Elizabeth R. Hauser

Fine Mapping of Autistic Disorder to Chromosome 15q11-q13 by Use of Phenotypic Subtypes

Autistic disorder (AutD) is a complex genetic disease. Available evidence suggests that several genes contribute to the underlying genetic risk for the development of AutD. However, both etiologic heterogeneity and genetic heterogeneity confound the discovery of AutD-susceptibility genes. Chromosome 15q11-q13 has been identified as a strong candidate region on the basis of both the frequent occurrence of chromosomal abnormalities in that region and numerous suggestive linkage and association findings. Ordered-subset analysis (OSA) is a novel statistical method to identify a homogeneous subset of families that contribute to overall linkage at a given chromosomal location and thus to potentially help in the fine mapping and localization of the susceptibility gene within a chromosomal area. For the present analysis, a factor that represents insistence on sameness (IS)--derived from a principal-component factor analysis using data on 221 patients with AutD from the repetitive behaviors/stereotyped patterns domain in the Autism Diagnostic Interview-Revised--was used as a covariate in OSA. Analysis of families sharing high scores on the IS factor increased linkage evidence for the 15q11-q13 region, at the GABRB3 locus, from a LOD score of 1.45 to a LOD score of 4.71. These results narrow our region of interest on chromosome 15 to an area surrounding the gamma-aminobutyric acid-receptor subunit genes, in AutD, and support the hypothesis that the analysis of phenotypic homogeneous subtypes may be a powerful tool for the mapping of disease-susceptibility genes in complex traits.

The Finland-United States investigation of non-insulin-dependent diabetes mellitus genetics (FUSION) study. I. An autosomal genome scan for genes that predispose to type 2 diabetes

We performed a genome scan at an average resolution of 8 cM in 719 Finnish sib pairs with type 2 diabetes. Our strongest results are for chromosome 20, where we observe a weighted maximum LOD score (MLS) of 2.15 at map position 69.5 cM from pter and secondary weighted LOD-score peaks of 2.04 at 56.5 cM and 1.99 at 17.5 cM. Our next largest MLS is for chromosome 11 (MLS = 1.75 at 84.0 cM), followed by chromosomes 2 (MLS = 0.87 at 5.5 cM), 10 (MLS = 0.77 at 75.0 cM), and 6 (MLS = 0.61 at 112.5 cM), all under an additive model. When we condition on chromosome 2 at 8.5 cM, the MLS for chromosome 20 increases to 5.50 at 69.0 cM (P=.0014). An ordered-subsets analysis based on families with high or low diabetes-related quantitative traits yielded results that support the possible existence of disease-predisposing genes on chromosomes 6 and 10. Genomewide linkage-disequilibrium analysis using microsatellite marker data revealed strong evidence of association for D22S423 (P=.00007). Further analyses are being carried out to confirm and to refine the location of these putative diabetes-predisposing genes.

Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events

Background—Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. Methods and Results—We performed mass–spectrometry–based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls (“initial”), and 140 CAD cases and 140 controls (“replication”). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined (“event” group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled (“event-replication” group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis–derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). Conclusions—Metabolite profiles are associated with CAD and subsequent cardiovascular events.

Affected-sib-pair interval mapping and exclusion for complex genetic traits: Sampling considerations

We describe an extension of Rischs [(1990a,b) Am J Hum Genet 46:222–228, 229–241] method of linkage detection and exclusion for complex genetic traits. The method uses interval mapping to infer disease locus identity‐by‐descent (IBD) sharing for affected sib pairs (ASPs) based on marker information for the ASP and other genotyped family members. The method is likelihood based, and makes use of Rischs parameterization in terms of recurrence risk ratios for relatives. We describe specific linkage detection and exclusion tests for use as genome screening tools to prioritize genomic regions for further study. We also examine issues of optimal study design.

