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Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins. The immune response is complex and varies across diseases and patients, and its modelling requires the collective expertise of the clinical, immunology, and computational modelling communities. This review outlines the initial progress on immune digital twins and the various initiatives to facilitate communication between interdisciplinary communities. We also outline the crucial aspects of an immune digital twin design and the prerequisites for its implementation in the clinic. We propose some initial use cases that could serve as "proof of concept" regarding the utility of immune digital technology, focusing on diseases with a very different immune response across spatial and temporal scales (minutes, days, months, years). Lastly, we discuss the use of digital twins in drug discovery and point out emerging challenges that the scientific community needs to collectively overcome to make immune digital twins a reality., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts. We identify several consistent changes (individual genes, proteins, and molecular pathways) occurring across all insulin-resistant kidney cell types, together with cell-line-specific changes occurring in response to insulin resistance, which are replicated in DKD biopsies. This study provides a rich data resource to direct future studies in elucidating underlying kidney signalling pathways and potential therapeutic targets in DKD., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

The characterization of genes and biological functions underlying functional diversification and the formation of species is a major goal of evolutionary biology. In this study, we investigated the fast radiation of Microtus voles, one of the most speciose group of mammals, which shows strong genetic divergence despite few readily observable morphological differences. We produced an annotated reference genome for the common vole, Microtus arvalis, and resequenced the genomes of 10 different species and evolutionary lineages spanning the Microtus speciation continuum. Our full-genome sequences illustrate the recent and fast diversification of this group, and we identified genes in highly divergent genomic windows that have likely particular roles in their radiation. We found three biological functions enriched for highly divergent genes in most Microtus species and lineages: olfaction, immunity and metabolism. In particular, olfaction-related genes (mostly olfactory receptors and vomeronasal receptors) are fast evolving in all Microtus species indicating the exceptional importance of the olfactory system in the evolution of these rodents. Of note is e.g. the shared signature among vole species on Olfr1019 which has been associated with fear responses against predator odors in rodents. Our analyses provide a genome-wide basis for the further characterization of the ecological factors and processes of natural and sexual selection that have contributed to the fast radiation of Microtus voles., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

To identify the pathways that are coordinately regulated in pancreatic β cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2, and Balb/c mice a regular chow or a high fat diet for 5, 13, and 33 days. Physiological, transcriptomic and lipidomic data were used in a data fusion approach to identify organ-specific pathways linked to fasting glycemia across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels was associated with reduced expression of hormone and neurotransmitter receptors, OXPHOS, cadherins, integrins, and gap junction mRNAs. Higher glycemia and insulin resistance were associated, in muscle, with decreased insulin signaling, glycolytic, Krebs' cycle, OXPHOS, and endo/exocytosis mRNAs; in hepatocytes, with reduced insulin signaling, branched chain amino acid catabolism and OXPHOS mRNAs; in adipose tissue, with increased innate immunity and lipid catabolism mRNAs. These data provide a resource for further studies of interorgan communication in glucose homeostasis., Competing Interests: M.G., C.K., and K.S. are employees of Lipotype GmbH., (© 2024 The Author(s).)

Fungi of the genus Aspergillus are widespread in the environment, where they produce large quantities of airborne conidia. Inhalation of Aspergillus spp. conidia in immunocompromised individuals can cause a wide spectrum of diseases, ranging from hypersensitivity responses to lethal invasive infections. Upon deposition in the lung epithelial surface, conidia encounter and interact with complex microbial communities that constitute the lung microbiota. The lung microbiota has been suggested to influence the establishment and growth of Aspergillus spp. in the human airways. However, the mechanisms underlying this interaction have not yet been sufficiently investigated. In this study, we aimed to enrich and isolate bacterial strains capable of inhibiting the germination and growth of A. fumigatus conidia from bronchoalveolar lavage fluid (BALF) samples of lung transplant recipients using a novel enrichment method. This method is based on a soft agar overlay plate assay in which bacteria are directly in contact with conidia, allowing inhibition to be readily observed during enrichment. We isolated a total of five clonal bacterial strains with identical genotypic fingerprints, as shown by random amplified polymorphic DNA PCR (RAPD-PCR). All strains were identified as Pseudomonas aeruginosa (strains b1-b5). The strains were able to inhibit the germination and growth of Aspergillus fumigatus in a soft agar confrontation assay, as well as in a germination multiplate assay. Moreover, when compared with ten P. aeruginosa strains isolated from expectoration through standard methods, no significant differences in inhibitory potential were observed. Additionally, we showed inhibition of A. fumigatus growth on Calu-3 cell culture monolayers. However, the isolated P. aeruginosa strains were shown to cause significant damage to the cell monolayers. Overall, although P. aeruginosa is a known opportunistic lung pathogen and antagonist of A. fumigatus , we validated this novel one-step enrichment approach for the isolation of bacterial strains antagonistic to A. fumigatus from BALF samples as a proof-of-concept. This opens up a new venue for the targeted enrichment of antagonistic bacterial strains against specific fungal pathogens.

