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The early infantile epileptic encephalopathies (EIEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 novel putative transcript models. The extended transcriptional footprint of these genes allowed for 294 intronic or intergenic variants, found in human mutation databases, to be reclassified as exonic, while a further 70 intronic variants were reclassified as splice-site proximal. Using SCN1A as a case study due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome, or a similar phenotype, with a panel of novel exon sequences representing eight established genes and identified two de novo SCN1A variants that now, through improved gene annotation can be ascribed to residing among novel exons. These two (from 122 screened patients, 1.6%) new molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously-classified SCN1A intronic Dravet-associated variant that now lies within a deeply conserved novel exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders. We would expect to find new molecular diagnoses in our 191 genes that were originally suspected by clinicians for patients, with a negative diagnosis.

The developmental and epileptic encephalopathies (DEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60–65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for a lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 putative transcript models. Our annotations increase the transcriptional ‘footprint’ of these genes by over 674 kb. Using SCN1A as a case study, due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome or a similar phenotype with a panel of exon sequences representing eight established genes and identified two de novo SCN1A variants that now - through improved gene annotation - are ascribed to residing among our exons. These two (from 122 screened people, 1.6%) molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously classified SCN1A intronic Dravet syndrome-associated variant that now lies within a deeply conserved exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders.

This study investigates heart rate (HR), in 11 young adults (22.4±3.21yr), at V̇O2max, to ascertain whether measured maximal heart rate (HRmax), as determined by a plateau in HR (HRplat), can reliably confirm V̇O2max. V̇O2max and HRplat were determined, using the parameters of a V̇O2≤50 ml•min−1 and a ∆HR≤2b•min−1, respectively, over the final 60 s of sampling. V̇O2 was also independently determined using a verification phase protocol. A HRplat was achieved by 91% of participants (∆HR=1.3±1b•min−1) and critically the time at which HRmax was reached coincided with that at which V̇O2max was achieved. Moreover RER and ΔRER criteria were reached significantly earlier (p

The purpose of this study was to assess the VO2max plateau response at VO2max during a series of pre-determined trials. METHODS: Ten male well-trained athletes (age, 23.0 ± 3.2; height, 183.3 ± 5.5 cm; mass 77.5 ± 11.1 Kg; VO2max 66.5 ± 5.0 ml.kg-1,min-1), but who were VO2max testing naïve and with prior-knowledge of trial number completed four incremental tests to volitional exhaustion, separated by ~72-h for the determination of VO2max and gas exchange threshold. Throughout all trials VO2max was recorded on a breath-by-breath basis using a pre-calibrated metabolic cart, using a plateau criterion of Δ VO2 ≤1.5 ml.kg-1.min-1 over the final 2 consecutive 30 s sampling periods. A significant difference was observed between trial-1 and trial-4 for plateau incidence (p = 0.0285) rising from 20% in trial-1 to a 70% response rate in trial-4. Furthermore a significant difference was observed for VO2dif (difference between criterion value and Δ VO2) in trial-1, 1.02 ± 1.69 ml.kg-1.min-1 (p = 0.038), with non-significant differences observed for all other trials, despite a non-significant difference for VO2max across all trials (p > 0.05). Finally, a significant difference was observed for effort perception (RPE) at volitional exhaustion between trial-1 (17.7 ± 1.3) and trial-4 (19.0 ± 1.4) (p = 0.0052). These data indicate that prior-knowledge of trial number can influence the manifestation of the VO2 plateau in a group of well-trained male athletes, thereby suggesting that a form of effort control is established in order to preserve the finite anaerobic capacity.