New therapies for patients with hematologic malignancies who relapse after allogeneic hematopoietic cell transplantation (allo-HCT) are needed. Interleukin 15 (IL-15) is a cytokine that stimulates ...CD8+ T-cell and natural killer (NK) cell antitumor responses, and we hypothesized this cytokine may augment antileukemia/antilymphoma immunity in vivo. To test this, we performed a first-in-human multicenter phase 1 trial of the IL-15 superagonist complex ALT-803 in patients who relapsed >60 days after allo-HCT. ALT-803 was administered to 33 patients via the IV or subcutaneous (SQ) routes once weekly for 4 doses (dose levels of 1, 3, 6, and 10 μg/kg). ALT-803 was well tolerated, and no dose-limiting toxicities or treatment-emergent graft-versus-host disease requiring systemic therapy was observed in this clinical setting. Adverse events following IV administration included constitutional symptoms temporally related to increased serum IL-6 and interferon-γ. To mitigate these effects, the SQ route was tested. SQ delivery resulted in self-limited injection site rashes infiltrated with lymphocytes without acute constitutional symptoms. Pharmacokinetic analysis revealed prolonged (>96 hour) serum concentrations following SQ, but not IV, injection. ALT-803 stimulated the activation, proliferation, and expansion of NK cells and CD8+ T cells without increasing regulatory T cells. Responses were observed in 19% of evaluable patients, including 1 complete remission lasting 7 months. Thus, ALT-803 is a safe, well-tolerated agent that significantly increased NK and CD8+ T cell numbers and function. This immunostimulatory IL-15 superagonist warrants further investigation to augment antitumor immunity alone and combined with other immunotherapies. This trial was registered at www.clinicaltrials.gov as #NCT01885897.
•Single-agent IL-15/IL-15Rα-Fc (ALT-803) therapy was well tolerated and resulted in clinical responses in patients who relapsed post-HCT.•First-in-human use of ALT-803 promoted NK and CD8+ T-cell expansion and activation in vivo without stimulating regulatory T cells.
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Purpose
The higher prevalence of cognitive impairment/ dementia among cancer survivors is likely multifactorial. Since both exposures to cytomegalovirus (CMV) and inflammation are common among ...elderly cancer survivors, we evaluated their contribution towards dementia.
Methods
Data from 1387 cancer survivors and 7004 participants without cancer in the 2016 wave of the Health and Retirement Study (HRS) was used in this study. Two inflammatory biomarkers, C-reactive protein (CRP) and neutrophil–lymphocyte ratio (NLR), were used to create an inflammation score. We used survey logistic regression adjusted for survey design parameters.
Results
CMV seropositivity was not associated with cognitive impairment among cancer survivors (
p
= 0.2). In addition, inflammation was associated with elevated odds of cognitive impairment (
OR
= 2.2, 95% CI 1.2, 4.2). Cancer survivors who were both CMV seropositive and had increased inflammation had the highest odds of cognitive impairment compared to those who were CMV seronegative and had low inflammation (
OR
= 3.8, 95% CI 1.5, 9.4). The stratified analysis among cancer survivors showed this association was seen only among cancer survivors in whom the cancer was diagnosed within three years of measurement of inflammation score and CMV serostatus (
OR
= 18.5; 95% CI 6.1, 56.1).
Conclusion
The CMV seropositivity and high inflammation was associated with higher cognitive impairment among cancer survivors. The stronger associations seen among cancer survivors diagnosed within the last three years suggest that strategies to reduce CMV activation and inflammation during or immediately after cancer treatment may be important in reducing the prevalence of cognitive impairment/ dementia among cancer survivors.
Summary
Background
Aspirin is associated with decreased risk of colorectal cancer (CRC), potentially by modulating the gut microbiome.
Aims
To evaluate the effect of aspirin on the gut microbiome in ...a double‐blinded, randomised placebo‐controlled pilot trial.
Methods
Healthy volunteers aged 50‐75 received a standard dose of aspirin (325 mg, N = 30) or placebo (N = 20) once daily for 6 weeks and provided stool samples every 3 weeks for 12 weeks. Serial measurements of gut microbial community composition and bacterial abundance were derived from 16S rRNA sequences. Linear discriminant analysis of effect size (LEfSe) was tested for between‐arm differences in bacterial abundance. Mixed‐effect regression with binomial distribution estimated the effect of aspirin use on changes in the relative abundance of individual bacterial taxa via an interaction term (treatment × time).
