Comment
investigation. In any event, there is contribution at the identified loci across more than one cohort, but the extent and nature of the overall association remains unclear. Heterogeneity is often the price paid for assembly of huge sample sizes for GWAS or meta-analyses. However, the power of GWAS can be boosted not only by increasing sample size, but also in creative ways that exploit previous biological knowledge. For example, findings from many studies have suggested an important role for GABAA receptor function in genetic generalised epilepsies,7 and techniques such as genomewide pathway and hypothesis-driven analyses8 can be exploited to test such specific hypotheses and generate potential therapeutic targets. Another approach that sidesteps the complications of phenotype integrity is the use of imaging endophenotypes; changes in structural connectivity and grey matter volume have already been identified in juvenile myoclonic epilepsy.9 Quantitative measures closer to the underlying biology than the clinical phenotype might also reduce required sample sizes to the hundreds with newly developed mathematical methods,10 while improving specificity of findings. Knowledge of the genetics of common epilepsies is in need of integration. Strong but rare risk factors in the form of recurrent copy-number variation are known, and researchers have understood for some time that there are distinct genetic influences on absence and myoclonic seizure types within the genetic generalised epilepsies.11 We openly speak of complex models for common epilepsies, but recent efforts have been largely in search of rare monogenic causes, or single common variants for heterogeneous phenotypic groupings. A change in research strategy towards use of more specific phenotypes (that are guided by family studies of phenotype coaggregation in epilepsy syndromes, or by endophenotypes), and modelling of complexity in studies of the genetic architecture of these phenotypes,
would serve to reduce heterogeneity and identify genes for specific syndromes, seizures, and comorbid traits. Such studies, hand-in-hand with epigenetics and other omics methods, could offer a way to account for individual patient differences in presentation, comorbidity, and prognosis. *Deb K Pal, Lisa J Strug Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London SE5 8AF, UK (DKP); and Program in Genetics and Genome Biology, The Hospital for Sick Children and Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5G 0A4, Canada (LJS) [email protected] We declare no competing interests. Copyright © Pal et al. Open Access article distributed under the terms of CC-BY-NC-ND. 1
2
3 4
5 6
7 8
9
10
11
International League Against Epilepsy Consortium on Complex Epilepsies. Genetic determinants of common epilepsies: a meta-analysis of genomewide association studies. Lancet Neurol 2014; published online July 31. http://dx.doi.org/10.1016/S1474-4422(14)70171-1. EPICURE Consortium, EMINet Consortium, Steffens M, et al. Genome-wide association analysis of genetic generalized epilepsies implicates susceptibility loci at 1q43, 2p16.1, 2q22.3 and 17q21.32. Hum Mol Genet 2012; 21: 5359–72. Berkovic SF, Howell RA, Hay DA, Hopper JL. Epilepsies in twins: genetics of the major epilepsy syndromes. Ann Neurol 1998; 43: 435–45. Lesca G, Rudolf G, Bruneau N, et al. GRIN2A mutations in acquired epileptic aphasia and related childhood focal epilepsies and encephalopathies with speech and language dysfunction. Nat Genet 2013; 45: 1061–66. Ishida S, Picard F, Rudolf G, et al. Mutations of DEPDC5 cause autosomal dominant focal epilepsies. Nat Genet 2013; 45: 552–55. Han B, Eskin E. Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am J Hum Genet 2011; 88: 586–98. Cossette P, Liu L, Brisebois K, et al. Mutation of GABRA1 in an autosomal dominant form of juvenile myoclonic epilepsy. Nat Genet 2002; 31: 184–89. Sun L, Rommens JM, Corvol H, et al. Multiple apical plasma membrane constituents are associated with susceptibility to meconium ileus in individuals with cystic fibrosis. Nat Genet 2012; 44: 562–69. O’Muircheartaigh J, Vollmar C, Barker GJ, et al. Abnormal thalamocortical structural and functional connectivity in juvenile myoclonic epilepsy. Brain 2012; 135: 3635–44. Vounou M, Nichols TE, Montana G, Alzheimer’s Disease Neuroimaging I. Discovering genetic associations with high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach. NeuroImage 2010; 53: 1147–59. Durner M, Keddache MA, Tomasini L, et al. Genome scan of idiopathic generalised epilepsy: evidence for major susceptibility gene and modifying genes influencing the seizure type. Ann Neurol 2001; 49: 328–35.
