Autism and the measurement of urinary amino acids

Today's post concerns the findings reported by Aiping Liu and colleagues [1] who, following the analysis of urine samples from a group of children diagnosed with an autism spectrum disorder (ASD) and a not-autism control group, concluded that there may be something to see with regards to the urinary excretion of amino acids.

First things first, amino acids are the building blocks of proteins. Long chains of amino acids form different proteins (and peptides) that serve multiple biological functions. But making up proteins is but one of the roles of amino acids, as a variety of other functions are also included in their repertoire; notably also being the raw material for the formation of some neurotransmitters and related compounds (see here for example).

Liu et al approached their analysis of amino acids in relation to autism from the point of view of their measurement being "potential novel metabolic biomarkers for ASD." This follows something of a trend in autism research circles whereby patterns of certain amino acids and their associated chemistry in certain biofluids might have such 'potential' for some types of autism (see here and see here and see here for some other examples) albeit with certain caveats. Researchers utilised some quite well known methods when it came to their analysis - "liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis" - and set to work using a tried-and-tested method (see here): "a two-step discovery–validation approach."

Analysing urine samples from nearly 60 children with autism and over 80 not-autism controls ("28 ASD and 41 TD  [typically developing] children for the discovery stage and from an additional cohort of 29 ASD and 41 TD children for the validation stage"), researchers reported detecting and identifying "63 UAA [urinary amino acid] indicators." Twenty-one of these amino acids and/or amino acid metabolites were observed to be "present at significantly different levels in the urine of ASD children compared with TD children" in both participant sets. These compounds were fairly evenly either higher or lower in the kids with autism group (10 higher and 11 lower). I was particularly interested to see that creatinine was observed to be in the significantly higher category associated with the autism group given some other results that were counter to this finding (see here and see here) including some of my own published data [2] from a few years back. Authors also mention how they "identified a panel of 7 UAA indicators that [most effectively] discriminated between the samples from ASD and TD children (lysine, 2-aminoisobutyric acid, 5-hydroxytryptamine, proline, aspartate, arginine/ornithine, and 4-hydroxyproline)."

From those compounds, a few themes emerged with regards to the biochemistry that *might* show some involvement with autism. So: "Abnormalities in the Methionine Cycle in Children With ASD", "Evidence of High Oxidative Stress Levels in Children With ASD" and "Abnormalities in 5HT Metabolism in Children With ASD" are some of the systems potentially implicated by Liu et al. Needless to say that such biological systems are by no means strangers to autism research (see here and see here for examples) albeit not necessarily always in the same direction as the Liu findings.

Caveats? Well yes, a few, such as a reliance solely on single spot urine samples rather than multiple samples from the same person, no other measures of amino acid content in blood for example, and the focus on participants diagnosed with autism excluding things like "attention-deficit hyperactivity disorder, obsessive compulsive disorder" where 'real-life autism' rarely exists in some sort of diagnostic vacuum (see here). But, the findings are interesting and once again highlight how metabolomics is something particularly valuable to autism research (see here) and complementary to genetic studies for example, when trying to decipher the very heterogeneous autisms (plural). Issues with certain amino acids when identified in the context of autism *might* also point to a wider issue (see here) that could also indicate intervention too...

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[1] Liu A. et al. Altered urinary amino acids in children with autism spectrum disorders. Front. Cell. Neurosci. 2019. Jan 10.

[2] Whiteley P. et al. Spot urinary creatinine excretion in pervasive developmental disorders. Pediatr Int. 2006 Jun;48(3):292-7.

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An easily testable blood metabolic profile associated with ASD diagnosis?

"The present study supports early recognition of a distinctive metabolic profile in DBS [dried blood spots] whose distinguishing features suggest a reduced flux through the mitochondrial fatty acid β-oxidation pathway and provides insight into concealed molecular mechanisms determining ASD [autism spectrum disorder]."

So said the findings reported by Rita Barone and colleagues [1] including some notable names on the authorship list with some previous interest in acyl-carnitines and autism (see here), one important source of discussions in the Barone study.

Some basics from the Barone study: "A targeted panel of 45 ASD analytes including acyl-carnitines and amino acids extracted from DBS was examined in 83 children with ASD... and 79 matched, neurotypical (NT) control children." Autism was confirmed as autism in the 83 autistic children, also including the application of some important exclusionary criteria such as a "positive history for mitochondrial disease or known medical conditions including autoimmune disease and inflammatory bowel diseases (IBD)/celiac disease." I was also happy to see that researchers screened for 'possible autism' in their control participants too: "The Social Communication Questionnaire was used to screen and exclude autism in TD [typically developing] children."

Although the Barone study was a study predominantly analysing dried blood spot samples (a sample medium that has always been slightly under-utilised in research circles), researchers did also look at urine and blood samples obtained during the course of their study. They reported some interesting observations as a consequence of analysis; notably that: "Twenty-five out of 40 studied [autistic] subjects (62.5%) had significantly decreased blood Vitamin D3 levels with normal Ca/P ratio." Decreased vitamin D levels are no stranger to autism (see here and see here).

Insofar as the 'ASD analytes' results, we are told that 8 acyl-carnitines were significantly increased in the autism group compared to the control (not autism) group. I'm not going to bore you with the specific details but suffice to say the list of compounds was pretty robust and "confirm the same, unique pattern of acyl-carnitine profile" as noted in other studies with other groups. Researchers also mention how one particular amino acid - citrulline - was also significantly increased in the autism group compared to controls. They talk about how: "Blood citrulline level is considered a biomarker of gastrointestinal mucosal surface and enterocyte integrity" among other things and could have some implications for that and other 'effects'.

And then something else: "The present study confirms that patients with ASD may show a distinct metabolic profile, demonstrating that this can be used to identify a subset of ASD patients with respect to TD at younger ages." I'm always a little bit wary of studies talking about biomarkers and autism (see here for another example) but the important use of the word 'subset' denoting how autism is a label covering significant heterogeneity makes me feel a little easier about such sentiments (see here and see here) albeit with much more study being required.

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[1] Barone R. et al. A Subset of Patients With Autism Spectrum Disorders Show a Distinctive Metabolic Profile by Dried Blood Spot Analyses. Front Psychiatry. 2018 Dec 7;9:636.

