Continuous Traits Research Articles

Evoked and transmitted culture models: Using bayesian methods to infer the evolution of cultural traits in history.

A central question in behavioral and social sciences is understanding to what extent cultural traits are inherited from previous generations, transmitted from adjacent populations or produced in response to changes in socioeconomic and ecological conditions. As quantitative diachronic databases recording the evolution of cultural artifacts over many generations are becoming more common, there is a need for appropriate data-driven methods to approach this question. Here we present a new Bayesian method to infer the dynamics of cultural traits in a diachronic dataset. Our method called Evoked-Transmitted Cultural model (ETC) relies on fitting a latent-state model where a cultural trait is a latent variable which guides the production of the cultural artifacts observed in the database. The dynamics of this cultural trait may depend on the value of the cultural traits present in previous generations and in adjacent populations (transmitted culture) and/or on ecological factors (evoked culture). We show how ETC models can be fitted to quantitative diachronic or synchronic datasets, using the Expectation-Maximization algorithm, enabling estimating the relative contribution of vertical transmission, horizontal transmission and evoked component in shaping cultural traits. The method also allows to reconstruct the dynamics of cultural traits in different regions. We tested the performance of the method on synthetic data for two variants of the method (for binary or continuous traits). We found that both variants allow reliable estimates of parameters guiding cultural evolution, and that they outperform purely phylogenetic tools that ignore horizontal transmission and ecological factors. Overall, our method opens new possibilities to reconstruct how culture is shaped from quantitative data, with possible application in cultural history, cultural anthropology, archaeology, historical linguistics and behavioral ecology.

A genome-wide epistatic network underlies the molecular architecture of continuous color variation of body extremities

Deciphering the molecular architecture of coat coloration for a better understanding of the biological mechanisms underlying pigmentation still remains a challenge. We took advantage of a rabbit French experimental population in which both a pattern and a gradient of coloration from white to brown segregated within the himalayan phenotype. The whole experimental design was genotyped using the high density Affymetrix® AxiomOrcun™ SNP Array and phenotyped into 6 different groups ordered from the lighter to the darker. Genome-wide association analyses pinpointed an oligogenic determinism, under recessive and additive inheritance, involving genes already known in melanogenesis (ASIP, KIT, MC1R, TYR), and likely processed pseudogenes linked to ribosomal function, RPS20 and RPS14. We also identified (i) gene-gene interactions through ASIP:MC1R affecting light cream/beige phenotypes while KIT:RPS responsible of dark chocolate/brown colors and (ii) a genome-wide epistatic network involving several others coloration genes such as POT1 or HPS5. Finally, we determined the recessive inheritance of the English spotting phenotype likely involving a copy number variation affecting at least the end of the coding sequence of the KIT gene. Our analyses of coloration as a continuous trait allowed us to go beyond much of the established knowledge through the detection of additional genes and gene-gene interactions that may contribute to the molecular architecture of the coloration phenotype.

MiRKAT-MC: A Distance-Based Microbiome Kernel Association Test With Multi-Categorical Outcomes.

Increasing evidence has elucidated that the microbiome plays a critical role in many human diseases. Apart from continuous and binary traits that measure the extent or presence of a disease, multi-categorical outcomes including variations/subtypes of a disease or ordinal levels of disease severity are commonly seen in clinical studies. On top of that, studies with clustered design (i.e., family-based and longitudinal studies) are popular alternatives to population-based ones as they are able to identify characteristics on both individual and population levels and to investigate the trajectory of traits of interest over time. However, existing methods for microbiome association analysis are inadequate to handle multi-categorical outcomes, neither independent nor clustered data. We propose a microbiome kernel association test with multi-categorical outcomes (MiRKAT-MC). Our method is versatile to deal with both nominal and ordinal outcomes for independent and clustered data. In addition, it incorporates multiple ecological distances to allow for different association patterns between outcomes and microbiome compositions to be incorporated. A computationally efficient pseudo-permutation strategy is used to evaluate the statistical significance. Comprehensive simulations show that MiRKAT-MC preserves the nominal type I error and increases statistical powers under various scenarios and data types. We also apply MiRKAT-MC to real data sets with nominal and ordinal outcomes to gain biological insights. MiRKAT-MC is easy to implement, and freely available via an R package at https://github.com/Zhiwen-Owen-Jiang/MiRKATMC with a Graphical User Interface through R Shinny also available.

Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries

SummarySince 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals because of various confounding challenges. Here, we demonstrate that enrichment analyses that aggregate SNP-level association statistics at multiple genomic scales—from genes to genomic regions and pathways—have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts.

