Metabolic liability for weight gain in early adulthood.

While weight gain is associated with a host of chronic illnesses, efforts in obesity have relied on single "snapshots" of body mass index (BMI) to guide genetic and molecular discovery. Here, we study >2,000 young adults with metabolomics and proteomics to identify a metabolic liability to weight gain in early adulthood. Using longitudinal regression and penalized regression, we identify a metabolic signature for weight liability, associated with a 2.6% (2.0%-3.2%, p = 7.5 × 10-19) gain in BMI over ≈20 years per SD higher score, after comprehensive adjustment. Identified molecules specified mechanisms of weight gain, including hunger and appetite regulation, energy expenditure, gut microbial metabolism, and host interaction with external exposure. Integration of longitudinal and concurrent measures in regression with Mendelian randomization highlights the complexity of metabolic regulation of weight gain, suggesting caution in interpretation of epidemiologic or genetic effect estimates traditionally used in metabolic research.

Current Realities of Wilms Tumor Burden and Therapy in Ghana.

BACKGROUND: Between 2005 and 2014, Ghana's Wilms tumor (WT) 2-year disease-free survival of 44% trailed behind that of high-income countries. This study aimed to uncover social determinants of health leading to preventable WT death in Ghana. METHODS: WT patient records (2014-2022) at Korle-Bu Teaching Hospital (KBTH; Ghana) were reviewed retrospectively. Demographics, clinical course, tumor characteristics, and survival were evaluated using t-tests, Pearson Chi-square, and multivariate Cox logistic regression. RESULTS: Of 127 patients identified, 65 were female. Median age was 44 months [IQR 25-66]. Forty-eight patients (38%) presented with distant metastasis (75% lung, 25% liver), which associated with hypoalbuminemia (p = 0.009), caregiver informal employment (p = 0.04), and larger tumors (p = 0.002). Despite neoadjuvant chemotherapy shrinking 84% of tumors, larger initial size associated with incomplete resection (p = 0.046). Of 110 nephrectomies, 31 patients had residual disease, negatively impacting survival (p = 2.7 × 10-5). Twenty-two patients (17%) abandoned treatment (45% before nephrectomy; 55% after nephrectomy), with seven patients ultimately lost to follow-up (LTFU). Decedents represented 43% of stage IV patients compared to 28% in other stages. Event-free survival (EFS) was 60% at 4 years with overall survival (OS) at 67%. CONCLUSIONS: Although Ghana's WT survival has improved, informal employment and distance from KBTH predisposed patients to delayed referral, greater tumor burden, hypoalbuminemia, and lower survival. TYPE OF STUDY: Prognosis Study. LEVEL OF EVIDENCE: II.

Green Fruit Detection with a Small Dataset under a Similar Color Background Based on the Improved YOLOv5-AT.

Green fruit detection is of great significance for estimating orchard yield and the allocation of water and fertilizer. However, due to the similar colors of green fruit and the background of images, the complexity of backgrounds and the difficulty in collecting green fruit datasets, there is currently no accurate and convenient green fruit detection method available for small datasets. The YOLO object detection model, a representative of the single-stage detection framework, has the advantages of a flexible structure, fast inference speed and excellent versatility. In this study, we proposed a model based on the improved YOLOv5 model that combined data augmentation methods to detect green fruit in a small dataset with a background of similar color. In the improved YOLOv5 model (YOLOv5-AT), a Conv-AT block and SA and CA blocks were designed to construct feature information from different perspectives and improve the accuracy by conveying local key information to the deeper layer. The proposed method was applied to green oranges, green tomatoes and green persimmons, and the mAPs were higher than those of other YOLO object detection models, reaching 84.6%, 98.0% and 85.1%, respectively. Furthermore, taking green oranges as an example, a mAP of 82.2% was obtained on the basis of retaining 50% of the original dataset (163 images), which was only 2.4% lower than that obtained when using 100% of the dataset (326 images) for training. Thus, the YOLOv5-AT model combined with data augmentation methods can effectively achieve accurate detection in small green fruit datasets under a similar color background. These research results could provide supportive data for improving the efficiency of agricultural production.

Are children with food allergies more likely to have lower urinary tract symptoms? A case-control study.

