New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

Exploiting the Legacy of the Arbovirus Hunters

In recent years, it has become evident that a generational gap has developed in the community of arbovirus research. This apparent gap is due to the dis-investment of training for the next generation of arbovirologists, which threatens to derail the rich history of virus discovery, field epidemiology, and understanding of the richness of diversity that surrounds us. On the other hand, new technologies have resulted in an explosion of virus discovery that is constantly redefining the virosphere and the evolutionary relationships between viruses. This paradox presents new challenges that may have immediate and disastrous consequences for public health when yet to be discovered arboviruses emerge. In this review we endeavor to bridge this gap by providing a historical context for the work being conducted today and provide continuity between the generations. To this end, we will provide a narrative of the thrill of scientific discovery and excitement and the challenges lying ahead

Genetic characterization, molecular epidemiology, and phylogenetic relationships of insect-specific viruses in the taxon Negevirus

Work at UTMB was supported by NIH grant U54 AI057156, R24 AI120942 (HG, RBT, NV) and by NIH contract HHSN272202000040I/ HHSN200004/D04 (HG, RBT, NV). MAC was supported by Programa de Doctorados Nacionales – Colciencias” (Convocatoria 567) (MAC) PhD fellowship. The field collection in Colombia was supported in part by Colciencias C.T-695-2014 and by Colciencias grant 111549326198. This work was supported in part by CNPq (Brazilian National Council for Research and Development) grant no. 302032/2011-8 (MRTN). We also acknowledge support from the Yale Institute for Biospheric Studies Center for EcoEpidemiology and from the U.S. National Park Service (Collecting Permit #EVER-2013-SCI-0032)Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.Universidad Nacional de Colombia. Facultad de Ciencias,Ciencias. Grupo de Investigación en Sistemática Molecular. Medellín, Medellín, Colombia / Universidad de Antioquia. Programa de Estudio y Control de Enfermedades Tropicales - PECET - SIU-Sede de Investigación Universitaria. Medellín, Colombia.University of Texas Medical Branch. Department of Pathology and Center for Biodefense and Emerging Infectious Diseases. Galveston, TX, United States / University of Texas Medical Branch. Center for Tropical Diseases. Galveston, TX, United States / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Vale S.A. Projeto Ferro Carajás. Canaã dos Carajás, PA, Brazil.Yale University. Department of Ecology and Evolutionary Biology. New Haven, CT, United States.University of Washington. School of Public Health. Seattle, WA, United States.Universidad Nacional de Colombia. Facultad de Ciencias,Ciencias. Grupo de Investigación en Sistemática Molecular. Medellín, Colombia.Universidad Nacional de Colombia. Facultad de Ciencias,Ciencias. Grupo de Investigación en Sistemática Molecular. Medellín, Medellín, Colombia / Universidad de Antioquia. Programa de Estudio y Control de Enfermedades Tropicales - PECET - SIU-Sede de Investigación Universitaria. Medellín, Colombia.Universidad Nacional de Colombia. Facultad de Ciencias,Ciencias. Grupo de Investigación en Sistemática Molecular. Medellín, Medellín, Colombia / Universidad de Antioquia. Programa de Estudio y Control de Enfermedades Tropicales - PECET - SIU-Sede de Investigación Universitaria. Medellín, Colombia.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Vale S.A. Projeto Ferro Carajás. Canaã dos Carajás, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.University of Texas Medical Branch. Department of Biochemistry and Molecular Biology. Galveston, TX, United States.University of Texas Medical Branch. Department of Biochemistry and Molecular Biology. Galveston, TX, United States.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Yale School of Public Health. Department of Epidemiology of Microbial Diseases. New Haven, CT, United States.University of Texas Medical Branch. Department of Pathology and Center for Biodefense and Emerging Infectious Diseases. Galveston, TX, United States / University of Texas Medical Branch. Center for Tropical Diseases. Galveston, TX, United States / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.University of Texas Medical Branch. Department of Pathology and Center for Biodefense and Emerging Infectious Diseases. Galveston, TX, United States / University of Texas Medical Branch. Center for Tropical Diseases. Galveston, TX, United States / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.The recently described taxon Negevirus is comprised of a diverse group of insect-specific viruses isolated from mosquitoes and phlebotomine sandflies. In this study, a comprehensive genetic characterization, molecular, epidemiological and evolutionary analyses were conducted on nearly full-length sequences of 91 new negevirus isolates obtained in Brazil, Colombia, Peru, Panama, USA and Nepal. We demonstrated that these arthropod restricted viruses are clustered in two major phylogenetic groups with origins related to three plant virus genera (Cilevirus, Higrevirus and Blunevirus). Molecular analyses demonstrated that specific host correlations are not present with most negeviruses; instead, high genetic variability, wide host-range, and cross-species transmission were noted. The data presented here also revealed the existence of five novel insect-specific viruses falling into two arthropod-restrictive virus taxa, previously proposed as distinct genera, designated Nelorpivirus and Sandewavirus. Our results provide a better understanding of the molecular epidemiology, evolution, taxonomy and stability of this group of insect-restricted viruses

Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index

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 promising given that the association with obesity was primarily driven by females. In addition, the detected altered hypothalamic expression patterns of Ctbp2 and Nbeal1 as a result of fasting and DIO implicate these genes in weight regulation

Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index

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 promising given that the association with obesity was primarily driven by females. In addition, the detected altered hypothalamic expression patterns of Ctbp2 and Nbeal1 as a result of fasting and DIO implicate these genes in weight regulation

Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.

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