Search

Runs-of-homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE (runs-of-homozygous diplotype cluster enumerator), to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 single nucleotide polymorphisms (SNPs) and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended human leukocyte antigen (HLA) region and autoimmune disorders. We found an association between a diplotype covering the homeostatic iron regulator (HFE) gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (p-value = 1.82 × 10 -11 ). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale., Competing Interests: AN, DZ, SZ No competing interests declared, (© 2024, Naseri et al.)

Background: Lower birth weight is associated with diabetes although the underlying mechanisms are unclear. Muscle mass could be a modifiable link and hence a target of intervention. We assessed the associations of birth weight with muscle and fat mass observationally in a population with little socio-economic patterning of birth weight and using Mendelian randomization (MR) for validation. Methods: In the population-representative “Children of 1997” birth cohort (n = 8,327), we used multivariable linear regression to assess the adjusted associations of birth weight (kg) with muscle mass (kg) and body fat (%) at ~17.5 years. Genetically predicted birth weight (effect size) was applied to summary genetic associations with fat-free mass and fat mass (kg) from the UK Biobank (n = ~331,000) to obtain unconfounded estimates using inverse-variance weighting. Results: Observationally, birth weight was positively associated with muscle mass (3.29 kg per kg birth weight, 95% confidence interval (CI) 2.83 to 3.75) and body fat (1.09% per kg birth weight, 95% CI 0.54 to 1.65). Stronger associations with muscle mass were observed in boys than in girls (p for interaction 0.004). Using MR, birth weight was positively associated with fat-free mass (0.77 kg per birth weight z-score, 95% CI 0.22 to 1.33) and fat mass (0.58, 95% CI 0.01 to 1.15). No difference by sex was evident. Conclusion: Higher birth weight increasing muscle mass may be relevant to lower birth weight increasing the risk of diabetes and suggests post-natal muscle mass as a potential target of intervention. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews of randomised controlled trials (RCTs) have suggested that maternal vitamin D (25[OH]D) and calcium supplementation increase birth weight. However, limitations of many trials were highlighted in the reviews. Our aim was to combine genetic and RCT data to estimate causal effects of these two maternal traits on offspring birth weight.Methods and Findings: We performed two-sample mendelian randomisation (MR) using genetic instrumental variables associated with 25(OH)D and calcium that had been identified in genome-wide association studies (GWAS; sample 1; N = 122,123 for 25[OH]D and N = 61,275 for calcium). Associations between these maternal genetic variants and offspring birth weight were calculated in the UK Biobank (UKB) (sample 2; N = 190,406). We used data on mother-child pairs from two United Kingdom birth cohorts (combined N = 5,223) in sensitivity analyses to check whether results were influenced by fetal genotype, which is correlated with the maternal genotype (r ≈ 0.5). Further sensitivity analyses to test the reliability of the results included MR-Egger, weighted-median estimator, 'leave-one-out', and multivariable MR analyses. We triangulated MR results with those from RCTs, in which we used randomisation to supplementation with vitamin D (24 RCTs, combined N = 5,276) and calcium (6 RCTs, combined N = 543) as an instrumental variable to determine the effects of 25(OH)D and calcium on birth weight. In the main MR analysis, there was no strong evidence of an effect of maternal 25(OH)D on birth weight (difference in mean birth weight -0.03 g [95% CI -2.48 to 2.42 g, p = 0.981] per 10% higher maternal 25[OH]D). The effect estimate was consistent across our MR sensitivity analyses. Instrumental variable analyses applied to RCTs suggested a weak positive causal effect (5.94 g [95% CI 2.15-9.73, p = 0.002] per 10% higher maternal 25[OH]D), but this result may be exaggerated because of risk of bias in the included RCTs. The main MR analysis for maternal calcium also suggested no strong evidence of an effect on birth weight (-20 g [95% CI -44 to 5 g, p = 0.116] per 1 SD higher maternal calcium level). Some sensitivity analyses suggested that the genetic instrument for calcium was associated with birth weight via exposures that are independent of calcium levels (horizontal pleiotropy). Application of instrumental variable analyses to RCTs suggested that calcium has a substantial effect on birth weight (178 g [95% CI 121-236 g, p = 1.43 × 10-9] per 1 SD higher maternal calcium level) that was not consistent with any of the MR results. However, the RCT instrumental variable estimate may have been exaggerated because of risk of bias in the included RCTs. Other study limitations include the low response rate of UK Biobank, which may bias MR estimates, and the lack of suitable data to test whether the effects of genetic instruments on maternal calcium levels during pregnancy were the same as those outside of pregnancy.Conclusions: Our results suggest that maternal circulating 25(OH)D does not influence birth weight in otherwise healthy newborns. However, the effect of maternal circulating calcium on birth weight is unclear and requires further exploration with more research including RCT and/or MR analyses with more valid instruments. [ABSTRACT FROM AUTHOR]

Introduction: The UK Biobank (UKB) is a resource that includes detailed health-related data on about 500,000 individuals and is available to the research community. However, several obstacles limit immediate analysis of the data: data files vary in format, may be very large, and have numerical codes for column names. Results: ukbtools removes all the upfront data wrangling required to get a single dataset for statistical analysis. All associated data files are merged into a single dataset with descriptive column names. The package also provides tools to assist in quality control by exploring the primary demographics of subsets of participants; query of disease diagnoses for one or more individuals, and estimating disease frequency relative to a reference variable; and to retrieve genetic metadata. Conclusion: Having a dataset with meaningful variable names, a set of UKB-specific exploratory data analysis tools, disease query functions, and a set of helper functions to explore and write genetic metadata to file, will rapidly enable UKB users to undertake their research. [ABSTRACT FROM AUTHOR]

Introduction and aims: Since 2013 MenC and MenW disease incidence and associated mortality rates have increased in the Republic of Ireland. From 2002/2003 to 2012/2013, the average annual MenC incidence was 0.08/100,000, which increased to 0.34/100,000 during 2013/2014 to 2017/18, peaking in 2016/17 (0.72/100,000) with an associated case fatality rate (CFR) of 14.7%. MenW disease incidence has increased each year from 0.02/100,000 in 2013/2014, to 0.29/100,000 in 2017/18, with an associated CFR of 28.6%. We aimed to characterise and relate recent MenC isolates to the previously prevalent MenC:cc11 ET-15 clones, and also characterise and relate recent MenW isolates to the novel ‘Hajj’ clones. Methods: Using WGS we characterised invasive (n = 74, 1997/98 to 2016/17) and carried (n = 16, 2016/17) MenC isolates, and invasive (n = 18, 2010/11 to 2016/17) and carried (n = 15, 2016/17) MenW isolates. Genomes were assembled using VelvethOptimiser and stored on the PubMLST Neisseria Bacterial Isolate Genome Sequence Database. Isolates were compared using the cgMLST approach. Results: Most MenC and MenW isolates identified were cc11. A single MenC:cc11 sub-lineage contained the majority (68%, n = 19/28) of recent MenC:cc11 disease isolates and all carried MenC:cc11 isolates, which were interspersed and distinct from the historically significant ET-15 clones. MenW:cc11 study isolates clustered among international examples of both the original UK 2009 MenW:cc11, and novel 2013 MenW:cc11clones. Conclusions: We have shown that the majority of recent MenC disease incidence was caused by strain types distinct from the MenC:cc11 ET-15 clone of the late 1990s, which still circulate but have caused only sporadic disease in recent years. We have identified that the same aggressive MenW clone now established in several other European countries, is endemic in the RoI and responsible for the recent MenW incidence increases. This data informed the National immunisation Advisory Committee, who are currently deliberating a vaccine policy change to protect teenagers. [ABSTRACT FROM AUTHOR]

