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Probing the Virtual Proteome to Identify Novel Disease Biomarkers.
Mosley JD, Benson MD, Smith JG, Melander O, Ngo D, Shaffer CM, Ferguson JF, Herzig MS, McCarty CA, Chute CG, Jarvik GP, Gordon AS, Palmer MR, Crosslin DR, Larson EB, Carrell DS, Kullo IJ, Pacheco JA, Peissig PL, Brilliant MH, Kitchner TE, Linneman JG, Namjou B, Williams MS, Ritchie MD, Borthwick KM, Kiryluk K, Mentch FD, Sleiman PM, Karlson EW, Verma SS, Zhu Y, Vasan RS, Yang Q, Denny JC, Roden DM, Gerszten RE, Wang TJ
(2018) Circulation 138: 2469-2481
MeSH Terms: Adult, Aged, Aged, 80 and over, Biomarkers, Carotid Artery Diseases, Female, Genome-Wide Association Study, Genotype, Humans, Lectins, C-Type, Male, Middle Aged, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Proteome, Proteomics, Receptor, Platelet-Derived Growth Factor beta
Show Abstract · Added April 2, 2019
BACKGROUND - Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals.
METHODS - We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651).
RESULTS - In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β.
CONCLUSIONS - We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
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18 MeSH Terms
Hypertension genetic risk score is associated with burden of coronary heart disease among patients referred for coronary angiography.
Lukács Krogager M, Skals RK, Appel EVR, Schnurr TM, Engelbrechtsen L, Have CT, Pedersen O, Engstrøm T, Roden DM, Gislason G, Poulsen HE, Køber L, Stender S, Hansen T, Grarup N, Andersson C, Torp-Pedersen C, Weeke PE
(2018) PLoS One 13: e0208645
MeSH Terms: Aged, Cohort Studies, Coronary Angiography, Female, Genetic Predisposition to Disease, Humans, Hypertension, Male, Middle Aged, Models, Genetic, Polymorphism, Single Nucleotide, Risk Assessment
Show Abstract · Added March 24, 2020
BACKGROUND - Recent GWAS studies have identified more than 300 SNPs associated with variation in blood pressure. We investigated whether a genetic risk score constructed from these variants is associated with burden of coronary heart disease.
METHODS - From 2010-2014, 4,809 individuals admitted to coronary angiography in Capital Region of Copenhagen were genotyped. We calculated hypertension GRS comprised of GWAS identified SNPs associated with blood pressure. We performed logistic regression analyses to estimate the risk of hypertension and prevalent CHD. We also assessed the severity of CHD associated with the GRS. The analyses were performed using GRS quartiles. We used the Inter99 cohort to validate our results and to investigate for possible pleiotropy for the GRS with other CHD risk factors.
RESULTS - In COGEN, adjusted odds ratios comparing the 2nd, 3rd and 4th cumulative GRS quartiles with the reference were 1.12(95% CI 0.95-1.33), 1.35(95% CI 1.14-1.59) and 1.29(95% CI 1.09-1.53) respectively, for prevalent CHD. The adjusted multinomial logistic regression showed that 3rd and 4th GRS quartiles were associated with increased odds of developing two(OR 1.33, 95% CI 1.04-1.71 and OR 1.36, 95% CI 1.06-1.75, respectively) and three coronary vessel disease(OR 1.77, 95% CI 1.36-2.30 and OR 1.65, 95% CI 1.26-2.15, respectively). Similar results for incident CHD were observed in the Inter99 cohort. The hypertension GRS did not associate with type 2 diabetes, smoking, BMI or hyperlipidemia.
CONCLUSION - Hypertension GRS quartiles were associated with an increased risk of hypertension, prevalent CHD, and burden of coronary vessel disease in a dose-response pattern. We showed no evidence for pleiotropy with other risk factors for CHD.
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Genetic determinants of risk in pulmonary arterial hypertension: international genome-wide association studies and meta-analysis.
