scholarly journals Novel genetic determinants of telomere length from a trans-ethnic analysis of 109,122 whole genome sequences in TOPMed

2019 ◽  
Author(s):  
Margaret A Taub ◽  
Matthew P Conomos ◽  
Rebecca Keener ◽  
Kruthika R Iyer ◽  
Joshua S Weinstock ◽  
...  

ABSTRACTTelomeres shorten in replicating somatic cells, and telomere length (TL) is associated with age-related diseases 1,2. To date, 17 genome-wide association studies (GWAS) have identified 25 loci for leukocyte TL 3–19, but were limited to European and Asian ancestry individuals and relied on laboratory assays of TL. In this study from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of TL in n=109,122 trans-ethnic (European, African, Asian and Hispanic/Latino) individuals. We identified 59 sentinel variants (p-value <5×10−9) from 36 loci (20 novel, 13 replicated in external datasets). There was little evidence of effect heterogeneity across populations, and 10 loci had >1 independent signal. Fine-mapping at OBFC1 indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). We further identified two novel genes, DCLRE1B (SNM1B) and PARN, using a multi-variant gene-based approach.

2017 ◽  
Vol 55 (1) ◽  
pp. 64-71 ◽  
Author(s):  
Dayana A Delgado ◽  
Chenan Zhang ◽  
Lin S Chen ◽  
Jianjun Gao ◽  
Shantanu Roy ◽  
...  

BackgroundLeucocyte telomere length (TL) is a potential biomarker of ageing and risk for age-related disease. Leucocyte TL is heritable and shows substantial differences by race/ethnicity. Recent genome-wide association studies (GWAS) report ~10 loci harbouring SNPs associated with leucocyte TL, but these studies focus primarily on populations of European ancestry.ObjectiveThis study aims to enhance our understanding of genetic determinants of TL across populations.MethodsWe performed a GWAS of TL using data on 5075 Bangladeshi adults. We measured TL using one of two technologies (qPCR or a Luminex-based method) and used standardised variables as TL phenotypes.ResultsOur results replicate previously reported associations in the TERC and TERT regions (P=2.2×10−8 and P=6.4×10−6, respectively). We observed a novel association signal in the RTEL1 gene (intronic SNP rs2297439; P=2.82×10−7) that is independent of previously reported TL-associated SNPs in this region. The minor allele for rs2297439 is common in South Asian populations (≥0.25) but at lower frequencies in other populations (eg, 0.07 in Northern Europeans). Among the eight other previously reported association signals, all were directionally consistent with our study, but only rs8105767 (ZNF208) was nominally significant (P=0.003). SNP-based heritability estimates were as high as 44% when analysing close relatives but much lower when analysing distant relatives only.ConclusionsIn this first GWAS of TL in a South Asian population, we replicate some, but not all, of the loci reported in prior GWAS of individuals of European ancestry, and we identify a novel second association signal at the RTEL1 locus.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 715-715
Author(s):  
Seishi Ogawa ◽  
Aiko Matsubara ◽  
Koichi Kashiwase ◽  
Makoto Onizuka ◽  
Masashi Sanada ◽  
...  

