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a non-IHG-I grade was greater in females compared with males Fig. The odds of having IHG-II vs. IHG-I, or IHG-III or IHG-IV vs. IHG-I, increased with age; however, these odds were greater in males than females Fig. IHG-III or IHG-IV did not change significantly with age; however, females compared with males were more likely to have IHG-II than IHG-III or IHG-IV Fig.

The IHG distributions during aging Fig. First, across lifespan, there is a strong preference to preserve grades tracking CD8-CD4 equilibrium IHG-I or IHG-II than disequilibrium IHG-III or IHG-IV states.

Second, females compared with males are more likely to preserve CD8-CD4 equilibrium grades IHG-I or IHG-II, including post-menopause. Third, IHG-I is the primordial IHG from which the other IHGs emerge during aging. For this reason, preservation of IHG-I at any age was assigned as an indicator of the IR erosion-resistant phenotype and optimal IR Fig.

Conversely, having a non-IHG-I grade was assigned as an indicator of the IR erosion-susceptible phenotype and suboptimal or nonoptimal IR Fig. Fourth, older and younger persons with the same IHG may share similar immunologic attributes IR-associated traits after controlling for age ; in contrast, a separate set of immunologic traits may track older vs.

younger persons preserving IHG-I or IHG-II, the two most-common grades across age age-associated traits. The validity of these inferences and IHG assignments were tested as described below.

In the context of acute antigenic stimulation, the IR erosion phenotypes as gauged by the IHG metric were evaluated in two infection models: schistosomiasis and SARS-CoV-2 infection. In Kenyan children with schistosomiasis, the level of antigenic stimulation was proxied by urinary egg counts Fig.

Akin to younger SardiNIA participants Fig. the zero-egg count stratum had IHG-IV. b — f Acute COVID cohort. convalescence paired : overall, by age and cytomegalovirus CMV serostatus.

c IHG degradation and reconstitution during COVID by CMV serostatus. rates, and CMV seropositivity rates by age strata. F female, M male. Disease severity status defined by World Health Organization WHO ordinal scale: [mild]; 5 [moderate]; 6—8 [severe].

h Primary HIV infection cohort PIC. Behavioral acitivty score BAS is the sum of scores of these risk factors. STI scores were derived based on direct and indirect indicators of STI.

By comparing IHG distribution patterns at presentation in HIV-seronegative patients with COVID baseline vs. convalescence, with preferential emergence of IHG-II and less so of IHG-IV Fig.

CMV serostatus influenced the nature of the IHGs that emerged during COVID Fig. Since CMV seropositivity rates increase with age Fig. The association between CD8-CD4 disequilibrium grades IHG-III or IHG-IV and high rates of CMV seropositivity was confirmed in persons without COVID Supplementary Note 3.

baseline Fig. The IHG distribution patterns in cohorts of persons without SardiNIA or with acute COVID showed three similarities. Second, within each age stratum of both cohorts, some persons resisted erosion of IHG-I Figs.

hospitalized patients, those with mild disease severity status indexed by WHO ordinal scale 28 of 1—4 , and survivors Fig. Third, females preserved IHG-I to a greater extent than males Figs.

Taken together, these findings convey two key inferences. First, the IHG at presentation with acute COVID is dependent on five factors: age, sex, CMV serostatus, the IR erosion phenotype, and the IHG present before COVID, as IHG-I during acute COVID is mostly possible in persons who had the same grade before SARS-CoV-2 infection.

Thus, persons preserving IHG-I before and at presentation with acute COVID have the IR erosion-resistant phenotype. Second, erosion of IHG-I can be temporary, and even older persons can retain the capacity to reconstitute IHG-I during convalescence. Compared with age-matched SardiNIA participants Fig.

Level of HIV-associated antigenic stimulation was proxied by HIV viral load HIV-VL. However, within each HIV-VL stratum, a small subset preserved IHG-I IR erosion-resistant phenotype.

The interval between the estimated date of infection and starting ART was 3. We focused on the elite subset 5. During five years of the therapy-naïve disease course, the capacity to preserve IHG-I decreased, resulting in the emergence of the other grades Fig. IR erosion phenotypes in the context of repetitive, moderate-grade antigenic stimulation was examined in FSWs Supplementary Fig.

The extent of moderate-grade antigenic stimulation was proxied by behavioral frequency of unprotected sex and biological [sexually transmitted infection STI ] risk factors for HIV acquisition.

Behavioral risk factors and baseline IHG status were available for FSWs Supplementary Fig. To mitigate confounding attributable to a false-negative HIV seronegative test, the association between baseline IHG and subsequent incident HIV seroconversion was restricted to FSWs with at least 2 HIV seronegative tests performed at least 3 months apart Supplementary Fig.

Of these, 53 women subsequently seroconverted Supplementary Fig. The median interval between baseline and HIV seroconversion was 4. Prevalence of IHGs was similar regardless of the duration of sex work Fig.

Among those without IHG-III or IHG-IV at baseline, a higher baseline BAS was associated with an increased hazard of subsequently developing these grades Supplementary Fig.

Hence, higher BAS and STI scores were risk factors for having or developing IHG-III or IHG-IV. After baseline measurements, FSWs were provided education and interventions e. Right, behavioral activity score BAS. g Groups based on IHG at baseline and predicted IHG before COVID top.

Model 1, by baseline IHG; and model 2, by CMV serostatus. h Time to second occurrence of cutaneous squamous cell carcinoma CSCC by IHG at time of first occurrence of CSCC in renal transplant recipients.

P, for differences in HIV-VL vs. IHG-I is shown. j HIV-VL by entry IHG in the primary HIV infection cohort PIC. k HIV-VL at entry and subsequent 5 years of therapy-naïve follow-up in EIC participants.

Differences in HIV-VL are between participants with IHG-I vs. rest i. For box plots: center line, median; box, interquartile range IQR ; whiskers, rest of the data distribution and outliers greater than ±1. Pre- and post-HIV seroconversion IHG data were available on 43 FSWs.

Akin to the elite group of individuals accrued during early HIV infection who preserved IHG-I at presentation Fig. Sooty mangabeys without and with natural simian immunodeficiency virus SIV infection allowed for evaluation of the additive impact of a single non-SIV source vs.

two non-SIV and SIV 18 sources of antigenic stimulation on erosion of IHG-I. Akin to humans Fig. Evolutionary parallels were also observed in the Collaborative Cross-RIX mice Groups of mice strains categorized into those who manifested relative resistance vs.

susceptibility to lethal Ebola virus infection Thus, resistance vs. susceptibility to lethal Ebola in mice may partly relate to a genetically associated capacity to preserve IHG-I or develop IHG-IV, respectively, before infection. Consistent with our model Fig. The juxtaposition of findings in human vs.

nonhuman primate cohorts suggest three evolutionary parallels. First, in both species, IHG-I is the primordial grade from which non-IHG-I grades emerge with increased antigenic stimulation.

Third, akin to FSWs who acquired HIV, sooty mangabeys categorized into those preserving IHG-I after SIV infection group 1 Fig. Thus, a key evolutionary difference was that IHG-III and IHG-IV were much less frequent in otherwise healthy humans Fig.

The higher prevalence of IHG-III and IHG-IV in nonhuman primates vs. humans may be attributable to differences in types and levels of antigenic exposures between species and suggests a potential survival benefit for humans to preserve CD8-CD4 equilibrium grades IHG-I or IHG-II vs.

disequilibrium grades IHG-III or IHG-IV. First, at any age, increased antigenic stimulation induces a shift from IHG-I to non-IHG-I grades.

Second, the extent of the deviation or shift from IHG-I is proportionate to the level of antigenic stimulation. These similarities across human cohorts have clinical relevance, as they suggest that i cohorts with varying host characteristics may comprise individuals with similar levels of immunosuppression linked to a non-IHG-I grade, ii immunosuppression may antedate HIV seroconversion, and iii development of a non-IHG-I grade may explain why some younger patients with HIV or SLE prematurely manifest immune and clinical features of age-associated diseases 31 , Third, reconstitution of IHG-I is possible.

For example, in three different contexts [COVID Fig. Fourth, individuals may have multiple concurrent sources of increased antigenic stimulation; hence, reconstitution of IHG-I may be impaired without mitigation of all sources. Thus, the age-associated erosion of IHG-I to a non-IHG-I grade may be partly attributable to accumulated antigenic experience.

Fifth, consistent with our model Fig. In study phase 2 below , we examined whether preservation of IHG-I was associated with superior immunity-dependent health outcomes. Juxtaposition of the IHG distribution patterns across age in persons without Fig.

with Fig. Group A comprises patients presenting with IHG-I; based on the above-noted results Fig. Group B is a conflated group of individuals presenting with IHG-II or IHG-IV; these grades before COVID could have been IHG-I or IHG-II.

