HOUSTON – (June 17, 2013) – The architecture of the genome - its variation, its genes and the elements that control them - can define traits that affect our bodies and our health - even the levels of so-called "good cholesterol" (high density lipoprotein cholesterol or HDL-C), said a consortium of researchers including those at The University of Texas Health Science Center at Houston (UTHealth) and Baylor College of Medicine in a report on massive whole genome sequencing and analysis that appears in a report online in the journal Nature Genetics.
In this study, researchers looked at the genome sequences of 962 people who were part of the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium to determine the genomic determinants of a trait with many components - levels of high density lipoprotein C (HDL-C), the so-called good cholesterol. High levels of HDL-C are believed to protect against heart disease while low levels leave people at risk.
“This is the first time that DNA sequence differences from a large sample of individuals have been analyzed in this way. The results of this research show that parts of the genome with no known function are influencing differences at risk to disease,” said Eric Boerwinkle, Ph.D., associate director of the Baylor College of Medicine Human Genome Sequencing Center and director of the Human Genetics Center at The University of Texas School of Public Health and the Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases (IMM), which are part of UTHealth. All of the sequencing in the project took place at the BCM Genome Sequencing Center.
“This study is a precursor to the application of whole genome studies of healthy people as a part of medical practice,” said Richard Gibbs, Ph.D., director of the Baylor College of Medicine Human Genome Sequencing Center and a senior author of the report. “Currently, the Whole Genome Laboratory at Baylor is helping to identify the problem in people with known genetic disease. Eventually, we will be at a point where we can sequence everyone, inform those who have known genome problems and maintain the rest for future reference - both for them and for future studies.”
“In this study, we have large-scale genome production integrated with phenotypic data (information about disease, symptoms, etc.) that presages the use of large scale genomes in clinical practice,” said Gibbs.
“Some people have thought that analyzing whole genomes is an intractable problem, and this work shows that whole genome sequence variation can be analyzed and related to risk of disease,” said Boerwinkle. “This work represents a first in a series of high profile papers/discoveries originating out of the collaboration among genome researchers at UTHealth and BCM.”
Other centers that took part included the University of Washington, Seattle; the National Heart, Lung and Blood Institute Framingham Heart Study in Massachusetts; the NHLBI; Kansas State University in Manhattan; the University of North Carolina in Chapel Hill; the Group Health Research Institute in Seattle and Boston University School of Public Health.
The consortium found 25 million genetic variants, which they analyzed across regions and with regard to function. They found that common variants explain 61.8 percent of the variance in HDL-C levels and rare variants explain 7.8 percent. Common variants are variations in a gene that are shared by a significant part of the population. Rare variants occur in only a handful of people. Much of the analytical work in the study was done by first authors Alanna C. Morrison, Ph.D., and Xiaoming Liu, Ph.D., of UTHealth, Arend Voorman of the University of Washington at Seattle and Andrew D. Johnson, Ph.D., of the National Heart, Lung and Blood Institute.
“The exciting aspect of this research that has not been done before is that we were able to comprehensively access the parts of the genome that lie outside gene regions and determine if genetic variation in those regions influence risk to disease,” said Morrison.
When they looked for genes known to affect levels of high density lipoprotein cholesterol (HDL-C), they found individuals who had abnormally low levels of the lipoprotein, which is believed to be protective against heart disease.
Looking at the genomic landscape through the prism of whole genome sequencing, the researchers found that genetic variation contributed more to HDL-C levels than had been understood from previous studies known as genome-wide association studies. For example, examining a gene known as CETP showed that variations in regulatory elements were likely to contribute to its role establishing levels of HDL-C.
The authors wrote: “By using whole-genome sequencing instead of genome-wide association (GWAS) or candidate gene studies, we are able to obtain an unbiased glimpse of the relative contributions of rare and common variation to the heritability of a model trait. The results indicate that the majority (that is, 61.8%) of the heritability of HDL-C levels can be attributable to common variation. Given the results of GWAS and targeted resequencing, these common variants likely represent true polygenic variations with small effects, which are of limited diagnostic use but may be important in identifying the biological pathways involved.”
Boerwinkle pointed out that the work reflects the great strength of Texas Medical Center collaborators.
“This work is the result of a close partnership between established groups at The University of Texas Health Science Center at Houston and Baylor College of Medicine, and further establishes Houston's preeminent role in the exploding fields of medical sequencing,” he said.
“UTHealth had a wonderful collection of valuable samples which we could sequence,” said Gibbs. “This collaboration shows the sequencing and analytical power of the Genome Center and the value of the new analytical approaches that UT and Boerwinkle could bring to the research.”
Others who took part in this work included Jin Yu, Donna Muzny and Fuli Yu, Ph.D., all of BCM; Alexander Li of UTHealth; Kenneth Rice, Ph.D., and Joshua Bis of University of Washington; Chengsong Zhu of Kansas State: Gerardo Heiss, M.D., Ph.D, and Bruce M Psaty, M.D., Ph.D., of the University of North Carolina; Christopher J O’Donnell, M.D., M.P.H., and L. Adrienne Cupples, Ph.D., of NHLBI.
Funding for this work came from Atherosclerosis Risk in Communities (ARIC) Study with NHLBI contracts HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C and HHSN268201100012C and the NHLBI-sponsored project RC2HL102419-02. Other funding came from the Cardiovascular Health Study (CHS) supported by NHLBI contracts N01-HC-85239, N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133 and HHSN268201200036C and by NHLBI grants HL080295, HL087652 and HL105756, with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG-023629, AG-15928, AG-20098 and AG-027058 from the National Institute on Aging (NIA). Still more support came from the Framingham Heart Study (FHS) of the NHLBI of the U.S. National Institutes of Health and Boston University School of Medicine: (contract N01-HC-25195).
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Baylor College of Medicine and UTHealth contributed to this news release. For interviews, please contact Rob Cahill of UTHealth Media Relations, 713-500-3030 or Robert.Cahill@uth.tmc.edu