Low-level lasers. Part 1. Shining a light on an unconventional treatment for autism

 

'Light enters, then a miracle happens, and good things come out!' (Quirk & Whelan, 2011*)

I'm occasionally asked to investigate weird interventions for children's neurodevelopmental conditions, and recently I've found myself immersed in the world of low-level laser treatments. The material I've dug up is not new - it's been around for some years, but has not been on my radar until now. 

A starting point is this 2018 press statement by Erchonia, a firm that makes low-level laser devices for quasi-medical interventions. 

They had tested a device that was supposed to reduce irritability in autistic children by applying low-level laser light to the temporal and posterior regions of the head (see Figure 1) for 5 minute sessions twice a week for 4 weeks.

Figure 1: sites of stimulation by low-level laser

 The study, which was reported here, was carefully designed as a randomized controlled trial. Half the children received a placebo intervention. Placebo and active laser devices were designed to look identical and both emitted light, and neither the child nor the person administering the treatment knew whether the active or placebo light was being used.

According to Erchonia “The results are so strong, nobody can argue them.” (sic). Alas, their confidence turned out to be misplaced.

The rationale given by Leisman et al (with my annotations in yellow in square brackets) is as follows: "LLLT promotes cell and neuronal repair (Dawood and Salman 2013) [This article is about wound healing, not neurons] and brain network rearrangement (Erlicher et al. 2002) [This is a study of rat cells in a dish] in many neurologic disorders identified with lesions in the hubs of default mode networks (Buckner et al. 2008)[This paper does not mention lasers]. LLLT facilitates a fast-track wound-healing (Dawood and Salman 2013) as mitochondria respond to light in the red and near-infrared spectrum (Quirk and Whelan 2011*)[review of near-infrared irradiation photobiomodulation that notes inadequate knowledge of mechanisma - see cartoon]. On the other hand, Erlicher et al. (2002) have demonstrated that weak light directs the leading edge of growth cones of a nerve [cells in a dish]. Therefore, when a light beam is positioned in front of a nerve’s leading edge, the neuron will move in the direction of the light and grow in length (Black et al. 2013 [rat cells in a dish]; Quirk and Whelan 2011). Nerve cells appear to thrive and grow in the presence of low-energy light, and we think that the effect seen here is associated with the rearrangement of connectivity."

I started out looking at the registration of the trial on ClinicalTrials.gov. This included a very thorough document that detailed a protocol and analysis plan, but there were some puzzling inconsistencies; I documented them here on PubPeer,  and subsequently a much more detailed critique was posted there by Florian Naudet and André Gillibert. Among other things, there was confusion about where the study was done. The registration document said it was done in Nazareth, Israel, which is where the first author, Gerry Leisman was based. But it also said that the PI was Calixto Machado, who is based in Havana, Cuba.

Elvira Cawthon, from Regulatory Insight, Inc, Tennessee was mentioned on the protocol as clinical consultant and study monitor. The role of the study monitor is specified as follows: 

"The study Monitor will assure that the investigator is executing the protocol as outlined and intended. This includes insuring that a signed informed consent form has been attained from each subject’s caregiver prior to commencing the protocol, that the study procedure protocol is administered as specified, and that all study evaluations and measurements are taken using the specified methods and correctly and fully recorded on the appropriate clinical case report forms."

This does not seem ideal, given that the study monitor was in Tennessee, and the study was conducted in either Nazareth or Havana. Accordingly, I contacted Ms Cawthon, who replied: 

"I can confirm that I performed statistical analysis on data from the clinical study you reference that was received from paper CRFs from Dr. Machado following completion of the trial. I was not directly involved in the recruitment, treatment, or outcomes assessment of the subjects whose data was recorded on those CRFs. I have not reviewed any of the articles you referenced below so I cannot attest to whether the data included was based on the analyses that I performed or not or comment on any of the discrepancies without further evaluation at this time."

