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. 2016 Feb;48(2):134-43.
doi: 10.1038/ng.3448. Epub 2015 Dec 21.

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

Lars G Fritsche  1 Wilmar Igl  2 Jessica N Cooke Bailey  3 Felix Grassmann  4 Sebanti Sengupta  1 Jennifer L Bragg-Gresham  1   5 Kathryn P Burdon  6 Scott J Hebbring  7 Cindy Wen  8 Mathias Gorski  2 Ivana K Kim  9 David Cho  10 Donald Zack  11   12   13   14   15 Eric Souied  16 Hendrik P N Scholl  11   17 Elisa Bala  18 Kristine E Lee  19 David J Hunter  20   21 Rebecca J Sardell  22 Paul Mitchell  23 Joanna E Merriam  24 Valentina Cipriani  25   26 Joshua D Hoffman  27 Tina Schick  28 Yara T E Lechanteur  29 Robyn H Guymer  30 Matthew P Johnson  31 Yingda Jiang  32 Chloe M Stanton  33 Gabriëlle H S Buitendijk  34   35 Xiaowei Zhan  1   36   37 Alan M Kwong  1 Alexis Boleda  38 Matthew Brooks  38 Linn Gieser  38 Rinki Ratnapriya  38 Kari E Branham  39 Johanna R Foerster  1 John R Heckenlively  39 Mohammad I Othman  39 Brendan J Vote  6 Helena Hai Liang  30 Emmanuelle Souzeau  40 Ian L McAllister  41 Timothy Isaacs  41 Janette Hall  40 Stewart Lake  40 David A Mackey  6   30   41 Ian J Constable  41 Jamie E Craig  40 Terrie E Kitchner  7 Zhenglin Yang  42   43 Zhiguang Su  44 Hongrong Luo  8 Daniel Chen  8 Hong Ouyang  8 Ken Flagg  8 Danni Lin  8 Guanping Mao  8 Henry Ferreyra  8 Klaus Stark  2 Claudia N von Strachwitz  45 Armin Wolf  46 Caroline Brandl  2   4   47 Guenther Rudolph  46 Matthias Olden  2 Margaux A Morrison  48 Denise J Morgan  48 Matthew Schu  49   50   51   52   53 Jeeyun Ahn  54 Giuliana Silvestri  55 Evangelia E Tsironi  56 Kyu Hyung Park  57 Lindsay A Farrer  49   50   51   52   53 Anton Orlin  58 Alexander Brucker  59 Mingyao Li  60 Christine A Curcio  61 Saddek Mohand-Saïd  62   63   64   65 José-Alain Sahel  25   62   63   64   65   66   67 Isabelle Audo  62   63   64   68 Mustapha Benchaboune  65 Angela J Cree  69 Christina A Rennie  70 Srinivas V Goverdhan  69 Michelle Grunin  71 Shira Hagbi-Levi  71 Peter Campochiaro  11   13 Nicholas Katsanis  72   73   74 Frank G Holz  17 Frédéric Blond  62   63   64 Hélène Blanché  75 Jean-François Deleuze  75   76 Robert P Igo Jr  3 Barbara Truitt  3 Neal S Peachey  18   77 Stacy M Meuer  19 Chelsea E Myers  19 Emily L Moore  19 Ronald Klein  19 Michael A Hauser  78   79   80 Eric A Postel  78 Monique D Courtenay  22 Stephen G Schwartz  81 Jaclyn L Kovach  81 William K Scott  22 Gerald Liew  23 Ava G Tan  23 Bamini Gopinath  23 John C Merriam  24 R Theodore Smith  24   82 Jane C Khan  41   83   84 Humma Shahid  84   85 Anthony T Moore  25   26   86 J Allie McGrath  27 Reneé Laux  3 Milam A Brantley Jr  87 Anita Agarwal  87 Lebriz Ersoy  28 Albert Caramoy  28 Thomas Langmann  28 Nicole T M Saksens  29 Eiko K de Jong  29 Carel B Hoyng  29 Melinda S Cain  30 Andrea J Richardson  30 Tammy M Martin  88 John Blangero  31 Daniel E Weeks  32   89 Bal Dhillon  90 Cornelia M van Duijn  35 Kimberly F Doheny  91 Jane Romm  91 Caroline C W Klaver  34   35 Caroline Hayward  33 Michael B Gorin  92   93 Michael L Klein  88 Paul N Baird  30 Anneke I den Hollander  29   94 Sascha Fauser  28 John R W Yates  25   26   84 Rando Allikmets  24   95 Jie Jin Wang  23 Debra A Schaumberg  20   96   97 Barbara E K Klein  19 Stephanie A Hagstrom  77 Itay Chowers  71 Andrew J Lotery  69 Thierry Léveillard  62   63   64 Kang Zhang  8   44 Murray H Brilliant  7 Alex W Hewitt  6   30   41 Anand Swaroop  38 Emily Y Chew  98 Margaret A Pericak-Vance  22 Margaret DeAngelis  48 Dwight Stambolian  10 Jonathan L Haines  3   99 Sudha K Iyengar  3 Bernhard H F Weber  4 Gonçalo R Abecasis  1 Iris M Heid  2
Affiliations

