Clonal expansion and epigenetic reprogramming following deletion or amplification of mutant IDH1.

IDH1 mutation is the earliest genetic alteration in low-grade gliomas (LGGs), but its role in tumor recurrence is unclear. Mutant IDH1 drives overproduction of the oncometabolite d-2-hydroxyglutarate (2HG) and a CpG island (CGI) hypermethylation phenotype (G-CIMP). To investigate the role of mutant IDH1 at recurrence, we performed a longitudinal analysis of 50 IDH1 mutant LGGs. We discovered six cases with copy number alterations (CNAs) at the IDH1 locus at recurrence. Deletion or amplification of IDH1 was followed by clonal expansion and recurrence at a higher grade. Successful cultures derived from IDH1 mutant, but not IDH1 wild type, gliomas systematically deleted IDH1 in vitro and in vivo, further suggestive of selection against the heterozygous mutant state as tumors progress. Tumors and cultures with IDH1 CNA had decreased 2HG, maintenance of G-CIMP, and DNA methylation reprogramming outside CGI. Thus, while IDH1 mutation initiates gliomagenesis, in some patients mutant IDH1 and 2HG are not required for later clonal expansions.

Improved accuracy assessment for 3D genome reconstructions.

BACKGROUND: Three dimensional (3D) genome spatial organization is critical for numerous cellular functions, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Genome conformation had been difficult to elucidate but the advent chromatin conformation capture assays, notably Hi-C, has transformed understanding of chromatin architecture and yielded numerous biological insights. Although most of these findings have flowed from analysis of proximity data produced by these assays, added value in generating 3D reconstructions has been demonstrated, deriving, in part, from superposing genomic features on the reconstruction. However, advantages of 3D structure-based analyses are clearly conditional on the accuracy of the attendant reconstructions, which is difficult to assess. Proponents of competing reconstruction algorithms have evaluated their accuracy by recourse to simulation of toy structures and/or limited fluorescence in situ hybridization (FISH) imaging that features a handful of low resolution probes. Accordingly, new methods of reconstruction accuracy assessment are needed. RESULTS: Here we utilize two recently devised assays to develop methodology for assessing 3D reconstruction accuracy. Multiplex FISH increases the number of probes by an order of magnitude and hence the number of inter-probe distances by two orders, providing sufficient information for structure-level evaluation via mean-squared deviations (MSD). Crucially, underscoring multiplex FISH applications are large numbers of coordinate-system aligned replicates that provide the basis for a referent distribution for MSD statistics. Using this system we show that reconstructions based on Hi-C data for IMR90 cells are accurate for some chromosomes but not others. The second new assay, genome architecture mapping, utilizes large numbers of thin cryosections to obtain a measure of proximity. We exploit the planarity of the cryosections - not used in inferring proximity - to obtain measures of reconstruction accuracy, with referents provided via resampling. Application to mouse embryonic stem cells shows reconstruction accuracies that vary by chromosome. CONCLUSIONS: We have developed methods for assessing the accuracy of 3D genome reconstructions that exploit features of recently advanced multiplex FISH and genome architecture mapping assays. These approaches can help overcome the absence of gold standards for making such assessments which are important in view of the considerable uncertainties surrounding 3D genome reconstruction.

Validation of GEMCaP as a DNA Based Biomarker to Predict Prostate Cancer Recurrence after Radical Prostatectomy.

PURPOSE: We aimed to validate GEMCaP (Genomic Evaluators of Metastatic Cancer of the Prostate) as a novel copy number signature predictive of prostate cancer recurrence. MATERIALS AND METHODS: We randomly selected patients who underwent radical prostatectomy at Cleveland Clinic or University of Rochester from 2000 to 2005. DNA isolated from the cancer region was extracted and subjected to high resolution array comparative genomic hybridization. A high GEMCaP score was defined as 20% or greater of genomic loci showing copy number gain or loss in a given tumor. Cox regression was used to evaluate associations between the GEMCaP score and the risk of biochemical recurrence. RESULTS: We report results in 140 patients. Overall 38% of patients experienced recurrence with a median time to recurrence of 45 months. Based on the CAPRA-S (Cancer of the Prostate Risk Assessment Post-Surgical) score 39% of the patients were at low risk, 42% were at intermediate risk and 19% were at high risk. The GEMCaP score was high (20% or greater) in 31% of the cohort. A high GEMCaP score was associated with a higher risk of biochemical recurrence (HR 2.69, 95% CI 1.51-4.77) and it remained associated after adjusting for CAPRA-S score and age (HR 1.94, 95% CI 1.06-3.56). The C-index of GEMCaP alone was 0.64, which improved when combined with the CAPRA-S score and patient age (C-index = 0.75). CONCLUSIONS: A high GEMCaP score was associated with biochemical recurrence in 2 external cohorts. This remained true after adjusting for clinical and pathological factors. The GEMCaP biomarker could be an efficient and effective clinical risk assessment tool to identify patients with prostate cancer for early adjuvant therapy.

Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions.

The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome conformation capture) data; however, corresponding assessments for continuous functional genomic data (e.g. chromatin immunoprecipitation-sequencing (ChIP-seq) peak height) are lacking. Here, we demonstrate that applying bump hunting via the patient rule induction method (PRIM) to ChIP-seq data superposed on a Saccharomyces cerevisiae 3D genome reconstruction can discover 'functional 3D hotspots', regions in 3-space for which the mean ChIP-seq peak height is significantly elevated. For the transcription factor Swi6, the top hotspot by P-value contains MSB2 and ERG11 - known Swi6 target genes on different chromosomes. We verify this finding in a number of ways. First, this top hotspot is relatively stable under PRIM across parameter settings. Second, this hotspot is among the top hotspots by mean outcome identified by an alternative algorithm, k-Nearest Neighbor (k-NN) regression. Third, the distance between MSB2 and ERG11 is smaller than expected (by resampling) in two other 3D reconstructions generated via different normalization and reconstruction algorithms. This analytic approach can discover functional 3D hotspots and potentially reveal novel regulatory interactions.

DNA copy number analysis of fresh and formalin-fixed specimens by shallow whole-genome sequencing with identification and exclusion of problematic regions in the genome assembly.

Detection of DNA copy number aberrations by shallow whole-genome sequencing (WGS) faces many challenges, including lack of completion and errors in the human reference genome, repetitive sequences, polymorphisms, variable sample quality, and biases in the sequencing procedures. Formalin-fixed paraffin-embedded (FFPE) archival material, the analysis of which is important for studies of cancer, presents particular analytical difficulties due to degradation of the DNA and frequent lack of matched reference samples. We present a robust, cost-effective WGS method for DNA copy number analysis that addresses these challenges more successfully than currently available procedures. In practice, very useful profiles can be obtained with ∼0.1× genome coverage. We improve on previous methods by first implementing a combined correction for sequence mappability and GC content, and second, by applying this procedure to sequence data from the 1000 Genomes Project in order to develop a blacklist of problematic genome regions. A small subset of these blacklisted regions was previously identified by ENCODE, but the vast majority are novel unappreciated problematic regions. Our procedures are implemented in a pipeline called QDNAseq. We have analyzed over 1000 samples, most of which were obtained from the fixed tissue archives of more than 25 institutions. We demonstrate that for most samples our sequencing and analysis procedures yield genome profiles with noise levels near the statistical limit imposed by read counting. The described procedures also provide better correction of artifacts introduced by low DNA quality than prior approaches and better copy number data than high-resolution microarrays at a substantially lower cost.

Pollutant Concentrations and Toxic Effects on the Red Alga Ceramium tenuicorne of Sediments from Natural Harbors and Small Boat Harbors on the West Coast of Sweden.

This investigation set out to analyze the toxicity of surface sediments in a number of natural harbors and small boat harbors on the west coast of Sweden. This was done with the growth inhibition method with Ceramium tenuicorne. Also, concentrations of copper (Cu), lead (Pb), zinc (Zn), irgarol, organotin compounds, and polycyclic aromatic hydrocarbons (PAHs) in the sediments were analyzed. The small boat harbors were heavily polluted by Cu, Zn, butyltins, and PAHs, and to a lesser extent by Pb. The Cu, Pb, Zn, and butyltins probably originated from their past and/or present use in antifouling paints, whereas the PAHs probably had multiple sources, including boat motor exhausts. The measured toxicity of the sediment was generally related to their Cu, Zn, and butyltin content, although other toxic substances than those analyzed here probably contributed to the toxicity in some of the harbors. The natural harbor sediments contained less pollutants and were less toxic than the small boat harbor sediments. Nevertheless, our data indicate that the boating pressure today may be high enough to produce toxic effects even in natural harbors in pristine areas. The strongest relationship between toxicity and the major pollutants was obtained when the sediment toxicity was expressed as gram wet weight per liter compared with gram dry weight per liter and gram total organic carbon per liter. Hence, for pollutants that can be elutriated with natural sea water, sediment toxicity expressed as gram wet weight per liter appears preferable.