Rhodes CJ, Batai K, Bleda M, Haimel M, Southgate L, Germain M, Pauciulo MW, Hadinnapola C, Aman J, Girerd B, Arora A, Knight J, Hanscombe KB, Karnes JH, Kaakinen M, Gall H, Ulrich A, Harbaum L, Cebola I, Ferrer J, Lutz K, Swietlik EM, Ahmad F, Amouyel P, Archer SL, Argula R, Austin ED, Badesch D, Bakshi S, Barnett C, Benza R, Bhatt N, Bogaard HJ, Burger CD, Chakinala M, Church C, Coghlan JG, Condliffe R, Corris PA, Danesino C, Debette S, Elliott CG, Elwing J, Eyries M, Fortin T, Franke A, Frantz RP, Frost A, Garcia JGN, Ghio S, Ghofrani HA, Gibbs JSR, Harley J, He H, Hill NS, Hirsch R, Houweling AC, Howard LS, Ivy D, Kiely DG, Klinger J, Kovacs G, Lahm T, Laudes M, Machado RD, MacKenzie Ross RV, Marsolo K, Martin LJ, Moledina S, Montani D, Nathan SD, Newnham M, Olschewski A, Olschewski H, Oudiz RJ, Ouwehand WH, Peacock AJ, Pepke-Zaba J, Rehman Z, Robbins I, Roden DM, Rosenzweig EB, Saydain G, Scelsi L, Schilz R, Seeger W, Shaffer CM, Simms RW, Simon M, Sitbon O, Suntharalingam J, Tang H, Tchourbanov AY, Thenappan T, Torres F, Toshner MR, Treacy CM, Vonk Noordegraaf A, Waisfisz Q, Walsworth AK, Walter RE, Wharton J, White RJ, Wilt J, Wort SJ, Yung D, Lawrie A, Humbert M, Soubrier F, Trégouët DA, Prokopenko I, Kittles R, Gräf S, Nichols WC, Trembath RC, Desai AA, Morrell NW, Wilkins MR, UK NIHR BioResource Rare Diseases Consortium, UK PAH Cohort Study Consortium, US PAH Biobank Consortium
(2019) Lancet Respir Med 7: 227-238
MeSH Terms: Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotyping Techniques, HLA-DP alpha-Chains, HLA-DP beta-Chains, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Pulmonary Arterial Hypertension, Risk Assessment, SOXF Transcription Factors, Signal Transduction, Survival Analysis
Show Abstract · Added March 8, 2020
BACKGROUND - Rare genetic variants cause pulmonary arterial hypertension, but the contribution of common genetic variation to disease risk and natural history is poorly characterised. We tested for genome-wide association for pulmonary arterial hypertension in large international cohorts and assessed the contribution of associated regions to outcomes.
METHODS - We did two separate genome-wide association studies (GWAS) and a meta-analysis of pulmonary arterial hypertension. These GWAS used data from four international case-control studies across 11 744 individuals with European ancestry (including 2085 patients). One GWAS used genotypes from 5895 whole-genome sequences and the other GWAS used genotyping array data from an additional 5849 individuals. Cross-validation of loci reaching genome-wide significance was sought by meta-analysis. Conditional analysis corrected for the most significant variants at each locus was used to resolve signals for multiple associations. We functionally annotated associated variants and tested associations with duration of survival. All-cause mortality was the primary endpoint in survival analyses.