Background: Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis.Methods and Findings: Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10(-60)). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10(-9)). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied.Conclusions: Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) is a complex disorder characterized by high blood sugar, insulin resistance, and relative lack of insulin. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in T2D using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 357 SNPs was found to have the best predictive accuracy in a British population. A weighted risk score calculated by using this set produced an area under the curve (AUC) score of 0.86, which is comparable to risk models built by phenotypic markers. These results identify a novel genetic risk element in T2D susceptibility and provide a potentially useful genetic method to identify individuals with high risk of T2D. [ABSTRACT FROM AUTHOR]

Prediction and control of the spread of infectious disease in human populations benefits greatly from our growing capacity to quantify human movement behavior. Here we develop a mathematical model for non-transmissible infections contracted from a localized environmental source, informed by a detailed description of movement patterns of the population of Great Britain. The model is applied to outbreaks of Legionnaires' disease, a potentially life-threatening form of pneumonia caused by the bacteria Legionella pneumophilia. We use case-report data from three recent outbreaks that have occurred in Great Britain where the source has already been identified by public health agencies. We first demonstrate that the amount of individual-level heterogeneity incorporated in the movement data greatly influences our ability to predict the source location. The most accurate predictions were obtained using reported travel histories to describe movements of infected individuals, but using detailed simulation models to estimate movement patterns offers an effective fast alternative. Secondly, once the source is identified, we show that our model can be used to accurately determine the population likely to have been exposed to the pathogen, and hence predict the residential locations of infected individuals. The results give rise to an effective control strategy that can be implemented rapidly in response to an outbreak. [ABSTRACT FROM AUTHOR]

Squirrelpox virus (SQPV) shows little evidence for morbidity or mortality in North American grey squirrels (Sciurus carolinensis), in which the virus is endemic. However, more recently the virus has emerged to cause epidemics with high mortality in Eurasian red squirrels (S. vulgaris) in Great Britain, which are now threatened. Here we report the genome sequence of SQPV. Comparison with other Poxviridae revealed a core set of poxvirus genes, the phylogeny of which showed SQPV to be in a new Chordopoxvirus subfamily between the Molluscipoxviruses and Parapoxviruses. A number of SQPV genes were related to virulence, including three major histocomaptibility class I homologs, and one CD47 homolog. In addition, a novel potential virulence factor showing homology to mammalian oligoadenylate synthetase (OAS) was identified. This family of proteins normally causes activation of an endoribonuclease (RNaseL) within infected cells. The putative function of this novel SQPV protein was predicted in silico. [ABSTRACT FROM AUTHOR]

Objective: In many high-income countries with low HIV prevalence, significant numbers of persons living with HIV (PLHIV) remain undiagnosed. Identification of PLHIV via HIV testing offers timely access to lifesaving antiretroviral therapy (ART) and decreases HIV transmission. We estimated the effectiveness and cost-effectiveness of HIV testing in the United Kingdom (UK), where 25% of PLHIV are estimated to be undiagnosed. Design: We developed a dynamic compartmental model to analyze strategies to expand HIV testing and treatment in the UK, with particular focus on men who have sex with men (MSM), people who inject drugs (PWID), and individuals from HIV-endemic countries. Methods: We estimated HIV prevalence, incidence, quality-adjusted life years (QALYs), and health care costs over 10 years, and cost-effectiveness. Results: Annual HIV testing of all adults could avert 5% of new infections, even with no behavior change following HIV diagnosis because of earlier ART initiation, or up to 18% if risky behavior is halved. This strategy costs £67,000–£106,000/QALY gained. Providing annual testing only to MSM, PWID, and people from HIV-endemic countries, and one-time testing for all other adults, prevents 4–15% of infections, requires one-fourth as many tests to diagnose each PLHIV, and costs £17,500/QALY gained. Augmenting this program with increased ART access could add 145,000 QALYs to the population over 10 years, at £26,800/QALY gained. Conclusions: Annual HIV testing of key populations in the UK is very cost-effective. Additional one-time testing of all other adults could identify the majority of undiagnosed PLHIV. These findings are potentially relevant to other low-prevalence, high-income countries. [ABSTRACT FROM AUTHOR]

Although the incidence of variant Creutzfeldt-Jakob disease (vCJD) has declined to 1 since 2012 in the UK, uncertainty remains regarding possible future cases and the size of the subclinical population that may cause secondary transmission of the disease through blood transfusion. Estimating the number of individuals who were exposed to the bovine spongiform encephalopathy (BSE) infectious agent and may be susceptible to vCJD will help to clarify related public health concerns and plan strategies. In this paper, we explore this estimate by describing the probability of potential exposure due to dietary intake throughout the BSE epidemic period from 1980 to 1996 as a stochastic Poisson process. We estimate the age- and gender-specific exposure intensities in food categories of beef and beef-containing dishes, burgers and kebabs, pies, and sausages, separating the two periods of 1980–1989 and 1990–1996 due to the specified bovine offal legislation of 1989. The estimated total number of (living) exposed individuals during each period is 5,089,027 (95% confidence interval [CI] 4,514,963–6,410,317), which was obtained by multiplying the population size of different birth cohorts by the probability of exposure via dietary intake and the probability of survival until the end of 2013. The estimated number is approximately doubled, assuming a contamination rate of . Among those individuals estimated, 31,855 (95% CI 26,849–42,541) are susceptible to infection. We also examined the threshold hypothesis by fitting an extreme-value distribution to the estimated infectious dose of the exposed individuals and obtained a threshold estimate of 13.7 bID50 (95% CI 6.6–26.2 bID50) (Weibull). The results provide useful information on potential carriers of prion disease who may pose a threat of infection via blood transfusion and thus provide insight into the likelihood of new incidents of vCJD occurring in the future. [ABSTRACT FROM AUTHOR]

