Agnete Troen Lundgaard’s research while affiliated with IT University of Copenhagen and other places

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Publications (18)


a Flowchart for inclusion. b Timepoints for data collection. Data from the electronic health record was obtained throughout the pregnancy and postpartum
Heatmap of phenotypes across participants using hierarchical clustering based on MSD biomarkers. Phenotypes are divided into maternal characteristics, pregnancy-related outcomes for the current pregnancy (observed before or at inclusion), fetal characteristics, pregnancy-related outcomes for prior pregnancies, prior diseases to the current pregnancy, and phenotypes observed after inclusion. ASA, acetylsalicylic acid; BMI, body mass index; C-section, cesarean section; DM, diabetes mellitus; GA, gestational age; GDM, gestational diabetes mellitus; IBD, inflammatory bowel diseases; IUI, intrauterine insemination; IVF, in vitro fertilization; MoM, multiples of medians; PCOS, polycystic ovary syndrome; PE, pre-eclampsia; PPH, postpartum hemorrhage; SGA, small for gestational age; UTI, urinary tract infection
Previous pregnancies and pre-existing conditions effects on inflammatory markers. Effect size is increase or decrease in standard deviations. Only associations where the 95% Bayesian credible interval does not include zero are shown. ASA, acetylsalicylic acid; BMI, body mass index; GA, gestational age; GDM, gestational diabetes mellitus; IUI, intrauterine insemination; IVF, in vitro fertilization; MOM, multiples of medians; PCOS, polycystic ovary syndrome; PE, pre-eclampsia; PPH, postpartum hemorrhage
Associations between markers and later obstetrical outcomes. The effect size is the log-hazard rate for all outcomes, except birth weight-gestational age ratio (BWGA). The effect of biomarkers on BWGA is a change in percentile from the 50th percentile. Only associations where the 95% Bayesian credible interval does not include zero are shown. BMI, body mass index; GA, gestational age; IUI, intrauterine insemination; IVF, in vitro fertilization
Summarized SHAP values for each feature category (red = clinical measure, blue = MSD biomarker) across all outcomes investigated in the prognostic model. PPH, postpartum hemorrhage

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Immune changes in pregnancy: associations with pre-existing conditions and obstetrical complications at the 20th gestational week—a prospective cohort study
  • Article
  • Full-text available

December 2024

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14 Reads

BMC Medicine

David Westergaard

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Agnete Troen Lundgaard

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[...]

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Background Pregnancy is a complex biological process and serious complications can arise when the delicate balance between the maternal and semi-allogeneic fetal immune systems is disrupted or challenged. Gestational diabetes mellitus (GDM), pre-eclampsia, preterm birth, and low birth weight pose serious threats to maternal and fetal health. Identification of early biomarkers through an in-depth understanding of molecular mechanisms is critical for early intervention. Methods We analyzed the associations between 47 proteins involved in inflammation, chemotaxis, angiogenesis, and immune system regulation, maternal and neonatal health outcomes, and the baseline characteristics and pre-existing conditions of the mother in a prospective cohort of 1049 pregnant women around the 20th gestational week. We used Bayesian linear regression models to examine the impact of risk factors on biomarker levels and Bayesian cause-specific parametric proportional hazards models to analyze the effect of biomarkers on maternal and neonatal outcomes. We evaluated the predictive value of baseline characteristics and 47 proteins using machine-learning models and identified the most predictive biomarkers using Shapley additive explanation scores. Results Associations were identified between specific inflammatory markers and several conditions, including maternal age and pre-pregnancy body mass index, chronic diseases, complications from prior pregnancies, and COVID-19 exposure. Smoking during pregnancy affected GM-CSF and 9 other biomarkers. Distinct biomarker patterns were observed for different ethnicities. Within obstetric complications, IL-6 inversely correlated with pre-eclampsia risk, while birth weight to gestational age ratio was linked to markers including VEGF and PlGF. GDM was associated with IL-1RA, IL-17D, and eotaxin-3. Severe postpartum hemorrhage correlated with CRP, IL-13, and proteins of the IL-17 family. Predictive modeling yielded area under the receiver operating characteristic curve values of 0.708 and 0.672 for GDM and pre-eclampsia, respectively. Significant predictive biomarkers for GDM included IL-1RA and eotaxin-3, while pre-eclampsia prediction yielded the highest predictions when including MIP-1β, IL-1RA, and IL-12p70. Conclusions Our study provides novel insights into the interplay between preexisting conditions and immune dysregulation in pregnancy. These findings contribute to our understanding of the pathophysiology of obstetric complications and the identification of novel biomarkers for early intervention(s) to improve maternal and fetal health.

