Publicly Available Data Provide Evidence against NR1H3 R415Q Causing Multiple Sclerosis

Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts

Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.

Whole Exome Sequencing in Multi-Incident Families Identifies Novel Candidate Genes for Multiple Sclerosis

Multiple sclerosis (MS) is a degenerative disease of the central nervous system in which auto-immunity-induced demyelination occurs. MS is thought to be caused by a complex interplay of environmental and genetic risk factors. While most genetic studies have focused on identifying common genetic variants for MS through genome-wide association studies, the objective of the present study was to identify rare genetic variants contributing to MS susceptibility. We used whole exome sequencing (WES) followed by co-segregation analyses in nine multi-incident families with two to four affected individuals. WES was performed in 31 family members with and without MS. After applying a suite of selection criteria, co-segregation analyses for a number of rare variants selected from the WES results were performed, adding 24 family members. This approach resulted in 12 exonic rare variants that showed acceptable co-segregation with MS within the nine families, implicating the genes MBP, PLK1, MECP2, MTMR7, TOX3, CPT1A, SORCS1, TRIM66, ITPR3, TTC28, CACNA1F, and PRAM1. Of these, three genes (MBP, MECP2, and CPT1A) have been previously reported as carrying MS-related rare variants. Six additional genes (MTMR7, TOX3, SORCS1, ITPR3, TTC28, and PRAM1) have also been implicated in MS through common genetic variants. The proteins encoded by all twelve genes containing rare variants interact in a molecular framework that points to biological processes involved in (de-/re-)myelination and auto-immunity. Our approach provides clues to possible molecular mechanisms underlying MS that should be studied further in cellular and/or animal models.

Expanding ACMG variant classification guidelines into a general framework

BACKGROUND

The American College of Medical Genetics and Genomics (ACMG)-recommended five variant classification categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign) have been widely used in medical genetics. However, these guidelines are fundamentally constrained in practice owing to their focus upon Mendelian disease genes and their dichotomous classification of variants as being either causal or not. Herein, we attempt to expand the ACMG guidelines into a general variant classification framework that takes into account not only the continuum of clinical phenotypes, but also the continuum of the variants' genetic effects, and the different pathological roles of the implicated genes.

MAIN BODY

As a disease model, we employed chronic pancreatitis (CP), which manifests clinically as a spectrum from monogenic to multifactorial. Bearing in mind that any general conceptual proposal should be based upon sound data, we focused our analysis on the four most extensively studied CP genes, PRSS1, CFTR, SPINK1 and CTRC. Based upon several cross-gene and cross-variant comparisons, we first assigned the different genes to two distinct categories in terms of disease causation: CP-causing (PRSS1 and SPINK1) and CP-predisposing (CFTR and CTRC). We then employed two new classificatory categories, "predisposing" and "likely predisposing", to replace ACMG's "pathogenic" and "likely pathogenic" categories in the context of CP-predisposing genes, thereby classifying all pathologically relevant variants in these genes as "predisposing". In the case of CP-causing genes, the two new classificatory categories served to extend the five ACMG categories whilst two thresholds (allele frequency and functional) were introduced to discriminate "pathogenic" from "predisposing" variants.

CONCLUSION

Employing CP as a disease model, we expand ACMG guidelines into a five-category classification system (predisposing, likely predisposing, uncertain significance, likely benign, and benign) and a seven-category classification system (pathogenic, likely pathogenic, predisposing, likely predisposing, uncertain significance, likely benign, and benign) in the context of disease-predisposing and disease-causing genes, respectively. Taken together, the two systems constitute a general variant classification framework that, in principle, should span the entire spectrum of variants in any disease-related gene. The maximal compliance of our five-category and seven-category classification systems with the ACMG guidelines ought to facilitate their practical application.

Regulation of Brain Cholesterol: What Role Do Liver X Receptors Play in Neurodegenerative Diseases?

Liver X Receptors (LXR) alpha and beta are two members of nuclear receptor superfamily documented as endogenous cholesterol sensors. Following conversion of cholesterol in oxysterol, both LXR isoforms detect intracellular concentrations and act as transcription factors to promote expression of target genes. Among their numerous physiological roles, they act as central cholesterol-lowering factors. In the central nervous system (CNS), cholesterol has been shown to be an essential determinant of brain function, particularly as a major constituent of myelin and membranes. In the brain, LXRs act as cholesterol central regulators, and, beyond this metabolic function, LXRs have additional roles such as providing neuroprotective effects and lowering neuroinflammation. In many neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), and multiple sclerosis (MS), dysregulations of cholesterol and oxysterol have been reported. In this paper, we propose to focus on recent advances in the knowledge of the LXRs roles on brain cholesterol and oxysterol homeostasis, neuroinflammation, neuroprotection, and their putative involvement in neurodegenerative disorders. We will discuss their potential use as candidates for both molecular diagnosis and as promising pharmacological targets in the treatment of ALS, AD, or MS patients.

