Search

TET3 encodes an essential dioxygenase involved in epigenetic regulation through DNA demethylation. TET3 deficiency, or Beck-Fahrner syndrome (BEFAHRS; MIM: 618798), is a recently described neurodevelopmental disorder of the DNA demethylation machinery with a nonspecific phenotype resembling other chromatin-modifying disorders, but inconsistent variant types and inheritance patterns pose diagnostic challenges. Given TET3’s direct role in regulating 5-methylcytosine and recent identification of syndrome-specific DNA methylation profiles, we analyzed genome-wide DNA methylation in whole blood of TET3-deficient individuals and identified an episignature that distinguishes affected and unaffected individuals and those with mono-allelic and bi-allelic pathogenic variants. Validation and testing of the episignature correctly categorized known TET3 variants and determined pathogenicity of variants of uncertain significance. Clinical utility was demonstrated when the episignature alone identified an affected individual from over 1000 undiagnosed cases and was confirmed upon distinguishing TET3-deficient individuals from those with 46 other disorders. The TET3-deficient signature - and the signature resulting from activating mutations in DNMT1 which normally opposes TET3 - are characterized by hypermethylation, which for BEFAHRS involves CpG sites that may be biologically relevant. This work expands the role of epi-phenotyping in molecular diagnosis and reveals genome-wide DNA methylation profiling as a quantitative, functional readout for characterization of this new biochemical category of disease.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P, Reporting Summary. Further information on experimental design is available in the Life Sciences Reporting Summary linked to this article.

Kabuki syndrome is a monogenic disorder caused by loss of function variants in either of two genes encoding histone-modifying enzymes. We performed targeted sequencing in a cohort of 27 probands with a clinical diagnosis of Kabuki syndrome. Of these, 12 had causative variants in the two known Kabuki syndrome genes. In 2, we identified presumptive loss of function de novo variants in KMT2A (missense and splice site variants), a gene that encodes another histone modifying enzyme previously exclusively associated with Wiedermann-Steiner syndrome. Although Kabuki syndrome is a disorder of histone modification, we also find alterations in DNA methylation among individuals with a Kabuki syndrome diagnosis relative to matched normal controls, regardless of whether they carry a variant in KMT2A or KMT2D or not. Furthermore, we observed characteristic global abnormalities of DNA methylation that distinguished patients with a loss of function variant in KMT2D or missense or splice site variants in either KMT2D or KMT2A from normal controls. Our results provide new insights into the relationship of genotype to epigenotype and phenotype and indicate cross-talk between histone and DNA methylation machineries exposed by inborn errors of the epigenetic apparatus.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P −6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel “disease gene” discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

Recent technological advancements have permitted high-throughput measurement of the human genome, epigenome, metabolome, transcriptome, and proteome at the population level. We hypothesized that subsets of genes identified from omic studies might have closely related biological functions and thus might interact directly at the network level. Therefore, we conducted an integrative analysis of multi-omic datasets of non-small cell lung cancer (NSCLC) to search for association patterns beyond the genome and transcriptome. A large, complex, and robust gene network containing well-known lung cancer-related genes, including EGFR and TERT, was identified from combined gene lists for lung adenocarcinoma. Members of the hypoxia-inducible factor (HIF) gene family were at the center of this network. Subsequent sequencing of network hub genes within a subset of samples from the Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO) consortium revealed a SNP (rs12614710) in EPAS1 associated with NSCLC that reached genome-wide significance (OR = 1.50; 95% CI: 1.31–1.72; p = 7.75 × 10−9). Using imputed data, we found that this SNP remained significant in the entire TRICL-ILCCO consortium (p = .03). Additional functional studies are warranted to better understand interrelationships among genetic polymorphisms, DNA methylation status, and EPAS1 expression., • Previous Evidence • As a major participant of Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO), we continued monitoring the progress of genomic and other omics studies of lung cancer through regular communications within the consortium and literature search using the PubMed database. The TRICL-ILCCO is one of the largest international consortium of lung cancer which includes many major ongoing lung cancer case-control and cohort studies with the aim of sharing comparable data. Although GWAS successfully defined many lung cancer-associated genomic loci, the integrative studies of multi-dimensional high throughput “-omics” measurements from tumor tissues and corresponding blood specimens are limited. • Added value of this study • We identified a HIFs-EGFR-HDAC4-TERT network associated with lung adenocarcinoma, and subsequent sequencing of network hub genes identified a new locus within EPAS1 that is associated with lung cancer risk. This locus is in hub gene EPAS1, which is a key member of the HIF family involved in every aspect of cancer development and progression. • Implications of all the available evidence • We developed a network building approach for the integrative analysis of multi-omic datasets. The integration of multi-dimensional high throughput “-omics” measurements from tumor tissues and corresponding blood specimens, together with new systems strategies for diagnostics, enables the identification of cancer biomarkers that will facilitate pre-symptomatic diagnosis, stratification of disease, assessment of disease progression, evaluation of patient response to therapy, and identification of recurrences.

The common nonsynonymous variant rs16969968 in the α5 nicotinic receptor subunit gene (CHRNA5) is the strongest genetic risk factor for nicotine dependence in European Americans and contributes to risk in African Americans. To comprehensively examine whether other CHRNA5 coding variation influences nicotine dependence risk, we performed targeted sequencing on 1582 nicotine-dependent cases (Fagerstrom Test for Nicotine Dependence score⩾4) and 1238 non-dependent controls, with independent replication of common and low frequency variants using 12 studies with exome chip data. Nicotine dependence was examined using logistic regression with individual common variants (minor allele frequency (MAF)⩾0.05), aggregate low frequency variants (0.05>MAF⩾0.005) and aggregate rare variants (MAF

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

Bioinformatics approaches to examine gene-gene models provide a means to discover interactions between multiple genes that underlie complex disease. Extensive computational demands and adjusting for multiple testing make uncovering genetic interactions a challenge. Here, we address these issues using our knowledge-driven filtering method, Biofilter, to identify putative single nucleotide polymorphism (SNP) interaction models for cataract susceptibility, thereby reducing the number of models for analysis. Models were evaluated in 3,377 European Americans (1,185 controls, 2,192 cases) from the Marshfield Clinic, a study site of the Electronic Medical Records and Genomics (eMERGE) Network, using logistic regression. All statistically significant models from the Marshfield Clinic were then evaluated in an independent dataset of 4,311 individuals (742 controls, 3,569 cases), using independent samples from additional study sites in the eMERGE Network: Mayo Clinic, Group Health/University of Washington, Vanderbilt University Medical Center, and Geisinger Health System. Eighty-three SNP-SNP models replicated in the independent dataset at likelihood ratio test P < 0.05. Among the most significant replicating models was rs12597188 (intron of CDH1)–rs11564445 (intron of CTNNB1). These genes are known to be involved in processes that include: cell-to-cell adhesion signaling, cell-cell junction organization, and cell-cell communication. Further Biofilter analysis of all replicating models revealed a number of common functions among the genes harboring the 83 replicating SNP-SNP models, which included signal transduction and PI3K-Akt signaling pathway. These findings demonstrate the utility of Biofilter as a biology-driven method, applicable for any genome-wide association study dataset.

Summary/AbstractGenome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development, and clinical guidelines. However, the dominance of European-ancestry populations in GWAS creates a biased view of the role of human variation in disease, and hinders the equitable translation of genetic associations into clinical and public health applications. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioral phenotypes in 49,839 non-European individuals. Using strategies designed for analysis of multi-ethnic and admixed populations, we confirm 574 GWAS catalog variants across these traits, and find 38 secondary signals in known loci and 27 novel loci. Our data shows strong evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts, and insights into clinical implications. We strongly advocate for continued, large genome-wide efforts in diverse populations to reduce health disparities.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1–3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4–10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States—where minority populations have a disproportionately higher burden of chronic conditions13—the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.