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Graphical representation of study set-up. Individuals with incident diabetes were selected based on a diabetes register capturing patients with type 1 or type 2 diabetes (DM) in the period 1977–2016. Only individuals with at least one DBDS inclusion sample collected in the period 2010–2016 and two additional plasma samples (archival sample or DBDS inclusion sample) collected in the period 2006–2016 were included as participants. The three plasma samples had to be donated at least 9 months apart to ensure ample time for molecular changes reflecting the development of diabetes to take place
Biomarker-specific effect estimates for incident diabetes. Effect estimates obtained using mixed-effects models (fold change, FC) are shown for proteins (a), metabolites (a, b) and lipoprotein particles (b). All estimates are shown as point estimates and 95% CIs. Biomarkers with a significant interaction term are indicated by triangles that show the direction of the trend. Significant associations (FDR-adjusted p<0.05) are indicated by filled circles; non-significant estimates are indicated by open circles. bFGF, basic fibroblast growth factor; FA, fatty acids; GM-CSF, granulocyte macrophage colony-stimulating factor; IDL, intermediate-density lipoprotein; IP-10, interferon-induced protein 10; MDC, macrophage-derived chemokine; MUFAs, mono-unsaturated fatty acids; PlGF, placental growth factor; PUFAs, poly-unsaturated fatty acids; SFAs, saturated fatty acids; sVCAM-1, soluble vascular cell adhesion molecule-1; ULDL, ultra low-density lipoprotein; VEGF, vascular endothelial growth factor. The prefixes XS, S, M, L, XL and XXL refer to lipoprotein sizes from extra small to extremely large
Per-year estimated marginal means for temporally changing biomarkers. Estimated marginal means are shown for proteins (a), metabolites (b) and lipoprotein particles (c) that showed a significant interaction between incident diabetes and time to end of follow-up (FDR-adjusted p<0.05) as assessed by ANOVA. Estimated marginal means are shown as point estimates and 95% CIs for the diabetes group (points with error bars) and the non-diabetes group (line with shaded area) for each year before the end of follow-up, i.e. time 0 (diabetes diagnosis for incident diabetes cases and the end of the study period for individuals without diabetes). Values have been z score-normalised to ease visualisation; hence one unit difference corresponds to one SD. The exact estimated marginal means are given in ESM Table 4. Significant estimates (FDR-adjusted p<0.05) are indicated by filled circles; non-significant estimates are indicated by open circles. Conc., concentration; IDL, intermediate-density lipoprotein; PG, phosphoglycerides; TG, triacylglycerol; ULDL, ultra low-density lipoprotein. The prefixes XS, S, M, L, XL and XXL refer to lipoprotein sizes from extra small to extremely large
Parameter importance for the top 40 markers from each molecular dataset. Parameter importance for the top 40 markers for each molecular dataset as assessed by variable importance values from the surv-RF model using 100 trees over 1000 bootstraps and the percentage of models where p<0.1 for the marker estimate calculated from the boot-Poisson model with 1000 bootstraps. The rank within each combination of biomarker data types is shown in the heatmap. Markers are arranged according to molecular type and groups. Groups are coloured to assist distinction between marker groups. Variable importance has been multiplied by 10 to give a range of 0–1. AMI, acute myocardial infarction; bFGF, basic fibroblast growth factor; CAD, coronary artery disease; CKD, chronic kidney disease; FA, fatty acids; GIP, gastric inhibitory polypeptide; GLP-1, glucagon-like peptide-1; IMID, immune-mediated inflammatory diseases; IP-10, interferon-induced protein 10; MDC, macrophage-derived chemokine; MUFAs, mono-unsaturated fatty acids; NAFLD, non-alcoholic fatty liver disease; PlGF, placental growth factor; PUFAs, poly-unsaturated fatty acids; SFAs, saturated fatty acids; T1DM, type 1 diabetes; T2DM, type 2 diabetes; TSLP, thymic stromal lymphopoietin; ULDL, ultra low-density lipoprotein; VEGF, vascular endothelial growth factor. The prefixes XS, S, M, L, XL and XXL refer to lipoprotein sizes from extra small to extremely large
Longitudinal metabolite and protein trajectories prior to diabetes mellitus diagnosis in Danish blood donors: a nested case–control study

