The dynamic genetic architecture of early childhood BMI

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The genetic architecture of polygenic childhood obesity remains poorly understood. New work characterizes the dynamic genetic architecture of childhood BMI during the first eight years of life, identifying genetic loci involved in the leptin-melanocortin pathway.

The global rise in obesity among children and adolescents is staggering, with the proportion of children classified as obese growing from less than 1% of children in 1975 to more than 7% in 2015.¹ The majority of children classified as obese at age three remain obese during adolescence,² which in turn increases the risk of severe obesity in adulthood.³ Thus, prevention of obesity during early childhood may be crucial for preventing health complications of obesity later in life, including type 2 diabetes, hypertension and other cardiovascular diseases, and several cancers.^1,4 Obesity is influenced by a complex interplay of genetic and environmental factors, and genome-wide association studies (GWAS) have identified thousands of loci associated with adult body mass index (BMI).⁵ However, despite the importance of the early growth period, there is a paucity of studies on the genetic architecture of early childhood growth and obesity. Until recently, most studies on obese children have focused on monogenic Mendelian forms of obesity typically caused by rare genetic variants (causal allele frequencies < 0.01),^6,7 with few large-scale, longitudinal GWAS conducted. In this issue of Nature Metabolism, Helgeland and Vaudel et al⁸ present the largest to-date^9,10 longitudinal GWAS of childhood BMI in n = 28,681 children in the Norwegian Mother, Father and Child Cohort Study (MoBa), revealing 30 novel childhood obesity loci.

Helgeland and Vaudel et al performed GWAS to identify genetic loci associated with BMI across 12 time points in early childhood between birth and 8 years of age, a period of dynamic changes in childhood BMI. They identified 46 independent loci reaching genome-wide significance (p < 5 x 10⁻⁸) for at least one time point, of which 30 were independent of known birth weight and adult BMI loci and therefore considered new loci.^5,11 To characterize the dynamic nature of genetic loci-BMI associations during early childhood, the authors used clustering analyses to define four major clusters of loci that they categorized as the “Birth,” “Transient,” “Early Rise,” and “Late Rise” clusters (Figure 1). The loci in these clusters showed differential patterns of effect across early life; for example, some loci were only associated with birth weight, while others demonstrated no effect at birth but peak association during infancy or early childhood.

Fig. 1 |. Genetic architecture of childhood BMI exhibits dynamic changes over early childhood.

Associated with early childhood BMI across the first 8 years of life were 46 distinct loci, representing four clusters: Birth, Transient, Early Rise and Late Rise. The Birth cluster contained 9 loci previously identified for birth weight, with half of these demonstrating effects in the postnatal period and early childhood. The Transient cluster contained 21 independent SNPs at 16 loci with no effect at birth, peak association during infancy or early childhood, and little or no effect after the adiposity rebound. The Early Rise cluster contained 12 loci that gradually show stronger association with BMI from infancy into childhood but only rarely maintain effects into adulthood. The Late Rise cluster contained 4 loci with little to no effect before the adiposity rebound. Bold indicates previously identified monogenic obesity genes involved in the leptin–melanocortin signalling pathway. All but one were restricted to the Transient and Early Rise clusters. The leptin–melanocortin pathway regulates energy intake and expenditure, suggesting that age-dependent genetic variation affecting the leptin–melanocortin system, in addition to numerous environmental factors, plays a central role in controlling BMI during early childhood. ^aLoci that demonstrate effects in the postnatal period and early childhood. ^bLoci that maintain effects into adulthood. AgRP, agouti-related protein; Alpha-MSH, alpha melanocyte stimulating hormone; CART, cocaine and amphetamine-regulated transcript; NPY, neuropeptide Y; POMC, propiomelanocortin; PYY, peptide YY.

Several of the identified loci, including LEPR, PCSK1, ADCY3, MC4R, and GLP1R play important roles in the leptin-melanocortin hypothalamic signaling pathway, and were previously identified for their role in Mendelian obesity.^12,13 Thus, these results support the idea that monogenic and polygenic obesity may share underlying etiologies, including a critical shared central role of the brain in the regulation of obesity. Although several of the identified genes, including GLP1R, LEPR, and PCSK1 are already pharmaceutical targets for treating adult obesity and monogenic forms of the disease,^12,13 more research will be needed to determine whether these loci could be targeted for prevention or treatment of obesity during early childhood.

To interrogate the role that parental genotypes may play on early childhood growth, Helgeland and Vaudel et al also conducted genetic analyses to determine maternal/paternal effects for the identified loci. For most of the identified loci, there was no parental effect on the variant-BMI association. However, five variants demonstrated differential maternal effects, including maternal imprinting, or the silencing of the paternally-inherited gene, for two KLF14 variants, which has previously been identified at this locus for type 2 diabetes. Collectively, these results illustrate the ways in which parental genomes can have heterogenous effects on fetal and early childhood growth.

Polygenic risk scores (PRS), which assess an individual’s genetic susceptibility to disease by summarizing the combined effects of many genetic variants, are a promising potential tool for early identification of disease risk, such as increased risk for childhood obesity. Helgeland and Vaudel et al generated PRS for birth weight and adult BMI and then stratified the MoBa cohort by PRS deciles to assess their relationship with BMI over time. These PRS demonstrated strong age-dependent effects, with the difference in standardized BMI between the top and bottom birth weight-PRS deciles greatest at birth, and the difference in standardized BMI between top and bottom adult BMI-PRS deciles greatest between 3 and 8 years. With the adult BMI-PRS identifying children at higher risk of obesity as early as 5 years old, these findings have important implications for precision medicine and may be used to target prevention and treatment options.

The work presented by Helgeland and Vaudel et al, which is the largest to-date longitudinal genetic analysis of childhood BMI, provides evidence for the key role of the central leptin-melanocortin system in regulating polygenic obesity during early childhood, and highlights how genetic loci involved in this pathway may only exert influence during particular early life stages. Indeed, this study suggests that there may be critical periods during the lifecourse for potential intervention and treatment of obesity, a contention that has been largely advocated for in non-genetic epidemiological studies.¹⁴ Despite the strengths of this study, there are limitations that must be addressed in future research. Increased sample sizes will be necessary for additional discovery and formal replication of age-specific loci. Furthermore, future analyses must include large studies of ancestrally diverse populations. Continued research into the genetic underpinnings of childhood BMI in large-scale diverse populations will enable better understanding of the mechanisms and pathways, including the leptin-melanocortin pathway, through which early childhood growth is regulated. Such knowledge can fuel development of intervention and treatment strategies for obesity early in the life-course, before negative consequences of obesity can develop.