Reconstructing the history-such as the place of birth and death-of an individual sample is a fundamental goal in ancient DNA (aDNA) studies. However, knowing the place of death can be particularly challenging when samples come from museum collections with incomplete or erroneous archives. While analyses of human DNA and isotope data can inform us about the ancestry of an individual and provide clues about where the person lived, they cannot specifically trace the place of death. Moreover, while ancient human DNA can be retrieved, a large fraction of the sequenced molecules in ancient DNA studies derive from exogenous DNA. This DNA-which is usually discarded in aDNA analyses-is constituted mostly by microbial DNA from soil-dwelling microorganisms that have colonized the buried remains post-mortem. In this study, we hypothesize that remains of individuals buried in the same or close geographic areas, exposed to similar microbial communities, could harbor more similar metagenomes. We propose to use metagenomic data from ancient samples' shotgun sequencing to locate the place of death of a given individual which can also help to solve cases of sample mislabeling. We used a k-mer-based approach to compute similarity scores between metagenomic samples from different locations and propose a method based on dimensionality reduction and logistic regression to assign a geographical origin to target samples. We apply our method to several public datasets and observe that individual samples from closer geographic locations tend to show higher similarities in their metagenomes compared to those of different origin, allowing good geographical predictions of test samples. Moreover, we observe that the genus Streptomyces commonly infiltrates ancient remains and represents a valuable biomarker to trace the samples' geographic origin. Our results provide a proof of concept and show how metagenomic data can also be used to shed light on the place of origin of ancient samples., (© 2024. The Author(s).)

In this study, we investigated the temporal and spatial quantitative changes in the concentration of antibiotic resistance gene (ARG) markers in a municipal wastewater treatment plant (WWTP). Four ARGs conferring resistance to different classes of antibiotics (ermB, sul1, tet[W], and bla CTXM ) and a gene used as a proxy for ARG pollution (intl1) were quantified in two separate sampling campaigns covering two and half years of operation of the WWTP. First, a systematic monthly monitoring of multiple points in the inlet and the outlet revealed an absolute decrease in the concentration of all analyzed ARGs. However, the relative abundance of sul1 and intl1 genes relative to the total bacterial load (estimated using the universal marker 16S rDNA) increased in the outlet samples as compared to the inlet. To pinpoint the exact stage of removal and/or enrichment within the WWTP, a second sampling including the stages of the biological treatment was performed bimonthly. This revealed a distinct enrichment of sul1 and intl1 genes during the biological treatment phase. Moreover, the temporal and spatial variations in ARG abundance patterns within the WWTP underscored the complexity of the dynamics associated with the removal of ARGs during wastewater treatment. Understanding these dynamics is pivotal for developing efficient strategies to mitigate the dissemination of ARGs in aquatic environments. PRACTITIONER POINTS: Regular monitoring of ARG markers in WWTPs is essential to assess temporal and spatial changes, aiding in the development of effective mitigation strategies. Understanding the dynamics of ARG abundance during biological treatment is crucial for optimizing processes and minimizing dissemination in aquatic environments. Increased relative abundance of certain ARGs highlights potential enrichment during wastewater treatment, necessitating targeted interventions. Systematic monitoring of multiple points within WWTPs can provide valuable insights into the efficacy of treatment processes in reducing ARG levels over time. The complexity of ARG abundance patterns underscores the need to develop holistic approaches to tackle antibiotic resistance in wastewater systems., (© 2024 The Author(s). Water Environment Research published by Wiley Periodicals LLC on behalf of Water Environment Federation.)

We recently indicated that four-week probiotic supplementation significantly reduced depression along with microbial and neural changes in people with depression. Here we further elucidated the biological modes of action underlying the beneficial clinical effects of probiotics by focusing on immune-inflammatory processes. The analysis included a total of N = 43 participants with depression, from which N = 19 received the probiotic supplement and N = 24 received a placebo over four weeks, in addition to treatment as usual. Blood and saliva were collected at baseline, at post-intervention (week 4) and follow-up (week 8) to assess immune-inflammatory markers (IL-1β, IL-6, CRP, MIF), gut-related hormones (ghrelin, leptin), and a stress marker (cortisol). Furthermore, transcriptomic analyses were conducted to identify differentially expressed genes. Finally, we analyzed the associations between probiotic-induced clinical and immune-inflammatory changes. We observed a significant group x time interaction for the gut hormone ghrelin, indicative of an increase in the probiotics group. Additionally, the increase in ghrelin was correlated with the decrease in depressive symptoms in the probiotics group. Transcriptomic analyses identified 51 up- and 57 down-regulated genes, which were involved in functional pathways related to enhanced immune activity. We identified a probiotic-dependent upregulation of the genes ELANE, DEFA4 and OLFM4 associated to immune activation and ghrelin concentration. These results underscore the potential of probiotic supplementation to produce biological meaningful changes in immune activation in patients with depression. Further large-scale mechanistic trials are warranted to validate and extend our understanding of immune-inflammatory measures as potential biomarkers for stratification and treatment response in depression. Trial Registration: www.clinicaltrials.gov , identifier: NCT02957591., (© 2024. The Author(s).)

