Persistence with tamoxifen and aromatase inhibitors in Germany: a retrospective cohort study with 284,383 patients.

PURPOSE: The aim of this study was to analyze the persistence of women on tamoxifen (TAM) and aromatase inhibitors (AIs) in Germany, and to investigate possible determinants of non-persistence. METHODS: The present retrospective cohort study was based on the IQVIA longitudinal prescription database (LRx). The study included women with an initial prescription of TAM or AIs (anastrozole, letrozole, and exemestane) between January 2016 and December 2020 (index date). Kaplan-Meier analyses were performed to show the persistence for TAM and AI, using a therapy gap of 90 or 180 days, respectively. A multivariable Cox proportional hazards regression model was further used to estimate the relationship between non-persistence and drug prescription (AI versus TAM), age, and the specialty of the physician initiating therapy (gynecologist, oncologist, or general practitioner). RESULTS: Up to 5 years after the index date, only 35.1% of AI and 32.5% of TAM patients were continuing therapy when therapy discontinuation was defined as at least 90 days without therapy. Using a 180-day therapy gap, 51.9% of AI and 50.4% of TAM patients remained on therapy after 5 years. Cox regression models reveal that initial therapy with TAM (HR 1.06, 95% CI 1.04-1.07), therapy initiation by oncologists (HR 1.09, 95% CI 1.07-1.11), or general practitioners (HR 1.24, 95% CI 1.21-1.27) and age ≤ 50 (HR 1.08, 95% CI 1.06-1.10) were significantly associated with an increased risk of therapy discontinuation. CONCLUSION: Overall, the present study indicates that persistence rates are low in all age groups for both TAM and AI treatment. We found several factors (e.g., physician specialty, younger age, and type of endocrine therapy) to be associated with an increased risk for non-persistence.

Incidence of other cancer diagnoses in women with breast cancer: a retrospective cohort study with 42,248 women.

PURPOSE: The aim of the present study was to determine whether women diagnosed with breast cancer (BC) have an increased incidence of other cancers, e.g., gastric cancer, lung cancer, skin cancer, and so on, compared to healthy women without a breast cancer diagnosis. METHODS: This retrospective cohort study was based on data from the Disease Analyzer database (IQVIA) and included adult women with an initial diagnosis of BC documented in one of 1,274 general practices in Germany between January 2000 and December 2018. Women with BC were matched to women without cancer by age, index year, yearly consultation frequency, and co-diagnoses. Univariate Cox regression models were used to study the association between BC and the incidence of other cancer diagnoses. RESULTS: 21,124 women with BC and 21,124 women (mean age: 63 years) without cancer were included. Within 10 years of the index date, 14.3% of women with BC and 10.0% of women without cancer were diagnosed with cancer (p < 0.001). BC was significantly associated with the incidence of other cancer diagnoses (HR: 1.42, p < 0.001). The strongest association was observed for respiratory organ cancer (HR = 1.69, p < 0.001), followed by female genital organ cancer (HR = 1.61, p < 0.001) and cancer of lymphoid and hematopoietic tissue (HR: 1.59, p < 0.001). CONCLUSION: The results of this study show that women with BC have an increased incidence of another cancer compared to women without cancer. Therefore, it is important to pay particular attention to the development of other malignancies during follow-up in patients with BC. This should be considered especially in patients with a proven genetic mutation.

Imitating Emergencies: Generating Thermal Surveillance Fall Data Using Low-Cost Human-like Dolls.

