Daniel K. Burns

An autosomal genomic scan for loci linked to type II diabetes mellitus and body-mass index in Pima Indians

Genetic factors influence the development of type II diabetes mellitus, but genetic loci for the most common forms of diabetes have not been identified. A genomic scan was conducted to identify loci linked to diabetes and body-mass index (BMI) in Pima Indians, a Native American population with a high prevalence of type II diabetes. Among 264 nuclear families containing 966 siblings, 516 autosomal markers with a median distance between adjacent markers of 6.4 cM were genotyped. Variance-components methods were used to test for linkage with an age-adjusted diabetes score and with BMI. In multipoint analyses, the strongest evidence for linkage with age-adjusted diabetes (LOD = 1.7) was on chromosome 11q, in the region that was also linked most strongly with BMI (LOD = 3.6). Bivariate linkage analyses strongly rejected both the null hypothesis of no linkage with either trait and the null hypothesis of no contribution of the locus to the covariation among the two traits. Sib-pair analyses suggest additional potential diabetes-susceptibility loci on chromosomes 1q and 7q.

Characterization of E-selectin-deficient mice: demonstration of overlapping function of the endothelial selectins.

The initial rolling interaction of leukocytes with the blood vessel wall during leukocyte trafficking has been postulated to rely on members of the selectin family of adhesion molecules. Two selectins, E-selectin and P-selectin, have been identified that are expressed on activated endothelial cells. Mice deficient in E-selectin expression have been produced in order to examine the role of this selectin in leukocyte trafficking. Mice homozygous for an E-selectin null mutation were viable and exhibited no obvious developmental alterations. E-selectin-deficient mice displayed no significant change in the trafficking of neutrophils in several models of inflammation. However, blocking both endothelial selectins by treatment of the E-selectin-deficient animals with an anti-murine P-selectin antibody, 5H1, significantly inhibited neutrophil emigration in two distinct models of inflammation. While neutrophil accumulation at early times during thioglycollate-induced peritonitis was dependent on P-selectin, neutrophil accumulation at later time points was blocked by 5H1 only in E-selectin-deficient mice but not in wild-type mice. Similarly, edema as well as leukocyte accumulation in a model of delayed-type hypersensitivity in the skin was almost completely prevented by blockade of P-selectin function with 5H1 in the E-selectin-deficient mice while the same treatment had no effect in wild-type mice. These data demonstrate that the majority of neutrophil migration in both models requires an endothelial selectin but that E-selectin and P-selectin are functionally redundant. These data have important implications in the use of selectin antagonists in the treatment of inflammatory disease.

Genome-wide association and meta-analysis of bipolar disorder in individuals of European ancestry

Bipolar disorder (BP) is a disabling and often life-threatening disorder that affects ≈1% of the population worldwide. To identify genetic variants that increase the risk of BP, we genotyped on the Illumina HumanHap550 Beadchip 2,076 bipolar cases and 1,676 controls of European ancestry from the National Institute of Mental Health Human Genetics Initiative Repository, and the Prechter Repository and samples collected in London, Toronto, and Dundee. We imputed SNP genotypes and tested for SNP-BP association in each sample and then performed meta-analysis across samples. The strongest association P value for this 2-study meta-analysis was 2.4 × 10−6. We next imputed SNP genotypes and tested for SNP-BP association based on the publicly available Affymetrix 500K genotype data from the Wellcome Trust Case Control Consortium for 1,868 BP cases and a reference set of 12,831 individuals. A 3-study meta-analysis of 3,683 nonoverlapping cases and 14,507 extended controls on >2.3 M genotyped and imputed SNPs resulted in 3 chromosomal regions with association P ≈ 10−7: 1p31.1 (no known genes), 3p21 (>25 known genes), and 5q15 (MCTP1). The most strongly associated nonsynonymous SNP rs1042779 (OR = 1.19, P = 1.8 × 10−7) is in the ITIH1 gene on chromosome 3, with other strongly associated nonsynonymous SNPs in GNL3, NEK4, and ITIH3. Thus, these chromosomal regions harbor genes implicated in cell cycle, neurogenesis, neuroplasticity, and neurosignaling. In addition, we replicated the reported ANK3 association results for SNP rs10994336 in the nonoverlapping GSK sample (OR = 1.37, P = 0.042). Although these results are promising, analysis of additional samples will be required to confirm that variant(s) in these regions influence BP risk.

