To advance a personalized approach to healthcare, such biomarkers must reliably and accurately capture individual biology, predict biological age, and provide scalable and cost-effective measurements. We developed a novel approach – image-based chromatin and epigenetic age (ImAge) that captures intrinsic progressions of biological age, which readily emerge as principal changes in the spatial organization of chromatin and epigenetic marks in single nuclei without regression on chronological age. ImAge captured the expected acceleration or deceleration of biological age in mice treated with chemotherapy or following a caloric restriction regimen, respectively. ImAge from chronologically identical mice inversely correlated with their locomotor activity (greater activity for younger ImAge), consistent with the widely accepted role of locomotion as an aging biomarker across species. Finally, we demonstrated that ImAge is reduced following transient expression of OSKM cassette in the liver and skeletal muscles and reveals heterogeneity of in vivo reprogramming. We propose that ImAge represents the first-in-class imaging-based biomarker of aging with single-cell resolution.Biomarkers of biological age that predict the risk of disease and expected lifespan better than chronological age are key to efficient and cost-effective healthcare Such biomarkers should quantitate disease and mortality risks better than chronological age, thus improving the efficacy and quality of geriatric care while reducing associated cost10. Biomarkers of aging include grip strength and gait11, frailty indices13, frailty-based clocks14, metrics of the immune system16, telomere length17, glycosylation readouts18, levels of cellular senescence19.With a steady increase in average lifespan and population aging20 and Horvath21 have identified CpG sites in human blood and other tissues with consistent age-dependent changes in DNA methylation (DNAm), enabling the development of DNAm clocks. This discovery represents a major step in the development of aging biomarkers rooted in epigenetics. Since the original discovery, many other clocks have been established26, often utilizing functional biomarkers alongside DNAm readouts, yielding biological clocks such as PhenoAge26 and DunedinPACE27 tailored to specific cell types or pan tissues31. These biomarkers correlate with mortality33, may inform on the lifespan (GrimAge)24, and are sensitive to lifespan-altering interventions35. However, separating the biological components from the chronological components remains a chellenge36.The fascinating discoveries of Hannum37 on chronological age and, for biological clocks, surrogate functional biomarkers (e.g. plasma protein levels). It often takes large cohorts to build DNAm clocks; that is, to extract the most informative CpGs and their regression coefficients. To use these clocks, additional individual DNAm levels are sequenced and the clock CpGs are multiplied by the regression coefficients. Age acceleration/deceleration  is then calculated by comparing the position of the new sample with respect to the clock’s average (regression line). Note that such an approach de facto excludes the biological components of newly tested samples, which do not participate in building DNAm clocks. This is important because comparing the biological functions of an individual, which is highly context-dependent, with a “golden mean” could be less informative for a particular individual40.One common characteristic of all DNAm clocks is the use of linear regression41. Likewise, the loss of epigenetic information has been proposed to be a cause of mammalian aging44, and transient expression of Yamanaka’s OSKM factors45 is sufficient for shifting aged mice towards an apparently younger state in at least some organs an tissues46. Well-defined cell identities  ensure organismal homeostasis48. Although driven by master regulator transcription factors51, epigenetic changes may precede a global change of cell identity at the transcription or proteome level52; the new cell identity is associated with a new epigenetic state55. Unsurprisingly, the alteration of epigenetic states is generally associated with cellular functional and phenotypic changes56, including aging57. It is known that epigenetic changes during aging result in altered epigenome and chromatin accessibility, aberrant gene expression, reactivation of transposable elements, and genomic instability59. Which specific epigenetic marks best convey age-dependent alterations is unclear; however, several studies linked aging to the loss of heterochromatin and alterations in global and local levels of H3K9me3, H3K27me3, H4K20me3, and H3K4me361. The pattern of active enhancers, marked with a combination of H3K27ac & H3K4me162, is also age-dependent64.Epigenetic alterations represent one of the primary characteristics of aging, as chromatin structure is intimately related to gene expression and regulation and, thus, cellular function65. We employed immunolabeling with antibodies specific for histone modifications (e.g. acetylation and methylation marks) and automated microscopy to capture cell-specific patterns using image texture analysis, resulting in multiparametric signatures of cellular states65. Here, we took advantage of this technique to develop image-based chromatin and epigenetic age (ImAge), an approach to studying aging that is fundamentally different from other methods, such as DNAm clocks.Since these epigenetic modifications exist on the chromatin manifold, the information collectively encoded by their spatial arrangement will likely be relevant in determining the progress of epigenetic aging. Several years ago, we pioneered microscopic imaging of epigenetic landscapes rooted in the analysis of chromatin topography in single cellsWe discovered the emergence of age-associated trajectories as an intrinsic and principal property of the spatial chromatin evolution with time. We observed that ImAge correlates with chronological age in mouse peripheral blood mononuclear cells (PBMCs) and several solid organs without linear regression. Encouragingly, we discovered ImAge measurements were consistent with expected perturbations to biological age: observing that calorie restriction decreased ImAge and chemotherapy treatment increased ImAge. Critically, ImAge of skeletal muscles from chronologically identical mice inversely correlated with their locomotor activity, suggesting its utility as a biomarker that measures behavioral and functional differences. Finally, we demonstrated that ImAge is reduced following transient expression of OSKM cassette in the liver and skeletal muscle and reveals heterogeneity of in vivo reprogramming.65. Here, we applied this technique to investigate aging, with either freshly isolated primary cells or fixed isolated nuclei. 63 to label epigenetic marks (multiplexing subjected the availability of compatible primary antibodies). We used DAPI to label DNA/chromatin, which enables joint registration of all other epigenetic marks and provides chromatin pattern information. Acquired fluorescence images are processed using custom-built Python scripts, including nuclei segmentation with StarDist66, and feature extraction using threshold adjacency statistic (TAS)68 .We previously pioneered the technique of microscopic imaging of epigenetic landscapes, which captured patterns of nuclear immunostaining of epigenetic marks and derived multiparametric signatures in single cells (TAS)68 . It is i65. We employed Euclidean multi-dimensional scaling (EMDS), to embed the data in a reduced 2-dimensional (2D) Euclidean space. EMDS revealed a clear separation of data points by cell type, CD3+ vs CD3−, mainly by the first dimension (EMDS1), and a clear age-related trajectory within each lineage, mainly by the second dimension (EMDS2)  to low  dimensional space. A relatively small (0.08) EMDS Kruskal’s stress . Cells were labeled with anti-H3K4me1, anti-CD3, and DAPI; image features were computed using H3K4me1, anti-CD3 and DAPI channels as described before (EMDS2) . The Krus stress  confirme73. Thus, we sampled the CD3+/− single-cell data and embedded their relative distances into a 12-dimensional hyperbolic space with curvature (κ = 7.2) using hyperbolic multidimensional scaling (HMDS), optimized as previously described75. HMDS). Notably, the distances among samples when embedded in hyperbolic space exhibit significantly reduced distortions and uncertainties when compared to a Euclidean space with an equivalent number of parameters (dimensions): R2 = 0.99 for HMDS versus R2 = 0.67 for EMDS . This observation substantiates the hypothesis that our data inherently adheres to a hyperbolic structure. We visualized this embedding in a three-dimensional (3D) hyperbolic space. Within this hyperbolic space, the shortest path connecting two data points is commonly referred to as a geodesic, which is curved instead of a straight line like in the Euclidean space  in high-dimensional space better than Euclidean-based methods an space . We obsean space . These f−7), CD3− cells , and total PBMCs  (−9), CD3− cells , and total PBMCs  (We aimed to find the simplest method to extract the observed aging trajectories. We reasoned the geodesic (the shortest path) connecting the centroid (average position) of the youngest and oldest provided the simplest solution. Measurement of epigenetic age can then be defined as the progression along this geodesic. We calculated the geodesic connecting the centroids of the youngest and the oldest mice in full dimensional space, which we will henceforth call the ImAge axis. We then calculated the progression along the ImAge axis via orthogonal projection, which we will henceforth call the ImAge . In the  × 10−6) , left. I× 10−10) , right.Extended Data Fig. 2). This indicated that changes along the ImAge axis are a principal source of variance in the dataset. Indeed, the variance along the ImAge axis accounts for a significant majority of the total variance: 81.5% for CD3+ and 79.1% for CD3−. Note that no regression on chronological age was necessary to reveal the aging trajectory: the trajectory is revealed as a principal feature of the dataset geometry, as seen in both Euclidean and hyperbolic embeddings  of the total variance in the data , CD3− cells , and total PBMCs  . The unanimous improvement of accuracy in all cases conclusively supported SVM as a robust method for obtaining the optimal ImAge