July 2024

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77 Reads

Diabetologia

Aims/hypothesis Metabolic risk factors and plasma biomarkers for diabetes have previously been shown to change prior to a clinical diabetes diagnosis. However, these markers only cover a small subset of molecular biomarkers linked to the disease. In this study, we aimed to profile a more comprehensive set of molecular biomarkers and explore their temporal association with incident diabetes. Methods We performed a targeted analysis of 54 proteins and 171 metabolites and lipoprotein particles measured in three sequential samples spanning up to 11 years of follow-up in 324 individuals with incident diabetes and 359 individuals without diabetes in the Danish Blood Donor Study (DBDS) matched for sex and birth year distribution. We used linear mixed-effects models to identify temporal changes before a diabetes diagnosis, either for any incident diabetes diagnosis or for type 1 and type 2 diabetes mellitus diagnoses specifically. We further performed linear and non-linear feature selection, adding 28 polygenic risk scores to the biomarker pool. We tested the time-to-event prediction gain of the biomarkers with the highest variable importance, compared with selected clinical covariates and plasma glucose. Results We identified two proteins and 16 metabolites and lipoprotein particles whose levels changed temporally before diabetes diagnosis and for which the estimated marginal means were significant after FDR adjustment. Sixteen of these have not previously been described. Additionally, 75 biomarkers were consistently higher or lower in the years before a diabetes diagnosis. We identified a single temporal biomarker for type 1 diabetes, IL-17A/F, a cytokine that is associated with multiple other autoimmune diseases. Inclusion of 12 biomarkers improved the 10-year prediction of a diabetes diagnosis (i.e. the area under the receiver operating curve increased from 0.79 to 0.84), compared with clinical information and plasma glucose alone. Conclusions/interpretation Systemic molecular changes manifest in plasma several years before a diabetes diagnosis. A particular subset of biomarkers shows distinct, time-dependent patterns, offering potential as predictive markers for diabetes onset. Notably, these biomarkers show shared and distinct patterns between type 1 diabetes and type 2 diabetes. After independent replication, our findings may be used to develop new clinical prediction models. Graphical Abstract


Vaginal Microbiota Transplantation (VMT) for treatment of vaginal dysbiosis without the use of antibiotics – A Double-Blinded Randomized Controlled Trial in healthy women with vaginal dysbiosis

July 2024

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43 Reads

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1 Citation

Here we describe the first double-blinded, randomized, placebo-controlled trial (RCT) on vaginal microbiota transplantation (VMT) without antibiotics in women with both symptomatic and asymptomatic vaginal dysbiosis. Forty-nine women were randomly assigned to VMT or placebo. The trial did not show a significant conversion to our predefined Lactobacillus -dominated microbiome. However, in participants not initially converting, antiseptic pretreatment before a subsequent VMT led to a 50% conversion rate, associated with an anti-inflammatory shift in gene expression. Metagenomic sequencing and strain-level genetic analysis confirmed donor engraftment in five of 10 women who showed microbiome conversion. Extensive exploration of the microbiome, immune response and metadata revealed differences in baseline energy metabolism in participants who later experienced donor engraftment. Treatments for vaginal dysbiosis are urgently needed and given that VMT can lead to donor engraftment and change the vaginal immune profile, future studies should focus on optimizing this treatment for various women’s health diseases.



