1,124 results on '"Van Duijn"'
Search Results
2. DNA Methylation Signatures of Educational Attainment
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Jenny van Dongen, Marc Jan Bonder, Koen F. Dekkers, Michel G. Nivard, Maarten van Iterson, Gonneke Willemsen, Marian Beekman, Ashley van der Spek, Joyce B. J. van Meurs, Lude Franke, Bastiaan T. Heijmans, Cornelia M. van Duijn, P. Eline Slagboom, Dorret I. Boomsma, and BIOS Consortium
- Abstract
Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs (N = 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.
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- 2018
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3. A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies
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Srinivasan, Shylaja, Wu, Peitao, Mercader, Josep M, Udler, Miriam S, Porneala, Bianca C, Bartz, Traci M, Floyd, James S, Sitlani, Colleen, Guo, Xiquing, Haessler, Jeffrey, Kooperberg, Charles, Liu, Jun, Ahmad, Shahzad, van Duijn, Cornelia, Liu, Ching-Ti, Goodarzi, Mark O, Florez, Jose C, Meigs, James B, Rotter, Jerome I, Rich, Stephen S, Dupuis, Josée, and Leong, Aaron
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Biomedical and Clinical Sciences ,Clinical Sciences ,Genetics ,Diabetes ,2.1 Biological and endogenous factors ,4.1 Discovery and preclinical testing of markers and technologies ,Metabolic and endocrine ,type 1 diabetes ,type 2 diabetes ,genetics ,polygenic score ,Cardiovascular medicine and haematology - Abstract
ContextBoth type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight.ObjectiveWe examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.MethodsWe constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D.ResultsThe T1D PS was not associated with T2D both in CHARGE (P = .15) and in the MGB Biobank (P = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, P = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, P = .03) in CHARGE T2D cases but not with other outcomes.ConclusionIn large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.
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- 2023
4. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.
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Young, William J, Haessler, Jeffrey, Benjamins, Jan-Walter, Repetto, Linda, Yao, Jie, Isaacs, Aaron, Harper, Andrew R, Ramirez, Julia, Garnier, Sophie, van Duijvenboden, Stefan, Baldassari, Antoine R, Concas, Maria Pina, Duong, ThuyVy, Foco, Luisa, Isaksen, Jonas L, Mei, Hao, Noordam, Raymond, Nursyifa, Casia, Richmond, Anne, Santolalla, Meddly L, Sitlani, Colleen M, Soroush, Negin, Thériault, Sébastien, Trompet, Stella, Aeschbacher, Stefanie, Ahmadizar, Fariba, Alonso, Alvaro, Brody, Jennifer A, Campbell, Archie, Correa, Adolfo, Darbar, Dawood, De Luca, Antonio, Deleuze, Jean-François, Ellervik, Christina, Fuchsberger, Christian, Goel, Anuj, Grace, Christopher, Guo, Xiuqing, Hansen, Torben, Heckbert, Susan R, Jackson, Rebecca D, Kors, Jan A, Lima-Costa, Maria Fernanda, Linneberg, Allan, Macfarlane, Peter W, Morrison, Alanna C, Navarro, Pau, Porteous, David J, Pramstaller, Peter P, Reiner, Alexander P, Risch, Lorenz, Schotten, Ulrich, Shen, Xia, Sinagra, Gianfranco, Soliman, Elsayed Z, Stoll, Monika, Tarazona-Santos, Eduardo, Tinker, Andrew, Trajanoska, Katerina, Villard, Eric, Warren, Helen R, Whitsel, Eric A, Wiggins, Kerri L, Arking, Dan E, Avery, Christy L, Conen, David, Girotto, Giorgia, Grarup, Niels, Hayward, Caroline, Jukema, J Wouter, Mook-Kanamori, Dennis O, Olesen, Morten Salling, Padmanabhan, Sandosh, Psaty, Bruce M, Pattaro, Cristian, Ribeiro, Antonio Luiz P, Rotter, Jerome I, Stricker, Bruno H, van der Harst, Pim, van Duijn, Cornelia M, Verweij, Niek, Wilson, James G, Orini, Michele, Charron, Philippe, Watkins, Hugh, Kooperberg, Charles, Lin, Henry J, Wilson, James F, Kanters, Jørgen K, Sotoodehnia, Nona, Mifsud, Borbala, Lambiase, Pier D, Tereshchenko, Larisa G, and Munroe, Patricia B
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Humans ,Cardiovascular Diseases ,Electrocardiography ,Risk Factors ,Arrhythmias ,Cardiac ,Atrioventricular Block ,Genome-Wide Association Study ,Biomarkers ,Human Genome ,Cardiovascular ,Genetics ,Heart Disease - Abstract
The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
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- 2023
5. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI
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Yang, Yunju, Knol, Maria J, Wang, Ruiqi, Mishra, Aniket, Liu, Dan, Luciano, Michelle, Teumer, Alexander, Armstrong, Nicola, Bis, Joshua C, Jhun, Min A, Li, Shuo, Adams, Hieab HH, Aziz, Nasir Ahmad, Bastin, Mark E, Bourgey, Mathieu, Brody, Jennifer A, Frenzel, Stefan, Gottesman, Rebecca F, Hosten, Norbert, Hou, Lifang, Kardia, Sharon LR, Lohner, Valerie, Marquis, Pascale, Maniega, Susana Muñoz, Satizabal, Claudia L, Sorond, Farzaneh A, Valdés Hernández, Maria C, van Duijn, Cornelia M, Vernooij, Meike W, Wittfeld, Katharina, Yang, Qiong, Zhao, Wei, Boerwinkle, Eric, Levy, Daniel, Deary, Ian J, Jiang, Jiyang, Mather, Karen A, Mosley, Thomas H, Psaty, Bruce M, Sachdev, Perminder S, Smith, Jennifer A, Sotoodehnia, Nona, DeCarli, Charles S, Breteler, Monique MB, Ikram, M Arfan, Grabe, Hans J, Wardlaw, Joanna, Longstreth, WT, Launer, Lenore J, Seshadri, Sudha, Debette, Stephanie, and Fornage, Myriam
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Health Sciences ,Neurodegenerative ,Aging ,Acquired Cognitive Impairment ,Alzheimer's Disease Related Dementias (ADRD) ,Human Genome ,Cerebrovascular ,Neurosciences ,Brain Disorders ,Clinical Research ,Genetics ,Vascular Cognitive Impairment/Dementia ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Dementia ,2.1 Biological and endogenous factors ,Middle Aged ,Humans ,Aged ,White Matter ,Genome-Wide Association Study ,Brain ,DNA Methylation ,Magnetic Resonance Imaging ,Epigenesis ,Genetic ,Protein-Arginine N-Methyltransferases ,Repressor Proteins ,epigenome-wide association study ,white matter hyperintensities ,cerebral small vessel disease ,integrative cross-omics analysis ,blood-brain barrier dysfunction ,blood–brain barrier dysfunction ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery ,Biomedical and clinical sciences ,Health sciences ,Psychology - Abstract
Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.
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- 2023
6. Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants
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Young, Kristin L, Fisher, Virginia, Deng, Xuan, Brody, Jennifer A, Graff, Misa, Lim, Elise, Lin, Bridget M, Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E, Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G, Buth, Erin J, Heavner, Benjamin D, Jain, Deepti, Smith, Albert V, Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R, Kalyani, Rita R, Kardia, Sharon LR, Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A, McDonald, Merry-Lynn, Mitchell, Braxton D, Peyser, Patricia A, Regan, Elizabeth A, Redline, Susan, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Weiss, Scott, Wiggins, Kerri L, Yanek, Lisa R, Arnett, Donna, Heard-Costa, Nancy L, Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M, North, Kari E, Cupples, L Adrienne, and Liu, Ching-Ti
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Biological Sciences ,Genetics ,Clinical Research ,Biotechnology ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,Generic health relevance ,Good Health and Well Being ,Humans ,Genome-Wide Association Study ,Exome ,Body Mass Index ,Quantitative Trait Loci ,Anthropometry ,Intercellular Signaling Peptides and Proteins ,Cell Cycle Proteins ,body mass index ,central obesity ,exome sequencing ,height - Abstract
Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.
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- 2023
7. Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation: discovering causal pathways
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Kasher, Melody, Williams, Frances MK, Freidin, Maxim B, Malkin, Ida, Cherny, Stacey S, Benjamin, Emelia, Chasman, Daniel I, Dehghan, Abbas, Ahluwalia, Tarunveer Singh, Meigs, James, Tracy, Russell, Alizadeh, Behrooz Z, Ligthart, Symen, Bis, Josh, Eiriksdottir, Gudny, Pankratz, Nathan, Gross, Myron, Rainer, Alex, Snieder, Harold, Wilson, James G, Psaty, Bruce M, Dupuis, Josee, Prins, Bram, Vaso, Urmo, Stathopoulou, Maria, Franke, Lude, Lehtimaki, Terho, Koenig, Wolfgang, Jamshidi, Yalda, Siest, Sophie, Abbasi, Ali, Uitterlinden, Andre G, Abdollahi, Mohammadreza, Schnabel, Renate, Schick, Ursula M, Nolte, Ilja M, Kraja, Aldi, Hsu, Yi-Hsiang, Tylee, Daniel S, Zwicker, Alyson, Uher, Rudolf, Davey-Smith, George, Morrison, Alanna C, Hicks, Andrew, van Duijn, Cornelia M, Ward-Caviness, Cavin, Boerwinkle, Eric, Rotter, J, Rice, Ken, Lange, Leslie, Perola, Markus, de Geus, Eco, Morris, Andrew P, Makela, Kari Matti, Stacey, David, Eriksson, Johan, Frayling, Tim M, Slagboom, Eline P, and Livshits, Gregory
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Aging ,Autoimmune Disease ,Arthritis ,Osteoporosis ,Human Genome ,Heart Disease ,Cardiovascular ,Rheumatoid Arthritis ,Genetics ,2.1 Biological and endogenous factors ,Aetiology ,Inflammatory and immune system ,Arthritis ,Rheumatoid ,C-Reactive Protein ,Genome-Wide Association Study ,Humans ,Inflammation ,Mendelian Randomization Analysis ,Polymorphism ,Single Nucleotide ,CHARGE Inflammation Working Group ,Biological Sciences ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (β = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP.
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- 2022
8. Gene-mapping study of extremes of cerebral small vessel disease reveals TRIM47 as a strong candidate
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Mishra, Aniket, Duplaà, Cécile, Vojinovic, Dina, Suzuki, Hideaki, Sargurupremraj, Muralidharan, Zilhão, Nuno R, Li, Shuo, Bartz, Traci M, Jian, Xueqiu, Zhao, Wei, Hofer, Edith, Wittfeld, Katharina, Harris, Sarah E, van der Auwera-Palitschka, Sandra, Luciano, Michelle, Bis, Joshua C, Adams, Hieab HH, Satizabal, Claudia L, Gottesman, Rebecca F, Gampawar, Piyush G, Bülow, Robin, Weiss, Stefan, Yu, Miao, Bastin, Mark E, Lopez, Oscar L, Vernooij, Meike W, Beiser, Alexa S, Völker, Uwe, Kacprowski, Tim, Soumare, Aicha, Smith, Jennifer A, Knopman, David S, Morris, Zoe, Zhu, Yicheng, Rotter, Jerome I, Dufouil, Carole, Hernández, Maria Valdés, Maniega, Susana Muñoz, Lathrop, Mark, Boerwinkle, Erik, Schmidt, Reinhold, Ihara, Masafumi, Mazoyer, Bernard, Yang, Qiong, Joutel, Anne, Tournier-Lasserve, Elizabeth, Launer, Lenore J, Deary, Ian J, Mosley, Thomas H, Amouyel, Philippe, DeCarli, Charles S, Psaty, Bruce M, Tzourio, Christophe, Kardia, Sharon LR, Grabe, Hans J, Teumer, Alexander, van Duijn, Cornelia M, Schmidt, Helena, Wardlaw, Joanna M, Ikram, M Arfan, Fornage, Myriam, Gudnason, Vilmundur, Seshadri, Sudha, Matthews, Paul M, Longstreth, William T, Couffinhal, Thierry, and Debette, Stephanie
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Epidemiology ,Health Sciences ,Neurosciences ,Cerebrovascular ,Neurodegenerative ,Brain Disorders ,Human Genome ,Aging ,Alzheimer's Disease Related Dementias (ADRD) ,Stroke ,Vascular Cognitive Impairment/Dementia ,Dementia ,Acquired Cognitive Impairment ,Minority Health ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Clinical Research ,Genetics ,2.1 Biological and endogenous factors ,Cardiovascular ,Neurological ,Animals ,Brain Ischemia ,Cerebral Small Vessel Diseases ,Endothelial Cells ,Genome-Wide Association Study ,Mice ,cerebral small vessel disease ,endothelial cells ,GWAS ,TRIM47 ,whole-exome association study ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery ,Biomedical and clinical sciences ,Health sciences ,Psychology - Abstract
Cerebral small vessel disease is a leading cause of stroke and a major contributor to cognitive decline and dementia, but our understanding of specific genes underlying the cause of sporadic cerebral small vessel disease is limited. We report a genome-wide association study and a whole-exome association study on a composite extreme phenotype of cerebral small vessel disease derived from its most common MRI features: white matter hyperintensities and lacunes. Seventeen population-based cohorts of older persons with MRI measurements and genome-wide genotyping (n = 41 326), whole-exome sequencing (n = 15 965), or exome chip (n = 5249) data contributed 13 776 and 7079 extreme small vessel disease samples for the genome-wide association study and whole-exome association study, respectively. The genome-wide association study identified significant association of common variants in 11 loci with extreme small vessel disease, of which the chr12q24.11 locus was not previously reported to be associated with any MRI marker of cerebral small vessel disease. The whole-exome association study identified significant associations of extreme small vessel disease with common variants in the 5' UTR region of EFEMP1 (chr2p16.1) and one probably damaging common missense variant in TRIM47 (chr17q25.1). Mendelian randomization supports the causal association of extensive small vessel disease severity with increased risk of stroke and Alzheimer's disease. Combined evidence from summary-based Mendelian randomization studies and profiling of human loss-of-function allele carriers showed an inverse relation between TRIM47 expression in the brain and blood vessels and extensive small vessel disease severity. We observed significant enrichment of Trim47 in isolated brain vessel preparations compared to total brain fraction in mice, in line with the literature showing Trim47 enrichment in brain endothelial cells at single cell level. Functional evaluation of TRIM47 by small interfering RNAs-mediated knockdown in human brain endothelial cells showed increased endothelial permeability, an important hallmark of cerebral small vessel disease pathology. Overall, our comprehensive gene-mapping study and preliminary functional evaluation suggests a putative role of TRIM47 in the pathophysiology of cerebral small vessel disease, making it an important candidate for extensive in vivo explorations and future translational work.
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- 2022
9. Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation
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Longchamps, RJ, Yang, SY, Castellani, CA, Shi, W, Lane, J, Grove, ML, Bartz, TM, Sarnowski, C, Liu, C, Burrows, K, Guyatt, AL, Gaunt, TR, Kacprowski, T, Yang, J, De Jager, PL, Yu, L, Bergman, A, Xia, R, Fornage, M, Feitosa, MF, Wojczynski, MK, Kraja, AT, Province, MA, Amin, N, Rivadeneira, F, Tiemeier, H, Uitterlinden, AG, Broer, L, Van Meurs, JBJ, Van Duijn, CM, Raffield, LM, Lange, L, Rich, SS, Lemaitre, RN, Goodarzi, MO, Sitlani, CM, Mak, ACY, Bennett, DA, Rodriguez, S, Murabito, JM, Lunetta, KL, Sotoodehnia, N, Atzmon, G, Ye, K, Barzilai, N, Brody, JA, Psaty, BM, Taylor, KD, Rotter, JI, Boerwinkle, E, Pankratz, N, and Arking, DE
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Biological Sciences ,Genetics ,Aging ,Hematology ,Biotechnology ,Human Genome ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Cardiovascular ,Generic health relevance ,Aged ,Cell Proliferation ,DNA Copy Number Variations ,DNA ,Mitochondrial ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Male ,Megakaryocytes ,Middle Aged ,Mitochondria ,Nucleotides ,Phenotype ,Platelet Activation ,Polymorphism ,Single Nucleotide ,Complementary and Alternative Medicine ,Paediatrics and Reproductive Medicine ,Genetics & Heredity ,Reproductive medicine - Abstract
Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10-8) and mtDNA replication (p = 1.2 × 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10-4).