I had copied Drs Leisman and Machado into my query, and Dr Leisman also replied. He stated:

"I am the senior author of the paper pertaining to a trial of low-level laser therapy in autism spectrum disorder.... I take full responsibility for the publication indicated above and vouch for having personally supervised the implementation of the project whose results were published under the following citation:

Leisman, G. Machado, C., Machado, Y, Chinchilla-Acosta, M. Effects of Low-Level Laser Therapy in Autism Spectrum Disorder. Advances in Experimental Medicine and Biology 2018:1116:111-130. DOI:10.1007/5584_2018_234. The publication is referenced in PubMed as: PMID: 29956199.

I hold a dual appointment at the University of Haifa and at the University of the Medical Sciences of Havana with the latter being "Professor Invitado" by the Ministry of Health of the Republic of Cuba. Ms. Elvira Walls served as the statistical consultant on this project."

However, Dr Leisman denied any knowledge of subsequent publications of follow-up data by Dr Machado. I asked if I could see the data from the Leisman et al study, and he provided a link to a data file on ResearchGate, the details of which I have put on PubPeer.

Alas, the data were amazing, but not in a good way. The main data came from five subscales of the Aberrant Behavior Checklist (ABC)**, which can be combined into a Global score. (There were a handful of typos in the dataset for the Global score, which I have corrected in the following analysis). For the placebo group, 15 of 19 children obtained exactly the same global score on all 4 sessions. Note that there is no restriction of range for this scale: reported scores range from 9 to 154. This pattern was also seen in the five individual subscales. You might think that is to be expected if the placebo intervention is ineffective, but that's not the case. Questionnaire measures such as that used here are never totally stable. In part this is because children's behaviour fluctuates. But even if the behaviour is constant, you expect to see some variability in responses, depending on how the rater interprets the scale of measurement. Furthermore, when study participants are selected because they have extreme scores on a measure, the tendency is for scores to improve on later testing - a phenomenon known as regression to the mean, Such unchanging scores are out of line with anything I have ever come across in the intervention literature. If we turn to the treated group, we see that 20 of 21 children showed a progressive decline in global scores (i.e. improvement), with each measurement improving from the previous one over 4 sessions. This again is just not credible because we'd expect some fluctuation in children's behaviour as well as variable ratings due to error of measurement. These results were judged to be abnormal in a further commentary by Gillibert and Naudet on PubPeer. They also noted that the statistical distribution of scores was highly improbable, with far more even than odd numbers.

Although Dr Machado has been copied into my correspondence, he has not responded to queries. Remember, he was PI for the study in Cuba, and he is first author on a follow-up study from which Dr Leisman dissociated himself. Indeed, I subsequently found that there were no fewer than three follow-up reports, all appearing in a strange journal whose DOIs did not appear to be genuine: 

Machado, C., Machado, Y., Chinchilla, M., & Machado, Yazmina. (2019a). Follow-up assessment of autistic children 6 months after finishing low lever (sic) laser therapy. Internet Journal of Neurology, 21(1). https://doi.org/10.5580/IJN.54101 (available from https://ispub.com/IJN/21/1/54101).

Machado, C., Machado, Y., Chinchilla, M., & Machado, Yazmina. (2019b). Twelve months follow-up comparison between autistic children vs. Initial placebo (treated) groups. Internet Journal of Neurology, 21(2). https://doi.org/10.5580/IJN.54812 (available from https://ispub.com/IJN/21/2/54812).

Machado, C., Machado, Y., Chinchilla, M., & Machado, Yazmina. (2020). Follow-up assessment of autistic children 12 months after finishing low lever (sic) laser therapy. Internet Journal of Neurology, 21(2). https://doi.org/10.5580/IJN.54809 (available from available from https://ispub.com/IJN/21/2/54809)

The 2019a paper starts by talking of a study of anatomic and functional brain connectivity in 21 children, but then segues to an extended follow-up (6 months) of the 21 treated and 19 placebo children from the Leisman et al study. The Leisman et al study is mentioned but not adequately referenced. Remarkably, all the original participants participated in the follow-up. The same trend as before continued: the placebo group stagnated, whereas the treated group continue to improve up to 6 months later, even though they received no further active treatment after the initial 4 week period. The 2020 Abstract reported a further follow-up to 12 months. The huge group difference was sustained (see Figure 2). Three of the treated group were now reported as scoring in the normal range on a measure of clinical impairment. 

