Oliver Robinson

Background DNA methylation (DNAm) based age acceleration is an indicator of biological ageing. However, it is unclear how age acceleration is linked to mental health in adolescents. We examined the longitudinal associations between DNAm age acceleration and depression and anxiety in adolescents. We also triangulated the evidence using Mendelian Randomisation (MR). Methods We analysed a subsample of adolescents (n=261) from a London-based adolescent cohort study. DNAm profile was generated from saliva samples collected at ages 11-12 years. DNAm age acceleration measures were derived from Horvath, PhenoAge, and PedBE clocks. Depressive and anxiety symptoms were measured at ages 13-15 years, using the Patient Health Questionnaire and Generalised Anxiety Disorder scale, respectively. The associations between DNAm age acceleration and depressive and anxiety symptoms were assessed using logistic regression. We also conducted a two-sample MR to investigate the potential causal relationship between Horvath and PhenoAge acceleration and depression and anxiety. Results We found that PhenoAge age acceleration was associated with higher severity levels of depressive symptoms (OR=1.04, 95% CI 1.01, 1.08) and clinically significant depressive symptoms (OR=1.05, 95% CI 1.01, 1.10). None of these three clocks was associated with anxiety outcomes. MR suggested a potential causal relationship between PhenoAge age acceleration and depression (Inverse variance weighted OR = 1.01, 95% CI 1.00, 1.02). Conclusions PhenoAge acceleration at ages 11-12 years was associated with depressive symptoms at ages 13-15 years. The association patterns are consistent between longitudinal and MR analyses. PhenoAge acceleration may represent a potential early biomarker for subsequent depressive symptoms in adolescents.

Understanding the links between metabolism, ageing, and age-related phenotypes may clarify the role of ageing in disease onset and improve risk prediction. We conducted a cross-cohort assessment of biological age using broad-spectrum LC–MS metabolomics of 3,686 plasma samples in 2,295 participants, aged 20–89, from the UK Airwave study ( N = 960) and the Irish Longitudinal Study of Ageing ( N = 1,335). The nucleoside N ₂ ,N ₂ -dimethylguanosine, C-glycosyltryptophan, bile acid glucuronides, and the antioxidant zeta-carotene were associated with chronological age, frailty, and mortality. The noradrenergic metabolite 3-methoxy-4-hydroxyphenylglycol sulphate and the oligosaccharide sialyllactose were strongly associated with both age and mortality. We developed a metabolomic clock that was highly predictive of chronological age ( r = 0.92) in test samples. Metabolomic age acceleration was strongly correlated between study visits ( r > 0.6). Each standard deviation increase in metabolomic age acceleration (~ 5 years) was associated with 43% higher mortality risk, 27% higher risk of mild cognitive impairment, and 10% increased risk of a higher frailty score in fully adjusted models. The metabolites identified here may link ageing and age-related vulnerability and should be further investigated in mechanistic studies. The metabolomic clock has potential for translational applications, including as a prognostic and response marker of generalised age-related disease risk.

Assessment of biological aging using proteomic clocks may enhance risk prediction and elucidate the molecular links between aging and chronic diseases. Here, among 17,473 participants of the European Prospective Investigation into Cancer and Nutrition, we examined associations of plasma SomaScan-based proteomic clocks, including organ-specific clocks, with risk factors, 24 incident chronic diseases and all-cause mortality, over up to 28 years of follow-up. Replication was conducted in the Whitehall II study. We show that the global age gap, an age acceleration score combining proteomic clocks, was associated with smoking, alcohol consumption, physical inactivity and higher risk of mortality, cardiovascular diseases, dementia and cancers of the liver, upper aero-digestive tract, lung and kidney. Lung, kidney and stomach cancers were more strongly associated with related organ-specific age gaps. Predictive performance of proteomic clocks for mortality was comparable to that of classical lifestyle risk factors. In summary, proteomic clocks appear promising biomarkers of generalized age-related disease risk.

