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bioRxiv preprint doi: https://doi.org/10.1101/2019.12.20.883801; this version posted December 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Genome-wide association meta-analysis for early age-related 2 macular degeneration highlights novel loci and insights for 3 advanced disease 4 5 Authors 6 Thomas W Winkler1*, Felix Grassmann2,3*, Caroline Brandl1,2,4, Christina Kiel2, Felix Günther1,5, 7 Tobias Strunz2, Lorraine Weidner1, Martina E Zimmermann1, Christina A. Korb6, Alicia 8 Poplawski7, Alexander K Schuster6, Martina Müller-Nurasyid8,9,10, Annette Peters11,12, 9 Franziska G Rauscher13,14, Tobias Elze13,15, Katrin Horn13,14, Markus Scholz13,14, Marisa 10 Cañadas-Garre16, Amy Jayne McKnight16, Nicola Quinn16, Ruth E Hogg16, Helmut Küchenhoff5, 11 Iris M Heid1§, Klaus J Stark1§ and Bernhard HF Weber2§ 12 Affiliations 13 1: Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany; 2: Institute of Human Genetics, 14 University of Regensburg, Regensburg, Germany; 3: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 15 Stockholm, Sweden; 4: Department of Ophthalmology, University Hospital Regensburg, Regensburg, Germany; 5: Statistical 16 Consulting Unit StaBLab, Department of Statistics, Ludwig-Maximilians-Universität Munich, Munich, Germany; 6: Department of 17 Ophthalmology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany; 7: Institute for Medical 18 Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, 19 Germany; 8: Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 20 Neuherberg, Germany; 9: Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) 21 Munich, Munich, Germany; 10: Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Germany; 11: German 22 Center for Diabetes Research (DZD), Neuherberg, Germany; 12: Institute of Epidemiology, Helmholtz Zentrum München 23 Research Center for Environmental Health, Neuherberg, Germany; 13: Leipzig Research Centre for Civilization Diseases (LIFE), 24 Leipzig University, Leipzig, Germany; 14: Institute for Medical Informatics, Statistics, and Epidemiology (IMISE), Leipzig 25 University, Leipzig, Germany; 15: Schepens Eye Research Institute, Harvard Medical School, Boston, MA, United States; 16: 26 Centre for Public Health, Queen's University of Belfast, UK 27 28 * These authors contributed equally 29 § These authors jointly supervised this work 30 31 Corresponding author: [email protected] 32 33 ABSTRACT 1 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.20.883801; this version posted December 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 34 Background: Advanced age-related macular degeneration (AMD) is a leading cause of 35 blindness. While around half of the genetic contribution to advanced AMD has been 36 uncovered, little is known about the genetic architecture of the preceding early stages of the 37 diseases. 38 Methods: To identify genetic factors for early AMD, we conducted a genome-wide association 39 meta-analysis with 14,034 early AMD cases and 91,214 controls from 11 sources of data 40 including data from the International AMD Genomics Consortium (IAMDGC) and the UK 41 Biobank (UKBB). We ascertained early AMD via color fundus photographs by manual grading 42 for 10 sources and by using an automated machine learning approach for >170,000 images 43 from UKBB. We searched for significant genetic loci in a genome-wide association screen 44 (P<5x10-8) based on the meta-analysis of the 11 sources and via a candidate approach based 45 on 13 suggestive early AMD variants from Holliday et al 2013 (P<0.05/13, additional 3,432 46 early AMD cases and 11,235 controls). For the novel AMD regions, we conducted in-silico 47 follow-up analysis to prioritize causal genes and pathway analyses. 48 Results: We identified 11 loci for early AMD, 9 novel and 2 known for early AMD. Most of 49 these 11 loci overlapped with known advanced AMD loci (near ARMS2/HTRA1, CFH, APOE, 50 C2, C3, CETP, PVRL2, TNFRSF10A, VEGFA), except two that were completely novel to any 51 AMD. Among the 17 genes within the two novel loci, in-silico functional annotation suggested 52 CD46 and TYR as the most likely responsible genes. We found the presence or absence of 53 an early AMD effect to distinguish known pathways of advanced AMD genetics 54 (complement/lipid pathways or extracellular matrix metabolism, respectively). 55 Conclusions: Our data on early AMD genetics provides a resource comparable to the existing 56 data on advanced AMD genetics, which enables a joint view. Our large GWAS on early AMD 57 identified novel loci, highlighted shared and distinct genetics between early and advanced 58 AMD and provides insights into AMD etiology. The ability of early AMD effects to differentiate 59 the major pathways for advanced AMD underscores the biological relevance of a joint view on 60 early and advanced AMD genetics. 