Third, in PARSIFAL dust from children’s mattresses were collected by vacuuming — it is not very likely that many helminthic eggs were transported from stable to bedroom. In GABRIELA, only airborne dust samples were collected which again may miss helminth eggs although being certainly present in stable dust.
Fourth, more microbial exposure and more fungal taxa on farms are a trivial finding.
The inverse associations of the diversity scores with asthma were not confounded by status with respect to living on a farm because adjustment did not change the respective point estimates for asthma (Table 2), although the associations became nonsignificant.
Small sample size, borderline p-values even after a long fishing expedition?
What do these strange “probability” plots really show – the probability of asthma or the probability to live on a farm?
N Engl J Med 2011;364:701-9 Figure 3 Does it refute any general effect of diversity?
The plots are misleading if adjustment for farm living does not change the parameter estimates for bacterial/fungal diversity.
Sixth – even many years later, the main findings of this study have not been independently replicated. There is not any single study that shows listeriosis (Listeria) or diphtheria (Corynebacterium) to be protective.
Ignoring the long-standing paradox that endotoxin is also acting as a natural adjuvant to atopic inflammation, the credibility of the Science paper is further reduced.
IMHO it is also a strange experimental condition to have all animals on a standard vitamin D diet – a known co-sensitizers – and looking then for A20 which is co-regulated by vitamin D ??
Unfortunately most studies in the farming environment do not report the prevalence of parental history. Neither did they report the effect size of parental genetic risk in the farming population. This is, however, a critical issue as the so called healthy worker effect (HEW) may be a rather trivial explanation of the results.
Specifically, it is a sampling bias: the kind of subjects that voluntarily enroll in a clinical trial and actually follow the experimental regimen are not representative of the general population. They can be expected, on average, to be healthier as they are concerned for their health [or as ill people already dropped out]
Leynaert 2001 showed only a slightly reduced prevalence of “allergy” (39.1% vs 41.5%, NS). Her table 4 is most interesting. The association started only after year 1960 which points towards severe misclassification as far as the analysis is not stratified by year of birth.
Remes 2002 showed a dose dependent effect decline between farming (36.2%) and controls (31.6%, P=0.075),
Perkin 2006 also found some significant lower prevalence in farmers 47.3% versus 57.7%, P<0.001. HWE is therefore likely.
I found further six studies (Thelin 1994, Braback 2006, Chenard 2007, Thaon 2011, Elholm 2013 and Spierenburg 2015) that examined in detail a possible relationship of HWE, allergy and farming. Unfortunately the examination period in five of these studies is too short to make any conclusion while Braback 2006 seems to be the only reliable study.
From this study, we can safely conclude, that there is a significant HWE.
Addendum 22 Nov 2019
It seems that I missed some papers on HWE and farming.
Timm 2019 is a hard to understand cluttered 3 generation study of unclear asthma type. Point estimates of parental asthma on farm upbringing are not really a measure of HWE – shuffling exposure and outcome distorts temporality. In contrast to the interpretation of the authors, I see a clear effect if both parents are born on a farm and one parent has asthma. The RR drops here to 0.33 that their child will be raised on a farm.
Vogelzang 1999: 400 pig farmers, X-sectional point estimates, not a real HWE study, although HWE offered as explanation.
Health-based selection of nonasthmatics for pig farming, which tends to mask a work-related hazard for asthma, is offered as an explanation for these results.
Eduard 2015: compares asthma prevalence of 313 Danish farm children to their 518 sibs (which is identical) but useless, as affected parents would basically dropout all children.
There is even a second comparison of Norwegian farmers with a clear effect. Instead of comparing the early retired farmers with their respective age cohort they invented a c complicated quantile logitic regression in 4 year intervals. Detailed model parameter and significance levels are missing.
At least the conclusion was
A healthy survivor selection was observed in Norwegian farmers, but it was too small to fully explain the reduced risk of asthma observed in this population. A strong selection effect was observed among farmers who had changed production type
There is an interesting meta-analysis at JAMA Pediatrics about vitamin D supplementation during pregnancy and offspring growth, morbidity, and mortality. Nothing special, standardized methodology and even somewhat expected outcome.
In this systematic review and meta-analysis of 24 randomized clinical trials including 5405 individuals, vitamin D supplementation during pregnancy was associated with a lower risk of infants being small for gestational age and improved growth during infancy without an increased risk of fetal or neonatal mortality or congenital abnormality.
More interesting are the vitamin D lobbyists writing the accompanying editorial (Bo Chawes , Klaus Bønnelykke, Hans Bisgaard) . They try by nearly every sentence to devalue the findings of the meta-analysis. They are even getting to the point of
no adverse effects have been found
We don’t see things as they are, we see them as we are.
The recent encyclopedia article about the hygiene hypothesis seems to be well written. At least on the first instance … in reality it is more a novel than a scientific review.
For many years already, the hygiene hypothesis has been called an outdated concept; various times it was revised and transformed, and finally it gave birth to novel hypotheses.
In other words, the hypothesis has been rejected for being wrong . Even many revisions did not change that. There seem to be only one proven fact – the obsession of some authors with hygiene and nouvel Rousseauism.
Anyway, the hygiene hypothesis has promoted radical rethinking of infections, microbiota, and coevolution of mankind and microbes.
There is nothing radical in backward thinking. We still carry tons of microbes, freezer and antibiotics only did some qualitative but not so much quantitative changes,
With the advent of novel high-throughput sequencing technologies the human microbiome, which is sometimes called the ‘forgotten organ,’ has attracted much attention and is currently being implemented in a wider concept of self-foreign relationship, which may even include recognition of the nonmicrobial nonself as a vital stimulus to a well-developing immune system.
So the interest is technology and not science driven.
The microbiome is not an organ.
The hype is already over.
The Self is not defined by any bacterium.
Most bacteria are excreted and not vital stimulus.
Given the many molecule classes regulating immune functions across individuals such as short RNAs, the hygiene hypothesis may eventually come back as a surprising explanation of the phenomena evoked by crowding, day care, sibship size, orofecally transmitted diseases, and respiratory infections.
Why that?
A comeback of the hygiene hypothesis by short RNA?
The listed phenomena are not intrinsically related, but are occuring only at the same time scale.
Even the old birth order effect might be rediscovered as epigenetic programming someday. Admittedly, these notions are entirely hypothetical, but without hypotheses, proven or not, science hardly advances.
So if David Strachan’s birth order effect would be really caused by epigenetic programming – why would that be related to hygiene at all?
Science is is not so much about proven or unproven but about reasonable and non reasonable hypotheses.
The main arguments in favour of sharing work in its preliminary form are, firstly, that science works faster if work is made available sooner after it is completed and, secondly, that articles are improved by feedback from a wider group of readers, alongside formal peer review by a few experts. Simple estimates suggest that halving the delay to sharing a research result can double the speed at which research progresses. Ambitious research funders are now embracing preprints and other measures that aim to accelerate the pace of research.
MedArXiv will have a hard time attracting preprints if mainstream medical journal editors decide they won’t publish final versions of the papers. Currently, The BMJ and The Lancet are among the few medical journals that have explicitly said that posting a preprint doesn’t preclude publication; Nature and Science, which both occasionally publish medical studies, have the same policy. But at the JAMA Network, which publishes a dozen journals, the issue is hotly debated.
@medRxiv opened on June 6. So far they have only 304 followers on Twitter (and no allergy paper in the archive).
As the current “Allergy” editor and the publisher (John Wiley and Sons A/S) agreed to preprints last week, I have submited now my first preprint paper. Therefore, there are now 305 followers and 1 allergy paper :-)
It is one of the minor papers in a minor journal but nevertheless has some big impact: “A phenome-wide Mendelian-randomization study of genetically determined vitamin D on multiple health outcomes using the UK Biobank” in Int J Epidemiol. 2019 Sep 13
Existing studies suggest that a low vitamin D level is associated with more than 130 outcomes. … We then implemented a Mendelian Randomization-Phenome Wide Association Study (MR-PheWAS) analysis on data from 339 256 individuals of White British origin from UK Biobank. We first ran a PheWAS analysis to test the associations between a 25(OH)D polygenic risk score and 920 disease outcomes…The PheWAS analysis did not identify any health outcome associated with the 25(OH)D polygenic risk score.
“Die Werbeaussage, wonach jeder Mensch eine Extraportion Vitamine oder Mineralstoffe zur Aufrechterhaltung der Leistungsfähigkeit und Gesundheit braucht, ist schlicht und einfach falsch“, sagte Jürgen Schölmerich, Facharzt für Gastroenterologie und ehemaliger ärztlicher Direktor und Vorstandsvorsitzender des Universitätsklinikums Frankfurt am Main. Nur für wenige Personengruppen, etwa Schwangere oder Veganer, seien bestimmte Nahrungsergänzungsmittel-Präparate tatsächlich empfohlen.
I think it is quite reasonable that childhood skin care practices is involved in the increase in atopic dermatis (AD) according to a recent review.
Kelleher and colleagues found skin barrier dysfunction precedes AD development. Thus, soaps and detergents may aggravate preexisting tendencies to skin barrier dysfunction and promote skin inflammation and initiate AD in susceptible individuals. Whether skin care practices have changed over time to explain the increase in AD incidence remains unknown, but high bathing frequency and the use of fragranced lotions are commonplace in US children, two practices potentially harmful to the skin barrier. Protecting the skin barrier early in life with emollients appears to reduce the risk of AD development.
While some researchers still believe that genetics cannot be responsible for the asthma epidemic as the prevalence increased with only two generations I have no doubt that (within the gene by environment framework) any environmental change is a necessary but not sufficient cause.
I would count also epigenetic changes as “genetic” while there seems now even direct evidence of an increased mutational load in humans
While the overall deleterious homozygosity has consistently decreased, risk alleles have steadily increased in frequency over that period of time. Those that increased most are associated with diseases such as asthma, Crohn disease, diabetes and obesity, which are highly prevalent in present-day populations.
N Engl J Med 2002; 347:869-877 made a strong point that the farm effect is mediated by endotoxin but could show only a 1,7 fold higher endotoxin exposure at farms.
LPS therefore will not explain the negative farm association as endotoxin effects are so much similar between farming and non-farming environment. BTW why is only the result of the total sample given here and not just the farm result?
N Engl J Med 2011; 364:701-709 table 2 endotoxin effect is not stronger at farms – more some unspecific immunosuppressive effect?
So, what is the reason for the lower IL10 capacity in Figure 2D after LPS exposure – exhaustion, adaptation? And even more important: What is the reason for the lower allergy rate at farms?
If we now go back to table 1 there is a 5,0 fold Der p1 excess in farm – much higher than the 1,7 fold increase of endotoxin. As nearly all allergens have helminth homologues – the question is what did the authors really measure? Da Costa Santiago 2015 has a nice table that could give an answer.
J Immunol. 2015 Jan 1;194(1):93-100 shows Der p1 homologs
Der p1 is a cysteine protease of 25kDa that has homologues for example in Loa loa. Unfortuneately Loa loa is not an explanation at Bavarian farms – as it is more common in tropical Africa. Cysteine proteases are nevertheless a big tool for helminths – in Schistosoma japonicum a cathepsin B2 cysteine protease is considered the main penetration tool.
Usually cysteine proteases are not allergenic, but the excessive (and rather isolated) rise combined with a reduced Der p1 sensitization in the children, is definitely an unusual finding. The Dermatophagoides pteronyssinus habitat is cosmopolitan, house dust, also influenced by altitude, but there is no known reasons for this excess in farms. Is the Der p1 value just a false positive and has it helminthic and not mite origin?
Wormbase blastp results – e+ values are somewhat lower than my local blast result at the same locus
With identity values between 40% and 70% there could well be a confusion of mite Der p1 and helminth (Fasciola?) CL6, which should be tested for cross-reactivity.
Helminth parasites have complicated life cycles … at the same time as skewing the immune system toward a Th2-driven response, they have a general suppressive effect on the host immune system that prevents their elimination and reduces immune-mediated tissue damage. It has been suggested that cytokines of the anti-inflammatory network, particularly IL-10 and transforming growth factor- (TGF-), that are produced in response to continual stimulation of the immune system by parasite antigens, are pivotal to regulating the damage they cause and that, coincidentally, these have a bystander protective affect against allergic reactions.
This is exactly what N Engl J Med 2002; 347:869-877 showed: increasingly exhausted IL10 capacity. May the x-axis label should be CL6 instead of LPS?
N Engl J Med 2002; 347:869-877 Figure 2. Smoothed Plots of the Log-Transformed Capacity of Peripheral-Blood Leukocytes (PBL) to Produce Interleukin-10 (Panel D) after Stimulation with Lipopolysaccharide (LPS) or Staphylococcal Enterotoxin B (SEB) in Relation to the Log-Transformed Endotoxin-Load Values.
A recent study in the NEJM found remarkable differences in the asthma prevalence between Amish and Hutterite populations. The lifestyle of both communities is similar but their farming practice is distinct as the Amish follow a more traditional style of outdoor grazing whereas the Hutterities use industrialized farming practices. Gene expression data in the Amish children have been interpreted as „intense exposure to microbes“ because protection of experimental asthma by Amish derived house dust was nearly abrogated in mice deficient for MyD88.
Any helminth exposure has been excluded due to low IgE and eosinophil counts in the children while I still think that this could be an explanation in particular as the attempt to show an effect of bacterial exposure was unsuccessful since the discovery of the farming effect.
One difference between conventional stable (Hutterites) and outdoor grazing (Amish) is the higher helminthic infection rate on pasture, mainly with Fasciola, Ostertagia, Eimeria, Cooperia, Dictyocaulus and Trichostrongylos species.
Infected cattle rarely demonstrate clinical disease, while it is known that Fasciola (as for example Schistosome) has numerous immunosuppressive functions in the host. IgE is not always raised as Fasciola can degrade human immunoglobulin or even induce eosinophil apoptosis.
Re-analysis of Gene Expression Network using string-db.org (String Consortium 2019). The gene expression network in Amish children {Stein et al., 2016, #73074} in the upper area has similarities with the network observed in sheep after Fasciola infection {Fu et al., 2017, #6751} module #1 and #3, in the lower plot.
The most recent study introduces FaRMI, a “bacterial relative abundance farm home microbiota index”, probably introduced as the authors couldn’t find anything else. It reminds me very much to the polygenic risk score that rescues your study if you could not find the gene.
Asthma prevalence has increased in epidemic proportions with urbanization
Already the first sentence is wrong if we look at the following plot where asthma is clearly levelling off.
Urbanization happened in the late späten 19th century and not after 1950. Source of plot: The prevalence of asthma in children: a reversing trend ( ERJ 2005 )
Unfortunately, the difference between farm and non farm children is never explained in the Kirjavainen et al. paper. What is the average distance of a non farm house to a farm house? Are there any joint school or sports activities of children from farms and non farms (allergens travel in the classroom)? And why is there such a strong conclusion in the title?
Farm-like indoor microbiota in non-farm homes protects children from asthma development
A lower risk score is not equivalent to protection.
And did any reviewer ever look at the plots or tables?
I do not understand Figure 3c. It even makes only sense when I cross out the top labels. But even then it menas: GABRIELA does not show a significant replication.
What should these values tell us? 5 times p<0.05 in a grid of 6×11=66 tests? Quantile regression that has been “adjusted” by the data?
The FaRMI calculation is overly complicated. Probably the calculation can never be replicated by changing software, changing samples, unclear wording, suboptimal dimension reduction and data snooping.
Farm home microbiota-like community composition was modeled in LUKAS1 with logistic regression analysis (PROC LOGISTIC statement, SAS version 9.3). The home location on a farm or non-farm rural environment was the dependent variable and the main components of PCoA axis scores of β-diversity matrices were the predictor variables. Bacterial and fungal microbiota were investigated separately. For both bacteria and fungi, separate models were built using axis scores from PCoA of abundance-unweighted and -weighted β-diversity matrices. The PCoA axes were selected based on the scree plot method including axes above the point at which the variance explained by the additional axes levels off (Supplementary Fig. 3). The models give an estimate of the probability that the sample is from a farm home. The farm home likeness of the microbial composition in the LUKAS2 non-farm homes was then estimated by applying the regression coefficients obtained from the LUKAS1-based models to the corresponding microbial data from LUKAS2 samples.Some analyses were performed in non-farm homes of both LUKAS2 and LUKAS1 to obtain increased sample size and power if results remain comparable as was observed. Due to the discovered association with asthma, the probability that was modeled based on the relative abundance-weighted bacterial/archaeal β-diversity was named FaRMI and was studied further in greater detail.
And isn’t that just an association that may have a rather simple explanation?
As FaRMI is weakly associated with muramic acid concentration in dust, the authors make Gram-positive bacteria responsible for the effect. The rhizosphere of soil is extremly rich of bacteria. The world’s first soil atlas showed hundreds of taxa but never differentiated between water resistant, gram positive and less water resistant gram-negative taxa. Maybe Gram positive Streptococcaceae are ubiquitous and depend on where you draw your samples?
FaRMI is found in non farm / rural children by bacterial/archaeal operational taxonomic units (OTUs) of soil origin which basically confirms my initial assumption: There was the same contamination of soil both in farm and non-farm homes if we look at supplement table 6 where walking indoors with outdoor shoes results in significant higher FaRMI values…Maybe the microbiome hype is already over.
Our results warrant translational studies to confirm the causal relationship through indoor microbial exposure-modifying intervention that may also form a novel strategy for primary asthma prevention.
Good luck with your future studies.
BTW – The scripts at Github are useless references to shell and Python scripts that will never run due to “—” characters. And what about that baby code?
Using R heredoc syntax I can rewrite 20 unreadable by 8 readable lines.
tmp <- 'Eigenvalue min / max: min.eigen / max.eigen
Sum of all eigenvalues: neg.eigensum
Sum of all eigenvalues (negatives as 0): nonneg.eigensum
Eigenvalues (pos & neg): pcoa
Percents (Negatives as negatives): neg.percent %
Percents (Negatives as 0): nonneg.percent %'
for (i in c("min.eigen","max.eigen","neg.eigensum","nonneg.eigensum","pcoa$value$Eigenvalues","neg.percent","nonneg.percent") ) { tmp <- gsub(i,get(i),tmp) }
write(tmp, file=paste(getwd(),out,"/")
And why moving to SAS for a simple logistic regression? Is there anyone else in the academic world who pays $8,700 annually for a basic SAS Windows Analytics package just for that reason?