axis in Euclidean space.While the centroid-based method provided strong correlations with age, the centroid can be significantly affected by non-normal distributions in the reference groups (young and old) , top. Th70. Therefore, we will use SVM to construct ImAge axes on all subsequent organs and tissues when operating in a Euclidean space, and when more precise measurements are required, we will use the original centroid-based method to construct the ImAge axis in hyperbolic space.Surprisingly, ImAge measurements from the SVM-based method were inferior to those obtained from the centroid-based hyperbolic ImAge. However, despite the higher accuracy, the computational cost of hyperbolic embedding limits the number of cells able to be embeddedTaken together, these results suggest a spontaneous emergence of chromatin and epigenetic trajectories of mouse PBMC aging in both Euclidean and hyperbolic space. Critically, we described the ImAge axis connecting the youngest and oldest samples, which captures the principal (~80%) variance in the dataset.78. We investigated the distribution of ImAge readouts in 5 major organs, including brain, heart, kidney, liver, and skeletal muscles (quadriceps) in 3 cohorts of mice: young (2 months), middle age (15 months), and old (27 months). To directly compare ImAge trajectories in different organs and tissues, we developed a protocol to isolate nuclei from flash-frozen solid tissues (nuclei are PFA fixed immediately upon isolation to prevent any changes in chromatin state) and performed the imaging of chromatin and epigenetic landscape like that described for the freshly fixed cells . Interestingly, the statistical significance of separation appeared to be mark-dependent. Pearson correlation of ImAge with chronological age yielded strong and significant  correlations for brain (r = 0.84 ± 0.05), heart (r = 0.88 ± 0.03), kidney (r = 0.88 ± 0.06), liver (r = 0.81 ± 0.09), and skeletal muscles (r = 0.86 ± 0.04). Furthermore, among the 25 ImAge axes , 12 were most highly correlated with PC1, 10 for PC2 and 1 for PC3, with only 2 having no significant correlation with the first three PCs . Across the epigenetic marks (channels), taking the maximum Pearson correlation of ImAge and the first three PCs yielded strong correlations for skeletal muscle and kidney , moderate correlations for heart and brain  and a weak correlation for liver (r = 0.58 ± 0.15). All correlation values above are presented as mean ± standard deviation across the channels (Supplementary Data Table 1). These results extend our observation in blood to 5 solid organs and suggest a broad utility of ImAge to quantitate age-associated changes in chromatin and epigenetic organization. The predominant correlation with the first principal components indicates that organ aging is a principal source of chromatin and epigenetic texture variance measured by ImAge.A Euclidean ImAge axis was then constructed between the youngest (2 months) and oldest (27 months) samples for each organ separately. In all tissues and organs analyzed, we observed that ImAge was increased with chronological age ; however−4, R=0.81, p=7.2 × 10−3 , R=0.93, p=3.0 × 10−5 for H3K27me3, H3K4me1, and all channels combined, respectively) .Next, we inquired about the relative pace of aging between the 5 different organs. Given the ubiquitous monotonic increase observed in all organs, we calculated the Spearman correlation between each pair of organs. We discovered a strong and robust correlation of ImAge in the heart and quads across several epigenetic marks and chronological age groups  . Other pctively) . There aTaken together, the strong and robust correlation observed between heart and skeletal muscle suggests we have observed organ-level synchronicity in the aging of two organs related by cell type (myocytes). The correlation observed between other pairs may indicate synchronicity that extends beyond cell type and will require further insights into the mechanisms.From our lower-dimensional visualization of ImAge trajectories using MDS in both Euclidian and hyperbolic spaces, it visually appears that the separation between T cells (CD3+) and non-T cells (CD3−) is reduced with age  and c. TExtended Data Fig. 5a). Likewise, the KS distance measurements again revealed a prevailing negative correlation with age in liver, kidney, heart, and quads    for the In sum, our analysis suggests an age-related erosion of cellular epigenetic identity and a loss of cell- and tissue type-specific information with the variable trajectories that depend on particular epigenetic marks and are organ and tissue-specific.81. We compared the effect of CR on ImAge of liver hepatocytes. C57BL/6J males were fed ad libitum (control) or 75% of ad libitum (25% CR diet) from 2 months of age. Nuclei were purified from frozen liver tissues as previously described 82, distributed in 384 well plates, fixed, and immunolabelled with anti-H3K9me3 and anti-H3K27ac (+DAPI). Images and multiparametric epigenetic image features were acquired as before and a Euclidean ImAge axis was constructed as described above. We observed that CR treatment shifts the ImAge readouts in liver hepatocytes towards that of a younger age  slows aging in various species nger age . StatistPrevious work demonstrated the age-accelerating effect of widely used chemotherapeutic agents. We followed Demaria et al., 2017 protocol for doxorubicin treatment . Live hepatocytes were isolated 21 days post injection, to avoid acute stress response to DNA damage. Purified hepatocytes (2-step perfusion method) were plated in 384 well plates, fixed, immunolabelled with antiH3K9me3 and anti-H3K27ac (+DAPI), imaged, multiparametric image features were computed as before and a Euclidean ImAge axis was constructed as described above. We observed that doxorubicin treatment shifted the ImAge readouts from freshly isolated liver hepatocytes toward that of an older age . StatistTaken together these results suggest that ImAge, specifically, its H3K9me3-based component, tracks with the expected change of biological age in the liver cells following longevity interventions.Extended Data Fig. 6). This suggests that the tumor state may appear as a return to a younger state for some specific epigenetic marks. However, these relationships do not dominate when all epigenetic marks are considered. In sum, these results that tumors may appear younger with respect to some epigenetic marks. The significance of this observation will need to be further elucidated.We compared ImAge of liver tumors induced by diethylnitrosamine injection  with normal tissues from the same livers in 8 months old C57BL/6NJ mice using immunolabeling for H3K27me3, H3K27ac, H3K4me1, and DAPI. No difference in ImAge was observed using DAPI or H3K27ac, whereas tumors appeared significantly younger with H3K27me3 , and a trend was observed for H3K4me1, imaged, and multiparametric epigenetic image features were acquired as previously described65.Next we investigated whether or not ImAge readouts map to functionally meaningful organismal readouts  in chronologically identical samples. To this end, we conducted metabolic, cognitive, and motor behavioral tests in chronologically identical C57BL/6 males  and acquired image features from the skeletal muscles. We used young  and old  mice to derive the ImAge axis of chronological young and old controls. We focused on skeletal muscles (quadriceps), which bear the functional load of motor behavior and mediate systemic metabolismR2 = 0.87) evaluated with the shepherd diagram  was significantly better than the EMDS (R2 = 0.35) using the same number of parameters (dimensions), supporting the notion that our data exhibits inherent hyperbolic structure. The curvature of this hyperbolic space was determined to be −8.4 . This finding underscores the prominence of aging as the principal axis of variation within our dataset. Note that a 3-dimensional space in Extended data Fig. 7c and d), thus deriving regression coefficients for 9 orthogonal clusters  correlation with ImAge . Consistent with numerous previous studies, several forms of locomotor activity  were negatively correlated with ImAge (greater activity for younger ImAge). Taken together these 4 major clusters provided strong (Pearson r=−0.62 p=6.3 × 10−3) correlation with ImAge  accounts for 82% of the variance in this dataset. This is in line with the previously observed properties of hyperbolic space that appear to reduce the noise and better represent complex biological dataTaken together, these findings suggest that ImAge faithfully captures salient behavioral/functional readouts, such as locomotor activity, in chronologically identical animals, meaning that ImAge captures salient determinants of biological age.46. We analyzed liver, heart, and skeletal muscle tissues from 13.8 month old i4F and littermate control mice treated for one week with a low dose of doxycycline (0.2 mg/ml)46. Nuclei were isolated from the frozen samples of young (3.2 months), old (13.8 months), and old treated with doxycycline to overexpress OSKM factors (old-OSKM) . We observed that the median ImAge in the old-OSKM group was significantly decreased compared to that in the old group, but was significantly higher than that of the young samples. These results suggest liver and muscle cells in old-OSKM mice are partially reprogrammed on average.We inquired whether ImAge reports the reversion of the aging process using OSKM-driven partial reprogramming in vivoExtended Data Fig. 8b and c, Levene’s test, p < 0.05). In the liver sample, there were significant differences  between the median ImAge of two (#3 and #4) among the five old-OSKM mice samples as compared to the mouse with the lowest median ImAge in the old group (old #5) . These findings suggest that ImAge detects cellular rejuvenation and reports variable reprogramming efficiency, at least in the liver and muscle, between individual organisms.Mouse sample-wise heterogeneity in response to the reprogramming was observed in the comparison of age group-wise variance and sample-wise ImAge readout distributions. At age group comparison, the variance of ImAge in the old-OSKM group was significantly higher than that of young and old groups ((old #5) . In the (old #5) . Almost Extended Data Fig. 9a, left), where OSKM-old #1–4 showed a significant decrease in ImAge. In H3K27me3, OSKM-old mice #1, #3, and #4 were found to be significantly reprogrammed. H3K27ac