Researchers analyzed two Gene Expression Omnibus datasets separately before intersecting their differentially expressed genes. The hypothyroidism dataset, GSE176153, contained four euthyroid controls and four patients, but only one man in each group. The researchers therefore restricted their main comparison to women, leaving three hypothyroid cases and three controls. The subclinical atherosclerosis dataset, GSE221615, included 391 people, of whom only 27 were women: 13 with subclinical atherosclerosis and 14 controls. In this female-restricted intersection, 15 shared genes were upregulated in both disorders, two were downregulated and three changed in opposite directions. A stricter analysis using Benjamini–Hochberg-adjusted significance found no shared genes, making the 20-gene signature exploratory rather than statistically robust.

Functional enrichment connected the shared signature to B-cell proliferation and activation, a result that differed from the interferon, antiviral and antimicrobial pathways found when the authors compared hypothyroidism with rheumatoid arthritis and systemic lupus erythematosus. A high-confidence protein-interaction network linked CD19, BLK, FCRLA and TNFRSF13C. CD19 had the highest degree of connectivity, while BLK and FCRLA were also central nodes. CD180 and SPIB were added to the six-gene pivotal group through the combined evidence from enrichment, functional-network and protein-interaction analyses. These genes encode components associated with B-cell signaling, maturation or regulation, providing a plausible molecular basis for the shared signature. However, whole-blood measurements cannot determine whether the pattern arises from altered activity within cells or from subtle changes in the proportions of circulating immune-cell subsets.

The study used CIBERSORTx to estimate the relative abundance of 22 immune-cell types from bulk RNA-sequencing data. It found no significant differences in estimated immune-cell proportions between diseased and control groups. Expression levels nevertheless correlated with inferred cell signatures: BLK and SPIB were strongly positively associated with the CD8-positive T-cell signature in the female hypothyroidism cohort, while FCRLA was negatively associated with the naïve CD4-positive T-cell signature. In the female atherosclerosis cohort, IFRD1 correlated negatively with the memory B-cell signature, and several pivotal genes correlated positively with activated natural killer cell, M2 macrophage and resting mast-cell signatures. Because these were computational estimates and the M2 macrophage fraction was relatively small, the correlations do not establish functional relationships between the genes and those cell populations.

ROC analyses suggested that some pivotal genes could discriminate groups in the discovery cohorts. Among women with subclinical atherosclerosis, TNFRSF13C had an area under the ROC curve of 0.835, with a 95% confidence interval of 0.664–1.000, while SPIB reached 0.808, with a 95% interval of 0.626–0.990. All six genes produced an AUC of 1.00 in the hypothyroidism cohort, but that calculation separated only three cases from three controls and therefore cannot be interpreted as evidence of diagnostic utility. The candidate transcription factors were less consistent: all had AUC values below 0.70 in the female subclinical atherosclerosis cohort. These results show why the reported classification performance should be treated as hypothesis-generating rather than a clinically usable biomarker panel.

The researchers sought an external check using GSE202625, a cohort of consecutive patients undergoing coronary CT angiography that represented established atherosclerotic disease rather than subclinical disease. Its female subset contained only 11 participants—six with coronary artery disease and five controls—so it served as a limited proxy rather than a matching validation cohort. CD180 had the highest AUC among the six pivotal genes in this group, at 0.87, followed by SPIB and BLK, both at 0.70. Among predicted regulators, MEF2A reached 0.90, SPI1 0.80 and PPARG 0.73. The wide confidence intervals and the mismatch between advanced and subclinical disease limit interpretation, but the results suggest that parts of the candidate axis may remain detectable beyond the early stage of atherosclerosis.

To explore thyroid-stimulating hormone signaling outside circulating blood, the team examined GSE275079, a dataset of primary bone-marrow-derived macrophages from male mice with myeloid-specific Tshr knockout and their wild-type littermates after TSH stimulation. Downregulated genes in knockout macrophages were enriched for leukocyte and mononuclear-cell proliferation, regulation of inflammatory responses, immune signaling, chemotaxis and migration. Ifrd1 expression was lower in knockout cells, whereas Cd19, Arhgap24, Pparg and Mef2c were higher. These findings connect disruption of TSH-receptor signaling with immune pathways, but they do not validate the B-cell-dominated human signature or demonstrate that the same responses occur in women. The mouse macrophage experiments instead provide a complementary myeloid context for the systemic human analysis.

Human THP-1 monocytes were differentiated into macrophages and exposed to TSH, bacterial lipopolysaccharide, both together, or vehicle for 24 hours. IFRD1 messenger RNA was significantly reduced by 1 mU/mL TSH alone, with an adjusted p-value of 0.001, and by TSH combined with lipopolysaccharide, with an adjusted p-value below 0.001. The same reduction was not observed at the higher TSH concentration of 10 mU/mL, leaving the basis for this concentration-dependent response unresolved. MEF2A expression did not differ significantly from vehicle in any treatment group. The experiment provides initial evidence that TSH exposure can alter IFRD1 expression in a human macrophage model, but a cell line experiment cannot establish a mechanism in patients or show that IFRD1 mediates cardiovascular risk.

