👤 M Lathrop

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Also published as: G Mark Lathrop, Marc Lathrop, Mark Lathrop, Tatiana Siegler Lathrop
articles
Tatiana Siegler Lathrop, Inés Martínez Sanchez, Ioannis S Chronakis +1 more · 2026 · Brain, behavior, & immunity - health · Elsevier · added 2026-04-24
The maternal perinatal environment shapes brain development and long-term neurodevelopmental trajectories. Probiotic supplementation during this period has emerged as a promising strategy to support h Show more
The maternal perinatal environment shapes brain development and long-term neurodevelopmental trajectories. Probiotic supplementation during this period has emerged as a promising strategy to support healthy neurodevelopmental outcomes through modulation of immune and synaptic plasticity pathways. However, the persistence and specificity of molecular effects in the offspring brain, particularly with respect to sex and brain region, remain poorly understood. We conducted two independent mouse experiments using different probiotic strains and exposure windows to evaluate the long-term transcriptional effects of maternal probiotic supplementation. Time-mated C57BL/6JRj dams received a multi-species probiotic (Ecologic® Panda) from gestational day (GD) 6 until birth, whereas BALB/cJRj dams received Multi-species supplementation induced broad and persistent transcriptional changes in hippocampus and hypothalamus, with generally larger effects in males. Altered transcripts included markers of synaptic plasticity ( These findings highlight that short, targeted maternal probiotic supplementation during the perinatal period is associated with persistent molecular signatures in the adult offspring brain across genetic backgrounds, converging on neuroimmune-related pathways. Show less
📄 PDF DOI: 10.1016/j.bbih.2026.101191
BDNF
Olav M Andersen, Matthijs W J de Waal, Giulia Monti +103 more · 2025 · Molecular neurodegeneration · BioMed Central · added 2026-04-24
Olav M Andersen, Matthijs W J de Waal, Giulia Monti, Niccolo Tesi, Anne Mette G Jensen, Christa de Geus, Rosalina van Spaendonk, Maartje Vogel, Shahzad Ahmad, Najaf Amin, Philippe Amouyel, Gary W Beecham, Céline Bellenguez, Claudine Berr, Joshua C Bis, Anne Boland, Paola Bossù, Femke Bouwman, Jose Bras, Camille Charbonnier, Jordi Clarimon, Carlos Cruchaga, Antonio Daniele, Jean-François Dartigues, Stéphanie Debette, Jean-François Deleuze, Nicola Denning, Anita L Destefano, Oriol Dols-Icardo, Cornelia M Van Duijn, Lindsay A Farrer, Maria Victoria Fernández, Wiesje M van der Flier, Nick C Fox, Daniela Galimberti, Emmanuelle Genin, Johan J P Gille, Benjamin Grenier-Boley, Detelina Grozeva, Yann Le Guen, Rita Guerreiro, Jonathan L Haines, Clive Holmes, Holger Hummerich, M Arfan Ikram, M Kamran Ikram, Amit Kawalia, Robert Kraaij, Jean-Charles Lambert, Marc Lathrop, Afina W Lemstra, Alberto Lleó, Richard M Myers, Marcel M A M Mannens, Rachel Marshall, Eden R Martin, Carlo Masullo, Richard Mayeux, Simon Mead, Patrizia Mecocci, Alun Meggy, Merel O Mol, Benedetta Nacmias, Adam C Naj, Valerio Napolioni, J Nicholas Cochran, Gaël Nicolas, Florence Pasquier, Pau Pastor, Margaret A Pericak-Vance, Yolande A L Pijnenburg, Fabrizio Piras, Olivier Quenez, Alfredo Ramirez, Rachel Raybould, Richard Redon, Marcel J T Reinders, Anne-Claire Richard, Steffi G Riedel-Heller, Fernando Rivadeneira, Jeroen G J van Rooij, Stéphane Rousseau, Natalie S Ryan, Pascual Sanchez-Juan, Gerard D Schellenberg, Philip Scheltens, Jonathan M Schott, Sudha Seshadri, Daoud Sie, Rebecca Sims, Erik A Sistermans, Sandro Sorbi, John C Van Swieten, Betty Tijms, André G Uitterlinden, Pieter Jelle Visser, Michael Wagner, David Wallon, Li-San Wang, Julie Williams, Jennifer S Yokoyama, Aline Zarea, Sven J van der Lee, Johan G Olsen, Marc Hulsman, Henne Holstege Show less