showed the weakest impact; only one significantly reprogrammed mouse was found (OSKM-old #4). In the muscle, all channels showed almost equal strength of reprogramming with significant decreases of ImAge observed in two mice (OSKM-old #5 and #3/#4), except for H3K9ac, which showed a significant decrease in three mice (OSKM-old #3–5). DAPI and H3K27me3 had the same mice pair significantly reprogrammed (#3 and 5) .We observed different degrees of partial reprogramming per epigenetic marks/channels. To evaluate the channel-wise difference, the ImAge axis was constructed in the same way as described above for each channel . In the liver, strong partial reprogramming was observed using DAPI and H3K9ac . The signature cells for each age group (young or old) were defined by single cells, whose ImAge readout was hardly observed in the other group. For instance, young signature cells were cells with an ImAge readout lower than the 5th percentile of old ImAge, meaning young cells can only be observed at a maximum of 5 percent in the old group  in the liver and a significant decrease of the old signatures in the muscle . We observed three different patterns of significant changes in the proportion of signature cells; an increase of young signature cells, a decrease of old signature cells and both of them. Particularly in the old-OSKM#4 in the liver, #3 and #5, which were three of the most reprogrammed mice, showed a significant increment of young signature and decrement of old signature .We leveraged single-cell-nature of imaging to get insights into the heterogeneity of reprogramming, which is of critical importance for rejuvenationld group . Conversignature  and h. B87. Further dissecting this phenomenon, ImAge uncovered reprogramming-associated changes of individual epigenetic marks and provided first insights into the dynamics of epigenetic-based cellular age in the reprogrammed samples.Taken together, these results suggest that ImAge is decreased in some of old-OSKM samples compared to old samples in liver and skeletal muscles, confirming the heterogeneity of in vivo reprogramming6. In addition, existing histologic, capturing tissue and organ morphology, biomarkers are less popular in aging research due to the measurement difficulties, tissue specificity, and scarcity of computational methods6. Here we describe novel class of biomarkers of aging, ImAge, based on imaging of chromatin and epigenetic patterns in single cells.Several major categories, including molecular, measuring specific molecules of omics, physiological, measuring physical performance and physical characteristics, and digital health, measuring wearable and non-wearable, biomarkers of aging have recently been proposedOne of our most surprising findings is the discovery of intrinsic aging trajectories formed by multiparametric epigenetic image features that could be rendered and visualized using Euclidian and hyperbolic metrics. Remarkably, no regression was required for ImAge axis construction, yet all intermediate age groups were naturally arranged in a highly ordered manner. Serendipitously, the ImAge axis emerged as a principal source of information in the image data manifold. Given no prior expectation, this is a compelling property of ImAge, which indicates that we have extracted information proximal to an aspect of the aging phenomenon. We reason this aspect is related to the robust spatial organization of chromatin topography in individual nuclei in each organism and their evolution with time.37. DNAm clocks are based on a small subset of all CpGs in the genome . Although the actual variance of genome-wide DNAm is difficult to capture due to sample-wise variations in bisulfate sequencing, we estimated that rodent DNAm clocks extract from 0.15% (our estimate from publicly available mouse data) to 4.7%88 (rat DNAm clock) of the total variance in the DNAm dataset. In contrast, ImAge captures the data manifold’s major (~80%) characteristics, including in the case of chronologically identical mice (see below). We posit that the highly ordered nature of the image feature space results in our ability to perform direct and precise measurements of the relative distances between individual samples.As an imaging-based approach, ImAge is complementary to previous aging biomarkers, such as DNAm clocks, which utilize a fundamentally different technique (sequencing). While ImAge is intimately linked with chromatin and epigenetic organization and is blind to sequence-level modifications, DNAm presents a sequence-level approach that is largely blind to the 3-dimensional organization of chromatin. Another notable difference between ImAge and DNAm clocks is the utilization of linear regression: DNAm clocks universally regress CpG methylation levels against chronological age (i.e. building DNAm clock) to construct robust population average useful for numerous applications89 is likely not the issue. Rather the pixel values per channel and their relative intensities . Future work should investigate the stability of the image-feature manifold across imaging conditions to separate biological variability at the single cell level from technical limitations. Fiduciary samples applied across multiple experiments and computational developments in deep learning provide the empirical path to addressing these questions.However, ImAge’s advantages do not come without limitation. DNAm clocks have become the gold standard for aging biomarkers, in part because they enable individual measurements to be easily compared against the population without reconstruction of entire model. A key part of the universality of these clocks is the stability of both DNAm itself and the biochemical technique to sequence CpGs. However, imaging is quite the opposite: image features are sensitive to imaging conditions (such as microscope setup and labeling procedures), leading to many opportunities for instability of feature values between experiments. Currently, this limitation demands that ImAge axes must be computed for each new sample combination. However, it is worth noting that the spatial organization of chromatin, the imaging substrate, although fundamentally variable at single cell level90, limiting its practical applicability. For instance, exploration of intrinsic geometry using Euclidean and hyperbolic embedding could be challenging because it requires the same set of features to be compared for all single cells. While the image analysis presented here  struggles to fully resolve age-related chromatin changes at the single-cell level, we have only scratched the surface of the available imaging capabilities: high resolution confocal microscopy and advanced colocalization features present clear path towards extracting significantly more information from nuclear images and, potentially, highly structured single-cell resolution. Indeed, our accuracy measurements show near perfect separation accuracy at a single-cell resolution is not far away . Thus, ImAge, being in its nescient stages of development, promises significant room for improvement on both imaging and computational fronts.Current single-cell DNAm analysis has been relying on statistical imputation due to sparsity of the methylation readouts for single cells78 while the Tabula Muris Senis studies demonstrated a similar yet asynchronous inter-organ progression of aging91. Some degree of organ connectivity is plausible so that the decline of one organ can promote the dysfunction of other organs, accelerating organismal aging92. We observed an overall monotonic progression of ImAge along chronological age for all epigenetic marks and 5 organs tested. Together with our observations in PBMCs, it suggests that a monotonic correlation of ImAge and chronological age is universal. We observed a strong correlation of ImAge between the heart and skeletal muscles (quads) for all epigenetic marks (and DAPI) as well as the heart and kidney for all mark combinations. ImAge of the liver also correlated with the brain and kidney. Note that ImAge correlation between organs doesn’t mean that the pace of ImAge progression is the same in those organs. Incidentally, a metabolic imbalance of lipids accelerates inflammation and leads to lipotoxicity, mostly afflicting the kidney, heart, and skeletal muscle93, and lipotoxic insults precipitate aging94. Immobilization and atrazine induce oxidative stress in the liver, kidney, and brain, with curcumin and quercetin exhibiting a protective effect96.Imputing organ aging from plasma protein suggested different rates of organs and systems aging within the same organism (aging ageotypes)44 which increases the noise in part through cell-to-cell variation in gene expression97, loss of lineage fidelity with age, and activation of lineage-inappropriate genes during aging102. Reactivation of human endogenous retroviruses during aging could also contribute to this process104. Our observations are consistent with the information theory of aging, which proposes that aging in eukaryotes is associated with loss of epigenetic information over time107 and that loss could be causative44.Cellular epigenetic identity is integral to governing cell functionality and maintaining tissue homeostasis. We observed an age-related juxtaposition of cellular states and a diminished separation of cellular identity among diverse tissues or cells, suggesting an erosion of cellular chromatin and epigenetic identity. Although we documented this effect for CD3+ and CD3− cells in the blood and between 5 different organs, this is likely a general phenomenon. This could be explained by the age-related erosion of epigenetic and chromatin landscape110 and chemotherapy treatments have damaging effects on the entire organism and accelerate the aging process 114 including increased frailty, chronic organ dysfunction, increase in cardiovascular diseases, cognitive impairment, and secondary cancers 119. We observed a shift of ImAge towards old age in mice treated with doxorubicin, resembling the observations in humans 120. The changes were driven by H3K9me3, suggesting possible changes in heterochromatin. If ImAge could faithfully report the effects of other chemotherapy drugs and in different organs, it will be useful to design interventions that increase the resilience to chemotherapy 121, and to reduce the aging effects of chemotherapy.DNA damage is known to induce cancer and accelerate aging 81, albeit the full picture could be more complex 