Publications by authors named "Harald Grallert"

222 Publications

Genetic insights into biological mechanisms governing human ovarian ageing.

Nature 2021 08 4;596(7872):393-397. Epub 2021 Aug 4.

Genome Integrity and Instability Group, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Reproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-021-03779-7DOI Listing
August 2021

Linking the obesity rs1421085 variant circuitry to cellular, metabolic, and organismal phenotypes in vivo.

Sci Adv 2021 Jul 21;7(30). Epub 2021 Jul 21.

Mammalian Genetics Unit, MRC Harwell Institute, Oxfordshire OX11 0RD, UK.

Variants in FTO have the strongest association with obesity; however, it is still unclear how those noncoding variants mechanistically affect whole-body physiology. We engineered a deletion of the rs1421085 conserved cis-regulatory module (CRM) in mice and confirmed in vivo that the CRM modulates and gene expression and mitochondrial function in adipocytes. The CRM affects molecular and cellular phenotypes in an adipose depot-dependent manner and affects organismal phenotypes that are relevant for obesity, including decreased high-fat diet-induced weight gain, decreased whole-body fat mass, and decreased skin fat thickness. Last, we connected the CRM to a genetically determined effect on steroid patterns in males that was dependent on nutritional challenge and conserved across mice and humans. Together, our data establish cross-species conservation of the rs1421085 regulatory circuitry at the molecular, cellular, metabolic, and organismal level, revealing previously unknown contextual dependence of the variant's action.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/sciadv.abg0108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294759PMC
July 2021

N-glycosylation of immunoglobulin G predicts incident hypertension.

J Hypertens 2021 Jul 19. Epub 2021 Jul 19.

Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia Department of Twin Research, Kings College London, London, UK Genos Glycoscience Research Laboratory, Zagreb, Croatia Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health German Center for Diabetes Research (DZD) Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health LMU Munich, IBE-Chair of Epidemiology, Neuherberg, Germany Department of Public Health, University of Split, School of Medicine, Split, Croatia NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London Academic Rheumatology Clinical Sciences Building, Nottingham City Hospital, University of Nottingham, Nottingham University of Glasgow, Glasgow, Scotland, UK.

Objectives: Glycosylation of immunoglobulin G (IgG) is an important regulator of the immune system and has been implicated in prevalent hypertension.The aim of this study is to investigate whether the IgG glycome begins to change prior to hypertension diagnosis by analysing the IgG glycome composition in a large population-based female cohort with two independent replication samples.

Methods: We included 989 unrelated cases with incident hypertension and 1628 controls from the TwinsUK cohort (mean follow-up time of 6.3 years) with IgG measured at baseline by ultra-performance liquid chromatography and longitudinal BP measurement available. We replicated our findings in 106 individuals from the 10 001 Dalmatians and 729 from KORA S4. Cox regression mixed models were applied to identify changes in glycan traits preincident hypertension, after adjusting for age, mean arterial pressure, BMI, family relatedness and multiple testing (FDR < 0.1). Significant IgG-incident hypertension associations were replicated in the two independent cohorts by leveraging Cox regression mixed models in the 10 001 Dalmatians and logistic regression models in the KORA cohort.

Results: We identified and replicated four glycan traits, incidence of bisecting GlcNAc, GP4, GP9 and GP21, that are predictive of incident hypertension after adjusting for confoundes and multiple testing [hazard ratio (95% CI) ranging from 0.45 (0.24-0.84) for GP21 to 2.9 (1.5-5.68) for GP4]. We then linearly combined the four replicated glycans and found that the glycan score correlated with incident hypertension, SBP and DBP.

Conclusion: Our results suggest that the IgG glycome changes prior to the development of hypertension.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/HJH.0000000000002963DOI Listing
July 2021

Synergistic effect of genetic polymorphisms in and genes on the risk of pulmonary tuberculosis in a Moldavian population.

Innate Immun 2021 Jul 18;27(5):365-376. Epub 2021 Jul 18.

Hannover Unified Biobank, 9177Hannover Medical School, Hannover Medical School, Germany.

