Childhood asthma, allergies and risk of premenstrual disorders in young adulthood

Scientists Uncover Unexpected Link To Childhood Asthma

Antibiotics can be a double-edged sword, especially for very young kids. Recent research has found evidence that frequent antibiotic use can raise children's risk of childhood asthma and allergies.

Scientists at Rutgers University led the research, published this month in the Journal of Infectious Diseases. The study found that children given antibiotics before the age of two were noticeably more likely to be diagnosed with asthma and allergies later on, particularly the more antibiotics they took. The findings are the latest to suggest that antibiotics should be carefully managed in their use, the researchers say.

The Rise of Super Gonorrhea

Antibiotics are our best weapon against bacterial infections. But scientists have known for decades that they don't come without risks. Bacteria have steadily learned how to resist these drugs, for instance, and antibiotic resistance is now one of the most pressing public health issues of our time.

Another risk concerns the microbiome, the neighborhood of usually harmless and often helpful bacteria that live in or on our bodies. Many antibiotics are broad-spectrum, meaning they can kill a wide variety of bacteria, including these friendly bacteria. The splash damage caused by antibiotics might then disturb the microbiome in ways that could increase our risk of other health problems.

Some research has suggested that antibiotic-triggered disruptions of the microbiome are even more harmful to children, with studies linking their use to chronic conditions like asthma. But according to the Rutgers researchers, past studies had limitations—such as small sample sizes and numerous variables to account for—issues they tried to minimize in their new study.

The researchers analyzed the medical records of over one million children born in the UK. They also conducted a separate analysis of children and their siblings, allowing them to compare children with similar environmental and genetic backgrounds.

Overall, the researchers found that antibiotic use before age two was positively linked to a higher risk of asthma, food allergy, and allergic rhinitis (hay fever). They also found a possible association between antibiotic use and intellectual disability in general. On the positive side, they failed to find any connection between antibiotics and most other conditions they looked for, including autism spectrum disorder, celiac disease, type 1 diabetes, or anxiety.

This sort of research can't prove that antibiotics are triggering asthma in some young children, it can only suggest a correlation. But the researchers did see a higher risk of asthma in children who took more antibiotics than others, which is evidence of a dose-response effect. The same pattern was also seen when the researchers only compared children to their siblings, further strengthening a causative link.

Other studies have shown that antibiotics are frequently prescribed when they shouldn't be, such as for infections likely not caused by bacteria—a problem in children as well. A study in 2020, for instance, found that one of every four children given antibiotics in hospitals likely didn't need them.

So while further research might be warranted to confirm these links between antibiotics and certain chronic childhood conditions like asthma, the take-home message should remain the same: We need to rein in our use of these vital, but not risk-free, medications, perhaps even more so in kids.

"Antibiotics are important and sometimes life-saving medicines, but not all infections in young kids need to be treated with antibiotics," said lead author Daniel Horton, an associate professor of pediatrics and epidemiology at Rutgers Robert Wood Johnson Medical School and Rutgers School of Public Health, in a statement from the university. "Parents should continue to consult with their children's doctors on the best course of care."

Better Tools When Searching For Genetic Causes Of Asthma

Genome wide association studies (GWAS) have identified hundreds of genome regions containing thousands of genetic variants associated with asthma, but it's still not clear which variants have an actual causal link to the disease. This "variant-to-function" gap is one of the biggest challenges to the usefulness of these genomic studies and has motivated researchers to develop new tools to make sense of GWAS results.

A new study by researchers from the University of Chicago combines genetic data and improved computational tools to look more closely at GWAS results for both adult-onset and childhood-onset asthma. The research identified many genetic variants with a high likelihood of having a causal effect on both types of asthma, paving the way for further studies to target the genes connected to these variants as potential treatments.

The study, published in Genome Medicine, also found significant differences in the sets of genes that could be linked to adult-onset and childhood-onset asthma, with relatively little overlap between the two.

"The real uniqueness of our study is that the differences between childhood- and adult-onset asthma were evident at every level that we looked at," said Carole Ober, PhD, the Blum-Riese Distinguished Service Professor and Chair of Human Genetics at UChicago, and co-senior author of the paper. "You find out it's actually different variants that are contributing to asthma. Even when the GWAS locus looks the same, the genes functionally linked to these variants are also different. So, they're really quite different diseases."

