Schlagwort-Archive: von Mutius

Alte Freunde, neue Feinde – Gegendarstellung

O-Ton: “In dieser ersten Studie, die wir gemacht hatten, hatten wir einen Stadt-Land Vergleich. Wir haben München verglichen und die Umgebung. Und wir haben gesehen, dass, äm, in dieser allerersten Studie, das stärkste Signal war, dass wenn einer mit Holz und Kohle heizt, aber nicht im Sinn eines Risikos, sondern im Sinn eines Schutzes. Und das haben wir nicht verstanden.”
Sprecher: “Schliesslich erwähnte ein Schularzt beiläufig, dass er noch nie ein Bauernkind mit Asthma gesehen habe und brachte sie damit auf die richtige Spur.”

Gegendarstellung

Es ist nicht die erste Studie die ich gemacht habe und es ist auch nicht die erste Studie von Frau von Mutius. Wenn hier dennoch die Asthma- und Allergiestudie 1989 gemeint ist, dann halte ich dazu fest

  1. Bei der Schuluntersuchung fiel uns als Team (Sabine Braun, Annette Fuger und mir) auf, dass es in den kleinen ländlichen Orten im Ostallgäu mit viel Bauernhöfen nur wenig positive Prickteste in den Schulen gab.
  2. Frau von Mutius war nur am Rand mit der Studie befasst. Organisation, Durchführung und Auswertung lag bei uns beziehungsweise den Kollegen am damaligen gsf Forschungszentrum (Peter Reitmeir, Andrea Wulff u.a.) während Frau von Mutius mit klinischer Tätigkeit, Facharzt Weiterbildung, Organisation der Studie in München und einer Dissertation über rheumatische Erkrankungen ausgelastet war.
  3. Der Zusammenhang mit der Heizung beruhte nicht auf einem Stadt-Land Vergleich, sondern war nur in Oberbayern zu sehen.
  4. Und natürlich haben wir auch erklärt, dass der (statistische Zusammenhang) mit der Heizung nur in den Orten auftrat, wo sehr viel Landwirtschaft war.
  5. Von einem Schutz zu reden ist übertrieben – es war lediglich eine negative Assoziation.
  6. Ich habe nie gesagt, dass ich noch kein Bauernkind mit Asthma und Allergien gesehen habe. Natürlich haben auch Kinder auf Bauernhöfen Asthma und Allergien.
  7. Mehr oder weniger zeitgleich zu unserer Beobachtung im Dezember 1989 in Bayern wurde die Beobachtung der Bauernhöfe auch aus der Schweiz berichtet (Gassen-Bachmann. Allergie und Umwelt. Allergologie 1989; 12:492-502).
  8. 30 Jahre später ist der Bauernhof Effekt nicht verstanden, auch wenn bisher eine Vielzahl von Erklärungen verbreitet wurden.
  9. Alternative Forschungsansätze (Healthy Worker Effect, Vitamin D Supplementierung, Wurmerkrankungen, etc.) wurden bisher komplett ignoriert und nur auf einen Ansatz (“Hygiene-Hypothese”) fokussiert-
  10. Die wahrscheinlichste Erklärung ist ein einfacher Selektionsbias [1, 2]

New England Journal of Medicine Retractions

Retraction Watch says on Jan 30, 2020 that

Until yesterday the New England Journal of Medicine had retracted only 24 papers. Now that tally is 25.

While the retracted paper has been cited 190 times, here are inaccuracies in a NEJM paper that has been cited 1961 times. Full details are at PubPeer.

FIG 2C
FIG 1A

Is it justified to speak of a “protective” effect just by a  negative association?

In addition to the problems with the math, I don’t get the point – farming should be leading to a generally reduced capacity for numerous pleiotropic cytokines?

There are even reports that LPS induces TH2 dependent senstization – exactly the opposite of what this paper wants us to believe with soem cryptic smoother run over a heterogenous population.

Die Widerlegung der Farming Hypothese

Durch eine nachträgliche Korrektur (verschwiegene Interessenskonflikte) wurde eine frühere Farming Studie nun wieder an die Oberfläche gespült.

Die Ergebnisse der Studie sind eigentlich eindeutig und widerlegen die Bauernhof-Hypothese.

