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| 2. |
- Chikowore, Tinashe, et al.
(författare)
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GWAS transethnic meta-analysis of BMI in similar to 700k individuals reveals novel gene-smoking interaction in African populations
- 2020
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 44:5, s. 475-476
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Sixty two percent of the 1.12 billion obese people globally reside in low‐middle income countries, 77% of which are in Africa. There is paucity of data on gene‐lifestyle interactions associated with the increasing prevalence of obesity among Africans. We hypothesised that gene‐environment interacting (GEI) variants exhibit heterogenous effects on obesity in transethnic meta‐analysis of marginal SNP associations as a result of modification by an unknown exposure that varies across populations.Body mass index (BMI) genome‐wide association study (GWAS) summary statistics for 678,671 individuals representative of the major global ancestries were aggregated at 21,338,816 SNPs via fixed‐effects meta‐analysis. Lead SNPs attaining genome‐wide significance (P < 5 × 10−8) were tested for heterogeneity in effects between GWAS. Lead SNPs with significant evidence of heterogeneity after Bonferroni correction were then selected for interaction analysis with selected lifestyle factors in an independent AWI‐Gen study of 10,500 African participants. Significant interaction findings were then replicated in 3,177 individuals of African ancestry in the UK Biobank.Of 881 lead SNPs, five had significant heterogenous effects on BMI (P < 5.7 × 10−5). Rs471094, at the CDKAL1 locus had significant interaction with smoking status, which reduced the effect of the BMI raising allele in current smokers (Betaint = −0.949 kg/m2; P int = .002) compared with non‐smokers in AWI‐Gen. This finding was validated in the UK Biobank (Betaint = −1.471 kg/m2, P int = .020; meta‐analysis Betaint = −1.050 kg/m2, P int = .0002). Our results highlight the first gene‐lifestyle interaction on BMI in Africans and demonstrate the utility of transethnic meta‐analysis of GWAS for identifying GEI effects.
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| 4. |
- Din, Lennox, et al.
(författare)
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Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes
- 2019
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Ingår i: Genetic Epidemiology. - : WILEY. - 0741-0395 .- 1098-2272. ; 43:7, s. 844-863
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Tidskriftsartikel (refereegranskat)abstract
- Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p =.0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.
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| 5. |
- Feng, Helian, et al.
(författare)
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Cross-cancer cross-tissue Transcriptome-wide Association Study (TWAS) of 11 cancers identifies 56 novel genes
- 2020
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 44:5, s. 481-481
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Though heterogeneous, multiple tumor types share hallmark mechanisms. Thus, identifying genes associated with multiple cancer types may shed light on general oncogenic mechanisms and identify genes missed in single‐cancer analyses. TWAS have been successful in testing whether genetically‐predicted tissue‐specific gene expression is associated with cancer risk. Although cross‐cancer genome‐wide association studies (GWAS) analyses have been performed previously, no cross‐cancer TWAS has been conducted to date. Here, we implement a pipeline to perform cross‐cancer, cross‐tissue TWAS analysis. We use newly‐developed multi‐trait TWAS test statistics to integrate the TWAS results for association between 11 separated cancers and predicted gene expression in 43 GTEx tissues, including a “sum” test and a “variance components” test, analogous to fixed‐ and random‐effects meta‐analyses. We then integrated the results across different tissues using the Aggregated Cauchy Association Test (ACAT) combined test.A total of 403 genes were significantly associated with at least one cancer type for at least one tissue; 96 additional genes were identified when combining test results across cancers; and 35 additional genes when further combining test results across tissue. Among these significant genes, 70 were not near previously‐published GWAS index variants. 14 of the 70 novel genes were identified from the single‐cancer single‐tissue test; an additional 43 were identified with the cross‐cancer test; and another 13 were identified when further combined across tissues. The newly identified genes, including RBBP8 and TP53BP , are involved in chromatin structure, tumorigenesis, apoptosis, transcriptional regulation, DNA repair, immune system, oxidative damage and cell‐cycle, proliferation, progression, shape, structure, and migration.
