Dietary Regimens Modify Early Onset of Obesity in Mice Haploinsufficient for Rai1

Smith-Magenis syndrome is a complex genomic disorder in which a majority of individuals are obese by adolescence. While an interstitial deletion of chromosome 17p11.2 is the leading cause, mutation or deletion of the RAI1 gene alone results in most features of the disorder. Previous studies have shown that heterozygous knockout of Rai1 results in an obese phenotype in mice and that Smith-Magenis syndrome mouse models have a significantly reduced fecundity and an altered transmission pattern of the mutant Rai1 allele, complicating large, extended studies in these models. In this study, we show that breeding C57Bl/6J Rai1+/−mice with FVB/NJ to create F1 Rai1+/− offspring in a mixed genetic background ameliorates both fecundity and Rai1 allele transmission phenotypes. These findings suggest that the mixed background provides a more robust platform for breeding and larger phenotypic studies. We also characterized the effect of dietary intake on Rai1+/− mouse growth during adolescent and early adulthood developmental stages. Animals fed a high carbohydrate or a high fat diet gained weight at a significantly faster rate than their wild type littermates. Both high fat and high carbohydrate fed Rai1+/− mice also had an increase in body fat and altered fat distribution patterns. Interestingly, Rai1+/− mice fed different diets did not display altered fasting blood glucose levels. These results suggest that dietary regimens are extremely important for individuals with Smith- Magenis syndrome and that food high in fat and carbohydrates may exacerbate obesity outcomes

Biallelic variants in COX4I1 associated with a novel phenotype resembling Leigh syndrome with developmental regression, intellectual disability, and seizures

Autosomal recessive COX4I1 deficiency has been previously reported in a single individual with a homozygous pathogenic variant in COX4I1, who presented with short stature, poor weight gain, dysmorphic features, and features of Fanconi anemia. COX4I1 encodes subunit 4, isoform 1 of cytochrome c oxidase. Cytochrome c oxidase is a respiratory chain enzyme that plays an important role in mitochondrial electron transport and reduces molecular oxygen to water leading to the formation of ATP. Defective production of cytochrome c oxidase leads to a variable phenotypic spectrum ranging from isolated myopathy to Leigh syndrome. Here, we describe two siblings, born to consanguineous parents, who presented with encephalopathy, developmental regression, hypotonia, pathognomonic brain imaging findings resembling Leigh‐syndrome, and a novel homozygous variant on COX4I1, expanding the known clinical phenotype associated with pathogenic variants in COX4I1

CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models

We consider the following general family of algorithmic problems that arises in transcriptomics, metabolomics and other fields: given a weighted graph G and a subset of its nodes S, find subsets of S that show significant connectedness within G. A specific solution to this problem may be defined by devising a scoring function, the Maximum Clique problem being a classic example, where S includes all nodes in G and where the score is defined by the size of the largest subset of S fully connected within G. Major practical obstacles for the plethora of algorithms addressing this type of problem include computational efficiency and, particularly for more complex scores which take edge weights into account, the computational cost of permutation testing, a statistical procedure required to obtain a bound on the p-value for a connectedness score. To address these problems, we developed CTD, "Connect the Dots", a fast algorithm based on data compression that detects highly connected subsets within S. CTD provides information-theoretic upper bounds on p-values when S contains a small fraction of nodes in G without requiring computationally costly permutation testing. We apply the CTD algorithm to interpret multi-metabolite perturbations due to inborn errors of metabolism and multi-transcript perturbations associated with breast cancer in the context of disease-specific Gaussian Markov Random Field networks learned directly from respective molecular profiling data

Frameshift mutation hotspot identified in Smith-Magenis syndrome: case report and review of literature

