Why Does Monoamine Oxidase (MAO) Catalyze the Oxidation of Some Tetrahydropyridines?

Results pertaining to the mechanism of the oxidation of the tertiary amine 1-methyl-4-(1-methyl-1-H-pyrrol-2-yl)-1,2,3,6-tetrahydropyridine (MMTP, a close analog of the Parkinsonism inducing compound MPTP) by 3-methyllumiflavin (3MLF), a chemical model for the FAD cofactor of monoamine oxidase, are reported. MMTP and related compounds are among the few tertiary amines that are monoamine oxidase B (MAO-B) substrates. The MMTP/3MLF reaction is catalytic in the presence of O2 and the results under anaerobic conditions strongly suggest the involvement of radical intermediates, consistent with a single electron transfer mechanism. These observations support a new hypothesis to explain the MAO-catalyzed oxidations of amines. In general, electron transfer is thermodynamically unfavorable, and as a result, most 1° and 2° amines react via one of the currently accepted polar pathways. Steric constraints prevent 3° amines from reacting via a polar pathway. Those select 3° amines that are MAO substrates possess certain structural features (e. g., a C-H bond that is α- both to nitrogen and a C=C) that dramatically lower the pKa of the corresponding radical cation. Consequently, the thermodynamically unfavorable electron transfer equilibrium is driven towards products by an extremely favorable deprotonation step in the context of Le Chatelier's principle.

A data-driven approach to improve wellness and reduce recurrence in cancer survivors.

For many cancer survivors, toxic side effects of treatment, lingering effects of the aftermath of disease and cancer recurrence adversely affect quality of life (QoL) and reduce healthspan. Data-driven approaches for quantifying and improving wellness in healthy individuals hold great promise for improving the lives of cancer survivors. The data-driven strategy will also guide personalized nutrition and exercise recommendations that may help prevent cancer recurrence and secondary malignancies in survivors.

microRNA-33 controls hunger signaling in hypothalamic AgRP neurons.

AgRP neurons drive hunger, and excessive nutrient intake is the primary driver of obesity and associated metabolic disorders. While many factors impacting central regulation of feeding behavior have been established, the role of microRNAs in this process is poorly understood. Utilizing unique mouse models, we demonstrate that miR-33 plays a critical role in the regulation of AgRP neurons, and that loss of miR-33 leads to increased feeding, obesity, and metabolic dysfunction in mice. These effects include the regulation of multiple miR-33 target genes involved in mitochondrial biogenesis and fatty acid metabolism. Our findings elucidate a key regulatory pathway regulated by a non-coding RNA that impacts hunger by controlling multiple bioenergetic processes associated with the activation of AgRP neurons, providing alternative therapeutic approaches to modulate feeding behavior and associated metabolic diseases.

Timing of selective serotonin reuptake inhibitor use and risk for preterm birth and related adverse events: with a consideration of the COVID-19 pandemic period.

OBJECTIVE: There is uncertainty around the safety of SSRIs for treating depression during pregnancy. Nevertheless, the use of SSRIs has been gradually increasing, especially during the COVID-19 pandemic period. We aimed to (1) characterize maternal depression rate and use of SSRIs in a recent 10-year period, (2) address confounding by indication, as well as socioeconomic and environmental factors, and (3) evaluate associations of the timing of SSRI exposure in pregnancy with risk for preterm birth (PTB), low birthweight (LBW), and small for gestational age (SGA) infants among women with depression before pregnancy. METHODS: We conducted propensity score-adjusted regression to calculate odds ratios (ORs) of PTB, LBW, and SGA. We accounted for maternal/pregnancy characteristics, comorbidity, depression severity, time of delivery, social vulnerability, and rural residence. RESULTS: There were 50.3% and 40.3% increases in the prevalence rate of prenatal depression and prenatal SSRI prescription rate during the pandemic. We identified women with depression ≤180 days before pregnancy (n = 8406). Women with no SSRI order during pregnancy (n = 3760) constituted the unexposed group. The late SSRI exposure group consisted of women with an SSRI order after the first trimester (n = 3759). The early-only SSRI exposure group consisted of women with SSRI orders only in the first trimester (n = 887). The late SSRI exposure group had an increased risk of PTB of OR = 1.5 ([1.2,1.8]) and LBW of OR = 1.5 ([1.2,2.0]), relative to the unexposed group. Associations between late SSRI exposure and risk of PTB/LBW were similar among a subsample of patients who delivered during the pandemic. CONCLUSIONS: These findings suggest an association between PTB/LBW and SSRI exposure is dependent on exposure timing during pregnancy. Small for gestational age is not associated with SSRI exposure.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop.