C6orf10 Low-Frequency and Rare Variants in Italian Multiple Sclerosis Patients

In light of the complex nature of multiple sclerosis (MS) and the recently estimated contribution of low-frequency variants into disease, decoding its genetic risk components requires novel variant prioritization strategies. We selected, by reviewing MS Genome Wide Association Studies (GWAS), 107 candidate loci marked by intragenic single nucleotide polymorphisms (SNPs) with a remarkable association (p-value ≤ 5 × 10^-6). A whole exome sequencing (WES)-based pilot study of SNPs with minor allele frequency (MAF) ≤ 0.04, conducted in three Italian families, revealed 15 exonic low-frequency SNPs with affected parent-child transmission. These variants were detected in 65/120 Italian unrelated MS patients, also in combination (22 patients). Compared with databases (controls gnomAD, dbSNP150, ExAC, Tuscany-1000 Genome), the allelic frequencies of C6orf10 rs16870005 and IL2RA rs12722600 were significantly higher (i.e., controls gnomAD, p = 9.89 × 10^-7 and p < 1 × 10^-20). TET2 rs61744960 and TRAF3 rs138943371 frequencies were also significantly higher, except in Tuscany-1000 Genome. Interestingly, the association of C6orf10 rs16870005 (Ala431Thr) with MS did not depend on its linkage disequilibrium with the HLA-DRB1 locus. Sequencing in the MS cohort of the C6orf10 3′ region revealed 14 rare mutations (10 not previously reported). Four variants were null, and significantly more frequent than in the databases. Further, the C6orf10 rare variants were observed in combinations, both intra-locus and with other low-frequency SNPs. The C6orf10 Ser389Xfr was found homozygous in a patient with early onset of the MS. Taking into account the potentially functional impact of the identified exonic variants, their expression in combination at the protein level could provide functional insights in the heterogeneous pathogenetic mechanisms contributing to MS.

Complement C7 is a novel risk gene for Alzheimer's disease in Han Chinese

Alzheimer's disease is the most common neurodegenerative disease, and has a high level of genetic heritability and population heterogeneity. In this study, we performed the whole-exome sequencing of Han Chinese patients with familial and/or early-onset Alzheimer's disease, followed by independent validation, imaging analysis and function characterization. We identified an exome-wide significant rare missense variant rs3792646 (p.K420Q) in the C7 gene in the discovery stage (P = 1.09 × 10⁻⁶, odds ratio = 7.853) and confirmed the association in different cohorts and a combined sample (1615 cases and 2832 controls, P_combined = 2.99 × 10⁻⁷, odds ratio = 1.930). The risk allele was associated with decreased hippocampal volume and poorer working memory performance in early adulthood, thus resulting in an earlier age of disease onset. Overexpression of the mutant p.K420Q disturbed cell viability, immune activation and β-amyloid processing. Electrophysiological analyses showed that the mutant p.K420Q impairs the inhibitory effect of wild type C7 on the excitatory synaptic transmission in pyramidal neurons. These findings suggested that C7 is a novel risk gene for Alzheimer's disease in Han Chinese.

Genetics of Multiple Sclerosis: An Overview and New Directions

The contribution of genetic inheritance in multiple sclerosis was established early on. Although multiple sclerosis is not a Mendelian disease, its incidence and prevalence is higher in family members of affected individuals compared with the general population. Throughout the last decade, several small studies failed to identify any robust genetic associations besides the classic associations in the major histocompatibility complex region. During the past few years, genome-wide association studies (GWAS) have revolutionized the genetics of multiple sclerosis, uncovering more than 200 implicated genetic loci. Here, we describe these main findings and discuss the new avenues that these discoveries lay open.

Linkage analysis and whole exome sequencing identify a novel candidate gene in a Dutch multiple sclerosis family

BACKGROUND

Multiple sclerosis (MS) is a complex disease resulting from the joint effect of many genes. It has been speculated that rare variants might explain part of the missing heritability of MS.

OBJECTIVE

To identify rare coding genetic variants by analyzing a large MS pedigree with 11 affected individuals in several generations.

METHODS

Genome-wide linkage screen and whole exome sequencing (WES) were performed to identify novel coding variants in the shared region(s) and in the known 110 MS risk loci. The candidate variants were then assessed in 591 MS patients and 3169 controls.

