Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1 , but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5 . It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be fully recovered from whole-genome sequence (WGS) data on 21,620 unrelated individuals of European ancestry. We assigned 47.1 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned variation accordingly. The estimated heritability was 0.79 (SE 0.09) for height and 0.40 (SE 0.09) for BMI, consistent with pedigree estimates. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein altering variants, consistent with negative selection thereon. Cumulatively variants in the MAF range of 0.0001 to 0.1 explained 0.54 (SE 0.05) and 0.51 (SE 0.11) of heritability for height and BMI, respectively. Our results imply that the still missing heritability of complex traits and disease is accounted for by rare variants, in particular those in regions of low LD.

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large ( n = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in Admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study (GWAS) data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide binding groove, explaining 12.9% of trait variance.

Steroids are frequently used for postoperative pain relief without definite evidence. This study was conducted to assess the pain management effect of the addition of steroids to a multimodal cocktail periarticular injection (MCPI) in patients undergoing knee arthroplasty and evaluate their safety. Pubmed, Embase, and Cochrane Library were searched through April, 2018. A total of 918 patients from ten randomized controlled trials (RCTs) were ultimately included. Compared with placebo groups, steroids application could effectively relieve pain on postoperative day (POD)1; decrease C-Reactive protein (CRP) level on POD3; improve range of motion (ROM) in postoperative 5 days; reduce morphine consumption, achieve earlier straight leg raising (SLR), and shorten the length of stay (LOS) in hospital. With regards to adverse effects, it did not increase the risk of postoperative infection, postoperative nausea and vomiting (PONV), or other complications. However, no significant difference in pain relief, ROM, or increased Knee Society Knee Function Scores were found during long-term follow up. Overall, this meta-analysis ensured the efficiency and safety of steroids with MCPI in knee arthroplasty patients during the early postoperative period.

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