Enacting a Grand Challenge for Business and Society: Theorizing Issue Maturation in the Media-Based Public Discourse on COVID-19 in Three National Contexts.

While today it is universally acknowledged that COVID-19 has generated immense challenges for businesses and societies worldwide, public perceptions varied significantly at the time of the pandemic's initial appearance, even among democratic societies with comparable media systems. The growing scholarship on grand societal challenges in management and organization studies, however, tends to neglect the initial social construction of issues as complex, uncertain, evaluative, and widespread. We address this shortcoming by exploring the initial communicative enactment of COVID-19 in the media-based public discourse in Switzerland, Germany, and the United Kingdom. By applying a social problem work lens, we identify three mechanisms that explain the maturation of COVID-19 into a grand challenge, further showing how these are contextually dependent on differences in discourse quality. We add to research on grand challenges, issue maturation, and framing dynamics by theorizing how issues become constructed and acknowledged as grand challenges in the first place.

Glomerular transcriptomics predicts long term outcome and identifies therapeutic strategies for patients with assumed benign IgA nephropathy.

Some patients diagnosed with benign IgA nephropathy (IgAN) develop a progressive clinical course, not predictable by known clinical or histopathological parameters. To assess if gene expression can differentiate between progressors and non-progressors with assumed benign IgAN, we tested microdissected glomeruli from archival kidney biopsy sections from adult patients with stable clinical remission (21 non-progressors) or from 15 patients that had undergone clinical progression within a 25-year time frame. Based on 1 240 differentially expressed genes from patients with suitable sequencing results, we identified eight IgAN progressor and nine non-progressor genes using a two-component classifier. These genes, including APOL5 and ZXDC, predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity on average 21.6 years before progressive disease was clinically documented. APOL lipoproteins are associated with inflammation, autophagy and kidney disease while ZXDC is a zinc-finger transcription factor modulating adaptive immunity. Ten genes from our transcriptomics data overlapped with an external genome wide association study dataset, although the gene set enrichment test was not statistically significant. We also identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan (dual antagonist of the endothelin type A receptor and the angiotensin II type 1 receptor) currently investigated for IgAN treatment. Two validation cohorts were used for substantiating key results, one by immunohistochemistry and the other by nCounter technology. Thus, glomerular mRNA sequencing from diagnostic kidney biopsies from patients with assumed benign IgAN can differentiate between future progressors and non-progressors at the time of diagnosis.

Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance.

BACKGROUND: Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome. RESULTS: We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data. CONCLUSIONS: The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.

The Quartet Data Portal: integration of community-wide resources for multiomics quality control.

The Quartet Data Portal facilitates community access to well-characterized reference materials, reference datasets, and related resources established based on a family of four individuals with identical twins from the Quartet Project. Users can request DNA, RNA, protein, and metabolite reference materials, as well as datasets generated across omics, platforms, labs, protocols, and batches. Reproducible analysis tools allow for objective performance assessment of user-submitted data, while interactive visualization tools support rapid exploration of reference datasets. A closed-loop "distribution-collection-evaluation-integration" workflow enables updates and integration of community-contributed multiomics data. Ultimately, this portal helps promote the advancement of reference datasets and multiomics quality control.

The effect of the zero-field splitting in light-induced pulsed dipolar electron paramagnetic resonance (EPR) spectroscopy.

Laser-induced magnetic dipole (LaserIMD) spectroscopy and light-induced double electron-electron resonance (LiDEER) spectroscopy are important techniques in the emerging field of light-induced pulsed dipolar electron paramagnetic resonance (EPR) spectroscopy (light-induced PDS). These techniques use the photoexcitation of a chromophore to the triplet state and measure its dipolar coupling to a neighboring electron spin, which allows the determination of distance restraints. To date, LaserIMD and LiDEER have been analyzed with software tools that were developed for a pair of two S=1/2 spins and that neglected the zero-field splitting (ZFS) of the excited triplet. Here, we explore the limits of this assumption and show that the ZFS can have a significant effect on the shape of the dipolar trace. For a detailed understanding of the effect of the ZFS, a theoretical description for LaserIMD and LiDEER is derived, taking into account the non-secular terms of the ZFS. Simulations based on this model show that the effect of the ZFS is not that pronounced in LiDEER for experimentally relevant conditions. However, the ZFS leads to an additional decay in the dipolar trace in LaserIMD. This decay is not that pronounced in Q-band but can be quite noticeable for lower magnetic field strengths in X-band. Experimentally recorded LiDEER and LaserIMD data confirm these findings. It is shown that ignoring the ZFS in the data analysis of LaserIMD traces can lead to errors in the obtained modulation depths and background decays. In X-band, it is additionally possible that the obtained distance distribution is plagued by long distance artifacts.

Transcriptomic analysis reveals partial epithelial-mesenchymal transition and inflammation as common pathogenic mechanisms in hypertensive nephrosclerosis and Type 2 diabetic nephropathy.

