Personalizing exercise to fight obesity: Study finds genetics influence effectiveness

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In a recent study published in the journal JAMA Network Open, researchers investigated the role of genetic risk in physical activity interventions against incident obesity (body mass index [BMI] >30). Their dataset included clinical, genetic, and physical activity data from a large retrospective sample cohort comprising more than 3,000 All of Us Research Program (AoURP) participants. Their findings reveal that daily step count and BMI polygenic risk score (PRS) are both independently associated with incident obesity risk. Notably, engaging in physical activity is shown to mitigate obesity incidence and risk effectively. Importantly, however, the degree of physical activity (measured herein as participants’ mean daily step count) required to reverse incident obesity varied substantially based on the participant’s genetic PRS.

Study: Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity. Image Credit: Amani A / ShutterstockStudy: Physical Activity and Incident Obesity Across the Spectrum of Genetic Risk for Obesity. Image Credit: Amani A / Shutterstock

This study provides the first evidence that genetic obesity risk is not a deterministic trait but can instead be overcome by altering (generally increasing) physical activity levels. It highlights the need for clinicians to consider genetic history when designing intervention action plans against the condition, suggesting that future treatment against incident obesity may be tailored to the patient under care as opposed to the current “one size fits all” approach.

The dangers of obesity and the impact of genetics

Obesity is a medical condition wherein the body accumulates excess fat reserves, usually accompanied by adverse health effects. The global collective impact of obesity is so medically significant that the World Health Organization labeled obesity the ‘greatest threat to the health of the Westernized world’ more than 20 years ago (2000). In the United States of America (US) alone, the condition is reported as being responsible for more than 400,000 deaths per year, with a staggering 40% of the adult population coping with the disease. Alarmingly, despite global efforts aimed at curbing disease prevalence, the global burden of obesity continues to rise unabated annually,

Encouragingly, obesity represents an entirely modifiable and reversible condition, with diet, physical exercise, and, in extreme cases, pharmacotherapy proving effective in disease management. Physical exercise is the most often recommended intervention against obesity. The recent rise in fitness tracker popularity has seemingly bolstered the effectiveness of this intervention, with these smart devices providing clinicians and policymakers with a relatively accurate and objective means of monitoring activity levels and their impacts on disease progression.

While current medical recommendations suggest a ballpark of 8,000 daily steps as adequate for mitigating incident obesity (body mass index [BMI] >30), these estimates do not account for dietary (caloric) intake or the patient’s genetics, likely resulting in a step count underestimate based on the interplay between these factors. Genetics, in particular, is assumed to play a significant role in obesity risk and progression, with previous research estimating between 40-70% heritability. While genetic evaluations into obesity outcomes do exist, most use outdated methodology, small sample sizes, or short (<7 days) study durations, thereby confounding results and reducing overall accuracy in obesity intervention estimates.

A large cohort and long-term study investigating the association between patients’ genetic predisposition to incident obesity and the impacts of varying step counts (physical activity) accounting for this predisposition would allow for the development of novel, patient-specific intervention action plans, hypothesized to substantially improve obesity outcomes and reduce disease burden compared to current traditional interventions.

About the study

The present study aims to use a retrospective longitudinal activity monitoring methodology in tandem with genome sequencing data to evaluate and quantify the compounded genetic risk for BMI and physical activity against the risk of incident obesity. The study complies with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. It comprises participants enrolled in the All of Us Research Program (AoURP), specifically the AoURP Controlled Tier dataset (ver. 7). It includes sociodemographic, medical, and anthropometric data from participants volunteering between May 1, 2018, and July 1, 2022.

Data generation was comprised of activity monitoring (fitness tracker output; daily step count), genetic risk assessments (polygenic risk score [PRS]) obtained from a large-scale, BMI-centric genome-wide association study (GWAS), and obesity evaluations (BMI – weight in kg divided by height in m2). Of these, the former (step count) was obtained from consenting patients who linked their wearable records to the AoURP database, allowing for analyses of data even prior to study initiation.