Smith-Magenis syndrome (SMS) is a complex syndrome involving intellectual disabilities, sleep disturbance, behavioural problems, and a variety of craniofacial, skeletal, and visceral anomalies. While the majority of SMS cases harbor an ~3.5 Mb common deletion on 17p11.2 that encompasses the retinoic acid induced-1 (RAI1) gene, some patients carry small intragenic deletions or point mutations in RAI1. We present data on two cases of Smith-Magenis syndrome with mutation of RAI1. Both cases are phenotypically consistent with SMS and RAI1 mutation but also have other anomalies not previously reported in SMS, including spontaneous pneumothoraces. These cases also illustrate variability in the SMS phenotype not previously shown for RAI1 mutation cases, including hearing loss, absence of self-abusive behaviours, and mild global delays. Sequencing of RAI1 revealed mutation of the same heptameric C-tract (CCCCCCC) in exon 3 in both cases (c.3103delC one case and and c.3103insC in the other), resulting in frameshift mutations. Of the seven reported frameshift mutations occurring in poly C-tracts in RAI1, four cases (~57%) occur at this heptameric C-tract. Collectively, these results indicate that this heptameric C-tract is a preferential hotspot for single nucleotide insertion/deletions (SNindels) and therefore, should be considered a primary target for analysis in patients suspected for mutations in RAI1. We expect that as more patients are sequenced for mutations in RAI1, the incidence of frameshift mutations in this hotspot will become more evident

2-Pyrrolidinone and Succinimide as Clinical Screening Biomarkers for GABA-Transaminase Deficiency: Anti-seizure Medications Impact Accurate Diagnosis

Broad-scale untargeted biochemical phenotyping is a technology that supplements widely accepted assays, such as organic acid, amino acid, and acylcarnitine analyses typically utilized for the diagnosis of inborn errors of metabolism. In this study, we investigate the analyte changes associated with 4-aminobutyrate aminotransferase (ABAT, GABA transaminase) deficiency and treatments that affect GABA metabolism. GABA-transaminase deficiency is a rare neurodevelopmental and neurometabolic disorder caused by mutations in ABAT and resulting in accumulation of GABA in the cerebrospinal fluid (CSF). For that reason, measurement of GABA in CSF is currently the primary approach to diagnosis. GABA-transaminase deficiency results in severe developmental delay with intellectual disability, seizures, and movement disorder, and is often associated with death in childhood. Using an untargeted metabolomics platform, we analyzed EDTA plasma, urine, and CSF specimens from four individuals with GABA-transaminase deficiency to identify biomarkers by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort. Metabolomic analyses of over 1,000 clinical plasma samples revealed a rich source of biochemical information. Three out of four patients showed significantly elevated levels of the molecule 2-pyrrolidinone (Z-score ≥ 2) in plasma, and whole exome sequencing revealed variants of uncertain significance in ABAT. Additionally, these same patients also had elevated levels of succinimide or its ring-opened form, succinamic acid, in plasma, urine, and CSF and/or homocarnosine in urine and CSF. In the analysis of clinical EDTA plasma samples, the levels of succinamic acid and 2-pyrrolidinone showed a high level of correlation (R = 0.72), indicating impairment in GABA metabolism and further supporting the association with GABA-transaminase deficiency and the pathogenicity of the ABAT variants. Further analysis of metabolomic data across our patient population revealed the association of elevated levels of 2-pyrrolidinone with administration of vigabatrin, a commonly used anti-seizure medication and a known inhibitor of GABA-transaminase. These data indicate that anti-seizure medications may alter the biochemical and metabolomic data, potentially impacting the interpretation and diagnosis for the patient. Further, these data demonstrate the power of combining broad scale genotyping and phenotyping technologies to diagnose inherited neurometabolic disorders and support the use of metabolic phenotyping of plasma to screen for GABA-transaminase deficiency

Prevalence of DDC genotypes in patients with aromatic L-amino acid decarboxylase (AADC) deficiency and in silico prediction of structural protein changes

Aromatic L-amino acid decarboxylase (AADC) deficiency is a rare autosomal recessive genetic disorder affecting the biosynthesis of dopamine, a precursor of both norepinephrine and epinephrine, and serotonin. Diagnosis is based on the analysis of CSF or plasma metabolites, AADC activity in plasma and genetic testing for variants in the DDC gene. The exact prevalence of AADC deficiency, the number of patients, and the variant and genotype prevalence are not known. Here, we present the DDC variant (n = 143) and genotype (n = 151) prevalence of 348 patients with AADC deficiency, 121 of whom were previously not reported. In addition, we report 26 new DDC variants, classify them according to the ACMG/AMP/ACGS recommendations for pathogenicity and score them based on the predicted structural effect. The splice variant c.714+4A>T, with a founder effect in Taiwan and China, was the most common variant (allele frequency = 32.4%), and c.[714+4A>T];[714+4A>T] was the most common genotype (genotype frequency = 21.3%). Approximately 90% of genotypes had variants classified as pathogenic or likely pathogenic, while 7% had one VUS allele and 3% had two VUS alleles. Only one benign variant was reported. Homozygous and compound heterozygous genotypes were interpreted in terms of AADC protein and categorized as: i) devoid of full-length AADC, ii) bearing one type of AADC homodimeric variant or iii) producing an AADC protein population composed of two homodimeric and one heterodimeric variant. Based on structural features, a score was attributed for all homodimers, and a tentative prediction was advanced for the heterodimer. Almost all AADC protein variants were pathogenic or likely pathogenic

