DNA methylation biomarker selected by an ensemble machine learning approach predicts mortality risk in an HIV-positive veteran population

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

A multi-trait epigenome-wide association study identified DNA methylation signature of inflammation among people with HIV

Inflammation underlies many conditions causing excess morbidity and mortality among people with HIV (PWH). A handful of single-trait epigenome-wide association studies (EWAS) have suggested that inflammation is associated with DNA methylation (DNAm) among PWH. Multi-trait EWAS may further improve statistical power and reveal pathways in common between different inflammatory markers. We conducted single-trait EWAS of three inflammatory markers (soluble CD14, D-dimers, and interleukin 6) in the Veteran Aging Cohort Study (n = 920). The study population was all male PWH with an average age of 51 years, and 82.3% self-reported as Black. We then applied two multi-trait EWAS methods-CPASSOC and OmniTest-to combine single-trait EWAS results. CPASSOC and OmniTest identified 189 and 157 inflammation-associated DNAm sites respectively, of which 112 overlapped. Among the identified sites, 56% were not significant in any single-trait EWAS. Top sites were mapped to inflammation-related genes including IFITM1, PARP9 and STAT1. These genes were significantly enriched in pathways such as "type I interferon signaling" and "immune response to virus". We demonstrate that multi-trait EWAS can improve the discovery of inflammation-associated DNAm sites, genes, and pathways. These DNAm sites suggest molecular mechanisms in response to inflammation associated with HIV and might hold the key to addressing persistent inflammation in PWH.

Effects of highly active antiretroviral therapy initiation on epigenomic DNA methylation in persons living with HIV

Introduction: Highly active antiretroviral therapy (HAART) helps improve some measures of accelerated epigenetic aging in persons living with HIV (PLWH), but its overall impact on the epigenome is not fully understood. Methods: In this study, we analyzed the DNA methylation profiles of PLWH (n = 187) shortly before and approximately 2-3 years after they started HAART, as well as matched seronegative (SN) controls (n = 187), taken at two time intervals. Our aim was to identify specific CpGs and biologic pathways associated with HIV infection and initiation of HAART. Additionally, we attempted to identify epigenetic changes associated with HAART initiation that were independent of HIV-associated changes, using matched HIV seronegative (SN) controls (matched on age, hepatitis C status, and interval between visits) to identify CpGs that did not differ between PLWH and SN pre-HAART but were significantly associated with HAART initiation while being unrelated to HIV viral load. Epigenome-wide association studies (EWAS) on >850,000 CpG sites were performed using pre- and post-HAART samples from PLWH. The results were then annotated using the Genomic Regions Enrichment of Annotations Tool (GREAT). Results: When only pre- and post-HAART visits in PLWH were compared, gene ontologies related to immune function and diseases related to immune function were significant, though with less significance for PLWH with detectable HIV viral loads (>50 copies/mL) at the post-HAART visit. To specifically elucidate the effects of HAART separately from HIV-induced methylation changes, we performed EWAS of HAART while also controlling for HIV viral load, and found gene ontologies associated with transplant rejection, transplant-related diseases, and other immunologic signatures. Additionally, we performed a more focused analysis that examined CpGs reaching genome-wide significance (p < 1 × 10-7) from the viral load-controlled EWAS that did not differ between all PLWH and matched SN controls pre-HAART. These CpGs were found to be near genes that play a role in retroviral drug metabolism, diffuse large B cell lymphoma proliferation, and gastric cancer metastasis. Discussion: Overall, this study provides insight into potential biological functions associated with DNA methylation changes induced by HAART initiation in persons living with HIV.

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis

BACKGROUND

Early prediction of mortality in individuals with HIV (PWH) has perpetually posed a formidable challenge. With the widespread integration of machine learning into clinical practice, some researchers endeavor to formulate models predicting the mortality risk for PWH. Nevertheless, the diverse timeframes of mortality among PWH and the potential multitude of modeling variables have cast doubt on the efficacy of the current predictive model for HIV-related deaths. To address this, we undertook a systematic review and meta-analysis, aiming to comprehensively assess the utilization of machine learning in the early prediction of HIV-related deaths and furnish evidence-based support for the advancement of artificial intelligence in this domain.

