Ординатура / Офтальмология / Английские материалы / Recent Advances in Retinal Degeneration_LaVail, Hollyfield, Anderson _2008

Mutations in Known Genes Account

for 58% of Autosomal Dominant Retinitis Pigmentosa (adRP)

Stephen P. Daiger, Lori S. Sullivan, Anisa I. Gire, David G. Birch, John R. Heckenlively, and Sara J. Bowne

1 Introduction

Inherited retinal diseases such as autosomal dominant retinitis pigmentosa (adRP) are strikingly complex, with mutations in many different genes causing the same disease, with many different mutations in each gene, and with different clinical consequences resulting from the same mutation, even within the same family. For example, mutations in sixteen genes are known to cause adRP and an additional two adRP genes have been mapped but not identified yet (Table 1). This raises two questions: what fraction of adRP cases are accounted for by mutations in known genes, and what accounts for the remaining cases?

To answer these questions we applied a step-wise screening process to a cohort of well-characterized adRP families, now numbering 215 (Sullivan et al., 2006a). Methods included sequencing of known genes, detection of deletions using MLPA (multiplex ligation-dependent probe amplification) (Sullivan et al., 2006b), linkage mapping against known loci, and genome-wide linkage mapping. By this combination of approaches we detected mutations in 58% of the families (largely Americans of European origin). Approximately 3% of these families have large deletions that cannot be detected by conventional PCR-based methods, and linkage testing against known loci revealed several additional mutations that were not detected earlier. Thus some of the remaining families are likely to have large deletions or other “hidden” mutations in known genes. However, linkage testing also confirms the existence of new adRP genes.

Being able to find the cause of adRP in all or nearly all affected individuals is a difficult but achievable goal, perhaps within the next decade (Daiger et al., 2007). This information is of immediate value to patients and families, and is a necessary precursor to gene and mutation-specific therapies.

S.P. Daiger

Human Genetics Center, School of Public Health, and Dept. of Ophthalmology, The Univ. of Texas, Houston, TX, USA, Tel: 713-500-9829, Fax: 713-500-0900

e-mail: stephen.p.daiger@uth.tmc.edu.

Table 1 Genes known to cause adRP, references in RetNet, (RetNet, 2007)

2 Methods

We tested a panel of affected individuals from 215 adRP families for mutations in most of the known dominant RP genes (Table 1) (Sullivan et al., 2006a) and unpublished]. To be included in the study a family had to have a diagnosis of adRP by a knowledgeable clinical specialist, and either (a) three affected generations with affected females, or (b) two affected generations with male-to-male transmission. The latter requirement was to reduce the likelihood of including families with X- linked RP. This possibility arises because some mutations in the X-linked gene RPGR affect female “carriers”, thus the disease in these families may be misinterpreted as adRP (Mears et al., 2000; Rozet et al., 2002; Vervoort et al., 2000).

The cohort of adRP patients was screened (largely by DNA sequencing) for mutations in the protein coding regions and intron-exon junctions of all adRP genes or gene regions causing at least 1% of cases. ORF15, the “hot spot” for mutations in RPGR, was also tested in families without male-to-male transmission. Determining whether a novel, rare variant is pathogenic was done using several computational and genetic tools (Grantham et al., 1974; Ng, 2003; Ramensky et al., 2002; Reese et al., 1997).

In subsequent studies, we tested several of the remaining families for linkage to genetic markers within or close to the known adRP genes and to RPGR [(Sullivan et al., 2006b) and unpublished]. This was done to uncover mutations that might have been missed by sequencing or to locate genes that have been mapped but

to the ABI 5 cM STR marker set. Linkage mapping in these families suggests the existence of novel adRP loci [(Sullivan et al., 2005) and unpublished].

4 Conclusions

Mutations in known adRP genes account for at least 58% of adRP cases. “Common” mutations among the total account for at least 35% of cases, but novel mutations are found in the remainder. Thus screening adRP patients for known mutations and for mutations in selected regions of adRP genes can detect a large fraction of disease-causing variants, but additional methods, including MPLA and linkage, are also required. These prevalences are based largely on Americans of European origin and Europeans; other populations have different “common” mutations and different prevalences.

