Relaxed Threshold Research Articles

Analyses of GWAS signal using GRIN identify additional genes contributing to suicidal behavior

Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks when GWAS thresholds are relaxed. GRIN was validated on both simulated interrelated gene sets as well as multiple GWAS traits. From multiple GWAS summary statistics of suicide attempt, a complex phenotype, GRIN identified additional genes that replicated across independent cohorts and retained biologically interrelated genes despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways that may influence suicidal behavior, and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate GRIN’s utility in boosting GWAS results by increasing the number of true positive genes identified from GWAS results.

Genetics, age, and diet influence gut bacterial communities and performance of black soldier fly larvae (Hermetia illucens)

BackgroundThe gut microbiota of black soldier fly larvae (BSFL, Hermetia illucens) play a crucial role in recycling various organic waste streams. This capability is linked to the presence of a potential common core microbiota in BSFL. However, subjective thresholds for defining core taxa and the difficulty of separating genetic and environmental influences have prevented a clear consensus in the literature. We analysed the gut bacterial communities of two genetically distinct BSF lines (wild type (WT) and lab-adapted line (LD)) raised on ten different diets based on common agricultural by-products and food waste in Southeast Asia.ResultsHigh-throughput 16S rRNA gene sequencing revealed that gut bacterial communities were significantly influenced by genetics (p = 0.001), diet (plant/meat-dominated; p = 0.001), larval age (p = 0.001), and the interactions between all three (p = 0.002). This led us to investigate both common core taxa and lineage-specific core taxa. At a strict > 97% prevalence threshold, four core taxa were identified: Providencia_A_732258, an unclassified genus within the family Enterococcaceae, Morganella, and Enterococcus_H_360604. A relaxed threshold (> 80% prevalence) extended the core to include other potential common core taxa such as Klebsiella, Proteus, and Scrofimicrobium. Our data suggest that Proteus, Scrofimicrobium, Corynebacterium, Vagococcus_B, Lysinibacillus_304693 (all LD), and Paenibacillus_J_366884 (WT) are lineage-specific rather than members of a common core (> 90% prevalence in either LD or WT, with prevalence significantly different between lines (p ≤ 0.05)). Positive correlations were observed between several core genera and larval performance in LD, typical of a highly optimized lab-adapted line. Interestingly, only members of the genus Providencia appeared to play a crucial role in most aspects of larval performance in both genetic lineages.ConclusionOur study demonstrates that the gut microbiota of BSFL is influenced by genetic factors, diet composition, larval age, and their interactions. We identified a distinct lineage-specific core microbiota, emphasizing genetic background’s role. Future studies should apply a standardized high prevalence threshold of at least > 90% unless there is a valid reason for relaxation or sample exclusion. The consistent association of Providencia spp. with larval performance across both genetic lines highlights their crucial role in the BSFL gut ecosystem.

Testing the causal relationship of fat and sugar intake with depression and cortisol: a Mendelian Randomisation study

Unhealthy diets high in fat and sugar content may have an impact on psychological health and increase the risk of Major Depressive Disorder (MDD) and stress levels. On the other hand, MDD and stress might be related to food choices and intake. However, it is not clear whether diet, and specifically fat and sugar intake, is causally related to stress and MDD, and whether this relationship may be bi-directional. This study utilised Mendelian Randomisation (MR) to investigate the causal nature of the relationship of fat and sugar intake with MDD and cortisol (as a proxy of stress), and to shed light on the direction of this relationship. Summary-level data for all exposure and outcome variables were obtained from large-scale, non-overlapping GWASs in individuals of European ancestry. Bidirectional analyses were performed: one with macronutrients as exposures and one with MDD/cortisol as exposures. Random-effects inverse-variance weighted regression was used as the primary analytic method for genetic instruments with at least two single nucleotide polymorphisms (SNPs) available (and individual Wald ratio was used when only one SNP was available). Higher levels of genetically predicted relative sugar intake were causally associated with lower MDD risk, for both genome-wide significant p-value threshold of p < 1 × 10−8, (OR = 0.553, 95% CI: 0.395-0.775) and relaxed p-value threshold of p < 1 × 10−6 (OR = 0.786, 95% CI: 0.630–0.981). No reverse causality was detected in the opposite direction as MDD was not associated with sugar consumption. The associations observed for all the other pairs of variables were weak and imprecise. A number of limitations was present in the study, such as low-SNP based heritability for some exposures, inability to prove whether variants were correlated with unmeasured confounders and self-reporting of MDD data. Lifestyle and/or pharmacological interventions targeting sugar-related physiological mechanisms may help to reduce depressive symptoms. However, more research is necessary on short- and long-term effects of sugar on the risk of MDD. Additionally, future studies should investigate whether the amount and type of sugar consumed may underlie the impact of sugar on mood and stress levels.

