Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank

Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, we use deep learning to measure bone marrow adiposity in the femoral head, total hip, femoral diaphysis, and spine from MRI scans of approximately 47,000 UK Biobank participants, including over 41,000 white and over 6300 non-white participants. We then establish the heritability and genome-wide significant associations for bone marrow adiposity at each site. Our meta-GWAS in the white population finds 67, 147, 134, and 174 independent significant single nucleotide polymorphisms, which map to 54, 90, 43, and 100 genes for the femoral head, total hip, femoral diaphysis, and spine, respectively. Transcriptome-wide association studies, colocalization analyses, and sex-stratified meta-GWASes in the white participants further resolve functional and sex-specific genes associated with bone marrow adiposity at each site. Finally, we perform a multi-ancestry meta-GWAS to identify genes associated with bone marrow adiposity across the different bone regions and across ancestry groups. Our findings provide insights into BMAT formation and function and provide a basis to study the impact of BMAT on human health and disease.

Causal relationship between iron status and preeclampsia-eclampsia: a Mendelian randomization analysis

BACKGROUND

Preeclampsia/eclampsia is a severe pregnancy-related disorder associated with hypertension and organ damage. While observational studies have suggested a link between maternal iron status and preeclampsia/eclampsia, the causal relationship remains unclear. The aim of this study was to investigate the genetic causality between iron status and preeclampsia/eclampsia using large-scale genome-wide association study (GWAS) summary data and Mendelian randomization (MR) analysis.

METHODS

Summary data for the GWAS on preeclampsia/eclampsia and genetic markers related to iron status were obtained from the FinnGen Consortium and the IEU genetic databases. The "TwoSampleMR" software package in R was employed to test the genetic causality between these markers and preeclampsia/eclampsia. The inverse variance weighted (IVW) method was primarily used for MR analysis. Heterogeneity, horizontal pleiotropy, and potential outliers were evaluated for the MR analysis results.

RESULTS

The random-effects IVW results showed that ferritin (OR = 1.11, 95% CI: .89-1.38, p = .341), serum iron (OR = .90, 95% CI: .75-1.09, p = .275), TIBC (OR = .98, 95% CI: .89-1.07, p = .613), and TSAT (OR = .94, 95% CI: .83-1.07, p = .354) have no genetic causal relationship with preeclampsia/eclampsia. There was no evidence of heterogeneity, horizontal pleiotropy, or possible outliers in our MR analysis (p > .05).

CONCLUSIONS

Our study did not detect a genetic causal relationship between iron status and preeclampsia/eclampsia. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.

Polygenic risk for epigenetic aging and adverse life experiences interact to predict growth in adolescent depression in a racially/ethnically diverse sample

Introduction

Research has yet to examine the interplay between indices of environmental risk and resilience processes and genetic predisposition for epigenetic aging in predicting early adolescent depressive symptoms. In the current study we examine whether adverse life events and parental acceptance moderate polygenic predisposition for GrimAge epigenetic aging in predicting trajectories of depressive symptoms across early adolescence.

Method

Using data from the Adolescent Brain Development Study (ABCD, N = 11,875), we created polygenic scores for GrimAge, and examined whether exposure to adverse life events and parental acceptance moderated the relation between genetic risk and depressive symptom trajectories from age 10/11 to 12/13 using growth mixture modelling. We examined models separately in European American (EA), African American (AA), and Latinx (LX) subgroups of ABCD.

Results

In the EA and AA subgroups, adverse life events moderated polygenic scores for GrimAge such that there was increased likelihood of membership in a higher vs. lower depression trajectory.

Discussion

We extend literature by identifying genetic contributions to epigenetic aging as a depression diathesis in adolescence. Findings also highlight the detrimental role of adverse life events in exacerbating genetic risk for the development of depression in adolescence.

Genetic architecture of epigenetic cortical clock age in brain tissue from older individuals: alterations in CD46 and other loci

The cortical epigenetic clock was developed in brain tissue as a biomarker of brain aging. As one way to identify mechanisms underlying aging, we conducted a GWAS of cortical age. We leveraged postmortem cortex tissue and genotyping array data from 694 participants of the Rush Memory and Aging Project and Religious Orders Study (ROSMAP; 11000,000 SNPs), and meta-analysed ROSMAP with 522 participants of Brains for Dementia Research (5,000,000 overlapping SNPs). We confirmed results using eQTL (cortical bulk and single nucleus gene expression), cortical protein levels (ROSMAP), and phenome-wide association studies (clinical/neuropathologic phenotypes, ROSMAP). In the meta-analysis, the strongest association was rs4244620 (p = 1.29 × 10-7), which also exhibited FDR-significant cis-eQTL effects for CD46 in bulk and single nucleus (microglia, astrocyte, oligodendrocyte, neuron) cortical gene expression. Additionally, rs4244620 was nominally associated with lower cognition, faster slopes of cognitive decline, and greater Parkinsonian signs (n ~ 1700 ROSMAP with SNP/phenotypic data; all p ≤ 0.04). In ROSMAP alone, the top SNP was rs4721030 (p = 8.64 × 10-8) annotated to TMEM106B and THSD7A. Further, in ROSMAP (n = 849), TMEM106B and THSD7A protein levels in cortex were related to many phenotypes, including greater AD pathology and lower cognition (all p ≤ 0.0007). Overall, we identified converging evidence of CD46 and possibly TMEM106B/THSD7A for potential roles in cortical epigenetic clock age.

The causal impact of gut microbiota on circulating adipokine concentrations: a two-sample Mendelian randomization study

PURPOSE

Evidence from previous experimental and observational research demonstrates that the gut microbiota is related to circulating adipokine concentrations. Nevertheless, the debate as to whether gut microbiome composition causally influences circulating adipokine concentrations remains unresolved. This study aimed to take an essential step in elucidating this issue.

METHODS

We used two-sample Mendelian randomization (MR) to causally analyze genetic variation statistics for gut microbiota and four adipokines (including adiponectin, leptin, soluble leptin receptor [sOB-R], and plasminogen activator inhibitor-1 [PAI-1]) from large-scale genome-wide association studies (GWAS) datasets. A range of sensitivity analyses was also conducted to assess the stability and reliability of the results.

RESULTS

The composite results of the MR and sensitivity analyses revealed 22 significant causal associations. In particular, there is a suggestive causality between the family Clostridiaceae1 (IVW: β = 0.063, P = 0.034), the genus Butyrivibrio (IVW: β = 0.029, P = 0.031), and the family Alcaligenaceae (IVW: β=-0.070, P = 0.014) and adiponectin. Stronger causal effects with leptin were found for the genus Enterorhabdus (IVW: β=-0.073, P = 0.038) and the genus Lachnospiraceae (NK4A136 group) (IVW: β=-0.076, P = 0.01). Eight candidate bacterial groups were found to be associated with sOB-R, with the phylum Firmicutes (IVW: β = 0.235, P = 0.03) and the order Clostridiales (IVW: β = 0.267, P = 0.028) being of more interest. In addition, the genus Roseburia (IVW: β = 0.953, P = 0.022) and the order Lactobacillales (IVW: β=-0.806, P = 0.042) were suggestive of an association with PAI-1.

CONCLUSION

This study reveals a causal relationship between the gut microbiota and circulating adipokines and may help to offer novel insights into the prevention of abnormal concentrations of circulating adipokines and obesity-related diseases.

Gut microbiota and epigenetic age acceleration: a bi-directional Mendelian randomization study

BACKGROUND

The gut microbiota is closely related to aging, but the genetic relationship between gut microbiota and aging has not been well investigated. The aim of the study was to explore the association of microbiota with epigenetic age acceleration (EAA) using the Mendelian randomization.

METHOD

The independent genetic instruments of gut microbiota were obtained from MiBioGen consortium and the Dutch Microbiome Project. EAA data were derived from genome-wide association study. To assess the causal relationship between gut microbiota and EAA, we applied four different methods of Mendelian Randomization (MR) analysis: the inverse variance weighted method (IVW), the MR-Egger regression, the weighted median analysis (WMA), and the weighted mode. Furthermore, sensitivity analyses were conducted to evaluate heterogeneity and horizontal pleiotropy.