Lost in space: sleep Published Online August 8, 2014 http://dx.doi.org/10.1016/ S1474-4422(14)70176-0 See Articles page 904
860
Space is one of the most hostile environments. Sufficient sleep duration and quality are crucial to ensure performance and prevent fatal errors and accidents in space. Data on astronauts’ sleep in space are scarce, but in The Lancet Neurology, Laura Barger and colleagues1
report findings from their study assessing 4267 days of actigraphically measured sleep in 85 astronauts during Space Shuttle or International Space Station (ISS) missions. Sleep averaged 5·96 h (SD 0·56) during shuttle missions, 6·09 h (0·67) during ISS missions, and www.thelancet.com/neurology Vol 13 September 2014
Comment
www.thelancet.com/neurology Vol 13 September 2014
3–4 months, sedentariness and sleep time increased in most crew members, presumably due to the monotony of confinement and to reduced real-time communications and control of the crew by mission control.6 This trend reversed during the final 3 months of the mission as the crew members simulated approaching Earth. Two crew members reported persistent poor sleep quality throughout the mission,7 and another was not entrained to the 24 h day, but was behaviourally free-running with a near 25 h sleep– wake cycle; this behaviour is likewise noted in Antarctic winter-over8 and can partly be explained by inadequate timing, intensity, and spectral composition of light exposure for circadian entrainment. Once astronauts land on Mars, they will also have to entrain to the 24·66 h Martian sol.9 Barger and colleagues used unobtrusive actigraphy to estimate sleep time in space objectively. Studies of the physiology of sleep stages and the intensity of sleep homeostatic responses in space are necessary to answer the important question of whether spaceflight reduces the need for sleep and therefore the ability to sleep, or whether it reduces the ability to sleep but not the need for sleep. The answers also require measurement of neurobehavioural performance in space. A study that surveyed sleep times and obtained data for more than 2000 in-flight Psychomotor Vigilance Tests10 in 24 astronauts on the ISS has just been completed and might provide new insights.11 Sleep is pervasive among complex animals on Earth, and vital to the brain and body. We do not know what will happen to sleep or the biological functions it serves when human beings stay in space for a prolonged period of time. Space exploration requires that we answer that fundamental question.
NASA/Science Photo Library
less than 6·5 h pre-launch. Chronic restriction of sleep to a similar extent has been shown to increase neurobehavioural performance deficits2 and promote negative health outcomes.3 Moreover, chronic sleep restriction should increase sleep propensity and promote consolidated sleep;2 however, astronauts reported use of sleep-promoting drugs (mostly zolpidem) on 500 (52%) of 963 in-flight shuttle nights and in 96 (11%) of 852 ISS sleep logs, with marginal benefits for sleep duration, efficiency, and quality. Research into how sleep drugs affect astronaut performance when awakened for an emergency is underway at Johnson Space Center (Houston, TX, USA).4 Factors that can adversely affect sleep are prevalent in space, and include noise, physical discomfort, non24 h light–dark cycles, hypoxia and hypercapnia, acute operational shifts in sleep timing (so-called slam shifts), and psychological factors related to living in an isolated, confined, and extreme environment. Microgravity requires astronauts to sleep in bags tethered to a wall; it causes back pain in some astronauts and can result in fluid shifts associated with increased intracranial pressure and visual impairment.5 High workload during pre-mission training (including repeated transmeridian travel) and during spaceflight can contribute to chronic sleep curtailment and use of sleep-promoting drugs. On the ISS, maintenance and research tasks often take longer than scheduled, and astronauts can run substantially behind at the end of the day. This delay can contribute to sleep restriction if astronauts use some of the scheduled sleep time for personal and private activities instead. Thus, astronauts might use sleep drugs to ensure they get sleep in the restricted time available for it. Astronauts typically spend 6 months on the ISS, but 12-month missions are planned. However, space exploration to Mars will require unprecedented time in space—probably beyond 500 days with current propulsion technology. Only four people have consecutively lived and worked for more than 1 year in space; as such, how sleep and behavioural health will be affected during space exploration is poorly understood. Results from a 520-day simulated mission to Mars that did not involve microgravity suggest that sleep during exploration missions might be affected in different ways compared with sleep during high-tempo shuttle and ISS missions.6,7 After an initial period of
*Mathias Basner, David F Dinges Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA19104-6021, USA [email protected] MB and DFD report grants from NASA and the National Space Biomedical Research Institute for topics related to the submitted work, and grants from US National Institutes of Health the US Office of Naval Research, outside the submitted work. 1
Barger LK, Flynn-Evans EE, Kubey A, et al. Prevalence of sleep deficiency and use of hypnotic drugs among astronauts before, during, and after spaceflight: an observational study. Lancet Neurol 2014; published online Aug 8. http://dx.doi.org/10.1016/S1474-4422(14)70122-X.
