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Traces the centuries-long battle to treat and prevent malaria in numerous regions of the world while revealing how hundreds of millions of people are infected annually in spite of available preventions.

DNA methylation plays an important role in the regulation of transcription. Genetic control of DNA methylation is a potential candidate for explaining the many identified SNP associations with disease that are not found in coding regions. We replicated 52,916 cis and 2,025 trans DNA methylation quantitative trait loci (mQTL) using methylation from whole blood measured on Illumina HumanMethylation450 arrays in the Brisbane Systems Genetics Study (n = 614 from 177 families) and the Lothian Birth Cohorts of 1921 and 1936 (combined n = 1366). The trans mQTL SNPs were found to be over-represented in 1 Mbp subtelomeric regions, and on chromosomes 16 and 19. There was a significant increase in trans mQTL DNA methylation sites in upstream and 5′ UTR regions. The genetic heritability of a number of complex traits and diseases was partitioned into components due to mQTL and the remainder of the genome. Significant enrichment was observed for height (p = 2.1 × 10 −10 ), ulcerative colitis (p = 2 × 10 −5 ), Crohn’s disease (p = 6 × 10 −8 ) and coronary artery disease (p = 5.5 × 10 −6 ) when compared to a random sample of SNPs with matched minor allele frequency, although this enrichment is explained by the genomic location of the mQTL SNPs.

\"En los últimos cincuenta años, más de trescientas enfermedades infecciosas han surgido o resurgido en lugares donde nunca se habían visto. Mucho antes de la llegada de la COVID-19, casi todos los epidemiólogos coincidían en que una de ellas causaría una pandemia mortal en las próximas generaciones: el ébola, la gripe aviar o algo completamente nuevo. Si bien era imposible predecir la aparición del SARS-CoV-2 y tampoco podemos saber qué patógeno causará el próximo brote global, al desentrañar las historias de pandemias pasadas podemos comenzar a comprender mejor nuestro futuro y prepararnos para lo que nos tiene reservado.Pandemia es una obra fundamental de historia epidemiológica que explora los orígenes de las epidemias, trazando paralelismos entre el cólera --uno de los patógenos causantes de pandemias más letales y perturbadores de la historia-- y otras nuevas enfermedades que nos acechan. Rastreando cada etapa del dramático viaje del cólera, desde su aparición en el interior del sur de Asia como un microbio inofensivo hasta su rápida dispersión por el mundo en el siglo XIX y su última aparición en Haití, nos informa sobre otros patógenos que ahora siguen sus pasos, como la bacteria SARM, que asedia a su propia familia, o los virus letales nunca antes vistos que salen de los húmedos mercados de China, las salas quirúrgicas de Nueva Delhi y los patios traseros suburbanos de la costa este de Estados Unidos.\"-- Editor

DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Here we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

Salt homeostasis is maintained by tight control of Na + filtration and reabsorption. In the distal part of the nephron the ubiquitin protein ligase Nedd4-2 regulates membrane abundance and thus activity of the epithelial Na + channel (ENaC), which is rate-limiting for Na + reabsorption. Nedd4-2 deficiency in mouse results in elevated ENaC and nephropathy, however the contribution of dietary salt to this has not been characterized. In this study we show that high dietary Na + exacerbated kidney injury in Nedd4-2 -deficient mice, significantly perturbing normal postnatal nephrogenesis and resulting in multifocal areas of renal dysplasia, increased markers of kidney injury and a decline in renal function. In control mice, high dietary Na + resulted in reduced levels of ENaC. However, Nedd4-2 -deficient kidneys maintained elevated ENaC even after high dietary Na + , suggesting that the inability to efficiently downregulate ENaC is responsible for the salt-sensitivity of disease. Importantly, low dietary Na + significantly ameliorated nephropathy in Nedd4-2 -deficient mice. Our results demonstrate that due to dysregulation of ENaC, kidney injury in Nedd4-2 -deficient mice is sensitive to dietary Na + , which may have implications in the management of disease in patients with kidney disease.

