Joris Deelen

Genome-wide association meta-analysis of human longevity identifies a novel locus conferring survival beyond 90 years of age

The genetic contribution to the variation in human lifespan is ∼25%. Despite the large number of identified disease-susceptibility loci, it is not known which loci influence population mortality. We performed a genome-wide association meta-analysis of 7729 long-lived individuals of European descent (≥85 years) and 16 121 younger controls (<65 years) followed by replication in an additional set of 13 060 long-lived individuals and 61 156 controls. In addition, we performed a subset analysis in cases aged ≥90 years. We observed genome-wide significant association with longevity, as reflected by survival to ages beyond 90 years, at a novel locus, rs2149954, on chromosome 5q33.3 (OR = 1.10, P = 1.74 × 10−8). We also confirmed association of rs4420638 on chromosome 19q13.32 (OR = 0.72, P = 3.40 × 10−36), representing the TOMM40/APOE/APOC1 locus. In a prospective meta-analysis (n = 34 103), the minor allele of rs2149954 (T) on chromosome 5q33.3 associates with increased survival (HR = 0.95, P = 0.003). This allele has previously been reported to associate with low blood pressure in middle age. Interestingly, the minor allele (T) associates with decreased cardiovascular mortality risk, independent of blood pressure. We report on the first GWAS-identified longevity locus on chromosome 5q33.3 influencing survival in the general European population. The minor allele of this locus associates with low blood pressure in middle age, although the contribution of this allele to survival may be less dependent on blood pressure. Hence, the pleiotropic mechanisms by which this intragenic variation contributes to lifespan regulation have to be elucidated.

Genome-wide linkage analysis for human longevity: Genetics of Healthy Aging Study

Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome‐wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12‐q22 (LOD = 2.95), chromosome 19p13.3‐p13.11 (LOD = 3.76), and chromosome 19q13.11‐q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed‐effect meta‐analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (P‐value = 9.6 × 10−8). By combined modeling of linkage and association, we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11‐q13.32 with P‐value = 0.02 and P‐value = 1.0 × 10−5, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12‐q22, and 19p13.3‐p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.

The impact of low-frequency and rare variants on lipid levels

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.

A Meta-Analysis of Thyroid-Related Traits Reveals Novel Loci and Gender-Specific Differences in the Regulation of Thyroid Function

Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism.

GWAS of Longevity in CHARGE Consortium Confirms APOE and FOXO3 Candidacy

BACKGROUND The genetic contribution to longevity in humans has been estimated to range from 15% to 25%. Only two genes, APOE and FOXO3, have shown association with longevity in multiple independent studies. METHODS We conducted a meta-analysis of genome-wide association studies including 6,036 longevity cases, age ≥90 years, and 3,757 controls that died between ages 55 and 80 years. We additionally attempted to replicate earlier identified single nucleotide polymorphism (SNP) associations with longevity. RESULTS In our meta-analysis, we found suggestive evidence for the association of SNPs near CADM2 (odds ratio [OR] = 0.81; p value = 9.66 × 10(-7)) and GRIK2 (odds ratio = 1.24; p value = 5.09 × 10(-8)) with longevity. When attempting to replicate findings earlier identified in genome-wide association studies, only the APOE locus consistently replicated. In an additional look-up of the candidate gene FOXO3, we found that an earlier identified variant shows a highly significant association with longevity when including published data with our meta-analysis (odds ratio = 1.17; p value = 1.85×10(-10)). CONCLUSIONS We did not identify new genome-wide significant associations with longevity and did not replicate earlier findings except for APOE and FOXO3. Our inability to find new associations with survival to ages ≥90 years because longevity represents multiple complex traits with heterogeneous genetic underpinnings, or alternatively, that longevity may be regulated by rare variants that are not captured by standard genome-wide genotyping and imputation of common variants.

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.

Disease variants alter transcription factor levels and methylation of their binding sites

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.

Gene expression analysis of mTOR pathway: association with human longevity

mTOR signalling is implicated in the development of disease and in lifespan extension in model organisms. This pathway has been associated with human diseases such as diabetes and cancer, but has not been investigated for its impact on longevity per se. Here, we investigated whether transcriptional variation within the mTOR pathway is associated with human longevity using whole‐blood samples from the Leiden Longevity Study. This is a unique cohort of Dutch families with extended survival across generations, decreased morbidity and beneficial metabolic profiles in middle‐age. By comparing mRNA levels of nonagenarians and middle‐aged controls, the mTOR signalling gene set was found to associate with old age (P = 4.6 × 10−7). Single gene analysis showed that seven of 40 mTOR pathway genes had a significant differential expression of at least 5%. Of these, the RPTOR (Raptor) gene was found to be differentially expressed also when the offspring of nonagenarians was compared with their spouses, indicating association with familial longevity in middle‐age. This association was not explained by variation between the groups in the prevalence of type 2 diabetes and cancer or glucose levels. Thus, the mTOR pathway not only plays a role in the regulation of disease and aging in animal models, but also in human health and longevity.

Identifying the genomic determinants of aging and longevity in human population studies: Progress and challenges

Human lifespan variation is mainly determined by environmental factors, whereas the genetic contribution is 25–30% and expected to be polygenic. Two complementary fields go hand in hand in order to unravel the mechanisms of biological aging: genomic and biomarker research. Explorative and candidate gene studies of the human genome by genetic, transcriptomic, and epigenomic approaches have resulted in the identification of a limited number of interesting positive linkage regions, genes, and pathways that contribute to lifespan variation. The possibilities to further exploit these findings are rapidly increasing through the use of novel technologies, such as next‐generation sequencing. Genomic research is progressively being integrated with biomarker studies on aging, including the application of (noninvasive) deep phenotyping and omics data – generated using novel technologies – in a wealth of studies in human populations. Hence, these studies may assist in obtaining a more holistic perspective on the role of the genome in aging and lifespan regulation.

Gene set analysis of GWAS data for human longevity highlights the relevance of the insulin/IGF-1 signaling and telomere maintenance pathways

In genome-wide association studies (GWAS) of complex traits, single SNP analysis is still the most applied approach. However, the identified SNPs have small effects and provide limited biological insight. A more appropriate approach to interpret GWAS data of complex traits is to analyze the combined effect of a SNP set grouped per pathway or gene region. We used this approach to study the joint effect on human longevity of genetic variation in two candidate pathways, the insulin/insulin-like growth factor (IGF-1) signaling (IIS) pathway and the telomere maintenance (TM) pathway. For the analyses, we used genotyped GWAS data of 403 unrelated nonagenarians from long-lived sibships collected in the Leiden Longevity Study and 1,670 younger population controls. We analyzed 1,021 SNPs in 68 IIS pathway genes and 88 SNPs in 13 TM pathway genes using four self-contained pathway tests (PLINK set-based test, Global test, GRASS and SNP ratio test). Although we observed small differences between the results of the different pathway tests, they showed consistent significant association of the IIS and TM pathway SNP sets with longevity. Analysis of gene SNP sets from these pathways indicates that the association of the IIS pathway is scattered over several genes (AKT1, AKT3, FOXO4, IGF2, INS, PIK3CA, SGK, SGK2, and YWHAG), while the association of the TM pathway seems to be mainly determined by one gene (POT1). In conclusion, this study shows that genetic variation in genes involved in the IIS and TM pathways is associated with human longevity.