Results
Over the study period, there were differences in microbial composition in the aspirin vs placebo arm. After treatment, four taxa were differentially abundant across arms: Prevotella, Veillonella, Clostridium XlVa and Clostridium XVIII clusters. Of pre‐specified bacteria associated with CRC (n = 8) or aspirin intake (n = 4) in published studies, interactions were significant for four taxa, suggesting relative increases in Akkermansia, Prevotella and Ruminococcaceae and relative decreases in Parabacteroides, Bacteroides and Dorea in the aspirin vs placebo arm.
Conclusion
Compared to placebo, aspirin intake influenced several microbial taxa (Ruminococcaceae, Clostridium XlVa, Parabacteroides and Dorea) in a direction consistent with a priori hypothesis based on their association with CRC. This suggests that aspirin may influence CRC development through an effect on the gut microbiome. The findings need replication in a larger trial.
Background
Alzheimer’s disease (AD) and AD related dementias (ADRD) are complex multifactorial neurodegenerative diseases. Application of deep learning methods to analyze large scale whole ...genome‐wide SNP data and transcriptomic data may be a powerful approach to utilize early molecular changes for early detection of ADRD and elucidate the biological mechanisms in AD/ADRD.
Method
We harmonized the definition of dementia in the Health and Retirement Study (HRS) and an external study Religious Orders Study/Memory and Aging Project (ROSMAP) using a diagnostic algorithm previously validated in the HRS based on cognitive tests. The cognitive tests included immediate and delayed word recall, and backward counting that measure working memory and episodic memory. We developed an explainable variational autoencoder (E‐VAE) classifier model using genetic variants (genome‐wide SNP data, 5474 SNPs) and RNAseq data (592 differentially expresses genes in ADRD) from 204 study participants (102 participants with dementia and 102 controls) in the HRS to predict dementia. We validated the prediction performance in a test set of the HRS participants (26 participants with dementia and 26 controls), and further assessed the generalizability of the multi‐omics‐based VAE classifier model in the ROSMAP data (12 participants with dementia and 222 controls).
Result
Our results showed a predictive accuracy of 0.73 (95% CI 0.61, 0.85) with an AUC of 0.80 in the HRS validation data and an accuracy of 0.58 (95% CI 0.51, 0.64) with an AUC of 0.66 in the ROSMAP study data. The E‐VAE model outperformed a penalized logistic regression model (Figure in supplementary file). We identified genes that involved in the apoptotic process, neuron and nervous system development were highly weighted in the multi‐omics‐based VAE model and found that genes in ‘Butyrophilin interactions pathway’ were over represented in ADRD (FDR adjusted p <0.05).
Conclusion
This is the first study showing the generalizability of a deep learning prediction model for dementia in an independent dataset using an integrated multi‐omics approach. The more precise and definitive latent variables identified using E‐VAE can help us understand the complex biology in ADRD and characterize the disease status.
Background
Alzheimer’s disease (AD) and AD related dementias (ADRD) are complex heterogeneous diseases with multiple pathogenic mechanisms. Previous experimental studies showed that serum clusterin ...has a significant role in the maturation of dendritic cells (DCs). Studies showed that myeloid DCs (mDCs) in blood were dysregulated in AD and higher levels of serum clusterin related to higher incidence of dementia. We evaluated the association of DCs in peripheral blood and serum clusterin and their interaction with AD/ADRD.
Method
We used data from 3072 participants in the Health and Retirement Study (HRS) who participated in the 2016 Venous Blood Study (VBS), and had flow cytometry, clusterin and cognition assessed. We used generalized survey logit models to evaluate the association between the DCs, clusterin, and dementia after adjusting for age, sex, race, education, comorbidity, body mass index (BMI) and Cytomegalovirus (CMV) seroprevalence. Utilizing the RNAseq data, we performed differential gene expression (DGE) analysis on DCs, clusterin and dementia to identify overlapping genes in the biological process.
Result
We found that after covariate adjustment, a higher percentage of dendritic cells was associated with lower odds of having dementia (OR = 0.61, 95% CI: 0.44, 0.86; p = 0.005). We found that higher levels of serum clusterin was associated with higher odds of having dementia. This relationship was somewhat attenuated after covariate adjustment (OR = 1.07, 95% CI 0.99, 1.16, p = 0.09). We found a significant interaction between serum clusterin and DCs in the association with dementia (p = 0.02) with those having low DCs and high clusterin being at increased ADRD risk (OR = 1.25) and those with high DCs and low clusterin being at lower ADRD risk (OR = 0.48) as compared to those who have both low DCs and low clusterin. We identified three genes (TUBB4A, WASHC5 and GSTA4) that were dysregulated in the pathways of DCs and clusterin in association with dementia.
Conclusion
This study has shown, for the first time, an interaction between serum clusterin and DCs in peripheral blood that is associated with increased risk of dementia in a large sample of older adults that needs to be validated in future studies.
