Publications by authors named "Markku Laakso"

503 Publications

Profiles of glucose metabolism in different prediabetes phenotypes, classified by fasting glycemia, 2-hour OGTT, glycated hemoglobin, and 1-hour OGTT: An IMI DIRECT study.

Diabetes 2021 Jul 7. Epub 2021 Jul 7.

Department of Epidemiology and Data Science, Amsterdam Medical Centre, location VUMC, Amsterdam, the Netherlands.

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (=2111) underwent 2h-75g OGTT at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose, IFG; impaired glucose tolerance, IGT; HbA1c-prediabetes, IA1c), two defects (IFG+IGT, IFG+IA1c, IGT+IA1c), or all defects (IFG+IGT+IA1c). Beta-cell function (BCF) and insulin sensitivity (IS) were assessed from OGTT. At baseline, when pooling participants with isolated defects, they showed impairment in both BCF and IS compared to healthy controls. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, IGT showed lower IS, insulin secretion at reference glucose (ISR), and insulin secretion potentiation (p<0.002). Conversely, IA1c showed higher IS and ISR (p<0.0001). Among groups with two defects, we similarly found differences in both BCF and IS. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, p<0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared to the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.
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http://dx.doi.org/10.2337/db21-0227DOI Listing
July 2021

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Nat Commun 2021 06 9;12(1):3505. Epub 2021 Jun 9.

Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
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http://dx.doi.org/10.1038/s41467-021-23556-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190084PMC
June 2021

Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences.

Hum Genomics 2021 Jun 7;15(1):34. Epub 2021 Jun 7.

McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.

Background: Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell-type composition. Here, we studied MT-CN variation in blood-derived DNA from 19184 Finnish individuals using a combination of genome (N = 4163) and exome sequencing (N = 19034) data as well as imputed genotypes (N = 17718).

Results: We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6 × 10), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0 × 10), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0 × 10) and other metabolic syndrome (metS)-related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell-type composition.

Conclusion: These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits.
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http://dx.doi.org/10.1186/s40246-021-00335-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185936PMC
June 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.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Blood n-3 fatty acid levels and total and cause-specific mortality from 17 prospective studies.

Nat Commun 2021 04 22;12(1):2329. Epub 2021 Apr 22.

MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK.

The health effects of omega-3 fatty acids have been controversial. Here we report the results of a de novo pooled analysis conducted with data from 17 prospective cohort studies examining the associations between blood omega-3 fatty acid levels and risk for all-cause mortality. Over a median of 16 years of follow-up, 15,720 deaths occurred among 42,466 individuals. We found that, after multivariable adjustment for relevant risk factors, risk for death from all causes was significantly lower (by 15-18%, at least p < 0.003) in the highest vs the lowest quintile for circulating long chain (20-22 carbon) omega-3 fatty acids (eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids). Similar relationships were seen for death from cardiovascular disease, cancer and other causes. No associations were seen with the 18-carbon omega-3, alpha-linolenic acid. These findings suggest that higher circulating levels of marine n-3 PUFA are associated with a lower risk of premature death.
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http://dx.doi.org/10.1038/s41467-021-22370-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062567PMC
April 2021

Association of structural variation with cardiometabolic traits in Finns.

Am J Hum Genet 2021 04;108(4):583-596

McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA; Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA. Electronic address:

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10) and is also associated with increased levels of total cholesterol (p = 1.22 × 10) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10) and alanine (p = 6.14 × 10) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.
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http://dx.doi.org/10.1016/j.ajhg.2021.03.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059371PMC
April 2021

Novel biomarkers associated with incident heart failure in 10 106 Finnish men.

ESC Heart Fail 2021 02 5;8(1):605-614. Epub 2020 Dec 5.

Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.

Aims: There are only a few studies on novel biomarkers for incident heart failure (HF). We investigated the association of multiple circulating biomarkers with incident HF in a large prospective population-based study.

