Biology subjects

Beekman, M.

Publications and source records attributed to Beekman, M..

16 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

Penalized reduced rank regression for multi-outcome survival data supports a common metabolic risk score for age-related diseases

The increasing availability of multi-outcome data in health research presents new opportunities for understanding complex health processes, such as ageing. Ageing is a multifaceted process, encompassing both lifespan and healthspan, as well as the onset of age-related diseases. To model this complexity, we propose the penalized reduced rank regression model for multi-outcome survival data (penalized survRRR), which identifies shared latent factors driving multiple outcomes. The model imposes a rank constraint on the coefficient matrix to capture underlying mechanisms of ageing, while accommodating high-dimensional and correlated predictors and outcomes by introducing penalization. We discuss the statistical properties of this doubly-regularized approach and show how the optimal number of ranks can be estimated from the data. We apply a lasso-penalized reduced rank regression model to 78,553 participants of the UK Biobank, using over 200 metabolic variables as predictors and the onset of seven age-related diseases and mortality as the outcomes of interest. Our results indicate that a rank 1 model provides the best fit to the data, resulting in a single metabolite-based score of age-related disease susceptibility. This highlights the potential of the penalized survRRR model to provide new insights into the nature of the relationship between metabolomics and age-related diseases.

molecular biology↗

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

Deformed wing virus genotypes A and B do not elicit immunologically different responses in naive honey bee hosts

Deformed wing virus (DWV), in association with Varroa destructor, is currently the leading factor associated with global honey bee deaths. With the exception of Australia, the virus and mite have a near global distribution, making it difficult to separate the effect of one from the other. Over time, the prevalence of the two main DWV genotypes (DWV-A and DWV-B) has changed, leading to the suggestion that the two strains elicit a different immune response by the host, the western honey bee Apis mellifera. Here we use a honey bee population naive to both the mite and the virus to investigate if honey bees show a different immunological response to DWV genotypes. We examined the expression of 19 immune genes by RT-qPCR and comprehensively analysed the small RNA response in honey bees after experimental injection with DWV-A and DWV-B. We found no evidence to indicate that DWV-A and DWV-B elicit a different immune response in honey bees. We found that RNA interference genes are up-regulated during DWV infection and that the small interfering RNA (siRNA) response is proportional to viral loads, yet does not inhibit the virus from accumulating to high loads. We also found that the siRNA response towards DWV was weaker than the response to another honey bee pathogen, Black queen cell virus. This suggests that DWV is comparatively better at evading antiviral host defences. There was no evidence for the production of virus-derived PIWI-RNAs in response to DWV infection. In contrast to previous studies, and in the absence of V. destructor, we found no evidence that DWV has an immunosuppressive effect in honey bees. Overall, our results advance our understanding of the immunological effect DWV elicits in honey bees.

immunology↗

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↗

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

Systematic evaluation of normalization methods for glycomics data based on performance of network inference

Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, we here quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms (LC-ESI-MS, UHPLC-FLD and MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the Probabilistic Quotient method followed by log-transformation, irrespective of the measurement platform.

bioinformatics↗

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

Lifestyle-intervention-induced reduction of abdominal fat is reflected by a decreased circulating glycerol level and an increased HDL diameter

SCOPEAbdominal obesity is one of the main modifiable risk factors of age-related cardiometabolic disease. Cardiometabolic disease risk and its associated high abdominal fat mass, high cholesterol and glucose concentrations can be reduced by a healthier lifestyle. Hence, our aim is to understand the relation between lifestyle-induced changes in body composition, and specifically abdominal fat, and accompanying changes in circulating metabolic biomarkers.\n\nMethods and resultsWe used the data from the Growing Old Together (GOTO) study, in which 164 older adults (mean age 63 years, BMI 23-35 kg/m2) changed their lifestyle during 13 weeks by 12.5% caloric restriction plus 12.5% increase in energy expenditure. We show that levels of circulating metabolic biomarkers, even after adjustment for body mass index, specifically associate with abdominal fat mass. Next, we show that the applied lifestyle intervention mainly reduces abdominal fat mass (-2.6%, SD=3.0) and that this reduction, when adjusted for general weight loss, is highly associated with decreased circulating glycerol concentrations and increased HDL diameter.\n\nConclusionsThe lifestyle-induced reduction of abdominal fat mass is particularly associated, independent of body mass index or general weight loss, with associated with decreased circulating glycerol concentrations and increased HDL diameter.

