mtDNA-Server 2: advancing mitochondrial DNA analysis through highly parallelized data processing and interactive analytics.

Over the past decade, mtDNA-Server established itself as one of the most widely used variant calling web-services for human mitochondrial genomes. The service accepts sequencing data in BAM format and returns an annotated variant analysis report for both homoplasmic and heteroplasmic variants. In this work we present mtDNA-Server 2, which includes several new features highly requested by the community. Most importantly, it includes (a) the integration of a novel variant calling mode that accurately call insertions, deletions and single nucleotide variants at once, (b) the integration of additional quality control and input validation modules, (c) a method to estimate the required coverage to minimize false positives and (d) an interactive analytics dashboard. Furthermore, we migrated the complete analysis workflow to the Nextflow workflow manager for improved parallelization, reproducibility and local execution. Recognizing the importance of insertions and deletions as well as offering novel quality control, validation and reporting features, mtDNA-Server 2 provides researchers and clinicians a new state-of-the-art analysis platform for interpreting mitochondrial genomes. mtDNA-Server 2 is available via mitoverse, our analysis platform that offers a centralized place for mtDNA analysis in the cloud. The web-service, source code and its documentation are freely accessible at https://mitoverse.i-med.ac.at.

Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers.

Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.

Meta-imputation: An efficient method to combine genotype data after imputation with multiple reference panels.

Genotype imputation is an integral tool in genome-wide association studies, in which it facilitates meta-analysis, increases power, and enables fine-mapping. With the increasing availability of whole-genome-sequence datasets, investigators have access to a multitude of reference-panel choices for genotype imputation. In principle, combining all sequenced whole genomes into a single large panel would provide the best imputation performance, but this is often cumbersome or impossible due to privacy restrictions. Here, we describe meta-imputation, a method that allows imputation results generated using different reference panels to be combined into a consensus imputed dataset. Our meta-imputation method requires small changes to the output of existing imputation tools to produce necessary inputs, which are then combined using dynamically estimated weights that are tailored to each individual and genome segment. In the scenarios we examined, the method consistently outperforms imputation using a single reference panel and achieves accuracy comparable to imputation using a combined reference panel.

Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing.

Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r2 > 0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF > 5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.

Haplogrep 3 - an interactive haplogroup classification and analysis platform.

Over the last decade, Haplogrep has become a standard tool for haplogroup classification in the field of human mitochondrial DNA and is widely used by medical, forensic, and evolutionary researchers. Haplogrep scales well for thousands of samples, supports many file formats and provides an intuitive graphical web interface. Nevertheless, the currently available version has limitations when applying it to large biobank-scale data. In this paper, we present a major upgrade to the software by adding (a) haplogroup summary statistics and variant annotations from various publicly available genome databases, (b) an interface to connect new phylogenetic trees, (c) a new state-of-the-art web framework managing large scale data, (d) algorithmic adaptions to improve FASTA classification using BWA-specific alignment rules and (e) a pre-classification quality control step for VCF samples. These improvements will give researchers the opportunity to classify thousands of samples as usual but providing additional ways to investigate the dataset directly in the browser. The web service and its documentation can be accessed freely without any registration at https://haplogrep.i-med.ac.at.

Contamination detection in sequencing studies using the mitochondrial phylogeny.

Within-species contamination is a major issue in sequencing studies, especially for mitochondrial studies. Contamination can be detected by analyzing the nuclear genome or by inspecting polymorphic sites in the mitochondrial genome (mtDNA). Existing methods using the nuclear genome are computationally expensive, and no appropriate tool for detecting sample contamination in large-scale mtDNA data sets is available. Here we present haplocheck, a tool that requires only the mtDNA to detect contamination in both targeted mitochondrial and whole-genome sequencing studies. Our in silico simulations and amplicon mixture experiments indicate that haplocheck detects mtDNA contamination accurately and is independent of the phylogenetic distance within a sample mixture. By applying haplocheck to The 1000 Genomes Project Consortium data, we further evaluate the application of haplocheck as a fast proxy tool for nDNA-based contamination detection using the mtDNA and identify the mitochondrial copy number within a mixture as a critical component for the overall accuracy. The haplocheck tool is available both as a command-line tool and as a cloud web service producing interactive reports that facilitates the navigation through the phylogeny of contaminated samples.

