A bidirectional Mendelian randomization study supports causal effects of kidney function on blood pressure

Blood pressure and kidney function have a bidirectional relation. Hypertension has long been considered as a risk factor for kidney function decline. However, whether intensive blood pressure control could promote kidney health has been uncertain. The kidney is known to have a major role in affecting blood pressure through sodium extraction and regulating electrolyte balance. This bidirectional relation makes causal inference between these two traits difficult. Therefore, to examine the causal relations between these two traits, we performed two-sample Mendelian randomization analyses using summary statistics of large-scale genome-wide association studies. We selected genetic instruments more likely to be specific for kidney function using meta-analyses of complementary kidney function biomarkers (glomerular filtration rate estimated from serum creatinine [eGFRcr], and blood urea nitrogen from the CKDGen Consortium). Systolic and diastolic blood pressure summary statistics were from the International Consortium for Blood Pressure and UK Biobank. Significant evidence supported the causal effects of higher kidney function on lower blood pressure. Based on the mode-based Mendelian randomization method, the effect estimates for one standard deviation (SD) higher in log-transformed eGFRcr was -0.17 SD unit (95 % confidence interval: -0.09 to -0.24) in systolic blood pressure and -0.15 SD unit (95% confidence interval: -0.07 to -0.22) in diastolic blood pressure. In contrast, the causal effects of blood pressure on kidney function were not statistically significant. Thus, our results support causal effects of higher kidney function on lower blood pressure and suggest preventing kidney function decline can reduce the public health burden of hypertension

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores

STATISTICAL METHODS FOR ANALYSIS OF GENOME-WIDE ASSOCIATION STUDIES ACROSS MULTIPLE TRAITS

Pleiotropy is the phenomenon that one genetic variant has effects on multiple phenotypes. Genome-wide association studies found widespread pleiotropy across complex traits and diseases, which has transformed the interpretation of GWAS results and understanding of genetic architecture. The discovery of pleiotropy has provided major opportunities for novel statistical analysis of GWAS. In this thesis, I first describe a method to aggregate information across multiple traits to improve power of genetic association tests. Application of the method identified novel loci associated with blood lipids, psychiatric diseases and social science traits. Second, I describe a method for robust Mendelian randomization analysis using mixture models, in order to identify causal relationships between risk factors and diseases even when the instrumental variable assumptions are violated. Application of the method identified a protective effect of later menarche on the risk of breast cancer, and no causal effect of HDL cholesterol and triglycerides on the risk of coronary artery disease. In addition, I present a comprehensive evaluation of Mendelian randomization methods using realistic simulation studies informed by recent studies on heritability and genetic effect size distribution. Comparison of the methods in real data analysis to study the causal effect of blood and urine biomarkers on type 2 diabetes revealed major heterogeneity in estimated causal effects among some biomarkers. In conclusion, novel statistical methods for pleiotropic analysis have led to new insights into the genetics of complex traits and the causal role of risk factors in diseases

Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits.

Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed method to publicly available data for three groups of genetically related traits, lipids (N = 188,577), psychiatric diseases (Ncase = 33,332, Ncontrol = 27,888) and social science traits (N ranging between 161,460 to 298,420 across individual traits) increased the number of genome-wide significant loci by 12%, 200% and 50%, respectively, compared to those found by analysis of individual traits. Evidence of replication is present for many of these loci in subsequent larger studies for individual traits. HIPO can potentially be extended to high-dimensional phenotypes as a way of dimension reduction to maximize power for subsequent genetic association testing

Design of foreign object recognition and positioning system for sorting robot of coal mine belt conveyor