No Evidence That Vitamin D Levels or Deficiency Are Associated with the Risk of Open-Angle Glaucoma in Individuals of European Ancestry: A Mendelian Randomisation Analysis.

Glaucoma is the second leading cause of blindness worldwide, with intraocular pressure as the only known modifiable risk factor. Vitamin D has been proposed to influence intraocular pressure and decrease retinal ganglion cell degeneration. Based on these findings, vitamin D has been suggested to prevent or reduce the severity of primary open-angle glaucoma (POAG), which is the most common form. We applied two-sample Mendelian randomisation (MR) analyses to data from the SUNLIGHT consortium and the UK Biobank to assess the causal effect of vitamin D levels and vitamin D deficiency on primary open-angle glaucoma (POAG). MR analysis, including sensitivity tests using other GWAS summary statistics from FinnGen, was also performed. We also investigated the association between single nucleotide polymorphisms (SNPs) on genes involved in vitamin D metabolic pathways and POAG. We found no statistical evidence that vitamin D levels (OR = 1.146, 95% CI 0.873 to 1.504, p = 0.326) or vitamin D deficiency (OR = 0.980 (95% CI 0.928 to 1.036, p = 0.471) causally affect the risk of developing POAG. Sensitivity analyses, including the use of a more relaxed p-value threshold, and use of winter-measured samples only, replication in the FinnGen dataset, and exploration of specific genetic markers also showed no evidence of association between SNPs for genes involved in key steps of vitamin D metabolism and POAG. These results indicate that vitamin D may not be a significant factor in modifying POAG risk, challenging the hypothesis that vitamin D supplementation could be effective in reducing POAG risk. Further research should focus on identifying other potential risk factors for POAG prevention strategies.

Stochastic parabolic growth promotes coexistence and a relaxed error threshold in RNA-like replicator populations

The RNA world hypothesis proposes that during the early evolution of life, primordial genomes of the first self-propagating evolutionary units existed in the form of RNA-like polymers. Autonomous, non-enzymatic, and sustained replication of such information carriers presents a problem, because product formation and hybridization between template and copy strands reduces replication speed. Kinetics of growth is then parabolic with the benefit of entailing competitive coexistence, thereby maintaining diversity. Here, we test the information-maintaining ability of parabolic growth in stochastic multispecies population models under the constraints of constant total population size and chemostat conditions. We find that large population sizes and small differences in the replication rates favor the stable coexistence of the vast majority of replicator species (‘genes’), while the error threshold problem is alleviated relative to exponential amplification. In addition, sequence properties (GC content) and the strength of resource competition mediated by the rate of resource inflow determine the number of coexisting variants, suggesting that fluctuations in building block availability favored repeated cycles of exploration and exploitation. Stochastic parabolic growth could thus have played a pivotal role in preserving viable sequences generated by random abiotic synthesis and providing diverse genetic raw material to the early evolution of functional ribozymes.

Stochastic parabolic growth promotes coexistence and a relaxed error threshold in RNA-like replicator populations.

The RNA world hypothesis proposes that during the early evolution of life, primordial genomes of the first self-propagating evolutionary units existed in the form of RNA-like polymers. Autonomous, non-enzymatic, and sustained replication of such information carriers presents a problem, because product formation and hybridization between template and copy strands reduces replication speed. Kinetics of growth is then parabolic with the benefit of entailing competitive coexistence, thereby maintaining diversity. Here, we test the information-maintaining ability of parabolic growth in stochastic multispecies population models under the constraints of constant total population size and chemostat conditions. We find that large population sizes and small differences in the replication rates favor the stable coexistence of the vast majority of replicator species ('genes'), while the error threshold problem is alleviated relative to exponential amplification. In addition, sequence properties (GC content) and the strength of resource competition mediated by the rate of resource inflow determine the number of coexisting variants, suggesting that fluctuations in building block availability favored repeated cycles of exploration and exploitation. Stochastic parabolic growth could thus have played a pivotal role in preserving viable sequences generated by random abiotic synthesis and providing diverse genetic raw material to the early evolution of functional ribozymes.

