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Chami, N.

Publications and source records attributed to Chami, N..

4 recordsLinked to original sources

Whole genome association testing in 333,100 individuals across three biobanks identifies rare non-coding single variant and genomic aggregate associations with height

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N=200,003), TOPMed (N=87,652) and All of Us (N=45,445). We performed rare (<0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal, intergenic and deep-intronic annotation. We observed 29 independent variants associated with height at P < 6 x 10-10 after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed a novel approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

genetics↗

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.

genetics↗

Clonal hematopoiesis is driven by aberrant activation of TCL1A

A diverse set of driver genes, such as regulators of DNA methylation, RNA splicing, and chromatin remodeling, have been associated with pre-malignant clonal expansion of hematopoietic stem cells (HSCs). The factors mediating expansion of these mutant clones remain largely unknown, partially due to a paucity of large cohorts with longitudinal blood sampling. To circumvent this limitation, we developed and validated a method to infer clonal expansion rate from single timepoint data called PACER (passenger-approximated clonal expansion rate). Applying PACER to 5,071 persons with clonal hematopoiesis accurately recapitulated the known fitness effects due to different driver mutations. A genome-wide association study of PACER revealed that a common inherited polymorphism in the TCL1A promoter was associated with slower clonal expansion. Those carrying two copies of this protective allele had up to 80% reduced odds of having driver mutations in TET2, ASXL1, SF3B1, SRSF2, and JAK2, but not DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 by CRISPR editing led to aberrant expression of TCL1A and expansion of HSCs in vitro. These effects were abrogated in HSCs from donors carrying the protective TCL1A allele. Our results indicate that the fitness advantage of multiple common driver genes in clonal hematopoiesis is mediated through TCL1A activation. PACER is an approach that can be widely applied to uncover genetic and environmental determinants of pre-malignant clonal expansion in blood and other tissues.

genetics↗

Very severe anemia and one year mortality outcome after hospitalization in Tanzanian children: A prospective cohort study

BackgroundAfrica has the highest rates of child mortality. Little is known about outcomes after hospitalization for children with very severe anemia.\n\nObjectiveTo determine one year mortality and predictors of mortality in Tanzanian children hospitalized with very severe anemia.\n\nMethodsWe conducted a prospective cohort study enrolling children 2-12 years hospitalized from August 2014 to November 2014 at two public hospitals in northwestern Tanzania. Children were screened for anemia and followed until 12 months after discharge. The primary outcome measured was mortality. Predictors of mortality were determined using Cox regression analysis.\n\nResultsOf the 505 children, 90 (17.8%) had very severe anemia and 415 (82.1%) did not. Mortality was higher for children with very severe anemia compared to children without over a one year period from admission, 27/90 (30.0%) vs. 59/415 (14.2%) respectively (Hazard Ratio (HR) 2.42, 95% Cl 1.53-3.83). In-hospital mortality was 11/90 (12.2%) and post-hospital mortality was 16/79 (20.2%) for children with very severe anemia. The strongest predictors of mortality were age (HR 1.01, 95% Cl 1.00-1.03) and decreased urine output (HR 4.30, 95% Cl 1.04 - 17.7).\n\nConclusionsChildren up to 12 years of age with very severe anemia have nearly a 30% chance of mortality following admission over a one year period, with over 50% of mortality occurring after discharge. Post-hospital interventions are urgently needed to reduce mortality in children with very severe anemia, and should include older children.

epidemiology↗