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Publications (10 of 16) Show all publications
Bueno Álvez, M., Bergström, S., Kenrick, J., Johansson, E., Altay, Ö., Sköld, H., . . . et al., . (2025). A human pan-disease blood atlas of the circulating proteome. Science, 390(6779), Article ID eadx2678.
Open this publication in new window or tab >>A human pan-disease blood atlas of the circulating proteome
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2025 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 390, no 6779, article id eadx2678Article in journal (Refereed) Published
Abstract [en]

The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. In this study, we present a pan-disease resource to enable the study of diverse disease phenotypes within a harmonized proteomics dataset. By profiling protein concentrations across 59 diseases and healthy cohorts, we identified proteins associated with age, sex, and body mass index, as well as disease-specific signatures. This study highlights shared and distinct protein patterns across conditions, demonstrating the power of a unified proteomics approach to uncover biological insights. The dataset, covering 8262 individuals and up to 5416 proteins, serves as an online resource for exploring disease-specific protein profiles and advancing precision medicine research.

Place, publisher, year, edition, pages
American Association for the Advancement of Science (AAAS), 2025
National Category
Medical Biotechnology (Focus on Cell Biology, (incl. Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-378079 (URN)10.1126/science.adx2678 (DOI)001643421200001 ()41066540 (PubMedID)2-s2.0-105025246161 (Scopus ID)
Note

QC 20260318

Available from: 2026-03-18 Created: 2026-03-18 Last updated: 2026-04-27Bibliographically approved
Shi, M., Shi, M., Karlsson, M., Alvez, M. B., Jin, H., Yuan, M., . . . et al., . (2025). A resource for whole-body gene expression map of human tissues based on integration of single cell and bulk transcriptomics. Genome Biology, 26(1), Article ID 152.
Open this publication in new window or tab >>A resource for whole-body gene expression map of human tissues based on integration of single cell and bulk transcriptomics
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2025 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 26, no 1, article id 152Article in journal (Refereed) Published
Abstract [en]

New technologies enable single-cell transcriptome analysis, mapping genome-wide expression across the human body. Here, we present an extended analysis of protein-coding genes in all major human tissues and organs, combining single-cell and bulk transcriptomics. To enhance transcriptome depth, 31 tissues were analyzed using a pooling method, identifying 557 unique cell clusters, manually annotated by marker gene expression. Genes were classified by body-wide expression and validated through antibody-based profiling. All results are available in the updated open-access Single Cell Type section of the Human Protein Atlas for genome-wide exploration of genes, proteins, and their spatial distribution in cells.

Place, publisher, year, edition, pages
Springer Nature, 2025
Keywords
Cell type classification, Gene expression mapping, Human Protein Atlas, Single-cell
National Category
Bioinformatics and Computational Biology Cell and Molecular Biology Medical Genetics and Genomics Medical Biotechnology (Focus on Cell Biology, (incl. Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-366187 (URN)10.1186/s13059-025-03616-4 (DOI)001502167900001 ()40462185 (PubMedID)2-s2.0-105007441526 (Scopus ID)
Note

Not duplicate with DiVA 1959447

QC 20250707

Available from: 2025-07-07 Created: 2025-07-07 Last updated: 2025-08-15Bibliographically approved
Huang, J., Lin, L., Dong, Z., Yang, L., Zheng, T., Gu, W., . . . Luo, Y. (2021). A porcine brain-wide RNA editing landscape. Communications Biology, 4(1), Article ID 717.
Open this publication in new window or tab >>A porcine brain-wide RNA editing landscape
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2021 (English)In: Communications Biology, E-ISSN 2399-3642, Vol. 4, no 1, article id 717Article in journal (Refereed) Published
Abstract [en]

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by ADAR enzymes, is an essential post-transcriptional modification. Although hundreds of thousands of RNA editing sites have been reported in mammals, brain-wide analysis of the RNA editing in the mammalian brain remains rare. Here, a genome-wide RNA-editing investigation is performed in 119 samples, representing 30 anatomically defined subregions in the pig brain. We identify a total of 682,037 A-to-I RNA editing sites of which 97% are not identified before. Within the pig brain, cerebellum and olfactory bulb are regions with most edited transcripts. The editing level of sites residing in protein-coding regions are similar across brain regions, whereas region-distinct editing is observed in repetitive sequences. Highly edited conserved recoding events in pig and human brain are found in neurotransmitter receptors, demonstrating the evolutionary importance of RNA editing in neurotransmission functions. Although potential data biases caused by age, sex or health status are not considered, this study provides a rich resource to better understand the evolutionary importance of post-transcriptional RNA editing. Huang et al performed a genome-wide RNA editing investigation in the porcine brain in which they found over 680,000 A-to-I RNA editing sites. They identified conserved recoding events between pig and human brains thus providing an extensive resource to aid our understanding of the evolutionary importance of post-transcriptional RNA editing.

