Does diabetes start in the intestines?

The findings of an interesting paper by Wei and colleagues* (full-text) pose a question: are the origins of diabetes in the intestines?

For those that don't know too much about diabetes, here is a link that should help. The concise version (if there is such a thing) is that diabetes normally manifests as either type-1 diabetes or type-2 diabetes with insulin being the key compound in controlling blood sugar, and corresponding issues either with its production or when resistance is built up to it.

The crux of the paper by Wei et al is that an insulin-responsive super enzyme called fatty acid synthase (FAS) involved in lipogenesis is also involved in gut barrier regulation through its action on Mucin 2 (Muc2), a gel-forming component of mucus. The authors' suggestion is that becoming resistant to insulin is associated with issues with FAS and correspondingly problems with mucus in the gut, inflammation and diabetes. No pressure then.

The paper summarised (deep breath):

• Several groups of mice were included for study: (a) mice with chemically-induced (tamoxifen induction of Cre recombinase) decreases of FAS protein and mRNA, (b) mice bred with inactivated FAS in the intestine and (c) control germ-free mice. For group (b) mice, diabetes was induced by administration of streptozotocin, a toxin to the beta cells which produce insulin in the pancreas.
• Assays looking at gut bacteria, intestinal permeability, cytokine release and protein S-palmitoylation were used to investigate various parameters.
• The findings: a chemically-induced deficiency of FAS in mice started a cascade of events linked to inflammation. One of the primary cytokine markers of this inflammation was elevated levels of TNF-α although animals were also noted to show weight loss and other gastrointestinal symptoms. A quarter of these mice actually died within 14 days.
• The authors deduced that although some changes were noted to the intestinal bacterial makeup of FAS reduced mice, these changes were not enough to cause the inflammation observed but rather were as a result of the inflammation. They demonstrated this via a previously discussed method on this blog, bacterial transplantation; in this case to the germ-free mice (group c) who did not show the accompanying inflammation as a result of their donor bacteria. That is not however to say that gut microbiota did not have some effect, as per the reduction in inflammation noted in the FAS deficient mice following administration of the antibiotics ciprofloxacin and metronidazole.
• The link between FAS deficiency and Muc2 was evidenced by the lower levels of Muc2 shown in FAS deficient mice and reduced inner mucus layer thickness in the colon of affected mice. 
• Looking at the inactivated FAS (group b) diabetic mice, a similar pattern of issues with Muc2 and reductions in the mucus layer was seen alongside penetration of bacteria indicating intestinal hyperpermeability (leaky gut). Interestingly, insulin supplementation seemed to positively affect some of the permeability issues.

This is quite a complicated paper and so please do not take my summary as gospel. It is intriguing that inflammation is at the heart of their theory and in particular, inflammation as a result of not having enough FAS present in the gut with the knock-on effects on gut permeability. Indeed not for the first time has it been suggested that diabetes and leaky gut are connected as per articles like this one. Makes you wonder also about any other possible dietary inter-related connections?

* Wei X. et al. Fatty acid synthase modulates intestinal barrier function through palmitoylation of mucin. Cell Host & Microbe. February 2012.
DOI:  10.1016/j.chom.2011.12.00

On gut parasites and chronic fatigue

An interesting exchange on Twitter prompted this short post regarding a paper by Naess and colleagues* (full-text) on Giardia lamblia gastroenteritis and chronic fatigue syndrome (CFS). The tweets concerned another parasitic nasty called Toxomplasma gondii which has featured quite a bit on a sister blog with regards to its link to various behaviourally-defined conditions. I thought that T.gondii was a spine-tingling protozoa until someone posted about these other chaps and their brain-eating, behaviour-changing and belly exploding antics (pass the sauce, please).

Giardia lamblia is quite a special  protozoa in terms of its survival, persistence and ability to link into quite a few other health complaints particularly of the gastrointestinal variety and specifically links to lactose intolerance. The current observations by Naess et al are interesting in that based on an examination of over 1200 patients with laboratory-confirmed giardiasis following a large community outbreak in Bergen, Norway, approximately 5% of cases (58/1262) were diagnosed with CFS as classified by the CDC criteria (see here for a related post on the trials and tribulations of diagnosing CFS/ME).

Even assuming a CFS prevalence of 1% previously noted in children (not adults) in the UK, the 5% figure seems high bearing in mind correlation is not necessarily causation. What can perhaps be ascertained from this latest study is that it might be a good idea to screen for giardiasis where active functional bowel issues are present alongside fatigue-related conditions and further research on any mechanism of parasitic infection linked to long-term fatigue might be advisable.

* Naess H. et al. Chronic fatigue syndrome after Giardia enteritis: clinical characteristics, disability and long-term sickness absence. BMC Gastroenterology. February 2012.
DOI: 10.1186/1471-230X-12-13

Plasma amino acids and inflammatory bowel disease

My recent post on the application of metabolomics to food fingerprinting got me thinking about the examination of biological fluids and how our metabolome might have some interesting secrets to one day share. The 'promise' of the science of metabolomics is that one day, we should be able to look at various biological fluids across a range of conditions and based on the compounds excreted/detected determine diagnosis, disease progression and how well someone responds to intervention. I hasten to add that we are nowhere near that position yet.

