SNP haplotypes in the Angiotensin I-converting Enzyme (ACE) gene: Analysis of Nigerian family data using gamete competition models

Gamete competition models were used to explore the relationships between 13 ACE gene polymorphisms and plasma ACE concentration in a set of Nigerian families. Several markers in the 5′ and 3′ regions of the gene were significantly associated with ACE concentration (P \u3c 10-4). Multi-locus genotypes comprising different combinations of markers from the 5′ UTR and the 3′ region of the gene were also analysed; in addition to G2350A, in the 3′ region, two markers from the 5′ UTR (A-5466C and A-240T) were found to be associated with ACE concentration. These results are consistent with reports that have suggested the presence of at least two ACE-linked QTLs, and demonstrate the utility of gamete competition models in the exploratory investigation of the relationship between a quantitative trait and multiple variants in a small genomic region. © University College London 2005

Diversity of methyl halide-degrading microorganisms in oceanic and coastal waters

Methyl halides have a significant impact on atmospheric chemistry, particularly in the degradation of stratospheric ozone. Bacteria are known to contribute to the degradation of methyl halides in the oceans and marine bacteria capable of using methyl bromide and methyl chloride as sole carbon and energy source have been isolated. A genetic marker for microbial degradation of methyl bromide ( cmuA ) was used to examine the distribution and diversity of these organisms in the marine environment. Three novel marine clades of cmuA were identified in unamended seawater and in marine enrichment cultures degrading methyl halides. Two of these cmuA clades are not represented in extant bacteria, demonstrating the utility of this molecular marker in identifying uncultivated marine methyl halide-degrading bacteria. The detection of populations of marine bacteria containing cmuA genes suggests that marine bacteria employing the CmuA enzyme contribute to methyl halide cycling in the ocean

External validation of the QCovid risk prediction algorithm for risk of COVID-19 hospitalisation and mortality in adults:national validation cohort study in Scotland

Funding Medical Research Council (MR/R008345/1), National Institute for Health Research Health Technology Assessment Programme, funded through the UK Research and Innovation Industrial Strategy Challenge Fund Health Data Research UK.Background : The QCovid algorithm is a risk prediction tool that can be used to stratify individuals by risk of COVID-19 hospitalisation and mortality. Version 1 of the algorithm was trained using data covering 10.5 million patients in England in the period 24 January 2020 to 30 April 2020. We carried out an external validation of version 1 of the QCovid algorithm in Scotland. Methods : We established a national COVID-19 data platform using individual level data for the population of Scotland (5.4 million residents). Primary care data were linked to reverse-transcription PCR (RT-PCR) virology testing, hospitalisation and mortality data. We assessed the performance of the QCovid algorithm in predicting COVID-19 hospitalisations and deaths in our dataset for two time periods matching the original study: 1 March 2020 to 30 April 2020, and 1 May 2020 to 30 June 2020. Results : Our dataset comprised 5 384 819 individuals, representing 99% of the estimated population (5 463 300) resident in Scotland in 2020. The algorithm showed good calibration in the first period, but systematic overestimation of risk in the second period, prior to temporal recalibration. Harrell’s C for deaths in females and males in the first period was 0.95 (95% CI 0.94 to 0.95) and 0.93 (95% CI 0.92 to 0.93), respectively. Harrell’s C for hospitalisations in females and males in the first period was 0.81 (95% CI 0.80 to 0.82) and 0.82 (95% CI 0.81 to 0.82), respectively. Conclusions : Version 1 of the QCovid algorithm showed high levels of discrimination in predicting the risk of COVID-19 hospitalisations and deaths in adults resident in Scotland for the original two time periods studied, but is likely to need ongoing recalibration prospectively.Publisher PDFPeer reviewe

Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes

There is an increasing expectation that advanced, computationally expensive machine learning (ML) techniques, when applied to large population-wide neuroimaging datasets, will help to uncover key differences in the human brain in health and disease. We take a comprehensive approach to explore how multiple aspects of brain structural connectivity can predict sex, age, general cognitive function and general psychopathology, testing different ML algorithms from deep learning (DL) model (BrainNetCNN) to classical ML methods. We modelled N = 8183 structural connectomes from UK Biobank using six different structural network weightings obtained from diffusion MRI. Streamline count generally provided the highest prediction accuracies in all prediction tasks. DL did not improve on prediction accuracies from simpler linear models. Further, high correlations between gradient attribution coefficients from DL and model coefficients from linear models suggested the models ranked the importance of features in similar ways, which indirectly suggested the similarity in models' strategies for making predictive decision to some extent. This highlights that model complexity is unlikely to improve detection of associations between structural connectomes and complex phenotypes with the current sample size

Neurogranin in Alzheimer’s disease and ageing: a human post-mortem study

Neurogranin (Ng), a post-synaptic protein involved in memory formation, has been investigated as a biomarker in the cerebrospinal fluid (CSF) in Alzheimer's disease (AD) and ageing. CSF Ng levels are elevated in AD relative to healthy controls and correlate with cognition; however, few studies have focused on Ng abundance in the brain. Synapse loss in the brain correlates closely with cognitive decline in AD making synaptic biomarkers potentially important for tracking disease progression, but the links between synaptic protein changes in CSF and brain remain incompletely understood. In the current study, Ng abundance was examined in post-mortem human brain tissue across AD, healthy ageing (HA), and mid-life (ML) cohorts. Ng levels were quantified in three brain regions associated with cognitive change found during ageing and neurodegenerative diseases, namely the middle temporal gyrus, primary visual cortex and the posterior hippocampus using immunohistochemistry. To support immunohistochemical analysis, total homogenate and biochemically enriched synaptic fractions from available temporal gyrus tissues were examined by immunoblot. Finally, we examined whether Ng is associated with lifetime cognitive ageing. Ng levels were significantly reduced in AD relative to HA and ML cases across all regions. Additionally Ng was significantly reduced in HA in comparison to ML in the primary visual cortex. Immunoblotting confirms reduced Ng levels in AD cases supporting immunohistochemical results. Interestingly, there was also a significant reduction of synapse-associated Ng in our group who had lifetime cognitive decline in comparison to the group with lifetime cognitive resilience indicating loss of neurogranin in remaining synapses during ageing is associated with cognitive decline. Our findings indicate that increases in CSF Ng reflect loss of brain neurogranin and support the use of CSF Ng as a biomarker of AD and potentially of cognitive decline in healthy ageing

Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936

Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β = −0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (β = −0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (β = −0.07; SE = 0.03; N = 658; n = 390), thinner cortex (β = −0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (β = −0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (β = −0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (β = −0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability

Phylogenetic determinants of toxin gene distribution in genomes of Brevibacillus laterosporus

Brevibacillus laterosporus is a globally ubiquitous, spore forming bacterium, strains of which have shown toxic activity against invertebrates and microbes and several have been patented due to their commercial potential. Relatively little is known about this bacterium. Here, we examined the genomes of six published and five newly determined genomes of B. laterosporus, with an emphasis on the relationships between known and putative toxin encoding genes, as well as the phylogenetic relationships between strains. Phylogenetically, strain relationships are similar using average nucleotide identity (ANI) values and multi-gene approaches, although PacBio sequencing revealed multiple copies of the 16S rDNA gene which lessened utility at the strain level. Based on ANI values, the New Zealand isolates were distant from other isolates and may represent a new species. While all of the genomes examined shared some putative toxicity or virulence related proteins, many specific genes were only present in a subset of strains