Examining the causal relationship between circulating immune cells and the susceptibility to osteomyelitis: A Mendelian randomization study

BackgroundOsteomyelitis is considered as a deleterious inflammatory condition affecting the bone, primarily attributed to pathogenic infection. However, the underlying factors predisposing individuals to osteomyelitis remain incompletely elucidated. The immune system plays a multifaceted role in the progression of this condition, yet previous observational studies and randomized controlled trials investigating the association between circulating immune cell counts and osteomyelitis have been constrained. In order to address this knowledge gap, we conducted a Mendelian randomization (MR) analysis to evaluate the impact of diverse immune cell counts on the risk of developing osteomyelitis. MethodsIn our study, we utilized single nucleotide polymorphisms (SNPs) that have been strongly linked to circulating immune cells or specific lymphocyte subtypes, as identified in large-scale genome-wide association studies (GWAS). These SNPs served as instrumental variables (IVs) for our MR analysis. We employed a more relaxed clumping threshold to conduct MR analysis on several related lymphocyte subtypes. To estimate causal effects, we utilized the Wald ratio, as well as the random-effects inverse variance weighted (IVW) and weighted median (WM) methods. To enhance the credibility of our results, we performed F-statistic calculations and a series of sensitivity analyses. ResultsOur findings revealed a significant correlation between the absolute count of circulating lymphocytes and the risk of osteomyelitis [odds ratio(OR) 1.20；95 % confidence interval (CI), 1.08–1.32；P = 0.0005]. Furthermore, we identified a causal relationship between the absolute count of CD8+ T cells and susceptibility to osteomyelitis (OR 1.16; 95 % CI, 1.04–1.30; P = 0.0098). Importantly, these findings remained robust across a wide range of sensitivity analyses. ConclusionThrough our MR analysis, we have provided evidence supporting a causal relationship between genetic predisposition to higher circulating immune cell counts and an increased risk of osteomyelitis. Specifically, our findings highlight the association between elevated CD8+ T cell counts and a heightened susceptibility to osteomyelitis. These results offer valuable insights for the future exploration of immunotherapy approaches in the management of osteomyelitis.

Assessing the causal relationship between 731 immunophenotypes and the risk of lung cancer: a bidirectional mendelian randomization study

BackgroundPrevious studies have observed a link between immunophenotypes and lung cancer, both of which are closely associated with genetic factors. However, the causal relationship between them remains unclear.MethodsBidirectional Mendelian randomization (MR) was performed on publicly available genome-wide association study (GWAS) summary statistics to analyze the causal relationships between 731 immunophenotypes and lung cancer. Sensitivity analyses were conducted to verify the robustness, heterogeneity, and potential horizontal pleiotropy of our findings.ResultsFollowing Bonferroni adjustment, CD14− CD16+ monocyte (OR = 0.930, 95%CI 0.900–0.960, P = 8.648 × 10− 6, PBonferroni = 0.006) and CD27 on CD24+ CD27+ B cells (OR = 1.036, 95%CI 1.020–1.053, P = 1.595 × 10 − 5, PBonferroni = 0.012) were identified as having a causal role in lung cancer via the inverse variance weighted (IVW) method. At a more relaxed threshold, CD27 on IgD+ CD24+ B cell (OR = 1.035, 95%CI 1.017–1.053, P = 8.666 × 10− 5, PBonferroni = 0.063) and CD27 on switched memory B cell (OR = 1.037, 95%CI 1.018–1.056, P = 1.154 × 10− 4, PBonferroni = 0.084) were further identified. No statistically significant effects of lung cancer on immunophenotypes were found.ConclusionsThe elevated level of CD14− CD16+ monocytes was a protective factor against lung cancer. Conversely, CD27 on CD24+ CD27+ B cell was a risk factor. CD27 on class-switched memory B cells and IgD+ CD24+ B cells were potential risk factors for lung cancer. This research enhanced our comprehension of the interplay between immune responses and lung cancer risk. Additionally, these findings offer valuable perspectives for the development of immunologically oriented therapeutic strategies.