Reconstruction of 3D genome architecture via a two-stage algorithm.

BACKGROUND: The three-dimensional (3D) configuration of chromosomes within the eukaryote nucleus is an important factor for several cellular functions, including gene expression regulation, and has also been linked with cancer-causing translocation events. While visualization of such architecture remains limited to low resolutions, the ability to infer structures at increasing resolutions has been enabled by recently-devised chromosome conformation capture techniques. In particular, when coupled with next generation sequencing, such methods yield an inventory of genome-wide chromatin contacts or interactions. Various algorithms have been advanced to operate on such contact data to produce reconstructed 3D configurations. Studies have shown that these reconstructions can provide added value over raw interaction data with respect to downstream biological insights. However, only limited, low-resolution reconstructions have been realized for mammals due to computational bottlenecks. RESULTS: Here we propose a two-stage algorithm to partially overcome these computational barriers. The central idea is to initially utilize existing reconstruction techniques on an individual chromosome basis, using intra-chromosomal contacts, and then to relatively position these chromosome-level reconstructions using inter-chromosomal contacts. This two-stage strategy represents a natural approach in view of the within- versus between- chromosome distribution of contacts. It can increase resolution ≈ 20 fold for mouse and human. After describing the algorithm we present 3D architectures for mouse embryonic stem cells and human lymphoblastoid cells. We evaluate the impact of several factors on reconstruction reproducibility and explore a variety of sampling schemes. We further analyze replicate data at differing resolutions obtained from recently devised in situ Hi-C assays. In all instances we demonstrate insensitivity of the whole-genome 3D reconstruction obtained by the two-stage algorithm to the sampling strategy used. CONCLUSIONS: Our two-stage algorithm has the potential to significantly increase the resolution of 3D genome reconstructions. The improvements are such that we can progress from 1 Mb resolution to 100 kb resolution, notable since this latter value has been identified as critical to inferring topological domains in analyses performed on the contact (rather than 3D) level.

Subtype and pathway specific responses to anticancer compounds in breast cancer.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.

CalMaTe: a method and software to improve allele-specific copy number of SNP arrays for downstream segmentation.

SUMMARY: CalMaTe calibrates preprocessed allele-specific copy number estimates (ASCNs) from DNA microarrays by controlling for single-nucleotide polymorphism-specific allelic crosstalk. The resulting ASCNs are on average more accurate, which increases the power of segmentation methods for detecting changes between copy number states in tumor studies including copy neutral loss of heterozygosity. CalMaTe applies to any ASCNs regardless of preprocessing method and microarray technology, e.g. Affymetrix and Illumina. AVAILABILITY: The method is available on CRAN (http://cran.r-project.org/) in the open-source R package calmate, which also includes an add-on to the Aroma Project framework (http://www.aroma-project.org/).

Querying genomic databases: refining the connectivity map.

The advent of high-throughput biotechnologies, which can efficiently measure gene expression on a global basis, has led to the creation and population of correspondingly rich databases and compendia. Such repositories have the potential to add enormous scientific value beyond that provided by individual studies which, due largely to cost considerations, are typified by small sample sizes. Accordingly, substantial effort has been invested in devising analysis schemes for utilizing gene-expression repositories. Here, we focus on one such scheme, the Connectivity Map (cmap), that was developed with the express purpose of identifying drugs with putative efficacy against a given disease, where the disease in question is characterized by a (differential) gene-expression signature. Initial claims surrounding cmap intimated that such tools might lead to new, previously unanticipated applications of existing drugs. However, further application suggests that its primary utility is in connecting a disease condition whose biology is largely unknown to a drug whose mechanisms of action are well understood, making cmap a tool for enhancing biological knowledge.The success of the Connectivity Map is belied by its simplicity. The aforementioned signature serves as an unordered query which is applied to a customized database of (differential) gene-expression experiments designed to elicit response to a wide range of drugs, across of spectrum of concentrations, durations, and cell lines. Such application is effected by computing a per experiment score that measures "closeness" between the signature and the experiment. Top-scoring experiments, and the attendant drug(s), are then deemed relevant to the disease underlying the query. Inference supporting such elicitations is pursued via re-sampling. In this paper, we revisit two key aspects of the Connectivity Map implementation. Firstly, we develop new approaches to measuring closeness for the common scenario wherein the query constitutes an ordered list. These involve using metrics proposed for analyzing partially ranked data, these being of interest in their own right and not widely used. Secondly, we advance an alternate inferential approach based on generating empirical null distributions that exploit the scope, and capture dependencies, embodied by the database. Using these refinements we undertake a comprehensive re-evaluation of Connectivity Map findings that, in general terms, reveal that accommodating ordered queries is less critical than the mode of inference.

