Publications by authors named "Karsten Suhre"

226 Publications

maplet: An extensible R toolbox for modular and reproducible metabolomics pipelines.

Bioinformatics 2021 Oct 25. Epub 2021 Oct 25.

Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.

: This paper presents maplet, an open-source R package for the creation of highly customizable, fully reproducible statistical pipelines for metabolomics data analysis. It builds on the SummarizedExperiment data structure to create a centralized pipeline framework for storing data, analysis steps, results, and visualizations. maplet's key design feature is its modularity, which offers several advantages, such as ensuring code quality through the maintenance of individual functions and promoting collaborative development by removing technical barriers to code contribution. With over 90 functions, the package includes a wide range of functionalities, covering many widely used statistical approaches and data visualization techniques.

Availability: The maplet package is implemented in R and freely available at https://github.com/krumsieklab/maplet.
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http://dx.doi.org/10.1093/bioinformatics/btab741DOI Listing
October 2021

SGI: Automatic clinical subgroup identification in omics datasets.

Bioinformatics 2021 Sep 16. Epub 2021 Sep 16.

Department of Physiology and Biophysics, Institute for Computational Biomedicine.

: The 'Subgroup Identification' (SGI) toolbox provides an algorithm to automatically detect clinical subgroups of samples in large-scale omics datasets. It is based on hierarchical clustering trees in combination with a specifically designed association testing and visualization framework that can process an arbitrary number of clinical parameters and outcomes in a systematic fashion. A multi-block extension allows for the simultaneous use of multiple omics datasets on the same samples. In this paper, we first describe the functionality of the toolbox and then demonstrate its capabilities through application examples on a type 2 diabetes metabolomics study as well as two copy number variation datasets from The Cancer Genome Atlas.

Availability: SGI is an open-source package implemented in R. Package source codes and hands-on tutorials are available at https://github.com/krumsieklab/sgi. The QMdiab metabolomics data is included in the package and can be downloaded from https://doi.org/10.6084/m9.figshare.5904022.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btab656DOI Listing
September 2021

Kidney Allograft Function Is a Confounder of Urine Metabolite Profiles in Kidney Allograft Recipients.

Metabolites 2021 Aug 11;11(8). Epub 2021 Aug 11.

Division of Nephrology and Hypertension, Department of Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY 10065, USA.

Noninvasive biomarkers of kidney allograft status can help minimize the need for standard of care kidney allograft biopsies. Metabolites that are measured in the urine may inform about kidney function and health status, and potentially identify rejection events. To test these hypotheses, we conducted a metabolomics study of biopsy-matched urine cell-free supernatants from kidney allograft recipients who were diagnosed with two major types of acute rejections and no-rejection controls. Non-targeted metabolomics data for 674 metabolites and 577 unidentified molecules, for 192 biopsy-matched urine samples, were analyzed. Univariate and multivariate analyses identified metabolite signatures for kidney allograft rejection. The replicability of a previously developed urine metabolite signature was examined. Our study showed that metabolite profiles can serve as biomarkers for discriminating rejection biopsies from biopsies without rejection features, but also revealed a role of estimated Glomerular Filtration Rate (eGFR) as a major confounder of the metabolite signal.
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http://dx.doi.org/10.3390/metabo11080533DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399888PMC
August 2021

Salivary metabolites associated with a 5-year tooth loss identified in a population-based setting.

BMC Med 2021 07 14;19(1):161. Epub 2021 Jul 14.

Department of Restorative Dentistry, Periodontology, Endodontology, and Preventive and Pediatric Dentistry, University Medicine Greifswald, Fleischmannstr. 42, 17475, Greifswald, Germany.

Background: Periodontitis is among the most common chronic diseases worldwide, and it is one of the main reasons for tooth loss. Comprehensive profiling of the metabolite content of the saliva can enable the identification of novel pathways associated with periodontitis and highlight non-invasive markers to facilitate time and cost-effective screening efforts for the presence of periodontitis and the prediction of tooth loss.

Methods: We first investigated cross-sectional associations of 13 oral health variables with saliva levels of 562 metabolites, measured by untargeted mass spectrometry among a sub-sample (n = 938) of the Study of Health in Pomerania (SHIP-2) using linear regression models adjusting for common confounders. We took forward any candidate metabolite associated with at least two oral variables, to test for an association with a 5-year tooth loss over and above baseline oral health status using negative binomial regression models.