Genetically predicted osteoprotegerin levels and the risk of cardiovascular diseases: A Mendelian randomization study

PurposeThe relationship between circulating osteoprotegerin (OPG) levels and the risk of cardiovascular diseases (CVDs) has been the subject of conflicting results in previous observational and experimental studies. To assess the causal effect of genetically predicted OPG levels on the risk of a wide range of CVDs, we used the Mendelian randomization design. DesignWe initially extracted information of genetic variants on OPG levels and their corresponding effect values from the summary data based on the European ancestry genome-wide association study. Subsequently, we performed two-sample Mendelian randomization analyses to assess the causal effect of genetically predicted OPG levels on CVDs by using inverse variance weighting (IVW), MR-Egger, weighted median, and MR-PRESSO methods. We also conducted sensitivity analyzes as well as complementary analyses with a more relaxed threshold for the exposure genetic instrumental variable (P < 5 × 10−6) to test the robustness of our results. ResultsOur results indicated that genetically predicted OPG levels causally reduce the risk of atrial fibrillation (IVW OR = 0.84; 95% CI = 0.72–0.98; P = 0.0241), myocardial infarction(IVW OR = 0.89; 95% CI = 0.80–0.98; P = 0.0173) and coronary heart disease (IVW: OR = 0.90; 95% CI = 0.82–0.99; P = 0.0286). Further complementary analyses also confirmed the above results remain robust and we also identified a potential causal association of OPG levels with a reduced risk of hypertensive diseases(IVW OR = 0.94;95% CI = 0.88–1.00; P = 0.0394). ConclusionThis study provides compelling evidence for a causal relationship between genetically predicted OPG levels and risk reduction of coronary heart disease, myocardial infarction, and atrial fibrillation, indicating that OPG could potentially serve as a cardiovascular risk marker in clinical practice.

Sex‐specific DNA methylation differences associated with Alzheimer’s disease

AbstractBackgroundSex has increasingly been recognized as an important factor contributing to the heterogeneity in Alzheimer’s disease (AD).MethodWe performed a sex‐specific meta‐analysis of two large epigenome‐wide association studies (ADNI, AIBL) in the blood, with a total of 633 and 651 samples in females and males, respecitively. For each dataset, we adjusted covariate variables age, sex, batch, and immune cell‐type proportions. The Inverse‐variance fixed‐effects meta‐analysis model was then used to prioritize the most consistent DNAm differences across datasets.ResultIn female samples, 2 CpGs, mapped to the PRRC2A and RPS8 genes, reached the 5% false discovery rate (FDR). No CpGs reached 5% FDR in male samples analysis. At a more relaxed significance threshold of P &lt; 1×10−5, an additional 22 CpGs and 5 CpGs were identified in female samples and male samples, respectively. For these 29 AD‐associated CpGs, the odds ratios ranged from 0.843 to 1.335 in females and 0.993 to 1.058 in males. The majority of these CpGs were hypermethylated in AD subjects (23 CpGs), located outside CpG islands or shores (27 CpGs), or in distal regions located greater than 2k bp from the TSS (27 CpGs). Only 2 of these 29 CpGs were located in gene promoters at SLC5A8 and C16orf89.At 5% Sidak corrected P‐value, our DMR analysis using comb‐p software identified 49 distinct differentially methylated regions (DMRs) in female and male samples each. The median numbers of CpGs in these DMRs are 5 CpGs in females and 4 CpGs in males. Among the top 10 most significant DMRs, about half of them (6 in females, 5 in males) were hypermethylated in AD. In females, 5 out of the 10 DMRs were mapped to promoter regions of the NNAT, CCDC169‐SOHLH2, ARHGEF15, LPAR5, and ZNF595 genes. In males, 4 out of the 10 DMRs were mapped to promoter regions of the MCCC1, PM20D1, PRR19, TTC23, and LRRC28 genes.ConclusionAs sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding AD pathophysiology. They also provide a valuable resource for sex‐specific biomarkers and drug targets in AD.

