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Bick, A. G.

Publications and source records attributed to Bick, A. G..

12 recordsLinked to original sources

Rhodopsin is a tunable capacitor buffering the toxic, desensitizing retinoids of the vertebrate eye

The eye is a marvel of evolution, but visual sensitivity introduces the risk of blinding photodamage. Here we reveal that the locus of sensitivity--the visual pigment rhodopsin --moonlights as a tunable mechanism of retinal photoprotection. Independent of signaling, light activated rhodopsin (R*) serves as an overflow capacitor buffering all-trans retinal (atRAL), a toxic and desensitizing retinoid agonist that accumulates as lipofuscin--a clinical marker of macular degeneration. Across mammals, R* stability reflects binding affinity and sequestration of atRAL (capacitance), thereby mitigating phototoxicity to a degree proportional to species photodamage risk, with human R* uniquely non-protective. A mouse model of defective atRAL clearance treated with a synthetic R* of unnaturally high atRAL capacitance preserved retinal function following light damage. This gene therapy also provided supra-physiological scotopic sensitivity despite being a signal-silent receptor, shielding neighboring dark-state receptors from agonist interference during regeneration, while also enhancing the signaling of endogenous R*. While the consensus human rhodopsin is not photoprotective, during recent evolution, mutations that protect against light damage emerged in high irradiance human environments and are now significantly associated with a 38% reduced risk of blindness and low vision. Together, our findings redefine rhodopsin as a tunable light buffer that can be leveraged to enhance photoreceptor function beyond natural limits.

biochemistry↗

Closing the loop: Teaching single-cell foundation models to learn from perturbations

The application of transfer learning models to large scale single-cell datasets has enabled the development of single-cell foundation models (scFMs) that can predict cellular responses to perturbations in silico. Although these predictions can be experimentally tested, current scFMs are unable to "close the loop" and learn from these experiments to create better predictions. Here, we introduce a "closed-loop" framework that extends the scFM by incorporating perturbation data during model fine-tuning. Our closed-loop model improves prediction accuracy, increasing positive predictive value in the setting of T-cell activation three-fold. We applied this model to RUNX1-familial platelet disorder, a rare pediatric blood disorder and identified two therapeutic targets (mTOR and CD74-MIF signaling axis) and two novel pathways (protein kinase C and phosphoinositide 3-kinase). This work establishes that iterative incorporation of experimental data to foundation models enhances biological predictions, representing a crucial step toward realizing the promise of "virtual cell" models for biomedical discovery.

bioinformatics↗

Inherited resilience to clonal hematopoiesis by modifying stem cell RNA regulation

Somatic mutations that increase hematopoietic stem cell (HSC) fitness drive their expansion in clonal hematopoiesis (CH) and predispose to blood cancers. Although CH frequently occurs with aging, it rarely progresses to overt malignancy. Population variation in the growth rate and potential of mutant clones suggests the presence of genetic factors protecting against CH, but these remain largely undefined. Here, we identify a non-coding regulatory variant, rs17834140-T, that significantly protects against CH and myeloid malignancies by downregulating HSC-selective expression and function of the RNA-binding protein MSI2. By modeling variant effects and mapping MSI2 binding targets, we uncover an RNA network that maintains human HSCs and influences CH risk. Importantly, rs17834140-T is associated with slower CH expansion rates in humans, and stem cell MSI2 levels modify ASXL1-mutant HSC clonal dominance in experimental models. These findings leverage natural resilience to highlight a key role for post-transcriptional regulation in human HSCs, and offer genetic evidence supporting inhibition of MSI2 or its downstream targets as rational strategies for blood cancer prevention.

genetics↗

Clinical progression of clonal hematopoiesis is determined by a combination of mutation timing, fitness, and clonal structure

Clonal hematopoiesis (CH) is characterized by expanding blood cell clones carrying somatic mutations in healthy aged individuals and is associated with various age-related diseases and all-cause mortality. While CH mutations affect diverse genes associated with myeloid malignancies, their mechanisms of expansion and disease associations remain poorly understood. We investigate the relationship between clonal fitness and clinical outcomes by integrating data from three longitudinal aging cohorts (n=713, observations=2,341). We demonstrate pathway-specific fitness advantage and clonal composition influence clonal dynamics. Further, the timing of mutation acquisition is necessary to determine the extent of clonal expansion reached during the host individuals lifetime. We introduce MACS120, a metric combining mutation context, timing, and variant fitness to predict future clonal growth, outperforming traditional variant allele frequency measurements in predicting clinical outcomes. Our unified analytical framework enables standardized clonal dynamics inference across cohorts, advancing our ability to predict and potentially intervene in CH-related pathologies.

