Publications
1182 results found
Abderrahmani A, Ezanno H, Jacovetti C, et al., 2017, Dual Leucine zipper Kinase (DLK) activity is required for beta cell plasticity during gestation, obesity and postnatal development, 53rd Annual Meeting of the European-Association-for-the-Study-of-Diabetes (EASD), Publisher: SPRINGER, Pages: S84-S85, ISSN: 0012-186X
Graff M, Scott RA, Justice AE, et al., 2017, Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults., PLoS Genetics, Vol: 13, ISSN: 1553-7390
[This corrects the article DOI: 10.1371/journal.pgen.1006528.].
Griscelli F, Feraud O, Ernault T, et al., 2017, Resource: Stem Cell Line Generation of an induced pluripotent stem cell (iPSC) line from a patient with maturity-onset diabetes of the young type 13 (MODY13) with a the potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) mutation, STEM CELL RESEARCH, Vol: 23, Pages: 178-181, ISSN: 1873-5061
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- Citations: 9
Verbanck M, Canouil M, Leloire A, et al., 2017, Low-dose exposure to bisphenols A, F and S of human primary adipocyte impacts coding and non-coding RNA profiles, PLOS ONE, Vol: 12, ISSN: 1932-6203
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- Citations: 52
Peddinti G, Cobb J, Yengo L, et al., 2017, Early metabolic markers identify potential targets for the prevention of type 2 diabetes, Diabetologia, Vol: 60, Pages: 1740-1750, ISSN: 0012-186X
AIMS/HYPOTHESIS: The aims of this study were to evaluate systematically the predictive power of comprehensive metabolomics profiles in predicting the future risk of type 2 diabetes, and to identify a panel of the most predictive metabolic markers. METHODS: We applied an unbiased systems medicine approach to mine metabolite combinations that provide added value in predicting the future incidence of type 2 diabetes beyond known risk factors. We performed mass spectrometry-based targeted, as well as global untargeted, metabolomics, measuring a total of 568 metabolites, in a Finnish cohort of 543 non-diabetic individuals from the Botnia Prospective Study, which included 146 individuals who progressed to type 2 diabetes by the end of a 10 year follow-up period. Multivariate logistic regression was used to assess statistical associations, and regularised least-squares modelling was used to perform machine learning-based risk classification and marker selection. The predictive performance of the machine learning models and marker panels was evaluated using repeated nested cross-validation, and replicated in an independent French cohort of 1044 individuals including 231 participants who progressed to type 2 diabetes during a 9 year follow-up period in the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) study. RESULTS: Nine metabolites were negatively associated (potentially protective) and 25 were positively associated with progression to type 2 diabetes. Machine learning models based on the entire metabolome predicted progression to type 2 diabetes (area under the receiver operating characteristic curve, AUC = 0.77) significantly better than the reference model based on clinical risk factors alone (AUC = 0.68; DeLong's p = 0.0009). The panel of metabolic markers selected by the machine learning-based feature selection also significantly improved the predictive performance over the reference model (AUC&nb
Gromada X, Rabhi N, Carney C, et al., 2017, E2F1 Controls Pancreatic Beta-Cell Plasticity and Function through GLP-1 Signaling, 77th Scientific Sessions of the American-Diabetes-Association, Publisher: AMER DIABETES ASSOC, Pages: A504-A504, ISSN: 0012-1797
Abderrahmani A, Yengo L, Canouil M, et al., 2017, Epigenetics Links Hyperinsulinemia with Liver Overproduction of Fibrosis Marker PDGFA and to Hepatic Insulin Resistance, 77th Scientific Sessions of the American-Diabetes-Association, Publisher: AMER DIABETES ASSOC, Pages: A85-A85, ISSN: 0012-1797
Scott RA, Scott LJ, Mägi R, et al., 2017, An expanded genome-wide association study of Type 2 diabetes in Europeans, Diabetes, Vol: 66, Pages: 2888-2902, ISSN: 0012-1797
To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promising association signals were followed-up in additional data sets (of 14,545 or 7,397 T2D cases and 38,994 or 71,604 controls). We identified 13 novel T2D-associated loci (p<5×10(-8)), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common SNVs. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
Rivera-Millot A, Lesne E, Solans L, et al., 2017, Characterization of a Bvg-regulated fatty acid methyl-transferase in Bordetella pertussis, PLOS ONE, Vol: 12, ISSN: 1932-6203