RESULTS

We identified potential causal associations between 12 bacterial taxa and EAA (PIVW and PWMA < 0.05). Among them, species Holdemania_unclassified (OR: 1.31, 95% CI: 1.13-1.52, P = 0.0004) retained a strong positive association with GrimAge acceleration. Family Acidaminococcaceae (OR: 0.64, 95% CI: 0.44-0.93, P = 0.019) and family Clostridiaceae1 (OR: 0.69, 95% CI: 0.49-0.97 P = 0.031) were negative association with GrimAge acceleration. Reverse MR analyses indicated that EAA was associated with 6 bacterial taxa in IVW and WMA. Among them, a strong inverse association was found between Phenoage acceleration and genus Turicibacter (OR: 0.928, 95%CI: 0.888-0.971, PIVW and PWMA < 0.001).

CONCLUSION

Our study implicates the potential causal effects of specific microbiota on EAA, potentially providing novel insights into the prevention aging through specific gut microbiota.

Causal association between epigenetic age acceleration and two pulmonary vascular diseases: pulmonary arterial hypertension and pulmonary embolism-a bidirectional Mendelian study

BACKGROUND

Pulmonary arterial hypertension (PAH) is a relatively rare but severe disease with a poor prognosis. Pulmonary embolism (PE) is a serious condition that can cause sudden death. Epigenetic age acceleration (EAA) is a robust indicator derived from the DNA methylation-based epigenetic clock, which can predict the extent of aging. It has been proved that the epigenetic clock and EAA are associated with many cardiovascular diseases, while their associations with PAH and PE remain inconclusive. Our study aims to investigate the associations among these factors.

METHOD

By harnessing summary-level data from large-scale genome-wide association studies (GWAS), we designed a two-sample bidirectional Mendelian randomization (MR) analysis to assess the causal associations between measures of three epigenetic clocks, including GrimAge acceleration (n = 34,467), Hannum Age acceleration (n = 34,449) and PhenoAge acceleration (n = 34,463) and PAH (including 125 cases and 162,837 controls), as well as PE (including 3940 cases and 480,658 controls). The inverse variance-weighted (IVW) method was used as the primary method for MR analysis. Other methods, such as MR egger and weighted mode, served as complements to the IVW approach, were also applied in the analyses. Then, the MR pleiotropy test and MR-PRESSO test, which are effective tools for quality control of MR analysis, were subsequently used to ensure the accuracy of the study.

RESULTS

The forward MR analysis indicated that all three epigenetic clocks had no significant effects on PAH or PE. The reverse analysis indicated that the onset and progression of PAH and PE had insignificant effects on three epigenetic clocks. The results of the quality control assessment confirmed that our findings were reliable.

CONCLUSION

Our two-sample bidirectional MR analysis suggested that there is no significant association between epigenetic clocks and these two pulmonary vascular diseases.

Analyzing the causal role of blood cells in aging: a Mendelian randomization study

Blood cells are crucial components of the human body, closely linked to the aging process. This study aims to explore the causal relationship between 91 blood cell phenotypes and aging through Mendelian randomization (MR) analysis. Exposure data from genome-wide association studies (GWAS) was extracted from the GWAS of blood cell perturbation phenotypes in 2,600 European individuals. Initial analysis utilized GWAS data related to aging from the GWAS Catalog database GCST90014288, with inverse-variance weighting as the primary method for causal analysis. Sensitivity analyses included Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. For significant associations, replication and meta-analysis were conducted using independent aging GWAS data from GCST90014300. Initial analysis revealed that environmental peroxide-impacted red blood cells and ciprofloxacin-impacted reticulocytes accelerated aging. Additionally, elevated neutrophil levels were found to accelerate aging, while LiCl-impacted neutrophils reduced aging risk. Replication and meta-analysis showed consistent results: ciprofloxacin-impacted reticulocytes and elevated neutrophil levels increased the risk of aging, while LiCl-impacted neutrophils reduced the risk. RBCs showed no significant impact on aging progression. Sensitivity analyses confirmed the robustness and reliability of these positive findings. Our study provides evidence of a causal relationship between three blood cell disturbance phenotypes and human aging.

Epigenetic age acceleration is associated with occupational exposures, sex, and survival in amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is linked to ageing and genetic and environmental risk factors, yet underlying mechanisms are incompletely understood. We aimed to evaluate epigenetic age acceleration (EAA), i.e., DNA methylation (DNAm) age acceleration, and its association with ALS case status and survival.

METHODS

In this study, we included 428 ALS and 288 control samples collected between 2011 and 2021. We calculated EAA using the GrimAge residual method from ALS and control blood samples and grouped participants with ALS into three ageing groups (fast, normal, slow). We associated EAA with ALS case status and survival, stratified by sex, and correlated it with environmental and biological factors through occupational exposure assessments, immune cell proportions, and transcriptome changes.

FINDINGS

Participants with ALS had higher average EAA by 1.80 ± 0.30 years (p < 0.0001) versus controls. Participants with ALS in the fast ageing group had a hazard ratio of 1.52 (95% confidence interval 1.16-2.00, p = 0.0028) referenced to the normal ageing group. In males, this hazard ratio was 1.55 (95% confidence interval 1.11-2.17, p = 0.010), and EAA was positively correlated with high-risk occupational exposures including particulate matter (adj.p < 0.0001) and metals (adj.p = 0.0087). Also, in male participants with ALS, EAA was positively correlated with neutrophil proportions and was negatively correlated with CD4+ T cell proportions. Pathways dysregulated in participants with ALS with fast ageing included spliceosome, nucleocytoplasmic transport, axon guidance, and interferons.

INTERPRETATION

EAA was associated with ALS case status and, at least in males, with shorter survival after diagnosis. The effect of EAA on ALS was partially explained by occupational exposures and immune cell proportions in a sex-dependent manner. These findings highlight the complex interactions of ageing and exposures in ALS.

FUNDING

NIH, CDC/National ALS Registry, ALS Association, Dr. Randall Whitcomb Fund for ALS Genetics, Peter Clark Fund for ALS Research, Sinai Medical Staff Foundation, Scott L. Pranger ALS Clinic Fund, NeuroNetwork Therapeutic Discovery Fund, NeuroNetwork for Emerging Therapies.

Integrating bulk and single-cell transcriptomics to elucidate the role and potential mechanisms of autophagy in aging tissue

PURPOSE

Autophagy is frequently observed in tissues during the aging process, yet the tissues most strongly correlated with autophagy during aging and the underlying regulatory mechanisms remain inadequately understood. The purpose of this study is to identify the tissues with the highest correlation between autophagy and aging, and to explore the functions and mechanisms of autophagy in the aging tissue microenvironment.

METHODS

Integrated bulk RNA-seq from over 7000 normal tissue samples, single-cell sequencing data from blood samples of different ages, more than 2000 acute myeloid leukemia (AML) bulk RNA-seq, and multiple sets of AML single-cell data. The datasets were analysed using various bioinformatic approaches.

RESULTS

Blood tissue exhibited the highest positive correlation between autophagy and aging among healthy tissues. Single-cell resolution analysis revealed that in aged blood, classical monocytes (C. monocytes) are most closely associated with elevated autophagy levels. Increased autophagy in these monocytes correlated with a higher proportion of C. monocytes, with hypoxia identified as a crucial contributing factor. In AML, a representative myeloid blood disease, enhanced autophagy was accompanied by an increased proportionof C. monocytes. High autophagy levels in monocytes are associated with pro-inflammatory gene upregulation and Reactive Oxygen Species (ROS) accumulation, contributing to tissue aging.

CONCLUSION

This study revealed that autophagy is most strongly correlated with aging in blood tissue. Enhanced autophagy levels in C. monocytes demonstrate a positive correlation with increased secretion of pro-inflammatory factors and elevated production of ROS, which may contribute to a more rapid aging process. This discovery underscores the critical role of autophagy in blood aging and suggests potential therapeutic targets to mitigate aging-related health issues.

Relationship between hearing impairment and dementia and cognitive function: a Mendelian randomization study

BACKGROUND

There is a substantial body of observational research indicating an association between hearing impairment and dementia, yet the causal relationship and underlying mechanisms remain uncertain. This study aims to investigate the causal relationship between hearing impairment and its subtypes with dementia and cognitive function using two-sample Mendelian randomization (MR) analysis.

METHODS

We performed two-sample MR analysis to examine the causal effects of hearing impairment and its subtypes, including conductive and sensorineural hearing loss (CSHL), conductive hearing loss (CHL), sensorineural hearing loss (SHL), and sudden sensorineural hearing loss (SIHL), on six dementia phenotypes (overall dementia, Alzheimer's disease [AD], Lewy body dementia [DLB], frontotemporal dementia [FTD], Parkinson's disease dementia, and vascular dementia) and four cognitive functions. Additionally, multivariable MR (MVMR) analysis was employed to investigate potential mediating mechanisms.

