Association between CYP19 gene SNP rs2414096 Polymorphism and polycystic ovary syndrome in Chinese women

<p>Abstract</p> <p>Background</p> <p>Several studies have reported the association of the SNP rs2414096 in the CYP19 gene with hyperandrogenism, which is one of the clinical manifestations of polycystic ovary syndrome (PCOS). These studies suggest that SNP rs2414096 may be involved in the etiopathogenisis of PCOS. To investigate whetherthe CYP19 gene SNP rs2414096 polymorphism is associated with the susceptibility to PCOS, we designed a case-controlled association study including 684 individuals.</p> <p>Methods</p> <p>A case-controlled association study including 684 individuals (386 PCOS patients and 298 controls) was performed to assess the association of SNP rs2414096 with PCOS. Genotyping of SNP rs2414096 was conducted by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method that was performed on genomic DNA isolated from blood leucocytes. Results were analyzed in respect to clinical test results.</p> <p>Results</p> <p>The genotypic distributions of rs2414096 (GG, AG, AA) in the CYP19 gene (GG, AG, AA) in women with PCOS (0.363, 0.474, 0.163, respectively) were significantly different from that in controls (0.242, 0.500, 0.258, respectively) (<it>P </it>= 0.001). E2/T was different between the AA and GG genotypes. Age at menarche (AAM) and FSH were also significantly different among the GG, AG, and AA genotypes in women with PCOS (P = 0.0391 and 0.0118, respectively). No differences were observed in body mass index (BMI) and other serum hormone concentrations among the three genotypes, either in the PCOS patients or controls.</p> <p>Conclusions</p> <p>Our data suggest that SNP rs2414096 in the CYP19 gene is associated with susceptibility to PCOS.</p

Characterization of novel isoforms and evaluation of SNF2L/SMARCA1 as a candidate gene for X-linked mental retardation in 12 families linked to Xq25-26

<p>Abstract</p> <p>Background</p> <p>Mutations in genes whose products modify chromatin structure have been recognized as a cause of X-linked mental retardation (XLMR). These genes encode proteins that regulate DNA methylation (<it>MeCP2</it>), modify histones (<it>RSK2 </it>and <it>JARID1C</it>), and remodel nucleosomes through ATP hydrolysis (<it>ATRX</it>). Thus, genes encoding other chromatin modifying proteins should also be considered as disease candidate genes. In this work, we have characterized the <it>SNF2L </it>gene, encoding an ATP-dependent chromatin remodeling protein of the ISWI family, and sequenced the gene in patients from 12 XLMR families linked to Xq25-26.</p> <p>Methods</p> <p>We used an <it>in silico </it>and RT-PCR approach to fully characterize specific SNF2L isoforms. Mutation screening was performed in 12 patients from individual families with syndromic or non-syndromic XLMR. We sequenced each of the 25 exons encompassing the entire coding region, complete 5' and 3' untranslated regions, and consensus splice-sites.</p> <p>Results</p> <p>The <it>SNF2L </it>gene spans 77 kb and is encoded by 25 exons that undergo alternate splicing to generate several distinct transcripts. Specific isoforms are generated through the alternate use of exons 1 and 13, and by the use of alternate donor splice sites within exon 24. Alternate splicing within exon 24 removes a NLS sequence and alters the subcellular distribution of the SNF2L protein. We identified 3 single nucleotide polymorphisms but no mutations in our 12 patients.</p> <p>Conclusion</p> <p>Our results demonstrate that there are numerous splice variants of SNF2L that are expressed in multiple cell types and which alter subcellular localization and function. <it>SNF2L </it>mutations are not a cause of XLMR in our cohort of patients, although we cannot exclude the possibility that regulatory mutations might exist. Nonetheless, <it>SNF2L </it>remains a candidate for XLMR localized to Xq25-26, including the Shashi XLMR syndrome.</p

Characterization of novel isoforms and evaluation of SNF2L/SMARCA1 as a candidate gene for X-linked mental retardation in 12 families linked to Xq25-26