Results: We identified 84 saliva metabolites that were associated with at least one oral variable cross-sectionally, for a subset of which we observed robust replication in an independent study. Out of 34 metabolites associated with more than two oral variables, baseline saliva levels of nine metabolites were positively associated with a 5-year tooth loss. Across all analyses, the metabolites 2-pyrrolidineacetic acid and butyrylputrescine were the most consistent candidate metabolites, likely reflecting oral dysbiosis. Other candidate metabolites likely reflected tissue destruction and cell proliferation.

Conclusions: Untargeted metabolic profiling of saliva replicated metabolic signatures of periodontal status and revealed novel metabolites associated with periodontitis and future tooth loss.
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http://dx.doi.org/10.1186/s12916-021-02035-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278731PMC
July 2021

Plasma Proteomics of Renal Function: A Trans-ethnic Meta-analysis and Mendelian Randomization Study.

J Am Soc Nephrol 2021 Jun 16. Epub 2021 Jun 16.

M Prunotto, School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.

Background: Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed.

Methods: A cross-sectional study of 993 plasma proteins among 2,882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified trans-ethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR .

Results: Fifty-seven plasma proteins were associated with eGFR, including one novel protein. Twenty-three of these were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR.

Conclusions: In a discovery-replication setting, we identified 57 proteins trans-ethnically associated with eGFR. The revealed causal relationships are an important stepping-stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.
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http://dx.doi.org/10.1681/ASN.2020071070DOI Listing
June 2021

Metabolic syndrome and the plasma proteome: from association to causation.

Cardiovasc Diabetol 2021 05 20;20(1):111. Epub 2021 May 20.

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.

Background: The metabolic syndrome (MetS), defined by the simultaneous clustering of cardio-metabolic risk factors, is a significant worldwide public health burden with an estimated 25% prevalence worldwide. The pathogenesis of MetS is not entirely clear and the use of molecular level data could help uncover common pathogenic pathways behind the observed clustering.

Methods: Using a highly multiplexed aptamer-based affinity proteomics platform, we examined associations between plasma proteins and prevalent and incident MetS in the KORA cohort (n = 998) and replicated our results for prevalent MetS in the HUNT3 study (n = 923). We applied logistic regression models adjusted for age, sex, smoking status, and physical activity. We used the bootstrap ranking algorithm of least absolute shrinkage and selection operator (LASSO) to select a predictive model from the incident MetS associated proteins and used area under the curve (AUC) to assess its performance. Finally, we investigated the causal effect of the replicated proteins on MetS using two-sample Mendelian randomization.

Results: Prevalent MetS was associated with 116 proteins, of which 53 replicated in HUNT. These included previously reported proteins like leptin, and new proteins like NTR domain-containing protein 2 and endoplasmic reticulum protein 29. Incident MetS was associated with 14 proteins in KORA, of which 13 overlap the prevalent MetS associated proteins with soluble advanced glycosylation end product-specific receptor (sRAGE) being unique to incident MetS. The LASSO selected an eight-protein predictive model with an (AUC = 0.75; 95% CI = 0.71-0.79) in KORA. Mendelian randomization suggested causal effects of three proteins on MetS, namely apolipoprotein E2 (APOE2) (Wald-Ratio = - 0.12, Wald-p = 3.63e-13), apolipoprotein B (APOB) (Wald-Ratio = - 0.09, Wald-p = 2.54e-04) and proto-oncogene tyrosine-protein kinase receptor (RET) (Wald-Ratio = 0.10, Wald-p = 5.40e-04).

Conclusions: Our findings offer new insights into the plasma proteome underlying MetS and identify new protein associations. We reveal possible casual effects of APOE2, APOB and RET on MetS. Our results highlight protein candidates that could potentially serve as targets for prevention and therapy.
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http://dx.doi.org/10.1186/s12933-021-01299-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138979PMC
May 2021

Evidence of Recombination Suppression Blocks on the Y Chromosome of Date Palm ().

Front Plant Sci 2021 20;12:634901. Epub 2021 Apr 20.

Genomics Laboratory, Weill Cornell Medicine in Qatar, Doha, Qatar.

