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: Obesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, outbred heterogeneous stock (HS) rats were used in controlled environmental conditions to fine‐map novel genetic modifiers of adiposity.Methods: Body weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome‐wide. Quantitative trait loci (QTL) were identified by genome‐wide association of imputed single‐nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively.Results: HS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine‐mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus.Conclusions: These data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits.

Recent large-scale multiomics studies suggest that genetic factors influence the chemical individuality of donated blood. To examine this concept, we performed metabolomics analyses of 643 blood units from volunteers who donated units of packed red blood cells (RBCs) on 2 separate occasions. These analyses identified carnitine metabolism as the most reproducible pathway across multiple donations from the same donor. We also measured l-carnitine and acyl-carnitines in 13 091 packed RBC units from donors in the Recipient Epidemiology and Donor Evaluation study. Genome-wide association studies against 879 000 polymorphisms identified critical genetic factors contributing to interdonor heterogeneity in end-of-storage carnitine levels, including common nonsynonymous polymorphisms in genes encoding carnitine transporters (SLC22A16, SLC22A5, and SLC16A9); carnitine synthesis (FLVCR1 and MTDH) and metabolism (CPT1A, CPT2, CRAT, and ACSS2), and carnitine-dependent repair of lipids oxidized by ALOX5. Significant associations between genetic polymorphisms on SLC22 transporters and carnitine pools in stored RBCs were validated in 525 Diversity Outbred mice. Donors carrying 2 alleles of the rs12210538 SLC22A16 single-nucleotide polymorphism exhibited the lowest l-carnitine levels, significant elevations of in vitro hemolysis, and the highest degree of vesiculation, accompanied by increases in lipid peroxidation markers. Separation of RBCs by age, via in vivo biotinylation in mice, and Percoll density gradients of human RBCs, showed age-dependent depletions of l-carnitine and acyl-carnitine pools, accompanied by progressive failure of the reacylation process after chemically induced membrane lipid damage. Supplementation of stored murine RBCs with l-carnitine boosted posttransfusion recovery, suggesting this could represent a viable strategy to improve RBC storage quality.

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we perform discovery-based proteomics in 10 tissues from 20 C57BL/6J mice, representing both sexes at adult and late midlife ages (8 and 18 months). Consistent with previous studies, age-related changes in protein abundance often have no corresponding transcriptional change. Aging results in increases in immune proteins across all tissues, consistent with a global pattern of immune infiltration with age. Our protein-centric data reveal tissue-specific aging changes with functional consequences, including altered endoplasmic reticulum and protein trafficking in the spleen. We further observe changes in the stoichiometry of protein complexes with important roles in protein homeostasis, including the CCT/TriC complex and large ribosomal subunit. These data provide a foundation for understanding how proteins contribute to systemic aging across tissues.

Red blood cell (RBC) metabolism regulates hemolysis during aging in vivo and in the blood bank. However, the genetic underpinnings of RBC metabolic heterogeneity and extravascular hemolysis at population scale are incompletely understood. On the basis of the breeding of 8 founder strains with extreme genetic diversity, the Jackson Laboratory diversity outbred population can capture the impact of genetic heterogeneity in like manner to population-based studies. RBCs from 350 outbred mice, either fresh or stored for 7 days, were tested for posttransfusion recovery, as well as metabolomics and lipidomics analyses. Metabolite and lipid quantitative trait loci (QTL) mapped >400 gene-metabolite associations, which we collated into an online interactive portal. Relevant to RBC storage, we identified a QTL hotspot on chromosome 1, mapping on the region coding for the ferrireductase 6-transmembrane epithelial antigen of the prostate 3 (Steap3), a transcriptional target to p53. Steap3 regulated posttransfusion recovery, contributing to a ferroptosis-like process of lipid peroxidation, as validated via genetic manipulation in mice. Translational validation of murine findings in humans, STEAP3 polymorphisms were associated with RBC iron content, lipid peroxidation, and in vitro hemolysis in 13 091 blood donors from the Recipient Epidemiology and Donor Evaluation Study. QTL analyses in humans identified a network of gene products (fatty acid desaturases 1 and 2, epoxide hydrolase 2, lysophosphatidylcholine acetyl-transferase 3, solute carrier family 22 member 16, glucose 6-phosphate dehydrogenase, very long chain fatty acid elongase, and phospholipase A2 group VI) associated with altered levels of oxylipins. These polymorphisms were prevalent in donors of African descent and were linked to allele frequency of hemolysis-linked polymorphisms for Steap3 or p53. These genetic variants were also associated with lower hemoglobin increments in thousands of single-unit transfusion recipients from the vein-to-vein database.