Polymorphisms in genes that control immune function and regulation may influence susceptibility to pulmonary tuberculosis (TB). In this study, 14 polymorphisms in 12 key genes involved in the immune response (, , , , , , , , , , , and ) were tested for their association with pulmonary TB in 271 patients with TB and 251 community-matched controls from the Republic of Moldova. In addition, gene-gene interactions involved in TB susceptibility were analyzed for a total of 43 genetic loci. Single nucleotide polymorphism (SNP) analysis revealed a nominal association between rs1800629 and pulmonary TB (Fisher exact test  = 0.01843). In the pairwise interaction analysis, the combination of the genotypes rs5743810 GA and rs11096957 GT was significantly associated with an increased genetic risk of pulmonary TB (OR = 2.48, 95% CI = 1.62-3.85; Fisher exact test value = 1.5 × 10, significant after Bonferroni correction). In conclusion, the rs5743810 and rs11096957 two-locus interaction confers a significantly higher risk for pulmonary TB; due to its high frequency in the population, this SNP combination may serve as a novel biomarker for predicting TB susceptibility.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1177/17534259211029996DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419295PMC
July 2021

Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study.

Genet Epidemiol 2021 Sep 3;45(6):633-650. Epub 2021 Jun 3.

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

It is still unclear how genetic information, provided as single-nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population-based case-cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRS ); selection of the most predictive SNPs among these literature-confirmed variants using priority-Lasso (PL ); validation of two comprehensive polygenic risk scores: GRS based on Metabochip data, and GRS (available in the testset only) based on cross-validated genome-wide genotyping data. We used Cox regression to assess associations with incident CHD. C-index, category-free net reclassification index (cfNRI) and relative integrated discrimination improvement (IDI ) were used to quantify the predictive performance of genetic information beyond Framingham risk score variables. In contrast to GRS and PL , GRS significantly improved the prediction (delta C-index [95% confidence interval]: 0.0087 [0.0044, 0.0130]; IDI : 0.0509 [0.0131, 0.0894]; cfNRI improved only in cases: 0.1761 [0.0253, 0.3219]). GRS yielded slightly worse prediction results than GRS .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/gepi.22389DOI Listing
September 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12933-021-01299-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138979PMC
May 2021

Association between Single Nucleotide Polymorphisms and Weight Reduction in Behavioural Interventions-A Pooled Analysis.

Nutrients 2021 Mar 2;13(3). Epub 2021 Mar 2.

Clinic of Internal Medicine II, University Hospital of Regensburg, 93053 Regensburg, Germany.

Knowledge of the association between single nucleotide polymorphisms (SNPs) and weight loss is limited. The aim was to analyse whether selected obesity-associated SNPs within the fat mass and obesity-associated (), transmembrane protein 18 (), melanocortin-4 receptor (), SEC16 homolog B (), and brain-derived neurotrophic factor () gene are associated with anthropometric changes during behavioural intervention for weight loss. genetic and anthropometric data from 576 individuals with overweight and obesity from four lifestyle interventions were obtained. A genetic predisposition score (GPS) was calculated. Our results show that study participants had a mean age of 48.2 ± 12.6 years and a mean baseline body mass index of 33.9 ± 6.4 kg/m. Mean weight reduction after 12 months was -7.7 ± 10.9 kg. After 12 months of intervention, the SNPs rs571312 and rs17782313 were significantly associated with a greater decrease in body weight and BMI ( 0.012, = 0.011, respectively). The investigated SNPs within the other four genetic loci showed no statistically significant association with changes in anthropometric parameters. The GPS showed no statistically significant association with weight reduction. In conclusion there was no consistent evidence for statistically significant associations of SNPs with anthropometric changes during a behavioural intervention. It seems that other factors play a more significant in weight management than the investigated SNPs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/nu13030819DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998423PMC
March 2021

Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation.

Microbiome 2021 03 16;9(1):61. Epub 2021 Mar 16.

Independent Research Unit Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.

Background: The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study.

Results: Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant's gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5.

Conclusions: The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s40168-020-00969-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967986PMC
March 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-021-21542-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904950PMC
February 2021

Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Hum Mol Genet 2021 04;30(5):393-409

Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK.

