Publications by authors named "Joris Deelen"

85 Publications

Targeting multimorbidity: Using healthspan and lifespan to identify biomarkers of ageing that pinpoint shared disease mechanisms.

Authors:
Joris Deelen

EBioMedicine 2021 May 6;67:103364. Epub 2021 May 6.

Max Planck Institute for Biology of Ageing, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany. Electronic address:

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http://dx.doi.org/10.1016/j.ebiom.2021.103364DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114127PMC
May 2021

From mutation to mechanism: deciphering the molecular function of genetic variants linked to human ageing.

Brief Funct Genomics 2021 Mar 5. Epub 2021 Mar 5.

Max Planck Institute for Biology of Ageing.

Many of the leading causes of death in humans, such as cardiovascular disease, type 2 diabetes and Alzheimer's disease are influenced by biological mechanisms that become dysregulated with increasing age. Hence, by targeting these ageing-related mechanisms, we may be able to improve health in old age. Ageing is partly heritable and genetic studies have been moderately successful in identifying genetic variants associated with ageing-related phenotypes (lifespan, healthspan and longevity). To decipher the mechanisms by which the identified variants influence ageing, studies that focus on their functional validation are vital. In this perspective, we describe the steps that could be taken in the process of functional validation: (1) in silico characterisation using bioinformatic tools; (2) in vitro characterisation using cell lines or organoids; and (3) in vivo characterisation studies using model organisms. For the in vivo characterisation, it is important to focus on translational phenotypes that are indicative of both healthspan and lifespan, such as the frailty index, to inform subsequent intervention studies. The depth of functional validation of a genetic variant depends on its location in the genome and conservation in model organisms. Moreover, some variants may prove to be hard to characterise due to context-dependent effects related to the experimental environment or genetic background. Future efforts to functionally characterise the (newly) identified genetic variants should shed light on the mechanisms underlying ageing and will help in the design of targeted interventions to improve health in old age.
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http://dx.doi.org/10.1093/bfgp/elab005DOI Listing
March 2021

Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Hum Mol Genet 2021 04;30(5):393-409

Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK.

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.
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http://dx.doi.org/10.1093/hmg/ddab023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098112PMC
April 2021

Metabolic Age Based on the BBMRI-NL H-NMR Metabolomics Repository as Biomarker of Age-related Disease.

Circ Genom Precis Med 2020 10 14;13(5):541-547. Epub 2020 Aug 14.

Department of Internal Medicine, Maastricht University Medical Center, the Netherlands (C.D.A.S., C.J.H.v.d.K., M.M.J.v.G.).

Background: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status.

Methods: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts.

Results: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data.

Conclusions: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.
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http://dx.doi.org/10.1161/CIRCGEN.119.002610DOI Listing
October 2020

Correlation of the two most frequent HLA haplotypes in the Italian population to the differential regional incidence of Covid-19.

J Transl Med 2020 09 15;18(1):352. Epub 2020 Sep 15.

Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Via Salvatore Allende, 84081, Baronissi, SA, Italy.

Background: Understanding how HLA polymorphisms may affect both susceptibility, course and severity of Covid-19 infection could help both at the clinical level to identify individuals at higher risk from the disease and at the epidemiological one to explain the differences in the epidemic trend among countries or even within a specific country. Covid-19 disease in Italy showed a peculiar geographical distribution from the northern most affected regions to the southern ones only slightly touched.

Methods: In this study we analysed the regional frequencies for the most common Italian haplotypes from the Italian Bone Marrow Donor Registry (HLA-A, -B, -C and -DRB1 at four-digit level). Then we performed Pearson correlation analyses among regional haplotypes estimated frequency in the population and Covid-19 incidence and mortality.

Results: In this study we found that the two most frequent HLA haplotypes in the Italian population, HLA-A*:01:01g-B*08:01 g-C*07:01g-DRB1*03:01g and HLA-A*02.01g-B*18.01g-C*07.01g-DRB1*11.04g, had a regional distribution overlapping that of Covid-19 and showed respectively a positive (suggestive of susceptibility) and negative (suggestive of protection) significant correlation with both Covid-19 incidence and mortality.

Conclusions: Based on these results, in order to define such HLA haplotypes as a factor effectively associated to the disease susceptibility, the creation of national networks that can collect patients' samples from all regions for HLA typing should be highly encouraged.
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http://dx.doi.org/10.1186/s12967-020-02515-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491019PMC
September 2020

Similar burden of pathogenic coding variants in exceptionally long-lived individuals and individuals without exceptional longevity.

