Interactions between immune cell types facilitate the evolution of immune traits.

An essential prerequisite for evolution by natural selection is variation among individuals in traits that affect fitness1. The ability of a system to produce selectable variation, known as evolvability2, thus greatly affects the rate of evolution. The immune system belongs to the fastest evolving components in mammals3, yet the sources of variation in immune traits remain largely unknown4,5. Here, we show that an important determinant of the immune system's evolvability is its organisation into interacting modules represented by different immune cell types. By profiling immune cell variation in bone marrow of 54 genetically diverse mouse strains from the Collaborative Cross6, we found that variation in immune cell frequencies is polygenic and that many associated genes are involved in homeostatic balance through cell-intrinsic functions of proliferation, migration and cell death. However, we also found genes associated with the frequency of a particular cell type, which are expressed in a different cell type, exerting their effect in what we term cyto-trans. Vertebrate evolutionary record shows that genes associated in cyto-trans have faced weaker negative selection, thus increasing the robustness and hence evolvability2,7,8 of the immune system. This phenomenon is similarly observable in human blood. Our findings suggest that interactions between different components of the immune system provide a phenotypic space where mutations can produce variation without much detriment, underscoring the role of modularity in the evolution of complex systems9.

Interferon-stimulated neutrophils as a predictor of immunotherapy response.

Despite the remarkable success of anti-cancer immunotherapy, its effectiveness remains confined to a subset of patients-emphasizing the importance of predictive biomarkers in clinical decision-making and further mechanistic understanding of treatment response. Current biomarkers, however, lack the power required to accurately stratify patients. Here, we identify interferon-stimulated, Ly6Ehi neutrophils as a blood-borne biomarker of anti-PD1 response in mice at baseline. Ly6Ehi neutrophils are induced by tumor-intrinsic activation of the STING (stimulator of interferon genes) signaling pathway and possess the ability to directly sensitize otherwise non-responsive tumors to anti-PD1 therapy, in part through IL12b-dependent activation of cytotoxic T cells. By translating our pre-clinical findings to a cohort of patients with non-small cell lung cancer and melanoma (n = 109), and to public data (n = 1440), we demonstrate the ability of Ly6Ehi neutrophils to predict immunotherapy response in humans with high accuracy (average AUC ≈ 0.9). Overall, our study identifies a functionally active biomarker for use in both mice and humans.

A personalized network framework reveals predictive axis of anti-TNF response across diseases.

Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we use a computational approach termed Disruption Networks to generate a data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. This data type extends beyond the "feature level space", to the "relations space", by quantifying individual-level breaking or rewiring of cross-feature relations. Applying Disruption Networks to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.

Reconstructing disease dynamics for mechanistic insights and clinical benefit.

Diseases change over time, both phenotypically and in their underlying molecular processes. Though understanding disease progression dynamics is critical for diagnostics and treatment, capturing these dynamics is difficult due to their complexity and the high heterogeneity in disease development between individuals. We present TimeAx, an algorithm which builds a comparative framework for capturing disease dynamics using high-dimensional, short time-series data. We demonstrate the utility of TimeAx by studying disease progression dynamics for multiple diseases and data types. Notably, for urothelial bladder cancer tumorigenesis, we identify a stromal pro-invasion point on the disease progression axis, characterized by massive immune cell infiltration to the tumor microenvironment and increased mortality. Moreover, the continuous TimeAx model differentiates between early and late tumors within the same tumor subtype, uncovering molecular transitions and potential targetable pathways. Overall, we present a powerful approach for studying disease progression dynamics-providing improved molecular interpretability and clinical benefits for patient stratification and outcome prediction.

Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work, we aimed to determine the relevance of changes in cell proportions in peripheral blood mononuclear cells (PBMCs) during the development of disease and following treatment. Samples from healthy blood donors, newly diagnosed RA patients, and established RA patients that had an inadequate response to MTX and were about to start tumor necrosis factor inhibitors (TNFi) treatment were collected before and after 3 months of treatment. We used in parallel a computational deconvolution approach based on RNA expression and flow cytometry to determine the relative cell-type frequencies. Cell-type frequencies from deconvolution of gene expression indicate that monocytes (both classical and non-classical) and CD4+ cells (Th1 and Th2) were increased in RA patients compared to controls, while NK cells and B cells (naïve and mature) were significantly decreased in RA patients. Treatment with MTX caused a decrease in B cells (memory and plasma cell), and a decrease in CD4 Th cells (Th1 and Th17), while treatment with TNFi resulted in a significant increase in the population of B cells. Characterization of the RNA expression patterns found that most of the differentially expressed genes in RA subjects after treatment can be explained by changes in cell frequencies (98% and 74% respectively for MTX and TNFi).