Methods And Results: Conventional risk factors and inflammatory biomarkers were measured, and systemic metabolic measures determined by a high-throughput serum nuclear magnetic resonance platform in a population-based Metabolic Syndrome in Men study including 10 106 Finnish men without HF at baseline. During an 8.8 year follow-up, 172 (1.7%) participants developed HF. Adiponectin, high-sensitivity C-reactive protein (hs-CRP), glycoprotein acetyls, alanine, phenylalanine, glycerol, and pyruvate were associated with incident HF in unadjusted Cox regression analyses, in addition to age, systolic blood pressure, body mass index (BMI), waist circumference, fasting plasma glucose and insulin, haemoglobin A1c (HbA1c), and urinary albumin excretion rate (UAER). After adjustment for age, BMI, diabetes, and statin medication, only adiponectin [hazard ratio (HR) 1.18 (1.10-1.26, P = 4.1E-08)], pyruvate [HR 1.38 (1.28-1.50, P = 8.2E-05)], and UAER [HR 1.15 (1.11-1.18, P = 7.8E-06)] remained statistically significant. In principal component analysis of biomarkers associated with HF in univariate Cox regression analysis, we identified six components, explaining 61.7% of total variance. Four principal components, one with significant loadings on waist, BMI, fasting plasma insulin, interleukin 1 receptor antagonist, and hs-CRP; another on pyruvate, glycoprotein acetyls, alanine, glycerol and HbA1c; third on age and glomerular filtration rate; and fourth on systolic blood pressure, UAER, and adiponectin, significantly associated with incident HF.

Conclusions: Several novel metabolic and inflammatory biomarkers were associated with incident HF, suggesting early activation of respective pathways in the pathogenesis of HF.
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http://dx.doi.org/10.1002/ehf2.13132DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835558PMC
February 2021

n-3 Fatty Acid Biomarkers and Incident Type 2 Diabetes: An Individual Participant-Level Pooling Project of 20 Prospective Cohort Studies.

Diabetes Care 2021 May 3;44(5):1133-1142. Epub 2021 Mar 3.

Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Objective: Prospective associations between n-3 fatty acid biomarkers and type 2 diabetes (T2D) risk are not consistent in individual studies. We aimed to summarize the prospective associations of biomarkers of α-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with T2D risk through an individual participant-level pooled analysis.

Research Design And Methods: For our analysis we incorporated data from a global consortium of 20 prospective studies from 14 countries. We included 65,147 participants who had blood measurements of ALA, EPA, DPA, or DHA and were free of diabetes at baseline. De novo harmonized analyses were performed in each cohort following a prespecified protocol, and cohort-specific associations were pooled using inverse variance-weighted meta-analysis.

Results: A total of 16,693 incident T2D cases were identified during follow-up (median follow-up ranging from 2.5 to 21.2 years). In pooled multivariable analysis, per interquintile range (difference between the 90th and 10th percentiles for each fatty acid), EPA, DPA, DHA, and their sum were associated with lower T2D incidence, with hazard ratios (HRs) and 95% CIs of 0.92 (0.87, 0.96), 0.79 (0.73, 0.85), 0.82 (0.76, 0.89), and 0.81 (0.75, 0.88), respectively (all < 0.001). ALA was not associated with T2D (HR 0.97 [95% CI 0.92, 1.02]) per interquintile range. Associations were robust across prespecified subgroups as well as in sensitivity analyses.

Conclusions: Higher circulating biomarkers of seafood-derived n-3 fatty acids, including EPA, DPA, DHA, and their sum, were associated with lower risk of T2D in a global consortium of prospective studies. The biomarker of plant-derived ALA was not significantly associated with T2D risk.
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http://dx.doi.org/10.2337/dc20-2426DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132316PMC
May 2021

Machine Learning Reveals Time-Varying Microbial Predictors with Complex Effects on Glucose Regulation.

mSystems 2021 Feb 16;6(1). Epub 2021 Feb 16.

Institute of Genomics, Estonian Genome Centre, University of Tartu, Tartu, Estonia