Several limitations constrain the findings. Cross-dataset technical differences may have influenced the intersection, and important clinical variables—including thyroid hormone concentrations in the atherosclerosis cohort, vascular measurements in the hypothyroidism cohort, body mass index, glucose, lipids, menopausal status, hormone replacement therapy and thyroid-antibody profiles—were unavailable. The female-only design reduced sex-related heterogeneity but left effects of reproductive stage unresolved. Bulk RNA also lacks the resolution to distinguish cell-intrinsic changes from shifts in rare or subtle immune-cell populations. In addition, the functional experiments concentrated on macrophages rather than the B cells that dominate the human signature, and the male-derived models cannot establish female specificity. Overall, the study identifies a testable candidate network linking thyroid dysfunction with early atherosclerosis in women, but larger independent cohorts, single-cell profiling and direct functional studies in relevant lymphocyte populations are required before its clinical or prognostic significance can be determined.

Subject of Research: Whole-blood transcriptomics of shared molecular mechanisms between subclinical atherosclerosis and hypothyroidism in women

Article Title: A whole-blood transcriptomic analysis of shared molecular mechanisms between subclinical atherosclerosis and hypothyroidism in women

Article References: Torres, E. M., Raffo, D. A., & Tellechea, M. L. (2026). A whole-blood transcriptomic analysis of shared molecular mechanisms between subclinical atherosclerosis and hypothyroidism in women. Frontiers in Bioinformatics, 6, Article 1932220. https://doi.org/10.3389/fbinf.2026.1932220

Image Credits: AI Generated

DOI: 10.3389/fbinf.2026.1932220

Keywords: hypothyroidism, subclinical atherosclerosis, whole-blood transcriptomics, women's health, B-cell activation, immune regulation, TSH signaling, TSHR, IFRD1, macrophages, whole-blood, transcriptomic

The study combined high-resolution liquid chromatography with tandem mass spectrometry to profile secondary metabolites in methanolic extracts of L. arborea leaves and stalks and in three leaf-derived fractions. LC-ESI/LTQ-Orbitrap-MS/MS permitted the tentative identification of 14 compounds, including flavonoids, a phenolic derivative, fatty acids, oxygenated fatty acids and a diterpene glycoside. The researchers then isolated five major flavonoids and unequivocally characterized them by one- and two-dimensional nuclear magnetic resonance spectroscopy, confirming annotations initially based on accurate mass, retention time and fragmentation patterns.

Plant material was collected in Aswan Governorate, Egypt, in November 2023 during flowering and fruiting, and a voucher specimen was deposited at Aswan University. Leaves and stalks were separated, air-dried at 36 °C, ground and macerated separately with 80% methanol for 48 hours, with two extractions performed for each material. The crude leaf extract was subsequently partitioned on a reversed-phase C18 column with a stepwise methanol gradient. The resulting 40%, 60% and 80% methanol fractions were designated LaLA, LaLB and LaLC, while the original leaf and stalk extracts were designated LaL and LaS. Preliminary thin-layer chromatography detected flavonoid derivatives and glycosylated compounds in all three leaf fractions.

For chemical profiling, extracts were analyzed in negative electrospray mode using reversed-phase ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry. The method covered a mass range of 120 to 1,600 m/z, with data-dependent acquisition selecting abundant precursor ions for fragmentation at a normalized collision energy of 30%. Feature detection and alignment used a mass tolerance below 5 parts per million, a signal-to-noise ratio above 3 and a retention-time window of plus or minus 0.2 minutes. Peak areas were normalized to total ion current, and identifications relied on accurate mass, elemental composition, isotope-pattern agreement and comparison of tandem mass spectra with literature on the Apocynaceae family.

Flavonoids predominated in the profile, chiefly as O-glycosides. Diagnostic fragment ions supported tentative assignments of apigenin-6,8-di-C-glycoside, luteolin-7-O-β-glucopyranoside, apigenin-7-O-β-glucopyranoside, luteolin and apigenin, as well as rutin and chrysoeriol. The researchers isolated apigenin-6,8-di-C-glycoside, luteolin-7-O-β-glucopyranoside, apigenin-7-O-β-glucopyranoside, luteolin and apigenin, then used detailed NMR data to determine their structures, including glycosylation positions and sugar identities. This structural confirmation strengthened the LC-MS assignments and reduced the possibility that structurally similar isomeric glycosides had been confused on mass-spectrometric evidence alone.