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

Lars G Fritsche et al. Nat Genet. 2016 Feb.

Abstract

Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

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Figures

Figure 1
Figure 1. Genome-wide search reveals 34 loci and genes with rare variant burden for AMD
(a) We conducted a genome-wide single variant association analysis for >12 million variants in 16,144 advanced AMD patients versus 17,832 controls. Shown is the Manhattan Plot exhibiting P-values for association highlighting novel (P < 5×10–8 for the first time, green) and known (blue) AMD loci (see Table 1). (b) We computed independent effect size (Odds Ratios) of each of the 52 identified variants (Supplementary Table 4). Shown are these effect sizes versus the frequency of the AMD risk increasing allele and a 80% power curve. (c) We conducted a genome-wide gene-based test for disease burden based on the protein-altering variants testing 17,044 RefSeq genes by the variable threshold test. Shown is the Manhattan Plot with P-values, the red horizontal line indicating genome-wide significance (P ≤ 0.05/17,044 = 2.9×10–6) and the yellow line indicating AMD-locus-wide significance (given 703 genes in the 34 AMD loci, P ≤ 0.05/703 = 7.1×10–5). No gene outside the 34 loci is genome-wide significant; 14 genes are AMD-locus-wide significant (blue), four remain significant after locus-wide conditioning (bold letters, Supplementary Table 11).
Figure 2
Figure 2. Genes with top priority based on biological and statistical evidence combined
We queried 368 genes in the 34 narrow AMD regions (index and proxies, r ≥0.5, ±100kb) for biological (red; expression in retina/RPE/choroid, Supplementary File 6; ocular mouse phenotype, Supplementary File 7), statistical, (blue; ≥1 credible set variant in gene ±50 kb, Supplementary File 3; rare variant burden, Table 2), putative functional (green; ≥ 1 credible set variant in gene ±50 kb being protein-altering, 5′/3′ UTR, other exonic, or putative promoter, Supplementary File 3), and molecular (magenta; enriched molecular pathway, drug target) evidence. We here focus on the gene(s) with the highest gene priority score (GPS) per locus (full list of genes in Supplementary File 9). Shown are (a) the 16 genes with highest GPS in the 15 novel AMD loci (one novel locus without any gene), and (b) the 25 genes with highest GPS in the 18 known AMD loci. Colored fields indicate yes and GPS counts number of colored fields per row.
Figure 3
Figure 3. Comparison of advanced AMD subtypes and intermediate versus advanced AMD
We compared associations of the 34 lead variants across different AMD phenotypes. Shown are effect sizes (log Odds Ratio) per minor allele in controls as well as 95% confidence intervals (widths and heights of diamonds). (a) Comparison of neovascular disease (10,749 CNV cases vs. 17,832 controls) and GA (3,235 GA cases vs. 17,832 controls) identified four variants (in loci MMP9, ARMS2/HTRA1, CETP, and SYN3/TIMP3) with significantly different association comparing CNV with GA (Pdiff < 0.05/34, marked in red, see also Supplementary Table 16). (b) Comparison of intermediate AMD (6,657 cases vs. 17,832 controls) with advanced AMD (16,144 cases vs. 17,832 controls) identifies 24 variants with nominally significant (P < 0.05, marked in red) association with intermediate AMD (Pbinomial = 4.8 × 10–24), all of which have the same effect direction and less extreme effect sizes compared to advanced AMD (Supplementary Table 17).
Figure 4
Figure 4. Variance explained and absolute risk of disease based on the 52 identified variants
(a) Absolute disease risk (=proportion of affected) by genetic risk score intervals (deciles and top 10 percentiles in embedded bar plot) based on our cases-control-data weighted to model a general population with 5% disease prevalence (see also Supplementary Table 20). (b) Shown is disease liability explained by the 52 identified variants (bars) compared to the genomic heritability based on all genotyped variants (red lines) assuming disease prevalence of 1%, 5%, or 10%, respectively.

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