123. successfully applied CR regimens help to understand the biology of aging 126 and could help recovery after chemotherapy in clinic 121. We have observed a shift in ImAge readouts in CR animals towards that of young animals consistent with the phenotypic observations. Again, the changes were driven by the H3K9me3 mark, which has been robustly associated with aging128 further substantiating the relevance of ImAge readouts for measuring biological age. It will be important to further refine these analyses, covering different CR regimens in mice and other species , and to correlate the epigenetic changes with functional readouts at the organismal level as well as with various OMICs datasets .Because CR robustly increases maximum lifespan and delays biological aging in diverse scenarios 31. However, recent studies matching tumor and normal tissue from the same organ/individual painted a more complex picture with deceleration of DNAm age in stomach adenocarcinoma129 and no change in triple-negative breast tumors130. Analysis of ~439 endometrial cancers suggested unchanged DNAm age in 90% of tumors while DNAm age deceleration was associated with advanced diseases and shorter patient survival131. Given that extended partial reprogramming in vivo results in tumors132, a younger chromatin and epigenetic age of tumors is rather intuitive.We observed younger ImAge in liver tumors, but only for H3K27me3 mark. Early studies suggested DNAm age acceleration in tumors compared to normal tissues88. Here, the largest group of behaviors that inversely correlated with ImAge comprised various flavors of locomotor activity. Age-related decline in locomotor activity is a universal feature of living organisms well documented in Drosophila133 and insects in general134, rodents135, dogs136, primates137, and humans138 where it is associated with cognitive impairment and decline in brain dopamine activity139. Locomotion is a very reliable factor for exploratory behavior in mice141. The only correlate of older ImAge was the respiratory exchange ratio (RER), previously observed to be increased in old mice only in the dark phase84. Taken together, the nature of the correlated behaviors suggests that ImAge captures appropriate functional readouts to represent biological age. Further, ImAge captures 82% of the variance in this dataset comprising chronologically identical mice. Therefore, the principal aspect captured by ImAge represents the biological difference between animals, i.e., their biological age.We discovered that in chronologically identical mice, ImAge was inversely correlated with a weighted combination of behaviors. Indeed, a significant association between DNAm clock and physical function after controlling for age has been reported142. Given the robust correlation of ImAge with key physiological, behavioral, and metabolic metrics underlying functional decline with age, we posit that ImAge represents the first-in-class imaging-based biomarker of aging with single-cell resolution.Finally, ImAge detected liver and muscle rejuvenation following one cycle of OSKM-mediated reprogramming in vivo. The advantage of analyzing a single cycle is that we detect the “proximal” effects of OSKM overexpression. With multiple cycles, the combined effect over months may include many secondary effects. Although the final outcome is more pronounced, the underlying mechanism is likely to be “buried” in many layers of effects over months. Curiously, different mice appeared to be mostly reprogrammed for liver and skeletal muscles, with DAPI and H3K9ac being the most informative to detect the change. Although we didn’t have H3K9me3 for this experiment the combination of DAPI and H3K9ac (complimentary to H3K9me3) suggests that we might be detecting heterochromatin changes. It will be informative to directly compare the performance of DNAm clocks and ImAge to quantify the apparent heterogeneity of in vivo reprogrammingExperiments were conducted according to guidelines and protocols approved by the Institutional Animal Care and Use Committee (IACUC) of Sanford Burnham Prebys Medical Discovery Institute. Data presented within this manuscript were obtained using male mice. C57BL/6 mice, ranging in age from 2 to 27 months old, and were obtained from National Institute on Aging, Aged Rodent Colonies (RRID:SCR_007317).144, and qNMR body composition analysis with EchoMRI instrumentation has been proposed to be “gold standard” methodology for metabolic studies in the mouse 145. Following calibration, each mouse was put in a holder and placed into the EchoMRI chamber and lean mass, fat mass and water mass was calculated.The EchoMRI 3-in-1 instrument  is a quantitative nuclear magnetic resonance (qNMR) imaging system for whole body composition analysis of unaesthesized small animals The optomotor allows for assessment of visual ability and consists of a stationary elevated platform surrounded by a drum with black and white striped walls. Each mouse is placed on the platform to habituate for 1 minute and then the drum rotates at 2rpm in one direction for 1 minute, is stopped for 30 sec, and then rotates in the other direction for 1 minute. The number of head tracks (15 degree movements at speed of drum) is recorded. Blind mice do not track the moving stripes.147). Testing occurred in clear respiratory chambers (20 × 10 × 12.5 cm) equipped with a sipper tube delivering water, food tray connected to a balance, and 16 photobeams situated in rows at 0.5 in intervals to detect motor activity along the x- and z-axes. Room air is passed through chambers at a flow rate of 0.5 L/min. Exhaust air from each chamber is sampled at 15-min intervals for 1 min. Sample air is sequentially passed through O2 and CO2 sensors (Columbus Instruments) for determination of O2 and CO2 content, from which measures of oxygen consumption (VO2) and carbon dioxide production (VCO2) are estimated. Outdoor air reference values are sampled after every 8 measurements. Gas sensors are calibrated prior to the onset of experiments with primary gas standards containing known concentrations of O2, CO2, and N2 . Respiratory exchange ratios (RER) were calculated as the ratio of carbon dioxide production (VCO2) to oxygen consumption (VO2). Energy expenditure measures *VO2 (in liters)]) were corrected for effective metabolic mass by using each mouse’s lean mass obtained from the EchoMRI test.Indirect calorimetry was performed in acclimated, singly-housed mice using a computer-controlled, open-circuit system (Oxymax System) that is part of an integrated Comprehensive Lab Animal Monitoring System  as well as to capture spontaneous activity measures. The apparatus is a square white Plexiglas (50 × 50 cm) open field illuminated to 600 lux in the center. Each animal is placed in the center of the field and several behavioral parameters  are recorded during a 5-minute observation period and analyzed using Noldus Ethovision XT software.This test predicts how animals respond when introduced into a brightly illuminated open arena 151. The basic principal is that animals explore novel environments and that with repeated exposure decreased exploration ensues . A subsequent object substitution results in dishabituation of the previously habituated exploratory behavior (154) and is expressed as a preferential exploration of the novel object relative to familiar features in the environment. Mice were individually habituated to a 51cm × 51cm × 39cm open field for 5 min. They were then be tested with two identical objects placed in the field for 5 min. After two such trials (each separated by 1 minute in a holding cage), the mouse was tested in the object novelty recognition test in which a novel object replaced one of the familiar objects. Behavior was video recorded and then scored for object contact time. The first time the mice were tested the objects used were clear plastic rectangular boxes filled with blue marbles and green plastic drink bottles filled with water and for the second test the objects were amber glass bottles and glass flasks filled with beige marbles. All objects were too tall for the mice to climb up on and too heavy for the mice to move.This test assays recognition memory while leaving the spatial location of the objects intact and is believed to involve the hippocampus, perirhinal cortex, and raphe nuclei 156. Nontoxic paint was applied to each mouse’s paws (a different color was used for front and back paws). The mouse was then placed at one end of a runway covered in paper and allowed to ambulate until their paws no longer left marks. Measurements were forelimb and hindlimb stride lengths (left and right) and front and back leg stride widths. Three full strides were averaged for each mouse’s values. Data were excluded from mice that did not make 3 measurable strides (i.e. they circled or stopped).Basic gait measures can be assessed using simple footprint pattern analysis 159 sensitive to impaired hippocampal function 160. Mice learn to find an escape chamber (19 × 8 × 7 cm) below one of twenty holes  below an elevated brightly lit and noisy platform  using cues placed around the room. Spatial learning and memory were assessed across 4 trials (maximum time is 3 min) and then directly analyzed on the final (5th) probe trial in which the tunnel was removed and the time spent in each quadrant was determined, and the percent time spent in the target quadrant  was compared with the average percent time in the other three quadrants. This is a direct test of spatial memory as there is no potential for local cues to be used in the mouse’s behavioral decision.This is a spatial memory test Grip strength was measured with a mouse Grip Strength Meter (Columbus Instruments) according to the manufacturer’s instructions . All-limb measurements were performed with the angled grid attachment, pulling the mouse towards the meter by the tail after engagement of all limbs. Four consecutive measurements per mouse were taken and the highest three values were averaged, and data were expressed as newtons of peak force.162. Mice were held so that only their forelimbs contact an elevated metal bar  held parallel to the table by a large ring stand and let go to hang. Each mouse was given three trials separated by 30 seconds. Each trial was scored as follows and the average for each mouse was calculated: 0 — fell off, 1 — hung onto the wire by two forepaws, 2 — hung onto the wire by two forepaws, but also attempted to