Biomedical subjects

Barbara E Stranger

Publications and source records attributed to Barbara E Stranger.

8 recordsLinked to original sources

PubMed2026

Menopause in the All of Us Research Program: a descriptive summary of electronic health record and survey response across sociodemographic characteristics.

OBJECTIVES: Menopause is a significant physiological transition with implications for health outcomes (eg, cardiometabolic disease), yet gaps remain in understanding this transition, including how menopause timing and type influence health outcomes. Large-scale cohort studies in midlife (age=40-60) females, including the All of Us Research Program (AoURP), provide opportunities to study menopause across diverse populations and data modalities. We characterized menopause-related data in AoURP, focusing on age distributions and concordance between electronic health record (EHR) diagnosis codes and survey responses. METHODS: We analyzed menopause-related surveys, EHR diagnostic codes, and genomic data among ~396,000 AoURP female participants. We summarized menopause-related variables across data sources, evaluated overlap between survey, EHR, and genomic data sets, and described age distributions overall and across sociodemographic characteristics. RESULTS: Among ~396,000 females, survey responses captured ~193,000 menopause observations, nearly seven times more than EHR diagnoses (~28,000), suggesting under-ascertainment in EHR data. Nearly all females (~99%) with an EHR menopause diagnosis reported menopause in the survey. Approximately 22,000 participants had overlapping menopause-related EHR, survey, and genomic data. Survey age patterns matched expectations, with participants predominantly <40 years reporting premenopausal status and those >60 years reporting postmenopausal status. A small subset with age >70 years (N≈1,700; 4%) reported no menopause, suggesting response or recall bias. EHR menopause codes were concentrated after age 45 years, with a notable spike at age 65. Modest differences in survey-based menopause age distributions were observed across sociodemographic characteristics (eg, race and ancestry). CONCLUSIONS: These findings inform sampling strategies, power calculations, phenotype definition, and study design for menopause research using AoURP data.

Age↗

PubMed2006

Functional variation and evolution of non-coding DNA.

The focus of large genomic studies has shifted from only looking at genes and protein-coding sequences to exploring the full set of elements in each genome. The explosion of comparative sequencing data has led to an increase in methodologies, approaches and ideas on how to analyze the unknown fraction of the genome, namely the non-protein-coding fraction. The main issues relate to the discovery, evolutionary analysis and natural variation of non-coding DNA, and the parameters that prevent us from fully understanding the properties of non-coding DNA.

Animals↗

PubMed2006

Genetic variation in human gene expression.

Gene expression variation has been the focus of many studies in the past few years. The relevance of gene regulation and gene expression to disease and the development of the technologies used to screen large numbers of genes simultaneously have allowed this rapid development. In this review we discuss issues relating to the biological information one obtains from such studies and the biological significance and use of signals from mapping of gene expression variation.

Gene Expression Profiling↗

PubMed2006

From DNA to RNA to disease and back: the 'central dogma' of regulatory disease variation.

Much of the focus of human disease genetics is directed towards identifying nucleotide variants that contribute to disease phenotypes. This is a complex problem, often involving contributions from multiple loci and their interactions, as well as effects due to environmental factors. Although some diseases with a genetic basis are caused by nucleotide changes that alter an amino acid sequence, in other cases, disease risk is associated with altered gene regulation. This paper focuses on how studies of gene expression variation might complement disease studies and provide crucial links between genotype and phenotype.

DNA↗

PubMed2005

Genome-wide associations of gene expression variation in humans.

The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.

Chromosome Mapping↗

PubMed2005

Nucleotide variation at the myrosinase-encoding locus, TGG1, and quantitative myrosinase enzyme activity variation in Arabidopsis thaliana.

The Arabidopsis thaliana TGG1 gene encodes thioglucoside glucohydrolase (myrosinase), an enzyme catalysing the hydrolysis of glucosinolate compounds. The enzyme is involved in plant defence against some insect herbivores, and is present in species of the order Capparales (Brassicales). Nucleotide variation was surveyed by sequencing c. 2.4 kb of the TGG1 locus in a sample of 28 worldwide A. thaliana accessions, and one Arabidopsis lyrata ssp. lyrata individual. Myrosinase activity was quantified for 27 of these same A. thaliana accessions, plus five additional others. Overall, estimated nucleotide diversity in A. thaliana was low compared to other published A. thaliana surveys, and the frequency distribution was skewed toward an excess of low-frequency variants. Furthermore, comparison to the outgroup species A. lyrata demonstrated that A. thaliana exhibited an excess of high-frequency derived variants relative to a neutral equilibrium model, suggesting a selective sweep. A. thaliana accessions differed significantly in total myrosinase activity, but analysis of variance detected no statistical evidence for an association between quantitative enzyme activity and alleles at the TGG1 myrosinase-encoding locus. We thus conclude that other, unsurveyed factors primarily affect the observed myrosinase activity levels in this species. The pattern of nucleotide variation was consistent with a model of positive selection but might also be compatible with a completely neutral model that takes into account the metapopulation behaviour of this highly inbreeding species which experienced a relatively recent worldwide expansion.

Arabidopsis↗

PubMed2005

The genetics of regulatory variation in the human genome.

The regulation of gene expression plays an important role in complex phenotypes, including disease in humans. For some genes, the genetic mechanisms influencing gene expression are well elucidated; however, it is unclear how applicable these results are to gene expression on a genome-wide level. Studies in model organisms and humans have clearly documented gene expression variation among individuals and shown that a significant proportion of this variation has a genetic basis. Recent studies combine microarray surveys of gene expression for thousands of genes with dense marker maps, and are beginning to identify regions in the human genome that have functional effects on gene expression. This paper reviews recent developments and methodologies in this field, and discusses implications and future directions of this research in the context of understanding the influence of human genomic variation on the regulation of gene expression.

Female↗

PubMed2004

Multilocus analysis of variation and speciation in the closely related species Arabidopsis halleri and A. lyrata.

Nucleotide variation in eight effectively unlinked genes was surveyed in species-wide samples of the closely related outbreeding species Arabidopsis halleri and A. lyrata ssp. petraea and in three of these genes in A. lyrata ssp. lyrata and A. thaliana. Significant genetic differentiation was observed more frequently in A. l. petraea than in A. halleri. Average estimates of nucleotide variation were highest in A. l. petraea and lowest in A. l. lyrata, reflecting differences among species in effective population size. The low level of variation in A. l. lyrata is concordant with a bottleneck effect associated with its origin. The A. halleri/A. l. petraea speciation process was studied, considering the orthologous sequences of an outgroup species (A. thaliana). The high number of ancestral mutations relative to exclusive polymorphisms detected in A. halleri and A. l. petraea, the significant results of the multilocus Fay and Wu H tests, and haplotype sharing between the species indicate introgression subsequent to speciation. Average among-population variation in A. halleri and A. l. petraea was approximately 1.5- and 3-fold higher than that in the inbreeder A. thaliana. The detected reduction of variation in A. thaliana is less than that expected from differences in mating system alone, and therefore from selective processes related to differences in the effective recombination rate, but could be explained by differences in population structure.

Arabidopsis↗