Medicine and Health Sciences Commons^™

Phenotype-Aware Prioritisation Of Rare Mendelian Disease Variants., Catherine Kelly, Anita Szabo, Nikolas Pontikos, Gavin Arno, Peter N Robinson, Jules O B Jacobsen, Damian Smedley, Valentina Cipriani

Faculty Research 2022

A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, …

Leveraging Pleiotropy To Discover And Interpret Gwas Results For Sleep-Associated Traits, Sung Chun, Sebastian Akle, Athanasios Teodosiadis, Brian E Cade, Heming Wang, Tamar Sofer, Daniel S Evans, Katie L Stone, Sina A Gharib, Sutapa Mukherjee, Lyle J Palmer, David Hillman, Jerome I Rotter, Craig L Hanis, John A Stamatoyannopoulos, Susan Redline, Chris Cotsapas, Shamil R Sunyaev

Journal Articles

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations …

A Framework For Detecting Noncoding Rare-Variant Associations Of Large-Scale Whole-Genome Sequencing Studies, Zilin Li, Xihao Li, Hufeng Zhou, Sheila M Gaynor, Margaret Sunitha Selvaraj, Theodore Arapoglou, Corbin Quick, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K Arnett, Paul L Auer, Lawrence F Bielak, Joshua C Bis, Thomas W Blackwell, John Blangero, Eric Boerwinkle, Donald W Bowden, Jennifer A Brody, Brian E Cade, Matthew P Conomos, Adolfo Correa, L Adrienne Cupples, Joanne E Curran, Paul S De Vries, Ravindranath Duggirala, Nora Franceschini, Barry I Freedman, Harald H H Göring, Xiuqing Guo, Rita R Kalyani, Charles Kooperberg, Brian G Kral, Leslie A Lange, Bridget M Lin, Ani Manichaikul, Alisa K Manning, Lisa W Martin, Rasika A Mathias, James B Meigs, Braxton D Mitchell, May E Montasser, Alanna C Morrison, Take Naseri, Jeffrey R O'Connell, Nicholette D Palmer, Patricia A Peyser, Bruce M Psaty, Laura M Raffield, Susan Redline, Alexander P Reiner, Muagututi'a Sefuiva Reupena, Kenneth M Rice, Stephen S Rich, Jennifer A Smith, Kent D Taylor, Margaret A Taub, Ramachandran S Vasan, Daniel E Weeks, James G Wilson, Lisa R Yanek, Wei Zhao, Jerome I Rotter, Cristen J Willer, Pradeep Natarajan, Gina M Peloso, Xihong Lin

Journal Articles

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate …

Adding Gene Transcripts Into Genomic Prediction Improves Accuracy And Reveals Sampling Time Dependence., Bruno C Perez, Marco C A M Bink, Karen L. Svenson, Gary Churchill, Mario P L Calus

Faculty Research 2022

Recent developments allowed generating multiple high-quality 'omics' data that could increase the predictive performance of genomic prediction for phenotypes and genetic merit in animals and plants. Here, we have assessed the performance of parametric and nonparametric models that leverage transcriptomics in genomic prediction for 13 complex traits recorded in 478 animals from an outbred mouse population. Parametric models were implemented using the best linear unbiased prediction, while nonparametric models were implemented using the gradient boosting machine algorithm. We also propose a new model named GTCBLUP that aims to remove between-omics-layer covariance from predictors, whereas its counterpart GTBLUP does not do …

[Rare-Disease Data Standards]., Peter N Robinson, Holm Graessner

Faculty Research 2022

The use of standardized data formats (data standards) in healthcare supports four main goals: (1) exchange of data, (2) integration of computer systems and tools, (3) data storage and archiving, and (4) support of federated databases. Standards are especially important for rare-disease research and clinical care.In this review, we introduce healthcare standards and present a selection of standards that are commonly used in the field of rare diseases. The Human Phenotype Ontology (HPO) is the most commonly used standard for annotating phenotypic abnormalities and supporting phenotype-driven analysis of diagnostic exome and genome sequencing. Numerous standards for diseases are available that …