A Genomewide Scan for Early-Onset Coronary Artery Disease in 438 Families: The GENECARD Study

A family history of coronary artery disease (CAD), especially when the disease occurs at a young age, is a potent risk factor for CAD. DNA collection in families in which two or more siblings are affected at an early age allows identification of genetic factors for CAD by linkage analysis. We performed a genomewide scan in 1,168 individuals from 438 families, including 493 affected sibling pairs with documented onset of CAD before 51 years of age in men and before 56 years of age in women. We prospectively defined three phenotypic subsets of families: (1) acute coronary syndrome in two or more siblings; (2) absence of type 2 diabetes in all affected siblings; and (3) atherogenic dyslipidemia in any one sibling. Genotypes were analyzed for 395 microsatellite markers. Regions were defined as providing evidence for linkage if they provided parametric two-point LOD scores >1.5, together with nonparametric multipoint LOD scores >1.0. Regions on chromosomes 3q13 (multipoint LOD = 3.3; empirical P value <.001) and 5q31 (multipoint LOD = 1.4; empirical P value <.081) met these criteria in the entire data set, and regions on chromosomes 1q25, 3q13, 7p14, and 19p13 met these criteria in one or more of the subsets. Two regions, 3q13 and 1q25, met the criteria for genomewide significance. We have identified a region on chromosome 3q13 that is linked to early-onset CAD, as well as additional regions of interest that will require further analysis. These data provide initial areas of the human genome where further investigation may reveal susceptibility genes for early-onset CAD.

Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease

BACKGROUND Cardiovascular risk models remain incomplete. Small-molecule metabolites may reflect underlying disease and, as such, serve as novel biomarkers of cardiovascular risk. METHODS We studied 2,023 consecutive patients undergoing cardiac catheterization. Mass spectrometry profiling of 69 metabolites and lipid assessments were performed in fasting plasma. Principal component analysis reduced metabolites to a smaller number of uncorrelated factors. Independent relationships between factors and time-to-clinical events were assessed using Cox modeling. Clinical and metabolomic models were compared using log-likelihood and reclassification analyses. RESULTS At median follow-up of 3.1 years, there were 232 deaths and 294 death/myocardial infarction (MI) events. Five of 13 metabolite factors were independently associated with mortality: factor 1 (medium-chain acylcarnitines: hazard ratio [HR] 1.12 [95% CI, 1.04-1.21], P = .005), factor 2 (short-chain dicarboxylacylcarnitines: HR 1.17 [1.05-1.31], P = .005), factor 3 (long-chain dicarboxylacylcarnitines: HR 1.14 [1.05-1.25], P = .002); factor 6 (branched-chain amino acids: HR 0.86 [0.75-0.99], P = .03), and factor 12 (fatty acids: HR 1.19 [1.06-1.35], P = .004). Three factors independently predicted death/MI: factor 2 (HR 1.11 [1.01-1.23], P = .04), factor 3 (HR 1.13 [1.04-1.22], P = .005), and factor 12 (HR 1.18 [1.05-1.32], P = .004). For mortality, 27% of intermediate-risk patients were correctly reclassified (net reclassification improvement 8.8%, integrated discrimination index 0.017); for death/MI model, 11% were correctly reclassified (net reclassification improvement 3.9%, integrated discrimination index 0.012). CONCLUSIONS Metabolic profiles predict cardiovascular events independently of standard predictors.

The Finland-United States investigation of non-insulin-dependent diabetes mellitus genetics (FUSION) study. II. An autosomal genome scan for diabetes-related quantitative-trait loci

Type 2 diabetes mellitus is a complex disorder encompassing multiple metabolic defects. We report results from an autosomal genome scan for type 2 diabetes-related quantitative traits in 580 Finnish families ascertained for an affected sibling pair and analyzed by the variance components-based quantitative-trait locus (QTL) linkage approach. We analyzed diabetic and nondiabetic subjects separately, because of the possible impact of disease on the traits of interest. In diabetic individuals, our strongest results were observed on chromosomes 3 (fasting C-peptide/glucose: maximum LOD score [MLS] = 3.13 at 53.0 cM) and 13 (body-mass index: MLS = 3.28 at 5.0 cM). In nondiabetic individuals, the strongest results were observed on chromosomes 10 (acute insulin response: MLS = 3.11 at 21.0 cM), 13 (2-h insulin: MLS = 2.86 at 65.5 cM), and 17 (fasting insulin/glucose ratio: MLS = 3.20 at 9.0 cM). In several cases, there was evidence for overlapping signals between diabetic and nondiabetic individuals; therefore we performed joint analyses. In these joint analyses, we observed strong signals for chromosomes 3 (body-mass index: MLS = 3.43 at 59.5 cM), 17 (empirical insulin-resistance index: MLS = 3.61 at 0.0 cM), and 19 (empirical insulin-resistance index: MLS = 2.80 at 74.5 cM). Integrating genome-scan results from the companion article by Ghosh et al., we identify several regions that may harbor susceptibility genes for type 2 diabetes in the Finnish population.