Apolipoprotein A-IV concentrations and cancer in a large cohort of chronic kidney disease patients: results from the GCKD study.

BACKGROUND: Chronic kidney disease (CKD) is highly connected to inflammation and oxidative stress. Both favour the development of cancer in CKD patients. Serum apolipoprotein A-IV (apoA-IV) concentrations are influenced by kidney function and are an early marker of kidney impairment. Besides others, it has antioxidant and anti-inflammatory properties. Proteomic studies and small case-control studies identified low apoA-IV as a biomarker for various forms of cancer; however, prospective studies are lacking. We therefore investigated whether serum apoA-IV is associated with cancer in the German Chronic Kidney Disease (GCKD) study. METHODS: These analyses include 5039 Caucasian patients from the prospective GCKD cohort study followed for 6.5 years. Main inclusion criteria were an eGFR of 30-60 mL/min/1.73m2 or an eGFR > 60 mL/min/1.73m2 in the presence of overt proteinuria. RESULTS: Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dL (median 27.6 mg/dL). 615 patients had a history of cancer before the enrolment into the study. ApoA-IV concentrations above the median were associated with a lower odds for a history of cancer (OR = 0.79, p = 0.02 when adjusted age, sex, smoking, diabetes, BMI, albuminuria, statin intake, and eGFRcreatinine). During follow-up 368 patients developed an incident cancer event and those with apoA-IV above the median had a lower risk (HR = 0.72, 95%CI 0.57-0.90, P = 0.004). Finally, 62 patients died from such an incident cancer event and each 10 mg/dL higher apoA-IV concentrations were associated with a lower risk for fatal cancer (HR = 0.62, 95%CI 0.44-0.88, P = 0.007). CONCLUSIONS: Our data indicate an association of high apoA-IV concentrations with reduced frequencies of a history of cancer as well as incident fatal and non-fatal cancer events in a large cohort of patients with CKD.

Interactive exploration of adverse events and multimorbidity in CKD.

BACKGROUND AND HYPOTHESIS: Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality, and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study. METHODS: The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73m2 and an overt proteinuria. Cardio-, cerebro- and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology. RESULTS: Over a median of 6.5 years, 10 271 events occurred in total and 680 participants (13.0%) died while 2947 participants (56.5%) experienced any event. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology, and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney), and 66.0 (infection). Participants with diabetic kidney disease and men were more prone to experiencing events. CONCLUSION: This comprehensive explorative tool to visualize adverse events (https://gckd.diz.uk-erlangen.de/), their combination, mortality, and multimorbidity among persons with CKD may manifest as a valuable resource for patient care, identification of high-risk groups, health services, and public health policy planning.

Filling the gap: Genetic risk assessment in hypercholesterolemia using LDL-C and LPA genetic scores.

Routine genetic testing in hypercholesterolemia patients reveals a causative monogenic variant in less than 50% of affected individuals. Incomplete genetic characterization is partly due to polygenic factors influencing low-density-lipoprotein-cholesterol (LDL-C). Additionally, functional variants in the LPA gene affect lipoprotein(a)-associated cholesterol concentrations but are difficult to determine due to the complex structure of the LPA gene. In this study we examined whether complementing standard sequencing with the analysis of genetic scores associated with LDL-C and Lp(a) concentrations improves the diagnostic output in hypercholesterolemia patients. 1.020 individuals including 252 clinically diagnosed hypercholesterolemia patients from the FH Register Austria were analyzed by massive-parallel-sequencing of candidate genes combined with array genotyping, identifying nine novel variants in LDLR. For each individual, validated genetic scores associated with elevated LDL-C and Lp(a) were calculated based on imputed genotypes. Integrating these scores especially the score for Lp(a) increased the proportion of individuals with a clearly defined disease etiology to 68.8% compared to 46.6% in standard genetic testing. The study highlights the major role of Lp(a) in disease etiology in clinically diagnosed hypercholesterolemia patients, of which parts are misclassified. Screening for monogenic causes of hypercholesterolemia and genetic scores for LDL-C and Lp(a) permits more precise diagnosis, allowing individualized treatment.

The kringle IV type 2 domain variant 4925G>A causes the elusive association signal of the LPA pentanucleotide repeat.

