Large-scale discovery of novel genetic causes of developmental disorders

The rapid automatized naming task (RAN) is a well-established tool to evaluate risk of developmental disorders. Its potential use with 3-year-olds who are at risk for learning difficulties and factors affecting its dependent measures are not yet understood. This study investigated the effects of neonatal central nervous system compromise grouping (five levels, N = 617) on RAN task adapted for 3-year-olds, using two levels of information load and two presentation orders. Results showed that increased errors and slowed speed in toddlers are expected subsequent to severe neonatal CNS compromise. Furthermore, collaborative information may have a beneficial effect on processing speeds of toddlers born with severe, but not with moderate, neonatal CNS compromise. Finally, the study highlights the feasability of evaluating RAN performance in toddlers who are at a developmental risk for learning disabilities and the conditions of RAN that may facilitate performance of severely affected participants.

Download Full-text

Genetic causes of developmental disorders

Current Opinion in Neurology ◽

10.1097/wco.0b013e32835f1a30 ◽

2013 ◽

Vol 26 (2) ◽

pp. 128-136 ◽

Cited By ~ 39

Author(s):

Jacob A.S. Vorstman ◽

Roel A. Ophoff

Keyword(s):

Developmental Disorders ◽

Genetic Causes

Download Full-text

Systematic assessment of outcomes following a genetic diagnosis identified through a large-scale research study into developmental disorders

Genetics in Medicine ◽

10.1038/s41436-021-01110-3 ◽

2021 ◽

Author(s):

H. Copeland ◽

E. Kivuva ◽

H. V. Firth ◽

C. F. Wright

Keyword(s):

Developmental Disorders ◽

Large Scale ◽

Genetic Diagnosis ◽

Specific Treatment ◽

Psychosocial Outcomes ◽

Patient Specific ◽

Emotional Impact ◽

Clinical Genetics ◽

Specific Information ◽

Disease Specific

Abstract Purpose The clinical and psychosocial outcomes associated with receiving a genetic diagnosis for developmental disorders are wide-ranging but under-studied. We sought to investigate outcomes from a subset of families who received a diagnosis through the Deciphering Developmental Disorders (DDD) study. Methods Individuals recruited through the Peninsula Clinical Genetics Service who received a confirmed genetic diagnosis through the DDD study before August 2019 (n = 112) were included in a clinical audit. Families with no identified clinical outcomes (n = 16) were invited to participate in semistructured telephone interviews. Results Disease-specific treatment was identified for 7 probands (6%), while 48 probands (43%) were referred for further investigations or screening and 60 probands (54%) were recruited to further research. Just 5 families (4%) opted for prenatal testing in a subsequent pregnancy, reflecting the relatively advanced maternal age in our cohort, and 42 families (38%) were given disease-specific information or signposting to patient-specific resources such as support groups. Six interviews were performed (response rate = 47%) and thematic analysis identified four major themes: reaching a diagnosis, emotional impact, family implications, and practical issues. Conclusion Our data demonstrate that receiving a genetic diagnosis has substantial positive medical and psychosocial outcomes for the majority of patients and their families.

Download Full-text

Whole-Exome Sequencing for Identifying Genetic Causes of Intellectual Developmental Disorders

International Journal of General Medicine ◽

10.2147/ijgm.s300775 ◽

2021 ◽

Vol Volume 14 ◽

pp. 1275-1282

Author(s):

Yu-Xiong Guo ◽

Hong-Xia Ma ◽

Yu-Xin Zhang ◽

Zhi-Hong Chen ◽

Qiong-Xiang Zhai

Keyword(s):

Exome Sequencing ◽

Whole Exome Sequencing ◽

Developmental Disorders ◽

Genetic Causes ◽

Whole Exome

Download Full-text

VEP-G2P: A Tool for Efficient, Flexible and Scalable Diagnostic Filtering of Genomic Variants

10.1101/416552 ◽

2018 ◽

Author(s):

Anja Thormann ◽

Mihail Halachev ◽

William McLaren ◽

David J Moore ◽

Victoria Svinti ◽

...