Outdoor fall detection, in the context of accidents, such as falling from heights or in water, is a research area that has not received as much attention as other automated surveillance areas. Gathering sufficient data for developing deep-learning models for such applications has also proven to be not a straight-forward task. Normally, footage of volunteer people falling is used for providing data, but that can be a complicated and dangerous process. In this paper, we propose an application for thermal images of a low-cost rubber doll falling in a harbor, for simulating real emergencies. We achieve thermal signatures similar to a human on different parts of the doll's body. The change of these thermal signatures over time is measured, and its stability is verified. We demonstrate that, even with the size and weight differences of the doll, the produced videos of falls have a similar motion and appearance to what is expected from real people. We show that the captured thermal doll data can be used for the real-world application of pedestrian detection by running the captured data through a state-of-the-art object detector trained on real people. An average confidence score of 0.730 is achieved, compared to a confidence score of 0.761 when using footage of real people falling. The captured fall sequences using the doll can be used as a substitute to sequences of people.

Quantifying the Influence of Surface Texture and Shape on Structure from Motion 3D Reconstructions.

In general, optical methods for geometrical measurements are influenced by the surface properties of the examined object. In Structure from Motion (SfM), local variations in surface color or topography are necessary for detecting feature points for point-cloud triangulation. Thus, the level of contrast or texture is important for an accurate reconstruction. However, quantitative studies of the influence of surface texture on geometrical reconstruction are largely missing. This study tries to remedy that by investigating the influence of object texture levels on reconstruction accuracy using a set of reference artifacts. The artifacts are designed with well-defined surface geometries, and quantitative metrics are introduced to evaluate the lateral resolution, vertical geometric variation, and spatial-frequency information of the reconstructions. The influence of texture level is compared to variations in capturing range. For the SfM measurements, the ContextCapture software solution and a 50 Mpx DSLR camera are used. The findings are compared to results using calibrated optical microscopes. The results show that the proposed pipeline can be used for investigating the influence of texture on SfM reconstructions. The introduced metrics allow for a quantitative comparison of the reconstructions at varying texture levels and ranges. Both range and texture level are seen to affect the reconstructed geometries although in different ways. While an increase in range at a fixed focal length reduces the spatial resolution, an insufficient texture level causes an increased noise level and may introduce errors in the reconstruction. The artifacts are designed to be easily replicable, and by providing a step-by-step procedure of our testing and comparison methodology, we hope that other researchers will make use of the proposed testing pipeline.

Rough or Noisy? Metrics for Noise Estimation in SfM Reconstructions.

Structure from Motion (SfM) can produce highly detailed 3D reconstructions, but distinguishing real surface roughness from reconstruction noise and geometric inaccuracies has always been a difficult problem to solve. Existing SfM commercial solutions achieve noise removal by a combination of aggressive global smoothing and the reconstructed texture for smaller details, which is a subpar solution when the results are used for surface inspection. Other noise estimation and removal algorithms do not take advantage of all the additional data connected with SfM. We propose a number of geometrical and statistical metrics for noise assessment, based on both the reconstructed object and the capturing camera setup. We test the correlation of each of the metrics to the presence of noise on reconstructed surfaces and demonstrate that classical supervised learning methods, trained with these metrics can be used to distinguish between noise and roughness with an accuracy above 85%, with an additional 5-6% performance coming from the capturing setup metrics. Our proposed solution can easily be integrated into existing SfM workflows as it does not require more image data or additional sensors. Finally, as part of the testing we create an image dataset for SfM from a number of objects with varying shapes and sizes, which are available online together with ground truth annotations.

Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder.

To identify susceptibility loci for bipolar disorder, we tested 1.8 million variants in 4,387 cases and 6,209 controls and identified a region of strong association (rs10994336, P = 9.1 x 10(-9)) in ANK3 (ankyrin G). We also found further support for the previously reported CACNA1C (alpha 1C subunit of the L-type voltage-gated calcium channel; combined P = 7.0 x 10(-8), rs1006737). Our results suggest that ion channelopathies may be involved in the pathogenesis of bipolar disorder.

Identification of loci associated with schizophrenia by genome-wide association and follow-up.

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).

Support for neuregulin 1 as a susceptibility gene for bipolar disorder and schizophrenia.