Group C was envisaged based on having IHG-IV at presentation and before COVID While age was associated with a stepwise increase in the likelihood of hospitalization and death Supplementary Fig.

IHG-I group A was associated with a significantly higher odds ratio of hospitalization Fig. CMV serostatus was not associated with hospitalization or death Fig.

These findings suggest that i the capacity to preserve IHG-I both before and during early SARS-CoV-2 infection was associated with less-severe COVID nonhospitalization, survival , and ii while CMV serostatus may influence the nature of the IHG that emerges during COVID Fig.

RTRs are at a heightened up to fold risk of developing recurrent cutaneous squamous cell carcinoma CSCC We examined the risk of a second episode of CSCC according to the IHG at the time of initial diagnosis of CSCC baseline. In a prospective RTR cohort Supplementary Data 5 15 , the hazard of a second episode of CSCC was lowest, intermediate, and highest in individuals who, at the time of the first episode of CSCC, had IHG-I, IHG-II, and IHG-III or IHG-IV, respectively Fig.

In persons with recurrent CSCC, duration of immunosuppression or age did not differ substantially by baseline IHG Supplementary Data 5. Thus, In participants of the early HIV infection cohort, the rates of progression to AIDS were slowest, intermediate, and fastest in patients who at presentation had IHG-I, IHG-II or IHG-III, and IHG-IV, respectively Fig.

HIV-VL in participants from the early Fig. those who developed IHG-II, IHG-III, or IHG-IV Fig. Thus, the elite capacity to preserve IHG-I during HIV infection was associated with greater immunocompetence as proxied by lower AIDS risk and restriction of HIV viral replication.

In FSWs, higher baseline BAS and total STI scores were associated with two outcomes: higher rates Fig. However, baseline IHG-III or IHG-IV vs. IHG-I was also associated with an increased likelihood of HIV seroconversion Fig.

In multivariate analysis Supplementary Data 8a , IHG-IV independently associated with a nearly 3-fold increased risk of HIV seroconversion adjusted OR, 2. a Female sex workers FSWs stratified first by baseline behavioral activity score BAS and then by subsequent HIV seroconversion status.

Far right, OR for HIV seroconversion by baseline IHG. c Associations of CD8-CD4 disequilibrium grades IHG-III and IHG-IV with age and sex; inducers of these grades; and outcomes. Findings are from the literature survey also see Supplementary Table 2 for details and references and our primary datasets.

d — f Models depicting risk of indicated outcomes is lower in persons with the IR erosion-resistant phenotype IHG-I. d HIV-AIDS, e COVID, and f recurrent cutaneous squamous cell cancer CSCC in renal transplant recipients.

Pie charts depict relative proportions of the IHGs in the study group. Risk scaled from 1 to 3. Ag, antigenic; VL, viral load. These findings suggest that risk factor-associated antigenic stimulation increases the risk of developing IHG-III or IHG-IV, and IHG-III and especially IHG-IV prognosticate HIV seroconversion risk after controlling for BAS, a proxy for the level of HIV exposure.

This inference was supported by our literature survey Fig. This survey also affirmed that i prevalence of IHG-III or IHG-IV increases with age and is higher in males and ii CMV seropositivity rates in HIV— persons increase with age and IHG-III or IHG-IV associated with CMV seropositivity.

Furthermore, these findings suggest that IR status indexed by the IHGs may shape the continuity spectrum from disease susceptibility to outcomes in the context of HIV-AIDS Fig. Toward defining the precise level of IR eroded that prognosticates inferior immunity-dependent health outcomes, we characterized the full repertoire of IHGs that emerge in settings of antigenic stimulation.

a Schema for defining the full repertoire of IHGs. b Distribution of IHGs with subgrades in the SardiNIA cohort by age strata. Age, median age at IHG assessment, baseline or pre-ART are shown.

e Model depicting the enrichment of non-IHG-I grades during aging and at presentation with COVID or HIV infection.

IHG-I and IHG-IIa were the first and second-most prevalent grades during aging SardiNIA; Fig. In comparison with age-matched controls in the SardiNIA cohort Fig. Thus, the IHG repertoires provide a unifying framework of IR: a shared subset of detrimental non-IHG-I grades associated with worse health outcomes emerges in settings of lower e.

The subgrades may provide more precise risk prognostication attributable to where a person may reside along an IR continuum: i we previously found that presentation with subgrades b and c of IHG-II or IHG-IV predicted higher risk of COVIDassociated mortality 6 , after controlling for age; ii HIV acquisition occurred mainly in FSWs presenting with IHG-III and IHG-IVa Supplementary Fig.

Our findings suggest that the IHG repertoire defines three tiers of IR Fig. For these reasons, IHG-III was classified as a detrimental non-IHG-I grade in this study. Thus, the IHGs define a continuum: IHG-I, the most prevalent grade, signified optimal IR tier 1 ; IHG-IIa, the second-most prevalent grade, signified suboptimal IR tier 2 ; and the detrimental and less-frequent non-IHG-I grades signified nonoptimal IR tier 3 Fig.

a Schema for IR continuum. IR tiers and erosion phenotypes defined by the IR metrics IHGs, survival-associated signature SAS -1, and mortality-associated signature MAS Higher expression of SAS-1 and MAS-1 serve as transcriptomic proxies for immunocompetence IC and inflammation IF , respectively.

Groupings of SAS-1 and MAS-1 based on higher or lower levels of these signatures are depicted. with Alzheimer disease AD and other dementia disorders; e persons without control vs.

Asymp, asymptomatic. Cohort characteristics and sources of gene expression profile data are in Supplementary Data 13a. Our hypothesis Figs. To test this proposition, we examined whether the transcriptomic gene expression metrics of IR, namely, survival- vs. To corroborate that SAS-1 high was a transcriptomic proxy for IC high and not IF low , we focused on the findings of Alpert et al.

Higher levels of IMM-AGE based on gene expression associated with lower levels of an immune-aging metric based on immune senescence-associated T-cell subset frequencies 11 as well as survival in the FHS cohort Fig.

We found that, akin to higher SAS-1 expression, higher expression of IMM-AGE was also associated with lower mortality hazards in the COVID cohort Fig. Congruently, expression of SAS-1 and IMM-AGE was positively correlated; conversely, SAS-1 and IMM-AGE expression was negatively correlated with MAS-1 expression Supplementary Fig.

First, the correlation between expression of these gene signatures and age, while statistically significant, was low Supplementary Fig. Second, while expression levels of SAS-1 and IMM-AGE declined and those of MAS-1 increased with age Supplementary Fig.

Thus, the age-associated changes in SAS-1 and MAS-1 levels appeared to be more closely related to accumulated antigenic experience than the direct effects of age per se.

Together, these findings and the gene composition of the signatures Fig. SAS-1 high -MAS-1 low , SAS-1 high -MAS-1 high , SAS-1 low -MAS-1 low , and SAS-1 low -MAS-1 high profiles are considered as representative of IC high -IF low , IC high -IF high , IC low -IF low , and IC low -IF high states, respectively Fig.

First, akin to the age-associated shift from IHG-I to non-IHG-I grades Fig. Second, akin to the overrepresentation of IHG-I in females across age strata Fig. SAS-1 low -MAS-1 high profiles were more prevalent in females than males Fig.

These findings were consistent with our observation that, across all ages in the FHS, females compared with males preserved higher levels of SAS-1 and lower levels of MAS-1 Supplementary Fig.

Conversely, representation of SAS-1 low -MAS-1 high was progressively greater with the a, b, and c subgrades of IHG-II and IHG-IV Fig. IHG-III lacked representation of the SAS-1 high -MAS-1 low profile. Thus, IHG-I was hallmarked by nearly complete representation of the SAS-1 high -MAS-1 low profile and underrepresentation of the SAS-1 low -MAS-1 high profile.

In contrast, IHG-IIc and IHG-IVc were hallmarked by complete representation of the SAS-1 low -MAS-1 high profile and absence of the SAS-1 high -MAS-1 low profile. IHG-IIa had some representation of the SAS-1 high -MAS-1 low profile.

Congruent with these findings, expression of SAS-1 was higher, whereas expression of MAS-1 was lower in IHG-I vs. the other grades in three distinct cohorts Supplementary Fig. In the COVID cohort, there was a stepwise decrease in IHG-I with age Fig.

Paralleling these findings with IHG-I, the representation of SAS-1 high -MAS-1 low i decreased with age Fig. hospitalized survivors and absent in nonsurvivors Fig.