Investigating the potential of a prematurely aged immune phenotype in severely injured patients as predictor of risk of sepsis.

BACKGROUND: Traumatic injury elicits a hyperinflammatory response and remodelling of the immune system leading to immuneparesis. This study aimed to evaluate whether traumatic injury results in a state of prematurely aged immune phenotype to relate this to clinical outcomes and a greater risk of developing additional morbidities post-injury. METHODS AND FINDINGS: Blood samples were collected from 57 critically injured patients with a mean Injury Severity Score (ISS) of 26 (range 15-75 years), mean age of 39.67 years (range 20-84 years), and 80.7% males, at days 3, 14, 28 and 60 post-hospital admission. 55 healthy controls (HC), mean age 40.57 years (range 20-85 years), 89.7% males were also recruited. The phenotype and frequency of adaptive immune cells were used to calculate the IMM-AGE score, an indicator of the degree of phenotypic ageing of the immune system. IMM-AGE was elevated in trauma patients at an early timepoint (day 3) in comparison with healthy controls (p < 0.001), driven by an increase in senescent CD8 T cells (p < 0.0001), memory CD8 T cells (p < 0.0001) and regulatory T cells (p < 0.0001) and a reduction in naïve CD8 T cells (p < 0.001) and overall T cell lymphopenia (p < 0 .0001). These changes persisted to day 60. Furthermore, the IMM-AGE scores were significantly higher in trauma patients (mean score 0.72) that developed sepsis (p = 0.05) in comparison with those (mean score 0.61) that did not. CONCLUSIONS: The profoundly altered peripheral adaptive immune compartment after critical injury can be used as a potential biomarker to identify individuals at a high risk of developing sepsis and this state of prematurely aged immune phenotype in biologically young individuals persists for up to two months post-hospitalisation, compromising the host immune response to infections. Reversing this aged immune system is likely to have a beneficial impact on short- and longer-term outcomes of trauma survivors.

Mature neutrophils and a NF-κB-to-IFN transition determine the unifying disease recovery dynamics in COVID-19.

Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome. Furthermore, we present strong indications for global regulatory changes in gene programs, decoupled from cell compositional changes, including an early rise in T cell activation and differentiation, resulting in immune rebalancing between interferon and NF-κB activity and restoration of cell homeostasis. Overall, we present a clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

B cell-derived cfDNA after primary BNT162b2 mRNA vaccination anticipates memory B cells and SARS-CoV-2 neutralizing antibodies.

BACKGROUND: Much remains unknown regarding the response of the immune system to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccination. METHODS: We employed circulating cell-free DNA (cfDNA) to assess the turnover of specific immune cell types following administration of the Pfizer/BioNTech vaccine. FINDINGS: The levels of B cell cfDNA after the primary dose correlated with development of neutralizing antibodies and memory B cells after the booster, revealing a link between early B cell turnover-potentially reflecting affinity maturation-and later development of effective humoral response. We also observed co-elevation of B cell, T cell, and monocyte cfDNA after the booster, underscoring the involvement of innate immune cell turnover in the development of humoral and cellular adaptive immunity. Actual cell counts remained largely stable following vaccination, other than a previously demonstrated temporary reduction in neutrophil and lymphocyte counts. CONCLUSIONS: Immune cfDNA dynamics reveal the crucial role of the primary SARS-CoV-2 vaccine in shaping responses of the immune system following the booster vaccine. FUNDING: This work was supported by a generous gift from Shlomo Kramer. Supported by grants from Human Islet Research Network (HIRN UC4DK116274 and UC4DK104216 to R.S. and Y.D.), Ernest and Bonnie Beutler Research Program of Excellence in Genomic Medicine, The Alex U Soyka Pancreatic Cancer Fund, The Israel Science Foundation, the Waldholtz/Pakula family, the Robert M. and Marilyn Sternberg Family Charitable Foundation, the Helmsley Charitable Trust, Grail, and the DON Foundation (to Y.D.). Y.D. holds the Walter and Greta Stiel Chair and Research Grant in Heart Studies. I.F.-F. received a fellowship from the Glassman Hebrew University Diabetes Center.

Identification of Gene Expression Profiles Associated with an Increased Risk of Post-Operative Recurrence in Crohn's Disease.

