NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

Nucleosome positioning is involved in many gene regulatory processes happening in the cell, and it may change as cells differentiate or respond to the changing microenvironment in a healthy or diseased organism. One important implication of nucleosome positioning in clinical epigenetics is its use in the “nucleosomics” analysis of cell-free DNA (cfDNA) for the purpose of patient diagnostics in liquid biopsies. The rationale for this is that the apoptotic nucleases that digest chromatin of the dying cells mostly cut DNA between nucleosomes. Thus, the short pieces of DNA in body fluids reflect the positions of nucleosomes in the cells of origin. Here, we report a systematic nucleosomics database — NucPosDB — curating published nucleosome positioning datasets in vivo as well as datasets of sequenced cell-free DNA (cfDNA) that reflect nucleosome positioning in situ in the cells of origin. Users can select subsets of the database by a number of criteria and then obtain raw or processed data. NucPosDB also reports the originally determined regions with stable nucleosome occupancy across several individuals with a given condition. An additional section provides a catalogue of computational tools for the analysis of nucleosome positioning or cfDNA experiments and theoretical algorithms for the prediction of nucleosome positioning preferences from DNA sequence. We provide an overview of the field, describe the structure of the database in this context, and demonstrate data variability using examples of different medical conditions. NucPosDB is useful both for the analysis of fundamental gene regulation processes and the training of computational models for patient diagnostics based on cfDNA. The database currently curates ~ 400 publications on nucleosome positioning in cell lines and in situ as well as cfDNA from > 10,000 patients and healthy volunteers. For open-access cfDNA datasets as well as key MNase-seq datasets in human cells, NucPosDB allows downloading processed mapped data in addition to the regions with stable nucleosome occupancy. NucPosDB is available at https://generegulation.org/nucposdb/

Electric Vehicle Wireless Charging using RFID

Electric vehicle (EV) wireless charging using radio-frequency identification (RFID) is a novel technology that enables the charging of electric vehicles without the need for wires or cables. The technology utilizes RFID tags that are installed on the EV, which communicate with the charging pad through electromagnetic fields. The charging process is initiated when the RFID reader detects the presence of the EV with the installed RFID tag, and the charging pad is activated. The power transfer is then enabled between the charging pad and the EV, allowing for the charging process to begin. RFID-based wireless charging technology offers numerous benefits over traditional wired charging systems. For instance, it eliminates the need for physical connectors, thereby reducing the wear and tear of components and increasing the convenience of charging. Moreover, the technology is more efficient, with minimal energy losses, and reduces the risk of electrical hazards. It also minimizes the impact of weather conditions and road debris on the charging process, making it suitable for both indoor and outdoor charging application. In conclusion, EV wireless charging using RFID is a promising technology that can potentially revolutionize the EV charging industry. It offers numerous benefits, including increased convenience, efficiency, and safety, and has the potential to significantly reduce the environmental impact of transportation

Are textbook lungs really normal? A cadaveric study on the anatomical and clinical importance of variations in the major lung fissures, and the incomplete right horizontal fissure.

INTRODUCTION: The lungs have three main fissures: the right oblique fissure (ROF), right horizontal fissure (RHF), and left oblique fissure (LOF). These can be complete, incomplete or absent; quantifying the degree of completeness of these fissures is novel. Standard textbooks often refer to the fissures as complete, but awareness of variation is essential in thoracic surgery. MATERIALS AND METHODS: Fissures in 81 pairs of cadaveric lungs were classified. Oblique fissures were measured from lung hila posteriorly to the lung hila anteriorly; and the RHF measured from the ROF to the anteromedial lung edge. The degree of completeness of fissures was expressed as a percentage of the total projected length were they to be complete. The frequency and location of accessory fissures was noted. RESULTS: LOF were complete in 66/81 (81.5%), incomplete in 13/81 (16.0%) and absent in 2/81 (2.47%); ROF were complete in 52/81 (64.2%), incomplete in 29/81 (35.8%) and never absent; RHF were more variable, complete in 18/81 (22.2%), incomplete in 54/81 (66.7%) and absent in 9/81 (11.1%). LOF and ROF were on average 97.1% and 91.6% complete, respectively, being deficient posteriorly at the lung hila. The RHF on average 69.4% complete, being deficient anteromedially. There were accessory fissures in 10 left and 19 right lungs. CONCLUSIONS: This study provides a projection of the anatomy thoracic surgeons may encounter at operation, in particular the variable RHF. This knowledge is essential for optimal outcomes in both benign and oncological procedures influenced by the fissures

Activin type I receptor polymorphisms and body composition in older individuals with sarcopenia-Analyses from the LACE randomised controlled trial

