Associations Between Dietary Patterns and Kidney Health Assessed in the Population-Based CHRIS Study Using Reduced Rank Regression.

OBJECTIVE: While diet plays a key role in chronic kidney disease (CKD) management, the potential for diet to impact CKD prevention in the general population is less clear. Using a priori knowledge, we derived disease-related dietary patterns (DPs) through reduced rank regression (RRR) and investigated associations with kidney function, separately focusing on generally healthy individuals and those with self-reported kidney diseases, hypertension, or diabetes mellitus. METHODS: Eight thousand six hundred eighty-six participants from the population-based Cooperative Health Research in South Tyrol study were split into a group free of kidney disease, hypertension and diabetes (n = 6,133) and a group with any of the 3 conditions (n = 2,553). Diet was assessed through the self-administered Global Allergy and Asthma Network of Excellence food frequency questionnaire and DPs were derived through RRR selecting food frequency questionnaire-derived sodium, potassium, phosphorus, and protein intake as mediators. Outcomes were creatinine-based estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, CKD and microalbuminuria. Multiple linear and logistic models were used to assess associations between RRR-based DPs and kidney outcomes separately in the 2 analytic groups. RESULTS: We identified 3 DPs, where high adherence reflected high levels of all nutrients (DP1), high potassium-phosphorus and low protein-sodium levels (DP2), and low potassium-sodium and high protein-phosphorus levels (DP3), respectively. We observed heterogeneous associations with kidney outcomes, varying by analytic group and sex. Kidney outcomes were much more strongly associated with DPs than with single nutrients. CONCLUSION: RRR is a feasible approach to estimate disease-related DPs and explore the combined effects of nutrients on kidney health. Heterogeneous associations across kidney outcomes suggest possible specificity to kidney function or damage. In individuals reporting kidney disease, hypertension or diabetes, specific dietary habits were associated with better kidney health, indicating that disease-specific dietary interventions can be effective for disease control.

Cluster analysis of angiotensin biomarkers to identify antihypertensive drug treatment in population studies.

BACKGROUND: The recent progress in molecular biology generates an increasing interest in investigating molecular biomarkers as markers of response to treatments. The present work is motivated by a study, where the objective was to explore the potential of the molecular biomarkers of renin-angiotensin-aldosterone system (RAAS) to identify the undertaken antihypertensive treatments in the general population. Population-based studies offer an opportunity to assess the effectiveness of treatments in real-world scenarios. However, lack of quality documentation, especially when electronic health record linkage is unavailable, leads to inaccurate reporting and classification bias. METHOD: We present a machine learning clustering technique to determine the potential of measured RAAS biomarkers for the identification of undertaken treatments in the general population. The biomarkers were simultaneously determined through a novel mass-spectrometry analysis in 800 participants of the Cooperative Health Research In South Tyrol (CHRIS) study with documented antihypertensive treatments. We assessed the agreement, sensitivity and specificity of the resulting clusters against known treatment types. Through the lasso penalized regression, we identified clinical characteristics associated with the biomarkers, accounting for the effects of cluster and treatment classifications. RESULTS: We identified three well-separated clusters: cluster 1 (n = 444) preferentially including individuals not receiving RAAS-targeting drugs; cluster 2 (n = 235) identifying angiotensin type 1 receptor blockers (ARB) users (weighted kappa κw = 74%; sensitivity = 73%; specificity = 83%); and cluster 3 (n = 121) well discriminating angiotensin-converting enzyme inhibitors (ACEi) users (κw = 81%; sensitivity = 55%; specificity = 90%). Individuals in clusters 2 and 3 had higher frequency of diabetes as well as higher fasting glucose and BMI levels. Age, sex and kidney function were strong predictors of the RAAS biomarkers independently of the cluster structure. CONCLUSIONS: Unsupervised clustering of angiotensin-based biomarkers is a viable technique to identify individuals on specific antihypertensive treatments, pointing to a potential application of the biomarkers as useful clinical diagnostic tools even outside of a controlled clinical setting.

Prevalence and determinants of serum antibodies to SARS-CoV-2 in the general population of the Gardena valley.

