Research of genetic factors in disease have traditionally focused on finding rare, highly penetrant gene variants with a high risk of disease. For obesity, many such causes have now been identified [1] (Fig. 1). These ‘monogenic’ causes of obesity are characterised by variants within the coding sequences of the genome (i.e. exons) that often follow a Mendelian inheritance pattern in families (e.g. dominant or recessive, see also chapter “General Introduction to Obesity Genetics and Genomics”). However, in recent years the scope in the search of genes for obesity has expanded to common genetic variants (i.e. variants present in >1% of the population) through large collaborative genome-wide association studies [2] (GWAS). Individual common genetic variants such as single-nucleotide polymorphisms (SNPs) have only a minor effect on obesity risk, however their abundance in the population lead to a substantial contribution of these variants to the overall heritability of obesity [3]. Developments in polygenic risk scoring (PRS) have provided new tools to capture and quantify an individual’s genome-wide risk of disease based on a multitude of risk variants observed in GWAS. These PRS have promising applications in both public health and clinical settings to better understand who is most at risk of obesity and may benefit most from interventions. In this chapter, we discuss the role of common genetic variation in obesity, as has been explored through GWAS. We explain several methods that build forth on GWAS to understand the biological factors involved in obesity, and use information from common variants to understand its causes and consequences, such PRS and Mendelian Randomization (MR).