Beyond flavonoids, the analytical workflow detected coumaroyl-O-glucaric acid, azelaic acid, a compound assigned as steviolbioside, three oxylipins and dihydroxypalmitic acid. The oxylipin assignments were based partly on a diagnostic product ion at m/z 171, while sequential sugar losses supported the steviolbioside annotation. Most compounds appeared across the leaf extract, stalk extract and the three leaf fractions, although one oxylipin was detected only in the 80% leaf fraction and stalk extract, and dihydroxypalmitic acid was absent from the 40% fraction. The authors reported coumaroyl-O-glucaric acid, steviolbioside and the polar lipid derivatives as new descriptions within the genus Leptadenia.

For the biological tests, blood was obtained with consent from healthy, nonsmoking volunteers aged 19 to 24 who reported no alcohol use and no medication, antiplatelet medicine or antioxidant supplementation during the preceding two weeks. Plasma and platelets were incubated for 30 minutes at 37 °C with extracts, fractions or isolated compounds, with extract and fraction concentrations ranging from 0.5 to 50 micrograms per milliliter and pure compounds tested at 5 micrograms per milliliter. Oxidative stress was induced with 4.7 mM H2O2, 3.8 mM Fe2+ and 2.5 mM EDTA. The researchers measured thiobarbituric acid-reactive substances as an indicator of lipid peroxidation, protein carbonyl groups as a marker of protein oxidation and free thiol groups as a measure of thiol oxidation.

The 80% leaf fraction had the broadest statistically significant antioxidant profile at 5 micrograms per milliliter, significantly lowering lipid peroxidation, protein carbonylation and thiol oxidation in both plasma and platelets. The 60% fraction also showed substantial activity against platelet lipid peroxidation and protein carbonylation, and the 40% fraction was effective in several assays, although responses were not uniformly significant. At 50 micrograms per milliliter, all three fractions significantly inhibited platelet lipid peroxidation by about 60%. Extracts and fractions did not appreciably change the measured biomarkers in samples lacking the oxidative-stress inducer, indicating that the observed effects occurred under the imposed stress condition rather than as a general alteration of baseline values.

Five purified flavonoids also showed antioxidant activity in the comparison experiment. At 5 micrograms per milliliter, apigenin, luteolin, apigenin-6,8-di-C-glycoside, apigenin-7-O-glucopyranoside and luteolin-7-O-β-glucopyranoside reduced one or more indicators of oxidative damage in plasma or platelets, with significant effects reported in the relevant models. For example, apigenin reduced plasma lipid peroxidation by about 47% and plasma protein carbonylation by about 34%, while it increased free thiols by about 42% in plasma and 45% in platelets. These purified compounds were often less effective than some plant preparations, which the authors interpreted cautiously as possible evidence of combined or synergistic effects among multiple metabolites rather than proof of a specific mechanism.

Whole-blood testing produced a different pattern. Blood was passed through a collagen-coated PL-chip in the Total Thrombus-formation Analysis System, with secondary hemostasis blocked so that the assay focused on primary hemostasis under shear. Only the 40% leaf fraction significantly increased the 10-minute area under the pressure curve, by approximately 20%, at concentrations of 5 and 50 micrograms per milliliter. This represented greater thrombus formation in that in vitro system. Aspirin, used as a reference, reduced the area under the curve by about 50% and significantly prolonged occlusion time. None of the other extracts or fractions significantly modulated thrombus formation, separating the antioxidant findings in plasma and platelets from the procoagulant response observed for one fraction in whole blood.

The findings provide a detailed chemical and experimental basis for further studying L. arborea, a climbing plant whose leaves, shoots and young fruits are consumed as a nutritious green vegetable in parts of the Sahel and Arabian Peninsula. However, the work remains limited to laboratory assays using human samples from volunteers in a narrow age group, with no in vivo or clinical evaluation reported. The PL-chip does not identify individual platelet activation pathways, while the possible influence of digestion, metabolism and bioavailability on the extracts and isolated phenolics remains unresolved. The authors called for further in vitro and in vivo research to determine whether the measured antioxidant effects and modulation of hemostasis correspond to biologically relevant outcomes.

Subject of Research: In vitro phytochemical, antioxidant and hemostatic assessment of Leptadenia arborea leaf and stalk preparations

Article Title: LC-HRMS/MS-based qualitative secondary metabolites profiling of Leptadenia arborea and evaluation of its antioxidant and hemostatic activities

Article References: Olas, B., Rashidi, N. A., Cerulli, A., Mohamed, A. A. A., Kontek, B., Sławińska, N., Kalamat, K., Abdel-Farid, I. B., Piacente, S., & Hamed, A. I. (2026). LC-HRMS/MS-based qualitative secondary metabolites profiling of Leptadenia arborea and evaluation of its antioxidant and hemostatic activities. Frontiers in Molecular Biosciences, 13, 1951196. https://doi.org/10.3389/fmolb.2026.1951196

Image Credits: AI Generated

DOI: 10.3389/fmolb.2026.1951196

Keywords: Leptadenia arborea, flavonoid glycosides, LC-HRMS/MS, NMR spectroscopy, oxidative stress, human plasma, blood platelets, whole blood, thrombus formation, hemostasis, LC-HRMS, MS-based

The researchers designed the device around a stochastic sensor comprising a matrix of Ti Al nitride MAX phase and graphite. They physically immobilized 4-tert-butylcalix[4]arene on this matrix, then designed, characterized and validated the resulting lab-on-chip platform with real samples of whole blood, saliva and urine from patients with confirmed heart disease. According to the abstract, the reported concentration range and limit of determination apply to the analytical method as tested; the abstract does not provide details about the number of participants, sample volumes, replicates or the procedures used to establish the range.