genetics↗

Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies has not yet been performed. To do so, we optimized Targeted Methylation Sequencing protocol (TMS)--which profiles [~]4 million CpG sites--for miniaturization, flexibility, and multispecies use at a cost of [~]$80. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n=55 paired samples) and whole genome bisulfite sequencing (n=6 paired samples). In both cases, we found strong agreement between technologies (R{superscript 2} = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean=77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R{superscript 2} = 0.98). Finally, we applied our protocol to profile age-associated DNA methylation variation in two subsistence-level populations--the Tsimane of lowland Bolivia and the Orang Asli of Peninsular Malaysia--and found age-methylation patterns that were strikingly similar to those reported in high income cohorts, despite known differences in age-health relationships between lifestyle contexts. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

genomics↗

Human Plasma Proteomic Profile of Clonal Hematopoiesis

Plasma proteomic profiles associated with subclinical somatic mutations in blood cells may offer novel insights into downstream clinical consequences. Here, we explore such patterns in clonal hematopoiesis of indeterminate potential (CHIP), which is linked to several cancer and non-cancer outcomes, including coronary artery disease (CAD). Among 61,833 ancestrally diverse participants (3,881 with CHIP) from NHLBI TOPMed and UK Biobank with blood-based DNA sequencing and proteomic measurements (1,148 proteins by SomaScan in TOPMed and 2,917 proteins by Olink in UK Biobank), we identified 32 and 345 unique proteins from TOPMed and UK Biobank, respectively, associated with the most prevalent driver genes (DNMT3A, TET2, and ASXL1). These associations showed substantial heterogeneity by driver genes, sex, and race, and were enriched for immune response and inflammation pathways. Mendelian randomization in humans, coupled with ELISA in hematopoietic Tet2-/- vs wild-type mice validation, disentangled causal proteomic perturbations from TET2 CHIP. Lastly, we identified plasma proteins shared between CHIP and CAD.

genetics↗

Mutated cells mediate distinct inflammatory responses in clonal hematopoiesis

Clonal hematopoiesis (CH) is an age-associated phenomenon that increases risk for hematologic malignancy and cardiovascular disease. CH is thought to enhance disease risk through inflammation in the peripheral blood1. Here, we profile peripheral blood gene expression in 66,968 single cells from a cohort of 17 CH patients and 7 controls. Using a novel mitochondrial DNA barcoding approach, we were able to identify and separately compare mutant TET2 and DNMT3A cells to non-mutant counterparts. We discovered the vast majority of mutated cells were in the myeloid compartment. Additionally, patients harboring DNMT3A and TET2 CH mutations possessed a pro-inflammatory profile in CD14+ monocytes through previously unrecognized pathways such as galectin and macrophage Inhibitory Factor (MIF). We also found that T cells from CH patients, though mostly un-mutated, had decreased expression of GTPase of the immunity associated protein (GIMAP) genes, which are critical to T cell development, suggesting that CH may impair T cell function. Key points- CD14+ monocytes from clonal hematopoiesis patients stimulate inflammation through increased cytokine expression. - T cells from clonal hematopoiesis are deficient in GIMAP expression, suggesting CH may impair T cell differentiation.

genetics↗

Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

The rapid growth of genomic data has led to a new research paradigm where data are stored centrally in Trusted Research Environments (TREs) such as the All of Us Researcher Workbench (AoU RW) and the UK Biobank Research Analysis Platform (RAP). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conducted a Genome-Wide Association Study (GWAS) of standard lipid measures on the UKB RAP and AoU RW using two approaches: meta-analysis and pooled analysis. We curated lipid measurements for 37,754 All of Us participants with whole genome sequence (WGS) data and 190,982 UK Biobank participants with whole exome sequence (WES) data. For the meta-analysis, we performed a GWAS of each cohort in their respective platform and meta-analyzed the results. We separately performed a pooled GWAS on both datasets combined. We identified 490 and 464 significant variants in meta-analysis and pooled analysis, respectively. Comparison of full summary data from both meta-analysis and pooled analysis with an external study showed strong correlation of known loci with lipid levels (R2[~]83-97%). Importantly, 90 variants met the significance threshold only in the meta-analysis and 64 variants were significant only in pooled analysis. These method-specific differences may be explained by differences in cohort size, ancestry, and phenotype distributions in All of Us and UK Biobank. We noted approximately 20% of variants significant in only the pooled analysis or significant in only the meta-analysis were most prevalent in non-European, non-Asian ancestry individuals. Pooled analyses included more variants than meta-analyses. Pooled analysis required about half as many computational steps as meta-analysis. These findings have important implications for both platform implementations and researchers undertaking large-scale cross-cohort analyses, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

genetics↗

Subset-specific mitochondrial and DNA damage shapes T cell responses to fever and inflammation