Figure 2. Chart 1 from Machado et al 2020

 

In the 2019b paper, it is reported that, after the stunning success of the initial phase of the study, the placebo group were offered the intervention, and all took part, whereupon they proceeded to make an almost identical amount of remarkable progress on all five subscales, as well as the global scale (see Figure 3). We might expect the 'baseline' scores of the cross-over group to correspond to the scores reported at the final follow-up (as placebo group prior to cross-over) but they don't. 

Figure 3: Chart 2 of Machado et al 2019b

I checked for other Erchonia studies on clinicaltrials.gov. Another study, virtually identical except for the age range, was registered in 2020 with Dr Leon Morales-Quezada of Spaulding Rehabilitation Hospital, Boston as Principal Investigator.  Comments in the documents suggest this was conducted after Erchonia failed to get the desired FDA approval. Although I have not found a published report of this second trial, I found a recruitment advertisement, which confusingly cites the NCT registration number of the 2013 study. Some summary results are included on clinicaltrials.gov, and they are strikingly different from the Leisman et al trial, with no indication of any meaningful difference between active and placebo groups in the final outcome measure, and both groups showing some improvement. I have requested fuller data from Elvira Cawthon (listed as results point of contact) with cc. to Dr Morales-Quezada and will update this post if I hear back.

It would appear that at one level this is a positive story, because it shows the regulatory system working. We do not know why FDA rejected Erchonia's request for 510k Market Clearance, but the fact that they did so might indicate that they were unimpressed by the data provided by Leisman and Machado. The fact that Machado et al reported their three follow-up studies in what appears to be an unregistered journal suggests they had difficulty persuading regular journals that the findings were legitimate. If eight 5-minute sessions with a low-level laser pointed at the head really could dramatically improve the function of children with autism 12 months later, one would imagine that Nature, Cell and Science would be scrambling to publish the articles. On the other hand, any device that has the potential to stimulate neuronal growth might also ring alarm bells in terms of potential for harm.

Use of low-level lasers to treat autism is only part of the story. Questions remain about the role of Regulatory Insight, Inc., whose statistician apparently failed to notice anything strange about the data from the first autism study. In another post, I plan to look at cases where the same organisation was involved in monitoring and analysing trials of Erchonia laser devices for other conditions such as cellulite, pain, and hearing loss.

Notes

* Quirk, B. J., & Whelan, H. T. (2011). Near-infrared irradiation photobiomodulation: The need for basic science. Photomedicine and Laser Surgery, 29(3), 143–144. https://doi.org/10.1089/pho.2011.3014. This article states "clinical uses of NIR-PBM have been studied in such diverse areas as wound healing, oral mucositis, and retinal toxicity. In addition, NIR-PBM is being considered for study in connection with areas such as aging and neural degenerative diseases (Parkinson's disease in particular). One thing that is missing in all of these pre-clinical and clinical studies is a proper investigation into the basic science of the NIR-PBM phenomenon. Although there is much discussion of the uses of NIR, there is very little on how it actually works. As far as explaining what really happens, we are basically left to resort to saying 'light enters, then a miracle happens, and good things come out!' Clearly, this is insufficient, if for no other reason than our own intellectual curiosity." 

**Aman, M. G., Singh, N. N., Stewart, A. W., & Field, C. J. (1985). The aberrant behavior checklist: A behavior rating scale for the assessment of treatment effects. American Journal of Mental Deficiency, 89(5), 485–491. N. B. this is different from the Autism Behavior Checklist which is a commonly used autism assessment. 

