Solving inherited white matter disorder etiologies in the neurology clinic: Challenges and lessons learned using next-generation sequencing

IntroductionRare neurodevelopmental disorders, including inherited white matter disorders or leukodystrophies, often present a diagnostic challenge on a genetic level given the large number of causal genes associated with a range of disease subtypes. This study aims to demonstrate the challenges and lessons learned in the genetic investigations of leukodystrophies through presentation of a series of cases solved using exome or genome sequencing.MethodsEach of the six patients had a leukodystrophy associated with hypomyelination or delayed myelination on MRI, and inconclusive clinical diagnostic genetic testing results. We performed next generation sequencing (case-based exome or genome sequencing) to further investigate the genetic cause of disease.ResultsFollowing different lines of investigation, molecular diagnoses were obtained for each case, with patients harboring pathogenic variants in a range of genes including TMEM106B, GJA1, AGA, POLR3A, and TUBB4A. We describe the lessons learned in reaching the genetic diagnosis, including the importance of (a) utilizing proper multi-gene panels in clinical testing, (b) assessing the reliability of biochemical assays in supporting diagnoses, and (c) understanding the limitations of exome sequencing methods in regard to CNV detection and region coverage in GC-rich areas.DiscussionThis study illustrates the importance of applying a collaborative diagnostic approach by combining detailed phenotyping data and metabolic results from the clinical environment with advanced next generation sequencing analysis techniques from the research environment to increase the diagnostic yield in patients with genetically unresolved leukodystrophies

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.Peer reviewe

Mutant human myocilin induces strain specific differences in ocular hypertension and optic nerve damage in mice.

Elevated intraocular pressure (IOP) is a causative risk factor for the development and progression of glaucoma. Glaucomatous mutations in myocilin (MYOC) damage the trabecular meshwork and elevate IOP in humans and in mice. Animal models of glaucoma are important to discover and better understand molecular pathogenic pathways and to test new glaucoma therapeutics. Although a number of different animal models of glaucoma have been developed and characterized, there are no true models of human primary open angle glaucoma (POAG). The overall goal of this work is to develop the first inducible mouse model of POAG using a human POAG relevant transgene (i.e. mutant MYOC) expression in mouse eyes to elevate IOP and cause pressure-induced damage to the optic nerve. Four mouse strains (A/J, BALB/cJ, C57BL/6J, and C3H/HeJ) were used in this study. Ad5.MYOC.Y437H (5 × 10(7) pfu) was injected intravitreally into one eye, with the uninjected contralateral eye serving as the control eye. Conscious IOP measurements were taken using a TonoLab rebound tonometer. Optic nerve damage was determined by scoring PPD stained optic nerve cross sections. Retinal ganglion cell and superior colliculus damage was assessed by Nissl stain cell counts. Intravitreal administration of viral vector Ad5.MYOC.Y437H caused a prolonged, reproducible, and statistically significant IOP elevation in BALB/cJ, A/J, and C57BL/6J mice. IOPs increased to approximately 25 mm Hg for 8 weeks (p \u3c 0.0001). In contrast, the C3H/HeJ mouse strain was resistant to Ad5.MYOC.Y437H induced IOP elevation for the 8-week time period. IOPs were stable (12-15 mm Hg) in the uninjected control eyes. We also determined whether there were any strain differences in pressure-induced optic nerve damage. Even though IOP was similarly elevated in three of the strains tested (BALB/cJ, C57BL/6J, and A/J) only the A/J strain had considerable and significant optic nerve damage at the end of 8 weeks with optic nerve damage score of 2.64 ± 0.19 (n = 18, p \u3c 0.001) in the injected eye. There was no statistical difference in retinal ganglion cell death or superior colliculus damage at the 8-week time point in any of the strains tested. These results demonstrate strain dependent responses to Ad5.MYOC.Y437H-induced ocular hypertension and pressure-induced optic nerve damage

Table_1_Biallelic pathogenic variants in POLR3D alter tRNA transcription and cause a hypomyelinating leukodystrophy: A case report.xlsx

RNA polymerase III-related leukodystrophy (POLR3-related leukodystrophy) is a rare, genetically determined hypomyelinating disease arising from biallelic pathogenic variants in genes encoding subunits of RNA polymerase III (Pol III). Here, we describe the first reported case of POLR3-related leukodystrophy caused by biallelic pathogenic variants in POLR3D, encoding the RPC4 subunit of Pol III. The individual, a female, demonstrated delays in walking and expressive and receptive language as a child and later cognitively plateaued. Additional neurological features included cerebellar signs (e.g., dysarthria, ataxia, and intention tremor) and dysphagia, while non-neurological features included hypodontia, hypogonadotropic hypogonadism, and dysmorphic facial features. Her MRI was notable for diffuse hypomyelination with myelin preservation of early myelinating structures, characteristic of POLR3-related leukodystrophy. Exome sequencing revealed the biallelic variants in POLR3D, a missense variant (c.541C > T, p.P181S) and an intronic splice site variant (c.656-6G > A, p.?). Functional studies of the patient’s fibroblasts demonstrated significantly decreased RNA-level expression of POLR3D, along with reduced expression of other Pol III subunit genes. Notably, Pol III transcription was also shown to be aberrant, with a significant decrease in 7SK RNA and several distinct tRNA genes analyzed. Affinity purification coupled to mass spectrometry of the POLR3D p.P181S variant showed normal assembly of Pol III subunits yet altered interaction of Pol III with the PAQosome chaperone complex, indicating the missense variant is likely to alter complex maturation. This work identifies biallelic pathogenic variants in POLR3D as a novel genetic cause of POLR3-related leukodystrophy, expanding the molecular spectrum associated with this disease, and proposes altered tRNA homeostasis as a factor in the underlying biology of this hypomyelinating disorder.</p

Hundreds of variants clustered in genomic loci and biological pathways affect human height.

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P &lt; 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways