Predicting acute ovarian failure in female survivors of childhood cancer: a cohort study in the Childhood Cancer Survivor Study (CCSS) and the St Jude Lifetime Cohort (SJLIFE).

BACKGROUND: Cancer treatment can cause gonadal impairment. Acute ovarian failure is defined as the permanent loss of ovarian function within 5 years of cancer diagnosis. We aimed to develop and validate risk prediction tools to provide accurate clinical guidance for paediatric patients with cancer. METHODS: In this cohort study, prediction models of acute ovarian failure risk were developed using eligible female US and Canadian participants in the Childhood Cancer Survivor Study (CCSS) cohort and validated in the St Jude Lifetime Cohort (SJLIFE) Study. 5-year survivors from the CCSS cohort were included if they were at least 18 years old at their most recent follow-up and had complete treatment exposure and adequate menstrual history (including age at menarche, current menstrual status, age at last menstruation, and menopausal aetiology) information available. Participants in the SJLIFE cohort were at least 10-year survivors. Participants were excluded from the prediction analysis if they had an ovarian hormone deficiency, had missing exposure information, or had indeterminate ovarian status. The outcome of acute ovarian failure was defined as permanent loss of ovarian function within 5 years of cancer diagnosis or no menarche after cancer treatment by the age of 18 years. Logistic regression, random forest, and support vector machines were used as candidate methods to develop the risk prediction models in the CCSS cohort. Prediction performance was evaluated internally (in the CCSS cohort) and externally (in the SJLIFE cohort) using the areas under the receiver operating characteristic curve (AUC) and the precision-recall curve (average precision [AP; average positive predictive value]). FINDINGS: Data from the CCSS cohort were collected for participants followed up between Nov 3, 1992, and Nov 25, 2016, and from the SJLIFE cohort for participants followed up between Oct 17, 2007, and April 16, 2012. Of 11 336 female CCSS participants, 5886 (51·9%) met all inclusion criteria for analysis. 1644 participants were identified from the SJLIFE cohort, of whom 875 (53·2%) were eligible for analysis. 353 (6·0%) of analysed CCSS participants and 50 (5·7%) of analysed SJLIFE participants had acute ovarian failure. The overall median follow-up for the CCSS cohort was 23·9 years (IQR 20·4-27·9), and for SJLIFE it was 23·9 years (19·0-30·0). The three candidate methods (logistic regression, random forest, and support vector machines) yielded similar results, and a prescribed dose model with abdominal and pelvic radiation doses and an ovarian dose model with ovarian radiation dosimetry using logistic regression were selected. Common predictors in both models were history of haematopoietic stem-cell transplantation, cumulative alkylating drug dose, and an interaction between age at cancer diagnosis and haematopoietic stem-cell transplant. External validation of the model in the SJLIFE cohort produced an estimated AUC of 0·94 (95% CI 0·90-0·98) and AP of 0·68 (95% CI 0·53-0·81) for the ovarian dose model, and AUC of 0·96 (0·94-0·97) and AP of 0·46 (0·34-0·61) for the prescribed dose model. Based on these models, an online risk calculator has been developed for clinical use. INTERPRETATION: Both acute ovarian failure risk prediction models performed well. The ovarian dose model is preferred if ovarian radiation dosimetry is available. The models, along with the online risk calculator, could help clinical discussions regarding the need for fertility preservation interventions in girls and young women newly diagnosed with cancer

Effect of 28 days of creatine ingestion on muscle metabolism and performance of a simulated cycling road race

