In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late.

Down syndrome (DS) is mostly caused by a trisomy of the entire Chromosome 21 (Trisomy 21, T21). Here, we use SWATH mass spectrometry to quantify protein abundance and protein turnover in fibroblasts from a monozygotic twin pair discordant for T21, and to profile protein expression in 11 unrelated DS individuals and matched controls. The integration of the steadystate and turnover proteomic data indicates that protein-specific degradation of members of stoichiometric complexes is a major determinant of T21 gene dosage outcome, both within and between individuals. This effect is not apparent from genomic and transcriptomic data. The data also reveal that T21 results in extensive proteome remodeling, affecting proteins encoded by all chromosomes. Finally, we find broad, organelle-specific post-transcriptional effects such as significant downregulation of the mitochondrial proteome contributing to T21 hallmarks. Overall, we provide a valuable proteomic resource to understand the origin of DS phenotypic manifestations.

Advancements in mass spectrometry‐based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much‐needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step‐by‐step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.

OBJECTIVE: NADPH oxidase 4 (NOX4) is a reactive oxygen species (ROS) producing NADPH oxidase that regulates redox homeostasis in diverse insulin-sensitive cell types. In particular, NOX4-derived ROS is a key modulator of adipocyte differentiation and mediates insulin receptor signaling in mature adipocytes in vitro. Our study was aimed at investigating the role of NOX4 in adipose tissue differentiation, whole body metabolic homeostasis and insulin sensitivity in vivo. DESIGN: Mice with genetic ablation of NOX4 (NOX4-deficient mice) were subjected to chow or high-fat-containing diet for 12 weeks. Body weight gain, adiposity, insulin sensitivity, and adipose tissue and liver gene and protein expression were analyzed and compared with similarly treated wild-type mice. RESULTS: Here, we report that NOX4-deficient mice display latent adipose tissue accumulation and are susceptible to diet-induced obesity and early onset insulin resistance. Obesity results from accelerated adipocyte differentiation and hypertrophy, and an increase in whole body energy efficiency. Insulin resistance is associated with increased adipose tissue hypoxia, inflammation and adipocyte apoptosis. In the liver, more severe diet-induced steatosis was observed due to the lack of proper upregulation of mitochondrial fatty acid b-oxidation. CONCLUSION: These findings identify NOX4 as a regulator of metabolic homeostasis. Moreover, they indicate an anti-adipogenic role for NOX4 in vivo and reveal its function as a protector against the development of diet-induced obesity, insulin resistance and hepatosteatosis.

Cancer is mostly incurable when diagnosed at a metastatic stage, making its early detection via blood proteins of immense clinical interest. Proteomic changes in tumor tissue may lead to changes detectable in the protein composition of circulating blood plasma. Using a proteomic workflow combining N-glycosite enrichment and SWATH mass spectrometry, we generate a data resource of 284 blood samples derived from patients with different types of localized-stage carcinomas and from matched controls. We observe whether the changes in the patient's plasma are specific to a particular carcinoma or represent a generic signature of proteins modified uniformly in a common, systemic response to many cancers. A quantitative comparison of the resulting N-glycosite profiles discovers that proteins related to blood platelets are common to several cancers (e.g., THBS1), whereas others are highly cancer-type specific. Available proteomics data, including a SWATH library to study N-glycoproteins, will facilitate follow-up biomarker research into early cancer detection.