Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits.

Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR < 0.05) with a median expected true positive rate (π1) across tissues of 0.806 and 0.390, respectively. The target proteins of trans-acting genes were enriched for transcription factor binding sites and autoimmune diseases in the GWAS catalog. Furthermore, we found a higher correlation between predicted expression and protein levels of the same underlying gene (R = 0.17) than observed expression (R = 0.10, p = 7.50 × 10-11). This indicates the cis-acting genetically regulated (heritable) component of gene expression is more consistent across tissues than total observed expression (genetics + environment) and is useful in uncovering the function of SNPs associated with complex traits.

Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects.

Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.

Methods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons.

Epigenetic researchers often evaluate DNA methylation as a potential mediator of the effect of social/environmental exposures on a health outcome. Modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large multi-ethnic cohort in the United States, while providing an R package for their seamless implementation and adoption. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model (BSLMM) and high-dimensional mediation analysis (HDMA); while the preferred methods for estimating the global mediation effect are high-dimensional linear mediation analysis (HILMA) and principal component mediation analysis (PCMA). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.

Canonical correlation analysis for multi-omics: Application to cross-cohort analysis.

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.

Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits.

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

Methods for large-scale single mediator hypothesis testing: Possible choices and comparisons.

Mediation hypothesis testing for a large number of mediators is challenging due to the composite structure of the null hypothesis, H 0 : α ß = 0 ${H}_{0}:\alpha \beta =0$ ( α $\alpha $ : effect of the exposure on the mediator after adjusting for confounders; ß $\beta $ : effect of the mediator on the outcome after adjusting for exposure and confounders). In this paper, we reviewed three classes of methods for large-scale one at a time mediation hypothesis testing. These methods are commonly used for continuous outcomes and continuous mediators assuming there is no exposure-mediator interaction so that the product α ß $\alpha \beta $ has a causal interpretation as the indirect effect. The first class of methods ignores the impact of different structures under the composite null hypothesis, namely, (1) α = 0 , ß ≠ 0 $\alpha =0,\beta \ne 0$ ; (2) α ≠ 0 , ß = 0 $\alpha \ne 0,\beta =0$ ; and (3) α = ß = 0 $\alpha =\beta =0$ . The second class of methods weights the reference distribution under each case of the null to form a mixture reference distribution. The third class constructs a composite test statistic using the three p values obtained under each case of the null so that the reference distribution of the composite statistic is approximately U ( 0 , 1 ) $U(0,1)$ . In addition to these existing methods, we developed the Sobel-comp method belonging to the second class, which uses a corrected mixture reference distribution for Sobel's test statistic. We performed extensive simulation studies to compare all six methods belonging to these three classes in terms of the false positive rates (FPRs) under the null hypothesis and the true positive rates under the alternative hypothesis. We found that the second class of methods which uses a mixture reference distribution could best maintain the FPRs at the nominal level under the null hypothesis and had the greatest true positive rates under the alternative hypothesis. We applied all methods to study the mediation mechanism of DNA methylation sites in the pathway from adult socioeconomic status to glycated hemoglobin level using data from the Multi-Ethnic Study of Atherosclerosis (MESA). We provide guidelines for choosing the optimal mediation hypothesis testing method in practice and develop an R package medScan available on the CRAN for implementing all the six methods.

Non-cigarette tobacco products, aryl-hydrocarbon receptor repressor gene methylation and smoking-related health outcomes.