molecular biology↗

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

Genome-wide association study of plasma lipids

There is continuous interest in the genetic determinants of plasma triglycerides (TGs) and phospholipids and their role in the etiology of cardiovascular disease (CVD). Here, we report the results of a Dutch genome wide association study (GWAS) of an in-house developed lipidomics platform, focusing on 90 plasma lipids. Lipids were assessed by liquid chromatography mass spectrometry in participants from the Leiden Longevity Study, the Netherlands Twin Register and the Erasmus Rucphen Family (ERF) study and meta-analysed, resulting in a sample size of 5537 participants. In addition, we performed genetic correlation analyses between the 90 plasma lipids and markers of metabolic health, as well as vascular pathology and CVD combining our GWAS results with publicly available GWAS outputs. We replicated previously known associations between 34 lipids and 10 lipid quantitative trait loci (lipQTL) (GCKR, APOA1, FADS1, SGPP1,TMEM229B, LIPC, PDXDC1, CETP, CERS4 and SPTLC3) with metabolome-wide (P < 1.61 x 10-9) significance. Moreover, we report 6 novel phospholipid-related and 5 triglyceride (TG)-related loci: SGGP1 (SM21:0), SPTLC3 (SM21:0 and SM25:1), FADS1 (LPCO16:1, PC38:2, PEO36:5, PEO38:5, TG56:5, TG56:6, and TG56:7), TMEM229 (LPCO16:1), GCKR (TG50:2), and APOA1 (TG54:4). In addition, we report suggestively significant (P < 5 x 10-8) associations mapping to eleven novel lipid quantitative trait loci (lipQTLs), three of which are supported by mining previous GWAS data: MAU (PC34:4), LDLR (SM16:0), and MLXIPL (TG48:1 and TG50:1)). Genetic correlation analysis indicates that one specific specific sphingomyelin, SM22:0, shares common genetic background with CVD. Levels of SM22:0 also positively associate with carotid artery intima-media thickness in the ERF study, and this observation is independent of LDL-C level. Our findings yield higher resolution of plasma lipid species and new insights in the biology of circulating phosholipids and their relation to CVD risk.

epidemiology↗

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↗

bioRxiv2018

Vector-mediated viral transmission favours less virulent viruses

While it is well-established that the ectoparasitic mite Varroa destructor is largely responsible for the widely-reported decline of populations of the Western honeybee Apis mellifera, the exact role the mite plays in honeybee health remains unclear. The last few years have seen a surge in studies associating RNA viruses vectored by the mite with the death of honeybee colonies. Varroa facilitates the spread of RNA viruses because it feeds on developing bee brood and transfers haemolymph from bee-to-bee. Such a change in transmission, from horizontal and vertical to vector-based, is predicted to lead to an increase in virulence of RNA viruses, thus potentially providing an explanation for the observed association between Varroa and certain viruses. Here we document the effect of changing the route of transmission of honeybee viruses contained in the haemolymph of honeybee pupae. We find that a change in mode of transmission rapidly increases viral titres of two honeybee viruses, Sacbrood virus (SBV) and Black queen cell virus (BQCV). This increase in viral titre is accompanied by an increase in virulence. In contrast, the virus most often associated with Varroa, Deformed wing virus (DWV), shows a reduction in viral titre in the presence of SBV and BQCV. In addition, DWV does not cause mortality to honeybee pupae in isolation. Most likely a change in mode of transmission due to the arrival of a vector quickly eliminates the most virulent honeybee viruses resulting in an association between Varroa and less virulent viruses such as DWV. Our work therefore provides empirical evidence for an alternative explanation for the widely-observed association between Varroa and DWV.

evolutionary biology↗