Biology subjects

Slagboom, P. E.

Publications and source records attributed to Slagboom, P. E..

15 recordsLinked to original sources

bioRxiv2026

Rare genetic variants in the IIS/mTOR signalling pathway identified in exceptionally long-lived individuals show shared in vitro effects associated with lifespan across species

BackgroundThe increase in human lifespan without a proportional increase in healthspan imposes a substantial burden on individuals and society. Exceptionally long-lived individuals and members of long-lived families exhibit compression of multi-morbidity. Genetics, and in particular rare protein-altering variants, appear to play an important role in their longevity. MethodsIn this study, we employed a targeted pathway approach to provide functional evidence of the significance of rare variants in the insulin/insulin-like growth factor 1 signalling - mechanistic target of rapamycin (IIS/mTOR) signalling pathway identified in long-lived individuals. To this end, we used CRISPR/Cas9 to introduce these rare genetic variants into mouse embryonic stem cells (mESCs). We subsequently assessed several functional readouts that have previously been associated with lifespan regulation in model organisms and/or IIS/mTOR and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) signalling pathway activity. ResultsFunctional characterisation revealed that the variants exhibit both shared and distinct effects on the signalling pathways. Principal component analysis of omics-based datasets showed that the variants clustered into two groups, a distribution that corresponds with the grouping observed for a subset of functional readouts. All variant mESC lines exhibited a downregulation in IIS/mTOR and MAPK/ERK signalling pathway activity as well as an increase in Foxo3 expression and FOXO3 binding activity. We identified alterations in lipid and mitochondrial metabolism, including a reduction in mitochondrial DNA levels, which were mostly shared among all variants. All variant mESC lines exhibited a signature implying increased pluripotency. The effects on stress resistance and growth rate diverged between the two variant groups, with partially opposing effects. Group 1 demonstrated a reduced growth rate and increased resistance to a subset of stressors, while Group 2 demonstrated an increased growth rate and reduced resistance to a subset of stressors. ConclusionsHere, we provide evidence that rare genetic variants in the IIS/mTOR and MAPK/ERK signalling pathways identified in long-lived human individuals result in shared functional effects associated with longevity in model organisms. These insights can serve as a foundation to better understand the role of rare variants in the insulin signalling network in the regulation of human longevity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/728260v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1ef36c3org.highwire.dtl.DTLVardef@1f44c96org.highwire.dtl.DTLVardef@1d0150forg.highwire.dtl.DTLVardef@16ab7d_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2025

Rare longevity-associated variants, including a reduced-function mutation in cGAS, identified in multigenerational long-lived families

Life expectancy has steadily increased in the last two centuries, while healthspan has been lagging behind. Survival into extreme ages strongly clusters within families which often exhibit a delayed onset of (multi)morbidity, yet the underlying protective genetic mechanisms are still largely undefined. We performed affected sib-pair linkage analysis in 212 sibships enriched for ancestral longevity and identified four genomic regions (LODmax [≥]3.0) at 1q21.1, 6p24.3, 6q14.3, and 19p13.3. Within these regions, we prioritized 12 rare protein-altering variants in seven candidate genes (NUP210L, SLC27A3, CD1A, CGAS, IBTK, RARS2, and SH2D3A) located in longevity-associated loci. Notably, a missense variant in CGAS (rs200818241), was present in two sibships. Using human- and mouse-based cell models, we showed that rs200818241 reduced protein stability and attenuated activation of the canonical cGAS-STING pathway in a cell-type specific manner. This dampened signalling mitigated inflammation and delayed cellular senescence, mechanisms that may contribute to the survival advantage of CGAS variant carriers. Our findings indicate novel rare variants and candidate genes linked to familial longevity and highlight the cGAS-STING pathway as a potential contributor to the protective mechanisms underlying human longevity.

genetics↗

bioRxiv2024

DNA methylation and gene expression trajectories of human postprandial metabolism

