Ageing biomarkers can predict mortality risk beyond chronological age. Recently, plasma proteins were used to estimate the biological ages of eleven human organs, including the brain, heart, liver, kidneys, and pancreas. Accelerated organ ageing is linked to higher all-cause mortality; however, systematic benchmarking against established ageing biomarkers is lacking. Here, we pursued two complementary aims. First, we benchmarked proteomic organ ages against multimodal ageing biomarkers for all-cause mortality (444 deaths; ≤17-year follow-up) using Cox regression in 861 Lothian Birth Cohort 1936 (LBC1936) participants. Ageing biomarkers included epigenetic age (GrimAge2), telomere length, neuroimaging, general cognitive function (g), and physical function (grip strength, walk time, and respiratory function). Among proteomic organ ageing biomarkers, accelerated liver (HRperSD [95%CI] = 1.43 [1.30-1.58]), immune (1.42 [1.29-1.57]), and heart (1.38 [1.25-1.53]) ageing were most strongly associated with higher mortality risk. However, GrimAge2 acceleration, total brain volume (TBV), grey matter volume, respiratory function, and g exhibited higher hazard estimates (HRperSD = 1.44-1.62) than organ ageing biomarkers. In a Cox model including all biomarkers, only TBV, white matter hyperintensity volume, g, and walk time associated with mortality. Second, survival analyses of SomaScan 11K plasma proteins identified 202 proteins associated with mortality and enriched for the liver and immune-related biological processes, with the strongest effects observed for GDF15 (HRperSD [95%CI] = 1.53 [1.37-1.72]), CST3 (1.48 [1.29-1.69]), and COL18A1 (1.47 [1.30-1.68]). These findings provide a systematic, cross-modal benchmarking of proteomic organ ages against established ageing biomarkers and highlight plasma proteomic signatures of mortality.

Both short and long sleep duration have been associated with poor glycemic control and an increased risk of developing type 2 diabetes mellitus. Although sleep duration may differentially modify the effects of genetic risk factors for type 2 diabetes, this has not been systematically investigated. In the present study, we conducted genome-wide gene by sleep duration meta-analyses, separately assessing interactions of short and long sleep, for fasting glucose, fasting insulin, and hemoglobin A1c in up to 489,309 individuals without diabetes from seven different population groups. In total, 16 loci were identified to interact with sleep duration - six with short sleep and ten with long sleep. Of these, four loci were identified through cross-population meta-analysis. Mapped genes exhibit pathway connections to pericyte apoptosis, NMDA receptor activity, the GLUT1 receptor, neurological health, and sleep architecture. Eleven loci (VRK2, PCDH7, TFAP2A, CAP2, PAPPA, ZCCHC2, MYH9, SGIP1, JAKMIP3, RRAS2, MAPT) have not been reported in previous glycemic trait genome-wide association studies. Interaction loci identify divergent biological mechanisms for short and long sleep duration influencing glycemic control, suggesting specific pathways of intervention for precision medicine approaches to diabetes prevention and management.

Genetic predisposition and alcohol consumption are risk factors for increased blood pressure (BP), but their interactions influencing BP remain understudied. We conducted population-specific and cross-population meta-analyses of genome-wide gene-alcohol (GxAlc) interactions affecting BP in >1.1M individuals from multiple populations. We identified 46 GxAlc interaction loci for BP, including 21 from one-degree-of-freedom interaction tests (PGxAlc<5×10-8; or <0.05/Meff, Meff independent BP associations at P<10-5), and 25 from two-degree-of-freedom tests of main and interaction effects (PGxAlc<0.05/M2df, M2df independent 2df-associations at P2df<5×10-8), including 7 novel and 39 known BP loci. The 12q24 locus highlights the genetic effect of BRAP-rs11066001 on BP, being ~6 times larger in current drinkers than in non-drinkers. Gene prioritization with 46 GxAlc loci identified 15 genes with ≥3 lines of evidence (location, literature, druggability, functional/regulatory annotation, or pathway analyses). Several loci showed sex- and population-specific effects and revealed biological pathways of alcohol's influence on BP, suggesting mechanisms underlying alcohol-induced hypertension.

