractDiffusion MRI has provided insight into the widespread structural connectivity changes that characterise the epilepsies. Although syndrome-specific white matter abnormalities have been demonstrated, studies have predominantly relied on statistical comparisons between patient and control groups. For diffusion MRI techniques to be of clinical value, they should be able to detect white matter microstructural changes in individual patients. In this study, we apply an individualised approach to a novel technique known as fixel-based analysis, to examine fibre-tract-specific abnormalities in individuals with epilepsy. We explore the potential clinical value of this individualised fixel-based approach in epilepsy patients with differing syndromic diagnoses. Diffusion MRI data from 90 neurologically healthy control participants and 10 patients with epilepsy (temporal lobe epilepsy, Progressive Myoclonus Epilepsy, Dravet Syndrome, malformations of cortical development) were included in this study. Measures of fibre density and cross-section were extracted for all participants across brain white matter fixels, and mean values computed within select tracts-of-interest. Scanner harmonised and normalised data were then used to compute Z-scores for individual patients with epilepsy. Microstructural white matter abnormalities were observed in distinct patterns in individual patients with epilepsy, both at the tract and fixel level. For patients with specific epilepsy syndromes, the detected white matter abnormalities were largely in line with expected syndrome-specific clinical phenotypes. In patients with lesional epilepsies (e.g., hippocampal sclerosis, periventricular nodular heterotopia, bottom-of-sulcus dysplasia), microstructural abnormalities were concordant with lesion location. This study demonstrates the clinical potential of translating advanced diffusion MRI methodology to individual patient-level use in epilepsy. This technique could be useful both in aiding diagnosis of specific epilepsy syndromes, and in localising structural abnormalities, and is readily amenable to other neurological disorders. We have included code and data for this study, so that individualised white matter changes can be explored robustly in larger cohorts in future work.
DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Accurate Protein-Ligand Interaction Prediction
Authors: Zhang Haiping , Saravanan Konda Mani , Zhang John Z.H. 
Published: March 2023

AbstractThe core of large-scale drug virtual screening is to accurately and efficiently select the binders with high affinity from large libraries of small molecules in which nonbinders are usually dominant. The protein pocket, ligand spatial information, and residue types/atom types play a pivotal role in binding affinity. Here we used the pocket residues or ligand atoms as nodes and constructed edges with the neighboring information to comprehensively represent the protein pocket or ligand information. Moreover, we find that the model with pre-trained molecular vectors performs better than the onehot representation. The main advantage of DeepBindGCN is that it is non-dependent on docking conformation and concisely keeps the spatial information and physical-chemical feature. Notably, the DeepBindGCN_BC has high precision in many DUD.E datasets, and DeepBindGCN_RG achieve a very low RMSE value in most DUD.E datasets. Using TIPE3 and PD-L1 dimer as proof-of-concept examples, we proposed a screening pipeline by integrating DeepBindGCN_BC, DeepBindGCN_RG, and other methods to identify strong binding affinity compounds. In addition, a DeepBindGCN_RG_x model has been used for comparing performance with other methods in PDBbind v.2016 and v.2013 core set. It is the first time that a non-complex dependent model achieves an RMSE value of 1.3843 and Pearson-R value of 0.7719 in the PDBbind v.2016 core set, showing comparable prediction power with the state-of-the-art affinity prediction models that rely upon the 3D complex. Our DeepBindGCN provides a powerful tool to predict the protein-ligand interaction and can be used in many important large-scale virtual screening application scenarios.
De novomutation rates in sticklebacks
Authors: Zhang Chaowei , Reid Kerry , Sands Arthur F. , Fraimout Antoine , Schierup Mikkel Heide , Merilä Juha 
Published: March 2023