RESULTS

Genetically determined CSHL was associated with an elevated risk of DLB (odds ratio [OR] 1.69; 95% CI 1.08 to 2.63; P = 0.021) and FTD (OR 1.66; 1.04 to 2.67; P = 0.035), but not AD (P = 0.958). Genetic predisposition to CHL was found to link with increased risks of AD (OR 1.07; 1.01 to 1.14; P = 0.031). Genetically determined SHL was causally associated with an elevated risk of semantic dementia (OR 3.81; 1.09 to 13.37; P = 0.037). Genetically predicted CHL and SIHL were both causally associated with lower general cognitive performance (β -0.015 and - 0.043; P = 0.007 and 0.013) and fluid intelligence score (β -0.045 and - 0.095; P = 0.037 and 0.040). In MVMR analysis, the causal relationship between hearing impairment and dementia was mediated by loneliness, depressed mood, and brain cortical volume, particularly the medial temporal lobe, but not by aging or ischemic stroke.

CONCLUSION

Overall, the study provides evidence supporting a causal relationship between hearing impairment and increased risks of different types of dementia (including AD, FTD, and DLB), as well as poorer general cognitive function. These findings underscore the importance of addressing hearing impairment as a modifiable risk factor for dementia.

Association between biological ageing and periodontitis: Evidence from a cross-sectional survey and multi-omics Mendelian randomization analysis

AIM

To investigate the relationship and potential causality between biological ageing and periodontitis.

MATERIALS AND METHODS

We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis.

RESULTS

We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration.

CONCLUSIONS

Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

Probabilistic inference of epigenetic age acceleration from cellular dynamics

The emergence of epigenetic predictors was a pivotal moment in geroscience, propelling the measurement and concept of biological aging into a quantitative era; however, while current epigenetic clocks show strong predictive power, they are data-driven in nature and are not based on the underlying biological mechanisms driving methylation dynamics. We show that predictions of these clocks are susceptible to several confounding non-age-related phenomena that make interpretation of these estimates and associations difficult. To address these limitations, we developed a probabilistic model describing methylation transitions at the cellular level. Our approach reveals two measurable components, acceleration and bias, which directly reflect perturbations of the underlying cellular dynamics. Acceleration is the proportional increase in the speed of methylation transitions across CpG sites, whereas bias corresponds to global changes in methylation levels. Using data from 15,900 participants from the Generation Scotland study, we develop a robust inference framework and show that these are two distinct processes confounding current epigenetic predictors. Our results show improved associations of acceleration and bias with physiological traits known to impact healthy aging, such as smoking and alcohol consumption, respectively. Furthermore, a genome-wide association study of epigenetic age acceleration identified seven genomic loci.

Functional landscape of genome-wide postzygotic somatic mutations between monozygotic twins

Monozygotic (MZ) twins originate from a single fertilized egg, making them genetically identical at the time of conception. However, postzygotic somatic mutations (PZMs) can introduce genetic differences after separation. Although whole-genome sequencing (WGS) sheds light on somatic mutations in cancer genomics, its application in genomic studies of MZ twins remains limited. In this study, we investigate PZMs in 30 healthy MZ twin pairs from the Osaka University Center for Twin Research using WGS (average depth = 23.8) and a robust germline-calling algorithm. We find high genotype concordance rates (exceeding 99%) in MZ twins. We observe an enrichment of PZMs with variant allele frequency around 0.5 in twins with highly concordant genotypes. These PZMs accumulate more frequently in non-coding regions compared with protein-coding regions, which could potentially influence gene expression. No significant association is observed between the number of PZMs and age or sex. Direct sequencing confirms a missense mutation in the ANKRD35 gene among the PZMs. By applying a genome-wide mutational signature pattern technique, we detect an age-related clock-like signature in these early postzygotic somatic mutations in MZ twins. Our study provides insights that contribute to a deeper understanding of genetic variation in MZ twins.

Causal effects of cardiovascular health on five epigenetic clocks

BACKGROUND

This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.

METHODS AND RESULTS

We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population.

CONCLUSIONS

Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.

Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans

Aging can be understood as a consequence of the declining force of natural selection with age. Consistent with this the antagonistic pleiotropic theory of aging suggests that aging results from the trade-offs that promote early growth and reproduction. However, evidence for antagonistic pleiotropy in humans is largely lacking. Using Mendelian Randomization (MR), we demonstrated that later ages of menarche or first childbirth were genetically associated with longer parental lifespan, decreased frailty index, slower epigenetic aging, later menopause, and reduced facial aging. Moreover, later menarche or first childbirth were also genetically associated with a lower risk of several age-related diseases, including late-onset Alzheimer's disease (LOAD), type 2 diabetes, heart disease, essential hypertension, and chronic obstructive pulmonary disease (COPD). We validated the associations between the age of menarche, childbirth, and the number of childbirths with several age-related outcomes in the UK Biobank by conducting regression analysis of nearly 200,000 subjects. Our results demonstrated that menarche before the age 11 and childbirth before 21 significantly accelerated the risk of several diseases, and almost doubled the risk for diabetes, heart failure, and quadrupled the risk of obesity, supporting the antagonistic pleiotropy theory. We identified 128 significant single nucleotide polymorphisms (SNPs) that influenced age-related outcomes, some of which were involved in known longevity pathways, including IGF1, growth hormone, AMPK, and mTOR signaling. Our study also identified higher BMI as a mediating factor in causing the increased risk of certain diseases, such as type 2 diabetes and heart failure, in women with early menarche or early pregnancy, emphasizing the importance of the thrifty gene hypothesis in explaining in part the mechanisms behind antagonistic pleiotropy. Our study highlights the complex relationship between genetic legacies and modern diseases, emphasizing the need for gender-sensitive healthcare strategies that consider the unique connections between female reproductive health and aging.

Causal association of epigenetic age acceleration and risk of subacute thyroiditis: a bidirectional Mendelian randomization study

BACKGROUND

Epigenetic age accelerations (EAAs) are a promising new avenue of research, yet their investigation in subacute thyroiditis (SAT) remains scarce. Our study endeavors to fill this void by exploring the potential causal association between EAAs and SAT.

METHODS

Our study utilized publicly available genome-wide association study (GWAS) data of European ancestry to conduct a bidirectional Mendelian randomization (MR) study. Five MR methods were employed to measure causal association between EAAs and SAT multiple analyses were utilized to perform quality control.

RESULTS

Our study evaluated causal association between SAT and four EAAs, included GrimAge acceleration (GrimAA), Hannum age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), intrinsic epigenetic age acceleration (IEAA). Results showed that there is a significant causal association between PhenoAA and SAT (OR 1.109, 95% CI 1.000-1.228, p = 0.049, by IVW method). On the contrary, SAT was associated with IEAA (OR 0.933, 95% CI 0.884-0.984, p = 0.011, by IVW method; OR 0.938, 95% CI 0.881-0.998, p = 0.043, by weighted median method). Leave-one-out sensitivity analysis, heterogeneity test, pleiotropy test, and MR-PRESSO analysis provide good quality control.

CONCLUSION

The bidirectional MR analysis concluded that an increase in PhenoAA was correlated with a higher risk of SAT, indicating a potential causal relationship between PhenoAA and risk of SAT. Conversely, SAT was found to be closely associated with IEAA, suggesting that SAT may accelerate the aging process. Slowing down biological aging has emerged as a new research direction in curbing SAT.

Preterm birth as a determinant of neurodevelopment and cognition in children (PRENCOG): protocol for an exposure-based cohort study in the UK

INTRODUCTION

Preterm birth (PTB) is strongly associated with encephalopathy of prematurity (EoP) and neurocognitive impairment. The biological axes linking PTB with atypical brain development are uncertain. We aim to elucidate the roles of neuroendocrine stress activation and immune dysregulation in linking PTB with EoP.