61 KEYWORDS 2 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.20.883801; this version posted December 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 62 Genome-wide association study (GWAS); Meta-analysis; Age-related macular degeneration 63 (AMD); Early AMD; CD46; TYR; International AMD Genomics Consortium (IAMDGC); UK 64 Biobank (UKBB); machine-learning; automated phenotyping 65 66 BACKGROUND 67 Age-related macular degeneration (AMD) is the leading cause of irreversible central vision 68 impairment in industrialized countries. Advanced AMD presents as geographic atrophy (GA) 69 and/or neovascular (NV) complications (1). Typically, advanced AMD is preceded by clinically 70 asymptomatic and thus often unrecognized early disease stages. Early AMD is characterised 71 by differently sized yellowish accumulations of extracellular material between Bruch's 72 membrane and retinal pigment epithelium (RPE) or between RPE and the photoreceptors 73 (drusen or subretinal drusenoid deposits, respectively). Other features of early AMD are RPE 74 abnormalities, including depigmentation or increased amount of pigment (1). 75 Early and advanced AMD can be documented by color fundus imaging of the central 76 retina and/or other multimodal imaging approaches including optical coherence tomography 77 (OCT) (1–3). While the definition of advanced AMD is reasonably homogeneous across clinical 78 and epidemiological studies, the classification of early AMD is more variable and different 79 studies traditionally apply differing classification systems (4,5). 80 Epidemiological studies show that high age is the strongest risk factor for early and 81 advanced AMD onset as well as progression (1,6–8). A robust genetic influence was shown 82 for advanced AMD (1,9,10) with 34 distinct loci at genome-wide significance in a large genome- 83 wide association study (GWAS) for advanced AMD (9). The genes underneath these advanced 84 AMD loci were found to be enriched for genes in the alternative complement pathway, HDL 85 transport, and extracellular matrix organization and assembly (9). 86 Exploring the genetics of early AMD offers the potential to understand the mechanisms 87 of early disease processes, but also for the development to advanced AMD when comparing 88 genetic effect sizes for early and advanced stages. Yet there have been few published GWAS 89 searches for early AMD. One meta-analysis on 4,089 early AMD patients and 20,453 control 3 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.20.883801; this version posted December 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 90 persons reported two loci with genome-wide significance, both being well known from 91 advanced AMD, the CFH and the ARMS2/HTRA1 locus (11). 92 We have thus set out to gather GWAS data for early AMD from 11 sources including 93 own study data, data from the International AMD Genomics Consortium (IAMDGC), dbGaP 94 and UK Biobank to conduct the largest GWAS meta-analysis on early AMD to date. 95 96 METHODS 97 GWAS data from 11 sources 98 We included 11 sources of data with GWAS data and color fundus photography for early AMD 99 phenotyping (Table S1). Our studies were primarily population-based cohort studies, where 100 the baseline survey data were used for this analysis from studies of the authors (GHS, LIFE, 101 NICOLA, KORA, AugUR) as well as for publicly available studies from dbGaP (ARIC, CHS, 102 WHI; accession numbers: phs000090.v5.p1, phs000287.v6.p1, phs000746.v2.p3). We also 103 included data from UK Biobank for participants from baseline and additional participants from 104 the follow-up survey, since the color fundus photography program had started only after the 105 main study onset (application number #33999). The studies captured an age range from 25 to 106 100 years of age (mean age from 47.5 years to 77.2 years across the 10 population-based 107 studies, AugUR with the very old individuals range from 70.3 years to 95 years). About 50% of 108 the study participants in each study were male (except for the Women's Health Initiative, WHI) 109 and all demonstrated European ancestry. For each of these cross-sectional data sets, 110 participants with at least one eye gradable for AMD (see below) and with existing GWAS data 111 were eligible for our analysis. We excluded participants with advanced AMD. We used 112 participants with ascertained early AMD as cases and participants being ascertained for not 113 having any signs of AMD as controls (n=7,363 cases, 73,358 controls across these population- 114 based studies).