INTRODUCTION: There are multiple historic reports linking lower urinary tract symptoms (LUTS) in children with food allergies (FA), but contemporary studies are sparse. The objective of this study was to evaluate a potential link between FA and LUTS in the pediatric population. We hypothesized that children with FAs are more likely to have LUTS. MATERIALS AND METHODS: After local IRB approval, pediatric patients (6-17 years [y]) with FAs proven by positive skin prick and/or serum IgE testing were invited to participate. A control group of pediatric patients without FAs was also recruited. All families/legal guardians signed informed consent, and all children signed written assent. Each participant filled out the Vancouver Symptom Score (VSS), a validated questionnaire for dysfunctional elimination syndrome, and the Pediatric Incontinence Questionnaire (PinQ), a validated quality of life assessment for children with bladder dysfunction. Demographic and clinical information were obtained retrospectively. RESULTS: From 2019-2020, 26 children with FAs and 57 without agreed to participate. Mean age was 9.3 y (IQR 7.9 y-13.5 y). There were no differences in gender, age, or race between the two cohorts. There were no significant differences between the two groups in mean VSS score or mean PinQ score. Four children with FAs (15%) and 15 children without (26%) had VSS score ≥ 11 (p = 0.339), indicating dysfunctional elimination. The median PinQ score was 0 (IQR 0-2) in both cohorts. CONCLUSIONS: This study did not identify an association between FAs and LUTS in a population of pediatric patients with laboratory proven FAs.

Proteomics, Human Environmental Exposure, and Cardiometabolic Risk.

BACKGROUND: The biological mechanisms linking environmental exposures with cardiovascular disease pathobiology are incompletely understood. We sought to identify circulating proteomic signatures of environmental exposures and examine their associations with cardiometabolic and respiratory disease in observational cohort studies. METHODS: We tested the relations of >6500 circulating proteins with 29 environmental exposures across the built environment, green space, air pollution, temperature, and social vulnerability indicators in ≈3000 participants of the CARDIA study (Coronary Artery Risk Development in Young Adults) across 4 centers using penalized and ordinary linear regression. In >3500 participants from FHS (Framingham Heart Study) and JHS (Jackson Heart Study), we evaluated the prospective relations of proteomic signatures of the envirome with cardiovascular disease and mortality using Cox models. RESULTS: Proteomic signatures of the envirome identified novel/established cardiovascular disease-relevant pathways including DNA damage, fibrosis, inflammation, and mitochondrial function. The proteomic signatures of the envirome were broadly related to cardiometabolic disease and respiratory phenotypes (eg, body mass index, lipids, and left ventricular mass) in CARDIA, with replication in FHS/JHS. A proteomic signature of social vulnerability was associated with a composite of cardiovascular disease/mortality (1428 events; FHS: hazard ratio, 1.16 [95% CI, 1.08-1.24]; P=1.77×10-5; JHS: hazard ratio, 1.25 [95% CI, 1.13-1.38]; P=6.38×10-6; hazard ratioexpressed as per 1 SD increase in proteomic signature), robust to adjustment for known clinical risk factors. CONCLUSIONS: Environmental exposures are related to an inflammatory-metabolic proteome, which identifies individuals with cardiometabolic disease and respiratory phenotypes and outcomes. Future work examining the dynamic impact of the environment on human cardiometabolic health is warranted.

Elucidating the role of EPPK1 in lung adenocarcinoma development.

