Application of Bayesian classification with singular value decomposition method in genome-wide association studies

To analyze multiple single-nucleotide polymorphisms simultaneously when the number of markers is much larger than the number of studied individuals, as is the situation we have in genome-wide association studies (GWAS), we developed the iterative Bayesian variable selection method and successfully applied it to the simulated rheumatoid arthritis data provided by the Genetic Analysis Workshop 15 (GAW15). One drawback for applying our iterative Bayesian variable selection method is the relatively long running time required for evaluation of GWAS data. To improve computing speed, we recently developed a Bayesian classification with singular value decomposition (BCSVD) method. We have applied the BCSVD method here to the rheumatoid arthritis data distributed by GAW16 Problem 1 and demonstrated that the BCSVD method works well for analyzing GWAS data

Heritability patterns in hand osteoarthritis: the role of osteophytes

Abstract Introduction The objective of the present study was to assess heritability of clinical and radiographic features of hand osteoarthritis (OA) in affected patients and their siblings. Methods A convenience sample of patients with clinical and radiographic hand OA and their siblings were evaluated by examination and radiography. Radiographs were scored for hand OA features by radiographic atlas. The heritability of hand OA phenotypes was assessed for clinical and radiographic measures based on anatomic locations and radiographic characteristics. Phenotypic data were transformed to reduce non-normality, if necessary. A variance components approach was used to calculate heritability. Results One hundred and thirty-six probands with hand OA and their sibling(s) were enrolled. By anatomic location, the highest heritability was seen with involvement of the first interphalangeal joint (h 2 = 0.63, P = 0.00004), the first carpometacarpal joint (h 2 = 0.38, P = 0.01), the distal interphalangeal joints (h 2 = 0.36, P = 0.02), and the proximal interphalangeal joints (h 2 = 0.30, P = 0.03) with osteophytes. The number and severity of joints with osteophyte involvement was heritable overall (h 2 = 0.38, P = 0.008 for number and h 2 = 0.35, P = 0.01 for severity) and for all interphalangeal joints (h 2 = 0.42, P = 0.004 and h 2 = 0.33, P = 0.02). The severity of carpometacarpal joint involvement was also heritable (h 2 = 0.53, P = 0.0006). Similar results were obtained when the analysis was limited to the Caucasian sample. Conclusions In a population with clinical and radiographic hand OA and their siblings, the presence of osteophytes was the most sensitive biomarker for hand OA heritability. Significant heritability was detected for anatomic phenotypes by joint location, severity of joint involvement with osteophytes as well as for overall number and degree of hand OA involvement. These findings are in agreement with the strong genetic predisposition for hand OA reported by others. The results support phenotyping based on severity of osteophytes and a joint-specific approach. More specific phenotypes may hold greater promise in the study of genetics in hand OA

Application of Bayesian regression with singular value decomposition method in association studies for sequence data

Genetic association studies usually involve a large number of single-nucleotide polymorphisms (SNPs) (k) and a relative small sample size (n), which produces the situation that k is much greater than n. Because conventional statistical approaches are unable to deal with multiple SNPs simultaneously when k is much greater than n, single-SNP association studies have been used to identify genes involved in a disease’s pathophysiology, which causes a multiple testing problem. To evaluate the contribution of multiple SNPs simultaneously to disease traits when k is much greater than n, we developed the Bayesian regression with singular value decomposition (BRSVD) method. The method reduces the dimension of the design matrix from k to n by applying singular value decomposition to the design matrix. We evaluated the model using a Markov chain Monte Carlo simulation with Gibbs sampler constructed from the posterior densities driven by conjugate prior densities. Permutation was incorporated to generate empirical p-values. We applied the BRSVD method to the sequence data provided by Genetic Analysis Workshop 17 and found that the BRSVD method is a practical method that can be used to analyze sequence data in comparison to the single-SNP association test and the penalized regression method

Chinese Expert Consensus on Critical Care Ultrasound Applications at COVID-19 Pandemic

The spread of new coronavirus (SARS-Cov-2) follows a different pattern than previous respiratory viruses, posing a serious public health risk worldwide. World Health Organization (WHO) named the disease as COVID-19 and declared it a pandemic. COVID-19 is characterized by highly contagious nature, rapid transmission, swift clinical course, profound worldwide impact, and high mortality among critically ill patients. Chest X-ray, computerized tomography (CT), and ultrasound are commonly used imaging modalities. Among them, ultrasound, due to its portability and non-invasiveness, can be easily moved to the bedside for examination at any time. In addition, with use of 4G or 5G networks, remote ultrasound consultation can also be performed, which allows ultrasound to be used in isolated medial areas. Besides, the contact surface of ultrasound probe with patients is small and easy to be disinfected. Therefore, ultrasound has gotten lots of positive feedbacks from the frontline healthcare workers, and it has played an indispensable role in the course of COVID-19 diagnosis and follow up

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Research on Market Competitiveness Assessment Methods of Smart Home Enterprises Under the Perspective of Long-Term User Experience

Since the 20th century, there has been a wave of digitalization in homes and businesses worldwide, and smart homes have gradually become a high-profile business sector. However, behind fierce competition in the digital home market, the importance of user experience for companies to enhance their competitiveness as a business model for providing services to home users is often overlooked. Combining the industry&#x2019;s basic theories and our own empirical research, this study expands the assessment perspective and assessment methods on the basis of the industry&#x2019;s existing assessment methods and constructs a comprehensive assessment system that is both innovative and practical - the Smart Home Product Competitiveness Index (PCI). The index constructs a three-in-one smart home product competitiveness index assessment system for brand power, product power, and marketing power from the perspective of long-term user experience. Twelve representative enterprises were selected from the five categories of camps, covering three demand levels, six typical scenarios, and 17 mainstream products. This study shows that Internet enterprises are characterized as all-round. Traditional home appliance manufacturers, Internet enterprises, and communication carriers must strengthen the construction of product power. The competitiveness assessment method for digital home enterprises from the perspective of long-term user experience proposed in this study is effective and can provide a reference for subsequent related studies