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  • Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways

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    biomolecules Article Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways Aayushi Srivastava 1,2,3,4 , Abhishek Kumar 1,5,6 , Sara Giangiobbe 1, Elena Bonora 7, Kari Hemminki 1, Asta Försti 1,2,3 and Obul Reddy Bandapalli 1,2,3,* 1 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany; [email protected] (A.S.); [email protected] (A.K.); [email protected] (S.G.); [email protected] (K.H.); [email protected] (A.F.) 2 Hopp Children’s Cancer Center (KiTZ), D-69120 Heidelberg, Germany 3 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), D-69120 Heidelberg, Germany 4 Medical Faculty, Heidelberg University, D-69120 Heidelberg, Germany 5 Institute of Bioinformatics, International Technology Park, Bangalore 560066, India 6 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576104, India 7 S.Orsola-Malphigi Hospital, Unit of Medical Genetics, 40138 Bologna, Italy; [email protected] * Correspondence: [email protected]; Tel.: +49-6221-42-1709 Received: 29 August 2019; Accepted: 10 October 2019; Published: 13 October 2019 Abstract: Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family.
  • Case–Control Association Study of 59 Candidate Genes Reveals the DRD2

    Case–Control Association Study of 59 Candidate Genes Reveals the DRD2

    Journal of Human Genetics (2009) 54, 98–107 & 2009 The Japan Society of Human Genetics All rights reserved 1434-5161/09 $32.00 www.nature.com/jhg ORIGINAL ARTICLE Case–control association study of 59 candidate genes reveals the DRD2 SNP rs6277 (C957T) as the only susceptibility factor for schizophrenia in the Bulgarian population Elitza T Betcheva1, Taisei Mushiroda2, Atsushi Takahashi3, Michiaki Kubo4, Sena K Karachanak5, Irina T Zaharieva5, Radoslava V Vazharova5, Ivanka I Dimova5, Vihra K Milanova6, Todor Tolev7, George Kirov8, Michael J Owen8, Michael C O’Donovan8, Naoyuki Kamatani3, Yusuke Nakamura1,9 and Draga I Toncheva5 The development of molecular psychiatry in the last few decades identified a number of candidate genes that could be associated with schizophrenia. A great number of studies often result with controversial and non-conclusive outputs. However, it was determined that each of the implicated candidates would independently have a minor effect on the susceptibility to that disease. Herein we report results from our replication study for association using 255 Bulgarian patients with schizophrenia and schizoaffective disorder and 556 Bulgarian healthy controls. We have selected from the literatures 202 single nucleotide polymorphisms (SNPs) in 59 candidate genes, which previously were implicated in disease susceptibility, and we have genotyped them. Of the 183 SNPs successfully genotyped, only 1 SNP, rs6277 (C957T) in the DRD2 gene (P¼0.0010, odds ratio¼1.76), was considered to be significantly associated with schizophrenia after the replication study using independent sample sets. Our findings support one of the most widely considered hypotheses for schizophrenia etiology, the dopaminergic hypothesis.