Biological age may provide a more informative metric of individual physiological function and life expectancy, compared to chronological age. Proteomic aging clocks are predictive models trained using high-dimensional proteomic data to quantify biological age. Owing to the central biological role of proteins and their established clinical utility as druggable targets and prognostic biomarkers, proteomics is particularly promising for the assessment of aging. In this Review, we provide an overview of current proteomic clocks based on different platforms in human blood samples, emphasizing their potential clinical application as discovery, predictive and response aging biomarkers. While the field is advancing rapidly, proteomic clocks vary widely in their assay platforms, study populations and modeling strategies, which may limit their generalizability, biological interpretability and translational utility. We further discuss current challenges and prospects in this research area, which aims to facilitate the implementation of proteomic clocks in proactive, preventive medicine to extend population healthspan.

Introduction: Understanding the links between metabolism, ageing and age-related phenotypes may clarify the role of ageing in disease onset and improve risk prediction. Methods: We conducted a cross-cohort assessment of biological age using broad-spectrum LC-MS metabolomics in 2,295 participants, aged 20-89, from the UK Airwave study (N=960) and The Irish Longitudinal Study of Ageing (N=1,335). Results: N ₂ ,N ₂ -dimethylguanosine, C-glycosyltryptophan, bile acid glucuronides, and zeta-carotene were associated with chronological age, frailty, and mortality. We developed a metabolomic clock that was highly predictive of chronological age (r = 0.92) in test samples. Metabolomic age acceleration was strongly correlated between study visits ( r > 0.6). Each standard deviation higher metabolomic age acceleration (∼5 years) was associated with 43% higher mortality risk, 27% higher risk of mild cognitive impairment, and 10% increased risk of a higher frailty score in fully adjusted models. Discussion: Our metabolomic clock provides a reproducible marker of generalised age-related disease risk.

Background: Evidence on sex differences in cognition and dementia is inconsistent, and it is unclear whether such differences are explained by dementia risk factors. Objective: To assess (i) sex differences in cognitive decline and dementia risk, (ii) the extent to which modifiable and nonmodifiable risk factors explain these differences and (iii) whether birth cohort and apolipoprotein (APOE)‐Ꜫ4 carrier status modify sex differences in cognitive decline. Methods: Data from the Whitehall II study were analysed to examine cross‐sectional and longitudinal associations between sex, cognitive decline and dementia risk. Cognitive outcomes included verbal memory and verbal fluency, assessed from Phase 5 onward, with over 16 years of follow‐up. Test scores were standardised using means and standard deviations from the baseline cognitive tests to generate z‐scores. All‐cause dementia was ascertained through linkage to three electronic health record databases. Results: Among 5920 participants aged 44.8–68.2 years, women demonstrated better baseline performance than men in memory (adjusted mean difference = −0.2, p < 0.0001), phonemic fluency (−0.1, p = 0.001) and semantic fluency (−0.2, p < 0.0001). Men exhibited a steeper decline in semantic fluency (adjusted β = −2.6, p < 0.0001) and a nominal decline in phonemic fluency (−1.7, p = 0.007). Sex differences remained after adjustment for covariates. Dementia incidence did not differ significantly by sex. Birth cohort and APOE‐Ꜫ4 carrier status did not meaningfully modify associations between sex and cognitive outcomes. Conclusion: Cognitive advantages observed in women in midlife did not translate into lower dementia risk. Further research incorporating biological, psychosocial and life‐course factors, as well as the timing and heterogeneity of underlying disease processes, is needed to better understand sex differences in cognitive ageing and dementia.

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. Methods: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). Findings: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson’s and Alzheimer’s disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. Interpretation: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention.

