Task relevance alters the effect of emotion on congruency judgments during action understanding.

The congruency judgments in action understanding helps individuals make timely adjustments to unexpected occurrence, and this process may be influenced by emotion. Previous research has showed contradictory effect of emotion on conflict processing, possibly due to the degree of relevance between emotion and task. However, to date, no study has systematically manipulated the relevance to explore how emotion affects congruency judgments in action understanding. We employed a cue-target paradigm and controlled the way emotional stimuli were presented on the target interface, setting up three experiments: emotion served as task-irrelevant distractor, task-irrelevant target and task-relevant target. The results showed that when emotion was irrelevant to the task, it impaired congruency judgements performance, regardless of a distractor or a target, while task-relevant emotion facilitated this process. These findings indicate that the impact of emotion on congruency judgements during action understanding depends on the degree of emotion-task relevance.

Identification and validation of NAD+ metabolism-related biomarkers in patients with diabetic peripheral neuropathy.

Background: The mechanism of Nicotinamide Adenine Dinucleotide (NAD+) metabolism-related genes (NMRGs) in diabetic peripheral neuropathy (DPN) is unclear. This study aimed to find new NMRGs biomarkers in DPN. Methods: DPN related datasets GSE95849 and GSE185011 were acquired from the Gene Expression Omnibus (GEO) database. 51 NMRGs were collected from a previous article. To explore NMRGs expression in DPN and control samples, differential expression analysis was completed in GSE95849 to obtain differentially expressed genes (DEGs), and the intersection of DEGs and NMRGs was regarded as DE-NMRGs. Next, a protein-protein interaction (PPI) network based on DE-NMRGs was constructed and biomarkers were screened by eight algorithms. Additionally, Gene Set Enrichment Analysis (GSEA) enrichment analysis was completed, biomarker-based column line graphs were constructed, lncRNA-miRNA-mRNA and competing endogenouse (ce) RNA networks were constructed, and drug prediction was completed. Finally, biomarkers expression validation was completed in GSE95849 and GSE185011. Results: 5217 DEGs were obtained from GSE95849 and 21 overlapping genes of DEGs and NMRGs were DE-NMRGs. Functional enrichment analysis revealed that DE-NMRGs were associated with glycosyl compound metabolic process. The PPI network contained 93 protein-interaction pairs and 21 nodes, with strong interactions between NMNAT1 and NAMPT, NADK and NMNAT3, ENPP3 and NUDT12 as biomarkers based on 8 algorithms. Expression validation suggested that ENPP3 and NUDT12 were upregulated in DPN samples (P < 0.05). Moreover, an alignment diagram with good diagnostic efficacy based on ENPP3 and NUDT12 were identified was constructed. GSEA suggested that ENPP3 was enriched in Toll like receptor (TLR) pathway, NUDT12 was enriched in maturity onset diabetes of the young and insulin pathway. Furthermore, 18 potential miRNAs and 36 Transcription factors (TFs) were predicted and the miRNA-mRNA-TF networks were constructed, suggesting that ENPP3 might regulate hsa-miR-34a-5p by affecting MYNN. The ceRNA network suggested that XLOC_013024 might regulate hsa-let-7b-5p by affecting NUDT12. 15 drugs were predicted, with 8 drugs affecting NUDT12 such as resveratrol, and 13 drugs affecting ENPP3 such as troglitazone. Conclusion: ENPP3 and NUDT12 might play key roles in DPN, which provides reference for further research on DPN.

Ultrastable N-Type Semiconducting Fiber Organic Electrochemical Transistors for Highly Sensitive Biosensors.

Organic electrochemical transistors (OECTs) have attracted increasing attention due to their merits of high transconductance, low operating voltage, and good biocompatibility, ideal for biosensors. However, further advances in their practical applications face challenges of low n-type performance and poor stability. Here, it is demonstrated that wet-spinning the commercially available n-type conjugated polymer poly(benzimidazobenzophenanthroline) (BBL) into highly aligned and crystalline fibers enhances both OECT performance and stability. Although BBL is only soluble in high-boiling-point strong acids, it can be wet-spun into high-quality fibers with adjustable diameters. The BBL fiber OECTs exhibit a record-high area-normalized transconductance (gm,A ) of 2.40 µS µm-2 and over 10 times higher figure-of-merit (µC*) than its thin-film counterparts. More importantly, these fiber OECTs exhibit remarkable stability with no noticeable performance attenuation after 1500 cycles over 4 h operation, outperforming all previously reported n-type OECTs. The superior performance and stability can be attributed to shorter π-π stacking distance and ordered molecular arrangement in the fibers, endowing the BBL fiber OECT-based biosensors with outstanding sensitivity while keeping a miniaturized form factor. This work demonstrates that, beyond new material development, developing new fabrication technology is also crucial for addressing the performance and stability issues in n-type OECTs.