Abstract Allogeneic stem cell transplantation (allo-SCT) is one of the most effective therapeutic options for blood cell cancers. While its major anti-leukemic benefits are obtained from allo-immune reactions against leukemic cells, or GVL, the same kind of allo-reactions could be also directed to normal host tissues, giving rise to a severe complication, know as graft versus host disease (GvHD). In HLA-matched transplantation, the development of both reactions absolutely depends on the presence of one or more mismatched minor histocompatibility antigens (mHAgs) and could be further modified by other genetic as well as environmental factors, including for example, cytokine polymorphisms and GvHD prophylaxis. Thus, in view of better preventing GvHD and specifically targeting allo-immunity to the tumor component, it is critical to understand what mHAgs are mismatched and responsible for the development of GVHD or GVL and what genetic factors can influence the overall reactions. To address these questions, we conducted whole genome association studies by genotyping more than 500,000 SNPs in donors and recipients of 1598 unrelated transplants from Japan Marrow Donation Program (JMDP). All transplants were matched for HLA-A, B, C, DRB1 and DQB1, while 1033 (63%) transplants were mismatched for HLA-DPB1. 656 (41.7%) and 245 (14.9%) of transplants had developed grade II–IV and III–IV of acute GvHD (aGvHD), respectively. Overall call rates exceeded 98% both in donors and in recipients. Unobserved HapMap PhaseII SNPs were rigorously imputed using genotyped SNPs. After excluding those SNPs showing <95% call rate, deviation from Hardy-Weinberg equilibrium, or <5% minor allele frequency, 1,276,699 SNPs were tested for association with development of acute and chronic GvHD, relapse, and overall survival, by calculating LogRank statistics for each SNP according to single genotypes in donors and recipients or based on mismatch in genotypes between donor and recipient. Statistical thresholds for genome-wide-P value of 0.05 were determined empirically by doing 1,000 permutations for each analysis. In the analysis of mismatched genotypes, SNPs around the HLA-DPB1 locus uniquely showed a strong association with the development of >grade II aGvHD with the maximum P-value of 1.81 × 10−9 at rs6937034, and thus, successfully captured the association of DPB1 allele mismatch as directly defined by HLA typing (HR = 1.91, P= 2.88 × 10−13). To facilitate the identification of target mHAgs for aGvHD, we performed subgroup analysis, where association tests were confined to those transplants sharing particular HLA types based on the fact that recognition of mHAgs is restricted to particular HLA contexts (HLA restriction). Six loci was identified as candidate mHAg loci whose mismatch may confer increased risk for development of aGvHD. These included rs17473423 on chr12 associated with an A*2402/B*5201/Cw*1202/DRB1*1501/DQB1*0601 allele set shared in ~40% of unrelated transplants in Japanese (grade III–IV aGvHD with maximum P=3.99 × 10−13), rs9657655 on chr9 associated with another common allele in Japanese, A*3303/B*4403/Cw*1403 (grade III–IV aGvHD with maximum P=8.56 × 10−10), and other four loci associated with DQB1*0501, Cw*0102, B*5201, and Cw*1202. Two SNPs in patients were also found to be associated with aGvHD, rs5998746 on chr22 (P=3.41 × 10−8) and rs11873016 on chr18 (P=1.26 × 10−8), although no donor SNPs showed significant associations). Similarly, we identified four candidate SNPs associated with the development of severe cGvHD or relapse. Current study provided a unique opportunity in that combination of two different genotypes, not merely genotypes of single individuals, that is associated with particular disease phenotypes, is explored by whole genome association scans. Although further replication studies and biological confirmation are required, our results suggest that whole genome association studies of allo-SCT could provide a novel clue to understanding the genetic basis of allo-SCT.


2019 ◽  
Author(s):  
Jude Gibson ◽  
Tom C. Russ ◽  
Toni-Kim Clarke ◽  
David M. Howard ◽  
Kathryn L. Evans ◽  
...  

Abstract‘Epigenetic age acceleration’ is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC,TPMT) and immune system pathways (TRIM59,EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3,MANBA,TRIM46), with metabolic functions (UBE2D3,MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father’s age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.Author SummaryDNA methylation, a type of epigenetic process, is known to vary with age. Methylation levels at specific sites across the genome can be combined to form estimates of age known as ‘epigenetic age’. The difference between epigenetic age and chronological age is referred to as ‘epigenetic age acceleration’, with positive values indicating that a person is biologically older than their years. Understanding why some people seem to age faster than others could shed light on the biological processes behind age-related decline; however, the mechanisms underlying differential rates of epigenetic ageing are largely unknown. Here, we investigate genetic determinants of two commonly used epigenetic age acceleration measures, based on the Horvath and Hannum epigenetic clocks. We report novel genetic variants and genes associated with epigenetic age acceleration, and highlight differences in the genetic factors influencing these two measures. We identify ten genetic variants and 21 genes associated with Horvath-based epigenetic age acceleration, and one variant and 12 genes associated with the Hannum-based measure. There were no genome-wide significant variants or genes in common between the Horvath-based and Hannum-based measures, supporting the hypothesis that they represent different aspects of ageing. Our results suggest a partial genetic basis underlying some previously reported phenotypic associations.


2017 ◽  
Author(s):  
Daniel J. Wilson

Analysis of ‘big data’ frequently involves statistical comparison of millions of competing hypotheses to discover hidden processes underlying observed patterns of data, for example in the search for genetic determinants of disease in genome-wide association studies (GWAS). Controlling the family-wise error rate (FWER) is considered the strongest protection against false positives, but makes it difficult to reach the multiple testing-corrected significance threshold. Here I introduce the harmonic mean p-value (HMP) which controls the FWER while greatly improving statistical power by combining dependent tests using generalized central limit theorem. I show that the HMP easily combines information to detect statistically significant signals among groups of individually nonsignificant hypotheses in examples of a human GWAS for neuroticism and a joint human-pathogen GWAS for hepatitis C viral load. The HMP simultaneously tests all combinations of hypotheses, allowing the smallest groups of hypotheses that retain significance to be sought. The power of the HMP to detect significant hypothesis groups is greater than the power of the Benjamini-Hochberg procedure to detect significant hypotheses, even though the latter only controls the weaker false discovery rate (FDR). The HMP has broad implications for the analysis of large datasets because it enhances the potential for scientific discovery.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 243-244
Author(s):  
Brittany N Diehl ◽  
Andres A Pech-Cervantes ◽  
Thomas H Terrill ◽  
Ibukun M Ogunade ◽  
Owen Rae ◽  
...  

Abstract Florida Native sheep is an indigenous breed from Florida and expresses superior parasite resistance. Previous candidate and genome wide association studies with Florida Native sheep have identified single nucleotide polymorphisms with additive and non-additive effects associated with parasite resistance. However, the role of other potential DNA variants, such as copy number variants (CNVs), controlling this complex trait have not been evaluated. The objective of the present study was to investigate the importance of CNVs on resistance to natural Haemonchus contortus infections in Florida Native sheep. A total of 200 sheep were evaluated in the present study. Phenotypic records included fecal egg count (FEC, eggs/gram), FAMACHA score, and packed cell volume (PCV, %). Sheep were genotyped using the GGP Ovine 50K SNP chip. The copy number analysis was used to identify CNVs using the univariate method. A total of 170 animals with CNVs and phenotypic data were used for the association testing. Association tests were carried out using single linear regression and Principal Component Analysis (PCA) correction to identify CNVs associated with FEC, FAMACHA, and PCV. To confirm our results, a second association testing using the correlation-trend test with PCA correction was performed. Significant CNVs were detected when their adjusted p-value was &lt; 0.05 after FDR correction. A deletion CNV in chromosome 21 was associated with FEC. This DNA variant was located in intron 2 of RAB3IL gene and overlapped a QTL associated with changes in eosinophil number. Our study demonstrated for the first time that CNVs could be potentially involved with parasite resistance in this heritage sheep breed.


2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Gabriel Costa Monteiro Moreira ◽  
Clarissa Boschiero ◽  
Aline Silva Mello Cesar ◽  
James M. Reecy ◽  
Thaís Fernanda Godoy ◽  
...  

Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.


2021 ◽  
Author(s):  
Ronald J Yurko ◽  
Kathryn Roeder ◽  
Bernie Devlin ◽  
Max G'Sell

In genome-wide association studies (GWAS), it has become commonplace to test millions of SNPs for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a gene's test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive p-value thresholding (AdaPT), guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.


2019 ◽  
Vol 116 (4) ◽  
pp. 1195-1200 ◽  
Author(s):  
Daniel J. Wilson

Analysis of “big data” frequently involves statistical comparison of millions of competing hypotheses to discover hidden processes underlying observed patterns of data, for example, in the search for genetic determinants of disease in genome-wide association studies (GWAS). Controlling the familywise error rate (FWER) is considered the strongest protection against false positives but makes it difficult to reach the multiple testing-corrected significance threshold. Here, I introduce the harmonic mean p-value (HMP), which controls the FWER while greatly improving statistical power by combining dependent tests using generalized central limit theorem. I show that the HMP effortlessly combines information to detect statistically significant signals among groups of individually nonsignificant hypotheses in examples of a human GWAS for neuroticism and a joint human–pathogen GWAS for hepatitis C viral load. The HMP simultaneously tests all ways to group hypotheses, allowing the smallest groups of hypotheses that retain significance to be sought. The power of the HMP to detect significant hypothesis groups is greater than the power of the Benjamini–Hochberg procedure to detect significant hypotheses, although the latter only controls the weaker false discovery rate (FDR). The HMP has broad implications for the analysis of large datasets, because it enhances the potential for scientific discovery.


2019 ◽  
Vol 20 (10) ◽  
pp. 765-780 ◽  
Author(s):  
Diana Cruz ◽  
Ricardo Pinto ◽  
Margarida Freitas-Silva ◽  
José Pedro Nunes ◽  
Rui Medeiros

Atrial fibrillation (AF) and stroke are included in a group of complex traits that have been approached regarding of their study by susceptibility genetic determinants. Since 2007, several genome-wide association studies (GWAS) aiming to identify genetic variants modulating AF risk have been conducted. Thus, 11 GWAS have identified 26 SNPs (p < 5 × 10-2), of which 19 reached genome-wide significance (p < 5 × 10-8). From those variants, seven were also associated with cardioembolic stroke and three reached genome-wide significance in stroke GWAS. These associations may shed a light on putative shared etiologic mechanisms between AF and cardioembolic stroke. Additionally, some of these identified variants have been incorporated in genetic risk scores in order to elucidate new approaches of stroke prediction, prevention and treatment.


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