Biology subjects

Willer, C.

Publications and source records attributed to Willer, C..

5 recordsLinked to original sources

bioRxiv2021

Identification of ACE2 modifiers by CRISPR screening

SARS-CoV-2 infection is initiated by binding of the viral spike protein to its receptor, ACE2, on the surface of host cells. ACE2 expression is heterogeneous both in vivo and in immortalized cell lines, but the molecular pathways that govern ACE2 expression remain unclear. We now report high-throughput CRISPR screens for functional modifiers of ACE2 surface abundance. We identified 35 genes whose disruption was associated with a change in the surface abundance of ACE2 in HuH7 cells. Enriched among these ACE2 regulators were established transcription factors, epigenetic regulators, and functional networks. We further characterized individual cell lines with disruption of SMAD4, EP300, PIAS1, or BAMBI and found these genes to regulate ACE2 at the mRNA level and to influence cellular susceptibility to SARS-CoV-2 infection. Collectively, our findings clarify the host factors involved in SARS-CoV-2 entry and suggest potential targets for therapeutic development.

genomics↗

bioRxiv2019

Mendelian Randomization Analysis Dissects the Relationship between NAFLD, T2D, and Obesity and Provides Implications to Precision Medicine

BackgroundNon-alcoholic fatty liver disease (NAFLD) is epidemiologically correlated with both type 2 diabetes (T2D) and obesity. However, the causal inter-relationships among the three diseases have not been completely investigated.\n\nAimWe aim to explore the causal relationships among the three diseases.\n\nDesign and methodsWe performed a genome-wide association study (GWAS) on fatty liver disease in [~]400,000 UK BioBank samples. Using this data as well as the largest-to-date publicly available summary-level GWAS data, we performed a two-sample bidirectional Mendelian Randomization (MR) analysis. This analysis tested the causal inter-relationship between NAFLD, T2D, and obesity, as well as the association between genetically driven NAFLD (with two well-established SNPs at the PNPLA3 and TM6SF2 loci) and glycemic and lipidemic traits, respectively. Transgenic mice expressing the human PNPLA3 I148I (TghPNPLA3-I148I) and PNPLA3 I148M (TghPNPLA3-I148M) isoforms were used to further validate the causal effects.\n\nResultsWe found that genetically instrumented hepatic steatosis significantly increased the risk for T2D (OR=1.3, 95% CI: [1.2, 1.4], p=8.3e-14) but not the intermediate glycemic phenotypes at the Bonferroni-adjusted level of significance (p<0.002). There was a moderate, but significant causal association between genetically driven hepatic steatosis and decreased risk for BMI ({beta}=- 0.027 SD, 95%CI: [-0.043, -0.01], p=1.3e-4), but an increased risk for WHRadjBMI (Waist-Hip Ratio adjusted for BMI) ({beta}=0.039 SD, 95%CI: [0.023, 0.054], p=8.2e-7), as well as a decreased level for total cholesterol ({beta}=-0.084 SD, 95%CI [-0.13, -0.036], p=6.8e-4), but not triglycerides ({beta}=0.02 SD, 95%CI [-0.023, 0.062], p=0.36). The reverse MR analyses suggested that genetically driven T2D (OR=1.1, 95% CI: [1.0, 1.2], p=1.7e-3), BMI (OR=2.3, 95% CI: [2.0, 2.7], p=1.4e-25) and WHRadjBMI (OR=1.5, 95% CI: [1.3, 1.8], p=1.1e-6) causally increase the NAFLD risk. In the animal study, as compared to the TghPNPLA3-I148I controls, the TghPNPLA3-I148M mice developed higher fasting glucose level and reduced glucose clearance. Meanwhile, the TghPNPLA3-I148M mice demonstrated a reduced body weight, increased central to peripheral fat ratio, decreased circulating total cholesterol as compared to the TghPNPLA3-I148I controls.\n\nConclusionThis large-scale bidirectional MR study suggests that lifelong, genetically driven NAFLD is a causal risk factor for T2D (hence potentially a \"NAFLD-driven T2D\" subtype) and central obesity (or \"NAFLD-driven obesity\" subtype), but protects against overall obesity; while genetically driven T2D, obesity, and central obesity also causally increase the risk of NAFLD, hence a \"metabolic NAFLD\". This causal relationship revealed new insights into disease subtypes and provided novel hypotheses for precision treatment or prevention for the three diseases.

epidemiology↗

bioRxiv2019

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

genetics↗

bioRxiv2019

SNPs associated with HHIP expression have differential effects on lung function in males and females

Adult lung function is highly heritable and 279 genetic loci were recently reported as associated with spirometry-based measures of lung function. Though lung development and function differ between males and females throughout life, there has been no genome-wide study to identify genetic variants with differential effects on lung function in males and females. Here, we present the first genome-wide genotype-by-sex interaction study on four lung function traits in 303,612 participants from the UK Biobank. We detected five SNPs showing genome-wide significant (P<5 x 10-8) interactions with sex on lung function, as well as 21 suggestively significant interactions (P<1 x 10-6). The strongest sex interaction signal came from rs7697189 at 4:145436894 on forced expiratory volume in 1 second (FEV1) (P = 3.15 x 10-15), and was replicated (P = 0.016) in 75,696 individuals in the SpiroMeta consortium. Sex-stratified analyses demonstrated that the minor (C) allele of rs7697189 increased lung function to a greater extent in males than females (untransformed FEV1 {beta} = 0.028 [SE 0.0022] litres in males vs {beta} = 0.009 [SE 0.0014] litres in females), and this effect was not accounted for by differential effects on height, smoking or age at puberty. This SNP resides upstream of the gene encoding hedgehog-interacting protein (HHIP) and has previously been reported for association with lung function and HHIP expression in lung tissue. In our analyses, while HHIP expression in lung tissue was significantly different between the sexes with females having higher expression (most significant probeset P=6.90 x 10-6) after adjusting for age and smoking, rs7697189 did not demonstrate sex differential effects on expression. Establishing the mechanism by which HHIP SNPs have different effects on lung function in males and females will be important for our understanding of lung health and diseases, such as chronic obstructive pulmonary disease (COPD), in both sexes.

genetics↗

bioRxiv2018

Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis

Chronic Kidney Disease (CKD) is a growing health burden currently affecting 10-15% of adults worldwide. Estimated glomerular filtration rate (eGFR) as a marker of kidney function is commonly used to diagnose CKD. Previous genome-wide association study (GWAS) meta-analyses of CKD and eGFR or related phenotypes have identified a number of variants associated with kidney function, but these only explain a fraction of the variability in kidney phenotypes attributed to genetic components. To extend these studies, we analyzed data from the Nord-Trondelag Health Study (HUNT), which is more densely imputed than previous studies, and performed a GWAS meta-analysis of eGFR with publicly available summary statistics, more than doubling the sample size of previous meta-analyses. We identified 147 loci (53 novel loci) associated with eGFR, including genes involved in transcriptional regulation, kidney development, cellular signaling, metabolism, and solute transport. Moreover, genes at these loci show enriched expression in urogenital tissues and highlight gene sets known to play a role in kidney function. In addition, sex-stratified analysis identified three regions (prioritized genes: PPM1J, MCL1, and SLC47A1) with more significant effects in women than men. Using genetic risk scores constructed from these eGFR meta-analysis results, we show that associated variants are generally predictive of CKD but improve detection only modestly compared with other known clinical risk factors. Collectively, these results yield additional insight into the genetic factors underlying kidney function and progression to CKD.

genomics↗