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Magis, A. T.

Publications and source records attributed to Magis, A. T..

10 recordsLinked to original sources

Novel Oral LNAD+ Increases Intracellular NAD and Metabolic Flux Without Elevating Circulating NAD: Evidence from a Randomized Controlled Trial

Declines in nicotinamide adenine dinucleotide (NAD+) are linked to metabolic stress accompanying aging and disease. While precursor-based approaches elevate systemic NAD, their clinical translation can be constrained by biosynthetic bottlenecks and first-pass metabolism. RENEWAL-NAD+ (ClinicalTrials.gov NCT07336836; retrospectively registered 01/04/2026) was a double-blind, randomized, placebo-controlled Phase 0/1b trial in healthy adults aged 45-75 years (60 randomized; primary analysis n=50) evaluating 5 days of oral LathMized(R) NAD+ (LNAD+), a physicochemically modulated formulation that alters the supramolecular organization and solution behavior of NAD+ while preserving its native molecular structure. The primary endpoints were change in intracellular NAD (icNAD), measured in whole blood, and circulating NAD (cirNAD), measured in separated plasma, relative to baseline. LNAD+ produced a rapid and pronounced increase in icNAD, with a 53% elevation versus placebo at Day 6 (p=5.48e-14; Hedges g=3.66), while cirNAD was unchanged (p=0.60), demonstrating compartment-selective augmentation. Plasma NAD catabolites increased substantially (1-methyl-nicotinamide, MeNAM p=5.39e-13; N1-methyl-2-pyridone-5-carboxamide, 2PY p=2.95e-16), consistent with downstream engagement of NAD metabolic flux. Exploratory analyses identified non-overlapping correlates for the two compartments (cirNAD tracking inflammatory and metabolic markers, icNAD tracking red blood cell indices and NAM). Treatment was very well tolerated: symptom incidence was comparable between groups (p=0.68), only one mild adverse event (nausea, Grade 1) occurred in the LNAD+ arm, and no secondary clinical, vital-sign, wellbeing, or wearable-derived endpoint survived multiplicity correction. These data demonstrate rapid intracellular NAD augmentation after oral LNAD+ dosing with pharmacodynamic evidence of downstream metabolism, compartment-specific physiological signatures, and a favorable short-term safety profile, with exploratory multi-omic analyses ongoing.

systems biology↗

A conserved immune dysregulation is associated with infection severity, risk factors prior to infection, and treatment response

Older age, being male, obesity, smoking, and comorbidities (e.g., diabetes, asthma) are associated with the increased risk for severe infections. We hypothesized that there is a conserved common immune dysregulation across these risk factors. We integrated single cell and bulk transcriptomic data and proteomic data from 12,026 blood samples across 68 cohorts to test this hypothesis. We found that our previously described 42-gene Severe-or-Mild (SoM) signature, is associated with each of these risk factors prior to infection. Furthermore, we found this conserved immune signature is modifiable using immunomodulatory drugs and lifestyle changes. The SoM score predicted patients with sepsis that would be harmed from hydrocortisone treatment, and patients with asthma that will not respond to monoclonal antibody treatment. Finally, the SoM score was associated with all-cause mortality. The SoM signature has the potential to redefine the immunologic framing of baseline immune state and response to chronic, subacute, and acute illnesses.

immunology↗

APMAT analysis reveals the association between CD8 T cell receptors, cognate antigen, and T cell phenotype and persistence

Elucidating the relationships between a class I peptide antigen, a CD8 T cell receptor (TCR) specific to that antigen, and the T cell phenotype that emerges following antigen stimulation, remains a mostly unsolved problem, largely due to the lack of large data sets that can be mined to resolve such relationships. Here, we describe Antigen-TCR Pairing and Multiomic Analysis of T-cells (APMAT), an integrated experimental-computational framework designed for the high-throughput capture and analysis of CD8 T cells, with paired antigen, TCR sequence, and single-cell transcriptome. Starting with 951 putative antigens representing a comprehensive survey of the SARS-CoV-2 viral proteome, we utilize APMAT for the capture and single cell analysis of CD8 T cells from 62 HLA A*02:01 COVID-19 participants. We leverage this unique, comprehensive dataset to integrate with peptide antigen properties, TCR CDR3 sequences, and T cell phenotypes to show that distinct physicochemical features of the antigen-TCR pairs strongly associate with both T cell phenotype and T cell persistence. This analysis suggests that CD8+ T cell phenotype following antigen stimulation is at least partially deterministic, rather than the result of stochastic biological properties.

immunology↗

APOE Genotype and Biological Age Impact Inter-Omic Associations Related to Bioenergetics