climb onto the wire, 3 — hung onto the wire by two forepaws plus one or both hindpaws around the wire, 4 — hung onto the wire by all four paws plus tail wrapped, 5 — escaped (crawled to the ring stand and righted itself or climbed down the stand to the table). Latency to falling off was also measured up to a maximum of 30 s.The hanging wire test allows for the assessment of grip strength and motor coordination 156. An Accurotar rotarod apparatus  was used in these studies. A protocol was used whereby the rod starts in a stationary state and then begins to rotate with a constant acceleration of 10 rpm. When the mice were incapable of staying on the moving rod, they fell 38cm into a sanichip bedding filled chamber, breaking a photobeam in the process. The time of fall  was recorded by computer. The mice were tested in four sets of 3 trials, alternating directions between sets which were 30 min apart.Rotarod balancing requires a variety of proprioceptive, vestibular, and fine-tuned motor abilities as well as motor learning capabilities 163. Mice are motivated to run to exhaustion in order to escape a shock at the base of the treadmill. Mice were trained to run in three daily 5 min sessions in which stopping would result in the mice touching the back of the apparatus and experiencing a mild shock (200 msec pulses of electric current with pulse repetition rate of 3 times per second (3 Hz) and an intensity of 1 mA). The treadmill speed for training was 10 m/min (0.373 mph). For the exhaustion test, the speed was initially set at 10 m/min for 5 min, and was increased 2 m/min every 2 min up to a maximum speed of 46 m/min (1.7 mph). The mice were run until they were exhausted or the maximal speed was achieved (which would mean a maximum run time of 41 min). Exhaustion was defined as the inability of the animal to run on the treadmill for 10 sec despite receiving shocks, a maximum of 30 mild shocks. To prevent injury, the mice were monitored carefully and continually during each session, and immediately upon meeting the criterion for exhaustion the shock grid was turned off and the mouse was removed from the treadmill.The treadmill exhaustion test evaluates exercise capacity and endurance 166. Organs and tissues were collected from freshly dissected mice, snap frozen using liquid Nitrogen, and stored at − 80°C. Organs and tissues were then transferred to a pre-chilled mortar and laid on top of dry ice; liquid Nitrogen was poured over the frozen tissue and a pestle was used to grind and pulverized the sample until a uniformly fine powder was obtained. Pulverized sample was the aliquoted and returned to − 80°C. To extract nuclei from frozen aliquots, 500 ul homogenization buffer (Nuclear Isolation Buffer 1 (NIM1) consisting of 250 mM Sucrose, 25 mM KCL, 10 mM Tris-buffer pH 8.0, 5 mM MgCl2, 1 mM DTT, and 10% Triton X-100) were added to powdered tissue and transferred to the mixture a glass Dounce homogenizer and dounced ~ 10 times (avoiding bubbles) on ice. Add homogenization buffer up to 1 mL and filter homogenization solution through a 40 mm cell strainer. Centrifuge filtered solution at 600×g  for 4 min at 4° C. Aspirate supernatant and resuspend in 200 mL of PBS. Nuclei were then count on CellDrop FL (DeNovix) using 1:1 Acridine Orange /Propidium Iodide and homogenization solution. Samples were diluted in PBS to 1 million/mL to seed each well  of 384 well plate  pre-coated (1 mL/25 cm2) with poly-L-Lysine (50 mL/mg). Centrifuge plate at 4000×g for 15 min at 4° C and immediately added 60 mL of 4% PFA to each well and incubate for 15 min at 4° C. Followed by one wash of PBS then proceed with microscopic imaging of epigenetic landscapes.Flash-frozen in liquid nitrogen (stored at −80°C) is a common practice to preserve tissue and organs that are not to be processed immediately 2) with poly-L-Lysine (50 mL/mg). Centrifuge plate at 4000×g for 15 min at 4° C and immediately added 60 mL of 4% PFA to each well and incubate for 15 min at 4° C followed by PBS wash.200 mL of blood was collected retroorbital for each mouse and immediately mixed with an equal volume of 50 mM EDTA (to prevent coagulation). Blood mixture was further diluted with 200 mL of PBS and carefully layering on top of 750 mL of Ficoll-Paque Plus (Millipore Sigma Cat. No. GE17-1440-02); followed by density gradient centrifugation at 700×g for 30 minutes at room temperature. The PBMC rich layer (cloudy phase) was carefully collected avoiding mixing the above and below layers and transferred to a new tube containing 10 mL of PBS. The PBMC mixture was centrifuged at 700×g for 20 minutes at room temperature and then removed supernatant and resuspend pellet in 1 mL of PBS. Isolated PBMC’s were counted manually using a hemocytometer (Hausser Scientific Cat. No. 3120). Samples were diluted in PBS to 1 million/mL to seed each well  of 384 well plate  pre-coated  10 mg/Kg. Doxorubicin was diluted in 150mM NaCl solution, and control mice were injected only with the vehicle solution (150mM NaCl). Fourteen days after treatment, mice were sacrificed and liver collected and immediately snap frozen in liquid nitrogen.Animal studies were conducted in accordance with approved protocols submitted through the respective Institutional Animal Care and Use Committees (IACUCs) at the University of Wisconsin Madison. Caloric Restriction mice: male C57BL/6N mice were individually housed under pathogen free conditions. Mice were randomized into control or restricted groups at 2 months of age and fed the AIN-93M semi-purified diet (Bio-Serv) either a Control diet (95% ad libitum) or Restricted diet (25% less than control). The mice were sacrificed at 7 months of age and tissues were harvested, flash frozen and stored at −80°C.Animal studies were conducted in accordance with approved protocols submitted through the respective Institutional Animal Care and Use Committees (IACUCs) at the University of California San Diego. C57BL/6(?) male mice were intraperitoneally injected with 25 mg/kg diethylnitrosamine  at postnatal day 15. At 8 months of age the mice were then sacrificed and dissected tumor and non-tumor parts of the liver and samples were immediately fresh frozen using dry ice/2-methylbutane bath and then stored at − 80 °C. All tissue collection occurred during a 4-hour time frame  to minimize circadian effects on metabolism, proliferation, etc.™ 488 (Thermo Fisher Scientific Cat. No. A11034), and Donkey anti-Mouse IgG (H+L) Alexa Fluor™ 488 (Thermo Fisher Scientific Cat. No. A31570). Wells were counterstained with DAPI (Thermo Fisher Scientific Cat. No. D1306) during the secondary antibody staining and plates were sealed with adhesive foil (VWR Cat. No. 60941–124). Cells/nuclei were imaged on either an Opera Phenix high-content screening system (PerkinElmer) or an IC200-KIC  using a 20x objective. At least five fields/well and a total of 9 z-stacks at a 1mm z-step for Opera Phenix and nine fields/well and a total of 10 z-stacks at a 1mm z-step for IC200 were acquired and five wells per mouse sample were imaged. Unless stated otherwise, at least three wells and a minimum of 300 cells for each condition were used for analysis.Wells were blocked with 2% BSA in PBS 0.5% Triton X-100 for 1 hour at room temperature, and then incubated with primary antibody overnight at 4C and then washed with PBS 3× (5 minutes each at room temperature). Next, wells were incubated with secondary antibody overnight at 4C and then washed with PBS 3× (5 minutes each at room temperature). Antibodies were used at the following concentrations: Anti H3K27ac 1:1000 (Active Motif Cat No. 39685), and /or Anti H3K27me3 1:1000 (Active Motif Cat No. 39155), and/or Anti H3K4me1 1:1000 (Active Motif Cat No. 61633). Antibodies were detected using the following secondary antibodies for their appropriate hots: Goat anti-Rabbit IgG (H+L) Alexa Fluor168 artifact of the images was corrected using BaSiC Illumination correction on all channels as a preprocessing step167. The segmentation was performed using StarDist[Citation error] applied to DAPI images. We defined cell nuclei as the segmentation masks after the removal of small objects with an area corresponding to a radius less than 3–7μm, assuming spherical shape, dependent on tissue and microscope used. The cell nuclei masks were applied to all channels to isolate raw images of each nucleus in each channel. Texture features  were calculated from each nucleus for each channel as previously described68. In this study, 28 binarized images per epigenetic mark/channel were obtained by applying band-pass thresholding with the following intervals: Image features were extracted for each single cell (nucleus) within a segmentation mask annotating cell nuclei on the images. The radial falloff The ImAge axis was obtained using z-scored features of young and old groups based on their centroids or linear SVM models. The centroid-based axis was then defined by the vector from the centroid of the young group to the centroid of the old group. The SVM-based axis was defined by the vector orthogonal to the hyperplane optimized to separate young and old groups; the precise location of this axis can be defined as the intersection of the orthonormal vector to the hyperplane and the centroid of all data points. The calculation of centroids and optimization of SVM models were performed using all features (without feature selection) over all data points resampled using bootstrap (see the following section for details of bootstrapping). It is important to note that the ImAge axis does not deform the feature space in any way; it is a simple linear transposition and projection.The robustness of the ImAge axis was validated in 100 iterations of tests, where 75% and 25% of data were randomly sampled without replacement for training (axis construction) and testing (projection onto the axis), respectively. This training step only involves the young and old groups. Importantly, the other age or condition groups  were not included in the training.At each iteration of training/testing, we resampled single cell data with bootstraps of 200 cells to obtain the average data point representative to each mouse sample with uncertainty of the average. The bootstrap was performed 1000 times for each mouse sample to equalize the number of data points per mouse. In our analysis, the utilization of bootstrap sampling is essential to examine the aging related changes in the cell composition. Throughout the aging