Deletions and copy number variants in PRPF31, not detectable by sequencing, account for 2.8 % of cases. Some of these deletions are very large, encompassing flanking genes. Deletions in other genes may also cause adRP.

Digenic RDS-ROM1 and X-linked dominant mutations in RPGR affect 0.5% and 1.5%, respectively, of “dominant” RP families. For diagnostic and counseling purposes it is very important to consider alternate modes of inheritance in adRP families.

Identifying the underlying disease-causing mutation in families with adRP is an essential step in diagnosis, counseling and, eventually, treatment (Daiger et al., 2007).

Acknowledgments Supported by grants from the Foundation Fighting Blindness, the William Stamps Farish Fund, the Gustavus and Louise Pfeiffer Research Foundation, and the Hermann Eye Fund; and by NIH grants EY007142, EY014170, and EY005235.

References

Daiger, S. P., Bowne, S. J., and Sullivan, L. S., 2007, Perspective on genes and mutations causing retinitis pigmentosa, Arch. Ophthalmol. 125: 151–158.

Felbor, U., Schilling, H., and Weber, B. H., 1997, Adult vitelliform macular dystrophy is frequently associated with mutations in the peripherin/RDS gene, Hum. Mutat. 10: 301–309.

Grantham, R., 1974, Amino acid difference formula to help explain protein evolution, Science 185: 862–864.

Kajiwara, K., Sandberg, M. A., Berson, E. L., and Dryja, T. P., 1993, A null mutation in the human peripherin/RDS gene in a family with autosomal dominant retinitis punctata albescens, Nat. Genet. 3: 208–212.

Lathrop, G. M., Lalouel, J. M., Julier, C., and Ott, J., 1984, Strategies for multilocus linkage analysis in humans, Proc. Natl. Acad. Sci. USA 81: 3443–3446.

Mears, A. J., Hiriyanna, S., Vervoort, R., Yashar, B., Gieser, L., Fahrner, S., Daiger, S. P., Heckenlively, J. R., Sieving, P. A., Wright, A. F., and Swaroop, A., 2000, Remapping of the

RP15 locus for X-linked cone-rod degeneration to Xp11.4-p21.1, and identification of a de novo insertion in the RPGR exon ORF15, Am. J. Hum. Genet. 67: 1000–1003.

Ng, P. C., and Henikoff, S., 2003, SIFT: Predicting amino acid changes that affect protein function, Nucleic Acids Res. 31: 3812–3814.

Ramensky, V., Bork, P., and Sunyaev, S., 2002, Human non-synonymous SNPs: server and survey, Nucleic Acids Res. 30: 3894–3900.

Reese, M. G., Eeckman, F. H., Kulp, D., and Haussler, D., 1997, Improved splice site detection in Genie, J. Comput. Biol. 4: 311–323.

Rozet, J. M., Perrault, I., Gigarel, N., Souied, E., Ghazi, I., Gerber, S., Dufier, J. L., Munnich, A., and Kaplan, J., 2002, Dominant X linked retinitis pigmentosa is frequently accounted for by truncating mutations in exon ORF15 of the RPGR gene, J. Med. Genet. 39: 284–285.

Schouten, J. P., McElgunn, C. J., Waaijer, R., Zwijnenburg, D., Diepvens, F., and Pals, G., 2002, Relative quantification of 40 nucleic acid sequences by multiplex ligation-dependent probe amplification, Nucleic Acids Res. 30: e57.

Sears, J. E., Aaberg, T. A., Sr., Daiger, S. P., and Moshfeghi, D. M., 2001, Splice site mutation in the peripherin/RDS gene associated with pattern dystrophy of the retina, Am. J. Ophthalmol. 132: 693–699.

Sullivan, L. S., Bowne, S. J., Birch, D. G., Hughbanks-Wheaton, D., Heckenlively, J. R., Lewis, R. A., Garcia, C. A., Ruiz, R. S., Blanton, S. H., Northrup, H., Gire, A. I., Seaman, R., Duzkale, H., Spellicy, C. J., Zhu, J., Shankar, S. P., and Daiger, S. P., 2006a, Prevalence of disease-causing mutations in families with autosomal dominant retinitis pigmentosa (adRP): a screen of known genes in 200 families, Invest. Ophthalmol. Vis. Sci. 47: 3052–3064.

