Of over 7000 patients referred to a diagnostic laboratory, 28% had diagnoses based on DNA sequencing, 5% of whom had two or more diagnoses. Their phenotypes could be better understood by considering ...whether the implicated genes affect independent biologic processes or organ systems.
Medical genetics focuses on the relationship between observed phenotypes and their underlying genotypes, modes of transmission, and risks of recurrence. Expected patterns of mendelian inheritance are often used to confirm the identification of disease genes, and deviations from mendelian expectations have led to the discovery of more complicated genetic underpinnings of disease (Fig. S1 in the Supplementary Appendix, available with the full text of this article at NEJM.org).
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Multiple (or dual) molecular diagnoses involve more than one clinical diagnosis and more than one genetic locus (Figure 1), each segregating independently.
Diagnostic whole-exome sequencing affords opportunities for providing insights into relationships . . .
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.
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.
Genetic ataxias are associated with mutations in hundreds of genes with high phenotypic overlap complicating the clinical diagnosis. Whole‐exome sequencing (WES) has increased the overall diagnostic ...rate considerably. However, the upper limit of this method remains ill‐defined, hindering efforts to address the remaining diagnostic gap. To further assess the role of rare coding variation in ataxic disorders, we reanalyzed our previously published exome cohort of 76 predominantly adult and sporadic‐onset patients, expanded the total number of cases to 260, and introduced analyses for copy number variation and repeat expansion in a representative subset. For new cases (n = 184), our resulting clinically relevant detection rate remained stable at 47% with 24% classified as pathogenic. Reanalysis of the previously sequenced 76 patients modestly improved the pathogenic rate by 7%. For the combined cohort (n = 260), the total observed clinical detection rate was 52% with 25% classified as pathogenic. Published studies of similar neurological phenotypes report comparable rates. This consistency across multiple cohorts suggests that, despite continued technical and analytical advancements, an approximately 50% diagnostic rate marks a relative ceiling for current WES‐based methods and a more comprehensive genome‐wide assessment is needed to identify the missing causative genetic etiologies for cerebellar ataxia and related neurodegenerative diseases.
Genetic ataxias are associated with mutations in hundreds of genes with high phenotypic overlap complicating the clinical diagnosis. To assess rare coding variation in ataxic disorders, we performed whole‐exome sequencing of patients (n = 260) including analysis for copy number variation and repeat expansion in a representative subset. We suggest that, despite continued technical and analytical advancements, an approximately 50% diagnostic rate marks a relative ceiling for current WES‐based methods and a more comprehensive genome‐wide assessment is needed to further improve diagnosis.
The goal of this study was to assess the scale of low-level parental mosaicism in exome sequencing (ES) databases.
We analyzed approximately 2000 family trio ES data sets from the Baylor-Hopkins ...Center for Mendelian Genomics (BHCMG) and Baylor Genetics (BG). Among apparent de novo single-nucleotide variants identified in the affected probands, we selected rare unique variants with variant allele fraction (VAF) between 30% and 70% in the probands and lower than 10% in one of the parents.
Of 102 candidate mosaic variants validated using amplicon-based next-generation sequencing, droplet digital polymerase chain reaction, or blocker displacement amplification, 27 (26.4%) were confirmed to be low- (VAF between 1% and 10%) or very low (VAF <1%) level mosaic. Detection precision in parental samples with two or more alternate reads was 63.6% (BHCMG) and 43.6% (BG). In nine investigated individuals, we observed variability of mosaic ratios among blood, saliva, fibroblast, buccal, hair, and urine samples.
Our computational pipeline enables robust discrimination between true and false positive candidate mosaic variants and efficient detection of low-level mosaicism in ES samples. We confirm that the presence of two or more alternate reads in the parental sample is a reliable predictor of low-level parental somatic mosaicism.