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"a 256-peptide immunosignature with the ability to separate ME/CFS cases from controls"

The findings reported by Oliver Günther and colleagues [1] (open-access available here) really interested me. They interested me because they talked about the "hit and run" hypothesis being pertinent to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), where "a pathogen or other immunological insult experienced by a subject may be gone, but leaves behind physiological disequilibrium." They interested me because researchers turned to "an immunosignature assay (ISA) that employs a microarray of thousands of random-sequence peptides to interrogate antibodies in a broad and unbiased fashion" to try and pick out the biological effects of the 'hit and run' hypothesis in relation to ME/CFS. And they interested me because researchers reported that they were able to identify "a 256-peptide signature that separates ME/CFS samples from healthy controls, suggesting that the hit-and-run hypothesis of immune dysfunction merits further investigation." Lots of interesting things (honest!).

The Günther paper is open-access so doesn't really need too grand an explanation from me. The long-and-short of it was that following the adoption of a discovery and validation methodology (an increasingly favoured option in ME/CFS research circles), authors came up with a sort of 'biological fingerprint' "optimally separating ME/CFS cases and controls" based on the examination of serum samples. They also noted that in amongst their 256-peptide signature, one particular peptide - "LRVVWLSGVASG" - was also mentioned in another independent study with similar aims [2] perhaps therefore requiring further research focus. For those who might not be totally au fait with peptide designation, that string of letters is not meant to be pronounced, but rather each letter corresponds to an amino acid making up that particular peptide.

Whilst this is great work and indeed, represents some really quite detailed analysis, the authors caution that the science is not quite there yet when it comes to a 'biological test' for ME/CFS. So: "the heterogenous nature of ME/CFS clinical presentation and the variance natural present amongst control samples means that group labels in the Discovery and Validation Sets are not based on any gold standard." Diagnosis of ME/CFS still remains a point of real contention in various circles (see here) given the variety of diagnostic criteria available. Indeed, some commentators have suggested that the combination of 'ME/CFS' as a unified diagnostic label simply cannot ever exist (see here). The authors further note that: "Even the best research case definitions are often subjective and—in the absence of clear biomarkers—any group of ME/CFS cases likely comprise a heterogeneous set of pathologies."

I'm also minded to suggest that as per the lessons being learned in connection to autism biomarker research for example (see here), one needs to perhaps think about getting different research groups together who are looking at ME/CFS from different angles (see here). Y'know, sort of combining various different biomarker studies looking at various different biological 'angles' and sorta meta-analysing all the collected data to see if a larger, grander, range of variables might provide a more accurate biomarker picture of the condition(s)...

Still, the Günther study represents some good science and good value-for-research-money. It stresses how, by utilising the pretty sophisticated analytical equipment available these days, one can start creeping ever closer to some of the possible biochemistry that underpins ME/CFS (or at least some ME/CFS) and perhaps then also start some conversations centred on what can be done to alleviate symptoms and cure such a devastating illness.

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[1] Günther OP. et al. Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Mol Neurobiol. 2018 Oct 8.

[2] Singh S. et al. Humoral Immunity Profiling of Subjects with Myalgic Encephalomyelitis Using a Random Peptide Microarray Differentiates Cases from Controls with High Specificity and Sensitivity. Mol Neurobiol. 2018 Jan;55(1):633-641.

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"Starting this week, the first blood test for autism will be available to the public"

I have to say that of all the news outlets that I peruse now and again, the resource known as Disability Scoop is typically one of the best. They just always seem to be 'on the ball'. The headline titling this post - "Starting this week, the first blood test for autism will be available to the public" - comes from that resource and well, 'whoa' is a word that springs to mind.

The report details that a company called NeuroPointDX is "launching its NPDX AA test, a blood plasma test that screens for certain metabolic markers that the company has linked to autism spectrum disorder." Said test is based on some peer-reviewed science by Alan Smith [1] which concluded that the: "Identification and utilization of metabotypes of ASD [autism spectrum disorder] can lead to actionable metabolic tests that support early diagnosis and stratification for targeted therapeutic interventions." And before you ask, yes, I have covered the Smith paper before on this blog (see here).

Specific details of what is included in the NPDX AA test are, at the time of writing, not seemingly readily available. The 'AA' mention in the test name implies amino acids are going to be central to the analysis. Indeed, the Smith paper [1] talked about a few specific amino acids as potentially being important: "The combination of glutamine, glycine, and ornithine AADMs [Amino Acid Dysregulation Metabotypes] identified a dysregulation in AA/BCAA [branch chain amino acids] metabolism that is present in 16.7% of the CAMP [Children’s Autism Metabolome Project] ASD subjects and is detectable with a specificity of 96.3% and a PPV [positive predictive value] of 93.5%." What this translates into is that for at least one part of the very heterogeneous autism spectrum (maybe one or more of the autisms?), this test might be able to identify some metabolic issues that could be considered both diagnostic (for that particular 'type of autism') and also therapeutic, insofar as specific interventions aimed at specific amino acid 'issues' when identified (see here for one possible example).

Of course we've kinda been here before with the talk about a biological test for autism (see here for example) and history teaches us to be quite cautious when it comes to such discussions. We'll just have to see how well the NPDX AA test does 'in the field' before any further claims are made and even bigger 'shifts' in our knowledge of autism reported and accepted. But hey, at least give it a chance...

To close, your customary 'chat' from V to remember the date today...

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[1] Smith AM. et al. Amino acid dysregulation metabotypes: potential biomarkers for diagnosis and individualized treatment for subtypes of autism spectrum disorder. Biological Psychiatry. 2018. Sept 6

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"C-Reactive Protein as a Peripheral Biomarker in Schizophrenia"

The results of the 'updated systematic review' published by Guillaume Fond and colleagues [1] looking at the "relationships between elevated blood C-reactive protein (CRP) levels and schizophrenia (SZ) onset risk, illness characteristics and treatments, cognition and physical health" provides the blogging fodder today.

Fond (a name not unfamiliar to all-things schizophrenia) et al dip into a topic with more than its fair share of research 'uncertainty' (see here and see here for examples) on whether or not C-reactive protein (CRP), a marker of systemic inflammation, shows a connection to schizophrenia. On this particular research occasion, no new data is added to the debate, but rather authors looked at the collected peer-reviewed data (up to November 2017) to see if any 'general opinions' could be discerned from the collected works.

Results: based on over 50 studies included in their review, authors concluded that it was 'reasonable' to assume that high-sensitivity CRP (hs-CRP) may be a marker for 'schizophrenia onset risk'. The caveat to that statement is that CRP is probably not something 'schizophrenia-specific' in terms of elevations of CRP being indicative of a inflammatory state. So increased hs-CRP may well be a risk factor for "increased positive symptoms, cognitive impairment, hypovitaminosis D, microbiota disturbances, cardiovascular and metabolic syndrome risk in SZ subjects, and increased nicotine dependence in SZ smokers."

