Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence.

Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.

Automatic fundus image quality assessment on a continuous scale.

Fundus photography is commonly used for screening, diagnosis, and monitoring of various diseases affecting the eye. In addition, it has shown promise in the diagnosis of brain diseases and evaluation of cardiovascular risk factors. Good image quality is important if diagnosis is to be accurate and timely. Here, we propose a method that automatically grades image quality on a continuous scale which is more flexible than binary quality classification. The method utilizes random forest regression models trained on image features discovered automatically by combining basic image filters using simulated annealing as well as features extracted with the discrete Fourier transform. The method was developed and tested on images from two different fundus camera models. The quality of those images was rated on a continuous scale from 0.0 to 1.0 by five experts. In addition, the method was tested on DRIMDB, a publicly available dataset with binary quality ratings. On the DRIMDB dataset the method achieves an accuracy of 0.981, sensitivity of 0.993 and specificity of 0.958 which is consistent with the state of the art. When evaluating image quality on a continuous scale the method outperforms human raters.

Associations of autozygosity with a broad range of human phenotypes.

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.

Surrogate potency assays: Comparison of binding profiles complements dose response curves for unambiguous assessment of relative potencies.

Surface plasmon resonance (SPR) systems are widely used for detailed characterization of antibody activities including antigen and Fc-receptor binding. During the later stages of development, where the focus is to ensure that established critical quality attributes (CQAs) are maintained during cell culture, purification and formulation processes, analysis is simplified, and relative potencies are often determined. Here, simulation of binding data revealed that relative potency values, determined via parallel line analysis (PLA) and half maximal effective concentration (EC50) analysis accurately reflect changes in active concentration only if binding kinetics remain unchanged. Changes in the association rate constant shifted dose response curves, and therefore relative potencies, in the same way as changes in analyte concentration do. However, for interactions characterized by stable binding, changes in the dissociation rate constant did not result in any shift, suggesting that this type of change may go unnoticed in the dose response curve. Thus, EC50 and PLA analyses of dose response curves obtained with an anti-TNF-α antibody were complemented with the Biacore functionality for sensorgram comparison analysis, whereby changes in antigen and Fc-receptor binding profiles could be detected. Next, analysis of temperature stressed TNF-α antibody revealed that calibration free concentration analysis (CFCA) data correlated perfectly with relative potency values. Together, these results demonstrate that combinations of SPR based dose response curves, sensorgram comparison and CFCA can be used to strengthen the confidence in relative potency assessments, and suggest that SPR can potentially be used as a surrogate potency assay in the quality control of biotherapeutic medicines.

A population-based assessment of germline HOXB13 G84E mutation and prostate cancer risk.

BACKGROUND: A rare but recurrent missense mutation (G84E, rs138213197) in the gene homeobox B13 (HOXB13) was recently reported to be associated with hereditary prostate cancer. OBJECTIVE: To explore the prevalence and penetrance of HOXB13 G84E in a general population. DESIGN, SETTING, AND PARTICIPANTS: G84E and 14 additional HOXB13 polymorphisms were genotyped in two population-based, Swedish, case-control samples (Cancer of the Prostate in Sweden [CAPS] and Stockholm-1) comprising 4693 controls and 5003 prostate cancer cases. CAPS collected data on patients and population controls nationally between 2001 and 2003. Stockholm-1 collected data on biopsy-positive patients and biopsy-negative controls in the Stockholm area between 2005 and 2007. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The outcome was pathologically verified prostate cancer. Relative and absolute risks among HOXB13 G84E mutation carriers were explored, as was the combined impact on disease risk of G84E and a polygenic score based on 33 established, common, low-risk variants. RESULTS AND LIMITATIONS: HOXB13 G84E was observed in 1.3% of population controls and was strongly associated with prostate cancer risk (CAPS: odds ratio [OR]: 3.4; 95% confidence interval [CI], 2.2-5.4; Stockholm-1: OR: 3.5; 95% CI, 2.4-5.2). The strongest association was observed for young-onset (OR: 8.6; 95% CI, 5.1-14.0) and hereditary (OR: 6.6; 95% CI, 3.3-12.0) prostate cancer. Haplotype analyses supported that G84E is a founder mutation. G84E carriers have an estimated 33% (95% CI, 23-46) cumulative risk to age 80 yr of prostate cancer, compared to 12% (95% CI, 11-13) among noncarriers. For G84E carriers within the top quartile of a polygenic score of established susceptibility variants, the cumulative risk was estimated at 48% (95% CI, 36-64). CONCLUSIONS: HOXB13 G84E is prevalent in >1% of the Swedish population and is associated with a 3.5-fold increased risk of prostate cancer. One-third of G84E carriers will be diagnosed with prostate cancer, which has implications for surveillance in mutation carriers.

A genome-wide assessment of variability in human serum metabolism.

The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10(-13) -10(-91)). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.

Statistical aspects of van't Hoff analysis: a simulation study.

The thermodynamics of biological interactions is frequently studied by the van't Hoff analysis whereby data on variation of the binding constant K(D) with temperature are used to obtain estimates of standard enthalpy (Delta H degrees ), entropy (Delta S degrees ), and heat capacity (Delta C degrees P) of complex formation. A Monte Carlo simulation demonstrates that the absolute error of the above parameters is proportional to the relative error of KD and independent of the actual values of KD and of the way they vary with temperature. The error of Delta H degrees is approximately the same as that of T Delta S degrees (within 14% in the temperature range 5-45 degrees C). The error depends both on the number of temperature points within the experimental temperature range and on the size of the range, but it is more sensitive to the latter. Using the linear form of the van't Hoff equation to fit data with non-zero Delta C degrees P gives erroneous Delta H degrees and DeltaS degrees estimates at standard temperature except for the case when the T points are placed symmetrically with respect to the standard temperature. With the range of Delta C degrees P values usual for protein-protein interactions, the KD error must be very low to confidently infer that Delta C degrees P is non-zero or to claim that two interactions have different Delta C degrees P.