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The Iberian Peninsula is linguistically diverse and has a complex demographic history, including a centuries-long period of Muslim rule. Here, we study the fine-scale genetic structure of its population, and the genetic impacts of historical events, leveraging powerful, haplotype-based statistical methods to analyse 1413 individuals from across Spain. We detect extensive fine-scale population structure at extremely fine scales (below 10 Km) in some regions, including Galicia. We identify a major east-west axis of genetic differentiation, and evidence of historical north to south population movement. We find regionally varying fractions of north-west African ancestry (0–11%) in modern-day Iberians, related to an admixture event involving European-like and north-west African-like source populations. We date this event to 860–1120 CE, implying greater genetic impacts in the early half of Muslim rule in Iberia. Together, our results indicate clear genetic impacts of population movements associated with both the Muslim conquest and the subsequent Reconquista . The Iberian Peninsula has a complex history. Here, the authors analyse the genetic structure of the modern Iberian population at fine scale, revealing historical population movements associated with the time of Muslim rule.

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is unknown. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school age. We examined associations of both DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age 4–15 years) in 2477 children from 5 cohorts and of DNA methylation at school age with concurrent ADHD symptoms (age 7–11 years) in 2374 children from 9 cohorts, with 3 cohorts participating at both timepoints. CpGs identified with nominal significance ( p  < 0.05) in either of the EWAS were correlated between timepoints ( ρ  = 0.30), suggesting overlap in associations; however, top signals were very different. At birth, we identified nine CpGs that predicted later ADHD symptoms ( p  < 1 × 10 –7 ), including ERC2 and CREB5 . Peripheral blood DNA methylation at one of these CpGs (cg01271805 in the promoter region of ERC2 , which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5 , which previously was associated with neurite outgrowth and an ADHD diagnosis. In contrast, at school age, no CpGs were associated with ADHD with p  < 1 × 10 −7 . In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.

The textbook description of mitochondrial respiratory complexes (RCs) views them as free-moving entities linked by the mobile carriers coenzyme Q (CoQ) and cytochrome c (cyt c). This model (known as the fluid model) is challenged by the proposal that all RCs except complex II can associate in supercomplexes (SCs). The proposed SCs are the respirasome (complexes I, III, and IV), complexes I and III, and complexes III and IV. The role of SCs is unclear, and their existence is debated. By genetic modulation of interactions between complexes I and III and III and IV, we show that these associations define dedicated CoQ and cyt c pools and that SC assembly is dynamic and organizes electron flux to optimize the use of available substrates.

Cells can fine-tune which genes they activate, when and at which levels using a range of chemical marks on the DNA and certain proteins that help to organise the genome. One well-known example of such ‘epigenetic tags’ is DNA methylation, whereby a methyl group is added onto particular positions in the genome. Many factors – including environmental effects such as diet – control DNA methylation, allowing an organism to adapt to ever-changing conditions. An expression quantitative trait methylation (eQTM) is a specific position of the genome whose DNA methylation status regulates the activity of a given gene. A catalogue of eQTMs would be useful in helping to reveal how the environment and disease impacts the way cells work. Yet, currently, the relationships between most epigenetic tags and gene activity remains unclear, especially in children. To fill this gap, Ruiz-Arenas et al. studied DNA methylation in blood samples from over 800 healthy children across Europe. Amongst all tested DNA methylation sites, 22,000 (5.7% of total) were associated with the expression of a gene – and therefore were eQTMs; reciprocally, 9,000 genes (15.3% of all tested genes) were linked to at least one methylation site, leading to a total of 40,000 pairs of DNA methylation sites and genes. Most often, eQTMs regulated the expression of nearby genes – but only half controlled the gene that was the closest to them. Age and the genetic background of the individuals influenced the nature of eQTMs. This catalogue is a useful resource for the scientific community to start understanding the relationship between epigenetics and gene activity. Similar studies are now needed for other tissues and age ranges. Overall, extending our knowledge of eQTMs may help reveal how life events lead to illness, and could inform prevention efforts.

Background The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. Methods We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. Results Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. Conclusion In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.