Mendelian Gene Identification Through Mouse Embryo Viability Screening., Pilar Cacheiro, Carl Henrik Westerberg, Jesse Mager, Mary E Dickinson, Lauryl M J Nutter, Violeta Muñoz-Fuentes, Chih-Wei Hsu, Ignatia B Van Den Veyver, Ann M Flenniken, Colin Mckerlie, Stephen A Murray, Lydia Teboul, Jason D Heaney, K C Kent Lloyd, Louise Lanoue, Robert E Braun, Jacqueline K White, Amie K Creighton, Valerie Laurin, Ruolin Guo, Dawei Qu, Sara Wells, James Cleak, Rosie Bunton-Stasyshyn, Michelle Stewart, Jackie Harrisson, Jeremy Mason, Hamed Haseli Mashhadi, Helen Parkinson, Ann-Marie Mallon, International Mouse Phenotyping Consortium, Genomics England Research Consortium, Damian Smedley

Faculty Research 2022

BACKGROUND: The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS: Here we further dissected this spectrum by assessing the embryonic stage at which homozygous …

Leveraging Family History In Genetic Association Analyses Of Binary Traits, Yixin Zhang, James B Meigs, Ching-Ti Liu, Josée Dupuis, Chloé Sarnowski

Journal Articles

BACKGROUND: Considering relatives' health history in logistic regression for case-control genome-wide association studies (CC-GWAS) may provide new information that increases accuracy and power to detect disease associated genetic variants. We conducted simulations and analyzed type 2 diabetes (T2D) data from the Framingham Heart Study (FHS) to compare two methods, liability threshold model conditional on both case-control status and family history (LT-FH) and Fam-meta, which incorporate family history into CC-GWAS.

RESULTS: In our simulation scenario of trait with modest T2D heritability (h

CONCLUSIONS: Overall, LT-FH and Fam-meta had higher power than CC-GWAS in simulations, especially using phenotypes that were more prevalent …

Lesion Environments Direct Transplanted Neural Progenitors Towards A Wound Repair Astroglial Phenotype In Mice., T M O'Shea, Y Ao, S Wang, A L Wollenberg, J H Kim, R A Ramos Espinoza, Anne M. Czechanski, Laura G. Reinholdt, T J Deming, M V Sofroniew

Faculty Research 2022

Neural progenitor cells (NPC) represent potential cell transplantation therapies for CNS injuries. To understand how lesion environments influence transplanted NPC fate in vivo, we derived NPC expressing a ribosomal protein-hemagglutinin tag (RiboTag) for transcriptional profiling of transplanted NPC. Here, we show that NPC grafted into uninjured mouse CNS generate cells that are transcriptionally similar to healthy astrocytes and oligodendrocyte lineages. In striking contrast, NPC transplanted into subacute CNS lesions after stroke or spinal cord injury in mice generate cells that share transcriptional, morphological and functional features with newly proliferated host astroglia that restrict inflammation and fibrosis and isolate lesions from …

Evaluation Of Phenotype-Driven Gene Prioritization Methods For Mendelian Diseases., Julius O B Jacobsen, Catherine Kelly, Valentina Cipriani, Peter N Robinson, Damian Smedley

Faculty Research 2022

Yuan et al. recently described an independent evaluation of several phenotype-driven gene prioritization methods for Mendelian disease on two separate, clinical datasets. Although they attempted to use default settings for each tool, we describe three key differences from those we currently recommend for our Exomiser and PhenIX tools. These influence how variant frequency, quality and predicted pathogenicity are used for filtering and prioritization. We propose that these differences account for much of the discrepancy in performance between that reported by them (15-26% diagnoses ranked top by Exomiser) and previously published reports by us and others (72-77%). On a set of …

Phenotype-Driven Approaches To Enhance Variant Prioritization And Diagnosis Of Rare Disease., Julius O B Jacobsen, Catherine Kelly, Valentina Cipriani, Genomics England Research Consortium, Christopher J Mungall, Justin Reese, Daniel Danis, Peter N Robinson, Damian Smedley