Prospective treatment of urea cycle disorders

We present a diagnostic and therapeutic protocol designed to prevent clinical expression of inborn errors of urea synthesis in the neonatal period, and discuss the long-term developmental outcome of survivors. The families of 32 infants, among 43 identified prenatally as being at risk for a urea cycle disorder, chose to have their infants treated according to a diagnostic and therapeutic protocol, beginning at birth. The therapy was effective in avoiding neonatal hyperammonemic coma and death in seven patients with carbamoyl phosphate synthetase deficiency, argininosuccinate synthetase deficiency, and argininosuccinate lyase deficiency. When treated prospectively, five of eight patients with ornithine transcarbamylase deficiency avoided severe hyperammonemia and survived the neonatal period. Two patients with carbamoyl phosphate synthetase deficiency and two with ornithine transcarbamylase deficiency have subsequently died; three additional patients with the latter disorder have received orthotopic liver transplants. Our experience suggests that these surviving patients have had a more favorable neurologic outcome than patients rescued from neonatal hyperammonemic coma. However, all of them require a burdensome medical regimen and may have handicaps that include impairment of development and recurrent episodes of hyperammonemia. Further, those with deficiency of carbamoyl phosphate synthetase or ornithine transcarbamylase have a high mortality rate.

High heritability of metabolomic profiles in families burdened with premature cardiovascular disease

Integration of genetic and metabolic profiling holds promise for providing insight into human disease. Coronary artery disease (CAD) is strongly heritable, but the heritability of metabolomic profiles has not been evaluated in humans. We performed quantitative mass spectrometry‐based metabolic profiling in 117 individuals within eight multiplex families from the GENECARD study of premature CAD. Heritabilities were calculated using variance components. We found high heritabilities for amino acids (arginine, ornithine, alanine, proline, leucine/isoleucine, valine, glutamate/glutamine, phenylalanine and glycine; h2=0.33–0.80, P=0.005–1.9 × 10−16), free fatty acids (arachidonic, palmitic, linoleic; h2=0.48–0.59, P=0.002–0.00005) and acylcarnitines (h2=0.23–0.79, P=0.05–0.0000002). Principal components analysis was used to identify metabolite clusters. Reflecting individual metabolites, several components were heritable, including components comprised of ketones, β‐hydroxybutyrate and C2‐acylcarnitine (h2=0.61); short‐ and medium‐chain acylcarnitines (h2=0.39); amino acids (h2=0.44); long‐chain acylcarnitines (h2=0.39) and branched‐chain amino acids (h2=0.27). We report a novel finding of high heritabilities of metabolites in premature CAD, establishing a possible genetic basis for these profiles. These results have implications for understanding CAD pathophysiology and genetics.

Familiality of Quantitative Metabolic Traits in Finnish Families with Non-Insulin-Dependent Diabetes mellitus

Type 2 diabetes mellitus (NIDDM) is a complex disorder encompassing multiple metabolic defects. There exists strong evidence for a genetic component to NIDDM; however, to date there have been few reports of linkage between genetic markers along the genome and NIDDM or NIDDM-related quantitative traits. We sought to determine whether individual quantitative traits which determine glucose tolerance exhibit familiality in Finnish families with at least one NIDDM-affected sibling pair. Tolbutamide-modified frequently sampled intravenous glucose tolerance tests (FSIGT) were performed on unaffected offspring (n = 431) and spouses (n = 154) of affected sibling pairs sampled for the Finland-United States Investigation of NIDDM Genetics (FUSION) study. FSIGT data were analyzed using the Minimal Model to obtain quantitative measures of insulin sensitivity (SI), glucose effectiveness (SG), and insulin secretion assessed as the acute insulin response to glucose (AIR). The disposition index (DI), a measure of insulin resistance-corrected β-cell function, was also derived as the product of SI and AIR. Variance components analysis was used to determine for each trait, the heritability (h2), the proportion of the total trait variance accounted for by additive genes. After adjustment for age, gender, and body mass index, h2 estimates were: SG: 18 ± 9%, SI: 28 ± 8%, AIR: 35 ± 8%, and DI: 23 ± 8%. We conclude that there is strong evidence for modest heritability of Minimal-Model-derived NIDDM-related quantitative traits in unaffected spouses and offspring of Finnish affected sibling pairs.