Verification of immunology-related genetic associations in BPD supports ABCA3 and five other genes.

BACKGROUND: Inflammatory processes are key drivers of bronchopulmonary dysplasia (BPD), a chronic lung disease in preterm infants. In a large sample, we verify previously reported associations of genetic variants of immunology-related genes with BPD. METHODS: Preterm infants with a gestational age ≤32 weeks from PROGRESS and the German Neonatal Network (GNN) were included. Through a consensus case/control definition, 278 BPD cases and 670 controls were identified. We identified 49 immunity-related genes and 55 single-nucleotide polymorphisms (SNPs) previously associated with BPD through a comprehensive literature survey. Additionally, a quantitative genetic association analysis regarding oxygen supplements, mechanical ventilation, and continuous positive air pressure (CPAP) was performed. RESULTS: Five candidate SNPs were nominally associated with BPD-related phenotypes with effect directions not conflicting the original studies: rs11265269-CRP, rs1427793-NUAK1, rs2229569-SELL, rs1883617-VNN2, and rs4148913-CHST3. Four of these genes are involved in cell adhesion. Extending our analysis to all well-imputed SNPs of all candidate genes, the strongest association was rs45538638-ABCA3 with CPAP (p = 4.9 × 10-7, FDR = 0.004), an ABC transporter involved in surfactant formation. CONCLUSIONS: Most of the previously reported associations could not be replicated. We found additional support for SNPs in CRP, NUAK1, SELL, VNN2, and ABCA3. Larger studies and meta-analyses are required to corroborate these findings. IMPACT: Larger cohort for improved statistical power to detect genetic associations with bronchopulmonary dysplasia (BPD). Most of the previously reported genetic associations with BPD could not be replicated in this larger study. Among investigated immunological relevant candidate genes, additional support was found for variants in genes CRP, NUAK1, SELL, VNN2, and CHST3, four of them related to cell adhesion. rs45538638 is a novel candidate SNP in reported candidate gene ABC-transporter ABCA3. Results help to prioritize molecular candidate pathomechanisms in follow-up studies.

Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline.

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2 at follow-up among those with eGFRcrea 60 mL/min/1.73m2 or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

Sequential organ failure assessment score is an excellent operationalization of disease severity of adult patients with hospitalized community acquired pneumonia - results from the prospective observational PROGRESS study.

BACKGROUND: CAP (Community acquired pneumonia) is frequent, with a high mortality rate and a high burden on health care systems. Development of predictive biomarkers, new therapeutic concepts, and epidemiologic research require a valid, reproducible, and quantitative measure describing CAP severity. METHODS: Using time series data of 1532 patients enrolled in the PROGRESS study, we compared putative measures of CAP severity for their utility as an operationalization. Comparison was based on ability to correctly identify patients with an objectively severe state of disease (death or need for intensive care with at least one of the following: substantial respiratory support, treatment with catecholamines, or dialysis). We considered IDSA/ATS minor criteria, CRB-65, CURB-65, Halm criteria, qSOFA, PSI, SCAP, SIRS-Score, SMART-COP, and SOFA. RESULTS: SOFA significantly outperformed other scores in correctly identifying a severe state of disease at the day of enrollment (AUC = 0.948), mainly caused by higher discriminative power at higher score values. Runners-up were the sum of IDSA/ATS minor criteria (AUC = 0.916) and SCAP (AUC = 0.868). SOFA performed similarly well on subsequent study days (all AUC > 0.9) and across age groups. In univariate and multivariate analysis, age, sex, and pack-years significantly contributed to higher SOFA values whereas antibiosis before hospitalization predicted lower SOFA. CONCLUSIONS: SOFA score can serve as an excellent operationalization of CAP severity and is proposed as endpoint for biomarker and therapeutic studies. TRIAL REGISTRATION: clinicaltrials.gov NCT02782013 , May 25, 2016, retrospectively registered.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

Genome-wide association analysis of actigraphic sleep phenotypes in the LIFE Adult Study.