861
Comment
2
3
4
5
6
Van Dongen HP, Maislin G, Mullington JM, Dinges DF. The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep 2003; 26: 117–26. Schmid SM, Hallschmid M, Schultes B. The metabolic burden of sleep loss. Lancet Diabetes Endocrinol 2014; published online March 25. http://dx.doi. org/10.1016/S2213-8587(14)70012-9. National Aeronautics and Space Administration (NASA). Operational ground testing protocol to optimize astronaut sleep medication efficacy and individual effects (Sleep_Meds_Phase_II). July 15, 2014. http://lsda.jsc.nasa. gov/scripts/experiment/exper.aspx?exp_index=2104 (accessed Aug 1, 2014). Mader TH, Gibson CR, Pass AF, et al. Optic disc edema, globe flattening, choroidal folds, and hyperopic shifts observed in astronauts after longduration space flight. Ophthalmology 2011; 118: 2058–69. Basner M, Dinges DF, Mollicone D, et al. Mars 520-d mission simulation reveals protracted crew hypokinesis and alterations of sleep duration and timing. Proc Natl Acad Sci USA 2013; 110: 2635–40.
7
8 9
10
11
Basner M, Dinges DF, Mollicone DJ, et al. Psychological and behavioral changes during confinement in a 520-day simulated interplanetary mission to mars. PLoS One 2014; 9: e93298. Arendt J. Biological rhythms during residence in polar regions. Chronobiol Int 2012; 29: 379–94. Barger LK, Sullivan JP, Vincent AS, et al. Learning to live on a Mars day: fatigue countermeasures during the Phoenix Mars Lander mission. Sleep 2012; 35: 1423–35. Basner M, Mollicone DJ, Dinges DF. Validity and sensitivity of a brief Psychomotor Vigilance Test (PVT-B) to total and partial sleep deprivation. Acta Astronautica 2011; 69: 949–59. NASA. Psychomotor Vigilance Test (PVT) on ISS (Reaction). July 15, 2014. http://lsda.jsc.nasa.gov/scripts/experiment/exper.aspx?exp_index=1490 (accessed Aug 1, 2014).