Human postprandial metabolism is characterised by a highly individualised response to food that is predictive of cardiometabolic health and underexplored at the molecular level. We profiled blood DNA methylation (DNAm) and gene expression trajectories before and after a test meal in 225 European participants. We identify DNAm changes at fasting, 30 minutes and 4 hours after meal challenge, including in metabolically relevant genes INPP4A, GHRL, ASIP and ABCG1, with changes observed as early as 30mins postprandially. Gene expression trajectories also changed postprandially predominantly at 4 hours, with replication of lipid metabolism (CPT1A) and circadian rhythm (PER1) genes. Genetic variants affect postprandial molecular trajectories at genes linked to obesity (PDE9A) and glucose response (GPT2). Multiple signals associated with postprandial glucose and triglyceride levels, with replication of CPT1A methylation. The postprandial DNAm and expression trajectories target metabolically relevant genes, giving insights towards mechanisms underlying inter-individual response to food and cardiometabolic disease risk.

genomics↗

bioRxiv2023

The AccelerAge framework: A new statistical approach to predict biological age based on time-to-event data

Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the "AccelerAge" framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individuals survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individuals aging status.

molecular biology↗

bioRxiv2023

Functional characterisation of rare variants in genes encoding the MAPK/ERK signalling pathway identified in long-lived Leiden Longevity Study participants

Human longevity, which is coupled to a compression of age-related disease, has been shown to be heritable. However, the number of identified common genetic variants linked to this trait remains small. This may indicate that longevity is, at least to some extent, determined by rare genetic variants that are potentially family-specific. We therefore investigated whole-genome sequencing data of long-lived families from the Leiden Longevity Study for family-specific variants. We identified variants residing in genes involved in the mitogen-activated protein kinase (MAPK) cascade, a lifespan-associated and evolutionarily conserved pathway emerging from studies in model organisms. We subsequently generated mouse embryonic stem cells (mESCs) harbouring these variants and conducted in vitro functional characterisation. Two variants, located in NF1 (Phe1112Leu) and RAF1 (Asp633Tyr), reduce MAPK/extracellular signal-regulated kinase (ERK) signalling pathway activity in mESCs. At the proteomic and transcriptomic level, we observed prominent changes that were shared (e.g. up-regulation of the ribosome) and opposing between the variants (e.g. down-regulation of mTORC1 signalling in the RAF1Asp633Tyr variant cell line versus up-regulation in the NF1Phe1112Leu variant cell lines). These metabolic changes were accompanied by an opposing effect of the variants on proliferation. Moreover, the RAF1Asp633Tyr variant improved resistance to replication stress, while this was not the case for the NF1Phe1112Leu variant. In conclusion, we identified two rare genetic variants in long-lived families that influence MAPK/ERK signalling in a manner that has previously been linked to increased lifespan in model organisms. Interestingly, we also observe some opposing and diverging effects between the variants, which indicates that they may either have some pleiotropic effects that are not relevant to longevity or that they target slightly different mechanisms to elicit their effects in mESCs. Our findings suggest that mESCs offer a good starting point for in vitro characterisation of rare genetic variants linked to human longevity and can be used to assess which of these variants to take forward to in vivo studies in model organisms.

genetics↗

bioRxiv2023

Clarifying the biological and statistical assumptions of cross-sectional biological age predictors

There is variability in the rate of aging among people of the same chronological age. The concept of biological age is postulated to capture this variability, and hence to better represent an individuals true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference between chronological and predicted biological age is informative of ones chronological age-independent rate of aging {Delta}. We show that the most popular cross-sectional biological age predictors--based on multiple linear regression, the Klemera-Doubal method or principal component analysis--rely on the same strong underlying assumption, namely that a candidate marker of agings association with chronological age is directly informative of its association with the aging rate {Delta}. We call this the identical-association assumption and prove that it is untestable in a cross-sectional setting. Using synthetic data, we illustrate the consequences if the assumption does not hold: in such scenarios, there is no guarantee that the weights that a cross-sectional method assigns to candidate markers are informative of the underlying truth. Using real data we illustrate that the extent to which the identical-association assumption holds is of direct practical relevance for anyone interested in developing or interpreting cross-sectional biological age predictors.