BACKGROUND: There is support that Neuregulin 1 (NRG1) plays a role in susceptibility to schizophrenia but limited evidence for its involvement in bipolar disorder. We wished to investigate further the involvement of NRG1 in schizophrenia and bipolar disorder. METHODS: We used hierarchical association analysis in parent-offspring trios, 634 with schizophrenia/schizoaffective disorder (SZ/SA) and 243 with bipolar 1 disorder (BP1). The primary analysis was the markers defining the "core Icelandic haplotype" (HAP(ICE)). We undertook polymorphism discovery, additional genotyping, and also explored phenotypic associations, as a secondary analysis aimed at refining the signal. RESULTS: The initial global haplotype test yielded significant evidence for association (p = .01) with SZ/SA and BP1 (p = .004), although HAP(ICE) was not overtransmitted. The marker showing strongest evidence for association in the deCODE studies, SNP8NRG221533, was associated with SZ/SA (p(corrected) = .039) and with BP1 (p(corrected) = .039), with BP1 showing association to the opposite allele as SZ/SA. The pattern of transmission at SNP8NRG221533 was significantly different in SZ/SA than in BP1 (p = .0004). Secondary analyses of markers and phenotypes provided no additional evidence for association to SZ/SA. However, a new marker, rs7014762, was associated with an a priori defined "typical" bipolar phenotype characterized by excellent recovery between episodes and no mood incongruent features (p(corrected) = .003). CONCLUSIONS: Our data provide significant levels of support for NRG1 as a susceptibility gene for both major forms of psychosis, and this cannot be interpreted as being due to population stratification. More tentatively, they also might indicate the presence of multiple alleles that influence the psychosis phenotype.

Association study in the 5q31-32 linkage region for schizophrenia using pooled DNA genotyping.

BACKGROUND: Several linkage studies suggest that chromosome 5q31-32 might contain risk loci for schizophrenia (SZ). We wanted to identify susceptibility genes for schizophrenia within this region. METHODS: We saturated the interval between markers D5S666 and D5S436 with 90 polymorphic microsatellite markers and genotyped two sets of DNA pools consisting of 300 SZ patients of Bulgarian origin and their 600 parents. Positive associations were followed-up with SNP genotyping. RESULTS: Nominally significant evidence for association (p < 0.05) was found for seven markers (D5S0023i, IL9, RH60252, 5Q3133_33, D5S2017, D5S1481, D5S0711i) which were then individually genotyped in the trios. The predicted associations were confirmed for two of the markers: D5S2017, localised in the SPRY4-FGF1 locus (p = 0.004) and IL9, localized within the IL9 gene (p = 0.014). Fine mapping was performed using single nucleotide polymorphisms (SNPs) around D5S2017 and IL9. In each region four SNPs were chosen and individually genotyped in our full sample of 615 SZ trios. Two SNPs showed significant evidence for association: rs7715300 (p = 0.001) and rs6897690 (p = 0.032). Rs7715300 is localised between the TGFBI and SMAD5 genes and rs6897690 is within the SPRY4 gene. CONCLUSION: Our screening of 5q31-32 implicates three potential candidate genes for SZ: SMAD5, TGFBI and SPRY4.

Multiple testing in the genomics era: findings from Genetic Analysis Workshop 15, Group 15.

Recent advances in molecular technologies have resulted in the ability to screen hundreds of thousands of single nucleotide polymorphisms and tens of thousands of gene expression profiles. While these data have the potential to inform investigations into disease etiologies and advance medicine, the question of how to adequately control both type I and type II error rates remains. Genetic Analysis Workshop 15 datasets provided a unique opportunity for participants to evaluate multiple testing strategies applicable to microarray and single nucleotide polymorphism data. The Genetic Analysis Workshop 15 multiple testing and false discovery rate group (Group 15) investigated three general categories for multiple testing corrections, which are summarized in this review: statistical independence, error rate adjustment, and data reduction. We show that while each approach may have certain advantages, adequate error control is largely dependent upon the question under consideration and often requires the use of multiple analytic strategies.

