The evenness score (E) in next-generation sequencing (NGS) quantifies the homogeneity in coverage of the NGS targets. Here I clarify the mathematical description of E, which is 1 minus the integral ...from 0 to 1 over the cumulative distribution function F(x) of the normalized coverage x, where normalization means division by the mean, and derive a computationally more efficient formula; that is, 1 minus the integral from 0 to 1 over the probability density distribution f(x) times 1-x. An analogous formula for empirical coverage data is provided as well as fast R command line scripts. This new formula allows for a general comparison of E with the coefficient of variation (=standard deviation σ of normalized data) which is the conventional measure of the relative width of a distribution. For symmetrical distributions, including the Gaussian, E can be predicted closely as 1-σ(2)/2⩾E⩾1-σ/2 with σ⩽1 owing to normalization and symmetry. In case of the log-normal distribution as a typical representative of positively skewed biological data, the analysis yields E≈exp(-σ*/2) with σ*(2)=ln(σ(2)+1) up to large σ (⩽3), and E≈1-F(exp(-1)) for very large σ (⩾2.5). In the latter kind of rather uneven coverage, E can provide direct information on the fraction of well-covered targets that is not immediately delivered by the normalized σ. Otherwise, E does not appear to have major advantages over σ or over a simple score exp(-σ) based on it. Actually, exp(-σ) exploits a much larger part of its range for the evaluation of realistic NGS outputs.
Abstract Complications of diabetes are often attributed to glucose and reactive dicarbonyl metabolites derived from glycolysis or gluconeogenesis, such as methylglyoxal. However, in the CNS, neurons ...and endothelial cells use lactate as energy source in addition to glucose, which does not lead to the formation of methylglyoxal and has previously been considered a safer route of energy consumption than glycolysis. Nevertheless, neurons and endothelial cells are hotspots for the cellular pathology underlying neurological complications in diabetes, suggesting a cause that is distinct from other diabetes complications and independent of methylglyoxal. Here, we show that in clinical and experimental diabetes plasma concentrations of dimethylglyoxal are increased. In a mouse model of diabetes, ilvb acetolactate-synthase-like (ILVBL, HACL2) is the enzyme involved in formation of increased amounts of dimethylglyoxal from lactate-derived pyruvate. Dimethylglyoxal reacts with lysine residues, forms Nε−3-hydroxy-2-butanonelysine (HBL) as an adduct, induces oxidative stress more strongly than other dicarbonyls, causes blood-brain barrier disruption, and can mimic mild cognitive impairment in experimental diabetes. These data suggest dimethylglyoxal formation as a pathway leading to neurological complications in diabetes that is distinct from other complications. Importantly, dimethylglyoxal formation can be reduced using genetic, pharmacological and dietary interventions, offering new strategies for preventing CNS dysfunction in diabetes.
A remark on rare variants Oexle, Konrad
Journal of human genetics,
04/2010, Volume:
55, Issue:
4
Journal Article
Peer reviewed
Open access
The genetic architecture of a disease determines the epidemiological methods for its examination. Recently, Bodmer and Bonilla suggested that moderately strong, moderately rare variants contribute ...substantially to the genetic population attributable risk (PAR) of common diseases. In the first part of this communication, I provide a concise reconstruction of their deliberation. Variants contributing to human disease can be identified by linkage or by association tests. Risch and Merikangas analyzed the power of these tests by comparing the affected sib-pair linkage test (ASP) and the transmission disequilibrium association test (TDT). In the second part of this paper, I give an accessible reconstruction of this comparison and derive simple approximations in the low allele frequency range, directly showing that the linkage test is much more sensitive to a decrease of frequency or effect size. In the third part, I analyze a disease model whose genetic architecture is proportional to Kimura's infinite sites model. The relation between a variant's selection coefficient and its effect size in disease generation is assumed to be simple, and the number of contributing genetic variants is determined by the sum of their approximative PAR contributions. An association test (TDT) is finally applied to this disease model. For different ranges of effect size and allele frequency, I derive the minimal sample size necessary to detect at least one contributing variant. It turns out that, although the majority of contributing variants is not accessible with realistic sample sizes, a minimum of sample size may be given for moderately strong variants in the 1% frequency range.
Mitochondrial disorders are a group of rare diseases, caused by nuclear or mitochondrial DNA mutations. Their marked clinical and genetic heterogeneity as well as referral and ascertainment biases ...render phenotype-based prevalence estimations difficult. Here we calculated the lifetime risk of all known autosomal recessive mitochondrial disorders on basis of genetic data.