The genus includes the fruit producing date palm tree among 14 species that are all dioecious. Females produce the fruit that are high in sugar content and used in multiple countries ranging from North Africa to South Asia, especially from the , , and species. While females produce the fruit, understanding of the genetic basis of sex control only began recently. Through genus-wide sequencing of males and females we recently identified three genes that are conserved in all males and absent in all females of the genus and confirmed an XY sex chromosome system. While our previous study focused on conservation of male-specific sequences at the genus-level, it would be of interest to better understand the spread of male-specific sequences away from the core conserved male genes on the Y chromosome during speciation. To this end, we enumerated male-specific 16 bp sequences using three male/female pairs from the western subpopulation of date palm and documented the density of these sequences in contigs of a phased date palm genome assembly. Here we show that male specific sequences in the date palm Y chromosome have likely spread in defined events that appear as blocks of varying density with significant changes in density between them. Collinearity of genes in these blocks with oil palm shows high synteny with chromosome 10 between megabase 15 and 23 and reveals that large sections of the date palm Y chromosome have maintained the ancestral structure even as recombination has stopped between X and Y.
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http://dx.doi.org/10.3389/fpls.2021.634901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093805PMC
April 2021

Deep sequencing of DNA from urine of kidney allograft recipients to estimate donor/recipient-specific DNA fractions.

PLoS One 2021 15;16(4):e0249930. Epub 2021 Apr 15.

Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.

Kidney transplantation is the treatment of choice for patients with end-stage kidney failure, but transplanted allograft could be affected by viral and bacterial infections and by immune rejection. The standard test for the diagnosis of acute pathologies in kidney transplants is kidney biopsy. However, noninvasive tests would be desirable. Various methods using different techniques have been developed by the transplantation community. But these methods require improvements. We present here a cost-effective method for kidney rejection diagnosis that estimates donor/recipient-specific DNA fraction in recipient urine by sequencing urinary cell DNA. We hypothesized that in the no-pathology stage, the largest tissue types present in recipient urine are donor kidney cells, and in case of rejection, a larger number of recipient immune cells would be observed. Extensive in-silico simulation was used to tune the sequencing parameters: number of variants and depth of coverage. Sequencing of DNA mixture from 2 healthy individuals showed the method is highly predictive (maximum error < 0.04). We then demonstrated the insignificant impact of familial relationship and ethnicity using an in-house and public database. Lastly, we performed deep DNA sequencing of urinary cell pellets from 32 biopsy-matched samples representing two pathology groups: acute rejection (AR, 11 samples) and acute tubular injury (ATI, 12 samples) and 9 samples with no pathology. We found a significant association between the donor/recipient-specific DNA fraction in the two pathology groups compared to no pathology (P = 0.0064 for AR and P = 0.026 for ATI). We conclude that deep DNA sequencing of urinary cells from kidney allograft recipients offers a noninvasive means of diagnosing acute pathologies in the human kidney allograft.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249930PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049329PMC
September 2021

Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19.

medRxiv 2021 Apr 7. Epub 2021 Apr 7.

Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target.
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http://dx.doi.org/10.1101/2021.04.01.21254789DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043484PMC
April 2021

Genome-wide investigation identifies a rare copy-number variant burden associated with human spina bifida.

Genet Med 2021 07 8;23(7):1211-1218. Epub 2021 Mar 8.

Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.

Purpose: Next-generation sequencing has implicated some risk variants for human spina bifida (SB), but the genome-wide contribution of structural variation to this complex genetic disorder remains largely unknown. We examined copy-number variant (CNV) participation in the genetic architecture underlying SB risk.

Methods: A high-confidence ensemble approach to genome sequences (GS) was benchmarked and employed for systematic detection of common and rare CNVs in two separate ancestry-matched SB case-control cohorts.

Results: SB cases were enriched with exon disruptive rare CNVs, 44% of which were under 10 kb, in both ancestral populations (P = 6.75 × 10; P = 7.59 × 10). Genes containing these disruptive CNVs fall into molecular pathways, supporting a role for these genes in SB. Our results expand the catalog of variants and genes with potential contribution to genetic and gene-environment interactions that interfere with neurulation, useful for further functional characterization.

Conclusion: This study underscores the need for genome-wide investigation and extends our previous threshold model of exonic, single-nucleotide variation toward human SB risk to include structural variation. Since GS data afford detection of CNVs with greater resolution than microarray methods, our results have important implications toward a more comprehensive understanding of the genetic risk and mechanisms underlying neural tube defect pathogenesis.
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http://dx.doi.org/10.1038/s41436-021-01126-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257499PMC
July 2021

Signal Transducer and Activator of Transcription 3 (STAT3) Suppresses STAT1/Interferon Signaling Pathway and Inflammation in Senescent Preadipocytes.

Antioxidants (Basel) 2021 Feb 23;10(2). Epub 2021 Feb 23.

Department of Microbiology and Immunology, Weill Cornell Medicine-Qatar (WCM-Q), Qatar Foundation, Doha 24144, Qatar.