Though the microbiome’s impact on immune system homeostasis is well documented, the effect of circulating T cells on the gut microbiome remains unexamined. We analyzed data from 50 healthy volunteers ...in a pilot trial of aspirin, using immunophenotyping and 16S rRNA sequencing to evaluate the effect of baseline T cells on microbiome changes over 6 weeks. We employed an unsupervised sparse canonical correlation analysis (sCCA) and used multivariable linear regression models to evaluate the association between selected T cell subsets and selected bacterial genera after adjusting for covariates. In the cross-sectional analysis, percentages of naïve CD4+ T cells were positively associated with a relative abundance of Intestinimonas, and the percentage of activated CD8+ T cells was inversely associated with Cellulosibacter. In the longitudinal analysis, the baseline percentages of naïve CD4+ T cells and activated CD4+ T cells were inversely associated with a 6-week change in the relative abundance of Clostridium_XlVb and Anaerovorax, respectively. The baseline percentage of terminal effector CD4+ T cells was positively associated with the change in Flavonifractor. Notably, the microbiome taxa associated with T cell subsets exclusively belonged to the Bacillota phylum. These findings can guide future experimental studies focusing on the role of T cells in impacting gut microbiome homeostasis.
Abstract
Background
Cellular changes in adaptive immune system accompany the process of aging and contribute to an aging-related immune phenotype (ARIP) characterized by decrease in naïve T-cells (T
...N
) and increase in memory T-cells (T
M
). A population-representative marker of ARIP and its associations with biological aging and age-related chronic conditions have not been studied previously.
Methods
We developed two ARIP indicators based on well understood age-related changes in T cell distribution: T
N
/(T
CM
(Central Memory) + T
EM
(Effector Memory) + T
EFF
(Effector)) (referred as T
N
/T
M
) in CD4 + and CD8 + T-cells. We compared them with existing ARIP measures including CD4/CD8 ratio and CD8 + TN cells by evaluating associations with chronological age and the Klemera Doubal measure of biological age (measured in years) using linear regression, multimorbidity using multinomial logistic regression and two-year mortality using logistic regression.
Results
CD8 + T
N
and CD8 + T
N
/T
M
had the strongest inverse association with chronological age (beta estimates: -3.41 and -3.61 respectively;
p
-value < 0.0001) after adjustment for sex, race/ethnicity and CMV status. CD4 + T
N
/T
M
and CD4 + T
N
had the strongest inverse association with biological age (β = -0.23;
p
= 0.003 and β = -0.24;
p
= 0.004 respectively) after adjustment for age, sex, race/ethnicity and CMV serostatus. CD4/CD8 ratio was not associated with chronological age or biological age. CD4 + T
N
/T
M
and CD4 + T
N
was inversely associated with multimorbidity. For CD4 + T
N
/T
M
, people with 2 chronic conditions had an odds ratio of for 0.74 (95%CI: 0.63–0.86
p
= 0.0003) compared to those without any chronic conditions while those with 3 chronic conditions had an odds ratio of 0.75 (95% CI: 0.63–0.90;
p
= 0.003) after adjustment for age, sex, race/ethnicity, CMV serostatus, smoking, and BMI. The results for the CD4 + T
N
subset were very similar to the associations seen with the CD4 + T
N
/T
M
. CD4 + T
N
/T
M
and CD4 + T
N
were both associated with two-year mortality (OR = 0.80 (95% CI: 0.67–0.95;
p
= 0.01) and 0.81 (0.70–0.94;
p
= 0.01), respectively).
Conclusion
CD4 + T
N
/T
M
and CD4 + T
N
had a stronger association with biological age, age-related morbidity and mortality compared to other ARIP measures. Future longitudinal studies are needed to evaluate the utility of the CD4 + subsets in predicting the risk of aging-related outcomes.
Age-related immunosenescence is characterized by changes in immune cell subsets and is associated with mortality. However, since immunosenescence is associated with other concurrent age-related ...changes such as inflammation and multi-organ dysfunction, it is unclear whether the association between age-related immunosenescence and mortality is independent of other concurrent age-related changes. To address these limitations, we evaluated the independent association between immune cell subsets and mortality after adjustment for age-related inflammation and biologic age.
Data for this study was obtained from the 2016 interview of the Health and Retirement Study (N=6802). Cox proportional hazards regression models were used to estimate the association between 25 immune cell subsets (11 T-cell subsets, 4 B-cell subsets, 3 monocyte subsets, 3 natural killer cell subsets, 3 dendritic cell subsets, and neutrophils) and 4-year mortality adjusting for covariates such as the Klemera-Doubal algorithm biological age, chronological age, gender, race/ethnicity, BMI, smoking status, comorbidity index, CMV seropositivity, and inflammatory latent variable comprising C-reactive protein, and 4 cytokines (interleukin-10, interleukin-1 receptor antagonist, interleukin-6, and soluble tumor necrosis factor).