Background:Carotid-intima media-thickness (cIMT) predicts cardiovascular events and informs mechanistic research on cardiovascular diseases. However, cardiovascular disease research remains Eurocentric despite etiological differences across ancestries. Incorporating Asian populations who face substantial cardiovascular disease burden with distinct etiological landscape can enhance our understanding of cIMT biology and subclinical processes linked to CVD. This study aims to elucidate methylation-based mechanisms of cIMT through DNA methylation profiling integrated with multi-omics data and clinically informative cIMT thresholds, leveraging an Asian cohort to enhance discovery. Methods:We conducted an epigenome-wide association study (EWAS) of cIMT using peripheral blood DNA methylation at ~850,000 CpG sites in the Asian Health for Life in Singapore (HELIOS) cohort (n=1,357), followed by targeted trans-ancestry meta-analysis with European cohorts (overall n=2,765). Causal inference analyses (summary data-based Mendelian Randomisation [SMR] and colocalisation) evaluated methylation-mediated effects on cIMT, cardiovascular disease and proximal gene expression. We derived a methylation risk score (MRS) and tested its association with cIMT thresholds indicative of elevated cardiovascular risk (≥75th percentile for age, sex and ethnicity). Results:Three novel CpG-cIMT associations were identified (P<9.35E-07). Causal analyses supported cg08227773 methylation-mediated effects on both coronary artery disease risk (PSMR=2.91E-05, coloc PP.H4 =0.91) and NBEAL2 (Neurobeachin-like 2) expression (PSMR=9.13E-08, coloc PP.H4=0.69), a gene implicated in immune dysregulation. MRS of cIMT aggregating the three sentinel CpGs was associated with clinically-informative cIMT elevation (Odds Ratio=2.75 for Q4 vs Q1, 95% CI: 1.47-5.13). Conclusions:Through Asian-led discovery, this study identifies three novel DNA methylation markers for cIMT that are linked to cIMT elevation above clinically meaningful risk thresholds. Causal inference analyses suggest methylation-mediated coronary artery disease risk via NBEAL2 regulation, nominating biologically relevant targets while underscoring the need for larger multi-omics resources to refine mechanisms.

Abstract Background CYP2C19 metabolises many medications. Its enzymatic activity can be inferred from genetic variants within CYP2C19 that link to the efficacy of drug treatments and their side effects. It is, however, unclear if enzymatic activity is associated with local or widespread differences in DNA methylation. DNA methylation differences associated with CYP2C19 metabolising status may also reveal interacting genes and pathways that underlie CYP2C19 effects on drug response and health consequences. A discovery methylome-wide association study (MWAS) was conducted in the Generation Scotland (n = 18,396) to investigate the non-linear and linear effects of CYP2C19 metaboliser status on DNA methylation. A targeted replication analysis on significant CpG sites from the discovery MWAS was conducted in Lothian Birth Cohorts of 1921 and 1936 (n = 1238). Pathway enrichment analysis was conducted for significant cytosine-guanine dinucleotide (CpG) sites. We examined whether the associations between CYP2C19 metaboliser status and DNA methylation were independent of the use of drugs that are inducers, inhibitors, or substrates of the CYP2C19 enzyme through interaction analysis. Results Forty-eight CpG sites were significantly associated with the quadratic term of CYP2C19 metaboliser status (PBonferroni<0.05). Nineteen CpG sites, annotated to genes involving drug metabolism, inflammation, lipid levels, and Type 2 diabetes, demonstrated non-linear associations with CYP2C19 metaboliser status. Among the significant CpG sites in the discovery sample, there was a high correlation of standardised regression coefficients between the discovery and replication samples (r = 0.92). We found enrichment in biological processes involving metabolic activities and the Cytochrome P450 pathway. CYP2C19 metaboliser status did not interact with CYP2C19-related medication use to affect methylation of non-linear CpG signals. Conclusions This research suggests that genetically-determined CYP2C19 metaboliser status is associated with both local and distal DNA methylation. These associations are independent of whether individuals were receiving drugs that are related to this enzyme.

Blood-based DNA methylation may help identify biological changes related to dementia risk before clinical symptoms appear. We conducted an epigenome-wide association study of incident all-cause dementia in 5,999 cognitively healthy women from the Women's Health Initiative Memory Study, 777 of whom developed dementia over up to 25 years of follow-up. Baseline blood DNA methylation was tested for association with time to dementia. One CpG site, cg05917797, was significantly associated with dementia risk, with higher methylation linked to lower risk. This association was only minimally changed after accounting for APOE ε4 carrier status, plasma p-tau217, and epigenetic aging measures. cg05917797 also replicated in meta-analysis of four independent prospective cohorts including 10,916 participants and 413 incident dementia cases. In post-mortem brain methylation datasets, higher methylation at cg05917797 was associated with lower Braak stage in temporal gyrus and cerebellum. In meta-analysis of all five prospective cohorts, including 16,915 participants and 1,190 dementia cases, cg05917797 remained the leading association, and three additional CpGs were identified for further study. These findings support cg05917797 as a reproducible blood-based epigenetic marker of long-term dementia risk.