Obesity promotes premature aging and dysfunction of white adipose tissue (WAT) through the accumulation of cellular senescence. The senescent cells burden in WAT has been linked to inflammation, insulin-resistance (IR), and type 2 diabetes (T2D). There is limited knowledge about molecular mechanisms that sustain inflammation in obese states. Here, we describe a robust and physiologically relevant in vitro system to trigger senescence in mouse 3T3-L1 preadipocytes. By employing transcriptomics analyses, we discovered up-regulation of key pro-inflammatory molecules and activation of interferon/signal transducer and activator of transcription (STAT)1/3 signaling in senescent preadipocytes, and expression of downstream targets was induced in epididymal WAT of obese mice, and obese human adipose tissue. To test the relevance of STAT1/3 signaling to preadipocyte senescence, we used Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated protein 9 (CRISPR/Cas9) technology to delete STAT1/3 and discovered that STAT1 promoted growth arrest and cooperated with cyclic Guanosine Monophosphate-Adenosine Monophosphate (GMP-AMP) synthase-stimulator of interferon genes (cGAS-STING) to drive the expression of interferon β (IFNβ), C-X-C motif chemokine ligand 10 (CXCL10), and interferon signaling-related genes. In contrast, we discovered that STAT3 was a negative regulator of STAT1/cGAS-STING signaling-it suppressed senescence and inflammation. These data provide insights into how STAT1/STAT3 signaling coordinates senescence and inflammation through functional interactions with the cGAS/STING pathway.
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http://dx.doi.org/10.3390/antiox10020334DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927067PMC
February 2021

Revealing the role of the human blood plasma proteome in obesity using genetic drivers.

Nat Commun 2021 02 24;12(1):1279. Epub 2021 Feb 24.

Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar.

Blood circulating proteins are confounded readouts of the biological processes that occur in different tissues and organs. Many proteins have been linked to complex disorders and are also under substantial genetic control. Here, we investigate the associations between over 1000 blood circulating proteins and body mass index (BMI) in three studies including over 4600 participants. We show that BMI is associated with widespread changes in the plasma proteome. We observe 152 replicated protein associations with BMI. 24 proteins also associate with a genome-wide polygenic score (GPS) for BMI. These proteins are involved in lipid metabolism and inflammatory pathways impacting clinically relevant pathways of adiposity. Mendelian randomization suggests a bi-directional causal relationship of BMI with LEPR/LEP, IGFBP1, and WFIKKN2, a protein-to-BMI relationship for AGER, DPT, and CTSA, and a BMI-to-protein relationship for another 21 proteins. Combined with animal model and tissue-specific gene expression data, our findings suggest potential therapeutic targets further elucidating the role of these proteins in obesity associated pathologies.
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http://dx.doi.org/10.1038/s41467-021-21542-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904950PMC
February 2021

Whole genome sequencing in the Middle Eastern Qatari population identifies genetic associations with 45 clinically relevant traits.

Nat Commun 2021 02 23;12(1):1250. Epub 2021 Feb 23.

College of Health and Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar.

Clinical laboratory tests play a pivotal role in medical decision making, but little is known about their genetic variability between populations. We report a genome-wide association study with 45 clinically relevant traits from the population of Qatar using a whole genome sequencing approach in a discovery set of 6218 individuals and replication in 7768 subjects. Trait heritability is more similar between Qatari and European populations (r = 0.81) than with Africans (r = 0.44). We identify 281 distinct variant-trait-associations at genome wide significance that replicate known associations. Allele frequencies for replicated loci show higher correlations with European (r = 0.94) than with African (r = 0.85) or Japanese (r = 0.80) populations. We find differences in linkage disequilibrium patterns and in effect sizes of the replicated loci compared to previous reports. We also report 17 novel and Qatari-predominate signals providing insights into the biological pathways regulating these traits. We observe that European-derived polygenic scores (PGS) have reduced predictive performance in the Qatari population which could have implications for the translation of PGS between populations and their future application in precision medicine.
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http://dx.doi.org/10.1038/s41467-021-21381-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902658PMC
February 2021

Metabolic Predictors of Equine Performance in Endurance Racing.

Metabolites 2021 Jan 31;11(2). Epub 2021 Jan 31.

Equine Veterinary Medical Center, Qatar Foundation, Doha 5825, Qatar.