Machine vision has a certain theoretical basis in target detection and recognition for sorting robot of coal mine belt conveyor. But current target recognition of sorting robot of coal mine belt conveyor is mainly aimed at coal-gangue recognition. There are few kinds of research on the recognition of foreign object targets causing conveyor belt penetration and tearing, and also few kinds of research on the precise positioning of target foreign object. In order to solve the above problems, a foreign object recognition and positioning system based on machine vision for sorting robots of coal mine belt conveyor is designed. The system can recognize and position different types and shapes of foreign objects on the conveyor belt. The image information of the foreign objects on the conveyor belt in real-time is obtained by adopting binocular vision, and the image is preprocessed. Image information is enhanced based on the Canny operator. The gray stretching method is used to improve image edge information to highlight the edge features of foreign objects on coal mine belt conveyor. The morphological method is used to extract foreign object shape features, and establish foreign object image feature sample library. The image feature matching method is used to solve the existing area of foreign objects to realize the detection, classification and recognition of foreign objects. On the basis of the successful recognition of foreign object type, the region of interest (ROI) of the target foreign object is established based on the edge feature value of the target foreign object. The coordinate conversion relationship is built between the camera, conveyor belt and target foreign object. The fast multi-target centroid calculation method is used to obtain the centroid coordinate of the target foreign object, so as to realize the positioning of the target foreign object. The experimental result of the system prototype shows that the foreign object recognition rate of foreign object recognition and positioning system for sorting robot of coal mine belt conveyor is not affected by the size, material, color and other factors, the system can realize the image acquisition, process, feature extraction, recognition and positioning of the target foreign object of coal mine conveyor belt. The recognition rate is above 92.5%, and the average error of the target foreign object positioning is about 3%

Asymptomatic stones in the lacrimal canaliculus

Key Clinical Message Asymptomatic lacrimal canaliculus stones causing many stones without symptoms are rare. The patient recovered well within a week after dacryolith removal. This diagnosis is prevalent in this age group. However, asymptomatic nasolacrimal obstruction should be considered. Abstract Dacryoliths, also known as symptomatic stones, are frequently observed in the lacrimal drainage system. These stones manifest through symptoms such as conjunctivitis, discharge, and epiphora. Nevertheless, the occurrence of numerous stones in the lacrimal canaliculus, in the absence of apparent symptoms, is uncommon. In this study, we present a case with the presence of several stones within the inferior lacrimal canaliculus. A female patient, aged 74, appeared with bilateral senile cataracts and was scheduled for cataract surgery. During a standard ocular examination, it was observed that the tear meniscus height in the left eye had a greater magnitude compared with the right eye. Canaliculitis with dacryolith was verified using a series of diagnostic procedures, including physical inspection, fluorescent dye disappearance test, palpation, 50 Mhz ultrasound biomicroscope scan, and irrigation of the lacrimal canaliculi. Upon surgical investigation, the canaliculus obstruction was confirmed, characterized by the existence of many tiny dacryolith formations inside the inferior canalicular system. Following the surgical excision of the dacryoliths, the patient experienced a full remission within a week. While it is common for individuals in this age range to receive this diagnosis, it is important to consider silent nasolacrimal blockage as a potential alternative diagnosis. It is important to note that the presence of dacryoliths in the lacrimal drainage system might manifest independently of conjunctivitis. No discernible risk indicators were found in relation to the aforementioned patient