Fine-mapping causal variants

Researchers use GWAS to compare genome sequences from a large group of people with a disease to another set of sequences from healthy individuals. The differences identified in the disease group could point to genetic variants that increase risk for that disease and warrant further study. Most human diseases -- including asthma -- are not caused by a single genetic variant, however. Instead, they are the result of complex interactions among multiple genes, environmental factors, and host of other variables. As a result, GWAS often identifies too many variants across the genome to be of use without further refinement.

GWAS also identifies association only, not causality. In a typical genomic region, many variants are highly correlated with each other, due to a phenomenon called linkage disequilibrium. This is because DNA is passed from one generation to the next in entire blocks, not as individual variants. Therefore, variants nearby each other tend to be correlated. To make the problem more difficult, most of the genetic variants associated with diseases are located in non-coding regions of the genome, making their effects difficult to interpret.

In the new study, Ethan Zhong, a graduate student working with Ober and Xin He, PhD, Associate Professor of Human Genetics and another co-senior author of the paper, wanted to bridge the variant-to-function gap and find more concrete biological insights from different sets of asthma GWAS data. He worked with data from the UK Biobank, a large-scale biomedical database and research resource containing de-identified genetic data from nearly 500,000 people in the United Kingdom. Using a statistical method called "fine-mapping," he was able to estimate the probability that a given genetic variant has a causal relationship to asthma.

The new estimates incorporated data on the accessibility of chromatin, the bundle of DNA and proteins that make up chromosomes. When a region is involved in regulating gene expression, the chromatin "opens" to become more accessible. The amount of open chromatin can be measured and used as an indicator of regulatory activity; when combined with statistical evidence, it builds an even stronger case that the variant is causally linked to asthma.

"The GWAS associations provide sets of variants associated with the disease," Zhong said. "So, when those variants overlap with open chromatin regions in cell types that are relevant to asthma pathogenesis like lung epithelial cells, we think that they are more likely to be causal to these asthma phenotypes."

Zhong also included data on expression quantitative trait loci (eQTLs), genetic variants associated with differences in gene expression, and chromatin interactions from blood and lung cell types, to link fine-mapped variants to their target genes. Using this information, he built a list of likely causal genes supported by genetic evidence.

Closing the gap

The fine-mapping analysis uncovered 21 independent sets of variants (called credible sets) for adult-onset asthma and 67 for childhood-onset, with only 16% shared between the two. Zhong also looked for cis-regulatory elements (CREs), short DNA sequences that control expression of nearby genes, that were linked to asthma and found 62 and 169 candidate genes for adult-onset and childhood-onset, respectively. More than 60% of these had open chromatin in different cell types, including many genes involved in immune and inflammatory responses.

The team selected six of the candidate CREs and tested them in bronchial epithelial cells to see if the variants had a regulatory effect; four of the six did, meaning their efforts are getting closer to the mark in the right kind of cells involved in asthma. The variant-to-function gap closes ever so slightly, opening the door to further studies of these candidate genes as potential targets for treatment.

The study was supported in part by a National Institutes of Health grant to discover genes in asthma and allergy, in collaboration with Marcelo Nobrega, MD, PhD, A.N. Pritzker Professor of Human Genetics at UChicago, Nathan Schoettler, MD, PhD, Assistant Professor of Medicine, and Anne Sperling, PhD, formerly of UChicago and now Professor of Medicine at the University of Virginia.

Additional authors include Robert Mitchell, Christine Billstrand, Emma Thompson, Noboru J. Sakabe, Ivy Aneas, Isabella M. Salamone, and Jing Gu.

Method To Identify Genetic Variations Linked To Asthma Onset Developed By University Of Chicago

UChicago study combines genetic data with computational models to pinpoint likely genetic variations which cause asthma onset in both children and adults

Genome wide association studies (GWAS) have identified a large number of genome regions containing many thousands of genetic variations that have been linked to asthma. However, it remains unclear which variants have any causal link to the condition.

The 'variant-to-function' gap continues to be a significant challenge to the practical application and usefulness of genomic studies. Consequently, researchers have worked to develop tools that can make more sense of the results produced by GWAS.