Epilepsy: lost in translation Published Online August 11, 2014 http://dx.doi.org/10.1016/ S1474-4422(14)70125-5 See Personal View page 949
862
The Personal View by Simonato and colleagues1 was overdue, but it falls short of what is needed. Is epilepsy truly a disorder that can be easily defined? Epilepsy is a brain state characterised by its ability to generate seizures more easily than can a healthy brain.2 Thus, in contrast to many other diseases, epilepsy is characterised by a symptom—the epileptic seizure—which can be viewed as the common denominator for the various types of epilepsy. As such, epilepsy cannot be compared with other neurological disorders that have shown good progress by improvements in translational research, such as multiple sclerosis. Moreover, although seizures and epilepsies in animals can be generated easily and many models of epilepsy exist, their relevance for human epilepsies is open to question. Epilepsy has two facets: first, the seizure symptom; and second, the cause or process leading to epilepsy as a chronic state (the epileptogenicity) of the brain. Epilepsies are treated primarily with anticonvulsive drugs, which are ineffective in about a third of cases. Generally, all the years of translational research have resulted in little progress in terms of efficacy. In focal epilepsies, results of controlled, blinded studies have not shown superiority of monotherapy compared with the old standby carbamazepine.3,4 And when high-quality studies are taken into account for the add-on design, efficacy is lost with the newer anticonvulsive drugs because of an increase in the placebo response.5,6 Disease-modifying therapy (the prevention of an epilepsy after an initial, potentially epileptogenic hit) is an important concept, but with only a small amount
of experimental background and no real measure of whether this type of therapy can be proven to work in humans. The use of experimental post-traumatic epilepsy as a model for a disease-modifying therapy ignores two facts for translation: the complexity of human posttraumatic epilepsy and efforts to reduce its incidence; and Andres Salazar’s experience in Vietnam veterans, who were often uncompliant for preventive therapy but compliant for a therapy after the first seizure.7 The search for biomarkers to predict a developing epilepsy is intense. The MRI screening of all children with febrile convulsions to identify those at risk is not only an economic challenge but also an ethical one, because children need to be anaesthetised for many MRI scans over the years.8 Additionally, power calculations will show the immense logistical effort necessary to establish whether or not one substance is anti-epileptogenic (or disease-modifying). When selecting and using epilepsy models, one must ask for which group of epilepsy patients do we want to provide better treatment? The answer should be those who are pharmacoresistant. This group, comprising about a third of patients with epilepsy, is badly characterised. In many cases, we do not know the phenotype (ie, the epilepsy is of unknown cause or cryptogenic), nor do we know the degree of pharmacoresistance (which might be slight or amount to no response at all). How can we create models when the epilepsy type with which we are dealing is an unknown? Glauser’s study on childhood absence epilepsy has shown that identification of the epilepsy phenotype can provide answers in treatment trials and www.thelancet.com/neurology Vol 13 September 2014
investigation. In any event, there is contribution at the identified loci across more than one cohort, but the extent and nature of the overall association remains unclear. Heterogeneity is often the price paid for assembly of huge sample sizes for GWAS or meta-analyses. However, the power of GWAS can be boosted not only by increasing sample size, but also in creative ways that exploit previous biological knowledge. For example, findings from many studies have suggested an important role for GABAA receptor function in genetic generalised epilepsies,7 and techniques such as genomewide pathway and hypothesis-driven analyses8 can be exploited to test such specific hypotheses and generate potential therapeutic targets. Another approach that sidesteps the complications of phenotype integrity is the use of imaging endophenotypes; changes in structural connectivity and grey matter volume have already been identified in juvenile myoclonic epilepsy.9 Quantitative measures closer to the underlying biology than the clinical phenotype might also reduce required sample sizes to the hundreds with newly developed mathematical methods,10 while improving specificity of findings. Knowledge of the genetics of common epilepsies is in need of integration. Strong but rare risk factors in the form of recurrent copy-number variation are known, and researchers have understood for some time that there are distinct genetic influences on absence and myoclonic seizure types within the genetic generalised epilepsies.11 We openly speak of complex models for common epilepsies, but recent efforts have been largely in search of rare monogenic causes, or single common variants for heterogeneous phenotypic groupings. A change in research strategy towards use of more specific phenotypes (that are guided by family studies of phenotype coaggregation in epilepsy syndromes, or by endophenotypes), and modelling of complexity in studies of the genetic architecture of these phenotypes,