The incidence of type 2 diabetes (T2D) has been increasing globally, and a growing body of evidence links type 2 diabetes with altered microbiota composition. Type 2 diabetes is preceded by a long prediabetic state characterized by changes in various metabolic parameters. We tested whether the gut microbiome could have predictive potential for T2D development during the healthy and prediabetic disease stages. We used prospective data of 608 well-phenotyped Finnish men collected from the population-based Metabolic Syndrome in Men (METSIM) study to build machine learning models for predicting continuous glucose and insulin measures in a shorter (1.5 year) and longer (4 year) period. Our results show that the inclusion of the gut microbiome improves prediction accuracy for modeling T2D-associated parameters such as glycosylated hemoglobin and insulin measures. We identified novel microbial biomarkers and described their effects on the predictions using interpretable machine learning techniques, which revealed complex linear and nonlinear associations. Additionally, the modeling strategy carried out allowed us to compare the stability of model performance and biomarker selection, also revealing differences in short-term and long-term predictions. The identified microbiome biomarkers provide a predictive measure for various metabolic traits related to T2D, thus providing an additional parameter for personal risk assessment. Our work also highlights the need for robust modeling strategies and the value of interpretable machine learning. Recent studies have shown a clear link between gut microbiota and type 2 diabetes. However, current results are based on cross-sectional studies that aim to determine the microbial dysbiosis when the disease is already prevalent. In order to consider the microbiome as a factor in disease risk assessment, prospective studies are needed. Our study is the first study that assesses the gut microbiome as a predictive measure for several type 2 diabetes-associated parameters in a longitudinal study setting. Our results revealed a number of novel microbial biomarkers that can improve the prediction accuracy for continuous insulin measures and glycosylated hemoglobin levels. These results make the prospect of using the microbiome in personalized medicine promising.
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http://dx.doi.org/10.1128/mSystems.01191-20DOI Listing
February 2021

The FADS1 Genotype Modifies Metabolic Responses to the Linoleic Acid and Alpha-linolenic Acid Containing Plant Oils-Genotype Based Randomized Trial FADSDIET2.

Mol Nutr Food Res 2021 04 3;65(7):e2001004. Epub 2021 Mar 3.

Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, Kuopio, Finland.

Scope: The article investigates the FADS1 rs174550 genotype interaction with dietary intakes of high linoleic acid (LA) and high alpha-linolenic acid (ALA) on the response of fatty acid composition of plasma phospholipids (PLs), and of markers of low-grade inflammation and glucose-insulin homeostasis.

Methods And Results: One-hundred thirty homozygotes men for FADS1 rs174550 SNP (TT and CC genotypes) were randomized to an 8-week intervention with either LA- or ALA-enriched diet (13 E% PUFA). The source of LA and ALA are 30-50 mL of sunflower oil (SFO, 62-63% LA) and Camelina sativa oil (CSO, 30- are randomized to an 35% ALA), respectively. In the SFO arm, there is a significant genotype x diet interaction for the proportion of arachidonic acid in plasma phospholipids (p < 0.001), disposition index (DI ) (p = 0.039), and for serum high-sensitive c-reactive protein (hs-CRP, p = 0.029) after excluding the participants with hs-CRP concentration of >10 mg L and users of statins or anti-inflammatory therapy. In the CSO arm, there are significant genotype x diet interactions for n-3 polyunsaturated fatty acids, but not for the clinical characteristics.

Conclusions: The FADS1 genotype modifies the response to high PUFA diets, especially to high-LA diet. These findings suggest that approaches considering FADS variation may be useful in personalized dietary counseling.
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http://dx.doi.org/10.1002/mnfr.202001004DOI Listing
April 2021

Large-scale association analyses identify host factors influencing human gut microbiome composition.

Nat Genet 2021 02 18;53(2):156-165. Epub 2021 Jan 18.

Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10 < P < 5 × 10) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.
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http://dx.doi.org/10.1038/s41588-020-00763-1DOI Listing
February 2021

Insulin Resistance Is Associated With Enhanced Brain Glucose Uptake During Euglycemic Hyperinsulinemia: A Large-Scale PET Cohort.

Diabetes Care 2021 Mar 14;44(3):788-794. Epub 2021 Jan 14.

Turku PET Centre, University of Turku, Turku, Finland

Objective: Whereas insulin resistance is expressed as reduced glucose uptake in peripheral tissues, the relationship between insulin resistance and brain glucose metabolism remains controversial. Our aim was to examine the association of insulin resistance and brain glucose uptake (BGU) during a euglycemic hyperinsulinemic clamp in a large sample of study participants across a wide range of age and insulin sensitivity.

Research Design And Methods: [F]-fluorodeoxyglucose positron emission tomography (PET) data from 194 participants scanned under clamp conditions were compiled from a single-center cohort. BGU was quantified by the fractional uptake rate. We examined the association of age, sex, M value from the clamp, steady-state insulin and free fatty acid levels, C-reactive protein levels, HbA, and presence of type 2 diabetes with BGU using Bayesian hierarchical modeling.

