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Non-coding RNAs have emerged as crucial regulators of gene expression and cell fate decisions. However, their expression patterns and regulatory functions during normal and malignant human hematopoiesis are incompletely understood. Here we present a comprehensive resource defining the non-coding RNA landscape of the human hematopoietic system. Based on highly specific non-coding RNA expression portraits per blood cell population, we identify unique fingerprint non-coding RNAs—such as LINC00173 in granulocytes — and assign these to critical regulatory circuits involved in blood homeostasis. Following the incorporation of acute myeloid leukemia samples into the landscape, we further uncover prognostically relevant non-coding RNA stem cell signatures shared between acute myeloid leukemia blasts and healthy hematopoietic stem cells. Our findings highlight the importance of the non-coding transcriptome in the formation and maintenance of the human blood hierarchy. While micro-RNAs are known regulators of haematopoiesis and leukemogenesis, the role of long non-coding RNAs is less clear. Here the authors provide a non-coding RNA expression landscape of the human hematopoietic system, highlighting their role in the formation and maintenance of the human blood hierarchy.

Obesity and related comorbidities heighten risks for complications in kidney transplant settings. While pre-transplant patients often have access to nutrition counseling and health support, literature is limited on patients' perceptions of weight and motivation to lose weight prior to transplantation. We conducted a survey among ≥18-year-old patients on the kidney transplant waitlist at a single center. Questions addressed weight perception, motivation for weight loss, available resources, and engagement in physical activity. Medical records provided demographic and clinical data. Statistical tests analyzed quantitative data, while free-text responses were thematically grouped and described. Of 1055 patients, 291 responded and were matched with demographic data. Perceived weight changes correlated with actual changes in body mass index (BMI) (<24.9) were more receptive to weight center resources (<30 kg/m 2 ) are most interested in weight loss resources and demonstrate motivation. Furthermore, pre-transplant nutrition counseling correlates with healthier behaviors. Integrating patients’ perspectives enhances pre-transplant protocols by encouraging active involvement in health decisions.

Introduction Obesity affects 36 % of American women and is a well-documented breast cancer risk factor. Preoperative axillary ultrasound (AUS) is used routinely for axillary staging in newly diagnosed breast cancer patients; However, the impact of obesity on the usefulness of AUS is unknown. Our aim was to evaluate the effect of body mass index (BMI) on the performance of AUS. Methods From our prospective breast surgery database, we identified 1,510 consecutive invasive breast cancers in patients undergoing primary surgery, including axillary operation, from January 2010 to July 2013. Preoperative AUS was performed in 1,375 cases (91 %). We analyzed patient, pathology and imaging data. Results Median BMI was 27.4 and 479 patients (36 %) were classified as obese (BMI ≥ 30). Most tumors were T1 (71 %) and estrogen receptor-positive (87 %). AUS was suspicious in 401 (29 %) patients, of whom 374 had ultrasound-guided lymph node fine-needle aspiration (FNA). Overall, 124 patients (33.2 %) were FNA positive. FNA identified disease preoperatively in 35.8 % of node-positive obese patients. For all BMI categories (normal, overweight, obese), AUS was predictive of pathologic nodal status ( p  < 0.0001). AUS sensitivity did not differ across BMI categories, while specificity and accuracy were better for overweight ( p  = 0.001 and 0.008, respectively) and obese ( p  = 0.007 and 0.02, respectively) patients, than for normal-BMI patients. Conclusions Despite theoretical concern regarding both potential technical challenges and obesity-related lymph node alterations, the sensitivity of preoperative AUS for detecting nodal metastasis was similar in obese and non-obese patients, while specificity was better in obese patients. Preoperative AUS is valuable for preoperative nodal staging of obese breast cancer patients.