INTRODUCTION: Cigarette smoking leads to altered DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) gene. However, it remains unknown whether pipe or cigar smoking is associated with AHRR methylation. We evaluated associations of non-cigarette tobacco use with AHRR methylation and determined if AHRR methylation was associated with smoking-related health outcomes. METHODS: Data were pooled across four population-based cohorts that enrolled participants from 1985 to 2002. Tobacco exposures were evaluated using smoking questionnaires. AHRR cg05575921 methylation was measured in peripheral blood leucocyte DNA. Spirometry and respiratory symptoms were evaluated at the time of methylation measurements and in subsequent visits. Vital status was monitored using the National Death Index. RESULTS: Among 8252 adults (mean age 56.7±10.3 years, 58.1% women, 40.6% black), 4857 (58.9%) participants used cigarettes and 634 (7.7%) used non-cigarette tobacco products. Exclusive use of non-cigarette tobacco products was independently associated with lower AHRR methylation (-2.44 units, 95% CI -4.42 to -0.45), though to a lesser extent than exclusive use of cigarettes (-6.01 units, 95% CI -6.01 to -4.10). Among participants who exclusively used non-cigarette tobacco products, reduced AHRR methylation was associated with increased respiratory symptom burden (OR 1.60, 95% CI 1.03 to 2.68) and higher all-cause mortality (log-rank p=0.02). CONCLUSION: Pipe and cigar smoking were independently associated with lower AHRR methylation in a multiethnic cohort of US adults. Among users of non-cigarette tobacco products, lower AHRR methylation was associated with poor respiratory health outcomes and increased mortality. AHRR methylation may identify non-cigarette tobacco users with an increased risk of adverse smoking-related health outcomes.

Characterization of CCoV-HuPn-2018 spike protein-mediated viral entry.

Canine coronavirus-human pneumonia-2018 (CCoV-HuPn-2018) was recently isolated from a child with pneumonia. This novel human pathogen resulted from cross-species transmission of a canine coronavirus. It has been known that CCoV-HuPn-2018 uses aminopeptidase N (APN) from canines, felines, and porcines, but not humans, as functional receptors for cell entry. The molecular mechanism of cell entry in CCoV-HuPn-2018 remains poorly understood. In this study, we demonstrated that among the nine APN orthologs tested, the APN of the Mexican free-tailed bat could also efficiently support CCoV-HuPn-2018 spike (S) protein-mediated entry, raising the possibility that bats may also be an alternative host epidemiologically important for the transmission of this virus. The glycosylation at residue N747 of canine APN is critical for its receptor activity. The gain of glycosylation at the corresponding residues in human and rabbit APNs converted them to functional receptors for CCoV-HuPn-2018. Interestingly, the CCoV-HuPn-2018 spike protein pseudotyped virus infected multiple human cancer cell lines in a human APN-independent manner, whereas sialic acid appeared to facilitate the entry of the pseudotyped virus into human cancer cells. Moreover, while host cell surface proteases trypsin and TMPRSS2 did not promote the entry of CCoV-HuPn-2018, endosomal proteases cathepsin L and B are required for the entry of CCoV-HuPn-2018 in a pH-dependent manner. IFITMs and LY6E are host restriction factors for the CCoV-HuPn-2018 entry. Our results thus suggest that CCoV-HuPn-2018 has not yet evolved to be an efficient human pathogen. Collectively, this study helps us understand the cell tropism, receptor usage, cross-species transmission, natural reservoir, and pathogenesis of this potential human coronavirus. IMPORTANCE Viral entry is driven by the interaction between the viral spike protein and its specific cellular receptor, which determines cell tropism and host range and is the major constraint to interspecies transmission of coronaviruses. Aminopeptidase N (APN; also called CD13) is a cellular receptor for HCoV-229E, the newly discovered canine coronavirus-human pneumonia-2018 (CCoV-HuPn-2018), and many other animal alphacoronaviruses. We examined the receptor activity of nine APN orthologs and found that CCoV-HuPn-2018 utilizes APN from a broad range of animal species, including bats but not humans, to enter host cells. To our surprise, we found that CCoV-HuPn-2018 spike protein pseudotyped viral particles successfully infected multiple human hepatoma-derived cell lines and a lung cancer cell line, which is independent of the expression of human APN. Our findings thus provide mechanistic insight into the natural hosts and interspecies transmission of CCoV-HuPn-2018-like coronaviruses.

Characterization of an Emergent Chicken H3N8 Influenza Virus in Southern China: a Potential Threat to Public Health.

