Peripheral Immune Cell Composition is Altered in Women Before and After a Hypertension Diagnosis

A novel method for cell deconvolution using DNA methylation in PCA space

BACKGROUND

In this study, we present a novel method for reference-based cell deconvolution using data from DNA methylation arrays. Different from existing methods like IDOL-Ext, which operate on probe-level data, our approach represents features in the principal component analysis (PCA) space for cell type deconvolution.

RESULTS

Our method's accuracy in estimating cell compositions is validated across various public datasets, including blood samples from glioma patients. It demonstrates precision comparable to IDOL-Ext, with R2 values ranging from 0.73 to 0.99 for most cell types, while offering improved discrimination between similar cell types, particularly T cell subtypes in glioma patient samples (R2 0.42-0.75 vs. 0.36-0.66 for IDOL-Ext). However, both methods showed lower accuracy for certain cell types, such as memory CD8 T cells in glioma patients (R2 0.42 vs. 0.36 for IDOL-Ext), highlighting the challenges in distinguishing closely related cell populations. We have made this method available as an R package "BloodCellDecon" on GitHub.

CONCLUSIONS

Our study confirms the efficacy of cell type deconvolution in PCA space. The results indicate wide-ranging applicability and potential for adaptation to other forms of genomic data.

methscore: a comprehensive R function for DNA methylation-based health predictors

MOTIVATION

DNA methylation-based predictors of various biological metrics have been widely published and are becoming valuable tools in epidemiologic studies of epigenetics and personalized medicine. However, generating these predictors from original source software and web servers is complex and time consuming. Furthermore, different predictors were often derived based on data from different types of arrays, where array differences and batch effects can make predictors difficult to compare across studies.

RESULTS

We integrate these published methods into a single R function to produce 158 previously published predictors for chronological age, biological age, exposures, lifestyle traits and serum protein levels using both classical and principal component-based methods. To mitigate batch and array differences, we also provide a modified RCP method (ref-RCP) that normalize input DNA methylation data to reference data prior to estimation. Evaluations in real datasets show that this approach improves estimate precision and comparability across studies.

AVAILABILITY AND IMPLEMENTATION

The function was included in software package ENmix, and is freely available from Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html).

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.

Circulating Leukocyte Subsets Before and After a Breast Cancer Diagnosis and Therapy

Importance

Changes in leukocyte composition often precede chronic disease onset. Patients with a history of breast cancer (hereinafter referred to as breast cancer survivors) are at increased risk for subsequent chronic diseases, but the long-term changes in peripheral leukocyte composition following a breast cancer diagnosis and treatment remain unknown.

Objective

To examine longitudinal changes in peripheral leukocyte composition in women who did and did not develop breast cancer and identify whether differences in breast cancer survivors were associated with specific treatments.

Design, Setting, and Participants

In this prospective cohort study, paired blood samples were collected from 2315 women enrolled in The Sister Study, a US-nationwide prospective cohort study of 50 884 women, at baseline (July 2003 to March 2009) and follow-up (October 2013 to March 2015) home visits, with a mean (SD) follow-up interval of 7.6 (1.4) years. By design, approximately half of the included women had been diagnosed and treated for breast cancer after enrollment and before the second blood draw. A total of 410 women were included in the present study, including 185 breast cancer survivors and 225 who remained free of breast cancer over a comparable follow-up period. Data were analyzed from April 21 to September 9, 2022.

Exposures

Breast cancer status and, among breast cancer survivors, cancer treatment type (chemotherapy, radiotherapy, endocrine therapy, or surgery).

Main Outcomes and Measures

Blood DNA methylation data were generated in 2019 using a genome-wide methylation screening tool and deconvolved to estimate percentages of 12 circulating leukocyte subsets.

