Cricopharyngeal bar on videofluoroscopy: high specificity for inclusion body myositis.

OBJECTIVE: To determine the prevalence and characteristics of the cricopharyngeal bar (CPB), defined as marked protrusion with lacking relaxation and stricture of the upper esophageal sphincter on videofluoroscopy, in patients with inclusion body myositis (IBM). METHODS: We conducted a case-control study of comprehensive series of adult healthy individuals and consecutive patients with neuropsychiatric disorders aged over 45 (52 versus 2486). A standard videofluoroscopy was performed. RESULTS: Overall, 47 individuals with CPB were identified. Of the individuals with CPB, 36% were IBM followed by neurodegenerative disorders, muscular disorders, neuromuscular disorders, and others (32%, 21%, 2.1%, and 8.5%, respectively), indicating the heterogeneity of the etiologies. Against muscular disorders, the sensitivity and specificity of the CPB for IBM were 33% (= 17/52; 95% confidence interval [CI], 20-45%) and 96% (= 264/274; 95% CI, 94-99%), respectively. IBM with CPB showed a higher frequency of obstruction-related dysphagia (88% versus 22%, p < 0.001) and severe CPB (76% versus 23%, p < 0.001) than the control with one. The ratio of the upper esophageal distance at the maximum distension at the level of C6 to that of C4 was lower in IBM with CPB than in the controls with one (0.50 versus 0.77, p < 0.001), which suggests the insufficient opening of the upper esophageal sphincter. CONCLUSION: A CPB could be indicative of IBM. The upper esophagus in IBM with CPB became narrow, like a bottleneck. We provide new perspectives of dysphagia diagnosis by videofluoroscopy, especially for IBM-associated dysphagia, to expand the knowledge on the CPB.

Noncoding CGG repeat expansions in neuronal intranuclear inclusion disease, oculopharyngodistal myopathy and an overlapping disease.

Noncoding repeat expansions cause various neuromuscular diseases, including myotonic dystrophies, fragile X tremor/ataxia syndrome, some spinocerebellar ataxias, amyotrophic lateral sclerosis and benign adult familial myoclonic epilepsies. Inspired by the striking similarities in the clinical and neuroimaging findings between neuronal intranuclear inclusion disease (NIID) and fragile X tremor/ataxia syndrome caused by noncoding CGG repeat expansions in FMR1, we directly searched for repeat expansion mutations and identified noncoding CGG repeat expansions in NBPF19 (NOTCH2NLC) as the causative mutations for NIID. Further prompted by the similarities in the clinical and neuroimaging findings with NIID, we identified similar noncoding CGG repeat expansions in two other diseases: oculopharyngeal myopathy with leukoencephalopathy and oculopharyngodistal myopathy, in LOC642361/NUTM2B-AS1 and LRP12, respectively. These findings expand our knowledge of the clinical spectra of diseases caused by expansions of the same repeat motif, and further highlight how directly searching for expanded repeats can help identify mutations underlying diseases.

Four parameters increase the sensitivity and specificity of the exon array analysis and disclose 25 novel aberrantly spliced exons in myotonic dystrophy.

Myotonic dystrophy type 1 (DM1) is an RNA gain-of-function disorder in which abnormally expanded CTG repeats of DMPK sequestrate a splicing trans-factor MBNL1 and upregulate another splicing trans-factor CUGBP1. To identify a diverse array of aberrantly spliced genes, we performed the exon array analysis of DM1 muscles. We analyzed 72 exons by RT-PCR and found that 27 were aberrantly spliced, whereas 45 were not. Among these, 25 were novel and especially splicing aberrations of LDB3 exon 4 and TTN exon 45 were unique to DM1. Retrospective analysis revealed that four parameters efficiently detect aberrantly spliced exons: (i) the signal intensity is high; (ii) the ratio of probe sets with reliable signal intensities (that is, detection above background P-value=0.000) is high within a gene; (iii) the splice index (SI) is high; and (iv) SI is deviated from SIs of the other exons that can be estimated by calculating the deviation value (DV). Application of the four parameters gave rise to a sensitivity of 77.8% and a specificity of 95.6% in our data set. We propose that calculation of DV, which is unique to our analysis, is of particular importance in analyzing the exon array data.