FINDINGS - A locus near SOX17 (rs10103692, odds ratio 1·80 [95% CI 1·55-2·08], p=5·13 × 10) and a second locus in HLA-DPA1 and HLA-DPB1 (collectively referred to as HLA-DPA1/DPB1 here; rs2856830, 1·56 [1·42-1·71], p=7·65 × 10) within the class II MHC region were associated with pulmonary arterial hypertension. The SOX17 locus had two independent signals associated with pulmonary arterial hypertension (rs13266183, 1·36 [1·25-1·48], p=1·69 × 10; and rs10103692). Functional and epigenomic data indicate that the risk variants near SOX17 alter gene regulation via an enhancer active in endothelial cells. Pulmonary arterial hypertension risk variants determined haplotype-specific enhancer activity, and CRISPR-mediated inhibition of the enhancer reduced SOX17 expression. The HLA-DPA1/DPB1 rs2856830 genotype was strongly associated with survival. Median survival from diagnosis in patients with pulmonary arterial hypertension with the C/C homozygous genotype was double (13·50 years [95% CI 12·07 to >13·50]) that of those with the T/T genotype (6·97 years [6·02-8·05]), despite similar baseline disease severity.
INTERPRETATION - This is the first study to report that common genetic variation at loci in an enhancer near SOX17 and in HLA-DPA1/DPB1 is associated with pulmonary arterial hypertension. Impairment of SOX17 function might be more common in pulmonary arterial hypertension than suggested by rare mutations in SOX17. Further studies are needed to confirm the association between HLA typing or rs2856830 genotyping and survival, and to determine whether HLA typing or rs2856830 genotyping improves risk stratification in clinical practice or trials.
FUNDING - UK NIHR, BHF, UK MRC, Dinosaur Trust, NIH/NHLBI, ERS, EMBO, Wellcome Trust, EU, AHA, ACClinPharm, Netherlands CVRI, Dutch Heart Foundation, Dutch Federation of UMC, Netherlands OHRD and RNAS, German DFG, German BMBF, APH Paris, INSERM, Université Paris-Sud, and French ANR.
Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.
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16 MeSH Terms
integRATE: a desirability-based data integration framework for the prioritization of candidate genes across heterogeneous omics and its application to preterm birth.
Eidem HR, Steenwyk JL, Wisecaver JH, Capra JA, Abbot P, Rokas A
(2018) BMC Med Genomics 11: 107
MeSH Terms: Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Premature Birth, Proteomics, Trans-Activators, User-Computer Interface
Show Abstract · Added March 3, 2020
BACKGROUND - The integration of high-quality, genome-wide analyses offers a robust approach to elucidating genetic factors involved in complex human diseases. Even though several methods exist to integrate heterogeneous omics data, most biologists still manually select candidate genes by examining the intersection of lists of candidates stemming from analyses of different types of omics data that have been generated by imposing hard (strict) thresholds on quantitative variables, such as P-values and fold changes, increasing the chance of missing potentially important candidates.
METHODS - To better facilitate the unbiased integration of heterogeneous omics data collected from diverse platforms and samples, we propose a desirability function framework for identifying candidate genes with strong evidence across data types as targets for follow-up functional analysis. Our approach is targeted towards disease systems with sparse, heterogeneous omics data, so we tested it on one such pathology: spontaneous preterm birth (sPTB).
RESULTS - We developed the software integRATE, which uses desirability functions to rank genes both within and across studies, identifying well-supported candidate genes according to the cumulative weight of biological evidence rather than based on imposition of hard thresholds of key variables. Integrating 10 sPTB omics studies identified both genes in pathways previously suspected to be involved in sPTB as well as novel genes never before linked to this syndrome. integRATE is available as an R package on GitHub ( https://github.com/haleyeidem/integRATE ).
CONCLUSIONS - Desirability-based data integration is a solution most applicable in biological research areas where omics data is especially heterogeneous and sparse, allowing for the prioritization of candidate genes that can be used to inform more targeted downstream functional analyses.
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MeSH Terms
Bid maintains mitochondrial cristae structure and function and protects against cardiac disease in an integrative genomics study.