The conductivity of Nb2O5 enhanced by the triple effect of fluorine doping, oxygen vacancy, and carbon modification for improving the lithium storage performance.

In view of the inherent pseudocapacitance, rich redox pairs (Nb5+/Nb4+ and Nb4+/Nb3+), and high lithiation potential (1.0-3.0 V vs Li/Li+), Nb2O5 is considered a promising anode material. However, the inherent low electronic conductivity of Nb2O5 limits its lithium storage performance, and the rate performance after carbon modification is still unsatisfactory because the intrinsic conductivity of Nb2O5 has not been substantially improved. In this experiment, taking the improvement of the intrinsic electrical conductivity of Nb2O5 as the guiding ideology, we prepared F-doped Nb2O5@fluorocarbon composites (F-Nb2O5@FC) with a large number of oxygen vacancies by one-step annealing. As the anode electrode of lithium-ion batteries, the reversible specific capacity of F-Nb2O5@FC reaches 150 mA g-1 at 5 A g-1 after 1100 cycles, and the rate performance is particularly outstanding, with a capacity up to 130 mA g-1 at 16 A g-1, which is far superior to other Nb2O5@carbon-based anode electrodes. Compared with other single conductivity sources of Nb2O5@carbon-based composites, the electrical conductivity of F-Nb2O5@FC composites is greatly improved in many aspects, including the introduction of free electrons by F- doping, the generation of oxygen vacancies, and the provision of a three-dimensional conductive network by FC. Through analytical chemistry (work function, UV-Vis diffuse reflectance spectroscopy, and EIS) and theoretical calculations, it is proved that F-Nb2O5@FC has high electrical conductivity and realizes rapid electron transfer.

Ultra-Fast Single-Nucleotide-Variation Detection Enabled by Argonaute-Mediated Transistor Platform.

"Test-and-go" single-nucleotide variation (SNV) detection within several minutes remains challenging, especially in low-abundance samples, since existing methods face a trade-off between sensitivity and testing speed. Sensitive detection usually relies on complex and time-consuming nucleic acid amplification or sequencing. Here, a graphene field-effect transistor (GFET) platform mediated by Argonaute protein that enables rapid, sensitive, and specific SNV detection is developed. The Argonaute protein provides a nanoscale binding channel to preorganize the DNA probe, accelerating target binding and rapidly recognizing SNVs with single-nucleotide resolution in unamplified tumor-associated microRNA, circulating tumor DNA, virus RNA, and reverse transcribed cDNA when a mismatch occurs in the seed region. An integrated microchip simultaneously detects multiple SNVs in agreement with sequencing results within 5 min, achieving the fastest SNV detection in a "test-and-go" manner without the requirement of nucleic acid extraction, reverse transcription, and amplification.

The bone mesenchymal stem cell-derived exosomal miR-146a-5p promotes diabetic wound healing in mice via macrophage M1/M2 polarization.

A diabetic wound is a refractory disease that afflicts patients globally. MicroRNA-146a-5p (miR-146a-5p) is reported to represent a potential therapeutic target for diabetic wounds. However, microRNA easily degrades in the wound microenvironment. This study extracted bone marrow mesenchymal stem cell (BMSC)-derived exosomes (EXO). Electroporation technology was used to load miR-146a-5p into EXO (labeled as EXO-miR-146a). The endothelial cells (human umbilical vein endothelial cells [HUVECs]) and macrophages were cocultured in transwell chambers in the presence of high glucose. Cell proliferation, migration, and angiogenesis were measured with cell counting kit 8, scratch, and tube forming assays, respectively. Flow cytometry was introduced to validate the biomarker of macrophages and BMSCs. The expression level of macrophage polarization-related proteins and tumor necrosis factor receptor-associated factor 6 (TRAF6) was assessed with western blotting analysis. The full-thickness skin wound model was developed to verify the in vitro results. EXO-miR-146a promoted the proliferation, migration, and angiogenesis of HUVECs in the hyperglycemic state by suppressing the TRAF6 expression in vitro. Additionally, EXO-miR-146a treatment facilitated M2 but inhibited M1 macrophage polarization. Furthermore, EXO-miR-146a enhances reepithelialization, angiogenesis, and M2 macrophage polarization, thereby accelerating diabetic wound healing in vivo. The EXO-miR-146a facilitated M2 macrophage polarization, proliferation, migration, and angiogenesis of HUVECs through TRAF6, thereby ameliorating intractable diabetic wound healing. These results established the basis for using EXO to deliver drugs and revealed mediators for diabetic wound treatment.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases.