There is considerable interest in locally adapted breeds of livestock as reservoirs of genetic diversity that may provide important fitness traits for future use in agriculture. In marginal areas, these animals contribute to food security and extract value from land unsuitable for other systems of farming. In England, close to 50% of the national sheep flock is farmed on grassland designated as disadvantaged areas for agricultural production. Many of these areas are in the uplands, where some native breeds of sheep continue to be commercially farmed only in highly localised geographical regions to which they are adapted. This study focuses on three of these breeds, selected for their adaptation to near identical environments and their geographical concentration in regions close to one another. Our objective has been to use retrotyping, microsatellites and single nucleotide polymorphisms to explore the origins of the breeds and whether, despite their similar adaptations and proximity, they are genetically distinctive. We find the three breeds each have a surprisingly different pattern of retrovirus insertions into their genomes compared with one another and with other UK breeds. Uniquely, there is a high incidence of the R0 retrotype in the Herdwick population, characteristic of a primitive genome found previously in very few breeds worldwide and none in the UK mainland. The Herdwick and Rough Fells carry two rare retroviral insertion events, common only in Texels, suggesting sheep populations in the northern uplands have a historical association with the original pin-tail sheep of Texel Island. Microsatellite data and analyses of SNPs associated with RXFP2 (horn traits) and PRLR (reproductive performance traits) also distinguished the three breeds. Significantly, an SNP linked to TMEM154, a locus controlling susceptibility to infection by Maedi-Visna, indicated that all three native hill breeds have a lower than average risk of infection to the lentivirus. [ABSTRACT FROM AUTHOR]

Salmonella spp are a major foodborne zoonotic cause of human illness. Consumption of pork products is believed to be a major source of human salmonellosis and Salmonella control throughout the food-chain is recommended. A number of on-farm interventions have been proposed, and some have been implemented in order to try to achieve Salmonella control. In this study we utilize previously developed models describing Salmonella dynamics to investigate the potential effects of a range of these on-farm interventions. As the models indicated that the number of bacteria shed in the faeces of an infectious animal was a key factor, interventions applied within a high-shedding scenario were also analysed. From simulation of the model, the probability of infection after Salmonella exposure was found to be a key driver of Salmonella transmission. The model also highlighted that minimising physiological stress can have a large effect but only when shedding levels are not excessive. When shedding was high, weekly cleaning and disinfection was not effective in Salmonella control. However it is possible that cleaning may have an effect if conducted more often. Furthermore, separating infectious animals, shedding bacteria at a high rate, from the rest of the population was found to be able to minimise the spread of Salmonella. [ABSTRACT FROM AUTHOR]

Background: There is interest in expanding ART to prevent HIV transmission, but in the group with the highest levels of ART use, men-who-have-sex-with-men (MSM), numbers of new infections diagnosed each year have not decreased as ARTcoverage has increased for reasons which remain unclear. Methods: We analysed data on the HIV-epidemic in MSM in the UK from a range of sources using an individual-based simulation model. Model runs using parameter sets found to result in good model fit were used to infer changes in HIV-incidence and risk behaviour. Results: HIV-incidence has increased (estimated mean incidence 0.30/100 person-years 1990–1997, 0.45/100 py 1998–2010), associated with a modest (26%) rise in condomless sex. We also explored counter-factual scenarios: had ART not been introduced, but the rise in condomless sex had still occurred, then incidence 2006–2010 was 68% higher; a policy of ART initiation in all diagnosed with HIV from 2001 resulted in 32% lower incidence; had levels of HIV testing been higher (68% tested/year instead of 25%) incidence was 25% lower; a combination of higher testing and ART at diagnosis resulted in 62% lower incidence; cessation of all condom use in 2000 resulted in a 424% increase in incidence. In 2010, we estimate that undiagnosed men, the majority in primary infection, accounted for 82% of new infections. Conclusion: A rise in HIV-incidence has occurred in MSM in the UK despite an only modest increase in levels of condomless sex and high coverage of ART. ART has almost certainly exerted a limiting effect on incidence. Much higher rates of HIV testing combined with initiation of ART at diagnosis would be likely to lead to substantial reductions in HIV incidence. Increased condom use should be promoted to avoid the erosion of the benefits of ART and to prevent other serious sexually transmitted infections. [ABSTRACT FROM AUTHOR]

Breast cancer is an excellent disease paradigm for systems biology. At the time of writing, a simple PubMed search for 'breast cancer' returns nearly 99,000 hits, compared with 51,000 or 16,000 for lung and colon cancer respectively, even though in terms of mortality lung and colon cancers are responsible for four-times more deaths per annum in the UK. These figures reflect the effort and money invested in breast cancer research. It is because breast cancer research is data-rich, crowded and competitive (often perceived as a negative for clinical and basic scientific researchers) that it is such an appealing area of research for systems biologists. For systems biologists, data is currency, and they scavenge diverse and multilayered datasets, from biochemical through genomics and transcriptomics to proteomics, in order to populate computational models. We discuss how dynamic modeling can be used as a tool for predicting responses to new and existing drugs, and what needs to be done to make systems biology a useful tool in the clinic. [ABSTRACT FROM AUTHOR]

Since December 2019, a novel coronavirus (COVID-19) has spread all over the world, causing unpredictable economic losses and public fear. Although vaccines against this virus have been developed and administered for months, many countries still suffer from secondary COVID-19 infections, including the United Kingdom, France, and Malaysia. Observations of COVID-19 infections in the United Kingdom and France and their governance measures showed a certain number of similarities. A further investigation of these countries' COVID-19 transmission patterns suggested that when a turning point appeared, the values of their stringency indices per population density (PSI) were nearly proportional to their absolute infection rate (AIR). To justify our assumptions, we developed a mathematical model named VSHR to predict the COVID-19 turning point for Malaysia. VSHR was first trained on 30-day infection records prior to the United Kingdom, Germany, France, and Belgium's known turning points. It was then transferred to Malaysian COVID-19 data to predict this nation's turning point. Given the estimated AIR parameter values in 5 days, we were now able to locate the turning point's appearance on June 2 nd , 2021. VSHR offered two improvements: (1) gathered countries into groups based on their SI patterns and (2) generated a model to identify the turning point for a target country within 5 days with 90% CI. Our research on COVID-19's turning point for a country is beneficial for governments and clinical systems against future COVID-19 infections., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Xiang Yu et al.)

