NEW YORK (GenomeWeb) – Researchers from the Genetic Investigation of Anthropometric Traits (GIANT) consortium have linked some 140 spots in the human genome to body-mass index or waist and hip measurements.
In a pair of papers appearing today in Nature, the international consortium described their meta-analyses that drew on hundreds of thousands of people to uncover genetic loci associated with BMI or with waist and hip measurements, both of which are indicators of obesity and risk of related diseases like type 2 diabetes.
In both studies, the researchers homed in on loci involved in the adipogenesis pathway. The BMI study also found a role for the central nervous system and other pathways, while the waist and hip circumference study noted differences in the effect of certain loci based on gender.
"Our work clearly shows that predisposition to obesity and increased BMI is not due to a single gene or genetic change," said Elizabeth Speliotes, an assistant professor at the University of Michigan Health System and co-senior author of the BMI paper, in a statement. "The large number of genes makes it less likely that one solution to beat obesity will work for everyone and opens the door to possible ways we could use genetic clues to help defeat obesity."
Previous GIANT analyses of a smaller set of studies and individuals had linked 14 loci to waist-to-hip ratio and 32 loci to BMI.
Speliotes and her colleagues performed a meta-analysis of 125 studies — 82 genome-wide association studies and 43 Metabochip-based studies — that combined results from some 339,000 people. From this, they identified 97 loci of genome-wide significance linked to BMI, 41 of which had previously been linked with obesity and 56 of which were novel.
The researchers found that 27 of the 31 tissues enriched for expression of these BMI-linked variants were in the central nervous system. The sites, the researchers noted, were not only in the hypothalamus and pituitary gland — regions that regulate appetite — but also in the hippocampus and limbic system, which are involved in learning, cognition, emotion, and memory.
Further, they found that a number of CNS-related pathways were enriched for these BMI-associated SNPs.
In particular, they homed in on genes like ELAVL4, GRID1, and CADM2 that are involved in synaptic function, cell-cell adhesion, and glutamate signaling, as well as others like NPC1, PTBP2, and MAP2K5 that are involved in insulin secretion and action, energy metabolism, adipogenesis, and more.
Meanwhile, GIANT researchers led by co-senior author Ruth Loos at Mount Sinai Hospital also reported on a meta-analysis of some 225,000 people from GWAS and Metabochip-based studies to identify SNPs linked to waist and hip measurements and body fat distribution. After adjusting for BMI, they found 49 loci linked to waist and hip ratio, 33 of which were new.
More than a dozen of the 49 loci were linked to high-density lipoprotein cholesterol, triglycerides, low-density lipoprotein cholesterol, adiponectin levels, fasting insulin levels, and/or height.
Of these 49 loci, the researchers also noted that 19 of them had a stronger effect in women, a finding they said underscored the strong sexual dimorphism in the genetic regulation of fat distribution.
By annotating these loci, Loos and her colleagues traced them to genes with roles in body fat regulation, skeletal growth, and transcriptional regulation and development. Another gene set at the loci highlighted genes specific to metabolically active tissues including adipose, heart, liver, and muscle, which the researchers said highlighted the role of mesenchemally derived tissue in fat distribution. These tissues, they further noted, have been implicated in insulin resistance.
"Finding the genes that increase risk of obesity is only the end of the beginning," Loos added.
"A major challenge now is learning about the function of these genetic variations and how they indeed increase people's susceptibility to gain weight," she said. "This will be the critical next step, which will require input from scientists with a range of expertise, before our new findings can be used towards targeted obesity prevention or treatment strategies."