3901 results for "*geneti*"

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• Rare coding variants in lupus risk genes

  Systemic lupus erythematosus (SLE) is the prototypic systemic autoimmune disease. It is thought that many common variant gene loci of weak effect act additively to predispose to common autoimmune diseases, while the contribution of rare variants remains unclear. Here we describe that rare coding variants in lupus-risk genes are present in most SLE patients and healthy controls. We demonstrate the functional consequences of rare and low frequency missense variants in the interacting proteins BLK and BANK1, which are present alone, or in combination, in a substantial proportion of lupus patients. The rare variants found in patients, but not those found exclusively in controls, impair suppression of IRF5 and type-I IFN in human B cell lines and increase pathogenic lymphocytes in lupus-prone mice. Thus, rare gene variants are common in SLE and likely contribute to genetic risk.

  Study EGAS00001003548

• Presence of rare potential pathogenic variants in subjects under 65 years old with very severe or fatal COVID‑19

  Rare variants affecting host defense against pathogens could be involved in COVID‑19 severity and may help explain fatal outcomes in young and middle‑aged patients. Our aim was to report the presence of rare genetic variants in certain genes, by using whole exome sequencing, in a selected group of COVID‑19 patients under 65 years who required intubation or resulting in death (n = 44). To this end, different etiopathogenic mechanisms were explored using gene prioritization‑based analysis in which genes involved in immune response, immunodeficiencies or blood coagulation were studied. We detected 44 different variants of interest, in 29 different patients (66%). Some of these variants were previously described as pathogenic and were located in genes mainly involved in immune response. A network analysis, including the 42 genes with candidate variants, showed three main components, consisting of 25 highly interconnected genes related to immune response and two additional networks composed by genes enriched in carbohydrate metabolism and in DNA metabolism and repair processes. In conclusion, we have detected candidate variants that may potentially influence COVID‑19 outcome in our cohort of patients. Further studies are needed to confirm the ultimate role of the genetic variants described in the present study on COVID‑19 severity.

  Study EGAS00001006372

• Bulk-tissue RNA-sequencing paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from post-mortem neuropathologically-confirmed control individuals.

  Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.

  Study EGAS00001006380

• Genetic Alterations in Benign Breast Biopsies of Subsequent Breast Cancer Patients

  Fibrocystic changes are associated with an increased risk of breast cancer (approximately 1.5-2 times that of the general population). Although the relative risk seems low, because of the high frequency of such changes, the absolute risk is significant. Genetic alterations have been found in fibrocystic changes with or without epithelial changes, suggesting that critical oncogenic events are occurring at an early stage. We investigated a unique collective of 17 breast cancer patients who, prior to the diagnosis of invasive breast cancer, underwent open surgical biopsy showing fibrocystic changes of the breast. Massive parallel sequencing targeting genes frequently mutated in breast cancer was performed on the fibrocystic breast tissue as well as the ensuing cancer tissue.

  Study EGAS00001003563

• SARS-CoV-2 host genetics and COVID-19 outcomes in admixed Brazilians with extreme phenotypes

  COVID-19 comprises clinical outcomes of SARS-CoV-2 infection and is highly heterogeneous, ranging from asymptomatic individuals to deceased young adults without comorbidities. There is growing evidence that host genetics play an important role in COVID-19 severity, including inborn errors of immunity, age-related inflammation and immunosenescence. This study proposes a strategy of subject’s ascertainment based on phenotypic extremes to take part in genomic studies and elucidate intrinsic risk factors involved in COVID-19 severe outcomes. Different cohorts were collected and submitted to Next-Generation Sequencing (Whole exome and whole genome sequencing).

  Study EGAS00001006376

• Disease and phenotype relevant genetic variants identified from histone acetylomes in human hearts

  Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to demonstrate statistical significance1. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising variants for disease-association. Here, we captured non-coding genetic variants by performing enhancer H3K27ac ChIP-seq in 70 human control and end-stage failing hearts, mapping out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR < 0.05) pointed to recognizable pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test2 to call out 1,680 haQTLs (FDR < 0.1). A subset of these showed significant association to gene expression, either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. Furthermore, a concordant relationship was found between the gain or disruption of specific transcription factor (TF) binding motifs, inferred from alternative alleles at the haQTLs, associated with altered H3K27ac peak heights. Finally, colocalisation of our haQTLs with heart-related GWAS datasets allowed us to identify 62 unique loci. Disease-association for these new loci may indeed be mediated through modification of H3K27-acetylation enrichment and their corresponding gene expression differences.