Lipoprotein(a) [Lp(a)] concentrations are regulated by the LPA gene mainly via the large kringle IV-type 2 (KIV-2) copy number variation and multiple causal variants. Early studies suggested an effect of long pentanucleotide repeat (PNR) alleles (10 and 11 repeats, PNR10 and PNR11) in the LPA promoter on gene transcription and found an association with lower Lp(a). Subsequent in vitro studies showed no effects on mRNA transcription, but the association with strongly decreased Lp(a) remained consistent. We investigated the isolated and combined effect of PNR10, PNR11, and the frequent splice site variant KIV-2 4925G>A on Lp(a) concentrations in the Cooperative Health Research in the Region of Augsburg F4 study by multiple quantile regression in single-SNP and joint models. Data on Lp(a), apolipoprotein(a) Western blot isoforms, and variant genotypes were available for 2,858 individuals. We found a considerable linkage disequilibrium between KIV-2 4925G>A and the alleles PNR10 and PNR11. In single-variant analysis adjusted for age, sex, and the shorter apo(a) isoform, we determined that both PNR alleles were associated with a highly significant Lp(a) decrease (PNR10: ß = -14.43 mg/dl, 95% CI: -15.84, -13.02, P = 3.33e-84; PNR11: ß = -17.21 mg/dl, 95% CI: -20.19, -14.23, P = 4.01e-29). However, a joint model, adjusting the PNR alleles additionally for 4925G>A, abolished the effect on Lp(a) (PNR10: ß = +0.44 mg/dl, 95% CI: -1.73, 2.60, P = 0.69; PNR11: ß = -1.52 mg/dl, 95% CI: -6.05, 3.00, P = 0.51). Collectively, we conclude that the previously reported Lp(a) decrease observed in pentanucleotide alleles PNR10 or PNR11 carriers results from a linkage disequilibrium with the frequent splicing mutation KIV-2 4925G>A.

A Family and a Genome-Wide Polygenic Risk Score Are Independently Associated With Stroke in a Population-Based Study.

BACKGROUND: Positive family history and genetic risk scores have been shown to independently capture those individuals with high risk for stroke. The aim of our study was to evaluate the amount of shared information between family history and genetic risk and to investigate their combined effect on the association with prevalent and incident stroke cases. METHODS: We obtained a family risk score (FamRS), weighted for disease onset and family size as well as genome-wide polygenic risk score (PGS) including over 3.2 million single-nucleotide polymorphisms in the population-based prospective KORA F3 (Cooperative Health Research in the Region of Augsburg) study (n=3071) from Southern Germany. FamRS and PGS were evaluated separately and combined. The measures were once treated as continuous variables but also divided in the highest 20%, 10%, 5%, and 1% percentiles. Odds ratios via logistic regression and hazard ratios via Cox regression were estimated. A stroke event was defined as a hospitalization for stroke that was self-reported in a standardized interview by certified and supervised personnel. RESULTS: The FamRS outperformed other simplified family measures such as affected parents or number of affected family members. FamRS and PGS were not correlated, and no individuals were observed with both very high FamRS and very high PGS (top 1% percentile). In a combined model, both FamRS and PGS were independently from each other associated with risk of stroke, also independent of other traditional risk factors (p [FamRS]=0.02, p [PGS]=0.005). Individuals in the top 1% of either FamRS or PGS were found to have >5-fold risk for stroke (odds ratios, 5.82 [95% CI, 2.08-14]; P=0.0002). The results for incident stroke events showed the same trend but were not significant. CONCLUSIONS: Our study shows that a family risk score and PGS capture different information concerning individual stroke risk. Combining the risk measures FamRS and PGS increases predictive power, as demonstrated in a population-based study.

Lipoprotein(a) and SARS-CoV-2 infections: Susceptibility to infections, ischemic heart disease and thromboembolic events.