INTRODUCTION: Cerebral microhemorrhages (CMHs) and superficial siderosis (SS) are relatively common side effects of anti‐amyloid immunotherapies, termed amyloid‐related imaging abnormalities (ARIA‐H). They are also observed in treatment‐naïve older adults. This study explored relationships with modifiable and non‐modifiable risk factors.METHODS: This cross‐sectional study included 1414 cognitively unimpaired, treatment‐naïve individuals aged 60 to 85 years from the Cognitive Health in Ageing Register: Investigational, Observational and Trial Studies in Dementia Research (CHARIOT): Prospective Readiness cOhort (PRO) SubStudy. Relationships between CMHs/SS and cardiovascular risk factors, amyloid beta (Aβ) load, apolipoprotein E (APOE) ε4 status, educational attainment, and white matter hyperintensities were investigated using regression analyses and structural equation modeling.RESULTS: CMHs were observed in 8.3% of participants and SS in 1.3%. Significant risk factors for CMHs included age and hypertension. Higher education attainment appeared to have a protective effect. Elevated amyloid is a risk factor, particularly when adjusting for APOE ε4 status in individuals aged 70 or younger.DISCUSSION: Increasing age and hypertension are significant risk factors of CMHs. Higher educational attainment may offer a protective effect.Highlights: Of the 1414 participants from the CHARIOT‐PRO SubStudy (CPSS), CMHs were present in 118 (8.3%), and SS was present in 18 (1.3%). Age and hypertension were identified as significant risk factors for CMHs, and the latter had a stronger association with the presence of CMHs among female participants. Having a bachelor's degree or higher was found to be protective. Elevated brain amyloid burden, particularly when adjusted for APOE ε4 carrier status, was identified as a risk factor in individuals aged 70 years and below.

More than 57 million people globally suffer from neurodegenerative diseases, a figure expected to double every 20 years. Despite this growing burden, there are currently no cures, and treatment options remain limited due to disease heterogeneity, prolonged preclinical and prodromal phases, poor understanding of disease mechanisms, and diagnostic challenges. Identifying novel biomarkers is crucial for improving early detection, prognosis, staging and subtyping of these conditions. High-dimensional molecular studies in biofluids (‘omics’) offer promise for scalable biomarker discovery, but challenges in assembling large, diverse datasets hinder progress. To address this, the Global Neurodegeneration Proteomics Consortium (GNPC)—a public–private partnership—established one of the world’s largest harmonized proteomic datasets. It includes approximately 250 million unique protein measurements from multiple platforms from more than 35,000 biofluid samples (plasma, serum and cerebrospinal fluid) contributed by 23 partners, alongside associated clinical data spanning Alzheimer’s disease (AD), Parkinson’s disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). This dataset is accessible to GNPC members via the Alzheimer’s Disease Data Initiative’s AD Workbench, a secure cloud-based environment, and will be available to the wider research community on 15 July 2025. Here we present summary analyses of the plasma proteome revealing disease-specific differential protein abundance and transdiagnostic proteomic signatures of clinical severity. Furthermore, we describe a robust plasma proteomic signature of APOE ε4 carriership, reproducible across AD, PD, FTD and ALS, as well as distinct patterns of organ aging across these conditions. This work demonstrates the power of international collaboration, data sharing and open science to accelerate discovery in neurodegeneration research.

Assessment of biological ageing using proteomic clocks may enhance risk prediction and elucidate the molecular links between ageing and chronic diseases. Within a pre-diagnostic cohort of 17,473 Europeans with up to 28 years of follow-up, we examined associations of plasma SomaScan-based proteomic clocks, including organ-specific clocks, with 24 incident chronic diseases, all-cause mortality, and lifestyle risk factors. Global proteomic age gap (a composite biological age acceleration score combining previously published clocks) showed the strongest positive association of all tested clocks with all-cause mortality. Accelerated proteomic ageing was significantly associated with smoking, alcohol consumption, physical inactivity, and higher risk of cardiovascular diseases, dementia, and liver, upper aero-digestive tract, lung, and kidney cancers. Some organ-specific cancers were more strongly associated with their respective organ-specific age gaps. Mortality prediction by proteomic clocks was comparable in performance to classical lifestyle risk factors. In summary, proteomic clocks appear promising biomarkers of generalized age-related disease risk.