Biology subjects

Ni, J.-J.

Publications and source records attributed to Ni, J.-J..

2 recordsLinked to original sources

bioRxiv2021

Efficient identification of trait-associated loss-of-function variants in the UK Biobank cohort by exome-sequencing based genotype imputation

The large-scale open access whole-exome sequencing (WES) data of the UK Biobank ~200,000 participants is accelerating a new wave of genetic association studies aiming to identify rare and functional loss-of-function (LoF) variants associated with a broad range of complex traits and diseases, however the community is in short of stringent replication of new associations. In this study, we proposed to merge the WES genotypes and the genome-wide genotyping (GWAS) genotypes of 167,000 UKB Caucasian participants into a combined reference panel, and then to impute 241,911 UKB Caucasian participants who had the GWAS genotypes only. We then proposed to use the imputed data to replicate association identified in the discovery WES sample. Using a leave-100-out imputation strategy in the reference panel, we showed that average imputation accuracy measure r2 is modest to high at LoF variants of all minor allele frequency (MAF) intervals including ultra-rare ones: 0.942 at MAF interval [1%, 50%], 0.807 at [0.1%, 1.0%), 0.805 at [0.01%, 0.1%), 0.664 at [0.001%, 0.01%) and 0.410 at (0, 0.001%). As applications, we studied single variant level and gene level associations of LoF variants with estimated heel BMD (eBMD) and 4 lipid traits: high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), triglycerides (TG) and total cholesterol (TC). In addition to replicating dozens of previously reported genes such as MEPE for eBMD and PCSK9 for more than one lipid trait, the results also identified 2 novel gene-level associations: PLIN1 (cumulative MAF=0.10%, discovery BETA=0.38, P=1.20x10-13; replication BETA=0.25, P=1.03x10-6) and ANGPTL3 (cumulative MAF=0.10%, discovery BETA=-0.36, P=4.70x10-11; replication BETA=-0.30, P=6.60x10-11) for HDL-C, as well as one novel single variant level association (11:14843853:C:T, MAF=0.11%, discovery BETA=-0.31, P=2.70x10-9; replication BETA=-0.31, P=8.80x10-14, PDE3B) for TG. Our results highlighted the strength of WES based genotype imputation as well as provided useful imputed data within the UKB cohort.

genetics↗

bioRxiv2020

Mendelian randomization analysis revealed causal effects from gut microbiota to abdominal obesity

Although recent studies have revealed the association between the gut microbiota and obesity, the causality remains elusive. We performed a Mendelian Randomization (MR) analysis to determine whether there is a causal relationship between gut microbiota and abdominal obesity. We used a two-sample MR approach to assess the causal effect from gut microbiota to obesity based on genome-wide association studies (GWAS) summary statistics. The GWAS summary statistics of gut microbiota obtained from UK-twins cohort (N=1,126) were used as discovery sample exposure, and the GWAS summary statistics from the Genetic Environmental Microbial (GEM) project (N=1,098) were used as replication sample exposure. Trunk fat mass (TFM) summary statistics from the UK Biobank (UKB) cohort (N=330,762) were used as outcome. Bacteria were grouped into taxa features at family level. A total of 16 families were analyzed in the discovery sample. Family Barnesiellaceae was associated with TFM at the nominal significance level (b=-3.81x10-4, P=1.96x10-3). The causal association was successfully replicated in the replication sample (b=-7.34x10-3, P =2.77x10-2). Our findings provided evidence of causal relationship from microbiota to fat development, and may be helpful in selecting potential causal bacteria for manipulating candidate gut microbiota to therapy obesity. IMPORTANCEObesity, as a global public health problem, is one of the most important risk factors contributing to the overall global burden of disease, and is associated with an increased risk of cardiovascular disease, type 2 diabetes, and certain cancers. Recent studies have shown that gut microbiota is closely related to the development of obesity, but the causal relationship is unclear. Therefore, it is necessary to identify the causality between gut microbiota and obesity. The significance of our research is in identifying the causal relationship from specific bacteria to fat development, which will provide the new insights into the microbiota mediated the fat development mechanism.

genomics↗