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| 9. |
- Helle, Emmi, et al.
(författare)
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Loss of function, missense, and intronic variants in NOTCH1 confer different risks for left ventricular outflow tract obstructive heart defects in two European cohorts
- 2019
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395 .- 1098-2272. ; 43:2, s. 215-226
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Tidskriftsartikel (refereegranskat)abstract
- Loss of function variants in NOTCH1 cause left ventricular outflow tract obstructive defects (LVOTO). However, the risk conferred by rare and noncoding variants in NOTCH1 for LVOTO remains largely uncharacterized. In a cohort of 49 families affected by hypoplastic left heart syndrome, a severe form of LVOTO, we discovered predicted loss of function NOTCH1 variants in 6% of individuals. Rare or low-frequency missense variants were found in 16% of families. To make a quantitative estimate of the genetic risk posed by variants in NOTCH1 for LVOTO, we studied associations of 400 coding and noncoding variants in NOTCH1 in 1,085 cases and 332,788 controls from the UK Biobank. Two rare intronic variants in strong linkage disequilibrium displayed significant association with risk for LVOTO amongst European-ancestry individuals. This result was replicated in an independent analysis of 210 cases and 68,762 controls of non-European and mixed ancestry. In conclusion, carrying rare predicted loss of function variants in NOTCH1 confer significant risk for LVOTO. In addition, the two intronic variants seem to be associated with an increased risk for these defects. Our approach demonstrates the utility of population-based data sets in quantifying the specific risk of individual variants for disease-related phenotypes.
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| 10. |
- Huang, Lucy, et al.
(författare)
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Haplotype variation and genotype imputation in African populations
- 2011
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395 .- 1098-2272. ; 35:8, s. 766-780
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Tidskriftsartikel (refereegranskat)abstract
- Sub-Saharan Africa has been identified as the part of the world with the greatest human genetic diversity. This high level of diversity causes difficulties for genome-wide association (GWA) studies in African populationsfor example, by reducing the accuracy of genotype imputation in African populations compared to non-African populations. Here, we investigate haplotype variation and imputation in Africa, using 253 unrelated individuals from 15 Sub-Saharan African populations. We identify the populations that provide the greatest potential for serving as reference panels for imputing genotypes in the remaining groups. Considering reference panels comprising samples of recent African descent in Phase 3 of the HapMap Project, we identify mixtures of reference groups that produce the maximal imputation accuracy in each of the sampled populations. We find that optimal HapMap mixtures and maximal imputation accuracies identified in detailed tests of imputation procedures can instead be predicted by using simple summary statistics that measure relationships between the pattern of genetic variation in a target population and the patterns in potential reference panels. Our results provide an empirical basis for facilitating the selection of reference panels in GWA studies of diverse human populations, especially those of African ancestry.
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| 13. |
- Karvanen, Juha, et al.
(författare)
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The impact of newly identified loci on coronary heart disease, stroke and total mortality in the MORGAM prospective cohorts.
- 2009
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395 .- 1098-2272. ; 33:3, s. 237-246
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Tidskriftsartikel (refereegranskat)abstract
- Recently, genome wide association studies (GWAS) have identified a number of single nucleotide polymorphisms (SNPs) as being associated with coronary heart disease (CHD). We estimated the effect of these SNPs on incident CHD, stroke and total mortality in the prospective cohorts of the MORGAM Project. We studied cohorts from Finland, Sweden, France and Northern Ireland (total N=33,282, including 1,436 incident CHD events and 571 incident stroke events). The lead SNPs at seven loci identified thus far and additional SNPs (in total 42) were genotyped using a case-cohort design. We estimated the effect of the SNPs on disease history at baseline, disease events during follow-up and classic risk factors. Multiple testing was taken into account using false discovery rate (FDR) analysis. SNP rs1333049 on chromosome 9p21.3 was associated with both CHD and stroke (HR=1.20, 95% CI 1.08-1.34 for incident CHD events and 1.15, 0.99-1.34 for incident stroke). SNP rs11670734 (19q12) was associated with total mortality and stroke. SNP rs2146807 (10q11.21) showed some association with the fatality of acute coronary event. SNP rs2943634 (2q36.3) was associated with high density lipoprotein (HDL) cholesterol and SNPs rs599839, rs4970834 (1p13.3) and rs17228212 (15q22.23) were associated with non-HDL cholesterol. SNPs rs2943634 (2q36.3) and rs12525353 (6q25.1) were associated with blood pressure. These findings underline the need for replication studies in prospective settings and confirm the candidacy of several SNPs that may play a role in the etiology of cardiovascular disease.