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/hmg/ddab023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098112PMC
April 2021

A Pathophysiology of Type 2 Diabetes Unrelated to Metabolic Syndrome.

J Clin Endocrinol Metab 2021 04;106(5):1460-1471

Diabetes Research Group, Medizinische Klinik und Poliklinik IV, LMU Klinikum, München, Germany.

Objective: Clinically, type 2 diabetes mellitus (T2DM) is heterogeneous, but the prevailing pathophysiologic hypothesis nevertheless contends that components of metabolic syndrome are central to all cases of T2DM. Here, we re-evaluated this hypothesis.

Research Design And Methods: We conducted a cross-sectional analysis of 138 women from the monocenter, post gestational diabetes study PPSDiab, 73 of which had incident prediabetes or T2DM. Additionally, we examined all the 412 incident cases of T2DM in phases 3 to 9 of the Whitehall II study in comparison to healthy controls. Our analysis included a medical history, anthropometrics, oral glucose tolerance testing, and laboratory chemistry in both studies. Additional analyses from the PPSDiab Study consisted of cardiopulmonary exercise testing, magnetic resonance imaging, auto-antibody testing, and the exclusion of glucokinase maturity-onset diabetes of the young.

Results: We found that 33 (45%) of the women with prediabetes or T2DM in the PPSDiab study displayed no components of metabolic syndrome. They reached no point for metabolic syndrome in the National Cholesterol Education Program Adult Treatment Panel III score other than hyperglycemia and, moreover, had levels of liver fat content, plasma triglycerides, high-density lipoprotein cholesterol, c-reactive protein, and blood pressure that were comparable to healthy controls. In the Whitehall II study, 62 (15%) of the incident T2DM cases fulfilled the same criteria. In both studies, these cases without metabolic syndrome revealed insulin resistance and inadequately low insulin secretion.

Conclusions: Our results contradict the hypothesis that components of metabolic syndrome are central to all cases of T2DM. Instead, they suggest the common occurrence of a second, unrelated pathophysiology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1210/clinem/dgab057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063234PMC
April 2021

Human genome diversity data reveal that L564P is the predominant TPC2 variant and a prerequisite for the blond hair associated M484L gain-of-function effect.

PLoS Genet 2021 01 19;17(1):e1009236. Epub 2021 Jan 19.

Walther Straub Institute of Pharmacology and Toxicology, Faculty of Medicine, Ludwig-Maximilians-Universität, Munich, Germany.

The endo-lysosomal two-pore channel (TPC2) has been established as an intracellular cation channel of significant physiological and pathophysiological relevance in recent years. For example, TPC2-/- mice show defects in cholesterol degradation, leading to hypercholesterinemia; TPC2 absence also results in mature-onset obesity, and a role in glucagon secretion and diabetes has been proposed. Infections with bacterial toxins or viruses e.g., cholera toxin or Ebola virus result in reduced infectivity rates in the absence of TPC2 or after pharmacological blockage, and TPC2-/- cancer cells lose their ability to migrate and metastasize efficiently. Finally, melanin production is affected by changes in hTPC2 activity, resulting in pigmentation defects and hair color variation. Here, we analyzed several publicly available genome variation data sets and identified multiple variations in the TPC2 protein in distinct human populations. Surprisingly, one variation, L564P, was found to be the predominant TPC2 isoform on a global scale. By applying endo-lysosomal patch-clamp electrophysiology, we found that L564P is a prerequisite for the previously described M484L gain-of-function effect that is associated with blond hair. Additionally, other gain-of-function variants with distinct geographical and ethnic distribution were discovered and functionally characterized. A meta-analysis of genome-wide association studies was performed, finding the polymorphisms to be associated with both distinct and overlapping traits. In sum, we present the first systematic analysis of variations in TPC2. We functionally characterized the most common variations and assessed their association with various disease traits. With TPC2 emerging as a novel drug target for the treatment of various diseases, this study provides valuable insights into ethnic and geographical distribution of TPC2 polymorphisms and their effects on channel activity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1009236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7845996PMC
January 2021

Genome-wide association study in 8,956 German individuals identifies influence of ABO histo-blood groups on gut microbiome.