I'm pretty happy with the Fond results and interpretation as they stand. They suggest that CRP probably does show some sort of connection to schizophrenia and onward, points to an immune system connection to at least some cases (see here and see here). At the same time, they also imply that certain other observations around schizophrenia - such as a link with certain physical health issues (see here) and/or vitamin D deficiency (see here) - probably also contribute to the elevations of CRP noted in relation to cases of schizophrenia. They also imply that moves to reduce levels of CRP in relation to schizophrenia may well have various other 'knock-on' effects on those other risk factors associated with the condition/diagnosis. This 'double hit' effect could be quite useful.

And with that last sentence in mind, and accepting that consistently high levels of CRP are probably good for no-one, the next question: what can we do about elevated CRP levels in relation to schizophrenia and further, the immune system issues also being co-expressed? Lots, is my impression; perhaps also learning from other labels where immune function (and dysfunction) has been noted [2] and intervention is similarly indicated.

And there's more to come from this authorship group on this blog soon...

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[1] Fond G. et al. C-Reactive Protein as a Peripheral Biomarker in Schizophrenia. An Updated Systematic Review. Front. Psychiatry. 2018. Aug 23.

[2] Marchezan J. et al. Immunological Dysfunction in Autism Spectrum Disorder: A Potential Target for Therapy. Neuroimmunomodulation. 2018 Sep 5:1-20.

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The Children’s Autism Metabolome Project (CAMP) reports: "Amino acid dysregulation metabotypes"

The Children’s Autism Metabolome Project (CAMP), mentioned in the title of this post, is an initiative that aims to develop "a diagnostic blood test for autism." It's a project that grabbed my attention for a few reasons; not least the reliance on the science of metabolomics and the use of some pretty amazing technology headed under the term 'mass spectrometry' (see here for another example) to try and accomplish their goal.

The recent results published by Alan Smith and colleagues [1] provide some of the first results to come from the CAMP, and the observation that: "Identification and utilization of metabotypes of ASD [autism spectrum disorder] can lead to actionable metabolic tests that support early diagnosis and stratification for targeted therapeutic interventions." Just in case you were wondering: "A metabotype is a subpopulation defined by a common metabolic signature that can be differentiated from other members of the study population." Inevitable lay media headlines have also followed on from this work (see here).

The nuts and bolts? Well: "Dysregulation of AA metabolism was identified by comparing plasma metabolites from 516 children with ASD with those from 164 age-matched typically-developing (TYP) children recruited into CAMP." AA refers to amino acids, the biological building blocks of proteins, and how, yet again (see here and see here) these compounds might be quite important to at least some autism. Researchers were able to analyse blood (plasma) samples from the participants, pertinent to detecting various amino acids and looking at how levels might differ as a function of a diagnosis of autism. Interestingly and importantly, the words "Training and Test Sets" are also used in the Smith paper, denoting how: "A training set was used to identify metabotypes associated with ASD and a test set was used to evaluate the reproducibility of the metabotypes." Similar methodological processes have been noted in other autism metabolomic studies (see here). I'm not going to bore you with the technological details of the "Triple Quadrupole LC-MS/MS Method" used (I'm more inclined to q-ToF mass spec myself) but suffice to say that such technology did yield some pretty accurate and important results, and it wasn't all just about autism vs. not-autism either.

"A simple analysis of the mean concentrations of free plasma amines did not reveal meaningful differences between the ASD and TYP populations of children." This is an important point. It suggests that within this cohort, there was no significant difference in the biological profiles following a straight 'autism vs not-autism' analysis. Something perhaps not entirely unexpected given the significant heterogeneity under the behaviourally-defined label called autism. But... "scatterplots of amine levels indicated that there were subsets of children with ASD with amine levels at the extreme upper or lower end of the abundance distribution." Researchers then began zooming in on different sub-groups of their autistic cohort as part of their "Amino Acid Dysregulation Metabotype (AADM)" description. Such analysis revealed a few AADMs based on the ratios between various amino acids. Further: "Taken together, all AADMs identified an altered metabolic phenotype of imbalanced BCAA [branched chain amino acid] metabolism in 16.7% of CAMP ASD subjects with a specificity of 96.3% and PPV [positive predictive value] of 93.5%." This *could* be interpreted as suggesting that about 15% of kids with autism *could* be correctly identified via their amino acid profile.

Caveats? Well yes, a few. This was work, for example, based on a single blood sample from each participant, in effect, providing a snapshot of each person at a particular point in time. There are lots and lots of different variables that will affect our metabolome including health/illness, diet, exercise, any medicines taken, comorbidity, et al. It's not beyond the realms of possibility that any or all of those factors could have influenced the results both in the short- or longer-term. Indeed, I'd like to see a lot more research on the consistency of individual sample results across different time frames before any big claims about a diagnostic test for autism are made. Also, the term 'biomaker for autism': I again get the impression that there needs to be lots more 'cross-linking' discussion between groups committed to this research agenda (see here and see here for examples).

But I don't want to take anything away from this work and (hopefully) future publications to come the CAMP. And I do also want to mention a couple of other interesting snippets of information garnered from the current study. So, in one of the write-ups of the study, one of the authors who is not stranger to the concept of 'biomarkers for autism' (see here) discusses: "Amaral points to phenylketonuria (PKU) as a possible template. PKU is a rare disease in which the amino acid phenylalanine builds up, causing brain damage. However, relatively small dietary adjustments can make a big difference." PKU as a template for autism? I think I've heard that somewhere before (see here). And that's also to acknowledge that PKU and autism can very much exist together (see here) in the context that various inborn errors of metabolism seem to be able to produce autistic signs and symptoms (see here). And some of them are very treatable...

Also alongside, I must quickly mention about those branched-chain amino acids (BCAAs) highlighted by Smith et al. How, in the context of other previous important research talking for example, about a 'new form of autism found' (see here), there are lots and lots of research (and clinical) possibilities to come from the analysis of these types of amino acids in the context of autism (see here). And yes, this includes intervention...

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[1] Smith AM. et al. Amino acid dysregulation metabotypes: potential biomarkers for diagnosis and individualized treatment for subtypes of autism spectrum disorder. Biological Psychiatry. 2018. Sept 6.

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'Comprehensive metabolomics' and ME/CFS: lipid and energy production turn up again

The findings reported by Dorottya Nagy-Szakal and colleagues [1] describing the results of "biomarker discovery and topological analysis of plasma metabolomic, fecal bacterial metagenomic, and clinical data from 50 ME/CFS [myalgic encephalomyelitis/chronic fatigue syndrome] patients and 50 healthy controls" provide the rather long blogging fodder today.