An autosomal genomic scan for loci linked to prediabetic phenotypes in Pima Indians.

Type 2 diabetes mellitus is a common chronic disease that is thought to have a substantial genetic basis. Identification of the genes responsible has been hampered by the complex nature of the syndrome. Abnormalities in insulin secretion and insulin action predict the development of type 2 diabetes and are, themselves, highly heritable traits. Since fewer genes may contribute to these precursors of type 2 diabetes than to the overall syndrome, such genes may be easier to identify. We, therefore, undertook an autosomal genomic scan to identify loci linked to prediabetic traits in Pima Indians, a population with a high prevalence of type 2 diabetes. 363 nondiabetic Pima Indians were genotyped at 516 polymorphic microsatellite markers on all 22 autosomes. Linkage analyses were performed using three methods (single-marker, nonparametric multipoint [MAPMAKER/SIBS], and variance components multipoint). These analyses provided evidence for linkage at several chromosomal regions, including 3q21-24 linked to fasting plasma insulin concentration and in vivo insulin action, 4p15-q12 linked to fasting plasma insulin concentration, 9q21 linked to 2-h insulin concentration during oral glucose tolerance testing, and 22q12-13 linked to fasting plasma glucose concentration. These results suggest loci that may harbor genes contributing to type 2 diabetes in Pima Indians. None of the linkages exceeded a LOD score of 3.6 (a 5% probability of occurring in a genome-wide scan). These findings must, therefore, be considered tentative until extended in this population or replicated in others.

The Population Reference Sample, POPRES: A Resource for Population, Disease, and Pharmacological Genetics Research

Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetics research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This growing resource was initially genotyped with a commercially available genome-wide 500,000 single-nucleotide polymorphism panel. This project includes nearly 6,000 subjects of African-American, East Asian, South Asian, Mexican, and European origin. Seven informative axes of variation identified via principal-component analysis (PCA) of these data confirm the overall integrity of the data and highlight important features of the genetic structure of diverse populations. The potential value of such extensively genotyped collections is illustrated by selection of genetically matched population controls in a genome-wide analysis of abacavir-associated hypersensitivity reaction. We find that matching based on country of origin, identity-by-state distance, and multidimensional PCA do similarly well to control the type I error rate. The genotype and demographic data from this reference sample are freely available through the NCBI database of Genotypes and Phenotypes (dbGaP).

Genomewide search for type 2 diabetes susceptibility genes in four American populations.

Type 2 diabetes is a serious, genetically influenced disease for which no fully effective treatments are available. Identification of biochemical or regulatory pathways involved in the disease syndrome could lead to innovative therapeutic interventions. One way to identify such pathways is the genetic analysis of families with multiple affected members where disease predisposing genes are likely to be segregating. We undertook a genomewide screen (389-395 microsatellite markers) in samples of 835 white, 591 Mexican American, 229 black, and 128 Japanese American individuals collected as part of the American Diabetes Associations GENNID study. Multipoint nonparametric linkage analyses were performed with diabetes, and diabetes or impaired glucose homeostasis (IH). Linkage to diabetes or IH was detected near markers D5S1404 (map position 77 cM, LOD = 2.80), D12S853 (map position 82 cM, LOD = 2.81) and GATA172D05 (X-chromosome map position 130 cM, LOD = 2.99) in whites, near marker D3S2432 (map position 51 cM, LOD = 3.91) in Mexican Americans, and near marker D10S1412 (map position 14 cM, LOD = 2.39) in African Americans mainly collected in phase 1 of the study. Further analyses showed evidence for interactions between the chromosome 5 locus and region on chromosome 12 containing the MODY 3 gene (map position 132 cM) and between the X-chromosome locus and region near D12S853 (map position 82 cM) in whites. Although these results were not replicated in samples collected in phase 2 of the GENNID study, the region on chromosome 12 was replicated in samples from whites described by Bektas et al. (1999).