Results

Of the 410 women included in the analysis, the mean (SD) age at enrollment was 56 (9) years. Compared with breast cancer-free women, breast cancer survivors had decreased percentages of circulating eosinophils (-0.45% [95% CI, -0.87% to -0.03%]; P = .03), total CD4+ helper T cells (-1.50% [95% CI, -2.56% to -0.44%]; P = .01), and memory B cells (-0.22% [95% CI, -0.34% to -0.09%]; P = .001) and increased percentages of circulating naive B cells (0.46% [95% CI, 0.17%-0.75%]; P = .002). In breast cancer survivor-only analyses, radiotherapy was associated with decreases in total CD4+ T cell levels, whereas chemotherapy was associated with increases in naive B cell levels. Surgery and endocrine therapy were not meaningfully associated with leukocyte changes.

Conclusions and Relevance

In this cohort study of 410 women, breast cancer survivors experienced lasting changes in peripheral leukocyte composition compared with women who remained free of breast cancer. These changes may be related to treatment with chemotherapy or radiotherapy and could influence future chronic disease risk.

Methylation-Based Biological Age and Hypertension Prevalence and Incidence

BACKGROUND

Hypertension is common in older individuals and is a major risk factor for cardiovascular disease. Blood DNA methylation profiles have been used to derive metrics of biological age that capture age-related physiological change, disease risk, and mortality. The relationships between hypertension and DNA methylation-based biological age metrics have yet to be carefully described.

METHODS

Among 4419 women enrolled in the prospective Sister Study cohort, DNA methylation data generated from whole blood samples collected at baseline were used to calculate 3 biological age metrics (PhenoAgeAccel, GrimAgeAccel, DunedinPACE). Women were classified as hypertensive at baseline if they had high blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg) or reported current use of antihypertensive medication. New incident cases of hypertension during follow-up were identified via self-report on annual health questionnaires.

RESULTS

All 3 DNA methylation metrics of biological age were positively associated with prevalent hypertension at baseline (per 1-SD increase; PhenoAgeAccel, adjusted odds ratio, 1.16 [95% CI, 1.05-1.28]; GrimAgeAccel, adjusted odds ratio, 1.28 [95% CI, 1.14-1.45]; DunedinPACE, adjusted odds ratio, 1.16 [95% CI, 1.03-1.30]). Among 2610 women who were normotensive at baseline, women with higher biological age were more likely to be diagnosed with incident hypertension (per 1-SD increase; PhenoAgeAccel, adjusted hazard ratio, 1.09 [95% CI, 0.97-1.23]; GrimAgeAccel, adjusted hazard ratio, 1.16 [95% CI, 0.99-1.36]; DunedinPACE, adjusted hazard ratio, 1.16 [95% CI, 1.01-1.33]).

CONCLUSIONS

Methylation-based biological age metrics increase before a hypertension diagnosis and appear to remain elevated in the years after clinical diagnosis and treatment.

Androgen-Induced Cardiovascular Risk in Polycystic Ovary Syndrome: The Role of T Lymphocytes

An estimated 15-20% of reproductive-age women are affected by polycystic ovary syndrome (PCOS). PCOS is associated with substantial metabolic and cardiovascular long-term consequences. In young women with PCOS, several cardiovascular risk factors may be found, including chronic inflammation, high blood pressure, and elevated leukocytes. These women are at an increased risk of cardiovascular diseases (CVD), not only during the reproductive years, but also with aging and menopause; therefore, the early prevention and treatment of future cardiovascular adverse effects are necessary. The fundamental characteristic of PCOS is hyperandrogenemia, which is associated with increased pro-inflammatory cytokines and T lymphocytes. Whether these factors play a role in the pathophysiology of hypertension, a risk factor of CVD, due to PCOS is not well established. This review will briefly discuss how a modest increase in androgens in females is linked to the development of hypertension through pro-inflammatory cytokines and T lymphocyte subsets and the promotion of renal injury. Moreover, it reveals a few existing research gaps in this area, including the lack of specific therapy directed at androgen-induced inflammation and immune activation, thus emphasizing the necessity to explore the systemic inflammation in women with PCOS to halt the inevitable inflammatory process targeting the underlying abnormalities of CVD.