molecular biology↗

bioRxiv2022

Increasing number of long-lived ancestors associates with up to a decade of healthspan extension and a healthy metabolomic profile in mid-life

Globally, the lifespan of populations increases but the healthspan is lagging behind. Previous research showed that survival into extreme ages (longevity) clusters in families as illustrated by the increasing lifespan of study participants with each additional long-lived family member. Here we investigate whether the healthspan in such families follows a similar quantitative pattern using three-generational data from two databases, LLS (Netherlands), and SEDD (Sweden). We study healthspan in 2,143 families containing index persons and two ancestral generations, comprising 17,539 persons with 25 follow-up years. Our results provide strong evidence that an increasing number of long-lived ancestors associates with up to a decade of healthspan extension. Further evidence indicates that members of long-lived families have a delayed onset of medication use, multimorbidity and, in mid-life, healthier metabolomic profiles than their partners. We conclude that in longevity families, both lifespan and healthspan are quantitatively linked to ancestral longevity, making such families highly suitable to identify protective mechanisms of multimorbidity.

molecular biology↗

bioRxiv2022

Metabolic predictors of phenotypic traits can replace and complement measured clinical variables in transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) can provide valuable insights into biological and disease-underlying mechanisms. For studying clinical effects, availability of (confounding) phenotypic traits is essential. The (re)use of RNA-seq or other omics data can be limited by missing, incomplete, or inaccurate phenotypic information. A possible solution are molecular predictors inferring clinical or behavioral phenotypic traits. Such predictors have been developed based on different omics data types and are being applied in various studies. In this study, we applied 17 metabolic predictors to infer various traits, including diabetes status or exposure to lipid medication. We evaluated whether these metabolic surrogates can be used as an alternative to reported information for studying the respective phenotypes using TWAS. Our results revealed that in most cases, the use of metabolic surrogates yields similar results compared to using reported information, making them suitable substitutes for such studies. The application of metabolomics-derived surrogate outcomes opens new possibilities for reuse of multi-omics data sets, especially in situations where availability of clinical metadata is limited. Missing or incomplete information can be complemented by these surrogates, thereby increasing the size of available data sets. Studies would likely also benefit from the use of such surrogates to correct for potential biological confounding. This should be further investigated. Author summaryTranscriptome-wide association studies (TWAS) can be used to associate gene expression levels with phenotypic traits. These associations can provide insights into biological mechanisms including those that underlie diseases. Such studies require molecular profiling data from a large number of individuals as well as information on the phenotypic trait of interest. Biobanks that collect samples and corresponding molecular data, also collect information on phenotypic traits or clinical information. However, this information can be heterogeneous and/or incomplete, or a certain piece of information could be missing entirely. In this study, we apply metabolic predictors to infer various traits, including diabetes status or exposure to lipid medication. We evaluate whether these metabolic surrogates can be used as an alternative to reported information for studying the respective phenotypes using TWAS. Our results reveal that in many cases, the use of metabolic surrogates yields similar results compared to using reported information, making them suitable substitutes for such studies. The possibility of using these surrogate outcomes can thus increase the size of data sets for studies where phenotypic information is incomplete or missing.

bioinformatics↗

bioRxiv2021

A combined lifestyle intervention induces a sensitization of the blood transcriptomic response to a nutrient challenge