Heat is a cardinal feature of inflammation. Despite temperature variability and dependence of enzymes and complexes, how heat and fever affect immune cells remains uncertain. We found that heat broadly increased inflammatory activity of CD4+ T cell subsets and decreased Treg suppressive function. Th1 cells, however, also selectively developed mitochondrial dysfunction with high levels of ROS production and DNA damage. This led Th1 cells to undergo Tp53-dependent death, which was required to minimize the accumulation of mutations in heat and inflammation. Th1 cells with similar DNA damage signatures were also detected in Crohns disease and rheumatoid arthritis. Fever and inflammation-associated heat thus selectively induce mitochondrial stress and DNA damage in activated Th1 cells that requires p53 to maintain genomic integrity of the T cell repertoire. One Sentence SummaryFever temperatures augment CD4+ T cell-mediated inflammation but induce differential metabolic stress and DNA damage in T cell subsets, with Th1 cells selectively sensitive and dependent on p53 to induce apoptosis and maintain genomic integrity.

immunology↗

Deep learning enables genetic analysis of the human thoracic aorta

The aorta is the largest blood vessel in the body, and enlargement or aneurysm of the aorta can predispose to dissection, an important cause of sudden death. While rare syndromes have been identified that predispose to aortic aneurysm, the common genetic basis for the size of the aorta remains largely unknown. By leveraging a deep learning architecture that was originally developed to recognize natural images, we trained a model to evaluate the dimensions of the ascending and descending thoracic aorta in cardiac magnetic resonance imaging. After manual annotation of just 116 samples, we applied this model to 3,840,140 images from the UK Biobank. We then conducted a genome-wide association study in 33,420 individuals, revealing 68 loci associated with ascending and 35 with descending thoracic aortic diameter, of which 10 loci overlapped. Integration of common variation with transcriptome-wide analyses, rare-variant burden tests, and single nucleus RNA sequencing prioritized SVIL, a gene highly expressed in vascular smooth muscle, that was significantly associated with the diameter of the ascending and descending aorta. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in the remaining 391,251 UK Biobank participants who did not undergo imaging (HR = 1.44 per standard deviation; P = 3.7{middle dot}10-12). Defining the genetic basis of the diameter of the aorta may enable the identification of asymptomatic individuals at risk for aneurysm or dissection and facilitate the prioritization of potential therapeutic targets for the prevention or treatment of aortic aneurysm. Finally, our results illustrate the potential for rapidly defining novel quantitative traits derived from a deep learning model, an approach that can be more broadly applied to biomedical imaging data.

genomics↗

Genetic predisposition to myeloproliferative neoplasms implicates hematopoietic stem cell biology

Myeloproliferative neoplasms (MPNs) are blood cancers characterized by excessive production of mature myeloid cells that result from the acquisition of somatic driver mutations in hematopoietic stem cells (HSCs)1. While substantial progress has been made to define the causal somatic mutation profile for MPNs2, epidemiologic studies indicate a significant heritable component for the disease that is among the highest known for all cancers3. However, only a limited set of genetic risk loci have been identified, and the underlying biological mechanisms leading to MPN acquisition remain unexplained. Here, to define the inherited risk profile, we conducted the largest genome-wide association study of MPNs to date (978,913 individuals with 3,224 cases) and identified 14 genome-wide significant loci, as well as a polygenic signature that increases the odds for disease acquisition by nearly 3-fold between the top and median deciles. Interestingly, we find a shared genetic architecture between MPN risk and several hematopoietic traits spanning distinct lineages, as well as an association between increased MPN risk and longer leukocyte telomere length, collectively implicating HSC function and self-renewal. Strikingly, we find a significant enrichment for risk variants mapping to accessible chromatin in HSCs compared with other hematopoietic populations. Finally, gene mapping identifies modulators of HSC biology and targeted variant-to-function analyses suggest likely roles for CHEK2 and GFI1B in altering HSC function to confer disease risk. Overall, we demonstrate the power of human genetic studies to illuminate a previously unappreciated mechanism for MPN risk through modulation of HSC function.

genetics↗

Inherited Causes of Clonal Hematopoiesis of Indeterminate Potential in TOPMed Whole Genomes

Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown.1 Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations was associated with both hematologic cancer incidence2-4 and coronary heart disease prevalence.5 Somatic mutations with leukemogenic potential may confer selective cellular advantages leading to clonal expansion, a phenomenon termed Clonal Hematopoiesis of Indeterminate Potential (CHIP).6 Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico-informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer. Aggregates of rare germline loss-of-function variants in CHEK2, a DNA damage repair gene, predisposed to CHIP acquisition. Overall, we observe that germline genetic variation altering hematopoietic stem cell function and the fidelity of DNA-damage repair increase the likelihood of somatic mutations leading to CHIP.

genomics↗