Flowchart of study enrolment. COVID-19, coronavirus disease 2019.
Forest plots illustrating the associations in base and adjusted models. (A) Base models with HbA1c as the predictor. (B) Adjusted models with HbA1c as the predictor. (C) Base models with admission p-glucose as the predictor. (D) Adjusted models with admission p-glucose as the predictor. (E) Base models with the glycaemic gap as the predictor. (F) Adjusted models with the glycaemic gap as the predictor. The x-axis shows the fold change in protein concentration for each 1 unit increase in HbA1c (mmol/mol), admission p-glucose (mmol/L), or glycaemic gap (mmol/L), with the corresponding 95% confidence intervals. Only proteins with statistically significant false discovery rate-adjusted p-values are included.
Inflammatory and endothelial host responses in community-acquired pneumonia: exploring the relationships with HbA1c, admission plasma glucose, and glycaemic gap—a cross-sectional study

May 2024

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12 Reads

Introduction Diabetes is associated with dysregulated immune function and impaired cytokine release, while transient acute hyperglycaemia has been shown to enhance inflammatory cytokine release in preclinical studies. Although diabetes and acute hyperglycaemia are common among patients with community-acquired pneumonia (CAP), the impact of chronic, acute, and acute-on-chronic hyperglycaemia on the host response within this population remains poorly understood. This study investigated whether chronic, acute, and acute-on- chronic hyperglycaemia are associated with distinct mediators of inflammatory, endothelial, and angiogenic host response pathways in patients with CAP. Methods In a cross-sectional study of 555 patients with CAP, HbA1c, admission plasma (p)-glucose, and the glycaemic gap (admission p-glucose minus HbA1c- derived average p-glucose) were employed as measures of chronic, acute, and acute-on-chronic hyperglycaemia, respectively. Linear regression was used to model the associations between the hyperglycaemia measures and 47 proteins involved in inflammation, endothelial activation, and angiogenesis measured at admission. The models were adjusted for age, sex, CAP severity, pathogen, immunosuppression, comorbidity, and body mass index. Adjustments for multiple testing were performed with a false discovery rate threshold of less than 0.05. Results The analyses showed that HbA1c levels were positively associated with IL-8, IL-15, IL-17A/F, IL-1RA, sFlt-1, and VEGF-C. Admission plasma glucose was also positively associated with these proteins and GM-CSF. The glycaemic gap was positively associated with IL-8, IL-15, IL-17A/F, IL-2, and VEGF-C. Conclusion In conclusion, chronic, acute, and acute-on-chronic hyperglycaemia were positively associated with similar host response mediators. Furthermore, acute and acute-on-chronic hyperglycaemia had unique associations with the inflammatory pathways involving GM-CSF and IL-2, respectively.


Fig. 1 | Study design. The first row lists the datasets used in the GWAS metaanalysis, number of ET cases, controls and variants analyzed. We included variants with MAF > 0.01% in all datasets except for the Estonian dataset and the previous GWAS 12 , where variants with MAF > 1% were included. The summary data from a previous GWAS, only includes the top 10,000 variants. The last row lists the multiomics approaches used to search for potential causal genes. Expression quantitative
Fig. 2 | Manhattan plot showing common variants in the ET meta-analysis. The -log 10 P-values (y-axis) are plotted for each variant against their chromosomal position (x-axis). Variants with P-values below their weighted variant-class threshold are highlighted. Novel variants are marked in orange and previously reported variants are marked in blue. P-values are two-sided and derived from a likelihood-ratio test. Manhattan plots for each dataset are shown in Supplementary Fig. 2.
Fig. 3 | Sequence variants that associate with ET and multiomics approaches used to uncover candidate causal genes. Using multiomics approaches of the lead 12 variants, we identified 7 potential causal genes. Gray boxes indicate where data points to a candidate causal gene. Effects are shown for the minor allele. Combined Annotation Dependent Depletion (CADD) 84 score estimates the deleteriousness of sequence variants. Variants are considered pathogenic if CADD > 12.37. *Secondary signal at PPARGC1A.
GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis

April 2024

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97 Reads

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3 Citations

Communications Biology

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1 . CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1 , encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson’s disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.