Equine performance in endurance racing depends on the interplay between physiological and metabolic processes. However, there is currently no parameter for estimating the readiness of animals for competition. Our objectives were to provide an in-depth characterization of metabolic consequences of endurance racing and to establish a metabolic performance profile for those animals. We monitored metabolite composition, using a broad non-targeted metabolomics approach, in blood plasma samples from 47 Arabian horses participating in endurance races. The samples were collected before and after the competition and a total of 792 metabolites were measured. We found significant alterations between before and after the race in 417 molecules involved in lipids and amino acid metabolism. Further, even before the race starts, we found metabolic differences between animals who completed the race and those who did not. We identified a set of six metabolite predictors (imidazole propionate, pipecolate, ethylmalonate, 2R-3R-dihydroxybutyrate, β-hydroxy-isovalerate and X-25455) of animal performance in endurance competition; the resulting model had an area under a receiver operating characteristic (AUC) of 0.92 (95% CI: 0.85-0.98). This study provides an in-depth characterization of metabolic alterations driven by endurance races in equines. Furthermore, we showed the feasibility of identifying potential metabolic signatures as predictors of animal performance in endurance competition.
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http://dx.doi.org/10.3390/metabo11020082DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912089PMC
January 2021

Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse.

Metabolites 2021 Feb 3;11(2). Epub 2021 Feb 3.

Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.

Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.
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http://dx.doi.org/10.3390/metabo11020089DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913334PMC
February 2021

Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data.

Brief Bioinform 2021 07;22(4)

Statistical Genetics Research Group at the Institute of Medical Biometry and Informatics, Heidelberg University, Germany.

Least absolute shrinkage and selection operator (LASSO) regression is often applied to select the most promising set of single nucleotide polymorphisms (SNPs) associated with a molecular phenotype of interest. While the penalization parameter λ restricts the number of selected SNPs and the potential model overfitting, the least-squares loss function of standard LASSO regression translates into a strong dependence of statistical results on a small number of individuals with phenotypes or genotypes divergent from the majority of the study population-typically comprised of outliers and high-leverage observations. Robust methods have been developed to constrain the influence of divergent observations and generate statistical results that apply to the bulk of study data, but they have rarely been applied to genetic association studies. In this article, we review, for newcomers to the field of robust statistics, a novel version of standard LASSO that utilizes the Huber loss function. We conduct comprehensive simulations and analyze real protein, metabolite, mRNA expression and genotype data to compare the stability of penalization, the cross-iteration concordance of the model, the false-positive and true-positive rates and the prediction accuracy of standard and robust Huber-LASSO. Although the two methods showed controlled false-positive rates ≤2.1% and similar true-positive rates, robust Huber-LASSO outperformed standard LASSO in the accuracy of predicted protein, metabolite and gene expression levels using individual SNP data. The conducted simulations and real-data analyses show that robust Huber-LASSO represents a valuable alternative to standard LASSO in genetic studies of molecular phenotypes.
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http://dx.doi.org/10.1093/bib/bbaa230DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293825PMC
July 2021

A strategy to incorporate prior knowledge into correlation network cutoff selection.

Nat Commun 2020 10 14;11(1):5153. Epub 2020 Oct 14.

Institute of Computational Biology, Helmholtz Center Munich - German Research Center for Environmental Health, 85764, Neuherberg, Germany.

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization.
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http://dx.doi.org/10.1038/s41467-020-18675-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560866PMC
October 2020

The metabolic footprint of compromised insulin sensitivity under fasting and hyperinsulinemic-euglycemic clamp conditions in an Arab population.

Sci Rep 2020 10 13;10(1):17164. Epub 2020 Oct 13.

Department of Internal Medicine, Qatar Metabolic Institute, Hamad Medical Corporation, Doha, Qatar.

Metabolic pathways that are corrupted at early stages of insulin resistance (IR) remain elusive. This study investigates changes in body metabolism in clinically healthy and otherwise asymptomatic subjects that may become apparent already under compromised insulin sensitivity (IS) and prior to IR. 47 clinically healthy Arab male subjects with a broad range of IS, determined by hyperinsulinemic-euglycemic clamp (HIEC), were investigated. Untargeted metabolomics and complex lipidomics were conducted on serum samples collected under fasting and HIEC conditions. Linear models were used to identify associations between metabolites concentrations and IS levels. Among 1896 identified metabolites, 551 showed significant differences between fasting and HIEC, reflecting the metabolic switch in energy utilization. At fasting, 336 metabolites, predominantly di- and tri-acylglycerols, showed significant differences between subjects with low and high levels of IS. Changes in amino acid, carbohydrate and fatty acid metabolism in response to insulin were impaired in subjects with low IS. Association of altered mannose and amino acids with IS was also replicated in an independent cohort of T2D patients. We identified metabolic phenotypes that characterize clinically healthy Arab subjects with low levels of IS at their fasting state. Our study is providing further insights into the metabolic pathways that precede IR.
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http://dx.doi.org/10.1038/s41598-020-73723-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555540PMC
October 2020

Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes.

