NEW YORK (GenomeWeb News) – Three new papers appearing in the advance online edition of Nature Genetics yesterday are illustrating the power of population-based studies for identifying genetic variants linked to lipid levels and metabolism.
In the first of these, an international team of researchers focused on the Northern Finland Birth Cohort 1966, a longitudinal birth cohort involving almost all individuals born in two Finnish provinces in 1966 in an effort to identify genetic variants associated with nine metabolic traits. The team identified roughly two dozen loci linked to metabolic traits related to cardiovascular disease, type 2 diabetes, blood pressure, inflammation, and lipid levels. Six of these variants were new.
Rather than using a case-control study comparing patients with a seemingly healthy control population, the team focused on an unselected group of people born in the same area in the same year. That approach allowed them to compare individuals who had similar environmental exposures and genetic backgrounds.
“Our population sample allows us to look at gene-environment interactions,” co-lead author Chiara Sabatti, a human geneticist at the University of California at Los Angeles, said in a statement, “but we need to examine larger populations in order to validate these.”
The team assessed nine heritable, quantitative traits known to influence the risk of cardiovascular disease or type 2 diabetes by genotyping 4,763 individuals at 329,091 SNPs using an Illumina Infinium array. Along with genetic information, the team also looked at six co-variants: alcohol use, body mass index, sex, oral contraceptive use, and pregnancy status.
They identified 23 genetic associations using a combination of association and imputation analyses. Nine of these associations had not been described previously. Five fell within genetic regions previously implicated in metabolism.
In the process, the researchers verified many — but not all — associations described in prior GWA studies. They speculated that these associations may provide different types of information than that gleaned from traditional case-control GWA studies.
“[S]tronger association in cohort studies may characterize loci with broader phenotypic effects,” Sabatti and colleagues wrote, “whereas stronger associations in case-control studies may characterize loci that more directly influence the diseases that define cases.”
The researchers noted that the loci they uncovered so far explain just six percent or so of the metabolic trait variability found in the Northern Finland Birth Cohort 1966. And their results suggest that environmental factors explain roughly a third, leaving a great deal of genetic variance unexplained.
“Clearly we have to increase our efforts to understand the genetic factors involved,” co-author Leena Peltonen, head of human genetics at the Wellcome Trust Sanger Institute, said in a statement.
The researchers speculated that this variance may be caused by common genetic variants interacting with environmental variables or an accumulation of rare variants. They argued that GWA studies are ill-equipped to evaluate such rare variants. Instead, the team touted re-sequencing projects such as the 1000 Genomes Project for their potential to aid rare variant discovery and association analysis.
“We are only starting to have a glimpse of how the power of modern genetics can work with population data to uncover genes that will be able to help clinical and public health work in the future,” Sabatti said. “We still have many challenges ahead.”
In a second study, Peltonen led a team of researchers who evaluated data from more than a dozen European projects. The effort, part of the European Network on Genomic and Genetic Epidemiology project, revealed 16 known loci as well as six new genetic variants influencing the levels of various lipids in the blood.
“This impressive result shows that not only can we find the known genetic associations, but we can also find novel associations in this large-scale collaboration of very diverse population-based cohort studies spanning populations from Lapland to the Dalmatian Islands” co-author Cornelia van Duijn, a genetic epidemiology and biostatistics researcher at the Erasmus University in Rotterdam, said in a statement.
For that paper, the researchers did genome-wide association studies looking for loci influencing total cholesterol, low- and high-density lipoprotein, cholesterol, and triglyceride levels. The team assessed data from 16 European studies involving between 17,797 and 22,562 individuals who were 18 to 104 years old. Most had been genotyped using the Illumina HumanHap300-Duo platform.
They discovered 22 genetic variants, including six loci that had not been identified previously. Using genome-wide association network analysis, the researchers pinpointed pathways most likely affected by these loci. For example, the researchers reported that total cholesterol was associated with genes involved in pathways for cholesterol and sterol metabolism, lipid transporters, and nutrient response.
The researchers also found three SNPs that appear to have different effects in men and women: the rs3846662 SNP in HMGCR, the rs2304130 SNP in NCAN, and the rs2083637 SNP in LPL.
“None of the published GWA studies have addressed the potential sex-based difference in genetic risk profiles for lipids,” Peltonen and her team noted. “Here we found significantly different sex-specific effects for some genes, as expected from epidemiological and clinical data.”
Based on the data compiled in the study, the researchers prospectively came up with genetic risk scores for evaluating blood lipid levels in three large cohorts — the Northern Finnish Birth Cohort, the Rotterdam Study, and the monozygotic twins study. The team was able to glean associations between loci identified in the study and clinical outcomes, including atherosclerosis and coronary heart disease, when they looked at the Rotterdam Study, the cohort containing the oldest participants.
“We can be confident that the increased understanding of the control of lipid levels that will come from these genetic discoveries will, in time, lead to improved ways of treating and preventing heart disease and stroke,” co-author Mark McCarthy, a diabetes researcher at the University of Oxford, said in a statement.
Finally, an international team of researchers hunted for genes influencing lipoprotein concentrations by compiling data from seven GWA studies involving nearly 20,000 individuals. After validating their results in an even larger group of individuals, the team highlighted 30 loci — 11 of them new — that seem to influence lipid levels.
“Finding new gene regions involved in lipid levels could improve our understanding of cholesterol regulation, help identify individuals who are at greater risk for heart disease, and point out new targets for drugs to control cholesterol levels,” lead author Sekar Kathiresan, director of preventive cardiology at the Massachusetts General Hospital, said in a statement.
The researchers compiled data on 19,840 individuals from seven GWA studies, including the Framingham Heart Study, to look for new genetic variants associated with blood low-density lipoprotein levels, high-density lipoprotein levels, and triglyceride levels. They replicated their results using data from five other studies representing as many as 20,623 additional individuals.
Overall, they found 30 loci that were associated with lipoprotein concentration. Among them, 11 new loci influence low density lipoprotein levels. Because rare mutations in some of these genes have been previously implicated in cholesterol disorders and/or type 2 diabetes, the researchers noted that it will be important to tease apart the impact of both rare and common mutations on gene function — as well as the long-term consequences of such mutations.
“With rare mutations, gene function is usually completely abolished, but these common variants appear to affect the quantity but not necessarily the quality of protein being produced,” Kathiresan said. “We are currently designing studies to test whether individuals inheriting several of these lipid risk genes really are at higher risk for heart attack and whether they are more likely to benefit from cholesterol-lowering treatments like statins.”