Juge P-A, Borie R, Kannengiesser C, et al., 2017, Shared genetic predisposition in rheumatoid arthritis-interstitial lung disease and familial pulmonary fibrosis, EUROPEAN RESPIRATORY JOURNAL, Vol: 49, ISSN: 0903-1936
Visvikis-Siest S, Aldasoro Arguinano A-A, Stathopoulou M, et al., 2017, 8th Santorini Conference: Systems medicine and personalized health and therapy, Santorini, Greece, 3-5 October 2016., Drug Metab Pers Ther, Vol: 32, Pages: 119-127
Graff M, Scott RA, Justice AE, et al., 2017, Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults, PLOS GENETICS, Vol: 13, ISSN: 1553-7404
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Justice AE, Winkler TW, Feitosa MF, et al., 2017, Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits, NATURE COMMUNICATIONS, Vol: 8, ISSN: 2041-1723
Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
Ndiaye FK, Ortalli A, Canouil M, et al., 2017, Expression and functional assessment of candidate type 2 diabetes susceptibility genes identify four new genes contributing to human insulin secretion, MOLECULAR METABOLISM, Vol: 6, Pages: 459-470, ISSN: 2212-8778
Objectives:Genome-wide association studies (GWAS) have identified >100 loci independently contributing to type 2 diabetes (T2D) risk. However, translational implications for precision medicine and for the development of novel treatments have been disappointing, due to poor knowledge of how these loci impact T2D pathophysiology. Here, we aimed to measure the expression of genes located nearby T2D associated signals and to assess their effect on insulin secretion from pancreatic beta cells.Methods:The expression of 104 candidate T2D susceptibility genes was measured in a human multi-tissue panel, through PCR-free expression assay. The effects of the knockdown of beta-cell enriched genes were next investigated on insulin secretion from the human EndoC-βH1 beta-cell line. Finally, we performed RNA-sequencing (RNA-seq) so as to assess the pathways affected by the knockdown of the new genes impacting insulin secretion from EndoC-βH1, and we analyzed the expression of the new genes in mouse models with altered pancreatic beta-cell function.Results:We found that the candidate T2D susceptibility genes' expression is significantly enriched in pancreatic beta cells obtained by laser capture microdissection or sorted by flow cytometry and in EndoC-βH1 cells, but not in insulin sensitive tissues. Furthermore, the knockdown of seven T2D-susceptibility genes (CDKN2A, GCK, HNF4A, KCNK16, SLC30A8, TBC1D4, and TCF19) with already known expression and/or function in beta cells changed insulin secretion, supporting our functional approach. We showed first evidence for a role in insulin secretion of four candidate T2D-susceptibility genes (PRC1, SRR, ZFAND3, and ZFAND6) with no previous knowledge of presence and function in beta cells. RNA-seq in EndoC-βH1 cells with decreased expression of PRC1, SRR, ZFAND6, or ZFAND3 identified specific gene networks related to T2D pathophysiology. Finally, a positive correlation between the expression of Ins2 and the expression
Saeed S, Bonnefond A, Manzoor J, et al., 2017, Genetic Variants in LEP, LEPR, and MC4R Explain 30% of Severe Obesity in Children from a Consanguineous Population (vol 23, pg 1687, 2015), OBESITY, Vol: 25, Pages: 807-807, ISSN: 1930-7381
Lizzete Antunez-Ortiz D, Flores-Alfaro E, Isabel Burguete-Garcia A, et al., 2017, Copy number variations in candidate genes and intergenic regions affect body mass index and abdominal obesity in Mexican children, BioMed Research International, Vol: 2017, ISSN: 2314-6133
Introduction. Increase in body weight is a gradual process that usually begins in childhood and in adolescence as a result of multiple interactions among environmental and genetic factors. This study aimed to analyze the relationship between copy number variants (CNVs) in five genes and four intergenic regions with obesity in Mexican children. Methods. We studied 1423 children aged 6–12 years. Anthropometric measurements and blood levels of biochemical parameters were obtained. Identification of CNVs was performed by real-time PCR. The effect of CNVs on obesity or body composition was assessed using regression models adjusted for age, gender, and family history of obesity. Results. Gains in copy numbers of LEPR and NEGR1 were associated with decreased body mass index (BMI), waist circumference (WC), and risk of abdominal obesity, whereas gain in ARHGEF4 and CPXCR1 and the intergenic regions 12q15c, 15q21.1a, and 22q11.21d and losses in INS were associated with increased BMI and WC. Conclusion. Our results indicate a possible contribution of CNVs in LEPR, NEGR1, ARHGEF4, and CPXCR1 and the intergenic regions 12q15c, 15q21.1a, and 22q11.21d to the development of obesity, particularly abdominal obesity in Mexican children.