process, the cell identity remains unchanged, while the composition of the cell distribution undergoes variations. For instance, individual T cells from a young and an older mouse may appear identical, but when sampling a bootstrap of 200 cells from blood samples, the composition of cells, or the ratio between different cell types, differs between young and old mice. Clustering the single cells do not reveal the difference between young and old samples but simply put the cells of the sample type together.The ImAge orthogonal distance was defined by the distance to the ImAge axis. Thus, the orthogonal component can be considered the positive scalar value representing the distance of a datapoint to the ImAge axis. The orthogonal distance rd removed were considered robust and significant.To select the most robust correlations, we removed 1 age group iteratively and corrected for multiple comparisons. Spearman correlations were calculated via pairwise comparisons between all combinations of either 2 or 3 age groups per organ pair per channel. P-values were post-hoc corrected for multiple comparisons using the Bonferroni method. An alpha of 0.05 was applied to the p-values and significant correlations per organ pair per channel were counted. Organ pairs which were correlated in both all age groups and 2 age groups with the 3169, or information distance metric we call here, is a measure of information that is not shared by both variables. Like the correlation and correlation distance, mutual information and information distance measures the dependence and independence between two random variables. However, unlike the correlation and correlation distance that measures the linear relationship between two variables, mutual information and information distance can capture the nonlinear relationship between two variables. The information distance can be written in terms of marginal entropies: We have used a distance metric based on mutual information. Considering two random variables In practice, we can consider two samples as 170. The hyperbolic geometry can be visualized using Poincare half space model and Poincare disk 170. Hyperbolic space is better suited compared to Euclidean space for representing complex multipara metrical biological datasets. This is because hyperbolic space enables using fewer dimensions, inferring the hidden nodes based on the activity of observed “leaf” nodes, and reading out the “centrality” of each node 173. Using the information distance metric, the nodes in the middle are features that sample take different values and the nodes on the boundary are samples. In another words, the sample is a representation of a serious feature value selection starting from middle to boundary.Hyperbolic geometry provides continuous approximation to tree-like hierarchical system, resulting in the distinguishing property of exponential expansion of states compared to quadratic expansion of states in Euclidean space 72, which is a version of MDS in hyperbolic space. Euclidean MDS minimizes the difference between the distances calculated in the original Euclidean data space and the distances calculated in the high dimensional reduced space. Once we specify the dimension of the reduced space, the quality of embedding could be assessed using Shepherd diagram, which compares the distance in the original space and the distance in the dimensionality reduced hyperbolic space.Considering the aging process is due to a sequence of biological changes, and each change is chosen from a variety of choices, hence the number of possible states increase exponentially. We employed the Hyperbolic Multidimensional Scaling (HMDS) In order to quantify the performance of the dimension reduction using MDS, we can plot the Shepherd diagram where we compare the distances between samples in the original high dimensional space and the distances between samples in the lower dimensional embedded space. In general, the better the MDS performs, the closer the distances between samples embedded in the lower dimension correlate linearly with the distances between samples in the original space. The linear relationship ensures that the distances between samples are not distorted when we embed the samples from original high dimensional space to lower dimensional space. The correlation, the tightness of linear fitting, ensures the accuracy and robustness of the embedding.174. The tangent space is Euclidean, and the curved geodesic in the hyperbolic space can be approximated by a straight line in the tangent space which is easier to compute.We took advantage of the logarithmic and exponential representations, which map the points from the hyperbolic space to the tangent space centered at a reference point and vice versa In our analysis, we consider n samples with distinct biological ages represented as the column vector To ensure the uniqueness of the linear coefficients To assess changes in epigenetic variation across diverse cell types during aging, we utilize two key metrics: the Silhouette score and the Kolmogorov–Smirnov distance (KS distance). The Silhouette score evaluates clustering performance, adaptable to both original and dimensional reduced data. In this study, we calculate Silhouette scores directly on raw data to avoid the bias introduced in the various dimension reduction processes. We utilize both the information distance and Euclidean distance metrics to illustrate changes in separation among different cell types from both an informational and a value perspective. Also, we employ 100 bootstraps to estimate the silhouette score within each age group, which allows us to assess the statistical stability and robustness of the silhouette score across various age categories.To further confirm our observation of reduced separation between cell types during aging, we need a metric quantifying differences across cell types in individual features. The KS distance measures the distance between one-dimensional distributions characterizing distinct cell types. We sample 5000 cells per feature to capture distributions of specific cell types at given ages. Evaluating differences across To compare each mouse at the individual level, the SVM model was trained using averaged data points obtained by bootstrapping 200 single-cell data points (see Methods for details of bootstrap sampling). The accuracy of the separation of young and old samples was 1.000 and 0.997 in testing for the liver and muscle samples, respectively, in 100 iterations of tests using random data splits (see Methods for details of training/testing scheme). We obtained ImAge based on the distance from the hyperplane of a linear SVM using 3D TAS features extracted from confocal images.The signature cells for each age group (young or old) were identified as single cells where the ImAge readout was hardly observed in the other group and can be given by following indicator functions for young signature th percentile value of single-cell ImAge readout in old samples, and th percentile  of old in Here, 76. First, reduced representation bisulfate sequence (RRBS) data collected from C57BL/6 whole blood samples of various ages were downloaded from GEO (accession number GSE80672). Only control mice were obtained for the purposes of comparison. Data preprocessing was performed as previously described with the following changes: newer versions of Trim Galore! (v0.6.1)175 and Bismark (v0.24.2)176 were used for adapter trimming and sequence alignment. Due to the sparsity in RRBS data versus our TAS features, CpGs with less than 99% coverage across all samples were eliminated for PCA for a fairer comparison between techniques. Any missing WLMT clock CpG sites after filtering were replaced. Total variance was calculated from the densified data, which was subsequently used to calculate the proportion of variance explained by the WLMT clock. To further equalize the comparison, DNAm data was randomly sampled without replacement  for 100 iterations and PCA and variance explained were computed for each iteration. Here we report the 1st-99th percentile of these 100 iterations, and confirmed the total variance explained without subsampling is within these bounds.To compare ImAge to a comparable mouse DNA methylation clock, we selected the whole lifespan mouse multi-tissue (WLMT)


Background: Spinal anaesthesia is the most commonly used technique for lower limb orthopaedic surgeries as it is economical and easy to administer. Opioids as adjuvants to local anaesthetics during spinal anaesthesia have played a vital role in reducing post-operative pain qualitatively and effectively.Methods: This prospective randomised study was conducted on 100 patients divided into two groups scheduled for lower limb orthopaedic surgeries. Group bupivacaine fentanyl (BF) received 25 mcg of fentanyl with 15 mg of bupivacaine and Group bupivacaine nalbuphine (BN) received 1 mg of nalbuphine and 15 mg of 0.5% bupivacaine. The aim of the study was to compare the analgesic efficacy of intrathecal fentanyl and nalbuphine as an adjuvant to hyperbaric bupivacaine for spinal anaesthesia. Duration of effective analgesia, haemodynamic parameters, onset and duration of sensory and motor block, adverse effects, and visual analogue scale (VAS) score were assessed.Results: Duration of effective analgesia was 388±24.88 minutes in the BN group and was higher  in comparison to the BF group, which was 304.70±15.76 minutes.Conclusion: Nalbuphine was more effective than fentanyl in providing post-operative analgesia when used as an adjuvant to hyperbaric bupivacaine. Intrathecal adjuvants to local anaesthesia have been introduced to boost clinical effectiveness and duration of analgesia following orthopaedic surgical operations as spinal anaesthesia alone provides poor postoperative analgesia. Intrathecal opioid effectively extends postoperative analgesia ,2. OpioiOnly a few trials have studied the efficacy of intrathecal fentanyl and nalbuphine as adjuvants to hyperbaric bupivacaine in lower limb orthopaedic surgeries ,7. The cThe study was a randomized, prospective, double-blind study done in the Department of Anesthesiology at Pradyumna Bal Memorial Hospital, Kalinga Institute of Medical Sciences, Bhubaneswar, India. The Institutional Ethics Committee of Kalinga Institutional Medical Sciences approved the study . This study was registered with the Clinical Trial Registry of India (CTRI/ 2021/01/030252). All participants were asked to