would serve to reduce heterogeneity and identify genes for specific syndromes, seizures, and comorbid traits. Such studies, hand-in-hand with epigenetics and other omics methods, could offer a way to account for individual patient differences in presentation, comorbidity, and prognosis. *Deb K Pal, Lisa J Strug Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London SE5 8AF, UK (DKP); and Program in Genetics and Genome Biology, The Hospital for Sick Children and Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5G 0A4, Canada (LJS) [email protected] We declare no competing interests. Copyright © Pal et al. Open Access article distributed under the terms of CC-BY-NC-ND. 1
2
3 4
5 6
7 8
9
10
11
International League Against Epilepsy Consortium on Complex Epilepsies. Genetic determinants of common epilepsies: a meta-analysis of genomewide association studies. Lancet Neurol 2014; published online July 31. http://dx.doi.org/10.1016/S1474-4422(14)70171-1. EPICURE Consortium, EMINet Consortium, Steffens M, et al. Genome-wide association analysis of genetic generalized epilepsies implicates susceptibility loci at 1q43, 2p16.1, 2q22.3 and 17q21.32. Hum Mol Genet 2012; 21: 5359–72. Berkovic SF, Howell RA, Hay DA, Hopper JL. Epilepsies in twins: genetics of the major epilepsy syndromes. Ann Neurol 1998; 43: 435–45. Lesca G, Rudolf G, Bruneau N, et al. GRIN2A mutations in acquired epileptic aphasia and related childhood focal epilepsies and encephalopathies with speech and language dysfunction. Nat Genet 2013; 45: 1061–66. Ishida S, Picard F, Rudolf G, et al. Mutations of DEPDC5 cause autosomal dominant focal epilepsies. Nat Genet 2013; 45: 552–55. Han B, Eskin E. Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am J Hum Genet 2011; 88: 586–98. Cossette P, Liu L, Brisebois K, et al. Mutation of GABRA1 in an autosomal dominant form of juvenile myoclonic epilepsy. Nat Genet 2002; 31: 184–89. Sun L, Rommens JM, Corvol H, et al. Multiple apical plasma membrane constituents are associated with susceptibility to meconium ileus in individuals with cystic fibrosis. Nat Genet 2012; 44: 562–69. O’Muircheartaigh J, Vollmar C, Barker GJ, et al. Abnormal thalamocortical structural and functional connectivity in juvenile myoclonic epilepsy. Brain 2012; 135: 3635–44. Vounou M, Nichols TE, Montana G, Alzheimer’s Disease Neuroimaging I. Discovering genetic associations with high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach. NeuroImage 2010; 53: 1147–59. Durner M, Keddache MA, Tomasini L, et al. Genome scan of idiopathic generalised epilepsy: evidence for major susceptibility gene and modifying genes influencing the seizure type. Ann Neurol 2001; 49: 328–35.
Lost in space: sleep Published Online August 8, 2014 http://dx.doi.org/10.1016/ S1474-4422(14)70176-0 See Articles page 904
860
Space is one of the most hostile environments. Sufficient sleep duration and quality are crucial to ensure performance and prevent fatal errors and accidents in space. Data on astronauts’ sleep in space are scarce, but in The Lancet Neurology, Laura Barger and colleagues1
report findings from their study assessing 4267 days of actigraphically measured sleep in 85 astronauts during Space Shuttle or International Space Station (ISS) missions. Sleep averaged 5·96 h (SD 0·56) during shuttle missions, 6·09 h (0·67) during ISS missions, and www.thelancet.com/neurology Vol 13 September 2014
Comment
www.thelancet.com/neurology Vol 13 September 2014
3–4 months, sedentariness and sleep time increased in most crew members, presumably due to the monotony of confinement and to reduced real-time communications and control of the crew by mission control.6 This trend reversed during the final 3 months of the mission as the crew members simulated approaching Earth. Two crew members reported persistent poor sleep quality throughout the mission,7 and another was not entrained to the 24 h day, but was behaviourally free-running with a near 25 h sleep– wake cycle; this behaviour is likewise noted in Antarctic winter-over8 and can partly be explained by inadequate timing, intensity, and spectral composition of light exposure for circadian entrainment. Once astronauts land on Mars, they will also have to entrain to the 24·66 h Martian sol.9 Barger and colleagues used unobtrusive actigraphy to estimate sleep time in space objectively. Studies of the physiology of sleep stages and the intensity of sleep homeostatic responses in space are necessary to answer the important question of whether spaceflight reduces the need for sleep and therefore the ability to sleep, or whether it reduces the ability to sleep but not the need for sleep. The answers also require measurement of neurobehavioural performance in space. A study that surveyed sleep times and obtained data for more than 2000 in-flight Psychomotor Vigilance Tests10 in 24 astronauts on the ISS has just been completed and might provide new insights.11 Sleep is pervasive among complex animals on Earth, and vital to the brain and body. We do not know what will happen to sleep or the biological functions it serves when human beings stay in space for a prolonged period of time. Space exploration requires that we answer that fundamental question.