AbstractMutation rate is a fundamental parameter in population genetics. Apart from being an important scaling parameter for demographic and phylogenetic inference, it allows one to understand at what rate new genetic diversity is generated and what is the expected level of genetic diversity in a population at equilibrium. However, except for well-established model organisms, accurate estimates ofde novomutation rates are available for a very limited number of organisms from the wild. We estimated mutation rates (µ) in two marine populations of the nine-spined stickleback (Pungitius pungitius) with the aid of several 2- and 3-generational family pedigrees, deep (>50×) whole genome re-sequencing and a high-quality reference genome. After stringent filtering, we discovered 295 germline mutations from 106 offspring translating toµ= 4.64 × 10−9andµ= 4.08 × 10−9per base, per generation, in the two populations, respectively. Twenty percent of the mutations were shared by full-sibs showing that the level of parental mosaicism was relatively high. Since the estimatedµwas 3.2 times smaller than the commonly used substitution rate, recalibration withµled to substantial increase in estimated divergence times between different stickleback species. Our estimates ofde novomutation rate should provide a useful resource for research focused on fish population genetics and that of sticklebacks in particular.
Mathematical Modeling of PCR with Variable Concentrations of DNA andTaqPolymerase
Authors: Ahmad Fraz , Zia Saeeda , Saif Rashid , Raza Muhammad Hassan 
Published: March 2023

AbstractPolymerase Chain Reaction (PCR) is one of the important techniques in molecular biology for many diagnostics and research applications. In this current theoretical PCR optimization research, out of its seven recipe reagents, two of the important constituents e.g., DNA which might be very rare in forensic cases and polymerase enzyme due to its high cost were mathematically modeled and computationally simulated using MATLAB programming platform. Chemical equations of PCR stages were established using the law of mass action followed by differential equations derivations from each of the DNA amplification phases. Firstly, a mathematical model ofTaqpolymerase enzyme with its variable concentrations ranging from 0.05-0.35IU/μLwas formulated which showed the best PCR product of 0.61ng/μLobtained with 0.2IU/μLof polymerase. Similarly, by fixing the optimal polymerase concentration obtained in the previous simulation, the prime-DNA variable concentrations ranging from 0.5-3.5ng/μLwere further simulated which showed the best PCR product of 0.94ng/μLat 2.0ng/μLof DNA. PCR wet-lab experimentation and gel-electrophoresis visualization validated mathematically simulated optimized concentrations of the aforementioned two reagents which vary the PCR product considerably. Current findings indicate that mathematically optimized concentrations ofTaq-polymerase and template-DNA may reduce the PCR cost, time and energy, but other factors of target-sequence specificity, purity/concentrations of the other reagents, working hygiene, technical intricacies, biosafety and biosecurity factors may also contribute the desired yield of the amplicon.
Single-cell Electrochemical Aptasensor Array
Authors: Li Shuo , Coffinier Yannick , Lagadec Chann , Cleri Fabrizio , Nishiguchi Katsuhiko , Fujiwara Akira , Kim Soo Hyeon , Clément Nicolas 
Published: March 2023

ABSTRACTDespite several demonstrations of electrochemical devices with limits of detection (LOD) of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to the challenges of scaling up. In this study, we show that the recently introduced nanopillar array technology combined with redox-labelled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array, based on Brownian-fluctuating redox species, opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.For Table of Contents only
Neoepitope formation through the generation of RNA-derived “editopes”
Authors: Casati Beatrice , Pinamonti Veronica , Pecori Riccardo , Lindner John M. , Papavasiliou Fotini Nina 
Published: March 2023