A Duplication CNV That Conveys Traits Reciprocal to Metabolic Syndrome and Protects against Diet-Induced Obesity in Mice and Men

The functional contribution of CNV to human biology and disease pathophysiology has undergone limited exploration. Recent observations in humans indicate a tentative link between CNV and weight regulation. Smith-Magenis syndrome (SMS), manifesting obesity and hypercholesterolemia, results from a deletion CNV at 17p11.2, but is sometimes due to haploinsufficiency of a single gene, RAI1. The reciprocal duplication in 17p11.2 causes Potocki-Lupski syndrome (PTLS). We previously constructed mouse strains with a deletion, Df(11)17, or duplication, Dp(11)17, of the mouse genomic interval syntenic to the SMS/PTLS region. We demonstrate that Dp(11)17 is obesity-opposing; it conveys a highly penetrant, strain-independent phenotype of reduced weight, leaner body composition, lower TC/LDL, and increased insulin sensitivity that is not due to alteration in food intake or activity level. When fed with a high-fat diet, Dp(11)17/+ mice display much less weight gain and metabolic change than WT mice, demonstrating that the Dp(11)17 CNV protects against metabolic syndrome. Reciprocally, Df(11)17/+ mice with the deletion CNV have increased weight, higher fat content, decreased HDL, and reduced insulin sensitivity, manifesting a bona fide metabolic syndrome. These observations in the deficiency animal model are supported by human data from 76 SMS subjects. Further, studies on knockout/transgenic mice showed that the metabolic consequences of Dp(11)17 and Df(11)17 CNVs are not only due to dosage alterations of Rai1, the predominant dosage-sensitive gene for SMS and likely also PTLS. Our experiments in chromosome-engineered mouse CNV models for human genomic disorders demonstrate that a CNV can be causative for weight/metabolic phenotypes. Furthermore, we explored the biology underlying the contribution of CNV to the physiology of weight control and energy metabolism. The high penetrance, strain independence, and resistance to dietary influences associated with the CNVs in this study are features distinct from most SNP–associated metabolic traits and further highlight the potential importance of CNV in the etiology of both obesity and MetS as well as in the protection from these traits

Prevalence of DDC genotypes in patients with aromatic L-amino acid decarboxylase (AADC) deficiency and in silico prediction of structural protein changes

Aromatic L-amino acid decarboxylase (AADC) deficiency is a rare autosomal recessive genetic disorder affecting the biosynthesis of dopamine, a precursor of both norepinephrine and epinephrine, and serotonin. Diagnosis is based on the analysis of CSF or plasma metabolites, AADC activity in plasma and genetic testing for variants in the DDC gene. The exact prevalence of AADC deficiency, the number of patients, and the variant and genotype prevalence are not known. Here, we present the DDC variant (n = 143) and genotype (n = 151) prevalence of 348 patients with AADC deficiency, 121 of whom were previously not reported. In addition, we report 26 new DDC variants, classify them according to the ACMG/AMP/ACGS recommendations for pathogenicity and score them based on the predicted structural effect. The splice variant c.714+4A>T, with a founder effect in Taiwan and China, was the most common variant (allele frequency = 32.4%), and c.[714+4A>T];[714+4A>T] was the most common genotype (genotype frequency = 21.3%). Approximately 90% of genotypes had variants classified as pathogenic or likely pathogenic, while 7% had one VUS allele and 3% had two VUS alleles. Only one benign variant was reported. Homozygous and compound heterozygous genotypes were interpreted in terms of AADC protein and categorized as: i) devoid of full-length AADC, ii) bearing one type of AADC homodimeric variant or iii) producing an AADC protein population composed of two homodimeric and one heterodimeric variant. Based on structural features, a score was attributed for all homodimers, and a tentative prediction was advanced for the heterodimer. Almost all AADC protein variants were pathogenic or likely pathogenic