BACKGROUND: We recently found that epiplakin 1 (EPPK1) alterations were present in 12% of lung adenocarcinoma (LUAD) cases and were associated with a poor prognosis in early-stage LUAD when combined with other molecular alterations. This study aimed to identify a probable crucial role for EPPK1 in cancer development. METHODS: EPPK1 mRNA and protein expression was analyzed with clinical variables. Normal bronchial epithelial cell lines were exposed to cigarette smoke for 16 weeks to determine whether EPPK1 protein expression was altered after exposure. Further, we used CRISPR-Cas9 to knock out (KO) EPPK1 in LUAD cell lines and observed how the cancer cells were altered functionally and genetically. RESULTS: EPPK1 protein expression was associated with smoking and poor prognosis in early-stage LUAD. Moreover, a consequential mesenchymal-to-epithelial transition was observed, subsequently resulting in diminished cell proliferation and invasion after EPPK1 KO. RNA sequencing revealed that EPPK1 KO induced downregulation of 11 oncogenes, 75 anti-apoptosis, and 22 angiogenesis genes while upregulating 8 tumor suppressors and 12 anti-cell growth genes. We also observed the downregulation of MYC and upregulation of p53 expression at both protein and RNA levels following EPPK1 KO. Gene ontology enrichment analysis of molecular functions highlighted the correlation of EPPK1 with the regulation of mesenchymal cell proliferation, mesenchymal differentiation, angiogenesis, and cell growth after EPPK1 KO. CONCLUSIONS: Our data suggest that EPPK1 is linked to smoking, epithelial to mesenchymal transition, and the regulation of cancer progression, indicating its potential as a therapeutic target for LUAD.

Immunoproteasomal Processing of IsoLG-Adducted Proteins Is Essential for Hypertension.

BACKGROUND: Hypertension is characterized by CD8+ (cluster differentiation 8) T cell activation and infiltration into peripheral tissues. CD8+ T cell activation requires proteasomal processing of antigenic proteins. It has become clear that isoLG (isolevuglandin)-adduced peptides are antigenic in hypertension; however, IsoLGs inhibit the constitutive proteasome. We hypothesized that immunoproteasomal processing of isoLG-adducts is essential for CD8+ T cell activation and inflammation in hypertension. METHODS: IsoLG adduct processing was studied in murine dendritic cells (DCs), endothelial cells (ECs), and B8 fibroblasts. The role of the proteasome and the immunoproteasome in Ang II (angiotensin II)-induced hypertension was studied in C57BL/6 mice treated with bortezomib or the immunoproteasome inhibitor PR-957 and by studying mice lacking 3 critical immunoproteasome subunits (triple knockout mouse). We also examined hypertension in mice lacking the critical immunoproteasome subunit LMP7 (large multifunctional peptidase 7) specifically in either DCs or ECs. RESULTS: We found that oxidant stress increases the presence of isoLG adducts within MHC-I (class I major histocompatibility complex), and immunoproteasome overexpression augments this. Pharmacological or genetic inhibition of the immunoproteasome attenuated hypertension and tissue inflammation. Conditional deletion of LMP7 in either DCs or ECs attenuated hypertension and vascular inflammation. Finally, we defined the role of the innate immune receptors STING (stimulator of interferon genes) and TLR7/8 (toll-like receptor 7/8) as drivers of LMP7 expression in ECs. CONCLUSIONS: These studies define a previously unknown role of the immunoproteasome in DCs and ECs in CD8+ T cell activation. The immunoproteasome in DCs and ECs is critical for isoLG-adduct presentation to CD8+ T cells, and in the endothelium, this guides homing and infiltration of T cells to specific tissues.

Unbiased characterization of atrial fibrillation phenotypic architecture provides insight to genetic liability and clinically relevant outcomes.

Background: Atrial Fibrillation (AF) is a common and clinically heterogeneous arrythmia. Machine learning (ML) algorithms can define data-driven disease subtypes in an unbiased fashion, but whether the AF subgroups defined in this way align with underlying mechanisms, such as high polygenic liability to AF or inflammation, and associate with clinical outcomes is unclear. Methods: We identified individuals with AF in a large biobank linked to electronic health records (EHR) and genome-wide genotyping. The phenotypic architecture in the AF cohort was defined using principal component analysis of 35 expertly curated and uncorrelated clinical features. We applied an unsupervised co-clustering machine learning algorithm to the 35 features to identify distinct phenotypic AF clusters. The clinical inflammatory status of the clusters was defined using measured biomarkers (CRP, ESR, WBC, Neutrophil %, Platelet count, RDW) within 6 months of first AF mention in the EHR. Polygenic risk scores (PRS) for AF and cytokine levels were used to assess genetic liability of clusters to AF and inflammation, respectively. Clinical outcomes were collected from EHR up to the last medical contact. Results: The analysis included 23,271 subjects with AF, of which 6,023 had available genome-wide genotyping. The machine learning algorithm identified 3 phenotypic clusters that were distinguished by increasing prevalence of comorbidities, particularly renal dysfunction, and coronary artery disease. Polygenic liability to AF across clusters was highest in the low comorbidity cluster. Clinically measured inflammatory biomarkers were highest in the high comorbid cluster, while there was no difference between groups in genetically predicted levels of inflammatory biomarkers. Subgroup assignment was associated with multiple clinical outcomes including mortality, stroke, bleeding, and use of cardiac implantable electronic devices after AF diagnosis. Conclusion: Patient subgroups identified by unsupervised clustering were distinguished by comorbidity burden and associated with risk of clinically important outcomes. Polygenic liability to AF across clusters was greatest in the low comorbidity subgroup. Clinical inflammation, as reflected by measured biomarkers, was lowest in the subgroup with lowest comorbidities. However, there were no differences in genetically predicted levels of inflammatory biomarkers, suggesting associations between AF and inflammation is driven by acquired comorbidities rather than genetic predisposition.