“Consistent with our prior data curation approach, days with less than 10 hours of wear time, less than 100 steps, or greater than 45 000 steps or for which the participant was younger than 18 years were removed. For time-varying analyses, mean daily steps were calculated on a monthly basis for each participant. Months with fewer than 15 valid days of monitoring were removed. Because the existing PRS models have limited transferability across ancestry groups and to ensure appropriate power of the subsequent PRS analysis, we limited our analysis to the populations who had a sample size of greater than 500, resulting in 5964 participants of European ancestry with 5 515 802 common SNVs for analysis.”

Genomic analyses were filtered to only account for biallelic, autosomal single-nucleotide variants (SNVs), following which identified SNVs were further pruned based on their Hardy-Weinberg equilibrium P value (cutoff >1.0 × 10−15). Estimated ancestral populations were then used to assign participants into one of six ethnic groups (Admixed American, African, European, Middle Eastern, East- and South-Asian). PLINK, version 1.9 (Harvard University), was used to generate principle components deriving from generated SNVs and a European ancestry linkage disequilibrium reference panel (1000 Genomes Project phase 3).

Finally, the clinical differences between identified PRS quartiles were computed using Wilcoxon rank sums and the Kruskal-Wallis test (continuous variables) or the Pearson χ2 test (categorical variables). Associations between daily step count (physical activity), PRS (genetics), and time to event for obesity (outcomes) were computed using Cox proportional hazards regression models. These models were corrected for medical and anthropometric factors, including age, sex, cancer status, cardiovascular health, education levels, and alcohol/drug use/dependency.

Study findings and conclusions

Of the 5,964 participants of European ancestry enrolled in the AoURP study, 3,124 were found to be free of obesity at the study baseline and further provided completed activity and genome data, thereby being included in downstream data analyses. An overwhelming majority of participants were found to be White (N = 2958; 95%) and female (N = 2216; 73%). Participants’ mean age was found to be 52.7 years, with participants providing, on average, 5.4 years of follow-up data. When modeling obesity risk stratified by PRS percentile, the association between PRS and obesity was observed to be linear and direct, with PRS and daily steps independently associated with incident obesity risk and progression.

“Individuals with a PRS at the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to reduce the HR for obesity to 1.00 (Figure 1). Conversely, those in the 25th percentile PRS could reach an HR of 1.00 by walking a mean of 3660 (95% CI, 2180-8740) fewer steps than those at the 50th percentile PRS. When assuming a median daily step count of 8740 (cohort median), those in the 75th percentile PRS had an HR for obesity of 1.33 (95% CI, 1.25-1.41), whereas those at the 25th percentile PRS had an obesity HR of 0.74 (95% CI, 0.69-0.79).”

This study highlights the profound impact of PRS (genetics) on obesity risk and outcomes and establishes the importance of personalized interventions and genetic evaluations in future treatment of this disease. Unlikely previously assumed, not only is 8,000 steps daily too vague an estimate for obesity correction, but the number of required steps generally increases (but may also decrease) given the unique genetic makeup of the patient in question.

“These results have important clinical and public health implications and may offer a novel strategy for addressing the obesity epidemic by informing activity recommendations that incorporate genetic information.”

Journal reference:
Hugo Francisco de Souza

Written by

Hugo Francisco de Souza

Hugo Francisco de Souza is a scientific writer based in Bangalore, Karnataka, India. His academic passions lie in biogeography, evolutionary biology, and herpetology. He is currently pursuing his Ph.D. from the Centre for Ecological Sciences, Indian Institute of Science, where he studies the origins, dispersal, and speciation of wetland-associated snakes. Hugo has received, amongst others, the DST-INSPIRE fellowship for his doctoral research and the Gold Medal from Pondicherry University for academic excellence during his Masters. His research has been published in high-impact peer-reviewed journals, including PLOS Neglected Tropical Diseases and Systematic Biology. When not working or writing, Hugo can be found consuming copious amounts of anime and manga, composing and making music with his bass guitar, shredding trails on his MTB, playing video games (he prefers the term ‘gaming’), or tinkering with all things tech.

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