Identification of novel bat coronaviruses sheds light on the evolutionary origins of SARS-CoV-2 and related viruses.

Despite the discovery of animal coronaviruses related to SARS-CoV-2, the evolutionary origins of this virus are elusive. We describe a meta-transcriptomic study of 411 bat samples collected from a small geographical region in Yunnan province, China, between May 2019 and November 2020. We identified 24 full-length coronavirus genomes, including four novel SARS-CoV-2-related and three SARS-CoV-related viruses. Rhinolophus pusillus virus RpYN06 was the closest relative of SARS-CoV-2 in most of the genome, although it possessed a more divergent spike gene. The other three SARS-CoV-2-related coronaviruses carried a genetically distinct spike gene that could weakly bind to the hACE2 receptor in vitro. Ecological modeling predicted the co-existence of up to 23 Rhinolophus bat species, with the largest contiguous hotspots extending from South Laos and Vietnam to southern China. Our study highlights the remarkable diversity of bat coronaviruses at the local scale, including close relatives of both SARS-CoV-2 and SARS-CoV.

O-GlcNAcylation of Raptor transduces glucose signals to mTORC1.

The mechanistic target of rapamycin complex 1 (mTORC1) regulates metabolism and cell growth in response to nutrient levels. Dysregulation of mTORC1 results in a broad spectrum of diseases. Glucose is the primary energy supply of cells, and therefore, glucose levels must be accurately conveyed to mTORC1 through highly responsive signaling mechanisms to control mTORC1 activity. Here, we report that glucose-induced mTORC1 activation is regulated by O-GlcNAcylation of Raptor, a core component of mTORC1, in HEK293T cells. Mechanistically, O-GlcNAcylation of Raptor at threonine 700 facilitates the interactions between Raptor and Rag GTPases and promotes the translocation of mTOR to the lysosomal surface, consequently activating mTORC1. In addition, we show that AMPK-mediated phosphorylation of Raptor suppresses Raptor O-GlcNAcylation and inhibits Raptor-Rags interactions. Our findings reveal an exquisitely controlled mechanism, which suggests how glucose coordinately regulates cellular anabolism and catabolism.

Glucose-induced CRL4COP1-p53 axis amplifies glycometabolism to drive tumorigenesis.

The diabetes-cancer association remains underexplained. Here, we describe a glucose-signaling axis that reinforces glucose uptake and glycolysis to consolidate the Warburg effect and overcome tumor suppression. Specifically, glucose-dependent CK2 O-GlcNAcylation impedes its phosphorylation of CSN2, a modification required for the deneddylase CSN to sequester Cullin RING ligase 4 (CRL4). Glucose, therefore, elicits CSN-CRL4 dissociation to assemble the CRL4COP1 E3 ligase, which targets p53 to derepress glycolytic enzymes. A genetic or pharmacologic disruption of the O-GlcNAc-CK2-CSN2-CRL4COP1 axis abrogates glucose-induced p53 degradation and cancer cell proliferation. Diet-induced overnutrition upregulates the CRL4COP1-p53 axis to promote PyMT-induced mammary tumorigenesis in wild type but not in mammary-gland-specific p53 knockout mice. These effects of overnutrition are reversed by P28, an investigational peptide inhibitor of COP1-p53 interaction. Thus, glycometabolism self-amplifies via a glucose-induced post-translational modification cascade culminating in CRL4COP1-mediated p53 degradation. Such mutation-independent p53 checkpoint bypass may represent the carcinogenic origin and targetable vulnerability of hyperglycemia-driven cancer.

IL-17-receptor-associated adaptor Act1 directly stabilizes mRNAs to mediate IL-17 inflammatory signaling.

