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Genome-wide analysis identifies 12 loci influencing human reproductive behavior.
The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.
The effects of an aerobic training intervention on cognition, grey matter volumes and white matter microstructure.
While there is strong evidence from observational studies that physical activity is associated with reduced risk of cognitive decline and dementia, the extent to which aerobic training interventions impact on cognitive health and brain structure remains subject to debate. In a pilot study of 46 healthy older adults (66.6 years ± 5.2 years, 63% female), we compared the effects of a twelve-week aerobic training programme to a waitlist control condition on cardiorespiratory fitness, cognition and magnetic resonance imaging (MRI) outcomes. Cardiorespiratory fitness was assessed by VO2 max testing. Cognitive assessments spanned executive function, memory and processing speed. Structural MRI analysis included examination of hippocampal volume, and voxel-wise assessment of grey matter volumes using voxel-based morphometry. Diffusion tensor imaging analysis of fractional anisotropy, axial diffusivity and radial diffusivity was performed using tract-based spatial statistics. While the intervention successfully increased cardiorespiratory fitness, there was no evidence that the aerobic training programme led to changes in cognitive functioning or measures of brain structure in older adults. Interventions that are longer lasting, multi-factorial, or targeted at specific high-risk populations, may yield more encouraging results.
Strengthening ethical community engagement in contemporary Malawi
Although community engagement is increasingly promoted in global health research to improve ethical research practice, there is sometimes a disconnect between the broader moral ambitions for community engagement in the literature and guidelines on the one hand and its rather narrower practical application in health research on the other. In practice, less attention is paid to engaging communities for the ‘intrinsic’ value of showing respect and ensuring inclusive participation of community partners in research design. Rather, more attention is paid to the use of community engagement for ‘instrumental’ purposes to improve community understanding of research and ensure successful study implementation. Against this backdrop, we reviewed the literature and engaged various research stakeholders at a workshop to discuss ways of strengthening ethical engagement of communities and to develop context-relevant guidelines for community engagement in health research in Malawi.
Confound modelling in UK Biobank brain imaging
Abstract Dealing with confounds is an essential step in large cohort studies to address problems such as unexplained variance and spurious correlations. UK Biobank is a powerful resource for studying associations between imaging and nonimaging measures such as lifestyle factors and health outcomes, in part because of the large subject numbers. However, the resulting high statistical power also raises the sensitivity to confound effects, which therefore have to be carefully considered. In this work we describe a set of possible confounds (including non-linear effects and interactions) that researchers may wish to consider for their studies using such data. We include descriptions of how we can estimate the confounds, and study the extent to which each of these confounds affects the data, and the spurious correlations that may arise if they are not controlled. Finally, we discuss several issues that future studies should consider when dealing with confounds.
Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease.
Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease.
Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.
Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10-8). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
Body size, body composition and endometrial cancer risk among postmenopausal women in UK Biobank.
Previous studies on the association of adiposity with endometrial cancer risk have mostly used body mass index (BMI) as the main exposure of interest. Whether more precise measures of body fat, such as body fat percentage and fat mass estimated by bioimpedance analyses, are better indicators of risk than BMI is unknown. The role of central adiposity and fat-free mass in endometrial cancer development remains unclear. We used Cox regression models to estimate hazard ratios (HR) and corresponding 95% confidence intervals (CI) for the associations of various measures of body size/composition with the risk of endometrial cancer among 135 110 postmenopausal women enrolled in UK Biobank. During a mean follow up of 6.8 years, 706 endometrial cancers were diagnosed, with a mean age at diagnosis of 65.5 years. The HRs (95%CIs) for endometrial cancer per 1 SD (SD) increase in BMI, body fat percentage and fat mass were broadly comparable, being 1.71 (1.61-1.82), 1.92 (1.75-2.11) and 1.73 (1.63-1.85), respectively. There was an indication of positive association between central adiposity, as reflected by waist circumference (HR per 1-SD increase = 1.08, 95%CI:1.00-1.17) and waist to hip ratio (HR per 1-SD increase = 1.13, 95%CI: 1.01-1.26), and endometrial cancer risk after accounting for BMI. Fat-free mass was not an independent predictor of risk in this cohort. These findings suggest that body fat percentage and fat mass are not better indicators of endometrial cancer risk than BMI. Further studies are needed to establish whether central adiposity contributes to risk beyond overall adiposity.
Haematological markers and prostate cancer risk: a prospective analysis in UK Biobank.