Examining differentiation of sympatricSchizothoraxfishes reveals low differentiation in internal compared to external feeding traits

AbstractIn the process of sympatric species differentiation, which feeding traits are most differentiated? The complete feeding process of capture, ingestion, and digestion requires certain external, as well as internal traits. Therefore, comprehensive comparisons are needed to study fish feeding habits. This study systematically investigated the adaptive radiation and parallel evolution ofSchizothoraxfishes, and quantified the external, frame, pharyngeal bone, and digestive traits of the systematically differentiated omnivorousSchizothorax davidiand herbivorousS. wangchiachii. A member of their sister genus, the carnivorousPercocypris pingi, was used as an outgroup control to explore the feeding differentiation of sympatricSchizothoraxfishes. The results showed that these species had highly differentiated external traits, while the internal traits (pharyngeal bone and digestive traits) showed low differentiation, indicating that predatory traits diverged first in the differentiation of sympatricSchizothoraxfishes, while chewing and digestive traits were slower to diverge. Furthermore, we screened 16 continuous feeding traits, and the quantified values of these traits progressively increased or decreased with increasing nutritional level of food. These findings provide a reference for the selection of quantitative indicators in future studies of sympatric species differentiation.

Multi-Omics Characterization of Early- and Adult-Onset Major Depressive Disorder.

Age at depressive onset (AAO) corresponds to unique symptomatology and clinical outcomes. Integration of genome-wide association study (GWAS) results with additional “omic” measures to evaluate AAO has not been reported and may reveal novel markers of susceptibility and/or resistance to major depressive disorder (MDD). To address this gap, we integrated genomics with metabolomics using data-driven network analysis to characterize and differentiate MDD based on AAO. This study first performed two GWAS for AAO as a continuous trait in (a) 486 adults from the Pharmacogenomic Research Network-Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS), and (b) 295 adults from the Combining Medications to Enhance Depression Outcomes (CO-MED) study. Variants from top signals were integrated with 153 p180-assayed metabolites to establish multi-omics network characterizations of early (<age 18) and adult-onset depression. The most significant variant (p = 8.77 × 10−8) localized to an intron of SAMD3. In silico functional annotation of top signals (p < 1 × 10−5) demonstrated gene expression enrichment in the brain and during embryonic development. Network analysis identified differential associations between four variants (in/near INTU, FAT1, CNTN6, and TM9SF2) and plasma metabolites (phosphatidylcholines, carnitines, biogenic amines, and amino acids) in early- compared with adult-onset MDD. Multi-omics integration identified differential biosignatures of early- and adult-onset MDD. These biosignatures call for future studies to follow participants from childhood through adulthood and collect repeated -omics and neuroimaging measures to validate and deeply characterize the biomarkers of susceptibility and/or resistance to MDD development.

The individual and global impact of copy-number variants on complex human traits

SummaryThe impact of copy-number variations (CNVs) on complex human traits remains understudied. We called CNVs in 331,522 UK Biobank participants and performed genome-wide association studies (GWASs) between the copy number of CNV-proxy probes and 57 continuous traits, revealing 131 signals spanning 47 phenotypes. Our analysis recapitulated well-known associations (e.g., 1q21 and height), revealed the pleiotropy of recurrent CNVs (e.g., 26 and 16 traits for 16p11.2-BP4-BP5 and 22q11.21, respectively), and suggested gene functionalities (e.g., MARF1 in female reproduction). Forty-eight CNV signals (38%) overlapped with single-nucleotide polymorphism (SNP)-GWASs signals for the same trait. For instance, deletion of PDZK1, which encodes a urate transporter scaffold protein, decreased serum urate levels, while deletion of RHD, which encodes the Rhesus blood group D antigen, associated with hematological traits. Other signals overlapped Mendelian disorder regions, suggesting variable expressivity and broad impact of these loci, as illustrated by signals mapping to Rotor syndrome (SLCO1B1/3), renal cysts and diabetes syndrome (HNF1B), or Charcot-Marie-Tooth (PMP22) loci. Total CNV burden negatively impacted 35 traits, leading to increased adiposity, liver/kidney damage, and decreased intelligence and physical capacity. Thirty traits remained burden associated after correcting for CNV-GWAS signals, pointing to a polygenic CNV architecture. The burden negatively correlated with socio-economic indicators, parental lifespan, and age (survivorship proxy), suggesting a contribution to decreased longevity. Together, our results showcase how studying CNVs can expand biological insights, emphasizing the critical role of this mutational class in shaping human traits and arguing in favor of a continuum between Mendelian and complex diseases.

