Showing papers by "Boston University published in 2022"
01 Jan 2022
TL;DR: In this paper, the authors assessed how depressive symptoms changed among U.S. adults over the course of the COVID-19 pandemic and identified the key risk factors for these symptoms.
Abstract: Background The COVID-19 pandemic and its consequences have been associated with an increase in poor population mental health. We assessed how depressive symptoms changed among U.S. adults over the course of the COVID-19 pandemic and identified the key risk factors for these symptoms. Methods Longitudinal panel study of a nationally representative group of U.S. adults ages 18 years and older surveyed in March-April 2020 (Time 1; N=1441) and March-April 2021 (Time 2; N=1161) in the COVID-19 and Life Stressors Impact on Mental Health and Well-being study (CLIMB). The Patient Health Questionnaire-9 (PHQ-9) was used to define elevated depressive symptoms (cut-off ≥10) and depressive symptoms score (0-27). Findings The prevalence of elevated depressive symptoms persisted from 27.8% in 2020 (95% CI: 24.9, 30.9) to 32.8% in 2021 (95% CI: 29.1, 36.8). Over time, the central drivers of depressive symptoms were low household income, not being married, and experiencing multiple stressors during the COVID-19 pandemic. The odds ratio of elevated depressive symptoms for low income relative to high income persons increased from 2.3 (95% CI: 1.2, 4.2) in 2020 to 7.0 (95% CI: 3.7, 13.3) in 2021. Fewer people reported experiencing 4 or more COVID-19 stressors in 2021 than in 2020 (47.5% in 2020 vs 37.1% in 2021), but the odds ratio of elevated depressive symptoms associated with 4 or more stressors relative to 1 stressor or less increased from 1.9 (95% CI: 1.2, 3.1) in 2020 to 5.4 (95% CI: 3.2, 9.2) in 2021. Interpretation The burden of depressive symptoms in the U.S. adult population increased over the course of the COVID-19 pandemic. Mental health gaps grew between populations with different assets and stressor experiences during the COVID-19 pandemic. Funding CLIMB Time 1 was sponsored by the Rockefeller Foundation-Boston University 3-D Commission. CLIMB Time 2 was sponsored by the de Beaumont Foundation.
74 citations
TL;DR: In this article , the inner ring of the isolated yeast pore complex is resolved by cryo-EM at sub-nanometer resolution to show how flexible connectors tie together different structural and functional layers.
54 citations
TL;DR: In this paper, a survey of 1478 travelers and multistep group structural equation model analysis revealed that the Health Belief Model constructs of cues to action (trust in third-party information sources), perceived severity of and susceptibility to COVID-19, and beliefs about the protection benefits of a COVID19 vaccine, subsequently elicited willingness to vaccinate and beliefs that others should vaccinate prior to travel and enhanced support for pre-travel vaccination mandates.
43 citations
TL;DR: In this paper , a systematic review and meta-analysis of observational studies investigating the relation between cadmium exposure and risk of type 2 diabetes and prediabetes, and to summarize data on the magnitude and shape of the association was performed.
37 citations
TL;DR: In this paper, a systematic review and meta-analysis of observational studies investigating the relation between cadmium exposure and risk of type 2 diabetes and prediabetes, and to summarize data on the magnitude and shape of the association was performed.
37 citations
TL;DR: In this paper, exosomes derived from rhesus monkey mesenchymal stromal cells (MSC-Exo) were used for demyelination in mice.
36 citations
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TL;DR: In this paper , the authors present the Pragmatic markers, a set of markers that can be used to mark the ground truth of a given sentence with a pragmatical marker.
Abstract: Preview this article: Pragmatic markers, Page 1 of 1 < Previous page | Next page > /docserver/preview/fulltext/prag.6.2.03fra-1.gif
34 citations
TL;DR: A systematic review of published and unpublished clinical trials using zinc or selenium supplementation to treat or prevent COVID-19 in the Pubmed, Scopus and ClinicalTrials databases up to 10 January 2022 is presented in this paper .
33 citations
TL;DR: A game-theoretic model develops to investigate how a blockchain platform's decision on its settings affects the competition between blockchain platforms as well as the participation behavior of customers and miners suggests that increasing the transaction fee alleviates congestion on the platform when customers have a relatively balanced need between efficiency and safety.
