The Health Impacts of Climate Change: A Study of Cholera in Tanzania

Increased temperatures and changes in patterns of rainfall as a result of climate change are widely recognized to entail serious consequences for human health, including the risk of diarrheal diseases. Indeed, there is strong evidence that temperature and rainfall patterns affect the disease pattern. This paper presents the first study that links the incidence of cholera to environmental and socioeconomic factors and uses that relationship to predict how climate change will affect the incidence of cholera. Specifically, the paper integrates historical data on temperature and rainfall with the burden of disease from cholera in Tanzania, and uses socioeconomic data to control for impacts of general development on the risk of cholera. Based on these results we estimate the number and costs of additional cholera cases and deaths that can be attributed to climate change by year 2030 in Tanzania. The analyses are based on primary data collected from the Ministry of Health, Tanzania, and the Tanzania Meteorological Agency. The result shows a significant relationship between cholera cases and temperature and predicts an increase in the initial risk ratio for cholera in Tanzania in the range of 23 to 51 percent for a 1 degree Celsius increase in annual mean temperature. The cost of reactive adaptation to cholera attributed to climate change impacts by year 2030 in Tanzania is projected to be in the range of 0.02 to 0.09 percent of GDP for the lower and upper bounds respectively. Total costs, including loss of lives are estimated in the range of 1.4 to 7.8 percent of GDP by year 2030. Lastly, costs of additional cholera cases and deaths attributed to climate change impacts in Tanzania by the year 2030 largely exceed the costs of preventive measures such as household chlorination.climate change,health impacts,adaptation costs,Tanzania

The Health Impacts of Climate Change: A Study of Cholera in Tanzania

27 p.Increased temperatures and changes in patterns of rainfall as a result of climate change are widely recognized to entail serious consequences for human health, including the risk of diarrheal diseases. Indeed, there is strong evidence that temperature and rainfall patterns affect the disease pattern. This paper presents the first study that links the incidence of cholera to environmental and socioeconomic factors and uses that relationship to predict how climate change will affect the incidence of cholera. Specifically, the paper integrates historical data on temperature and rainfall with the burden of disease from cholera in Tanzania, and uses socioeconomic data to control for impacts of general development on the risk of cholera. Based on these results we estimate the number and costs of additional cholera cases and deaths that can be attributed to climate change by year 2030 in Tanzania. The analyses are based on primary data collected from the Ministry of Health, Tanzania, and the Tanzania Meteorological Agency. The result shows a significant relationship between cholera cases and temperature and predicts an increase in the initial risk ratio for cholera in Tanzania in the range of 23 to 51 percent for a 1 degree Celsius increase in annual mean temperature. The cost of reactive adaptation to cholera attributed to climate change impacts by year 2030 in Tanzania is projected to be in the range of 0.02 to 0.09 percent of GDP for the lower and upper bounds respectively. Total costs, including loss of lives are estimated in the range of 1.4 to 7.8 percent of GDP by year 2030. Lastly, costs of additional cholera cases and deaths attributed to climate change impacts in Tanzania by the year 2030 largely exceed the costs of preventive measures such as household chlorination

The yield of essential oils in Melaleuca alternifolia (Myrtaceae) is regulated through transcript abundance of genes in the MEP pathway

Medicinal tea tree (Melaleuca alternifolia) leaves contain large amounts of an essential oil, dominated by monoterpenes. Several enzymes of the chloroplastic methylerythritol phosphate (MEP) pathway are hypothesised to act as bottlenecks to the production of monoterpenes. We investigated, whether transcript abundance of genes encoding for enzymes of the MEP pathway were correlated with foliar terpenes in M. alternifolia using a population of 48 individuals that ranged in their oil concentration from 39 -122 mg x g DM(-1). Our study shows that most genes in the MEP pathway are co-regulated and that the expression of multiple genes within the MEP pathway is correlated with oil yield. Using multiple regression analysis, variation in expression of MEP pathway genes explained 87% of variation in foliar monoterpene concentrations. The data also suggest that sesquiterpenes in M. alternifolia are synthesised, at least in part, from isopentenyl pyrophosphate originating from the plastid via the MEP pathway