Phylogenetic signal and evolutionary relationships among traits of inland fishes along elevational and longitudinal gradients

AbstractUnderstanding the main drivers of species distributions is one of the main goals of ecology. However, the relationships between traits and elevational and longitudinal distributions in inland fishes, as well as their underlying evolutionary processes, have been less investigated. Thus, we aimed to quantify and assess the relationships among several types of traits resulting from species’ evolutionary histories by measuring their phylogenetic signal across inland fishes of the Iberian Peninsula. We also aimed to test for correlated evolution of these traits with elevation and stream size (i.e. stream order), to test whether a species’ suite of traits and their elevational and longitudinal niche tend to evolve together.We compiled data on 23 fish biological and ecological traits for 30 inland fish species present in the Iberian Peninsula. We quantified their phylogenetic signal using four complementary indices (Pagel’sλ, Blomberg’sK, and Abouheif’sCmeanfor continuous and −D + 1 for binary traits). We used both phylogenetic and non‐phylogenetic methods to evaluate the relationship among traits and their relationship with elevation and stream order.We found a significant phylogenetic signal for 65% of the studied traits. Phylogenetic signals were quite variable, but we did not detect clear differences between continuous and binary traits or among trait types (i.e. morphological, trophic, reproductive, and habitat use). Evolutionary models revealed that elevational and longitudinal distribution showed little evidence for directional trends of evolution. Hence, species elevational and longitudinal niches tend to resemble to those of the common ancestor.Many fish traits were inter‐correlated as revealed by phylogenetic methods, indicating correlated evolution of pairs of traits. For example, reproductive traits such as maximum longevity, fecundity and age at maturity tended to evolve together with fish maximum length. Consequently, certain orders of fish showed shared suites of traits.Comparative methods revealed a significant positive relationship of parental care with elevation and stream order. By contrast, non‐phylogenetic analyses and multivariate analyses indicated positive relationships between elevation and rheophily and lithophily, and a negative relationship between stream order and invertivory and rheophily.Overall, our results point to a notable phylogenetic signal in many traits of inland fishes and a strong phylogenetic structure in their functional traits along their elevational and longitudinal gradients. Thereby, our results contribute to an improved understanding of species’ adaptations to environmental changes with important conceptual and practical implications for minimising further species losses.

Modeling Pulsed Evolution and Time-Independent Variation Improves the Confidence Level of Ancestral and Hidden State Predictions.

Ancestral state reconstruction is not only a fundamental tool for studying trait evolution, but also very useful for predicting the unknown trait values (hidden states) of extant species. A well-known problem in ancestral and hidden state predictions is that the uncertainty associated with predictions can be so large that predictions themselves are of little use. Therefore, for meaningful interpretation of predicted traits and hypothesis testing, it is prudent to accurately assess the uncertainty of the predictions. Commonly used constant-rate Brownian motion (BM) model fails to capture the complexity of tempo and mode of trait evolution in nature, making predictions under the BM model vulnerable to lack-of-fit errors from model misspecification. Using empirical data (mammalian body size and bacterial genome size), we show that the distribution of residual Z-scores under the BM model is neither homoscedastic nor normal as expected. Consequently, the 95% confidence intervals of predicted traits are so unreliable that the actual coverage probability ranges from 33% (strongly permissive) to 100% (strongly conservative). Alternative methods such as BayesTraits and StableTraits that allow variable rates in evolution improve the predictions but are computationally expensive. Here, we develop Reconstructing Ancestral State under Pulsed Evolution in R by Gaussian Decomposition (RasperGade), a method of ancestral and hidden state prediction that uses the Levy process to explicitly model gradual evolution, pulsed evolution, and time-independent variation. Using the same empirical data, we show that RasperGade outperforms both BayesTraits and StableTraits in providing reliable confidence estimates and is orders-of-magnitude faster. Our results suggest that, when predicting the ancestral and hidden states of continuous traits, the rate variation should always be assessed and the quality of confidence estimates should always be examined. [Bacterial genomic traits; model misspecification; trait evolution.].

Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes

Aims/hypothesisType 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes.MethodsOur main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD.ResultsEight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%).Conclusions/interpretationMost traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual’s liability to type 2 diabetes.Graphical abstract

A striking color variation is detected in Poneratestacea Emery, 1895 (Hymenoptera, Formicidae) across its Western Palaearctic geographic range.