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Risk factors associated with periodontal disease and its impact on quality of life among pregnant women.

BACKGROUND: Periodontal disease during pregnancy affects maternal oral health and increases the risk of adverse pregnancy outcomes. However, studies on the risk factors for periodontal disease and its impact on oral health-related quality of life in pregnant women in Taiwan are lacking. This present study aimed to identify the risk factors associated with periodontal disease during pregnancy and examine the relationship of periodontal disease with oral health-related quality of life among pregnant women. METHODS: This study was conducted in a large medical centre in northern Taiwan. Eighty-four participants completed a periodontal examination by dentists as well as structured questionnaires, including the Oral Health Impact Profile-14, demographics, obstetric history, dietary habits, and oral hygiene behaviours. Multivariate logistic regression was used to determine the risk factors associated with periodontal disease and a t-test was used to compare the difference in oral health-related quality of life between pregnant women with and without periodontal disease. RESULTS: Fifty participants (59.5%) had periodontal diseases. Risk factors for periodontal disease included eating out for lunch, consuming beverages, brushing less than three times per day, and not receiving regular professional dental cleanings. The oral health-related quality of life was significantly poorer in pregnant women with periodontal disease than in those without. CONCLUSIONS: The risk factors for periodontal disease, including eating out for lunch, drinking beverages, brushing teeth less, and not regular dental cleaning, provide convincing evidence for pregnant women to maintain good oral hygiene to prevent periodontal disease and improve oral health-related quality of life.

Pregnancy can cause poor mouth health. Expectant mothers with gum disease might face problems such as low birth weight and premature birth. This study found that certain factors can worsen gum disease during pregnancy. These include eating out for lunch, drinking sugary or acidic drinks, brushing their teeth less than three daily, and skipping regular teeth cleaning by a dentist. Pregnant women with gum disease also reported a lower quality of life related to oral health compared to those without it. Healthcare providers should educate pregnant women about oral health maintenance. Emphasize the importance of professional dental cleanings every three months, frequent tooth brushing, avoiding sugary and acidic drinks, and reducing eating out for lunch. Future research should explore additional ways to support pregnant women in this regard.

A closed-loop catalytic nanoreactor system on a transistor.

Precision chemistry demands miniaturized catalytic systems for sophisticated reactions with well-defined pathways. An ideal solution is to construct a nanoreactor system functioning as a chemistry laboratory to execute a full chemical process with molecular precision. However, existing nanoscale catalytic systems fail to in situ control reaction kinetics in a closed-loop manner, lacking the precision toward ultimate reaction efficiency. We find an inter-electrochemical gating effect when operating DNA framework-constructed enzyme cascade nanoreactors on a transistor, enabling in situ closed-loop reaction monitoring and modulation electrically. Therefore, a comprehensive system is developed, encapsulating nanoreactors, analyzers, and modulators, where the gate potential modulates enzyme activity and switches cascade reaction "ON" or "OFF." Such electric field-effect property enhances catalytic efficiency of enzyme by 343.4-fold and enables sensitive sarcosine assay for prostate cancer diagnoses, with a limit of detection five orders of magnitude lower than methodologies in clinical laboratory. By coupling with solid-state electronics, this work provides a perspective to construct intelligent nano-systems for precision chemistry.

Catalytic Hairpin Assembly-Enhanced Graphene Transistor for Ultrasensitive miRNA Detection.

MicroRNAs (miRNAs) have emerged as powerful biomarkers for disease diagnosis and screening. Traditional miRNA analytical techniques are inadequate for point-of-care testing due to their reliance on specialized expertise and instruments. Graphene field-effect transistors (GFETs) offer the prospect of simple and label-free diagnostics. Herein, a GFET biosensor based on tetrahedral DNA nanostructure (TDN)-assisted catalytic hairpin assembly (CHA) reaction (TCHA) has been fabricated and applied to the sensitive and specific detection of miRNA-21. TDN structures are assembled to construct the biosensing interface, facilitating CHA reaction by providing free space and preventing unwanted entanglements, aggregation, and adsorption of probes on the graphene channel. Owing to synergistic effects of TDN-assisted in situ nucleic acid amplification on the sensing surface, as well as inherent signal sensitization of GFETs, the biosensor exhibits ultrasensitive detection of miRNA-21 down to 5.67 × 10-19 M, approximately three orders of magnitude lower than that normally achieved by graphene transistors with channel functionalization of single-stranded DNA probes. In addition, the biosensor demonstrates excellent analytical performance regarding selectivity, stability, and reproducibility. Furthermore, the practicability of the biosensor is verified by analyzing targets in a complex serum environment and cell lysates, showing tremendous potential in bioanalysis and clinical diagnosis.

