Impact of Hypertensive Disorders of Pregnancy and Gestational Diabetes Mellitus on Offspring Cardiovascular Health in Early Adolescence.

BACKGROUND: Adverse pregnancy outcomes, including hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM), influence maternal cardiovascular heath (CVH) long after pregnancy, but their relationship to offspring CVH following in utero exposure remains uncertain. OBJECTIVE: To examine associations of HDP or GDM with offspring CVH in early adolescence. STUDY DESIGN: This analysis used data from the prospective Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study from 2000 to 2006 and the HAPO Follow-Up Study from 2013 to 2016. This analysis included 3,317 mother-child dyads from 10 field centers, comprising 70.8% of HAPO Follow-Up Study participants. Those with pregestational diabetes and chronic hypertension were excluded. The exposures were having any HDP or GDM compared with not having HDP or GDM, respectively (reference). The outcome was offspring CVH at ages 10 to 14 years, based on four metrics: body mass index, blood pressure, total cholesterol level, and glucose level. Each metric was categorized as ideal, intermediate, or poor using a framework provided by the American Heart Association. The outcome was primarily defined as having at least one CVH metric that was non-ideal versus all ideal (reference), and secondarily as the number of non-ideal CVH metrics: at least one intermediate metric, one poor metric, or at least two poor metrics versus all ideal (reference). Modified Poisson regression with robust error variance was used and adjusted for covariates at pregnancy enrollment, including field center, parity, age, gestational age, alcohol or tobacco use, child's assigned sex at birth, and child's age at follow-up. RESULTS: Among 3,317 maternal-child dyads, the median (IQR) ages were 30.4 (25.6, 33.9) years for pregnant individuals and 11.6 (10.9, 12.3) years for children. During pregnancy, 10.4% of individuals developed HDP and 14.6% developed GDM. At follow-up, 55.5% of offspring had at least one non-ideal CVH metric. In adjusted models, having HDP (aRR 1.14; 95% CI 1.04, 1.25) or having GDM (aRR 1.10; 95% CI 1.02, 1.19) was associated with greater risk that offspring developed less-than-ideal CVH at ages 10 to 14 years. The above associations strengthened in magnitude as the severity of adverse CVH metrics increased (i.e., with the outcome measured as >1 intermediate, 1 poor, and >2 poor adverse metrics), albeit the only statistically significant association was with the "1-poor-metric" exposure. CONCLUSONS: In this multi-national prospective cohort, pregnant individuals who experienced either HDP and GDM were at significantly increased risk of having offspring with worse CVH in early adolescence. Reducing adverse pregnancy outcomes and increasing surveillance with targeted interventions after an adverse pregnancy outcome should be studied as potential avenues to enhance long-term cardiovascular health in the offspring exposed in utero.

Metabolomic and genetic architecture of gestational diabetes subtypes.

AIMS/HYPOTHESIS: Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes. METHODS: This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM). RESULTS: Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM. CONCLUSIONS/INTERPRETATION: This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes.

BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.

Leptin and adiposity measures from birth to later childhood: Findings from the Hyperglycemia and Adverse Pregnancy Outcomes Follow-Up Study.

BACKGROUND: Cord blood (CB) leptin is positively associated with adiposity at birth, but the association with child adiposity is unclear. OBJECTIVES: We hypothesized that CB leptin is positively associated with adiposity in peripubertal children and with childhood leptin. METHODS: Leptin was measured in 986 CB and 931 childhood stored samples from a prospective birth cohort. Adiposity measures were collected at birth and mean age 11.5 years. Linear and logistic regression analyses were used to evaluate associations between log-transformed CB leptin and neonatal and childhood adiposity measures as continuous and categorical variables, respectively. RESULTS: CB leptin was positively associated with neonatal and childhood adiposity. Childhood associations were attenuated when adjusted for maternal body mass index (BMI) and glucose, but remained statistically significant for childhood body fat percentage (ß = 1.15%, confidence interval [CI] = 0.46-1.84), body fat mass (ß = 0.69 kg, 95% CI = 0.16-1.23), sum of skin-folds (ß = 1.77 mm, 95% CI = 0.31-3.24), log-transformed child serum leptin (ß = 0.13, 95% CI = 0.06-0.20), overweight/obesity (OR = 1.21, 95% CI = 1.03-1.42), obesity (OR = 1.31, 95% CI = 1.04-1.66) and body fat percentage >85th percentile (OR = 1.38, 95% CI = 1.12-1.73). Positive associations between newborn adiposity measures and CB leptin confirmed previous reports. CONCLUSION: CB leptin is positively associated with neonatal and childhood adiposity and child leptin levels, independent of maternal BMI and maternal hyperglycemia. CB leptin may be a biomarker of future adiposity risk.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis.