32 citations
TL;DR: The prefrontal cortex as discussed by the authors has been found to have an increased capacity to engage high-level regulatory strategies aimed at coping with and modifying the experience of anxiety, which can affect negative bias, failure to regulate autonomic arousal, and avoidance that characterize anxiety disorders.
30 citations
TL;DR: Neely et al. as discussed by the authors found that surviving oligodendrocytes make few new sheaths and frequently mistarget new myelin to neuronal cell bodies, a pathology they also found in MS.
Abstract: Oligodendrocytes that survive demyelination can remyelinate, including in multiple sclerosis (MS), but how they do so is unclear. In this study, using zebrafish, we found that surviving oligodendrocytes make few new sheaths and frequently mistarget new myelin to neuronal cell bodies, a pathology we also found in MS. In contrast, oligodendrocytes generated after demyelination make abundant and correctly targeted sheaths, indicating that they likely also have a better regenerative potential in MS. Neely et al. investigated the regeneration of different oligodendrocytes after demyelination. They found that newly generated cells exhibit much more proficient remyelination than those that survive demyelination, with implications for MS.
TL;DR: In this article , the authors present a comprehensive and critical systematic review of 701 studies (and a shorter sample of 375 studies examined in depth) to assess glass manufacturing and use across multiple sectors (including buildings, automotive manufacturing, construction, electronics, and renewable energy).
Abstract: Glass is a material inextricably linked with human civilization. It is also the product of an energy intensive industry. About 75%–85% of the total energy requirements to produce glass occur when the raw materials are heated in a furnace to more than 1500 °C. During this process, large volumes of emissions arise. The container and flat glass industries, which combined account for 80% of total glass production, emit over 60 million tonne of CO2 per year. However, environmental issues relating to the glass industry are not just limited to the manufacturing stage, but also from raw materials extraction, which impacts local ecosystems and creates other environmental challenges associated with tailing ponds, waste disposal and landfills. This systematic review poses five questions to examine these issues and themes: What alternatives exist to abate the climate effects of glass and thus make the full life cycle of glass more sustainable? What are the key determinants of energy and carbon from glass? What technical innovations have been identified to make glass manufacturing low to zero carbon? What benefits will amass from more carbon-friendly process in glass manufacturing, and what barriers will need tackling? To examine these questions, this study presents the findings of a comprehensive and critical systematic review of 701 studies (and a shorter sample of 375 studies examined in depth). A sociotechnical lens is used to assess glass manufacturing and use across multiple sectors (including buildings, automotive manufacturing, construction, electronics, and renewable energy), and options to decarbonize. The study identifies a number of barriers ranging from financial to infrastructural capacity, along with high potential avenues for future research.
TL;DR: In this article, high-resolution structures of amyloid fibrils formed from normally-folded proteins have revealed non-native conformations of the polypeptide chains, in contrast to earlier models that posited a role for assembly of partially folded proteins.
TL;DR: Wang et al. as discussed by the authors developed a family of wound dressings for intraoral wound repair by infiltrating a ductile long-chain hydrogel network into a prefabricated, sturdy macromolecular meshwork and in situ crosslinking.
Abstract: Due to the wet and dynamic environment of the oral cavity, the healing of intraoral wounds, such as tooth extraction wounds, requires stable and firm wound dressings. In clinical practice, cotton balls and gauzes, sponge plugs, or sutures are used to treat extraction wounds, but none of these means can continuously isolate the wound from the intraoral environment and facilitate ideal healing conditions. Herein, inspired by the natural extracellular matrix, a family of wound dressings is developed for intraoral wound repair. Infiltrating a ductile long-chain hydrogel network into a prefabricated, sturdy macromolecular meshwork and in situ crosslinking endowed the composite hydrogel with controllable swelling behaviors and robust mechanical properties. The macromolecular meshwork functioned as the backbone to support the composite and restricts the swelling of the long-chain hydrogel network. In vitro tests verified that this wound dressing can provide durable protection for intraoral wounds against complex irritations. Furthermore, accelerated wound healing occurred when the wound dressing is applied in vivo on a canine tooth extraction model, due to the effective reduction of acute inflammation. These results suggest that this family of bioinspired hydrogels has great potential for application as intraoral wound dressing.
