Polygenic scores (PGS) summarize the genetic contribution of a person's genotype to a disease or phenotype. They can be used to group participants into different risk categories for diseases, and are also used as covariates in epidemiological analyses. A number of possible ways of calculating PGS have been proposed, and recently there is much interest in methods that incorporate information available in published summary statistics. As there is no inherent information on linkage disequilibrium (LD) in summary statistics, a pertinent question is how we can use LD information available elsewhere to supplement such analyses. To answer this question, we propose a method for constructing PGS using summary statistics and a reference panel in a penalized regression framework, which we call lassosum. We also propose a general method for choosing the value of the tuning parameter in the absence of validation data. In our simulations, we showed that pseudovalidation often resulted in prediction accuracy that is comparable to using a dataset with validation phenotype and was clearly superior to the conservative option of setting the tuning parameter of lassosum to its lowest value. We also showed that lassosum achieved better prediction accuracy than simple clumping and P‐value thresholding in almost all scenarios. It was also substantially faster and more accurate than the recently proposed LDpred.

Interaction between tumor cells and immune cells in the tumor microenvironment is important in cancer development. Immune cells interact with the tumor cells to shape this process. Here, we use single-cell RNA sequencing analysis to delineate the immune landscape and tumor heterogeneity in a cohort of patients with HBV-associated human hepatocellular carcinoma (HCC). We found that tumor-associated macrophages suppress tumor T cell infiltration and TIGIT-NECTIN2 interaction regulates the immunosuppressive environment. The cell state transition of immune cells towards a more immunosuppressive and exhaustive status exemplifies the overall cancer-promoting immunocellular landscape. Furthermore, the heterogeneity of global molecular profiles reveals co-existence of intra-tumoral and inter-tumoral heterogeneity, but is more apparent in the latter. This analysis of the immunosuppressive landscape and intercellular interactions provides mechanistic information for the design of efficacious immune-oncology treatments in hepatocellular carcinoma.

Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underlie the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertake a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture are identified. In addition to the human leukocyte antigen (HLA) region, nine disease loci show clear ancestral differences and implicate antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores perform significantly better when trained on ancestry-matched data sets. These analyses help to reveal the genetic basis for disparities in SLE among ancestral groups.

Hirschsprung's disease (HSCR), or aganglionic megacolon, is a congenital disorder characterized by the absence of enteric ganglia in variable portions of the distal intestine. RET is a well-established susceptibility locus, although existing evidence strongly suggests additional loci contributing to sporadic HSCR. To identify these additional genetic loci, we carried out a genome-wide association study using the Affymetrix 500K marker set. We successfully genotyped 293,836 SNPs in 181 Chinese subjects with sporadic HSCR and 346 ethnically matched control subjects. The SNPs most associated with HSCR were genotyped in an independent set of 190 HSCR and 510 control subjects. Aside from SNPs in RET , the strongest overall associations in plausible candidate genes were found for 2 SNPs located in intron 1 of the neuregulin1 gene ( NRG1 ) on 8p12, with rs16879552 and rs7835688 yielding odds ratios of 1.68 [CI _95% :(1.40, 2.00), P = 1.80 × 10 ⁻⁸ ] and 1.98 [CI _95% :(1.59, 2.47), P = 1.12 × 10 ⁻⁹ ], respectively, for the heterozygous risk genotypes under an additive model. There was also a significant interaction between RET and NRG1 ( P = 0.0095), increasing the odds ratio 2.3-fold to 19.53 for the RET rs2435357 risk genotype (TT) in the presence of the NRG1 rs7835688 heterozygote, indicating that NRG1 is a modifier of HSRC penetrance. Our highly significant association findings are backed-up by the important role of NRG1 as regulator of the development of the enteric ganglia precursors. The identification of NRG1 as an additional HSCR susceptibility locus not only opens unique fields of investigation into the mechanisms underlying the HSCR pathology, but also the mechanisms by which a discrete number of loci interact with each other to cause disease.