Familial hypercholesterolaemia is a common autosomal-dominant disorder caused by mutations in three known genes. DNA-based cascade testing is recommended by UK guidelines to identify affected relatives; however, about 60% of patients are mutation-negative. We assessed the hypothesis that familial hypercholesterolaemia can also be caused by an accumulation of common small-effect LDL-C-raising alleles. In November, 2011, we assembled a sample of patients with familial hypercholesterolaemia from three UK-based sources and compared them with a healthy control sample from the UK Whitehall II (WHII) study. We also studied patients from a Belgian lipid clinic (Hôpital de Jolimont, Haine St-Paul, Belgium) for validation analyses. We genotyped participants for 12 common LDL-C-raising alleles identified by the Global Lipid Genetics Consortium and constructed a weighted LDL-C-raising gene score. We compared the gene score distribution among patients with familial hypercholesterolaemia with no confirmed mutation, those with an identified mutation, and controls from WHII. We recruited 321 mutation-negative UK patients (451 Belgian), 319 mutation-positive UK patients (273 Belgian), and 3020 controls from WHII. The mean weighted LDL-C gene score of the WHII participants (0·90 [SD 0·23]) was strongly associated with LDL-C concentration (p=1·4 × 10−77; R2=0·11). Mutation-negative UK patients had a significantly higher mean weighted LDL-C score (1·0 [SD 0·21]) than did WHII controls (p=4·5 × 10−16), as did the mutation-negative Belgian patients (0·99 [0·19]; p=5·2 × 10−20). The score was also higher in UK (0·95 [0·20]; p=1·6 × 10−5) and Belgian (0·92 [0·20]; p=0·04) mutation-positive patients than in WHII controls. 167 (52%) of 321 mutation-negative UK patients had a score within the top three deciles of the WHII weighted LDL-C gene score distribution, and only 35 (11%) fell within the lowest three deciles. In a substantial proportion of patients with familial hypercholesterolaemia without a known mutation, their raised LDL-C concentrations might have a polygenic cause, which could compromise the efficiency of cascade testing. In patients with a detected mutation, a substantial polygenic contribution might add to the variable penetrance of the disease. British Heart Foundation, Pfizer, AstraZeneca, Schering-Plough, National Institute for Health Research, Medical Research Council, Health and Safety Executive, Department of Health, National Heart Lung and Blood Institute, National Institute on Aging, Agency for Health Care Policy Research, John D and Catherine T MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health, Unilever, and Departments of Health and Trade and Industry.

Kidney disease progression can be affected by Na + abundance. A key regulator of Na + homeostasis is the ubiquitin ligase NEDD4-2 and its deficiency leads to increased Na + transport activity and salt-sensitive progressive kidney damage. However, the mechanisms responsible for high Na + induced damage remain poorly understood. Here we show that a high Na + diet compromised kidney function in Nedd4-2 -deficient mice, indicative of progression toward end-stage renal disease. Injury was characterized by enhanced tubule dilation and extracellular matrix accumulation, together with sustained activation of both Wnt/β-catenin and TGF-β signaling. Nedd4-2 knockout in cortical collecting duct cells also activated these pathways and led to epithelial–mesenchymal transition. Furthermore, low dietary Na + rescued kidney disease in Nedd4-2 -deficient mice and silenced Wnt/β-catenin and TGF-β signaling. Our study reveals the important role of NEDD4-2-dependent ubiquitination in Na + homeostasis and protecting against aberrant Wnt/β-catenin/TGF-β signaling in progressive kidney disease.

Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here, we aimed to use genomic approaches to investigate this further. Using Connectivity Map (CMap), we first investigated whether statins and antidepressants shared pharmacological effects by interrogating gene expression responses to drug exposure in human cell lines. Second, using Mendelian randomization analysis, we investigated both on-target (through HMGCR inhibition) and potential off-target (through ITGAL and HDAC2 inhibition) causal effects of statins on depression risk and depressive symptoms, and traits related to the shared biological pathways identified from CMap analysis. Compounds inducing highly similar gene expression responses to statins in HA1E cells (indicated by an average connectivity score with statins > 90) were found to be enriched for antidepressants (12 out of 38 antidepressants; p = 9E-08). Genes perturbed in the same direction by both statins and antidepressants were significantly enriched for diverse cellular and metabolic pathways, and various immune activation, development and response processes. MR analysis did not identify any significant associations between statin exposure and depression risk or symptoms after multiple testing correction. However, genetically proxied HMGCR inhibition was strongly associated with alterations in platelets (a prominent serotonin reservoir) and monocyte percentage, which have previously been implicated in depression. Genetically proxied ITGAL inhibition was strongly associated with basophil, monocyte and neutrophil counts. We identified biological pathways that are commonly perturbed by both statins and antidepressants, and haematological biomarkers genetically associated with statin targets. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression and potential as therapeutic targets, and investigation of whether blood biomarkers may be important considerations in clinical trials investigating effects of statins on depression.