BACKGROUND AND AIMS: Ileocolonic resection is frequently needed in the course of Crohn's disease [CD] treatment and post-operative recurrence is extremely common. Our main objective was to analyse gene expression in the mucosa of CD patients at the time of surgery and at post-operative endoscopy, in order to identify predictors and mechanisms of early endoscopic recurrence. METHODS: We conducted transcriptome analyses on ileal mucosa samples collected from inflamed sections of the surgical specimens [n = 200], from ileal resection margins [n = 149] and in the neo-terminal ileum 6 months after surgery [n = 122]; these were compared with non-inflammatory bowel disease controls [n = 25]. The primary endpoint was post-operative endoscopic recurrence at 6 months. We applied regression models to identify gene signatures predicting endoscopic recurrence. RESULTS: Chronic inflammation was associated with strong expression of inflammatory genes [IL-6, IL-8, IL-1B] and decreased expression of genes involved in metabolic processes, but with a high inter-individual heterogeneity. Gene signatures associated with early endoscopic recurrence were mainly characterized by upregulation of TNFα, IFNγ, IL23A and IL17A. Pathway analyses showed that upregulation of mitochondrial dysfunction within the inflamed sections and JAK/STAT at the ileal margin were predictive of post-operative recurrence. A combined model integrating these top pathway signatures improved the prediction of endoscopic recurrence [area under the curve of 0.79]. STAT3 phosphorylation at the surgical ileal margin was associated with severe recurrence at 6 months. CONCLUSION: We identified several biological pathways in surgical ileal mucosa specimens associated with an increased risk of disease recurrence. Integration of the JAK/STAT and mitochondrial dysfunction pathways in the clinical model improved the prediction of post-operative recurrence.

Alignment of single-cell trajectories by tuMap enables high-resolution quantitative comparison of cancer samples.

Single-cell technologies allow characterization of cancer samples as continuous developmental trajectories. Yet, the obtained temporal resolution cannot be leveraged for a comparative analysis due to the large phenotypic heterogeneity existing between patients. Here, we present the tuMap algorithm that exploits high-dimensional single-cell data of cancer samples exhibiting an underlying developmental structure to align them with the healthy development, yielding the tuMap pseudotime axis that allows their systematic, meaningful comparison. We applied tuMap on single-cell mass cytometry data of acute lymphoblastic and myeloid leukemia to reveal associations between the tuMap pseudotime axis and clinics that outperform cellular assignment into developmental populations. Application of the tuMap algorithm on single-cell RNA sequencing data further identified gene signatures of stem cells residing at the very-early parts of the cancer trajectories. The quantitative framework provided by tuMap allows generation of metrics for cancer patients evaluation.

An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging.

While many diseases of aging have been linked to the immunological system, immune metrics capable of identifying the most at-risk individuals are lacking. From the blood immunome of 1,001 individuals aged 8-96 years, we developed a deep-learning method based on patterns of systemic age-related inflammation. The resulting inflammatory clock of aging (iAge) tracked with multimorbidity, immunosenescence, frailty and cardiovascular aging, and is also associated with exceptional longevity in centenarians. The strongest contributor to iAge was the chemokine CXCL9, which was involved in cardiac aging, adverse cardiac remodeling and poor vascular function. Furthermore, aging endothelial cells in human and mice show loss of function, cellular senescence and hallmark phenotypes of arterial stiffness, all of which are reversed by silencing CXCL9. In conclusion, we identify a key role of CXCL9 in age-related chronic inflammation and derive a metric for multimorbidity that can be utilized for the early detection of age-related clinical phenotypes.

Autologous Hematological Stem Cell Transplantation for Systemic Sclerosis in Israel.

BACKGROUND: Autologous hematological stem cell transplantation (HSCT) is a novel therapy for systemic sclerosis (SSc) that has been validated in three randomized controlled trials. OBJECTIVES: To report the first Israeli experience with HSCT for progressive SSc and review the current literature. METHODS: Five SSc patients who were evaluated in our department and were treated by HSCT were included. Medical records were evaluated retrospectively. Demographic, clinical, and laboratory data were recorded. Continuous data are presented as the mean ± standard deviation. Categorical variables are presented as frequencies and percentages. RESULTS: Five SSc patients were treated with HSCT. Four patients were adults (mean age 53 ± 12 years) and one was a 12-year-old pediatric patient. All patients were female. HSCT was initiated 1.4 ± 0.8 years after diagnosis. Two patients were RNA POLIII positive, two were anti-topoisomerase 1 positive, and one only antinuclear antibodies positive. All patients had skin and lung involvement. The mean modified Rodnan Skin Score was 29 ± 4.7 before HSCT, which improved to 10.4 ± 9.6 after HSCT. The forced vital capacity improved from 68 ± 13% to 90 ± 28%. Diffusing capacity of the lungs for carbon monoxide increased by 6%. Among severe adverse events were cyclophosphamide-related congestive heart failure, antithymocyte globulin-related capillary leak syndrome, and scleroderma renal crisis. All symptoms completely resolved with treatment without sequela. No treatment related mortality was recorded. CONCLUSIONS: HSCT is an important step in the treatment of progressive SSc in Israel. Careful patient selection reduces treatment related morbidity and mortality.

