Biology subjects

Hägg, S.

Publications and source records attributed to Hägg, S..

7 recordsLinked to original sources

bioRxiv2024

Biological aging of different blood cell types

A biological age (BA) indicator is intended to capture detrimental age-related changes occurring with passing time. To date, the best-known and used BA indicators include DNA-methylation-based epigenetic ages (epigenetic clocks) and telomere length. The most common biological sample material for epidemiological aging studies is composed of different cell types, whole blood. We aimed to compare differences in BAs between blood cell types and assessed BA indicators cell type-specific associations with donors calendar age. Analysis on DNA methylation-based BA indicators including telomere length, methylation level at cg16867657 (a CpG-site in ELOVL2) and the Hannum, Horvath, DNAmPhenoAge and DunedinPACE epigenetic clocks was performed in 428 biological samples from 12 blood cell types. BA values were different (p<0.05) in the majority of pairwise comparisons between the cell types. Most cell types also displayed differences as compared to whole blood (p<0.05). Some of the observed differences persisted across blood donors calendar ages from 20 to 80 years (50-years-difference in DNAmPhenoAge between naive CD4+ T cells and monocytes), while others did not (up to four-fold difference in DunedinPACE values between monocytes and B cells). All BA indicators, except DunedinPACE, had mostly a very strong correlation with donors calendar age within a cell type. Our findings demonstrate that DNA methylation-based indicators of biological age exhibit cell type-specific characteristics, underscoring the importance of accounting for cell composition in related studies. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and and provide guidance for utilizing them as indicators for success of aging interventions.

molecular biology↗

bioRxiv2022

Methylation status of VTRNA2-1/nc886 is stable across human populations, monozygotic twin pairs and in majority of somatic tissues

Aims and methodsOur aim was to characterise the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues. We utilised 48 datasets, consisting of >30 different tissues and >30 000 individuals. ResultsWe show that the nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, while [~]30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. ConclusionWe hypothesize that the nc886 imprint is established in the oocyte and that after implantation, the methylation status is stable, excluding a few specific tissues.

molecular biology↗

bioRxiv2019

Comprehensive longitudinal study of epigenetic mutations in aging

BackgroundThe role of DNA methylation in aging has been widely studied. However, epigenetic mutations, here defined as aberrant methylation levels compared to the distribution in a population, are less understood. Hence, we investigated longitudinal accumulation of epigenetic mutations, using 994 blood samples collected at up to five time points from 375 individuals in old ages.\n\nResultsWe verified earlier cross-sectional evidence on the increase of epigenetic mutations with age, and identified important contributing factors including sex, CD19+ B cells, genetic background, cancer diagnosis and technical artifacts. We further classified epigenetic mutations into High/Low Methylation Outliers (HMO/LMO) according to their changes in methylation, and specifically studied methylation sites (CpGs) that were prone to mutate (frequently mutated CpGs). We validated four epigenetically mutated CpGs using pyrosequencing in 93 samples. Furthermore, by using twins, we concluded that the age-related accumulation of epigenetic mutations was not related to genetic factors, hence driven by stochastic or environmental effects.\n\nConclusionsHere we conducted a comprehensive study of epigenetic mutation and highlighted its important role in aging process and cancer development.

genetics↗

bioRxiv2018

The frailty index is a predictor of cause-specific mortality independent of familial effects from midlife onwards

BackgroundFrailty index (FI) is a well-established predictor of all-cause mortality, but less is known for cause-specific mortality and whether familial effects influence the associations. Furthermore, the population mortality impact of frailty remains understudied.\n\nObjectivesTo estimate the predictive value of frailty for all-cause and cause-specific mortality, and to test whether the associations are time-dependent. We also assessed the proportion of deaths that are attributable to increased levels of frailty.\n\nMethodsWe analyzed 42,953 participants from the Screening Across the Lifespan Twin Study (aged 41-95 years at baseline) with up to 20-years mortality follow-up. The FI was constructed using 44 health-related items. Deaths due to cardiovascular disease (CVD), respiratory-related causes and cancer were considered in the cause-specific analysis. Generalized survival models were used in the analysis.\n\nResultsIncreased FI was associated with higher risks of all-cause, CVD, and respiratory-related mortality. No significant associations were observed for cancer mortality. No attenuation of the mortality associations was found in unrelated individuals when adjusting for familial effects in twin pairs. The associations were time-dependent with relatively greater effects observed in younger ages. The proportion of deaths attributable to FI levels >0.10 were 13.0% of all-cause deaths, 14.7% of CVD deaths and 12.5% of respiratory-related deaths in men, and 12.2% of all-cause deaths, 9.9% of CVD deaths and 21.9% of respiratory-related deaths in women.\n\nConclusionsIncreased FI predicts higher risks of all-cause, CVD, and respiratory-related mortality independent of familial effects. Increased FI levels have a significant population mortality impact in both men and women.