Accelerating thermokarst lake changes on the Qinghai–Tibetan Plateau

Abstract As significant evidence of ice-rich permafrost degradation due to climate warming, thermokarst lake was developing and undergoing substantial changes. Thermokarst lake was an essential ecosystem component, which significantly impacted the global carbon cycle, hydrology process and the stability of the Qinghai–Tibet Engineering Corridor. In this paper, based on Sentinel-2 (2021) and Landsat (1988–2020) images, thermokarst lakes within a 5000 m range along both sides of Qinghai–Tibet Highway were extracted to analyse the spatio-temporal variations. The results showed that the number and area of thermokarst lake in 2021 were 3965 and 4038.6 ha (1 ha = 10,000 m $$^{2}$$ 2 ), with an average size of 1.0186 ha. Small thermokarst lakes ( $$\,$$ > 10 ha) occupied for 44.92% of the whole lake area. In all sub-regions, the number of small lake far exceeds 75% of the total lake number in each sub-region. R1 sub-region (around Wudaoliang region) had the maximum number density of thermokarst lakes with 0.0071, and R6 sub-region (around Anduo region) had the minimum number density with 0.0032. Thermokarst lakes were mainly distributed within elevation range of 4300 m–5000 m a.s.l. (94.27% and 97.13% of the total number and size), on flat terrain with slopes less than 3 $$^\circ$$ ∘ (99.17% and 98.47% of the total number and surface) and in the north, south, and southeast aspects (51.98% and 50.00% of the total number and area). Thermokarst lakes were significantly developed in warm permafrost region with mean annual ground temperature (MAGT) > − 1.5  $$^\circ$$ ∘ C, accounting for 47.39% and 54.38% of the total count and coverage, respectively. From 1988 to 2020, in spite of shrinkage or even drain of small portion of thermokarst lake, there was a general expansion trend of thermokarst lake with increase in number of 195 (8.58%) and area of 1160.19 ha (41.36%), which decreased during 1988–1995 (− 702 each year and − 706.27 ha/yr) and then increased during 1995–2020 (184.96–702 each year and 360.82 ha/yr). This significant expansion was attributed to ground ice melting as rising air temperature at a rate of 0.03–0.04  $$^\circ$$ ∘ C/yr. Followed by the increasing precipitation (1.76–3.07 mm/yr) that accelerated the injection of water into lake

Single-cell sequencing reveals lineage-specific dynamic genetic regulation of gene expression during human cardiomyocyte differentiation

Dynamic and temporally specific gene regulatory changes may underlie unexplained genetic associations with complex disease. During a dynamic process such as cellular differentiation, the overall cell type composition of a tissue (or an in vitro culture) and the gene regulatory profile of each cell can both experience significant changes over time. To identify these dynamic effects in high resolution, we collected single-cell RNA-sequencing data over a differentiation time course from induced pluripotent stem cells to cardiomyocytes, sampled at 7 unique time points in 19 human cell lines. We employed a flexible approach to map dynamic eQTLs whose effects vary significantly over the course of bifurcating differentiation trajectories, including many whose effects are specific to one of these two lineages. Our study design allowed us to distinguish true dynamic eQTLs affecting a specific cell lineage from expression changes driven by potentially non-genetic differences between cell lines such as cell composition. Additionally, we used the cell type profiles learned from single-cell data to deconvolve and re-analyze data from matched bulk RNA-seq samples. Using this approach, we were able to identify a large number of novel dynamic eQTLs in single cell data while also attributing dynamic effects in bulk to a particular lineage. Overall, we found that using single cell data to uncover dynamic eQTLs can provide new insight into the gene regulatory changes that occur among heterogeneous cell types during cardiomyocyte differentiation.</p

Identifying primary site of lung-limited Cancer of unknown primary based on relative gene expression orderings

Abstract Background Precise diagnosis of the tissue origin for metastatic cancer of unknown primary (CUP) is essential for deciding the treatment scheme to improve patients’ prognoses, since the treatment for the metastases is the same as their primary counterparts. The purpose of this study is to identify a robust gene signature that can predict the origin for CUPs. Methods The within-sample relative gene expression orderings (REOs) of gene pairs within individual samples, which are insensitive to experimental batch effects and data normalizations, were exploited for identifying the prediction signature. Results Using gene expression profiles of the lung-limited metastatic colorectal cancer (LmCRC), we firstly showed that the within-sample REOs in lung metastases of colorectal cancer (CRC) samples were concordant with the REOs in primary CRC samples rather than with the REOs in primary lung cancer. Based on this phenomenon, we selected five gene pairs with consistent REOs in 498 primary CRC and reversely consistent REOs in 509 lung cancer samples, which were used as a signature for predicting primary sites of metastatic CRC based on the majority voting rule. Applying the signature to 654 primary CRC and 204 primary lung cancer samples collected from multiple datasets, the prediction accuracy reached 99.36%. This signature was also applied to 24 LmCRC samples collected from three datasets produced by different laboratories and the accuracy reached 100%, suggesting that the within-sample REOs in the primary site could reveal the original tissue of metastatic cancers. Conclusions The result demonstrated that the signature based on within-sample REOs of five gene pairs could exactly and robustly identify the primary sites of CUPs