Genetic and environmental influences on the relationship between peer alcohol use and own alcohol use in adolescents.

AIMS: Genetically influenced aspects of adolescent behaviour can play a role in alcohol use and peer affiliation. We explored the correlations between friends' alcohol use and adolescent own use with a genetically sensitive design. DESIGN: Genetic and environmental factors were estimated on adolescent reports of their friends' alcohol use and their own use and problem use of alcohol. The correlations between the genetic and environmental factors that influence friends' alcohol use and adolescent own alcohol use and problem use were also estimated. PARTICIPANTS: A total of 862 twin pairs aged 11-17 years sampled from the UK population-based Cardiff Study of All Wales and North-west of England Twins (CaStANET). MEASUREMENTS: Data on adolescent own alcohol use and problem use and the alcohol use of their three best friends were obtained using self-report questionnaires. FINDINGS: A significant genetic influence was found on adolescent friends' alcohol use (about 30%). Significant correlations of 0.60 and 0.70 were found between the genetic influences on friends' alcohol use and adolescents' own use and problem use of alcohol. Common environmental influences were almost completely correlated for friends' alcohol use and adolescents' own alcohol use and problem use (0.91 and 0.94). CONCLUSIONS: There is considerable overlap in the common environmental and genetic factors that contribute to the relationship between adolescents' own alcohol use and that of their friends. These findings contribute to understanding of the mechanisms by which friends' alcohol use influences adolescent drinking behaviour.

Association analysis of AKT1 and schizophrenia in a UK case control sample.

AKT1 (V-akt murine thyoma viral oncogene homolog 1) is involved in intracellular signalling pathways postulated as of aetiological importance in schizophrenia. Markers in the AKT1 gene have also recently been associated with schizophrenia in two samples of European origin and in Japanese and Iranian samples. Aiming to replicate these findings, we examined ten SNPs spanning AKT1 in a UK case-control sample (schizophrenia cases n=673, controls n=716). These included all SNPs previously reported to be associated in European, Japanese and Iranian samples, alone or in haplotypes, as well as additional markers defined by the Haploview Tagger program (pair-wise tagging, minimum r(2)=0.8, minor allele frequency=0.02). We found no association with single markers (min p=0.17). We found weak evidence for association (p=0.04) with a four marker haplotype reported as significant in the original positive European sample of Emamian et al. [Emamian, E.S., Hall, D., Birnbaum, M.J., Karayiorgou, M., Gogos, J.A., 2004. Convergent evidence for impaired AKT1-GSK3beta signaling in schizophrenia. Nat. Genet. 36, 131-137] and also an overlapping three marker haplotype (p=0.016) that had previously been reported as significant in a Japanese sample. Nominal p-values for these haplotypes did not survive correction for multiple testing. Our study provides at best weak support for the hypothesis that AKT1 is a susceptibility gene for schizophrenia. Examination of our own data and those of other groups leads us to conclude that overall, the evidence for association of AKT1 as a susceptibility gene for schizophrenia is weakly positive, but not yet convincing.

Three-dimensional slice cultures from murine fetal gut for investigations of the enteric nervous system.

Three-dimensional intestinal cultures offer new possibilities for the examination of growth potential, analysis of time specific gene expression, and spatial cellular arrangement of enteric nervous system in an organotypical environment. We present an easy to produce in vitro model of the enteric nervous system for analysis and manipulation of cellular differentiation processes. Slice cultures of murine fetal colon were cultured on membrane inserts for up to 2 weeks without loss of autonomous contractility. After slice preparation, cultured tissue reorganized within the first days in vitro. Afterward, the culture possessed more than 35 cell layers, including high prismatic epithelial cells, smooth muscle cells, glial cells, and neurons analyzed by immunohistochemistry. The contraction frequency of intestinal slice culture could be modulated by the neurotransmitter serotonin and the sodium channel blocker tetrodotoxin. Coculture experiments with cultured neurospheres isolated from enhanced green fluorescent protein (eGFP) transgenic mice demonstrated that differentiating eGFP-positive neurons were integrated into the intestinal tissue culture. This slice culture model of enteric nervous system proved to be useful for studying cell-cell interactions, cellular signaling, and cell differentiation processes in a three-dimensional cell arrangement.

Large-scale linkage analysis of 1302 affected relative pairs with rheumatoid arthritis.

Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and clinical phenotypes as covariates within a linkage analysis framework to search for rheumatoid arthritis susceptibility loci. The raw genotypes of 1302 affected relative pairs were combined from four large family-based samples (North American Rheumatoid Arthritis Consortium, United Kingdom, European Consortium on Rheumatoid Arthritis Families, and Canada). The familiality of the clinical phenotypes was assessed. The affected relative pairs were subjected to autosomal multipoint affected relative-pair linkage analysis. Covariates were included in the linkage analysis to take account of heterogeneity within the sample. Evidence of familiality was observed with age at onset (p << 0.001) and rheumatoid factor (RF) IgM (p << 0.001), but not definite erosions (p = 0.21). Genome-wide significant evidence for linkage was observed on chromosome 6. Genome-wide suggestive evidence for linkage was observed on chromosomes 13 and 20 when conditioning on age at onset, chromosome 15 conditional on gender, and chromosome 19 conditional on RF IgM after allowing for multiple testing of covariates.

Combining linkage data sets for meta-analysis and mega-analysis: the GAW15 rheumatoid arthritis data set.

We have used the genome-wide marker genotypes from Genetic Analysis Workshop 15 Problem 2 to explore joint evidence for genetic linkage to rheumatoid arthritis across several samples. The data consisted of four high-density genome scans on samples selected for rheumatoid arthritis. We cleaned the data, removed intermarker linkage disequilibrium, and assembled the samples onto a common genetic map using genome sequence positions as a reference for map interpolation. The individual studies were combined first at the genotype level (mega-analysis) prior to a multipoint linkage analysis on the combined sample, and second using the genome scan meta-analysis method after linkage analysis of each sample. The two approaches were compared, and give strong support to the HLA locus on chromosome 6 as a susceptibility locus. Other regions of interest include loci on chromosomes 11, 2, and 12.

Analyses of single marker and pairwise effects of candidate loci for rheumatoid arthritis using logistic regression and random forests.

Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid Arthritis Consortium (NARAC) candidate gene data set (Problem 2), analyzing 463 independent patients and 855 controls. Specifically, our work examined the correspondence between logistic regression (LR) analysis of single-locus and pairwise interaction effects, and random forest (RF) single and joint importance measures. For this comparison, we selected small but stable RFs (500 trees), which showed strong correlations (r~0.98) between their importance measures and those by RFs grown on 5000 trees. Both RF importance measures captured most of the LR single-locus and pairwise interaction effects, while joint importance measures also corresponded to full LR models containing main and interaction effects. We furthermore showed that RF measures were particularly sensitive to data imputation. The most consistent pairwise effect on rheumatoid arthritis was found between two markers within MAP3K7IP2/SUMO4 on 6q25.1, although LR and RFs assigned different significance levels.Within a hypothetical two-stage design, pairwise LR analysis of all markers with significant RF single importance would have reduced the number of possible combinations in our small data set by 61%, whereas joint importance measures would have been less efficient for marker pair reduction. This suggests that RF single importance measures, which are able to detect a wide range of interaction effects and are computationally very efficient, might be exploited as pre-screening tool for larger association studies. Follow-up analysis, such as by LR, is required since RFs do not indicate high-risk genotype combinations.

Convergent evidence that oligodendrocyte lineage transcription factor 2 (OLIG2) and interacting genes influence susceptibility to schizophrenia.