Currently, the global report of COVID-19 cases is around 110 million, and more than 2.43 million related death cases as of February 18, 2021. Viruses continuously change through mutation; hence, different virus of SARS-CoV-2 has been reported globally. The United Kingdom (UK), South Africa, Brazil, and Nigeria are the countries from which these emerged variants have been notified and now spreading globally. Therefore, these countries have been selected as a research sample for the present study. The datasets analyzed in this study spanned from March 1, 2020, to January 31, 2021, and were obtained from the World Health Organization website. The study used the Autoregressive Integrated Moving Average (ARIMA) model to forecast coronavirus incidence in the UK, South Africa, Brazil, and Nigeria. ARIMA models with minimum Akaike Information Criterion Correction (AICc) and statistically significant parameters were chosen as the best models in this research. Accordingly, for the new confirmed cases, ARIMA (3,1,14), ARIMA (0,1,11), ARIMA (1,0,10), and ARIMA (1,1,14) models were chosen for the UK, South Africa, Brazil, and Nigeria, respectively. Also, the model specification for the confirmed death cases was ARIMA (3,0,4), ARIMA (0,1,4), ARIMA (1,0,7), and ARIMA (Brown); models were selected for the UK, South Africa, Brazil, and Nigeria, respectively. The results of the ARIMA model forecasting showed that if the required measures are not taken by the respective governments and health practitioners in the days to come, the magnitude of the coronavirus pandemic is expected to increase in the study's selected countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Cai Li et al.)

Disrupted iron homeostasis is associated with several neurodegenerative diseases, including Alzheimer's disease (AD), and may be partially modulated by genetic risk factors. Here we evaluated whether subcortical iron deposition is associated with ApoE genotype, which substantially affects risk for late-onset AD. We evaluated differences in subcortical quantitative susceptibility mapping (QSM), a type of MRI sensitive to cerebral iron deposition, between either ApoE4 (E3E4+E4E4) or ApoE2 (E2E3+E2E2) carriers and E3 homozygotes (E3E3) in 27,535 participants from the UK Biobank (age: 45-82 years). We found that ApoE4 carriers had higher hippocampal (d=0.036; p=0.012) and amygdalar (d=0.035; p=0.013) magnetic susceptibility, particularly individuals aged 65 years or older, while those carrying ApoE2 (which protects against AD) had higher QSM only in the hippocampus (d=0.05; p=0.006), particularly those under age 65. Secondary diffusion MRI microstructural associations in these regions revealed greater diffusivity and less diffusion restriction in E4 carriers, however no differences were detected in E2 carriers. Disease risk conferred by ApoE4 may be linked with higher subcortical iron burden in conjunction with inflammation or neuronal loss in aging individuals, while ApoE2 associations may not necessarily reflect unhealthy iron deposits earlier in life.

The study of the interaction between the SARS-CoV-2 spike protein and the angiotensin-converting enzyme 2 (ACE2) receptor is key to understanding binding affinity and stability. In the present report, we sought to investigate the differences between two already sequenced genome variants (Spanish and British) of SARS-CoV-2. Methods: In silico model evaluating the homology, identity and similarity in the genome sequence and the structure and alignment of the predictive spike by computational docking methods. Results: The identity results between the Spanish and British variants of the Spike protein were 28.67%. This close correspondence in the results between the Spanish and British SARS-CoV-2 variants shows that they are very similar (99.99%). The alignment obtained results in four deletions. There were 23 nucleotide substitutions also predicted which could affect the functionality of the proteins produced from this sequence. The interaction between the binding receptor domain from the spike protein and the ACE2 receptor produces some of the mutations found and, therefore, the energy of this ligand varies. However, the estimated antigenicity of the British variant is higher than its Spanish counterpart. Conclusions: Our results indicate that minimal mutations could interfere in the infectivity of the virus due to changes in the fitness between host cell recognition and interaction proteins. In particular, the N501Y substitution, situated in the RBD of the spike of the British variant, might be the reason for its extraordinary infective potential.

Background: Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study has identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank., Methods: We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used Functional Mapping and Annotation of Genome-Wide Association Studies for post-genome-wide association study annotations and Multi-marker Analysis of GenoMic Annotation for gene-based and gene-set analyses., Results: We found Trans-Omics for Precision Medicine imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near TNS1 . We identified an additional risk locus on Chr1 ( SYT2 ) and 2 suggestive risk loci on chr8 ( MSRA ) and chr19 ( FBXO46 ), all driven by common variants. Gene-based association using Multi-marker Analysis of GenoMic Annotation revealed 6 risk genes for MVP with pronounced expression levels in cardiovascular tissues, especially the heart and globally part of enriched GO terms related to cardiac development., Conclusions: We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.

Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive patients. However, we then consider each mutation individually and cannot hope to study interactions between several mutations. Here, we aim to leverage the ever-growing quantity of high-quality sequence data and machine learning methods to study such interactions (i.e. epistasis), as well as try to find new DRMs. We trained classifiers to discriminate between Reverse Transcriptase Inhibitor (RTI)-experienced and RTI-naive samples on a large HIV-1 reverse transcriptase (RT) sequence dataset from the UK (n ≈ 55, 000), using all observed mutations as binary representation features. To assess the robustness of our findings, our classifiers were evaluated on independent data sets, both from the UK and Africa. Important representation features for each classifier were then extracted as potential DRMs. To find novel DRMs, we repeated this process by removing either features or samples associated to known DRMs. When keeping all known resistance signal, we detected sufficiently prevalent known DRMs, thus validating the approach. When removing features corresponding to known DRMs, our classifiers retained some prediction accuracy, and six new mutations significantly associated with resistance were identified. These six mutations have a low genetic barrier, are correlated to known DRMs, and are spatially close to either the RT active site or the regulatory binding pocket. When removing both known DRM features and sequences containing at least one known DRM, our classifiers lose all prediction accuracy. These results likely indicate that all mutations directly conferring resistance have been found, and that our newly discovered DRMs are accessory or compensatory mutations. Moreover, apart from the accessory nature of the relationships we found, we did not find any significant signal of further, more subtle epistasis combining several mutations which individually do not seem to confer any resistance., Competing Interests: The authors have declared that no competing interests exist.

On March 23 2020, the UK enacted an intensive, nationwide lockdown to mitigate transmission of COVID-19. As restrictions began to ease, more localized interventions were used to target resurgences in transmission. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to targeting interventions at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. We use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. We found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance connections central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. We propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions., Competing Interests: The authors have declared that no competing interests exist.