Estimating the spread of SARS-CoV-2 infection in communities is critical. We surveyed 2244 stratified random sample community members of the Gardena valley, a winter touristic area, amidst the first expansion phase of the COVID-19 pandemic in Europe. We measured agreement between Diasorin and Abbott serum bioassay outputs and the Abbott optimal discriminant threshold of serum neutralisation titres with recursive receiver operating characteristic curve. We analytically adjusted serum antibody tests for unbiased seroprevalence estimate and analysed the determinants of infection with non-response weighted multiple logistic regression. SARS-CoV-2 seroprevalence was 26.9% (95% CI 25.2-28.6) by June 2020. The bioassays had a modest agreement with each other. At a lower threshold than the manufacturer's recommended level, the Abbott assay reflected greater discrimination of serum neutralisation capacity. Seropositivity was associated with place and economic activity, not with sex or age. Symptoms like fever and weakness were age-dependent. SARS-CoV-2 mitigation strategies should account for context in high prevalence areas.

Directional dominance on stature and cognition in diverse human populations.

Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

Integration of GWAS Summary Statistics and Gene Expression Reveals Target Cell Types Underlying Kidney Function Traits.

BACKGROUND: Genetic variants identified in genome-wide association studies (GWAS) are often not specific enough to reveal complex underlying physiology. By integrating RNA-seq data and GWAS summary statistics, novel computational methods allow unbiased identification of trait-relevant tissues and cell types. METHODS: The CKDGen consortium provided GWAS summary data for eGFR, urinary albumin-creatinine ratio (UACR), BUN, and serum urate. Genotype-Tissue Expression Project (GTEx) RNA-seq data were used to construct the top 10% specifically expressed genes for each of 53 tissues followed by linkage disequilibrium (LD) score-based enrichment testing for each trait. Similar procedures were performed for five kidney single-cell RNA-seq datasets from humans and mice and for a microdissected tubule RNA-seq dataset from rat. Gene set enrichment analyses were also conducted for genes implicated in Mendelian kidney diseases. RESULTS: Across 53 tissues, genes in kidney function-associated GWAS loci were enriched in kidney (P=9.1E-8 for eGFR; P=1.2E-5 for urate) and liver (P=6.8·10-5 for eGFR). In the kidney, proximal tubule was enriched in humans (P=8.5E-5 for eGFR; P=7.8E-6 for urate) and mice (P=0.0003 for eGFR; P=0.0002 for urate) and confirmed as the primary cell type in microdissected tubules and organoids. Gene set enrichment analysis supported this and showed enrichment of genes implicated in monogenic glomerular diseases in podocytes. A systematic approach generated a comprehensive list of GWAS genes prioritized by cell type-specific expression. CONCLUSIONS: Integration of GWAS statistics of kidney function traits and gene expression data identified relevant tissues and cell types, as a basis for further mechanistic studies to understand GWAS loci.

A bidirectional Mendelian randomization study supports causal effects of kidney function on blood pressure.

Blood pressure and kidney function have a bidirectional relation. Hypertension has long been considered as a risk factor for kidney function decline. However, whether intensive blood pressure control could promote kidney health has been uncertain. The kidney is known to have a major role in affecting blood pressure through sodium extraction and regulating electrolyte balance. This bidirectional relation makes causal inference between these two traits difficult. Therefore, to examine the causal relations between these two traits, we performed two-sample Mendelian randomization analyses using summary statistics of large-scale genome-wide association studies. We selected genetic instruments more likely to be specific for kidney function using meta-analyses of complementary kidney function biomarkers (glomerular filtration rate estimated from serum creatinine [eGFRcr], and blood urea nitrogen from the CKDGen Consortium). Systolic and diastolic blood pressure summary statistics were from the International Consortium for Blood Pressure and UK Biobank. Significant evidence supported the causal effects of higher kidney function on lower blood pressure. Based on the mode-based Mendelian randomization method, the effect estimates for one standard deviation (SD) higher in log-transformed eGFRcr was -0.17 SD unit (95 % confidence interval: -0.09 to -0.24) in systolic blood pressure and -0.15 SD unit (95% confidence interval: -0.07 to -0.22) in diastolic blood pressure. In contrast, the causal effects of blood pressure on kidney function were not statistically significant. Thus, our results support causal effects of higher kidney function on lower blood pressure and suggest preventing kidney function decline can reduce the public health burden of hypertension.