METHODS AND ANALYSIS

PRENCOG (PREterm birth as a determinant of Neurodevelopment and COGnition in children: mechanisms and causal evidence) is an exposure-based cohort study at the University of Edinburgh. Three hundred mother-infant dyads comprising 200 preterm births (gestational age, GA <32 weeks, exposed) and 100 term births (GA >37 weeks, non-exposed), will be recruited between January 2023 and December 2027. We will collect parental and infant medical, demographic, socioeconomic characteristics and biological data which include placental tissue, umbilical cord blood, maternal and infant hair, infant saliva, infant dried blood spots, faecal material, and structural and diffusion MRI. Infant biosamples will be collected between birth and 44 weeks GA.EoP will be characterised by MRI using morphometric similarity networks (MSNs), hierarchical complexity (HC) and magnetisation transfer saturation imaging (MTsat). We will conduct: first, multivariable regressions and statistical association assessments to test how PTB-associated risk factors (PTB-RFs) relate to MSNs, HC and or MTsat; second, structural equation modelling to investigate neuroendocrine stress activation and immune dysregulation as mediators of PTB-RFs on features of EoP. PTB-RF selection will be informed by the variables that predict real-world educational outcomes, ascertained by linking the UK National Neonatal Research Database with the National Pupil Database.

ETHICS AND DISSEMINATION

A favourable ethical opinion has been given by the South East Scotland Research Ethics Committee 02 (23/SS/0067) and NHS Lothian Research and Development (2023/0150). Results will be reported to the Medical Research Council, in scientific media, via stakeholder partners and on a website in accessible language (https://www.ed.ac.uk/centre-reproductive-health/prencog).

Comprehensive analysis of molecular, physiological, and functional biomarkers of aging with neurological diseases using Mendelian randomization

An increasing burden of neurological diseases (NDs) has been a public health challenge in an aging society. Age, especially biological age, is the most important risk factor for NDs. Identification of biomarkers of aging to capture NDs might lead to a better understanding of the underlying mechanisms of pathological brain aging and the implementation of effective intervention. We conducted a comprehensive two-sample Mendelian Randomization (MR) study to investigate the association between various biomarkers of aging and three leading causes of NDs: Alzheimer's disease (AD), vascular dementia (VaD), and ischemic stroke. Publicly available GWAS summary statistics on people from European ancestry were obtained for six molecular biomarkers, two physiological biomarkers, and eight functional biomarkers, and three NDs. Genetic variants serving as instrumental variables (IVs) were identified for each biomarker. The MR analysis included inverse variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO. We found that short telomere length and decrease in appendicular lean mass were associated with an increased risk for AD (OR IVW = 1.12 per 1SD decrease, 95% confidence interval 1.02-1.22, and OR IVW = 1.11, 1.06-1.16, respectively), whereas high frailty index showed a protective effect for AD. Accelerated BioAge appeared to be associated with increased risk for ischemic stroke (OR IVW = 1.3 per year in BioAge acceleration, 95% CI 1.19-1.41). Our findings implied a causal association of short telomere length and a decrease in appendicular lean mass with an increased risk for AD, while BioAge appeared to be a good biomarker for ischemic stroke. Further studies are needed to validate these associations and explore underlying mechanisms.

Major Psychiatric Disorders, Substance Use Behaviors, and Longevity

Importance

Observational studies suggest that major psychiatric disorders and substance use behaviors reduce longevity, making it difficult to disentangle their relationships with aging-related outcomes.

Objective

To evaluate the associations between the genetic liabilities for major psychiatric disorders, substance use behaviors (smoking and alcohol consumption), and longevity.

Design, Settings, and Participants

This 2-sample mendelian randomization (MR) study assessed associations between psychiatric disorders, substance use behaviors, and longevity using single-variable and multivariable models. Multiomics analyses were performed elucidating transcriptomic underpinnings of the MR associations and identifying potential proteomic therapeutic targets. This study sourced summary-level genome-wide association study (GWAS) data, gene expression, and proteomic data from cohorts of European ancestry. Analyses were performed from May 2022 to November 2023.

Exposures

Genetic susceptibility for major depression (n = 500 199), bipolar disorder (n = 413 466), schizophrenia (n = 127 906), problematic alcohol use (n = 435 563), weekly alcohol consumption (n = 666 978), and lifetime smoking index (n = 462 690).

Main Outcomes and Measures

The main outcome encompassed aspects of health span, lifespan, and exceptional longevity. Additional outcomes were epigenetic age acceleration (EAA) clocks.

Results

Findings from multivariable MR models simultaneously assessing psychiatric disorders and substance use behaviorsm suggest a negative association between smoking and longevity in cohorts of European ancestry (n = 709 709; 431 503 [60.8%] female; β, -0.33; 95% CI, -0.38 to -0.28; P = 4.59 × 10-34) and with increased EAA (n = 34 449; 18 017 [52.3%] female; eg, PhenoAge: β, 1.76; 95% CI, 0.72 to 2.79; P = 8.83 × 10-4). Transcriptomic imputation and colocalization identified 249 genes associated with smoking, including 36 novel genes not captured by the original smoking GWAS. Enriched pathways included chromatin remodeling and telomere assembly and maintenance. The transcriptome-wide signature of smoking was inversely associated with longevity, and estimates of individual smoking-associated genes, eg, XRCC3 and PRMT6, aligned with the smoking-longevity MR analyses, suggesting underlying transcriptomic mediators. Cis-instrument MR prioritized brain proteins associated with smoking behavior, including LY6H (β, 0.02; 95% CI, 0.01 to 0.03; P = 2.37 × 10-6) and RIT2 (β, 0.02; 95% CI, 0.01 to 0.03; P = 1.05 × 10-5), which had favorable adverse-effect profiles across 367 traits evaluated in phenome-wide MR.

Conclusions

The findings suggest that the genetic liability of smoking, but not of psychiatric disorders, is associated with longevity. Transcriptomic associations offer insights into smoking-related pathways, and identified proteomic targets may inform therapeutic development for smoking cessation strategies.

Differential white blood cell count and epigenetic clocks: a bidirectional Mendelian randomization study

BACKGROUND

Human aging and white blood cell (WBC) count are complex traits influenced by multiple genetic factors. Predictors of chronological age have been developed using epigenetic clocks. However, the bidirectional causal effects between epigenetic clocks and WBC count have not been fully examined.

METHODS

This study employed Mendelian randomization (MR) to analyze summary statistics from four epigenetic clocks involving 34,710 participants, alongside data from the Blood Cell Consortium encompassing 563,946 individuals. We primarily explored bidirectional causal relationships using the random-effects inverse-variance weighted method, supplemented by additional MR methods for comprehensive analysis. Additionally, multivariate MR was applied to investigate independent effects of WBC count on epigenetic age acceleration.

RESULTS

In the two-sample univariate MR (UVMR) analysis, we observed that a decrease in lymphocyte count markedly accelerated aging according to the PhenoAge, GrimAge, and HannumAge metrics (all P < 0.01, β < 0), though it did not affect Intrinsic Epigenetic Age Acceleration (IEAA). Conversely, an increase in neutrophil count significantly elevated PhenoAge levels (β: 0.38; 95% CI 0.14, 0.61; P = 1.65E-03 < 0.01). Reverse MR revealed no significant causal impacts of epigenetic clocks on overall WBC counts. Furthermore, in multivariate MR, the impact of lymphocyte counts on epigenetic aging metrics remained statistically significant. We also identified a marked causal association between neutrophil counts and PhenoAge, GrimAge, and HannumAge, with respective results showing strong associations (PhenoAge β: 0.78; 95% CI 0.47, 1.09; P = 8.26E-07; GrimAge β: 0.55; 95% CI 0.31, 0.79; P = 5.50E-06; HannumAge β: 0.42; 95% CI 0.18, 0.67; P = 6.30E-04). Likewise, eosinophil cell count demonstrated significant association with HannumAge (β: 0.33; 95% CI 0.13, 0.53; P = 1.43E-03 < 0.01).

CONCLUSION

These findings demonstrated that within WBCs, lymphocyte and neutrophil counts exert irreversible and independent causal effects on the acceleration of PhenoAge, GrimAge, and HannumAge. Our findings highlight the critical role of WBCs in influencing epigenetic clocks and underscore the importance of considering immune parameters when interpreting epigenetic age.

Mendelian randomization analysis reveals the combined effects of epigenetics and telomere biology in hematologic cancers

BACKGROUND

Telomere shortening and epigenetic modifications are key factors in aging and hematologic diseases. This study investigates the relationship of telomere length and epigenetic age acceleration (EAA) with hematologic cancers, blood cells, and biochemical markers through the epigenetic clocks.

METHODS

This study primarily utilizes genome-wide association studies of populations of European descent as instrumental variables, exploring the causal relationships between exposures and outcomes through a bidirectional two-sample Mendelian randomization (MR) approach. MR techniques include inverse variance weighted (IVW), MR Egger, and weighted median modes. Heterogeneity and pleiotropy in MR are assessed using Cochran's Q test and the MR Egger intercept, with the robustness of the conclusions further validated by multivariable MR (MVMR).

