Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays.

Most epigenetic epidemiology to date has utilized microarrays to identify positions in the genome where variation in DNA methylation is associated with environmental exposures or disease. However, these profile less than 3% of DNA methylation sites in the human genome, potentially missing affected loci and preventing the discovery of disrupted biological pathways. Third generation sequencing technologies, including Nanopore sequencing, have the potential to revolutionize the generation of epigenetic data, not only by providing genuine genome-wide coverage but profiling epigenetic modifications direct from native DNA. Here we assess the viability of using Nanopore sequencing for epidemiology by performing a comparison with DNA methylation quantified using the most comprehensive microarray available, the Illumina EPIC array. We implemented a CRISPR-Cas9 targeted sequencing approach in concert with Nanopore sequencing to profile DNA methylation in three genomic regions to attempt to rediscover genomic positions that existing technologies have shown are differentially methylated in tobacco smokers. Using Nanopore sequencing reads, DNA methylation was quantified at 1779 CpGs across three regions, providing a finer resolution of DNA methylation patterns compared to the EPIC array. The correlation of estimated levels of DNA methylation between platforms was high. Furthermore, we identified 12 CpGs where hypomethylation was significantly associated with smoking status, including 10 within the AHRR gene. In summary, Nanopore sequencing is a valid option for identifying genomic loci where large differences in DNAm are associated with a phenotype and has the potential to advance our understanding of the role differential methylation plays in the etiology of complex disease.

Triangulating evidence from observational and Mendelian randomization studies of ketone bodies for cognitive performance.

BACKGROUND: Ketone bodies (KBs) are an alternative energy supply for brain functions when glucose is limited. The most abundant ketone metabolite, 3-ß-hydroxybutyrate (BOHBUT), has been suggested to prevent or delay cognitive impairment, but the evidence remains unclear. We triangulated observational and Mendelian randomization (MR) studies to investigate the association and causation between KBs and cognitive function. METHODS: In observational analyses of 5506 participants aged ≥ 45 years from the Whitehall II study, we used multiple linear regression to investigate the associations between categorized KBs and cognitive function scores. Two-sample MR was carried out using summary statistics from an in-house KBs meta-analysis between the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium and Kettunen et al. (N = 45,031), and publicly available summary statistics of cognitive performance and Alzheimer's disease (AD) from the Social Science Genetic Association Consortium (N = 257,841), and the International Genomics of Alzheimer's Project (N = 54,162), respectively. Both strong (P < 5 × 10-8) and suggestive (P < 1 × 10-5) sets of instrumental variables for BOHBUT were applied. Finally, we performed cis-MR on OXCT1, a well-known gene for KB catabolism. RESULTS: BOHBUT was positively associated with general cognitive function (ß = 0.26, P = 9.74 × 10-3). In MR analyses, we observed a protective effect of BOHBUT on cognitive performance (inverse variance weighted: ßIVW = 7.89 × 10-2, PIVW = 1.03 × 10-2; weighted median: ßW-Median = 8.65 × 10-2, PW-Median = 9.60 × 10-3) and a protective effect on AD (ßIVW = - 0.31, odds ratio: OR = 0.74, PIVW = 3.06 × 10-2). Cis-MR showed little evidence of therapeutic modulation of OXCT1 on cognitive impairment. CONCLUSIONS: Triangulation of evidence suggests that BOHBUT has a beneficial effect on cognitive performance. Our findings raise the hypothesis that increased BOHBUT may improve general cognitive functions, delaying cognitive impairment and reducing the risk of AD.

Does the feedback of blood results in observational studies influence response and consent? A randomised study of the Understanding Society Innovation Panel.