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- 2022
10. Plasma amyloid β levels are driven by genetic variants near APOE, BACE1, APP, PSEN2: A genome‐wide association study in over 12,000 non‐demented participants
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Damotte, Vincent, van der Lee, Sven J, Chouraki, Vincent, Grenier‐Boley, Benjamin, Simino, Jeannette, Adams, Hieab, Tosto, Giuseppe, White, Charles, Terzikhan, Natalie, Cruchaga, Carlos, Knol, Maria J, Li, Shuo, Schraen, Susanna, Grove, Megan L, Satizabal, Claudia, Amin, Najaf, Berr, Claudine, Younkin, Steven, Initiative, Alzheimer's Disease Neuroimaging, Gottesman, Rebecca F, Buée, Luc, Beiser, Alexa, Knopman, David S, Uitterlinden, Andre, DeCarli, Charles, Bressler, Jan, DeStefano, Anita, Dartigues, Jean‐François, Yang, Qiong, Boerwinkle, Eric, Tzourio, Christophe, Fornage, Myriam, Ikram, M Arfan, Amouyel, Philippe, de Jager, Phil, Reitz, Christiane, Mosley, Thomas H, Lambert, Jean‐Charles, Seshadri, Sudha, and van Duijn, Cornelia M
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Dementia ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Human Genome ,Neurodegenerative ,Genetics ,Prevention ,Clinical Research ,Brain Disorders ,Acquired Cognitive Impairment ,Alzheimer's Disease ,Aging ,2.1 Biological and endogenous factors ,Neurological ,Alzheimer Disease ,Amyloid ,Amyloid Precursor Protein Secretases ,Amyloid beta-Protein Precursor ,Apolipoproteins E ,Aspartic Acid Endopeptidases ,Brain ,Genome-Wide Association Study ,Healthy Volunteers ,Humans ,Positron-Emission Tomography ,Presenilin-2 ,Alzheimer&apos ,s disease ,APOE ,APP ,BACE1 ,endophenotype ,genetic epidemiology ,genome‑ ,wide association study ,plasma amyloid beta levels ,plasma biomarkers ,preclinical biomarkers ,PSEN2 ,Alzheimer's Disease Neuroimaging Initiative ,Alzheimer's disease ,genome-wide association study ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionThere is increasing interest in plasma amyloid beta (Aβ) as an endophenotype of Alzheimer's disease (AD). Identifying the genetic determinants of plasma Aβ levels may elucidate important biological processes that determine plasma Aβ measures.MethodsWe included 12,369 non-demented participants from eight population-based studies. Imputed genetic data and measured plasma Aβ1-40, Aβ1-42 levels and Aβ1-42/Aβ1-40 ratio were used to perform genome-wide association studies, and gene-based and pathway analyses. Significant variants and genes were followed up for their association with brain positron emission tomography Aβ deposition and AD risk.ResultsSingle-variant analysis identified associations with apolipoprotein E (APOE) for Aβ1-42 and Aβ1-42/Aβ1-40 ratio, and BACE1 for Aβ1-40. Gene-based analysis of Aβ1-40 additionally identified associations for APP, PSEN2, CCK, and ZNF397. There was suggestive evidence for interaction between a BACE1 variant and APOE ε4 on brain Aβ deposition.DiscussionIdentification of variants near/in known major Aβ-processing genes strengthens the relevance of plasma-Aβ levels as an endophenotype of AD.
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- 2021
11. Assessment of the 9p21.3 locus in severity of coronary artery disease in the presence and absence of type 2 diabetes
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Rivera Natalia V, Carreras-Torres Robert, Roncarati Roberta, Viviani-Anselmi Chiara, De Micco Francesca, Mezzelani Alessandra, Koch Werner, Hoppmann Petra, Kastrati Adnan, Stewart Alexandre FR, Chen Li, Roberts Robert, Karssen Lennart C, Amin Najaf, Trimarco Valentina, Izzo Raffaele, Iaccarino Guido, Condorelli Gerolama, Puca Annibale A, Pagnotta Paolo, Airoldi Flavio, Trimarco Bruno, van Duijn Cornelia M, Condorelli Gianluigi, and Briguori Carlo
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Severity of CAD ,Coronary artery disease ,Diabetes mellitus ,T2D ,9p21.3 ,Genetics ,Single nucleotide polymorphism ,Internal medicine ,RC31-1245 ,QH426-470 - Abstract
Abstract Background The 9p21.3 locus is strongly associated with the risk of coronary artery disease (CAD) and with type 2 diabetes (T2D). We investigated the association of 9p21.3 variants with severity of CAD (defined by the number of vessel diseased [VD]) in the presence and absence of T2D. Methods We tested 11 9p21.3-variants for association in a white Italian study (N = 2,908), and carried out replication in 2 independent white populations, a German study (N = 2,028) and a Canadian Study (N=950). SNP association and permutation analyses were conducted. Results We identified two 9p21.3-variants, rs4977574 (P < 4×10-4) and rs2383207 (P < 1.5×10-3) that were associated with severity of CAD in subjects without T2D. Association of rs4977574 with severity of CAD was confirmed in the Canadian Study. Results from subgroup analysis among patients with T2D showed an interaction between rs10738610 and T2D with P = 4.82×10-2. Further investigation showed that rs10738610 (P < 1.99×10-2) was found to be significantly associated with severity of CAD in subjects with T2D. Conclusions The 9p21.3 locus is significantly associated with severity of CAD. The number of associations of 9p21.3 variants with severity of CAD is variable to the presence and absence of T2D. In a CAD-susceptible region of 115 kb, there is only one variant associated with the severity of coronary vessel disease in the presence of type 2 diabetes.
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- 2013
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12. An R package 'VariABEL' for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
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Struchalin Maksim V, Amin Najaf, Eilers Paul HC, van Duijn Cornelia M, and Aulchenko Yurii S
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single-nucleotide polymorphisms (SNPs) ,genome-wide association (GWA) ,gene-environment interactions (GxE) ,gene-gene interactions (GxG) ,variance heterogeneity ,environmental sensitivity ,VariABEL ,the GenABEL project ,Genetics ,QH426-470 - Abstract
Abstract Background Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010) developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. Results In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. Conclusions Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.
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- 2012
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13. A polymorphism in the regulatory region of PRNP is associated with increased risk of sporadic Creutzfeldt-Jakob disease
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Will Robert G, Knight Richard SG, Croes Esther A, Bishop Matthew T, Sanchez-Juan Pascual, van Duijn Cornelia M, and Manson Jean C
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Creutzfeldt-Jakob disease ,prion protein gene ,molecular subtype ,regulatory region ,early onset ,Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background Creutzfeldt-Jakob disease (CJD) is a rare transmissible neurodegenerative disorder. An important determinant for CJD risk and phenotype is the M129V polymorphism of the human prion protein gene (PRNP), but there are also other coding and non-coding polymorphisms inside this gene. Methods We tested whether three non-coding polymorphism located inside the PRNP regulatory region (C-101G, G310C and T385C) were associated with risk of CJD and with age at onset in a United Kingdom population-based sample of 131 sporadic CJD (sCJD) patients and 194 controls. Results We found no disease association for either PRNP C-101G or PRNP T385C. Although the crude analysis did not show a significant association between PRNP G310C and sCJD (OR: 1.5; 95%CI = 0.7 to 2.9), after adjusting by PRNP M129V genotype, it resulted that being a C allele carrier at PRNP G310C was significantly (p = 0.03) associated with a 2.4 fold increased risk of developing sCJD (95%CI = 1.1 to 5.4). Additionally, haplotypes carrying PRNP 310C coupled with PRNP 129M were significantly overrepresented in patients (p = 0.02) compared to controls. Cases of sCJD carrying a PRNP 310C allele presented at a younger age (on average 8.9 years younger than those without this allele), which was of statistical significance (p = 0.05). As expected, methionine and valine homozygosity at PRNP M129V increased significantly the risk of sCJD, alone and adjusted by PRNP G310C (OR MM/MV = 7.3; 95%CI 3.9 to 13.5 and OR VV/MV = 4.0; 95%CI 1.7 to 9.3). Conclusions Our findings support the hypothesis that genetic variations in the PRNP promoter may have a role in the pathogenesis of sCJD.
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- 2011
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14. The dopamine β-hydroxylase -1021C/T polymorphism is associated with the risk of Alzheimer's disease in the Epistasis Project
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Arias-Vásquez Alejandro, Oulhaj Abderrahim, Mateo Ignacio, Kölsch Heike, Heun Reinhard, Gwilliam Rhian, Deloukas Panos, Alvarez Victoria, Coto Eliecer, Barber Rachel, Kehoe Patrick G, Brown Kristelle, Wilcock Gordon K, Lehmann Michael G, Belbin Olivia, Cortina-Borja Mario, Hammond Naomi, Warden Donald R, Combarros Onofre, Schuur Maaike, Aulchenko Yurii S, Ikram M Arfan, Breteler Monique M, van Duijn Cornelia M, Morgan Kevin, Smith A David, and Lehmann Donald J
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Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background The loss of noradrenergic neurones of the locus coeruleus is a major feature of Alzheimer's disease (AD). Dopamine β-hydroxylase (DBH) catalyses the conversion of dopamine to noradrenaline. Interactions have been reported between the low-activity -1021T allele (rs1611115) of DBH and polymorphisms of the pro-inflammatory cytokine genes, IL1A and IL6, contributing to the risk of AD. We therefore examined the associations with AD of the DBH -1021T allele and of the above interactions in the Epistasis Project, with 1757 cases of AD and 6294 elderly controls. Methods We genotyped eight single nucleotide polymorphisms (SNPs) in the three genes, DBH, IL1A and IL6. We used logistic regression models and synergy factor analysis to examine potential interactions and associations with AD. Results We found that the presence of the -1021T allele was associated with AD: odds ratio = 1.2 (95% confidence interval: 1.06-1.4, p = 0.005). This association was nearly restricted to men < 75 years old: odds ratio = 2.2 (1.4-3.3, 0.0004). We also found an interaction between the presence of DBH -1021T and the -889TT genotype (rs1800587) of IL1A: synergy factor = 1.9 (1.2-3.1, 0.005). All these results were consistent between North Europe and North Spain. Conclusions Extensive, previous evidence (reviewed here) indicates an important role for noradrenaline in the control of inflammation in the brain. Thus, the -1021T allele with presumed low activity may be associated with misregulation of inflammation, which could contribute to the onset of AD. We suggest that such misregulation is the predominant mechanism of the association we report here.
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- 2010
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15. Variance heterogeneity analysis for detection of potentially interacting genetic loci: method and its limitations
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van Duijn Cornelia, Witteman Jacqueline CM, Dehghan Abbas, Struchalin Maksim V, and Aulchenko Yurii S
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Genetics ,QH426-470 - Abstract
Abstract Background Presence of interaction between a genotype and certain factor in determination of a trait's value, it is expected that the trait's variance is increased in the group of subjects having this genotype. Thus, test of heterogeneity of variances can be used as a test to screen for potentially interacting single-nucleotide polymorphisms (SNPs). In this work, we evaluated statistical properties of variance heterogeneity analysis in respect to the detection of potentially interacting SNPs in a case when an interaction variable is unknown. Results Through simulations, we investigated type I error for Bartlett's test, Bartlett's test with prior rank transformation of a trait to normality, and Levene's test for different genetic models. Additionally, we derived an analytical expression for power estimation. We showed that Bartlett's test has acceptable type I error in the case of trait following a normal distribution, whereas Levene's test kept nominal Type I error under all scenarios investigated. For the power of variance homogeneity test, we showed (as opposed to the power of direct test which uses information about known interacting factor) that, given the same interaction effect, the power can vary widely depending on the non-estimable direct effect of the unobserved interacting variable. Thus, for a given interaction effect, only very wide limits of power of the variance homogeneity test can be estimated. Also we applied Levene's approach to test genome-wide homogeneity of variances of the C-reactive protein in the Rotterdam Study population (n = 5959). In this analysis, we replicate previous results of Pare and colleagues (2010) for the SNP rs12753193 (n = 21, 799). Conclusions Screening for differences in variances among genotypes of a SNP is a promising approach as a number of biologically interesting models may lead to the heterogeneity of variances. However, it should be kept in mind that the absence of variance heterogeneity for a SNP can not be interpreted as the absence of involvement of the SNP in the interaction network.
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- 2010
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16. A meta-analysis of genome-wide data from five European isolates reveals an association of COL22A1, SYT1, and GABRR2 with serum creatinine level
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Oostra Ben A, Meitinger Thomas, Boban Mladen, Hastie Nick, Campbell Susan, Schreiber Stefan, Gnewuch Carsten, Zemunik Tatijana, Zgaga Lina, Nöthlings Ute, Kolcic Ivana, Ellinghaus David, Polasek Ozren, Isaacs Aaron, Melville Scott A, Wild Sarah H, Johansson Asa, Aulchenko Yurii S, Franke Andre, Hayward Caroline, Vitart Veronique, De Grandi Alessandro, Pattaro Cristian, Riegler Peter, Minelli Cosetta, Wright Alan F, Campbell Harry, van Duijn Cornelia M, Gyllensten Ulf, Wilson James F, Krawczak Michael, Rudan Igor, and Pramstaller Peter P
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Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background Serum creatinine (SCR) is the most important biomarker for a quick and non-invasive assessment of kidney function in population-based surveys. A substantial proportion of the inter-individual variability in SCR level is explicable by genetic factors. Methods We performed a meta-analysis of genome-wide association studies of SCR undertaken in five population isolates ('discovery cohorts'), all of which are part of the European Special Population Network (EUROSPAN) project. Genes showing the strongest evidence for an association with SCR (candidate loci) were replicated in two additional population-based samples ('replication cohorts'). Results After the discovery meta-analysis, 29 loci were selected for replication. Association between SCR level and polymorphisms in the collagen type XXII alpha 1 (COL22A1) gene, on chromosome 8, and in the synaptotagmin-1 (SYT1) gene, on chromosome 12, were successfully replicated in the replication cohorts (p value = 1.0 × 10-6 and 1.7 × 10-4, respectively). Evidence of association was also found for polymorphisms in a locus including the gamma-aminobutyric acid receptor rho-2 (GABRR2) gene and the ubiquitin-conjugating enzyme E2-J1 (UBE2J1) gene (replication p value = 3.6 × 10-3). Previously reported findings, associating glomerular filtration rate with SNPs in the uromodulin (UMOD) gene and in the schroom family member 3 (SCHROOM3) gene were also replicated. Conclusions While confirming earlier results, our study provides new insights in the understanding of the genetic basis of serum creatinine regulatory processes. In particular, the association with the genes SYT1 and GABRR2 corroborate previous findings that highlighted a possible role of the neurotransmitters GABAA receptors in the regulation of the glomerular basement membrane and a possible interaction between GABAAreceptors and synaptotagmin-I at the podocyte level.
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- 2010
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17. Developing a set of ancestry-sensitive DNA markers reflecting continental origins of humans
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den Dunnen Johan T, Kloosterman Ate D, van Duijn Kate, Kersbergen Paula, Kayser Manfred, and de Knijff Peter
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Genetics ,QH426-470 - Abstract
Abstract Background The identification and use of Ancestry-Sensitive Markers (ASMs), i.e. genetic polymorphisms facilitating the genetic reconstruction of geographical origins of individuals, is far from straightforward. Results Here we describe the ascertainment and application of five different sets of 47 single nucleotide polymorphisms (SNPs) allowing the inference of major human groups of different continental origin. For this, we first used 74 cell lines, representing human males from six different geographical areas and screened them with the Affymetrix Mapping 10K assay. In addition to using summary statistics estimating the genetic diversity among multiple groups of individuals defined by geography or language, we also used the program STRUCTURE to detect genetically distinct subgroups. Subsequently, we used a pairwise FST ranking procedure among all pairs of genetic subgroups in order to identify a single best performing set of ASMs. Our initial results were independently confirmed by genotyping this set of ASMs in 22 individuals from Somalia, Afghanistan and Sudan and in 919 samples from the CEPH Human Genome Diversity Panel (HGDP-CEPH) Conclusion By means of our pairwise population FST ranking approach we identified a set of 47 SNPs that could serve as a panel of ASMs at a continental level.
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- 2009
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18. Type 2 diabetes gene TCF7L2 polymorphism is not associated with fetal and postnatal growth in two birth cohort studies
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Hofman Albert, Uitterlinden Andre G, van Duijn Cornelia M, de Kort Sandra WK, Mook-Kanamori Dennis O, Moll Henriëtte A, Steegers Eric AP, Hokken-Koelega Anita CS, and Jaddoe Vincent WV
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Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background An inverse association between birth weight and the risk of developing type 2 diabetes (T2D) in adulthood has been reported. This association may be explained by common genetic variants related to insulin secretion and resistance, since insulin is the most important growth factor in fetal life. The objective of this study was to examine whether T2D gene polymorphism TCF7L2 rs7903146 is associated with growth patterns from fetal life until infancy. Methods This study was performed in two independent birth cohort studies, one prospective population-based (Generation R), and one of subjects born small-for-gestational-age (SGA cohort). Fetal growth was assessed by ultrasounds in second and third trimesters of pregnancy in Generation R. Growth in infancy was assessed in both cohorts at birth and at 6, 12 and 24 months postnatally. TCF7L2 genotype was determined in 3,419 subjects in Generation R and in 566 subjects in the SGA cohort. Results Minor allele frequency did not differ significantly (p = 0.47) between Generation R (T-allele: 28.7%) and the SGA cohort (T-allele: 29.8%). No differences at birth were found in gestational age or size (head circumference, length, weight) between the genotypes in either cohort. TCF7L2 genotype was also not associated with any pre- or postnatal growth characteristic in either Generation R or the SGA cohort. Conclusion We found no evidence for an association between TCF7L2 genotype and fetal and early postnatal growth. Furthermore, this TCF7L2 polymorphism was not associated with an increased risk of SGA.