Validation results were compared with measurements obtained by a specialized clinical laboratory using an ELISA kit. A Student’s t test conducted at the 99.00% confidence level found no statistically significant difference between the lab-on-chip and ELISA results. The abstract therefore reports agreement between the two methods in the tested patient samples, rather than establishing the device’s performance in a broader population or in prospective clinical use. The abstract also states that average recoveries exceeded 98.00%, although it does not provide fluid-specific recovery values or uncertainty estimates.

Only the abstract and publisher-provided article information were available for this report, so the full experimental results could not be assessed. The abstract does not report the size and characteristics of the patient cohort, whether healthy or disease-control groups were included, or the device’s specificity, stability, reproducibility and performance outside the stated concentration range. It also does not state that the measurements were used to guide treatment or that the device changes clinical outcomes. The reported findings are limited to the design, analytical validation and sample comparison summarized in the abstract.

Subject of Research: Analytical validation of a lab-on-chip sensor for C-type natriuretic peptide in blood, saliva and urine

Article Title: 4-tert-butylcalix[4]arene/Ti Al nitride MAX phase@graphite-based lab-on-chip for fast ultrasensitive determination of natriuretic peptide C-type

Article References: Buzalin-Enache, M., Sava, T.-M., Stefan-van Staden, R.-I., Gheorghe, D.-C., Ilie-Mihai, R.-M., & Dan, A. (2026). 4-tert-butylcalix[4]arene/Ti Al nitride MAX phase@graphite-based lab-on-chip for fast ultrasensitive determination of natriuretic peptide C-type. Journal of Materials Science. https://doi.org/10.1007/s10853-026-13779-5

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13779-5

Keywords: C-type natriuretic peptide, lab-on-chip, stochastic sensor, biological fluids, ELISA comparison, analytical validation, whole blood, saliva, urine, heart disease, tert-butylcalix, arene

The scale and clinical breadth of the underlying cohort is what sets the resource apart. Most transcriptomic studies focus on one disease at a time, comparing patients against a small control group, which makes it difficult to know whether a gene signature is truly specific to a condition or merely reflects generic illness. By collecting whole blood RNA profiles across 98 different health states within a coordinated framework, the researchers could ask, for the first time at this scale, which molecular changes are shared across many diseases and which are genuinely distinctive. The atlas characterizes each condition at multiple levels of biological organization: individual genes, co-expressed gene modules, and entire biological pathways, with particular attention to immune cell composition, metabolic activity, and cell-type-specific signals that can be inferred from bulk blood measurements.

Technically, whole blood transcriptomics presents a deconvolution problem. A blood sample is a mixture of red cells, platelets, and a diverse population of leukocytes, including neutrophils, monocytes, lymphocytes, and dendritic cells, each with its own expression program. When a disease shifts the proportions of these cell types, the bulk RNA profile changes even if no individual cell alters its internal state. The atlas addresses this by explicitly modeling immune and cell-type-specific features alongside gene and pathway-level signals, allowing the authors to separate changes driven by cellular composition from changes driven by transcriptional regulation within cells. This layered characterization means that a researcher probing, say, a suspected autoimmune condition can distinguish whether the dominant signal is an expansion of neutrophil-associated transcripts or a genuine upregulation of interferon-response genes inside lymphocytes.

A second major component of the study extends the atlas beyond RNA. For 1,280 participants representing 28 of the health conditions, the team generated matched plasma proteomics data, measuring the circulating protein landscape in the same individuals whose blood RNA had been profiled. This pairing allowed a systematic assessment of the relationship between messenger RNA abundance in blood cells and protein concentration in plasma, a relationship that is notoriously imperfect. Many transcripts are translated at low efficiency, many proteins are secreted by tissues far from the bloodstream, and many blood proteins have half-lives that decouple them from the transient RNA signals that produced them. By quantifying these RNA-protein relationships across dozens of conditions, the researchers demonstrated that the two molecular layers carry complementary rather than redundant information, each capturing aspects of disease biology the other misses.