Percentages, quasi statistics and bad arguments

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Percentages have been much in the news lately. First, we have a PLOS One paper by John Ioannidis and his colleagues which noted that less than one per cent of all publishing scientists in the period from 1996 to 2011 published something in each and every year of this 16-year period.

Then there was have a trailer for a wonderfully silly forthcoming film, Lucy, in which Scarlett Johansson suffers from a drug overdose that leads her to learn Chinese in an hour and develop an uncanny ability to make men fall over by merely pouting at them. Morgan Freeman plays a top neuroscientist who explains that whereas the rest of us use a mere ten per cent of our brain capacity, Johansson's character has access to a full hundred per cent of her brain.

And today I've just read an opinion piece in Prospect Magazine by the usually clear-thinking philosopher, A. C. Grayling, which states: Neuropsychology tells us that more than ninety per cent of mental computation happens below the level of awareness.

Examples like these can be used to demonstrate just how careful you need to be when interpreting percentages. There are two issues. For a start, a percentage is uninterpretable unless you know the origin of the denominator (i.e., the total number of cases that the percentage is based on).  I'm sure the paper by Ioannidis and colleagues is competently conducted, but the result seems far less surprising when you realise that the 'less than one per cent' figure was obtained using a denominator based on all authors mentioned on all papers during the target period. As Ioannidis et al noted, this will include a miscellaneous bunch of people, including those who are unsuccessful at gaining research funding or in getting papers published, those taking career breaks, people who are trainees or research assistants, those working in disciplines where it is normal to publish infrequently, and those who fit in  research activity around clinical responsibilities. Presumably it also includes those who have died, retired, or left the field in the study period.

So if you are someone who publishes regularly, and are feeling smug at your rarity value, you might want to rethink. In fact, given the heterogeneity of the group on whom the numerator is based, I'm not sure what conclusions to draw from this paper. Ioannidis et al noted that those who publish frequently also get cited more frequently – even after taking into account number of publications and concluded that the stability and continuity of the publishing scientific workforce may have important implications for the efficiency of science. But what one should actually do with this information is unclear. The authors suggest that one option is to give more opportunities to younger scientists so that they can join the elite group who publish regularly. However, I suspect that's not how the study will be interpreted: instead, we'll have university administrators adding 'continuity of publishing record' to their set of metrics for recruiting new staff, leading to even more extreme pressure to publish quickly, rather than taking time to reflect on results. A dismal thought indeed.

The other two examples that I cited are worse still. It's not that they have a misleading denominator: as far as one can tell, they don't have a denominator at all.  In effect, they are quasi-statistics. Since the publication of the Lucy trailer, neuroscientists have stepped up to argue that of course we use much more than ten per cent of our brains, and to note that the origin of this mythical statistic is hard to locate (see, for instance here and here). I'd argue there's an even bigger problem – the statement can't be evaluated as accurate or inaccurate without defining what scale is being adopted to quantify 'brain use'. Does it refer to cells, neural networks, white matter, grey matter, or brain regions? Are we only 'using' these if there is measurable activity? And is that activity measured by neural oscillations, synaptic firing, a haemodynamic response or something else?

In a similar vein, in the absence of any supporting reference for the Grayling quote, it remains opaque to me how you'd measure 'mental computation' and then subdivide it into the conscious and the unconscious. Sure, he's right that our brains carry out many computations of which we have no explicit awareness. Language is a classic case – I assume most readers would have no difficulty turning a sentence like You wanted to eat the apples that she gave you into a negative form (You didn't want to eat the apples that she gave you) or a question (Did you want to eat the apples that she gave you?) but unless you are a linguist, you will have difficulty explaining how you did this. I don't take issue with Grayling's main point, but I am surprised that an expert philosopher should introduce a precise number into the argument, when it can readily be shown to be meaningless.