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

Novel Processes Associated with the Repair of Interstrand Cross-Links Derived from Abasic Sites in Duplex DNA: Roles for the Base Excision Repair Glycosylase NEIL3 and the SRAP Protein HMCES.

Recent studies have defined a novel pathway for the repair of interstrand cross-links derived from the reaction of an adenine residue with an apurinic/apyrimidinic (AP) site on the opposing strand of DNA (dA-AP ICL). Stalling of a replication fork at the dA-AP ICL triggers TRAIP-dependent ubiquitylation of the CMG helicase that recruits the base excision repair glycosylase NEIL3 to the lesion. NEIL3 unhooks the dA-AP ICL to regenerate the native adenine residue on one strand and an AP site on the other strand. Covalent capture of the abasic site by the SRAP protein HMCES protects against genomic instability that would result from cleavage of the abasic site in the context of single-stranded DNA at the replication fork. After repair synthesis moves the HMCES-AP adduct into the context of double-stranded DNA, the DNA-protein cross-link is resolved by a nonproteolytic mechanism involving dissociation of thiazolidine attachment. The AP site in duplex DNA is then repaired by the base excision repair pathway.

The transition from genomics to phenomics in personalized population health.

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Obesity and lifespan, a complex tango.

Obesity and aging share comorbidities, phenotypes, and deleterious effects on health that are associated with chronic diseases. However, distinct features set them apart, with underlying biology that should be explored and exploited, especially given the demographic shifts and the obesity epidemic that the world is facing.

Correction: Reproducible big data science: A case study in continuous FAIRness.

[This corrects the article DOI: 10.1371/journal.pone.0213013.].

Survey of organ-derived small extracellular vesicles and particles (sEVPs) to identify selective protein markers in mouse serum.

Extracellular vesicles and particles (EVPs) are secreted by organs across the body into different circulatory systems, including the bloodstream, and reflect pathophysiologic conditions of the organ. However, the heterogeneity of EVPs in the blood makes it challenging to determine their organ of origin. We hypothesized that small (s)EVPs (<100 nm in diameter) in the bloodstream carry distinctive protein signatures associated with each originating organ, and we investigated this possibility by studying the proteomes of sEVPs produced by six major organs (brain, liver, lung, heart, kidney, fat). We found that each organ contained distinctive sEVP proteins: 68 proteins were preferentially found in brain sEVPs, 194 in liver, 39 in lung, 15 in heart, 29 in kidney, and 33 in fat. Furthermore, we isolated sEVPs from blood and validated the presence of sEVP proteins associated with the brain (DPP6, SYT1, DNM1L), liver (FABPL, ARG1, ASGR1/2), lung (SFPTA1), heart (CPT1B), kidney (SLC31), and fat (GDN). We further discovered altered levels of these proteins in serum sEVPs prepared from old mice compared to young mice. In sum, we have cataloged sEVP proteins that can serve as potential biomarkers for organ identification in serum and show differential expression with age.

Integrated unbiased multiomics defines disease-independent placental clusters in common obstetrical syndromes.