METHODS

We systematically combed through the PubMed, Cochrane, Embase, and Web of Science databases on November 25, 2023. To evaluate the bias risk in the original studies included, we employed the Predictive Model Bias Risk Assessment Tool (PROBAST). During the meta-analysis, we conducted subgroup analysis based on survival and non-survival models. Additionally, we utilized meta-regression to explore the influence of death time on the predictive value of the model for HIV-related deaths.

RESULTS

After our comprehensive review, we analyzed a total of 24 pieces of literature, encompassing data from 401,389 individuals diagnosed with HIV. Within this dataset, 23 articles specifically delved into deaths during long-term follow-ups outside hospital settings. The machine learning models applied for predicting these deaths comprised survival models (COX regression) and other non-survival models. The outcomes of the meta-analysis unveiled that within the training set, the c-index for predicting deaths among people with HIV (PWH) using predictive models stands at 0.83 (95% CI: 0.75-0.91). In the validation set, the c-index is slightly lower at 0.81 (95% CI: 0.78-0.85). Notably, the meta-regression analysis demonstrated that neither follow-up time nor the occurrence of death events significantly impacted the performance of the machine learning models.

CONCLUSIONS

The study suggests that machine learning is a viable approach for developing non-time-based predictions regarding HIV deaths. Nevertheless, the limited inclusion of original studies necessitates additional multicenter studies for thorough validation.

Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts

BACKGROUND

Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes.

METHODS

Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis.

RESULTS

The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells: NLRC5, CX3CR1, B cells: IFI44L, NK cells: IL12R, monocytes: IRF7), and in oncogenesis (e.g. CD4+ T-cells: BCL family, PRDM16, monocytes: PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways.

CONCLUSION

Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.

Decrypting biological hallmarks of aging in people with HIV

PURPOSE OF REVIEW

HIV infection adds further complexity to the heterogenous process of aging. In this focused review, we examine and discuss recent advances to better elucidate mechanisms of biological aging perturbed and accelerated in the context of HIV, particularly among those with viral suppression through the benefits of antiretroviral therapy (ART). New hypotheses from these studies are poised to provide an improved understanding of multifaceted pathways that converge and likely form the basis for effective interventions toward successful aging.

RECENT FINDINGS

Evidence to date suggests multiple mechanisms of biological aging impact people living with HIV (PLWH). Recent literature delves and expands on how epigenetic alterations, telomere attrition, mitochondrial perturbations, and intercellular communications may underpin accelerated or accentuated aging phenotypes and the disproportionate prevalence of age-related complications among PLWH. Although most hallmarks of aging are likely exacerbated in the setting of HIV, ongoing research efforts are providing new insight on the collective impact these conserved pathways may have in the aging disease processes.

SUMMARY

New knowledge on underlying molecular disease mechanisms impacting people aging with HIV are reviewed. Also examined are studies that may facilitate the development and implementation of effective therapeutics and guidance on improving geriatric HIV clinical care.

Epigenome-Wide Meta-Analysis Reveals Differential DNA Methylation Associated With Estimated Glomerular Filtration Rate Among African American Men With HIV

Introduction

People with HIV (PWH) of African ancestry have faster decline of kidney function and faster progression to end-stage renal disease than PWH of European ancestry. DNA methylation have been associated with kidney function in the general population, however, their relationships are unclear for PWH of African ancestry.

Methods

We performed epigenome-wide association studies (EWAS) of estimated glomerular filtration rate (eGFR) among PWH of African ancestry in 2 subsets of the Veterans Aging Cohort Study cohort (N = 885), followed by a meta-analysis to combine the results. Replication was conducted among independent African American samples without HIV.

Results

DNA methylation sites cg17944885 near Zinc Finger Family Member 788 (ZNF788) and Zinc Finger Protein 20 (ZNF20), and cg06930757 in SHANK1 were significantly associated with eGFR among PWH of African ancestry (false discovery rate < 0.05). DNA methylation site cg17944885 was also associated with eGFR among different populations including African Americans without HIV.

