Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) ...from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10
), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin βE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.
The process of platelet production has so far been understood to be a 2-stage process: megakaryocyte maturation from hematopoietic stem cells followed by proplatelet formation, with each phase ...regulating the peripheral blood platelet count. Proplatelet formation releases into the bloodstream beads-on-a-string preplatelets, which undergo fission into mature platelets. For the first time, we show that preplatelet maturation is a third, tightly regulated, critical process akin to cytokinesis that regulates platelet count. We show that deficiency in cytokine receptor-like factor 3 (CRLF3) in mice leads to an isolated and sustained 25% to 48% reduction in the platelet count without any effect on other blood cell lineages. We show that Crlf3−/− preplatelets have increased microtubule stability, possibly because of increased microtubule glutamylation via the interaction of CRLF3 with key members of the Hippo pathway. Using a mouse model of JAK2 V617F essential thrombocythemia, we show that a lack of CRLF3 leads to long-term lineage-specific normalization of the platelet count. We thereby postulate that targeting CRLF3 has therapeutic potential for treatment of thrombocythemia.
•CRLF3 deficiency causes an isolated and sustained reduction in platelet count in mice.•CRLF3 is a potential therapeutic target for thrombocythemia.
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In this study, we leveraged the combined evidence of rare coding variants and common alleles to identify therapeutic targets for osteoporosis. We undertook a large-scale multiancestry exome-wide ...association study for estimated bone mineral density, which showed that the burden of rare coding alleles in 19 genes was associated with estimated bone mineral density (P < 3.6 × 10
). These genes were highly enriched for a set of known causal genes for osteoporosis (65-fold; P = 2.5 × 10
). Exome-wide significant genes had 96-fold increased odds of being the top ranked effector gene at a given GWAS locus (P = 1.8 × 10
). By integrating proteomics Mendelian randomization evidence, we prioritized CD109 (cluster of differentiation 109) as a gene for which heterozygous loss of function is associated with higher bone density. CRISPR-Cas9 editing of CD109 in SaOS-2 osteoblast-like cell lines showed that partial CD109 knockdown led to increased mineralization. This study demonstrates that the convergence of common and rare variants, proteomics and CRISPR can highlight new bone biology to guide therapeutic development.
Cardiovascular diseases are culpable for the majority of mortalities the world over, hence the significance of advances in preventive medicine and imaging. Cardiovascular imaging constitutes the ...cornerstone of not only early but also precise diagnoses. Indeed, advanced imaging enables cardiologists to make efficacious management plans for various heart conditions. The present article discusses essential innovations in cardiovascular imaging.
The results of the multiple logistic regression showed that risk of hospital LOS > 6 days in unsuccessful percutaneous coronary intervention (PCI) was 33.2 versus 66.8 in successful PCI (P = 0/001). ......the risk of hospital LOS > 6 days in subjects who had post-procedure complication, problems at admission, and primary comorbidities was 9.13 (7.22-11.53)-fold, 4.09 (2.86-5.85)-fold, and 1.75 (1.35-2.27)-fold more than those who had not, respectively CONCLUSION: Reduction in the number of inpatient days increases hospital profit with more efficient bed management. ...determination of die factors associated widi reducing hospitalization period is vital. ...by controlling the factors associated with the long-term admission of patients after PPCI, the length of hospitalization and subsequently contributing costs, manpower, and time in the health care system can be reduced. According to the age group classification, 25.7% of subjects (n = 144) were in the group of less than 50 years old, and 29.1% (n = 163), 28.5% (n = 160), and 16.8% (n = 94) of subjects were in the age groups of 51 to 60, 61 to 70, and above 70 years, respectively. 74.2% (n = 416) of subjects were men and 25.8% (n = 145) were women.
Melanoma is the most common form of skin cancer, and skin disease image segmentation plays a vital role in automated diagnosis of skin cancer. A primary challenge of image segmentation and other ...automated object recognition techniques is the large amount of redundant input information which often obfuscates critical input features. In the context of dermatoscopy lesion segmentation we show that unsupervised clustering algorithms applied to input images can reduce local image redundancy and result in dramatic improvements in segmentation performance. Our work proposes a skin disease image segmentation algorithm combining an unsupervised simple linear iterative cluster algorithm (SLIC), and the supervised deep learning U-Net model. The unsupervised SLIC method can detect the fine structure of skin damage highlighting critical features that improve segmentation performance of the supervised U-Net model. Both the superpixel dermoscope image and original image are used as input information for the U-Net training deep learning model. Finally, a fully-connected conditional random field (CRF) is used for image post-processing. This algorithm achieves an Intersection Over Unit(IOU) coefficient reaching 83%, dice coefficient 90%, sensitivity 90%, improved by 10%, 7% and 4% respectively in comparison with the results of the classic U-Net, showing that this approach improves the performance of network image segmentation.
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