Mechanisms that degrade inflammatory mRNAs are well known; however, stabilizing mechanisms are poorly understood. Here, we show that Act1, an interleukin-17 (IL-17)-receptor-complex adaptor, binds and stabilizes mRNAs encoding key inflammatory proteins. The Act1 SEFIR domain binds a stem-loop structure, the SEFIR-binding element (SBE), in the 3' untranslated region (UTR) of Cxcl1 mRNA, encoding an inflammatory chemokine. mRNA-bound Act1 directs formation of three compartmentally distinct RNA-protein complexes (RNPs) that regulate three disparate events in inflammatory-mRNA metabolism: preventing mRNA decay in the nucleus, inhibiting mRNA decapping in P bodies and promoting translation. SBE RNA aptamers decreased IL-17-mediated mRNA stabilization in vitro, IL-17-induced skin inflammation and airway inflammation in a mouse asthma model, thus providing a therapeutic strategy for autoimmune diseases. These results reveal a network in which Act1 assembles RNPs on the 3' UTRs of select mRNAs and consequently controls receptor-mediated mRNA stabilization and translation during inflammation.

Ultracold field-linked tetratomic molecules.

Ultracold polyatomic molecules offer opportunities1 in cold chemistry2,3, precision measurements4 and quantum information processing5,6, because of their rich internal structure. However, their increased complexity compared with diatomic molecules presents a challenge in using conventional cooling techniques. Here we demonstrate an approach to create weakly bound ultracold polyatomic molecules by electroassociation7 (F.D. et al., manuscript in preparation) in a degenerate Fermi gas of microwave-dressed polar molecules through a field-linked resonance8-11. Starting from ground-state NaK molecules, we create around 1.1 × 103 weakly bound tetratomic (NaK)2 molecules, with a phase space density of 0.040(3) at a temperature of 134(3) nK, more than 3,000 times colder than previously realized tetratomic molecules12. We observe a maximum tetramer lifetime of 8(2) ms in free space without a notable change in the presence of an optical dipole trap, indicating that these tetramers are collisionally stable. Moreover, we directly image the dissociated tetramers through microwave-field modulation to probe the anisotropy of their wavefunction in momentum space. Our result demonstrates a universal tool for assembling weakly bound ultracold polyatomic molecules from smaller polar molecules, which is a crucial step towards Bose-Einstein condensation of polyatomic molecules and towards a new crossover from a dipolar Bardeen-Cooper-Schrieffer superfluid13-15 to a Bose-Einstein condensation of tetramers. Moreover, the long-lived field-linked state provides an ideal starting point for deterministic optical transfer to deeply bound tetramer states16-18.

Van der Waals polarity-engineered 3D integration of 2D complementary logic.

Vertical three-dimensional integration of two-dimensional (2D) semiconductors holds great promise, as it offers the possibility to scale up logic layers in the z axis1-3. Indeed, vertical complementary field-effect transistors (CFETs) built with such mixed-dimensional heterostructures4,5, as well as hetero-2D layers with different carrier types6-8, have been demonstrated recently. However, so far, the lack of a controllable doping scheme (especially p-doped WSe2 (refs. 9-17) and MoS2 (refs. 11,18-28)) in 2D semiconductors, preferably in a stable and non-destructive manner, has greatly impeded the bottom-up scaling of complementary logic circuitries. Here we show that, by bringing transition metal dichalcogenides, such as MoS2, atop a van der Waals (vdW) antiferromagnetic insulator chromium oxychloride (CrOCl), the carrier polarity in MoS2 can be readily reconfigured from n- to p-type via strong vdW interfacial coupling. The consequential band alignment yields transistors with room-temperature hole mobilities up to approximately 425 cm2 V-1 s-1, on/off ratios reaching 106 and air-stable performance for over one year. Based on this approach, vertically constructed complementary logic, including inverters with 6 vdW layers, NANDs with 14 vdW layers and SRAMs with 14 vdW layers, are further demonstrated. Our findings of polarity-engineered p- and n-type 2D semiconductor channels with and without vdW intercalation are robust and universal to various materials and thus may throw light on future three-dimensional vertically integrated circuits based on 2D logic gates.