ABSTRACTTreatment-resistant tumors are frequently characterized by a low tumor mutational burden (TMB) and poor T-cell infiltration into the tumor microenvironment. Conversely, good responses to immunotherapy have been associated with high TMB and T-cell infiltration. This may imply that at least a subset of mutations in TMB-high tumors result in the generation of neoepitopes that are recognized (and cleared) by T cells. Currently, methods that specifically mutate MHC-presented tumor epitopes, while preserving genomic integrity, do not exist. Here, we have employed site-directed RNA editing to specifically alter MHC-presented tumor epitopes at the transcript level, with no modification to the genomic DNA, to modulate their antigenicity and recognition by cognate T-cell receptors (TCR). We demonstrate that RNA editing can be employed as a precision tool to specifically modulate antigenicity through the formation of RNA editing derived neoepitopes, which we have termed “editopes”. In particular, we show potent induction of a T-cell response to an optimally edited peptide (40%) compared to a non-immunogenic mutant peptide (<2%) and its WT counterpart (20%). This study shows the potential of RNA editing as a method to improve tumor recognition by T cells and to favor tumor clearance.
REAL-TIME AT-LINE MONITORING OF INFLUENZA VIRUS IN CELL CULTURE BY A SURFACE PLASMON RESONANCE BIOSENSOR
Authors: Durous Laurent , Padey Blandine , Traversier Aurélien , Chupin Caroline , Julien Thomas , Blum Loïc J. , Marquette Christophe A. , Rosa-Calatrava Manuel , Petiot Emma 
Published: March 2023

ABSTRACTSince the early 2000’, regulation agencies have encouraged viral vaccine manufacturers to implement in-process and real-time monitoring tools in production processes. Even if more assays have been recently developed, none of the novel viral particle quantification technologies can monitor virus levels and their secretion kinetics within production vessels. Vaccine manufacturers still rely on offline cell-based infectivity assays and antigen amount quantification to monitor their processes. The present study describes the development of the first automated biosensor for at-line monitoring of influenza virus production. It involves coupling a fetuin-based SPRi quantitative biosensor with an automated sampler of culture broth and a consecutive clarification setup via an acoustic filter. The SPRi response of different viral strains produced in two distinct cell production platforms was qualified. We demonstrated that fetuin-based quantitative SPRi is a robust, potency-indicating, and universal analytical technology for quantifying bioactive influenza virus particles. It was validated with both purified and complex matrices. Finally, an influenza viral production kinetic was monitoredonlinefor three days. This novel online tool enabled the access in real-time to total bioactive viral particles from early production phases (8hpi).
Chemodiversity affects preference forTanacetum vulgarechemotypes in two aphid species
Authors: Neuhaus-Harr Annika , Ojeda-Prieto Lina , Eilers Elisabeth , Müller Caroline , Weisser Wolfgang W. , Heinen Robin 
Published: March 2023

AbstractPlants of the same species often strongly differ in morphological traits, as well as in the abundance and composition of specialized metabolite profiles. Specialized metabolites can act as mediators of interactions on plants, and affect insect presence and abundance in the field. However, how specialized chemistry shapes plant attractiveness to herbivorous insects is not fully understood. Here we used common tansy (Tanacetum vulgareL., Asteraceae) – a perennial plant that is highly diverse in terpenoid composition and is known to have variable chemotypes – to test whether 1) plants with different chemotype profiles differ in attractiveness to two specialized aphids,Macrosiphoniella tanacetariaandUroleucon tanaceti, in pairwise choice assays. Furthermore, we tested whether 2) the diversity of the terpenoid blend affects aphid attractiveness. Lastly, we tested how 3) plant chemical traits relate to plant morphological traits, and which best explain aphid preference. We found thatM. tanacetariapreferred two out of five chemotypes, dominated by α-thujone/β-thujone and β-trans-chrysanthenyl acetate, respectively, while avoiding a chemotype dominated by α-pinene/sabinene.U. tanacetishowed no clear preference towards chemotypes, but when given the choice between chemotypes dominated by α-thujone/β-thujone and by α-pinene/sabinene, they preferred the former. Importantly, plant attractiveness to aphids tended to be negatively correlated with chemodiversity, i.e., the number of terpenoid compounds, inM. tanacetaria, but not inU. tanaceti. Interestingly, the approximate concentration and number of terpenoid compounds was generally higher in larger and bushier plants. Hence, we did not observe a trade-off between plant growth and defence. We conclude that plant chemical composition affects plant attractiveness to aphids and hence may contribute to variation in natural aphid colonization patterns on plants of the same species.