Results: Insulin sensitivity, indexed by the M value, was associated negatively with BGU in all brain regions, confirming that in insulin-resistant participants BGU was enhanced during euglycemic hyperinsulinemia. In addition, the presence of type 2 diabetes was associated with additional increase in BGU. On the contrary, age was negatively related to BGU. Steady-state insulin levels, C-reactive protein and free fatty acid levels, sex, and HbA were not associated with BGU.

Conclusions: In this large cohort of participants of either sex across a wide range of age and insulin sensitivity, insulin sensitivity was the best predictor of BGU.
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http://dx.doi.org/10.2337/dc20-1549DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7896252PMC
March 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.
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http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

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

Simvastatin profoundly impairs energy metabolism in primary human muscle cells.

Endocr Connect 2020 Nov;9(11):1103-1113

Minerva Foundation Institute for Medical Research, Helsinki, Finland.

Objectives: Simvastatin use is associated with muscular side effects, and increased risk for type 2 diabetes (T2D). In clinical use, simvastatin is administered in inactive lipophilic lactone-form, which is then converted to active acid-form in the body. Here, we have investigated if lactone- and acid-form simvastatin differentially affect glucose metabolism and mitochondrial respiration in primary human skeletal muscle cells.

Methods: Muscle cells were exposed separately to lactone- and acid-form simvastatin for 48 h. After pre-exposure, glucose uptake and glycogen synthesis were measured using radioactive tracers; insulin signalling was detected with Western blotting; and glycolysis, mitochondrial oxygen consumption and ATP production were measured with Seahorse XFe96 analyzer.

Results: Lactone-form simvastatin increased glucose uptake and glycogen synthesis, whereas acid-form simvastatin did not affect glucose uptake and decreased glycogen synthesis. Phosphorylation of insulin signalling targets Akt substrate 160 kDa (AS160) and glycogen synthase kinase 3β (GSK3β) was upregulated with lactone-, but not with acid-form simvastatin. Exposure to both forms of simvastatin led to a decrease in glycolysis and glycolytic capacity, as well as to a decrease in mitochondrial respiration and ATP production.

Conclusions: These data suggest that lactone- and acid-forms of simvastatin exhibit differential effects on non-oxidative glucose metabolism as lactone-form increases and acid-form impairs glucose storage into glycogen, suggesting impaired insulin sensitivity in response to acid-form simvastatin. Both forms profoundly impair oxidative glucose metabolism and energy production in human skeletal muscle cells. These effects may contribute to muscular side effects and risk for T2D observed with simvastatin use.
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http://dx.doi.org/10.1530/EC-20-0444DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780958PMC
November 2020

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

Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study.

PLoS One 2020 30;15(11):e0242360. Epub 2020 Nov 30.

Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.

Aim: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D.

Methods: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders.

Results: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose.

Conclusions: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242360PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703960PMC
January 2021

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals.

Nat Genet 2020 12 23;52(12):1314-1332. Epub 2020 Nov 23.

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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http://dx.doi.org/10.1038/s41588-020-00713-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610439PMC
December 2020

Metabolite Signature of Albuminuria Involves Amino Acid Pathways in 8661 Finnish Men Without Diabetes.

J Clin Endocrinol Metab 2021 Jan;106(1):143-152

Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.

Objective: To investigate the metabolite signature of albuminuria in individuals without diabetes or chronic kidney disease to identify possible mechanisms that result in increased albuminuria and elevated risk of type 2 diabetes (T2D).

Research Design And Methods: The study cohort was a population-based Metabolic Syndrome In Men (METSIM) study including 8861 middle-aged and elderly Finnish men without diabetes or chronic kidney disease at baseline. A total of 5504 men participated in a 7.5-year follow-up study, and 5181 of them had metabolomics data measured by Metabolon's ultrahigh performance liquid chromatography-tandem mass spectroscopy.

Results: We found 32 metabolites significantly (P < 5.8 × 10-5) and positively associated with the urinary albumin excretion (UAE) rate. These metabolites were especially downstream metabolites in the amino acid metabolism pathways (threonine, phenylalanine, leucine, arginine). In our 7.5-year follow-up study, UAE was significantly associated with a 19% increase (hazard ratio 1.19; 95% confidence interval, 1.13-1.25) in the risk of T2D after the adjustment for confounding factors. Conversion to diabetes was more strongly associated with a decrease in insulin secretion than a decrease in insulin sensitivity.