The global population is growing older. As age is a primary risk factor of (multi)morbidity, there is a need for novel indicators to predict, track, treat and prevent the development of disease. Lifestyle interventions have shown promising results in improving the health of participants and reducing the risk for disease, but in the elderly population, such interventions often show less reliable or subtle effects on health outcomes. This is further complicated by a poor understanding of the homeodynamics and the molecular effects of lifestyle interventions, by which their effects of a lifestyle intervention remain obscured. In the Growing Old Together (GOTO) study, we examined the responses of 164 healthy, elderly men and women to a 13-week combined physical and dietary lifestyle intervention. In addition to collecting blood samples at a fasted state, we sampled blood also 30 minutes following a standardized meal. This allows us to investigate an intervention response not only in the traditional fasted state, but also in the blood metabolic and cellular responses to a nutrient challenge. We investigated the transcriptomic and metabolomic responses to this nutrient challenge, how these responses relate to each other, and how this response is affected by the lifestyle intervention. We find that the intervention has very little effect on the fasted blood transcriptome, but that the nutrient challenge induces a large translational inhibition, and an innate immune activation, which together comprise a cellular stress response that is stimulated by the intervention. A sex-specific analysis reveals that although the same set of genes respond in the same direction in both males and females, the magnitude of these effects differ, and are modulated differently by the intervention. On the other hand, the metabolomic response to the nutrient challenge is largely unaffected by the intervention, and the correlation between the metabolomic nutrient response and transcriptomic modules indicates that the change in transcriptomic response to the nutrient challenge is independent from a change in cellular metabolomic environment. This work constitutes a glance at the acute transcriptomic stress response to nutrient intake in blood, and how a lifestyle intervention affects this response in healthy elderly, and may lead to the development of novel biomarkers to capture the phenotypic flexibility of health.

molecular biology↗

bioRxiv2019

Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identified 818 genes that influence DNA methylation patterns in blood using large-scale population genomics data. By employing genetic instruments as causal anchors, we identified directed associations between gene expression and distant DNA methylation levels, whilst ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. We found that DNA methylation patterns are commonly shaped by transcription factors that consistently increase or decrease DNA methylation levels. However, we also observed genes encoding proteins without DNA binding activity with widespread effects on DNA methylation (e.g. NFKBIE, CDCA7(L) and NLRC5) and we suggest plausible mechanisms underlying these findings. Many of the reported genes were unknown to influence DNA methylation, resulting in a comprehensive resource providing insights in the principles underlying epigenetic regulation.

genomics↗

bioRxiv2019

Intergenerational transmission of longevity is not affected by other familial factors: Evidence from 16,905 Dutch families from Zeeland, 1812-1962

Studies have shown that long-lived individuals seem to pass their survival advantage on to their offspring. Offspring of long-lived parents had a lifelong survival advantage over individuals without long-lived parents, making them more likely to become long-lived themselves. We test whether the survival advantage enjoyed by offspring of long-lived individuals is explained by environmental factors. 101,577 individuals from 16,905 families in the 1812-1886 Zeeland cohort were followed over time. To prevent that certain families were overrepresented in our data, disjoint family trees were selected. Offspring was included if the age at death of both parents was known. Our analyses show that multiple familial resources are associated with survival within the first 5 years of life, with stronger maternal than paternal effects. However, between ages 5 and 100 both parents contribute equally to offsprings survival chances. After age 5, offspring of long-lived fathers and long-lived mothers had a 16-19% lower chance of dying at any given point in time than individuals without long-lived parents. This survival advantage is most likely genetic in nature, as it could not be explained by other, tested familial resources and is transmitted equally by fathers and mothers.

genetics↗

bioRxiv2019

A NINE-YEAR LONGITUDINAL STUDY IN THE BLOOD OF A SUPERCENTENARIAN REVEALS AN EXTENSIVE SUBCLONAL ARCHITECTURE AND ONGOING SUBCLONAL DYNAMICS