sign an informed consent form after being educated about spinal anaesthesia and the risks involved. A total of 100 suitable cases were included in our study.Inclusion and exclusion criteriaInclusion criteria were patients posted for orthopaedic procedures on the lower limbs, American Society of Anesthesiologists (ASA) I and II, and age of 18-65 years. Exclusion criteria were: body mass index (BMI) more than 30, height under 155 cm, contraindications to spinal anaesthesia , patients using tranquillizers, antipsychotics, hypnotics, or other central nervous system depressants, patients who have previously experienced adverse reactions to opioid reactions, and pregnant patients.ProcedureEach patient underwent a full pre-anaesthetic evaluation, which included a review of their medical history, clinical examination, systemic evaluation, and spine examination. Patients were instructed on how to use a visual analogue scale (VAS). Alprazolam 0.5 mg was given the night before surgery and on the morning of the operation with a sip of water.A computer-generated randomization table was used to assign the 100 patients at random to two groups (50 each) and sequentially numbered opaque sealed envelopes were used for concealment. Group bupivacaine fentanyl (BF) received 25 mcg (0.5 ml) of fentanyl together and 15 mg of diluted 0.5% hyperbaric bupivacaine, and Group bupivacaine nalbuphine (BN) received 1 mg (0.5 ml) of nalbuphine and 15 mg of 0.5% hyperbaric bupivacaine.Ringer lactate or regular saline at a rate of 15 ml/kg was used to preload the patient. Standard monitoring included a pulse oximeter, non-invasive blood pressure (NIBP), and electrocardiogram. Under all aseptic conditions, a 25G Quincke spinal needle was softly inserted in the midline of the L3-L4 /L4-L5 intervertebral space and advanced to the subarachnoid space. The unimpeded flow of cerebrospinal fluid via the needle verified the needle's location in the subarachnoid area. With the bevel end cephalad, the study medication (3.5 ml) was slowly injected into the subarachnoid area at a rate of 0.25 ml/sec. The patient was immediately placed in a supine position once the needle was withdrawn. A face mask delivering 100% oxygen at a flow rate of 4 L/minute was used. Dermatomes levels were checked every two minutes until the level of T10 was reached. Loss of cold sensation (cotton swab soaked in spirit) in the mid-axillary line and loss of pinprick sensation to a 23G hypodermic needle were used to determine sensory level. Surgery was commenced after T10 level was reached. A modified Bromage scale was used to evaluate the motor block that immediately followed the sensory block.Following surgery the sensory and motor status were checked every two minutes for the first 10 minutes, then every five minutes for the next 10 minutes, and finally every 15 minutes until the sensory level regressed to dermatome S2 and the motor scale reached modified Bromage grade 0.The following variables were defined : (i) TimThe modified Bromage scale was used to subjectively rate the degree of motor blockage in the lower limbs : 1 = PatAdverse effects like nausea, vomiting, bradycardia, hypotension, pruritus, sedation, and respiratory depression were noted both during and following surgery and were treated as per institutional protocol. Sedation was scored on the Ramsay sedation scale .Following surgery, patients were moved to the post anaesthesia care unit after measuring pulse, blood pressure, oxygen saturation, respiration rate, and clinical evaluation of motor as well as sensory blockade. Continuous monitoring and recordings at regular intervals were done until the complete return of sensory and motor function.Using a VAS with a range of 0 to 10 (with 0 denoting no pain and 10 denoting the most intense pain), the postoperative pain score was recorded. Injection paracetamol (15 mg/kg) was administered as rescue analgesia when VAS was > 4.Data analysisConsidering the mean difference and effect size of a previous study by Umesh et al.  with 95%The study was conducted with a total of 100 patients randomly divided into two groups of 50 each  as shown in Table The time taken to reach T10 segment is faster in the BN p=0.822) group. The highest sensory level was achieved faster in the BF group (p=0.225)  Table . Althoug Table . For lower limb procedures, single-shot subarachnoid blocks are a frequent anaesthetic strategy. To offer postoperative pain relief and extend the duration while reducing the dose of local anaesthetic, intrathecal adjuvants are utilised with local anaesthetics. Bupivacaine when used alone for subarachnoid block, lasts for a short time and the duration of postoperative analgesia is also reduced. Opioids are frequently used in conjunction with local anaesthetics to increase hemodynamic stability while increasing the duration of motor and sensory block; 2.5 mg nalbuphine is equipotent to fentanyl 25 μg . After aNalbuphine when used as an intrathecal adjuvant, significantly delayed the onset of sensory block compared to patients receiving intrathecal fentanyl in our study. However, Shakooh et al. and Ahluwalia et al. reported earlier onset in patients getting nalbuphine intrathecally as compared to the control group ,11. ThotIn the current study, patients receiving intrathecal fentanyl experienced faster onset of motor block than patients receiving intrathecal nalbuphine. According to Sharma et al., patients receiving intrathecal fentanyl experienced complete motor block substantially sooner than patients receiving intrathecal nalbuphine, despite both being equivalent to control . The comOur results showed similar findings to that of Mukherjee et al, who observed longer sensory block in all the groups receiving nalbuphine, as compared to the control . In the Patients who got fentanyl had significantly higher VAS scores than those who received nalbuphine at all time intervals from 60 to 720 minutes. Duration of effective analgesia was determined from the point of subarachnoid block to the administration of the first rescue analgesic dose at VAS score > 4. When compared, the effective analgesia was significantly longer in patients receiving intrathecal nalbuphine (323.18±57.39 minutes) than in intrathecal fentanyl (287.05±78.87 minutes). Our study findings are consistent with those of other studies, which reported a considerable lengthening of the duration of spinal analgesia with nalbuphine -15.The hemodynamics in the current investigation was discovered to be comparable across the two groups, which was alike to the findings of Sharma et al. . In a stFortunately, neither group of patients in this trial experienced any significant negative outcomes. However, the incidence of headache, nausea, and vomiting in all the groups was comparable to the study by Sharma et al. . Gomaa eThe limited sample size would be the study's main drawback. Additional research must be done on a wider population of patients as well as those undergoing different surgical procedures. Opioids as adjuvants to intrathecal bupivacaine is a commonly used intervention to achieve good postoperative outcomes. We conclude that both fentanyl and nalbuphine were equally efficacious in providing excellent intraoperative surgical anaesthesia and postoperative analgesia with good hemodynamic stability. The fentanyl group had a faster onset of both sensory and motor blockade as compared to the nalbuphine group, though it was not statistically significant. The duration of effective analgesia was, however, significantly more in the nalbuphine group.


We enrolled older patients having elective joint replacement (N = 19) or spine (N = 16) surgery and investigated pre- to postoperative expression changes in 784 immune-related genes in monocytes. Joint replacement altered the expression of 489 genes (adjusted p < 0.05), of which 38 had a |logFC| > 1. Spine surgery changed the expression of 209 genes (adjusted p < 0.05), of which 27 had a |logFC| > 1. In both, the majority of genes with a |logFC| > 1 change were downregulated. In the combined group (N = 35), 471 transcripts were differentially expressed (adjusted p < 0.05) after surgery; 29 had a |logFC| > 1 and 72% of these were downregulated. Notably, 21 transcripts were common across procedures. Thus, elective surgery in older patients produces myriad changes in the immune gene transcriptome of monocytes, with many suggesting development of an immunocompromised/hypoactive phenotype. Because monocytes are strongly implicated in the quality of surgical recovery, this signature provides insight into the cellular and molecular mechanisms of the immune response to surgery and warrants further study as a potential biomarker for predicting poor outcomes in older surgical patients.Surgery is a major challenge for the immune system, but little is known about the immune response of geriatric patients to surgery. We therefore investigated the impact of surgery on the molecular signature of circulating CD14 Surgical trauma produces a profound peripheral immune response that is essential for recovery but is also implicated in the development of complications and suboptimal outcomes. This intricate programmed response is activated within hours of tissue injury and engages multiple types of immune cells, which are recruited to the site by damage-response antigens, alarmins, and increased levels of pro-inflammatory cytokines ,3,4,5,6.Nowhere is this issue more relevant than in geriatric surgery. Older patients are a demographic that is under-represented in studies of trauma or surgery, including those examining the immune response. Despite representing just 15% of the population, older adults constitute over 50% of all surgical admissions and, on a per capita basis, are nearly three times more likely to have surgery than a middle-aged individual . Likewis+ monocytes. We hypothesized that surgery induces numerous changes in the immune gene transcriptome of these cells, with the profile having features of both immune activation and suppression, and that some aspects of the signal are conserved across different surgical procedures. To test these possibilities, we examined the expression of 784 inflammation-related genes in the circulating monocytes of older patients before and after elective spinal or total hip or knee replacement surgery, procedures that are among the most common in this age group. Our results reveal a replicable effect of elective geriatric surgery on expression