Background Obesity and neurodevelopmental delay are complex traits that often co-occur and differ between boys and girls. Prenatal exposures are believed to influence children’s obesity, but it is unknown whether exposures of pregnant mothers can confer a different risk of obesity between sexes, and whether they can affect neurodevelopment. Methods We analyzed data from 1044 children from the HELIX project, comprising 93 exposures during pregnancy, and clinical, neuropsychological, and methylation data during childhood (5–11 years). Using exposome-wide interaction analyses, we identified prenatal exposures with the highest sexual dimorphism in obesity risk, which were used to create a multiexposure profile. We applied causal random forest to classify individuals into two environments: E1 and E0. E1 consists of a combination of exposure levels where girls have significantly less risk of obesity than boys, as compared to E0, which consists of the remaining combination of exposure levels. We investigated whether the association between sex and neurodevelopmental delay also differed between E0 and E1. We used methylation data to perform an epigenome-wide association study between the environments to see the effect of belonging to E1 or E0 at the molecular level. Results We observed that E1 was defined by the combination of low dairy consumption, non-smokers’ cotinine levels in blood, low facility richness, and the presence of green spaces during pregnancy (OR interaction  = 0.070, P  = 2.59 × 10 −5 ). E1 was also associated with a lower risk of neurodevelopmental delay in girls, based on neuropsychological tests of non-verbal intelligence (OR interaction  = 0.42, P  = 0.047) and working memory (OR interaction  = 0.31, P  = 0.02). In line with this, several neurodevelopmental functions were enriched in significant differentially methylated probes between E1 and E0. Conclusions The risk of obesity can be different for boys and girls in certain prenatal environments. We identified an environment combining four exposure levels that protect girls from obesity and neurodevelopment delay. The combination of single exposures into multiexposure profiles using causal inference can help determine populations at risk.

Conplastic mice that share the same nuclear genome but have different mitochondrial DNA were analysed throughout their life — the mitochondrial genome affects many aspects of physiology and results in differences in median lifespan; the authors propose that the interplay of mitochondrial and nuclear genomes may be an important factor influencing this phenomenon. Mitochondrial DNA affects metabolism and ageing José Antonio Enríquez and colleagues look into the effects of mitochondrial DNA sequence variation by using congenic mice strains that share the same nuclear genome, but have different mitochondrial DNA. They show that the mitochondrial genome has a profound influence on many aspects of physiology — including insulin signalling, obesity and telomere shortening — and results in differences in median lifespan. Thus non-pathological mitochondrial DNA variants have a broad effect on metabolism, with the differences more pronounced later in life. The authors suggest that the interplay of mitochondrial and nuclear genomes may be an important factor influencing this phenomenon, which may have implications for the field of mitochondrial replacement. Human mitochondrial DNA (mtDNA) shows extensive within-population sequence variability 1 . Many studies suggest that mtDNA variants may be associated with ageing or diseases 2 , 3 , 4 , although mechanistic evidence at the molecular level is lacking 5 , 6 . Mitochondrial replacement has the potential to prevent transmission of disease-causing oocyte mtDNA. However, extension of this technology requires a comprehensive understanding of the physiological relevance of mtDNA sequence variability and its match with the nuclear-encoded mitochondrial genes. Studies in conplastic animals 7 , 8 , 9 allow comparison of individuals with the same nuclear genome but different mtDNA variants, and have provided both supporting and refuting evidence that mtDNA variation influences organismal physiology. However, most of these studies did not confirm the conplastic status, focused on younger animals, and did not investigate the full range of physiological and phenotypic variability likely to be influenced by mitochondria. Here we systematically characterized conplastic mice throughout their lifespan using transcriptomic, proteomic, metabolomic, biochemical, physiological and phenotyping studies. We show that mtDNA haplotype profoundly influences mitochondrial proteostasis and reactive oxygen species generation, insulin signalling, obesity, and ageing parameters including telomere shortening and mitochondrial dysfunction, resulting in profound differences in health longevity between conplastic strains.

Background Sepsis is a severe systemic inflammatory response to infections that is accompanied by organ dysfunction and has a high mortality rate in adult intensive care units. Most genetic studies have identified gene variants associated with development and outcomes of sepsis focusing on biological candidates. We conducted the first genome-wide association study (GWAS) of 28-day survival in adult patients with sepsis. Methods This study was conducted in two stages. The first stage was performed on 687 European sepsis patients from the GEN-SEP network and 7.5 million imputed variants. Association testing was conducted with Cox regression models, adjusting by sex, age, and the main principal components of genetic variation. A second stage focusing on the prioritized genetic variants was performed on 2,063 ICU sepsis patients (1362 European Americans and 701 African-Americans) from the MESSI study. A meta-analysis of results from the two stages was conducted and significance was established at p  < 5.0 × 10 −8 . Whole-blood transcriptomic, functional annotations, and sensitivity analyses were evaluated on the identified genes and variants. Findings We identified three independent low-frequency variants associated with reduced 28-day sepsis survival, including a missense variant in SAMD9 (hazard ratio [95% confidence interval] = 1.64 [1.37–6.78], p  = 4.92 × 10 −8 ). SAMD9 encodes a possible mediator of the inflammatory response to tissue injury. Interpretation We performed the first GWAS of 28-day sepsis survival and identified novel variants associated with reduced survival. Larger sample size studies are needed to better assess the genetic effects in sepsis survival and to validate the findings.

