Znf202 Affects High Density Lipoprotein Cholesterol Levels and Promotes Hepatosteatosis in Hyperlipidemic Mice

Background: The zinc finger protein Znf202 is a transcriptional suppressor of lipid related genes and has been linked to hypoalphalipoproteinemia. A functional role of Znf202 in lipid metabolism in vivo still remains to be established. Methodology and Principal Findings: We generated mouse Znf202 expression vectors, the functionality of which was established in several in vitro systems. Next, effects of adenoviral znf202 overexpression in vivo were determined in normo- as well as hyperlipidemic mouse models. Znf202 overexpression in mouse hepatoma cells mhAT3F2 resulted in downregulation of members of the Apoe/c1/c2 and Apoa1/c3/a4 gene cluster. The repressive activity of Znf202 was firmly confirmed in an apoE reporter assay and Znf202 responsive elements within the ApoE promoter were identified. Adenoviral Znf202 transfer to Ldlr-/- mice resulted in downregulation of apoe, apoc1, apoa1, and apoc3 within 24 h after gene transfer. Interestingly, key genes in bile flux (abcg5/8 and bsep) and in bile acid synthesis (cyp7a1) were also downregulated. At 5 days post-infection, the expression of the aforementioned genes was normalized, but mice had developed severe hepatosteatosis accompanied by hypercholesterolemia and hypoalphalipoproteinemia. A much milder phenotype was observed in wildtype mice after 5 days of hepatic Znf202 overexpression. Interestingly and similar to Ldl-/- mice, HDL-cholesterol levels in wildtype mice were lowered after hepatic Znf202 overexpression. Conclusion/Significance: Znf202 overexpression in vivo reveals an important role of this transcriptional regulator in liver lipid homeostasis, while firmly establishing the proposed key role in the control of HDL levels

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) is influenced by both foetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease1. These lifecourse associations have often been attributed to the impact of an adverse early life environment. We performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where foetal genotype was associated with BW (P <5x10-8). Overall, ˜15% of variance in BW could be captured by assays of foetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (rg-0.22, P =5.5x10-13), T2D (rg-0.27, P =1.1x10-6) and coronary artery disease (rg-0.30, P =6.5x10-9) and, in large cohort data sets, demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P =1.9x10-4). We have demonstrated that lifecourse associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and have highlighted some of the pathways through which these causal genetic effects are mediated

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW ($\textit{P}$  < 5 × 10$^{-8}$). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure ($\textit{R}$ $_{g}$ = -0.22, $\textit{P}$  = 5.5 × 10$^{-13}$), T2D ($\textit{R}$ $_{g}$ = -0.27, $\textit{P}$  = 1.1 × 10$^{-6}$) and coronary artery disease ($\textit{R}$ $_{g}$ = -0.30, $\textit{P}$  = 6.5 × 10$^{-9}$). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions ($\textit{P}$ = 1.9 × 10$^{-4}$). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.For a full list of the funders pelase visit the publisher's website and look at the supplemetary material provided. Some of the funders are: British Heart Foundation, Cancer Research UK, Medical Research Council, National Institutes of Health, Royal Society and Wellcome Trust

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Postoperative course of body weight.

<p>Points represent average relative body weight, in relation to the weight prior to operation, for the control group (□) and the groups receiving tacrolimus: T0.5 (◼), T2 (Δ) and T5 (●).</p

Wound hydroxyproline content.

<p>Data are expressed as hydroxyproline content per 5 mm tissue length and represent mean and SEM for the controls (white bars) and the T2 (grey bars) and T5 (black bars) tacrolimus groups. A= ileum, B= colon, C = fascia. *: p<0.05 vs T2 group; #: p<0.05 vs control group.</p

MMP activity in intestinal anastomoses.

<p>Columns represent mean values + SEM for controls (white bars) and the T2 (grey bars) and T5 (black bars) tacrolimus groups. Data represent total activities, in arbitrary units, per 5-mm segment for proMMP-9 (A), MMP-9 (B), proMMP-2 (C), and MMP-2 (D). *: p<0.05 vs control group.</p

Wound breaking strength.

<p>Data represent mean and SEM in the control groups (white bars) and the T0.5 (black & white bars), T2 (grey bars) and T5 (black bars) tacrolimus groups. A= ileum anastomoses, B= colon anastomoses, C = fascia.</p