BACKGROUND: Comorbidities including ischemic heart disease (IHD) worsen outcomes after SARS-CoV-2 infections. High lipoprotein(a) [Lp(a)] concentrations are a strong risk factor for IHD and possibly for thromboembolic events. We therefore evaluated whether SARS-CoV-2 infections modify the risk of high Lp(a) concentrations for IHD or thromboembolic events during the first 8.5 months follow-up of the pandemic. METHOD: Cohort study using data from the UK Biobank during the SARS-CoV-2 pandemic. Baseline Lp(a) was compared between SARS-CoV-2 positive patients and the population controls. RESULTS: SARS-CoV-2 positive patients had Lp(a) concentrations similar to the population controls. The risk for IHD increased with higher Lp(a) concentrations in both, the population controls (n = 435,104) and SARS-CoV-2 positive patients (n = 6937). The causality of the findings was supported by a genetic risk score for Lp(a). A SARS-CoV-2 infection modified the association with a steeper increase in risk for infected patients (interaction p-value = 0.03). Although SARS-CoV-2 positive patients had a five-times higher frequency of thromboembolic events compared to the population controls (1.53% vs. 0.31%), the risk was not influenced by Lp(a). CONCLUSIONS: SARS-CoV-2 infections enforce the association between high Lp(a) and IHD but the risk for thromboembolic events is not influenced by Lp(a).

Apolipoprotein A-IV concentrations and clinical outcomes in a large chronic kidney disease cohort: Results from the GCKD study.

BACKGROUND: Chronic kidney disease (CKD) represents a chronic proinflammatory state and is associated with very high cardiovascular risk. Apolipoprotein A-IV (apoA-IV) has antiatherogenic, antioxidative, anti-inflammatory and antithrombotic properties and levels increase significantly during the course of CKD. OBJECTIVES: We aimed to investigate the association between apoA-IV and all-cause mortality and cardiovascular outcomes in the German Chronic Kidney Disease study. METHODS: This was a prospective cohort study including 5141 Caucasian patients with available apoA-IV measurements and CKD. The majority of the patients had an estimated glomerular filtration rate (eGFR) of 30-60 ml/min/1.73m2 or an eGFR >60 ml/min/1.73m2 in the presence of overt proteinuria. Median follow-up was 6.5 years. The association of apoA-IV with comorbidities at baseline and endpoints during follow-up was modelled adjusting for major confounders. RESULTS: Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dl. Patients in the highest apoA-IV quartile had the lowest high-sensitivity C-reactive protein values despite the highest prevalence of diabetes, albuminuria and the lowest eGFR. Each 10 mg/dl higher apoA-IV translated into lower odds of prevalent cardiovascular disease (1289 cases, odds ratio = 0.80, 95% confidence interval [CI] 0.72-0.86, p = 0.0000003). During follow-up, each 10 mg/dl higher apoA-IV was significantly associated with a lower risk for all-cause mortality (600 cases, hazard ratio [HR] = 0.81, 95% CI 0.73-0.89, p = 0.00004), incident major adverse cardiovascular events (506 cases, HR = 0.88, 95% CI 0.79-0.99, p = 0.03) and death or hospitalizations due to heart failure (346 cases, HR = 0.84, 95% CI 0.73-0.96, p = 0.01). CONCLUSIONS: These data support a link between elevated apoA-IV concentrations and reduced inflammation in moderate CKD. ApoA-IV appears to be an independent risk marker for reduced all-cause mortality, cardiovascular events and heart failure in a large cohort of patients with CKD.

Analyzing Low-Level mtDNA Heteroplasmy-Pitfalls and Challenges from Bench to Benchmarking.

Massive parallel sequencing technologies are promising a highly sensitive detection of low-level mutations, especially in mitochondrial DNA (mtDNA) studies. However, processes from DNA extraction and library construction to bioinformatic analysis include several varying tasks. Further, there is no validated recommendation for the comprehensive procedure. In this study, we examined potential pitfalls on the sequencing results based on two-person mtDNA mixtures. Therefore, we compared three DNA polymerases, six different variant callers in five mixtures between 50% and 0.5% variant allele frequencies generated with two different amplification protocols. In total, 48 samples were sequenced on Illumina MiSeq. Low-level variant calling at the 1% variant level and below was performed by comparing trimming and PCR duplicate removal as well as six different variant callers. The results indicate that sensitivity, specificity, and precision highly depend on the investigated polymerase but also vary based on the analysis tools. Our data highlight the advantage of prior standardization and validation of the individual laboratory setup with a DNA mixture model. Finally, we provide an artificial heteroplasmy benchmark dataset that can help improve somatic variant callers or pipelines, which may be of great interest for research related to cancer and aging.

