Activation of GPR15 and its involvement in the biological effects of smoking

Smoking is one of the most significant modifiable environmental risk factors for many diseases. Smoking causes excessive mortality worldwide. Despite decades of long research, there has not been a clear understanding regarding the molecular mechanism that makes smoking harmful to health. Some recent studies have found that smoking influences most significantly the expression and methylation of GPR15. GPR15 is an orphan receptor that is involved in the regulation of the innate immunity and the T-cell trafficking in the intestinal epithelium. Further studies have confirmed that GPR15 is very strongly involved in smoking and smoking-induced molecular changes. Therefore, the altered expression and epigenetic regulation of GPR15 could have a significant role in the health impact of smoking

Smoking-related general and cause-specific mortality in Estonia

Abstract Background Tobacco smoking is known to be the single largest cause of premature death worldwide. The aim of present study was to analyse the effect of smoking on general and cause-specific mortality in the Estonian population. Methods The data from 51,756 adults in the Estonian Genome Center of the University of Tartu was used. Information on dates and causes of death was retrieved from the National Causes of Death Registry. Smoking status, general survival, general mortality and cause-specific mortality were analysed using Kaplan-Meier estimator and Cox proportional hazards models. Results The study found that smoking reduces median survival in men by 11.4 years and in women by 5.8 years. Tobacco smoking produces a very specific pattern in the cause of deaths, significantly increasing the risks for different cancers and cardiovascular diseases as causes of death for men and women. This study also identified that external causes, such as alcohol intoxication and intentional self-harm, are more prevalent causes of death among smokers than non-smokers. Additionally, smoking cessation was found to reverse the increased risks for premature mortality. Conclusions Tobacco smoking remains the major cause for losses of life inducing cancers and cardiovascular diseases. In addition to the common diseases, external causes also reduce substantially the years of life. External causes of death indicate that smoking has a long-term influence on the behaviour of smokers, provoking self-destructive behaviour. Our study supports the idea, that tobacco smoking generates complex harm to our health increasing mortality from both somatic and mental disorders

Transcriptional Basis of Psoriasis from Large Scale Gene Expression Studies: The Importance of Moving towards a Precision Medicine Approach

Transcriptome profiling techniques, such as microarrays and RNA sequencing (RNA-seq), are valuable tools for deciphering the regulatory network underlying psoriasis and have revealed large number of differentially expressed genes in lesional and non-lesional skin. Such approaches provide a more precise measurement of transcript levels and their isoforms than any other methods. Large cohort transcriptomic analyses have greatly improved our understanding of the physiological and molecular mechanisms underlying disease pathogenesis and progression. Here, we mostly review the findings of some important large scale psoriatic transcriptomic studies, and the benefits of such studies in elucidating potential therapeutic targets and biomarkers for psoriasis treatment. We also emphasised the importance of looking into the alternatively spliced RNA isoforms/transcripts in psoriasis, rather than focussing only on the gene-level annotation. The neutrophil and blood transcriptome signature in psoriasis is also briefly reviewed, as it provides the immune status information of patients and is a less invasive platform. The application of precision medicine in current management of psoriasis, by combining transcriptomic data, improves the clinical response outcome in individual patients. Drugs tailored to individual patient's genetic profile will greatly improve patient outcome and cost savings for the healthcare system

