Background Abnormal kidney function in pregnancy may represent chronic kidney disease or pregnancy-associated acute kidney injury, both associated with adverse outcomes during and after pregnancy. Serum creatinine remains the standard biomarker for kidney function in pregnancy, but normal levels change dynamically through pregnancy and at term. Existing gestation-specific reference ranges for serum creatinine and recommendations to investigate for abnormal kidney function in pregnancy are based on limited data. Data describing trajectories of serum creatinine through pregnancy and the normal, physiological increase in serum creatinine at term are also lacking.Methods We recruited 476 healthy pregnant individuals aged 16 years or over, 2019-21, measuring serum creatinine in the first, second and third trimesters of pregnancy, at birth and postpartum. Clinical data were abstracted. Gestation-specific reference ranges for serum creatinine were defined as mean +/- 1.96 x SD, after excluding those with adverse pregnancy outcomes. Trajectories of serum creatinine through pregnancy, and the change in serum creatinine at delivery were described.Results 1875 creatinine measurements were recorded. Reference ranges for serum creatinine in the first, second and third trimesters of healthy pregnancy were 37-67 mu mol/l (0.42-0.75 mg/dl), 34-63 mu mol/l (0.38-0.71 mg/dl), and 34-66 mu mol/l (0.39-0.75 mg/dl). Increasing serum creatinine in early pregnancy was more common in those with hypertensive disorders of pregnancy, prior to disease onset. In healthy participants, median serum creatinine increase from 36 weeks to birth was 6.8% (95% CI 4.5%, 9.1%).Conclusions Investigation for abnormal kidney function in pregnancy should be considered at a lower creatinine threshold than currently recommended. Detecting abnormal creatinine trajectories may help early identification of high-risk pregnancies. 10.1093/ckj/sfae418 Video Abstract Watch the video abstract of this contribution sfae418Media1 6368633600112

BackgroundMicroplastics, produced through degradation of environmental plastic pollution, have been detected in human tissues including placenta and fetal meconium. Cell culture and animal studies have demonstrated potential reproductive toxicity of these particles; however, their association with adverse fertility or pregnancy outcomes in humans is not known.ObjectivesTo synthesise evidence for the presence of microplastics in human reproductive tissue and their associations with environmental exposures and reproductive outcomes.Search StrategyMEDLINE, Embase, Emcare, CINAHL, ClinicalTrials.gov and ICTRP were searched from inception to 03/02/2023.Selection CriteriaStudies of human participants, assessing presence of microplastics in reproductive tissues, environmental exposures to microplastics, and fertility- or pregnancy-related outcomes.Data Collection and AnalysisTwo independent reviewers selected studies and extracted data on study characteristics, microplastics detected, environmental exposures and reproductive outcomes. Narrative synthesis was performed due to methodological heterogeneity.Main ResultsOf 1094 citations, seven studies were included, covering 96 participants. Microplastics composed of 16 different polymer types were detected in both placental and meconium samples. Two studies reported associations between lifestyle factors (daily water intake, use of scrub cleanser or toothpaste, bottled water and takeaway food) and placental microplastics. One study reported associations between meconium microplastics and reduced microbiota diversity. One reported placental microplastic levels correlated with reduced birthweights and 1-minute Apgar scores.ConclusionsThere is a need for high-quality observational studies to assess the effects of microplastics on human reproductive health.

Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region ( HEATR3 ) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.

BACKGROUND Glioblastoma is an aggressive form of brain cancer. Approximately five in 100 people with glioblastoma survive for five years past diagnosis. Glioblastomas that have a particular modification to their DNA (called methylation) in a particular region (the O6-methylguanine-DNA methyltransferase (MGMT) promoter) respond better to treatment with chemotherapy using a drug called temozolomide. OBJECTIVES To determine which method for assessing MGMT methylation status best predicts overall survival in people diagnosed with glioblastoma who are treated with temozolomide. SEARCH METHODS We searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies, we additionally searched NHS Economic Evaluation Database (EED) up to December 2014. SELECTION CRITERIA Eligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiotherapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with sufficient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focused mainly on studies comparing two or more methods, and listed brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies and cost analysis. DATA COLLECTION AND ANALYSIS Two review authors independently undertook all steps of the identification and data extraction process for multiple-method studies. We assessed risk of bias and applicability using our own modified and extended version of the QUality In Prognosis Studies (QUIPS) tool. We compared different techniques, exact promoter regions (5'-cytosine-phosphate-guanine-3' (CpG) sites) and thresholds for interpretation within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios (RHR), using an imputed value of the correlation between results based on the same individuals. MAIN RESULTS We included 32 independent cohorts involving 3474 people that compared two or more methods. We found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds (RHR 1.31, 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR 1.36, 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR 1.14, 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarised 190 articles describing a single method for measuring MGMT promoter methylation status. AUTHORS' CONCLUSIONS PSQ and MSP appear more prognostic for overall survival than IHC. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies making such comparisons.

Genome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n=1,194 and whole blood, n=31,684) and glioma subtype (all glioma (7,400 cases, 8,257 controls) glioblastoma (GBM, 3,112 cases) and non-GBM gliomas (2,411 cases)). We also leveraged tissuespecific eQTLs collected from 13 brain tissues (n=114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes ( RETREG2/FAM134A, FAM178B and MVB12B/FAM125B ). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes ( JAK1, STMN3, PICK1 and EGFR ). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.

This is a protocol for a Cochrane Review (Prognosis). The objectives are as follows:

BACKGROUND:This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. METHODS:A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of <60 ml/min/1.73 m2. Ultimately, 51 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included. RESULTS:Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD. In two independent replication analyses, we observed that increased hypertension risk showed reliable evidence of a causal effect on increasing CKD risk in Europeans but in contrast showed a null effect in East Asians. Although liability to T2D showed consistent effects on CKD, the effects of glycaemic phenotypes on CKD were weak. Non-linear Mendelian randomization indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI of >25 kg/m2. CONCLUSIONS:Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.

Neuroimaging offers a valuable insight into human brain development by allowing in vivo assessment of structure, connectivity and function. Multimodal neuroimaging data have been obtained as part of three sub-studies within the Avon Longitudinal Study of Parents and Children, a prospective multigenerational pregnancy and birth cohort based in the United Kingdom. Brain imaging data were acquired when offspring were between 18 and 24 years of age, and included acquisition of structural, functional and magnetization transfer magnetic resonance, diffusion tensor, and magnetoencephalography imaging. This resource provides a unique opportunity to combine neuroimaging data with extensive phenotypic and genotypic measures from participants, their mothers, and fathers.

Neuroimaging offers a valuable insight into human brain development by allowing in vivo assessment of structure, connectivity and function. Multimodal neuroimaging data have been obtained as part of three sub-studies within the Avon Longitudinal Study of Parents and Children, a prospective multigenerational pregnancy and birth cohort based in the United Kingdom. Brain imaging data were acquired when offspring were between 18 and 24 years of age, and included acquisition of structural, functional and magnetization transfer magnetic resonance, diffusion tensor, and magnetoencephalography imaging. This resource provides a unique opportunity to combine neuroimaging data with extensive phenotypic and genotypic measures from participants, their mothers, and fathers.