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- 2009
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19. Large-scale association analyses identify host factors influencing human gut microbiome composition
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Kurilshikov, Alexander, Medina-Gomez, Carolina, Bacigalupe, Rodrigo, Radjabzadeh, Djawad, Wang, Jun, Demirkan, Ayse, Le Roy, Caroline I, Raygoza Garay, Juan Antonio, Finnicum, Casey T, Liu, Xingrong, Zhernakova, Daria V, Bonder, Marc Jan, Hansen, Tue H, Frost, Fabian, Rühlemann, Malte C, Turpin, Williams, Moon, Jee-Young, Kim, Han-Na, Lüll, Kreete, Barkan, Elad, Shah, Shiraz A, Fornage, Myriam, Szopinska-Tokov, Joanna, Wallen, Zachary D, Borisevich, Dmitrii, Agreus, Lars, Andreasson, Anna, Bang, Corinna, Bedrani, Larbi, Bell, Jordana T, Bisgaard, Hans, Boehnke, Michael, Boomsma, Dorret I, Burk, Robert D, Claringbould, Annique, Croitoru, Kenneth, Davies, Gareth E, van Duijn, Cornelia M, Duijts, Liesbeth, Falony, Gwen, Fu, Jingyuan, van der Graaf, Adriaan, Hansen, Torben, Homuth, Georg, Hughes, David A, Ijzerman, Richard G, Jackson, Matthew A, Jaddoe, Vincent WV, Joossens, Marie, Jørgensen, Torben, Keszthelyi, Daniel, Knight, Rob, Laakso, Markku, Laudes, Matthias, Launer, Lenore J, Lieb, Wolfgang, Lusis, Aldons J, Masclee, Ad AM, Moll, Henriette A, Mujagic, Zlatan, Qibin, Qi, Rothschild, Daphna, Shin, Hocheol, Sørensen, Søren J, Steves, Claire J, Thorsen, Jonathan, Timpson, Nicholas J, Tito, Raul Y, Vieira-Silva, Sara, Völker, Uwe, Völzke, Henry, Võsa, Urmo, Wade, Kaitlin H, Walter, Susanna, Watanabe, Kyoko, Weiss, Stefan, Weiss, Frank U, Weissbrod, Omer, Westra, Harm-Jan, Willemsen, Gonneke, Payami, Haydeh, Jonkers, Daisy MAE, Arias Vasquez, Alejandro, de Geus, Eco JC, Meyer, Katie A, Stokholm, Jakob, Segal, Eran, Org, Elin, Wijmenga, Cisca, Kim, Hyung-Lae, Kaplan, Robert C, Spector, Tim D, Uitterlinden, Andre G, Rivadeneira, Fernando, Franke, Andre, Lerch, Markus M, Franke, Lude, Sanna, Serena, D’Amato, Mauro, and Pedersen, Oluf
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Microbiology ,Biological Sciences ,Genetics ,Human Genome ,Biotechnology ,Clinical Research ,Digestive Diseases ,Nutrition ,2.1 Biological and endogenous factors ,Aetiology ,Oral and gastrointestinal ,Adolescent ,Adult ,Bifidobacterium ,Child ,Child ,Preschool ,Cohort Studies ,Female ,Gastrointestinal Microbiome ,Genetic Variation ,Genome-Wide Association Study ,Humans ,Lactase ,Linkage Disequilibrium ,Male ,Mendelian Randomization Analysis ,Metabolism ,Quantitative Trait Loci ,RNA ,Ribosomal ,16S ,Medical and Health Sciences ,Developmental Biology ,Agricultural biotechnology ,Bioinformatics and computational biology - Abstract
To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P
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- 2021
20. No evidence for association between tau gene haplotypic variants and susceptibility to Creutzfeldt-Jakob disease
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Arias-Vasquez Alejandro, Giannattasio Claudia, Green Alison, Bishop Matthew T, Sánchez-Juan Pascual, Poleggi Anna, Knight Richard SG, and van Duijn Cornelia M
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Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background A polymorphism at codon 129 of the prion protein gene (PRNP) is the only well-known genetic risk factor for Creutzfeldt-Jakob disease (CJD). However, there is increasing evidence that other loci outside the PRNP open reading frame might play a role in CJD aetiology as well. Methods We studied tau protein gene (MAPT) haplotypic variations in a population of sporadic and variant CJD patients. We tested 6 MAPT haplotype tagging SNPs (htSNPs) in a Dutch population-based sample of sporadic CJD (sCJD) patients and a cognitively normal control group of similar age distribution. We genotyped the same polymorphisms in two other sample groups of sCJD cases from Italy and the UK. In addition, we compared MAPT haplotypes between sCJD and variant CJD (vCJD) patients. Results Single locus and haplotype analyses did not detect any significant difference between sCJD cases and controls. When we compared MAPT haplotypes between sCJD and variant CJD (vCJD) patients, we found that two of them were represented differently (H1f: 8% in sCJD versus 2% in vCJD; H1j:1% in sCJD versus 7% in vCJD). However, these two haplotypes were rare in both groups of patients, and taking the small sample sizes into account, we cannot exclude that the differences are due to chance. None of the p-values remained statistically significant after applying a multiple testing correction. Conclusion Our study shows no evidence for an association between MAPT gene variations and sCJD, and some weak evidence for an association to vCJD.
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- 2007
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21. Multi-ancestry genome-wide association study accounting for gene-psychosocial factor interactions identifies novel loci for blood pressure traits
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Sun, Daokun, Richard, Melissa A, Musani, Solomon K, Sung, Yun Ju, Winkler, Thomas W, Schwander, Karen, Chai, Jin Fang, Guo, Xiuqing, Kilpeläinen, Tuomas O, Vojinovic, Dina, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Brown, Michael R, Chitrala, Kumaraswamy, Hartwig, Fernando P, Horimoto, Andrea RVR, Liu, Yongmei, Manning, Alisa K, Noordam, Raymond, Smith, Albert V, Harris, Sarah E, Kühnel, Brigitte, Lyytikäinen, Leo-Pekka, Nolte, Ilja M, Rauramaa, Rainer, van der Most, Peter J, Wang, Rujia, Ware, Erin B, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Arking, Dan E, Arnett, Donna K, Barac, Ana, Boerwinkle, Eric, Broeckel, Ulrich, Chakravarti, Aravinda, Chen, Yii-Der Ida, Cupples, L Adrienne, Davigulus, Martha L, de las Fuentes, Lisa, de Mutsert, Renée, de Vries, Paul S, Delaney, Joseph AC, Roux, Ana V Diez, Dörr, Marcus, Faul, Jessica D, Fretts, Amanda M, Gallo, Linda C, Grabe, Hans Jörgen, Gu, C Charles, Harris, Tamara B, Hartman, Catharina CA, Heikkinen, Sami, Ikram, M Arfan, Isasi, Carmen, Johnson, W Craig, Jonas, Jost Bruno, Kaplan, Robert C, Komulainen, Pirjo, Krieger, Jose E, Levy, Daniel, Study, Lifelines Cohort, Liu, Jianjun, Lohman, Kurt, Luik, Annemarie I, Martin, Lisa W, Meitinger, Thomas, Milaneschi, Yuri, O’Connell, Jeff R, Palmas, Walter R, Peters, Annette, Peyser, Patricia A, Pulkki-Råback, Laura, Raffel, Leslie J, Reiner, Alex P, Rice, Kenneth, Robinson, Jennifer G, Rosendaal, Frits R, Schmidt, Carsten Oliver, Schreiner, Pamela J, Schwettmann, Lars, Shikany, James M, Shu, Xiao-ou, Sidney, Stephen, Sims, Mario, Smith, Jennifer A, Sotoodehnia, Nona, Strauch, Konstantin, Tai, E Shyong, Taylor, Kent D, Uitterlinden, André G, van Duijn, Cornelia M, Waldenberger, Melanie, Wee, Hwee-Lin, Wei, Wen-Bin, Wilson, Gregory, Xuan, Deng, and Yao, Jie
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Hypertension ,Mental Health ,Genetics ,Cardiovascular ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Lifelines Cohort Study - Abstract
Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value
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- 2021
22. Genome-wide association study identifies 48 common genetic variants associated with handedness
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Cuellar-Partida, Gabriel, Tung, Joyce Y, Eriksson, Nicholas, Albrecht, Eva, Aliev, Fazil, Andreassen, Ole A, Barroso, Inês, Beckmann, Jacques S, Boks, Marco P, Boomsma, Dorret I, Boyd, Heather A, Breteler, Monique MB, Campbell, Harry, Chasman, Daniel I, Cherkas, Lynn F, Davies, Gail, de Geus, Eco JC, Deary, Ian J, Deloukas, Panos, Dick, Danielle M, Duffy, David L, Eriksson, Johan G, Esko, Tõnu, Feenstra, Bjarke, Geller, Frank, Gieger, Christian, Giegling, Ina, Gordon, Scott D, Han, Jiali, Hansen, Thomas F, Hartmann, Annette M, Hayward, Caroline, Heikkilä, Kauko, Hicks, Andrew A, Hirschhorn, Joel N, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Liang-Dar, Ikram, M Arfan, Kaprio, Jaakko, Kemp, John P, Khaw, Kay-Tee, Klopp, Norman, Konte, Bettina, Kutalik, Zoltan, Lahti, Jari, Li, Xin, Loos, Ruth JF, Luciano, Michelle, Magnusson, Sigurdur H, Mangino, Massimo, Marques-Vidal, Pedro, Martin, Nicholas G, McArdle, Wendy L, McCarthy, Mark I, Medina-Gomez, Carolina, Melbye, Mads, Melville, Scott A, Metspalu, Andres, Milani, Lili, Mooser, Vincent, Nelis, Mari, Nyholt, Dale R, O’Connell, Kevin S, Ophoff, Roel A, Palmer, Cameron, Palotie, Aarno, Palviainen, Teemu, Pare, Guillaume, Paternoster, Lavinia, Peltonen, Leena, Penninx, Brenda WJH, Polasek, Ozren, Pramstaller, Peter P, Prokopenko, Inga, Raikkonen, Katri, Ripatti, Samuli, Rivadeneira, Fernando, Rudan, Igor, Rujescu, Dan, Smit, Johannes H, Smith, George Davey, Smoller, Jordan W, Soranzo, Nicole, Spector, Tim D, Pourcain, Beate St, Starr, John M, Stefánsson, Hreinn, Steinberg, Stacy, Teder-Laving, Maris, Thorleifsson, Gudmar, Stefánsson, Kári, Timpson, Nicholas J, Uitterlinden, André G, van Duijn, Cornelia M, van Rooij, Frank JA, Vink, Jaqueline M, Vollenweider, Peter, Vuoksimaa, Eero, and Waeber, Gérard
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Biological Psychology ,Pharmacology and Pharmaceutical Sciences ,Biomedical and Clinical Sciences ,Psychology ,Human Genome ,Mental Health ,Brain Disorders ,Neurosciences ,Schizophrenia ,Genetics ,2.1 Biological and endogenous factors ,Aetiology ,Mental health ,Adult ,Aged ,Female ,Functional Laterality ,Gene Frequency ,Genetic Loci ,Genetic Variation ,Genome-Wide Association Study ,Humans ,Linkage Disequilibrium ,Male ,Middle Aged ,Polymorphism ,Single Nucleotide ,Quantitative Trait ,Heritable ,Sex Factors ,Biomedical and clinical sciences ,Health sciences - Abstract
Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P
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- 2021
23. Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries
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Gharahkhani, Puya, Jorgenson, Eric, Hysi, Pirro, Khawaja, Anthony P, Pendergrass, Sarah, Han, Xikun, Ong, Jue Sheng, Hewitt, Alex W, Segrè, Ayellet V, Rouhana, John M, Hamel, Andrew R, Igo, Robert P, Choquet, Helene, Qassim, Ayub, Josyula, Navya S, Cooke Bailey, Jessica N, Bonnemaijer, Pieter WM, Iglesias, Adriana, Siggs, Owen M, Young, Terri L, Vitart, Veronique, Thiadens, Alberta AHJ, Karjalainen, Juha, Uebe, Steffen, Melles, Ronald B, Nair, K Saidas, Luben, Robert, Simcoe, Mark, Amersinghe, Nishani, Cree, Angela J, Hohn, Rene, Poplawski, Alicia, Chen, Li Jia, Rong, Shi-Song, Aung, Tin, Vithana, Eranga Nishanthie, Tamiya, Gen, Shiga, Yukihiro, Yamamoto, Masayuki, Nakazawa, Toru, Currant, Hannah, Birney, Ewan, Wang, Xin, Auton, Adam, Lupton, Michelle K, Martin, Nicholas G, Ashaye, Adeyinka, Olawoye, Olusola, Williams, Susan E, Akafo, Stephen, Ramsay, Michele, Hashimoto, Kazuki, Kamatani, Yoichiro, Akiyama, Masato, Momozawa, Yukihide, Foster, Paul J, Khaw, Peng T, Morgan, James E, Strouthidis, Nicholas G, Kraft, Peter, Kang, Jae H, Pang, Chi Pui, Pasutto, Francesca, Mitchell, Paul, Lotery, Andrew J, Palotie, Aarno, van Duijn, Cornelia, Haines, Jonathan L, Hammond, Chris, Pasquale, Louis R, Klaver, Caroline CW, Hauser, Michael, Khor, Chiea Chuen, Mackey, David A, Kubo, Michiaki, Cheng, Ching-Yu, Craig, Jamie E, MacGregor, Stuart, and Wiggs, Janey L
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Neurodegenerative ,Genetics ,Eye Disease and Disorders of Vision ,Aging ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,Asian People ,Genetic Loci ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genotype ,Glaucoma ,Open-Angle ,Humans ,Polymorphism ,Single Nucleotide ,White People ,NEIGHBORHOOD consortium ,ANZRAG consortium ,Biobank Japan project ,FinnGen study ,UK Biobank Eye and Vision Consortium ,GIGA study group ,and Me Research Team - Abstract
Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates.
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- 2021
24. Association of low-frequency and rare coding variants with information processing speed
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Bressler, Jan, Davies, Gail, Smith, Albert V, Saba, Yasaman, Bis, Joshua C, Jian, Xueqiu, Hayward, Caroline, Yanek, Lisa, Smith, Jennifer A, Mirza, Saira S, Wang, Ruiqi, Adams, Hieab HH, Becker, Diane, Boerwinkle, Eric, Campbell, Archie, Cox, Simon R, Eiriksdottir, Gudny, Fawns-Ritchie, Chloe, Gottesman, Rebecca F, Grove, Megan L, Guo, Xiuqing, Hofer, Edith, Kardia, Sharon LR, Knol, Maria J, Koini, Marisa, Lopez, Oscar L, Marioni, Riccardo E, Nyquist, Paul, Pattie, Alison, Polasek, Ozren, Porteous, David J, Rudan, Igor, Satizabal, Claudia L, Schmidt, Helena, Schmidt, Reinhold, Sidney, Stephen, Simino, Jeannette, Smith, Blair H, Turner, Stephen T, van der Lee, Sven J, Ware, Erin B, Whitmer, Rachel A, Yaffe, Kristine, Yang, Qiong, Zhao, Wei, Gudnason, Vilmundur, Launer, Lenore J, Fitzpatrick, Annette L, Psaty, Bruce M, Fornage, Myriam, Arfan Ikram, M, van Duijn, Cornelia M, Seshadri, Sudha, Mosley, Thomas H, and Deary, Ian J
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Genetics ,Brain Disorders ,Aging ,Human Genome ,Adult ,Cognition ,Genome-Wide Association Study ,Geroscience ,Humans ,Polymorphism ,Single Nucleotide ,Ubiquitin-Protein Ligases ,Clinical Sciences ,Public Health and Health Services ,Psychology - Abstract
Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10-6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.