Just in case that opening quote sounds like gibberish, this was a study that in effect examined two quite prominent biological 'systems' alongside looking at symptom profiles of participants diagnosed with ME/CFS compared with controls. Metabolomics is a discipline that is no stranger to this blog, and is focused on the analysis of small molecule metabolities in a range of biological fluids (see here). The interface between the technology used to separate out and analyse said metabolites and the statistical analysis of the huge amounts of data generated as a result, are what make metabolomics the science that it is. 'Fecal bacterial metagenomics' also known as microbiomics (see here) refers to the science of cataloguing what bacterial species are present in poo(p) samples. Yes, bacteria have their own genomes too, and stool samples can therefore be a rather informative medium.

It's important to realise that this isn't the first time that metabolomics has been spoken in the same breath as CFS/ME (see here and see here for examples); something alluded to in the Nagy-Szakal paper. Indeed, this most recent paper adds to the authors other work in this area [2] (see here for my take) where the focus was on immune-related parameters and their *association* with CFS/ME in the context of the gut and its bacterial inhabitants. And once again, there are some eminent research names included on the authorship list as last time...

So, fifty participants diagnosed with CFS/ME were compared with 50 asymptomatic (I hate the words 'healthy control') participants, and their blood (plasma) and stool were analysed. Mass spectrometry played an important role in their metabolomic work, as over 550 compounds were initially separated out from the samples provided and identified.

Results: "Among the top plasma biomarkers differentiating ME/CFS patients from controls were decreased levels of betaine, complex lipids (lysophosphatidylcholine [LPC], phosphatidylcholine [PC]) and sphingomyelin (SM), and increased levels of triglycerides (TG), α-N-phenylacetyl-glutamine, ε-caprolactam and urobilin." I'm not going to go through all of those compounds individually as to their possible relevance but there are some important classes of compound being mentioned (i.e. lipids and triglycerides).

Authors also mention another group of compounds as also potentially being important: ceramides. You may have heard the word 'ceramide' before if you are/were a user of certain brands of shampoo in recent times (see here). Outside of any hair care role, ceramide "is a waxy lipid implicated in suppression of electron transport, insulin and leptin resistance and apoptosis." Among the many roles they play 'in' the body, there is some research literature to suggest that ceramides "may play a role in gut barrier dysfunction and increased gut permeability." Interesting (see here). And going back to the Nagy-Szakal results we are told that "patients with ME/CFS and IBS [irritable bowel syndrome] have increased plasma levels of ceramide." Even more interesting.

Having mentioned the gut and gut issues in the form of IBS, it's also important to note that the authors made allowances for the presence of such gut dysfunction in their participant groups. And yes, one needs to remember that it was "based on self-reported diagnosis of IBS on the medical history form". As probably expected, the introduction of IBS (self-reported) did seem to affect the metagenomic (microbiomic) data obtained (something authors talked about in their last paper). More than that: "Chemical enrichment analysis of plasma metabolites revealed that metabolomic profiles of ME/CFS patients with IBS were distinguished from controls by levels of TG, ceramides, phosphatidylethanolmines (PE) and metabolites in the carnitine-choline pathway." Indeed also, take away the IBS bit from the ME/CFS findings and: "ME/CFS patients without IBS co-morbidity showed disturbances in PCs and carnitine-choline pathways, similar to the disturbances found in the overall ME/CFS cohort." Again, interesting.

Authors conclude that their results draw attention to a few areas already pertinent to CFS/ME, in particular, "lipid and energy metabolism." The word 'mitochondria' figures a few times in their results write-up and specifically how: "compounds in the choline-carnitine pathway were decreased in ME/CFS patients regardless of their IBS status." I've written about quite a bit of research on mitochondria and CFS/ME (see here and see here for examples) and how even if there aren't genetic reasons for mitochondrial issues (see here), this does not mean that there may not be more other issues with this system (see here).

We really need much more research in the area of metabolomics and ME/CFS. And patients really need it now, not some time later in the future...

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[1] Nagy-Szakal D. et al. Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics. Sci Rep. 2018 Jul 3;8(1):10056.

[2] Nagy-Szakal D. et al. Fecal metagenomic profiles in subgroups of patients with myalgic encephalomyelitis/chronic fatigue syndrome. Microbiome. 2017; 5: 44.

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Another blood test for autism?

"These results form the foundation for the development of a biochemical test for ASD [autism spectrum disorder] which promises to aid diagnosis of ASD and provide biochemical understanding of the disease, applicable to at least a subset of the ASD population."

OK, use of the word 'disease' in the context of autism is really, really not OK in this day and age. Researchers, peer reviewers and their publishing journals should be doing something about this kind of language. There are however some potentially important aspects to the work published by Daniel Howsmon and colleagues [1] worth talking about. Not least is their observation on how "folate‐dependent one carbon metabolism (FOCM) and transsulfuration (TS) pathways" that have been quite readily *associated* with autism might be linked to quite a bit more than just uncovering the biochemistry of at least some autism (see here for example).

Before progressing further into these findings, I note there has already been some media interest in them (see here) with a byline reading: "First physiological test for autism proves high accuracy in second trial." We'll see about that...

So, after quite a long introduction about 'biomarkers for autism' and how they "come with their own set of challenges before they reach clinical translation", authors report further results building on some of their previous work in this area [2] that I've already covered on this blog (see here). On that previous research occasion, the suggestion was that between 5 and 7 metabolites linked to folate and/or transsulfuration pathways provided a 'best fit' when it came to picking out children diagnosed with autism from those not diagnosed with autism.

This time around, there was an 'extension' to that work: "(a) By comparing univariate analysis with four different multivariate methods on FOCM/TS data for ASD biomarker development to ensure that the identified results are not restricted to FDA [Fisher Discriminant Analysis] and (b) to test and validate multivariate FOCM/TS biomarkers on data collected from a new cohort of ASD participants." The words 'training data' and 'validation data' are used quite a bit throughout the Howsmon article, illustrating how different statistical classification methods were initially applied to training data from the cohort used in their first paper, which were then tested on a new cohort of participants (n=154) diagnosed with an ASD. Given some of the names included on the authorship list, it's no surprise that participant data with regards to the metabolites being looked at were drawn from other studies looking at the possible clinical value of preparations like folinic acid (see here) and sapropterin (see here) with autism in mind.