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

Motivation: Familial aggregation analysis is an important early step for characterizing the genetic determinants of phenotypes in epidemiological studies. To facilitate this analysis, a collection of methods to detect familial aggregation in large pedigrees has been made available recently. However, efficacy of these methods in real world scenarios remains largely unknown. Here, we assess the performance of five aggregation methods to identify individuals or groups of related individuals affected by a Mendelian trait within a large set of decoys. We investigate method performance under a representative set of combinations of causal variant penetrance, trait prevalence and number of affected generations in the pedigree. These methods are then applied to assess familial aggregation of familial hypercholesterolemia and stroke, in the context of the Cooperative Health Research in South Tyrol (CHRIS) study. Results: We find that in some situations statistical hypothesis testing with a binomial null distribution achieves performance similar to methods that are based on kinship information, while kinship based methods perform better when information is available on fewer generations. Potential case families from the CHRIS study are reported and the results are discussed taking into account insights from the performance assessment. Availability and implementation: The familial aggregation analysis package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg. Supplementary information: Supplementary data are available at Bioinformatics online.

Microbiota, type 2 diabetes and non-alcoholic fatty liver disease: protocol of an observational study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is characterized by triglyceride accumulation in the hepatocytes in the absence of alcohol overconsumption, commonly associated with insulin resistance and obesity. Both NAFLD and type 2 diabetes (T2D) are characterized by an altered microbiota composition, however the role of the microbiota in NAFLD and T2D is not well understood. To assess the relationship between alteration in the microbiota and NAFLD while dissecting the role of T2D, we established a nested study on T2D and non-T2D individuals within the Cooperative Health Research In South Tyrol (CHRIS) study, called the CHRIS-NAFLD study. Here, we present the study protocol along with baseline and follow-up characteristics of study participants. METHODS: Among the first 4979 CHRIS study participants, 227 individuals with T2D were identified and recalled, along with 227 age- and sex-matched non-T2D individuals. Participants underwent ultrasound and transient elastography examination to evaluate the presence of hepatic steatosis and liver stiffness. Additionally, sampling of saliva and faeces, biochemical measurements and clinical interviews were carried out. RESULTS: We recruited 173 T2D and 183 non-T2D participants (78% overall response rate). Hepatic steatosis was more common in T2D (63.7%) than non-T2D (36.3%) participants. T2D participants also had higher levels of liver stiffness (median 4.8 kPa, interquartile range (IQR) 3.7, 5.9) than non-T2D participants (median 3.9 kPa, IQR 3.3, 5.1). The non-invasive scoring systems like the NAFLD fibrosis score (NFS) suggests an increased liver fibrosis in T2D (mean - 0.55, standard deviation, SD, 1.30) than non-T2D participants (mean - 1.30, SD, 1.17). DISCUSSION: Given the comprehensive biochemical and clinical characterization of study participants, once the bioinformatics classification of the microbiota will be completed, the CHRIS-NAFLD study will become a useful resource to further our understanding of the relationship between microbiota, T2D and NAFLD.

The UMOD Locus: Insights into the Pathogenesis and Prognosis of Kidney Disease.

The identification of genetic factors associated with kidney disease has the potential to provide critical insights into disease mechanisms. Genome-wide association studies have uncovered genomic regions associated with renal function metrics and risk of CKD. UMOD is among the most outstanding loci associated with CKD in the general population, because it has a large effect on eGFR and CKD risk that is consistent across different ethnic groups. The relevance of UMOD for CKD is clear, because the encoded protein, uromodulin (Tamm-Horsfall protein), is exclusively produced by the kidney tubule and has specific biochemical properties that mediate important functions in the kidney and urine. Rare mutations in UMOD are the major cause of autosomal dominant tubulointerstitial kidney disease, a condition that leads to CKD and ESRD. In this brief review, we use the UMOD paradigm to describe how population genetic studies can yield insight into the pathogenesis and prognosis of kidney diseases.

Negative effect of vitamin D on kidney function: a Mendelian randomization study.