That complementarity became the foundation for the study’s most translational result: multi-class classification models that integrate RNA and protein signatures to distinguish among a wide range of health conditions. Where most diagnostic machine learning studies tackle a binary question, diseased versus healthy, the atlas models were trained to assign samples to the correct condition among many alternatives, a substantially harder task that mirrors real clinical differential diagnosis. The integrated multi-omics models consistently outperformed classifiers built on RNA data alone or protein data alone, confirming quantitatively that the information content of the combined signatures exceeds the sum achievable with either layer by itself. The authors validated the identified RNA and protein signatures across ten independent whole blood transcriptomics cohorts and in the UK Biobank, providing external replication that is rare in single-center omics studies.

The validation strategy deserves emphasis because it speaks to a chronic weakness of the biomarker literature. Candidate signatures discovered in one cohort frequently fail when tested elsewhere, a phenomenon driven by differences in sequencing platforms, sample handling, population demographics, and disease prevalence. By requiring that the atlas-derived signatures hold up in ten external transcriptomics datasets and in the population-scale UK Biobank resource, used under Application Number 150710, the team provided evidence that the disease-associated patterns are robust biological signals rather than artifacts of a particular laboratory or cohort. For clinicians and translational researchers, this kind of cross-cohort reproducibility is the difference between an interesting observation and a candidate diagnostic tool.

The consortium behind the work is itself notable. Alongside the Stockholm computational team, which includes Mathias Uhlen, Saeed Shoaie, Cheng Zhang, and corresponding author Adil Mardinoglu, the author list spans dozens of clinician-researchers at Atatürk University’s Faculty of Medicine, Erzurum Regional Training and Research Hospital, and partner institutions, reflecting the enormous clinical recruitment effort required to assemble thousands of well-phenotyped patient samples across such a wide diagnostic spectrum. The work received support from the Knut and Alice Wallenberg Foundation, and the resulting atlas is being positioned as an open resource for the precision medicine community, enabling other groups to query disease-associated transcriptomic signatures without repeating the costly sample collection.

What might the atlas enable in practice? For diagnostic developers, the multi-class models suggest a route toward blood tests that do not merely flag that something is wrong but help triangulate what is wrong, potentially accelerating workups in settings where patients present with nonspecific symptoms. For drug developers, the pathway and module-level maps offer a way to see which biological processes are perturbed across disease families, highlighting shared inflammatory or metabolic axes that might be targeted therapeutically or that explain why a single drug produces effects across seemingly unrelated conditions. For basic researchers, the resource provides a reference against which new patient data can be projected, instantly contextualizing an individual expression profile within a landscape of 98 known health states.

The study also contributes a methodological lesson about the biology of blood itself. The finding that RNA and protein layers play complementary biological roles underscores that neither measurement alone can serve as a complete proxy for physiological state. Transcripts reflect what blood cells are actively doing at the moment of sampling; plasma proteins reflect secretion, clearance, and contributions from distant organs. Diseases leave different imprints on each layer depending on their mechanism, whether they act primarily through immune activation, tissue damage, or systemic metabolic change. An atlas that records both layers, in matched samples, across a broad disease spectrum, therefore functions less like a single dataset and more like a bilingual dictionary for translating between cellular activity and circulating physiology.

Published as an open-access article with extensive supplementary datasets, the WBT Atlas arrives at a moment when large-scale, multi-omic reference resources are reshaping how biomedical research is organized, echoing the impact of earlier protein and tissue atlases from the same Stockholm research environment. Its authors describe it as a genome-wide resource enabling translational discovery in precision medicine, and the external validations included in the paper suggest the description is more than aspiration. As more cohorts and conditions are added and as the community begins projecting new patient data onto the map, the atlas may well become a standard reference point, the molecular backdrop against which the next generation of blood-based diagnostics is drawn.

Subject of Research: A whole blood transcriptomics atlas characterizing disease-associated gene, module, and pathway signatures across 98 human health conditions with integrated plasma proteomics

Article Title: Whole blood transcriptomics atlas across human diseases

Article References: Li, M., Tatar, A., Green, E., Simsek, E., Kahraman, C. Y., Ceylan, M., Laloglu, F., Ceviz, N., Tatar, A., Laloglu, E., Akcay, G., Cadirci, K., Yapca, O. E., Ozmen, H. K., Yapanoglu, T., Kudas, O., Simsek, F., Yılmaz, E. P. T., Senocak, G. N. C., … Mardinoglu, A. (2026). Whole blood transcriptomics atlas across human diseases. Nature Communications. https://doi.org/10.1038/s41467-026-78440-w

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78440-w

Keywords: transcriptomics, whole blood, biomarkers, multi-omics, plasma proteomics, precision medicine, machine learning, gene expression, disease classification, UK Biobank, Nature Communications, diagnostics

The research, led by Takashi Shida of the Tokyo Metropolitan Institute for Geriatrics and Gerontology and colleagues, drew on participants from the Itabashi Longitudinal Study on Aging, an ongoing community-based cohort in a residential ward of northern Tokyo. The team analyzed data from 529 adults aged 65 and older who took part in the 2025 survey wave, a group in which 54.3 percent were women. Frailty, the state of heightened vulnerability that leaves older adults at risk of falls, disability, hospitalization, and death, was assessed using the revised Japanese version of the Cardiovascular Health Study criteria, a validated instrument that scores weight loss, exhaustion, low physical activity, weakness, and slowness. Of the 529 participants, 32, or 6.0 percent, met the criteria for frailty.