Place, publisher, year, edition, pages
Springer Nature, 2021
National Category
Biochemistry Molecular Biology Cell and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-298865 (URN)10.1038/s42003-021-02238-3 (DOI)000663559200010 ()34112917 (PubMedID)2-s2.0-85107566342 (Scopus ID)
Note

QC 20210720

Available from: 2021-07-20 Created: 2021-07-20 Last updated: 2025-02-20Bibliographically approved
Remnestål, J., Bergström, S., Olofsson, J., Sjöstedt, E., Uhlén, M., Blennow, K., . . . Månberg, A. (2021). Association of CSF proteins with tau and amyloid beta levels in asymptomatic 70-year-olds. Alzheimer's Research & Therapy, 13(1), Article ID 54.
Open this publication in new window or tab >>Association of CSF proteins with tau and amyloid beta levels in asymptomatic 70-year-olds
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2021 (English)In: Alzheimer's Research & Therapy, E-ISSN 1758-9193, Vol. 13, no 1, article id 54Article in journal (Refereed) Published
Abstract [en]

Background Increased knowledge of the evolution of molecular changes in neurodegenerative disorders such as Alzheimer's disease (AD) is important for the understanding of disease pathophysiology and also crucial to be able to identify and validate disease biomarkers. While several biological changes that occur early in the disease development have already been recognized, the need for further characterization of the pathophysiological mechanisms behind AD still remains. Methods In this study, we investigated cerebrospinal fluid (CSF) levels of 104 proteins in 307 asymptomatic 70-year-olds from the H70 Gothenburg Birth Cohort Studies using a multiplexed antibody- and bead-based technology. Results The protein levels were first correlated with the core AD CSF biomarker concentrations of total tau, phospho-tau and amyloid beta (A beta 42) in all individuals. Sixty-three proteins showed significant correlations to either total tau, phospho-tau or A beta 42. Thereafter, individuals were divided based on CSF A beta 42/A beta 40 ratio and Clinical Dementia Rating (CDR) score to determine if early changes in pathology and cognition had an effect on the correlations. We compared the associations of the analysed proteins with CSF markers between groups and found 33 proteins displaying significantly different associations for amyloid-positive individuals and amyloid-negative individuals, as defined by the CSF A beta 42/A beta 40 ratio. No differences in the associations could be seen for individuals divided by CDR score. Conclusions We identified a series of transmembrane proteins, proteins associated with or anchored to the plasma membrane, and proteins involved in or connected to synaptic vesicle transport to be associated with CSF biomarkers of amyloid and tau pathology in AD. Further studies are needed to explore these proteins' role in AD pathophysiology.

Place, publisher, year, edition, pages
BMC, 2021
Keywords
Preclinical Alzheimer&#8217, s disease, Affinity proteomics, CSF markers, Brain-enriched proteins, Multidisciplinary epidemiological studies, AD pathophysiology
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-292272 (URN)10.1186/s13195-021-00789-5 (DOI)000624542700001 ()33653397 (PubMedID)2-s2.0-85101906750 (Scopus ID)
Note

QC 20210401

Available from: 2021-04-01 Created: 2021-04-01 Last updated: 2024-03-18Bibliographically approved
Grapotte, M., Forsberg, M., Oksvold, P., Sivertsson, Å., Sjöstedt, E., Uhlén, M., . . . et al., . (2021). Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network. Nature Communications, 12(1), Article ID 3297.
Open this publication in new window or tab >>Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network
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2021 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 12, no 1, article id 3297Article in journal (Refereed) Published
Abstract [en]

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

Place, publisher, year, edition, pages
Springer Nature, 2021
National Category
Biochemistry Molecular Biology
Identifiers
urn:nbn:se:kth:diva-309717 (URN)10.1038/s41467-021-23143-7 (DOI)000660869500001 ()34078885 (PubMedID)2-s2.0-85107388625 (Scopus ID)
Note