Background: The kidney plays a central role in the regulation of vitamin D metabolism. It is not clear, however, whether vitamin D influences kidney function. Previous studies have reported conflicting results, which may have been influenced by reverse causation and residual confounding. We conducted a Mendelian randomization (MR) study to obtain unconfounded estimates of the association between genetically instrumented vitamin D metabolites and estimated glomerular filtration rate (eGFR) as well as the urinary albumin:creatinine ratio (UACR). Methods: We performed a two-sample MR study based on three single nucleotide variants associated with 25(OH)D levels: rs2282679, rs10741657 and rs12785878, related to the genes GC, CYP2R1 and DHCR7, respectively. Estimates of the allele-dependent effects on serum 25(OH)D and eGFR/UACR were obtained from summary statistics of published genome-wide association meta-analyses. Additionally, we performed a one-sample MR analysis for both 25(OH)D and 1,25(OH)2 D using individual-level data from six cohorts. Results: The combined MR estimate supported a negative causal effect of log transformed 25(OH)D on log transformed eGFR (ß = -0.013, P = 0.003). The analysis of individual-level data confirmed the main findings and also revealed a significant association of 1,25(OH)2 D on eGFR (ß = -0.094, P = 0.008). These results show that a 10% increase in serum 25(OH)D levels causes a 0.3% decrease in eGFR. There was no effect of 25(OH)D on UACR (ß = 0.032, P = 0.265). Conclusion: Our study suggests that circulating vitamin D metabolite levels are negatively associated with eGFR. Further studies are needed to elucidate the underlying mechanisms.

Sequential recruitment of study participants may inflate genetic heritability estimates.

After the success of genome-wide association studies to uncover complex trait loci, attempts to explain the remaining genetic heritability (h 2) are mainly focused on unraveling rare variant associations and gene-gene or gene-environment interactions. Little attention is paid to the possibility that h 2 estimates are inflated as a consequence of the epidemiological study design. We studied the time series of 54 biochemical traits in 4373 individuals from the Cooperative Health Research In South Tyrol (CHRIS) study, a pedigree-based study enrolling ten participants/day over several years, with close relatives preferentially invited within the same day. We observed distributional changes of measured traits over time. We hypothesized that the combination of such changes with the pedigree structure might generate a shared-environment component with consequent h 2 inflation. We performed variance components (VC) h 2 estimation for all traits after accounting for the enrollment period in a linear mixed model (two-stage approach). Accounting for the enrollment period caused a median h 2 reduction of 4%. For 9 traits, the reduction was of >20%. Results were confirmed by a Bayesian Markov chain Monte Carlo analysis with all VCs included at the same time (one-stage approach). The electrolytes were the traits most affected by the enrollment period. The h 2 inflation was independent of the h 2 magnitude, laboratory protocol changes, and length of the enrollment period. The enrollment process may induce shared-environment effects even under very stringent and standardized operating procedures, causing h 2 inflation. Including the day of participation as a random effect is a sensitive way to avoid overestimation.

FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees.

UNLABELLED: Familial aggregation analysis is the first fundamental step to perform when assessing the extent of genetic background of a disease. However, there is a lack of software to analyze the familial clustering of complex phenotypes in very large pedigrees. Such pedigrees can be utilized to calculate measures that express trait aggregation on both the family and individual level, providing valuable directions in choosing families for detailed follow-up studies. We developed FamAgg, an open source R package that contains both established and novel methods to investigate familial aggregation of traits in large pedigrees. We demonstrate its use and interpretation by analyzing a publicly available cancer dataset with more than 20 000 participants distributed across approximately 400 families. AVAILABILITY AND IMPLEMENTATION: The FamAgg package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg CONTACT: Christian.Weichenberger@eurac.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Serum iron level and kidney function: a Mendelian randomization study.

Background: Iron depletion is a known consequence of chronic kidney disease (CKD), but there is contradicting epidemiological evidence on whether iron itself affects kidney function and whether its effect is protective or detrimental in the general population. While epidemiological studies tend to be affected by confounding and reverse causation, Mendelian randomization (MR) can provide unconfounded estimates of causal effects by using genes as instruments. Methods: We performed an MR study of the effect of serum iron levels on estimated glomerular filtration rate (eGFR), using genetic variants known to be associated with iron. MR estimates of the effect of iron on eGFR were derived based on the association of each variant with iron and eGFR from two large genome-wide meta-analyses on 48 978 and 74 354 individuals. We performed a similar MR analysis for ferritin, which measures iron stored in the body, using variants associated with ferritin. Results: A combined MR estimate across all variants showed a 1.3% increase in eGFR per standard deviation increase in iron (95% confidence interval 0.4­2.1%; P = 0.004). The results for ferritin were consistent with those for iron. Secondary MR analyses of the effects of iron and ferritin on CKD did not show significant associations but had very low statistical power. Conclusions: Our study suggests a protective effect of iron on kidney function in the general population. Further research is required to confirm this causal association, investigate it in study populations at higher risk of CKD and explore its underlying mechanism of action.

