Publications by authors named "ES Lander"

The time required to conduct clinical trials limits the rate at which we can evaluate and deliver new treatment options to patients with cancer. New approaches to increase trial efficiency while maintaining rigor would benefit patients, especially in oncology, in which adjuvant trials hold promise for intercepting metastatic disease, but typically require large numbers of patients and many years to complete. We envision a standing platform - an infrastructure to support ongoing identification and trial enrolment of patients with cancer with early molecular evidence of disease (MED) after curative-intent therapy for early-stage cancer, based on the presence of circulating tumour DNA.

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  • - The study introduces a method to identify natural selection signals in ancient DNA by analyzing trends in allele frequency changes over 14,000 years across a large population, revealing 347 significant genetic loci with strong selection evidence.
  • - Findings indicate that traditional hard sweeps of advantageous mutations have been rare in human evolution, but recently (in the last 10,000 years), many alleles have shown strong directional selection, with notable increases in traits like celiac disease risk and blood type B.
  • - The research suggests coordinated selection on traits affecting body fat, skin color, and cognitive performance, pointing to a shift in adaptive strategies as environments changed, although the exact adaptive traits from the past remain unclear.
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  • Most genetic variants linked to physical traits are found in non-coding regulatory areas rather than coding regions of the human genome, especially in those associated with blood cell traits.
  • We created a method called Perturb-multiome to analyze chromatin accessibility and gene expression simultaneously in single cells, using CRISPR to perturb master transcription factors during hematopoiesis.
  • Our findings indicate that a small fraction of TF-sensitive chromatin regions is significantly enriched in heritability for blood cell phenotypes, highlighting their importance in understanding genetic variants linked to these traits.
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Enhancers are key drivers of gene regulation thought to act via 3D physical interactions with the promoters of their target genes. However, genome-wide depletions of architectural proteins such as cohesin result in only limited changes in gene expression, despite a loss of contact domains and loops. Consequently, the role of cohesin and 3D contacts in enhancer function remains debated.

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Analyses of ancient DNA typically involve sequencing the surviving short oligonucleotides and aligning to genome assemblies from related, modern species. Here, we report that skin from a female woolly mammoth (†Mammuthus primigenius) that died 52,000 years ago retained its ancient genome architecture. We use PaleoHi-C to map chromatin contacts and assemble its genome, yielding 28 chromosome-length scaffolds.

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Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types.

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Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes.

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Infection with Lassa virus (LASV) can cause Lassa fever, a haemorrhagic illness with an estimated fatality rate of 29.7%, but causes no or mild symptoms in many individuals. Here, to investigate whether human genetic variation underlies the heterogeneity of LASV infection, we carried out genome-wide association studies (GWAS) as well as seroprevalence surveys, human leukocyte antigen typing and high-throughput variant functional characterization assays.

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  • Scientists are studying how DNA sequences work to control gene expression in different cell types, but it's been hard to figure out how these sequences affect gene activity.
  • They created a new method called Variant-FlowFISH to test many tiny changes in DNA and see how they change gene expression, using advanced tools like CRISPR.
  • By testing 672 different changes, they found that many can really change gene activity, and some changes work differently in different types of cells, which helps improve predictions about how genes are controlled.
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Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using large correlation matrices, but this approach is inefficient, especially in ancestrally diverse studies. In the present study, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD.

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Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods.

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Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells.

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Background: A key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene () are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia.

Methods: To search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls.

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Molecular profiling studies have enabled discoveries for metastatic prostate cancer (MPC) but have predominantly occurred in academic medical institutions and involved non-representative patient populations. We established the Metastatic Prostate Cancer Project (MPCproject, mpcproject.org), a patient-partnered initiative to involve patients with MPC living anywhere in the US and Canada in molecular research.

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For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.

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Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation.

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  • Gene regulation in humans involves distal enhancers activating nearby promoters, with a proposed model suggesting that promoters have specific sequence preferences for certain enhancers mediated by transcription factors.
  • A new high-throughput assay called ExP STARR-seq was developed to analyze the compatibility between 1,000 enhancer and 1,000 promoter sequences in human K562 cells, revealing that enhancers generally activate promoters similarly and their combined effects determine RNA output.
  • The study found that housekeeping gene promoters, which have activating motifs, are less responsive to enhancers, while promoters of variably expressed genes are more responsive, indicating a nuanced model of gene transcription control based on enhancer-promoter compatibility.
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  • Single-cell RNA sequencing (scRNA-seq) combined with RNA velocity and metabolic labeling provides detailed insights into how cells change states and transition over time.
  • The dynamo framework is introduced as a tool that enhances the analysis of scRNA-seq data by inferring RNA velocity, predicting cell fates, and identifying key regulatory mechanisms using advanced mathematical techniques.
  • Dynamically demonstrating its effectiveness, dynamo helps uncover the processes behind platelet cell formation and predicts how changes in gene activity can influence cell fates, marking a significant advancement in understanding cell state transitions.
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Transmission of coronavirus disease 2019 (COVID-19) from people without symptoms confounds societal mitigation strategies. From April to June 2020, we tested nasopharyngeal swabs by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) from 15 514 staff and 16 966 residents of nursing homes and assisted living facilities in Massachusetts. Cycle threshold (Ct) distributions were very similar between populations with (n = 739) and without (n = 2179) symptoms at the time of sampling (mean Ct, 25.

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Recent methods for spatial imaging of tissue samples can identify up to ~100 individual proteins or RNAs at single-cell resolution. However, the number of proteins or genes that can be studied in these approaches is limited by long imaging times. Here we introduce Composite In Situ Imaging (CISI), a method that leverages structure in gene expression across both cells and tissues to limit the number of imaging cycles needed to obtain spatially resolved gene expression maps.

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  • Genome-wide association studies (GWAS) have found many noncoding regions related to diseases, but translating these findings into functional insights is challenging due to insufficient maps of enhancers and target genes.
  • The activity-by-contact (ABC) model was developed to predict enhancer-gene interactions and applied across 131 human cell types, linking over 5,000 GWAS signals to nearly 2,250 unique genes with implications for various diseases.
  • Specifically for inflammatory bowel disease (IBD), ABC model identified risk variants in enhancers that regulate gene expression, offering a new understanding of disease mechanisms and providing a blueprint for future connections between genetic variants and their functions.
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Skeletal and glycemic traits have shared etiology, but the underlying genetic factors remain largely unknown. To identify genetic loci that may have pleiotropic effects, we studied Genome-wide association studies (GWASs) for bone mineral density and glycemic traits and identified a bivariate risk locus at 3q21. Using sequence and epigenetic modeling, we prioritized an adenylate cyclase 5 (ADCY5) intronic causal variant, rs56371916.

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