This is greatly facilitated when clinical, physiologic, or morphologic studies point to a candidate protein or gene. For example, a kinetic abnormality of AChR detected at the single channel level [6
], or severe EP AChR deficiency revealed by α-bungarotoxin binding studies [7
], predicts mutations in an AChR subunit gene. lists generic and specific clinical clues that facilitate targeted mutation analysis.
Generic and specific clinical features of the congenital myasthenic syndromes based on patients investigated at the Mayo Clinic
When no candidate genes are apparent, mutation analysis can be based on frequencies of the heretofore identified mutations in different EP proteins, as shown in . This approach is more expensive and time intensive than the candidate gene approach.
In patients with strong phenotypic clues for a given recessive CMS but only one or no identified mutations in the open reading frame, cDNA isolated from muscle can reveal an intronic mutation. This was the case for some patients with Dok-7 myasthenia.[3
] cDNA analysis was also useful in deciphering the consequences of a frameshifting mutation in ColQ. [8
Genetic testing for CMS is now commercially available and facilitates diagnosis and management by neuromuscular specialists. It is best used in a targeted manner based on specific clinical features, as listed in , or beginning with the most frequently mutated genes, as shown in . However, this approach has a number of drawbacks: (1) it is expensive, especially if used in a shotgun manner; (2) it does not establish that recessive mutations are heteroallelic unless they are homozygous; therefore DNA from both parents also must be analyzed; (3) it will miss intronic mutations not close to exons; (4) evaluation of pathogenicity is based on software programs whose reliability is still debated; (5) it does not inform on kinetic consequences of mutations in AChR or ChAT, or on pathogenicity of mutations that render the disease protein structurally unstable; and (6) negative results do not exclude the diagnosis of a CMS because only previously identified disease genes are sequenced.
Another approach is linkage analysis if a sufficient number of informative relatives are available. If successful, it will point to a candidate chromosomal locus. If the physical map of the locus shows an attractive candidate gene, then mutation analysis by direct sequencing becomes feasible. This approach seldom works for CMS because large informative CMS kinships are seldom available; however, it has been successful in inbred populations with multiple consanguineous families [9
A direct and efficient approach is the use microarrays specifically designed for screening multiple candidate disease loci in known CMS genes. One publication finds this approach has a 73.3% overall sensitivity and a 95.5%a sensitivity for missense mutation, but it is not recommended for detecting insertion or deletion mutations [10
]. Also, this approach will miss mutations in novel CMS disease genes.
A novel approach to mutation discovery is whole exome sequencing that searches for mutations in exons. Kits available for this method presently capture only ~97% of the entire exome but read only 75% of the exome with more than 20x coverage. The enormous amount of generated data need to be filtered against previously identified variants deemed nonpathogenic and scrutinized for mutations in genes encoding EP related genes. The putative mutations must be confirmed by capillary sequencing and the non-truncating mutations examined by expression studies. Also, the cost of exome sequencing with the required bioinformatics analysis is still high [11
]. Other pitfalls in this approach are that (1) disease causing variants in noncoding regions and some large deletions or duplications can be missed, (2) pathogenic variants causing rare diseases may have previously been entered in dbSNP, (3) synonymous variants in good candidate genes that might affect a splice enhancer/repressor are often filtered out. Exome sequencing is most efficient when large and/or multiple kinships are available for analysis. Whole genome sequencing is also feasible but is even more expensive and more complicated to interpret than exome sequencing.
Large deletion or duplication mutations can be missed both by Sanger sequencing or whole exome sequencing. Although rare, they can be identified by array based comparative genomic hybridization.[12