BACKGROUND: While medical studies generally provide health feedback to participants, in observational studies this is not always the case due to logistical and financial difficulties, or concerns about changing observed behaviours. However, evidence suggests that lack of feedback may deter participants from providing biological samples. This paper investigates the effect of offering feedback of blood results on participation in biomeasure sample collection. METHODS: Participants aged 16 and over from a longitudinal study - the Understanding Society Innovation Panel-were randomised to three arms - nurse interviewer, interviewer, web survey - and invited to participate in biomeasures data collection. Within each arm they were randomised to receive feedback of their blood results or not. For those interviewed by a nurse both venous and dried blood samples (DBS) were taken in the interview. For the other two arms, they were asked if they would be willing to take a sample, and if they agreed a DBS kit was left or sent to them so the participant could take their own sample and return it. Blood samples were analysed and, if in the feedback arms, participants were sent their total cholesterol and HbA1c results. Response rates for feedback and non-feedback groups were compared: overall; in each arm of the study; by socio-demographic and health characteristics; and by previous study participation. Logistic regression models of providing a blood sample by feedback group and data collection approach controlling for confounders were calculated. RESULTS: Overall 2162 (80.3% of individuals in responding households) took part in the survey; of those 1053 (48.7%) consented to provide a blood sample. Being offered feedback had little effect on overall participation but did increase consent to provide a blood sample (unadjusted OR 1.38; CI: 1.16-1.64). Controlling for participant characteristics, the effect of feedback was highest among web participants (1.55; 1.11-2.17), followed by interview participants (1.35; 0.99 -1.84) and then nurse interview participants (1.30; 0.89-1.92). CONCLUSIONS: Offering feedback of blood results increased willingness to give samples, especially for those taking part in a web survey.

Density functional theory studies on molecular geometry, spectroscopy, HOMO-LUMO and reactivity descriptors of titanium(IV) and oxidozirconium(IV) complexes of phenylacetohydroxamic acid.

The molecular geometry of new titanium(IV) and oxidozirconium(IV) phenylacetohydroxamate complexes [TiCl2 (L1)2 ] (I) and [ZrO(L1)2 ] (II) (where L1 = Potassium phenylacetohydroxamate = C6 H5 CH2 CONHOK) computed by B3LYP/6-311++G(d,p) method has shown these to be distorted octahedral and square pyramidal, respectively. A comparison of computed characteristic bond lengths (CO, CN, and NO) of complexes with that of free ligand has shown chelation through carbonyl and hydroxamic oxygen atoms (O, O coordination). The TiO/ZrO bond lengths in complexes are suggestive of weak coordination through (carbonyl CO) and strong covalent (hydroxamic NO) bonding of the ligand. The magnitude of ClTiCl bond angle involving two chloride atoms is suggestive of cis-conformation at titanium metal in (I). The thermodynamic parameters Gibbs free energy, enthalpy, entropy, nuclear internal energy, constant volume heat capacity, and internal energy of ligand and complexes have been computed. From the energies of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), the global reactivity descriptors such as ionization potential (IP), electron affinity (EA), chemical potential (µ), hardness (η), softness (S), electronegativity (χ), electrophilicity index (ω), and dipole moment have been calculated. The computed vibrational frequencies, 1 H and 13 C NMR spectra have substantiated the molecular structure of complexes. The thermal behavior of complexes has been studied by thermogravimetric techniques (TGA, DTG, and DTA) in N2 atmosphere has shown complexes are thermally stable.

The mental health impact of COVID-19 and lockdown-related stressors among adults in the UK.

BACKGROUND: The COVID-19 pandemic in the UK and subsequent lockdown may have affected the mental health of the population. This study examines whether there was an increase in the prevalence and incidence of common mental disorders (CMD) in the UK adult population during the first months of lockdown and whether changes in CMD were associated with stressors related to the pandemic and lockdown. METHODS: Longitudinal data from the UK Household Longitudinal Study waves 10-11: 2019-2020 and waves 1-4 of the COVID-19 monthly surveys in April (n = 17 761) to July 2020 (n = 13 754), a representative sample of UK adult population, were analysed. CMD was measured using the 12-item General Health Questionnaire (GHQ-12) (cut-off >2). Changes in CMD were analysed in relation to COVID-19 and social stressors. RESULTS: Around 29% of adults without CMD less than a year earlier had a CMD in April 2020. However, by July 2020, monthly incidence of CMD had reduced to 9%. Most employment, financial and psychological 'shocks' were at their highest levels in April and reduced steadily in later months. Despite the lifting of some lockdown conditions by July, stressors related to loneliness, unemployment, financial problems and domestic work continued to influence CMD. CONCLUSION: Some COVID-19 policy responses such as furloughing may have been effective in mitigating the increase in CMD for some groups of employees. Despite some reduction in levels of pandemic and lockdown-related stressors by the middle of 2020, loneliness and financial stressors remained key determinants of incidence in CMD among the UK adult population.

Biological costs and benefits of social relationships for men and women in adulthood: The role of partner, family and friends.