While height is a highly heritable trait with strong polygenic prediction, previous studies have postulated that minimal variation of its individual differences can be captured by DNA methylation (DNAm). We investigated the role of blood-based genome-wide DNAm in capturing the variance in adult height in a large population-based cohort of 7,654 unrelated individuals from Generation Scotland using DNAm profiled on the Illumina EPIC array. The posterior DNAm probe effects were used to construct a DNAm profile score (Methylation Profile Score—MPS) which was evaluated in three independent cohorts. Genome-wide DNAm captures 25.0

We were invited to make a response to Gargus’s and Haier’s (Gargus & Haier, 2025) paper Toward a Molecular Biology of Human Intelligence: Psychometrics Meets Gene Expressions and Brain Metabolism . We’re tramping ‘toward’ that goal too. Our comments recognise that the authors have pointed to some biological loci/concepts that might help with understanding intelligence differences. We muse on what genomic and brain imaging studies have contributed, and their limitations. Mostly, the reader will note our efforts (sometimes not successful) at trying not to appear overwhelmed by the off-putting complexity of explaining how differences arise in intelligence and other complex traits. Note : The title of this paper comes from Emily Dickinson’s poem, “We Grow Accustomed to the Dark.”

Gene-environment interactions may enhance our understanding of blood pressure (BP) biology. We conducted a meta-analysis of multi-population genome-wide association studies (GWASs) of BP traits accounting for gene-depressive symptomatology (DEPR) interactions. Our study included 564,680 adults from 67 cohorts and four population backgrounds: African (5%), Asian (7%), European (85%), and Hispanic (3%). We discovered seven previously unreported BP loci showing gene-DEPR interaction. These loci mapped to genes implicated in neurogenesis (TGFA and CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6 and DBI). We also showed evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 were derived from non-European populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4 and MAGI2) and neuronal signaling (CCK, UGDH, and SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets linked to pathways involved in mood disorders as well as known anti-hypertensive drugs. Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.

Gardening is a common leisure activity among older adults, yet its potential to support healthy aging remains underexplored, particularly in longitudinal contexts and across multiple aging domains. This study investigated whether gardening frequency was associated with psychological, physical, and biological aging markers, as well as mortality, in the Lothian Birth Cohort 1921 (LBC1921). Gardening frequency was assessed via questionnaire at a mean age of 79 years (baseline: 1999-2001) in 475 participants. Aging markers were measured at 79, 83, 87, and 90 years. Psychological markers (quality of life, psychological wellbeing) were self-reported; physical function markers (lung function, gait speed, grip strength, functional ability) were objectively assessed; and biological markers (telomere length, DNA methylation-based PhenoAge) were blood-derived. Survival was tracked using 25-year mortality linkage data. Analyses included linear regression, growth curve modeling, and Cox proportional hazards, adjusted for individual-and neighbourhood-level covariates. Of the sample, 207 gardened frequently, 78 sometimes, and 190 never or rarely. At baseline (age 79), higher gardening frequency was associated with better psychological wellbeing, stronger physical function, and longer telomeres. Longitudinally, more frequent gardening predicted slower declines in gait speed and telomere attrition from age 79 to 90. Frequent gardeners had a 22 % lower mortality risk (HR = 0.78, 95 % CI: 0.62-0.97) than those who never or rarely gardened. Associations were not substantially confounded by sociodemographic, lifestyle, or physical activity factors. Our results suggest that gardening may support wellbeing and longevity, with potential implications for aging in place for older adults.

The allostatic load (AL) concept measures physiological dysregulation in response to internal and external stressors that accumulate across the life course. AL has been consistently linked to chronic disease risk across studies. However, there is considerable variation in its operationalization. In the present study, DNA methylation (DNAm) data (using the Illumina Infinium MethylationEPIC BeadChip array) from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) cohort, a Swiss-based family cohort study, were used in a discovery epigenome-wide association study to identify cytosine-guanine nucleotide sites associated with phenotypic measures of AL. Elastic net linear regression models were used to estimate an epigenetic signature of AL (methAL), including an Illumina HumanMethylation450K (HM450K) assay-compatible signature (methALT). The methALT signature was validated in the 1936 Lothian Birth Cohort (LBC1936), population-based prospective cohort study. We found that the methAL signature was positively associated with the clinical phenotype of AL in both the SKIPOGH (R2 = 0.59) and LBC1936 (R2 = 0.16) cohorts. In the validation cohort, a one standard deviation increase in methALT signature was associated with 25% higher odds of reported history of cardiovascular disease (CVD) (odd ratio [OR] = 1.25, 95% confidence interval [CI] = 1.05-1.50), and a nearly two-fold increase in all-cause mortality rate at the beginning of follow-up (hazard ratio = 1.68, 95% CI = 1.33-2.13) when adjusting for all potential confounders. In conclusion, the epigenetic signature for AL not only correlated well with phenotype-based AL scores but also exhibited a stronger association with the history of CVD and all-cause mortality compared with AL scores. The methAL signature could help assuage issues of comparison across studies.

