👤 M den Hoed

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Also published as: Marcel den Hoed
articles
Oveis Jamialahmadi, Endrina Mujica, Lowri Morris +18 more · 2025 · Clinical and molecular hepatology · added 2026-04-24
Metabolic dysfunction-associated steatotic liver disease (MASLD) may progress to liver inflammation, fibrosis, cirrhosis and hepatocellular carcinoma. So far, genome-wide association studies explain a Show more
Metabolic dysfunction-associated steatotic liver disease (MASLD) may progress to liver inflammation, fibrosis, cirrhosis and hepatocellular carcinoma. So far, genome-wide association studies explain a small fraction of MASLD heritability. We sought to identify novel genetic determinants of MASLD by exploring interactions between genetic variants and body mass index (BMI). First, we examined genome-wide interactions with BMI for circulating alanine aminotransferase (ALT) levels using UK Biobank data. For identified loci, we next examined associations with hepatic proton density fat fraction (PDFF) in 35,146 independent UK Biobank participants. Associations with PDFF were replicated in four independent European cohorts, followed by a phenome-wide association study. Finally, we used human liver epigenomic maps and CRISPR/Cas9 experiments in vitro and in vivo to functionally characterize the CYP7A1 locus. Thirteen loci interact with BMI for ALT (P<5E-8), including eight well-known genetic modulators of MASLD. Two loci-UBXN2B/CYP7A1 and GIPR-are additionally associated with PDFF. For the intronic rs34783010 in GIPR, the minor T allele is associated with lower BMI and higher HbA1c and liver triglyceride content in humans. The UBXN2B/CYP7A1 locus is associated with PDFF in four additional European cohorts. Epigenomic data and in vitro experiments in human liver cells prioritise rs10504255 and CYP7A1 as the functional effectors in this locus. Perturbation of CYP7A1 orthologues using CRISPR/Cas9 results in less liver fat in 10-day-old, metabolically challenged zebrafish larvae. A genome-wide single nucleotide polymorphism×BMI design fuelled identification of two MASLD genes: CYP7A1 and GIPR. Show less
📄 PDF DOI: 10.3350/cmh.2025.0159
GIPR
Iain Mathieson, Felix R Day, Nicola Barban +122 more · 2023 · Nature human behaviour · Nature · added 2026-04-24
Iain Mathieson, Felix R Day, Nicola Barban, Felix C Tropf, David M Brazel, eQTLGen Consortium, BIOS Consortium, Ahmad Vaez, Natalie van Zuydam, Bárbara D Bitarello, Eugene J Gardner, Evelina T Akimova, Ajuna Azad, Sven Bergmann, Lawrence F Bielak, Dorret I Boomsma, Kristina Bosak, Marco Brumat, Julie E Buring, David Cesarini, Daniel I Chasman, Jorge E Chavarro, Massimiliano Cocca, Maria Pina Concas, George Davey Smith, Gail Davies, Ian J Deary, Tõnu Esko, Jessica D Faul, FinnGen Study, Oscar Franco, Andrea Ganna, Audrey J Gaskins, Andrea Gelemanovic, Eco J C de Geus, Christian Gieger, Giorgia Girotto, Bamini Gopinath, Hans Jörgen Grabe, Erica P Gunderson, Caroline Hayward, Chunyan He, Diana van Heemst, W David Hill, Eva R Hoffmann, Georg Homuth, Jouke Jan Hottenga, Hongyang Huang, Elina Hyppӧnen, M Arfan Ikram, Rick Jansen, Magnus Johannesson, Zoha Kamali, Sharon L R Kardia, Maryam Kavousi, Annette Kifley, Tuomo Kiiskinen, Peter Kraft, Brigitte Kühnel, Claudia Langenberg, Gerald Liew, LifeLines Cohort Study, Penelope A Lind, Jian'an Luan, Reedik Mägi, Patrik K E Magnusson, Anubha Mahajan, Nicholas G Martin, Hamdi Mbarek, Mark I McCarthy, George McMahon, Sarah E Medland, Thomas Meitinger, Andres Metspalu, Evelin Mihailov, Lili Milani, Stacey A Missmer, Paul Mitchell, Stine Møllegaard, Dennis O Mook-Kanamori, Anna Morgan, Peter J van der Most, Renée de Mutsert, Matthias Nauck, Ilja M Nolte, Raymond Noordam, Brenda W J H Penninx, Annette Peters, Patricia A Peyser, Ozren Polašek, Chris Power, Ajka Pribisalic, Paul Redmond, Janet W Rich-Edwards, Paul M Ridker, Cornelius A Rietveld, Susan M Ring, Lynda M Rose, Rico Rueedi, Vallari Shukla, Jennifer A Smith, Stasa Stankovic, Kári Stefánsson, Doris Stöckl, Konstantin Strauch, Morris A Swertz, Alexander Teumer, Gudmar Thorleifsson, Unnur Thorsteinsdottir, A Roy Thurik, Nicholas J Timpson, Constance Turman, André G Uitterlinden, Melanie Waldenberger, Nicholas J Wareham, David R Weir, Gonneke Willemsen, Jing Hau Zhao, Wei Zhao, Yajie Zhao, Harold Snieder, Marcel den Hoed, Ken K Ong, Melinda C Mills, John R B Perry Show less
Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European a Show more
Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success. Show less
📄 PDF DOI: 10.1038/s41562-023-01528-6
FADS1
J V van Vliet-Ostaptchouk, M den Hoed, J Luan +13 more · 2013 · Diabetologia · Springer · added 2026-04-24
Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also in Show more
Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies. We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR. We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (RBJ [also known as DNAJC27], QPTCL: effect sizes -0.068 and -0.107 SD, respectively), HDL-cholesterol (SLC39A8: -0.065 SD, MTCH2: -0.039 SD), and diastolic BP (SLC39A8: -0.069 SD), and higher and lower levels of LDL- and total cholesterol (QPTCL: 0.041 and 0.042 SDs, respectively, FLJ35779 [also known as POC5]: -0.042 and -0.041 SDs, respectively) (all p < 2.4 × 10(-4)), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (GRB14: 0.069 SD) and lower fasting glucose levels (CPEB4: -0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (-0.005 SD), diastolic BP (-0.006 SD) and 2 h glucose (-0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (-0.015 SD) and higher triacylglycerol levels (0.014 SD) (all p < 2.9 × 10(-3)), independent of BMI and/or WHR. These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities. Show less
no PDF DOI: 10.1007/s00125-013-2985-y
POC5
Tuomas O Kilpeläinen, Marcel den Hoed, Ken K Ong +9 more · 2011 · The American journal of clinical nutrition · added 2026-04-24
High birth weight is associated with adult body mass index (BMI). We hypothesized that birth weight and BMI may partly share a common genetic background. The objective was to examine the associations Show more
High birth weight is associated with adult body mass index (BMI). We hypothesized that birth weight and BMI may partly share a common genetic background. The objective was to examine the associations of 12 established BMI variants in or near the NEGR1, SEC16B, TMEM18, ETV5, GNPDA2, BDNF, MTCH2, BCDIN3D, SH2B1, FTO, MC4R, and KCTD15 genes and their additive score with birth weight. A meta-analysis was conducted with the use of 1) the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk, Hertfordshire, Fenland, and European Youth Heart Study cohorts (n(max) = 14,060); 2) data extracted from the Early Growth Genetics Consortium meta-analysis of 6 genome-wide association studies for birth weight (n(max) = 10,623); and 3) all published data (n(max) = 14,837). Only the MTCH2 and FTO loci showed a nominally significant association with birth weight. The BMI-increasing allele of the MTCH2 variant (rs10838738) was associated with a lower birth weight (β ± SE: -13 ± 5 g/allele; P = 0.012; n = 23,680), and the BMI-increasing allele of the FTO variant (rs1121980) was associated with a higher birth weight (β ± SE: 11 ± 4 g/allele; P = 0.013; n = 28,219). These results were not significant after correction for multiple testing. Obesity-susceptibility loci have a small or no effect on weight at birth. Some evidence of an association was found for the MTCH2 and FTO loci, ie, lower and higher birth weight, respectively. These findings may provide new insights into the underlying mechanisms by which these loci confer an increased risk of obesity. Show less
no PDF DOI: 10.3945/ajcn.110.000828
SEC16B
Marcel den Hoed, Ulf Ekelund, Søren Brage +6 more · 2010 · Diabetes · added 2026-04-24
Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci Show more
Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents. Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (N(total) = 13,071 children and adolescents). In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033-0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028-0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference). Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar. Show less
no PDF DOI: 10.2337/db10-0370
SEC16B