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Heterogeneous accumulation of senescent cells expressing the senescence-associated secretory phenotype (SASP) affects tissue homeostasis which leads to diseases, such as osteoarthritis (OA). In this study, we set out to characterize heterogeneity of cellular senescence within aged articular cartilage and explored the presence of corresponding metabolic profiles in blood that could function as representative biomarkers. Hereto, we set out to perform cluster analyses, using a gene-set of 131 senescence genes (N= 57) in a previously established RNA sequencing dataset of aged articular cartilage and a generated metabolic dataset in overlapping blood samples. Using unsupervised hierarchical clustering and pathway analysis, we identified two robust cellular senescent endotypes. Endotype-1 was enriched for cell proliferating pathways, expressing forkhead box protein O4 (FOXO4), RB transcriptional corepressor like 2 (RBL2), and cyclin-dependent kinase inhibitor 1B (CDKN1B); the FOXO mediated cell cycle was identified as possible target for endotype-1 patients. Endotype-2 showed enriched inflammation-associated pathways, expressed by interleukin 6 (IL6), matrix metallopeptidase (MMP)1/3, and vascular endothelial growth factor (VEGF)C and SASP pathways were identified as possible targets for endotype-2 patients. Notably, plasma-based metabolic profiles in overlapping blood samples (N= 21) showed two corresponding metabolic clusters in blood. These non-invasive metabolic profiles could function as biomarkers for patient-tailored targeting of senescence in OA.

Circulating cell-free DNA (cf-DNA) has emerged as a promising biomarker of ageing, tissue damage and cellular stress. However, less is known about health behaviours, ageing phenotypes and metabolic processes that lead to elevated cf-DNA levels. We sought to analyse the relationship of circulating cf-DNA level to age, sex, smoking, physical activity, vegetable consumption, ageing phenotypes (physical functioning, the number of diseases, frailty) and an extensive panel of biomarkers including blood and urine metabolites and inflammatory markers in three human cohorts (N = 5385; 17–82 years). The relationships were assessed using correlation statistics, and linear and penalised regressions (the Lasso), also stratified by sex.

Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.

Background: Resistance to activated protein C (APC), which results from various factors, including a mutation in the gene for coagulant factor V, has been associated with increased risk for venous thrombosis. However, its relation to arterial disease is still not well defined. Objective: To investigate the association of both response to APC and the factor V Leiden mutation with arterial disease. Design: Population-based case-control study. Setting: A district of Rotterdam, the Netherlands. Participants: 115 patients with a history of myocardial infarction; 112 patients with a history of stroke, transient ischemic attack, or both; and 222 age-matched controls without arterial disease chosen from among 7983 persons in the Rotterdam Study cohort. Patients using anticoagulant drugs were excluded. Measurements: Response to APC was determined in double-centrifuged platelet-poor plasma. Patients were genotyped for the Arg 506 to Gln mutation in the gene for coagulant factor V. Results: The prevalence of cerebrovascular disease increased gradually and corresponded to a decreasing response to APC (odds ratio per 1-unit decrease of response to APC, 1.43 [95% CI, 1.12 to 1.81], adjusted for age and sex). Adjustment for the factor V mutation did not change the findings. We found no association between response to APC and myocardial infarction or between factor V mutation and cerebrovascular disease or myocardial infarction. Conclusions: Low response to APC is associated with an increased risk for cerebrovascular disease but not with an increased risk for myocardial infarction, independent of the factor V Leiden mutation. The association between the factor V Leiden mutation and cerebrovascular disease or myocardial infarction remains to be determined., A decreased response to activated protein C (APC) may be linked with a greater risk for stroke but not heart attack. APC inhibits blood clotting and a deficiency can cause excessive clotting. Researchers measured the response to APC blood samples from 227 men and women with a history of stroke or heart attack and compared the results to 222 healthy volunteers. The response to APC was lower in those with a history of stroke but not in those with a history of heart attack. This was true regardless of whether they had a mutation in the factor V gene.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

Mobile elements are major drivers in changing genomic architecture and can cause disease. The detection of mobile elements is hindered due to the low mappability of their highly repetitive sequences. We have developed an algorithm, called Mobster, to detect non-reference mobile element insertions in next generation sequencing data from both whole genome and whole exome studies. Mobster uses discordant read pairs and clipped reads in combination with consensus sequences of known active mobile elements. Mobster has a low false discovery rate and high recall rate for both L1 and Aluelements. Mobster is available at http://sourceforge.net/projects/mobster.

