The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.

Olfactory impairment is increasingly recognized as an early symptom in the development of Parkinson's disease. Testing olfactory function is a non-invasive method but can be time-consuming which restricts its application in clinical settings and epidemiological studies. Here, we investigate odor identification as a supportive diagnostic tool for Parkinson's disease and estimate the performance of odor subsets to allow a more rapid testing of olfactory impairment. Odor identification was assessed with 16 Sniffin' sticks in 148 Parkinson patients and 148 healthy controls. Risks of olfactory impairment were estimated with proportional odds models. Random forests were applied to classify Parkinson and non-Parkinson patients. Parkinson patients were rarely normosmic (identification of more than 12 odors; 16.8%) and identified on average seven odors whereas the reference group identified 12 odors and showed a higher prevalence of normosmy (31.1%). Parkinson patients with rigidity dominance had a twofold greater prevalence of olfactory impairment. Disease severity was associated with impairment of odor identification (per score point of the Hoehn and Yahr rating OR 1.87, 95% CI 1.26–2.77). Age-related impairment of olfaction showed a steeper gradient in Parkinson patients. Coffee, peppermint, and anise showed the largest difference in odor identification between Parkinson patients and controls. Random forests estimated a misclassification rate of 22.4% when comparing Parkinson patients with healthy controls using all 16 odors. A similar rate (23.8%) was observed when only the three aforementioned odors were applied. Our findings indicate that testing odor identification can be a supportive diagnostic tool for Parkinson's disease. The application of only three odors performed well in discriminating Parkinson patients from controls, which can facilitate a wider application of this method as a point-of-care test.

Amyotrophic lateral sclerosis (ALS), the most common adult-onset motor neuron disorder, is characterized by the progressive and selective loss of upper and lower motor neurons. Diagnosis of this disorder is based on clinical assessment, and the average survival time is less than 3 years. Injections of IgG from ALS patients into mice are known to specifically mark motor neurons. Moreover, IgG has been found in upper and lower motor neurons in ALS patients. These results led us to perform a case-control study using human protein microarrays to identify the antibody profiles of serum samples from 20 ALS patients and 20 healthy controls. We demonstrated high levels of 20 IgG antibodies that distinguished the patients from the controls. These findings suggest that a panel of antibodies may serve as a potential diagnostic biomarker for ALS.

Today, label-free mass spectrometry methods are frequently used for quantification of proteins and peptides. There have been several proposals of measurable parameters that best reflect quantities, such as peak areas as well as spectral counts. This review provides a systematic overview of the proposed methods. Owing to the shotgun proteomics approach generally used today for label-free mass spectrometry, any quantitative measure in the first place is a measure of peptide quantity. There has been no systematic research on how to best infer protein quantity from its measured peptides' quantities. The way peptide identifications are assembled to protein lists may especially lead to significantly different results in protein quantification. A further focus of this review will thus be the assembly of measured peptide quantities to a protein quantity.

The organization and storage of proteomics data are challenging issues today and even more for the rising amount of information in the future. This review article describes the advantages of using Laboratory Information Management Systems (LIMS) in proteomics laboratories. Seven typical LIMS are explored in detail to describe their role in an even bigger interrelation. They are a central part of the proteomics data workflow, starting with data generation and ending with the publication in journals and repositories. Therefore, they enable community‐wide data utilization and further Systems Biology discoveries.