Staphylococcus aureus is a serious human and animal pathogen threat exhibiting extraordinary capacity for acquiring new antibiotic resistance traits in the pathogen population worldwide. The development of fast, affordable and effective diagnostic solutions capable of discriminating between antibiotic-resistant and susceptible S. aureus strains would be of huge benefit for effective disease detection and treatment. Here we develop a diagnostics solution that uses Matrix-Assisted Laser Desorption/Ionisation-Time of Flight Mass Spectrometry (MALDI-TOF) and machine learning, to identify signature profiles of antibiotic resistance to either multidrug or benzylpenicillin in S. aureus isolates. Using ten different supervised learning techniques, we have analysed a set of 82 S. aureus isolates collected from 67 cows diagnosed with bovine mastitis across 24 farms. For the multidrug phenotyping analysis, LDA, linear SVM, RBF SVM, logistic regression, naïve Bayes, MLP neural network and QDA had Cohen's kappa values over 85.00%. For the benzylpenicillin phenotyping analysis, RBF SVM, MLP neural network, naïve Bayes, logistic regression, linear SVM, QDA, LDA, and random forests had Cohen's kappa values over 85.00%. For the benzylpenicillin the diagnostic systems achieved up to (mean result ± standard deviation over 30 runs on the test set): accuracy = 97.54% ± 1.91%, sensitivity = 99.93% ± 0.25%, specificity = 95.04% ± 3.83%, and Cohen's kappa = 95.04% ± 3.83%. Moreover, the diagnostic platform complemented by a protein-protein network and 3D structural protein information framework allowed the identification of five molecular determinants underlying the susceptible and resistant profiles. Four proteins were able to classify multidrug-resistant and susceptible strains with 96.81% ± 0.43% accuracy. Five proteins, including the previous four, were able to classify benzylpenicillin resistant and susceptible strains with 97.54% ± 1.91% accuracy. Our approach may open up new avenues for the development of a fast, affordable and effective day-to-day diagnostic solution, which would offer new opportunities for targeting resistant bacteria., Competing Interests: The authors have declared that no competing interests exist.

Amyloidosis is a relatively rare human disease caused by the deposition of abnormal protein fibres in the extracellular space of various tissues, impairing their normal function. Proteomic analysis of patients' biopsies, developed by Dogan and colleagues at the Mayo Clinic, has become crucial for clinical diagnosis and for identifying the amyloid type. Currently, the proteomic approach is routinely used at National Amyloidosis Centre (NAC, London, UK) and Istituto di Tecnologie Biomediche-Consiglio Nazionale delle Ricerche (ITB-CNR, Milan, Italy). Both centres are members of the European Proteomics Amyloid Network (EPAN), which was established with the aim of sharing and discussing best practice in the application of amyloid proteomics. One of the EPAN's activities was to evaluate the quality and the confidence of the results achieved using different software and algorithms for protein identification. In this paper, we report the comparison of proteomics results obtained by sharing NAC proteomics data with the ITB-CNR centre. Mass spectrometric raw data were analysed using different software platforms including Mascot, Scaffold, Proteome Discoverer, Sequest and bespoke algorithms developed for an accurate and immediate amyloid protein identification. Our study showed a high concordance of the obtained results, suggesting a good accuracy of the different bioinformatics tools used in the respective centres. In conclusion, inter-centre data exchange is a worthwhile approach for testing and validating the performance of software platforms and the accuracy of results, and is particularly important where the proteomics data contribute to a clinical diagnosis.

While traditional microbiological freshwater tests focus on the detection of specific bacterial indicator species, including pathogens, direct tracing of all aquatic DNA through metagenomics poses a profound alternative. Yet, in situ metagenomic water surveys face substantial challenges in cost and logistics. Here, we present a simple, fast, cost-effective and remotely accessible freshwater diagnostics workflow centred around the portable nanopore sequencing technology. Using defined compositions and spatiotemporal microbiota from surface water of an example river in Cambridge (UK), we provide optimised experimental and bioinformatics guidelines, including a benchmark with twelve taxonomic classification tools for nanopore sequences. We find that nanopore metagenomics can depict the hydrological core microbiome and fine temporal gradients in line with complementary physicochemical measurements. In a public health context, these data feature relevant sewage signals and pathogen maps at species level resolution. We anticipate that this framework will gather momentum for new environmental monitoring initiatives using portable devices., Competing Interests: LU, AH, JB, MH, PB, MS, DK, SP, DM, ET, SS, MS No competing interests declared, (© 2021, Urban et al.)

Fitting stochastic transmission models to electronic patient data can offer detailed insights into the transmission of healthcare-associated infections and improve infection control. Pathogen whole-genome sequencing may improve the precision of model inferences, but computational constraints have limited modelling applications predominantly to small datasets and specific outbreaks, whereas large-scale sequencing studies have mostly relied on simple rules for identifying/excluding plausible transmission. We present a novel approach for integrating detailed epidemiological data on patient contact networks in hospitals with large-scale pathogen sequencing data. We apply our approach to study Clostridioides difficile transmission using a dataset of 1223 infections in Oxfordshire, UK, 2007-2011. 262 (21% [95% credibility interval 20-22%]) infections were estimated to have been acquired from another known case. There was heterogeneity by sequence type (ST) in the proportion of cases acquired from another case with the highest rates in ST1 (ribotype-027), ST42 (ribotype-106) and ST3 (ribotype-001). These same STs also had higher rates of transmission mediated via environmental contamination/spores persisting after patient discharge/recovery; for ST1 these persisted longer than for most other STs except ST3 and ST42. We also identified variation in transmission between hospitals, medical specialties and over time; by 2011 nearly all transmission from known cases had ceased in our hospitals. Our findings support previous work suggesting only a minority of C. difficile infections are acquired from known cases but highlight a greater role for environmental contamination than previously thought. Our approach is applicable to other healthcare-associated infections. Our findings have important implications for effective control of C. difficile., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: DWE has received lecture fees from Gilead, outside the submitted work. No other author has a conflict of interest to declare.

The rate of people getting affected by Oral cancer in Sri Lanka is growing rapidly since the root cause of such cancer, betel quid chewing is tightly coupled with the tradition of the country. The five-year survival rate of the disease is also pretty low as it is typically detected at advanced stages. This urges a comprehensive study on the marker genes of oral cancer for the successful therapeutic revisions that would potentially identify cancer in its early stages. Further, the identification of molecular subclasses can assist in individualizing the treatment for this type of fatal disease. This study uses the bioinformatics analysis on the gene expression dataset of 56 oral cancer patients from Sri Lanka and the United Kingdom to identify the differentially expressed genes where these genes are later clustered and classified into molecular subclasses. Molecular subclasses are found by clustering the genes that stratify together and the stages were identified with the use of gene co-expression networks. Five molecular subclasses of oral cancer were identified and the genes associated with each tumour stage. Out of the genes that are clustered and classified, TAGLN2, CCND2 and CCL8 were well-known tumour suppressor genes and GPX3, GRN and ITGB4 genes are involved in several carcinomas. Putative marker genes of Oral Squamous Cell Carcinoma were identified which could facilitate the medical practitioner in the early detection of oral cancer and also in the improvement of treatment methods., (Copyright © 2021. Published by Elsevier Ltd.)