In this paper, we provide numeric morphology-based evidence that the dark-colored Poneracoarctatavar.lucida Emery, 1898, formerly considered a synonym of P.coarctata (Latreille, 1802), is conspecific with the lighter-colored Poneratestacea Emery, 1895. Species hypotheses are developed via NC-PART clustering, combined with Partitioning Algorithm based on Recursive Thresholding (PART), and via PCA combined with gap statistics. We obtained our results from an extensive dataset from the 10 continuous morphometric traits measured on 165 workers belonging to 73 nest samples. Linear discriminant analysis (LDA) confirmed the grouping of hypotheses generated by exploratory analyses with 100% classification success when all ten morphometric traits were involved. The Anatolian Turkish black and the predominantly European yellow samples, did not separate based on their morphometric characteristics. These two color variations broadly overlap in their geographic range in Anatolian Turkey. The investigated type series of Poneracoarctatavar.lucida Emery, 1898 (collected from Kazakhstan) fell within the P.testacea cluster instead of P.coarctata and is also classified with high certainty as P.testacea by confirmatory LDA. Therefore, we propose the synonymy of Poneracoarctatavar.lucida Emery, 1898 with Poneratestacea Emery, 1895. As no other morphological differences than color patterns were detected between the “black” and “pale” P.testacea samples, we hold that these populations constitute geographically occurring color variations of the same species. Finally, our quantitative morphology-based results show that relying on color patterns is not a robust approach in identifying European Ponera samples, particularly in the east, but using multivariate analyses of morphometric traits is advised instead.

Identification of genetic loci simultaneously associated with multiple cardiometabolic traits

Background and aimsCardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits. Methods and resultsWe conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N = 356,574–456,823). Multiple loci reached genome-wide levels of significance (N = 145–333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P < 5 × 10−8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses. GRB14-COBLL1 showed the most consistent replication, revealing nominally significant associations (P < 0.05) with all traits except DBP. ConclusionsOur analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.

Ergodic Behaviour of a Multi-Type Growth-Fragmentation Process Modelling the Mycelial Network of a Filamentous Fungus

In this work, we introduce a stochastic growth-fragmentation model for the expansion of the network of filaments, or mycelium, of a filamentous fungus. In this model, each individual is described by a discrete type 𝔢 ∈ {0,1} indicating whether the individual corresponds to an internal or terminal segment of filament, and a continuous trait x ≥ 0 corresponding to the length of this segment. The length of internal segments cannot grow, while the length of terminal segments increases at a deterministic speed v. Both types of individuals/segments branch according to a type-dependent mechanism. After constructing the stochastic bi-type growth-fragmentation process of interest, we analyse the corresponding mean measure (or first moment semigroup). We show that its ergodic behaviour is, as expected, governed by the maximal eigenelements. In the long run, the total mass of the mean measure increases exponentially fast while the type-dependent density in trait converges to an explicit distribution N, independent of the initial condition, at some exponential speed. We then obtain a law of large numbers that relates the long term behaviour of the stochastic process to the limiting distribution N. In the particular model we consider, which depends on only 3 parameters, all the quantities needed to describe this asymptotic behaviour are explicit, which paves the way for parameter inference based on data collected in lab experiments.

Genetics of T2DM and Its Chronic Complications: Are We Any Closer to the Individual Prediction of Genetic Risk?

Type 2 diabetes mellitus (T2DM) is a complex disease that has risen in global prevalence over recent decades, resulting in concomitant and enormous socio-economic impacts. In addition to the well-documented risk factors of obesity, poor dietary habits and sedentary lifestyles, genetic background plays a key role in the aetiopathogenesis of diabetes and the development of associated micro- and macro-vascular complications. Recent advances in genomic research, notably next-generation sequencing and genome-wide association studies, have greatly improved the efficiency with which genetic backgrounds to complex diseases are analysed. To date, several hundred single-nucleotide polymorphisms have been associated with T2DM or its complications. Given the polygenic background to T2DM (and numerous other complex diseases), the degree of genetic predisposition can be treated as a “continuous trait” quantified by a genetic risk score. Focusing mainly on the Central European population, this review summarizes recent state-of-the-art methods that have enabled us to better determine the genetic architecture of T2DM and the utility of genetic risk scores in disease prediction.

