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 individual's 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 individual's aging status.

Improved selection of participants in genetic longevity studies: family scores revisited.

BACKGROUND: Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data. METHODS: We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN). RESULTS: Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score . CONCLUSIONS: Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.

Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis.

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10-8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies.

Meta-analysis of 65,734 individuals identifies TSPAN15 and SLC44A2 as two susceptibility loci for venous thromboembolism.

Venous thromboembolism (VTE), the third leading cause of cardiovascular mortality, is a complex thrombotic disorder with environmental and genetic determinants. Although several genetic variants have been found associated with VTE, they explain a minor proportion of VTE risk in cases. We undertook a meta-analysis of genome-wide association studies (GWASs) to identify additional VTE susceptibility genes. Twelve GWASs totaling 7,507 VTE case subjects and 52,632 control subjects formed our discovery stage where 6,751,884 SNPs were tested for association with VTE. Nine loci reached the genome-wide significance level of 5 × 10(-8) including six already known to associate with VTE (ABO, F2, F5, F11, FGG, and PROCR) and three unsuspected loci. SNPs mapping to these latter were selected for replication in three independent case-control studies totaling 3,009 VTE-affected individuals and 2,586 control subjects. This strategy led to the identification and replication of two VTE-associated loci, TSPAN15 and SLC44A2, with lead risk alleles associated with odds ratio for disease of 1.31 (p = 1.67 × 10(-16)) and 1.21 (p = 2.75 × 10(-15)), respectively. The lead SNP at the TSPAN15 locus is the intronic rs78707713 and the lead SLC44A2 SNP is the non-synonymous rs2288904 previously shown to associate with transfusion-related acute lung injury. We further showed that these two variants did not associate with known hemostatic plasma markers. TSPAN15 and SLC44A2 do not belong to conventional pathways for thrombosis and have not been associated to other cardiovascular diseases nor related quantitative biomarkers. Our findings uncovered unexpected actors of VTE etiology and pave the way for novel mechanistic concepts of VTE pathophysiology.

Secondary phenotype analysis in ascertained family designs: application to the Leiden longevity study.

The case-control design is often used to test associations between the case-control status and genetic variants. In addition to this primary phenotype, a number of additional traits, known as secondary phenotypes, are routinely recorded, and typically, associations between genetic factors and these secondary traits are studied too. Analysing secondary phenotypes in case-control studies may lead to biased genetic effect estimates, especially when the marker tested is associated with the primary phenotype and when the primary and secondary phenotypes tested are correlated. Several methods have been proposed in the literature to overcome the problem, but they are limited to case-control studies and not directly applicable to more complex designs, such as the multiple-cases family studies. A proper secondary phenotype analysis, in this case, is complicated by the within families correlations on top of the biased sampling design. We propose a novel approach to accommodate the ascertainment process while explicitly modelling the familial relationships. Our approach pairs existing methods for mixed-effects models with the retrospective likelihood framework and uses a multivariate probit model to capture the association between the mixed type primary and secondary phenotypes. To examine the efficiency and bias of the estimates, we performed simulations under several scenarios for the association between the primary phenotype, secondary phenotype and genetic markers. We will illustrate the method by analysing the association between triglyceride levels and glucose (secondary phenotypes) and genetic markers from the Leiden Longevity Study, a multiple-cases family study that investigates longevity. © 2017 The Authors. Statistics in Medicine Published by JohnWiley & Sons Ltd.

An alternative approach to multiple testing for methylation QTL mapping reduces the proportion of falsely identified CpGs.