Pharmacogenetics studies how genetic variation leads to variability in drug response. Guidelines for selecting the right drug and right dose for patients based on their genetics are clinically effective, but are widely unused. For some drugs, the normal clinical decision making process may lead to the optimal dose of a drug that minimizes side effects and maximizes effectiveness. Without measurements of genotype, physicians and patients may adjust dosage in a manner that reflects the underlying genetics. The emergence of genetic data linked to longitudinal clinical data in large biobanks offers an opportunity to confirm known pharmacogenetic interactions as well as discover novel associations by investigating outcomes from normal clinical practice. Here we use the UK Biobank to search for pharmacogenetic interactions among 200 drugs and 9 genes among 200,000 participants. We identify associations between pharmacogene phenotypes and drug maintenance dose as well as differential drug response phenotypes. We find support for several known drug-gene associations as well as novel pharmacogenetic interactions.

Despite increasing interest in pharmacogenomics, and the potential benefits to improve patient care, implementation into clinical practice has not been widespread. Recently, there has been a drive to implement genomic medicine into the UK National Health Service (NHS), largely spurred on by the success of the 100,000 Genomes Project. The UK Pharmacogenetics and Stratified Medicine Network, NHS England and Genomics England invited experts from academia, the healthcare sector, industry and patient representatives to come together to discuss the opportunities and challenges of implementing pharmacogenomics into the NHS. This report highlights the discussions of the workshop to provide an overview of the issues that need to be considered to enable pharmacogenomic medicine to become mainstream within the NHS.

A computational model based on game theory is here proposed to forecast the prevalence of depression caused by frustration in a competitive environment. This model comprises a spatially structured game, in which the individuals are socially connected. This game, which is equivalent to the well-known prisoner's dilemma, represents the payoffs that can be received by the individuals in the labor market. These individuals may or may not have invested in a formal academic education. It is assumed that an individual becomes depressed when the difference between the average payoff earned by the neighbors in this game and the personal payoff surpasses a critical number, which can be distinct for men and women. Thus, the transition to depression depends on two thresholds, whose values are tuned for the model accurately predicting the percentage of individuals that become depressed due to a frustrating payoff. Here, this tuning is performed by using data of young adults living in the United Kingdom in 2014-2016., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2020 R. Loula and L. H. A. Monteiro.)

Tuberculosis (TB) remains a public health threat in low TB incidence countries, through a combination of reactivated disease and onward transmission. Using surveillance data from the United Kingdom (UK) and the Netherlands (NL), we demonstrate a simple and predictable relationship between the probability of observing a cluster and its size (the number of cases with a single genotype). We demonstrate that the full range of observed cluster sizes can be described using a modified branching process model with the individual reproduction number following a Poisson lognormal distribution. We estimate that, on average, between 2010 and 2015, a TB case generated 0.41 (95% CrI 0.30,0.60) secondary cases in the UK, and 0.24 (0.14,0.48) secondary cases in the NL. A majority of cases did not generate any secondary cases. Recent transmission accounted for 39% (26%,60%) of UK cases and 23%(13%,37%) of NL cases. We predict that reducing UK transmission rates to those observed in the NL would result in 538(266,818) fewer cases annually in the UK. In conclusion, while TB in low incidence countries is strongly associated with reactivated infections, we demonstrate that recent transmission remains sufficient to warrant policies aimed at limiting local TB spread., Competing Interests: The authors have declared that no competing interests exist.

Transcriptome-wide association studies (TWAS) integrate genome-wide association studies (GWAS) and transcriptomic data to showcase their improved statistical power of identifying gene-trait associations while, importantly, offering further biological insights. TWAS have thus far focused on common variants as available from GWAS. Compared with common variants, the findings for or even applications to low-frequency variants are limited and their underlying role in regulating gene expression is less clear. To fill this gap, we extend TWAS to integrating whole genome sequencing data with transcriptomic data for low-frequency variants. Using the data from the Framingham Heart Study, we demonstrate that low-frequency variants play an important and universal role in predicting gene expression, which is not completely due to linkage disequilibrium with the nearby common variants. By including low-frequency variants, in addition to common variants, we increase the predictivity of gene expression for 79% of the examined genes. Incorporating this piece of functional genomic information, we perform association testing for five lipid traits in two UK10K whole genome sequencing cohorts, hypothesizing that cis-expression quantitative trait loci, including low-frequency variants, are more likely to be trait-associated. We discover that two genes, LDLR and TTC22, are genome-wide significantly associated with low-density lipoprotein cholesterol based on 3203 subjects and that the association signals are largely independent of common variants. We further demonstrate that a joint analysis of both common and low-frequency variants identifies association signals that would be missed by testing on either common variants or low-frequency variants alone., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the disease process, there is ample room for improvement. The policy of the UK government and National Health Service (NHS) is to increase rates of timely dementia diagnosis. We used data from general practice (GP) patient records to create a machine-learning model to identify patients who have or who are developing dementia, but are currently undetected as having the condition by the GP., Methods: We used electronic patient records from Clinical Practice Research Datalink (CPRD). Using a case-control design, we selected patients aged >65y with a diagnosis of dementia (cases) and matched them 1:1 by sex and age to patients with no evidence of dementia (controls). We developed a list of 70 clinical entities related to the onset of dementia and recorded in the 5 years before diagnosis. After creating binary features, we trialled machine learning classifiers to discriminate between cases and controls (logistic regression, naïve Bayes, support vector machines, random forest and neural networks). We examined the most important features contributing to discrimination., Results: The final analysis included data on 93,120 patients, with a median age of 82.6 years; 64.8% were female. The naïve Bayes model performed least well. The logistic regression, support vector machine, neural network and random forest performed very similarly with an AUROC of 0.74. The top features retained in the logistic regression model were disorientation and wandering, behaviour change, schizophrenia, self-neglect, and difficulty managing., Conclusions: Our model could aid GPs or health service planners with the early detection of dementia. Future work could improve the model by exploring the longitudinal nature of patient data and modelling decline in function over time.

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism 1-5 , yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.