Despite numerous studies on social relationships and health, the empirical focus has often been on middle-aged or older adults, even though young adulthood is a period of considerable change in social networks. We investigated whether the associations between social relationships and allostatic load, a multisystem physiological dysregulation index that reflects chronic stress responses, vary by type of relationship and stages of the lifecourse. Relationships with spouse/partner, immediate family and friends were assessed in terms of emotional support and social strain. Poisson regression models on multiple imputed data sets from waves 2-3 (2010-2012) of the UK Household Longitudinal Study (N = 10,380) were estimated. Social strain, particularly from partners and immediate family, appeared to elicit greater stress related dysregulation during early adulthood (age 21-34 years), corresponding to a predicted difference in the allostatic load index (range 0-12) between high and low strained relationships of 1.1 (95% CI: 0.5-1.6) among young women and 0.6 (95% CI: -0.04 to 1.2) among young men. There was little evidence of an association between allostatic load and any of the social relationships among older men and women. Models of social relationships over the lifecourse need to take account of how stressful social relationships become biologically embedded in early adulthood.

DNA methylation-based sex classifier to predict sex and identify sex chromosome aneuploidy.

BACKGROUND: Sex is an important covariate of epigenome-wide association studies due to its strong influence on DNA methylation patterns across numerous genomic positions. Nevertheless, many samples on the Gene Expression Omnibus (GEO) frequently lack a sex annotation or are incorrectly labelled. Considering the influence that sex imposes on DNA methylation patterns, it is necessary to ensure that methods for filtering poor samples and checking of sex assignment are accurate and widely applicable. RESULTS: Here we presented a novel method to predict sex using only DNA methylation beta values, which can be readily applied to almost all DNA methylation datasets of different formats (raw IDATs or text files with only signal intensities) uploaded to GEO. We identified 4345 significantly (p<0.01) sex-associated CpG sites present on both 450K and EPIC arrays, and constructed a sex classifier based on the two first principal components of the DNA methylation data of sex-associated probes mapped on sex chromosomes. The proposed method is constructed using whole blood samples and exhibits good performance across a wide range of tissues. We further demonstrated that our method can be used to identify samples with sex chromosome aneuploidy, this function is validated by five Turner syndrome cases and one Klinefelter syndrome case. CONCLUSIONS: This proposed sex classifier not only can be used for sex predictions but also applied to identify samples with sex chromosome aneuploidy, and it is freely and easily accessible by calling the 'estimateSex' function from the newest wateRmelon Bioconductor package ( https://github.com/schalkwyk/wateRmelon ).

Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits.

Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. We undertook a comprehensive analysis of common genetic variation on DNA methylation (DNAm) by using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (p < 6.52 × 10-14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified by previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits by using summary-data-based Mendelian randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression and thereby identify 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database as a resource to the research community.

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory.

BACKGROUND/OBJECTIVES: The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain. SUBJECTS/METHODS: We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of 'disinhibition', indicative of opportunistic eating or overeating and 'hunger' which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex. RESULTS: Disinhibition was associated with higher BMI (ß = 2.96; 95% CI: 2.66-3.25 kg/m2), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (ß = 1.20; 0.82-1.59 kg/m2) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition. CONCLUSIONS: Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry.

Genome-Wide Association Study Identifies Two Novel Loci Associated with Female Stress and Urgency Urinary Incontinence.

PURPOSE: Genome-wide association studies have not identified replicable genetic risk loci for stress or urgency urinary incontinence. MATERIALS AND METHODS: We carried out a discovery stage, case control, genome-wide association study in 3 independent discovery cohorts of European women (8,979) for stress incontinence, urgency incontinence, and any incontinence phenotypes. We conducted replication in 6 additional studies of European ancestry (4,069). We collected bladder biopsies from women with incontinence (50) to further investigate bladder expression of implicated genes and pathways and used symptom questionnaires for phenotyping. We conducted meta-analyses using inverse variance fixed effects models and whole transcriptome analyses using Affymetrix® arrays with replication with TaqMan® polymerase chain reaction. RESULTS: In the discovery stage, we identified 16 single nucleotide polymorphisms genotyped or imputed at 5 loci that reached genome-wide significance (p <5×10-8). In replication, rs138724718 on chromosome 2 near the macrophage receptor with collagenous structure (MARCO) gene (replication p=0.003) was associated with stress incontinence. In addition, rs34998271 on chromosome 6 near the endothelin 1 (EDN1) gene (replication p=0.0008) was associated with urgency incontinence. In combined meta-analyses of discovery and replication cohorts, associations with genome-wide significance for these 2 single nucleotide polymorphisms were confirmed. Transcriptomics analyses showed differential expression of 7 of 19 genes in the endothelin pathway between stress and urgency incontinence (p <0.0001). CONCLUSIONS: We uncovered 2 new risk loci near the genes endothelin 1 (EDN1), associated with urgency incontinence, and macrophage receptor with collagenous structure (MARCO), associated with stress incontinence. These loci are biologically plausible given their roles in smooth muscle contraction and innate host defense, respectively.

Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex.

Human DNA methylation data have been used to develop biomarkers of ageing, referred to as 'epigenetic clocks', which have been widely used to identify differences between chronological age and biological age in health and disease including neurodegeneration, dementia and other brain phenotypes. Existing DNA methylation clocks have been shown to be highly accurate in blood but are less precise when used in older samples or in tissue types not included in training the model, including brain. We aimed to develop a novel epigenetic clock that performs optimally in human cortex tissue and has the potential to identify phenotypes associated with biological ageing in the brain. We generated an extensive dataset of human cortex DNA methylation data spanning the life course (n = 1397, ages = 1 to 108 years). This dataset was split into 'training' and 'testing' samples (training: n = 1047; testing: n = 350). DNA methylation age estimators were derived using a transformed version of chronological age on DNA methylation at specific sites using elastic net regression, a supervised machine learning method. The cortical clock was subsequently validated in a novel independent human cortex dataset (n = 1221, ages = 41 to 104 years) and tested for specificity in a large whole blood dataset (n = 1175, ages = 28 to 98 years). We identified a set of 347 DNA methylation sites that, in combination, optimally predict age in the human cortex. The sum of DNA methylation levels at these sites weighted by their regression coefficients provide the cortical DNA methylation clock age estimate. The novel clock dramatically outperformed previously reported clocks in additional cortical datasets. Our findings suggest that previous associations between predicted DNA methylation age and neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calibrated to the tissue being tested and for phenotypes that become manifest in older ages. The age distribution and tissue type of samples included in training datasets need to be considered when building and applying epigenetic clock algorithms to human epidemiological or disease cohorts.

A Bidirectional Mendelian Randomization Study to evaluate the causal role of reduced blood vitamin D levels with type 2 diabetes risk in South Asians and Europeans.

CONTEXT: Multiple observational studies have reported an inverse relationship between 25-hydroxyvitamin D concentrations (25(OH)D) and type 2 diabetes (T2D). However, the results of short- and long-term interventional trials concerning the relationship between 25(OH)D and T2D risk have been inconsistent. OBJECTIVES AND METHODS: To evaluate the causal role of reduced blood 25(OH)D in T2D, here we have performed a bidirectional Mendelian randomization study using 59,890 individuals (5,862 T2D cases and 54,028 controls) from European and Asian Indian ancestries. We used six known SNPs, including three T2D SNPs and three vitamin D pathway SNPs, as a genetic instrument to evaluate the causality and direction of the association between T2D and circulating 25(OH)D concentration. RESULTS: Results of the combined meta-analysis of eight participating studies showed that a composite score of three T2D SNPs would significantly increase T2D risk by an odds ratio (OR) of 1.24, p = 1.82 × 10-32; Z score 11.86, which, however, had no significant association with 25(OH)D status (Beta -0.02nmol/L ± SE 0.01nmol/L; p = 0.83; Z score -0.21). Likewise, the genetically instrumented composite score of 25(OH)D lowering alleles significantly decreased 25(OH)D concentrations (-2.1nmol/L ± SE 0.1nmol/L, p = 7.92 × 10-78; Z score -18.68) but was not associated with increased risk for T2D (OR 1.00, p = 0.12; Z score 1.54). However, using 25(OH)D synthesis SNP (DHCR7; rs12785878) as an individual genetic instrument, a per allele reduction of 25(OH)D concentration (-4.2nmol/L ± SE 0.3nmol/L) was predicted to increase T2D risk by 5%, p = 0.004; Z score 2.84. This effect, however, was not seen in other 25(OH)D SNPs (GC rs2282679, CYP2R1 rs12794714) when used as an individual instrument. CONCLUSION: Our new data on this bidirectional Mendelian randomization study suggests that genetically instrumented T2D risk does not cause changes in 25(OH)D levels. However, genetically regulated 25(OH)D deficiency due to vitamin D synthesis gene (DHCR7) may influence the risk of T2D.