The genetic basis of sleep is still poorly understood. Despite the moderate to high heritability of sleep-related phenotypes, known genetic variants explain only a small proportion of the phenotypical variance. However, most previous studies were based solely upon self-report measures. The present study aimed to conduct the first genome-wide association (GWA) of actigraphic sleep phenotypes. The analyses included 956 middle- to older-aged subjects (40-79 years) from the LIFE Adult Study. The SenseWear Pro 3 Armband was used to collect 11 actigraphic parameters of night- and daytime sleep and three parameters of rest (lying down). The parameters comprised measures of sleep timing, quantity and quality. A total of 7 141 204 single nucleotide polymorphisms (SNPs) were analysed after imputation and quality control. We identified several variants below the significance threshold of P ≤ 5× 10-8 (not corrected for analysis of multiple traits). The most significant was a hit near UFL1 associated with sleep efficiency on weekdays (P = 1.39 × 10-8 ). Further SNPs were close to significance, including an association between sleep latency and a variant in CSNK2A1 (P = 8.20 × 10-8 ), a gene known to be involved in the regulation of circadian rhythm. In summary, our GWAS identified novel candidate genes with biological plausibility being promising candidates for replication and further follow-up studies.

Impact of pre-imputation SNP-filtering on genotype imputation results.

BACKGROUND: Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. RESULTS: We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of completely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. CONCLUSION: Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time.

Phenome- and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health.

The human retina is a multilayered tissue that offers a unique window into systemic health. Optical coherence tomography (OCT) is widely used in eye care and allows the noninvasive, rapid capture of retinal anatomy in exquisite detail. We conducted genotypic and phenotypic analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed OCT layer cross-phenotype association analyses (OCT-XWAS), associating retinal thicknesses with 1866 incident conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association studies (GWASs), identifying inherited genetic markers that influence retinal layer thicknesses and replicated our associations among the LIFE-Adult Study (N = 6313). Last, we performed a comparative analysis of phenome- and genome-wide associations to identify putative causal links between retinal layer thicknesses and both ocular and systemic conditions. Independent associations with incident mortality were detected for thinner photoreceptor segments (PSs) and, separately, ganglion cell complex layers. Phenotypic associations were detected between thinner retinal layers and ocular, neuropsychiatric, cardiometabolic, and pulmonary conditions. A GWAS of retinal layer thicknesses yielded 259 unique loci. Consistency between epidemiologic and genetic associations suggested links between a thinner retinal nerve fiber layer with glaucoma, thinner PS with age-related macular degeneration, and poor cardiometabolic and pulmonary function with a thinner PS. In conclusion, we identified multiple inherited genetic loci and acquired systemic cardio-metabolic-pulmonary conditions associated with thinner retinal layers and identify retinal layers wherein thinning is predictive of future ocular and systemic conditions.

X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements.

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

Automated detection of genetic relatedness from fundus photographs using Siamese Neural Networks.

Heritability of common eye diseases and ocular traits are relatively high. Here, we develop an automated algorithm to detect genetic relatedness from color fundus photographs (FPs). We estimated the degree of shared ancestry amongst individuals in the UK Biobank using KING software. A convolutional Siamese neural network-based algorithm was trained to output a measure of genetic relatedness using 7224 pairs (3612 related and 3612 unrelated) of FPs. The model achieved high performance for prediction of genetic relatedness; when computed Euclidean distances were used to determine probability of relatedness, the area under the receiver operating characteristic curve (AUROC) for identifying related FPs reached 0.926. We performed external validation of our model using FPs from the LIFE-Adult study and achieved an AUROC of 0.69. An occlusion map indicates that the optic nerve and its surrounding area may be the most predictive of genetic relatedness. We demonstrate that genetic relatedness can be captured from FP features. This approach may be used to uncover novel biomarkers for common ocular diseases.

Insights into human health from phenome- and genome-wide analyses of UK Biobank retinal optical coherence tomography phenotypes.