We have validated ITS-2 rDNA nemabiome next-generation amplicon sequencing to determine relative species abundance of gastrointestinal nematode species in ovine fecal samples. In order to determine species representation biases, ITS-2 rDNA amplicon sequencing was applied to mock communities or field populations with known proportions of L3 for eight of the major ovine gastrointestinal nematode species: Teladorsagia circumcincta, Trichostrongylus vitrinus, Haemonchus contortus, Cooperia curticei, Trichostrongylus axei, Trichostrongylus colubriformis, Chabertia ovina and Oesophagostumum venulosum. Correction factors, calculated from this data, were shown to reduce species representation biases when applied to an independent set of field samples of known composition. We compared ITS-2 rDNA amplicon sequencing data that was generated from harvested eggs, freshly hatched L1 or L3 larvae following fecal culture and no statistically significant differences were found for the more abundant parasite species. We then applied the validated ITS-2 rDNA nemabiome amplicon sequencing assay to a set of archived L1 gastrointestinal nematode populations, collected in 2008 from fecal samples from 93 groups of 20 ewes and 61 groups of 20 lambs derived from 99 UK sheep farms. The presence of the major gastrointestinal nematode species had previously been determined on this large sample set by species-specific PCR. We show how the ITS-2rDNA amplicon sequencing data provided much more detailed information on species abundance than the previous species-specific PCR. This new data represents the most comprehensive overview of the relative abundance of the major gastrointestinal nematode species across UK sheep farms to date. Substantial variance in the relative abundance of both T. circumcincta and T. vitrinus between farms was revealed with the former species being of statistically significantly higher abundance in all three regions sampled (England, Scotland and Wales). The data also revealed that the relative abundance of T. circumcinta was statistically significantly higher in ewes than in lambs with the opposite pattern being the case for T. vitrinus. The nemabiome sequencing data also clearly illustrated the sporadic nature and skewed distribution of H. controtus across UK sheep farms as well as a higher relative abundance on farms from England compared to Wales and Scotland. The nemabiome survey also provides the first widescale data on the relative abundance of the two major large intestinal nematodes C. ovina and O. venulosum. This work validates ITS-2 rDNA nemabiome sequencing for use in sheep and illustrates the power of the approach for large scale surveillance of ovine gastrointestinal nematodes., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Aging populations face diminishing quality of life due to increased disease and morbidity. These challenges call for longevity research to focus on understanding the pathways controlling healthspan. We use the data from the UK Biobank (UKB) cohort and observe that the risks of major chronic diseases increased exponentially and double every eight years, i.e., at a rate compatible with the Gompertz mortality law. Assuming that aging drives the acceleration in morbidity rates, we build a risk model to predict the age at the end of healthspan depending on age, gender, and genetic background. Using the sub-population of 300,447 British individuals as a discovery cohort, we identify 12 loci associated with healthspan at the whole-genome significance level. We find strong genetic correlations between healthspan and all-cause mortality, life-history, and lifestyle traits. We thereby conclude that the healthspan offers a promising new way to interrogate the genetics of human longevity., Competing Interests: P.F. is a shareholder of Gero LLC. Y.A. is a founder and co-owner of PolyOmica, a private research organization that specializes in computational and statistical (gen)omics, and a shareholder of PolyKnomics BV. A.Z., L.M., E.G., and P.F. are employees of Gero LLC. A patent application submitted by Gero LLC on the described methods and tools for evaluating genetic risks factors in association with diseases is pending. The remaining authors declare no competing interests.

Benign prostatic hyperplasia and associated lower urinary tract symptoms (BPH/LUTS) are common conditions affecting the majority of elderly males. Here we report the results of a genome-wide association study of symptomatic BPH/LUTS in 20,621 patients and 280,541 controls of European ancestry, from Iceland and the UK. We discovered 23 genome-wide significant variants, located at 14 loci. There is little or no overlap between the BPH/LUTS variants and published prostate cancer risk variants. However, 15 of the variants reported here also associate with serum levels of prostate specific antigen (PSA) (at a Bonferroni corrected P < 0.0022). Furthermore, there is a strong genetic correlation, r g  = 0.77 (P = 2.6 × 10 -11 ), between PSA and BPH/LUTS, and one standard deviation increase in a polygenic risk score (PRS) for BPH/LUTS increases PSA levels by 12.9% (P = 1.6×10 -55 ). These results shed a light on the genetic background of BPH/LUTS and its substantial influence on PSA levels.

Alcohol is metabolized in the liver via the enzymes alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH). Polymorphisms in the genes encoding these enzymes, which are common in East Asian populations, can alter enzyme kinetics and hence the risk of alcohol dependence and its sequelae. One of the most important genetic variants, in this regards, is the single nucleotide polymorphism (SNP) rs671 in ALDH2, the gene encoding the primary acetaldehyde metabolizing enzyme ALDH2. However, the protective allele of rs671 is absent in most Europeans although ALDH1B1, which shares significant sequence homology with ALDH2, contains several, potentially functional, missense SNPs that do occur in European populations. The aims of this study were: (i) to use bioinformatic techniques to characterize the possible effects of selected variants in ALDH1B1 on protein structure and function; and, (ii) to genotype three missense and one stop-gain, protein-altering, non-synonymous SNPs in 1478 alcohol dependent cases and 1254 controls of matched British and Irish ancestry. No significant allelic associations were observed between the three missense SNPs and alcohol dependence risk. The minor allele frequency of rs142427338 (Gln378Ter) was higher in alcohol dependent cases than in controls (allelic P = 0.19, OR = 2.98, [0.62-14.37]) but as this SNP is very rare the study was likely underpowered to detect an association with alcohol dependence risk. This potential association will needs to be further evaluated in other large, independent European populations.

We are facing a major challenge in bridging the gap between identifying subtypes of asthma to understand causal mechanisms and translating this knowledge into personalized prevention and management strategies. In recent years, "big data" has been sold as a panacea for generating hypotheses and driving new frontiers of health care; the idea that the data must and will speak for themselves is fast becoming a new dogma. One of the dangers of ready accessibility of health care data and computational tools for data analysis is that the process of data mining can become uncoupled from the scientific process of clinical interpretation, understanding the provenance of the data, and external validation. Although advances in computational methods can be valuable for using unexpected structure in data to generate hypotheses, there remains a need for testing hypotheses and interpreting results with scientific rigor. We argue for combining data- and hypothesis-driven methods in a careful synergy, and the importance of carefully characterized birth and patient cohorts with genetic, phenotypic, biological, and molecular data in this process cannot be overemphasized. The main challenge on the road ahead is to harness bigger health care data in ways that produce meaningful clinical interpretation and to translate this into better diagnoses and properly personalized prevention and treatment plans. There is a pressing need for cross-disciplinary research with an integrative approach to data science, whereby basic scientists, clinicians, data analysts, and epidemiologists work together to understand the heterogeneity of asthma., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: The objective of this study was to determine the population structure of Escherichia coli ST73 isolated from human bacteraemia and urinary tract infections., Methods: The genomes of 22 E. coli ST73 isolates were sequenced using the Illumina HiSeq platform. High-resolution SNP typing was used to create a phylogenetic tree. Comparative genomics were also performed using a pangenome approach. In silico and S1-PFGE plasmid profiling was conducted, and isolates were checked for their ability to survive exposure to human serum., Results: E. coli ST73 isolates circulating in clinically unrelated episodes show a high degree of diversity at a whole-genome level, but exhibit conservation in gene content, particularly in virulence-associated gene carriage. The isolates also contain a highly diverse plasmid pool that confers MDR via carriage of CTX-M genes., Conclusions: Our data show that a rise in incidence of MDR E. coli ST73 clinical isolates is not due to a circulating outbreak strain as in E. coli ST131. Rather the ST73 circulating strains are distantly related and carry a diverse set of resistance plasmids. This suggests that the evolutionary events behind emergence of drug-resistant E. coli differ between lineages., (© The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

This article focuses on the Proteomics IDEntifications (PRIDE) Database developed by the European Bioinformatics Institute in Great Britain and the Flanders Interuniversity Institute for Biotechnology Ghent University in response to a growing need for protein information to be brought together in a way that is easy to access and share, as of October 2005. PRIDE provides an open-source database of protein identifications and has been designed to allow researchers to store, share and compare their results.

