variable clinical presentation of severe recurrent bacterial infections, glomerulonephritis, autoimmune diseases, and leucocytoclastic vasculitis [69]. MCP is a membrane-bound regulator, and mutations in the MCP gene are associated with aHUS, glomerulonephritis with C3 deposits, and HELLP (haemolysis, elevated liver enzymes, and low platelets) syndrome [70]. In addition, the complement system is also implicated in several other diseases, including Alzheimer’s disease,
Parkinson’s disease, multiple sclerosis, Huntington’s disease, and atherosclerosis [71-74]. This
implies that variants in genes of the complement system are associated with multiple and very diverse diseases, and that the role of the complement system extends far beyond the removal of cellular debris and infectious microbes.
However, the precise nature and extent of allelic overlap between distinct phenotypes remains unclear. In some cases, variants in the same gene can even have an opposite effect in different diseases. For example, the p.Arg620Trp variant in the PTPN22 gene is a risk factor for type 1
diabetes (T1D) and rheumatoid arthritis (RA), whereas it is a protective for Crohn’s disease [75-77].
However, in most cases it is not clear how variants in the same gene can lead to different phenotypes. A study speculated that the surface-bound glycocalyx, a multifunctional thick layer of proteoglycans and glycoproteins covering the laminar endothelium [78], may determine different clinical manifestations in AMD and aHUS [79]. This study suggested that a different composition of the glycocalyx on the microvascular choroidal endothelium in the eye compared to the glomerular endothelium in the kidney may alter the binding properties of mutant complement proteins and give rise to different clinical outcomes. Some emerging evidence also supports the involvement of the glycocalyx in the pathogenesis of AMD and aHUS. Mutations in theCOG7 gene are known to cause aHUS, and the protein encoded by this gene is vital for sialyation of proteins in the glycocalyx [80]. Common variants in the B3GALTL gene, which encodes a glycosyltransferase, are associated with AMD [2]. This supports the involvement of the glycocalyx in the pathogenesis of AMD and aHUS and might provide an explanation for the different clinical outcomes of variants in the complement system, as the outcome may depend on the integrity of the glycocalyx in the affected organ. This hypothesis, however, has not yet been proven at the cellular level.
Another hypothesis suggests the requirement of additional genetic factors (multiple hits) or compounding (genetic and environmental) factors to manifest a particular disease state. For example, one study has demonstrated that additional genetics factors can trigger aHUS disease [81]. Another study demonstrated that specific combinations of common variants in the C3, CFB, and CFH genes alter the alternative pathway activity to 50%, which suggests that a single variant may not be sufficient, but that a combination of alleles are required to cause aHUS [37]. In addition, several other risk factors have been described that contribute to aHUS, including genetic factors in genes of the coagulation system (THBD), autoantibodies (anti-factor H), and environmental triggers (infections, childbirth, immunosuppressive drugs, pregnancy, etc.) [82]. It can be postulated that a certain combination of risk factors can lead to aHUS, whereas a combination of other risk factors can lead to AMD, with variants in the complement system being the common denominator. Along similar lines, a different combination of other risk factors may yet lead to other complement-
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mediated diseases, such as HELLP, Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, Huntington’s disease, and atherosclerosis.
These findings support and encourage cross-phenotype studies to identify variants that are unique and common to clinically distinct phenotypes. These studies will provide a broader understanding of human health and diseases [83,84].
5. Novel Approaches to Solving the Remaining Missing Heritability
The present thesis identified several rare sequence variants in AMD. It is likely, however, that a greater number of rare variants that contribute to AMD are yet to be discovered. More comprehensive approaches are required to employ the entire genome, and the following methods can be performed to identify rare variants in AMD [85].
5.1 Exome Array
WGS and WES are still expensive methods to sequence large number of samples to detect rare sequence variants in complex diseases. Therefore, exome arrays offer an alternative approach to test a predetermined set of rare and low frequency coding variants in large number of samples at lower costs. The first exome chip, the Illumina Infinium HumanExome BeadChip, was designed to test 247,870 protein-altering variants. These variants were selected from >12,000 exome and genome sequenced individuals [86]. The selected protein-altering variants have been identified three or more times in at least two studies. The exome array approach successfully identified rare causal variants at GWAS loci for insulin processing and secretion traits [86]. The International AMD Genomics Consortium has recently analysed >50,000 samples using exome chips, which identified additional common and rare variants in AMD (Fritsche et al., manuscript submitted). In addition, an exome array approach was recently used to identify new common and rare AMD variants in East Asians [87].
The exome array approach is a powerful tool for analysis of rare coding variants, and also to fine- map GWAS loci in complex diseases. However, the approach has some limitations. Firstly, they have been designed to analyse a fixed set of coding variants, thereby excluding many other coding variants, novel variants, and all non-coding variants. Secondly, exome arrays might not capture rare variants homogenously, since the majority of genetic variation is rare and private to different human populations [88]. In conclusion, the exome array approach alone is not sufficient to solve the missing heritability in complex traits. Therefore, sequencing studies using either targeted capture of candidate genes, WES or WGS are ultimate requirements for comprehensive analyses of genetic variation in complex diseases.