RESULTS

Our research shows that longer telomere lengths significantly increase the risk of multiple myeloma, leukemia, and lymphoma (OR > 1, P < 0.05) and establish a causal relationship between telomere length and red blood cell indices such as RBC (OR = 1.121, PIVW = 0.034), MCH (OR = 0.801, PIVW = 2.046e-06), MCV (OR = 0.801, PIVW = 0.001), and MCHC (OR = 0.813, PIVW = 0.002). Additionally, MVMR analysis revealed an association between DNA methylation PhenoAge acceleration and alkaline phosphatase (OR = 1.026, PIVW = 0.007).

CONCLUSION

The study clarifies the relationships between telomere length, EAA, and hematological malignancies, further emphasizing the prognostic significance of telomere length and EAA. This deepens our understanding of the pathogenesis of hematological diseases, which can inform risk assessment and therapeutic strategies.

Biological aging mediates the association between periodontitis and cardiovascular disease: results from a national population study and Mendelian randomization analysis

BACKGROUND

The relationship between periodontitis and cardiovascular disease (CVD) has been extensively studied, but the role of biological aging in this relationship remains poorly understood. This study is dedicated to investigating the effect of periodontitis on the incidence of CVD and to elucidating the potential mediating role of biological aging. Furthermore, this study will seek to elucidate the causal association between periodontitis, CVD, and biological aging.

METHODS

We included 3269 participants from the National Health and Nutrition Examination Survey (2009-2014) with diagnostic information on periodontitis and composite CVD events. Biological aging was evaluated by utilizing both the Klemera-Doubal method's calculated biological age (KDMAge) and phenotypic age (PhenoAge). Logistic regression, restricted cubic spline (RCS) analysis, and subgroup analysis were used for data analysis. Mediation analysis was employed to explore the mediating role of biological aging. Subsequently, Mendelian randomization (MR) analyses were performed using genome-wide association study databases to explore potential causal relationships between periodontitis, CVD, and biological aging.

RESULTS

Periodontitis was associated with a higher risk of CVD. Participants with periodontitis were found to have increased levels of biological aging, and elevated levels of biological aging were associated with increased CVD risk. Mediation analyses showed a partial mediating effect of biological aging (PhenoAge: 44.6%; KDMAge: 22.9%) between periodontitis and CVD risk. MR analysis showed that periodontitis played a causal role in increasing the risk of small vessel stroke, while myocardial infarction was found to increase the risk of periodontitis. In addition, reverse MR analysis showed that phenotypic aging can increase the risk of periodontitis, and there is a two-way causal relationship between CVD and biological aging.

CONCLUSIONS

Periodontitis is associated with an increased CVD risk, partially mediated by biological aging, with a complex causal interrelationship. Targeted interventions for periodontal health may slow the biological aging processes and reduce CVD risk.

Exploring the causal association between epigenetic clocks and menopause age: insights from a bidirectional Mendelian randomization study

Background

Evidence suggests a connection between DNA methylation (DNAm) aging and reproductive aging. However, the causal relationship between DNAm and age at menopause remains uncertain.

Methods

Employing established DNAm epigenetic clocks, such as DNAm Hannum age acceleration (Hannum), Intrinsic epigenetic age acceleration (IEAA), DNAm-estimated granulocyte proportions (Gran), DNAm GrimAge acceleration (GrimAgeAccel), DNAm PhenoAge acceleration (PhenoAgeAccel), and DNAm-estimated plasminogen activator inhibitor-1 levels (DNAmPAIadjAge), a bidirectional Mendelian randomization (MR) study was carried out to explore the potential causality between DNAm and menopausal age. The primary analytical method used was the inverse variance weighted (IVW) estimation model, supplemented by various other estimation techniques.

Results

DNAm aging acceleration or deceleration, as indicated by Hannum, IEAA, Gran, GrimAgeAccel, PhenoAgeAccel, and DNAmPAIadjAge, did not exhibit a statistically significant causal effect on menopausal age according to forward MR analysis. However, there was a suggestive positive causal association between age at menopause and Gran (Beta = 0.0010; 95% confidence interval (CI): 0.0004, 0.0020) in reverse MR analysis.

Conclusion

The observed increase in granulocyte DNAm levels in relation to menopausal age could potentially serve as a valuable indicator for evaluating the physiological status at the onset of menopause.

DNA methylation-estimated phenotypes, telomere length and risk of ischemic stroke: epigenetic age acceleration of screening and a Mendelian randomization study

BACKGROUND

Aging is a complex biological process that may be accelerated in certain pathological conditions. DNA methylation age (DNAmAge) has emerged as a biomarker for biological age, which can differ from chronological age. This research peels back the layers of the relationship between fast-forward aging and ischemic stroke, poking and prodding the potential two-way causal influences between stroke and biological aging indicators.

METHODS

We analyzed a cohort of ischemic stroke patients, comparing DNAmAge with chronological age to measure age acceleration. We assessed variations in age acceleration among stroke subtypes and between sexes. Using Mendelian randomization, we examined the causal links between stroke, aging biomarkers like telomere length, and age acceleration's effect on stroke risk.

RESULTS

Our investigation reveals a pronounced association between ischemic stroke and age acceleration, most notably in patients with cardioembolic strokes, who exhibited a striking median difference of 9 years between DNAmAge and chronological age. Furthermore, age acceleration differed significantly across stroke subtypes and was higher in women than in men. In terms of causality, MR analysis indicated a modest negative effect of stroke on telomere length, but no causal effect of age phenotypes on stroke or its subtypes. However, some indication of a potential causal effect of ischemic stroke on PhenoAge acceleration was observed.

CONCLUSION

The study provides insight into the relationship between DNAmAge and ischemic stroke, particularly cardioembolic stroke, and suggests possible gender differences. These insights carry profound clinical significance and set stage for future investigations into the entwined pathways of stroke and accelerated aging.

Mendelian randomization implicates causal association between epigenetic age acceleration and age-related eye diseases or glaucoma endophenotypes

BACKGROUND

Age-related eye diseases (AREDs) have become increasingly prevalent with the aging population, serving as the leading causes of visual impairment worldwide. Epigenetic clocks are generated based on DNA methylation (DNAm) levels and are considered one of the most promising predictors of biological age. This study aimed to investigate the bidirectional causal association between epigenetic clocks and common AREDs or glaucoma endophenotypes.

METHODS

Instrumental variables for epigenetic clocks, AREDs, and glaucoma endophenotypes were obtained from corresponding genome-wide association study data of European descent. Bidirectional two-sample Mendelian randomization (MR) was employed to explore the causal relationship between epigenetic clocks and AREDs or glaucoma endophenotypes. Multivariable MR (MVMR) was used to determine whether glaucoma endophenotypes mediated the association of epigenetic clocks with glaucoma. Multiple sensitivity analyses were conducted to confirm the robustness of MR estimates.

RESULTS

The results showed that an increased intrinsic epigenetic age acceleration (HorvathAge) was significantly associated with an increased risk of primary open-angle glaucoma (OR = 1.04, 95% CI 1.02 to 1.06, P = 6.1E-04). The epigenetic age acceleration (EEA) of HannumAge was related to a decreased risk of primary angle-closure glaucoma (OR = 0.92, 95% CI 0.86 to 0.99, P = 0.035). Reverse MR analysis showed that age-related cataract was linked to decreased HannumAge (β = -0.190 year, 95% CI -0.374 to -0.008, P = 0.041). The EEA of HannumAge (β = -0.85 μm, 95% CI -1.57 to -0.14, P = 0.019) and HorvathAge (β = -0.63 μm, 95% CI -1.18 to -0.08, P = 0.024) were associated with decreased central corneal thickness (CCT). PhenoAge was related to an increased retinal nerve fiber layer thickness (β = 0.06 μm, 95% CI 0.01 to 0.11, P = 0.027). MVMR analysis found no mediation effect of CCT in the association of HannumAge and HorvathAge with glaucoma. DNAm-based granulocyte proportions were significantly associated with presbyopia, rhegmatogenous retinal detachment, and intraocular pressure (P < 0.05). DNAm-based plasminogen activator inhibitor-1 levels were significantly related to age-related macular degeneration and intraocular pressure (P < 0.05).