TL;DR: In this paper , the authors estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019 for 1470 county sets in the U.S. representing 3138 counties.
Abstract: The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.
TL;DR: DeLTA 2.0 as discussed by the authors uses deep convolutional neural networks to extract single-cell information from time-lapse images, requiring no human input after training, which can be used to quantify gene expression and cell growth.
Abstract: Improvements in microscopy software and hardware have dramatically increased the pace of image acquisition, making analysis a major bottleneck in generating quantitative, single-cell data. Although tools for segmenting and tracking bacteria within time-lapse images exist, most require human input, are specialized to the experimental set up, or lack accuracy. Here, we introduce DeLTA 2.0, a purely Python workflow that can rapidly and accurately analyze images of single cells on two-dimensional surfaces to quantify gene expression and cell growth. The algorithm uses deep convolutional neural networks to extract single-cell information from time-lapse images, requiring no human input after training. DeLTA 2.0 retains all the functionality of the original version, which was optimized for bacteria growing in the mother machine microfluidic device, but extends results to two-dimensional growth environments. Two-dimensional environments represent an important class of data because they are more straightforward to implement experimentally, they offer the potential for studies using co-cultures of cells, and they can be used to quantify spatial effects and multi-generational phenomena. However, segmentation and tracking are significantly more challenging tasks in two-dimensions due to exponential increases in the number of cells. To showcase this new functionality, we analyze mixed populations of antibiotic resistant and susceptible cells, and also track pole age and growth rate across generations. In addition to the two-dimensional capabilities, we also introduce several major improvements to the code that increase accessibility, including the ability to accept many standard microscopy file formats as inputs and the introduction of a Google Colab notebook so users can try the software without installing the code on their local machine. DeLTA 2.0 is rapid, with run times of less than 10 minutes for complete movies with hundreds of cells, and is highly accurate, with error rates around 1%, making it a powerful tool for analyzing time-lapse microscopy data.
01 Jan 2022
TL;DR: A framework based on Recurrent Neural Networks (RNNs) is proposed to determine an optimal control strategy for a discrete-time system that is required to satisfy specifications given as Signal Temporal Logic (STL) formulae.
Abstract: We propose a framework based on Recurrent Neural Networks (RNNs) to determine an optimal control strategy for a discrete-time system that is required to satisfy specifications given as Signal Temporal Logic (STL) formulae. RNNs can store information of a system over time, thus, enable us to determine satisfaction of the dynamic temporal requirements specified in STL formulae. Given a STL formula, a dataset of satisfying system executions and corresponding control policies, we can use RNNs to predict a control policy at each time based on the current and previous states of system. We use Control Barrier Functions (CBFs) to guarantee the safety of the predicted control policy. We validate our theoretical formulation and demonstrate its performance in an optimal control problem subject to partially unknown safety constraints through simulations.
DOI•
01 Feb 2022
TL;DR: In this article, the long-term humoral immune response in naive and previously infected volunteers who received Gam-COVID-Vac (SPUTNIK V) was studied.
Abstract: Background Gam-COVID-Vac (SPUTNIK V) has been granted emergency use authorization in 70 nations and has been administered to millions worldwide. However, there are very few peer-reviewed studies describing its effects. Independent reports regarding safety and effectiveness could accelerate the final approval by the WHO. We aimed to study the long-term humoral immune response in naive and previously infected volunteers who received SPUTNIK V. Methods Humoral immune responses, assayed by anti-SARS-CoV-2-spike-RBD IgG ELISA and neutralization assays, were measured in 602 healthcare workers at 0, 14, 28, 60 and 180 days after receiving SPUTNIK V between December 2020 and July 2021 in Tucuman, Argentina. Findings Seroconversion was detected in 97% of individuals after 28 days post-vaccination (dpv) (N = 405). Anti-RBD titers began to decrease after 60 dpv (N = 328), but remained detectable in 94% at 90 dpv (N = 224). At 180 dpv, anti-RDB titers persisted in 31% (N = 146). Previous infection triggered an increased immune response to the first dose and increased neutralization activity against variants of concern (VOC). Second doses in previously infected individuals further increased titers, even 90 dpv (N = 75). Basal antibody titers had more influence on post-vaccination anti-RBD responses than the time elapsed between diagnosis and vaccination (N = 274). Interpretation Data presented herein provides essential knowledge regarding the kinetics of antibodies induced by SPUTNIK V up to six months after immunization, and suggests that when considering one-dose vaccination policies for individuals with previous SARS-CoV-2 infection, serological studies to determine basal titers may be important, independent of when diagnosis occurred. Funding Tucuman Public Health System (SIPROSA), Argentinean National Research Council (CONICET), National University of Tucuman (UNT).