epidemiology↗

bioRxiv2018

Levels of histidine-rich glycoprotein in human blood predict accelerated aging

1.Despite recognizing aging as risk factor of human diseases, little is still known about the molecular traits of biological age and mortality risk. To identify age-associated proteins circulating human blood, we screened 156 subjects aged 50-92 years using an exploratory and multiplexed affinity proteomics approach. We corroborated the top age-associated protein profile (adjusted P < 0.001) in eight additional study sets (N = 4,044 individuals), and confirmed a consistent age-associated increase (P = 6.61 x 10-6) by meta-analysis. Applying antibody validation determined circulating histidine-rich glycoprotein (HRG) as the target, and we observed that sequence variants influenced the antibodies ability to bind to the protein. Profiles of circulating HRG were associated to several clinical traits and predicted the risk of mortality during a follow-up period of 8.5 years (IQR = 7.7-9.3 years) after blood sampling (HR = 1.25 per SD; 95% CI = 1.12-1.39; P = 7.41 x 10-5). In conclusion, our affinity proteomics analysis found associations between the molecular traits of circulating HRG with age and all-cause mortality. This suggests that the profiles of multi-purpose protein HRG could serve as an accessible indicator of physiological processes related to aging.

epidemiology↗

bioRxiv2017

Epigenetic influences on aging: a longitudinal genome-wide methylation study in old Swedish twins

Age-related changes in DNA methylation have been observed in many cross-sectional studies, but longitudinal evidence is still very limited. Here, we aimed to characterize longitudinal age-related methylation patterns (Illumina HumanMethylation450 array) using 1011 blood samples collected from 385 old Swedish twins (mean age of 69 at baseline) up to five times over 20 years. We identified 1316 age-associated methylation sites (p<1.3x10-7) using a longitudinal epigenome-wide association study design. We measured how estimated cellular compositions changed with age and how much they confounded the age effect. We validated the results in two independent longitudinal cohorts, where 118 CpGs were replicated in PIVUS (p<3.9x10-5) and 594 were replicated in LBC (p<5.1x10-5). Functional annotation of age-associated CpGs showed enrichment in CCCTC-binding factor (CTCF) and other unannotated transcription factor binding sites. We further investigated genetic influences on methylation (methylation quantitative trait loci) and found no interaction between age and genetic effects in the 1316 age-associated CpGs. Moreover, in the same CpGs, methylation differences within twin pairs increased over time, where monozygotic twins had smaller intra-pair differences than dizygotic twins. We show that age-related methylation changes persist in a longitudinal perspective, and are fairly stable across cohorts. Moreover, the changes are under genetic influence, although this effect is independent of age. In addition, inter-individual methylation variations increase over time, especially in age-associated CpGs, indicating the increase of environmental contributions on DNA methylation with age.

genetics↗

bioRxiv2017

GWAS meta-analysis (N=279,930) identifies new genes and functional links to intelligence

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present the largest genetic association study of intelligence to date (N=279,930), identifying 206 genomic loci (191 novel) and implicating 1,041 genes (963 novel) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and identify 89 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain and specifically in striatal medium spiny neurons and cortical and hippocampal pyramidal neurons. Gene-set analyses implicate pathways related to neurogenesis, neuron differentiation and synaptic structure. We confirm previous strong genetic correlations with several neuropsychiatric disorders, and Mendelian Randomization results suggest protective effects of intelligence for Alzheimers dementia and ADHD, and bidirectional causation with strong pleiotropy for schizophrenia. These results are a major step forward in understanding the neurobiology of intelligence as well as genetically associated neuropsychiatric traits.

genetics↗