The central measurement was the concentration of NAD+ in whole blood, quantified in micromoles per liter. Whole-blood NAD+ is a composite signal: it reflects the molecule’s presence inside red blood cells, white blood cells, and platelets, as well as whatever circulates in plasma. Because red blood cells lack mitochondria and rely heavily on NAD+ for glycolysis and antioxidant defense, the blood compartment offers a convenient, if imperfect, window into systemic NAD+ metabolism. The researchers found that the median whole-blood NAD+ concentration was measurably lower among participants with frailty than among those without it, at 24.00 versus 25.00 micromoles per liter, a difference that reached statistical significance with a P value of 0.007.

To move beyond a simple group comparison, the team built multivariable regression models that adjusted for the most obvious confounders: age, sex, and fasting time before the blood draw, the last of which matters because NAD+ levels can fluctuate with recent food intake. After these adjustments, each 1 micromole per liter increase in whole-blood NAD+ concentration was associated with 13 percent lower odds of frailty, with an odds ratio of 0.871 and a 95 percent confidence interval spanning 0.780 to 0.970, and a P value of 0.013. In a cohort where the median sits near 25 micromoles per liter, a one-unit shift is a meaningful fraction of the biological range, which makes the effect size noteworthy rather than trivial.

The investigators then subjected their finding to a battery of robustness checks that reveal how carefully the result was constructed. Restricted cubic spline analysis, a technique that allows the relationship between NAD+ and frailty to bend and curve freely rather than assuming a straight line, showed no clear evidence of nonlinearity, suggesting the association behaves approximately linearly across the observed range. Because frailty was relatively rare in the sample, the team also ran a Firth penalized-likelihood logistic regression, a method designed to produce more stable estimates when outcomes are infrequent and conventional models risk bias. Under this broader covariate adjustment, the association held firm, with an odds ratio of 0.880 and a confidence interval of 0.782 to 0.986.

But the story took a more complicated turn when the researchers added hematocrit, the proportion of blood volume occupied by red blood cells, to the model. With that adjustment, the association weakened and lost statistical significance, with the odds ratio drifting to 0.911 and the confidence interval crossing unity at 0.800 to 1.034. This attenuation is not a failure of the study; it is one of its most informative results. It suggests that part of the apparent link between blood NAD+ and frailty may be explained by blood cell composition itself. Frail older adults often have altered hematological profiles, including tendencies toward anemia and shifts in red cell indices, and since the vast majority of whole-blood NAD+ resides within blood cells, differences in cell counts and packing could masquerade as, or at least substantially contribute to, differences in NAD+ concentration.

This caveat places the new findings within a lively and sometimes contentious scientific debate. NAD+ has become one of the most hyped molecules in the longevity world, with supplements such as nicotinamide riboside and nicotinamide mononucleotide marketed aggressively on the premise that restoring youthful NAD+ levels can slow aging. Human evidence, however, has been mixed. Some studies have reported that whole-blood NAD+ contents decline with age, while others, including a recent analysis published in Nature Metabolism, found that human whole-blood NAD+ levels do not vary with age or with lifestyle interventions. Blood NAD+ has also been reported to be reduced in very old patients hospitalized for heart failure, hinting that the molecule may track with disease severity rather than chronological age per se. The Itabashi study adds a crucial piece: a community-dwelling, non-hospitalized population in which the association with frailty, a clinical syndrome rather than a single disease, was detectable.

The study’s design imposes important limits on interpretation. As a cross-sectional analysis, it captures a single moment in time and cannot determine whether low NAD+ contributes to causing frailty, whether frailty and its metabolic consequences deplete NAD+, or whether both are driven by a shared underlying process such as chronic inflammation, mitochondrial dysfunction, or poor nutrition. The frailty group was also small, with only 32 affected participants, which limits statistical power and explains the team’s recourse to penalized regression. And the whole-blood measurement, while practical and increasingly standardized, cannot distinguish between NAD+ dynamics in muscle, brain, immune cells, and other tissues where the molecule’s age-related decline is thought to matter most. The authors themselves emphasize that further studies using cell- and tissue-specific measurements are needed to clarify the relationship between NAD+ metabolism and frailty.

Those caveats notwithstanding, the significance of the work lies in its grounding. Much of the NAD+ literature rests on cell culture experiments, animal models, or small and highly selected human samples. Here, the association emerges from ordinary older adults living at home in a Tokyo ward, measured with a validated frailty instrument and adjusted for the mundane but essential variables of age, sex, and fasting status. If blood NAD+ does prove to be a genuine marker of physiological resilience, even one partly confounded by blood cell composition, it could eventually help clinicians identify which older patients are silently sliding toward frailty before falls and disability make it obvious. Biomarkers of frailty are a recognized public health priority, and most current candidates, from inflammatory cytokines to metabolomic signatures, remain far from clinical deployment.