Cognitive deficits are common across many neurodevelopmental and psychiatric conditions, including those studied in the current set of PGC-CNV papers. How changes in regional gene expression across the cerebral cortex influence cognitive ability remains unknown. Population variation in gene dosage-which significantly impacts gene expression-represents a unique paradigm to address this question. We developed a cerebral-cortex gene-set burden analysis (CC-GSBA) to associate a trait with genomic deletions and duplications that disrupt genes with similar expression profiles across 180 cortical regions. We performed CC-GSBA across 180 cortical regions to test associations with cognitive ability in 260,000 individuals from general population cohorts. Most cortical gene sets were associated with a decrease in cognitive ability when deleted or duplicated, and this novel approach revealed opposing cortical patterns for the effect sizes of deletions and duplications. These cortical patterns of effect sizes followed the cortical gradient previously characterized at the molecular, cellular, and functional levels. We show that genes with preferential expression in sensorimotor regions demonstrated the largest effect on cognition when deleted. At the opposing end of the cortical gradient, genes with preferential expression in multimodal association regions affected cognition the most when duplicated. These two gene dosage cortical patterns could not be explained by particular cell types, developmental epochs, or genetic constraints, highlighting the fact that the macroscopic network organization of the cerebral cortex is key to understanding the effects of gene dosage on cognitive traits.

Variation in the gene for apolipoprotein E (APOE) is one of the few variables that is associated with individual differences in age-related cognitive decline in humans. Therefore, it is important to understand the conditions that affect the strength of its effect. Here we examine how the effect size of APOE variation (possession of one or more e4 alleles) on a test of general cognitive ability changes with age from 11–90 years. The data are from the Lothian Birth Cohorts of 1936 and 1921 who took the same cognitive test (the Moray House Test No. 12) at, respectively, ages 11 (N = 954), 70 (N = 1001), 76 (N = 636), 79 (N = 471), and 11 (N = 483), 79 (N = 533), 87 (N = 198), 90 (N = 120). The standardised absolute effect of APOE e4 on general cognitive ability was about zero at ages 11 (beta < 0.05) and 70 (beta ≤ 0.025) and increased linearly to beta = 0.30 (p < 0.001) at age 90. The effect sizes were minimally affected by adjusting for medical conditions (hypertension, diabetes, cardiovascular disease, stroke). However, the results were less robust to removing those participants who developed dementia; effect sizes were reduced by about a third to a half, and were largely non-significant. The results suggest that the negative effect of APOE e4 on cognitive functioning becomes greater with age; this urges more work to understand the mechanisms by which e4 status renders the older person’s brain increasingly vulnerable to cognitive decline and dementia.

Cigarette smoking influences blood pressure (BP) levels. Studying and accounting for potential gene-smoking interactions can help discover novel loci and provide insights into biological pathways for smoking-associated BP regulation. We conducted a genome-wide association meta-analysis involving 1,188,241 individuals from 66 studies in five ancestry groups, analyzing systolic BP, diastolic BP, and pulse pressure while considering interactions between genetic variants and three smoking exposures: smoking status, cigarettes per day, and pack years. These analyses identified twelve novel loci for BP at genome-wide significance ( P < 5 × 10 - 9 ), and highlighted biological processes including tight junction integrity, mitochondrial health, vascular relaxation, and endothelial function. In smoking status-stratified analyses, smoking modifies the genetic effect of six variants on BP. To prioritize likely causal, we developed and applied SuSiEgxe, a fine-mapping method based on a two-degree-of-freedom joint test using gene-environment interaction summary statistics. Fine-mapped loci uncovered immune-related pathway for smoking-associated BP regulation.

