Search PubMed⌕ Search

Biomedical subjects

Chiara Sabatti

Publications and source records attributed to Chiara Sabatti.

At least 19 recordsLinked to original sources
PubMed2026

Uncovering heterogeneous effects via localized feature selection.

Identifying features that interact to trigger disease, while accounting for heterogeneity across diverse populations, is essential for the development of precision and targeted medicine. Despite the availability of vast and complex health-related datasets, most existing works focus on identifying disease-associated features at the population level or within a few subpopulations, often overlooking individual-level heterogeneity within these groups. To address this limitation, we propose a framework that utilizes localized test statistics to identify disease-associated features tailored to individual profiles. Our method leverages the recently developed knockoffs methodology to control the noise level of the selection set so that the results are replicable. Moreover, it allows for the discovery of hidden heterogeneous effects within the data, as demonstrated in an application to single-cell RNA sequencing data for Alzheimer's disease. By aggregating localized feature selection results, our framework also enables powerful population-level feature selection. Our framework provides a powerful tool for exploratory studies of precision medicine, offering the potential to generate novel hypotheses for confirmatory biological experiments.

Alzheimer Disease↗
PubMed2006

Volume measures for linkage disequilibrium.

BACKGROUND: Defining measures of linkage disequilibrium (LD) that have good small sample properties and are applicable to multiallelic markers poses some challenges. The potential of volume measures in this context has been noted before, but their use has been hampered by computational challenges. RESULTS: We design a sequential importance sampling algorithm to evaluate volume measures on I x J tables. The algorithm is implemented in a C routine as a complement to exhaustive enumeration. We make the C code available as open source. We achieve fast and accurate evaluation of volume measures in two dimensional tables. CONCLUSION: Applying our code to simulated and real datasets reinforces the belief that volume measures are a very useful tool for LD evaluation: they are not inflated in small samples, their definition encompasses multiallelic markers, and they can be computed with appreciable speed.

Algorithms↗
PubMed2006

Linkage disequilibrium and haplotype homozygosity in population samples genotyped at a high marker density.

OBJECTIVE: Analyze the information contained in homozygous haplotypes detected with high density genotyping. METHODS: We analyze the genotypes of approximately 2,500 markers on chr 22 in 12 population samples, each including 200 individuals. We develop a measure of disequilibrium based on haplotype homozygosity and an algorithm to identify genomic segments characterized by non-random homozygosity (NRH), taking into account allele frequencies, missing data, genotyping error, and linkage disequilibrium. RESULTS: We show how our measure of linkage disequilibrium based on homozygosity leads to results comparable to those of R(2), as well as the importance of correcting for small sample variation when evaluating D'. We observe that the regions that harbor NRH segments tend to be consistent across populations, are gene rich, and are characterized by lower recombination. CONCLUSIONS: It is crucial to take into account LD patterns when interpreting long stretches of homozygous markers.

Chromosomes, Human, Pair 22↗
PubMed2006

Overrepresentation of rare variants in a specific ethnic group may confuse interpretation of association analyses.

Rare sequence variants may be important in understanding the biology of common diseases, but clearly establishing their association with disease is often difficult. Association studies of such variants are becoming increasingly common as large-scale sequence analysis of candidate genes has become feasible. A recent report suggested SLITRK1 (Slit and Trk-like 1) as a candidate gene for Tourette Syndrome (TS). The statistical evidence for this suggestion came from association analyses of a rare 3'-UTR variant, var321, which was observed in two patients but not observed in more than 2000 controls. We genotyped 307 Costa Rican and 515 Ashkenazi individuals (TS probands and their parents) and observed var321 in five independent Ashkenazi parents, two of whom did not transmit this variant to their affected child. Furthermore, we identified var321 in one subject from an Ashkenazi control sample. Our findings do not support the previously reported association and suggest that var321 is overrepresented among Ashkenazi Jews compared with other populations of European origin. The results further suggest that overrepresentation of rare variants in a specific ethnic group may complicate the interpretation of association analyses of such variants, highlighting the particular importance of precisely matching case and control populations for association analyses of rare variants.

Case-Control Studies↗
PubMed2006

Convergent linkage evidence from two Latin-American population isolates supports the presence of a susceptibility locus for bipolar disorder in 5q31-34.

We performed a whole genome microsatellite marker scan in six multiplex families with bipolar (BP) mood disorder ascertained in Antioquia, a historically isolated population from North West Colombia. These families were characterized clinically using the approach employed in independent ongoing studies of BP in the closely related population of the Central Valley of Costa Rica. The most consistent linkage results from parametric and non-parametric analyses of the Colombian scan involved markers on 5q31-33, a region implicated by the previous studies of BP in Costa Rica. Because of these concordant results, a follow-up study with additional markers was undertaken in an expanded set of Colombian and Costa Rican families; this provided a genome-wide significant evidence of linkage of BPI to a candidate region of approximately 10 cM in 5q31-33 (maximum non-parametric linkage score=4.395, P<0.00004). Interestingly, this region has been implicated in several previous genetic studies of schizophrenia and psychosis, including disease association with variants of the enthoprotin and gamma-aminobutyric acid receptor genes.