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- 2021
25. Association of common genetic variants with brain microbleeds: A Genome-wide Association Study
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Knol, Maria J, Lu, Dongwei, Traylor, Matthew, Adams, Hieab HH, Romero, José Rafael J, Smith, Albert V, Fornage, Myriam, Hofer, Edith, Liu, Junfeng, Hostettler, Isabel C, Luciano, Michelle, Trompet, Stella, Giese, Anne-Katrin, Hilal, Saima, van den Akker, Erik B, Vojinovic, Dina, Li, Shuo, Sigurdsson, Sigurdur, van der Lee, Sven J, Jack, Clifford R, Wilson, Duncan, Yilmaz, Pinar, Satizabal, Claudia L, Liewald, David CM, van der Grond, Jeroen, Chen, Christopher, Saba, Yasaman, van der Lugt, Aad, Bastin, Mark E, Windham, B Gwen, Cheng, Ching Yu, Pirpamer, Lukas, Kantarci, Kejal, Himali, Jayandra J, Yang, Qiong, Morris, Zoe, Beiser, Alexa S, Tozer, Daniel J, Vernooij, Meike W, Amin, Najaf, Beekman, Marian, Koh, Jia Yu, Stott, David J, Houlden, Henry, Schmidt, Reinhold, Gottesman, Rebecca F, MacKinnon, Andrew D, DeCarli, Charles, Gudnason, Vilmundur, Deary, Ian J, van Duijn, Cornelia M, Slagboom, P Eline, Wong, Tien Yin, Rost, Natalia S, Jukema, J Wouter, Mosley, Thomas H, Werring, David J, Schmidt, Helena, Wardlaw, Joanna M, Ikram, M Arfan, Seshadri, Sudha, Launer, Lenore J, Markus, Hugh S, and Initiative, for the Alzheimer’s Disease Neuroimaging
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Stroke ,Human Genome ,Neurosciences ,Brain Disorders ,Genetics ,Prevention ,Aetiology ,2.1 Biological and endogenous factors ,Aged ,Aged ,80 and over ,Alleles ,Apolipoprotein E2 ,Apolipoprotein E4 ,Apolipoproteins E ,Case-Control Studies ,Cerebral Hemorrhage ,Cerebral Small Vessel Diseases ,Cohort Studies ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Magnetic Resonance Imaging ,Male ,Middle Aged ,Polymorphism ,Single Nucleotide ,Risk ,White Matter ,Alzheimer's Disease Neuroimaging Initiative ,Clinical Sciences ,Cognitive Sciences ,Neurology & Neurosurgery - Abstract
ObjectiveTo identify common genetic variants associated with the presence of brain microbleeds (BMBs).MethodsWe performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.ResultsBMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21-1.45]; p = 2.5 × 10-10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; p = 1.0 × 10-6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.ConclusionsGenetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.
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- 2020
26. Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity
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Yaghootkar, Hanieh, Zhang, Yiying, Spracklen, Cassandra N, Karaderi, Tugce, Huang, Lam Opal, Bradfield, Jonathan, Schurmann, Claudia, Fine, Rebecca S, Preuss, Michael H, Kutalik, Zoltan, Wittemans, Laura BL, Lu, Yingchang, Metz, Sophia, Willems, Sara M, Li-Gao, Ruifang, Grarup, Niels, Wang, Shuai, Molnos, Sophie, Sandoval-Zárate, América A, Nalls, Mike A, Lange, Leslie A, Haesser, Jeffrey, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Feitosa, Mary F, Sitlani, Colleen M, Venturini, Cristina, Mahajan, Anubha, Kacprowski, Tim, Wang, Carol A, Chasman, Daniel I, Amin, Najaf, Broer, Linda, Robertson, Neil, Young, Kristin L, Allison, Matthew, Auer, Paul L, Blüher, Matthias, Borja, Judith B, Bork-Jensen, Jette, Carrasquilla, Germán D, Christofidou, Paraskevi, Demirkan, Ayse, Doege, Claudia A, Garcia, Melissa E, Graff, Mariaelisa, Guo, Kaiying, Hakonarson, Hakon, Hong, Jaeyoung, Ida Chen, Yii-Der, Jackson, Rebecca, Jakupović, Hermina, Jousilahti, Pekka, Justice, Anne E, Kähönen, Mika, Kizer, Jorge R, Kriebel, Jennifer, LeDuc, Charles A, Li, Jin, Lind, Lars, Luan, Jian'an, Mackey, David A, Mangino, Massimo, Männistö, Satu, Martin Carli, Jayne F, Medina-Gomez, Carolina, Mook-Kanamori, Dennis O, Morris, Andrew P, de Mutsert, Renée, Nauck, Matthias, Prokic, Ivana, Pennell, Craig E, Pradhan, Arund D, Psaty, Bruce M, Raitakari, Olli T, Scott, Robert A, Skaaby, Tea, Strauch, Konstantin, Taylor, Kent D, Teumer, Alexander, Uitterlinden, Andre G, Wu, Ying, Yao, Jie, Walker, Mark, North, Kari E, Kovacs, Peter, Ikram, M Arfan, van Duijn, Cornelia M, Ridker, Paul M, Lye, Stephen, Homuth, Georg, Ingelsson, Erik, Spector, Tim D, McKnight, Barbara, Province, Michael A, Lehtimäki, Terho, Adair, Linda S, Rotter, Jerome I, Reiner, Alexander P, and Wilson, James G
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Genetics ,Nutrition ,Prevention ,Obesity ,Aetiology ,2.1 Biological and endogenous factors ,Oral and gastrointestinal ,Metabolic and endocrine ,Cardiovascular ,Stroke ,Cancer ,Adiposity ,Gene Expression Regulation ,Developmental ,Genetic Variation ,Genotype ,Humans ,Leptin ,Models ,Molecular ,Protein Conformation ,Racial Groups ,Medical and Health Sciences ,Endocrinology & Metabolism - Abstract
Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.
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- 2020
27. Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation
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Weng, Lu-Chen, Hall, Amelia Weber, Choi, Seung Hoan, Jurgens, Sean J, Haessler, Jeffrey, Bihlmeyer, Nathan A, Grarup, Niels, Lin, Honghuang, Teumer, Alexander, Li-Gao, Ruifang, Yao, Jie, Guo, Xiuqing, Brody, Jennifer A, Müller-Nurasyid, Martina, Schramm, Katharina, Verweij, Niek, van den Berg, Marten E, van Setten, Jessica, Isaacs, Aaron, Ramírez, Julia, Warren, Helen R, Padmanabhan, Sandosh, Kors, Jan A, de Boer, Rudolf A, van der Meer, Peter, Sinner, Moritz F, Waldenberger, Melanie, Psaty, Bruce M, Taylor, Kent D, Völker, Uwe, Kanters, Jørgen K, Li, Man, Alonso, Alvaro, Perez, Marco V, Vaartjes, Ilonca, Bots, Michiel L, Huang, Paul L, Heckbert, Susan R, Lin, Henry J, Kornej, Jelena, Munroe, Patricia B, van Duijn, Cornelia M, Asselbergs, Folkert W, Stricker, Bruno H, van der Harst, Pim, Kääb, Stefan, Peters, Annette, Sotoodehnia, Nona, Rotter, Jerome I, Mook-Kanamori, Dennis O, Dörr, Marcus, Felix, Stephan B, Linneberg, Allan, Hansen, Torben, Arking, Dan E, Kooperberg, Charles, Benjamin, Emelia J, Lunetta, Kathryn L, Ellinor, Patrick T, and Lubitz, Steven A
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Clinical Research ,Genetics ,Heart Disease ,Cardiovascular ,Human Genome ,2.1 Biological and endogenous factors ,Aetiology ,Atrial Fibrillation ,Cardiac Myosins ,Connectin ,Electrocardiography ,Genetic Variation ,Genome-Wide Association Study ,Homeodomain Proteins ,Humans ,Myosin Heavy Chains ,NAV1.8 Voltage-Gated Sodium Channel ,Quantitative Trait Loci ,Transcription Factors ,atrial fibrillation ,electrophysiology ,exome ,genetic ,genome-wide association studies ,population ,Medical Biotechnology ,Cardiorespiratory Medicine and Haematology ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology - Abstract
BackgroundThe P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD.MethodsFifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies.ResultsWe identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk.ConclusionsOur results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF.
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- 2020
28. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.
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Hofer, Edith, Roshchupkin, Gennady V, Adams, Hieab HH, Knol, Maria J, Lin, Honghuang, Li, Shuo, Zare, Habil, Ahmad, Shahzad, Armstrong, Nicola J, Satizabal, Claudia L, Bernard, Manon, Bis, Joshua C, Gillespie, Nathan A, Luciano, Michelle, Mishra, Aniket, Scholz, Markus, Teumer, Alexander, Xia, Rui, Jian, Xueqiu, Mosley, Thomas H, Saba, Yasaman, Pirpamer, Lukas, Seiler, Stephan, Becker, James T, Carmichael, Owen, Rotter, Jerome I, Psaty, Bruce M, Lopez, Oscar L, Amin, Najaf, van der Lee, Sven J, Yang, Qiong, Himali, Jayandra J, Maillard, Pauline, Beiser, Alexa S, DeCarli, Charles, Karama, Sherif, Lewis, Lindsay, Harris, Mat, Bastin, Mark E, Deary, Ian J, Veronica Witte, A, Beyer, Frauke, Loeffler, Markus, Mather, Karen A, Schofield, Peter R, Thalamuthu, Anbupalam, Kwok, John B, Wright, Margaret J, Ames, David, Trollor, Julian, Jiang, Jiyang, Brodaty, Henry, Wen, Wei, Vernooij, Meike W, Hofman, Albert, Uitterlinden, André G, Niessen, Wiro J, Wittfeld, Katharina, Bülow, Robin, Völker, Uwe, Pausova, Zdenka, Bruce Pike, G, Maingault, Sophie, Crivello, Fabrice, Tzourio, Christophe, Amouyel, Philippe, Mazoyer, Bernard, Neale, Michael C, Franz, Carol E, Lyons, Michael J, Panizzon, Matthew S, Andreassen, Ole A, Dale, Anders M, Logue, Mark, Grasby, Katrina L, Jahanshad, Neda, Painter, Jodie N, Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P, Lind, Penelope A, Pizzagalli, Fabrizio, Stein, Jason L, Thompson, Paul M, Medland, Sarah E, ENIGMA consortium, Sachdev, Perminder S, Kremen, William S, Wardlaw, Joanna M, Villringer, Arno, van Duijn, Cornelia M, Grabe, Hans J, Longstreth, William T, Fornage, Myriam, Paus, Tomas, Debette, Stephanie, Ikram, M Arfan, Schmidt, Helena, Schmidt, Reinhold, and Seshadri, Sudha
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ENIGMA consortium ,Brain ,Chromosome Structures ,Humans ,Neurodegenerative Diseases ,Cognition ,Mental Disorders ,Genomics ,Aging ,Phenotype ,Polymorphism ,Single Nucleotide ,Adult ,Aged ,Aged ,80 and over ,Middle Aged ,Female ,Male ,Genome-Wide Association Study ,Genetics ,Neurosciences ,Human Genome ,Brain Disorders ,Biotechnology ,1.1 Normal biological development and functioning ,2.1 Biological and endogenous factors ,Neurological - Abstract
Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
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- 2020
29. Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities
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Armstrong, Nicola J, Mather, Karen A, Sargurupremraj, Muralidharan, Knol, Maria J, Malik, Rainer, Satizabal, Claudia L, Yanek, Lisa R, Wen, Wei, Gudnason, Vilmundur G, Dueker, Nicole D, Elliott, Lloyd T, Hofer, Edith, Bis, Joshua, Jahanshad, Neda, Li, Shuo, Logue, Mark A, Luciano, Michelle, Scholz, Markus, Smith, Albert V, Trompet, Stella, Vojinovic, Dina, Xia, Rui, Alfaro-Almagro, Fidel, Ames, David, Amin, Najaf, Amouyel, Philippe, Beiser, Alexa S, Brodaty, Henry, Deary, Ian J, Fennema-Notestine, Christine, Gampawar, Piyush G, Gottesman, Rebecca, Griffanti, Ludovica, Jack, Clifford R, Jenkinson, Mark, Jiang, Jiyang, Kral, Brian G, Kwok, John B, Lampe, Leonie, C.M. Liewald, David, Maillard, Pauline, Marchini, Jonathan, Bastin, Mark E, Mazoyer, Bernard, Pirpamer, Lukas, Rafael Romero, José, Roshchupkin, Gennady V, Schofield, Peter R, Schroeter, Matthias L, Stott, David J, Thalamuthu, Anbupalam, Trollor, Julian, Tzourio, Christophe, van der Grond, Jeroen, Vernooij, Meike W, Witte, Veronica A, Wright, Margaret J, Yang, Qiong, Morris, Zoe, Siggurdsson, Siggi, Psaty, Bruce, Villringer, Arno, Schmidt, Helena, Haberg, Asta K, van Duijn, Cornelia M, Jukema, J Wouter, Dichgans, Martin, Sacco, Ralph L, Wright, Clinton B, Kremen, William S, Becker, Lewis C, Thompson, Paul M, Mosley, Thomas H, Wardlaw, Joanna M, Ikram, M Arfan, Adams, Hieab HH, Seshadri, Sudha, Sachdev, Perminder S, Smith, Stephen M, Launer, Lenore, Longstreth, William, DeCarli, Charles, Schmidt, Reinhold, Fornage, Myriam, Debette, Stephanie, and Nyquist, Paul A
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Epidemiology ,Health Sciences ,Neurodegenerative ,Aging ,Dementia ,Stroke ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Genetics ,Acquired Cognitive Impairment ,Human Genome ,Biotechnology ,Vascular Cognitive Impairment/Dementia ,Brain Disorders ,Neurosciences ,Cerebrovascular ,Alzheimer's Disease Related Dementias (ADRD) ,2.1 Biological and endogenous factors ,Aged ,Brain ,Cerebral Small Vessel Diseases ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Male ,Middle Aged ,White Matter ,brain ,genome-wide association study ,neuroimaging ,risk factors ,white matter ,Cardiorespiratory Medicine and Haematology ,Clinical Sciences ,Neurology & Neurosurgery ,Clinical sciences ,Allied health and rehabilitation science - Abstract
Background and purposePeriventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings.MethodsParticipants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC.ResultsIn the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype.ConclusionsOur study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
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- 2020
30. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose
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Wu, Peitao, Rybin, Denis, Bielak, Lawrence F, Feitosa, Mary F, Franceschini, Nora, Li, Yize, Lu, Yingchang, Marten, Jonathan, Musani, Solomon K, Noordam, Raymond, Raghavan, Sridharan, Rose, Lynda M, Schwander, Karen, Smith, Albert V, Tajuddin, Salman M, Vojinovic, Dina, Amin, Najaf, Arnett, Donna K, Bottinger, Erwin P, Demirkan, Ayse, Florez, Jose C, Ghanbari, Mohsen, Harris, Tamara B, Launer, Lenore J, Liu, Jingmin, Liu, Jun, Mook-Kanamori, Dennis O, Murray, Alison D, Nalls, Mike A, Peyser, Patricia A, Uitterlinden, André G, Voortman, Trudy, Bouchard, Claude, Chasman, Daniel, Correa, Adolfo, de Mutsert, Renée, Evans, Michele K, Gudnason, Vilmundur, Hayward, Caroline, Kao, Linda, Kardia, Sharon LR, Kooperberg, Charles, Loos, Ruth JF, Province, Michael M, Rankinen, Tuomo, Redline, Susan, Ridker, Paul M, Rotter, Jerome I, Siscovick, David, Smith, Blair H, van Duijn, Cornelia, Zonderman, Alan B, Rao, DC, Wilson, James G, Dupuis, Josée, Meigs, James B, Liu, Ching-Ti, and Vassy, Jason L
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Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Epidemiology ,Health Sciences ,Pharmacology and Pharmaceutical Sciences ,Clinical Research ,Tobacco Smoke and Health ,Diabetes ,Health Disparities ,Prevention ,Aging ,Human Genome ,Tobacco ,Minority Health ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,Good Health and Well Being ,Adult ,Aged ,Black People ,Blood Glucose ,Cigarette Smoking ,Cohort Studies ,Diabetes Mellitus ,Type 2 ,Fasting ,Feasibility Studies ,Female ,Genetic Loci ,Genome-Wide Association Study ,Genotype ,Humans ,Incidence ,Male ,Middle Aged ,Polymorphism ,Single Nucleotide ,Risk ,White People ,General Science & Technology - Abstract
Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p
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- 2020
31. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction
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Ntalla, Ioanna, Weng, Lu-Chen, Cartwright, James H, Hall, Amelia Weber, Sveinbjornsson, Gardar, Tucker, Nathan R, Choi, Seung Hoan, Chaffin, Mark D, Roselli, Carolina, Barnes, Michael R, Mifsud, Borbala, Warren, Helen R, Hayward, Caroline, Marten, Jonathan, Cranley, James J, Concas, Maria Pina, Gasparini, Paolo, Boutin, Thibaud, Kolcic, Ivana, Polasek, Ozren, Rudan, Igor, Araujo, Nathalia M, Lima-Costa, Maria Fernanda, Ribeiro, Antonio Luiz P, Souza, Renan P, Tarazona-Santos, Eduardo, Giedraitis, Vilmantas, Ingelsson, Erik, Mahajan, Anubha, Morris, Andrew P, Del Greco M, Fabiola, Foco, Luisa, Gögele, Martin, Hicks, Andrew A, Cook, James P, Lind, Lars, Lindgren, Cecilia M, Sundström, Johan, Nelson, Christopher P, Riaz, Muhammad B, Samani, Nilesh J, Sinagra, Gianfranco, Ulivi, Sheila, Kähönen, Mika, Mishra, Pashupati P, Mononen, Nina, Nikus, Kjell, Caulfield, Mark J, Dominiczak, Anna, Padmanabhan, Sandosh, Montasser, May E, O’Connell, Jeff R, Ryan, Kathleen, Shuldiner, Alan R, Aeschbacher, Stefanie, Conen, David, Risch, Lorenz, Thériault, Sébastien, Hutri-Kähönen, Nina, Lehtimäki, Terho, Lyytikäinen, Leo-Pekka, Raitakari, Olli T, Barnes, Catriona LK, Campbell, Harry, Joshi, Peter K, Wilson, James F, Isaacs, Aaron, Kors, Jan A, van Duijn, Cornelia M, Huang, Paul L, Gudnason, Vilmundur, Harris, Tamara B, Launer, Lenore J, Smith, Albert V, Bottinger, Erwin P, Loos, Ruth JF, Nadkarni, Girish N, Preuss, Michael H, Correa, Adolfo, Mei, Hao, Wilson, James, Meitinger, Thomas, Müller-Nurasyid, Martina, Peters, Annette, Waldenberger, Melanie, Mangino, Massimo, Spector, Timothy D, Rienstra, Michiel, van de Vegte, Yordi J, van der Harst, Pim, Verweij, Niek, Kääb, Stefan, Schramm, Katharina, Sinner, Moritz F, Strauch, Konstantin, Cutler, Michael J, Fatkin, Diane, London, Barry, Olesen, Morten, and Roden, Dan M
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Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Heart Disease ,Cardiovascular ,Biotechnology ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Arrhythmias ,Cardiac ,Cardiovascular Diseases ,Electrocardiography ,Endophenotypes ,Female ,Gene Expression ,Genetic Loci ,Genetic Predisposition to Disease ,Genetic Variation ,Genome-Wide Association Study ,Humans ,Male ,Multifactorial Inheritance ,Quantitative Trait Loci - Abstract
The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
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- 2020
32. Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness
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Abdellaoui, Abdel, Sanchez-Roige, Sandra, Sealock, Julia, Treur, Jorien L, Dennis, Jessica, Fontanillas, Pierre, Elson, Sarah, Team, The 23andme Research, Nivard, Michel G, Ip, Hill Fung, van der Zee, Matthijs, Baselmans, Bart ML, Hottenga, Jouke Jan, Willemsen, Gonneke, Mosing, Miriam, Lu, Yi, Pedersen, Nancy L, Denys, Damiaan, Amin, Najaf, van Duijn, Cornelia M, Szilagyi, Ingrid, Tiemeier, Henning, Neumann, Alexander, Verweij, Karin JH, Cacioppo, Stephanie, Cacioppo, John T, Davis, Lea K, Palmer, Abraham A, and Boomsma, Dorret I
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Biological Sciences ,Genetics ,Mental Health ,Prevention ,Human Genome ,Obesity ,2.1 Biological and endogenous factors ,2.3 Psychological ,social and economic factors ,Mental health ,Cardiovascular ,Good Health and Well Being ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genotype ,Health ,Humans ,Loneliness ,Male ,Mendelian Randomization Analysis ,Mental Disorders ,Multifactorial Inheritance ,Phenomics ,Phenotype ,Polymorphism ,Single Nucleotide ,23andme Research Team ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.