When those different statistical classification methods were applied and data was crunched, a few observations were made. The headline result was that one model/method produced the best 'potential' biomarker results and it was the same/similar method to that previously discussed by the authors. To quote: "An FDA model using five variables was shown to slightly outperform the other models on this new validation data set." That being said, the accuracy rates (including false positive and false negative rates) hovering around the high 80%s have to take into account that two of the metabolites thought to be important on the last research occasion - % DNA methylation and 8‐OHG - "were not present in the validation set" on this research occasion. This is a pity and a weakness of the current study.

So, do we at last have a 'physiological test' with 'high accuracy' for picking out autism from not-autism? Erm, not quite yet. With all due respect to the authors, their data is interesting and does partially back up their original findings, but we're not quite there yet with regards to rolling out any sort of biological test for autism. Indeed, in these days of the plural 'autisms' (see here) and acknowledging that the diagnosis of autism rarely presents in some sort of diagnostic vacuum (see here) it could be worthwhile re-evaluating whether we're ever likely to see a 'one biological test to diagnose them all' situation.

Further investigations are however indicated and of course, this more recent information does add to the quite rich data already generated suggesting that quite a bit more focus on things like methionine, homocysteine, cysteine and glutathione in relation to autism could be an important research path to follow. I'm also minded to suggest that different research teams taking on a 'possible biomarker for autism' type research perhaps need to talk more to each other (see here) pooling findings, resources and perhaps participant groups too...

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[1] Howsmon DP. et al. Multivariate techniques enable a biochemical classification of children with autism spectrum disorder versus typically‐developing peers: A comparison and validation study. Bioengineering & Translational Medicine. 2018. May 14.

[2] Howsmon DP. et al. Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation. PLoS Comput Biol. 2017 Mar 16;13(3):e1005385.

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"DNA methylation data from neonatal blood spots can be used to accurately predict age and maternal smoking status"

There were two primary reasons why I wanted to blog about the findings reported by Eilis Hannon and colleagues [1]: first, the focus of the study was "to identify DNA methylation biomarkers of ASD [autism spectrum disorder] detectable at birth", and second, the authors actually "identified robust epigenetic signatures of gestational age and prenatal tobacco exposure, confirming the utility of DNA methylation data generated from neonatal blood spots."

The first reason, looking at DNA methylation biomarkers in relation to autism, follows other similar initiatives down the years (see here for example) on the back of some significant interest in how "epigenetic variation induced by non-genetic exposures" might complement/fill in some gaps left by more traditional genetic studies. Epigenetics by the way, seemingly means different things to different people, but is currently summarised as "the study of heritable changes in gene function that do not involve changes in the DNA sequence." DNA methylation reflects one epigenetic process (there are others). The second reason - robust epigenetic signatures linked to gestational age and prenatal tobacco exposure - actually turned out to be the more important finding, or at least the more significant finding, reported by Hannon et al hence the title of this post...

'Guthrie cards' are mentioned as the starting material for the Hannon paper, and yet another hat-tip to a true medical pioneer, Robert Guthrie (and his team), who has saved multitudes of lives with his cards used to collect and store neonatal blood spots. As well as being used to screen for various potential inborn errors of metabolism (some of which seem to have something of a relationship with some autism), those archived blood spot cards have also proved to be important research fodder too (see here).

Hannon garnered neonatal methylomic data for approaching 1300 individual - "comprising equal numbers of ASD cases and matched controls, 50% male/female" - derived from "the iPSYCH case–control sample" based in Denmark. We are told that: "DNA methylation was quantified across the genome using the Infinium HumanMethylation450k array" bearing in mind this technique/system "only assays ~ 3% of CpG sites in the genome." Alongside: "Matched genome-wide single nucleotide polymorphism (SNP) genotyping data from the same individuals enabled us to undertake an integrated genetic–epigenetic analysis of ASD, exploring the extent to which neonatal methylomic variation at birth is associated with elevated polygenic burden for ASD."

Results: with regards to a neonatal methylomic 'signature' for autism or ASD, nothing significant was detected. Obviously one has to bear in mind the limitations of the assay/method used and the fact that blood from bloodspots represents only one type of tissue (DNA methylation patterns are not necessarily the same across different tissues). I was also interested to see the authors talk about "the chronology of sample collection prior to ASD diagnosis" and the 'plausability' that they were "looking too early on in the disease process." No, autism isn't 'a disease', but this work might provide some support for the idea that the processes and onset of autism is not always set either during conception nor during gestation (see here). Dangerous thinking for some people of a sweeping generalisation ilk...

Having said all that, researchers did talk about a "significant association between increased polygenic burden for autism and methylomic variation at specific loci" but I'd like to see replication of this effect before any big claims are made.

Then to those other findings of "robust epigenetic signatures of gestational age and prenatal tobacco exposure" and what that could mean to several different areas of research, autism and beyond. I'm a little surprised that the authors didn't make more of their 'robust findings' in their discussion of these results. I appreciate that their primary aim to "identify DNA methylation biomarkers of ASD detectable at birth" was not met with startling success but the suggestion of a tell-tale epigenetic sign of exposure to maternal smoking during pregnancy for example is, I would have thought, an important advance. Certainly one that could be at least relevant to various other studies, including those related to an important comorbidity that seems to be 'over-represented' in relation to some autism (see here) and perhaps more.

To close, it's not the first time that the Star Wars universe has been subject to peer-reviewed 'science' but the paper by Hatters Friedman and colleagues is an interesting one...

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[1] Hannon E. et al. Elevated polygenic burden for autism is associated with differential DNA methylation at birth. Genome Med. 2018 Mar 28;10(1):19.

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Folate-dependent one carbon metabolism and transsulfuration pathways: biomarkers for autism?

I found it a little unusual that the findings reported by Daniel Howsmon and colleagues [1] (open-access) talking about "multivariate statistical analysis presented herein [provided] unprecedented quantitative classification results for separating participants into ASD [autism spectrum disorder] and NEU [neurotypical] cohorts based solely on biochemical data" merited a rapid reply in a prominent science magazine pouring cold water on the results (see here). Not least because one of the commentators interviewed in said science magazine article is also not seemingly immune when it comes to sweeping claims being made on the basis of preliminary research findings about autism (see here as per the previous headline: 'Super-parenting' improves children's autism).