Faculty Research 2022

Rare disease diagnostics and disease gene discovery have been revolutionized by whole-exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. The use of deep phenotyping of patients and reference genotype-phenotype knowledge, alongside variant data such as allele frequency, segregation, and predicted pathogenicity, has proved an effective strategy to tackle this issue. Here we review the numerous tools that have been developed to automate this approach and demonstrate the power of such an approach on several thousand diagnosed cases from the 100,000 Genomes Project. Finally, we discuss the challenges that need to be …

The Rd-Connect Genome-Phenome Analysis Platform: Accelerating Diagnosis, Research, And Gene Discovery For Rare Diseases., Steven Laurie, Davide Piscia, Leslie Matalonga, Alberto Corvó, Marcos Fernández-Callejo, Carles Garcia-Linares, Carles Hernandez-Ferrer, Cristina Luengo, Inés Martínez, Anastasios Papakonstantinou, Daniel Picó-Amador, Joan Protasio, Rachel Thompson, Raul Tonda, Mònica Bayés, Gemma Bullich, Jordi Camps-Puchadas, Ida Paramonov, Jean-Rémi Trotta, Angel Alonso, Marcella Attimonelli, Christophe Béroud, Virginie Bros-Facer, Orion J Buske, Andrés Cañada-Pallarés, José M Fernández, Mats G Hansson, Rita Horvath, Julius O B Jacobsen, Rajaram Kaliyaperumal, Séverine Lair-Préterre, Luana Licata, Pedro Lopes, Estrella López-Martín, Deborah Mascalzoni, Lucia Monaco, Luis A Pérez-Jurado, Manuel Posada De La Paz, Jordi Rambla, Ana Rath, Olaf Riess, Peter N Robinson, David Salgado, Damian Smedley, Dylan Spalding, Peter A C 'T Hoen, Ana Töpf, Irina Zaharieva, Holm Graessner, Ivo G Gut, Hanns Lochmüller, Sergi Beltran

Faculty Research 2022

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is …

Prenatal Phenotyping: A Community Effort To Enhance The Human Phenotype Ontology., Ferdinand Dhombres, Patricia Morgan, Bimal P Chaudhari, Isabel Filges, Teresa N Sparks, Pablo Lapunzina, Tony Roscioli, Umber Agarwal, Shagun Aggarwal, Claire Beneteau, Pilar Cacheiro, Leigh Carmody, Sophie Collardeau-Frachon, Esther A Dempsey, Andreas Dufke, Michael Henri Duyzend, Mirna El Ghosh, Jessica L Giordano, Ragnhild Glad, Ieva Grinfelde, Dominic G Iliescu, Markus S Ladewig, Monica C Munoz-Torres, Marzia Pollazzon, Francesca Clementina Radio, Carlota Rodo, Raquel Gouveia Silva, Damian Smedley, Jagadish Chandrabose Sundaramurthi, Sabrina Toro, Irene Valenzuela, Nicole A Vasilevsky, Ronald J Wapner, Roni Zemet, Melissa A Haendel, Peter N Robinson

Faculty Research 2022

Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype-driven early genetic diagnosis of fetal genetic disease can help to strategize treatment options and clinical preventive measures during the perinatal period, to plan in utero therapies, and to inform parental decision-making. Fetal phenotypes of genetic diseases are often unique and at present are not well understood; more comprehensive knowledge about prenatal phenotypes and computational resources have an enormous potential to improve diagnostics and translational research. The Human Phenotype Ontology (HPO) has been widely used to support diagnostics and …

Transcriptional Profiling Of Macrophages In Situ In Metastatic Melanoma Reveals Localization-Dependent Phenotypes And Function., Jan Martinek, Jianan Lin, Kyung In Kim, Victor G Wang, Te-Chia Wu, Michael Chiorazzi, Hannah Boruchov, Ananya Gulati, Shamreethaa Seeniraj, Lili Sun, Florentina Marches, Paul Robson, Anthony Rongvaux, Richard A Flavell, Joshy George, Jeffrey Chuang, Jacques Banchereau, Karolina Palucka