- Published
- 2019
33. Association of Genetic Variants With Primary Open-Angle Glaucoma Among Individuals With African Ancestry
- Author
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Consortium, The Genetics of Glaucoma in People of African Descent, Hauser, Michael A, Allingham, R Rand, Aung, Tin, Van Der Heide, Carly J, Taylor, Kent D, Rotter, Jerome I, Wang, Shih-Hsiu J, Bonnemaijer, Pieter WM, Williams, Susan E, Abdullahi, Sadiq M, Abu-Amero, Khaled K, Anderson, Michael G, Akafo, Stephen, Alhassan, Mahmoud B, Asimadu, Ifeoma, Ayyagari, Radha, Bakayoko, Saydou, Nyamsi, Prisca Biangoup, Bowden, Donald W, Bromley, William C, Budenz, Donald L, Carmichael, Trevor R, Challa, Pratap, Chen, Yii-Der Ida, Chuka-Okosa, Chimdi M, Bailey, Jessica N Cooke, Costa, Vital Paulino, Cruz, Dianne A, DuBiner, Harvey, Ervin, John F, Feldman, Robert M, Flamme-Wiese, Miles, Gaasterland, Douglas E, Garnai, Sarah J, Girkin, Christopher A, Guirou, Nouhoum, Guo, Xiuqing, Haines, Jonathan L, Hammond, Christopher J, Herndon, Leon, Hoffmann, Thomas J, Hulette, Christine M, Hydara, Abba, Igo, Robert P, Jorgenson, Eric, Kabwe, Joyce, Kilangalanga, Ngoy Janvier, Kizor-Akaraiwe, Nkiru, Kuchtey, Rachel W, Lamari, Hasnaa, Li, Zheng, Liebmann, Jeffrey M, Liu, Yutao, Loos, Ruth JF, Melo, Monica B, Moroi, Sayoko E, Msosa, Joseph M, Mullins, Robert F, Nadkarni, Girish, Napo, Abdoulaye, Ng, Maggie CY, Nunes, Hugo Freire, Obeng-Nyarkoh, Ebenezer, Okeke, Anthony, Okeke, Suhanya, Olaniyi, Olusegun, Olawoye, Olusola, Oliveira, Mariana Borges, Pasquale, Louise R, Perez-Grossmann, Rodolfo A, Pericak-Vance, Margaret A, Qin, Xue, Ramsay, Michele, Resnikoff, Serge, Richards, Julia E, Schimiti, Rui Barroso, Sim, Kar Seng, Sponsel, William E, Svidnicki, Paulo Vinicius, Thiadens, Alberta AHJ, Uche, Nkechinyere J, van Duijn, Cornelia M, de Vasconcellos, José Paulo Cabral, Wiggs, Janey L, Zangwill, Linda M, Risch, Neil, Milea, Dan, Ashaye, Adeyinka, Klaver, Caroline CW, Weinreb, Robert N, Koch, Allison E Ashley, Fingert, John H, and Khor, Chiea Chuen
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Biomedical and Clinical Sciences ,Ophthalmology and Optometry ,Genetics ,Neurodegenerative ,Clinical Research ,Neurosciences ,Human Genome ,Eye Disease and Disorders of Vision ,Aging ,2.1 Biological and endogenous factors ,2.4 Surveillance and distribution ,Eye ,Adaptor Proteins ,Signal Transducing ,Aged ,Amyloid beta-Peptides ,Black People ,Case-Control Studies ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genotype ,Glaucoma ,Open-Angle ,Humans ,Immunohistochemistry ,Male ,Meta-Analysis as Topic ,Middle Aged ,Polymorphism ,Single Nucleotide ,Risk Factors ,Genetics of Glaucoma in People of African Descent (GGLAD) Consortium ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
ImportancePrimary open-angle glaucoma presents with increased prevalence and a higher degree of clinical severity in populations of African ancestry compared with European or Asian ancestry. Despite this, individuals of African ancestry remain understudied in genomic research for blinding disorders.ObjectivesTo perform a genome-wide association study (GWAS) of African ancestry populations and evaluate potential mechanisms of pathogenesis for loci associated with primary open-angle glaucoma.Design, settings, and participantsA 2-stage GWAS with a discovery data set of 2320 individuals with primary open-angle glaucoma and 2121 control individuals without primary open-angle glaucoma. The validation stage included an additional 6937 affected individuals and 14 917 unaffected individuals using multicenter clinic- and population-based participant recruitment approaches. Study participants were recruited from Ghana, Nigeria, South Africa, the United States, Tanzania, Britain, Cameroon, Saudi Arabia, Brazil, the Democratic Republic of the Congo, Morocco, Peru, and Mali from 2003 to 2018. Individuals with primary open-angle glaucoma had open iridocorneal angles and displayed glaucomatous optic neuropathy with visual field defects. Elevated intraocular pressure was not included in the case definition. Control individuals had no elevated intraocular pressure and no signs of glaucoma.ExposuresGenetic variants associated with primary open-angle glaucoma.Main outcomes and measuresPresence of primary open-angle glaucoma. Genome-wide significance was defined as P C) with primary open-angle glaucoma (odds ratio [OR], 1.32 [95% CI, 1.20-1.46]; P = 2 × 10-8). The association was validated in an analysis of an additional 6937 affected individuals and 14 917 unaffected individuals (OR, 1.15 [95% CI, 1.09-1.21]; P
- Published
- 2019
34. Association of Genetic Variants With Primary Open-Angle Glaucoma Among Individuals With African Ancestry.
- Author
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Genetics of Glaucoma in People of African Descent (GGLAD) Consortium, Hauser, Michael A, Allingham, R Rand, Aung, Tin, Van Der Heide, Carly J, Taylor, Kent D, Rotter, Jerome I, Wang, Shih-Hsiu J, Bonnemaijer, Pieter WM, Williams, Susan E, Abdullahi, Sadiq M, Abu-Amero, Khaled K, Anderson, Michael G, Akafo, Stephen, Alhassan, Mahmoud B, Asimadu, Ifeoma, Ayyagari, Radha, Bakayoko, Saydou, Nyamsi, Prisca Biangoup, Bowden, Donald W, Bromley, William C, Budenz, Donald L, Carmichael, Trevor R, Challa, Pratap, Chen, Yii-Der Ida, Chuka-Okosa, Chimdi M, Cooke Bailey, Jessica N, Costa, Vital Paulino, Cruz, Dianne A, DuBiner, Harvey, Ervin, John F, Feldman, Robert M, Flamme-Wiese, Miles, Gaasterland, Douglas E, Garnai, Sarah J, Girkin, Christopher A, Guirou, Nouhoum, Guo, Xiuqing, Haines, Jonathan L, Hammond, Christopher J, Herndon, Leon, Hoffmann, Thomas J, Hulette, Christine M, Hydara, Abba, Igo, Robert P, Jorgenson, Eric, Kabwe, Joyce, Kilangalanga, Ngoy Janvier, Kizor-Akaraiwe, Nkiru, Kuchtey, Rachel W, Lamari, Hasnaa, Li, Zheng, Liebmann, Jeffrey M, Liu, Yutao, Loos, Ruth JF, Melo, Monica B, Moroi, Sayoko E, Msosa, Joseph M, Mullins, Robert F, Nadkarni, Girish, Napo, Abdoulaye, Ng, Maggie CY, Nunes, Hugo Freire, Obeng-Nyarkoh, Ebenezer, Okeke, Anthony, Okeke, Suhanya, Olaniyi, Olusegun, Olawoye, Olusola, Oliveira, Mariana Borges, Pasquale, Louise R, Perez-Grossmann, Rodolfo A, Pericak-Vance, Margaret A, Qin, Xue, Ramsay, Michele, Resnikoff, Serge, Richards, Julia E, Schimiti, Rui Barroso, Sim, Kar Seng, Sponsel, William E, Svidnicki, Paulo Vinicius, Thiadens, Alberta AHJ, Uche, Nkechinyere J, van Duijn, Cornelia M, de Vasconcellos, José Paulo Cabral, Wiggs, Janey L, Zangwill, Linda M, Risch, Neil, Milea, Dan, Ashaye, Adeyinka, Klaver, Caroline CW, Weinreb, Robert N, Ashley Koch, Allison E, Fingert, John H, and Khor, Chiea Chuen
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Genetics of Glaucoma in People of African Descent (GGLAD) Consortium ,Humans ,Glaucoma ,Open-Angle ,Genetic Predisposition to Disease ,Adaptor Proteins ,Signal Transducing ,Immunohistochemistry ,Risk Factors ,Case-Control Studies ,Genotype ,Polymorphism ,Single Nucleotide ,Aged ,Middle Aged ,African Continental Ancestry Group ,Female ,Male ,Meta-Analysis as Topic ,Genome-Wide Association Study ,Amyloid beta-Peptides ,Eye Disease and Disorders of Vision ,Clinical Research ,Human Genome ,Aging ,Neurodegenerative ,Genetics ,Neurosciences ,2.1 Biological and endogenous factors ,General & Internal Medicine ,Medical and Health Sciences - Abstract
Importance:Primary open-angle glaucoma presents with increased prevalence and a higher degree of clinical severity in populations of African ancestry compared with European or Asian ancestry. Despite this, individuals of African ancestry remain understudied in genomic research for blinding disorders. Objectives:To perform a genome-wide association study (GWAS) of African ancestry populations and evaluate potential mechanisms of pathogenesis for loci associated with primary open-angle glaucoma. Design, Settings, and Participants:A 2-stage GWAS with a discovery data set of 2320 individuals with primary open-angle glaucoma and 2121 control individuals without primary open-angle glaucoma. The validation stage included an additional 6937 affected individuals and 14 917 unaffected individuals using multicenter clinic- and population-based participant recruitment approaches. Study participants were recruited from Ghana, Nigeria, South Africa, the United States, Tanzania, Britain, Cameroon, Saudi Arabia, Brazil, the Democratic Republic of the Congo, Morocco, Peru, and Mali from 2003 to 2018. Individuals with primary open-angle glaucoma had open iridocorneal angles and displayed glaucomatous optic neuropathy with visual field defects. Elevated intraocular pressure was not included in the case definition. Control individuals had no elevated intraocular pressure and no signs of glaucoma. Exposures:Genetic variants associated with primary open-angle glaucoma. Main Outcomes and Measures:Presence of primary open-angle glaucoma. Genome-wide significance was defined as P C) with primary open-angle glaucoma (odds ratio [OR], 1.32 [95% CI, 1.20-1.46]; P = 2 × 10-8). The association was validated in an analysis of an additional 6937 affected individuals and 14 917 unaffected individuals (OR, 1.15 [95% CI, 1.09-1.21]; P
- Published
- 2019
35. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility
- Author
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Patsopoulos, Nikolaos A, Baranzini, Sergio E, Santaniello, Adam, Shoostari, Parisa, Cotsapas, Chris, Wong, Garrett, Beecham, Ashley H, James, Tojo, Replogle, Joseph, Vlachos, Ioannis S, McCabe, Cristin, Pers, Tune H, Brandes, Aaron, White, Charles, Keenan, Brendan, Cimpean, Maria, Winn, Phoebe, Panteliadis, Ioannis-Pavlos, Robbins, Allison, Andlauer, Till FM, Zarzycki, Onigiusz, Dubois, Bénédicte, Goris, An, Søndergaard, Helle Bach, Sellebjerg, Finn, Sorensen, Per Soelberg, Ullum, Henrik, Thørner, Lise Wegner, Saarela, Janna, Cournu-Rebeix, Isabelle, Damotte, Vincent, Fontaine, Bertrand, Guillot-Noel, Lena, Lathrop, Mark, Vukusic, Sandra, Berthele, Achim, Pongratz, Viola, Buck, Dorothea, Gasperi, Christiane, Graetz, Christiane, Grummel, Verena, Hemmer, Bernhard, Hoshi, Muni, Knier, Benjamin, Korn, Thomas, Lill, Christina M, Luessi, Felix, Mühlau, Mark, Zipp, Frauke, Dardiotis, Efthimios, Agliardi, Cristina, Amoroso, Antonio, Barizzone, Nadia, Benedetti, Maria D, Bernardinelli, Luisa, Cavalla, Paola, Clarelli, Ferdinando, Comi, Giancarlo, Cusi, Daniele, Esposito, Federica, Ferrè, Laura, Galimberti, Daniela, Guaschino, Clara, Leone, Maurizio A, Martinelli, Vittorio, Moiola, Lucia, Salvetti, Marco, Sorosina, Melissa, Vecchio, Domizia, Zauli, Andrea, Santoro, Silvia, Mancini, Nicasio, Zuccalà, Miriam, Mescheriakova, Julia, van Duijn, Cornelia, Bos, Steffan D, Celius, Elisabeth G, Spurkland, Anne, Comabella, Manuel, Montalban, Xavier, Alfredsson, Lars, Bomfim, Izaura L, Gomez-Cabrero, David, Hillert, Jan, Jagodic, Maja, Lindén, Magdalena, Piehl, Fredrik, Jelčić, Ilijas, Martin, Roland, Sospedra, Mirela, Baker, Amie, Ban, Maria, Hawkins, Clive, Hysi, Pirro, Kalra, Seema, Karpe, Fredrik, Khadake, Jyoti, Lachance, Genevieve, Molyneux, Paul, and Neville, Matthew
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Neurosciences ,Brain Disorders ,Multiple Sclerosis ,Human Genome ,Autoimmune Disease ,Clinical Research ,Genetics ,Neurodegenerative ,Aetiology ,2.1 Biological and endogenous factors ,Inflammatory and immune system ,Neurological ,Case-Control Studies ,Cell Cycle Proteins ,Chromosome Mapping ,Chromosomes ,Human ,X ,GTPase-Activating Proteins ,Gene Frequency ,Genetic Loci ,Genome-Wide Association Study ,Genomics ,Humans ,Inheritance Patterns ,Major Histocompatibility Complex ,Microglia ,Polymorphism ,Single Nucleotide ,Quantitative Trait Loci ,RNA-Seq ,Transcriptome ,International Multiple Sclerosis Genetics Consortium ,General Science & Technology - Abstract
We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses.