The road ahead will require longitudinal follow-up within cohorts like Itabashi, where repeated NAD+ measurements can be tested as predictors of incident frailty, and intervention studies in which NAD+-boosting compounds are evaluated against hard clinical endpoints rather than blood chemistry alone. Recent work comparing different NAD+ precursors has shown that they exert differential effects on circulating NAD and microbial metabolism in humans, underscoring how much remains unknown about how these interventions behave in the body. Exercise training, for its part, has been shown to reverse the age-dependent decline in NAD+ salvage capacity in human skeletal muscle, pointing to lifestyle approaches that may act on the same pathway without a pill. For now, the Itabashi findings should be read as a carefully qualified signal rather than a prescription: a molecule central to energy metabolism and cellular signaling appears to run low in the blood of frail older adults, and untangling whether that deficit is a driver, a passenger, or a mirror of declining resilience is now one of the most compelling questions in the biology of aging.

Subject of Research: Association between whole-blood NAD+ concentration and frailty in community-dwelling older adults

Article Title: Association between whole-blood NAD+ concentration and frailty in community-dwelling older adults: the Itabashi Longitudinal Study on Aging

Article References: Shida, T., Hatanaka, S., Kojima, N., Osuka, Y., & Sasai, H. (2026). Association between whole-blood NAD+ concentration and frailty in community-dwelling older adults: the Itabashi Longitudinal Study on Aging. GeroScience. https://doi.org/10.1007/s11357-026-02545-9

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02545-9

Keywords: NAD+, frailty, aging, older adults, whole blood, biomarkers, energy metabolism, sirtuins, hematocrit, GeroScience, Itabashi Longitudinal Study, geriatrics

The biological signal the team hunted for is DNA methylation, a chemical modification in which methyl groups are attached to cytosine bases, most often at cytosine-guanine dinucleotides known as CpG sites. Methylation patterns act as a layer of gene regulation, silencing or activating genomic regions without altering the underlying DNA sequence. Because tumors shed DNA and because immune and other blood cells undergo measurable epigenetic shifts in response to cancer, methylation signatures detectable in blood have attracted growing interest as biomarkers for a range of malignancies. Yet while several methylation biomarkers associated with renal cell carcinoma have been found in tumor tissue, blood-derived methylation markers for the disease have remained scarce, leaving clinicians dependent on computed tomography scans and ultrasonography for early detection.

The Japanese team’s methodological choice proved decisive. Most epigenome-wide association studies, or EWAS, rely on microarrays such as the Illumina Infinium MethylationEPIC chip, which can interrogate only about 3 to 3.5 percent of the CpG sites in the human genome. That limitation means potentially valuable biomarkers may simply be invisible to conventional screens. Ohmomo and colleagues instead used targeted bisulfite sequencing, or TB-seq, a technique in which DNA fragments are treated with bisulfite to convert unmethylated cytosines into uracils, then captured and sequenced at millions of CpG positions. This approach proved essential for one region in particular: the segment of chromosome 5 that ultimately yielded the study’s key markers is densely homologous to other parts of the genome, making it impossible to amplify with standard PCR primers. Custom hybridization probes allowed the researchers to capture and sequence the region accurately where conventional methods would have failed.

The study was structured in two phases. In the discovery phase, the team analyzed whole blood DNA from 50 ccRCC patients treated at the National Cancer Center Hospital and 50 age- and sex-matched healthy controls drawn from the Tohoku Medical Megabank Community-Based Cohort. They performed an EWAS using a linear regression model adjusted for age, sex, and the estimated cellular composition of each blood sample, a critical correction because different leukocyte populations carry distinct methylation profiles. The model showed minimal statistical inflation, with a lambda value of 1.030, indicating that the results were not driven by confounding from cell-type mixtures. In the replication phase, the same analysis was repeated in an entirely independent set of 48 ccRCC patients and 48 controls to test whether the initial findings would hold.

The discovery screen identified eleven CpG sites with p-values below the suggestive threshold of 1.00 × 10⁻⁶, and six of those crossed the stringent Bonferroni-corrected significance threshold of 1.59 × 10⁻⁸. All six mapped to a single region on chromosome 5 spanning the PCBD2 gene and the adjacent pseudogene MTND4P12, within a stretch of DNA between positions 134,923,256 and 134,928,594. Notably, the six sites were all hypomethylated in the cancer patients, showing roughly 10 percent lower methylation levels than in the healthy controls. The surrounding genomic landscape is densely populated with DNase I hypersensitive sites, transcription factor binding sites, and binding sites for CCCTC-binding factor (CTCF), an architectural protein that organizes chromatin into loops. That structural context suggests the methylation changes could influence chromatin conformation and, in turn, gene regulation across the neighborhood.