Transformation and environmental chemical characteristics of hazardous trace elements in an 800 t/d waste incineration thermal power plant.

The hazardous trace elements (HTEs) emitted during the municipal solid waste incineration (MSWI) process have been widely concerned. In this work, the bottom ash (BA), heat recovery boiler ash (HA), and ash after desulfurization (SA) were collected to explore the occurrence forms of HTEs in the three types of ash and their relationship with minerals and leaching characteristics. The results show that the volatility of the seven studied HTEs follows the order of Cd, As > Ni, Zn > Pb > Cr, Cu. In the process of BA â†’ HA â†’ SA, the content of Cd, As, Zn, and Pb shows an increasing trend. The seven HTEs are mainly in the forms of chlorides and oxides. There is an obvious relationship between the occurrence forms and simulated existence form of HTEs. SiO2 and CaCO3 are the major mineral components in the three ashes, while SA also contains chlorine-containing compounds which are easily leached out. The risk assessment code and soluble ratio show that HTEs in SA are more leachable than BA and HA, where Cd, Pb and Ni need to be addressed to reduce their impact on soil or water during subsequent landfill treatment of SA.

Targeted Proteomics Reveals Functional Targets for Early Diabetes Susceptibility in Young Adults.

BACKGROUND: The circulating proteome may encode early pathways of diabetes susceptibility in young adults for surveillance and intervention. Here, we define proteomic correlates of tissue phenotypes and diabetes in young adults. METHODS: We used penalized models and principal components analysis to generate parsimonious proteomic signatures of diabetes susceptibility based on phenotypes and on diabetes diagnosis across 184 proteins in >2000 young adults in the CARDIA (Coronary Artery Risk Development in Young Adults study; mean age, 32 years; 44% women; 43% Black; mean body mass index, 25.6±4.9 kg/m2), with validation against diabetes in >1800 individuals in the FHS (Framingham Heart Study) and WHI (Women's Health Initiative). RESULTS: In 184 proteins in >2000 young adults in CARDIA, we identified 2 proteotypes of diabetes susceptibility-a proinflammatory fat proteotype (visceral fat, liver fat, inflammatory biomarkers) and a muscularity proteotype (muscle mass), linked to diabetes in CARDIA and WHI/FHS. These proteotypes specified broad mechanisms of early diabetes pathogenesis, including transorgan communication, hepatic and skeletal muscle stress responses, vascular inflammation and hemostasis, fibrosis, and renal injury. Using human adipose tissue single cell/nuclear RNA-seq, we demonstrate expression at transcriptional level for implicated proteins across adipocytes and nonadipocyte cell types (eg, fibroadipogenic precursors, immune and vascular cells). Using functional assays in human adipose tissue, we demonstrate the association of expression of genes encoding these implicated proteins with adipose tissue metabolism, inflammation, and insulin resistance. CONCLUSIONS: A multifaceted discovery effort uniting proteomics, underlying clinical susceptibility phenotypes, and tissue expression patterns may uncover potentially novel functional biomarkers of early diabetes susceptibility in young adults for future mechanistic evaluation.

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver.