RESULTS

Suggestive evidence for linkage was obtained to 7q11.22-q11.23. In WES data, a rare missense variant p.R183C in FKBP6 was identified that segregated with the disease in this family. The minor allele frequency was higher in an independent cohort of MS patients than in healthy controls (1.27% vs 0.95%), but not significant (odds ratio (OR) = 1.33 (95% confidence interval (CI): 0.8-2.4), p = 0.31).

CONCLUSION

The rare missense variant in FKBP6 was identified in a large Dutch MS family segregating with the disease. This association to MS was not found in an independent MS cohort. Overall, genome-wide studies in larger cohorts are needed to adequately investigate the role of rare variants in MS risk.

Genetic variants regulate NR1H3 expression and contribute to multiple sclerosis risk

A recent study analyzed 2053 multiple sclerosis (MS) cases and 799 healthy controls to investigate whether five genetic variants (rs11039149, rs12221497, rs2279238, rs7120118 and rs7114704) in NR1H3 are associated with MS risk. However this study reported negative results. It is very important that the appropriate samples and approach should be used in replication studies, which may provide the correct interpretation of the results. Here, we evaluated the above findings using large-scale MS genome-wide association studies with a total of 27,148 samples including 9772 MS cases and 17,376 controls, and multiple expression quantitative trait loci datasets. The results suggest that rs7120118 and rs2279238 variants are significantly associated with MS risk, and could significantly regulate NR1H3 expression in kinds of human tissues and cells. In summary, these findings provide important supplementary information about the association between NR1H3 variants and MS risk.

Highly Efficient, Rapid and Co-CRISPR-Independent Genome Editing in Caenorhabditis elegans

We describe a rapid and highly efficient method to generate point mutations in Caenorhabditis elegans using direct injection of CRISPR-Cas9 ribonucleoproteins. This versatile method does not require sensitized genetic backgrounds or co-CRISPR selection-based methods, and represents a single strategy that can be used for creating genomic point mutations, regardless of location. As proof of principle, we show that knock-in mutants more faithfully report variant-associated phenotypes as compared to transgenic overexpression. Data for nine knock-in mutants across five genes are presented that demonstrate high editing efficiencies (60%), a reduced screening workload (24 F1 progeny), and a rapid timescale (4–5 d). This optimized method simplifies genome engineering and is readily adaptable to other model systems.

NR1H3 p.Arg415Gln Is Not Associated to Multiple Sclerosis Risk

A recent study by Wang et al. (2016a) claims that the low-frequency variant NR1H3 p.Arg415Gln is sufficient to cause multiple sclerosis in certain individuals and determines a patient's likelihood of primary progressive disease. We sought to replicate this finding in the International MS Genetics Consortium (IMSGC) patient collection, which is 13-fold larger than the collection of Wang et al. (2016a), but we find no evidence that this variant is associated with either MS or disease subtype. Wang et al. (2016a) also report a common variant association in the region, which we show captures the association the IMSGC reported in 2013. Therefore, we conclude that the reported low-frequency association is a false positive, likely generated by insufficient sample size. The claim of NR1H3 mutations describing a Mendelian form of MS-of which no examples exist-can therefore not be substantiated by data. This Matters Arising paper is in response to Wang et al. (2016a), published in Neuron. See also the related Matters Arising paper by Minikel and MacArthur (2016) and the response by Wang et al. (2016b), published in this issue.

Case-Control Studies Are Not Familial Studies

Identifying rare genetic variants that drive the onset of disease is challenging, even before considering the additional genetic and environmental influences that likely exist in complex diseases. We recently published a study proposing a rare variant in the NR1H3 gene (p.R415Q, rs61731956) as responsible for the onset of multiple sclerosis (MS) in two multi-incident families (Wang et al., 2016). This publication has generated much discussion, and fortunately the possibility to validate a finding or prove it spurious can occur rapidly in genetic studies. All novel discoveries must be replicated, and best efforts should be made to ensure that these replications use the appropriate samples and approach, and provide the correct interpretation of the results. This Matters Arising Response paper addresses the Minikel and MacArthur (2016) and The International Multiple Sclerosis Genetics Consortium (2016) Matters Arising papers, published concurrently in Neuron.

Settling the score: variant prioritization and Mendelian disease

When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype-phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Using high-resolution variant frequencies to empower clinical genome interpretation

PurposeWhole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.MethodsWe present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.ResultsUsing the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).ConclusionWe outline a statistically robust framework for assessing whether a variant is "too common" to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.

Using high-resolution variant frequencies to empower clinical genome interpretation

Purpose

Whole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.

Methods

We present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.

Results

Using the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).

Conclusion

We outline a statistically robust framework for assessing whether a variant is “too common” to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.