NASA/Science Photo Library
less than 6·5 h pre-launch. Chronic restriction of sleep to a similar extent has been shown to increase neurobehavioural performance deficits2 and promote negative health outcomes.3 Moreover, chronic sleep restriction should increase sleep propensity and promote consolidated sleep;2 however, astronauts reported use of sleep-promoting drugs (mostly zolpidem) on 500 (52%) of 963 in-flight shuttle nights and in 96 (11%) of 852 ISS sleep logs, with marginal benefits for sleep duration, efficiency, and quality. Research into how sleep drugs affect astronaut performance when awakened for an emergency is underway at Johnson Space Center (Houston, TX, USA).4 Factors that can adversely affect sleep are prevalent in space, and include noise, physical discomfort, non24 h light–dark cycles, hypoxia and hypercapnia, acute operational shifts in sleep timing (so-called slam shifts), and psychological factors related to living in an isolated, confined, and extreme environment. Microgravity requires astronauts to sleep in bags tethered to a wall; it causes back pain in some astronauts and can result in fluid shifts associated with increased intracranial pressure and visual impairment.5 High workload during pre-mission training (including repeated transmeridian travel) and during spaceflight can contribute to chronic sleep curtailment and use of sleep-promoting drugs. On the ISS, maintenance and research tasks often take longer than scheduled, and astronauts can run substantially behind at the end of the day. This delay can contribute to sleep restriction if astronauts use some of the scheduled sleep time for personal and private activities instead. Thus, astronauts might use sleep drugs to ensure they get sleep in the restricted time available for it. Astronauts typically spend 6 months on the ISS, but 12-month missions are planned. However, space exploration to Mars will require unprecedented time in space—probably beyond 500 days with current propulsion technology. Only four people have consecutively lived and worked for more than 1 year in space; as such, how sleep and behavioural health will be affected during space exploration is poorly understood. Results from a 520-day simulated mission to Mars that did not involve microgravity suggest that sleep during exploration missions might be affected in different ways compared with sleep during high-tempo shuttle and ISS missions.6,7 After an initial period of
*Mathias Basner, David F Dinges Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA19104-6021, USA [email protected] MB and DFD report grants from NASA and the National Space Biomedical Research Institute for topics related to the submitted work, and grants from US National Institutes of Health the US Office of Naval Research, outside the submitted work. 1
Barger LK, Flynn-Evans EE, Kubey A, et al. Prevalence of sleep deficiency and use of hypnotic drugs among astronauts before, during, and after spaceflight: an observational study. Lancet Neurol 2014; published online Aug 8. http://dx.doi.org/10.1016/S1474-4422(14)70122-X.
861
Comment
2
3
4
5
6
Van Dongen HP, Maislin G, Mullington JM, Dinges DF. The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep 2003; 26: 117–26. Schmid SM, Hallschmid M, Schultes B. The metabolic burden of sleep loss. Lancet Diabetes Endocrinol 2014; published online March 25. http://dx.doi. org/10.1016/S2213-8587(14)70012-9. National Aeronautics and Space Administration (NASA). Operational ground testing protocol to optimize astronaut sleep medication efficacy and individual effects (Sleep_Meds_Phase_II). July 15, 2014. http://lsda.jsc.nasa. gov/scripts/experiment/exper.aspx?exp_index=2104 (accessed Aug 1, 2014). Mader TH, Gibson CR, Pass AF, et al. Optic disc edema, globe flattening, choroidal folds, and hyperopic shifts observed in astronauts after longduration space flight. Ophthalmology 2011; 118: 2058–69. Basner M, Dinges DF, Mollicone D, et al. Mars 520-d mission simulation reveals protracted crew hypokinesis and alterations of sleep duration and timing. Proc Natl Acad Sci USA 2013; 110: 2635–40.