The human retina is a complex multi-layered tissue which offers a unique window into systemic health and disease. Optical coherence tomography (OCT) is widely used in eye care and allows the non-invasive, rapid capture of retinal measurements in exquisite detail. We conducted genome- and phenome-wide analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed phenome-wide association analyses, associating retinal thicknesses with 1,866 incident ICD-based conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association analyses, identifying inherited genetic markers which influence the retina, and replicated our associations among 6,313 individuals from the LIFE-Adult Study. And lastly, we performed comparative association of phenome- and genome- wide associations to identify putative causal links between systemic conditions, retinal layer thicknesses, and ocular disease. Independent associations with incident mortality were detected for photoreceptor thinning and ganglion cell complex thinning. Significant phenotypic associations were detected between retinal layer thinning and ocular, neuropsychiatric, cardiometabolic and pulmonary conditions. Genome-wide association of retinal layer thicknesses yielded 259 loci. Consistency between epidemiologic and genetic associations suggested putative causal links between thinning of the retinal nerve fiber layer with glaucoma, photoreceptor segment with AMD, as well as poor cardiometabolic and pulmonary function with PS thinning, among other findings. In conclusion, retinal layer thinning predicts risk of future ocular and systemic disease. Furthermore, systemic cardio-metabolic-pulmonary conditions promote retinal thinning. Retinal imaging biomarkers, integrated into electronic health records, may inform risk prediction and potential therapeutic strategies.

Genetic dissection of serum vaspin highlights its causal role in lipid metabolism.

OBJECTIVE: Vaspin (visceral adipose tissue derived serine protease inhibitor, SERPINA12) is associated with obesity-related metabolic traits, but its causative role is still elusive. The role of genetics in serum vaspin variability to establish its causal relationship with metabolically relevant traits was investigated. METHODS: A meta-analysis of genome-wide association studies for serum vaspin from six independent cohorts (N = 7446) was conducted. Potential functional variants of vaspin were included in Mendelian randomization (MR) analyses to assess possible causal pathways between vaspin and homeostasis model assessment and lipid traits. To further validate the MR analyses, data from Genotype-Tissue Expression (GTEx) were analyzed, db/db mice were treated with vaspin, and serum lipids were measured. RESULTS: A total of 468 genetic variants represented by five independent variants (rs7141073, rs1956709, rs4905216, rs61978267, rs73338689) within the vaspin locus were associated with serum vaspin (all p < 5×10-8 , explained variance 16.8%). MR analyses revealed causal relationships between serum vaspin and triglycerides, low-density lipoprotein, and total cholesterol. Gene expression correlation analyses suggested that genes, highly correlated with vaspin expression in adipose tissue, are enriched in lipid metabolic processes. Finally, in vivo vaspin treatment reduced serum triglycerides in obese db/db mice. CONCLUSIONS: The data show that serum vaspin is strongly determined by genetic variants within vaspin, which further highlight vaspin's causal role in lipid metabolism.

Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake.

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P < 5 × 10-8) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits.

First genome-wide association study of 99 body measures derived from 3-dimensional body scans.

Body height, body mass index, hip and waist circumference are important risk factors or outcome variables in clinical and epidemiological research with complex underlying genetics. However, these classical anthropometric traits represent only a very limited view on the human body and other traits with potentially higher functional specificity are not yet studied to a larger extent. Participants of LIFE-Adult were assessed by three-dimensional body scanner VITUS XXL determining 99 high-quality anthropometric traits in parallel. Genotyping was performed by Axiom Genome-Wide CEU 1 Array Plate microarray technology and imputation was done using 1000 Genomes phase 3 reference panel. Combined phenotype and genetic information are available for a total of 7,562 participants. Largest heritabilities were estimated for height traits (maximum heritability with h2 = 44% for neck height) and 61 traits achieved values larger than 20%. By genome-wide analyses, we identified 16 loci associated with at least one of the 99 traits. Ten of these loci were not described for association with classical anthropometric traits so far. The strongest novel association was observed for 7p14.3 (rs11979006, P = 2.12 × 10-9) for the trait Back Width with ZNRF2 as the most plausible candidate gene. Loci established for association with classical anthropometric traits were subjected to anthropometric phenome-wide association analysis. From the reported 709 loci, 211 are co-associated with body scanner traits (enrichment: OR = 1.96, P = 1.08 × 10-61). We conclude that genetics of 3D laser-based anthropometry is promising to identify novel loci and to improve the functional understanding of established ones.

Genetic Regulation of Cytokine Response in Patients with Acute Community-Acquired Pneumonia.

