Methods have been developed for Mendelian randomization that can obtain consistent causal estimates under weaker assumptions than the standard instrumental variable assumptions. The median-based ...estimator and MR-Egger are examples of such methods. However, these methods can be sensitive to genetic variants with heterogeneous causal estimates. Such heterogeneity may arise from over-dispersion in the causal estimates, or specific variants with outlying causal estimates. In this paper, we develop three extensions to robust methods for Mendelian randomization with summarized data: 1) robust regression (MM-estimation); 2) penalized weights; and 3) Lasso penalization. Methods using these approaches are considered in two applied examples: one where there is evidence of over-dispersion in the causal estimates (the causal effect of body mass index on schizophrenia risk), and the other containing outliers (the causal effect of low-density lipoprotein cholesterol on Alzheimer's disease risk). Through an extensive simulation study, we demonstrate that robust regression applied to the inverse-variance weighted method with penalized weights is a worthwhile additional sensitivity analysis for Mendelian randomization to provide robustness to variants with outlying causal estimates. The results from the applied examples and simulation study highlight the importance of using methods that make different assumptions to assess the robustness of findings from Mendelian randomization investigations with multiple genetic variants.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
While comorbidity between coronary heart disease (CHD) and depression is evident, it is unclear whether the two diseases have shared underlying mechanisms. We performed a range of analyses in 367,703 ...unrelated middle-aged participants of European ancestry from UK Biobank, a population-based cohort study, to assess whether comorbidity is primarily due to genetic or environmental factors, and to test whether cardiovascular risk factors and CHD are likely to be causally related to depression using Mendelian randomization. We showed family history of heart disease was associated with a 20% increase in depression risk (95% confidence interval CI 16-24%, p < 0.0001), but a genetic risk score that is strongly associated with CHD risk was not associated with depression. An increase of 1 standard deviation in the CHD genetic risk score was associated with 71% higher CHD risk, but 1% higher depression risk (95% CI 0-3%; p = 0.11). Mendelian randomization analyses suggested that triglycerides, interleukin-6 (IL-6), and C-reactive protein (CRP) are likely causal risk factors for depression. The odds ratio for depression per standard deviation increase in genetically-predicted triglycerides was 1.18 (95% CI 1.09-1.27; p = 2 × 10
); per unit increase in genetically-predicted log-transformed IL-6 was 0.74 (95% CI 0.62-0.89; p = 0.0012); and per unit increase in genetically-predicted log-transformed CRP was 1.18 (95% CI 1.07-1.29; p = 0.0009). Our analyses suggest that comorbidity between depression and CHD arises largely from shared environmental factors. IL-6, CRP and triglycerides are likely to be causally linked with depression, so could be targets for treatment and prevention of depression.
Abstract
Aims
The causal role of adiposity for several cardiovascular diseases (CVDs) is unclear. Our primary aim was to apply the Mendelian randomization design to investigate the associations of ...body mass index (BMI) with 13 CVDs and arterial hypertension. We also assessed the roles of fat mass and fat-free mass on the same outcomes.
Methods and results
Single-nucleotide polymorphisms associated with BMI and fat mass and fat-free mass indices were used as instrumental variables to estimate the associations with the cardiovascular conditions among 367 703 UK Biobank participants. After correcting for multiple testing, genetically predicted BMI was significantly positively associated with eight outcomes, including and with decreasing magnitude of association: aortic valve stenosis, heart failure, deep vein thrombosis, arterial hypertension, peripheral artery disease, coronary artery disease, atrial fibrillation, and pulmonary embolism. The odds ratio (OR) per 1 kg/m2 increase in BMI ranged from 1.06 95% confidence interval (CI) 1.02–1.11; P = 2.6 × 10−3 for pulmonary embolism to 1.13 (95% CI 1.05–1.21; P = 1.2 × 10−3) for aortic valve stenosis. There was suggestive evidence of positive associations of genetically predicted fat mass index with nine outcomes (P < 0.05). The strongest magnitude of association was with aortic valve stenosis (OR per 1 kg/m2 increase in fat mass index 1.46, 95% CI 1.13–1.88; P = 3.9 × 10−3). There was suggestive evidence of inverse associations of fat-free mass index with atrial fibrillation, ischaemic stroke, and abdominal aortic aneurysm.
