https://researchdata.se/en/catalogue Search results en Autoantibodies (autoAbs) against type I interferons (IFNs) can severely compromise antiviral defense in a broad range of severe viral infections. To investigate the mechanisms underlying autoantibody development, we performed paired scRNA-seq and scBCR-seq on sorted IFN-α2-positive and IFN-α2-negative B cells, together with scRNA-seq of other non-B immune cells. PBMCs were obtained from eight aIFN⁺ patients with severe COVID-19, five aIFN⁻ patients with severe COVID-19, five patients with APS-1, and ten healthy donors. The dataset is comprised of about 150 files and a total size of 810 GB. Mon, 28 Sep 2026 06:35:02 GMT https://researchdata.se/en/catalogue/dataset/2026-253 https://researchdata.se/en/catalogue/dataset/2026-253 Karolinska Institutet Rui Sun Qiang Pan-Hammarström This dataset contains image files from 1021 memory clinic patients that have undergone screening for 5 different neuronal autoantibodies. The files are in the .nd2 format, owned by Nikon, but can be accessed through multiple open-source platforms, for example ImageJ, BioFormats or RBioFormats. For each individual, there are five files with two duplicates (two for each antigen). Each file contains three images, 2048+2048 pixels in size, that have been taken from random locations in a well in a microscopy-grade 96-well plate. The cells in the images are 293 MSR cells (ThermoFisher). For the full protocol, see https://github.com/jtheorell/Laboratory-protocols. Thu, 04 Jun 2026 12:48:26 GMT https://researchdata.se/en/catalogue/dataset/2026-60 https://researchdata.se/en/catalogue/dataset/2026-60 Karolinska Institutet Jakob Theorell This dataset is made up of single-cell omics files from 16 individuals with myasthenia gravis at various stages of the disease and with differing disease onset age. The samples have been acquired 8+8 on a 10X Genomics Chromium 3.0 system (https://www.10xgenomics.com/platforms/chromium) on two consecutive days and all sequenced in a NovaSeq instrument (https://www.illumina.com/systems/sequencing-platforms/novaseq.html) in the same run. For each of the two experimental days, the data has been hash-tagged and then mixed. Complicating the matter somewhat, there are three sets of files (= three 10X serial IDs) for each day, each of whom contains cells that are a hashed mixture of all eight individuals from this day. Furthermore, four different kinds of data is available for each cell: RNA sequences (GE), B-cell receptor sequences (ENRB), T-cell receptor sequences (ENRT) and RNA-tagged surface-protein binding antibodies (HTO). The last portion contains a set of 10 lineage marker antibodies as well as the hashing antibodies. Further, considering that each set of files is made up of four lanes, and each lane has one file per direction, the total number of files is 6x4x4x2=192 files. This is the abstract from the forthcoming publication: The two main subgroups of autoimmune myasthenia gravis, a neuromuscular junction disorder associated with muscle weakness, are the early and late-onset forms, defined by onset before or after 50 years of age. Both carry acetylcholine-receptor autoantibodies, but differ in sex ratios, genetics and occurrence of disease-specific thymus inflammation. By applying multimodal techniques, including deep spectral cytometric phenotyping and single cell sequencing to peripheral blood and thymocyte samples we explored the possibility to discriminate the two forms by cellular immune phenotyping. Analyzing two independent cohorts we identified distinct immunological differences driven by three main lymphocyte populations. Lower frequencies of mucosa-associated invariant T cells and naïve CD8 T cells were observed in late-onset myasthenia, suggesting enhanced immune senescence. Further, a highly differentiated, canonical natural killer cell population was reduced in early-onset myasthenia, which was negatively correlated with degree of thymic inflammation. Using only the frequency of these three populations, correct myasthenia subgroup assignment could be predicted with an accuracy of 90%. These findings identify diverging cellular immune phenotypes between early and late-onset disease, indicating distinct underlying immunopathogenic processes. Together with demographic and disease subgroup-specific features, this may improve clinical classification, in turn of relevance for channeling to interventions. The dataset consists of 192 files in fastq format, compressed with gzip, and 42 files in other formats (pdf, csv, docx, and txt). Please, see documentations files, Readme.txt and file_list.csv, for details. The total size of the dataset is approximately 450 GiB. Tue, 28 Oct 2025 07:53:48 GMT https://researchdata.se/en/catalogue/dataset/2025-247 https://researchdata.se/en/catalogue/dataset/2025-247 Karolinska Institutet Jakob Theorell Fredrik Piehl This data was generated using plasma samples from the EIMS study (1). The overall goal of the EIMS study is to understand which lifestyle and genetic factors influence MS risk. The aim of this sub-study was to better understand how epstein barr virus can affect the onset of autoimmune reactions. The study includes data from 661 population based controls and 650 multiple sclerosis patients from Sweden. The data consists of antibody levels estimated using fluorescence-activated bead-based assay. Samples were run in duplicate. The levels were adjusted between plates using batch controlled samples. The values given are the average of the two run samples after batch correction. HLA genotypes have been imputed from SNP genotypes in the HlA region of chromosome 6 using HLA*IMP:02 as described previously (2). The dataset contains of the following files: - PNAS_Data_combined.csv (433 kB) - MetaData.csv - MetaDescription.docx Details about the variables in the tables can be found in the documentation file Wed, 12 Feb 2025 10:22:01 GMT https://researchdata.se/en/catalogue/dataset/2025-21 https://researchdata.se/en/catalogue/dataset/2025-21 Karolinska Institutet Ingrid Skelton Kockum Transcriptions of interviews (in Swedish) where all personal information that could potentially enable identification of individuals has been removed. Seven textfiles numbered from 1-7 containing manual transcripts from interviews with children and adolescents in Sweden. Files are named Intervju1.txt, Intervju2.txt, etc. but file numbers are arbitrarily assigned and have no identifying function. Wed, 11 Oct 2023 09:16:14 GMT https://researchdata.se/en/catalogue/dataset/2023-197 https://researchdata.se/en/catalogue/dataset/2023-197 Stockholm University Noam Ringer To improve our understanding of MS pathology and heterogeneity and provide new strategies for biomarkers and treatments development we carried out a genome-wide small non-coding RNA analysis. The analysis was performed in paired peripheral blood mononuclear cells, plasma, cerebrospinal fluid (CSF) cells and cell-free CSF from 29 MS patients and 16 controls using next-generation sequencing. We aimed to detect differentially expressed small non-coding RNAs between MS and controls. The data contains unique molecular identifier (UMI) count information for each transcript. The small non-coding RNA analysis was performed in paired peripheral blood mononuclear cells, plasma, cerebrospinal fluid (CSF) cells and cell-free CSF from 29 MS patients and 16 controls using next-generation sequencing. One INDC control was missing a CSF cell and cell-free CSF sample and one NINDC control was missing a PBMC and plasma sample. Small non-coding RNAs were isolated from 300 ul of plasma or CSF using the miRCURY RNA isolation kit for biofluids (Exiqon, Denmark) or from CSF cells and peripheral blood mononuclear cells precipitate using the miRNAeasy micro kit (Qiagen, Germany). Small non-coding RNA libraries were prepared as previously described at PMID: 27798564. The libraries were sequenced on eight lanes of HiSeq2500. Preprocessing and alignment were done according to PMID: 30250291. The "Unique molecular identifier_sncRNAs_analysis_MS" file contains unique molecular identifier count information for each small non-coding RNA transcript as well as other types of transcripts identified in the sequencing libraries from 44 individuals and 4 compartments (PBMCs, CSF cells, plasma, cell-free CSF). Altogether 176 samples. The metafile contains information about the disease status, sex, age for all MS patients and controls. The "readme" explains the contents of the data files and contains the variables list. Thu, 08 Apr 2021 09:30:03 GMT https://researchdata.se/en/catalogue/dataset/snd1150-1 https://researchdata.se/en/catalogue/dataset/snd1150-1 Karolinska Institutet Galina Zheleznyakova Eliane Piket Maria Needhamsen Maja Jagodic Swedish - Finnish glossary with words relating to diabetes. Contains approximately 180 entries. Published in Kieliviesti 4/2001. 