Bipolar Disorder↗
PubMed2006

Results of a SNP genome screen in a large Costa Rican pedigree segregating for severe bipolar disorder.

We have ascertained in the Central Valley of Costa Rica a new kindred (CR201) segregating for severe bipolar disorder (BP-I). The family was identified by tracing genealogical connections among eight persons initially independently ascertained for a genome wide association study of BP-I. For the genome screen in CR201, we trimmed the family down to 168 persons (82 of whom are genotyped), containing 25 individuals with a best-estimate diagnosis of BP-I. A total of 4,690 SNP markers were genotyped. Analysis of the data was hampered by the size and complexity of the pedigree, which prohibited using exact multipoint methods on the entire kindred. Two-point parametric linkage analysis, using a conservative model of transmission, produced a maximum LOD score of 2.78 on chromosome 6, and a total of 39 loci with LOD scores >1.0. Multipoint parametric and non-parametric linkage analysis was performed separately on four sections of CR201, and interesting (nominal P-value from either analysis <0.01), although not statistically significant, regions were highlighted on chromosomes 1, 2, 3, 12, 16, 19, and 22, in at least one section of the pedigree, or when considering all sections together. The difficulties of analyzing genome wide SNP data for complex disorders in large, potentially informative, kindreds are discussed.

Bipolar Disorder↗
PubMed2006

Magnitude and distribution of linkage disequilibrium in population isolates and implications for genome-wide association studies.

The genome-wide distribution of linkage disequilibrium (LD) determines the strategy for selecting markers for association studies, but it varies between populations. We assayed LD in large samples (200 individuals) from each of 11 well-described population isolates and an outbred European-derived sample, using SNP markers spaced across chromosome 22. Most isolates show substantially higher levels of LD than the outbred sample and many fewer regions of very low LD (termed 'holes'). Young isolates known to have had relatively few founders show particularly extensive LD with very few holes; these populations offer substantial advantages for genome-wide association mapping.

Chromosomes, Human, Pair 22↗
PubMed2006

Reconstructing ancestral haplotypes with a dictionary model.

We propose a dictionary model for haplotypes. According to the model, a haplotype is constructed by randomly concatenating haplotype segments from a given dictionary of segments. A haplotype block is defined as a set of haplotype segments that begin and end with the same pair of markers. In this framework, haplotype blocks can overlap, and the model provides a setting for testing the accuracy of simpler models invoking only nonoverlapping blocks. Each haplotype segment in a dictionary has an assigned probability and alternate spellings that account for genotyping errors and mutation. The model also allows for missing data, unphased genotypes, and prior distribution of parameters. Likelihood evaluations rely on forward and backward recurrences similar to the ones encountered in hidden Markov models. Parameter estimation is carried out with an EM algorithm. The search for the optimal dictionary is particularly difficult because of the variable dimension of the model space. We define a minimum description length criteria to evaluate each dictionary and use a combination of greedy search and careful initialization to select a best dictionary for a given dataset. Application of the model to simulated data gives encouraging results. In a real dataset, we are able to reconstruct a parsimonious dictionary that captures patterns of linkage disequilibrium well.

Algorithms↗
PubMed2005

Bayesian sparse hidden components analysis for transcription regulation networks.

MOTIVATION: In systems like Escherichia Coli, the abundance of sequence information, gene expression array studies and small scale experiments allows one to reconstruct the regulatory network and to quantify the effects of transcription factors on gene expression. However, this goal can only be achieved if all information sources are used in concert. RESULTS: Our method integrates literature information, DNA sequences and expression arrays. A set of relevant transcription factors is defined on the basis of literature. Sequence data are used to identify potential target genes and the results are used to define a prior distribution on the topology of the regulatory network. A Bayesian hidden component model for the expression array data allows us to identify which of the potential binding sites are actually used by the regulatory proteins in the studied cell conditions, the strength of their control, and their activation profile in a series of experiments. We apply our methodology to 35 expression studies in E.Coli with convincing results. AVAILABILITY: www.genetics.ucla.edu/labs/sabatti/software.html SUPPLEMENTARY INFORMATION: The supplementary material are available at Bioinformatics online.

Algorithms↗
PubMed2005

A genome-wide linkage scan of familial benign recurrent vertigo: linkage to 22q12 with evidence of heterogeneity.