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| 14. |
- Kurbasic, Azra, et al.
(författare)
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A general method for linkage disequilibrium correction for multipoint linkage and association.
- 2008
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395 .- 1098-2272. ; 32:7, s. 647-657
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Tidskriftsartikel (refereegranskat)abstract
- Lately, many different methods of linkage, association or joint analysis for family data have been invented and refined. Common to most of those is that they require a map of markers that are in linkage equilibrium. However, at the present day, high-density single nucleotide polymorphisms (SNPs) maps are both more inexpensive to create and they have lower genotyping error. When marker data is incomplete, the crucial and computationally most demanding moment in the analysis is to calculate the inheritance distribution at a certain position on the chromosome. Recently, different ways of adjusting traditional methods of linkage analysis to denser maps of SNPs in linkage disequilibrium (LD) have been proposed. We describe a hidden Markov model which generalizes the Lander-Green algorithm. It combines Markov chain for inheritance vectors with a Markov chain modelling founder haplotypes and in this way takes account for LD between SNPs. It can be applied to association, linkage or combined association and linkage analysis, general phenotypes and arbitrary score functions. We also define a joint likelihood for linkage and association that extends an idea of Kong and Cox (1997 Am. J. Hum. Genet. 61: 1179-1188) for pure linkage analysis. Genet. Epidemiol. 2008. (c) 2008 Wiley-Liss, Inc.
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| 23. |
- Melin, Beatrice S., et al.
(författare)
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hTERT Cancer Risk Genotypes Are Associated With Telomere Length
- 2012
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Ingår i: Genetic Epidemiology. - Malden : Wiley-Blackwell. - 0741-0395 .- 1098-2272. ; 36:4, s. 368-372
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Tidskriftsartikel (refereegranskat)abstract
- Telomere biology is associated with cancer initiation and prognosis. Collected data suggest that blood cell telomere length (TL) can change over time, which may be related to development of common disorders, such as cardiovascular diseases and cancer. Recently, single nucleotide polymorphisms in the region of the human telomerase reverse transcriptase (hTERT) gene were associated with various malignancies, including glioma, lung and urinary bladder cancer, and telomerase RNA gene hTERC genotypes were recently linked to TL. In the present study a hypothetical association between identified genotypes in hTERT and hTERC genes and TL were investigated. We analyzed 21 polymorphisms, covering 90% of the genetic variance, in the hTERT gene, two genetic variants in hTERC, and relative TL(RTL) at average age 50 and 60 in 959 individuals with repeated blood samples. Mean RTL at age 60 was associated with four genetic variants of the hTERT gene (rs2736100, rs2853672, rs2853677, and rs2853676), two of which reported to be associated with cancer risk. Two alleles (rs12696304, rs16847897) near the hTERC gene were confirmed as also being associated with RTL at age 60. Our data suggest that hTERT and hTERC genotypes have an impact on TL of potential relevance and detectable first at higher ages, which gives us further insight to the complex regulation of TL. Genet. Epidemiol. 36:368-372, 2012. (c) 2012 Wiley Periodicals, Inc.
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| 30. |
- Sofer, Tamar, et al.