The main point here is that we are readily impressed by numbers. A percentage seems to imply that there is a body of evidence on which a statement is based. But we need to treat percentages with suspicion; unless we can identify the numerator and denominator from which they are calculated, they are likely to just be fancy ways of trying to persuade us into giving more weight to an argument than it deserves.

Raising awareness of language learning impairments

A couple of years ago I did a Google search for ‘Specific language impairment’. I was  appalled by what I found. The top hit was a video by a chiropractor who explained he’d read a paper about neurological basis of language difficulties; he proceeded to mangle its contents, concluding that cranial osteopathy would help affected children.

I’ve previously described how I got together with colleagues in 2012 to try and remedy this situation, culminating in a campaign for Raising Awareness of Language Learning Impairments (RALLI). The practicalities have sometimes been challenging but I’m pleased to say that the collection of videos on our RALLI site has now attracted over 90,000 hits, providing an accessible and evidence-based source of information about developmental language impairments. As well as research-based films we have videos with practical information for parents, children and teachers.

So here, for those of you interested in this topic, is an index of what we have so far:

Background to RALLI

• What is RALLI?
• Why we've launched RALLI
• What is SLI?
• Meet Seb

Research topics

• Identification of Specific Language Impairment Video Slides References 
• How specific is SLI? Video Slides References 
• Speech, language and communication Video Slides 
• What is Pragmatic Language Impairment? Video Slides 
• How common is specific language impairment? Video Slides References 
• When should we be concerned about late-talkers? Video Slides References 
• SLI and Autism Video Slides References 
• Auditory processing disorder (APD) and language impairment Video Slides References 
• The causes of Specific Language Impairment Video Slides References 
• Specific language impairment and the brain Video Slides References 
• An extra X or Y chromosome: a rare cause of language impairment Video Slides References 
• SLI & reading: 1. Decoding (phonics) Video Slides References 
• SLI and reading: 2. Understanding written language Video Slides References 
•  Reading intervention for children with language impairments Video  References 
• Friendships in teenagers with SLI Video Slides 
• La Amistad y el TEL (Spanish) Video Slides 

Information for teachers

• Signs of SLI
• Literacy difficulties and SLI
• Looking behind behaviour
• Teacher tips: practical strategies
• Teacher tips: adapting your language
• What is the Better Communication Research Programme?

Support for parents and children

• Finding my strengths
• A Parent's Perspective of SLI: Meet Suzanne.
• You are not alone
• It's OK to ask for help
• Getting support
• Helping your child
• Sophie's Story: SLI in adulthood
• Talking about friendships: Megan and Eleshia
• Supporting families: the role of Afasic
• Speech and language therapy: Helping Michael  
• It's not your fault
• Things I wish I'd known: a parent's perspective 

International

• O que é o DEL? (Portuguese)
• 什麼是特定型語言障礙? (Mandarin)
• ¿Qué es el TEL? (Spanish)
• Qu'est-ce que le TSL? (French)
• Was sind spezifische Sprachentwicklungsstörungen? (German)
• Wat is een taalstoornis? (Dutch)
• 甚麽是特殊語言障礙（廣東話版）(Cantonese)
• Che cos'é il DSL? (Italian)
• Beth yw NIP? (Welsh)
• Τι είναι η Ειδική Γλωσσική Διαταραχή ( Greek)  

     Spanish translations/subtitled versions

• ¿Porqué hemos lanzado la campaña RALLI?
• Introducción a Spanish RALLI
• No es tu culpa para niños

Reference  
Bishop, D. V. M., Clark, B., Conti-Ramsden, G., Norbury, C., & Snowling, M. J. (2012). RALLI: An internet campaign for raising awareness of language learning impairments Child Language Teaching & Therapy, 28 (3), 259-262 DOI: 10.1177/0265659012459467

Genes, brains and lateralisation: how solid is the evidence?