Protein truncating variants (PTVs) in To identify high-priority missense variants (HPVs), we applied ‘domain mapping of disease mutations’ for the 637 unique coding In this sample, PTVs and HPVs assoc Show more
Protein truncating variants (PTVs) in To identify high-priority missense variants (HPVs), we applied ‘domain mapping of disease mutations’ for the 637 unique coding In this sample, PTVs and HPVs associated with respectively a 35- and 10-fold increased risk of early onset AD and 17- and 6-fold increased risk of overall AD. The median age at onset (AAO) of PTV- and HPV-carriers was 62 and 64 years, and Our results justify a debate on whether HPV carriers should be considered for clinical counseling. The online version contains supplementary material available at 10.1186/s13024-025-00907-z. Show less
📄 PDF DOI: 10.1186/s13024-025-00907-z
APOE
Hao Yu Chen, Benjamin J Cairns, Aeron M Small +43 more · 2020 · JAMA cardiology · added 2026-04-24
Aortic stenosis (AS) has no approved medical treatment. Identifying etiological pathways for AS could identify pharmacological targets. To identify novel genetic loci and pathways associated with AS. Show more
Aortic stenosis (AS) has no approved medical treatment. Identifying etiological pathways for AS could identify pharmacological targets. To identify novel genetic loci and pathways associated with AS. This genome-wide association study used a case-control design to evaluate 44 703 participants (3469 cases of AS) of self-reported European ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort (from January 1, 1996, to December 31, 2015). Replication was performed in 7 other cohorts totaling 256 926 participants (5926 cases of AS), with additional analyses performed in 6942 participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Follow-up biomarker analyses with aortic valve calcium (AVC) were also performed. Data were analyzed from May 1, 2017, to December 5, 2019. Genetic variants (615 643 variants) and polyunsaturated fatty acids (ω-6 and ω-3) measured in blood samples. Aortic stenosis and aortic valve replacement defined by electronic health records, surgical records, or echocardiography and the presence of AVC measured by computed tomography. The mean (SD) age of the 44 703 GERA participants was 69.7 (8.4) years, and 22 019 (49.3%) were men. The rs174547 variant at the FADS1/2 locus was associated with AS (odds ratio [OR] per C allele, 0.88; 95% CI, 0.83-0.93; P = 3.0 × 10-6), with genome-wide significance after meta-analysis with 7 replication cohorts totaling 312 118 individuals (9395 cases of AS) (OR, 0.91; 95% CI, 0.88-0.94; P = 2.5 × 10-8). A consistent association with AVC was also observed (OR, 0.91; 95% CI, 0.83-0.99; P = .03). A higher ratio of arachidonic acid to linoleic acid was associated with AVC (OR per SD of the natural logarithm, 1.19; 95% CI, 1.09-1.30; P = 6.6 × 10-5). In mendelian randomization, increased FADS1 liver expression and arachidonic acid were associated with AS (OR per unit of normalized expression, 1.31 [95% CI, 1.17-1.48; P = 7.4 × 10-6]; OR per 5-percentage point increase in arachidonic acid for AVC, 1.23 [95% CI, 1.01-1.49; P = .04]; OR per 5-percentage point increase in arachidonic acid for AS, 1.08 [95% CI, 1.04-1.13; P = 4.1 × 10-4]). Variation at the FADS1/2 locus was associated with AS and AVC. Findings from biomarker measurements and mendelian randomization appear to link ω-6 fatty acid biosynthesis to AS, which may represent a therapeutic target. Show less
