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Polygenic risk scores (PRS) have shown promise in predicting human complex traits and diseases. Here, we present PRS-CS, a polygenic prediction method that infers posterior effect sizes of single nucleotide polymorphisms (SNPs) using genome-wide association summary statistics and an external linkage disequilibrium (LD) reference panel. PRS-CS utilizes a high-dimensional Bayesian regression framework, and is distinct from previous work by placing a continuous shrinkage (CS) prior on SNP effect sizes, which is robust to varying genetic architectures, provides substantial computational advantages, and enables multivariate modeling of local LD patterns. Simulation studies using data from the UK Biobank show that PRS-CS outperforms existing methods across a wide range of genetic architectures, especially when the training sample size is large. We apply PRS-CS to predict six common complex diseases and six quantitative traits in the Partners HealthCare Biobank, and further demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods. Polygenic risk scores (PRS) have the potential to predict complex diseases and traits from genetic data. Here, Ge et al. develop PRS-CS which uses a Bayesian regression framework, continuous shrinkage (CS) priors and an external LD reference panel for polygenic prediction of binary and quantitative traits from GWAS summary statistics.

Linking human behavior to resting-state brain function is a central question in systems neuroscience. In particular, the functional timescales at which different types of behavioral factors are encoded remain largely unexplored. The behavioral counterparts of static functional connectivity (FC), at the resolution of several minutes, have been studied but behavioral correlates of dynamic measures of FC at the resolution of a few seconds remain unclear. Here, using resting-state fMRI and 58 phenotypic measures from the Human Connectome Project, we find that dynamic FC captures task-based phenotypes (e.g., processing speed or fluid intelligence scores), whereas self-reported measures (e.g., loneliness or life satisfaction) are equally well explained by static and dynamic FC. Furthermore, behaviorally relevant dynamic FC emerges from the interconnections across all resting-state networks, rather than within or between pairs of networks. Our findings shed new light on the timescales of cognitive processes involved in distinct facets of behavior. An individual’s pattern of resting state brain connectivity, as measured with fMRI, has been shown to predict cognitive and behavioral traits. Here, the authors show that different traits are predicted by different time-scales of resting state activity (dynamic vs. static).

High-entropy metal-organic frameworks (HE-MOFs) hold promise as versatile materials, yet current rare examples are confined to low-valence elements in the fourth period, constraining their design and optimization for diverse applications. Here, a novel high-entropy, defect-rich and small-sized (32 nm) UiO-66 (ZrHfCeSnTi HE-UiO-66) has been synthesized for the first time, leveraging increased configurational entropy to achieve high tolerance to doping with diverse metal ions. The lattice distortion of HE-UiO-66 induces high exposure of metal nodes to create coordination unsaturated metal sites with a concentration of 322.4 μmol/g, which increases the abundance of Lewis acid-base sites, thereby achieving a significant improvement in the performance of the catalytic transfer hydrogenation (CTH) reaction. Systematic investigation manifests that the special electronic structure of HE-UiO-66 enhances the interaction and bonding with substrate molecules and reduces the energy barrier of the hydrogen transfer process. Our approach offers a new strategy for constructing coordination unsaturated metal sites in MOFs. High-entropy metal-organic frameworks offer significant potential as versatile materials, but existing examples are largely limited to low-valence elements in the fourth period, restricting their design and optimization for various applications. Here, a novel high-entropy, defect-rich, and small-sized UiO-66 framework has been synthesized to enhance catalytic transfer hydrogenation.

Nitrogen (N) is one of the most required mineral elements for plant growth, and potassium (K) plays a vital role in nitrogen metabolism, both elements being widely applied as fertilizers in agricultural production. However, the exact relationship between K and nitrogen use efficiency (NUE) remains unclear. Apple dwarf rootstock seedlings (M9T337) were used to study the impacts of different K levels on plant growth, nitrogen metabolism, and carbon (C) assimilation in water culture experiments for 2 years. The results showed that both deficiency and excess K inhibited the growth and root development of M9T337 seedlings. When the K supply concentration was 0 mM and 12 mM, the biomass of each organ, root-shoot ratio, root activity and NO3– ion flow rate decreased significantly, net photosynthetic rate ( P n) and photochemical efficiency ( F v/ F m) being lower. Meanwhile, seedlings treated with 6 mM K+ had higher N and C metabolizing enzyme activities and higher nitrate transporter gene expression levels ( NRT1.1 ; NRT2.1 ). 13C and 15N labeling results showed that deficiency and excess K could not only reduce 15N absorption and 13C assimilation accumulation of M9T337 seedlings, but also reduced the 15N distribution ratio in leaves and 13C distribution ratio in roots. These results suggest that appropriate K supply (6 mM) was optimal as it enhanced photoassimilate transport from leaves to roots and increased NUE by influencing photosynthesis, C and N metabolizing enzyme activities, nitrate assimilation gene activities, and nitrate transport.

Outlier removal is a fundamental data processing task to ensure the quality of scanned point cloud data (PCD), which is becoming increasing important in industrial applications and reverse engineering. Acquired scanned PCD is usually noisy, sparse and temporarily incoherent. Thus the processing of scanned data is typically an ill-posed problem. In the paper, we present a simple and effective method based on two geometrical characteristics constraints to trim the noisy points. One of the geometrical characteristics is the local density information and another is the deviation from the local fitting plane. The local density based method provides a preprocessing step, which could remove those sparse outlier and isolated outlier. The non-isolated outlier removal in this paper depends on a local projection method, which placing those points onto objects. There is no doubt that the deviation of any point from the local fitting plane should be a criterion to reduce the noisy points. The experimental results demonstrate the ability to remove the noisy point from various man-made objects consisting of complex outlier.