Abstract
Alzheimer’s disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research ...evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias. There is a lack of comprehensive research aimed to identify AD-associated risk mutations systematically. To address this challenge, we hereby construct a large-scale AD mutation and co-mutation framework (‘AD-Syn-Net’), and propose deep learning models named Deep-SMCI and Deep-CMCI configured with fully connected layers that are capable of predicting cognitive impairment of subjects effectively based on genetic mutation and co-mutation profiles. Next, we apply the customized frameworks to data sets to evaluate the importance scores of the mutations and identified mutation effectors and co-mutation combination vulnerabilities contributing to cognitive impairment. Furthermore, we evaluate the influence of mutation pairs on the network architecture to dissect the genetic organization of AD and identify novel co-mutations that could be responsible for dementia, laying a solid foundation for proposing future targeted therapy for AD precision medicine. Our deep learning model codes are available open access here: https://github.com/Pan-Bio/AD-mutation-effectors.
Kinesin proteins are critical for various cellular functions such as intracellular transport and cell division, and many members of the family have been linked to monogenic disorders and cancer. We ...report eight individuals with intellectual disability and microcephaly from four unrelated families with parental consanguinity. In the affected individuals of each family, homozygosity for likely pathogenic variants in KIF14 were detected; two loss-of-function (p.Asn83Ilefs*3 and p.Ser1478fs), and two missense substitutions (p.Ser841Phe and p.Gly459Arg). KIF14 is a mitotic motor protein that is required for spindle localization of the mitotic citron rho-interacting kinase, CIT, also mutated in microcephaly. Our results demonstrate the involvement of KIF14 in development and reveal a wide phenotypic variability ranging from fetal lethality to moderate developmental delay and microcephaly.
Megacystis microcolon intestinal hypoperistalsis syndrome (MMIHS) is a congenital disorder characterized by loss of smooth muscle contraction in the bladder and intestine. To date, three genes are ...known to be involved in MMIHS pathogenesis: ACTG2, MYH11, and LMOD1. However, for approximately 10% of affected individuals, the genetic cause of the disease is unknown, suggesting that other loci are most likely involved. Here, we report on three MMIHS-affected subjects from two consanguineous families with no variants in the known MMIHS-associated genes. By performing homozygosity mapping and whole-exome sequencing, we found homozygous variants in myosin light chain kinase (MYLK) in both families. We identified a 7 bp duplication (c.3838_3844dupGAAAGCG p.Glu1282_Glyfs∗51) in one family and a putative splice-site variant (c.3985+5C>A) in the other. Expression studies and splicing assays indicated that both variants affect normal MYLK expression. Because MYLK encodes an important kinase required for myosin activation and subsequent interaction with actin filaments, it is likely that in its absence, contraction of smooth muscle cells is impaired. The existence of a conditional-Mylk-knockout mouse model with severe gut dysmotility and abnormal function of the bladder supports the involvement of this gene in MMIHS pathogenesis. In aggregate, our findings implicate MYLK as a gene involved in the recessive form of MMIHS, confirming that this disease of the visceral organs is heterogeneous with a myopathic origin.
Patients with common variable immunodeficiency associated with autoimmune cytopenia (CVID+AIC) generate few isotype-switched B cells with severely decreased frequencies of somatic hypermutations ...(SHMs), but their underlying molecular defects remain poorly characterized. We identified a CVID+AIC patient who displays a rare homozygous missense M466V mutation in β-catenin-like protein 1 (CTNNBL1). Because CTNNBL1 binds activation-induced cytidine deaminase (AID) that catalyzes SHM, we tested AID interactions with the CTNNBL1 M466V variant. We found that the M466V mutation interfered with the association of CTNNBL1 with AID, resulting in decreased AID in the nuclei of patient EBV-transformed B cell lines and of CTNNBL1 466V/V Ramos B cells engineered to express only CTNNBL1 M466V using CRISPR/Cas9 technology. As a consequence, the scarce IgG+ memory B cells from the CTNNBL1 466V/V patient showed a low SHM frequency that averaged 6.7 mutations compared with about 18 mutations per clone in healthy-donor counterparts. In addition, CTNNBL1 466V/V Ramos B cells displayed a decreased incidence of SHM that was reduced by half compared with parental WT Ramos B cells, demonstrating that the CTNNBL1 M466V mutation is responsible for defective SHM induction. We conclude that CTNNBL1 plays an important role in regulating AID-dependent antibody diversification in humans.
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