Apolipoprotein E (APOE) modifies human aging; specifically, the {varepsilon}2 and {varepsilon}4 alleles are among the strongest genetic predictors of longevity and Alzheimers disease (AD) risk, respectively. However, detailed mechanisms for their influence on aging remain unclear. Herein, we analyzed inter-omic, context-dependent association patterns across APOE genotypes, sex, and health axes in 2,229 community-dwelling individuals to test APOE genotypes for variation in metabolites and metabolite-associations tied to a previously-validated metric of biological aging (BA) based on blood biomarkers. Our analysis, supported by validation in an independent cohort, identified top APOE-associated plasma metabolites as diacylglycerols, which were increased in {varepsilon}2-carriers and trended higher in {varepsilon}4-carriers compared to {varepsilon}3-homozygotes, despite the known opposing aging effects of the allele variants. Omics association patterns of {varepsilon}2-carriers and increased biological age were also counter-intuitively similar, displaying increased associations between insulin resistance markers and energy-generating pathway metabolites. These results provide an atlas of APOE-related omic associations and support the involvement of bioenergetic pathways in mediating the impact of APOE on aging.

systems biology↗

Generally-healthy individuals with aberrant bowel movement frequencies show enrichment for microbially-derived blood metabolites associated with impaired kidney function.

Bowel movement frequency (BMF) has been linked to changes in the composition of the human gut microbiome and to many chronic conditions, like metabolic disorders, neurodegenerative diseases, chronic kidney disease (CKD), and other intestinal pathologies like irritable bowel syndrome and inflammatory bowel disease. Lower BMF (constipation) can lead to compromised intestinal barrier integrity and a switch from saccharolytic to proteolytic fermentation within the microbiota, giving rise to microbially-derived toxins that may make their way into circulation and cause damage to organ systems. However, the connections between BMF, gut microbial metabolism, and the early-stage development and progression of chronic disease remain underexplored. Here, we examined the phenotypic impact of BMF variation in a cohort of generally-healthy, community dwelling adults with detailed clinical, lifestyle, and multi-omic data. We showed significant differences in microbially-derived blood plasma metabolites, gut bacterial genera, clinical chemistries, and lifestyle factors across BMF groups that have been linked to inflammation, cardiometabolic health, liver function, and CKD severity and progression. We found that the higher plasma levels of 3-indoxyl sulfate (3-IS), a microbially-derived metabolite associated with constipation, was in turn negatively associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. Causal mediation analysis revealed that the effect of BMF on eGFR was significantly mediated by 3-IS. Finally, we identify self-reported diet, lifestyle, and psychological factors associated with BMF variation, which indicate several common-sense strategies for mitigating constipation and diarrhea. Overall, we suggest that aberrant BMF is an underappreciated risk factor in the development of chronic diseases, even in otherwise healthy populations.

systems biology↗

Genome-microbiome interplay provides insight into the determinants of the human blood metabolome

Variation in the blood metabolome is intimately related to human health. Prior work has shown that host genetics and gut microbiome composition, combined, explain sizable, but orthogonal, components of the overall variance in blood metabolomic profiles. However, few details are known about the interplay between genetics and the microbiome in explaining variation on a metabolite-by-metabolite level. Here, we performed analyses of variance for each of the 945 blood metabolites that were robustly detected across a cohort of 2,049 individuals, while controlling for a number of relevant covariates, like sex, age, and genetic ancestry. Over 60% of the detected blood metabolites were significantly associated with either host genetics or the gut microbiome, with more than half of these associations driven solely by the microbiome and around 30% under hybrid genetic-microbiome control. The variances explained by genetics and the microbiome for each metabolite were indeed largely additive, although subtle, but significant, non-additivity was detected. We found that interaction effects, where a metabolitemicrobe association was specific to a particular genetic background, were quite common, albeit with modest effect sizes. The outputs of our integrated genetic-microbiome regression models provide novel biological insights into the processes governing the composition of the blood metabolome. For example, we found that unconjugated secondary bile acids were solely associated with the microbiome, while their conjugated forms were under strong host genetic control. Overall, our results reveal which components of the blood metabolome are under strong genetic control, which are more dependent on gut microbiome composition, and which are dependent upon both. This knowledge will help to guide targeted interventions designed to alter the composition of the blood metabolome.

systems biology↗

Manifestations of genetic risk for Alzheimer's Disease in the blood: a cross-sectional multi-omic analysis in healthy adults aged 18-90+