📄 PDF DOI: 10.1001/jamacardio.2020.0246
FADS1
Noémie Péan, Aurelie Le Lay, Francois Brial +11 more · 2020 · Diabetologia · Springer · added 2026-04-24
Drug and surgical-based therapies in type 2 diabetes are associated with altered gut microbiota architecture. Here we investigated the role of the gut microbiome in improved glucose homeostasis follow Show more
Drug and surgical-based therapies in type 2 diabetes are associated with altered gut microbiota architecture. Here we investigated the role of the gut microbiome in improved glucose homeostasis following bariatric surgery. We carried out gut microbiome analyses in gastrectomised (by vertical sleeve gastrectomy [VSG]) rats of the Goto-Kakizaki (GK) non-obese model of spontaneously occurring type 2 diabetes, followed by physiological studies in the GK rat. VSG in the GK rat led to permanent improvement of glucose tolerance associated with minor changes in the gut microbiome, mostly characterised by significant enrichment of caecal Prevotella copri. Gut microbiota enrichment with P. copri in GK rats through permissive antibiotic treatment, inoculation of gut microbiota isolated from gastrectomised GK rats, and direct inoculation of P. copri, resulted in significant improvement of glucose tolerance, independent of changes in body weight. Plasma bile acids were increased in GK rats following inoculation with P. copri and P. copri-enriched microbiota from VSG-treated rats; the inoculated GK rats then showed increased liver glycogen and upregulated expression of Fxr (also known as Nr1h4), Srebf1c, Chrebp (also known as Mlxipl) and Il10 and downregulated expression of Cyp7a1. Our data underline the impact of intestinal P. copri on improved glucose homeostasis through enhanced bile acid metabolism and farnesoid X receptor (FXR) signalling, which may represent a promising opportunity for novel type 2 diabetes therapeutics. Show less
📄 PDF DOI: 10.1007/s00125-020-05122-7
MLXIPL
K Le Guennec, O Quenez, G Nicolas +40 more · 2017 · Molecular psychiatry · Nature · added 2026-04-24
To assess the role of rare copy number variations in Alzheimer's disease (AD), we conducted a case-control study using whole-exome sequencing data from 522 early-onset cases and 584 controls. The most Show more
To assess the role of rare copy number variations in Alzheimer's disease (AD), we conducted a case-control study using whole-exome sequencing data from 522 early-onset cases and 584 controls. The most recurrent rearrangement was a 17q21.31 microduplication, overlapping the CRHR1, MAPT, STH and KANSL1 genes that was found in four cases, including one de novo rearrangement, and was absent in controls. The increased MAPT gene dosage led to a 1.6-1.9-fold expression of the MAPT messenger RNA. Clinical signs, neuroimaging and cerebrospinal fluid biomarker profiles were consistent with an AD diagnosis in MAPT duplication carriers. However, amyloid positon emission tomography (PET) imaging, performed in three patients, was negative. Analysis of an additional case with neuropathological examination confirmed that the MAPT duplication causes a complex tauopathy, including prominent neurofibrillary tangle pathology in the medial temporal lobe without amyloid-β deposits. 17q21.31 duplication is the genetic basis of a novel entity marked by prominent tauopathy, leading to early-onset dementia with an AD clinical phenotype. This entity could account for a proportion of probable AD cases with negative amyloid PET imaging recently identified in large clinical series. Show less