Mendelian Randomization as an Approach to Assess Causality Using Observational Data.

Mendelian randomization refers to an analytic approach to assess the causality of an observed association between a modifiable exposure or risk factor and a clinically relevant outcome. It presents a valuable tool, especially when randomized controlled trials to examine causality are not feasible and observational studies provide biased associations because of confounding or reverse causality. These issues are addressed by using genetic variants as instrumental variables for the tested exposure: the alleles of this exposure-associated genetic variant are randomly allocated and not subject to reverse causation. This, together with the wide availability of published genetic associations to screen for suitable genetic instrumental variables make Mendelian randomization a time- and cost-efficient approach and contribute to its increasing popularity for assessing and screening for potentially causal associations. An observed association between the genetic instrumental variable and the outcome supports the hypothesis that the exposure in question is causally related to the outcome. This review provides an overview of the Mendelian randomization method, addresses assumptions and implications, and includes illustrative examples. We also discuss special issues in nephrology, such as inverse risk factor associations in advanced disease, and outline opportunities to design Mendelian randomization studies around kidney function and disease.

Combination of mouse models and genomewide association studies highlights novel genes associated with human kidney function.

Genomewide association studies have identified numerous chronic kidney disease-associated genetic variants, but often do not pinpoint causal genes. This limitation was addressed by combining Mouse Genome Informatics with human genomewide association studies of kidney function. Genes for which mouse models showed abnormal renal physiology, morphology, glomerular filtration rate (GFR), or urinary albumin-to-creatinine ratio were identified from Mouse Genome Informatics. The corresponding human orthologs were then evaluated for GFR-associated single-nucleotide polymorphisms in 133,814 individuals and urinary albumin-to-creatinine ratio-associated SNPs in 54,451 individuals in genome-wide association studies meta-analysis of the CKDGen Consortium. After multiple testing corrections, significant associations with estimated GFR in humans were identified for single-nucleotide polymorphisms in 2, 7, and 17 genes causing abnormal GFR, abnormal physiology, and abnormal morphology in mice, respectively. Genes identified for abnormal kidney morphology showed significant enrichment for estimated GFR-associated single-nucleotide polymorphisms. In total, 19 genes contained variants associated with estimated GFR or the urinary albumin-to-creatinine ratio of which 16 mapped into previously reported genomewide significant loci. CYP26A1 and BMP4 emerged as novel signals subsequently validated in a large, independent study. An additional gene, CYP24A1, was discovered after conditioning on a published nearby association signal. Thus, our novel approach to combine comprehensive mouse phenotype information with human genomewide association studies data resulted in the identification of candidate genes for kidney disease pathogenesis.

Bayesian analysis of censored response data in family-based genetic association studies.

Biomarkers are subject to censoring whenever some measurements are not quantifiable given a laboratory detection limit. Methods for handling censoring have received less attention in genetic epidemiology, and censored data are still often replaced with a fixed value. We compared different strategies for handling a left-censored continuous biomarker in a family-based study, where the biomarker is tested for association with a genetic variant, S, adjusting for a covariate, X. Allowing different correlations between X and S, we compared simple substitution of censored observations with the detection limit followed by a linear mixed effect model (LMM), Bayesian model with noninformative priors, Tobit model with robust standard errors, the multiple imputation (MI) with and without S in the imputation followed by a LMM. Our comparison was based on real and simulated data in which 20% and 40% censoring were artificially induced. The complete data were also analyzed with a LMM. In the MICROS study, the Bayesian model gave results closer to those obtained with the complete data. In the simulations, simple substitution was always the most biased method, the Tobit approach gave the least biased estimates at all censoring levels and correlation values, the Bayesian model and both MI approaches gave slightly biased estimates but smaller root mean square errors. On the basis of these results the Bayesian approach is highly recommended for candidate gene studies; however, the computationally simpler Tobit and the MI without S are both good options for genome-wide studies.

A Prospective Nonrandomized Study on Carotid Surgery Performed under General Anesthesia without Intraoperative Cerebral Monitoring.