of immune-related genes in monocytes, with many changes consistent with development of a hypoactive/immunocompromised phenotype postoperatively.Cellular immunity is a critical component of the response to injury. There are significant changes in circulating leukocyte populations within hours of a surgical incision, and the changes last for at least a day . Monocyt+ cells.The Partners Institutional Review Board (IRB) approved two prospective observational studies (2016P000012 and 2014P002400) from which these data were obtained. Study participants were aged 65 years and older and scheduled for elective surgery at Brigham and Women’s Hospital  with planned hospital admission of at least one night. One group consisted of patients scheduled for lower extremity total joint replacement surgery (hip or knee) and were recruited between 1 February 2016 and 30 March 2017. Another group included patients scheduled for elective spinal surgery , and were recruited between 22 February 2016 and 9 October 2018. Details have been reported previously . For botPreoperative blood samples were collected along with routine laboratory studies drawn during the patients’ preoperative appointment (preop). If routine laboratory studies were not collected during the preoperative appointment, a preoperative sample was collected prior to entry into the operating room on the day of surgery. The postoperative blood sample was collected by study staff on postoperative day 1 (postop). Postoperative day 1 was chosen as the postoperative time point because several other studies have found the greatest appreciable differences in inflammatory markers at this time ,19,20. S+ monocytes were isolated using the positive immunomagnetic selection kit from Miltenyi Biotec according to the manufacturer’s instructions. A total of 2 mL of whole blood and 100 µL of StraightFrom Whole Blood CD14+ MicroBeads  were incubated at 4 °C for 15 min. Then 3 mL of phosphate-buffered saline (PBS) containing 0.5% bovine serum albumin (BSA), and 0.4% EDTA was added and the mixture was spun at 450 g for 10 min. Plasma was aspirated, and another 1 mL of buffer was added. The cell suspension was loaded onto an LS magnetic column  placed in the magnetic field of a MACS Separator (MIDIMACS) and rinsed three times with buffer. The column was then removed from the magnetic field, and the CD14+ fraction was eluted in a total volume of 5 mL. Cell concentrations were taken to ensure accurate and sufficient cell count using a Countess II FL Automated Cell Counter . Cell counts in the range of 1.0 × 105 were considered accurate and acceptable. The fraction was then centrifuged at 450× g for 10 min, elution buffer was aspirated, and the cells were lysed with 600 µL of Buffer RLT . Lysate was then frozen at −80 °C until RNA was isolated.CD14+ cells was isolated and purified using the Qiagen RNeasy mini kit  according to the manufacturer’s instructions. RNA was isolated form all samples for each cohort at once to limit potential batch effects. Following RNA isolation, total RNA was quantified with an A260/A280 ratio via a Nanodrop ND-1000 spectrophotometer  for a few samples at random to confirm extraction efficacy and expected concentration. Isolated RNA samples were then sent for a more robust quality assessment with an Agilent 2100 Bioanalyzer  for determination of total eukaryotic RNA concentration and the RNA integrity number (RIN). All samples had a spectral 260/280 ratio of between 2.05 and 2.13 and an RIN of at least 8, with most samples above 9.5.Total RNA from CD14® platform at the Center for Advanced Molecular Diagnostics, a Brigham and Women’s Hospital Core Facility. The “PanCancer Immune Profiling Panel” panel of 770 genes was chosen, and 14 unique genes were added for a total microarray of 784 immune-related genes. Probe sets for each gene were designed and synthesized by NanoString nCounter®. Technical replicates of samples were used to ensure consistency within and between batches. There were no significant differences between or within batches.Samples were diluted to 20 ng/µL based on dilutions provided by the Bioanalyzer. Isolated RNA samples were sent to the NanoString nCountert-tests or Wilcoxon-tests for continuous variables where appropriate and Chi-square tests for categorical variables to examine demographic and clinical data. We utilized the Linear Models for Microarray Data “limma” R package to screen for pairwise comparisons of gene expression between preoperative and postoperative samples [p-values for false discovery rate (FDR) using Benjamini–Hochberg (BH) adjustment, with the cutoff set at 0.05. Genes that met the adjusted p-value cutoff were defined as differentially expressed genes (DEGs). We also applied an absolute log2 fold change (logFC) > 1 as an additional cut-off criterion of biological relevance. Visualizations were configured in “Gplots”, “EnhancedVolcano”, and/or “pheatmap” R language packages.All analyses were performed in RStudio (Version 1.2.1335 for MacOS) using the R programming language. We used  samples . The voo samples , and we p > 0.5), BMI, and education, and in clinical and outcome variables including estimated blood loss and length of stay (The joint replacement (N = 19) and spine surgery (N = 16) groups were comparable in age . Of these DEGs, 38 (7.8%) had a |logFC| > 1  in the postoperative period compared to their preoperative baseline expression, and 8 (1.6%) exhibited at least a 1.5 logFC . Of these DEGs, 27 (12.9%) had a |logFC| > 1 postoperatively compared to the preoperative baseline expression, and 4 had at least a 1.5 logFC  of the genes on the panel were differentially expressed after surgery (BH-corrected .5 logFC B. As in p < 0.05) as a result of elective surgery. Of these DEGs, 29 transcripts (6.2%) had a |logFC| > 1 change  were differentially expressed —a threshold compatible with biological relevance. Most strikingly, among the DEGs with at least a 1 logFC change, 21 were common to the joint replacement, spine, and combined groups. This commonality suggests these molecular events reflect general aspects of surgery, such as tissue injury and stress, more than the procedural specifics, though a larger data set is necessary to prove this assertion. The fact that the majority of the DEGs with at least a 1 logFC change were downregulated suggests that surgery triggers an imbalance in the immune homeostasis of these cells, likely shifting them toward a hypoactive phenotype. Further work is needed to establish such a functional correlate, but the data presented here support previous studies showing that monocyte dysfunction occurs postoperatively [This exploratory study demonstrates that surgery in the older patient produces widespread changes in the molecular signature of circulating CD14ratively ,45,46.Numerous investigations of the immune response to surgery or tissue injury reveal that blunt trauma or surgery induce a consistent and robust immune response. This is measurable in plasma and/or circulating immune cells and is both rapidly activated and persistent . However+ cells, but changes in other transcripts suggest anti-inflammatory pathways are also perturbed. IL1R2, which serves as a decoy receptor and molecular trap for the proinflammatory cytokine IL1, increases, as does IL-10, one of the most potent anti-inflammatory cytokines [Our analysis focused on transcripts that have a role in mediating and fine tuning the immune and inflammatory response, but their role in surgical recovery and morbidity is largely unexplored. Peroxisome proliferator-activated receptor gamma (PPARγ), the most robustly upregulated transcript, increases the capacity of macrophages to engulf apoptotic neutrophils  and is aytokines . In addiytokines , a proceytokines . Likewisytokines , is downytokines  and reduytokines . The cliytokines ,16 makesOur study has notable strengths, including analysis by within-subject change that offsets variation in baseline inflammatory status or genetic factors, use of a large but focused panel of genes, and the high prevalence and relative homogeneity of the surgical procedures within the joint replacement and spinal surgery groups. Nonetheless, it also has important limitations. First, the study is small, and we sampled at only one postoperative time point. This prevented an examination of associations between gene expression changes and surgical outcomes. It also means we cannot exclude the possibility that some biologically and clinically relevant changes in gene expression were missed or that they occurred later in the recovery process. Differences in the sex of the patients as well as the anesthetic agents used could also influence the outcomes, as both have an impact on the immune response. However, the fact that the molecular signature of monocytes was similar in the spine and joint replacement surgery patients, and that four of the 20 DEGs common to both were detected in a previous study of abdominal surgery, suggests the molecular signature we identified is partially conserved across sex, anesthetics, and procedures. Second, we focused on older patients and do not have a younger comparator group. Consequently, although older patients have considerably more postoperative morbidity than younger persons, and much of it is thought to be inflammation-related, we cannot say definitively that the changes are specific to older surgical patients or the specific morbidities of these procedures. However, at least in the case of postoperative delirium, which is one of the most common morbidities of geriatric surgery, the plasma proteomic signature is age-dependent . Third, In summary, in this exploratory study, we identified a broad effect of elective spine and joint replacement surgery on the inflammatory gene transcriptome of circulating monocytes in older patients. The fact that most of the affected genes were downregulated implies there is a period of immune hypoactivity or paralysis in such patients after surgery. A subset of 21 differentially expressed genes were common across procedures, highlighting these transcripts as a molecular signature of the immune response to surgery in this population and cell type. While a larger data set is required to establish an association of these cellular events with postoperative outcomes, the data identify molecular targets for development as potential risk biomarkers and/or immunotherapeutics to improve postoperative outcomes in this high-risk age group.