Genotyping arrays have been widely adopted as an efficient means to interrogate variation across the human genome. Genetic variants may be observed either directly, via genotyping, or indirectly, through linkage disequilibrium with a genotyped variant. The total proportion of genomic variation captured by an array, either directly or indirectly, is referred to as “genomic coverage.” Here we use genotype imputation and Phase 3 of the 1000 Genomes Project to assess genomic coverage of several modern genotyping arrays. We find that in general, coverage increases with increasing array density. However, arrays designed to cover specific populations may yield better coverage in those populations compared to denser arrays not tailored to the given population. Ultimately, array choice involves trade-offs between cost, density, and coverage, and our work helps inform investigators weighing these choices and trade-offs.

Author(s): Taylor, Kimberly E; Wong, Quenna; Levine, David M; McHugh, Caitlin; Laurie, Cathy; Doheny, Kimberly; Lam, Mi Y; Baer, Alan N; Challacombe, Stephen; Lanfranchi, Hector; Schiodt, Morten; Srinivasan, M; Umehara, Hisanori; Vivino, Frederick B; Zhao, Yan; Shiboski, Stephen C; Daniels, Troy E; Greenspan, John S; Shiboski, Caroline H; Criswell, Lindsey A | Abstract: ObjectiveThe Sjogren's International Collaborative Clinical Alliance (SICCA) is an international data registry and biorepository derived from a multisite observational study of participants in whom genotyping was performed on the Omni2.5M platform and who had undergone deep phenotyping using common protocol-directed methods. The aim of this study was to examine the genetic etiology of Sjogren's syndrome (SS) across ancestry and disease subsets.MethodsWe performed genome-wide association study analyses using SICCA subjects and external controls obtained from dbGaP data sets, one using all participants (1,405 cases, 1,622 SICCA controls, and 3,125 external controls), one using European participants (585, 966, and 580, respectively), and one using Asian participants (460, 224, and 901, respectively) with ancestry adjustments via principal components analyses. We also investigated whether subphenotype distributions differ by ethnicity, and whether this contributes to the heterogeneity of genetic associations.ResultsWe observed significant associations in established regions of the major histocompatibility complex (MHC), IRF5, and STAT4 (P = 3 × 10-42 , P = 3 × 10-14 , and P = 9 × 10-10 , respectively), and several novel suggestive regions (those with 2 or more associations at P l 1 × 10-5 ). Two regions have been previously implicated in autoimmune disease: KLRG1 (P = 6 × 10-7 [Asian cluster]) and SH2D2A (P = 2 × 10-6 [all participants]). We observed striking differences between the associations in Europeans and Asians, with high heterogeneity especially in the MHC; representative single-nucleotide polymorphisms from established and suggestive regions had highly significant differences in the allele frequencies in the study populations. We showed that SSA/SSB autoantibody production and the labial salivary gland focus score criteria were associated with the first worldwide principal component, indicative of higher non-European ancestry (P = 4 × 10-15 and P = 4 × 10-5 , respectively), but that subphenotype differences did not explain most of the ancestry differences in genetic associations.ConclusionGenetic associations with SS differ markedly according to ancestry; however, this is not explained by differences in subphenotypes.

The OCAC OncoArray genotyping project: et al., To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC., The OCAC OncoArray genotyping project was funded through grants from the US National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.) and R01-CA058598 (M.T.G.)); Canadian Institutes of Health Research (MOP-86727 (L.E.K.)); and the Ovarian Cancer Research Fund (A.B.). Funding for the CIMBA OncoArray genotyping was provided by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Génome Québec, the Quebec Breast Cancer Foundation for the PERSPECTIVE project, the US National Institutes of Health (CA1X01HG007491-01 (C.I.A.)), the Odense University Hospital Research Foundation (M.T.), the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (1420190 (S.K.P.)), the Italian Association for Cancer Research (IG16933 (L.O.)) and German Cancer Aid (110837 (R.K.S.).

Lateral meningocele syndrome (LMS, OMIM%130720), also known as Lehman syndrome, is a very rare skeletal disorder with facial anomalies, hypotonia and meningocele-related neurologic dysfunction. The characteristic lateral meningoceles represent the severe end of the dural ectasia spectrum and are typically most severe in the lower spine. Facial features of LMS include hypertelorism and telecanthus, high arched eyebrows, ptosis, midfacial hypoplasia, micrognathia, high and narrow palate, low-set ears and a hypotonic appearance. Hyperextensibility, hernias and scoliosis reflect a connective tissue abnormality, and aortic dilation, a high-pitched nasal voice, wormian bones and osteolysis may be present. Lateral meningocele syndrome has phenotypic overlap with Hajdu–Cheney syndrome. We performed exome resequencing in five unrelated individuals with LMS and identified heterozygous truncating NOTCH3 mutations. In an additional unrelated individual Sanger sequencing revealed a deleterious variant in the same exon 33. In total, five novel de novo NOTCH3 mutations were identified in six unrelated patients. One had a 26 bp deletion (c.6461_6486del, p.G2154fsTer78), two carried the same single base pair insertion (c.6692_93insC, p.P2231fsTer11), and three individuals had a nonsense point mutation at c.6247A > T (pK2083*), c.6663C > G (p.Y2221*) or c.6732C > A, (p.Y2244*). All mutations cluster into the last coding exon, resulting in premature termination of the protein and truncation of the negative regulatory proline-glutamate-serine-threonine rich PEST domain. Our results suggest that mutant mRNA products escape nonsense mediated decay. The truncated NOTCH3 may cause gain-of-function through decreased clearance of the active intracellular product, resembling NOTCH2 mutations in the clinically related Hajdu–Cheney syndrome and contrasting the NOTCH3 missense mutations causing CADASIL. © 2014 Wiley Periodicals, Inc.

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.

Microarray single-nucleotide polymorphism genotyping, combined with imputation of untyped variants, has been widely adopted as an efficient means to interrogate variation across the human genome. “Genomic coverage” is the total proportion of genomic variation captured by an array, either by direct observation or through an indirect means such as linkage disequilibrium or imputation. We have performed imputation-based genomic coverage assessments of eight current genotyping arrays that assay from ~0.3 to ~5 million variants. Coverage was determined separately in each of the four continental ancestry groups in the 1000 Genomes Project phase 1 release. We used the subset of 1000 Genomes variants present on each array to impute the remaining variants and assessed coverage based on correlation between imputed and observed allelic dosages. More than 75% of common variants (minor allele frequency > 0.05) are covered by all arrays in all groups except for African ancestry, and up to ~90% in all ancestries for the highest density arrays. In contrast, less than 40% of less common variants (0.01 < minor allele frequency < 0.05) are covered by low density arrays in all ancestries and 50–80% in high density arrays, depending on ancestry. We also calculated genome-wide power to detect variant-trait association in a case-control design, across varying sample sizes, effect sizes, and minor allele frequency ranges, and compare these array-based power estimates with a hypothetical array that would type all variants in 1000 Genomes. These imputation-based genomic coverage and power analyses are intended as a practical guide to researchers planning genetic studies.