AG-dependent 3'-splice sites are predisposed to aberrant splicing due to a mutation at the first nucleotide of an exon.

In pre-mRNA splicing, a conserved AG/G at the 3'-splice site is recognized by U2AF(35). A disease-causing mutation abrogating the G nucleotide at the first position of an exon (E(+1)) causes exon skipping in GH1, FECH and EYA1, but not in LPL or HEXA. Knockdown of U2AF(35) enhanced exon skipping in GH1 and FECH. RNA-EMSA revealed that wild-type FECH requires U2AF(35) but wild-type LPL does not. A series of artificial mutations in the polypyrimidine tracts of GH1, FECH, EYA1, LPL and HEXA disclosed that a stretch of at least 10-15 pyrimidines is required to ensure normal splicing in the presence of a mutation at E(+1). Analysis of nine other disease-causing mutations at E(+1) detected five splicing mutations. Our studies suggest that a mutation at the AG-dependent 3'-splice site that requires U2AF(35) for spliceosome assembly causes exon skipping, whereas one at the AG-independent 3'-splice site that does not require U2AF(35) gives rise to normal splicing. The AG-dependence of the 3'-splice site that we analyzed in disease-causing mutations at E(+1) potentially helps identify yet unrecognized splicing mutations at E(+1).

Thermodynamic instability of siRNA duplex is a prerequisite for dependable prediction of siRNA activities.

We developed a simple algorithm, i-Score (inhibitory-Score), to predict active siRNAs by applying a linear regression model to 2431 siRNAs. Our algorithm is exclusively comprised of nucleotide (nt) preferences at each position, and no other parameters are taken into account. Using a validation dataset comprised of 419 siRNAs, we found that the prediction accuracy of i-Score is as good as those of s-Biopredsi, ThermoComposition21 and DSIR, which employ a neural network model or more parameters in a linear regression model. Reynolds and Katoh also predict active siRNAs efficiently, but the numbers of siRNAs predicted to be active are less than one-eighth of that of i-Score. We additionally found that exclusion of thermostable siRNAs, whose whole stacking energy (DeltaG) is less than -34.6 kcal/mol, improves the prediction accuracy in i-Score, s-Biopredsi, ThermoComposition21 and DSIR. We also developed a universal target vector, pSELL, with which we can assay an siRNA activity of any sequence in either the sense or antisense direction. We assayed 86 siRNAs in HEK293 cells using pSELL, and validated applicability of i-Score and the whole DeltaG value in designing siRNAs.

In vitro and in silico analysis reveals an efficient algorithm to predict the splicing consequences of mutations at the 5' splice sites.

We have found that two previously reported exonic mutations in the PINK1 and PARK7 genes affect pre-mRNA splicing. To develop an algorithm to predict underestimated splicing consequences of exonic mutations at the 5' splice site, we constructed and analyzed 31 minigenes carrying exonic splicing mutations and their derivatives. We also examined 189,249 U2-dependent 5' splice sites of the entire human genome and found that a new variable, the SD-Score, which represents a common logarithm of the frequency of a specific 5' splice site, efficiently predicts the splicing consequences of these minigenes. We also employed the information contents (R(i)) to improve the prediction accuracy. We validated our algorithm by analyzing 32 additional minigenes as well as 179 previously reported splicing mutations. The SD-Score algorithm predicted aberrant splicings in 198 of 204 sites (sensitivity = 97.1%) and normal splicings in 36 of 38 sites (specificity = 94.7%). Simulation of all possible exonic mutations at positions -3, -2 and -1 of the 189 249 sites predicts that 37.8, 88.8 and 96.8% of these mutations would affect pre-mRNA splicing, respectively. We propose that the SD-Score algorithm is a practical tool to predict splicing consequences of mutations affecting the 5' splice site.