Aging Cell 2020 10 29;19(10):e13216. Epub 2020 Aug 29.

Faculty of Natural Sciences, University of Haifa, Haifa, Israel.

Centenarians (exceptionally long-lived individuals-ELLI) are a unique segment of the population, exhibiting long human lifespan and healthspan, despite generally practicing similar lifestyle habits as their peers. We tested disease-associated mutation burden in ELLI genomes by determining the burden of pathogenic variants reported in the ClinVar and HGMD databases using data from whole exome sequencing (WES) conducted in a cohort of ELLI, their offspring, and control individuals without antecedents of familial longevity (n = 1879), all descendent from the founder population of Ashkenazi Jews. The burden of pathogenic variants did not differ between the three groups. Additional analyses of variants subtypes and variant effect predictor (VEP) biotype frequencies did not reveal a decrease of pathogenic or loss-of-function (LoF) variants in ELLI and offspring compared to the control group. Case-control pathogenic variants enrichment analyses conducted in ELLI and controls also did not identify significant differences in any of the variants between the groups and polygenic risk scores failed to provide a predictive model. Interestingly, cancer and Alzheimer's disease-associated variants were significantly depleted in ELLI compared to controls, suggesting slower accumulation of mutation. That said, polygenic risk score analysis failed to find any predictive variants among the functional variants tested. The high similarity in the burden of pathogenic variation between ELLI and individuals without familial longevity supports the notion that extension of lifespan and healthspan in ELLI is not a consequence of pathogenic variant depletion but rather a result of other genomic, epigenomic, or potentially nongenomic properties.
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http://dx.doi.org/10.1111/acel.13216DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576295PMC
October 2020

Lack of consensus on an aging biology paradigm? A global survey reveals an agreement to disagree, and the need for an interdisciplinary framework.

Mech Ageing Dev 2020 10 18;191:111316. Epub 2020 Jul 18.

Department of Neurology and Neurosurgery, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada; Metabolic Disorders and Complications Program, and Brain Repair and Integrative Neuroscience Program, Research Institute of the McGill University Health Centre, 1001 Decarie Boulevard, Montreal, Quebec, H4A 3J1, Canada. Electronic address:

At a recent symposium on aging biology, a debate was held as to whether or not we know what biological aging is. Most of the participants were struck not only by the lack of consensus on this core question, but also on many basic tenets of the field. Accordingly, we undertook a systematic survey of our 71 participants on key questions that were raised during the debate and symposium, eliciting 37 responses. The results confirmed the impression from the symposium: there is marked disagreement on the most fundamental questions in the field, and little consensus on anything other than the heterogeneous nature of aging processes. Areas of major disagreement included what participants viewed as the essence of aging, when it begins, whether aging is programmed or not, whether we currently have a good understanding of aging mechanisms, whether aging is or will be quantifiable, whether aging will be treatable, and whether many non-aging species exist. These disagreements lay bare the urgent need for a more unified and cross-disciplinary paradigm in the biology of aging that will clarify both areas of agreement and disagreement, allowing research to proceed more efficiently. We suggest directions to encourage the emergence of such a paradigm.
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http://dx.doi.org/10.1016/j.mad.2020.111316DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7603428PMC
October 2020

Multivariate genomic scan implicates novel loci and haem metabolism in human ageing.

Nat Commun 2020 07 16;11(1):3570. Epub 2020 Jul 16.

Max Planck Institute for Biology of Ageing, Cologne, Germany.

Ageing phenotypes, such as years lived in good health (healthspan), total years lived (lifespan), and survival until an exceptional old age (longevity), are of interest to us all but require exceptionally large sample sizes to study genetically. Here we combine existing genome-wide association summary statistics for healthspan, parental lifespan, and longevity in a multivariate framework, increasing statistical power, and identify 10 genomic loci which influence all three phenotypes, of which five (near FOXO3, SLC4A7, LINC02513, ZW10, and FGD6) have not been reported previously at genome-wide significance. The majority of these 10 loci are associated with cardiovascular disease and some affect the expression of genes known to change their activity with age. In total, we implicate 78 genes, and find these to be enriched for ageing pathways previously highlighted in model organisms, such as the response to DNA damage, apoptosis, and homeostasis. Finally, we identify a pathway worthy of further study: haem metabolism.
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http://dx.doi.org/10.1038/s41467-020-17312-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366647PMC
July 2020

Searching for the genetic key to a long and healthy life.

