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• Genetic contributions of lupus nephritis in a multi-ethnic cohort of systemic lupus erythematosus (SLE)

  Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE) and it occurs at a much higher rate in patients that are not of European descent. The purpose of this study is to identify genetic variants contributing to the risk of LN in a multi-ethnic cohort of SLE patients. We used a comprehensive genome-wide screen and 1244 SLE patients from 5 different ethnic groups. In genome-wide gene-based and candidate SNP analyses, we found distinct genes and pathways, and established risk SNPs associated with lupus nephritis for each ethnic group. This study represents progress in elucidating the genetic underpinnings driving LN among SLE patients of different ethnic groups.

  Study phs001609

• Diabetes Multi-Omic Investigation of Drug Response (DIAMOND)

  The Diabetes Multi-omic Investigation of Drug Response (DIAMOND) cohort is a population-based cohort of individuals with type-2 diabetes (T2D) who receive their care through a large health system serving southeast Michigan and metropolitan Detroit. The cohort represents the diversity of the population from which it was created. Because of their health plan membership, participants have a rich dataset of longitudinal clinical health information related to their care. The intent of the DIAMOND study is to use genomic profiling, drug exposure information, and electronic health record (EHR) derived outcome data to identify genetic predictors of treatment response. Genome-wide genotyping was performed using the AxiomTM Precision Medicine Research Array (ThermoFisher Scientific Inc.).

  Study phs003350

• A Combined Omics and Tissue Biobank for Paediatric Cancers

  The Swedish Childhood Tumour Biobank (BTB) is a nonprofit national infrastructure for samples and genomic data collection from pediatric patients diagnosed with central nervous system and other solid tumours in Sweden. Fresh frozen tumour tissue and patient’s matched blood are collected from affected patients and genomic data is continuously generated and made available for approved medical research projects. We expect that the accessibility of biological samples and/or data to the research community will contribute to further advances in the understanding of tumour biology, which in turn will impact many aspects of clinical care of children with cancer, by refining diagnosis and/or identifying oncogenic drivers and therapeutic targets.

  Study EGAS50000000209

• Transcriptomic profiling of granulosa cells from IVF patients at different ages

  Two major factors contributing to reduced fertility is use of exogenous hormones and old age. Here, we sequenced RNA from granulosa cell samples from human patients undergoing in vitro fertilization to test how hormonally stimulated cells' transcriptional profiles change with age. All patients were normal responders referred for male infertility and were grouped into two age groups. The gene expression differences in aging were compared to mouse data (previous experiments, see ArrayExpress E-MTAB-13479) and the results are published in the article "Granulosa cell transcription is similarly impacted by superovulation and aging and predicts early embryonic trajectories". Corresponding count tables are available in ArrayExpress (E-MTAB-13496).

  Study EGAS50000000824

• Biomarker Research for Anti EGFR Monoclonal Antibodies by Comprehensive Cancer Genomics

  The purpose of this study is to explore new biomarkers for predicting the effectiveness of an anti-epidermal growth factor receptor (anti-EGFR) antibody in patients with advanced colorectal cancer. The investigation involves analyzing the entire exome, conducting a genome-wide association study (GWAS), and analyzing copy number variations (CNVs) using single nucleotide polymorphism (SNP) arrays. Genetic material from both cancerous and non-cancerous tissues, as well as blood samples from patients who received the antibody treatment, will be used. The goal is to identify genetic mutations and SNPs associated with treatment efficacy and adverse events, and to assess the correlation between their presence and treatment effectiveness using statistical methods.

  Study JGAS000779

• Proteomic measurements in BioBank Japan

  The BioBank Japan (BBJ) is a biobank established in the Institute of Medical Science, the University of Tokyo to collect clinical information and biological materials (DNA and serum samples). It collected about 200 thousand participants of 47 diseases started in 2003 (BBJ 1st cohort), and 67 thousand participants of 38 diseases started in 2013 (BBJ 2nd cohort), both in collaboration with 12 medical centers through the MEXT and AMED's "The BioBank Japan Project." This project is aiming at further utilization of the materials, and clinical and genomic information managed by BBJ to contribute to precision medicine by storing, managing, and providing the materials and data, as well as identifying biomarkers associated with disease risk, prognosis, and drug sensitivity.

  Study JGAS000785

• Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

  Patients with amyotrophic lateral sclerosis (ALS), a rare fatal neurodegenerative disease, face a lengthy diagnostic process, and, although most survive only 2 to 4 years from diagnosis, lack information regarding their specific anticipated disease course due to a lack of prognostic tools. Although ALS is a heterogeneous disease of varied etiology, peripheral immune system dysfunction is ubiquitous, reflected in altered whole blood transcriptome. Herein, we profiled whole blood gene expression by RNA sequencing in a large cohort of ALS cases versus controls. Several machine learning classifiers trained on our gene expression dataset predicted case-control status and survival, and integration analysis with external cohorts led to the identification of drug candidates.

  Study EGAS50000001019

• Transcriptomic profiling of proximal and distal regions of human long head biceps tendon

  Tendinopathy is a prevalent musculoskeletal disorder marked by extracellular matrix disorganization, collagen remodeling, vascular ingrowth, and pain, yet its underlying molecular mechanisms remain insufficiently defined. The long head of the biceps tendon (LHBT) is particularly prone to mechanical overload and early degenerative changes, making it a relevant model for studying tendon pathology. In this study, we aimed to characterize region-specific gene expression changes along the LHBT to better understand the molecular basis of degeneration. We collected paired proximal and distal LHBT tissue from patients undergoing rotator cuff repair surgery and performed bulk RNA sequencing. This approach enables the identification of degeneration-associated transcriptional signatures while minimizing inter-patient variability.

  Study EGAS50000001454

• CAGE analysis for non-small cell lung carcinoma

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). The result was followed up by by immunohistochemical analysis (IHC) in an independent group.

  Study JGAS000070

• The role of gut microbiota in metabolic diseases

  Diabetes is a major disease in the elderly and is responsible for increased risk of myocardial infarction and stroke. Recently, the relationship between microbiota and diabetes has been reported in animals and humans. In this study, blood, stool, and saliva samples were collected from examinees at the University of Tokyo Health Screening Center, and 16S rRNA and metagenomic analyses were performed to determine the variation of microbiota. Furthermore, metabolome analysis and transcriptome analysis (CAGE analysis) using blood were performed to reveal changes in host metabolites and gene expression. By comparing the host- and bacteria- derived information with the metabolic parameters, we analyzed whether microbiota can be a predictor of metabolic diseases.

  Study JGAS000569