Keyword(s):

Developmental Disorders ◽

Large Scale ◽

De Novo ◽

Genetic Research ◽

Evidence Based ◽

Large Numbers ◽

Whole Exome ◽

Variant Filtering ◽

And Control ◽

Exome Sequence

AbstractPurposeWe aimed to develop an efficient, flexible, scalable and evidence-based approach to sequence-based diagnostic analysis/re-analysis of conditions with very large numbers of different causative genes. We then wished to define the expected rate of plausibly causative variants coming through strict filtering in control in comparison to disease populations to quantify background diagnostic “noise”.MethodsWe developed G2P (www.ebi.ac.uk/gene2phenotype) as an online system to facilitate the development, validation, curation and distribution of large-scale, evidence-based datasets for use in diagnostic variant filtering. Each locus-genotype-mechanism-disease-evidence thread (LGMDET) associates an allelic requirement and a mutational consequence at a defined locus with a disease entity and a confidence level and evidence links. We then developed an extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P, which can filter based on G2P other widely used gene panel curation systems. We compared the output of disease-associated and control whole exome sequence (WES) using Developmental Disorders G2P (G2PDD; 2044 LGMDETs) and constitutional cancer predisposition G2P (G2PCancer; 128 LGMDETs).ResultsWe have shown a sensitivity/precision of 97.3%/33% and 81.6%/22.7% for causative de novo and inherited variants respectively using VEP-G2PDD in DDD study probands WES. Many of the apparently diagnostic genotypes “missed” are likely false-positive reports with lower minor allele frequencies and more severe predicted consequences being diagnostically-discriminative features.ConclusionCase:control comparisons using VEP-G2PDD established an observed:expected ratio of 1:30,000 plausibly causative variants in proband WES to ~1:40,000 reportable but presumed-benign variants in controls. At least half the filtered variants in probands represent background “noise”. Supporting phenotypic evidence is, therefore, necessary in genetically-heterogeneous disorders. G2P and VEP-G2P provides a practical approach to optimize disease-specific filtering parameters in diagnostic genetic research.

Download Full-text

Large-scale cDNA analysis reveals phased gene expression patterns during preimplantation mouse development

Development ◽

10.1242/dev.127.8.1737 ◽

2000 ◽

Vol 127 (8) ◽

pp. 1737-1749 ◽

Cited By ~ 2

Author(s):

M.S. Ko ◽

J.R. Kitchen ◽

X. Wang ◽

T.A. Threat ◽

X. Wang ◽

...

Keyword(s):

Gene Expression ◽

Developmental Disorders ◽

Large Scale ◽

Expression Patterns ◽

Mammalian Development ◽

Mouse Development ◽

New Genes ◽

Entry Points ◽

Preimplantation Mouse ◽

Mammalian Genes

Little is known about gene action in the preimplantation events that initiate mammalian development. Based on cDNA collections made from each stage from egg to blastocyst, 25438 3′-ESTs were derived, and represent 9718 genes, half of them novel. Thus, a considerable fraction of mammalian genes is dedicated to embryonic expression. This study reveals profound changes in gene expression that include the transient induction of transcripts at each stage. These results raise the possibility that development is driven by the action of a series of stage-specific expressed genes. The new genes, 798 of them placed on the mouse genetic map, provide entry points for analyses of human and mouse developmental disorders.

Download Full-text

10 years of CEMARA database in the AnDDI-Rares network: a unique resource facilitating research and epidemiology in developmental disorders in France

Orphanet Journal of Rare Diseases ◽

10.1186/s13023-021-01957-4 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Claude Messiaen ◽

Caroline Racine ◽

Ahlem Khatim ◽

Louis Soussand ◽

Sylvie Odent ◽

...