Authors:
Joris Deelen

Elife 2020 04 24;9. Epub 2020 Apr 24.

Max Planck Institute for Biology of Ageing, Cologne, Germany.

A study of over 40,000 individuals suggests that carrying a small number of ultra-rare genetic variants is associated with a longer lifespan.
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http://dx.doi.org/10.7554/eLife.57242DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7182428PMC
April 2020

Lifestyle-Intervention-Induced Reduction of Abdominal Fat Is Reflected by a Decreased Circulating Glycerol Level and an Increased HDL Diameter.

Mol Nutr Food Res 2020 05 23;64(10):e1900818. Epub 2020 Apr 23.

Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, 2333ZC, The Netherlands.

Scope: Abdominal obesity is one of the main modifiable risk factors of age-related cardiometabolic disease. Cardiometabolic disease risk and its associated high abdominal fat mass, cholesterol, and glucose concentrations can be reduced by a healthier lifestyle. Hence, the aim is to understand the relation between lifestyle-induced changes in body composition, and specifically abdominal fat, and accompanying changes in circulating metabolic biomarkers.

Methods And Results: Data from the Growing Old Together (GOTO) study was used, which is a single arm lifestyle intervention in which 164 older adults (mean age 63 years, BMI 23-35 kg/m ) changed their lifestyle during 13 weeks by 12.5% caloric restriction plus 12.5% increase in energy expenditure. It is shown here that levels of circulating metabolic biomarkers, even after adjustment for body mass index, specifically associate with abdominal fat mass. The applied lifestyle intervention mainly reduces abdominal fat mass (-2.6%, SD = 3.0) and this reduction, when adjusted for general weight loss, is highly associated with decreased circulating glycerol concentrations and increased HDL diameter.

Conclusion: The lifestyle-induced reduction of abdominal fat mass is particularly associated, independent of body mass index or general weight loss, with decreased circulating glycerol concentrations and increased HDL diameter.
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http://dx.doi.org/10.1002/mnfr.201900818DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317364PMC
May 2020

Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases.

Sci Adv 2020 02 19;6(8):eaax0301. Epub 2020 Feb 19.

MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.

Effector functions of immunoglobulin G (IgG) are regulated by the composition of a glycan moiety, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the underlying mechanisms. We performed a genome-wide association study of IgG N-glycosylation ( = 8090) and, using a data-driven network approach, suggested how associated loci form a functional network. We confirmed in vitro that knockdown of decreases the expression of fucosyltransferase FUT8, resulting in increased levels of fucosylated glycans, and suggest that RUNX1 and RUNX3, together with SMARCB1, regulate expression of glycosyltransferase MGAT3. We also show that variants affecting the expression of genes involved in the regulation of glycoenzymes colocalize with variants affecting risk for inflammatory diseases. This study provides new evidence that variation in key transcription factors coupled with regulatory variation in glycogenes modifies IgG glycosylation and has influence on inflammatory diseases.
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http://dx.doi.org/10.1126/sciadv.aax0301DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7030929PMC
February 2020

Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length.

Am J Hum Genet 2020 03 27;106(3):389-404. Epub 2020 Feb 27.

Department of Cardiovascular Sciences, University of Leicester, LE3 9QP, United Kingdom; NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, United Kingdom.

Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.
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http://dx.doi.org/10.1016/j.ajhg.2020.02.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058826PMC
March 2020

A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals.

Nat Commun 2019 08 20;10(1):3346. Epub 2019 Aug 20.

Division of Human Nutrition, Wageningen University, PO Box 17, 6700 AA, Wageningen, The Netherlands.

Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18-109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.
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http://dx.doi.org/10.1038/s41467-019-11311-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702196PMC
August 2019

A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Nat Commun 2019 08 14;10(1):3669. Epub 2019 Aug 14.

Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark.

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.
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http://dx.doi.org/10.1038/s41467-019-11558-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694136PMC
August 2019

Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium.

Sci Rep 2019 08 12;9(1):11623. Epub 2019 Aug 12.

Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10), methionine (p-value = 9.2 × 10), tyrosine (p-value = 2.1 × 10), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.
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http://dx.doi.org/10.1038/s41598-019-47282-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690953PMC
August 2019

Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.