  Study EGAS00001003586

• A catalog of the genetic causes of Hereditary Angioedema in the Canary Islands (Spain)

  Hereditary angioedema (HAE) is a rare disease where known causes involve C1 inhibitor dysfunction or dysregulation of the kinin cascade. The updated HAE management guidelines recommend performing genetic tests to reach a precise diagnosis. Unfortunately, genetic tests are still uncommon in the diagnosis routine. Here, we characterized for the first time the genetic causes of HAE in affected families from the Canary Islands (Spain). Whole-exome sequencing data was obtained from 41 affected patients and unaffected relatives from 29 unrelated families identified in the archipelago. The Hereditary Angioedema Database Annotation (HADA) tool was used for pathogenicity classification and causal variant prioritization among the genes known to cause HAE. Manual reclassification of prioritized variants was used in those families lacking known causal variants. We detected a total of eight different variants causing HAE in this patient series, affecting essentially SERPING1 and F12 genes, one of them being a novel SERPING1 variant (c.686-12A>G) with a predicted splicing effect which was reclassified as likely pathogenic in one family. Altogether, the diagnostic yield by assessing previously reported causal genes and considering variant reclassifications according to the American College of Medical Genetics guidelines reached 66.7% (95% Confidence Interval [CI]: 30.1-91.0) in families with more than one affected member and 10.0% (95% CI: 1.8-33.1) among cases without family information for the disease. Despite the genetic causes of many patients remain to be identified, our results reinforce the need of genetic tests as first-tier diagnostic tool in this disease, as recommended by the international WAO/EAACI guidelines for the management of HAE.

  Study EGAS00001006547

• Gene copy number variation in pediatric mental illness in a general population

  We assessed the relationship of gene copy number variation (CNV) in mental health/neurodevelopmental traits and diagnoses, physical health, and cognitive biomarkers in a community sample of 7,100 unrelated European, and East Asian children and youth (Spit for Science). Diagnoses of mental health disorders were found in 17.5% of participants and 27.6% scored in the highest 10% on either or both ADHD and OCD trait measures. Clinically relevant CNVs were present in 3.9% of participants and were associated with elevated scores on a continuous measure of ADHD (p=5.0×10-3), on a cognitive biomarker of mental health (response inhibition (p=1.0×10-2)), and on prevalence of mental disorders (p=1.9×10-6, odds ratio: 3.09). With a rise of mental illness, our data establishes a baseline for delineating genetic contributors in paediatric-onset conditions.

  Study EGAS00001006659

• 5- FU treated organoids

  5-Fluorouracil (5-FU) is a chemotherapeutic drug component that is commonly used for the treatment of solid cancers. The anticancer properties of 5-FU have been attributed to interference with nucleotide synthesis and through direct incorporation into the DNA as being a pyrimidine analog. As both mechanisms of action may have a mutational impact on surviving tumor cells, we performed three independent analyses to characterize the genomic consequences of 5-FU treatment: i) in vitro treatment of intestinal organoids with 5-FU followed by whole genome sequencing, ii) genome-wide mutation analyses in tumor samples from 5-FU treated patients with breast or colorectal cancer, and iii) analysis of paired biopsies from patients treated with 5-FU between biopsies. Our results demonstrate that both in vitro and in vivo 5-FU causes a mutational pattern that is dominated by T>G substitutions in a CTT context and with strong resemblance to COSMIC signature 17. Interestingly, this signature is also found in non 5-FU treated patients, most prominently in esophageal tumors, indicating that distinct endogenous and exogenous triggers can converge into highly similar mutational signatures. Furthermore, our results suggest that 5-FU may have adverse mutagenic effects on healthy cells and contributes to genetic variability in surviving cancer cells thereby contributing to tumor evolution.

  Study EGAS00001003592

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. The repository includes the raw mass spectrometry-based proteomics data

  Study EGAS00001006712