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The thousands of features commonly observed when performing untargeted metabolomics with quadrupole time-of-flight (QTOF) and Orbitrap mass spectrometers often correspond to only a few hundred unique metabolites of biological origin, which is in the range of what can be assayed in a single targeted metabolomics experiment by using a triple quadrupole (QqQ) mass spectrometer. A major benefit of performing targeted metabolomics with QqQ mass spectrometry is the affordability of the instruments relative to high-resolution QTOF and Orbitrap platforms. Optimizing targeted methods to profile hundreds of metabolites on a QqQ mass spectrometer, however, has historically been limited by the availability of authentic standards, particularly for "unknowns" that have yet to be structurally identified. Here, we report a strategy to develop multiple reaction monitoring (MRM) methods for QqQ instruments on the basis of high-resolution spectra, thereby enabling us to use data from untargeted metabolomics to design targeted experiments without the need for authentic standards. We demonstrate that using high-resolution fragmentation data alone to design MRM methods results in the same quantitative performance as when methods are optimized by measuring authentic standards on QqQ instruments, as is conventionally done. The approach was validated by showing that Orbitrap ID-X data can be used to establish MRM methods on a Thermo TSQ Altis and two Agilent QqQs for hundreds of metabolites, including unknowns, without a dependence on standards. Finally, we highlight an application where metabolite profiling was performed on an ID-X and a QqQ by using the strategy introduced here, with both data sets yielding the same result. The described approach therefore allows us to use QqQ instruments, which are often associated with targeted metabolomics, to profile knowns and unknowns at a comprehensive scale that is typical of untargeted metabolomics.

Background: The Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) study has enrolled a racially and ethnically diverse population with type 2 diabetes, performed extensive phenotyping, and randomly assigned the participants to one of four second-line diabetes medications. The continuous glucose monitoring (CGM) substudy has been added to determine whether there are racial/ethnic differences in the relationship between average glucose (AG) and hemoglobin A1c (HbA1c). CGM will also be used to compare time in target range, glucose variability, and the frequency and duration of hypoglycemia across study groups. Methods: The observational CGM substudy will enroll up to 1800 of the 5047 GRADE study participants from the four treatment groups, including as many as 450 participants from each of 4 racial/ethnic minority groups to be compared: Hispanic White, non-Hispanic White, non-Hispanic African American, and non-Hispanic Other. CGM will be performed for 2 weeks in proximity to a GRADE annual visit, during which an oral glucose tolerance test will be performed and HbA1c and glycated albumin measured. Indicators of interindividual variation in red blood cell turnover, based on specialized erythrocyte measurements, will also be measured to explore the potential causes of interindividual HbA1c variations. Conclusions: The GRADE CGM substudy will provide new insights into whether differences exist in the relationship between HbA1c and AG among different racial/ethnic groups and whether glycemic profiles differ among frequently used diabetes medications and their potential clinical implications. Understanding such differences is important for clinical care and adjustment of diabetes medications in patients of different races or ethnicities.

OBJECTIVE Women with type 1 diabetes have increased risk of infertility compared to women without diabetes even after adjustment for irregular menses, but aetiologies are incompletely understood. Our aim was to examine the prevalence of abnormalities in ovarian markers consistent with polycystic ovary syndrome in women with type 1 diabetes and associations with irregular menses and diabetes-specific variables. DESIGN, PATIENTS AND MEASUREMENTS We conducted a secondary analysis of women in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC), a randomized trial and observational follow-up of intensive insulin therapy for type 1 diabetes. We included women with anti-Mullerian hormone (AMH) measurements among women not using oral contraceptives (n = 187). Initial AMH and testosterone measures were performed between EDIC years 1 and 4. History of irregular menses was assessed annually. RESULTS The median age of women was 35 (interquartile ratio 29, 40) years; 133 (35%) had elevated AMH and 62 (17%) reported irregular menses. Twelve per cent of women had relative elevations in total testosterone. In multivariable models, lower insulin dosages were associated with higher AMH concentrations (P = .0027), but not diabetes duration, glycemic control, body mass index or irregular menses. Neither irregular menses nor diabetes-specific variables were associated with testosterone concentrations. CONCLUSIONS Among women with type 1 diabetes in their thirties, abnormalities in ovarian markers are common and not associated with irregular menses and thus may partially account for decreased fecundity in women with type 1 diabetes.

Implementation of multicenter and/or longitudinal studies requires an effective quality assurance program to identify trends, data inconsistencies and process variability of results over time. The Diabetes Control and Complications Trial (DCCT) and the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study represent over 30 years of data collection among a cohort of participants across 27 clinical centers. The quality assurance plan is overseen by the Data Coordinating Center and is implemented across the clinical centers and central reading units. Each central unit incorporates specific DCCT/EDIC quality monitoring activities into their routine quality assurance plan. The results are reviewed by a data quality assurance committee whose function is to identify variances in quality that may impact study results from the central units as well as within and across clinical centers, and to recommend implementation of corrective procedures when necessary. Over the 30-year period, changes to the methods, equipment, or clinical procedures have been required to keep procedures current and ensure continued collection of scientifically valid and clinically relevant results. Pilot testing to compare historic processes with contemporary alternatives is performed and comparability is validated prior to incorporation of new procedures into the study. Details of the quality assurance plan across and within the clinical and central reading units are described, and quality outcomes for core measures analyzed by the central reading units (e.g. biochemical samples, fundus photographs, ECGs) are presented.

Background: Previous studies have shown that ATP-binding cassette transporter 1 ( ABCA1) polymorphisms associated with increased ABCA1 expression result in increased small HDL (high-density lipoprotein) subclass particle concentration. This study examines the effect of treatment with fenofibrate, a drug known to bind peroxisome proliferator-activated receptor alpha (PPARα) which increases the expression of ABCA1 gene, on lipoprotein subclass profiles of individuals stratified by ABCA1 genotypes. Methods: Participants of Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) were treated with fenofibrate over a three week period. We analyzed six ABCA1 polymorphisms in 287 GOLDN participants with triglyceride concentrations ⩾150mg/dL and studied their associations with HDL subclass particle concentrations, as measured by nuclear magnetic resonance spectroscopy, before and after treatment. Results: Fenofibrate treatment did not result in significant changes in small HDL subclass particle concentration. When changes in HDL subclasses were stratified by ABCA1 polymorphism genotypes, there were no statistically significant associations between ABCA1 genotypes and small HDL subclasses before fenofibrate treatment. However, after fenofibrate treatment the KK genotype of R1587K (mean 4.40μmol/L; p =0.004) and the RK genotype of R219K (mean 1.60μmol/L; p =0.02) polymorphisms were associated with significantly increased small HDL. The R1587KKK genotype (mean 4.80μmol/L; p =0.0002) and the R219K KK genotype (mean 2.50μmol/L; p =0.02) were also associated with increased HDL particle concentrations. Conclusion: There is a synergistic effect between ABCA1 polymorphisms and fenofibrate. Thus, our study indirectly confirms the role of fenofibrate and genotype in increasing cholesterol efflux, as evidenced by increased small HDL particles.