Background Uterine fibroids (UF) affect 77% of women by menopause, and account for $9.4 billion in annual healthcare costs. Type-2-diabetes (T2D) has inconsistently associated with protection from UFs in prior studies. To further evaluate the relationship between T2D and UFs we tested for association between T2D and UF risk in a large clinical population as well as the potential differences due to T2D medications and interaction with race. Methods This nested case–control study is derived from a clinical cohort. Our outcome was UF case-control status and our exposure was T2D. UF outcomes and T2D exposure were classified using validated electronic medical record (EMR) algorithms. Logistic regression, adjusted for covariates, was used to model the association between T2D diagnosis and UF risk. Secondary analyses were performed evaluating the interaction between T2D exposure and race and stratifying T2D exposed subjects by T2D medication being taken. Results We identified 3,789 subjects with UF outcomes (608 UF cases and 3,181 controls), 714 were diabetic and 3,075 were non-diabetic. We observed a nominally significant interaction between T2D exposure and race in adjusted models (interaction p  = 0.083). Race stratified analyses demonstrated more protection by T2D exposure on UF risk among European Americans (adjusted odds ratio [aOR] = 0.50, 95% CI 0.35 to 0.72) than African Americans (aOR = 0.76, 95% CI 0.50 to 1.17). We also observed a protective effect by T2D regardless of type of T2D medication being taken, with slightly more protection among subjects on insulin treatments (European Americans aOR = 0.42, 95% CI 0.26 to 0.68; African Americans aOR = 0.60, 95% CI 0.36 to 1.01). Conclusions These data, conducted in a large population of UF cases and controls, support prior studies that have found a protective association between diabetes presence and UF risk and is further modified by race. Protection from UFs by T2D exposure was observed regardless of medication type with slightly more protection among insulin users. Further mechanistic research in larger cohorts is necessary to reconcile the potential role of T2D in UF risk.

Background A recent genome-wide association study (GWAS) has identified a single nucleotide polymorphism (SNP) rs11249433 in the 1p11.2 region as a novel genetic risk factor for breast cancer, and this association was stronger in patients with estrogen receptor (ER) + versus ER - cancer. Results We found association between SNP rs11249433 and expression of the NOTCH2 gene located in the 1p11.2 region. Examined in 180 breast tumors, the expression of NOTCH2 was found to be lowest in tumors with TP53 mutations and highest in TP53 wild-type/ER + tumors (p = 0.0059). In the latter group, the NOTCH2 expression was particularly increased in carriers of the risk genotypes (AG/GG) of rs11249433 when compared to the non-risk AA genotype (p = 0.0062). Similar association between NOTCH2 expression and rs11249433 was observed in 60 samples of purified monocytes from healthy controls (p = 0.015), but not in total blood samples from 302 breast cancer patients and 76 normal breast tissue samples. We also identified the first possible dominant-negative form of NOTCH2 , a truncated version of NOTCH2 consisting of only the extracellular domain. Conclusion This is the first study to show that the expression of NOTCH2 differs in subgroups of breast tumors and by genotypes of the breast cancer-associated SNP rs11249433. The NOTCH pathway has key functions in stem cell differentiation of ER + luminal cells in the breast. Therefore, increased expression of NOTCH2 in carriers of rs11249433 may promote development of ER + luminal tumors. Further studies are needed to investigate possible mechanisms of regulation of NOTCH2 expression by rs11249433 and the role of NOTCH2 splicing forms in breast cancer development.

De novo mutations (DNMs) are novel mutations which occur for the first time in an offspring and are not inherited from the parents. High-Throughput Sequencing (HTS) technologies such as whole genome sequencing (WGS) and whole exome sequencing (WES) of trios have allowed the investigation of DNMs and their role in diseases. Increased contribution of DNMs in both rare monogenic and common complex disorders is now known.Identification of DNMs from WGS is challenging since the error rates in the HTS data are much higher than the expected DNM rate. To facilitate the evaluation of existing DNM callers and development of new callers, I developed TrioSim, the first automated tool to generate simulated WGS datasets for trios with a feature to spike-in DNMs in the offspring WGS data.Several computational methods have been developed to call DNMs from HTS data. I performed the first systematic evaluation of current DNM callers for WGS trio data using real dataset and simulated trio datasets and found that DNM callers have high sensitivity and can detect the majority of true DNMs. However, they suffer from very low specificity with thousands of false positive calls made by each caller.To address this, I developed MetaDeNovo, a consensus-based ensemble computational method to call DNMs using cloud-based technologies. MetaDeNovo is a fully automated methodology that utilises existing DNM callers and integrates their results. It demonstrates much higher specificity than all other callers while maintaining high sensitivity.Congenital Heart Disease (CHD) is the most common birth disorder worldwide. DNMs have been found to contribute to CHD causation. Most CHD cases are sporadic, suggesting role of DNMs in large proportion of them. I applied MetaDeNovo to detect DNMs in a WGS dataset of CHD trios to aid with genetic variant prioritization. MetaDeNovo can dramatically reduce the number of false positive DNMs as compared to individual DNM callers. This has improved the current practices of identifying the genetic causes of disease in such cohorts. MetaDeNovo is applicable to other trio WGS datasets of other genetic diseases.This thesis has contributed new knowledge by in depth exploration of existing DNM callers, development of a novel tool (TrioSim) to simulate trio WGS data and an ensemble improved automated tool (MetaDeNovo) to identify DNMs with high specificity. MetaDeNovo demonstrates its use to identify disease-causing mutations in a trio analysis using WGS.