Aims/hypothesis: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA 1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value., Methods: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA 1c , HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic., Results: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA 1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA 1c ) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance., Conclusions/interpretation: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification., Data Availability: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch ., (© 2024. The Author(s).)

Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma., Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics., Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p =3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor., Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D., Competing Interests: GR has received grant funding from, and is a consultant for, Sun Pharmaceuticals Inc. KS is CEO of Lipotype. KS and CK are shareholders of Lipotype. MG is an employee of Lipotype. MH is an employee of Janssen Research & Development. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Li, Dragan, Tran, Fung, Kuznetsov, Hansen, Beulens, Hart, Slieker, Donnelly, Gerl, Klose, Mehl, Simons, Elders, Pearson, Rutter and Ibberson.)

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Aims/hypothesis: Repeated exposures to insulin-induced hypoglycaemia in people with diabetes progressively impairs the counterregulatory response (CRR) that restores normoglycaemia. This defect is characterised by reduced secretion of glucagon and other counterregulatory hormones. Evidence indicates that glucose-responsive neurons located in the hypothalamus orchestrate the CRR. Here, we aimed to identify the changes in hypothalamic gene and protein expression that underlie impaired CRR in a mouse model of defective CRR., Methods: High-fat-diet fed and low-dose streptozocin-treated C57BL/6N mice were exposed to one (acute hypoglycaemia [AH]) or multiple (recurrent hypoglycaemia [RH]) insulin-induced hypoglycaemic episodes and plasma glucagon levels were measured. Single-nuclei RNA-seq (snRNA-seq) data were obtained from the hypothalamus and cortex of mice exposed to AH and RH. Proteomic data were obtained from hypothalamic synaptosomal fractions., Results: The final insulin injection resulted in similar plasma glucose levels in the RH group and AH groups, but glucagon secretion was significantly lower in the RH group (AH: 94.5±9.2 ng/l [n=33]; RH: 59.0±4.8 ng/l [n=37]; p<0.001). Analysis of snRNA-seq data revealed similar proportions of hypothalamic cell subpopulations in the AH- and RH-exposed mice. Changes in transcriptional profiles were found in all cell types analysed. In neurons from RH-exposed mice, we observed a significant decrease in expression of Avp, Pmch and Pcsk1n, and the most overexpressed gene was Kcnq1ot1, as compared with AH-exposed mice. Gene ontology analysis of differentially expressed genes (DEGs) indicated a coordinated decrease in many oxidative phosphorylation genes and reduced expression of vacuolar H + - and Na + /K + -ATPases; these observations were in large part confirmed in the proteomic analysis of synaptosomal fractions. Compared with AH-exposed mice, oligodendrocytes from RH-exposed mice had major changes in gene expression that suggested reduced myelin formation. In astrocytes from RH-exposed mice, DEGs indicated reduced capacity for neurotransmitters scavenging in tripartite synapses as compared with astrocytes from AH-exposed mice. In addition, in neurons and astrocytes, multiple changes in gene expression suggested increased amyloid beta (Aβ) production and stability. The snRNA-seq analysis of the cortex showed that the adaptation to RH involved different biological processes from those seen in the hypothalamus., Conclusions/interpretation: The present study provides a model of defective counterregulation in a mouse model of type 2 diabetes. It shows that repeated hypoglycaemic episodes induce multiple defects affecting all hypothalamic cell types and their interactions, indicative of impaired neuronal network signalling and dysegulated hypoglycaemia sensing, and displaying features of neurodegenerative diseases. It also shows that repeated hypoglycaemia leads to specific molecular adaptation in the hypothalamus when compared with the cortex., Data Availability: The transcriptomic dataset is available via the GEO ( http://www.ncbi.nlm.nih.gov/geo/ ), using the accession no. GSE226277. The proteomic dataset is available via the ProteomeXchange data repository ( http://www.proteomexchange.org ), using the accession no. PXD040183., (© 2023. The Author(s).)