Four hundred and seventy-six participants died during the study period with an overall median follow up time of 2.5 years. After controlling for covariates and adjustment for sample-weights, total T cells HR: 0.86, p=0.004, NK CD56LO cells HR: 0.88, p=0.005, and neutrophils HR: 1.22, p=0.004 were significantly associated with mortality.
These findings support the idea that an aging immune system is associated with short-term mortality independent of age-related inflammation or other age-related measures of physiological dysfunction. If replicated in other external cohorts, these findings could identify novel targets for both monitoring and intervention to reduce the age-related mortality.
Alzheimer's disease (AD) and AD related dementias (ADRD) are complex multifactorial neurodegenerative diseases. The associations between genetic variants obtained from genome wide association studies ...(GWAS) are the most widely available and well documented variants associated with ADRD. Application of deep learning methods to analyze large scale GWAS data may be a powerful approach to elucidate the biological mechanisms in ADRD compared to penalized regression models that may lead to over-fitting.
We developed a deep learning frame work explainable variational autoencoder (E-VAE) classifier model using genotype (GWAS SNPs = 5474) data from 2714 study participants in the Health and Retirement Study (HRS) to classify ADRD. We validated the generalizability of this model among 234 participants in the Religious Orders Study and Memory and Aging Project (ROSMAP). Utilizing a linear decoder approach we have extracted the weights associated with latent features for biological interpretation.
We obtained a predictive accuracy of 0.71 (95 % CI 0.59, 0.84) with an AUC of 0.69 in the HRS test dataset and got an accuracy of 0.62 (95 % CI 0.56, 0.68) with an AUC of 0.63 in the ROSMAP dataset.
This is the first study showing the generalizability of a deep learning prediction model for dementia using genetic variants in an independent cohort. The latent features identified using E-VAE can help us understand the biology of AD/ ADRD and better characterize disease status.
Abstract only
Introduction:
High blood pressure (BP) is a global public health problem that is strongly associated with many aspects of cardiovascular disease. Approximately 90% of hypertension cases ...have unknown cause. Studies of white blood cell gene expression may help to clarify the pathobiology.
Methods:
Gene expression (25 genes) was assayed in CARDIA at the Year 25 Exam (N=3,074 black and white men and women in 4 US cities, examined in 2010-2011, age 42-56 years). Whole blood was collected in PAXgene Blood RNA tubes; mRNA was isolated using the PAXgene Blood RNA kit (Qiagen Inc., Germantown, MD). The nCounter analysis system (Nanostring Inc., Seattle, WA) was used to measure expression of 25 genes related to inflammation and oxidative stress. Gene expression levels were logarithmically (base 2) transformed to approximate a normal distribution, so 1 unit higher represents doubling of the expression. Average cumulative sitting rest BP exposure was calculated (N=2,823) as the time weighted average across ≥5 BP measurements among 9 CARDIA exams with ≥1 measurement in each of Set 1 Years 0, 2, 5, 7; Set 2 Years 10, 15; and Set 3 Years 20, 25, 30. We added 10 mmHg to the systolic BP and 5 mmHg to the diastolic BP at visits in which antihypertensive medications were used. Linear regression estimated associations between dependent variables cumulative systolic and diastolic BP and each of the 25 gene expression levels, adjusting for age, race, sex, clinic, and year 25 body mass index. Hypertension at year 25 was defined as BP >140/90 mmHg or taking antihypertensive medications and pre-hypertension at year 25 was defined as BP between 121-139/81-90 mmHg, not taking antihypertensive medications. Unconditional logistic regression models were used to estimate the cross sectional association between hypertension and gene expression after adjusting for the covariates mentioned above.
Results:
The mean ± standard deviation for cumulative systolic BP was 113±11 mm Hg and for cumulative diastolic BP was 72±8 mmHg. NADH Dehydrogenase Ubiquinone 1 Beta Subcomplex Subunit 3 (
NDUFB3)
, a mitochondrial gene involved in the electron transport chain was significantly associated with both cumulative systolic (β=1.549; p<0.0001) and diastolic BP measures (β=1.281 mmHg/1 log 2 unit of expression; p<0.0001), even after Bonferroni correction. Other genes had weaker signals. Consistent with these observations, hypertension (n=898) at year 25 (OR: 1.737; p<0.001) and pre-hypertension (n=1,127) at year 25 (OR:1.288; p=0.005) were also associated with increased NDUFB3 expression.
Conclusions:
Expression of the NDUFB3 gene, an element of oxidative stress, was associated with BP assessed throughout young adult and middle age and with concurrent hypertension.
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