Long-term changes in the functional trait composition and diversity of fish assemblages in eastern plain lakes under the regime of river-lake connectivity loss

东部平原湖泊区是我国淡水湖泊最集中的地区，分布着我国的五大淡水湖等诸多湖泊.然而，江湖阻隔对该区域湖泊的生物多样性造成严重威胁.本文选取东部平原的9个湖泊，对江湖阻隔前后鱼类功能性状（3组分类性状和6个连续性状）和功能多样性指数的变化规律开展了研究.结果表明，9个湖泊的鱼类总物种数由江湖阻隔前的140种减少为江湖阻隔后的100种，平均物种数由79.6种减少到52.1种（减少34.4%）.江湖阻隔后鱼类群落的功能性状和功能多样性指数发生了显著变化，洄游性鱼类（包括河海洄游和江湖洄游）物种占比（由39.7%降至32.6%）和鱼食性物种占比（由31.1%降至25.2%）显著下降，而非洄游性物种占比（由60.3%升至67.5%）和浮游生物食性物种占比（由13.5%升至15.5%）显著上升.连续型性状中，平均营养级（由3.14降至3.10）显著下降、平均生长速率（由0.57 a^-1升至0.65 a^-1）显著上升.阻隔后的物种数（SR）、功能丰富度指数、功能离散度指数和功能分散指数显著低于阻隔前.本研究表明江湖阻隔后鱼类群落不仅物种丰富度下降，且功能性状趋向同质化（或单一化）发展，致使功能多样性下降.研究结果可为东部平原湖泊的渔业资源管理及湖区生态修复和保护提供重要的理论依据.;The eastern plain lake area is the most concentrated area of freshwater lakes in China, supporting numerous lakes, including China's five largest freshwater lakes. However, human activities such as disconnecting lakes from the mainstream are seriously threatening the aquatic biodiversity in the region. In this study, 9 lakes in the eastern plain were selected to study the temporal (before and after the river-lake disconnection) changes in functional traits (3 groups of categorical traits and 6 continuous traits) and functional diversity index of fish assemblages. The results showed that the total number of fish species across the 9 lakes decreased from 140 species to 100 species through time, and the average species richness per lake decreased from 79.6 to 52.1 (accounting for 34.4% of historical species). The functional trait composition and diversity indices of fish communities changed significantly before and after the river-lake disconnection. The percentages of migratory (from 39.7% to 32.6%) and piscivorous species (from 31.1% to 25.2%) significantly decreased, while the percentages of non-migratory (from 60.3% to 67.5%) and planktivorous species (from 13.5% to 15.5%) significantly increased. For the continuous traits, the average trophic level (from 3.14 to 3.10) significantly decreased but the average growth rate (from 0.57 a^-1 to 0.65 a^-1) significantly increased. Species richness, FRic, FDiv and FDis all significantly decreased. These results indicated that, after river-lake disconnection, fish assemblages experienced not only a decrease in species richness but also homogenization (or simplification) trend of functional trait composition and decline in functional diversity. Our study provided scientific background for the ecological protection and restoration of eastern plain lakes in China.

Genome and EnvironmentBased Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction.

Genomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includes extensive multienvironment and multiyear field trial data. Hence, genomic-enabled prediction models should include genotype × environment (G×E) interaction, which most of the time increases the prediction performance when the response of lines are different from environment to environment. In this chapter, we describe a historical timeline since 2012 related to advances of the GS models that take into account G×E interaction. We describe theoretical and practical aspects of those GS models, including the gains in prediction performance when including G×E structures for both complex continuous and categorical scale traits. Then, we detailed and explained the main G×E genomic prediction models for complex traits measured in continuous and noncontinuous (categorical) scale. Related to G×E interaction models this review also examine the analyses of the information generated with high-throughput phenotype data (phenomic) and the joint analyses of multitrait and multienvironment field trial data that is also employed in the general assessment of multitrait G×E interaction. The inclusion of nongenomic data in increasing the accuracy and biological reliability of the G×E approach is also outlined. We show the recent advances in large-scale envirotyping (enviromics), and how the use of mechanistic computational modeling can derive the crop growth and development aspects useful for predicting phenotypes and explaining G×E.