Introduction: Diabetic kidney disease (DKD) is a common cause of chronic kidney disease with around 25-40% of patients with diabetes being affected. The course of DKD is variable, and estimated glomerular filtration rate (eGFR) and albuminuria, the currently used clinical markers, are not able to accurately predict the individual disease trajectory, in particular in early stages of the disease. The aim of this study was to assess the association of urine levels of selected protein biomarkers with the progression of DKD at an early stage of disease., Methods: We measured 22 protein biomarkers using the Mesoscale Discovery platform in 461 urine samples of the PROVALID cohort, an observational study of patients with type 2 diabetes mellitus followed at the primary health care level for a minimum of 4 years. Odds ratios (ORs) were estimated for the effect of marker values above median on fast progression using unadjusted and adjusted logistic regression models. RNA expression at the single-cell level in kidney biopsy samples obtained from a cohort of young persons with type 2 diabetes mellitus was in addition determined for markers showing significant associations with disease progression., Results: Increased urinary levels of epidermal growth factor (EGF) were linked to lower odds of fast progression (defined as annual eGFR decline greater than 2.58 mL/min per 1.73 m2) with an OR of 0.60 (95% CI: 0.46, 0.78). The association with outcome was even stronger when adjusting for a set of 14 baseline clinical parameters including age, biological sex, eGFR, body mass index, albuminuria, and HbA1c. Elevated urinary levels of fatty acid-binding protein 3 (FABP3) and vascular cell adhesion molecule 1 (VCAM1) were each significantly associated with fast progression with an OR of 1.44 (95% CI: 1.11, 1.87) and an OR of 1.41 (95% CI: 1.08, 1.83), respectively. Enriched expression of EGF and FABP3 was observed in distal convoluted tubular cells and VCAM1 in parietal epithelial cells at single-cell level from biopsies of patients with early DKD., Conclusion: In summary, we show that lower urinary levels of EGF and higher urinary levels of FABP3 and VCAM1 are significantly associated with DKD progression in early-stage disease., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Objective: Human functional genomics has proven powerful in discovering drug targets for common metabolic disorders. Through this approach, we investigated the involvement of the purinergic receptor P2RY1 in type 2 diabetes (T2D)., Methods: P2RY1 was sequenced in 9,266 participants including 4,177 patients with T2D. In vitro analyses were then performed to assess the functional effect of each variant. Expression quantitative trait loci (eQTL) analysis was performed in pancreatic islets from 103 pancreatectomized individuals. The effect of P2RY1 on glucose-stimulated insulin secretion was finally assessed in human pancreatic beta cells (EndoCβH5), and RNA sequencing was performed on these cells., Results: Sequencing P2YR1 in 9,266 participants revealed 22 rare variants, seven of which were loss-of-function according to our in vitro analyses. Carriers, except one, exhibited impaired glucose control. Our eQTL analysis of human islets identified P2RY1 variants, in a beta-cell enhancer, linked to increased P2RY1 expression and reduced T2D risk, contrasting with variants located in a silent region associated with decreased P2RY1 expression and increased T2D risk. Additionally, a P2RY1-specific agonist increased insulin secretion upon glucose stimulation, while the antagonist led to decreased insulin secretion. RNA-seq highlighted TXNIP as one of the main transcriptomic markers of insulin secretion triggered by P2RY1 agonist., Conclusion: Our findings suggest that P2RY1 inherited or acquired dysfunction increases T2D risk and that P2RY1 activation stimulates insulin secretion. Selective P2RY1 agonists, impermeable to the blood-brain barrier, could serve as potential insulin secretagogues., Competing Interests: Declaration of competing interest Authors declare that they have no competing interests., (Copyright © 2023 The Authors. Published by Elsevier GmbH.. All rights reserved.)

Surface antigenic variation is crucial for major pathogens that infect humans. To escape the immune system, they exploit various mechanisms. Understanding these mechanisms is important to better prevent and fight the deadly diseases caused. Those used by the fungus Pneumocystis jirovecii that causes life-threatening pneumonia in immunocompromised individuals remain poorly understood. Here, though this fungus is currently not cultivable, our detailed analysis of the subtelomeric sequence motifs and genes encoding surface proteins suggests that the system involves the reassortment of the repertoire of ca. 80 non-expressed genes present in each strain, from which single genes are retrieved for mutually exclusive expression. Dispersion of the new repertoires, supposedly by healthy carrier individuals, appears very efficient because identical alleles are observed in patients from different countries. Our observations reveal a unique strategy of antigenic variation. They also highlight the possible role in genome rearrangements of small imperfect mirror sequences forming DNA triplexes., (© 2023. The Author(s).)

