👤 Sara Hägg

Cardiovascular diseases are the leading cause of death globally. Consequently, metabolomics studies have in recent years aimed at identifying relevant biomarkers, yet no studies have been performed in twin populations, which reduce confounding due to genetic and environmental factors. We included 11,217 twins (age at intake, 47-94 years (mean = 65)) from the Swedish Twin Registry, holding data on 173 nuclear magnetic resonance metabolomic biomarkers and nationwide register-based data on diagnoses of ischemic stroke, ischemic heart disease, myocardial infarction, angina pectoris, and coronary artery disease. Only incident cases (i.e., exclusively holding diagnosis after blood sampling) were included for statistical analyses, which were performed at the individual level and the twin-pair level by Cox regression analyses. Lastly, biomarkers significant in both analyses were inspected, hence conditioning on the twin pair design. Fifty-one biomarkers were found to be associated with myocardial infarction after correction for multiple testing, all showing a hazard ratio above 1. LASSO regression analysis of these biomarkers identified four biomarkers, all related to ApoB lipoprotein biology, potentially reflecting a pro-atherogenic effect. Investigation of biomarkers with p-values < 0.05 identified 20 biomarkers for ischemic heart disease, all showing hazard ratios below 1 and primarily related to ApoA1 lipoprotein biology, potentially reflecting an anti-atherogenic effect. Lastly, three biomarkers, i.e., acetoacetate, bOHbutyrate, and isoleucine, were found for ischemic stroke, all showing a hazard ratio above 1. Taken together, different biomarkers associated with the disease phenotypes indicate that their molecular profiles are different, despite their common basis. The ApoB stands out as a promising biomarker for myocardial infarction. Show less

Alzheimer’s disease and related dementias (ADRD) are complex, polygenic conditions with substantial public health impact. Accurate genetic risk prediction may enable earlier identification and stratification of individuals at elevated risk. To evaluate the predictive performance of polygenic risk scores (PRS) for ADRD using a Bayesian variational autoencoders approach and to assess the modifying effects of age and We analyzed data from 276,566 unrelated individuals of European ancestry in the UK Biobank, with a median follow-up of 9.19 years. PRS and polygenic hazard scores (PHS) were constructed using genome-wide association study summary statistics, with PHS incorporating age-at-onset information. Three PRS methods were compared: DDML (Bayesian variational autoencoders), SBayesR (Bayesian multiple regression), and clumping and thresholding (C + T). Models were stratified by age and Among the participants (mean age 56.8 ± 8.0 years; 46.7% male), 1,328 (0.48%) developed ADRD. In covariate-adjusted models, DDML_PRS achieved the highest predictive accuracy (AUC = 0.847) in individuals aged 65–70 years. PHS models showed peak performance at 7 years of follow-up. DDML_PRS significantly improved classification in The DDML_PRS framework showed consistently higher discrimination than standard PRS baselines in this UK Biobank setting, particularly in older adults and The online version contains supplementary material available at 10.1186/s13195-026-02011-w. Show less

Epigenetic mechanisms are important in aging and may be involved in late-life changes in cognitive abilities. We conducted an epigenome-wide association study of leukocyte DNA methylation in relation to level and change in cognitive abilities, from midlife through late life in 535 Swedish twins. Methylation levels were measured with the Infinium Human Methylation 450 K or Infinium MethylationEPIC array, and all sites passing quality control on both arrays were selected for analysis (n = 250,816). Empirical Bayes estimates of individual intercept (age 65), linear, and quadratic change were obtained from latent growth curve models of cognitive traits and used as outcomes in linear regression models. Significant sites (p < 2.4 × 10 Leukocyte DNA methylation was associated with level, but not change in cognitive abilities. The associations were substantially attenuated in within-pair analyses, indicating they are influenced in part by genetic factors. Show less

High circulating low-density lipoprotein cholesterol (LDL-C) is a major risk factor for atherosclerosis and age-associated cardiovascular events. Long-term dyslipidaemia could contribute to the development of frailty in older individuals through its role in determining cardiovascular health and potentially other physiological pathways. We conducted Mendelian randomization (MR) analyses using genetic variants to estimate the effects of long-term LDL-C modification on frailty in UK Biobank (n = 378,161). Frailty was derived from health questionnaire and interview responses at baseline when participants were aged 40 to 69 years, and calculated using an accumulation-of-deficits approach, i.e. the frailty index (FI). Several aggregated instrumental variables (IVs) using 50 and 274 genetic variants were constructed from independent single-nucleotide polymorphisms (SNPs) to instrument circulating LDL-C concentrations. Specific sets of variants in or near genes that encode six lipid-lowering drug targets (HMGCR, PCSK9, NPC1L1, APOB, APOC3, and LDLR) were used to index effects of exposure to related drug classes on frailty. SNP-LDL-C effects were available from previously published studies. SNP-FI effects were obtained using adjusted linear regression models. Two-sample MR analyses were performed with the IVs as instruments using inverse-variance weighted, MR-Egger, weighted median, and weighted mode methods. To address the stability of the findings, MR analyses were also performed using i) a modified FI excluding the cardiometabolic deficit items and ii) data from comparatively older individuals (aged ≥60 years) only. Several sensitivity analyses were also conducted. On average 0.14% to 0.23% and 0.16% to 0.31% decrements in frailty were observed per standard deviation reduction in LDL-C exposure, instrumented by the general IVs consisting of 50 and 274 variants, respectively. Consistent, though less precise, associations were observed in the HMGCR-, APOC3-, NPC1L1-, and LDLR-specific IV analyses. In contrast, results for PCSK9 were in the same direction but more modest, and null for APOB. All sensitivity analyses produced similar findings. A genetically-predicted life-long lowering of LDL-C is associated with decreased frailty in midlife and older age, representing supportive evidence for LDL-C's role in multiple health- and age-related pathways. The use of lipid-lowering therapeutics with varying mechanisms of action may differ by the extent to which they provide overall health benefits. Show less