TL;DR: Synthetic gene circuits that precisely control human cell function could expand the capabilities of gene-and cell-based therapies as discussed by the authors , however, platforms for developing circuits in primary human cells that drive robust functional changes in vivo and have compositions suitable for clinical use are lacking.
Abstract: Synthetic gene circuits that precisely control human cell function could expand the capabilities of gene- and cell-based therapies. However, platforms for developing circuits in primary human cells that drive robust functional changes in vivo and have compositions suitable for clinical use are lacking. Here, we developed synthetic zinc finger transcription regulators (synZiFTRs), which are compact and based largely on human-derived proteins. As a proof of principle, we engineered gene switches and circuits that allow precise, user-defined control over therapeutically relevant genes in primary T cells using orthogonal, US Food and Drug Administration-approved small-molecule inducers. Our circuits can instruct T cells to sequentially activate multiple cellular programs such as proliferation and antitumor activity to drive synergistic therapeutic responses. This platform should accelerate the development and clinical translation of synthetic gene circuits in diverse human cell types and contexts.
Institute for the Physics and Mathematics of the Universe1, Kavli Institute for the Physics and Mathematics of the Universe2, Kobe University3, University of Tokyo4, King's College London5, University of California, Irvine6, Tohoku University7, Duke University8, KEK9, Okayama University10, Kyoto University11, Keio University12, Tokyo University of Science13, Boston University14, University of Oxford15, Miyagi University of Education16, University of Toronto17, Obayashi Corporation18, Shizuoka University of Welfare19, Tokai University20, Yokohama National University21, Nagoya University22, Imperial College London23, Tokyo Institute of Technology24, Tsinghua University25, Sungkyunkwan University26, INFN Sezione di Bari27, Okayama University of Science28, International Centre for Interdisciplinary Science and Education29
TL;DR: In order to improve Super-Kamiokande's neutron detection efficiency and to increase its sensitivity to the diffuse supernova neutrino background flux, 13 tons of Gd2(SO4)3⋅8H2O (gadolinium sulfate octahydrate) was dissolved into the detector's otherwise ultrapure water from July 14 to August 17, 2020, marking the start of the SK-Gd phase of operations as mentioned in this paper .
Abstract: In order to improve Super-Kamiokande’s neutron detection efficiency and to thereby increase its sensitivity to the diffuse supernova neutrino background flux, 13 tons of Gd2(SO4)3⋅8H2O (gadolinium sulfate octahydrate) was dissolved into the detector’s otherwise ultrapure water from July 14 to August 17, 2020, marking the start of the SK-Gd phase of operations. During the loading, water was continuously recirculated at a rate of 60 m3/h, extracting water from the top of the detector and mixing it with concentrated Gd2(SO4)3⋅8H2O solution to create a 0.02% solution of the Gd compound before injecting it into the bottom of the detector. A clear boundary between the Gd-loaded and pure water was maintained through the loading, enabling monitoring of the loading itself and the spatial uniformity of the Gd concentration over the 35 days it took to reach the top of the detector. During the subsequent commissioning the recirculation rate was increased to 120 m3/h, resulting in a constant and uniform distribution of Gd throughout the detector and water transparency equivalent to that of previous pure-water operation periods. Using an Am–Be neutron calibration source the mean neutron capture time was measured to be 115±1 μs, which corresponds to a Gd concentration of 111±2 ppm, as expected for this level of Gd loading. This paper describes changes made to the water circulation system for this detector upgrade, the Gd loading procedure, detector commissioning, and the first neutron calibration measurements in SK-Gd.