A research team from the University of Chicago (UChicago) have combined empirical genetic information with computational models to examine the GWAS data for asthma onset in both adults and children.

Many genetic variants were identified in the study that had a high likelihood of causal link with both types of asthma, with the research also finding significant differences in the sets of genes that could be associated with adult-onset vs childhood-onset of asthma, showing relatively little commonality between the two sets.

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"The real uniqueness of our study is that the differences between childhood- and adult-onset asthma were evident at every level that we looked at," said Professor Carole Ober, PhD, the Blum-Riese distinguished service professor and chair of human genetics at UChicago, who was also a co-senior author for the article.

GWAS is used in research to allow for the comparison of genomic sequences from a large group of people who have a disease with other sets of sequences from healthy individuals. Genetic differences seen in the disease group could indicate a risk increase for that disease to be examined further.

"You find out it's actually different variants that are contributing to asthma. Even when the GWAS locus looks the same, the genes functionally linked to these variants are also different. So, they're really quite different diseases," Professor Ober added.

Most human diseases – including asthma – are not directly caused by a single genetic variant. They result from complex interactions among multiple genes, moderated by environmental factors and many other variables. Consequently, GWAS studies often produce too many variants across the genome to be of immediate use and need refinement.

Importantly, GWAS is indicative of association only, and not causality. In a given genomic region, variants will be highly correlated, because of a phenomenon called 'linkage disequilibrium'.

Here DNA passes from one generation to the next in entire blocks, rather than as discrete variations. Therefore, variants nearby to each other tend to be correlated. Additionally, most of the genetic variants associated with diseases are located in non-coding regions of the genome, making their effects difficult to interpret.

In the study the team wanted to bridge the gap between variant-and-function in order to have more definitive insights into the biology that formed different data sets for asthma GWAS. A graduate researcher, Ethan Zhong, accessed UK Biobank data – a large-scale biomedical database and resource which contains anonymised genetic data from nearly half a million people in the UK – and applied a statistical methodology called 'fine mapping'.

This approach was able to give an estimate of probability that a given genetic variant had a causal relationship with asthma.

These estimates included data on the accessibility of chromatin, the DNA and protein bundle that makes up chromosomes. A region's involvement in regulation of gene expression will become more accessible and the chromatin is seen to 'open'. Measurements of open chromatin can be used to indicate whether there is involvement of that region in regulatory activity. In combination with the probabilistic statistics a stronger case can be built to link a variant causally with asthma.

"GWAS association provides sets of variants associated with disease," Zhong said.

"So, when those variants overlap with open chromatin regions in cell types that are relevant to asthma pathogenesis like lung epithelial cells, we think that they are more likely to be causal to these asthma phenotypes," he said.

By also including data on expression quantitative trait loci (eQTLs), with genetic variants associated with differences in gene expression, and chromatin interactions from blood and lung cell types, Zhong was able to link fine-mapped variants to target genes and so build a list of genes which were a probable cause in the disease.

Fine-mapping analysis found 21 independent sets of variants – called 'credible sets' – in adults and 67 in children. Only 16% was shared between both. Zhong also looked for cis-regulatory elements (CREs) – short DNA sequences that control expression of nearby genes – that link to asthma. He found 62 candidate genes for adult-onset and 169 for childhood-onset. Open chromatin in different cell types was found in excess of 60%, along with genes indicated to immune and inflammatory responses.

The team, which included Associate Professor Xin He, PhD, a professor of human genetics and another co-senior author of the paper, selected six candidate CREs to test in bronchial epithelial cells to determine whether there was a regulatory effect with these variants. Four out of the six did so, indicating the work was getting closer to developing a process which could identify those cells involved in asthma.

The study was supported in part by a US National Institutes of Health grant to discover genes in asthma and allergy, in collaboration with Dr Marcelo Nobrega, A.N. Pritzker Professor of Human Genetics at UChicago; Dr. Nathan Schoettler, Assistant Professor of Medicine; and Dr. Anne Sperling, formerly of UChicago and now Professor of Medicine at the University of Virginia. Additional authors include Robert Mitchell, Christine Billstrand, Emma Thompson, Noboru J. Sakabe, Ivy Aneas, Isabella M. Salamone and Jing Gu.

For further reading please visit: 10.1186/s13073-025-01459-z 

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