At the dawn of the transcriptomic medicine

Impact statement This review describes the impact of transcriptomics on experimental biology and its integration into medical practice. Transcriptomics is an essential part of modern biomedical research based on highly sophisticated and reliable technology. Transcriptomics can aid clinical practice and improve the precision of clinical diagnoses and decision-making by complementing existing clinical best practice. The power of which will be increased when combined with genomic variation from genome wide association studies and next generation sequencing. We are witnessing the implementation of RNA-based technologies in clinical practice that will eventually lead to the establishment of transcriptional medicine as a routine tool in diagnosis. Progress in genomic analytical technologies has improved our possibilities to obtain information regarding DNA, RNA, and their dynamic changes that occur over time or in response to specific challenges. This information describes the blueprint for cells, tissues, and organisms and has fundamental importance for all living organisms. This review focuses on the technological challenges to analyze the transcriptome and what is the impact of transcriptomics on precision medicine. The transcriptome is a term that covers all RNA present in cells and a substantial part of it will never be translated into protein but is nevertheless functional in determining cell phenotype. Recent developments in transcriptomics have challenged the fundamentals of the central dogma of biology by providing evidence of pervasive transcription of the genome. Such massive transcriptional activity is challenging the definition of a gene and especially the term “pseudogene” that has now been demonstrated in many examples to be both transcribed and translated. We also review the common sources of biomaterials for transcriptomics and justify the suitability of whole blood RNA as the current optimal analyte for clinical transcriptomics. At the end of the review, a brief overview of the clinical implications of transcriptomics in clinical trial design and clinical diagnosis is given. Finally, we introduce the transcriptome as a target for modern drug development as a tool for extending our capacity for precision medicine in multiple diseases

Recent Insights into the Role of Unfolded Protein Response in ER Stress in Health and Disease

Peer reviewe

Mutational analysis of COL1A1 and COL1A2 genes among Estonian osteogenesis imperfecta patients

Background Osteogenesis imperfecta (OI) is a rare bone disorder. In 90% of cases, OI is caused by mutations in the COL1A1/2 genes, which code procollagen α1 and α2 chains. The main aim of the current research was to identify the mutational spectrum of COL1A1/2 genes in Estonian patients. The small population size of Estonia provides a unique chance to explore the collagen I mutational profile of 100% of OI families in the country. Methods We performed mutational analysis of peripheral blood gDNA of 30 unrelated Estonian OI patients using Sanger sequencing of COL1A1 and COL1A2 genes, including all intron-exon junctions and 5′UTR and 3′UTR regions, to identify causative OI mutations. Results We identified COL1A1/2 mutations in 86.67% of patients (26/30). 76.92% of discovered mutations were located in the COL1A1 (n = 20) and 23.08% in the COL1A2 (n = 6) gene. Half of the COL1A1/2 mutations appeared to be novel. The percentage of quantitative COL1A1/2 mutations was 69.23%. Glycine substitution with serine was the most prevalent among missense mutations. All qualitative mutations were situated in the chain domain of pro-α1/2 chains. Conclusion Our study shows that among the Estonian OI population, the range of collagen I mutations is quite high, which agrees with other described OI cohorts of Northern Europe. The Estonian OI cohort differs due to the high number of quantitative variants and simple missense variants, which are mostly Gly to Ser substitutions and do not extend the chain domain of COL1A1/2 products

Aneurysmal subarachnoid haemorrhage: effect of CRHR1 genotype on fatigue and depression

Background Emotional health disturbances are common after aneurysmal subarachnoid hemorrhage (aSAH) and their causes are largely unexplored. Corticotropin-releasing hormone receptor 1 (CRHR1) is a key factor in stress reactivity and development of mental health disturbances after adverse life-events. Methods We explore the effect of CRHR1 genotype on mental health after aSAH in a retrospective cohort study. One hundred twenty-five patients have been assessed using EST-Q mental health questionnaire. Genotyping of CRHR1 single nucleotide polymorphisms (SNP-s) was performed (Rs7209436, Rs110402, Rs242924). Results Fatigue was present in almost half of aSAH patients, depression and anxiety in one-third. There was a high prevalence of insomnia and panic complaints. Rs110402 minor allele decreased the risk of depression (OR = 0.25, p = 0.027 for homozygotes). Depression was present in 14% vs 41% in minor and major allele homozygotes, respectively. Rs110402, Rs242924 and Rs7209436 minor alleles and TAT-haplotype, formed by them, were protective against fatigue. After Bonferroni correction only the association of Rs110402 with fatigue remained statistically significant (OR = 0.21, p = 0.006 for minor allele homozygotes). Results remained statistically significant when adjusted for gender, admission state, age and time from aSAH. In multiple regression analysis occurrence of fatigue was dependent on anxiety, modified Rankin score and Rs110402 genotype (R2 = 0.34, p <  0.001). Conclusions CRHR1 minor genotype was associated with a lower risk of fatigue and depression after aSAH. Genetic predisposition to mental health disturbances associated with negative life-events could be a risk factor for fatigue and depression after aSAH and selected patients might benefit from advanced counselling in the recovery phase