Conclusions

Our study attempted to address an important gap in the literature and to understand the role of DNA methylation in renal diseases in PWH of African ancestry. Replication of cg17944885 among different populations suggests there may be a common pathway for renal diseases progression among PWH and people without HIV, and across different ancestral groups. Our results suggest that genes ZNF788/ZNF20 and SHANK1 could be involved in a pathway linking DNA methylation to renal diseases among PWH and are worth further investigation.

Cell-type specific EWAS identifies genes involved in HIV pathogenesis and oncogenesis among people with HIV infection

Epigenome-wide association studies (EWAS) of heterogenous blood cells have identified CpG sites associated with chronic HIV infection, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. Applying a computational deconvolution method validated by capture bisulfite DNA methylation sequencing, we conducted a cell type-based EWAS and identified differentially methylated CpG sites specific for chronic HIV infection among five immune cell types in blood: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes in two independent cohorts (N total =1,134). Differentially methylated CpG sites for HIV-infection were highly concordant between the two cohorts. Cell-type level meta-EWAS revealed distinct patterns of HIV-associated differential CpG methylation, where 67% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of HIV-associated CpG sites (N=1,472) compared to any other cell type. Genes harboring statistically significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CX3CR1 in CD4+ T-cells, CCR7 in B cells, IL12R in NK cells, LCK in monocytes). More importantly, HIV-associated CpG sites were overrepresented for hallmark genes involved in cancer pathology ( FDR <0.05) (e.g. BCL family, PRDM16, PDCD1LGD, ESR1, DNMT3A, NOTCH2 ). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis such as Kras-signaling, interferon-α and -γ, TNF-α, inflammatory, and apoptotic pathways. Our findings are novel, uncovering cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding pathogen-induced epigenetic oncogenicity, specifically on HIV and its comorbidity with cancers.

Epigenetic Age Acceleration Markers Are Associated With Physiologic Frailty and All-Cause Mortality in People With Human Immunodeficiency Virus

BACKGROUND

Biomarkers that provide insight into drivers of aging are needed for people with human immunodeficiency virus (PWH). The study objective was to determine if epigenetic age acceleration (EAA) markers are associated with physiologic frailty measured by the Veterans Aging Cohort Study (VACS) Index and predict all-cause mortality for PWH.

METHODS

Epigenome-wide DNA methylation was profiled in VACS total white blood cell samples collected during 2005-2007 from 531 PWH to generate 6 established markers of EAA. The association of each EAA marker was tested with VACS Index 2.0. All-cause mortality was assessed over 10 years. For each EAA marker, the hazard ratio per increased year was determined using Cox regression. To evaluate mortality discrimination, C-statistics were derived.

RESULTS

Participants were mostly men (98.5%) and non-Hispanic Black (84.4%), with a mean age of 52.4 years (standard deviation [SD], 7.8 years). Mean VACS Index score was 59.3 (SD, 16.4) and 136 deaths occurred over a median follow-up of 8.7 years. Grim age acceleration (AA), PhenoAA, HannumAA, and extrinsic epigenetic AA were associated with the VACS Index and mortality. HorvathAA and intrinsic epigenetic AA were not associated with either outcome. GrimAA had the greatest mortality discrimination among EAA markers and predicted mortality independently of the VACS Index. One-year increase in GrimAA was associated with a 1-point increase in VACS Index and a 10% increased hazard for mortality.

CONCLUSIONS

The observed associations between EAA markers with physiologic frailty and mortality support future research to provide mechanistic insight into the accelerated aging process and inform interventions tailored to PWH for promoting increased healthspan.

Effect of HIV infection and antiretroviral therapy initiation on genome-wide DNA methylation patterns

BACKGROUND

Previous epigenome-wide association studies have shown that HIV infection can disrupt the host DNA methylation landscape. However, it remains unclear how antiretroviral therapy (ART) affects the HIV-induced epigenetic modifications.

METHODS

184 individuals with HIV from the NEAT001/ANRS143 clinical trial (with pre-ART and post-ART samples [96 weeks of follow-up]) and 44 age-and-sex matched individuals without HIV were included. We compared genome-wide DNA methylation profiles in whole blood between groups adjusting for age, sex, batch effects, and DNA methylation-based estimates of leucocyte composition.