7
8 9
10
11
Basner M, Dinges DF, Mollicone DJ, et al. Psychological and behavioral changes during confinement in a 520-day simulated interplanetary mission to mars. PLoS One 2014; 9: e93298. Arendt J. Biological rhythms during residence in polar regions. Chronobiol Int 2012; 29: 379–94. Barger LK, Sullivan JP, Vincent AS, et al. Learning to live on a Mars day: fatigue countermeasures during the Phoenix Mars Lander mission. Sleep 2012; 35: 1423–35. Basner M, Mollicone DJ, Dinges DF. Validity and sensitivity of a brief Psychomotor Vigilance Test (PVT-B) to total and partial sleep deprivation. Acta Astronautica 2011; 69: 949–59. NASA. Psychomotor Vigilance Test (PVT) on ISS (Reaction). July 15, 2014. http://lsda.jsc.nasa.gov/scripts/experiment/exper.aspx?exp_index=1490 (accessed Aug 1, 2014).
Epilepsy: lost in translation Published Online August 11, 2014 http://dx.doi.org/10.1016/ S1474-4422(14)70125-5 See Personal View page 949
862
The Personal View by Simonato and colleagues1 was overdue, but it falls short of what is needed. Is epilepsy truly a disorder that can be easily defined? Epilepsy is a brain state characterised by its ability to generate seizures more easily than can a healthy brain.2 Thus, in contrast to many other diseases, epilepsy is characterised by a symptom—the epileptic seizure—which can be viewed as the common denominator for the various types of epilepsy. As such, epilepsy cannot be compared with other neurological disorders that have shown good progress by improvements in translational research, such as multiple sclerosis. Moreover, although seizures and epilepsies in animals can be generated easily and many models of epilepsy exist, their relevance for human epilepsies is open to question. Epilepsy has two facets: first, the seizure symptom; and second, the cause or process leading to epilepsy as a chronic state (the epileptogenicity) of the brain. Epilepsies are treated primarily with anticonvulsive drugs, which are ineffective in about a third of cases. Generally, all the years of translational research have resulted in little progress in terms of efficacy. In focal epilepsies, results of controlled, blinded studies have not shown superiority of monotherapy compared with the old standby carbamazepine.3,4 And when high-quality studies are taken into account for the add-on design, efficacy is lost with the newer anticonvulsive drugs because of an increase in the placebo response.5,6 Disease-modifying therapy (the prevention of an epilepsy after an initial, potentially epileptogenic hit) is an important concept, but with only a small amount
of experimental background and no real measure of whether this type of therapy can be proven to work in humans. The use of experimental post-traumatic epilepsy as a model for a disease-modifying therapy ignores two facts for translation: the complexity of human posttraumatic epilepsy and efforts to reduce its incidence; and Andres Salazar’s experience in Vietnam veterans, who were often uncompliant for preventive therapy but compliant for a therapy after the first seizure.7 The search for biomarkers to predict a developing epilepsy is intense. The MRI screening of all children with febrile convulsions to identify those at risk is not only an economic challenge but also an ethical one, because children need to be anaesthetised for many MRI scans over the years.8 Additionally, power calculations will show the immense logistical effort necessary to establish whether or not one substance is anti-epileptogenic (or disease-modifying). When selecting and using epilepsy models, one must ask for which group of epilepsy patients do we want to provide better treatment? The answer should be those who are pharmacoresistant. This group, comprising about a third of patients with epilepsy, is badly characterised. In many cases, we do not know the phenotype (ie, the epilepsy is of unknown cause or cryptogenic), nor do we know the degree of pharmacoresistance (which might be slight or amount to no response at all). How can we create models when the epilepsy type with which we are dealing is an unknown? Glauser’s study on childhood absence epilepsy has shown that identification of the epilepsy phenotype can provide answers in treatment trials and www.thelancet.com/neurology Vol 13 September 2014