Characterization of pig skin microbiome and appraisal as an in vivo subcutaneous injection model.

Pig skin is commonly used in the medical industry as an injection model due to its compelling physiological affinity to human skin. However, the pig neck skin microflora remains largely uncharacterized, which may have undesirable implications for the translatability of results to humans. This study aimed to characterize pig neck skin microbiome with direct comparison with human skin microflora at emblematic injection sites to appraise its suitability as an injection model. Ten minipigs were sampled with tape strips and swabs and analysed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry and 16S/ITS high throughput sequencing and confocal laser scanning microscopy. Results were directly compared with previous investigations of human injection sites. Pig skin was dominated by phyla 94.8% Firmicutes, 3% Proteobacteria, and 2.2% Actinobacteria. Staphylococcus spp. prevailed (44.4%) at the genus level with S. capitis and S. chromogenes present in all samples. Pig skin revealed populations in the 104 colony-forming units (CFU)/cm2 range with 3% identified as Gram-negative and increased alpha diversity (compared with 102 CFU/cm2 and 10% in humans). While notable taxonomical differences on species levels were seen, pig skin encompassed 97.1% of genera found in human samples. The increased population and variation found support the pig neck as an imperfect but fidelitous subcutaneous injection model that can adequately challenge devices from a microbial standpoint.

Profiling the Somatic Mutational Landscape of Breast Tumors from Hispanic/Latina Women Reveals Conserved and Unique Characteristics.

Somatic mutational profiling is increasingly being used to identify potential targets for breast cancer. However, limited tumor-sequencing data from Hispanic/Latinas (H/L) are available to guide treatment. To address this gap, we performed whole-exome sequencing (WES) and RNA sequencing on 146 tumors and WES of matched germline DNA from 140 H/L women in California. Tumor intrinsic subtype, somatic mutations, copy-number alterations, and expression profiles of the tumors were characterized and compared with data from tumors of non-Hispanic White (White) women in The Cancer Genome Atlas (TCGA). Eight genes were significantly mutated in the H/L tumors including PIK3CA, TP53, GATA3, MAP3K1, CDH1, CBFB, PTEN, and RUNX1; the prevalence of mutations in these genes was similar to that observed in White women in TCGA. Four previously reported Catalogue of Somatic Mutations in Cancer (COSMIC) mutation signatures (1, 2, 3, 13) were found in the H/L dataset, along with signature 16 that has not been previously reported in other breast cancer datasets. Recurrent amplifications were observed in breast cancer drivers including MYC, FGFR1, CCND1, and ERBB2, as well as a recurrent amplification in 17q11.2 associated with high KIAA0100 gene expression that has been implicated in breast cancer aggressiveness. In conclusion, this study identified a higher prevalence of COSMIC signature 16 and a recurrent copy-number amplification affecting expression of KIAA0100 in breast tumors from H/L compared with White women. These results highlight the necessity of studying underrepresented populations. SIGNIFICANCE: Comprehensive characterization of genomic and transcriptomic alterations in breast tumors from Hispanic/Latina patients reveals distinct genetic alterations and signatures, demonstrating the importance of inclusive studies to ensure equitable care for patients. See related commentary by Schmit et al., p. 2443.

Parent-specific copy number in paired tumor-normal studies using circular binary segmentation.