Sullivan, L. S., Bowne, S. J., Seaman, C. R., Blanton, S. H., Lewis, R. A., Heckenlively, J. R., Birch, D. G., Hughbanks-Wheaton, D., and Daiger, S. P., 2006b, Genomic rearrangements of the PRPF31 gene account for 2.5% of autosomal dominant retinitis pigmentosa, Invest. Ophthalmol. Vis. Sci. 47: 4579–4588.

Sullivan, L. S., Bowne, S. J., Shankar, S. P., Blanton, S. H., Heckenlively, J. R., Birch, D. G., Wheaton, D. H., Pelias, M. Z., and Daiger, S. P., 2005, Linkage mapping in families with autosomal dominant retinitis pigmentosa (adRP), Invest. Ophthalmol. Vis. Sci. 46: E-Abstract 2293.

Vervoort, R., Lennon, A., Bird, A. C., Tulloch, B., Axton, R., Miano, M. G., Meindl, A., Meitinger, T., Ciccodicola, A., and Wright, A. F., 2000, Mutational hot spot within a new RPGR exon in X-linked retinitis pigmentosa, Nat. Genet. 25: 462–466.

Genetics of Age-related Macular Degeneration

Albert O. Edwards

There have been major advances over the past two years in identifying genetic risks for age-related macular degeneration (AMD). The complexity of genetic association and genetic epidemiology studies and differences in the conclusions and data reported from various laboratories make it difficult for the general scientific reader to understand the significance and limitations of these advances. Thus, the scientific foundations and limitations of these genetic studies are not widely understood. The general scientific reader needs an approach to recognize spurious genetic association from those that are real and to understand what genetic association studies can teach us about AMD and where we need to be cautious. The purpose of this article is to provide an overview of the genetics of AMD and explain how to approach a genetic association study.

1 Genetic Risks for AMD

Reported genetic risks for AMD include genes with confirmed sequence variation increasing the risk of AMD in most studies, variants that have been partially reproducible, and those that have not been replicated, either because they are recent reports or could not be replicated (Table 1).

Genes with confirmed sequence variation include complement factor H (CFH) on chromosome 1q31 (Edwards et al., 2005; Haines et al., 2005; Klein et al., 2005). The Y402H polymorphism in this gene has a minor allele frequency of 40% and is highly associated with AMD. The LOC387715/PRSS11 locus on chromosome 10q26 contains multiple sequence variants associated with AMD, including an Ala69Ser polymorphism in LOC387715 with a minor allele frequency of 30%; the precise variant or variants explaining the association is not yet understood as discussed below (Jakobsdottir et al., 2005; Rivera et al., 2005). Finally, the factor

A.O. Edwards

Mayo Clinic, Department of Ophthalmology, 200 First Street SW, Rochester, MN 55905. Supported by the NEI, FFB, and RPB, Tel: (507) 284-2787, Fax: (507) 284-4612 e-mail: edwards.albert@mayo.edu

Table 1 DNA sequence variants reported to increase the risk of AMD grouped by reproducibility and frequency of variant

Genes with sequence variants confirmed in all studies

•Complement factor H (Tyr402His) with MAF = 40%

•LOC387715/PRSS11 (Ala69Ser) with MAF = 30%

•BF/C2 protective variants (e.g., Lue9His) with MAF = 3% Genes with variants confirmed in some studies

•APOE4 with MAF = 10%

•VEGF (multiple variants)

Genes with unconfirmed variants

•ERCC6, CX3CR1, LRP6, VLDLR, IL1A, CRP, HLA, MMP-9 Genes reported to have rare variation associated with AMD

•Fibulin 3, Fibulin 5, ABCA4

Genes reported, but not reproduced

• PON1, SOD2, CST3, ACE, FBLN6, TLR4

B/C2 locus (BF/C2) contains variants on chromosome 6 that alter the risk of AMD (Gold et al., 2006). Other variation has been reported to increase the risk of AMD, but less support for the association exists and they will not be discussed in this article.