Keyword(s):

Rare Diseases ◽

Developmental Disorders ◽

Large Scale ◽

Clinical Care ◽

Demographic Data ◽

Improve Patient Care ◽

Data Repository ◽

Care Organization ◽

Online Data ◽

Expert Center

Abstract Background In France, the Ministry of Health has implemented a comprehensive program for rare diseases (RD) that includes an epidemiological program as well as the establishment of expert centers for the clinical care of patients with RD. Since 2007, most of these centers have entered the data for patients with developmental disorders into the CEMARA population-based registry, a national online data repository for all rare diseases. Through the CEMARA web portal, descriptive demographic data, clinical data, and the chronology of medical follow-up can be obtained for each center. We address the interest and ongoing challenges of this national data collection system 10 years after its implementation. Methods Since 2007, clinicians and researchers have reported the “minimum dataset (MDS)” for each patient presenting to their expert center. We retrospectively analyzed administrative data, demographic data, care organization and diagnoses. Results Over 10 years, 228,243 RD patients (including healthy carriers and family members for whom experts denied any suspicion of RD) have visited an expert center. Among them, 167,361 were patients affected by a RD (median age 11 years, 54% children, 46% adults, with a balanced sex ratio), and 60,882 were unaffected relatives (median age 37 years). The majority of patients (87%) were seen no more than once a year, and 52% of visits were for a diagnostic procedure. Among the 2,869 recorded rare disorders, 1,907 (66.5%) were recorded in less than 10 patients, 802 (28%) in 10 to 100 patients, 149 (5.2%) in 100 to 1,000 patients, and 11 (0.4%) in > 1,000 patients. Overall, 45.6% of individuals had no diagnosis and 6.7% had an uncertain diagnosis. Children were mainly referred by their pediatrician (46%; n = 55,755 among the 121,136 total children referrals) and adults by a medical specialist (34%; n = 14,053 among the 41,564 total adult referrals). Given the geographical coverage of the centers, the median distance from the patient’s home was 25.1 km (IQR = 6.3 km-64.2 km). Conclusions CEMARA provides unprecedented support for epidemiological, clinical and therapeutic studies in the field of RD. Researchers can benefit from the national scope of CEMARA data, but also focus on specific diseases or patient subgroups. While this endeavor has been a major collective effort among French RD experts to gather large-scale data into a single database, it provides tremendous potential to improve patient care.

Download Full-text

A systematic comparison of two new releases of exome sequencing products: the aim of use determines the choice of product

Biological Chemistry ◽

10.1515/hsz-2015-0300 ◽

2016 ◽

Vol 397 (8) ◽

pp. 791-801 ◽

Cited By ~ 7

Author(s):

Janine Altmüller ◽

Susanne Motameny ◽

Christian Becker ◽

Holger Thiele ◽

Sreyoshi Chatterjee ◽

...

Keyword(s):

Exome Sequencing ◽

Developmental Disorders ◽

Large Scale ◽

Data Sets ◽

Early Access ◽

Whole Exome ◽

Agilent Sureselect ◽

Disease Associated Genes ◽

Diagnostic Setting ◽

Better Than

Abstract We received early access to the newest releases of exome sequencing products, namely Agilent SureSelect v6 (Agilent, Santa Clara, CA, USA) and NimbleGen MedExome (Roche NimbleGen, Basel, Switzerland), and we conducted whole exome sequencing (WES) of several DNA samples with each of these products in order to assess their performance. Here, we provide a detailed evaluation of the original, normalized (with respect to the different target sizes), and trimmed data sets and compare them in terms of the amount of duplicates, the reads on target, and the enrichment evenness. In addition to these general statistics, we performed a detailed analysis of the frequently mutated and newly described genes found in ‘The Deciphering Developmental Disorders Study’ published very recently (Fitzgerald, T.W., Gerety, S.S., Jones, W.D., van Kogelenberg, M., King, D.A., McRae, J., Morley, K.I., Parthiban, V., Al-Turki, S., Ambridge, K., et al. (2015). Large-scale discovery of novel genetic causes of developmental disorders. Nature 519, 223–228.). In our comparison, the Agilent v6 exome performs better than the NimbleGen’s MedExome both in terms of efficiency and evenness of coverage distribution. With its larger target size, it is also more comprehensive, and therefore the better choice in research projects that aim to identify novel disease-associated genes. In contrast, if the exomes are mainly used in a diagnostic setting, we see advantages for the new NimbleGen MedExome. We find a superior coverage here in those genes of high clinical relevance that likely allows for a better detection of relevant, disease-causing mutations.

Download Full-text