Although influenza A viruses of several subtypes have occasionally infected humans, to date only those of the H1, H2, and H3 subtypes have led to pandemics and become established in humans. The detection of two human infections by avian H3N8 viruses in April and May of 2022 raised pandemic concerns. Recent studies have shown the H3N8 viruses were introduced into humans from poultry, although their genesis, prevalence, and transmissibility in mammals have not been fully elucidated. Findings generated from our systematic influenza surveillance showed that this H3N8 influenza virus was first detected in chickens in July 2021 and then disseminated and became established in chickens over wider regions of China. Phylogenetic analyses revealed that the H3 HA and N8 NA were derived from avian viruses prevalent in domestic ducks in the Guangxi-Guangdong region, while all internal genes were from enzootic poultry H9N2 viruses. The novel H3N8 viruses form independent lineages in the glycoprotein gene trees, but their internal genes are mixed with those of H9N2 viruses, indicating continuous gene exchange among these viruses. Experimental infection of ferrets with three chicken H3N8 viruses showed transmission through direct contact and inefficient transmission by airborne exposure. Examination of contemporary human sera detected only very limited antibody cross-reaction to these viruses. The continuing evolution of these viruses in poultry could pose an ongoing pandemic threat. IMPORTANCE A novel H3N8 virus with demonstrated zoonotic potential has emerged and disseminated in chickens in China. It was generated by reassortment between avian H3 and N8 virus(es) and long-term enzootic H9N2 viruses present in southern China. This H3N8 virus has maintained independent H3 and N8 gene lineages but continues to exchange internal genes with other H9N2 viruses to form novel variants. Our experimental studies showed that these H3N8 viruses were transmissible in ferrets, and serological data suggest that the human population lacks effective immunological protection against it. With its wide geographical distribution and continuing evolution in chickens, other spillovers to humans can be expected and might lead to more efficient transmission in humans.

Omicron BA.4/5 neutralization and cell-mediated immune responses in relation to baseline immune status and breakthrough infection among PLWH: A follow-up cohort study.

There is a paucity of data on hybrid immunity (vaccination plus breakthrough infection [BI]), especially cell-mediated responses to Omicron among immunosuppressed patients. We aim to investigate humoral and cellular responses to Omicron BA.4/5 among people living with HIV (PLWH) with/without BIs, the most prevalent variant of concern after the reopening of China. Based on our previous study, we enrolled 77 PLWH with baseline immune status of severe acute respiratory syndrome coronavirus 2 specific antibodies after inactivated vaccination. "Correlates of protection," including serological immunoassays, T cell phenotypes and memory B cells (MBC) were determined in PLWH without and with BI, together with 16 PLWH with reinfections. Higher inhibition rate of neutralizing antibodies (NAb) against BA.4/5 was elicited among PLWH with BI than those without. Omicron-reactive IL4+ CD8+ T cells were significantly elevated in PLWH experienced postvaccine infection contrasting with those did not. NAb towards wild type at baseline was associated with prolonged negative conversion time for PLWH whereas intermediate MBCs serve as protecting effectors. We uncovered that hybrid immunity intensified more protection on BA.4/5 than vaccination did. Strengthened surveillance on immunological parameters and timely clinical intervention on PLWH deficient in protection would reduce the severity and mortality in the context of coexistence with new Omicron subvariants.

First-line treatment of driver gene-negative metastatic lung adenocarcinoma with malignant pleural effusion: Should chemotherapy be combined with an immune checkpoint inhibitor or bevacizumab?