Benign recurrent vertigo (BRV) is a common disorder affecting up to 2% of the adult population and may be etiologically related to migraine because of similarities in the clinical spectrum of the phenotypes and a high co-morbidity within families. Many families have multiple-affected genetically related individuals suggesting familial transmission of the disorder with moderate to high penetrance. While clinically similar to episodic ataxias, there are currently no genes identified that contribute to BRV and no systematic linkage studies performed. In an initial effort to genetically define BRV, we have selected from our Neurology Clinic population a subset of 20 multigenerational families with apparent autosomal dominant transmission, and performed genetic linkage mapping using both parametric and non-parametric linkage (NPL) approaches. The Affymetrix 10K SNP Mapping Assay was used for the genotyping. Heterogeneity LOD (HLOD) analysis reveals the evidence of genetic heterogeneity for BRV and evidence of linkage in a subset of the families to 22q12 (HLOD = 4.02). An additional region was identified by NPL analysis at 5p15 (LOD = 2.63). As migraine is observed substantially more commonly both within the BRV-affected individuals and the related family members, it is possible that a form of migraine is allelic to the BRV locus at 22q12. However, testing linkage or the chromosome 22q12 region to a broader migraine/vertigo phenotype by defining affectation status as either migrainous headaches or BRV greatly weakened the linkage signal, and no significant other peaks were detected. Thus, BRV and migraine does not appear to be allelic disorders within these families. We conclude that BRV is a heterogeneous genetic disorder, appears genetically distinct from migraine with aura and is linked to 22q12. Additional family and population-based linkage and association studies will be needed to determine the causative alleles.

Chromosomes, Human, Pair 22↗
PubMed2005

Distribution and dynamics of Lamp1-containing endocytic organelles in fibroblasts deficient in BLOC-3.

Late endosomes and lysosomes of mammalian cells in interphase tend to concentrate in the perinuclear region that harbors the microtubule-organizing center. We have previously reported abnormal distribution of these organelles - as judged by reduced percentages of cells displaying pronounced perinuclear accumulation - in mutant fibroblasts lacking BLOC-3 (for ;biogenesis of lysosome-related organelles complex 3'). BLOC-3 is a protein complex that contains the products of the genes mutated in Hermansky-Pudlak syndrome types 1 and 4. Here, we developed a method based on image analysis to estimate the extent of organelle clustering in the perinuclear region of cultured cells. Using this method, we corroborated that the perinuclear clustering of late endocytic organelles containing Lamp1 (for ;lysosome-associated membrane protein 1') is reduced in BLOC-3-deficient murine fibroblasts, and found that it is apparently normal in fibroblasts deficient in BLOC-1 or BLOC-2, which are another two protein complexes associated with Hermansky-Pudlak syndrome. Wild-type and mutant fibroblasts were transfected to express human LAMP1 fused at its cytoplasmic tail to green fluorescence protein (GFP). At low expression levels, LAMP1-GFP was targeted correctly to late endocytic organelles in both wild-type and mutant cells. High levels of LAMP1-GFP overexpression elicited aberrant aggregation of late endocytic organelles, a phenomenon that probably involved formation of anti-parallel dimers of LAMP1-GFP as it was not observed in cells expressing comparable levels of a non-dimerizing mutant variant, LAMP1-mGFP. To test whether BLOC-3 plays a role in the movement of late endocytic organelles, time-lapse fluorescence microscopy experiments were performed using live cells expressing low levels of LAMP1-GFP or LAMP1-mGFP. Although active movement of late endocytic organelles was observed in both wild-type and mutant fibroblasts, quantitative analyses revealed a relatively lower frequency of microtubule-dependent movement events, either towards or away from the perinuclear region, within BLOC-3-deficient cells. By contrast, neither the duration nor the speed of these microtubule-dependent events seemed to be affected by the lack of BLOC-3 function. These results suggest that BLOC-3 function is required, directly or indirectly, for optimal attachment of late endocytic organelles to microtubule-dependent motors.

Animals↗
PubMed2005

Inferring protein domain interactions from databases of interacting proteins.

We describe domain pair exclusion analysis (DPEA), a method for inferring domain interactions from databases of interacting proteins. DPEA features a log odds score, Eij, reflecting confidence that domains i and j interact. We analyzed 177,233 potential domain interactions underlying 26,032 protein interactions. In total, 3,005 high-confidence domain interactions were inferred, and were evaluated using known domain interactions in the Protein Data Bank. DPEA may prove useful in guiding experiment-based discovery of previously unrecognized domain interactions.

Animals↗
PubMed2005

Empirical bayes estimation of a sparse vector of gene expression changes.