no PDF DOI: 10.1038/mp.2016.226
KANSL1
G Jun, C A Ibrahim-Verbaas, M Vronskaya +115 more · 2016 · Molecular psychiatry · Nature · added 2026-04-24
APOE ɛ4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics o Show more
APOE ɛ4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ɛ4+ (10 352 cases and 9207 controls) and APOE ɛ4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ɛ4 status. Suggestive associations (P<1 × 10(-4)) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ɛ4+: 1250 cases and 536 controls; APOE ɛ4-: 718 cases and 1699 controls). Among APOE ɛ4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10(-9)). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ɛ4+ subjects (CR1 and CLU) or APOE ɛ4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10(-7)) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P ⩽ 1.3 × 10(-8)), frontal cortex (P ⩽ 1.3 × 10(-9)) and temporal cortex (P⩽1.2 × 10(-11)). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10(-6)) and temporal cortex (P=2.6 × 10(-6)). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ɛ4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted. Show less
📄 PDF DOI: 10.1038/mp.2015.23
KANSL1
Elin Grundberg, Eshwar Meduri, Johanna K Sandling +20 more · 2013 · American journal of human genetics · Elsevier · added 2026-04-24
Epigenetic modifications such as DNA methylation play a key role in gene regulation and disease susceptibility. However, little is known about the genome-wide frequency, localization, and function of Show more
Epigenetic modifications such as DNA methylation play a key role in gene regulation and disease susceptibility. However, little is known about the genome-wide frequency, localization, and function of methylation variation and how it is regulated by genetic and environmental factors. We utilized the Multiple Tissue Human Expression Resource (MuTHER) and generated Illumina 450K adipose methylome data from 648 twins. We found that individual CpGs had low variance and that variability was suppressed in promoters. We noted that DNA methylation variation was highly heritable (h(2)median = 0.34) and that shared environmental effects correlated with metabolic phenotype-associated CpGs. Analysis of methylation quantitative-trait loci (metQTL) revealed that 28% of CpGs were associated with nearby SNPs, and when overlapping them with adipose expression quantitative-trait loci (eQTL) from the same individuals, we found that 6% of the loci played a role in regulating both gene expression and DNA methylation. These associations were bidirectional, but there were pronounced negative associations for promoter CpGs. Integration of metQTL with adipose reference epigenomes and disease associations revealed significant enrichment of metQTL overlapping metabolic-trait or disease loci in enhancers (the strongest effects were for high-density lipoprotein cholesterol and body mass index [BMI]). We followed up with the BMI SNP rs713586, a cg01884057 metQTL that overlaps an enhancer upstream of ADCY3, and used bisulphite sequencing to refine this region. Our results showed widespread population invariability yet sequence dependence on adipose DNA methylation but that incorporating maps of regulatory elements aid in linking CpG variation to gene regulation and disease risk in a tissue-dependent manner. Show less
