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Volume 10 Supplement 1

Human Genome Meeting 2016

Human genome meeting 2016

Houston, TX, USA. 28 February - 2 March 2016

Table of contents

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder

A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson

O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents

R. Polimanti, J. Gelernter

O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort

X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group

O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus

A. Kapoor, D. Lee, A. Chakravarti

O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells

C. Maercker, F. Graf, M. Boutros

O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies

G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis

O7 Role of microRNA in LCL to IPSC reprogramming

S. Kumar, J. Curran, J. Blangero

O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease

S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti

O9 Metabolomic profiling for the diagnosis of neurometabolic disorders

T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea

O10 A novel causal methylation network approach to Alzheimer’s disease

Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett

O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway

A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni

O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types

B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest

O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types

C. A. Semple

O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer

E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project

O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer

F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu

O16 Modeling genetic interactions associated with molecular subtypes of breast cancer

B. Ji, A. Tyler, G. Ananda, G. Carter

O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors

H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski

O18 Predictive biomarkers to metastatic pancreatic cancer treatment

J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman

O19 DDIT4 gene expression as a prognostic marker in several malignant tumors

L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto

O20 Spatial organization of the genome and genomic alterations in human cancers

K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group

O21 Landscape of targeted therapies in solid tumors

S. Patterson, C. Statz, S. Mockus

O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma

S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis

O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis

S. Likhitrattanapisal

O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study

S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen

O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array

T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada

O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation

A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics

O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4

C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung

O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13

K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone

O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data

N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh

O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review

S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs

O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio

S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle

O32 Legal interoperability: a sine qua non for international data sharing

A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group

O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target

H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci

O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs

J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio

O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes

R. Ghosh, S. Plon

O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing

S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs

O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma

T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman

O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver

E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker

O40 A general statistic framework for genome-based disease risk prediction

M. Xiong, L. Ma, N. Lin, C. Amos

O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies

N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong

O42 Big data and NGS data analysis: the cloud to the rescue

O. Dobretsberger, M. Egger, F. Leimgruber

O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing

S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance

O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data

V. A. A. Antonio, N. Ono, Clark Kendrick C. Go

O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data

Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar

O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans

C. Zeng, J. Shao

O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations

H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula

O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing

Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng

O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes?

I. Campbell, M.-A. Young, P. James, Lifepool

O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS

C. Schumacher, S. Sandhu, T. Harkins, V. Makarov

O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform

H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs

O55 Rapid capture methods for clinical sequencing

J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs

O56 A diploid personal human genome model for better genomes from diverse sequence data

K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs

O57 Development of PacBio long range capture for detection of pathogenic structural variants

Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs

O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans

R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers

O59 Assessing RNA structure disruption induced by single-nucleotide variation

J. Lin, Y. Zhang, Z. Ouyang

P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number

A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt

P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility

E. S. Chen

P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients

H. Bahrami, A. Khoshzaban, S. Heidari Keshal

P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population

K. K. R. Alharbi

P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding

M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova

P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population

M. Matar

P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization

N. Mili, R. Molinari, Y. Ma, S. Guerrier

P9 Vulnerability of genetic variants to the risk of autism among Saudi children

N. Elhawary, M. Tayeb, N. Bogari, N. Qotb

P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction

S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion

P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3rd7 mice

Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina

P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients

B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel

P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments

A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey

P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome

D. Graur

P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients

J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak

P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns

B. S. Soibam

P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer

D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder

P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes

J. J. Gruber, N. Jaeger, M. Snyder

P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors

K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson

P23 RNA sequencing identifies gene mutations for neuroblastoma

K. Zhang

P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines

M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales

P25 Targeted Methylation Sequencing of Prostate Cancer

N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder

P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico

S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía

P28 Genetic modifiers of Alström syndrome

J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina

P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos

E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group

P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D

K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess

P34 Molecular regulation of chondrogenic human induced pluripotent stem cells

M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah

P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting

M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid

P36 Accessing genomic evidence for clinical variants at NCBI

S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko

P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA

C. Xiao, E. Yaschenko, S. Sherry

P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling

C. Rangel-Escareño, H. Rueda-Zarate

P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr

S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang

P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data

S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs

P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells

T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium

P43 Rapid and scalable typing of structural variants for disease cohorts

W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs

P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population

A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim

P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations

J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras

P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits

L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups

P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study

S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu

P49 Common variants in casr gene are associated with serum calcium levels in koreans