This unit describes a technique for generating exome-enriched sequencing libraries using DNA extracted from formalin-fixed paraffin-embedded (FFPE) samples. Utilizing commercially available kits, we present a low-input FFPE workflow starting with 50 ng of DNA. This procedure includes a repair step to address damage caused by FFPE preservation that improves sequence quality. Subsequently, libraries undergo an in-solution-targeted selection for exons, followed by sequencing using the Illumina next-generation short-read sequencing platform. © 2017 by John Wiley & Sons, Inc.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P

Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. TRICL (Transdisciplinary Research for Cancer of Lung) and International Lung Cancer Consortium (ILCCO): National Institute of Health U19 CA148127-01 (C.I. Amos, J. Byun, Y. Li, X. Xiao, J. L. Forman, A. Risch, H. Bickeböller, M. Waldenberger, I. Brüske, J. Manz, P. Brennan, R. Hung, H. Shen, Y. Shi, A. Kamal, C. I. Amos, J.K. Field), Canadian Cancer Society Research Institute (no. 020214, R. Hung). DRIVE (Discovery, Biology, and Risk of Inherited Variants in Breast Cancer): National Institute of Health U19 CA148065 (D.J. Hazelett, D. F. Easton, S. Lindström, P. Kraft, J. Dennis, A. Dunning, K. Michailidou, L. Fachal, S. Benlloch, J. Cunningham, K. Butterbach, K. Offit, R. Schmutzler, L. Ottini, D. Vincent). CORECT (ColoRectal Transdisciplinary Study): National Institute of Health U19 CA148107; R01 CA81488, P30 CA014089 (S. Gruber, U. Peters, G. Casey). ELLIPSE (ELLIPSE, Elucidating Loci in Prostate Cancer Susceptibility): This work was support by U19 CA148537(F. Schumacher, S.A. Gayther, S.L. Schmit, C.K. Edlund, D.J. Hazelett, G.A. Coetzee, C. Haiman, S. Demetriades, D. Van Den Berg). FOCI (Transdisciplinary Cancer Genetic Association and Interacting Studies): National Institutes of Health U19 CA148112- 01 (T.A. Sellers, C. Phelan), R01-CA122443(B. Hicks) ) P50-CA116201, CA192393 (F. Couch), P50-CA136393(J. Cunningham, F. Couch), OCAC - CA-149429 (C. Phelan). , P30-CA15083 (B. Hicks), Cancer Research UK (C490/A8339(A. Antoniou, P. Pharoah, A. Dunning), C490/A16561(P. Pharoah, A. Dunning), C490/A10119 (A. Dunning, P. Pharoah), C490/A10124 (A. Dunning, P. Pharoah)). ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC) (F. Bacot). DACHS: German Research Council (Deutsche Downloaded from cebp.aacrjournals.org on October 31, 2016. © 2016 American Association for Cancer Research. Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 3, 2016; DOI: 10.1158/1055-9965.EPI-16-0106 Forschungsgemeinschaft, BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, and CH 117/1-1, C.K. Edlund), and the German Federal Ministry of Education and Research (01KH0404 and 01ER0814). Prostate Lung Colon Ovarian Screening trial: Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: R. Schmutzler, Cologne). The PERSPECTIVE (J. Simard) project was supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (MOP-86727, L.E. Kelemen), the Ministère de l’Économie, Innovation et Exportation du Québec through Genome Québec, and thee Quebec Breast Cancer Foundation, including additional funding from the Canadian Breast Cancer Foundation and the National Cancer Institute USA through Breast Cancer Family Registry Cohort (#1UM1CA164920-01A1). European Union Framework Programme for Research and Innovation (MSCA-IF-2014-EF-656144)(L. Fachal). The Breast Cancer Research Foundation, P30 CA08748, Andrew Sabin Foundation (K. Offit). CIDR genotyping for the Oncoarray was conducted under contract 268201200008I to K.Doheny and through grant 1X01HG007491- 01 to C.I. Amos. This is the author accepted manuscript. The final version is available from American Association for Cancer Research via http://dx.doi.org/10.1158/1055-9965.EPI-16-0106

Karen Mohlke, Markku Laakso, Michael Boehnke and colleagues report the first application of the Illumina HumanExome Beadchip array, examining association with insulin and glycemic traits in 8,229 nondiabetic Finnish males from the population-based Metabolic Syndrome in Men (METSIM) study. They identify low-frequency coding variants at both known and newly associated loci with insulin processing and secretion.

DNA sample contamination is a serious problem in DNA sequencing studies and may result in systematic genotype misclassification and false positive associations. Although methods exist to detect and filter out cross-species contamination, few methods to detect within-species sample contamination are available. In this paper, we describe methods to identify within-species DNA sample contamination based on (1) a combination of sequencing reads and array-based genotype data, (2) sequence reads alone, and (3) array-based genotype data alone. Analysis of sequencing reads allows contamination detection after sequence data is generated but prior to variant calling; analysis of array-based genotype data allows contamination detection prior to generation of costly sequence data. Through a combination of analysis of in silico and experimentally contaminated samples, we show that our methods can reliably detect and estimate levels of contamination as low as 1%. We evaluate the impact of DNA contamination on genotype accuracy and propose effective strategies to screen for and prevent DNA contamination in sequencing studies.

When smokers were separated by their nicotinic receptor gene variants, those with the low-risk genotype responded equally well to pharmacological treatments, including both nicotine replacement and bupropion, and nonpharmacological therapies. Those with the high-risk genotype, as identified by DNA sequencing, responded only to pharmacological treatments. Clinicians advising patients on smoking cessation can suspect genetic risk on the basis of early onset of heavy smoking and direct those smokers specifically to pharmacological treatments.

Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (

Genome-wide association studies (GWAS) are a useful approach in the study of the genetic components of complex phenotypes. Aside from large cohorts, GWAS have generally been limited to the study of one or a few diseases or traits. The emergence of biobanks linked to electronic medical records (EMRs) allows the efficient re-use of genetic data to yield meaningful genotype-phenotype associations for multiple phenotypes or traits. Phase I of the electronic MEdical Records and GEnomics (eMERGE-I) Network is a National Human Genome Research Institute (NHGRI)-supported consortium composed of five sites to perform various genetic association studies using DNA repositories and EMR systems. Each eMERGE site has developed EMR-based algorithms to comprise a core set of fourteen phenotypes for extraction of study samples from each site’s DNA repository. Each eMERGE site selected samples for a specific phenotype, and these samples were genotyped at either the Broad Institute or at the Center for Inherited Disease Research (CIDR) using the Illumina Infinium BeadChip technology. In all, approximately 17,000 samples from across the five sites were genotyped. A unified quality control (QC) pipeline was developed by the eMERGE Genomics Working Group and used to ensure thorough cleaning of the data. This process includes examination of sample quality, marker quality, and various batch effects. Upon completion of the genotyping and QC analyses for each site’s primary study, the eMERGE Coordinating Center merged the datasets from all five sites. This larger merged dataset re-entered the established eMERGE QC pipeline. Based on lessons learned during the process, additional analyses and QC checkpoints were added to the pipeline to ensure proper merging. Here we explore the challenges associated with combining datasets from different genotyping centers and describe the expansion to the eMERGE QC pipeline for merged datasets. These additional steps will be useful as the eMERGE project expands to include additional sites in eMERGE-II and also serve as a starting point for investigators merging multiple genotype data sets accessible through the National Center for Biotechnology Information (NCBI) in the database of Genotypes and Phenotypes (dbGaP). Our experience demonstrates that merging multiple datasets after additional QC can be an efficient use of genotype data despite new challenges that appear in the process.

Ischemic stroke (IS) is among the leading causes of death in Western countries. There is a significant genetic component to IS susceptibility, especially among young adults. To date, research to identify genetic loci predisposing to stroke has met only with limited success. We performed a genome-wide association (GWA) analysis of early-onset IS to identify potential stroke susceptibility loci. The GWA analysis was conducted by genotyping 1 million SNPs in a biracial population of 889 IS cases and 927 controls, ages 15–49 years. Genotypes were imputed using the HapMap3 reference panel to provide 1.4 million SNPs for analysis. Logistic regression models adjusting for age, recruitment stages, and population structure were used to determine the association of IS with individual SNPs. Although no single SNP reached genome-wide significance (P < 5 × 10−8), we identified two SNPs in chromosome 2q23.3, rs2304556 (in FMNL2; P = 1.2 × 10−7) and rs1986743 (in ARL6IP6; P = 2.7 × 10−7), strongly associated with early-onset stroke. These data suggest that a novel locus on human chromosome 2q23.3 may be associated with IS susceptibility among young adults.