BACKGROUND:Risk factors for prostate cancer are not well understood. Red blood cell, platelet and white blood cell indices may be markers of a range of exposures that might be related to prostate cancer risk. Therefore, we examined the associations of haematological parameters with prostate cancer risk. METHODS:Complete blood count data from 209,686 male UK Biobank participants who were free from cancer at study baseline were analysed. Participants were followed-up via data linkage. After a mean follow-up of 6.8 years, 5,723 men were diagnosed with prostate cancer and 323 men died from prostate cancer. Multivariable-adjusted Cox regression was used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for prostate cancer incidence and mortality by haematological parameters, and corrected for regression dilution bias. RESULTS:Higher red blood cell (HR per 1 SD increase=1.09, 95% CI 1.05-1.13) and platelet counts (HR=1.07, 1.04-1.11) were associated with an increased risk of prostate cancer. Higher mean corpuscular volume (HR=0.90, 0.87-0.93), mean corpuscular haemoglobin (HR=0.90, 0.87-0.93), mean corpuscular haemoglobin concentration (HR=0.87, 0.77-0.97) and mean sphered cell volume (HR=0.91, 0.87-0.94) were associated with a lower prostate cancer risk. Higher white blood cell (HR=1.14, 1.05-1.24) and neutrophil count (HR=1.27, 1.09-1.48) were associated with prostate cancer mortality. CONCLUSIONS:These associations of blood indices of prostate cancer risk and mortality may implicate shared common causes, including testosterone, nutrition and inflammation/infection among several others in prostate cancer development and/or progression. IMPACT:These associations provide insights into prostate cancer development and progression.
Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report)
Copyright © The Author(s) 2020. Published by Cambridge University Press. BackgroundMajor depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression.MethodsWithin the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS).ResultsEstimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15-1.32, R2 = 1.47%).ConclusionsBy assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.
The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions.
UK Biobank is a population-based cohort of half a million participants aged 40-69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world's largest multi-modal imaging study, with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future directions.
Patterns of sociocognitive stratification and perinatal risk in the child brain.
The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain-environment interactions and flavored by unique life experiences. The transition into young adulthood offers opportunities for adaptation and growth but also increased susceptibility to environmental perturbations, such as the characteristics of social relationships, family environment, quality of schools and activities, financial security, urbanization and pollution, drugs, cultural practices, and values, that all act in concert with our genetic architecture and biology. Our multivariate brain-behavior mapping in 7,577 children aged 9 to 11 y across 585 brain imaging phenotypes and 617 cognitive, behavioral, psychosocial, and socioeconomic measures revealed three population modes of brain covariation, which were robust as assessed by cross-validation and permutation testing, taking into account siblings and twins, identified using genetic data. The first mode revealed traces of perinatal complications, including preterm and twin birth, eclampsia and toxemia, shorter period of breastfeeding, and lower cognitive scores, with higher cortical thickness and lower cortical areas and volumes. The second mode reflected a pattern of sociocognitive stratification, linking lower cognitive ability and socioeconomic status to lower cortical thickness, area, and volumes. The third mode captured a pattern related to urbanicity, with particulate matter pollution (PM25) inversely related to home value, walkability, and population density, associated with diffusion properties of white matter tracts. These results underscore the importance of a multidimensional and interdisciplinary understanding, integrating social, psychological, and biological sciences, to map the constituents of healthy development and to identify factors that may precede maladjustment and mental illness.
A structural brain network of genetic vulnerability to psychiatric illness.
Psychiatry is undergoing a paradigm shift from the acceptance of distinct diagnoses to a representation of psychiatric illness that crosses diagnostic boundaries. How this transition is supported by a shared neurobiology remains largely unknown. In this study, we first identify single nucleotide polymorphisms (SNPs) associated with psychiatric disorders based on 136 genome-wide association studies. We then conduct a joint analysis of these SNPs and brain structural connectomes in 678 healthy children in the PING study. We discovered a strong, robust, and transdiagnostic mode of genome-connectome covariation which is positively and specifically correlated with genetic risk for psychiatric illness at the level of individual SNPs. Similarly, this mode is also significantly positively correlated with polygenic risk scores for schizophrenia, alcohol use disorder, major depressive disorder, a combined bipolar disorder-schizophrenia phenotype, and a broader cross-disorder phenotype, and significantly negatively correlated with a polygenic risk score for educational attainment. The resulting "vulnerability network" is shown to mediate the influence of genetic risks onto behaviors related to psychiatric vulnerability (e.g., marijuana, alcohol, and caffeine misuse, perceived stress, and impulsive behavior). Its anatomy overlaps with the default-mode network, with a network of cognitive control, and with the occipital cortex. These findings suggest that the brain vulnerability network represents an endophenotype funneling genetic risks for various psychiatric illnesses through a common neurobiological root. It may form part of the neural underpinning of the well-recognized but poorly explained overlap and comorbidity between psychiatric disorders.