Metabolic dysfunction-associated steatotic liver disease (MASLD) prevalence is increasing in parallel with an obesity pandemic, calling for novel strategies for prevention and treatment. We defined a circulating proteome of human MASLD across ≈7000 proteins in ≈5000 individuals from diverse, at-risk populations across the metabolic health spectrum, demonstrating reproducible diagnostic performance and specifying both known and novel metabolic pathways relevant to MASLD (central carbon and amino acid metabolism, hepatocyte regeneration, inflammation, fibrosis, insulin sensitivity). A parsimonious proteomic signature of MASLD was associated with a protection from MASLD and its related multi-system metabolic consequences in >26000 free-living individuals, with an additive effect to polygenic risk. The MASLD proteome was encoded by genes that demonstrated transcriptional enrichment in liver, with spatial transcriptional activity in areas of steatosis in human liver biopsy and dynamicity for select targets in human liver across stages of steatosis. We replicated several top relations from proteomics and spatial tissue transcriptomics in a humanized "liver-on-a-chip" model of MASLD, highlighting the power of a full translational approach to discovery in MASLD. Collectively, these results underscore utility of blood-based proteomics as a dynamic "liquid biopsy" of human liver relevant to clinical biomarker and mechanistic applications.

Why prescribe antibiotics? A systematic review of knowledge, tension, and motivation among clinicians in low-, middle- and high-income countries.

Medical professionals such as physicians and veterinarians are responsible for appropriate antimicrobial prescription (AMP) and use. Although seemingly straightforward, the factors influencing antibiotic prescription, a category of antimicrobials, are complex. Many studies have been conducted in the past two decades on this subject. As a result, there is a plethora of empirical evidence regarding the factors influencing clinicians' AMP practices. AIM: A systematic review of AMR studies on AMP was conducted, condensing findings according to a combination of the Knowledge, Attitude, and Practice (KAP) and Capacity, Opportunity, Motivation-Behavior (COM-B) models. Review findings were then synthesized and analyzed for policy implementation according to the Consolidated Framework for Implementation Research (CFIR). DESIGN AND METHODOLOGY: A systematic literature review was conducted according to PRISMA guidelines to identify peer-reviewed papers indexed in pre-determined medical science, social sciences, and humanities databases that apply the KAP model in their investigations. Antimicrobial prescription factors were compared and contrasted among low- and middle-income countries (LMICs) and high-income countries (HICs). FINDINGS: The KAP model is a heuristic and structured framework for identifying and classifying respondents' knowledge. However, other than medical knowledge, factors that influence prescription decision-making can be expanded to include attitudes, perception, personal affinities, professional circumstances, relational pressure, and social norms.

Differences in Cardiometabolic Proteins in Pregnancy Prioritize Relevant Targets of Preeclampsia.

BACKGROUND: Preeclampsia is a hypertensive disorder of pregnancy characterized by widespread vascular inflammation. It occurs frequently in pregnancy, often without known risk factors, and has high rates of maternal and fetal morbidity and mortality. Identification of biomarkers that predict preeclampsia and its cardiovascular sequelae before clinical onset, or even before pregnancy, is a critical unmet need for the prevention of adverse pregnancy outcomes. METHODS: We explored differences in cardiovascular proteomics (Olink Explore 384) in 256 diverse pregnant persons across 2 centers (26% Hispanic, 21% Black). RESULTS: We identified significant differences in plasma abundance of markers associated with angiogenesis, blood pressure, cell adhesion, inflammation, and metabolism between individuals delivering with preeclampsia and controls, some of which have not been widely described previously and are not represented in the preeclampsia placental transcriptome. While we observed a broadly similar pattern in early (<34 weeks) versus late (≥34 weeks) preeclampsia, several proteins related to hemodynamic stress, hemostasis, and immune response appeared to be more highly dysregulated in early preeclampsia relative to late preeclampsia. CONCLUSIONS: These results demonstrate the value of performing targeted proteomics using a panel of cardiovascular biomarkers to identify biomarkers relevant to preeclampsia pathophysiology and highlight the need for larger multiomic studies to define modifiable pathways of surveillance and intervention upstream to preeclampsia diagnosis.

A Protocol Driven Approach to Reduce Lengths of Stay for Pediatric Blunt Liver and Spleen Injury Patients.