No mind, the Howsmon paper - including a notable research name on the authorship list - mentions a few important compounds and biological processes in their discussions on: "Stepping towards this goal of incorporating biochemical data into ASD diagnosis." The sorts of things covered included various biological 'markers' pertinent to folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) some of which have been fodder for this blog previously (see here and see here for examples). Researchers looked at these various compounds in blood samples from some 80 children diagnosed with an ASD and compared levels with 47 siblings and 76 age-matched controls. They applied some nifty statistics to try and determine whether any combination of the 24 analytes examined might be potential biomarker-material for an autism diagnosis. You'll note that once again the quite problematic binary description of 'neurotypical' was used to define 'not-autism' leading onwards to the inevitable questions: 'what is neurotypical?' and 'what are the boundaries of being neurotypical?' Sensible [evidence-based] answers on a postcard please.

Results: "FDA [Fisher Discriminant Analysis] on seven metabolites allows sufficient separation such that a linear classifier can correctly resolve 96.9% of participants." But actually this was not the whole story as the authors also report that five compounds/variables - GSSG, tGSH/GSSG, Nitrotyrosine, Tyrosine, and fCysteine - provided the best 'fit' when it came to potentially picking out children with autism. You might note that some of those 'famous five' have some autism research history (see here). The authors similarly note that: "these variables are affected by high quality vitamin supplementation that also decreases ASD severity in at least a subset of cases." Mmm.

There is definitely more science to do in this area. Biomarkers in relation to autism have come and gone down the years (see here for example) and I'm not altogether sure that using the label 'autism' as a starting point for this kind of research is necessarily the best idea (see here). Outside of just the heterogeneity and plurality - the autisms - associated with the label autism, there are other considerations to take on board such as the impact of all that over-represented comorbidity too (something that continues to 'mess around' with various 'autism is linked to..' studies).

But that shouldn't stop further efforts in this area including those also looking to expand into the 'genetics' of folate metabolism alongside the biochemistry, as per everyone's favourite scrabble word 'MTHFR' (see here) and its [meta-analysed] potential contribution to some autism. I agree that we are not quite there when it comes to folate metabolism as providing a generic biomarker or set of biomarkers for autism, but there again, the authors never said that it definitively did: "it should be noted that these studies should be replicated and empirically tested on a wider scale before more definite conclusions can be drawn." Too true but the Howsmon results represent an interesting first attempt...

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[1] Howsmon DP. et al. Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation. PLoS Comput Biol. 2017 Mar 16;13(3):e1005385.

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Howsmon DP, Kruger U, Melnyk S, James SJ, & Hahn J (2017). Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation. PLoS computational biology, 13 (3) PMID: 28301476

Urinary metabolomics in autism turns up tryptophan (again)

"The tryptophan metabolic pathway collectively displays the largest perturbations in ASD [autism spectrum disorder]."

So said the findings reported by Federica Gevi and colleagues [1] (open-access) who provide yet more 'metabolomic' data when it comes to autism to add to the already quite voluminous peer-reviewed matter on this topic (see here for example).

Just in case you aren't analytical chemistry-saavy, metabolomics is basically the study of the various chemical fingerprints that the multitude of cellular processes going on in the body leave behind. It's the technology available these days that makes metabolomics the discipline that it is, as words such as mass spectrometry and nuclear magnetic resonance (spectroscopy) fill the metabolomic airwaves coupled with some rather smart statistics and software to translate all that captured data into something meaningful.

Gevi et al report results based on the analysis of urine samples from a small-ish group of children diagnosed with an ASD ("idiopathic ASD") compared with samples from a similar number of not autism controls. The aim was to focus on "autistic and unrelated typically developing children 2–8 years old, tightly matched by age, sex, Italian ancestry, and city of origin within the country" and look-see whether a particular HPLC-mass spec technique "hydrophilic interaction chromatography (HILIC)-LC-electrospray ionization (ESI)-MS" might provide some important data on autism vs. not autism.

Results: well, it's always nice to get a research mention in such studies as per the line: "Data were normalized by urinary specific gravity, because creatinine excretion may be abnormally reduced in ASD children" with reference to some work published a few years back [2]. Indeed, this is not the first time creatinine has cropped up in autism metabolomic studies (see here) and is perhaps worthy of quite a bit more study itself (see here).

The authors report that urine samples from those with autism vs. those with not-autism are "largely distinguishable" based on some nifty analysis of the compounds examined from those groups. They even provide a 'top 25 discriminating metabolites' summary to illustrate this fact. Before venturing further into this list, I would perhaps advise some caution however. Caution based on the fact that urine contains many hundreds/thousands of small molecules or chemical entities as a function of being a waste product and carrying waste products from a multitude of different biological processes. It's not outside the realms of possibility that with such a huge number of metabolites, any two groups could be separated out, not just those based on the appearance of autism or not...

Anyhow: "The “metabolome overview” obtained through metabolic pathway analysis (MetPA) shows tryptophan metabolism, purine metabolism, vitamin B6 metabolism, and phenylalanine-tyrosine-tryptophan biosynthesis as the four most perturbed metabolic pathways in ASD." The reference to the aromatic amino acid called tryptophan (the stuff that eventually ends up as serotonin and melatonin) used in the title of this post kinda points to where the money might be when it came to these particular results. I've been interested in tryptophan metabolism and autism for quite a while now (see here for example) and how, outside of the whole serotonin/melatonin bit, there is quite a lot more to see besides. Mention of something called the kynurenine pathway by Gevi is interesting; not least because this pathway overlaps with other conditions/labels too (see here). This pathway might also have some important implications when it comes to epilepsy (see here) as a comorbidity to autism too.

It's also interesting (to me at least!) to note that the authors found something related to the indoles in their analyses too. So: "we also detect a significant increase in indole derivatives of bacterial tryptophan including indolyl 3-acetic acid, indoxyl sulfate, and most prominently, indolyl lactate." Indoxyl sulfate, a uremic toxin - something that is not great for the kidneys - crops up yet again [3] and importantly, highlights how bacteria can also 'go to work' on tryptophan in the gut. Indole -3-acetic acid also brings back research memories in relation to an indole compound close to my research heart, indolyl-3-acrylolyglycine (IAG) [4] that has received a bit of a research bruising quite recently [5] (the authors of that study and another one [6] however, really need to rethink their paper titles insofar as them not actually testing whether dietary intervention actually 'affects' levels of IAG or related metabolites but nonetheless implying so).