Correction in: DOI 10.1038/s41467-022-28758-y, WOS:000771136200018

QC 20250402

Available from: 2022-03-09 Created: 2022-03-09 Last updated: 2025-04-02Bibliographically approved
Sjostedt, E., Kolnes, A. J., Olarescu, N. C., Mitsios, N., Hikmet, F., Sivertsson, Å., . . . Casar-Borota, O. (2021). TGFBR3L-An Uncharacterised Pituitary Specific Membrane Protein Detected in the Gonadotroph Cells in Non-Neoplastic and Tumour Tissue. Cancers, 13(1), Article ID 114.
Open this publication in new window or tab >>TGFBR3L-An Uncharacterised Pituitary Specific Membrane Protein Detected in the Gonadotroph Cells in Non-Neoplastic and Tumour Tissue
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2021 (English)In: Cancers, ISSN 2072-6694, Vol. 13, no 1, article id 114Article in journal (Refereed) Published
Abstract [en]

Simple Summary: Pituitary neuroendocrine tumours originate from the endocrine cells of the anterior pituitary gland and may develop from any of the cell lineages responsible for producing the different pituitary hormones. The details related to tumour differentiation and hormone production in these tumours are not fully understood. The aim of our study was to investigate an uncharacterised pituitary enriched protein, transforming growth factor beta-receptor 3 like (TGFBR3L). The TGFBR3L protein is highly expressed in the pituitary compared to other organs. We found the protein to be gonadotroph-specific, i.e., detected in the cells that express follicle-stimulating and luteinizing hormones (FSH/LH). The gonadotroph-specific nature of TGFBR3L, a correlation to both FSH and LH as well as an inverse correlation to membranous E-cadherin and oestrogen receptor beta suggests a role in gonadotroph cell development and function and, possibly, tumour progression. Here, we report the investigation of transforming growth factor beta-receptor 3 like (TGFBR3L), an uncharacterised pituitary specific membrane protein, in non-neoplastic anterior pituitary gland and pituitary neuroendocrine tumours. A polyclonal antibody produced within the Human Protein Atlas project (HPA074356) was used for TGFBR3L staining and combined with SF1 and FSH for a 3-plex fluorescent protocol, providing more details about the cell lineage specificity of TGFBR3L expression. A cohort of 230 pituitary neuroendocrine tumours were analysed. In a subgroup of previously characterised gonadotroph tumours, correlation with expression of FSH/LH, E-cadherin, oestrogen (ER) and somatostatin receptors (SSTR) was explored. TGFBR3L showed membranous immunolabeling and was found to be gonadotroph cell lineage-specific, verified by co-expression with SF1 and FSH/LH staining in both tumour and non-neoplastic anterior pituitary tissues. TGFBR3L immunoreactivity was observed in gonadotroph tumours only and demonstrated intra-tumour heterogeneity with a perivascular location. TGFBR3L immunostaining correlated positively to both FSH (R = 0.290) and LH (R = 0.390) immunostaining, and SSTR3 (R = 0.315). TGFBR3L correlated inversely to membranous E-cadherin staining (R = -0.351) and oestrogen receptor beta mRNA (R = -0.274). In conclusion, TGFBR3L is a novel pituitary gland specific protein, located in the membrane of gonadotroph cells in non-neoplastic anterior pituitary gland and in a subset of gonadotroph pituitary tumours.

Place, publisher, year, edition, pages
MDPI AG, 2021
Keywords
gonadotroph cells, pituitary gland, pituitary neuroendocrine tumours, membrane protein, immunohistochemistry, hormone secretion
National Category
Clinical Medicine
Identifiers
urn:nbn:se:kth:diva-289514 (URN)10.3390/cancers13010114 (DOI)000605901700001 ()33396509 (PubMedID)2-s2.0-85100180643 (Scopus ID)
Note

QC 20210202

Available from: 2021-02-02 Created: 2021-02-02 Last updated: 2024-03-15Bibliographically approved
Sjöstedt, E., Zhong, W., Fagerberg, L., Karlsson, M., Mitsios, N., Adori, C., . . . Mulder, J. (2020). An atlas of the protein-coding genes in the human, pig, and mouse brain. Science, 367(6482), 1090-+, Article ID eaay5947.
Open this publication in new window or tab >>An atlas of the protein-coding genes in the human, pig, and mouse brain
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2020 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 367, no 6482, p. 1090-+, article id eaay5947Article in journal (Refereed) Published
Abstract [en]

The brain, with its diverse physiology and intricate cellular organization, is the most complex organ of the mammalian body. To expand our basic understanding of the neurobiology of the brain and its diseases, we performed a comprehensive molecular dissection of 10 major brain regions and multiple subregions using a variety of transcriptomics methods and antibody-based mapping. This analysis was carried out in the human, pig, and mouse brain to allow the identification of regional expression profiles, as well as to study similarities and differences in expression levels between the three species. The resulting data have been made available in an open-access Brain Atlas resource, part of the Human Protein Atlas, to allow exploration and comparison of the expression of individual protein-coding genes in various parts of the mammalian brain.

