Josephine Hoh

A genomewide screen for autism susceptibility loci

We report the analysis of 335 microsatellite markers genotyped in 110 multiplex families with autism. All families include at least two affected siblings, at least one of whom has autism; the remaining affected sibs carry diagnoses of either Asperger syndrome or pervasive developmental disorder. Affected sib-pair analysis yielded multipoint maximum LOD scores (MLS) that reach the accepted threshold for suggestive linkage on chromosomes 5, X, and 19. Nominal evidence for linkage (point-wise P<.05) was obtained on chromosomes 2, 3, 4, 8, 10, 11, 12, 15, 16, 18, and 20, and secondary loci were found on chromosomes 5 and 19. Analysis of families sharing alleles at the putative X chromosomal linked locus and one or more other putative linked loci produced an MLS of 3.56 for the DXS470-D19S174 marker combination. In an effort to increase power to detect linkage, scan statistics were used to evaluate the significance of peak LOD scores based on statistical evidence at adjacent marker loci. This analysis yielded impressive evidence for linkage to autism and autism-spectrum disorders with significant genomewide P values <.05 for markers on chromosomes 5 and 8 and with suggestive linkage evidence for a marker on chromosome 19.

Mathematical multi-locus approaches to localizing complex human trait genes

Statistical analysis methods for gene mapping originated in counting recombinant and non-recombinant offspring, but have now progressed to sophisticated approaches for the mapping of complex trait genes. Here, we outline new statistical methods that capture the simultaneous effects of multiple gene loci and thereby achieve a more global view of gene action and interaction than is possible by traditional gene-by-gene analysis. We aim to show that the work of statisticians goes far beyond the running of computer programs.

The p53MH algorithm and its application in detecting p53-responsive genes

A computer algorithm, p53MH, was developed, which identifies putative p53 transcription factor DNA-binding sites on a genomewide scale with high power and versatility. With the sequences from the human and mouse genomes, putative p53 DNA-binding elements were identified in a scan of 2,583 human genes and 1,713 mouse orthologs based on the experimental data of el-Deiry et al. [el-Deiry, W. S., Kern, S. E., Pietenpol, J. A., Kinzler, K. W. & Vogelstein, B. (1992) Nat. Genet. 1, 45–49] and Funk et al. [Funk, W. D., Pak, D. T., Karas, R. H., Wright, W. E. & Shay, J. W. (1992) Mol. Cell. Biol. 12, 2866–2871] (http://linkage.rockefeller.edu/p53). The p53 DNA-binding motif consists of a 10-bp palindrome and most commonly a second related palindrome linked by a spacer region. By scanning from the 5′ to 3′ end of each gene with an additional 10-kb nucleotide sequence appended at each end (most regulatory DNA elements characterized in the literature are in these regions), p53MH computes the binding likelihood for each site under a discrete discriminant model and then outputs ordered scores, corresponding site positions, sequences, and related information. About 300 genes receiving scores greater than a theoretical cut-off value were identified as potential p53 targets. Semiquantitative reverse transcription–PCR experiments were performed in 2 cell lines on 16 genes that were previously unknown regarding their functional relationship to p53 and were found to have high scores in either proximal promoter or possible distal enhancer regions. Ten (∼63%) of these genes responded to the presence of p53.

A protein kinase A–dependent molecular switch in synapsins regulates neurite outgrowth

Cyclic AMP (cAMP) promotes neurite outgrowth in a variety of neuronal cell lines through the activation of protein kinase A (PKA). We show here, using both Xenopus laevis embryonic neuronal culture and intact X. laevis embryos, that the nerve growth–promoting action of cAMP/PKA is mediated in part by the phosphorylation of synapsins at a single amino acid residue. Expression of a mutated form of synapsin that prevents phosphorylation at this site, or introduction of phospho-specific antibodies directed against this site, decreased basal and dibutyryl cAMP–stimulated neurite outgrowth. Expression of a mutation mimicking constitutive phosphorylation at this site increased neurite outgrowth, both under basal conditions and in the presence of a PKA inhibitor. These results provide a potential molecular approach for stimulating neuron regeneration, after injury and in neurodegenerative diseases.

Selecting SNPs in two-stage analysis of disease association data : A model-free approach

For large numbers of marker loci in a genomic scan for disease loci, we propose a novel 2‐stage approach for linkage or association analysis. The two stages are (1) selection of a subset of markers that are ‘important’ for the trait studied, and (2) modelling interactions among markers and between markers and trait. Here we focus on stage 1 and develop a selection method based on a 2‐level nested bootstrap procedure. The method is applied to single nucleotide polymorphisms (SNPs) data in a cohort study of heart disease patients. Out of the 89 original SNPs the method selects 11 markers as being ‘important’. Conventional backward stepwise logistic regression on the 89 SNPs selects 7 markers, which are a subset of the 11 markers chosen by our method.