BACKGROUND: Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM. METHODS: Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA). RESULTS: A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers. CONCLUSIONS: Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Gestational Diabetes (GDM) is high blood sugar that develops during pregnancy and may cause complications. GDM diagnosis is centered on blood sugar levels. Despite everyone receiving standard treatment, the clinical outcomes may vary from one individual to another. This indicates a need to identify factors that may help GDM diagnosis and result in improved classification of those at greatest risk for complications. Here, we systematically analyzed all published evidence for potential markers that could identify those with GDM who have greater risk of complications. We find that high maternal weight is a risk factor for offspring born larger for their gestational age. Other promising markers were identified, but further analysis is needed before they can be applied in the clinic.

Use of fasting plasma glucose to determine the approach for diagnosing gestational diabetes mellitus.

AIMS: Estimate the impact of OGTTs only on women with a screening FPG of 4.5-5.0 mmol/L using data from HAPO. METHODS: HAPO participants had 75-g OGTTs (24-32 weeks' gestation). At follow-up, children had adiposity assessed (overweight/obesity, obesity) and mothers and children had OGTTs. GDM was defined retrospectively using IADPSG criteria. Odds for neonatal (birthweight, percent neonatal fat, sum of skinfolds, cord C-peptide > 90th percentiles) and follow-up outcomes were assessed in those with HAPO FPG ≤ 4.4 or > 4.4 mmol/L and GDM or no GDM focusing on women with FPG > 4.4 and no GDM (Group 3) vs women with GDM and FPG ≤ 4.4 (Group 2). RESULTS: This strategy would miss a diagnosis of GDM in 14.7%. Odds for neonatal outcomes in Groups 2 and 3 were not different (ORs: 1.14 to 1.29). Odds at follow-up for type 2 diabetes and disorders of glucose metabolism in mothers were higher in Group 2 (ORs: 3.51, 2.57). Odds for childhood impaired glucose tolerance or adiposity outcomes were not different for Groups 2 and 3. CONCLUSIONS: HAPO mothers whose GDM diagnosis would be missed were not at greater risk for adverse neonatal and childhood outcomes than mothers with FPG of 4.5-5.0 without GDM.

Racial and ethnic differences in the association between pregnancy dysglycemia and cardiometabolic risk factors 10-14 years' postpartum in the HAPO follow-up study.

Associations between pregnancy dysglycemia and subsequent maternal cardiometabolic factors 10-14 years postpartum were largely similar across self-identified racial and ethnic groups among birthing people in the U.S. enrolled in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Follow-up Study.

Maternal and Cord Blood Serum Metabolite Associations with Childhood Adiposity and Body Composition Outcomes.

Maternal metabolites influence the size of newborns independently of maternal body mass index (BMI) and glycemia, highlighting the importance of maternal metabolism on offspring outcomes. This study examined associations of maternal metabolites during pregnancy with childhood adiposity, and cord blood metabolites with childhood adiposity using phenotype and metabolomic data from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and the HAPO Follow-Up Study. The maternal metabolites analyses included 2324 mother-offspring pairs, while the cord blood metabolites analyses included 937 offspring. Multiple logistic and linear regression were used to examine associations between primary predictors, maternal or cord blood metabolites, and childhood adiposity outcomes. Multiple maternal fasting and 1 hr metabolites were significantly associated with childhood adiposity outcomes in Model 1 but were no longer significant after adjusting for maternal BMI and/or maternal glycemia. In the fully adjusted model, fasting lactose levels were negatively associated with child BMI z-scores and waist circumference, while fasting urea levels were positively associated with waist circumference. One-hour methionine was positively associated with fat-free mass. There were no significant associations between cord blood metabolites and childhood adiposity outcomes. Few metabolites were associated with childhood adiposity outcomes after adjusting for maternal BMI and glucose, suggesting that maternal BMI accounts for the association between maternal metabolites and childhood adiposity.

Haploinsufficiency of NFKBIA reshapes the epigenome antipodal to the IDH mutation and imparts disease fate in diffuse gliomas.