(författare)
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A fully adjusted two-stage procedure for rank-normalization in genetic association studies
- 2019
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 43:3, s. 263-275
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Tidskriftsartikel (refereegranskat)abstract
- When testing genotype–phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. Because genotypes are expected to have small effects (if any) investigators now routinely use a two‐stage method, in which they first regress the trait on covariates, obtain residuals, rank‐normalize them, and then use the rank‐normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice, no further adjustment is done in the second stage. Here, we show that this widely used approach can lead to tests with undesirable statistical properties, due to both combination of a mis‐specified mean–variance relationship and remaining covariate associations between the rank‐normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome‐wide and whole‐genome sequencing association studies. We further propose and evaluate an alternative fully adjusted two‐stage approach that adjusts for covariates both when residuals are obtained and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.
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| 31. |
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| 32. |
- Sun, Ryan, et al.
(författare)
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Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer
- 2021
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 45:1, s. 99-114
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Tidskriftsartikel (refereegranskat)abstract
- Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1 beta pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-kappa B signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.
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| 33. |
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| 34. |
- Yang, Tianzhong, et al.
(författare)
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Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer
- 2020
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Ingår i: Genetic Epidemiology. - : Wiley-Blackwell. - 0741-0395 .- 1098-2272. ; 44:8, s. 880-892
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Tidskriftsartikel (refereegranskat)abstract
- It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G x E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G x E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes,TRIP10andKDM3A, were identified. The aGEw test is implemented in an R package aGE.
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| 35. |
- Yin, ZY, et al.
(författare)
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Fast eQTL Analysis for Twin Studies
- 2015
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Ingår i: Genetic epidemiology. - : Wiley. - 1098-2272 .- 0741-0395. ; 39:5, s. 357-365
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Tidskriftsartikel (refereegranskat)
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| 46. |
- Guey, Lin T., et al.
(författare)
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Power in the Phenotypic Extremes: A Simulation Study of Power in Discovery and Replication of Rare Variants
- 2011
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Ingår i: Genetic Epidemiology. - : Wiley. - 0741-0395. ; 35:4, s. 236-246
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Tidskriftsartikel (refereegranskat)abstract
- Next-generation sequencing technologies are making it possible to study the role of rare variants in human disease. Many studies balance statistical power with cost-effectiveness by (a) sampling from phenotypic extremes and (b) utilizing a two-stage design. Two-stage designs include a broad-based discovery phase and selection of a subset of potential causal genes/variants to be further examined in independent samples. We evaluate three parameters: first, the gain in statistical power due to extreme sampling to discover causal variants; second, the informativeness of initial (Phase I) association statistics to select genes/variants for follow-up; third, the impact of extreme and random sampling in (Phase 2) replication. We present a quantitative method to select individuals from the phenotypic extremes of a binary trait, and simulate disease association studies under a variety of sample sizes and sampling schemes. First, we find that while studies sampling from extremes have excellent power to discover rare variants, they have limited power to associate them to phenotype-suggesting high false-negative rates for upcoming studies. Second, consistent with previous studies, we find that the effect sizes estimated in these studies are expected to be systematically larger compared with the overall population effect size; in a well-cited lipids study, we estimate the reported effect to be twofold larger. Third, replication studies require large samples from the general population to have sufficient power; extreme sampling could reduce the required sample size as much as fourfold. Our observations offer practical guidance for the design and interpretation of studies that utilize extreme sampling. Genet. Epidemiol. 35: 236-246, 2011. (c) 2011 Wiley-Liss, Inc.
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| 50. |
- Hemminki, K, et al.
(författare)
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Estimation of genetic and environmental components in colorectal and lung cancer and melanoma
- 2001
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Ingår i: GENETIC EPIDEMIOLOGY. - : WILEY-LISS. - 0741-0395. ; 20:1, s. 107-116
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Tidskriftsartikel (refereegranskat)abstract
- Cancer has predominant environmental and somatic causes but the assessment of hereditary (genetic) causes is difficult, except for highly penetrant single-gene causes. Family studies are only partially informative in this regard because family members sha
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