Conclusion
This study provides evidence that higher BMI and particularly fat mass index are associated with increased risk of aortic valve stenosis and most other cardiovascular conditions.
Methods have been developed for Mendelian randomization that can obtain consistent causal estimates while relaxing the instrumental variable assumptions. These include multivariable Mendelian ...randomization, in which a genetic variant may be associated with multiple risk factors so long as any association with the outcome is via the measured risk factors (measured pleiotropy), and the MR‐Egger (Mendelian randomization‐Egger) method, in which a genetic variant may be directly associated with the outcome not via the risk factor of interest, so long as the direct effects of the variants on the outcome are uncorrelated with their associations with the risk factor (unmeasured pleiotropy). In this paper, we extend the MR‐Egger method to a multivariable setting to correct for both measured and unmeasured pleiotropy. We show, through theoretical arguments and a simulation study, that the multivariable MR‐Egger method has advantages over its univariable counterpart in terms of plausibility of the assumption needed for consistent causal estimation and power to detect a causal effect when this assumption is satisfied. The methods are compared in an applied analysis to investigate the causal effect of high‐density lipoprotein cholesterol on coronary heart disease risk. The multivariable MR‐Egger method will be useful to analyse high‐dimensional data in situations where the risk factors are highly related and it is difficult to find genetic variants specifically associated with the risk factor of interest (multivariable by design), and as a sensitivity analysis when the genetic variants are known to have pleiotropic effects on measured risk factors.
We consider dissipative effects occurring in the optically thick inner parts of the relativistic outflows producing gamma-ray bursts and X-ray flashes, emphasizing in particular the Comptonization of ...the thermal radiation flux that is advected from the base of the outflow. Such dissipative effects--e.g., from magnetic reconnection, neutron decay, or shocks would boost the energy density of the thermal radiation. The dissipation can lead to pair production, in which case the pairs create an effective photosphere farther out than the usual baryonic one. In a slow dissipation scenario, pair creation can be suppressed, and the effects are most important when dissipation occurs below the baryonic photosphere. In both cases an increased photospheric luminosity is obtained. We suggest that the spectral peak in gamma-ray bursts is essentially due to the Comptonized thermal component from the photosphere, where the comoving optical depth in the outflow falls to unity. Typical peak photon energies range between those of classical bursts and X-ray flashes. The relationship between the observed photon peak energy and the luminosity depends on the details of the dissipation, but under plausible assumptions can resemble the observed correlations.
Ammonia (NH3) and nitrous oxide (N2O) are two important air pollutants that have major impacts on climate change and biodiversity losses. Agriculture represents their largest source and effective ...mitigation measures of individual gases have been well studied. However, the interactions and trade‐offs between NH3 and N2O emissions remain uncertain. Here, we report the results of a two‐year field experiment in a wheat‐maize rotation in the North China Plain (NCP), a global hotspot of reactive N emissions. Our analysis is supported by a literature synthesis of global croplands, to understand the interactions between NH3 and N2O emissions and to develop the most effective approaches to jointly mitigate NH3 and N2O emissions. Field results indicated that deep placement of urea with nitrification inhibitors (NIs) reduced both emissions of NH3 by 67% to 90% and N2O by 73% to 100%, respectively, in comparison with surface broadcast urea which is the common farmers’ practice. But, deep placement of urea, surface broadcast urea with NIs, and application of urea with urease inhibitors probably led to trade‐offs between the two gases, with a mitigation potential of −201% to 101% for NH3 and −112% to 89% for N2O. The literature synthesis showed that deep placement of urea with NIs had an emission factor of 1.53%‐4.02% for NH3 and 0.22%‐0.36% for N2O, which were much lower than other fertilization regimes and the default values recommended by IPCC guidelines. This would translate to a reduction of 3.86–5.47 Tg N yr−1 of NH3 and 0.41–0.50 Tg N yr−1 of N2O emissions, respectively, when adopting deep placement of urea with NIs (relative to current practice) in global croplands. We conclude that the combination of NIs and deep placement of urea can successfully tackle the trade‐offs between NH3 and N2O emissions, therefore avoiding N pollution swapping in global croplands.
Deep application of urea with nitrification inhibitors consistently achieved low NH3 and N2O emissions, and therefore tackles the trade‐offs between NH3 and N2O emissions. Other N application methods (e.g., surface or subsurface application) and N sources (e.g., urea or urea with nitrification or urease inhibitors) probably lead to the high NH3 and/or N2O emissions.