Effects of Mindfulness-Based Elder Care (MBEC) on symptoms of depression and anxiety and spiritual well-being of institutionalized seniors with disabilities: a randomized controlled trial.

BACKGROUND: Despite the need to incorporate seniors from various settings into mindfulness-based empirical research, issues of geriatric frailties and non-compliance remain. This study aimed to evaluate the effects of a mindfulness-based elder care (MBEC) program on mental health and spiritual well-being among seniors with disabilities in long-term care residential settings. METHODS: This single-blind, randomized controlled trial (RCT) randomly assigned seventy-seven participants into an MBEC group or control group of an eight-week MBEC program. Participants were assessed every four weeks at baseline (T0), mid-intervention (T1), post-intervention (T2) and follow-up (T3) using the Geriatric Depression Scale Short Form (GDS-SF), the State-Trait Anxiety Inventory (STAI) and the Spiritual Well-Being Scale (SWBS), respectively. RESULTS: Linear mixed model (LMM) showed that MBEC participants' mental health improved significantly after completing the intervention; compared with controls, the MBEC group exhibited significantly lower anxiety (state-anxiety at T2; trait-anxiety at T2 and T3) and fewer depressive symptoms. Spiritual well-being was also significantly enhanced compared to that in the control group. CONCLUSIONS: MBEC has positive effects on both mental health and spiritual well-being outcomes among seniors with disabilities. In long-term care facilities, seniors with abilities have the potential to adhere to and engage in activities of a mindfulness-based intervention. This low risk, easily accessible, and effective 8-week program is recommended to be integrated into regular long-term care institutional routines. TRIAL REGISTRATION: This study was registered with Clinical Trial Registry (ClinicalTrials.gov - U.S. National Library of Medicine #NCT05123261. Retrospectively registered on 07/04/2021.). The CONSORT 2010 guidelines were used in this study for properly reporting how the randomized trial was conducted.

Highly Bionic Neurotransmitter-Communicated Neurons Following Integrate-and-Fire Dynamics.

In biological neural networks, chemical communication follows the reversible integrate-and-fire (I&F) dynamics model, enabling efficient, anti-interference signal transport. However, existing artificial neurons fail to follow the I&F model in chemical communication, causing irreversible potential accumulation and neural system dysfunction. Herein, we develop a supercapacitively gated artificial neuron that mimics the reversible I&F dynamics model. Upon upstream neurotransmitters, an electrochemical reaction occurs on a graphene nanowall (GNW) gate electrode of artificial neurons. Charging and discharging the supercapacitive GNWs mimic membrane potential accumulation and recovery, realizing highly efficient chemical communication upon use of acetylcholine down to 2 × 10-10 M. By combining artificial chemical synapses with axon-hillock circuits, the output of neural spikes is realized. With the same neurotransmitter and I&F dynamics, the artificial neuron establishes chemical communication with other artificial neurons and living cells, holding promise as a basic unit to construct a neural network with compatibility to organisms for artificial intelligence and deep human-machine fusion.

Integrating genetics and metabolomics from multi-ethnic and multi-fluid data reveals putative mechanisms for age-related macular degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness in older adults. Investigating shared genetic components between metabolites and AMD can enhance our understanding of its pathogenesis. We conduct metabolite genome-wide association studies (mGWASs) using multi-ethnic genetic and metabolomic data from up to 28,000 participants. With bidirectional Mendelian randomization analysis involving 16,144 advanced AMD cases and 17,832 controls, we identify 108 putatively causal relationships between plasma metabolites and advanced AMD. These metabolites are enriched in glycerophospholipid metabolism, lysophospholipid, triradylcglycerol, and long chain polyunsaturated fatty acid pathways. Bayesian genetic colocalization analysis and a customized metabolome-wide association approach prioritize putative causal AMD-associated metabolites. We find limited evidence linking urine metabolites to AMD risk. Our study emphasizes the contribution of plasma metabolites, particularly lipid-related pathways and genes, to AMD risk and uncovers numerous putative causal associations between metabolites and AMD risk.