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- 2019
36. A genome-wide association study identifies genetic loci associated with specific lobar brain volumes
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van der Lee, Sven J, Knol, Maria J, Chauhan, Ganesh, Satizabal, Claudia L, Smith, Albert Vernon, Hofer, Edith, Bis, Joshua C, Hibar, Derrek P, Hilal, Saima, van den Akker, Erik B, Arfanakis, Konstantinos, Bernard, Manon, Yanek, Lisa R, Amin, Najaf, Crivello, Fabrice, Cheung, Josh W, Harris, Tamara B, Saba, Yasaman, Lopez, Oscar L, Li, Shuo, van der Grond, Jeroen, Yu, Lei, Paus, Tomas, Roshchupkin, Gennady V, Amouyel, Philippe, Jahanshad, Neda, Taylor, Kent D, Yang, Qiong, Mathias, Rasika A, Boehringer, Stefan, Mazoyer, Bernard, Rice, Ken, Cheng, Ching Yu, Maillard, Pauline, van Heemst, Diana, Wong, Tien Yin, Niessen, Wiro J, Beiser, Alexa S, Beekman, Marian, Zhao, Wanting, Nyquist, Paul A, Chen, Christopher, Launer, Lenore J, Psaty, Bruce M, Ikram, M Kamran, Vernooij, Meike W, Schmidt, Helena, Pausova, Zdenka, Becker, Diane M, De Jager, Philip L, Thompson, Paul M, van Duijn, Cornelia M, Bennett, David A, Slagboom, P Eline, Schmidt, Reinhold, Longstreth, WT, Ikram, M Arfan, Seshadri, Sudha, Debette, Stéphanie, Gudnason, Vilmundur, Adams, Hieab HH, and DeCarli, Charles
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Biological Sciences ,Genetics ,Mental Health ,Human Genome ,Brain Disorders ,Neurosciences ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Neurological ,Frontal Lobe ,Gene Expression Regulation ,Developmental ,Genetic Loci ,Genetic Variation ,Genome-Wide Association Study ,Genotype ,Heredity ,Humans ,Magnetic Resonance Imaging ,Occipital Lobe ,Organ Size ,Parietal Lobe ,Phenotype ,Temporal Lobe ,United Kingdom ,Biomarkers ,Genome-wide association studies ,Neurology ,Biological sciences ,Biomedical and clinical sciences - Abstract
Brain lobar volumes are heritable but genetic studies are limited. We performed genome-wide association studies of frontal, occipital, parietal and temporal lobe volumes in 16,016 individuals, and replicated our findings in 8,789 individuals. We identified six genetic loci associated with specific lobar volumes independent of intracranial volume. Two loci, associated with occipital (6q22.32) and temporal lobe volume (12q14.3), were previously reported to associate with intracranial and hippocampal volume, respectively. We identified four loci previously unknown to affect brain volumes: 3q24 for parietal lobe volume, and 1q22, 4p16.3 and 14q23.1 for occipital lobe volume. The associated variants were located in regions enriched for histone modifications (DAAM1 and THBS3), or close to genes causing Mendelian brain-related diseases (ZIC4 and FGFRL1). No genetic overlap between lobar volumes and neurological or psychiatric diseases was observed. Our findings reveal part of the complex genetics underlying brain development and suggest a role for regulatory regions in determining brain volumes.
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- 2019
37. Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology
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Spracklen, Cassandra N, Karaderi, Tugce, Yaghootkar, Hanieh, Schurmann, Claudia, Fine, Rebecca S, Kutalik, Zoltan, Preuss, Michael H, Lu, Yingchang, Wittemans, Laura BL, Adair, Linda S, Allison, Matthew, Amin, Najaf, Auer, Paul L, Bartz, Traci M, Blüher, Matthias, Boehnke, Michael, Borja, Judith B, Bork-Jensen, Jette, Broer, Linda, Chasman, Daniel I, Chen, Yii-Der Ida, Chirstofidou, Paraskevi, Demirkan, Ayse, van Duijn, Cornelia M, Feitosa, Mary F, Garcia, Melissa E, Graff, Mariaelisa, Grallert, Harald, Grarup, Niels, Guo, Xiuqing, Haesser, Jeffrey, Hansen, Torben, Harris, Tamara B, Highland, Heather M, Hong, Jaeyoung, Ikram, M Arfan, Ingelsson, Erik, Jackson, Rebecca, Jousilahti, Pekka, Kähönen, Mika, Kizer, Jorge R, Kovacs, Peter, Kriebel, Jennifer, Laakso, Markku, Lange, Leslie A, Lehtimäki, Terho, Li, Jin, Li-Gao, Ruifang, Lind, Lars, Luan, Jian'an, Lyytikäinen, Leo-Pekka, MacGregor, Stuart, Mackey, David A, Mahajan, Anubha, Mangino, Massimo, Männistö, Satu, McCarthy, Mark I, McKnight, Barbara, Medina-Gomez, Carolina, Meigs, James B, Molnos, Sophie, Mook-Kanamori, Dennis, Morris, Andrew P, de Mutsert, Renee, Nalls, Mike A, Nedeljkovic, Ivana, North, Kari E, Pennell, Craig E, Pradhan, Aruna D, Province, Michael A, Raitakari, Olli T, Raulerson, Chelsea K, Reiner, Alex P, Ridker, Paul M, Ripatti, Samuli, Roberston, Neil, Rotter, Jerome I, Salomaa, Veikko, Sandoval-Zárate, America A, Sitlani, Colleen M, Spector, Tim D, Strauch, Konstantin, Stumvoll, Michael, Taylor, Kent D, Thuesen, Betina, Tönjes, Anke, Uitterlinden, Andre G, Venturini, Cristina, Walker, Mark, Wang, Carol A, Wang, Shuai, Wareham, Nicholas J, Willems, Sara M, Willems van Dijk, Ko, Wilson, James G, Wu, Ying, Yao, Jie, Young, Kristin L, Langenberg, Claudia, and Frayling, Timothy M
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Epidemiology ,Biological Sciences ,Health Sciences ,Genetics ,Human Genome ,Nutrition ,Obesity ,2.1 Biological and endogenous factors ,Aetiology ,Metabolic and endocrine ,Cardiovascular ,Adiponectin ,Adipose Tissue ,Adolescent ,Adult ,Black or African American ,Aged ,Aged ,80 and over ,Exome ,Female ,Genetic Predisposition to Disease ,Hispanic or Latino ,Humans ,Lipids ,Male ,Middle Aged ,Phenotype ,Polymorphism ,Single Nucleotide ,Quantitative Trait Loci ,White People ,Young Adult ,adiponectin ,cardio metabolic traits ,exome ,genetics ,genome-wide association study ,lipids ,obesity ,Medical and Health Sciences ,Genetics & Heredity ,Biological sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10-7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r2 > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10-4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.
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- 2019
38. An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis
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Liu, Jun, Carnero-Montoro, Elena, van Dongen, Jenny, Lent, Samantha, Nedeljkovic, Ivana, Ligthart, Symen, Tsai, Pei-Chien, Martin, Tiphaine C, Mandaviya, Pooja R, Jansen, Rick, Peters, Marjolein J, Duijts, Liesbeth, Jaddoe, Vincent WV, Tiemeier, Henning, Felix, Janine F, Willemsen, Gonneke, de Geus, Eco JC, Chu, Audrey Y, Levy, Daniel, Hwang, Shih-Jen, Bressler, Jan, Gondalia, Rahul, Salfati, Elias L, Herder, Christian, Hidalgo, Bertha A, Tanaka, Toshiko, Moore, Ann Zenobia, Lemaitre, Rozenn N, Jhun, Min A, Smith, Jennifer A, Sotoodehnia, Nona, Bandinelli, Stefania, Ferrucci, Luigi, Arnett, Donna K, Grallert, Harald, Assimes, Themistocles L, Hou, Lifang, Baccarelli, Andrea, Whitsel, Eric A, van Dijk, Ko Willems, Amin, Najaf, Uitterlinden, André G, Sijbrands, Eric JG, Franco, Oscar H, Dehghan, Abbas, Spector, Tim D, Dupuis, Josée, Hivert, Marie-France, Rotter, Jerome I, Meigs, James B, Pankow, James S, van Meurs, Joyce BJ, Isaacs, Aaron, Boomsma, Dorret I, Bell, Jordana T, Demirkan, Ayşe, and van Duijn, Cornelia M
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Biological Sciences ,Genetics ,Nutrition ,Diabetes ,Human Genome ,Obesity ,2.1 Biological and endogenous factors ,Aetiology ,Metabolic and endocrine ,Adult ,Aged ,Aged ,80 and over ,Computer Simulation ,CpG Islands ,DNA Methylation ,Diabetes Mellitus ,Type 2 ,Epigenesis ,Genetic ,Epigenomics ,Female ,Gene Expression Profiling ,Gene Expression Regulation ,Genome-Wide Association Study ,Glucose ,Homeostasis ,Humans ,Insulin ,Male ,Metabolic Networks and Pathways ,Middle Aged ,Polymorphism ,Single Nucleotide ,Young Adult - Abstract
Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.
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- 2019
39. Altered bile acid profile associates with cognitive impairment in Alzheimer's disease—An emerging role for gut microbiome
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MahmoudianDehkordi, Siamak, Arnold, Matthias, Nho, Kwangsik, Ahmad, Shahzad, Jia, Wei, Xie, Guoxiang, Louie, Gregory, Kueider‐Paisley, Alexandra, Moseley, M Arthur, Thompson, J Will, St John Williams, Lisa, Tenenbaum, Jessica D, Blach, Colette, Baillie, Rebecca, Han, Xianlin, Bhattacharyya, Sudeepa, Toledo, Jon B, Schafferer, Simon, Klein, Sebastian, Koal, Therese, Risacher, Shannon L, Kling, Mitchel Allan, Motsinger‐Reif, Alison, Rotroff, Daniel M, Jack, John, Hankemeier, Thomas, Bennett, David A, De Jager, Philip L, Trojanowski, John Q, Shaw, Leslie M, Weiner, Michael W, Doraiswamy, P Murali, van Duijn, Cornelia M, Saykin, Andrew J, Kastenmüller, Gabi, Kaddurah‐Daouk, Rima, and Consortium, for the Alzheimer's Disease Neuroimaging Initiative and the Alzheimer Disease Metabolomics
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Biological Psychology ,Psychology ,Alzheimer's Disease ,Dementia ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurodegenerative ,Genetics ,Brain Disorders ,Acquired Cognitive Impairment ,Liver Disease ,Behavioral and Social Science ,Digestive Diseases ,Neurosciences ,Aging ,Microbiome ,2.1 Biological and endogenous factors ,4.1 Discovery and preclinical testing of markers and technologies ,Neurological ,Aged ,Alzheimer Disease ,Bile Acids and Salts ,Cognitive Dysfunction ,Dysbiosis ,Female ,Gastrointestinal Microbiome ,Humans ,Liver ,Male ,Metabolome ,Metabolomics ,Lipidomics ,Alzheimer's disease ,Gut microbiome ,Gut-liver-brain axis ,Atlas for Alzheimer ,Genetic variants ,Immunity ,Inflammation ,Alzheimer's Disease Neuroimaging Initiative and the Alzheimer Disease Metabolomics Consortium ,Clinical Sciences ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionIncreasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut-brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD).MethodsSerum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for confounders and multiple testing.ResultsIn AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response-related genes implicated in AD showed associations with BA profiles.DiscussionWe report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut-liver-brain axis in the pathogenesis of AD.
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- 2019
40. A meta-analysis of genome-wide association studies identifies multiple longevity genes
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Deelen, Joris, Evans, Daniel S, Arking, Dan E, Tesi, Niccolò, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K, Biggs, Mary L, van der Spek, Ashley, Atzmon, Gil, Ware, Erin B, Sarnowski, Chloé, Smith, Albert V, Seppälä, Ilkka, Cordell, Heather J, Dose, Janina, Amin, Najaf, Arnold, Alice M, Ayers, Kristin L, Barzilai, Nir, Becker, Elizabeth J, Beekman, Marian, Blanché, Hélène, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C, Cubaynes, Sarah, Cummings, Steven R, Davies, Karen, Debrabant, Birgit, Deleuze, Jean-François, Duncan, Rachel, Faul, Jessica D, Franceschi, Claudio, Galan, Pilar, Gudnason, Vilmundur, Harris, Tamara B, Huisman, Martijn, Hurme, Mikko A, Jagger, Carol, Jansen, Iris, Jylhä, Marja, Kähönen, Mika, Karasik, David, Kardia, Sharon LR, Kingston, Andrew, Kirkwood, Thomas BL, Launer, Lenore J, Lehtimäki, Terho, Lieb, Wolfgang, Lyytikäinen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebel, Almut, Newman, Anne B, Nie, Chao, Nohr, Ellen A, Orwoll, Eric S, Perls, Thomas T, Province, Michael A, Psaty, Bruce M, Raitakari, Olli T, Reinders, Marcel JT, Robine, Jean-Marie, Rotter, Jerome I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild IA, Taylor, Kent D, Uitterlinden, André G, van der Flier, Wiesje, van der Lee, Sven J, van Duijn, Cornelia M, van Heemst, Diana, Vaupel, James W, Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P, Lunetta, Kathryn L, Slagboom, P Eline, and Murabito, Joanne M
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Epidemiology ,Biological Sciences ,Health Sciences ,Genetics ,Aging ,Human Genome ,Apolipoprotein E2 ,Apolipoprotein E4 ,Endoplasmic Reticulum Chaperone BiP ,Genome-Wide Association Study ,Heat-Shock Proteins ,Humans ,Longevity - Abstract
Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.
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- 2019
41. Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6
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Prins, Bram P, Mead, Timothy J, Brody, Jennifer A, Sveinbjornsson, Gardar, Ntalla, Ioanna, Bihlmeyer, Nathan A, van den Berg, Marten, Bork-Jensen, Jette, Cappellani, Stefania, Van Duijvenboden, Stefan, Klena, Nikolai T, Gabriel, George C, Liu, Xiaoqin, Gulec, Cagri, Grarup, Niels, Haessler, Jeffrey, Hall, Leanne M, Iorio, Annamaria, Isaacs, Aaron, Li-Gao, Ruifang, Lin, Honghuang, Liu, Ching-Ti, Lyytikäinen, Leo-Pekka, Marten, Jonathan, Mei, Hao, Müller-Nurasyid, Martina, Orini, Michele, Padmanabhan, Sandosh, Radmanesh, Farid, Ramirez, Julia, Robino, Antonietta, Schwartz, Molly, van Setten, Jessica, Smith, Albert V, Verweij, Niek, Warren, Helen R, Weiss, Stefan, Alonso, Alvaro, Arnar, David O, Bots, Michiel L, de Boer, Rudolf A, Dominiczak, Anna F, Eijgelsheim, Mark, Ellinor, Patrick T, Guo, Xiuqing, Felix, Stephan B, Harris, Tamara B, Hayward, Caroline, Heckbert, Susan R, Huang, Paul L, Jukema, JW, Kähönen, Mika, Kors, Jan A, Lambiase, Pier D, Launer, Lenore J, Li, Man, Linneberg, Allan, Nelson, Christopher P, Pedersen, Oluf, Perez, Marco, Peters, Annette, Polasek, Ozren, Psaty, Bruce M, Raitakari, Olli T, Rice, Kenneth M, Rotter, Jerome I, Sinner, Moritz F, Soliman, Elsayed Z, Spector, Tim D, Strauch, Konstantin, Thorsteinsdottir, Unnur, Tinker, Andrew, Trompet, Stella, Uitterlinden, André, Vaartjes, Ilonca, van der Meer, Peter, Völker, Uwe, Völzke, Henry, Waldenberger, Melanie, Wilson, James G, Xie, Zhijun, Asselbergs, Folkert W, Dörr, Marcus, van Duijn, Cornelia M, Gasparini, Paolo, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Hansen, Torben, Kääb, Stefan, Kanters, Jørgen K, Kooperberg, Charles, Lehtimäki, Terho, Lin, Henry J, Lubitz, Steven A, Mook-Kanamori, Dennis O, Conti, Francesco J, Newton-Cheh, Christopher H, Rosand, Jonathan, Rudan, Igor, and Samani, Nilesh J
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Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Cardiovascular ,Human Genome ,Heart Disease ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,ADAMTS Proteins ,Animals ,Black People ,Connexin 43 ,Electrocardiography ,Exome ,Female ,Gene Expression ,Gene Expression Profiling ,Genetic Loci ,Genome-Wide Association Study ,Heart Conduction System ,Humans ,Male ,Mice ,Middle Aged ,Myocardium ,Open Reading Frames ,Polymorphism ,Single Nucleotide ,White People ,Exome Sequencing ,Exome chip ,Conduction ,ADAMTS6 ,Meta-analysis ,Environmental Sciences ,Information and Computing Sciences ,Bioinformatics - Abstract
BackgroundGenome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear.ResultsHere, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction.ConclusionsOur approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.