Results from the German Chronic Kidney Disease (GCKD) study support association of relative telomere length with mortality in a large cohort of patients with moderate chronic kidney disease.

Telomere length is known to be inversely associated with aging and has been proposed as a marker for aging-related diseases. Telomere attrition can be accelerated by oxidative stress and inflammation, both commonly present in patients with chronic kidney disease. Here, we investigated whether relative telomere length is associated with mortality in a large cohort of patients with chronic kidney disease stage G3 and A1-3 or G1-2 with overt proteinuria (A3) at enrollment. Relative telomere length was quantified in peripheral blood by a quantitative PCR method in 4,955 patients from the GCKD study, an ongoing prospective observational cohort. Complete four-year follow-up was available from 4,926 patients in whom we recorded 354 deaths. Relative telomere length was a strong and independent predictor of all-cause mortality. Each decrease of 0.1 relative telomere length unit was highly associated with a 14% increased risk of death (hazard ratio1.14 [95% confidence interval 1.06-1.22]) in a model adjusted for age, sex, baseline eGFR, urine albumin/creatinine ratio, diabetes mellitus, prevalent cardiovascular disease, LDL-cholesterol, HDL-cholesterol, smoking, body mass index, systolic and diastolic blood pressure, C-reactive protein and serum albumin. This translated to a 75% higher risk for those in the lowest compared to the highest quartile of relative telomere length. The association was mainly driven by 117 cardiovascular deaths (1.20 [1.05-1.35]) as well as 67 deaths due to infections (1.27 [1.07-1.50]). Thus, our findings support an association of shorter telomere length with all-cause mortality, cardiovascular mortality and death due to infections in patients with moderate chronic kidney disease.

Association of changes in bone mineral parameters with mortality in haemodialysis patients: insights from the ARO cohort.

BACKGROUND: There is little information in haemodialysis (HD) patients on whether temporal changes in serum calcium, phosphate or intact parathyroid hormone (iPTH) are associated with mortality. METHODS: We analysed associations of phosphate, total calcium and iPTH with all-cause and cardiovascular mortality in 8817 incident HD patients from the European second Analyzing Data, Recognizing Excellence and Optimizing Outcomes (AROii) cohort enrolled in 2007-09, which were prospectively followed for a median of 3 years, using time-dependent Cox proportional hazards models. We evaluated changes in risk over time depending on changes in phosphate, calcium or iPTH. RESULTS: The association of phosphate and iPTH with all-cause mortality was U-shaped, with the lowest risk ranges between 1.20 and 1.89 mmol/L for phosphate and between 239 and 710 ng/L for iPTH. For total calcium, the associations were J-shaped, with an increased risk for all-cause mortality at levels >2.36 mmol/L. Lowest risk ranges for cardiovascular mortality did not change markedly for all three parameters. If iPTH was below the lowest risk range at baseline (iPTH <239 ng/L), a subsequent increase in levels was associated with improved survival. For phosphate, an increase or decrease out of the lowest risk range was associated with increased mortality risk. For calcium, this was only the case when the values increased above the lowest risk range. CONCLUSION: In the AROii cohort, the ranges of bone mineral biomarkers associated with the lowest mortality ranges were largely consistent with the current Kidney Disease: Improving Global Outcomes chronic kidney disease-mineral and bone disorder guideline recommendations. Allowing a suppressed iPTH to increase was associated with a lower mortality, whereas shifts of phosphate or calcium outside the lowest risk range increased mortality.

A comprehensive map of single-base polymorphisms in the hypervariable LPA kringle IV type 2 copy number variation region.

Lipoprotein (a) [Lp(a)] concentrations are among the strongest genetic risk factors for cardiovascular disease and present pronounced interethnic and interindividual differences. Approximately 90% of Lp(a) variance is controlled by the LPA gene, which contains a 5.6-kb-large copy number variation [kringle IV type 2 (KIV-2) repeat] that generates >40 protein isoforms. Variants within the KIV-2 region are not called in common sequencing projects, leaving up to 70% of the LPA coding region currently unaddressed. To completely assess the variability in LPA, we developed a sequencing strategy for this region and report here the first map of genetic variation in the KIV-2 region, a comprehensively evaluated ultradeep sequencing protocol, and an easy-to-use variant analysis pipeline. We sequenced 123 Central-European individuals and reanalyzed public data of 2,504 individuals from 26 populations. We found 14 different loss-of-function and splice-site mutations, as well as >100, partially even common, missense variants. Some coding variants were frequent in one population but absent in others. This provides novel candidates to explain the large ethnic and individual differences in Lp(a) concentrations. Importantly, our approach and pipeline are also applicable to other similar copy number variable regions, allowing access to regions that are not captured by common genome sequencing.