1.1 Genetic Association Studies

Genetic association studies may include affected cases and related controls (e.g., sib-pairs, including either an affected or unaffected sib), or unrelated, unaffected controls. In the case in which one ascertains unrelated cases and controls, genetic association studies are fundamentally similar to other case-control studies. To perform a genetic association study, one must first ascertain a sample of cases and controls from the population of interest. Careful attention should be paid to the definitions of phenotype (diagnosis or quantification of disease) and, in particular its absence. The cases and controls should be from as similar groups as possible, with the exception of the complex trait being studied. Population stratification or admixture (e.g., concluding that a variant is associated with disease when the variant actually is associated with an unobserved difference in ethnicity between cases and controls) is always a possibility in association studies based on unrelated individuals. These concerns need to be address with good study design or within the statistical analysis. Input from an epidemiologist or statistician should be considered prior to starting the project.

Second, polymorphisms are selected and genotyped in the population or cohort; these polymorphisms are typically single nuclei-type polymorphisms or SNPs. The SNPs are often selected based on possible functional significance (e.g., coding polymorphism) or their presence near a gene with the expectation that they will be close enough to a nearby polymorphism altering the risk of disease to also be associated with disease (see next paragraph). The SNPs are usually selected manually taking into consideration the extent of linkage disequilibrium across the gene (see next paragraph), but software is available to optimize and streamline the process

(Xu et al., 2005). The minor allele frequency should be sufficiently common to enable statistical power in the population being studied; it is important to look at the allele and genotype counts in addition to measures of statistical power when small numbers of observations are expected.

One reason why genetic association studies are a powerful means for refining the location of a disease variant or discovering novel variants is linkage disequilibrium(Daly et al., 2001). Linkage disequilibrium refers to the observation that polymorphisms may be inherited more frequently together than would be expected by chance. For example, if two polymorphisms are located near each other and are in linkage disequilibrium, they will be inherited together more than the 50% expected by random inheritance (segregation). Some polymorphisms are in such tight linkage disequilibrium that they serve as proxies for each other and provide the same information. Depending on the region of the genome being studied, a single SNP can provide information over several hundred to many thousands of base-pairs. For example, in each of three AMD loci described above (CFH, 10q26, and BF/C2) the linkage disequilibrium is extensive, making it difficult to identify the exact polymorphisms explaining the association with disease. The greater the linkage disequilibrium, the easier it is to identify association because fewer SNPs are needed over a large region to detect the association, but the harder it is to refine the association. This process can be further complicated by the presence of multiple different risk variants in the same locus (see discussion of CFH below).

The third step is to validate the genotyping assay, for example, by confirming Hardy-Weinberg equilibrium (i.e., the genotypes frequencies roughly follow p2, (1–p)2 and 2p(1–p) were p represents the frequency of the common allele) and reviewing the original datafile for the accuracy of the allele calls. In the fourth step, one performs a statistical test of association, using one of the many available approaches. For quantitative phenotypes, often analysis of variance (ANOVA) or linear regression is performed. In the cases of a binary phenotype (e.g., affection status), allelic tests or genotype test are often performed with Chi-square test or tests for trend (Crochran-Armtigage Trend test, logistic regression). Regardless of type of phenotype, tests of genetic assocation are used to assess if a genotype or allele is significantly associated with the phenotype.Regardless of the specific statistical test employed, their purpose is to provide an estimate of obtaining the significant result by chance. They cannot be used to determine which of the various SNPs might explain the association with disease because other variables such as allele frequency influence the p-values. Increasing statistical significance does not equate to increasing chance of causality, a fallacy frequently observed in the literature. In addition to the p-value not implying causative findings, testing of multiple genetic variants increases the chance of a type I error (i.e., false-positive). Hence, care should be taken when interpreting p-values from statistical tests. We next need to know if there is one SNP or multiple SNPs that are associated with disease. This question is answered by using a multilocus statistical method or statistical test that conditions the effect of one SNP to assessthe effect of another SNP. The end result of these analyses are to determine which if any SNPs across a region/gene independently contribute to altered disease risk.