BACKGROUND: The purpose of this study was to assess our experience of carotid surgery habitually performed under general anesthesia without intraoperative intracerebral monitoring, and following a pre-established perioperative protocol, which includes extensive use of an intraoperative shunt (IOS). METHODS: This study included 311 consecutive carotid operations performed over 32 months. This patient cohort represents 14% of our total experience in carotid surgery (2219 operations, major stroke/mortality rate: 1.4%). The IOS was inserted routinely in the presence of intraoperative blood pressure instability during cross-clamping and when the predictable clamping time might have exceeded 20 minutes. A moderate and stable hypertension was maintained throughout surgery without IOS. RESULTS: Overall, 120 (38.6%) endarterectomies were performed with primary closure, 73 (23.5%) with eversion technique, 113 (36.3%) with patch angioplasty, and 5 (1.6%) with other techniques. Out of 113 patch angioplasties, 111 (98.2%) were performed with an IOS. This was utilized in only 3 cases of direct carotid reconstructions or other carotid endarterectomy techniques (1.5%). Overall, the IOS placement rate was 36.7%. Postoperatively, 2 major strokes (.64%), 2 minor strokes (.64%), 4 hyperperfusion syndromes (1.3%), and no mortality were recorded. No cases of cross-clamp ischemia/shunt-related perioperative strokes were observed. CONCLUSIONS: The low perioperative stroke rate reported in this prospective study proves the advantages of wide use of IOS during carotid surgery. This coupled with a large experience in carotid surgery and close monitoring and support of blood pressure, are the major determinants of these results that demonstrate the low risk of shunt-related complications for surgeons who regularly utilize an IOS.

Genome-wide association study of kidney function decline in individuals of European descent.

Genome-wide association studies (GWASs) have identified multiple loci associated with cross-sectional eGFR, but a systematic genetic analysis of kidney function decline over time is missing. Here we conducted a GWAS meta-analysis among 63,558 participants of European descent, initially from 16 cohorts with serial kidney function measurements within the CKDGen Consortium, followed by independent replication among additional participants from 13 cohorts. In stage 1 GWAS meta-analysis, single-nucleotide polymorphisms (SNPs) at MEOX2, GALNT11, IL1RAP, NPPA, HPCAL1, and CDH23 showed the strongest associations for at least one trait, in addition to the known UMOD locus, which showed genome-wide significance with an annual change in eGFR. In stage 2 meta-analysis, the significant association at UMOD was replicated. Associations at GALNT11 with Rapid Decline (annual eGFR decline of 3 ml/min per 1.73 m(2) or more), and CDH23 with eGFR change among those with CKD showed significant suggestive evidence of replication. Combined stage 1 and 2 meta-analyses showed significance for UMOD, GALNT11, and CDH23. Morpholino knockdowns of galnt11 and cdh23 in zebrafish embryos each had signs of severe edema 72 h after gentamicin treatment compared with controls, but no gross morphological renal abnormalities before gentamicin administration. Thus, our results suggest a role in the deterioration of kidney function for the loci GALNT11 and CDH23, and show that the UMOD locus is significantly associated with kidney function decline.

The Cooperative Health Research in South Tyrol (CHRIS) study: rationale, objectives, and preliminary results.

The Cooperative Health Research In South Tyrol (CHRIS) study is a population-based study with a longitudinal lookout to investigate the genetic and molecular basis of age-related common chronic conditions and their interaction with life style and environment in the general population. All adults of the middle and upper Vinschgau/Val Venosta are invited, while 10,000 participants are anticipated by mid-2017. Family participation is encouraged for complete pedigree reconstruction and disease inheritance mapping. After a pilot study on the compliance with a paperless assessment mode, computer-assisted interviews have been implemented to screen for conditions of the cardiovascular, endocrine, metabolic, genitourinary, nervous, behavioral, and cognitive system. Fat intake, cardiac health, and tremor are assessed instrumentally. Nutrient intake, physical activity, and life-course smoking are measured semi-quantitatively. Participants are phenotyped for 73 blood and urine parameters and 60 aliquots per participant are biobanked (cryo-preserved urine, DNA, and whole and fractionated blood). Through liquid-chromatography mass-spectrometry analysis, metabolite profiling of the mitochondrial function is assessed. Samples are genotyped on 1 million variants with the Illumina HumanOmniExpressExome array and the first data release including 4570 fully phenotyped and genotyped samples is now available for analysis. Participants' follow-up is foreseen 6 years after the first visit. The target population is characterized by long-term social stability and homogeneous environment which should both favor the identification of enriched genetic variants. The CHRIS cohort is a valuable resource to assess the contribution of genomics, metabolomics, and environmental factors to human health and disease. It is awaited that this will result in the identification of novel molecular targets for disease prevention and treatment.