Salisbury-Ruf CT, Bertram CC, Vergeade A, Lark DS, Shi Q, Heberling ML, Fortune NL, Okoye GD, Jerome WG, Wells QS, Fessel J, Moslehi J, Chen H, Roberts LJ, Boutaud O, Gamazon ER, Zinkel SS
(2018) Elife 7:
MeSH Terms: Animals, Apoptosis, BH3 Interacting Domain Death Agonist Protein, Beclin-1, Cell Respiration, Fibrosis, Gene Expression Regulation, Genome-Wide Association Study, Genomics, Heart Diseases, Heart Ventricles, Humans, Mice, Inbred C57BL, Mitochondria, Mitochondrial Proton-Translocating ATPases, Mutation, Myeloid Progenitor Cells, Myocardial Infarction, Myocytes, Cardiac, Polymorphism, Single Nucleotide, Protein Multimerization, Protein Structure, Secondary, Protein Subunits, Reactive Oxygen Species, Reproducibility of Results, Up-Regulation
Show Abstract · Added December 11, 2018
Bcl-2 family proteins reorganize mitochondrial membranes during apoptosis, to form pores and rearrange cristae. In vitro and in vivo analysis integrated with human genetics reveals a novel homeostatic mitochondrial function for Bcl-2 family protein Bid. Loss of full-length Bid results in apoptosis-independent, irregular cristae with decreased respiration. mice display stress-induced myocardial dysfunction and damage. A gene-based approach applied to a biobank, validated in two independent GWAS studies, reveals that decreased genetically determined BID expression associates with myocardial infarction (MI) susceptibility. Patients in the bottom 5% of the expression distribution exhibit >4 fold increased MI risk. Carrier status with nonsynonymous variation in Bid's membrane binding domain, Bid, associates with MI predisposition. Furthermore, Bid but not Bid associates with Mcl-1, previously implicated in cristae stability; decreased MCL-1 expression associates with MI. Our results identify a role for Bid in homeostatic mitochondrial cristae reorganization, that we link to human cardiac disease.
© 2018, Salisbury-Ruf et al.
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26 MeSH Terms
Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31.
Wang H, Nandakumar P, Tekola-Ayele F, Tayo BO, Ware EB, Gu CC, Lu Y, Yao J, Zhao W, Smith JA, Hellwege JN, Guo X, Edwards TL, Loos RJF, Arnett DK, Fornage M, Rotimi C, Kardia SLR, Cooper RS, Rao DC, Ehret G, Chakravarti A, Zhu X
(2019) Eur J Hum Genet 27: 269-277
MeSH Terms: African Americans, Chromosomes, Human, Pair 1, Gene Frequency, Genome-Wide Association Study, Humans, Hypertension, Linkage Disequilibrium, Polymorphism, Single Nucleotide
Show Abstract · Added March 3, 2020
High blood pressure (BP) is a major risk factor for cardiovascular disease (CVD) and is more prevalent in African Americans as compared to other US groups. Although large, population-based genome-wide association studies (GWAS) have identified over 300 common polymorphisms modulating inter-individual BP variation, largely in European ancestry subjects, most of them do not localize to regions previously identified through family-based linkage studies. This discrepancy has remained unexplained despite the statistical power differences between current GWAS and prior linkage studies. To address this issue, we performed genome-wide linkage analysis of BP traits in African-American families from the Family Blood Pressure Program (FBPP) and genotyped on the Illumina Human Exome BeadChip v1.1. We identified a genomic region on chromosome 1q31 with LOD score 3.8 for pulse pressure (PP), a region we previously implicated in DBP studies of European ancestry families. Although no reported GWAS variants map to this region, combined linkage and association analysis of PP identified 81 rare and low frequency exonic variants accounting for the linkage evidence. Replication analysis in eight independent African ancestry cohorts (N = 16,968) supports this specific association with PP (P = 0.0509). Additional association and network analyses identified multiple potential candidate genes in this region expressed in multiple tissues and with a strong biological support for a role in BP. In conclusion, multiple genes and rare variants on 1q31 contribute to PP variation. Beyond producing new insights into PP, we demonstrate how family-based linkage and association studies can implicate specific rare and low frequency variants for complex traits.