Joint health is affected by local and systemic hormones. It is well accepted that systemic factors regulate the metabolism of joint tissues, and that substantial cross-talk between tissues actively contributes to homeostasis. In the current review, we try to define a subtype of osteoarthritis (OA), metabolic OA, which is dependent on an unhealthy phenotype.

This study aimed to test the association between the Val158Met polymorphism (rs4680) of the catechol-O-methyl transferase gene and anorexia nervosa (AN).

The contribution of genetics to osteoarthritis (OA) progression is not known. To gain more insight into whether familial factors play a role in disease progression of OA, we analyzed familial aggregation of radiologic OA progression in a study of sibling pairs (the Genetics, Arthrosis, and Progression [GARP] study).A total of 105 white probands and their 105 siblings with OA at multiple joint sites were included in a prospective cohort study. Radiologic progression of OA was defined as a 1‐point score increase in total scores for severity of joint space narrowing (JSN) or osteophytes on standardized radiographs of the hands, knees, and hips obtained at baseline and after 2 years. Odds ratios were calculated for siblings and probands sharing radiologic disease progression.A total of 100 probands and 93 siblings were followed for 2 years (median age 60 years, 80% women). In 92 sibling pairs both the proband and sibling had complete radiographic followup. Radiologic progression of JSN and osteophytes was present in 47% and 42% of the probands and 34% and 37% of the siblings, respectively. The odds ratios (95% confidence intervals), adjusted for age, sex, and body mass index, of a sibling having radiologic progression if the proband had progression were 3.0 (1.2–7.8) for JSN progression and 1.5 (0.6–3.6) for osteophyte progression. A dose‐response relationship was found between the amount of increase in JSN total scores among probands and the progression of JSN in siblings.Familial factors played a role in the radiologic progression of JSN over 2 years in patients with OA at multiple sites.

Objective. Patients with insulin‐dependent diabetes mellitus (IDDM) have a high risk of developing diabetic nephropathy, retinopathy and cardiovascular diseases. The contribution of gene polymorphisms of the renin angiotensin system to these complications is controversial and may differ among populations.Methods. In 257 Dutch IDDM patients (188 with urinary albumin excretion (UAE) [lt ]30 mg/24 h), logistic regression analysis was used to study the relationships among, on the one hand, the insertion/deletion gene polymorphism of the angiotensin‐converting enzyme gene (ACE‐ID), the M235T gene polymorphism of the angiotensinogen gene (AGT‐M235T), and the A1166C gene polymorphism of the angiotensin type 1 receptor gene (AT1‐A1166C), and, on the other hand, UAE, retinopathy, hypertension, and coronary heart disease.Results. The T‐allele of the AGT‐M235T polymorphism was associated with an increased risk of an elevated UAE (odds ratio (OR) 3.03; 95% confidence interval (CI) 1.06–8.61), but only when interaction with the D‐allele of the ACE‐ID polymorphism was considered. A previously described positive interaction between the T‐allele of the AGT‐M235T polymorphism and the D‐allele of the ACE‐ID polymorphism could not be confirmed. The T‐allele was also associated with an increased risk of retinopathy (OR 3.89, 95% CI 1.79–8.47). The CC‐genotype of the AT1‐A1166C polymorphism was associated with hypertension (OR 3.58; 95% CI 1.23–10.37).Conclusions. In a Dutch IDDM population, including 69 patients with (incipient) diabetic nephropathy, the T‐allele of the AGT‐M235T polymorphism is associated with an elevated UAE and diabetic retinopathy and the CC‐genotype of the AT1‐A1166C polymorphism is associated with hypertension. A previously described interaction between the AGT‐M235T and the ACE‐ID polymorphisms could not be confirmed. Since the number of nephropathic patients in this study is small, these conclusions must be interpreted with caution.