Tiere auf der Farm sind in den wohlhabenden Regionen nicht assoziiert, in weniger industrialisierten Regionen ein Risiko,

Besonders dubios wird die Diskussion des Artikel, sobald er auf Endotoxin zu sprechen kommt. Natürlich induziert Endotoxin eine entzündliche Reaktion, aber ist es nicht ein epidemiologischer Mythos, dass es eine protektive Endotoxinwirkung gibt?

Brunekreef (der sonst nie zu dem Thema gearbeitet hat, dem Stil nach auch die Diskussion nicht geschrieben hat) bevorzugt hier als Erklärung nun die übliche Endotoxin Variante, denn nur diese passt zu den Daten

This suggests that increased endotoxin exposure associated with early life contact with farm animals … could possibly be responsible for the [positive] associations seen in our study.

Damit stellt sich abschliessend die Frage, wie oft denn diese Studie (die überhaupt nicht in das Framing der Bauernhof Hypothese passt) wohl zitiert wurde? Scholar zeigt nur 15 Zitate, davon nur ein einziges Zitat durch von Mutius, obwohl es nun doch die grösste epidemiologische Studie zu dem Thema ist. Klarer Spin!

Dieses eine Zitat (Martikainen 2015) kam wohl auch nur durch ein Versehen zustande, denn es zitiert das Brunekreef Paper nicht für seine Hauptaussage, dass die Farming Hypothese widerlegt ist, sondern für den Anstieg der Allergien weltweit…

 

Update 11.12.2019

Ich habe an das “Journal of Clinical Epidemiology” geschrieben ob sie nicht auch finden, dass die Diskussion des Artikels völlig verzerrt ist. Das ist die Antwort

I am afraid that we found that your submission was not suitable for publication in the International Journal of Epidemiology. This decision was based on the editors’ evaluation of the merits of your manuscript compared with those of the many others we receive.
Stephen Leeder
Editor-in-Chief
International Journal of Epidemiology

Der angebliche Schutz vor Allergien auf dem Bauernhof

Keine Frage, die Lebensbedingungen auf Bauernhöfen sind anders. Mehr Tiere, mehr Dreck, mehr frische Luft, vieles ist anders als in derr Großstadt. Dass es hier auch weniger Allergien gibt, wird wohl auf Selektionsbedingungen zurückzuführen sein, und ist gut zu sehen bereits an einer der ersten Studien vor 30 Jahren.

Clin Exp Allergy. 1999 Jan;29(1):28-34. https://doi.org/10.1016/S0140-6736(01)06252-3 Hier nicht relevante Daten ausgegraut

Auch die Eltern hatten schon weniger Allergien. Der “protektive” Effekt kann also einfach dadurch erklärt werden, dass mit weniger Eltern als Risikoträger auch weniger Kinder mit Allergien haben (nennt sich population attributable fraction oder PAF).

Nehmen wir an, alle grau markierten Personen haben keine Allergie, nur die rot markierten. Dunkel sind alle Kinder mit Risikofaktor Genetik markiert, hell alle ohne. Das genetische Risiko ist gleich hoch, aber auf Bauernhöfen hat nur die Hälfte der Kinder eine Allergie. Man kann für den nicht existierenden Risikofaktor auch nicht bereinigen, wenn man eine Studie nur auf Bauernhöfen bzw der Landbevölkerung macht.

Wenn man genau hinschaut, dann haben alle Bauernhofstudien immer wieder dieselbe Argumentationsstruktur: weil die Bedingung X dort so ist, dann kann die Folge Y auch auf die Bedingung X zurückgeführt werden. Allerdings machen immer mehr Beschreibungen von X die Story nicht glaubwürdiger.  Keine der jemals beschriebenen Bedingungen X, ist aus der Bauernhofsituation auf eine allgemeine Situation übertragbar gewesen, von einem einzigen verunglückten Versuch einmal abgesehen.

Zur weiteren Erklärung hier ein simulierter Datensatz mit normal verteilter Allergiehäufigkeit und normal verteilten Endotoxinwerten. Zwischen beiden Variablen gibt es keine Korrelation. Wenn nun aber eine isolierte Studie nur im ländlichen Bereich durchgeführt wird, wo es weniger Allergien gibt, dann kann es durchaus eine negative Assoziation geben.

Eine Scheinassoziation kann jederzeit erzeugt werden, wenn durch eine Selektion nach bestimmten Kriterium durchgeführt wird. In dem Fall der rot markierten Fälle wurde nach niedrigerer Prävalenz und starken Kontrasten in der Endotoxin Belastung ausgewählt. Bei nur geringfügig unterschiedlichen Endotoxinwerten verläuft die Regressionsgerade nach unten. So verglich die bekannteste Studie zu dem Thema 319 Kinder mit hohen Endotoxinwerten mit 493 Kindern die nur mittlere Werten hatten NEJM 2002

 

Natürlich kann ein hoher Endotoxin Spiegel auf den Bauernhöfen eine bestimmte Wirkung haben –  zumindest bei einigen Menschen und bei einigen Mäusen – aber mehr als ein Effekt modifizierender Faktor ist völlig unwahrscheinlich.

Da die Lebensbedingungen auf dem Bauernhof angeblich protektiv sind, müsste es eigentlich auch ein Kind geben, das eine Allergie haben müssten (zB mit doppelter Familienanamnese über die letzten zwei Generation) aber nun keine Allergien bekommen hat. Aber solche Kinder gib es nicht, weil auch schon die Eltern keine Allergien hatten.

Farming and allergy prevention could be caused by Berkson’s fallacy

Lets look at the Wikipedia definition

Berkson’s fallacy is a result in conditional probability and statistics which is often found to be counterintuitive, and hence a veridical paradox. It is a complicating factor arising in statistical tests of proportions. Specifically, it arises when there is an ascertainment bias inherent in a study design … The most common example of Berkson’s paradox is a false observation of a negative correlation between two positive traits, i.e., that members of a population which have some positive trait tend to lack a second.

The original example is developed using the example of an hospital based group of patients. The only thing to know is that diabetes is a risk for cholecystitis in the general population.

Any given hospital in-patient without diabetes must have another disease (otherwise he would not be there), for example cholecystitis. And by definition this will be cholecystitis without diabetes caused by some other risk fff textbook factors. So in this group of in-patients there maybe a spurious negative association between cholecystitis and diabetes.

Basically some strong selection bias in a subgroup not only defined by the trait of interest but by some other trait as well?

My example here is with families who are living on farms. Since around 1960  [Leynaert 2001] it is known that farming families have less allergy, an effect that I found back in 1989 and that is most likely a healthy farmer effect.
This selected farm population has a lower allergy prevalence and of course their children will also have less allergy. All the negative correlations (that are interpreted as protection) with endotoxin, microbiome, etc could be caused by this bias (Linneberg 2005). The observation will also be even replicated as the same selection criteria are also present in the replication sample.

What is wrong with the 2011 NEJM paper?

N Engl J Med 2011;364:701-9 is another paper with 1000+ citations  that had a lasting impression on some but not all people.

First, I can’t remember of any study with such an enormous selection bias  where >94% of individuals have been lost.

Second, we should not forget that farm is not protective per se – farmers may just avoid a known allergy risk factor.  PARSIFAL participants in this study included Steiner schools — anthroposophic medicine mostly avoids vitamin D (ref). This is of course a major issue for any cross-sectional study that doesn’t take into account the temporality of events.

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.

Allergy protection on farms – why also studies in mice could have failed

There are  many immunological differences in humans and mice (follow my link) that are never discussed — not even in Science 2015;349/6252:1106.

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 ??

Does a healthy worker effect explain the “allergy protection” at Bavarian farms?

Unfortunately most studies in the farming environment did not report the prevalence of parental history nor did they report the effect size of parental 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]

At least Braun-Fahrländer 1999 reported that allergic parents were seen much less at farms: allergic rhinitis 12.7% versus 29.4% (P=0.001). A history of allergy at farms is no more a risk factor as it is otherwise in the general population. How that? Risk genes or risk behaviour (supplementation) has been eliminated.

Are there any studies in adults? I know of three studies (and one review Le Moual N 2008).

Leynaert 2001 showed only a slightly reduced prevalence of “allergy” (39.1% vs 41.5%, NS) while her table 4 is most interesting. The association started only after year 1960 which points towards 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.

A HWE is therefore likely.

There are 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 for any conclusion while Braback 2006 seems to be the only reliable study.

Source: Braback 2006

Also 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. For asthma it is important to discriminate atopic and non-atopic asthma.

Timm 2019: a hard to understand 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. Neither protection by farm nor HWE found but also selection bias (approx. 50% dropout) and non-differential bias for residency.

Eduard 2015: 1,964 farming students. Current asthma in farmers was 3.0% compared to 6.3% in farmers who had retired early. No HWE found at entry level but during farm work.

Farmers who had changed the type of production had an increased risk of current asthma (OR 9.8), compared with those who had not changed production, indicating a strong selection effect.

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.

Taken together – more data but not more knowledge.

Claim to fame of the hygiene hypothesis

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.

  1. So the interest is technology and not science driven.
  2. The microbiome is not an organ.
  3. The hype is already over.
  4. The Self is not defined by any bacterium.
  5. 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 endotoxin phantom – discrepancies in the NEJM 2002 farm paper

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.

N Engl J Med 2002; 347:869-877 table 1 shows environmental exposure between farm and non-farming households

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?

I am therefore blasting Der p1  sequence (P08176) against all known cow endoparasite genomes. Fasciola has a strong hit with CL6, a papain family cysteine protease with e+48.

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.

The story even gets more interesting when reading more about parasites

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.

 

 

The Amish paradox in NEJM 2016 explained

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.

FaRMI

I will add now a special collection of farming studies here as many of them are just candidates for the Ig nobel prize.

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?

outfolder=getwd()
eigenfile <- paste(outfolder, "/", prefix, "_PCoA_eigenvalues.txt", sep="")
writerow <- paste("Eigenvalue min / max: ", min.eigen, " / ", max.eigen, sep="")
write(writerow, file=eigenfile, append=F)
writerow <- paste("Sum of all eigenvalues: ", round(neg.eigensum, digits=6), sep="")
write(writerow, file=eigenfile, append=T)
writerow <- paste("Sum of all eigenvalues (negatives as 0): ", round(nonneg.eigensum, digits=6), sep="")
write(writerow, file=eigenfile, append=T)
writerow <- "Eigenvalues (pos & neg): "
write(writerow, file=eigenfile, append=T)
writerow <- paste(pcoa$value$Eigenvalues, collapse="\t")
write(writerow, file=eigenfile, append=T)
writerow <- "Percents (Negatives as negatives): "
write(writerow, file=eigenfile, append=T)
writerow <- paste(paste(neg.percent, " %", sep=""), collapse="\t")
write(writerow, file=eigenfile, append=T)
writerow <- "Percents (Negatives as 0): "
write(writerow, file=eigenfile, append=T)
writerow <- paste(paste(nonneg.percent, " %", sep=""), collapse="\t")
write(writerow, file=eigenfile, append=T)

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?

How to interpret an odds ratio of less than 1

In a recent paper, I read that an OR of 0.7 means a 30% risk reduction.  Let’s have a look on the following table to see why this is wrong

 Disease+Disease-
Exposure+a=7b=10
Exposure-c=10d=10

The odds of an event is the number of those who experience the event divided by the number of those who do not.
Comparing the odds in an exposed and a not exposed group results in the simple odds ratio OR formula.

OR = (a/b) / (c/d) = a*c / b*d

The interpretation is straightforward for more patients in the exposed group: With a=13 we get an OR=1.3.

An odds of 0.7 however is less intuitive to interprete. 0.7 people will experience the event for every event that does not occur. This translates to one event for every 1,42 non-events, the reciprocal value of 0,7. The percent change PC is therefore

PC = 1/0,7 - 1 = 1,42 -1 = 0,42 = 42%

42% and not 30%. Read more.

The end of the hygiene hypothesis

The authors put a question mark at the end of the above statement while I would not hesitate to put an exclamation mark there. Writing this as a comment to a new study in the IJE they summarize the evidence that the “epidemics” of asthma in Western countries has begun to decline – as hygiene standards are not declining this might indicate the end of the hygiene hypothesis. The end of the hygiene hypothesis weiterlesen