Manning A, Highland HM, Gasser J, et al., 2017, A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk., Diabetes, Vol: 66, Pages: 2019-2032, ISSN: 0012-1797
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting insulin, a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in fasting plasma insulin (FI) levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-hour insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio=1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.
Vaxillaire M, Froguel P, 2017, Maturity-onset diabetes of the young: From genetics to translational biology and personalized medicine, Diabetes Associated with Single Gene Defects and Chromosomal Abnormalities, Pages: 26-48, ISBN: 9783318060249
Monogenic diabetes is defined as diabetes resulting from a rare causal deleterious mutation of a single gene that usually impairs pancreatic ß-cell function. There is a large spectrum of clinical presentations of monogenic diabetes, depending on the affected gene and the nature of the mutation. Maturity-onset diabetes of the young (MODY) is the most frequent, representing 1-2% of all diabetes cases. MODY is dominantly inherited with early-onset nonautoimmune diabetes. At least 14 MODY genes have been identified so far, including key genes involved in developmental and/or functional processes of the pancreatic β-cell physiology. These discoveries remarkably modified patients' care, improving their quality of life and long-term evolution, and offer proof-of-concepts of successful genomic diabetes medicine. Further, recent advances in genome editing and pluripotent stem-cell reprogramming technologies are providing new opportunities and challenges for in vitro human cell-based diabetes modelling and for novel drugs and cell-based diabetes therapy discovery. This review chapter focuses on the lessons learned from MODY gene identification to clinical translational research and implementation of personalized genomic medicine, as well as on future directions to further elucidate and better understand the pathophysiological mechanisms underlying early-onset monogenic diabetes.
Bonnefond A, Froguel P, 2017, The case for too little melatonin signalling in increased diabetes risk, DIABETOLOGIA, Vol: 60, Pages: 823-825, ISSN: 0012-186X
Bonnefond A, Yengo L, Dechaume A, et al., 2017, Relationship between salivary/pancreatic amylase and body mass index: a systems biology approach, BMC MEDICINE, Vol: 15, ISSN: 1741-7015
Background:Salivary (AMY1) and pancreatic (AMY2) amylases hydrolyze starch. Copy number of AMY1A (encoding AMY1) was reported to be higher in populations with a high-starch diet and reduced in obese people. These results based on quantitative PCR have been challenged recently. We aimed to re-assess the relationship between amylase and adiposity using a systems biology approach.Methods:We assessed the association between plasma enzymatic activity of AMY1 or AMY2, and several metabolic traits in almost 4000 French individuals from D.E.S.I.R. longitudinal study. The effect of the number of copies of AMY1A (encoding AMY1) or AMY2A (encoding AMY2) measured through droplet digital PCR was then analyzed on the same parameters in the same study. A Mendelian randomization analysis was also performed. We subsequently assessed the association between AMY1A copy number and obesity risk in two case-control studies (5000 samples in total). Finally, we assessed the association between body mass index (BMI)-related plasma metabolites and AMY1 or AMY2 activity.Results:We evidenced strong associations between AMY1 or AMY2 activity and lower BMI. However, we found a modest contribution of AMY1A copy number to lower BMI. Mendelian randomization identified a causal negative effect of BMI on AMY1 and AMY2 activities. Yet, we also found a significant negative contribution of AMY1 activity at baseline to the change in BMI during the 9-year follow-up, and a significant contribution of AMY1A copy number to lower obesity risk in children, suggesting a bidirectional relationship between AMY1 activity and adiposity. Metabonomics identified a BMI-independent association between AMY1 activity and lactate, a product of complex carbohydrate fermentation.Conclusions:These findings provide new insights into the involvement of amylase in adiposity and starch metabolism.