Lifestyle and demographic associations with 47 inflammatory and vascular stress biomarkers in 9876 blood donors

March 2024

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79 Reads

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5 Citations

Communications Medicine

Background The emerging use of biomarkers in research and tailored care introduces a need for information about the association between biomarkers and basic demographics and lifestyle factors revealing expectable concentrations in healthy individuals while considering general demographic differences. Methods A selection of 47 biomarkers, including markers of inflammation and vascular stress, were measured in plasma samples from 9876 Danish Blood Donor Study participants. Using regression models, we examined the association between biomarkers and sex, age, Body Mass Index (BMI), and smoking. Results Here we show that concentrations of inflammation and vascular stress biomarkers generally increase with higher age, BMI, and smoking. Sex-specific effects are observed for multiple biomarkers. Conclusion This study provides comprehensive information on concentrations of 47 plasma biomarkers in healthy individuals. The study emphasizes that knowledge about biomarker concentrations in healthy individuals is critical for improved understanding of disease pathology and for tailored care and decision support tools.


Figure 1. Social trust in the DBDS. (A) Sex and year of birth distributions in the discovery cohort. Solid lines represent the median year of birth (1968 and 1965 for men and women, respectively); dashed lines represent the 25th and 75th quartiles. (B) The three social trust questionnaire items and their responses in the DBDS discovery cohort (gray bars; n = 25,819; median in red) and a random sample of the Danish population (black line; n = 10,369; source: European Social Survey; median in black). (C) Manhattan plot of associations between genetic sequence variants and social trust in the discovery cohort. (D) Manhattan plot of associations between genetic sequence variants and social trust in the meta-analysis. In (C, D), the horizontal dotted line represents the Bonferroni-corrected 5e−08 significance threshold. The genomic loci found to be associated with social trust (see Table 1) are colored in red and the closest protein-coding gene is indicated.
Figure 3. Regional patterns of association between genetic variants around the discovered loci, social trust, and a non-exhaustive list of psychological and psychiatric phenotypes. (A) Locus on chromosome 10 with lead variant rs12776883 as discovered in the discovery GWAS. (B) Locus on chromosome 7 with lead variant rs71543507 as discovered in the meta-analysis.
Sequence variants significantly associated with social trust in the discovery cohort or the meta- analysis. Genes shown are those either linked through eQTL activity to the lead variant or physically closest to it. In the case of rs71543507, we report the two closest genes, as the first is a very poorly characterized gene not available in the NCBI RefSeq dataset. alt/ref alleles Alternative/reference alleles, MAF Minor allele frequency, LD Linkage disequilibrium.
A genome-wide association study of social trust in 33,882 Danish blood donors

January 2024

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75 Reads

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2 Citations

Social trust is a heritable trait that has been linked with physical health and longevity. In this study, we performed genome-wide association studies of self-reported social trust in n = 33,882 Danish blood donors. We observed genome-wide and local evidence of genetic similarity with other brain-related phenotypes and estimated the single nucleotide polymorphism-based heritability of trust to be 6% (95% confidence interval = (2.1, 9.9)). In our discovery cohort (n = 25,819), we identified one significantly associated locus (lead variant: rs12776883) in an intronic enhancer region of PLPP4 , a gene highly expressed in brain, kidneys, and testes. However, we could not replicate the signal in an independent set of donors who were phenotyped a year later (n = 8063). In the subsequent meta-analysis, we found a second significantly associated variant (rs71543507) in an intergenic enhancer region. Overall, our work confirms that social trust is heritable, and provides an initial look into the genetic factors that influence it.