Patients with metastatic lung adenocarcinoma (MLA) and malignant pleural effusion (MPE) without driver gene mutations have a poor prognosis. None of the standard treatment strategies is recommended for such patients. We retrospectively analyzed the efficacy of the first-line treatment for this specific population: standard platinum-based doublet chemotherapy (CT), CT plus an immune checkpoint inhibitor (CT plus ICI), and CT plus bevacizumab (CT plus Bev). A total of 323 eligible patients were enrolled: CT alone (n = 166), CT plus Bev (n = 72), and CT plus ICI (n = 85). Treatment efficacy assessments were performed every two cycles according to the RECIST guidelines. The endpoints were overall survival (OS) and progression-free survival (PFS). Kaplan-Meier (K‒M) curves and the log-rank test were used to compare OS and PFS. p < 0.05 was the threshold of significance (statistical software: SPSS). The median follow-up was 11.4 months (range, 2.1-49.6 months). PFS and OS in the CT plus ICI/CT plus Bev cohort were significantly longer than those in the CT group (PFS: 7.8/6.4/3.9 months, p < 0.0001; OS: 16.4/15.6/9.6 months, p < 0.0001, respectively). CT plus Bev had better PFS and OS than CT plus ICI/CT in PD-L1 < 1% patients (PFS: 8.4/5.0/3.8 months, p < 0.0001; OS: 15.6/12.9/9.3 months, p < 0.0001). Among patients with PD-L1 1-49%, CT plus ICI led to a longer PFS and OS (PFS: 8.9/5.8/4.2 months, p = 0.009; OS: 24.2/18.8/11.5 months, p = 0.03). In the cohort with PD-L1 ≥ 50%, CT plus ICI was still the best first-line treatment (PFS: 19.7/13.8/9.6 months, p = 0.033; OS: 27.2/19.6/14.9 months, p = 0.047). In driver gene-negative MLA with MPE, CT plus Bev or ICI better controlled MPE and significantly prolonged survival compared to CT alone. PD-L1 expression (negative/positive) may be a key factor influencing the choice of CT plus Bev or ICI.

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts.

BACKGROUND: Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. METHODS: Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. RESULTS: Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. CONCLUSIONS: Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

Arsenic Exposure, Blood DNA Methylation, and Cardiovascular Disease.

BACKGROUND: Epigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD. METHODS: Blood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE-/-) mouse model of atherosclerosis. RESULTS: A total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic. CONCLUSIONS: Differential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.

Immune and inflammation features of severe and critical Omicron infected patients during Omicron wave in China.

OBJECTIVE: The current study aimed to investigate the baseline immune and inflammatory features and in-hospital outcomes of patients infected with the Omicron variant (PIWO) who presented with different disease severities during the first wave of mass Omicron infections in the Chinese population has occurred. METHOD: A cross-sectional study was conducted on 140 hospitalized PIWO between December 11, 2022, and February 16, 2023. The clinical features, antibodies against SARS-CoV-2, immune cells, and inflammatory cytokines among mildly, severely, and critically ill PIWO at baseline and during follow-up period were compared. RESULT: Patients with severe (n = 49) and critical (n = 35) disease were primarily male, needed invasive mechanical ventilation treatment, and exhibited higher mortality than those with mild disease (n = 56). During acute infection, SARS-CoV-2-specific antibody levels fluctuated with disease severity, serum antibodies increased and the incidence of severe cases decreased in critically ill PIWO over time. Antibody titers in severe or critical PIWO with no antibody responses at baseline did not increase significantly over time. Meanwhile, CD4+T cell, CD8+T cell, and natural killer cell counts were negatively correlated with disease severity, whereas interleukin (IL)-6 and IL-10 levels were positively correlated. In addition, combined diabetes, immunosuppressive therapy before infection, serum amyloid A, IL-10 and neutrophil counts were independently associated with severe and critical illness in PIWO. Among the 11 nonsurvivors, 8, 2, 1 died of respiratory failure, sudden cardiac death, and renal failure, respectively. Compared with survivors, nonsurvivors exhibited lower seropositivity of SARS-CoV-2-specific antibody, reduced CD3+T and CD4+T cell counts, and higher IL-2R, IL-6, IL-8, and IL-10 levels. Of note, lactate dehydrogenase was a significant risk factor of death in severe or critically ill PIWO. CONCLUSION: This present study assessed the dynamic changes of SARS-CoV-2-specific antibodies, immune cells and inflammatory indexes between severely and critically ill PIWO. Critical and dead PIWO featured compromised humoral immune response and excessive inflammation, which broadened the understanding of the pathophysiology of Omicron infection and provides warning markers for severe disease and poor prognosis.