If there were a dictionary of famous neurological quotes, “Nous parlons avec l'hémisphère gauche” by Paul Broca (1865) would be up there among the top hits. Broca’s realisation that the two sides of the brain are functionally distinct was a landmark observation. It was based on a rather small series of patients, but has since been confirmed in numerous studies. After localised brain injury, aphasia (language impairment) is far more likely after damage to the left side than the right side. And nowadays, we can visualise greater activation of the left side in neurologically intact people as they do language tasks in a brain scanner.

There are many fascinating features of cerebral lateralisation, but I’m going to focus here on just one specific question: what do we know about genetic influences on brain asymmetry in humans?  There are really two questions here: (1) how do genes lead to asymmetric brain development? (2) are there genetic variants that can account for individual variation?  – e.g. the fact that a minority of people have right hemisphere language. I hope to return to question 2 at a later date, but for now, I’ll focus on question 1, because after reading a key paper on this topic, I've struck a whole load of questions that I can’t answer. I’m hoping that some of my genetically-sophisticated readers will be able to help me out.

It’s sometimes stated that cerebral lateralisation is a uniquely human trait, but that’s not true. Nevertheless, we are very different from our primate cousins, insofar as we show a strong population bias to right-handedness, and most people have left-hemisphere language. There are other species which show consistent brain asymmetries, but they are a long way from us on the evolutionary tree. Most of the research I’ve come across is on nematode worms, zebrafish, or songbirds. This is a long way from my comfort zone, but there are some nice reviews that document research on genes influencing asymmetries in these creatures (e.g. here and here). It’s clear, though, that it’s complicated: not just in terms of the range of genes involved, but in the different ways they can generate asymmetry. And there don't seem to be obvious parallels to human brain development.

Despite all this uncertainty, there’s growing evidence that brain asymmetries are present from very early on in life –in newborn babies and even in foetal life. This field is still in its infancy (forgive the pun), and samples of babies are typically too small to reveal reliable relationships between structure and function. Nevertheless, there’s considerable interest in the idea that physical differences between the two sides of the brain may be an indicator of potential for language development.

A particularly exciting topic is genetic determinants of cerebral lateralisation. One study in particular, by Sun et al made a splash when it was published in Science in 2005, since when it has attracted over 140 citations. The authors looked for asymmetric gene expression in post mortem embryonic brains. Their conclusions have been widely cited: “We identified and verified 27 differentially expressed genes, which suggests that human cortical asymmetry is accompanied by early, marked transcriptional asymmetries.” The fact that several different genes were identified was of particular interest to me, because genetic theories by neuropsychologists have typically assumed that just a single gene is responsible for human cerebral lateralisation. I’ve never found a single-gene theory plausible, so I was all too ready to accept evidence that involved multiple genes. But first I wanted to drill down deeper into the methods to find out how the authors reached their conclusions. I’m a psychologist, not a geneticist, and so this was rather challenging. But my deeper reading raised a number of questions.

Sun et al used a method called Serial Analysis of Gene Expression (SAGE) which compares gene expression in different tissues or – as in this case – in corresponding left and right regions of the embryonic brain. The analysis looks for specific sequences of 10 DNA base-pairs, or tags, which index particular genes. SAGE output consists of simple tables, giving the identity of each tag, its count (a measure of cellular gene expression) and an identifier and more detailed description of the corresponding gene. These tables are available for left and right sides for three brain regions (frontal, perisylvian and occipital) for 12- and 14-week old brains, and for perisylvian only for a 19-week-old brain. The perisylvian region is of particular interest because it is the brain region that will develop into the planum temporale, which has been linked with language development.  One brain at each age was used to create the set of SAGE tags.

To identify asymmetrically expressed genes the authors state performed a Monte Carlo test and verified this using the chi square test. I haven’t tracked down the specifics of the Monte Carlo test, which is part of the SAGE software package, but the chi square is pretty straightforward, and involves testing whether the distribution of expression on left and right is significantly different from the distribution of left vs. right expression across all tags in this brain region – which is close to 50%.  In the left-right perisylvian region of a 12-week-old embryonic human brain, there were 49 genes with chi square greater than 6.63 (p < .01): 21 were more highly expressed on the left and 28 more highly expressed on the right.  But for each region the authors considered several thousand tags. So I wondered whether the number of asymmetrically expressed genes was any different from what you’d expect if asymmetry was just arising by chance.