White blood cell count (WBC) is unique among identified inflammatory predictors of chronic disease in that it is routinely measured in asymptomatic patients in the course of routine patient care. We led a genome-wide association analysis to identify variants associated with WBC levels in 13,923 subjects in the electronic Medical Records and Genomics (eMERGE) Network. We identified two regions of interest that were each unique to subjects of genetically determined ancestry to the African continent (AA) or to the European continent (EA). WBC varies among different ancestry groups. Despite being ancestry specific, these regions were identifiable in the combined analysis. In AA subjects, the region surrounding the Duffy antigen/chemokine receptor gene (DARC) on 1q21 exhibited significant association (p value = 6.71e–55). These results validate the previously reported association between WBC and of the regulatory variant rs2814778 in the promoter region, which causes the Duffy negative phenotype (Fy−/−). A second missense variant (rs12075) is responsible for the two principal antigens, Fya and Fyb of the Duffy blood group system. The two variants, consisting of four alleles, act in concert to produce five antigens and subsequent phenotypes. We were able to identify the marginal and novel interaction effects of these two variants on WBC. In the EA subjects, we identified significantly associated SNPs tagging three separate genes in the 17q21 region: (1) GSDMA, (2) MED24, and (3) PSMD3. Variants in this region have been reported to be associated with WBC, neutrophil count, and inflammatory diseases including asthma and Crohn’s disease.

Cannabis dependence is the third leading contributor to admissions to chemical dependency treatment settings (Treatment Episode Data Set, 2003) and rates of past year cannabis dependence in the U.S. population have increased by 18% since 1991–1992 (Compton et al., 2004). Several studies report strong heritable influences on cannabis dependence [h2 of 50–70%] (Agrawal and Lynskey, 2006). In an effort to identify contributors to this composite heritability, multiple linkage and association studies have been conducted. Several promising linkage regions (e.g. chromosome 3) exist. Candidate gene studies have largely focused on variants in the gene encoding the cannabinoid receptor CNR1 – results remain equivocal (Agrawal and Lynskey, 2009). To our knowledge, there are currently no published genomewide association studies (GWAS) of cannabis dependence. The goal of this investigation is to conduct association analysis between 948,142 single nucleotide polymorphisms (SNPs) and lifetime DSM-IV cannabis dependence using data on 708 cases with DSM-IV cannabis dependence and 2346 controls who report lifetime cannabis use but do not meet criteria for DSM-IV dependence. Data for this study come from the Study of Addiction: Genes and Environment (SAGE) (Bierut et al., 2010), which was one of the 8 Phase 1 studies of the Gene Environment Association (GENEVA) consortium (Cornelis et al., 2010). The study was designed primarily to study DSM-IV alcohol dependence as well as other correlated addiction phenotypes. All phenotypic data were collected using the Semi-Structured Assessment for the Genetics of Alcoholism Interview (SSAGA) (Bucholz et al., 1994b). Reliability of SSAGA diagnoses of substance use disorders is good (kappas of 0.7 and higher)(Bucholz et al., 1994a). Case status for the analyses reported here was defined as a lifetime history of DSM-IV cannabis dependence, modified to include cannabis withdrawal (i.e. 3 or more of 7 criteria clustering within a 12-month period). Controls had used cannabis at least once in their lifetime but did not meet criteria for DSM-IV dependence criteria (however, those meeting criteria for dependence on other psychoactive substances, including alcohol, were not excluded). Those who had never used cannabis even once in their lifetime (N=946) were omitted (however, re-doing analyses including them as unaffected showed similar results). DNA samples were genotyped on the Illumina Human 1M beadchip by the Center for Inherited Diseases Research (CIDR) at Johns Hopkins University. 948,658 SNPs passed data cleaning procedures – further within-sample filtering for autosomal and X-chromosome markers yielded 948,142 markers. HapMap genotyping controls, duplicates, related subjects, and outliers were removed from the sample set. Two thousand and nineteen subjects reported being European American and 1,035 reported being African American. Further details are available in a related publication (Bierut et al., 2010). Logistic regressions analyses were conducted in PLINK (Purcell et al., 2007), controlling for sex, age (defined, using quartiles, as 3 dummy measures representing 34 years or younger, 35–39 years, 40–44 years, with 45 years and older as the reference group), study source (see Bierut et al., 2010 for details) and two principal components (computed in EIGENSTRAT/EIGENSOFT, (Price et al., 2006)) indexing continuous variation in ethnicity. The overall genomic inflation factor was 1.014 after controlling for principal components representing ethnicity, suggesting minimal stratification effects. Genotypes (917,694 autosomal SNPs and 30,448 SNPs on the X-chromosome) were coded as 0, 1 or 2 copies of the reference allele so that risk associated with genotype was modified with each additional copy of the reference allele. DSM-IV cannabis dependent cases were significantly more likely to be males (68% vs. 43%) and were less likely to report completion of high school (18% vs 10% who did not complete). Consistent with ascertainment, cases were significantly more likely than controls to meet criteria for alcohol (94% vs 46%), nicotine (78% vs 46%) and cocaine (73% vs 21%) dependence, greater use of other illicit drugs (88% vs 47%) as well as report a younger age at initiation of cannabis use (14.5 vs 17.4 years) and more recent (44% vs 19% using in the past year) cannabis involvement. Thus, cases show marked phenotypic similarity to the highly heritable TypeII/B cluster of cannabis dependent subjects (Ehlers et al., 2009). The lowest p-values were obtained for polymorphisms on chromosome 17 (rs1019238 and rs1431318, p-values < E−7; rs8065311, p-value < E−6; rs9894332 and rs10521290, p-values < E−5). The top SNP lies in the ankyrin-repeat and fibronectin type III domain containing 1 (ANKFN1) gene, which was previously identified in a genomic study of general vulnerability to substance use disorders (Johnson et al., 2009). The genomic control p-value for rs1019238 was 7.3 × 10−7 suggesting adequate control for ethnic variation. The remaining SNPs (except rs10521290) are non-genic but are in strong LD (r2 of 0.75–0.88) with SNPs in ANKFN1. Fibronectin repeats are important constituents of a variety of proteins (Bloom and Calabro, 2009) and ankyrin repeats mediate protein interactions (Li et al., 2006). While there are links between ANKFN1 and PTEN (phosphatase and tensin homolog) in tumorigenesis (Syed et al., 2010), the specific role that ANKFN1 might play in the etiology of cannabis dependence is unknown. Table 1 presents odds-ratios for the full sample, as well as results stratified by ethnicity, for SNPs that yielded the most promising results. A number of genes on chromosome 12 (including the p- and q-arm) were associated, including carbohydrate (chondroitin 4) sulfotransferase 11 (CHST11). None of the SNPs that emerged as our top findings have known functional significance. Association results across the full autosomal genome and the X chromosome are shown in Figure 1. Figure 1 Manhattan plot showing genomewide association results for autosomal SNPs and SNPs on the X chromosome for DSM-IV cannabis dependence in SAGE. Table 1 Association results of top 30 SNPs from a genomewide association study of 708 DSM-IV cannabis dependence cases and 2346 controls from SAGE. (All allele frequencies and odds-ratios reflect analysis of increasing risk associated with the reference allele). ... While our primary analyses accounted for population stratification, we also show, in Table 1, findings within each ethnic group. A number of the SNPs showed ethnic variations in allele frequency. In a majority of instances, odds-ratios were comparable across the European- and African-American samples. However, 5 SNPs were found to have exceedingly low MAFs in the European-American sample suggesting that their overall significance in the full sample may be attributable to their effects in the smaller African-American sample. A limitation of this study is that SAGE was ascertained for alcohol dependence. This led to a high level of comorbidity in the cannabis dependent cases and exposed controls. However, the use of controls with other forms of substance dependence, but not cannabis dependence, protected against signals that may have been less specific. In addition, a series of analyses was conducted that supported the specificity of these findings. First, SNPs in ANKFN1 were not significant when case status was alcohol (also nicotine and cocaine) dependence without comorbid cannabis dependence. Second, we created a polydrug dependence diagnosis, and results were not significant when cannabis dependent individuals were excluded from those with other polydrug dependence. While a sample ascertained for cannabis dependence would be ideal, there are challenges associated with the recruitment of such a sample (Agrawal and Lynskey, 2009), and to our knowledge, no such samples currently exist. Further, while cannabis dependence is highly heritable, none of our association signals reach genomewide significance, nor do the composite of the top 30 signals explain a considerable proportion of this heritable variance in cannabis dependence. The Benjamini-Hochberg False Discovery Rate (Benjamini and Hochberg, 1995) for the top signal was .325. Power computations reveal that at MAFs ranging from 15–40%, association signals with odds-ratios exceeding 1.45, such as our top SNP, would be detected. Thus, both replication and meta-analysis are required to confirm or refute these findings. Characterizing the genetic underpinnings of cannabis dependence remains elusive – to this end, results from GWAS might provide clues into alternative biological pathways that shape the etiology of cannabis dependence.

Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies. This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium (HWE) test p-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis (PCA) to SNP selection. The methods are illustrated with examples from the ‘Gene Environment Association Studies’ (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of genome-wide association studies.

Parkinson's disease is a common disorder that leads to motor and cognitive disability. We performed a genome-wide association study of 2,000 individuals with Parkinson's disease (cases) and 1,986 unaffected controls from the NeuroGenetics Research Consortium (NGRC)(1-5). We confirmed associations with SNCA(2,6-8) and MAPT(3,7-9), replicated an association with GAK9 (using data from the NGRC and a previous study(9), P = 3.2 x 10(-9)) and detected a new association with the HLA region (using data from the NGRC only, P = 2.9 x 10(-8)), which replicated in two datasets (meta-analysis P = 1.9 x 10(-10)). The HLA association was uniform across all genetic and environmental risk strata and was strong in sporadic (P = 5.5 x 10(-10)) and late-onset (P = 2.4 x 10(-8)) disease. The association peak we found was at rs3129882, a noncoding variant in HLA-DRA. Two studies have previously suggested that rs3129882 influences expression of HLA-DR and HLA-DQ(10,11). The brains of individuals with Parkinson's disease show upregulation of DR antigens and the presence of DR-positive reactive microglia(12), and nonsteroidal anti-inflammatory drugs reduce Parkinson's disease risk(4,13). The genetic association with HLA supports the involvement of the immune system in Parkinson's disease and offers new targets for drug development.

Excessive alcohol consumption is one of the leading causes of preventable death in the United States. Approximately 14% of those who use alcohol meet criteria during their lifetime for alcohol dependence, which is characterized by tolerance, withdrawal, inability to stop drinking, and continued drinking despite serious psychological or physiological problems. We explored genetic influences on alcohol dependence among 1,897 European-American and African-American subjects with alcohol dependence compared with 1,932 unrelated, alcohol-exposed, nondependent controls. Constitutional DNA of each subject was genotyped using the Illumina 1M beadchip. Fifteen SNPs yielded P < 10 −5 , but in two independent replication series, no SNP passed a replication threshold of P < 0.05. Candidate gene GABRA2 , which encodes the GABA receptor α2 subunit, was evaluated independently. Five SNPs at GABRA2 yielded nominal (uncorrected) P < 0.05, with odds ratios between 1.11 and 1.16. Further dissection of the alcoholism phenotype, to disentangle the influence of comorbid substance-use disorders, will be a next step in identifying genetic variants associated with alcohol dependence.

Genome-wide association studies (GWAS) have emerged as powerful means for identifying genetic loci related to complex diseases. However, the role of environment and its potential to interact with key loci has not been adequately addressed in most GWAS. Networks of collaborative studies involving different study populations and multiple phenotypes provide a powerful approach for addressing the challenges in analysis and interpretation shared across studies. The Gene, Environment Association Studies (GENEVA) consortium was initiated to: identify genetic variants related to complex diseases; identify variations in gene-trait associations related to environmental exposures; and ensure rapid sharing of data through the database of Genotypes and Phenotypes. GENEVA consists of several academic institutions, including a coordinating center, two genotyping centers and 14 independently designed studies of various phenotypes, as well as several Institutes and Centers of the National Institutes of Health led by the National Human Genome Research Institute. Minimum detectable effect sizes include relative risks ranging from 1.24 to 1.57 and proportions of variance explained ranging from 0.0097 to 0.02. Given the large number of research participants (N > 80,000), an important feature of GENEVA is harmonization of common variables, which allow analyses of additional traits. Environmental exposure information available from most studies also enables testing of gene-environment interactions. Facilitated by its sizeable infrastructure for promoting collaboration, GENEVA has established a unified framework for genotyping, data quality control, analysis and interpretation. By maximizing knowledge obtained through collaborative GWAS incorporating environmental exposure information, GENEVA aims to enhance our understanding of disease etiology, potentially identifying opportunities for intervention.

Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types, genotyping 515,922 single-nucleotide polymorphisms (SNPs) in 5739 lung cancer cases and 5848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from ten additional studies, for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication, resulting in 3333 adenocarcinomas (AD), 2589 squamous cell carcinomas (SQ), and 1418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT), on chromosome 5p15.33, was associated with risk of adenocarcinoma (odds ratio [OR] = 1.23, 95% confidence interval [CI] = 1.13–1.33, p = 3.02 × 10−7), but not with other histologic types (OR = 1.01, p = 0.84 and OR = 1.00, p = 0.93 for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR = 1.24, 95% CI = 1.17–1.31, p = 3.74 × 10−14 for AD; OR = 0.99, p = 0.69 and OR = 0.97, p = 0.48 for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma.

Cleft palate (CP) is a common birth defect occurring in 1 in 2,500 live births. Approximately half of infants with CP have a syndromic form, exhibiting other physical and cognitive disabilities. The other half have nonsyndromic CP, and to date, few genes associated with risk for nonsyndromic CP have been characterized. To identify such risk factors, we performed a genome-wide association study of this disorder. We discovered a genome-wide significant association with a missense variant in GRHL3 (p.Thr454Met [c.1361C>T]; rs41268753; p = 4.08 × 10(-9)) and replicated the result in an independent sample of case and control subjects. In both the discovery and replication samples, rs41268753 conferred increased risk for CP (OR = 8.3, 95% CI 4.1-16.8; OR = 2.16, 95% CI 1.43-3.27, respectively). In luciferase transactivation assays, p.Thr454Met had about one-third of the activity of wild-type GRHL3, and in zebrafish embryos, perturbed periderm development. We conclude that this mutation is an etiologic variant for nonsyndromic CP and is one of few functional variants identified to date for nonsyndromic orofacial clefting. This finding advances our understanding of the genetic basis of craniofacial development and might ultimately lead to improvements in recurrence risk prediction, treatment, and prognosis. Cleft palate (CP) is a common birth defect occurring in 1 in 2,500 live births. Approximately half of infants with CP have a syndromic form, exhibiting other physical and cognitive disabilities. The other half have nonsyndromic CP, and to date, few genes associated with risk for nonsyndromic CP have been characterized. To identify such risk factors, we performed a genome-wide association study of this disorder. We discovered a genome-wide significant association with a missense variant in GRHL3 (p.Thr454Met [c.1361C>T]; rs41268753; p = 4.08 × 10(-9)) and replicated the result in an independent sample of case and control subjects. In both the discovery and replication samples, rs41268753 conferred increased risk for CP (OR = 8.3, 95% CI 4.1-16.8; OR = 2.16, 95% CI 1.43-3.27, respectively). In luciferase transactivation assays, p.Thr454Met had about one-third of the activity of wild-type GRHL3, and in zebrafish embryos, perturbed periderm development. We conclude that this mutation is an etiologic variant for nonsyndromic CP and is one of few functional variants identified to date for nonsyndromic orofacial clefting. This finding advances our understanding of the genetic basis of craniofacial development and might ultimately lead to improvements in recurrence risk prediction, treatment, and prognosis.