S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung

P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions

Y. Zhou, S. Xu

P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies

X. Wang, V. Philip, G. Carter

P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment

A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol

P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling

A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar

P54 Direct enrichment for the rapid preparation of targeted NGS libraries

C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel

P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System

R. Nitsche, L. Prieto-Lafuente

P57 ClinVar: a multi-source archive for variant interpretation

M. Landrum, J. Lee, W. Rubinstein, D. Maglott

P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome

Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad

P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation

A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler

P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia

F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder

A. K. Srivastava1, Y. Wang2, R. Huang3, C. Skinner1, T. Thompson3, L. Pollard3, T. Wood3, F. Luo2, R. Stevenson1

1JCSRI, Greenwood Genetic Center, Greenwood, SC, USA; 2School of Computing, Clemson University, Clemson, SC, USA; 3Biochemical Genetics Laboratory, Greenwood Genetic Center, Greenwood, SC, USA

Correspondence: A. K. Srivastava – JCSRI, Greenwood Genetic Center, Greenwood, SC, USA


From the first description by Leo Kanner [1], autism has been an enigmatic neurobehavioral phenomenon. The new genetic/genomic technologies of the past decade have not been as productive as originally anticipated in unveiling the mysteries of autism. The specific etiology of the majority of cases of autism spectrum disorder (ASD) is unknown, although numerous genetic/genomic variants and alterations of diverse cellular functions have been reported. Prompted by this failure, we have investigated whether the metabolomics approach might yield results which could simultaneously lead to a blood-based screening/diagnostic test and to treatment options.


Plasma samples from a clinically well-defined cohort of 100 male individuals, ages 2-16+ years, with ASD and 32 age-matched typically developing (TD) controls were subjected to global metabolomic analysis.


We have identified more than 25 plasma metabolites among the approximately 650 metabolites analyzed, representing over 70 biochemical pathways, that can discriminate children with ASD as young as 2 years from children that are developing typically. The discriminating power was greatest in the 2–10 year age group and weaker in older age groups. The initial findings were validated in a second cohort of 83 children, males and females, ages 2–10 years, with ASD and 76 age and gender-matched TD children. The discriminant metabolites were associated with several key biochemical pathways suggestive of potential contributions of increased oxidative stress, mitochondrial dysfunction, inflammation and immune dysregulation in ASD. Further, targeted quantitative analysis of a subset of discriminating metabolites using tandem mass spectrometry provided a reliable laboratory method to detect children with ASD.


Metabolic profiling appears to be a robust technique to identify children with ASD ages 2–10 years and provides insights into the altered metabolic pathways in ASD, which could lead to treatment strategies.


1. Kanner, L. Autistic disturbances of affective contact. Nervous Child. 1943; 2: 217–250.

Disclosure of interest

None declared.

O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents

R. Polimanti1, J. Gelernter1,2,3

1Department Psychiatry, Yale Sch Med and VA CT Healthcare Center, West Haven, CT, USA; 2Department Genetics, Yale Sch Med and VA CT Healthcare Center, West Haven, CT, USA; 3Department Neurobiology, Yale Sch Med and VA CT Healthcare Center, West Haven, CT, USA

Correspondence: R. Polimanti – Dept Psychiatry, Yale Sch Med and VA CT Healthcare Center, West Haven, CT, USA


To uncover novel traits associated with nicotine and alcohol use genetics, we performed a phenome-wide association study in a large multi-ethnic cohort.


We investigated 7,688 African-Americans (AFR), 1,133 Asian-Americans (ASN), 14,081 European-Americans (EUR), and 3,492 Hispanic-Americans (HISP) from the Women’s Health Initiative, analyzing risk alleles located in the CHRNA5CHRNA3 locus (rs8034191, rs1051730, rs12914385, rs2036527, and rs16969968) for nicotine-related traits and ADH1B (rs1229984 and rs2066702) and ALDH2 (rs671) for alcohol-related traits with respect to anthropometric characteristics, dietary habits, social status, psychological circumstances, reproductive history, health conditions, and nicotine- and alcohol-related traits.