Achieving a good outcome for a person with Psoriatic Arthritis (PsA) is made difficult by late diagnosis, heterogenous clinical disease expression and in many cases, failure to adequately suppress inflammatory disease features. Single-centre studies have certainly contributed to our understanding of disease pathogenesis, but to adequately address the major areas of unmet need, multi-partner, collaborative research programmes are now required. HIPPOCRATES is a 5-year, Innovative Medicines Initiative (IMI) programme which includes 17 European academic centres experienced in PsA research, 5 pharmaceutical industry partners, 3 small-/medium-sized industry partners and 2 patient-representative organizations. In this review, the ambitious programme of work to be undertaken by HIPPOCRATES is outlined and common approaches and challenges are identified. It is expected that, when completed, the results will ultimately allow for changes in the approaches to diagnosing, managing and treating PsA allowing for better short-term and long-term outcomes., Competing Interests: OF has received grants from AbbVie, Bristol Myers Squibb, Janssen, Eli-Lilly, Novartis, Pfizer and UCB. DS has received grants from AbbVie, Janssen, Eli-Lilly and Novartis. SK is an employee of and has stocks or stock options in Bristol Myers Squibb. LCC has received grants/research support from AbbVie, Amgen, Celgene, Eli-Lilly, Janssen, Novartis, Pfizer and UCB; worked as a paid consultant for AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli-Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer and UCB and has been paid as a speaker for AbbVie, Amgen, Biogen, Celgene, Eli-Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer and UCB. FB and MK have received grants/research support from AbbVie, Amgen, Celgene, Eli-Lilly, Janssen, Novartis, Pfizer and UCB; worked as a paid consultant for AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli-Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer and UCB and has been paid as a speaker for AbbVie, Amgen, Biogen, Celgene, Eli-Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer and UCB. AB has received grants/research support from Pfizer, Bristol Myers Squibb, Galapagos and Schiper Medicine and received speaker fees from Chugai-Roche. AV, MKl and JMS – no conflicts of interest to declare. CSG has received grants/research support from AstraZeneca, Bristol Myers Squibb, Boehringer Ingelheim Pharmaceuticals, Eli-Lilly, Istesso, Janssen, MedAnnex, MiroBio, Pfizer, UCB; worked as a consultant for AstraZeneca, Bristol Myers Squibb, Janssen, MedAnnex, MiroBio; and has been paid as a speaker for AbbVie and UCB. BBD was an employee and then a consultant of Novartis Pharma AG. CH is an employee of Novartis Pharma AG. SS has received institutional research support from Amgen (previously Celgene), Boehringer Ingelheim, Bristol Myers Squibb, Eli-Lilly, GSK, Janssen and UCB; consultancy/speaker fees from AbbVie, Amgen, AstraZeneca, Eli-Lilly, GSK, Janssen and UCB. MdW: Over the last 3 years Stichting Tools has received fees for lectures or consultancy provided by Maarten de Wit from Celgene, Eli-Lilly, Pfizer and UCB., (© The Author(s), 2023.)

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: D.Vi. is employed at Novo Nordisk A/S and holds shares in Novo Nordisk A/S. T.Sp. is employed at Novo Nordisk A/S and holds shares in Novo Nordisk A/S. T.Si. holds shares in Armata Pharmaceuticals Inc., Intellia Therapeutics Inc., Moderna Inc., and IGM Biosciences Inc. S.B. holds shares in Intomics A/S, Hoba Therapeutics Aps, Novo Nordisk A/S, Lundbeck A/S, and managing board memberships in Proscion A/S and Intomics A/S. All other authors have no conflicts of interest to declare., (Copyright: © 2023 Lundgaard et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The COVID-19 pandemic has highlighted the need for FAIR (Findable, Accessible, Interoperable, and Reusable) data more than any other scientific challenge to date. We developed a flexible, multi-level, domain-agnostic FAIRification framework, providing practical guidance to improve the FAIRness for both existing and future clinical and molecular datasets. We validated the framework in collaboration with several major public-private partnership projects, demonstrating and delivering improvements across all aspects of FAIR and across a variety of datasets and their contexts. We therefore managed to establish the reproducibility and far-reaching applicability of our approach to FAIRification tasks., (© 2023. The Author(s).)

The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an open, online resource of hands-on recipes for "FAIR doers" in the Life Sciences. Created by researchers and data managers professionals in academia, (bio)pharmaceutical companies and information service industries, the FAIR Cookbook covers the key steps in a FAIRification journey, the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges to achieve and improve data FAIRness. Part of the ELIXIR ecosystem, and recommended by funders, the FAIR Cookbook is open to contributions of new recipes., (© 2023. The Author(s).)

Background: Respiratory syncytial virus (RSV) is associated with acute respiratory infection. We sought to identify RSV variants associated with prolonged infection., Methods: Among healthy term infants we identified those with prolonged RSV infection and conducted (1) a human genome-wide association study (GWAS) to test the dependence of infection risk on host genotype, (2) a viral GWAS for association with prolonged RSV infection using RSV whole-genome sequencing, (3) an analysis of all viral public sequences, (4) an assessment of immunological responses, and (5) a summary of all major functional data. Analyses were adjusted for viral/human population structure and host factors associated with infection risk., Results: We identified p.E123K/D and p.P218T/S/L in G protein that were associated with prolonged infection (Padj = .01). We found no evidence of host genetic risk for infection. The RSV variant positions approximate sequences that could bind a putative viral receptor, heparan sulfate., Conclusions: Using analysis of both viral and host genetics we identified a novel RSV variant associated with prolonged infection in otherwise healthy infants and no evidence supporting host genetic susceptibility to infection. As the capacity of RSV for chronicity and its viral reservoir are not defined, these findings are important for understanding the impact of RSV on chronic disease and endemicity., Competing Interests: Potential conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed. Funding for this work has been supplied by the NIH and the SNSF. Funding to pay the Open Access publication charges for this article was provided by NIH. Tina Hartert; consulting fees: Sanofi Pasteur scientific advisory board RSV vaccines, participation on a data safety monitoring board: Pfizer. Larry J. Anderson; Grants or contracts (exlcuding funding for this project): CDC contract for herpes simplex antibody testing, subcontract with Sciogen on an NIH SBIR for RSV vaccines, contract with Pfizer to serologic testing studies of RSV, consulting fees: Janssen scientific advisory board RSV vaccines, ADVI scientific advisory board RSV vaccines, and Bavarian Nordic scientific advisory board, patents planned, issued or pending: RSV vaccines and Immune treatment, and RSV VLP vaccines., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression., (© 2023. The Author(s).)