Nat Genet 2021 02 18;53(2):147-155. Epub 2021 Jan 18.

Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany.

The intestinal microbiome is implicated as an important modulating factor in multiple inflammatory, neurologic and neoplastic diseases. Recent genome-wide association studies yielded inconsistent, underpowered and rarely replicated results such that the role of human host genetics as a contributing factor to microbiome assembly and structure remains uncertain. Nevertheless, twin studies clearly suggest host genetics as a driver of microbiome composition. In a genome-wide association analysis of 8,956 German individuals, we identified 38 genetic loci to be associated with single bacteria and overall microbiome composition. Further analyses confirm the identified associations of ABO histo-blood groups and FUT2 secretor status with Bacteroides and Faecalibacterium spp. Mendelian randomization analysis suggests causative and protective effects of gut microbes, with clade-specific effects on inflammatory bowel disease. This holistic investigative approach of the host, its genetics and its associated microbial communities as a 'metaorganism' broaden our understanding of disease etiology, and emphasize the potential for implementing microbiota in disease treatment and management.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-020-00747-1DOI Listing
February 2021

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Nat Commun 2021 01 5;12(1):24. Epub 2021 Jan 5.

Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population.

J Clin Endocrinol Metab 2021 03;106(4):e1647-e1659

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

Context: Improved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most.

Objective: This work aimed to assess whether novel biomarkers improve the prediction of type 2 diabetes beyond noninvasive standard clinical risk factors alone or in combination with glycated hemoglobin A1c (HbA1c).

Methods: We used a population-based case-cohort study for discovery (689 incident cases and 1850 noncases) and an independent cohort study (262 incident cases, 2549 noncases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the noninvasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c).

Results: Interleukin-1 receptor antagonist, insulin-like growth factor binding protein 2, soluble E-selectin, decorin, adiponectin, and high-density lipoprotein cholesterol were selected as the most relevant biomarkers. The simultaneous addition of these 6 biomarkers significantly improved the predictive performance both in the discovery (C index [95% CI], 0.053 [0.039-0.066]; cfNRI [95% CI], 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies.

Conclusion: The addition of 6 biomarkers significantly improved the prediction of type 2 diabetes when added to a noninvasive clinical model or to a clinical model plus HbA1c.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1210/clinem/dgaa953DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993565PMC
March 2021

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density.

PLoS Genet 2020 12 28;16(12):e1009190. Epub 2020 Dec 28.

Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America.

The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored data from 3,823 mutant mouse strains for BMD, a measure that is frequently altered in a range of bone pathologies, including osteoporosis. A total of 200 genes were found to significantly affect BMD. This pool of BMD genes comprised 141 genes with previously unknown functions in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 genes also caused skeletal abnormalities. Examination of the BMD genes in osteoclasts and osteoblasts underscored BMD pathways, including vesicle transport, in these cells and together with in silico bone turnover studies resulted in the prioritization of candidate genes for further investigation. Overall, the results add novel pathophysiological and molecular insight into bone health and disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1009190DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822523PMC
December 2020

Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus.

Circ Genom Precis Med 2020 12 13;13(6):e002769. Epub 2020 Aug 13.

The Usher Institute of Population Health Sciences & Informatics (A.D.M.), University of Edinburgh, Edinburgh, U.K.

Background: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D).

Methods: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D).

Results: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background.

Conclusions: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/CIRCGEN.119.002769DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7748049PMC
December 2020

Obesity Genes and Weight Loss During Lifestyle Intervention in Children With Obesity.

JAMA Pediatr 2021 Jan 4;175(1):e205142. Epub 2021 Jan 4.

Department of Prevention and Sports Medicine, Centre for Sports Cardiology, University Hospital "Klinikum rechts der Isar," Technical University of Munich, Munich, Germany.

Importance: Genome-wide association studies have identified genetic loci influencing obesity risk in children. However, the importance of these loci in the associations with weight reduction through lifestyle interventions has not been investigated in large intervention trials.

Objective: To evaluate the associations between various obesity susceptibility loci and changes in body weight in children during an in-hospital, lifestyle intervention program.

