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Circulating metabolite levels have been associated with type 2 diabetes (T2D), but the extent to which T2D affects metabolite levels and their genetic regulation remains to be elucidated. In this study, we investigate the interplay between genetics, metabolomics, and T2D risk in the UK Biobank dataset using the Nightingale panel composed of 249 metabolites, 92% of which correspond to lipids (HDL, IDL, LDL, VLDL) and lipoproteins. By integrating these data with large-scale T2D GWAS from the DIAMANTE meta-analysis through Mendelian randomization analyses, we find 79 metabolites with a causal association to T2D, all spanning lipid-related classes except for Glucose and Tyrosine. Twice as many metabolites are causally affected by T2D liability, spanning almost all tested classes, including branched-chain amino acids. Secondly, using an interaction quantitative trait locus (QTL) analysis, we describe four metabolites consistently replicated in an independent dataset from the Estonian Biobank, for which genetic loci in two different genomic regions show attenuated regulation in T2D cases compared to controls. The significant variants from the interaction QTL analysis are significant QTLs for the corresponding metabolites in the general population but are not associated with T2D risk, pointing towards consequences of T2D on the genetic regulation of metabolite levels. Finally, through differential level analyses, we find 165 metabolites associated with microvascular, macrovascular, or both types of T2D complications, with only a few discriminating between complication classes. Of the 165 metabolites, 40 are not causally linked to T2D in either direction, suggesting biological mechanisms specific to the occurrence of complications. Overall, this work provides a map of the consequences of T2D on Nightingale targeted metabolite levels and on their genetic regulation, enabling a better understanding of the T2D trajectory leading to complications.

Background In present study we performed whole transcriptome analysis in plaque psoriasis patients and compared lesional skin with non-lesional skin and with the skin from healthy controls. We sequenced total RNA from 12 lesional (LP), 12 non-lesional (NLP) and from 12 normal (C) skin biopsies. Results Compared with previous gene expression profiling studies we had three groups under analysis - LP, NLP and C. Using NLP samples allows to see the transcriptome of visually normal skin from psoriasis patient. In LP skin S100A12, S100A7A, LCE3E, DEFB4A, IL19 were found up regulated. In addition to already these well-described genes, we also found several other genes related to psoriasis. Namely, KLK9, OAS2, OAS3, PLA2G, IL36G, IL36RN were found to be significantly and consistently related to the psoriatic lesions and this finding is supported also by previous studies. The genes up-regulated in the LP samples were related to the innate immunity, IL17 and IL10 networks. In NLP samples innate immunity and IL17 network were activated, but activation of IL10 network was not evident. The transcriptional changes characteristic in the NLP samples can be considered as a molecular signature of “dormant psoriasis”. Conclusions Taken together, our study described the transcriptome profile characteristic for LP and NLP psoriatic skin. RNA profile of the NLP skin is in between the lesional and healthy skin, with its own specific pattern. We found that both LP and NLP have up-regulated IL17 network, whereas LP skin has up regulated IL10 related cytokines (IL19, IL20, IL24). Moreover, IL36G and IL36RN were identified as strong regulators of skin pathology in both LP and NLP skin samples, with stronger influence in LP samples.

To evaluate skin tissue gene expression patterns correctly, extracting sufficient quantities of good quality RNA is essential. However, RNA extraction from skin tissue is challenging, as the hyaluronic acid-collagen matrix is extremely difficult to homogenize. Although there are multiple ways to extract RNA from skin, there are no comparative studies that identify the most critical steps, e.g. sample collection, storage and homogenization. We analysed the various steps involved in RNA extraction (i.e. biopsy collection as dry biopsy or into nucleotide stabilizing reagents, different storage conditions, enzymatic digestion, stator-rotor and bead motion-based homogenizing combined with column-based RNA purification). We hypothesised that domestic pig skin is applicable as a model for human skin studies. Altogether twenty different workflows were tested on pig skin and the four most promising workflows were tested on human skin samples. The optimal strategy for extracting human skin RNA was to collect, store and homogenize the sample in RLT lysis buffer from the RNeasy Fibrous Tissue Kit combined with beta-mercaptoethanol. Both stator-rotor and bead motion-based homogenizing were found to result in high quality and quantity of extracted RNA. Our results confirmed that domestic pig skin can be successfully used as a model for human skin RNA studies.

Melanocytes possess several functions besides a role in pigment synthesis, but detailed characteristics of the cells are still unclear. We used whole transcriptome sequencing (RNA-Seq) to assess differential gene expression of cultivated normal human melanocytes with respect to keratinocytes, fibroblasts and whole skin. The present results reveal cultivated melanocytes as highly proliferative cells with possible stem cell-like properties. The enhanced readiness to regenerate makes melanocytes the most vulnerable cells in the skin and explains their high risk of developing into malignant melanoma.