There are a range of other findings reported by Gevi and colleagues but I don't want to bore you with all the details. Suffice to say that metabolomics continues its research rise with autism in mind, and provides some rather interesting results. Of course there is more to do in this area; not least the focus on subgroups in these days of 'the autisms' and perhaps a little more metabolomic inquiry when it comes to the myriad of intervention options put forward 'for autism'. Who for example, wouldn't like to see metabolomic profiles pre- and post-folinic acid for example alongside the myriad of other interventions detailed in the peer-reviewed literature? Indeed, I might also advocate a little more investigation on whether specific patterns of urinary compounds might also be related to specific behavioural facets of autism. Given the move towards gut bacteria as potentially showing involvement in some of the results obtained by Gevi et al, it would also be interesting to see if 'altering' certain types of gut bacteria (see here for example) might also have some interesting knock-on effects when it comes to the metabolites detected too? There is quite a bit more to do.

Music and more bad lip reading.... sick of blue milk?

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[1] Gevi F. et al. Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism. Molecular Autism. 2016l 7: 47.

[2] Whiteley P. et al. Spot urinary creatinine excretion in pervasive developmental disorders. Pediatr Int. 2006 Jun;48(3):292-7.

[3] Diémé B. et al. Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology. J Proteome Res. 2015 Dec 4;14(12):5273-82.

[4] Bull G. et al. Indolyl-3-acryloylglycine (IAG) is a putative diagnostic urinary marker for autism spectrum disorders. Med Sci Monit. 2003 Oct;9(10):CR422-5.

[5] Wilson J. et al. Can urinary indolylacroylglycine (IAG) levels be used to determine whether children with autism will benefit from dietary intervention? Pediatr Res. 2016 Nov 23.

[6] Dalton NR. et al. Measurement of urine indolylacroylglycine is not useful in the diagnosis or dietary management of autism. Autism Res. 2016 Aug 29.

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Gevi, F., Zolla, L., Gabriele, S., & Persico, A. (2016). Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism Molecular Autism, 7 (1) DOI: 10.1186/s13229-016-0109-5

"A Putative Blood-Based Biomarker for Autism Spectrum Disorder-Associated Ileocolitis"

Contrary to Murphy's Law - 'never repeat a successful experiment' - replication or reproducibility is a cornerstone of good science. Today, I'm blogging about a piece of research that aimed to do just that as per the findings reported by Stephen Walker and colleagues [1] (open-access).

The title of this post has been borrowed from the title of the Walker paper to illustrate how moving on from the quite widely known 'fact' that functional gastrointestinal (GI) symptoms are over-represented when it comes to the label of autism (see here for example) so further research focus is required on more pathological bowel conditions potentially linked to autism too (see here). Yes, I know this potentially takes us into some uncomfortable territory but for those with autism suffering with various bowel issues (and I do mean suffering) this marks some important science for them and their families onward to the resolution of any further health inequalities.

The latest Walker paper follows on from their original findings [2] which have been previously covered on this blog (see here) observing that: "ASDGI children have a gastrointestinal mucosal molecular profile that overlaps significantly with known inflammatory bowel disease (IBD), yet has distinctive features that further supports the presence of an ASD-associated IBD variant, or, alternatively, a prodromal phase of typical inflammatory bowel disease." ASDGI by the way, referred to their small grouping of "twenty five consecutive ASDGI cases (6 autism; 19 autism spectrum disorder) with histopathologic findings of ileitis, colitis, or both."

This latest time around authors report on the extending of their 'initial findings' in "an additional case/control cohort." Further they "report a gene expression profile in peripheral blood that may reflect the presence of ASD-associated ileocolitis and provide a putative surrogate biomarker that, upon validation, would be of significant clinical relevance." Potentially, big words.

The paper is open-access but here are a few choice details:

• Biopsy samples - "a specimen from each of seven anatomic locations (from the terminal ileum to rectum)" - and blood samples were provided by 21 participants (patients) diagnosed with an autism spectrum disorder (ASD). All presented with gastrointestinal (GI) symptoms and all had "a history of normal development for at least 12 months followed by developmental regression and onset of gastrointestinal symptoms." All also had "histologically-confirmed ileitis, colitis, or both in at least one of seven collected and archived colonic biopsies." 
• A control group of 21 'typically-developing' children "without ASD who had gastrointestinal symptoms... but no identifiable histologic inflammation on any biopsies in either the ileum or colon" were also included for analysis.
• Part 1 of the study "compared whole genome gene expression profiles of inflamed ASD GI mucosal tissue (ASDIC+) to non-inflamed TD mucosal tissue (TDIC−) in biopsies from both the terminal ileum and colon." This is pretty much what was done by the authors during their first research voyage in this area. Part 2 was more novel insofar as blood gene expression profiles were compared between the groups. It's also important to note that: "blood was obtained from the same patients, and at the same time, as their respective mucosal tissue samples."
• Results: applying a statistical technique called Principal Component Analysis (PCA) looking at gene expression in those mucosal (bowel) samples, authors were again able to say that there were differences between inflamed and non-inflamed samples/groups. They also observed some potentially important differences in those blood samples too: "Nine of these DETs [gene transcripts that are differentially-expressed] were also differentially expressed in blood in our most recent cohort." You might ask what does this actually tell us about the autism+GI group? Well, nothing and something, insofar as it is not really being ethical to start taking bowel biopsies from children with autism without any indication to do so, which means that comparisons between non-GI and GI+ children with autism were not possible. The data do however suggest that a "putative peripheral marker could provide a proxy for gastrointestinal inflammation and also provide functional insights."
• Insofar as the details of what genes were being differentially expressed in ASDIC+ vs. TDIC- samples and how these overlapped with the previous study from the authors, there were some interesting candidates including "a key mitochondrial folate pathway gene, MTHFD2 (methylenetetrahydrofolate dehydrogenase (NADP + dependent) 2, methenyltetrahydrofolate cyclohydrolase)" hinting at an effect beyond just immune function and inflammation/inflammatory signalling. Authors modelled various combinations of these genes expressed (or not) to try and come up with some preliminary Receiver Operating Characteristic (ROC) curve analysis. Regular readers of this blog will probably have heard me talk about ROC analyses before (see here for example) with regards to the search for potential classifiers or biomarker profiles associated with autism. Bearing in mind the small participant numbers included in this study and the final figures arrived at, I'd suggest that quite a bit more work is required before anyone takes the reported findings as gospel just yet. But they are interesting...

So, there you have it. This is important work for two reasons: (i) more pathological bowel states can and do present alongside autism [3] (the diagnosis of autism is seemingly protective of very little as science is learning) and (ii) with the strong requirement for further investigations in this area, science is seemingly starting on a path to potentially identifying blood-based 'biomarkers' possibly useful in identifying those who might benefit from further screening for such bowel issues.

Given the history and debate in the area of bowel disease accompanying some autism, I'm not expecting giant fanfares to greet these results nor any big rush to try and prove/disprove these latest findings. That is an unfortunate truth and in the end, it is the children/adults with autism and significant GI issues who lose out as a consequence. The fact that this and the previous work by the authors is peer-reviewed science and not just speculation however will I think eventually be important, as talk about medical comorbidity accompanying autism continues at a pace [4] (see here too) and further moves towards 'what can we do about such issues?' eventually start to come to the forefront.

And just before I go, there may also be other research uses for biopsies as and when they have to be taken from children/adults under clinical investigation [5]...

To close, I note there is an election across the Pond. With all the nastiness that has followed the campaign, surely there's an easier way to pick the Leader of the Free World...

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[1] Walker SJ. et al. A Putative Blood-Based Biomarker for Autism Spectrum Disorder-Associated Ileocolitis. Sci Rep. 2016 Oct 21;6:35820.

[2] Walker SJ. et al. Identification of unique gene expression profile in children with regressive autism spectrum disorder (ASD) and ileocolitis. PLoS One. 2013;8(3):e58058.

[3] Doshi-Velez F. et al. Prevalence of Inflammatory Bowel Disease Among Patients with Autism Spectrum Disorders. Inflamm Bowel Dis. 2015 Oct;21(10):2281-8.

[4] Vohra R. et al. Comorbidity prevalence, healthcare utilization, and expenditures of Medicaid enrolled adults with autism spectrum disorders. Autism. 2016. Oct 20.

[5] Kushak RI. et al. Analysis of the Duodenal Microbiome in Autistic Individuals: Association with Carbohydrate Digestion. J Pediatr Gastroenterol Nutr. 2016 Nov 2.

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Walker SJ, Beavers DP, Fortunato J, & Krigsman A (2016). A Putative Blood-Based Biomarker for Autism Spectrum Disorder-Associated Ileocolitis. Scientific reports, 6 PMID: 27767057

Yet more on potential biomarkers and chronic fatigue syndrome

'Thick and fast' is probably the best way that I can describe the flurry of peer-reviewed scientific papers recently appearing (see here and see here for examples) talking about how chronic fatigue syndrome (CFS) (also linked to the diagnosis of myalgic encephalomyelitis, ME) might have some important biological processes attached to it.

Now we can add the findings reported by Federica Ciregia and colleagues [1] (open-access) to the list and their observations that "the identification of biomarkers present in particular subgroups of CFS patients may help in shedding light upon the complex entity of CFS."

The Ciregia paper is open-access but well-worth a few inches of discussion on this blog. Not least because (a) the word 'mitochondria' is part and parcel of the their findings in line with other research in this area, (b) one of the gold standards of analytical chemistry - liquid chromatography mass spectrometry -  was used, and (c) some of the findings are based on a study of twins: "a patient suffering from CFS in comparison with his healthy monozygotic twin." This mirrors other similar published work from this authorship group [2].

So, using a discovery/training and validation approach similar to other biomarker studies in other areas, researchers initially set out to "study the mitochondria extracted from platelets of the twins" using "nano-liquid chromatography electrospray ionization mass spectrometry (nano-LC-MS)." They were looking for evidence of different compounds being presented/expressed in those twins diagnosed with CFS compared with their non-affected twin and eventually came up with 41 proteins - "34 were upregulated in CFS and 7 were downregulated" (see here for the list of compounds).

Using a process called Ingenuity Pathway Analysis (IPA) "to retrieve the known functions of each protein" authors were able to visualise where each compound 'fitted' in terms of specific biological functions. The top three included: "metabolism of isocitric acid..., metabolism of NADH... and metabolism of nucleic-acid component or derivative." Certainly NADH has some 'history' when it comes to CFS/ME (see here).

Then came the validation side of the study where "the most promising biomarkers were validated by western blot [WB] analysis in a big cohort of patients, using whole saliva (WS)." Here some 45 patients diagnosed with CFS ("based on the classification criteria of Fukuda et al") were recruited alongside 45 not-CFS controls and spit samples from all were analysed for "aconitate hydratase (ACON), ATP synthase subunit beta (ATPB) and malate dehydrogenase (MDHM)." Two proteins, ACON and ATPB. were replicated or at least "consistent with the results from nano-LC-MS."

Finally, researchers looked at whether presented clinical features as described in various questionnaires delivered to participants might play a role in the presentation of their biological results. They did see something (see here) - "For each marker, the values were actually higher in the group of patients who had clinical features similar to the ill twin" - but I would be minded to suggest that quite a bit more work is needed before anyone reads too much into this as the results stand.

So, there you have it. A little bit more evidence to suggest that science is edging a little closer to potentially identifying some of the biology behind (or least associated with) at least some CFS (and ME). A little bit more peer-reviewed evidence moving the discussions away from 'psychosomatic' [3] to something a little more testable/analysable with CFS/ME in mind (I'll be coming to the paper by Geraghty & Esmail soon enough on this blog by the way). Independent replication is the next step, onwards to potentially "developing tailored treatments." That bearing in mind, we already have some emerging data in this area too (see here) (with no medical advice given or intended).

And just in case you want yet more potential biomarker research for CFS, here's another paper that has just been published [4]. Thick and fast people, thick and fast.

So, there is a new trailer for Rogue One (A Star Wars story)...

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[1] Ciregia F. et al. Bottom-up proteomics suggests an association between differential expression of mitochondrial proteins and chronic fatigue syndrome. Transl Psychiatry. 2016 Sep 27;6(9):e904.

[2] Ciregia F. et al. A multidisciplinary approach to study a couple of monozygotic twins discordant for the chronic fatigue syndrome: a focus on potential salivary biomarkers. J Transl Med. 2013 Oct 2;11:243.

[3] Geraghty KJ. & Esmail A. Chronic fatigue syndrome: is the biopsychosocial model responsible for patient dissatisfaction and harm? Br J General Practitioners. 2016. Aug 1.

[4] Yamano E. et al. Index markers of chronic fatigue syndrome with dysfunction of TCA and urea cycles. Scientific Reports. 2016; 6: 34990.

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Ciregia F, Kollipara L, Giusti L, Zahedi RP, Giacomelli C, Mazzoni MR, Giannaccini G, Scarpellini P, Urbani A, Sickmann A, Lucacchini A, & Bazzichi L (2016). Bottom-up proteomics suggests an association between differential expression of mitochondrial proteins and chronic fatigue syndrome. Translational psychiatry, 6 (9) PMID: 27676445