Genetic alterations help predict the clinical behavior of diffuse gliomas, but some variability remains uncorrelated. Here, we demonstrate that haploinsufficient deletions of chromatin-bound tumor suppressor NFKB inhibitor alpha (NFKBIA) display distinct patterns of occurrence in relation to other genetic markers and are disproportionately present at recurrence. NFKBIA haploinsufficiency is associated with unfavorable patient outcomes, independent of genetic and clinicopathologic predictors. NFKBIA deletions reshape the DNA and histone methylome antipodal to the IDH mutation and induce a transcriptome landscape partly reminiscent of H3K27M mutant pediatric gliomas. In IDH mutant gliomas, NFKBIA deletions are common in tumors with a clinical course similar to that of IDH wild-type tumors. An externally validated nomogram model for estimating individual patient survival in IDH mutant gliomas confirms that NFKBIA deletions predict comparatively brief survival. Thus, NFKBIA haploinsufficiency aligns with distinct epigenome changes, portends a poor prognosis, and should be incorporated into models predicting the disease fate of diffuse gliomas.

Association of Maternal Metabolites and Metabolite Networks with Newborn Outcomes in a Multi-Ancestry Cohort.

The in utero environment is important for newborn size at birth, which is associated with childhood adiposity. We examined associations between maternal metabolite levels and newborn birthweight, sum of skinfolds (SSF), and cord C-peptide in a multinational and multi-ancestry cohort of 2337 mother-newborn dyads. Targeted and untargeted metabolomic assays were performed on fasting and 1 h maternal serum samples collected during an oral glucose tolerance test performed at 24-32 week gestation in women participating in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. Anthropometric measurements were obtained on newborns at birth. Following adjustment for maternal BMI and glucose, per-metabolite analyses demonstrated significant associations between maternal metabolite levels and birthweight, SSF, and cord C-peptide. In the fasting state, triglycerides were positively associated and several long-chain acylcarnitines were inversely associated with birthweight and SSF. At 1 h, additional metabolites including branched-chain amino acids, proline, and alanine were positively associated with newborn outcomes. Network analyses demonstrated distinct clusters of inter-connected metabolites significantly associated with newborn phenotypes. In conclusion, numerous maternal metabolites during pregnancy are significantly associated with newborn birthweight, SSF, and cord C-peptide independent of maternal BMI and glucose, suggesting that metabolites in addition to glucose contribute to newborn size at birth and adiposity.

SpiderLearner: An ensemble approach to Gaussian graphical model estimation.

Gaussian graphical models (GGMs) are a popular form of network model in which nodes represent features in multivariate normal data and edges reflect conditional dependencies between these features. GGM estimation is an active area of research. Currently available tools for GGM estimation require investigators to make several choices regarding algorithms, scoring criteria, and tuning parameters. An estimated GGM may be highly sensitive to these choices, and the accuracy of each method can vary based on structural characteristics of the network such as topology, degree distribution, and density. Because these characteristics are a priori unknown, it is not straightforward to establish universal guidelines for choosing a GGM estimation method. We address this problem by introducing SpiderLearner, an ensemble method that constructs a consensus network from multiple estimated GGMs. Given a set of candidate methods, SpiderLearner estimates the optimal convex combination of results from each method using a likelihood-based loss function. K $$ K $$ -fold cross-validation is applied in this process, reducing the risk of overfitting. In simulations, SpiderLearner performs better than or comparably to the best candidate methods according to a variety of metrics, including relative Frobenius norm and out-of-sample likelihood. We apply SpiderLearner to publicly available ovarian cancer gene expression data including 2013 participants from 13 diverse studies, demonstrating our tool's potential to identify biomarkers of complex disease. SpiderLearner is implemented as flexible, extensible, open-source code in the R package ensembleGGM at https://github.com/katehoffshutta/ensembleGGM.

Implementation and evaluation of an expanded electronic health record-integrated bilingual electronic symptom management program across a multi-site Comprehensive Cancer Center: The NU IMPACT protocol.

BACKGROUND: People with cancer experience symptoms that adversely affect quality of life. Despite existing interventions and clinical guidelines, timely symptom management remains uneven in oncology care. We describe a study to implement and evaluate an electronic health record (EHR)-integrated symptom monitoring and management program in adult outpatient cancer care. METHODS: Our cancer patient-reported outcomes (cPRO) symptom monitoring and management program is a customized EHR-integrated installation. We will implement cPRO across all Northwestern Memorial HealthCare (NMHC) hematology/oncology clinics. We will conduct a cluster randomized modified stepped-wedge trial to evaluate patient and clinician engagement with cPRO. Further, we will embed a patient-level randomized clinical trial to evaluate the impact of an additional enhanced care (EC; cPRO plus web-based symptom self-management intervention) relative to usual care (UC; cPRO alone). The project uses a Type 2 hybrid effectiveness-implementation approach. The intervention will be implemented across seven regional clusters within the healthcare system comprising 32 clinic sites. A 6-month prospective pre-implementation enrollment period will be followed by a post-implementation enrollment period, during which newly enrolled, consenting patients will be randomly assigned (1:1) to EC or UC. We will follow patients for 12 months post-enrollment. Patients randomized to EC will receive evidence-based symptom-management content on cancer-related concerns and approaches to enhance quality of life, using a web-based tool ("MyNM Care Corner"). This design allows for within- and between-site evaluation of implementation plus a group-based comparison to demonstrate effectiveness on patient-level outcomes. DISCUSSION: The project has potential to guide implementation of future healthcare system-level cancer symptom management programs. http://ClinicalTrials.gov # NCT03988543.