The prevalence and risk factors of postpartum depression among women during the early postpartum period: a retrospective secondary data analysis.

OBJECTIVE: Postpartum depression (PPD) is common and detrimental affecting both maternal health and child development. The purpose of this study was to determine the prevalence and factors of PPD screened immediately after delivery. MATERIALS AND METHODS: A retrospective study design using secondary data analysis is applied. Four years of data, containing linkable maternal, neonate and PPD screen records between 2014 and 2018, was retrieved and combined from the electronic medical systems of MacKay Memorial Hospital in Taiwan. For each woman, the PPD screen record contained self-reported depressive symptoms assessed by the Edinburgh Postnatal Depression Scale (EPDS) within 48-72 h after delivery. A set of factors pertaining to maternal, pregnancy and obstetric, neonatal and breastfeeding were selected from the combined data set. RESULTS: In total, 10.2% (1244 of 12,198) of women reported with the symptoms of PPD (EPDS ≥10). Through logistic regression analysis, eight predictors of PPD were identified. Specifically, PPD was shown to be associated with educational level of high school or lower (odds ratio (OR) = 1.57, 95% confidence interval (CI) 1.27-1.93), marital status of unmarried (OR = 1.52, 95% CI 1.18-1.99), unemployed (OR = 1.26, 95% CI 1.11-1.42), Cesarean section (OR = 1.7, 95% CI 1.5-1.93), unplanned pregnancy (OR = 1.38, 95% CI = 1.22-1.57), gestational age at 24-36 weeks (OR = 1.3, 95% CI 1.08-1.56), non-intention of breastfeeding (OR = 1.7, 95% CI 1.18-2.45) and Apgar at 5 min < 7 (OR = 2.18, 95% CI 1.11-4.29). CONCLUSION: Low educational level, unmarried, unemployed, Caesarean section, unplanned pregnancy, preterm delivery, not breastfeeding and low Apgar at 5 min are predictors for postpartum women to develop PPD. These predictors are easily recognized in the clinical environment for patient guidance, support and referral as early as possible to ensure the health and well-being of the mothers and the neonates.

Effects of a biopsychosocial-spiritual group therapy on quality of life among institutionalized older adults with disabilities: A randomized controlled trial.

The traditional biomedical care approach has been unsatisfactory to meet the complex needs of seniors with long-term multimorbidity and irreversible disability, particularly for those living in residential LTC facilities. This study aimed to develop and evaluate the effectiveness of an 8-week biopsychosocial-spiritual (BPS-S) group intervention with the attempt to enhance quality of life (QoL) and meaning in life among senior residents with disability. This single-blind randomized controlled trail was conducted in eight residential LTC facilities. The primary outcome, 'participants' overall and subdomain QoL', and the secondary outcome, 'meaning in life', were repeatedly assessed, including four time points: before, mid- and post-intervention, and at a 1-month follow-up. A generalized linear mixed model (GLMM) was used to assess between-group differences over time. The post-intervention differences indicated significant higher improvement on senior residents' overall and all 4 domains of QoL, as well as their meaning in life, between the baseline and both times of post-intervention and 1-month follow-up. On the other hand, participants' family QoL have improved immediately in the midst of intervention. This study provides preliminary evidence to support the feasibility and effectiveness of an 8-week BPS-S group therapy. We recommend the BPS-S be integrated into routine institutional care activities to help maximize senior residents' own capacity for self-healing, achieve a state of harmonious balance between body, mind, social and spiritual relationships; and in turn, enhance holistic health of this group.

Circulating proteins to predict COVID-19 severity.

Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict COVID-19 severity in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different COVID-19 severity were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of COVID-19 severity. Further research is needed to understand how to incorporate protein measurement into clinical care.

Predicting ExWAS findings from GWAS data: a shorter path to causal genes.