CONCLUSION

The present study revealed a causal association between epigenetic clocks and AREDs. More research is warranted to clarify the potential mechanisms of the biological aging process in AREDs.

Impact of childhood maltreatment on aging: a comprehensive Mendelian randomization analysis of multiple age-related biomarkers

BACKGROUND

Childhood maltreatment (CM) is linked to long-term adverse health outcomes, including accelerated biological aging and cognitive decline. This study investigates the relationship between CM and various aging biomarkers: telomere length, facial aging, intrinsic epigenetic age acceleration (IEAA), GrimAge, HannumAge, PhenoAge, frailty index, and cognitive performance.

METHODS

We conducted a Mendelian randomization (MR) study using published GWAS summary statistics. Aging biomarkers included telomere length (qPCR), facial aging (subjective evaluation), and epigenetic age markers (HannumAge, IEAA, GrimAge, PhenoAge). The frailty index was calculated from clinical assessments, and cognitive performance was evaluated with standardized tests. Analyses included Inverse-Variance Weighted (IVW), MR Egger, and Weighted Median (WM) methods, adjusted for multiple comparisons.

RESULTS

CM was significantly associated with shorter telomere length (IVW: β = - 0.1, 95% CI - 0.18 to - 0.02, pFDR = 0.032) and increased HannumAge (IVW: β = 1.33, 95% CI 0.36 to 2.3, pFDR = 0.028), GrimAge (IVW: β = 1.19, 95% CI 0.19 to 2.2, pFDR = 0.040), and PhenoAge (IVW: β = 1.4, 95% CI 0.12 to 2.68, pFDR = 0.053). A significant association was also found with the frailty index (IVW: β = 0.31, 95% CI 0.13 to 0.49, pFDR = 0.006). No significant associations were found with facial aging, IEAA, or cognitive performance.

CONCLUSIONS

CM is linked to accelerated biological aging, shown by shorter telomere length and increased epigenetic aging markers. CM was also associated with increased frailty, highlighting the need for early interventions to mitigate long-term effects. Further research should explore mechanisms and prevention strategies.

Identification of a longevity gene through evolutionary rate covariation of insect mito-nuclear genomes

Oxidative phosphorylation, essential for energy metabolism and linked to the regulation of longevity, involves mitochondrial and nuclear genes. The functions of these genes and their evolutionary rate covariation (ERC) have been extensively studied, but little is known about whether other nuclear genes not targeted to mitochondria evolutionarily and functionally interact with mitochondrial genes. Here we systematically examined the ERC of mitochondrial and nuclear benchmarking universal single-copy ortholog (BUSCO) genes from 472 insects, identifying 75 non-mitochondria-targeted nuclear genes. We found that the uncharacterized gene CG11837-a putative ortholog of human DIMT1-regulates insect lifespan, as its knockdown reduces median lifespan in five diverse insect species and Caenorhabditis elegans, whereas its overexpression extends median lifespans in fruit flies and C. elegans and enhances oxidative phosphorylation gene activity. Additionally, DIMT1 overexpression protects human cells from cellular senescence. Together, these data provide insights into the ERC of mito-nuclear genes and suggest that CG11837 may regulate longevity across animals.

Genome-wide association analysis of hypertension and epigenetic aging reveals shared genetic architecture and identifies novel risk loci

Hypertension is a disease associated with epigenetic aging. However, the pathogenic mechanism underlying this relationship remains unclear. We aimed to characterize the shared genetic architecture of hypertension and epigenetic aging, and identify novel risk loci. Leveraging genome-wide association studies (GWAS) summary statistics of hypertension (129,909 cases and 354,689 controls) and four epigenetic clocks (N = 34,710), we investigated genetic architectures and genetic overlap using bivariate casual mixture model and conditional/conjunctional false discovery rate methods. Functional gene-sets pathway analyses were performed by functional mapping and gene annotation (FUMA) protocol. Hypertension was polygenic with 2.8 K trait-influencing genetic variants. We observed cross-trait genetic enrichment and genetic overlap between hypertension and all four measures of epigenetic aging. Further, we identified 32 distinct genomic loci jointly associated with hypertension and epigenetic aging. Notably, rs1849209 was shared between hypertension and three epigenetic clocks (HannumAge, IEAA, and PhenoAge). The shared loci exhibited a combination of concordant and discordant allelic effects. Functional gene-set analyses revealed significant enrichment in biological pathways related to sensory perception of smell and nervous system processes. We observed genetic overlaps with mixed effect directions between hypertension and all four epigenetic aging measures, and identified 32 shared distinct loci with mixed effect directions, 25 of which were novel for hypertension. Shared genes enriched in biological pathways related to olfaction.

The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank

Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.

Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Editorial: Can Improving Youth Mental Health Reduce Mortality?

It is well established that mental health conditions, including substance use disorders, are associated with premature mortality. A meta-analysis1 has demonstrated that this association holds across a range of diagnoses. Although the effect is stronger for schizophrenia, depression and anxiety contribute to more deaths overall because of their high prevalence rates. Moreover, more than two-thirds of associated deaths were explained by natural causes.1 The next logical questions, then, are as follows: which mechanisms underlie this association, and can they can be mitigated? In the current issue of JAACAP, Clark et al.2 aim to tie mental health symptoms and substance use to the acceleration of biological aging.

Causal Relationship between Meat Intake and Biological Aging: Evidence from Mendelian Randomization Analysis

Existing research indicates that different types of meat have varying effects on health and aging, but the specific causal relationships remain unclear. This study aimed to explore the causal relationship between different types of meat intake and aging-related phenotypes. This study employed Mendelian randomization (MR) to select genetic variants associated with meat intake from large genomic databases, ensuring the independence and pleiotropy-free nature of these instrumental variables (IVs), and calculated the F-statistic to evaluate the strength of the IVs. The validity of causal estimates was assessed through sensitivity analyses and various MR methods (MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, and weighted mode), with the MR-Egger regression intercept used to test for pleiotropy bias and Cochran's Q test employed to evaluate the heterogeneity of the results. The findings reveal a positive causal relationship between meat consumers and DNA methylation PhenoAge acceleration, suggesting that increased meat intake may accelerate the biological aging process. Specifically, lamb intake is found to have a positive causal effect on mitochondrial DNA copy number, while processed meat consumption shows a negative causal effect on telomere length. No significant causal relationships were observed for other types of meat intake. This study highlights the significant impact that processing and cooking methods have on meat's role in health and aging, enhancing our understanding of how specific types of meat and their preparation affect the aging process, providing a theoretical basis for dietary strategies aimed at delaying aging and enhancing quality of life.

Effects of walking on epigenetic age acceleration: a Mendelian randomization study

INTRODUCTION

Walking stands as the most prevalent physical activity in the daily lives of individuals and is closely associated with physical functioning and the aging process. Nonetheless, the precise cause-and-effect connection between walking and aging remains unexplored. The epigenetic clock emerges as the most promising biological indicator of aging, capable of mirroring the biological age of the human body and facilitating an investigation into the association between walking and aging. Our primary objective is to investigate the causal impact of walking with epigenetic age acceleration (EAA).

METHODS

We conducted a two-sample two-way Mendelian randomization (MR) study to investigate the causal relationship between walking and EAA. Walking and Leisure sedentary behavior data were sourced from UK Biobank, while EAA data were gathered from a total of 28 cohorts. The MR analysis was carried out using several methods, including the inverse variance weighted (IVW), weighted median, MR-Egger, and robust adjusted profile score (RAPS). To ensure the robustness of our findings, we conducted sensitivity analyses, which involved the MR-Egger intercept test, Cochran's Q test, and MR-PRESSO, to account for and mitigate potential pleiotropy.

RESULTS

The IVW MR results indicate a significant impact of usual walking pace on GrimAge (BETA = - 1.84, 95% CI (- 2.94, - 0.75)), PhenoAge (BETA = - 1.57, 95% CI (- 3.05, - 0.08)), Horvath (BETA = - 1.09 (- 2.14, - 0.04)), and Hannum (BETA = - 1.63, 95% CI (- 2.70, - 0.56)). Usual walking pace is significantly associated with a delay in epigenetic aging acceleration (EAA) (P < 0.05). Moreover, the direction of effect predicted by the gene remained consistent across RAPS outcomes and sensitivity MR analyses. There is a lack of robust causal relationships between other walking conditions, such as walking duration and walking frequency, on EAA (P > 0.05).

CONCLUSION

Our evidence demonstrates that a higher usual walking pace is associated with a deceleration of the acceleration of all four classical epigenetic clocks acceleration.