Neurology 2019 Jan 16. Epub 2019 Jan 16.

Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.

Methods: We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.

Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, = 1.77 × 10; and LINC00539/ZDHHC20, = 5.82 × 10. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits ( value for BI, = 9.38 × 10; = 5.23 × 10 for hypertension), smoking ( = 4.4 × 10; = 1.2 × 10), diabetes ( = 1.7 × 10; = 2.8 × 10), previous cardiovascular disease ( = 1.0 × 10; = 2.3 × 10), stroke ( = 3.9 × 10; = 3.2 × 10), and MRI-defined white matter hyperintensity burden ( = 1.43 × 10; = 3.16 × 10), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI ( ≤ 0.0022), without indication of directional pleiotropy.

Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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http://dx.doi.org/10.1212/WNL.0000000000006851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369905PMC
January 2019

Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders.

Am J Hum Genet 2018 11;103(5):691-706

Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USA.

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.
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http://dx.doi.org/10.1016/j.ajhg.2018.09.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6218410PMC
November 2018

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Nat Commun 2018 10 26;9(1):4455. Epub 2018 Oct 26.

Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets.
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http://dx.doi.org/10.1038/s41467-018-06356-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203810PMC
October 2018

Sex Differences in Genetic Associations With Longevity.

JAMA Netw Open 2018 08 24;1(4):e181670. Epub 2018 Aug 24.

Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, North Carolina (Zeng, H. Chen); Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, Beijing, China (Zeng, Bai); BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China (Nie);BGI-Shenzhen, Shenzhen, China (Nie, Xiaomin Liu, Ye, Z. Chen, Bolund, Hou, Xiao Liu, Xu, H. Yang); The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China (Min, E. Xie); Business School of Xiangtan University, Xiangtan, China (H. Chen); Division of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, China (Yin); National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China (Lv, Shi); Department of Sociology, Peking University, Beijing, China (Lu, Li); School of Life Sciences, Fudan University, Shanghai, China (Ni); Department of Biomedicine, Aarhus University, Aarhus, Denmark (Bolund); Duke Population Research Institute, Duke University, Durham, North Carolina (Land, Yashin, O'Rand); The MOH Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China (Sun, Z. Yang); School of Life Sciences, Peking University, Beijing, China (Tao, Gu); Boston University, Boston, Massachusetts (Gurinovich, Sebastiani, Perls); University of Bologna, Bologna, Italy (Franceschi); Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina (J. Xie); French National Institute on Health and Medical Research and Ecole Pratique des Hautes Etudes, University of Montpellier, Montpellier, France (Robine); Max Planck Institute for Biology of Ageing, Cologne, Germany (Deelen); Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands (Slagboom); Molecular Physiology Institute, Medical Center, Duke University, Durham, North Carolina (Hauser); Department of Neurology, Medical Center, Duke University, Durham, North Carolina (Gottschalk, Lutz); University of Southern Denmark, Odense, Denmark (Tan, Christensen); Human Aging Research Institute and School of Life Science, Nanchang University, Jiangxi, China (Tian); James D. Watson Institute of Genome Sciences, Hangzhou, China (H. Yang); Max Planck Institute for Demographic Research, Rostock, Germany (Vaupel).

Importance: Sex differences in genetic associations with human longevity remain largely unknown; investigations on this topic are important for individualized health care.

Objective: To explore sex differences in genetic associations with longevity.

Design Setting And Participants: This population-based case-control study used sex-specific genome-wide association study and polygenic risk score (PRS) analyses to examine sex differences in genetic associations with longevity. Five hundred sixty-four male and 1614 female participants older than 100 years were compared with a control group of 773 male and 1526 female individuals aged 40 to 64 years. All were Chinese Longitudinal Healthy Longevity Study participants with Han ethnicity who were recruited in 1998 and 2008 to 2014.

Main Outcomes And Measures: Sex-specific loci and pathways associated with longevity and PRS measures of joint effects of sex-specific loci.