We queried the publicly available Genome Aggregation Database (gnomAD) and our in-house exome database to assess the allele frequency of disease-causing variants in genes associated with autosomal recessive mitochondrial disorders. Based on this, we estimated the lifetime risk of 249 autosomal recessive mitochondrial disorders. Three of these disorders and phenylketonuria (PKU) served as a proof of concept since calculations could be aligned with known birth prevalence data from newborn screening reports.
The estimated lifetime risks are very close to newborn screening data (where available), supporting the validity of the approach. For example, calculated lifetime risk of PKU (16·0/100,000) correlates well with known birth prevalence data (18·7/100,000). The combined estimated lifetime risk of 249 investigated mitochondrial disorders is 31·8 (20·9–50·6)/100,000 in our in-house database, 48·4 (40·3–58·5)/100,000 in the European gnomAD dataset, and 31·1 (26·7–36·3)/100,000 in the global gnomAD dataset. The disorders with the highest lifetime risk (> 3 per 100,000) were, in all datasets, those caused by mutations in the SPG7, ACADM, POLG and SLC22A5 genes.
We provide a population-genetic estimation on the lifetime risk of an entire class of monogenic disorders. Our findings reveal the substantial cumulative prevalence of autosomal recessive mitochondrial disorders, far above previous estimates. These data will be very important for assigning diagnostic a priori probabilities, and for resource allocation in therapy development, public health management and biomedical research.
German Federal Ministry of Education and Research.
Objective
Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have been identified, but the causatives ...genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes.
Methods
We analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low‐frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth.
Results
Highly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni‐corrected significance by the other to show a differential burden of low‐frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine‐mapping potentially causative domains within these genes.
Interpretation
Differential burden with intragenic low‐frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184–193
Niemann-Pick type C (NPC) disease is a rare autosomal-recessively inherited lysosomal storage disorder caused by mutations in NPC1 (95%) or NPC2. Given the highly variable phenotype, diagnosis is ...challenging and particularly late-onset forms with predominantly neuropsychiatric presentations are likely underdiagnosed. Pathophysiologically, genetic alterations compromising the endosomal/lysosomal system are linked with age-related neurodegenerative disorders. We sought to examine a possible association of rare sequence variants in NPC1 and NPC2 with Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD) and progressive supranuclear palsy (PSP), and to genetically determine the proportion of potentially misdiagnosed NPC patients in these neurodegenerative conditions. By means of high-resolution melting, we screened the coding regions of NPC1 and NPC2 for rare genetic variation in a homogenous German sample of patients clinically diagnosed with PD (n = 563), FTLD (n = 133) and PSP (n = 94), and 846 population-based controls. The frequencies of rare sequence variants in NPC1/2 did not differ significantly between patients and controls. Disease-associated NPC1/2 mutations were found in six PD patients (1.1%) and seven control subjects (0.8%), but not in FTLD or PSP. All rare variation was detected in the heterozygous state and no compound heterozygotes were observed. Our data do not support the hypothesis that rare NPC1/2 variants confer susceptibility for PD, FTLD, or PSP in the German population. Misdiagnosed NPC patients were not present in our samples. However, further assessment of NPC disease genes in age-related neurodegeneration is warranted.
Current clinical next-generation sequencing is done by using gene panels and exome analysis, both of which involve selective capturing of target regions. However, capturing has limitations in ...sufficiently covering coding exons, especially GC-rich regions. We compared whole exome sequencing (WES) with the most recent PCR-free whole genome sequencing (WGS), showing that only the latter is able to provide hitherto unprecedented complete coverage of the coding region of the genome. Thus, from a clinical/technical point of view, WGS is the better WES so that capturing is no longer necessary for the most comprehensive genomic testing of Mendelian disorders.
Rare variants cause Mendelian family aggregation in subsets of common diseases, and common variants may contribute to rare diseases. In this issue of Neuron, Gormley et al. (2018) report that the ...common variant burden in familial migraine is larger than in migraine of the general population.
Rare variants cause Mendelian family aggregation in subsets of common diseases, and common variants may contribute to rare diseases. In this issue of Neuron, Gormley et al. (2018) report that the common variant burden in familial migraine is larger than in migraine of the general population.
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