BACKGROUND: Placental dysfunction, a root cause of common syndromes affecting human pregnancy, such as preeclampsia (PE), fetal growth restriction (FGR), and spontaneous preterm delivery (sPTD), remains poorly defined. These common, yet clinically disparate obstetrical syndromes share similar placental histopathologic patterns, while individuals within each syndrome present distinct molecular changes, challenging our understanding and hindering our ability to prevent and treat these syndromes. METHODS: Using our extensive biobank, we identified women with severe PE (n = 75), FGR (n = 40), FGR with a hypertensive disorder (FGR + HDP; n = 33), sPTD (n = 72), and two uncomplicated control groups, term (n = 113), and preterm without PE, FGR, or sPTD (n = 16). We used placental biopsies for transcriptomics, proteomics, metabolomics data, and histological evaluation. After conventional pairwise comparison, we deployed an unbiased, AI-based similarity network fusion (SNF) to integrate the datatypes and identify omics-defined placental clusters. We used Bayesian model selection to compare the association between the histopathological features and disease conditions vs SNF clusters. RESULTS: Pairwise, disease-based comparisons exhibited relatively few differences, likely reflecting the heterogeneity of the clinical syndromes. Therefore, we deployed the unbiased, omics-based SNF method. Our analysis resulted in four distinct clusters, which were mostly dominated by a specific syndrome. Notably, the cluster dominated by early-onset PE exhibited strong placental dysfunction patterns, with weaker injury patterns in the cluster dominated by sPTD. The SNF-defined clusters exhibited better correlation with the histopathology than the predefined disease groups. CONCLUSIONS: Our results demonstrate that integrated omics-based SNF distinctively reclassifies placental dysfunction patterns underlying the common obstetrical syndromes, improves our understanding of the pathological processes, and could promote a search for more personalized interventions.

Effect of COVID-19 vaccination and booster on maternal-fetal outcomes: a retrospective cohort study.

BACKGROUND: COVID-19 in pregnant people increases the risk for poor maternal-fetal outcomes. However, COVID-19 vaccination hesitancy remains due to concerns over the vaccine's potential effects on maternal-fetal outcomes. Here we examine the impact of COVID-19 vaccination and boosters on maternal SARS-CoV-2 infections and birth outcomes. METHODS: This was a retrospective multicentre cohort study on the impact of COVID-19 vaccination on maternal-fetal outcomes for people who delivered (n=106 428) at Providence St Joseph Health across seven western US states from Jan 26, 2021 to Oct 26, 2022. Cohorts were defined by vaccination status at delivery: vaccinated (n=35 926; two or more doses of mRNA-1273 Moderna or BNT162b2 Pfizer-BioNTech), unvaccinated (n=55 878), unvaccinated propensity score matched (n=16 771), boosted (n=10 927; three or more doses), vaccinated unboosted (n=13 243; two doses only), and vaccinated unboosted with propensity score matching (n=4414). We built supervised machine learning classification models, which we used to determine which people were more likely to be vaccinated or boosted at delivery. The primary outcome was maternal SARS-CoV-2 infection. COVID-19 vaccination status at delivery, COVID-19-related health care, preterm birth, stillbirth, and very low birthweight were evaluated as secondary outcomes. FINDINGS: Vaccinated people were more likely to conceive later in the pandemic, have commercial insurance, be older, live in areas with lower household composition vulnerability, and have a higher BMI than unvaccinated people. Boosted people were more likely to have more days since receiving the second COVID-19 vaccine dose, conceive earlier in the pandemic, have commercial insurance, be older, and live in areas with lower household composition vulnerability than vaccinated unboosted people. Vaccinated pregnant people had lower rates of COVID-19 during pregnancy (4·0%) compared with unvaccinated matched people (5·3%; p<0·0001). COVID-19 rates were even lower in boosted people (3·2%) compared with vaccinated unboosted matched people (5·6%; p<0·0001). Vaccinated people were also less likely to have a preterm birth (7·9%; p<0·0001), stillbirth (0·3%; p<0·0002), or very low birthweight neonate (1·0%; p<0·0001) compared with unvaccinated matched people (preterm birth 9·4%; stillbirth 0·6%; very low birthweight 1·5%). Boosted people were less likely to have a stillbirth (0·3%; p<0·025) and have no differences in rates of preterm birth (7·6%; p=0·090) or very low birthweight neonates (0·8%; p=0·092) compared with vaccinated unboosted matched people (stillbirth 0·5%; preterm birth 8·4%; very low birthweight 1·1%). INTERPRETATION: COVID-19 vaccination protects against adverse maternal-fetal outcomes, with booster doses conferring additional protection. Pregnant people should be high priority for vaccination and stay up to date with their COVID-19 vaccination schedule. FUNDING: National Institute for Child Health & Human Development and the William O and K Carole Ellison Foundation.