A Genome-Wide Association Study of Dementia Using the Electronic Medical Record

Dementia is characterized as a decline in cognitive function, including memory, language and problem-solving abilities. In this paper, we conducted a Genome-Wide Association Study (GWAS) using data from the electronic Medical Records and Genomics (eMERGE) network. This study has two aims, (1) to investigate the genetic mechanism of dementia and (2) to discuss multiple p-value thresholds used to address multiple testing issues. Using the genome-wide significant threshold (p≤5×10−8), we identified four SNPs. Controlling the False Positive Rate (FDR) level below 0.05 leads to one extra SNP. Five SNPs that we found are also supported by QQ-plot comparing observed p-values with expected p-values. All these five SNPs belong to the TOMM40 gene on chromosome 19. Other published studies independently validate the relationship between TOMM40 and dementia. Some published studies use a relaxed threshold (p≤1×10−5) to discover SNPs when the statistical power is insufficient. This relaxed threshold is more powerful but cannot properly control false positives in multiple testing. We identified 13 SNPs using this threshold, which led to the discovery of extra genes (such as ATP10A-DT and PTPRM). Other published studies reported these genes as related to brain development or neuro-development, indicating these genes are potential novel genes for dementia. Those novel potential loci and genes may help identify targets for developing new therapies. However, we suggest using them with caution since they are discovered without proper false positive control.

Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy

Selective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood. In utero exposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression. Chorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score > 8 to indicate symptomatic depressed mood (“maternally-depressed”), and we further classified cases into SSRI-exposed, maternally-depressed (n = 14); SSRI-exposed, not maternally-depressed (n = 6); SSRI non-exposed, maternally-depressed (n = 20); and SSRI non-exposed, not maternally-depressed (n = 24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n = 17 SSRI-exposed, n = 17 SSRI non-exposed). No CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δβ| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n = 31; males n = 33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off. We did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment, as compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.

Joint Optimization Algorithm for Small Base Station States Control and User Association in Wireless Caching Networks

The energy consumption management of small base stations (SBSs) in wireless caching networks with dense deployment of SBSs is an urgent problem to be solved. This paper jointly optimizes the SBS state control and user association problems in caching networks to reduce network energy consumption while taking into account the average service latency of the network to ensure user experience. First, a new definition of three-state SBSs in caching networks is proposed based on their ability to keep content cache updated. Then, a relaxed threshold setting method is designed and the SBS traffic prediction is used to obtain the initial state information of SBSs in the next period. In order to eliminate the impact on the accessing users when the switched-off base station (BS) wakes up, a SBS state asynchronous switching mechanism is proposed to ensure that the users who switch to the waking SBS can carry out communication services normally, and a user association strategy is constructed with the SBS load as the optimization target. Finally, a joint optimization model of user association and SBS state control (SSC-UA) is constructed to admit and correct the initial state of SBSs to maximize the system gain and obtain the final state strategy for each SBS in the next period. The simulation results show that the proposed SSC-UA algorithm can effectively improve the energy efficiency and reduce the network service delay at the same time.

Multiscale contrast enhancement method for small infrared target detection

Infrared search and track (IRST) systems have been applied extensively in the civil and military fields. However, fast, effective, and robust dim and small infrared target detection remains a challenging research topic. Dim and small targets are easily obscured in different backgrounds or noises, which results in a high false alarm rate. A novel strategy is proposed for small infrared target detection to achieve a high true positive rate and robust detection. First, the prominent edge structures of the original image are obtained by constructing a structure tensor. Subsequently, a Gaussian bandpass filter with multiscale windows is used to obtain an infrared image that contains complex edges and small targets. An infrared image with an enhanced signal-to-clutter ratio is achieved by combining with the two methods, whereby the noise can be effectively reduced. Thereafter, candidate regions that contain the target and a smaller number of edges with higher brightness than that of the target are obtained using relaxed threshold segmentation. Finally, a Gaussian gradient contrast method is proposed in which the highlighted edges are removed so that only small infrared targets remain. Extensive experimental results demonstrate that the proposed method can achieve a significant optimization of the true positive and false alarm rates, as well as improved efficiency and robustness.

Expression complementation of gene presence/absence polymorphisms in hybrids contributes importantly to heterosis in sunflower