Design, Setting, And Participants: Long-term Effects of Lifestyle Intervention in Obesity and Genetic Influence in Children (LOGIC), an interventional prospective cohort study, enrolled 1429 children with overweight or obesity to participate in an in-hospital lifestyle intervention program. Genotyping of 56 validated obesity single-nucleotide variants (SNVs) was performed, and the associations between the SNVs and body weight reduction during the intervention were evaluated using linear mixed-effects models for each SNV. The LOGIC study was conducted from January 6, 2006, to October 19, 2013; data analysis was performed from July 15, 2015, to November 6, 2016.

Exposures: A 4- to 6-week standardized in-hospital lifestyle intervention program (daily physical activity, calorie-restricted diet, and behavioral therapy).

Main Outcomes And Measures: The association between 56 obesity-relevant SNVs and changes in body weight and body mass index.

Results: Of 1429 individuals enrolled in the LOGIC Study, 1198 individuals (mean [SD] age, 14.0 [2.2] years; 670 [56%] girls) were genotyped. A mean (SD) decrease was noted in body weight of -8.7 (3.6) kg (95% CI, -15.7 to -1.8 kg), and body mass index (calculated as weight in kilograms divided by height in meters squared) decreased by -3.3 (1.1) (95% CI, -5.4 to -1.1) (both P < .05). Five of 56 obesity SNVs were statistically significantly associated with a reduction of body weight or body mass index (all P < 8.93 × 10-4 corresponding to Bonferroni correction for 56 tests). Compared with homozygous participants without the risk allele, homozygous carriers of the rs7164727 (LOC100287559: 0.42 kg; 95% CI, 0.31-0.53 kg, P = 4.00 × 10-4) and rs12940622 (RPTOR: 0.35 kg; 95% CI, 0.18-0.52 kg; P = 1.86 × 10-5) risk alleles had a lower reduction of body weight, whereas carriers of the rs13201877 (IFNGR1: 0.65 kg; 95% CI, 0.51-0.79 kg; P = 2.39 × 10-5), rs10733682 (LMX1B: 0.45 kg; 95% CI, 0.27-0.63 kg; P = 6.37 × 10-4), and rs2836754 (ETS2: 0.56 kg; 95% CI, 0.38-0.74 kg; P = 1.51 × 10-4) risk alleles were associated with a greater reduction of body weight after adjustment for age and sex.

Conclusions And Relevance: Genes appear to play a minor role in weight reduction by lifestyle in children with overweight or obesity. The findings suggest that environmental, social, and behavioral factors are more important to consider in obesity treatment strategies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1001/jamapediatrics.2020.5142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737153PMC
January 2021

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

Genome Med 2020 12 1;12(1):109. Epub 2020 Dec 1.

NIHR Exeter Clinical Research Facility, University of Exeter Medical School, Exeter, UK.

Background: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.

Methods: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.

Results: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.

Conclusions: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13073-020-00806-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708171PMC
December 2020

Smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic traits.

Clin Epigenetics 2020 10 22;12(1):157. Epub 2020 Oct 22.

Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, 3015 GB, Rotterdam, The Netherlands.

Background: Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits.

Results: We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression.

Conclusions: Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13148-020-00951-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579899PMC
October 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2337/db20-0296DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679779PMC
December 2020

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity.

Diabetes 2020 12 11;69(12):2806-2818. Epub 2020 Sep 11.

Department of Biostatistics, Boston University School of Public Health, Boston, MA.

Leptin influences food intake by informing the brain about the status of body fat stores. Rare mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in , , , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry ( = 2 × 10, = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2337/db20-0070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679778PMC
December 2020

Arrhythmic Gut Microbiome Signatures Predict Risk of Type 2 Diabetes.

Cell Host Microbe 2020 08 2;28(2):258-272.e6. Epub 2020 Jul 2.