Effectiveness and implementation of an electronic health record-integrated digital health intervention for managing depressive symptoms in ambulatory oncology: The My Well-Being Guide study rationale and protocol.

BACKGROUND: Rates of clinically elevated depressive symptoms among ambulatory oncology patients are higher than in the general population and are associated with poorer health-related quality of life. Furthermore, a reduction in depressive symptoms may be associated with improved cancer survival. Several interventions have demonstrated efficacy in reducing oncologic depressive symptoms, including cognitive-behavioral stress management (CBSM). However, more work is needed to understand how to best implement CBSM into practice, such as through stepped-care approaches and digital health interventions linked to electronic health records (EHR). This manuscript presents the protocol of the My Well-Being Guide study, a pragmatic type 1 effectiveness-implementation hybrid study. This trial will test the effectiveness of My Well-Being Guide, a seven-week structured, CBSM-based digital health intervention designed to reduce depressive symptoms. This trial will also evaluate My Well-Being Guide's implementation across two health systems. METHODS: The final sample (N = 4561) will be oncology patients at Northwestern Medicine or University of Miami Health System who are ≥18 years of age; have a cancer diagnosis; elevated depressive symptoms on the Patient-Reported Outcomes Measurement Information System Depression; and primary language is English or Spanish. Data collection will occur at baseline, and 2-, 6-, and 12-months post baseline. Outcome domains include depressive symptoms and implementation evaluation. DISCUSSION: This study may provide valuable data on the effectiveness of our depressive symptom management digital health intervention linked to the EHR and the scalability of digital health interventions in general.

Determining venous thromboembolism risk in patients with adult-type diffuse glioma.

Venous thromboembolism (VTE) is a life-threating condition that is common in patients with adult-type diffuse gliomas, yet thromboprophylaxis is controversial because of possible intracerebral hemorrhage. Effective VTE prediction models exist for other cancers, but not glioma. Our objective was to develop a VTE prediction tool to improve glioma patient care, incorporating clinical, blood-based, histologic, and molecular markers. We analyzed preoperative arterial blood, tumor tissue, and clinical-pathologic data (including next-generation sequencing data) from 258 patients with newly diagnosed World Health Organization (WHO) grade 2 to 4 adult-type diffuse gliomas. Forty-six (17.8%) experienced VTE. Tumor expression of tissue factor (TF) and podoplanin (PDPN) each positively correlated with VTE, although only circulating TF and D-dimers, not circulating PDPN, correlated with VTE risk. Gliomas with mutations in isocitrate dehydrogenase 1 (IDH1) or IDH2 (IDHmut) caused fewer VTEs; multivariable analysis suggested that this is due to IDHmut suppression of TF, not PDPN. In a predictive time-to-event model, the following predicted increased VTE risk in newly diagnosed patients with glioma: (1) history of VTE; (2) hypertension; (3) asthma; (4) white blood cell count; (5) WHO tumor grade; (6) patient age; and (7) body mass index. Conversely, IDHmut, hypothyroidism, and MGMT promoter methylation predicted reduced VTE risk. These 10 variables were used to create a web-based VTE prediction tool that was validated in 2 separate cohorts of patients with adult-type diffuse glioma from other institutions. This study extends our understanding of the VTE landscape in these tumors and provides evidence-based guidance for clinicians to mitigate VTE risk in patients with glioma.

Docetaxel targets aggressive methylation profiles and serves as a radiosensitizer in high-risk meningiomas.