Conversely, representation of the SAS-1 low -MAS-1 high profile was higher in older persons, nonsurvivors, and individuals with IHG-IV; intermediate in hospitalized survivors and those with IHG-II; and lower or absent in nonhospitalized survivors or those with IHG-I Fig. Fourth, consistent with our finding that some younger persons develop non-IHG-I grades that are more common in older persons Figs.

Furthermore, the relative representation of SAS-1 high -MAS-1 low vs. Hence, individuals with a survival disadvantage COVID nonsurvivors, patients with AIDS share the hallmark features found in IHG-IIc and IHG-IVc, namely, absence of SAS-1 high -MAS-1 low and enrichment of SAS-1 low -MAS-1 high Fig.

We suggest that i the SAS-1 high -MAS-1 low profile is a transcriptomic proxy for IHG-I and that both of these metrics of optimal IR are overrepresented in females Fig.

Compared with the SAS-1 high -MAS-1 low profile, the hazard of dying, after controlling for age and sex, was higher and similar in persons with the SAS-1 high -MAS-1 high and SAS-1 low -MAS-1 low profiles and highest in persons with the SAS-1 low -MAS-1 high profile Fig. Correspondingly, SAS-1 low -MAS-1 high was overrepresented and SAS-1 high -MAS-1 low was underrepresented at baseline in nonsurvivors Fig.

First, among older FHS participants, females lived longer than males, and levels of SAS-1 and MAS-1 further stratified survival rates Supplementary Fig. The survival rates in older 66—92 years persons were highest in females with SAS-1 high or MAS-1 low , intermediate in females with SAS-1 low or MAS-1 high and males with SAS-1 high or MAS-1 low , and lowest in males with SAS-1 low or MAS-1 high Supplementary Fig.

This survival hierarchy and our findings in Fig. c Model: age, sex, and immunologic resilience IR levels influence lifespan. d Sepsis 1 comprises healthy controls and meta-analysis of patients with community-acquired pneumonia CAP and fecal peritonitis FP stratified by sepsis response signature groups G1 and G2 associated with higher and lower mortality, respectively.

Sepsis 2 comprises healthy controls and patients with systemic inflammatory response syndrome SIRS , sepsis, and septic shock survivors S and nonsurvivors NS. P values asterisks, ns for participants with SAS-1 low -MAS-1 high at pre-ARI right are for their cross-sectional comparison to the profiles at the corresponding timepoints for participants with SAS-1 high -MAS-1 low at pre-ARI middle.

f Schema of the timing of gene expression profiling in experimental intranasal challenges with respiratory viral infection in otherwise healthy young adults with data presented in panels g and h. T, time. g Participants inoculated intra-nasally with respiratory syncytial virus RSV , rhinovirus, or influenza virus stratified by symptom status and sampling timepoint.

symptomatic, Asymp. h Participants inoculated intra-nasally with influenza virus stratified by symptom status and sampling timepoint. i Individuals with severe influenza infection requiring hospitalization collected at three timepoints, overall, and by age strata and severity.

Patients were grouped by increasing severity levels: no supplemental oxygen required, oxygen by mask, and mechanical ventilation. Cohort characteristics and sources of biological samples and gene expression profile data are in Supplementary Data 13a.

Based on gene expression profiles obtained at baseline admission , Knight and colleagues categorized four cohorts of individuals into sepsis risk groups that predicted mortality vs. survival in individuals admitted to intensive care units with severe sepsis due to community-acquired pneumonia or fecal peritonitis 37 , Our evaluations revealed that, irrespective of age, the survival-associated SAS-1 high -MAS-1 low profile was highly underrepresented, whereas SAS-1 low -MAS-1 high and SAS-1 low -MAS-1 low profiles were disproportionately overrepresented in the sepsis risk group associated with mortality G1 group vs.

survival G2 group Fig. Thus, consistent with our model Fig. We next examined whether asymptomatic ARI was associated with the IR erosion-resistant phenotype, i. symptomatic infection after viral challenge at two timepoints: baseline T1 vs.

when symptomatic patients had peak symptoms T2 Fig. Figure 8g shows the combined results of three different viral challenges influenza virus, respiratory syncytial virus, rhinovirus.

Among symptomatic participants, SAS-1 low -MAS-1 high was enriched at T2 vs. T1 Fig. In contrast, among persons who remained asymptomatic, proportions of the SAS-1 low -MAS-1 high profile did not change substantially between T1 and T2; instead at T2, there was a significant enrichment of SAS-1 high -MAS-1 low compared to symptomatic participants Fig.

Similar results were observed in another study in which participants were challenged with influenza virus Fig. Supporting these findings in humans, among pre-Collaborative Cross-RIX mice strains infected with influenza, SAS-1 high -MAS-1 low was overrepresented, whereas SAS-1 low -MAS-1 high was underrepresented in strains that manifested histopathologic features of mild low response vs.

severe high response infection Supplementary Fig. Paralleling the time series shown in Fig. However, regardless of age, the hallmark of less-severe vs. most-severe influenza infection was the capacity to reconstitute a survival-associated SAS-1 high -MAS-1 low profile more quickly Fig.

Figure 9a synthesizes the key findings from study phases 1, 2, and 3. Viral challenge studies in humans Fig. rapid restoration of the survival-associated IC high -IF low state SAS-1 high -MAS-1 low profile during the convalescence phase Fig.

Ag antigenic, F female, H high, IC immunocompetence, IF inflammation, L low, M male b IR erosion-resistant and IR erosion-susceptible phenotypes based on experimental models. c Correlation r ; Pearson between expression levels of genes within SAS-1 and MAS-1 signatures with levels of an indicator for T-cell responsiveness, T-cell dysfunction, and systemic inflammation.

d , e Levels of the indicated immune traits by IHGs in d sooty mangabeys seropositive for simian immunodeficiency virus SIV and e SIV-seronegative Chinese rhesus macaques. Comparisons were made between IHG-I vs. IHG-III and IHG-II vs. To further support the idea that the SAS-1 high -MAS-1 low profile tracks an IC high -IF low state, we determined the correlation between expression levels of genes comprising SAS-1 and MAS-1 with indicators of T-cell responsiveness and dysfunction in peripheral blood 8 , 43 , as well as systemic inflammation plasma IL-6, a biomarker of age-associated diseases and mortality 44 , 45 , 46 Fig.

Genes correlating positively with T-cell responsiveness and negatively with T-cell dysfunction or plasma IL-6 levels were considered to have pro-IR functions; genes with the opposite attributes were considered to have IR-compromising functions Fig. We found that SAS-1 was enriched for genes whose expression levels correlated positively with pro-IR functions; several of these genes have essential roles in T-cell homeostasis e.

Compared with SAS-1, MAS-1 was enriched for genes whose expression levels correlated with IR-compromising functions e.

These associations, coupled with the distribution patterns of the IR metrics across age, raised the possibility that levels of immune traits differed by i IR IHG status, after controlling for age age-independent vs.

ii age, regardless of IR IHG status age-dependent , vs. iii both. Additionally, because we observed evolutionary parallels between humans and nonhuman primates Figs. Trait levels in both species differed to a greater extent by IHG status than age Supplementary Data Thus, CD8-CD4 disequilibrium grades IHG-III and IHG-IV were highly prevalent in nonhuman primates Fig.

In general, IHG-I appeared to be associated with a better immune trait profile e. Contrary to nonhuman primates, CD8-CD4 equilibrium grades IHG-I and IHG-II vs. disequilibrium grades IHG-III or IHG-IV are much more prevalent across age in humans Fig. However, emphasizing evolutionary parallels, we identified similar traits associated with IHG status after controlling for age in both humans and nonhuman primates.

Group 1 comprised 13 immune traits whose levels differed between CD8-CD4 equilibrium vs. disequilibrium grades IHG-I vs. IHG-III or IHG-II vs IHG-IV , after controlling for age and sex. Group 3 comprised 10 immune traits that differed by attributes of both groups 1 and 2 after controlling for sex.

Group 4 neutral comprised 30 immune traits that did not differ by group 1 or 2 attributes Fig. Within each group, traits were clustered into signatures according to whether their levels were higher or lower with IHG-III or IHG-IV, after controlling for age and sex; by age in older or younger persons with IHG-I or IHG-II, after controlling for sex; both; or neither.

cDC, conventional dendritic cells. Two arrows indicate both comparisons for IHG-I vs. IHG-IV or age within IHG-I and IHG-II are significant, one arrow indicates only one of the comparisons for IHG status or age is significant.

b Representative traits by age in persons with IHG-I or IHG-II and by IHG status. Comparisons for the indicated traits were made between IHG-I vs.

Median number of individuals evaluated by IHG status and age within IHG-I or IHG-II. ns nonsignificant. c Linear regression was used to analyze the association between log 2 transformed cell counts outcome with age and IHG status predictors.

