Twin studies are a type of genetic research that compares the similarity of traits and behaviors between monozygotic (identical) twins, who share 100% of their genomes, and dizygotic (fraternal) twins, who share about 50% of their gene sequences, to understand the influence of genetics versus environment on various characteristics.
Twin studies are a highly effective tool in estimating heritability, the proportion of variation in a trait attributable to genetic factors within a population. The effectiveness of twin studies in predicting heritability lies in several key aspects:
We will discuss twin studies and their immense value in genetics in a more detailed article in the future.
A polygenic risk score is a numerical value that quantifies an individual’s genetic susceptibility to a particular trait or disease based on the combined effect of multiple genetic variants. We calculate this score by summing the effects of various single nucleotide polymorphisms (SNPs), each contributing to a small increase or decrease in the susceptibility of the trait or disease.
A polygenic risk score estimates an individual’s predisposition based on their unique genetic makeup, aiding in risk assessment, personalized medicine, and understanding the genetic basis of complex diseases and traits. In a future article, we will go into more detail about this valuable genetic tool.
Obesity has tripled worldwide since 1975. This rise in obesity is multifactorial, resulting from a complex mix of multiple genetic factors, epigenetic influences, and environmental conditions.
Twin studies have been instrumental in understanding obesity, revealing that genetic factors account for up to 80% of the body mass index (BMI) differences in young adulthood. Genome-wide association studies have identified numerous genetic variants associated with BMI. These variants, known as SNPs, contribute to calculating a polygenic risk score for BMI, offering a personalized gauge of genetic susceptibility to obesity.
In studying obesity, monozygotic (MZ) twins with nearly identical genetic sequences provide a unique opportunity to investigate the impact of genetic factors versus environmental factors on BMI. Comparatively, dizygotic (DZ) twins share about 50% of their segregating genomic segments. When raised together, MZ and DZ twins experience similar environmental influences, allowing for a comparative analysis of genetic and environmental contributions to BMI.Â
Several previous studies have examined MZ and DZ twins with significant differences in BMI.Â
However, these studies were cross-sectional and varied in their definitions of extensive intrapair BMI differences without fully considering genetic predisposition.
In contrast, a longitudinal study is a research design that involves repeated observations of the same variables (such as people, groups, or data) over several years to even decades.
A longitudinal study published in November 2023 aimed to explore the long-term BMI trajectories over 36 years in twins. It focused mainly on those whose BMI in young adulthood was either below, within, or above the range predicted by their genetic profile. Twin pairs exhibiting large BMI differences, a within-pair BMI difference of 3 kg/m² or more, were given special attention.
Involving a cohort (group of individuals who share a defining characteristic or experience within a defined period) of 3,227 like-sexed twin pairs, of which 34% were monozygotic, the study commenced in 1975 when the participants were approximately 30 years old. It continued with follow-ups in 1981, 1990, and 2011. The BMI observed in 1975 was categorized as within (±2.0), below (<−2.0), or above (>+2.0) the genetically predicted BMI. They based this prediction on a polygenic risk score (PRS) derived from 996,919 SNPs.
The results revealed that in both monozygotic and dizygotic twin pairs with significant intrapair BMI differences, the twin with a higher BMI in 1975 more frequently had a BMI above the genetically predicted value, compared to the twin with a lower BMI who more often fell below the range. By 2011, those below, within, and above their predicted BMI in 1975 had typically reached regular weight, overweight, and obesity status, respectively.
From these findings, the study concluded that classifying individuals’ BMI as below, within, or above their genetically predicted BMI, using a polygenic risk score, is beneficial in identifying those who are either resistant or susceptible to weight gain. This classification could offer new insights into the factors contributing to and the consequences of obesity, enhancing our understanding of this complex health issue.
These findings could potentially redirect the course of obesity research. By categorizing an individual’s BMI as below, within, or above their genetic predisposition to BMI, researchers can now investigate separately those who are either resistant or susceptible to weight gain.
This approach offers a valuable new perspective in understanding the cause and development of obesity, focusing on individual variations in response to genetic predispositions. This nuanced understanding could be crucial in developing more targeted and effective interventions for obesity prevention and treatment.
* LifeDNA is not associated with the above company.
*Understanding your genetics can offer valuable insights into your well-being, but it is not deterministic. Your traits can be influenced by the complex interplay involving nature, lifestyle, family history, and others.
Our reports have not been evaluated by the Food and Drug Administration. The contents on our website and our reports are for informational purposes only, and are not intended to diagnose any medical condition, replace the advice of a healthcare professional, or provide any medical advice, diagnosis, or treatment. Consult with a healthcare professional before making any major lifestyle changes or if you have any other concerns about your results. The testimonials featured may have used more than one LifeDNA or LifeDNA vendors’ product or reports.