Ana Vega and colleagues report the results of a three-stage genome-wide association study of radiotherapy toxicity following treatment for prostate cancer. They find that susceptibility to late radiation-induced toxicity is associated with variants in the TANC1 gene at 2q24.1. There is increasing evidence supporting the role of genetic variants in the development of radiation-induced toxicity 1 . However, previous candidate gene association studies failed to elucidate the common genetic variation underlying this phenotype 2 , which could emerge years after the completion of treatment 3 . We performed a genome-wide association study on a Spanish cohort of 741 individuals with prostate cancer treated with external beam radiotherapy (EBRT). The replication cohorts consisted of 633 cases from the UK 4 and 368 cases from North America 5 . One locus comprising TANC1 (lowest unadjusted P value for overall late toxicity = 6.85 × 10 −9 , odds ratio (OR) = 6.61, 95% confidence interval (CI) = 2.23–19.63) was replicated in the second stage (lowest unadjusted P value for overall late toxicity = 2.08 × 10 −4 , OR = 6.17, 95% CI = 2.25–16.95; P combined = 4.16 × 10 −10 ). The inclusion of the third cohort gave unadjusted P combined = 4.64 × 10 −11 . These results, together with the role of TANC1 in regenerating damaged muscle, suggest that the TANC1 locus influences the development of late radiation-induced damage.

Experimental data showed that endothelial lipase (LIPG) is a crucial player in breast cancer. However, very limited data exists on the role of LIPG on the risk of breast cancer in humans. We examined the LIPG-breast cancer association within our population-based case–control study from Galicia, Spain, BREOGAN (BREast Oncology GAlicia Network). Plasma LIPG and/or OxLDL were measured on 114 breast cancer cases and 82 controls from our case–control study, and were included in the present study. The risk of breast cancer increased with increasing levels of LIPG (multivariable OR for the highest category (95% CI) 2.52 (1.11–5.81), P-trend = 0.037). The LIPG-breast cancer association was restricted to Pre-menopausal breast cancer (Multivariable OR for the highest LIPG category (95% CI) 4.76 (0.94–28.77), P-trend = 0.06, and 1.79 (0.61–5.29), P-trend = 0.372, for Pre-menopausal and Post-menopausal breast cancer, respectively). The LIPG-breast cancer association was restricted to Luminal A breast cancers (Multivariable OR for the highest LIPG category (95% CI) 3.70 (1.42–10.16), P-trend = 0.015, and 2.05 (0.63–7.22), P-trend = 0.311, for Luminal A and non-Luminal A breast cancers, respectively). Subset analysis only based on HER2 receptor indicated that the LIPG-breast cancer relationship was restricted to HER2-negative breast cancers (Multivariable OR for the highest LIPG category (95% CI) 4.39 (1.70–12.03), P-trend = 0.012, and 1.10 (0.28–4.32), P-trend = 0.745, for HER2-negative and HER2-positive tumors, respectively). The LIPG-breast cancer association was restricted to women with high total cholesterol levels (Multivariable OR for the highest LIPG category (95% CI) 6.30 (2.13–20.05), P-trend = 0.018, and 0.65 (0.11–3.28), P-trend = 0.786, among women with high and low cholesterol levels, respectively). The LIPG-breast cancer association was also restricted to non-postpartum breast cancer (Multivariable OR for the highest LIPG category (95% CI) 3.83 (1.37–11.39), P-trend = 0.003, and 2.35 (0.16–63.65), P-trend = 0.396, for non-postpartum and postpartum breast cancer, respectively), although we lacked precision. The LIPG-breast cancer association was more pronounced among grades II and III than grade I breast cancers (Multivariable ORs for the highest category of LIPG (95% CI) 2.73 (1.02–7.69), P-trend = 0.057, and 1.90 (0.61–6.21), P-trend = 0.170, for grades II and III, and grade I breast cancers, respectively). No association was detected for OxLDL levels and breast cancer (Multivariable OR for the highest versus the lowest category (95% CI) 1.56 (0.56–4.32), P-trend = 0.457).