INTRODUCTION: An increasing number of studies investigates the influence of local genetic variation on DNA methylation levels, so-called in cis methylation quantitative trait loci (meQTLs). A common multiple testing approach in genome-wide cis meQTL studies limits the false discovery rate (FDR) among all CpG-SNP pairs to 0.05 and reports on CpGs from the significant CpG-SNP pairs. However, a statistical test for each CpG is not performed, potentially increasing the proportion of CpGs falsely reported on. Here, we presented an alternative approach that properly control for multiple testing at the CpG level. RESULTS: We performed cis meQTL mapping for varying window sizes using publicly available single-nucleotide polymorphism (SNP) and 450 kb data, extracting the CpGs from the significant CpG-SNP pairs ([Formula: see text]). Using a new bait-and-switch simulation approach, we show that up to 50% of the CpGs found in the simulated data may be false-positive results. We present an alternative two-step multiple testing approach using the Simes and Benjamini-Hochberg procedures that does control the FDR among the CpGs, as confirmed by the bait-and-switch simulation. This approach indicates the use of window sizes in cis meQTL mapping studies that are significantly smaller than commonly adopted. DISCUSSION: Our approach to cis meQTL mapping properly controls the FDR at the CpG level, is computationally fast and can also be applied to cis eQTL studies. AVAILABILITY AND IMPLEMENTATION: An examplary R script for performing the Simes procedure is available as supplementary material. CONTACT: e.w.van_zwet@lumc.nl or b.t.heijmans@lumc.nl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Latent infection with cytomegalovirus is associated with poor memory CD4 responses to influenza A core proteins in the elderly.

Influenza remains a major pathogen in older people. Infection with CMV and the accumulation of late-differentiated T cells associated with it have been implicated in poor Ab responsiveness to influenza vaccination in the elderly, most of whom are CMV positive. However, whether CMV infection also affects memory T cell responses to influenza remains unknown. To investigate this, we assessed T cell responses to influenza A matrix protein and nucleoprotein ex vivo in 166 Dutch individuals (mean age 62.2 y, range 42-82) and validated the results in a second cohort from North America (mean age 73.1 y, range 65-81, n = 28). We found that less than half of the CMV-infected older subjects mounted a CD4 T cell response to influenza Ags, whereas ∼80% of uninfected elderly did so. A similar proportion of younger subjects possessed influenza A virus-responsive CD4 T cells, and, interestingly, this was the case whether they were CMV-infected. Thus, the effect of CMV was only seen in the older donors, who may have been exposed to the virus for decades. The percentage of donors with CD8 responses to influenza A virus was lower than those with CD4; this was not influenced by whether the subjects were CMV seropositive or seronegative. CMV-seropositive responders had significantly higher frequencies of late-differentiated CD4 T-cells (CD45RA(+/-)CCR7(-)CD27(-)CD28(-)) compared with CMV-infected nonresponders. These data add to the accumulating evidence that infection with CMV has profound but heterogeneous effects on responses to the products of other viruses and have implications for the design of influenza vaccines, especially in the elderly.

Genetically determined prospect to become long-lived is associated with less abdominal fat and in particular less abdominal visceral fat in men.

PURPOSE: familial longevity is marked by an exceptionally healthy metabolic profile and low prevalence of cardiometabolic disease observed already at middle age. We aim to investigate whether regional body fat distribution, which has previously shown to be associated with cardiometabolic risk, is different in offspring of long-lived siblings compared with controls. METHODS: our institutional review board approved the study, and all participants (n = 344, average age in years 65.6) gave written informed consent. Offspring (n = 175) of non-agenarian siblings were included. Their partners (n = 169) were enrolled as controls. For abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) measurements, a single-slice 8.0 mm computed tomography (CT) acquisition was planned at the level of the 5th lumbar vertebra. In addition, participants underwent prospectively electrocardiography-triggered unenhanced volumetric CT of the heart. Abdominal VAT and SAT areas (cm(2)) and epicardial adipose tissue (EAT) volumes (ml) were acquired by semi-automated segmentation techniques. Linear regression analysis was performed adjusting for cardiovascular risk factors. RESULTS: total abdominal fat areas were smaller in male offspring compared with controls (353.0 versus 382.9 cm(2), P = 0.022). The association between low abdominal VAT areas in male offspring (149.7 versus 167.0 cm(2) in controls, P = 0.043) attenuated after additional adjustment for diabetes (P = 0.078). Differences were not observed for females. EAT volumes were similar between offspring of long-lived siblings and controls. CONCLUSION: males who have genetically determined prospect to become long-lived have less abdominal fat and in particular less abdominal VAT compared with controls.