IntroductionNumerous crops have transitioned to hybrid seed production to increase yields and yield stability through heterosis. However, the molecular mechanisms underlying heterosis and its stability across environments are not yet fully understood. ObjectivesThis study aimed to (1) elucidate the genetic and molecular mechanisms underlying heterosis in sunflower, and (2) determine how heterosis is maintained under different environments. MethodsGenome-wide association (GWA) analyses were employed to assess the effects of presence/absence variants (PAVs) and stop codons on 16 traits phenotyped in the sunflower association mapping population at three locations. To link the GWA results to transcriptomic variation, we sequenced the transcriptomes of two sunflower cultivars and their F1 hybrid (INEDI) under both control and drought conditions and analyzed patterns of gene expression and alternative splicing. ResultsThousands of PAVs were found to affect phenotypic variation using a relaxed significance threshold, and at most such loci the “absence” allele reduced values of heterotic traits, but not those of non-heterotic traits. This pattern was strengthened for PAVs that showed expression complementation in INEDI. Stop codons were much rarer than PAVs and less likely to reduce heterotic trait values. Hybrid expression patterns were enriched for the GO category, sensitivity to stimulus, but all genotypes responded to drought similarily – by up-regulating water stress response pathways and down-regulating metabolic pathways. Changes in alternative splicing were strongly negatively correlated with expression variation, implying that alternative splicing in this system largely acts to reinforce expression responses. ConclusionOur results imply that complementation of expression of PAVs in hybrids is a major contributor to heterosis in sunflower, consistent with the dominance model of heterosis. This mechanism can account for yield stability across different environments. Moreover, given the much larger numbers of PAVs in plant vs. animal genomes, it also offers an explanation for the stronger heterotic responses seen in the former.

Joining forces in Ochnaceae phylogenomics: a tale of two targeted sequencing probe kits.

Both universal and family-specific targeted sequencing probe kits are becoming widely used for reconstruction of phylogenetic relationships in angiosperms. Within the pantropical Ochnaceae, we show that with careful data filtering, universal kits are equally as capable in resolving intergeneric relationships as custom probe kits. Furthermore, we show the strength in combining data from both kits to mitigate bias and provide a more robust result to resolve evolutionary relationships. We sampled 23 Ochnaceae genera and used targeted sequencing with two probe kits, the universal Angiosperms353 kit and a family-specific kit. We used maximum likelihood inference with a concatenated matrix of loci and multispecies-coalescence approaches to infer relationships in the family. We explored phylogenetic informativeness and the impact of missing data on resolution and tree support. For the Angiosperms353 data set, the concatenation approach provided results more congruent with those of the Ochnaceae-specific data set. Filtering missing data was most impactful on the Angiosperms353 data set, with a relaxed threshold being the optimum scenario. The Ochnaceae-specific data set resolved consistent topologies using both inference methods, and no major improvements were obtained after data filtering. Merging of data obtained with the two kits resulted in a well-supported phylogenetic tree. The Angiosperms353 data set improved upon data filtering, and missing data played an important role in phylogenetic reconstruction. The Angiosperms353 data set resolved the phylogenetic backbone of Ochnaceae as equally well as the family specific data set. All analyses indicated that both Sauvagesia L. and Campylospermum Tiegh. as currently circumscribed are polyphyletic and require revised delimitation.

Association of Autism Spectrum Disorder, Neuroticism, and Subjective Well-Being With Cardiovascular Diseases: A Two-Sample Mendelian Randomization Study.

Background: Previous observational studies have reported an association between psychiatric traits and cardiovascular diseases (CVDs). In this two-sample Mendelian randomization (MR) study, we aimed to investigate the causality between psychiatric traits and CVDs.Methods: Single-nucleotide polymorphisms (SNPs) associated with autism spectrum disorder (ASD), neuroticism, and subjective well-being at genome-wide significance (P < 1 × 10−8) were identified from genome-wide association studies. Summary-level data of the outcomes, including coronary artery disease (CAD), myocardial infarction (MI), atrial fibrillation (AF), and heart failure (HF), were obtained from several largest datasets. The inverse-variance weighted (IVW) method was used as our main analyses to conduct this MR study. Sensitivity analyses included the weighted median, the MR-robust adjusted profile score (MR-RAPS), and the MR pleiotropy residual sum and outlier (MR-PRESSO) method. Repeated MR analyses using a more relaxed threshold (P < 1 × 10−6) for instruments selection and multivariable MR analyses were also applied to evaluate the robustness of results.Results: The MR analyses showed that genetic predisposition to ASD was associated with a higher risk of AF [odds ratio (OR), 1.109; 95% confidence interval (CI), 1.023–1.201; P = 0.011] and HF (OR, 1.138; 95% CI, 1.036–1.251; P = 0.007). Neuroticism was casually associated with an increased risk of AF (OR, 1.201; 95% CI, 1.037–1.392; P = 0.015), whereas subjective well-being had a protective effect on HF (OR, 0.732; 95% CI, 0.574–0.933; P = 0.012). No other causal association between psychiatric traits and CVDs was observed. Consistent results were obtained in sensitivity analyses.Conclusion: This study provided evidence of causal associations of ASD with a higher risk of AF and HF. Besides, neuroticism was casually associated with an increased risk of AF, and subjective well-being was associated with a decreased risk of HF.