Hinney A, Kesselmeier M, Jall S, et al., 2017, Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index., Mol Psychiatry, Vol: 22, Pages: 192-201
The maintenance of normal body weight is disrupted in patients with anorexia nervosa (AN) for prolonged periods of time. Prior to the onset of AN, premorbid body mass index (BMI) spans the entire range from underweight to obese. After recovery, patients have reduced rates of overweight and obesity. As such, loci involved in body weight regulation may also be relevant for AN and vice versa. Our primary analysis comprised a cross-trait analysis of the 1000 single-nucleotide polymorphisms (SNPs) with the lowest P-values in a genome-wide association meta-analysis (GWAMA) of AN (GCAN) for evidence of association in the largest published GWAMA for BMI (GIANT). Subsequently we performed sex-stratified analyses for these 1000 SNPs. Functional ex vivo studies on four genes ensued. Lastly, a look-up of GWAMA-derived BMI-related loci was performed in the AN GWAMA. We detected significant associations (P-values <5 × 10(-5), Bonferroni-corrected P<0.05) for nine SNP alleles at three independent loci. Interestingly, all AN susceptibility alleles were consistently associated with increased BMI. None of the genes (chr. 10: CTBP2, chr. 19: CCNE1, chr. 2: CARF and NBEAL1; the latter is a region with high linkage disequilibrium) nearest to these SNPs has previously been associated with AN or obesity. Sex-stratified analyses revealed that the strongest BMI signal originated predominantly from females (chr. 10 rs1561589; Poverall: 2.47 × 10(-06)/Pfemales: 3.45 × 10(-07)/Pmales: 0.043). Functional ex vivo studies in mice revealed reduced hypothalamic expression of Ctbp2 and Nbeal1 after fasting. Hypothalamic expression of Ctbp2 was increased in diet-induced obese (DIO) mice as compared with age-matched lean controls. We observed no evidence for associations for the look-up of BMI-related loci in the AN GWAMA. A cross-trait analysis of AN and BMI loci revealed variants at three chromosomal loci with potential joint impact. The chromosome 10 locus is particularly pr
Carrat GR, Hu M, Nguyen-Tu MS, et al., 2017, Decreased STARD10 expression is associated with defective insulin secretion in humans and mice, American Journal of Human Genetics, Vol: 100, Pages: 238-256, ISSN: 1537-6605
Genetic variants near ARAP1 (CENTD2) and STARD10 influence type 2 diabetes (T2D) risk. The risk alleles impair glucose-induced insulin secretion and, paradoxically but characteristically, are associated with decreased proinsulin:insulin ratios, indicating improved proinsulin conversion. Neither the identity of the causal variants nor the gene(s) through which risk is conferred have been firmly established. Whereas ARAP1 encodes a GTPase activating protein, STARD10 is a member of the steroidogenic acute regulatory protein (StAR)-related lipid transfer protein family. By integrating genetic fine-mapping and epigenomic annotation data and performing promoter-reporter and chromatin conformational capture (3C) studies in β cell lines, we localize the causal variant(s) at this locus to a 5 kb region that overlaps a stretch-enhancer active in islets. This region contains several highly correlated T2D-risk variants, including the rs140130268 indel. Expression QTL analysis of islet transcriptomes from three independent subject groups demonstrated that T2D-risk allele carriers displayed reduced levels of STARD10 mRNA, with no concomitant change in ARAP1 mRNA levels. Correspondingly, β-cell-selective deletion of StarD10 in mice led to impaired glucose-stimulated Ca2+ dynamics and insulin secretion and recapitulated the pattern of improved proinsulin processing observed at the human GWAS signal. Conversely, overexpression of StarD10 in the adult β cell improved glucose tolerance in high fat-fed animals. In contrast, manipulation of Arap1 in β cells had no impact on insulin secretion or proinsulin conversion in mice. This convergence of human and murine data provides compelling evidence that the T2D risk associated with variation at this locus is mediated through reduction in STARD10 expression in the β cell.