Analysis of 1,161 cancer genomes across 14 cancer types shows that increased mutation density at gene promoters can be linked to transcription initiation activity and impairment of nucleotide excision repair. Mutation rates in active promoters in cancer Recent whole-genome analyses in cancer have identified numerous hotspots of somatic point mutations within gene promoters. Two papers in this issue of Nature examine this relationship and find evidence for mechanisms linking transcription initiation and DNA repair. Jason Wong and colleagues analyse more than a thousand cancer genomes across 14 cancer types and find that increased mutation density at gene promoters is linked to transcription initiation activity and impairment of nucleotide excision repair. The density of promoter mutations can be correlated with the dependence of the cancer on excision repair. Núria López-Bigas and colleagues report an analysis of genomic data from melanomas, finding an increased rate of somatic mutations at active transcription factor binding sites within promoter regions. The increased mutation rate at these genomic regions can be explained by reduced accessibility of the protein-bound DNA to nucleotide excision repair. Promoters are DNA sequences that have an essential role in controlling gene expression. While recent whole cancer genome analyses have identified numerous hotspots of somatic point mutations within promoters, many have not yet been shown to perturb gene expression or drive cancer development 1 , 2 , 3 , 4 . As such, positive selection alone may not adequately explain the frequency of promoter point mutations in cancer genomes. Here we show that increased mutation density at gene promoters can be linked to promoter activity and differential nucleotide excision repair (NER). By analysing 1,161 human cancer genomes across 14 cancer types, we find evidence for increased local density of somatic point mutations within the centres of DNase I-hypersensitive sites (DHSs) in gene promoters. Mutated DHSs were strongly associated with transcription initiation activity, in which active promoters but not enhancers of equal DNase I hypersensitivity were most mutated relative to their flanking regions. Notably, analysis of genome-wide maps of NER 5 shows that NER is impaired within the DHS centre of active gene promoters, while XPC -deficient skin cancers do not show increased promoter mutation density, pinpointing differential NER as the underlying cause of these mutation hotspots. Consistent with this finding, we observe that melanomas with an ultraviolet-induced DNA damage mutation signature show greatest enrichment of promoter mutations, whereas cancers that are not highly dependent on NER, such as colon cancer, show no sign of such enrichment. Taken together, our analysis has uncovered the presence of a previously unknown mechanism linking transcription initiation and NER as a major contributor of somatic point mutation hotspots at active gene promoters in cancer genomes.

Several reports have shown that statin treatment benefits patients with asthma; however, inconsistent effects have been observed. The mir-152 family (148a, 148b and 152) has been implicated in asthma. These microRNAs suppress HLA-G expression, and rs1063320, a common SNP in the HLA-G 3′UTR that is associated with asthma risk, modulates miRNA binding. We report that statins upregulate mir-148b and 152, and affect HLA-G expression in an rs1063320-dependent fashion. In addition, we found that individuals who carried the G minor allele of rs1063320 had reduced asthma-related exacerbations (emergency department visits, hospitalizations or oral steroid use) compared with non-carriers ( P =0.03) in statin users ascertained in the Personalized Medicine Research Project at the Marshfield Clinic ( n =421). These findings support the hypothesis that rs1063320 modifies the effect of statin benefit in asthma, and thus may contribute to variation in statin efficacy for the management of this disease.