Familial hypercholesterolemia (FH) is an autosomal-dominant disorder caused by mutations in 1 of 3 genes. In the 60% of patients who are mutation negative, we have recently shown that the clinical phenotype can be associated with an accumulation of common small-effect LDL cholesterol (LDL-C)-raising alleles by use of a 12-single nucleotide polymorphism (12-SNP) score. The aims of the study were to improve the selection of SNPs and replicate the results in additional samples. We used ROC curves to determine the optimum number of LDL-C SNPs. For replication analysis, we genotyped patients with a clinical diagnosis of FH from 6 countries for 6 LDL-C-associated alleles. We compared the weighted SNP score among patients with no confirmed mutation (FH/M-), those with a mutation (FH/M+), and controls from a UK population sample (WHII). Increasing the number of SNPs to 33 did not improve the ability of the score to discriminate between FH/M- and controls, whereas sequential removal of SNPs with smaller effects/lower frequency showed that a weighted score of 6 SNPs performed as well as the 12-SNP score. Metaanalysis of the weighted 6-SNP score, on the basis of polymorphisms in CELSR2 (cadherin, EGF LAG 7-pass G-type receptor 2), APOB (apolipoprotein B), ABCG5/8 [ATP-binding cassette, sub-family G (WHITE), member 5/8], LDLR (low density lipoprotein receptor), and APOE (apolipoprotein E) loci, in the independent FH/M- cohorts showed a consistently higher score in comparison to the WHII population (P < 2.2 × 10(-16)). Modeling in individuals with a 6-SNP score in the top three-fourths of the score distribution indicated a >95% likelihood of a polygenic explanation of their increased LDL-C. A 6-SNP LDL-C score consistently distinguishes FH/M- patients from healthy individuals. The hypercholesterolemia in 88% of mutation-negative patients is likely to have a polygenic basis.

The accuracy of grey-matter predictors of depression has remained limited. In this study, brain-based predictors of major depressive disorder (MDD) were trained using machine-learning (Best Linear Unbiased Predictors [BLUP]) and deep-learning (ResNet3D) techniques applied to high-dimensional (voxel-wise) grey-matter structure extracted from T1-weighted structural MRI. The training sample comprised 987 MDD cases and 3934 controls from the UK Biobank. Predictors were evaluated in an independent sub-cohort of 483 MDD cases and 1939 controls from the UK Biobank and replicated in a clinical cohort (DEP-ARREST CLIN) of 64 cases and 32 controls. In the UK Biobank, the BLUP predictor showed a significant association with MDD status (AUC = 0.57; OR = 1.28 [1.15-1.43]; p-value = 1.1×10 -5 ), which was confirmed in both males and females. By partitioning the BLUP predictor by brain regions of interest (ROI), we found nominal significance supporting the contribution of previously identified MDD-related ROIs (e.g. hippocampus and amygdala), though none passed multiple testing correction. The BLUP predictor overlapped partially with a polygenic score (PGS) of major depression (AUC = 0.65) but also captured a nominally significant signal that was not captured by the genetic score (combined AUC = 0.66, p-value = 0.024 when compared to PGS alone). No association passed multiple testing correction in the DEP-ARREST CLIN cohort, likely due to the small sample size. In contrast, the deep-learning predictor was not associated with MDD after multiple testing corrections. We estimated the morphometricity of MDD to be 0.061, implying limited potential of a brain-based predictor based on grey-matter structure (maximal AUC = 0.64). While the modest AUC values reiterate the challenge of developing brain-based MDD predictors for clinical applications, our predictors inform future research to explore brain-based relationships between MDD and comorbidities.