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Previous spatio-temporal COVID-19 prediction models have focused on the prediction of subsequent number of cases, and have shown varying accuracy and lack of high geographical resolution. We aimed to predict trends in COVID-19 test positivity, an important marker for planning local testing capacity and accessibility. We included a full year of information (June 29, 2020–July 4, 2021) with both direct and indirect indicators of transmission, e.g. mobility data, number of calls to the national healthcare advice line and vaccination coverage from Uppsala County, Sweden, as potential predictors. We developed four models for a 1-week-window, based on gradient boosting (GB), random forest (RF), autoregressive integrated moving average (ARIMA) and integrated nested laplace approximations (INLA). Three of the models (GB, RF and INLA) outperformed the naïve baseline model after data from a full pandemic wave became available and demonstrated moderate accuracy. An ensemble model of these three models slightly improved the average root mean square error to 0.039 compared to 0.040 for GB, RF and INLA, 0.055 for ARIMA and 0.046 for the naïve model. Our findings indicate that the collection of a wide variety of data can contribute to spatio-temporal predictions of COVID-19 test positivity. [ABSTRACT FROM AUTHOR]

Breast cancer is a major cause of morbidity and mortality in women and its metastatic spread is the principal reason behind the fatal outcome. Metastasis-related research of breast cancer is however underdeveloped when compared with the abundant literature on primary tumors. We applied an unexplored approach comparing at high resolution the genomic profiles of primary tumors and synchronous axillary lymph node metastases from 13 patients with breast cancer. Overall, primary tumors displayed 20% higher number of aberrations than metastases. In all but two patients, we detected in total 157 statistically significant differences between primary lesions and matched metastases. We further observed differences that can be linked to metastatic disease and there was also an overlapping pattern of changes between different patients. Many of the differences described here have been previously linked to poor patient survival, suggesting that this is a viable approach toward finding biomarkers for disease progression and definition of new targets useful for development of anticancer drugs. Frequent genetic differences between primary tumors and metastases in breast cancer also question, at least to some extent, the role of primary tumors as a surrogate subject of study for the systemic disease. [ABSTRACT FROM AUTHOR]

We analyzed 137 kb covering human neurofibromatosis 2 (NF2) tumor suppressor locus and orthologous loci from baboon, mouse, rat, and pufferfish Takifugurubripes. A predominant feature of human-rodent conservation is a very similar distribution of conserved islands, regarding length, position, and degree of identity. By use of a threshold of 75% identity over ≥100 bp of gap-free alignment, comparisons of human-mouse sequences resulted in 3.58% for extra-exonic conservation, which can be compared to 4.5% of exonic sequence content within the human locus. We identified a duplication of neurofibromin 2 in pufferfish, which resulted in two putative proteins with 74% and 76% identity to the human protein. One distinct island (called inter 1), conserved between all analyzed species, was located between promoters of the NIPSNAP1 and NF2 genes. Inter1 might represent a novel regulatory element, important for the function of this locus. The high level of intronic conservation in the NF2 locus suggests that a number of unknown regulatory elements might exist within this gene. These elements could be affected by disease-causing mutations in NF2 patients and NF2-associated tumors. Alternatively, this conservation might be explained by presence of not yet characterized transcriptional unit(s) within this locus. [ABSTRACT FROM AUTHOR]

Neurofibromatosis type 2 (NF2) is an autosomal dominant cancer syndrome caused by the biallelic inactivation of the neurofibromin 2 tumor suppressor gene (NF2). Current molecular diagnostic methods for NF2 involve the detection of point mutations and/or microdeletions across the 100-kb locus from 22q12. Despite the fact that NF2 gene inactivating deletions occur in 25–30% of NF2 patients, the available approaches for high-resolution and high-throughput detection of deletions are underdeveloped. This need for improved methodology for gene copy number analysis is especially apparent when compared to a variety of methods available for accurate detection of point mutations. The microarray-based form of comparative genomic hybridization has been previously applied in the high-resolution analysis of gene copy number variation across large genomic regions. In this study we apply a PCR-based, strictly sequence-defined, repeat-free approach for the preparation of a diagnostic microarray for the detection of disease-causing deletions in the NF2 gene. The methodology is based on the preselection of target DNA by excluding redundant sequence within the NF2 locus using bioinformatics. This approach allows a significant increase in the resolution of deletion detection. The current average resolution of analysis across the NF2 locus is 23 kb. Therefore this NF2 gene-specific microarray is the first high-resolution tool for detection of diagnostically significant gene copy number aberrations. This microarray should now be applied in the analysis of an extensive series of NF2 patients, and hence we would like to call for such samples. [ABSTRACT FROM AUTHOR]

The original version of this Article contained an error in the spelling of the author Jule Müller, which was incorrectly given as Julia Müller. Additionally, in Fig. 4a, the blue-red colour scale for fold change in ageing/disease regulation included a blue stripe in place of a red stripe at the right-hand end of the scale. These errors have been corrected in both the PDF and HTML versions of the Article. [ABSTRACT FROM AUTHOR]

Disease epidemiology during ageing shows a transition from cancer to degenerative chronic disorders as dominant contributors to mortality in the old. Nevertheless, it has remained unclear to what extent molecular signatures of ageing reflect this phenomenon. Here we report on the identification of a conserved transcriptomic signature of ageing based on gene expression data from four vertebrate species across four tissues. We find that ageing-associated transcriptomic changes follow trajectories similar to the transcriptional alterations observed in degenerative ageing diseases but are in opposite direction to the transcriptomic alterations observed in cancer. We confirm the existence of a similar antagonism on the genomic level, where a majority of shared risk alleles which increase the risk of cancer decrease the risk of chronic degenerative disorders and vice versa. These results reveal a fundamental trade-off between cancer and degenerative ageing diseases that sheds light on the pronounced shift in their epidemiology during ageing. Ageing is associated with a pronounced shift in mortality from cancer to degenerative diseases. Here, the authors show that in concordance with this shift, conserved transcriptional alterations during ageing across four vertebrates align with degenerative diseases but are opposite to those in cancer. [ABSTRACT FROM AUTHOR]