Identified senescence endotypes in aged cartilage are reflected in the blood metabolome.

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.

Epigenome-wide association study of dietary fatty acid intake.

BACKGROUND: Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake of n-6 PUFA was often reported to be associated with inflammation-related traits. The effect of PUFAs on health outcomes might be mediated by DNA methylation (DNAm). The aim of our study is to identify the impact of PUFA intake on DNAm in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and the Leiden Longevity Study (LLS). RESULTS: DNA methylation levels were measured in whole blood from the population-based KORA FF4 study (N = 1354) and LLS (N = 448), using the Illumina MethylationEPIC BeadChip and Illumina HumanMethylation450 array, respectively. We assessed associations between DNAm and intake of eight and four PUFAs in KORA and LLS, respectively. Where possible, results were meta-analyzed. Below the Bonferroni correction threshold (p < 7.17 × 10-8), we identified two differentially methylated positions (DMPs) associated with PUFA intake in the KORA study. The DMP cg19937480, annotated to gene PRDX1, was positively associated with docosahexaenoic acid (DHA) in model 1 (beta: 2.00 × 10-5, 95%CI: 1.28 × 10-5-2.73 × 10-5, P value: 6.98 × 10-8), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 × 10-5, 95%CI: 6.25 × 10-5-1.33 × 10-4, P value: 6.75 × 10-8). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 × 10-7) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 × 10-5, 95% CI: 1.27 × 10-5-2.73 × 10-5, P value = 5.99 × 10-8) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 × 10-5, 95% CI: 1.31 × 10-5-2.83 × 10-5, P value = 1.00 × 10-7 and beta: 2.19 × 10-5, 95% CI: 1.41 × 10-5-2.97 × 10-5, P value = 5.91 × 10-8 respectively). CONCLUSIONS: Our study identified three CpG sites associated with PUFA intake. The mechanisms of these sites remain largely unexplored, highlighting the novelty of our findings. Further research is essential to understand the links between CpG site methylation and PUFA outcomes.

Circulating cell-free DNA in health and disease - the relationship to health behaviours, ageing phenotypes and metabolomics.

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.cf-DNA levels were significantly higher in men than in women, and especially in middle-aged men and women who smoke, and in older more frail individuals. Correlation statistics of biomarker data showed that cf-DNA level was higher with elevated inflammation (C-reactive protein, interleukin-6), and higher levels of homocysteine, and proportion of red blood cells and lower levels of ascorbic acid. Inflammation (C-reactive protein, glycoprotein acetylation), amino acids (isoleucine, leucine, tyrosine), and ketogenesis (3-hydroxybutyrate) were included in the cf-DNA level-related biomarker profiles in at least two of the cohorts.In conclusion, circulating cf-DNA level is different by sex, and related to health behaviour, health decline and metabolic processes common in health and disease. These results can inform future studies where epidemiological and biological pathways of cf-DNA are to be analysed in details, and for studies evaluating cf-DNA as a potential clinical marker.

Epigenome-Wide Association Study Reveals CpG Sites Associated with Thyroid Function and Regulatory Effects on KLF9.