Gene microarray technology is often used to compare the expression of thousand of genes in two different cell lines. Typically, one does not expect measurable changes in transcription amounts for a large number of genes; furthermore, the noise level of array experiments is rather high in relation to the available number of replicates. For the purpose of statistical analysis, inference on the "population'' difference in expression for genes across the two cell lines is often cast in the framework of hypothesis testing, with the null hypothesis being no change in expression. Given that thousands of genes are investigated at the same time, this requires some multiple comparison correction procedure to be in place. We argue that hypothesis testing, with its emphasis on type I error and family analogues, may not address the exploratory nature of most microarray experiments. We instead propose viewing the problem as one of estimation of a vector known to have a large number of zero components. In a Bayesian framework, we describe the prior knowledge on expression changes using mixture priors that incorporate a mass at zero, and we choose a loss function that favors the selection of sparse solutions. We consider two different models applicable to the microarray problem, depending on the nature of replicates available, and show how to explore the posterior distributions of the parameters using MCMC. Simulations show an interesting connection between this Bayesian estimation framework and false discovery rate (FDR) control. Finally, two empirical examples illustrate the practical advantages of this Bayesian estimation paradigm.

Journal Article↗
PubMed2004

Vocabulon: a dictionary model approach for reconstruction and localization of transcription factor binding sites.

MOTIVATION: Gene expression arrays enable measurements of transcription values for a large number or all genes in the genome. In order to better interpret these results and to use them to reconstruct transcription networks, information on location of binding sites for regulatory proteins in the entire genome is needed. In particular, this represents an open problem in Escherichia coli. RESULTS: We describe the first implementation of dictionary-style models to the study of transcription factors binding sites in an entire genome. Vocabulon's unique feature is that it can both reconstruct binding sites characterized by unknown motifs and impute locations of known binding sites in long sequences by simultaneous search. On one hand, the dictionary model specifies a probability for the entire sequence taking simultaneously into account all the possible binding sites. This greatly reduces the number of false positives. On the other hand, the possibility of refining motif description, as an increasing number of binding sites are identified, augments the sensitivity of the method. We illustrate these properties with examples in E.coli. The results of gene expression arrays are used both to guide the search and corroborate it.

Algorithms↗
PubMed2004

A novel mutation in KCNA1 causes episodic ataxia without myokymia.

We describe a unique family in which several individual are affected with episodes of ataxia that best fit the phenotype of episodic ataxia type 2 (EA2). All of the affected family members had episodes typically lasting for several hours, and none of them had muscle abnormalities including myokymia. Episodic ataxia type 1 (EA1) was not considered initially as a clinical diagnosis for the affected individuals in this family. However, by linkage mapping, sequencing and polymorphism analysis, all affecteds were found to have a novel mutation in KCNA1. Numerous missense mutations have been described previously in KCNA1 that cause EA1. The mutation c.1025G>T replaces a highly conserved serine with isoleucine at position 342 (p.Ser342Ile) in the highly conserved fifth transmembrane domain of the KCNA1. This mutation leads to a distinct clinical phenotype without myokymia broadening the scope of clinical characteristics of EA1 and highlighting the heterogeneity of phenotypic effects from distinct missense mutations.

Adult↗
PubMed2004

The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology.

Efforts to identify gene variants associated with susceptibility to common diseases use three approaches: pedigree and affected sib-pair linkage studies and association studies of population samples. The different aims of these study designs reflect their derivation from biological versus epidemiological traditions. Similar principles regarding determination of the evidence levels required to consider the results statistically significant apply to both linkage and association studies, however. Such determination requires explicit attention to the prior probability of particular findings, as well as appropriate correction for multiple comparisons. For most common diseases, increasing the sample size in a study is a crucial step in achieving statistically significant genetic mapping results. Recent studies suggest that the technology and statistical methodology will soon be available to make well-powered studies feasible using any of these approaches.

Chromosome Mapping↗
PubMed2003

Transcriptome-based determination of multiple transcription regulator activities in Escherichia coli by using network component analysis.

Cells adjust gene expression profiles in response to environmental and physiological changes through a series of signal transduction pathways. Upon activation or deactivation, the terminal regulators bind to or dissociate from DNA, respectively, and modulate transcriptional activities on particular promoters. Traditionally, individual reporter genes have been used to detect the activity of the transcription factors. This approach works well for simple, non-overlapping transcription pathways. For complex transcriptional networks, more sophisticated tools are required to deconvolute the contribution of each regulator. Here, we demonstrate the utility of network component analysis in determining multiple transcription factor activities based on transcriptome profiles and available connectivity information regarding network connectivity. We used Escherichia coli carbon source transition from glucose to acetate as a model system. Key results from this analysis were either consistent with physiology or verified by using independent measurements.

Cyclic AMP↗