Efficiency of single-nucleotide polymorphism haplotype estimation from pooled DNA

The efficiency of single-nucleotide polymorphism haplotype analysis may be increased by DNA pooling, which can dramatically reduce the number of genotyping assays. We develop a method for obtaining maximum likelihood estimates of haplotype frequencies for different pool sizes, assess the accuracy of these estimates, and show that pooling DNA samples is efficient in estimating haplotype frequencies. Although pooling K individuals increases ambiguities, at least for small pool size K and small numbers of loci, the uncertainty of estimation increases <K times that of unpooled DNA. We also develop the asymptotic variance-covariance of maximum likelihood estimates and evaluate the accuracy of variance estimates by Monte Carlo methods. When the sample size of pools is moderately large, the asymptotic variance estimates are rather accurate. Completely or partially missing genotyping information is allowed for in our analysis. Finally, our methods are applied to single-nucleotide polymorphisms in the angiotensinogen gene.

Multi-locus interactions predict risk for post- PTCA restenosis: an approach to the genetic analysis of common complex disease

The complexity of recognizing the potential contribution of a number of possible predictors of complex disorders is increasingly challenging with the application of large-scale single nucleotide polymorphism (SNP) typing. In the search for putative genetic factors predisposing to coronary artery restenosis following balloon angioplasty, we determined genotypes for 94 SNPs representing 62 candidate genes, in a prospectively assembled cohort of 342 cases and 437 controls. Using a customized coupled-logistic regression procedure accounting for both additive and interactive effects, we identified seven SNPs in seven genes that, together, showed a statistically significant association with restenosis incidence (P <0.0001), accounting for 11.6% of overall variance observed. Among them are candidate genes for cardiovascular pathophysiology (apolipoprotein-species and NOS), inflammatory response (TNF receptor and CD14), and cell-cycle control (p53 and p53-associated protein). Our results emphasize the need to account for complex multi-gene influences and interactions when assessing the molecular pathology of multifactorial medical entities.

Set association analysis of SNP case-control and microarray data

Common heritable diseases (complex traits) are assumed to be due to multiple underlying susceptibility genes. While genetic mapping methods for mendelian disorders have been very successful, the search for genes underlying complex traits has been difficult and often disappointing. One of the reasons may be that most current gene mapping approaches are still based on conventional methodology of testing one or a few SNPs at a time. Here we demonstrate a simple strategy that allows for the joint analysis of multiple disease-associated SNPs in different genomic regions. Our set-association method combines information over SNPs by forming sums of relevant single-marker statistics. This approach successfully addresses the curse of dimensionality problem - too many variables should be estimated with a comparatively small number of observations. We also extend our method to microarray expression data, where expression levels for large numbers of genes should be compared between two tissue types. In applications to experimental expression data our approach turned out to be highly efficient.

Statistical Approaches to Gene Mapping

In this brief primer, we hope to provide a general overview on statistical methods for disease-gene mapping. Of course, this cannot be complete—our apologies to researchers whose methods are not mentioned below. More-detailed information may be found in relevant textbooks (Ott 1999) and at the Web Resources of Genetic Linkage Analysis site (Laboratory of Statistical Genetics, Rockefeller University). The main purpose of this primer is to present, in a nontechnical manner, the methodological background and rationale of genetic mapping and to relate the various approaches to each other. In addition, current analysis methods for analysis of microarray data are discussed. Microarray data represent a new type of information that can provide important insight about the interaction of genes and that thus can complement the statistical approaches to gene mapping. n nStatistical genetic-mapping methods all rest on one biological phenomenon, recombination (crossing-over), which is exploited for the purposes of determining the genetic distance—or at least the closeness—between two loci. Crossovers between homologous chromosome strands occur semirandomly. Loci in close proximity to each other will rarely be separated by a recombination, whereas, for distant loci, recombinations occur as often as not. This phenomenon is used to derive a statistical measure of genetic distance. In family pedigrees, recombinations may be seen more or less directly; on the other hand, the consequences of recombinations in past generations can be observed in the form of linkage disequilibrium—that is, the preferential occurrence, in one gamete, of specific alleles at different loci.

Association of Angiotensinogen Gene Polymorphisms with Essential Hypertension in African-Americans and Caucasians

Obective: Molecular variants of angiotensinogen (AGT) have been linked to essential hypertension, and promoter variants have been shown to alter the transcription rate of AGT in vitro. We employed a case-control study to determine whether single nucleotide polymorphisms (SNPs) in the promoter region of AGT were associated with hypertension in African-Americans and Caucasians. Methods: The frequencies of the variants at base positions –6, –20, –217, –793, and –776, both alone and in combination (haplotypes), were compared between cases and controls in samples stratified based on race and sex. A logistic regression model was applied to test whether AGT genotypes were significant predictors of the disease while adjusting for race, sex, and age. Results: Subjects with the AA or AG genotype at locus –793 were significantly more likely to have the disease (OR = 1.88, 95% CI = 1.12–3.15). Additionally, the differences in haplotype frequency distributions between cases and controls were significant at the 7% level for all four subgroups (stratified by race and sex) after adjusting for multiple testing. Based on the odds ratios for each individual haplotype, the haplotype AAAAT (nucleotide sequences at base positions –6, –20, –217, –793, –776) in African-American males, African-American females, and Caucasian females may confer susceptibility to the disease in these population subsets. Conclusion: Overall, the present report provides statistical evidence for the association of AGT with essential hypertension.