The investigated loci resulted associated with novel traits: rs1229984 were associated with family income (p=4.1*10−12), having a pet (p=6.5*10−11), partner education (p=1.8*10−10), “usually expect the best” (p=2.4*10−7), “felt calm and peaceful” (p=2.6*10−7), education (p=3.7*10−6), and number of term pregnancies (p=1.12*10−5) in EUR; rs1051730 and rs16969968 showed a suggestive association with “High cholesterol requiring pills ever” (p=3.8*10−4 and p=1.8*10−4) in trans-ethnic meta-analysis. We also replicated the known associations: rs80341911 was associated with cigarettes per day (CIGSDAY, p=3.4*10−8), smoking status (p=6.7*10−3), and “smoked at least 100 cigarettes” (p=7.3*10−3) in EUR; rs1051730 and rs16969968 were associated with CIGSDAY (p=9.1*10−8 and p=1.1*10−7) and lung cancer (p=7.3*10−3 and p=9.9*10−3) in EUR; rs2036527 was associated with CIGSDAY (p=3.5*10−3) in AFR; rs1229984 showed associations for alcohol servings (ALC, p=2.9*10−6), beer servings (p=3*10−6), wine servings (WINE, p=3.9*10−6), liquor servings (p=5.5*10−6), dietary alcohol (DIETALC, p=6.1*10−6), “Drinks alcohol (age 50)” (p=9.3*10−6) in EUR and for ALC (p=5.2*10−5) and DIETALC (p=9.6*10−5) in HISP; rs671 resulted associated with alcohol intake (p=3.8*10−8), DIETALC (p=1.9*10−7), ALC (p=1.3*10−6), WINE (p=1.1*10−5) and “Drank 12 alcoholic beverages ever” (p=1.2*10−5) in ASN.


We provided novel genetic data regarding the consequences of smoking and drinking behaviors and confirmed ethnic differences in their genetic predisposition.

Disclosure of interest

None declared.

O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort

X. Lin1, I. Y. Lim1, Y. Wu1, A. L. Teh1, L. Chen1, I. M. Aris1, S. E. Soh1, M. T. Tint2, J. L. MacIsaac3, F. Yap4, K. Kwek4, S. M. Saw2, M. S. Kobor3, M. J. Meaney1, K. M. Godfrey5, Y. S. Chong1, J. D. Holbrook1, Y. S. Lee1, P. D. Gluckman1,6, N. Karnani1, GUSTO study group

1Singapore Institute for Clinical Sciences, Singapore, Singapore; 2National University of Singapore, Singapore, Singapore; 3University of British Columbia, Vancouver, British Columbia, Canada; 4KK Women’s and Children’s Hospital, Singapore, Singapore; 5University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK; 6University of Auckland, Auckland, New Zealand

Correspondence: X. Lin – Singapore Institute for Clinical Sciences, Singapore, Singapore


Prenatal environment and genetic polymorphism can have a lasting impact on offspring’s metabolic function by perturbing its epigenome. Birth weight is often used as a surrogate for the overall quality of the intrauterine environment. We present the first neonate epigenome-wide association study in an Asian mother-offspring cohort, that interrogates the effects of prenatal environment variables, umbilical cord DNA methylation and SNPs, on birth weight.


In GUSTO, a prospective mother-offspring cohort study (N=987), we examined the associations between DNA methylation, SNPs, birth weight and 11 prenatal environment variables. First, we investigated the association between perinatal methylome and birth weight to identify sites of variability in methylation. Second, we interrogated the contribution of genetic and prenatal environmental factors on this variability in the epigenome. Finally, we examined whether these methylation marks at birth were associated with offspring size and adiposity in early childhood.


Methylation levels at 50 CpGs were significantly associated with birth weight, and a subset of these CpGs was located in genes and miRNA known to be involved in metabolic pathways/disorders. We further examined the influence of environmental and genetic factors on methylation at these 50 CpG sites. Sixteen CpGs were associated with both, an additional 24 CpGs were associated with only environmental factors, while only 3 CpGs were associated with genetic factors alone. Environmental factors associated with methylation were predominantly maternal-adiposity-related (pre-pregnancy body mass index, pregnancy weight gain and maternal glucose levels). Methylation levels at half of these CpGs were also associated with offspring size and adiposity in early childhood.


Developmental pathways to obesity begin before birth and involve genetic, epigenetic and environmental factors.

Disclosure of interest

X. Lin: None declared., I. Y. Lim: None declared., Y. Wu: None declared., A. L. Teh: None declared., L. Chen: None declared., I. M. Aris: None declared., S. E. Soh: None declared., M. T. Tint: None declared., J. L. MacIsaac: None declared., F. Yap: None declared., K. Kwek: None declared., S. M. Saw: None declared., M. S. Kobor: None declared., M. J. Meaney: None declared., K. M. Godfrey Conflict with: KMG has received reimbursement for speaking at conferences sponsored by companies selling nutritional products. He is part of an academic consortium that has received research funding from Abbott Nutrition, Nestec and Danone, Y. S. Chong Conflict with: YSC has received reimbursement for speaking at conferences sponsored by companies selling nutritional products. He is part of an academic consortium that has received research funding from Abbott Nutrition, Nestec and Danone, J. D. Holbrook: None declared., Y. S. Lee: None declared., P. D. Gluckman: None declared., N. Karnani: None declared.