Conclusions: Metabolic signature of UAE included multiple metabolites, especially from the amino acid metabolism pathways known to be associated with low-grade inflammation, and accumulation of reactive oxygen species that play an important role in the pathogenesis of UAE. These metabolites were primarily associated with an increase in UAE and were secondarily associated with a decrease in insulin secretion and insulin sensitivity, resulting in an increased risk of incident T2D.
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http://dx.doi.org/10.1210/clinem/dgaa661DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765644PMC
January 2021

RIPK1 gene variants associate with obesity in humans and can be therapeutically silenced to reduce obesity in mice.

Nat Metab 2020 10 28;2(10):1113-1125. Epub 2020 Sep 28.

Cardiometabolic microRNA Laboratory, University of Ottawa Heart Institute, Ottawa, Ontario, Canada.

Obesity is a major public health burden worldwide and is characterized by chronic low-grade inflammation driven by the cooperation of the innate immune system and dysregulated metabolism in adipose tissue and other metabolic organs. Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) is a central regulator of inflammatory cell function that coordinates inflammation, apoptosis and necroptosis in response to inflammatory stimuli. Here we show that genetic polymorphisms near the human RIPK1 locus associate with increased RIPK1 gene expression and obesity. We show that one of these single nucleotide polymorphisms is within a binding site for E4BP4 and increases RIPK1 promoter activity and RIPK1 gene expression in adipose tissue. Therapeutic silencing of RIPK1 in vivo in a mouse model of diet-induced obesity dramatically reduces fat mass, total body weight and improves insulin sensitivity, while simultaneously reducing macrophage and promoting invariant natural killer T cell accumulation in adipose tissue. These findings demonstrate that RIPK1 is genetically associated with obesity, and reducing RIPK1 expression is a potential therapeutic approach to target obesity and related diseases.
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http://dx.doi.org/10.1038/s42255-020-00279-2DOI Listing
October 2020

Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity.

J Clin Endocrinol Metab 2021 Jan;106(1):80-90

Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.

Context: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity.

Objective: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies.

Design: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models.

Results: Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity.

Conclusion: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.
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http://dx.doi.org/10.1210/clinem/dgaa653DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765651PMC
January 2021

Fgr kinase is required for proinflammatory macrophage activation during diet-induced obesity.

Nat Metab 2020 09 17;2(9):974-988. Epub 2020 Sep 17.

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.

Proinflammatory macrophages are key in the development of obesity. In addition, reactive oxygen species (ROS), which activate the Fgr tyrosine kinase, also contribute to obesity. Here we show that ablation of Fgr impairs proinflammatory macrophage polarization while preventing high-fat diet (HFD)-induced obesity in mice. Systemic ablation of Fgr increases lipolysis and liver fatty acid oxidation, thereby avoiding steatosis. Knockout of Fgr in bone marrow (BM)-derived cells is sufficient to protect against insulin resistance and liver steatosis following HFD feeding, while the transfer of Fgr-expressing BM-derived cells reverts protection from HFD feeding in Fgr-deficient hosts. Scavenging of mitochondrial peroxides is sufficient to prevent Fgr activation in BM-derived cells and HFD-induced obesity. Moreover, Fgr expression is higher in proinflammatory macrophages and correlates with obesity traits in both mice and humans. Thus, our findings reveal the mitochondrial ROS-Fgr kinase as a key regulatory axis in proinflammatory adipose tissue macrophage activation, diet-induced obesity, insulin resistance and liver steatosis.
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http://dx.doi.org/10.1038/s42255-020-00273-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8225238PMC
September 2020

The causal effect of obesity on prediabetes and insulin resistance reveals the important role of adipose tissue in insulin resistance.

PLoS Genet 2020 09 14;16(9):e1009018. Epub 2020 Sep 14.

Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.