Variants at the Interleukin 1 Gene Locus and Pericarditis

December 2023

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66 Reads

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14 Citations

JAMA Cardiology

Importance Recurrent pericarditis is a treatment challenge and often a debilitating condition. Drugs inhibiting interleukin 1 cytokines are a promising new treatment option, but their use is based on scarce biological evidence and clinical trials of modest sizes, and the contributions of innate and adaptive immune processes to the pathophysiology are incompletely understood. Objective To use human genomics, transcriptomics, and proteomics to shed light on the pathogenesis of pericarditis. Design, Setting, and Participants This was a meta-analysis of genome-wide association studies of pericarditis from 5 countries. Associations were examined between the pericarditis-associated variants and pericarditis subtypes (including recurrent pericarditis) and secondary phenotypes. To explore mechanisms, associations with messenger RNA expression ( cis -eQTL), plasma protein levels (pQTL), and CpG methylation of DNA (ASM-QTL) were assessed. Data from Iceland (deCODE genetics, 1983-2020), Denmark (Copenhagen Hospital Biobank/Danish Blood Donor Study, 1977-2022), the UK (UK Biobank, 1953-2021), the US (Intermountain, 1996-2022), and Finland (FinnGen, 1970-2022) were included. Data were analyzed from September 2022 to August 2023. Exposure Genotype. Main Outcomes and Measures Pericarditis. Results In this genome-wide association study of 4894 individuals with pericarditis (mean [SD] age at diagnosis, 51.4 [17.9] years, 2734 [67.6%] male, excluding the FinnGen cohort), associations were identified with 2 independent common intergenic variants at the interleukin 1 locus on chromosome 2q14. The lead variant was rs12992780 (T) (effect allele frequency [EAF], 31%-40%; odds ratio [OR], 0.83; 95% CI, 0.79-0.87; P = 6.67 × 10 ⁻¹⁶ ), downstream of IL1B and the secondary variant rs7575402 (A or T) (EAF, 45%-55%; adjusted OR, 0.89; 95% CI, 0.85-0.93; adjusted P = 9.6 × 10 ⁻⁸ ). The lead variant rs12992780 had a smaller odds ratio for recurrent pericarditis (0.76) than the acute form (0.86) ( P for heterogeneity = .03) and rs7575402 was associated with CpG methylation overlapping binding sites of 4 transcription factors known to regulate interleukin 1 production: PU.1 (encoded by SPI1 ), STAT1, STAT3, and CCAAT/enhancer-binding protein β (encoded by CEBPB ). Conclusions and Relevance This study found an association between pericarditis and 2 independent sequence variants at the interleukin 1 gene locus. This finding has the potential to contribute to development of more targeted and personalized therapy of pericarditis with interleukin 1–blocking drugs.


Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura

October 2023

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191 Reads

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20 Citations

Nature Genetics

Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2 , PALMD , ABO and LRRK2 ) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A , encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis -regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.


Citations (11)


... The Vel blood group antigens may play a significant role in metabolic function, as evidenced by the metabolic characterization of individuals homozygous for the SMIM1 deletion (homozygous Vel-negative). Studies utilizing plasma biochemistry, calorimetric chambers, and dual-energy X-ray absorptiometry (DXA) scans have revealed that these individuals exhibit a range of metabolic traits [18]. These include increased adiposity, signs of inflammation, altered liver function, and changes in triglyceride and lipoprotein metabolism. ...

Reference:

Molecular Basis and Clinical Research Progress of the Vel Blood Group System
SMIM1 absence is associated with reduced energy expenditure and excess weight

Med

... Novel approaches such as Mendelian randomization (MR), colocalization assays, spatial transcriptomics, and transcriptome-wide association studies (TWAS) could leverage larger GWAS datasets to establish robust links between gene expression and disease risk [45]. Additionally, larger GWAS studies could facilitate colocalization assays with expression qualitative trait loci (eQTLs) [46]. ...

GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis

Communications Biology

... PREGCO is a prospective cohort of pregnant women from Copenhagen University Hospital, Hvidovre, Denmark, that took place during the first coronavirus disease 2019 (COVID-19) pandemic wave in Denmark, between 4 April 2020 and 3 July 2020 [16,17]. Participants were invited to participate at the second trimester malformation scan (gestational weeks [18][19][20][21][22]. All pregnant women in Denmark are offered this scan and more than 90% accept. ...