Assessing the causal relationships between gout and hypertension: a bidirectional Mendelian randomisation study with coarsened exposures

ObjectivesObservational studies have demonstrated associations between gout and hypertension, but whether they are causal remains unclear. Our work aims to assess the causal relationship between gout and hypertension.MethodsWe obtained genetic information from the Taiwan Biobank, including 88,347 participants and 686,439 single-nucleotide polymorphisms (SNPs). A novel model of Mendelian randomisation (MR) with coarsened exposures was used to examine the causality between the liability of gout on hypertension and vice versa, using 4 SNPs associated with gout and 10 SNPs associated with hypertension after removal of SNPs associated with measured confounders. The binary exposure (gout/hypertension) can be considered a coarsened approximation of a latent continuous trait. The inverse-variance weighted (IVW) and polygenic risk score (PRS) methods were used to estimate effect size. The MR analysis with coarsened exposures was performed with and without adjustments for covariates.ResultsOf the 88,347 participants, 3253 (3.68%) had gout and 11,948 (13.52%) had hypertension (men, 31.9%; mean age 51.1 [SD, 11.1] years). After adjusting to measured confounders, MR analysis with coarsened exposures showed a significant positive causal effect of the liability of gout on hypertension in both the IVW method (relative risk [RR], 1.10; 95% confidence interval [CI], 1.03–1.19; p = 0.0077) and the PRS method (RR, 1.10; 95% CI, 1.02–1.19; p = 0.0092). The result of causality was the same before and after involving measured confounders. However, there was no causal effect of the liability of hypertension on gout.ConclusionsIn this study, we showed that the liability of gout has a causal effect on hypertension, but the liability of hypertension does not have a causal effect on gout. Adequate management of gout may reduce the risk of developing hypertension.

Weak central coherence - construct conception, development, research methods.

Central coherence allows for integration of different stimuli into a coherent whole. It also enables context-dependent information processing. This term was coined in an effort to arrange multiple observations of cognitive functioning of people with autism spectrum disorder (ASD). Weak central coherence, which is characteristic of ASD, is understood as adivergent cognitive style with a tendency to process incoming information locally. This allows us to describe central coherence as a continuous trait. Despite manifold research programs, a conclusive conceptualization of the construct is still lacking. The open question is whether weak central coherence constitutes alimited ability to integrate stimuli or rather an increased ability to focus on details. An important postulate concerns the establishment of a standard for measuring central coherence and its individual dimensions. Studies of central coherence outside of ASD context are scarce and deal predominantly with eating disorders. The following work is an overview of the current state of knowledge about central coherence construct and methods of research.

Between African and American Neo-Pentecostalism: An Examination of the Link, Influence, Merits and Demerits

This article is based on a research study that investigated the influence, merits and demerits of the link between African and American Neo-Pentecostalism. The study employed a qualitative research method through which 40 contemporary African Neo-Pentecostal leaders (drawn from South Africa and Nigeria) were interviewed. Additionally, given that most charismatic faith and miracle African Neo-Pentecostal leaders in focus took their roots from American Neo-Pentecostalism, two medical doctors (who equally serve as African Neo-Pentecostal lay ministers), were interviewed to investigate a mother-child link. This was done to ascertain the possibility of existing traits being passed on. Alongside the historical link, the interview findings show that African Neo-Pentecostal leaders display a continuous link and traits from their American Neo-Pentecostals mentors. Thus, they exhibit such traits in theology and other practices. Subsequently, the research study established that the influence of American Pentecostalism engenders more demerits, and the researchers proposed the need to constantly de-emphasise the Americanisation of the gospel in Africa. In order to achieve this, some relevant recommendations were made, proposing that African Neo-Pentecostals need to be separated from a toxic foreign culture and should “self-exist,” thereby making room for African uniqueness in contemporary Neo-Pentecostal practices.

A New Deep Learning Calibration Method Enhances Genome-Based Prediction of Continuous Crop Traits.

Genomic selection (GS) has the potential to revolutionize predictive plant breeding. A reference population is phenotyped and genotyped to train a statistical model that is used to perform genome-enabled predictions of new individuals that were only genotyped. In this vein, deep neural networks, are a type of machine learning model and have been widely adopted for use in GS studies, as they are not parametric methods, making them more adept at capturing nonlinear patterns. However, the training process for deep neural networks is very challenging due to the numerous hyper-parameters that need to be tuned, especially when imperfect tuning can result in biased predictions. In this paper we propose a simple method for calibrating (adjusting) the prediction of continuous response variables resulting from deep learning applications. We evaluated the proposed deep learning calibration method (DL_M2) using four crop breeding data sets and its performance was compared with the standard deep learning method (DL_M1), as well as the standard genomic Best Linear Unbiased Predictor (GBLUP). While the GBLUP was the most accurate model overall, the proposed deep learning calibration method (DL_M2) helped increase the genome-enabled prediction performance in all data sets when compared with the traditional DL method (DL_M1). Taken together, we provide evidence for extending the use of the proposed calibration method to evaluate its potential and consistency for predicting performance in the context of GS applied to plant breeding.