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      Revisiting the role of factor H in age-related macular degeneration: Insights from complement-mediated renal disease and rare genetic variants

      , , , , ,
      Survey of Ophthalmology
      Elsevier BV

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          Abstract

          <p class="first" id="d16304928e119">Ophthalmologists are long familiar with the eye showing signs of systemic disease, but the association between age-related macular degeneration and abnormal complement activation, common to several renal disorders, has only recently been elucidated. Although complement activation products were identified in drusen almost three decades ago, it was not until the early 21st century that a single-nucleotide polymorphism in the complement factor H gene was identified as a major heritable determinant of age-related macular degeneration, galvanizing global efforts to unravel the pathogenesis of this common disease. Advances in proteomic analyses and familial aggregation studies have revealed distinctive clinical phenotypes segregated by the functional effects of common and rare genetic variants on the mature protein and its splice variant, factor H-like protein 1. The predominance of loss-of-function, N-terminal mutations implicate age-related macular degeneration as a disease of general complement dysregulation, offering several therapeutic avenues for its modulation. Here, we explore the molecular impact of these mutations/polymorphisms on the ability of variant factor H/factor H-like protein 1 to localize to polyanions, pentraxins, proinflammatory triggers, and cell surfaces across ocular and renal tissues and exert its multimodal regulatory functions and their clinical implications. Finally, we critically evaluate key therapeutic and diagnostic efforts in this rapidly evolving field. </p>

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          The mutational constraint spectrum quantified from variation in 141,456 humans

          Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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            Is Open Access

            Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis.

            Numerous population-based studies of age-related macular degeneration have been reported around the world, with the results of some studies suggesting racial or ethnic differences in disease prevalence. Integrating these resources to provide summarised data to establish worldwide prevalence and to project the number of people with age-related macular degeneration from 2020 to 2040 would be a useful guide for global strategies. We did a systematic literature review to identify all population-based studies of age-related macular degeneration published before May, 2013. Only studies using retinal photographs and standardised grading classifications (the Wisconsin age-related maculopathy grading system, the international classification for age-related macular degeneration, or the Rotterdam staging system) were included. Hierarchical Bayesian approaches were used to estimate the pooled prevalence, the 95% credible intervals (CrI), and to examine the difference in prevalence by ethnicity (European, African, Hispanic, Asian) and region (Africa, Asia, Europe, Latin America and the Caribbean, North America, and Oceania). UN World Population Prospects were used to project the number of people affected in 2014 and 2040. Bayes factor was calculated as a measure of statistical evidence, with a score above three indicating substantial evidence. Analysis of 129,664 individuals (aged 30-97 years), with 12,727 cases from 39 studies, showed the pooled prevalence (mapped to an age range of 45-85 years) of early, late, and any age-related macular degeneration to be 8.01% (95% CrI 3.98-15.49), 0.37% (0.18-0.77), and 8.69% (4.26-17.40), respectively. We found a higher prevalence of early and any age-related macular degeneration in Europeans than in Asians (early: 11.2% vs 6.8%, Bayes factor 3.9; any: 12.3% vs 7.4%, Bayes factor 4.3), and early, late, and any age-related macular degeneration to be more prevalent in Europeans than in Africans (early: 11.2% vs 7.1%, Bayes factor 12.2; late: 0.5% vs 0.3%, 3.7; any: 12.3% vs 7.5%, 31.3). There was no difference in prevalence between Asians and Africans (all Bayes factors <1). Europeans had a higher prevalence of geographic atrophy subtype (1.11%, 95% CrI 0.53-2.08) than Africans (0.14%, 0.04-0.45), Asians (0.21%, 0.04-0.87), and Hispanics (0.16%, 0.05-0.46). Between geographical regions, cases of early and any age-related macular degeneration were less prevalent in Asia than in Europe and North America (early: 6.3% vs 14.3% and 12.8% [Bayes factor 2.3 and 7.6]; any: 6.9% vs 18.3% and 14.3% [3.0 and 3.8]). No significant gender effect was noted in prevalence (Bayes factor <1.0). The projected number of people with age-related macular degeneration in 2020 is 196 million (95% CrI 140-261), increasing to 288 million in 2040 (205-399). These estimates indicate the substantial global burden of age-related macular degeneration. Summarised data provide information for understanding the effect of the condition and provide data towards designing eye-care strategies and health services around the world. National Medical Research Council, Singapore. Copyright © 2014 Wong et al. Open Access article distributed under the terms of CC BY-NC-ND. Published by .. All rights reserved.
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              A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

              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, most rare, protein-altering variant. 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. While wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first signal specific to wet AMD, near MMP9 (difference-P = 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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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Survey of Ophthalmology
                Survey of Ophthalmology
                Elsevier BV
                00396257
                March 2021
                March 2021
                : 66
                : 2
                : 378-401
                Article
                10.1016/j.survophthal.2020.10.008
                33157112
                478a5a22-30e8-45b0-ac74-70a08dd03f0d
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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