Pregnancy-Induced Alterations in NK Cell Phenotype and Function.

Pregnant women are particularly susceptible to complications of influenza A virus infection, which may result from pregnancy-induced changes in the function of immune cells, including natural killer (NK) cells. To better understand NK cell function during pregnancy, we assessed the ability of the two main subsets of NK cells, CD56dim, and CD56bright NK cells, to respond to influenza-virus infected cells and tumor cells. During pregnancy, CD56dim and CD56bright NK cells displayed enhanced functional responses to both infected and tumor cells, with increased expression of degranulation markers and elevated frequency of NK cells producing IFN-γ. To better understand the mechanisms driving this enhanced function, we profiled CD56dim and CD56bright NK cells from pregnant and non-pregnant women using mass cytometry. NK cells from pregnant women displayed significantly increased expression of several functional and activation markers such as CD38 on both subsets and NKp46 on CD56dim NK cells. NK cells also displayed diminished expression of the chemokine receptor CXCR3 during pregnancy. Overall, these data demonstrate that functional and phenotypic shifts occur in NK cells during pregnancy that can influence the magnitude of the immune response to both infections and tumors.

UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma.

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

Infliximab-Tumor Necrosis Factor Complexes Elicit Formation of Anti-Drug Antibodies.

BACKGROUND & AIMS: Some patients develop anti-drug antibodies (ADAs), which reduce the efficacy of infliximab, a monoclonal antibody against tumor necrosis factor (TNF), in the treatment of immune-mediated diseases, including inflammatory bowel diseases. ADAs arise inconsistently, and it is not clear what factors determine their formation. We investigated features of the immune system, the infliximab antibody, and its complex with TNF that might contribute to ADA generation. METHODS: C57BL/6 mice were given injections of infliximab and recombinant human TNF or infliximab F(ab')2 fragments. Blood samples were collected every 2-3 days for 2 weeks and weekly thereafter for up to 6 weeks; infliximab-TNF complexes and ADAs were measured by enzyme-linked immunosorbent assay (ELISA). Intestinal biopsy and blood samples were obtained from patients having endoscopy who had received infliximab therapy for inflammatory bowel diseases; infliximab-TNF complexes were measured with ELISA. Infliximab-specific plasma cells were detected in patient tissue samples by using mass cytometry. We studied activation of innate immune cells in peripheral blood mononuclear cells (PBMCs) from healthy donors incubated with infliximab or infliximab-TNF complexes; toll-like receptors (TLRs) were blocked with antibodies, endocytosis was blocked with the inhibitor PitStop2, and cytokine expression was measured by real-time polymerase chain reaction and ELISAs. Uptake of infliximab and infliximab-TNF complexes by THP-1 cells was measured with confocal microscopy. RESULTS: Mice given increasing doses of infliximab produced increasing levels of ADAs. Blood samples from mice given injections of human TNF and infliximab contained infliximab-TNF complexes; complex formation was associated with ADA formation with an area under the curve of 0.944 (95% confidence interval, 0.851-1.000; P = .003). Intestinal tissues from patients, but not blood samples, contained infliximab-TNF complexes and infliximab-specific plasma cells. Incubation of PBMCs with infliximab-TNF complexes resulted in a 4.74-fold increase in level of interleukin (IL) 1ß (IL1B) messenger RNA (P for comparison = .005), increased IL1B protein secretion, and a 2.69-fold increase in the expression of TNF messenger RNA (P for comparison = 0.013) compared with control PBMCs. Infliximab reduced only IL1B and TNF expression. Antibodies against TLR2 or TLR4 did not block the increases in IL1B or TNF expression, but endocytosis was required. THP-1 cells endocytosed higher levels of infliximab-TNF complexes than infliximab alone. CONCLUSIONS: In mice, we found ADA formation to increase with dose of infliximab given and concentration of infliximab-TNF complexes detected in blood. Based on studies of human intestinal tissues and blood samples, we propose that infliximab-TNF complexes formed in the intestine are endocytosed by and activate innate immune cells, which increase expression of IL1B and TNF and production of antibodies against the drug complex. It is therefore important to optimize the infliximab dose to a level that is effective but does not activate an innate immune response against the drug-TNF complex.