Background: Thyroid hormones play a key role in differentiation and metabolism and are known regulators of gene expression through both genomic and epigenetic processes including DNA methylation. The aim of this study was to examine associations between thyroid hormones and DNA methylation. Methods: We carried out a fixed-effect meta-analysis of epigenome-wide association study (EWAS) of blood DNA methylation sites from 8 cohorts from the ThyroidOmics Consortium, incorporating up to 7073 participants of both European and African ancestry, implementing a discovery and replication stage. Statistical analyses were conducted using normalized beta CpG values as dependent and log-transformed thyrotropin (TSH), free thyroxine, and free triiodothyronine levels, respectively, as independent variable in a linear model. The replicated findings were correlated with gene expression levels in whole blood and tested for causal influence of TSH and free thyroxine by two-sample Mendelian randomization (MR). Results: Epigenome-wide significant associations (p-value <1.1E-7) of three CpGs for free thyroxine, five for free triiodothyronine, and two for TSH concentrations were discovered and replicated (combined p-values = 1.5E-9 to 4.3E-28). The associations included CpG sites annotated to KLF9 (cg00049440) and DOT1L (cg04173586) that overlap with all three traits, consistent with hypothalamic-pituitary-thyroid axis physiology. Significant associations were also found for CpGs in FKBP5 for free thyroxine, and at CSNK1D/LINCO1970 and LRRC8D for free triiodothyronine. MR analyses supported a causal effect of thyroid status on DNA methylation of KLF9. DNA methylation of cg00049440 in KLF9 was inversely correlated with KLF9 gene expression in blood. The CpG at CSNK1D/LINC01970 overlapped with thyroid hormone receptor alpha binding peaks in liver cells. The total additive heritability of the methylation levels of the six significant CpG sites was between 25% and 57%. Significant methylation QTLs were identified for CpGs at KLF9, FKBP5, LRRC8D, and CSNK1D/LINC01970. Conclusions: We report novel associations between TSH, thyroid hormones, and blood-based DNA methylation. This study advances our understanding of thyroid hormone action particularly related to KLF9 and serves as a proof-of-concept that integrations of EWAS with other -omics data can provide a valuable tool for unraveling thyroid hormone signaling in humans by complementing and feeding classical in vitro and animal studies.

Metabolomic profiles predict individual multidisease outcomes.

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.

Large replication study and meta-analyses of DVWA as an osteoarthritis susceptibility locus in European and Asian populations.

Recently, through a genome wide association study in Japanese knee osteoarthritis (OA) cases, a previously unknown gene, DVWA, was identified. The non-synonymous single nucleotide polymorphism (SNP) rs7639618 was subsequently found to be consistent and most significantly associated in Japanese and Han Chinese knee OA studies and functional relevant. Here, the association of the DVWA polymorphisms (rs7639618, rs11718863 and rs9864422) was genotyped in 1120 knee OA cases, 1482 hip OA cases and 2147 controls, all of white European descent from the Netherlands, the UK, Spain and Greece. Random effect DerSimonian and Laird meta-analyses were performed to assess the association in the different strata. To assess a more global effect, the original Japanese and Chinese data were included with the European. The meta-analyses provided evidence for global association of rs7639618 with knee OA with an odds ratio (OR) of 1.29, 95% confidence interval (CI) of 1.15-1.45 and a P-value of 2.70 x 10(-5). This effect, however, showed moderate heterogeneity, and rs7639618 was not independently associated with knee OA in Europeans, with an OR of 1.16, 95% CI of 0.99-1.35 and a P-value of 0.063. Furthermore, no association was observed with hip OA in Europeans, with a P-value of 0.851. Our results suggest that there may be global relevance for the DVWA SNP rs7639618 among knee OA cases, however, the apparent lower effect size in combination with the higher risk allele frequency in the European samples highlights again the ethnic differences in effects of discovered OA susceptibility genes.

Infection with cytomegalovirus but not herpes simplex virus induces the accumulation of late-differentiated CD4+ and CD8+ T-cells in humans.