Assessing potential shared genetic aetiology between body mass index and sleep duration in 142,209 individuals.

Observational studies find an association between increased body mass index (BMI) and short self-reported sleep duration in adults. However, the underlying biological mechanisms that underpin these associations are unclear. Recent findings from the UK Biobank suggest a weak genetic correlation between BMI and self-reported sleep duration. However, the potential shared genetic aetiology between these traits has not been examined using a comprehensive approach. To investigate this, we created a polygenic risk score (PRS) of BMI and examined its association with self-reported sleep duration in a combination of individual participant data and summary-level data, with a total sample size of 142,209 individuals. Although we observed a nonsignificant genetic correlation between BMI and sleep duration, using LD score regression (rg = -0.067 [SE = 0.039], P = 0.092) we found that a PRS of BMI is associated with a decrease in sleep duration (unstandardized coefficient = -1.75 min [SE = 0.67], P = 6.13 × 10-7 ), but explained only 0.02% of the variance in sleep duration. Our findings suggest that BMI and self-reported sleep duration possess a small amount of shared genetic aetiology and other mechanisms must underpin these associations.

Bigmelon: tools for analysing large DNA methylation datasets.

MOTIVATION: The datasets generated by DNA methylation analyses are getting bigger. With the release of the HumanMethylationEPIC micro-array and datasets containing thousands of samples, analyses of these large datasets using R are becoming impractical due to large memory requirements. As a result there is an increasing need for computationally efficient methodologies to perform meaningful analysis on high dimensional data. RESULTS: Here we introduce the bigmelon R package, which provides a memory efficient workflow that enables users to perform the complex, large scale analyses required in epigenome wide association studies (EWAS) without the need for large RAM. Building on top of the CoreArray Genomic Data Structure file format and libraries packaged in the gdsfmt package, we provide a practical workflow that facilitates the reading-in, preprocessing, quality control and statistical analysis of DNA methylation data.We demonstrate the capabilities of the bigmelon package using a large dataset consisting of 1193 human blood samples from the Understanding Society: UK Household Longitudinal Study, assayed on the EPIC micro-array platform. AVAILABILITY AND IMPLEMENTATION: The bigmelon package is available on Bioconductor (http://bioconductor.org/packages/bigmelon/). The Understanding Society dataset is available at https://www.understandingsociety.ac.uk/about/health/data upon request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

[This corrects the article DOI: 10.1371/journal.pgen.1006528.].

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Guidance for DNA methylation studies: statistical insights from the Illumina EPIC array.

BACKGROUND: There has been a steady increase in the number of studies aiming to identify DNA methylation differences associated with complex phenotypes. Many of the challenges of epigenetic epidemiology regarding study design and interpretation have been discussed in detail, however there are analytical concerns that are outstanding and require further exploration. In this study we seek to address three analytical issues. First, we quantify the multiple testing burden and propose a standard statistical significance threshold for identifying DNA methylation sites that are associated with an outcome. Second, we establish whether linear regression, the chosen statistical tool for the majority of studies, is appropriate and whether it is biased by the underlying distribution of DNA methylation data. Finally, we assess the sample size required for adequately powered DNA methylation association studies. RESULTS: We quantified DNA methylation in the Understanding Society cohort (n = 1175), a large population based study, using the Illumina EPIC array to assess the statistical properties of DNA methylation association analyses. By simulating null DNA methylation studies, we generated the distribution of p-values expected by chance and calculated the 5% family-wise error for EPIC array studies to be 9 × 10- 8. Next, we tested whether the assumptions of linear regression are violated by DNA methylation data and found that the majority of sites do not satisfy the assumption of normal residuals. Nevertheless, we found no evidence that this bias influences analyses by increasing the likelihood of affected sites to be false positives. Finally, we performed power calculations for EPIC based DNA methylation studies, demonstrating that existing studies with data on ~ 1000 samples are adequately powered to detect small differences at the majority of sites. CONCLUSION: We propose that a significance threshold of P < 9 × 10- 8 adequately controls the false positive rate for EPIC array DNA methylation studies. Moreover, our results indicate that linear regression is a valid statistical methodology for DNA methylation studies, despite the fact that the data do not always satisfy the assumptions of this test. These findings have implications for epidemiological-based studies of DNA methylation and provide a framework for the interpretation of findings from current and future studies.