Causal effects of denture wearing on epigenetic age acceleration and the mediating pathways: a mendelian randomization study

BACKGROUND

The epigenetic-age acceleration (EAA) represents the difference between chronological age and epigenetic age, reflecting accelerated biological aging. Observational studies suggested that oral disorders may impact DNA methylation patterns and aging, but their causal relationship remains largely unexplored. This study aimed to investigate potential causal associations between dental traits and EAA, as well as to identify possible mediators.

METHODS

Using summary statistics of genome-wide association studies of predominantly European ancestry, we conducted univariable and multivariable Mendelian randomization (MR) to estimate the overall and independent effects of ten dental traits (dentures, bleeding gums, painful gums, loose teeth, toothache, ulcers, periodontitis, number of teeth, and two measures of caries) on four EAA subtypes (GrimAge acceleration [GrimAA], PhenoAge acceleration [PhenoAA], HannumAge acceleration [HannumAA] and intrinsic EAA [IEAA]), and used two-step Mendelian randomization to evaluate twelve potential mediators of the associations. Comprehensive sensitivity analyses were used to verity the robustness, heterogeneity, and pleiotropy.

RESULTS

Univariable inverse variance weighted MR analyses revealed a causal effect of dentures on greater GrimAA (β: 2.47, 95% CI: 0.93-4.01, p = 0.002), PhenoAA (β: 3.00, 95% CI: 1.15-4.85, p = 0.001), and HannumAA (β: 1.96, 95% CI: 0.58-3.33, p = 0.005). In multivariable MR, the associations remained significant after adjusting for periodontitis, caries, number of teeth and bleeding gums. Three out of 12 aging risk factors were identified as mediators of the association between dentures and EAA, including body mass index, body fat percentage, and waist circumference. No evidence for reverse causality and pleiotropy were detected (p > 0.05).

CONCLUSIONS

Our findings supported the causal effects of genetic liability for denture wearing on epigenetic aging, with partial mediation by obesity. More attention should be paid to the obesity-monitoring and management for slowing EAA among denture wearers.

Five years of change in adult twins: longitudinal changes of genetic and environmental influence on epigenetic clocks

BACKGROUND

Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks.

METHODS

We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs.

RESULTS

Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks.

CONCLUSIONS

For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks.

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

The Significant Associations between Epigenetic Clocks and Bladder Cancer Risks

Bladder cancer is an age-related disease, with over three-quarters of cases occurring in individuals aged 65 years and older. Accelerated biological aging has been linked to elevated cancer risks. Epigenetic clocks serve as excellent predictors of biological age, yet it remains unclear whether they are associated with bladder cancer risk. In this large case-control study, we assessed the associations between four well-established epigenetic clocks-HannumAge, HorvathAge, GrimAge, and PhenoAge-and bladder cancer risk. Utilizing single nucleotide polymorphisms (SNPs), which were identified in a genome-wide association study (GWAS), linked to these clocks as instruments, we constructed a weighted genetic risk score (GRS) for each clock. We discovered that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69 per SD increase, 95% CI, 1.44-1.98, p = 1.56 × 10-10 and OR = 1.09 per SD increase, 95% CI, 1.00-1.19, p = 0.04, respectively). Employing a summary statistics-based Mendelian randomization (MR) method, inverse-variance weighting (IVW), we found consistent risk estimates for bladder cancer with both HannumAge and HorvathAge. Sensitivity analyses using weighted median analysis and MR-Egger regression further supported the validity of the IVW method. However, GrimAge and PhenoAge were not associated with bladder cancer risk. In conclusion, our data provide the first evidence that accelerated biological aging is associated with elevated bladder cancer risk.

Bidirectional relationship between epigenetic age and brain health events

Chronological age offers an imperfect estimate of the molecular changes that occur with aging. Epigenetic age, which is derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. This study examines the bidirectional relationship between epigenetic age and the occurrence of brain health events (stroke, dementia, and late-life depression). Using data from the Health and Retirement Study, we analyzed blood samples from over 4,000 participants to determine how epigenetic age relates to past and future brain health events. Study participants with a prior brain health event prior to blood collection were 4% epigenetically older (beta 0.04, SE 0.01), suggesting that these conditions are associated with faster aging than that captured by chronological age. Furthermore, a one standard deviation increase in epigenetic age was associated with 70% higher odds of experiencing a brain health event in the next four years after blood collection (OR 1.70, 95%CI 1.16-2.50), indicating that epigenetic age is not just a consequence but also a predictor of poor brain health. Both results were replicated through Mendelian Randomization analyses, supporting their causal nature. Our findings support the utilization of epigenetic age as a useful biomarker to evaluate the role of interventions aimed at preventing and promoting recovery after a brain health event.

Epigenetic Age Mediates the Association of Life's Essential 8 With Cardiovascular Disease and Mortality

BACKGROUND

Life's Essential 8 (LE8) is an enhanced metric for cardiovascular health. The interrelations among LE8, biomarkers of aging, and disease risks are unclear.

METHODS AND RESULTS

LE8 score was calculated for 5682 Framingham Heart Study participants. We implemented 4 DNA methylation-based epigenetic age biomarkers, with older epigenetic age hypothesized to represent faster biological aging, and examined whether these biomarkers mediated the associations between the LE8 score and cardiovascular disease (CVD), CVD-specific mortality, and all-cause mortality. We found that a 1 SD increase in the LE8 score was associated with a 35% (95% CI, 27-41; P=1.8E-15) lower risk of incident CVD, a 36% (95% CI, 24-47; P=7E-7) lower risk of CVD-specific mortality, and a 29% (95% CI, 22-35; P=7E-15) lower risk of all-cause mortality. These associations were partly mediated by epigenetic age biomarkers, particularly the GrimAge and the DunedinPACE scores. The potential mediation effects by epigenetic age biomarkers tended to be more profound in participants with higher genetic risk for older epigenetic age, compared with those with lower genetic risk. For example, in participants with higher GrimAge polygenic scores (greater than median), the mean proportion of mediation was 39%, 39%, and 78% for the association of the LE8 score with incident CVD, CVD-specific mortality, and all-cause mortality, respectively. No significant mediation was observed in participants with lower GrimAge polygenic score.

CONCLUSIONS

DNA methylation-based epigenetic age scores mediate the associations between the LE8 score and incident CVD, CVD-specific mortality, and all-cause mortality, particularly in individuals with higher genetic predisposition for older epigenetic age.

Causal Associations of DNA Methylation and Cardiovascular Disease: A Two-Sample Mendelian Randomization Study

Background

There is growing evidence that concentrations of DNA methylation are associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship.

Methods

We utilized a two-sample Mendelian randomization (MR) approach to investigate whether DNA methylation can affect the risk of developing cardiovascular disease in human life. We primarily performed the inverse variance weighted (IVW) method to analyze the causal effect of DNA methylation on multiple cardiovascular diseases. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These analysis methods included maximum likelihood, MR-Egger regression, weighted median method, and weighted model methods.

Results

Inverse variance weighted estimates suggested that an SD increase in DNA methylation Hannum age acceleration exposure increased the risk of cardiac arrhythmias (OR = 1.03, 95% CI 1.00-1.05, p = 0.0290) and atrial fibrillation (OR = 1.03, 95% CI 1.00-1.05, p = 0.0022). We also found that an SD increase in DNA methylation PhenoAge acceleration exposure increased the risk of heart failure (OR = 1.01, 95% CI 1.00-1.03, p = 0.0362). Exposure to DNA methylation-estimated granulocyte proportions was found to increase the risk of hypertension (OR = 1.00, 95% CI 1.00-1.0001, p = 0.0291). Exposure to DNA methylation-estimated plasminogen activator inhibitor-1 levels was found to increase the risk of heart failure (OR = 1.00, 95% CI 1.00-1.00, p = 0.0215).

Conclusion

This study reveals a causal relationship between DNA methylation and CVD. Exposed to high levels of DNA methylation Hannum age acceleration inhabitants with an increased risk of cardiac arrhythmias and atrial fibrillation. DNA methylation PhenoAge acceleration levels exposure levels were positively associated with the increased risk of developing heart failure. This has important implications for the prevention of cardiovascular diseases.

The effect of epigenetic aging on neurodegenerative diseases: a Mendelian randomization study

Background

Aging has always been considered as a risk factor for neurodegenerative diseases, but there are individual differences and its mechanism is not yet clear. Epigenetics may unveil the relationship between aging and neurodegenerative diseases.