Human cytomegalovirus (CMV) establishes persistent, usually asymptomatic, infection in healthy people. Because CMV infection is associated with the presence of lower proportions of peripheral naïve CD8+ T-cells and a higher fraction of late-differentiated CD8+ cells, commonly taken as biomarkers of age-associated compromised adaptive immunity ('immunosenescence'), we asked whether chronic exposure to any persistent virus mediates these effects. Herpes simplex virus (HSV) is also a widespread herpesvirus that establishes lifelong persistence, but, unlike CMV, its impact on the distribution of T-cell subsets has not been established. Here, we analysed T-cell subsets in 93 healthy people aged 42-81 years infected or not infected with CMV and/or HSV. Individuals harbouring CMV were confirmed to possess lower frequencies of naïve CD8+ T-cells (defined as CD45RA+CCR7+CD27+CD28+) and greater proportions of late-differentiated effector memory (CD45RA-CCR7-CD27-CD28-) and so-called TEMRA (CD45RA+CCR7-CD27-CD28-) CD4 and CD8 subsets, independent of HSV seropositivity. In CMV-seronegative donors, HSV did not affect T-cell subset distribution significantly. We conclude that these hallmarks of age-associated alterations to immune signatures are indeed observed in the general population in people infected with CMV and not those infected with a different persistent herpesvirus.

ADHD in Dutch adults: heritability and linkage study.

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental phenotype that persists into adulthood. This study investigated the heritability of inattentive and hyperactive symptoms and of total ADHD symptomatology load (ADHD index) in adults and performed linkage scans for these dimensions. Data on sibling pairs and their family members from the Netherlands Twin Register with genotype and phenotype data for inattention, hyperactivity and ADHD index (∼750 sib-pairs) were analyzed. Phenotypes were assessed with the short self-report form of the Conners' Adult ADHD Rating Scales (CAARS). Heritabilities were estimated in SOLAR under polygenic models. Genome-wide linkage scans were performed using variance components (VC) in MERLIN and MINX and model-based linkage analysis was carried out in MENDEL with empirical evaluation of the results via simulations. Heritability estimates for inattention, hyperactivity and ADHD index were 35%, 23%, and 31%, respectively. Chromosomes 18q21.31-18q21.32 (VC LOD = 4.58, p(emp) = 0.0026) and 2p25.1 (LOD = 3.58, p(emp) = 0.0372) provided significant evidence for linkage for inattention and the ADHD index, respectively. The QTL on chromosome 2p25.1 also showed suggestive linkage for hyperactivity. Two additional suggestive QTLs for hyperactivity and the ADHD index shared the same location on chromosome 3p24.3-3p24.1. Finally, a suggestive QTL on 8p23.3-8p23.2 for hyperactivity was also found. Heritability of inattention, hyperactivity and total ADHD symptoms is lower in adults than in children. Chromosomes 18q and 2p are likely to harbor genes that influence several aspects of adult ADHD.

Age, Sex, and BMI Influence on Copper, Zinc, and Their Major Serum Carrier Proteins in a Large European Population Including Nonagenarian Offspring From MARK-AGE Study.

The analysis of copper (Cu) and zinc (Zn) along with their major serum carriers, albumin (Alb) and ceruloplasmin (Cp), could provide information on the capacity of humans to maintain homeostasis of metals (metallostasis). However, their relationship with aging, sex, body mass index, as well as with nutritional and inflammatory markers was never investigated in a large-scale study. Here, we report results from the European large-scale cross-sectional study MARK-AGE in which Cu, Zn, Alb, Cp, as well as nutritional and inflammatory parameters were determined in 2424 age-stratified participants (35-75 years), including the general population (RASIG), nonagenarian offspring (GO), a well-studied genetic model of longevity, and spouses of GO (SGO). In RASIG, Cu to Zn ratio and Cp to Alb ratio were higher in women than in men. Both ratios increased with aging because Cu and Cp increased and Alb and Zn decreased. Cu, Zn, Alb, and Cp were found associated with several inflammatory as well as nutritional biomarkers. GO showed higher Zn levels and higher Zn to Alb ratio compared to RASIG, but we did not observe significant differences with SGO, likely as a consequence of the low sample size of SGO and the shared environment. Our results show that aging, sex, body mass index, and GO status are characterized by different levels of Cu, Zn, and their serum carrier proteins. These data and their relationship with inflammatory biomarkers support the concept that loss of metallostasis is a characteristic of inflammaging.