MOTIVATION: High-throughput techniques facilitate the simultaneous measurement of DNA copy number at hundreds of thousands of sites on a genome. Older techniques allow measurement only of total copy number, the sum of the copy number contributions from the two parental chromosomes. Newer single nucleotide polymorphism (SNP) techniques can in addition enable quantifying parent-specific copy number (PSCN). The raw data from such experiments are two-dimensional, but are unphased. Consequently, inference based on them necessitates development of new analytic methods. METHODS: We have adapted and enhanced the circular binary segmentation (CBS) algorithm for this purpose with focus on paired test and reference samples. The essence of paired parent-specific CBS (Paired PSCBS) is to utilize the original CBS algorithm to identify regions of equal total copy number and then to further segment these regions where there have been changes in PSCN. For the final set of regions, calls are made of equal parental copy number and loss of heterozygosity (LOH). PSCN estimates are computed both before and after calling. RESULTS: The methodology is evaluated by simulation and on glioblastoma data. In the simulation, PSCBS compares favorably to established methods. On the glioblastoma data, PSCBS identifies interesting genomic regions, such as copy-neutral LOH. AVAILABILITY: The Paired PSCBS method is implemented in an open-source R package named PSCBS, available on CRAN (http://cran.r-project.org/).

Influence of hypodermic needle dimensions on subcutaneous injection delivery--a pig study of injection deposition evaluated by CT scanning, histology, and backflow.

BACKGROUND: Thinner and shorter needles for subcutaneous administration are continuously developed. Previous studies have shown that a thinner needle causes fewer occurrences of painful needle insertions and that a shorter needle decreases the occurrence of painful intramuscular injections. However, little is known about local drug delivery in relation to needle length and thickness. This study aimed to compare deposition depth and backflow from three hypodermic needles of 3 mm 34G (0.19 mm), 5 mm 32G (0.23 mm), and 8 mm 30G (0.30 mm) in length and thickness. METHODS: Ex vivo experiments were carried out on pigs, in neck tissue comparable to human skin at typical injection sites. Six pigs were included and a total of 72 randomized injections were given, i.e. 24 subcutaneous injections given with each needle type. Accordingly, 400 µL was injected including 70% NovoRapid(®) (Novo Nordisk A/S, Bagsvµrd, Denmark) and 30% Xenetix(®) (Guerbet, Villepinte, France) contrast including 1 mg/mL Alcian blue. Surgical biopsies of injection sites were sampled and computer topographic (CT)-scanned in 3D to assess deposition and local distribution. Biopsies were prepared and stained to evaluate deposition in comparison to the CT-scanning findings. The backflow of each injection was collected with filter paper. The blue stains of filter paper were digitized and volume estimated by software calculation vs. control staining. RESULTS: CT-scanning (n = 57) and histology (n = 10) showed that, regardless of injection depth, the bulk of the injection was in the subcutaneous tissue and did not propagate from subcutis into dermis. With the 8 mm 30G needle all injections apart from one intramuscular injection were located in the subcutaneous layer. The volume depositions peaked in 4-5 mm depth for the 3 mm 34G needle, in 5-6 mm depth for the 5 mm 32G needle, and in 9-10 mm depth for the 8 mm 30G needle. In general, injection depositions evaluated by histology and CT-scans compared well for the individual biopsies. The amount of backflow (n = 69) from the 3 mm 34G needle was smaller (P < 0.05) as compared to the 5 mm 32G and the 8 mm 30G needles. Analysis showed a correlation between backflow and the needle's outer dimension with the needle diameter being the pivotal parameter. Furthermore, CT-scanning and histology confirmed that local propagation of the injection and final distribution followed a route of less mechanical resistance as determined by connective tissue barriers preset in the site of injection. CONCLUSION: Needles as short as 3 mm efficiently delivered injections into the subcutaneous target. The amount of backflow was smaller with thinner needles. Local distribution was variable and determined by mechanical barriers preset in the tissue. CT-scans and histology were concordant.

Correlation in Dose-Response to Rapid- and Long-Acting Insulin for People with Type 1 Diabetes.

In diabetes, it can become necessary to switch between pump- and pen-based insulin treatment. This switch involves a translation between rapid- and long-acting insulin analogues. In standard-of-care translation algorithms, a unit-to-unit conversion is applied. However, this simplification may not fit all individuals. In this paper, we investigate the correlation between dose-response to rapid- and long-acting insulin in the same individual, and compare the correlation across individuals. As a measure of dose-response, we estimate the insulin sensitivity in clinical data from 25 subjects with type 1 diabetes. For parameter estimation, we use maximum likelihood with a continuous-discrete extended Kalman filter and Bergman's minimal model. The results show a weak correlation between insulin sensitivity to rapid- and long-acting insulin across individuals. On this sparse data set, the analysis suggests that the standardized unit-to-unit translation between insulin analogues may not benefit all subjects.

