ORCID Profile
0000-0002-8676-7709
Current Organisation
KU Leuven
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Publisher: Elsevier BV
Date: 07-2023
Publisher: Springer Science and Business Media LLC
Date: 13-09-2018
DOI: 10.1038/S41467-018-04989-W
Abstract: Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.
Publisher: Springer Science and Business Media LLC
Date: 11-06-2018
Publisher: Springer Science and Business Media LLC
Date: 10-01-2019
DOI: 10.1038/S41467-018-08107-8
Abstract: The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article the PDF version was correct at the time of publication.
Publisher: Springer Science and Business Media LLC
Date: 21-01-2019
DOI: 10.1038/S41467-018-08106-9
Abstract: The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article the PDF version was correct at the time of publication.
Publisher: Springer Science and Business Media LLC
Date: 08-01-2019
DOI: 10.1038/S41467-018-08108-7
Abstract: The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, In the original HTML version of this Article, the order of authors within the author list was incorrect. The consortium PRACTICAL consortium was incorrectly listed after Bogdan Pasaniuc and should have been listed after Kathryn L. Penney. This error has been corrected in the HTML version of the Article the PDF version was correct at the time of publication.
Publisher: American Association for Cancer Research (AACR)
Date: 2019
DOI: 10.1158/1055-9965.EPI-18-0079
Abstract: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer–metabolite associations using two-s le Mendelian randomization (MR). The case–control portion of the study was conducted in nine UK centers with men ages 50–69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Thirty-five metabolites were strongly associated with prostate cancer (P & 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios) (ii) fatty acids and ratios (iii) amino acids (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.
Publisher: Oxford University Press (OUP)
Date: 19-03-2018
DOI: 10.1093/IJE/DYY016
Publisher: Springer Science and Business Media LLC
Date: 08-01-2021
Publisher: Springer Science and Business Media LLC
Date: 05-11-2018
DOI: 10.1038/S41467-018-06863-1
Abstract: Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer ( p 4.28 × 10 −15 ), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
Publisher: Springer Science and Business Media LLC
Date: 24-03-2020
DOI: 10.1038/S41467-020-14451-5
Abstract: The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective s le size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes.
Publisher: Cold Spring Harbor Laboratory
Date: 25-10-2018
DOI: 10.1101/453480
Abstract: Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer ( r g =0.57, p=4.6×10 −8 ), breast and ovarian cancer ( r g =0.24, p=7×10 −5 ), breast and lung cancer ( r g =0.18, p=1.5×10 −6 ) and breast and colorectal cancer ( r g =0.15, p=1.1×10 −4 ). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
Publisher: Springer Science and Business Media LLC
Date: 06-08-2020
DOI: 10.1038/S41467-020-17673-9
Abstract: It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.
Publisher: Springer Science and Business Media LLC
Date: 03-06-2020
DOI: 10.1038/S41586-020-2338-1
Abstract: High blood cholesterol is typically considered a feature of wealthy western countries 1,2 . However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world 3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health 4,5 . However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million in iduals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 08-2015
DOI: 10.1016/J.MCE.2015.04.030
Abstract: Androgen deficiency or androgen receptor knockout (ARKO) causes high-turnover osteopenia, but the target cells for this effect remain unclear. To examine whether AR in osteoclasts directly suppresses bone resorption, we crossed AR-floxed with cathepsin K-Cre mice. Osteoclast-specific ARKO (ocl-ARKO) mice showed no changes neither in osteoclast surface nor in bone microarchitecture nor in the response to orchidectomy and androgen replacement, indicating that the AR in osteoclasts is not critical for bone maintenance. In line with the lack of a bone phenotype, the levels of AR were very low in osteoclast-enriched cultures derived from bone marrow (BM) and undetectable in osteoclasts generated from spleen precursors. Since tibiae of ubiquitous ARKO mice displayed increased osteoclast counts, the role of AR was further explored using cell cultures from these animals. Osteoclast generation and activity in vitro were similar between ARKO and wildtype control (WT) mice. In co-culture experiments, BM stromal cells (BMSCs) were essential for the suppressive action of AR on osteoclastogenesis and osteoclast activity. Stimulation with 1,25(OH)2 vitamin D3 increased Rankl and decreased Tnfsf11 (osteoprotegerin, Opg) gene expression in BMSCs more than in osteoblasts. This increase in the Rankl/Opg ratio following 1,25(OH)2D3 stimulation was lower, not higher, in ARKO mice. Runx2 expression in BMSCs was however higher in ARKO vs. WT, suggesting that ARKO mice may more readily commit osteoprogenitor cells to osteoblastogenesis. In conclusion, the AR does not seem to suppress bone resorption through direct actions in osteoclasts. BMSCs may however represent an alternative AR target in the BM milieu.