More than 120 published reports have described associations between single nucleotide polymorphisms (SNPs) and type 2 diabetes. However, multiple studies of the same variant have often been discordant. From a literature search, we identified previously reported type 2 diabetes–associated SNPs. We initially genotyped 134 SNPs on 786 index case subjects from type 2 diabetes families and 617 control subjects with normal glucose tolerance from Finland and excluded from analysis 20 SNPs in strong linkage disequilibrium (r2 > 0.8) with another typed SNP. Of the 114 SNPs examined, we followed up the 20 most significant SNPs (P < 0.10) on an additional 384 case subjects and 366 control subjects from a population-based study in Finland. In the combined data, we replicated association (P < 0.05) for 12 SNPs: PPARG Pro12Ala and His447, KCNJ11 Glu23Lys and rs5210, TNF −857, SLC2A2 Ile110Thr, HNF1A/TCF1 rs2701175 and GE117881_360, PCK1 −232, NEUROD1 Thr45Ala, IL6 −598, and ENPP1 Lys121Gln. The replication of 12 SNPs of 114 tested was significantly greater than expected by chance under the null hypothesis of no association (P = 0.012). We observed that SNPs from genes that had three or more previous reports of association were significantly more likely to be replicated in our sample (P = 0.03), although we also replicated 4 of 58 SNPs from genes that had only one previous report of association.

Background In an effort to return actionable results from variant data to electronic health records (EHRs), participants in the Electronic Medical Records and Genomics (eMERGE) Network are being sequenced with the targeted Pharmacogenomics Research Network sequence platform (PGRNseq). This cost-effective, highly-scalable, and highly-accurate platform was created to explore rare variation in 84 key pharmacogenetic genes with strong drug phenotype associations. Methods To return Clinical Laboratory Improvement Amendments (CLIA) results to our participants at the Group Health Cooperative, we sequenced the DNA of 900 participants (61 % female) with non-CLIA biobanked samples. We then selected 450 of those to be re-consented, to redraw blood, and ultimately to validate CLIA variants in anticipation of returning the results to the participant and EHR. These 450 were selected using an algorithm we designed to harness data from self-reported race, diagnosis and procedure codes, medical notes, laboratory results, and variant-level bioinformatics to ensure selection of an informative sample. We annotated the multi-sample variant call format by a combination of SeattleSeq and SnpEff tools, with additional custom variables including evidence from ClinVar, OMIM, HGMD, and prior clinical associations. Results We focused our analyses on 27 actionable genes, largely driven by the Clinical Pharmacogenetics Implementation Consortium. We derived a ranking system based on the total number of coding variants per participant (75.2±14.7), and the number of coding variants with high or moderate impact (11.5±3.9). Notably, we identified 11 stop-gained (1 %) and 519 missense (20 %) variants out of a total of 1785 in these 27 genes. Finally, we prioritized variants to be returned to the EHR with prior clinical evidence of pathogenicity or annotated as stop-gain for the following genes: CACNA1S and RYR1 (malignant hyperthermia); SCN5A, KCNH2, and RYR2 (arrhythmia); and LDLR (high cholesterol). Conclusions The incorporation of genetics into the EHR for clinical decision support is a complex undertaking for many reasons including lack of prior consent for return of results, lack of biospecimens collected in a CLIA environment, and EHR integration. Our study design accounts for these hurdles and is an example of a pilot system that can be utilized before expanding to an entire health system. Electronic supplementary material The online version of this article (doi:10.1186/s13073-015-0181-z) contains supplementary material, which is available to authorized users.

Genetic risk factors for intracranial aneurysm (IA) are not yet fully understood. Genomewide association studies have been successful at identifying common variants; however, the role of rare variation in IA susceptibility has not been fully explored. In this study, we report the use of whole exome sequencing (WES) in seven densely-affected families (45 individuals) recruited as part of the Familial Intracranial Aneurysm study. WES variants were prioritized by functional prediction, frequency, predicted pathogenicity, and segregation within families. Using these criteria, 68 variants in 68 genes were prioritized across the seven families. Of the genes that were expressed in IA tissue, one gene (TMEM132B) was differentially expressed in aneurysmal samples (n=44) as compared to control samples (n=16) (false discovery rate adjusted p-value=0.023). We demonstrate that sequencing of densely affected families permits exploration of the role of rare variants in a relatively common disease such as IA, although there are important study design considerations for applying sequencing to complex disorders. In this study, we explore methods of WES variant prioritization, including the incorporation of unaffected individuals, multipoint linkage analysis, biological pathway information, and transcriptome profiling. Further studies are needed to validate and characterize the set of variants and genes identified in this study.

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population. Some individuals, studies, and centers received individual support. The grant numbers are: Addiction (U01HG004422, NIAAA: U10AA008401, NCI: P01CA089392, NIDA: R01DA013423, R01DA019963); Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (U.S. Public Health Service contracts: N01-CN-45165, N01-RC-45035, N01-RC-37004, NCI contract: HHSN261201000006C); Birth weight (U01HG004415); Blood clotting (R37 HL 039693); Broad Center for Genotyping and Analysis (U01HG04424); Cancer Prevention Study-II (American Cancer Society); Center for Inherited Disease Research (U01HG004438, HHSN268200782096C); Cleft lip/palate (NIDCR: U01DE018993 and R01DE016148, NIH contract: HHSN268200782096C); Dental Caries (NIDCR:U01DE018903 and R01DE014899, NIH CIDR contract: HHSN268200-782096C); Endometrial cancer (R01 CA134958); Fudan Lung Cancer Study (Ministry of Health (201002007); Ministry of Science and Technology (2011BAI09B00); National S&T Major Special Project (2011ZX09102-010-01); China National High-Tech Research and Development Program (2012AA02A517, 2012AA02A518); National Science Foundation of China (30890034); National Basic Research Program (2012CB944600); Scientific and Technological Support Plans from Jiangsu Province (BE2010715)); Gene-Environment Association Studies (Coordinating Center :U01 HG004446, Manuscript preparation: P01-GM099568); Genes and Environment in Lung Cancer, Singapore Study (National Medical Research Council Singapore grant (NMRC/0897/2004, NMRC/1075/2006); Agency for Science, Technology and Research (A*STAR) of Singapore); Genetic Epidemiological Study of Lung Adenocarcinoma (National Research Program on Genomic Medicine in Taiwan (DOH98-TD-G-111-015); National Research Program for Biopharmaceuticals in Taiwan (DOH 100-TD-PB-111-TM013); National Science Council,Taiwan (NSC 100-2319-B-400-001)); Glaucoma (NHGRI: U01HG004728, NEI: R01EY015473, NEI: R01EY015872, Harvard Medical School Distinguished Ophthalmology Scholar Award: Louis Pasquale); Guangdong Study (Foundation of Guangdong Science and Technology Department (2006B60101010, 2007A032000002, 2011A030400010); Guangzhou Science and Information Technology Bureau (2011Y2-00014); Chinese Lung Cancer Research Foundation; National Natural Science Foundation of China (81101549); Natural Science Foundation of Guangdong Province (S2011010000792)); Health Professionals Follow-up Study (UM1 CA167552, R01 HL35464); Hong Kong Study (General Research Fund of Research Grant Council, Hong Kong (781511M)); Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH; Intramural Research Program of the NIH, National Library of Medicine; Intramural Research Program of the National Institute for Occupational Safety and Health; Japanese Female Lung Cancer Collaborative Study (Grants-in-Aid from the Ministry of Health, Labor, and Welfare for Research on Applying Health Technology and for the 3rd-term Comprehensive 10-year Strategy for Cancer Control; National Cancer Center Research and Development Fund; Grant-in-Aid for Scientific Research on Priority Areas and on Innovative Area from the Ministry of Education, Science, Sports, Culture and Technology of Japan; NCI (R01-CA121210)); Lung cancer (Z01CP010200); Lung health (U01HG004738); Ministry of Health (201002007); Ministry of Science and Technology (2011BAI09B00); Melanoma (NCI R29CA70334, R01CA100264, P50CA093459); NLCS (China National High-Tech Research and Development Program Grant (2009AA022705); Priority Academic Program Development of Jiangsu Higher Education Institution; National Key Basic Research Program Grant (2011CB503805)); Nurses’ Health Study (P01 CA87969, R01 CA49449); Nurses’ Health Study II (UM1 CA176726, R01, 67262); OpPancreatic cancer (Mayo Clinic SPORE in Pancreatic Cancer: P50CA102701); Prematurity (U01HG004423); Prostate cancer (U01HG004726, NCI: CA63464, CA54281, CA1326792, RC2 CA148085); Shanghai Women’s Health Cohort Study (National Institutes of Health (R37 CA70867); National Cancer Institute intramural research program; NCI Intramural Research Program contract (N02 CP1101066)); Shenyang Lung Cancer Study (National Nature Science Foundation of China (81102194); Liaoning Provincial Department of Education (LS2010168); China Medical Board (00726)); Singapore Chinese Health Study (NIH grants: NCI R01 CA55069, R35 CA53890, R01 CA80205, and R01 CA144034); South Korea Multi-Center Lung Cancer Study (National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (2011-0016106); National R&D Program for Cancer Control, Ministry of Health &Welfare, Republic of Korea (0720550-2); (A010250)); Tianjin Lung Cancer Study (Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT); China (IRT1076), Tianjin Cancer Institute and Hospital, National Foundation for Cancer Research US); Venous thromboembolism (U01HG004735); Wuhan lung cancer study (National Key Basic Research and Development Program (2011CB503800)) and Yunnan Lung Cancer Study (Intramural program of U.S. National Institutes of Health; National Cancer Institute). Additionally, K.C.B. was supported in part by the Mary Beryl Patch Turnbull Scholar Program. The GENEVA consortium thanks the participants and the staff of all GENEVA studies for their important contributions. Support for the GENEVA genome-wide association studies was provided through the NIH Genes, Environment and Health Initiative (GEI).