Injection site microflora in persons with diabetes: why needle reuse is not associated with increased infections?

Needle reuse is a common practice and primary cause of customer compliance issues such as pain, bruising, clogging, injection site reactions (ISR), and associated lipodystrophy. This study aimed to characterize skin microflora at injection sites and establish microbial contamination of used pen injectors and needles. The second objective was to evaluate the risk of infections during typical and repeated subcutaneous injections. 50 participants with diabetes and 50 controls (n = 100) were sampled through tape strips and skin swabs on the abdomen and thigh for skin microflora. Used pen injectors and needles were collected after in-home use and from the hospital after drug administration by health care professionals (HCPs). Samples were analyzed by conventional culture, matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF), mass spectrometry (MS), confocal laser scanning microscopy (CLSM), and 16S/ITS high throughput sequencing (HTS). A mathematical model simulated the risk of needle contamination during injections. Injection site populations were in 102 cells/cm2 order, with increased viable bacteria and anaerobic bacteria on the skin in persons with diabetes (p = 0.05). Interpersonal variation dominated other factors such as sex or location. A higher prevalence of Staphylococcus aureus on abdominal skin was found in persons with diabetes than control skin (p ≤ 0.05). Most needles and cartridges (95% and 86%) contained no biological signal. The location of the device collection (hospital vs home-use) and use regimen did not affect contamination. CLSM revealed scarcely populated skin microflora scattered in aggregates, diplo, or single cells. Our mathematical model demonstrated that penetrating bacteria colonies during subcutaneous injection is unlikely. These findings clarify the lack of documented skin infections from subcutaneous insulin injections in research. Furthermore, these results can motivate the innovation and development of durable, reusable injection systems with pharmacoeconomic value and a simplified and enhanced user experience for patients.

The Diabetes teleMonitoring of patients in insulin Therapy (DiaMonT) trial: study protocol for a randomized controlled trial.

BACKGROUND: The effect of telemedicine solutions in diabetes remains inconclusive. However, telemedicine studies have shown a positive trend in regards to glycemic control. The telemedicine interventions that facilitate adjustment of medication seems to improve glycemic control more effectively. Hence, it is recommended that future telemedicine studies for patients with diabetes include patient-specific suggestions for changes in medicine. Hence, the aim of the trial is to explore the effect of telemonitoring in patients with type 2 diabetes (T2D) on insulin therapy. METHODS: The trial is an open-label randomized controlled trial with a trial period of 3 months conducted in two sites in Denmark. Patients with T2D on insulin therapy will be randomized (1:1) to a telemonitoring group (intervention) or a usual care group (control). The telemonitoring group will use a continuous glucose monitor (CGM), an insulin pen, an activity tracker, and smartphone applications throughout the trial. Hospital staff will monitor the telemonitoring group and contact the subjects by telephone repeatedly throughout the trial period. The usual care group will use a blinded CGM the first and last 20 days of the trial and will use a blinded insulin pen for the entire period. The primary endpoint will be changed from baseline in CGM time in range (3.9-10.0 mmol/L) 3 months after randomization. Secondary endpoints include change from baseline in glycated hemoglobin (HbA1c), total daily dose, time above range, and time below range 3 months after randomization. Exploratory endpoints include health-related quality of life, diabetes-related quality of life, etc. DISCUSSION: The DiaMonT trial will test a telemonitoring setup including various devices. Such a setup may be criticized, because it is impossible to determine which element(s) add to the potential effect. However, it is not possible and counterproductive to test the elements individually, since it is the full telemedicine setup that is being evaluated. The DiaMonT trial is the first Danish trial to explore the effect of telemonitoring on patients on insulin therapy. Thus, the DiaMonT trial has the potential to form the basis for the implementation of telemedicine for patients with T2D in Denmark. TRIAL REGISTRATION: ClinicalTrials.gov NCT04981808. Registered on 8 June 2021.

ACNE: a summarization method to estimate allele-specific copy numbers for Affymetrix SNP arrays.