Methods

Our study employed a bidirectional two-sample Mendelian randomization (MR) design to assess the potential causal association between epigenetic aging and neurodegenerative diseases. We utilized publicly available summary datasets from several genome-wide association studies (GWAS). Our investigation focused on multiple measures of epigenetic age as potential exposures and outcomes, while the occurrence of neurodegenerative diseases served as potential exposures and outcomes. Sensitivity analyses confirmed the accuracy of the results.

Results

The results show a significant decrease in risk of Parkinson's disease with GrimAge (OR = 0.8862, 95% CI 0.7914-0.9924, p = 0.03638). Additionally, we identified that HannumAge was linked to an increased risk of Multiple Sclerosis (OR = 1.0707, 95% CI 1.0056-1.1401, p = 0.03295). Furthermore, we also found that estimated plasminogen activator inhibitor-1(PAI-1) levels demonstrated an increased risk for Alzheimer's disease (OR = 1.0001, 95% CI 1.0000-1.0002, p = 0.04425). Beyond that, we did not observe any causal associations between epigenetic age and neurodegenerative diseases risk.

Conclusion

The findings firstly provide evidence for causal association of epigenetic aging and neurodegenerative diseases. Exploring neurodegenerative diseases from an epigenetic perspective may contribute to diagnosis, prognosis, and treatment of neurodegenerative diseases.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data

BACKGROUND

Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios.

METHODS

We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning.

RESULTS

Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively.

CONCLUSIONS

By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

Heterogeneity of aging and mortality risk among individuals with hypertension: Insights from phenotypic age and phenotypic age acceleration

OBJECTIVES

Hypertension, a key contributor to mortality, is impacted by biological aging. We investigated the relationship between novel biological aging metrics - Phenotypic Age (PA) and Phenotypic Age Acceleration (PAA) - and mortality in individuals with hypertension, exploring the mediating effects of arterial stiffness (estimated Pulse Wave Velocity, ePWV), and Heart/Vascular Age (HVA).

METHODS

Using data from 62,160 National Health and Nutrition Examination Survey (NHANES) participants (1999-2010), we selected 4,228 individuals with hypertension and computed PA, PAA, HVA, and ePWV. Weighted, multivariable Cox regression analysis yielded Hazard Ratios (HRs) relating PA, PAA to mortality, and mediation roles of ePWV, PAA, HVA were evaluated. Mendelian randomization (MR) analysis was employed to investigate causality between genetically inferred PAA and hypertension.

RESULTS

Over a 12-year median follow-up, PA and PAA were tied to increased mortality risks in individuals with hypertension. All-cause mortality hazard ratios per 10-year PA and PAA increments were 1.96 (95% CI, 1.81-2.11) and 1.67 (95% CI, 1.52-1.85), respectively. Cardiovascular mortality HRs were 2.32 (95% CI, 1.97-2.73) and 1.93 (95% CI, 1.65-2.26) for PA and PAA, respectively. ePWV, PAA, and HVA mediated 42%, 30.3%, and 6.9% of PA's impact on mortality, respectively. Mendelian randomization highlighted a causal link between PAA genetics and hypertension (OR = 1.002; 95% CI, 1.000-1.003).

CONCLUSION

PA and PAA, enhancing cardiovascular risk scores by integrating diverse biomarkers, offer vital insights for aging and mortality evaluation in individuals with hypertension, suggesting avenues for intensified aging mitigation and cardiovascular issue prevention. Validations in varied populations and explorations of underlying mechanisms are warranted.

Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

Causal relationship between gestational diabetes and preeclampsia: A bidirectional mendelian randomization analysis

AIMS

The study aimed to explore the potential causal link between gestational diabetes mellitus (GDM) and preeclampsia (PE) using a bidirectional mendelian randomization (MR) analysis.

MATERIALS

We conducted a bidirectional MR analysis to investigate the causal relationship between GDM and PE. Data from public genome-wide association studies (GWAS) for GDM and PE were obtained from the FinnGen consortium. Various MR methods were employed, including inverse-variance weighted (IVW), MR-Egger, and sensitivity analyses. Additionally, a knowledge-based approach identified genes underlying this potential connection.

RESULTS

The IVW method revealed a lack of significant association between GDM and PE (OR: 1.04, 95 % CI: 0.96-1.14; p = 0.275). Conversely, IVW analysis indicated a causal connection from PE to GDM (OR: 1.14, 95 % CI: 1.06-1.23; p < 0.001). Molecular pathway analysis identified 20 key genes, including ASAP2, central to the PE-GDM relationship. Tissue enrichment analysis showed pertinent gene expression in significant tissues. Moreover, lower ASAP2 expression was detected in PE patients' placentas.

CONCLUSIONS

Our bidirectional MR analysis offers evidence supporting a causal link between PE and GDM, elucidating their interconnected pathogenesis. Genetic and knowledge-based insights facilitate a deeper comprehension of these complex pregnancy complications.

A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis

BACKGROUND

'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056).

RESULTS

We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null.

CONCLUSION

Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.

Epigenetic age acceleration and risk of aortic valve stenosis: a bidirectional Mendelian randomization study

BACKGROUND

Aortic valve stenosis (AVS) is the most prevalent cardiac valve lesion in developed countries, and pathogenesis is closely related to aging. DNA methylation-based epigenetic clock is now recognized as highly accurate predictor of the aging process and associated health outcomes. This study aimed to explore the causal relationship between epigenetic clock and AVS by conducting a bidirectional Mendelian randomization (MR) analysis.

METHODS

Summary genome-wide association study statistics of epigenetic clocks (HannumAge, HorvathAge, PhenoAge, and GrimAge) and AVS were obtained and assessed for significant instrumental variables from Edinburgh DataShare (n = 34,710) and FinnGen biobank (cases = 9870 and controls = 402,311). The causal association between epigenetic clock and AVS was evaluated using inverse variance weighted (IVW), weighted median (WM), and MR-Egger methods. Multiple analyses (heterogeneity analysis, pleiotropy analysis, and sensitivity analysis) were performed for quality control assessment.

RESULTS

The MR analysis showed that the epigenetic age acceleration of HorvathAge and PhenoAge was associated with an increased risk of AVS (HorvathAge: OR = 1.043, P = 0.016 by IVW, OR = 1.058, P = 0.018 by WM; PhenoAge: OR = 1.058, P = 0.005 by IVW, OR = 1.053, P = 0.039 by WM). Quality control assessment proved our findings were reliable and robust. However, there was a lack of evidence supporting a causal link from AVS to epigenetic aging.

CONCLUSION

The present MR analysis unveiled a causal association between epigenetic clocks, especially HorvathAge and PhenoAge, with AVS. Further research is required to elucidate the underlying mechanisms and develop strategies for potential interventions.

Smoking and BMI mediate the causal effect of education on lower back pain: observational and Mendelian randomization analyses

Objective

Low back pain (LBP) has been associated with education in previous observational studies, but the causality remains unclear. This study aims to assess the impact of education on LBP and to explore mediation by multiple lifestyle factors.

Design

Univariable Mendelian randomization (MR) was performed to examine the overall effect of education on LBP. Subsequently, multivariable MR was conducted to assess both the direct effect of education on LBP and the influence of potential mediators. Indirect effects were estimated using either the coefficient product method or the difference method, and the proportion of mediation was calculated by dividing the indirect effect by the total effect. The observational study utilized data from the NHANES database collected between 1999 and 2004, and included 15,580 participants aged 20 years and above.

Results

Increasing education by 4.2 years leads to a 48% reduction in the risk of LBP (OR=0.52; 95% CI: 0.46 to 0.59). Compared to individuals with less than a high school education, those with education beyond high school have a 28% lower risk of LBP (OR=0.72; 95% CI: 0.63 to 0.83). In the MR study, smoking accounts for 12.8% (95% CI: 1.04% to 20.8%) of the total effect, while BMI accounts for 5.9% (95% CI: 2.99% to 8.55%). The combined mediation effect of smoking and BMI is 27.6% (95% CI: 23.99% to 32.7%). In the NHANES study, only smoking exhibits a mediating effect, accounting for 34.3% (95% CI: 21.07% to 41.65%) of the effect, while BMI does not demonstrate a mediating role.

Conclusions

Higher levels of education provide a protective effect against the risk of LBP. Additionally, implementing interventions to reduce smoking and promote weight loss among individuals with lower levels of education can also decrease this risk.