Results: Eleven male-specific and 11 female-specific longevity loci ( < 10) and 35 male-specific and 25 female-specific longevity loci (10 ≤ < 10) were identified. Each of these loci's associations with longevity were replicated in north and south regions of China in one sex but were not significant in the other sex ( = .13-.97), and loci-sex interaction effects were significant ( < .05). The associations of loci rs60210535 of the gene with longevity were replicated in Chinese women ( = 9.0 × 10) and US women ( = 4.6 × 10) but not significant in Chinese and US men. The associations of the loci rs2622624 of the gene were replicated in Chinese women ( = 6.8 × 10) and European women ( = .003) but not significant in both Chinese and European men. Eleven male-specific pathways (inflammation and immunity genes) and 34 female-specific pathways (tryptophan metabolism and PGC-1α induced) were significantly associated with longevity ( < .005; false discovery rate < 0.05). The PRS analyses demonstrated that sex-specific associations with longevity of the 4 exclusive groups of 11 male-specific and 11 female-specific loci ( < 10) and 35 male-specific and 25 female-specific loci (10 ≤ < 10) were jointly replicated across north and south discovery and target samples. Analyses using the combined data set of north and south showed that these 4 groups of sex-specific loci were jointly and significantly associated with longevity in one sex ( = 2.9 × 10 to 1.3 × 10) but not jointly significant in the other sex ( = .11 to .70), while interaction effects between PRS and sex were significant ( = 4.8 × 10 to 1.2 × 10).

Conclusion And Relevance: The sex differences in genetic associations with longevity are remarkable, but have been overlooked by previously published genome-wide association studies on longevity. This study contributes to filling this research gap and provides a scientific basis for further investigating effects of sex-specific genetic variants and their interactions with environment on healthy aging, which may substantially contribute to more effective and targeted individualized health care for male and female elderly individuals.
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http://dx.doi.org/10.1001/jamanetworkopen.2018.1670DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173523PMC
August 2018

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.

Nat Genet 2018 10 17;50(10):1412-1425. Epub 2018 Sep 17.

Laboratory of Genetics and Genomics, NIA/NIH, Baltimore, MD, USA.

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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http://dx.doi.org/10.1038/s41588-018-0205-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284793PMC
October 2018

Facing up to the global challenges of ageing.

Nature 2018 09 5;561(7721):45-56. Epub 2018 Sep 5.

Max Planck Institute for Biology of Ageing, Cologne, Germany.

Longer human lives have led to a global burden of late-life disease. However, some older people experience little ill health, a trait that should be extended to the general population. Interventions into lifestyle, including increased exercise and reduction in food intake and obesity, can help to maintain healthspan. Altered gut microbiota, removal of senescent cells, blood factors obtained from young individuals and drugs can all improve late-life health in animals. Application to humans will require better biomarkers of disease risk and responses to interventions, closer alignment of work in animals and humans, and increased use of electronic health records, biobank resources and cohort studies.
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http://dx.doi.org/10.1038/s41586-018-0457-8DOI Listing
September 2018

Facial Wrinkles in Europeans: A Genome-Wide Association Study.

J Invest Dermatol 2018 08 16;138(8):1877-1880. Epub 2018 Mar 16.

Department of Dermatology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands. Electronic address:

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http://dx.doi.org/10.1016/j.jid.2017.12.037DOI Listing
August 2018

Genome-Wide Association Study on Immunoglobulin G Glycosylation Patterns.

Front Immunol 2018 26;9:277. Epub 2018 Feb 26.

Research Unit Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.

Immunoglobulin G (IgG), a glycoprotein secreted by plasma B-cells, plays a major role in the human adaptive immune response and are associated with a wide range of diseases. Glycosylation of the Fc binding region of IgGs, responsible for the antibody's effector function, is essential for prompting a proper immune response. This study focuses on the general genetic impact on IgG glycosylation as well as corresponding subclass specificities. To identify genetic loci involved in IgG glycosylation, we performed a genome-wide association study (GWAS) on liquid chromatography electrospray mass spectrometry (LC-ESI-MS)-measured IgG glycopeptides of 1,823 individuals in the Cooperative Health Research in the Augsburg Region (KORA F4) study cohort. In addition, we performed GWAS on subclass-specific ratios of IgG glycans to gain power in identifying genetic factors underlying single enzymatic steps in the glycosylation pathways. We replicated our findings in 1,836 individuals from the Leiden Longevity Study (LLS). We were able to show subclass-specific genetic influences on single IgG glycan structures. The replicated results indicate that, in addition to genes encoding for glycosyltransferases (i.e., , and ), other genetic loci have strong influences on the IgG glycosylation patterns. A novel locus on chromosome 1, harboring , which encodes for a transcription factor of the runt domain-containing family, is associated with decreased galactosylation. Interestingly, members of the family are cross-regulated, and is involved in both IgA class switching and B-cell maturation as well as T-cell differentiation and apoptosis. Besides the involvement of glycosyltransferases in IgG glycosylation, we suggest that, due to the impact of variants within , potentially mechanisms involved in B-cell activation and T-cell differentiation during the immune response as well as cell migration and invasion involve IgG glycosylation.
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http://dx.doi.org/10.3389/fimmu.2018.00277DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834439PMC
March 2019

Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels.