Publisher: Springer Science and Business Media LLC
Date: 11-06-2018
DOI: 10.1038/S41467-018-04109-8
Abstract: Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
Publisher: Springer Science and Business Media LLC
Date: 12-02-2022
DOI: 10.1038/S41391-022-00497-7
Abstract: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry—the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for ex le, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43–15.16] in ProtecT, 7.07 [6.58–7.60] in African ancestry, 10.31 [9.58–11.11] in Asian ancestry, and 11.18 [10.34–12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11–0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15–0.22) and 0.26 (0.19–0.33), respectively. We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in erse populations.
Publisher: Springer Science and Business Media LLC
Date: 14-05-2019
DOI: 10.1038/S41467-019-09775-W
Abstract: Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention.
Publisher: Springer Science and Business Media LLC
Date: 04-10-2018
DOI: 10.1038/S41467-018-06302-1
Abstract: Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS ( N = 142,392) with gene expression measured in 45 tissues ( N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.
Publisher: Cold Spring Harbor Laboratory
Date: 19-11-2019
DOI: 10.1101/19012237
Abstract: A polygenic hazard score (PHS 1 )—weighted sum of 54 single-nucleotide polymorphism genotypes—was previously associated with age at prostate cancer (PCa) diagnosis and improved PCa screening accuracy in Europeans. Performance in more erse populations is unknown. We evaluated PHS association with PCa in multi-ethnic populations. PHS 1 was adapted for compatibility with genotype data from the OncoArray project (PHS 2 ) and tested for association with age at PCa diagnosis, at aggressive PCa diagnosis, and at PCa death. Multiple international institutions. Men with available OncoArray data from the PRACTICAL consortium who were not included in PHS 1 development/validation. PHS 2 was tested via Cox proportional hazards models for age at PCa diagnosis, age at aggressive PCa diagnosis (any of: Gleason score ≥7, stage T3-T4, PSA≥10 ng/mL, nodal/distant metastasis), and age at PCa-specific death. 80,491 men of various self-reported race/ethnicities were included (30,575 controls, 49,916 PCa cases genetic ancestry groups: 71,856 European, 6,253 African, 2,382 Asian). Median age at last follow-up was 70 years (IQR 63-76) 3,983 PCa deaths, 5,806 other deaths, 70,702 still alive. PHS 2 had 46 polymorphisms: 24 directly genotyped and 22 acceptable proxies (r 2 ≥0.94). PHS 2 was associated with age at PCa diagnosis in the multi-ethnic dataset (z=54, p -16 ) and in each genetic ancestry group: European (z=56, p -16 ), Asian (z=47, p -16 ), African (z=29, p -16 ). PHS 2 was also associated with age at aggressive PCa diagnosis in each genetic ancestry group (p -16 ) and with age of PCa death in the full dataset ( p -16 ). Comparing the 80 th and 20 th percentiles of genetic risk, men with high PHS had hazard ratios of 5.3 [95% CI: 5.0-5.7], 5.9 [5.5-6.3], and 5.7 [4.6-7.0] for PCa, aggressive PCa, and PCa-specific death, respectively. Within European, Asian, and African ancestries, analogous hazard ratios for PCa were 5.5 [5.2-5.9], 4.5 [3.2-6.3], and 2.5 [2.1-3.1], respectively. PHS 2 is strongly associated with age at PCa diagnosis in a multi-ethnic dataset. PHS 2 stratifies men of European, Asian, and African ancestry by genetic risk for any, aggressive, and fatal PCa. Genetic risk stratification can identify men with greater predisposition for developing prostate cancer, but these risk models may worsen health disparities, as most have only been validated for men of European ancestry A polygenic hazard score was previously associated with age at prostate cancer diagnosis and improved PCa screening accuracy in Europeans Performance of the polygenic hazard score in multi-ethnic populations is unknown In a dataset from 80,491 men of various self-reported race/ethnicities, the polygenic hazard score was associated with age at prostate cancer diagnosis, aggressive prostate cancer diagnosis, and prostate cancer death. PHS stratifies men of European, Asian, and African ancestry by genetic risk for any, aggressive, and fatal prostate cancer.