Autosomal genomic scan for loci linked to obesity and energy metabolism in Pima Indians

An autosomal genomic scan to search for linkage to obesity and energy metabolism was completed in Pima Indians, a population prone to obesity. Obesity was assessed by percent body fat (by hydrodensitometry) and fat distribution (the ratio of waist circumference to thigh circumference). Energy metabolism was measured in a respiratory chamber as 24-h metabolic rate, sleeping metabolic rate, and 24-h respiratory quotient (24RQ), an indicator of the ratio of carbohydrate oxidation to fat oxidation. Five hundred sixteen microsatellite markers with a median spacing of 6.4 cM were analyzed, in 362 siblings who had measurements of body composition and in 220 siblings who had measurements of energy metabolism. These comprised 451 sib pairs in 127 nuclear families, for linkage analysis to obesity, and 236 sib pairs in 82 nuclear families, for linkage analysis to energy metabolism. Pointwise and multipoint methods for regression of sib-pair differences in identity by descent, as well as a sibling-based variance-components method, were used to detect linkage. LOD scores >=2 were found at 11q21-q22, for percent body fat (LOD=2.1; P=.001), at 11q23-q24, for 24-h energy expenditure (LOD=2.0; P=.001), and at 1p31-p21 (LOD=2.0) and 20q11.2 (LOD=3.0; P=.0001), for 24RQ, by pointwise and multipoint analyses. With the variance-components method, the highest LOD score (LOD=2.3 P=.0006) was found at 18q21, for percent body fat, and at 1p31-p21 (LOD=2.8; P=.0003), for 24RQ. Possible candidate genes include LEPR (leptin receptor), at 1p31, and ASIP (agouti-signaling protein), at 20q11.2.

A single-nucleotide polymorphism tagging set for human drug metabolism and transport

Interindividual variability in drug response, ranging from no therapeutic benefit to life-threatening adverse reactions, is influenced by variation in genes that control the absorption, distribution, metabolism and excretion of drugs. We genotyped 904 single-nucleotide polymorphisms (SNPs) from 55 such genes in two population samples (European and Japanese) and identified a set of tagging SNPs that represents the common variation in these genes, both known and unknown. Extensive empirical evaluations, including a direct assessment of association with candidate functional SNPs in a new, larger population sample, validated the performance of these tagging SNPs and confirmed their utility for linkage-disequilibrium mapping in pharmacogenetics. The analyses also suggest that rare variation is not amenable to tagging strategies.

Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score—the CoLaus Study

Aims/hypothesisSeveral susceptibility genes for type 2 diabetes have been discovered recently. Individually, these genes increase the disease risk only minimally. The goals of the present study were to determine, at the population level, the risk of diabetes in individuals who carry risk alleles within several susceptibility genes for the disease and the added value of this genetic information over the clinical predictors.MethodsWe constructed an additive genetic score using the most replicated single-nucleotide polymorphisms (SNPs) within 15 type 2 diabetes-susceptibility genes, weighting each SNP with its reported effect. We tested this score in the extensively phenotyped population-based cross-sectional CoLaus Study in Lausanne, Switzerland (n = 5,360), involving 356 diabetic individuals.ResultsThe clinical predictors of prevalent diabetes were age, BMI, family history of diabetes, WHR, and triacylglycerol/HDL-cholesterol ratio. After adjustment for these variables, the risk of diabetes was 2.7 (95% CI 1.8–4.0, p = 0.000006) for individuals with a genetic score within the top quintile, compared with the bottom quintile. Adding the genetic score to the clinical covariates improved the area under the receiver operating characteristic curve slightly (from 0.86 to 0.87), yet significantly (p = 0.002). BMI was similar in these two extreme quintiles.Conclusions/interpretationIn this population, a simple weighted 15 SNP-based genetic score provides additional information over clinical predictors of prevalent diabetes. At this stage, however, the clinical benefit of this genetic information is limited.

Using genetics to enable studies on the prevention of Alzheimer's disease.

Curing Alzheimers disease (AD) remains an elusive goal; indeed, it may even prove to be impossible, given the nature of the disease. Although modulating disease progression is an attractive target and will alleviate the burden of the most severe stages, this strategy will not reduce the prevalence of the disease itself. Preventing or (as described in this article) delaying the onset of cognitive impairment and AD will provide the greatest benefit to individuals and society by pushing the onset of disease into the later years of life. Because of the high variability in the age of onset of the disease, AD prevention studies that do not stratify participants by age‐dependent disease risk will be operationally challenging, being large in size and of long duration. We present a composite genetic biomarker to stratify disease risk so as to facilitate clinical studies in high‐risk populations. In addition, we discuss the rationale for the use of pioglitazone to delay the onset of AD in individuals at high risk.