The aged hematopoietic system is characterized by decreased immuno-competence and by a reduced number of hematopoietic stem cells (HSCs) that actively generates new blood cell (age-related clonal hematopoiesis, ARCH). While both aspects are commonly associated with an increased risk of aging-related diseases, it is currently unknown to what extent these aspects co-occur during exceptional longevity. Here, we investigated these aspects in blood cells of an immuno-hematopoietically normal female who reached 111 years. Blood samples were collected across a 9-year period at ages 103, 110 and 111 years. We applied several genetic sequencing approaches to investigate clonality in peripheral blood samples and sorted cell subsets. Immuno-competence was characterized using flow cytometry, T-cell receptor excision circle (TREC) assays, and in vitro proliferation assays. We identified a single DNMT3A-mutated HSC clone with a complex subclonal architecture and observed ongoing subclonal dynamics within the 9-year timeframe of our sampling. The mutated HSC generated 78-87% myeloid cells, 6-7% of the B-cells, 6% of CD8+ T-cells, and notably 22% of the CD4+ T-cells. Intriguingly, we found that T-cells were capable of robust proliferation when challenged in vitro. Moreover, we observed a surprisingly high TREC content, indicative of recent generation of naive T-cells. Concluding, we observed long-term stability of extreme ARCH with ongoing clonal dynamics combined with functional T-cell immunity. Our results indicate that extreme ARCH does not compromise immuno-competence and that a clonally expanded CD4+ T-cell subset may serve as a potential hallmark of the supercentenarian immune system. Key pointsO_LILongitudinal blood sampling from a female aged 103-111 revealed a dynamic clonal hematopoiesis contributing to myeloid and lymphoid subsets C_LIO_LIDespite the highly advanced age and extreme clonal hematopoiesis we observed functional T-cell immunity C_LI

immunology↗

bioRxiv2019

The genomic architecture of blood metabolites based on a decade of genome-wide analyses

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes and lipid species. We performed a review of all genetic association studies, and identified > 800 class-specific metabolite loci that influence metabolite levels. In a twin-family cohort (N = 5,117), these metabolite loci were leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study revealed significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation had higher h2Metabolite-hits estimates than phosphatidylcholines with a low degree of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes and lipid species.

genetics↗

bioRxiv2019

Longevity Relatives Count score defines heritable longevity carriers and suggest case improvement in genetic studies

AbstractLongevity loci represent key mechanisms of a life-long decreased mortality and decreased/compressed morbidity. However, identifying such loci is challenging. One of the most plausible reasons is the uncertainty in defining long-lived cases with the heritable longevity trait amongst long-living phenocopies. To avoid phenocopies, family selection scores have been constructed but these have not yet been adopted as state of the art in longevity research. Here we aim to identify individuals with the heritable longevity trait by using current insights and a novel family score based on these insights. We use a unique dataset connecting living study participants to their deceased ancestors covering 37,825 persons from 1,326 five-generational families, living between 1788 and 2019. Our main finding suggests that longevity is transmitted for at least 2 subsequent generations only when at least 20% of all relatives are long-lived. This proves the importance of family data to avoid phenocopies in genetic studies.

genetics↗

bioRxiv2018

Longevity defined as top 10% survivors is transmitted as a quantitative genetic trait: results from large three-generation datasets

Survival to extreme ages clusters within families. However, identifying genetic loci conferring longevity and low morbidity in such longevous families is challenging. There is debate concerning the survival percentile that best isolates the genetic component in longevity. Here, we use three-generational mortality data from two large datasets, UPDB (US) and LINKS (Netherlands). We studied 21,046 unselected families containing index persons, their parents, siblings, spouses, and children, comprising 321,687 individuals. Our analyses provide strong evidence that longevity is transmitted as a quantitative genetic trait among survivors up to the top 10% of their birth cohort. We subsequently showed a survival advantage, mounting to 31%, for individuals with top 10% surviving first and second-degree relatives in both databases and across generations, even in the presence of non-longevous parents. To guide future genetic studies, we suggest to base case selection on top 10% survivors of their birth cohort with equally long-lived family members.

genetics↗