FDR, false discovery rate P values adjusted for multiple comparisons. d Model differentiating features of processes associated with lower immune status that occur due to aging or via erosion of IR. SAS-1, survival-associated signature-1; MAS-1, mortality-associated signature Figure 10b shows that the levels of a representative trait in signature 6 naïve CD8 bright differed between older vs.

younger persons with IHG-I or IHG-II but did not differ by IHG status. Thus, group 2 immune traits represent traits that are associated with aged CD8-CD4 equilibrium.

Additional trait features of Groups 1—4 are discussed Supplementary Note 8. Thus, suggesting evolutionary parallels, we identified similar immunologic features e. However, since the prevalence of IHG-III or IHG-IV increases with age Fig.

Our study addresses a fundamental conundrum. Conversely, why do some older persons resist manifesting these attributes? This failure indicates the IR erosion-susceptible phenotype. We examined IR levels and responses in varied human and nonhuman cohorts that are representative of different types and severity of inflammatory antigenic stressors.

The sum of our findings supports our study framework that optimal IR is an indicator of successful immune allostasis adaptation when experiencing inflammatory stressors, correlating with a distinctive immunocompetence-inflammation balance IC high -IF low that associates with superior immunity-dependent health outcomes, including longevity Fig.

This IR degradation correlates with a gene expression signature profile SAS-1 low -MAS-1 high tracking an IC low -IF high status linked to mortality both during aging and COVID, as well as immunosuppression e.

Despite clinical recovery from such common viral infections, some younger adults were unable to reconstitute optimal IR. However, since the prevalence of the SAS-1 low -MAS-1 high profile increases steadily with age, it may give the misimpression that this profile relates to the aging process vs.

IR degradation. To test our study framework Fig. These complementary metrics provide an easily implementable method to monitor the IR continuum irrespective of age Figs.

Paralleling the observation that females manifest advantages for immunocompetence and longevity 2 , 3 , 4 , 5 , the IR erosion-resistant phenotype was more common in females including postmenopausal.

Congruently, immune traits associated with some nonoptimal IR metrics were similar in humans and nonhuman primates. Additionally, in Collaborative Cross-RIX mice, the IR erosion-resistant phenotype was associated with resistance to lethal Ebola and severe influenza infection.

We accrued direct evidence of the benefits of optimal IR during exposure to a single inflammatory stressor by examining young adults during experimental intranasal challenge with common respiratory viruses e. The hallmark of asymptomatic status after intranasal inoculation of respiratory viruses was the capacity to preserve, enrich, or rapidly restore the survival-associated SAS-1 high -MAS-1 low profile Figs.

Findings noted on longitudinal monitoring of IR degradation and reconstitution during natural infection with common respiratory viruses supported this possibility.

During recovery, reconstitution of optimal IR was greater and faster in persons who before infection had the survival-associated SAS-1 high -MAS-1 low vs.

the SAS-1 low -MAS-1 high profile Fig. However, despite the elapse of several months from initial infection, some younger persons with the SAS-1 high -MAS-1 low profile before infection failed to reconstitute this profile exemplifying residual deficits in IR Fig.

An impairment in the capacity for reconstitution of optimal IR was also observed in prospective cohorts with other inflammatory contexts FSWs, COVID, HIV infection.

These findings support our viewpoint that the deviation from optimal IR that tends to occur with age could be due to an impairment in the reconstitution of IR in individuals with the IR erosion-susceptible phenotype Fig. There is significant interest in identifying host genetic factors that mediate resistance to acquiring SARS-CoV-2 or developing severe COVID 59 , 60 , We are currently investigating whether failure to reconstitute optimal IR after acute COVID may contribute to postacute sequelae.

Resistance to HIV acquisition despite exposure to the virus is a distinctive trait 62 observable in some FSWs. Among FSWs with comparable levels of risk factor-associated antigenic stimulation, HIV seronegativity was an indicator of the IR erosion-resistant phenotype, whereas seropositivity was an indicator of the IR erosion-susceptible phenotype.

Having baseline IHG-IV, a nonoptimal IR metric, associated with a nearly 3-fold increased risk of subsequently acquiring HIV, after controlling for level of risk factors.

We found that a subset of FSWs had the capacity for preservation of optimal IR, both before and after HIV infection. By analogy, we suggest that CMV seropositivity may have similar indicator functions Supplementary Notes 3 , 9.

The IR framework points to the commonalities in the HIV and COVID pandemics. Our findings suggest that these pandemics may be driven by individuals who had IR degradation before acquisition of viral infection.

With respect to the HIV pandemic, nonoptimal IR metrics are overrepresented in persons with behavioral and nonbehavioral risk factors for HIV, and these metrics predict an increased risk of HIV acquisition. Correspondingly, HIV burden is greater in geographic regions where the prevalence of nonbehavioral risk factors is also elevated e.

With respect to the COVID pandemic, the proportion of individuals preserving optimal IR metrics decreases with age and age serves as a dominant risk factor for developing severe acute COVID Controlling for age, the likelihood of being hospitalized was significantly lower in individuals preserving optimal IR at diagnosis with COVID Thus, individuals with the IR erosion-susceptible phenotype may have contributed substantially to the burden of these pandemics.

Our study has several limitations expanded limitations in Supplementary Note The primary limitation is our inability to examine the varied clinical outcomes assessed here in a single prospective human cohort.

Such a cohort that spans all ages with these varied inflammatory stressors and outcomes is nearly impossible to accrue, necessitating the juxtaposition of findings from varied cohorts. Additionally, we were unable to evaluate immune traits in peripheral blood samples bio-banked from the same individual when they were younger vs.

However, we took several steps to mitigate this limitation discussed in Supplementary Notes 2 , 8. However, our findings satisfy the nine Bradford-Hill criteria 65 , the most frequently cited framework for causal inference in epidemiologic studies Supplementary Note We acknowledge that, in addition to inflammatory stressors, the changes in IR metrics observed during aging Figs.

Possible confounders regarding the generation of the IHGs and their distribution patterns in varied settings of increased antigenic stimulation are discussed Supplementary Notes 1 , 2 , 3 and 6.

While we focused on the association between antigenic stimulation associated with inflammatory stressors and shifts in IHG status, psychosocial stressors may contribute, as they associate with age-related T lymphocyte percentages in older adults However, the latter lymphocyte changes can be indirect, as psychosocial stressors may predispose to infection 68 , As a final limitation, we could not evaluate whether eroded IR mitigates autoimmunity.

Supporting our conclusion that age-independent mechanisms contribute to IR status, we provide evidence that host genetic factors in MHC locus associate with the IR erosion phenotypes Supplementary Note 5. age Fig. First, while a significant effort is placed on targeting the immune traits associated with age, we show that immune traits group into those associated i uniquely with IR status irrespective of age, ii uniquely with age, and iii both age and IR status Fig.

Some of the immune traits that associate with uniquely nonoptimal IR metrics have been misattributed to age e. Hence, a comparison of immune traits between younger and older persons conflates these groupings, obscuring the immune correlates of age.

Second, the reversibility of eroded IR suggests that immune deficits linked to this erosion are separable from those linked directly to the aging process and may be more amenable to reversal.

However, our findings in FSWs and during natural respiratory viral infections indicate that this reversal may take months to years to occur. Additionally, data from FSWs and sooty mangabeys illustrate that multiple sources of inflammatory stress have additive negative effects on IR status Fig.

Hence, reconstitution of optimal IR may require cause-specific interventions. In summary, our findings support the principles of our framework Fig.

Irrespective of these factors, most individuals do not have the capacity to preserve optimal IR when experiencing common inflammatory insults such as symptomatic viral infections. Deviations from optimal IR associates with an immunosuppressive-proinflammatory, mortality-associated gene expression profile.

This deviation is more common in males. Those individuals with capacity to resist this deviation or who during the recovery phase rapidly reconstitute optimal IR manifest health and survival advantages. However, under the pressure of repeated inflammatory antigenic stressors experienced across their lifetime, the number of individuals who retain capacity to resist IR degradation declines.

How might these framework principles inform personalized medicine, development of therapies to promote immune health, and public health policies? First, individuals with suboptimal or nonoptimal IR can potentially regain optimal IR through reduction of exposure to infectious, environmental, behavioral, and other stressors.

Second, IR metrics provide a means to gauge immune health regardless of age, sex, and underlying comorbid conditions. Thus, early detection of individuals with IR degradation could prompt a work-up to identify the underlying inflammatory stressors.

