Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) is a powerful technique for in-depth metabolome analysis with high quantification accuracy. Unlike conventional LC-MS, it analyzes chemical-group-based submetabolomes and uses the combined results to represent the whole metabolome. Due to analysis time and cost constraint, not all submetabolomes can be profiled and thus knowledge of chemical group classification is important in guiding submetabolome selection. Herein we report a study of determining the distribution of functional groups of compounds in a database and then examine how well we can experimentally analyze the major chemical groups in two representative samples (i.e., human plasma and yeast). We developed a computer algorithm to classify chemical structures according to their functional groups. After removing lipids which are targeted molecules in lipidomic analysis, inorganic species and other molecules that are unique to drug, food, plant, and environmental origins, five groups (i.e., amine, phenol, hydroxyl, carboxyl, and carbonyl) are found to be the dominant classes. In the databases of MCID (2683 filtered metabolites), HMDB (5506), KEGG (11598), YMDB (1107), and ECMDB (1462), 94.7%, 85.7%, 86.4%, 85.7%, and 95.8% of the filtered metabolites belong to one or more of the five groups, respectively. These groups can be analyzed in four-channel CIL LC-MS where hydroxyls (H), amines and phenols (A), carboxyls (C), and carbonyls or ketones/aldehydes (K) are separately profiled as individual channels using dansyl and DmPA labeling reagents. A total of 7431 peak pairs were detected with 6109 unique-mass pairs from plasma, while 5629 pairs with 4955 unique-mass pairs were detected in yeast. Compared to group distributions of database compounds, hydroxylcontaining metabolites were severely underdetected, which might indicate that the current method is less than optimal for analyzing this group of metabolites. As a result, the overall experimental coverage is likely significantly lower than the databasederived coverage. In short, this study has shown that high metabolome coverage is theoretically attainable by analyzing only the H, A, C, and K submetabolomes and the group classification information should be helpful in guiding future analytical method development and choices of submetabolomes to be analyzed.

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The TSH receptor (TSHR) is the critical target for antibody production in Graves' disease (GD). Insulin-like growth factor 1 receptor (IGF1R) has been proposed as a second autoantigen in complications of GD such as orbitopathy. We attempted to induce orbital tissue remodeling in mice undergoing immunizations with plasmids encoding TSHR and IGF1R delivered by in vivo skeletal muscle electroporation, a procedure known to give a sustained, long-term antibody response. Female BALB/c mice were challenged with TSHR A-subunit or IGF1Rα subunit plasmid by injection and electroporation. Mice challenged with TSHR A-subunit plasmid resulted in high frequency (75%) of hyperthyroidism and thyroid-stimulating antibodies. But strikingly, immunization with TSHR A-subunit plasmid also elicited antibody to IGF1Rα subunit. Mice challenged in the same manner with IGF1Rα subunit plasmid produced strong antibody responses to IGF1R, but did not undergo any changes in phenotype. Simultaneous challenge by double antigen immunization with the two plasmids in distant anatomical sites reduced the incidence of hyperthyroidism, potentially as a consequence of antigenic competition. Thyroid glands from the TSHR A-subunit plasmid-challenged group were enlarged with patchy microscopic infiltrates. Histological analysis of the orbital tissues demonstrated moderate connective tissue fibrosis and deposition of Masson's trichrome staining material. Our findings imply that immunization with TSHR A-subunit plasmid leads to generation of IGF1R antibodies, which together with thyroid-stimulating antibodies may precipitate remodeling of orbital tissue, raising our understanding of its close association with GD.

Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance chemical isotope labeling (CIL) LC-MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential C- andC-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with C-labeling and spiked with aC-labeled pooled sample, followed by LC-MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 C-/C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org . Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that C-/C-DnsHz labeling LC-MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.

Frequency of circulating TSHR(+) fibrocytes is markedly increased in patients with TAO, and they express proinflammatory chemokines in response to TSH. Because they infiltrate both orbit and thyroid in GD, they may represent the link between systemic immunoreactivity and organ-specific autoimmunity.