BACKGROUND: Our institution updated blunt liver and spleen injury (BLSI) protocols in 2019 in adherence to updated American Pediatric Surgery Association (APSA) recommendations. This retrospective study compares resource utilization for pediatric BLSI patients treated under old and updated guidelines. METHODS: BLSI patients without severe non-abdomen injuries aged under 18 treated with prior (04/2015-06/2019) and updated (06/2019-12/2022) guidelines were retrospectively reviewed and compared. Each patient received an adjusted injury severity score (ISS) to control for non-BLSI injuries. Multivariate analysis examined protocol group differences while controlling for adjusted ISS and BLSI grades. Primary outcomes were ICU length of stay (LOS), hospital LOS (analyzed using Cox regression), and patient costs (linear regression). Secondary outcomes include readmission in two weeks and death rates (logistic regression). RESULTS: 176 and 170 BLSI patients were treated with old and updated protocols, respectively. Patient demographics, average BLSI grade, and adjusted ISS were similar in both groups. Patients treated with old protocols indicate decreased hazard, showing significantly more days before ICU discharge (coefficient = -0.3868, p < .0009) and hospital discharge (coefficient = -0.5507, p < .0001). Patient costs (coefficient = 0.0921, p = 0.1874) trend towards being lower in the new protocol. Readmission rates were significantly higher in the new protocol (coefficient = -1.1731, p = 0.0465), and death rates (coefficient = 0.0519, p = 0.9710) were comparable. CONCLUSIONS: BLSI patients treated under new APSA guidelines compared to old guidelines had significant decreases in ICU and hospital LOS, a decreasing trend in costs, comparable death rates, but higher readmission rates. Future studies with larger sample sizes and detailed cost analysis would explore whether updated guidelines reduce patient costs and help elucidate the veracity or potential cause of the increased readmission rates. LEVEL OF EVIDENCE: Level III, Therapeutic/Care Management.

Probiotics for adults with major depressive disorder compared with antidepressants: a systematic review and network meta-analysis.

CONTEXT: Despite recent advances in antidepressants in treating major depression (MDD), their usage is marred by adverse effects and social stigmas. Probiotics may be an efficacious adjunct or standalone treatment, potentially circumventing the aforementioned issues with antidepressants. However, there is a lack of head-to-head clinical trials between these 2 interventions. OBJECTIVE: A systematic review and network meta-analysis was conducted to compare the efficacy and acceptability of these 2 interventions in treating MDD. DATA SOURCES: Six databases and registry platforms for the clinical trial were systematically searched to identify the eligible double-blinded, randomized controlled trials published between 2015 and 2022. DATA EXACTION: Two authors selected independently the placebo-controlled trials of antidepressants and microbiota-targeted interventions (prebiotics, probiotics, and synbiotics) used for the treatment of MDD in adults (≥18 years old). Standardized mean differences (SMDs) of depressive symptom scores from individual trials were pooled for network meta-analysis (PROSPERO no. CRD42020222305). RESULTS: Forty-two eligible trials covering 22 interventions were identified, of which 16 were found to be effective in MDD treatment and the certainty of evidence was moderate to very low. When all trials were considered, compared with placebo, SMDs of interventions ranged from -0.16 (95% credible interval: -0.30, -0.04) for venlafaxine to -0.81 (-1.06, -0.52) for escitalopram. Probiotics were superior to brexpiprazole (SMD [95% credible interval]: -0.42 [-0.68, -0.17]), cariprazine (-0.44 [-0.69, -0.24]), citalopram (-0.37 [-0.66, -0.07]), duloxetine (-0.26, [-0.51, -0.04]), desvenlafaxine (-0.38 [-0.63, -0.14]), ketamine (-0.32 [-0.66, -0.01]), venlafaxine (-0.47 [-0.73, -0.23]), vilazodone (-0.37 [-0.61, -0.12]), vortioxetine (-0.39 [-0.63, -0.15]), and placebo (-0.62 [-0.86, -0.42]), and were noninferior to other antidepressants. In addition, probiotics ranked the second highest in the treatment hierarchy after escitalopram. Long-term treatment (≥8 weeks) using probiotics showed the same tolerability as antidepressants. CONCLUSION: Probiotics, compared with antidepressants and placebo, may be efficacious as an adjunct or standalone therapy for treating MDD. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42020222305.

