Rationale & Objective: Biomarkers that provide reliable evidence of future diabetic kidney disease (DKD) are needed to improve disease management. In a cross-sectional study, we previously identified thirteen urine metabolites that were reduced in DKD compared with healthy controls. Here, we evaluated associations of these thirteen metabolites with future DKD progression.

Abstract Context Many female survivors of adolescent and young adult cancers (AYA survivors) have shortened reproductive lifespans. However, the timing and duration of ovarian function after cancer treatment are largely unknown. Objective To model the trajectory of ovarian function over two decades following cancer treatment and evaluate how trajectories vary by treatment gonadotoxicity and age. Design In a prospective cohort, AYA survivors aged 18-39 at variable times since cancer treatment completion provided dried blood spots (DBS) every 6 months for up to 18 months. Anti-Müllerian hormone (AMH) levels were measured using the Ansh DBS AMH enzyme-linked immunosorbent assay. The mean AMH trajectory was modeled for the entire cohort and separately by treatment gonadotoxicity and age using functional principal components analysis. Results 763 participants, mean (standard deviation) enrollment age 33.3 (4.7) and age at cancer diagnosis 25.9 (5.7) years, contributed 1905 DBS samples. The most common cancers were breast (26.9%), lymphoma (24.8%), and thyroid (18.0%). AMH trajectories differed among survivors by treatment gonadotoxicity (low, moderate, or high) (P < 0.001). Following low or moderately gonadotoxic treatments, AMH levels increased over 2-3 years and plateaued over 10-15 years before declining. In contrast, following highly gonadotoxic treatment, AMH levels were lower overall and declined shortly after peak at 2-3 years. Younger age at treatment was associated with higher trajectories, but a protective effect of younger age was not observed in survivors exposed to highly gonadotoxic treatments (Pinteraction < 0.001). Conclusions In this large AYA survivor cohort, timing and duration of ovarian function strongly depended on treatment gonadotoxicity and age at treatment. The findings provide novel, more precise information to guide reproductive decision-making.

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<b><i>Introduction:</i></b> Metabolomics could offer novel prognostic biomarkers and elucidate mechanisms of diabetic kidney disease (DKD) progression. Via metabolomic analysis of urine samples from 995 CRIC participants with diabetes and state-of-the-art statistical modeling, we aimed to identify metabolites prognostic to DKD progression. <b><i>Methods:</i></b> Urine samples (<i>N</i> = 995) were assayed for relative metabolite abundance by untargeted flow-injection mass spectrometry, and stringent statistical criteria were used to eliminate noisy compounds, resulting in 698 annotated metabolite ions. Utilizing the 698 metabolites’ ion abundance along with clinical data (demographics, blood pressure, HbA1c, eGFR, and albuminuria), we developed univariate and multivariate models for the eGFR slope using penalized (lasso) and random forest models. Final models were tested on time-to-ESKD (end-stage kidney disease) via cross-validated C-statistics. We also conducted pathway enrichment analysis and a targeted analysis of a subset of metabolites. <b><i>Results:</i></b> Six eGFR slope models selected 9–30 variables. In the adjusted ESKD model with highest C-statistic, valine (or betaine) and 3-(4-methyl-3-pentenyl)thiophene were associated (<i>p</i> &#x3c; 0.05) with 44% and 65% higher hazard of ESKD per doubling of metabolite abundance, respectively. Also, 13 (of 15) prognostic amino acids, including valine and betaine, were confirmed in the targeted analysis. Enrichment analysis revealed pathways implicated in kidney and cardiometabolic disease. <b><i>Conclusions:</i></b> Using the diverse CRIC sample, a high-throughput untargeted assay, followed by targeted analysis, and rigorous statistical analysis to reduce false discovery, we identified several novel metabolites implicated in DKD progression. If replicated in independent cohorts, our findings could inform risk stratification and treatment strategies for patients with DKD.