Third, balancing trial and placebo arms of a clinical trial for IR status may mitigate the confounding effects of this status on outcomes that are dependent on differences in immunocompetence and inflammation. Fourth, while senolytic agents are being investigated for the reversal of age-associated pathologies 75 , the findings presented herein provide a rationale to consider the development of strategies that, by targeting the IR erosion-susceptible phenotype, may improve vaccine responsiveness, healthspan, and lifespan.

Finally, population-level differences in the prevalence of IR metrics may help to explain the racial, ethnic, and geographic distributions of diseases such as viral infections and cancers. Hence, strategies for improving IR and lowering recurrent inflammatory stress may emerge as high priorities for incorporation into public health policies.

All studies were approved by the institutional review boards IRBs at the University of Texas Health Science Center at San Antonio and institutions participating in this study. The IRBs of participating institutions are listed in the reporting summary. All studies adhered to ethical and inclusion practices approved by the local IRB.

The cohorts and study groups Fig. The SardiNIA study investigates genotypic and phenotypic aging-related traits in a longitudinal manner. The main features of this project have been described in detail previously 9 , 76 , All residents from 4 towns Lanusei, Arzana, Ilbono, and Elini in a valley in Sardinia Italy were invited to participate.

Immunophenotype data from participants age 15 to years were included in this study. Details provided in Supplementary Information Section 1. The Majengo sex worker cohort 17 is an open cohort dedicated to better understanding the natural history of HIV infection, including defining immunologic correlates of HIV acquisition and disease progression.

The present study comprised initially HIV-negative FSWs with data available for analysis and were evaluated from the time they were enrolled see criteria in Supplementary Fig. Of these, subsequently seroconverted.

The characteristics of these FSWs are listed in Supplementary Data 4a. The association of risk behavior e. Among these, 53 subsequently seroconverted. Prior to seroconversion, the 53 FSWs were followed for The characteristics of these FSWs are listed in Supplementary Data 4b.

To investigate the associations of IHG status with cancer development, we assessed the hazard of developing CSCC within a predominantly White cohort of long-term RTRs. A total of RTRs with available clinical and immunological phenotype were evaluated.

The characteristics of the RTRs are as described previously 15 and summarized in Supplementary Data 5. Briefly, 65 eligible RTRs with a history of post-transplant CSCC were identified, of whom 63 were approached and 59 participated.

Seventy-two matched eligible RTRs without a history of CSCC were approached and 58 were recruited. Fifteen percent of participants received induction therapy at the time of transplant, and 80 percent had received a period of dialysis prior to transplantation.

haematobium urinary tract infection were from a previous study Briefly, all participants were examined by ultrasound for S. haematobium infection and associated morbidity in the Msambweni Division of the Kwale district, southern Coast Province, Kenya, an area where S.

haematobium is endemic. No community-based treatment for schistosomiasis had been conducted during the preceding 8 years of enrollment in this population. From this initial survey, we selected all children 5—18 years old residing in 2 villages, Vidungeni and Marigiza, who had detectable bladder pathology and S.

haematobium infection. The HIV-seronegative UCSD cohort was accessed from HIV Neurobehavioral Research Center, UCSD, and derived from the following three resources: a those who enrolled as a normative population for ongoing studies funded by the National Institute of Mental Health; b those who enrolled as a normative population for studies funded by the National Institute on Drug Abuse; and c those who enrolled as HIV— users of recreational drugs for studies funded by the National Institute on Drug Abuse.

In the present study, we evaluated participants pooled from the three abovementioned sources. This was a prospective observational cohort study of patients testing positive for SARS-CoV-2 evaluated at the Audie L. Murphy VA Medical Center, South Texas Veterans Health Care System STVHCS , San Antonio, Texas, from March 20, , through November 15, The cohort characteristics and samples procedures are described in Supplementary Data 2 and Supplementary Data 7.

The cohort features of a smaller subset of patients studied herein and samples procedures have been previously described 6. COVID progression along the severity continuum was characterized by hospitalization and death. Standard laboratory methods in the Flow Cytometry Core of the Central Pathology Laboratory at the Audie L.

The overview of this cohort is shown in Supplementary Fig. All measurements evaluated in the present study were conducted prior to the availability of COVID vaccinations. RNA-Seq was performed on a subset of this cohort as previously described 6.

These participants were recruited between June and June and then followed prospectively. Details of the cohort are as described previously 7.

We evaluated only participants in whom an estimated date of infection could be calculated through a series of well-defined stepwise rules that characterize stages of infection based on our previously described serologic and virologic criteria 7. Of the participants, were evaluated in the present study while they were therapy-naïve see criteria in Supplementary Fig.

The inclusion criteria are outlined in Supplementary Fig. Participants in the cohort self-selected ART or no ART, and those who chose not to start therapy were followed in a manner identical to those who chose to start ART.

Rules of computing time to estimated date of infection are as reported by us previously 7. The US Military HIV Natural History Study is designated as the EIC.

This is an ongoing, continuous-enrollment, prospective, multicenter, observational cohort study conducted through the Uniformed Services University of the Health Sciences Infectious Disease Clinical Research Program. The EIC has enrolled approximately active-duty military service members and beneficiaries since at 7 military treatment facilities MTFs throughout the United States.

The US military medical system provides comprehensive HIV education, care, and treatment, including the provision of ART and regular visits with clinicians with expertise in HIV medicine at MTFs, at no cost to the patient. Mandatory periodic HIV screening according to Department of Defense policy allowed treatment initiation to be considered at an early stage of infection before it was recommended practice.

Eighty-eight percent of the participants since have documented seroconversion i. In the present study, of EIC participants were available for evaluation Supplementary Fig. Additional details of the SardiNIA 9 , 76 , 77 , FSW-MOCS 17 , PIC-UCSD 7 , RTR cohort 15 , S. haematobium -infected children cohort 78 , and EIC 8 , 79 , 80 , 81 , 82 have been described previously.

Some features of the entire populations or subsets of the SardiNIA, COVID, SLE Supplementary Information Section 8. One hundred sixty sooty mangabeys were evaluated in the current study.

Of these, 50 were SIV seronegative SIV— and were naturally infected with SIV Figs. Data from a subset of these sooty mangabeys have been reported by Sumpter et al. All sooty mangabeys were housed at the Yerkes National Primate Research Center and maintained in accordance with National Institutes of Health guidelines.

In uninfected animals, negative SIV determined by PCR in plasma confirmed the absence of SIV infection. Other immune traits studied are reported in Supplementary Data Forty-seven male and 40 female SIV— Chinese rhesus macaques from a previous study were evaluated Fig. All animals were colony-bred rhesus macaques M.

mulatta of Chinese origin. All animals were without overt symptoms of disease tumors, trauma, acute infection, or wasting disease ; estrous, pregnant, and lactational macaques were excluded. In a study by Rasmussen et al. Different strains were crossed with one another to generate CC-RIX F1 progeny.

We selected those cutoffs based on the following rationale. Additional details regarding the IHGs are described in Supplementary Note 1. Immune correlates markers that associated with IHG status vs. age in the SardiNIA cohort were assessed on fresh blood samples.

A set of multiplexed fluorescent surface antibodies was used to characterize the major leukocyte cell populations circulating in peripheral blood belonging to both adaptive and innate immunity. Briefly, with the antibody panel designated as T-B-NK in Supplementary Data 12 , we identified T-cells, B-cells, and NK-cells and their subsets.

We also used the HLA-DR marker to assess the activation status of T and NK cells. The regulatory T-cell panel Treg in Supplementary Data 12 was used to characterize regulatory T-cells subdivided into resting, activated, and secreting nonsuppressive cells 96 , Moreover, in selected T-cell subpopulations, we assessed the positivity for the ectoenzyme CD39 and the CD28 co-stimulatory antigen Finally, by the circulating dendritic cells DC panel, we divided circulating DCs into myeloid conventional DC, cDC and plasmacytoid DCs pDC and assessed the expression of the adhesion molecule CD62L and the co-stimulatory ligand CD86 , The circulating DC panel is labelled DC in Supplementary Data Detailed protocols and reproducibility of the measurements have been described 9.

Leukocytes were characterized on whole blood by polychromatic flow cytometry with 4 antibody panels, namely T-B-NK, regulatory T-cells Treg , Mat, and circulating DCs, as described elsewhere 9 and detailed in Supplementary Information Section 5.

IL-7 is a critical T-cell trophic cytokine. Methods were as described previously 8 , Systemic inflammation was assessed by measuring plasma IL-6 levels using Luminex assays, employing methods described by the manufacturer. Further details are provided in Supplementary Information Section 6.

RNA-seq analysis was performed in the designated groups See Supplementary Information section 7. RNA quantity and purity were determined using an Agilent Bioanalyzer with an RNA Nano assay Agilent Technologies, Palo Alto, CA.