Proteomics and Precise Exercise Phenotypes in Heart Failure With Preserved Ejection Fraction: A Pilot Study.

BACKGROUND: While exercise impairments are central to symptoms and diagnosis of heart failure with preserved ejection fraction (HFpEF), prior studies of HFpEF biomarkers have mostly focused on resting phenotypes. We combined precise exercise phenotypes with cardiovascular proteomics to identify protein signatures of HFpEF exercise responses and new potential therapeutic targets. METHODS AND RESULTS: We analyzed 277 proteins (Olink) in 151 individuals (N=103 HFpEF, 48 controls; 62±11 years; 56% women) with cardiopulmonary exercise testing with invasive monitoring. Using ridge regression adjusted for age/sex, we defined proteomic signatures of 5 physiological variables involved in HFpEF: peak oxygen uptake, peak cardiac output, pulmonary capillary wedge pressure/cardiac output slope, peak pulmonary vascular resistance, and peak peripheral O2 extraction. Multiprotein signatures of each of the exercise phenotypes captured a significant proportion of variance in respective exercise phenotypes. Interrogating the importance (ridge coefficient magnitude) of specific proteins in each signature highlighted proteins with putative links to HFpEF pathophysiology (eg, inflammatory, profibrotic proteins), and novel proteins linked to distinct physiologies (eg, proteins involved in multiorgan [kidney, liver, muscle, adipose] health) were implicated in impaired O2 extraction. In a separate sample (N=522, 261 HF events), proteomic signatures of peak oxygen uptake and pulmonary capillary wedge pressure/cardiac output slope were associated with incident HFpEF (odds ratios, 0.67 [95% CI, 0.50-0.90] and 1.43 [95% CI, 1.11-1.85], respectively) with adjustment for clinical factors and B-type natriuretic peptides. CONCLUSIONS: The cardiovascular proteome is associated with precision exercise phenotypes in HFpEF, suggesting novel mechanistic targets and potential methods for risk stratification to prevent HFpEF early in its pathogenesis.

COVID-19 mRNA vaccine-mediated antibodies in human breast milk and their association with breast milk microbiota composition.

Newborns can acquire immunological protection to SARS-CoV-2 through vaccine-conferred antibodies in human breast milk. However, there are some concerns around lactating mothers with regards to potential short- and long-term adverse events and vaccine-induced changes to their breast milk microbiome composition, which helps shape the early-life microbiome. Thus, we sought to explore if SARS-CoV-2 mRNA vaccine could change breast milk microbiota and how the changes impact the levels of antibodies in breast milk. We recruited 49 lactating mothers from Hong Kong who received two doses of BNT162b2 vaccine between June 2021 and August 2021. Breast milk samples were self-collected by participants pre-vaccination, one week post-first dose, one week post-second dose, and one month post-second dose. The levels of SARS-CoV-2 spike-specific IgA and IgG in breast milk peaked at one week post-second dose. Subsequently, the levels of both antibodies rapidly waned in breast milk, with IgA levels returning to baseline levels one month post-second dose. The richness and composition of human breast milk microbiota changed dynamically throughout the vaccination regimen, but the abundances of beneficial microbes such as Bifidobacterium species did not significantly change after vaccination. Additionally, we found that baseline breast milk bacterial composition can predict spike-specific IgA levels at one week post-second dose (Area Under Curve: 0.72, 95% confidence interval: 0.58-0.85). Taken together, our results identified specific breast milk microbiota markers associated with high levels of IgA in the breast milk following BNT162b2 vaccine. Furthermore, in lactating mothers, BNT162b2 vaccines did not significantly reduce probiotic species in breast milk.

Baseline gut microbiota and metabolome predict durable immunogenicity to SARS-CoV-2 vaccines.