Reverse causality has made it difficult to establish the causal directions between obesity and prediabetes and obesity and insulin resistance. To disentangle whether obesity causally drives prediabetes and insulin resistance already in non-diabetic individuals, we utilized the UK Biobank and METSIM cohort to perform a Mendelian randomization (MR) analyses in the non-diabetic individuals. Our results suggest that both prediabetes and systemic insulin resistance are caused by obesity (p = 1.2×10-3 and p = 3.1×10-24). As obesity reflects the amount of body fat, we next studied how adipose tissue affects insulin resistance. We performed both bulk RNA-sequencing and single nucleus RNA sequencing on frozen human subcutaneous adipose biopsies to assess adipose cell-type heterogeneity and mitochondrial (MT) gene expression in insulin resistance. We discovered that the adipose MT gene expression and body fat percent are both independently associated with insulin resistance (p≤0.05 for each) when adjusting for the decomposed adipose cell-type proportions. Next, we showed that these 3 factors, adipose MT gene expression, body fat percent, and adipose cell types, explain a substantial amount (44.39%) of variance in insulin resistance and can be used to predict it (p≤2.64×10-5 in 3 independent human cohorts). In summary, we demonstrated that obesity is a strong determinant of both prediabetes and insulin resistance, and discovered that individuals' adipose cell-type composition, adipose MT gene expression, and body fat percent predict their insulin resistance, emphasizing the critical role of adipose tissue in systemic insulin resistance.
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http://dx.doi.org/10.1371/journal.pgen.1009018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515203PMC
September 2020

Adiponectin GWAS loci harboring extensive allelic heterogeneity exhibit distinct molecular consequences.

PLoS Genet 2020 09 11;16(9):e1009019. Epub 2020 Sep 11.

Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.

Loci identified in genome-wide association studies (GWAS) can include multiple distinct association signals. We sought to identify the molecular basis of multiple association signals for adiponectin, a hormone involved in glucose regulation secreted almost exclusively from adipose tissue, identified in the Metabolic Syndrome in Men (METSIM) study. With GWAS data for 9,262 men, four loci were significantly associated with adiponectin: ADIPOQ, CDH13, IRS1, and PBRM1. We performed stepwise conditional analyses to identify distinct association signals, a subset of which are also nearly independent (lead variant pairwise r2<0.01). Two loci exhibited allelic heterogeneity, ADIPOQ and CDH13. Of seven association signals at the ADIPOQ locus, two signals colocalized with adipose tissue expression quantitative trait loci (eQTLs) for three transcripts: trait-increasing alleles at one signal were associated with increased ADIPOQ and LINC02043, while trait-increasing alleles at the other signal were associated with decreased ADIPOQ-AS1. In reporter assays, adiponectin-increasing alleles at two signals showed corresponding directions of effect on transcriptional activity. Putative mechanisms for the seven ADIPOQ signals include a missense variant (ADIPOQ G90S), a splice variant, a promoter variant, and four enhancer variants. Of two association signals at the CDH13 locus, the first signal consisted of promoter variants, including the lead adipose tissue eQTL variant for CDH13, while a second signal included a distal intron 1 enhancer variant that showed ~2-fold allelic differences in transcriptional reporter activity. Fine-mapping and experimental validation demonstrated that multiple, distinct association signals at these loci can influence multiple transcripts through multiple molecular mechanisms.
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http://dx.doi.org/10.1371/journal.pgen.1009019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511027PMC
September 2020

Generation of a human induced pluripotent stem cell line (UEFi003-A) carrying heterozygous A673T variant in amyloid precursor protein associated with a reduced risk of Alzheimer's disease.

Stem Cell Res 2020 10 2;48:101968. Epub 2020 Sep 2.

Neuroscience Center, University of Helsinki, Helsinki, Finland; A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland. Electronic address:

A673T mutation in the amyloid precursor protein (APP) is a rare variant associated with a reduced risk of late-onset Alzheimer's disease (AD) and age-related cognitive decline. The A673T mutation decreases beta-amyloid (Aβ) production and aggregation in neuronal cultures in vitro. Here we have identified a Finnish non-diseased male individual carrying a heterozygous A673T mutation, obtained a skin biopsy sample from him, and generated an iPSC line using commercially available integration-free Sendai virus-based kit. The established iPSC line retained the mutation, expressed pluripotency markers, had a normal karyotype, and differentiated into all three germ layers in vitro.
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http://dx.doi.org/10.1016/j.scr.2020.101968DOI Listing
October 2020
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