The pattern and nature of linkage disequilibrium in the human genome is being studied and catalogued as part of the International HapMap Project [:2003 Nature 426:789-796]. A key goal of the HapMap Project is to enable identification of tag single nucleotide polymorphisms (SNPs) that capture a substantial portion of common human genetic variability while requiring only a small fraction of SNPs to be genotyped [International HapMap Consortium, 2005: Nature 437:1299-1320]. In the current study, we examined the effectiveness of using the CEU HapMap database to select tag SNPs for a Finnish sample. We selected SNPs in a 17.9-Mb region of chromosome 14 based on pairwise linkage disequilibrium (r(2)) estimates from the HapMap CEU sample, and genotyped 956 of these SNPs in 1,425 Finnish individuals. An excess of SNPs showed significantly different allele frequencies between the HapMap CEU and the Finnish samples, consistent with population-specific differences. However, we observed strong correlations between the two samples for estimates of allele frequencies, r(2) values, and haplotype frequencies. Our results demonstrate that the HapMap CEU samples provide an adequate basis for tag SNP selection in Finnish individuals, without the need to create a map specifically for the Finnish population, and suggest that the four-population HapMap data will provide useful information for tag SNP selection beyond the specific populations from which they were sampled.

We have designed and utilized two in vivo assays of kinetochore integrity in S. cerevisiae. One assay detects relaxation of a transcription block formed at centromeres; the other detects an increase in the mitotic stability of a dicentric test chromosome. ctf13-30 and ctf14-42 were identified as putative kinetochore mutants by both assays. CTF14 is identical to NDC10/CBF2, a recently identified essential gene that encodes a 110 kd kinetochore component. CTF13 is an essential gene that encodes a predicted 478 amino acid protein with no homology to known proteins. ctf13 mutants missegregate chromosomes at permissive temperature and transiently arrest at nonpermissive temperature as large-budded cells with a G2 DNA content and a short spindle. Antibodies recognizing epitope-tagged CTF13 protein decrease the electrophoretic mobility of a CEN DNA-protein complex formed in vitro. Together, the genetic and biochemical data indicate that CTF13 is an essential kinetochore protein.

The aim of the Finland-United States Investigation of NIDDM Genetics (FUSION) study is to identify genes that predispose to type 2 diabetes or are responsible for variability in diabetes-related traits via a positional cloning and positional candidate gene approach. In a previously published genome-wide scan of 478 Finnish affected sibling pair (ASP) families (FUSION 1), the strongest linkage results were on chromosomes 20 and 11. We now report a second genome-wide scan using an independent set of 242 Finnish ASP families (FUSION 2), a detailed analysis of the combined set of 737 FUSION 1 + 2 families (495 updated FUSION 1 families), and fine mapping of the regions of chromosomes 11 and 20. The strongest FUSION 2 linkage results were on chromosomes 6 (maximum logarithm of odds score [MLS] = 2.30 at 95 cM) and 14 (MLS = 1.80 at 57 cM). For the combined FUSION 1 + 2 families, three results were particularly notable: chromosome 11 (MLS = 2.98 at 82 cM), chromosome 14 (MLS = 2.74 at 58 cM), and chromosome 6 (MLS = 2.66 at 96 cM). We obtained smaller FUSION 1 + 2 MLSs on chromosomes X (MLS = 1.27 at 152 cM) and 20p (MLS = 1.21 at 20 cM). Among the 10 regions that showed nominally significant evidence for linkage in FUSION 1, four (on chromosomes 6, 11, 14, and X) also showed evidence for linkage in FUSION 2 and stronger evidence for linkage in the combined FUSION 1 + 2 sample.

Fifty percent of variability in HIV-1 susceptibility is attributable to host genetics. Thus identifying genetic associations is essential to understanding pathogenesis of HIV-1 and important for targeting drug development. To date, however, CCR5 remains the only gene conclusively associated with HIV acquisition. To identify novel host genetic determinants of HIV-1 acquisition, we conducted a genome-wide association study among a high-risk sample of 3,136 injection drug users (IDUs) from the Urban Health Study (UHS). In addition to being IDUs, HIV-controls were frequency-matched to cases on environmental exposures to enhance detection of genetic effects. We tested independent replication in the Women's Interagency HIV Study (N=2,533). We also examined publicly available gene expression data to link SNPs associated with HIV acquisition to known mechanisms affecting HIV replication/infectivity. Analysis of the UHS nominated eight genetic regions for replication testing. SNP rs4878712 in FRMPD1 met multiple testing correction for independent replication (P=1.38x10(-4)), although the UHS-WIHS meta-analysis p-value did not reach genome-wide significance (P=4.47x10(-7) vs. P