<i>C14orf132</i> gene is possibly related to extremely low birth weight

BackgroundDespite extensive research the genetic component of extremely low birth weight (ELBW) in newborns has remained obscure.ResultsThe aim of the case study was to identify candidate gene(s) causing ELBW in newborns and hypotrophy in infants. A family of four was studied: mother, father and two ELBW-phenotype children. Studies were made of the medical conditions of the second child at birth and post-partum - peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy and suspected metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate the genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene - C14orf132 (chromosome 14 open reading frame 132) differentially expressed, with the level of the transcript significantly lower in the blood samples of the children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children.ConclusionWe demonstrated the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the pre- and early postnatal developmental delay through the altered gene expression

Transcriptional landscape analysis identifies differently expressed genes involved in follicle-stimulating hormone induced postmenopausal osteoporosis

Osteoporosis is a disorder associated with bone tissue reorganization, bone mass, and mineral density. Osteoporosis can severely affect postmenopausal women, causing bone fragility and osteoporotic fractures. The aim of the current study was to compare blood mRNA profiles of postmenopausal women with and without osteoporosis, with the aim of finding different gene expressions and thus targets for future osteoporosis biomarker studies. Our study consisted of transcriptome analysis of whole blood serum from 12 elderly female osteoporotic patients and 12 non-osteoporotic elderly female controls. The transcriptome analysis was performed with RNA sequencing technology. For data analysis, the edgeR package of R Bioconductor was used. Two hundred and fourteen genes were expressed differently in osteoporotic compared with non-osteoporotic patients. Statistical analysis revealed 20 differently expressed genes with a false discovery rate of less than 1.47 × 10(−4) among osteoporotic patients. The expression of 10 genes were up-regulated and 10 down-regulated. Further statistical analysis identified a potential osteoporosis mRNA biomarker pattern consisting of six genes: CACNA1G, ALG13, SBK1, GGT7, MBNL3, and RIOK3. Functional ingenuity pathway analysis identified the strongest candidate genes with regard to potential involvement in a follicle-stimulating hormone activated network of increased osteoclast activity and hypogonadal bone loss. The differentially expressed genes identified in this study may contribute to future research of postmenopausal osteoporosis blood biomarkers

RNA sequencing analysis reveals increased expression of interferon signaling genes and dysregulation of bone metabolism affecting pathways in the whole blood of patients with osteogenesis imperfecta

Background Osteogenesis imperfecta (OI) is a rare genetic disorder in which the patients suffer from numerous fractures, skeletal deformities and bluish sclera. The disorder ranges from a mild form to severe and lethal cases. The main objective of this pilot study was to compare the blood transcriptional landscape of OI patients with COL1A1 pathogenic variants and their healthy relatives, in order to find out different gene expression and dysregulated molecular pathways in OI. Methods We performed RNA sequencing analysis of whole blood in seven individuals affected with different OI severity and their five unaffected relatives from the three families. The data was analyzed using edgeR package of R Bioconductor. Functional profiling and pathway analysis of the identified differently expressed genes was performed with g:GOSt and MinePath web-based tools. Results We identified 114 differently expressed genes. The expression of 79 genes was up-regulated, while 35 genes were down-regulated. The functional analysis identified a presence of dysregulated interferon signaling pathways (IFI27, IFITM3, RSAD12, GBP7). Additionally, the expressions of the genes related to extracellular matrix organization, Wnt signaling, vitamin D metabolism and MAPK-ERK 1/2 pathways were also altered. Conclusions The current pilot study successfully captured the differential expression of inflammation and bone metabolism pathways in OI patients. This work can contribute to future research of transcriptional bloodomics in OI. Transcriptional bloodomics has a strong potential to become a major contributor to the understanding of OI pathological mechanisms, the discovery of phenotype modifying factors, and the identification of new therapeutic targets. However, further studies in bigger cohorts of OI patients are needed to confirm the findings of the current work