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How Your Height May Influence Your Risk of Disease

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Researchers at the University of Colorado Denver have conducted one of the largest investigations into the association between height and disease risk to date. Whether tall or short in stature, the results show that it is possible that a person’s height can influence their risk of developing a range of diseases. The findings were published in the journal PLOS Genetics.

Insights into height and disease

Some associations between a person’s height and their risk for developing several different diseases have already been established. Being taller, for example, is known to increase the risk of atrial fibrillation and decrease the risk of coronary artery disease. However, it was unclear whether these associations were directly caused by a person’s height, or if other environmental factors came into play.

Now, results of a new phenome-wide association study evaluating the height of >250,000 US veterans have shown that height is a plausible risk factor for many common adult conditions. Additionally, the study identified several novel associations between height and disease – including conditions such as peripheral neuropathy, as well as skin and bone infections.

What is a phenome-wide association study?

These studies search for associations between a range of diseases or clinical conditions (known as phenotypes) and individual genetic differences in our DNA, known as single nucleotide polymorphisms (SNPs).

In this way, researchers identified connections between phenotypes and the SNPs in a person’s DNA that control their genetically determined height.

A genome-wide association (GWAS) study does exactly the opposite. These take SNPs and search for phenotypes they may be associated with – therefore, they can identify if an individual SNP is linked to several phenotypes.

Analyzing height vs genetic height

Led by Dr. Sridharan Raghavan, assistant professor at the Colorado Clinical and Translational Sciences Institute, the new study is the largest investigation of the association between height and disease risk to date. It expands on a previous GWAS study by the University of Leicester that examined 50 clinical traits in data from European-ancestry individuals sourced from the UK Biobank.

To perform their phenome-wide association study, the Colorado researchers used genetic data obtained from the US Department of Veterans Affairs (VA) Million Veteran Program (MVP), which aims to collect data from the blood samples of 1 million US veterans. So far, high-quality genetic data has been gathered from 459,777 individuals using array technology. The genomes of these individuals were analyzed for the presence of hundreds of thousands of clinically relevant SNPs, including 3,290 associated with height taken from a previous European-ancestry meta-analysis.

From the MVP, Sridharan and colleagues selected 235,398 non-Hispanic White (EA) and 63,898 non-Hispanic Black (AA) participants that had records of both genetic and height information for their study. Unfortunately, 24,497 Hispanic participants were excluded due to the relatively small sample size.

From the genetic data, researchers calculated genetic risk scores (GRS) based on how many of the 3,290 height-determining SNPs were found in each person’s DNA. The number of SNPs was counted for each individual, with each SNP weighted based on the predicted effect they would have on height. Therefore, a GRS was created for each participant which was then used to calculate their genetically predicted height.

Using these estimates of genetically predicted height and actual height measurements from clinical records, researchers then carried out their phenome-wide association studies. Out of the 1000 clinical conditions that were assessed, 142 clinical traits were identified that were impacted by genetically predicted height in EA adults. In AA adults, only two of these traits were also significant with statistical testing. However, the researchers hypothesized that this could be due to limitations such as the smaller sample size of the AA group compared to the EA group, and the fact that the SNPs associated with height may not apply as strongly to the AA group as they were identified in a study of European-ancestry individuals. Despite this, 124 of the 142 traits identified in EA adults followed the same trend for association with genetically predicted height in AA adults, although the statistics are not yet strong enough to back these up.

These results were compared to those using actual height measurements taken from each participant. In the EA group, 345 traits were associated with actual height. One hundred and thirty three of these traits were also detected in the AA group, with a further 17 traits unique to the AA group.

Overall, this means that the study found a genetic basis supporting 37% of the clinical traits that were associated with actual measured height in AE individuals.

Which diseases are affected?

The clinical conditions associated with height found in this study confirmed many of the same associations that were previously found by the University of Leicester study, showing that taller stature was linked with an increased risk of atrial fibrillation, venous thromboembolic events, hip fracture, intervertebral disc disease, vasculitis and various cancers. On the other hand, taller people were also at decreased risk of heart disease, hypertension, diaphragmatic hernia and gastroesophageal reflux disease.

The findings also shed light on several novel associations that had not been identified previously. “We found that genetically-predicted taller stature was associated with a higher risk of several common conditions that are in turn associated with poor outcomes and quality of life – peripheral neuropathy, lower extremity ulcers and chronic venous insufficiency,” explains Raghavan in an interview with Technology Networks.

“The peripheral neuropathy result was particularly interesting to me. When we first saw that association, I asked some of my clinical colleagues who see patients with peripheral neuropathy often. All of them confirmed that this is a phenomenon they see clinically – tall people get worse neuropathy – but that they weren’t aware there were studies that described the association,” Raghavan adds.

Controlling confounding factors – A tall order

It is important to note that the associations discovered between height and disease may be confounded by other factors that can determine adult height. These include socioeconomic status, nutrition and various other demographic factors.

The fact that height is highly genetically heritable, and that researchers have made strides in understanding the genetic determiners of height hidden in someone’s DNA, means that genetic tools can be employed to calculate an individual’s genetically predicted height to reduce these confounding effects.

What is a confounding factor?

A confounding factor is a variable – other than those already being studied – that wasn’t accounted for and may skew the results of a study.

For example, increased ice cream consumption is associated with a higher risk of sunburn. The ice cream itself does not cause sunburn, but hot sunny weather – when people are more likely to eat ice cream – does. In this case, the weather is a confounding factor.

“While a person’s measured height in adulthood could be influenced by confounding factors like nutrition and socioeconomic status, their genetically predicted height should be less susceptible to such confounding,” Raghavan explains. “We’re born with the genetic markers that influence height, so using just those markers to predict a person’s height is less susceptible to confounding than using a person’s actual measured height.”

He continues, “By comparing associations of traits with measured height and with genetically predicted height, we aimed to discriminate between potentially causal associations of traits with height (those associated with genetically predicted height) from associations that may be confounded by environmental exposures over the life course (those associated with measured height but not with genetically predicted height).”

Limitations and future work

Based on the results of this study, the researchers are planning additional investigations to further clarify the observed links between height and disease risk. They plan to participate in an international collaboration performing similar analyses on data from other sources, both from the US and from other countries, focusing on the need for larger, non-European ancestry samples.

Raghavan adds, “This also addresses a limitation of the present study in that it uses a genetic risk score for height from a contemporary, multi-population genome-wide association study, a genetic predictor of height which performs better in non-European ancestry populations.”

In a news release discussing the work, the researchers also state that “future studies are needed to address the mechanisms through which height is associated with different clinical conditions,” and whether using height and other risk information may be suitable for targeting clinical interventions at the individual and population levels. For example, the authors of a study linking short stature with risk of coronary artery disease advise that those at risk could consider lifestyle changes such as increased physical activity and reduced alcohol consumption.

Overall, translating the associations between height and disease risk into clinical care may one day be a viable prospect but remains some way off right now.

Dr. Sridharan Raghavan was speaking to Sarah Whelan, Science Writer for Technology Networks.

Reference: Raghavan S, Huang J, Tcheandjieu C, et al. A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program. PLOS Genetics. 2022;18(6):e1010193. doi: 10.1371/journal.pgen.1010193