2001. Wed, 14 Oct 2020 12:39:15 GMT https://researchdata.se/en/catalogue/dataset/ext0354-1 https://researchdata.se/en/catalogue/dataset/ext0354-1 Institute for Language and Folklore Diabetes Prediction in Scania (DiPiS) aims to determine why children develop type 1 diabetes. By being able to predict which children are at risk of developing diabetes, the hope is to prevent the onset of the disease in the future. DiPiS was conducted in two stages: Stage 1: Examination of the hereditary risk for type 1 diabetes in all newborns in Scania. This stage took place from September 2000 to September 2004. During this stage, almost 36,000 children were examined. Stage 2: Follow-up of a group of children with hereditary risk. Approximately 5,000 children were followed. Participants in the follow-up study provided blood samples once a year and also completed a questionnaire. Children with multiple antibodies are at an increased risk of developing type 1 diabetes and were therefore monitored more frequently. The children were followed until the age of 15. Objective: To determine factors that can predict autoimmune (type 1) diabetes in children. Thu, 12 Sep 2013 14:32:05 GMT https://researchdata.se/en/catalogue/dataset/ext0081-1 https://researchdata.se/en/catalogue/dataset/ext0081-1 Lund University Åke Lernmark Helena Larsson Umbilical cord blood was taken from 48000 new born children in the county of Skåne in order to determine the risk of hereditary type 1 diabetes. Of the screened children 7,4% had an increased risk. Of these, 2,525 children participate in the study follow-up part. TEDDY children will be followed until they are 15 years old. Up until 4 years of age, the child visits a TEDDY office every 3 months. After 4 years of age, the visits takes place two times per year. If the child shows signs of an autoimmune process started, that the child has acquired antibodies in the blood, the child are followed-up every three months in the future. The study includes blood, feaces, urine and saliva samples as well as samples from the nails. Height and weight are recorded and children's physical activity is measured. Food Diary conducted during periods and sample on the family's tap water is taken. Further interviews are conducted and the parents respond to different questionnaires. Purpose: To identify environmental exposures that are associated with increased risk of developing autoantibodies against pancreatic islet beta cells in children. Children who develop two or more islet cell autoantibodies develop type 1 diabetes, which may take months or years. The secondary aim is to study the mechanisms behind why some children that developed two or more islet cell autoantibodies eventually develop diabetes. Wed, 11 Sep 2013 14:32:05 GMT https://researchdata.se/en/catalogue/dataset/ext0080-1 https://researchdata.se/en/catalogue/dataset/ext0080-1 Lund University Åke Lernmark ANDIS is a combined research and quality assurance project with the long term aim of introducing precision medicine in diabetes. In connection with a visit to your doctor or diabetes nurse personal identification number, name, address, date of diagnosis, initial and current diabetes treatment, time of start of diabetes treatment, weight and height, possible diabetes during pregnancy, information on the prevalence of diabetes in the family as well as information about the country of birth of the study person and his/her parents was registered. Upon registration, blood samples for determination of GAD antibodies and C-peptide as well as for DNA analysis are taken. The DNA sample is used to classify the disease into subtypes, and to investigate hereditary causes of diabetes, diabetic complications and other medical conditions associated with diabetes. One blood sample is stored for possible future analysis. If the study person previously have given consent for registration of his or her data in the National Diabetes Register (NDR) the study person is asked whether this information can be linked to the ANDIS database on an annual basis. The ANDIS registry is also linked with the Region Skåne Care Database and the register for prescribed drugs to add information about the use of medications and diabetic complications. Ongoing study, currently> 11,000 patients (January 2015). Purpose: To register all new cases of diabetes in Scania and improve diagnosis and treatment strategies. The cohort cover the full spectrum of diabetes in Region Skåne. It has unique representation since a majority of all health care providers, hospitals and clinics participate. Fri, 06 Sep 2013 08:48:32 GMT https://researchdata.se/en/catalogue/dataset/ext0057-1 https://researchdata.se/en/catalogue/dataset/ext0057-1 Lund University Leif Groop