MOTIVATION: Current algorithms for estimating DNA copy numbers (CNs) borrow concepts from gene expression analysis methods. However, single nucleotide polymorphism (SNP) arrays have special characteristics that, if taken into account, can improve the overall performance. For example, cross hybridization between alleles occurs in SNP probe pairs. In addition, most of the current CN methods are focused on total CNs, while it has been shown that allele-specific CNs are of paramount importance for some studies. Therefore, we have developed a summarization method that estimates high-quality allele-specific CNs. RESULTS: The proposed method estimates the allele-specific DNA CNs for all Affymetrix SNP arrays dealing directly with the cross hybridization between probes within SNP probesets. This algorithm outperforms (or at least it performs as well as) other state-of-the-art algorithms for computing DNA CNs. It better discerns an aberration from a normal state and it also gives more precise allele-specific CNs. AVAILABILITY: The method is available in the open-source R package ACNE, which also includes an add on to the aroma.affymetrix framework (http://www.aroma-project.org/).

Machine Learning-Based Adherence Detection of Type 2 Diabetes Patients on Once-Daily Basal Insulin Injections.

BACKGROUND: Lack of treatment adherence can lead to life-threatening health complications for people with type 2 diabetes (T2D). Recent improvements and availability in continuous glucose monitoring (CGM) technology have enabled various possibilities to monitor diabetes treatment. Detection of missed once-daily basal insulin injections can be used to provide feedback to patients, thus improving their diabetes management. In this study, we explore how machine learning (ML) based on CGM data can be used for detecting adherence to once-daily basal insulin injections. METHODS: In-silico CGM data were generated to simulate a cohort of T2D patients on once-daily insulin injection (Tresiba®). Deep learning methods within ML based on automatic feature extraction including convolutional neural networks were explored and compared with simple feature-engineered ML classification models for adherence detection. It was further investigated whether fused expert-dependent and automatically learned features could improve performance, resulting in a comparison of six different detection models. Adherence was detected throughout each day with an increasing amount of CGM data available. RESULTS: The adherence detection accuracy improved as more CGM data became available on the day of classification. The three classification models based on expert-engineered features obtained mean accuracies of 78.6%, 78.2%, and 78.3%. The classification model based purely on learned features obtained a mean accuracy of 79.7%. The two classification models fusing expert-engineered and learned features obtained mean accuracies of 79.7% and 79.8%. All the mentioned results were obtained 16 hours after time of injection. CONCLUSION: The results suggest that adherence detection based on CGM data is feasible. Even though our study based on in-silico data indicates only slightly improved performance of more complex models, the question remains whether advanced models would outperform the simple in a real-world setting. Thus, future studies on adherence monitoring using real CGM data are relevant.

Early Glycemic Control Assessment Based on Consensus CGM Metrics.

Continuous glucose monitoring (CGM) has revolutionized the world of diabetes and transformed the approach to diabetes care. In this context, an expert panel has reached consensus on clinical targets for CGM data interpretation based on eight CGM metrics. At least 70% of 14 consecutive CGM days (referred to as a period) are recommended to assess glycemic control based on the metrics. In clinical practice less CGM data may be available. Therefore, the primary aim of this study is to explore the ability to recover the consensus metrics utilizing less than 14 days of CGM data (intra-period). As a secondary aim, we investigate the recovery considering two consecutive periods (inter-period). The analyses are based on real-world CGM data from 484 diabetes users (4726 periods) acquired from the Cornerstones4Care® Powered by Glooko app. Using up to 14 accumulated days, the consensus metrics are calculated for each user and period, and compared to the fully 14 accumulated intra- and inter-period days. Relatively low deviations were observed for time in range (TIR) and average based metrics when using less than 14 days, however, we observed large deviations in metrics characterizing infrequent events such as time below range (TBR). Furthermore, the consensus metrics obtained in two consecutive 14 day periods have clear discrepancies (inter-period). Recovering consensus metrics using less than 14 days might still be valuable in terms of interpreting CGM data in certain clinical contexts. However, caution should be taken if treatment decisions would be made with less than 14 days of data on critical metrics such as TBR, since the metrics characterizing infrequent events deviate substantially when less data are available. Substantial deviation is also seen when comparing across two consecutive periods, which means that care should be taken not to over-generalize consensus metric based glycemic control conclusions from one period to subsequent periods.