BACKGROUND: Ageing is associated with changes in body composition including an overall reduction in muscle mass and a proportionate increase in fat mass. Sarcopenia is characterised by losses in both muscle mass and strength. Body composition and muscle strength are at least in part genetically determined, consequently polymorphisms in pathways important in muscle biology (e.g., the activin/myostatin signalling pathway) are hypothesised to contribute to the development of sarcopenia.METHODS: We compared regional body composition measured by DXA with genotypes for two polymorphisms (rs10783486, minor allele frequency (MAF) = 0.26 and rs2854464, MAF = 0.26) in the activin 1B receptor (ACVR1B) determined by PCR in a cross-sectional analysis of DNA from 110 older individuals with sarcopenia from the LACE trial.RESULTS: Neither muscle mass nor strength showed any significant associations with either genotype in this cohort. Initial analysis of rs10783486 showed that males with the AA/AG genotype were taller than GG males (174±7cm vs 170±5cm, p = 0.023) and had higher arm fat mass, (median higher by 15%, p = 0.008), and leg fat mass (median higher by 14%, p = 0.042). After correcting for height, arm fat mass remained significantly higher (median higher by 4% padj = 0.024). No associations (adjusted or unadjusted) were seen in females. Similar analysis of the rs2854464 allele showed a similar pattern with the presence of the minor allele (GG/AG) being associated with greater height (GG/AG = 174±7 cm vs AA = 170 ±5cm, p = 0.017) and greater arm fat mass (median higher by 16%, p = 0.023). Again, the difference in arm fat remained after correction for height. No similar associations were seen in females analysed alone.CONCLUSION: These data suggest that polymorphic variation in the ACVR1B locus could be associated with body composition in older males. The activin/myostatin pathway might offer a novel potential target to prevent fat accumulation in older individuals.</p

Activin type I receptor polymorphisms and body composition in older individuals with sarcopenia—Analyses from the LACE randomised controlled trial

Background: Ageing is associated with changes in body composition including an overall reduction in muscle mass and a proportionate increase in fat mass. Sarcopenia is characterised by losses in both muscle mass and strength. Body composition and muscle strength are at least in part genetically determined, consequently polymorphisms in pathways important in muscle biology (e.g., the activin/myostatin signalling pathway) are hypothesised to contribute to the development of sarcopenia.Methods: We compared regional body composition measured by DXA with genotypes for two polymorphisms (rs10783486, minor allele frequency (MAF) =0.26 and rs2854464, MAF =0.26) in the activin 1B receptor (ACVR1B) determined by PCR in a cross-sectional analysis of DNA from 110 older individuals with sarcopenia from the LACE trial.Results: Neither muscle mass nor strength showed any significant associations with either genotype in this cohort. Initial analysis of rs10783486 showed that males with the AA/AG genotype were taller than GG males (174±7cm vs 170±5cm, p=0.023) and had higher arm fat mass, (median higher by 15%, p=0.008), and leg fat mass (median higher by 14%, p=0.042). After correcting for height, arm fat mass remained significantly higher (median higher by 4% padj=0.024). No associations (adjusted or unadjusted) were seen in females.Similar analysis of the rs2854464 allele showed a similar pattern with the presence of the minor allele (GG/AG) being associated with greater height (GG/AG = 174±7 cm vs AA = 170 ±5cm, p=0.017) and greater arm fat mass (median higher by 16%, p=0.023). Again, the difference in arm fat remained after correction for height. No similar associations were seen in females analysed alone.Conclusion: These data suggest that polymorphic variation in the ACVR1B locus could be associated with body composition in older males. The activin/myostatin pathway might offer a novel potential target to prevent fat accumulation in older individuals

ACE I/D genotype associates with strength in sarcopenic men but not with response to ACE inhibitor therapy in older adults with sarcopenia:Results from the LACE trial