Diabetes 2020 12 6;69(12):2756-2765. Epub 2020 Oct 6.

Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany

Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolite biomarkers and the best set of predictors of CKD in the longitudinal, population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort by targeted metabolomics and machine learning approaches. Out of 125 targeted metabolites, sphingomyelin C18:1 and phosphatidylcholine diacyl C38:0 were identified as candidate metabolite biomarkers of incident CKD specifically in hyperglycemic individuals followed during 6.5 years. Sets of predictors for incident CKD developed from 125 metabolites and 14 clinical variables showed highly stable performances in all three machine learning approaches and outperformed the currently established clinical algorithm for CKD. The two metabolites in combination with five clinical variables were identified as the best set of predictors, and their predictive performance yielded a mean area value under the receiver operating characteristic curve of 0.857. The inclusion of metabolite variables in the clinical prediction of future CKD may thus improve the risk prediction in people with prediabetes and T2D. The metabolite link with hyperglycemia-related early kidney dysfunction warrants further investigation.
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http://dx.doi.org/10.2337/db20-0586DOI Listing
December 2020

Deciphering the Plasma Proteome of Type 2 Diabetes.

Diabetes 2020 12 14;69(12):2766-2778. Epub 2020 Sep 14.

Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany

With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort ( = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort ( = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor-binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone-binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes-protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes.
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http://dx.doi.org/10.2337/db20-0296DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679779PMC
December 2020

Genetics meets proteomics: perspectives for large population-based studies.

Nat Rev Genet 2021 01 28;22(1):19-37. Epub 2020 Aug 28.

Affinity Proteomics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.
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http://dx.doi.org/10.1038/s41576-020-0268-2DOI Listing
January 2021

Identification of genetic variants controlling RNA editing and their effect on RNA structure stabilization.

Eur J Hum Genet 2020 12 10;28(12):1753-1762. Epub 2020 Jul 10.

Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.

Post-transcriptional modification of RNA (RNA editing, RNAe) results in differences between the RNA transcript and the genomic DNA sequence (RDD). Enzymatic modification of adenosine to inosine (A2I) by ADAR is the most studied type of RNAe. However, few genetic association studies with A2I RNAe events have been conducted. Some studies have analyzed the inter-population RNAe-QTL diversity in humans, but the sample size of these studies was limited. Other types of RNA and DNA differences have been reported but are largely understudied. Here, we report a comprehensive analysis of all types of RDD, based on two independent datasets. We found that A2I was by far the most observed type of RDD. Moreover, manual curation suggests that A2I is likely the only enzymatically driven RNAe type observed in blood derived DNA, all other non-A2I RDD could either be attributed to sequencing and processing artifacts, or are a result of somatic DNA rearrangements. We then conducted an in-cis genetic association study and identified 472 genetic associations (RNAe-QTL), that were replicated in both datasets. We confirm the potential effect of the RNAe-QTL on RNA structure by showing that allele specific RNAe occurs in heterozygotes. Although the generally assumed function of RNAe is to destabilize double stranded RNA structure, we found clear evidence for the potential additional involvement of RNAe in maintaining RNA hairpin that has been altered by the RNAe-QTL. Our study confirms, in two independent datasets, the potential role of RNAe in maintaining RNA structure in the presence of genetic variation.
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http://dx.doi.org/10.1038/s41431-020-0688-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7784984PMC
December 2020

Genome-Wide Association Study Reveals a Novel Association Between MYBPC3 Gene Polymorphism, Endurance Athlete Status, Aerobic Capacity and Steroid Metabolism.

Front Genet 2020 16;11:595. Epub 2020 Jun 16.

Biomedical Research Institute (BRC), Qatar University, Doha, Qatar.

Background: The genetic predisposition to elite athletic performance has been a controversial subject due to the underpowered studies and the small effect size of identified genetic variants. The aims of this study were to investigate the association of common single-nucleotide polymorphisms (SNPs) with endurance athlete status in a large cohort of elite European athletes using GWAS approach, followed by replication studies in Russian and Japanese elite athletes and functional validation using metabolomics analysis.