BACKGROUND: Community-acquired pneumonia (CAP) is an acute disease condition with a high risk of rapid deteriorations. We analysed the influence of genetics on cytokine regulation to obtain a better understanding of patient's heterogeneity. METHODS: For up to N = 389 genotyped participants of the PROGRESS study of hospitalised CAP patients, we performed a genome-wide association study of ten cytokines IL-1ß, IL-6, IL-8, IL-10, IL-12, MCP-1 (MCAF), MIP-1α (CCL3), VEGF, VCAM-1, and ICAM-1. Consecutive secondary analyses were performed to identify independent hits and corresponding causal variants. RESULTS: 102 SNPs from 14 loci showed genome-wide significant associations with five of the cytokines. The most interesting associations were found at 6p21.1 for VEGF (p = 1.58 × 10-20), at 17q21.32 (p = 1.51 × 10-9) and at 10p12.1 (p = 2.76 × 10-9) for IL-1ß, at 10p13 for MIP-1α (CCL3) (p = 2.28 × 10-9), and at 9q34.12 for IL-10 (p = 4.52 × 10-8). Functionally plausible genes could be assigned to the majority of loci including genes involved in cytokine secretion, granulocyte function, and cilial kinetics. CONCLUSION: This is the first context-specific genetic association study of blood cytokine concentrations in CAP patients revealing numerous biologically plausible candidate genes. Two of the loci were also associated with atherosclerosis with probable common or consecutive pathomechanisms.

Impact of medication on blood transcriptome reveals off-target regulations of beta-blockers.

BACKGROUND: For many drugs, mechanisms of action with regard to desired effects and/or unwanted side effects are only incompletely understood. To investigate possible pleiotropic effects and respective molecular mechanisms, we describe here a catalogue of commonly used drugs and their impact on the blood transcriptome. METHODS AND RESULTS: From a population-based cohort in Germany (LIFE-Adult), we collected genome-wide gene-expression data in whole blood using in Illumina HT12v4 micro-arrays (n = 3,378; 19,974 gene expression probes per individual). Expression profiles were correlated with the intake of active substances as assessed by participants' medication. This resulted in a catalogue of fourteen substances that were identified as associated with differential gene expression for a total of 534 genes. As an independent replication cohort, an observational study of patients with suspected or confirmed stable coronary artery disease (CAD) or myocardial infarction (LIFE-Heart, n = 3,008, 19,966 gene expression probes per individual) was employed. Notably, we were able to replicate differential gene expression for three active substances affecting 80 genes in peripheral blood mononuclear cells (carvedilol: 25; prednisolone: 17; timolol: 38). Additionally, using gene ontology enrichment analysis, we demonstrated for timolol a significant enrichment in 23 pathways, 19 of them including either GPER1 or PDE4B. In the case of carvedilol, we showed that, beside genes with well-established association with hypertension (GPER1, PDE4B and TNFAIP3), the drug also affects genes that are only indirectly linked to hypertension due to their effects on artery walls or their role in lipid biosynthesis. CONCLUSIONS: Our developed catalogue of blood gene expressions profiles affected by medication can be used to support both, drug repurposing and the identification of possible off-target effects.

Genome-wide meta-analysis of phytosterols reveals five novel loci and a detrimental effect on coronary atherosclerosis.

Phytosterol serum concentrations are under tight genetic control. The relationship between phytosterols and coronary artery disease (CAD) is controversially discussed. We perform a genome-wide meta-analysis of 32 phytosterol traits reflecting resorption, cholesterol synthesis and esterification in six studies with up to 9758 subjects and detect ten independent genome-wide significant SNPs at seven genomic loci. We confirm previously established associations at ABCG5/8 and ABO and demonstrate an extended locus heterogeneity at ABCG5/8 with different functional mechanisms. New loci comprise HMGCR, NPC1L1, PNLIPRP2, SCARB1 and APOE. Based on these results, we perform Mendelian Randomization analyses (MR) revealing a risk-increasing causal relationship of sitosterol serum concentrations and CAD, which is partly mediated by cholesterol. Here we report that phytosterols are polygenic traits. MR add evidence of both, direct and indirect causal effects of sitosterol on CAD.

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.

Genome-wide association and transcriptome analysis suggests total serum ghrelin to be linked with GFRAL.