Nat Commun 2018 01 17;9(1):260. Epub 2018 Jan 17.

Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD, 20892, USA.

Vitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Consortium GWAS discovery sample size from 16,125 to 79,366 (all European descent). This larger GWAS yields two additional loci harboring genome-wide significant variants (P = 4.7×10 at rs8018720 in SEC23A, and P = 1.9×10 at rs10745742 in AMDHD1). The overall estimate of heritability of 25-hydroxyvitamin D serum concentrations attributable to GWAS common SNPs is 7.5%, with statistically significant loci explaining 38% of this total. Further investigation identifies signal enrichment in immune and hematopoietic tissues, and clustering with autoimmune diseases in cell-type-specific analysis. Larger studies are required to identify additional common SNPs, and to explore the role of rare or structural variants and gene-gene interactions in the heritability of circulating 25-hydroxyvitamin D levels.
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http://dx.doi.org/10.1038/s41467-017-02662-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5772647PMC
January 2018

Integrative network analysis highlights biological processes underlying GLP-1 stimulated insulin secretion: A DIRECT study.

PLoS One 2018 2;13(1):e0189886. Epub 2018 Jan 2.

Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands.

Glucagon-like peptide 1 (GLP-1) stimulated insulin secretion has a considerable heritable component as estimated from twin studies, yet few genetic variants influencing this phenotype have been identified. We performed the first genome-wide association study (GWAS) of GLP-1 stimulated insulin secretion in non-diabetic individuals from the Netherlands Twin register (n = 126). This GWAS was enhanced using a tissue-specific protein-protein interaction network approach. We identified a beta-cell protein-protein interaction module that was significantly enriched for low gene scores based on the GWAS P-values and found support at the network level in an independent cohort from Tübingen, Germany (n = 100). Additionally, a polygenic risk score based on SNPs prioritized from the network was associated (P < 0.05) with glucose-stimulated insulin secretion phenotypes in up to 5,318 individuals in MAGIC cohorts. The network contains both known and novel genes in the context of insulin secretion and is enriched for members of the focal adhesion, extracellular-matrix receptor interaction, actin cytoskeleton regulation, Rap1 and PI3K-Akt signaling pathways. Adipose tissue is, like the beta-cell, one of the target tissues of GLP-1 and we thus hypothesized that similar networks might be functional in both tissues. In order to verify peripheral effects of GLP-1 stimulation, we compared the transcriptome profiling of ob/ob mice treated with liraglutide, a clinically used GLP-1 receptor agonist, versus baseline controls. Some of the upstream regulators of differentially expressed genes in the white adipose tissue of ob/ob mice were also detected in the human beta-cell network of genes associated with GLP-1 stimulated insulin secretion. The findings provide biological insight into the mechanisms through which the effects of GLP-1 may be modulated and highlight a potential role of the beta-cell expressed genes RYR2, GDI2, KIAA0232, COL4A1 and COL4A2 in GLP-1 stimulated insulin secretion.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189886PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749727PMC
January 2018

IgG glycosylation and DNA methylation are interconnected with smoking.

Biochim Biophys Acta Gen Subj 2018 Mar 18;1862(3):637-648. Epub 2017 Oct 18.

Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.

Background: Glycosylation is one of the most common post-translation modifications with large influences on protein structure and function. The effector function of immunoglobulin G (IgG) alters between pro- and anti-inflammatory, based on its glycosylation. IgG glycan synthesis is highly complex and dynamic.

Methods: With the use of two different analytical methods for assessing IgG glycosylation, we aim to elucidate the link between DNA methylation and glycosylation of IgG by means of epigenome-wide association studies. In total, 3000 individuals from 4 cohorts were analyzed.