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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, Ntritsos G, Dimou N, Cabrera CP, Karaman I, Ng FL, Evangelou M, Witkowska K, Tzanis E, Hellwege JN, Giri A, Velez Edwards DR, Sun YV, Cho K, Gaziano JM, Wilson PWF, Tsao PS, Kovesdy CP, Esko T, Mägi R, Milani L, Almgren P, Boutin T, Debette S, Ding J, Giulianini F, Holliday EG, Jackson AU, Li-Gao R, Lin WY, Luan J, Mangino M, Oldmeadow C, Prins BP, Qian Y, Sargurupremraj M, Shah N, Surendran P, Thériault S, Verweij N, Willems SM, Zhao JH, Amouyel P, Connell J, de Mutsert R, Doney ASF, Farrall M, Menni C, Morris AD, Noordam R, Paré G, Poulter NR, Shields DC, Stanton A, Thom S, Abecasis G, Amin N, Arking DE, Ayers KL, Barbieri CM, Batini C, Bis JC, Blake T, Bochud M, Boehnke M, Boerwinkle E, Boomsma DI, Bottinger EP, Braund PS, Brumat M, Campbell A, Campbell H, Chakravarti A, Chambers JC, Chauhan G, Ciullo M, Cocca M, Collins F, Cordell HJ, Davies G, de Borst MH, de Geus EJ, Deary IJ, Deelen J, Del Greco M F, Demirkale CY, Dörr M, Ehret GB, Elosua R, Enroth S, Erzurumluoglu AM, Ferreira T, Frånberg M, Franco OH, Gandin I, Gasparini P, Giedraitis V, Gieger C, Girotto G, Goel A, Gow AJ, Gudnason V, Guo X, Gyllensten U, Hamsten A, Harris TB, Harris SE, Hartman CA, Havulinna AS, Hicks AA, Hofer E, Hofman A, Hottenga JJ, Huffman JE, Hwang SJ, Ingelsson E, James A, Jansen R, Jarvelin MR, Joehanes R, Johansson Å, Johnson AD, Joshi PK, Jousilahti P, Jukema JW, Jula A, Kähönen M, Kathiresan S, Keavney BD, Khaw KT, Knekt P, Knight J, Kolcic I, Kooner JS, Koskinen S, Kristiansson K, Kutalik Z, Laan M, Larson M, Launer LJ, Lehne B, Lehtimäki T, Liewald DCM, Lin L, Lind L, Lindgren CM, Liu Y, Loos RJF, Lopez LM, Lu Y, Lyytikäinen LP, Mahajan A, Mamasoula C, Marrugat J, Marten J, Milaneschi Y, Morgan A, Morris AP, Morrison AC, Munson PJ, Nalls MA, Nandakumar P, Nelson CP, Niiranen T, Nolte IM, Nutile T, Oldehinkel AJ, Oostra BA, O'Reilly PF, Org E, Padmanabhan S, Palmas W, Palotie A, Pattie A, Penninx BWJH, Perola M, Peters A, Polasek O, Pramstaller PP, Nguyen QT, Raitakari OT, Ren M, Rettig R, Rice K, Ridker PM, Ried JS, Riese H, Ripatti S, Robino A, Rose LM, Rotter JI, Rudan I, Ruggiero D, Saba Y, Sala CF, Salomaa V, Samani NJ, Sarin AP, Schmidt R, Schmidt H, Shrine N, Siscovick D, Smith AV, Snieder H, Sõber S, Sorice R, Starr JM, Stott DJ, Strachan DP, Strawbridge RJ, Sundström J, Swertz MA, Taylor KD, Teumer A, Tobin MD, Tomaszewski M, Toniolo D, Traglia M, Trompet S, Tuomilehto J, Tzourio C, Uitterlinden AG, Vaez A, van der Most PJ, van Duijn CM, Vergnaud AC, Verwoert GC, Vitart V, Völker U, Vollenweider P, Vuckovic D, Watkins H, Wild SH, Willemsen G, Wilson JF, Wright AF, Yao J, Zemunik T, Zhang W, Attia JR, Butterworth AS, Chasman DI, Conen D, Cucca F, Danesh J, Hayward C, Howson JMM, Laakso M, Lakatta EG, Langenberg C, Melander O, Mook-Kanamori DO, Palmer CNA, Risch L, Scott RA, Scott RJ, Sever P, Spector TD, van der Harst P, Wareham NJ, Zeggini E, Levy D, Munroe PB, Newton-Cheh C, Brown MJ, Metspalu A, Hung AM, O'Donnell CJ, Edwards TL, Psaty BM, Tzoulaki I, Barnes MR, Wain LV, Elliott P, Caulfield MJ, Million Veteran Program
(2018) Nat Genet 50: 1412-1425
MeSH Terms: Adult, Aged, Aged, 80 and over, Blood Pressure, Cardiovascular Diseases, Cells, Cultured, Female, Genetic Loci, Genetic Predisposition to Disease, Genetic Testing, Genetics, Population, Genome-Wide Association Study, Human Umbilical Vein Endothelial Cells, Humans, Hypertension, Life Style, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors
Show Abstract · Added March 3, 2020
High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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Genetic Variants Associated with Circulating Fibroblast Growth Factor 23.