It was possible to check this out from the giant supplementary Excel files that accompany the paper, but this proved far from straightforward.  It turns out that the relationship between tags and genes is not one-to-one.  For around 40% of the tags, there is more than one corresponding gene. It was not clear which gene was selected in such cases, and why. I did find some cases where two genes were assigned to a tag, but my impression was that this was unintentional and in general the authors aimed to avoid double-counting tags. We also have the further problem that some genes are indexed by numerous tags, a point I will return to below.

But let’s just focus first on the individual tags. I compiled a master list of all tags that were expressed in any region at any age, and then made a chart of the frequency of expression in each brain region/age. I excluded any tags where the total expression count on both sides was three or less, as this is too small to show lateralisation, and this left me with 3800 to 4600 tags for analysis in each brain region. I did compute chi square as described by Sun et al, but this is not recommended for small numbers, and so I also evaluated the significance of asymmetry using a two-tailed binomial test. This doesn’t make a huge difference, but is more accurate when comparing small numbers.  Figure 1 shows the proportion of the sample for each brain region where the binomial test gives a p-value of a given size. If the distribution of expression in left and right was purely determined by chance, we’d expect the points to fall on the line. If there were genes for asymmetry we would expect the observed values to fall above the line, especially at low levels of p. It is clear this is not the case. I did cross-check my figures against those of Sun et al, and found they appeared to have missed some cases of significant asymmetry, which meant that in general they found rather fewer cases of significant asymmetry than are shown in Figure 1.

Fig 1. Proportion of tags with "significant" asymmetry, by Age/Brain Region

Sun et al didn’t rely solely on statistical tests of SAGE data to establish asymmetrical expression.  They reported validation studies using a different method for assessing gene expression (real-time PCR). But this used genes selected on the basis of a chi square value of 1.9 or greater (P < .17), which included many where the degree of asymmetry was not large. One goal of PCR analysis was to confirm asymmetric expression levels in the same embryonic brains as the SAGE analysis. Of more interest is whether the findings generalise to new brains. The authors did further cross-validation using real-time PCR with six additional brains of different ages, and reported results for the LMO4 gene, where higher perisylvian expression on the right was evident in two brains at 12 and 14 weeks of age, as well as in the original two brains of the same age. Four other brains, aged 16 to 19 months, did not show asymmetry of expression. Some of the other asymmetrically expressed genes were also tested using real-time PCR in the two other brains, and 27 showed consistent asymmetric expression. It was, however, not clear to me how the significance of asymmetry was assessed in these replication samples.

There is one particular issue I find confusing when I try to evaluate the robustness of the asymmetry results. My expectation was that if a gene was asymmetrically expressed, then this should be evident in all the tags indexing that gene. But Table 1 shows that this isn’t so. For the LMO4 gene, which is the focus of special attention in this paper, there are seven tags that are linked with the gene in at least one brain region: only one of these (in red) shows the rightward asymmetry that is the focus of the paper. Another tag (in blue) shows leftward asymmetry in one sample, and the rest have low levels of expression. Maybe there’s a simple explanation for this – if so I hope that expert geneticists among my readers may be able to comment on this aspect.

Table 1. Left- and right-expression levels for seven tags for the LMO4 gene

I’m aware of two other studies (here and here) that looked for asymmetric gene expression in embryonic human brains but failed to find it . One possible reason for this discrepancy is that these studies focused on later stages of development, rather than the 12-14 week-old period where Sun et al found asymmetry. In addition, power is always low in these studies because of the small number of brains available. As Lambert et al (2011) noted, as well as possible effects of age and gender, there may be individual variation from brain to brain, but typically only one or two samples are available at each age.