Vaxillaire M, Froguel P, 2017, Maturity-Onset Diabetes of the Young: From Genetics to Translational Biology and Personalized Medicine, DIABETES ASSOCIATED WITH SINGLE GENE DEFECTS AND CHROMOSOMAL ABNORMALITIES, Editors: Barbetti, Ghizzoni, Guaraldi, Publisher: KARGER, Pages: 26-48, ISBN: 978-3-318-06024-9
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Schmidt AF, Swerdlow DI, Holmes MV, et al., 2016, PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study, Lancet Diabetes and Endocrinology, Vol: 5, Pages: 97-105, ISSN: 2213-8587
Background: Statin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductionsin both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modesthyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way off sets theirsubstantial benefi ts. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2diabetes and related biomarkers to gauge the likely eff ects of PCSK9 inhibitors on diabetes risk.Methods: In this mendelian randomisation study, we used data from cohort studies, randomised controlled trials,case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol,fasting blood glucose, HbA1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, usinga standardised analysis plan, meta-analyses, and weighted gene-centric scores.Findings: Data were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analysesof four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lowerLDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight(1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50).Based on the collected data, we did not identify associations with HbA1c (0·03%, –0·01 to 0·08), fasting insulin (0·00%,–0·06 to 0·07), and BMI (0·11 kg/m², –0·09 to 0·30).Interpretation: PCSK9 variants associated with lower LDL cholesterol were also associated with circulating higherfasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diab
Schumann G, Liu C, O'Reilly P, et al., 2016, KLB is associated with alcohol drinking, and its gene product β-Klotho is necessary for FGF21 regulation of alcohol preference, Proceedings of the National Academy of Sciences of the United States of America, Vol: 113, Pages: 14372-14377, ISSN: 1091-6490
Alcohol is a widely consumed drug in western societies that can lead to addiction. A small shift in consumption can have dramatic consequences on public health. We performed the largest genome-wide association metaanalysis and replication study to date (>105,000 individuals) and identified a genetic basis for alcohol consumption during nonaddictive drinking. We found that a locus in the gene encoding β-Klotho is associated with alcohol consumption. β-Klotho is an essential receptor component for the endocrine FGFs, FGF19 and FGF21. Using mouse models and pharmacologic administration of FGF21, we show that β-Klotho in the brain controls alcohol drinking. These findings reveal a mechanism regulating alcohol consumption in humans that may be pharmacologically tractable for reducing alcohol intake.
Field Y, Boyle EA, Telis N, et al., 2016, Detection of human adaptation during the past 2000 years, SCIENCE, Vol: 354, Pages: 760-764, ISSN: 0036-8075
Juge PA, Borie R, Kannengiesser C, et al., 2016, Shared genetic factor between rheumatoid arthritis-associated interstitial lung disease and idiopathic pulmonary fibrosis, Revue du Rhumatisme (Edition Francaise), Vol: 83, Pages: A91-A92, ISSN: 1169-8330
Canouil M, Froguel P, Rocheleau G, 2016, Single Nucleotide Polymorphisms (SNPs) Associated with Fasting Blood Glucose Trajectory and Type 2 Diabetes Incidence: A Joint Modelling Approach, Annual Meeting of the International-Genetic-Epidemiology-Society, Publisher: WILEY-BLACKWELL, Pages: 626-626, ISSN: 0741-0395
Barban N, Jansen R, de Vlaming R, et al., 2016, Genome-wide analysis identifies 12 loci influencing human reproductive behavior, Nature Genetics, Vol: 48, Pages: 1462-1472, ISSN: 1061-4036
The genetic architecture of human reproductive behavior—age at first birth (AFB) and number of children ever born (NEB)—has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.
Baumeier C, Saussenthaler S, Kammel A, et al., 2016, Hepatic DPP4 DNA Methylation Associates With Fatty Liver, DIABETES, Vol: 66, Pages: 25-35, ISSN: 0012-1797
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