Lifestyle and demographic associations with 47 inflammatory and vascular stress biomarkers in 9876 blood donors

Communications Medicine

... PLPP4 plays a vital role in facilitating the transfer of signals inside cells, dynamic changes in membrane structure, and intracellular material transport 48 . PLPP4 is highly expressed in the brain, especially in the hippocampus, substantia nigra, and other brain regions, and is a driving factor in neurological diseases 49,50 . Studies have suggested that increased PLPP4 activity and expression may indicate the onset of neurological disease 48 . ...

A genome-wide association study of social trust in 33,882 Danish blood donors

... p=8.3´10 -6 ) ( Fig 4F). Notably, a recent GWAS study on pericarditis revealed a variant (rs12992780, with risk allele T) near IL1B 53 . Linkage disequilibrium (LD) analysis between rs12992780 and rs2708914 revealed that the theoretical frequency of risk allele T-T haplotypes was To further validate the elevated IL1 signaling in AfrA keratinocytes, we isolated keratinocytes from skin biopsies from individuals self-reported as African ancestry or European ancestry (see Methods), to understand the genome-wide expression differences in IL1 stimulation effect through bulk RNA-seq. ...

Variants at the Interleukin 1 Gene Locus and Pericarditis
  • Citing Article
  • December 2023

JAMA Cardiology

... Migraine and epilepsy, despite being distinct neurological disorders, share some pathophysiological features, including abnormal brain electrical activity, suggesting potential comorbidity as evidenced by shared clinical manifestations and treatment responses (57,58). This hypothesis is supported by reports linking FHM-associated gene mutations with ataxia and epilepsy (15)(16)(17)(18)(19)(20)(21)(22)(23)48,59). Gene testing of epilepsy patients has revealed heterozygous variants in the FHM3-associated SCN1A gene (60). ...

Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura

Nature Genetics

... Genetic regulatory networks (GRNs) [1][2][3] describe the complex networks of molecular regulators that control the expression of genes in a cell. They are key in understanding how genes interact with one another and how cells respond to internal and external stimuli. ...

Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits

... We also observed trends in metabolic pathways: a decrease in aminoacyl tRNA biosynthesis, metabolism of glycine, serine, and threonine, biosynthesis of valine, leucine, and isoleucine, and lysine degradation pathways. Aminoacyl tRNA biosynthesis is involved in the synthesis of amino acids as well as in a variety of metabolic processes such as protein synthesis, hormone synthesis, and glycolipid metabolism (28).Roas et al. found a significant enrichment of metabolites associated with aminoacyl-tRNA biosynthesis after the use of metformin (29), and in our study we found that the metabolism of a wide variety of amino acids centered on aminoacyl-tRNA biosynthesis mainly including amino acids such as glycine, serine, threonine, methionine, lysine, alanine, isoleucine, leucine, and tyrosine, and that a decrease in the metabolic pathways of glycine, serine, and threonine indicated an increase in the levels of glycine, serine, and threonine, which was in agreement with the previous study (30), in which glycine, serine, and threonine were associated with an improvement in insulin sensitivity (31). Previous studies have shown that changes in plasma glycine may be one of the biomarkers of T2DM (32), and Chen et al. found in their study that insulin secretion was higher in diabetic rats taking glycine compared to diabetic rats not taking glycine (33). ...

Author Correction: Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Nature Biotechnology

... Mice with a left ventricular ejection fraction (LVEF) between 55-60% one day post-occlusion were considered to have a successful I/R model. Prior to I/R injury, mice were administered Nicotinamide Riboside (NR, NIAGEN® ChromaDex) at doses ranging from 200-800 mg/kg/day diluted in drinking water for seven days [25]. ...

Oral supplementation of nicotinamide riboside alters intestinal microbial composition in rats and mice, but not humans

npj Aging

... Additionally, experiments generating these data modalities are conducted in various biological systems, including cell lines, organoids, and patient-derived samples, offering diverse experimental contexts. Phenotypic datasets, such as CRISPR-Cas9 and drug-response screens, are invaluable for identifying genetic dependencies and therapeutic vulnerabilities, linking molecular profiles to functional biological effects [7,13,23,[173][174][175]. ...

Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Nature Biotechnology