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- 2018
42. Genome-wide association study of primary open-angle glaucoma in continental and admixed African populations.
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Bonnemaijer, Pieter WM, Iglesias, Adriana I, Nadkarni, Girish N, Sanyiwa, Anna J, Hassan, Hassan G, Cook, Colin, GIGA Study Group, Simcoe, Mark, Taylor, Kent D, Schurmann, Claudia, Belbin, Gillian M, Kenny, Eimear E, Bottinger, Erwin P, van de Laar, Suzanne, Wiliams, Susan EI, Akafo, Stephen K, Ashaye, Adeyinka O, Zangwill, Linda M, Girkin, Christopher A, Ng, Maggie CY, Rotter, Jerome I, Weinreb, Robert N, Li, Zheng, Allingham, R Rand, Eyes of Africa Genetics Consortium, Nag, Abhishek, Hysi, Pirro G, Meester-Smoor, Magda A, Wiggs, Janey L, NEIGHBORHOOD Consortium, Hauser, Michael A, Hammond, Christopher J, Lemij, Hans G, Loos, Ruth JF, van Duijn, Cornelia M, Thiadens, Alberta AHJ, and Klaver, Caroline CW
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GIGA Study Group ,Eyes of Africa Genetics Consortium ,NEIGHBORHOOD Consortium ,Humans ,Glaucoma ,Open-Angle ,Vesicular Transport Proteins ,Aged ,Aged ,80 and over ,Middle Aged ,African Continental Ancestry Group ,Female ,Male ,Thioredoxin Reductase 2 ,Genome-Wide Association Study ,Genetic Loci ,Neurodegenerative ,Human Genome ,Aging ,Eye Disease and Disorders of Vision ,Genetics ,Neurosciences ,2.1 Biological and endogenous factors ,Genetics & Heredity ,Complementary and Alternative Medicine ,Paediatrics and Reproductive Medicine - Abstract
Primary open angle glaucoma (POAG) is a complex disease with a major genetic contribution. Its prevalence varies greatly among ethnic groups, and is up to five times more frequent in black African populations compared to Europeans. So far, worldwide efforts to elucidate the genetic complexity of POAG in African populations has been limited. We conducted a genome-wide association study in 1113 POAG cases and 1826 controls from Tanzanian, South African and African American study samples. Apart from confirming evidence of association at TXNRD2 (rs16984299; OR[T] 1.20; P = 0.003), we found that a genetic risk score combining the effects of the 15 previously reported POAG loci was significantly associated with POAG in our samples (OR 1.56; 95% CI 1.26-1.93; P = 4.79 × 10-5). By genome-wide association testing we identified a novel candidate locus, rs141186647, harboring EXOC4 (OR[A] 0.48; P = 3.75 × 10-8), a gene transcribing a component of the exocyst complex involved in vesicle transport. The low frequency and high degree of genetic heterogeneity at this region hampered validation of this finding in predominantly West-African replication sets. Our results suggest that established genetic risk factors play a role in African POAG, however, they do not explain the higher disease load. The high heterogeneity within Africans remains a challenge to identify the genetic commonalities for POAG in this ethnicity, and demands studies of extremely large size.
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- 2018
43. Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume.
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Vojinovic, Dina, Adams, Hieab H, Jian, Xueqiu, Yang, Qiong, Smith, Albert Vernon, Bis, Joshua C, Teumer, Alexander, Scholz, Markus, Armstrong, Nicola J, Hofer, Edith, Saba, Yasaman, Luciano, Michelle, Bernard, Manon, Trompet, Stella, Yang, Jingyun, Gillespie, Nathan A, van der Lee, Sven J, Neumann, Alexander, Ahmad, Shahzad, Andreassen, Ole A, Ames, David, Amin, Najaf, Arfanakis, Konstantinos, Bastin, Mark E, Becker, Diane M, Beiser, Alexa S, Beyer, Frauke, Brodaty, Henry, Bryan, R Nick, Bülow, Robin, Dale, Anders M, De Jager, Philip L, Deary, Ian J, DeCarli, Charles, Fleischman, Debra A, Gottesman, Rebecca F, van der Grond, Jeroen, Gudnason, Vilmundur, Harris, Tamara B, Homuth, Georg, Knopman, David S, Kwok, John B, Lewis, Cora E, Li, Shuo, Loeffler, Markus, Lopez, Oscar L, Maillard, Pauline, El Marroun, Hanan, Mather, Karen A, Mosley, Thomas H, Muetzel, Ryan L, Nauck, Matthias, Nyquist, Paul A, Panizzon, Matthew S, Pausova, Zdenka, Psaty, Bruce M, Rice, Ken, Rotter, Jerome I, Royle, Natalie, Satizabal, Claudia L, Schmidt, Reinhold, Schofield, Peter R, Schreiner, Pamela J, Sidney, Stephen, Stott, David J, Thalamuthu, Anbupalam, Uitterlinden, Andre G, Valdés Hernández, Maria C, Vernooij, Meike W, Wen, Wei, White, Tonya, Witte, A Veronica, Wittfeld, Katharina, Wright, Margaret J, Yanek, Lisa R, Tiemeier, Henning, Kremen, William S, Bennett, David A, Jukema, J Wouter, Paus, Tomas, Wardlaw, Joanna M, Schmidt, Helena, Sachdev, Perminder S, Villringer, Arno, Grabe, Hans Jörgen, Longstreth, WT, van Duijn, Cornelia M, Launer, Lenore J, Seshadri, Sudha, Ikram, M Arfan, and Fornage, Myriam
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Lateral Ventricles ,Humans ,Organ Size ,Genome ,Human ,Aged ,Middle Aged ,Genome-Wide Association Study ,Human Genome ,Aging ,Genetics ,2.1 Biological and endogenous factors ,Neurological - Abstract
The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρgenetic = -0.59, p-value = 3.14 × 10-6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.
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- 2018
44. Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging
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Jian, Xueqiu, Satizabal, Claudia L, Smith, Albert V, Wittfeld, Katharina, Bis, Joshua C, Smith, Jennifer A, Hsu, Fang-Chi, Nho, Kwangsik, Hofer, Edith, Hagenaars, Saskia P, Nyquist, Paul A, Mishra, Aniket, Adams, Hieab HH, Li, Shuo, Teumer, Alexander, Zhao, Wei, Freedman, Barry I, Saba, Yasaman, Yanek, Lisa R, Chauhan, Ganesh, van Buchem, Mark A, Cushman, Mary, Royle, Natalie A, Bryan, R Nick, Niessen, Wiro J, Windham, Beverly G, DeStefano, Anita L, Habes, Mohamad, Heckbert, Susan R, Palmer, Nicholette D, Lewis, Cora E, Eiriksdottir, Gudny, Maillard, Pauline, Mathias, Rasika A, Homuth, Georg, Valdés-Hernández, Maria del C, Divers, Jasmin, Beiser, Alexa S, Langner, Sönke, Rice, Kenneth M, Bastin, Mark E, Yang, Qiong, Maldjian, Joseph A, Starr, John M, Sidney, Stephen, Risacher, Shannon L, Uitterlinden, André G, Gudnason, Vilmundur G, Nauck, Matthias, Rotter, Jerome I, Schreiner, Pamela J, Boerwinkle, Eric, van Duijn, Cornelia M, Mazoyer, Bernard, von Sarnowski, Bettina, Gottesman, Rebecca F, Levy, Daniel, Sigurdsson, Sigurdur, Vernooij, Meike W, Turner, Stephen T, Schmidt, Reinhold, Wardlaw, Joanna M, Psaty, Bruce M, Mosley, Thomas H, DeCarli, Charles S, Saykin, Andrew J, Bowden, Donald W, Becker, Diane M, Deary, Ian J, Schmidt, Helena, Kardia, Sharon LR, Ikram, M Arfan, Debette, Stéphanie, Grabe, Hans J, Longstreth, WT, Seshadri, Sudha, Launer, Lenore J, and Fornage, Myriam
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Epidemiology ,Health Sciences ,Human Genome ,Dementia ,Alzheimer's Disease Related Dementias (ADRD) ,Neurodegenerative ,Minority Health ,Cerebrovascular ,Stroke ,Brain Disorders ,Genetics ,Biotechnology ,Neurosciences ,Clinical Research ,Acquired Cognitive Impairment ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Aging ,2.1 Biological and endogenous factors ,Neurological ,Brain ,Cohort Studies ,Exome ,Genetic Variation ,Humans ,Magnetic Resonance Imaging ,Mitochondrial Proteins ,White Matter ,cerebral small vessel disease ,exome ,magnetic resonance imaging ,meta-analysis ,white matter ,neuroCHARGE Working Group ,Cardiorespiratory Medicine and Haematology ,Clinical Sciences ,Neurology & Neurosurgery ,Clinical sciences ,Allied health and rehabilitation science - Abstract
Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P
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- 2018
45. Pharmacogenomics study of thiazide diuretics and QT interval in multi-ethnic populations: the cohorts for heart and aging research in genomic epidemiology
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Seyerle, AA, Sitlani, CM, Noordam, R, Gogarten, SM, Li, J, Li, X, Evans, DS, Sun, F, Laaksonen, MA, Isaacs, A, Kristiansson, K, Highland, HM, Stewart, JD, Harris, TB, Trompet, S, Bis, JC, Peloso, GM, Brody, JA, Broer, L, Busch, EL, Duan, Q, Stilp, AM, O'Donnell, CJ, Macfarlane, PW, Floyd, JS, Kors, JA, Lin, HJ, Li-Gao, R, Sofer, T, Méndez-Giráldez, R, Cummings, SR, Heckbert, SR, Hofman, A, Ford, I, Li, Y, Launer, LJ, Porthan, K, Newton-Cheh, C, Napier, MD, Kerr, KF, Reiner, AP, Rice, KM, Roach, J, Buckley, BM, Soliman, EZ, de Mutsert, R, Sotoodehnia, N, Uitterlinden, AG, North, KE, Lee, CR, Gudnason, V, Stürmer, T, Rosendaal, FR, Taylor, KD, Wiggins, KL, Wilson, JG, Chen, Y-DI, Kaplan, RC, Wilhelmsen, K, Cupples, LA, Salomaa, V, van Duijn, C, Jukema, JW, Liu, Y, Mook-Kanamori, DO, Lange, LA, Vasan, RS, Smith, AV, Stricker, BH, Laurie, CC, Rotter, JI, Whitsel, EA, Psaty, BM, and Avery, CL
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Pharmacology and Pharmaceutical Sciences ,Biomedical and Clinical Sciences ,Cardiovascular ,Human Genome ,Aging ,Minority Health ,Genetics ,Health Disparities ,Adult ,Aged ,Aged ,80 and over ,Cohort Studies ,Electrocardiography ,Ethnicity ,Female ,Genomics ,Heart Rate ,Humans ,Longitudinal Studies ,Male ,Middle Aged ,Pharmacogenetics ,Polymorphism ,Single Nucleotide ,Sodium Chloride Symporter Inhibitors ,Pharmacology & Pharmacy ,Pharmacology and pharmaceutical sciences - Abstract
Thiazide diuretics, commonly used antihypertensives, may cause QT interval (QT) prolongation, a risk factor for highly fatal and difficult to predict ventricular arrhythmias. We examined whether common single-nucleotide polymorphisms (SNPs) modified the association between thiazide use and QT or its component parts (QRS interval, JT interval) by performing ancestry-specific, trans-ethnic and cross-phenotype genome-wide analyses of European (66%), African American (15%) and Hispanic (19%) populations (N=78 199), leveraging longitudinal data, incorporating corrected standard errors to account for underestimation of interaction estimate variances and evaluating evidence for pathway enrichment. Although no loci achieved genome-wide significance (P
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- 2018
46. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
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Kanoni, Stavroula, Graham, Sarah E., Wang, Yuxuan, Surakka, Ida, Ramdas, Shweta, Zhu, Xiang, Clarke, Shoa L., Bhatti, Konain Fatima, Vedantam, Sailaja, Winkler, Thomas W., Locke, Adam E., Marouli, Eirini, Zajac, Greg J. M., Wu, Kuan-Han H., Ntalla, Ioanna, Hui, Qin, Klarin, Derek, Hilliard, Austin T., Wang, Zeyuan, Xue, Chao, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F., Holm, Hilma, Olafsson, Isleifur, Hwang, Mi Yeong, Han, Sohee, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M., Rasheed, Humaira, Havulinna, Aki S., Veturi, Yogasudha, Pacheco, Jennifer Allen, Rosenthal, Elisabeth A., Lingren, Todd, Feng, QiPing, Kullo, Iftikhar J., Narita, Akira, Takayama, Jun, Martin, Hilary C., Hunt, Karen A., Trivedi, Bhavi, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E., Campbell, Archie, Lin, Kuang, Millwood, Iona Y., Rasheed, Asif, Hindy, George, Faul, Jessica D., Zhao, Wei, Weir, David R., Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Choudhury, Ananyo, Sengupta, Dhriti, Mahajan, Anubha, Brown, Michael R., Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M., Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Wood, Andrew R., Ji, Yingji, Gao, Zishan, Haworth, Simon, Yousri, Noha A., Mitchell, Ruth E., Chai, Jin Fang, Aadahl, Mette, Bjerregaard, Anne A., Yao, Jie, Manichaikul, Ani, Hwu, Chii-Min, Hung, Yi-Jen, Warren, Helen R., Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L., Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Mauro, Pala, Matteo, Floris, McDaid, Aaron F., Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, Sattar, Naveed, Møllehave, Line T., Munz, Matthias, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Lamina, Claudia, Forer, Lukas, Scholz, Markus, Galesloot, Tessel E., Bradfield, Jonathan P., Ruotsalainen, Sanni E., Daw, EWarwick, Zmuda, Joseph M., Mitchell, Jonathan S., Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A., Vazquez-Moreno, Miguel, Feitosa, Mary F., Wojczynski, Mary K., Wang, Zhe, Preuss, Michael H., Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W., Engmann, Jorgen, Tsao, Noah L., Verma, Anurag, Slieker, Roderick C., Lo, Ken Sin, Zilhao, Nuno R., Le, Phuong, Kleber, Marcus E., Delgado, Graciela E., Huo, Shaofeng, Ikeda, Daisuke D., Iha, Hiroyuki, Yang, Jian, Liu, Jun, Demirkan, Ayşe, Leonard, Hampton L., Marten, Jonathan, Frank, Mirjam, Schmidt, Börge, Smyth, Laura J., Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlos, Lyssenko, Valeriya, Nongmaithem, Suraj S., Bayyana, Swati, Stringham, Heather M., Irvin, Marguerite R., Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul R. H. J., Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A., Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N., Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C., Wang, Ya Xing, Wei, Wen B., Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A., Banas, Bernhard, Nardone, Giuseppe Giovanni, Meidtner, Karina, Bielak, Lawrence F., Smith, Jennifer A., Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J., Pitkänen, Niina, Cade, Brian E., van der Laan, Sander W., Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Bentley, Amy R., Doumatey, Ayo P., Adeyemo, Adebowale A., Lee, Jong Young, Petersen, Eva R. B., Nielsen, Aneta A., Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W., Wang, Carol A., Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hidalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O., van Setten, Jessica, Li, Xiaoyin, Liang, Jingjing, Tang, Hua, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D., Reiner, Alexander P., Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C., Launer, Lenore J., Li, Huaixing, Nalls, Mike A., Raitakari, Olli T., Ichihara, Sahoko, Wild, Sarah H., Nelson, Christopher P., Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S., Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, de Kleijn, Dominique, de Borst, Gert J., Kim, Eung Kweon, Adams, Hieab H. H., Ikram, M. Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W., Kraaijeveld, Adriaan O., Beulens, Joline W. J., Shu, Xiao-Ou, Rallidis, Loukianos S., Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W., Kähönen, Mika, Pérusse, Louis, Bouchard, Claude, Tönjes, Anke, Chen, Yii-Der Ida, Pennell, Craig E., Mori, Trevor A., Lieb, Wolfgang, Franke, Andre, Ohlsson, Claes, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M., Stark, Klaus J., Zimmermann, Martina E., Völzke, Henry, Homuth, Georg, Evans, Michele K., Zonderman, Alan B., Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E., Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J., Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Kardia, Sharon L. R., Peyser, Patricia A., Kato, Norihiro, Schulze, Matthias B., Girotto, Giorgia, Böger, Carsten A., Jung, Bettina, Joshi, Peter K., Bennett, David A., De Jager, Philip L., Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morris, Caulfield, Mark J., Munroe, Patricia B., Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B., Samani, Nilesh J., Kaprio, Jaakko, Pajukanta, Päivi, Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A., Adair, Linda S., Bechayda, Sonny Augustin, de Silva, H. Janaka, Wickremasinghe, Ananda R., Krauss, Ronald M., Wu, Jer-Yuarn, Zheng, Wei, Hollander, Anneke Iden, Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G., Lind, Lars, Heng, Chew-Kiat, Nelson, Amanda E., Golightly, Yvonne M., Wilson, James F., Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J., Rao, D. C., Arnett, Donna K., Hunt, Steven C., Walker, Mark, Koistinen, Heikki A., Chandak, Giriraj R., Mercader, Josep M., Costanzo, Maria C., Jang, Dongkeun, Burtt, Noël P., Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, EShyong, van Dam, Rob M., Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F., McKnight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, McCarthy, Mark I., Palmer, Colin N. A., Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M., Jin, Zi-Bing, Qu, Jia, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, Hart, Leen M.‘t, Elders, Petra J. M., Damrauer, Scott M., Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D., Loos, Ruth J. F., Province, Michael A., Parra, Esteban J., Cruz, Miguel, Psaty, Bruce M., Brandslund, Ivan, Pramstaller, Peter P., Rotimi, Charles N., Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F. A., Kiemeney, Lambertus A. L. M., de Graaf, Jacqueline, Loeffler, Markus, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W., Linneberg, Allan, Jukema, J. Wouter, Khera, Amit V., Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Francesco, Cucca, Mook-Kanamori, Dennis O., van Dijk, Ko Willems, Watkins, Hugh, Strachan, David P., Grarup, Niels, Sever, Peter, Poulter, Neil, Chuang, Lee-Ming, Rotter, Jerome I., Dantoft, Thomas M., Karpe, Fredrik, Neville, Matt J., Timpson, Nicholas J., Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Li, Hengtong, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T., Pedersen, Nancy L., Magnusson, Patrik K. E., Boomsma, Dorret I., Willemsen, Allegonda H. M., Cupples, LAdrienne, van Meurs, Joyce B. J., Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J., Langenberg, Claudia, Zeggini, Eleftheria, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C., Kooner, Jaspal S., de Vries, Paul S., Morrison, Alanna C., Hazelhurst, Scott, Ramsay, Michèle, North, Kari E., Daviglus, Martha, Kraft, Peter, Martin, Nicholas G., Whitfield, John B., Abbas, Shahid, Saleheen, Danish, Walters, Robin G., Holmes, Michael V., Black, Corri, Smith, Blair H., Baras, Aris, Justice, Anne E., Buring, Julie E., Ridker, Paul M., Chasman, Daniel I., Kooperberg, Charles, Tamiya, Gen, Yamamoto, Masayuki, van Heel, David A., Trembath, Richard C., Wei, Wei-Qi, Jarvik, Gail P., Namjou, Bahram, Hayes, M. Geoffrey, Ritchie, Marylyn D., Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Kim, Bong-Jo, Thorsteinsdottir, Unnur, Stefansson, Kari, Zhang, Jifeng, Chen, YEugene, Ho, Yuk-Lam, Lynch, Julie A., Rader, Daniel J., Tsao, Philip S., Chang, Kyong-Mi, Cho, Kelly, O’Donnell, Christopher J., Gaziano, John M., Wilson, Peter W. F., Frayling, Timothy M., Hirschhorn, Joel N., Kathiresan, Sekar, Mohlke, Karen L., Sun, Yan V., Morris, Andrew P., Boehnke, Michael, Brown, Christopher D., Natarajan, Pradeep, Deloukas, Panos, Willer, Cristen J., Assimes, Themistocles L., and Peloso, Gina M.