BACKGROUND: Meningioma is the most common primary intracranial tumor in adults. A subset of these tumors recur and invade the brain, even after surgery and radiation, resulting in significant disability. There is currently no standard-of-care chemotherapy for meningiomas. As genomic DNA methylation profiling can prognostically stratify these lesions, we sought to determine whether any existing chemotherapies might be effective against meningiomas with high-risk methylation profiles. METHODS: A previously published dataset of meningioma methylation profiles was used to screen for clinically significant CpG methylation events and associated cellular pathways. Based on these results, patient-derived meningioma cell lines were used to test candidate drugs in vitro and in vivo, including efficacy in conjunction with radiotherapy. RESULTS: We identified 981 genes for which methylation of mapped CpG sites was related to progression-free survival in meningiomas. Associated molecular pathways were cross-referenced with FDA-approved cancer drugs, which nominated Docetaxel as a promising candidate for further preclinical analyses. Docetaxel arrested growth in 17 meningioma cell sources, representing all tumor grades, with a clinically favorable IC50 values ranging from 0.3 nM to 10.7 mM. The inhibitory effects of this medication scaled with tumor doubling time, with maximal benefit in fast-growing lesions. The combination of Docetaxel and radiation therapy increased markers of apoptosis and double-stranded DNA breaks, and extended the survival of mice engrafted with meningioma cells relative to either modality alone. CONCLUSIONS: Global patterns of DNA methylation may be informative for the selection of chemotherapies against meningiomas, and existing drugs may enhance radiation sensitivity in high-risk cases.

Urinary metal profiles in mother-offspring pairs and their association with early dysglycemia in the International Hyperglycemia and Adverse Pregnancy Outcome Follow Up Study (HAPO-FUS).

BACKGROUND: Variations in dietary intake and environmental exposure patterns of essential and non-essential trace metals influence many aspects of human health throughout the life span. OBJECTIVE: To examine the relationship between urine profiles of essential and non-essential metals in mother-offspring pairs and their association with early dysglycemia. METHODS: Herein, we report findings from an ancillary study to the international Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study (HAPO-FUS) that examined urinary essential and non-essential metal profiles from mothers and offspring ages 10-14 years (1012 mothers, 1013 offspring, 968 matched pairs) from 10 international sites. RESULTS: Our analysis demonstrated a diverse exposure pattern across participating sites. In multiple regression modelling, a positive association between markers of early dysglycemia and urinary zinc was found in both mothers and offspring after adjustment for common risk factors for diabetes. The analysis showed weaker, positive, and negative associations of the 2-h glucose value with urinary selenium and arsenic respectively. A positive association between 2-h glucose values and cadmium was found only in mothers in the fully adjusted model when participants with established diabetes were excluded. There was a high degree of concordance between mother and offspring urinary metal profiles. Mother-to-offspring urinary metal ratios were unique for each metal, providing insights into changes in their homeostasis across the lifespan. SIGNIFICANCE: Urinary levels of essential and non-essential metals are closely correlated between mothers and their offspring in an international cohort. Urinary levels of zinc, selenium, arsenic, and cadmium showed varying degrees of association with early dysglycemia in a comparatively healthy cohort with a low rate of preexisting diabetes. IMPACT STATEMENT: Our data provides novel evidence for a strong correlation between mother and offspring urinary metal patterns with a unique mother-to-offspring ratio for each metal. The study also provides new evidence for a strong positive association between early dysglycemia and urinary zinc, both in mothers and offspring. Weaker positive associations with urinary selenium and cadmium and negative associations with arsenic were also found. The low rate of preexisting diabetes in this population provides the unique advantage of minimizing the confounding effect of preexisting, diabetes related renal changes that would alter the relationship between dysglycemia and renal metal excretion.

Ventricular Assist Device Self-care Education at Tertiary Care Medical Centers.

Ventricular assist device (VAD) implantation requires patients and caregivers to attain self-care knowledge and skills before discharge from implant hospitalization. Inability to perform these skills can have devastating outcomes (i.e., death from pump malfunction, driveline site infections, and stroke). No standard-of-care guiding VAD self-care education exists. We sought to describe how select tertiary care VAD implant centers across the United States currently educate VAD patients and their caregivers. Using a multiple case studies design with a purposive sampling strategy, we conducted semistructured interviews of VAD coordinators responsible for VAD education at 18 centers. From audio recording of interviews, we used rapid qualitative analysis to organize and analyze the data. All centers spent significant time and effort educating patients and caregivers on VAD self-care. Although centers teach similar content, the rigor of assessments and follow-up education differed vastly. Only 3/18 (17%) centers performed competency-based assessments with a skills checklist and minimum passing standard assessing readiness to perform VAD self-care independently. Twelve of 18 (67%) centers provided formal follow-up education to address skills decay, yet wide variation existed in timing and content of education. Due to the diversity among centers regarding VAD self-care education, more prescriptive practice guidelines are needed.