The role of gut microbiota in modulating the durability of COVID-19 vaccine immunity is yet to be characterised. In this cohort study, we collected blood and stool samples of 121 BNT162b2 and 40 CoronaVac vaccinees at baseline, 1 month, and 6 months post vaccination (p.v.). Neutralisation antibody, plasma cytokine and chemokines were measured and associated with the gut microbiota and metabolome composition. A significantly higher level of neutralising antibody (at 6 months p.v.) was found in BNT162b2 vaccinees who had higher relative abundances of Bifidobacterium adolescentis, Bifidobacterium bifidum, and Roseburia faecis as well as higher concentrations of nicotinic acid (Vitamin B) and γ-Aminobutyric acid (P < 0.05) at baseline. CoronaVac vaccinees with high neutralising antibodies at 6 months p.v. had an increased relative abundance of Phocaeicola dorei, a lower relative abundance of Faecalibacterium prausnitzii, and a higher concentration of L-tryptophan (P < 0.05) at baseline. A higher antibody level at 6 months p.v. was also associated with a higher relative abundance of Dorea formicigenerans at 1 month p.v. among CoronaVac vaccinees (Rho = 0.62, p = 0.001, FDR = 0.123). Of the species altered following vaccination, 79.4% and 42.0% in the CoronaVac and BNT162b2 groups, respectively, recovered at 6 months. Specific to CoronaVac vaccinees, both bacteriome and virome diversity depleted following vaccination and did not recover to baseline at 6 months p.v. (FDR < 0.1). In conclusion, this study identified potential microbiota-based adjuvants that may extend the durability of immune responses to SARS-CoV-2 vaccines.

Proteomic architecture of frailty across the spectrum of cardiovascular disease.

While frailty is a prominent risk factor in an aging population, the underlying biology of frailty is incompletely described. Here, we integrate 979 circulating proteins across a wide range of physiologies with 12 measures of frailty in a prospective discovery cohort of 809 individuals with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation. Our aim was to characterize the proteomic architecture of frailty in a highly susceptible population and study its relation to clinical outcome and systems-wide phenotypes to define potential novel, clinically relevant frailty biology. Proteomic signatures (specifically of physical function) were related to post-intervention outcome in AS, specifying pathways of innate immunity, cell growth/senescence, fibrosis/metabolism, and a host of proteins not widely described in human aging. In published cohorts, the "frailty proteome" displayed heterogeneous trajectories across age (20-100 years, age only explaining a small fraction of variance) and were associated with cardiac and non-cardiac phenotypes and outcomes across two broad validation cohorts (N > 35,000) over ≈2-3 decades. These findings suggest the importance of precision biomarkers of underlying multi-organ health status in age-related morbidity and frailty.

Family Typology for Adults With Type 2 Diabetes: Longitudinal Stability and Validity for Diabetes Management and Well-being.

OBJECTIVE: We validated longitudinally a typology of diabetes-specific family functioning (named Collaborative and Helpful, Satisfied with Low Involvement, Want More Involvement, and Critically Involved) in adults with type 2 diabetes. RESEARCH DESIGN AND METHODS: We conducted k-means cluster analyses with nine dimensions to determine if the typology replicated in a diverse sample and if type assignment was robust to variations in sampling and included dimensions. In a subsample with repeated assessments over 9 months, we examined the stability and validity of the typology. We also applied a multinomial logistic regression approach to make the typology usable at the individual level, like a diagnostic tool. RESULTS: Participants (N = 717) were 51% male, more than one-third reported minority race or ethnicity, mean age was 57 years, and mean hemoglobin A1c (HbA1c) was 7.9% (63 mmol/mol; 8.7% [72 mmol/mol] for the longitudinal subsample). The typology was replicated with respect to the number of types and dimension patterns. Type assignment was robust to sampling variations (97% consistent across simulations). Type had an average 52% stability over time within participants; instability was not explained by measurement error. Over 9 months, type was independently associated with HbA1c, diabetes self-efficacy, diabetes medication adherence, diabetes distress, and depressive symptoms (all P < 0.05). CONCLUSIONS: The typology of diabetes-specific family functioning was replicated, and longitudinal analyses suggest type is more of a dynamic state than a stable trait. However, type varies with diabetes self-management and well-being over time as a consistent independent indicator of outcomes. The typology is ready to be applied to further precision medicine approaches to behavioral and psychosocial diabetes research and care.