Urea can inhibit efficient reduction and alkylation of protein dimers in solution demonstrated by the beta subunit of alpha glucosidase II.

Protein reduction and alkylation is routinely used for analysis of protein dimers and protein complexes in cell fractions using two dimensional gel electrophoresis and mass spectrometry. To resolve the heterogeneity of a high molecular weight protein band that is highlighted by an antibody to the beta subunit of alpha glucosidase II (GIIß), we performed reduction and alkylation of cytosolic proteins extracted from mouse brain. The presence of urea in the reduction/alkylation buffer inhibited the chemical processes. It is thus recommended that protein reduction/alkylation be performed both in the presence and absence of urea for the separation of mono-/hetero-mers.

Better governance, better access: practising responsible data sharing in the METADAC governance infrastructure.

BACKGROUND: Genomic and biosocial research data about individuals is rapidly proliferating, bringing the potential for novel opportunities for data integration and use. The scale, pace and novelty of these applications raise a number of urgent sociotechnical, ethical and legal questions, including optimal methods of data storage, management and access. Although the open science movement advocates unfettered access to research data, many of the UK's longitudinal cohort studies operate systems of managed data access, in which access is governed by legal and ethical agreements between stewards of research datasets and researchers wishing to make use of them. Amongst other things, these agreements aim to respect the reasonable expectations of the research participants who provided data and samples, as expressed in the consent process. Arguably, responsible data management and governance of data and sample use are foundational to the consent process in longitudinal studies and are an important source of trustworthiness in the eyes of those who contribute data to genomic and biosocial research. METHODS: This paper presents an ethnographic case study exploring the foundational principles of a governance infrastructure for Managing Ethico-social, Technical and Administrative issues in Data ACcess (METADAC), which are operationalised through a committee known as the METADAC Access Committee. METADAC governs access to phenotype, genotype and 'omic' data and samples from five UK longitudinal studies. FINDINGS: Using the example of METADAC, we argue that three key structural features are foundational for practising responsible data sharing: independence and transparency; interdisciplinarity; and participant-centric decision-making. We observe that the international research community is proactively working towards optimising the use of research data, integrating/linking these data with routine data generated by health and social care services and other administrative data services to improve the analysis, interpretation and utility of these data. The governance of these new complex data assemblages will require a range of expertise from across a number of domains and disciplines, including that of study participants. Human-mediated decision-making bodies will be central to ensuring achievable, reasoned and responsible decisions about the use of these data; the METADAC model described in this paper provides an example of how this could be realised.

In Vitro Cytotoxicity and Interaction of Noscapine with Human Serum Albumin: Effect on Structure and Esterase Activity of HSA.

Noscapine is effective to inhibit cellular proliferation and induced apoptosis in nonsmall cell, lung, breast, lymphoma, and prostate cancer. It also shows good efficiency to skin cancer cells. In the current work, we studied the mechanism of interaction between the anticancer drug noscapine (NOS) and carrier protein human serum albumin (HSA) by using a variety of spectroscopic techniques (fluorescence spectroscopy, time-resolved fluorescence, UV-visible, fluorescence resonance energy transfer (FRET), Fourier transform infrared (FTIR), and circular dichroism (CD) spectroscopy), electrochemistry (cyclic voltammetry), and computational methods (molecular docking and molecular dynamic simulation). The steady-state fluorescence results showed that fluorescence intensity of HSA decreased in the presence of NOS via a static quenching mechanism, which involves ground state complex formation between NOS and HSA. UV-visible and FRET results also supported the fluorescence result. The corresponding thermodynamic result shows that binding of NOS with HSA is exothermic in nature, involving electrostatic interactions as major binding forces. The binding results were further confirmed through a cyclic voltammetry approach. The FRET result signifies the energy transfer from Trp214 of HSA to the NOS. Molecular site marker, molecular docking, and MD simulation results indicated that the principal binding site of HSA for NOS is site I. Synchronous fluorescence spectra, FTIR, 3D fluorescence, CD spectra, and MD simulation results reveal that NOS induced the structural change in HSA. In addition, the MTT assay study on a human skin cancer cell line (A-431) was also performed for NOS, which shows that NOS induced 80% cell death of the population at a 320 µM concentration. Moreover, the esterase-like activity of HSA with NOS was also done to determine the variation in protein functionality after binding with NOS.