Results: The association of 476,728 SNPs of Illumina DrugCore Gene chip and endurance athlete status was investigated in 796 European international-level athletes (645 males, 151 females) by comparing allelic frequencies between athletes specialized in sports with high ( = 662) and low/moderate ( = 134) aerobic component. Replication of results was performed by comparing the frequencies of the most significant SNPs between 242 and 168 elite Russian high and low/moderate aerobic athletes, respectively, and between 60 elite Japanese endurance athletes and 406 controls. A meta-analysis has identified rs1052373 (GG homozygotes) in Myosin Binding Protein (; implicated in cardiac hypertrophic myopathy) gene to be associated with endurance athlete status ( = 1.43 × 10, odd ratio 2.2). Homozygotes carriers of rs1052373 G allele in Russian athletes had significantly greater VO than carriers of the AA + AG ( = 0.005). Subsequent metabolomics analysis revealed several amino acids and lipids associated with rs1052373 G allele (1.82 × 10) including the testosterone precursor androstenediol (3beta,17beta) disulfate.

Conclusions: This is the first report of genome-wide significant SNP and related metabolites associated with elite athlete status. Further investigations of the functional relevance of the identified SNPs and metabolites in relation to enhanced athletic performance are warranted.
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http://dx.doi.org/10.3389/fgene.2020.00595DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308547PMC
June 2020

Metabolic Signatures of Tumor Responses to Doxorubicin Elucidated by Metabolic Profiling .

Metabolites 2020 Jun 28;10(7). Epub 2020 Jun 28.

Department of Physiology and Biophysics, Weill Cornell Medicine - Qatar, Doha 24144, Qatar.

Background: Dysregulated cancer metabolism is associated with acquired resistance to chemotherapeutic treatment and contributes to the activation of cancer survival mechanisms. However, which metabolic pathways are activated following treatment often remains elusive. The combination of chicken embryo tumor models () with metabolomics phenotyping could offer a robust platform for drug testing. Here, we assess the potential of this approach in the treatment of an triple negative breast cancer with doxorubicin.

Methods: MB-MDA-231 cells were grafted The resulting tumors were then treated with doxorubicin or dimethyl sulfoxide (DMSO) for six days. Tumors were collected and analyzed using a global untargeted metabolomics and comprehensive lipidomics.

Results: We observed a significant suppression of tumor growth in the doxorubicin treated group. The metabolic profiles of doxorubicin and DMSO-treated tumors were clearly separated in a principle component analysis. Inhibition of glycolysis, nucleotide synthesis, and glycerophospholipid metabolism appear to be triggered by doxorubicin treatment, which could explain the observed suppressed tumor growth. In addition, metabolic cancer survival mechanisms could be supported by an acceleration of antioxidative pathways.

Conclusions: Metabolomics in combination with tumor models provide a robust platform for drug testing to reveal tumor specific treatment targets such as the antioxidative tumor capacity.
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http://dx.doi.org/10.3390/metabo10070268DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7408021PMC
June 2020

Proteome-wide assessment of diabetes mellitus in Qatari identifies IGFBP-2 as a risk factor already with early glycaemic disturbances.

Arch Biochem Biophys 2020 08 22;689:108476. Epub 2020 Jun 22.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands.

Background: Proteomics is expected to provide novel insights in the underlying pathophysiology of type 2 diabetes mellitus. In the present study, we aimed to identify and biochemically characterize proteins associated with diabetes mellitus in a Qatari population.

Methods: In a diabetes case-control study (175 cases, 164 controls; Arab, South Asian and Philippine ethnicities), we conducted a discovery study to screen 1141 blood protein levels for associations with diabetes mellitus. Additional analyses were done in controls in relation to Hb1Ac, and biochemical characterization of the main findings was performed with metabolomics (501 metabolites). We performed two-sample Mendelian Randomization to provide evidence of potential causality using data from European descent of the DIAGRAM consortium (74,124 cases of diabetes mellitus and 824,006 controls) for the identified proteins for T2D and Hb1Ac.

Results: After accounting for multiple testing, 30 protein levels were different (p-values<8.6e) between cases and controls. Of these, a higher Hb1Ac in controls was associated with a lower IGFBP-2 level (p-value = 4.1e). IGFBP-2 protein level was found lower among cases compared with controls across all ethnicities. In controls, IGFBP-2 was associated with 21 metabolite levels, but specifically connected to the metabolite citrulline in network analyses. We observed no evidence, however, that the association between IGFBP-2 and diabetes mellitus was causal.

Conclusions: We specifically identified IGFBP-2 to be associated with diabetes mellitus, although with no evidence for causality, which was specifically connected to citrulline metabolism.
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http://dx.doi.org/10.1016/j.abb.2020.108476DOI Listing
August 2020

Author Correction: Effect of induced hypoglycemia on inflammation and oxidative stress in type 2 diabetes and control subjects.

Sci Rep 2020 Jun 19;10(1):10233. Epub 2020 Jun 19.

Royal College of Surgeon in Ireland, Manama, Bahrain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41598-020-66189-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305170PMC
June 2020

Deletion of beta-fructofuranosidase (invertase) genes is associated with sucrose content in Date Palm fruit.