Field-linked resonances of polar molecules.

Scattering resonances are an essential tool for controlling the interactions of ultracold atoms and molecules. However, conventional Feshbach scattering resonances1, which have been extensively studied in various platforms1-7, are not expected to exist in most ultracold polar molecules because of the fast loss that occurs when two molecules approach at a close distance8-10. Here we demonstrate a new type of scattering resonance that is universal for a wide range of polar molecules. The so-called field-linked resonances11-14 occur in the scattering of microwave-dressed molecules because of stable macroscopic tetramer states in the intermolecular potential. We identify two resonances between ultracold ground-state sodium-potassium molecules and use the microwave frequencies and polarizations to tune the inelastic collision rate by three orders of magnitude, from the unitary limit to well below the universal regime. The field-linked resonance provides a tuning knob to independently control the elastic contact interaction and the dipole-dipole interaction, which we observe as a modification in the thermalization rate. Our result provides a general strategy for resonant scattering between ultracold polar molecules, which paves the way for realizing dipolar superfluids15 and molecular supersolids16, as well as assembling ultracold polyatomic molecules.

Flatband λ-Ti3O5 towards extraordinary solar steam generation.

Solar steam interfacial evaporation represents a promising strategy for seawater desalination and wastewater purification owing to its environmentally friendly character1-3. To improve the solar-to-steam generation, most previous efforts have focused on effectively harvesting solar energy over the full solar spectrum4-7. However, the importance of tuning joint densities of states in enhancing solar absorption of photothermal materials is less emphasized. Here we propose a route to greatly elevate joint densities of states by introducing a flat-band electronic structure. Our study reveals that metallic λ-Ti3O5 powders show a high solar absorptivity of 96.4% due to Ti-Ti dimer-induced flat bands around the Fermi level. By incorporating them into three-dimensional porous hydrogel-based evaporators with a conical cavity, an unprecedentedly high evaporation rate of roughly 6.09 kilograms per square metre per hour is achieved for 3.5 weight percent saline water under 1 sun of irradiation without salt precipitation. Fundamentally, the Ti-Ti dimers and U-shaped groove structure exposed on the λ-Ti3O5 surface facilitate the dissociation of adsorbed water molecules and benefit the interfacial water evaporation in the form of small clusters. The present work highlights the crucial roles of Ti-Ti dimer-induced flat bands in enchaining solar absorption and peculiar U-shaped grooves in promoting water dissociation, offering insights into access to cost-effective solar-to-steam generation.

Evaporation of microwave-shielded polar molecules to quantum degeneracy.

Ultracold polar molecules offer strong electric dipole moments and rich internal structure, which makes them ideal building blocks to explore exotic quantum matter1-9, implement quantum information schemes10-12 and test the fundamental symmetries of nature13. Realizing their full potential requires cooling interacting molecular gases deeply into the quantum-degenerate regime. However, the intrinsically unstable collisions between molecules at short range have so far prevented direct cooling through elastic collisions to quantum degeneracy in three dimensions. Here we demonstrate evaporative cooling of a three-dimensional gas of fermionic sodium-potassium molecules to well below the Fermi temperature using microwave shielding. The molecules are protected from reaching short range with a repulsive barrier engineered by coupling rotational states with a blue-detuned circularly polarized microwave. The microwave dressing induces strong tunable dipolar interactions between the molecules, leading to high elastic collision rates that can exceed the inelastic ones by at least a factor of 460. This large elastic-to-inelastic collision ratio allows us to cool the molecular gas to 21 nanokelvin, corresponding to 0.36 times the Fermi temperature. Such cold and dense samples of polar molecules open the path to the exploration of many-body phenomena with strong dipolar interactions.

The Ras GTPase-activating-like protein IQGAP1 bridges Gasdermin D to the ESCRT system to promote IL-1ß release via exosomes.