Common genetic variation in the Estrogen Receptor Beta (ESR2) gene and osteoarthritis: results of a meta-analysis.

BACKGROUND: The objective of this study was to examine the relationship between common genetic variation of the ESR2 gene and osteoarthritis. METHODS: In the discovery study, the Rotterdam Study-I, 7 single nucleotide polymorphisms (SNPs) were genotyped and tested for association with hip (284 cases, 2772 controls), knee (665 cases, 2075 controls), and hand OA (874 cases, 2184 controls) using an additive model. In the replication stage one SNP (rs1256031) was tested in an additional 2080 hip, 1318 knee and 557 hand OA cases and 4001, 2631 and 1699 controls respectively. Fixed- and random-effects meta-analyses were performed over the complete dataset including 2364 hip, 1983 knee and 1431 hand OA cases and approximately 6000 controls. RESULTS: The C allele of rs1256031 was associated with a 36% increased odds of hip OA in women of the Rotterdam Study-I (OR 1.36, 95% CI 1.08-1.70, p = 0.009). Haplotype analysis and analysis of knee- and hand OA did not give additional information. With the replication studies, the meta-analysis did not show a significant effect of this SNP on hip OA in the total population (OR 1.06, 95% CI 0.99-1.15, p = 0.10). Stratification according to gender did not change the results. In this study, we had 80% power to detect an odds ratio of at least 1.14 for hip OA (α = 0.05). CONCLUSION: This study showed that common genetic variation in the ESR2 gene is not likely to influence the risk of osteoarthritis with effects smaller than a 13% increase.

Broad phenotype of cysteine-altering NOTCH3 variants in UK Biobank: CADASIL to nonpenetrance.

OBJECTIVE: To determine the small vessel disease spectrum associated with cysteine-altering NOTCH3 variants in community-dwelling individuals by analyzing the clinical and neuroimaging features of UK Biobank participants harboring such variants. METHODS: The exome and genome sequencing datasets of the UK Biobank (n = 50,000) and cohorts of cognitively healthy elderly (n = 751) were queried for cysteine-altering NOTCH3 variants. Brain MRIs of individuals harboring such variants were scored according to Standards for Reporting Vascular Changes on Neuroimaging criteria, and clinical information was extracted with ICD-10 codes. Clinical and neuroimaging data were compared to age- and sex-matched UK Biobank controls and clinically diagnosed patients from the Dutch cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) registry. RESULTS: We identified 108 individuals harboring a cysteine-altering NOTCH3 variant (2.2 of 1,000), of whom 75% have a variant that has previously been reported in CADASIL pedigrees. Almost all variants were located in 1 of the NOTCH3 protein epidermal growth factor-like repeat domains 7 to 34. White matter hyperintensity lesion load was higher in individuals with NOTCH3 variants than in controls (p = 0.006) but lower than in patients with CADASIL with the same variants (p < 0.001). Almost half of the 24 individuals with brain MRI had a Fazekas score of 0 or 1 up to age 70 years. There was no increased risk of stroke. CONCLUSIONS: Although community-dwelling individuals harboring a cysteine-altering NOTCH3 variant have a higher small vessel disease MRI burden than controls, almost half have no MRI abnormalities up to age 70 years. This shows that NOTCH3 cysteine altering variants are associated with an extremely broad phenotypic spectrum, ranging from CADASIL to nonpenetrance.

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, here, we 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: Liquid Chromatography - ElectroSpray Ionization - Mass Spectrometry (LC-ESI-MS), Ultra High Performance Liquid Chromatography with Fluorescence Detection (UHPLC-FLD), and Matrix Assisted Laser Desorption Ionization - Furier Transform Ion Cyclotron Resonance - Mass Spectrometry (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. This recommendation is further supported by an additional analysis, where we ranked normalization methods based on their statistical associations with age, a factor known to associate with glycomics measurements.