<p>Abstract</p> <p>Background</p> <p>Mutations in genes whose products modify chromatin structure have been recognized as a cause of X-linked mental retardation (XLMR). These genes encode proteins that regulate DNA methylation (<it>MeCP2</it>), modify histones (<it>RSK2 </it>and <it>JARID1C</it>), and remodel nucleosomes through ATP hydrolysis (<it>ATRX</it>). Thus, genes encoding other chromatin modifying proteins should also be considered as disease candidate genes. In this work, we have characterized the <it>SNF2L </it>gene, encoding an ATP-dependent chromatin remodeling protein of the ISWI family, and sequenced the gene in patients from 12 XLMR families linked to Xq25-26.</p> <p>Methods</p> <p>We used an <it>in silico </it>and RT-PCR approach to fully characterize specific SNF2L isoforms. Mutation screening was performed in 12 patients from individual families with syndromic or non-syndromic XLMR. We sequenced each of the 25 exons encompassing the entire coding region, complete 5' and 3' untranslated regions, and consensus splice-sites.</p> <p>Results</p> <p>The <it>SNF2L </it>gene spans 77 kb and is encoded by 25 exons that undergo alternate splicing to generate several distinct transcripts. Specific isoforms are generated through the alternate use of exons 1 and 13, and by the use of alternate donor splice sites within exon 24. Alternate splicing within exon 24 removes a NLS sequence and alters the subcellular distribution of the SNF2L protein. We identified 3 single nucleotide polymorphisms but no mutations in our 12 patients.</p> <p>Conclusion</p> <p>Our results demonstrate that there are numerous splice variants of SNF2L that are expressed in multiple cell types and which alter subcellular localization and function. <it>SNF2L </it>mutations are not a cause of XLMR in our cohort of patients, although we cannot exclude the possibility that regulatory mutations might exist. Nonetheless, <it>SNF2L </it>remains a candidate for XLMR localized to Xq25-26, including the Shashi XLMR syndrome.</p

CYP17 genetic polymorphism, breast cancer, and breast cancer risk factors: Australian Breast Cancer Family Study

INTRODUCTION: Because CYP17 can influence the degree of exposure of breast tissues to oestrogen, the interaction between polymorphisms in this gene and hormonal risk factors is of particular interest. We attempted to replicate the findings of studies assessing such interactions with the -34T→C polymorphism. METHODS: Risk factor and CYP17 genotyping data were derived from a large Australian population-based case-control-family study of 1,284 breast cancer cases and 679 controls. Crude and adjusted odds ratio (OR) estimates and 95% confidence intervals (CIs) were calculated by unconditional logistic regression analyses. RESULTS: We found no associations between the CYP17 genotype and breast cancer overall. Premenopausal controls with A(2)/A(2 )genotype had a later age at menarche (P < 0.01). The only associations near statistical significance were that postmenopausal women with A(1)/A(1 )(wild-type) genotype had an increased risk of breast cancer if they had ever used hormone replacement therapy (OR 2.40, 95% CI 1.0 to 5.7; P = 0.05) and if they had menopause after age 47 years (OR 2.59, 95% CI 1.0 to 7.0; P = 0.06). We found no associations in common with any other studies, and no evidence for interactions. CONCLUSION: We observed no evidence of effect modification of reproductive risk factors by CYP17 genotype, although the experiment did not have sufficient statistical power to detect small main effects and modest effects in subgroups. Associations found only in subgroup analyses based on relatively small numbers require cautious interpretation without confirmation by other studies. This emphasizes the need for replication in multiple and large population-based studies to provide convincing evidence for gene–environment interactions

Brain Region–Specific Decrease in the Activity and Expression of Protein Kinase A in the Frontal Cortex of Regressive Autism

Autism is a severe neurodevelopmental disorder that is characterized by impaired language, communication, and social skills. In regressive autism, affected children first show signs of normal social and language development but eventually lose these skills and develop autistic behavior. Protein kinases are essential in G-protein-coupled, receptor-mediated signal transduction and are involved in neuronal functions, gene expression, memory, and cell differentiation. We studied the activity and expression of protein kinase A (PKA), a cyclic AMP–dependent protein kinase, in postmortem brain tissue samples from the frontal, temporal, parietal, and occipital cortices, and the cerebellum of individuals with regressive autism; autistic subjects without a clinical history of regression; and age-matched developmentally normal control subjects. The activity of PKA and the expression of PKA (C-α), a catalytic subunit of PKA, were significantly decreased in the frontal cortex of individuals with regressive autism compared to control subjects and individuals with non-regressive autism. Such changes were not observed in the cerebellum, or the cortices from the temporal, parietal, and occipital regions of the brain in subjects with regressive autism. In addition, there was no significant difference in PKA activity or expression of PKA (C-α) between non-regressive autism and control groups. These results suggest that regression in autism may be associated, in part, with decreased PKA-mediated phosphorylation of proteins and abnormalities in cellular signaling

Consensus Paper: Radiological Biomarkers of Cerebellar Diseases

Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

A global reference for human genetic variation

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Däkel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche duQuébec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute