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Good Bugs Gone Bad: The Microbiome in Health and Disease · Pediatrics Now: Cases Updates and Discussions for the Busy Pediatric Practitioner

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I'm Holly Wayment, and this is Pediatrics Now, cases, updates,
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and discussions for the busy pediatric practitioner.
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Click on the link in this podcast for MOC credits.
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Today I'm bringing you this fascinating episode, a Grand Rounds talk.
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Let's listen in. It's my great pleasure to introduce this morning's Grand Rounds speaker, Dr.
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David David Haslam, who is a professor of pediatrics in the Division of Infectious
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Diseases at Cincinnati Children's Hospital,
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where he is medical director of the Antimicrobial Stewardship Program and director
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of the Microbial Genomics and Metagenomics Laboratory.
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Dr. Haslam received his MD from the University of Calgary Medical School,
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and he completed his residency in pediatrics at Children's Hospital of Eastern
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Ontario at University of Ottawa.
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Subsequently, he did his clinical fellowship in pediatric infectious diseases at St.
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Louis Children's Hospital, Washington University School of Medicine,
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and research fellowship in molecular microbiology also at Washington University
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School of Medicine in St. Louis, Missouri.
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Dr. Haslam's research focuses on childhood diseases caused by bacterial toxins
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and the role of microbiome in health and disease.
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His interest in microBAM is closely related to his goal of improving appropriateness
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of antibiotic prescribing practices as antibiotic-induced disruption of microBAM
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appears to place children at greater risk of disease,
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including hospital-based acquired bloodstream infection. perfection.
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Dr. Haslam, thank you very much for accepting our invitation.
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I know you are very, very busy. You're on clinical service right now and still
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decided to join us today. So, really appreciate it. The floor is yours.
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Oh, thank you very much. It's my great pleasure to be invited.
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Thank you very much and discuss some of our work, both as in my role as director
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of the Antimicrobial Stewardship Program, and role as director of the Microbial
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Genomics and Metagenomics Laboratory,
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otherwise known as the Microbiome Laboratory.
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So I'm actually going to talk about both of those roles and hopefully convince
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you how I think they overlap and how my interest in the microbiome is really driven by antibiotic.
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Prescribing practices and how they may influence the microbiome for better or worse.
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Then I'll say mostly for the worse as we'll find out as we go along.
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So I don't have any relevant financial disclosures or conflicts of interest.
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And we'll start by saying, as I'm sure you're all aware, that the human skin
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and mucosal surfaces harbor a diverse community of microbes.
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And this has now been well established over the past 15 plus years,
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where at that time, new technology allowed us to really document or investigate which organisms,
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which microbes were present in different parts of the body.
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So we know, for example, that the gut, the intestine, harbors actually more
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than 2,000 species of bacteria, fungi, and viruses.
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The mouth is also, not shown on this slide, but the mouth is also a very rich
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microbial environment.
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Almost as many species of bacteria live in the mouth as in the intestines, surprisingly.
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And the skin as well has a very diverse microbiome.
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And I would say as clinicians, we don't really think about the microbiome very
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often, if at all, but probably as I go through the presentation,
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you'll see that I think there are clear cases where the microbiome does influence
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health, and in particular,
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from my perspective as an infectious disease doctor,
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influences our risk for infection.
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We do know now that these microbes usually serve beneficial functions.
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They provide nutrients and metabolites that we're still understanding how that influences health.
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But a very clear example, I think, for pediatricians that we've known about
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for a long time is that the intestinal microbes provide us with vitamin K.
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So humans have no ability to make vitamin K on our own.
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We rely on microbes in the intestine to metabolize precursors to produce vitamin K.
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And we know that because one of the first things we do to babies after they're
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born is give them a shot of vitamin K,
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and that's to give them a boost until the babies are able to establish their
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own microbiome, which can produce vitamin K without supplementation.
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We know sometimes in kids, if we treat them with very broad spectrum antibiotics
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for prolonged periods, they're at risk of hemorrhage because of vitamin K deficiency,
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and that's because we deplete microbes that provide that vitamin.
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But we're learning more and more about beneficial metabolites that are produced
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by the microbiome and could influence health.
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In that regard, there have been many, many studies now that have looked at a
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link between the microbiome, that is, which organisms occupy the intestine,
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the mouth, or the skin of a person, and how that relates to disease.
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I like to show this graph looking at the number of publications every year that
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describe some sort of a link or putative link between the microbiome and disease states.
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And some of those diseases that have been most implicated in as associated with
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the microbiome are allergies and atopic diseases like asthma,
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heart disease, cancer, diabetes,
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many immune mediated disorders, especially inflammatory bowel disease,
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but even neurologic inflammatory diseases like multiple sclerosis.
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And even neurologic diseases, which seems a little bit counterintuitive if we
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think that there shouldn't be any microbes in the brain influencing risk for
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Alzheimer's or autism or Parkinson's disease.
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But it's not so much the presence of the organisms in the central nervous system
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that seem to contribute to these neurologic diseases, but rather it's the metabolites
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that are produced by organisms,
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for example, in the gut or the mouth or skin that may then go to the brain and
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influence risk for some of these other diseases.
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I don't study any of these diseases directly,
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but in my role as the director of the microbiome lab,
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we have worked with many investigators across the university and the surrounding
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area to look at most of these disease states and compare the microbiome,
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for example, in people with or without autism or Parkinson's disease.
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Areas that I have been directly involved with include C.
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Diff infection. So this is probably the disease where there's the very clearest
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link between abnormalities in the microbiome and risk for C. diff infection.
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We all know that antibiotics are the major risk factor for C. diff infection.
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And we now know that replacing the microbiome, for example, with fecal transplant
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from a healthy person is a very effective preventative against C.
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Diff infection. And now there are some products on the market that are derived
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from mixtures of organisms that can colonize the gut and protect against C.
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Diff colonization and infection.
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So very clear associations between an abnormal microbiome and C.
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Diff risk. But I'll show you some work that we've been doing that shows,
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at least in hospitalized, high-risk patients, there's a link between an abnormal
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microbiome and risk for invasive disease.
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So we'll jump right in and look at that data now.
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So we did a study looking at patients at very high risk for bloodstream infection,
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including bone marrow transplant patients, liver transplant,
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kids with intestinal failure, or often called kids with short guts.
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So many of these are babies or children who had small bowel resections due to
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necrotizing enterocolitis and were subsequently TPN dependent.
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And then children at our institution who had undergone small bowel transplant.
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So these are, in our hospital, are the children that are at highest risk of
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bloodstream infection.
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And we did a prospective study where we collected stool samples from these children
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and then monitored for children that subsequently developed a bloodstream infection.
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And you can see that the rates of infection were very high.
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During this two-plus-year study period, 13% of bone marrow transplant patients
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developed bloodstream infection. and you can see the rates in other disease
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states were even higher.
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So that meant that we had stool samples in many patients before they developed
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a bloodstream infection.
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And then in some children, excuse me, we have stool samples after they develop
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bloodstream infection.
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And so we could look at microbiome in those kids and see if we saw any difference
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between children that develop bloodstream infection and those that didn't.
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And our hypothesis was that we would see differences in the kids that develop
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BSI compared to those that didn't. And in fact, that's what we found.
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So just to take a step back and discuss how we measure the microbiome or how
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do we know which organisms and how many of those organisms are there,
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what we do is take a sample.
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So in this case, we're looking at stool samples, which contain bacteria,
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different types of bacteria, fungi, and viruses.
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And we extract all of the DNA from the stool sample.
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And then we go through a process of digesting the DNA and then subjecting each
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fragment to next generation sequencing.
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And we use those sequences as a bar tag basically to align to a database of microbial genomes.
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And if there's a match between a DNA fragment sequence and the genome database,
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then we assign that read to that microbe.
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And then we can count up the number of reads that is aligned to different microbes
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and present the data in different ways, including this bubble graph,
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which is one way I like to look at the data.
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So in this bubble graph, each circle is an organism, and then the size of the
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circle represents the abundance or the amount of that bacteria in the sample.
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And you can see, for example in this sample there are many many different bacteria.
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And in many cases, it's a fairly diverse microbiome. So there are lots of different organisms.
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One or two are most prevalent, but in general, it has a good diversity,
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which is in the stool is a good thing.
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And so when we looked in our patient cohort, we saw patients like this.
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This is a bone marrow transplant patient who came into the hospital for conditioning
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for bone marrow transplant. We had a stool sample shortly after the patient
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was admitted that looked like this.
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So there were many different organisms similar to the previous slide.
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And most of these were normal commensal organisms.
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So bacteroides, very common, and other organisms that should be in the gut and
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we would say are generally thought to be beneficial.
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The child was undergoing chemotherapy
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and conditioning for bone marrow transplant, plant, spiked a fever,
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and you can see compared to this sample on December 6th, after receiving antibiotics
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for a few days, the microbiome had totally changed and now was completely dominated by E. coli.
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And the antibiotic treatment continued.
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The patient continued to have low-grade fevers and then became acutely ill,
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septic actually, became hypotensive and had to go to the intensive care unit
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and was started on pressers and was very ill.
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And the blood culture, two days after the stool sample, grew E. coli from the blood.
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And so we can actually not just look at the organism, but we can look at relatedness
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and and compare the genetic sequence of this E.
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Coli compared to the organism that was in the gut previously,
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and we're able to show that these are essentially identical organisms.
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So to us, this suggested that, or indicated that antibiotic treatment had disrupted
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the normal microbiome, allowed proliferation of this E. coli, and then the E.
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Coli went from the intestine into the bloodstream.
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This patient's E. coli was resistant to antibiotics and it took us a little
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bit of time to get the patient on the appropriate antibiotic,
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but fortunately the patient recovered
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and subsequently had the bone marrow transplant and has done well.
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This is kind of an extreme example. We had many patients that didn't have as
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much disruption during antibiotic treatment, But I would say there were several
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patients where we saw a similar pattern.
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And overall, I'll show you how there are associations across all patients between
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the microbiome and bloodstream infection.
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But I would say this experience and working with our BMT colleagues,
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as well as oncology and critical care,
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situations like this where we can say really antibiotic treatment,
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in this case, seem to predispose to infection has had a pretty big impact on
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the way we think about antibiotics,
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even in our highest risk kids.
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So, the previous slide was one individual patient experience.
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When we look across all of the samples, one way to look at the microbiome composition
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in children that have bloodstream infection compared to those that don't is
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to look at the microbiome composition
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in this 2D graphical method called principal component analysis.
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And in this analysis, each sample is a dot, and then the closer together the
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dots are, the more similar the samples are, the more similar the microbiome composition is.
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And here we're looking at 55 control samples, so healthy patients.
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And you can see in this analysis, those 55 samples all cluster fairly closely together.
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Then we looked at patients who develop bloodstream infection within 30 days
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of having a stool sample.
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And when we looked at these kits that developed bloodstream infection and looked
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at their stool within the last 30 days before developing bloodstream infection,
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we could see that essentially none of them had a microbiome composition that
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would fall within the normal range.
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And that was the case no matter what type of organism caused the bloodstream infection.
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We saw essentially all of the kits that developed bloodstream infection had
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an abnormal microbiome prior to developing the invasive infection.
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So when we looked at which organisms were associated with risk of infection,
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we found a little bit surprisingly that it was mostly a decrease in the protective
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bacteria that was correlated with risk of bloodstream infection and not so much
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the abundance of pathogenic bacteria.
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Pseudomonas was correlated with risk for infection. And lower on this list, things like E.
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Coli abundance and Klebsiella abundance were correlated with risk.
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But it seemed in this analysis that it was, in fact, a decrease in these really
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commensal or beneficial bacteria that was a greater risk for subsequent infection.
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So it seems like they really are protective against developing invasive infection.
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And so that leads to the model that kids may come into the hospital with a diverse
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microbiome, which we would say is protective against infection,
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receive antibiotics that in
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many kids really disrupts the microbiome and leaves pathogenic organisms,
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often antibiotic-resistant pathogenic organisms.
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And this is really a setup in high-risk kids for developing invasive infection.
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Things like breakdown of the intestinal barrier through chemotherapy,
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alteration on feeds that may impair beneficial metabolites, may allow the gut
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to become leaky, and let these organisms into the bloodstream to cause sepsis.
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Another area that we were interested in was whether there was any evidence that
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kids that harbored an abnormal microbiome might be the source of transmission
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of those resistant organisms to other children in the hospital.
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And in fact, when we looked at organisms in the stool of these high-risk cohorts,
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we were able to see several examples where we thought there was evidence of
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transmission of a pathogenic organism from one patient to another.
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So this slide shows each point on this graph is an individual sample,
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a stool sample, and we're looking at, in this case, E.
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Coli within the stool of these patients.
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The samples are colored by patient identity, so this is one patient that gave
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us two stool samples with E.
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Coli, and when we compare the E.
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Coli, these two are very close to each other, essentially identical in genetic sequence.
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So this child had the same E. coli at two different time points.
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And when we look at different patients, we see that they're often colonized
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or carrying the same E. coli in their gut over time.
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This was a patient, a liver transplant patient, who carried the same E.
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Coli in the stool, but also developed invasive bloodstream infection with the same E. coli.
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When we looked at other patients, one of these was a liver transplant patient,
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but there was a bone marrow transplant patient who didn't seem to have any overlap
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in the hospital with these patients.
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Nevertheless, these three kids seem to have exactly the same E. coli in their gut.
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This doesn't prove that there was direct transmission from one child to another. other.
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In fact, it probably wasn't direct transmission, but we would argue this suggests
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that there was a route through the hospital that E.
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Coli from one child was able to colonize other children.
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This expands this section a little bit. We looked at this hypothesis in a slightly different way.
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So last year, two years ago, we were noticing an increase in infections with
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vancomycin-resistant enterococcus among our bone marrow transplant and oncology patients.
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So this is a number of VRE isolates, invasive infections in our hospital.
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And you could see that we really had none for several years and then a real uptick.
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And so we wondered, what's driving this? And was this due to colonization?
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Was it due to transmission? mission? Or were these just random and just happened
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to be different organisms, but a random spike in the number of VRE infections?
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And so one of our fellows actually, Catherine Murphy, collected these invasive isolates,
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the blood isolates, but also we had been screening for VRE colonization and
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then culturing that VRE to collect those organisms and ultimately compare pair
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of them between organisms,
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theory of organisms in the gut from patients compared to the invasive isolates.
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So in this case, it's a little bit different. We're not looking at the microbiome,
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but we're looking at individual organisms cultured from either the stool or
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from blood or respiratory tract and isolates.
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And when we did that, we found that most of the isolates collected over this
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time period were exactly identical.
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So, the genetic sequence was identical between these VRE isolates,
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even though some of them came from stool.
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For example, two oncology patients in July of 2022 had an organism in their intestine,
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that was identical to subsequent isolates you can see from oncology patients
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from the bloodstream three months later.
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So it did look like there were patients that were colonized with VRE.
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These two kids didn't, or one was an adult, didn't develop invasive infection,
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but subsequent patients did develop invasive infection with VRE.
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And we would say likely either these patients or other patients that we weren't
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sampling could have been the source for these later infections.
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So that leads us to the point where we think that if we monitor high-risk kids
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in the hospital by collecting stool samples, or I would say even skin or oral samples,
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we may be able to use methods like shotgun
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sequencing or metagenomic sequencing to look for the
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presence of an abnormal microbiome that
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would put a child at risk and and subsequently
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hopefully be able to intervene potentially by
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ideally using fewer antibiotics in
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these high-risk kids that might disrupt their microbiome less but at least have
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a clue as to which organism the child's at risk of the infection with and this
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extends not just to the high-risk hits that I've discussed so far.
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We've also been looking at the microbiome in preterm infants.
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And this is driven largely by Yan Ping, who's a neonatologist from Zhejiang
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University in China, as well as my colleague in neonatology,
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Henry Akimbi, here at University of Cincinnati.
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And we were interested in the known observation that the type of organism that
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causes infection in preterm babies is different in the United States compared to China.
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So in the U.S. now, most bloodstream infections in preterm infants are caused
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by gram-positive organisms.
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That's shown at the sort of highest level here, where we compare babies in the
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NICU from Cincinnati versus Hangzhou,
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where in Cincinnati, most bloodstream infections over a two-year period are
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caused by gram-positives, whereas in China, Hangzhou, China,
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most bloodstream infections are gram-negatives.
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And in particular, Klebsiella accounts for most of the bloodstream infections
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in Hangzhou, whereas in Cincinnati, most bloodstream infections in babies are from Staph aureus.
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And so our hypothesis was, if that's the case, it probably is related to the
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underlying microbiome.
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So probably the organisms that are present on the skin or in the gut of babies
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in Cincinnati is different than the babies in Hangzhou.
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And so we sought out to investigate that by collecting stool samples and skin
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swabs from babies at day 7 of life and day 21 in both centers,
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and then sequencing the microbiome to look for potential differences in the
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abundance of organisms.
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And indeed, when we look overall at all of the samples obtained during the study
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and compare the organisms that are most abundant,
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we find that Staph aureus is the most abundant bacteria in the microbiome of kids in Cincinnati,
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whereas in honcho, Klebsiella pneumoniae was the most prevalent.
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Similarly, for example, organisms like Acinetobacter and Etrobacter were much
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more prevalent in honcho than Cincinnati,
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whereas other gram positives like Staph febi were somewhat more abundant in Cincinnati.
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And that's shown graphically here when we look at either axilla,
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groin, or stool at week one or week three of life in either Cincinnati or Hangzhou.
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And we can see, for example, for Klebsiella, at most time points and body sites,
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the abundance of Klebsiella was higher in Hangzhou than Cincinnati.
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Interestingly, that was the case for axilla and groin, so skin samples had a
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lot of gram-negative organisms.
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And it was less notable in the stool, which was a little bit of a surprise to
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us, because we would have assumed that if Klebsiella is causing bloodstream
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infections in these babies, that it was probably coming from the stool.
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But actually, this information suggests that maybe Maybe Klebsiella infections
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in babies in Hangzhou may be coming from the skin rather than the gut.
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We saw similar trends with Acinetobacter. So recall that these organisms caused
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most of the bloodstream infections in Hangzhou.
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And we saw increased abundance of Acinetobacter in Hangzhou compared to Cincinnati.
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And it was the inverse when we looked at staphylococci. So staphorus was by
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far the most abundant organism on the skin of the axilla and groin skin in babies in Cincinnati,
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and more abundant than compared to Hangzhou, and more abundant than the stool.
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And that was the case for stapepi as well. So overall,
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we found that staphorus and stapepterminus were more common cause of bloodstream
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infection, and also much more abundant on the skin in Cincinnati compared to babies in Hangzhou.
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So there is an overall correlate between differences in the microbiome and risk for infection.
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And I guess in some ways that's intuitive, although I would say when I started
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out as an infectious disease fellow or junior faculty, I think we used to think
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that these organisms, like a staph aureus bloodstream infection just came out of nowhere.
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It was because the line was put in incorrectly or there was transmission directly
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from one baby to another.
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But now I think we're starting to see that it's what happens for weeks,
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days to weeks before a bloodstream infection that really put the baby at risk.
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So what are the drivers that account for increased amounts of staph aureus on
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the skin in babies in Cincinnati?
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And what are the drivers of increased
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klebsiella and acinetobacter in the microbiome in babies in China?
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And could we adjust those to influence the risk of bloodstream infection,
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ideally to decrease all of them with commensal organisms and hopefully prevent
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infection with any of these pathogens?
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So I'll revise an earlier slide to say that it may not just be the gut,
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but the skin microbiome is probably an important contributor to risk for bloodstream infection,
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both in the newborn nursery, but also in our high-risk patients.
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So we were interested in not just identifying the organisms that were present
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on the microbiome that seemed to correlate with risk for infection,
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but could we actually predict which antibiotic was likely to be the most effective
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against those organisms if the patient did develop bloodstream infection?
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So here we're using fairly advanced machine learning tools to try and predict
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antibiotic resistance based on microbiome data. And I'll show you how that works.
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So for example, this is that patient I highlighted earlier.
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What if we could tell here that this E. coli was resistant to multiple antibiotics?
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It certainly would have influenced, I think, what we did when the patient became septic.
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We probably would have been able to more quickly get the patient on the appropriate antibiotic.
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So what we'd like to be able to do is not just identify abnormalities in the
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abundance of organisms, but be able to predict which antibiotic is most likely to be effective.
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And so we started that by looking at individual isolates and developing a neural
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network to go from the sequence of this organism to predict which antibiotics
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were likely to be sensitive or resistant.
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Active or inactive against this E. coli.
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And so I had a summer student from Harvard who had never done any programming.
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He hadn't any experience with machine learning beforehand, nor did I,
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but we decided we were going to try and do this.
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So we took many, many different isolates of E.
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Coli, Klebsiella, Pseudomonas, and then had sequence data for them.
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And we looked at the abundance of resistance genes and then the coverage,
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basically how much of the gene was present in the organism.
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And then he developed this neural network to be able to predict resistance to various antibiotics.
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And by the end of the summer, he had developed a neural network that was very accurate.
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So you could feed in, we could sequence an E. coli or a Klebsiella pseudomonas
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and then feed it into this neural network.
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And it could predict meropenem or or cefepime, or other antibiotic susceptibility
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based on known susceptibility of those organisms with what we predicted very accurately.
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And for example, for Staph aureus and methicillin resistance,
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we were essentially 100% accurate in predicting resistance.
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So this was nice, at least from individual organisms that we already grew in
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the laboratory, had already tested in the the clinical lab for resistance and
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then could predict their resistance based on their sequence.
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We wanted to know if we could extend this to a sort of crude microbiome data.
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So could we take a stool sample, sequence everything that was in that stool
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sample, and then identifying antibiotic-resistant organisms in that stool sample?
31:26
And so I had another, I was a co-mentor of PJ Van Camp, who's,
31:30
it was actually a pediatrics resident from Holland who came to Cincinnati to
31:36
do a bioinformatics PhD.
31:38
So I was a co-mentor of PJ and he took the work that Max had done previously
31:44
and applied this to the microbiome and had a very productive couple of years
31:50
and was able to develop a few tools that could take shotgun sequencing data.
31:56
So just all of the sequence information from a stool sample,
32:02
and then be able to predict the presence of an antibiotic resistance gene or
32:08
organism with very high accuracy.
32:11
And not only could he predict the presence of an resistant organism,
32:16
but he could say it's likely to be E.
32:19
Coli that carries this resistant mechanism, or it's likely to be Klebsiella.
32:24
And so we think now that from just taking a stool sample, putting it through
32:30
this sequencing protocol, we can predict the presence of a multidrug-resistant organism.
32:38
And if we could do that in real time, cheaply, neither of which are possible
32:43
now, but if we could do that, we think it could be quite beneficial,
32:47
especially for these kits that are likely to develop bloodstream infection during
32:51
their hospitalization.
32:54
So just to turn to one last project that we did looking at antibiotic resistance
33:00
and antibiotic effect, this follows up on the work that I mentioned from preterm infants.
33:07
And here we're looking at how antibiotic exposure affects the microbiome.
33:12
It's developing in preterm infants.
33:15
And then I'll show you that we can look at not just that presence of resistant
33:19
organisms, but actually expression of those resistant genes.
33:24
So when we look at the microbiome at babies at one week of life,
33:29
and these are preterm infants,
33:31
their microbiome, this is again a principal component analysis where this looks
33:36
at the whole abundance of organisms in the gut or the skin, and then looks how
33:42
similar the samples are.
33:43
And then we can group them based on, for example, these are samples from the
33:48
axilla of babies at week one. This is at week three.
33:52
So you can see there's a shift in the overall microbiome composition based on
33:57
where the samples fall on this PCA block from week one to week three.
34:03
So early in life, the samples are a little bit more closely clustered together. other.
34:08
And over a two-week period, there's maturation and differentiation of the microbiome
34:14
in babies that do not receive antibiotics.
34:18
So these are, although these are preterm kits, actually our NICU now is remarkably
34:23
not treating most preterm babies unless they have evidence of sepsis.
34:28
That's a change from recently when all preterm babies used to get a sort of
34:33
a rule out with antibiotics.
34:34
That's not the case in most preterm babies in our NICU anymore.
34:39
But many babies did get antibiotics during that first three weeks of life,
34:44
and compared to babies that didn't get antibiotics at week three here in the upper sort of circles,
34:51
we found that antibiotic exposure pushed or blunted maturation of the microbiome.
34:58
So compared to babies without antibiotics, the microbiome was more blunted towards
35:03
this less differentiated state compared to babies that didn't get antibiotics.
35:09
So, we argued that antibiotic exposure blunts maturation of the microbiome,
35:14
and if that's the case, then organisms that are beneficial for gut development,
35:20
for example, may be impaired in their maturation in babies that received antibiotics.
35:28
So, we looked at genes for production of metabolites called short-chain fatty acids.
35:34
So butyrate and acetate are thought to be beneficial for gut health,
35:39
and we found that in babies that did not receive antibiotics,
35:43
they acquired genes in bacteria able to produce butyrate from week one to week
35:49
three, and this should be beneficial then for gut health and gut development.
35:54
But if babies received antibiotics, we completely blunted their acquisition
35:59
of these beneficial metabolic genes. genes, and that was the case for acetate as well.
36:05
We also saw enrichment for antibiotic resistance genes in babies that received
36:11
antibiotics versus babies that didn't.
36:14
This is perhaps not too surprising, but still worrisome, I would say.
36:19
These are immunoglycoside-resistant genes that were more abundant in babies
36:22
that received Ceptas-Ampgentomycin compared to babies that And same with broad-spectrum
36:29
antibiotic resistance genes like CTXM and OXA beta-lactamases.
36:35
And this gets a little bit complicated as if I haven't given you lots of complicated
36:40
data already, but here we're looking not just at presence of an antibiotic resistance
36:45
gene, but how highly is it expressed.
36:48
So not only is the DNA present, but if it's being expressed at high level,
36:53
the RNA will be expressed to an even greater degree than abundance of DNA.
36:59
And so we could look at expression of individual antibiotic resistance genes
37:04
based on RNA versus DNA abundance in babies that had no or low antibiotic exposure
37:12
compared to babies that had high antibiotic exposure.
37:15
And we saw really dramatic increases in expression of several antibiotic resistance genes.
37:22
We saw, for example, AMP-C beta-lactamases were markedly upregulated in the
37:28
intestines of babies that received antibiotics.
37:30
And this is actually a known thing. You may have heard of inducible beta-lactamases.
37:36
So those are the AMP-C beta-lactamases, where antibiotic exposure is known to
37:41
turn on expression of these genes and can make organisms resistant to treatment on therapy.
37:48
So this was somewhat expected, but we saw increased expression of,
37:52
for example, aminoglycoside-resistant genes and other very extended beta-lactamases.
37:59
And this hasn't been seen before. But what it suggests to us is that exposing
38:04
these preterm babies to antibiotics not only enriches abundance of the genes,
38:11
but turns on their expression to make it more likely that they'll be resistant
38:15
if the baby develops an invasive infection.
38:19
So that's a lot of information, but I've summarized the key points here.
38:23
Organisms present in the gut, skin, or oral microbiome are the likely source
38:28
of the most invasive infections in the hospital, and I'd argue in the community as well.
38:34
Asymptomatically colonized individuals may be the source of transmission to other kids,
38:39
at least in the hospital and probably in the community, and that antibiotic
38:43
exposure modifies the microbiome to decrease the presence of beneficial organisms
38:49
and increase the environments of pathogenic organisms.
38:53
Further, antibiotics increases the presence and the expression of antibiotic resistance genes.
38:59
So antibiotic exposure increases the risk for later invasive infection with
39:05
antibiotic resistant organisms.
39:08
So, this is all well and good, but it's all research and right now not very
39:14
applicable to real-time actionable information.
39:19
But nevertheless, I will say that our work on the microbiome with our colleagues
39:24
in bone marrow transplant,
39:25
oncology, and other transplant services, I think has, they've contributed all
39:31
of these samples and been involved in the analysis.
39:35
And I think it's really changed the way that we think about what we're doing
39:39
with antibiotics in kids that are at risk of subsequent infection.
39:45
And I would say for my first several years as a director of the Antimicrobial
39:50
Stewardship Program, we were really focused on those high-risk kids.
39:54
And we've had an impact there. I'll show you some of that data in a minute.
39:59
But in reality, most antibiotic prescribing happens in the outpatient setting.
40:05
And that's an area where we have been less focused, but I think we've realized
40:11
now that we've had some impact on our high-risk hospitalized kids,
40:15
but most antibiotic prescribing actually happens outside the hospital.
40:19
And we think much of what happens in hospitalized kids also happens in the community
40:25
when we expose kids to antibiotics.
40:28
So I don't have to convince anybody that there have been increased rates of
40:33
antibiotic-resistant infections,
40:34
at least over the previous years, and that antibiotic resistance results in
40:40
worse outcomes for patients and also for the healthcare system,
40:44
accounts for lots of costs.
40:46
We know that young kids receive the highest rates of antibiotics.
40:50
So this is number of antibiotic prescriptions in the outpatient setting at different age ranges.
40:55
So the kids less than 10 years receive the highest rates of antibiotic prescriptions
41:01
per year compared to any other age range.
41:05
When we look at what antibiotics are being prescribed for, we know that in young
41:10
infants, it's mostly otitis media.
41:13
And as kids get a little bit older, for example, in the early teenage and toddler
41:18
years, there's a bit of a shift from otitis to pharyngitis as the reason for
41:24
antibiotic prescriptions.
41:26
And yet we know that most cases of otitis media are caused by viruses,
41:31
and similarly for pharyngitis, around the same percentage of cases of pharyngitis are caused by viruses.
41:39
And yet those two illnesses account for most prescribing in the outpatient setting.
41:45
Well, this is a huge problem because we know that babies get a lot of viral infections every year.
41:52
This was a study done by my colleague Mary Stack and one of our fellows,
41:56
Teo Zahe, who's now in University of Seattle.
42:00
So Mary has been collecting samples from babies and moms during their first
42:06
two years of life in a very intensive way.
42:09
So she collected nasal and stool samples every week from a large cohort of moms and babies.
42:15
And then also very intensively kept in touch with the family and the medical
42:20
records to look at illnesses.
42:22
And so from this two-year collection period, there were 13,000 nasal swabs tested
42:27
for viruses, and these are in babies that were symptomatic or asymptomatic.
42:31
And of those 13,000 samples, 2,000 had a virus, a viral pathogen detected.
42:38
And so they found that each baby in in their study, got an average of 9.4 viral infections per year.
42:45
And these were things like RSV, influenza, parainfluenza.
42:48
This cohort was before COVID, although she's continued through COVID.
42:53
And I would say the epidemiology changed a little bit, but still the rates of
42:58
viral infection are dramatically higher than I think any of us would have predicted.
43:03
So in fact, much of the time when a swab was obtained, there was a virus present,
43:09
whether or not the child was ill.
43:12
But I think this sort of gets to the point that babies are going to get,
43:15
or young infants are going to get sick, and they're going to get lots of viruses,
43:20
and most times the children are going to recover without intervention.
43:25
Yet many of those kids are going to receive antibiotics.
43:29
So I mentioned already that up to 95% of antibiotics are prescribed in the outpatient setting.
43:34
30% of those prescriptions are probably unnecessary based on guidelines,
43:39
and about half of them may be either inappropriate antibiotics or inappropriate durations.
43:46
We know from 2000 to 2010 worldwide, there were increases in antibiotic prescriptions
43:53
across all antibiotic classes.
43:55
This is globally looking at 2000 to 2010 and increases in antibiotic prescribing.
44:03
And there were increased rates of resistance for essentially all organisms that were looked at.
44:08
This is Klebsiella resistance in the U.S. to different antibiotics over time.
44:13
And from early 2000s to 2010, there were increased rates of resistance.
44:20
Around that time, American Academy and the Infectious Disease Society came out
44:25
with practice guidelines for most of the respiratory illnesses or other illnesses
44:30
that drive antibiotic prescribing in pediatrics.
44:34
Similarly, around that time, there has been a requirement for each hospital
44:40
to have an antibiotic stewardship program.
44:42
And that was most recently implemented for Children's Hospital,
44:47
where now it's required that all Children's Hospitals have a stewardship program.
44:52
And so I'm director of that program. And so there are a number of different ways to do stewardship.
44:57
We mostly have focused on guideline development and education,
45:02
although we know that that can be less effective than more restrictive practices,
45:06
Like formulary restrictions where you just can't have an antibiotic to requiring prior approval.
45:13
So we focus mostly here, and some of that's shown on this next slide.
45:19
So we rely a lot on a computerized approach.
45:24
Third-party system that monitors prescribing and cultural results.
45:29
And we've used that information to help educate our colleagues and help develop guidelines.
45:34
I would say this has been a major
45:36
activity is to collaborate with our colleagues to develop guidelines.
45:40
We do have some restrictions, although I would say I'm not a very aggressive person.
45:46
And so this is probably less effective for us than some of our guidelines.
45:51
And if we look at what's happened over time, we have seen decreases in overall
45:55
antibiotic use that were not so much reflected in antifungal and antiviral use,
46:01
although recently we have been starting to look at antifungal potential overuse as well.
46:07
If we look at individual antibiotics that we were most targeting,
46:11
we saw decreases over time in and meropenem, vancomycin, Cipro,
46:16
and aminoglycosides in particular.
46:19
And that was, I think, has been very rewarding. I'll just go back to this and
46:23
say, this is now all inpatient prescribing.
46:27
And we've had some really great advocates, including our director of the bone
46:31
marrow transplant unit, Stella Davies, our oncology and intensive care unit
46:36
colleagues have all contributed to this decline.
46:38
But until recently, we haven't really focused much on outpatient antibiotic
46:43
prescribing, but we have now, mostly through a collaborative run by my former fellow,
46:50
actually, Rana El-Faghali, who's now a professor in Kansas City,
46:55
who has put together a collaborative where we share our outpatient antibiotic
47:00
prescribing practices.
47:01
And here we're comparing Cincinnati and Orange over time to peer hospitals and looking at.
47:09
Antibiotic prescribing practices. And so we see, for example,
47:13
in the emergency room, a child that comes in with a respiratory illness gets
47:17
antibiotics about 15% of the time.
47:20
In the urgent care, it's a little bit higher. In primary care, it varies.
47:25
And we see big differences in our individual practices in prescribing rate.
47:31
So there's practice to practice variability. One thing I'm not going to show
47:35
here, but we've also been looking at equitable prescribing practices.
47:41
And we do see, like many other centers, that there are differences in antibiotic
47:45
prescribing practices based on race, for example.
47:49
We also found that primary language spoken in the home seems to be a driver
47:55
of disparate prescribing practices.
47:57
So for us, kids that speak predominantly Spanish at home receive antibiotics
48:03
at a different rate than kids that speak English.
48:07
And I think Cincinnati, we don't have a large Spanish-speaking population,
48:11
and so we're not very well equipped with interpreters.
48:14
And we think that in addition to race and ethnicity, that language is a barrier
48:20
to appropriate prescribing in most of our primary care practices.
48:27
If we look at, I'm sorry, this was all visits prescribing rates.
48:31
This is respiratory illnesses.
48:33
So you can see that if a child comes in with a cough or a runny nose,
48:38
they're going to get antibiotics about 40 to 50% of the time,
48:41
although there is variability among, again, our sites and our providers.
48:48
We can look at which fraction of kids received amoxicillin, which is the first-line
48:54
recommended antibiotic for most respiratory illnesses.
48:59
And this fraction, in this case, the higher the better. In Cincinnati, we are at the low end.
49:05
This is kids that are prescribed azithromycin as the first-line antibiotic.
49:10
And here we're on the right side of where we'd prefer to be.
49:14
So we have work to do. If we look at the percentage of prescriptions that are
49:18
greater than 10 days, which is almost always inappropriate in the outpatient
49:22
setting, we find that we're really outliers compared to most of our peers.
49:27
So we do have work to do, and this just goes to the point that we haven't really
49:32
focused on outpatient prescribing.
49:35
Well, Rana and her group have shown that you actually can improve appropriate
49:39
prescribing practices in the community. And so they did this study where they
49:44
looked at four interventions to see how that impacted appropriate prescribing.
49:49
They did tracking of antibiotic prescribing and then reporting back to providers.
49:54
They provided education and handbooks. They developed order sets.
49:58
So for example, if the diagnosis code was ontitis media, they developed order
50:03
sets that suggested the most appropriate antibiotic and duration.
50:06
And then they had providers voluntarily put up letters of commitment that say
50:12
things like, I'm dedicated to appropriate antibiotic prescribing and looked
50:19
at how that impacted prescribing practices.
50:21
And they saw over time an improvement in their first line or guideline recommended
50:27
prescribing practices.
50:29
So she would say, and her group would say, that providing education and treatment
50:35
guidelines to prescribers is helpful, information sheets for families,
50:40
comparative antibiotic use information to peers.
50:43
So I mentioned there are differences across our practices and across patient populations,
50:50
and we feel that just providing that information may, in some cases,
50:56
influence how our prescribers are using antibiotics.
51:00
And we've run into a little bit of, we're trying to implement these in a study
51:05
now that we're doing, where we're looking at suitability or adaptability of
51:10
some of these interventions. mentions.
51:12
And sometimes these commitment posters are not very popular,
51:16
although I would say many of our primary care providers are interested in having
51:21
a poster in their office that discusses this.
51:26
So I mentioned guidelines have been developed. These actually,
51:30
most of these have not been updated since 2012.
51:33
So these guidelines are still the existing guidelines.
51:36
That said, they're multi-page documents and it can take some time to wade through these.
51:42
And I think for a busy pediatrician to have to flip through a guideline each
51:46
time a child comes in is not very convenient.
51:50
But there are some more succinct resources.
51:53
And one that I really like is the American, the Red Book, the AAP Red Book that
51:57
has in the back a systems-based treatment table that, for example,
52:01
acute otitis media lists the most common organisms.
52:05
What is the appropriate first First-line therapy, what's the recommended duration
52:09
based on age, and what other things should you think about?
52:14
So this watchful waiting, for example, in kids over 24 months of age is recommended
52:20
for most kids with non-severe otitis media.
52:25
And so we're trying to develop resources, just a one-page resource with the
52:30
most common respiratory and other, like UTI illnesses, and the guideline-appropriate therapy.
52:38
And I'll just finish by saying that although we often in stewardship are people
52:43
that walk around spouting gloom and doom, there is actually good news since
52:48
guidelines were developed. it.
52:49
So this figure looks at antibiotic prescribing up until 2015 in different countries
52:56
and looked at change in antibiotic prescribing practices.
52:59
And actually in North America and some other countries in the world,
53:03
there have been decreases in antibiotic prescribing in the most recent period.
53:08
And that's been correlated actually with declines in antibiotic resistance,
53:12
at least in this case, this is strep pneumo, and here we're looking at penicillin
53:17
and suprasporin resistance.
53:18
And in our hospital and many places, rates of highly resistant strep pneumo
53:24
have fallen over the last several years.
53:26
And I would say this is really because of the guideline.
53:29
Well, the guidelines almost certainly contributed to less antibiotic use for
53:34
otitis media in the community.
53:36
And that's had a direct impact on rates of resistance. But if we look at other
53:42
organisms like MRSA abundance, that's actually falling across the United States over time.
53:48
And we've seen that in our hospital where MRSA causes fewer,
53:52
even skin and soft tissue infections than, say, 10 years ago.
53:58
VRE rates are declining across the United States.
54:01
Multidrug-resistant pseudomonas infections, including CF patients,
54:05
actually, are declining.
54:07
And if we look at clostridium difficile infection rates, which were rising steadily
54:12
up until 2010, we're seeing evidence nationwide that rates of C. diff are falling.
54:19
So it's not all gloom and doom, and I think we can say that changes in prescribing
54:24
practice, largely or at least partly driven by COVID,
54:30
Guidelines, as well as antimicrobial stewardship, and just increased awareness
54:35
by our prescribers in the hospital and in the community, seem to be having an
54:40
impact on resistance rates.
54:42
So, in summary, antibiotic resistance accounts for a large share of morbidity
54:46
and mortality, and rates were increasing until about 2010.
54:50
10, but rates of prescribing practices among children have declined corresponding
54:57
to decreased rates of antibiotic resistance.
55:00
And so our word to our providers in the community, I think having a succinct
55:06
guideline or recommendation table available for yourselves and also for families can be helpful.
55:12
Consider posting a commitment to appropriate antibiotic use and support your
55:18
local antimicrobial steward.
55:20
Some references and some thank yous.
55:24
So I apologize, I haven't left a ton of time for questions, but would be happy
55:30
to take any if you have them.
55:33
Dr. Haslam, thank you very much for that fascinating presentation.
55:36
I have a question in the chat box and then I'll go to Dr. Barton.
55:40
I'm curious, how much does it cost to do complete DNA stool evaluation?
55:46
So right now it costs about $120 per sample, which is not terrible when we think
55:53
about costs of other tests.
55:55
For example, the syndromic panels that we do for viruses in the nose or in the
55:59
stool, those cost patients more than $600.
56:03
In fact, sometimes up to $800 per sample.
56:07
We don't think about that, but so the stool for us on a research basis,
56:12
it's about $120 per sample.
56:14
I would say it's more the turnaround time, that's a barrier.
56:19
It's not cost effective to do them one at a time. So we have to do them in batch.
56:24
And so I think that's a big barrier.
56:27
Another thing, and this is a little bit off tangent, but I think there's still
56:31
questions about how useful would it be clinically.
56:35
So let's say we screen every child that came into hospital and we found that
56:39
10% of them carried a multi-drug resistant organism.
56:43
Well, then I would say, do we put all of those kits in contact precautions?
56:47
Do we, you know, what exactly, how do we use that? I think those are questions
56:52
that we need to, to answer.
56:54
But one thing I will say, it may, it may influence our antibiotic prescribing.
57:00
So if we start to see a child develop an abnormal microbiome,
57:03
then I think this antibiotic stewardship people have a strong case to say,
57:08
let's hold off on antibiotics for that child. But Yes.
57:13
Dr. Barton, go ahead and ask your question. Hi. So thank you so much for a great talk.
57:18
So my question, I have two questions that are kind of just related to each other.
57:21
One is how impactful are probiotic products at shifting the microbiome back
57:32
to something less pathogenic?
57:34
And can that happen in the setting of actively giving antibiotics?
57:40
That's a great question. I would say the short answer is they're not.
57:43
The existing commercial probiotics are not very effective. I want to say not effective at all.
57:50
That might be a little bit of an overstatement, but we had plenty of kids.
57:54
Actually, our hospital does tend to prescribe probiotics.
57:58
We mostly use lactobacillus rudii, and we saw lots of kids in our study that
58:03
They have, you know, a bubble of lactobacillus, but then they also have huge
58:07
bubbles of klebsiella or pseudomonas.
58:09
And so we didn't see any apparent benefit of those probiotics.
58:15
Now, we did see fecal transplant. I didn't include this, but we're doing fecal
58:19
transplant for C. diff, recurrent C. diff.
58:21
And there you can really shift the microbiome.
58:24
The question is, you know, would we feel comfortable giving a bone marrow transplant
58:28
patient fecal transplant? plant.
58:31
Maybe not, but there are some new products on the market for C.
58:37
Diff that are mixtures of organisms that typically come from the gut.
58:43
And they seem to be pretty effective at preventing C. diff.
58:47
So maybe they would be good at shifting the microbiome to a less aggressive state.
58:55
Dr. Herndon? Yes. Okay. My question, well, I've been through a lot of experiences
59:02
in this pandemic, as well as, you know, being a cancer doc,
59:07
where you end up being multiply recolonized and made sick by a campylobacter or something like that.
59:15
The providers come in and a sick patient, a marrow transplant, whatever.
59:19
But I'm wondering about enfolding in the data from prenatal exposures,
59:26
known neuro as well as immunotetradigens like alcohol or barbiturate drugs, things like that,
59:34
might affect the data that your overall data constellation here about colonization
59:41
and the sustainment of pathogenic colonization.
59:45
That's a great question. There is a lot of interest in looking at other drugs
59:50
and their impact on the microbiome.
59:52
I would say for sure, chemotherapeutic agents do have an impact on the microbiome.
59:58
In fact, some chemotherapeutics were initially being developed as antimicrobials.
1:00:04
And I think they were found to be too toxic for healthy individuals,
1:00:09
but had chemotherapeutic activity. So chemotherapy, yes, for sure, shifts the microbiome.
1:00:16
There certainly are other drugs that have been implicated in shifting the microbiome,
1:00:22
mostly in a non-healthy way.
1:00:25
A diet is another, so we don't think about this very often, but we see kits
1:00:30
that when they go on, well, certainly parenteral nutrition, there's a huge shift
1:00:35
in the microbiome in a more pathogenic direction.
1:00:38
Direction, but even say tube feedings is, doesn't seem to be beneficial.
1:00:44
Although I don't think, I shouldn't say that it, you definitely see differences in the microbiome.
1:00:50
I don't think we've looked to see if tube feeding alone is associated with risk
1:00:54
for infection, but yes, I completely agree with you.
1:00:57
I think there's a lot that we do to people that, that affects their microbiome
1:01:02
and potentially does increase risk of infection. Okay.
1:01:07
But I'm also worried about things like alcohol. Yes.
1:01:12
Yeah, alcohol does shift the microbiome. And then there are actually interesting
1:01:17
studies that show that microbes can produce alcohol themselves, ethanol.
1:01:23
And there are circumstances where there was a really fascinating publication
1:01:27
about a patient who had so much of an organism that metabolized carbohydrates.
1:01:33
That person would get drunk every time he ate pasta.
1:01:37
So that's kind of a little bit off of your question. But yes,
1:01:42
ethanol does affect the microbiome.
1:01:44
And in fact, with liver disease, both alcoholic and non-alcoholic liver disease,
1:01:51
there seems to be a strong contribution of the microbiome to the inflammatory
1:01:55
response in the liver, like in NASH and NAFLD.
1:01:59
And alcohol is part of that, but also microbial inflammatory factors and probably
1:02:03
alcohols produced by the microbes contribute to that as well.
1:02:08
And I think about prenatal other, or natal other exposures like breastfeeding.
1:02:15
How does breastfeeding fit into all of this?
1:02:18
Yeah, so Ardith Morrow here, listed here, is really, that's her real area of
1:02:24
interest is in breastfeeding.
1:02:25
And in fact, a lot of NICUs now do supplement commercial feeds with breast milk.
1:02:32
And there are actual, there are proteins, breast milk derived proteins that
1:02:37
are supplemented by some commercial formula makers to try and make it look more like breast milk.
1:02:43
I think the jury's still out about how well those work in correcting the microbiome,
1:02:49
but it's an active area of interest.
1:02:50
And I think, I think it definitely, there's a, there's a lot to learn there.
1:02:56
The last question, I think you partly answered this question.
1:02:59
What are your thoughts about using probiotics in the extreme premature population?
1:03:04
You know, there might be some neonatologists on the line, and so I don't want
1:03:09
to say anything that's going to get me in trouble.
1:03:11
I think our neonatologists, we see real differences in opinion there.
1:03:16
I think there's data in both directions. It seems to me a little bit hard to
1:03:21
tease out whether there are potential benefits.
1:03:26
And some people would argue, one of my colleagues in St. Louis feels pretty
1:03:30
strongly that probiotics may be harmful and may increase the risk of infection
1:03:36
due to probiotic organisms.
1:03:37
In fact, I think the FDA may be just, I don't want to say this because I don't know for for sure.
1:03:45
But I think the FDA just suggested that probiotics shouldn't be included in
1:03:50
supplementation in the newborn, but I don't take my word for that.
1:03:54
What I will say is my understanding is that there's information on both sides
1:03:59
of benefit versus non-benefit, and there may be some indication there.
1:04:04
In some babies, there could be some risk. So I think it's still a developing question.
1:04:13
We'll probably learn more. Thank you for joining us for that wonderful Grand Rounds talk.
1:04:21
Click on the link in this podcast for MOC credit. Our sister podcast is Pediatrics Now for Parents.
1:04:28
It's meant to be one less thing you have to say in the exam room.
1:04:32
That's Pediatrics Now for Parents, anywhere you get your podcasts.
1:04:36
That website is pediatricsnowforparents.com.
1:04:42
Our website is pediatricsnowpodcast.com. My email address is on there.
1:04:49
Please email me with questions or episode ideas.
1:04:53
Thank you so much for listening. I'm Holly Wayment. I'll see you next week.