FINDINGS

We identified 430 differentially methylated positions (DMPs) between HIV+ pre-ART individuals and HIV-uninfected controls. In participants with HIV, ART initiation modified the DNA methylation levels at 845 CpG positions and restored 49.3% of the changes found between HIV+ pre-ART and HIV-uninfected individuals. We only found 15 DMPs when comparing DNA methylation profiles between HIV+ post-ART individuals and participants without HIV. The Gene Ontology enrichment analysis of DMPs associated with untreated HIV infection revealed an enrichment in biological processes regulating the immune system and antiviral responses. In participants with untreated HIV infection, DNA methylation levels at top HIV-related DMPs were associated with CD4/CD8 ratios and viral loads. Changes in DNA methylation levels after ART initiation were weakly correlated with changes in CD4+ cell counts and the CD4/CD8 ratio.

INTERPRETATION

Control of HIV viraemia after 96 weeks of ART initiation partly restores the host DNA methylation changes that occurred before antiretroviral treatment of HIV infection.

FUNDING

NEAT-ID Foundation and Instituto de Salud Carlos III, co-funded by European Union.

Blood DNA methylation marks discriminate Chagas cardiomyopathy disease clinical forms

Chagas disease is a parasitic disease from South America, affecting around 7 million people worldwide. Decades after the infection, 30% of people develop chronic forms, including Chronic Chagas Cardiomyopathy (CCC), for which no treatment exists. Two stages characterized this form: the moderate form, characterized by a heart ejection fraction (EF) ≥ 0.4, and the severe form, associated to an EF < 0.4. We propose two sets of DNA methylation biomarkers which can predict in blood CCC occurrence, and CCC stage. This analysis, based on machine learning algorithms, makes predictions with more than 95% accuracy in a test cohort. Beyond their predictive capacity, these CpGs are located near genes involved in the immune response, the nervous system, ion transport or ATP synthesis, pathways known to be deregulated in CCCs. Among these genes, some are also differentially expressed in heart tissues. Interestingly, the CpGs of interest are tagged to genes mainly involved in nervous and ionic processes. Given the close link between methylation and gene expression, these lists of CpGs promise to be not only good biomarkers, but also good indicators of key elements in the development of this pathology.

Ageing with HIV: Challenges and biomarkers

The antiretroviral treatment (ART) developed to control HIV infection led to a revolution in the prognosis of people living with HIV (PLWH). PLWH underwent from suffering severe disease and often fatal complications at young ages to having a chronic condition and a life expectancy close to the general population. Nevertheless, chronic age-related diseases increase as PLWH age. The harmful effect of HIV infection on the individual's immune system adds to its deterioration during ageing, exacerbating comorbidities. In addition, PLWH are more exposed to risk factors affecting ageing, such as coinfections or harmful lifestyles. The ART initiation reverses the biological ageing process but only partially, and additionally can have some toxicities that influence ageing. Observational studies suggest premature ageing in PLWH. Therefore, there is considerable interest in the early prediction of unhealthy ageing through validated biomarkers, easy to implement in HIV-clinical settings. The most promising biomarkers are second-generation epigenetic clocks and integrative algorithms.

Epigenome-wide epidemiologic studies of human immunodeficiency virus infection, treatment, and disease progression

Despite significant advances in the treatment and care of people with HIV (PWH), several challenges remain in our understanding of disease pathogenesis to improve patient care. HIV infection can modify the host epigenome and as such can impact disease progression, as well as the molecular processes driving non-AIDS comorbidities in PWH. Epigenetic epidemiologic studies including epigenome-wide association studies (EWAS) offer a unique set of tools to expand our understanding of HIV disease and to identify novel strategies applicable to treatment and diagnosis in this patient population. In this review, we summarize the current state of knowledge from epigenetic epidemiologic studies of PWH, identify the main challenges of this approach, and highlight future directions for the field. Emerging epigenetic epidemiologic studies of PWH can expand our understanding of HIV infection and health outcomes, improve scientific validity through collaboration and replication, and increase the coverage of diverse populations affected by the global HIV pandemic. Through this review, we hope to highlight the potential of EWAS as a tool for HIV research and to engage more investigators to explore its application to important research questions.