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- 2022
- Full Text
- View/download PDF
47. ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals
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Bihlmeyer, Nathan A, Brody, Jennifer A, Smith, Albert Vernon, Warren, Helen R, Lin, Honghuang, Isaacs, Aaron, Liu, Ching-Ti, Marten, Jonathan, Radmanesh, Farid, Hall, Leanne M, Grarup, Niels, Mei, Hao, Müller-Nurasyid, Martina, Huffman, Jennifer E, Verweij, Niek, Guo, Xiuqing, Yao, Jie, Li-Gao, Ruifang, van den Berg, Marten, Weiss, Stefan, Prins, Bram P, van Setten, Jessica, Haessler, Jeffrey, Lyytikäinen, Leo-Pekka, Li, Man, Alonso, Alvaro, Soliman, Elsayed Z, Bis, Joshua C, Austin, Tom, Chen, Yii-Der Ida, Psaty, Bruce M, Harrris, Tamara B, Launer, Lenore J, Padmanabhan, Sandosh, Dominiczak, Anna, Huang, Paul L, Xie, Zhijun, Ellinor, Patrick T, Kors, Jan A, Campbell, Archie, Murray, Alison D, Nelson, Christopher P, Tobin, Martin D, Bork-Jensen, Jette, Hansen, Torben, Pedersen, Oluf, Linneberg, Allan, Sinner, Moritz F, Peters, Annette, Waldenberger, Melanie, Meitinger, Thomas, Perz, Siegfried, Kolcic, Ivana, Rudan, Igor, de Boer, Rudolf A, van der Meer, Peter, Lin, Henry J, Taylor, Kent D, de Mutsert, Renée, Trompet, Stella, Jukema, J Wouter, Maan, Arie C, Stricker, Bruno HC, Rivadeneira, Fernando, Uitterlinden, André, Völker, Uwe, Homuth, Georg, Völzke, Henry, Felix, Stephan B, Mangino, Massimo, Spector, Timothy D, Bots, Michiel L, Perez, Marco, Raitakari, Olli T, Kähönen, Mika, Mononen, Nina, Gudnason, Vilmundur, Munroe, Patricia B, Lubitz, Steven A, van Duijn, Cornelia M, Newton-Cheh, Christopher H, Hayward, Caroline, Rosand, Jonathan, Samani, Nilesh J, Kanters, Jørgen K, Wilson, James G, Kääb, Stefan, Polasek, Ozren, van der Harst, Pim, Heckbert, Susan R, Rotter, Jerome I, Mook-Kanamori, Dennis O, Eijgelsheim, Mark, Dörr, Marcus, Jamshidi, Yalda, Asselbergs, Folkert W, Kooperberg, Charles, Lehtimäki, Terho, Arking, Dan E, and Sotoodehnia, Nona
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Genetics ,Prevention ,Heart Disease ,Cardiovascular ,1.1 Normal biological development and functioning ,Antiporters ,DNA-Binding Proteins ,Electrocardiography ,Exome ,Genome-Wide Association Study ,Humans ,Long QT Syndrome ,Oligonucleotide Array Sequence Analysis ,Polymorphism ,Single Nucleotide ,Quantitative Trait Loci ,Receptors ,Calcium-Sensing ,Transcription Factors ,arrhythmias ,cardiac ,death ,sudden ,cardiac ,genetics ,genome ,humans ,Medical Biotechnology ,Cardiorespiratory Medicine and Haematology ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology - Abstract
BackgroundQT interval, measured through a standard ECG, captures the time it takes for the cardiac ventricles to depolarize and repolarize. JT interval is the component of the QT interval that reflects ventricular repolarization alone. Prolonged QT interval has been linked to higher risk of sudden cardiac arrest.Methods and resultsWe performed an ExomeChip-wide analysis for both QT and JT intervals, including 209 449 variants, both common and rare, in 17 341 genes from the Illumina Infinium HumanExome BeadChip. We identified 10 loci that modulate QT and JT interval duration that have not been previously reported in the literature using single-variant statistical models in a meta-analysis of 95 626 individuals from 23 cohorts (comprised 83 884 European ancestry individuals, 9610 blacks, 1382 Hispanics, and 750 Asians). This brings the total number of ventricular repolarization associated loci to 45. In addition, our approach of using coding variants has highlighted the role of 17 specific genes for involvement in ventricular repolarization, 7 of which are in novel loci.ConclusionsOur analyses show a role for myocyte internal structure and interconnections in modulating QT interval duration, adding to previous known roles of potassium, sodium, and calcium ion regulation, as well as autonomic control. We anticipate that these discoveries will open new paths to the goal of making novel remedies for the prevention of lethal ventricular arrhythmias and sudden cardiac arrest.
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- 2018
48. Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects
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Medina-Gomez, Carolina, Kemp, John P, Trajanoska, Katerina, Luan, Jian’an, Chesi, Alessandra, Ahluwalia, Tarunveer S, Mook-Kanamori, Dennis O, Ham, Annelies, Hartwig, Fernando P, Evans, Daniel S, Joro, Raimo, Nedeljkovic, Ivana, Zheng, Hou-Feng, Zhu, Kun, Atalay, Mustafa, Liu, Ching-Ti, Nethander, Maria, Broer, Linda, Porleifsson, Gudmar, Mullin, Benjamin H, Handelman, Samuel K, Nalls, Mike A, Jessen, Leon E, Heppe, Denise HM, Richards, J Brent, Wang, Carol, Chawes, Bo, Schraut, Katharina E, Amin, Najaf, Wareham, Nick, Karasik, David, Van der Velde, Nathalie, Ikram, M Arfan, Zemel, Babette S, Zhou, Yanhua, Carlsson, Christian J, Liu, Yongmei, McGuigan, Fiona E, Boer, Cindy G, Bønnelykke, Klaus, Ralston, Stuart H, Robbins, John A, Walsh, John P, Zillikens, M Carola, Langenberg, Claudia, Li-Gao, Ruifang, Williams, Frances MK, Harris, Tamara B, Akesson, Kristina, Jackson, Rebecca D, Sigurdsson, Gunnar, Heijer, Martin den, van der Eerden, Bram CJ, van de Peppel, Jeroen, Spector, Timothy D, Pennell, Craig, Horta, Bernardo L, Felix, Janine F, Zhao, Jing Hua, Wilson, Scott G, de Mutsert, Renée, Bisgaard, Hans, Styrkársdóttir, Unnur, Jaddoe, Vincent W, Orwoll, Eric, Lakka, Timo A, Scott, Robert, Grant, Struan FA, Lorentzon, Mattias, van Duijn, Cornelia M, Wilson, James F, Stefansson, Kari, Psaty, Bruce M, Kiel, Douglas P, Ohlsson, Claes, Ntzani, Evangelia, van Wijnen, Andre J, Forgetta, Vincenzo, Ghanbari, Mohsen, Logan, John G, Williams, Graham R, Bassett, JH Duncan, Croucher, Peter I, Evangelou, Evangelos, Uitterlinden, Andre G, Ackert-Bicknell, Cheryl L, Tobias, Jonathan H, Evans, David M, and Rivadeneira, Fernando
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Rare Diseases ,Aging ,Human Genome ,Osteoporosis ,Clinical Research ,Genetics ,Aetiology ,2.1 Biological and endogenous factors ,Musculoskeletal ,Good Health and Well Being ,Adolescent ,Age Factors ,Animals ,Bone Density ,Child ,Child ,Preschool ,Genetic Loci ,Genome-Wide Association Study ,Humans ,Infant ,Infant ,Newborn ,Mice ,Knockout ,Polymorphism ,Single Nucleotide ,Quantitative Trait ,Heritable ,Regression Analysis ,BMD ,CREB3L1 ,ESR1 ,GWASs ,RANKL ,age-dependent effects ,bone mineral density ,fracture ,genetic correlation ,genome-wide association studies ,meta-regression ,total-body DXA ,Biological Sciences ,Medical and Health Sciences ,Genetics & Heredity - Abstract
Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course.
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- 2018
49. Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases
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Iglesias, Adriana I, Mishra, Aniket, Vitart, Veronique, Bykhovskaya, Yelena, Höhn, René, Springelkamp, Henriët, Cuellar-Partida, Gabriel, Gharahkhani, Puya, Bailey, Jessica N Cooke, Willoughby, Colin E, Li, Xiaohui, Yazar, Seyhan, Nag, Abhishek, Khawaja, Anthony P, Polašek, Ozren, Siscovick, David, Mitchell, Paul, Tham, Yih Chung, Haines, Jonathan L, Kearns, Lisa S, Hayward, Caroline, Shi, Yuan, van Leeuwen, Elisabeth M, Taylor, Kent D, Blue Mountains Eye Study—GWAS group, Bonnemaijer, Pieter, Rotter, Jerome I, Martin, Nicholas G, Zeller, Tanja, Mills, Richard A, Souzeau, Emmanuelle, Staffieri, Sandra E, Jonas, Jost B, Schmidtmann, Irene, Boutin, Thibaud, Kang, Jae H, Lucas, Sionne EM, Wong, Tien Yin, Beutel, Manfred E, Wilson, James F, NEIGHBORHOOD Consortium, Wellcome Trust Case Control Consortium 2 (WTCCC2), Uitterlinden, André G, Vithana, Eranga N, Foster, Paul J, Hysi, Pirro G, Hewitt, Alex W, Khor, Chiea Chuen, Pasquale, Louis R, Montgomery, Grant W, Klaver, Caroline CW, Aung, Tin, Pfeiffer, Norbert, Mackey, David A, Hammond, Christopher J, Cheng, Ching-Yu, Craig, Jamie E, Rabinowitz, Yaron S, Wiggs, Janey L, Burdon, Kathryn P, van Duijn, Cornelia M, and MacGregor, Stuart
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Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Ophthalmology and Optometry ,Eye Disease and Disorders of Vision ,Human Genome ,Women's Health ,Aging ,Rare Diseases ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Eye ,ADAMTS Proteins ,Asian People ,Cornea ,Corneal Diseases ,Corneal Dystrophies ,Hereditary ,Decorin ,Ehlers-Danlos Syndrome ,Eye Diseases ,Hereditary ,Fibrillin-1 ,Gene Expression ,Genome ,Human ,Genome-Wide Association Study ,Glaucoma ,Open-Angle ,Humans ,Keratoconus ,Loeys-Dietz Syndrome ,Lumican ,Marfan Syndrome ,Mendelian Randomization Analysis ,Myopia ,Polymorphism ,Single Nucleotide ,Proteoglycans ,Quantitative Trait Loci ,Quantitative Trait ,Heritable ,Transforming Growth Factor beta2 ,White People ,Blue Mountains Eye Study—GWAS group ,NEIGHBORHOOD Consortium ,Wellcome Trust Case Control Consortium 2 - Abstract
Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r = -0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r = -0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation.
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- 2018
50. DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation
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Richard, Melissa A, Huan, Tianxiao, Ligthart, Symen, Gondalia, Rahul, Jhun, Min A, Brody, Jennifer A, Irvin, Marguerite R, Marioni, Riccardo, Shen, Jincheng, Tsai, Pei-Chien, Montasser, May E, Jia, Yucheng, Syme, Catriona, Salfati, Elias L, Boerwinkle, Eric, Guan, Weihua, Mosley, Thomas H, Bressler, Jan, Morrison, Alanna C, Liu, Chunyu, Mendelson, Michael M, Uitterlinden, André G, van Meurs, Joyce B, Consortium, BIOS, Heijmans, Bastiaan T, Hoen, Peter AC ’t, van Meurs, Joyce, Isaacs, Aaron, Jansen, Rick, Franke, Lude, Boomsma, Dorret I, Pool, René, van Dongen, Jenny, Hottenga, Jouke J, van Greevenbroek, Marleen MJ, Stehouwer, Coen DA, van der Kallen, Carla JH, Schalkwijk, Casper G, Wijmenga, Cisca, Zhernakova, Alexandra, Tigchelaar, Ettje F, Slagboom, P Eline, Beekman, Marian, Deelen, Joris, van Heemst, Diana, Veldink, Jan H, van den Berg, Leonard H, van Duijn, Cornelia M, Hofman, Albert, Jhamai, P Mila, Verbiest, Michael, Suchiman, H Eka D, Verkerk, Marijn, van der Breggen, Ruud, van Rooij, Jeroen, Lakenberg, Nico, Mei, Hailiang, van Iterson, Maarten, van Galen, Michiel, Bot, Jan, van ’t Hof, Peter, Deelen, Patrick, Nooren, Irene, Moed, Matthijs, Vermaat, Martijn, Zhernakova, Dasha V, Luijk, René, Bonder, Marc Jan, van Dijk, Freerk, Arindrarto, Wibowo, Kielbasa, Szymon M, Swertz, Morris A, van Zwet, Erik W, Franco, Oscar H, Zhang, Guosheng, Li, Yun, Stewart, James D, Bis, Joshua C, Psaty, Bruce M, Chen, Yii-Der Ida, Kardia, Sharon LR, Zhao, Wei, Turner, Stephen T, Absher, Devin, Aslibekyan, Stella, Starr, John M, McRae, Allan F, Hou, Lifang, Just, Allan C, Schwartz, Joel D, Vokonas, Pantel S, Menni, Cristina, Spector, Tim D, Shuldiner, Alan, Damcott, Coleen M, Rotter, Jerome I, Palmas, Walter, Liu, Yongmei, and Paus, Tomáš
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Epidemiology ,Biological Sciences ,Health Sciences ,Genetics ,Hypertension ,Human Genome ,2.1 Biological and endogenous factors ,Cardiovascular ,Aged ,Blood Pressure ,CpG Islands ,Cross-Sectional Studies ,DNA Methylation ,Epigenesis ,Genetic ,Genetic Variation ,Genome-Wide Association Study ,Humans ,Mendelian Randomization Analysis ,Middle Aged ,Nerve Tissue Proteins ,Quantitative Trait Loci ,Tetraspanins ,BIOS Consortium ,DNA methylation ,Mendelian randomization ,blood pressure ,epigenome-wide association study ,gene expression ,sequence variation ,Medical and Health Sciences ,Genetics & Heredity ,Biological sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p 30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.
- Published
- 2017
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