Value-Added Upcycling of PET to 1,4-Cyclohexanedimethanol by a Hydrogenation/Hydrogenolysis Relay Catalysis.

We present an innovative process for directly transforming poly(ethylene terephthalate) (PET), a polymer extensively used in food and beverage packaging, into trans-isomer-enriched 1,4-cyclohexanedimethanol (CHDM), a key ingredient in advanced specialty polymers. Our approach leverages a dual-catalyst system featuring palladium on reduced graphene oxide (Pd/r-GO) and oxalate-gel-derived copper-zinc oxide (og-CuZn), utilizing hydrogenation/hydrogenolysis relay catalysis. This method efficiently transforms PET into polyethylene-1,4-cyclohexanedicarboxylate (PECHD), which is then converted into CHDM with an impressive overall yield of 95 % in a two-stage process. Our process effectively handles various post-consumer PET plastics, converting them into CHDM with yields between 78 % and 89 % across different substrates. Additionally, we demonstrate the applicability and scalability of this approach through a temperature-programmed three-stage relay process on a 10-gram scale, which results in purified CHDM with an isolated yield of 87 % and a notably higher trans/cis ratio of up to 4.09/1, far exceeding that of commercially available CHDM. This research not only provides a viable route for repurposing PET waste but also enhances the control of selectivity patterns in multistage relay catalysis.

AtheroSpectrum Reveals Novel Macrophage Foam Cell Gene Signatures Associated With Atherosclerotic Cardiovascular Disease Risk.

BACKGROUND: Whereas several interventions can effectively lower lipid levels in people at risk for atherosclerotic cardiovascular disease (ASCVD), cardiovascular event risks remain, suggesting an unmet medical need to identify factors contributing to cardiovascular event risk. Monocytes and macrophages play central roles in atherosclerosis, but studies have yet to provide a detailed view of macrophage populations involved in increased ASCVD risk. METHODS: A novel macrophage foaming analytics tool, AtheroSpectrum, was developed using 2 quantitative indices depicting lipid metabolism and the inflammatory status of macrophages. A machine learning algorithm was developed to analyze gene expression patterns in the peripheral monocyte transcriptome of MESA participants (Multi-Ethnic Study of Atherosclerosis; set 1; n=911). A list of 30 genes was generated and integrated with traditional risk factors to create an ASCVD risk prediction model (30-gene cardiovascular disease risk score [CR-30]), which was subsequently validated in the remaining MESA participants (set 2; n=228); performance of CR-30 was also tested in 2 independent human atherosclerotic tissue transcriptome data sets (GTEx [Genotype-Tissue Expression] and GSE43292). RESULTS: Using single-cell transcriptomic profiles (GSE97310, GSE116240, GSE97941, and FR-FCM-Z23S), AtheroSpectrum detected 2 distinct programs in plaque macrophages-homeostatic foaming and inflammatory pathogenic foaming-the latter of which was positively associated with severity of atherosclerosis in multiple studies. A pool of 2209 pathogenic foaming genes was extracted and screened to select a subset of 30 genes correlated with cardiovascular event in MESA set 1. A cardiovascular disease risk score model (CR-30) was then developed by incorporating this gene set with traditional variables sensitive to cardiovascular event in MESA set 1 after cross-validation generalizability analysis. The performance of CR-30 was then tested in MESA set 2 (P=2.60×10-4; area under the receiver operating characteristic curve, 0.742) and 2 independent data sets (GTEx: P=7.32×10-17; area under the receiver operating characteristic curve, 0.664; GSE43292: P=7.04×10-2; area under the receiver operating characteristic curve, 0.633). Model sensitivity tests confirmed the contribution of the 30-gene panel to the prediction model (likelihood ratio test; df=31, P=0.03). CONCLUSIONS: Our novel computational program (AtheroSpectrum) identified a specific gene expression profile associated with inflammatory macrophage foam cells. A subset of 30 genes expressed in circulating monocytes jointly contributed to prediction of symptomatic atherosclerotic vascular disease. Incorporating a pathogenic foaming gene set with known risk factors can significantly strengthen the power to predict ASCVD risk. Our programs may facilitate both mechanistic investigations and development of therapeutic and prognostic strategies for ASCVD risk.

Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease.

BACKGROUND: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. METHODS: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). RESULTS: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, ß=0.61±0.05, P=3.27×10-30) and MMP-3 (ß=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, ß=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. CONCLUSIONS: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Nitrogen-Neighbored Single-Cobalt Sites Enable Heterogeneous Oxidase-Type Catalysis.

The development of biomimetic catalytic systems that can imitate or even surpass natural enzymes remains an ongoing challenge, especially for bioinspired syntheses that can access non-natural reactions. Here, we show how an all-inorganic biomimetic system bearing robust nitrogen-neighbored single-cobalt site/pyridinic-N site (Co-N4/Py-N) pairs can act cooperatively as an oxidase mimic, which renders an engaged coupling of oxygen (O2) reduction with synthetically beneficial chemical transformations. By developing this broadly applicable platform, the scalable synthesis of greater than 100 industrially and pharmaceutically appealing O-silylated compounds including silanols, borasiloxanes, and silyl ethers via the unprecedented aerobic oxidation of hydrosilane under ambient conditions is demonstrated. Moreover, this heterogeneous oxidase mimic also offers the potential for expanding the catalytic scope of enzymatic synthesis. We anticipate that the strategy demonstrated here will pave a new avenue for understanding the underlying nature of redox enzymes and open up a new class of material systems for artificial biomimetics.

Real-world clinical analysis in 190 advanced NSCLC patients with uncommon EGFR mutations: A multi-center study.

Differently from epidermal growth factor receptor (EGFR) 19Del and L858R mutations, the panoramic description of uncommon EGFR mutations is far from mature. Our understanding of its population characteristics, treatment response, and drug resistance mechanisms needs urgent expansion and deepening. Our study enrolled 437 patients with non-small-cell lung cancer from four clinical centers and who had uncommon EGFR mutations. The clinical characteristics of all patients and the treatment outcomes of 190 advanced patients who received pharmacotherapy were analyzed. Moreover, the acquired resistance mechanisms were explored based on 53 tissue or liquid re-biopsy data in 45 patients. Patients with EGFR 20ins had a shorter survival time compared with patients with non-20ins mutations. In total, 149 cases had received EGFR-tyrosine kinase inhibitors (TKI); afatinib was significantly superior to other EGFR-TKIs both in ORR and mPFS in all uncommon mutations and especially in the L861Q group. The most common acquired drug resistance mechanism was MET amplification, followed by EGFR T790M, which was significantly different from common EGFR mutations.

Associations of Early-Life Adversity With Later-Life Epigenetic Aging Profiles in the Multi-Ethnic Study of Atherosclerosis.

Epigenetic biomarkers of accelerated aging have been widely used to predict disease risk and may enhance our understanding of biological mechanisms between early-life adversity and disparities in aging. With respect to childhood adversity, most studies have used parental education or childhood disadvantage and/or have not examined the role played by socioemotional or physical abuse and trauma in epigenetic profiles at older ages. This study leveraged data from the Multi-Ethnic Study of Atherosclerosis (MESA) on experiences of threat and deprivation in participants' early lives (i.e., before the age of 18 years) to examine whether exposure to specific dimensions of early-life adversity is associated with epigenetic profiles at older ages that are indicative of accelerated biological aging. The sample included 842 MESA respondents with DNA methylation data collected between 2010 and 2012 who answered questions on early-life adversities in a 2018-2019 telephone follow-up. We found that experiences of deprivation, but not threat, were associated with later-life GrimAge epigenetic aging signatures that were developed to predict mortality risk. Results indicated that smoking behavior partially mediates this association, which suggests that lifestyle behaviors may act as downstream mechanisms between parental deprivation in early life and accelerated epigenetic aging in later life.