Clonal hematopoiesis (CH) is characterized by expanding blood cell clones carrying somatic mutations in healthy aged individuals and is associated with various age-related diseases and all-cause mortality. While CH mutations affect diverse genes associated with myeloid malignancies, their mechanisms of expansion and disease associations remain poorly understood. We investigate the relationship between clonal fitness and clinical outcomes by integrating data from three longitudinal aging cohorts (n=713, observations=2,341). We demonstrate pathway-specific fitness advantage and clonal composition influence clonal dynamics. Further, the timing of mutation acquisition is necessary to determine the extent of clonal expansion reached during the host individual’s lifetime. We introduce MACS120, a metric combining mutation context, timing, and variant fitness to predict future clonal growth, outperforming traditional variant allele frequency measurements in predicting clinical outcomes. Our unified analytical framework enables standardized clonal dynamics inference across cohorts, advancing our ability to predict and potentially intervene in CH-related pathologies.

Major depression (MD) is a leading cause of global disease burden, and both experimental and population-based studies suggest that differences in DNA methylation may be associated with the condition. However, previous DNA methylation studies have, so far, not been widely replicated, suggesting a need for larger meta-analysis studies. Here we conducted a meta-analysis of methylome-wide association analysis for lifetime MD across 18 studies of 24,754 European-ancestry participants (5,443 MD cases) and an East Asian sample (243 cases, 1,846 controls). We identified 15 CpG sites associated with lifetime MD with methylome-wide significance. The methylation score created using the methylome-wide association analysis summary statistics was significantly associated with MD status in an out-of-sample classification analysis (area under the curve 0.53). Methylation score was also associated with five inflammatory markers, with the strongest association found with tumor necrosis factor beta. Mendelian randomization analysis revealed 23 CpG sites potentially causally linked to MD, with 7 replicated in an independent dataset. Our study provides evidence that variations in DNA methylation are associated with MD, and further evidence supporting involvement of the immune system.

Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait. Here, we explore the epigenetic architecture of self-reported weekly units of alcohol consumption in the Generation Scotland study. We first create a blood-based epigenetic score (EpiScore) of alcohol consumption using elastic net penalized linear regression. We explore the effect of pre-filtering for CpG features ahead of elastic net, as well as differential patterns by sex and by units consumed in the last week relative to an average week. The final EpiScore was trained on 16,717 individuals and tested in four external cohorts: the Lothian Birth Cohorts (LBC) of 1921 and 1936, the Sister Study, and the Avon Longitudinal Study of Parents and Children (total N across studies > 10,000). The maximum Pearson correlation between the EpiScore and self-reported alcohol consumption within cohort ranged from 0.41 to 0.53. In LBC1936, higher EpiScore levels had significant associations with poorer global brain imaging metrics, whereas self-reported alcohol consumption did not. Finally, we identified two novel CpG loci via a Bayesian penalized regression epigenome-wide association study of alcohol consumption. Together, these findings show how DNAm can objectively characterize patterns of alcohol consumption that associate with brain health, unlike self-reported estimates.

Background:Gene-environment interactions may enhance our understanding of hypertension. Our previous study highlighted the importance of considering psychosocial factors in gene discovery for blood pressure (BP) but was limited in statistical power and population diversity. To address these challenges, we conducted a multi-population genome-wide association study (GWAS) of BP accounting for gene-depressive symptomatology (DEPR) interactions in a larger and more diverse sample. Results:Our study included 564,680 adults aged 18 years or older from 67 cohorts and 4 population backgrounds (African (5%), Asian (7%), European (85%), and Hispanic (3%)). We discovered seven novel gene-DEPR interaction loci for BP traits. These loci mapped to genes implicated in neurogenesis (TGFA, CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6, DBI). We also identified evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 loci were derived from African, Asian, or Hispanic populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4, MAGI2) and neuronal signaling (CCK, UGDH, SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets, including genes implicated in pathways linked to mood disorders as well as gene products targeted by known antihypertensive drugs. Conclusions:Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.

DNA methylation offers an objective method to assess the impact of smoking. In this work, we conduct a Bayesian EWAS of smoking pack years (n = 17,865, ~850k sites, Illumina EPIC array) and extend it by analysing whole genome data of smokers and non-smokers from Generation Scotland (n = 46, ~4-21 million sites via TWIST and Oxford Nanopore sequencing). We develop mCigarette, an epigenetic biomarker of smoking, and test it in two British cohorts. Results of brain- and blood-based EWAS (nbrain=14, nblood = 882, >450k sites, Illumina arrays) reveal several loci with near-perfect discrimination of smoking status, but which do not overlap across tissues. Furthermore, we perform a GWAS of epigenetic smoking, identifying several smoking-related loci. Overall, we improve smoking-related biomarker accuracy and enhance the understanding of the effects of smoking by integrating DNA methylation data from multiple tissues and cohorts.