Publisher: Springer Science and Business Media LLC
Date: 20-01-2021
Publisher: Elsevier BV
Date: 08-2015
Publisher: Springer Science and Business Media LLC
Date: 08-01-2019
DOI: 10.1038/S41467-018-08105-W
Abstract: The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.
Publisher: Cold Spring Harbor Laboratory
Date: 18-08-2021
DOI: 10.1101/2021.08.14.21261931
Abstract: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry—the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for ex le, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively. We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in erse populations.
Publisher: Bioscientifica
Date: 09-06-2014
DOI: 10.1530/ERC-14-0274
Publisher: eLife Sciences Publications, Ltd
Date: 09-03-2021
DOI: 10.7554/ELIFE.60060
Abstract: From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.
Publisher: Elsevier BV
Date: 09-2021
Publisher: Springer Science and Business Media LLC
Date: 29-03-2023
DOI: 10.1038/S41586-023-05772-8
Abstract: Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being 1–6 . Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was .1 kg m –2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have lified.
Publisher: Wiley
Date: 07-2019
DOI: 10.1111/ANDR.12667
Abstract: Testicular germ cell tumour (TGCT) is highly heritable but > 50% of the genetic risk remains unexplained. Epidemiological observation of greater relative risk to brothers of men with TGCT compared to sons has long alluded to recessively acting TGCT genetic susceptibility factors, but to date none have been reported. Runs of homozygosity (RoH) are a signature indicating underlying recessively acting alleles and have been associated with increased risk of other cancer types. To examine whether RoH are associated with TGCT risk. We performed a genome-wide RoH analysis using GWAS data from 3206 TGCT cases and 7422 controls uniformly genotyped using the OncoArray platform. Global measures of homozygosity were not significantly different between cases and controls, and the frequency of in idual consensus RoH was not significantly different between cases and controls, after correction for multiple testing. RoH at three regions, 11p13-11p14.3, 5q14.1-5q22.3 and 13q14.11-13q.14.13, were, however, nominally statistically significant at p < 0.01. Intriguingly, RoH200 at 11p13-11p14.3 encompasses Wilms tumour 1 (WT1), a recognized cancer susceptibility gene with roles in sex determination and developmental transcriptional regulation, processes repeatedly implicated in TGCT aetiology. Overall, our data do not support a major role in the risk of TGCT for recessively acting alleles acting through homozygosity, as measured by RoH in outbred populations of cases and controls.
Publisher: Springer Science and Business Media LLC
Date: 05-2019
Publisher: Springer Science and Business Media LLC
Date: 23-02-2021
DOI: 10.1038/S41467-021-21287-0
Abstract: Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS 1 ) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS 2 (PHS 1 , adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS 2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p 10 −180 ). Comparing the 80 th /20 th PHS 2 percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS 2 risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.
Publisher: eLife Sciences Publications, Ltd
Date: 29-03-2022
DOI: 10.7554/ELIFE.75374
Abstract: Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker. We conducted a two-s le Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671–13,879 N controls = 173,493–372,016), FinnGen (N cases = 719–8401 N controls = 74,685–174,006) and several international cancer genetic consortia (N cases = 11,348–122,977 N controls = 15,861–105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. In idual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach. Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04–1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09–1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97–1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers. GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results. FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic’s Operational Programme ‘Competitiveness, Entrepreneurship & Innovation’ (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer’s Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor’s Research Fellow at the University of Bristol.