Hypertensive nephrosclerosis (HN) and Type 2 diabetic nephropathy (T2DN) are the leading causes of chronic kidney disease (CKD). To explore shared pathogenetic mechanisms, we analyzed transcriptomes of kidney biopsies from patients with HN or T2DN. Total RNA was extracted from 10 µm whole kidney sections from patients with HN, T2DN, and normal controls (Ctrl) (n = 6 for each group) and processed for RNA sequencing. Differentially expressed (log2 fold change >1, adjusted p < 0.05) genes (DEG) and molecular pathways were analyzed, and selected results were validated by immunohistochemistry (IHC). ELISA on serum samples was performed on a related cohort consisting of patients with biopsy-proven HN (n = 13) and DN (n = 9), and a normal control group (n = 14). Cluster analysis on RNA sequencing data separated diseased and normal tissues. RNA sequencing revealed that 88% (341 out of 384) of DEG in HN were also altered in T2DN, while gene set enrichment analysis (GSEA) showed that over 90% of affected molecular pathways, including those related to inflammation, immune response, and cell-cycle regulation, were similarly impacted in both HN and T2DN samples. The increased expression of genes tied to interleukin signaling and lymphocyte activation was more pronounced in HN, while genes associated with extracellular matrix organization were more evident in T2DN. Both HN and T2DN tissues exhibited significant upregulation of genes connected with inflammatory responses, T-cell activity, and partial epithelial to mesenchymal transition (p-EMT). Immunohistochemistry (IHC) further confirmed T-cell (CD4+ and CD8+ ) infiltration in the diseased tissues. Additionally, IHC revealed heightened AXL protein expression, a key regulator of inflammation and p-EMT, in both HN and T2DN, while serum analysis indicated elevated soluble AXL levels in patients with both conditions. These findings underline the shared molecular mechanisms between HN and T2DN, hinting at the potential for common therapeutic strategies targeting both diseases.

Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling.

Certified RNA reference materials are indispensable for assessing the reliability of RNA sequencing to detect intrinsically small biological differences in clinical settings, such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multi-omics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two samples, providing cross-platform and cross-laboratory 'ground truth'. Investigation of the intrinsically subtle biological differences among the Quartet samples enables sensitive assessment of cross-batch integration of transcriptomic measurements at the ratio level. The Quartet RNA reference materials, combined with the ratio-based reference datasets, can serve as unique resources for assessing and improving the quality of transcriptomic data in clinical and biological settings.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials.

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Glomerular proteomic profiling of kidney biopsies with hypertensive nephropathy reveals a signature of disease progression.

Hypertensive nephropathy (HN) requires a kidney biopsy as diagnostic gold-standard but histological findings are unspecific and specific prognostic markers are missing. We aimed at identifying candidate prognostic markers based on glomerular protein signatures. We studied adult patients (n = 17) with eGFR >30 ml/min/1.73m2 and proteinuria <3 g/d from the Norwegian Kidney Biopsy Registry, including subjects non progressing (NP, n = 9), or progressing (P, n = 8) to end-stage renal disease (ESRD) within an average follow-up of 22 years. Glomerular cross-sections from archival kidney biopsy sections were microdissected and processed for protein extraction. Proteomic analyses were performed using Q-exactive HF mass spectrometer and relative glomerular protein abundances were compared between P and NP patients. Immunohistochemistry (IHC) was used to validate selected data. Amongst 1870 quality filtered proteins, 58 were differentially expressed in P and NP patients' glomeruli, with absolute fold changes (FC) ≥1.5, p ≤ 0.05. Supervised classifier analysis (K nearest neighbor) identified a set of five proteins, including Gamma-butyrobetaine dioxygenase (BBOX1, O75936) and Cadherin 16 (CDH16, O75309), overexpressed in P, and Eosinophil peroxidase (EPX, P11678), DnaJ homolog subfamily B member 1 (DNAJB1, P25685) and Alpha-1-syntrophin (SNTA1, Q13424), overexpressed in NP glomeruli, correctly classifying 16/17 kidney biopsy samples. Geneset Enrichment Analysis (GSEA), showed that metabolic pathways were generally enriched in P, and structural cell pathways in NP. Pathway analysis identified Epithelial Adherens Junction Signaling as most affected canonical pathway. IHC analysis confirmed overexpression of BBOX1 and Cadherin 16 in glomeruli from P patients. In conclusion, glomerular proteomic profiling can be used to discriminate P from NP HN patients.

Increasing the Modulation Depth of GdIII-Based Pulsed Dipolar EPR Spectroscopy (PDS) with Porphyrin-GdIII Laser-Induced Magnetic Dipole Spectroscopy.

Distance determination with pulsed EPR has become an important technique for the structural investigation of biomacromolecules, with double electron-electron resonance spectroscopy (DEER) as the most important method. GdIII-based spin labels are one of the most frequently used spin labels for DEER owing to their stability against reduction, high magnetic moment, and absence of orientation selection. A disadvantage of GdIII-GdIII DEER is the low modulation depth due to the broad EPR spectrum of GdIII. Here, we introduce laser-induced magnetic dipole spectroscopy (LaserIMD) with a spin pair consisting of GdIII(PymiMTA) and a photoexcited porphyrin as an alternative technique. We show that the excited state of the porphyrin is not disturbed by the presence of the GdIII complex and that herewith modulation depths of almost 40% are possible. This is significantly higher than the value of 7.2% that was achieved with GdIII-GdIII DEER.

Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report.

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.

A multiomics disease progression signature of low-risk ccRCC.

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Identification of ccRCC likely to progress, despite an apparent low risk at the time of surgery, represents a key clinical issue. From a cohort of adult ccRCC patients (n = 443), we selected low-risk tumors progressing within a 5-years average follow-up (progressors: P, n = 8) and non-progressing (NP) tumors (n = 16). Transcriptome sequencing, miRNA sequencing and proteomics were performed on tissues obtained at surgery. We identified 151 proteins, 1167 mRNAs and 63 miRNAs differentially expressed in P compared to NP low-risk tumors. Pathway analysis demonstrated overrepresentation of proteins related to "LXR/RXR and FXR/RXR Activation", "Acute Phase Response Signaling" in NP compared to P samples. Integrating mRNA, miRNA and proteomic data, we developed a 10-component classifier including two proteins, three genes and five miRNAs, effectively differentiating P and NP ccRCC and capturing underlying biological differences, potentially useful to identify "low-risk" patients requiring closer surveillance and treatment adjustments. Key results were validated by immunohistochemistry, qPCR and data from publicly available databases. Our work suggests that LXR, FXR and macrophage activation pathways could be critically involved in the inhibition of the progression of low-risk ccRCC. Furthermore, a 10-component classifier could support an early identification of apparently low-risk ccRCC patients.

Consensus guidelines for the validation of qRT-PCR assays in clinical research by the CardioRNA consortium.

Despite promising findings, quantitative PCR (qPCR)-based tests for RNA quantification have experienced serious limitations in their clinical application. The noticeable lack of technical standardization remains a huge obstacle in the translation of qPCR-based tests. The incorporation of qPCR-based tests into the clinic will benefit from guidelines for clinical research assay validation. This will ultimately impact the clinical management of the patient, including diagnosis, prognosis, prediction, monitoring of the therapeutic response, and evaluation of toxicity. However, clear assay validation protocols for biomarker investigation in clinical trials using molecular assays are currently lacking. Here, we will focus on the necessary steps, including sample acquisition, processing and storage, RNA purification, target selection, assay design, and experimental design, that need to be taken toward the appropriate validation of qRT-PCR assays in clinical research. These recommendations can fill the gap between research use only (RUO) and in vitro diagnostics (IVD). Our contribution provides a tool for basic and clinical research for the development of validated assays in the intermediate steps of biomarker research. These guidelines are based on the current understanding and consensus within the EU-CardioRNA COST Action consortium (www.cardiorna.eu). Their applicability encompasses all clinical areas.

Assessing reproducibility of inherited variants detected with short-read whole genome sequencing.

BACKGROUND: Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. RESULTS: To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. CONCLUSIONS: Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.

AGAP2-AS1 as a prognostic biomarker in low-risk clear cell renal cell carcinoma patients with progressing disease.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer and one of the most common cancers. While survival for localized ccRCC is good, the survival of metastatic disease is not, and thirty percent of patients with ccRCC develop metastases during follow-up. Although current scoring methods accurately identify patients at low progression risk, a small subgroup of those patients still experience metastasis. We therefore aimed to identify ccRCC progression biomarkers in "low-risk" patients who were potentially eligible for adjuvant treatments or more intensive follow-up. METHODS: We assembled a cohort of ccRCC patients (n = 443) and identified all "low-risk" patients who later developed progressing tumors (n = 8). Subsequently, we performed genome-wide expression profiling from formalin-fixed samples obtained at initial surgery from these "low-risk" patients and 16 matched patients not progressing to recurrence with metastasis. The patients were matched for Leibovich sore, creatinine, age, sex, tumor size and tumor stage. Key results were confirmed with qPCR and external data from The Cancer Genome Atlas. RESULTS: Principal component analysis indicated that systematic transcriptomic differences were already detectable at the time of initial surgery. One thousand one hundred sixty-seven genes, mainly associated with cancer and immune-related pathways, were differentially expressed between progressors and nonprogressors. A search for a classifier revealed that overexpression of AGAP2-AS1, an antisense long noncoding RNA, correctly classified 23 of 24 samples, years (4.5 years average) in advance of the discovery of metastasis and without requiring larger gene panels. Subsequently, we confirmed AGAP2-AS1 gene overexpression by qPCR in the same samples (p < 0.05). Additionally, in external data from The Cancer Genome Atlas, overexpression of AGAP2-AS1 is correlated with overall unfavorable survival outcome in ccRCC, irrespective of other prognostic predictors (p = 2.44E-7). CONCLUSION: AGAP2-AS1 may represent a novel biomarker identifying high-risk ccRCC patients currently classified as "low risk" at the time of surgery.

The SEQC2 epigenomics quality control (EpiQC) study.

BACKGROUND: Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group. RESULTS: Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms. CONCLUSIONS: The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.

Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.