O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus

A. Kapoor, D. Lee, A. Chakravarti

McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

Correspondence: A. Kapoor – McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA


Genome-wide association studies (GWAS) have indicated that sequence variation in cis-regulatory elements (CRE) plays important roles in common disease risk/trait variation, but identification of these causal variants has remained a major challenge in complex trait genetics. Here, we performed reporter assays for all common variants at the QT interval associated SCN5A GWAS locus, with the goal of identifying the underlying causal variants.


A target region of ~500kb at SCN5A was defined based on recombination hotspots (rate>10cM/Mb; HapMap) flanking the 5 independent QT interval GWAS hits. Within the target region, all common variants (minor allele frequency >5%) from the 1000 Genomes European ancestry populations in moderate linkage disequilibrium (r2>0.3) with any of the 5 GWAS hits were selected. Both alleles of these variants were amplified with flanking sequences and cloned upstream of a minimal promoter driven firefly luciferase gene in pGL4.23. Human cardiomyocyte cells, AC16, were transfected with test constructs and Renilla luciferase vector (for transfection normalization) in triplicate and luciferase assays were performed 24h later. Reporter assays on a subset of variants were repeated for assessing allelic difference in regulatory activity. All cloning and reporter assays were performed in 96- and 24-well plates.


Of a total 121 variants selected, 112 variants in 104 amplicons passed primer design (amplicon size 256-617bp; median 397bp), and we successfully cloned both alleles for 106 variants in 98 amplicons. In reporter assays, compared to empty vector, 24 and 40 amplicons showed enhancer (>2-fold) and suppressor (<0.5-fold) activities in AC16 cells, respectively. Of these only 4 were observed as open chromatin regions in heart tissue in NIH Epigenomics data. Overall, 12 variants showed nominally significant allelic difference (P<0.05) in reporter activity and were repeated with 18 replicates and 7 variants were identified to have repeated significant allelic difference in regulatory activity.


Independent of the available epigenomic data, which are of limited relevance, an unbiased in vitro reporter screen for CREs overlapping all common variants associated with QT interval at the SCN5A GWAS locus identified 7 common cis-regulatory variants. Our immediate next goals are to a) evaluate the effect of deleting these 7 CREs on SCN5A expression in AC16 cells and b) identify the trans-acting factors regulating their functions.

Disclosure of interest

None declared.

O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells

C. Maercker1, F. Graf2, M. Boutros2

1Esslingen University of Applied Sciences, Esslingen, Germany; 2German Cancer Research Center, Heidelberg, Germany

Correspondence: C. Maercker – Esslingen University of Applied Sciences, Esslingen, Germany


Some cancers show a strong tendency to metastasize to bone, a tissue of mesenchymal origin and a prominent site of mesenchymal stem cells (MSC) residing in the stem cell niche. With bone metastasis formation being one of the most detrimental steps in cancer progression, a better understanding of how bone metastases are initially formed is key to successfully targeting bone metastasis of, for example, prostate cancer. Recent reports have suggested that bone-metastasizing cancers may mimic the process of homing of hematopoietic stem cells to their bone niche.


In order to understand the role of MSC in metastasis formation, we investigated the interaction of primary human bone marrow MSC with established cancer cell lines able to metastasize to bone. With a trans-well migration assay we could show that MSC induced a rapid migration response of prostate and breast cancer cell lines already within two hours after start of the experiment. In order to identify factors stimulating cancer cell migration, MSC cell culture supernatant was separated by size exclusion and ion exchange chromatography. Migratory fractions then were further analyzed by mass spectrometry and antibody array analysis.


With this approach we identified the extracellular matrix proteins type I and type III collagen, fibronectin and laminin 421 as potential drivers of cancer cell migration, which was confirmed by using recombinant proteins. RNAi experiments showed that the cancer cell extracellular matrix receptor beta 1 integrin obviously plays a pivotal role for cell migration.


From our results we conclude that the extracellular matrix as it is produced by MSC obviously plays a crucial role for cancer metastasis and therefore might be a promising anti-cancer drug target.

Disclosure of interest

None declared.