So what do I conclude from all of this? I realise for a start that these studies are very hard to do. I also realise we have to make a start somewhere, even if the amount of post mortem material is limited. But I have to say I’m not convinced from the evidence so far that the researchers have demonstrated significant asymmetry of genetic expression in embryonic brains. The methods seem to take insufficient account of the possibility of chance fluctuations in the measurements, and the numbers of asymmetries that have been found don't seem impressive, given the huge number of genes that were investigated. Clearly, something has to be responsible for the physical asymmetries that have been found in foetal and neonatal brains, and the odds seem high that genes are implicated. But is the evidence from Sun et al convincing enough to conclude that we have found some of those genes? I'd love to hear views from readers who have more expertise in this area of research.

P.S. 7th Jan 2013
Thanks to Silvia Paracchini, who drew my attention to further relevant articles:
Johnson, M. B., et al (2009). Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron, 62(4), 494-509. doi: 10.1016/j.neuron.2009.03.027
This paper looked at a slightly later developmental stage - 18 to 23 weeks gestational age - and did correct for the number of genes considered (False Discovery Rate). They reported striking symmetry of gene expression in the mid-gestational period, even though structural brain asymmetries have been described at this stage of development. Note, however, that this is not incompatible with Sun et al, who did not find evidence of asymmetry after 17 weeks gestational age.
Kang, H. J., et al (2011). Spatio-temporal transcriptome of the human brain. Nature, 478(7370), 483-489. 
This is a much larger study, covering the range from 4 weeks gestational age through childhood up to adulthood and old age. This paper does not explicitly report on asymmetry, but they describe genes where the expression varies from brain region to region, or from age to age, after adjustment for False Discovery Rate. I could find no overlap in the list of the genes identified by Sun et al and Kang et al's list of differentially expressed genes.

References 

Abrahams, B. S., Tentler, D., Peredely, J. V., Oldham, M. C., Coppola, G., & Geschwind, D. H. (2007). Genome-wide analyses of human perisylvian cerebral cortical patterning. Proceedings of the National Academy of Sciences, 104, 17849-17854.
 
Dehaene-Lambertz, G., Hertz-Pannier, L., & Dubois, J. (2006). Nature and nurture in language acquisition: anatomical and functional brain-imaging studies in infants. Trends in Neurosciences, 29, 367-373.
 
Kivilevitch, Z., Achiron, R., & Zalel, Y. (2010). Fetal brain asymmetry: in utero sonographic study of normal fetuses. American Journal of Obstetrics and Gynecology, 202(4). doi: 359.e1
10.1016/j.ajog.2009.11.001
 
Lambert, N., Lambot, M.-A., Bilheu, A., Albert, V., Englert, Y., Libert, F., . . . Vanderhaeghen, P. (2011). Genes expressed in specific areas of the human fetal cerebral cortex display distinct patterns of evolution. PLOS One, 6(3), e17753. doi: 10.1371/journal.pone.0017753
 
Lash, A. E., Tolstoshev, C. M., Wagner, L., Schuler, G. D., Strausberg, R. L., Riggins, G. J., & Altschul, S. F. (2000). SAGEmap: A public gene expression resource. Genome Research, 10(7), 1051-1060. doi: 10.1101/gr.10.7.1051
 
Sagasti, A. (2007). Three ways to make two sides: Genetic models of asymmetric nervous system development. Neuron, 55(3), 345-351. doi: 10.1016/j.neuron.2007.07.015
 
Sun T, Patoine C, Abu-Khalil A, Visvader J, Sum E, Cherry TJ, Orkin SH, Geschwind DH, & Walsh CA (2005). Early asymmetry of gene transcription in embryonic human left and right cerebral cortex. Science (New York, N.Y.), 308 (5729), 1794-8 PMID: 15894532

Sun, T., & Walsh, C. A. (2006). Molecular approaches to brain asymmetry and handedness. Nature Reviews Neuroscience, 7, 655-662.