OBJECTIVE: Ghrelin is an orexigenic peptide hormone involved in the regulation of energy homeostasis, food intake and glucose metabolism. Serum levels increase anticipating a meal and fall afterwards. Underlying genetic mechanisms of the ghrelin secretion are unknown. METHODS: Total serum ghrelin was measured in 1501 subjects selected from the population-based LIFE-ADULT-sample after an overnight fast. A genome-wide association study (GWAS) was performed. Gene-based expression association analyses (transcriptome-wide association study (TWAS)) are statistical tests associating genetically predicted expression to a certain trait and were done using MetaXcan. RESULTS: In the GWAS, three loci reached genome-wide significance: the WW-domain containing the oxidoreductase-gene (WWOX; P = 1.80E-10) on chromosome 16q23.3-24.1 (SNP: rs76823993); the contactin-associated protein-like 2 gene (CNTNAP2; P = 9.0E-9) on chromosome 7q35-q36 (SNP: rs192092592) and the ghrelin And obestatin prepropeptide gene (GHRL; P = 2.72E-8) on chromosome 3p25.3 (SNP: rs143729751). In the TWAS, the three genes where the expression was strongest associated with serum ghrelin levels was the ribosomal protein L36 (RPL36; P = 1.3E-06, FDR = 0.011, positively correlated), AP1B1 (P = 1.1E-5, FDR = 0.048, negatively correlated) and the GDNF family receptor alpha like (GFRAL), receptor of the anorexigenic growth differentiation factor-15 (GDF15), (P = 1.8E-05, FDR = 0.15, also negatively correlated). CONCLUSIONS: The three genome-wide significant genetic loci from the GWA and the genes identified in the TWA are functionally plausible and should initiate further research.

Sex-Specific Causal Relations between Steroid Hormones and Obesity-A Mendelian Randomization Study.

Steroid hormones act as important regulators of physiological processes including gene expression. They provide possible mechanistic explanations of observed sex-dimorphisms in obesity and coronary artery disease (CAD). Here, we aim to unravel causal relationships between steroid hormones, obesity, and CAD in a sex-specific manner. In genome-wide meta-analyses of four steroid hormone levels and one hormone ratio, we identified 17 genome-wide significant loci of which 11 were novel. Among loci, seven were female-specific, four male-specific, and one was sex-related (stronger effects in females). As one of the loci was the human leukocyte antigen (HLA) region, we analyzed HLA allele counts and found four HLA subtypes linked to 17-OH-progesterone (17-OHP), including HLA-B*14*02. Using Mendelian randomization approaches with four additional hormones as exposure, we detected causal effects of dehydroepiandrosterone sulfate (DHEA-S) and 17-OHP on body mass index (BMI) and waist-to-hip ratio (WHR). The DHEA-S effect was stronger in males. Additionally, we observed the causal effects of testosterone, estradiol, and their ratio on WHR. By mediation analysis, we found a direct sex-unspecific effect of 17-OHP on CAD while the other four hormone effects on CAD were mediated by BMI or WHR. In conclusion, we identified the sex-specific causal networks of steroid hormones, obesity-related traits, and CAD.

Characterization and quantification of clonal heterogeneity among hematopoietic stem cells: a model-based approach.

Hematopoietic stem cells (HSCs) show pronounced heterogeneity in self-renewal and differentiation behavior, which is reflected in their repopulation kinetics. Here, a single-cell-based mathematical model of HSC organization is used to examine the basis of HSC heterogeneity. Our modeling results, which are based on the analysis of limiting dilution competitive repopulation experiments in mice, demonstrate that small quantitative but clonally fixed differences of cellular properties are necessary and sufficient to account for the observed functional heterogeneity. The model predicts, and experimental data validate, that competitive pressures will amplify small clonal differences into large changes in the number of differentiated progeny. We further predict that the repertoire of HSC clones will evolve over time. Last, our results suggest that larger differences in cellular properties have to be assumed to account for genetically determined differences in HSC behavior as observed in different inbred mice strains. The model provides comprehensive systemic and quantitative insights into the clonal heterogeneity among HSCs with potential applications in predicting the behavior of malignant and/or genetically modified cells.