International audience; Importance: Microphthalmias are rare disorders whose genetic bases are not fully understood. HMGB3 is a new candidate gene for X-linked forms of this disease.Objective: To identify the causative gene in a pedigree with an X-linked colobomatous microphthalmos phenotype. Design, setting, and participants: Whole-genome sequencing and chromosome X-exome-targeted sequencing were performed at the High Throughput Sequencing Laboratory of the Genetic Resources Core Facility at the Johns Hopkins University School of Medicine on the DNA of the male proband and informatically filtered to identify rare variants. Polymerase chain reaction and Sanger sequencing were used to confirm the variant in the proband and the carrier status of his mother. Thirteen unrelated male patients with a similar phenotype were also screened. Main outcomes and measures: Whole-genome and X-exome sequencing to identify a frameshift variant in HMGB3. Results: A 2-base pair frameshift insertion (c.477_478insTA, coding for p.Lys161Ilefs*54) in the HGMB3 gene was found in the proband and his carrier mother but not in the unrelated patients. The mutation, confirmed by 3 orthogonal methods, alters an evolutionarily conserved region of the HMGB3 protein from a negatively charged polyglutamic acid tract to a positively charged arginine-rich motif that is likely to interfere with normal protein function. Conclusions and relevance: In this family, microphthalmia, microcephaly, intellectual disability, and short stature are associated with a mutation on the X chromosome in the HMGB3 gene. HMGB3 should be considered when performing genetic studies of patients with similar phenotype

In March 2013 the American College of Medical Genetics and Genomics published a list of 56 genes with the recommendation that pathogenic and likely pathogenic variants detected incidentally by clinical sequencing be reported to patients. As an initial step in determining the practical consequences of this recommendation in the research setting, we searched for variants in these genes in 232 whole-exome sequences from the Baylor-Hopkins Center for Mendelian Genomics.We identified rare, nonsynonymous, and splicing single-nucleotide variants and insertions/deletions and assessed variant classification using the Human Gene Mutation, Emory, and ClinVar databases. We analyzed the burden of mutation in each of the 56 genes and determined which variants should be reported to patients.Our filtering resulted in 249 distinct variants, with a mean of 1.69 variants per individual. Half of these were novel missense mutations not classified by any of the three reference databases. Of 101 variants listed in the Human Gene Mutation Database, 48 were also in ClinVar and 3 were also in Emory; half of these shared variants were classified discordantly between databases. Some genes consistently had greater variation than others. In total, 0.86% of individuals had a reportable incidental variant.These observations demonstrate some current challenges of assessing phenotypic consequences of incidental variants for counseling patients.

Cardiomyocyte cell division and replication in mammals proceed through embryonic development and abruptly decline soon after birth. The process governing cardiomyocyte cell cycle arrest is poorly understood. Here we carry out whole exome sequencing in an infant with evidence of persistent postnatal cardiomyocyte replication to determine the genetic risk factors. We identify compound heterozygous ALMS1 mutations in the proband, and confirm their presence in her affected sibling, one copy inherited from each heterozygous parent. Next, we recognise homozygous or compound heterozygous truncating mutations in ALMS1 in four other children with high levels of postnatal cardiomyocyte proliferation. Alms1 mRNA knockdown increases multiple markers of proliferation in cardiomyocytes, the percentage of cardiomyocytes in G2/M phases, and the number of cardiomyocytes by 10% in cultured cells. Homozygous Alms1-mutant mice have increased cardiomyocyte proliferation at two weeks postnatal compared to wild-type littermates. We conclude that deficiency of Alström protein impairs postnatal cardiomyocyte cell cycle arrest.

Acrodermatitis enteropathica (AE) is a rare autosomal recessive pediatric disease characterized by dermatitis, diarrhea, alopecia, and growth failure. The disease results from insufficient uptake of zinc by the intestine and can be fatal unless the diet is supplemented with zinc. To map the gene responsible for AE, a genomewide screen was performed on 17 individuals, including 4 affected individuals, in a consanguineous Jordanian family. Three markers-D8S373, D10S212, and D6S1021-had a pattern consistent with tight linkage to a recessive disease: one allele in the affected sibs and multiple alleles in unaffected sibs and parents. Two-point parametric linkage analysis using FASTLINK identified one region, D8S373, with a maximum LOD score1.5 (1.94 at D8S373: recombination fraction.001). Twelve additional markers flanking D8S373 were used to genotype the extended family, to fine-map the AE gene. All five affected individuals-including one who was not genotyped in the genomewide screen-were found to be homozygous for a common haplotype, spanning approximately 3.5 cM, defined by markers D8S1713 and D8S2334 on chromosomal region 8q24.3. To support these mapping data, seven consanguineous Egyptian families with eight patients with AE were genotyped using these markers, and six patients from five families were found to be homozygous in this region. Multipoint analysis with all consanguineous families, by Mapmaker/Homoz, resulted in a maximum LOD score of 3.89 between D8S1713 and D8S373. Sliding three-point analysis resulted in a maximum LOD score of 5.16 between markers D8S1727 and D8S1744.

An interchromosomal insertion in 3 generations of a family was ascertained through two developmentally delayed first cousins. Cytogenetic analysis using G-banding and chromosome painting showed an apparently balanced direct insertion of chromosome 10 material into chromosome 12, ins(12;10)(q15;q21.2q22.1), in the mothers and grandfather of these children. The proposita inherited only the derivative 10 chromosome, resulting in deletion of 10q21.2 --> 22.1 while her cousin inherited only the derivative 12, resulting in duplication of 10q21.2 --> 22.1. A comparison of the proposita with published deletion cases suggests a pattern of anomalies attributable to deletion of the 10q21 --> q22 region: developmental delay, hypotonia, a heart murmur, telecanthus, broad nasal root and ear abnormalities. This is the first report of a nontandem duplication of the 10q21 --> q22 region. The phenotype of the cousin with the duplication does not overlap greatly with published tandem 10q duplications. Finally, this report reaffirms the importance of obtaining family studies of patients with interstitial chromosomal abnormalities.

In oocytes with nondisjoined chromosomes 21 due to a meiosis I (MI) error, recombination is significantly reduced along chromosome 21; several lines of evidence indicate that this contributes to the nondisjunction event. A pilot study found evidence that these oocytes also have reduced recombination genome-wide when compared with controls. This suggests that factors that act globally may be contributing to the reduced recombination on chromosome 21, and hence, the nondisjunction event. To identify the source of these factors, we examined two levels of recombination count regulation in oocytes: (i) regulation at the maternal level that leads to correlation in genome-wide recombination across her oocytes and (ii) regulation at the oocyte level that leads to correlation in recombination count among the chromosomes of an oocyte. We sought to determine whether either of these properties was altered in oocytes with an MI error. As it relates to maternal regulation, we found that both oocytes with an MI error (N = 94) and their siblings (N = 64) had reduced recombination when compared with controls (N = 2723). At the oocyte level, we found that the correlation in recombination count among the chromosomes of an oocyte is reduced in oocytes with MI errors compared with that of their siblings or controls. These results suggest that regulation at the maternal level predisposes MI error oocytes to reduced levels of recombination, but additional oocyte-specific dysregulation contributes to the nondisjunction event.

The spondylometaphyseal dysplasias (SMDs) are a group of about a dozen rare disorders characterized by short stature, irregular, flat vertebrae, and metaphyseal abnormalities. Aside from spondylometaphyseal dysplasia Kozlowski type (MIM 184252) caused by mutations in TRPV4 (MIM 605427) and spondyloenchondrodysplasia (MIM 607944) resulting from mutations in ACP5 (MIM 171640), the genetic etiologies of SMDs are unknown. 1 Two of these unexplained SMDs have ophthalmologic manifestations: SMD with cone-rod dystrophy (SMD-CRD [MIM 608940]) and axial SMD with retinal degeneration (MIM 602271). Delineated clinically a decade ago, SMD-CRD is a presumed autosomal-recessive disorder with postnatal growth deficiency leading to profound short stature; rhizomelia with bowing of the lower extremities; platyspondyly with anterior vertebral protrusions; progressive metaphyseal irregularity and cupping with shortened tubular bones; and early-onset, progressive visual impairment associated with a pigmentary maculopathy and electroretinographic evidence of cone-rod dysfunction. 2‐5 In contrast to retinitis pigmentosa, the CRDs have early involvement of cone photoreceptors. 6