Deeply phenotyped cohort data can elucidate differences associated with genetic risk for common complex diseases across an age spectrum. Previous work has identified genetic variants associated with Alzheimers disease (AD) risk from large-scale genome-wide association study meta-analyses. To explore effects of known AD-risk variants, we performed a phenome-wide association study on ~2000 clinical, proteomic, and metabolic blood-based analytes obtained from 2,831 cognitively normal adult clients of a consumer-based scientific wellness company. Results uncovered statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE). These effects were detectable from early adulthood. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. Sex-stratified GWAS results from an independent AD case-control meta-analysis supported sexspecific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. These analyses support evidence from previous functional genomics studies in the identification of a causal variant within the PILRA gene. Taken together, this study highlights clues to the earliest effects of AD genetic risk variants in individuals where disease symptoms have not (yet) arisen.

genetics↗

Weight loss response following lifestyle intervention associated with baseline gut metagenomic signature in humans

We report a weight-loss response analysis on a small cohort of individuals (N=25) selected from a larger population (N[~]5,000) enrolled in a commercial scientific wellness program, which included healthy lifestyle coaching. Each individual had baseline data on blood metabolomics, blood proteomics, clinical labs, lifestyle questionnaires, and stool metagenomes. A subset of these participants (N=15) lost at least 10% of their body weight within a 6-12 month period and saw significant improvement in metabolic health markers ( weight loss group), while another subset of individuals (N=10) undergoing the same lifestyle intervention showed no change in BMI over the same timeframe ( no weight loss group). Only a single baseline blood analyte, a metabolite linked to fried food consumption, was (negatively) associated with weight loss, but a large number of baseline stool metagenomic features, including complex polysaccharide and protein degradation genes, stress-response genes, respiration-related genes, cell wall synthesis genes, and gut bacterial replication rates, were significantly associated with weight loss after explicitly controlling for baseline BMI. Together, these results provide a set of baseline gut microbiome functional features that are associated with weight loss outcomes.

microbiology↗

Gut Microbiome Pattern Reflects Healthy Aging and Predicts Extended Survival in Humans

The gut microbiome has important effects on human health, yet its importance in human aging remains unclear. Using two independent cohorts comprising 4582 individuals across the adult lifespan we demonstrate that, starting in mid-to-late adulthood, gut microbiomes become increasingly unique with age. This uniqueness pattern is strongly associated with gut microbial amino acid derivatives circulating within the bloodstream, many of which have been previously identified as longevity biomarkers. At the latest stages of human life, two distinct patterns emerge wherein individuals in good health show continued microbial drift toward a unique compositional state, while the same drift is absent in individuals who perform worse on a number of validated health measures. The identified healthy aging pattern is characterized by an overall depletion of core genera found across most humans - primarily a depletion in the nearly ubiquitous genus Bacteroides. Consistently, retaining a high Bacteroides dominance into extreme age, or, equivalently, having a low gut microbiome uniqueness score, predicts decreased survival in a four-year follow-up. Our comprehensive analysis identifies the gut microbiome as a novel component of healthy aging, with important implications for the worlds growing older population.

systems biology↗

Blood metabolome signature predicts gut microbiome α-diversity in health and disease

Defining a healthy gut microbiome has been a challenge in the absence of detailed information on both host health and microbiome composition. Here, we analyzed a multi-omics dataset from hundreds of individuals (discovery n=399, validation n=540) enrolled in a consumer scientific wellness program to identify robust associations between host physiology and gut microbiome structure. We attempted to predict gut microbiome -diversity from nearly 1000 analytes measured from blood, including clinical laboratory tests, proteomics and metabolomics. While a broad panel of 77 standard clinical laboratory tests and a set of 263 proteins from blood could not accurately predict gut microbial -diversity, we found that 45% of the variance in microbial community diversity was explained by a subset of 40 blood metabolites, many of microbial origin. This relationship between the host metabolome and gut microbiome -diversity was very robust, persisting across disease conditions and antibiotics use. Several of these novel metabolic biomarkers of gut microbial diversity were previously associated with host health (e.g. cardiovascular disease risk, diabetes, and kidney function). A subset of 11 metabolites classified participants with potentially problematic low -diversity (ROC AUC=0.88, Precision-Recall AUC=0.76). Relationships between host metabolites and -diversity remained consistent across most of the Body Mass Index (BMI) spectrum, but were modified in extreme obesity (class II/III, but not class I), suggesting a significant metabolic shift. Out-of-sample prediction accuracy of -diversity from the 40 identified blood metabolites in a validation cohort, whose microbiome samples were analyzed by a different vendor, confirmed the robust correspondence between gut microbiome structure and host physiology. Collectively, our results reveal a strong coupling between the human blood metabolome and gut microbial diversity, with implications for human health.

bioinformatics↗