BACKGROUND: Angiotensin II (AII), has been suggested to promote muscle loss. Reducing AII synthesis, by inhibiting angiotensin converting enzyme (ACE) activity has been proposed as a method to inhibit muscle loss. The LACE clinical trial was designed to determine whether ACE inhibition would reduce further muscle loss in individuals with sarcopenia but suffered from low recruitment and returned a negative result. Polymorphic variation in the ACE promoter (I/D alleles) has been associated with differences in ACE activity and muscle physiology in a range of clinical conditions. This aim of this analysis was to determine whether I/D polymorphic variation is associated with muscle mass, strength, in sarcopenia or contributed to the lack of response to treatment in the LACE study.METHODS: Sarcopenic individuals were recruited into a 2x2 factorial multicentre double-blind study of the effects of perindopril and/or leucine versus placebo on physical performance and muscle mass. DNA extracted from blood samples (n = 130 72 women and 58 men) was genotyped by PCR for the ACE I/D polymorphism. Genotypes were then compared with body composition measured by DXA, hand grip and quadriceps strength before and after 12 months' treatment with leucine and/or perindopril in a cross-sectional analysis of the influence of genotype on these variables.RESULTS: Allele frequencies for the normal UK population were extracted from 13 previous studies (I = 0.473, D = 0.527). In the LACE cohort the D allele was over-represented (I = 0.412, D = 0.588, p = 0.046). This over-representation was present in men (I = 0.353, D = 0.647, p = 0.010) but not women (I = 0.458, D = 0.532, p = 0.708). In men but not women, individuals with the I allele had greater leg strength (II/ID = 18.00 kg (14.50, 21.60) vs DD = 13.20 kg (10.50, 15.90), p = 0.028). Over the 12 months individuals with the DD genotype increased in quadriceps strength but those with the II or ID genotype did not. Perindopril did not increase muscle strength or mass in any polymorphism group relative to placebo.CONCLUSION: Our results suggest that although ACE genotype was not associated with response to ACE inhibitor therapy in the LACE trial population, sarcopenic men with the ACE DD genotype may be weaker than those with the ACE I/D or II genotype.</p

Nucleosome reorganisation in breast cancer tissues.

Background Nucleosome repositioning in cancer is believed to cause many changes in genome organisation and gene expression. Understanding these changes is important to elucidate fundamental aspects of cancer. It is also important for medical diagnostics based on cell-free DNA (cfDNA), which originates from genomic DNA regions protected from digestion by nucleosomes. Results We have generated high-resolution nucleosome maps in paired tumour and normal tissues from the same breast cancer patients using MNase-assisted histone H3 ChIP-seq and compared them with the corresponding cfDNA from blood plasma. This analysis has detected single-nucleosome repositioning at key regulatory regions in a patient-specific manner and common cancer-specific patterns across patients. The nucleosomes gained in tumour versus normal tissue were particularly informative of cancer pathways, with ~ 20-fold enrichment at CpG islands, a large fraction of which marked promoters of genes encoding DNA-binding proteins. The tumour tissues were characterised by a 5-10 bp decrease in the average distance between nucleosomes (nucleosome repeat length, NRL), which is qualitatively similar to the differences between pluripotent and differentiated cells. This effect was correlated with gene activity, differential DNA methylation and changes in local occupancy of linker histone variants H1.4 and H1X. Conclusions Our study offers a novel resource of high-resolution nucleosome maps in breast cancer patients and reports for the first time the effect of systematic decrease of NRL in paired tumour versus normal breast tissues from the same patient. Our findings provide a new mechanistic understanding of nucleosome repositioning in tumour tissues that can be valuable for patient diagnostics, stratification and monitoring

GWAS of Suicide Attempt in Psychiatric Disorders Identifies Association With Major Depression Polygenic Risk Scores

Objective: Over 90% of suicide attempters have a psychiatric diagnosis, however twin and family studies suggest that the genetic etiology of suicide attempt (SA) is partially distinct from that of the psychiatric disorders themselves. Here, we present the largest genome-wide association study (GWAS) on suicide attempt using major depressive disorder (MDD), bipolar disorder (BIP) and schizophrenia (SCZ) cohorts from the Psychiatric Genomics Consortium. Method: Samples comprise 1622 suicide attempters and 8786 non-attempters with MDD, 3264 attempters and 5500 non-attempters with BIP and 1683 attempters and 2946 non-attempters with SCZ. SA GWAS were performed by comparing attempters to non-attempters in each disorder followed by meta-analyses across disorders. Polygenic risk scoring was used to investigate the genetic relationship between SA and the psychiatric disorders. Results: Three genome-wide significant loci for SA were found: one associated with SA in MDD, one in BIP, and one in the meta-analysis of SA in mood disorders. These associations were not replicated in independent mood disorder cohorts from the UK Biobank and iPSYCH. No significant associations were found in the meta-analysis of all three disorders. Polygenic risk scores for major depression were significantly associated with SA in MDD (R2=0.25%, P=0.0006), BIP (R2=0.24%, P=0.0002) and SCZ (R2=0.40%, P=0.0006). Conclusions: This study provides new information on genetic associations and demonstrates that genetic liability for major depression increases risk for suicide attempt across psychiatric disorders. Further collaborative efforts to increase sample size hold potential to robustly identify genetic associations and gain biological insights into the etiology of suicide attempt

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14