MicroRNA-135b Regulates Leucine Zipper Tumor Suppressor 1 in Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin malignancy and it presents a therapeutic challenge in organ transplant recipient patients. Despite the need, there are only a few targeted drug treatment options. Recent studies have revealed a pivotal role played by microRNAs (miRNAs) in multiple cancers, but only a few studies tested their function in cSCC. Here, we analyzed differential expression of 88 cancer related miRNAs in 43 study participants with cSCC; 32 immunocompetent, 11 OTR patients, and 15 non-lesional skin samples by microarray analysis. Of the examined miRNAs, miR-135b was the most upregulated (13.3-fold, 21.5-fold; p=0.0001) in both patient groups. Similarly, the miR-135b expression was also upregulated in three cSCC cell lines when evaluated by quantitative real-time PCR. In functional studies, inhibition of miR-135b by specific anti-miR oligonucleotides resulted in upregulation of its target gene LZTS1 mRNA and protein levels and led to decreased cell motility and invasion of both primary and metastatic cSCC cell lines. In contrast, miR-135b overexpression by synthetic miR-135b mimic induced further down-regulation of LZTS1 mRNA in vitro and increased cancer cell motility and invasiveness. Immunohistochemical evaluation of 67 cSCC tumor tissues demonstrated that miR-135b expression inversely correlated with LZTS1 staining intensity and the tumor grade. These results indicate that miR-135b functions as an oncogene in cSCC and provide new understanding into its pathological role in cSCC progression and invasiveness

Long non-coding and coding RNAs characterization in Peripheral Blood Mononuclear Cells and Spinal Cord from Amyotrophic Lateral Sclerosis patients

Alteration in RNA metabolism, concerning both coding and long non-coding RNAs (lncRNAs), may play an important role in Amyotrophic Lateral Sclerosis (ALS) pathogenesis. In this work, we performed a whole transcriptome RNA-seq analysis to investigate the regulation of non-coding and coding RNAs in Sporadic ALS patients (SALS), mutated ALS patients (FUS, TARDBP and SOD1) and matched controls in Peripheral Blood Mononuclear Cells (PBMC). Selected transcripts were validated in spinal cord tissues. A total of 293 differentially expressed (DE) lncRNAs was found in SALS patients, whereas a limited amount of lncRNAs was deregulated in mutated patients. A total of 87 mRNAs was differentially expressed in SALS patients; affected genes showed an association with transcription regulation, immunity and apoptosis pathways. Taken together our data highlighted the importance of extending the knowledge on transcriptomic molecular alterations and on the significance of regulatory lncRNAs classes in the understanding of ALS disease. Our data brought the light on the importance of lncRNAs and mRNAs regulation in central and peripheral systems, offering starting points for new investigations about pathogenic mechanism involved in ALS disease

Met exon 14 skipping: A case study for the detection of genetic variants in cancer driver genes by deep learning

Background: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell lung cancer (NSCLC) MET exon 14 skipping was shown to be targetable. Methods: We constructed neural networks (NN/CNN) specifically designed to detect MET exon 14 skipping events using RNAseq data. Furthermore, for discovery purposes we also developed a sparsely connected autoencoder to identify uncharacterized MET isoforms. Results: The neural networks had a Met exon 14 skipping detection rate greater than 94% when tested on a manually curated set of 690 TCGA bronchus and lung samples. When globally applied to 2605 TCGA samples, we observed that the majority of false positives was characterized by a blurry coverage of exon 14, but interestingly they share a common coverage peak in the second intron and we speculate that this event could be the transcription signature of a LINE1 (Long Interspersed Nuclear Element 1)-MET (Mesenchymal Epithelial Transition receptor tyrosine kinase) fusion. Conclusions: Taken together, our results indicate that neural networks can be an effective tool to provide a quick classification of pathological transcription events, and sparsely connected autoencoders could represent the basis for the development of an effective discovery tool

Characterization of a genetic mouse model of lung cancer: a promise to identify Non-Small Cell Lung Cancer therapeutic targets and biomarkers.