Circadian rhythmicity in renal function suggests rhythmic adaptations in renal metabolism. To decipher the role of the circadian clock in renal metabolism, we studied diurnal changes in renal metabolic pathways using integrated transcriptomic, proteomic, and metabolomic analysis performed on control mice and mice with an inducible deletion of the circadian clock regulator Bmal1 in the renal tubule (cKOt). With this unique resource, we demonstrated that approximately 30% of RNAs, approximately 20% of proteins, and approximately 20% of metabolites are rhythmic in the kidneys of control mice. Several key metabolic pathways, including NAD+ biosynthesis, fatty acid transport, carnitine shuttle, and β-oxidation, displayed impairments in kidneys of cKOt mice, resulting in perturbed mitochondrial activity. Carnitine reabsorption from primary urine was one of the most affected processes with an approximately 50% reduction in plasma carnitine levels and a parallel systemic decrease in tissue carnitine content. This suggests that the circadian clock in the renal tubule controls both kidney and systemic physiology.

Spinicaudatan clam shrimps are an evolutionarily ancient lineage restricted to temporary freshwater pools. Use of classical morpho-taxonomic approaches alone have led to some issues in the taxonomy of this group, which are now being resolved through integrative taxonomy. Here, we describe two new leptestherid spiny clam shrimps Leptestheria chalukyae sp. nov. and Leptestheria gomantaki sp. nov. from peninsular India based on their unique morphological characters and distinct phylogenetic position. We also re-describe Leptestheria nobilis and present an overview of the morphological characters of all the Indian leptestherids. Most of the conventional taxonomic characters appear to overlap among all the Indian species, although the combination of occipital condyle shape and the cercopod marginal spines arrangement in combination, appear to be useful in separating leptestherid species.

At particular stages during their life cycles, fungi use multiple strategies to form specialized structures to survive unfavorable environmental conditions. These strategies encompass sporulation, as well as cell-wall melanization, multicellular tissue formation or even dimorphism. The resulting structures are not only used to disperse to other environments, but also to survive long periods of time awaiting favorable growth conditions. As a result, these specialized fungal structures are part of the microbial seed bank, which is known to influence the microbial community composition and contribute to the maintenance of diversity. Despite the importance of the microbial seed bank in the environment, methods to study the diversity of fungal structures with improved resistance only target spores dispersing in the air, omitting the high diversity of these structures in terms of morphology and environmental distribution. In this study, we applied a separation method based on cell lysis to enrich lysis-resistant fungal structures (for instance, spores, sclerotia, melanized yeast) to obtain a proxy of the composition of the fungal seed bank. This approach was first evaluated in-vitro in selected species. The results obtained showed that DNA from fungal spores and from yeast was only obtained after the application of the enrichment method, while mycelium was always lysed. After validation, we compared the diversity of the total and lysis-resistant fractions in the polyextreme environment of the Salar de Huasco, a high-altitude athalassohaline wetland in the Chilean Altiplano. Environmental samples were collected from the salt flat and from microbial mats in small surrounding ponds. Both the lake sediments and microbial mats were dominated by Ascomycota and Basidiomycota, however, the diversity and composition of each environment differed at lower taxonomic ranks. Members of the phylum Chytridiomycota were enriched in the lysis-resistant fraction, while members of the phylum Rozellomycota were never detected in this fraction. Moreover, we show that the community composition of the lysis-resistant fraction reflects the diversity of life cycles and survival strategies developed by fungi in the environment. To the best of our knowledge this is the first time that the fungal diversity is explored in the Salar de Huasco. In addition, the method presented here provides a simple and culture independent approach to assess the diversity of fungal lysis-resistant cells in the environment., (© 2023. The Author(s).)

Summary: We introduce mapache, a flexible, robust and scalable pipeline to map, quantify and impute ancient and present-day DNA in a reproducible way. Mapache is implemented in the workflow manager Snakemake and is optimized for low-space consumption, allowing to efficiently (re)map large datasets-such as reference panels and multiple extracts and libraries per sample - to one or several genomes. Mapache can easily be customized or combined with other Snakemake tools., Availability and Implementation: Mapache is freely available on GitHub (https://github.com/sneuensc/mapache). An extensive manual is provided at https://github.com/sneuensc/mapache/wiki., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2023. Published by Oxford University Press.)