<p>Abstract</p> <p>Purpose</p> <p>The effects of creatine supplementation on muscle metabolism and exercise performance during a simulated endurance road race was investigated.</p> <p>Methods</p> <p>Twelve adult male (27.3 ± 1.0 yr, 178.6 ± 1.4 cm, 78.0 ± 2.5 kg, 8.9 ± 1.1 %fat) endurance-trained (53.3 ± 2.0 ml* kg^-1* min^-1, cycling ~160 km/wk) cyclists completed a simulated road race on a cycle ergometer (Lode), consisting of a two-hour cycling bout at 60% of peak aerobic capacity (VO_2peak) with three 10-second sprints performed at 110% VO_{2 peak}every 15 minutes. Cyclists completed the 2-hr cycling bout before and after dietary creatine monohydrate or placebo supplementation (3 g/day for 28 days). Muscle biopsies were taken at rest and five minutes before the end of the two-hour ride.</p> <p>Results</p> <p>There was a 24.5 ± 10.0% increase in resting muscle total creatine and 38.4 ± 23.9% increase in muscle creatine phosphate in the creatine group (<it>P </it>< 0.05). Plasma glucose, blood lactate, and respiratory exchange ratio during the 2-hour ride, as well as VO_{2 peak}, were not affected by creatine supplementation. Submaximal oxygen consumption near the end of the two-hour ride was decreased by approximately 10% by creatine supplementation (P < 0.05). Changes in plasma volume from pre- to post-supplementation were significantly greater in the creatine group (⁺14.0 ± 6.3%) than the placebo group (^-10.4 ± 4.4%; <it>P </it>< 0.05) at 90 minutes of exercise. The time of the final sprint to exhaustion at the end of the 2-hour cycling bout was not affected by creatine supplementation (creatine pre, 64.4 ± 13.5s; creatine post, 88.8 ± 24.6s; placebo pre, 69.0 ± 24.8s; placebo post 92.8 ± 31.2s: creatine vs. placebo not significant). Power output for the final sprint was increased by ~33% in both groups (creatine vs. placebo not significant).</p> <p>Conclusions</p> <p>It can be concluded that although creatine supplementation may increase resting muscle total creatine, muscle creatine phosphate, and plasma volume, and may lead to a reduction in oxygen consumption during submaximal exercise, creatine supplementation does not improve sprint performance at the end of endurance cycling exercise.</p

The genomic psychiatry cohort: Partners in discovery

The Genomic Psychiatry Cohort (GPC) is a longitudinal resource designed to provide the necessary population-based sample for large-scale genomic studies, studies focusing on Research Domain Criteria (RDoC) and/or other alternate phenotype constructs, clinical and interventional studies, nested case-control studies, long-term disease course studies, and genomic variant-to-phenotype studies. We provide and will continue to encourage access to the GPC as an international resource. DNA and other biological samples and diagnostic data are available through the National Institute of Mental Health (NIMH) Repository. After appropriate review and approval by an advisory board, investigators are able to collaborate in, propose, and co-lead studies involving cohort participants

A Rare Functional Noncoding Variant at the GWAS-Implicated MIR137/MIR2682 Locus Might Confer Risk to Schizophrenia and Bipolar Disorder

Schizophrenia (SZ) genome-wide association studies (GWASs) have identified common risk variants in >100 susceptibility loci; however, the contribution of rare variants at these loci remains largely unexplored. One of the strongly associated loci spans MIR137 (miR137) and MIR2682 (miR2682), two microRNA genes important for neuronal function. We sequenced ∼6.9 kb MIR137/MIR2682 and upstream regulatory sequences in 2,610 SZ cases and 2,611 controls of European ancestry. We identified 133 rare variants with minor allele frequency (MAF) <0.5%. The rare variant burden in promoters and enhancers, but not insulators, was associated with SZ (p = 0.021 for MAF < 0.5%, p = 0.003 for MAF < 0.1%). A rare enhancer SNP, 1:g.98515539A>T, presented exclusively in 11 SZ cases (nominal p = 4.8 × 10−4). We further identified its risk allele T in 2 of 2,434 additional SZ cases, 11 of 4,339 bipolar (BP) cases, and 3 of 3,572 SZ/BP study controls and 1,688 population controls; yielding combined p values of 0.0007, 0.0013, and 0.0001 for SZ, BP, and SZ/BP, respectively. The risk allele T of 1:g.98515539A>T reduced enhancer activity of its flanking sequence by >50% in human neuroblastoma cells, predicting lower expression of MIR137/MIR2682. Both empirical and computational analyses showed weaker transcription factor (YY1) binding by the risk allele. Chromatin conformation capture (3C) assay further indicated that 1:g.98515539A>T influenced MIR137/MIR2682, but not the nearby DPYD or LOC729987. Our results suggest that rare noncoding risk variants are associated with SZ and BP at MIR137/MIR2682 locus, with risk alleles decreasing MIR137/MIR2682 expression

Prednisone/prednisolone and deflazacort regimens in the CINRG Duchenne Natural History Study

We aimed to perform an observational study of age at loss of independent ambulation (LoA) and side-effect profiles associated with different glucocorticoid corticosteroid (GC) regimens in Duchenne muscular dystrophy (DMD)

Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry.

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke's R2 = 0.032; liability R2 = 0.017; P &lt; 10-52), Latino (Nagelkerke's R2 = 0.089; liability R2 = 0.021; P &lt; 10-58), and European individuals (Nagelkerke's R2 = 0.089; liability R2 = 0.037; P &lt; 10-113), further highlighting the advantages of incorporating data from diverse human populations