1. |
- Nicolas, Aude, et al.
(author)
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Genome-wide Analyses Identify KIF5A as a Novel ALS Gene
- 2018
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In: Neuron. - : Cell Press. - 0896-6273 .- 1097-4199. ; 97:6, s. 1268-1283.e6
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Journal article (peer-reviewed)abstract
- To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.
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2. |
- Adhikari, Subash, et al.
(author)
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A high-stringency blueprint of the human proteome
- 2020
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Research review (peer-reviewed)abstract
- The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP’s tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.
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3. |
- Aebersold, Ruedi, et al.
(author)
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How many human proteoforms are there?
- 2018
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In: Nature Chemical Biology. - : NATURE PUBLISHING GROUP. - 1552-4450 .- 1552-4469. ; 14:3, s. 206-214
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Journal article (peer-reviewed)abstract
- Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA-and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.
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4. |
- Burnum-Johnson, Kristin E., et al.
(author)
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New Views of Old Proteins : Clarifying the Enigmatic Proteome
- 2022
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In: Molecular & Cellular Proteomics. - : Elsevier BV. - 1535-9476 .- 1535-9484. ; 21:7
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Journal article (peer-reviewed)abstract
- All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.
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5. |
- Byström, Sanna
(author)
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Affinity assays for profiling disease-associated proteins in human plasma
- 2017
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Doctoral thesis (other academic/artistic)abstract
- Affinity-based proteomics offers opportunities for the discovery and validation of disease-associated proteins in human body fluids. This thesis describes the use of antibody-based immunoassays for multiplexed analysis of proteins in human plasma, serum and cerebrospinal fluid (CSF). This high-throughput method was applied with the objective to identify proteins associated to clinical variables. The main work in this thesis was conducted within the diseases of multiple sclerosis and malignant melanoma, as well as mammographic density, a risk factor for breast cancer.The suspension bead array (SBA) technology has been the main method for the work presented in this thesis (Paper I-IV). SBA assays and other affinity proteomic technologies were introduced for protein profiling of sample material obtained from clinical collaborators and biobanks. Perspectives on the validation of antibody selectivity by means of e.g. immuno-capture mass spectrometry are also provided.Paper I describes the development and application of a protocol for multiplexed pro- tein profiling of CSF. The analysis of 340 CSF samples from patients with multiple sclerosis and other neurological disease revealed proteins with potential association to disease progression (GAP43) and inflammation (SERPINA3). Paper II continued on this work with an extended investigation of more than 1,000 clinical samples and included both plasma and CSF collected from the same patients. Comparison of disease subtypes and controls revealed five plasma proteins of potential diagnostic relevance, such as IRF8 and GAP43. The previously reported associations for GAP43 and SERPINA3 in CSF was confirmed. Subsequent immunohistochemical analysis of post-mortem brain tissue revealed differential protein expression in disease affected areas. In Paper III, 150 serum samples from patients with cutaneous malignant melanoma were analyzed. Protein profiles from antibody bead arrays suggested three proteins (RGN, MTHFD1L, STX7) of differential abundance between patients with no disease recurrence and low tumor thickness (T-stage 1 and 2) compared to patients with high tumor thickness (T-stage 3 and 4) and disease recurrence. We observed MTHFD1L expression in tissue of a majority of patients, while expression of STX7 in melanoma tissue had been reported previously. Paper IV describes the analysis of protein in plasma in relation to mammographic breast density (MD), one of the strongest risk factors for the development of breast cancers. More than 1,300 women without prior history of breast cancer were screened. Linear associations to MD in two independent sample sets were found for 11 proteins, which are expressed in the breast and involved in tissue homeostasis, DNA repair, cancer development and/or progression in MD.In conclusion, this thesis describes the use of multiplexed antibody bead arrays for protein profiling of serum, plasma and CSF, and it shortlists disease associated proteins for further validation studies.
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7. |
- Omenn, Gilbert S., et al.
(author)
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Progress on Identifying and Characterizing the Human Proteome : 2018 Metrics from the HUPO Human Proteome Project
- 2018
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 17:12, s. 4031-4041
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Journal article (peer-reviewed)abstract
- The Human Proteome Project (HPP) annually reports on progress throughout the field in credibly identifying and characterizing the human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2018-01-17, the baseline for this sixth annual HPP special issue of the Journal of Proteome Research, contains 17 470 PE1 proteins, 89% of all neXtProt predicted PE1-4 proteins, up from 17 008 in release 2017-01-23 and 13 975 in release 2012-02-24. Conversely, the number of neXtProt PE2,3,4 missing proteins has been reduced from 2949 to 2579 to 2186 over the past two years. Of the PEI proteins, 16 092 are based on mass spectrometry results, and 1378 on other kinds of protein studies, notably protein protein interaction findings. PeptideAtlas has 15 798 canonical proteins, up 625 over the past year, including 269 from SUMOylation studies. The largest reason for missing proteins is low abundance. Meanwhile, the Human Protein Atlas has released its Cell Atlas, Pathology Atlas, and updated Tissue Atlas, and is applying recommendations from the International Working Group on Antibody Validation. Finally, there is progress using the quantitative multiplex organ-specific popular proteins targeted proteomics approach in various disease categories.
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8. |
- Omenn, Gilbert S., et al.
(author)
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Research on the Human Proteome Reaches a Major Milestone : > 90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project
- 2020
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 19:12, s. 4735-4746
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Journal article (peer-reviewed)abstract
- According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.
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9. |
- Omenn, Gilbert S., et al.
(author)
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The 2023 Report on the Proteome from the HUPO Human Proteome Project
- 2024
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 23:2, s. 532-549
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Research review (peer-reviewed)abstract
- Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1–4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.
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10. |
- Ruiz-Romero, Cristina, et al.
(author)
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Mining the Proteome Associated with Rheumatic and Autoimmune Diseases
- 2019
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 18:12, s. 4231-4239
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Journal article (peer-reviewed)abstract
- A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjogren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders.
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