Osteoarthritis is the most common form of arthritis and is a major cause of pain and disability in the elderly. To search for sequence variants that confer risk of osteoarthritis of the hand, we carried out a genome-wide association study (GWAS) in subjects with severe hand osteoarthritis, using variants identified through the whole-genome sequencing of 2,230 Icelanders. We found two significantly associated loci in the Icelandic discovery set: at 15q22 (frequency of 50.7%, odds ratio (OR) = 1.51, P = 3.99 × 10(-10)) in the ALDH1A2 gene and at 1p31 (frequency of 0.02%, OR = 50.6, P = 9.8 × 10(-10)). Among the carriers of the variant at 1p31 is a family with several members in whom the risk allele segregates with osteoarthritis. The variants within the ALDH1A2 gene were confirmed in replication sets from The Netherlands and the UK, yielding an overall association of OR = 1.46 and P = 1.1 × 10(-11) (rs3204689).

Pseudomonas aeruginosa is an opportunistic pathogen of humans and is a major cause of morbidity and mortality in patients with cystic fibrosis (CF). Prolonged infection of the respiratory tract can lead to adaptation of the pathogen to the CF lung environment. To examine the general patterns of adaptation associated with chronic infection, we obtained genome sequences from a collection of P. aeruginosa isolated from airways of patients with CF. Our analyses support a nonclonal epidemic population structure, with a background of unique, recombining genotypes, and the rare occurrence of successful epidemic clones. We present unique genome sequence evidence for the intercontinental spread of an epidemic strain shared between CF clinics in the United Kingdom and North America. Analyses of core and accessory genomes identified candidate genes and important functional pathways associated with adaptive evolution. Many genes of interest were involved in biological functions with obvious roles in this pathosystem, such as biofilm formation, antibiotic metabolism, pathogenesis, transport, reduction/oxidation, and secretion. Key factors driving the adaptive evolution of this pathogen within the host appear to be the presence of oxidative stressors and antibiotics. Regions of the accessory genome unique to the epidemic strain were enriched for genes in transporter families that efflux heavy metals and antibiotics. The epidemic strain was significantly more resistant than nonepidemic strains to three different antibiotics. Multiple lines of evidence suggest that selection imposed by the CF lung environment has a major influence on genomic evolution and the genetic characteristics of P. aeruginosa isolates causing contemporary infection.

Objectives: Coronary artery bypass graft (CABG) is performed for symptomatic and prognostic reasons. We aimed to determine the factors that contribute to in-hospital mortality and long-term survival in young patients (aged less than 65) undergoing CABG., Methods: A prospective database was retrospectively analysed and cross-correlated with the United Kingdom's Strategic Tracing Service to evaluate survival in patients under the age of 65, following isolated primary CABG. Univariate-, multivariate logistic with Cox regression- and neural network analyses were performed., Results: Patients under the age of 65, who had undergone isolated CABG between April 1997 and March 2010 were studied;n = 5967. In-hospital mortality was 1.1% and long-term mortality was 13.5%; median follow-up 7.9 years. Multivariate analysis demonstrated that atrial fibrillation, 'urgent' operation status, postoperative creatinine kinase (CKMB), moderate or poor left ventricular (LV) function, and female sex were significant factors predicting in-hospital mortality. Cox regression demonstrated that age, diabetes (oral and insulin controlled), moderate and poor LV function, cerebrovascular disease, dialysis, left internal mammary artery (LIMA) usage, postoperative CKMB, atrial fibrillation, 'urgent' operation status, and peripheral vascular disease were significant factors determining long-term survival. Radial artery use, off-pump surgery, composite arterial grating and graft number had no effect on in-hospital mortality or long-term survival. Neural network analysis confirmed the factors identified by logistic and Cox multivariate analysis., Conclusions: The risk factors for in-hospital mortality in patients under the age of 65 include postoperative CKMB, urgent operation status, LV function, female sex and atrial fibrillation. Significant factors determining long-term survival in the under-65 age group include age, atrial fibrillation, diabetes (diet and insulin controlled), LV function, cerebrovascular disease, dialysis, LIMA usage, 'urgent' operation status, CKMB and peripheral vascular disease.

We determined the complete nucleotide sequences of three plasmids that encode CTX-M extended-spectrum beta-lactamases (ESBLs) in pulsed-field gel electrophoresis-defined United Kingdom variants (strains A, C, and D) of the internationally prevalent Escherichia coli O25:H4-ST131 clone. Plasmid pEK499 (strain A; 117,536 bp) was a fusion of type FII and FIA replicons and harbored the following 10 antibiotic resistance genes conferring resistance to eight antibiotic classes: bla(CTX-M-15), bla(OXA-1), bla(TEM-1,) aac6'-Ib-cr, mph(A), catB4, tet(A), and the integron-borne dfrA7, aadA5, and sulI genes. pEK516 (strain D; 64,471 bp) belonged to incompatibility group IncFII and carried seven antibiotic resistance genes: bla(CTX-M-15), bla(OXA-1), bla(TEM-1), aac6'-Ib-cr, catB4, and tet(A), all as in pEK499. It also carried aac3-IIa, conferring gentamicin resistance, and was highly related to pC15-1a, a plasmid encoding the CTX-M-15 enzyme in Canada. By contrast, pEK204 (strain C; 93,732 bp) belonged to incompatibility group IncI1 and carried only two resistance genes, bla(CTX-M-3) and bla(TEM-1). It probably arose by the transposition of Tn3 and ISEcp1-bla(CTX-M-3) elements into a pCOLIb-P9-like plasmid. We conclude that (i) United Kingdom variants of the successful E. coli ST131 clone have acquired different plasmids encoding CTX-M ESBLs on separate occasions, (ii) the bla(CTX-M-3) and bla(CTX-M-15) genes on pEK204 and pEK499/pEK516 represent separate escape events, and (iii) IncFII plasmids harboring bla(CTX-M-15) have played a crucial role in the global spread of CTX-M-15 ESBLs in E. coli.