The development of single-cell RNA sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive amount of biological information, the marked heterogeneity and variability between studies, and the technical challenges in processing heterogeneous datasets create major bottlenecks for the full exploitation of scRNA-seq data. We have developed IMMUcan scDB (https://immucanscdb.vital-it.ch), a fully integrated scRNA-seq database exclusively dedicated to human cancer and accessible to nonspecialists. IMMUcan scDB encompasses 144 datasets on 56 different cancer types, annotated in 50 fields containing precise clinical, technological, and biological information. A data processing pipeline was developed and organized in four steps: (i) data collection; (ii) data processing (quality control and sample integration); (iii) supervised cell annotation with a cell ontology classifier of the TME; and (iv) interface to analyze TME in a cancer type-specific or global manner. This framework was used to explore datasets across tumor locations in a gene-centric (CXCL13) and cell-centric (B cells) manner as well as to conduct meta-analysis studies such as ranking immune cell types and genes correlated to malignant transformation. This integrated, freely accessible, and user-friendly resource represents an unprecedented level of detailed annotation, offering vast possibilities for downstream exploitation of human cancer scRNA-seq data for discovery and validation studies., Significance: The IMMUcan scDB database is an accessible supportive tool to analyze and decipher tumor-associated single-cell RNA sequencing data, allowing researchers to maximally use this data to provide new insights into cancer biology., (©2022 The Authors; Published by the American Association for Cancer Research.)

Extracellular vesicles (EV) are membranous particles secreted by all cells and found in body fluids. Established EV contents include a variety of RNA species, proteins, lipids and metabolites that are considered to reflect the physiological status of their parental cells. However, to date, little is known about cell-type enriched EV cargo in complex EV mixtures, especially in urine. To test whether EV secretion from distinct human kidney cells in culture differ and can recapitulate findings in normal urine, we comprehensively analysed EV components, (particularly miRNAs, long RNAs and protein) from conditionally immortalised human kidney cell lines (podocyte, glomerular endothelial, mesangial and proximal tubular cells) and compared to EV secreted in human urine. EV from cell culture media derived from immortalised kidney cells were isolated by hydrostatic filtration dialysis (HFD) and characterised by electron microscopy (EM), nanoparticle tracking analysis (NTA) and Western blotting (WB). RNA was isolated from EV and subjected to miRNA and RNA sequencing and proteins were profiled by tandem mass tag proteomics. Representative sets of EV miRNAs, RNAs and proteins were detected in each cell type and compared to human urinary EV isolates (uEV), EV cargo database, kidney biopsy bulk RNA sequencing and proteomics, and single-cell transcriptomics. This revealed that a high proportion of the in vitro EV signatures were also found in in vivo datasets. Thus, highlighting the robustness of our in vitro model and showing that this approach enables the dissection of cell type specific EV cargo in biofluids and the potential identification of cell-type specific EV biomarkers of kidney disease., (© 2023 The Authors. Journal of Extracellular Vesicles published by Wiley Periodicals, LLC on behalf of the International Society for Extracellular Vesicles.)

Targeted DNA sequencing approaches will improve how the size of short tandem repeats is measured for diagnostic tests and preclinical studies. The expansion of these sequences causes dozens of disorders, with longer tracts generally leading to a more severe disease. Interrupted alleles are sometimes present within repeats and can alter disease manifestation. Determining repeat size mosaicism and identifying interruptions in targeted sequencing datasets remains a major challenge. This is in part because standard alignment tools are ill-suited for repetitive and unstable sequences. To address this, we have developed Repeat Detector (RD), a deterministic profile weighting algorithm for counting repeats in targeted sequencing data. We tested RD using blood-derived DNA samples from Huntington's disease and Fuchs endothelial corneal dystrophy patients sequenced using either Illumina MiSeq or Pacific Biosciences single-molecule, real-time sequencing platforms. RD was highly accurate in determining repeat sizes of 609 blood-derived samples from Huntington's disease individuals and did not require prior knowledge of the flanking sequences. Furthermore, RD can be used to identify alleles with interruptions and provide a measure of repeat instability within an individual. RD is therefore highly versatile and may find applications in the diagnosis of expanded repeat disorders and in the development of novel therapies., (© The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Candida species are the most commonly isolated opportunistic fungal pathogens in humans. Candida albicans causes most of the diagnosed infections, closely followed by Candida glabrata . C. albicans is well studied, and many genes have been shown to be important for infection and colonization of the host. It is however less clear how C. glabrata infects the host. With the help of fungal RNA enrichment, we here investigated for the first time the transcriptomic profile of C. glabrata during urinary tract infection (UTI) in mice. In the UTI model, bladders and kidneys are major target organs and therefore fungal transcriptomes were addressed in these organs. Our results showed that, next to adhesins and proteases, nitrogen metabolism and regulation play a vital role during C. glabrata UTI. Genes involved in nitrogen metabolism were upregulated and among them we show that DUR1,2 (urea amidolyase) and GAP1 (amino acid permease) were important for virulence. Furthermore, we confirmed the importance of the glyoxylate cycle in the host and identified MLS1 (malate synthase) as an important gene necessary for C. glabrata virulence. In conclusion, our study shows with the support of in vivo transcriptomics how C. glabrata adapts to host conditions.