Brain structural plasticity in visual and sensorimotor areas of airline pilots: A voxel-based morphometric study

Background and Purpose: Airline pilot is a highly specialized profession that requires to response quickly and accurately in the presence of a wide variety of visual information. Although functional imaging studies have employed virtual simulation to identify brain areas that underlie various flying-related tasks, little is known about the specific patterns of structural plasticity in the airline pilot’s brain. Materials and MethodsIn this study, we examined differences of gray matter and white matter volumes between 42 airline pilots and 39 non-pilots by using voxel-based morphometry, and further assessed the association between magnitude of structural alterations and flight time in the pilots. ResultsWe found significantly increased white matter volume in the cuneus area in the pilot group compared to the non-pilot group (p < 0.05, FWE corrected). Using a relaxed threshold, it was also observed that the pilots had increased gray matter volume in the lingual gyrus, inferior frontal gyrus, supramarginal gyrus, cuneus, and postcentral gyrus, and increased white matter volume in the postcentral area (p < 0.001, uncorrected). Moreover, the pilots’ flight time was positively correlated with gray matter volume in the postcentral gyrus and white matter volume in the cuneus area (p < 0.001, uncorrected). ConclusionsThe morphological changes in specific visual and sensorimotor areas may provide airline pilots with neural efficiency in the visuo-motor processing related to flight.

Support for an inhibitory model of word retrieval

Word retrieval may involve an inhibitory process in which a target word is activated and related words are suppressed. In the current functional magnetic resonance imaging (fMRI) study, we examined the inhibition of language processing cortex by the left dorsolateral prefrontal cortex (DLPFC) during word retrieval using an anagram-solving paradigm. Participants were presented with a distractor that was read aloud followed by a to-be-solved anagram. Distractor types were defined relative to orthographic overlap with the subsequent anagram solution and included related words with one letter different (e.g., “gripe” for the anagram of “price”), related pseudo-words, and unrelated words (i.e., all five letters were different). The anagram solution reaction time was slower in both the related word and related pseudo-word distractor conditions as compared to the unrelated word distractor condition, which can be attributed to greater inhibition following related distractors. The contrast of related words and unrelated words produced one activation in the left DLPFC, a region that has been associated with memory inhibition. To identify the regions that were negatively correlated with activity in the left DLPFC for related distractors, we conducted a functional connectivity analysis between this left DLPFC region and the rest of the brain. We found negatively correlated activity between the DLPFC and language processing cortex for the related word distractor condition (and the related pseudo-word distractor condition at a relaxed threshold). These findings suggest that that the left DLPFC may inhibit related word (and pseudo-word) representations in language processing cortex.

Epigenome-wide study of brain DNA methylation following acute opioid intoxication

BackgroundOpioid abuse poses significant risk to individuals in the United States and epigenetic changes are a leading potential biomarker of opioid abuse. Current evidence, however, is mostly limited to candidate gene analysis in whole blood. To clarify the association between opioid abuse and DNA methylation, we conducted an epigenome-wide analysis of DNA methylation in brain samples of individuals who died from acute opioid intoxication and group-matched controls. MethodsTissue samples were extracted from the dorsolateral prefrontal cortex of 153 deceased individuals (Mage = 35.42; 62 % male; 77 % European ancestry). The study included 72 opioid samples, 53 psychiatric controls, and 28 normal controls. The epigenome-wide analysis was implemented using the Illumina MethylationEPIC BeadChip; analyses adjusted for sociodemographic characteristics, negative control principal components, ancestry principal components, cellular composition, and surrogate variables. Horvath’s epigenetic age and Levine’s PhenoAge were calculated, and gene set enrichment analyses were performed. ResultsAlthough no CpG sites survived false-discovery rate correction for multiple testing, 13 sites surpassed a relaxed significance threshold (p < 1.0 × 10−5). One of these sites was located within Netrin-1, a gene implicated in kappa opioid receptor activity. There was an association between opioid use and accelerated PhenoAge (b = 2.24, se = 1.11, p = .045). Gene set enrichment analyses revealed enrichment of differential methylation in GO and KEGG pathways broadly related to substance use. ConclusionsNetrin-1 may be associated with opioid overdose, and future research with larger samples across stages of opioid use will elucidate the complex genomics of opioid abuse.