GWAS has identified thousands of loci associated with disease, yet the causal genes within these loci remain largely unknown. Identifying these causal genes would enable deeper understanding of the disease and assist in genetics-based drug development. Exome-wide association studies (ExWAS) are more expensive but can pinpoint causal genes offering high-yield drug targets, yet suffer from a high false-negative rate. Several algorithms have been developed to prioritize genes at GWAS loci, such as the Effector Index (Ei), Locus-2-Gene (L2G), Polygenic Prioritization score (PoPs), and Activity-by-Contact score (ABC) and it is not known if these algorithms can predict ExWAS findings from GWAS data. However, if this were the case, thousands of associated GWAS loci could potentially be resolved to causal genes. Here, we quantified the performance of these algorithms by evaluating their ability to identify ExWAS significant genes for nine traits. We found that Ei, L2G, and PoPs can identify ExWAS significant genes with high areas under the precision recall curve (Ei: 0.52, L2G: 0.37, PoPs: 0.18, ABC: 0.14). Furthermore, we found that for every unit increase in the normalized scores, there was an associated 1.3-4.6-fold increase in the odds of a gene reaching exome-wide significance (Ei: 4.6, L2G: 2.5, PoPs: 2.1, ABC: 1.3). Overall, we found that Ei, L2G, and PoPs can anticipate ExWAS findings from widely available GWAS results. These techniques are therefore promising when well-powered ExWAS data are not readily available and can be used to anticipate ExWAS findings, allowing for prioritization of genes at GWAS loci.

Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity.

Obesity is a major risk factor for Coronavirus disease (COVID-19) severity; however, the mechanisms underlying this relationship are not fully understood. As obesity influences the plasma proteome, we sought to identify circulating proteins mediating the effects of obesity on COVID-19 severity in humans. Here, we screened 4,907 plasma proteins to identify proteins influenced by body mass index using Mendelian randomization. This yielded 1,216 proteins, whose effect on COVID-19 severity was assessed, again using Mendelian randomization. We found that an s.d. increase in nephronectin (NPNT) was associated with increased odds of critically ill COVID-19 (OR = 1.71, P = 1.63 × 10-10). The effect was driven by an NPNT splice isoform. Mediation analyses supported NPNT as a mediator. In single-cell RNA-sequencing, NPNT was expressed in alveolar cells and fibroblasts of the lung in individuals who died of COVID-19. Finally, decreasing body fat mass and increasing fat-free mass were found to lower NPNT levels. These findings provide actionable insights into how obesity influences COVID-19 severity.

Increasing serum iron levels and their role in the risk of infectious diseases: a Mendelian randomization approach.

OBJECTIVES: Increased iron stores have been associated with elevated risks of different infectious diseases, suggesting that iron supplementation may increase the risk of infections. However, these associations may be biased by confounding or reverse causation. This is important, since up to 19% of the population takes iron supplementation. We used Mendelian randomization (MR) to bypass these biases and estimate the causal effect of iron on infections. METHODS: As instrumental variables, we used genetic variants associated with iron biomarkers in two genome-wide association studies (GWASs) of European ancestry participants. For outcomes, we used GWAS results from the UK Biobank, FinnGen, the COVID-19 Host Genetics Initiative or 23andMe, for seven infection phenotypes: 'any infections', combined, COVID-19 hospitalization, candidiasis, pneumonia, sepsis, skin and soft tissue infection (SSTI) and urinary tract infection (UTI). RESULTS: Most of our analyses showed increasing iron (measured by its biomarkers) was associated with only modest changes in the odds of infectious outcomes, with all 95% odds ratios confidence intervals within the 0.88 to 1.26 range. However, for the three predominantly bacterial infections (sepsis, SSTI, UTI), at least one analysis showed a nominally elevated risk with increased iron stores (P <0.05). CONCLUSION: Using MR, we did not observe an increase in risk of most infectious diseases with increases in iron stores. However for bacterial infections, higher iron stores may increase odds of infections. Hence, using genetic variation in iron pathways as a proxy for iron supplementation, iron supplements are likely safe on a population level, but we should continue the current practice of conservative iron supplementation during bacterial infections or in those at high risk of developing them.

Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases.

Metabolic processes can influence disease risk and provide therapeutic targets. By conducting genome-wide association studies of 1,091 blood metabolites and 309 metabolite ratios, we identified associations with 690 metabolites at 248 loci and associations with 143 metabolite ratios at 69 loci. Integrating metabolite-gene and gene expression information identified 94 effector genes for 109 metabolites and 48 metabolite ratios. Using Mendelian randomization (MR), we identified 22 metabolites and 20 metabolite ratios having estimated causal effect on 12 traits and diseases, including orotate for estimated bone mineral density, α-hydroxyisovalerate for body mass index and ergothioneine for inflammatory bowel disease and asthma. We further measured the orotate level in a separate cohort and demonstrated that, consistent with MR, orotate levels were positively associated with incident hip fractures. This study provides a valuable resource describing the genetic architecture of metabolites and delivers insights into their roles in common diseases, thereby offering opportunities for therapeutic targets.