Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis.

Deep vein thrombosis (DVT) is a leading cause of morbidity and mortality after trauma. Here, we integrate plasma metabolomics and proteomics to evaluate the metabolic alterations and their function in up to 680 individuals with and without DVT after trauma (pt-DVT). We identify 28 metabolites and 2 clinical parameter clusters associated with pt-DVT. Then, we develop a panel of 9 metabolites (hexadecanedioic acid, pyruvic acid, L-Carnitine, serotonin, PE(P-18:1(11Z)/18:2(9Z,12Z)), 3-Hydroxycapric acid, 5,6-DHET, 3-Methoxybenzenepropanoic acid and pentanenitrile) that can predict pt-DVT with high performance, which can be verified in an independent cohort. Furthermore, the integration analysis of metabolomics and proteomics data indicates that the upregulation of glycolysis/gluconeogenesis-TCA cycle may promote thrombosis by regulating ROS levels in red blood cells, suggesting that interfering with this process might be potential therapeutic strategies for pt-DVT. Together, our study comprehensively delineates the metabolic and hematological dysregulations for pt-DVT, and provides potential biomarkers for early detection.

Blood metabolites, neurocognition and psychiatric disorders: a Mendelian randomization analysis to investigate causal pathways.

BACKGROUND: Neurocognitive dysfunction is observationally associated with the risk of psychiatric disorders. Blood metabolites, which are readily accessible, may become highly promising biomarkers for brain disorders. However, the causal role of blood metabolites in neurocognitive function, and the biological pathways underlying their association with psychiatric disorders remain unclear. METHODS: To explore their putative causalities, we conducted bidirectional two-sample Mendelian randomization (MR) using genetic variants associated with 317 human blood metabolites (nmax = 215,551), g-Factor (an integrated index of multiple neurocognitive tests with nmax = 332,050), and 10 different psychiatric disorders (n = 9,725 to 807,553) from the large-scale genome-wide association studies of European ancestry. Mediation analysis was used to assess the potential causal pathway among the candidate metabolite, neurocognitive trait and corresponding psychiatric disorder. RESULTS: MR evidence indicated that genetically predicted acetylornithine was positively associated with g-Factor (0.035 standard deviation units increase in g-Factor per one standard deviation increase in acetylornithine level; 95% confidence interval, 0.021 to 0.049; P = 1.15 × 10-6). Genetically predicted butyrylcarnitine was negatively associated with g-Factor (0.028 standard deviation units decrease in g-Factor per one standard deviation increase in genetically proxied butyrylcarnitine; 95% confidence interval, -0.041 to -0.015; P = 1.31 × 10-5). There was no evidence of associations between genetically proxied g-Factor and metabolites. Furthermore, the mediation analysis via two-step MR revealed that the causal pathway from acetylornithine to bipolar disorder was partly mediated by g-Factor, with a mediated proportion of 37.1%. Besides, g-Factor mediated the causal pathway from butyrylcarnitine to schizophrenia, with a mediated proportion of 37.5%. Other neurocognitive traits from different sources provided consistent findings. CONCLUSION: Our results provide genetic evidence that acetylornithine protects against bipolar disorder through neurocognitive abilities, while butyrylcarnitine has an adverse effect on schizophrenia through neurocognition. These findings may provide insight into interventions at the metabolic level for risk of neurocognitive and related disorders.

Two-sample Mendelian randomization analysis reveals causal relationships between blood lipids and venous thromboembolism.

Venous thromboembolism (VTE) is a complex disease that can be classified into two subtypes: deep vein thrombosis (DVT) and pulmonary embolism (PE). Previous observational studies have shown associations between lipids and VTE, but causality remains unclear. Hence, by utilizing 241 lipid-related traits as exposures and data from the FinnGen consortium on VTE, DVT, and PE as outcomes, we conducted two-sample Mendelian randomization (MR) analysis to investigate causal relationships between lipids and VTE, DVT and PE. The MR results identified that fatty acid (FA) unsaturation traits (ratio of bis-allylic bonds to double bonds in lipids, and ratio of bis-allylic bonds to total fatty acids in lipids) were associated with VTE (odds ratio [OR]=1.21, 95% confidence interval [CI]: 1.15-1.27; OR=1.21, 95% CI: 1.13-1.30), DVT (OR=1.24, 95% CI: 1.16-1.33; OR= 1.26, 95% CI: 1.16-1.36) and PE (OR=1.18, 95% CI: 1.08-1.29; OR=1.18, 95% CI: 1.09-1.27). Phosphatidylcholines (PC) exhibit potential causal effects on VTE and PE. PC acyl-alkyl C40:4 (PC ae C40:4) was negatively associated with VTE (OR=0.79, 95% CI: 0.73-0.86), while PC diacyl C42:6 (PC aa C42:6) and PC acyl-alkyl C36:4 (PC ae C36:4) were positively associated with PE (OR=1.44, 95% CI: 1.20-1.72; OR=1.22, 95% CI: 1.10-1.35). Additionally, we found that medium LDL had a protective effect on VTE. Our study indicates that higher FA unsaturation may increase the risk of VTE, DVT, and PE. Different types of PC have either promotive or inhibitory effects on VTE and PE, contributing to a better understanding of the risk factors for VTE.