IL-1ß can exit the cytosol as an exosomal cargo following inflammasome activation in intestinal epithelial cells (IECs) in a Gasdermin D (GSDMD)-dependent manner. The mechanistic connection linking inflammasome activation and the biogenesis of exosomes has so far remained largely elusive. Here, we report the Ras GTPase-activating-like protein IQGAP1 functions as an adaptor, bridging GSDMD to the endosomal sorting complexes required for transport (ESCRT) machinery to promote the biogenesis of pro-IL-1ß-containing exosomes in response to NLPR3 inflammasome activation. We identified IQGAP1 as a GSDMD-interacting protein through a non-biased proteomic analysis. Functional investigation indicated the IQGAP1-GSDMD interaction is required for LPS and ATP-induced exosome release. Further analysis revealed that IQGAP1 serves as an adaptor which bridges GSDMD and associated IL-1ß complex to Tsg101, a component of the ESCRT complex, and enables the packaging of GSDMD and IL-1ß into exosomes. Importantly, this process is dependent on an LPS-induced increase in GTP-bound CDC42, a small GTPase known to activate IQGAP1. Taken together, this study reveals IQGAP1 as a link between inflammasome activation and GSDMD-dependent, ESCRT-mediated exosomal release of IL-1ß.

Phonon stability boundary and deep elastic strain engineering of lattice thermal conductivity.

Recent studies have reported the experimental discovery that nanoscale specimens of even a natural material, such as diamond, can be deformed elastically to as much as 10% tensile elastic strain at room temperature without the onset of permanent damage or fracture. Computational work combining ab initio calculations and machine learning (ML) algorithms has further demonstrated that the bandgap of diamond can be altered significantly purely by reversible elastic straining. These findings open up unprecedented possibilities for designing materials and devices with extreme physical properties and performance characteristics for a variety of technological applications. However, a general scientific framework to guide the design of engineering materials through such elastic strain engineering (ESE) has not yet been developed. By combining first-principles calculations with ML, we present here a general approach to map out the entire phonon stability boundary in six-dimensional strain space, which can guide the ESE of a material without phase transitions. We focus on ESE of vibrational properties, including harmonic phonon dispersions, nonlinear phonon scattering, and thermal conductivity. While the framework presented here can be applied to any material, we show as an example demonstration that the room-temperature lattice thermal conductivity of diamond can be increased by more than 100% or reduced by more than 95% purely by ESE, without triggering phonon instabilities. Such a framework opens the door for tailoring of thermal-barrier, thermoelectric, and electro-optical properties of materials and devices through the purposeful design of homogeneous or inhomogeneous strains.

Computational model for drug research.

This special issue focuses on computational model for drug research regarding drug bioactivity prediction, drug-related interaction prediction, modelling for immunotherapy and modelling for treatment of a specific disease, as conveyed by the following six research and four review articles. Notably, these 10 papers described a wide variety of in-depth drug research from the computational perspective and may represent a snapshot of the wide research landscape.

STAT2 hinders STING intracellular trafficking and reshapes its activation in response to DNA damage.

In cancer cells, endogenous or therapy-induced DNA damage leads to the abnormal presence of DNA in the cytoplasm, which triggers the activation of cGAS (cyclic GMP-AMP synthase) and STING (stimulator of interferon genes). STAT2 suppresses the cGAMP-induced expression of IRF3-dependent genes by binding to STING, blocking its intracellular trafficking, which is essential for the full response to STING activation. STAT2 reshapes STING signaling by inhibiting the induction of IRF3-dependent, but not NF-κB-dependent genes. This noncanonical activity of STAT2 is regulated independently of its tyrosine phosphorylation but does depend on the phosphorylation of threonine 404, which promotes the formation of a STAT2:STING complex that keeps STING bound to the endoplasmic reticulum (ER) and increases resistance to DNA damage. We conclude that STAT2 is a key negative intracellular regulator of STING, a function that is quite distinct from its function as a transcription factor.

Roles of Intramolecular Interactions in the Regulation of TRP Channels.