Briefly, mRNA was selected using poly-T oligo-attached magnetic beads and then enzymatically fragmented. First and second cDNA strands were synthesized and end-repaired. The library with adaptors was enriched by PCR.

Libraries were size checked using a DNA high-sensitivity assay on the Agilent Bioanalyzer Agilent Technologies, Palo Alto, CA and quantified by a Kapa Library quantification kit Kapa Biosystems, Woburn, MA. Base calling and quality filtering were performed using the CASAVA v1. Sequences were aligned and mapped to the UCSC hg19 build of the Homo sapiens genome from Illumina igenomes using tophat v2.

Gene counts for 23, unique, well-curated genes were obtained using HTSeq framework v0. Gene counts were normalized, and dispersion values were estimated using the R package, DESeq v1. The design matrix row — samples; column — experimental variables used in DESeq, along with gene-expression matrix row — genes; column — gene counts in each sample , included the group variable therapy-naïve, HIV—, IHG , CMV serostatus, and the personal identification number, all as factors, and other variables.

Genes with a gene count of 0 across all samples were removed; the remaining zeros 0 were changed to ones 1 and these genes were used in the gene-expression matrix in DESeq. The size factors were estimated using the gene-expression matrix taking library sizes into account; these were used to normalize the gene counts.

Cross-sectional differences between the groups were assessed. The correlation of genes with functional markers T-cell responsiveness, T-cell dysfunction, and systemic inflammation was assessed in a subset of this cohort and is detailed in Supplementary Information Section 7.

Details for deriving transcriptomic signature scores are in Supplementary Information Section 8. From our previous work on immunologic resilience in COVID 6 , 3 survival-associated signatures SAS and 7 mortality-associated signatures MAS were derived from peripheral blood transcriptomes of 48 patients of the COVID cohort.

Of these, the topmost hits in each category SAS-1 and MAS-1 were used in this study. Briefly, a generalized linear model based on the negative binomial distribution with the likelihood ratio test was used to examine the associations with outcomes: non-hospitalized [NH], hospitalized [H], nonhospitalized survivors [NH-S], hospitalized survivors [H-S], hospitalized-nonsurvivors [H-NS], and all nonsurvivors [NS] at days.

NH groups genes associated with hospitalization status , and H-NS vs. H-S genes associated with survival in hospitalized patients were identified.

Next, in peripheral blood transcriptomes, genes that were DE between H-S vs. NH-S, NS vs. H-S, and NS vs. NH-S groups were identified and the genes that overlapped in these comparisons with a concordant direction of expression were examined.

This approach allowed us to identify genes that track from less to greater disease severity and vice versa i. Note: NS in this analysis include both NH and H patients who died. DAVID v6.

Based on the differentially expressed genes identified in each comparison and their direction of expression upregulated vs. The filtering resulted in 51 GO-BP terms 51 sets of gene signatures and 1 signature set of 28 genes, the top 52 gene signatures.

Ten signatures overlapped between both cohorts and were further examined. Supplementary Data 9b describes the gene compositions of the 3 SAS and 7 MAS gene signatures. SASs and MASs were numbered according to their prognostic capacity for predicting survival or mortality, respectively in the FHS [lowest to highest Akaike information criteria; SAS-1 to SAS-3 and MAS-1 to MAS-7] Supplementary Data 9c—d.

The top associated signature in each category SAS-1 and MAS-1 were used in this study as z -scores. SAS-1 and MAS-1 correspond to the gene signature 32 immune response and 4 defense response to gram-positive bacterium , respectively, as detailed in our recent report 6. To generate the z -scores, the normalized expression of each gene is z -transformed mean centered then divided by standard deviation across all samples and then averaged.

High indicates expression of the score in the sample greater than the median expression of the score in the dataset, whereas low indicates expression of the score in the sample less than or equal to the median expression of the score in the dataset.

The profiles detailed statistical methods per figure panel Supplementary Information Sections A list of 57 genes Supplementary Information section 8. The genes significantly and consistently correlated with both age and cell-based IMM-AGE score that predicted all-cause mortality in the FHS offspring cohort Note: the directionality of association of IMM-AGE transcriptomic-based with mortality reported by us in Fig.

The IMM-AGE transcriptomic signature score was examined in different datasets to assess its association with survival. To generate the z -score, the log 2 normalized expression of each gene is z -transformed mean centered then divided by standard deviation across all samples and then averaged.

Details of the publicly available datasets are provided in Supplementary Information Section 8. The broad principles used for the statistical approach are described in Supplementary Information Section 2. This section provides general information on the study design and how statistical analyses were conducted and are detailed in the statistics per panel section in the Supplementary information.

In addition, each figure is linked with a source document for reproducibility. Furthermore, given the wide range of cohorts and conditions IHGs were examined under, we believe these results to be highly reproducible.

Because secondary analyses were conducted, a priori sample size calculations were not conducted. This was not an interventional study; therefore, no blinding or randomization was used. Reported P values are 2-sided and set at the 0.

The models and P values were not adjusted for multiple comparisons in the prespecified subgroup analyses, unless otherwise noted. All cutoffs and statistical tests were determined pre hoc.

The log-rank test was used to evaluate for overall significance. Details of Pearson vs. Spearman correlation coefficient are provided in Supplementary Information Section Follow-up times and analyses were prespecified.

Boxplots center line, median; box, the interquartile range IQR ; whiskers, rest of the data distribution ±1. Line plots were used to represent proportions of indicated variables. Kaplan-Meier plots were used to represent proportion survived over time since score calculation baseline by indicated groups.

Heatmaps were used to represent correlations of gene signature scores and continuous age. Stacked barplots or barplots were used to represent proportions or correlation coefficients of indicated variables. Pie charts were used to represent proportions of indicated variables. In the COVID cohort, a Cox proportional hazards model, adjusted for sex and age as a continuous variable, was used to determine whether the gene scores associated with day survival.

In the FHS offspring cohort, a Cox proportional hazards model, adjusted for sex and age as a continuous variable, was used to determine whether the gene scores associated with survival.

Kaplan-Meier survival plots of the FHS offspring cohort are accompanied by P values determined by log-rank test. Grades of antigenic stimulation and IR metrics were used as predictors. For determining the association between level of antigenic stimulation and IHG status in HIV— persons, proxies were used to grade this level and quantify host antigenic burden accumulated: 1 age was considered as a proxy for repetitive, low-grade antigenic experiences accrued during natural aging; 2 a BAS based on behavioral risk factors condom use, number of clients, number of condoms used per client and a total STI score based on direct [syphilis rapid plasma reagin test and gonorrhea] and indirect vaginal discharge, abdominal pain, genital ulcer, dysuria, and vulvar itch indicators of STI were used as proxies in HIV— FSWs for whom this information was available; and 3 S.

haematobium egg count in the urine was a proxy in children with this infection. ANOVA-based linear regression model was used to evaluate the overall differences between 3 or more groups.

For comparison of groups with multiple samples from the same individuals, we used a linear generalized estimating equation GEE model based on the normal distribution with an exchangeable correlation structure unless otherwise stated. For the association of gene scores with outcomes, linear regression linear model was used to test them, instead of nonparametric tests as highlighted below in the panel-by-panel detailed statistical methods for each of the figures.

For comparison of groups with multiple samples from the same individuals, we used a linear GEE model based on the normal distribution with an exchangeable correlation structure unless otherwise stated. For meta-analyses e.

All datasets were filtered for common probes. Then, an expression matrix of the probes and samples was created and concurrently normalized as stated in Supplementary Information Section 9. Example: if dataset 1 provided log 2 values and dataset 2 was quantile normalized, dataset 1 would be un-log transformed by exponentiation with the base 2 before combining with dataset 2 for concurrent normalization and computation of scores.

The phenotype groups for plots were determined from the phenotype data deposited in the GEO or ArrayExpress along with the dataset. The phenotype groups were classified based on the hypothesis evaluated. The transcriptomic signature score is a relative term within a dataset, and it is challenging to compare the score across different datasets.

For the meta-analyses, we used a series of criteria as described in Supplementary Information Section 9. Different RNA microarray or RNA-seq platforms have differences in the availability of gene probes corresponding to the genes in a given transcriptomic signature score.

Thus, we indicated the gene count range in each dataset Supplementary Data 13b. To fully support our immune resilience, we need to nourish the entire body and all organ systems. We do this through plant nutrition and by integrating the lifestyle practices that support the wellbeing of our mind, body, and spirit.

I encourage everyone to use this time to focus on creating habits such as:. These simple lifestyle practices can do wonders for our immune system and resiliency against harmful pathogens.