Robinson-Cohen C, Bartz TM, Lai D, Ikizler TA, Peacock M, Imel EA, Michos ED, Foroud TM, Akesson K, Taylor KD, Malmgren L, Matsushita K, Nethander M, Eriksson J, Ohlsson C, Mellström D, Wolf M, Ljunggren O, McGuigan F, Rotter JI, Karlsson M, Econs MJ, Ix JH, Lutsey PL, Psaty BM, de Boer IH, Kestenbaum BR
(2018) J Am Soc Nephrol 29: 2583-2592
MeSH Terms: African Continental Ancestry Group, Cohort Studies, European Continental Ancestry Group, Female, Fibroblast Growth Factors, Genome-Wide Association Study, Humans, Kidney, Male, Phosphates, Polymorphism, Single Nucleotide, RGS Proteins, Sodium-Phosphate Cotransporter Proteins, Type IIa, Vitamin D, Vitamin D3 24-Hydroxylase
Show Abstract · Added January 3, 2019
BACKGROUND - Fibroblast growth factor 23 (FGF23), a bone-derived hormone that regulates phosphorus and vitamin D metabolism, contributes to the pathogenesis of mineral and bone disorders in CKD and is an emerging cardiovascular risk factor. Central elements of FGF23 regulation remain incompletely understood; genetic variation may help explain interindividual differences.
METHODS - We performed a meta-analysis of genome-wide association studies of circulating FGF23 concentrations among 16,624 participants of European ancestry from seven cohort studies, excluding participants with eGFR<30 ml/min per 1.73 m to focus on FGF23 under normal conditions. We evaluated the association of single-nucleotide polymorphisms (SNPs) with natural log-transformed FGF23 concentration, adjusted for age, sex, study site, and principal components of ancestry. A second model additionally adjusted for BMI and eGFR.
RESULTS - We discovered 154 SNPs from five independent regions associated with FGF23 concentration. The SNP with the strongest association, rs17216707 (=3.0×10), lies upstream of , which encodes the primary catabolic enzyme for 1,25-dihydroxyvitamin D and 25-hydroxyvitamin D. Each additional copy of the T allele at this locus is associated with 5% higher FGF23 concentration. Another locus strongly associated with variations in FGF23 concentration is rs11741640, within and upstream of (a gene involved in renal phosphate transport). Additional adjustment for BMI and eGFR did not materially alter the magnitude of these associations. Another top locus (within , the ABO blood group transferase gene) was no longer statistically significant at the genome-wide level.
CONCLUSIONS - Common genetic variants located near genes involved in vitamin D metabolism and renal phosphate transport are associated with differences in circulating FGF23 concentrations.
Copyright © 2018 by the American Society of Nephrology.
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15 MeSH Terms
Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients.