Background: Non-small cell lung cancer (NSCLC) accounts for 81% of all cases of lung cancer and they are often fatal because 60% of the patients are diagnosed at an advanced stage. Besides the need for earlier diagnosis, there is a high need for additional effective therapies. In this work, we investigated the feasibility of a lung cancer progression mouse model, mimicking features of human aggressive NSCLC, as biological reservoir for potential therapeutic targets and biomarkers. Results: We performed RNA-seq profiling on total RNA extracted from lungs of a 30 week-old K-rasLA1/p53R172H\u394g and wild type (WT) mice to detect fusion genes and gene/exon-level differential expression associated to the increase of tumor mass. Fusion events were not detected in K-rasLA1/p53R172H\u394g tumors. Differential expression at exon-level detected 33 genes with differential exon usage. Among them nine, i.e. those secreted or expressed on the plasma membrane, were used for a meta-analysis of more than 500 NSCLC RNA-seq transcriptomes. None of the genes showed a significant correlation between exon-level expression and disease prognosis. Differential expression at gene-level allowed the identification of 1513 genes with a significant increase in expression associated to tumor mass increase. 74 genes, i.e. those secreted or expressed on the plasma membrane, were used for a meta-analysis of two transcriptomics datasets of human NSCLC samples, encompassing more than 900 samples. SPP1 was the only molecule whose over-expression resulted statistically related to poor outcome regarding both survival and metastasis formation. Two other molecules showed over-expression associated to poor outcome due to metastasis formation: GM-CSF and ADORA3. GM-CSF is a secreted protein, and we confirmed its expression in the supernatant of a cell line derived by a K-rasLA1/p53R172H\u394g mouse tumor. ADORA3 is instead involved in the induction of p53-mediated apoptosis in lung cancer cell lines. Since in our model p53 is inactivated, ADORA3 does not negatively affect tumor growth but remains expressed on tumor cells. Thus, it could represent an interesting target for the development of antibody-targeted therapy on a subset of NSCLC, which are p53 null and ADORA3 positive. Conclusions: Our study provided a complete transcription overview of the K-rasLA1/p53R172H\u394g mouse NSCLC model. This approach allowed the detection of ADORA3 as a potential target for antibody-based therapy in p53 mutated tumors

Extracellular Vesicles Derived From Plasma of Patients With Neurodegenerative Disease Have Common Transcriptomic Profiling

Objectives: There is a lack of effective biomarkers for neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia. Extracellular vesicle (EV) RNA cargo can have an interesting potential as a non-invasive biomarker for NDs. However, the knowledge about the abundance of EV-mRNAs and their contribution to neurodegeneration is not clear. Methods: Large and small EVs (LEVs and SEVs) were isolated from plasma of patients and healthy volunteers (control, CTR) by differential centrifugation and filtration, and RNA was extracted. Whole transcriptome was carried out using next generation sequencing (NGS). Results: Coding RNA (i.e., mRNA) but not long non-coding RNAs (lncRNAs) in SEVs and LEVs of patients with ALS could be distinguished from healthy CTRs and from other NDs using the principal component analysis (PCA). Some mRNAs were found in commonly deregulated between SEVs of patients with ALS and frontotemporal dementia (FTD), and they were classified in mRNA processing and splicing pathways. In LEVs, instead, one mRNA and one antisense RNA (i.e., MAP3K7CL and AP003068.3) were found to be in common among ALS, FTD, and PD. No deregulated mRNAs were found in EVs of patients with AD. Conclusion: Different RNA regulation occurs in LEVs and SEVs of NDs. mRNAs and lncRNAs are present in plasma-derived EVs of NDs, and there are common and specific transcripts that characterize LEVs and SEVs from the NDs considered in this study

Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals. Description of the diverse and most represented species

The role of non-coding RNAs in different biological processes and diseases is continuously expanding. Next-generation sequencing together with the parallel improvement of bioinformatics analyses allows the accurate detection and quantification of an increasing number of RNA species. With the aim of exploring new potential biomarkers for disease classification, a clear overview of the expression levels of common/unique small RNA species among different biospecimens is necessary. However, except for miRNAs in plasma, there are no substantial indications about the pattern of expression of various small RNAs in multiple specimens among healthy humans. By analysing small RNA-sequencing data from 243 samples, we have identified and compared the most abundantly and uniformly expressed miRNAs and non-miRNA species of comparable size with the library preparation in four different specimens (plasma exosomes, stool, urine, and cervical scrapes). Eleven miRNAs were commonly detected among all different specimens while 231 miRNAs were globally unique across them. Classification analysis using these miRNAs provided an accuracy of 99.6% to recognize the sample types. piRNAs and tRNAs were the most represented non-miRNA small RNAs detected in all specimen types that were analysed, particularly in urine samples. With the present data, the most uniformly expressed small RNAs in each sample type were also identified. A signature of small RNAs for each specimen could represent a reference gene set in validation studies by RT-qPCR. Overall, the data reported hereby provide an insight of the constitution of the human miRNome and of other small non-coding RNAs in various specimens of healthy individuals