Mitochondrial DNA copy number is associated with mortality and infections in a large cohort of patients with chronic kidney disease.

Damage of mitochondrial DNA (mtDNA) with reduction in copy number has been proposed as a biomarker for mitochondrial dysfunction and oxidative stress. Chronic kidney disease (CKD) is associated with increased mortality and risk of cardiovascular disease, but the underlying mechanisms remain incompletely understood. Here we investigated the prognostic role of mtDNA copy number for cause-specific mortality in 4812 patients from the German Chronic Kidney Disease study, an ongoing prospective observational national cohort study of patients with CKD stage G3 and A1-3 or G1-2 with overt proteinuria (A3) at enrollment. MtDNA was quantified in whole blood using a plasmid-normalized PCR-based assay. At baseline, 1235 patients had prevalent cardiovascular disease. These patients had a significantly lower mtDNA copy number than patients without cardiovascular disease (fully-adjusted model: odds ratio 1.03, 95% confidence interval [CI] 1.01-1.05 per 10 mtDNA copies decrease). After four years of follow-up, we observed a significant inverse association between mtDNA copy number and all-cause mortality, adjusted for kidney function and cardiovascular disease risk factors (hazard ratio 1.37, 95% CI 1.09-1.73 for quartile 1 compared to quartiles 2-4). When grouped by causes of death, estimates pointed in the same direction for all causes but in a fully-adjusted model decreased copy numbers were significantly lower only in infection-related death (hazard ratio 1.82, 95% CI 1.08-3.08). A similar association was observed for hospitalizations due to infections in 644 patients (hazard ratio 1.19, 95% CI 1.00-1.42 in the fully-adjusted model). Thus, our data support a role of mitochondrial dysfunction in increased cardiovascular disease and mortality risks as well as susceptibility to infections in patients with CKD.

A genome-wide association meta-analysis on apolipoprotein A-IV concentrations.

Apolipoprotein A-IV (apoA-IV) is a major component of HDL and chylomicron particles and is involved in reverse cholesterol transport. It is an early marker of impaired renal function. We aimed to identify genetic loci associated with apoA-IV concentrations and to investigate relationships with known susceptibility loci for kidney function and lipids. A genome-wide association meta-analysis on apoA-IV concentrations was conducted in five population-based cohorts (n = 13,813) followed by two additional replication studies (n = 2,267) including approximately 10 M SNPs. Three independent SNPs from two genomic regions were significantly associated with apoA-IV concentrations: rs1729407 near APOA4 (P = 6.77 × 10 - 44), rs5104 in APOA4 (P = 1.79 × 10-24) and rs4241819 in KLKB1 (P = 5.6 × 10-14). Additionally, a look-up of the replicated SNPs in downloadable GWAS meta-analysis results was performed on kidney function (defined by eGFR), HDL-cholesterol and triglycerides. From these three SNPs mentioned above, only rs1729407 showed an association with HDL-cholesterol (P = 7.1 × 10 - 07). Moreover, weighted SNP-scores were built involving known susceptibility loci for the aforementioned traits (53, 70 and 38 SNPs, respectively) and were associated with apoA-IV concentrations. This analysis revealed a significant and an inverse association for kidney function with apoA-IV concentrations (P = 5.5 × 10-05). Furthermore, an increase of triglyceride-increasing alleles was found to decrease apoA-IV concentrations (P = 0.0078). In summary, we identified two independent SNPs located in or next the APOA4 gene and one SNP in KLKB1 The association of KLKB1 with apoA-IV suggests an involvement of apoA-IV in renal metabolism and/or an interaction within HDL particles. Analyses of SNP-scores indicate potential causal effects of kidney function and by lesser extent triglycerides on apoA-IV concentrations.