The replication phase delivered strong confirmation. Four of the six CpGs again crossed the genome-wide significance threshold, set at 3.42 × 10⁻⁸ for the smaller number of sites tested, and all six showed the same directional pattern of approximately 10 percent hypomethylation in patients. The association survived additional statistical corrections for metabolic differences between groups, including hemoglobin A1c, cholesterol measures, diabetes, dyslipidemia, and chronic kidney disease, in both phases. A Jonckheere–Terpstra trend test revealed that methylation levels differed significantly between controls and patients at every cancer stage, although the levels did not track progressively with advancing stage, suggesting the marker reflects the presence of the disease rather than its extent.

To translate the finding into a practical test, the researchers evaluated how well the six CpGs could discriminate patients from controls using receiver operating characteristic analysis. Individually, each site performed well, but the sum of methylation levels across all six sites proved the strongest classifier. In the discovery cohort, the combined score achieved an area under the ROC curve of 0.922, with a 95 percent confidence interval of 0.871 to 0.973. In the independent replication cohort, the score remained robust at 0.871, with a confidence interval of 0.800 to 0.941. An AUC near 0.9 approaches the performance of clinically useful screening tests, and the fact that the signal persisted in a separate group of patients and controls lends credibility that many single-cohort biomarker discoveries lack. Only a small fraction of previously reported cancer methylation biomarkers, the authors note, have ever been validated, a problem they attribute in part to the false-positive burden of microarray-based discovery.

The team then probed what the methylation changes might actually do. Using the iMETHYL database, which integrates methylation, gene expression, and genetic variation data from blood, they performed cis-expression quantitative trait methylation analysis, examining 56 annotated genes within one million base pairs of the PCBD2/MTND4P12 region. Two emerged as significantly linked: TCF7, located 0.8 million base pairs upstream, and VDAC1, located 0.9 million base pairs upstream. Hypermethylation at one CpG was associated with increased TCF7 expression, while hypermethylation at another correlated with decreased VDAC1 expression, meaning the hypomethylation seen in ccRCC patients would correspond to reduced TCF7 and elevated VDAC1 activity. Both genes have plausible ties to cancer biology. VDAC1 encodes a voltage-dependent anion channel on the outer mitochondrial membrane that governs the transport of adenine nucleotides, calcium ions, and metabolites, and its overexpression has been documented in multiple cancer cell lines and linked to mitochondrial abnormalities in ccRCC. TCF7 encodes the transcription factor TCF1, a regulator of T cell and innate lymphoid cell development whose overexpression has been reported in ccRCC tumor tissue.

The authors are careful to frame the work as a promising beginning rather than a finished diagnostic. The study population was exclusively Japanese, so whether the six CpGs behave identically in other ethnic groups remains unknown. The analysis covered only clear cell renal cell carcinoma, leaving open the question of whether the markers are specific to ccRCC or shared across cancer types. And because the methylation changes were measured in blood cells rather than tumor tissue, the findings do not by themselves explain the etiology of the disease; the researchers did not directly measure TCF7 or VDAC1 expression in the patients’ blood cells, an experiment they flag as necessary. Why hypomethylation of PCBD2/MTND4P12 arises in the blood of ccRCC patients is a question for future work.

Even with those caveats, the study makes a methodological statement that resonates beyond kidney cancer. By demonstrating that sequencing-based methylation profiling can uncover disease-associated regions invisible to commercial microarrays, and by validating those regions in an independent cohort with strong discriminatory power, the Japanese team has shown a path toward blood-based epigenetic screening that could extend to other cancers and diseases. The six CpGs in PCBD2/MTND4P12 now stand as candidate biomarkers awaiting larger, multi-ethnic, prospective trials. If they survive that scrutiny, a simple blood test could join imaging as a first line of defense against a cancer that today is too often found by accident, or too late.

Subject of Research: Whole blood DNA methylation biomarkers for detecting clear cell renal cell carcinoma

Article Title: Potential DNA methylation biomarkers for the detection of clear cell renal cell carcinoma identified by a whole blood-based epigenome-wide association study

Article References: Ohmomo, H., Komaki, S., Sutoh, Y., Hachiya, T., Ono, K., Arai, E., Fujimoto, H., Yoshida, T., Kanai, Y., Asahi, K., Sasaki, M., & Shimizu, A. (2022). Potential DNA methylation biomarkers for the detection of clear cell renal cell carcinoma identified by a whole blood-based epigenome-wide association study. Epigenetics Communications, 2(1), Article 2. https://doi.org/10.1186/s43682-022-00009-7

Image Credits: AI Generated

DOI: 10.1186/s43682-022-00009-7

Keywords: clear cell renal cell carcinoma, DNA methylation, epigenome-wide association study, biomarkers, targeted bisulfite sequencing, whole blood, PCBD2, MTND4P12, kidney cancer, early detection, TCF7, VDAC1