Results: The overlap of the results from the two glycan measurement panels yielded DNA methylation of 7 CpG-sites on 5 genomic locations to be associated with IgG glycosylation: cg25189904 (chr.1, GNG12); cg05951221, cg21566642 and cg01940273 (chr.2, ALPPL2); cg05575921 (chr.5, AHRR); cg06126421 (6p21.33); and cg03636183 (chr.19, F2RL3). Mediation analyses with respect to smoking revealed that the effect of smoking on IgG glycosylation may be at least partially mediated via DNA methylation levels at these 7 CpG-sites.

Conclusion: Our results suggest the presence of an indirect link between DNA methylation and IgG glycosylation that may in part capture environmental exposures.

General Significance: An epigenome-wide analysis conducted in four population-based cohorts revealed an association between DNA methylation and IgG glycosylation patterns. Presumably, DNA methylation mediates the effect of smoking on IgG glycosylation.
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http://dx.doi.org/10.1016/j.bbagen.2017.10.012DOI Listing
March 2018

Estimation of metabolite networks with regard to a specific covariable: applications to plant and human data.

Metabolomics 2017 22;13(11):129. Epub 2017 Sep 22.

Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Einthovenweg 20, 2300 RC Leiden, The Netherlands.

Introduction: In systems biology, where a main goal is acquiring knowledge of biological systems, one of the challenges is inferring biochemical interactions from different molecular entities such as metabolites. In this area, the metabolome possesses a unique place for reflecting "true exposure" by being sensitive to variation coming from genetics, time, and environmental stimuli. While influenced by many different reactions, often the research interest needs to be focused on variation coming from a certain source, i.e. a certain covariable [Formula: see text].

Objective: Here, we use network analysis methods to recover a set of metabolite relationships, by finding metabolites sharing a similar relation to [Formula: see text]. Metabolite values are based on information coming from individuals' [Formula: see text] status which might interact with other covariables.

Methods: Alternative to using the original metabolite values, the total information is decomposed by utilizing a linear regression model and the part relevant to [Formula: see text] is further used. For two datasets, two different network estimation methods are considered. The first is weighted gene co-expression network analysis based on correlation coefficients. The second method is graphical LASSO based on partial correlations.

Results: We observed that when using the parts related to the specific covariable of interest, resulting estimated networks display higher interconnectedness. Additionally, several groups of biologically associated metabolites (very large density lipoproteins, lipoproteins, etc.) were identified in the human data example.

Conclusions: This work demonstrates how information on the study design can be incorporated to estimate metabolite networks. As a result, sets of interconnected metabolites can be clustered together with respect to their relation to a covariable of interest.
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http://dx.doi.org/10.1007/s11306-017-1263-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610247PMC
September 2017

Phenome and genome based studies into human ageing and longevity: An overview.

Biochim Biophys Acta Mol Basis Dis 2018 09 22;1864(9 Pt A):2742-2751. Epub 2017 Sep 22.

Department of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands; Max Planck Institute for Biology of Ageing; Joseph-Stelzmann-Str. 9b, D-50931 Köln (Cologne), Germany. Electronic address:

Human ageing is an extremely personal process leading across the life course of individuals to large population heterogeneity in the decline of functional capacity, health and lifespan. The extremes of this process are witnessed by the healthy vital 100-year-olds on one end and the 60-year-olds suffering from multiple morbid conditions on the other end of the spectrum. Molecular studies into the basis of this heterogeneity have focused on a range of endpoints and methodological approaches. The phenotype definitions most prominently investigated in these studies are either lifespan-related or biomarker based indices of the biological ageing rate of individuals and their tissues. Unlike for many complex, age-related diseases, consensus on the ultimate set of multi-biomarker ageing or lifespan-related phenotypes for genetic and genomic studies has not been reached yet. Comparable to animal models, hallmarks of age-related disease risk, healthy ageing and longevity include immune and metabolic pathways. Potentially novel genomic regions and pathways have been identified among many (epi)genomic studies into chronological age and studies into human lifespan regulation, with APOE and FOXO3A representing yet the most robust loci. Functional analysis of a handful of genes in cell-based and animal models is ongoing. The way forward in human ageing and longevity studies seems through improvements in the interpretation of the biology of the genome, in application of computational and systems biology, integration with animal models and by harmonization of repeated phenotypic and omics measures in longitudinal and intervention studies. This article is part of a Special Issue entitled: Model Systems of Aging - edited by "Houtkooper Riekelt".
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http://dx.doi.org/10.1016/j.bbadis.2017.09.017DOI Listing
September 2018
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