Inhibitory interneurons orchestrate information flow across the cortex and are implicated in psychiatric illness. Although interneuron classes have unique functional properties and spatial distributions, the influence of interneuron subtypes on brain function, cortical specialization, and illness risk remains elusive. Here, we demonstrate stereotyped negative correlation of somatostatin and parvalbumin transcripts within human and non-human primates. Cortical distributions of somatostatin and parvalbumin cell gene markers are strongly coupled to regional differences in functional MRI variability. In the general population ( n  = 9,713), parvalbumin-linked genes account for an enriched proportion of heritable variance in in-vivo functional MRI signal amplitude. Single-marker and polygenic cell deconvolution establish that this relationship is spatially dependent, following the topography of parvalbumin expression in post-mortem brain tissue. Finally, schizophrenia genetic risk is enriched among interneuron-linked genes and predicts cortical signal amplitude in parvalbumin-biased regions. These data indicate that the molecular-genetic basis of brain function is shaped by interneuron-related transcripts and may capture individual differences in schizophrenia risk. Interneuron subtypes have distinct properties and spatial distributions. Here, the authors show that the molecular-genetic basis of cortical resting-state brain function is shaped by distributions of interneuron-related transcripts and may capture individual differences in schizophrenia risk.

Humans survive and thrive through social exchange. Yet, social dependency also comes at a cost. Perceived social isolation, or loneliness, affects physical and mental health, cognitive performance, overall life expectancy, and increases vulnerability to Alzheimer’s disease-related dementias. Despite severe consequences on behavior and health, the neural basis of loneliness remains elusive. Using the UK Biobank population imaging-genetics cohort ( n  = ~40,000, aged 40–69 years when recruited, mean age = 54.9), we test for signatures of loneliness in grey matter morphology, intrinsic functional coupling, and fiber tract microstructure. The loneliness-linked neurobiological profiles converge on a collection of brain regions known as the ‘default network’. This higher associative network shows more consistent loneliness associations in grey matter volume than other cortical brain networks. Lonely individuals display stronger functional communication in the default network, and greater microstructural integrity of its fornix pathway. The findings fit with the possibility that the up-regulation of these neural circuits supports mentalizing, reminiscence and imagination to fill the social void. Here, using pattern-learning analyses of structural, functional, and diffusion brain scans in ~40,000 UK Biobank participants, the authors provide population-scale evidence that the default network is associated with perceived social isolation.

Vitamin D has been associated with a variety of human complex traits and diseases in observational studies, but a causal relationship remains unclear. To examine a putative causal effect of vitamin D across phenotypic domains and disease categories, we conducted Mendelian randomization (MR) analyses using genetic instruments associated with circulating 25-hydroxyvitamin D [25(OH)D] concentrations. We leveraged genome-wide significant 25(OH)D-associated SNPs (N = 138) from a meta-analysis combining a vitamin D GWAS conducted in 401,460 white British UK Biobank (UKBB) participants and an independent vitamin D GWAS including 42,274 samples of European ancestry, and examined 190 large-scale health-related GWAS spanning a broad spectrum of complex traits, diseases and biomarkers. We applied multiple MR methods to estimate the causal effect of vitamin D while testing and controlling for potential biases from horizontal pleiotropy. Consistent with previous findings, genetically predicted increased 25(OH)D levels significantly decreased the risk of multiple sclerosis (OR = 0.824; 95% CI 0.689–0.986). The protective effect estimate was consistent across different MR methods and four different multiple sclerosis GWAS with varying sample sizes and genotyping platforms. On the contrary, we found limited evidence in support of a causal effect of 25(OH)D on anthropometric traits, obesity, cognitive function, sleep behavior, breast and prostate cancer, and autoimmune, cardiovascular, metabolic, neurological and psychiatric traits and diseases, and blood biomarkers. Our results may inform ongoing and future randomized clinical trials of vitamin D supplementation.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

The formation of boronate complexes through the coordination of alkoxide salts with organoborons serves as key intermediates in transition-metal-catalyzed coupling reactions. These complexes typically undergo classical transmetallation followed by reductive elimination to form C–C and C–X bonds. However, 1,2-oxygen migration in such boronate complexes remain underdeveloped, particularly in asymmetric catalysis, likely due to competing transmetallation pathways. Successfully achieving this migration potentially establish a fundamentally distinct reaction step, thereby significantly broadening the scope of transition-metal-catalyzed coupling reactions. In this study, we develope an iridium-catalyzed asymmetric alkylation that enables the stereoselective construction of cis -cyclobutanes. Our strategy employs the high ring strain of bicyclo[1.1.0]butane (BCB)-derived boronate complexes to induce 1,2-alkoxy migration. Mechanistic investigations reveal that 1,2-alkoxy migration proceeds stepwise, beginning with C–C bond formation, followed by a distinctive C–B bond rotation and subsequent 1,2-oxygen migration. Notably, exocyclic C–B rotation, which is outcompeted by 1,2-carbon migration in prior studies, can occur in this system because the competing 1,2-oxygen migration has a higher energy barrier. These findings provide crucial insights into the origin of stereoselectivity and the rate-determining step of this reaction. The formation of alkoxyl boronate complexes in cross-coupling reactions typically undergo classical transmetallation followed by reductive elimination to form C–C and C–X bonds. Here, the authors report an iridium-catalyzed asymmetric alkylation that enables the stereoselective construction of cis -cyclobutanes, employing the high ring strain of bicyclo[1.1.0]butane-derived boronate complexes to induce 1,2-alkoxy migration.