Place, publisher, year, edition, pages
American Association for the Advancement of Science (AAAS), 2020
National Category
Medical Genetics and Genomics
Identifiers
urn:nbn:se:kth:diva-271745 (URN)10.1126/science.aay5947 (DOI)000520018400034 ()32139519 (PubMedID)2-s2.0-85081532587 (Scopus ID)
Note

QC 20200408

Available from: 2020-04-08 Created: 2020-04-08 Last updated: 2025-02-10Bibliographically approved
Sjöstedt, E., Sivertsson, Å., Norradin, F. H., Katona, B., Näsström, Å., Vuu, J., . . . Lindskog, C. (2018). Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues. Journal of Proteome Research, 17(12), 4127-4137
Open this publication in new window or tab >>Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues
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2018 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 17, no 12, p. 4127-4137Article in journal (Refereed) Published
Abstract [en]

A large portion of human proteins are referred to as missing proteins, defined as protein-coding genes that lack experimental data on the protein level due to factors such as temporal expression, expression in tissues that are difficult to sample, or they actually do not encode functional proteins. In the present investigation, an integrated omics approach was used for identification and exploration of missing proteins. Transcriptomics data from three different sourcesthe Human Protein Atlas (HPA), the GTEx consortium, and the FANTOM5 consortiumwere used as a starting point to identify genes selectively expressed in specialized tissues. Complementing the analysis with profiling on more specific tissues based on immunohistochemistry allowed for further exploration of cell-type-specific expression patterns. More detailed tissue profiling was performed for >300 genes on complementing tissues. The analysis identified tissue-specific expression of nine proteins previously listed as missing proteins (POU4F1, FRMD1, ARHGEF33, GABRG1, KRTAP2-1, BHLHE22, SPRR4, AVPR1B, and DCLK3), as well as numerous proteins with evidence of existence on the protein level that previously lacked information on spatial resolution and cell-type- specific expression pattern. We here present a comprehensive strategy for identification of missing proteins by combining transcriptomics with antibody-based proteomics. The analyzed proteins provide interesting targets for organ-specific research in health and disease.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2018
Keywords
missing proteins, transcriptomics, proteomics, protein localization, immunohistochemistry, antibodies, tissue profiling
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Biological Sciences
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-236474 (URN)10.1021/acs.jproteome.8b00406 (DOI)000452930000010 ()30272454 (PubMedID)2-s2.0-85055105364 (Scopus ID)
Note

QC 20181018

Available from: 2018-10-17 Created: 2018-10-17 Last updated: 2022-10-24Bibliographically approved
Uhlén, M., Zhang, C., Lee, S., Sjöstedt, E., Fagerberg, L., Bidkhori, G., . . . Ponten, F. (2017). A pathology atlas of the human cancer transcriptome. Science, 357(6352), 660-+
Open this publication in new window or tab >>A pathology atlas of the human cancer transcriptome
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2017 (English)In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 357, no 6352, p. 660-+Article in journal (Refereed) Published
Abstract [en]

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

Place, publisher, year, edition, pages
American Association for the Advancement of Science, 2017
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:kth:diva-214334 (URN)10.1126/science.aan2507 (DOI)000407793600028 ()28818916 (PubMedID)2-s2.0-85028362951 (Scopus ID)
Funder
Swedish Cancer SocietyScience for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg FoundationSwedish Research Council
Note

QC 20170913

Available from: 2017-09-13 Created: 2017-09-13 Last updated: 2024-03-15Bibliographically approved
Sjöstedt, E., Bollerslev, J., Mulder, J., Lindskog, C., Ponten, F. & Casar-Borota, O. (2017). A specific antibody to detect transcription factor T-Pit: a reliable marker of corticotroph cell differentiation and a tool to improve the classification of pituitary neuroendocrine tumours [Letter to the editor]. Acta Neuropathologica, 134(4), 675-677
Open this publication in new window or tab >>A specific antibody to detect transcription factor T-Pit: a reliable marker of corticotroph cell differentiation and a tool to improve the classification of pituitary neuroendocrine tumours
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2017 (English)In: Acta Neuropathologica, ISSN 0001-6322, E-ISSN 1432-0533, Vol. 134, no 4, p. 675-677Article in journal, Letter (Refereed) Published
Place, publisher, year, edition, pages
SPRINGER, 2017
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-214869 (URN)10.1007/s00401-017-1768-9 (DOI)000409369000012 ()28823042 (PubMedID)2-s2.0-85027889508 (Scopus ID)
Note

QC 20171024

Available from: 2017-10-24 Created: 2017-10-24 Last updated: 2024-03-15Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0327-7377

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