In light of this, it was perhaps inevitable ('it is your destiny') that this paper by Hisamatsu and colleagues* (full-text) on possible plasma biomarkers for inflammatory bowel disease (IBD) would get some attention. I'm pretty sure that I don't have to explain this to viewers but the term inflammatory bowel disease covers quite a bit of diagnostic ground including Crohn's disease and ulcerative colitis. Diagnostic confirmation of these conditions is quite a complicated process normally involving a combination of peripheral measures (blood tests, stool analysis) coupled with more direct observation of the bowel.

Hisamatsu and colleagues reported that a previously trialed network analysis of plasma amino acid levels in patients diagnosed with IBD might provide novel, non-invasive and importantly, objective biomarkers potentially opening up some new research areas into the nature of IBDs.

The details:

• Fasting plasma 'aminograms' for a discovery group of 102 Japanese adult patients diagnosed with Crohn's disease (CD) and 102 patients with ulcerative colitis (UC) were initially compared against 102 healthy control participants. The majority of participants were male (70%) with disease duration ranging between an average of 7.8-11 years. A minority of participants were described as having 'active' disease (CD = 29/102; UC = 38/102).  Obtained aminogram results were also validated using a validation set of participants (CD: n=63; UC: n=120; controls: n=108).
• Serum albumin levels were reported as significantly lower in the IBD groups compared to controls.
• Various differences were noted between the groups in terms of amino acid levels. The authors seemed to have concentrated on histidine and tryptophan as primary examples with a view to disease activity and correlation with C-reactive protein levels (a marker for inflammation).
• Implementing their network analysis (MIAI), the authors came up with a formula based on 6 amino acids which discriminated CD and UC groups from controls with ROC values ranging from 0.894 to 0.955 depending on whether the discovery or validation group were used and comparing across the IBDs with controls. 
• Depending on whether disease was active or in remission, a formula incorporating data for 7 amino acids was suggested to have some power in discriminating disease activity with ROC values ranging from 0.894 (CD active vs. CD remission) and 0.849 (UC active vs. UC remission).

The data produced by this study is interesting. OK, it is not totally 'diagnostic' either in terms of classifying IBD from controls or looking at active vs. remissive symptom presentation but it's not a bad start at all. Indeed the use of discovery and training sets takes me back to a wonderful paper covered last year on schizophrenia, which did find a perfect classification based on a handful of serum and urinary markers. It makes me wonder if they were looking at serum and urine at the same time or maybe incorporating a few more well-known markers, whether those ROC values might further approach the magical number 1 (denoting a perfect classification).

The use of statistical models allied to biochemical data is also interesting. I note that similar linkages have been used in other areas of medicine, possibly even to recreate speech from brain activity...?

* Hisamatsu T. et al. 2012 Novel, objective, multivariate biomarkers composed of plasma amino acid profiles for the diagnosis and assessment of inflammatory bowel disease. PLoS ONE. January 2012
DOI: 10.1371/journal.pone.0031131

Newsflash: defining gluten-related disorders

In the style of one Homer J Simpson... can't stop... must finish for the day.. new guidance of what constitutes a gluten-related disorder just published by Sapone and colleagues*.

If there is one document that you absolutely have to look at which summarises where we are in relation to gluten-related conditions, not just coeliac disease, this is it.

It's full-text, has a myriad of gluten research names included on it (including Alessio Fasano, Marios Hadjivassiliou and David Sanders), so enjoy.

* Sapone A. et al. Spectrum of gluten-related disorders: consensus on new nomenclature and classification. BMC Medicine. February 2012.
DOI: 10.1186/1741-7015-10-13

Pesticides and vitamin D deficiency

Chemistry World, the public face of the UK Royal Society of Chemistry (RSC), carried an interesting report recently discussing research linking exposure to organochlorine pesticides (OCs) with vitamin D deficiency. The research in question is this paper by Jin-Hoon Yang and colleagues* (full-text) and before you ask, yes, it is a study of 'association', so we tread carefully.

Before wading into this study it is interesting to note that vitamin D is currently enjoying quite a trendy following in many areas. Important discussions are underway to determine whether a resurgence of conditions like childhood rickets means supplementation needs to be more closely inspected. 

I digress. A summary of the paper in question:

• An analysis of plasma levels of 7 OCs (including DDE and DDT) was undertaken for 2,337 people aged 12 and above recruited as part of the US National Health and Nutrition Examination Survey (NHANES). After exclusion of those where accompanying 25-hydroxyvitamin D (25(OH)D) were not available alongside other exclusions (e.g. pregnant women, being under 20 years old), the final participant group number was N=1275.
• The results: based across various grouping on concentrations of OCs, there were quite a few significant inverse relationships reported. That is, for the OCs -  p,p′-DDT, p,p′-DDE, and β-hexachlorocyclohexane - elevated plasma levels of these compounds individually and collectively were associated with lower vitamin D levels. Plasma levels of DDT in particular showed quite an enduring association with vitamin D levels. 
• There is a suggestion that the relationship may also be dose-dependent up to a certain point; that is up to a value of 200 ng/g lipid of DDT, vitamin D levels dropped, but increasing levels of DDT after that seemed to be linked with increasing vitamin D levels bearing in mind that most participants presented below this 200 ng/g lipid threshold.

As I said, this is a study based on association. Controlling for factors such as gender, age, race and vitamin D supplementation is an admirable quality of the study but association is normally only a guidepost to a possible relationship, not a dead cert. That and the fact that little information has been provided on why the results came out as they did, leaves the door open to further study in this area.

Noting that this blog is primarily concerned with the gut, I do wonder about these recent findings and how they may (or may not) fit into a past post on gut bacteria and organochlorine pesticides. It's a bit of a long shot but how about testing the suggestion that OCs affect gut bacteria which in turn affects other systems including vitamin D and its receptors?

* Yang J-H. et al. Associations between organochlorine pesticides and vitamin D deficiency in the U.S. population. PLoS ONE. January 2012. DOI:10.1371/journal.pone.0030093

Metabolomics and the food fingerprint

I've touched upon the beautiful science of metabolomics previously on a sister blog; that is, looking for 'chemical fingerprints' in various biological fluids to garner further information on underlying biological processes related to health. Already metabolomics has provided us with a few preliminary clues in relation to more behaviourally-led conditions such as autism and schizophrenia (AUC=1), but as the technology gets smarter and smaller (and cheaper), I foresee great things ahead for this flourishing branch of biochemistry similar to the genomic high-throughput screening technology carried out at places like the Sanger Institute.

When a story recently appeared on the BBC website discussing a food 'fingerprints' test, it was therefore always going to attract my attention. Indeed so much so that after a few quick emails to one of the people involved with the research, I was very satisfied to receive some of their peer-reviewed papers on the details behind the headlines. 

The BBC story discusses some collaborative research based on the notion that what we eat leads to the production of various chemical metabolites and that detecting those metabolites in fluids like urine means we can objectively find out what someone has consumed recently and if necessary promote any dietary changes. Food diaries are the normal way of collecting information on what people have eaten recently but recall is often not as accurate as you think.

My take on this work was slightly different in terms of the fact that the researchers are in effect, building up a large bank of information based on very controlled eating habits about what comes out when we eat certain foods. 

This paper by Favé and colleagues* (full-text) sums up the research aims and objectives; also providing a great overview of the various techniques used in metabolomics and importantly the statistical analyses required (normally PCA or some variant). The researchers have been very methodical in their approach to this issue. This paper again by Favé and colleagues** (full-text) details how they went about clearing a few potential interfering variables such as the fasting period and some information on the reproducibility of findings over various testing occasions. In short, they wanted to make sure that interesting collected metabolites were food derived and were consistent.

So what have they got so far?

Well, according to this paper by Lloyd and colleagues*** when compared to a standard breakfast made up of orange juice, tea with skimmed milk and sugar, butter croissant, and cornflakes with milk, an alternative dietary schedule made up of either salmon, broccoli, whole-grain wheat cereal or raspberries produced some notable differences in urinary metabolites. The differences were even more notable when the alternative dietary schedule was compared against fasting urine samples.

Looking more specifically at individual compounds formed as a result of dietary intake, a few interesting snippets were reported including:

• Smoked salmon intake was associated with increased levels of 1-methylhistidine and anserine (b-alanyl-L-methylhistidine), metabolites of the amino acid histidine, probably derived from fish skeletal muscle. Also alongside were findings of TMAO, a degradation product from carnitine (remember that?).
• Broccoli and raspberry were both associated with increased ascorbate and individually, xylonate/lyxonate and polyphenols.
• For each of these three dietary components, there were at least 7 putative biomarkers of intake reported although nothing was reported on for the wholegrain cereal consumption.

Another paper by Lloyd and colleagues**** reported that proline betaine was associated with citrus exposure, with detected levels using the same technology and methods explanatory of both acute and habitual exposure to citrus containing foods (makes it sound like an illicit drug or something).

Appreciating that this and related work is still an emerging area of investigation, subject to all manner of confounders that we as human beings do to ourselves every day, I am suitably impressed that there are groups out there looking at our food and how we metabolise it. I can envisage many applications for this kind of work, ranging from a non-invasive test of recent food consumption, to measuring adherence to certain kinds of dietary intervention, to examining whether there are any differences in the metabolism of certain foods as a function of say gut bacteria which might cast some light on the biology behind lots of conditions.

To finish how about a bit of artistic interpretation through the medium of dance from Kate Bush...

* Favé G. et al. Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics? Genes & Nutrition. 2009; 4: 135-141

** Favé G. et al. Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples. Metabolomics. 2011; 7: 469-484

*** Lloyd AJ. et al. Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods. American Journal of Clinical Nutrition. 2011; 94: 981-91.

**** Lloyd AJ. et al. Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption. British Journal of Nutrition. 2011; 106: 812-824.