Kahles A, Lehmann KV, Toussaint NC, Hüser M, Stark SG, Sachsenberg T, Stegle O, Kohlbacher O, Sander C, Cancer Genome Atlas Research Network, Rätsch G
(2018) Cancer Cell 34: 211-224.e6
MeSH Terms: Alternative Splicing, Humans, Neoplasms, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sequence Analysis, RNA, Whole Exome Sequencing
Show Abstract · Added October 30, 2019
Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects alternative splicing events and tumor variants by reanalyzing RNA and whole-exome sequencing data. Tumors have up to 30% more alternative splicing events than normal samples. Association analysis of somatic variants with alternative splicing events confirmed known trans associations with variants in SF3B1 and U2AF1 and identified additional trans-acting variants (e.g., TADA1, PPP2R1A). Many tumors have thousands of alternative splicing events not detectable in normal samples; on average, we identified ≈930 exon-exon junctions ("neojunctions") in tumors not typically found in GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast and ovarian tumor samples, we confirmed ≈1.7 neojunction- and ≈0.6 single nucleotide variant-derived peptides per tumor sample that are also predicted major histocompatibility complex-I binders ("putative neoantigens").
Copyright © 2018 Elsevier Inc. All rights reserved.
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A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, Im HK, Chen YA, Permuth JB, Reid BM, Teer JK, Moysich KB, Andrulis IL, Anton-Culver H, Arun BK, Bandera EV, Barkardottir RB, Barnes DR, Benitez J, Bjorge L, Brenton J, Butzow R, Caldes T, Caligo MA, Campbell I, Chang-Claude J, Claes KBM, Couch FJ, Cramer DW, Daly MB, deFazio A, Dennis J, Diez O, Domchek SM, Dörk T, Easton DF, Eccles DM, Fasching PA, Fortner RT, Fountzilas G, Friedman E, Ganz PA, Garber J, Giles GG, Godwin AK, Goldgar DE, Goodman MT, Greene MH, Gronwald J, Hamann U, Heitz F, Hildebrandt MAT, Høgdall CK, Hollestelle A, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James P, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Kwong A, Le ND, Leslie G, Lesueur F, Levine DA, Mattiello A, May T, McGuffog L, McNeish IA, Merritt MA, Modugno F, Montagna M, Neuhausen SL, Nevanlinna H, Nielsen FC, Nikitina-Zake L, Nussbaum RL, Offit K, Olah E, Olopade OI, Olson SH, Olsson H, Osorio A, Park SK, Parsons MT, Peeters PHM, Pejovic T, Peterlongo P, Phelan CM, Pujana MA, Ramus SJ, Rennert G, Risch H, Rodriguez GC, Rodríguez-Antona C, Romieu I, Rookus MA, Rossing MA, Rzepecka IK, Sandler DP, Schmutzler RK, Setiawan VW, Sharma P, Sieh W, Simard J, Singer CF, Song H, Southey MC, Spurdle AB, Sutphen R, Swerdlow AJ, Teixeira MR, Teo SH, Thomassen M, Tischkowitz M, Toland AE, Trichopoulou A, Tung N, Tworoger SS, van Rensburg EJ, Vanderstichele A, Vega A, Edwards DV, Webb PM, Weitzel JN, Wentzensen N, White E, Wolk A, Wu AH, Yannoukakos D, Zorn KK, Gayther SA, Antoniou AC, Berchuck A, Goode EL, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J
(2018) Cancer Res 78: 5419-5430
MeSH Terms: Carcinogenesis, Carcinoma, Ovarian Epithelial, Cohort Studies, Female, Gene Expression Profiling, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Prognosis, Quantitative Trait Loci, Risk Factors, Transcriptome
Show Abstract · Added December 6, 2018
Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their -predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of < 2.2 × 10, we identified 35 genes, including at 11q14.2 (Z = 5.08, = 3.83 × 10, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained ( < 1.47 × 10). These data identify one novel locus ) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. .
©2018 American Association for Cancer Research.
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