Publisher: The Endocrine Society
Date: 09-09-2014
DOI: 10.1210/ER.2014-1024
Publisher: Springer Science and Business Media LLC
Date: 25-01-2019
DOI: 10.1038/S41467-018-08054-4
Abstract: Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer ( r g = 0.57, p = 4.6 × 10 −8 ), breast and ovarian cancer ( r g = 0.24, p = 7 × 10 −5 ), breast and lung cancer ( r g = 0.18, p =1.5 × 10 −6 ) and breast and colorectal cancer ( r g = 0.15, p = 1.1 × 10 −4 ). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
Publisher: Springer Science and Business Media LLC
Date: 12-05-2023
DOI: 10.1007/S00125-023-05925-4
Abstract: Epidemiological studies have generated conflicting findings on the relationship between glucose-lowering medication use and cancer risk. Naturally occurring variation in genes encoding glucose-lowering drug targets can be used to investigate the effect of their pharmacological perturbation on cancer risk. We developed genetic instruments for three glucose-lowering drug targets (peroxisome proliferator activated receptor γ [PPARG] sulfonylurea receptor 1 [ATP binding cassette subfamily C member 8 (ABCC8)] glucagon-like peptide 1 receptor [GLP1R]) using summary genetic association data from a genome-wide association study of type 2 diabetes in 148,726 cases and 965,732 controls in the Million Veteran Program. Genetic instruments were constructed using cis -acting genome-wide significant ( p ×10 −8 ) SNPs permitted to be in weak linkage disequilibrium ( r 2 .20). Summary genetic association estimates for these SNPs were obtained from genome-wide association study (GWAS) consortia for the following cancers: breast (122,977 cases, 105,974 controls) colorectal (58,221 cases, 67,694 controls) prostate (79,148 cases, 61,106 controls) and overall (i.e. site-combined) cancer (27,483 cases, 372,016 controls). Inverse-variance weighted random-effects models adjusting for linkage disequilibrium were employed to estimate causal associations between genetically proxied drug target perturbation and cancer risk. Co-localisation analysis was employed to examine robustness of findings to violations of Mendelian randomisation (MR) assumptions. A Bonferroni correction was employed as a heuristic to define associations from MR analyses as ‘strong’ and ‘weak’ evidence. In MR analysis, genetically proxied PPARG perturbation was weakly associated with higher risk of prostate cancer (for PPARG perturbation equivalent to a 1 unit decrease in inverse rank normal transformed HbA 1c : OR 1.75 [95% CI 1.07, 2.85], p =0.02). In histological subtype-stratified analyses, genetically proxied PPARG perturbation was weakly associated with lower risk of oestrogen receptor-positive breast cancer (OR 0.57 [95% CI 0.38, 0.85], p =6.45×10 −3 ). In co-localisation analysis, however, there was little evidence of shared causal variants for type 2 diabetes liability and cancer endpoints in the PPARG locus, although these analyses were likely underpowered. There was little evidence to support associations between genetically proxied PPARG perturbation and colorectal or overall cancer risk or between genetically proxied ABCC8 or GLP1R perturbation with risk across cancer endpoints. Our drug target MR analyses did not find consistent evidence to support an association of genetically proxied PPARG, ABCC8 or GLP1R perturbation with breast, colorectal, prostate or overall cancer risk. Further evaluation of these drug targets using alternative molecular epidemiological approaches may help to further corroborate the findings presented in this analysis. Summary genetic association data for select cancer endpoints were obtained from the public domain: breast cancer ( bcac.ccge.medschl.cam.ac.uk/bcacdata/ ) and overall prostate cancer ( practical.icr.ac.uk/blog/ ). Summary genetic association data for colorectal cancer can be accessed by contacting GECCO (kafdem at fredhutch.org). Summary genetic association data on advanced prostate cancer can be accessed by contacting PRACTICAL (practical at icr.ac.uk). Summary genetic association data on type 2 diabetes from Vujkovic et al (Nat Genet, 2020) can be accessed through dbGAP under accession number phs001672.v3.p1 (pha004945.1 refers to the European-specific summary statistics). UK Biobank data can be accessed by registering with UK Biobank and completing the registration form in the Access Management System (AMS) ( www.ukbiobank.ac.uk/enable-your-research/apply-for-access ).
Publisher: MDPI AG
Date: 04-11-2020
Abstract: The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the CHEK2 recurrent variant c.349A G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case–control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The CHEK2 missense variant c.349A G was found significantly associated with an increased risk for PrCa (OR 1.9 95% CI: 1.1–3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with CHEK2 c.349A G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.
Publisher: Springer Science and Business Media LLC
Date: 2021
No related grants have been discovered for Frank Claessens.