Estimating heritability and genetic correlations from large health datasets in the absence of genetic data

Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearmans rho = 0.32, p amp;lt; 10(-16)); and (3) the disease onset age and heritability are negatively correlated (rho = -0.46, p amp;lt; 10(-16)).Funding Agencies|DARPA Big Mechanism program under ARO [W911NF1410333]; National Institutes of HealthUnited States Department of Health &amp; Human ServicesNational Institutes of Health (NIH) - USA [R01HL122712, 1P50MH094267, U01HL108634-01]; King Abdullah University of Science and Technology (KAUST)King Abdullah University of Science &amp; Technology [FCC/1/1976-18-01, FCC/1/1976-23-01, FCC/1/1976-25-01, FCC/1/1976-26-01, FCS/1/4102-02-01]</p

Estimating heritability and genetic correlations from large health datasets in the absence of genetic data.

Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearman\u27s ρ = 0.32, p \u3c 1

Evaluation of the Reclamation Suitability of Industrial and Mining Wasteland

To evaluate the reclamation suitability of industrial and mining wasteland is the premise of reclamation. The wasteland was firstly categorized according to land use status and damage types. Then the evaluation process of reclamation suitability was introduced, which involves two steps, the first step was to exclude those unsuitable wasteland by the limits conditions, while the second step was to evaluate the suitability degree of those suitable wasteland. From the perspectives of soil fertility, soil pollution, farmland water conservancy and land damage, twelve evaluation factors, including soil depth, gravel content, bulk density, organic material content, pollution index, gradient, flatness, irrigation and drainage condition, source of borrowed earth, distance from the residential settlement, erosion modulus and damage extent, were selected to establish an index system for evaluating the abandoned industrial and mining land, aiming to provide references for the future reclamation of industrial and mining wasteland

Research on the spatial distribution characteristics of arable land economic quality composite grade and ecology environment in Yunnan Province, China

ABSTRACT Understanding the distribution characteristics of arable land in Yunnan Province is of significant importance to make scientific decisionsto use and improve the quality of arable land. In this study, the distribution characteristics of the arable land grade including 129 counties were analyzed based on the accomplishment of cultivated land classification in Yunnan Province. The results showed that the average economic quality composite grade was 2.9, in a range of 1 to 13, which means that the economic quality of arable landof Yunnan Province is relatively lower. In excellent zone, the grade ranges from 1 to 10, and the average grade is 2.4. In good zone, it ranges from 1~13, and the average grade is 3.1. In medium zone, it ranges from 1~12, and the average value is 3.2. In poor zone, it ranges from 1~11, and the average is 3. In worse zone, it ranges from 1~10, and the average is 2.2. The middle and poor arable land has the largest area, which concentrated in the middle and poor zones and dominantly influenced the average grade in the whole province. This research will serve as a reference forarable landpolicy making in the future, especiallyon apace arrangement optimization, quality improvement and ecology environment protection in Yunnan Province

Ultra-multiplexed analysis of single-cell dynamics reveals logic rules in differentiation

Dynamical control of cellular microenvironments is highly desirable to study complex processes such as stem cell differentiation and immune signaling. We present an ultra-multiplexed microfluidic system for high-throughput single-cell analysis in precisely defined dynamic signaling environments. Our system delivers combinatorial and time-varying signals to 1500 independently programmable culture chambers in week-long live-cell experiments by performing nearly 106 pipetting steps, where single cells, two-dimensional (2D) populations, or 3D neurospheres are chemically stimulated andtracked. Using our system and statistical analysis, we investigatedthe signaling landscape of neural stem cell differentiation and discovered "cellular logic rules" that revealed the critical role of signal timing and sequence in cell fate decisions. We find synergistic and antagonistic signal interactions and show that differentiation pathways are highly redundant. Our system allows dissection of hidden aspects of cellular dynamics and enables accelerated biological discovery

High-Purity Fucoxanthin Can Be Efficiently Prepared from Isochrysis zhangjiangensis by Ethanol-Based Green Method Coupled with Octadecylsilyl (ODS) Column Chromatography

The exploitation of new economically valuable microalgae as a sustainable source of minor high-value products can effectively promote the full utilization of microalgae. The efficient preparation of minor products from microalgae remains the challenge, owing to the coexistence of various components with a similar polarity in the microalgae biomass. In this study, a novel approach based on the sustainable-oriented strategy for fucoxanthin (FX) production was proposed, which consisted of four steps, including the culture of microalga, ethanol extraction, ODS column chromatography, and ethanol precipitation. The high-purity FX (around 95%) was efficiently obtained in a total recovery efficiency of 84.28 &plusmn; 2.56%. This study reveals that I. zhangjiangensis is a potentially promising feedstock for FX production and firstly provides a potentially eco-friendly method for the scale-up preparation of FX from the microalga I. zhangjiangensis

An MRTF-A–ZEB1–IRF9 axis contributes to fibroblast–myofibroblast transition and renal fibrosis

Abstract Myofibroblasts, characterized by the expression of the matricellular protein periostin (Postn), mediate the profibrogenic response during tissue repair and remodeling. Previous studies have demonstrated that systemic deficiency in myocardin-related transcription factor A (MRTF-A) attenuates renal fibrosis in mice. In the present study, we investigated the myofibroblast-specific role of MRTF-A in renal fibrosis and the underlying mechanism. We report that myofibroblast-specific deletion of MRTF-A, achieved through crossbreeding Mrtfa-flox mice with Postn-CreERT2 mice, led to amelioration of renal fibrosis. RNA-seq identified zinc finger E-Box binding homeobox 1 (Zeb1) as a downstream target of MRTF-A in renal fibroblasts. MRTF-A interacts with TEA domain transcription factor 1 (TEAD1) to bind to the Zeb1 promoter and activate Zeb1 transcription. Zeb1 knockdown retarded the fibroblast–myofibroblast transition (FMyT) in vitro and dampened renal fibrosis in mice. Transcriptomic assays showed that Zeb1 might contribute to FMyT by repressing the transcription of interferon regulatory factor 9 (IRF9). IRF9 knockdown overcame the effect of Zeb1 depletion and promoted FMyT, whereas IRF9 overexpression antagonized TGF-β-induced FMyT. In conclusion, our data unveil a novel MRTF-A–Zeb1–IRF9 axis that can potentially contribute to fibroblast–myofibroblast transition and renal fibrosis. Screening for small-molecule compounds that target this axis may yield therapeutic options for the mollification of renal fibrosis