Faculty Research 2022

Modulation of immune function at the tumor site could improve patient outcomes. Here, we analyze patient samples of metastatic melanoma, a tumor responsive to T cell-based therapies, and find that tumor-infiltrating T cells are primarily juxtaposed to CD14⁺ monocytes/macrophages rather than melanoma cells. Using immunofluorescence-guided laser capture microdissection, we analyze transcriptomes of CD3⁺ T cells, CD14 ⁺ monocytes/macrophages, and melanoma cells in non-dissociated tissue. Stromal CD14⁺ cells display a specific transcriptional signature distinct from CD14⁺ cells within tumor nests. This signature contains LY75, a gene linked with antigen capture and regulation of tolerance and immunity in …

A Bayesian Model Selection Approach To Mediation Analysis., Wesley L Crouse, Gregory R Keele, Madeleine S Gastonguay, Gary Churchill, William Valdar

Faculty Research 2022

Genetic studies often seek to establish a causal chain of events originating from genetic variation through to molecular and clinical phenotypes. When multiple phenotypes share a common genetic association, one phenotype may act as an intermediate for the genetic effects on the other. Alternatively, the phenotypes may be causally unrelated but share genetic loci. Mediation analysis represents a class of causal inference approaches used to determine which of these scenarios is most plausible. We have developed a general approach to mediation analysis based on Bayesian model selection and have implemented it in an R package, bmediatR. Bayesian model selection provides …

Prediction Performance Of Linear Models And Gradient Boosting Machine On Complex Phenotypes In Outbred Mice., Bruno C Perez, Marco C A M Bink, Karen L. Svenson, Gary Churchill, Mario P L Calus

Faculty Research 2022

We compared the performance of linear (GBLUP, BayesB, and elastic net) methods to a nonparametric tree-based ensemble (gradient boosting machine) method for genomic prediction of complex traits in mice. The dataset used contained genotypes for 50,112 SNP markers and phenotypes for 835 animals from 6 generations. Traits analyzed were bone mineral density, body weight at 10, 15, and 20 weeks, fat percentage, circulating cholesterol, glucose, insulin, triglycerides, and urine creatinine. The youngest generation was used as a validation subset, and predictions were based on all older generations. Model performance was evaluated by comparing predictions for animals in the validation subset …

Auriculocondylar Syndrome 2 Results From The Dominant-Negative Action Of Plcb4 Variants., Stanley M Kanai, Caleb Heffner, Timothy C Cox, Michael L Cunningham, Francisco A Perez, Aaron M Bauer, Philip Reigan, Cristan Carter, Stephen A. Murray, David E Clouthier

Faculty Research 2022

Auriculocondylar syndrome 2 (ARCND2) is a rare autosomal dominant craniofacial malformation syndrome linked to multiple genetic variants in the coding sequence of phospholipase C β4 (PLCB4). PLCB4 is a direct signaling effector of the endothelin receptor type A (EDNRA)-Gq/11 pathway, which establishes the identity of neural crest cells (NCCs) that form lower jaw and middle ear structures. However, the functional consequences of PLCB4 variants on EDNRA signaling is not known. Here, we show, using multiple signaling reporter assays, that known PLCB4 variants resulting from missense mutations exert a dominant-negative interference over EDNRA signaling. In addition, using CRISPR/Cas9, we find that …

Centers For Mendelian Genomics: A Decade Of Facilitating Gene Discovery, Samantha M Baxter, Jennifer E Posey, Nicole J Lake, Nara Sobreira, Jessica X Chong, Steven Buyske, Elizabeth E Blue, Lisa H Chadwick, Zeynep H Coban-Akdemir, Kimberly F Doheny, Colleen P Davis, Monkol Lek, Christopher Wellington, Shalini N Jhangiani, Mark Gerstein, Richard A Gibbs, Richard P Lifton, Daniel G Macarthur, Tara C Matise, James R Lupski, David Valle, Michael J Bamshad, Ada Hamosh, Shrikant Mane, Deborah A Nickerson, Heidi L Rehm, Anne O'Donnell-Luria

Journal Articles

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration.

METHODS: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution.

RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships …

Elucidating The Clinical Spectrum And Molecular Basis Of Hyal2 Deficiency, James Fasham, Siying Lin, Promita Ghosh, Francesca Clementina Radio, Emily G Farrow, Isabelle Thiffault, Jennifer Kussman, Dihong Zhou, Rick Hemming, Kenneth Zahka, Barry A Chioza, Lettie E Rawlins, Olivia K Wenger, Adam C Gunning, Simone Pizzi, Roberta Onesimo, Giuseppe Zampino, Emily Barker, Natasha Osawa, Megan Christine Rodriguez, Teresa M Neuhann, Elaine H Zackai, Beth Keena, Jenina Capasso, Alex V Levin, Elizabeth Bhoj, Dong Li, Hakon Hakonarson, Ingrid M Wentzensen, Adam Jackson, Kate E Chandler, Zeynep H Coban-Akdemir, Jennifer E Posey, Siddharth Banka, James R Lupski, Sarah E Sheppard, Marco Tartaglia, Barbara Triggs-Raine, Andrew H Crosby, Emma L Baple

Journal Articles

PURPOSE: We previously defined biallelic HYAL2 variants causing a novel disorder in 2 families, involving orofacial clefting, facial dysmorphism, congenital heart disease, and ocular abnormalities, with Hyal2 knockout mice displaying similar phenotypes. In this study, we better define the phenotype and pathologic disease mechanism.

METHODS: Clinical and genomic investigations were undertaken alongside molecular studies, including immunoblotting and immunofluorescence analyses of variant/wild-type human HYAL2 expressed in mouse fibroblasts, and in silico modeling of putative pathogenic variants.

RESULTS: Ten newly identified individuals with this condition were investigated, and they were associated with 9 novel pathogenic variants. Clinical studies defined genotype-phenotype correlations and …

Genetic Interaction Between Mfrp And Adipor1 Mutations Affect Retinal Disease Phenotypes, Navdeep Gogna, Sonia Weatherly, Fuxin Zhao, Gayle B. Collin, Jai Pinkney, Lisa Stone, Juergen K. Naggert, Gregory W. Carter, Patsy M. Nishina

Faculty Research 2022

Adipor1^tm1Dgen and Mfrp^rd6 mutant mice share similar eye disease characteristics. Previously, studies established a functional relationship of ADIPOR1 and MFRP proteins in maintaining retinal lipidome homeostasis and visual function. However, the independent and/or interactive contribution of both genes to similar disease phenotypes, including fundus spots, decreased axial length, and photoreceptor degeneration has yet to be examined. We performed a gene-interaction study where homozygous Adipor1^tm1Dgen and Mfrp^rd6 mice were bred together and the resulting doubly heterozygous F1 offspring were intercrossed to produce 210 F2 progeny. Four-month-old mice from all nine genotypic combinations obtained in the F2 generation …

Curation And Expansion Of Human Phenotype Ontology For Defined Groups Of Inborn Errors Of Immunity., Matthias Haimel, Julia Pazmandi, Raúl Jiménez Heredia, Jasmin Dmytrus, Sevgi Köstel Bal, Samaneh Zoghi, Paul Van Daele, Tracy A Briggs, Carine Wouters, Brigitte Bader-Meunier, Florence A Aeschlimann, Roberta Caorsi, Despina Eleftheriou, Esther Hoppenreijs, Elisabeth Salzer, Shahrzad Bakhtiar, Beata Derfalvi, Francesco Saettini, Maaike A A Kusters, Reem Elfeky, Johannes Trück, Jacques G Rivière, Mirjam Van Der Burg, Marco Gattorno, Markus G Seidel, Siobhan Burns, Klaus Warnatz, Fabian Hauck, Paul Brogan, Kimberly C Gilmour, Catharina Schuetz, Anna Simon, Christoph Bock, Sophie Hambleton, Esther De Vries, Peter N Robinson, Marielle Van Gijn, Kaan Boztug

Faculty Research 2022

BACKGROUND: Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchical structure. However, to date, the use of HPO has not yet been widely implemented in the field of inborn errors of immunity (IEIs), mainly due to a lack of comprehensive IEI-related terms.

OBJECTIVES: We sought to systematically review available terms in HPO for the depiction of IEIs, to expand HPO, yielding more comprehensive sets of …