no PDF DOI: 10.1016/j.ajhg.2013.10.004
ADCY3
John C Chambers, Weihua Zhang, Joban Sehmi +140 more · 2011 · Nature genetics · Nature · added 2026-04-24
John C Chambers, Weihua Zhang, Joban Sehmi, Xinzhong Li, Mark N Wass, Pim Van der Harst, Hilma Holm, Serena Sanna, Maryam Kavousi, Sebastian E Baumeister, Lachlan J Coin, Guohong Deng, Christian Gieger, Nancy L Heard-Costa, Jouke-Jan Hottenga, Brigitte Kühnel, Vinod Kumar, Vasiliki Lagou, Liming Liang, Jian'an Luan, Pedro Marques Vidal, Irene Mateo Leach, Paul F O'Reilly, John F Peden, Nilufer Rahmioglu, Pasi Soininen, Elizabeth K Speliotes, Xin Yuan, Gudmar Thorleifsson, Behrooz Z Alizadeh, Larry D Atwood, Ingrid B Borecki, Morris J Brown, Pimphen Charoen, Francesco Cucca, Debashish Das, Eco J C de Geus, Anna L Dixon, Angela Döring, Georg Ehret, Gudmundur I Eyjolfsson, Martin Farrall, Nita G Forouhi, Nele Friedrich, Wolfram Goessling, Daniel F Gudbjartsson, Tamara B Harris, Anna-Liisa Hartikainen, Simon Heath, Gideon M Hirschfield, Albert Hofman, Georg Homuth, Elina Hyppönen, Harry L A Janssen, Toby Johnson, Antti J Kangas, Ido P Kema, Jens P Kühn, Sandra Lai, Mark Lathrop, Markus M Lerch, Yun Li, T Jake Liang, Jing-Ping Lin, Ruth J F Loos, Nicholas G Martin, Miriam F Moffatt, Grant W Montgomery, Patricia B Munroe, Kiran Musunuru, Yusuke Nakamura, Christopher J O'Donnell, Isleifur Olafsson, Brenda W Penninx, Anneli Pouta, Bram P Prins, Inga Prokopenko, Ralf Puls, Aimo Ruokonen, Markku J Savolainen, David Schlessinger, Jeoffrey N L Schouten, Udo Seedorf, Srijita Sen-Chowdhry, Katherine A Siminovitch, Johannes H Smit, Timothy D Spector, Wenting Tan, Tanya M Teslovich, Taru Tukiainen, Andre G Uitterlinden, Melanie M Van der Klauw, Ramachandran S Vasan, Chris Wallace, Henri Wallaschofski, H-Erich Wichmann, Gonneke Willemsen, Peter Würtz, Chun Xu, Laura M Yerges-Armstrong, Alcohol Genome-wide Association (AlcGen) Consortium, Diabetes Genetics Replication and Meta-analyses (DIAGRAM+) Study, Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Global Lipids Genetics Consortium, Genetics of Liver Disease (GOLD) Consortium, International Consortium for Blood Pressure (ICBP-GWAS), Meta-analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), Goncalo R Abecasis, Kourosh R Ahmadi, Dorret I Boomsma, Mark Caulfield, William O Cookson, Cornelia M Van Duijn, Philippe Froguel, Koichi Matsuda, Mark I McCarthy, Christa Meisinger, Vincent Mooser, Kirsi H Pietiläinen, Gunter Schumann, Harold Snieder, Michael J E Sternberg, Ronald P Stolk, Howard C Thomas, Unnur Thorsteinsdottir, Manuela Uda, Gérard Waeber, Nicholas J Wareham, Dawn M Waterworth, Hugh Watkins, John B Whitfield, Jacqueline C M Witteman, Bruce H R Wolffenbuttel, Caroline S Fox, Mika Ala-Korpela, Kari Stefansson, Peter Vollenweider, Henry Völzke, Eric E Schadt, James Scott, Marjo-Riitta Järvelin, Paul Elliott, Jaspal S Kooner Show less
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with conc Show more
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function. Show less
📄 PDF DOI: 10.1038/ng.970
FADS1
Lavinia Paternoster, David M Evans, Ellen Aagaard Nohr +22 more · 2011 · PloS one · PLOS · added 2026-04-24
Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ∼1.45% of BMI variation in general population cohorts. We performed Show more
Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ∼1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations. From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ∼212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10(-8); FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations. Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power. Show less
no PDF DOI: 10.1371/journal.pone.0024303
SEC16B
Josée Dupuis, Claudia Langenberg, Inga Prokopenko +305 more · 2010 · Nature genetics · Nature · added 2026-04-24
Josée Dupuis, Claudia Langenberg, Inga Prokopenko, Richa Saxena, Nicole Soranzo, Anne U Jackson, Eleanor Wheeler, Nicole L Glazer, Nabila Bouatia-Naji, Anna L Gloyn, Cecilia M Lindgren, Reedik Mägi, Andrew P Morris, Joshua Randall, Toby Johnson, Paul Elliott, Denis Rybin, Gudmar Thorleifsson, Valgerdur Steinthorsdottir, Peter Henneman, Harald Grallert, Abbas Dehghan, Jouke Jan Hottenga, Christopher S Franklin, Pau Navarro, Kijoung Song, Anuj Goel, John R B Perry, Josephine M Egan, Taina Lajunen, Niels Grarup, Thomas Sparsø, Alex Doney, Benjamin F Voight, Heather M Stringham, Man Li, Stavroula Kanoni, Peter Shrader, Christine Cavalcanti-Proença, Meena Kumari, Lu Qi, Nicholas J Timpson, Christian Gieger, Carina Zabena, Ghislain Rocheleau, Erik Ingelsson, Ping An, Jeffrey O'Connell, Jian'an Luan, Amanda Elliott, Steven A McCarroll, Felicity Payne, Rosa Maria Roccasecca, François Pattou, Praveen Sethupathy, Kristin Ardlie, Yavuz Ariyurek, Beverley Balkau, Philip Barter, John P Beilby, Yoav Ben-Shlomo, Rafn Benediktsson, Amanda J Bennett, Sven Bergmann, Murielle Bochud, Eric Boerwinkle, Amélie Bonnefond, Lori L Bonnycastle, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Suzannah J Bumpstead, Guillaume Charpentier, Yii-der Ida Chen, Peter Chines, Robert Clarke, Lachlan J M Coin, Matthew N Cooper, Marilyn Cornelis, Gabe Crawford, Laura Crisponi, Ian N M Day, Eco J C de Geus, Jerome Delplanque, Christian Dina, Michael R Erdos, Annette C Fedson, Antje Fischer-Rosinsky, Nita G Forouhi, Caroline S Fox, Rune Frants, Maria Grazia Franzosi, Pilar Galan, Mark O Goodarzi, Jürgen Graessler, Christopher J Groves, Scott Grundy, Rhian Gwilliam, Ulf Gyllensten, Samy Hadjadj, Göran Hallmans, Naomi Hammond, Xijing Han, Anna-Liisa Hartikainen, Neelam Hassanali, Caroline Hayward, Simon C Heath, Serge Hercberg, Christian Herder, Andrew A Hicks, David R Hillman, Aroon D Hingorani, Albert Hofman, Jennie Hui, Joe Hung, Bo Isomaa, Paul R V Johnson, Torben Jørgensen, Antti Jula, Marika Kaakinen, Jaakko Kaprio, Y Antero Kesaniemi, Mika Kivimaki, Beatrice Knight, Seppo Koskinen, Peter Kovacs, Kirsten Ohm Kyvik, G Mark Lathrop, Debbie A Lawlor, Olivier Le Bacquer, Cécile Lecoeur, Yun Li, Valeriya Lyssenko, Robert Mahley, Massimo Mangino, Alisa K Manning, María Teresa Martínez-Larrad, Jarred B McAteer, Laura J McCulloch, Ruth McPherson, Christa Meisinger, David Melzer, David Meyre, Braxton D Mitchell, Mario A Morken, Sutapa Mukherjee, Silvia Naitza, Narisu Narisu, Matthew J Neville, Ben A Oostra, Marco Orrù, Ruth Pakyz, Colin N A Palmer, Giuseppe Paolisso, Cristian Pattaro, Daniel Pearson, John F Peden, Nancy L Pedersen, Markus Perola, Andreas F H Pfeiffer, Irene Pichler, Ozren Polasek, Danielle Posthuma, Simon C Potter, Anneli Pouta, Michael A Province, Bruce M Psaty, Wolfgang Rathmann, Nigel W Rayner, Kenneth Rice, Samuli Ripatti, Fernando Rivadeneira, Michael Roden, Olov Rolandsson, Annelli Sandbaek, Manjinder Sandhu, Serena Sanna, Avan Aihie Sayer, Paul Scheet, Laura J Scott, Udo Seedorf, Stephen J Sharp, Beverley Shields, Gunnar Sigurethsson, Eric J G Sijbrands, Angela Silveira, Laila Simpson, Andrew Singleton, Nicholas L Smith, Ulla Sovio, Amy Swift, Holly