ZIEL - Institute for Food & Health, Technical University of Munich, 85354 Freising, Germany; Chair of Nutrition and Immunology, Technical University of Munich, Gregor-Mendel-Str. 2, 85354 Freising, Germany. Electronic address:

Lifestyle, obesity, and the gut microbiome are important risk factors for metabolic disorders. We demonstrate in 1,976 subjects of a German population cohort (KORA) that specific microbiota members show 24-h oscillations in their relative abundance and identified 13 taxa with disrupted rhythmicity in type 2 diabetes (T2D). Cross-validated prediction models based on this signature similarly classified T2D. In an independent cohort (FoCus), disruption of microbial oscillation and the model for T2D classification was confirmed in 1,363 subjects. This arrhythmic risk signature was able to predict T2D in 699 KORA subjects 5 years after initial sampling, being most effective in combination with BMI. Shotgun metagenomic analysis functionally linked 26 metabolic pathways to the diurnal oscillation of gut bacteria. Thus, a cohort-specific risk pattern of arrhythmic taxa enables classification and prediction of T2D, suggesting a functional link between circadian rhythms and the microbiome in metabolic diseases.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.chom.2020.06.004DOI Listing
August 2020

Investigation of Adiposity Measures and Operational Taxonomic unit (OTU) Data Transformation Procedures in Stool Samples from a German Cohort Study Using Machine Learning Algorithms.

Microorganisms 2020 Apr 10;8(4). Epub 2020 Apr 10.

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

The analysis of the gut microbiome with respect to health care prevention and diagnostic purposes is increasingly the focus of current research. We analyzed around 2000 stool samples from the KORA (Cooperative Health Research in the Region of Augsburg) cohort using high-throughput 16S rRNA gene amplicon sequencing representing a total microbial diversity of 2089 operational taxonomic units (OTUs). We evaluated the combination of three different components to assess the reflection of obesity related to microbiota profiles: (i) four prediction methods (i.e., partial least squares (PLS), support vector machine regression (SVMReg), random forest (RF), and M5Rules); (ii) five OTU data transformation approaches (i.e., no transformation, relative abundance without and with log-transformation, as well as centered and isometric log-ratio transformations); and (iii) predictions from nine measurements of obesity (i.e., body mass index, three measures of body shape, and five measures of body composition). Our results showed a substantial impact of all three components. The applications of SVMReg and PLS in combination with logarithmic data transformations resulted in considerably predictive models for waist circumference-related endpoints. These combinations were at best able to explain almost 40% of the variance in obesity measurements based on stool microbiota data (i.e., OTUs) only. A reduced loss in predictive performance was seen after sex-stratification in waist-height ratio compared to other waist-related measurements. Moreover, our analysis showed that the contribution of OTUs less prevalent and abundant is minor concerning the predictive power of our models.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/microorganisms8040547DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232268PMC
April 2020

Rare Variants in Specific Lysosomal Genes Are Associated With Parkinson's Disease.

Mov Disord 2020 07 8;35(7):1245-1248. Epub 2020 Apr 8.

Department of Neurology, Universitätsklinikum Schleswig-Holstein, Christian-Albrechts-University, Kiel, Germany.

Objective: Impaired lysosomal degradation of α-synuclein and other cellular constituents may play an important role in Parkinson's disease (PD). Rare genetic variants in the glucocerebrosidase (GBA) gene were consistently associated with PD. Here we examine the association between rare variants in lysosomal candidate genes and PD.

Methods: We investigated the association between PD and rare genetic variants in 23 lysosomal candidate genes in 4096 patients with PD and an equal number of controls using pooled targeted next-generation DNA sequencing. Genewise association of rare variants in cases or controls was analyzed using the optimized sequence kernel association test with Bonferroni correction for the 23 tested genes.

Results: We confirm the association of rare variants in GBA with PD and report novel associations for rare variants in ATP13A2, LAMP1, TMEM175, and VPS13C.

Conclusion: Rare variants in selected lysosomal genes, first and foremost GBA, are associated with PD. Rare variants in ATP13A2 and VPC13C previously linked to monogenic PD and more common variants in TMEM175 and VPS13C previously linked to sporadic PD in genome-wide association studies are associated with PD. © 2020 International Parkinson and Movement Disorder Society.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/mds.28037DOI Listing
July 2020

GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI.

Sci Adv 2019 09 4;5(9):eaaw3095. Epub 2019 Sep 4.

Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/sciadv.aaw3095DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904961PMC
September 2019
-->