The melanocortin system is a major regulator of stress responses in the skin and is responsible for the induction of melanin synthesis through activation of melanogenesis enzymes. The expression of both melanocortin system genes and melanogenesis enzyme genes is altered in psoriasis, and the focus here was on twelve genes related to the signal transduction between them. Additionally, five endogenous opioid system genes that are involved in cutaneous inflammation were examined. Quantitative real-time-PCR was utilized to measure mRNA expression in punch biopsies from lesional and non-lesional skin of psoriasis patients and from the skin of healthy control subjects. Most of the genes related to melanogenesis were down-regulated in patients (CREB1, MITF, LEF1, USF1, MAPK14, ICAM1, PIK3CB, RPS6KB1, KIT, and ATRN). Conversely, an up-regulation occurred in the case of opioids (PENK, PDYN, and PNOC). The suppression of genes related to melanogenesis is in agreement with the reported reduction in pigmentation signaling in psoriatic skin and potentially results from the pro-inflammatory environment. The increase in endogenous opioids can be associated with their involvement in inflammatory dysregulation in psoriasis.

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.

Repetitive elements (RE) constitute the majority of the human genome and have a range of functions both structural and regulatory on genomic function and gene expression. RE overexpression has been observed in several neurodegenerative diseases, consistent with the observation of aberrant expression of RE posing a mutagenic threat. Despite reports that associate RE expression with PD no study has comprehensively analysed the role of these elements in the disease. This study presents the first genome-wide analysis of RE expression in PD to date. Analysis of RNA-sequencing data of 12 PD patients and 12 healthy controls identified tissue-specific expression differences and more significantly, differential expression of four satellite elements; two simple satellite III (repName = CATTC_n and _GAATG_n) a high-copy satellite II (HSATII) and a centromeric satellite (ALR_Alpha) in the blood of PD patients. In support of the growing body of recent evidence associating REs with neurodegenerative disease, this study highlights the potential importance of characterization of RE expression in such diseases.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies. Measurement(s) Somatic Mutation Analysis Technology Type(s) whole genome sequencing • Whole Exome Sequencing Factor Type(s) sequencing platform • sample prepration • library preparation • bioinformatics method Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.16713655

Background Osteogenesis imperfecta (OI) covers a spectrum of bone fragility disorders. OI is classified into five types; however, the genetic causes of OI might hide in pathogenic variants of 20 different genes. Often clinical OI types mimic each other. This sometimes makes it impossible to identify the OI type clinically, which can be a risk for patients. Up to 90% of OI types I–IV are caused by pathogenic variants in the COL1A1/2 genes. OI type V is caused by the c.-14C > T pathogenic variant in the 5′UTR of the IFITM5 gene and is characterized by hyperplastic callus formation and the ossification of interosseous membranes. Results In the current study, we performed IFITM5 5′UTR region mutational analysis using Sanger sequencing on 90 patients who were negative for COL1A1 / 2 pathogenic variants. We also investigated the phenotypes of five patients with genetically confirmed OI type V. The proportion of OI type V patients in our cohort of all OI patients was 1.48%. In one family, there was a history of OI in at least three generations. Phenotype severity differed from mild to extremely severe among patients, but all patients harbored the same typical pathogenic variant. One patient had no visible symptoms of OI type V and was suspected to have had OI type IV previously. We also identified a case of extremely severe hyperplastic callus in a 15-year-old male, who has hearing loss and brittleness of teeth. Conclusions OI type V is underlined with some unique clinical features; however, not all patients develop them. The phenotype spectrum might be even broader than previously suspected, including typical OI features: teeth brittleness, bluish sclera, hearing loss, long bones deformities, and joint laxity. We suggest that all patients negative for COL1A1 / 2 pathogenic variants be tested for the presence of an IFITM5 pathogenic variant, even if they are not expressing typical OI type V symptoms. Further studies on the pathological nature and hyperplastic callus formation mechanisms of OI type V are necessary.

We report the changed levels of serum amyloid alpha, an immunologically active protein, in Parkinson's disease (PD) patients' peripheral tissues. We have previously shown that and (serum amyloid alpha-1,-2, genes) were among the top downregulated genes in PD patients' skin, using whole-genome RNA sequencing. In the current study, we characterized the gene and protein expression profiles of skin and blood samples from patients with confirmed PD diagnosis and age/sex matched controls. qRT-PCR analysis of PD skin demonstrated downregulation of and genes in PD patients. However, the lowered amount of protein could not be visualized using immunohistochemistry, due to low quantity of SAA (Serum Amyloid Alpha, protein) in skin. and expression levels in whole blood were below detection threshold based on RNA sequencing, however significantly lowered protein levels of SAA1/2 in PD patients' serum were shown with ELISA, implying that SAA is secreted into the blood. These results show that SAA is differentially expressed in the peripheral tissues of PD patients.