Policy implications of the potential use of a novel vaccine to prevent infection with Schistosoma mansoni with or without mass drug administration.
Schistosomiasis is one of the most important neglected tropical diseases (NTDs) affecting millions of people in 79 different countries. The World Health Organization (WHO) has specified two control goals to be achieved by 2020 and 2025 - morbidity control and elimination as a public health problem (EPHP). Mass drug administration (MDA) is the main method for schistosomiasis control but it has sometimes proved difficult to both secure adequate supplies of the most efficacious drug praziquantel to treat the millions infected either annually or biannually, and to achieve high treatment coverage in targeted communities in regions of endemic infection. The development of alternative control methods remains a priority. In this paper, using stochastic individual-based models, we analyze whether the addition of a novel vaccine alone or in combination with drug treatment, is a more effective control strategy, in terms of achieving the WHO goals, as well as the time and costs to achieve these goals when compared to MDA alone. The key objective of our analyses is to help facilitate decision making for moving a promising candidate vaccine through the phase I, II and III trials in humans to a final product for use in resource poor settings. We find that in low to moderate transmission settings, both vaccination and MDA are highly likely to achieve the WHO goals within 15 years and are likely to be cost-effective. In high transmission settings, MDA alone is unable to achieve the goals, whereas vaccination is able to achieve both goals in combination with MDA. In these settings Vaccination is cost-effective, even for short duration vaccines, so long as vaccination costs up to US$7.60 per full course of vaccination. The public health value of the vaccine depends on the duration of vaccine protection, the baseline prevalence prior to vaccination and the WHO goal.
Horizontal gene transfer rate is not the primary determinant of observed antibiotic resistance frequencies in Streptococcus pneumoniae
<jats:p>The extent to which evolution is constrained by the rate at which horizontal gene transfer (HGT) allows DNA to move between genetic lineages is an open question, which we address in the context of antibiotic resistance in <jats:italic>Streptococcus pneumoniae</jats:italic>. We analyze microbiological, genomic, and epidemiological data from the largest-to-date sequenced pneumococcal carriage study in 955 infants from a refugee camp on the Thailand-Myanmar border. Using a unified framework, we simultaneously test prior hypotheses on rates of HGT and a key evolutionary covariate (duration of carriage) as determinants of resistance frequencies. We conclude that in this setting, there is little evidence of HGT playing a major role in determining resistance frequencies. Instead, observed resistance frequencies are best explained as the outcome of selection acting on a pool of variants, irrespective of the rate at which resistance determinants move between genetic lineages.</jats:p>
Exome Sequencing Analysis Identifies Rare Variants in ATM and RPL8 That Are Associated With Shorter Telomere Length.
Telomeres are important for maintaining genomic stability. Telomere length has been associated with aging, disease, and mortality and is highly heritable (∼82%). In this study, we aimed to identify rare genetic variants associated with telomere length using whole-exome sequence data. We studied 1,303 participants of the Erasmus Rucphen Family (ERF) study, 1,259 of the Rotterdam Study (RS), and 674 of the British Heart Foundation Family Heart Study (BHF-FHS). We conducted two analyses, first we analyzed the family-based ERF study and used the RS and BHF-FHS for replication. Second, we combined the summary data of the three studies in a meta-analysis. Telomere length was measured by quantitative polymerase chain reaction in blood. We identified nine rare variants significantly associated with telomere length (p-value < 1.42 × 10-7, minor allele frequency of 0.2-0.5%) in the ERF study. Eight of these variants (in C11orf65, ACAT1, NPAT, ATM, KDELC2, and EXPH5) were located on chromosome 11q22.3 that contains ATM, a gene involved in telomere maintenance. Although we were unable to replicate the variants in the RS and BHF-FHS (p-value ≥ 0.21), segregation analysis showed that all variants segregate with shorter telomere length in a family. In the meta-analysis of all studies, a nominally significant association with LTL was observed with a rare variant in RPL8 (p-value = 1.48 × 10-6), which has previously been associated with age. Additionally, a novel rare variant in the known RTEL1 locus showed suggestive evidence for association (p-value = 1.18 × 10-4) with LTL. To conclude, we identified novel rare variants associated with telomere length. Larger samples size are needed to confirm these findings and to identify additional variants.
Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.
Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.