TL;DR: In this paper , colloidal complexes were prepared from bovine lactoferrin (BLF) and tannic acid (TA) and then their ability to form and stabilize foams was characterized.
TL;DR: In this paper , through high-throughput stimulated Raman scattering imaging and single cell analysis, the authors found that cisplatin-resistant cells exhibit increased fatty acids (FA) uptake, accompanied by decreased glucose uptake and lipogenesis, indicating reprogramming from glucose to FA dependent anabolic and energy metabolism.
Abstract: Abstract Increased glycolysis is considered as a hallmark of cancer. Yet, cancer cell metabolic reprograming during therapeutic resistance development is under-studied. Here, through high-throughput stimulated Raman scattering imaging and single cell analysis, we find that cisplatin-resistant cells exhibit increased fatty acids (FA) uptake, accompanied by decreased glucose uptake and lipogenesis, indicating reprogramming from glucose to FA dependent anabolic and energy metabolism. A metabolic index incorporating glucose derived anabolism and FA uptake correlates linearly to the level of cisplatin resistance in ovarian cancer (OC) cell lines and primary cells. The increased FA uptake facilitates cancer cell survival under cisplatin-induced oxidative stress by enhancing beta-oxidation. Consequently, blocking beta-oxidation by a small molecule inhibitor combined with cisplatin or carboplatin synergistically suppresses OC proliferation in vitro and growth of patient-derived xenografts in vivo. Collectively, these findings support a rapid detection method of cisplatin-resistance at single cell level and a strategy for treating cisplatin-resistant tumors.
TL;DR: The authors performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries.
Abstract: Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
TL;DR: In this paper, the authors evaluated the relationship between diagnosed mental health conditions and current symptoms of depression and/or anxiety and suicidality in the past year and determined how these associations varied by race/ethnicity, gender, and sexual orientation.
TL;DR: In this article, an integrated TVP-VAR model was proposed to investigate the volatility spillover mechanisms among different financial markets as well as their respective roles in the global volatility transmission system, including Bitcoin, crude oil, gold, stocks, foreign exchange and natural gas market.
TL;DR: In this paper, the authors investigated the possibility that outdoor air nitrogen dioxide (NO2) and particulate matter with diameter ≤ 2.5μm (PM2.5) adversely affect hippocampal volume, through a meta-analysis.
TL;DR: In this article , the authors provide an overview of osteoarthritis imaging using a narrative review aimed at an audience of scientists, clinicians, students, industry employees, and others who are interested in OA but who do not necessarily focus on OA.
TL;DR: In this paper , the authors investigated the possibility that outdoor air nitrogen dioxide (NO2) and particulate matter with diameter ≤ 2.5 μm and ≤ 10 μm (PM10) adversely affect hippocampal volume, through a meta-analysis.
Abstract: Growing epidemiological evidence suggests that air pollution may increase the risk of cognitive decline and neurodegenerative disease. A hallmark of neurodegeneration and an important diagnostic biomarker is volume reduction of a key brain structure, the hippocampus. We aimed to investigate the possibility that outdoor air nitrogen dioxide (NO2) and particulate matter with diameter ≤2.5 μm (PM2.5) and ≤10 μm (PM10) adversely affect hippocampal volume, through a meta-analysis. We considered studies that assessed the relation between outdoor air pollution and hippocampal volume by structural magnetic resonance imaging in adults and children, searching in Pubmed and Scopus databases from inception through July 13, 2021. For inclusion, studies had to report the correlation coefficient along with its standard error or 95% confidence interval (CI) between air pollutant exposure and hippocampal volume, to use standard space for neuroimages, and to consider at least age, sex and intracranial volume as covariates or effect modifiers. We meta-analyzed the data with a random-effects model, considering separately adult and child populations. We retrieved four eligible studies in adults and two in children. In adults, the pooled summary β regression coefficients of the association of PM2.5, PM10 and NO2 with hippocampal volume showed respectively a stronger association (summary β -7.59, 95% CI -14.08 to -1.11), a weaker association (summary β -2.02, 95% CI -4.50 to 0.47), and no association (summary β -0.44, 95% CI -1.27 to 0.40). The two studies available for children, both carried out in preadolescents, did not show an association between PM2.5 and hippocampal volume. The inverse association between PM2.5 and hippocampal volume in adults appeared to be stronger at higher mean PM2.5 levels. Our results suggest that outdoor PM2.5 and less strongly PM10 could adversely affect hippocampal volume in adults, a phenomenon that may explain why air pollution has been related to memory loss, cognitive decline, and dementia.