The transient receptor potential (TRP) channels, classified into six (-A, -V, -P, -C, -M, -ML, -N and -Y) subfamilies, are important membrane sensors and mediators of diverse stimuli including pH, light, mechano-force, temperature, pain, taste, and smell. The mammalian TRP superfamily of 28 members share similar membrane topology with six membrane-spanning helices (S1-S6) and cytosolic N-/C-terminus. Abnormal function or expression of TRP channels is associated with cancer, skeletal dysplasia, immunodeficiency, and cardiac, renal, and neuronal diseases. The majority of TRP members share common functional regulators such as phospholipid PIP2, 2-aminoethoxydiphenyl borate (2-APB), and cannabinoid, while other ligands are more specific, such as allyl isothiocyanate (TRPA1), vanilloids (TRPV1), menthol (TRPM8), ADP-ribose (TRPM2), and ML-SA1 (TRPML1). The mechanisms underlying the gating and regulation of TRP channels remain largely unclear. Recent advances in cryogenic electron microscopy provided structural insights into 19 different TRP channels which all revealed close proximity of the C-terminus with the N-terminus and intracellular S4-S5 linker. Further studies found that some highly conserved residues in these regions of TRPV, -P, -C and -M members mediate functionally critical intramolecular interactions (i.e., within one subunit) between these regions. This review provides an overview on (1) intramolecular interactions in TRP channels and their effect on channel function; (2) functional roles of interplays between PIP2 (and other ligands) and TRP intramolecular interactions; and (3) relevance of the ligand-induced modulation of intramolecular interaction to diseases.

A Bivalent Omicron-Containing Booster Vaccine against Covid-19.

BACKGROUND: The safety and immunogenicity of the bivalent omicron-containing mRNA-1273.214 booster vaccine are not known. METHODS: In this ongoing, phase 2-3 study, we compared the 50-µg bivalent vaccine mRNA-1273.214 (25 µg each of ancestral Wuhan-Hu-1 and omicron B.1.1.529 [BA.1] spike messenger RNAs) with the previously authorized 50-µg mRNA-1273 booster. We administered mRNA-1273.214 or mRNA-1273 as a second booster in adults who had previously received a two-dose (100-µg) primary series and first booster (50-µg) dose of mRNA-1273 (≥3 months earlier). The primary objectives were to assess the safety, reactogenicity, and immunogenicity of mRNA-1273.214 at 28 days after the booster dose. RESULTS: Interim results are presented. Sequential groups of participants received 50 µg of mRNA-1273.214 (437 participants) or mRNA-1273 (377 participants) as a second booster dose. The median time between the first and second boosters was similar for mRNA-1273.214 (136 days) and mRNA-1273 (134 days). In participants with no previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the geometric mean titers of neutralizing antibodies against the omicron BA.1 variant were 2372.4 (95% confidence interval [CI], 2070.6 to 2718.2) after receipt of the mRNA-1273.214 booster and 1473.5 (95% CI, 1270.8 to 1708.4) after receipt of the mRNA-1273 booster. In addition, 50-µg mRNA-1273.214 and 50-µg mRNA-1273 elicited geometric mean titers of 727.4 (95% CI, 632.8 to 836.1) and 492.1 (95% CI, 431.1 to 561.9), respectively, against omicron BA.4 and BA.5 (BA.4/5), and the mRNA-1273.214 booster also elicited higher binding antibody responses against multiple other variants (alpha, beta, gamma, and delta) than the mRNA-1273 booster. Safety and reactogenicity were similar with the two booster vaccines. Vaccine effectiveness was not assessed in this study; in an exploratory analysis, SARS-CoV-2 infection occurred in 11 participants after the mRNA-1273.214 booster and in 9 participants after the mRNA-1273 booster. CONCLUSIONS: The bivalent omicron-containing vaccine mRNA-1273.214 elicited neutralizing antibody responses against omicron that were superior to those with mRNA-1273, without evident safety concerns. (Funded by Moderna; ClinicalTrials.gov number, NCT04927065.).