Background: Exposure to environmental toxicants is associated with numerous disease outcomes, many of which involve underlying immune and inflammatory dysfunction. Objectives: To address the gap ...between environmental exposures and immune dysfunction, we investigated the association of two endocrine-disrupting compounds (EDCs) with markers of immune function. Methods: Using data from the 2003—2006 National Health and Nutrition Examination Survey, we compared urinary bisphenol A (BPA) and triclosan levels with serum cytomegalovirus (CMV) antibody levels and diagnosis of allergies or hay fever in U.S. adults and children > 6 years of age. We used multivariate ordinary least squares linear regression models to examine the association of BPA and tridosan with CMV antibody titers, and multivariate logistic regression models to investigate the association of these chemicals with allergy or hay fever diagnosis. Statistical models were stratified by age (< 18 years and > 18 years). Results: In analyses adjusted for age, sex, race, body mass index, creatinine levels, family income, and educational attainment, in the > 18-year age group, higher urinary BPA levels were associated with higher CMV antibody titers (p < 0.001). In the < 18-year age group, lower levels of BPA were associated with higher CMV antibody titers (p < 0.05). However, tridosan, but not BPA, showed a positive association with allergy or hay fever diagnosis. In the < 18-year age group, higher levels of tridosan were associated with greater odds of having been diagnosed with allergies or hay fever (p < 0.01). Conclusions: EDCs such as BPA and tridosan may negatively affect human immune function as measured by CMV antibody levels and allergy or hay fever diagnosis, respectively, with differential consequences based on age. Additional studies should be done to investigate these findings.
In an experiment on dyadic social interaction, we invited participants to verbal interactions in cooperative, competitive, and 'fun task' conditions. We focused on the link between interactants' ...affectivity and their nonverbal synchrony, and explored which further variables contributed to affectivity: interactants' personality traits, sex, and the prescribed interaction tasks. Nonverbal synchrony was quantified by the coordination of interactants' body movement, using an automated video-analysis algorithm (motion energy analysis). Traits were assessed with standard questionnaires of personality, attachment, interactional style, psychopathology, and interpersonal reactivity. We included 168 previously unacquainted individuals who were randomly allocated to same-sex dyads (84 females, 84 males, mean age 27.8 years). Dyads discussed four topics of general interest drawn from an urn of eight topics, and finally engaged in a fun interaction. Each interaction lasted 5 min. In between interactions, participants repeatedly assessed their affect. Using hierarchical linear modeling, we found moderate to strong effect sizes for synchrony to occur, especially in competitive and fun task conditions. Positive affect was associated positively with synchrony, negative affect was associated negatively. As for causal direction, data supported the interpretation that synchrony entailed affect rather than vice versa. The link between nonverbal synchrony and affect was strongest in female dyads. The findings extend previous reports of synchrony and mimicry associated with emotion in relationships and suggest a possible mechanism of the synchrony-affect correlation.
Growth patterns for shape-shifting elastic bilayers van Rees, Wim M.; Vouga, Etienne; Mahadevan, L.
Proceedings of the National Academy of Sciences - PNAS,
10/2017, Letnik:
114, Številka:
44
Journal Article
Recenzirano
Odprti dostop
Inspired by the differential-growth-driven morphogenesis of leaves, flowers, and other tissues, there is increasing interest in artificial analogs of these shape-shifting thin sheets made of active ...materials that respond to environmental stimuli such as heat, light, and humidity. But how can we determine the growth patterns to achieve a given shape from another shape? We solve this geometric inverse problem of determining the growth factors and directions (the metric tensors) for a given isotropic elastic bilayer to grow into a target shape by posing and solving an elastic energy minimization problem. A mathematical equivalence between bilayers and curved monolayers simplifies the inverse problem considerably by providing algebraic expressions for the growth metric tensors in terms of those of the final shape. This approach also allows us to prove that we can grow any target surface from any reference surface using orthotropically growing bilayers. We demonstrate this by numerically simulating the growth of a flat sheet into a face, a cylindrical sheet into a flower, and a flat sheet into a complex canyon-like structure.
The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic ...escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care.
We performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community.
We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies-four each within and outside China-with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10-19) days for China, compared with 5 (IQR 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date.
Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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