If you are feeling intimidated by lifestyle changes, explore one positive lifestyle practice every week or two along with increasing your plant diversity. You may be amazed at how small changes can accumulate to profound lifestyle habits.

On the other side, thoughts and feelings of love, peace, acceptance, and gratitude improve immune and organ functions. I think this is becoming more important to maintain our overall health during the current political, economic, and social climates. Take a few deep breaths right now.

Think of three things you are grateful for and begin sending signals throughout your body and mind for a resilient and adaptive immune system and stress response. Enjoy this feeling and smile while we continue talking about the role of plants and nutrition. When we use herbs and food to support our immune system, we bring in the nutritional building blocks that fuel and support our immune functions while inhibiting the growth of harmful viruses and bacteria.

If we do not have diverse nutrition from plants, our immune system has no materials to create the defenses. The beneficial flora will not be populated or diverse enough to play their essential role either. Resulting in less overall resiliency and increased opportunities for harmful pathogens to take advantage.

This leads to an increased frequency of illness, duration, and symptoms. This article will focus on building and strengthening immunity to prevent.

We use different plants to prevent pathogen-related colds, flu, and respiratory ailments than the herbs used to reduce symptoms and support us when we are sick. We often call these herbs deep immune tonics or adaptogens. I will highlight a few essential nutrients known for their vital role in our immune functions and how we can naturally source them from plants below.

Keep in mind we need diversity of all nutrients to support the complex picture of health and resilience. Most of us are aware Vitamin C is essential for our immune system and is used to create immune cells.

One of the best ways we can increase our bioavailable sources is from fresh seasonal fruit. During this time of year, explore those hearty fall and winter fruits like apples, oranges, rosehips, elderberry, mulberry, cranberry, pomegranate, and passion fruit.

They feed the beneficial flora and support liver and kidney health, digestion, elimination, blood cleansing, and more.

Here is more information about two herbal berries rich in vitamin C and immune support: elderberry and rosehip. Elderberry Sambucus canadensis; S.

nigra; S. Elderberry is a very potent anti-viral, most specific for the flu virus. It is best when taken daily to prevent getting sick as it has a protective nature. It coats the cells throughout our respiratory tract and creates a barrier of protection, inhibiting viruses from finding a home in our cell.

Without a host, the virus dies and is unable to replicate. Then it is cleared out through the mucous or lymph. Use the dried berries in tea, syrup, tincture, oxymel, supplement, honey, jam, or compote preparations. If you are harvesting your own, be sure you are gathering from the blue or black elder as there are non-medicinal species.

Rosehip Rosa spp. The hips or berries from the medicinal or wild rose develop after the petals fall, and they ripen in the frost. Rosehips are among the few food sources found during the cold winter months, especially in areas with snow. They are delicious in tea, syrups, jam, and compote.

Those deficient in vitamin D have a slower recovery and more symptoms than those within the recommended range. As we go into the shorter days of late fall and winter, mushrooms become an excellent way to make up for our lack of sun exposure.

Mushrooms are known for protecting the cells against damage and strengthening the structural integrity of our cells. They directly support the production and efficiency of our immune cells and digestion, liver, lymph, stress, and detoxing.

Mushrooms address every aspect of building a resilient immune system ready to fight off illness upon exposure. Eat your mushrooms, make broths, soups, stews, and sauces, and add them into stir-fries, vegetable dishes, and more.

They are so versatile. You can also find high-quality mushroom supplements, powders, teas, and extracts. Explore the diversity of seasonal mushrooms when you can.

As the plants die back during the colder months, we are left with many hearty and nourishing roots as a primary food source. Roots and tubers have a deep nutritious quality and tend to be very mineral-rich with various enzymes and beneficial bacteria they receive from the soil.

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Michael Garko, a nutrition expert, says one of the best ways to prevent those Body composition is to give your Oxidative stress-induced diseases the boost it needs.

There's no 'one size fits all,' Buildimg by Building immune system resilience our bodies and addressing deficiencies, we can significantly resilidnce our Bjilding. When you Bkilding, that's when your immune system reconstitutes itself.

That's when your memories are consolidated too by the way, and that's when your whole body gets a chance to sort of recover and take— hit a reset button," said Garko.

That's what it is," said Garko. Doctors say building your body's defense system by taking care of it on the inside is key to staying healthy and not getting sick during the peak of cold and flu season. Thanks for reading CBS NEWS. Please enter email address to continue.

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: Building immune system resilience