Batch correction evaluation framework using a-priori gene-gene associations: applied to the GTEx dataset.

BACKGROUND: Correcting a heterogeneous dataset that presents artefacts from several confounders is often an essential bioinformatics task. Attempting to remove these batch effects will result in some biologically meaningful signals being lost. Thus, a central challenge is assessing if the removal of unwanted technical variation harms the biological signal that is of interest to the researcher. RESULTS: We describe a novel framework, B-CeF, to evaluate the effectiveness of batch correction methods and their tendency toward over or under correction. The approach is based on comparing co-expression of adjusted gene-gene pairs to a-priori knowledge of highly confident gene-gene associations based on thousands of unrelated experiments derived from an external reference. Our framework includes three steps: (1) data adjustment with the desired methods (2) calculating gene-gene co-expression measurements for adjusted datasets (3) evaluating the performance of the co-expression measurements against a gold standard. Using the framework, we evaluated five batch correction methods applied to RNA-seq data of six representative tissue datasets derived from the GTEx project. CONCLUSIONS: Our framework enables the evaluation of batch correction methods to better preserve the original biological signal. We show that using a multiple linear regression model to correct for known confounders outperforms factor analysis-based methods that estimate hidden confounders. The code is publicly available as an R package.

A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring.

Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual's immune age. Here, we use multiple 'omics' technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a high-dimensional trajectory of immune aging (IMM-AGE) that describes a person's immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk.

Cell-centred meta-analysis reveals baseline predictors of anti-TNFα non-response in biopsy and blood of patients with IBD.

OBJECTIVE: Although anti-tumour necrosis factor alpha (anti-TNFα) therapies represent a major breakthrough in IBD therapy, their cost-benefit ratio is hampered by an overall 30% non-response rate, adverse side effects and high costs. Thus, finding predictive biomarkers of non-response prior to commencing anti-TNFα therapy is of high value. DESIGN: We analysed publicly available whole-genome expression profiles of colon biopsies obtained from multiple cohorts of patients with IBD using a combined computational deconvolution-meta-analysis paradigm which allows to estimate immune cell contribution to the measured expression and capture differential regulatory programmes otherwise masked due to variation in cellular composition. Insights from this in silico approach were experimentally validated in biopsies and blood samples of three independent test cohorts. RESULTS: We found the proportion of plasma cells as a robust pretreatment biomarker of non-response to therapy, which we validated in two independent cohorts of immune-stained colon biopsies, where a plasma cellular score from inflamed biopsies was predictive of non-response with an area under the curve (AUC) of 82%. Meta-analysis of the cell proportion-adjusted gene expression data suggested that an increase in inflammatory macrophages in anti-TNFα non-responding individuals is associated with the upregulation of the triggering receptor expressed on myeloid cells 1 (TREM-1) and chemokine receptor type 2 (CCR2)-chemokine ligand 7 (CCL7) -axes. Blood gene expression analysis of an independent cohort, identified TREM-1 downregulation in non-responders at baseline, which was predictive of response with an AUC of 94%. CONCLUSIONS: Our study proposes two clinically feasible assays, one in biopsy and one in blood, for predicting non-response to anti-TNFα therapy prior to initiation of treatment. Moreover, it suggests that mechanism-driven novel drugs for non-responders should be developed.

UV-Protection Timer Controls Linkage between Stress and Pigmentation Skin Protection Systems.

Skin sun exposure induces two protection programs: stress responses and pigmentation, the former within minutes and the latter only hours afterward. Although serving the same physiological purpose, it is not known whether and how these programs are coordinated. Here, we report that UVB exposure every other day induces significantly more skin pigmentation than the higher frequency of daily exposure, without an associated increase in stress responses. Using mathematical modeling and empirical studies, we show that the melanocyte master regulator, MITF, serves to synchronize stress responses and pigmentation and, furthermore, functions as a UV-protection timer via damped oscillatory dynamics, thereby conferring a trade-off between the two programs. MITF oscillations are controlled by multiple negative regulatory loops, one at the transcriptional level involving HIF1α and another post-transcriptional loop involving microRNA-148a. These findings support trait linkage between the two skin protection programs, which, we speculate, arose during furless skin evolution to minimize skin damage.