Causal Associations Between Blood Lipids and COVID-19 Risk: A Two-Sample Mendelian Randomization Study.

[Figure: see text].

[Research on fast experimental measurement method for atmosphere downward long-wave radiance].

Direct measurement of the sky radiation in the direction of a special zenith angle as the average downward radiation is the fastest instantaneous downward radiation measurement. But this method has not been widely used, because there is no accu rate method for determining special zenith angle. The present paper analyzed the special angle with the variation of the aerosol optical thickness and atmospheric temperature and humidity through simulation by radiative transfer model. The results show that the special angles will be affected none by aerosols in clear skies, very little by atmospheric temperature, but significantly by atmospheric water vapor content. Therefore, the special angle could be determined only by atmospheric water vapor content in downward radiance infrared spectroscopy measurements in clear sky conditions. The downward radiation measurements results in western desert region indicate that the special angles determined by local atmospheric water vapor content are the same as experimental results. Besides, the error caused by taking the radiance at the special angle as the integral radiance meets the accuracy requirements. Accordingly, this fast measurement method can be widely used in field experiments while the special angle can be determined by atmospheric water vapor of the study area, since it can measure instantaneous downward radiance conveniently and accurately.

[Dynamic assessment of grassland degradation in Naqu of northern Tibet].

Based on the past years vegetation cover, annual maximal grass yield and June-September mean modified soil-adjusted vegetation index (MSAVI) that were inversely deduced from the 10-day composite data of NOAA/AVHRR channels 1 and 2 and NDVI in 1982-2000, this paper analyzed the recent 20 years dynamics of grassland desertification in Naqu of northern Tibet. The results showed that in recent 20 years, the area of degraded grassland in Naqu was averagely 43.1% of the total land area. It was decreased in the former ten years while increased in the latter ten years, but overall, had a decreasing trend. The degraded area was larger in west part of Naqu than in its other regions. Among the eight climatic factors including temperature, precipitation, potential evapotranspiration, vapor pressure, wind velocity, sunshine hour, ratio of precipitation to evapotranspiration, and ratio of temperature to precipitation, the most remarkable factor affecting the dynamic of grassland degradation was the potential evapotranspiration.

[Classification and dynamic changes of grasslands in northern Tibet based on recent 20 years satellite data].

Based on the NOAA/AVHRR 10-day composite NDVI data from 1982 to 2000 and by the methods of principal component analysis and unsupervised classification, the vegetations in Naqu District of northern Tibet were classified, and the annual and inter-annual variations of NDVI on the pixels selected from different grassland types were analyzed. The regions where the mean NDVI values during the main growth season of grass were equal to or great than 0.1 were defined as vegetation regions, while those where the mean NDVI values were less than 0.1 were defined as non-vegetation regions. The spatiotemporal changes of NDVI in each pixel in vegetation regions were analyzed, and the results showed that the grasslands in northern Tibet could be classified into four types, i. e., high-cold meadow, high-cold meadow steppe, high-cold steppe, and high-cold desert. This classification was accorded with practical status. The annual changes of the NDVI in the four grassland types showed one peak value, with the maximum in August. In recent 20 years, the mean NDVI from July to August in vegetation regions decreased gradually from southeast to northwest, ranging from 0.1 to 0.6, and the variation coefficient changed between 0.05 and 0.40, which was smaller in the place of high NDVI than in the place of low NDVI. The annual variability of NDVI changed between -0.005 and 0.008. In recent 20 years, the vegetations had no observable change, but the vegetation development in 20% of vegetation regions, which mainly located in Nima in western Naqu and in Jiali, Biru, Suoxian and Baqing in eastern Naqu, was weakened.