Ubiquitin-specific proteinase 1 stabilizes PRRSV nonstructural protein Nsp1ß to promote viral replication by regulating K48 ubiquitination.

The porcine reproductive and respiratory syndrome virus (PRRSV) can lead to severe reproductive problems in sows, pneumonia in weaned piglets, and increased mortality, significantly negatively impacting the economy. Post-translational changes are essential for the host-dependent replication and long-term infection of PRRSV. Uncertainty surrounds the function of the ubiquitin network in PRRSV infection. Here, we screened 10 deubiquitinating enzyme inhibitors and found that the ubiquitin-specific proteinase 1 (USP1) inhibitor ML323 significantly inhibited PRRSV replication in vitro. Importantly, we found that USP1 interacts with nonstructural protein 1ß (Nsp1ß) and deubiquitinates its K48 to increase protein stability, thereby improving PRRSV replication and viral titer. Among them, lysine at position 45 is essential for Nsp1ß protein stability. In addition, deficiency of USP1 significantly reduced viral replication. Moreover, ML323 loses antagonism to PRRSV rSD16-K45R. This study reveals the mechanism by which PRRSV recruits the host factor USP1 to promote viral replication, providing a new target for PRRSV defense.IMPORTANCEDeubiquitinating enzymes are critical factors in regulating host innate immunity. The porcine reproductive and respiratory syndrome virus (PRRSV) nonstructural protein 1ß (Nsp1ß) is essential for producing viral subgenomic mRNA and controlling the host immune system. The host inhibits PRRSV proliferation by ubiquitinating Nsp1ß, and conversely, PRRSV recruits the host protein ubiquitin-specific proteinase 1 (USP1) to remove this restriction. Our results demonstrate the binding of USP1 to Nsp1ß, revealing a balance of antagonism between PRRSV and the host. Our research identifies a brand-new PRRSV escape mechanism from the immune response.

SNRMPACDC: computational model focused on Siamese network and random matrix projection for anticancer synergistic drug combination prediction.

Synergistic drug combinations can improve the therapeutic effect and reduce the drug dosage to avoid toxicity. In previous years, an in vitro approach was utilized to screen synergistic drug combinations. However, the in vitro method is time-consuming and expensive. With the rapid growth of high-throughput data, computational methods are becoming efficient tools to predict potential synergistic drug combinations. Considering the limitations of the previous computational methods, we developed a new model named Siamese Network and Random Matrix Projection for AntiCancer Drug Combination prediction (SNRMPACDC). Firstly, the Siamese convolutional network and random matrix projection were used to process the features of the two drugs into drug combination features. Then, the features of the cancer cell line were processed through the convolutional network. Finally, the processed features were integrated and input into the multi-layer perceptron network to get the predicted score. Compared with the traditional method of splicing drug features into drug combination features, SNRMPACDC improved the interpretability of drug combination features to a certain extent. In addition, the introduction of convolutional networks can better extract the potential information in the features. SNRMPACDC achieved the root mean-squared error of 15.01 and the Pearson correlation coefficient of 0.75 in 5-fold cross-validation of regression prediction for response data. In addition, SNRMPACDC achieved the AUC of 0.91 ± 0.03 and the AUPR of 0.62 ± 0.05 in 5-fold cross-validation of classification prediction of synergistic or not. These results are almost better than all the previous models. SNRMPACDC would be an effective approach to infer potential anticancer synergistic drug combinations.

MCFF-MTDDI: multi-channel feature fusion for multi-typed drug-drug interaction prediction.