Endosporulation is a complex morphophysiological process resulting in a more resistant cellular structure that is produced within the mother cell and is called endospore. Endosporulation evolved in the common ancestor of Firmicutes, but it is lost in descendant lineages classified as asporogenic. While Kurthia spp. is considered to comprise only asporogenic species, we show here that strain 11kri321, which was isolated from an oligotrophic geothermal reservoir, produces phase-bright spore-like structures. Phylogenomics of strain 11kri321 and other Kurthia strains reveals little similarity to genetic determinants of sporulation known from endosporulating Bacilli. However, morphological hallmarks of endosporulation were observed in two of the four Kurthia strains tested, resulting in spore-like structures (cryptospores). In contrast to classic endospores, these cryptospores did not protect against heat or UV damage and successive sub-culturing led to the loss of the cryptosporulating phenotype. Our findings imply that a cryptosporulation phenotype may have been prevalent and subsequently lost by laboratory culturing in other Firmicutes currently considered as asporogenic. Cryptosporulation might thus represent an ancestral but unstable and adaptive developmental state in Firmicutes that is under selection under harsh environmental conditions., (© 2022 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)

Background: Smoking and alcohol consumption may compromise health by way of epigenetic modifications. Epigenetic signatures of alcohol and tobacco consumption could provide insights into the reversibility of phenotypic changes incurred with differing levels of lifestyle exposures. This study describes and validates two novel epigenetic signatures of tobacco (EpiTob) and alcohol (EpiAlc) consumption and investigates their association with disease outcomes., Methods: The epigenetic signatures, EpiTob and EpiAlc, were developed using data from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) (N = 689). Epigenetic and phenotypic data available from the 1921 (N = 550) and 1936 (N = 1091) Lothian Birth Cohort (LBC) studies, and two publicly available datasets on GEO Accession (GSE50660, N = 464; and GSE110043, N = 94) were used to validate the signatures. A multivariable logistic regression model, adjusting for age and sex, was used to assess the association between self-reported tobacco or alcohol consumption and the respective epigenetic signature, as well as to estimate the association between CVD and epigenetic signatures. A Cox proportional hazard model was used to estimate the risk of mortality in association with the EpiTob and EpiAlc signatures., Results: The EpiTob signature was positively associated with self-reported tobacco consumption for current or never smokers with explained variance ranging from 0.49 (LBC1921) to 0.72 (LBC1936) (pseudo-R 2 ). In the SKIPOGH, LBC1921 and LBC1936 cohorts, the epigenetic signature for alcohol consumption explained limited variance in association with self-reported alcohol status [i.e., non-drinker, moderate drinker, and heavy drinker] (pseudo-R 2  = 0.05, 0.03 and 0.03, respectively), although this improved considerably when measuring self-reported alcohol consumption with standardized units consumed per week (SKIPOGH R 2  = 0.21; LBC1921 R 2  = 0.31; LBC1936 R 2  = 0.41). Both signatures were associated with history of CVD in SKIPOGH and LBC1936, but not in LBC1921. The EpiTob signature was associated with increased risk of all-cause and lung-cancer specific mortality in the 1936 and 1921 LBC cohorts., Conclusions: This study found the EpiTob and EpiAlc signatures to be well-correlated with self-reported exposure status and associated with long-term health outcomes. Epigenetic signatures of lifestyle exposures may reduce measurement issues and biases and could aid in risk stratification for informing early-stage targeted interventions., (© 2022. The Author(s).)

Genetic variations affect behavior and cause disease but understanding how these variants drive complex traits is still an open question. A common approach is to link the genetic variants to intermediate molecular phenotypes such as the transcriptome using RNA-sequencing (RNA-seq). Paradoxically, these variants between the samples are usually ignored at the beginning of RNA-seq analyses of many model organisms. This can skew the transcriptome estimates that are used later for downstream analyses, such as expression quantitative trait locus (eQTL) detection. Here, we assessed the impact of reference-based analysis on the transcriptome and eQTLs in a widely-used mouse genetic population: the BXD panel of recombinant inbred lines. We highlight existing reference bias in the transcriptome data analysis and propose practical solutions which combine available genetic variants, genotypes, and genome reference sequence. The use of custom BXD line references improved downstream analysis compared to classical genome reference. These insights would likely benefit genetic studies with a transcriptomic component and demonstrate that genome references need to be reassessed and improved., Competing Interests: The authors have declared that no competing interests exist.