O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies

G. Stamoulis1, F. Santoni2, P. Makrythanasis2, A. Letourneau1, M. Guipponi2, N. Panousis1, M. Garieri1, P. Ribaux1, E. Falconnet1, C. Borel1, S. E. Antonarakis1,2,3

1Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland; 2Geneva University Hospitals-HUG, Service of Genetic Medicine, Geneva, Switzerland; 3iGE3 Institute of Genetics and Genomics of Geneva, University of Geneva Medical School, Geneva, Switzerland

Correspondence: G. Stamoulis – Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland


Trisomy 21 is a model disorder of altered gene expression. We have previously used a pair of monozygotic twins discordant for trisomy 21 to study the global dysregulation of gene expression, without the noise due to genetic variation among individuals (Nature:508; 345–350;2014). The majority of previous studies focused on aneuploidies were conducted οn cell populations or tissues. Our study focusing on gene and allelic expression behaviour of single cells (SC), aims to reveal biological insights regarding the cellular impact of aneuploidy and uncover the mechanisms of gene dosage.


We estimated the allele specific expression (ASE) from RNAseq of ~1000 single cells in different aneuploidies. We used 352 SC fibroblasts (173 Normal and 179 T21 cells) from the pair of monozygotic twins discordant for T21, 166 SC from a mosaic T21, 176 SC from a mosaic T18, 151 SC from a mosaic T8, and 146 SC from a mosaic T13.


In the monozygotic twins, a considerable number of heterozygous sites at the non-chr21 genome showed monoallelic expression (MAE);(Normal: 73.5 % monoallelic in 564,668 observations, and T21: 78.7 % monoallelic in 549,799 observations). There was also considerable MAE for chr21 sites in Normal and, surprisingly, in T21 cells as well (Normal: 63,3 % monoallelic in 5,009 observations, and T21: 72.8 % monoallelic in 6,456 observations). We classified the genes on chr21 in 3 classes according to the level of the aggregate MAE of their corresponding sites (9 monoallelic, 29 intermediate, 2 biallelic). Similar results, i.e. extensive MAE on the supernumerary chromosome genes, were also observed in the other aneuploidies.


We hypothesize that each class of genes contributes in a specific way to the phenotypic variability of Down Syndrome. Our analysis showed that, for genes with monoallelic expression, the abnormal gene dosage induced by the aneuploid chromosome is maybe due to the number of cells expressing the gene. This difference in the fraction of expressing cells could contribute to the development and the variability of phenotypes in aneuploidies. This study provides a new fundamental understanding of the allele specific expression in T21 and other aneuploidies.

Disclosure of interest

None declared.

O7 Role of microRNA in LCL to IPSC reprogramming

S. Kumar1, J. Curran2, J. Blangero2

1South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio-Grande Valley, Edinburg, TX, USA; 2South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio-Grande Valley, Brownsville, TX, USA

Correspondence: S. Kumar – South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio-Grande Valley, Edinburg, TX, USA


A large number of EBV immortalized lymphoblastoid cell lines (LCLs) have been generated and maintained in genetic/epidemiological studies as a perpetual source of DNA and as a surrogate in-vitro cell model. Recent successes in reprograming LCLs into induced pluripotent stem cells (iPSCs) have paved the way to generate more relevant in-vitro disease models using this existing bio-resource. However the effects of EBV encoded oncoproteins on cellular transcription and function make LCLs a unique biomaterial to reprogramme. Accumulating evidence now provides support that miRNAs play a critical role in transcription factor-induced reprogramming of iPSCs.


To investigate the role of miRNAs in regulating gene expression and cellular functions during LCL to iPSC reprogramming, we performed a parallel genome-wide miRNA and mRNA expression analysis in six LCLs and their reprogrammed iPSCs.


A total of 77 miRNAs and 5,228 mRNAs were significantly (FC-abs ≥ 2.0 and FDR ≤ 0.05) differentially expressed (DE) during LCL to iPSC reprogramming out of which 29 miRNAs and 2,317 mRNAs were significantly down-regulated and 48 miRNAs and 2,911mRNAs were significantly up-regulated. The down-regulated miRNAs were highly enriched for LCL specific miRNAs (miR-155, let-7a-i, miR-21, miR-142, miR103, miR-320, miR-146a-b) and the up-regulated miRNAs were highly enriched for iPSC specific miRNAs (miR-302a, miR-302c, miR-371a, miR-302b, miR-302d, miR-372, miR-373miR-92a-1, miR-92a-2, miR-92b, miR-17, miR-20a, miR-18a). Further we performed target prediction analysis for all the significantly DE miRNAs using the miRNA target prediction data bases. The 3,456 genes were predicted to be the targets of the 29 miRNAs that were significantly down-regulated during LCL to iPSC reprogramming. Out of these 3,456 predicted target genes 1,023 were significantly DE during LCL to iPSC reprogramming. For the 48 mi