Estrogen receptor mutations and splice variants determined in liquid biopsies from metastatic breast cancer patients

Mutations and splice variants in the estrogen receptor (ER) gene, ESR1, may yield endocrine resistance in metastatic breast cancer (MBC) patients. These putative endocrine resistance markers are likely to emerge during treatment, and therefore, its detection in liquid biopsies, such as circulating tumor cells (CTCs) and cell-free DNA (cfDNA), is of great interest. This research aimed to determine whether ESR1 mutations and splice variants occur more frequently in CTCs of MBC patients progressing on endocrine treatment. In addition, the presence of ESR1 mutations was evaluated in matched cfDNA and compared to CTCs. CellSearch-enriched CTC fractions (≥5/7.5 mL) of two MBC cohorts were evaluated, namely (a) patients starting first-line endocrine therapy (n = 43, baseline cohort) and (b) patients progressing on any line of endocrine therapy (n = 40, progressing cohort). ESR1 hotspot mutations (D538G and Y537S/N/C) were evaluated in CTC-enriched DNA using digital PCR and compared with matched cfDNA (n = 18 baseline cohort; n = 26 progressing cohort). Expression of ESR1 full-length and 4 of its splice variants ((increment)5, (increment)7, 36 kDa, and 46 kDa) was evaluated in CTC-enriched mRNA. It was observed that in the CTCs, the ESR1 mutations were not enriched in the progressing cohort (8%), when compared with the baseline cohort (5%) (P = 0.66). In the cfDNA, however, ESR1 mutations were more prevalent in the progressing cohort (42%) than in the baseline cohort (11%) (P = 0.04). Three of the same mutations were observed in both CTCs and cfDNA, 1 mutation in CTCs only, and 11 in cfDNA only. Only the (increment)5 ESR1 splice variant was CTC-specific expressed, but was not enriched in the progressing cohort. In conclusion, sensitivity for detecting ESR1 mutations in CTC-enriched fractions was lower than for cfDNA. ESR1 mutations detected in cfDNA, rarely present at the start of first-line endocrine therapy, were enriched at progression, strongly suggesting a role in conferring endocrine resistance in MBC

An 8-gene mRNA expression profile in circulating tumor cells predicts response to aromatase inhibitors in metastatic breast cancer patients

Background: Molecular characterization of circulating tumor cells (CTC) is promising for personalized medicine. We aimed to identify a CTC gene expression profile predicting outcome to first-line aromatase inhibitors in metastatic breast cancer (MBC) patients. Methods: CTCs were isolated from 78 MBC patients before treatment start. mRNA expression levels of 96 genes were measured by quantitative reverse transcriptase polymerase chain reaction. After applying predefined exclusion criteria based on lack of sufficient RNA quality and/or quantity, the data from 45 patients were used to construct a gene expression profile to predict poor responding patients, defined as disease progression or death <9 months, by a leave-one-out cross validation. Results: Of the 45 patients, 19 were clinically classified as poor responders. To identify them, the 75 % most variable genes were used to select genes differentially expressed between good and poor responders. An 8-gene CTC predictor was significantly associated with outcome (Hazard Ratio [HR] 4.40, 95 % Confidence Interval [CI]: 2.17-8.92, P < 0.001). This predictor identified poor responding patients with a sensitivity of 63 % and a positive predictive value of 75 %, while good responding patients were correctly predicted in 85 % of the cases. In multivariate Cox regression analysis, including CTC count at baseline, the 8-gene CTC predictor was the only factor independently associated with outcome (HR 4.59 [95 % CI: 2.11-9.56], P < 0.001). This 8-gene signature was not associated with outcome in a group of 71 MBC patients treated with systemic treatments other than AI. Conclusions: An 8-gene CTC predictor was identified which discriminates good and poor outcome to first-line aromatase inhibitors in MBC patients. Although results need to be validated, this study underscores the potential of molecular characterization of CTCs

Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles

Background: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. Results: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. Conclusions: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression

Diagnostic yield and accuracy of CT angiography, MR angiography, and digital subtraction angiography for detection of macrovascular causes of intracerebral haemorrhage: Prospective, multicentre cohort study

Study question What are the diagnostic yield and accuracy of early computed tomography (CT) angiography followed by magnetic resonance imaging/angiography (MRI/MRA) and digital subtraction angiography (DSA) in patients with non-traumatic intracerebral haemorrhage? Methods This prospective diagnostic study enrolled 298 adults (18-70 years) treated in 22 hospitals in the Netherlands over six years. CT angiography was performed within seven days of haemorrhage. If the result was negative, MRI/MRA was performed four to eight weeks later. DSA was performed when the CT angiography or MRI/MRA results were inconclusive or negative. The main outcome was a macrovascular cause, including arteriovenous malformation, aneurysm, dural arteriovenous fistula, and cavernoma. Three blinded neuroradiologists independently evaluated the images for macrovascular causes of haemorrhage. The reference standard was the best available evidence from all findings during one year's follow-up. Study answer and limitations A macrovascular cause was identified in 69 patients (23%). 291 patients (98%) underwent CT angiography; 214 with a negative result underwent additional MRI/MRA and 97 with a negative result for both CT angiography and MRI/MRA underwent DSA. Early CT angiography detected 51 macrovascular causes (yield 17%, 95% confidence interval 13% to 22%). CT angiography with MRI/MRA identified two additional macrovascular causes (18%, 14% to 23%) and these modalities combined with DSA another 15 (23%, 18% to 28%). This last extensive strategy failed to detect a cavernoma, which was identified on MRI during follow-up (reference strategy). The positive predictive value of CT angiography was 72% (60% to 82%), of additional MRI/MRA was 35% (14% to 62%), and of additional DSA was 100% (75% to 100%). None of the patients experienced complications with CT angiography or MRI/MRA; 0.6% of patients who underwent DSA experienced p

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers

Altres ajuts: European Alzheimer DNA BioBank, EADB; EU Joint Programme, Neurodegenerative Disease Research (JPND); Neurodegeneration research program of Amsterdam Neuroscience; Stichting Alzheimer Nederland; Stichting VUmc fonds; Stichting Dioraphte; JPco-fuND FP-829-029 (ZonMW projectnumber 733051061); Dutch Federation of University Medical Centers; Dutch Government (from 2007-2011); JPND EADB grant (German Federal Ministry of Education and Research (BMBF) grant: 01ED1619A); German Research Foundation (DFG RA 1971/6-1, RA1971/7-1, RA 1971/8-1); Grifols SA; Fundación bancaria 'La Caixa'; Fundació ACE; CIBERNED; Fondo Europeo de Desarrollo Regional (FEDER-'Una manera de hacer Europa'); NIH (P30AG066444, P01AG003991); Alzheimer Research Foundation (SAO-FRA), The Research Foundation Flanders (FWO), and the University of Antwerp Research Fund. FK is supported by a BOF DOCPRO fellowship of the University of Antwerp Research Fund; Siemens Healthineers; Valdecilla Biobank (PT17/0015/0019); Academy of Finland (338182); German Center for Neurodegenerative Diseases (DZNE); German Federal Ministry of Education and Research (BMBF 01G10102, 01GI0420, 01GI0422, 01GI0423, 01GI0429, 01GI0431, 01GI0433, 04GI0434, 01GI0711); ZonMW (#73305095007); Health~Holland, Topsector Life Sciences & Health (PPP-allowance #LSHM20106); Hersenstichting; Edwin Bouw Fonds; Gieskes-Strijbisfonds; NWO Gravitation program BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (NWO: 024.004.012); Swedish Alzheimer Foundation (AF-939988, AF-930582, AF-646061, AF-741361); Dementia Foundation (2020-04-13, 2021-04-17); Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALF 716681); Swedish Research Council (11267, 825-2012-5041, 2013-8717, 2015-02830, 2017-00639, 2019-01096); Swedish Research Council for Health, Working Life and Welfare (2001-2646, 2001-2835, 2001-2849, 2003-0234, 2004-0150, 2005-0762, 2006-0020, 2008-1229, 2008-1210, 2012-1138, 2004-0145, 2006-0596, 2008-1111, 2010-0870, 2013-1202, 2013-2300, 2013-2496); Swedish Brain Power, Hjärnfonden, Sweden (FO2016-0214, FO2018-0214, FO2019-0163); Alzheimer's Association Zenith Award (ZEN-01-3151); Alzheimer's Association Stephanie B. Overstreet Scholars (IIRG-00-2159); Alzheimer's Association (IIRG-03-6168, IIRG-09-131338); Bank of Sweden Tercentenary Foundation; Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALFGBG-81392, ALFGBG-771071); Swedish Alzheimer Foundation (AF-842471, AF-737641, AF-939825); Swedish Research Council (2019-02075); Swedish Research Council (2016-01590); BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (024.004.012); Swedish Research Council (2018-02532); Swedish State Support for Clinical Research (ALFGBG-720931); Alzheimer Drug Discovery Foundation (ADDF), USA (201809-2016862); UK Dementia Research Institute at UCL; Swedish Research Council (#2017-00915); Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615); Swedish Alzheimer Foundation (#AF-742881); Hjärnfonden, Sweden (#FO2017-0243); Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986); National Institute of Health (NIH), USA, (#1R01AG068398-01); Alzheimer's Association 2021 Zenith Award (ZEN-21-848495); National Institutes of Health (R01AG044546, R01AG064877, RF1AG053303, R01AG058501, U01AG058922, RF1AG058501, R01AG064614); Chuck Zuckerberg Initiative (CZI).Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding: Bill & Melinda Gates Foundation

Genome-wide identification of directed gene networks using large-scale population genomics data

Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. Here, we develop a method for the large-scale inference of gene–gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). Analysis of genotype and whole-blood RNA-sequencing data from 3072 individuals identified 49 genes as drivers of downstream transcriptional changes (Wald P < 7 × 10−10), among which transcription factors were overrepresented (Fisher’s P = 3.3 × 10−7). Our analysis suggests new gene functions and targets, including for SENP7 (zinc-finger genes involved in retroviral repression) and BCL2A1 (target genes possibly involved in auditory dysfunction). Our work highlights the utility of population genomics data in deriving directed gene expression networks. A resource of trans-effects for all 6600 genes with a genetic instrument can be explored individually using a web-based browser

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk

Port cities as hubs of diversity and inclusivity: The case of Rotterdam

Port cities are a particular type of territory and are often long-standing examples of resilience, bringing opportunities, wealth, and innovation to their nations and their citizens. They have developed at the crossroads of international trade and commerce and the intersection of sea and land. Flows of people through trade and migration have played a key role in their spatial, social and cultural development. Their strong local identities share legacies of diversity and cosmopolitanism, but also of colonialism and segregation. The Qingjing Mosque in Quanzhou, Fujian speaks of the exchange between Arabia and China along the maritime silk road. Hanseatic cities stand as an example of far-flung networks with districts for foreign traders—think of the German merchants who established Bryggen, the German dock, in Bergen, now a UNESCO world heritage site.History & ComplexityDesign Conceptualization and CommunicationUrban Desig