Abnormal oligodendrocyte function has been postulated as a primary etiological event in schizophrenia. Oligodendrocyte lineage transcription factor 2 (OLIG2) encodes a transcription factor central to oligodendrocyte development. Analysis of OLIG2 in a case-control sample (n = approximately 1,400) in the U.K. revealed several SNPs to be associated with schizophrenia (minimum P = 0.0001, gene-wide P = 0.0009). To obtain independent support for this association, we sought evidence for genetic interaction between OLIG2 and three genes of relevance to oligodendrocyte function for which we have reported evidence for association with schizophrenia: CNP, NRG1, and ERBB4. We found interaction effects on disease risk between OLIG2 and CNP (minimum P = 0.0001, corrected P = 0.008) for interaction with ERBB4 (minimum P = 0.002, corrected P = 0.04) but no evidence for interaction with NRG1. To investigate the biological plausibility of the interactions, we sought correlations between the expression of the genes. The results were similar to those of the genetic interaction analysis. OLIG2 expression significantly correlated in cerebral cortex with CNP (P < 10(-7)) and ERBB4 (P = 0.002, corrected P = 0.038) but not NRG1. In mouse striatum, Olig2 and Cnp expression also was correlated, and linkage analysis for trans-effects on gene expression suggests that each locus regulates the other's expression. Our data provide strong convergent evidence that variation in OLIG2 confers susceptibility to schizophrenia alone and as part of a network of genes implicated in oligodendrocyte function.

Pooled DNA genotyping on Affymetrix SNP genotyping arrays.

BACKGROUND: Genotyping technology has advanced such that genome-wide association studies of complex diseases based upon dense marker maps are now technically feasible. However, the cost of such projects remains high. Pooled DNA genotyping offers the possibility of applying the same technologies at a fraction of the cost, and there is some evidence that certain ultra-high throughput platforms also perform with an acceptable accuracy. However, thus far, this conclusion is based upon published data concerning only a small number of SNPs. RESULTS: In the current study we prepared DNA pools from the parents and from the offspring of 30 parent-child trios that have been extensively genotyped by the HapMap project. We analysed the two pools with Affymetrix 10 K Xba 142 2.0 Arrays. The availability of the HapMap data allowed us to validate the performance of 6843 SNPs for which we had both complete individual and pooled genotyping data. Pooled analyses averaged over 5-6 microarrays resulted in highly reproducible results. Moreover, the accuracy of estimating differences in allele frequency between pools using this ultra-high throughput system was comparable with previous reports of pooling based upon lower throughput platforms, with an average error for the predicted allelic frequencies differences between the two pools of 1.37% and with 95% of SNPs showing an error of < 3.2%. CONCLUSION: Genotyping thousands of SNPs with DNA pooling using Affymetrix microarrays produces highly accurate results and can be used for genome-wide association studies.

Bipolar disorder and polymorphisms in the dysbindin gene (DTNBP1).

BACKGROUND: Several studies support the dysbindin (dystrobrevin binding protein 1) gene (DTNBP1) as a susceptibility gene for schizophrenia. We previously reported that variation at a specific 3-locus haplotype influences susceptibility to schizophrenia in a large United Kingdom (UK) Caucasian case-control sample. METHODS: Using similar methodology to our schizophrenia study, we have investigated this same 3-locus haplotype in a large, well-characterized bipolar sample (726 Caucasian UK DSM-IV bipolar I patients; 1407 ethnically matched controls). RESULTS: No significant differences were found in the distribution of the 3-locus haplotype in the full sample. Within the subset of bipolar I cases with predominantly psychotic episodes of mood disturbance (n = 133) we found nominally significant support for association at this haploptype (p < .042) and at SNP rs2619538 (p = .003), with a pattern of findings similar to that in our schizophrenia sample. This finding was not significant after correction for multiple testing. CONCLUSIONS: Our data suggest that variation at the polymorphisms examined does not make a major contribution to susceptibility to bipolar disorder in general. They are consistent with the possibility that DTNBP1 influences susceptibility to a subset of bipolar disorder cases with psychosis. However, our subset sample is small and the hypothesis requires testing in independent, adequately powered samples.