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Biology subjects

Aldrich, M.

Publications and source records attributed to Aldrich, M..

4 recordsLinked to original sources

Minimum entropy framework identifies a novel class of genomic functional elements and reveals regulatory mechanisms at human disease loci

We introduce CoRE-BED, a framework trained using 19 epigenomic features in 33 major cell and tissue types to predict cell-type-specific regulatory function. CoRE-BED identifies nine functional classes de-novo, capturing both known and new regulatory categories. Notably, we describe a previously undercharacterized class that we term Development Associated Elements (DAEs), which are highly enriched in cell types with elevated regenerative potential and distinguished by the dual presence of either H3K4me2 and H3K9ac (an epigenetic signature associated with kinetochore assembly) or H3K79me3 and H4K20me1 (a signature associated with transcriptional pause release). Unlike bivalent promoters, which represent a transitory state between active and silenced promoters, DAEs transition directly to or from a non-functional state during stem cell differentiation and are proximal to highly expressed genes. CoRE-BEDs interpretability facilitates causal inference and functional prioritization. Across 70 complex traits, distal insulators account for the largest mean proportion of SNP heritability ([~]49%) captured by the GWAS. Collectively, our results demonstrate the value of exploring non-conventional ways of regulatory classification that enrich for trait heritability, to complement existing approaches for cis-regulatory prediction.

genomics↗

Genetic Landscape of Gullah African Americans

ObjectivesGullah African Americans are descendants of formerly enslaved Africans living in the Sea Islands along the coast of the southeastern U.S., from North Carolina to Florida. Their relatively high numbers and geographic isolation were conducive to the development and preservation of a unique culture that retains deep African features. Although historical evidence supports a West and Central African ancestry for the Gullah, linguistic and cultural evidence of a connection to Sierra Leone has led to the suggestion of this country/region as their ancestral home. This study sought to elucidate the genetic structure and ancestry of the Gullah. Materials and MethodsWe leveraged whole-genome genotype data from Gullah, African Americans from Jackson, Mississippi, Sierra Leone Africans, and population reference panels from Africa and Europe, to infer population structure, ancestry proportions, and global estimates of admixture. ResultsRelative to southeastern non-Gullah African Americans, the Gullah exhibit higher mean African ancestry, lower European admixture, a similarly small Native American contribution, and stronger male-biased European admixture. A slightly tighter bottleneck in the Gullah 13 generations ago suggests a largely shared demographic history with non-Gullah African Americans. Despite a slightly higher relatedness to Sierra Leone, our data demonstrate that the Gullah are genetically related to many West African populations. DiscussionThis study confirms that subtle differences in African American population structure exist at finer regional levels. Such observations can help to inform medical genetics research in African Americans, and guide the interpretation of genetic data used by African Americans seeking to explore ancestral identities. Research HighlightsO_LIUsing genomic data, we show that the Gullah have lower European and higher West African genomic background compared to non-Gullah African Americans, confirming their diverse African ancestry and rejecting a model that asserts a predominant Sierra Leone origin. C_LIO_LIOur data reveal a largely shared demographic history with southeastern non-Gullah African Americans, but also subtle differences related to high African genetic ancestry due to isolation in the Sea Islands. C_LI

genetics↗

A Clinical Phenotyping Algorithm to Identify Cases of Chronic Obstructive Pulmonary Disease in Electronic Health Records

RationaleChronic obstructive pulmonary disease (COPD) is a leading cause of mortality in the United States. Electronic health records provide large-scale healthcare data for clinical research, but have been underutilized in COPD research due to challenges identifying these individuals, especially in the absence of pulmonary function testing data.\n\nObjectivesTo develop an algorithm to electronically phenotype individuals with COPD at a large tertiary care center.\n\nMethodsWe identified individuals over 45 years of age at last clinic visit within Vanderbilt University Medical Center electronic health records. We tested phenotyping algorithms using combinations of both structured and unstructured text and examined the clinical characteristics of the resulting case sets.\n\nMeasurement and Main ResultsA simple algorithm consisting of 3 International Classification of Disease codes for COPD achieved a sensitivity of 97.6%, a specificity of 76.0%, a positive predictive value of 57.1%, and a negative predictive value of 99.0%. A more complex algorithm consisting of both billing codes and a mention of oxygen on the problem list that achieved a positive predictive value of 86.5%. However, the association of known risk factors with chronic obstructive pulmonary disease was consistent in both algorithm sets, suggesting a simple code-only algorithm may suffice for many research applications.\n\nConclusionsSimple code-only phenotyping algorithms for chronic obstructive pulmonary disease can identify case populations with epidemiologic and genetic profiles consistent with published literature. Implementation of this phenotyping algorithm will expand opportunities for clinical research and pragmatic trials for COPD.

bioinformatics↗

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg=0.57, p=4.6x10-8), breast and ovarian cancer (rg=0.24, p=7x10-5), breast and lung cancer (rg=0.18, p=1.5x10-6) and breast and colorectal cancer (rg=0.15, p=1.1x10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

genomics↗