How to Build a Resilient Immune System	Second, akin to the overrepresentation of IHG-I in females across age strata Fig. This failure indicates the IR erosion-susceptible phenotype. In doing so, we protect ourselves so that if we become exposed to the virus, we may only develop a mild case. About your immune system Factors that affect your immune system Strengthening your immune system Last words What to know Authors. February 15, Helpful ways to strengthen your immune system and fight off disease How can you improve your immune system? doi:
How to boost your immune system - Harvard Health	Elderberry Sambucus canadensis; S. nigra; S. Elderberry is a very potent anti-viral, most specific for the flu virus. It is best when taken daily to prevent getting sick as it has a protective nature. It coats the cells throughout our respiratory tract and creates a barrier of protection, inhibiting viruses from finding a home in our cell. Without a host, the virus dies and is unable to replicate. Then it is cleared out through the mucous or lymph. Use the dried berries in tea, syrup, tincture, oxymel, supplement, honey, jam, or compote preparations. If you are harvesting your own, be sure you are gathering from the blue or black elder as there are non-medicinal species. Rosehip Rosa spp. The hips or berries from the medicinal or wild rose develop after the petals fall, and they ripen in the frost. Rosehips are among the few food sources found during the cold winter months, especially in areas with snow. They are delicious in tea, syrups, jam, and compote. Those deficient in vitamin D have a slower recovery and more symptoms than those within the recommended range. As we go into the shorter days of late fall and winter, mushrooms become an excellent way to make up for our lack of sun exposure. Mushrooms are known for protecting the cells against damage and strengthening the structural integrity of our cells. They directly support the production and efficiency of our immune cells and digestion, liver, lymph, stress, and detoxing. Mushrooms address every aspect of building a resilient immune system ready to fight off illness upon exposure. Eat your mushrooms, make broths, soups, stews, and sauces, and add them into stir-fries, vegetable dishes, and more. They are so versatile. You can also find high-quality mushroom supplements, powders, teas, and extracts. Explore the diversity of seasonal mushrooms when you can. As the plants die back during the colder months, we are left with many hearty and nourishing roots as a primary food source. Roots and tubers have a deep nutritious quality and tend to be very mineral-rich with various enzymes and beneficial bacteria they receive from the soil. Many roots provide complex carbohydrates and are high in antioxidants, vitamin A, vitamin C, potassium, magnesium, dietary fiber, inulin, and more. Root vegetables are known to help reduce inflammation and protect the cells from free radical damage. They nourish and protect skin and eye health, help lower cholesterol, support a happy heart, improve cognitive functions, nourish the liver, regulate insulin by slowing sugar conversion, and more. Root veggies are beneficial as a prebiotic to feed and create an environment for beneficial bacteria to thrive. All these benefits can be enjoyed by eating roots and making decoctions to drink throughout the day. Some examples of winter root vegetables include beets, rutabaga, parsnips, turnips, sweet potatoes, potatoes, onion, garlic, leeks, horseradish, radish, daikon radish, carrots, burdock, dandelion, yellow dock, etc. Warming Spices. Have delicious fun in the kitchen and spice up your life!! Almost all spices have benefits for our immune system. They support a diverse population of healthy flora by feeding the good bacteria and inhibiting harmful growth. Spices also support digestion, gut health, liver health, and more. Incorporate chai-like beverages, mulling spices, curry spice blends, Mediterranean spices, Indian Spices, Asian Spices, and any other cuisine you enjoy. Bring in your favorite fresh spices like garlic, onion, ginger, turmeric, chives, rosemary, sage, oregano, thyme, and parsley, when you can. Remembering diversity is key! Note: If you run hot all the time, even in cooler weather, limit heating and pungent spices and focus on more neutral or cooling ones instead. Use any combination of Mediterranean herbs i. along with nourishing herbs such as nettle, dandelion leaf, or burdock root. Include immune-enhancing mushrooms shitake have the best flavor , astragalus root, and seaweeds. Chop up some onion and garlic as much as you can palate and incorporate chicken or other meat for protein, if desired. Add any veggies or scraps you have for additional nutrients. Sauté any vegetables and spices in oil for a few minutes, add water and simmer on low heat for hours covered. Strain and drink or use as a base to make soup, cook beans, grains, and other meals. We can naturally source it from various beans, lentils, oats, nuts, seeds, tofu, and mushrooms. Zinc can be found in animal sources, including meat, oysters, dairy, cheese, and yoghurt. I like the idea of making sure I eat nuts and fruit daily for vitamin C and zinc combination. Sometimes with a little yoghurt if I am not avoiding dairy. Thanks for reading CBS NEWS. Please enter email address to continue. Please enter valid email address to continue. Featured Local Savings. More from CBS News. Maryland MVA changes learner's permit test to make more equitable for aspiring drivers. Maryland high school diver inspires young athletes with book, "A Diver Like Me". Anne Arundel County Public Schools taking back Chromebooks from students. Mayor's Office of Safety and Engagement announces funding to improve public safety. View CBS News In. CBS News App Open.
Immune Fitness: working towards a resilient immune system	Immne, R. Venticinque, Jorge A. Little, Oxidative stress-induced diseases Gianella, Davey Resilieence. IHG-I group A Leafy green retailers associated with a significantly higher odds ratio of hospitalization Fig. Their Email Required. Many of the immune-supporting herbs support a healthier stress response to manage how we react and respond to stressors in our lives.
Build a More Resilient Immune System	Importantly, the researchers also developed accessible tools for measuring immune resilience in both healthcare settings and clinical research. Those tests could help doctors factor in immune resilience before surgeries or during checkups to predict patient risks and outcomes. Another measurement is based on the expression of certain genes. These tests could help researchers control for immune resilience in clinical trials, uncover connections between immune resilience and aging, and learn more about how and why immune resilience is eroded in some persons but not others facing the same inflammatory stressor. The paper, published June 13 in the journal Nature Communications , combines findings from around 48, people in different studies conducted in Africa, Europe and North America. The research involved a global team led by Sunil Ahuja, MD, a professor of medicine at The University of Texas Health Science Center at San Antonio and director of the Veterans Administration Center for Personalized Medicine. The research team found that, as in other facets of life, resilience at an immune level is related to both what you are up against and how you respond. According to the researchers, low levels of inflammatory stress combined with highly competent immune responses were most protective for health. Still, some people managed to maintain high immune function even in the face of lots of inflammatory stress, a finding that raises new opportunities for research into longevity and health. The ability to respond effectively is called immunocompetence, which the researchers assessed by two different metrics. The first metric involves measuring the proportional mix of two different types of T-cells, which are the white blood cells that activate when the body responds to threats. Researchers identified a specific mix that predicted the best immunocompetence. They created an immune health grade IHG to capture how well people align with this mix on a scale of one to four, with IHG-I being the most protective and IHG-IV being the least. A simple lab test can measure that mix for individuals. Some of our genes change their expression in response to infections or other inflammatory stressors. The researchers found one pattern of gene expression that was associated with survival, which they called survival-associated signature or SAS SAS-1 comprised genes related to immune competence and higher expression of these genes correlated with survival. They also found another cluster of genes and gene expression associated with lower resilience and premature death. That mortality-associated cluster they termed MAS MAS-1 comprised genes related to inflammation and higher expression of these genes correlated with mortality. When the body kicks into gear — whether in response to the flu or simply to allergy season — that response is known as inflammation. The researchers found that, like the T-cell metric, these patterns of gene expression can be used as a proxy for overall immune resilience. A mix of high SAS-1 gene expression and low MAS-1 gene expression, which the researchers labeled optimal immune resilience, correlated with general longevity, as well as a wide variety of specific positive health outcomes, like survival from sepsis and COVID, resistance to acquiring HIV infection, a slower rate of progression to AIDS, avoiding recurring cancer after a kidney transplant, and avoiding flu symptoms. To tease apart the roles of immunocompetence and inflammation in immune resilience, the researchers looked at people likely to face high, medium and low levels of immune stressors in their daily lives. For low levels, they looked at thousands of people participating in studies on aging. For medium levels, they looked at people with autoimmune disorders, kidney transplants or COVID infections, along with sex workers exposed to sexually transmitted infections. For high levels of immune system activation, they looked at people living with HIV, who experience consistent inflammatory stress because their immune systems misread lots of things as threats. The researchers found that immune resilience can change during inflammatory stress. In T-cell readings before and after flu season or COVID, as well as after volunteer challenges with common respiratory viruses, the researchers found that immune resilience goes down while the immune system is actively inflamed and fighting a threat. For most people, once the threat had passed, the metrics of immune resilience returned to levels that preceded the threat. But for other people, metrics dropped and stayed lower for months. The researchers found that periods of inflammatory stress can degrade immunocompetence, making our bodies less effective at responding to future risks. That finding may open new avenues for research into longevity. But they did find that more competent immune systems were associated with lower mortality. COVID patients, for example, were less likely to die if they presented with metrics of optimal immune resilience. In good news for people with lower immune resilience, the researchers also found that immunocompetence may improve over time. For degraded immune systems, it appears that just getting a break from inflammatory stress may help immunocompetence rebound. One group of sex workers, for example, had frequent unprotected sex at the beginning of the year study — meaning lots of sexually transmitted infections for their immune systems to fight off. Stress is the number one enemy of immunity. Abhyanga also corrects the functioning of the lymphatic system that is responsible to keep our immune system robust. Clarified butter is now popular enough in the west for the healthy fat that it is, as more research shows its myriad benefits in improving digestion, eyesight, detoxifying the body and building resilience. Ghee, when made using the milk of finest breeds of grass-fed cows, whose well-being is looked into, reflects in the purity and texture of the ghee. Ghee absorbs fat soluble vitamins like A,D,E and K into the body. It is known for ages to support a healthy immunity and comes loaded with many health benefits. Yoga works up each and every aspect of our physical body and mind, responsible for a robust immunity. It refines the functioning of the lymph nodes that help expel waste from the cellular level in the body. Yoga helps calm your mind and nervous system, resetting the system to our real nature which is peace and inner strength. Yogic practices do not let aama accumulate in the body that weaken the immunity and make the body a fertile ground for diseases and illnesses to flourish. Here are a few yoga poses you can choose to practice to work up a sluggish immune system. Like we said earlier, stress is the number one enemy of our immune system, as chronic stress means an overactive sympathetic nervous, that keeps the body constantly in the fight or flight mode, in which state, the vitals of our body are tense and rising. When stress persists, it starts to break down and weaken the immune response. This can further make it difficult for the body to respond to viruses and other foreign pathogens. An effective antidote to stress, recommended by the WHO to stay healthy, is meditation. If you are a beginner, you can start off with simple short guided meditations. Make sure you sit for meditation on an empty stomach and not after having downed a heavy meal. Or you can practice yoga nidra meditation , which is a meditation in restful awareness that gives you deep rest and relaxes your body in just 20 minutes. This content on the Sri Sri Tattva blog is not intended to be a substitute for professional medical advice, diagnosis or treatment. Always seek the advice of your physician, or other qualified health providers with any questions you may have regarding a medical condition. Any links to third party websites is provided as a convenience only and the Sri Sri Tattva Blog is not responsible for their content. New customer? Create your account Lost password? Your cart is empty. Personal Care Oral Care Face Care Skin care Hair Care Cleansing Bars. Natural Foods Ojasvita with 7 Herbs Chyawanprash Karela Jamun Juice Amla Candy Chocolates. Speciality Products Gift Cards Incense Sticks g Incense Sticks 20g Incense Cones Dhoop Sticks. Food · Digestible and well cooked meals Go for easy to digest but cooked hot meals and avoid fried, cold or sweet foods. Abhyanga or self-massage According to Ayurveda, a common reason for low immunity is the buildup of toxins in our body in the form of aama. Ghee or clarified butter Clarified butter is now popular enough in the west for the healthy fat that it is, as more research shows its myriad benefits in improving digestion, eyesight, detoxifying the body and building resilience. Yoga Yoga works up each and every aspect of our physical body and mind, responsible for a robust immunity. Shishuasana Child pose Setu Bandhasana Bridge pose Halasana Plow pose Bhujangasana Cobra pose Dhanurasana Bow pose Matsyasana Fish pose Adho Mukha Svanasana Downward facing dog 5. Meditation Like we said earlier, stress is the number one enemy of our immune system, as chronic stress means an overactive sympathetic nervous, that keeps the body constantly in the fight or flight mode, in which state, the vitals of our body are tense and rising. Tags: Anti-stress , Ayurveda , Boost immunity , Immunity. Previous article Next article. Your email. Follow us. Featured products. Henna Shikakai Ayurvedic Shampoo Best For Oily to Normal Hair 2 reviews. Ayurvedic Consultation. Devavati Plus Ayurveda Supplements with 12 Herbs No reviews. Shatavari Premium Quality Organic Herbs 1 review. Turmeric Plus Black Pepper Premium Quality Organic Herbs 1 review.