Syddall, Ann-Christine Syvänen, Toshiko Tanaka, Barbara Thorand, Jean Tichet, Anke Tönjes, Tiinamaija Tuomi, André G Uitterlinden, Ko Willems Van Dijk, Mandy van Hoek, Dhiraj Varma, Sophie Visvikis-Siest, Veronique Vitart, Nicole Vogelzangs, Gérard Waeber, Peter J Wagner, Andrew Walley, G Bragi Walters, Kim L Ward, Hugh Watkins, Michael N Weedon, Sarah H Wild, Gonneke Willemsen, Jaqueline C M Witteman, John W G Yarnell, Eleftheria Zeggini, Diana Zelenika, Björn Zethelius, Guangju Zhai, Jing Hua Zhao, M Carola Zillikens, DIAGRAM Consortium, GIANT Consortium, Global BPgen Consortium, Ingrid B Borecki, Ruth J F Loos, Pierre Meneton, Patrik K E Magnusson, David M Nathan, Gordon H Williams, Andrew T Hattersley, Kaisa Silander, Veikko Salomaa, George Davey Smith, Stefan R Bornstein, Peter Schwarz, Joachim Spranger, Fredrik Karpe, Alan R Shuldiner, Cyrus Cooper, George V Dedoussis, Manuel Serrano-Ríos, Andrew D Morris, Lars Lind, Lyle J Palmer, Frank B Hu, Paul W Franks, Shah Ebrahim, Michael Marmot, W H Linda Kao, James S Pankow, Michael J Sampson, Johanna Kuusisto, Markku Laakso, Torben Hansen, Oluf Pedersen, Peter Paul Pramstaller, H Erich Wichmann, Thomas Illig, Igor Rudan, Alan F Wright, Michael Stumvoll, Harry Campbell, James F Wilson, Anders Hamsten on behalf of Procardis Consortium, MAGIC Investigators, Richard N Bergman, Thomas A Buchanan, Francis S Collins, Karen L Mohlke, Jaakko Tuomilehto, Timo T Valle, David Altshuler, Jerome I Rotter, David S Siscovick, Brenda W J H Penninx, Dorret I Boomsma, Panos Deloukas, Timothy D Spector, Timothy M Frayling, Luigi Ferrucci, Augustine Kong, Unnur Thorsteinsdottir, Kari Stefansson, Cornelia M Van Duijn, Yurii S Aulchenko, Antonio Cao, Angelo Scuteri, David Schlessinger, Manuela Uda, Aimo Ruokonen, Marjo-Riitta Jarvelin, Dawn M Waterworth, Peter Vollenweider, Leena Peltonen, Vincent Mooser, Goncalo R Abecasis, Nicholas J Wareham, Robert Sladek, Philippe Froguel, Richard M Watanabe, James B Meigs, Leif Groop, Michael Boehnke, Mark I McCarthy, Jose C Florez, Inês Barroso Show less
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, Show more
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less
📄 PDF DOI: 10.1038/ng.520
FADS1
Sekar Kathiresan, Cristen J Willer, Gina M Peloso +58 more · 2009 · Nature genetics · Nature · added 2026-04-24
Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these Show more
Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to 20,623 individuals. We identified 30 distinct loci associated with lipoprotein concentrations (each with P < 5 x 10(-8)), including 11 loci that reached genome-wide significance for the first time. The 11 newly defined loci include common variants associated with LDL cholesterol near ABCG8, MAFB, HNF1A and TIMD4; with HDL cholesterol near ANGPTL4, FADS1-FADS2-FADS3, HNF4A, LCAT, PLTP and TTC39B; and with triglycerides near AMAC1L2, FADS1-FADS2-FADS3 and PLTP. The proportion of individuals exceeding clinical cut points for high LDL cholesterol, low HDL cholesterol and high triglycerides varied according to an allelic dosage score (P < 10(-15) for each trend). These results suggest that the cumulative effect of multiple common variants contributes to polygenic dyslipidemia. Show less
📄 PDF DOI: 10.1038/ng.291
FADS1
Cristen J Willer, Serena Sanna, Anne U Jackson +47 more · 2008 · Nature genetics · Nature · added 2026-04-24
To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6 Show more
To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls. Show less
no PDF DOI: 10.1038/ng.76
APOA4