From an animal health perspective, relatively little is known about the typical or healthy ranges of concentrations for many metabolites in bovine biofluids and tissues. Here, we describe the results of a comprehensive, quantitative metabolomic characterization of six bovine biofluids and tissues, including serum, ruminal fluid, liver, Longissimus thoracis (LT) muscle, semimembranosus (SM) muscle, and testis tissues. Using nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography–tandem mass spectrometry (LC–MS/MS), and inductively coupled plasma–mass spectrometry (ICP–MS), we were able to identify and quantify more than 145 metabolites in each of these biofluids/tissues. Combining these results with previous work done by our team on other bovine biofluids, as well as previously published literature values for other bovine tissues and biofluids, we were able to generate quantitative reference concentration data for 2100 unique metabolites across five different bovine biofluids and seven different tissues. These experimental data were combined with computer-aided, genome-scale metabolite inference techniques to add another 48,628 unique metabolites that are biochemically expected to be in bovine tissues or biofluids. Altogether, 51,801 unique metabolites were identified in this study. Detailed information on these 51,801 unique metabolites has been placed in a publicly available database called the Bovine Metabolome Database.

Residual feed intake (RFI) is a feed efficiency measure commonly used in the livestock industry to identify animals that efficiently/inefficiently convert feed into meat or body mass. Selection for low-residual feed intake (LRFI), or feed efficient animals, is gaining popularity among beef producers due to the fact that LRFI cattle eat less and produce less methane per unit weight gain. RFI is a difficult and time-consuming measure to perform, and therefore a simple blood test that could distinguish high-RFI (HRFI) from LRFI animals (early on) would potentially benefit beef farmers in terms of optimizing production or selecting which animals to cull or breed. Using three different metabolomics platforms (nuclear magnetic resonance (NMR) spectrometry, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and inductively coupled plasma mass spectrometry (ICP-MS)) we successfully identified serum biomarkers for RFI that could potentially be translated to an RFI blood test. One set of predictive RFI biomarkers included formate and leucine (best for NMR), and another set included C4 (butyrylcarnitine) and LysoPC(28:0) (best for LC-MS/MS). These serum biomarkers have high sensitivity and specificity (AUROC > 0.85), for distinguishing HRFI from LRFI animals. These results suggest that serum metabolites could be used to inexpensively predict and categorize bovine RFI values. Further validation using a larger, more diverse cohort of cattle is required to confirm these findings.

Wiedemann–Steiner syndrome (WDSTS) is a Mendelian syndromic intellectual disability (ID) condition associated with hypertrichosis cubiti, short stature, and characteristic facies caused by pathogenic variants in the KMT2A gene. Clinical features can be inconclusive in mild and unusual WDSTS presentations with variable ID (mild to severe), facies (typical or not) and other associated malformations (bone, cerebral, renal, cardiac and ophthalmological anomalies). Interpretation and classification of rare KMT2A variants can be challenging. A genome-wide DNA methylation episignature for KMT2A-related syndrome could allow functional classification of variants and provide insights into the pathophysiology of WDSTS. Therefore, we assessed genome-wide DNA methylation profiles in a cohort of 60 patients with clinical diagnosis for WDSTS or Kabuki and identified a unique highly sensitive and specific DNA methylation episignature as a molecular biomarker of WDSTS. WDSTS episignature enabled classification of variants of uncertain significance in the KMT2A gene as well as confirmation of diagnosis in patients with clinical presentation of WDSTS without known genetic variants. The changes in the methylation profile resulting from KMT2A mutations involve global reduction in methylation in various genes, including homeobox gene promoters. These findings provide novel insights into the molecular etiology of WDSTS and explain the broad phenotypic spectrum of the disease.

Background: Since the identification of JAK2 V617F and exon 12 mutations as driver mutations in polycythemia vera (PV) in 2005, molecular testing of these mutations for patients with erythrocytosis has become a routine clinical practice. However, the incidence of myeloid mutations other than the common JAK2 V617F mutation in unselected patients referred for elevated hemoglobin is not well studied. This study aimed to characterize the mutational landscape in a real-world population of patients referred for erythrocytosis using a targeted next-generation sequencing (NGS)-based assay. Method: A total of 529 patients (hemoglobin levels >160 g/L in females or >165 g/L in males) were assessed between January 2018 and May 2021 for genetic variants using the Oncomine Myeloid Research Assay (ThermoFisher Scientific, Waltham, MA, USA) targeting 40 key genes with diagnostic and prognostic implications in hematological conditions (17 full genes and 23 genes with clinically relevant “hotspot” regions) and a panel of 29 fusion driver genes (>600 fusion partners). Results: JAK2 mutations were detected in 10.9% (58/529) of patients, with 57 patients positive for JAK2 V617F, while one patient had a JAK2 exon 12 mutation. Additional mutations were detected in 34.5% (20/58) of JAK2-positive patients: TET2 (11; 19%), DNMT3A (2;3.4%), ASXL1 (2; 3.4%), SRSF2 (2; 3.4%), BCOR (1; 1.7%), TP53 (1; 1.7%), and ZRSR2 (1; 1.7%). Diagnosis of PV was suspected in 2 JAK2-negative patients based on the 2016 World Health Organization (WHO) diagnostic criteria. Notably, one patient carried mutations in the SRSF2 and TET2 genes, and the other patient carried mutations in the SRSF2, IDH2, and ASXL1 genes. Three JAK2-negative patients with elevated hemoglobin who tested positive for BCR/ABL1 fusion were diagnosed with chronic myeloid leukemia (CML) and excluded from further analysis. The remaining 466 JAK2-negative patients were diagnosed with secondary erythrocytosis and mutations were found in 6% (28/466) of these cases. Conclusion: Mutations other than JAK2 mutations were frequently identified in patients referred for erythrocytosis, with mutations in the TET2, DNMT3A, and ASXL1 genes being detected in 34.5% of JAK2-positive PV patients. The presence of additional mutations, such as ASXL1 mutations, in this population has implications for prognosis. Both the incidence and mutation type identified in patients with secondary erythrocytosis likely reflects incidental, age-associated clonal hematopoiesis of indeterminate potential (CHIP).