01 Feb 2022
TL;DR: In this article , the authors examined the energy and climate impacts of existing and proposed datacenters, both quantitatively and in terms of stakeholder and public perceptions, and analyzed 40 solutions for ecofriendly design or green datacenter management across the entire lifecycle.
Abstract: Both policymakers and the technology industry need to do more to combat the ever-growing demand for data and its associated energy impacts. In this study, based on novel corporate data, expert interviews, focus groups with members of the public, extensive site visits across Greenland, Iceland and Norway and a literature review, we look at the energy and climate impacts of existing and proposed datacenters, both quantitatively and in terms of stakeholder and public perceptions. The paper examines datacenter management and sustainability practices in the Nordic region. It explores what community impacts occur, and how communities manage conflicting objectives. It investigates the technical and policy options that can make datacenters more sustainable and/or lower-carbon and it explores associated stakeholder and public views in the three countries. In exploring these themes, our study examines the shifting energy governance of datacenters, including patterns of electricity consumption and cooling but also circular economy operations and power densities. We also analyze a series of 40 solutions for eco-friendly design or green datacenter management across the entire lifecycle. We conclude with implications for energy and climate policy as well as future research.
TL;DR: In this article , the authors leveraged whole-exome imputation within the full UK Biobank cohort (n ∼ 500k) to extend such analyses to 3,475 rare variants curated from ClinVar and OMIM.
Abstract: Recent work has found increasing evidence of mitigated, incompletely penetrant phenotypes in heterozygous carriers of recessive Mendelian disease variants. We leveraged whole-exome imputation within the full UK Biobank cohort (n ∼ 500K) to extend such analyses to 3,475 rare variants curated from ClinVar and OMIM. Testing these variants for association with 58 quantitative traits yielded 102 significant associations involving variants previously implicated in 34 different diseases. Notable examples included a POR missense variant implicated in Antley-Bixler syndrome that associated with a 1.76 (SE 0.27) cm increase in height and an ABCA3 missense variant implicated in interstitial lung disease that associated with reduced FEV1/FVC ratio. Association analyses with 1,134 disease traits yielded five additional variant-disease associations. We also observed contrasting levels of recessiveness between two more-common, classical Mendelian diseases. Carriers of cystic fibrosis variants exhibited increased risk of several mitigated disease phenotypes, whereas carriers of spinal muscular atrophy alleles showed no evidence of altered phenotypes. Incomplete penetrance of cystic fibrosis carrier phenotypes did not appear to be mediated by common allelic variation on the functional haplotype. Our results show that many disease-associated recessive variants can produce mitigated phenotypes in heterozygous carriers and motivate further work exploring penetrance mechanisms. Recent work has found increasing evidence of mitigated, incompletely penetrant phenotypes in heterozygous carriers of recessive Mendelian disease variants. We leveraged whole-exome imputation within the full UK Biobank cohort (n ∼ 500K) to extend such analyses to 3,475 rare variants curated from ClinVar and OMIM. Testing these variants for association with 58 quantitative traits yielded 102 significant associations involving variants previously implicated in 34 different diseases. Notable examples included a POR missense variant implicated in Antley-Bixler syndrome that associated with a 1.76 (SE 0.27) cm increase in height and an ABCA3 missense variant implicated in interstitial lung disease that associated with reduced FEV1/FVC ratio. Association analyses with 1,134 disease traits yielded five additional variant-disease associations. We also observed contrasting levels of recessiveness between two more-common, classical Mendelian diseases. Carriers of cystic fibrosis variants exhibited increased risk of several mitigated disease phenotypes, whereas carriers of spinal muscular atrophy alleles showed no evidence of altered phenotypes. Incomplete penetrance of cystic fibrosis carrier phenotypes did not appear to be mediated by common allelic variation on the functional haplotype. Our results show that many disease-associated recessive variants can produce mitigated phenotypes in heterozygous carriers and motivate further work exploring penetrance mechanisms.