Adverse drug-drug interactions (DDIs) have become an increasingly serious problem in the medical and health system. Recently, the effective application of deep learning and biomedical knowledge graphs (KGs) have improved the DDI prediction performance of computational models. However, the problems of feature redundancy and KG noise also arise, bringing new challenges for researchers. To overcome these challenges, we proposed a Multi-Channel Feature Fusion model for multi-typed DDI prediction (MCFF-MTDDI). Specifically, we first extracted drug chemical structure features, drug pairs' extra label features, and KG features of drugs. Then, these different features were effectively fused by a multi-channel feature fusion module. Finally, multi-typed DDIs were predicted through the fully connected neural network. To our knowledge, we are the first to integrate the extra label information into KG-based multi-typed DDI prediction; besides, we innovatively proposed a novel KG feature learning method and a State Encoder to obtain target drug pairs' KG-based features which contained more abundant and more key drug-related KG information with less noise; furthermore, a Gated Recurrent Unit-based multi-channel feature fusion module was proposed in an innovative way to yield more comprehensive feature information about drug pairs, effectively alleviating the problem of feature redundancy. We experimented with four datasets in the multi-class and the multi-label prediction tasks to comprehensively evaluate the performance of MCFF-MTDDI for predicting interactions of known-known drugs, known-new drugs and new-new drugs. In addition, we further conducted ablation studies and case studies. All the results fully demonstrated the effectiveness of MCFF-MTDDI.

Drug-drug interaction prediction: databases, web servers and computational models.

In clinical treatment, two or more drugs (i.e. drug combination) are simultaneously or successively used for therapy with the purpose of primarily enhancing the therapeutic efficacy or reducing drug side effects. However, inappropriate drug combination may not only fail to improve efficacy, but even lead to adverse reactions. Therefore, according to the basic principle of improving the efficacy and/or reducing adverse reactions, we should study drug-drug interactions (DDIs) comprehensively and thoroughly so as to reasonably use drug combination. In this review, we first introduced the basic conception and classification of DDIs. Further, some important publicly available databases and web servers about experimentally verified or predicted DDIs were briefly described. As an effective auxiliary tool, computational models for predicting DDIs can not only save the cost of biological experiments, but also provide relevant guidance for combination therapy to some extent. Therefore, we summarized three types of prediction models (including traditional machine learning-based models, deep learning-based models and score function-based models) proposed during recent years and discussed the advantages as well as limitations of them. Besides, we pointed out the problems that need to be solved in the future research of DDIs prediction and provided corresponding suggestions.

Associations of Heavy Metals with Cognitive Function: An Epigenome-Wide View of DNA Methylation and Mediation Analysis.

OBJECTIVE: Exposure to heavy metals has been reported to be associated with impaired cognitive function, but the underlying mechanisms remain unclear. This pilot study aimed to identify key heavy metal elements associated with cognitive function and further explore the potential mediating role of metal-related DNA methylation. METHODS: Blood levels of arsenic, cadmium, lead, copper, manganese, and zinc and genome-wide DNA methylations were separately detected in peripheral blood in 155 older adults. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE). Least absolute shrinkage and selection operator penalized regression and Bayesian kernel machine regression were used to identify metals associated with cognitive function. An epigenome-wide association study examined the DNA methylation profile of the identified metal, and mediation analysis investigated its mediating role. RESULTS: The MMSE scores showed a significant decrease of 1.61 (95% confidence interval [CI]: -2.64, -0.59) with each 1 standard deviation increase in ln-transformed arsenic level; this association was significant in multiple-metal models and dominated the overall negative effect of 6 heavy metal mixture on cognitive function. Seventy-three differentially methylated positions were associated with blood arsenic (p < 1.0 × 10-5). The methylation levels at cg05226051 (annotated to TDRD3) and cg18886932 (annotated to GAL3ST3) mediated 24.8% and 25.5% of the association between blood arsenic and cognitive function, respectively (all p < 0.05). INTERPRETATION: Blood arsenic levels displayed a negative association with the cognitive function of older adults. This finding shows that arsenic-related DNA methylation alterations are critical partial mediators that may serve as potential biomarkers for further mechanism-related studies. ANN NEUROL 2024;96:87-98.