Lifespan-extending interventions induce consistent patterns of fatty acid oxidation in mouse livers.

Aging manifests as progressive deteriorations in homeostasis, requiring systems-level perspectives to investigate the gradual molecular dysregulation of underlying biological processes. Here, we report systemic changes in the molecular regulation of biological processes under multiple lifespan-extending interventions. Differential Rank Conservation (DIRAC) analyses of mouse liver proteomics and transcriptomics data show that mechanistically distinct lifespan-extending interventions (acarbose, 17α-estradiol, rapamycin, and calorie restriction) generally tighten the regulation of biological modules. These tightening patterns are similar across the interventions, particularly in processes such as fatty acid oxidation, immune response, and stress response. Differences in DIRAC patterns between proteins and transcripts highlight specific modules which may be tightened via augmented cap-independent translation. Moreover, the systemic shifts in fatty acid metabolism are supported through integrated analysis of liver transcriptomics data with a mouse genome-scale metabolic model. Our findings highlight the power of systems-level approaches for identifying and characterizing the biological processes involved in aging and longevity.

Prolonged fasting times reap greater geroprotective effects when combined with caloric restriction in adult female mice.

Emerging new evidence highlights the importance of prolonged daily fasting periods for the health and survival benefits of calorie restriction (CR) and time-restricted feeding (TRF) in male mice; however, little is known about the impact of these feeding regimens in females. We placed 14-month-old female mice on five different dietary regimens, either CR or TRF with different feeding windows, and determined the effects of these regimens on physiological responses, progression of neoplasms and inflammatory diseases, serum metabolite levels, and lifespan. Compared with TRF feeding, CR elicited a robust systemic response, as it relates to energetics and healthspan metrics, a unique serum metabolomics signature in overnight fasted animals, and was associated with an increase in lifespan. These results indicate that daytime (rest-phase) feeding with prolonged fasting periods initiated late in life confer greater benefits when combined with imposed lower energy intake.

Acute noise is harmful on the anti-predator behaviour of commercially important juvenile coral reef fishes.

Fish stock enhancement has been utilised in Taiwan for more than 30 years, yet the impacts of anthropogenic noise on the enhancement programs remain unknown. Anthropogenic noise can induce physiological and behavioural changes in many marine fishes. Therefore, we investigated the effects of acute boat noise (from stock enhancement release sites) and chronic noise (from aquaculture processes) on the anti-predator behaviour in three juvenile reef fishes: Epinephelus coioides, Amphiprion ocellaris and Neoglyphidodon melas. We exposed fish to aquaculture noise, boat noise and a combination of both, followed by a predator scare and documented kinematic variables (response latency, response distance, response speed and response duration). For the grouper E. coioides, their response latency decreased in the presence of acute noise, while their response duration increased in the presence of both chronic and acute noise. Among the anemonefish A. ocellaris, all variables remained unaffected by chronic noise, whereas acute noise increased the response distance and response speed. In the case of the black damselfish N. melas, chronic noise decreased the response speed, while acute noise decreased the response latency and response duration. Our results indicate that acute noise had a stronger influence on anti-predator behaviour than chronic noise. This study suggests that acute noise levels at restocking release sites can impact anti-predator behaviour in fishes, potentially altering fitness and likelihood of survival. Such negative effects and interspecific differences must be considered when restocking fish populations.

Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention.

Multiomic profiling can reveal population heterogeneity for both health and disease states. Obesity drives a myriad of metabolic perturbations and is a risk factor for multiple chronic diseases. Here we report an atlas of cross-sectional and longitudinal changes in 1,111 blood analytes associated with variation in body mass index (BMI), as well as multiomic associations with host polygenic risk scores and gut microbiome composition, from a cohort of 1,277 individuals enrolled in a wellness program (Arivale). Machine learning model predictions of BMI from blood multiomics captured heterogeneous phenotypic states of host metabolism and gut microbiome composition better than BMI, which was also validated in an external cohort (TwinsUK). Moreover, longitudinal analyses identified variable BMI trajectories for different omics measures in response to a healthy lifestyle intervention; metabolomics-inferred BMI decreased to a greater extent than actual BMI, whereas proteomics-inferred BMI exhibited greater resistance to change. Our analyses further identified blood analyte-analyte associations that were modified by metabolomics-inferred BMI and partially reversed in individuals with metabolic obesity during the intervention. Taken together, our findings provide a blood atlas of the molecular perturbations associated with changes in obesity status, serving as a resource to quantify metabolic health for predictive and preventive medicine.

Gene body DNA hydroxymethylation restricts the magnitude of transcriptional changes during aging.

DNA hydroxymethylation (5hmC) is the most abundant oxidative derivative of DNA methylation (5mC) and is typically enriched at enhancers and gene bodies of transcriptionally active and tissue-specific genes. Although aberrant genomic 5hmC has been implicated in many age-related diseases, the functional role of the modification in aging remains largely unknown. Here, we report that 5hmC is stably enriched in multiple aged organs. Using the liver and cerebellum as model organs, we show that 5hmC accumulates in gene bodies associated with tissue-specific function and thereby restricts the magnitude of gene expression changes during aging. Mechanistically, we found that 5hmC decreases binding affinity of splicing factors compared to unmodified cytosine and 5mC, and is correlated with age-related alternative splicing events, suggesting RNA splicing as a potential mediator of 5hmC's transcriptionally restrictive function. Furthermore, we show that various age-related contexts, such as prolonged quiescence and senescence, are partially responsible for driving the accumulation of 5hmC with age. We provide evidence that this age-related function is conserved in mouse and human tissues, and further show that the modification is altered by regimens known to modulate lifespan. Our findings reveal that 5hmC is a regulator of tissue-specific function and may play a role in regulating longevity.

microRNA-33 deficiency in macrophages enhances autophagy, improves mitochondrial homeostasis, and protects against lung fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and ultimately fatal disease. Recent findings have shown a marked metabolic reprogramming associated with changes in mitochondrial homeostasis and autophagy during pulmonary fibrosis. The microRNA-33 (miR-33) family of microRNAs (miRNAs) encoded within the introns of sterol regulatory element binding protein (SREBP) genes are master regulators of sterol and fatty acid (FA) metabolism. miR-33 controls macrophage immunometabolic response and enhances mitochondrial biogenesis, FA oxidation, and cholesterol efflux. Here, we show that miR-33 levels are increased in bronchoalveolar lavage (BAL) cells isolated from patients with IPF compared with healthy controls. We demonstrate that specific genetic ablation of miR-33 in macrophages protects against bleomycin-induced pulmonary fibrosis. The absence of miR-33 in macrophages improves mitochondrial homeostasis and increases autophagy while decreasing inflammatory response after bleomycin injury. Notably, pharmacological inhibition of miR-33 in macrophages via administration of anti-miR-33 peptide nucleic acids (PNA-33) attenuates fibrosis in different in vivo and ex vivo mice and human models of pulmonary fibrosis. These studies elucidate a major role of miR-33 in macrophages in the regulation of pulmonary fibrosis and uncover a potentially novel therapeutic approach to treat this disease.