38 research outputs found

    Understanding the genetic complexity of puberty timing across the allele frequency spectrum

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    Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

    Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

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    Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution

    Opportunities and Perils of Data Science

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    Presented in-person and online via Bluejeans Events on October 15, 2021 att 2:00 p.m.Dr. Alfred Z. Spector was most recently CTO and Head of Engineering at Two Sigma, a firm dedicated to algorithmic approaches to a wide collection of financial optimization problems. His career has led him from innovation in large scale, networked computing systems to broad engineering and research leadership. Most recently, he has been writing a book on Data Science, which will be published in early 2022. Spector lectures widely on the growing importance of computer science across all disciplines based on the evocative phrase, CS+X. More recently, he has written and lectured on the societal implications of data science -- both the great benefits and the unintended consequences.Runtime: 64:39 minutesData science has provided unprecedented opportunities to learn new insights and to predict, recommend, cluster, classify, transform, and optimize. Catalyzed by large-scale, networked computer systems, vast availability of data, and machine learning algorithms, data science has been extraordinarily impactful to-date, and it holds great promise in all disciplines. However, no new technology arrives without complications, and we have recently seen both the press and various political circles illustrating real, potential, and fictional implications of the field. This presentation aims to balance the opportunities provided by data science against the many challenges that have ensued. At its core, the talk proposes a rubric that practitioners can apply to tease out data science’s complexities and also maps out seven categories of data sciences challenges, ranging from engineering to ethics. The talk is illustrated with examples from many applications, and it concludes with some suggested ways to address the downsides of the field

    Performing remote operations efficiently on a local computer network

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    An algorithm for replicated directories

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    An algorithm for replicated directories

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    Computer Science Departmen

    Synchronizing shared abstract types

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    Computer Science Departmen
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