Plant Direct 2020 May 27;4(5):e00214. Epub 2020 May 27.

Department of Genetic Medicine Weill Cornell Medicine in Qatar Doha Qatar.

The fruit of date palm trees are an important part of the diet for a large portion of the Middle East and North Africa. The fruit is consumed both fresh and dry and can be stored dry for extended periods of time. Date fruits vary significantly across hundreds of cultivars identified in the main regions of cultivation. Most dried date fruit are low in sucrose but high in glucose and fructose. However, high sucrose content is a distinctive feature of some date fruit and affects flavor as well as texture and water retention. To identify the genes controlling high sucrose content, we analyzed date fruit metabolomics for association with genotype data from 120 date fruits. We found significant association of dried date sucrose content and a genomic region that contains 3 tandem copies of the beta-fructofuranosidase (invertase) gene in the reference Khalas genome, a low-sucrose fruit. High-sucrose cultivars including the popular Deglet Noor had a homozygous deletion of two of the 3 copies of the invertase gene. We show the deletion allele is derived when compared to the ancestral allele that retains all copies of the gene in 3 other species of . The fact that 2 of the 3 tandem invertase copies are associated with dry fruit sucrose content will assist in better understanding the distinct roles of multiple date palm invertases in plant physiology. Identification of the recessive alleles associated with end-point sucrose content in date fruit may be used in selective breeding in the future.
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http://dx.doi.org/10.1002/pld3.214DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251787PMC
May 2020

Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes.

Diabetes 2020 08 8;69(8):1843-1853. Epub 2020 May 8.

Faculty of Medicine, University of Iceland, Reykjavik, Iceland

The increasing prevalence of type 2 diabetes poses a major challenge to societies worldwide. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach, measuring serum levels of 4,137 proteins in 5,438 elderly Icelanders, and identified 536 proteins associated with prevalent and/or incident type 2 diabetes. We validated a subset of the observed associations in an independent case-control study of type 2 diabetes. These protein associations provide novel biological insights into the molecular mechanisms that are dysregulated prior to and following the onset of type 2 diabetes and can be detected in serum. A bidirectional two-sample Mendelian randomization analysis indicated that serum changes of at least 23 proteins are downstream of the disease or its genetic liability, while 15 proteins were supported as having a causal role in type 2 diabetes.
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http://dx.doi.org/10.2337/db19-1070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372075PMC
August 2020

Effect of induced hypoglycemia on inflammation and oxidative stress in type 2 diabetes and control subjects.

Sci Rep 2020 03 16;10(1):4750. Epub 2020 Mar 16.

Royal College of Surgeon in Ireland, Manama, Bahrain.

Intensive diabetes control has been associated with increased mortality in type 2 diabetes (T2DM); this has been suggested to be due to increased hypoglycemia. We measured hypoglycemia-induced changes in endothelial parameters, oxidative stress markers and inflammation at baseline and after a 24-hour period in type 2 diabetic (T2DM) subjects versus age-matched controls. Case-control study: 10 T2DM and 8 control subjects. Blood glucose was reduced from 5 (90 mg/dl) to hypoglycemic levels of 2.8 mmol/L (50 mg/dl) for 1 hour by incremental hyperinsulinemic clamps using baseline and 24 hour samples. Measures of endothelial parameters, oxidative stress and inflammation at baseline and at 24-hours post hypoglycemia were performed: proteomic (Somalogic) analysis for inflammatory markers complemented by C-reactive protein (hsCRP) measurement, and proteomic markers and urinary isoprostanes for oxidative measures, together with endothelial function. Between baseline and 24 -hours after hypoglycemia, 15 of 140 inflammatory proteins differed in T2DM whilst only 1 of 140 differed in controls; all returned to baseline at 24-hours. However, elevated hsCRP levels were seen at 24-hours in T2DM (2.4 mg/L (1.2-5.4) vs. 3.9 mg/L (1.8-6.1), Baseline vs 24-hours, P < 0.05). In patients with T2DM, between baseline and 24-hour after hypoglycemia, only one of 15 oxidative stress proteins differed and this was not seen in controls. An increase (P = 0.016) from baseline (73.4 ng/mL) to 24 hours after hypoglycemia (91.7 ng/mL) was seen for urinary isoprostanes. Hypoglycemia resulted in inflammatory and oxidative stress markers being elevated in T2DM subjects but not controls 24-hours after the event.
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http://dx.doi.org/10.1038/s41598-020-61531-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7075968PMC
March 2020
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